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      Genome-wide patterns of homozygosity provide clues about the population history and adaptation of goats

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          Abstract

          Background

          Patterns of homozygosity can be influenced by several factors, such as demography, recombination, and selection. Using the goat SNP50 BeadChip, we genotyped 3171 goats belonging to 117 populations with a worldwide distribution. Our objectives were to characterize the number and length of runs of homozygosity (ROH) and to detect ROH hotspots in order to gain new insights into the consequences of neutral and selection processes on the genome-wide homozygosity patterns of goats.

          Results

          The proportion of the goat genome covered by ROH is, in general, less than 15% with an inverse relationship between ROH length and frequency i.e. short ROH (< 3 Mb) are the most frequent ones. Our data also indicate that ~ 60% of the breeds display low F ROH coefficients (< 0.10), while ~ 30 and ~ 10% of the goat populations show moderate (0.10 <  F ROH < 0.20) or high (> 0.20) F ROH values. For populations from Asia, the average number of ROH is smaller and their coverage is lower in goats from the Near East than in goats from Central Asia, which is consistent with the role of the Fertile Crescent as the primary centre of goat domestication. We also observed that local breeds with small population sizes tend to have a larger fraction of the genome covered by ROH compared to breeds with tens or hundreds of thousands of individuals. Five regions on three goat chromosomes i.e. 11, 12 and 18, contain ROH hotspots that overlap with signatures of selection.

          Conclusions

          Patterns of homozygosity (average number of ROH of 77 and genome coverage of 248 Mb; F ROH < 0.15) are similar in goats from different geographic areas. The increased homozygosity in local breeds is the consequence of their small population size and geographic isolation as well as of founder effects and recent inbreeding. The existence of three ROH hotspots that co-localize with signatures of selection demonstrates that selection has also played an important role in increasing the homozygosity of specific regions in the goat genome. Finally, most of the goat breeds analysed in this work display low levels of homozygosity, which is favourable for their genetic management and viability.

          Electronic supplementary material

          The online version of this article (10.1186/s12711-018-0424-8) contains supplementary material, which is available to authorized users.

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          Most cited references30

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          Genomic patterns of homozygosity in worldwide human populations.

          Genome-wide patterns of homozygosity runs and their variation across individuals provide a valuable and often untapped resource for studying human genetic diversity and evolutionary history. Using genotype data at 577,489 autosomal SNPs, we employed a likelihood-based approach to identify runs of homozygosity (ROH) in 1,839 individuals representing 64 worldwide populations, classifying them by length into three classes-short, intermediate, and long-with a model-based clustering algorithm. For each class, the number and total length of ROH per individual show considerable variation across individuals and populations. The total lengths of short and intermediate ROH per individual increase with the distance of a population from East Africa, in agreement with similar patterns previously observed for locus-wise homozygosity and linkage disequilibrium. By contrast, total lengths of long ROH show large interindividual variations that probably reflect recent inbreeding patterns, with higher values occurring more often in populations with known high frequencies of consanguineous unions. Across the genome, distributions of ROH are not uniform, and they have distinctive continental patterns. ROH frequencies across the genome are correlated with local genomic variables such as recombination rate, as well as with signals of recent positive selection. In addition, long ROH are more frequent in genomic regions harboring genes associated with autosomal-dominant diseases than in regions not implicated in Mendelian diseases. These results provide insight into the way in which homozygosity patterns are produced, and they generate baseline homozygosity patterns that can be used to aid homozygosity mapping of genes associated with recessive diseases. Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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            Genomic Runs of Homozygosity Record Population History and Consanguinity

            The human genome is characterised by many runs of homozygous genotypes, where identical haplotypes were inherited from each parent. The length of each run is determined partly by the number of generations since the common ancestor: offspring of cousin marriages have long runs of homozygosity (ROH), while the numerous shorter tracts relate to shared ancestry tens and hundreds of generations ago. Human populations have experienced a wide range of demographic histories and hold diverse cultural attitudes to consanguinity. In a global population dataset, genome-wide analysis of long and shorter ROH allows categorisation of the mainly indigenous populations sampled here into four major groups in which the majority of the population are inferred to have: (a) recent parental relatedness (south and west Asians); (b) shared parental ancestry arising hundreds to thousands of years ago through long term isolation and restricted effective population size (Ne), but little recent inbreeding (Oceanians); (c) both ancient and recent parental relatedness (Native Americans); and (d) only the background level of shared ancestry relating to continental Ne (predominantly urban Europeans and East Asians; lowest of all in sub-Saharan African agriculturalists), and the occasional cryptically inbred individual. Moreover, individuals can be positioned along axes representing this demographic historic space. Long runs of homozygosity are therefore a globally widespread and under-appreciated characteristic of our genomes, which record past consanguinity and population isolation and provide a distinctive record of the demographic history of an individual's ancestors. Individual ROH measures will also allow quantification of the disease risk arising from polygenic recessive effects.
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              Sequencing and automated whole-genome optical mapping of the genome of a domestic goat (Capra hircus).

              We report the ∼2.66-Gb genome sequence of a female Yunnan black goat. The sequence was obtained by combining short-read sequencing data and optical mapping data from a high-throughput whole-genome mapping instrument. The whole-genome mapping data facilitated the assembly of super-scaffolds >5× longer by the N50 metric than scaffolds augmented by fosmid end sequencing (scaffold N50 = 3.06 Mb, super-scaffold N50 = 16.3 Mb). Super-scaffolds are anchored on chromosomes based on conserved synteny with cattle, and the assembly is well supported by two radiation hybrid maps of chromosome 1. We annotate 22,175 protein-coding genes, most of which were recovered in the RNA-seq data of ten tissues. Comparative transcriptomic analysis of the primary and secondary follicles of a cashmere goat reveal 51 genes that are differentially expressed between the two types of hair follicles. This study, whose results will facilitate goat genomics, shows that whole-genome mapping technology can be used for the de novo assembly of large genomes.
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                Author and article information

                Contributors
                fbert@iastate.edu , franb@dtu.dk
                taina.figueiredo@cragenomica.es
                gmarras@uoguelph.ca
                ezequielluis.nicolazzi@gmail.com
                mfrothsc@iastate.edu
                marcel.Amills@uab.cat
                Journal
                Genet Sel Evol
                Genet. Sel. Evol
                Genetics, Selection, Evolution : GSE
                BioMed Central (London )
                0999-193X
                1297-9686
                19 November 2018
                19 November 2018
                2018
                : 50
                : 59
                Affiliations
                [1 ]ISNI 0000 0004 1936 7312, GRID grid.34421.30, Department of Animal Science, , Iowa State University, ; Ames, IA 50011 USA
                [2 ]ISNI 0000 0001 2181 8870, GRID grid.5170.3, National Institute of Aquatic Resources, , Technical University of Denmark (DTU), ; Lyngby, 2800 Denmark
                [3 ]GRID grid.7080.f, Centre for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, , Campus, Universitat Autonoma de Barcelona, ; 08193 Bellaterra, Barcelona Spain
                [4 ]ISNI 0000 0004 0604 0732, GRID grid.425375.2, Fondazione Parco Tecnologico Padano (PTP), ; 26900 Lodi, Italy
                Author information
                http://orcid.org/0000-0003-4181-3895
                Article
                424
                10.1186/s12711-018-0424-8
                6241033
                30449279
                de740823-9d03-4d34-b2be-8792e0943e1e
                © The Author(s) 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 22 November 2017
                : 15 October 2018
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Genetics
                Genetics

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