VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity.

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.

In silico identification of variations in microRNAs with a potential impact on dairy traits using whole ruminant genome SNP datasets.

MicroRNAs are small noncoding RNAs that have important roles in the lactation process and milk biosynthesis. Some polymorphisms have been studied in various livestock species from the perspective of pathology or production traits. To target variants that could be the causal variants of dairy traits, genetic variants of microRNAs expressed in the mammary gland or present in milk and localized in dairy quantitative trait loci (QTLs) were investigated in bovine, caprine, and ovine species. In this study, a total of 59,124 (out of 28 millions), 13,427 (out of 87 millions), and 4761 (out of 38 millions) genetic variants in microRNAs expressed in the mammary gland or present in milk were identified in bovine, caprine, and ovine species, respectively. A total of 4679 of these detected bovine genetic variants are located in dairy QTLs. In caprine species, 127 genetic variants are localized in dairy QTLs. In ovine species, no genetic variant was identified in dairy QTLs. This study leads to the detection of microRNA genetic variants of interest in the context of dairy production, taking advantage of whole genome data to identify microRNA genetic variants expressed in the mammary gland and localized in dairy QTLs.

Analysis of Polycerate Mutants Reveals the Evolutionary Co-option of HOXD1 for Horn Patterning in Bovidae.

In the course of evolution, pecorans (i.e., higher ruminants) developed a remarkable diversity of osseous cranial appendages, collectively referred to as "headgear," which likely share the same origin and genetic basis. However, the nature and function of the genetic determinants underlying their number and position remain elusive. Jacob and other rare populations of sheep and goats are characterized by polyceraty, the presence of more than two horns. Here, we characterize distinct POLYCERATE alleles in each species, both associated with defective HOXD1 function. We show that haploinsufficiency at this locus results in the splitting of horn bud primordia, likely following the abnormal extension of an initial morphogenetic field. These results highlight the key role played by this gene in headgear patterning and illustrate the evolutionary co-option of a gene involved in the early development of bilateria to properly fix the position and number of these distinctive organs of Bovidae.

Comparison of the response of mammary gland tissue from two divergent lines of goat with high and low milk somatic cell scores to an experimental Staphylococcus aureus infection.

Mastitis represents one of the major economic and health threats to the livestock sector associated with reduction in milk quality, loss of production and is a major reason for culling. Somatic cell score (SCS) is used as a criterion in breeding programmes to select cows genetically less susceptible to mastitis. The relevance of SCS as a predictor of udder health and susceptibility to mastitis is still untested in goats. In this study, two lines of French Alpine goats selected for extreme breeding values for somatic cell scores, one line with high SCS (HSCS) and the other with low SCS (LSCS), were used to test the hypothesis that the mammary response and function differed between the lines. The aim of the present study was to investigate differences in the early immune response in caprine mammary gland tissues challenged with Staphylococcus aureus, one of the main pathogens responsible for the intra-mammary infection in small ruminants, using transcriptomic and histopathology analyses. The comparison between HSCS and LSCS goat lines, showed differences in the response at the histological level for inflammation, presence of neutrophils and micro-abscess formation, and at the molecular level in the expression of CXCL8, IL-6, NFKBIZ and IL-1ß. CXCL8 and CXCL2 genes, which showed a higher level of expression in the experimentally infected HSCS line. The molecular data and histopathology both suggested that following S. aureus infection, mobilization, recruitment, infiltration, and chemotaxis of neutrophil, leads to a more severe inflammation in the HSCS compared to LSCS animals. Our results represent an initial basis for further studies to unravel the genetic basis of early mastitis inflammatory responses and the selection of dairy animals more resistant to bacterial mastitis.

Using sequence variants of a QTL region improves the accuracy of genomic evaluation in French Saanen goats.

The enhanced availability of sequence data in livestock provides an opportunity for more accurate predictions in routine genomic evaluations. Such evaluations would therefore no longer rely only on the linkage disequilibrium between a chip marker and the causal mutation. The objective of this study was to assess the usefulness of sequence data in Saanen goats (n = 33) to better capture a quantitative trait locus (QTL) on chromosome 19 (CHI19) and improve the accuracy of predictions for 3 milk production traits, 5 type traits, and somatic cell scores. All 1,207 50K genotypes were imputed to the sequence level. Four scenarios, each using a subset of CHI19 imputed variants, were then tested. Sequence-derived information included all CHI19 variants (529,576), all variants in the QTL region (22,269), 178 variants selected in the QTL region and added to an updated chip, or 178 randomly selected variants on CHI19. Two genomic evaluation models were applied: single-step genomic BLUP and weighted single-step genomic BLUP. All scenarios were compared with single-step genomic BLUP using 50K genotypes. Best overall results were obtained using single-step genomic BLUP on 50K genotypes completed with all variants in the QTL region of chromosome 19 (6.2% average increase in accuracy for 9 traits) with the highest accuracy gain for fat yield (17.9%), significant increases for milk (13.7%) and protein yields (12.5%), and type traits associated with CHI19. Despite its association with the QTL region of chromosome 19, the somatic cell score showed decreased accuracy in every alternative scenario. Using all CHI19 variants led to an overall decrease of 4.8% in prediction accuracy. The updated chip was efficient and improved genomic evaluations by 3.1 to 6.4% on average, depending on the scenario. Indeed, information from only a few carefully selected variants increased accuracies for traits of interest when used in a single-step genomic BLUP model. In conclusion, using QTL region variants imputed from sequence data in single-step genomic evaluations represents a promising perspective for such evaluations in dairy goats. Furthermore, using only a limited number of selected variants in QTL regions, as available on SNP chip updates, significantly increases the accuracy for QTL-associated traits without deteriorating the evaluation accuracy for other traits. The latter approach is interesting, as it avoids time-consuming imputation and data formatting processes and provides reliable genotypes.

Genomic predictions based on haplotypes fitted as pseudo-SNP for milk production and udder type traits and SCS in French dairy goats.

The development of statistical methods aiming to improve the accuracy of genomic predictions is of utmost value for dairy goat breeding programs. In this context, the use of haplotypes, instead of individual SNP, could improve the accuracy of genomic predictions by better capturing the effect of causal variants, instead of relying solely on linkage disequilibrium with individual SNP. Haplotypes can be included in genomic evaluation models in various ways, such as fitting them as pseudo-SNP (i.e., haplotypes converted into biallelic SNP format). This can be easily incorporated in the software already available for single-step genomic predictions (ssGBLUP). Therefore, the aim of this study was to compare the predictive performances of ssGBLUP and weighted ssGBLUP (WssGBLUP) based on individual SNP or on haplotypes fitted as pseudo-SNP. Performance was compared in terms of accuracy, bias, and weights for SNP versus pseudo-SNP. Genomic predictions were performed on 5 milk production traits, 5 udder type traits, and somatic cell score (SCS). The training population was formed by 307 Alpine and 247 Saanen progeny-tested bucks, genotyped using the Illumina Goat SNP50 BeadChip (Illumina, San Diego, CA). The validation population included 205 Alpine and 146 Saanen young bucks. The accuracy of genomic predictions was evaluated in the validation population as the Pearson correlation between genomic estimated breeding values (GEBV), predicted based on various methods, and daughter deviation (DD) based on the official genetic evaluation of January 2016. Haplotype-based models were shown to improve the performance of genomic predictions for some traits. Gains in accuracy of up to +19% (0.310 to 0.368 for fat yield) in Alpine and up to +3% (0.361 to 0.373 for udder shape) in Saanen were observed with ssGBLUP. The ssGBLUP accuracies averaged across all traits and methods were equal to 0.467 (SNP) versus 0.471 (pseudo-SNP) in Alpine and 0.528 (SNP) versus 0.523 (pseudo-SNP) in Saanen. With WssGBLUP, gains in accuracy of up to 24% (0.298 to 0.370 for fat yield) in Alpine and 14% (0.431 to 0.490 for SCS) in Saanen were observed with WssGBLUP. Accuracies of WssGBLUP averaged across all traits and methods were equal to 0.455 (SNP and pseudo-SNP) in Alpine and 0.542 (SNP) versus 0.528 (pseudo-SNP) in Saanen. The average (±SD) slope of the regression of DD on GEBV for the validation animals, across all breeds, traits and scenarios, were equal to 0.82 ± 0.20 (SNP) and 0.83 ± 0.18 (pseudo-SNP) for ssGBLUP and 0.67 ± 0.16 (SNP) and 0.65 ± 0.16 (pseudo-SNP) for WssGBLUP, which suggest that haplotype-based models and ssGBLUPSNP were similarly biased. However, WssGBLUP was more biased than ssGBLUP, and its gains in accuracies were limited to milk production traits. Despite the fact that genomic predictions based on haplotypes require additional steps and time, the observed gains in GEBV predictive performance indicate that haplotype-based methods could be recommended for some traits.

Genome wide association analysis on semen volume and milk yield using different strategies of imputation to whole genome sequence in French dairy goats.

BACKGROUND: Goats were domesticated 10,500 years ago to supply humans with useful resources. Since then, specialized breeds that are adapted to their local environment have been developed and display specific genetic profiles. The VarGoats project is a 1000 genomes resequencing program designed to cover the genetic diversity of the Capra genus. In this study, our main objective was to assess the use of sequence data to detect genomic regions associated with traits of interest in French Alpine and Saanen breeds. RESULTS: Direct imputation from the GoatSNP50 BeadChip genotypes to sequence level was investigated in these breeds using FImpute and different reference panels: within-breed, all Capra hircus sequenced individuals, European goats and French mainland goats. The best results were obtained with the French goat panel with allele and genotype concordance rates reaching 0.86 and 0.75 in the Alpine and 0.86 and 0.73 in the Saanen breed respectively. Mean correlations tended to be low in both breeds due to the high proportion of variants with low frequencies. For association analysis, imputation was performed using FImpute for 1129 French Alpine and Saanen males using within-breed and French panels on 23,338,436 filtered variants. The association results of both imputation scenarios were then compared. In Saanen goats, a large region on chromosome 19 was significantly linked to semen volume and milk yield in both scenarios. Significant variants for milk yield were annotated for 91 genes on chromosome 19 in Saanen goats. For semen volume, the annotated genes include YBOX2 which is related to azoospermia or oligospermia in other species. New signals for milk yield were detected on chromosome 2 in Alpine goats and on chromosome 5 in Saanen goats when using a multi-breed panel. CONCLUSION: Even with very small reference populations, an acceptable imputation quality can be achieved in French dairy goats. GWAS on imputed sequences confirmed the existence of QTLs and identified new regions of interest in dairy goats. Adding identified candidates to a genotyping array and sequencing more individuals might corroborate the involvement of identified regions while removing potential imputation errors.

Alternative methods improve the accuracy of genomic prediction using information from a causal point mutation in a dairy sheep model.

BACKGROUND: Genomic evaluation is usually based on a set of markers assumed to be linked with causal mutations. Selection and precise management of major genes and the remaining polygenic component might be improved by including causal polymorphisms in the evaluation models. In this study, various methods involving a known mutation were used to estimate prediction accuracy. The SOCS2 gene, which influences body growth, milk production and somatic cell scores, a proxy for mastitis, was studied as an example in dairy sheep. METHODS: The data comprised 1,503,148 phenotypes and 9844 54K SNPs genotypes. The SOCS2 SNP was genotyped for 4297 animals and imputed in the above 9844 animals. Breeding values and their accuracies were estimated for each of nine traits by using single-step approaches. Pedigree-based BLUP, single-step genomic BLUP (ssGBLUP) involving the 54K ovine SNPs chip, and four weighted ssGBLUP (WssGBLUP) methods were compared. In WssGBLUP methods, weights are assigned to SNPs depending on their effect on the trait. The ssGBLUP and WssGBLUP methods were again tested after including the SOCS2 causal mutation as a SNP. Finally, the Gene Content approach was tested, which uses a multiple-trait model that considers the SOCS2 genotype as a trait. RESULTS: EBV accuracies were increased by 14.03% between the pedigree-based BLUP and ssGBLUP methods and by 3.99% between ssGBLUP and WssGBLUP. Adding the SOCS2 SNP to ssGBLUP methods led to an average gain of 0.26%. Construction of the kinship matrix and estimation of breeding values was generally improved by placing emphasis on SNPs in regions with a strong effect on traits. In the absence of chip data, the Gene Content method, compared to pedigree-based BLUP, efficiently accounted for partial genotyping information on SOCS2 as accuracy was increased by 6.25%. This method also allowed dissociation of the genetic component due to the major gene from the remaining polygenic component. CONCLUSIONS: Causal mutations with a moderate to strong effect can be captured with conventional SNP chips by applying appropriate genomic evaluation methods. The Gene Content method provides an efficient way to account for causal mutations in populations lacking genome-wide genotyping.

A validation study of loci associated with mastitis resistance in two French dairy sheep breeds.

BACKGROUND: The identification of loci associated with resistance to mastitis or of the causative mutations may be helpful in breeding programs for dairy sheep as it is for cattle worldwide. Seven genomic regions that control milk somatic cell counts, an indirect indicator of udder infection, have already been identified in sheep (Spanish Churra, French Lacaune and Italian Sardinian-Lacaune backcross populations). In this study, we used a 960 custom-designed ovine single nucleotide polymorphism (SNP) chip in Lacaune and Manech Tête Rousse dairy sheep to validate these seven genomic regions associated with mastitis. RESULTS: The most significant SNP (rs868996547) on Ovis aries chromosome (OAR) 3 was a previously described mutation in the suppressor of cytokine signalling 2 (SOCS2) gene. An antagonist effect of this causal candidate between health and growth in Lacaune sheep was confirmed. Effects of the mutation on the infectious status of the udder, i.e. increases in milk somatic cell counts and bacteria shedding, were also identified. This SNP was not present in the data available on Manech Tête Rousse. Three other regions associated with mastitis were also confirmed on OAR16 (Manech Tête Rousse), 19 (Lacaune) and 2 (both breeds). For the OAR2 region, we validated previously detected SNPs in several other breeds (Sarda, Churra, and Chios). For significant SNPs in the four mastitis regions, the effect varied from 0.24 to 0.67 phenotypic standard deviation of the traits. Two of the mastitis quantitative trait loci (QTL) regions (OAR2 and 16) that we validated here were also associated in opposite ways with milk production traits in both populations. CONCLUSIONS: These results indicate, at least in part, a genomic basis for the trade-off between milk production and mastitis resistance. Four of the seven mastitis QTL regions that were previously identified in independent populations, were confirmed in this study, which demonstrates partial sharing of mastitis-related genetic mechanisms between different distant dairy sheep populations.

Diversity of copy number variation in the worldwide goat population.

Goats (Capra hircus) are an important farm animal species. Copy number variation (CNV) represents a major source of genomic structural variation. We investigated the diversity of CNV distribution in goats using CaprineSNP50 genotyping data generated by the ADAPTmap Project. We identified 6286 putative CNVs in 1023 samples from 50 goat breeds using PennCNV. These CNVs were merged into 978 CNV regions, spanning ~262 Mb of total length and corresponding to ~8.96% of the goat genome. We then divided the samples into six subgroups per geographic distribution and constructed a comparative CNV map. Our results revealed a population differentiation in CNV across different geographical areas, including Western Asia, Eastern Mediterranean, Alpine & Northern Europe, Madagascar, Northwestern Africa, and Southeastern Africa groups. The results of a cluster heatmap analysis based on the CNV count per individual across different groups was generally consistent with the one generated from the SNP data, likely reflecting the population history of different goat breeds. We sought to determine the gene content of these CNV events and found several important CNV-overlapping genes (e.g. EDNRA, ADAMTS20, ASIP, KDM5B, ADAM8, DGAT1, CHRNB1, CLCN7, and EXOSC4), which are involved in local adaptations such as coat color, muscle development, metabolic processes, osteopetrosis, and embryonic development. Therefore, this research generated an extensive CNV map in the worldwide population of goat, which offers novel insight into the goat genome and its functional annotation.

Host factors determine the evolution of infection with Staphylococcus aureus to gangrenous mastitis in goats.

Staphylococcus aureus is the major cause of very severe mastitis of dairy goats. The initial objective of our study was to fine-tune an experimental model of infection of the goat mammary gland with two strains of S. aureus and two lines of goats (low and high somatic cell score lines). Following the challenge, the 10 infected goats divided in two clear-cut severity groups, independently of the S. aureus strain and the goat line. Five goats developed very severe mastitis (of which four were gangrenous) characterized by uncontrolled infection (UI group), whereas the other five kept the infection under control (CI group). The outcome of the infection was determined by 18 h post-infection (hpi), as heralded by the bacterial milk concentration at 18 hpi: more than 107/mL in the UI group, about 106/mL in the CI group. Leukocyte recruitment and composition did not differ between the groups, but the phagocytic killing at 18 hpi efficiency did. Contributing factors involved milk concentrations of α-toxin and LukMF' leukotoxin, but not early expression of the genes encoding the pentraxin PTX3, the cytokines IL-1α and IL-1ß, and the chemokines IL-8 and CCL5. Concentrations of TNF-α, IFN-γ, IL-17A, and IL-22 rose sharply in the milk of UI goats when infection was out of control. The results indicate that defenses mobilized by the mammary gland at an early stage of infection were essential to prevent staphylococci from reaching critical concentrations. Staphylococcal exotoxin production appeared to be a consequent event inducing the evolution to gangrenous mastitis.

Author Correction: A genome scan for milk production traits in dairy goats reveals two new mutations in Dgat1 reducing milk fat content.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Genome-wide association mapping for type and mammary health traits in French dairy goats identifies a pleiotropic region on chromosome 19 in the Saanen breed.

Type traits and mammary health traits are important to dairy ruminant breeding because they influence animal health, milking ability, and longevity, as well as the economic sustainability of farms. The availability of the genomic sequence and a single nucleotide polymorphism chip in goats has opened up new fields of investigation to better understand the genes and mechanisms that underlie such complex traits and to be able to select them. Our objective was to perform a genome-wide association study in dairy goats for 11 type traits and somatic cell count (SCC) as proxies for mastitis resistance. A genome-wide association study was implemented using a daughter design composed of 1,941 Alpine and Saanen goats sired by 20 artificial insemination bucks, genotyped with the Illumina GoatSNP50 BeadChip (Illumina Inc., San Diego, CA). This association study was based on both linkage analyses and linkage disequilibrium using QTLmap software (http://dga7.jouy.inra.fr/qtlmap/) interval mapping was performed with the likelihood ratio test using linear regressions. Breeds were analyzed together and separately. The study highlighted 37 chromosome-wide significant quantitative trait loci (QTL) with linkage analyses and 222 genome-wide significant QTL for linkage disequilibrium, for type and SCC traits in dairy goats. Genomic control of those traits was mostly polygenic and breed-specific, suggesting that within-breed selection would be favored for those traits. Of note, Capra hircus autosome (CHI) 19 appeared to be highly enriched in single nucleotide polymorphisms associated with type and SCC, with 2 highly significant regions in the Saanen breed. One region (33-42 Mb) was significantly associated with SCC and includes candidate genes associated with response to intramammary infections (RARA, STAT3, STAT5A, and STAT5B). Another region of the CHI 19 (24.5-27 Mb) exhibited an adverse pleiotropic effect on milk production (milk, fat yield, and protein yield) and udder traits (udder floor position and rear udder attachment) that agreed with the negative genetic correlations that exist between those 2 groups of traits. These QTL were not found in the Alpine breed. In Alpine, the 2 most significant regions were associated with chest depth on CHI 6 (45.8-46.0 Mb) and CHI 8 (80.7-81.1 Mb). These results will be helpful for goat selection in the future and could lead to identification of causal mutations.

Correction: Genome Wide Association Study Identifies New Loci Associated with Undesired Coat Color Phenotypes in Saanen Goats.

[This corrects the article DOI: 10.1371/journal.pone.0152426.].

A genome scan for milk production traits in dairy goats reveals two new mutations in Dgat1 reducing milk fat content.

The quantity of milk and milk fat and proteins are particularly important traits in dairy livestock. However, little is known about the regions of the genome that influence these traits in goats. We conducted a genome wide association study in French goats and identified 109 regions associated with dairy traits. For a major region on chromosome 14 closely associated with fat content, the Diacylglycerol O-Acyltransferase 1 (DGAT1) gene turned out to be a functional and positional candidate gene. The caprine reference sequence of this gene was completed and 29 polymorphisms were found in the gene sequence, including two novel exonic mutations: R251L and R396W, leading to substitutions in the protein sequence. The R251L mutation was found in the Saanen breed at a frequency of 3.5% and the R396W mutation both in the Saanen and Alpine breeds at a frequencies of 13% and 7% respectively. The R396W mutation explained 46% of the genetic variance of the trait, and the R251L mutation 6%. Both mutations were associated with a notable decrease in milk fat content. Their causality was then demonstrated by a functional test. These results provide new knowledge on the genetic basis of milk synthesis and will help improve the management of the French dairy goat breeding program.

Whole blood transcriptome analysis reveals potential competition in metabolic pathways between negative energy balance and response to inflammatory challenge.

Negative Energy Balance (NEB) is considered to increase susceptibility to mastitis. The objective of this study was to improve our understanding of the underlying mechanisms by comparing transcriptomic profiles following NEB and a concomitant mammary inflammation. Accordingly, we performed RNA-seq analysis of blood cells in energy-restricted ewes and control-diet ewes at four different time points before and after intra mammary challenge with phlogogenic ligands. Blood leucocytes responded to NEB by shutting down lipid-generating processes, including cholesterol and fatty acid synthesis, probably under transcriptional control of SREBF 1. Furthermore, fatty acid oxidation was activated and glucose oxidation and transport inhibited in response to energy restriction. Among the differentially expressed genes (DEGs) in response to energy restriction, 64 genes were also differential in response to the inflammatory challenge. Opposite response included the activation of cholesterol and fatty acid synthesis during the inflammatory challenge. Moreover, activation of glucose oxidation and transport coupled with the increase of plasma glucose concentration in response to the inflammatory stimuli suggested a preferential utilization of glucose as the energy source during this stress. Leucocyte metabolism therefore undergoes strong metabolic changes during an inflammatory challenge, which could be in competition with those induced by energy restriction.

Heritability and genome-wide association mapping for supernumerary teats in French Alpine and Saanen dairy goats.

This paper reports a quantitative genetics and genomic analysis of undesired presence of supernumerary teats (SNT) in goats. Supernumerary teats are a problem in goat breeding as they can considerably impede machine milking efficiency, leading to increased milking time and injury. This phenotype has routinely been recorded for the past 15 yr in French Alpine and Saanen goats. Around 4% of the females had been assigned the SNT phenotype and consequently could not be included in the breeding program as elite animals. The heritability of this binary trait, estimated by applying linear logistic polygenic models to 32,908 Alpine and 23,217 Saanen females, was 0.40 and 0.44, respectively. A genome-wide association study was implemented using a daughter design composed of 810 Saanen goats sired by 9 artificial insemination bucks and 1,185 Alpine goats sired by 11 bucks, genotyped with the goatSNP50 chip (Illumina Inc., San Diego, CA). This association study was based on logistic polygenic models, one with separately taken single nucleotide polymorphisms and the other with haplotypes as fixed effects. The 2 breeds were analyzed together and separately. No region was found to be significant at the genome level, but 17 regions on 10 chromosomes were significant at the chromosome level. These signals were always only slightly above the chromosome significance threshold and only a few of them overlapped across analyses. No evidence of segregation of a major gene in our Saanen and Alpine populations was observed, suggesting that SNT presence is inherited in a polygenic fashion. This conclusion regarding SNT determinism agrees with recent association analyses in cattle, and one locus was even found in an orthologous region. The possibility of applying markers-based selection on the SNT trait is therefore unlikely, but, as this trait is heritable and routinely recorded, it could be managed by attributing a dedicated estimated breeding value.

Genome Wide Association Study Identifies New Loci Associated with Undesired Coat Color Phenotypes in Saanen Goats.

This paper reports a quantitative genetics and genomic analysis of undesirable coat color patterns in goats. Two undesirable coat colors have routinely been recorded for the past 15 years in French Saanen goats. One fifth of Saanen females have been phenotyped "pink" (8.0%) or "pink neck" (11.5%) and consequently have not been included in the breeding program as elite animals. Heritability of the binary "pink" and "pink neck" phenotype, estimated from 103,443 females was 0.26 for "pink" and 0.21 for "pink neck". Genome wide association studies (using haplotypes or single SNPs) were implemented using a daughter design of 810 Saanen goats sired by 9 Artificial Insemination bucks genotyped with the goatSNP50 chip. A highly significant signal (-log10pvalue = 10.2) was associated with the "pink neck" phenotype on chromosome 11, suggesting the presence of a major gene. Highly significant signals for the "pink" phenotype were found on chromosomes 5 and 13 (-log10p values of 7.2 and, 7.7 respectively). The most significant SNP on chromosome 13 was in the ASIP gene region, well known for its association with coat color phenotypes. Nine significant signals were also found for both traits. The highest signal for each trait was detected by both single SNP and haplotype approaches, whereas the smaller signals were not consistently detected by the two methods. Altogether these results demonstrated a strong genetic control of the "pink" and "pink neck" phenotypes in French Saanen goats suggesting that SNP information could be used to identify and remove undesired colored animals from the breeding program.