101
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Zhao Y, Yang Z, Zhang Z, Yin M, Chu S, Tong Z, Qin Y, Zha L, Fang Q, Yuan Y, Huang L, Peng H. The first chromosome-level Fallopia multiflora genome assembly provides insights into stilbene biosynthesis. HORTICULTURE RESEARCH 2023; 10:uhad047. [PMID: 37213683 PMCID: PMC10194901 DOI: 10.1093/hr/uhad047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 03/07/2023] [Indexed: 05/23/2023]
Abstract
Fallopia multiflora (Thunb.) Harald, a vine belonging to the Polygonaceae family, is used in traditional medicine. The stilbenes contained in it have significant pharmacological activities in anti-oxidation and anti-aging. This study describes the assembly of the F. multiflora genome and presents its chromosome-level genome sequence containing 1.46 gigabases of data (with a contig N50 of 1.97 megabases), 1.44 gigabases of which was assigned to 11 pseudochromosomes. Comparative genomics confirmed that F. multiflora shared a whole-genome duplication event with Tartary buckwheat and then underwent different transposon evolution after separation. Combining genomics, transcriptomics, and metabolomics data to map a network of associated genes and metabolites, we identified two FmRS genes responsible for the catalysis of one molecule of p-coumaroyl-CoA and three molecules of malonyl-CoA to resveratrol in F. multiflora. These findings not only serve as the basis for revealing the stilbene biosynthetic pathway but will also contribute to the development of tools for increasing the production of bioactive stilbenes through molecular breeding in plants or metabolic engineering in microbes. Moreover, the reference genome of F. multiflora is a useful addition to the genomes of the Polygonaceae family.
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Affiliation(s)
| | | | | | | | - Shanshan Chu
- School of Pharmacy, Anhui University of Chinese Medicine, Hefei 230012, China
- Anhui Province Key Laboratory of Research & Development of Chinese Medicine, Hefei 230012, China
| | - Zhenzhen Tong
- School of Pharmacy, Anhui University of Chinese Medicine, Hefei 230012, China
| | - Yuejian Qin
- School of Pharmacy, Anhui University of Chinese Medicine, Hefei 230012, China
| | - Liangping Zha
- School of Pharmacy, Anhui University of Chinese Medicine, Hefei 230012, China
- Anhui Province Key Laboratory of Research & Development of Chinese Medicine, Hefei 230012, China
| | - Qingying Fang
- School of Pharmacy, Anhui University of Chinese Medicine, Hefei 230012, China
- Anhui Province Key Laboratory of Research & Development of Chinese Medicine, Hefei 230012, China
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102
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Olson ND, Wagner J, Dwarshuis N, Miga KH, Sedlazeck FJ, Salit M, Zook JM. Variant calling and benchmarking in an era of complete human genome sequences. Nat Rev Genet 2023:10.1038/s41576-023-00590-0. [PMID: 37059810 DOI: 10.1038/s41576-023-00590-0] [Citation(s) in RCA: 60] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/22/2023] [Indexed: 04/16/2023]
Abstract
Genetic variant calling from DNA sequencing has enabled understanding of germline variation in hundreds of thousands of humans. Sequencing technologies and variant-calling methods have advanced rapidly, routinely providing reliable variant calls in most of the human genome. We describe how advances in long reads, deep learning, de novo assembly and pangenomes have expanded access to variant calls in increasingly challenging, repetitive genomic regions, including medically relevant regions, and how new benchmark sets and benchmarking methods illuminate their strengths and limitations. Finally, we explore the possible future of more complete characterization of human genome variation in light of the recent completion of a telomere-to-telomere human genome reference assembly and human pangenomes, and we consider the innovations needed to benchmark their newly accessible repetitive regions and complex variants.
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Affiliation(s)
- Nathan D Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nathan Dwarshuis
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Karen H Miga
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Fritz J Sedlazeck
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, TX, USA
| | | | - Justin M Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA.
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103
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Song A, Su J, Wang H, Zhang Z, Zhang X, Van de Peer Y, Chen F, Fang W, Guan Z, Zhang F, Wang Z, Wang L, Ding B, Zhao S, Ding L, Liu Y, Zhou L, He J, Jia D, Zhang J, Chen C, Yu Z, Sun D, Jiang J, Chen S, Chen F. Analyses of a chromosome-scale genome assembly reveal the origin and evolution of cultivated chrysanthemum. Nat Commun 2023; 14:2021. [PMID: 37037808 PMCID: PMC10085997 DOI: 10.1038/s41467-023-37730-3] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Accepted: 03/29/2023] [Indexed: 04/12/2023] Open
Abstract
Chrysanthemum (Chrysanthemum morifolium Ramat.) is a globally important ornamental plant with great economic, cultural, and symbolic value. However, research on chrysanthemum is challenging due to its complex genetic background. Here, we report a near-complete assembly and annotation for C. morifolium comprising 27 pseudochromosomes (8.15 Gb; scaffold N50 of 303.69 Mb). Comparative and evolutionary analyses reveal a whole-genome triplication (WGT) event shared by Chrysanthemum species approximately 6 million years ago (Mya) and the possible lineage-specific polyploidization of C. morifolium approximately 3 Mya. Multilevel evidence suggests that C. morifolium is likely a segmental allopolyploid. Furthermore, a combination of genomics and transcriptomics approaches demonstrate the C. morifolium genome can be used to identify genes underlying key ornamental traits. Phylogenetic analysis of CmCCD4a traces the flower colour breeding history of cultivated chrysanthemum. Genomic resources generated from this study could help to accelerate chrysanthemum genetic improvement.
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Affiliation(s)
- Aiping Song
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Jiangshuo Su
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Haibin Wang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Zhongren Zhang
- Novogene Bioinformatics Institute, Beijing, 100083, China
| | - Xingtan Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, 518120, China
| | - Yves Van de Peer
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
- Department of Plant Biotechnology and Bioinformatics, Ghent University, VIB Center for Plant Systems Biology, 9052, Ghent, Belgium
- Center for Microbial Ecology and Genomics, Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Pretoria, 0028, South Africa
| | - Fei Chen
- College of tropical crops, Sanya Nanfan Research Institute, Hainan University & Hainan Yazhou Bay Seed Laboratory, Sanya, Hainan, 572025, China
| | - Weimin Fang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Zhiyong Guan
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Fei Zhang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Zhenxing Wang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Likai Wang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Baoqing Ding
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Shuang Zhao
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Lian Ding
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Ye Liu
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Lijie Zhou
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Jun He
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Diwen Jia
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Jiali Zhang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Chuwen Chen
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Zhongyu Yu
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Daojin Sun
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Jiafu Jiang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China.
| | - Sumei Chen
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China.
| | - Fadi Chen
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, Key Laboratory of Landscaping, Key Laboratory of Flower Biology and Germplasm Innovation (South), Ministry of Agriculture and Rural Affairs, Key Laboratory of Biology of Ornamental Plants in East China, National Forestry and Grassland Administration, College of Horticulture, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China.
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104
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Li Q, Zhao L, Zeng Y, Kuang Y, Guan Y, Chen B, Xu S, Tang B, Wu L, Mao X, Sun X, Shi J, Xu P, Diao F, Xue S, Bao S, Meng Q, Yuan P, Wang W, Ma N, Song D, Xu B, Dong J, Mu J, Zhang Z, Fan H, Gu H, Li Q, He L, Jin L, Wang L, Sang Q. Large-scale analysis of de novo mutations identifies risk genes for female infertility characterized by oocyte and early embryo defects. Genome Biol 2023; 24:68. [PMID: 37024973 PMCID: PMC10080761 DOI: 10.1186/s13059-023-02894-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 03/01/2023] [Indexed: 04/08/2023] Open
Abstract
BACKGROUND Oocyte maturation arrest and early embryonic arrest are important reproductive phenotypes resulting in female infertility and cause the recurrent failure of assisted reproductive technology (ART). However, the genetic etiologies of these female infertility-related phenotypes are poorly understood. Previous studies have mainly focused on inherited mutations based on large pedigrees or consanguineous patients. However, the role of de novo mutations (DNMs) in these phenotypes remains to be elucidated. RESULTS To decipher the role of DNMs in ART failure and female infertility with oocyte and embryo defects, we explore the landscape of DNMs in 473 infertile parent-child trios and identify a set of 481 confident DNMs distributed in 474 genes. Gene ontology analysis reveals that the identified genes with DNMs are enriched in signaling pathways associated with female reproductive processes such as meiosis, embryonic development, and reproductive structure development. We perform functional assays on the effects of DNMs in a representative gene Tubulin Alpha 4a (TUBA4A), which shows the most significant enrichment of DNMs in the infertile parent-child trios. DNMs in TUBA4A disrupt the normal assembly of the microtubule network in HeLa cells, and microinjection of DNM TUBA4A cRNAs causes abnormalities in mouse oocyte maturation or embryo development, suggesting the pathogenic role of these DNMs in TUBA4A. CONCLUSIONS Our findings suggest novel genetic insights that DNMs contribute to female infertility with oocyte and embryo defects. This study also provides potential genetic markers and facilitates the genetic diagnosis of recurrent ART failure and female infertility.
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Affiliation(s)
- Qun Li
- Institute of Pediatrics, Children's Hospital of Fudan University, the Shanghai Key Laboratory of Medical Epigenetics, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
| | - Lin Zhao
- Institute of Pediatrics, Children's Hospital of Fudan University, the Shanghai Key Laboratory of Medical Epigenetics, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
| | - Yang Zeng
- Institute of Pediatrics, Children's Hospital of Fudan University, the Shanghai Key Laboratory of Medical Epigenetics, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
| | - Yanping Kuang
- Reproductive Medicine Center, Shanghai Ninth Hospital, Shanghai Jiao Tong University, Shanghai, 200011, China
| | - Yichun Guan
- Department of Reproductive Medicine, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Biaobang Chen
- NHC Key Lab of Reproduction Regulation (Shanghai Institute for Biomedical and Pharmaceutical Technologies), Fudan University, Shanghai, 200032, China
| | - Shiru Xu
- Fertility Center, Shenzhen Zhongshan Urology Hospital, Shenzhen, 518001, Guangdong, China
| | - Bin Tang
- Reproductive Medicine Center, The First People's Hospital of Changde City, Changde, 415000, China
| | - Ling Wu
- Reproductive Medicine Center, Shanghai Ninth Hospital, Shanghai Jiao Tong University, Shanghai, 200011, China
| | - Xiaoyan Mao
- Reproductive Medicine Center, Shanghai Ninth Hospital, Shanghai Jiao Tong University, Shanghai, 200011, China
| | - Xiaoxi Sun
- Shanghai Ji Ai Genetics and IVF Institute, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, 200011, China
| | - Juanzi Shi
- Reproductive Medicine Center, Northwest Women's and Children's Hospital, Xi'an, 710000, China
| | - Peng Xu
- Hainan Jinghua Hejing Hospital for Reproductive Medicine, Haikou, 570125, China
| | - Feiyang Diao
- Reproductive Medicine Center, Jiangsu Province Hospital, Nanjing, 210036, China
| | - Songguo Xue
- Reproductive Medicine Center, School of Medicine, Shanghai East Hospital, Tongji University, Shanghai, China
| | - Shihua Bao
- Department of Reproductive Immunology, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, 201204, China
| | - Qingxia Meng
- Center for Reproduction and Genetics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, 215000, China
| | - Ping Yuan
- IVF Center, Department of Obstetrics and Gynecology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China
| | - Wenjun Wang
- IVF Center, Department of Obstetrics and Gynecology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China
| | - Ning Ma
- Reproductive Medical Center, Maternal and Child Health Care Hospital of Hainan Province, Haikou, 570206, Hainan Province, China
| | - Di Song
- Naval Medical University, Changhai Hospital, Shanghai, China
| | - Bei Xu
- Reproductive Medicine Centre, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Jie Dong
- Institute of Pediatrics, Children's Hospital of Fudan University, the Shanghai Key Laboratory of Medical Epigenetics, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
| | - Jian Mu
- Institute of Pediatrics, Children's Hospital of Fudan University, the Shanghai Key Laboratory of Medical Epigenetics, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
| | - Zhihua Zhang
- Institute of Pediatrics, Children's Hospital of Fudan University, the Shanghai Key Laboratory of Medical Epigenetics, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
| | - Huizhen Fan
- Institute of Pediatrics, Children's Hospital of Fudan University, the Shanghai Key Laboratory of Medical Epigenetics, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
| | - Hao Gu
- Institute of Pediatrics, Children's Hospital of Fudan University, the Shanghai Key Laboratory of Medical Epigenetics, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
| | - Qiaoli Li
- Institute of Pediatrics, Children's Hospital of Fudan University, the Shanghai Key Laboratory of Medical Epigenetics, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
| | - Lin He
- Bio-X Center, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, 200030, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, 200438, China
| | - Lei Wang
- Institute of Pediatrics, Children's Hospital of Fudan University, the Shanghai Key Laboratory of Medical Epigenetics, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China.
| | - Qing Sang
- Institute of Pediatrics, Children's Hospital of Fudan University, the Shanghai Key Laboratory of Medical Epigenetics, the Institutes of Biomedical Sciences, the State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China.
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105
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Lu Y, Rice E, Du K, Kneitz S, Naville M, Dechaud C, Volff JN, Boswell M, Boswell W, Hillier L, Tomlinson C, Milin K, Walter RB, Schartl M, Warren WC. High resolution genomes of multiple Xiphophorus species provide new insights into microevolution, hybrid incompatibility, and epistasis. Genome Res 2023; 33:557-571. [PMID: 37147111 PMCID: PMC10234306 DOI: 10.1101/gr.277434.122] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 03/29/2023] [Indexed: 05/07/2023]
Abstract
Because of diverged adaptative phenotypes, fish species of the genus Xiphophorus have contributed to a wide range of research for a century. Existing Xiphophorus genome assemblies are not at the chromosomal level and are prone to sequence gaps, thus hindering advancement of the intra- and inter-species differences for evolutionary, comparative, and translational biomedical studies. Herein, we assembled high-quality chromosome-level genome assemblies for three distantly related Xiphophorus species, namely, X. maculatus, X. couchianus, and X. hellerii Our overall goal is to precisely assess microevolutionary processes in the clade to ascertain molecular events that led to the divergence of the Xiphophorus species and to progress understanding of genetic incompatibility to disease. In particular, we measured intra- and inter-species divergence and assessed gene expression dysregulation in reciprocal interspecies hybrids among the three species. We found expanded gene families and positively selected genes associated with live bearing, a special mode of reproduction. We also found positively selected gene families are significantly enriched in nonpolymorphic transposable elements, suggesting the dispersal of these nonpolymorphic transposable elements has accompanied the evolution of the genes, possibly by incorporating new regulatory elements in support of the Britten-Davidson hypothesis. We characterized inter-specific polymorphisms, structural variants, and polymorphic transposable element insertions and assessed their association to interspecies hybridization-induced gene expression dysregulation related to specific disease states in humans.
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Affiliation(s)
- Yuan Lu
- The Xiphophorus Genetic Stock Center, Texas State University, San Marcos, Texas 78666, USA;
| | - Edward Rice
- Department of Animal Sciences, Department of Surgery, Institute for Data Science and Informatics, University of Missouri, Bond Life Sciences Center, Columbia, Missouri 65201, USA
| | - Kang Du
- The Xiphophorus Genetic Stock Center, Texas State University, San Marcos, Texas 78666, USA
| | - Susanne Kneitz
- Biochemistry and Cell Biology, Biozentrum, University of Würzburg, 97074 Würzburg, Germany
| | - Magali Naville
- Institut de Génomique Fonctionnelle de Lyon, Ecole Normale Supérieure de Lyon, CNRS UMR 5242, Université Claude Bernard Lyon 1, F-69364 Lyon, France
| | - Corentin Dechaud
- Institut de Génomique Fonctionnelle de Lyon, Ecole Normale Supérieure de Lyon, CNRS UMR 5242, Université Claude Bernard Lyon 1, F-69364 Lyon, France
| | - Jean-Nicolas Volff
- Institut de Génomique Fonctionnelle de Lyon, Ecole Normale Supérieure de Lyon, CNRS UMR 5242, Université Claude Bernard Lyon 1, F-69364 Lyon, France
| | - Mikki Boswell
- The Xiphophorus Genetic Stock Center, Texas State University, San Marcos, Texas 78666, USA
| | - William Boswell
- The Xiphophorus Genetic Stock Center, Texas State University, San Marcos, Texas 78666, USA
| | - LaDeana Hillier
- Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA
| | - Chad Tomlinson
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA
| | - Kremitzki Milin
- McDonnell Genome Institute, Washington University, St. Louis, Missouri 63108, USA
| | - Ronald B Walter
- Department of Life Sciences, Texas A&M University, Corpus Christi, Texas 78412, USA
| | - Manfred Schartl
- The Xiphophorus Genetic Stock Center, Texas State University, San Marcos, Texas 78666, USA
- Developmental Biochemistry, Biozentrum, University of Würzburg, 97074 Würzburg, Germany
| | - Wesley C Warren
- Department of Animal Sciences, Department of Surgery, Institute for Data Science and Informatics, University of Missouri, Bond Life Sciences Center, Columbia, Missouri 65201, USA
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106
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Zhao S, Mekbib KY, van der Ent MA, Allington G, Prendergast A, Chau JE, Smith H, Shohfi J, Ocken J, Duran D, Furey CG, Le HT, Duy PQ, Reeves BC, Zhang J, Nelson-Williams C, Chen D, Li B, Nottoli T, Bai S, Rolle M, Zeng X, Dong W, Fu PY, Wang YC, Mane S, Piwowarczyk P, Fehnel KP, See AP, Iskandar BJ, Aagaard-Kienitz B, Kundishora AJ, DeSpenza T, Greenberg ABW, Kidanemariam SM, Hale AT, Johnston JM, Jackson EM, Storm PB, Lang SS, Butler WE, Carter BS, Chapman P, Stapleton CJ, Patel AB, Rodesch G, Smajda S, Berenstein A, Barak T, Erson-Omay EZ, Zhao H, Moreno-De-Luca A, Proctor MR, Smith ER, Orbach DB, Alper SL, Nicoli S, Boggon TJ, Lifton RP, Gunel M, King PD, Jin SC, Kahle KT. Genetic dysregulation of an endothelial Ras signaling network in vein of Galen malformations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.18.532837. [PMID: 36993588 PMCID: PMC10055230 DOI: 10.1101/2023.03.18.532837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
To elucidate the pathogenesis of vein of Galen malformations (VOGMs), the most common and severe congenital brain arteriovenous malformation, we performed an integrated analysis of 310 VOGM proband-family exomes and 336,326 human cerebrovasculature single-cell transcriptomes. We found the Ras suppressor p120 RasGAP ( RASA1 ) harbored a genome-wide significant burden of loss-of-function de novo variants (p=4.79×10 -7 ). Rare, damaging transmitted variants were enriched in Ephrin receptor-B4 ( EPHB4 ) (p=1.22×10 -5 ), which cooperates with p120 RasGAP to limit Ras activation. Other probands had pathogenic variants in ACVRL1 , NOTCH1 , ITGB1 , and PTPN11 . ACVRL1 variants were also identified in a multi-generational VOGM pedigree. Integrative genomics defined developing endothelial cells as a key spatio-temporal locus of VOGM pathophysiology. Mice expressing a VOGM-specific EPHB4 kinase-domain missense variant exhibited constitutive endothelial Ras/ERK/MAPK activation and impaired hierarchical development of angiogenesis-regulated arterial-capillary-venous networks, but only when carrying a "second-hit" allele. These results illuminate human arterio-venous development and VOGM pathobiology and have clinical implications.
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107
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Kim H, Suyama M. Genome-wide identification of copy neutral loss of heterozygosity reveals its possible association with spatial positioning of chromosomes. Hum Mol Genet 2023; 32:1175-1183. [PMID: 36349694 PMCID: PMC10026252 DOI: 10.1093/hmg/ddac278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 10/17/2022] [Accepted: 11/02/2022] [Indexed: 11/10/2022] Open
Abstract
Loss of heterozygosity (LOH) is a genetic alteration that results from the loss of one allele at a heterozygous locus. In particular, copy neutral LOH (CN-LOH) events are generated, for example, by mitotic homologous recombination after monoallelic defection or gene conversion, resulting in novel homozygous locus having two copies of the normal counterpart allele. This phenomenon can serve as a source of genome diversity and is associated with various diseases. To clarify the nature of the CN-LOH such as the frequency, genomic distribution and inheritance pattern, we made use of whole-genome sequencing data of the three-generation CEPH/Utah family cohort, with the pedigree consisting of grandparents, parents and offspring. We identified an average of 40.7 CN-LOH events per individual taking advantage of 285 healthy individuals from 33 families in the cohort. On average 65% of them were classified as gonosomal-mosaicism-associated CN-LOH, which exists in both germline and somatic cells. We also confirmed that the incidence of the CN-LOH has little to do with the parents' age and sex. Furthermore, through the analysis of the genomic region including the CN-LOH, we found that the chance of the occurrence of the CN-LOH tends to increase at the GC-rich locus and/or on the chromosome having a relatively close inter-homolog distance. We expect that these results provide significant insights into the association between genetic alteration and spatial position of chromosomes as well as the intrinsic genetic property of the CN-LOH.
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Affiliation(s)
- Hyeonjeong Kim
- Division of Bioinformatics, Medical Institute of Bioregulation, Kyushu University, Fukuoka 812-8582, Japan
| | - Mikita Suyama
- Division of Bioinformatics, Medical Institute of Bioregulation, Kyushu University, Fukuoka 812-8582, Japan
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108
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Zhai Y, Bardel C, Vallée M, Iwaz J, Roy P. Performance comparisons between clustering models for reconstructing NGS results from technical replicates. Front Genet 2023; 14:1148147. [PMID: 37007945 PMCID: PMC10060969 DOI: 10.3389/fgene.2023.1148147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 03/06/2023] [Indexed: 03/18/2023] Open
Abstract
To improve the performance of individual DNA sequencing results, researchers often use replicates from the same individual and various statistical clustering models to reconstruct a high-performance callset. Here, three technical replicates of genome NA12878 were considered and five model types were compared (consensus, latent class, Gaussian mixture, Kamila–adapted k-means, and random forest) regarding four performance indicators: sensitivity, precision, accuracy, and F1-score. In comparison with no use of a combination model, i) the consensus model improved precision by 0.1%; ii) the latent class model brought 1% precision improvement (97%–98%) without compromising sensitivity (= 98.9%); iii) the Gaussian mixture model and random forest provided callsets with higher precisions (both >99%) but lower sensitivities; iv) Kamila increased precision (>99%) and kept a high sensitivity (98.8%); it showed the best overall performance. According to precision and F1-score indicators, the compared non-supervised clustering models that combine multiple callsets are able to improve sequencing performance vs. previously used supervised models. Among the models compared, the Gaussian mixture model and Kamila offered non-negligible precision and F1-score improvements. These models may be thus recommended for callset reconstruction (from either biological or technical replicates) for diagnostic or precision medicine purposes.
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Affiliation(s)
- Yue Zhai
- Université Lyon 1, Lyon, France
- Université de Lyon, Lyon, France
- Laboratoire de Biométrie et Biologie Évolutive, Villeurbanne, France
- *Correspondence: Yue Zhai,
| | - Claire Bardel
- Université Lyon 1, Lyon, France
- Université de Lyon, Lyon, France
- Laboratoire de Biométrie et Biologie Évolutive, Villeurbanne, France
- Service de Biostatistique-Bioinformatique, Hospices Civils de Lyon, Lyon, France
- Service de Génétique, Hospices Civils de Lyon, Bron, France
| | - Maxime Vallée
- Cellule Bioinformatique de La Plateforme de Séquençage Haut Débit NGS-HCL, Hospices Civils de Lyon, Bron, France
| | - Jean Iwaz
- Université Lyon 1, Lyon, France
- Université de Lyon, Lyon, France
- Laboratoire de Biométrie et Biologie Évolutive, Villeurbanne, France
- Service de Biostatistique-Bioinformatique, Hospices Civils de Lyon, Lyon, France
| | - Pascal Roy
- Université Lyon 1, Lyon, France
- Université de Lyon, Lyon, France
- Laboratoire de Biométrie et Biologie Évolutive, Villeurbanne, France
- Service de Biostatistique-Bioinformatique, Hospices Civils de Lyon, Lyon, France
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109
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Population Structure and Genetic Diversity Analysis of “Yufen 1” H Line Chickens Using Whole-Genome Resequencing. Life (Basel) 2023; 13:life13030793. [PMID: 36983948 PMCID: PMC10059704 DOI: 10.3390/life13030793] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/13/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023] Open
Abstract
The effective protection and utilization of poultry resources depend on an accurate understanding of the genetic diversity and population structure. The breeding of the specialized poultry lineage “Yufen 1”, with its defined characteristics, was approved by the China Poultry Genetic Resource Committee in 2015. Thus, to investigate the relationship between the progenitor H line and other poultry breeds, the genetic diversity and population structure of “Yufen 1” H line (YF) were investigated and compared with those of 2 commercial chicken breeds, the ancestor breed Red Jungle Fowls, and 11 Chinese indigenous chicken breeds based on a whole-genome resequencing approach using 8,112,424 SNPs. The genetic diversity of YF was low, and the rate of linkage disequilibrium decay was significantly slower than that of the other Chinese indigenous breeds. In addition, it was shown that the YF population was strongly selected during intensive breeding and that genetic resources have been seriously threatened, which highlights the need to establish a systematic conservation strategy as well as utilization techniques to maintain genetic diversity within YF. Moreover, a principal component analysis, a neighbor-joining tree analysis, a structure analysis, and genetic differentiation indices indicated that YF harbors a distinctive genetic resource with a unique genetic structure separate from that of Chinese indigenous breeds at the genome level. The findings provide a valuable resource and the theoretical basis for the further conservation and utilization of YF.
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110
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Revisiting mutagenesis at non-B DNA motifs in the human genome. Nat Struct Mol Biol 2023; 30:417-424. [PMID: 36914796 DOI: 10.1038/s41594-023-00936-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 02/03/2023] [Indexed: 03/16/2023]
Abstract
Non-B DNA structures formed by repetitive sequence motifs are known instigators of mutagenesis in experimental systems. Analyzing this phenomenon computationally in the human genome requires careful disentangling of intrinsic confounding factors, including overlapping and interrupted motifs and recurrent sequencing errors. Here, we show that accounting for these factors eliminates all signals of repeat-induced mutagenesis that extend beyond the motif boundary, and eliminates or dramatically shrinks the magnitude of mutagenesis within some motifs, contradicting previous reports. Mutagenesis not attributable to artifacts revealed several biological mechanisms. Polymerase slippage generates frequent indels within every variety of short tandem repeat motif, implicating slipped-strand structures. Interruption-correcting single nucleotide variants within short tandem repeats may originate from error-prone polymerases. Secondary-structure formation promotes single nucleotide variants within palindromic repeats and duplications within direct repeats. G-quadruplex motifs cause recurrent sequencing errors, whereas mutagenesis at Z-DNAs is conspicuously absent.
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111
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Sezmis AL, Woods LC, Peleg AY, McDonald MJ. Horizontal Gene Transfer, Fitness Costs and Mobility Shape the Spread of Antibiotic Resistance Genes into Experimental Populations of Acinetobacter Baylyi. Mol Biol Evol 2023; 40:msad028. [PMID: 36788632 PMCID: PMC9985319 DOI: 10.1093/molbev/msad028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 11/17/2022] [Accepted: 01/27/2023] [Indexed: 02/16/2023] Open
Abstract
Horizontal gene transfer (HGT) is important for microbial evolution, but how evolutionary forces shape the frequencies of horizontally transferred genetic variants in the absence of strong selection remains an open question. In this study, we evolve laboratory populations of Acinetobacter baylyi (ADP1) with HGT from two clinically relevant strains of multidrug-resistant Acinetobacter baumannii (AB5075 and A9844). We find that DNA can cross the species barrier, even without strong selection, and despite substantial DNA sequence divergence between the two species. Our results confirm previous findings that HGT can drive the spread of antibiotic resistance genes (ARGs) without selection for that antibiotic, but not for all of the resistance genes present in the donor genome. We quantify the costs and benefits of horizontally transferred variants and use whole population sequencing to track the spread of ARGs from HGT donors into antibiotic-sensitive recipients. We find that even though most ARGs are taken up by populations of A. baylyi, the long-term fate of an individual gene depends both on its fitness cost and on the type of genetic element that carries the gene. Interestingly, we also found that an integron, but not its host plasmid, is able to spread in A. baylyi populations despite its strong deleterious effect. Altogether, our results show how HGT provides an evolutionary advantage to evolving populations by facilitating the spread of non-selected genetic variation including costly ARGs.
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Affiliation(s)
- Aysha L Sezmis
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia
| | - Laura C Woods
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia
| | - Anton Y Peleg
- Department of Infectious Diseases, The Alfred Hospital and Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Infection Program, Monash Biomedicine Discovery Institute, Department of Microbiology, Monash University, Clayton, Victoria, Australia
- Centre to Impact AMR, Monash University, Clayton, Victoria, Australia
| | - Michael J McDonald
- School of Biological Sciences, Monash University, Clayton, Victoria, Australia
- Centre to Impact AMR, Monash University, Clayton, Victoria, Australia
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112
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Fan S, Spence JP, Feng Y, Hansen MEB, Terhorst J, Beltrame MH, Ranciaro A, Hirbo J, Beggs W, Thomas N, Nyambo T, Mpoloka SW, Mokone GG, Njamnshi A, Folkunang C, Meskel DW, Belay G, Song YS, Tishkoff SA. Whole-genome sequencing reveals a complex African population demographic history and signatures of local adaptation. Cell 2023; 186:923-939.e14. [PMID: 36868214 PMCID: PMC10568978 DOI: 10.1016/j.cell.2023.01.042] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 10/16/2022] [Accepted: 01/30/2023] [Indexed: 03/05/2023]
Abstract
We conduct high coverage (>30×) whole-genome sequencing of 180 individuals from 12 indigenous African populations. We identify millions of unreported variants, many predicted to be functionally important. We observe that the ancestors of southern African San and central African rainforest hunter-gatherers (RHG) diverged from other populations >200 kya and maintained a large effective population size. We observe evidence for ancient population structure in Africa and for multiple introgression events from "ghost" populations with highly diverged genetic lineages. Although currently geographically isolated, we observe evidence for gene flow between eastern and southern Khoesan-speaking hunter-gatherer populations lasting until ∼12 kya. We identify signatures of local adaptation for traits related to skin color, immune response, height, and metabolic processes. We identify a positively selected variant in the lightly pigmented San that influences pigmentation in vitro by regulating the enhancer activity and gene expression of PDPK1.
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Affiliation(s)
- Shaohua Fan
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, School of Life Science, Fudan University, Shanghai, 200438, China; Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jeffrey P Spence
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA 94305, USA
| | - Yuanqing Feng
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew E B Hansen
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jonathan Terhorst
- Department of Statistics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Marcia H Beltrame
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alessia Ranciaro
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jibril Hirbo
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - William Beggs
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Neil Thomas
- Computer Science Division, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Thomas Nyambo
- Department of Biochemistry, Kampala International University in Tanzania, P.O. Box 9790, Dar es Salaam, Tanzania
| | - Sununguko Wata Mpoloka
- Department of Biological Sciences, Faculty of Science, University of Botswana Gaborone, Private Bag UB 0022, Gaborone, Botswana
| | - Gaonyadiwe George Mokone
- Department of Biomedical Sciences, Faculty of Medicine, University of Botswana Gaborone, Private Bag UB 0022, Gaborone, Botswana
| | - Alfred Njamnshi
- Department of Neurology, Central Hospital Yaoundé; Brain Research Africa Initiative (BRAIN), Neuroscience Lab, Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, P.O. Box 337, Yaoundé, Cameroon
| | - Charles Folkunang
- Department of Pharmacotoxicology and Pharmacokinetics, Faculty of Medicine and Biomedical Sciences, The University of Yaoundé I, P.O. Box 337, Yaoundé, Cameroon
| | - Dawit Wolde Meskel
- Department of Microbial Cellular and Molecular Biology, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia
| | - Gurja Belay
- Department of Microbial Cellular and Molecular Biology, Addis Ababa University, P.O. Box 1176, Addis Ababa, Ethiopia
| | - Yun S Song
- Computer Science Division, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Statistics, University of California, Berkeley, Berkeley, CA 94720, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Sarah A Tishkoff
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA.
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113
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Sekino M, Hashimoto K, Nakamichi R, Yamamoto M, Fujinami Y, Sasaki T. Introgressive hybridization in the west Pacific pen shells (genus Atrina): Restricted interspecies gene flow within the genome. Mol Ecol 2023; 32:2945-2963. [PMID: 36855846 DOI: 10.1111/mec.16908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 02/03/2023] [Accepted: 02/14/2023] [Indexed: 03/02/2023]
Abstract
A compelling interest in marine biology is to elucidate how species boundaries between sympatric free-spawning marine invertebrates such as bivalve molluscs are maintained in the face of potential hybridization. Hybrid zones provide the natural resources for us to study the underlying genetic mechanisms of reproductive isolation between hybridizing species. Against this backdrop, we examined the occurrence of introgressive hybridization (introgression) between two bivalves distributed in the western Pacific margin, Atrina japonica and Atrina lischkeana, based on single-nucleotide polymorphisms (SNPs) derived from restriction site-associated DNA sequencing. Using 1066 ancestry-informative SNP sites, we also investigated the extent of introgression within the genome to search for SNP sites with reduced interspecies gene flow. A series of our individual-level clustering analyses including the principal component analysis, Bayesian model-based clustering, and triangle plotting based on ancestry-heterozygosity relationships for an admixed population sample from the Seto Inland Sea (Japan) consistently suggested the presence of specimens with varying degrees of genomic admixture, thereby implying that the two species are not completely isolated. The Bayesian genomic cline analysis identified 10 SNP sites with reduced introgression, each of which was located within a genic region or an intergenic region physically close to a functional gene. No, or very few, heterozygotes were observed at these sites in the hybrid zone, suggesting that selection acts against heterozygotes. Accordingly, we raised the possibility that the SNP sites are within genomic regions that are incompatible between the two species. Our finding of restricted interspecies gene flow at certain genomic regions gives new insight into the maintenance of species boundaries in hybridizing broadcast-spawning molluscs.
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Affiliation(s)
- Masashi Sekino
- Fisheries Resources Institute, Japan Fisheries Research and Education Agency, Yokohama, Kanagawa, Japan
| | - Kazumasa Hashimoto
- Fisheries Technology Institute, Japan Fisheries Research and Education Agency, Nagasaki, Japan
| | - Reiichiro Nakamichi
- Fisheries Resources Institute, Japan Fisheries Research and Education Agency, Yokohama, Kanagawa, Japan
| | - Masayuki Yamamoto
- Fisheries Division, Kagawa Prefectural Government, Takamatsu, Kagawa, Japan
| | - Yuichiro Fujinami
- Goto Field Station, Fisheries Technology Institute, Japan Fisheries Research and Education Agency, Nagasaki, Japan
| | - Takenori Sasaki
- The University Museum, The University of Tokyo, Tokyo, Japan
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114
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Zhi Y, Wang D, Zhang K, Wang Y, Geng W, Chen B, Li H, Li Z, Tian Y, Kang X, Liu X. Genome-Wide Genetic Structure of Henan Indigenous Chicken Breeds. Animals (Basel) 2023; 13:753. [PMID: 36830540 PMCID: PMC9952073 DOI: 10.3390/ani13040753] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 02/14/2023] [Accepted: 02/16/2023] [Indexed: 02/22/2023] Open
Abstract
There are five indigenous chicken breeds in Henan Province, China. These breeds have their own unique phenotypic characteristics in terms of morphology, behavior, skin and feather color, and productive performance, but their genetic basis is not well understood. Therefore, we analyzed the genetic structure, genomic diversity, and migration history of Henan indigenous chicken populations and the selection signals and genes responsible for Henan gamecock unique phenotypes using whole genome resequencing. The results indicate that Henan native chickens clustered most closely with the chicken populations in neighboring provinces. Compared to other breeds, Henan gamecock's inbreeding and selection intensity were more stringent. TreeMix analysis revealed the gene flow from southern chicken breeds into the Zhengyang sanhuang chicken and from the Xichuan black-bone chicken into the Gushi chicken. Selective sweep analysis identified several genes and biological processes/pathways that were related to body size, head control, muscle development, reproduction, and aggression control. Additionally, we confirmed the association between genotypes of SNPs in the strong selective gene LCORL and body size and muscle development in the Gushi-Anka F2 resource population. These findings made it easier to understand the traits of the germplasm and the potential for using the Henan indigenous chicken.
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Affiliation(s)
- Yihao Zhi
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
| | - Dandan Wang
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
| | - Ke Zhang
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
| | - Yangyang Wang
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
| | - Wanzhuo Geng
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
| | - Botong Chen
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
| | - Hong Li
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou 450046, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou 450046, China
| | - Zhuanjian Li
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou 450046, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou 450046, China
| | - Yadong Tian
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou 450046, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou 450046, China
| | - Xiangtao Kang
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou 450046, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou 450046, China
| | - Xiaojun Liu
- College of Animal Science and Technologyw, Henan Agricultural University, Zhengzhou 450046, China
- Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou 450046, China
- International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou 450046, China
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115
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Pfeilsticker TR, Jones RC, Steane DA, Vaillancourt RE, Potts BM. Molecular insights into the dynamics of species invasion by hybridisation in Tasmanian eucalypts. Mol Ecol 2023; 32:2913-2929. [PMID: 36807951 DOI: 10.1111/mec.16892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 11/26/2022] [Accepted: 01/26/2023] [Indexed: 02/22/2023]
Abstract
In plants where seed dispersal is limited compared with pollen dispersal, hybridisation may enhance gene exchange and species dispersal. We provide genetic evidence of hybridisation contributing to the expansion of the rare Eucalyptus risdonii into the range of the widespread Eucalyptus amygdalina. These closely related tree species are morphologically distinct, and observations suggest that natural hybrids occur along their distribution boundaries and as isolated trees or in small patches within the range of E. amygdalina. Hybrid phenotypes occur outside the range of normal dispersal for E. risdonii seed, yet in some hybrid patches small individuals resembling E. risdonii occur and are hypothesised to be a result of backcrossing. Using 3362 genome-wide SNPs assessed from 97 individuals of E. risdonii and E. amygdalina and 171 hybrid trees, we show that (i) isolated hybrids match the genotypes expected of F1 /F2 hybrids, (ii) there is a continuum in the genetic composition among the isolated hybrid patches from patches dominated by F1 /F2 -like genotypes to those dominated by E. risdonii-backcross genotypes, and (iii) the E. risdonii-like phenotypes in the isolated hybrid patches are most-closely related to proximal larger hybrids. These results suggest that the E. risdonii phenotype has been resurrected in isolated hybrid patches established from pollen dispersal, providing the first steps in its invasion of suitable habitat by long-distance pollen dispersal and complete introgressive displacement of E. amygdalina. Such expansion accords with the population demographics, common garden performance data, and climate modelling which favours E. risdonii and highlights a role of interspecific hybridisation in climate change adaptation and species expansion.
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Affiliation(s)
- Thais R Pfeilsticker
- School of Natural Sciences and ARC Training Centre for Forest Value, University of Tasmania, Hobart, Tasmania, Australia
| | - Rebecca C Jones
- School of Natural Sciences and ARC Training Centre for Forest Value, University of Tasmania, Hobart, Tasmania, Australia
| | - Dorothy A Steane
- School of Natural Sciences and ARC Training Centre for Forest Value, University of Tasmania, Hobart, Tasmania, Australia
| | - René E Vaillancourt
- School of Natural Sciences and ARC Training Centre for Forest Value, University of Tasmania, Hobart, Tasmania, Australia
| | - Brad M Potts
- School of Natural Sciences and ARC Training Centre for Forest Value, University of Tasmania, Hobart, Tasmania, Australia
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116
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Di Marco F, Spitaleri A, Battaglia S, Batignani V, Cabibbe AM, Cirillo DM. Advantages of long- and short-reads sequencing for the hybrid investigation of the Mycobacterium tuberculosis genome. Front Microbiol 2023; 14:1104456. [PMID: 36819039 PMCID: PMC9932330 DOI: 10.3389/fmicb.2023.1104456] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 01/16/2023] [Indexed: 02/05/2023] Open
Abstract
Introduction In the fight to limit the global spread of antibiotic resistance, computational challenges associated with sequencing technology can impact the accuracy of downstream analysis, including drug resistance identification, transmission, and genome resolution. About 10% of Mycobacterium tuberculosis (MTB) genome is constituted by the PE/PPE family, a GC-rich repetitive genome region. Although sequencing using short read technology is widely used, it is well recognized its limit in the PE/PPE regions due to the unambiguously mapping process onto the reference genome. The aim of this study was to compare the performances of short-reads (SRS), long-reads (LRS) and hybrid-reads (HYBR) based analysis over different common investigative tasks: genome coverage estimation, variant calling and cluster analysis, drug resistance detection and de novo assembly. Methods For the study 13 model MTB clinical isolates were sequenced with both SRS and LRS. HYBR were produced correcting the long reads with the short reads. The fastq from the three approaches were then processed using a customized version of MTBseq for genome coverage estimation and variant calling and using two different assemblers for de novo assembly evaluation. Results Estimation of genome coverage performances showed lower 8X breadth coverage for SRS respect to LRS and HYBR: considering the PE/PPE genes, SRS showed low results for the PE_PGRS family, while obtained acceptable coverage in PE and PPE genes; LRS and HYBR reached optimal coverages in PE/PPE genes. For variant calling HYBR showed the highest resolution, detecting the highest percentage of uniquely identified mutations compared to LRS and SRS. All three approaches agreed on the identification of two major clusters, with HYBR identifying an higher number of SNPs between the two clusters. Comparing the quality of the assemblies, HYBR and LRS obtained better results than SRS. Discussion In conclusion, depending on the aim of the investigation, both SRS and LRS present complementary advantages and limitations implying that for a full resolution of MTB genomes, where all the mentioned analyses and both technologies are needed, the use of the HYBR approach represents a valid option and a well-rounded strategy.
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Affiliation(s)
- Federico Di Marco
- Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy,Fondazione Centro San Raffaele, Milan, Italy
| | - Andrea Spitaleri
- Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy,Università Vita Salute San Raffaele, Milan, Italy
| | - Simone Battaglia
- Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Virginia Batignani
- Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Daniela Maria Cirillo
- Emerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy,*Correspondence: Daniela Maria Cirillo,
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Martin CA, Sheppard EC, Illera JC, Suh A, Nadachowska-Brzyska K, Spurgin LG, Richardson DS. Runs of homozygosity reveal past bottlenecks and contemporary inbreeding across diverging populations of an island-colonizing bird. Mol Ecol 2023; 32:1972-1989. [PMID: 36704917 DOI: 10.1111/mec.16865] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 01/11/2023] [Accepted: 01/20/2023] [Indexed: 01/28/2023]
Abstract
Genomes retain evidence of the demographic history and evolutionary forces that have shaped populations and drive speciation. Across island systems, contemporary patterns of genetic diversity reflect population demography, including colonization events, bottlenecks, gene flow and genetic drift. Here, we investigate genome-wide diversity and the distribution of runs of homozygosity (ROH) using whole-genome resequencing of individuals (>22× coverage) from six populations across three archipelagos of Berthelot's pipit (Anthus berthelotii)-a passerine that has recently undergone island speciation. We show the most dramatic reduction in diversity occurs between the mainland sister species (the tawny pipit) and Berthelot's pipit and is lowest in the populations that have experienced sequential bottlenecks (i.e., the Madeiran and Selvagens populations). Pairwise sequential Markovian coalescent (PSMC) analyses estimated that Berthelot's pipit diverged from its sister species ~2 million years ago, with the Madeiran archipelago founded 50,000 years ago, and the Selvagens colonized 8000 years ago. We identify many long ROH (>1 Mb) in these most recently colonized populations. Population expansion within the last 100 years may have eroded long ROH in the Madeiran archipelago, resulting in a prevalence of short ROH (<1 Mb). However, the extensive long and short ROH detected in the Selvagens suggest strong recent inbreeding and bottleneck effects, with as much as 38% of the autosomes consisting of ROH >250 kb. These findings highlight the importance of demographic history, as well as selection and genetic drift, in shaping contemporary patterns of genomic diversity across diverging populations.
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Affiliation(s)
- Claudia A Martin
- School of Biological Sciences, University of East Anglia, Norfolk, UK.,Terrestrial Ecology Unit, Biology Department, Ghent University, Ghent, Belgium
| | | | - Juan Carlos Illera
- Biodiversity Research Institute (CSIC-Oviedo University-Principality of Asturias), University of Oviedo, Mieres, Asturias, Spain
| | - Alexander Suh
- School of Biological Sciences, University of East Anglia, Norfolk, UK.,Department of Organismal Biology - Systematic Biology, Evolutionary Biology Centre (EBC), Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | | | - Lewis G Spurgin
- School of Biological Sciences, University of East Anglia, Norfolk, UK
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Yin X, Yang D, Zhao Y, Yang X, Zhou Z, Sun X, Kong X, Li X, Wang G, Duan Y, Yang Y, Yang Y. Differences in pseudogene evolution contributed to the contrasting flavors of turnip and Chiifu, two Brassica rapa subspecies. PLANT COMMUNICATIONS 2023; 4:100427. [PMID: 36056558 PMCID: PMC9860189 DOI: 10.1016/j.xplc.2022.100427] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 07/30/2022] [Accepted: 08/29/2022] [Indexed: 06/15/2023]
Abstract
Pseudogenes are important resources for investigation of genome evolution and genomic diversity because they are nonfunctional but have regulatory effects that influence plant adaptation and diversification. However, few systematic comparative analyses of pseudogenes in closely related species have been conducted. Here, we present a turnip (Brassica rapa ssp. rapa) genome sequence and characterize pseudogenes among diploid Brassica species/subspecies. The results revealed that the number of pseudogenes was greatest in Brassica oleracea (CC genome), followed by B. rapa (AA genome) and then Brassica nigra (BB genome), implying that pseudogene differences emerged after species differentiation. In Brassica AA genomes, pseudogenes were distributed asymmetrically on chromosomes because of numerous chromosomal insertions/rearrangements, which contributed to the diversity among subspecies. Pseudogene differences among subspecies were reflected in the flavor-related glucosinolate (GSL) pathway. Specifically, turnip had the highest content of pungent substances, probably because of expansion of the methylthioalkylmalate synthase-encoding gene family in turnips; these genes were converted into pseudogenes in B. rapa ssp. pekinensis (Chiifu). RNA interference-based silencing of the gene encoding 2-oxoglutarate-dependent dioxygenase 2, which is also associated with flavor and anticancer substances in the GSL pathway, resulted in increased abundance of anticancer compounds and decreased pungency of turnip and Chiifu. These findings revealed that pseudogene differences between turnip and Chiifu influenced the evolution of flavor-associated GSL metabolism-related genes, ultimately resulting in the different flavors of turnip and Chiifu.
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Affiliation(s)
- Xin Yin
- Plant Germplasm and Genomics Center, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China; Institute of Tibetan Plateau Research at Kunming, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Danni Yang
- Plant Germplasm and Genomics Center, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China; Institute of Tibetan Plateau Research at Kunming, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Youjie Zhao
- College of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming, Yunnan, China
| | - Xingyu Yang
- Plant Germplasm and Genomics Center, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China; Institute of Tibetan Plateau Research at Kunming, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhili Zhou
- Plant Germplasm and Genomics Center, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China; Institute of Tibetan Plateau Research at Kunming, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Xudong Sun
- Plant Germplasm and Genomics Center, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China; Institute of Tibetan Plateau Research at Kunming, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Xiangxiang Kong
- Plant Germplasm and Genomics Center, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China; Institute of Tibetan Plateau Research at Kunming, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Xiong Li
- Plant Germplasm and Genomics Center, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China; Institute of Tibetan Plateau Research at Kunming, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Guangyan Wang
- Plant Germplasm and Genomics Center, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China; Institute of Tibetan Plateau Research at Kunming, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Yuanwen Duan
- Plant Germplasm and Genomics Center, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China; Institute of Tibetan Plateau Research at Kunming, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
| | - Yunqiang Yang
- Plant Germplasm and Genomics Center, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China; Institute of Tibetan Plateau Research at Kunming, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China.
| | - Yongping Yang
- Plant Germplasm and Genomics Center, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China; Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China; Institute of Tibetan Plateau Research at Kunming, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China.
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119
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Hari A, Zhou Q, Gonzaludo N, Harting J, Scott SA, Qin X, Scherer S, Sahinalp SC, Numanagić I. An efficient genotyper and star-allele caller for pharmacogenomics. Genome Res 2023; 33:61-70. [PMID: 36657977 PMCID: PMC9977157 DOI: 10.1101/gr.277075.122] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 12/12/2022] [Indexed: 01/20/2023]
Abstract
High-throughput sequencing provides sufficient means for determining genotypes of clinically important pharmacogenes that can be used to tailor medical decisions to individual patients. However, pharmacogene genotyping, also known as star-allele calling, is a challenging problem that requires accurate copy number calling, structural variation identification, variant calling, and phasing within each pharmacogene copy present in the sample. Here we introduce Aldy 4, a fast and efficient tool for genotyping pharmacogenes that uses combinatorial optimization for accurate star-allele calling across different sequencing technologies. Aldy 4 adds support for long reads and uses a novel phasing model and improved copy number and variant calling models. We compare Aldy 4 against the current state-of-the-art star-allele callers on a large and diverse set of samples and genes sequenced by various sequencing technologies, such as whole-genome and targeted Illumina sequencing, barcoded 10x Genomics, and Pacific Biosciences (PacBio) HiFi. We show that Aldy 4 is the most accurate star-allele caller with near-perfect accuracy in all evaluated contexts, and hope that Aldy remains an invaluable tool in the clinical toolbox even with the advent of long-read sequencing technologies.
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Affiliation(s)
- Ananth Hari
- Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742, USA;,Cancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Qinghui Zhou
- Department of Computer Science, University of Victoria, Victoria, British Columbia V8P 5C2, Canada
| | | | - John Harting
- Pacific Biosciences, Menlo Park, California 94025, USA
| | - Stuart A. Scott
- Department of Pathology, Stanford University, Palo Alto, California 94304, USA
| | - Xiang Qin
- Baylor College of Medicine Human Genome Sequencing Center, Houston, Texas 77030, USA
| | - Steve Scherer
- Baylor College of Medicine Human Genome Sequencing Center, Houston, Texas 77030, USA
| | - S. Cenk Sahinalp
- Cancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Ibrahim Numanagić
- Department of Computer Science, University of Victoria, Victoria, British Columbia V8P 5C2, Canada
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120
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Bai H, Zhang X, Bush WS. Pharmacogenomic and Statistical Analysis. Methods Mol Biol 2023; 2629:305-330. [PMID: 36929083 DOI: 10.1007/978-1-0716-2986-4_14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Genetic variants can alter response to drugs and other therapeutic interventions. The study of this phenomenon, called pharmacogenomics, is similar in many ways to other types of genetic studies but has distinct methodological and statistical considerations. Genetic variants involved in the processing of exogenous compounds exhibit great diversity and complexity, and the phenotypes studied in pharmacogenomics are also more complex than typical genetic studies. In this chapter, we review basic concepts in pharmacogenomic study designs, data generation techniques, statistical analysis approaches, and commonly used methods and briefly discuss the ultimate translation of findings to clinical care.
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Affiliation(s)
- Haimeng Bai
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
- Department of Nutrition, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Xueyi Zhang
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - William S Bush
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA.
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121
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Gu Y, Zhou Y, Ju S, Liu X, Zhang Z, Guo J, Gao J, Zang J, Sun H, Chen Q, Wang J, Xu J, Xu Y, Chen Y, Guo Y, Dai J, Ma H, Wang C, Jin G, Li C, Xia Y, Shen H, Yang Y, Guo X, Hu Z. Multi-omics profiling visualizes dynamics of cardiac development and functions. Cell Rep 2022; 41:111891. [PMID: 36577384 DOI: 10.1016/j.celrep.2022.111891] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 09/14/2022] [Accepted: 12/05/2022] [Indexed: 12/29/2022] Open
Abstract
Cardiogenesis is a tightly regulated dynamic process through a continuum of differentiation and proliferation events. Key factors and pathways governing this process remain incompletely understood. Here, we investigate mice hearts from embryonic day 10.5 to postnatal week 8 and dissect developmental changes in phosphoproteome-, proteome-, metabolome-, and transcriptome-encompassing cardiogenesis and cardiac maturation. We identify mitogen-activated protein kinases as core kinases involved in transcriptional regulation by mediating the phosphorylation of chromatin remodeling proteins during early cardiogenesis. We construct the reciprocal regulatory network of transcription factors (TFs) and identify a series of TFs controlling early cardiogenesis involved in cycling-dependent proliferation. After birth, we identify cardiac resident macrophages with high arachidonic acid metabolism activities likely involved in the clearance of injured apoptotic cardiomyocytes. Together, our comprehensive multi-omics data offer a panoramic view of cardiac development and maturation that provides a resource for further in-depth functional exploration.
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Affiliation(s)
- Yayun Gu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Yan Zhou
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Sihan Ju
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Xiaofei Liu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Zicheng Zhang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Jia Guo
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Jimiao Gao
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Jie Zang
- School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Hao Sun
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Qi Chen
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Jinghan Wang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Jiani Xu
- School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Yiqun Xu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Yingjia Chen
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Yueshuai Guo
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Juncheng Dai
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Hongxia Ma
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Cheng Wang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Guangfu Jin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Chaojun Li
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Yankai Xia
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Hongbing Shen
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Yang Yang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Xuejiang Guo
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China
| | - Zhibin Hu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, Jiangsu 211100, China; School of Public Health, Center for Global Health, Nanjing Medical University, Nanjing, Jiangsu 211100, China.
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Saad M, El-Menyar A, Kunji K, Ullah E, Al Suwaidi J, Kullo IJ. Validation of Polygenic Risk Scores for Coronary Heart Disease in a Middle Eastern Cohort Using Whole Genome Sequencing. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2022; 15:e003712. [PMID: 36252120 PMCID: PMC9770120 DOI: 10.1161/circgen.122.003712] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 08/04/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND Enthusiasm for using polygenic risk scores (PRSs) in clinical practice is tempered by concerns about their portability to diverse ancestry groups, thus motivating genome-wide association studies in non-European ancestry cohorts. METHODS We conducted a genome-wide association study for coronary heart disease in a Middle Eastern cohort using whole genome sequencing and assessed the performance of 6 PRSs developed with methods including LDpred (PGS000296), metaGRS (PGS000018), Pruning and Thresholding (PGS000337), and an EnsemblePRS we developed. Additionally, we evaluated the burden of rare variants in lipid genes in cases and controls. Whole genome sequencing at 30× coverage was performed in 1067 coronary heart disease cases (mean age=59 years; 70.3% males) and 6170 controls (mean age=40 years; 43.5% males). RESULTS The majority of PRSs performed well; odds ratio (OR) per 1 SD increase (OR1sd) was highest for PGS000337 (OR1sd=1.81, 95% CI [1.66-1.98], P=3.07×10-41). EnsemblePRS performed better than individual PRSs (OR1sd=1.8, 95% CI [1.66-1.96], P=5.89×10-44). The OR for the 10th decile versus the remaining deciles was >3.2 for PGS000337, PGS000296, PGS000018, and reached 4.58 for EnsemblePRS. Of 400 known genome-wide significant loci, 33 replicated at P<10-4. However, the 9p21 locus did not replicate. Six suggestive (P<10-5) new loci/genes with plausible biological function were identified (eg, CORO7, RBM47, PDE4D). The burden of rare functional variants in LDLR, APOB, PCSK9, and ANGPTL4 was greater in cases than controls. CONCLUSIONS Overall, we demonstrate that PRSs derived from European ancestry genome-wide association studies performed well in a Middle Eastern cohort, suggesting these could be used in the clinical setting while ancestry-specific PRSs are developed.
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Affiliation(s)
- Mohamad Saad
- Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar (M.S., K.K., E.U.)
| | | | - Khalid Kunji
- Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar (M.S., K.K., E.U.)
| | - Ehsan Ullah
- Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar (M.S., K.K., E.U.)
| | | | - Iftikhar J. Kullo
- Department of Cardiovascular Medicine, and the Gonda Vascular Center, Mayo Clinic, Rochester, MN (I.J.K.)
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Khera AV, Wang M, Chaffin M, Emdin CA, Samani NJ, Schunkert H, Watkins H, McPherson R, Elosua R, Boerwinkle E, Ardissino D, Butterworth AS, Di Angelantonio E, Naheed A, Danesh J, Chowdhury R, Krumholz HM, Sheu WHH, Rich SS, Rotter JI, Chen YDI, Gabriel S, Lander ES, Saleheen D, Kathiresan S. Gene Sequencing Identifies Perturbation in Nitric Oxide Signaling as a Nonlipid Molecular Subtype of Coronary Artery Disease. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2022; 15:e003598. [PMID: 36215124 PMCID: PMC9771961 DOI: 10.1161/circgen.121.003598] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Accepted: 06/24/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND A key goal of precision medicine is to disaggregate common, complex diseases into discrete molecular subtypes. Rare coding variants in the low-density lipoprotein receptor gene (LDLR) are identified in 1% to 2% of coronary artery disease (CAD) patients, defining a molecular subtype with risk driven by hypercholesterolemia. METHODS To search for additional subtypes, we compared the frequency of rare, predicted loss-of-function and damaging missense variants aggregated within a given gene in 41 081 CAD cases versus 217 115 controls. RESULTS Rare variants in LDLR were most strongly associated with CAD, present in 1% of cases and associated with 4.4-fold increased CAD risk. A second subtype was characterized by variants in endothelial nitric oxide synthase gene (NOS3), a key enzyme regulating vascular tone, endothelial function, and platelet aggregation. A rare predicted loss-of-function or damaging missense variants in NOS3 was present in 0.6% of cases and associated with 2.42-fold increased risk of CAD (95% CI, 1.80-3.26; P=5.50×10-9). These variants were associated with higher systolic blood pressure (+3.25 mm Hg; [95% CI, 1.86-4.65]; P=5.00×10-6) and increased risk of hypertension (adjusted odds ratio 1.31; [95% CI, 1.14-1.51]; P=2.00×10-4) but not circulating cholesterol concentrations, suggesting that, beyond lipid pathways, nitric oxide synthesis is a key nonlipid driver of CAD risk. CONCLUSIONS Beyond LDLR, we identified an additional nonlipid molecular subtype of CAD characterized by rare variants in the NOS3 gene.
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Affiliation(s)
- Amit V. Khera
- Program in Medical & Population Genetics, Broad Inst of MIT & Harvard, Cambridge, MA
- Ctr for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Dept of Medicine, Harvard Medical School, Boston, MA
- Cardiology Division, Dept of Medicine, Massachusetts General Hospital, Boston, MA
| | - Minxian Wang
- Ctr for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Program in Medical & Population Genetics, Broad Inst of MIT & Harvard, Cambridge, MA
- CAS Key Laboratory of Genome Sciences & Information, Beijing Inst of Genomics, Chinese Academy of Sciences & China National Ctr for Bioinformation, Beijing, China
| | - Mark Chaffin
- Program in Medical & Population Genetics, Broad Inst of MIT & Harvard, Cambridge, MA
| | - Connor A. Emdin
- Ctr for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Dept of Medicine, Harvard Medical School, Boston, MA
- Program in Medical & Population Genetics, Broad Inst of MIT & Harvard, Cambridge, MA
| | - Nilesh J. Samani
- Dept of Cardiovascular Sciences, Univ of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Ctr, Glenfield Hospital, Leicester, UK
| | - Heribert Schunkert
- Dept of Cardiology, German Heart Ctr Munich, Technical Univ of Munich, Munich, Germany
- DZHK (German Ctr for Cardiovascular Research), Partner site Munich, Munich Heart Alliance, Munich, Germany
| | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Dept of Medicine, Univ of Oxford, Headington, UK
- Wellcome Trust Ctr for Human Genetics, Univ of Oxford, Oxford, UK
| | - Ruth McPherson
- Inst for Cardiogenetics, Univ of Lübeck, Lübeck, Schleswig-Holstein, Germany
- German Research Ctr for Cardiovascular Research, Partner Site Hamburg/Lübeck/Kiel & Univ Heart Center Lübeck (J.E.), Berlin, Brandenburg, Germany
- Depts of Medicine & Biochemistry, Univ of Ottawa Heart Inst, Ottawa, ON, Canada
| | - Roberto Elosua
- Cardiovascular Epidemiology & Genetics, Hospital del Mar Research Inst, Barcelona, Spain
- CIBER Enfermedades Cardiovasculares, Barcelona, Spain
- Facultat de Medicina, Universitat de Vic-Central de Cataluña, Barcelona, Spain
| | - Eric Boerwinkle
- Ctr for Human Genetics & Dept. of Epidemiology, Univ of Texas Health Science Ctr School of Public Health, Houston, TX
| | - Diego Ardissino
- Cardiology, Azienda Ospedaliero-Universitaria di Parma, Univ of Parma, Parma, Italy
- Associazione per lo Studio Della Trombosi in Cardiologia, Pavia, Italy
| | - Adam S. Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Dept of Public Health & Primary Care, Univ of Cambridge, Cambridge, UK
- National Inst for Health Research Blood & Transplant Research Unit in Donor Health & Genomics, Univ of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus & Univ of Cambridge, Cambridge, UK
| | - Emanuele Di Angelantonio
- British Heart Foundation Cardiovascular Epidemiology Unit, Dept of Public Health & Primary Care, Univ of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus & Univ of Cambridge, Cambridge, UK
- NIHR Blood & Transplant Research Unit in Donor Health & Genomics, Univ of Cambridge, Cambridge, UK
- BHF Ctr of Research Excellence, School of Clinical Medicine, Addenbrooke’s Hospital, Univ of Cambridge, Cambridge, UK
- Health Data Science Research Ctr, Human Technopole, Milan, Italy
| | - Aliya Naheed
- Initiative for Noncommunicable Bangladesh, Diseases, Health Systems & Population Studies Division, International Ctr for Diarrhoeal Disease Research, Dhaka, Bangladesh
| | - John Danesh
- British Heart Foundation Cardiovascular Epidemiology Unit, Dept of Public Health & Primary Care, Univ of Cambridge, Cambridge, UK
- National Inst for Health Research Blood & Transplant Research Unit in Donor Health & Genomics, Univ of Cambridge, Cambridge, UK
- British Heart Foundation Ctr of Research Excellence, Univ of Cambridge, Cambridge, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus & Univ of Cambridge, Cambridge, UK
- Dept of Human Genetics, Wellcome Sanger Inst, Hinxton, UK
| | - Rajiv Chowdhury
- British Heart Foundation Cardiovascular Epidemiology Unit, Dept of Public Health & Primary Care, Univ of Cambridge, Cambridge, UK
- Centre for Non-Communicable Disease Research, Dhaka, Bangladesh
| | - Harlan M. Krumholz
- Section of Cardiovascular Medicine, Dept of Medicine, Yale Univ, New Haven, CT
- Ctr for Outcomes Research & Evaluation, Yale-New Haven Hospital, New Haven, CT
| | - Wayne H-H Sheu
- Cardiovascular Research Ctr, Dept of Medicine, National Yang Ming Univ School of Medicine, Taipei, Taiwan
| | - Stephen S. Rich
- Ctr for Public Health Genomics, Univ of Virginia, Charlottesville, VA
| | - Jerome I. Rotter
- The Inst for Translational Genomics & Population Sciences, Dept of Pediatrics, The Lundquist Inst for Biomedical Innovation at Harbor-UCLA Medical Ctr, Torrance, CA
| | - Yii-der Ida Chen
- The Inst for Translational Genomics & Population Sciences, Dept of Pediatrics, The Lundquist Inst for Biomedical Innovation at Harbor-UCLA Medical Ctr, Torrance, CA
| | - Stacey Gabriel
- Program in Medical & Population Genetics, Broad Inst of MIT & Harvard, Cambridge, MA
| | - Eric S. Lander
- Program in Medical & Population Genetics, Broad Inst of MIT & Harvard, Cambridge, MA
- Dept of Biology, MIT, Cambridge, MA
- Dept of Systems Biology, Harvard Medical School, Boston, MA
| | - Danish Saleheen
- Dept of Medicine, Columbia Univ, New York, NY
- Ctr for Non-Communicable Diseases, Karachi, Sindh, Pakistan
| | - Sekar Kathiresan
- Ctr for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Dept of Medicine, Harvard Medical School, Boston, MA
- Cardiology Division, Dept of Medicine, Massachusetts General Hospital, Boston, MA
- Verve Therapeutics, Cambridge, MA
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124
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Robinson KG, Marsh AG, Lee SK, Hicks J, Romero B, Batish M, Crowgey EL, Shrader MW, Akins RE. DNA Methylation Analysis Reveals Distinct Patterns in Satellite Cell-Derived Myogenic Progenitor Cells of Subjects with Spastic Cerebral Palsy. J Pers Med 2022; 12:jpm12121978. [PMID: 36556199 PMCID: PMC9780849 DOI: 10.3390/jpm12121978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 11/25/2022] [Indexed: 12/03/2022] Open
Abstract
Spastic type cerebral palsy (CP) is a complex neuromuscular disorder that involves altered skeletal muscle microanatomy and growth, but little is known about the mechanisms contributing to muscle pathophysiology and dysfunction. Traditional genomic approaches have provided limited insight regarding disease onset and severity, but recent epigenomic studies indicate that DNA methylation patterns can be altered in CP. Here, we examined whether a diagnosis of spastic CP is associated with intrinsic DNA methylation differences in myoblasts and myotubes derived from muscle resident stem cell populations (satellite cells; SCs). Twelve subjects were enrolled (6 CP; 6 control) with informed consent/assent. Skeletal muscle biopsies were obtained during orthopedic surgeries, and SCs were isolated and cultured to establish patient-specific myoblast cell lines capable of proliferation and differentiation in culture. DNA methylation analyses indicated significant differences at 525 individual CpG sites in proliferating SC-derived myoblasts (MB) and 1774 CpG sites in differentiating SC-derived myotubes (MT). Of these, 79 CpG sites were common in both culture types. The distribution of differentially methylated 1 Mbp chromosomal segments indicated distinct regional hypo- and hyper-methylation patterns, and significant enrichment of differentially methylated sites on chromosomes 12, 13, 14, 15, 18, and 20. Average methylation load across 2000 bp regions flanking transcriptional start sites was significantly different in 3 genes in MBs, and 10 genes in MTs. SC derived MBs isolated from study participants with spastic CP exhibited fundamental differences in DNA methylation compared to controls at multiple levels of organization that may reveal new targets for studies of mechanisms contributing to muscle dysregulation in spastic CP.
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Affiliation(s)
- Karyn G. Robinson
- Nemours Children’s Research, Nemours Children’s Health System, Wilmington, DE 19803, USA
| | - Adam G. Marsh
- Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE 19716, USA
| | - Stephanie K. Lee
- Nemours Children’s Research, Nemours Children’s Health System, Wilmington, DE 19803, USA
| | - Jonathan Hicks
- Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE 19716, USA
| | - Brigette Romero
- Medical and Molecular Sciences, University of Delaware, Newark, DE 19716, USA
| | - Mona Batish
- Medical and Molecular Sciences, University of Delaware, Newark, DE 19716, USA
| | - Erin L. Crowgey
- Nemours Children’s Research, Nemours Children’s Health System, Wilmington, DE 19803, USA
| | - M. Wade Shrader
- Department of Orthopedics, Nemours Children’s Hospital Delaware, Wilmington, DE 19803, USA
| | - Robert E. Akins
- Nemours Children’s Research, Nemours Children’s Health System, Wilmington, DE 19803, USA
- Correspondence: ; Tel.: +1-302-651-6779
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125
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Xie HB, Yan C, Adeola AC, Wang K, Huang CP, Xu MM, Qiu Q, Yin X, Fan CY, Ma YF, Yin TT, Gao Y, Deng JK, Okeyoyin AO, Oluwole OO, Omotosho O, Okoro VMO, Omitogun OG, Dawuda PM, Olaogun SC, Nneji LM, Ayoola AO, Sanke OJ, Luka PD, Okoth E, Lekolool I, Mijele D, Bishop RP, Han J, Wang W, Peng MS, Zhang YP. African Suid Genomes Provide Insights into the Local Adaptation to Diverse African Environments. Mol Biol Evol 2022; 39:6840307. [PMID: 36413509 PMCID: PMC9733430 DOI: 10.1093/molbev/msac256] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 10/21/2022] [Accepted: 11/17/2022] [Indexed: 11/23/2022] Open
Abstract
African wild suids consist of several endemic species that represent ancient members of the family Suidae and have colonized diverse habitats on the African continent. However, limited genomic resources for African wild suids hinder our understanding of their evolution and genetic diversity. In this study, we assembled high-quality genomes of a common warthog (Phacochoerus africanus), a red river hog (Potamochoerus porcus), as well as an East Asian Diannan small-ear pig (Sus scrofa). Phylogenetic analysis showed that common warthog and red river hog diverged from their common ancestor around the Miocene/Pliocene boundary, putatively predating their entry into Africa. We detected species-specific selective signals associated with sensory perception and interferon signaling pathways in common warthog and red river hog, respectively, which contributed to their local adaptation to savannah and tropical rainforest environments, respectively. The structural variation and evolving signals in genes involved in T-cell immunity, viral infection, and lymphoid development were identified in their ancestral lineage. Our results provide new insights into the evolutionary histories and divergent genetic adaptations of African suids.
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Affiliation(s)
| | | | | | | | | | - Ming-Min Xu
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China
| | - Qiang Qiu
- School of Ecology and Environment, Northwestern Polytechnical University, Xi’an 710129, China
| | - Xue Yin
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming 650091, China
| | - Chen-Yu Fan
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming 650091, China
| | - Yun-Fei Ma
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China
| | - Ting-Ting Yin
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Yun Gao
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Jia-Kun Deng
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Agboola O Okeyoyin
- National Park Service Headquarter, Federal Capital Territory, Abuja 900108, Nigeria
| | - Olufunke O Oluwole
- Institute of Agricultural Research and Training, Obafemi Awolowo University, Ibadan, Nigeria
| | - Oladipo Omotosho
- Department of Veterinary Medicine, University of Ibadan, Ibadan 200005, Nigeria
| | - Victor M O Okoro
- Department of Animal Science and Technology, School of Agriculture and Agricultural Technology, Federal University of Technology, Owerri 460114, Nigeria
| | - Ofelia G Omitogun
- Department of Animal Sciences, Obafemi Awolowo University, Ile-Ife 220282, Nigeria
| | - Philip M Dawuda
- Department of Veterinary Surgery and Theriogenology, College of Veterinary Medicine, University of Agriculture Makurdi, Makurdi 970001, Nigeria
| | - Sunday C Olaogun
- Department of Veterinary Medicine, University of Ibadan, Ibadan 200005, Nigeria
| | - Lotanna M Nneji
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China,Sino-Africa Joint Research Center, Chinese Academy of Sciences, Kunming 650204, China
| | - Adeola O Ayoola
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China,Sino-Africa Joint Research Center, Chinese Academy of Sciences, Kunming 650204, China
| | - Oscar J Sanke
- Taraba State Ministry of Agriculture and Natural Resources, Jalingo 660213, Nigeria
| | - Pam D Luka
- National Veterinary Research Institute, Vom 930103, Nigeria
| | - Edward Okoth
- International Livestock Research Institute (ILRI), Nairobi 00100, Kenya
| | | | | | - Richard P Bishop
- International Livestock Research Institute (ILRI), Nairobi 00100, Kenya
| | | | - Wen Wang
- Corresponding authors: E-mails: ; ; ;
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126
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Understanding Mendelian errors in SNP arrays data using a Gochu Asturcelta pig pedigree: genomic alterations, family size and calling errors. Sci Rep 2022; 12:19686. [PMID: 36385499 PMCID: PMC9668983 DOI: 10.1038/s41598-022-24340-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 11/14/2022] [Indexed: 11/17/2022] Open
Abstract
Up to 478 Gochu Asturcelta pig parents-offspring trios (61 different families) were genotyped using the Axiom_PigHDv1 Array to identify the causes of Mendelian errors (ME). Up to 545,364 SNPs were retained. Up to 40,540 SNPs gathering 292,297 allelic mismatches were identified and were overlapped with SINEs and LINEs (Sscrofa genome 11.1). Copy number variations (CNV) were called using PennCNV. ME were classified into eight different classes according to the trio member ("Trio" meaning no assignment) and the allele on which ME was identified: TrioA/B, FatherA/B, MotherA/B, OffspringA/B. Most ME occurred due to systematic causes: (a) those assigned to the Father, Mother or Offspring occurred by null or partial null alleles characterized by heterozygote deficiency, varied with family size, involved a low number of loci (6506), and gathered most mismatches (228,145); (b) TrioB errors varied with family size, covaried with SINEs, LINEs and CNV, and involved most ME loci (33,483) and mismatches (65,682); and (c) TrioA errors were non-systematic ME with no sampling bias involving 1.2% of mismatches only and a low number of loci (1939). The influence of TrioB errors on the overall genotyping quality may be low and, since CNV vary among populations, their removal should be considered in each particular dataset. ME assignable to the Father, Mother or Offspring may be consistent within technological platforms and may bias severely linkage or association studies. Most ME caused by null or partial null alleles can be removed using heterozygote deficiency without affecting the size of the datasets.
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127
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von Seth J, van der Valk T, Lord E, Sigeman H, Olsen RA, Knapp M, Kardailsky O, Robertson F, Hale M, Houston D, Kennedy E, Dalén L, Norén K, Massaro M, Robertson BC, Dussex N. Genomic trajectories of a near-extinction event in the Chatham Island black robin. BMC Genomics 2022; 23:747. [PMID: 36357860 PMCID: PMC9647977 DOI: 10.1186/s12864-022-08963-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 10/23/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Understanding the micro--evolutionary response of populations to demographic declines is a major goal in evolutionary and conservation biology. In small populations, genetic drift can lead to an accumulation of deleterious mutations, which will increase the risk of extinction. However, demographic recovery can still occur after extreme declines, suggesting that natural selection may purge deleterious mutations, even in extremely small populations. The Chatham Island black robin (Petroica traversi) is arguably the most inbred bird species in the world. It avoided imminent extinction in the early 1980s and after a remarkable recovery from a single pair, a second population was established and the two extant populations have evolved in complete isolation since then. Here, we analysed 52 modern and historical genomes to examine the genomic consequences of this extreme bottleneck and the subsequent translocation. RESULTS We found evidence for two-fold decline in heterozygosity and three- to four-fold increase in inbreeding in modern genomes. Moreover, there was partial support for temporal reduction in total load for detrimental variation. In contrast, compared to historical genomes, modern genomes showed a significantly higher realised load, reflecting the temporal increase in inbreeding. Furthermore, the translocation induced only small changes in the frequency of deleterious alleles, with the majority of detrimental variation being shared between the two populations. CONCLUSION Our results highlight the dynamics of mutational load in a species that recovered from the brink of extinction, and show rather limited temporal changes in mutational load. We hypothesise that ancestral purging may have been facilitated by population fragmentation and isolation on several islands for thousands of generations and may have already reduced much of the highly deleterious load well before human arrival and introduction of pests to the archipelago. The majority of fixed deleterious variation was shared between the modern populations, but translocation of individuals with low mutational load could possibly mitigate further fixation of high-frequency deleterious variation.
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Affiliation(s)
- Johanna von Seth
- Centre for Palaeogenetics, Svante Arrhenius Väg 20C, 106 91, Stockholm, Sweden.
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.
- Department of Zoology, Stockholm University, 106 91, Stockholm, Sweden.
| | - Tom van der Valk
- Centre for Palaeogenetics, Svante Arrhenius Väg 20C, 106 91, Stockholm, Sweden
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
| | - Edana Lord
- Centre for Palaeogenetics, Svante Arrhenius Väg 20C, 106 91, Stockholm, Sweden
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
- Department of Zoology, Stockholm University, 106 91, Stockholm, Sweden
| | - Hanna Sigeman
- Department of Biology, Lund University, Ecology Building, 223 62, Lund, Sweden
- Ecology and Genetics Research Unit, University of Oulu, 90014, Oulu, Finland
| | - Remi-André Olsen
- Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, 17121, Solna, Sweden
| | - Michael Knapp
- Department of Anatomy, University of Otago, Dunedin, 9054, New Zealand
- Coastal People Southern Skies Centre of Research Excellence, University of Otago, PO Box 56, Dunedin, 9054, Aotearoa, New Zealand
| | - Olga Kardailsky
- Department of Anatomy, University of Otago, Dunedin, 9054, New Zealand
| | - Fiona Robertson
- Department of Zoology, University of Otago, Dunedin, 9054, New Zealand
| | - Marie Hale
- School of Biological Sciences, University of Canterbury, Christchurch, 8140, New Zealand
| | - Dave Houston
- Department of Conservation, Biodiversity Group, Auckland, New Zealand
| | - Euan Kennedy
- Department of Conservation, Science and Capability, Christchurch, New Zealand
| | - Love Dalén
- Centre for Palaeogenetics, Svante Arrhenius Väg 20C, 106 91, Stockholm, Sweden
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden
- Department of Zoology, Stockholm University, 106 91, Stockholm, Sweden
| | - Karin Norén
- Department of Zoology, Stockholm University, 106 91, Stockholm, Sweden
| | - Melanie Massaro
- School of Agricultural, Environmental and Veterinary Sciences and Gulbali Institute, Charles Sturt University, PO Box 789, Albury, NSW, Australia
| | - Bruce C Robertson
- Department of Zoology, University of Otago, Dunedin, 9054, New Zealand
| | - Nicolas Dussex
- Centre for Palaeogenetics, Svante Arrhenius Väg 20C, 106 91, Stockholm, Sweden.
- Department of Bioinformatics and Genetics, Swedish Museum of Natural History, Stockholm, Sweden.
- Department of Zoology, Stockholm University, 106 91, Stockholm, Sweden.
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128
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Lee J, Lee J, Jeon S, Lee J, Jang I, Yang JO, Park S, Lee B, Choi J, Choi BO, Gee HY, Oh J, Jang IJ, Lee S, Baek D, Koh Y, Yoon SS, Kim YJ, Chae JH, Park WY, Bhak JH, Choi M. A database of 5305 healthy Korean individuals reveals genetic and clinical implications for an East Asian population. Exp Mol Med 2022; 54:1862-1871. [PMID: 36323850 PMCID: PMC9628380 DOI: 10.1038/s12276-022-00871-4] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 07/21/2022] [Accepted: 08/08/2022] [Indexed: 11/29/2022] Open
Abstract
Despite substantial advances in disease genetics, studies to date have largely focused on individuals of European descent. This limits further discoveries of novel functional genetic variants in other ethnic groups. To alleviate the paucity of East Asian population genome resources, we established the Korean Variant Archive 2 (KOVA 2), which is composed of 1896 whole-genome sequences and 3409 whole-exome sequences from healthy individuals of Korean ethnicity. This is the largest genome database from the ethnic Korean population to date, surpassing the 1909 Korean individuals deposited in gnomAD. The variants in KOVA 2 displayed all the known genetic features of those from previous genome databases, and we compiled data from Korean-specific runs of homozygosity, positively selected intervals, and structural variants. In doing so, we found loci, such as the loci of ADH1A/1B and UHRF1BP1, that are strongly selected in the Korean population relative to other East Asian populations. Our analysis of allele ages revealed a correlation between variant functionality and evolutionary age. The data can be browsed and downloaded from a public website ( https://www.kobic.re.kr/kova/ ). We anticipate that KOVA 2 will serve as a valuable resource for genetic studies involving East Asian populations.
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Affiliation(s)
- Jeongeun Lee
- grid.31501.360000 0004 0470 5905Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul, 03080 Republic of Korea
| | - Jean Lee
- grid.31501.360000 0004 0470 5905Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, 03080 Republic of Korea
| | - Sungwon Jeon
- grid.42687.3f0000 0004 0381 814XDepartment of Biomedical Engineering, College of Information and Biotechnology, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
| | - Jeongha Lee
- grid.31501.360000 0004 0470 5905Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, 03080 Republic of Korea
| | - Insu Jang
- grid.249967.70000 0004 0636 3099Korea BioInformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, 34141 Republic of Korea
| | - Jin Ok Yang
- grid.249967.70000 0004 0636 3099Korea BioInformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, 34141 Republic of Korea ,grid.37172.300000 0001 2292 0500Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141 Republic of Korea
| | - Soojin Park
- grid.31501.360000 0004 0470 5905Department of Pediatrics, Seoul National University College of Medicine, Seoul, 03080 Republic of Korea
| | - Byungwook Lee
- grid.249967.70000 0004 0636 3099Korea BioInformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, 34141 Republic of Korea
| | - Jinwook Choi
- grid.31501.360000 0004 0470 5905Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul, 03080 Republic of Korea ,grid.31501.360000 0004 0470 5905Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, 03080 Republic of Korea
| | - Byung-Ok Choi
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351 Republic of Korea
| | - Heon Yung Gee
- grid.15444.300000 0004 0470 5454Department of Pharmacology, Brain Korea 21 PLUS Project for Medical Sciences, Yonsei University College of Medicine, Seoul, 03722 Republic of Korea
| | - Jaeseong Oh
- grid.31501.360000 0004 0470 5905Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, 03080 Republic of Korea
| | - In-Jin Jang
- grid.31501.360000 0004 0470 5905Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, 03080 Republic of Korea
| | - Sanghyuk Lee
- grid.255649.90000 0001 2171 7754Department of Bio-Information Science, Ewha Womans University, Seoul, 03760 Republic of Korea
| | - Daehyun Baek
- grid.31501.360000 0004 0470 5905School of Biological Sciences, Seoul National University, Seoul, 08826 Republic of Korea
| | - Youngil Koh
- grid.412484.f0000 0001 0302 820XDepartment of Internal Medicine, Seoul National University Hospital, Seoul, 03080 Republic of Korea
| | - Sung-Soo Yoon
- grid.412484.f0000 0001 0302 820XDepartment of Internal Medicine, Seoul National University Hospital, Seoul, 03080 Republic of Korea
| | - Young-Joon Kim
- grid.15444.300000 0004 0470 5454Department of Biochemistry, College of Life Science and Biotechnology, Yonsei University, Seoul, 03722 Republic of Korea
| | - Jong-Hee Chae
- grid.31501.360000 0004 0470 5905Department of Pediatrics, Seoul National University College of Medicine, Seoul, 03080 Republic of Korea ,grid.412484.f0000 0001 0302 820XDepartment of Genomic Medicine, Seoul National University Hospital, Seoul, 03080 Republic of Korea
| | - Woong-Yang Park
- grid.414964.a0000 0001 0640 5613Samsung Genome Institute, Samsung Medical Center, Seoul, 06351 Republic of Korea
| | - Jong Hwa Bhak
- grid.42687.3f0000 0004 0381 814XDepartment of Biomedical Engineering, College of Information and Biotechnology, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 Republic of Korea
| | - Murim Choi
- grid.31501.360000 0004 0470 5905Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, 03080 Republic of Korea
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Woerner AE, Mandape S, Kapema KB, Duque TM, Smuts A, King JL, Crysup B, Wang X, Huang M, Ge J, Budowle B. Optimized variant calling for estimating kinship. Forensic Sci Int Genet 2022; 61:102785. [DOI: 10.1016/j.fsigen.2022.102785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 08/07/2022] [Accepted: 09/29/2022] [Indexed: 11/16/2022]
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130
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Ferreira JC, Alshamali F, Pereira L, Fernandes V. Characterization of Arabian Peninsula whole exomes: Contributing to the catalogue of human diversity. iScience 2022; 25:105336. [DOI: 10.1016/j.isci.2022.105336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 08/01/2022] [Accepted: 10/10/2022] [Indexed: 11/24/2022] Open
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131
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Lee KS, Seo J, Lee CK, Shin S, Choi Z, Min S, Yang JH, Kwon WS, Yun W, Park MR, Choi JR, Chung HC, Lee ST, Rha SY. Analytical and Clinical Validation of Cell-Free Circulating Tumor DNA Assay for the Estimation of Tumor Mutational Burden. Clin Chem 2022; 68:1519-1528. [DOI: 10.1093/clinchem/hvac146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 07/21/2022] [Indexed: 11/12/2022]
Abstract
Abstract
Background
Ultra-deep sequencing to detect low-frequency mutations in circulating tumor-derived DNA (ctDNA) increases the diagnostic value of liquid biopsy. The demand for large ctDNA panels for comprehensive genomic profiling and tumor mutational burden (TMB) estimation is increasing; however, few ctDNA panels for TMB have been validated. Here, we designed a ctDNA panel with 531 genes, named TMB500, along with a technical and clinical validation.
Methods
Synthetic reference cell-free DNA materials with predefined allele frequencies were sequenced in a total of 92 tests in 6 batches to evaluate the precision, linearity, and limit of detection of the assay. We used clinical samples from 50 patients with various cancers, 11 healthy individuals, and paired tissue samples. Molecular barcoding and data analysis were performed using customized pipelines.
Results
The assay showed high precision and linearity (coefficient of determination, r2 = 0.87) for all single nucleotide variants, with a limit of detection of 0.24%. In clinical samples, the TMB500 ctDNA assay detected most variants present and absent in tissues, showing that ctDNA could assess tumor heterogeneity in different tissues and metastasis sites. The estimated TMBs correlated well between tissue and blood, except in 4 cases with extreme heterogeneity that showed very high blood TMBs compared to tissue TMBs. A pilot evaluation showed that the TMB500 assay could be used for disease monitoring.
Conclusions
The TMB500 assay is an accurate and reliable ctDNA assay for many clinical purposes. It may be useful for guiding the treatment of cancers with diverse genomic profiles, estimating TMB in immune therapy, and disease monitoring.
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Affiliation(s)
- Kwang Seob Lee
- Department of Laboratory Medicine, Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Jieun Seo
- Department of Laboratory Medicine, Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Choong-Kun Lee
- Division of Medical Oncology, Department of Internal Medicine, Yonsei University College of Medicine , Seoul , Republic of Korea
- Song-dang Institute for Cancer Research, Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Saeam Shin
- Department of Laboratory Medicine, Yonsei University College of Medicine , Seoul , Republic of Korea
| | | | | | | | - Woo Sun Kwon
- Song-dang Institute for Cancer Research, Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Woobin Yun
- Department of Laboratory Medicine, Graduate School of Medical Science, Brain Korea 21 Project, Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Mi Ri Park
- Department of Laboratory Medicine, Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Jong Rak Choi
- Department of Laboratory Medicine, Yonsei University College of Medicine , Seoul , Republic of Korea
- Dxome , Seoul , Republic of Korea
| | - Hyun Cheol Chung
- Division of Medical Oncology, Department of Internal Medicine, Yonsei University College of Medicine , Seoul , Republic of Korea
- Song-dang Institute for Cancer Research, Yonsei University College of Medicine , Seoul , Republic of Korea
- Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine , Seoul , Republic of Korea
| | - Seung-Tae Lee
- Department of Laboratory Medicine, Yonsei University College of Medicine , Seoul , Republic of Korea
- Dxome , Seoul , Republic of Korea
| | - Sun Young Rha
- Division of Medical Oncology, Department of Internal Medicine, Yonsei University College of Medicine , Seoul , Republic of Korea
- Song-dang Institute for Cancer Research, Yonsei University College of Medicine , Seoul , Republic of Korea
- Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine , Seoul , Republic of Korea
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Hlaváč V, Holý P, Václavíková R, Rob L, Hruda M, Mrhalová M, Černaj P, Bouda J, Souček P. Whole-exome sequencing of epithelial ovarian carcinomas differing in resistance to platinum therapy. Life Sci Alliance 2022; 5:5/12/e202201551. [PMID: 36229065 PMCID: PMC9574568 DOI: 10.26508/lsa.202201551] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 09/23/2022] [Accepted: 09/23/2022] [Indexed: 11/07/2022] Open
Abstract
Exploration of the prognostic and predictive significance of exome variation in epithelial ovarian carcinoma patients, with TP53, Hippo, homologous recombination genes, and the SBS6 signature as the most interesting results. Epithelial ovarian carcinoma (EOC) is highly fatal because of the risk of resistance to therapy and recurrence. We performed whole-exome sequencing of blood and tumor tissue pairs of 50 patients with surgically resected EOC. Compared with sensitive patients, platinum-resistant patients had a significantly higher somatic mutational rate in TP53 and lower in several genes from the Hippo pathway. We confirmed the pivotal role of somatic mutations in homologous recombination repair genes in platinum sensitivity and favorable prognosis of EOC patients. Implementing the germline homologous recombination repair profile significantly improved the prediction. In addition, distinct mutational signatures, for example, SBS6, and overall mutational load, somatic mutations in PABPC1, PABPC3, and TFAM co-segregated with the resistance status, high-grade serous carcinoma subtype, or overall survival of patients. We generated germline and somatic genetic landscapes of prognostically different subgroups of EOC patients for further follow-up studies focused on utilizing the observed associations in precision oncology.
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Affiliation(s)
- Viktor Hlaváč
- Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic,Toxicogenomics Unit, National Institute of Public Health, Prague, Czech Republic
| | - Petr Holý
- Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic,Toxicogenomics Unit, National Institute of Public Health, Prague, Czech Republic,Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Radka Václavíková
- Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic,Toxicogenomics Unit, National Institute of Public Health, Prague, Czech Republic
| | - Lukáš Rob
- Department of Gynecology and Obstetrics, Third Faculty of Medicine, Charles University and University Hospital Královské Vinohrady, Prague, Czech Republic
| | - Martin Hruda
- Department of Gynecology and Obstetrics, Third Faculty of Medicine, Charles University and University Hospital Královské Vinohrady, Prague, Czech Republic
| | - Marcela Mrhalová
- Department of Pathology and Molecular Medicine, Second Faculty of Medicine and Motol University Hospital, Charles University, Prague, Czech Republic
| | - Petr Černaj
- Department of Gynecology and Obstetrics, Faculty of Medicine and University Hospital in Pilsen, Charles University, Pilsen, Czech Republic
| | - Jiří Bouda
- Department of Gynecology and Obstetrics, Faculty of Medicine and University Hospital in Pilsen, Charles University, Pilsen, Czech Republic
| | - Pavel Souček
- Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic,Toxicogenomics Unit, National Institute of Public Health, Prague, Czech Republic,Correspondence:
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133
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Kelly JB, Carlson DE, Low JS, Thacker RW. Novel trends of genome evolution in highly complex tropical sponge microbiomes. MICROBIOME 2022; 10:164. [PMID: 36195901 PMCID: PMC9531527 DOI: 10.1186/s40168-022-01359-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 08/03/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Tropical members of the sponge genus Ircinia possess highly complex microbiomes that perform a broad spectrum of chemical processes that influence host fitness. Despite the pervasive role of microbiomes in Ircinia biology, it is still unknown how they remain in stable association across tropical species. To address this question, we performed a comparative analysis of the microbiomes of 11 Ircinia species using whole-metagenomic shotgun sequencing data to investigate three aspects of bacterial symbiont genomes-the redundancy in metabolic pathways across taxa, the evolution of genes involved in pathogenesis, and the nature of selection acting on genes relevant to secondary metabolism. RESULTS A total of 424 new, high-quality bacterial metagenome-assembled genomes (MAGs) were produced for 10 Caribbean Ircinia species, which were evaluated alongside 113 publicly available MAGs sourced from the Pacific species Ircinia ramosa. Evidence of redundancy was discovered in that the core genes of several primary metabolic pathways could be found in the genomes of multiple bacterial taxa. Across hosts, the metagenomes were depleted in genes relevant to pathogenicity and enriched in eukaryotic-like proteins (ELPs) that likely mimic the hosts' molecular patterning. Finally, clusters of steroid biosynthesis genes (CSGs), which appear to be under purifying selection and undergo horizontal gene transfer, were found to be a defining feature of Ircinia metagenomes. CONCLUSIONS These results illustrate patterns of genome evolution within highly complex microbiomes that illuminate how associations with hosts are maintained. The metabolic redundancy within the microbiomes could help buffer the hosts from changes in the ambient chemical and physical regimes and from fluctuations in the population sizes of the individual microbial strains that make up the microbiome. Additionally, the enrichment of ELPs and depletion of LPS and cellular motility genes provide a model for how alternative strategies to virulence can evolve in microbiomes undergoing mixed-mode transmission that do not ultimately result in higher levels of damage (i.e., pathogenicity) to the host. Our last set of results provides evidence that sterol biosynthesis in Ircinia-associated bacteria is widespread and that these molecules are important for the survival of bacteria in highly complex Ircinia microbiomes. Video Abstract.
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Affiliation(s)
- Joseph B Kelly
- Aquatic Ecology and Evolution, Limnological Institute University Konstanz, Konstanz, Germany.
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY, USA.
| | - David E Carlson
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY, USA
| | - Jun Siong Low
- Institute of Microbiology,ETH Zürich, Zürich, Switzerland
- Institute for Research in Biomedicine, Università della Svizzera Italiana, Bellinzona, Switzerland
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA
| | - Robert W Thacker
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY, USA
- Smithsonian Tropical Research Institute, Box 0843-03092, Balboa, Panama City, Republic of Panama
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134
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Zhou X, Feliciano P, Shu C, Wang T, Astrovskaya I, Hall JB, Obiajulu JU, Wright JR, Murali SC, Xu SX, Brueggeman L, Thomas TR, Marchenko O, Fleisch C, Barns SD, Snyder LG, Han B, Chang TS, Turner TN, Harvey WT, Nishida A, O'Roak BJ, Geschwind DH, Michaelson JJ, Volfovsky N, Eichler EE, Shen Y, Chung WK. Integrating de novo and inherited variants in 42,607 autism cases identifies mutations in new moderate-risk genes. Nat Genet 2022; 54:1305-1319. [PMID: 35982159 PMCID: PMC9470534 DOI: 10.1038/s41588-022-01148-2] [Citation(s) in RCA: 211] [Impact Index Per Article: 70.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Accepted: 06/28/2022] [Indexed: 12/16/2022]
Abstract
To capture the full spectrum of genetic risk for autism, we performed a two-stage analysis of rare de novo and inherited coding variants in 42,607 autism cases, including 35,130 new cases recruited online by SPARK. We identified 60 genes with exome-wide significance (P < 2.5 × 10-6), including five new risk genes (NAV3, ITSN1, MARK2, SCAF1 and HNRNPUL2). The association of NAV3 with autism risk is primarily driven by rare inherited loss-of-function (LoF) variants, with an estimated relative risk of 4, consistent with moderate effect. Autistic individuals with LoF variants in the four moderate-risk genes (NAV3, ITSN1, SCAF1 and HNRNPUL2; n = 95) have less cognitive impairment than 129 autistic individuals with LoF variants in highly penetrant genes (CHD8, SCN2A, ADNP, FOXP1 and SHANK3) (59% vs 88%, P = 1.9 × 10-6). Power calculations suggest that much larger numbers of autism cases are needed to identify additional moderate-risk genes.
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Affiliation(s)
- Xueya Zhou
- Department of Pediatrics, Columbia University Medical Center, New York, NY, USA
- Department of Systems Biology, Columbia University Medical Center, New York, NY, USA
| | | | - Chang Shu
- Department of Pediatrics, Columbia University Medical Center, New York, NY, USA
- Department of Systems Biology, Columbia University Medical Center, New York, NY, USA
| | - Tianyun Wang
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Department of Medical Genetics, Center for Medical Genetics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China
- Neuroscience Research Institute, Department of Neurobiology, School of Basic Medical Sciences, Peking University Health Science Center; Key Laboratory for Neuroscience, Ministry of Education of China & National Health Commission of China, Beijing, China
| | | | | | - Joseph U Obiajulu
- Department of Pediatrics, Columbia University Medical Center, New York, NY, USA
- Department of Systems Biology, Columbia University Medical Center, New York, NY, USA
| | | | - Shwetha C Murali
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | | | - Leo Brueggeman
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Taylor R Thomas
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | | | | | | | | | - Bing Han
- Simons Foundation, New York, NY, USA
| | - Timothy S Chang
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Tychele N Turner
- Department of Genetics, Washington University, St. Louis, MO, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Andrew Nishida
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Brian J O'Roak
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Daniel H Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jacob J Michaelson
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | | | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Yufeng Shen
- Department of Systems Biology, Columbia University Medical Center, New York, NY, USA
- Department of Biomedical Informatics, Columbia University Medical Center, New York, NY, USA
| | - Wendy K Chung
- Department of Pediatrics, Columbia University Medical Center, New York, NY, USA.
- Simons Foundation, New York, NY, USA.
- Department of Medicine, Columbia University Medical Center, New York, NY, USA.
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135
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Castaneda-Garcia C, Iyer V, Nsengimana J, Trower A, Droop A, Brown KM, Choi J, Zhang T, Harland M, Newton-Bishop JA, Bishop DT, Adams DJ, Iles MM, Robles-Espinoza CD. Defining novel causal SNPs and linked phenotypes at melanoma-associated loci. Hum Mol Genet 2022; 31:2845-2856. [PMID: 35357426 PMCID: PMC9433725 DOI: 10.1093/hmg/ddac074] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 11/13/2022] Open
Abstract
A number of genomic regions have been associated with melanoma risk through genome-wide association studies; however, the causal variants underlying the majority of these associations remain unknown. Here, we sequenced either the full locus or the functional regions including exons of 19 melanoma-associated loci in 1959 British melanoma cases and 737 controls. Variant filtering followed by Fisher's exact test analyses identified 66 variants associated with melanoma risk. Sequential conditional logistic regression identified the distinct haplotypes on which variants reside, and massively parallel reporter assays provided biological insights into how these variants influence gene function. We performed further analyses to link variants to melanoma risk phenotypes and assessed their association with melanoma-specific survival. Our analyses replicate previously known associations in the melanocortin 1 receptor (MC1R) and tyrosinase (TYR) loci, while identifying novel potentially causal variants at the MTAP/CDKN2A and CASP8 loci. These results improve our understanding of the architecture of melanoma risk and outcome.
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Affiliation(s)
- Carolina Castaneda-Garcia
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Santiago de Querétaro, México 76230, USA
| | - Vivek Iyer
- Cancer, Ageing and Somatic Mutation, Wellcome Sanger Institute, Hinxton, Cambridgeshire CB101SA, UK
| | - Jérémie Nsengimana
- Biostatistics Research Group, Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4BN, UK
| | - Adam Trower
- Leeds Institute of Medical Research, School of Medicine, University of Leeds, Leeds LS9 7TF, UK
- Leeds Institute for Data Analytics, University of Leeds, Leeds LS9 7TF, USA
| | - Alastair Droop
- Cancer, Ageing and Somatic Mutation, Wellcome Sanger Institute, Hinxton, Cambridgeshire CB101SA, UK
| | - Kevin M Brown
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jiyeon Choi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Tongwu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Mark Harland
- Leeds Institute of Medical Research, School of Medicine, University of Leeds, Leeds LS9 7TF, UK
| | - Julia A Newton-Bishop
- Leeds Institute of Medical Research, School of Medicine, University of Leeds, Leeds LS9 7TF, UK
| | - D Timothy Bishop
- Leeds Institute of Medical Research, School of Medicine, University of Leeds, Leeds LS9 7TF, UK
- Leeds Institute for Data Analytics, University of Leeds, Leeds LS9 7TF, USA
| | - David J Adams
- Cancer, Ageing and Somatic Mutation, Wellcome Sanger Institute, Hinxton, Cambridgeshire CB101SA, UK
| | - Mark M Iles
- Leeds Institute of Medical Research, School of Medicine, University of Leeds, Leeds LS9 7TF, UK
- Leeds Institute for Data Analytics, University of Leeds, Leeds LS9 7TF, USA
| | - Carla Daniela Robles-Espinoza
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Santiago de Querétaro, México 76230, USA
- Cancer, Ageing and Somatic Mutation, Wellcome Sanger Institute, Hinxton, Cambridgeshire CB101SA, UK
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Bouzinier MA, Etin D, Trifonov SI, Evdokimova VN, Ulitin V, Shen J, Kokorev A, Ghazani AA, Chekaluk Y, Albertyn Z, Giersch A, Morton CC, Abraamyan F, Bendapudi PK, Sunyaev S, Undiagnosed Diseases Network, Brigham Genomic Medicine, SEQuencing A Baby For An Optimal Outcome, Quantori, Krier JB. AnFiSA: An open-source computational platform for the analysis of sequencing data for rare genetic disease. J Biomed Inform 2022; 133:104174. [PMID: 35998814 DOI: 10.1016/j.jbi.2022.104174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 07/23/2022] [Accepted: 08/15/2022] [Indexed: 11/28/2022]
Abstract
Despite genomic sequencing rapidly transforming from being a bench-side tool to a routine procedure in a hospital, there is a noticeable lack of genomic analysis software that supports both clinical and research workflows as well as crowdsourcing. Furthermore, most existing software packages are not forward-compatible in regards to supporting ever-changing diagnostic rules adopted by the genetics community. Regular updates of genomics databases pose challenges for reproducible and traceable automated genetic diagnostics tools. Lastly, most of the software tools score low on explainability amongst clinicians. We have created a fully open-source variant curation tool, AnFiSA, with the intention to invite and accept contributions from clinicians, researchers, and professional software developers. The design of AnFiSA addresses the aforementioned issues via the following architectural principles: using a multidimensional database management system (DBMS) for genomic data to address reproducibility, curated decision trees adaptable to changing clinical rules, and a crowdsourcing-friendly interface to address difficult-to-diagnose cases. We discuss how we have chosen our technology stack and describe the design and implementation of the software. Finally, we show in detail how selected workflows can be implemented using the current version of AnFiSA by a medical geneticist.
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Affiliation(s)
- M A Bouzinier
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - D Etin
- Forome Association, Boston, MA, USA; Oracle Corporation, USA.
| | | | - V N Evdokimova
- Forome Association, Boston, MA, USA; SBCS Scientific Biomedical Consulting Services, London, UK
| | - V Ulitin
- Forome Association, Boston, MA, USA
| | - J Shen
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - A Kokorev
- ITMO University, St. Petersburg, Russian Federation
| | - A A Ghazani
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Brigham Genomic Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Y Chekaluk
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Z Albertyn
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - A Giersch
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - C C Morton
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Obstetrics and Gynecology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Manchester Centre for Audiology and Deafness (ManCAD), School of Health Sciences, University of Manchester, UK
| | - F Abraamyan
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - P K Bendapudi
- Division of Hemostasis and Thrombosis, Beth Israel Deaconess Medical Center, Boston, MA, USA; Division of Hematology and Blood Transfusion Service, Massachusetts General Hospital, Boston, MA, USA
| | - S Sunyaev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | | | | | | | | | - J B Krier
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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137
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Majeed A, Johar P, Raina A, Salgotra RK, Feng X, Bhat JA. Harnessing the potential of bulk segregant analysis sequencing and its related approaches in crop breeding. Front Genet 2022; 13:944501. [PMID: 36003337 PMCID: PMC9393495 DOI: 10.3389/fgene.2022.944501] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 06/28/2022] [Indexed: 12/26/2022] Open
Abstract
Most plant traits are governed by polygenes including both major and minor genes. Linkage mapping and positional cloning have contributed greatly to mapping genomic loci controlling important traits in crop species. However, they are low-throughput, time-consuming, and have low resolution due to which their efficiency in crop breeding is reduced. In this regard, the bulk segregant analysis sequencing (BSA-seq) and its related approaches, viz., quantitative trait locus (QTL)-seq, bulk segregant RNA-Seq (BSR)-seq, and MutMap, have emerged as efficient methods to identify the genomic loci/QTLs controlling specific traits at high resolution, accuracy, reduced time span, and in a high-throughput manner. These approaches combine BSA with next-generation sequencing (NGS) and enable the rapid identification of genetic loci for qualitative and quantitative assessments. Many previous studies have shown the successful identification of the genetic loci for different plant traits using BSA-seq and its related approaches, as discussed in the text with details. However, the efficiency and accuracy of the BSA-seq depend upon factors like sequencing depth and coverage, which enhance the sequencing cost. Recently, the rapid reduction in the cost of NGS together with the expected cost reduction of third-generation sequencing in the future has further increased the accuracy and commercial applicability of these approaches in crop improvement programs. This review article provides an overview of BSA-seq and its related approaches in crop breeding together with their merits and challenges in trait mapping.
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Affiliation(s)
- Aasim Majeed
- School of Agricultural Biotechnology, Punjab Agriculture University (PAU), Ludhiana, India
| | - Prerna Johar
- School of Biotechnology, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Jammu, India
| | - Aamir Raina
- Department of Botany, Faculty of Life Sciences, Aligarh Muslim University, Aligarh, India
| | - R. K. Salgotra
- School of Biotechnology, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Jammu, India
| | | | - Javaid Akhter Bhat
- Zhejiang Lab, Hangzhou, China
- International Genome Center, Jiangsu University, Zhenjiang, China
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138
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Brucato N, André M, Hudjashov G, Mondal M, Cox MP, Leavesley M, Ricaut FX. Chronology of natural selection in Oceanian genomes. iScience 2022; 25:104583. [PMID: 35880026 PMCID: PMC9308150 DOI: 10.1016/j.isci.2022.104583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 05/11/2022] [Accepted: 06/07/2022] [Indexed: 11/30/2022] Open
Abstract
As human populations left Asia to first settle in Oceania around 50,000 years ago, they entered a territory ecologically separated from the Old World for millions of years. We analyzed genomic data of 239 modern Oceanian individuals to detect and date signals of selection specific to this region. Combining both relative and absolute dating approaches, we identified a strong selection pattern between 52,000 and 54,000 years ago in the genomes of descendants of the first settlers of Sahul. This strikingly corresponds to the dates of initial settlement as inferred from archaeological evidence. Loci under selection during this period, some showing enrichment in Denisovan ancestry, overlap genes involved in the immune response and diet, especially based on plants. Pathogens and natural resources, especially from endemic plants, therefore appear to have acted as strong selective pressures on the genomes of the first settlers of Sahul.
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Affiliation(s)
- Nicolas Brucato
- Laboratoire Évolution et Diversité Biologique (EDB UMR 5174), Université de Toulouse Midi-Pyrénées, CNRS, IRD, UPS. 118 route de Narbonne, Bat 4R1, 31062 cedex 9 Toulouse, France
| | - Mathilde André
- Laboratoire Évolution et Diversité Biologique (EDB UMR 5174), Université de Toulouse Midi-Pyrénées, CNRS, IRD, UPS. 118 route de Narbonne, Bat 4R1, 31062 cedex 9 Toulouse, France
- Institute of Genomics, University of Tartu, Tartu, 51010 Tartumaa, Estonia
| | - Georgi Hudjashov
- Institute of Genomics, University of Tartu, Tartu, 51010 Tartumaa, Estonia
| | - Mayukh Mondal
- Institute of Genomics, University of Tartu, Tartu, 51010 Tartumaa, Estonia
| | - Murray P. Cox
- School of Natural Sciences, Massey University, Palmerston North 4442, New Zealand
| | - Matthew Leavesley
- Strand of Anthropology, Sociology and Archaeology, School of Humanities and Social Sciences, University of Papua New Guinea, PO Box 320, National Capital District 134, Papua New Guinea
- College of Arts, Society and Education, James Cook University, P.O. Box 6811, Cairns, QLD 4870, Australia
- ARC Centre of Excellence for Australian Biodiversity and Heritage, University of Wollongong, Wollongong, NSW 2522, Australia
| | - François-Xavier Ricaut
- Laboratoire Évolution et Diversité Biologique (EDB UMR 5174), Université de Toulouse Midi-Pyrénées, CNRS, IRD, UPS. 118 route de Narbonne, Bat 4R1, 31062 cedex 9 Toulouse, France
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Di Santo LN, Hoban S, Parchman TL, Wright JW, Hamilton JA. Reduced representation sequencing to understand the evolutionary history of Torrey pine (Pinus torreyana Parry) with implications for rare species conservation. Mol Ecol 2022; 31:4622-4639. [PMID: 35822858 DOI: 10.1111/mec.16615] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 06/29/2022] [Accepted: 07/01/2022] [Indexed: 11/30/2022]
Abstract
Understanding the contribution of neutral and adaptive evolutionary processes to population differentiation is often necessary for better informed management and conservation of rare species. In this study, we focused on Pinus torreyana Parry (Torrey pine), one of the world's rarest pines, endemic to one island and one mainland population in California. Small population size, low genetic diversity, and susceptibility to abiotic and biotic stresses suggest Torrey pine may benefit from inter-population genetic rescue to preserve the species' evolutionary potential. We leveraged reduced representation sequencing to tease apart the respective contributions of stochastic and deterministic evolutionary processes to population differentiation. We applied these data to model spatial and temporal demographic changes in effective population sizes and genetic connectivity, to identify loci possibly under selection, and evaluate genetic rescue as a potential conservation strategy. Overall, we observed exceedingly low standing variation within both Torrey pine populations, reflecting consistently low effective population sizes across time, and limited genetic differentiation, suggesting maintenance of gene flow between populations following divergence. However, genome scans identified more than 2000 candidate SNPs potentially under divergent selection. Combined with previous observations indicating population phenotypic differentiation, this indicates natural selection has likely contributed to the evolution of population genetic differences. Thus, while reduced genetic diversity, small effective population size, and genetic connectivity between populations suggest genetic rescue could mitigate the adverse effects of rarity, evidence for adaptive differentiation suggests genetic mixing could disrupt adaptation. Further work evaluating the fitness consequences of inter-population admixture is necessary to empirically evaluate the trade-offs associated with genetic rescue in Torrey pine.
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Affiliation(s)
- Lionel N Di Santo
- North Dakota State University, Department of Biological Sciences, Fargo, ND, USA
| | | | | | - Jessica W Wright
- USDA- Forest Service, Pacific Southwest Research Station, Davis, CA, USA
| | - Jill A Hamilton
- North Dakota State University, Department of Biological Sciences, Fargo, ND, USA.,Pennsylvania State University, Department of Ecosystem Science and Management, University Park, PA, USA
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140
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Exome sequencing analysis of Japanese autism spectrum disorder case-control sample supports an increased burden of synaptic function-related genes. Transl Psychiatry 2022; 12:265. [PMID: 35811316 PMCID: PMC9271461 DOI: 10.1038/s41398-022-02033-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 06/15/2022] [Accepted: 06/17/2022] [Indexed: 01/16/2023] Open
Abstract
Autism spectrum disorder (ASD) is a highly heritable, complex disorder in which rare variants contribute significantly to disease risk. Although many genes have been associated with ASD, there have been few genetic studies of ASD in the Japanese population. In whole exomes from a Japanese ASD sample of 309 cases and 299 controls, rare variants were associated with ASD within specific neurodevelopmental gene sets, including highly constrained genes, fragile X mental retardation protein target genes, and genes involved in synaptic function, with the strongest enrichment in trans-synaptic signaling (p = 4.4 × 10-4, Q-value = 0.06). In particular, we strengthen the evidence regarding the role of ABCA13, a synaptic function-related gene, in Japanese ASD. The overall results of this case-control exome study showed that rare variants related to synaptic function are associated with ASD susceptibility in the Japanese population.
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141
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Giorgashvili E, Reichel K, Caswara C, Kerimov V, Borsch T, Gruenstaeudl M. Software Choice and Sequencing Coverage Can Impact Plastid Genome Assembly-A Case Study in the Narrow Endemic Calligonum bakuense. FRONTIERS IN PLANT SCIENCE 2022; 13:779830. [PMID: 35874012 PMCID: PMC9296850 DOI: 10.3389/fpls.2022.779830] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Accepted: 06/13/2022] [Indexed: 06/15/2023]
Abstract
Most plastid genome sequences are assembled from short-read whole-genome sequencing data, yet the impact that sequencing coverage and the choice of assembly software can have on the accuracy of the resulting assemblies is poorly understood. In this study, we test the impact of both factors on plastid genome assembly in the threatened and rare endemic shrub Calligonum bakuense. We aim to characterize the differences across plastid genome assemblies generated by different assembly software tools and levels of sequencing coverage and to determine if these differences are large enough to affect the phylogenetic position inferred for C. bakuense compared to congeners. Four assembly software tools (FastPlast, GetOrganelle, IOGA, and NOVOPlasty) and seven levels of sequencing coverage across the plastid genome (original sequencing depth, 2,000x, 1,000x, 500x, 250x, 100x, and 50x) are compared in our analyses. The resulting assemblies are evaluated with regard to reproducibility, contig number, gene complement, inverted repeat length, and computation time; the impact of sequence differences on phylogenetic reconstruction is assessed. Our results show that software choice can have a considerable impact on the accuracy and reproducibility of plastid genome assembly and that GetOrganelle produces the most consistent assemblies for C. bakuense. Moreover, we demonstrate that a sequencing coverage between 500x and 100x can reduce both the sequence variability across assembly contigs and computation time. When comparing the most reliable plastid genome assemblies of C. bakuense, a sequence difference in only three nucleotide positions is detected, which is less than the difference potentially introduced through software choice.
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Affiliation(s)
- Eka Giorgashvili
- Systematische Botanik und Pflanzengeographie, Institut für Biologie, Freie Universität Berlin, Berlin, Germany
| | - Katja Reichel
- Systematische Botanik und Pflanzengeographie, Institut für Biologie, Freie Universität Berlin, Berlin, Germany
| | - Calvinna Caswara
- Systematische Botanik und Pflanzengeographie, Institut für Biologie, Freie Universität Berlin, Berlin, Germany
| | - Vuqar Kerimov
- Institute of Botany, Azerbaijan National Academy of Sciences (ANAS), Baku, Azerbaijan
| | - Thomas Borsch
- Systematische Botanik und Pflanzengeographie, Institut für Biologie, Freie Universität Berlin, Berlin, Germany
- Botanischer Garten und Botanisches Museum Berlin, Freie Universität Berlin, Berlin, Germany
| | - Michael Gruenstaeudl
- Systematische Botanik und Pflanzengeographie, Institut für Biologie, Freie Universität Berlin, Berlin, Germany
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142
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Lefouili M, Nam K. The evaluation of Bcftools mpileup and GATK HaplotypeCaller for variant calling in non-human species. Sci Rep 2022; 12:11331. [PMID: 35790846 PMCID: PMC9256665 DOI: 10.1038/s41598-022-15563-2] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 06/27/2022] [Indexed: 11/09/2022] Open
Abstract
Identification of genetic variations is a central part of population and quantitative genomics studies based on high-throughput sequencing data. Even though popular variant callers such as Bcftools mpileup and GATK HaplotypeCaller were developed nearly 10 years ago, their performance is still largely unknown for non-human species. Here, we showed by benchmark analyses with a simulated insect population that Bcftools mpileup performs better than GATK HaplotypeCaller in terms of recovery rate and accuracy regardless of mapping software. The vast majority of false positives were observed from repeats, especially for GATK HaplotypeCaller. Variant scores calculated by GATK did not clearly distinguish true positives from false positives in the vast majority of cases, implying that hard-filtering with GATK could be challenging. These results suggest that Bcftools mpileup may be the first choice for non-human studies and that variants within repeats might have to be excluded for downstream analyses.
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Affiliation(s)
| | - Kiwoong Nam
- DGIMI, Univ Montpellier, INRAE, Montpellier, France.
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143
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Zhao Y, Zhang K, Pan H, Wang Y, Zhou X, Xiang Y, Xu Q, Sun Q, Tan J, Yan X, Li J, Guo J, Tang B, Liu Z. Genetic Analysis of Six Transmembrane Protein Family Genes in Parkinson's Disease in a Large Chinese Cohort. Front Aging Neurosci 2022; 14:889057. [PMID: 35860667 PMCID: PMC9289399 DOI: 10.3389/fnagi.2022.889057] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 06/15/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives Parkinson's disease (PD) is a neurodegenerative disorder with the manifestation of motor symptoms and non-motor symptoms. Previous studies have indicated the role of several transmembrane (TMEM) protein family genes in PD pathogenesis. Materials and Methods In order to better investigate the genetic role of PD-related TMEM protein family genes in PD, including TMEM230, TMEM59, TMEM108, TMEM163, TMEM175, and TMEM229B, 1,917 sporadic early onset PD (sEOPD) or familial PD (FPD) patients and 1,652 healthy controls were analyzed by whole-exome sequencing (WES) while 1,962 sporadic late-onset PD (sLOPD) and 1,279 healthy controls were analyzed by whole-genome sequencing (WGS). Rare and common variants for each gene were included in the analysis. Results One hundred rare damaging or loss of function variants of six genes were found at the threshold of MAF < 0.1%. Three rare Dmis variants of TMEM230 were specifically identified in PD. Rare missense variants of TMEM59 were statistically significantly associated with PD in the WES cohort, indicating the role of TMEM59 in FPD and sEOPD. Rare missense variants of TMEM108 were suggestively associated with PD in the WGS cohort, indicating the potential role of TMEM108 in sLOPD. The rare variant of the other three genes and common variants of six genes were not significantly associated with PD. Conclusion We performed a large case-control study to systematically investigate the role of several PD-related TMEM protein family genes in PD. We identified three PD-specific variants in TMEM230, the significant association of TMEM59 with FPD, and sEOPD and the suggestive association of TMEM108 with sLOPD.
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Affiliation(s)
- Yuwen Zhao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Kailin Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Hongxu Pan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yige Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Xiaoxia Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yaqin Xiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Qian Xu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Qiying Sun
- Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, China
| | - Jieqiong Tan
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, China
| | - Xinxiang Yan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Jinchen Li
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, China
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, China
| | - Jifeng Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
| | - Zhenhua Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, China
- Key Laboratory of Hunan Province in Neurodegenerative Disorders, Central South University, Changsha, China
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144
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Wang RJ, Raveendran M, Harris RA, Murphy WJ, Lyons LA, Rogers J, Hahn MW. De novo Mutations in Domestic Cat are Consistent with an Effect of Reproductive Longevity on Both the Rate and Spectrum of Mutations. Mol Biol Evol 2022; 39:msac147. [PMID: 35771663 PMCID: PMC9290555 DOI: 10.1093/molbev/msac147] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
The mutation rate is a fundamental evolutionary parameter with direct and appreciable effects on the health and function of individuals. Here, we examine this important parameter in the domestic cat, a beloved companion animal as well as a valuable biomedical model. We estimate a mutation rate of 0.86 × 10-8 per bp per generation for the domestic cat (at an average parental age of 3.8 years). We find evidence for a significant paternal age effect, with more mutations transmitted by older sires. Our analyses suggest that the cat and the human have accrued similar numbers of mutations in the germline before reaching sexual maturity. The per-generation mutation rate in the cat is 28% lower than what has been observed in humans, but is consistent with the shorter generation time in the cat. Using a model of reproductive longevity, which takes into account differences in the reproductive age and time to sexual maturity, we are able to explain much of the difference in per-generation rates between species. We further apply our reproductive longevity model in a novel analysis of mutation spectra and find that the spectrum for the cat resembles the human mutation spectrum at a younger age of reproduction. Together, these results implicate changes in life-history as a driver of mutation rate evolution between species. As the first direct observation of the paternal age effect outside of rodents and primates, our results also suggest a phenomenon that may be universal among mammals.
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Affiliation(s)
- Richard J Wang
- Department of Biology, Indiana University, Bloomington, IN, USA
| | - Muthuswamy Raveendran
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - R Alan Harris
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - William J Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
| | - Leslie A Lyons
- Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, MO, USA
| | - Jeffrey Rogers
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Matthew W Hahn
- Department of Biology, Indiana University, Bloomington, IN, USA
- Department of Computer Science, Indiana University, Bloomington, IN, USA
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145
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Patel AP, Dron JS, Wang M, Pirruccello JP, Ng K, Natarajan P, Lebo M, Ellinor PT, Aragam KG, Khera AV. Association of Pathogenic DNA Variants Predisposing to Cardiomyopathy With Cardiovascular Disease Outcomes and All-Cause Mortality. JAMA Cardiol 2022; 7:723-732. [PMID: 35544052 PMCID: PMC9096692 DOI: 10.1001/jamacardio.2022.0901] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Importance Pathogenic variants associated with inherited cardiomyopathy are recognized as important and clinically actionable when identified, leading some clinicians to recommend population-wide genomic screening. Objective To determine the prevalence and clinical importance of pathogenic variants associated with inherited cardiomyopathy within the context of contemporary clinical care. Design, Setting, and Participants This was a genetic association study of participants in Atherosclerosis in Risk Communities (ARIC), recruited from 1987 to 1989, with median follow-up of 27 years, and the UK Biobank, recruited from 2006 to 2010, with median follow-up of 10 years. ARIC participants were recruited from 4 sites across the US. UK Biobank participants were recruited from 22 sites across the UK. Participants in the US were of African and European ancestry; those in the UK were of African, East Asian, South Asian, and European ancestry. Statistical analyses were performed between August 1, 2021, and February 9, 2022. Exposures Rare genetic variants predisposing to inherited cardiomyopathy. Main Outcomes and Measures Pathogenicity of observed DNA sequence variants in sequenced exomes of 13 genes (ACTC1, FLNC, GLA, LMNA, MYBPC3, MYH7, MYL2, MYL3, PRKAG2, TNNI3, TNNT2, TPM1, and TTN) associated with inherited cardiomyopathies were classified by a blinded clinical geneticist per American College of Medical Genetics recommendations. Incidence of all-cause mortality, heart failure, and atrial fibrillation were determined. Cardiac magnetic resonance imaging, echocardiography, and electrocardiogram measures were assessed in a subset of participants. Results A total of 9667 ARIC participants (mean [SD] age, 54.0 [5.7] years; 4232 women [43.8%]; 2658 African [27.5%] and 7009 European [72.5%] ancestry) and 49 744 UK Biobank participants (mean [SD] age, 57.1 [8.0] years; 27 142 women [54.5%]; 1006 African [2.0%], 173 East Asian [0.3%], 939 South Asian [1.9%], and 46 449 European [93.4%] European ancestry) were included in the study. Of those, 59 participants (0.61%) in ARIC and 364 participants (0.73%) in UK Biobank harbored an actionable pathogenic or likely pathogenic variant associated with dilated or hypertrophic cardiomyopathy. Carriers of these variants were not reliably identifiable by imaging. However, the presence of these variants was associated with increased risk of heart failure (hazard ratio [HR], 1.7; 95% CI, 1.1-2.8), atrial fibrillation (HR, 2.9; 95% CI, 1.9-4.5), and all-cause mortality (HR, 1.5; 95% CI, 1.1-2.2) in ARIC. Similar risk patterns were observed in the UK Biobank. Conclusions and Relevance Results of this genetic association study suggest that approximately 0.7% of study participants harbored a pathogenic variant associated with inherited cardiomyopathy. These variant carriers would be challenging to identify within clinical practice without genetic testing but are at increased risk for cardiovascular disease and all-cause mortality.
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Affiliation(s)
- Aniruddh P Patel
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston.,Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston.,Cardiovascular Disease Initiative, Broad Institute of MIT, Harvard, Cambridge, Massachusetts.,Department of Medicine, Harvard Medical School, Boston, Massachusetts.,Cardiovascular Research Center, Massachusetts General Hospital, Boston
| | - Jacqueline S Dron
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston.,Cardiovascular Disease Initiative, Broad Institute of MIT, Harvard, Cambridge, Massachusetts
| | - Minxian Wang
- Chinese Academy of Sciences Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - James P Pirruccello
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston.,Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston.,Cardiovascular Disease Initiative, Broad Institute of MIT, Harvard, Cambridge, Massachusetts.,Department of Medicine, Harvard Medical School, Boston, Massachusetts.,Cardiovascular Research Center, Massachusetts General Hospital, Boston
| | - Kenney Ng
- Center for Computational Health, IBM Research, Cambridge, Massachusetts
| | - Pradeep Natarajan
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston.,Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston.,Cardiovascular Disease Initiative, Broad Institute of MIT, Harvard, Cambridge, Massachusetts.,Department of Medicine, Harvard Medical School, Boston, Massachusetts.,Cardiovascular Research Center, Massachusetts General Hospital, Boston
| | - Matthew Lebo
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Boston, Massachusetts.,Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.,Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Patrick T Ellinor
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston.,Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston.,Cardiovascular Disease Initiative, Broad Institute of MIT, Harvard, Cambridge, Massachusetts.,Department of Medicine, Harvard Medical School, Boston, Massachusetts.,Cardiovascular Research Center, Massachusetts General Hospital, Boston
| | - Krishna G Aragam
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston.,Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston.,Cardiovascular Disease Initiative, Broad Institute of MIT, Harvard, Cambridge, Massachusetts.,Department of Medicine, Harvard Medical School, Boston, Massachusetts.,Cardiovascular Research Center, Massachusetts General Hospital, Boston
| | - Amit V Khera
- Division of Cardiology, Department of Medicine, Massachusetts General Hospital, Boston.,Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston.,Cardiovascular Disease Initiative, Broad Institute of MIT, Harvard, Cambridge, Massachusetts.,Department of Medicine, Harvard Medical School, Boston, Massachusetts.,Verve Therapeutics, Cambridge, Massachusetts
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146
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Agrawal S, Wang M, Klarqvist MDR, Smith K, Shin J, Dashti H, Diamant N, Choi SH, Jurgens SJ, Ellinor PT, Philippakis A, Claussnitzer M, Ng K, Udler MS, Batra P, Khera AV. Inherited basis of visceral, abdominal subcutaneous and gluteofemoral fat depots. Nat Commun 2022; 13:3771. [PMID: 35773277 PMCID: PMC9247093 DOI: 10.1038/s41467-022-30931-2] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 05/25/2022] [Indexed: 12/11/2022] Open
Abstract
For any given level of overall adiposity, individuals vary considerably in fat distribution. The inherited basis of fat distribution in the general population is not fully understood. Here, we study up to 38,965 UK Biobank participants with MRI-derived visceral (VAT), abdominal subcutaneous (ASAT), and gluteofemoral (GFAT) adipose tissue volumes. Because these fat depot volumes are highly correlated with BMI, we additionally study six local adiposity traits: VAT adjusted for BMI and height (VATadj), ASATadj, GFATadj, VAT/ASAT, VAT/GFAT, and ASAT/GFAT. We identify 250 independent common variants (39 newly-identified) associated with at least one trait, with many associations more pronounced in female participants. Rare variant association studies extend prior evidence for PDE3B as an important modulator of fat distribution. Local adiposity traits (1) highlight depot-specific genetic architecture and (2) enable construction of depot-specific polygenic scores that have divergent associations with type 2 diabetes and coronary artery disease. These results - using MRI-derived, BMI-independent measures of local adiposity - confirm fat distribution as a highly heritable trait with important implications for cardiometabolic health outcomes.
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Affiliation(s)
- Saaket Agrawal
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Minxian Wang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | | | - Kirk Smith
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Joseph Shin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Hesam Dashti
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nathaniel Diamant
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Seung Hoan Choi
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Sean J Jurgens
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Experimental Cardiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Patrick T Ellinor
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Anthony Philippakis
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Melina Claussnitzer
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Kenney Ng
- Center for Computational Health, IBM Research, Cambridge, MA, USA
| | - Miriam S Udler
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Puneet Batra
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Amit V Khera
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
- Verve Therapeutics, Cambridge, MA, USA.
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147
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Chen P, Tan Z, Qiu A, Yin S, Zhou Y, Dong Z, Qiu Y, Xu J, Li K, Dong L, Shek HT, Liu J, Yeung EHK, Gao B, Cheung KMC, To MKT. Patient-reported outcomes in a Chinese cohort of osteogenesis imperfecta unveil psycho-physical stratifications associated with clinical manifestations. Orphanet J Rare Dis 2022; 17:249. [PMID: 35765008 PMCID: PMC9238011 DOI: 10.1186/s13023-022-02394-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 06/11/2022] [Indexed: 11/10/2022] Open
Abstract
Background Osteogenesis imperfecta (OI) is a rare congenital disorder of the skeletal system, inflicting debilitating physical and psychological distress on patients and caregivers. Over the decades, much effort has been channeled towards understanding molecular mechanisms and developing new treatments. It has recently become more apparent that patient-reported outcome measurements (PROM) during treatment, healing and rehabilitation are helpful in facilitating smoother communication, refining intervention strategies and achieving higher quality of life. To date, systematic analyses of PROM in OI patients remain scarce. Results Here, utilizing a PROM Information System, we report a cross-sectional and longitudinal study in a southern Chinese cohort of 90 OI patients, covering both the child and adult age-groups. In the child group where both self and parental surveys were obtained, we identified two clusters of comparable sizes showing different outlooks in physical mobility and emotional experiences. One cluster (Cluster 1) is more negative about themselves than the other (Cluster 2). A concordance of 84.7% between self and parental assessments was recorded, suggesting the stability and validity of PROM-based stratification. Clinical subtyping, deformity, leg length discrepancy, and limited joint mobility were significantly associated with this stratification, with Cluster 1 showing higher percentages of severe phenotypes than Cluster 2. Since OI is a genetic disorder, we performed genetic testing on 72 of the 90 patients, but found no obvious association between genotypes and the PROM stratification. Analyses of longitudinal data suggested that patients tended to stay in the same psychological state, in both clusters. Adult patients also showed a continuous spectrum of self-evaluation that matches their clinical manifestations. Conclusion By systematically analyzing patient-reported outcomes, our study demonstrated the link between the sociopsychological wellbeing of OI patients, and their clinical manifestations, which may serve as the basis for evaluating clinical interventions and help achieve better patient-centric medical practices. The lack of genotype-PROM association may be due to the diverse mutational spectrum in OI, which warrants further investigation when a larger sample size is available. Supplementary Information The online version contains supplementary material available at 10.1186/s13023-022-02394-7.
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Affiliation(s)
- Peikai Chen
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China. .,School of Biomedical Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong.
| | - Zhijia Tan
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China.,Department of Orthopedics and Traumatology, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Anmei Qiu
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China
| | - Shijie Yin
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China
| | - Yapeng Zhou
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China
| | - Zhongxin Dong
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China
| | - Yan Qiu
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China
| | - Jichun Xu
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China
| | - Kangsen Li
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China
| | - Lina Dong
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China
| | - Hiu Tung Shek
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China
| | - Jingwen Liu
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China
| | - Eric H K Yeung
- Department of Physiotherapy, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China
| | - Bo Gao
- School of Biomedical Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Kenneth Man Chee Cheung
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China.,Department of Orthopedics and Traumatology, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Michael Kai-Tsun To
- Department of Orthopedics and Traumatology, The University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, 518053, Guangdong, China. .,Department of Orthopedics and Traumatology, The University of Hong Kong, Pok Fu Lam, Hong Kong.
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148
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Herzig AF, Ciullo M, Leutenegger AL, Perdry H. Moment estimators of relatedness from low-depth whole-genome sequencing data. BMC Bioinformatics 2022; 23:254. [PMID: 35751014 PMCID: PMC9233360 DOI: 10.1186/s12859-022-04795-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 06/09/2022] [Indexed: 11/29/2022] Open
Abstract
Background Estimating relatedness is an important step for many genetic study designs. A variety of methods for estimating coefficients of pairwise relatedness from genotype data have been proposed. Both the kinship coefficient \documentclass[12pt]{minimal}
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\begin{document}$$\varphi$$\end{document}φ and the fraternity coefficient \documentclass[12pt]{minimal}
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\begin{document}$$\psi$$\end{document}ψ for all pairs of individuals are of interest. However, when dealing with low-depth sequencing or imputation data, individual level genotypes cannot be confidently called. To ignore such uncertainty is known to result in biased estimates. Accordingly, methods have recently been developed to estimate kinship from uncertain genotypes. Results We present new method-of-moment estimators of both the coefficients \documentclass[12pt]{minimal}
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\begin{document}$$\varphi$$\end{document}φ and \documentclass[12pt]{minimal}
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\begin{document}$$\psi$$\end{document}ψ calculated directly from genotype likelihoods. We have simulated low-depth genetic data for a sample of individuals with extensive relatedness by using the complex pedigree of the known genetic isolates of Cilento in South Italy. Through this simulation, we explore the behaviour of our estimators, demonstrate their properties, and show advantages over alternative methods. A demonstration of our method is given for a sample of 150 French individuals with down-sampled sequencing data. Conclusions We find that our method can provide accurate relatedness estimates whilst holding advantages over existing methods in terms of robustness, independence from external software, and required computation time. The method presented in this paper is referred to as LowKi (Low-depth Kinship) and has been made available in an R package (https://github.com/genostats/LowKi). Supplementary Information The online version contains supplementary material available at 10.1186/s12859-022-04795-8.
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Affiliation(s)
| | - M Ciullo
- Institute of Genetics and Biophysics A. Buzzati-Traverso - CNR, Naples, Italy.,IRCCS Neuromed, Pozzilli, Isernia, Italy
| | | | - A-L Leutenegger
- Inserm, Université Paris Cité, UMR 1141, NeuroDiderot, 75019, Paris, France
| | - H Perdry
- CESP Inserm U1018, Université Paris-Saclay, UVSQ, Villejuif, France
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149
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Lee S, Hong S, Woo J, Lee JH, Kim K, Kim L, Park K, Jung J. RDscan: A New Method for Improving Germline and Somatic Variant Calling Based on Read Depth Distribution. J Comput Biol 2022; 29:987-1000. [PMID: 35749140 DOI: 10.1089/cmb.2021.0269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Several tools have been developed for calling variants from next-generation sequencing (NGS) data. Although they are generally accurate and reliable, most of them have room for improvement, especially regarding calling variants in datasets with low read depth. In addition, the somatic variants predicted by several somatic variant callers tend to have very low concordance rates. In this study, we developed a new method (RDscan) for improving germline and somatic variant calling in NGS data. RDscan removes misaligned reads, repositions reads, and calculates RDscore based on the read depth distribution. With RDscore, RDscan improves the precision of variant callers by removing false-positive variant calls. When we tested our new tool using the latest variant calling algorithms and data from the 1000 Genomes Project and Illumina's public datasets, accuracy was improved for most of the algorithms. After screening variants with RDscan, calling accuracies increased for germline variants in 11 of 12 cases and for somatic variants in 21 of 24 cases. RDscan is simple to use and can effectively remove false-positive variants while maintaining a low computation load. Therefore, RDscan, along with existing variant callers, should contribute to improvements in genome analysis.
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Affiliation(s)
- Sunho Lee
- Genome Data Integration Centre, Syntekabio, Inc., Daejeon, Republic of Korea.,Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea
| | - Seokchol Hong
- Genome Data Integration Centre, Syntekabio, Inc., Daejeon, Republic of Korea
| | - Jonathan Woo
- Genome Data Integration Centre, Syntekabio, Inc., Daejeon, Republic of Korea
| | - Jae-Hak Lee
- Genome Data Integration Centre, Syntekabio, Inc., Daejeon, Republic of Korea
| | - Kyunghee Kim
- Genome Data Integration Centre, Syntekabio, Inc., Daejeon, Republic of Korea
| | - Lucia Kim
- Department of Pathology, Inha University Hospital, Incheon, Republic of Korea
| | - Kunsoo Park
- Department of Computer Science and Engineering, Seoul National University, Seoul, Republic of Korea
| | - Jongsun Jung
- Genome Data Integration Centre, Syntekabio, Inc., Daejeon, Republic of Korea
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150
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Cai C, Yin Z, Liu A, Wang H, Zeng S, Wang Z, Qiu H, Li S, Zhou J, Wang M. Identifying Rare Genetic Variants of Immune Mediators as Risk Factors for Autism Spectrum Disorder. Genes (Basel) 2022; 13:1098. [PMID: 35741860 PMCID: PMC9223212 DOI: 10.3390/genes13061098] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 06/16/2022] [Accepted: 06/17/2022] [Indexed: 12/30/2022] Open
Abstract
Autism spectrum disorder (ASD) affects more than 1% of children, and there is no viable pharmacotherapeutic agent to treat the core symptoms of ASD. Studies have shown that children with ASD show changes in their levels of immune response molecules. Our previous studies have shown that ASD is more common in children with folate receptor autoantibodies. We also found that children with ASD have abnormal gut immune function, which was characterized by a significant increase in the content of immunoglobulin A and an increase in gut-microbiota-associated epitope diversity. These studies suggest that the immune mechanism plays an important role in the occurrence of ASD. The present study aims to systematically assess gene mutations in immune mediators in patients with ASD. We collected genetic samples from 72 children with ASD (2−12 years old) and 107 healthy controls without ASD (20−78 years old). We used our previously-designed immune gene panel, which can capture cytokine and receptor genes, the coding regions of MHC genes, and genes of innate immunity. Target region sequencing (500×) and bioinformatics analytical methods were used to identify variants in immune response genes associated with patients with ASD. A total of 4 rare variants were found to be associated with ASD, including HLA-B: p.A93G, HLA-DQB1: p.S229N, LILRB2: p.R322H, and LILRB2: c.956-4C>T. These variants were present in 44.44% (32/72) of the ASD patients and were detected in 3.74% (4/107) of the healthy controls. We expect these genetic variants will serve as new targets for the clinical genetic assessment of ASD, and our findings suggest that immune abnormalities in children with ASD may have a genetic basis.
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Affiliation(s)
- Chunquan Cai
- Tianjin Pediatric Research Institute, Tianjin Key Laboratory of Birth Defects for Prevention and Treatment, Tianjin Children’s Hospital (Children’s Hospital of Tianjin University), No. 238 Longyan Road, Beichen District, Tianjin 300134, China;
| | - Zhaoqing Yin
- Division of Neonatology, The People’s Hospital of Dehong Autonomous Prefecture, Mangshi 678400, China;
| | - Aiping Liu
- The Department of Laboratory, Public Health Service Center of Bao’an District, Bao’an District, Shenzhen 518018, China;
| | - Hui Wang
- Xiamen Branch of Children’s Hospital of Fudan University (Xiamen Children’s Hospital), Xiamen 361006, China;
| | - Shujuan Zeng
- Division of Neonatology, Longgang Central Hospital of Shenzhen, Shenzhen 518116, China; (S.Z.); (H.Q.)
| | - Zhangxing Wang
- Division of Neonatology, Shenzhen Longhua People’s Hospital, Shenzhen 518109, China;
| | - Huixian Qiu
- Division of Neonatology, Longgang Central Hospital of Shenzhen, Shenzhen 518116, China; (S.Z.); (H.Q.)
| | - Shijun Li
- Department of Radiology, Chinese People’s Liberation Army General Hospital, Beijing 100853, China
| | - Jiaxiu Zhou
- Division of Psychology, Shenzhen Children’s Hospital, Shenzhen 518038, China
| | - Mingbang Wang
- Microbiome Therapy Center, South China Hospital of Shenzhen University, Shenzhen 518111, China
- Shanghai Key Laboratory of Birth Defects, Division of Neonatology, Children’s Hospital of Fudan University, Shanghai 201102, China
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