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McHugo GP, Ward JA, Ng'ang'a SI, Frantz LAF, Salter-Townshend M, Hill EW, O'Gorman GM, Meade KG, Hall TJ, MacHugh DE. Genome-wide local ancestry and the functional consequences of admixture in African and European cattle populations. Heredity (Edinb) 2025; 134:49-63. [PMID: 39516247 PMCID: PMC11723932 DOI: 10.1038/s41437-024-00734-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2024] [Revised: 10/26/2024] [Accepted: 10/26/2024] [Indexed: 11/16/2024] Open
Abstract
Bos taurus (taurine) and Bos indicus (indicine) cattle diverged at least 150,000 years ago and, since that time, substantial genomic differences have evolved between the two lineages. During the last two millennia, genetic exchange in Africa has resulted in a complex tapestry of taurine-indicine ancestry, with most cattle populations exhibiting varying levels of admixture. Similarly, there are several Southern European cattle populations that also show evidence for historical gene flow from indicine cattle, the highest levels of which are found in the Central Italian White breeds. Here we use two different software tools (MOSAIC and ELAI) for local ancestry inference (LAI) with genome-wide high- and low-density SNP array data sets in hybrid African and residually admixed Southern European cattle populations and obtained broadly similar results despite critical differences in the two LAI methodologies used. Our analyses identified genomic regions with elevated levels of retained or introgressed ancestry from the African taurine, European taurine, and Asian indicine lineages. Functional enrichment of genes underlying these ancestry peaks highlighted biological processes relating to immunobiology and olfaction, some of which may relate to differing susceptibilities to infectious diseases, including bovine tuberculosis, East Coast fever, and tropical theileriosis. Notably, for retained African taurine ancestry in admixed trypanotolerant cattle we observed enrichment of genes associated with haemoglobin and oxygen transport. This may reflect positive selection of genomic variants that enhance control of severe anaemia, a debilitating feature of trypanosomiasis disease, which severely constrains cattle agriculture across much of sub-Saharan Africa.
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Affiliation(s)
- Gillian P McHugo
- UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland
| | - James A Ward
- UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland
| | - Said Ismael Ng'ang'a
- Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, 80539, Munich, Germany
- School of Biological and Chemical Sciences, Queen Mary University of London, London, E1 4NS, UK
| | - Laurent A F Frantz
- Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, 80539, Munich, Germany
- School of Biological and Chemical Sciences, Queen Mary University of London, London, E1 4NS, UK
| | | | - Emmeline W Hill
- UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland
| | - Grace M O'Gorman
- UK Agri-Tech Centre, Innovation Centre, York Science Park, York, YO10 5DG, UK
| | - Kieran G Meade
- UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland
- UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
- UCD One Health Centre, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Thomas J Hall
- UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland
| | - David E MacHugh
- UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland.
- UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland.
- UCD One Health Centre, University College Dublin, Dublin, D04 V1W8, Ireland.
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2
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Ogunbawo AR, Mulim HA, Campos GS, Schinckel AP, de Oliveira HR. Tailoring Genomic Selection for Bos taurus indicus: A Comprehensive Review of SNP Arrays and Reference Genomes. Genes (Basel) 2024; 15:1495. [PMID: 39766762 PMCID: PMC11675768 DOI: 10.3390/genes15121495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2024] [Revised: 11/15/2024] [Accepted: 11/19/2024] [Indexed: 01/11/2025] Open
Abstract
BACKGROUND Advances in SNP arrays and reference genome assemblies have significantly transformed cattle genomics, particularly for Bos taurus indicus (Zebu cattle). Many commercial SNP arrays were originally designed for Bos taurus taurus, leading to ascertainment bias and the exclusion of crucial SNPs specific to Zebu populations. This review assesses progress in SNP array and reference genome development, with a focus on efforts tailored to Zebu populations and their impact on genomic selection and breeding efficiency. METHODS We reviewed the relevant literature on the development of SNP arrays, reference genome assemblies, and SNP genotyping techniques used for Zebu cattle. Emphasis was placed on SNP arrays specifically designed for Zebu breeds, evaluating their contributions to genomic evaluations and identifying limitations in prediction accuracy. RESULTS Recent advancements, such as GeneSeek's low- and high-density SNP panels, have aimed to reduce ascertainment bias and include key SNPs for Zebu populations by providing breed-specific panels. These panels have been instrumental in identifying genomic regions associated with economically important traits in Nellore cattle. Studies show that tailored SNP arrays and breed-specific reference genomes can enhance genetic diversity assessment and improve genomic predictions, supporting more effective breeding programs for Zebu cattle. CONCLUSIONS Improved SNP arrays and breed-specific reference genomes are crucial for accurate genomic selection in Zebu cattle. Future efforts should prioritize expanding de novo genome assemblies, reducing ascertainment bias, and developing cost-effective genotyping solutions tailored to Zebu populations. Targeted genomic tools will ultimately enable more efficient breeding practices and enhance genomic selection for economically important traits in B. t. indicus cattle.
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Affiliation(s)
- Adebisi R. Ogunbawo
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (A.R.O.); (H.A.M.); (G.S.C.); (A.P.S.)
| | - Henrique A. Mulim
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (A.R.O.); (H.A.M.); (G.S.C.); (A.P.S.)
| | - Gabriel S. Campos
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (A.R.O.); (H.A.M.); (G.S.C.); (A.P.S.)
- Department of Animal Biosciences, Interbull Centre, S-75007 Uppsala, Sweden
| | - Allan P. Schinckel
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (A.R.O.); (H.A.M.); (G.S.C.); (A.P.S.)
| | - Hinayah Rojas de Oliveira
- Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA; (A.R.O.); (H.A.M.); (G.S.C.); (A.P.S.)
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3
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Rick JA, Brock CD, Lewanski AL, Golcher-Benavides J, Wagner CE. Reference Genome Choice and Filtering Thresholds Jointly Influence Phylogenomic Analyses. Syst Biol 2024; 73:76-101. [PMID: 37881861 DOI: 10.1093/sysbio/syad065] [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: 03/10/2022] [Revised: 09/20/2023] [Accepted: 10/20/2023] [Indexed: 10/27/2023] Open
Abstract
Molecular phylogenies are a cornerstone of modern comparative biology and are commonly employed to investigate a range of biological phenomena, such as diversification rates, patterns in trait evolution, biogeography, and community assembly. Recent work has demonstrated that significant biases may be introduced into downstream phylogenetic analyses from processing genomic data; however, it remains unclear whether there are interactions among bioinformatic parameters or biases introduced through the choice of reference genome for sequence alignment and variant calling. We address these knowledge gaps by employing a combination of simulated and empirical data sets to investigate the extent to which the choice of reference genome in upstream bioinformatic processing of genomic data influences phylogenetic inference, as well as the way that reference genome choice interacts with bioinformatic filtering choices and phylogenetic inference method. We demonstrate that more stringent minor allele filters bias inferred trees away from the true species tree topology, and that these biased trees tend to be more imbalanced and have a higher center of gravity than the true trees. We find the greatest topological accuracy when filtering sites for minor allele count (MAC) >3-4 in our 51-taxa data sets, while tree center of gravity was closest to the true value when filtering for sites with MAC >1-2. In contrast, filtering for missing data increased accuracy in the inferred topologies; however, this effect was small in comparison to the effect of minor allele filters and may be undesirable due to a subsequent mutation spectrum distortion. The bias introduced by these filters differs based on the reference genome used in short read alignment, providing further support that choosing a reference genome for alignment is an important bioinformatic decision with implications for downstream analyses. These results demonstrate that attributes of the study system and dataset (and their interaction) add important nuance for how best to assemble and filter short-read genomic data for phylogenetic inference.
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Affiliation(s)
- Jessica A Rick
- School of Natural Resources & the Environment, University of Arizona, Tucson, AZ 85719, USA
| | - Chad D Brock
- Department of Biological Sciences, Tarleton State University, Stephenville, TX 76401, USA
| | - Alexander L Lewanski
- Department of Integrative Biology and W.K. Kellogg Biological Station, Michigan State University, East Lansing, MI 48824, USA
| | - Jimena Golcher-Benavides
- Department of Natural Resource Ecology and Management, Iowa State University, Ames, IA 50011, USA
| | - Catherine E Wagner
- Program in Ecology and Evolution, University of Wyoming, Laramie, WY 82071, USA
- Department of Botany, University of Wyoming, Laramie, WY 82071, USA
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Lavenia C, Priyono DS, Yudha DS, Arisuryanti T. Species Identification of Rehabilitated Critically Endangered Orangutans Through DNA Forensic: Implication for Conservation. Trop Life Sci Res 2024; 35:123-137. [PMID: 39262863 PMCID: PMC11383629 DOI: 10.21315/tlsr2024.35.1.7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 08/14/2023] [Indexed: 09/13/2024] Open
Abstract
Rehabilitating and releasing orangutans back into the wild is one of the conservation strategies being pursued to conserve orangutans. However, the species determination between Sumatran, Tapanuli, and Bornean orangutans is essential for reintroduction to avoid outbreeding depression, which could lead to DNA hybridisation and increase the probability of recessive characters. Here, we reported on an investigation of three orangutans in which DNA forensic techniques were used to identify the species before release and reintroduction to their habitat. By applying DNA forensic, the orangutan was successfully confirmed with high probabilities (100%) by identifying two orangutan species, Pongo abelii and Pongo pygmaeus wurmbii. Based on ambiguous morphology, we found the possibility of orangutan species being misidentified in rehabilitation. This case report demonstrates the importance of molecular diagnostics to identify the orangutan species. We also provide workflow recommendations from genetic aspect for rehabilitated orangutans. These recommendations will enable decision-makers to consider genetics when assessing future management decisions, which will help ensure that the orangutan species is effectively conserved.
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Affiliation(s)
- Christy Lavenia
- Department of Biology, Universitas Indonesia, Depok 16424. West Java, Indonesia
| | - Dwi Sendi Priyono
- Department of Tropical Biology, Faculty of Biology, Universitas Gadjah Mada. Jl. Teknika Selatan, Sinduadi. Mlati, Sleman, 55281. Special Region of Yogyakarta, Indonesia
- Centre for Indonesia Tropical Biodiversity (CENTROBIO), Faculty of Biology, Universitas Gadjah Mada. Jl. Teknika Selatan, Sinduadi. Mlati, Sleman, 55281. Special Region of Yogyakarta, Indonesia
| | - Donan Satria Yudha
- Department of Tropical Biology, Faculty of Biology, Universitas Gadjah Mada. Jl. Teknika Selatan, Sinduadi. Mlati, Sleman, 55281. Special Region of Yogyakarta, Indonesia
| | - Tuty Arisuryanti
- Department of Tropical Biology, Faculty of Biology, Universitas Gadjah Mada. Jl. Teknika Selatan, Sinduadi. Mlati, Sleman, 55281. Special Region of Yogyakarta, Indonesia
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5
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Ward JA, Ng'ang'a SI, Randhawa IAS, McHugo GP, O'Grady JF, Flórez JM, Browne JA, Pérez O’Brien AM, Landaeta-Hernández AJ, Garcia JF, Sonstegard TS, Frantz LAF, Salter-Townshend M, MacHugh DE. Genomic insights into the population history and adaptive traits of Latin American Criollo cattle. ROYAL SOCIETY OPEN SCIENCE 2024; 11:231388. [PMID: 38571912 PMCID: PMC10990470 DOI: 10.1098/rsos.231388] [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: 09/14/2023] [Revised: 01/04/2024] [Accepted: 01/31/2024] [Indexed: 04/05/2024]
Abstract
Criollo cattle, the descendants of animals brought by Iberian colonists to the Americas, have been the subject of natural and human-mediated selection in novel tropical agroecological zones for centuries. Consequently, these breeds have evolved distinct characteristics such as resistance to diseases and exceptional heat tolerance. In addition to European taurine (Bos taurus) ancestry, it has been proposed that gene flow from African taurine and Asian indicine (Bos indicus) cattle has shaped the ancestry of Criollo cattle. In this study, we analysed Criollo breeds from Colombia and Venezuela using whole-genome sequencing (WGS) and single-nucleotide polymorphism (SNP) array data to examine population structure and admixture at high resolution. Analysis of genetic structure and ancestry components provided evidence for African taurine and Asian indicine admixture in Criollo cattle. In addition, using WGS data, we detected selection signatures associated with a myriad of adaptive traits, revealing genes linked to thermotolerance, reproduction, fertility, immunity and distinct coat and skin coloration traits. This study underscores the remarkable adaptability of Criollo cattle and highlights the genetic richness and potential of these breeds in the face of climate change, habitat flux and disease challenges. Further research is warranted to leverage these findings for more effective and sustainable cattle breeding programmes.
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Affiliation(s)
- James A. Ward
- Animal Genomics Laboratory, School of Agriculture and Food Science, University College Dublin, DublinD04 V1W8, Ireland
| | - Said I. Ng'ang'a
- Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, MunichD-80539, Germany
- School of Biological and Chemical Sciences, Queen Mary University of London, LondonE1 4NS, UK
| | | | - Gillian P. McHugo
- Animal Genomics Laboratory, School of Agriculture and Food Science, University College Dublin, DublinD04 V1W8, Ireland
| | - John F. O'Grady
- Animal Genomics Laboratory, School of Agriculture and Food Science, University College Dublin, DublinD04 V1W8, Ireland
| | - Julio M. Flórez
- Acceligen, Eagan, MN55121, USA
- Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University (Unesp), Jaboticabal, Brazil
| | - John A. Browne
- Animal Genomics Laboratory, School of Agriculture and Food Science, University College Dublin, DublinD04 V1W8, Ireland
| | | | - Antonio J. Landaeta-Hernández
- Unidad de Investigaciones Zootécnicas, Facultad de Ciencias Veterinarias, Universidad del Zulia, Maracaibo, Venezuela
| | - Jóse F. Garcia
- Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University (Unesp), Jaboticabal, Brazil
| | | | - Laurent A. F. Frantz
- Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, MunichD-80539, Germany
- School of Biological and Chemical Sciences, Queen Mary University of London, LondonE1 4NS, UK
| | | | - David E. MacHugh
- Animal Genomics Laboratory, School of Agriculture and Food Science, University College Dublin, DublinD04 V1W8, Ireland
- Conway Institute of Biomolecular and Biomedical Research, University College Dublin, DublinD04 V1W8, Ireland
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Flegontov P, Işıldak U, Maier R, Yüncü E, Changmai P, Reich D. Modeling of African population history using f-statistics is biased when applying all previously proposed SNP ascertainment schemes. PLoS Genet 2023; 19:e1010931. [PMID: 37676865 PMCID: PMC10508636 DOI: 10.1371/journal.pgen.1010931] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 09/19/2023] [Accepted: 08/21/2023] [Indexed: 09/09/2023] Open
Abstract
f-statistics have emerged as a first line of analysis for making inferences about demographic history from genome-wide data. Not only are they guaranteed to allow robust tests of the fits of proposed models of population history to data when analyzing full genome sequencing data-that is, all single nucleotide polymorphisms (SNPs) in the individuals being analyzed-but they are also guaranteed to allow robust tests of models for SNPs ascertained as polymorphic in a population that is an outgroup in a phylogenetic sense to all groups being analyzed. True "outgroup ascertainment" is in practice impossible in humans because our species has arisen from a substructured ancestral population that does not descend from a homogeneous ancestral population going back many hundreds of thousands of years into the past. However, initial studies suggested that non-outgroup-ascertainment schemes might produce robust enough results using f-statistics, and that motivated widespread fitting of models to data using non-outgroup-ascertained SNP panels such as the "Affymetrix Human Origins array" which has been genotyped on thousands of modern individuals from hundreds of populations, or the "1240k" in-solution enrichment reagent which has been the source of about 70% of published genome-wide data for ancient humans. In this study, we show that while analyses of population history using such panels work well for studies of relationships among non-African populations and one African outgroup, when co-modeling more than one sub-Saharan African and/or archaic human groups (Neanderthals and Denisovans), fitting of f-statistics to such SNP sets is expected to frequently lead to false rejection of true demographic histories, and failure to reject incorrect models. Analyzing panels of SNPs polymorphic in archaic humans, which has been suggested as a solution for the ascertainment problem, has limited statistical power and retains important biases. However, by carrying out simulations of diverse demographic histories, we show that bias in inferences based on f-statistics can be minimized by ascertaining on variants common in a union of diverse African groups; such ascertainment retains high statistical power while allowing co-analysis of archaic and modern groups.
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Affiliation(s)
- Pavel Flegontov
- Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
- Kalmyk Research Center of the Russian Academy of Sciences, Elista, Russia
| | - Ulaş Işıldak
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
| | - Robert Maier
- Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Eren Yüncü
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
| | - Piya Changmai
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
| | - David Reich
- Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
- Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
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7
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Ben-Jemaa S, Adam G, Boussaha M, Bardou P, Klopp C, Mandonnet N, Naves M. Whole genome sequencing reveals signals of adaptive admixture in Creole cattle. Sci Rep 2023; 13:12155. [PMID: 37500674 PMCID: PMC10374910 DOI: 10.1038/s41598-023-38774-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 07/14/2023] [Indexed: 07/29/2023] Open
Abstract
The Creole cattle from Guadeloupe (GUA) are well adapted to the tropical environment. Its admixed genome likely played an important role in such adaptation. Here, we sought to detect genomic signatures of selection in the GUA genome. For this purpose, we sequenced 23 GUA individuals and combined our data with sequenced genomes of 99 animals representative of European, African and indicine groups. We detect 17,228,983 single nucleotide polymorphisms (SNPs) in the GUA genome, providing the most detailed exploration, to date, of patterns of genetic variation in this breed. We confirm the higher level of African and indicine ancestries, compared to the European ancestry and we highlight the African origin of indicine ancestry in the GUA genome. We identify five strong candidate regions showing an excess of indicine ancestry and consistently supported across the different detection methods. These regions encompass genes with adaptive roles in relation to immunity, thermotolerance and physical activity. We confirmed a previously identified horn-related gene, RXFP2, as a gene under strong selective pressure in the GUA population likely owing to human-driven (socio-cultural) pressure. Findings from this study provide insight into the genetic mechanisms associated with resilience traits in livestock.
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Affiliation(s)
- Slim Ben-Jemaa
- INRAE, ASSET, 97170, Petit-Bourg, France.
- Laboratoire des Productions Animales et Fourragères, Institut National de la Recherche Agronomique de Tunisie, Université de Carthage, 2049, Ariana, Tunisia.
| | | | - Mekki Boussaha
- AgroParisTech, GABI, INRAE, Université Paris-Saclay, 78350, Jouy-en-Josas, France
| | - Philippe Bardou
- GenPhySE, Ecole Nationale Vétérinaire de Toulouse (ENVT), INRA, Université de Toulouse, 24 Chemin de Borde Rouge, 31320, Castanet-Tolosan, France
- Sigenae, INRAE, 24 Chemin de Borde Rouge, 31320, Castanet-Tolosan, France
| | - Christophe Klopp
- Genotoul Bioinfo, BioInfoMics, MIAT UR875, Sigenae, INRAE, Castanet-Tolosan, France
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Martinez R, Bejarano D, Ramírez J, Ocampo R, Polanco N, Perez JE, Onofre HG, Rocha JF. Genomic variability and population structure of six Colombian cattle breeds. Trop Anim Health Prod 2023; 55:185. [PMID: 37130925 PMCID: PMC10154261 DOI: 10.1007/s11250-023-03574-8] [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: 09/03/2022] [Accepted: 03/29/2023] [Indexed: 05/04/2023]
Abstract
Analyses of the genetic diversity of indigenous cattle are essential for implementing conservation programs, promoting their sustainable use and maintaining productive advantages offered by these breeds in local conditions. The aim of this study was to investigate the genetic diversity and population structure of six Colombian cattle breeds: Blanco Orejinegro (BON), Costeño con Cuernos (CCC), Romosinuano (ROM), Sanmartinero (SAM), Casanareño (CAS), and Hartón del Valle (HDV). Two additional breed groups were included for comparison: Zebu (CEB) and a crossbreed of Colombian cattle breeds × Zebu. Genetic diversity within breeds was analyzed using expected heterozygosity (He), inbreeding coefficient (f), and runs of homozygosity (ROH). Population structure was assessed using model-based clustering (ADMIXTURE) and principal components analysis (PCA). Zebu cattle showed the lowest genetic diversity (He = 0.240). Breeds with the highest genetic diversity level were HDV and BON (He = 0.350 and 0.340, respectively). Inbreeding was lower for Colombian cattle breeds ranging between 0.005 and 0.045. Overall, the largest average genetic distance was found among the group of Colombian cattle breeds and Zebu, while the smallest was found between ROM and CCC. Model-based clustering revealed some level of admixture among HDV and CAS cattle which is consistent with their recent history. The results of the present study provide a useful insight on the genetic structure of Colombian cattle breeds.
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Affiliation(s)
- Rodrigo Martinez
- Corporación Colombiana de Investigación Agropecuaria - Agrosavia, Mosquera, Cundinamarca, Colombia
| | - Diego Bejarano
- Corporación Colombiana de Investigación Agropecuaria - Agrosavia, Mosquera, Cundinamarca, Colombia
| | - Julián Ramírez
- Corporación Colombiana de Investigación Agropecuaria - Agrosavia, Mosquera, Cundinamarca, Colombia
| | - Ricardo Ocampo
- Corporación Colombiana de Investigación Agropecuaria - Agrosavia, Mosquera, Cundinamarca, Colombia.
| | - Nelson Polanco
- Corporación Colombiana de Investigación Agropecuaria - Agrosavia, Mosquera, Cundinamarca, Colombia
| | - Juan Esteban Perez
- Corporación Colombiana de Investigación Agropecuaria - Agrosavia, Mosquera, Cundinamarca, Colombia
| | - Héctor Guillermo Onofre
- Corporación Colombiana de Investigación Agropecuaria - Agrosavia, Mosquera, Cundinamarca, Colombia
| | - Juan Felipe Rocha
- Corporación Colombiana de Investigación Agropecuaria - Agrosavia, Mosquera, Cundinamarca, Colombia
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Smith J, Alfieri JM, Anthony N, Arensburger P, Athrey GN, Balacco J, Balic A, Bardou P, Barela P, Bigot Y, Blackmon H, Borodin PM, Carroll R, Casono MC, Charles M, Cheng H, Chiodi M, Cigan L, Coghill LM, Crooijmans R, Das N, Davey S, Davidian A, Degalez F, Dekkers JM, Derks M, Diack AB, Djikeng A, Drechsler Y, Dyomin A, Fedrigo O, Fiddaman SR, Formenti G, Frantz LA, Fulton JE, Gaginskaya E, Galkina S, Gallardo RA, Geibel J, Gheyas AA, Godinez CJP, Goodell A, Graves JA, Griffin DK, Haase B, Han JL, Hanotte O, Henderson LJ, Hou ZC, Howe K, Huynh L, Ilatsia E, Jarvis ED, Johnson SM, Kaufman J, Kelly T, Kemp S, Kern C, Keroack JH, Klopp C, Lagarrigue S, Lamont SJ, Lange M, Lanke A, Larkin DM, Larson G, Layos JKN, Lebrasseur O, Malinovskaya LP, Martin RJ, Martin Cerezo ML, Mason AS, McCarthy FM, McGrew MJ, Mountcastle J, Muhonja CK, Muir W, Muret K, Murphy TD, Ng'ang'a I, Nishibori M, O'Connor RE, Ogugo M, Okimoto R, Ouko O, Patel HR, Perini F, Pigozzi MI, Potter KC, Price PD, Reimer C, Rice ES, Rocos N, Rogers TF, Saelao P, Schauer J, Schnabel RD, Schneider VA, Simianer H, Smith A, et alSmith J, Alfieri JM, Anthony N, Arensburger P, Athrey GN, Balacco J, Balic A, Bardou P, Barela P, Bigot Y, Blackmon H, Borodin PM, Carroll R, Casono MC, Charles M, Cheng H, Chiodi M, Cigan L, Coghill LM, Crooijmans R, Das N, Davey S, Davidian A, Degalez F, Dekkers JM, Derks M, Diack AB, Djikeng A, Drechsler Y, Dyomin A, Fedrigo O, Fiddaman SR, Formenti G, Frantz LA, Fulton JE, Gaginskaya E, Galkina S, Gallardo RA, Geibel J, Gheyas AA, Godinez CJP, Goodell A, Graves JA, Griffin DK, Haase B, Han JL, Hanotte O, Henderson LJ, Hou ZC, Howe K, Huynh L, Ilatsia E, Jarvis ED, Johnson SM, Kaufman J, Kelly T, Kemp S, Kern C, Keroack JH, Klopp C, Lagarrigue S, Lamont SJ, Lange M, Lanke A, Larkin DM, Larson G, Layos JKN, Lebrasseur O, Malinovskaya LP, Martin RJ, Martin Cerezo ML, Mason AS, McCarthy FM, McGrew MJ, Mountcastle J, Muhonja CK, Muir W, Muret K, Murphy TD, Ng'ang'a I, Nishibori M, O'Connor RE, Ogugo M, Okimoto R, Ouko O, Patel HR, Perini F, Pigozzi MI, Potter KC, Price PD, Reimer C, Rice ES, Rocos N, Rogers TF, Saelao P, Schauer J, Schnabel RD, Schneider VA, Simianer H, Smith A, Stevens MP, Stiers K, Tiambo CK, Tixier-Boichard M, Torgasheva AA, Tracey A, Tregaskes CA, Vervelde L, Wang Y, Warren WC, Waters PD, Webb D, Weigend S, Wolc A, Wright AE, Wright D, Wu Z, Yamagata M, Yang C, Yin ZT, Young MC, Zhang G, Zhao B, Zhou H. Fourth Report on Chicken Genes and Chromosomes 2022. Cytogenet Genome Res 2023; 162:405-528. [PMID: 36716736 PMCID: PMC11835228 DOI: 10.1159/000529376] [Show More Authors] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 01/22/2023] [Indexed: 02/01/2023] Open
Affiliation(s)
- Jacqueline Smith
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Edinburgh, UK
| | - James M. Alfieri
- Interdisciplinary Program in Ecology and Evolutionary Biology, Texas A&M University, College Station, Texas, USA
- Department of Biology, Texas A&M University, College Station, Texas, USA
- Department of Poultry Science, Texas A&M University, College Station, Texas, USA
| | | | - Peter Arensburger
- Biological Sciences Department, California State Polytechnic University, Pomona, California, USA
| | - Giridhar N. Athrey
- Interdisciplinary Program in Ecology and Evolutionary Biology, Texas A&M University, College Station, Texas, USA
- Department of Poultry Science, Texas A&M University, College Station, Texas, USA
| | | | - Adam Balic
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Edinburgh, UK
| | - Philippe Bardou
- Université de Toulouse, INRAE, ENVT, GenPhySE, Sigenae, Castanet Tolosan, France
| | | | - Yves Bigot
- PRC, UMR INRAE 0085, CNRS 7247, Centre INRAE Val de Loire, Nouzilly, France
| | - Heath Blackmon
- Interdisciplinary Program in Ecology and Evolutionary Biology, Texas A&M University, College Station, Texas, USA
- Department of Biology, Texas A&M University, College Station, Texas, USA
| | - Pavel M. Borodin
- Department of Molecular Genetics, Cell Biology and Bioinformatics, Institute of Cytology and Genetics of Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russian Federation
| | - Rachel Carroll
- Department of Animal Sciences, Data Science and Informatics Institute, University of Missouri, Columbia, Missouri, USA
| | | | - Mathieu Charles
- University Paris-Saclay, INRAE, AgroParisTech, GABI, Sigenae, Jouy-en-Josas, France
| | - Hans Cheng
- USDA, ARS, USNPRC, Avian Disease and Oncology Laboratory, East Lansing, Michigan, USA
| | | | | | - Lyndon M. Coghill
- Department of Veterinary Pathology, University of Missouri, Columbia, Missouri, USA
| | - Richard Crooijmans
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | | | - Sean Davey
- University of Arizona, Tucson, Arizona, USA
| | - Asya Davidian
- Saint Petersburg State University, Saint Petersburg, Russian Federation
| | - Fabien Degalez
- Centre for Tropical Livestock Genetics and Health (CTLGH) − ILRI, Nairobi, Kenya
| | - Jack M. Dekkers
- Department of Animal Science, University of California, Davis, California, USA
- INRAE, MIAT UR875, Sigenae, Castanet Tolosan, France
| | - Martijn Derks
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Abigail B. Diack
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Edinburgh, UK
| | - Appolinaire Djikeng
- Department of Molecular Microbiology and Immunology, University of Missouri, Columbia, Missouri, USA
| | | | - Alexander Dyomin
- Saint Petersburg State University, Saint Petersburg, Russian Federation
| | | | | | | | - Laurent A.F. Frantz
- Queen Mary University of London, Bethnal Green, London, UK
- Palaeogenomics Group, Department of Veterinary Sciences, LMU Munich, Munich, Germany
| | - Janet E. Fulton
- Hy-Line International, Research and Development, Dallas Center, Iowa, USA
| | - Elena Gaginskaya
- Saint Petersburg State University, Saint Petersburg, Russian Federation
| | - Svetlana Galkina
- Saint Petersburg State University, Saint Petersburg, Russian Federation
| | - Rodrigo A. Gallardo
- School of Veterinary Medicine, University of California, Davis, California, USA
- Department of Animal Science, University of California, Davis, California, USA
| | - Johannes Geibel
- Institute of Farm Animal Genetics, Friedrich-Loeffler-Institut, Neustadt, Germany
- Center for Integrated Breeding Research, University of Göttingen, Göttingen, Germany
| | - Almas A. Gheyas
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Edinburgh, UK
| | - Cyrill John P. Godinez
- Department of Animal Science, College of Agriculture and Food Science, Visayas State University, Baybay City, Philippines
| | | | - Jennifer A.M. Graves
- Department of Environment and Genetics, La Trobe University, Melbourne, Victoria, Australia
- Institute for Applied Ecology, University of Canberra, Canberra, Australian Capital Territory, Australia
| | | | | | - Jian-Lin Han
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia
| | - Olivier Hanotte
- International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia
- Cells, Organisms and Molecular Genetics, School of Life Sciences, University of Nottingham, Nottingham, UK
- Centre for Tropical Livestock Genetics and Health, The Roslin Institute, Edinburgh, UK
| | - Lindsay J. Henderson
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Edinburgh, UK
| | - Zhuo-Cheng Hou
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | | | - Lan Huynh
- Institute for Immunology and Infection Research, University of Edinburgh, Edinburgh, UK
| | - Evans Ilatsia
- Dairy Research Institute, Kenya Agricultural and Livestock Organization, Naivasha, Kenya
| | | | | | - Jim Kaufman
- Institute for Immunology and Infection Research, University of Edinburgh, Edinburgh, UK
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
- Department of Pathology, University of Cambridge, Cambridge, UK
| | - Terra Kelly
- School of Veterinary Medicine, University of California, Davis, California, USA
- Department of Animal Science, University of California, Davis, California, USA
| | - Steve Kemp
- INRAE, INSTITUT AGRO, PEGASE UMR 1348, Saint-Gilles, France
| | - Colin Kern
- Feed the Future Innovation Lab for Genomics to Improve Poultry, University of California, Davis, California, USA
| | | | - Christophe Klopp
- Department of Animal Science, Iowa State University, Ames, Iowa, USA
| | - Sandrine Lagarrigue
- Centre for Tropical Livestock Genetics and Health (CTLGH) − ILRI, Nairobi, Kenya
| | - Susan J. Lamont
- Department of Animal Science, University of California, Davis, California, USA
- INRAE, MIAT UR875, Sigenae, Castanet Tolosan, France
| | - Margaret Lange
- Centre for Tropical Livestock Genetics and Health (CTLGH) − The Roslin Institute, Edinburgh, UK
| | - Anika Lanke
- College of Veterinary Medicine, Western University of Health Sciences, Pomona, California, USA
| | - Denis M. Larkin
- Department of Comparative Biomedical Sciences, Royal Veterinary College, University of London, London, UK
| | - Greger Larson
- The Palaeogenomics and Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, The University of Oxford, Oxford, UK
| | - John King N. Layos
- College of Agriculture and Forestry, Capiz State University, Mambusao, Philippines
| | - Ophélie Lebrasseur
- Centre d'Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Toulouse III Paul Sabatier, Toulouse, France
- Instituto Nacional de Antropología y Pensamiento Latinoamericano, Ciudad Autónoma de Buenos Aires, Argentina
| | - Lyubov P. Malinovskaya
- Department of Cytology and Genetics, Novosibirsk State University, Novosibirsk, Russian Federation
| | - Rebecca J. Martin
- Saint Petersburg State University, Saint Petersburg, Russian Federation
| | | | | | | | - Michael J. McGrew
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Edinburgh, UK
- Department of Molecular Microbiology and Immunology, University of Missouri, Columbia, Missouri, USA
| | | | - Christine Kamidi Muhonja
- Department of Veterinary Pathology, University of Missouri, Columbia, Missouri, USA
- Centre for Tropical Livestock Genetics and Health (CTLGH) − ILRI, Nairobi, Kenya
| | - William Muir
- Department of Animal Sciences, Purdue University, West Lafayette, Indiana, USA
| | - Kévin Muret
- Université Paris-Saclay, Commissariat à l'Energie Atomique et aux Energies Alternatives, Centre National de Recherche en Génomique Humaine, Evry, France
| | - Terence D. Murphy
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA
| | | | - Masahide Nishibori
- Laboratory of Animal Genetics, Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima, Japan
| | | | - Moses Ogugo
- Centre for Tropical Livestock Genetics and Health (CTLGH) − ILRI, Nairobi, Kenya
| | - Ron Okimoto
- Cobb-Vantress, Siloam Springs, Arkansas, USA
| | - Ochieng Ouko
- Department of Veterinary Pathology, University of Missouri, Columbia, Missouri, USA
| | - Hardip R. Patel
- The John Curtin School of Medical Research, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Francesco Perini
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Edinburgh, UK
- Department of Agricultural, Food and Environmental Sciences, University of Perugia, Perugia, Italy
| | - María Ines Pigozzi
- INBIOMED (CONICET-UBA), Facultad de Medicina, Universidad de Buenos Aires, Buenos Aires, Argentina
| | | | - Peter D. Price
- Ecology and Evolutionary Biology, School of Biosciences, University of Sheffield, Sheffield, UK
| | - Christian Reimer
- Institute of Farm Animal Genetics, Friedrich-Loeffler-Institut, Neustadt, Germany
| | - Edward S. Rice
- Department of Animal Sciences, Bond Life Sciences Center, University of Missouri, Columbia, Missouri, USA
| | - Nicolas Rocos
- USDA, ARS, USNPRC, Avian Disease and Oncology Laboratory, East Lansing, Michigan, USA
| | - Thea F. Rogers
- Department of Molecular Evolution and Development, University of Vienna, Vienna, Austria
| | - Perot Saelao
- Department of Animal Science, University of California, Davis, California, USA
- Veterinary Pest Genetics Research Unit, USDA, Kerrville, Texas, USA
| | - Jens Schauer
- Institute of Farm Animal Genetics, Friedrich-Loeffler-Institut, Neustadt, Germany
| | - Robert D. Schnabel
- Department of Animal Sciences, University of Missouri, Columbia, Missouri, USA
| | - Valerie A. Schneider
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA
| | - Henner Simianer
- Center for Integrated Breeding Research, University of Göttingen, Göttingen, Germany
| | - Adrian Smith
- Department of Zoology, University of Oxford, Oxford, UK
| | - Mark P. Stevens
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Edinburgh, UK
| | - Kyle Stiers
- Department of Veterinary Pathology, University of Missouri, Columbia, Missouri, USA
| | | | | | - Anna A. Torgasheva
- Department of Molecular Genetics, Cell Biology and Bioinformatics, Institute of Cytology and Genetics of Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russian Federation
| | - Alan Tracey
- University Paris-Saclay, INRAE, AgroParisTech, GABI, Sigenae, Jouy-en-Josas, France
| | - Clive A. Tregaskes
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
- Saint Petersburg State University, Saint Petersburg, Russian Federation
| | - Lonneke Vervelde
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Edinburgh, UK
| | - Ying Wang
- Department of Animal Science, University of California, Davis, California, USA
| | - Wesley C. Warren
- Department of Animal Sciences, Bond Life Sciences Center, University of Missouri, Columbia, Missouri, USA
- Department of Animal Sciences, University of Missouri, Columbia, Missouri, USA
| | - Paul D. Waters
- School of Biotechnology and Biomolecular Science, Faculty of Science, UNSW Sydney, Sydney, New South Wales, Australia
| | - David Webb
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA
| | - Steffen Weigend
- Institute of Farm Animal Genetics, Friedrich-Loeffler-Institut, Neustadt, Germany
- Center for Integrated Breeding Research, University of Göttingen, Göttingen, Germany
| | - Anna Wolc
- INRAE, MIAT UR875, Sigenae, Castanet Tolosan, France
- Hy-Line International, Research and Development, Dallas Center, Iowa, USA
| | - Alison E. Wright
- Ecology and Evolutionary Biology, School of Biosciences, University of Sheffield, Sheffield, UK
| | - Dominic Wright
- AVIAN Behavioural Genomics and Physiology, IFM Biology, Linköping University, Linköping, Sweden
| | - Zhou Wu
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Edinburgh, UK
| | - Masahito Yamagata
- Center for Brain Science, Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA
| | | | - Zhong-Tao Yin
- Department of Animal Sciences, Data Science and Informatics Institute, University of Missouri, Columbia, Missouri, USA
| | | | - Guojie Zhang
- Center for Evolutionary and Organismal Biology, Zhejiang University School of Medicine, Hangzhou, China
| | - Bingru Zhao
- College of Animal Science and Technology, Nanjing Agricultural University, Nanjing, China
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, California, USA
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10
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Flegontov P, Işıldak U, Maier R, Yüncü E, Changmai P, Reich D. Modeling of African population history using f -statistics can be highly biased and is not addressed by previously suggested SNP ascertainment schemes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.22.525077. [PMID: 36711923 PMCID: PMC9882349 DOI: 10.1101/2023.01.22.525077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
f -statistics have emerged as a first line of analysis for making inferences about demographic history from genome-wide data. These statistics can provide strong evidence for either admixture or cladality, which can be robust to substantial rates of errors or missing data. f -statistics are guaranteed to be unbiased under "SNP ascertainment" (analyzing non-randomly chosen subsets of single nucleotide polymorphisms) only if it relies on a population that is an outgroup for all groups analyzed. However, ascertainment on a true outgroup that is not co-analyzed with other populations is often impractical and uncommon in the literature. In this study focused on practical rather than theoretical aspects of SNP ascertainment, we show that many non-outgroup ascertainment schemes lead to false rejection of true demographic histories, as well as to failure to reject incorrect models. But the bias introduced by common ascertainments such as the 1240K panel is mostly limited to situations when more than one sub-Saharan African and/or archaic human groups (Neanderthals and Denisovans) or non-human outgroups are co-modelled, for example, f 4 -statistics involving one non-African group, two African groups, and one archaic group. Analyzing panels of SNPs polymorphic in archaic humans, which has been suggested as a solution for the ascertainment problem, cannot fix all these problems since for some classes of f -statistics it is not a clean outgroup ascertainment, and in other cases it demonstrates relatively low power to reject incorrect demographic models since it provides a relatively small number of variants common in anatomically modern humans. And due to the paucity of high-coverage archaic genomes, archaic individuals used for ascertainment often act as sole representatives of the respective groups in an analysis, and we show that this approach is highly problematic. By carrying out large numbers of simulations of diverse demographic histories, we find that bias in inferences based on f -statistics introduced by non-outgroup ascertainment can be minimized if the derived allele frequency spectrum in the population used for ascertainment approaches the spectrum that existed at the root of all groups being co-analyzed. Ascertaining on sites with variants common in a diverse group of African individuals provides a good approximation to such a set of SNPs, addressing the great majority of biases and also retaining high statistical power for studying population history. Such a "pan-African" ascertainment, although not completely problem-free, allows unbiased exploration of demographic models for the widest set of archaic and modern human populations, as compared to the other ascertainment schemes we explored.
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Affiliation(s)
- Pavel Flegontov
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
- Kalmyk Research Center of the Russian Academy of Sciences, Elista, Russia
| | - Ulaş Işıldak
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
| | - Robert Maier
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Eren Yüncü
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
| | - Piya Changmai
- Department of Biology and Ecology, Faculty of Science, University of Ostrava, Ostrava, Czechia
| | - David Reich
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
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11
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Kastally C, Niskanen AK, Perry A, Kujala ST, Avia K, Cervantes S, Haapanen M, Kesälahti R, Kumpula TA, Mattila TM, Ojeda DI, Tyrmi JS, Wachowiak W, Cavers S, Kärkkäinen K, Savolainen O, Pyhäjärvi T. Taming the massive genome of Scots pine with PiSy50k, a new genotyping array for conifer research. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2022; 109:1337-1350. [PMID: 34897859 PMCID: PMC9303803 DOI: 10.1111/tpj.15628] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 11/05/2021] [Accepted: 12/02/2021] [Indexed: 06/14/2023]
Abstract
Pinus sylvestris (Scots pine) is the most widespread coniferous tree in the boreal forests of Eurasia, with major economic and ecological importance. However, its large and repetitive genome presents a challenge for conducting genome-wide analyses such as association studies, genetic mapping and genomic selection. We present a new 50K single-nucleotide polymorphism (SNP) genotyping array for Scots pine research, breeding and other applications. To select the SNP set, we first genotyped 480 Scots pine samples on a 407 540 SNP screening array and identified 47 712 high-quality SNPs for the final array (called 'PiSy50k'). Here, we provide details of the design and testing, as well as allele frequency estimates from the discovery panel, functional annotation, tissue-specific expression patterns and expression level information for the SNPs or corresponding genes, when available. We validated the performance of the PiSy50k array using samples from Finland and Scotland. Overall, 39 678 (83.2%) SNPs showed low error rates (mean = 0.9%). Relatedness estimates based on array genotypes were consistent with the expected pedigrees, and the level of Mendelian error was negligible. In addition, array genotypes successfully discriminate between Scots pine populations of Finnish and Scottish origins. The PiSy50k SNP array will be a valuable tool for a wide variety of future genetic studies and forestry applications.
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Affiliation(s)
- Chedly Kastally
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Alina K. Niskanen
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Annika Perry
- UK Centre for Ecology & HydrologyBush EstatePenicuikMidlothianEH26 0QBUK
| | - Sonja T. Kujala
- Natural Resources Institute Finland (Luke)Paavo Havaksen tie 390570OuluFinland
| | - Komlan Avia
- Université de StrasbourgINRAESVQV UMR‐A 1131F‐68000ColmarFrance
| | - Sandra Cervantes
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Matti Haapanen
- Natural Resources Institute Finland (Luke)Latokartanonkaari 9FI‐00790HelsinkiFinland
| | - Robert Kesälahti
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Timo A. Kumpula
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Tiina M. Mattila
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
- Department of Organismal BiologyEBCUppsala UniversityNorbyvägen 18 AUppsala752 36Sweden
| | - Dario I. Ojeda
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
- Norwegian Institute of Bioeconomy ResearchP.O. Box 115Ås1431Norway
| | - Jaakko S. Tyrmi
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Witold Wachowiak
- Institute of Environmental BiologyFaculty of BiologyAdam Mickiewicz University in PoznańUniwersytetu Poznańskiego 661‐614PoznańPoland
| | - Stephen Cavers
- UK Centre for Ecology & HydrologyBush EstatePenicuikMidlothianEH26 0QBUK
| | - Katri Kärkkäinen
- Natural Resources Institute Finland (Luke)Paavo Havaksen tie 390570OuluFinland
| | - Outi Savolainen
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
| | - Tanja Pyhäjärvi
- Department of Ecology and GeneticsUniversity of OuluP.O. Box 300090014OuluFinland
- Department of Forest SciencesUniversity of HelsinkiP.O. Box 2700014HelsinkiFinland
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12
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Deleterious protein-coding variants in diverse cattle breeds of the world. Genet Sel Evol 2021; 53:80. [PMID: 34654372 PMCID: PMC8518297 DOI: 10.1186/s12711-021-00674-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Accepted: 09/22/2021] [Indexed: 11/16/2022] Open
Abstract
The domestication of wild animals has resulted in a reduction in effective population sizes, which can affect the deleterious mutation load of domesticated breeds. In addition, artificial selection contributes to the accumulation of deleterious mutations because of an increased rate of inbreeding among domesticated animals. Since founder population sizes and artificial selection differ between cattle breeds, their deleterious mutation load can vary. We investigated this question by using whole-genome data from 432 animals belonging to 54 worldwide cattle breeds. Our analysis revealed a negative correlation between genomic heterozygosity and nonsynonymous-to-silent diversity ratio, which suggests a higher proportion of single nucleotide variants (SNVs) affecting proteins in low-diversity breeds. Our results also showed that low-diversity breeds had a larger number of high-frequency (derived allele frequency (DAF) > 0.51) deleterious SNVs than high-diversity breeds. An opposite trend was observed for the low-frequency (DAF ≤ 0.51) deleterious SNVs. Overall, the number of high-frequency deleterious SNVs was larger in the genomes of taurine cattle breeds than of indicine breeds, whereas the number of low-frequency deleterious SNVs was larger in the genomes of indicine cattle than in those of taurine cattle. Furthermore, we observed significant variation in the counts of deleterious SNVs within taurine breeds. The variations in deleterious mutation load between taurine and indicine breeds could be attributed to the population sizes of the wild progenitors before domestication, whereas the variations observed within taurine breeds could be due to differences in inbreeding level, strength of artificial selection, and/or founding population size. Our findings imply that the incidence of genetic diseases can vary between cattle breeds.
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13
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Dokan K, Kawamura S, Teshima KM. Effects of single nucleotide polymorphism ascertainment on population structure inferences. G3-GENES GENOMES GENETICS 2021; 11:6237890. [PMID: 33871576 PMCID: PMC8496283 DOI: 10.1093/g3journal/jkab128] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 04/08/2021] [Indexed: 11/14/2022]
Abstract
Single nucleotide polymorphism (SNP) data are widely used in research on natural populations. Although they are useful, SNP genotyping data are known to contain bias, normally referred to as ascertainment bias, because they are conditioned by already confirmed variants. This bias is introduced during the genotyping process, including the selection of populations for novel SNP discovery and the number of individuals involved in the discovery panel and selection of SNP markers. It is widely recognized that ascertainment bias can cause inaccurate inferences in population genetics and several methods to address these bias issues have been proposed. However, especially in natural populations, it is not always possible to apply an ideal ascertainment scheme because natural populations tend to have complex structures and histories. In addition, it was not fully assessed if ascertainment bias has the same effect on different types of population structure. Here, we examine the effects of bias produced during the selection of population for SNP discovery and consequent SNP marker selection processes under three demographic models: the island, stepping-stone, and population split models. Results show that site frequency spectra and summary statistics contain biases that depend on the joint effect of population structure and ascertainment schemes. Additionally, population structure inferences are also affected by ascertainment bias. Based on these results, it is recommended to evaluate the validity of the ascertainment strategy prior to the actual typing process because the direction and extent of ascertainment bias vary depending on several factors.
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Affiliation(s)
- Kotaro Dokan
- Graduate School of System Life Science, Kyushu University, Fukuoka 819-0395, Japan
| | - Sayu Kawamura
- Graduate School of System Life Science, Kyushu University, Fukuoka 819-0395, Japan
| | - Kosuke M Teshima
- Department of Biology, Kyushu University, Fukuoka 819-0395, Japan
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In Search of Species-Specific SNPs in a Non-Model Animal (European Bison ( Bison bonasus))-Comparison of De Novo and Reference-Based Integrated Pipeline of STACKS Using Genotyping-by-Sequencing (GBS) Data. Animals (Basel) 2021; 11:ani11082226. [PMID: 34438684 PMCID: PMC8388393 DOI: 10.3390/ani11082226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 07/07/2021] [Accepted: 07/24/2021] [Indexed: 11/17/2022] Open
Abstract
The European bison is a non-model organism; thus, most of its genetic and genomic analyses have been performed using cattle-specific resources, such as BovineSNP50 BeadChip or Illumina Bovine 800 K HD Bead Chip. The problem with non-specific tools is the potential loss of evolutionary diversified information (ascertainment bias) and species-specific markers. Here, we have used a genotyping-by-sequencing (GBS) approach for genotyping 256 samples from the European bison population in Bialowieza Forest (Poland) and performed an analysis using two integrated pipelines of the STACKS software: one is de novo (without reference genome) and the other is a reference pipeline (with reference genome). Moreover, we used a reference pipeline with two different genomes, i.e., Bos taurus and European bison. Genotyping by sequencing (GBS) is a useful tool for SNP genotyping in non-model organisms due to its cost effectiveness. Our results support GBS with a reference pipeline without PCR duplicates as a powerful approach for studying the population structure and genotyping data of non-model organisms. We found more polymorphic markers in the reference pipeline in comparison to the de novo pipeline. The decreased number of SNPs from the de novo pipeline could be due to the extremely low level of heterozygosity in European bison. It has been confirmed that all the de novo/Bos taurus and Bos taurus reference pipeline obtained SNPs were unique and not included in 800 K BovineHD BeadChip.
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Geibel J, Reimer C, Weigend S, Weigend A, Pook T, Simianer H. How array design creates SNP ascertainment bias. PLoS One 2021; 16:e0245178. [PMID: 33784304 PMCID: PMC8009414 DOI: 10.1371/journal.pone.0245178] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 12/22/2020] [Indexed: 12/30/2022] Open
Abstract
Single nucleotide polymorphisms (SNPs), genotyped with arrays, have become a widely used marker type in population genetic analyses over the last 10 years. However, compared to whole genome re-sequencing data, arrays are known to lack a substantial proportion of globally rare variants and tend to be biased towards variants present in populations involved in the development process of the respective array. This affects population genetic estimators and is known as SNP ascertainment bias. We investigated factors contributing to ascertainment bias in array development by redesigning the Axiom™ Genome-Wide Chicken Array in silico and evaluating changes in allele frequency spectra and heterozygosity estimates in a stepwise manner. A sequential reduction of rare alleles during the development process was shown. This was mainly caused by the identification of SNPs in a limited set of populations and a within-population selection of common SNPs when aiming for equidistant spacing. These effects were shown to be less severe with a larger discovery panel. Additionally, a generally massive overestimation of expected heterozygosity for the ascertained SNP sets was shown. This overestimation was 24% higher for populations involved in the discovery process than not involved populations in case of the original array. The same was observed after the SNP discovery step in the redesign. However, an unequal contribution of populations during the SNP selection can mask this effect but also adds uncertainty. Finally, we make suggestions for the design of specialized arrays for large scale projects where whole genome re-sequencing techniques are still too expensive.
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Affiliation(s)
- Johannes Geibel
- Department of Animal Sciences, Animal Breeding and Genetics Group, University of Goettingen, Göttingen, Germany
- Center for Integrated Breeding Research, University of Goettingen, Göttingen, Germany
- * E-mail:
| | - Christian Reimer
- Department of Animal Sciences, Animal Breeding and Genetics Group, University of Goettingen, Göttingen, Germany
- Center for Integrated Breeding Research, University of Goettingen, Göttingen, Germany
| | - Steffen Weigend
- Center for Integrated Breeding Research, University of Goettingen, Göttingen, Germany
- Institute of Farm Animal Genetics, Friedrich-Loeffler-Institut, Neustadt-Mariensee, Germany
| | - Annett Weigend
- Institute of Farm Animal Genetics, Friedrich-Loeffler-Institut, Neustadt-Mariensee, Germany
| | - Torsten Pook
- Department of Animal Sciences, Animal Breeding and Genetics Group, University of Goettingen, Göttingen, Germany
- Center for Integrated Breeding Research, University of Goettingen, Göttingen, Germany
| | - Henner Simianer
- Department of Animal Sciences, Animal Breeding and Genetics Group, University of Goettingen, Göttingen, Germany
- Center for Integrated Breeding Research, University of Goettingen, Göttingen, Germany
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Fola AA, Kattenberg E, Razook Z, Lautu-Gumal D, Lee S, Mehra S, Bahlo M, Kazura J, Robinson LJ, Laman M, Mueller I, Barry AE. SNP barcodes provide higher resolution than microsatellite markers to measure Plasmodium vivax population genetics. Malar J 2020; 19:375. [PMID: 33081815 PMCID: PMC7576724 DOI: 10.1186/s12936-020-03440-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Accepted: 10/03/2020] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Genomic surveillance of malaria parasite populations has the potential to inform control strategies and to monitor the impact of interventions. Barcodes comprising large numbers of single nucleotide polymorphism (SNP) markers are accurate and efficient genotyping tools, however may need to be tailored to specific malaria transmission settings, since 'universal' barcodes can lack resolution at the local scale. A SNP barcode was developed that captures the diversity and structure of Plasmodium vivax populations of Papua New Guinea (PNG) for research and surveillance. METHODS Using 20 high-quality P. vivax genome sequences from PNG, a total of 178 evenly spaced neutral SNPs were selected for development of an amplicon sequencing assay combining a series of multiplex PCRs and sequencing on the Illumina MiSeq platform. For initial testing, 20 SNPs were amplified in a small number of mono- and polyclonal P. vivax infections. The full barcode was then validated by genotyping and population genetic analyses of 94 P. vivax isolates collected between 2012 and 2014 from four distinct catchment areas on the highly endemic north coast of PNG. Diversity and population structure determined from the SNP barcode data was then benchmarked against that of ten microsatellite markers used in previous population genetics studies. RESULTS From a total of 28,934,460 reads generated from the MiSeq Illumina run, 87% mapped to the PvSalI reference genome with deep coverage (median = 563, range 56-7586) per locus across genotyped samples. Of 178 SNPs assayed, 146 produced high-quality genotypes (minimum coverage = 56X) in more than 85% of P. vivax isolates. No amplification bias was introduced due to either polyclonal infection or whole genome amplification (WGA) of samples before genotyping. Compared to the microsatellite panels, the SNP barcode revealed greater variability in genetic diversity between populations and geographical population structure. The SNP barcode also enabled assignment of genotypes according to their geographic origins with a significant association between genetic distance and geographic distance at the sub-provincial level. CONCLUSIONS High-throughput SNP barcoding can be used to map variation of malaria transmission dynamics at sub-national resolution. The low cost per sample and genotyping strategy makes the transfer of this technology to field settings highly feasible.
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Affiliation(s)
- Abebe A Fola
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, USA
| | - Eline Kattenberg
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Vector Borne Diseases Unit, Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
- Malariology Unit, Institute of Tropical Medicine, Antwerp, Belgium
| | - Zahra Razook
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- IMPACT Institute for Innovation in Mental and Physical Health and Clinical Translation, Deakin University, 75 Pigdons Road, Waurn Ponds, Geelong, VIC, 3216, Australia
| | - Dulcie Lautu-Gumal
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
- Vector Borne Diseases Unit, Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
- Disease Elimination Program, Burnet Institute, Melbourne, VIC, Australia
- IMPACT Institute for Innovation in Mental and Physical Health and Clinical Translation, Deakin University, 75 Pigdons Road, Waurn Ponds, Geelong, VIC, 3216, Australia
| | - Stuart Lee
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
| | - Somya Mehra
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Disease Elimination Program, Burnet Institute, Melbourne, VIC, Australia
- IMPACT Institute for Innovation in Mental and Physical Health and Clinical Translation, Deakin University, 75 Pigdons Road, Waurn Ponds, Geelong, VIC, 3216, Australia
| | - Melanie Bahlo
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
| | - James Kazura
- Disease Elimination Program, Burnet Institute, Melbourne, VIC, Australia
- Centre for Global Health and Diseases, Case Western Reserve University, Cleveland, Ohio, USA
| | - Leanne J Robinson
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
- Vector Borne Diseases Unit, Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
- Disease Elimination Program, Burnet Institute, Melbourne, VIC, Australia
| | - Moses Laman
- Vector Borne Diseases Unit, Papua New Guinea Institute of Medical Research, Madang, Papua New Guinea
| | - Ivo Mueller
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia
- Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France
| | - Alyssa E Barry
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, VIC, Australia.
- Department of Medical Biology, The University of Melbourne, Melbourne, VIC, Australia.
- Disease Elimination Program, Burnet Institute, Melbourne, VIC, Australia.
- IMPACT Institute for Innovation in Mental and Physical Health and Clinical Translation, Deakin University, 75 Pigdons Road, Waurn Ponds, Geelong, VIC, 3216, Australia.
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Giordano R, Donthu RK, Zimin AV, Julca Chavez IC, Gabaldon T, van Munster M, Hon L, Hall R, Badger JH, Nguyen M, Flores A, Potter B, Giray T, Soto-Adames FN, Weber E, Marcelino JAP, Fields CJ, Voegtlin DJ, Hill CB, Hartman GL. Soybean aphid biotype 1 genome: Insights into the invasive biology and adaptive evolution of a major agricultural pest. INSECT BIOCHEMISTRY AND MOLECULAR BIOLOGY 2020; 120:103334. [PMID: 32109587 DOI: 10.1016/j.ibmb.2020.103334] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 01/07/2020] [Accepted: 02/10/2020] [Indexed: 05/12/2023]
Abstract
The soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae) is a serious pest of the soybean plant, Glycine max, a major world-wide agricultural crop. We assembled a de novo genome sequence of Ap. glycines Biotype 1, from a culture established shortly after this species invaded North America. 20.4% of the Ap. glycines proteome is duplicated. These in-paralogs are enriched with Gene Ontology (GO) categories mostly related to apoptosis, a possible adaptation to plant chemistry and other environmental stressors. Approximately one-third of these genes show parallel duplication in other aphids. But Ap. gossypii, its closest related species, has the lowest number of these duplicated genes. An Illumina GoldenGate assay of 2380 SNPs was used to determine the world-wide population structure of Ap. Glycines. China and South Korean aphids are the closest to those in North America. China is the likely origin of other Asian aphid populations. The most distantly related aphids to those in North America are from Australia. The diversity of Ap. glycines in North America has decreased over time since its arrival. The genetic diversity of Ap. glycines North American population sampled shortly after its first detection in 2001 up to 2012 does not appear to correlate with geography. However, aphids collected on soybean Rag experimental varieties in Minnesota (MN), Iowa (IA), and Wisconsin (WI), closer to high density Rhamnus cathartica stands, appear to have higher capacity to colonize resistant soybean plants than aphids sampled in Ohio (OH), North Dakota (ND), and South Dakota (SD). Samples from the former states have SNP alleles with high FST values and frequencies, that overlap with genes involved in iron metabolism, a crucial metabolic pathway that may be affected by the Rag-associated soybean plant response. The Ap. glycines Biotype 1 genome will provide needed information for future analyses of mechanisms of aphid virulence and pesticide resistance as well as facilitate comparative analyses between aphids with differing natural history and host plant range.
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Affiliation(s)
- Rosanna Giordano
- Puerto Rico Science, Technology and Research Trust, San Juan, PR, USA; Know Your Bee, Inc. San Juan, PR, USA.
| | - Ravi Kiran Donthu
- Puerto Rico Science, Technology and Research Trust, San Juan, PR, USA; Know Your Bee, Inc. San Juan, PR, USA.
| | - Aleksey V Zimin
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Irene Consuelo Julca Chavez
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain; Barcelona Supercomputing Centre (BSC-CNS), Barcelona, Spain; Institute for Research in Biomedicine, Barcelona, Spain
| | - Toni Gabaldon
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain; Barcelona Supercomputing Centre (BSC-CNS), Barcelona, Spain; Institute for Research in Biomedicine, Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Manuella van Munster
- CIRAD-INRA-Montpellier SupAgro, TA A54/K, Campus International de Baillarguet, Montpellier, France
| | | | | | - Jonathan H Badger
- Cancer and Inflammation Program, Center for Cancer Research, National Cancer Institute, National Institute of Health, DHHS, Bethesda, MD, USA
| | - Minh Nguyen
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Alejandra Flores
- College of Liberal Arts and Sciences, School of Molecular and Cellular Biology, University of Illinois, Urbana, IL, USA
| | - Bruce Potter
- University of Minnesota, Southwest Research and Outreach Center, Lamberton, MN, USA
| | - Tugrul Giray
- Department of Biology, University of Puerto Rico, San Juan, PR, USA
| | - Felipe N Soto-Adames
- Florida Department of Agriculture and Consumer Services, Division of Plant Industry, Entomology, Gainesville, FL, USA
| | | | - Jose A P Marcelino
- Puerto Rico Science, Technology and Research Trust, San Juan, PR, USA; Know Your Bee, Inc. San Juan, PR, USA; Department of Entomology and Nematology, University of Florida, Gainesville, FL, USA
| | - Christopher J Fields
- HPCBio, Roy J. Carver Biotechnology Center, University of Illinois, Urbana, IL, USA
| | - David J Voegtlin
- Illinois Natural History Survey, University of Illinois, Urbana, IL, USA
| | | | - Glen L Hartman
- USDA-ARS and Department of Crop Sciences, University of Illinois, Urbana, IL, USA
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18
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Smaragdov MG, Kudinov AA. Assessing the power of principal components and wright's fixation index analyzes applied to reveal the genome-wide genetic differences between herds of Holstein cows. BMC Genet 2020; 21:47. [PMID: 32345235 PMCID: PMC7189535 DOI: 10.1186/s12863-020-00848-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Accepted: 03/27/2020] [Indexed: 11/30/2022] Open
Abstract
Background Due to the advent of SNP array technology, a genome-wide analysis of genetic differences between populations and breeds has become possible at a previously unattainable level. The Wright’s fixation index (Fst) and the principal component analysis (PCA) are widely used methods in animal genetics studies. In paper we compared the power of these methods, their complementing each other and which of them is the most powerful. Results Comparative analysis of the power Principal Components Analysis (PCA) and Fst were carried out to reveal genetic differences between herds of Holsteinized cows. Totally, 803 BovineSNP50 genotypes of cows from 13 herds were used in current study. Obtained Fst values were in the range of 0.002–0.012 (mean 0.0049) while for rare SNPs with MAF 0.0001–0.005 they were even smaller in the range of 0.001–0.01 (mean 0.0027). Genetic relatedness of the cows in the herds was the cause of such small Fst values. The contribution of rare alleles with MAF 0.0001–0.01 to the Fst values was much less than common alleles and this effect depends on linkage disequilibrium (LD). Despite of substantial change in the MAF spectrum and the number of SNPs we observed small effect size of LD - based pruning on Fst data. PCA analysis confirmed the mutual admixture and small genetic difference between herds. Moreover, PCA analysis of the herds based on the visualization the results of a single eigenvector cannot be used to significantly differentiate herds. Only summed eigenvectors should be used to realize full power of PCA to differentiate small between herds genetic difference. Finally, we presented evidences that the significance of Fst data far exceeds the significance of PCA data when these methods are used to reveal genetic differences between herds. Conclusions LD - based pruning had a small effect on findings of Fst and PCA analyzes. Therefore, for weakly structured populations the LD - based pruning is not effective. In addition, our results show that the significance of genetic differences between herds obtained by Fst analysis exceeds the values of PCA. Proposed, to differentiate herds or low structured populations we recommend primarily using the Fst approach and only then PCA.
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Affiliation(s)
- M G Smaragdov
- Russian Research Institute of Farm Animal Genetics and Breeding - Branch of the l.K. Ernst Federal Science Center for Animal Husbandry, St. Petersburg, Pushkin, Russia. .,, St. Petersburg, Russian Federation.
| | - A A Kudinov
- Russian Research Institute of Farm Animal Genetics and Breeding - Branch of the l.K. Ernst Federal Science Center for Animal Husbandry, St. Petersburg, Pushkin, Russia.,Department of Agricultural Science, University of Helsinki, FI-00014, Helsinki, Finland
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19
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Barbato M, Reichel MP, Passamonti M, Low WY, Colli L, Tearle R, Williams JL, Ajmone Marsan P. A genetically unique Chinese cattle population shows evidence of common ancestry with wild species when analysed with a reduced ascertainment bias SNP panel. PLoS One 2020; 15:e0231162. [PMID: 32271816 PMCID: PMC7145104 DOI: 10.1371/journal.pone.0231162] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Accepted: 03/17/2020] [Indexed: 02/07/2023] Open
Abstract
In Hong Kong, there is a cattle population of ~1,200 individuals of uncertain origin and genetic diversity. This population shows heterogeneous morphology, both in body type and pigmentation. Once used as draught animals by the local farmers, they were abandoned around the 1970s due to changes in the economy, and since then have lived as feral populations. To explore the origins of these cattle, we analysed ~50k genotype data of 21 Hong Kong feral cattle, along with data from 703 individuals of 36 cattle populations of European, African taurine, and Asian origin, the wild x domestic hybrid gayal, plus two wild bovine species, gaur and banteng. To reduce the effect of ascertainment bias ~4k loci that are polymorphic in the two wild species were selected for further analysis. The stringent SNP selection we applied resulted in increased heterozygosity across all populations studies, compared with the full panel of SNP, thus reducing the impact of ascertainment bias and facilitating the comparison of divergent breeds of cattle. Our results showed that Hong Kong feral cattle have relatively high levels of genetic distinctiveness, possibly due to the low level of artificial selection, and a likely common ancestry with wild species. We found signs of a putative taurine introgression, probably dating to the import of north European breeds during the British colonialism of Hong Kong. We showed that Hong Kong feral cattle, are distinct from Bos taurus and Bos indicus breeds. Our results highlight the distinctiveness of Hong Kong feral cattle and stress the conservation value of this indigenous breed that is likely to harbour adaptive genetic variation, which is a fundamental livestock resource in the face of climate change and diversifying market demands.
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Affiliation(s)
- Mario Barbato
- Department of Animal Science, Food and Technology–DIANA, and Nutrigenomics and Proteomics Research Center–PRONUTRIGEN, Università Cattolica del Sacro Cuore, Piacenza, Italy
- * E-mail: (MB); (PAM)
| | - Michael P. Reichel
- Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong
| | - Matilde Passamonti
- Department of Animal Science, Food and Technology–DIANA, and Nutrigenomics and Proteomics Research Center–PRONUTRIGEN, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Wai Yee Low
- School of Animal and Veterinary Sciences, Davies Research Centre, University of Adelaide, Roseworthy, Australia
| | - Licia Colli
- Department of Animal Science, Food and Technology–DIANA, and Nutrigenomics and Proteomics Research Center–PRONUTRIGEN, Università Cattolica del Sacro Cuore, Piacenza, Italy
- Research Center on Biodiversity and Ancient DNA–BioDNA, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Rick Tearle
- School of Animal and Veterinary Sciences, Davies Research Centre, University of Adelaide, Roseworthy, Australia
| | - John L. Williams
- School of Animal and Veterinary Sciences, Davies Research Centre, University of Adelaide, Roseworthy, Australia
| | - Paolo Ajmone Marsan
- Department of Animal Science, Food and Technology–DIANA, and Nutrigenomics and Proteomics Research Center–PRONUTRIGEN, Università Cattolica del Sacro Cuore, Piacenza, Italy
- Research Center on Biodiversity and Ancient DNA–BioDNA, Università Cattolica del Sacro Cuore, Piacenza, Italy
- * E-mail: (MB); (PAM)
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20
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Barbato M, Hailer F, Upadhyay M, Del Corvo M, Colli L, Negrini R, Kim ES, Crooijmans RPMA, Sonstegard T, Ajmone-Marsan P. Adaptive introgression from indicine cattle into white cattle breeds from Central Italy. Sci Rep 2020; 10:1279. [PMID: 31992729 PMCID: PMC6987186 DOI: 10.1038/s41598-020-57880-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 12/26/2019] [Indexed: 11/19/2022] Open
Abstract
Cattle domestication occurred at least twice independently and gave rise to the modern taurine and indicine cattle breeds. European cattle diversity is generally dominated by taurine cattle, although elevated levels of indicine ancestry have been recorded in several breeds from southern Europe. Here we use genome-wide high-density SNP genotyping data to investigate the taurine and indicine ancestry in southern European cattle, based on a dataset comprising 508 individuals from 23 cattle breeds of taurine, indicine and mixed ancestry, including three breeds from Central Italy known to exhibit the highest levels of indicine introgression among southern European breeds. Based on local genomic ancestry analyses, we reconstruct taurine and indicine ancestry genome-wide and along chromosomes. We scrutinise local genomic introgression signals and identify genomic regions that have introgressed from indicine into taurine cattle under positive selection, harbouring genes with functions related to body size and feed efficiency. These findings suggest that indicine-derived traits helped enhance Central Italian cattle through adaptive introgression. The identified genes could provide genomic targets for selection for improved cattle performance. Our findings elucidate the key role of adaptive introgression in shaping the phenotypic features of modern cattle, aided by cultural and livestock exchange among historic human societies.
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Affiliation(s)
- Mario Barbato
- Università Cattolica del Sacro Cuore, Department of Animal Science Food and Nutrition - DIANA, Nutrigenomics and Proteomics Research Centre - PRONUTRIGEN, and Biodiversity and Ancient DNA Research Centre, Università Cattolica del Sacro Cuore, Piacenza, Italy.
| | - Frank Hailer
- School of Biosciences, Cardiff University, Cardiff, Wales, UK
| | - Maulik Upadhyay
- Animal Breeding and Genomics, Wageningen University & Research, Wageningen, The Netherlands.,Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Marcello Del Corvo
- Università Cattolica del Sacro Cuore, Department of Animal Science Food and Nutrition - DIANA, Nutrigenomics and Proteomics Research Centre - PRONUTRIGEN, and Biodiversity and Ancient DNA Research Centre, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Licia Colli
- Università Cattolica del Sacro Cuore, Department of Animal Science Food and Nutrition - DIANA, Nutrigenomics and Proteomics Research Centre - PRONUTRIGEN, and Biodiversity and Ancient DNA Research Centre, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Riccardo Negrini
- Università Cattolica del Sacro Cuore, Department of Animal Science Food and Nutrition - DIANA, Nutrigenomics and Proteomics Research Centre - PRONUTRIGEN, and Biodiversity and Ancient DNA Research Centre, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | | | | | | | - Paolo Ajmone-Marsan
- Università Cattolica del Sacro Cuore, Department of Animal Science Food and Nutrition - DIANA, Nutrigenomics and Proteomics Research Centre - PRONUTRIGEN, and Biodiversity and Ancient DNA Research Centre, Università Cattolica del Sacro Cuore, Piacenza, Italy.
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21
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Rincon-Sandoval M, Betancur-R R, Maldonado-Ocampo JA. Comparative phylogeography of trans-Andean freshwater fishes based on genome-wide nuclear and mitochondrial markers. Mol Ecol 2019; 28:1096-1115. [PMID: 30714250 DOI: 10.1111/mec.15036] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 01/17/2019] [Accepted: 01/23/2019] [Indexed: 01/06/2023]
Abstract
The Neotropical region represents one of the greatest biodiversity hot spots on earth. Despite its unparalleled biodiversity, regional comparative phylogeographic studies are still scarce, with most focusing on model clades (e.g. birds) and typically examining a handful of loci. Here, we apply a genome-wide comparative phylogeographic approach to test hypotheses of codiversification of freshwater fishes in the trans-Andean region. Using target capture methods, we examined exon data for over 1,000 loci combined with complete mitochondrial genomes to study the phylogeographic history of five primary fish species (>150 individuals) collected from eight major river basins in Northwestern South America and Lower Central America. To assess their patterns of genetic structure, we inferred genealogical concordance taking into account all major aspects of phylogeography (within loci, across multiple genes, across species and among biogeographic provinces). Based on phylogeographic concordance factors, we tested four a priori biogeographic hypotheses, finding support for three of them and uncovering a novel, unexpected pattern of codiversification. The four emerging inter-riverine patterns are as follows: (a) Tuira + Atrato, (b) Ranchería + Catatumbo, (c) Magdalena system and (d) Sinú + Atrato. These patterns are interpreted as shared responses to the complex uplifting and orogenic processes that modified or sundered watersheds, allowing codiversification and speciation over geological time. We also find evidence of cryptic speciation in one of the species examined and instances of mitochondrial introgression in others. These results help further our knowledge of the historical geographic factors shaping the outstanding biodiversity of the Neotropics.
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Affiliation(s)
- Melissa Rincon-Sandoval
- Laboratorio de Ictiología, Unidad de Ecología y Sistemática (UNESIS), Departamento de Biología, Facultad de Ciencias, Pontificia Universidad Javeriana, Bogotá, Colombia.,Department of Biology, University of Puerto Rico, San Juan, Puerto Rico
| | - Ricardo Betancur-R
- Department of Biology, University of Puerto Rico, San Juan, Puerto Rico.,Department of Biology, The University of Oklahoma, Norman, Oklahoma
| | - Javier A Maldonado-Ocampo
- Laboratorio de Ictiología, Unidad de Ecología y Sistemática (UNESIS), Departamento de Biología, Facultad de Ciencias, Pontificia Universidad Javeriana, Bogotá, Colombia
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22
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Fitak RR, Rinkevich SE, Culver M. Genome-Wide Analysis of SNPs Is Consistent with No Domestic Dog Ancestry in the Endangered Mexican Wolf (Canis lupus baileyi). J Hered 2019; 109:372-383. [PMID: 29757430 DOI: 10.1093/jhered/esy009] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Accepted: 02/28/2018] [Indexed: 11/13/2022] Open
Abstract
The Mexican gray wolf (Canis lupus baileyi) was historically distributed throughout the southwestern United States and northern Mexico. Extensive predator removal campaigns during the early 20th century, however, resulted in its eventual extirpation by the mid 1980s. At this time, the Mexican wolf existed only in 3 separate captive lineages (McBride, Ghost Ranch, and Aragón) descended from 3, 2, and 2 founders, respectively. These lineages were merged in 1995 to increase the available genetic variation, and Mexican wolves were reintroduced into Arizona and New Mexico in 1998. Despite the ongoing management of the Mexican wolf population, it has been suggested that a proportion of the Mexican wolf ancestry may be recently derived from hybridization with domestic dogs. In this study, we genotyped 87 Mexican wolves, including individuals from all 3 captive lineages and cross-lineage wolves, for more than 172000 single nucleotide polymorphisms. We identified levels of genetic variation consistent with the pedigree record and effects of genetic rescue. To identify the potential to detect hybridization with domestic dogs, we compared our Mexican wolf genotypes with those from studies of domestic dogs and other gray wolves. The proportion of Mexican wolf ancestry assigned to domestic dogs was only between 0.06% (SD 0.23%) and 7.8% (SD 1.0%) for global and local ancestry estimates, respectively; and was consistent with simulated levels of incomplete lineage sorting. Overall, our results suggested that Mexican wolves lack biologically significant ancestry with dogs and have useful implications for the conservation and management of this endangered wolf subspecies.
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Affiliation(s)
| | | | - Melanie Culver
- US Geological Survey Arizona Cooperative Fish and Wildlife Research Unit, School of Natural Resources and the Environment, University of Arizona, Tucson, AZ
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23
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Miller JM, Quinzin MC, Edwards DL, Eaton DAR, Jensen EL, Russello MA, Gibbs JP, Tapia W, Rueda D, Caccone A. Genome-Wide Assessment of Diversity and Divergence Among Extant Galapagos Giant Tortoise Species. J Hered 2019; 109:611-619. [PMID: 29986032 DOI: 10.1093/jhered/esy031] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2018] [Accepted: 07/04/2018] [Indexed: 12/19/2022] Open
Abstract
Genome-wide assessments allow for fuller characterization of genetic diversity, finer-scale population delineation, and better detection of demographically significant units to guide conservation compared with those based on "traditional" markers. Galapagos giant tortoises (Chelonoidis spp.) have long provided a case study for how evolutionary genetics may be applied to advance species conservation. Ongoing efforts to bolster tortoise populations, which have declined by 90%, have been informed by analyses of mitochondrial DNA sequence and microsatellite genotypic data, but could benefit from genome-wide markers. Taking this next step, we used double-digest restriction-site associated DNA sequencing to collect genotypic data at >26000 single nucleotide polymorphisms (SNPs) for 117 individuals representing all recognized extant Galapagos giant tortoise species. We then quantified genetic diversity, population structure, and compared results to estimates from mitochondrial DNA and microsatellite loci. Our analyses detected 12 genetic lineages concordant with the 11 named species as well as previously described structure within one species, C. becki. Furthermore, the SNPs provided increased resolution, detecting admixture in 4 individuals. SNP-based estimates of diversity and differentiation were significantly correlated with those derived from nuclear microsatellite loci and mitochondrial DNA sequences. The SNP toolkit presented here will serve as a resource for advancing efforts to understand tortoise evolution, species radiations, and aid conservation of the Galapagos tortoise species complex.
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Affiliation(s)
- Joshua M Miller
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT
| | - Maud C Quinzin
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT
| | - Danielle L Edwards
- Life and Environmental Sciences, University of California, Merced, Merced, CA
| | - Deren A R Eaton
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT.,Department of Ecology, Evolution, and Environmental Biology, Columbia University, New York, NY
| | - Evelyn L Jensen
- Department of Biology, University of British Columbia, Okanagan Campus, Kelowna, BC, Canada
| | - Michael A Russello
- Department of Biology, University of British Columbia, Okanagan Campus, Kelowna, BC, Canada
| | - James P Gibbs
- College of Environmental Science & Forestry, State University of New York, Syracuse, NY
| | - Washington Tapia
- Galapagos Conservancy, Fairfax, VA.,Galápagos National Park Directorate, Puerto Ayora, Galápagos, Ecuador
| | - Danny Rueda
- Galápagos National Park Directorate, Puerto Ayora, Galápagos, Ecuador
| | - Adalgisa Caccone
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT
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24
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Utsunomiya YT, Milanesi M, Fortes MRS, Porto-Neto LR, Utsunomiya ATH, Silva MVGB, Garcia JF, Ajmone-Marsan P. Genomic clues of the evolutionary history of Bos indicus cattle. Anim Genet 2019; 50:557-568. [PMID: 31475748 DOI: 10.1111/age.12836] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/19/2019] [Indexed: 01/08/2023]
Abstract
Together with their sister subspecies Bos taurus, zebu cattle (Bos indicus) have contributed to important socioeconomic changes that have shaped modern civilizations. Zebu cattle were domesticated in the Indus Valley 8000 years before present (YBP). From the domestication site, they expanded to Africa, East Asia, southwestern Asia and Europe between 4000 and 1300 YBP, intercrossing with B. taurus to form clinal variations of zebu ancestry across the landmass of Afro-Eurasia. In the past 150 years, zebu cattle reached the Americas and Oceania, where they have contributed to the prosperity of emerging economies. The zebu genome is characterized by two mitochondrial haplogroups (I1 and I2), one Y chromosome haplogroup (Y3) and three major autosomal ancestral groups (Indian-Pakistani, African and Chinese). Phenotypically, zebu animals are recognized by their hump, large ears and excess skin. They are rustic, resilient to parasites and capable of bearing the hot and humid climates of the tropics. Many resources are available to study the zebu genome, including commercial arrays of SNP, reference assemblies and publicly available genotypes and whole-genome sequences. Nevertheless, many of these resources were initially developed to support research and subsidize industrial applications in B. taurus, and therefore they can produce bias in data analysis. The combination of genomics with precision agriculture holds great promise for the identification of genetic variants affecting economically important traits such as tick resistance and heat tolerance, which were naturally selected for millennia and played a major role in the evolution of B. indicus cattle.
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Affiliation(s)
- Y T Utsunomiya
- Department of Support, Production and Animal Health, School of Veterinary Medicine, São Paulo State University (Unesp), 16050-680 R. Clovis Pestana 793-Dona Amelia, Araçatuba, SP, Brazil.,International Atomic Energy Agency, Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 R. Clovis Pestana 793-Dona Amelia, Araçatuba, SP, Brazil
| | - M Milanesi
- Department of Support, Production and Animal Health, School of Veterinary Medicine, São Paulo State University (Unesp), 16050-680 R. Clovis Pestana 793-Dona Amelia, Araçatuba, SP, Brazil.,International Atomic Energy Agency, Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 R. Clovis Pestana 793-Dona Amelia, Araçatuba, SP, Brazil
| | - M R S Fortes
- School of Chemistry and Molecular Biosciences, The University of Queensland, Chemistry Bld, 68 Cooper Rd, Brisbane, 4072, Qld, Australia
| | - L R Porto-Neto
- CSIRO Agriculture and Food, Queensland Bioscience Precinct, 306 Carmody Rd, St Lucia QLD, Brisbane, 4067, Qld, Australia
| | - A T H Utsunomiya
- Department of Support, Production and Animal Health, School of Veterinary Medicine, São Paulo State University (Unesp), 16050-680 R. Clovis Pestana 793-Dona Amelia, Araçatuba, SP, Brazil.,International Atomic Energy Agency, Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 R. Clovis Pestana 793-Dona Amelia, Araçatuba, SP, Brazil
| | - M V G B Silva
- Empresa Brasileira de Pesquisa Agropecuária, Embrapa Gado de Leite, Juiz de Fora, MG, 360381330, Brazil
| | - J F Garcia
- Department of Support, Production and Animal Health, School of Veterinary Medicine, São Paulo State University (Unesp), 16050-680 R. Clovis Pestana 793-Dona Amelia, Araçatuba, SP, Brazil.,International Atomic Energy Agency, Collaborating Centre on Animal Genomics and Bioinformatics, 16050-680 R. Clovis Pestana 793-Dona Amelia, Araçatuba, SP, Brazil.,Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University (Unesp), 14884-900 Via de Acesso Prof. Paulo Donato Castellane s/n, Jaboticabal, SP, Brazil
| | - P Ajmone-Marsan
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti-DIANA and BioDNA, Centro di Ricerca sulla Biodiversità e sul DNA Antico, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84, Piacenza, 29122, Italy
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25
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Zwane AA, Schnabel RD, Hoff J, Choudhury A, Makgahlela ML, Maiwashe A, Van Marle-Koster E, Taylor JF. Genome-Wide SNP Discovery in Indigenous Cattle Breeds of South Africa. Front Genet 2019; 10:273. [PMID: 30988672 PMCID: PMC6452414 DOI: 10.3389/fgene.2019.00273] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Accepted: 03/12/2019] [Indexed: 01/30/2023] Open
Abstract
Single nucleotide polymorphism arrays have created new possibilities for performing genome-wide studies to detect genomic regions harboring sequence variants that affect complex traits. However, the majority of validated SNPs for which allele frequencies have been estimated are limited primarily to European breeds. The objective of this study was to perform SNP discovery in three South African indigenous breeds (Afrikaner, Drakensberger, and Nguni) using whole genome sequencing. DNA was extracted from blood and hair samples, quantified and prepared at 50 ng/μl concentration for sequencing at the Agricultural Research Council Biotechnology Platform using an Illumina HiSeq 2500. The fastq files were used to call the variants using the Genome Analysis Tool Kit. A total of 1,678,360 were identified as novel using Run 6 of 1000 Bull Genomes Project. Annotation of the identified variants classified them into functional categories. Within the coding regions, about 30% of the SNPs were non-synonymous substitutions that encode for alternate amino acids. The study of distribution of SNP across the genome identified regions showing notable differences in the densities of SNPs among the breeds and highlighted many regions of functional significance. Gene ontology terms identified genes such as MLANA, SYT10, and CDC42EP5 that have been associated with coat color in mouse, and ADAMS3, DNAJC3, and PAG5 genes have been associated with fertility in cattle. Further analysis of the variants detected 688 candidate selective sweeps (ZHp Z-scores ≤ -4) across all three breeds, of which 223 regions were assigned as being putative selective sweeps (ZHp scores ≤-5). We also identified 96 regions with extremely low ZHp Z-scores (≤-6) in Afrikaner and Nguni. Genes such as KIT and MITF that have been associated with skin pigmentation in cattle and CACNA1C, which has been associated with biopolar disorder in human, were identified in these regions. This study provides the first analysis of sequence data to discover SNPs in indigenous South African cattle breeds. The information will play an important role in our efforts to understand the genetic history of our cattle and in designing appropriate breed improvement programmes.
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Affiliation(s)
- Avhashoni A. Zwane
- Department of Animal Breeding and Genetics, Agricultural Research Council-Animal Production, Irene, South Africa
- Department of Animal and Wildlife Sciences, University of Pretoria, Pretoria, South Africa
| | - Robert D. Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
- Informatics Institute, University of Missouri, Columbia, MO, United States
| | - Jesse Hoff
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
| | - Ananyo Choudhury
- Sydney Brenner Institute of Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa
| | - Mahlako Linah Makgahlela
- Department of Animal Breeding and Genetics, Agricultural Research Council-Animal Production, Irene, South Africa
- Department of Animal, Wildlife and Grassland Sciences, University of the Free State, Bloemfontein, South Africa
| | - Azwihangwisi Maiwashe
- Department of Animal Breeding and Genetics, Agricultural Research Council-Animal Production, Irene, South Africa
- Department of Animal, Wildlife and Grassland Sciences, University of the Free State, Bloemfontein, South Africa
| | - Este Van Marle-Koster
- Department of Animal and Wildlife Sciences, University of Pretoria, Pretoria, South Africa
| | - Jeremy F. Taylor
- Division of Animal Sciences, University of Missouri, Columbia, MO, United States
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26
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Theodoridis S, Randin C, Szövényi P, Boucher FC, Patsiou TS, Conti E. How Do Cold-Adapted Plants Respond to Climatic Cycles? Interglacial Expansion Explains Current Distribution and Genomic Diversity in Primula farinosa L. Syst Biol 2018; 66:715-736. [PMID: 28334079 DOI: 10.1093/sysbio/syw114] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2016] [Accepted: 12/14/2016] [Indexed: 12/16/2022] Open
Abstract
Understanding the effects of past climatic fluctuations on the distribution and population-size dynamics of cold-adapted species is essential for predicting their responses to ongoing global climate change. In spite of the heterogeneity of cold-adapted species, two main contrasting hypotheses have been proposed to explain their responses to Late Quaternary glacial cycles, namely, the interglacial contraction versus the interglacial expansion hypotheses. Here, we use the cold-adapted plant Primula farinosa to test two demographic models under each of the two alternative hypotheses and a fifth, null model. We first approximate the time and extent of demographic contractions and expansions during the Late Quaternary by projecting species distribution models across the last 72 ka. We also generate genome-wide sequence data using a Reduced Representation Library approach to reconstruct the spatial structure, genetic diversity, and phylogenetic relationships of lineages within P. farinosa. Finally, by integrating the results of climatic and genomic analyses in an Approximate Bayesian Computation framework, we propose the most likely model for the extent and direction of population-size changes in $P$. farinosa through the Late Quaternary. Our results support the interglacial expansion of $P$. farinosa, differing from the prevailing paradigm that the observed distribution of cold-adapted species currently fragmented in high altitude and latitude regions reflects the consequences of postglacial contraction processes.
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Affiliation(s)
- Spyros Theodoridis
- Department of Systematic and Evolutionary Botany, University of Zurich, CH-8008 Zurich, Switzerland.,Zurich-Basel Plant Science Center, CH-8092 Zurich, Switzerland
| | - Christophe Randin
- Institute of Botany, University of Basel, CH-4056 Basel, Switzerland.,Department of Ecology & Evolution, University of Lausanne, CH-1015 Lausanne, Switzerland
| | - Peter Szövényi
- Department of Systematic and Evolutionary Botany, University of Zurich, CH-8008 Zurich, Switzerland
| | - Florian C Boucher
- Department of Systematic and Evolutionary Botany, University of Zurich, CH-8008 Zurich, Switzerland.,Department of Botany and Zoology, University of Stellenbosch, 7602 Matieland, South Africa
| | - Theofania S Patsiou
- Department of Systematic and Evolutionary Botany, University of Zurich, CH-8008 Zurich, Switzerland.,Zurich-Basel Plant Science Center, CH-8092 Zurich, Switzerland.,Institute of Botany, University of Basel, CH-4056 Basel, Switzerland
| | - Elena Conti
- Department of Systematic and Evolutionary Botany, University of Zurich, CH-8008 Zurich, Switzerland.,Zurich-Basel Plant Science Center, CH-8092 Zurich, Switzerland
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27
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Malomane DK, Reimer C, Weigend S, Weigend A, Sharifi AR, Simianer H. Efficiency of different strategies to mitigate ascertainment bias when using SNP panels in diversity studies. BMC Genomics 2018; 19:22. [PMID: 29304727 PMCID: PMC5756397 DOI: 10.1186/s12864-017-4416-9] [Citation(s) in RCA: 71] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 12/22/2017] [Indexed: 12/30/2022] Open
Abstract
Background Single nucleotide polymorphism (SNP) panels have been widely used to study genomic variations within and between populations. Methods of SNP discovery have been a matter of debate for their potential of introducing ascertainment bias, and genetic diversity results obtained from the SNP genotype data can be misleading. We used a total of 42 chicken populations where both individual genotyped array data and pool whole genome resequencing (WGS) data were available. We compared allele frequency distributions and genetic diversity measures (expected heterozygosity (He), fixation index (FST) values, genetic distances and principal components analysis (PCA)) between the two data types. With the array data, we applied different filtering options (SNPs polymorphic in samples of two Gallus gallus wild populations, linkage disequilibrium (LD) based pruning and minor allele frequency (MAF) filtering, and combinations thereof) to assess their potential to mitigate the ascertainment bias. Results Rare SNPs were underrepresented in the array data. Array data consistently overestimated He compared to WGS data, however, with a similar ranking of the breeds, as demonstrated by Spearman’s rank correlations ranging between 0.956 and 0.985. LD based pruning resulted in a reduced overestimation of He compared to the other filters and slightly improved the relationship with the WGS results. The raw array data and those with polymorphic SNPs in the wild samples underestimated pairwise FST values between breeds which had low FST (<0.15) in the WGS, and overestimated this parameter for high WGS FST (>0.15). LD based pruned data underestimated FST in a consistent manner. The genetic distance matrix from LD pruned data was more closely related to that of WGS than the other array versions. PCA was rather robust in all array versions, since the population structure on the PCA plot was generally well captured in comparison to the WGS data. Conclusions Among the tested filtering strategies, LD based pruning was found to account for the effects of ascertainment bias in the relatively best way, producing results which are most comparable to those obtained from WGS data and therefore is recommended for practical use. Electronic supplementary material The online version of this article (doi: 10.1186/s12864-017-4416-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Dorcus Kholofelo Malomane
- Animal Breeding and Genetics Group, Department of Animal Sciences, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Goettingen, Germany.
| | - Christian Reimer
- Animal Breeding and Genetics Group, Department of Animal Sciences, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Goettingen, Germany
| | - Steffen Weigend
- Institute of Farm Animal Genetics, Friedrich-Loeffler-Institut, Höltystraße 10, 31535, Neustadt, Germany
| | - Annett Weigend
- Institute of Farm Animal Genetics, Friedrich-Loeffler-Institut, Höltystraße 10, 31535, Neustadt, Germany
| | - Ahmad Reza Sharifi
- Animal Breeding and Genetics Group, Department of Animal Sciences, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Goettingen, Germany
| | - Henner Simianer
- Animal Breeding and Genetics Group, Department of Animal Sciences, University of Goettingen, Albrecht-Thaer-Weg 3, 37075, Goettingen, Germany
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28
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Veale AJ, Russell JC, King CM. The genomic ancestry, landscape genetics and invasion history of introduced mice in New Zealand. ROYAL SOCIETY OPEN SCIENCE 2018; 5:170879. [PMID: 29410804 PMCID: PMC5792881 DOI: 10.1098/rsos.170879] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2017] [Accepted: 12/15/2017] [Indexed: 06/07/2023]
Abstract
The house mouse (Mus musculus) provides a fascinating system for studying both the genomic basis of reproductive isolation, and the patterns of human-mediated dispersal. New Zealand has a complex history of mouse invasions, and the living descendants of these invaders have genetic ancestry from all three subspecies, although most are primarily descended from M. m. domesticus. We used the GigaMUGA genotyping array (approximately 135 000 loci) to describe the genomic ancestry of 161 mice, sampled from 34 locations from across New Zealand (and one Australian city-Sydney). Of these, two populations, one in the south of the South Island, and one on Chatham Island, showed complete mitochondrial lineage capture, featuring two different lineages of M. m. castaneus mitochondrial DNA but with only M. m. domesticus nuclear ancestry detectable. Mice in the northern and southern parts of the North Island had small traces (approx. 2-3%) of M. m. castaneus nuclear ancestry, and mice in the upper South Island had approximately 7-8% M. m. musculus nuclear ancestry including some Y-chromosomal ancestry-though no detectable M. m. musculus mitochondrial ancestry. This is the most thorough genomic study of introduced populations of house mice yet conducted, and will have relevance to studies of the isolation mechanisms separating subspecies of mice.
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Affiliation(s)
- Andrew J. Veale
- Department of Environmental and Animal Sciences, Unitec, 139 Carrington Road, Auckland 1025, New Zealand
| | - James C. Russell
- School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland Mail Centre, Auckland 1142, New Zealand
| | - Carolyn M. King
- Environmental Research Institute, School of Science, University of Waikato, Private Bag 2105, Hamilton 3240, New Zealand
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29
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Edea Z, Dessie T, Dadi H, Do KT, Kim KS. Genetic Diversity and Population Structure of Ethiopian Sheep Populations Revealed by High-Density SNP Markers. Front Genet 2017; 8:218. [PMID: 29312441 PMCID: PMC5744078 DOI: 10.3389/fgene.2017.00218] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Accepted: 12/05/2017] [Indexed: 11/13/2022] Open
Abstract
Sheep in Ethiopia are adapted to a wide range of environments, including extreme habitats. Elucidating their genetic diversity is critical for improving breeding strategies and mapping quantitative trait loci associated with productivity. To this end, the present study investigated the genetic diversity and population structure of five Ethiopian sheep populations exhibiting distinct phenotypes and sampled from distinct production environments, including arid lowlands and highlands. To investigate the genetic relationships in greater detail and infer population structure of Ethiopian sheep breeds at the continental and global levels, we analyzed genotypic data of selected sheep breeds from the Ovine SNP50K HapMap dataset. All Ethiopian sheep samples were genotyped with Ovine Infinium HD SNP BeadChip (600K). Mean genetic diversity ranged from 0.29 in Arsi-Bale to 0.32 in Menz sheep, while estimates of genetic differentiation among populations ranged from 0.02 to 0.07, indicating low to moderate differentiation. An analysis of molecular variance revealed that 94.62 and 5.38% of the genetic variation was attributable to differences within and among populations, respectively. Our population structure analysis revealed clustering of five Ethiopian sheep populations according to tail phenotype and geographic origin-i.e., short fat-tailed (very cool high-altitude), long fat-tailed (mid to high-altitude), and fat-rumped (arid low-altitude), with clear evidence of admixture between long fat-tailed populations. North African sheep breeds showed higher levels of within-breed diversity, but were less differentiated than breeds from Eastern and Southern Africa. When African breeds were grouped according to geographic origin (North, South, and East), statistically significant differences were detected among groups (regions). A comparison of population structure between Ethiopian and global sheep breeds showed that fat-tailed breeds from Eastern and Southern Africa clustered together, suggesting that these breeds were introduced to the African continent via the Horn and migrated further south.
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Affiliation(s)
- Zewdu Edea
- Department of Animal Science, Chungbuk National University, Cheongju, South Korea
| | - Tadelle Dessie
- International Livestock Research Institute, Addis Ababa, Ethiopia
| | - Hailu Dadi
- Ethiopian Biotechnology Institute, Addis Ababa, Ethiopia
| | - Kyoung-Tag Do
- Department of Animal Biotechnology, Faculty of Biotechnology, Jeju National University, Jeju, South Korea
| | - Kwan-Suk Kim
- Department of Animal Science, Chungbuk National University, Cheongju, South Korea
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30
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Long-Term Impact of Optimum Contribution Selection Strategies on Local Livestock Breeds with Historical Introgression Using the Example of German Angler Cattle. G3-GENES GENOMES GENETICS 2017; 7:4009-4018. [PMID: 29089375 PMCID: PMC5714497 DOI: 10.1534/g3.117.300272] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The long-term performance of different selection strategies was evaluated via simulation using the example of a local cattle breed, German Angler cattle. Different optimum contribution selection (OCS) approaches to maximize genetic gain were compared to a reference scenario without selection and truncation selection. The kinships and migrant contribution (MC) were estimated from genomic data. Truncation selection achieved the highest genetic gain but decreased diversity considerably at native alleles. It also caused the highest increase in MCs. Traditional OCS, which only constrains kinship, achieved almost the same genetic gain but also caused a small increase of MC and remarkably reduced the diversity of native alleles. When MC was required not to increase and the increase of kinship at native alleles was restricted, the MC levels and the diversity at native alleles were well managed, and the genetic gain was only slightly reduced. However, genetic progress was substantially lower in the scenario that aimed to recover the original genetic background. Truncation selection and traditional OCS selection both reduce the genetic originality of breeds with historical introgression. The inclusion of MC and kinship at native alleles as additional constraints in OCS showed great potential for conservation. Recovery of the original genetic background is possible but requires many generations of selection and reduces the genetic progress in performance traits. Hence, constraining MCs at their current values can be recommended to avoid further reduction of genetic originality.
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31
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Leaché AD, Oaks JR. The Utility of Single Nucleotide Polymorphism (SNP) Data in Phylogenetics. ANNUAL REVIEW OF ECOLOGY EVOLUTION AND SYSTEMATICS 2017. [DOI: 10.1146/annurev-ecolsys-110316-022645] [Citation(s) in RCA: 109] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Adam D. Leaché
- Department of Biology and Burke Museum of Natural History and Culture, University of Washington, Seattle, Washington 98195
| | - Jamie R. Oaks
- Department of Biological Sciences, Auburn University, Auburn, Alabama 36849
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Barbato M, Hailer F, Orozco-terWengel P, Kijas J, Mereu P, Cabras P, Mazza R, Pirastru M, Bruford MW. Genomic signatures of adaptive introgression from European mouflon into domestic sheep. Sci Rep 2017; 7:7623. [PMID: 28790322 PMCID: PMC5548776 DOI: 10.1038/s41598-017-07382-7] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Accepted: 06/22/2017] [Indexed: 11/09/2022] Open
Abstract
Mouflon (Ovis aries musimon) became extinct from mainland Europe after the Neolithic, but remnant populations from the Mediterranean islands of Corsica and Sardinia have been used for reintroductions across Europe since the 19th-century. Mouflon x sheep hybrids are larger-bodied than mouflon, potentially showing increased male reproductive success, but little is known about genomic levels of admixture, or about the adaptive significance of introgression between resident mouflon and local sheep breeds. Here we analysed Ovine medium-density SNP array genotypes of 92 mouflon from six geographic regions, along with data from 330 individuals of 16 domestic sheep breeds. We found lower levels of genetic diversity in mouflon than in domestic sheep, consistent with past bottlenecks in mouflon. Introgression signals were bidirectional and affected most mouflon and sheep populations, being strongest in one Sardinian mouflon population. Developing and using a novel approach to identify chromosomal regions with consistent introgression signals, we infer adaptive introgression from mouflon to domestic sheep related to immunity mechanisms, but not in the opposite direction. Further, we infer that Soay and Sarda sheep carry introgressed mouflon alleles involved in bitter taste perception and/or innate immunity. Our results illustrate the potential for adaptive introgression even among recently diverged populations.
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Affiliation(s)
- Mario Barbato
- Istituto di Zootecnica, Università Cattolica del Sacro Cuore, via Emilia Parmense 84, Piacenza, Italy. .,School of Biosciences, Cardiff University, CF10 3AX, Cardiff, Wales, UK.
| | - Frank Hailer
- School of Biosciences, Cardiff University, CF10 3AX, Cardiff, Wales, UK
| | | | - James Kijas
- CSIRO Agriculture, St Lucia, Brisbane, 4067, QLD, Australia
| | - Paolo Mereu
- Department of Biomedical Sciences, and Centre for Biotechnology Development and Biodiversity Research, University of Sassari, V.le San Pietro 43, Sassari, Italy
| | - Pierangela Cabras
- Istituto Zooprofilattico Sperimentale della Sardegna, Tortolí, Ogliastra, Italy
| | - Raffaele Mazza
- Laboratorio Genetica e Servizi - Associazione Italiana Allevatori, Cremona, Italy
| | - Monica Pirastru
- Department of Biomedical Sciences, and Centre for Biotechnology Development and Biodiversity Research, University of Sassari, V.le San Pietro 43, Sassari, Italy
| | - Michael W Bruford
- School of Biosciences, Cardiff University, CF10 3AX, Cardiff, Wales, UK
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Weir BS, Goudet J. A Unified Characterization of Population Structure and Relatedness. Genetics 2017; 206:2085-2103. [PMID: 28550018 PMCID: PMC5560808 DOI: 10.1534/genetics.116.198424] [Citation(s) in RCA: 100] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2016] [Accepted: 05/17/2017] [Indexed: 11/18/2022] Open
Abstract
Many population genetic activities, ranging from evolutionary studies to association mapping, to forensic identification, rely on appropriate estimates of population structure or relatedness. All applications require recognition that quantities with an underlying meaning of allelic dependence are not defined in an absolute sense, but instead are made "relative to" some set of alleles other than the target set. The 1984 Weir and Cockerham [Formula: see text] estimate made explicit that the reference set of alleles was across populations, whereas standard kinship estimates do not make the reference explicit. Weir and Cockerham stated that their [Formula: see text] estimates were for independent populations, and standard kinship estimates have an implicit assumption that pairs of individuals in a study sample, other than the target pair, are unrelated or are not inbred. However, populations lose independence when there is migration between them, and dependencies between pairs of individuals in a population exist for more than one target pair. We have therefore recast our treatments of population structure, relatedness, and inbreeding to make explicit that the parameters of interest involve the differences in degrees of allelic dependence between the target and the reference sets of alleles, and so can be negative. We take the reference set to be the population from which study individuals have been sampled. We provide simple moment estimates of these parameters, phrased in terms of allelic matching within and between individuals for relatedness and inbreeding, or within and between populations for population structure. A multi-level hierarchy of alleles within individuals, alleles between individuals within populations, and alleles between populations, allows a unified treatment of relatedness and population structure. We expect our new measures to have a wide range of applications, but we note that their estimates are sensitive to rare or private variants: some population-characterization applications suggest exploiting those sensitivities, whereas estimation of relatedness may best use all genetic markers without filtering on minor allele frequency.
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Affiliation(s)
- Bruce S Weir
- Department of Biostatistics, University of Washington, Seattle, Washington 98195
| | - Jérôme Goudet
- Department of Ecology and Evolution
- Swiss Institute of Bioinformatics, University of Lausanne, 1015 Switzerland
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Brito LF, McEwan JC, Miller SP, Pickering NK, Bain WE, Dodds KG, Schenkel FS, Clarke SM. Genetic diversity of a New Zealand multi-breed sheep population and composite breeds' history revealed by a high-density SNP chip. BMC Genet 2017; 18:25. [PMID: 28288558 PMCID: PMC5348757 DOI: 10.1186/s12863-017-0492-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Accepted: 03/07/2017] [Indexed: 12/22/2022] Open
Abstract
Background Knowledge about the genetic diversity of a population is a crucial parameter for the implementation of successful genomic selection and conservation of genetic resources. The aim of this research was to establish the scientific basis for the implementation of genomic selection in a composite Terminal sheep breeding scheme by providing consolidated linkage disequilibrium (LD) measures across SNP markers, estimating consistency of gametic phase between breed-groups, and assessing genetic diversity measures, such as effective population size (Ne), and population structure parameters, using a large number of animals (n = 14,845) genotyped with a high density SNP chip (606,006 markers). Information generated in this research will be useful for optimizing molecular breeding values predictions and managing the available genetic resources. Results Overall, as expected, levels of pairwise LD decreased with increasing distance between SNP pairs. The mean LD r2 between adjacent SNP was 0.26 ± 0.10. The most recent effective population size for all animals (687) and separately per breed-groups: Primera (974), Lamb Supreme (380), Texel (227) and Dual-Purpose (125) was quite variable. The genotyped animals were outbred or had an average low level of inbreeding. Consistency of gametic phase was higher than 0.94 for all breed pairs at the average distance between SNP on the chip (~4.74 kb). Moreover, there was not a clear separation between the breed-groups based on principal component analysis, suggesting that a mixed-breed training population for calculation of molecular breeding values would be beneficial. Conclusions This study reports, for the first time, estimates of linkage disequilibrium, genetic diversity and population structure parameters from a genome-wide perspective in New Zealand Terminal Sire composite sheep breeds. The levels of linkage disequilibrium indicate that genomic selection could be implemented with the high density SNP panel. The moderate to high consistency of gametic phase between breed-groups and overlapping population structure support the pooling of the animals in a mixed training population for genomic predictions. In addition, the moderate to high Ne highlights the need to genotype and phenotype a large training population in order to capture most of the haplotype diversity and increase accuracies of genomic predictions. The results reported herein are a first step toward understanding the genomic architecture of a Terminal Sire composite sheep population and for the optimal implementation of genomic selection and genome-wide association studies in this sheep population. Electronic supplementary material The online version of this article (doi:10.1186/s12863-017-0492-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Luiz F Brito
- Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, N1G 2W1, Canada. .,AgResearch, Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand.
| | - John C McEwan
- AgResearch, Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand
| | - Stephen P Miller
- Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, N1G 2W1, Canada.,AgResearch, Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand
| | | | - Wendy E Bain
- AgResearch, Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand
| | - Ken G Dodds
- AgResearch, Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand
| | - Flávio S Schenkel
- Centre for Genetic Improvement of Livestock, University of Guelph, Guelph, N1G 2W1, Canada
| | - Shannon M Clarke
- AgResearch, Invermay Agricultural Centre, Private Bag 50034, Mosgiel, 9053, New Zealand
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Msalya G, Kim ES, Laisser ELK, Kipanyula MJ, Karimuribo ED, Kusiluka LJM, Chenyambuga SW, Rothschild MF. Determination of Genetic Structure and Signatures of Selection in Three Strains of Tanzania Shorthorn Zebu, Boran and Friesian Cattle by Genome-Wide SNP Analyses. PLoS One 2017; 12:e0171088. [PMID: 28129396 PMCID: PMC5271371 DOI: 10.1371/journal.pone.0171088] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2016] [Accepted: 01/16/2017] [Indexed: 11/29/2022] Open
Abstract
Background More than 90 percent of cattle in Tanzania belong to the indigenous Tanzania Short Horn Zebu (TSZ) population which has been classified into 12 strains based on historical evidence, morphological characteristics, and geographic distribution. However, specific genetic information of each TSZ population has been lacking and has caused difficulties in designing programs such as selection, crossbreeding, breed improvement or conservation. This study was designed to evaluate the genetic structure, assess genetic relationships, and to identify signatures of selection among cattle of Tanzania with the main goal of understanding genetic relationship, variation and uniqueness among them. Methodology/Principal findings The Illumina Bos indicus SNP 80K BeadChip was used to genotype genome wide SNPs in 168 DNA samples obtained from three strains of TSZ cattle namely Maasai, Tarime and Sukuma as well as two comparative breeds; Boran and Friesian. Population structure and signatures of selection were examined using principal component analysis (PCA), admixture analysis, pairwise distances (FST), integrated haplotype score (iHS), identical by state (IBS) and runs of homozygosity (ROH). There was a low level of inbreeding (F~0.01) in the TSZ population compared to the Boran and Friesian breeds. The analyses of FST, IBS and admixture identified no considerable differentiation between TSZ trains. Importantly, common ancestry in Boran and TSZ were revealed based on admixture and IBD, implying gene flow between two populations. In addition, Friesian ancestry was found in Boran. A few common significant iHS were detected, which may reflect influence of recent selection in each breed or strain. Conclusions Population admixture and selection signatures could be applied to develop conservation plan of TSZ cattle as well as future breeding programs in East African cattle.
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Affiliation(s)
- George Msalya
- Department of Animal, Aquaculture and Range Sciences, Sokoine University of Agriculture (SUA), Morogoro, Tanzania
- * E-mail:
| | - Eui-Soo Kim
- Department of Animal Science, Iowa State University, Ames, Iowa, United States of America
| | - Emmanuel L. K. Laisser
- Department of Animal, Aquaculture and Range Sciences, Sokoine University of Agriculture (SUA), Morogoro, Tanzania
- Ministry of Education and Vocational Training, Inspectorate Department Eastern Zone, Morogoro, Tanzania
| | | | - Esron D. Karimuribo
- Department of Veterinary Medicine and Public Health, SUA, Morogoro, Tanzania
| | - Lughano J. M. Kusiluka
- Department of Veterinary Medicine and Public Health, SUA, Morogoro, Tanzania
- Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania
| | - Sebastian W. Chenyambuga
- Department of Animal, Aquaculture and Range Sciences, Sokoine University of Agriculture (SUA), Morogoro, Tanzania
| | - Max F. Rothschild
- Department of Animal Science, Iowa State University, Ames, Iowa, United States of America
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Rezende VB, Congrains C, Lima ALA, Campanini EB, Nakamura AM, Oliveira JLD, Chahad-Ehlers S, Junior IS, Alves de Brito R. Head Transcriptomes of Two Closely Related Species of Fruit Flies of the Anastrepha fraterculus Group Reveals Divergent Genes in Species with Extensive Gene Flow. G3 (BETHESDA, MD.) 2016; 6:3283-3295. [PMID: 27558666 PMCID: PMC5068948 DOI: 10.1534/g3.116.030486] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2016] [Accepted: 08/10/2016] [Indexed: 11/18/2022]
Abstract
Several fruit flies species of the Anastrepha fraterculus group are of great economic importance for the damage they cause to a variety of fleshy fruits. Some species in this group have diverged recently, with evidence of introgression, showing similar morphological attributes that render their identification difficult, reinforcing the relevance of identifying new molecular markers that may differentiate species. We investigated genes expressed in head tissues from two closely related species: A. obliqua and A. fraterculus, aiming to identify fixed single nucleotide polymorphisms (SNPs) and highly differentiated transcripts, which, considering that these species still experience some level of gene flow, could indicate potential candidate genes involved in their differentiation process. We generated multiple libraries from head tissues of these two species, at different reproductive stages, for both sexes. Our analyses indicate that the de novo transcriptome assemblies are fairly complete. We also produced a hybrid assembly to map each species' reads, and identified 67,470 SNPs in A. fraterculus, 39,252 in A. obliqua, and 6386 that were common to both species. We identified 164 highly differentiated unigenes that had a mean interspecific index ([Formula: see text]) of at least 0.94. We selected unigenes that had Ka/Ks higher than 0.5, or had at least three or more highly differentiated SNPs as potential candidate genes for species differentiation. Among these candidates, we identified proteases, regulators of redox homeostasis, and an odorant-binding protein (Obp99c), among other genes. The head transcriptomes described here enabled the identification of thousands of genes hitherto unavailable for these species, and generated a set of candidate genes that are potentially important to genetically identify species and understand the speciation process in the presence of gene flow of A. obliqua and A. fraterculus.
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Affiliation(s)
- Victor Borges Rezende
- Departamento de Genética e Evolução, Universidade Federal de São Carlos, São Paulo 13565-905, Brazil
| | - Carlos Congrains
- Departamento de Genética e Evolução, Universidade Federal de São Carlos, São Paulo 13565-905, Brazil
| | - André Luís A Lima
- Departamento de Genética e Evolução, Universidade Federal de São Carlos, São Paulo 13565-905, Brazil
| | - Emeline Boni Campanini
- Departamento de Genética e Evolução, Universidade Federal de São Carlos, São Paulo 13565-905, Brazil
| | - Aline Minali Nakamura
- Departamento de Genética e Evolução, Universidade Federal de São Carlos, São Paulo 13565-905, Brazil
| | - Janaína Lima de Oliveira
- Departamento de Genética e Evolução, Universidade Federal de São Carlos, São Paulo 13565-905, Brazil
| | - Samira Chahad-Ehlers
- Departamento de Genética e Evolução, Universidade Federal de São Carlos, São Paulo 13565-905, Brazil
| | - Iderval Sobrinho Junior
- Departamento de Genética e Evolução, Universidade Federal de São Carlos, São Paulo 13565-905, Brazil
| | - Reinaldo Alves de Brito
- Departamento de Genética e Evolução, Universidade Federal de São Carlos, São Paulo 13565-905, Brazil
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Sorbolini S, Gaspa G, Steri R, Dimauro C, Cellesi M, Stella A, Marras G, Marsan PA, Valentini A, Macciotta NPP. Use of canonical discriminant analysis to study signatures of selection in cattle. Genet Sel Evol 2016; 48:58. [PMID: 27521154 PMCID: PMC4983034 DOI: 10.1186/s12711-016-0236-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Accepted: 08/01/2016] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Cattle include a large number of breeds that are characterized by marked phenotypic differences and thus constitute a valuable model to study genome evolution in response to processes such as selection and domestication. Detection of "signatures of selection" is a useful approach to study the evolutionary pressures experienced throughout history. In the present study, signatures of selection were investigated in five cattle breeds farmed in Italy using a multivariate approach. METHODS A total of 4094 bulls from five breeds with different production aptitudes (two dairy breeds: Italian Holstein and Italian Brown Swiss; two beef breeds: Piemontese and Marchigiana; and one dual purpose breed: Italian Simmental) were genotyped using the Illumina BovineSNP50 v.1 beadchip. Canonical discriminant analysis was carried out on the matrix of single nucleotide polymorphisms (SNP) genotyping data, separately for each chromosome. Scores for each canonical variable were calculated and then plotted in the canonical space to quantify the distance between breeds. SNPs for which the correlation with the canonical variable was in the 99th percentile for a specific chromosome were considered to be significantly associated with that variable. Results were compared with those obtained using an FST-based approach. RESULTS Based on the results of the canonical discriminant analysis, a large number of signatures of selection were detected, among which several had strong signals in genomic regions that harbour genes known to have an impact on production and morphological bovine traits, including MSTN, LCT, GHR, SCD, NCAPG, KIT, and ASIP. Moreover, new putative candidate genes were identified, such as GCK, B3GALNT1, MGAT1, GALNTL1, PRNP, and PRND. Similar results were obtained with the FST-based approach. CONCLUSIONS The use of canonical discriminant analysis on 50 K SNP genotypes allowed the extraction of new variables that maximize the separation between breeds. This approach is quite straightforward, it can compare more than two groups simultaneously, and relative distances between breeds can be visualized. The genes that were highlighted in the canonical discriminant analysis were in concordance with those obtained using the FST index.
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Affiliation(s)
- Silvia Sorbolini
- Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, V. le Italia, 9, 07100, Sassari, Italy
| | - Giustino Gaspa
- Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, V. le Italia, 9, 07100, Sassari, Italy
| | - Roberto Steri
- Consiglio per la Ricerca e la Sperimentazione in Agricoltura, via Salaria 31, 00015, Monterotondo, Italy
| | - Corrado Dimauro
- Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, V. le Italia, 9, 07100, Sassari, Italy
| | - Massimo Cellesi
- Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, V. le Italia, 9, 07100, Sassari, Italy
| | | | | | - Paolo Ajmone Marsan
- Istituto di Zootecnica, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Alessio Valentini
- Dipartimento per l'Innovazione dei Sistemi Biologici Agroalimentari e Forestali DIBAF, Università della Tuscia, Viterbo, Italy
| | - Nicolò Pietro Paolo Macciotta
- Dipartimento di Agraria, Sezione di Scienze Zootecniche, Università degli Studi di Sassari, V. le Italia, 9, 07100, Sassari, Italy.
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Cammen KM, Andrews KR, Carroll EL, Foote AD, Humble E, Khudyakov JI, Louis M, McGowen MR, Olsen MT, Van Cise AM. Genomic Methods Take the Plunge: Recent Advances in High-Throughput Sequencing of Marine Mammals. J Hered 2016; 107:481-95. [PMID: 27511190 DOI: 10.1093/jhered/esw044] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2016] [Accepted: 07/12/2016] [Indexed: 12/18/2022] Open
Abstract
The dramatic increase in the application of genomic techniques to non-model organisms (NMOs) over the past decade has yielded numerous valuable contributions to evolutionary biology and ecology, many of which would not have been possible with traditional genetic markers. We review this recent progression with a particular focus on genomic studies of marine mammals, a group of taxa that represent key macroevolutionary transitions from terrestrial to marine environments and for which available genomic resources have recently undergone notable rapid growth. Genomic studies of NMOs utilize an expanding range of approaches, including whole genome sequencing, restriction site-associated DNA sequencing, array-based sequencing of single nucleotide polymorphisms and target sequence probes (e.g., exomes), and transcriptome sequencing. These approaches generate different types and quantities of data, and many can be applied with limited or no prior genomic resources, thus overcoming one traditional limitation of research on NMOs. Within marine mammals, such studies have thus far yielded significant contributions to the fields of phylogenomics and comparative genomics, as well as enabled investigations of fitness, demography, and population structure. Here we review the primary options for generating genomic data, introduce several emerging techniques, and discuss the suitability of each approach for different applications in the study of NMOs.
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Affiliation(s)
- Kristina M Cammen
- From the School of Marine Sciences, University of Maine, Orono, ME 04469 (Cammen); Department of Fish and Wildlife Sciences, University of Idaho, 875 Perimeter Drive MS 1136, Moscow, ID 83844-1136 (Andrews); Scottish Oceans Institute, University of St Andrews, East Sands, St Andrews, Fife KY16 8LB, UK (Carroll and Louis); Computational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern CH-3012, Switzerland (Foote); Department of Animal Behaviour, University of Bielefeld, Postfach 100131, 33501 Bielefeld, Germany (Humble); British Antarctic Survey, High Cross, Madingley Road, Cambridge CB3 OET, UK (Humble); Department of Biology, Sonoma State University, Rohnert Park, CA 94928 (Khudyakov); School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK (Mcgowen); Evolutionary Genomics Section, Natural History Museum of Denmark, University of Copenhagen, DK-1353 Copenhagen K, Denmark (Olsen); and Scripps Institution of Oceanography, University of California San Diego, 8622 Kennel Way, La Jolla, CA 92037 (Van Cise).
| | - Kimberly R Andrews
- From the School of Marine Sciences, University of Maine, Orono, ME 04469 (Cammen); Department of Fish and Wildlife Sciences, University of Idaho, 875 Perimeter Drive MS 1136, Moscow, ID 83844-1136 (Andrews); Scottish Oceans Institute, University of St Andrews, East Sands, St Andrews, Fife KY16 8LB, UK (Carroll and Louis); Computational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern CH-3012, Switzerland (Foote); Department of Animal Behaviour, University of Bielefeld, Postfach 100131, 33501 Bielefeld, Germany (Humble); British Antarctic Survey, High Cross, Madingley Road, Cambridge CB3 OET, UK (Humble); Department of Biology, Sonoma State University, Rohnert Park, CA 94928 (Khudyakov); School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK (Mcgowen); Evolutionary Genomics Section, Natural History Museum of Denmark, University of Copenhagen, DK-1353 Copenhagen K, Denmark (Olsen); and Scripps Institution of Oceanography, University of California San Diego, 8622 Kennel Way, La Jolla, CA 92037 (Van Cise)
| | - Emma L Carroll
- From the School of Marine Sciences, University of Maine, Orono, ME 04469 (Cammen); Department of Fish and Wildlife Sciences, University of Idaho, 875 Perimeter Drive MS 1136, Moscow, ID 83844-1136 (Andrews); Scottish Oceans Institute, University of St Andrews, East Sands, St Andrews, Fife KY16 8LB, UK (Carroll and Louis); Computational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern CH-3012, Switzerland (Foote); Department of Animal Behaviour, University of Bielefeld, Postfach 100131, 33501 Bielefeld, Germany (Humble); British Antarctic Survey, High Cross, Madingley Road, Cambridge CB3 OET, UK (Humble); Department of Biology, Sonoma State University, Rohnert Park, CA 94928 (Khudyakov); School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK (Mcgowen); Evolutionary Genomics Section, Natural History Museum of Denmark, University of Copenhagen, DK-1353 Copenhagen K, Denmark (Olsen); and Scripps Institution of Oceanography, University of California San Diego, 8622 Kennel Way, La Jolla, CA 92037 (Van Cise)
| | - Andrew D Foote
- From the School of Marine Sciences, University of Maine, Orono, ME 04469 (Cammen); Department of Fish and Wildlife Sciences, University of Idaho, 875 Perimeter Drive MS 1136, Moscow, ID 83844-1136 (Andrews); Scottish Oceans Institute, University of St Andrews, East Sands, St Andrews, Fife KY16 8LB, UK (Carroll and Louis); Computational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern CH-3012, Switzerland (Foote); Department of Animal Behaviour, University of Bielefeld, Postfach 100131, 33501 Bielefeld, Germany (Humble); British Antarctic Survey, High Cross, Madingley Road, Cambridge CB3 OET, UK (Humble); Department of Biology, Sonoma State University, Rohnert Park, CA 94928 (Khudyakov); School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK (Mcgowen); Evolutionary Genomics Section, Natural History Museum of Denmark, University of Copenhagen, DK-1353 Copenhagen K, Denmark (Olsen); and Scripps Institution of Oceanography, University of California San Diego, 8622 Kennel Way, La Jolla, CA 92037 (Van Cise)
| | - Emily Humble
- From the School of Marine Sciences, University of Maine, Orono, ME 04469 (Cammen); Department of Fish and Wildlife Sciences, University of Idaho, 875 Perimeter Drive MS 1136, Moscow, ID 83844-1136 (Andrews); Scottish Oceans Institute, University of St Andrews, East Sands, St Andrews, Fife KY16 8LB, UK (Carroll and Louis); Computational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern CH-3012, Switzerland (Foote); Department of Animal Behaviour, University of Bielefeld, Postfach 100131, 33501 Bielefeld, Germany (Humble); British Antarctic Survey, High Cross, Madingley Road, Cambridge CB3 OET, UK (Humble); Department of Biology, Sonoma State University, Rohnert Park, CA 94928 (Khudyakov); School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK (Mcgowen); Evolutionary Genomics Section, Natural History Museum of Denmark, University of Copenhagen, DK-1353 Copenhagen K, Denmark (Olsen); and Scripps Institution of Oceanography, University of California San Diego, 8622 Kennel Way, La Jolla, CA 92037 (Van Cise)
| | - Jane I Khudyakov
- From the School of Marine Sciences, University of Maine, Orono, ME 04469 (Cammen); Department of Fish and Wildlife Sciences, University of Idaho, 875 Perimeter Drive MS 1136, Moscow, ID 83844-1136 (Andrews); Scottish Oceans Institute, University of St Andrews, East Sands, St Andrews, Fife KY16 8LB, UK (Carroll and Louis); Computational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern CH-3012, Switzerland (Foote); Department of Animal Behaviour, University of Bielefeld, Postfach 100131, 33501 Bielefeld, Germany (Humble); British Antarctic Survey, High Cross, Madingley Road, Cambridge CB3 OET, UK (Humble); Department of Biology, Sonoma State University, Rohnert Park, CA 94928 (Khudyakov); School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK (Mcgowen); Evolutionary Genomics Section, Natural History Museum of Denmark, University of Copenhagen, DK-1353 Copenhagen K, Denmark (Olsen); and Scripps Institution of Oceanography, University of California San Diego, 8622 Kennel Way, La Jolla, CA 92037 (Van Cise)
| | - Marie Louis
- From the School of Marine Sciences, University of Maine, Orono, ME 04469 (Cammen); Department of Fish and Wildlife Sciences, University of Idaho, 875 Perimeter Drive MS 1136, Moscow, ID 83844-1136 (Andrews); Scottish Oceans Institute, University of St Andrews, East Sands, St Andrews, Fife KY16 8LB, UK (Carroll and Louis); Computational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern CH-3012, Switzerland (Foote); Department of Animal Behaviour, University of Bielefeld, Postfach 100131, 33501 Bielefeld, Germany (Humble); British Antarctic Survey, High Cross, Madingley Road, Cambridge CB3 OET, UK (Humble); Department of Biology, Sonoma State University, Rohnert Park, CA 94928 (Khudyakov); School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK (Mcgowen); Evolutionary Genomics Section, Natural History Museum of Denmark, University of Copenhagen, DK-1353 Copenhagen K, Denmark (Olsen); and Scripps Institution of Oceanography, University of California San Diego, 8622 Kennel Way, La Jolla, CA 92037 (Van Cise)
| | - Michael R McGowen
- From the School of Marine Sciences, University of Maine, Orono, ME 04469 (Cammen); Department of Fish and Wildlife Sciences, University of Idaho, 875 Perimeter Drive MS 1136, Moscow, ID 83844-1136 (Andrews); Scottish Oceans Institute, University of St Andrews, East Sands, St Andrews, Fife KY16 8LB, UK (Carroll and Louis); Computational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern CH-3012, Switzerland (Foote); Department of Animal Behaviour, University of Bielefeld, Postfach 100131, 33501 Bielefeld, Germany (Humble); British Antarctic Survey, High Cross, Madingley Road, Cambridge CB3 OET, UK (Humble); Department of Biology, Sonoma State University, Rohnert Park, CA 94928 (Khudyakov); School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK (Mcgowen); Evolutionary Genomics Section, Natural History Museum of Denmark, University of Copenhagen, DK-1353 Copenhagen K, Denmark (Olsen); and Scripps Institution of Oceanography, University of California San Diego, 8622 Kennel Way, La Jolla, CA 92037 (Van Cise)
| | - Morten Tange Olsen
- From the School of Marine Sciences, University of Maine, Orono, ME 04469 (Cammen); Department of Fish and Wildlife Sciences, University of Idaho, 875 Perimeter Drive MS 1136, Moscow, ID 83844-1136 (Andrews); Scottish Oceans Institute, University of St Andrews, East Sands, St Andrews, Fife KY16 8LB, UK (Carroll and Louis); Computational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern CH-3012, Switzerland (Foote); Department of Animal Behaviour, University of Bielefeld, Postfach 100131, 33501 Bielefeld, Germany (Humble); British Antarctic Survey, High Cross, Madingley Road, Cambridge CB3 OET, UK (Humble); Department of Biology, Sonoma State University, Rohnert Park, CA 94928 (Khudyakov); School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK (Mcgowen); Evolutionary Genomics Section, Natural History Museum of Denmark, University of Copenhagen, DK-1353 Copenhagen K, Denmark (Olsen); and Scripps Institution of Oceanography, University of California San Diego, 8622 Kennel Way, La Jolla, CA 92037 (Van Cise)
| | - Amy M Van Cise
- From the School of Marine Sciences, University of Maine, Orono, ME 04469 (Cammen); Department of Fish and Wildlife Sciences, University of Idaho, 875 Perimeter Drive MS 1136, Moscow, ID 83844-1136 (Andrews); Scottish Oceans Institute, University of St Andrews, East Sands, St Andrews, Fife KY16 8LB, UK (Carroll and Louis); Computational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern CH-3012, Switzerland (Foote); Department of Animal Behaviour, University of Bielefeld, Postfach 100131, 33501 Bielefeld, Germany (Humble); British Antarctic Survey, High Cross, Madingley Road, Cambridge CB3 OET, UK (Humble); Department of Biology, Sonoma State University, Rohnert Park, CA 94928 (Khudyakov); School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK (Mcgowen); Evolutionary Genomics Section, Natural History Museum of Denmark, University of Copenhagen, DK-1353 Copenhagen K, Denmark (Olsen); and Scripps Institution of Oceanography, University of California San Diego, 8622 Kennel Way, La Jolla, CA 92037 (Van Cise)
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Yaro M, Munyard KA, Stear MJ, Groth DM. Molecular identification of livestock breeds: a tool for modern conservation biology. Biol Rev Camb Philos Soc 2016; 92:993-1010. [DOI: 10.1111/brv.12265] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2015] [Revised: 02/14/2016] [Accepted: 02/18/2016] [Indexed: 12/22/2022]
Affiliation(s)
- Mohammed Yaro
- School of Biomedical Sciences, CHIRI Biosciences Research Precinct, Faculty of Health Sciences; Curtin University; GPO Box U1987 Perth WA 6845 Australia
| | - Kylie A. Munyard
- School of Biomedical Sciences, CHIRI Biosciences Research Precinct, Faculty of Health Sciences; Curtin University; GPO Box U1987 Perth WA 6845 Australia
| | - Michael J. Stear
- Institute of Biodiversity, Animal Health and Comparative Medicine; University of Glasgow; Bearsden Road Glasgow G61 1QH U.K
| | - David M. Groth
- School of Biomedical Sciences, CHIRI Biosciences Research Precinct, Faculty of Health Sciences; Curtin University; GPO Box U1987 Perth WA 6845 Australia
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Jones MR, Good JM. Targeted capture in evolutionary and ecological genomics. Mol Ecol 2016; 25:185-202. [PMID: 26137993 PMCID: PMC4823023 DOI: 10.1111/mec.13304] [Citation(s) in RCA: 203] [Impact Index Per Article: 22.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2015] [Revised: 06/19/2015] [Accepted: 06/24/2015] [Indexed: 12/17/2022]
Abstract
The rapid expansion of next-generation sequencing has yielded a powerful array of tools to address fundamental biological questions at a scale that was inconceivable just a few years ago. Various genome-partitioning strategies to sequence select subsets of the genome have emerged as powerful alternatives to whole-genome sequencing in ecological and evolutionary genomic studies. High-throughput targeted capture is one such strategy that involves the parallel enrichment of preselected genomic regions of interest. The growing use of targeted capture demonstrates its potential power to address a range of research questions, yet these approaches have yet to expand broadly across laboratories focused on evolutionary and ecological genomics. In part, the use of targeted capture has been hindered by the logistics of capture design and implementation in species without established reference genomes. Here we aim to (i) increase the accessibility of targeted capture to researchers working in nonmodel taxa by discussing capture methods that circumvent the need of a reference genome, (ii) highlight the evolutionary and ecological applications where this approach is emerging as a powerful sequencing strategy and (iii) discuss the future of targeted capture and other genome-partitioning approaches in the light of the increasing accessibility of whole-genome sequencing. Given the practical advantages and increasing feasibility of high-throughput targeted capture, we anticipate an ongoing expansion of capture-based approaches in evolutionary and ecological research, synergistic with an expansion of whole-genome sequencing.
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Affiliation(s)
- Matthew R. Jones
- University of Montana, Division of Biological Sciences, 32 Campus Dr. HS104, Missoula, MT 59812, USA
| | - Jeffrey M. Good
- University of Montana, Division of Biological Sciences, 32 Campus Dr. HS104, Missoula, MT 59812, USA
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Identification of Diagnostic Mitochondrial DNA Single Nucleotide Polymorphisms Specific to Sumatran Orangutan (Pongo abelii) Populations. HAYATI JOURNAL OF BIOSCIENCES 2015. [DOI: 10.1016/j.hjb.2015.09.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
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