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Scarpa A, Pianezza R, Wierzbicki F, Kofler R. Genomes of historical specimens reveal multiple invasions of LTR retrotransposons in Drosophila melanogaster during the 19th century. Proc Natl Acad Sci U S A 2024; 121:e2313866121. [PMID: 38564639 PMCID: PMC11009621 DOI: 10.1073/pnas.2313866121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 01/05/2024] [Indexed: 04/04/2024] Open
Abstract
Transposable element invasions have a profound impact on the evolution of genomes and phenotypes. It is thus an important open question how often such TE invasions occur. To address this question, we utilize the genomes of historical specimens, sampled about 200 y ago. We found that the LTR retrotransposons Blood, Opus, and 412 spread in Drosophila melanogaster in the 19th century. These invasions constitute second waves, as degraded fragments were found for all three TEs. The composition of Opus and 412, but not of Blood, shows a pronounced geographic heterogeneity, likely due to founder effects during the invasions. Finally, we identified species from the Drosophila simulans complex as the likely origin of the TEs. We show that in total, seven TE families invaded D. melanogaster during the last 200y, thereby increasing the genome size by up to 1.2Mbp. We suggest that this high rate of TE invasions was likely triggered by human activity. Based on the analysis of strains and specimens sampled at different times, we provide a detailed timeline of TE invasions, making D. melanogaster the first organism where the invasion history of TEs during the last two centuries could be inferred.
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Affiliation(s)
- Almorò Scarpa
- Institut für Populationsgenetik, Vetmeduni Vienna, Wien1210, Austria
- Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Vienna1210, Austria
| | - Riccardo Pianezza
- Institut für Populationsgenetik, Vetmeduni Vienna, Wien1210, Austria
- Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Vienna1210, Austria
| | - Filip Wierzbicki
- Institut für Populationsgenetik, Vetmeduni Vienna, Wien1210, Austria
- Vienna Graduate School of Population Genetics, Vetmeduni Vienna, Vienna1210, Austria
| | - Robert Kofler
- Institut für Populationsgenetik, Vetmeduni Vienna, Wien1210, Austria
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Yan X, Li J, He L, Chen O, Wang N, Wang S, Wang X, Wang Z, Su R. Accuracy of Genomic prediction for fleece traits in Inner Mongolia Cashmere goats. BMC Genomics 2024; 25:349. [PMID: 38589806 PMCID: PMC11000370 DOI: 10.1186/s12864-024-10249-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 03/22/2024] [Indexed: 04/10/2024] Open
Abstract
The fleece traits are important economic traits of goats. With the reduction of sequencing and genotyping cost and the improvement of related technologies, genomic selection for goats has become possible. The research collect pedigree, phenotype and genotype information of 2299 Inner Mongolia Cashmere goats (IMCGs) individuals. We estimate fixed effects, and compare the estimates of variance components, heritability and genomic predictive ability of fleece traits in IMCGs when using the pedigree based Best Linear Unbiased Prediction (ABLUP), Genomic BLUP (GBLUP) or single-step GBLUP (ssGBLUP). The fleece traits considered are cashmere production (CP), cashmere diameter (CD), cashmere length (CL) and fiber length (FL). It was found that year of production, sex, herd and individual ages had highly significant effects on the four fleece traits (P < 0.01). All of these factors should be considered when the genetic parameters of fleece traits in IMCGs are evaluated. The heritabilities of FL, CL, CP and CD with ABLUP, GBLUP and ssGBLUP methods were 0.26 ~ 0.31, 0.05 ~ 0.08, 0.15 ~ 0.20 and 0.22 ~ 0.28, respectively. Therefore, it can be inferred that the genetic progress of CL is relatively slow. The predictive ability of fleece traits in IMCGs with GBLUP (56.18% to 69.06%) and ssGBLUP methods (66.82% to 73.70%) was significantly higher than that of ABLUP (36.73% to 41.25%). For the ssGBLUP method is significantly (29% ~ 33%) higher than that with ABLUP, and which is slightly (4% ~ 14%) higher than that of GBLUP. The ssGBLUP will be as an superiors method for using genomic selection of fleece traits in Inner Mongolia Cashmere goats.
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Affiliation(s)
- Xiaochun Yan
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region, 010018, China
| | - Jinquan Li
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region, 010018, China
- Inner Mongolia Key Laboratory of Sheep & Goat Genetics Breeding and Reproduction, Hohhot, Inner Mongolia Autonomous Region, 010018, China
- Key Laboratory Of Mutton Sheep & Goat Genetics And Breeding, Ministry of Agriculture And Rural Affairs, Hohhot, Inner Mongolia Autonomous Region, 010018, China
- Engineering Research Centre for Goat Genetics and Breeding, Inner Mongolia Autonomous Region, Hohhot, Inner Mongolia Autonomous Region, 010018, China
| | - Libing He
- Inner Mongolia Jinlai Livestock Technology Co., Ltd, Hohhot, Inner Mongolia Autonomous Region, 010018, China
| | - Oljibilig Chen
- Inner Mongolia Yiwei White Cashmere Goat Co., Ltd, Ordos, Inner Mongolia Autonomous Region, 010018, China
| | - Na Wang
- Inner Mongolia Yiwei White Cashmere Goat Co., Ltd, Ordos, Inner Mongolia Autonomous Region, 010018, China
| | - Shuai Wang
- Inner Mongolia Yiwei White Cashmere Goat Co., Ltd, Ordos, Inner Mongolia Autonomous Region, 010018, China
| | - Xiuyan Wang
- Livestock Improvement Center of Alxa Left Banner, Alxa League, Inner Mongolia Autonomous Region, 75000, China
| | - Zhiying Wang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region, 010018, China.
| | - Rui Su
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia Autonomous Region, 010018, China.
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Du P, Zhu K, Qiao H, Zhang J, Meng H, Huang Z, Yu Y, Xie S, Allen E, Xiong J, Zhang B, Chang X, Ren X, Xu Y, Zhou Q, Han S, Jin L, Wei P, Wang CC, Wen S. Ancient genome of the Chinese Emperor Wu of Northern Zhou. Curr Biol 2024; 34:1587-1595.e5. [PMID: 38552628 DOI: 10.1016/j.cub.2024.02.059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 12/23/2023] [Accepted: 02/23/2024] [Indexed: 04/11/2024]
Abstract
Emperor Wu (, Wudi) of the Xianbei-led Northern Zhou dynasty, named Yuwen Yong (, 543-578 CE), was a highly influential emperor who reformed the system of regional troops, pacified the Turks, and unified the northern part of the country. His genetic profile and physical characteristics, including his appearance and potential diseases, have garnered significant interest from the academic community and the public. In this study, we have successfully generated a 0.343×-coverage genome of Wudi with 1,011,419 single-nucleotide polymorphisms (SNPs) on the 1240k panel. By analyzing pigmentation-relevant SNPs and conducting cranial CT-based facial reconstruction, we have determined that Wudi possessed a typical East or Northeast Asian appearance. Furthermore, pathogenic SNPs suggest Wudi faced an increased susceptibility to certain diseases, such as stroke. Wudi shared the closest genetic relationship with ancient Khitan and Heishui Mohe samples and modern Daur and Mongolian populations but also showed additional affinity with Yellow River (YR) farmers. We estimated that Wudi derived 61% of his ancestry from ancient Northeast Asians (ANAs) and nearly one-third from YR farmer-related groups. This can likely be attributed to continuous intermarriage between Xianbei royal families, and local Han aristocrats.1,2 Furthermore, our study has revealed genetic diversities among available ancient Xianbei individuals from different regions, suggesting that the formation of the Xianbei was a dynamic process influenced by admixture with surrounding populations.
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Affiliation(s)
- Panxin Du
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China; State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, and Human Phenome Institute, Fudan University, Shanghai 200433, China; Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Kongyang Zhu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen 361102, China
| | - Hui Qiao
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, and Human Phenome Institute, Fudan University, Shanghai 200433, China; Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200433, China
| | | | - Hailiang Meng
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Zixiao Huang
- Department of History, Fudan University, Shanghai 200433, China
| | - Yao Yu
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China
| | - Shouhua Xie
- Department of History, Fudan University, Shanghai 200433, China
| | - Edward Allen
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China
| | - Jianxue Xiong
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China
| | - Baoshuai Zhang
- USTC Archaeometry Laboratory, University of Science and Technology of China, Hefei 230026, China
| | - Xin Chang
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China
| | - Xiaoying Ren
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China
| | - Yiran Xu
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China
| | - Qi Zhou
- Shanghai Federation of Social Science Associations, Shanghai 200020, China
| | - Sheng Han
- Department of History, Fudan University, Shanghai 200433, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, and Human Phenome Institute, Fudan University, Shanghai 200433, China.
| | - Pianpian Wei
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China.
| | - Chuan-Chao Wang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen 361102, China; Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen 361005, China; State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen 361102, China; Institute of Artificial Intelligence, Xiamen University, Xiamen 361005, China.
| | - Shaoqing Wen
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China; Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200433, China; MOE Laboratory for National Development and Intelligent Governance, Fudan University, Shanghai 200433, China; Center for the Belt and Road Archaeology and Ancient Civilizations, Shanghai 200433, China.
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Chen L, Yu XY, Zhang F, Zhang HM, Guo LX, Ren L, Hong XY, Sun JT. A chromosome-level genome assembly of the spider mite Tetranychus piercei McGregor. Sci Data 2024; 11:340. [PMID: 38580722 PMCID: PMC10997676 DOI: 10.1038/s41597-024-03189-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 03/25/2024] [Indexed: 04/07/2024] Open
Abstract
Despite the rapid advances in sequencing technology, limited genomic resources are currently available for phytophagous spider mites, which include many important agricultural pests. One of these pests is Tetranychus piercei (McGregor), a serious banana pest in East Asia exhibiting remarkable tolerance to high temperature. In this study, we assembled a high-quality genome of T. piercei using a combination of PacBio long reads and Illumina short reads sequencing. With the assistance of chromatin conformation capture technology, 99.9% of the contigs were anchored into three pseudochromosomes with a total size of 86.02 Mb. Repetitive elements, accounting for 14.16% of this genome (12.20 Mb), are predominantly composed of long-terminal repeats (30.7%). By combining evidence of ab initio prediction, transcripts, and homologous proteins, we annotated 11,881 protein-coding genes. Both the genome and proteins have high BUSCO completeness scores (>94%). This high-quality genome, along with reliable annotation, provides a valuable resource for investigating the high-temperature tolerance of this species and exploring the genomic basis that underlies the host range evolution of spider mites.
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Affiliation(s)
- Lei Chen
- Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Xin-Yue Yu
- Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Feng Zhang
- Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Hua-Meng Zhang
- Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Li-Xue Guo
- Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Lu Ren
- Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Xiao-Yue Hong
- Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China
| | - Jing-Tao Sun
- Department of Entomology, Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China.
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Toriyama K, Au Yeung WK, Inoue A, Kurimoto K, Yabuta Y, Saitou M, Nakamura T, Nakano T, Sasaki H. DPPA3 facilitates genome-wide DNA demethylation in mouse primordial germ cells. BMC Genomics 2024; 25:344. [PMID: 38580899 PMCID: PMC10996186 DOI: 10.1186/s12864-024-10192-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 03/05/2024] [Indexed: 04/07/2024] Open
Abstract
BACKGROUND Genome-wide DNA demethylation occurs in mammalian primordial germ cells (PGCs) as part of the epigenetic reprogramming important for gametogenesis and resetting the epigenetic information for totipotency. Dppa3 (also known as Stella or Pgc7) is highly expressed in mouse PGCs and oocytes and encodes a factor essential for female fertility. It prevents excessive DNA methylation in oocytes and ensures proper gene expression in preimplantation embryos: however, its role in PGCs is largely unexplored. In the present study, we investigated whether or not DPPA3 has an impact on CG methylation/demethylation in mouse PGCs. RESULTS We show that DPPA3 plays a role in genome-wide demethylation in PGCs even before sex differentiation. Dppa3 knockout female PGCs show aberrant hypermethylation, most predominantly at H3K9me3-marked retrotransposons, which persists up to the fully-grown oocyte stage. DPPA3 works downstream of PRDM14, a master regulator of epigenetic reprogramming in embryonic stem cells and PGCs, and independently of TET1, an enzyme that hydroxylates 5-methylcytosine. CONCLUSIONS The results suggest that DPPA3 facilitates DNA demethylation through a replication-coupled passive mechanism in PGCs. Our study identifies DPPA3 as a novel epigenetic reprogramming factor in mouse PGCs.
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Affiliation(s)
- Keisuke Toriyama
- Division of Epigenomics and Development, Medical Institute of Bioregulation, Kyushu University, Fukuoka, 812-8582, Japan
| | - Wan Kin Au Yeung
- Division of Epigenomics and Development, Medical Institute of Bioregulation, Kyushu University, Fukuoka, 812-8582, Japan.
| | - Azusa Inoue
- Laboratory for Epigenome Inheritance, Riken Center for Integrative Medical Sciences, Kanagawa, 230-0045, Japan
- Tokyo Metropolitan University, Tokyo, 192-0397, Japan
| | - Kazuki Kurimoto
- Department of Embryology, School of Medicine, Nara Medical University, 840 Shijo-Cho, Kashihara, Nara, 634-8521, Japan
| | - Yukihiro Yabuta
- Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Yoshida-Konoe- cho, Sakyo-ku, Kyoto, 606-8501, Japan
- Department of Anatomy and Cell Biology, Graduate School of Medicine, Kyoto University, Yoshida-Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Mitinori Saitou
- Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Yoshida-Konoe- cho, Sakyo-ku, Kyoto, 606-8501, Japan
- Department of Anatomy and Cell Biology, Graduate School of Medicine, Kyoto University, Yoshida-Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan
- Center for iPS Cell Research and Application (CiRA), Kyoto University, 53 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Toshinobu Nakamura
- Laboratory for Epigenetic Regulation, Department of Animal Bio-Science, Nagahama Institute of Bio-Science and Technology, Shiga, 526-0829, Japan
| | - Toru Nakano
- Graduate School of Frontier Biosciences, Osaka University, Osaka, 565-0871, Japan
| | - Hiroyuki Sasaki
- Division of Epigenomics and Development, Medical Institute of Bioregulation, Kyushu University, Fukuoka, 812-8582, Japan.
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Jiang H, Chai ZX, Chen XY, Zhang CF, Zhu Y, Ji QM, Xin JW. Yak genome database: a multi-omics analysis platform. BMC Genomics 2024; 25:346. [PMID: 38580907 PMCID: PMC10998334 DOI: 10.1186/s12864-024-10274-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 03/31/2024] [Indexed: 04/07/2024] Open
Abstract
BACKGROUND The yak (Bos grunniens) is a large ruminant species that lives in high-altitude regions and exhibits excellent adaptation to the plateau environments. To further understand the genetic characteristics and adaptive mechanisms of yak, we have developed a multi-omics database of yak including genome, transcriptome, proteome, and DNA methylation data. DESCRIPTION The Yak Genome Database ( http://yakgenomics.com/ ) integrates the research results of genome, transcriptome, proteome, and DNA methylation, and provides an integrated platform for researchers to share and exchange omics data. The database contains 26,518 genes, 62 transcriptomes, 144,309 proteome spectra, and 22,478 methylation sites of yak. The genome module provides access to yak genome sequences, gene annotations and variant information. The transcriptome module offers transcriptome data from various tissues of yak and cattle strains at different developmental stages. The proteome module presents protein profiles from diverse yak organs. Additionally, the DNA methylation module shows the DNA methylation information at each base of the whole genome. Functions of data downloading and browsing, functional gene exploration, and experimental practice were available for the database. CONCLUSION This comprehensive database provides a valuable resource for further investigations on development, molecular mechanisms underlying high-altitude adaptation, and molecular breeding of yak.
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Affiliation(s)
- Hui Jiang
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, 850000, Lhasa, Tibet, China
- Institute of Animal Science and Veterinary, Tibet Academy of Agricultural and Animal Husbandry Sciences, 850000, Lhasa, Tibet, China
| | - Zhi-Xin Chai
- Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Southwest Minzu University, 610041, Chengdu, Sichuan, China
| | - Xiao-Ying Chen
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, 850000, Lhasa, Tibet, China
- Institute of Animal Science and Veterinary, Tibet Academy of Agricultural and Animal Husbandry Sciences, 850000, Lhasa, Tibet, China
| | - Cheng-Fu Zhang
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, 850000, Lhasa, Tibet, China
- Institute of Animal Science and Veterinary, Tibet Academy of Agricultural and Animal Husbandry Sciences, 850000, Lhasa, Tibet, China
| | - Yong Zhu
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, 850000, Lhasa, Tibet, China
- Institute of Animal Science and Veterinary, Tibet Academy of Agricultural and Animal Husbandry Sciences, 850000, Lhasa, Tibet, China
| | - Qiu-Mei Ji
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, 850000, Lhasa, Tibet, China.
- Institute of Animal Science and Veterinary, Tibet Academy of Agricultural and Animal Husbandry Sciences, 850000, Lhasa, Tibet, China.
| | - Jin-Wei Xin
- State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement, 850000, Lhasa, Tibet, China.
- Institute of Animal Science and Veterinary, Tibet Academy of Agricultural and Animal Husbandry Sciences, 850000, Lhasa, Tibet, China.
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Ding W, Li X, Zhang J, Ji M, Zhang M, Zhong X, Cao Y, Liu X, Li C, Xiao C, Wang J, Li T, Yu Q, Mo F, Zhang B, Qi J, Yang JC, Qi J, Tian L, Xu X, Peng Q, Zhou WZ, Liu Z, Fu A, Zhang X, Zhang JJ, Sun Y, Hu B, An NA, Zhang L, Li CY. Adaptive functions of structural variants in human brain development. Sci Adv 2024; 10:eadl4600. [PMID: 38579006 DOI: 10.1126/sciadv.adl4600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 03/01/2024] [Indexed: 04/07/2024]
Abstract
Quantifying the structural variants (SVs) in nonhuman primates could provide a niche to clarify the genetic backgrounds underlying human-specific traits, but such resource is largely lacking. Here, we report an accurate SV map in a population of 562 rhesus macaques, verified by in-house benchmarks of eight macaque genomes with long-read sequencing and another one with genome assembly. This map indicates stronger selective constrains on inversions at regulatory regions, suggesting a strategy for prioritizing them with the most important functions. Accordingly, we identified 75 human-specific inversions and prioritized them. The top-ranked inversions have substantially shaped the human transcriptome, through their dual effects of reconfiguring the ancestral genomic architecture and introducing regional mutation hotspots at the inverted regions. As a proof of concept, we linked APCDD1, located on one of these inversions and down-regulated specifically in humans, to neuronal maturation and cognitive ability. We thus highlight inversions in shaping the human uniqueness in brain development.
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Affiliation(s)
- Wanqiu Ding
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Xiangshang Li
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Jie Zhang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Mingjun Ji
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Mengling Zhang
- State Key Laboratory of Membrane Biology, Biomedical Pioneer Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
| | - Xiaoming Zhong
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
- Center of Excellence for Leukemia Studies, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Yong Cao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, 119S Fourth Ring Rd W, Fengtai District, Beijing, China
| | - Xiaoge Liu
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Chunqiong Li
- Chinese Institute for Brain Research, Beijing, China
| | - Chunfu Xiao
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Jiaxin Wang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Ting Li
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Qing Yu
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Fan Mo
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Boya Zhang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Jianhuan Qi
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Jie-Chun Yang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Juntian Qi
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Lu Tian
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Xinwei Xu
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Qi Peng
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Wei-Zhen Zhou
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhijin Liu
- College of Life Sciences, Capital Normal University, Beijing, China
| | - Aisi Fu
- Wuhan Dgensee Clinical Laboratory, Wuhan, China
| | - Xiuqin Zhang
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
| | - Jian-Jun Zhang
- Shanxi Key Laboratory of Chinese Medicine Encephalopathy, National International Joint Research Center for Molecular Chinese Medicine, Shanxi University of Chinese Medicine, Jinzhong, China
| | - Yujie Sun
- State Key Laboratory of Membrane Biology, Biomedical Pioneer Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
| | - Baoyang Hu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Stem Cell and Regeneration, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Ni A An
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China
| | - Li Zhang
- Chinese Institute for Brain Research, Beijing, China
| | - Chuan-Yun Li
- State Key Laboratory of Protein and Plant Gene Research, Laboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
- National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China
- Southwest United Graduate School, Kunming 650092, China
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Brault C, Segura V, Roques M, Lamblin P, Bouckenooghe V, Pouzalgues N, Cunty C, Breil M, Frouin M, Garcin L, Camps L, Ducasse MA, Romieu C, Masson G, Julliard S, Flutre T, Le Cunff L. Enhancing grapevine breeding efficiency through genomic prediction and selection index. G3 (Bethesda) 2024; 14:jkae038. [PMID: 38401528 PMCID: PMC10989862 DOI: 10.1093/g3journal/jkae038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 02/09/2024] [Accepted: 02/18/2024] [Indexed: 02/26/2024]
Abstract
Grapevine (Vitis vinifera) breeding reaches a critical point. New cultivars are released every year with resistance to powdery and downy mildews. However, the traditional process remains time-consuming, taking 20-25 years, and demands the evaluation of new traits to enhance grapevine adaptation to climate change. Until now, the selection process has relied on phenotypic data and a limited number of molecular markers for simple genetic traits such as resistance to pathogens, without a clearly defined ideotype, and was carried out on a large scale. To accelerate the breeding process and address these challenges, we investigated the use of genomic prediction, a methodology using molecular markers to predict genotypic values. In our study, we focused on 2 existing grapevine breeding programs: Rosé wine and Cognac production. In these programs, several families were created through crosses of emblematic and interspecific resistant varieties to powdery and downy mildews. Thirty traits were evaluated for each program, using 2 genomic prediction methods: Genomic Best Linear Unbiased Predictor and Least Absolute Shrinkage Selection Operator. The results revealed substantial variability in predictive abilities across traits, ranging from 0 to 0.9. These discrepancies could be attributed to factors such as trait heritability and trait characteristics. Moreover, we explored the potential of across-population genomic prediction by leveraging other grapevine populations as training sets. Integrating genomic prediction allowed us to identify superior individuals for each program, using multivariate selection index method. The ideotype for each breeding program was defined collaboratively with representatives from the wine-growing sector.
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Affiliation(s)
- Charlotte Brault
- UMT Geno-Vigne®, IFV, INRAE, Institut Agro Montpellier, Montpellier 34398, France
- Institut Français de la vigne et du vin, Pôle National Matériel Végétal, Le Grau du Roi 30240, France
| | - Vincent Segura
- UMT Geno-Vigne®, IFV, INRAE, Institut Agro Montpellier, Montpellier 34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro Montpellier, Montpellier 34398, France
| | - Maryline Roques
- UMT Geno-Vigne®, IFV, INRAE, Institut Agro Montpellier, Montpellier 34398, France
- Institut Français de la vigne et du vin, Pôle National Matériel Végétal, Le Grau du Roi 30240, France
| | - Pauline Lamblin
- Institut Français de la vigne et du vin, Pôle National Matériel Végétal, Le Grau du Roi 30240, France
| | - Virginie Bouckenooghe
- UMT Geno-Vigne®, IFV, INRAE, Institut Agro Montpellier, Montpellier 34398, France
- Institut Français de la vigne et du vin, Pôle National Matériel Végétal, Le Grau du Roi 30240, France
| | | | - Constance Cunty
- Institut Français de la vigne et du vin, Pôle National Matériel Végétal, Le Grau du Roi 30240, France
- Centre du Rosé, Vidauban 83550, France
| | - Matthieu Breil
- UMT Geno-Vigne®, IFV, INRAE, Institut Agro Montpellier, Montpellier 34398, France
- Institut Français de la vigne et du vin, Pôle National Matériel Végétal, Le Grau du Roi 30240, France
| | - Marina Frouin
- Conservatoire du Vignoble Charentais, Institut de Formation de Richemont, Cherves-Richemont 16370, France
| | - Léa Garcin
- Institut Français de la vigne et du vin, Pôle National Matériel Végétal, Le Grau du Roi 30240, France
- Conservatoire du Vignoble Charentais, Institut de Formation de Richemont, Cherves-Richemont 16370, France
| | - Louise Camps
- Conservatoire du Vignoble Charentais, Institut de Formation de Richemont, Cherves-Richemont 16370, France
| | - Marie-Agnès Ducasse
- Institut Français de la vigne et du vin, Pôle National Matériel Végétal, Le Grau du Roi 30240, France
| | - Charles Romieu
- UMT Geno-Vigne®, IFV, INRAE, Institut Agro Montpellier, Montpellier 34398, France
- UMR AGAP Institut, Univ Montpellier, CIRAD, INRAE, Institut Agro Montpellier, Montpellier 34398, France
| | - Gilles Masson
- Institut Français de la vigne et du vin, Pôle National Matériel Végétal, Le Grau du Roi 30240, France
- Centre du Rosé, Vidauban 83550, France
| | - Sébastien Julliard
- Conservatoire du Vignoble Charentais, Institut de Formation de Richemont, Cherves-Richemont 16370, France
| | - Timothée Flutre
- INRAE, CNRS, AgroParisTech, Université Paris-Saclay, GQE—Le Moulon, Gif-sur-Yvette 91190, France
| | - Loïc Le Cunff
- UMT Geno-Vigne®, IFV, INRAE, Institut Agro Montpellier, Montpellier 34398, France
- Institut Français de la vigne et du vin, Pôle National Matériel Végétal, Le Grau du Roi 30240, France
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Tumas H, Ilska JJ, Gérardi S, Laroche J, A’Hara S, Boyle B, Janes M, McLean P, Lopez G, Lee SJ, Cottrell J, Gorjanc G, Bousquet J, Woolliams JA, MacKay JJ. High-density genetic linkage mapping in Sitka spruce advances the integration of genomic resources in conifers. G3 (Bethesda) 2024; 14:jkae020. [PMID: 38366548 PMCID: PMC10989875 DOI: 10.1093/g3journal/jkae020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 01/03/2024] [Indexed: 02/18/2024]
Abstract
In species with large and complex genomes such as conifers, dense linkage maps are a useful resource for supporting genome assembly and laying the genomic groundwork at the structural, populational, and functional levels. However, most of the 600+ extant conifer species still lack extensive genotyping resources, which hampers the development of high-density linkage maps. In this study, we developed a linkage map relying on 21,570 single nucleotide polymorphism (SNP) markers in Sitka spruce (Picea sitchensis [Bong.] Carr.), a long-lived conifer from western North America that is widely planted for productive forestry in the British Isles. We used a single-step mapping approach to efficiently combine RAD-seq and genotyping array SNP data for 528 individuals from 2 full-sib families. As expected for spruce taxa, the saturated map contained 12 linkages groups with a total length of 2,142 cM. The positioning of 5,414 unique gene coding sequences allowed us to compare our map with that of other Pinaceae species, which provided evidence for high levels of synteny and gene order conservation in this family. We then developed an integrated map for P. sitchensis and Picea glauca based on 27,052 markers and 11,609 gene sequences. Altogether, these 2 linkage maps, the accompanying catalog of 286,159 SNPs and the genotyping chip developed, herein, open new perspectives for a variety of fundamental and more applied research objectives, such as for the improvement of spruce genome assemblies, or for marker-assisted sustainable management of genetic resources in Sitka spruce and related species.
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Affiliation(s)
- Hayley Tumas
- Department of Biology, University of Oxford, Oxford OX1 3RB, UK
| | - Joana J Ilska
- The Roslin Institute, Royal (Dick) School of Veterinary Science, University of Edinburgh, Midlothian EH25 9RG, UK
| | - Sebastien Gérardi
- Canada Research Chair in Forest Genomics, Forest Research Centre, Université Laval, Québec, QC GIV 0A6, Canada
- Institute for Systems and Integrative Biology, Université Laval, Québec, QC GIV 0A6, Canada
| | - Jerome Laroche
- Institute for Systems and Integrative Biology, Université Laval, Québec, QC GIV 0A6, Canada
| | - Stuart A’Hara
- Forest Research, Northern Research Station, Midlothian EH25 9SY, UK
| | - Brian Boyle
- Institute for Systems and Integrative Biology, Université Laval, Québec, QC GIV 0A6, Canada
| | - Mateja Janes
- The Roslin Institute, Royal (Dick) School of Veterinary Science, University of Edinburgh, Midlothian EH25 9RG, UK
| | - Paul McLean
- Forest Research, Northern Research Station, Midlothian EH25 9SY, UK
| | - Gustavo Lopez
- Forest Research, Northern Research Station, Midlothian EH25 9SY, UK
| | - Steve J Lee
- Forest Research, Northern Research Station, Midlothian EH25 9SY, UK
| | - Joan Cottrell
- Forest Research, Northern Research Station, Midlothian EH25 9SY, UK
| | - Gregor Gorjanc
- The Roslin Institute, Royal (Dick) School of Veterinary Science, University of Edinburgh, Midlothian EH25 9RG, UK
| | - Jean Bousquet
- Canada Research Chair in Forest Genomics, Forest Research Centre, Université Laval, Québec, QC GIV 0A6, Canada
- Institute for Systems and Integrative Biology, Université Laval, Québec, QC GIV 0A6, Canada
| | - John A Woolliams
- The Roslin Institute, Royal (Dick) School of Veterinary Science, University of Edinburgh, Midlothian EH25 9RG, UK
| | - John J MacKay
- Department of Biology, University of Oxford, Oxford OX1 3RB, UK
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60
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Fang Y, Wu D, Gao N, Lv M, Zhou M, Ma C, Sun Y, Cui B. Whole- genome sequencing and comparative genomic analyses of the medicinal fungus Sanguinoderma infundibulare in Ganodermataceae. G3 (Bethesda) 2024; 14:jkae005. [PMID: 38366555 PMCID: PMC10989896 DOI: 10.1093/g3journal/jkae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 01/05/2024] [Indexed: 02/18/2024]
Abstract
Sanguinoderma infundibulare is a newly discovered species of Ganodermataceae known to have high medicinal and ecological values. In this study, the whole-genome sequencing and comparative genomic analyses were conducted to further understand Ganodermataceae's genomic structural and functional characteristics. Using the Illumina NovaSeq and PacBio Sequel platforms, 88 scaffolds were assembled to obtain a 48.99-Mb high-quality genome of S. infundibulare. A total of 14,146 protein-coding genes were annotated in the whole genome, with 98.6% of complete benchmarking universal single-copy orthologs (BUSCO) scores. Comparative genomic analyses were conducted among S. infundibulare, Sanguinoderma rugosum, Ganoderma lucidum, and Ganoderma sinense to determine their intergeneric differences. The 4 species were found to share 4,011 orthogroups, and 24 specific gene families were detected in the genus Sanguinoderma. The gene families associated with carbohydrate esterase in S. infundibulare were significantly abundant, which was reported to be involved in hemicellulose degradation. One specific gene family in Sanguinoderma was annotated with siroheme synthase, which may be related to the typical characteristics of fresh pore surface changing to blood red when bruised. This study enriched the available genome data for the genus Sanguinoderma, elucidated the differences between Ganoderma and Sanguinoderma, and provided insights into the characteristics of the genome structure and function of S. infundibulare.
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Affiliation(s)
- Yuxuan Fang
- State Key Laboratory of Efficient Production of Forest Resources, School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China
| | - Dongmei Wu
- Xinjiang Production and Construction Group Key Laboratory of Crop Germplasm Enhancement and Gene Resources Utilization, Biotechnology Research Institute, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi 832061, China
| | - Neng Gao
- Xinjiang Production and Construction Group Key Laboratory of Crop Germplasm Enhancement and Gene Resources Utilization, Biotechnology Research Institute, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi 832061, China
| | - Mengxue Lv
- State Key Laboratory of Efficient Production of Forest Resources, School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China
| | - Miao Zhou
- State Key Laboratory of Efficient Production of Forest Resources, School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China
| | - Chuangui Ma
- Beijing Jingcheng Biotechnology Co., Ltd, Beijing 100083, China
| | - Yifei Sun
- State Key Laboratory of Efficient Production of Forest Resources, School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China
| | - Baokai Cui
- State Key Laboratory of Efficient Production of Forest Resources, School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China
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61
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Murga-Moreno J, Casillas S, Barbadilla A, Uricchio L, Enard D. An efficient and robust ABC approach to infer the rate and strength of adaptation. G3 (Bethesda) 2024; 14:jkae031. [PMID: 38365205 DOI: 10.1093/g3journal/jkae031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 10/10/2023] [Accepted: 01/29/2024] [Indexed: 02/18/2024]
Abstract
Inferring the effects of positive selection on genomes remains a critical step in characterizing the ultimate and proximate causes of adaptation across species, and quantifying positive selection remains a challenge due to the confounding effects of many other evolutionary processes. Robust and efficient approaches for adaptation inference could help characterize the rate and strength of adaptation in nonmodel species for which demographic history, mutational processes, and recombination patterns are not currently well-described. Here, we introduce an efficient and user-friendly extension of the McDonald-Kreitman test (ABC-MK) for quantifying long-term protein adaptation in specific lineages of interest. We characterize the performance of our approach with forward simulations and find that it is robust to many demographic perturbations and positive selection configurations, demonstrating its suitability for applications to nonmodel genomes. We apply ABC-MK to the human proteome and a set of known virus interacting proteins (VIPs) to test the long-term adaptation in genes interacting with viruses. We find substantially stronger signatures of positive selection on RNA-VIPs than DNA-VIPs, suggesting that RNA viruses may be an important driver of human adaptation over deep evolutionary time scales.
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Affiliation(s)
- Jesús Murga-Moreno
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85719, USA
| | - Sònia Casillas
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | - Antonio Barbadilla
- Department of Genetics and Microbiology, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
- Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Bellaterra, Barcelona 08193, Spain
| | | | - David Enard
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85719, USA
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62
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Bhattarai UR, Poulin R, Gemmell NJ, Dowle E. Genome assembly and annotation of the mermithid nematode Mermis nigrescens. G3 (Bethesda) 2024; 14:jkae023. [PMID: 38301266 PMCID: PMC10989877 DOI: 10.1093/g3journal/jkae023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 01/21/2024] [Accepted: 01/22/2024] [Indexed: 02/03/2024]
Abstract
Genetic studies of nematodes have been dominated by Caenorhabditis elegans as a model species. A lack of genomic resources has limited the expansion of genetic research to other groups of nematodes. Here, we report a draft genome assembly of a mermithid nematode, Mermis nigrescens. Mermithidae are insect parasitic nematodes with hosts including a wide range of terrestrial arthropods. We sequenced, assembled, and annotated the whole genome of M. nigrescens using nanopore long reads and 10X Chromium link reads. The assembly is 524 Mb in size consisting of 867 scaffolds. The N50 value is 2.42 Mb, and half of the assembly is in the 30 longest scaffolds. The assembly BUSCO score from the eukaryotic database (eukaryota_odb10) indicates that the genome is 86.7% complete and 5.1% partial. The genome has a high level of heterozygosity (6.6%) with a repeat content of 83.98%. mRNA-seq reads from different sized nematodes (≤2 cm, 3.5-7 cm, and >7 cm body length) representing different developmental stages were also generated and used for the genome annotation. Using ab initio and evidence-based gene model predictions, 12,313 protein-coding genes and 24,186 mRNAs were annotated. These genomic resources will help researchers investigate the various aspects of the biology and host-parasite interactions of mermithid nematodes.
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Affiliation(s)
- Upendra R Bhattarai
- Department of Anatomy, University of Otago, Dunedin 9016, New Zealand
- Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Robert Poulin
- Department of Zoology, University of Otago, Dunedin 9016, New Zealand
| | - Neil J Gemmell
- Department of Anatomy, University of Otago, Dunedin 9016, New Zealand
| | - Eddy Dowle
- Department of Anatomy, University of Otago, Dunedin 9016, New Zealand
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Armstrong EE, Bissell KL, Fatima HS, Heikkinen MA, Jessup A, Junaid MO, Lee DH, Lieb EC, Liem JT, Martin EM, Moreno M, Otgonbayar K, Romans BW, Royar K, Adler MB, Needle DB, Harkess A, Kelley JL, Mooney JA, Mychajliw AM. Chromosome-level assembly of the gray fox (Urocyon cinereoargenteus) confirms the basal loss of PRDM9 in Canidae. G3 (Bethesda) 2024; 14:jkae034. [PMID: 38366575 PMCID: PMC10989890 DOI: 10.1093/g3journal/jkae034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/31/2024] [Accepted: 02/02/2024] [Indexed: 02/18/2024]
Abstract
Reference genome assemblies have been created from multiple lineages within the Canidae family; however, despite its phylogenetic relevance as a basal genus within the clade, there is currently no reference genome for the gray fox (Urocyon cinereoargenteus). Here, we present a chromosome-level assembly for the gray fox (U. cinereoargenteus), which represents the most contiguous, non-domestic canid reference genome available to date, with 90% of the genome contained in just 34 scaffolds and a contig N50 and scaffold N50 of 59.4 and 72.9 Megabases, respectively. Repeat analyses identified an increased number of simple repeats relative to other canids. Based on mitochondrial DNA, our Vermont sample clusters with other gray fox samples from the northeastern United States and contains slightly lower levels of heterozygosity than gray foxes on the west coast of California. This new assembly lays the groundwork for future studies to describe past and present population dynamics, including the delineation of evolutionarily significant units of management relevance. Importantly, the phylogenetic position of Urocyon allows us to verify the loss of PRDM9 functionality in the basal canid lineage, confirming that pseudogenization occurred at least 10 million years ago.
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Affiliation(s)
- Ellie E Armstrong
- School of Biological Sciences, Washington State University, Pullman, WA 99164, USA
| | - Ky L Bissell
- Department of Biology, Middlebury College, Middlebury, VT 05753, USA
| | - H Sophia Fatima
- Department of Biology, Middlebury College, Middlebury, VT 05753, USA
| | - Maya A Heikkinen
- Department of Biology, Middlebury College, Middlebury, VT 05753, USA
| | - Anika Jessup
- Department of Biology, Middlebury College, Middlebury, VT 05753, USA
| | - Maryam O Junaid
- Department of Biology, Middlebury College, Middlebury, VT 05753, USA
| | - Dong H Lee
- Department of Biology, Middlebury College, Middlebury, VT 05753, USA
| | - Emily C Lieb
- Department of Biology, Middlebury College, Middlebury, VT 05753, USA
| | - Josef T Liem
- Department of Biology, Middlebury College, Middlebury, VT 05753, USA
| | - Estelle M Martin
- Department of Biology, Middlebury College, Middlebury, VT 05753, USA
| | - Mauricio Moreno
- Department of Biology, Middlebury College, Middlebury, VT 05753, USA
| | | | - Betsy W Romans
- Department of Biology, Middlebury College, Middlebury, VT 05753, USA
| | - Kim Royar
- Vermont Department of Fish and Wildlife, Montpelier, VT 05620, USA
| | - Mary Beth Adler
- Vermont Department of Fish and Wildlife, Montpelier, VT 05620, USA
| | - David B Needle
- Department of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, NH 03824, USA
| | - Alex Harkess
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Joanna L Kelley
- School of Biological Sciences, Washington State University, Pullman, WA 99164, USA
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Jazlyn A Mooney
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90007, USA
| | - Alexis M Mychajliw
- Department of Biology, Middlebury College, Middlebury, VT 05753, USA
- Program in Environmental Studies, Middlebury College, Middlebury, VT 05753, USA
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64
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Duchêne DA, Duchêne S, Stiller J, Heller R, Ho SYW. ClockstaRX: Testing Molecular Clock Hypotheses With Genomic Data. Genome Biol Evol 2024; 16:evae064. [PMID: 38526019 PMCID: PMC10999959 DOI: 10.1093/gbe/evae064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 01/11/2024] [Accepted: 03/21/2024] [Indexed: 03/26/2024] Open
Abstract
Phylogenomic data provide valuable opportunities for studying evolutionary rates and timescales. These analyses require theoretical and statistical tools based on molecular clocks. We present ClockstaRX, a flexible platform for exploring and testing evolutionary rate signals in phylogenomic data. Here, information about evolutionary rates in branches across gene trees is placed in Euclidean space, allowing data transformation, visualization, and hypothesis testing. ClockstaRX implements formal tests for identifying groups of loci and branches that make a large contribution to patterns of rate variation. This information can then be used to test for drivers of genomic evolutionary rates or to inform models for molecular dating. Drawing on the results of a simulation study, we recommend forms of data exploration and filtering that might be useful prior to molecular-clock analyses.
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Affiliation(s)
- David A Duchêne
- Center for Evolutionary Hologenomics, University of Copenhagen, Copenhagen 1352, Denmark
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen 1352, Denmark
| | - Sebastián Duchêne
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3010, Australia
| | - Josefin Stiller
- Villum Centre for Biodiversity Genomics, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Rasmus Heller
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen 2100, Denmark
| | - Simon Y W Ho
- School of Life and Environmental Sciences, University of Sydney, Sydney, NSW 2006, Australia
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65
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Du H, Liu Z, Lu SY, Jiang L, Zhou L, Liu JF. Genomic evidence for human-mediated introgressive hybridization and selection in the developed breed. BMC Genomics 2024; 25:331. [PMID: 38565992 PMCID: PMC10986048 DOI: 10.1186/s12864-024-10259-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 03/26/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND The pig (Sus Scrofa) is one of the oldest domesticated livestock species that has undergone extensive improvement through modern breeding. European breeds have advantages in lean meat development and highly-productive body type, whereas Asian breeds possess extraordinary fat deposition and reproductive performance. Consequently, Eurasian breeds have been extensively used to develop modern commercial breeds for fast-growing and high prolificacy. However, limited by the sequencing technology, the genome architecture of some nascent developed breeds and the human-mediated impact on their genomes are still unknown. RESULTS Through whole-genome analysis of 178 individuals from an Asian locally developed pig breed, Beijing Black pig, and its two ancestors from two different continents, we found the pervasive inconsistent gene trees and species trees across the genome of Beijing Black pig, which suggests its introgressive hybrid origin. Interestingly, we discovered that this developed breed has more genetic relationships with European pigs and an unexpected introgression from Asian pigs to this breed, which indicated that human-mediated introgression could form the porcine genome architecture in a completely different type compared to native introgression. We identified 554 genomic regions occupied 63.30 Mb with signals of introgression from the Asian ancestry to Beijing Black pig, and the genes in these regions enriched in pathways associated with meat quality, fertility, and disease-resistant. Additionally, a proportion of 7.77% of genomic regions were recognized as regions that have been under selection. Moreover, combined with the results of a genome-wide association study for meat quality traits in the 1537 Beijing Black pig population, two important candidate genes related to meat quality traits were identified. DNAJC6 is related to intramuscular fat content and fat deposition, and RUFY4 is related to meat pH and tenderness. CONCLUSIONS Our research provides insight for analyzing the origins of nascent developed breeds and genome-wide selection remaining in the developed breeds mediated by humans during modern breeding.
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Affiliation(s)
- Heng Du
- State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University (West District), No.2 Yuanmingyuan West Road, 100193, Beijing, China
| | - Zhen Liu
- State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University (West District), No.2 Yuanmingyuan West Road, 100193, Beijing, China
| | - Shi-Yu Lu
- State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University (West District), No.2 Yuanmingyuan West Road, 100193, Beijing, China
| | - Li Jiang
- State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University (West District), No.2 Yuanmingyuan West Road, 100193, Beijing, China
| | - Lei Zhou
- State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University (West District), No.2 Yuanmingyuan West Road, 100193, Beijing, China.
| | - Jian-Feng Liu
- State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, China Agricultural University (West District), No.2 Yuanmingyuan West Road, 100193, Beijing, China.
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66
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David G, Bertolotti A, Layer R, Scofield D, Hayward A, Baril T, Burnett HA, Gudmunds E, Jensen H, Husby A. Calling Structural Variants with Confidence from Short-Read Data in Wild Bird Populations. Genome Biol Evol 2024; 16:evae049. [PMID: 38489588 PMCID: PMC11018544 DOI: 10.1093/gbe/evae049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 02/28/2024] [Accepted: 03/07/2024] [Indexed: 03/17/2024] Open
Abstract
Comprehensive characterization of structural variation in natural populations has only become feasible in the last decade. To investigate the population genomic nature of structural variation, reproducible and high-confidence structural variation callsets are first required. We created a population-scale reference of the genome-wide landscape of structural variation across 33 Nordic house sparrows (Passer domesticus). To produce a consensus callset across all samples using short-read data, we compare heuristic-based quality filtering and visual curation (Samplot/PlotCritic and Samplot-ML) approaches. We demonstrate that curation of structural variants is important for reducing putative false positives and that the time invested in this step outweighs the potential costs of analyzing short-read-discovered structural variation data sets that include many potential false positives. We find that even a lenient manual curation strategy (e.g. applied by a single curator) can reduce the proportion of putative false positives by up to 80%, thus enriching the proportion of high-confidence variants. Crucially, in applying a lenient manual curation strategy with a single curator, nearly all (>99%) variants rejected as putative false positives were also classified as such by a more stringent curation strategy using three additional curators. Furthermore, variants rejected by manual curation failed to reflect the expected population structure from SNPs, whereas variants passing curation did. Combining heuristic-based quality filtering with rapid manual curation of structural variants in short-read data can therefore become a time- and cost-effective first step for functional and population genomic studies requiring high-confidence structural variation callsets.
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Affiliation(s)
- Gabriel David
- Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | | | - Ryan Layer
- BioFrontiers Institute, University of Colorado, Boulder, CO, USA
- Department of Computer Science, University of Colorado, Boulder, CO, USA
| | - Douglas Scofield
- Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Alexander Hayward
- Centre for Ecology and Conservation, University of Exeter, Penryn Campus, Penryn, Cornwall, UK
| | - Tobias Baril
- Centre for Ecology and Conservation, University of Exeter, Penryn Campus, Penryn, Cornwall, UK
| | - Hamish A Burnett
- Centre for Biodiversity Dynamics, Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Erik Gudmunds
- Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
| | - Henrik Jensen
- Centre for Biodiversity Dynamics, Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Arild Husby
- Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
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67
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De Jode A, Faria R, Formenti G, Sims Y, Smith TP, Tracey A, Wood JMD, Zagrodzka ZB, Johannesson K, Butlin RK, Leder EH. Chromosome-scale Genome Assembly of the Rough Periwinkle Littorina saxatilis. Genome Biol Evol 2024; 16:evae076. [PMID: 38584387 DOI: 10.1093/gbe/evae076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 03/26/2024] [Accepted: 03/29/2024] [Indexed: 04/09/2024] Open
Abstract
The intertidal gastropod Littorina saxatilis is a model system to study speciation and local adaptation. The repeated occurrence of distinct ecotypes showing different levels of genetic divergence makes L. saxatilis particularly suited to study different stages of the speciation continuum in the same lineage. A major finding is the presence of several large chromosomal inversions associated with the divergence of ecotypes and, specifically, the species offers a system to study the role of inversions in this divergence. The genome of L. saxatilis is 1.35 Gb and composed of 17 chromosomes. The first reference genome of the species was assembled using Illumina data, was highly fragmented (N50 of 44 kb), and was quite incomplete, with a BUSCO completeness of 80.1% on the Metazoan dataset. A linkage map of one full-sibling family enabled the placement of 587 Mbp of the genome into 17 linkage groups corresponding to the haploid number of chromosomes, but the fragmented nature of this reference genome limited the understanding of the interplay between divergent selection and gene flow during ecotype formation. Here, we present a newly generated reference genome that is highly contiguous, with a N50 of 67 Mb and 90.4% of the total assembly length placed in 17 super-scaffolds. It is also highly complete with a BUSCO completeness of 94.1% of the Metazoa dataset. This new reference will allow for investigations into the genomic regions implicated in ecotype formation as well as better characterization of the inversions and their role in speciation.
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Affiliation(s)
- Aurélien De Jode
- Department of Marine Sciences, Tjärnö Marine Laboratory, University of Gothenburg, SE 45296 Strömstad, Sweden
- Department of Biological Sciences, University of Alabama, Tuscaloosa, AL, USA
- Dauphin Island Sea Lab, Dauphin Island, AL, USA
| | - Rui Faria
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, 4485-661 Vairão, Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, 4485-661 Vairão, Portugal
- Ecology and Evolutionary Biology, School of Biosciences, The University of Sheffield, Sheffield S10 2TN, UK
| | - Giulio Formenti
- The Vertebrate Genome Laboratory, The Rockefeller University, New York, NY 10065, USA
| | - Ying Sims
- Tree of Life, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| | - Timothy P Smith
- USDA Agricultural Research Service, U.S. Meat Animal Research Center, Clay Center, NE 68933, USA
| | - Alan Tracey
- Tree of Life, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| | - Jonathan M D Wood
- Tree of Life, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| | - Zuzanna B Zagrodzka
- Ecology and Evolutionary Biology, School of Biosciences, The University of Sheffield, Sheffield S10 2TN, UK
| | - Kerstin Johannesson
- Department of Marine Sciences, Tjärnö Marine Laboratory, University of Gothenburg, SE 45296 Strömstad, Sweden
| | - Roger K Butlin
- Department of Marine Sciences, Tjärnö Marine Laboratory, University of Gothenburg, SE 45296 Strömstad, Sweden
- Ecology and Evolutionary Biology, School of Biosciences, The University of Sheffield, Sheffield S10 2TN, UK
| | - Erica H Leder
- Department of Marine Sciences, Tjärnö Marine Laboratory, University of Gothenburg, SE 45296 Strömstad, Sweden
- Natural History Museum, University of Oslo, Oslo, Norway
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Saunders PA, Ferre-Ortega C, Hill PL, Simakov O, Ezaz T, Burridge CP, Wapstra E. Using a Handful of Transcriptomes to Detect Sex-Linked Markers and Develop Molecular Sexing Assays in a Species with Homomorphic Sex Chromosomes. Genome Biol Evol 2024; 16:evae060. [PMID: 38526014 PMCID: PMC11003529 DOI: 10.1093/gbe/evae060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 03/12/2024] [Accepted: 03/17/2024] [Indexed: 03/26/2024] Open
Abstract
To understand the biology of a species, it is often crucial to be able to differentiate males and females. However, many species lack easily identifiable sexually dimorphic traits. In those that possess sex chromosomes, molecular sexing offers a good alternative, and molecular sexing assays can be developed through the comparison of male and female genomic sequences. However, in many nonmodel species, sex chromosomes are poorly differentiated, and identifying sex-linked sequences and developing sexing assays can be challenging. In this study, we highlight a simple transcriptome-based procedure for the detection of sex-linked markers suitable for the development of sexing assays that circumvents limitations of more commonly used approaches. We apply it to the spotted snow skink Carinascincus ocellatus, a viviparous lizard with homomorphic XY chromosomes that has environmentally induced sex reversal. With transcriptomes from three males and three females alone, we identify thousands of putative Y-linked sequences. We confirm linkage through alignment of assembled transcripts to a distantly related lizard genome and readily design multiple single locus polymerase chain reaction primers to sex C. ocellatus and related species. Our approach also facilitates valuable comparisons of sex determining systems on a broad taxonomic scale.
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Affiliation(s)
- Paul A Saunders
- Discipline of Biological Sciences, University of Tasmania, Sandy Bay, Tasmania 7000, Australia
| | - Carles Ferre-Ortega
- Discipline of Biological Sciences, University of Tasmania, Sandy Bay, Tasmania 7000, Australia
| | - Peta L Hill
- Institute for Applied Ecology, University of Canberra, Bruce, Australian Capital Territory 2601, Australia
| | - Oleg Simakov
- Department of Molecular Evolution and Development, University of Vienna, Vienna 1010, Austria
| | - Tariq Ezaz
- Institute for Applied Ecology, University of Canberra, Bruce, Australian Capital Territory 2601, Australia
| | - Christopher P Burridge
- Discipline of Biological Sciences, University of Tasmania, Sandy Bay, Tasmania 7000, Australia
| | - Erik Wapstra
- Discipline of Biological Sciences, University of Tasmania, Sandy Bay, Tasmania 7000, Australia
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Xu S, Shao S, Feng X, Li S, Zhang L, Wu W, Liu M, Tracy ME, Zhong C, Guo Z, Wu CI, Shi S, He Z. Adaptation in Unstable Environments and Global Gene Losses: Small but Stable Gene Networks by the May-Wigner Theory. Mol Biol Evol 2024; 41:msae059. [PMID: 38507653 PMCID: PMC10991078 DOI: 10.1093/molbev/msae059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 03/07/2024] [Accepted: 03/15/2024] [Indexed: 03/22/2024] Open
Abstract
Although gene loss is common in evolution, it remains unclear whether it is an adaptive process. In a survey of seven major mangrove clades that are woody plants in the intertidal zones of daily environmental perturbations, we noticed that they generally evolved reduced gene numbers. We then focused on the largest clade of Rhizophoreae and observed the continual gene set reduction in each of the eight species. A great majority of gene losses are concentrated on environmental interaction processes, presumably to cope with the constant fluctuations in the tidal environments. Genes of the general processes for woody plants are largely retained. In particular, fewer gene losses are found in physiological traits such as viviparous seeds, high salinity, and high tannin content. Given the broad and continual genome reductions, we propose the May-Wigner theory (MWT) of system stability as a possible mechanism. In MWT, the most effective solution for buffering continual perturbations is to reduce the size of the system (or to weaken the total genic interactions). Mangroves are unique as immovable inhabitants of the compound environments in the land-sea interface, where environmental gradients (such as salinity) fluctuate constantly, often drastically. Extending MWT to gene regulatory network (GRN), computer simulations and transcriptome analyses support the stabilizing effects of smaller gene sets in mangroves vis-à-vis inland plants. In summary, we show the adaptive significance of gene losses in mangrove plants, including the specific role of promoting phenotype innovation and a general role in stabilizing GRN in unstable environments as predicted by MWT.
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Affiliation(s)
- Shaohua Xu
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China
- School of Ecology, Sun Yat-sen University, Shenzhen, China
| | - Shao Shao
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China
| | - Xiao Feng
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China
| | - Sen Li
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China
| | - Lingjie Zhang
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China
| | - Weihong Wu
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China
| | - Min Liu
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China
| | - Miles E Tracy
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China
| | - Cairong Zhong
- Institute of Wetland Research, Hainan Academy of Forestry (Hainan Academy of Mangrove), Haikou, China
| | - Zixiao Guo
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China
| | - Chung-I Wu
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China
| | - Suhua Shi
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China
| | - Ziwen He
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Guangzhou, China
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70
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Jin M, Wang H, Liu G, Lu J, Yuan Z, Li T, Liu E, Lu Z, Du L, Wei C. Whole- genome resequencing of Chinese indigenous sheep provides insight into the genetic basis underlying climate adaptation. Genet Sel Evol 2024; 56:26. [PMID: 38565986 PMCID: PMC10988870 DOI: 10.1186/s12711-024-00880-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 01/31/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Chinese indigenous sheep are valuable resources with unique features and characteristics. They are distributed across regions with different climates in mainland China; however, few reports have analyzed the environmental adaptability of sheep based on their genome. We examined the variants and signatures of selection involved in adaptation to extreme humidity, altitude, and temperature conditions in 173 sheep genomes from 41 phenotypically and geographically representative Chinese indigenous sheep breeds to characterize the genetic basis underlying environmental adaptation in these populations. RESULTS Based on the analysis of population structure, we inferred that Chinese indigenous sheep are divided into four groups: Kazakh (KAZ), Mongolian (MON), Tibetan (TIB), and Yunnan (YUN). We also detected a set of candidate genes that are relevant to adaptation to extreme environmental conditions, such as drought-prone regions (TBXT, TG, and HOXA1), high-altitude regions (DYSF, EPAS1, JAZF1, PDGFD, and NF1) and warm-temperature regions (TSHR, ABCD4, and TEX11). Among all these candidate genes, eight ABCD4, CNTN4, DOCK10, LOC105608545, LOC121816479, SEM3A, SVIL, and TSHR overlap between extreme environmental conditions. The TSHR gene shows a strong signature for positive selection in the warm-temperature group and harbors a single nucleotide polymorphism (SNP) missense mutation located between positions 90,600,001 and 90,650,001 on chromosome 7, which leads to a change in the protein structure of TSHR and influences its stability. CONCLUSIONS Analysis of the signatures of selection uncovered genes that are likely related to environmental adaptation and a SNP missense mutation in the TSHR gene that affects the protein structure and stability. It also provides information on the evolution of the phylogeographic structure of Chinese indigenous sheep populations. These results provide important genetic resources for future breeding studies and new perspectives on how animals can adapt to climate change.
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Affiliation(s)
- Meilin Jin
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Huihua Wang
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Gang Liu
- National Animal Husbandry Service, National Center of Preservation and Utilization of Animal Genetic Resources, Beijing, China
| | - Jian Lu
- National Animal Husbandry Service, National Center of Preservation and Utilization of Animal Genetic Resources, Beijing, China
| | - Zehu Yuan
- College of Animal Science and Technology, Yangzhou University, Yangzhou, China
| | - Taotao Li
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Engming Liu
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zengkui Lu
- Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lan-Zhou, China
| | - Lixin Du
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
| | - Caihong Wei
- Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
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71
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Mahout M, Carlson RP, Simon L, Peres S. Logic programming-based Minimal Cut Sets reveal consortium-level therapeutic targets for chronic wound infections. NPJ Syst Biol Appl 2024; 10:34. [PMID: 38565568 PMCID: PMC10987626 DOI: 10.1038/s41540-024-00360-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Accepted: 03/13/2024] [Indexed: 04/04/2024] Open
Abstract
Minimal Cut Sets (MCSs) identify sets of reactions which, when removed from a metabolic network, disable certain cellular functions. The traditional search for MCSs within genome-scale metabolic models (GSMMs) targets cellular growth, identifies reaction sets resulting in a lethal phenotype if disrupted, and retrieves a list of corresponding gene, mRNA, or enzyme targets. Using the dual link between MCSs and Elementary Flux Modes (EFMs), our logic programming-based tool aspefm was able to compute MCSs of any size from GSMMs in acceptable run times. The tool demonstrated better performance when computing large-sized MCSs than the mixed-integer linear programming methods. We applied the new MCSs methodology to a medically-relevant consortium model of two cross-feeding bacteria, Staphylococcus aureus and Pseudomonas aeruginosa. aspefm constraints were used to bias the computation of MCSs toward exchanged metabolites that could complement lethal phenotypes in individual species. We found that interspecies metabolite exchanges could play an essential role in rescuing single-species growth, for instance inosine could complement lethal reaction knock-outs in the purine synthesis, glycolysis, and pentose phosphate pathways of both bacteria. Finally, MCSs were used to derive a list of promising enzyme targets for consortium-level therapeutic applications that cannot be circumvented via interspecies metabolite exchange.
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Affiliation(s)
- Maxime Mahout
- Université Paris-Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique, 91405, Orsay, France
| | - Ross P Carlson
- Department of Chemical and Biological Engineering, Center for Biofilm Engineering, Microbiology and Immunology, Montana State University, Bozeman, MT, 59717, USA
| | - Laurent Simon
- Bordeaux-INP, Université Bordeaux, LaBRI, 33405, Talence Cedex, France
| | - Sabine Peres
- UMR CNRS 5558, Laboratoire de Biométrie et de Biologie Évolutive, Université Claude Bernard Lyon 1, 69100, Villeurbanne, France.
- INRIA Lyon Centre, 69100, Villeurbanne, France.
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72
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Eisenstein M. Startups probe hidden viruses in the 'dark genome' to treat disease. Nat Biotechnol 2024; 42:539-541. [PMID: 38632451 DOI: 10.1038/s41587-024-02215-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
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73
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Yi W, Hu M, Shi L, Li T, Sun H, Qin L, Yan S. Analysis of genetic variants in protein-coding genes of Aoluguya reindeer based on the whole- genome data. Anim Genet 2024; 55:296-298. [PMID: 38319118 DOI: 10.1111/age.13402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 01/19/2024] [Accepted: 01/19/2024] [Indexed: 02/07/2024]
Affiliation(s)
- Wenfeng Yi
- College of Animal Science, Jilin University, Changchun, China
| | - Mingyue Hu
- College of Animal Science, Jilin University, Changchun, China
| | - Lulu Shi
- College of Animal Science, Jilin University, Changchun, China
| | - Ting Li
- College of Animal Science, Jilin University, Changchun, China
| | - Hao Sun
- College of Animal Science, Jilin University, Changchun, China
| | - Lihong Qin
- Institute of Animal Husbandry and Veterinary, Jilin Academy of Agricultural Sciences, Gongzhuling, China
| | - Shouqing Yan
- College of Animal Science, Jilin University, Changchun, China
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74
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Tang X, Zeng P, Liu K, Qing L, Sun Y, Liu X, Lu L, Wei C, Wang J, Jiang S, Sun J, Chang W, Yu H, Chen H, Zhou J, Xu C, Fan L, Miao YL, Ding J. The PTM profiling of CTCF reveals the regulation of 3D chromatin structure by O-GlcNAcylation. Nat Commun 2024; 15:2813. [PMID: 38561336 PMCID: PMC10985093 DOI: 10.1038/s41467-024-47048-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 03/18/2024] [Indexed: 04/04/2024] Open
Abstract
CCCTC-binding factor (CTCF), a ubiquitously expressed and highly conserved protein, is known to play a critical role in chromatin structure. Post-translational modifications (PTMs) diversify the functions of protein to regulate numerous cellular processes. However, the effects of PTMs on the genome-wide binding of CTCF and the organization of three-dimensional (3D) chromatin structure have not been fully understood. In this study, we uncovered the PTM profiling of CTCF and demonstrated that CTCF can be O-GlcNAcylated and arginine methylated. Functionally, we demonstrated that O-GlcNAcylation inhibits CTCF binding to chromatin. Meanwhile, deficiency of CTCF O-GlcNAcylation results in the disruption of loop domains and the alteration of chromatin loops associated with cellular development. Furthermore, the deficiency of CTCF O-GlcNAcylation increases the expression of developmental genes and negatively regulates maintenance and establishment of stem cell pluripotency. In conclusion, these results provide key insights into the role of PTMs for the 3D chromatin structure.
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Affiliation(s)
- Xiuxiao Tang
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Pharmacology and Cardiac & Cerebral Vascular Research Center, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Pengguihang Zeng
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Kezhi Liu
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Li Qing
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Yifei Sun
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Xinyi Liu
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Lizi Lu
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Chao Wei
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Jia Wang
- GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, 511436, China
| | - Shaoshuai Jiang
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Jun Sun
- West China Biomedical Big Data Center, West China Hospital/West China School of Medicine, Sichuan University, Chengdu, 610041, China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610041, China
| | - Wakam Chang
- Department of Biomedical Sciences, Faculty of Health Sciences, University of Macau, Taipa, Macau, China
| | - Haopeng Yu
- West China Biomedical Big Data Center, West China Hospital/West China School of Medicine, Sichuan University, Chengdu, 610041, China
- Med-X Center for Informatics, Sichuan University, Chengdu, 610041, China
| | - Hebing Chen
- Institute of Health Service and Transfusion Medicine, Beijing, 100850, China
| | - Jiaguo Zhou
- Department of Pharmacology and Cardiac & Cerebral Vascular Research Center, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Chengfang Xu
- The obstetric and gynecology Department of The third affiliated hospital of Sun Yat-Sen University, Guangzhou, China.
| | - Lili Fan
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, Guangdong, China.
| | - Yi-Liang Miao
- Institute of Stem Cell and Regenerative Biology, College of Animal Science and Veterinary Medicine, Huazhong Agricultural University, Wuhan, Hubei, China.
| | - Junjun Ding
- RNA Biomedical Institute, Sun Yat-Sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China.
- Department of Rehabilitation Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, 518107, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China.
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou, 510080, China.
- West China Biomedical Big Data Center, West China Hospital/West China School of Medicine, Sichuan University, Chengdu, 610041, China.
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75
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Lawson J, Rahimzadeh V, Baek J, Dove ES. Achieving Procedural Parity in Managing Access to Genomic and Related Health Data: A Global Survey of Data Access Committee Members. Biopreserv Biobank 2024; 22:123-129. [PMID: 37192473 DOI: 10.1089/bio.2022.0205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2023] Open
Abstract
Data access committees (DACs) are critical players in the data sharing ecosystem. DACs review requests for access to data held in one or more repositories and where specific constraints determine how the data may be used and by whom. Our team surveyed DAC members affiliated with genomic data repositories worldwide to understand standard processes and procedures, operational metrics, bottlenecks, and efficiencies, as well as their perspectives on possible improvements to quality review. We found that DAC operations and systemic issues were common across repositories globally. In general, DAC members endeavored to achieve an appropriate balance of review efficiency, quality, and compliance. Our results suggest a similarly proportionate path forward that helps DACs pursue mutual improvements to efficiency and compliance without sacrificing review quality.
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Affiliation(s)
- Jonathan Lawson
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Vasiliki Rahimzadeh
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, Texas, USA
| | - Jinyoung Baek
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Edward S Dove
- School of Law, University of Edinburgh, Edinburgh, United Kingdom
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76
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Maier PA, Vandergast AG, Bohonak AJ. Yosemite toad (Anaxyrus canorus) transcriptome reveals interplay between speciation genes and adaptive introgression. Mol Ecol 2024; 33:e17317. [PMID: 38488670 DOI: 10.1111/mec.17317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 02/15/2024] [Accepted: 02/23/2024] [Indexed: 04/09/2024]
Abstract
Genomes are heterogeneous during the early stages of speciation, with small 'islands' of DNA appearing to reflect strong adaptive differences, surrounded by vast seas of relative homogeneity. As species diverge, secondary contact zones between them can act as an interface and selectively filter through advantageous alleles of hybrid origin. Such introgression is another important adaptive process, one that allows beneficial mosaics of recombinant DNA ('rivers') to flow from one species into another. Although genomic islands of divergence appear to be associated with reproductive isolation, and genomic rivers form by adaptive introgression, it is unknown whether islands and rivers tend to be the same or different loci. We examined three replicate secondary contact zones for the Yosemite toad (Anaxyrus canorus) using two genomic data sets and a morphometric data set to answer the questions: (1) How predictably different are islands and rivers, both in terms of genomic location and gene function? (2) Are the adaptive genetic trait loci underlying tadpole growth and development reliably islands, rivers or neither? We found that island and river loci have significant overlap within a contact zone, suggesting that some loci are first islands, and later are predictably converted into rivers. However, gene ontology enrichment analysis showed strong overlap in gene function unique to all island loci, suggesting predictability in overall gene pathways for islands. Genome-wide association study outliers for tadpole development included LPIN3, a lipid metabolism gene potentially involved in climate change adaptation, that is island-like for all three contact zones, but also appears to be introgressing (as a river) across one zone. Taken together, our results suggest that adaptive divergence and introgression may be more complementary forces than currently appreciated.
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Affiliation(s)
- Paul A Maier
- Department of Biology, San Diego State University, San Diego, California, USA
- Family TreeDNA, Gene by Gene, Houston, Texas, USA
| | - Amy G Vandergast
- Western Ecological Research Center, San Diego Field Station, U.S. Geological Survey, San Diego, California, USA
| | - Andrew J Bohonak
- Department of Biology, San Diego State University, San Diego, California, USA
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77
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Audoor S, Bilcke G, Pargana K, Belišová D, Thierens S, Van Bel M, Sterck L, Rijsdijk N, Annunziata R, Ferrante MI, Vandepoele K, Vyverman W. Transcriptional chronology reveals conserved genes involved in pennate diatom sexual reproduction. Mol Ecol 2024; 33:e17320. [PMID: 38506152 DOI: 10.1111/mec.17320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 01/23/2024] [Accepted: 03/07/2024] [Indexed: 03/21/2024]
Abstract
Sexual reproduction is a major driver of adaptation and speciation in eukaryotes. In diatoms, siliceous microalgae with a unique cell size reduction-restitution life cycle and among the world's most prolific primary producers, sex also acts as the main mechanism for cell size restoration through the formation of an expanding auxospore. However, the molecular regulators of the different stages of sexual reproduction and size restoration are poorly explored. Here, we combined RNA sequencing with the assembly of a 55 Mbp reference genome for Cylindrotheca closterium to identify patterns of gene expression during different stages of sexual reproduction. These were compared with a corresponding transcriptomic time series of Seminavis robusta to assess the degree of expression conservation. Integrative orthology analysis revealed 138 one-to-one orthologues that are upregulated during sex in both species, among which 56 genes consistently upregulated during cell pairing and gametogenesis, and 11 genes induced when auxospores are present. Several early, sex-specific transcription factors and B-type cyclins were also upregulated during sex in other pennate and centric diatoms, pointing towards a conserved core regulatory machinery for meiosis and gametogenesis across diatoms. Furthermore, we find molecular evidence that the pheromone-induced cell cycle arrest is short-lived in benthic diatoms, which may be linked to their active mode of mate finding through gliding. Finally, we exploit the temporal resolution of our comparative analysis to report the first marker genes for auxospore identity called AAE1-3 ("Auxospore-Associated Expression"). Altogether, we introduce a multi-species model of the transcriptional dynamics during size restoration in diatoms and highlight conserved gene expression dynamics during different stages of sexual reproduction.
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Affiliation(s)
- Sien Audoor
- Laboratory of Protistology and Aquatic Ecology, Department of Biology, University Ghent, Ghent, Belgium
| | - Gust Bilcke
- Laboratory of Protistology and Aquatic Ecology, Department of Biology, University Ghent, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
| | - Katerina Pargana
- Laboratory of Protistology and Aquatic Ecology, Department of Biology, University Ghent, Ghent, Belgium
| | - Darja Belišová
- Laboratory of Protistology and Aquatic Ecology, Department of Biology, University Ghent, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
| | - Sander Thierens
- VIB Center for Plant Systems Biology, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
| | - Michiel Van Bel
- VIB Center for Plant Systems Biology, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
| | - Lieven Sterck
- VIB Center for Plant Systems Biology, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
| | - Nadine Rijsdijk
- Laboratory of Protistology and Aquatic Ecology, Department of Biology, University Ghent, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
| | | | - Maria Immacolata Ferrante
- Stazione Zoologica Anton Dohrn, Naples, Italy
- Associate to the National Institute of Oceanography and Applied Geophysics, Trieste, Italy
| | - Klaas Vandepoele
- VIB Center for Plant Systems Biology, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- VIB Center for AI & Computational Biology, VIB, Ghent, Belgium
| | - Wim Vyverman
- Laboratory of Protistology and Aquatic Ecology, Department of Biology, University Ghent, Ghent, Belgium
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van der Els S, Sheombarsing R, van Kempen T, Wels M, Boekhorst J, Bron PA, Kleerebezem M. Detection and classification of the integrative conjugative elements of Lactococcus lactis. BMC Genomics 2024; 25:324. [PMID: 38561675 PMCID: PMC10983677 DOI: 10.1186/s12864-024-10255-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 03/26/2024] [Indexed: 04/04/2024] Open
Abstract
Lactococcus lactis is widely applied by the dairy industry for the fermentation of milk into products such as cheese. Adaptation of L. lactis to the dairy environment often depends on functions encoded by mobile genetic elements (MGEs) such as plasmids. Other L. lactis MGEs that contribute to industrially relevant traits like antimicrobial production and carbohydrate utilization capacities belong to the integrative conjugative elements (ICE). Here we investigate the prevalence of ICEs in L. lactis using an automated search engine that detects colocalized, ICE-associated core-functions (involved in conjugation or mobilization) in lactococcal genomes. This approach enabled the detection of 36 candidate-ICEs in 69 L. lactis genomes. By phylogenetic analysis of conserved protein functions encoded in all lactococcal ICEs, these 36 ICEs could be classified in three main ICE-families that encompass 7 distinguishable ICE-integrases and are characterized by apparent modular-exchangeability and plasticity. Finally, we demonstrate that phylogenetic analysis of the conjugation-associated VirB4 ATPase function differentiates ICE- and plasmid-derived conjugation systems, indicating that conjugal transfer of lactococcal ICEs and plasmids involves genetically distinct machineries. Our genomic analysis and sequence-based classification of lactococcal ICEs creates a comprehensive overview of the conserved functional repertoires encoded by this family of MGEs in L. lactis, which can facilitate the future exploitation of the functional traits they encode by ICE mobilization to appropriate starter culture strains.
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Affiliation(s)
- Simon van der Els
- Host-Microbe Interactomics Group, Department of Animal Sciences, Wageningen University & Research, De Elst 1, 6708 WD, Wageningen, The Netherlands
- NIZO B.V, Kernhemseweg 2, 6718, ZB, Ede, The Netherlands
- BE-Basic Foundation, Mijnbouwstraat 120, 2628 RX, Delft, The Netherlands
| | - Reshtrie Sheombarsing
- Host-Microbe Interactomics Group, Department of Animal Sciences, Wageningen University & Research, De Elst 1, 6708 WD, Wageningen, The Netherlands
- NIZO B.V, Kernhemseweg 2, 6718, ZB, Ede, The Netherlands
| | | | - Michiel Wels
- NIZO B.V, Kernhemseweg 2, 6718, ZB, Ede, The Netherlands
| | - Jos Boekhorst
- Host-Microbe Interactomics Group, Department of Animal Sciences, Wageningen University & Research, De Elst 1, 6708 WD, Wageningen, The Netherlands
| | - Peter A Bron
- NIZO B.V, Kernhemseweg 2, 6718, ZB, Ede, The Netherlands
- BE-Basic Foundation, Mijnbouwstraat 120, 2628 RX, Delft, The Netherlands
| | - Michiel Kleerebezem
- Host-Microbe Interactomics Group, Department of Animal Sciences, Wageningen University & Research, De Elst 1, 6708 WD, Wageningen, The Netherlands.
- BE-Basic Foundation, Mijnbouwstraat 120, 2628 RX, Delft, The Netherlands.
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79
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Cowzer D, Shah RH, Chou JF, Kundra R, Punn S, Fiedler L, DeMore A, Capanu M, Berger MF, Reidy-Lagunes D, Raj N. Clinical utility of plasma cell-free DNA in pancreatic neuroendocrine neoplasms. Endocr Relat Cancer 2024; 31:e230292. [PMID: 38252063 DOI: 10.1530/erc-23-0292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 01/22/2024] [Indexed: 01/23/2024]
Abstract
In advanced pancreatic neuroendocrine neoplasms (PanNEN), there are little data detailing the frequency of genetic alterations identified in cell free DNA (cfDNA), plasma-tissue concordance of detected alterations, and clinical utility of cfDNA. Patients with metastatic PanNENs underwent cfDNA collection in routine practice. Next-generation sequencing (NGS) of cfDNA and matched tissue when available was performed. Clinical actionability of variants was annotated by OncoKB. Thirty-two cfDNA samples were analyzed from 25 patients, the majority who had well-differentiated intermediate grade disease (13/25; 52%). Genomic alterations were detected in 68% of patients and in 66% of all cfDNA samples. The most frequently altered genes were DAXX (28%), TSC2 (24%), MEN1 (24%), ARID1B (20%), ARID1A (12%), and ATRX (12%). Twenty-three out of 25 (92%) patients underwent tumor tissue NGS. Tissue-plasma concordance for select genes was as follows:DAXX (95.7%), ARID1A (91.1%), ATRX (87%), TSC2 (82.6%), MEN1 (69.6%). Potentially actionable alterations were identified in cfDNA of 8 patients, including TSC2 (4; level 3b), ATM (1; level 3b), ARID1A (2; level 4), and KRAS (1; level 4). An ETV6:NTRK fusion detected in tumor tissue was treated with larotrectinib; at progression, sequencing of cfDNA identified an NTRK3 G623R alteration as the acquired mechanism of resistance; the patient enrolled in a clinical trial of a second-generation TRK inhibitor with clinical benefit. In metastatic PanNENs, cfDNA-based NGS identified tumor-associated mutations in 66% of plasma samples with a high level of plasma-tissue agreement in PanNEN-associated genes. Clonal evolution, actionable alterations, and resistance mechanisms were detected through circulating cfDNA genotyping.
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Affiliation(s)
- Darren Cowzer
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Ronak H Shah
- Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Joanne F Chou
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Ritika Kundra
- Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Sippy Punn
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Laura Fiedler
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - April DeMore
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Marinela Capanu
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Michael F Berger
- Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Department of Pathology and laboratory medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Diane Reidy-Lagunes
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Weill Medical College of Cornell University, New York, New York, USA
| | - Nitya Raj
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Weill Medical College of Cornell University, New York, New York, USA
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80
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Field MC. Ras superfamily GTPases and signal transduction in Euglena gracilis. Protist 2024; 175:126017. [PMID: 38295671 DOI: 10.1016/j.protis.2024.126017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/21/2023] [Accepted: 01/26/2024] [Indexed: 03/13/2024]
Abstract
Biological complexity is challenging to define, but can be considered through one or more features, including overall genome size, number of genes, morphological features, multicellularity, number of life cycle stages and the ability to adapt to different environments. Euglena gracilis meets several of these criteria, with a large genome of ∼38,000 protein coding genes and a considerable ability to survive under many different conditions, some of which can be described as challenging or harsh. Potential molecular exemplars of complexity tying these aspects together are signalling pathways, including GTPases, kinases and ubiquitylation, which increase the functionality of the gene-encoded proteome manyfold. Each of these examples can modulate both protein activity and gene expression. To address the connection between genome size and complexity I have undertaken a brief, and somewhat qualitative, survey of the small ras-like GTPase superfamily of E. gracilis. Unexpectedly, apart from Rab-GTPases which control intracellular transport and organelle identify, the size of the GTPase cohort is modest, and, for example, has not scaled with gene number when compared to the close relatives, trypanosomatids. I suggest that understanding the functions of this protein family will be vital to uncovering the complexity of E. gracilis biology.
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Affiliation(s)
- Mark C Field
- School of Life Sciences, University of Dundee, Dundee, UK; Biology Centre, Czech Academy of Sciences, České Budějovice, Czech Republic.
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81
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Huang Z, Liu Q, Zeng X, Ni G. High-quality chromosome-level genome assembly of the Northern Pacific sea star Asterias amurensis. DNA Res 2024; 31:dsae007. [PMID: 38416146 DOI: 10.1093/dnares/dsae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 02/17/2024] [Accepted: 02/26/2024] [Indexed: 02/29/2024] Open
Abstract
Asterias amurensis, a starfish species that is native to countries such as China and Japan, as well as non-native regions like Australia, has raised serious concerns in terms of its impact on ecology and economy. To gain a better understanding of its population genomics and dynamics, we successfully assembled a high-quality chromosome-level genome of A. amurensis using PacBio and Hi-C sequencing technologies. A total of 87 scaffolds assembly with contig N50 length of 10.85 Mb and scaffold N50 length of 23.34 Mb were obtained, with over 98.80% (0.48 Gb) of them anchored to 22 pseudochromosomes. We predicted 16,673 protein-coding genes, 95.19% of which were functionally annotated. Our phylogenetic analysis revealed that A. amurensis and Asterias rubens formed a clade, and their divergence time was estimated ~ 28 million years ago (Mya). The significantly enriched pathways and Gene Ontology terms related to the amplified gene family were mainly associated with immune response and energy metabolism, suggesting that these factors might have contributed to the adaptability of A. amurensis to its environment. This study provides valuable genomic resources for comprehending the genetics, dynamics, and evolution of A. amurensis, especially when population outbreaks or invasions occur.
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Affiliation(s)
- Zhichao Huang
- Ministry of Education Key Laboratory of Mariculture, Ocean University of China, Qingdao 266003, China
| | - Qi Liu
- Wuhan Onemore-tech Co., Ltd, Wuhan 430000, China
| | - Xiaoqi Zeng
- Ministry of Education Key Laboratory of Mariculture, Ocean University of China, Qingdao 266003, China
- Institute of Evolution and Marine Biodiversity, Ocean University of China, Qingdao 266003, China
| | - Gang Ni
- Ministry of Education Key Laboratory of Mariculture, Ocean University of China, Qingdao 266003, China
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82
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Schiavo G, Bertolini F, Bovo S, Galimberti G, Muñoz M, Bozzi R, Čandek-Potokar M, Óvilo C, Fontanesi L. Identification of population-informative markers from high-density genotyping data through combined feature selection and machine learning algorithms: Application to European autochthonous and cosmopolitan pig breeds. Anim Genet 2024; 55:193-205. [PMID: 38191264 DOI: 10.1111/age.13396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 11/09/2023] [Accepted: 12/27/2023] [Indexed: 01/10/2024]
Abstract
Large genotyping datasets, obtained from high-density single nucleotide polymorphism (SNP) arrays, developed for different livestock species, can be used to describe and differentiate breeds or populations. To identify the most discriminating genetic markers among thousands of genotyped SNPs, a few statistical approaches have been proposed. In this study, we applied the Boruta algorithm, a wrapper of the machine learning random forest algorithm, on a database of 23 European pig breeds (20 autochthonous and three cosmopolitan breeds) genotyped with a 70k SNP chip, to pre-select informative SNPs. To identify different sets of SNPs, these pre-selected markers were then ranked with random forest based on their mean decrease accuracy and mean decrease gene indexes. We evaluated the efficiency of these subsets for breed classification and the usefulness of this approach to detect candidate genes affecting breed-specific phenotypes and relevant production traits that might differ among breeds. The lowest overall classification error (2.3%) was reached with a subpanel including only 398 SNPs (ranked based on their mean decrease accuracy), with no classification error in seven breeds using up to 49 SNPs. Several SNPs of these selected subpanels were in genomic regions in which previous studies had identified signatures of selection or genes associated with morphological or production traits that distinguish the analysed breeds. Therefore, even if these approaches have not been originally designed to identify signatures of selection, the obtained results showed that they could potentially be useful for this purpose.
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Affiliation(s)
- Giuseppina Schiavo
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Francesca Bertolini
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Samuele Bovo
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Giuliano Galimberti
- Department of Statistical Sciences 'Paolo Fortunati', University of Bologna, Bologna, Italy
| | - María Muñoz
- Departamento Mejora Genética Animal, INIA-CSIC, Madrid, Spain
| | - Riccardo Bozzi
- Animal Science Division, Dipartimento di Scienze e Tecnologie Agrarie, Alimentari, Ambientali e Forestali, Università di Firenze, Firenze, Italy
| | | | - Cristina Óvilo
- Departamento Mejora Genética Animal, INIA-CSIC, Madrid, Spain
| | - Luca Fontanesi
- Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
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83
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Chen K, Chi Y, Cheng H, Yang M, Tan Q, Hao J, Lin Y, Mao F, He S, Yang J. Identification and characterization of extrachromosomal circular DNA in large-artery atherosclerotic stroke. J Cell Mol Med 2024; 28:e18210. [PMID: 38506071 PMCID: PMC10951879 DOI: 10.1111/jcmm.18210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 01/30/2024] [Accepted: 02/16/2024] [Indexed: 03/21/2024] Open
Abstract
Extrachromosomal circular DNA (eccDNA) is a new biomarker and regulator of diseases. However, the role of eccDNAs in large-artery atherosclerotic (LAA) stroke remains unclear. Through high-throughput circle-sequencing technique, the length distribution, genomic characteristic and motifs feature of plasma eccDNA from healthy controls (CON) and patients with LAA stroke were analysed. Then, the potential functions of the annotated eccDNAs were investigated using GO and KEGG pathway analyses. EccDNAs mapped to the reference genome showed SHN3 and BCL6 were LAA stroke unique transcription factors. The genes of differentially expressed eccDNAs between LAA stroke patients and CON were mainly involved in axon/dendrite/neuron projection development and maintenance of cellular structure via Wnt, Rap1 and MAPK pathways. Moreover, LAA stroke unique eccDNA genes played a role in regulation of coagulation and fibrinolysis, and there were five LAA stroke unique eccDNAs (Chr2:12724406-12724784, Chr4:1867120-186272046, Chr4:186271494-186271696, Chr7:116560296-116560685 and Chr11:57611780-5761192). Additionally, POLR2C and AURKA carried by ecDNAs (eccDNA size >100 kb) of LAA stroke patients were significantly associated with development of LAA stroke. Our data firstly revealed the characteristics of eccDNA in LAA stroke and the functions of LAA stroke unique eccDNAs and eccDNA genes, suggesting eccDNA is a novel biomarker and mechanism of LAA stroke.
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Affiliation(s)
- Kejie Chen
- School of Public HealthChengdu Medical CollegeChengduPR China
| | - Yanqi Chi
- School of Public HealthChengdu Medical CollegeChengduPR China
| | - Hang Cheng
- Department of NeurologyClinical Medical College and The First Affiliated Hospital of Chengdu Medical CollegeChengduPR China
| | - Min Yang
- Department of NeurologyClinical Medical College and The First Affiliated Hospital of Chengdu Medical CollegeChengduPR China
| | - Quandan Tan
- Department of NeurologyClinical Medical College and The First Affiliated Hospital of Chengdu Medical CollegeChengduPR China
| | - Junli Hao
- School of Bioscience and TechnologyChengdu Medical CollegeChengduPR China
| | - Yapeng Lin
- Department of NeurologyClinical Medical College and The First Affiliated Hospital of Chengdu Medical CollegeChengduPR China
| | - Fengkai Mao
- Department of NeurologyClinical Medical College and The First Affiliated Hospital of Chengdu Medical CollegeChengduPR China
| | - Song He
- Department of NeurologyClinical Medical College and The First Affiliated Hospital of Chengdu Medical CollegeChengduPR China
| | - Jie Yang
- Department of Neurology, Sichuan Provincial People's Hospital, School of MedicineUniversity of Electronic Science and Technology of ChinaChengduPR China
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84
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Dietz L, Mayer C, Stolle E, Eberle J, Misof B, Podsiadlowski L, Niehuis O, Ahrens D. Metazoa-level USCOs as markers in species delimitation and classification. Mol Ecol Resour 2024; 24:e13921. [PMID: 38146909 DOI: 10.1111/1755-0998.13921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 12/06/2023] [Accepted: 12/13/2023] [Indexed: 12/27/2023]
Abstract
Metazoa-level universal single-copy orthologs (mzl-USCOs) are universally applicable markers for DNA taxonomy in animals that can replace or supplement single-gene barcodes. Previously, mzl-USCOs from target enrichment data were shown to reliably distinguish species. Here, we tested whether USCOs are an evenly distributed, representative sample of a given metazoan genome and therefore able to cope with past hybridization events and incomplete lineage sorting. This is relevant for coalescent-based species delimitation approaches, which critically depend on the assumption that the investigated loci do not exhibit autocorrelation due to physical linkage. Based on 239 chromosome-level assembled genomes, we confirmed that mzl-USCOs are genetically unlinked for practical purposes and a representative sample of a genome in terms of reciprocal distances between USCOs on a chromosome and of distribution across chromosomes. We tested the suitability of mzl-USCOs extracted from genomes for species delimitation and phylogeny in four case studies: Anopheles mosquitos, Drosophila fruit flies, Heliconius butterflies and Darwin's finches. In almost all instances, USCOs allowed delineating species and yielded phylogenies that corresponded to those generated from whole genome data. Our phylogenetic analyses demonstrate that USCOs may complement single-gene DNA barcodes and provide more accurate taxonomic inferences. Combining USCOs from sources that used different versions of ortholog reference libraries to infer marker orthology may be challenging and, at times, impact taxonomic conclusions. However, we expect this problem to become less severe as the rapidly growing number of reference genomes provides a better representation of the number and diversity of organismal lineages.
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Affiliation(s)
- Lars Dietz
- Museum A. Koenig, Leibniz Institute for the Analysis of Biodiversity Change, Bonn, Germany
| | - Christoph Mayer
- Museum A. Koenig, Leibniz Institute for the Analysis of Biodiversity Change, Bonn, Germany
| | - Eckart Stolle
- Museum A. Koenig, Leibniz Institute for the Analysis of Biodiversity Change, Bonn, Germany
| | - Jonas Eberle
- Museum A. Koenig, Leibniz Institute for the Analysis of Biodiversity Change, Bonn, Germany
- Paris-Lodron-University, Salzburg, Austria
| | - Bernhard Misof
- Museum A. Koenig, Leibniz Institute for the Analysis of Biodiversity Change, Bonn, Germany
- Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany
| | - Lars Podsiadlowski
- Museum A. Koenig, Leibniz Institute for the Analysis of Biodiversity Change, Bonn, Germany
| | - Oliver Niehuis
- Abt. Evolutionsbiologie und Ökologie, Institut für Biologie I, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany
| | - Dirk Ahrens
- Museum A. Koenig, Leibniz Institute for the Analysis of Biodiversity Change, Bonn, Germany
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85
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Tavridou A, Rogers D, Farinelli G, Gravanis I, Jekerle V. Genome-editing medicinal products: the EMA perspective. Nat Rev Drug Discov 2024; 23:242-243. [PMID: 38491159 DOI: 10.1038/d41573-024-00050-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2024]
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86
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Lee K, Tripathi A. Insight into Increased Recovery and Simplification of Genomic DNA Extraction Methods from Dried Blood Spots. Biopreserv Biobank 2024; 22:130-138. [PMID: 37410524 DOI: 10.1089/bio.2022.0181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/07/2023] Open
Abstract
There is no consensus on how to perform the manual extraction of nucleic acids from dried blood spots (DBSs). Current methods typically involve agitation of the DBSs in a solution for varying amounts of time with or without heat, and then purification of the eluted nucleic acids with a purification protocol. We explored several characteristics of genomic DNA (gDNA) DBS extraction such as extraction efficiency, the role of red blood cells (RBCs) in extraction and critical kinetic factors to understand if these protocols can be simplified while maintaining sufficient gDNA recovery. We found that agitation in a RBC lysis buffer before performing a DBS gDNA extraction protocol increases yield 1.5 to 5-fold, depending upon the anticoagulant used. The use of an alkaline lysing agent along with either heat or agitation was sufficient to elute quantitative polymerase chain reaction (qPCR) amplifiable gDNA in 5 minutes. This work adds insight into the extraction of gDNA from DBSs with the intention of informing a simple, standardized manual protocol for extraction.
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Affiliation(s)
- Kiara Lee
- Center for Biomedical Engineering, School of Engineering, Brown University, Providence, Rhode Island, USA
- Brown University School of Public Health, Providence, Rhode Island, USA
| | - Anubhav Tripathi
- Center for Biomedical Engineering, School of Engineering, Brown University, Providence, Rhode Island, USA
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87
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James C, Pemberton JM, Navarro P, Knott S. Investigating pedigree- and SNP-associated components of heritability in a wild population of Soay sheep. Heredity (Edinb) 2024; 132:202-210. [PMID: 38341521 PMCID: PMC10997785 DOI: 10.1038/s41437-024-00673-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 01/19/2024] [Accepted: 01/24/2024] [Indexed: 02/12/2024] Open
Abstract
Estimates of narrow sense heritability derived from genomic data that contain related individuals may be biased due to the within-family effects such as dominance, epistasis and common environmental factors. However, for many wild populations, removal of related individuals from the data would result in small sample sizes. In 2013, Zaitlen et al. proposed a method to estimate heritability in populations that include close relatives by simultaneously fitting an identity-by-state (IBS) genomic relatedness matrix (GRM) and an identity-by-descent (IBD) GRM. The IBD GRM is identical to the IBS GRM, except relatedness estimates below a specified threshold are set to 0. We applied this method to a sample of 8557 wild Soay sheep from St. Kilda, with genotypic information for 419,281 single nucleotide polymorphisms. We aimed to see how this method would partition heritability into population-level (IBS) and family-associated (IBD) variance for a range of genetic architectures, and so we focused on a mixture of polygenic and monogenic traits. We also implemented a variant of the model in which the IBD GRM was replaced by a GRM constructed from SNPs with low minor allele frequency to examine whether any additive genetic variance is captured by rare alleles. Whilst the inclusion of the IBD GRM did not significantly improve the fit of the model for the monogenic traits, it improved the fit for some of the polygenic traits, suggesting that dominance, epistasis and/or common environment not already captured by the non-genetic random effects fitted in our models may influence these traits.
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Affiliation(s)
- Caelinn James
- Institute of Ecology and Evolution, School of Biological Sciences, The University of Edinburgh, Edinburgh, UK.
- Scotland's Rural College (SRUC), The Roslin Institute Building, Easter Bush, Midlothian, UK.
| | - Josephine M Pemberton
- Institute of Ecology and Evolution, School of Biological Sciences, The University of Edinburgh, Edinburgh, UK
| | - Pau Navarro
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, UK
| | - Sara Knott
- Institute of Ecology and Evolution, School of Biological Sciences, The University of Edinburgh, Edinburgh, UK
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88
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Hesping E, Boddey JA. Whole- genome CRISPR screens to understand Apicomplexan-host interactions. Mol Microbiol 2024; 121:717-726. [PMID: 38225194 DOI: 10.1111/mmi.15221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 12/13/2023] [Accepted: 12/17/2023] [Indexed: 01/17/2024]
Abstract
Apicomplexan parasites are aetiological agents of numerous diseases in humans and livestock. Functional genomics studies in these parasites enable the identification of biological mechanisms and protein functions that can be targeted for therapeutic intervention. Recent improvements in forward genetics and whole-genome screens utilising CRISPR/Cas technology have revolutionised the functional analysis of genes during Apicomplexan infection of host cells. Here, we highlight key discoveries from CRISPR/Cas9 screens in Apicomplexa or their infected host cells and discuss remaining challenges to maximise this technology that may help answer fundamental questions about parasite-host interactions.
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Affiliation(s)
- Eva Hesping
- Infectious Diseases and Immune Defence Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia
| | - Justin A Boddey
- Infectious Diseases and Immune Defence Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia
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89
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Dias MS, Pedrosa VB, Rocha da Cruz VA, Silva MR, Batista Pinto LF. Genome-wide association and functional annotation analysis for the calving interval in Nellore cattle. Theriogenology 2024; 218:214-222. [PMID: 38350227 DOI: 10.1016/j.theriogenology.2024.01.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 01/24/2024] [Accepted: 01/25/2024] [Indexed: 02/15/2024]
Abstract
Calving interval (CI) measures the number of days between two consecutive calves of the same cow, and previous studies based on phenotype and pedigree data reported low heritability for this trait. However, the genetic architecture of CI in the Nellore breed was not evaluated based on genomic data. Thus, this study aimed to estimate the heritability based on genomic data and carry out a genome-wide association study (GWAS) for CI in the Nellore breed, using 12,599 pedigree records, 5078 CI records, and 3818 animals genotyped with 50k SNPchip panel. Both quality control and GWAS were performed in BLUPF90 family packages, which use the single-step genomic best linear unbiased predictor (ssGBLUP) method. The average CI was 427.6 days, with a standard deviation of 106.9 and a total range of 270-730 days. The heritability estimate was 0.04 ± 0.04. The p-values of GWAS analysis resulted in a genomic inflation factor (lambda) of 1.08. The only significant SNP (rs136725686) at the genome-wide level (p-value = 1.53E-06) was located on BTA13. Other 19 SNPs were significant at the chromosome-wide level, distributed on BTA1, 2, 3, 6, 10, 13, 14, 17, 18, 22, and 26. Functional annotation analysis found thirty-six protein-coding genes, including genes related to cell cycle (RAD21, BCAR3), oocyte function (LHX8, CLPX, UTP23), immune system (TXK, TEC, NFATC2), endocrine function (LRRFIP2, GPR158), estrous cycle (SLC38A7), and female fertility (CCK, LYZL4, TRAK1, FOXP1, STAC). Therefore, CI is a complex trait with small heritability in Nellore cattle, and various biological processes may be involved with the genetic architecture of CI in Nellore cattle.
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Affiliation(s)
- Mayra Silva Dias
- Federal University of Bahia, Animal Science Department, Av. Milton Santos, 500, Ondina, Salvador, BA, 40170-110, Brazil.
| | | | | | - Marcio Ribeiro Silva
- Melhore Animal and Katayama Agropecuaria Lda, Guararapes, SP, 16700-000, Brazil.
| | - Luis Fernando Batista Pinto
- Federal University of Bahia, Animal Science Department, Av. Milton Santos, 500, Ondina, Salvador, BA, 40170-110, Brazil.
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90
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Nieuwenhuis R, Hesselink T, van den Broeck HC, Cordewener J, Schijlen E, Bakker L, Diaz Trivino S, Struss D, de Hoop SJ, de Jong H, Peters SA. Genome architecture and genetic diversity of allopolyploid okra (Abelmoschus esculentus). Plant J 2024; 118:225-241. [PMID: 38133904 DOI: 10.1111/tpj.16602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 10/17/2023] [Accepted: 12/06/2023] [Indexed: 12/23/2023]
Abstract
The allopolyploid okra (Abelmoschus esculentus) unveiled telomeric repeats flanking distal gene-rich regions and short interstitial TTTAGGG telomeric repeats, possibly representing hallmarks of chromosomal speciation. Ribosomal RNA (rRNA) genes organize into 5S clusters, distinct from the 18S-5.8S-28S units, indicating an S-type rRNA gene arrangement. The assembly, in line with cytogenetic and cytometry observations, identifies 65 chromosomes and a 1.45 Gb genome size estimate in a haploid sibling. The lack of aberrant meiotic configurations implies limited to no recombination among sub-genomes. k-mer distribution analysis reveals 75% has a diploid nature and 15% heterozygosity. The configurations of Benchmarking Universal Single-Copy Ortholog (BUSCO), k-mer, and repeat clustering point to the presence of at least two sub-genomes one with 30 and the other with 35 chromosomes, indicating the allopolyploid nature of the okra genome. Over 130 000 putative genes, derived from mapped IsoSeq data and transcriptome data from public okra accessions, exhibit a low genetic diversity of one single nucleotide polymorphisms per 2.1 kbp. The genes are predominantly located at the distal chromosome ends, declining toward central scaffold domains. Long terminal repeat retrotransposons prevail in central domains, consistent with the observed pericentromeric heterochromatin and distal euchromatin. Disparities in paralogous gene counts suggest potential sub-genome differentiation implying possible sub-genome dominance. Amino acid query sequences of putative genes facilitated phenol biosynthesis pathway annotation. Comparison with manually curated reference KEGG pathways from related Malvaceae species reveals the genetic basis for putative enzyme coding genes that likely enable metabolic reactions involved in the biosynthesis of dietary and therapeutic compounds in okra.
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Affiliation(s)
- Ronald Nieuwenhuis
- Business Unit of Bioscience, Cluster Applied Bioinformatics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Thamara Hesselink
- Business Unit of Bioscience, Cluster Applied Bioinformatics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Hetty C van den Broeck
- Business Unit of Bioscience, Cluster Applied Bioinformatics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Jan Cordewener
- Business Unit of Bioscience, Cluster Applied Bioinformatics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Elio Schijlen
- Business Unit of Bioscience, Cluster Applied Bioinformatics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Linda Bakker
- Business Unit of Bioscience, Cluster Applied Bioinformatics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Sara Diaz Trivino
- Business Unit of Bioscience, Cluster Applied Bioinformatics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Darush Struss
- East-West International B.V., Heiligeweg 18, 1601 PN, Enkhuizen, The Netherlands
| | - Simon-Jan de Hoop
- East-West International B.V., Heiligeweg 18, 1601 PN, Enkhuizen, The Netherlands
| | - Hans de Jong
- Laboratory of Genetics, Wageningen University, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
| | - Sander A Peters
- Business Unit of Bioscience, Cluster Applied Bioinformatics, Wageningen University and Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands
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91
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Bohutínská M, Peichel CL. Divergence time shapes gene reuse during repeated adaptation. Trends Ecol Evol 2024; 39:396-407. [PMID: 38155043 DOI: 10.1016/j.tree.2023.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 11/15/2023] [Accepted: 11/20/2023] [Indexed: 12/30/2023]
Abstract
When diverse lineages repeatedly adapt to similar environmental challenges, the extent to which the same genes are involved (gene reuse) varies across systems. We propose that divergence time among lineages is a key factor driving this variability: as lineages diverge, the extent of gene reuse should decrease due to reductions in allele sharing, functional differentiation among genes, and restructuring of genome architecture. Indeed, we show that many genomic studies of repeated adaptation find that more recently diverged lineages exhibit higher gene reuse during repeated adaptation, but the relationship becomes less clear at older divergence time scales. Thus, future research should explore the factors shaping gene reuse and their interplay across broad divergence time scales for a deeper understanding of evolutionary repeatability.
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Affiliation(s)
- Magdalena Bohutínská
- Division of Evolutionary Ecology, Institute of Ecology and Evolution, University of Bern, Bern, 3012, Switzerland; Department of Botany, Faculty of Science, Charles University, Prague, 12800, Czech Republic.
| | - Catherine L Peichel
- Division of Evolutionary Ecology, Institute of Ecology and Evolution, University of Bern, Bern, 3012, Switzerland
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92
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Martinet KM, Harmon LJ. Delimiting the rare, endangered and actively speciating. Mol Ecol Resour 2024; 24:e13938. [PMID: 38409662 DOI: 10.1111/1755-0998.13938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 01/23/2024] [Accepted: 02/05/2024] [Indexed: 02/28/2024]
Abstract
Species delimitation is a contentious topic. The genomics revolution initially brought hope that identifying and classifying species would be easier through better methods and more data, but genomics has also brought complexity and controversy to delimitation. One solution can be to collect a larger sample of individuals at a finer geographic scale. But what if taxa are rare and collecting more samples is difficult or detrimental to the organisms at hand? In this issue of Molecular Ecology Resources, Opatova et al. (2023) tackle the ambiguity of species delimitation in rare and endangered trapdoor spiders (genus Cyclocosmia). The authors propose a framework for delimiting species when samples are hard to come by, such as in these rare and cryptic spiders. The authors combine extensive genomic sampling with statistical approaches that consider both the genetic distinctiveness of each population of spiders and how much gene flow occurs between these populations. Their proposed taxonomy balances two opposing signals, structure and gene flow, to count eight lineages of Cyclocosmia, and to point the way for future taxonomic studies of the rare or difficult to obtain.
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Affiliation(s)
- Kristen M Martinet
- Department of Biological Sciences, University of Idaho, Moscow, Idaho, USA
| | - Luke J Harmon
- Department of Biological Sciences, University of Idaho, Moscow, Idaho, USA
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93
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Negro A, Cesarani A, Cortellari M, Bionda A, Fresi P, Macciotta NPP, Grande S, Biffani S, Crepaldi P. A comparison of genetic and genomic breeding values in Saanen and Alpine goats. Animal 2024; 18:101118. [PMID: 38508133 DOI: 10.1016/j.animal.2024.101118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 02/17/2024] [Accepted: 02/20/2024] [Indexed: 03/22/2024] Open
Abstract
Nowadays, several countries are developing or adopting genomic selection in the dairy goat sector. The most used method to estimate breeding values is Single-Step Genomic Best Linear Unbiased Prediction (ssGBLUP) which offers several advantages in terms of computational process and accuracy of the estimated breeding values (EBVs). Saanen and Alpine are the predominant dairy goat breeds in Italy, and both have similar breeding programs where EBVs for productive traits are currently calculated using BLUP. This work describes the implementation of genomic selection for these two breeds in Italy, aligning with the selection practices already carried out in the international landscape. The available dataset included 3 611 genotyped animals, 11 470 lactation records, five traits (milk, protein and fat yields, and fat and protein percentages), and three-generation pedigrees. EBVs were estimated using BLUP, GBLUP, and ssGBLUP both with single and multiple trait approaches. The methods were compared in terms of correlation between EBVs and genetic trends. Results were also validated with the linear regression method excluding part of the phenotypic data. In both breeds, EBVs and GEBVs were strongly correlated and the trend of each trait was similar comparing the three methods. The average increase in accuracy across traits and methods amounted to +13 and +10% from BLUP to ssGBLUP for Alpine and Saanen breeds, respectively. Results indicated higher prediction accuracy and correlation for GBLUP and ssGBLUP compared to BLUP, implying that the use of genotypes increases the accuracy of EBVs, particularly in the absence of phenotypic data. Therefore, ssGBLUP is likely to be the most effective method to enhance genetic gain in Italian Saanen and Alpine goats.
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Affiliation(s)
- A Negro
- Ufficio Studi, Associazione Nazionale della Pastorizia, 00187 Rome, Italy; Dipartimento di Scienze Agrarie e alimentari, Università degli studi di Milano, 20133 Milan, Italy
| | - A Cesarani
- Dipartimento di Scienze Agrarie, Università degli Studi di Sassari, 07100 Sassari, Italy; Department of Animal and Dairy Science, University of Georgia, Athens, GA, USA
| | - M Cortellari
- Dipartimento di Scienze Agrarie e alimentari, Università degli studi di Milano, 20133 Milan, Italy
| | - A Bionda
- Dipartimento di Scienze Agrarie e alimentari, Università degli studi di Milano, 20133 Milan, Italy.
| | - P Fresi
- Ufficio Studi, Associazione Nazionale della Pastorizia, 00187 Rome, Italy
| | - N P P Macciotta
- Dipartimento di Scienze Agrarie, Università degli Studi di Sassari, 07100 Sassari, Italy
| | - S Grande
- Ufficio Studi, Associazione Nazionale della Pastorizia, 00187 Rome, Italy
| | - S Biffani
- Istituto di Biologia e Biotecnologia, Consiglio Nazionale delle Ricerche, 20133 Milan, Italy
| | - P Crepaldi
- Dipartimento di Scienze Agrarie e alimentari, Università degli studi di Milano, 20133 Milan, Italy
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94
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Garg KM, Gwee CY, Chattopadhyay B, Ng NS, Prawiradilaga DM, David G, Fuchs J, Hung Le Manh, Martinez J, Olsson U, Vuong Tan Tu, Chhin S, Alström P, Lei F, Rheindt FE. When colors mislead: Genomics and bioacoustics prompt re-classification of Asian flycatcher radiation (Aves: Niltavinae). Mol Phylogenet Evol 2024; 193:107999. [PMID: 38160993 DOI: 10.1016/j.ympev.2023.107999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 11/10/2023] [Accepted: 12/25/2023] [Indexed: 01/03/2024]
Abstract
Traditional classification of many animals, including birds, has been highly dependent on external morphological characters like plumage coloration. However, both bioacoustics and genetic or genomic data have revolutionized our understanding of the relationships of certain lineages and led to sweeping taxonomic re-organizations. In this study, we present a case of erroneous delimitation of genus boundaries in the species-rich flycatcher subfamily Niltavinae. Genera within this subfamily have historically been delineated based on blue versus brown male body plumage until recent studies based on a few mitochondrial and nuclear loci unearthed several cases of generic misclassification. Here we use extensive bioacoustic data from 43 species and genomic data from 28 species for a fundamental reclassification of species in the Niltavinae. Our study reveals that song is an important trait to classify these birds even at the genus level, whereas plumage traits exhibit ample convergence and have led to numerous historic misattributions. Our taxonomic re-organization leads to new biogeographic limits of major genera, such that the genus Cyornis now only extends as far east as the islands of Sulawesi, Sula, and Banggai, whereas Eumyias is redefined to extend far beyond Wallace's Line to the islands of Seram and Timor. Our conclusions advise against an over-reliance on morphological traits and underscore the importance of integrative datasets.
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Affiliation(s)
- Kritika M Garg
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore; Centre for Interdisciplinary Archaeological Research, Ashoka University, Sonipat, India; Department of Biology, Ashoka University, Sonipat, India
| | - Chyi Yin Gwee
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore; Division of Evolutionary Biology, Faculty of Biology, LMU Munich, Munich, Germany
| | - Balaji Chattopadhyay
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore; Department of Biology, Ashoka University, Sonipat, India; Trivedi School of Biosciences, Ashoka University, Sonipat, India
| | - Nathaniel S Ng
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Dewi M Prawiradilaga
- Research Center for Biosystematics and Evolution, National Research and Innovation Agency (BRIN), Bogor-Cibinong, West Java, Indonesia
| | - Gabriel David
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore; Animal Ecology, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden; Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing, China
| | - Jérôme Fuchs
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum National d'Histoire Naturelle, CNRS, 22 S U, EPHE, UA CP51, Paris, France
| | - Hung Le Manh
- Institute of Ecology and Biological Resources, Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | | | - Urban Olsson
- Systematics and Biodiversity, Department of Biology and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden; Gothenburg Global Biodiversity Center, Göteborg, Sweden
| | - Vuong Tan Tu
- Institute of Ecology and Biological Resources, Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
| | - Sophea Chhin
- Department of Biodiversity, General Directorate of Policy and Strategy, Ministry of Environment, Phnom Penh, Cambodia
| | - Per Alström
- Animal Ecology, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18D, SE-752 36 Uppsala, Sweden; Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Fumin Lei
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Frank E Rheindt
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore.
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95
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Peng W, Gao M, Zhu X, Liu X, Yang G, Li S, Liu Y, Bai L, Yang J, Bao J. Visual screening of CRISPR/Cas9 editing efficiency based on micropattern arrays for editing porcine cells. Biotechnol J 2024; 19:e2300691. [PMID: 38622798 DOI: 10.1002/biot.202300691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 03/13/2024] [Accepted: 03/19/2024] [Indexed: 04/17/2024]
Abstract
CRISPR/Cas9 technology, combined with somatic cell nuclear transplantation (SCNT), represents the primary approach to generating gene-edited pigs. The inefficiency in acquiring gene-edited nuclear donors is attributed to low editing and delivery efficiency, both closely linked to the selection of CRISPR/Cas9 forms. However, there is currently no direct method to evaluate the efficiency of CRISPR/Cas9 editing in porcine genomes. A platform based on fluorescence reporting signals and micropattern arrays was developed in this study, to visually assess the efficiency of gene editing. The optimal specifications for culturing porcine cells, determined by the quantity and state of cells grown on micropattern arrays, were a diameter of 200 µm and a spacing of 150 µm. By visualizing the area of fluorescence loss and measuring the gray value of the micropattern arrays, it was quickly determined that the mRNA form targeting porcine cells exhibited the highest editing efficiency compared to DNA and Ribonucleoprotein (RNP) forms of CRISPR/Cas9. Subsequently, four homozygotes of the β4GalNT2 gene knockout were successfully obtained through the mRNA form, laying the groundwork for the subsequent generation of gene-edited pigs. This platform facilitates a quick, simple, and effective evaluation of gene knockout efficiency. Additionally, it holds significant potential for swiftly testing novel gene editing tools, assessing delivery methods, and tailoring evaluation platforms for various cell types.
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Affiliation(s)
- Wanliu Peng
- Department of Pathology, Institute of Clinical Pathology, Key Laboratory of Transplant Engineering and Immunology, NHC, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Mengyu Gao
- Department of Pathology, Institute of Clinical Pathology, Key Laboratory of Transplant Engineering and Immunology, NHC, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xinglong Zhu
- Department of Pathology, Institute of Clinical Pathology, Key Laboratory of Transplant Engineering and Immunology, NHC, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xinmei Liu
- Department of Pathology, Institute of Clinical Pathology, Key Laboratory of Transplant Engineering and Immunology, NHC, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Guang Yang
- Experimental Animal Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Shun Li
- Department of Biophysics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Yong Liu
- Department of Plastic and Burn Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lang Bai
- Center of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jiayin Yang
- Transplant Center, Key Laboratory of Transplant Engineering and Immunology, NHC, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ji Bao
- Department of Pathology, Institute of Clinical Pathology, Key Laboratory of Transplant Engineering and Immunology, NHC, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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96
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Ma KY, Song JJ, Li DP, Wu Y, Wang CH, Liu ZL, Li TT, Ma YJ. Genomic structure analysis and construction of DNA fingerprint for four sheep populations. Animal 2024; 18:101116. [PMID: 38484632 DOI: 10.1016/j.animal.2024.101116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 02/16/2024] [Accepted: 02/16/2024] [Indexed: 04/20/2024] Open
Abstract
The Yongdeng Qishan sheep (QS) is a sheep population found locally in China. To gain in-depth knowledge of its population characteristics, three control groups were chosen, comprising the Lanzhou fat-tailed sheep (LFT), TAN sheep (TAN), and Minxian black fur sheep (MBF), inhabiting the nearby environments. This study genotyped a total of 120 individuals from four sheep populations: QS, LFT, TAN, and MBF. Using Specific-Locus Amplified Fragment Sequencing, we conducted genetic diversity, population structure, and selective sweep analysis, and constructed the fingerprint of each population. In total, there were 782 535 single nucleotide polymorphism (SNP) variations identified, with most being situated within regions that are intergenic or intronic. The genetic diversity analysis revealed that the QS population exhibited lower genetic diversity compared to the other three populations. Consistent results were obtained from the principal component, phylogenetic tree, and population structure analysis, indicating significant genetic differences between QS and the other three populations. However, a certain degree of differentiation was observed within the QS population. The linkage disequilibrium (LD) patterns among the four populations showed clear distinctions, with the QS group demonstrating the most rapid LD decline. Kinship analysis supported the findings of population structure, dividing the 90 QS individuals into two subgroups consisting of 23 and 67 individuals. Selective sweep analysis identified a range of genes associated with reproduction, immunity, and adaptation to high-altitude hypoxia. These genes hold potential as candidate genes for marker-assisted selection breeding. Additionally, a total of 86 523 runs of homozygosity (ROHs) were detected, showing non-uniform distribution across chromosomes, with chromosome 1 having the highest coverage percentage and chromosome 26 the lowest. In the high-frequency ROH islands, 79 candidate genes were associated with biological processes such as reproduction and fat digestion and absorption. Furthermore, a DNA fingerprint was constructed for the four populations using 349 highly polymorphic SNPs. In summary, our research delves into the genetic diversity and population structure of QS population. The construction of DNA fingerprint profiles for each population can provide valuable references for the identification of sheep breeds both domestically and internationally.
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Affiliation(s)
- Ke-Yan Ma
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Juan-Juan Song
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Deng-Pan Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Yi Wu
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Chun-Hui Wang
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Zi-Long Liu
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - Tao-Tao Li
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China
| | - You-Ji Ma
- College of Animal Science and Technology, Gansu Agricultural University, Lanzhou 730070, China; Gansu Key Laboratory of Animal Generational Physiology and Reproductive Regulation, Lanzhou 730070, China.
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97
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Yao D, Tycko J, Oh JW, Bounds LR, Gosai SJ, Lataniotis L, Mackay-Smith A, Doughty BR, Gabdank I, Schmidt H, Guerrero-Altamirano T, Siklenka K, Guo K, White AD, Youngworth I, Andreeva K, Ren X, Barrera A, Luo Y, Yardımcı GG, Tewhey R, Kundaje A, Greenleaf WJ, Sabeti PC, Leslie C, Pritykin Y, Moore JE, Beer MA, Gersbach CA, Reddy TE, Shen Y, Engreitz JM, Bassik MC, Reilly SK. Multicenter integrated analysis of noncoding CRISPRi screens. Nat Methods 2024; 21:723-734. [PMID: 38504114 PMCID: PMC11009116 DOI: 10.1038/s41592-024-02216-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 02/18/2024] [Indexed: 03/21/2024]
Abstract
The ENCODE Consortium's efforts to annotate noncoding cis-regulatory elements (CREs) have advanced our understanding of gene regulatory landscapes. Pooled, noncoding CRISPR screens offer a systematic approach to investigate cis-regulatory mechanisms. The ENCODE4 Functional Characterization Centers conducted 108 screens in human cell lines, comprising >540,000 perturbations across 24.85 megabases of the genome. Using 332 functionally confirmed CRE-gene links in K562 cells, we established guidelines for screening endogenous noncoding elements with CRISPR interference (CRISPRi), including accurate detection of CREs that exhibit variable, often low, transcriptional effects. Benchmarking five screen analysis tools, we find that CASA produces the most conservative CRE calls and is robust to artifacts of low-specificity single guide RNAs. We uncover a subtle DNA strand bias for CRISPRi in transcribed regions with implications for screen design and analysis. Together, we provide an accessible data resource, predesigned single guide RNAs for targeting 3,275,697 ENCODE SCREEN candidate CREs with CRISPRi and screening guidelines to accelerate functional characterization of the noncoding genome.
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Affiliation(s)
- David Yao
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Josh Tycko
- Department of Genetics, Stanford University, Stanford, CA, USA.
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
| | - Jin Woo Oh
- Departments of Biomedical Engineering and Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Lexi R Bounds
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
| | - Sager J Gosai
- Broad Institute of Harvard & MIT, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Center for System Biology, Harvard University, Cambridge, MA, USA
- Harvard Graduate Program in Biological and Biomedical Science, Boston, MA, USA
| | - Lazaros Lataniotis
- Department of Neurology, Institute for Human Genetics, University of California, San Franscisco, San Francisco, CA, USA
| | - Ava Mackay-Smith
- University Program in Genetics and Genomics, Duke University School of Medicine, Durham, NC, USA
| | | | - Idan Gabdank
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Henri Schmidt
- Department of Computer Science, Princeton University, Princeton, NJ, USA
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Tania Guerrero-Altamirano
- University Program in Genetics and Genomics, Duke University School of Medicine, Durham, NC, USA
- Department of Biology, Duke University, Durham, NC, USA
| | - Keith Siklenka
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA
| | - Katherine Guo
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Alexander D White
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | | | - Kalina Andreeva
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Xingjie Ren
- Department of Neurology, Institute for Human Genetics, University of California, San Franscisco, San Francisco, CA, USA
| | - Alejandro Barrera
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA
| | - Yunhai Luo
- Department of Genetics, Stanford University, Stanford, CA, USA
| | | | | | - Anshul Kundaje
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - William J Greenleaf
- Department of Genetics, Stanford University, Stanford, CA, USA
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Pardis C Sabeti
- Broad Institute of Harvard & MIT, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Center for System Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Immunology and Infectious Disease, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Christina Leslie
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yuri Pritykin
- Department of Computer Science, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Jill E Moore
- Program in Bioinformatics and Integrative Biology, RNA Therapeutics Institute, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Michael A Beer
- Departments of Biomedical Engineering and Genetic Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Charles A Gersbach
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
| | - Timothy E Reddy
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA
| | - Yin Shen
- Department of Neurology, Institute for Human Genetics, University of California, San Franscisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Jesse M Engreitz
- Department of Genetics, Stanford University, Stanford, CA, USA
- BASE Initiative, Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford, CA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Steven K Reilly
- Department of Genetics, Yale University, New Haven, CT, USA.
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98
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Abkallo HM, Arbuthnot P, Auer TO, Berger DK, Burger J, Chakauya E, Concordet JP, Diabate A, Di Donato V, Groenewald JH, Guindo A, Koekemoer LL, Nazare F, Nolan T, Okumu F, Orefuwa E, Paemka L, Prieto-Godino L, Runo S, Sadler M, Tesfaye K, Tripathi L, Wondji C. Making genome editing a success story in Africa. Nat Biotechnol 2024; 42:551-554. [PMID: 38504013 DOI: 10.1038/s41587-024-02187-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Affiliation(s)
| | - Patrick Arbuthnot
- Wits/SAMRC Antiviral Gene Therapy Research Unit, Infectious Diseases and Oncology Research Institute, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Thomas O Auer
- Department of Biology, Faculty of Science and Medicine, University Fribourg, Fribourg, Switzerland.
- TReND in Africa, Brighton, UK.
| | - Dave K Berger
- Department of Plant and Soil Sciences, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, South Africa
| | - Johan Burger
- Department of Genetics, Stellenbosch University, Stellenbosch, South Africa
| | - Ereck Chakauya
- Food Security and Safety Focus Area, Faculty of Natural and Agricultural Sciences, North-West University, Mmabatho, South Africa.
- AUDA NEPAD Southern Africa Network for Biosciences (SANBio), Council for Scientific and Industrial Research, Advanced Agriculture and Food Cluster (AAF), Pretoria, South Africa.
| | | | - Abdoulaye Diabate
- Institut de recherche en sciences de la santé (IRSS), Bobo Dioulasso, Burkina Faso
| | - Vincenzo Di Donato
- TReND in Africa, Brighton, UK.
- ZeClinics SL. Sant Feliu de Llobregat, Barcelona, Spain.
| | | | - Amadou Guindo
- African Center for Excellence in Molecular Engineering, Bamako, Mali
| | - Lizette L Koekemoer
- Wits Research Institute for Malaria, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Florence Nazare
- African Union Development Agency - NEPAD, Midrand, South Africa
| | - Tony Nolan
- Liverpool School of Tropical Medicine, Liverpool, UK
| | - Fredros Okumu
- Ifakara Health Institute, Ifakara, Tanzania
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, UK
| | - Emma Orefuwa
- Pan-African Mosquito Association, (PAMCA), KEMRI Headquarters, Nairobi, Kenya
| | - Lily Paemka
- University of Ghana, Biochemistry, Cell and Molecular Biology Department, Accra, Ghana
| | | | - Steven Runo
- Department of Biochemistry, Microbiology and Biotechnology Kenyatta University, Nairobi, Kenya
| | - Marie Sadler
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Kassahun Tesfaye
- Bio and Emerging Technology Institute, Addis Ababa, Ethiopia
- Department of Microbial, Cellular and Molecular Biology, Addis Ababa University, Addis Ababa, Ethiopia
| | - Leena Tripathi
- International Institute of Tropical Agriculture (IITA), Nairobi, Kenya
| | - Charles Wondji
- Liverpool School of Tropical Medicine, Liverpool, UK
- Centre for Research in Infectious Diseases, CRID, Yaoundé, Cameroon
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99
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Wright CJ, Stevens L, Mackintosh A, Lawniczak M, Blaxter M. Comparative genomics reveals the dynamics of chromosome evolution in Lepidoptera. Nat Ecol Evol 2024; 8:777-790. [PMID: 38383850 PMCID: PMC11009112 DOI: 10.1038/s41559-024-02329-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 01/12/2024] [Indexed: 02/23/2024]
Abstract
Chromosomes are a central unit of genome organization. One-tenth of all described species on Earth are butterflies and moths, the Lepidoptera, which generally possess 31 chromosomes. However, some species display dramatic variation in chromosome number. Here we analyse 210 chromosomally complete lepidopteran genomes and show that the chromosomes of extant lepidopterans are derived from 32 ancestral linkage groups, which we term Merian elements. Merian elements have remained largely intact through 250 million years of evolution and diversification. Against this stable background, eight lineages have undergone extensive reorganization either through numerous fissions or a combination of fusion and fission events. Outside these lineages, fusions are rare and fissions are rarer still. Fusions often involve small, repeat-rich Merian elements and the sex-linked element. Our results reveal the constraints on genome architecture in Lepidoptera and provide a deeper understanding of chromosomal rearrangements in eukaryotic genome evolution.
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Affiliation(s)
| | - Lewis Stevens
- Tree of Life, Wellcome Sanger Institute, Cambridge, UK
| | | | | | - Mark Blaxter
- Tree of Life, Wellcome Sanger Institute, Cambridge, UK.
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100
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Wirthlin ME, Schmid TA, Elie JE, Zhang X, Kowalczyk A, Redlich R, Shvareva VA, Rakuljic A, Ji MB, Bhat NS, Kaplow IM, Schäffer DE, Lawler AJ, Wang AZ, Phan BN, Annaldasula S, Brown AR, Lu T, Lim BK, Azim E, Clark NL, Meyer WK, Pond SLK, Chikina M, Yartsev MM, Pfenning AR, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements. Science 2024; 383:eabn3263. [PMID: 38422184 DOI: 10.1126/science.abn3263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 02/20/2024] [Indexed: 03/02/2024]
Abstract
Vocal production learning ("vocal learning") is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat (Rousettus aegyptiacus) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.
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Affiliation(s)
- Morgan E Wirthlin
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Tobias A Schmid
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Julie E Elie
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94708, USA
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Xiaomeng Zhang
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Amanda Kowalczyk
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Ruby Redlich
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Varvara A Shvareva
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Ashley Rakuljic
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Maria B Ji
- Department of Psychology, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Ninad S Bhat
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Irene M Kaplow
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Daniel E Schäffer
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Alyssa J Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Andrew Z Wang
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - BaDoi N Phan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Siddharth Annaldasula
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Ashley R Brown
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Tianyu Lu
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Byung Kook Lim
- Neurobiology section, Division of Biological Science, University of California, San Diego, La Jolla, CA 92093, USA
| | - Eiman Azim
- Molecular Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Nathan L Clark
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Wynn K Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | | | - Maria Chikina
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Michael M Yartsev
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94708, USA
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Andreas R Pfenning
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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