Large-scale analysis of sheep rumen metagenome profiles captured by reduced representation sequencing reveals individual profiles are influenced by the environment and genetics of the host.

BACKGROUND: Producing animal protein while reducing the animal's impact on the environment, e.g., through improved feed efficiency and lowered methane emissions, has gained interest in recent years. Genetic selection is one possible path to reduce the environmental impact of livestock production, but these traits are difficult and expensive to measure on many animals. The rumen microbiome may serve as a proxy for these traits due to its role in feed digestion. Restriction enzyme-reduced representation sequencing (RE-RRS) is a high-throughput and cost-effective approach to rumen metagenome profiling, but the systematic (e.g., sequencing) and biological factors influencing the resulting reference based (RB) and reference free (RF) profiles need to be explored before widespread industry adoption is possible. RESULTS: Metagenome profiles were generated by RE-RRS of 4,479 rumen samples collected from 1,708 sheep, and assigned to eight groups based on diet, age, time off feed, and country (New Zealand or Australia) at the time of sample collection. Systematic effects were found to have minimal influence on metagenome profiles. Diet was a major driver of differences between samples, followed by time off feed, then age of the sheep. The RF approach resulted in more reads being assigned per sample and afforded greater resolution when distinguishing between groups than the RB approach. Normalizing relative abundances within the sampling Cohort abolished structures related to age, diet, and time off feed, allowing a clear signal based on methane emissions to be elucidated. Genus-level abundances of rumen microbes showed low-to-moderate heritability and repeatability and were consistent between diets. CONCLUSIONS: Variation in rumen metagenomic profiles was influenced by diet, age, time off feed and genetics. Not accounting for environmental factors may limit the ability to associate the profile with traits of interest. However, these differences can be accounted for by adjusting for Cohort effects, revealing robust biological signals. The abundances of some genera were consistently heritable and repeatable across different environments, suggesting that metagenomic profiles could be used to predict an individual's future performance, or performance of its offspring, in a range of environments. These results highlight the potential of using rumen metagenomic profiles for selection purposes in a practical, agricultural setting.

Combining host and rumen metagenome profiling for selection in sheep: prediction of methane, feed efficiency, production, and health traits.

BACKGROUND: Rumen microbes break down complex dietary carbohydrates into energy sources for the host and are increasingly shown to be a key aspect of animal performance. Host genotypes can be combined with microbial DNA sequencing to predict performance traits or traits related to environmental impact, such as enteric methane emissions. Metagenome profiles were generated from 3139 rumen samples, collected from 1200 dual purpose ewes, using restriction enzyme-reduced representation sequencing (RE-RRS). Phenotypes were available for methane (CH4) and carbon dioxide (CO2) emissions, the ratio of CH4 to CH4 plus CO2 (CH4Ratio), feed efficiency (residual feed intake: RFI), liveweight at the time of methane collection (LW), liveweight at 8 months (LW8), fleece weight at 12 months (FW12) and parasite resistance measured by faecal egg count (FEC1). We estimated the proportion of phenotypic variance explained by host genetics and the rumen microbiome, as well as prediction accuracies for each of these traits. RESULTS: Incorporating metagenome profiles increased the variance explained and prediction accuracy compared to fitting only genomics for all traits except for CO2 emissions when animals were on a grass diet. Combining the metagenome profile with host genotype from lambs explained more than 70% of the variation in methane emissions and residual feed intake. Predictions were generally more accurate when incorporating metagenome profiles compared to genetics alone, even when considering profiles collected at different ages (lamb vs adult), or on different feeds (grass vs lucerne pellet). A reference-free approach to metagenome profiling performed better than metagenome profiles that were restricted to capturing genera from a reference database. We hypothesise that our reference-free approach is likely to outperform other reference-based approaches such as 16S rRNA gene sequencing for use in prediction of individual animal performance. CONCLUSIONS: This paper shows the potential of using RE-RRS as a low-cost, high-throughput approach for generating metagenome profiles on thousands of animals for improved prediction of economically and environmentally important traits. A reference-free approach using a microbial relationship matrix from log10 proportions of each tag normalized within cohort (i.e., the group of animals sampled at the same time) is recommended for future predictions using RE-RRS metagenome profiles.

Efficiency of genotyping by sequencing in inferring genomic relatedness and molecular insights into fat tail selection in Tunisian sheep.

In developing countries, the use of simple and cost-efficient molecular technology is crucial for genetic characterization of local animal resources and better development of conservation strategies. The genotyping by sequencing (GBS) technique, also called restriction enzyme- reduced representational sequencing, is an efficient, cost-effective method for simultaneous discovery and genotyping of many markers. In the present study, we applied a two-enzyme GBS protocol (PstI/MspI) to discover and genotype SNP markers among 197 Tunisian sheep samples. A total of 100 333 bi-allelic SNPs were discovered and genotyped with an SNP call rate of 0.69 and mean sample depth 3.33. The genomic relatedness between 183 samples grouped the samples perfectly to their populations and pointed out a high genetic relatedness of inbred subpopulation reflecting the current adopted reproductive strategies. The genome-wide association study contrasting fat vs. thin-tailed breeds detected 41 significant variants including a peak positioned on OAR20. We identified FOXC1, GMDS, VEGFA, OXCT1, VRTN and BMP2 as the most promising for sheep tail-type trait. The GBS data have been useful to assess the population structure and improve our understanding of the genomic architecture of distinctive characteristics shaped by selection pressure in local sheep breeds. This study successfully investigates a cost-efficient method to discover genotypes, assign populations and understand insights into sheep adaptation to arid area. GBS could be of potential utility in livestock species in developing/emerging countries.

Risk factors for, and genetic association with, intestinal atresia in dairy calves.

Intestinal atresia is an under-diagnosed congenital defect in cattle. It results in complete occlusion of the intestinal lumen and, unless surgically corrected, results in death or euthanasia of the affected calf. There is limited information on the incidence of this condition or on risk factors, including predisposing alleles, associated with the defect. In this study, active surveillance of 39 dairy farms over 8 years identified 197 cases of intestinal atresia among 56 454 calves born, an incidence of 0.35%. The majority of cases (83%) had occlusion of the jejunum, although cases with blockage of the colon (14%) or anus (4%) were also identified. The defect was twice as common in male as in female calves (p < 0.0001), and was more common in progeny of older cows than in progeny of first or second lactation cows (p < 0.001). Year and farm of birth were also significantly associated with incidence (p < 0.05). The incidence of intestinal atresia was highest among the progeny of three related Jersey sires, suggesting that a gene for intestinal atresia was segregating within this family. Linkage analysis utilising 28 affected progeny of two half-sib putative carrier sires identified two putative quantitative trait loci associated with the defect, on chromosomes 14 and 26, although no clear candidate genes were identified. There was no evidence of a sire-effect among the progeny of Holstein-Friesian sires. However, a case-control genome-wide association study involving 91 cases and 375 healthy controls, identified 31 SNP in 18 loci as associated with the defect in this breed. These data suggest that intestinal atresia in dairy calves is not a simple Mendelian trait as previously reported but a complex multigenic disorder.

Geographical contrasts of Y-chromosomal haplogroups from wild and domestic goats reveal ancient migrations and recent introgressions.

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.

Across-country genomic predictions in Norwegian and New Zealand Composite sheep populations with similar development history.

The goal of this study was to assess the feasibility of across-country genomic predictions in Norwegian White Sheep (NWS) and New Zealand Composite (NZC) sheep populations with similar development history. Different training populations were evaluated (i.e., including only NWS or NZC, or combining both populations). Predictions were performed using the actual phenotypes (normalized) and the single-step GBLUP via Bayesian inference. Genotyped NWS animals born in 2016 (N = 267) were used to assess the accuracy and bias of genomic estimated breeding values (GEBVs) predicted for birth weight (BW), weaning weight (WW), carcass weight (CW), EUROP carcass classification (EUC), and EUROP fat grading (EUF). The accuracy and bias of GEBVs differed across traits and training population used. For instance, the GEBV accuracies ranged from 0.13 (BW) to 0.44 (EUC) for GEBVs predicted including only NWS, from 0.06 (BW) to 0.15 (CW) when including only NZC, and from 0.10 (BW) to 0.41 (EUC) when including both NWS and NZC animals in the training population. The regression coefficients used to assess the spread of GEBVs (bias) ranged from 0.26 (BW) to 0.64 (EUF) for only NWS, 0.10 (EUC) to 0.52 (CW) for only NZC, and from 0.42 (WW) to 2.23 (EUC) for both NWS and NZC in the training population. Our findings suggest that across-country genomic predictions based on ssGBLUP might be possible for NWS and NZC, especially for novel traits.

Genetic variation in skin traits in New Zealand lambs.

BACKGROUND: This study explored the genetic variability in the New Zealand sheep population for economically important skin traits. Skins were collected at slaughter from two progeny test flocks, resulting in 725 skins evaluated for grain strain, flatness, crust leather strength and overall suitability for shoe leather. DNA profiles collected from skins post-slaughter were matched to individual animals using previously collected high-density genotypes. RESULTS: Considerable phenotypic variation for skin traits was observed, with around 40% of the skins being identified as suitable for high-value shoe leather production. Several key traits associated with leather production, including flatness, tear strength, grain strength and grain strain were found to be moderate to highly heritable (h2 = 0.28-0.82). There were no major significant genome-wide association study (GWAS) peaks associated with many of the traits examined, however, one single-nucleotide polymorphism (SNP) reached significance for the flatness of the skin over the hindquarters. CONCLUSION: This research confirms that suitable lamb skins can be bred for use as high-value shoe leather. While moderately to highly heritable, skin traits in New Zealand lambs appear to be polygenic with no genes of major effect underlaying the traits of interest. Given the complex nature of these traits, the identification and selection of animals with higher-value skins may be enabled by geomic selection. © 2022 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

On the origin of European sheep as revealed by the diversity of the Balkan breeds and by optimizing population-genetic analysis tools.

BACKGROUND: In the Neolithic, domestic sheep migrated into Europe and subsequently spread in westerly and northwesterly directions. Reconstruction of these migrations and subsequent genetic events requires a more detailed characterization of the current phylogeographic differentiation. RESULTS: We collected 50 K single nucleotide polymorphism (SNP) profiles of Balkan sheep that are currently found near the major Neolithic point of entry into Europe, and combined these data with published genotypes from southwest-Asian, Mediterranean, central-European and north-European sheep and from Asian and European mouflons. We detected clines, ancestral components and admixture by using variants of common analysis tools: geography-informative supervised principal component analysis (PCA), breed-specific admixture analysis, across-breed [Formula: see text] profiles and phylogenetic analysis of regional pools of breeds. The regional Balkan sheep populations exhibit considerable genetic overlap, but are clearly distinct from the breeds in surrounding regions. The Asian mouflon did not influence the differentiation of the European domestic sheep and is only distantly related to present-day sheep, including those from Iran where the mouflons were sampled. We demonstrate the occurrence, from southeast to northwest Europe, of a continuously increasing ancestral component of up to 20% contributed by the European mouflon, which is assumed to descend from the original Neolithic domesticates. The overall patterns indicate that the Balkan region and Italy served as post-domestication migration hubs, from which wool sheep reached Spain and north Italy with subsequent migrations northwards. The documented dispersal of Tarentine wool sheep during the Roman period may have been part of this process. Our results also reproduce the documented 18th century admixture of Spanish Merino sheep into several central-European breeds. CONCLUSIONS: Our results contribute to a better understanding of the events that have created the present diversity pattern, which is relevant for the management of the genetic resources represented by the European sheep population.

Genomics detects population structure within and between ocean basins in a circumpolar seabird: The white-chinned petrel.

The Southern Ocean represents a continuous stretch of circumpolar marine habitat, but the potential physical and ecological drivers of evolutionary genetic differentiation across this vast ecosystem remain unclear. We tested for genetic structure across the full circumpolar range of the white-chinned petrel (Procellaria aequinoctialis) to unravel the potential drivers of population differentiation and test alternative population differentiation hypotheses. Following range-wide comprehensive sampling, we applied genomic (genotyping-by-sequencing or GBS; 60,709 loci) and standard mitochondrial-marker approaches (cytochrome b and first domain of control region) to quantify genetic diversity within and among island populations, test for isolation by distance, and quantify the number of genetic clusters using neutral and outlier (non-neutral) loci. Our results supported the multi-region hypothesis, with a range of analyses showing clear three-region genetic population structure, split by ocean basin, within two evolutionary units. The most significant differentiation between these regions confirmed previous work distinguishing New Zealand and nominate subspecies. Although there was little evidence of structure within the island groups of the Indian or Atlantic oceans, a small set of highly-discriminatory outlier loci could assign petrels to ocean basin and potentially to island group, though the latter needs further verification. Genomic data hold the key to revealing substantial regional genetic structure within wide-ranging circumpolar species previously assumed to be panmictic.

Methane yield phenotypes linked to differential gene expression in the sheep rumen microbiome.

Ruminant livestock represent the single largest anthropogenic source of the potent greenhouse gas methane, which is generated by methanogenic archaea residing in ruminant digestive tracts. While differences between individual animals of the same breed in the amount of methane produced have been observed, the basis for this variation remains to be elucidated. To explore the mechanistic basis of this methane production, we measured methane yields from 22 sheep, which revealed that methane yields are a reproducible, quantitative trait. Deep metagenomic and metatranscriptomic sequencing demonstrated a similar abundance of methanogens and methanogenesis pathway genes in high and low methane emitters. However, transcription of methanogenesis pathway genes was substantially increased in sheep with high methane yields. These results identify a discrete set of rumen methanogens whose methanogenesis pathway transcription profiles correlate with methane yields and provide new targets for CH4 mitigation at the levels of microbiota composition and transcriptional regulation.

Estimation of linkage disequilibrium and effective population size in New Zealand sheep using three different methods to create genetic maps.

BACKGROUND: Investments in genetic selection have played a major role in the New Zealand sheep industry competitiveness. Selection may erode genetic diversity, which is a crucial factor for the success of breeding programs. Better understanding of linkage disequilibrium (LD) and ancestral effective population size (Ne) through quantifying this diversity and comparison between populations allows for more informed decisions with regards to selective breeding taking population genetic diversity into account. The estimation of N e can be determined via genetic markers and requires knowledge of genetic distances between these markers. Single nucleotide polymorphisms (SNP) data from a sample of 12,597 New Zealand crossbred and purebred sheep genotyped with the Illumina Ovine SNP50 BeadChip was used to perform a genome-wide scan of LD and N e . Three methods to estimate genetic distances were investigated: 1) M1: a ratio fixed across the whole genome of one Megabase per centiMorgan; 2) M2: the ratios of genetic distance (using M3, below) over physical distance fixed for each chromosome; and, 3) M3: a genetic map of inter-SNP distances estimated using CRIMAP software (v2.503). RESULTS: The estimates obtained with M2 and M3 showed much less variability between autosomes than those with M1, which tended to give lower N e results and higher LD decay. The results suggest that N e has decreased since the development of sheep breeds in Europe and this reduction in Ne has been accelerated in the last three decades. The N e estimated for five generations in the past ranged from 71 to 237 for Texel and Romney breeds, respectively. A low level of genetic kinship and inbreeding was estimated in those breeds suggesting avoidance of mating close relatives. CONCLUSIONS: M3 was considered the most accurate method to create genetic maps for the estimation of LD and Ne. The findings of this study highlight the history of genetic selection in New Zealand crossbred and purebred sheep and these results will be very useful to understand genetic diversity of the population with respect to genetic selection. In addition, it will help geneticists to identify genomic regions which have been preferentially selected within a variety of breeds and populations.

Genetic diversity of a New Zealand multi-breed sheep population and composite breeds' history revealed by a high-density SNP chip.

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.

Prediction of genomic breeding values for growth, carcass and meat quality traits in a multi-breed sheep population using a HD SNP chip.

BACKGROUND: New Zealand has some unique Terminal Sire composite sheep breeds, which were developed in the last three decades to meet commercial needs. These composite breeds were developed based on crossing various Terminal Sire and Maternal breeds and, therefore, present high genetic diversity compared to other sheep breeds. Their breeding programs are focused on improving carcass and meat quality traits. There is an interest from the industry to implement genomic selection in this population to increase the rates of genetic gain. Therefore, the main objectives of this study were to determine the accuracy of predicted genomic breeding values for various growth, carcass and meat quality traits using a HD SNP chip and to evaluate alternative genomic relationship matrices, validation designs and genomic prediction scenarios. A large multi-breed population (n = 14,845) was genotyped with the HD SNP chip (600 K) and phenotypes were collected for a variety of traits. RESULTS: The average observed accuracies (± SD) for traits measured in the live animal, carcass, and, meat quality traits ranged from 0.18 ± 0.07 to 0.33 ± 0.10, 0.28 ± 0.09 to 0.55 ± 0.05 and 0.21 ± 0.07 to 0.36 ± 0.08, respectively, depending on the scenario/method used in the genomic predictions. When accounting for population stratification by adjusting for 2, 4 or 6 principal components (PCs) the observed accuracies of molecular breeding values (mBVs) decreased or kept constant for all traits. The mBVs observed accuracies when fitting both G and A matrices were similar to fitting only G matrix. The lowest accuracies were observed for k-means cross-validation and forward validation performed within each k-means cluster. CONCLUSIONS: The accuracies observed in this study support the feasibility of genomic selection for growth, carcass and meat quality traits in New Zealand Terminal Sire breeds using the Ovine HD SNP chip. There was a clear advantage on using a mixed training population instead of performing analyzes per genomic clusters. In order to perform genomic predictions per breed group, genotyping more animals is recommended to increase the size of the training population within each group and the genetic relationship between training and validation populations. The different scenarios evaluated in this study will help geneticists and breeders to make wiser decisions in their breeding programs.

Copy number variants in the sheep genome detected using multiple approaches.

BACKGROUND: Copy number variants (CNVs) are a type of polymorphism found to underlie phenotypic variation, both in humans and livestock. Most surveys of CNV in livestock have been conducted in the cattle genome, and often utilise only a single approach for the detection of copy number differences. Here we performed a study of CNV in sheep, using multiple methods to identify and characterise copy number changes. Comprehensive information from small pedigrees (trios) was collected using multiple platforms (array CGH, SNP chip and whole genome sequence data), with these data then analysed via multiple approaches to identify and verify CNVs. RESULTS: In total, 3,488 autosomal CNV regions (CNVRs) were identified in this study, which substantially builds on an initial survey of the sheep genome that identified 135 CNVRs. The average length of the identified CNVRs was 19 kb (range of 1 kb to 3.6 Mb), with shorter CNVRs being more frequent than longer CNVRs. The total length of all CNVRs was 67.6Mbps, which equates to 2.7 % of the sheep autosomes. For individuals this value ranged from 0.24 to 0.55 %, and the majority of CNVRs were identified in single animals. Rather than being uniformly distributed throughout the genome, CNVRs tended to be clustered. Application of three independent approaches for CNVR detection facilitated a comparison of validation rates. CNVs identified on the Roche-NimbleGen 2.1M CGH array generally had low validation rates with lower density arrays, while whole genome sequence data had the highest validation rate (>60 %). CONCLUSIONS: This study represents the first comprehensive survey of the distribution, prevalence and characteristics of CNVR in sheep. Multiple approaches were used to detect CNV regions and it appears that the best method for verifying CNVR on a large scale involves using a combination of detection methodologies. The characteristics of the 3,488 autosomal CNV regions identified in this study are comparable to other CNV regions reported in the literature and provide a valuable and sizeable addition to the small subset of published sheep CNVs.

Natural variation in methane emission of sheep fed on a lucerne pellet diet is unrelated to rumen ciliate community type.

Only limited information is available on the roles of different rumen ciliate community types, first described by Eadie in 1962, in enteric methane (CH4) formation by their ruminant hosts. If the different types were differentially associated with CH4 formation, then ciliate community typing could be used to identify naturally high and low CH4-emitting animals. Here we measured the CH4 yields [g CH4 (kg feed dry matter intake, DMI)(-1)] of 118 sheep fed a standard pelleted lucerne diet at two different times, at least 2 weeks apart. There were significant differences (P < 2.2 × 10(-16), Wilcoxon rank sum test) in the CH4 yields (± sd) from sheep selected as high [16.7 ± 1.5 g CH4 (kg DMI)(-1)] and low emitters [13.3 ± 1.5 g CH4 (kg DMI)(-1)]. A rumen sample was collected after each of the two measurements, and ciliate composition was analysed using barcoded 454 Titanium pyrosequencing of 18S rRNA genes. The genera found, in order of mean relative abundance, were Epidinium, Entodinium, Dasytricha, Eudiplodinium, Polyplastron, Isotricha and Anoplodinium-Diplodinium, none of which was significantly correlated with the CH4 emissions ranking associated with the rumen sample. Ciliate communities naturally assembled into four types (A, AB, B and O), characterized by the presence and absence of key genera. There was no difference in CH4 yield between sheep that harboured different ciliate community types, suggesting that these did not underlie the natural variation in CH4 yields. Further research is needed to unravel the nature of interactions between ciliate protozoa and other rumen micro-organisms, which may ultimately lead to contrasting CH4 emission phenotypes.

Assessing accuracy of imputation using different SNP panel densities in a multi-breed sheep population.

BACKGROUND: Genotype imputation is a key element of the implementation of genomic selection within the New Zealand sheep industry, but many factors can influence imputation accuracy. Our objective was to provide practical directions on the implementation of imputation strategies in a multi-breed sheep population genotyped with three single nucleotide polymorphism (SNP) panels: 5K, 50K and HD (600K SNPs). RESULTS: Imputation from 5K to HD was slightly better (0.6 %) than imputation from 5K to 50K. Two-step imputation from 5K to 50K and then from 50K to HD outperformed direct imputation from 5K to HD. A slight loss in imputation accuracy was observed when a large fixed reference population was used compared to a smaller within-breed reference (including all 50K genotypes on animals from different breeds excluding those in the validation set i.e. to be imputed), but only for a few animals across all imputation scenarios from 5K to 50K. However, a major gain in imputation accuracy for a large proportion of animals (purebred and crossbred), justified the use of a fixed and large reference dataset for all situations. This study also investigated the loss in imputation accuracy specifically for SNPs located at the ends of each chromosome, and showed that only chromosome 26 had an overall imputation (5K to 50K) accuracy for 100 SNPs at each end higher than 60 % (r2). Most of the chromosomes displayed reduced imputation accuracy at least at one of their ends. Prediction of imputation accuracy based on the relatedness of low-density genotypes to those of the reference dataset, before imputation (without running an imputation software) was also investigated. FIMPUTE V2.2 outperformed BEAGLE 3.3.2 across all imputation scenarios. CONCLUSIONS: Imputation accuracy in sheep breeds can be improved by following a set of recommendations on SNP panels, software, strategies of imputation (one- or two-step imputation), and choice of the animals to be genotyped using both high- and low-density SNP panels. We present a method that predicts imputation accuracy for individual animals at the low-density level, before running imputation, which can be used to restrict genomic prediction only to the animals that can be imputed with sufficient accuracy.

Genomic prediction and genome-wide association study for dagginess and host internal parasite resistance in New Zealand sheep.

BACKGROUND: Dagginess (faecal soiling of the perineum region) and host nematode parasite resistance are important animal welfare traits in New Zealand sheep. Genomic prediction (GP) estimates the genetic merit, as a molecular breeding value (mBV), for each trait based on many SNPs. The additional information the mBV provides (as determined by its accuracy) has led to its incorporation into breeding schemes. Some GP methods give SNP effects, which provide additional information to identify genome-wide associations (GWAS) for a trait of interest. Here we report results from a GP and GWAS study for dagginess and host nematode parasite resistance in a New Zealand sheep industry resource. RESULTS: Genomic prediction analysis was performed using 50K SNP chip data and parent average-removed, de-regressed BVs for five traits, from a resource of 8705 pedigree recorded animals. The five traits were dag score at three and eight months (DAG3, DAG8) and nematode faecal egg count in summer (FEC1), autumn (FEC2) and as an adult (AFEC). The resource consisted of Romney, Coopworth, Perendale, Texel and various breed crosses (designated: CompRCP, CompRCPT and CompCRP). The pure breeds, apart from Texel, plus CompRCP were used to develop the GP. The resulting SNP effects were used to identify genetic regions associated with dagginess and parasite resistance. Accuracies of the weighted correlation between mBV and true BV ranged between -0.07 (Texel) and 0.56 (Coopworth) for DAG3 and DAG8. For FEC1, FEC2 and AFEC accuracies ranged between -0.22 (CompRCPT) and 0.69 (Coopworth). The weighted average individual accuracy (calculated from theory) ranges were 0.13 (Texel) to 0.52 (Coopworth) and 0.11 (Texel) to 0.55 (Coopworth) respectively, for dagginess and parasite traits. There was one SNP for DAG8 that reached Bonferroni significance threshold (P < 1 × 10(-6)) on OAR15, the same two SNPs for each of the parasite traits (OAR26) and none for DAG3. A notable peak was also observed on OAR7 for all the parasite traits, however, it did not reach the Bonferroni significance threshold. CONCLUSIONS: This study presents the first results of a GWAS on dagginess and faecal egg count traits in New Zealand sheep. The results suggest that there are quantitative trait loci on OAR 15 for dagginess and on OAR26 and seven for faecal egg count.

Construction of relatedness matrices using genotyping-by-sequencing data.

BACKGROUND: Genotyping-by-sequencing (GBS) is becoming an attractive alternative to array-based methods for genotyping individuals for a large number of single nucleotide polymorphisms (SNPs). Costs can be lowered by reducing the mean sequencing depth, but this results in genotype calls of lower quality. A common analysis strategy is to filter SNPs to just those with sufficient depth, thereby greatly reducing the number of SNPs available. We investigate methods for estimating relatedness using GBS data, including results of low depth, using theoretical calculation, simulation and application to a real data set. RESULTS: We show that unbiased estimates of relatedness can be obtained by using only those SNPs with genotype calls in both individuals. The expected value of this estimator is independent of the SNP depth in each individual, under a model of genotype calling that includes the special case of the two alleles being read at random. In contrast, the estimator of self-relatedness does depend on the SNP depth, and we provide a modification to provide unbiased estimates of self-relatedness. We refer to these methods of estimation as kinship using GBS with depth adjustment (KGD). The estimators can be calculated using matrix methods, which allow efficient computation. Simulation results were consistent with the methods being unbiased, and suggest that the optimal sequencing depth is around 2-4 for relatedness between individuals and 5-10 for self-relatedness. Application to a real data set revealed that some SNP filtering may still be necessary, for the exclusion of SNPs which did not behave in a Mendelian fashion. A simple graphical method (a 'fin plot') is given to illustrate this issue and to guide filtering parameters. CONCLUSION: We provide a method which gives unbiased estimates of relatedness, based on SNPs assayed by GBS, which accounts for the depth (including zero depth) of the genotype calls. This allows GBS to be applied at read depths which can be chosen to optimise the information obtained. SNPs with excess heterozygosity, often due to (partial) polyploidy or other duplications can be filtered based on a simple graphical method.

Genome-wide analysis of the world's sheep breeds reveals high levels of historic mixture and strong recent selection.

Through their domestication and subsequent selection, sheep have been adapted to thrive in a diverse range of environments. To characterise the genetic consequence of both domestication and selection, we genotyped 49,034 SNP in 2,819 animals from a diverse collection of 74 sheep breeds. We find the majority of sheep populations contain high SNP diversity and have retained an effective population size much higher than most cattle or dog breeds, suggesting domestication occurred from a broad genetic base. Extensive haplotype sharing and generally low divergence time between breeds reveal frequent genetic exchange has occurred during the development of modern breeds. A scan of the genome for selection signals revealed 31 regions containing genes for coat pigmentation, skeletal morphology, body size, growth, and reproduction. We demonstrate the strongest selection signal has occurred in response to breeding for the absence of horns. The high density map of genetic variability provides an in-depth view of the genetic history for this important livestock species.

Signatures of selection in sheep bred for resistance or susceptibility to gastrointestinal nematodes.

BACKGROUND: Gastrointestinal nematodes are one of the most serious causes of disease in domestic ruminants worldwide. There is considerable variation in resistance to gastrointestinal nematodes within and between sheep breeds, which appears to be due to underlying genetic diversity. Through selection of resistant animals, rapid genetic progress has been demonstrated in both research and commercial flocks. Recent advances in genome sequencing and genomic technologies provide new opportunities to understand the ovine host response to gastrointestinal nematodes at the molecular level, and to identify polymorphisms conferring nematode resistance. RESULTS: Divergent lines of Romney and Perendale sheep, selectively bred for high and low faecal nematode egg count, were genotyped using the Illumina® Ovine SNP50 BeadChip. The resulting genome-wide SNP data were analysed for selective sweeps on loci associated with resistance or susceptibility to gastrointestinal nematode infection. Population differentiation using FST and Peddrift revealed sixteen regions, which included candidate genes involved in chitinase activity and the cytokine response. Two of the sixteen regions identified were contained within previously identified QTLs associated with nematode resistance. CONCLUSIONS: In this study we identified fourteen novel regions associated with resistance or susceptibility to gastrointestinal nematodes. Results from this study support the hypothesis that host resistance to internal nematode parasites is likely to be controlled by a number of loci of moderate to small effects.