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Nayak SS, Panigrahi M, Rajawat D, Ghildiyal K, Sharma A, Jain K, Bhushan B, Dutt T. Deciphering climate resilience in Indian cattle breeds by selection signature analyses. Trop Anim Health Prod 2024; 56:46. [PMID: 38233536 DOI: 10.1007/s11250-023-03879-8] [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: 08/11/2023] [Accepted: 12/07/2023] [Indexed: 01/19/2024]
Abstract
The signature of selection is a crucial concept in evolutionary biology that refers to the pattern of genetic variation which arises in a population due to natural selection. In the context of climate adaptation, the signature of selection can reveal the genetic basis of adaptive traits that enable organisms to survive and thrive in changing environmental conditions. Breeds living in diverse agroecological zones exhibit genetic "footprints" within their genomes that mirror the influence of climate-induced selective pressures, subsequently impacting phenotypic variance. It is assumed that the genomes of animals residing in these regions have been altered through selection for various climatic adaptations. These regions are known as signatures of selection and can be identified using various summary statistics. We examined genotypic data from eight different cattle breeds (Gir, Hariana, Kankrej, Nelore, Ongole, Red Sindhi, Sahiwal, and Tharparkar) that are adapted to diverse regional climates. To identify selection signature regions in this investigation, we used four intra-population statistics: Tajima's D, CLR, iHS, and ROH. In this study, we utilized Bovine 50 K chip data and four genome scan techniques to assess the genetic regions of positive selection for high-temperature adaptation. We have also performed a genome-wide investigation of genetic diversity, inbreeding, and effective population size in our target dataset. We identified potential regions for selection that are likely to be caused by adverse climatic conditions. We observed many adaptation genes in several potential selection signature areas. These include genes like HSPB2, HSPB3, HSP20, HSP90AB1, HSF4, HSPA1B, CLPB, GAP43, MITF, and MCHR1 which have been reported in the cattle populations that live in varied climatic regions. The findings demonstrated that genes involved in disease resistance and thermotolerance were subjected to intense selection. The findings have implications for marker-assisted breeding, understanding the genetic landscape of climate-induced adaptation, putting breeding and conservation programs into action.
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Affiliation(s)
- Sonali Sonejita Nayak
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India.
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Anurodh Sharma
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Karan Jain
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
| | - Triveni Dutt
- Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122, UP, India
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Gao Z. Unveiling recent and ongoing adaptive selection in human populations. PLoS Biol 2024; 22:e3002469. [PMID: 38236800 PMCID: PMC10796035 DOI: 10.1371/journal.pbio.3002469] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2024] Open
Abstract
Genome-wide scans for signals of selection have become a routine part of the analysis of population genomic variation datasets and have resulted in compelling evidence of selection during recent human evolution. This Essay spotlights methodological innovations that have enabled the detection of selection over very recent timescales, even in contemporary human populations. By harnessing large-scale genomic and phenotypic datasets, these new methods use different strategies to uncover connections between genotype, phenotype, and fitness. This Essay outlines the rationale and key findings of each strategy, discusses challenges in interpretation, and describes opportunities to improve detection and understanding of ongoing selection in human populations.
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Affiliation(s)
- Ziyue Gao
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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Panigrahi M, Rajawat D, Nayak SS, Ghildiyal K, Sharma A, Jain K, Lei C, Bhushan B, Mishra BP, Dutt T. Landmarks in the history of selective sweeps. Anim Genet 2023; 54:667-688. [PMID: 37710403 DOI: 10.1111/age.13355] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [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: 05/12/2023] [Accepted: 08/28/2023] [Indexed: 09/16/2023]
Abstract
Half a century ago, a seminal article on the hitchhiking effect by Smith and Haigh inaugurated the concept of the selection signature. Selective sweeps are characterised by the rapid spread of an advantageous genetic variant through a population and hence play an important role in shaping evolution and research on genetic diversity. The process by which a beneficial allele arises and becomes fixed in a population, leading to a increase in the frequency of other linked alleles, is known as genetic hitchhiking or genetic draft. Kimura's neutral theory and hitchhiking theory are complementary, with Kimura's neutral evolution as the 'null model' and positive selection as the 'signal'. Both are widely accepted in evolution, especially with genomics enabling precise measurements. Significant advances in genomic technologies, such as next-generation sequencing, high-density SNP arrays and powerful bioinformatics tools, have made it possible to systematically investigate selection signatures in a variety of species. Although the history of selection signatures is relatively recent, progress has been made in the last two decades, owing to the increasing availability of large-scale genomic data and the development of computational methods. In this review, we embark on a journey through the history of research on selective sweeps, ranging from early theoretical work to recent empirical studies that utilise genomic data.
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Affiliation(s)
- Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | | | - Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Anurodh Sharma
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Karan Jain
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Chuzhao Lei
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Bishnu Prasad Mishra
- Division of Animal Biotechnology, ICAR-National Bureau of Animal Genetic Resources, Karnal, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Bareilly, India
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Chen J, Zhang S, Liu S, Dong J, Cao Y, Sun Y. Single nucleotide polymorphisms (SNPs) and indels identified from whole-genome re-sequencing of four Chinese donkey breeds. Anim Biotechnol 2023; 34:1828-1839. [PMID: 35382683 DOI: 10.1080/10495398.2022.2053145] [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: 11/01/2022]
Abstract
This paper represents the fundamental report of the survey of genome-wide changes of four Chinese indigenous donkey breeds, Dezhou (DZ), Guangling (GL), North China (NC), and Shandong Little donkey (SDL), and the findings will prove usefully for identification of biomarkers that perhaps predict or characterize the growth and coat color patterns. Three genomic regions in CYP3A12, TUBGCP5, and GSTA1 genes, were identified as putative selective sweeps in all researched donkey populations. The loci of candidate genes that may have contributed to the phenotypes in body size (ACSL4, MSI2, ADRA1B, and CDKL5) and coat color patterns (KITLG and TBX3) in donkey populations would be found in underlying strong selection signatures when compared between large and small donkey types, and between different coat colors. The results of the phylogenetic analysis, FST, and principal component analysis (PCA) supported that each population cannot clearly deviate from each other, showing no obvious population structure. We can conclude from the population history that the formation processes between DZS and NC, GL, and SDL are completely different. The genetic variants discovered here provide a rich resource to help identify potential genomic markers and their associated molecular mechanisms that impact economically important traits for Chinese donkey breeding programs.
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Affiliation(s)
- Jianxing Chen
- College of Chemistry and Life Science, Chifeng University, Chifeng, China
- College of Animal Science and Technology, Qingdao Agricultural University, Qingdao, China
| | - Shuer Zhang
- Shandong Animal Husbandry General Station, Jinan, China
| | - Shuqin Liu
- College of Animal Science and Technology, Qingdao Agricultural University, Qingdao, China
| | - Jianbao Dong
- Department of Veterinary Medical Science, Shandong Vocational Animal Science and Veterinary College, Weifang, China
| | - Yanhang Cao
- Modern Animal Husbandry Development Service Center of Dongying, Dongying, China
| | - Yujiang Sun
- College of Animal Science and Technology, Qingdao Agricultural University, Qingdao, China
- Vocational College of Dongying, Dongying, China
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Salazar-Tortosa DF, Huang YF, Enard D. Assessing the Presence of Recent Adaptation in the Human Genome With Mixture Density Regression. Genome Biol Evol 2023; 15:evad170. [PMID: 37713622 PMCID: PMC10563788 DOI: 10.1093/gbe/evad170] [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: 03/18/2023] [Revised: 08/30/2023] [Accepted: 09/04/2023] [Indexed: 09/17/2023] Open
Abstract
How much genome differences between species reflect neutral or adaptive evolution is a central question in evolutionary genomics. In humans and other mammals, the presence of adaptive versus neutral genomic evolution has proven particularly difficult to quantify. The difficulty notably stems from the highly heterogeneous organization of mammalian genomes at multiple levels (functional sequence density, recombination, etc.) which complicates the interpretation and distinction of adaptive versus neutral evolution signals. In this study, we introduce mixture density regressions (MDRs) for the study of the determinants of recent adaptation in the human genome. MDRs provide a flexible regression model based on multiple Gaussian distributions. We use MDRs to model the association between recent selection signals and multiple genomic factors likely to affect the occurrence/detection of positive selection, if the latter was present in the first place to generate these associations. We find that an MDR model with two Gaussian distributions provides an excellent fit to the genome-wide distribution of a common sweep summary statistic (integrated haplotype score), with one of the two distributions likely enriched in positive selection. We further find several factors associated with signals of recent adaptation, including the recombination rate, the density of regulatory elements in immune cells, GC content, gene expression in immune cells, the density of mammal-wide conserved elements, and the distance to the nearest virus-interacting gene. These results support the presence of strong positive selection in recent human evolution and highlight MDRs as a powerful tool to make sense of signals of recent genomic adaptation.
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Affiliation(s)
- Diego F Salazar-Tortosa
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, USA
- Department of Ecology, University of Granada, Granada, Spain
| | - Yi-Fei Huang
- Department of Biology, Pennsylvania State University, University Park, State College, Pennsylvania, PA 16801, USA
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, State College, Pennsylvania, PA 16801, USA
| | - David Enard
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, USA
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Liu X, Matsunami M, Horikoshi M, Ito S, Ishikawa Y, Suzuki K, Momozawa Y, Niida S, Kimura R, Ozaki K, Maeda S, Imamura M, Terao C. Natural Selection Signatures in the Hondo and Ryukyu Japanese Subpopulations. Mol Biol Evol 2023; 40:msad231. [PMID: 37903429 PMCID: PMC10615566 DOI: 10.1093/molbev/msad231] [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: 03/27/2023] [Revised: 09/20/2023] [Accepted: 10/06/2023] [Indexed: 11/01/2023] Open
Abstract
Natural selection signatures across Japanese subpopulations are under-explored. Here we conducted genome-wide selection scans with 622,926 single nucleotide polymorphisms for 20,366 Japanese individuals, who were recruited from the main-islands of Japanese Archipelago (Hondo) and the Ryukyu Archipelago (Ryukyu), representing two major Japanese subpopulations. The integrated haplotype score (iHS) analysis identified several signals in one or both subpopulations. We found a novel candidate locus at IKZF2, especially in Ryukyu. Significant signals were observed in the major histocompatibility complex region in both subpopulations. The lead variants differed and demonstrated substantial allele frequency differences between Hondo and Ryukyu. The lead variant in Hondo tags HLA-A*33:03-C*14:03-B*44:03-DRB1*13:02-DQB1*06:04-DPB1*04:01, a haplotype specific to Japanese and Korean. While in Ryukyu, the lead variant tags DRB1*15:01-DQB1*06:02, which had been recognized as a genetic risk factor for narcolepsy. In contrast, it is reported to confer protective effects against type 1 diabetes and human T lymphotropic virus type 1-associated myelopathy/tropical spastic paraparesis. The FastSMC analysis identified 8 loci potentially affected by selection within the past 20-150 generations, including 2 novel candidate loci. The analysis also showed differences in selection patterns of ALDH2 between Hondo and Ryukyu, a gene recognized to be specifically targeted by selection in East Asian. In summary, our study provided insights into the selection signatures within the Japanese and nominated potential sources of selection pressure.
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Affiliation(s)
- Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Masatoshi Matsunami
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yuki Ishikawa
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kunihiko Suzuki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shumpei Niida
- Core Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Shiro Maeda
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Minako Imamura
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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Horiuchi A, Masuda K, Shirasawa K, Onoue N, Matsuzaki R, Tao R, Kubo Y, Ushijima K, Akagi T. Genetic basis of lineage-specific evolution of fruit traits in hexaploid persimmon. DNA Res 2023; 30:dsad015. [PMID: 37326063 PMCID: PMC10468310 DOI: 10.1093/dnares/dsad015] [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: 03/08/2023] [Revised: 06/06/2023] [Accepted: 06/13/2023] [Indexed: 06/17/2023] Open
Abstract
Frequent polyploidization events in plants have led to the establishment of many lineage-specific traits representing each species. Little is known about the genetic bases for these specific traits in polyploids, presumably due to plant genomic complexity and their difficulties in applying genetic approaches. Hexaploid Oriental persimmon (Diospyros kaki) has evolved specific fruit characteristics, including wide variations in fruit shapes and astringency. In this study, using whole-genome diploidized/quantitative genotypes from ddRAD-Seq data of 173 persimmon cultivars, we examined their population structures and potential correlations between their structural transitions and variations in nine fruit traits. The population structures of persimmon cultivars were highly randomized and not substantially correlated with the representative fruit traits focused on in this study, except for fruit astringency. With genome-wide association analytic tools considering polyploid alleles, we identified the loci associated with the nine fruit traits; we mainly focused on fruit-shape variations, which have been numerically characterized by principal component analysis of elliptic Fourier descriptors. The genomic regions that putatively underwent selective sweep exhibited no overlap with the loci associated with these persimmon-specific fruit traits. These insights will contribute to understanding the genetic mechanisms by which fruit traits are independently established, possibly due to polyploidization events.
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Affiliation(s)
- Ayano Horiuchi
- Graduate School of Environmental and Life Science, Okayama University, Okayama 700-8530, Japan
| | - Kanae Masuda
- Graduate School of Environmental and Life Science, Okayama University, Okayama 700-8530, Japan
| | | | - Noriyuki Onoue
- Institute of Fruit Tree and Tea Science, NARO, Hiroshima 739-2494, Japan
| | - Ryusuke Matsuzaki
- Institute of Fruit Tree and Tea Science, NARO, Hiroshima 739-2494, Japan
| | - Ryutaro Tao
- Graduate School of Agriculture, Kyoto University, Kyoto 606-8502, Japan
| | - Yasutaka Kubo
- Graduate School of Environmental and Life Science, Okayama University, Okayama 700-8530, Japan
| | - Koichiro Ushijima
- Graduate School of Environmental and Life Science, Okayama University, Okayama 700-8530, Japan
| | - Takashi Akagi
- Graduate School of Environmental and Life Science, Okayama University, Okayama 700-8530, Japan
- Japan Science and Technology Agency (JST), PRESTO, Saitama 332-0012, Japan
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8
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Tanaka T, Hayakawa T, Teshima KM. Power of neutrality tests for detecting natural selection. G3 (Bethesda) 2023; 13:jkad161. [PMID: 37481468 PMCID: PMC10542275 DOI: 10.1093/g3journal/jkad161] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [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: 06/09/2023] [Revised: 06/09/2023] [Accepted: 07/19/2023] [Indexed: 07/24/2023]
Abstract
Detection of natural selection is one of the main interests in population genetics. Thus, many tests have been developed for detecting natural selection using genomic data. Although it is recognized that the utility of tests depends on several evolutionary factors, such as the timing of selection, strength of selection, frequency of selected alleles, demographic events, and initial frequency of selected allele when selection started acting (softness of selection), the relationships between such evolutionary factors and the power of tests are not yet entirely clear. In this study, we investigated the power of 4 tests: Tajiama's D, Fay and Wu's H, relative extended haplotype homozygosity (rEHH), and integrated haplotype score (iHS), under ranges of evolutionary parameters and demographic models to quantitatively expand the understanding of approaches for detecting selection. The results show that each test detects selection within a limited parameter range, and there are still wide ranges of parameters for which none of these tests work effectively. In addition, the parameter space in which each test shows the highest power overlaps the empirical results of previous research. These results indicate that our present perspective of adaptation is limited to only a part of actual adaptation.
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Affiliation(s)
- Tomotaka Tanaka
- Graduate School of System Life Science, Kyushu University, Fukuoka 819-0395, Japan
| | - Toshiyuki Hayakawa
- Graduate School of System Life Science, Kyushu University, Fukuoka 819-0395, Japan
- Faculty of Arts and Science, Kyushu University, Fukuoka 819-0395, Japan
| | - Kosuke M Teshima
- Department of Biology, Faculty of Science, Kyushu University, Fukuoka 819-0395, Japan
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Uppal S, Postnikova O, Villasmil R, Rogozin IB, Bocharov AV, Eggerman TL, Poliakov E, Redmond TM. Low-Density Lipoprotein Receptor (LDLR) Is Involved in Internalization of Lentiviral Particles Pseudotyped with SARS-CoV-2 Spike Protein in Ocular Cells. Int J Mol Sci 2023; 24:11860. [PMID: 37511618 PMCID: PMC10380832 DOI: 10.3390/ijms241411860] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/16/2023] [Accepted: 07/17/2023] [Indexed: 07/30/2023] Open
Abstract
Here, we present evidence that caveolae-mediated endocytosis using LDLR is the pathway for SARS-CoV-2 virus internalization in the ocular cell line ARPE-19. Firstly, we found that, while Angiotensin-converting enzyme 2 (ACE2) is expressed in these cells, blocking ACE2 by antibody treatment did not prevent infection by SARS-CoV-2 spike pseudovirions, nor did antibody blockade of extracellular vimentin and other cholesterol-rich lipid raft proteins. Next, we implicated the role of cholesterol homeostasis in infection by showing that incubating cells with different cyclodextrins and oxysterol 25-hydroxycholesterol (25-HC) inhibits pseudovirion infection of ARPE-19. However, the effect of 25-HC is likely not via cholesterol biosynthesis, as incubation with lovastatin did not appreciably affect infection. Additionally, is it not likely to be an agonistic effect of 25-HC on LXR receptors, as the LXR agonist GW3965 had no significant effect on infection of ARPE-19 cells at up to 5 μM GW3965. We probed the role of endocytic pathways but determined that clathrin-dependent and flotillin-dependent rafts were not involved. Furthermore, 20 µM chlorpromazine, an inhibitor of clathrin-mediated endocytosis (CME), also had little effect. In contrast, anti-dynamin I/II antibodies blocked the entry of SARS-CoV-2 spike pseudovirions, as did dynasore, a noncompetitive inhibitor of dynamin GTPase activity. Additionally, anti-caveolin-1 antibodies significantly blocked spike pseudotyped lentiviral infection of ARPE-19. However, nystatin, a classic inhibitor of caveolae-dependent endocytosis, did not affect infection while indomethacin inhibited only at 10 µM at the 48 h time point. Finally, we found that anti-LDLR antibodies block pseudovirion infection to a similar degree as anti-caveolin-1 and anti-dynamin I/II antibodies, while transfection with LDLR-specific siRNA led to a decrease in spike pseudotyped lentiviral infection, compared to scrambled control siRNAs. Thus, we conclude that SARS-CoV-2 spike pseudovirion infection in ARPE-19 cells is a dynamin-dependent process that is primarily mediated by LDLR.
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Affiliation(s)
- Sheetal Uppal
- Laboratory of Retinal Cell & Molecular Biology, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Olga Postnikova
- Laboratory of Retinal Cell & Molecular Biology, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Rafael Villasmil
- Flow Cytometry Core Facility, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Igor B Rogozin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | | | - Thomas L Eggerman
- Clinical Center, National Institutes of Health, Bethesda, MD 20894, USA
- National Institute of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Eugenia Poliakov
- Laboratory of Retinal Cell & Molecular Biology, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - T Michael Redmond
- Laboratory of Retinal Cell & Molecular Biology, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
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Abstract
BACKGROUND Cancer is a life-threatening disease in humans; yet, cancer genes are frequently reported to be under positive selection. This suggests an evolutionary-genetic paradox in which cancer evolves as a secondary product of selection in human beings. However, systematic investigation of the evolution of cancer driver genes is sparse. RESULTS Using comparative genomics analysis, population genetics analysis and computational molecular evolutionary analysis, the evolution of 568 cancer driver genes of 66 cancer types were evaluated at two levels, selection on the early evolution of humans (long timescale selection in the human lineage during primate evolution, i.e., millions of years), and recent selection in modern human populations (~ 100,000 years). Results showed that eight cancer genes covering 11 cancer types were under positive selection in the human lineage (long timescale selection). And 35 cancer genes covering 47 cancer types were under positive selection in modern human populations (recent selection). Moreover, SNPs associated with thyroid cancer in three thyroid cancer driver genes (CUX1, HERC2 and RGPD3) were under positive selection in East Asian and European populations, consistent with the high incidence of thyroid cancer in these populations. CONCLUSIONS These findings suggest that cancer can be evolved, in part, as a by-product of adaptive changes in humans. Different SNPs at the same locus can be under different selection pressures in different populations, and thus should be under consideration during precision medicine, especially for targeted medicine in specific populations.
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Affiliation(s)
- Langyu Gu
- State Key Laboratory for Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, 510275, China.
| | - Canwei Xia
- Ministry of Education Key Laboratory for Biodiversity and Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing, 100875, China
| | - Shiyu Yang
- The Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou, 510180, Guangdong, China
| | - Guofen Yang
- Department of Gynecology, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510060, Guangdong, China.
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11
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Barroso GV, Lohmueller KE. Inferring the mode and strength of ongoing selection. Genome Res 2023; 33:632-643. [PMID: 37055196 PMCID: PMC10234300 DOI: 10.1101/gr.276386.121] [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: 11/12/2021] [Accepted: 03/29/2023] [Indexed: 04/15/2023]
Abstract
Genome sequence data are no longer scarce. The UK Biobank alone comprises 200,000 individual genomes, with more on the way, leading the field of human genetics toward sequencing entire populations. Within the next decades, other model organisms will follow suit, especially domesticated species such as crops and livestock. Having sequences from most individuals in a population will present new challenges for using these data to improve health and agriculture in the pursuit of a sustainable future. Existing population genetic methods are designed to model hundreds of randomly sampled sequences but are not optimized for extracting the information contained in the larger and richer data sets that are beginning to emerge, with thousands of closely related individuals. Here we develop a new method called trio-based inference of dominance and selection (TIDES) that uses data from tens of thousands of family trios to make inferences about natural selection acting in a single generation. TIDES further improves on the state of the art by making no assumptions regarding demography, linkage, or dominance. We discuss how our method paves the way for studying natural selection from new angles.
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Affiliation(s)
- Gustavo V Barroso
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095-1606, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California 90095, USA
| | - Kirk E Lohmueller
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095-1606, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, California 90095, USA
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12
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Chen J, Wang Y, Qi X, Cheng H, Chen N, Ahmed Z, Chen Q, Lei C, Yang X. Genome-wide analysis emancipates genomic diversity and signature of selection in Altay white-headed cattle of Xinjiang, China. Front Genet 2023; 14:1144249. [PMID: 37065480 PMCID: PMC10098193 DOI: 10.3389/fgene.2023.1144249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 03/17/2023] [Indexed: 04/01/2023] Open
Abstract
Altay white-headed cattle have not received enough attention for several reasons. Due to irrational breeding and selection practices, the number of pure Altay white-headed cattle has decreased significantly and the breed is now on the eve of extinction. The genomic characterization will be a crucial step towards understanding the genetic basis of productivity and adaptability to survival under native Chinese agropastoral systems; nevertheless, no attempt has been made in Altay white-headed cattle. In the current study, we compared the genomes of 20 Altay white-headed cattle to the genomes of 144 individuals in representative breeds. Population genetic diversity revealed that the nucleotide diversity of Altay white-headed cattle was less than that of indicine breeds and comparable to that of Chinese taurus cattle. Using population structure analysis, we also found that Altay white-headed cattle carried the ancestry of the European and East Asian cattle lineage. In addition, we used three different methods (FST, θπ ratio and XP-EHH) to investigate the adaptability and white-headed phenotype of Altay white-headed cattle and compared it with Bohai black cattle. We found EPB41L5, SCG5 and KIT genes on the list of the top one percent genes, these genes might have an association with environmental adaptability and the white-headed phenotype for this breed. Our research reveals the distinctive genomic features of Altay white-headed cattle at the genome-wide level.
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Affiliation(s)
- Jialei Chen
- Life Science College, Luoyang Normal University, Luoyang, China
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Yushu Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Xingshan Qi
- Biyang Xianan Cattle Technology and Development Company Ltd., Biyang, China
| | - Haijian Cheng
- Shandong Key Lab of Animal Disease Control and Breeding, Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan, China
| | - Ningbo Chen
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Zulfiqar Ahmed
- Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, and Key Lab of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
- Faculty of Veterinary and Animal Sciences, University of Poonch Rawalakot, Shabestar, Pakistan
| | - Qiuming Chen
- College of Animal Science, Xinjiang Agricultural University, Urumqi, Xinjiang, China
| | - Chuzhao Lei
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
- *Correspondence: Chuzhao Lei, ; Xueyi Yang,
| | - Xueyi Yang
- Life Science College, Luoyang Normal University, Luoyang, China
- *Correspondence: Chuzhao Lei, ; Xueyi Yang,
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13
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Ghildiyal K, Panigrahi M, Kumar H, Rajawat D, Nayak SS, Lei C, Bhushan B, Dutt T. Selection signatures for fiber production in commercial species: A review. Anim Genet 2023; 54:3-23. [PMID: 36352515 DOI: 10.1111/age.13272] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 10/11/2022] [Accepted: 10/11/2022] [Indexed: 11/11/2022]
Abstract
Natural fibers derived from diverse animal species have gained increased attention in recent years due to their favorable environmental effects, long-term sustainability benefits, and remarkable physical and mechanical properties that make them valuable raw materials used for textile and non-textile production. Domestication and selective breeding for the economically significant fiber traits play an imperative role in shaping the genomes and, thus, positively impact the overall productivity of the various fiber-producing species. These selection pressures leave unique footprints on the genome due to alteration in the allelic frequencies at specific loci, characterizing selective sweeps. Recent advances in genomics have enabled the discovery of selection signatures across the genome using a variety of methods. The increased demand for 'green products' manufactured from natural fibers necessitates a detailed investigation of the genomes of the various fiber-producing plant and animal species to identify the candidate genes associated with important fiber attributes such as fiber diameter/fineness, color, length, and strength, among others. The objective of this review is to present a comprehensive overview of the concept of selection signature and selective sweeps, discuss the main methods used for its detection, and address the selection signature studies conducted so far in the diverse fiber-producing animal species.
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Affiliation(s)
- Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Harshit Kumar
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | | | - Chuzhao Lei
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Bareilly, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Bareilly, India
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14
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Lazareva TE, Barbitoff YA, Changalidis AI, Tkachenko AA, Maksiutenko EM, Nasykhova YA, Glotov AS. Biobanking as a Tool for Genomic Research: From Allele Frequencies to Cross-Ancestry Association Studies. J Pers Med 2022; 12:jpm12122040. [PMID: 36556260 PMCID: PMC9783756 DOI: 10.3390/jpm12122040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/19/2022] [Accepted: 11/28/2022] [Indexed: 12/14/2022] Open
Abstract
In recent years, great advances have been made in the field of collection, storage, and analysis of biological samples. Large collections of samples, biobanks, have been established in many countries. Biobanks typically collect large amounts of biological samples and associated clinical information; the largest collections include over a million samples. In this review, we summarize the main directions in which biobanks aid medical genetics and genomic research, from providing reference allele frequency information to allowing large-scale cross-ancestry meta-analyses. The largest biobanks greatly vary in the size of the collection, and the amount of available phenotype and genotype data. Nevertheless, all of them are extensively used in genomics, providing a rich resource for genome-wide association analysis, genetic epidemiology, and statistical research into the structure, function, and evolution of the human genome. Recently, multiple research efforts were based on trans-biobank data integration, which increases sample size and allows for the identification of robust genetic associations. We provide prominent examples of such data integration and discuss important caveats which have to be taken into account in trans-biobank research.
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Affiliation(s)
- Tatyana E. Lazareva
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
- Department of Genetics and Biotechnology, St. Petersburg State University, 199034 St. Petersburg, Russia
| | - Yury A. Barbitoff
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
- Department of Genetics and Biotechnology, St. Petersburg State University, 199034 St. Petersburg, Russia
- Correspondence: (Y.A.B.); (A.S.G.)
| | - Anton I. Changalidis
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
- Faculty of Software Engineering and Computer Systems, ITMO University, 197101 St. Petersburg, Russia
| | - Alexander A. Tkachenko
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
| | - Evgeniia M. Maksiutenko
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
| | - Yulia A. Nasykhova
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
| | - Andrey S. Glotov
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
- Correspondence: (Y.A.B.); (A.S.G.)
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15
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Souilmi Y, Tobler R, Johar A, Williams M, Grey ST, Schmidt J, Teixeira JC, Rohrlach A, Tuke J, Johnson O, Gower G, Turney C, Cox M, Cooper A, Huber CD. Admixture has obscured signals of historical hard sweeps in humans. Nat Ecol Evol 2022; 6:2003-2015. [PMID: 36316412 PMCID: PMC9715430 DOI: 10.1038/s41559-022-01914-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 09/16/2022] [Indexed: 11/06/2022]
Abstract
The role of natural selection in shaping biological diversity is an area of intense interest in modern biology. To date, studies of positive selection have primarily relied on genomic datasets from contemporary populations, which are susceptible to confounding factors associated with complex and often unknown aspects of population history. In particular, admixture between diverged populations can distort or hide prior selection events in modern genomes, though this process is not explicitly accounted for in most selection studies despite its apparent ubiquity in humans and other species. Through analyses of ancient and modern human genomes, we show that previously reported Holocene-era admixture has masked more than 50 historic hard sweeps in modern European genomes. Our results imply that this canonical mode of selection has probably been underappreciated in the evolutionary history of humans and suggest that our current understanding of the tempo and mode of selection in natural populations may be inaccurate.
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Affiliation(s)
- Yassine Souilmi
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
| | - Raymond Tobler
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
- Evolution of Cultural Diversity Initiative, Australian National University, Canberra, Australian Capital Territory, Australia.
| | - Angad Johar
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA.
| | - Matthew Williams
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Shane T Grey
- Transplantation Immunology Group, Immunology Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- St Vincent's Clinical School, Faculty of Medicine, UNSW, Darlinghurst, New South Wales, Australia
| | - Joshua Schmidt
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - João C Teixeira
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Adam Rohrlach
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, The University of Adelaide, Adelaide, South Australia, Australia
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Jena, Germany
| | - Jonathan Tuke
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, The University of Adelaide, Adelaide, South Australia, Australia
- School of Mathematical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Olivia Johnson
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Graham Gower
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Chris Turney
- Chronos 14Carbon-Cycle Facility and Earth and Sustainability Science Research Centre, University of New South Wales, Sydney, New South Wales, Australia
| | - Murray Cox
- Statistics and Bioinformatics Group, School of Fundamental Sciences, Massey University, Palmerston North, New Zealand
| | - Alan Cooper
- South Australian Museum, Adelaide, South Australia, Australia.
- BlueSky Genetics, Ashton, South Australia, Australia.
| | - Christian D Huber
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
- Department of Biology, Penn State University, University Park, PA, USA.
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16
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Xie HB, Yan C, Adeola AC, Wang K, Huang CP, Xu MM, Qiu Q, Yin X, Fan CY, Ma YF, Yin TT, Gao Y, Deng JK, Okeyoyin AO, Oluwole OO, Omotosho O, Okoro VMO, Omitogun OG, Dawuda PM, Olaogun SC, Nneji LM, Ayoola AO, Sanke OJ, Luka PD, Okoth E, Lekolool I, Mijele D, Bishop RP, Han J, Wang W, Peng MS, Zhang YP. African Suid Genomes Provide Insights into the Local Adaptation to Diverse African Environments. Mol Biol Evol 2022; 39:6840307. [PMID: 36413509 PMCID: PMC9733430 DOI: 10.1093/molbev/msac256] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 10/21/2022] [Accepted: 11/17/2022] [Indexed: 11/23/2022] Open
Abstract
African wild suids consist of several endemic species that represent ancient members of the family Suidae and have colonized diverse habitats on the African continent. However, limited genomic resources for African wild suids hinder our understanding of their evolution and genetic diversity. In this study, we assembled high-quality genomes of a common warthog (Phacochoerus africanus), a red river hog (Potamochoerus porcus), as well as an East Asian Diannan small-ear pig (Sus scrofa). Phylogenetic analysis showed that common warthog and red river hog diverged from their common ancestor around the Miocene/Pliocene boundary, putatively predating their entry into Africa. We detected species-specific selective signals associated with sensory perception and interferon signaling pathways in common warthog and red river hog, respectively, which contributed to their local adaptation to savannah and tropical rainforest environments, respectively. The structural variation and evolving signals in genes involved in T-cell immunity, viral infection, and lymphoid development were identified in their ancestral lineage. Our results provide new insights into the evolutionary histories and divergent genetic adaptations of African suids.
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Affiliation(s)
| | | | | | | | | | - Ming-Min Xu
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China
| | - Qiang Qiu
- School of Ecology and Environment, Northwestern Polytechnical University, Xi’an 710129, China
| | - Xue Yin
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming 650091, China
| | - Chen-Yu Fan
- State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan, School of Life Sciences, Yunnan University, Kunming 650091, China
| | - Yun-Fei Ma
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China
| | - Ting-Ting Yin
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Yun Gao
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Jia-Kun Deng
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
| | - Agboola O Okeyoyin
- National Park Service Headquarter, Federal Capital Territory, Abuja 900108, Nigeria
| | - Olufunke O Oluwole
- Institute of Agricultural Research and Training, Obafemi Awolowo University, Ibadan, Nigeria
| | - Oladipo Omotosho
- Department of Veterinary Medicine, University of Ibadan, Ibadan 200005, Nigeria
| | - Victor M O Okoro
- Department of Animal Science and Technology, School of Agriculture and Agricultural Technology, Federal University of Technology, Owerri 460114, Nigeria
| | - Ofelia G Omitogun
- Department of Animal Sciences, Obafemi Awolowo University, Ile-Ife 220282, Nigeria
| | - Philip M Dawuda
- Department of Veterinary Surgery and Theriogenology, College of Veterinary Medicine, University of Agriculture Makurdi, Makurdi 970001, Nigeria
| | - Sunday C Olaogun
- Department of Veterinary Medicine, University of Ibadan, Ibadan 200005, Nigeria
| | - Lotanna M Nneji
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China,Sino-Africa Joint Research Center, Chinese Academy of Sciences, Kunming 650204, China
| | - Adeola O Ayoola
- State Key Laboratory of Genetic Resources and Evolution & Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, China,Sino-Africa Joint Research Center, Chinese Academy of Sciences, Kunming 650204, China
| | - Oscar J Sanke
- Taraba State Ministry of Agriculture and Natural Resources, Jalingo 660213, Nigeria
| | - Pam D Luka
- National Veterinary Research Institute, Vom 930103, Nigeria
| | - Edward Okoth
- International Livestock Research Institute (ILRI), Nairobi 00100, Kenya
| | | | | | - Richard P Bishop
- International Livestock Research Institute (ILRI), Nairobi 00100, Kenya
| | | | - Wen Wang
- Corresponding authors: E-mails: ; ; ;
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17
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Nikolakis ZL, Adams RH, Wade KJ, Lund AJ, Carlton EJ, Castoe TA, Pollock DD. Prospects for genomic surveillance for selection in schistosome parasites. Front Epidemiol 2022; 2:932021. [PMID: 38455290 PMCID: PMC10910990 DOI: 10.3389/fepid.2022.932021] [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] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 09/12/2022] [Indexed: 03/09/2024]
Abstract
Schistosomiasis is a neglected tropical disease caused by multiple parasitic Schistosoma species, and which impacts over 200 million people globally, mainly in low- and middle-income countries. Genomic surveillance to detect evidence for natural selection in schistosome populations represents an emerging and promising approach to identify and interpret schistosome responses to ongoing control efforts or other environmental factors. Here we review how genomic variation is used to detect selection, how these approaches have been applied to schistosomes, and how future studies to detect selection may be improved. We discuss the theory of genomic analyses to detect selection, identify experimental designs for such analyses, and review studies that have applied these approaches to schistosomes. We then consider the biological characteristics of schistosomes that are expected to respond to selection, particularly those that may be impacted by control programs. Examples include drug resistance, host specificity, and life history traits, and we review our current understanding of specific genes that underlie them in schistosomes. We also discuss how inherent features of schistosome reproduction and demography pose substantial challenges for effective identification of these traits and their genomic bases. We conclude by discussing how genomic surveillance for selection should be designed to improve understanding of schistosome biology, and how the parasite changes in response to selection.
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Affiliation(s)
- Zachary L. Nikolakis
- Department of Biology, University of Texas at Arlington, Arlington, TX, United States
| | - Richard H. Adams
- Department of Biological and Environmental Sciences, Georgia College and State University, Milledgeville, GA, United States
| | - Kristen J. Wade
- Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO, United States
| | - Andrea J. Lund
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado, Anschutz, Aurora, CO, United States
| | - Elizabeth J. Carlton
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado, Anschutz, Aurora, CO, United States
| | - Todd A. Castoe
- Department of Biology, University of Texas at Arlington, Arlington, TX, United States
| | - David D. Pollock
- Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO, United States
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18
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Shi S, Shao D, Yang L, Liang Q, Han W, Xue Q, Qu L, Leng L, Li Y, Zhao X, Dong P, Walugembe M, Kayang BB, Muhairwa AP, Zhou H, Tong H. Whole Genome Analyses Reveal Novel Genes Associated with Chicken Adaptation to Tropical and Frigid Environments. J Adv Res 2022; 47:13-25. [PMID: 35907630 PMCID: PMC10173185 DOI: 10.1016/j.jare.2022.07.005] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 07/01/2022] [Accepted: 07/17/2022] [Indexed: 01/25/2023] Open
Abstract
INTRODUCTION Investigating the genetic footprints of historical temperature selection can get insights to the local adaptation and feasible influences of climate change on long-term population dynamics. OBJECT Chicken is a significative species to study genetic adaptation on account of its similar domestication track related to human activity with the most diversified varieties. Yet, few studies have demonstrated the genetic signatures of its adaptation to naturally tropical and frigid environments. METHOD Here, we generated whole genome resequencing of 119 domesticated chickens in China including the following breeds which are in order of breeding environmental temperature from more tropical to more frigid: Wenchang chicken (WCC), green-shell chicken (GSC), Tibetan chicken (TBC), and Lindian chicken (LDC). RESULTS Our results showed WCC branched off earlier than LDC with an evident genetic admixture between WCC and LDC, suggesting their closer genetic relationship. Further comparative genomic analyses solute carrier family 33 member 1 (SLC33A1) and thyroid stimulating hormone receptor (TSHR) genes exhibited stronger signatures for positive selection in the genome of the more tropical WCC. Furthermore, genotype data from about 3,000 African local ecotypes confirmed that allele frequencies of single nucleotide polymorphisms (SNPs) in these 2 genes appeared strongly associated with tropical environment adaptation. In addition, the NADH:ubiquinone oxidoreductase subunit S4 (NDUFS4) gene exhibited a strong signature for positive selection in the LDC genome, and SNPs with marked allele frequency differences indicated a significant relationship with frigid environment adaptation. CONCLUSION Our findings partially clarify how selection footprints from environmental temperature stress can lead to advantageous genomic adaptions to tropical and frigid environments in poultry and provide a valuable resource for selective breeding of chickens.
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Affiliation(s)
- Shourong Shi
- Poultry Institute, Chinese Academy of Agriculture Science, Yangzhou, Jiangsu 225125, China
| | - Dan Shao
- Poultry Institute, Chinese Academy of Agriculture Science, Yangzhou, Jiangsu 225125, China
| | - Lingyun Yang
- Novogene Bioinformatics Institute, Beijing 10089, China
| | - Qiqi Liang
- Novogene Bioinformatics Institute, Beijing 10089, China
| | - Wei Han
- Poultry Institute, Chinese Academy of Agriculture Science, Yangzhou, Jiangsu 225125, China
| | - Qian Xue
- Poultry Institute, Chinese Academy of Agriculture Science, Yangzhou, Jiangsu 225125, China
| | - Liang Qu
- Poultry Institute, Chinese Academy of Agriculture Science, Yangzhou, Jiangsu 225125, China
| | - Li Leng
- College of Animal Science and technology, Northeast Agricultural University, Harbin, Heilongjiang, 150038, China
| | - Yishu Li
- Tropical Crop Germplasm Research Institute, Haikou, Hainan, 571101, China
| | - Xiaogang Zhao
- Agriculture and Animal Husbandry Rural and Science and Technology Bureau, Xiangcheng County, Ganzi Tibetan Autonomous Prefecture, Sichuan, 626000, China
| | - Ping Dong
- Agriculture and Animal Husbandry Rural and Science and Technology Bureau, Xiangcheng County, Ganzi Tibetan Autonomous Prefecture, Sichuan, 626000, China
| | - Muhammed Walugembe
- Department of Animal Science, Iowa State University, 2255 Kildee Hall, Ames, IA 50011, USA
| | - Boniface B Kayang
- Department of Animal Science, University of Ghana, Legon, Accra 233, Ghana
| | - Amandus P Muhairwa
- Department of Veterinary Medicine and Public Health, College of Veterinary Medicine and Biomedical Sciences, Sokoine University of Agriculture, P.O. Box 3000 Chuo Kikuu, Morogoro, Tanzania
| | - Huaijun Zhou
- Department of Animal Science, College of Agricultural and Environmental Sciences, University of California, Davis, CA 95616, USA
| | - Haibing Tong
- Poultry Institute, Chinese Academy of Agriculture Science, Yangzhou, Jiangsu 225125, China.
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19
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Muralidhar P, Veller C. Dominance shifts increase the likelihood of soft selective sweeps. Evolution 2022; 76:966-984. [PMID: 35213740 PMCID: PMC9928167 DOI: 10.1111/evo.14459] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 02/04/2022] [Indexed: 01/21/2023]
Abstract
Genetic models of adaptation to a new environment have typically assumed that the alleles involved maintain a constant fitness dominance across the old and new environments. However, theories of dominance suggest that this should often not be the case. Instead, the alleles involved should frequently shift from recessive deleterious in the old environment to dominant beneficial in the new environment. Here, we study the consequences of these expected dominance shifts for the genetics of adaptation to a new environment. We find that dominance shifts increase the likelihood that adaptation occurs from standing variation, and that multiple alleles from the standing variation are involved (a soft selective sweep). Furthermore, we find that expected dominance shifts increase the haplotypic diversity of selective sweeps, rendering soft sweeps more detectable in small genomic samples. In cases where an environmental change threatens the viability of the population, we show that expected dominance shifts of newly beneficial alleles increase the likelihood of evolutionary rescue and the number of alleles involved. Finally, we apply our results to a well-studied case of adaptation to a new environment: the evolution of pesticide resistance at the Ace locus in Drosophila melanogaster. We show that, under reasonable demographic assumptions, the expected dominance shift of resistant alleles causes soft sweeps to be the most frequent outcome in this case, with the primary source of these soft sweeps being the standing variation at the onset of pesticide use, rather than recurrent mutation thereafter.
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Affiliation(s)
- Pavitra Muralidhar
- Center for Population Biology, University of California,
Davis, CA 95616,Department of Evolution and Ecology, University of
California, Davis, CA 95616,corresponding author:
| | - Carl Veller
- Center for Population Biology, University of California,
Davis, CA 95616,Department of Evolution and Ecology, University of
California, Davis, CA 95616
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20
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Jagoda E, Xue JR, Reilly SK, Dannemann M, Racimo F, Huerta-Sanchez E, Sankararaman S, Kelso J, Pagani L, Sabeti PC, Capellini TD. Detection of Neanderthal Adaptively Introgressed Genetic Variants That Modulate Reporter Gene Expression in Human Immune Cells. Mol Biol Evol 2022; 39:msab304. [PMID: 34662402 PMCID: PMC8760939 DOI: 10.1093/molbev/msab304] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Although some variation introgressed from Neanderthals has undergone selective sweeps, little is known about its functional significance. We used a Massively Parallel Reporter Assay (MPRA) to assay 5,353 high-frequency introgressed variants for their ability to modulate the gene expression within 170 bp of endogenous sequence. We identified 2,548 variants in active putative cis-regulatory elements (CREs) and 292 expression-modulating variants (emVars). These emVars are predicted to alter the binding motifs of important immune transcription factors, are enriched for associations with neutrophil and white blood cell count, and are associated with the expression of genes that function in innate immune pathways including inflammatory response and antiviral defense. We combined the MPRA data with other data sets to identify strong candidates to be driver variants of positive selection including an emVar that may contribute to protection against severe COVID-19 response. We endogenously deleted two CREs containing expression-modulation variants linked to immune function, rs11624425 and rs80317430, identifying their primary genic targets as ELMSAN1, and PAN2 and STAT2, respectively, three genes differentially expressed during influenza infection. Overall, we present the first database of experimentally identified expression-modulating Neanderthal-introgressed alleles contributing to potential immune response in modern humans.
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Affiliation(s)
- Evelyn Jagoda
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - James R Xue
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Steven K Reilly
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Michael Dannemann
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Fernando Racimo
- Lundbeck GeoGenetics Centre, The Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Emilia Huerta-Sanchez
- Department of Ecology and Evolutionary Biology, Brown University, Providence, RI, USA
- Center for Computational Molecular Biology, Brown University, Providence, RI, USA
| | - Sriram Sankararaman
- Department of Computer Science, UCLA, Los Angeles, CA, USA
- Department of Human Genetics, UCLA, Los Angeles, CA, USA
| | - Janet Kelso
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Luca Pagani
- Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Department of Biology, University of Padova, Padova, Italy
| | - Pardis C Sabeti
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Terence D Capellini
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
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21
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Pathak AK, Sukhavasi K, Marnetto D, Chaubey G, Pandey AK. Human population genomics approach in food metabolism. Future Foods 2022. [DOI: 10.1016/b978-0-323-91001-9.00033-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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22
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Reeve J, Li Q, Lindtke D, Yeaman S. Comparing genome scans among species of the stickleback order reveals three different patterns of genetic diversity. Ecol Evol 2022; 12:e8502. [PMID: 35127027 PMCID: PMC8796908 DOI: 10.1002/ece3.8502] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 12/09/2021] [Accepted: 12/14/2021] [Indexed: 12/03/2022] Open
Abstract
Comparing genome scans among species is a powerful approach for investigating the patterns left by evolutionary processes. In particular, this offers a way to detect candidate genes that drive convergent evolution. We compared genome scan results to investigate if patterns of genetic diversity and divergence are shared among divergent species within the stickleback order (Gasterosteiformes): the threespine stickleback (Gasterosteus aculeatus), ninespine stickleback (Pungitius pungitus), and tubesnout (Aulorhynchus flavidus). Populations were sampled from the southern and northern edges of each species' range, to identify patterns associated with latitudinal changes in genetic diversity. Weak correlations in genetic diversity (F ST and expected heterozygosity) and three different patterns in the genomic landscape were found among these species. Additionally, no candidate genes for convergent evolution were detected. This is a counterexample to the growing number of studies that have shown overlapping genetic patterns, demonstrating that genome scan comparisons can be noisy due to the effects of several interacting evolutionary forces.
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Affiliation(s)
- James Reeve
- Department of Biological SciencesUniversity of CalgaryCalgaryAlbertaCanada
- Present address:
Tjärnö Marina LaboratoriumGöteborgs UniversitetStrömstadSweden
| | - Qiushi Li
- Department of Biological SciencesUniversity of CalgaryCalgaryAlbertaCanada
- Present address:
Institute of Chinese Materia MedicaChina Academy of Chinese Medical SciencesBeijingChina
| | - Dorothea Lindtke
- Department of Biological SciencesUniversity of CalgaryCalgaryAlbertaCanada
- Present address:
Institute of Plant SciencesUniversity of BernBernSwitzerland
| | - Samuel Yeaman
- Department of Biological SciencesUniversity of CalgaryCalgaryAlbertaCanada
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23
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Santos WB, Schettini GP, Maiorano AM, Bussiman FO, Balieiro JCC, Ferraz GC, Pereira GL, Baldassini WA, Neto ORM, Oliveira HN, Curi RA. Genome-wide scans for signatures of selection in Mangalarga Marchador horses using high-throughput SNP genotyping. BMC Genomics 2021; 22:737. [PMID: 34645387 PMCID: PMC8515666 DOI: 10.1186/s12864-021-08053-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 09/07/2021] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND The detection of signatures of selection in genomic regions provides insights into the evolutionary process, enabling discoveries regarding complex phenotypic traits. In this research, we focused on identifying genomic regions affected by different selection pressures, mainly highlighting the recent positive selection, as well as understanding the candidate genes and functional pathways associated with the signatures of selection in the Mangalarga Marchador genome. Besides, we seek to direct the discussion about genes and traits of importance in this breed, especially traits related to the type and quality of gait, temperament, conformation, and locomotor system. RESULTS Three different methods were used to search for signals of selection: Tajima's D (TD), the integrated haplotype score (iHS), and runs of homozygosity (ROH). The samples were composed of males (n = 62) and females (n = 130) that were initially chosen considering well-defined phenotypes for gait: picada (n = 86) and batida (n = 106). All horses were genotyped using a 670 k Axiom® Equine Genotyping Array (Axiom MNEC670). In total, 27, 104 (chosen), and 38 candidate genes were observed within the signatures of selection identified in TD, iHS, and ROH analyses, respectively. The genes are acting in essential biological processes. The enrichment analysis highlighted the following functions: anterior/posterior pattern for the set of genes (GLI3, HOXC9, HOXC6, HOXC5, HOXC4, HOXC13, HOXC11, and HOXC10); limb morphogenesis, skeletal system, proximal/distal pattern formation, JUN kinase activity (CCL19 and MAP3K6); and muscle stretch response (MAPK14). Other candidate genes were associated with energy metabolism, bronchodilator response, NADH regeneration, reproduction, keratinization, and the immunological system. CONCLUSIONS Our findings revealed evidence of signatures of selection in the MM breed that encompass genes acting on athletic performance, limb development, and energy to muscle activity, with the particular involvement of the HOX family genes. The genome of MM is marked by recent positive selection. However, Tajima's D and iHS results point also to the presence of balancing selection in specific regions of the genome.
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Affiliation(s)
- Wellington B Santos
- Department of Animal Science, São Paulo State University (Unesp) - FCAV, Via de Acesso Professor Paulo Donato Castelane, NN, CEP: 14884-900, Jaboticabal, SP, Brazil.
| | - Gustavo P Schettini
- Department of Animal Science, São Paulo State University (Unesp) - FCAV, Via de Acesso Professor Paulo Donato Castelane, NN, CEP: 14884-900, Jaboticabal, SP, Brazil
| | - Amanda M Maiorano
- Department of Animal Science, São Paulo State University (Unesp) - FCAV, Via de Acesso Professor Paulo Donato Castelane, NN, CEP: 14884-900, Jaboticabal, SP, Brazil
| | - Fernando O Bussiman
- Department of Animal Science, University of São Paulo (USP) - FZEA, Pirassununga, Brazil
| | - Júlio C C Balieiro
- Department of Animal Science, University of São Paulo (USP) - FZEA, Pirassununga, Brazil
| | - Guilherme C Ferraz
- Department of Animal Science, São Paulo State University (Unesp) - FCAV, Via de Acesso Professor Paulo Donato Castelane, NN, CEP: 14884-900, Jaboticabal, SP, Brazil
| | - Guilherme L Pereira
- Department of Breeding and Animal Nutrition, São Paulo State University (Unesp) - FMVZ, Botucatu, Brazil
| | - Welder Angelo Baldassini
- Department of Breeding and Animal Nutrition, São Paulo State University (Unesp) - FMVZ, Botucatu, Brazil
| | - Otávio R M Neto
- Department of Breeding and Animal Nutrition, São Paulo State University (Unesp) - FMVZ, Botucatu, Brazil
| | - Henrique N Oliveira
- Department of Animal Science, São Paulo State University (Unesp) - FCAV, Via de Acesso Professor Paulo Donato Castelane, NN, CEP: 14884-900, Jaboticabal, SP, Brazil
| | - Rogério A Curi
- Department of Breeding and Animal Nutrition, São Paulo State University (Unesp) - FMVZ, Botucatu, Brazil
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24
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Singh S, Jighly A, Sehgal D, Burgueño J, Joukhadar R, Singh SK, Sharma A, Vikram P, Sansaloni CP, Govindan V, Bhavani S, Randhawa M, Solis-Moya E, Singh S, Pardo N, Arif MAR, Laghari KA, Basandrai D, Shokat S, Chaudhary HK, Saeed NA, Basandrai AK, Ledesma-Ramírez L, Sohu VS, Imtiaz M, Sial MA, Wenzl P, Singh GP, Bains NS. Direct introgression of untapped diversity into elite wheat lines. Nat Food 2021; 2:819-827. [PMID: 37117978 DOI: 10.1038/s43016-021-00380-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 08/27/2021] [Indexed: 04/30/2023]
Abstract
The effective utilization of natural variation has become essential in addressing the challenges that climate change and population growth pose to global food security. Currently adopted protracted approaches to introgress exotic alleles into elite cultivars need substantial transformation. Here, through a strategic three-way crossing scheme among diverse exotics and the best historical elites (exotic/elite1//elite2), 2,867 pre-breeding lines were developed, genotyped and screened for multiple agronomic traits in four mega-environments. A meta-genome-wide association study, selective sweeps and haplotype-block-based analyses unveiled selection footprints in the genomes of pre-breeding lines as well as exotic-specific associations with agronomic traits. A simulation with a neutrality assumption demonstrated that many pre-breeding lines had significant exotic contributions despite substantial selection bias towards elite genomes. National breeding programmes worldwide have adopted 95 lines for germplasm enhancement, and 7 additional lines are being advanced in varietal release trials. This study presents a great leap forwards in the mobilization of GenBank variation to the breeding pipelines.
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Affiliation(s)
- Sukhwinder Singh
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
- Geneshifters, Pullman, WA, USA.
| | - A Jighly
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, Victoria, Australia
| | - D Sehgal
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - J Burgueño
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - R Joukhadar
- Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, Victoria, Australia
| | - S K Singh
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
| | - A Sharma
- Department of Plant Breeding & Genetics, Punjab Agricultural University, Ludhiana, India
| | - P Vikram
- International Center for Biosaline Agriculture, Dubai, United Arab Emirates
| | - C P Sansaloni
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - V Govindan
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - S Bhavani
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - M Randhawa
- CIMMYT-World Agroforestry Centre (ICRAF), Nairobi, Kenya
| | - E Solis-Moya
- Carretera Celaya-San Miguel de Allende, Celaya, México
| | - S Singh
- ICAR-National Institute of Plant Biotechnology, New Delhi, India
| | - N Pardo
- International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico
| | - M A R Arif
- Nuclear Institute for Agriculture and Biology, Faisalabad, Pakistan
| | - K A Laghari
- Nuclear Institute of Agriculture, Tando Jam, Pakistan
| | - D Basandrai
- CSK Himachal Pradesh Agricultural University Palampur, Palampur, India
| | - S Shokat
- Nuclear Institute for Agriculture and Biology, Faisalabad, Pakistan
- Department of Plant and Environmental Sciences, Crop Science, University of Copenhagen, Taastrup, Denmark
| | - H K Chaudhary
- CSK Himachal Pradesh Agricultural University Palampur, Palampur, India
| | - N A Saeed
- Nuclear Institute for Agriculture and Biology, Faisalabad, Pakistan
| | - A K Basandrai
- CSK Himachal Pradesh Agricultural University Palampur, Palampur, India
| | | | - V S Sohu
- Department of Plant Breeding & Genetics, Punjab Agricultural University, Ludhiana, India
| | | | - M A Sial
- Nuclear Institute of Agriculture, Tando Jam, Pakistan
| | | | - G P Singh
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, India
| | - N S Bains
- Department of Plant Breeding & Genetics, Punjab Agricultural University, Ludhiana, India
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25
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Wang Q, Ren X, Liu P, Li J, Lv J, Wang J, Zhang H, Wei W, Zhou Y, He Y, Li J. Improved genome assembly of Chinese shrimp (Fenneropenaeus chinensis) suggests adaptation to the environment during evolution and domestication. Mol Ecol Resour 2021; 22:334-344. [PMID: 34240531 DOI: 10.1111/1755-0998.13463] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/10/2021] [Accepted: 07/05/2021] [Indexed: 11/30/2022]
Abstract
A high-quality reference genome is necessary to determine the molecular mechanisms underlying important biological phenomena; therefore, in the present study, a chromosome-level genome assembly of the Chinese shrimp Fenneropenaeus chinensis was performed. Muscle of a male shrimp was sequenced using PacBio platform, and assembled by Hi-C technology. The assembled F. chinensis genome was 1.47 Gb with contig N50 of 472.84 Kb, including 57.73% repetitive sequences, and was anchored to 43 pseudochromosomes, with scaffold N50 of 36.87 Mb. In total, 25,026 protein-coding genes were predicted. The genome size of F. chinensis showed significant contraction in comparison with that of other penaeid species, which is likely related to migration observed in this species. However, the F. chinensis genome included several expanded gene families related to cellular processes and metabolic processes, and the contracted gene families were associated with virus infection process. The findings signify the adaptation of F. chinensis to the selection pressure of migration and cold environment. Furthermore, the selection signature analysis identified genes associated with metabolism, phototransduction, and nervous system in cultured shrimps when compared with wild population, indicating targeted, artificial selection of growth, vision, and behavior during domestication. The construction of the genome of F. chinensis provided valuable information for the further genetic mechanism analysis of important biological processes, and will facilitate the research of genetic changes during evolution.
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Affiliation(s)
- Qiong Wang
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China.,Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Xianyun Ren
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China.,Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Ping Liu
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China.,Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Jitao Li
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China.,Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Jianjian Lv
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China.,Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Jiajia Wang
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China.,Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Haien Zhang
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China
| | - Wei Wei
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China
| | - Yuxin Zhou
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China
| | - Yuying He
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China.,Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
| | - Jian Li
- Key Laboratory for Sustainable Utilization of Marine Fisheries Resources, Ministry of Agriculture and Rural Affairs, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao, China.,Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao, China
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26
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Leigh DM, Lischer HEL, Guillaume F, Grossen C, Günther T. Disentangling adaptation from drift in bottlenecked and reintroduced populations of Alpine ibex. Mol Ecol Resour 2021; 21:2350-2363. [PMID: 34097819 PMCID: PMC8518545 DOI: 10.1111/1755-0998.13442] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 05/27/2021] [Accepted: 06/01/2021] [Indexed: 01/25/2023]
Abstract
Identifying local adaptation in bottlenecked species is essential for conservation management. Selection detection methods have an important role in species management plans, assessments of adaptive capacity, and looking for responses to climate change. Yet, the allele frequency changes exploited in selection detection methods are similar to those caused by the strong neutral genetic drift expected during a bottleneck. Consequently, it is often unclear what accuracy selection detection methods have across bottlenecked populations. In this study, simulations were used to explore if signals of selection could be confidently distinguished from genetic drift across 23 bottlenecked and reintroduced populations of Alpine ibex (Capra ibex). The meticulously recorded demographic history of the Alpine ibex was used to generate comprehensive simulated SNP data. The simulated SNPs were then used to benchmark the confidence we could place in outliers identified in empirical Alpine ibex RADseq derived SNP data. Within the simulated data set, the false positive rates were high for all selection detection methods (FST outlier scans and Genetic‐Environment Association analyses) but fell substantially when two or more methods were combined. True positive rates were consistently low and became negligible with increased stringency. Despite finding many outlier loci in the empirical Alpine ibex SNPs, none could be distinguished from genetic drift‐driven false positives. Unfortunately, the low true positive rate also prevents the exclusion of recent local adaptation within the Alpine ibex. The baselines and stringent approach outlined here should be applied to other bottlenecked species to ensure the risk of false positive, or negative, signals of selection are accounted for in conservation management plans.
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Affiliation(s)
- Deborah M Leigh
- WSL Swiss Federal Research Institute, Birmensdorf, Switzerland
| | - Heidi E L Lischer
- Interfaculty Bioinformatics Unit, University of Bern, Bern, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Frédéric Guillaume
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | - Christine Grossen
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | - Torsten Günther
- Human Evolution, Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden
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27
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Bourgeois YXC, Warren BH. An overview of current population genomics methods for the analysis of whole-genome resequencing data in eukaryotes. Mol Ecol 2021; 30:6036-6071. [PMID: 34009688 DOI: 10.1111/mec.15989] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 04/26/2021] [Accepted: 05/11/2021] [Indexed: 01/01/2023]
Abstract
Characterizing the population history of a species and identifying loci underlying local adaptation is crucial in functional ecology, evolutionary biology, conservation and agronomy. The constant improvement of high-throughput sequencing techniques has facilitated the production of whole genome data in a wide range of species. Population genomics now provides tools to better integrate selection into a historical framework, and take into account selection when reconstructing demographic history. However, this improvement has come with a profusion of analytical tools that can confuse and discourage users. Such confusion limits the amount of information effectively retrieved from complex genomic data sets, and impairs the diffusion of the most recent analytical tools into fields such as conservation biology. It may also lead to redundancy among methods. To address these isssues, we propose an overview of more than 100 state-of-the-art methods that can deal with whole genome data. We summarize the strategies they use to infer demographic history and selection, and discuss some of their limitations. A website listing these methods is available at www.methodspopgen.com.
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Affiliation(s)
| | - Ben H Warren
- Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum National d'Histoire Naturelle, CNRS, Sorbonne Université, EPHE, UA, CP 51, Paris, France
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28
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Orbán L, Shen X, Phua N, Varga L. Toward Genome-Based Selection in Asian Seabass: What Can We Learn From Other Food Fishes and Farm Animals? Front Genet 2021; 12:506754. [PMID: 33968125 PMCID: PMC8097054 DOI: 10.3389/fgene.2021.506754] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 03/15/2021] [Indexed: 01/08/2023] Open
Abstract
Due to the steadily increasing need for seafood and the plateauing output of fisheries, more fish need to be produced by aquaculture production. In parallel with the improvement of farming methods, elite food fish lines with superior traits for production must be generated by selection programs that utilize cutting-edge tools of genomics. The purpose of this review is to provide a historical overview and status report of a selection program performed on a catadromous predator, the Asian seabass (Lates calcarifer, Bloch 1790) that can change its sex during its lifetime. We describe the practices of wet lab, farm and lab in detail by focusing onto the foundations and achievements of the program. In addition to the approaches used for selection, our review also provides an inventory of genetic/genomic platforms and technologies developed to (i) provide current and future support for the selection process; and (ii) improve our understanding of the biology of the species. Approaches used for the improvement of terrestrial farm animals are used as examples and references, as those processes are far ahead of the ones used in aquaculture and thus they might help those working on fish to select the best possible options and avoid potential pitfalls.
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Affiliation(s)
- László Orbán
- Reproductive Genomics Group, Temasek Life Sciences Laboratory, Singapore, Singapore.,Frontline Fish Genomics Research Group, Department of Applied Fish Biology, Institute of Aquaculture and Environmental Safety, Hungarian University of Agriculture and Life Sciences, Keszthely, Hungary
| | - Xueyan Shen
- Reproductive Genomics Group, Temasek Life Sciences Laboratory, Singapore, Singapore.,Tropical Futures Institute, James Cook University, Singapore, Singapore
| | - Norman Phua
- Reproductive Genomics Group, Temasek Life Sciences Laboratory, Singapore, Singapore
| | - László Varga
- Institute of Genetics and Biotechnology, Hungarian University of Agriculture and Life Sciences, Gödöllõ, Hungary.,Institute for Farm Animal Gene Conservation, National Centre for Biodiversity and Gene Conservation, Gödöllõ, Hungary
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29
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Shi H, Gazal S, Kanai M, Koch EM, Schoech AP, Siewert KM, Kim SS, Luo Y, Amariuta T, Huang H, Okada Y, Raychaudhuri S, Sunyaev SR, Price AL. Population-specific causal disease effect sizes in functionally important regions impacted by selection. Nat Commun 2021; 12:1098. [PMID: 33597505 PMCID: PMC7889654 DOI: 10.1038/s41467-021-21286-1] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Accepted: 01/15/2021] [Indexed: 01/31/2023] Open
Abstract
Many diseases exhibit population-specific causal effect sizes with trans-ethnic genetic correlations significantly less than 1, limiting trans-ethnic polygenic risk prediction. We develop a new method, S-LDXR, for stratifying squared trans-ethnic genetic correlation across genomic annotations, and apply S-LDXR to genome-wide summary statistics for 31 diseases and complex traits in East Asians (average N = 90K) and Europeans (average N = 267K) with an average trans-ethnic genetic correlation of 0.85. We determine that squared trans-ethnic genetic correlation is 0.82× (s.e. 0.01) depleted in the top quintile of background selection statistic, implying more population-specific causal effect sizes. Accordingly, causal effect sizes are more population-specific in functionally important regions, including conserved and regulatory regions. In regions surrounding specifically expressed genes, causal effect sizes are most population-specific for skin and immune genes, and least population-specific for brain genes. Our results could potentially be explained by stronger gene-environment interaction at loci impacted by selection, particularly positive selection.
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Affiliation(s)
- Huwenbo Shi
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Steven Gazal
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Masahiro Kanai
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Evan M Koch
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Armin P Schoech
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Katherine M Siewert
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samuel S Kim
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Yang Luo
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tiffany Amariuta
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Graduate School of Arts and Sciences, Harvard University, Cambridge, MA, USA
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
| | - Soumya Raychaudhuri
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Immunology, and Allergy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Arthritis Research UK Centre for Genetics and Genomics, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
| | - Shamil R Sunyaev
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Alkes L Price
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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30
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Hamid I, Korunes KL, Beleza S, Goldberg A. Rapid adaptation to malaria facilitated by admixture in the human population of Cabo Verde. eLife 2021; 10:e63177. [PMID: 33393457 PMCID: PMC7815310 DOI: 10.7554/elife.63177] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 01/04/2021] [Indexed: 12/20/2022] Open
Abstract
Humans have undergone large migrations over the past hundreds to thousands of years, exposing ourselves to new environments and selective pressures. Yet, evidence of ongoing or recent selection in humans is difficult to detect. Many of these migrations also resulted in gene flow between previously separated populations. These recently admixed populations provide unique opportunities to study rapid evolution in humans. Developing methods based on distributions of local ancestry, we demonstrate that this sort of genetic exchange has facilitated detectable adaptation to a malaria parasite in the admixed population of Cabo Verde within the last ~20 generations. We estimate that the selection coefficient is approximately 0.08, one of the highest inferred in humans. Notably, we show that this strong selection at a single locus has likely affected patterns of ancestry genome-wide, potentially biasing demographic inference. Our study provides evidence of adaptation in a human population on historical timescales.
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Affiliation(s)
- Iman Hamid
- Department of Evolutionary Anthropology, Duke UniversityDurhamUnited States
| | | | - Sandra Beleza
- Department of Genetics and Genome Biology, University of LeicesterLeicesterUnited Kingdom
| | - Amy Goldberg
- Department of Evolutionary Anthropology, Duke UniversityDurhamUnited States
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31
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Hejase HA, Salman-Minkov A, Campagna L, Hubisz MJ, Lovette IJ, Gronau I, Siepel A. Genomic islands of differentiation in a rapid avian radiation have been driven by recent selective sweeps. Proc Natl Acad Sci U S A 2020; 117:30554-65. [PMID: 33199636 DOI: 10.1073/pnas.2015987117] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Numerous studies of emerging species have identified genomic "islands" of elevated differentiation against a background of relative homogeneity. The causes of these islands remain unclear, however, with some signs pointing toward "speciation genes" that locally restrict gene flow and others suggesting selective sweeps that have occurred within nascent species after speciation. Here, we examine this question through the lens of genome sequence data for five species of southern capuchino seedeaters, finch-like birds from South America that have undergone a species radiation during the last ∼50,000 generations. By applying newly developed statistical methods for ancestral recombination graph inference and machine-learning methods for the prediction of selective sweeps, we show that previously identified islands of differentiation in these birds appear to be generally associated with relatively recent, species-specific selective sweeps, most of which are predicted to be soft sweeps acting on standing genetic variation. Many of these sweeps coincide with genes associated with melanin-based variation in plumage, suggesting a prominent role for sexual selection. At the same time, a few loci also exhibit indications of possible selection against gene flow. These observations shed light on the complex manner in which natural selection shapes genome sequences during speciation.
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32
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Cooke I, Ying H, Forêt S, Bongaerts P, Strugnell JM, Simakov O, Zhang J, Field MA, Rodriguez-Lanetty M, Bell SC, Bourne DG, van Oppen MJ, Ragan MA, Miller DJ. Genomic signatures in the coral holobiont reveal host adaptations driven by Holocene climate change and reef specific symbionts. Sci Adv 2020; 6:6/48/eabc6318. [PMID: 33246955 PMCID: PMC7695477 DOI: 10.1126/sciadv.abc6318] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 10/15/2020] [Indexed: 05/24/2023]
Abstract
Genetic signatures caused by demographic and adaptive processes during past climatic shifts can inform predictions of species' responses to anthropogenic climate change. To identify these signatures in Acropora tenuis, a reef-building coral threatened by global warming, we first assembled the genome from long reads and then used shallow whole-genome resequencing of 150 colonies from the central inshore Great Barrier Reef to inform population genomic analyses. We identify population structure in the host that reflects a Pleistocene split, whereas photosymbiont differences between reefs most likely reflect contemporary (Holocene) conditions. Signatures of selection in the host were associated with genes linked to diverse processes including osmotic regulation, skeletal development, and the establishment and maintenance of symbiosis. Our results suggest that adaptation to post-glacial climate change in A. tenuis has involved selection on many genes, while differences in symbiont specificity between reefs appear to be unrelated to host population structure.
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Affiliation(s)
- Ira Cooke
- College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Queensland, Australia.
- Centre for Tropical Bioinformatics and Molecular Biology, James Cook University, Townsville, Queensland, Australia
| | - Hua Ying
- Research School of Biology, Australian National University, Canberra, ACT, Australia
| | - Sylvain Forêt
- Research School of Biology, Australian National University, Canberra, ACT, Australia
- ARC Centre of Excellence for Coral Reef Studies, Australian National University, Canberra, ACT, Australia
| | - Pim Bongaerts
- California Academy of Sciences, Golden Gate Park, San Francisco, CA, USA
| | - Jan M Strugnell
- Centre for Sustainable Tropical Fisheries and Aquaculture, James Cook University, Townsville, Queensland, Australia
- Department of Ecology, Environment and Evolution, School of Life Sciences, La Trobe University, Melbourne, Australia
- College of Science and Engineering, James Cook University, Townsville, Queensland, Australia
| | - Oleg Simakov
- Department of Molecular Evolution and Development, University of Vienna, Austria
| | - Jia Zhang
- College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Queensland, Australia
- Centre for Tropical Bioinformatics and Molecular Biology, James Cook University, Townsville, Queensland, Australia
- ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland, Australia
| | - Matt A Field
- Centre for Tropical Bioinformatics and Molecular Biology, James Cook University, Townsville, Queensland, Australia
- Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, Queensland, Australia
| | - Mauricio Rodriguez-Lanetty
- Institute of Environment and Department of Biological Sciences, Florida International University, Miami, Fl 33199, USA
| | - Sara C Bell
- Australian Institute of Marine Science, Townsville, Queensland, Australia
| | - David G Bourne
- Centre for Tropical Bioinformatics and Molecular Biology, James Cook University, Townsville, Queensland, Australia
- College of Science and Engineering, James Cook University, Townsville, Queensland, Australia
- Australian Institute of Marine Science, Townsville, Queensland, Australia
| | - Madeleine Jh van Oppen
- Australian Institute of Marine Science, Townsville, Queensland, Australia
- School of BioSciences, University of Melbourne, Melbourne, Australia
| | - Mark A Ragan
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - David J Miller
- College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Queensland, Australia.
- Centre for Tropical Bioinformatics and Molecular Biology, James Cook University, Townsville, Queensland, Australia
- ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland, Australia
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33
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Abstract
Mammalian pluripotent stem cells (PSCs) have distinct molecular and biological characteristics among species, but to date we lack a comprehensive understanding of regulatory network evolution in mammals. Here, we carried out a comparative genetic analysis of 134 genes constituting the pluripotency gene regulatory network across 48 mammalian species covering all the major taxonomic groups. We report that mammalian genes in the pluripotency regulatory network show a remarkably high degree of evolutionary stasis, suggesting the conservation of fundamental biological process of mammalian PSCs across species. Nevertheless, despite the overall conservation of the regulatory network, we discovered rapid evolution of the downstream targets of the core regulatory elements and specific amino acid residues that have undergone positive selection. Our data indicate development of lineage-specific pluripotency regulating networks that may explain observed variations in some characteristics of mammalian PSCs. We further revealed that positively selected genes could be associated with species' unique adaptive characteristics that were not dedicated to regulation of PSCs. These results provide important insight into the evolution of the pluripotency gene regulatory network underlying variations in characteristics of mammalian PSCs.
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Affiliation(s)
| | - Ken-ichiro Kamei
- Institute for Integrated Cell-Material Sciences (WPI-iCeMS), Kyoto University, Japan
| | - Miho Inoue-Murayama
- Wildlife Research Center, Kyoto University, Japan
- Institute for Integrated Cell-Material Sciences (WPI-iCeMS), Kyoto University, Japan
- Wildlife Genome Collaborative Research Group, National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan
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34
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Sun T, Huang GY, Wang ZH, Teng SH, Cao YH, Sun JL, Hanif Q, Chen NB, Lei CZ, Liao YY. Selection signatures of Fuzhong Buffalo based on whole-genome sequences. BMC Genomics 2020; 21:674. [PMID: 32993537 PMCID: PMC7526191 DOI: 10.1186/s12864-020-07095-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 09/23/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Fuzhong buffalo, a native breed of Guangxi Zhuang Autonomous Region, is traditionally used as a draft animal to provide farm power in the rice cultivation. In addition, the Fuzhong buffalo also prepared for the bullfighting festival organized by the locals. The detection of the selective signatures in its genome can help in elucidating the selection mechanisms in its stamina and muscle development of a draft animal. RESULTS In this study, we analyzed 27 whole genomes of buffalo (including 15 Fuzhong buffalo genomes and 12 published buffalo genomes from Upper Yangtze region). The ZHp, ZFst, π-Ratio, and XP-EHH statistics were used to identify the candidate signatures of positive selection in Fuzhong buffalo. Our results detected a set of candidate genes involving in the pathways and GO terms associated with the response to exercise (e.g., ALDOA, STAT3, AKT2, EIF4E2, CACNA2D2, TCF4, CDH2), immunity (e.g., PTPN22, NKX2-3, PIK3R1, ITK, TMEM173), nervous system (e.g., PTPN21, ROBO1, HOMER1, MAGI2, SLC1A3, NRG3, SNAP47, CTNNA2, ADGRL3). In addition, we also identified several genes related to production and growth traits (e.g., PHLPP1, PRKN, MACF1, UCN3, RALGAPA1, PHKB, PKD1L). Our results depicted several pathways, GO terms, and candidate genes to be associated with response to exercise, immunity, nervous system, and growth traits. CONCLUSIONS The selective sweep analysis of the Fuzhong buffalo demonstrated positive selection pressure on potential target genes involved in behavior, immunity, and growth traits, etc. Our findings provided a valuable resource for future research on buffalo breeding and an insight into the mechanisms of artificial selection.
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Affiliation(s)
- Ting Sun
- Animal Husbandry Institute of Guangxi Zhuang Autonomous Region, Guangxi Key Laboratory of Livestock Genetic Improvement, Nanning, 530001, China.,College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Guang-Yun Huang
- Animal Husbandry Institute of Guangxi Zhuang Autonomous Region, Guangxi Key Laboratory of Livestock Genetic Improvement, Nanning, 530001, China
| | - Zi-Hao Wang
- Animal Husbandry Institute of Guangxi Zhuang Autonomous Region, Guangxi Key Laboratory of Livestock Genetic Improvement, Nanning, 530001, China
| | - Shao-Hua Teng
- Animal Husbandry Institute of Guangxi Zhuang Autonomous Region, Guangxi Key Laboratory of Livestock Genetic Improvement, Nanning, 530001, China
| | - Yan-Hong Cao
- Animal Husbandry Institute of Guangxi Zhuang Autonomous Region, Guangxi Key Laboratory of Livestock Genetic Improvement, Nanning, 530001, China
| | - Jun-Li Sun
- Animal Husbandry Institute of Guangxi Zhuang Autonomous Region, Guangxi Key Laboratory of Livestock Genetic Improvement, Nanning, 530001, China
| | - Quratulain Hanif
- Computational Biology Laboratory, Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering, Faisalabad, Pakistan.,Department of Biotechnology, Pakistan Institute of Engineering and Applied Sciences, Nilore, Islamabad, Pakistan
| | - Ning-Bo Chen
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Chu-Zhao Lei
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, Shaanxi, China.
| | - Yu-Ying Liao
- Animal Husbandry Institute of Guangxi Zhuang Autonomous Region, Guangxi Key Laboratory of Livestock Genetic Improvement, Nanning, 530001, China.
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35
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Werren EA, Garcia O, Bigham AW. Identifying adaptive alleles in the human genome: from selection mapping to functional validation. Hum Genet 2020; 140:241-276. [PMID: 32728809 DOI: 10.1007/s00439-020-02206-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 07/07/2020] [Indexed: 12/19/2022]
Abstract
The suite of phenotypic diversity across geographically distributed human populations is the outcome of genetic drift, gene flow, and natural selection throughout human evolution. Human genetic variation underlying local biological adaptations to selective pressures is incompletely characterized. With the emergence of population genetics modeling of large-scale genomic data derived from diverse populations, scientists are able to map signatures of natural selection in the genome in a process known as selection mapping. Inferred selection signals further can be used to identify candidate functional alleles that underlie putative adaptive phenotypes. Phenotypic association, fine mapping, and functional experiments facilitate the identification of candidate adaptive alleles. Functional investigation of candidate adaptive variation using novel techniques in molecular biology is slowly beginning to unravel how selection signals translate to changes in biology that underlie the phenotypic spectrum of our species. In addition to informing evolutionary hypotheses of adaptation, the discovery and functional annotation of adaptive alleles also may be of clinical significance. While selection mapping efforts in non-European populations are growing, there remains a stark under-representation of diverse human populations in current public genomic databases, of both clinical and non-clinical cohorts. This lack of inclusion limits the study of human biological variation. Identifying and functionally validating candidate adaptive alleles in more global populations is necessary for understanding basic human biology and human disease.
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Affiliation(s)
- Elizabeth A Werren
- Department of Human Genetics, The University of Michigan, Ann Arbor, MI, USA
- Department of Anthropology, The University of Michigan, Ann Arbor, MI, USA
| | - Obed Garcia
- Department of Anthropology, The University of Michigan, Ann Arbor, MI, USA
| | - Abigail W Bigham
- Department of Anthropology, University of California Los Angeles, 341 Haines Hall, Los Angeles, CA, 90095, USA.
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36
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Vicuña L, Fernandez MI, Vial C, Valdebenito P, Chaparro E, Espinoza K, Ziegler A, Bustamante A, Eyheramendy S. Adaptation to Extreme Environments in an Admixed Human Population from the Atacama Desert. Genome Biol Evol 2020; 11:2468-2479. [PMID: 31384924 PMCID: PMC6733355 DOI: 10.1093/gbe/evz172] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/29/2019] [Indexed: 12/11/2022] Open
Abstract
Inorganic arsenic (As) is a toxic xenobiotic and carcinogen associated with severe health conditions. The urban population from the Atacama Desert in northern Chile was exposed to extremely high As levels (up to 600 µg/l) in drinking water between 1958 and 1971, leading to increased incidence of urinary bladder cancer (BC), skin cancer, kidney cancer, and coronary thrombosis decades later. Besides, the Andean Native-American ancestors of the Atacama population were previously exposed for millennia to elevated As levels in water (∼120 µg/l) for at least 5,000 years, suggesting adaptation to this selective pressure. Here, we performed two genome-wide selection tests—PBSn1 and an ancestry-enrichment test—in an admixed population from Atacama, to identify adaptation signatures to As exposure acquired before and after admixture with Europeans, respectively. The top second variant selected by PBSn1 was associated with LCE4A-C1orf68, a gene that may be involved in the immune barrier of the epithelium during BC. We performed association tests between the top PBSn1 hits and BC occurrence in our population. The strongest association (P = 0.012) was achieved by the LCE4A-C1orf68 variant. The ancestry-enrichment test detected highly significant signals (P = 1.3 × 10−9) mapping MAK16, a gene with important roles in ribosome biogenesis during the G1 phase of the cell cycle. Our results contribute to a better understanding of the genetic factors involved in adaptation to the pathophysiological consequences of As exposure.
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Affiliation(s)
- Lucas Vicuña
- Department of Statistics, Faculty of Mathematics, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Mario I Fernandez
- Department of Urology, Clínica Alemana, Santiago, Chile.,Center for Genetics and Genomics, Faculty of Medicine, Clínica Alemana Universidad del Desarrollo, Santiago, Chile
| | - Cecilia Vial
- Center for Genetics and Genomics, Faculty of Medicine, Clínica Alemana Universidad del Desarrollo, Santiago, Chile
| | | | | | | | - Annemarie Ziegler
- Center for Genetics and Genomics, Faculty of Medicine, Clínica Alemana Universidad del Desarrollo, Santiago, Chile
| | | | - Susana Eyheramendy
- Department of Statistics, Faculty of Mathematics, Pontificia Universidad Católica de Chile, Santiago, Chile.,Faculty of Engineering and Sciences, Universidad Adolfo Ibañez, Peñalolén, Santiago, Chile
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37
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Naderi S, Moradi MH, Farhadian M, Yin T, Jaeger M, Scheper C, Korkuc P, Brockmann GA, König S, May K. Assessing selection signatures within and between selected lines of dual-purpose black and white and German Holstein cattle. Anim Genet 2020; 51:391-408. [PMID: 32100321 DOI: 10.1111/age.12925] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/02/2020] [Indexed: 12/29/2022]
Abstract
The aim of this study was to detect selection signatures considering cows from the German Holstein (GH) and the local dual-purpose black and white (DSN) population, as well as from generated sub-populations. The 4654 GH and 261 DSN cows were genotyped with the BovineSNP50 Genotyping BeadChip. The geographical herd location was used as an environmental descriptor to create the East-DSN and West-DSN sub-populations. In addition, two further sub-populations of GH cows were generated, using the extreme values for solutions of residual effects of cows for the claw disorder dermatitis digitalis. These groups represented the most susceptible and most resistant cows. We used cross-population extended haplotype homozygosity methodology (XP-EHH) to identify the most recent selection signatures. Furthermore, we calculated Wright's fixation index (FST ). Chromosomal segments for the top 0.1 percentile of negative or positive XP-EHH scores were studied in detail. For gene annotations, we used the Ensembl database and we considered a window of 250 kbp downstream and upstream of each core SNP corresponding to peaks of XP-EHH. In addition, functional interactions among potential candidate genes were inferred via gene network analyses. The most outstanding XP-EHH score was on chromosome 12 (at 77.34 Mb) for DSN and on chromosome 20 (at 36.29-38.42 Mb) for GH. Selection signature locations harbored QTL for several economically important milk and meat quality traits, reflecting the different breeding goals for GH and DSN. The average FST value between GH and DSN was quite low (0.068), indicating shared founders. For group stratifications according to cow health, several identified potential candidate genes influence disease resistance, especially to dermatitis digitalis.
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Affiliation(s)
- S Naderi
- Institute of Animal Breeding and Genetics, Justus-Liebig University Giessen, Ludwigstr. 21b, Giessen, Germany
| | - M H Moradi
- Department of Animal Sciences, Arak University, Shahid Beheshti Street, Arak, Iran
| | - M Farhadian
- Department of Animal Science, University of Tabriz, 29 Bahman Boulevard, Tabriz, Iran
| | - T Yin
- Institute of Animal Breeding and Genetics, Justus-Liebig University Giessen, Ludwigstr. 21b, Giessen, Germany
| | - M Jaeger
- Institute of Animal Breeding and Genetics, Justus-Liebig University Giessen, Ludwigstr. 21b, Giessen, Germany
| | - C Scheper
- Institute of Animal Breeding and Genetics, Justus-Liebig University Giessen, Ludwigstr. 21b, Giessen, Germany
| | - P Korkuc
- Albrecht Daniel Thaer Institute for Agricultural and Horticultural Sciences, Humboldt University Berlin, Invalidenstr. 42, Berlin, D-10115, Germany
| | - G A Brockmann
- Albrecht Daniel Thaer Institute for Agricultural and Horticultural Sciences, Humboldt University Berlin, Invalidenstr. 42, Berlin, D-10115, Germany
| | - S König
- Institute of Animal Breeding and Genetics, Justus-Liebig University Giessen, Ludwigstr. 21b, Giessen, Germany
| | - K May
- Institute of Animal Breeding and Genetics, Justus-Liebig University Giessen, Ludwigstr. 21b, Giessen, Germany
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38
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Abstract
The extent to which selection has shaped present-day human populations has attracted intense scrutiny, and examples of local adaptations abound. However, the evolutionary trajectory of alleles that, today, are deleterious has received much less attention. To address this question, the genomes of 2,062 individuals, including 1,179 ancient humans, were reanalyzed to assess how frequencies of risk alleles and their homozygosity changed through space and time in Europe over the past 45,000 years. Although the overall deleterious homozygosity has consistently decreased, risk alleles have steadily increased in frequency over that period of time. Those that increased most are associated with diseases such as asthma, Crohn disease, diabetes, and obesity, which are highly prevalent in present-day populations. These findings may not run against the existence of local adaptations but highlight the limitations imposed by drift and population dynamics on the strength of selection in purging deleterious mutations from human populations.
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Affiliation(s)
- Stéphane Aris-Brosou
- Department of Biology, University of Ottawa, Ottawa, ON, Canada.,Department of Mathematics and Statistics, University of Ottawa, Ottawa, ON, Canada
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39
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Nishino J, Watanabe S, Miya F, Kamatani T, Sugawara T, Boroevich KA, Tsunoda T. Quantification of multicellular colonization in tumor metastasis using exome-sequencing data. Int J Cancer 2020; 146:2488-2497. [PMID: 32020592 PMCID: PMC7079087 DOI: 10.1002/ijc.32910] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 12/18/2019] [Accepted: 01/14/2020] [Indexed: 11/10/2022]
Abstract
Metastasis is a major cause of cancer-related mortality, and it is essential to understand how metastasis occurs in order to overcome it. One relevant question is the origin of a metastatic tumor cell population. Although the hypothesis of a single-cell origin for metastasis from a primary tumor has long been prevalent, several recent studies using mouse models have supported a multicellular origin of metastasis. Human bulk whole-exome sequencing (WES) studies also have demonstrated a multiple "clonal" origin of metastasis, with different mutational compositions. Specifically, there has not yet been strong research to determine how many founder cells colonize a metastatic tumor. To address this question, under the metastatic model of "single bottleneck followed by rapid growth," we developed a method to quantify the "founder cell population size" in a metastasis using paired WES data from primary and metachronous metastatic tumors. Simulation studies demonstrated the proposed method gives unbiased results with sufficient accuracy in the range of realistic settings. Applying the proposed method to real WES data from four colorectal cancer patients, all samples supported a multicellular origin of metastasis and the founder size was quantified, ranging from 3 to 17 cells. Such a wide-range of founder sizes estimated by the proposed method suggests that there are large variations in genetic similarity between primary and metastatic tumors in the same subjects, which may explain the observed (dis)similarity of drug responses between tumors.
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Affiliation(s)
- Jo Nishino
- Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan
| | - Shuichi Watanabe
- Department of Hepatobiliary and Pancreatic Surgery, Tokyo Medical and Dental University (TMDU), Tokyo, Japan
| | - Fuyuki Miya
- Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan.,Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Takashi Kamatani
- Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan.,Laboratory for Medical Science Mathematics, Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, Japan
| | - Toshitaka Sugawara
- Department of Hepatobiliary and Pancreatic Surgery, Tokyo Medical and Dental University (TMDU), Tokyo, Japan
| | - Keith A Boroevich
- Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Tatsuhiko Tsunoda
- Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University (TMDU), Tokyo, Japan.,Laboratory for Medical Science Mathematics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan.,Laboratory for Medical Science Mathematics, Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo, Japan.,CREST, JST, Tokyo, Japan
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Bernaś R, Poćwierz-Kotus A, Árnyasi M, Kent MP, Lien S, Wenne R. Genetic Differentiation in Hatchery and Stocked Populations of Sea Trout in the Southern Baltic: Selection Evidence at SNP Loci. Genes (Basel) 2020; 11:genes11020184. [PMID: 32050680 PMCID: PMC7073890 DOI: 10.3390/genes11020184] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Revised: 01/23/2020] [Accepted: 02/06/2020] [Indexed: 11/16/2022] Open
Abstract
The impacts and interactions between hatchery-bred fish and wild fish populations has been a topic of active investigation in recent decades. In some instances, the benefits of stocking can be overshadowed by negative effects such as genetic introgression with natural populations, loss of genetic diversity, and dilution of local adaptations. Methods that facilitate the identification of stocked fish enable us to estimate not only the effectiveness of stocking but also the level of natural reproduction and the degree of hybridization. The longest Baltic river, the Vistula, also has the second highest discharge. Historically, it hosted numerous populations of the anadromous form of brown trout (sea trout); however, dam construction has since interfered with and reduced spawning migration to a rate that is much lower than before. Reduced spawning has resulted in a population collapse and a negative flow-on effect on commercial catches. In response, Poland (along with many other Baltic countries) initiated an intensive stocking program which continues today and which sees the average annual release of 700,000 smolts. As a consequence, today’s main-river and inshore catches come from stock-enhanced populations. High-throughput single-nucleotide polymorphism (SNP) genotyping was performed on samples of sea trout from southern Baltic populations; results suggest that a significant portion of the sea trout catches in the Vistula mouth region have direct hatchery origin and indicate the presence of Pomeranian specimens. SNP loci identified as outliers indicate a potential selection pressure that may be related with effects of hatchery breeding and mixing with natural populations. The brown trout SNP array applied in this study showed high effectiveness not only for population differentiation, but more importantly, it emerged as a sensitive tool to provide evidence of detection selection.
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Affiliation(s)
- Rafał Bernaś
- Inland Fisheries Institute in Olsztyn, Department of Migratory Fishes, Rutki, 83-330 Żukowo, Poland
- Correspondence: ; Tel.: +48-585-507-704
| | - Anita Poćwierz-Kotus
- Institute of Oceanology, Polish Academy of Sciences, 81-712 Sopot, Poland; (A.P.-K.); (R.W.)
| | - Mariann Árnyasi
- Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences (IHA), Faculty of Life Sciences (BIOVIT), Norwegian University of Life Sciences (NMBU), 5003 Ås, Norway; (M.Á.); (M.P.K.); (S.L.)
| | - Matthew Peter Kent
- Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences (IHA), Faculty of Life Sciences (BIOVIT), Norwegian University of Life Sciences (NMBU), 5003 Ås, Norway; (M.Á.); (M.P.K.); (S.L.)
| | - Sigbjørn Lien
- Centre for Integrative Genetics (CIGENE), Department of Animal and Aquacultural Sciences (IHA), Faculty of Life Sciences (BIOVIT), Norwegian University of Life Sciences (NMBU), 5003 Ås, Norway; (M.Á.); (M.P.K.); (S.L.)
| | - Roman Wenne
- Institute of Oceanology, Polish Academy of Sciences, 81-712 Sopot, Poland; (A.P.-K.); (R.W.)
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41
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Zhao L, Ke H, Xu H, Wang GD, Zhang H, Zou L, Xiang S, Li M, Peng L, Zhou M, Li L, Ao L, Yang Q, Shen CKJ, Yi P, Wang L, Jiao B. TDP-43 facilitates milk lipid secretion by post-transcriptional regulation of Btn1a1 and Xdh. Nat Commun 2020; 11:341. [PMID: 31953403 PMCID: PMC6969145 DOI: 10.1038/s41467-019-14183-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Accepted: 12/13/2019] [Indexed: 12/31/2022] Open
Abstract
Milk lipid secretion is a critical process for the delivery of nutrition and energy from parent to offspring. However, the underlying molecular mechanism is less clear. Here we report that TDP-43, a RNA-binding protein, underwent positive selection in the mammalian lineage. Furthermore, TDP-43 gene (Tardbp) loss induces accumulation of large lipid droplets and severe lipid secretion deficiency in mammary epithelial cells to outside alveolar lumens, eventually resulting in lactation failure and pup starvation within three weeks postpartum. In human milk samples from lactating women, the expression levels of TDP-43 is positively correlated with higher milk output. Mechanistically, TDP-43 exerts post-transcriptional regulation of Btn1a1 and Xdh mRNA stability, which are required for the secretion of lipid droplets from epithelial cells to the lumen. Taken together, our results highlights the critical role of TDP-43 in milk lipid secretion, providing a potential strategy for the screening and intervention of clinical lactation insufficiency. Milk lipid secretion is a critical process for the delivery of nutrition and energy from parent to offspring. Here the authors found that TDP-43, a RNA-binding protein, is required for milk lipid secretion by post-transcriptional regulation of Btn1a1 and Xdh mRNA stability.
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Affiliation(s)
- Limin Zhao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, 650223, Kunming, China
| | - Hao Ke
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, 650223, Kunming, China
| | - Haibo Xu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223, Kunming, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, 650223, Kunming, China
| | - Guo-Dong Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223, Kunming, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, 650223, Kunming, China
| | - Honglei Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223, Kunming, China
| | - Li Zou
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223, Kunming, China
| | - Shu Xiang
- The First Hospital of Kunming, Calmette International Hospital, 650011, Kunming, China
| | - Mengyuan Li
- Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Chongqing Medical University, 401120, Chongqing, China
| | - Li Peng
- Yubei District Maternal and Child Health Care Hospital, 401120, Chongqing, China
| | - Mingfang Zhou
- Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Chongqing Medical University, 401120, Chongqing, China
| | - Lingling Li
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223, Kunming, China.,School of Life Sciences, University of Science and Technology of China, 230026, Hefei, China
| | - Lei Ao
- Kunming Angel Women's and Children's Hospital, 650032, Kunming, China
| | - Qin Yang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223, Kunming, China
| | - Che-Kun James Shen
- Institute of Molecular Biology, Academia Sinica, 11529, Taipei, Nankang, Taiwan
| | - Ping Yi
- Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Chongqing Medical University, 401120, Chongqing, China.
| | - Lu Wang
- State Key Laboratory for Conservation and Utilization of Bio-resources in Yunnan, Yunnan University, 650091, Kunming, China.
| | - Baowei Jiao
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223, Kunming, China. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, 650223, Kunming, China. .,KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, 650223, Kunming, China.
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42
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Abstract
Between the 1930s and 1950s, scientists developed key principles of population genetics to try and explain the aging process. Almost a century later, these aging theories, including antagonistic pleiotropy and mutation accumulation, have been experimentally validated in animals. Although the theories have been much harder to test in humans despite research dating back to the 1970s, recent research is closing this evidence gap. Here we examine the strength of evidence for antagonistic pleiotropy in humans, one of the leading evolutionary explanations for the retention of genetic risk variation for non-communicable diseases. We discuss the analytical tools and types of data that are used to test for patterns of antagonistic pleiotropy and provide a primer of evolutionary theory on types of selection as a guide for understanding this mechanism and how it may manifest in other diseases. We find an abundance of non-experimental evidence for antagonistic pleiotropy in many diseases. In some cases, several studies have independently found corroborating evidence for this mechanism in the same or related sets of diseases including cancer and neurodegenerative diseases. Recent studies also suggest antagonistic pleiotropy may be involved in cardiovascular disease and diabetes. There are also compelling examples of disease risk variants that confer fitness benefits ranging from resistance to other diseases or survival in extreme environments. This provides increasingly strong support for the theory that antagonistic pleiotropic variants have enabled improved fitness but have been traded for higher burden of disease later in life. Future research in this field is required to better understand how this mechanism influences contemporary disease and possible consequences for their treatment.
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Romero-Velarde E, Delgado-Franco D, García-Gutiérrez M, Gurrola-Díaz C, Larrosa-Haro A, Montijo-Barrios E, Muskiet FAJ, Vargas-Guerrero B, Geurts J. The Importance of Lactose in the Human Diet: Outcomes of a Mexican Consensus Meeting. Nutrients 2019; 11:E2737. [PMID: 31718111 PMCID: PMC6893676 DOI: 10.3390/nu11112737] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 11/04/2019] [Accepted: 11/08/2019] [Indexed: 12/12/2022] Open
Abstract
Lactose is a unique component of breast milk, many infant formulas and dairy products, and is widely used in pharmaceutical products. In spite of that, its role in human nutrition or lactose intolerance is generally not well-understood. For that reason, a 2-day-long lactose consensus meeting with health care professionals was organized in Mexico to come to a set of statements for which consensus could be gathered. Topics ranging from lactase expression to potential health benefits of lactose were introduced by experts, and that was followed by a discussion on concept statements. Interestingly, lactose does not seem to induce a neurological reward response when consumed. Although lactose digestion is optimal, it supplies galactose for liver glycogen synthesis. In infants, it cannot be ignored that lactose-derived galactose is needed for the synthesis of glycosylated macromolecules. At least beyond infancy, the low glycemic index of lactose might be metabolically beneficial. When lactase expression decreases, lactose maldigestion may lead to lactose intolerance symptoms. In infancy, the temporary replacing of lactose by other carbohydrates is only justified in case of severe intolerance symptoms. In those who show an (epi)genetic decrease or absence of lactase expression, a certain amount (for adults mostly up to 12 g per portion) of lactose can still be consumed. In these cases, lactose shows beneficial intestinal-microbiota-shaping effects. Avoiding lactose-containing products may imply a lower intake of other important nutrients, such as calcium and vitamin B12 from dairy products, as well as an increased intake of less beneficial carbohydrates.
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Affiliation(s)
- Enrique Romero-Velarde
- Instituto de Nutrición Humana, Universidad de Guadalajara and Hospital Civil de Guadalajara “Dr. Juan I. Menchaca”, 44340 Guadalajara, Jalisco, Mexico
| | - Dagoberto Delgado-Franco
- Neonatology Department. ABC Medical Center, 01120 Mexico City and Instituto Tecnológico de Estudios Superiores de Monterrey, 64849 Monterrey, Mexico;
| | | | - Carmen Gurrola-Díaz
- Departamento de Biología Molecular y Genómica. Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, 44340 Guadalajara, Jalisco, Mexico; (C.G.-D.); (B.V.-G.)
| | - Alfredo Larrosa-Haro
- Instituto de Nutrición Humana, Universidad de Guadalajara, 44340 Guadalajara, Jalisco, Mexico;
| | - Ericka Montijo-Barrios
- Servicio de Gastroenterología. Instituto Nacional de Pediatría, 04530 Mexico City, Mexico;
| | - Frits A. J. Muskiet
- Laboratory Medicine, University Medical Center Groningen and University of Groningen, 9713 GZ Groningen, The Netherlands;
| | - Belinda Vargas-Guerrero
- Departamento de Biología Molecular y Genómica. Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, 44340 Guadalajara, Jalisco, Mexico; (C.G.-D.); (B.V.-G.)
| | - Jan Geurts
- FrieslandCampina, 3818 LEAmersfoort, The Netherlands;
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Abstract
The genetic variation of our species reflects human demographic history and adaptation to diverse local environments. Part of this genetic variation affects individual responses to exogenous substances, such as food, pollutants and drugs, and plays an important role in drug efficacy and safety. This review provides a synthesis of the evolution of loci implicated in human pharmacological response and metabolism, interpreted within the theoretical framework of population genetics and molecular evolution. In particular, I review and discuss key evolutionary aspects of different pharmacogenes in humans and other species, such as the relationship between the type of substrates and rate of evolution; the selective pressure exerted by landscape variables or dietary habits; expected and observed patterns of rare genetic variation. Finally, I discuss how this knowledge can be translated directly or after the implementation of specific studies, into practical guidelines.
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Affiliation(s)
- Silvia Fuselli
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
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45
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Zhang C, Gao Y, Ning Z, Lu Y, Zhang X, Liu J, Xie B, Xue Z, Wang X, Yuan K, Ge X, Pan Y, Liu C, Tian L, Wang Y, Lu D, Hoh BP, Xu S. PGG.SNV: understanding the evolutionary and medical implications of human single nucleotide variations in diverse populations. Genome Biol 2019; 20:215. [PMID: 31640808 PMCID: PMC6805450 DOI: 10.1186/s13059-019-1838-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Accepted: 09/26/2019] [Indexed: 12/23/2022] Open
Abstract
Despite the tremendous growth of the DNA sequencing data in the last decade, our understanding of the human genome is still in its infancy. To understand the implications of genetic variants in the light of population genetics and molecular evolution, we developed a database, PGG.SNV ( https://www.pggsnv.org ), which gives much higher weight to previously under-investigated indigenous populations in Asia. PGG.SNV archives 265 million SNVs across 220,147 present-day genomes and 1018 ancient genomes, including 1009 newly sequenced genomes, representing 977 global populations. Moreover, estimation of population genetic diversity and evolutionary parameters is available in PGG.SNV, a unique feature compared with other databases.
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Affiliation(s)
- Chao Zhang
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
- Present Address: Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Yang Gao
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Zhilin Ning
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
| | - Yan Lu
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
| | - Xiaoxi Zhang
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Jiaojiao Liu
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Bo Xie
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
| | - Zhe Xue
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
| | - Xiaoji Wang
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
| | - Kai Yuan
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
| | - Xueling Ge
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
| | - Yuwen Pan
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
| | - Chang Liu
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
| | - Lei Tian
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
| | - Yuchen Wang
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
| | - Dongsheng Lu
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
| | - Boon-Peng Hoh
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China
- Faculty of Medicine and Health Sciences, UCSI University, Jalan Menara Gading, Taman Connaught, Cheras, 56000, Kuala Lumpur, Malaysia
| | - Shuhua Xu
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology (PICB), Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, CAS, Shanghai, 200031, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- Collaborative Innovation Center of Genetics and Development, Shanghai, 200438, China.
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46
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Smith CCR, Flaxman SM. Leveraging whole genome sequencing data for demographic inference with approximate Bayesian computation. Mol Ecol Resour 2019; 20:125-139. [DOI: 10.1111/1755-0998.13092] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 08/30/2019] [Accepted: 09/06/2019] [Indexed: 01/16/2023]
Affiliation(s)
- Chris C. R. Smith
- Department of Ecology and Evolutionary Biology University of Colorado Boulder CO USA
| | - Samuel M. Flaxman
- Department of Ecology and Evolutionary Biology University of Colorado Boulder CO USA
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47
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Schreiweis C, Irinopoulou T, Vieth B, Laddada L, Oury F, Burguière E, Enard W, Groszer M. Mice carrying a humanized Foxp2 knock-in allele show region-specific shifts of striatal Foxp2 expression levels. Cortex 2019; 118:212-222. [DOI: 10.1016/j.cortex.2019.01.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Revised: 11/07/2018] [Accepted: 01/08/2019] [Indexed: 12/31/2022]
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48
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Harpur BA, Guarna MM, Huxter E, Higo H, Moon KM, Hoover SE, Ibrahim A, Melathopoulos AP, Desai S, Currie RW, Pernal SF, Foster LJ, Zayed A. Integrative Genomics Reveals the Genetics and Evolution of the Honey Bee's Social Immune System. Genome Biol Evol 2019; 11:937-948. [PMID: 30768172 PMCID: PMC6447389 DOI: 10.1093/gbe/evz018] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/24/2019] [Indexed: 12/13/2022] Open
Abstract
Social organisms combat pathogens through individual innate immune responses or through social immunity—behaviors among individuals that limit pathogen transmission within groups. Although we have a relatively detailed understanding of the genetics and evolution of the innate immune system of animals, we know little about social immunity. Addressing this knowledge gap is crucial for understanding how life-history traits influence immunity, and identifying if trade-offs exist between innate and social immunity. Hygienic behavior in the Western honey bee, Apis mellifera, provides an excellent model for investigating the genetics and evolution of social immunity in animals. This heritable, colony-level behavior is performed by nurse bees when they detect and remove infected or dead brood from the colony. We sequenced 125 haploid genomes from two artificially selected highly hygienic populations and a baseline unselected population. Genomic contrasts allowed us to identify a minimum of 73 genes tentatively associated with hygienic behavior. Many genes were within previously discovered QTLs associated with hygienic behavior and were predictive of hygienic behavior within the unselected population. These genes were often involved in neuronal development and sensory perception in solitary insects. We found that genes associated with hygienic behavior have evidence of positive selection within honey bees (Apis), supporting the hypothesis that social immunity contributes to fitness. Our results indicate that genes influencing developmental neurobiology and behavior in solitary insects may have been co-opted to give rise to a novel and adaptive social immune phenotype in honey bees.
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Affiliation(s)
- Brock A Harpur
- Department of Entomology, Purdue University.,Department of Biology, York University, Toronto, Ontario, Canada
| | - Maria Marta Guarna
- Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, British Columbia, Canada.,Agriculture and Agri-Food Canada, Beaverlodge Research Farm, Beaverlodge, Alberta, Canada
| | | | - Heather Higo
- Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Kyung-Mee Moon
- Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Shelley E Hoover
- Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, British Columbia, Canada.,Agriculture and Agri-Food Canada, Beaverlodge Research Farm, Beaverlodge, Alberta, Canada.,Alberta Agriculture and Forestry, Agriculture Centre, Lethbridge, Alberta, Canada
| | - Abdullah Ibrahim
- Agriculture and Agri-Food Canada, Beaverlodge Research Farm, Beaverlodge, Alberta, Canada
| | - Andony P Melathopoulos
- Agriculture and Agri-Food Canada, Beaverlodge Research Farm, Beaverlodge, Alberta, Canada.,Department of Horticulture, College of Agricultural Sciences, Oregon State University
| | - Suresh Desai
- Department of Entomology, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Robert W Currie
- Department of Entomology, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Stephen F Pernal
- Agriculture and Agri-Food Canada, Beaverlodge Research Farm, Beaverlodge, Alberta, Canada
| | - Leonard J Foster
- Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Amro Zayed
- Department of Biology, York University, Toronto, Ontario, Canada
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49
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Szpak M, Xue Y, Ayub Q, Tyler‐Smith C. How well do we understand the basis of classic selective sweeps in humans? FEBS Lett 2019; 593:1431-1448. [DOI: 10.1002/1873-3468.13447] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 04/29/2019] [Accepted: 05/17/2019] [Indexed: 12/14/2022]
Affiliation(s)
| | - Yali Xue
- The Wellcome Sanger Institute Hinxton UK
| | - Qasim Ayub
- School of Science Monash University Malaysia Bandar Sunway Malaysia
- Tropical Medicine and Biology Multidisciplinary Platform Monash University Malaysia Genomics Facility Bandar Sunway Malaysia
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50
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