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Tiwari M, Gujar G, Shashank CG, Ponsuksili S. Selection signatures for high altitude adaptation in livestock: A review. Gene 2024; 927:148757. [PMID: 38986751 DOI: 10.1016/j.gene.2024.148757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Revised: 07/01/2024] [Accepted: 07/05/2024] [Indexed: 07/12/2024]
Abstract
High altitude adapted livestock species (cattle, yak, goat, sheep, and horse) has critical role in the human socioeconomic sphere and acts as good source of animal source products including milk, meat, and leather, among other things. These species sustain production and reproduction even in harsh environments on account of adaptation resulting from continued evolution of beneficial traits. Selection pressure leads to various adaptive strategies in livestock whose footprints are evident at the different genomic sites as the "Selection Signature". Scrutiny of these signatures provides us crucial insight into the evolutionary process and domestication of livestock adapted to diverse climatic conditions. These signatures have the potential to change the sphere of animal breeding and further usher the selection programmes in right direction. Technological revolution and recent strides made in genomic studies has opened the routes for the identification of selection signatures. Numerous statistical approaches and bioinformatics tools have been developed to detect the selection signature. Consequently, studies across years have identified candidate genes under selection region found associated with numerous traits which have a say in adaptation to high-altitude environment. This makes it pertinent to have a better understanding about the selection signature, the ways to identify and how to utilize them for betterment of livestock populations as well as farmers. This review takes a closer look into the general concept, various methodologies, and bioinformatics tools commonly employed in selection signature studies and summarize the results of recent selection signature studies related to high-altitude adaptation in various livestock species. This review will serve as an informative and useful insight for researchers and students in the field of animal breeding and evolutionary biology.
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Affiliation(s)
- Manish Tiwari
- ICAR-National Dairy Research Institute, Karnal, India; U.P. Pt. Deen Dayal Upadhyaya Veterinary Science University and Cattle Research Institute, Mathura, India.
| | | | - C G Shashank
- ICAR-National Dairy Research Institute, Karnal, India
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2
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Shi L, Zhang P, Liu Q, Liu C, Cheng L, Yu B, Chen H. Genome-Wide Analysis of Genetic Diversity and Selection Signatures in Zaobei Beef Cattle. Animals (Basel) 2024; 14:2447. [PMID: 39199980 PMCID: PMC11350888 DOI: 10.3390/ani14162447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2024] [Revised: 08/17/2024] [Accepted: 08/21/2024] [Indexed: 09/01/2024] Open
Abstract
This investigation provides a comprehensive analysis of genomic diversity and selection signatures in Zaobei beef cattle, an indigenous breed known for its adaptation to hot and humid climates and superior meat quality. Whole-genome resequencing was conducted on 23 Zaobei cattle, compared with 46 Simmental cattle to highlight genetic distinctions. Population structure analysis confirmed the genetic uniqueness of Zaobei cattle. Using methods such as DASDC v1.01, XPEHH, and θπ ratio, we identified 230, 232, and 221 genes through DASDC, including hard sweeps, soft sweeps, and linkage sweeps, respectively. Coincidentally, 109 genes were identified when using XPEHH and θπ ratio methods. Together, these analyses revealed eight positive selection genes (ARHGAP15, ZNF618, USH2A, PDZRN4, SPATA6, ROR2, KCNIP3, and VWA3B), which are linked to critical traits such as heat stress adaptation, fertility, and meat quality. Moreover, functional enrichment analyses showed pathways related to autophagy, immune response, energy metabolism, and muscle development. The comprehensive genomic insights gained from this study provide valuable knowledge for breeding programs aimed at enhancing the beneficial traits in Zaobei cattle.
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Affiliation(s)
- Liangyu Shi
- Laboratory of Genetic Breeding, Reproduction and Precision Livestock Farming & Hubei Provincial Center of Technology Innovation for Domestic Animal Breeding, School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan 430023, China; (L.S.); (P.Z.); (Q.L.)
| | - Pu Zhang
- Laboratory of Genetic Breeding, Reproduction and Precision Livestock Farming & Hubei Provincial Center of Technology Innovation for Domestic Animal Breeding, School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan 430023, China; (L.S.); (P.Z.); (Q.L.)
| | - Qing Liu
- Laboratory of Genetic Breeding, Reproduction and Precision Livestock Farming & Hubei Provincial Center of Technology Innovation for Domestic Animal Breeding, School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan 430023, China; (L.S.); (P.Z.); (Q.L.)
| | - Chenhui Liu
- Institute of Animal Science and Veterinary Medicine, Wuhan Academy of Agricultural Sciences, Wuhan 430208, China; (C.L.); (L.C.)
| | - Lei Cheng
- Institute of Animal Science and Veterinary Medicine, Wuhan Academy of Agricultural Sciences, Wuhan 430208, China; (C.L.); (L.C.)
| | - Bo Yu
- Laboratory of Genetic Breeding, Reproduction and Precision Livestock Farming & Hubei Provincial Center of Technology Innovation for Domestic Animal Breeding, School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan 430023, China; (L.S.); (P.Z.); (Q.L.)
| | - Hongbo Chen
- Laboratory of Genetic Breeding, Reproduction and Precision Livestock Farming & Hubei Provincial Center of Technology Innovation for Domestic Animal Breeding, School of Animal Science and Nutritional Engineering, Wuhan Polytechnic University, Wuhan 430023, China; (L.S.); (P.Z.); (Q.L.)
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3
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Soni V, Jensen JD. Temporal challenges in detecting balancing selection from population genomic data. G3 (BETHESDA, MD.) 2024; 14:jkae069. [PMID: 38551137 DOI: 10.1093/g3journal/jkae069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 12/21/2023] [Accepted: 03/19/2024] [Indexed: 04/28/2024]
Abstract
The role of balancing selection in maintaining genetic variation remains an open question in population genetics. Recent years have seen numerous studies identifying candidate loci potentially experiencing balancing selection, most predominantly in human populations. There are however numerous alternative evolutionary processes that may leave similar patterns of variation, thereby potentially confounding inference, and the expected signatures of balancing selection additionally change in a temporal fashion. Here we use forward-in-time simulations to quantify expected statistical power to detect balancing selection using both site frequency spectrum- and linkage disequilibrium-based methods under a variety of evolutionarily realistic null models. We find that whilst site frequency spectrum-based methods have little power immediately after a balanced mutation begins segregating, power increases with time since the introduction of the balanced allele. Conversely, linkage disequilibrium-based methods have considerable power whilst the allele is young, and power dissipates rapidly as the time since introduction increases. Taken together, this suggests that site frequency spectrum-based methods are most effective at detecting long-term balancing selection (>25N generations since the introduction of the balanced allele) whilst linkage disequilibrium-based methods are effective over much shorter timescales (<1N generations), thereby leaving a large time frame over which current methods have little power to detect the action of balancing selection. Finally, we investigate the extent to which alternative evolutionary processes may mimic these patterns, and demonstrate the need for caution in attempting to distinguish the signatures of balancing selection from those of both neutral processes (e.g. population structure and admixture) as well as of alternative selective processes (e.g. partial selective sweeps).
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Affiliation(s)
- Vivak Soni
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ 85281, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ 85281, USA
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4
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Yu H, Zhang K, Cheng G, Mei C, Wang H, Zan L. Genome-wide analysis reveals genomic diversity and signatures of selection in Qinchuan beef cattle. BMC Genomics 2024; 25:558. [PMID: 38834950 DOI: 10.1186/s12864-024-10482-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Accepted: 05/30/2024] [Indexed: 06/06/2024] Open
Abstract
BACKGROUND Indigenous Chinese cattle have abundant genetic diversity and a long history of artificial selection, giving local breeds advantages in adaptability, forage tolerance and resistance. The detection of selective sweeps and comparative genome analysis of selected breeds and ancestral populations provide a basis for understanding differences among breeds and for the identification and utilization of candidate genes. We investigated genetic diversity, population structure, and signatures of selection using genome-wide sequencing data for a new breed of Qinchuan cattle (QNC, n = 21), ancestral Qinchuan cattle (QCC, n = 20), and Zaosheng cattle (ZSC, n = 19). RESULTS A population structure analysis showed that the ancestry components of QNC and ZSC were similar. In addition, the QNC and ZSC groups showed higher proportions of European taurine ancestry than that of QCC, and this may explain the larger body size of QNC, approaching that of European cattle under long-term domestication and selection. A neighbor-joining tree revealed that QCC individuals were closely related, whereas QNC formed a distinct group. To search for signatures of selection in the QNC genome, we evaluated nucleotide diversity (θπ), the fixation index (FST) and Tajima's D. Overlapping selective sweeps were enriched for one KEGG pathway, the apelin signaling pathway, and included five candidate genes (MEF2A, SMAD2, CAMK4, RPS6, and PIK3CG). We performed a comprehensive review of genomic variants in QNC, QCC, and ZSC using whole-genome sequencing data. QCC was rich in novel genetic diversity, while diversity in QNC and ZSC cattle was reduced due to strong artificial selection, with divergence from the original cattle. CONCLUSIONS We identified candidate genes associated with production traits. These results support the success of selective breeding and can guide further breeding and resource conservation of Qinchuan cattle.
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Affiliation(s)
- Hengwei Yu
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, 712100, China
| | - Ke Zhang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, 712100, China
| | - Gong Cheng
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, 712100, China
| | - Chugang Mei
- College of Grassland Agriculture, Northwest A&F University, No.22 Xinong Road, Yangling, 712100, China
- National Beef Cattle Improvement Center, Yangling, 712100, China
| | - Hongbao Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, 712100, China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, 712100, China.
- National Beef Cattle Improvement Center, Yangling, 712100, China.
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Kebede FG, Derks MFL, Dessie T, Hanotte O, Barros CP, Crooijmans RPMA, Komen H, Bastiaansen JWM. Landscape genomics reveals regions associated with adaptive phenotypic and genetic variation in Ethiopian indigenous chickens. BMC Genomics 2024; 25:284. [PMID: 38500079 PMCID: PMC10946127 DOI: 10.1186/s12864-024-10193-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 03/05/2024] [Indexed: 03/20/2024] Open
Abstract
Climate change is a threat to sustainable livestock production and livelihoods in the tropics. It has adverse impacts on feed and water availability, disease prevalence, production, environmental temperature, and biodiversity. Unravelling the drivers of local adaptation and understanding the underlying genetic variation in random mating indigenous livestock populations informs the design of genetic improvement programmes that aim to increase productivity and resilience. In the present study, we combined environmental, genomic, and phenotypic information of Ethiopian indigenous chickens to investigate their environmental adaptability. Through a hybrid sampling strategy, we captured wide biological and ecological variabilities across the country. Our environmental dataset comprised mean values of 34 climatic, vegetation and soil variables collected over a thirty-year period for 260 geolocations. Our biological dataset included whole genome sequences and quantitative measurements (on eight traits) from 513 individuals, representing 26 chicken populations spread along 4 elevational gradients (6-7 populations per gradient). We performed signatures of selection analyses ([Formula: see text] and XP-EHH) to detect footprints of natural selection, and redundancy analyses (RDA) to determine genotype-environment and genotype-phenotype-associations. RDA identified 1909 outlier SNPs linked with six environmental predictors, which have the highest contributions as ecological drivers of adaptive phenotypic variation. The same method detected 2430 outlier SNPs that are associated with five traits. A large overlap has been observed between signatures of selection identified by[Formula: see text]and XP-EHH showing that both methods target similar selective sweep regions. Average genetic differences measured by [Formula: see text] are low between gradients, but XP-EHH signals are the strongest between agroecologies. Genes in the calcium signalling pathway, those associated with the hypoxia-inducible factor (HIF) transcription factors, and sports performance (GALNTL6) are under selection in high-altitude populations. Our study underscores the relevance of landscape genomics as a powerful interdisciplinary approach to dissect adaptive phenotypic and genetic variation in random mating indigenous livestock populations.
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Affiliation(s)
- Fasil Getachew Kebede
- Animal Breeding and Genomics, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen, PB-6708, The Netherlands.
- International Livestock Research Institute, P.O. Box 5689, Addis Ababa, Ethiopia.
| | - Martijn F L Derks
- Animal Breeding and Genomics, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen, PB-6708, The Netherlands
| | - Tadelle Dessie
- International Livestock Research Institute, P.O. Box 5689, Addis Ababa, Ethiopia
| | - Olivier Hanotte
- International Livestock Research Institute, P.O. Box 5689, Addis Ababa, Ethiopia
- School of Life Sciences, The University of Nottingham, Nottingham, NG7 2RD, UK
| | - Carolina Pita Barros
- Animal Breeding and Genomics, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen, PB-6708, The Netherlands
| | - Richard P M A Crooijmans
- Animal Breeding and Genomics, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen, PB-6708, The Netherlands
| | - Hans Komen
- Animal Breeding and Genomics, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen, PB-6708, The Netherlands
| | - John W M Bastiaansen
- Animal Breeding and Genomics, Wageningen University & Research, Droevendaalsesteeg 1, Wageningen, PB-6708, The Netherlands
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Treindl AD, Stapley J, Croll D, Leuchtmann A. Two-speed genomes of Epichloe fungal pathogens show contrasting signatures of selection between species and across populations. Mol Ecol 2024; 33:e17242. [PMID: 38084851 DOI: 10.1111/mec.17242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 11/23/2023] [Accepted: 11/30/2023] [Indexed: 12/19/2023]
Abstract
Antagonistic selection between pathogens and their hosts can drive rapid evolutionary change and leave distinct molecular footprints of past and ongoing selection in the genomes of the interacting species. Despite an increasing availability of tools able to identify signatures of selection, the genetic mechanisms underlying coevolutionary interactions and the specific genes involved are still poorly understood, especially in heterogeneous natural environments. We searched the genomes of two species of Epichloe plant pathogen for evidence of recent selection. The Epichloe genus includes highly host-specific species that can sterilize their grass hosts. We performed selection scans using genome-wide SNP data from seven natural populations of two co-occurring Epichloe sibling species specialized on different hosts. We found evidence of recent (and ongoing) selective sweeps across the genome in both species. However, selective sweeps were more abundant in the species with a larger effective population size. Sweep regions often overlapped with highly polymorphic AT-rich regions supporting the role of these genome compartments in adaptive evolution. Although most loci under selection were specific to individual populations, we could also identify several candidate genes targeted by selection in sweep regions shared among populations. The genes encoded small secreted proteins typical of fungal effectors and cell wall-degrading enzymes. By investigating the genomic signatures of selection across multiple populations and species, this study contributes to our understanding of complex adaptive processes in natural plant pathogen systems.
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Affiliation(s)
- Artemis D Treindl
- Plant Ecological Genetics Group, Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland
- Biodiversity and Conservation Biology, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland
| | - Jessica Stapley
- Plant Pathology Group, Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland
| | - Daniel Croll
- Laboratory of Evolutionary Genetics, Institute of Biology, University of Neuchâtel, Neuchâtel, Switzerland
| | - Adrian Leuchtmann
- Plant Ecological Genetics Group, Institute of Integrative Biology, ETH Zurich, Zurich, Switzerland
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7
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Soni V, Johri P, Jensen JD. Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models. Evolution 2023; 77:2113-2127. [PMID: 37395482 PMCID: PMC10547124 DOI: 10.1093/evolut/qpad120] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/15/2023] [Accepted: 06/30/2023] [Indexed: 07/04/2023]
Abstract
The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modeled by a realistic mutation rate and as part of a realistic distribution of fitness effects, as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modeled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false-positive rates are in excess of true-positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.
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Affiliation(s)
- Vivak Soni
- School of Life Sciences, Arizona State University, Tempe, AZ, United States
| | - Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ, United States
| | - Jeffrey D Jensen
- School of Life Sciences, Arizona State University, Tempe, AZ, United States
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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, MD.) 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] [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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Smith SK, Frazel PW, Khodadadi-Jamayran A, Zappile P, Marier C, Okhovat M, Brown S, Long MA, Heguy A, Phelps SM. De novo assembly and annotation of the singing mouse genome. BMC Genomics 2023; 24:569. [PMID: 37749493 PMCID: PMC10521431 DOI: 10.1186/s12864-023-09678-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 09/14/2023] [Indexed: 09/27/2023] Open
Abstract
BACKGROUND Developing genomic resources for a diverse range of species is an important step towards understanding the mechanisms underlying complex traits. Specifically, organisms that exhibit unique and accessible phenotypes-of-interest allow researchers to address questions that may be ill-suited to traditional model organisms. We sequenced the genome and transcriptome of Alston's singing mouse (Scotinomys teguina), an emerging model for social cognition and vocal communication. In addition to producing advertisement songs used for mate attraction and male-male competition, these rodents are diurnal, live at high-altitudes, and are obligate insectivores, providing opportunities to explore diverse physiological, ecological, and evolutionary questions. RESULTS Using PromethION, Illumina, and PacBio sequencing, we produced an annotated genome and transcriptome, which were validated using gene expression and functional enrichment analyses. To assess the usefulness of our assemblies, we performed single nuclei sequencing on cells of the orofacial motor cortex, a brain region implicated in song coordination, identifying 12 cell types. CONCLUSIONS These resources will provide the opportunity to identify the molecular basis of complex traits in singing mice as well as to contribute data that can be used for large-scale comparative analyses.
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Affiliation(s)
- Samantha K Smith
- Department of Integrative Biology, University of Texas at Austin, Austin, TX, 78712, USA.
| | - Paul W Frazel
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Alireza Khodadadi-Jamayran
- Applied Bioinformatics Laboratory, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Paul Zappile
- Genome Technology Center, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Christian Marier
- Genome Technology Center, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Mariam Okhovat
- Department of Integrative Biology, University of Texas at Austin, Austin, TX, 78712, USA
- Present Address: Oregon Health & Science University, Portland, OR, USA
| | - Stuart Brown
- NYU Center for Health Informatics and Bioinformatics, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Present Address: Exxon Mobil Corporate, Houston, TX, USA
| | - Michael A Long
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Adriana Heguy
- Genome Technology Center, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Steven M Phelps
- Department of Integrative Biology, University of Texas at Austin, Austin, TX, 78712, USA
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10
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Hawliczek A, Borzęcka E, Tofil K, Alachiotis N, Bolibok L, Gawroński P, Siekmann D, Hackauf B, Dušinský R, Švec M, Bolibok-Brągoszewska H. Selective sweeps identification in distinct groups of cultivated rye (Secale cereale L.) germplasm provides potential candidate genes for crop improvement. BMC PLANT BIOLOGY 2023; 23:323. [PMID: 37328739 PMCID: PMC10273710 DOI: 10.1186/s12870-023-04337-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Accepted: 06/07/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND During domestication and subsequent improvement plants were subjected to intensive positive selection for desirable traits. Identification of selection targets is important with respect to the future targeted broadening of diversity in breeding programmes. Rye (Secale cereale L.) is a cereal that is closely related to wheat, and it is an important crop in Central, Eastern and Northern Europe. The aim of the study was (i) to identify diverse groups of rye accessions based on high-density, genome-wide analysis of genetic diversity within a set of 478 rye accessions, covering a full spectrum of diversity within the genus, from wild accessions to inbred lines used in hybrid breeding, and (ii) to identify selective sweeps in the established groups of cultivated rye germplasm and putative candidate genes targeted by selection. RESULTS Population structure and genetic diversity analyses based on high-quality SNP (DArTseq) markers revealed the presence of three complexes in the Secale genus: S. sylvestre, S. strictum and S. cereale/vavilovii, a relatively narrow diversity of S. sylvestre, very high diversity of S. strictum, and signatures of strong positive selection in S. vavilovii. Within cultivated ryes we detected the presence of genetic clusters and the influence of improvement status on the clustering. Rye landraces represent a reservoir of variation for breeding, and especially a distinct group of landraces from Turkey should be of special interest as a source of untapped variation. Selective sweep detection in cultivated accessions identified 133 outlier positions within 13 sweep regions and 170 putative candidate genes related, among others, to response to various environmental stimuli (such as pathogens, drought, cold), plant fertility and reproduction (pollen sperm cell differentiation, pollen maturation, pollen tube growth), and plant growth and biomass production. CONCLUSIONS Our study provides valuable information for efficient management of rye germplasm collections, which can help to ensure proper safeguarding of their genetic potential and provides numerous novel candidate genes targeted by selection in cultivated rye for further functional characterisation and allelic diversity studies.
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Affiliation(s)
- Anna Hawliczek
- Department of Plant Genetics, Breeding and Biotechnology, Institute of Biology, Warsaw, University of Life Sciences-SGGW, Warsaw, Poland
| | - Ewa Borzęcka
- Department of Plant Genetics, Breeding and Biotechnology, Institute of Biology, Warsaw, University of Life Sciences-SGGW, Warsaw, Poland
| | - Katarzyna Tofil
- Department of Plant Genetics, Breeding and Biotechnology, Institute of Biology, Warsaw, University of Life Sciences-SGGW, Warsaw, Poland
| | - Nikolaos Alachiotis
- Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, Enschede, The Netherlands
| | - Leszek Bolibok
- Department of Silviculture, Institute of Forest Sciences, Warsaw University of Life Sciences-SGGW, Warsaw, Poland
| | - Piotr Gawroński
- Department of Plant Genetics, Breeding and Biotechnology, Institute of Biology, Warsaw, University of Life Sciences-SGGW, Warsaw, Poland
| | | | | | - Roman Dušinský
- Department of Botany, Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovakia
| | - Miroslav Švec
- Department of Botany, Faculty of Natural Sciences, Comenius University in Bratislava, Bratislava, Slovakia
| | - Hanna Bolibok-Brągoszewska
- Department of Plant Genetics, Breeding and Biotechnology, Institute of Biology, Warsaw, University of Life Sciences-SGGW, Warsaw, Poland.
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11
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Soni V, Johri P, Jensen JD. Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.15.545166. [PMID: 37398347 PMCID: PMC10312679 DOI: 10.1101/2023.06.15.545166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modelled by a realistic mutation rate and as part of a realistic distribution of fitness effects (DFE), as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modelled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false positive rates are in excess of true positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong. Teaser Text Outlier-based genomic scans have proven a popular approach for identifying loci that have potentially experienced recent positive selection. However, it has previously been shown that an evolutionarily appropriate baseline model that incorporates non-equilibrium population histories, purifying and background selection, and variation in mutation and recombination rates is necessary to reduce often extreme false positive rates when performing genomic scans. Here we evaluate the power to detect recurrent selective sweeps using common SFS-based and haplotype-based methods under these increasingly realistic models. We find that while these appropriate evolutionary baselines are essential to reduce false positive rates, the power to accurately detect recurrent selective sweeps is generally low across much of the biologically relevant parameter space.
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Affiliation(s)
- Vivak Soni
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
| | - Parul Johri
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Present address: Department of Biology, Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
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12
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Cohen ZP, Schoville SD, Hawthorne DJ. The role of structural variants in pest adaptation and genome evolution of the Colorado potato beetle, Leptinotarsa decemlineata (Say). Mol Ecol 2023; 32:1425-1440. [PMID: 36591939 DOI: 10.1111/mec.16838] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 11/30/2022] [Accepted: 12/15/2022] [Indexed: 01/03/2023]
Abstract
Structural variation has been associated with genetic diversity and adaptation. Despite these observations, it is not clear what their relative importance is for evolution, especially in rapidly adapting species. Here, we examine the significance of structural polymorphisms in pesticide resistance evolution of the agricultural super-pest, the Colorado potato beetle, Leptinotarsa decemlineata. By employing a parent offspring trio sequencing procedure, we develop highly contiguous reference genomes to characterize structural variation. These updated assemblies represent >100-fold improvement of contiguity and include derived pest and ancestral nonpest individuals. We identify >200,000 structural variations, which appear to be nonrandomly distributed across the genome as they co-occur with transposable elements and genes. Structural variations intersect with exons in a large proportion of gene annotations (~20%) that are associated with insecticide resistance (including cytochrome P450s), development, and transcription. To understand the role structural variations play in adaptation, we measure their allele frequencies among an additional 57 individuals using whole genome resequencing data, which represents pest and nonpest populations of North America. Incorporating multiple independent tests to detect the signature of natural selection using SNP data, we identify 14 genes that are probably under positive selection, include structural variations, and SNPs of elevated frequency within the pest lineages. Among these, three are associated with insecticide resistance based on previous research. One of these genes, CYP4g15, is coinduced during insecticide exposure with glycosyltransferase-13, which is a duplicated gene enclosed within a structural variant adjacent to the CYP4g15 genic region. These results demonstrate the significance of structural variations as a genomic feature to describe species history, genetic diversity, and adaptation.
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Affiliation(s)
- Zachary P Cohen
- Department of Entomology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Sean D Schoville
- Department of Entomology, University of Wisconsin-Madison, Madison, Wisconsin, USA
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13
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Fang Y, Deng S, Li C. A generalizable deep learning framework for inferring fine-scale germline mutation rate maps. NAT MACH INTELL 2022. [DOI: 10.1038/s42256-022-00574-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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14
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Gabián M, Morán P, Saura M, Carvajal-Rodríguez A. Detecting Local Adaptation between North and South European Atlantic Salmon Populations. BIOLOGY 2022; 11:933. [PMID: 35741456 PMCID: PMC9219887 DOI: 10.3390/biology11060933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 06/09/2022] [Accepted: 06/16/2022] [Indexed: 06/15/2023]
Abstract
Pollution and other anthropogenic effects have driven a decrease in Atlantic salmon (Salmo salar) in the Iberian Peninsula. The restocking effort carried out in the 1980s, with salmon from northern latitudes with the aim of mitigating the decline of native populations, failed, probably due to the deficiency in adaptation of foreign salmon from northern Europe to the warm waters of the Iberian Peninsula. This result would imply that the Iberian populations of Atlantic salmon have experienced local adaptation in their past evolutionary history, as has been described for other populations of this species and other salmonids. Local adaptation can occur by divergent selections between environments, favoring the fixation of alleles that increase the fitness of a population in the environment it inhabits relative to other alleles favored in another population. In this work, we compared the genomes of different populations from the Iberian Peninsula (Atlantic and Cantabric basins) and Scotland in order to provide tentative evidence of candidate SNPs responsible for the adaptive differences between populations, which may explain the failures of restocking carried out during the 1980s. For this purpose, the samples were genotyped with a 220,000 high-density SNP array (Affymetrix) specific to Atlantic salmon. Our results revealed potential evidence of local adaptation for North Spanish and Scottish populations. As expected, most differences concerned the comparison of the Iberian Peninsula with Scotland, although there were also differences between Atlantic and Cantabric populations. A high proportion of the genes identified are related to development and cellular metabolism, DNA transcription and anatomical structure. A particular SNP was identified within the NADP-dependent malic enzyme-2 (mMEP-2*), previously reported by independent studies as a candidate for local adaptation in salmon from the Iberian Peninsula. Interestingly, the corresponding SNP within the mMEP-2* region was consistent with a genomic pattern of divergent selection.
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Affiliation(s)
- María Gabián
- Centro de Investigación Mariña (CIM), Departamento de Bioquímica, Genética e Inmunología, Universidade de Vigo, 36310 Vigo, Spain; (M.G.); (P.M.)
| | - Paloma Morán
- Centro de Investigación Mariña (CIM), Departamento de Bioquímica, Genética e Inmunología, Universidade de Vigo, 36310 Vigo, Spain; (M.G.); (P.M.)
| | - María Saura
- Departamento de Mejora Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), 28040 Madrid, Spain;
| | - Antonio Carvajal-Rodríguez
- Centro de Investigación Mariña (CIM), Departamento de Bioquímica, Genética e Inmunología, Universidade de Vigo, 36310 Vigo, Spain; (M.G.); (P.M.)
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15
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De-la-Cruz IM, Batsleer F, Bonte D, Diller C, Hytönen T, Muola A, Osorio S, Posé D, Vandegehuchte ML, Stenberg JA. Evolutionary Ecology of Plant-Arthropod Interactions in Light of the "Omics" Sciences: A Broad Guide. FRONTIERS IN PLANT SCIENCE 2022; 13:808427. [PMID: 35548276 PMCID: PMC9084618 DOI: 10.3389/fpls.2022.808427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 04/01/2022] [Indexed: 06/15/2023]
Abstract
Aboveground plant-arthropod interactions are typically complex, involving herbivores, predators, pollinators, and various other guilds that can strongly affect plant fitness, directly or indirectly, and individually, synergistically, or antagonistically. However, little is known about how ongoing natural selection by these interacting guilds shapes the evolution of plants, i.e., how they affect the differential survival and reproduction of genotypes due to differences in phenotypes in an environment. Recent technological advances, including next-generation sequencing, metabolomics, and gene-editing technologies along with traditional experimental approaches (e.g., quantitative genetics experiments), have enabled far more comprehensive exploration of the genes and traits involved in complex ecological interactions. Connecting different levels of biological organization (genes to communities) will enhance the understanding of evolutionary interactions in complex communities, but this requires a multidisciplinary approach. Here, we review traditional and modern methods and concepts, then highlight future avenues for studying the evolution of plant-arthropod interactions (e.g., plant-herbivore-pollinator interactions). Besides promoting a fundamental understanding of plant-associated arthropod communities' genetic background and evolution, such knowledge can also help address many current global environmental challenges.
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Affiliation(s)
- Ivan M. De-la-Cruz
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Femke Batsleer
- Terrestrial Ecology Unit, Department of Biology, Ghent University, Ghent, Belgium
| | - Dries Bonte
- Terrestrial Ecology Unit, Department of Biology, Ghent University, Ghent, Belgium
| | - Carolina Diller
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - Timo Hytönen
- Department of Agricultural Sciences, Viikki Plant Science Centre, University of Helsinki, Helsinki, Finland
- NIAB EMR, West Malling, United Kingdom
| | - Anne Muola
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden
- Biodiversity Unit, University of Turku, Finland
| | - Sonia Osorio
- Departamento de Biología Molecular y Bioquímica, Instituto de Hortofruticultura Subtropical y Mediterránea “La Mayora”, Universidad de Málaga-Consejo Superior de Investigaciones Científicas, Campus de Teatinos, Málaga, Spain
| | - David Posé
- Departamento de Biología Molecular y Bioquímica, Instituto de Hortofruticultura Subtropical y Mediterránea “La Mayora”, Universidad de Málaga-Consejo Superior de Investigaciones Científicas, Campus de Teatinos, Málaga, Spain
| | - Martijn L. Vandegehuchte
- Terrestrial Ecology Unit, Department of Biology, Ghent University, Ghent, Belgium
- Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Johan A. Stenberg
- Department of Plant Protection Biology, Swedish University of Agricultural Sciences, Alnarp, Sweden
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16
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Friedlander E, Steinrücken M. A numerical framework for genetic hitchhiking in populations of variable size. Genetics 2022; 220:6526396. [PMID: 35143667 PMCID: PMC8893261 DOI: 10.1093/genetics/iyac012] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 12/27/2021] [Indexed: 11/13/2022] Open
Abstract
Natural selection on beneficial or deleterious alleles results in an increase or decrease, respectively, of their frequency within the population. Due to chromosomal linkage, the dynamics of the selected site affect the genetic variation at nearby neutral loci in a process commonly referred to as genetic hitchhiking. Changes in population size, however, can yield patterns in genomic data that mimic the effects of selection. Accurately modeling these dynamics is thus crucial to understanding how selection and past population size changes impact observed patterns of genetic variation. Here, we model the evolution of haplotype frequencies with the Wright-Fisher diffusion to study the impact of selection on linked neutral variation. Explicit solutions are not known for the dynamics of this diffusion when selection and recombination act simultaneously. Thus, we present a method for numerically evaluating the Wright-Fisher diffusion dynamics of 2 linked loci separated by a certain recombination distance when selection is acting. We can account for arbitrary population size histories explicitly using this approach. A key step in the method is to express the moments of the associated transition density, or sampling probabilities, as solutions to ordinary differential equations. Numerically solving these differential equations relies on a novel accurate and numerically efficient technique to estimate higher order moments from lower order moments. We demonstrate how this numerical framework can be used to quantify the reduction and recovery of genetic diversity around a selected locus over time and elucidate distortions in the site-frequency-spectra of neutral variation linked to loci under selection in various demographic settings. The method can be readily extended to more general modes of selection and applied in likelihood frameworks to detect loci under selection and infer the strength of the selective pressure.
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Affiliation(s)
- Eric Friedlander
- Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA,Department of Mathematics, Saint Norbert College, Green Bay, WI 54115, USA
| | - Matthias Steinrücken
- Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA,Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA,Corresponding author: Department of Ecology & Evolution, The University of Chicago, 1101 E. 57th Street, Chicago, IL 60637, USA.
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17
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Deng TX, Ma XY, Lu XR, Duan AQ, Shokrollahi B, Shang JH. Signatures of selection reveal candidate genes involved in production traits in Chinese crossbred buffaloes. J Dairy Sci 2021; 105:1327-1337. [PMID: 34955275 DOI: 10.3168/jds.2021-21102] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 11/03/2021] [Indexed: 12/11/2022]
Abstract
Identification of selection signature is important for a better understanding of genetic mechanisms that affect phenotypic differentiation in livestock. However, the genome-wide selection responses have not been investigated for the production traits of Chinese crossbred buffaloes. In this study, an SNP data set of 133 buffaloes (Chinese crossbred buffalo, n = 45; Chinese local swamp buffalo, n = 88) was collected from the Dryad Digital Repository database (https://datadryad.org/stash/). Population genetics analysis showed that these buffaloes were divided into the following 2 groups: crossbred buffalo and swamp buffalo. The crossbred group had higher genetic diversity than the swamp group. Using 3 complementary statistical methods (integrated haplotype score, cross population extended haplotype homozygosity, and composite likelihood ratio), a total of 31 candidate selection regions were identified in the Chinese crossbred population. Here, within these candidate regions, 25 genes were under the putative selection. Among them, several candidate genes were reported to be associated with production traits. In addition, we identified 13 selection regions that overlapped with bovine QTLs that were mainly involved in milk production and composition traits. These results can provide useful insights regarding the selection response for production traits of Chinese crossbred buffalo, as identified candidate genes influence production performance.
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Affiliation(s)
- T X Deng
- Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China.
| | - X Y Ma
- Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China
| | - X R Lu
- Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China
| | - A Q Duan
- Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China
| | - Borhan Shokrollahi
- Department of Animal Science, Faculty of Agriculture, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran 5595-73919
| | - J H Shang
- Key Laboratory of Buffalo Genetics, Breeding and Reproduction Technology, Buffalo Research Institute, Chinese Academy of Agricultural Sciences, Nanning 530001, China.
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18
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Laval G, Patin E, Boutillier P, Quintana-Murci L. Sporadic occurrence of recent selective sweeps from standing variation in humans as revealed by an approximate Bayesian computation approach. Genetics 2021; 219:6377789. [PMID: 34849862 DOI: 10.1093/genetics/iyab161] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Accepted: 09/01/2021] [Indexed: 12/14/2022] Open
Abstract
During their dispersals over the last 100,000 years, modern humans have been exposed to a large variety of environments, resulting in genetic adaptation. While genome-wide scans for the footprints of positive Darwinian selection have increased knowledge of genes and functions potentially involved in human local adaptation, they have globally produced evidence of a limited contribution of selective sweeps in humans. Conversely, studies based on machine learning algorithms suggest that recent sweeps from standing variation are widespread in humans, an observation that has been recently questioned. Here, we sought to formally quantify the number of recent selective sweeps in humans, by leveraging approximate Bayesian computation and whole-genome sequence data. Our computer simulations revealed suitable ABC estimations, regardless of the frequency of the selected alleles at the onset of selection and the completion of sweeps. Under a model of recent selection from standing variation, we inferred that an average of 68 (from 56 to 79) and 140 (from 94 to 198) sweeps occurred over the last 100,000 years of human history, in African and Eurasian populations, respectively. The former estimation is compatible with human adaptation rates estimated since divergence with chimps, and reveals numbers of sweeps per generation per site in the range of values estimated in Drosophila. Our results confirm the rarity of selective sweeps in humans and show a low contribution of sweeps from standing variation to recent human adaptation.
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Affiliation(s)
- Guillaume Laval
- Human Evolutionary Genetics Unit, Institut Pasteur, UMR 2000, CNRS, Paris 75015, France
| | - Etienne Patin
- Human Evolutionary Genetics Unit, Institut Pasteur, UMR 2000, CNRS, Paris 75015, France
| | - Pierre Boutillier
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Lluis Quintana-Murci
- Human Evolutionary Genetics Unit, Institut Pasteur, UMR 2000, CNRS, Paris 75015, France.,Human Genomics and Evolution, Collège de France, 75005 Paris, France
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19
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Dumartinet T, Ravel S, Roussel V, Perez-Vicente L, Aguayo J, Abadie C, Carlier J. Complex adaptive architecture underlies adaptation to quantitative host resistance in a fungal plant pathogen. Mol Ecol 2021; 31:1160-1179. [PMID: 34845779 DOI: 10.1111/mec.16297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 11/12/2021] [Accepted: 11/17/2021] [Indexed: 11/26/2022]
Abstract
Plant pathogens often adapt to plant genetic resistance so characterization of the architecture underlying such an adaptation is required to understand the adaptive potential of pathogen populations. Erosion of banana quantitative resistance to a major leaf disease caused by polygenic adaptation of the causal agent, the fungus Pseudocercospora fijiensis, was recently identified in the northern Caribbean region. Genome scan and quantitative genetics approaches were combined to investigate the adaptive architecture underlying this adaptation. Thirty-two genomic regions showing host selection footprints were identified by pool sequencing of isolates collected from seven plantation pairs of two cultivars with different levels of quantitative resistance. Individual sequencing and phenotyping of isolates from one pair revealed significant and variable levels of correlation between haplotypes in 17 of these regions with a quantitative trait of pathogenicity (the diseased leaf area). The multilocus pattern of haplotypes detected in the 17 regions was found to be highly variable across all the population pairs studied. These results suggest complex adaptive architecture underlying plant pathogen adaptation to quantitative resistance with a polygenic basis, redundancy, and a low level of parallel evolution between pathogen populations. Candidate genes involved in quantitative pathogenicity and host adaptation of P. fijiensis were identified in genomic regions by combining annotation analysis with available biological data.
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Affiliation(s)
- Thomas Dumartinet
- CIRAD, UMR PHIM, Montpellier, France.,PHIM, Univ Montpellier, INRAe, CIRAD, Montpellier SupAgro, Montpellier, France
| | - Sébastien Ravel
- CIRAD, UMR PHIM, Montpellier, France.,PHIM, Univ Montpellier, INRAe, CIRAD, Montpellier SupAgro, Montpellier, France
| | - Véronique Roussel
- CIRAD, UMR PHIM, Montpellier, France.,PHIM, Univ Montpellier, INRAe, CIRAD, Montpellier SupAgro, Montpellier, France
| | | | - Jaime Aguayo
- ANSES, Laboratoire de la Santé des Végétaux (LSV), Unité de Mycologie, Malzéville, France
| | - Catherine Abadie
- CIRAD, UMR PHIM, Montpellier, France.,PHIM, Univ Montpellier, INRAe, CIRAD, Montpellier SupAgro, Montpellier, France
| | - Jean Carlier
- CIRAD, UMR PHIM, Montpellier, France.,PHIM, Univ Montpellier, INRAe, CIRAD, Montpellier SupAgro, Montpellier, France
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20
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Villegas-Mirón P, Acosta S, Nye J, Bertranpetit J, Laayouni H. Chromosome X-wide Analysis of Positive Selection in Human Populations: Common and Private Signals of Selection and its Impact on Inactivated Genes and Enhancers. Front Genet 2021; 12:714491. [PMID: 34646300 PMCID: PMC8502928 DOI: 10.3389/fgene.2021.714491] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 09/08/2021] [Indexed: 01/22/2023] Open
Abstract
The ability of detecting adaptive (positive) selection in the genome has opened the possibility of understanding the genetic basis of population-specific adaptations genome-wide. Here, we present the analysis of recent selective sweeps, specifically in the X chromosome, in human populations from the third phase of the 1,000 Genomes Project using three different haplotype-based statistics. We describe instances of recent positive selection that fit the criteria of hard or soft sweeps, and detect a higher number of events among sub-Saharan Africans than non-Africans (Europe and East Asia). A global enrichment of neural-related processes is observed and numerous genes related to fertility appear among the top candidates, reflecting the importance of reproduction in human evolution. Commonalities with previously reported genes under positive selection are found, while particularly strong new signals are reported in specific populations or shared across different continental groups. We report an enrichment of signals in genes that escape X chromosome inactivation, which may contribute to the differentiation between sexes. We also provide evidence of a widespread presence of soft-sweep-like signatures across the chromosome and a global enrichment of highly scoring regions that overlap potential regulatory elements. Among these, enhancers-like signatures seem to present putative signals of positive selection which might be in concordance with selection in their target genes. Also, particularly strong signals appear in regulatory regions that show differential activities, which might point to population-specific regulatory adaptations.
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Affiliation(s)
- Pablo Villegas-Mirón
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain
| | - Sandra Acosta
- Department Pathology and Experimental Therapeutics, Medical School, University of Barcelona, Barcelona, Spain
| | - Jessica Nye
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain
| | - Jaume Bertranpetit
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain
| | - Hafid Laayouni
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Barcelona, Spain.,Bioinformatics Studies, ESCI-UPF, Barcelona, Spain
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21
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Bisschop G, Lohse K, Setter D. Sweeps in time: leveraging the joint distribution of branch lengths. Genetics 2021; 219:iyab119. [PMID: 34849880 PMCID: PMC8633083 DOI: 10.1093/genetics/iyab119] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 07/10/2021] [Indexed: 11/14/2022] Open
Abstract
Current methods of identifying positively selected regions in the genome are limited in two key ways: the underlying models cannot account for the timing of adaptive events and the comparison between models of selective sweeps and sequence data is generally made via simple summaries of genetic diversity. Here, we develop a tractable method of describing the effect of positive selection on the genealogical histories in the surrounding genome, explicitly modeling both the timing and context of an adaptive event. In addition, our framework allows us to go beyond analyzing polymorphism data via the site frequency spectrum or summaries thereof and instead leverage information contained in patterns of linked variants. Tests on both simulations and a human data example, as well as a comparison to SweepFinder2, show that even with very small sample sizes, our analytic framework has higher power to identify old selective sweeps and to correctly infer both the time and strength of selection. Finally, we derived the marginal distribution of genealogical branch lengths at a locus affected by selection acting at a linked site. This provides a much-needed link between our analytic understanding of the effects of sweeps on sequence variation and recent advances in simulation and heuristic inference procedures that allow researchers to examine the sequence of genealogical histories along the genome.
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Affiliation(s)
- Gertjan Bisschop
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Konrad Lohse
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Derek Setter
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh EH9 3FL, UK
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22
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Otte KA, Nolte V, Mallard F, Schlötterer C. The genetic architecture of temperature adaptation is shaped by population ancestry and not by selection regime. Genome Biol 2021; 22:211. [PMID: 34271951 PMCID: PMC8285869 DOI: 10.1186/s13059-021-02425-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 06/29/2021] [Indexed: 12/28/2022] Open
Abstract
Background Understanding the genetic architecture of temperature adaptation is key for characterizing and predicting the effect of climate change on natural populations. One particularly promising approach is Evolve and Resequence, which combines advantages of experimental evolution such as time series, replicate populations, and controlled environmental conditions, with whole genome sequencing. Recent analysis of replicate populations from two different Drosophila simulans founder populations, which were adapting to the same novel hot environment, uncovered very different architectures—either many selection targets with large heterogeneity among replicates or fewer selection targets with a consistent response among replicates. Results Here, we expose the founder population from Portugal to a cold temperature regime. Although almost no selection targets are shared between the hot and cold selection regime, the adaptive architecture was similar. We identify a moderate number of targets under strong selection (19 selection targets, mean selection coefficient = 0.072) and parallel responses in the cold evolved replicates. This similarity across different environments indicates that the adaptive architecture depends more on the ancestry of the founder population than the specific selection regime. Conclusions These observations will have broad implications for the correct interpretation of the genomic responses to a changing climate in natural populations. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-021-02425-9.
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Affiliation(s)
- Kathrin A Otte
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria.,Present address: Institute for Zoology, University of Cologne, Cologne, Germany
| | - Viola Nolte
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria
| | - François Mallard
- Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria.,Present address: Institut de Biologie de l'École Normale Supérieure, CNRS UMR 8197, Inserm U1024, PSL Research University, F-75005, Paris, France
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23
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Frank LR, Rowe TB, Boyer DM, Witmer LM, Galinsky VL. Unveiling the third dimension in morphometry with automated quantitative volumetric computations. Sci Rep 2021; 11:14438. [PMID: 34262066 PMCID: PMC8280169 DOI: 10.1038/s41598-021-93490-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 06/25/2021] [Indexed: 02/06/2023] Open
Abstract
As computed tomography and related technologies have become mainstream tools across a broad range of scientific applications, each new generation of instrumentation produces larger volumes of more-complex 3D data. Lagging behind are step-wise improvements in computational methods to rapidly analyze these new large, complex datasets. Here we describe novel computational methods to capture and quantify volumetric information, and to efficiently characterize and compare shape volumes. It is based on innovative theoretical and computational reformulation of volumetric computing. It consists of two theoretical constructs and their numerical implementation: the spherical wave decomposition (SWD), that provides fast, accurate automated characterization of shapes embedded within complex 3D datasets; and symplectomorphic registration with phase space regularization by entropy spectrum pathways (SYMREG), that is a non-linear volumetric registration method that allows homologous structures to be correctly warped to each other or a common template for comparison. Together, these constitute the Shape Analysis for Phenomics from Imaging Data (SAPID) method. We demonstrate its ability to automatically provide rapid quantitative segmentation and characterization of single unique datasets, and both inter-and intra-specific comparative analyses. We go beyond pairwise comparisons and analyze collections of samples from 3D data repositories, highlighting the magnified potential our method has when applied to data collections. We discuss the potential of SAPID in the broader context of generating normative morphologies required for meaningfully quantifying and comparing variations in complex 3D anatomical structures and systems.
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Affiliation(s)
- Lawrence R Frank
- Institute for Engineering in Medicine, Center for Scientific Computation in Imaging, University of California San Diego, 8950 Villa La Jolla Dr., Suite B227, La Jolla, CA, 92037, USA.
- Department of Radiology, Center for Functional MRI, University of California San Diego, 9500 Gilman Dr., #0677, La Jolla, CA, 92093-0677, USA.
| | - Timothy B Rowe
- Department of Geological Sciences, Jackson School of Geosciences, University of Texas, Austin, TX, 78712, USA
| | - Doug M Boyer
- Department of Evolutionary Anthropology, Duke University, Chapel Hill, NC, USA
| | - Lawrence M Witmer
- Department of Biomedical Sciences, Heritage College of Osteopathic Medicine, Ohio University, Athens, OH, USA
| | - Vitaly L Galinsky
- Institute for Engineering in Medicine, Center for Scientific Computation in Imaging, University of California San Diego, 8950 Villa La Jolla Dr., Suite B227, La Jolla, CA, 92037, USA
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24
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Fernie AR, Alseekh S, Liu J, Yan J. Using precision phenotyping to inform de novo domestication. PLANT PHYSIOLOGY 2021; 186:1397-1411. [PMID: 33848336 PMCID: PMC8260140 DOI: 10.1093/plphys/kiab160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 03/22/2021] [Indexed: 05/09/2023]
Abstract
An update on the use of precision phenotyping to assess the potential of lesser cultivated species as candidates for de novo domestication or similar development for future agriculture.
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Affiliation(s)
- Alisdair R Fernie
- Max Planck Institute for Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany
- Centre of Plant Systems Biology and Biotechnology, 4000 Plovdiv, Bulgaria
| | - Saleh Alseekh
- Max Planck Institute for Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany
- Centre of Plant Systems Biology and Biotechnology, 4000 Plovdiv, Bulgaria
| | - Jie Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, 430070 Wuhan, Hubei, China
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, 430070 Wuhan, Hubei, China
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25
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Mao Y, Catacchio CR, Hillier LW, Porubsky D, Li R, Sulovari A, Fernandes JD, Montinaro F, Gordon DS, Storer JM, Haukness M, Fiddes IT, Murali SC, Dishuck PC, Hsieh P, Harvey WT, Audano PA, Mercuri L, Piccolo I, Antonacci F, Munson KM, Lewis AP, Baker C, Underwood JG, Hoekzema K, Huang TH, Sorensen M, Walker JA, Hoffman J, Thibaud-Nissen F, Salama SR, Pang AWC, Lee J, Hastie AR, Paten B, Batzer MA, Diekhans M, Ventura M, Eichler EE. A high-quality bonobo genome refines the analysis of hominid evolution. Nature 2021; 594:77-81. [PMID: 33953399 PMCID: PMC8172381 DOI: 10.1038/s41586-021-03519-x] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 04/07/2021] [Indexed: 12/17/2022]
Abstract
The divergence of chimpanzee and bonobo provides one of the few examples of recent hominid speciation1,2. Here we describe a fully annotated, high-quality bonobo genome assembly, which was constructed without guidance from reference genomes by applying a multiplatform genomics approach. We generate a bonobo genome assembly in which more than 98% of genes are completely annotated and 99% of the gaps are closed, including the resolution of about half of the segmental duplications and almost all of the full-length mobile elements. We compare the bonobo genome to those of other great apes1,3–5 and identify more than 5,569 fixed structural variants that specifically distinguish the bonobo and chimpanzee lineages. We focus on genes that have been lost, changed in structure or expanded in the last few million years of bonobo evolution. We produce a high-resolution map of incomplete lineage sorting and estimate that around 5.1% of the human genome is genetically closer to chimpanzee or bonobo and that more than 36.5% of the genome shows incomplete lineage sorting if we consider a deeper phylogeny including gorilla and orangutan. We also show that 26% of the segments of incomplete lineage sorting between human and chimpanzee or human and bonobo are non-randomly distributed and that genes within these clustered segments show significant excess of amino acid replacement compared to the rest of the genome. A high-quality bonobo genome assembly provides insights into incomplete lineage sorting in hominids and its relevance to gene evolution and the genetic relationship among living hominids.
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Affiliation(s)
- Yafei Mao
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - LaDeana W Hillier
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Ruiyang Li
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Arvis Sulovari
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Jason D Fernandes
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Francesco Montinaro
- Department of Biology, University of Bari, Bari, Italy.,Estonian Biocentre, Institute of Genomics, Tartu, Estonia
| | - David S Gordon
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.,Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | | | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Ian T Fiddes
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Shwetha Canchi Murali
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA.,Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Philip C Dishuck
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - PingHsun Hsieh
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - William T Harvey
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Peter A Audano
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | | | | | - Katherine M Munson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Alexandra P Lewis
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Carl Baker
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | | | - Kendra Hoekzema
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Tzu-Hsueh Huang
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Melanie Sorensen
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Jerilyn A Walker
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA
| | - Jinna Hoffman
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Sofie R Salama
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA.,Howard Hughes Medical Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | | | - Joyce Lee
- Bionano Genomics, San Diego, CA, USA
| | | | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Mark A Batzer
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Mario Ventura
- Department of Biology, University of Bari, Bari, Italy.
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA. .,Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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26
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Svedberg J, Shchur V, Reinman S, Nielsen R, Corbett-Detig R. Inferring Adaptive Introgression Using Hidden Markov Models. Mol Biol Evol 2021; 38:2152-2165. [PMID: 33502512 PMCID: PMC8097282 DOI: 10.1093/molbev/msab014] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Adaptive introgression-the flow of adaptive genetic variation between species or populations-has attracted significant interest in recent years and it has been implicated in a number of cases of adaptation, from pesticide resistance and immunity, to local adaptation. Despite this, methods for identification of adaptive introgression from population genomic data are lacking. Here, we present Ancestry_HMM-S, a hidden Markov model-based method for identifying genes undergoing adaptive introgression and quantifying the strength of selection acting on them. Through extensive validation, we show that this method performs well on moderately sized data sets for realistic population and selection parameters. We apply Ancestry_HMM-S to a data set of an admixed Drosophila melanogaster population from South Africa and we identify 17 loci which show signatures of adaptive introgression, four of which have previously been shown to confer resistance to insecticides. Ancestry_HMM-S provides a powerful method for inferring adaptive introgression in data sets that are typically collected when studying admixed populations. This method will enable powerful insights into the genetic consequences of admixture across diverse populations. Ancestry_HMM-S can be downloaded from https://github.com/jesvedberg/Ancestry_HMM-S/.
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Affiliation(s)
- Jesper Svedberg
- Department of Biomolecular Engineering, Genomics Institute, UC Santa Cruz, Santa Cruz, CA, USA
| | - Vladimir Shchur
- National Research University Higher School of Economics, Moscow, Russian Federation
| | - Solomon Reinman
- Department of Biomolecular Engineering, Genomics Institute, UC Santa Cruz, Santa Cruz, CA, USA
| | - Rasmus Nielsen
- National Research University Higher School of Economics, Moscow, Russian Federation
- Department of Integrative Biology and Department of Statistics, UC Berkeley, Berkeley, CA, USA
- Center for GeoGenetics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, Genomics Institute, UC Santa Cruz, Santa Cruz, CA, USA
- National Research University Higher School of Economics, Moscow, Russian Federation
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27
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Zeng K, Charlesworth B, Hobolth A. Studying models of balancing selection using phase-type theory. Genetics 2021; 218:6237896. [PMID: 33871627 DOI: 10.1093/genetics/iyab055] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 03/25/2021] [Indexed: 11/15/2022] Open
Abstract
Balancing selection (BLS) is the evolutionary force that maintains high levels of genetic variability in many important genes. To further our understanding of its evolutionary significance, we analyze models with BLS acting on a biallelic locus: an equilibrium model with long-term BLS, a model with long-term BLS and recent changes in population size, and a model of recent BLS. Using phase-type theory, a mathematical tool for analyzing continuous time Markov chains with an absorbing state, we examine how BLS affects polymorphism patterns in linked neutral regions, as summarized by nucleotide diversity, the expected number of segregating sites, the site frequency spectrum, and the level of linkage disequilibrium (LD). Long-term BLS affects polymorphism patterns in a relatively small genomic neighborhood, and such selection targets are easier to detect when the equilibrium frequencies of the selected variants are close to 50%, or when there has been a population size reduction. For a new mutation subject to BLS, its initial increase in frequency in the population causes linked neutral regions to have reduced diversity, an excess of both high and low frequency derived variants, and elevated LD with the selected locus. These patterns are similar to those produced by selective sweeps, but the effects of recent BLS are weaker. Nonetheless, compared to selective sweeps, nonequilibrium polymorphism and LD patterns persist for a much longer period under recent BLS, which may increase the chance of detecting such selection targets. An R package for analyzing these models, among others (e.g., isolation with migration), is available.
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Affiliation(s)
- Kai Zeng
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK
| | - Brian Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Asger Hobolth
- Department of Mathematics, Aarhus University, Aarhus DK-8000, Denmark
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28
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Pandey J, Scheuring DC, Koym JW, Coombs J, Novy RG, Thompson AL, Holm DG, Douches DS, Miller JC, Vales MI. Genetic diversity and population structure of advanced clones selected over forty years by a potato breeding program in the USA. Sci Rep 2021; 11:8344. [PMID: 33863959 PMCID: PMC8052460 DOI: 10.1038/s41598-021-87284-x] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 03/24/2021] [Indexed: 01/12/2023] Open
Abstract
Knowledge regarding genetic diversity and population structure of breeding materials is essential for crop improvement. The Texas A&M University Potato Breeding Program has a collection of advanced clones selected and maintained in-vitro over a 40-year period. Little is known about its genetic makeup and usefulness for the current breeding program. In this study, 214 potato clones were genotyped with the Infinium Illumina 22 K V3 Potato Array. After filtering, a total of 10,106 single nucleotide polymorphic (SNP) markers were used for analysis. Heterozygosity varied by SNP, with an overall average of 0.59. Three groups of tetraploid clones primarily based on potato market classes, were detected using STRUCTURE software and confirmed by discriminant analysis of principal components.
The highest coefficient of differentiation observed between the groups was 0.14. Signatures of selection were uncovered in genes controlling potato flesh and skin color, length of plant cycle and tuberization, and carbohydrate metabolism. A core set of 43 clones was obtained using Core Hunter 3 to develop a sub-collection that retains similar genetic diversity as the whole population, minimize redundancies, and facilitates long-term conservation of genetic resources. The comprehensive molecular characterization of our breeding clone bank collection contributes to understanding the genetic diversity of existing potato resources. This analysis could be applied to other breeding programs and assist in the selection of parents, fingerprinting, protection, and management of the breeding collections.
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Affiliation(s)
- Jeewan Pandey
- Department of Horticultural Sciences, Texas A&M University, College Station, TX, 77843-2133, USA
| | - Douglas C Scheuring
- Department of Horticultural Sciences, Texas A&M University, College Station, TX, 77843-2133, USA
| | - Jeffrey W Koym
- Texas A&M AgriLife Research and Extension Center, Lubbock, TX, 79403, USA
| | - Joseph Coombs
- Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, MI, 48824, USA
| | - Richard G Novy
- USDA-Agricultural Research Service, Small Grains and Potato Germplasm Research, Aberdeen, ID, 83210, USA
| | - Asunta L Thompson
- Department of Plant Sciences, North Dakota State University, Fargo, ND, 58108, USA
| | - David G Holm
- San Luis Valley Research Center, Department of Horticulture and Landscape Architecture, Colorado State University, Center, CO, 81125, USA
| | - David S Douches
- Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, MI, 48824, USA
| | - J Creighton Miller
- Department of Horticultural Sciences, Texas A&M University, College Station, TX, 77843-2133, USA
| | - M Isabel Vales
- Department of Horticultural Sciences, Texas A&M University, College Station, TX, 77843-2133, USA.
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29
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Harris AM, DeGiorgio M. A Likelihood Approach for Uncovering Selective Sweep Signatures from Haplotype Data. Mol Biol Evol 2021; 37:3023-3046. [PMID: 32392293 PMCID: PMC7530616 DOI: 10.1093/molbev/msaa115] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Selective sweeps are frequent and varied signatures in the genomes of natural populations, and detecting them is consequently important in understanding mechanisms of adaptation by natural selection. Following a selective sweep, haplotypic diversity surrounding the site under selection decreases, and this deviation from the background pattern of variation can be applied to identify sweeps. Multiple methods exist to locate selective sweeps in the genome from haplotype data, but none leverages the power of a model-based approach to make their inference. Here, we propose a likelihood ratio test statistic T to probe whole-genome polymorphism data sets for selective sweep signatures. Our framework uses a simple but powerful model of haplotype frequency spectrum distortion to find sweeps and additionally make an inference on the number of presently sweeping haplotypes in a population. We found that the T statistic is suitable for detecting both hard and soft sweeps across a variety of demographic models, selection strengths, and ages of the beneficial allele. Accordingly, we applied the T statistic to variant calls from European and sub-Saharan African human populations, yielding primarily literature-supported candidates, including LCT, RSPH3, and ZNF211 in CEU, SYT1, RGS18, and NNT in YRI, and HLA genes in both populations. We also searched for sweep signatures in Drosophila melanogaster, finding expected candidates at Ace, Uhg1, and Pimet. Finally, we provide open-source software to compute the T statistic and the inferred number of presently sweeping haplotypes from whole-genome data.
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Affiliation(s)
- Alexandre M Harris
- Department of Biology, Pennsylvania State University, University Park, PA.,Molecular, Cellular, and Integrative Biosciences, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA
| | - Michael DeGiorgio
- Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL
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30
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Crava CM, Varghese FS, Pischedda E, Halbach R, Palatini U, Marconcini M, Gasmi L, Redmond S, Afrane Y, Ayala D, Paupy C, Carballar‐Lejarazu R, Miesen P, van Rij RP, Bonizzoni M. Population genomics in the arboviral vector Aedes aegypti reveals the genomic architecture and evolution of endogenous viral elements. Mol Ecol 2021; 30:1594-1611. [PMID: 33432714 PMCID: PMC8048955 DOI: 10.1111/mec.15798] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 01/05/2021] [Accepted: 01/07/2021] [Indexed: 02/06/2023]
Abstract
Horizontal gene transfer from viruses to eukaryotic cells is a pervasive phenomenon. Somatic viral integrations are linked to persistent viral infection whereas integrations into germline cells are maintained in host genomes by vertical transmission and may be co-opted for host functions. In the arboviral vector Aedes aegypti, an endogenous viral element from a nonretroviral RNA virus (nrEVE) was shown to produce PIWI-interacting RNAs (piRNAs) to limit infection with a cognate virus. Thus, nrEVEs may constitute a heritable, sequence-specific mechanism for antiviral immunity, analogous to piRNA-mediated silencing of transposable elements. Here, we combine population genomics and evolutionary approaches to analyse the genomic architecture of nrEVEs in A. aegypti. We conducted a genome-wide screen for adaptive nrEVEs and searched for novel population-specific nrEVEs in the genomes of 80 individual wild-caught mosquitoes from five geographical populations. We show a dynamic landscape of nrEVEs in mosquito genomes and identified five novel nrEVEs derived from two currently circulating viruses, providing evidence of the environmental-dependent modification of a piRNA cluster. Overall, our results show that virus endogenization events are complex with only a few nrEVEs contributing to adaptive evolution in A. aegypti.
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Affiliation(s)
- Cristina M. Crava
- Department of Biology and BiotechnologyUniversity of PaviaPaviaItaly
- Present address:
Institute of Biotechnology and BiomedicineUniversitat de ValènciaBurjassotSpain
| | - Finny S. Varghese
- Department of Medical MicrobiologyRadboud University Medical CenterRadboud Institute for Molecular Life SciencesNijmegenThe Netherlands
| | - Elisa Pischedda
- Department of Biology and BiotechnologyUniversity of PaviaPaviaItaly
| | - Rebecca Halbach
- Department of Medical MicrobiologyRadboud University Medical CenterRadboud Institute for Molecular Life SciencesNijmegenThe Netherlands
| | - Umberto Palatini
- Department of Biology and BiotechnologyUniversity of PaviaPaviaItaly
| | | | - Leila Gasmi
- Department of Biology and BiotechnologyUniversity of PaviaPaviaItaly
| | - Seth Redmond
- Institute of Vector Borne DiseaseMonash UniversityAustralia
| | - Yaw Afrane
- Department of Medical MicrobiologyUniversity of GhanaAccraGhana
| | - Diego Ayala
- MIVEGECUniv. MontpellierIRDCNRSMontpellierFrance
| | | | - Rebeca Carballar‐Lejarazu
- Department of Biology and BiotechnologyUniversity of PaviaPaviaItaly
- Present address:
Department of Molecular Biology and BiochemistryUniversity of California at IrvineIrvineCAUSA
| | - Pascal Miesen
- Department of Medical MicrobiologyRadboud University Medical CenterRadboud Institute for Molecular Life SciencesNijmegenThe Netherlands
| | - Ronald P. van Rij
- Department of Medical MicrobiologyRadboud University Medical CenterRadboud Institute for Molecular Life SciencesNijmegenThe Netherlands
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31
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Identifying Potentially Beneficial Genetic Mutations Associated with Monophyletic Selective Sweep and a Proof-of-Concept Study with Viral Genetic Data. mSystems 2021; 6:6/1/e01151-20. [PMID: 33622855 PMCID: PMC8573955 DOI: 10.1128/msystems.01151-20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Genetic mutations play a central role in evolution. For a significantly beneficial mutation, a one-time mutation event suffices for the species to prosper and predominate through the process called “monophyletic selective sweep.” However, existing methods that rely on counting the number of mutation events to detect selection are unable to find such a mutation in selective sweep. We here introduce a method to detect mutations at the single amino acid/nucleotide level that could be responsible for monophyletic selective sweep evolution. The method identifies a genetic signature associated with selective sweep using the population genetic test statistic Tajima’s D. We applied the algorithm to ebolavirus, influenza A virus, and severe acute respiratory syndrome coronavirus 2 to identify known biologically significant mutations and unrecognized mutations associated with potential selective sweep. The method can detect beneficial mutations, possibly leading to discovery of previously unknown biological functions and mechanisms related to those mutations. IMPORTANCE In biology, research on evolution is important to understand the significance of genetic mutation. When there is a significantly beneficial mutation, a population of species with the mutation prospers and predominates, in a process called “selective sweep.” However, there are few methods that can find such a mutation causing selective sweep from genetic data. We here introduce a novel method to detect such mutations. Applying the method to the genomes of ebolavirus, influenza viruses, and the novel coronavirus, we detected known biologically significant mutations and identified mutations the importance of which is previously unrecognized. The method can deepen our understanding of molecular and evolutionary biology.
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32
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33
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Schneider K, White TJ, Mitchell S, Adams CE, Reeve R, Elmer KR. The pitfalls and virtues of population genetic summary statistics: Detecting selective sweeps in recent divergences. J Evol Biol 2020; 34:893-909. [DOI: 10.1111/jeb.13738] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 10/22/2020] [Accepted: 10/24/2020] [Indexed: 12/12/2022]
Affiliation(s)
- Kevin Schneider
- Institute of Biodiversity, Animal Health & Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
| | - Tom J. White
- Institute of Biodiversity, Animal Health & Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
| | - Sonia Mitchell
- Institute of Biodiversity, Animal Health & Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
| | - Colin E. Adams
- Institute of Biodiversity, Animal Health & Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
- Scottish Centre for Ecology and the Natural Environment Institute of Biodiversity, Animal Health and Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
| | - Richard Reeve
- Institute of Biodiversity, Animal Health & Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
| | - Kathryn R. Elmer
- Institute of Biodiversity, Animal Health & Comparative Medicine College of Medical, Veterinary & Life Sciences University of Glasgow Glasgow UK
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34
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Gu H, Zhu T, Li X, Chen Y, Wang L, Lv X, Yang W, Jia Y, Jiang Z, Qu L. A joint analysis strategy reveals genetic changes associated with artificial selection between egg-type and meat-type ducks. Anim Genet 2020; 51:890-898. [PMID: 33058234 DOI: 10.1111/age.13014] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/23/2020] [Indexed: 12/16/2022]
Abstract
Egg-type ducks and meat-type ducks are predominantly commercial or indigenous and have been subjected to artificial directional selection. These two duck types differ substantially in body shape, production performance and reproductivity. However, the genetic changes associated with phenotypic differences remain unclear. Here, we compared the two duck types at the genomic and transcriptomic levels. We identified a large number of SNPs and genes in genomic divergent regions in terms of FST and θπ values. The corresponding genes were mainly enriched in embryonic development function and metabolic pathway. RNA-seq analysis also revealed differential gene expression in the liver and gonads. The differentially expressed genes were functionally associated with signal transmission and substance metabolism respectively. Furthermore, we found that seven genes were related to differentiation between the two types by both g genome and transcriptome analysis and were plausible candidate genes. These genes were annotated to GO categories of cell development and disease immunity. These findings will enable a better understanding of the artificial selection history of meat and egg ducks and provide a valuable resource for future research on the breeding of these two lineages.
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Affiliation(s)
- H Gu
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing, 100193, China
| | - T Zhu
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing, 100193, China
| | - X Li
- College of Animal Science and Technology, Shandong Agricultural University, Daizong Street #61, Tai'an, Shandong, 271018, China
| | - Y Chen
- Beijing Municipal General Station of Animal Science, Beiyuan Road 15A#, Beijing, 100107, China
| | - L Wang
- Beijing Municipal General Station of Animal Science, Beiyuan Road 15A#, Beijing, 100107, China
| | - X Lv
- Beijing Municipal General Station of Animal Science, Beiyuan Road 15A#, Beijing, 100107, China
| | - W Yang
- Beijing Municipal General Station of Animal Science, Beiyuan Road 15A#, Beijing, 100107, China
| | - Y Jia
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Yuanmingyuan West Road 2#, Beijing, 100193, China
| | - Z Jiang
- Department of Animal Sciences, center for Reproductive Biology, Veterinary and Biomedical Research Building, Washington State University, Pullman, Washington, 647010, USA
| | - L Qu
- Department of Animal Genetics and Breeding, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Yuanmingyuan West Road 2#, Beijing, 100193, China
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Cortinovis G, Di Vittori V, Bellucci E, Bitocchi E, Papa R. Adaptation to novel environments during crop diversification. CURRENT OPINION IN PLANT BIOLOGY 2020; 56:203-217. [PMID: 32057695 DOI: 10.1016/j.pbi.2019.12.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 12/19/2019] [Accepted: 12/21/2019] [Indexed: 06/10/2023]
Abstract
In the context of the global challenge of climate change, mitigation strategies are needed to adapt crops to novel environments. The main goal to address this is an understanding of the genetic basis of crop adaptation to different agro-ecological conditions. The movement of crops during the Colombian Exchange that started with the travels of Columbus in 1492 is an example of rapid adaptation to novel environments. Many diversification-related traits have been characterised in multiple crop species, and association-mapping analyses have identified loci involved in these. Here, we present an overview of current knowledge regarding the molecular basis related to the complex patterns of crop adaptation and dissemination, particularly outside their centres of origin. Investigation of the genomic basis of crop expansion offers a powerful contribution to the development of tools to identify and exploit valuable genetic diversity and to improve and design novel resilient crop varieties.
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Affiliation(s)
- Gaia Cortinovis
- Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche, via Brecce Bianche, 60131 Ancona, Italy
| | - Valerio Di Vittori
- Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche, via Brecce Bianche, 60131 Ancona, Italy
| | - Elisa Bellucci
- Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche, via Brecce Bianche, 60131 Ancona, Italy
| | - Elena Bitocchi
- Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche, via Brecce Bianche, 60131 Ancona, Italy.
| | - Roberto Papa
- Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche, via Brecce Bianche, 60131 Ancona, Italy.
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Khedikar Y, Clarke WE, Chen L, Higgins EE, Kagale S, Koh CS, Bennett R, Parkin IAP. Narrow genetic base shapes population structure and linkage disequilibrium in an industrial oilseed crop, Brassica carinata A. Braun. Sci Rep 2020; 10:12629. [PMID: 32724070 PMCID: PMC7387349 DOI: 10.1038/s41598-020-69255-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 07/09/2020] [Indexed: 12/16/2022] Open
Abstract
Ethiopian mustard (Brassica carinata A. Braun) is an emerging sustainable source of vegetable oil, in particular for the biofuel industry. The present study exploited genome assemblies of the Brassica diploids, Brassica nigra and Brassica oleracea, to discover over 10,000 genome-wide SNPs using genotype by sequencing of 620 B. carinata lines. The analyses revealed a SNP frequency of one every 91.7 kb, a heterozygosity level of 0.30, nucleotide diversity levels of 1.31 × 10-05, and the first five principal components captured only 13% molecular variation, indicating low levels of genetic diversity among the B. carinata collection. Genome bias was observed, with greater SNP density found on the B subgenome. The 620 lines clustered into two distinct sub-populations (SP1 and SP2) with the majority of accessions (88%) clustered in SP1 with those from Ethiopia, the presumed centre of origin. SP2 was distinguished by a collection of breeding lines, implicating targeted selection in creating population structure. Two selective sweep regions on B3 and B8 were detected, which harbour genes involved in fatty acid and aliphatic glucosinolate biosynthesis, respectively. The assessment of genetic diversity, population structure, and LD in the global B. carinata collection provides critical information to assist future crop improvement.
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Affiliation(s)
- Yogendra Khedikar
- Agriculture and Agri-Food Canada, 107 Science Place, Saskatoon, SK, Canada
| | - Wayne E Clarke
- Agriculture and Agri-Food Canada, 107 Science Place, Saskatoon, SK, Canada
| | - Lifeng Chen
- Agrisoma Biosciences Inc., 110 Gymnasium Place, Saskatoon, SK, Canada
| | - Erin E Higgins
- Agriculture and Agri-Food Canada, 107 Science Place, Saskatoon, SK, Canada
| | - Sateesh Kagale
- National Research Council Canada, 110 Gymnasium Place, Saskatoon, SK, Canada
| | - Chu Shin Koh
- Global Institute of Food Security, Saskatoon, SK, Canada
| | - Rick Bennett
- Agrisoma Biosciences Inc., 110 Gymnasium Place, Saskatoon, SK, Canada
| | - Isobel A P Parkin
- Agriculture and Agri-Food Canada, 107 Science Place, Saskatoon, SK, Canada.
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Barrera-Redondo J, Piñero D, Eguiarte LE. Genomic, Transcriptomic and Epigenomic Tools to Study the Domestication of Plants and Animals: A Field Guide for Beginners. Front Genet 2020; 11:742. [PMID: 32760427 PMCID: PMC7373799 DOI: 10.3389/fgene.2020.00742] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Accepted: 06/22/2020] [Indexed: 01/07/2023] Open
Abstract
In the last decade, genomics and the related fields of transcriptomics and epigenomics have revolutionized the study of the domestication process in plants and animals, leading to new discoveries and new unresolved questions. Given that some domesticated taxa have been more studied than others, the extent of genomic data can range from vast to nonexistent, depending on the domesticated taxon of interest. This review is meant as a rough guide for students and academics that want to start a domestication research project using modern genomic tools, as well as for researchers already conducting domestication studies that are interested in following a genomic approach and looking for alternate strategies (cheaper or more efficient) and future directions. We summarize the theoretical and technical background needed to carry out domestication genomics, starting from the acquisition of a reference genome and genome assembly, to the sampling design for population genomics, paleogenomics, transcriptomics, epigenomics and experimental validation of domestication-related genes. We also describe some examples of the aforementioned approaches and the relevant discoveries they made to understand the domestication of the studied taxa.
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Affiliation(s)
| | | | - Luis E. Eguiarte
- Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico
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Harris RB, Jensen JD. Considering Genomic Scans for Selection as Coalescent Model Choice. Genome Biol Evol 2020; 12:871-877. [PMID: 32396636 PMCID: PMC7313662 DOI: 10.1093/gbe/evaa093] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/06/2020] [Indexed: 12/17/2022] Open
Abstract
First inspired by the seminal work of Lewontin and Krakauer (1973. Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genetics 74(1):175-195.) and Maynard Smith and Haigh (1974. The hitch-hiking effect of a favourable gene. Genet Res. 23(1):23-35.), genomic scans for positive selection remain a widely utilized tool in modern population genomic analysis. Yet, the relative frequency and genomic impact of selective sweeps have remained a contentious point in the field for decades, largely owing to an inability to accurately identify their presence and quantify their effects-with current methodologies generally being characterized by low true-positive rates and/or high false-positive rates under many realistic demographic models. Most of these approaches are based on Wright-Fisher assumptions and the Kingman coalescent and generally rely on detecting outlier regions which do not conform to these neutral expectations. However, previous theoretical results have demonstrated that selective sweeps are well characterized by an alternative class of model known as the multiple-merger coalescent. Taken together, this suggests the possibility of not simply identifying regions which reject the Kingman, but rather explicitly testing the relative fit of a genomic window to the multiple-merger coalescent. We describe the advantages of such an approach, which owe to the branching structure differentiating selective and neutral models, and demonstrate improved power under certain demographic scenarios relative to a commonly used approach. However, regions of the demographic parameter space continue to exist in which neither this approach nor existing methodologies have sufficient power to detect selective sweeps.
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Barghi N, Schlötterer C. Distinct Patterns of Selective Sweep and Polygenic Adaptation in Evolve and Resequence Studies. Genome Biol Evol 2020; 12:890-904. [PMID: 32282913 PMCID: PMC7313669 DOI: 10.1093/gbe/evaa073] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/07/2020] [Indexed: 12/15/2022] Open
Abstract
In molecular population genetics, adaptation is typically thought to occur via selective sweeps, where targets of selection have independent effects on the phenotype and rise to fixation, whereas in quantitative genetics, many loci contribute to the phenotype and subtle frequency changes occur at many loci during polygenic adaptation. The sweep model makes specific predictions about frequency changes of beneficial alleles and many test statistics have been developed to detect such selection signatures. Despite polygenic adaptation is probably the prevalent mode of adaptation, because of the traditional focus on the phenotype, we are lacking a solid understanding of the similarities and differences of selection signatures under the two models. Recent theoretical and empirical studies have shown that both selective sweep and polygenic adaptation models could result in a sweep-like genomic signature; therefore, additional criteria are needed to distinguish the two models. With replicated populations and time series data, experimental evolution studies have the potential to identify the underlying model of adaptation. Using the framework of experimental evolution, we performed computer simulations to study the pattern of selected alleles for two models: 1) adaptation of a trait via independent beneficial mutations that are conditioned for fixation, that is, selective sweep model and 2) trait optimum model (polygenic adaptation), that is adaptation of a quantitative trait under stabilizing selection after a sudden shift in trait optimum. We identify several distinct patterns of selective sweep and trait optimum models in populations of different sizes. These features could provide the foundation for development of quantitative approaches to differentiate the two models.
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Affiliation(s)
- Neda Barghi
- Institut für Populationsgenetik, Vetmeduni, Vienna, Austria
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Chen J, Glémin S, Lascoux M. From Drift to Draft: How Much Do Beneficial Mutations Actually Contribute to Predictions of Ohta's Slightly Deleterious Model of Molecular Evolution? Genetics 2020; 214:1005-1018. [PMID: 32015019 PMCID: PMC7153929 DOI: 10.1534/genetics.119.302869] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Accepted: 01/26/2020] [Indexed: 12/18/2022] Open
Abstract
Since its inception in 1973, the slightly deleterious model of molecular evolution, also known as the nearly neutral theory of molecular evolution, remains a central model to explain the main patterns of DNA polymorphism in natural populations. This is not to say that the quantitative fit to data are perfect. A recent study used polymorphism data from Drosophila melanogaster to test whether, as predicted by the nearly neutral theory, the proportion of effectively neutral mutations depends on the effective population size (Ne ). It showed that a nearly neutral model simply scaling with Ne variation across the genome could not alone explain the data, but that consideration of linked positive selection improves the fit between observations and predictions. In the present article, we extended the work in two main directions. First, we confirmed the observed pattern on a set of 59 species, including high-quality genomic data from 11 animal and plant species with different mating systems and effective population sizes, hence a priori different levels of linked selection. Second, for the 11 species with high-quality genomic data we also estimated the full distribution of fitness effects (DFE) of mutations, and not solely the DFE of deleterious mutations. Both Ne and beneficial mutations contributed to the relationship between the proportion of effectively neutral mutations and local Ne across the genome. In conclusion, the predictions of the slightly deleterious model of molecular evolution hold well for species with small Ne , but for species with large Ne , the fit is improved by incorporating linked positive selection to the model.
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Affiliation(s)
- Jun Chen
- College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, 75236 Uppsala, Sweden
| | - Sylvain Glémin
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, 75236 Uppsala, Sweden
- Université de Rennes, Centre National de la Recherche Scientifique (CNRS), ECOBIO (Ecosystèmes, Biodiversité, Evolution) - Unité Mixte de Recherche (UMR) 6553, F-35000 Rennes, France
| | - Martin Lascoux
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, 75236 Uppsala, Sweden
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Hejase HA, Dukler N, Siepel A. From Summary Statistics to Gene Trees: Methods for Inferring Positive Selection. Trends Genet 2020; 36:243-258. [PMID: 31954511 PMCID: PMC7177178 DOI: 10.1016/j.tig.2019.12.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 11/15/2019] [Accepted: 12/11/2019] [Indexed: 01/01/2023]
Abstract
Methods to detect signals of natural selection from genomic data have traditionally emphasized the use of simple summary statistics. Here, we review a new generation of methods that consider combinations of conventional summary statistics and/or richer features derived from inferred gene trees and ancestral recombination graphs (ARGs). We also review recent advances in methods for population genetic simulation and ARG reconstruction. Finally, we describe opportunities for future work on a variety of related topics, including the genetics of speciation, estimation of selection coefficients, and inference of selection on polygenic traits. Together, these emerging methods offer promising new directions in the study of natural selection.
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Affiliation(s)
- Hussein A Hejase
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
| | - Noah Dukler
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Adam Siepel
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
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Koropoulis A, Alachiotis N, Pavlidis P. Detecting Positive Selection in Populations Using Genetic Data. Methods Mol Biol 2020; 2090:87-123. [PMID: 31975165 DOI: 10.1007/978-1-0716-0199-0_5] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
High-throughput genomic sequencing allows to disentangle the evolutionary forces acting in populations. Among evolutionary forces, positive selection has received a lot of attention because it is related to the adaptation of populations in their environments, both biotic and abiotic. Positive selection, also known as Darwinian selection, occurs when an allele is favored by natural selection. The frequency of the favored allele increases in the population and, due to genetic hitchhiking, neighboring linked variation diminishes, creating so-called selective sweeps. Such a process leaves traces in genomes that can be detected in a future time point. Detecting traces of positive selection in genomes is achieved by searching for signatures introduced by selective sweeps, such as regions of reduced variation, a specific shift of the site frequency spectrum, and particular linkage disequilibrium (LD) patterns in the region. A variety of approaches can be used for detecting selective sweeps, ranging from simple implementations that compute summary statistics to more advanced statistical approaches, e.g., Bayesian approaches, maximum-likelihood-based methods, and machine learning methods. In this chapter, we discuss selective sweep detection methodologies on the basis of their capacity to analyze whole genomes or just subgenomic regions, and on the specific polymorphism patterns they exploit as selective sweep signatures. We also summarize the results of comparisons among five open-source software releases (SweeD, SweepFinder, SweepFinder2, OmegaPlus, and RAiSD) regarding sensitivity, specificity, and execution times. Furthermore, we test and discuss machine learning methods and present a thorough performance analysis. In equilibrium neutral models or mild bottlenecks, most methods are able to detect selective sweeps accurately. Methods and tools that rely on linkage disequilibrium (LD) rather than single SNPs exhibit higher true positive rates than the site frequency spectrum (SFS)-based methods under the model of a single sweep or recurrent hitchhiking. However, their false positive rate is elevated when a misspecified demographic model is used to build the distribution of the statistic under the null hypothesis. Both LD and SFS-based approaches suffer from decreased accuracy on localizing the true target of selection in bottleneck scenarios. Furthermore, we present an extensive analysis of the effects of gene flow on selective sweep detection, a problem that has been understudied in selective sweep literature.
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Affiliation(s)
- Angelos Koropoulis
- Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece
- Computer Science Department, University of Crete, Crete, Heraklion, Greece
| | - Nikolaos Alachiotis
- Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece
| | - Pavlos Pavlidis
- Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Greece.
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Whole genome detection of recent selection signatures in Sarabi cattle: a unique Iranian taurine breed. Genes Genomics 2019; 42:203-215. [DOI: 10.1007/s13258-019-00888-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 11/12/2019] [Indexed: 12/13/2022]
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Mattingsdal M, Jorde PE, Knutsen H, Jentoft S, Stenseth NC, Sodeland M, Robalo JI, Hansen MM, André C, Blanco Gonzalez E. Demographic history has shaped the strongly differentiated corkwing wrasse populations in Northern Europe. Mol Ecol 2019; 29:160-171. [DOI: 10.1111/mec.15310] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 11/06/2019] [Accepted: 11/13/2019] [Indexed: 12/11/2022]
Affiliation(s)
- Morten Mattingsdal
- Department of Natural Sciences Centre for Coastal Research University of Agder Kristiansand Norway
| | | | - Halvor Knutsen
- Department of Natural Sciences Centre for Coastal Research University of Agder Kristiansand Norway
- Institute of Marine Research Flødevigen Norway
| | - Sissel Jentoft
- Department of Biosciences Centre for Ecological and Evolutionary Synthesis University of Oslo Oslo Norway
| | - Nils Christian Stenseth
- Department of Natural Sciences Centre for Coastal Research University of Agder Kristiansand Norway
- Department of Biosciences Centre for Ecological and Evolutionary Synthesis University of Oslo Oslo Norway
| | - Marte Sodeland
- Department of Natural Sciences Centre for Coastal Research University of Agder Kristiansand Norway
| | - Joana I. Robalo
- Marine and Environmental Sciences Centre ISPA Instituto Universitário de Ciências Psicológicas, Sociais e da Vida Lisboa Portugal
| | | | - Carl André
- Department of Marine Sciences‐Tjärnö Göteborg University Strömstad Sweden
| | - Enrique Blanco Gonzalez
- Department of Natural Sciences Centre for Coastal Research University of Agder Kristiansand Norway
- Norwegian College of Fishery Science UiT The Arctic University of Norway Tromsø Norway
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Torada L, Lorenzon L, Beddis A, Isildak U, Pattini L, Mathieson S, Fumagalli M. ImaGene: a convolutional neural network to quantify natural selection from genomic data. BMC Bioinformatics 2019; 20:337. [PMID: 31757205 PMCID: PMC6873651 DOI: 10.1186/s12859-019-2927-x] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Accepted: 05/31/2019] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND The genetic bases of many complex phenotypes are still largely unknown, mostly due to the polygenic nature of the traits and the small effect of each associated mutation. An alternative approach to classic association studies to determining such genetic bases is an evolutionary framework. As sites targeted by natural selection are likely to harbor important functionalities for the carrier, the identification of selection signatures in the genome has the potential to unveil the genetic mechanisms underpinning human phenotypes. Popular methods of detecting such signals rely on compressing genomic information into summary statistics, resulting in the loss of information. Furthermore, few methods are able to quantify the strength of selection. Here we explored the use of deep learning in evolutionary biology and implemented a program, called ImaGene, to apply convolutional neural networks on population genomic data for the detection and quantification of natural selection. RESULTS ImaGene enables genomic information from multiple individuals to be represented as abstract images. Each image is created by stacking aligned genomic data and encoding distinct alleles into separate colors. To detect and quantify signatures of positive selection, ImaGene implements a convolutional neural network which is trained using simulations. We show how the method implemented in ImaGene can be affected by data manipulation and learning strategies. In particular, we show how sorting images by row and column leads to accurate predictions. We also demonstrate how the misspecification of the correct demographic model for producing training data can influence the quantification of positive selection. We finally illustrate an approach to estimate the selection coefficient, a continuous variable, using multiclass classification techniques. CONCLUSIONS While the use of deep learning in evolutionary genomics is in its infancy, here we demonstrated its potential to detect informative patterns from large-scale genomic data. We implemented methods to process genomic data for deep learning in a user-friendly program called ImaGene. The joint inference of the evolutionary history of mutations and their functional impact will facilitate mapping studies and provide novel insights into the molecular mechanisms associated with human phenotypes.
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Affiliation(s)
- Luis Torada
- Department of Life Sciences, Silwood Park campus, Imperial College London, Buckhurst Road, Ascot, SL5 7PY UK
| | - Lucrezia Lorenzon
- Department of Life Sciences, Silwood Park campus, Imperial College London, Buckhurst Road, Ascot, SL5 7PY UK
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, piazza Leonardo da Vinci 32, Milan, 20133 Italy
| | - Alice Beddis
- Department of Life Sciences, Silwood Park campus, Imperial College London, Buckhurst Road, Ascot, SL5 7PY UK
| | - Ulas Isildak
- Department of Biological Sciences, Middle East Technical University, METU Üniversiteler Mah. Dumlupınar Blv. No:1, Ankara, 06800 Çankaya Turkey
| | - Linda Pattini
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, piazza Leonardo da Vinci 32, Milan, 20133 Italy
| | - Sara Mathieson
- Department of Computer Science, Swarthmore College, 500 College Ave, Swarthmore, 19081 PA USA
| | - Matteo Fumagalli
- Department of Life Sciences, Silwood Park campus, Imperial College London, Buckhurst Road, Ascot, SL5 7PY UK
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Adaptation in structured populations and fuzzy boundaries between hard and soft sweeps. PLoS Comput Biol 2019; 15:e1007426. [PMID: 31710623 PMCID: PMC6872172 DOI: 10.1371/journal.pcbi.1007426] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 11/21/2019] [Accepted: 09/20/2019] [Indexed: 11/19/2022] Open
Abstract
Selective sweeps, the genetic footprint of positive selection, have been extensively studied in the past decades, with dozens of methods developed to identify swept regions. However, these methods suffer from both false positive and false negative reports, and the candidates identified with different methods are often inconsistent with each other. We propose that a biological cause of this problem can be population subdivision, and a technical cause can be incomplete, or inaccurate, modeling of the dynamic process associated with sweeps. Here we used simulations to show how these effects interact and potentially cause bias. In particular, we show that sweeps maybe misclassified as either hard or soft, when the true time stage of a sweep and that implied, or pre-supposed, by the model do not match. We call this "temporal misclassification". Similarly, "spatial misclassification (softening)" can occur when hard sweeps, which are imported by migration into a new subpopulation, are falsely identified as soft. This can easily happen in case of local adaptation, i.e. when the sweeping allele is not under positive selection in the new subpopulation, and the underlying model assumes panmixis instead of substructure. The claim that most sweeps in the evolutionary history of humans were soft, may have to be reconsidered in the light of these findings.
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Iquebal MA, Sharma P, Jasrotia RS, Jaiswal S, Kaur A, Saroha M, Angadi UB, Sheoran S, Singh R, Singh GP, Rai A, Tiwari R, Kumar D. RNAseq analysis reveals drought-responsive molecular pathways with candidate genes and putative molecular markers in root tissue of wheat. Sci Rep 2019; 9:13917. [PMID: 31558740 PMCID: PMC6763491 DOI: 10.1038/s41598-019-49915-2] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 08/12/2019] [Indexed: 01/08/2023] Open
Abstract
Drought is one of the major impediments in wheat productivity. Traditional breeding and marker assisted QTL introgression had limited success. Available wheat genomic and RNA-seq data can decipher novel drought tolerance mechanisms with putative candidate gene and marker discovery. Drought is first sensed by root tissue but limited information is available about how roots respond to drought stress. In this view, two contrasting genotypes, namely, NI5439 41 (drought tolerant) and WL711 (drought susceptible) were used to generate ~78.2 GB data for the responses of wheat roots to drought. A total of 45139 DEGs, 13820 TF, 288 miRNAs, 640 pathways and 435829 putative markers were obtained. Study reveals use of such data in QTL to QTN refinement by analysis on two model drought-responsive QTLs on chromosome 3B in wheat roots possessing 18 differentially regulated genes with 190 sequence variants (173 SNPs and 17 InDels). Gene regulatory networks showed 69 hub-genes integrating ABA dependent and independent pathways controlling sensing of drought, root growth, uptake regulation, purine metabolism, thiamine metabolism and antibiotics pathways, stomatal closure and senescence. Eleven SSR markers were validated in a panel of 18 diverse wheat varieties. For effective future use of findings, web genomic resources were developed. We report RNA-Seq approach on wheat roots describing the drought response mechanisms under field drought conditions along with genomic resources, warranted in endeavour of wheat productivity.
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Affiliation(s)
- Mir Asif Iquebal
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi, 110012, India
| | - Pradeep Sharma
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, Haryana, 132001, India
| | - Rahul Singh Jasrotia
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi, 110012, India
| | - Sarika Jaiswal
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi, 110012, India
| | - Amandeep Kaur
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, Haryana, 132001, India
| | - Monika Saroha
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, Haryana, 132001, India
| | - U B Angadi
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi, 110012, India
| | - Sonia Sheoran
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, Haryana, 132001, India
| | - Rajender Singh
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, Haryana, 132001, India
| | - G P Singh
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, Haryana, 132001, India
| | - Anil Rai
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi, 110012, India
| | - Ratan Tiwari
- ICAR-Indian Institute of Wheat and Barley Research, Karnal, Haryana, 132001, India.
| | - Dinesh Kumar
- Centre for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi, 110012, India.
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Wegary D, Teklewold A, Prasanna BM, Ertiro BT, Alachiotis N, Negera D, Awas G, Abakemal D, Ogugo V, Gowda M, Semagn K. Molecular diversity and selective sweeps in maize inbred lines adapted to African highlands. Sci Rep 2019; 9:13490. [PMID: 31530852 PMCID: PMC6748982 DOI: 10.1038/s41598-019-49861-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 08/28/2019] [Indexed: 11/08/2022] Open
Abstract
Little is known on maize germplasm adapted to the African highland agro-ecologies. In this study, we analyzed high-density genotyping by sequencing (GBS) data of 298 African highland adapted maize inbred lines to (i) assess the extent of genetic purity, genetic relatedness, and population structure, and (ii) identify genomic regions that have undergone selection (selective sweeps) in response to adaptation to highland environments. Nearly 91% of the pairs of inbred lines differed by 30-36% of the scored alleles, but only 32% of the pairs of the inbred lines had relative kinship coefficient <0.050, which suggests the presence of substantial redundancy in allelic composition that may be due to repeated use of fewer genetic backgrounds (source germplasm) during line development. Results from different genetic relatedness and population structure analyses revealed three different groups, which generally agrees with pedigree information and breeding history, but less so by heterotic groups and endosperm modification. We identified 944 single nucleotide polymorphic (SNP) markers that fell within 22 selective sweeps that harbored 265 protein-coding candidate genes of which some of the candidate genes had known functions. Details of the candidate genes with known functions and differences in nucleotide diversity among groups predicted based on multivariate methods have been discussed.
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Affiliation(s)
- Dagne Wegary
- International Maize and Wheat Improvement Center (CIMMYT) - Ethiopia Office, ILRI Campus, CMC Road, Gurd Sholla, P.O. Box 5689, Addis Ababa, Ethiopia
| | - Adefris Teklewold
- International Maize and Wheat Improvement Center (CIMMYT) - Ethiopia Office, ILRI Campus, CMC Road, Gurd Sholla, P.O. Box 5689, Addis Ababa, Ethiopia.
| | - Boddupalli M Prasanna
- International Maize and Wheat Improvement Center (CIMMYT), ICRAF House, United Nations Avenue, Gigiri, P.O. Box 1041-00621, Nairobi, Kenya
| | - Berhanu T Ertiro
- Bako National Maize Research Center, Ethiopian Institute of Agricultural Research (EIAR), Addis Ababa, Ethiopia
| | - Nikolaos Alachiotis
- Institute of Computer Science, Foundation for Research and Technology-Hellas, Nikolaou Plastira 100, 70013, Heraklion, Crete, Greece
| | - Demewez Negera
- International Maize and Wheat Improvement Center (CIMMYT) - Ethiopia Office, ILRI Campus, CMC Road, Gurd Sholla, P.O. Box 5689, Addis Ababa, Ethiopia
| | - Geremew Awas
- International Maize and Wheat Improvement Center (CIMMYT) - Ethiopia Office, ILRI Campus, CMC Road, Gurd Sholla, P.O. Box 5689, Addis Ababa, Ethiopia
| | - Demissew Abakemal
- Ambo Agricultural Research Center, P.O. Box 37, West Shoa, Ambo, Ethiopia
| | - Veronica Ogugo
- International Maize and Wheat Improvement Center (CIMMYT), ICRAF House, United Nations Avenue, Gigiri, P.O. Box 1041-00621, Nairobi, Kenya
| | - Manje Gowda
- International Maize and Wheat Improvement Center (CIMMYT), ICRAF House, United Nations Avenue, Gigiri, P.O. Box 1041-00621, Nairobi, Kenya
| | - Kassa Semagn
- International Maize and Wheat Improvement Center (CIMMYT), ICRAF House, United Nations Avenue, Gigiri, P.O. Box 1041-00621, Nairobi, Kenya.
- Africa Rice Center (AfricaRice), M'bé Research Station, 01 B.P. 2551, Bouaké 01, Côte d'Ivoire.
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Goodman KR, Prost S, Bi K, Brewer MS, Gillespie RG. Host and geography together drive early adaptive radiation of Hawaiian planthoppers. Mol Ecol 2019; 28:4513-4528. [PMID: 31484218 DOI: 10.1111/mec.15231] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Revised: 08/19/2019] [Accepted: 08/27/2019] [Indexed: 11/30/2022]
Abstract
The interactions between insects and their plant host have been implicated in driving diversification of both players. Early arguments highlighted the role of ecological opportunity, with the idea that insects "escape and radiate" on new hosts, with subsequent hypotheses focusing on the interplay between host shifting and host tracking, coupled with isolation and fusion, in generating diversity. Because it is rarely possible to capture the initial stages of diversification, it is particularly difficult to ascertain the relative roles of geographic isolation versus host shifts in initiating the process. The current study examines genetic diversity between populations and hosts within a single species of endemic Hawaiian planthopper, Nesosydne umbratica (Hemiptera, Delphacidae). Given that the species was known as a host generalist occupying unrelated hosts, Clermontia (Campanulaceae) and Pipturus (Urticaceae), we set out to determine the relative importance of geography and host in structuring populations in the early stages of differentiation on the youngest islands of the Hawaiian chain. Results from extensive exon capture data showed that N. umbratica is highly structured, both by geography, with discrete populations on each volcano, and by host plant, with parallel radiations on Clermontia and Pipturus leading to extensive co-occurrence. The marked genetic structure suggests that populations can readily become established on novel hosts provided opportunity; subsequent adaptation allows monopolization of the new host. The results support the role of geographic isolation in structuring populations and with host shifts occurring as discrete events that facilitate subsequent parallel geographic range expansion.
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Affiliation(s)
- Kari Roesch Goodman
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA
| | - Stefan Prost
- Department of Integrative Biology, University of California, Berkeley, CA, USA.,LOEWE-Centre for Translational Biodiversity Genomics, Senckenberg Research Institute, Frankfurt/Main, Germany
| | - Ke Bi
- Computational Genomics Resource Laboratory (CGRL), California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, CA, USA.,Ancestry, San Francisco, CA, USA.,Museum of Vertebrate Zoology, University of California, Berkeley, CA, USA
| | - Michael S Brewer
- Department of Biology, East Carolina University, Greenville, NC, USA
| | - Rosemary G Gillespie
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA
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Joukhadar R, Daetwyler HD, Gendall AR, Hayden MJ. Artificial selection causes significant linkage disequilibrium among multiple unlinked genes in Australian wheat. Evol Appl 2019; 12:1610-1625. [PMID: 31462918 PMCID: PMC6708422 DOI: 10.1111/eva.12807] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 04/17/2019] [Accepted: 04/19/2019] [Indexed: 01/21/2023] Open
Abstract
Australia has one of the oldest modern wheat breeding programs worldwide although the crop was first introduced to the country in 1788. Breeders selected wheat with high adaptation to different Australian climates, while ensuring satisfactory yield and quality. This artificial selection left distinct genomic signatures that can be used to retrospectively understand breeding targets, and to detect economically important alleles. To study the effect of artificial selection on modern cultivars and cultivars released in different Australian states, we genotyped 482 Australian cultivars representing the history of wheat breeding in Australia since 1840. Computer simulation showed that 86 genomic regions were significantly affected by artificial selection. Characterization of 18 major genes known to affect wheat adaptation, yield, and quality revealed that many were affected by artificial selection and contained within regions under selection. Similarly, many reported QTL and genes for yield, quality, and adaptation were also contained in regions affected by artificial selection. These included TaCwi-A1, TaGw2-6A, Sus-2B, TaSus1-7A, TaSAP1-7A, Glu-A1, Glu-B1, Glu-B3, PinA, PinB, Ppo-D1, Psy-A1, Psy-A2, Rht-A1, Rht-B1, Ppd-D1, Vrn-A1, Vrn-B1, and Cre8. Interestingly, 17 regions affected by artificial selection were in moderate-to-high linkage disequilibrium with each other with an average r 2 value of 0.35 indicating strong simultaneous selection on specific alleles. These regions included Glu-B1, TaGw2-6A, Cre8, Ppd-D1, Rht-B1, Vrn-B1, TaSus1-7A, TaSAP1-7A, and Psy-A1 plus multiple QTL affecting wheat yield and yield components. These results highlighted the effects of the long-term artificial selection on Australian wheat germplasm and identified putative regions underlying important traits in wheat.
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Affiliation(s)
- Reem Joukhadar
- Department of Animal, Plant and Soil SciencesLa Trobe UniversityBundooraVictoriaAustralia
- Agriculture Victoria Research, AgriBioCentre for AgribioscienceBundooraVictoriaAustralia
| | - Hans D. Daetwyler
- Agriculture Victoria Research, AgriBioCentre for AgribioscienceBundooraVictoriaAustralia
- School of Applied Systems BiologyLa Trobe UniversityBundooraVictoriaAustralia
| | - Anthony R. Gendall
- Department of Animal, Plant and Soil SciencesLa Trobe UniversityBundooraVictoriaAustralia
| | - Matthew J. Hayden
- Agriculture Victoria Research, AgriBioCentre for AgribioscienceBundooraVictoriaAustralia
- School of Applied Systems BiologyLa Trobe UniversityBundooraVictoriaAustralia
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