Search

By its paternal transmission, Y-chromosomal haplotypes are sensitive markers of population history and male-mediated introgression. We used whole-genome sequences (WGSs) of 386 domestic goats from 75 modern breeds and 7 wild goat species generated by the VarGoats goat genome project. Phylogenetic analyses indicated five domestic haplogroups Y1AA, Y1AB, Y1B, Y2A and Y2B. Haplogroup distributions for 180 domestic breeds indicate ancient paternal population bottlenecks during the migration into northern Europe, southern Asia and Africa. Sharing of haplogroups reveals male-mediated introgressions: from Asia into Madagascar and, more recently, into the South-African Boer goat; then from this breed into other southeastern African goats; and from Europe into native Korean and Ugandan goats. This study illustrates the power of the Y-chromosomal variation for the reconstructing the history of domestic species with a wide geographic range.

By their paternal transmission, Y-chromosomal haplotypes are sensitive markers of population history and male-mediated introgression. Previous studies identified biallelic single-nucleotide variants in the SRY, ZFY and DDX3Y genes, which in domestic goats identified four major Y-chromosomal haplotypes, Y1A, Y1B, Y2A and Y2B, with a marked geographical partitioning. Here, we extracted goat Y-chromosomal variants from whole-genome sequences of 386 domestic goats (75 breeds) and seven wild goat species, which were generated by the VarGoats goat genome project. Phylogenetic analyses indicated domestic haplogroups corresponding to Y1B, Y2A and Y2B, respectively, whereas Y1A is split into Y1AA and Y1AB. All five haplogroups were detected in 26 ancient DNA samples from southeast Europe or Asia. Haplotypes from present-day bezoars are not shared with domestic goats and are attached to deep nodes of the trees and networks. Haplogroup distributions for 186 domestic breeds indicate ancient paternal population bottlenecks and expansions during migrations into northern Europe, eastern and southern Asia, and Africa south of the Sahara. In addition, sharing of haplogroups indicates male-mediated introgressions, most notably an early gene flow from Asian goats into Madagascar and the crossbreeding that in the 19th century resulted in the popular Boer and Anglo-Nubian breeds. More recent introgressions are those from European goats into the native Korean goat population and from Boer goat into Uganda, Kenya, Tanzania, Malawi and Zimbabwe. This study illustrates the power of the Y-chromosomal variants for reconstructing the history of domestic species with a wide geographical range.

By its paternal transmission, Y-chromosomal haplotypes are sensitive markers of population history and male-mediated introgression. We used whole-genome sequences (WGSs) of 386 domestic goats from 75 modern breeds and 7 wild goat species generated by the VarGoats goat genome project. Phylogenetic analyses indicated five domestic haplogroups Y1AA, Y1AB, Y1B, Y2A and Y2B. Haplogroup distributions for 180 domestic breeds indicate ancient paternal population bottlenecks during the migration into northern Europe, southern Asia and Africa. Sharing of haplogroups reveals male-mediated introgressions: from Asia into Madagascar and, more recently, into the South-African Boer goat ; then from this breed into other southeastern African goats ; and from Europe into native Korean and Ugandan goats. This study illustrates the power of the Y-chromosomal variation for the reconstructing the history of domestic species with a wide geographic range.

[Background]: Since their domestication 10,500 years ago, goat populations with distinctive genetic backgrounds have adapted to a broad variety of environments and breeding conditions. The VarGoats project is an international 1000-genome resequencing program designed to understand the consequences of domestication and breeding on the genetic diversity of domestic goats and to elucidate how speciation and hybridization have modeled the genomes of a set of species representative of the genus Capra., [Findings]: A dataset comprising 652 sequenced goats and 507 public goat sequences, including 35 animals representing eight wild species, has been collected worldwide. We identified 74,274,427 single nucleotide polymorphisms (SNPs) and 13,607,850 insertion-deletions (InDels) by aligning these sequences to the latest version of the goat reference genome (ARS1). A Neighbor-joining tree based on Reynolds genetic distances showed that goats from Africa, Asia and Europe tend to group into independent clusters. Because goat breeds from Oceania and Caribbean (Creole) all derive from imported animals, they are distributed along the tree according to their ancestral geographic origin., [Conclusions]: We report on an unprecedented international effort to characterize the genome-wide diversity of domestic goats. This large range of sequenced individuals represents a unique opportunity to ascertain how the demographic and selection processes associated with post-domestication history have shaped the diversity of this species. Data generated for the project will also be extremely useful to identify deleterious mutations and polymorphisms with causal effects on complex traits, and thus will contribute to new knowledge that could be used in genomic prediction and genome-wide association studies., We are grateful to France Génomique “Call for high impact projects” (ANR‐10‐INBS‐09‐08) for selecting our project and providing us the resources to sequence 400 goats. We would like to mention that APIS-GENE funded some WGS sequences through ACTIVEGOAT & CAPRISNP projects. We thank the Occitanie region and the Animal Genetics Division of the French National Institute for Agriculture, Food and Environment (INRAE-GA) for financing the PhD of ET. We thank the Ministère de l'Enseignement supérieur, de la Recherche et de l'Innovation for financing LD. We thank André Eggen (Illumina) for providing chips to genotype 192 animals. We thank the Animal Genetics Division of the French National Institute for Agriculture, Food and Environment (INRAE-GA) for funding VarGoats2 grant, which allowed DNA extraction and genotyping of 384 animals and CRB-Anim, Grant Agreement ANR-11-INBS-0003, (https://crb-anim.fr/) for funding French local breeds sampling. We thank the Italian Goat and Sheep Breeders Association (AssoNaPa) for supporting in sampling. Whole-genome sequencing libraries for the African goats were prepared and sequenced by Edinburgh Genomics and funded via Biotechnology and Biological Sciences Research Council research grant (BBS/OS/GC/000012F) ‘Reference genome and population sequencing of African goats’ awarded to The Roslin Institute. USDA-ARS with funding from USAID funded the collection of samples from Uganda, Tanzania, Malawi, Mozambique and Zimbabwe. EC and MS were partially supported by the Bill & Melinda Gates Foundation and with UK aid from the UK Government’s Department for International Development (Grant Agreement OPP1127286) under the auspices of the Centre for Tropical Livestock Genetics and Health (CTLGH), established jointly by the University of Edinburgh, SRUC (Scotland’s Rural College), and the International Livestock Research Institute. The findings and conclusions contained within are those of the authors and do not necessarily reflect positions or policies of the Bill & Melinda Gates Foundation nor the UK Government.

Since its introduction, landscape genomics has developed quickly with the increasing availability of both molecular and topo-climatic data. The current challenges of the field mainly involve processing large numbers of models and disentangling selection from demography. Several methods address the latter, either by estimating a neutral model from population structure or by inferring simultaneously environmental and demographic effects. Here we present Sam$\beta$ada, an integrated approach to study signatures of local adaptation, providing rapid processing of whole genome data and enabling assessment of spatial association using molecular markers. Specifically, candidate loci to adaptation are identified by automatically assessing genome-environment associations. In complement, measuring the Local Indicators of Spatial Association (LISA) for these candidate loci allows to detect whether similar genotypes tend to gather in space, which constitutes a useful indication of the possible kinship relationship between individuals. In this paper, we also analyze SNP data from Ugandan cattle to detect signatures of local adaptation with Sam$\beta$ada, BayEnv, LFMM and an outlier method (FDIST approach in Arlequin) and compare their results. Sam$\beta$ada is an open source software for Windows, Linux and MacOS X available at \url{http://lasig.epfl.ch/sambada}, Comment: 1 figure in text, 1 figure in supplementary material The structure of the article was modified and some explanations were updated. The methods and results presented are the same as in the previous version

International audience; The AdaptMap project investigates worldwide goat diversity with a focus on domestication, adaptation associated with local environmental conditions, and adaptation in response to selection for production systems. The ultimate goal of the project is to enable sustainable goat breeding by leveraging the use of genomic information. During the first phase of AdaptMap, several analyses were performed to characterize population genetics and history, to identify selection signatures and signals of environmental adaptation through landscape genomics, and to devise a panel of SNPs for parentage assessment. Overall, our results showed a close association between the distribution of diversity and geography, with a clear partitioning of the populations into groups according to the continental origin. The 3 major gene pools corresponded to goats from Europe, Africa and western Asia, a pattern consistent with the recognized paths of human migration out of the Fertile Crescent. Within these major pools, further patterns of variation mirrored geographical sub-structuring, human history and animal husbandry practices. Comparing the European and African gene pools, European breeds tended to be more discreet, in line with the practice of creating breeds through active human-controlled genetic isolation, while greater gene flow was observed in Africa. Among the observed “hotspots” of runs of homozygosity, some were unique across continental groups. The results of selection signature analysis were generally consistent with previous evidence from independent studies. Signals of adaptation to the environment were also identified, showing the strongest association with differences in mean annual temperature. Finally, a highly informative marker panel for parentage assessment was developed to assist breeding in goat populations worldwide. Taken together, our evidence outlines a remarkable diversity occurring at the global scale, locally partitioned and often affected by introgression from cosmopolitan breeds. This provides a useful framework to direct improvement and conservation actions, and to select breeding targets. After excluding under-performing samples and markers, 970 targeted markers with 50X sequence coverage or greater and an overall average call rate of 98% were included in the data set. Furthermore, novel genetic mutations identified in these important targeted regions were characterized. Data from this panel can be used to identify known causative mutations, improve pedigree accuracy and assist in genetic selection for the sheep industry at a cost of US$15. The application of this cost-effective sheep genomics marker panel can be used to promote improved production, animal health and profitability of the US sheep industry.

Made available in DSpace on 2019-10-06T15:24:30Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-11-19 Background: Since goat was domesticated 10,000 years ago, many factors have contributed to the differentiation of goat breeds and these are classified mainly into two types: (i) adaptation to different breeding systems and/or purposes and (ii) adaptation to different environments. As a result, approximately 600 goat breeds have developed worldwide; they differ considerably from one another in terms of phenotypic characteristics and are adapted to a wide range of climatic conditions. In this work, we analyzed the AdaptMap goat dataset, which is composed of data from more than 3000 animals collected worldwide and genotyped with the CaprineSNP50 BeadChip. These animals were partitioned into groups based on geographical area, production uses, available records on solid coat color and environmental variables including the sampling geographical coordinates, to investigate the role of natural and/or artificial selection in shaping the genome of goat breeds. Results: Several signatures of selection on different chromosomal regions were detected across the different breeds, sub-geographical clusters, phenotypic and climatic groups. These regions contain genes that are involved in important biological processes, such as milk-, meat- or fiber-related production, coat color, glucose pathway, oxidative stress response, size, and circadian clock differences. Our results confirm previous findings in other species on adaptation to extreme environments and human purposes and provide new genes that could explain some of the differences between goat breeds according to their geographical distribution and adaptation to different environments. Conclusions: These analyses of signatures of selection provide a comprehensive first picture of the global domestication process and adaptation of goat breeds and highlight possible genes that may have contributed to the differentiation of this species worldwide. Department of Animal Science Iowa State University National Institute of Aquatic Resources Technical University of Denmark (DTU) GenPhySE INRA Université de Toulouse INPT ENVT Dipartimento di Medicina Veterinaria Università Degli Studi di Milano Laboratory of Geographic Information Systems (LASIG) School of Architecture Civil and Environmental Engineering (ENAC) Ecole Polytechnique Fédérale de Lausanne (EPFL) Recombinetics Inc Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria (CREA) Research Centre for Animal Production and Acquaculture Centre for Research in Agricultural Genomics (CRAG) CSIC-IRTA-UAB-UB Campus Universitat Autonoma de Barcelona DIANA Dipartimento di Scienze Animali della Nutrizione e Degli Alimenti Università Cattolica Del S. Cuore BioDNA Centro di Ricerca sulla Biodiversità e sul DNA Antico Università Cattolica Del S. Cuore Fondazione Parco Tecnologico Padano (PTP) Department of Support Production and Animal Health School of Veterinary Medicine São Paulo State University (UNESP) Animal Genomics and Improvement Laboratory ARS USDA Center for Quantitative Genetics and Genomics Aarhus University Department of Support Production and Animal Health School of Veterinary Medicine São Paulo State University (UNESP)

The 90K Affymetrix Axiom® Buffalo Genotyping Array has been used to genotype river buffalo samples from Pakistan, Iran, Turkey, Egypt, Romania, Bulgaria, Italy, Mozambique, Brazil and Colombia, and swamp buffaloes from China, Thailand, Philippines, Indonesia and Brazil. Model-based clustering algorithms (Admixture and FastStructure software) and graph tools (Treemix and network analysis) have been applied to SNP data to evaluate the levels of molecular diversity and to highlight population structure and migration events. The best-fitting resolution devised by Bayesian clustering highlighted three distinct gene pools in pure river as well as in pure swamp buffalo populations, together with some genomic admixture occurring in the Philippines and in Brazil, in agreement with documented importations of animals for breed improvement purposes. The Mediterranean buffalo and the Carabao breed from Brazil represent the most differentiated gene pools within the river and swamp group, respectively, which is most likely due to genetic bottlenecks, isolation and selection. Gene flow events, evidenced by Treemix and Network analyses, highlighted a likely contribution from the river buffalo gene pool to the admixed swamp populations and, within river buffaloes, from the Mediterranean to the breeds from Colombia and Brazil. When evaluated in a geographical framework, the results of our analyses support archeozoological evidence for the domestication of river and swamp buffalo in the Indian subcontinent and in Southeast Asia, respectively, and furthermore revealed some unexpected patterns of migration, which suggest that the spread of domestic buffaloes out of the domestication center may have followed alternative migration routes.

After sequencing the Buffalo genome, the International Buffalo Consortium has used the derived 90K Affymetrix Axiom® Buffalo Genotyping Array to characterize a set of river buffaloes from Pakistan, Iran, Turkey, Egypt, Romania, Bulgaria, Italy, Mozambique, Brazil and Colombia, and swamp buffaloes from China, Thailand, Philippines, Indonesia and Brazil. SNP genotype data have been analyzed with Bayesian clustering algorithms (ADMIXTURE software), multivariate statistics (Multi- Dimensional Scaling plots) and graph tools highlighting population splits and migration events (TREEMIX software) to estimate the levels of molecular diversity, population structure and the historical relationships among populations. When placed in the geographical context, the patterns of diversity confirmed archeozoological evidence for the domestication of river and swamp buffalo in the Indian subcontinent and in Southeast Asia, respectively, and provided hints on buffalo migrations and history. Admixture analysis revealed the presence of three main gene pools in pure river buffalo populations: one characterizes the breeds from the Indian subcontinent (Pakistan) and those recently exported from there to Bulgaria, Brazil and Colombia; the second includes breeds that, from the domestication center, spread westwards to Iran, Egypt and Turkey; the third includes the Italian Mediterranean buffalo, sampled both in Italy and in Mozambique where it has recently been exported. Among the breeds analysed, Mediterranean buffalo represents the most differentiated river buffalo gene pool, which is most likely due to genetic bottlenecks, isolation, selection and possible genetic contributions from breeds not included in our sampling. Four gene pools have been identified in pure swamp buffalo populations: the first from China; the second in Indonesian islands, other than Sumatra; the third in the Philippines and the fourth in Thailand and Sumatra. Some level of admixture is seen between river and swamp buffalo in the Philippines and in Brazil. TREEMIX software analyses confirmed the gene flows identified by Bayesian population structure analysis including those from the river buffalo gene pool to the admixed swamp populations and, within river buffaloes, from the Mediterranean to the breeds from Colombia and Brazil. Furthermore, these analyses revealed some unexpected migration patterns, which suggest that the westward spread of domestic buffaloes may have followed alternative migration routes.

The Italian Goat Consortium (IGC), joined the effort of many Universities and Research Institutes, in a comprehensive study of the Italian goat population genetic makeup using a medium density (54K) SNPs chip. Currently IGC has geno- typed more than 1,000 animals from more than 30 goat breeds and populations from all Italian geographical and agro- ecological areas of goat rearing. The aim of this work is to obtain a clear picture of the Italian caprine biodiversity, to reconstruct the ancestry, to disentangle the genetic background and to assess the relationships among and within the investigated breeds. To date, the IGC dataset includes about 50 million genotypes. The data were quality checked by excluding markers and individuals on the basis of missing genotypes, minor allele frequency and close individual relatedness. Genetic relationships among and within breeds was investigated by Multi-Dimensional Scaling and Principal Component Analysis. Population structure, ancestry models and admixture were estimated by ADMIXTURE and fastSTRUCTURE software. Finally, phylogenic trees were recon- structed with PHYLIP software suite starting from shared-allele identity by state, and Reynolds distance matrices, while past migration events were modeled with TreeMix software. The results confirmed high levels of genetic polymorphism and confirmed the North-South geographical pattern of diver- sity, previously reported on a smaller sample of Italian goat breeds. The analysis also revealed a pivotal role of Central Italy in connecting the genetic resources of the northern and southern areas of the country, and confirms the genetic isola- tion of insular breeds. Moreover, some breeds show clearly distinctive and homogeneous gene pools, whereas other breeds present complex and, in some cases, dishomogeneous genetic background. Even if "A breed is a group of domestic animals, termed such by common consent of the breeders" (Lush J.L., 1994), genomic tools are useful in understanding the genetic back- ground of populations and in defining their relationships or uniqueness. These tools can complement the traditional ones in providing farmers and their associations a powerful aid for a more conscious management of goat populations and their biodiversity.

The investigation of genetic diversity at molecular level has been proposed as a valuable complement and sometimes proxy to phenotypic diversity of local breeds and is presently considered as one of the FAO priorities for breed characterization. By recommending a set of selected molecular markers for each of the main livestock species, FAO has promoted the meta-analysis of local datasets, to achieve a global view of molecular genetic diversity. Analysis within the EU Globaldiv project of two large goat microsatellite datasets produced by the Econogene Consortium and the IAEA CRP-Asia Consortium, respectively, has generated a picture of goat diversity across continents. This indicates a gradient of decreasing diversity from the domestication centre towards Europe and Asia, a clear phylogeographic structure at the continental and regional levels, and in Asia a limited genetic differentiation among local breeds. The development of SNP panels that assay thousands of markers and the whole genome sequencing of livestock permit an affordable use of genomic technologies in all livestock species, goats included. Preliminary data from the Italian Goat Consortium indicate that the SNP panel developed for this species is highly informative. The existing panel can be improved by integrating additional SNPs identified from the whole genome sequence alignment of goats adapted to extreme climates. Part of this effort is being achieved by international projects (e.g. EU FP7 NextGen and 3SR projects), but a fair representation of the global diversity in goats requires a large panel of samples (i.e. as in the recently launched 1000 cattle genomes initiative). Genomic technologies offer new strategies to investigate complex traits difficult to measure. For example, the comparison of patterns of diversity among the genomes in selected groups of animals (e.g. adapted to different environments) and the integration of genome-wide diversity with new GIScience-based methods are able to identify molecular markers associated with genomic regions of putative importance in adaptation and thus pave the way for the identification of causative genes. Goat breeds adapted to different production systems in extreme and harsh environments will play an important role in this process. The new sequencing technologies also permit the analysis of the entire mitochondrial genome at maximum resolution. The complete mtDNA sequence is now the common standard format for the investigation of human maternal lineages. A preliminary analysis of the complete goat mtDNA genome supports a single Neolithic origin of domestic goats rather than multiple domestication events in different geographic areas.

Background\ud During the past decades, neutral DNA markers have been extensively employed to study demography, population genetics and structure in livestock, but less interest has been devoted to the evaluation of livestock adaptive potential through the identification of genomic regions likely to be under natural selection.\ud \ud Methodology/Principal findings\ud Landscape genomics can greatly benefit the entire livestock system through the identification of genotypes better adapted to specific or extreme environmental conditions. Therefore we analyzed 101 AFLP markers in 43 European and Western Asian goat breeds both with Matsam software, based on a correlative approach (SAM), and with Mcheza and Bayescan, two FST based software able to detect markers carrying signatures of natural selection.\ud \ud Matsam identified four loci possibly under natural selection – also confirmed by FST-outlier methods – and significantly associated with environmental variables such as diurnal temperature range, frequency of precipitation, relative humidity and solar radiation.\ud \ud Conclusions/Significance\ud These results show that landscape genomics can provide useful information on the environmental factors affecting the adaptive potential of livestock living in specific climatic conditions. Besides adding conservation value to livestock genetic resources, this knowledge may lead to the development of novel molecular tools useful to preserve the adaptive potential of local breeds during genetic improvement programs, and to increase the adaptability of industrial breeds to changing environments.

The Italian Goat Consortium was established from the Innovagen Project to join local efforts and resources for the genomic characterisation of Italian goat breeds. Thirteen Italian goat breeds (Valdostana, Saanen, Orobica, Bionda dell'Adamello, Val Passiria, Grigia Ciociara, Teramana, Nicastrese, Aspromontana, Girgentana, Argentata dell'Etna, Sarda and Maltese - the latter sampled in Sardinia and Sicily) for a total of 350 animals (15-32 per breed) were analysed using a medium density SNP array. Data editing was based on the following thresholds: MAF 5%; Missing animal >5%; HW within breed FDR >20%. After filtering, a total of 51,136 SNPs were retained, showing that the adopted SNP chip is highly informative for the characterization of Italian goat breeds. Population structure and breed distinctiveness were investigated with the software Admixture, that revealed the best fitting solution at K=11 partitions. The software also highlighted variable levels of admixture and an early differentiation of Val Passiria, Orobica, Valdostana, Teramana, Girgentana and Sarda breeds. Within MDS plot, some breeds are clearly appreciable as distinct: Girgentana, Teramana, Orobica and Maltese. PCA analysis revealed a gradient of diversity North (from alpine breeds) - South (to Sicilian breeds) and East (from Val Passiria breed) - West (to Valdostana breed) in the Alps. The calculation of Fis index indicated little or no inbreeding, while LD analysis in Chromosome 6 showed levels of disequilibrium much lower than cattle at short physical distance.