GWA analysis for milk production traits in dairy sheep and genetic support for a QTN influencing milk protein percentage in the LALBA gene

Genetic diversity of United States Rambouillet, Katahdin and Dorper sheep

BACKGROUND

Managing genetic diversity is critically important for maintaining species fitness. Excessive homozygosity caused by the loss of genetic diversity can have detrimental effects on the reproduction and production performance of a breed. Analysis of genetic diversity can facilitate the identification of signatures of selection which may contribute to the specific characteristics regarding the health, production and physical appearance of a breed or population. In this study, breeds with well-characterized traits such as fine wool production (Rambouillet, N = 745), parasite resistance (Katahdin, N = 581) and environmental hardiness (Dorper, N = 265) were evaluated for inbreeding, effective population size (Ne), runs of homozygosity (ROH) and Wright's fixation index (FST) outlier approach to identify differential signatures of selection at 36,113 autosomal single nucleotide polymorphisms (SNPs).

RESULTS

Katahdin sheep had the largest current Ne at the most recent generation estimated with both the GONe and NeEstimator software. The most highly conserved ROH Island was identified in Rambouillet with a signature of selection on chromosome 6 containing 202 SNPs called in an ROH in 50 to 94% of the individuals. This region contained the DCAF16, LCORL and NCAPG genes that have been previously reported to be under selection and have biological roles related to milk production and growth traits. The outlier regions identified through the FST comparisons of Katahdin with Rambouillet and Dorper contained genes with known roles in milk production and mastitis resistance or susceptibility, and the FST comparisons of Rambouillet with Katahdin and Dorper identified genes related to wool growth, suggesting these traits have been under natural or artificial selection pressure in these populations. Genes involved in the cytokine-cytokine receptor interaction pathways were identified in all FST breed comparisons, which indicates the presence of allelic diversity between these breeds in genomic regions controlling cytokine signaling mechanisms.

CONCLUSIONS

In this paper, we describe signatures of selection within diverse and economically important U.S. sheep breeds. The genes contained within these signatures are proposed for further study to understand their relevance to biological traits and improve understanding of breed diversity.

Genetic variability among and within domestic Old and New World camels at the α-lactalbumin gene (LALBA) reveals new alleles and polymorphisms responsible for differential expression

α-Lactalbumin (α-LA), which is encoded by the LALBA gene, is a major whey protein that binds to Ca2+ and facilitates lactose synthesis as a regulatory subunit of the synthase enzyme complex. In addition, it has been shown to play central roles in immune modulation, cell-growth regulation, and antimicrobial activity. In this study, a multitechnical approach was used to fully characterize the LALBA gene and its variants in both coding and regulatory regions for domestic camelids (dromedary, Bactrian camel, alpaca, and llama). The gene analysis revealed a conserved structure among the camelids, but a slight difference in size (2,012 bp on average) due to intronic variations. Promoters were characterized for the transcription factor binding sites (11 found in total). Intraspecies sequence comparison showed 36 SNPs in total (2 in the dromedary, none in the Bactrian camel, 22 in the alpaca, and 12 in the llama), whereas interspecies comparison showed 86 additional polymorphic sites. Eight SNPs were identified as trans-specific polymorphisms, and 2 of them (g.112A>G and g.1229A>G) were particularly interesting in the New World camels. The first creates a new binding site for transcription factor SP1. An enhancing effect of the g.112G variant on the expression was demonstrated by 3 independent pGL3 gene reporter assays. The latter is responsible for the p.78Ile>Val AA replacement and represents novel allelic variants (named LALBA A and B). A link to protein variants has been established by isoelectric focusing (IEF), and bioinformatics analysis revealed that carriers of valine (g.1229G) have a higher glycosylation rate. Genotyping methods based on restriction fragment length polymorphism (PCR-RFLP) were set up for both SNPs. Overall, adenine was more frequent (0.54 and 0.76) at both loci. Four haplotypes were found, and the AA and GA were the most common with a frequency of 0.403 and 0.365, respectively. Conversely, a putative biological gain characterizes the haplotype GG. Therefore, opportunities for rapid directional selection can be realized if this haplotype is associated with favorable milk protein properties. This study adds knowledge at the gene and protein level for α-LA (LALBA) in camelids and importantly contributes to a relatively unexplored research area in these species.

Genome-Wide Association Analysis of Muscle pH in Texel Sheep × Altay Sheep F2 Resource Population

pH was one of the important meat quality traits, which was an important factor affecting the storage/shelf life and quality of meat in meat production. In order to find a way to extend the storage/shelf life, the pH values (pH_45min, pH_24h, pH_48h and pH_72h) of the longissimus dorsi muscles in F₂ individuals of 462 Texel sheep × Altay sheep were determined, genotyping was performed using Illumina Ovine SNP 600 K BeadChip and whole genome resequencing technology, a genome-wide association analysis (GWAS) was used to screen the candidate genes and molecular markers for pH values related to the quality traits of mutton, and the effects of population stratification were detected by Q-Q plots. The results showed that the pH population stratification analysis did not find significant systemic bias, and there was no obvious population stratification effect. The results of the association analysis showed that 28 SNPs significantly associated with pH reached the level of genomic significance. The candidate gene associated with pH_45min was identified as the CCDC92 gene by gene annotation and a search of the literature. Candidate genes related to pH_24h were KDM4C, TGFB2 and GOT2 genes. The candidate genes related to pH_48h were MMP12 and MMP13 genes. The candidate genes related to pH_72h were HILPDA and FAT1 genes. Further bioinformatics analyses showed 24 gene ontology terms and five signaling pathways that were significantly enriched (p ≤ 0.05). Many terms and pathways were related to cellular components, processes of protein modification, the activity of protein dimerization and hydrolase activity. These identified SNPs and genes could provide useful information about meat and the storage/shelf life of meat, thereby extending the storage/shelf life and quality of meat.

Whole-genome resequencing reveals genetic diversity and selection characteristics of dairy goat

The dairy goat is one of the earliest dairy livestock species, which plays an important role in the economic development, especially for developing countries. With the development of agricultural civilization, dairy goats have been widely distributed across the world. However, few studies have been conducted on the specific characteristics of dairy goat. In this study, we collected the whole-genome data of 89 goat individuals by sequencing 48 goats and employing 41 publicly available goats, including five dairy goat breeds (Saanen, Nubian, Alpine, Toggenburg, and Guanzhong dairy goat; n = 24, 15, 11, 6, 6), and three goat breeds (Guishan goat, Longlin goat, Yunshang Black goat; n = 6, 15, 6). Through compared the genomes of dairy goat and non-dairy goat to analyze genetic diversity and selection characteristics of dairy goat. The results show that the eight goats could be divided into three subgroups of European, African, and Chinese indigenous goat populations, and we also found that Australian Nubian, Toggenburg, and Australian Alpine had the highest linkage disequilibrium, the lowest level of nucleotide diversity, and a higher inbreeding coefficient, indicating that they were strongly artificially selected. In addition, we identified several candidate genes related to the specificity of dairy goat, particularly genes associated with milk production traits (GHR, DGAT2, ELF5, GLYCAM1, ACSBG2, ACSS2), reproduction traits (TSHR, TSHB, PTGS2, ESR2), immunity traits (JAK1, POU2F2, LRRC66). Our results provide not only insights into the evolutionary history and breed characteristics of dairy goat, but also valuable information for the implementation and improvement of dairy goat cross breeding program.

Elucidating genes and gene networks linked to individual susceptibility to milk fat depression in dairy goats

Dietary supplementation with marine lipids modulates ruminant milk composition toward a healthier fatty acid profile for consumers, but it also causes milk fat depression (MFD). Because the dairy goat industry is mainly oriented toward cheese manufacturing, MFD can elicit economic losses. There is large individual variation in animal susceptibility with goats more (RESPO+) or less (RESPO-) responsive to diet-induced MFD. Thus, we used RNA-Seq to examine gene expression profiles in mammary cells to elucidate mechanisms underlying MFD in goats and individual variation in the extent of diet-induced MFD. Differentially expression analyses (DEA) and weighted gene co-expression network analysis (WGCNA) of RNA-Seq data were used to study milk somatic cell transcriptome changes in goats consuming a diet supplemented with marine lipids. There were 45 differentially expressed genes (DEGs) between control (no-MFD, before diet-induced MFD) and MFD, and 18 between RESPO+ and RESPO-. Biological processes and pathways such as "RNA transcription" and "Chromatin modifying enzymes" were downregulated in MFD compared with controls. Regarding susceptibility to diet-induced MFD, we identified the "Triglyceride Biosynthesis" pathway upregulated in RESPO- goats. The WGCNA approach identified 9 significant functional modules related to milk fat production and one module to the fat yield decrease in diet-induced MFD. The onset of MFD in dairy goats is influenced by the downregulation of SREBF1, other transcription factors and chromatin-modifying enzymes. A list of DEGs between RESPO+ and RESPO- goats (e.g., DBI and GPD1), and a co-related gene network linked to the decrease in milk fat (ABCD3, FABP3, and PLIN2) was uncovered. Results suggest that alterations in fatty acid transport may play an important role in determining individual variation. These candidate genes should be further investigated.

Host genetic control on rumen microbiota and its impact on dairy traits in sheep

BACKGROUND

Milk yield and fine composition in sheep depend on the volatile and long-chain fatty acids, microbial proteins, vitamins produced through feedstuff digestion by the rumen microbiota. In cattle, the host genome has been shown to have a low to moderate genetic control on rumen microbiota abundance but a high control on dairy traits with heritabilities higher than 0.30. There is little information on the genetic correlations and quantitative trait loci (QTL) that simultaneously affect rumen microbiota abundance and dairy traits in ruminants, especially in sheep. Thus, our aim was to quantify the effect of the host genetics on rumen bacterial abundance and the genetic correlations between rumen bacterial abundance and several dairy traits, and to identify QTL that are associated with both rumen bacterial abundance and milk traits.

RESULTS

Our results in Lacaune sheep show that the heritability of rumen bacterial abundance ranges from 0 to 0.29 and that the heritability of 306 operational taxonomic units (OTU) is significantly different from 0. Of these 306 OTU, 96 that belong mainly to the Prevotellaceae, Lachnospiraceae and Ruminococcaceae bacterial families show strong genetic correlations with milk fatty acids and proteins (absolute values ranging from 0.33 to 0.99). Genome-wide association studies revealed a QTL for alpha-lactalbumin concentration in milk on Ovis aries chromosome (OAR) 11, and six QTL for rumen bacterial abundances i.e., for two OTU belonging to the genera Prevotella (OAR3 and 5), Rikeneleaceae_RC9_gut_group (OAR5), Ruminococcus (OAR5), an unknown genus of order Clostridia UCG-014 (OAR10), and CAG-352 (OAR11). None of these detected regions are simultaneously associated with rumen bacterial abundance and dairy traits, but the bacterial families Prevotellaceae, Lachnospiraceae and F082 show colocalized signals on OAR3, 5, 15 and 26.

CONCLUSIONS

In Lacaune dairy sheep, rumen microbiota abundance is partially controlled by the host genetics and is poorly genetically linked with milk protein and fatty acid compositions, and three main bacterial families, Prevotellaceae, Lachnospiraceae and F082, show specific associations with OAR3, 5, 15 and 26.

Favored single nucleotide variants identified using whole genome Re-sequencing of Austrian and Chinese cattle breeds

Cattle have been essential for the development of human civilization since their first domestication few thousand years ago. Since then, they have spread across vast geographic areas following human activities. Throughout generations, the cattle genome has been shaped with detectable signals induced by various evolutionary processes, such as natural and human selection processes and demographic events. Identifying such signals, called selection signatures, is one of the primary goals of population genetics. Previous studies used various selection signature methods and normalized the outputs score using specific windows, in kbp or based on the number of SNPs, to identify the candidate regions. The recent method of iSAFE claimed for high accuracy in pinpointing the candidate SNPs. In this study, we analyzed whole-genome resequencing (WGS) data of ten individuals from Austrian Fleckvieh (Bos taurus) and fifty individuals from 14 Chinese indigenous breeds (Bos taurus, Bos taurus indicus, and admixed). Individual WGS reads were aligned to the cattle reference genome of ARS. UCD1.2 and subsequently undergone single nucleotide variants (SNVs) calling pipeline using GATK. Using these SNVs, we examined the population structure using principal component and admixture analysis. Then we refined selection signature candidates using the iSAFE program and compared it with the classical iHS approach. Additionally, we run Fst population differentiation from these two cattle groups. We found gradual changes of taurine in north China to admixed and indicine to the south. Based on the population structure and the number of individuals, we grouped samples to Fleckvieh, three Chinese taurines (Kazakh, Mongolian, Yanbian), admixed individuals (CHBI_Med), indicine individuals (CHBI_Low), and a combination of admixed and indicine (CHBI) for performing iSAFE and iHS tests. There were more significant SNVs identified using iSAFE than the iHS for the candidate of positive selection and more detectable signals in taurine than in indicine individuals. However, combining admixed and indicine individuals decreased the iSAFE signals. From both within-population tests, significant SNVs are linked to the olfactory receptors, production, reproduction, and temperament traits in taurine cattle, while heat and parasites tolerance in the admixed individuals. Fst test suggests similar patterns of population differentiation between Fleckvieh and three Chinese taurine breeds against CHBI. Nevertheless, there are genes shared only among the Chinese taurine, such as PAX5, affecting coat color, which might drive the differences between these yellowish coated breeds, and those in the greater Far East region.

Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep

The present study aimed to ascertain how different strategies for leveraging genomic information enhance the accuracy of estimated breeding values for milk and cheese-making traits and to evaluate the implementation of a low-density (LowD) SNP chip designed explicitly for that aim. Thus, milk samples from a total of 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra) were collected and analyzed to determine 3 milk production and composition traits and 2 traits related to milk coagulation properties and cheese yield. The 2 studied populations were genotyped with a customized 50K Affymetrix SNP chip (Affymetrix Inc.) containing 55,627 SNP markers. The prediction accuracies were obtained using different multitrait methodologies, such as the BLUP model based on pedigree information, the genomic BLUP (GBLUP), and the BLUP at the SNP level (SNP-BLUP), which are based on genotypic data, and the single-step GBLUP (ssGBLUP), which combines both sources of information. All of these methods were analyzed by cross-validation, comparing predictions of the whole population with the test population sets. Additionally, we describe the design of a LowD SNP chip (3K) and its prediction accuracies through the different methods mentioned previously. Furthermore, the results obtained using the LowD SNP chip were compared with those based on the 50K SNP chip data sets. Finally, we conclude that implementing genomic selection through the ssGBLUP model in the current breeding programs would increase the accuracy of the estimated breeding values compared with the BLUP methodology in the Assaf (from 0.19 to 0.39) and Churra (from 0.27 to 0.44) dairy sheep populations. The LowD SNP chip is cost-effective and has proven to be an accurate tool for estimating genomic breeding values for milk and cheese-making traits, microsatellite imputation, and parentage verification. The results presented here suggest that the routine use of this LowD SNP chip could potentially increase the genetic gains of the breeding selection programs of the 2 Spanish dairy sheep breeds considered here.

Comparative analyses of copy number variations between swamp and river buffalo

Domestic buffalo is an important livestock in the tropical and sub-tropical region, including two types: swamp and river buffalo. The swamp buffalo is mainly used as draft animal, while the river buffalo is raised for milk production. In this study, based on the new high-quality buffalo reference genome UOA_WB_1, we firstly investigated the copy number variants in buffalo using whole-genome Illumina sequencing. A total of 3,734 CNV regions (CNVRs) were detected in 106 buffalo population with a total length of 23,429,066 bp, corresponding to ∼ 0.88% of the water buffalo genome (UOA_WB_1). Our results revealed a clear population differentiation in CNV between swamp and river buffalo. In addition, a total of 667 highly differentiated CNVRs (covering 886 genes) were detected between river and swamp buffalo population. We detected a set of CNVR-overlapping genes associated with exercise, immunity, nerve, and milk trait which exhibited different copy numbers between swamp and river buffalo population. This study provides valuable genome variation resources for buffalo and would contribute to understanding the genetic differences between swamp and river buffalo.

Detection of candidate genes affecting milk production traits in sheep using whole-genome sequencing analysis

BACKGROUND

Artificial and natural selection for important economic traits and genetic adaptation of the populations to specific environments have led to the changes on the sheep genome. Recent advances in genome sequencing methods have made it possible to use comparative genomics tools to identify genes under selection for traits of economic interest in domestic animals.

OBJECTIVES

In this study, we compared the genomes of Assaf and Awassi sheep breeds with those of the Cambridge, Romanov and British du cher sheep breeds to explore positive selection signatures for milk traits using nucleotide diversity (Pi) and FST statistical methods.

METHODS

Genome sequences from fourteen sheep with a mean sequence depth of 9.32X per sample were analysed, and a total of 23 million single nucleotide polymorphisms (SNPs) were called and applied for this study. Genomic clustering of breeds was identified using ADMIXTURE software. The FST and Pi values for each SNP were computed between population A (Assaf and Awassi) and population B (Cambridge, British du cher, and Romanov).

RESULTS

The results of the PCA grouped two classes for these five dairy sheep breeds. The selection signatures analysis displayed 735 and 515 genes from FST and nucleotide diversity (Pi) statistical methods, respectively. Among all these, 12 genes were shared between the two approaches. The most conspicuous genes were related to milk traits, including ST3GAL1 (the synthesis of oligosacáridos), CSN1S1 (milk protein), CSN2 (milk protein), OSBPL8 (fatty acid traits), SLC35A3 (milk fat and protein percentage), VPS13B (total milk production, fat yield, and protein yield), DPY19L1 (peak yield), CCDC152 (lactation persistency and somatic cell count), NT5DC1 (lactation persistency), P4HTM (test day protein), CYTH4 (FAT Production) and METRNL (somatic cell), U1 (milk traits), U6 (milk traits) and 5S_RRNA (milk traits).

CONCLUSIONS

The findings provide new insight into the genetic basis of sheep milk properties and can play a role in designing sheep breeding programs incorporating genomic information.

Multi-Omics Integration and Network Analysis Reveal Potential Hub Genes and Genetic Mechanisms Regulating Bovine Mastitis

Mastitis, inflammation of the mammary gland, is the most prevalent disease in dairy cattle that has a potential impact on profitability and animal welfare. Specifically designed multi-omics studies can be used to prioritize candidate genes and identify biomarkers and the molecular mechanisms underlying mastitis in dairy cattle. Hence, the present study aimed to explore the genetic basis of bovine mastitis by integrating microarray and RNA-Seq data containing healthy and mastitic samples in comparative transcriptome analysis with the results of published genome-wide association studies (GWAS) using a literature mining approach. The integration of different information sources resulted in the identification of 33 common and relevant genes associated with bovine mastitis. Among these, seven genes—CXCR1, HCK, IL1RN, MMP9, S100A9, GRO1, and SOCS3—were identified as the hub genes (highly connected genes) for mastitis susceptibility and resistance, and were subjected to protein-protein interaction (PPI) network and gene regulatory network construction. Gene ontology annotation and enrichment analysis revealed 23, 7, and 4 GO terms related to mastitis in the biological process, molecular function, and cellular component categories, respectively. Moreover, the main metabolic-signalling pathways responsible for the regulation of immune or inflammatory responses were significantly enriched in cytokine–cytokine-receptor interaction, the IL-17 signaling pathway, viral protein interaction with cytokines and cytokine receptors, and the chemokine signaling pathway. Consequently, the identification of these genes, pathways, and their respective functions could contribute to a better understanding of the genetics and mechanisms regulating mastitis and can be considered a starting point for future studies on bovine mastitis.

Study on the concordance between different SNP-genotyping platforms in sheep

Different SNP genotyping technologies are commonly used in multiple studies to perform QTL detection, genotype imputation, and genomic predictions. Therefore, genotyping errors cannot be ignored, as they can reduce the accuracy of different procedures applied in genomic selection, such as genomic imputation, genomic predictions, and false-positive results in genome-wide association studies. Currently, whole-genome resequencing (WGR) also offers the potential for variant calling analysis and high-throughput genotyping. WGR might overshadow array-based genotyping technologies due to the larger amount and precision of the genomic information provided; however, its comparatively higher price per individual still limits its use in larger populations. Thus, the objective of this work was to evaluate the accuracy of the two most popular SNP-chip technologies, namely, Affymetrix and Illumina, for high-throughput genotyping in sheep considering high-coverage WGR datasets as references. Analyses were performed using two reference sheep genome assemblies, the popular Oar_v3.1 reference genome and the latest available version Oar_rambouillet_v1.0. Our results demonstrate that the genotypes from both platforms are suggested to have high concordance rates with the genotypes determined from reference WGR datasets (96.59% and 99.51% for Affymetrix and Illumina technologies, respectively). The concordance results provided in the current study can pinpoint low reproducible markers across multiple platforms used for sheep genotyping data. Comparing results using two reference genome assemblies also informs how genome assembly quality can influence genotype concordance rates among different genotyping platforms. Moreover, we describe an efficient pipeline to test the reliability of markers included in sheep SNP-chip panels against WGR datasets available on public databases. This pipeline may be helpful for discarding low-reliability markers before exploiting genomic information for gene mapping analyses or genomic prediction.

Genome-wide association studies (GWAS) and post-GWAS analyses for technological traits in Assaf and Churra dairy breeds

This study aimed to perform a GWAS to identify genomic regions associated with milk and cheese-making traits in Assaf and Churra dairy sheep breeds; second, it aimed to identify possible positional and functional candidate genes and their interactions through post-GWAS studies. For 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra), milk samples were collected and analyzed to determine 6 milk production and composition traits and 6 traits related to milk coagulation properties and cheese yield. The genetic profiles of the ewes were obtained using a genotyping chip array that included 50,934 SNP markers. For both milk and cheese-making traits, separate single-breed GWAS were performed using GCTA software. The set of positional candidate genes identified via GWAS was subjected to guilt-by-association-based prioritization analysis with ToppGene software. Totals of 84 and 139 chromosome-wise significant associations for the 6 milk traits and the 6 cheese-making traits were identified in this study. No significant SNPs were found in common between the 2 studied breeds, possibly due to their genetic heterogeneity of the phenotypes under study. Additionally, 63 and 176 positional candidate genes were located in the genomic intervals defined as confidence regions in relation to the significant SNPs identified for the analyzed traits for Assaf and Churra breeds. After the functional prioritization analysis, 71 genes were identified as promising positional and functional candidate genes and proposed as targets of future research to identify putative causative variants in relation to the traits under examination. In addition, this multitrait study allowed us to identify variants that have a pleiotropic effect on both milk production and cheese-related traits. The incorporation of variants among the proposed functional and positional candidate genes into genomic selection strategies represent an interesting approach for achieving rapid genetic gains, specifically for those traits difficult to measure, such as cheese-making traits.

Genome-Wide SNP Analysis for Milk Performance Traits in Indigenous Sheep: A Case Study in the Egyptian Barki Sheep

Simple Summary

The Barki sheep is one of the three main breeds in Egypt, which is spread mainly throughout the northwestern coastal zone, which has harsh conditions. Considering the harsh, semi-arid habitat of this breed, milk performance traits such as milk yield and milk composition have a very important role in the feeding of newborn lambs and affect their growth during the early stage of life. In this study, rare milk performance data and genomic information of Barki sheep were used to uncover diversified genomic regions that could explain the variability of milk yield and milk quality traits in the studied population of Barki ewes. Genome-wide analysis identified genomic regions harboring interesting candidate genes such as SLC5A8, NUB1, TBC1D1, KLF3 and ABHD5 for milk yield and PPARA and FBLN1 genes for milk quality traits. The findings offer valuable information for obtaining a better understanding of the genetics of milk performance traits and contribute to the genetic improvement of these traits in Barki sheep.

Abstract

Sheep milk yield and milk composition traits play an important role in supplying newborn lambs with essential components such as amino acids, energy, vitamins and immune antibodies and are also of interest in terms of the nutritional value of the milk for human consumption. The aim of this study was to identify genomic regions and candidate genes for milk yield and milk composition traits through genome-wide SNP analyses between high and low performing ewes of the Egyptian Barki sheep breed, which is well adapted to the harsh conditions of North-East Africa. Therefore, out of a herd of 111 ewes of the Egyptian Barki sheep breed (IBD = 0.08), ewes representing extremes in milk yield and milk quality traits (n = 25 for each group of animals) were genotyped using the Illumina OvineSNP50 V2 BeadChip. The fixation index (F_ST) for each SNP was calculated between the diversified groups. F_ST values were Z-transformed and used to identify putative SNPs for further analysis (Z(F_ST) > 10). Genome-wide SNP analysis revealed genomic regions covering promising candidate genes related to milk performance traits such as SLC5A8, NUB1, TBC1D1, KLF3 and ABHD5 for milk yield and PPARA and FBLN1 genes for milk quality trait. The results of this study may contribute to the genetic improvement of milk performance traits in Barki sheep breed and to the general understanding of the genetic contribution to variability in milk yield and quality traits.

Detection of genomic regions underlying milk production traits in Valle del Belice dairy sheep using regional heritability mapping

The aim of this study was to identify genomic regions underlying milk production traits in the Valle del Belice dairy sheep using regional heritability mapping (RHM). Repeated measurements for milk yield (MY), fat percentage and yield (F% and FY) and protein percentage and yield (P% and PY), collected over a period of 6 years (2006–2012) on 481 Valle del Belice ewes, were used for the analysis. Animals were genotyped with the Illumina 50k SNP chip. Variance components, heritabilities and repeatabilities within and across lactations were estimated, fitting parity, litter size, season of lambing and fortnights in milk, as fixed; and additive genetic, permanent environment within and across lactations, flock by test‐day interaction and residual as random effects. For the RHM analysis, the model included the same fixed and random effects as before, plus an additional regional genomic additive effect (specific for the region being tested) as random. While the whole genomic additive effect was estimated using the genomic relationship matrix (GRM) constructed from all SNPs, the regional genomic additive effect was estimated from a GRM matrix constructed from the SNPs within each region. Heritability estimates ranged between 0.06 and 0.15, with repeatabilities being between 0.14 and 0.24 across lactations and between 0.23 and 0.39 within lactation for all milk production traits. A substantial effect of flock‐test‐day on milk production traits was also estimated. Significant genomic regions at either genome‐wide (p < .05) or suggestive (i.e., one false positive per genome scan) level were identified on chromosome (OAR) 2, 3 and 20 for F% and on OAR3 for P%, with the regions on OAR3 in common between the two traits. Our results confirmed the role of LALBA and AQP genes, on OAR3, as candidate genes for milk production traits in sheep.

Candidate genes for productivity identified by genome-wide association study with indicators of class in the Russian meat merino sheep breed

Genome-wide association studies allow identification of loci and polymorphisms associated with the formation of relevant phenotypes. When conducting a full genome analysis of sheep, particularly promising is the study of individuals with outstanding productivity indicators – exhibition animals, representatives of the super-elite class. The aim of this study was to identify new candidate genes for economically valuable traits based on the search for single nucleotide polymorphisms (SNPs) associated with belonging to different evaluation classes in rams of the Russian meat merino breed. Animal genotyping was performed using Ovine Infinium HD BeadChip 600K DNA, association search was performed using PLINK v. 1.07 software. Highly reliable associations were found between animals belonging to different evaluation classes and the frequency of occurrence of individual SNPs on chromosomes 2, 6, 10, 13, and 20. Most of the substitutions with high association reliability are concentrated on chromosome 10 in the region 10: 30859297–31873769. To search for candidate genes, 15 polymorphisms with the highest association reliability were selected (–log10(р) > 9). Determining the location of the analyzed SNPs relative to the latest annotation Oar_rambouillet_v1.0 allowed to identify 11 candidate genes presumably associated with the formation of a complex of phenotypic traits of animals in the exhibition group: RXFP2, ALOX5AP, MEDAG, OPN5, PRDM5, PTPRT, TRNAS-GGA, EEF1A1, FRY, ZBTB21-like, and B3GLCT-like. The listed genes encode proteins involved in the control of the cell cycle and DNA replication, regulation of cell proliferation and apoptosis, lipid and carbohydrate metabolism, the development of the inflammatory process and the work of circadian rhythms. Thus, the candidate genes under consideration can influence the formation of exterior features and productive qualities of sheep. However, further research is needed to confirm the influence of genes and determine the exact mechanisms for implementing this influence on the phenotype.

Transcriptome Analysis Reveals the Potential Role of Long Non-coding RNAs in Mammary Gland of Yak During Lactation and Dry Period

The mammary gland is a remarkably dynamic organ of milk synthesis and secretion, and it experiences drastic structural and metabolic changes during the transition from dry periods to lactation, which involves the expression and regulation of numerous genes and regulatory factors. Long non-coding RNA (lncRNA) has considered as a novel type of regulatory factors involved in a variety of biological processes. However, their role in the lactation cycle of yak is still poorly understood. To reveal the involved mechanism, Ribo-zero RNA sequencing was employed to profile the lncRNA transcriptome in mammary tissue samples from yak at two physiological stages, namely lactation (LP) and dry period (DP). Notably, 1,599 lncRNA transcripts were identified through four rigorous steps and filtered through protein-coding ability. A total of 59 lncRNAs showed significantly different expression between two stages. Accordingly, the results of qRT-PCR were consistent with that of the transcriptome data. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that target genes of differentially expressed lncRNAs (DELs) were involved in pathways related to lactation, such as ECM-receptor interaction, PI3K-Akt signaling pathway, biosynthesis of amino acids and focal adhesion etc. Finally, we constructed a lncRNA-gene regulatory network containing some well known candidate genes for milk yield and quality traits. This is the first study to demonstrate a global profile of lncRNA expression in the mammary gland of yak. These results contribute to a valuable resource for future genetic and molecular studies on improving milk yield and quality, and help us to gain a better understanding of the molecular mechanisms underlying lactogenesis and mammary gland development of yak.

Analysis of Whole Genome Resequencing Datasets from a Worldwide Sample of Sheep Breeds to Identify Potential Causal Mutations Influencing Milk Composition Traits

Different studies have shown that polymorphisms in the sequence of genes coding for the milk proteins and milk fatty acids are associated with milk composition traits as well as with cheese-making traits. However, the lack of coincident results across sheep populations has prevented the use of this information in sheep breeding programs. The main objective of this study was to exploit the information derived from a total of 175 whole genome resequencing (WGR) datasets from 43 domestic sheep breeds and three wild sheep to evaluate the genetic diversity of 24 candidate genes for milk composition and identify genetic variants with a potential phenotypic effect. The functional annotation of the identified variants highlighted five single nucleotide polymorphisms (SNPs) predicted to have a high impact on the protein function and 42 missense SNPs with a putative deleterious effect. When comparing the allelic frequencies at these 47 polymorphisms with relevant functional effects between the genomes of Assaf and Churra sheep breeds, two missense deleterious variants were identified as potential markers associated to the milk composition differences found between the Churra and Assaf: XDH:92215727C>T and LALBA:137390760T>C. Future research is required to confirm the effect of the potential functionally relevant variants identified in the present study on milk composition and cheese-making traits.

Gene Networks Driving Genetic Variation in Milk and Cheese-Making Traits of Spanish Assaf Sheep

Most of the milk produced by sheep is used for the production of high-quality cheese. Consequently, traits related to milk coagulation properties and cheese yield are economically important to the Spanish dairy industry. The present study aims to identify candidate genes and their regulators related to 14 milk and cheese-making traits and to develop a low-density panel of markers that could be used to predict an individual's genetic potential for cheese-making efficiency. In this study, we performed a combination of the classical genome-wide association study (GWAS) with a stepwise regression method and a pleiotropy analysis to determine the best combination of the variants located within the confidence intervals of the potential candidate genes that may explain the greatest genetic variance for milk and cheese-making traits. Two gene networks related to milk and cheese-making traits were created using the genomic relationship matrices built through a stepwise multiple regression approach. Several co-associated genes in these networks are involved in biological processes previously found to be associated with milk synthesis and cheese-making efficiency. The methodology applied in this study enabled the selection of a co-association network comprised of 374 variants located in the surrounding of genes showing a potential influence on milk synthesis and cheese-making efficiency.

Review on Genomic Regions and Candidate Genes Associated with Economically Important Production and Reproduction Traits in Sheep (Ovies aries)

Sheep (Ovis aries) is one of the most economically, culturally, and socially important domestic animals. They are reared primarily for meat, milk, wool, and fur production. Sheep were reared using natural selection for a long period of time to offer these traits. In fact, this production system has been slowing the productivity and production potential of the sheep. To improve production efficiency and productivity of this animal through genetic improvement technologies, understanding the genetic background of traits such as body growth, weight, carcass quality, fat percent, fertility, milk yield, wool quality, horn type, and coat color is essential. With the development and utilization of animal genotyping technologies and gene identification methods, many functional genes and genetic variants associated with economically important phenotypic traits have been identified and annotated. This is useful and presented an opportunity to increase the pace of animal genetic gain. Quantitative trait loci and genome wide association study have been playing an important role in identifying candidate genes and animal characterization. This review provides comprehensive information on the identified genomic regions and candidate genes associated with production and reproduction traits, and gene function in sheep.

Genetic and genomic analyses underpin the feasibility of concomitant genetic improvement of milk yield and mastitis resistance in dairy sheep

Milk yield is the most important dairy sheep trait and constitutes the key genetic improvement goal via selective breeding. Mastitis is one of the most prevalent diseases, significantly impacting on animal welfare, milk yield and quality, while incurring substantial costs. Our objectives were to determine the feasibility of a concomitant genetic improvement programme for enhanced milk production and resistance to mastitis. Individual records for milk yield, and four mastitis-related traits (milk somatic cell count, California Mastitis Test score, total viable bacterial count in milk and clinical mastitis presence) were collected monthly throughout lactation for 609 ewes of the Chios breed. All ewes were genotyped with a mastitis specific custom-made 960 single nucleotide polymorphism (SNP) array. We performed targeted genomic association studies, (co)variance component estimation and pathway enrichment analysis, and characterised gene expression levels and the extent of allelic expression imbalance. Presence of heritable variation for milk yield was confirmed. There was no significant genetic correlation between milk yield and mastitis traits. Environmental factors appeared to favour both milk production and udder health. There were no overlapping of SNPs associated with mastitis resistance and milk yield in Chios sheep. Furthermore, four distinct Quantitative Trait Loci (QTLs) affecting milk yield were detected on chromosomes 2, 12, 16 and 19, in locations other than those previously identified to affect mastitis resistance. Five genes (DNAJA1, GHR, LYPLA1, NUP35 and OXCT1) located within the QTL regions were highly expressed in both the mammary gland and milk transcriptome, suggesting involvement in milk synthesis and production. Furthermore, the expression of two of these genes (NUP35 and OXCT1) was enriched in immune tissues implying a potentially pleiotropic effect or likely role in milk production during udder infection, which needs to be further elucidated in future studies. In conclusion, the absence of genetic antagonism between milk yield and mastitis resistance suggests that simultaneous genetic improvement of both traits be achievable.

Mapping genomic regions affecting milk traits in Sarda sheep by using the OvineSNP50 Beadchip and principal components to perform combined linkage and linkage disequilibrium analysis

Background

The detection of regions that affect quantitative traits (QTL), to implement selection assisted by molecular information, remains of particular interest in dairy sheep for which genetic gain is constrained by the high costs of large-scale phenotype and pedigree recording. QTL detection based on the combination of linkage disequilibrium and linkage analysis (LDLA) is the most suitable approach in family-structured populations. The main issue in performing LDLA mapping is the handling of the identity-by-descent (IBD) probability matrix. Here, we propose the use of principal component analysis (PCA) to perform LDLA mapping for milk traits in Sarda dairy sheep.

Methods

A resource population of 3731 ewes belonging to 161 sire families and genotyped with the OvineSNP50 Beadchip was used to map genomic regions that affect five milk traits. The paternally and maternally inherited gametes of genotyped individuals were reconstructed and IBD probabilities between them were defined both at each SNP position and at the genome level. A QTL detection model fitting fixed effects of principal components that summarize IBD probabilities was tested at each SNP position. Genome-wide (GW) significance thresholds were determined by within-trait permutations.

Results

PCA resulted in substantial dimensionality reduction, in fact 137 and 32 (on average) principal components were able to capture 99% of the IBD variation at the locus and genome levels, respectively. Overall, 2563 positions exceeded the 0.05 GW significance threshold for at least one trait, which clustered into 75 QTL regions most of which affected more than one trait. The strongest signal was obtained for protein content on Ovis aries (OAR) chromosome 6 and overlapped with the region that harbours the casein gene cluster. Additional interesting positions were identified on OAR4 for fat content and on OAR11 for the three yield traits.

Conclusions

PCA is a good strategy to summarize IBD probabilities. A large number of regions associated to milk traits were identified. The outputs provided by the proposed method are useful for the selection of candidate genes, which need to be further investigated to identify causative mutations or markers in strong LD with them for application in selection programs assisted by molecular information.

Identification of genetic markers associated with milk production traits in Chinese Holstein cattle based on post genome-wide association studies

With the rapid development of dairy industry, the breeding process of dairy cows has been accelerated. In previous genome-wide association studies (GWAS), a large number of genetic markers have been reported which may contribute to the selection of Holstein populations with superior milk-producing traits, but they remain to be further verified before practical application. In this study, 90 single nucleotide polymorphisms (SNPs) were selected, which were reported to be significantly associated with five milk production traits, including 305-day milk yield (305MY), 305-day milk fat percent (305FC), 305-day milk protein percent (305PC), 305-day milk fat yield (305FY) and 305-day milk protein yield (305PY). Effective 305-day data and fresh DNA samples were obtained from 295 healthy cows with gestational age of 1-4. Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) was used to perform precise genotyping of these loci, followed by site association and haplotype analysis. Results showed that 36 out of 90 loci were supported to be used as genetic markers. In particular, several novel and effective haplotypes were also presented. Overall, our results verified tens of useful markers and provided a basis for further development of breeding strategies.

Genome-wide association study between CNVs and milk production traits in Valle del Belice sheep

Copy number variation (CNV) is a major source of genomic structural variation. The aim of this study was to detect genomic CNV regions (CNVR) in Valle del Belice dairy sheep population and to identify those affecting milk production traits. The GO analysis identified possible candidate genes and pathways related to the selected traits. We identified CNVs in 416 individuals genotyped using the Illumina OvineSNP50 BeadChip array. The CNV association using a correlation-trend test model was examined with the Golden Helix SVS 8.7.0 tool. Significant CNVs were detected when their adjusted p-value was <0.01 after false discovery rate (FDR) correction. We identified 7,208 CNVs, which gave 365 CNVRs after aggregating overlapping CNVs. Thirty-one CNVRs were significantly associated with one or more traits included in the analysis. All CNVRs, except those on OAR19, overlapped with quantitative trait loci (QTL), even if they were not directly related to the traits of interest. A total of 222 genes were annotated within the significantly associated CNVRs, most of which played important roles in biological processes related to milk production and health-related traits. Identification of the genes in the CNVRs associated with the studied traits will provide the basis for further investigation of their role in the metabolic pathways related to milk production and health traits.

Detection of quantitative trait loci and putative causal variants affecting somatic cell score in dairy sheep by using a 50K SNP chip and whole-genome sequencing

This study presents a scan of the ovine genome to identify quantitative trait loci (QTL) influencing the somatic cell score (SCS), a classical indicator of subclinical mastitis in sheep, and a subsequent high-resolution analysis of one of the identified QTL regions based on the analysis of whole-genome sequence data sets. A half-sib commercial population of Churra sheep genotyped with a 50K SNP chip was analyzed using linkage analysis (LA) and combined linkage and linkage disequilibrium analysis (LDLA). By LA, 2 5% chromosome-wide significant QTL on OAR5 and OAR25 and one 5% genome-wide significant QTL on ovine chromosome 20 (OAR20) were detected, whereas 22 significant associations were identified by LDLA. Two of the associations detected by LDLA replicated LA-detected effects (OAR20, OAR25). We compared the detected associations with previously reported QTL in sheep and cattle, and functional candidate genes were identified within the estimated confidence intervals. We then performed a high-resolution analysis of the OAR20 QTL region, the most significant QTL region identified by LA that replicated a QTL previously described in Churra sheep for SCS using microsatellite markers. For that, 2 segregating trios of 2 segregating families for the OAR20 QTL (each including the Qq sire and 2 daughters, QQ and qq) were selected for whole-genome sequencing. The bioinformatic analysis of the 6 sequenced samples performed across the genomic interval considered (14.2-41.7 Mb) identified a total of 227,030 variants commonly identified by 2 independent software packages. For the 3 different concordance tests considered, due to discrepancies regarding the QTL peak in the segregating families, the list of mutations concordant with the QTL segregating pattern was processed to identify the variants identified in immune-related genes that show a moderate/high impact on the encoded protein function. Among a list of 85 missense variants concordant with the QTL segregation pattern that were within candidate immune-related genes, 13 variants distributed across 7 genes [PKHD1, NOTCH4, AGER, ENSOARG00000009395 (HLA-C, Homo sapiens), ENSOARG00000015002 (HLA-B, H. sapiens), MOG, and ENSOARG00000018075 (BoLA, Bos taurus, orthologous to human HLA-A] were predicted to cause deleterious effects on protein function. Future studies should assess the possible associations of the candidate variants identified herein in commercial populations with indicator traits of udder inflammation (SCS, clinical mastitis).

Genome-wide scan for runs of homozygosity identifies potential candidate genes associated with local adaptation in Valle del Belice sheep

Background

Because very large numbers of single nucleotide polymorphisms (SNPs) are now available throughout the genome, they are particularly suitable for the detection of genomic regions where a reduction in heterozygosity has occurred and they offer new opportunities to improve the accuracy of inbreeding (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F) estimates. Runs of homozygosity (ROH) are contiguous lengths of homozygous segments of the genome where the two haplotypes inherited from the parents are identical. Here, we investigated the occurrence and distribution of ROH using a medium-dense SNP panel to characterize autozygosity in 516 Valle del Belice sheep and to identify the genomic regions with high ROH frequencies.

Results

We identified 11,629 ROH and all individuals displayed at least one ROH longer than 1 Mb. The mean value of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F$$\end{document}F estimated from ROH longer than1 Mb was 0.084 ± 0.061. ROH that were shorter than 10 Mb predominated. The highest and lowest coverages of Ovis aries chromosomes (OAR) by ROH were on OAR24 and OAR1, respectively. The number of ROH per chromosome length displayed a specific pattern, with higher values for the first three chromosomes. Both number of ROH and length of the genome covered by ROH varied considerably between animals. Two hundred and thirty-nine SNPs were considered as candidate markers that may be under directional selection and we identified 107 potential candidate genes. Six genomic regions located on six chromosomes, corresponding to ROH islands, are presented as hotspots of autozygosity, which frequently coincided with regions of medium recombination rate. According to the KEGG database, most of these genes were involved in multiple signaling and signal transduction pathways in a wide variety of cellular and biochemical processes. A genome scan revealed the presence of ROH islands in genomic regions that harbor candidate genes for selection in response to environmental stress and which underlie local adaptation.

Conclusions

These results suggest that natural selection has, at least partially, a role in shaping the genome of Valle del Belice sheep and that ROH in the ovine genome may help to detect genomic regions involved in the determinism of traits under selection.

Electronic supplementary material

The online version of this article (10.1186/s12711-017-0360-z) contains supplementary material, which is available to authorized users.

High-resolution analysis of selection sweeps identified between fine-wool Merino and coarse-wool Churra sheep breeds

BACKGROUND

With the aim of identifying selection signals in three Merino sheep lines that are highly specialized for fine wool production (Australian Industry Merino, Australian Merino and Australian Poll Merino) and considering that these lines have been subjected to selection not only for wool traits but also for growth and carcass traits and parasite resistance, we contrasted the OvineSNP50 BeadChip (50 K-chip) pooled genotypes of these Merino lines with the genotypes of a coarse-wool breed, phylogenetically related breed, Spanish Churra dairy sheep. Genome re-sequencing datasets of the two breeds were analyzed to further explore the genetic variation of the regions initially identified as putative selection signals.

RESULTS

Based on the 50 K-chip genotypes, we used the overlapping selection signals (SS) identified by four selection sweep mapping analyses (that detect genetic differentiation, reduced heterozygosity and patterns of haplotype diversity) to define 18 convergence candidate regions (CCR), five associated with positive selection in Australian Merino and the remainder indicating positive selection in Churra. Subsequent analysis of whole-genome sequences from 15 Churra and 13 Merino samples identified 142,400 genetic variants (139,745 bi-allelic SNPs and 2655 indels) within the 18 defined CCR. Annotation of 1291 variants that were significantly associated with breed identity between Churra and Merino samples identified 257 intragenic variants that caused 296 functional annotation variants, 275 of which were located across 31 coding genes. Among these, four synonymous and four missense variants (NPR2_His847Arg, NCAPG_Ser585Phe, LCORL_Asp1214Glu and LCORL_Ile1441Leu) were included.

CONCLUSIONS

Here, we report the mapping and genetic variation of 18 selection signatures that were identified between Australian Merino and Spanish Churra sheep breeds, which were validated by an additional contrast between Spanish Merino and Churra genotypes. Analysis of whole-genome sequencing datasets allowed us to identify divergent variants that may be viewed as candidates involved in the phenotypic differences for wool, growth and meat production/quality traits between the breeds analyzed. The four missense variants located in the NPR2, NCAPG and LCORL genes may be related to selection sweep regions previously identified and various QTL reported in sheep in relation to growth traits and carcass composition.

Detection of QTL for greasy fleece weight in sheep using a 50 K single nucleotide polymorphism chip

Genome-wide association studies (GWAS) have introduced an influential tool in the search for quantitative trait loci (QTL) influencing economically important traits in sheep. To identify QTL associated with greasy fleece weight, a GWAS with 50 K single nucleotide polymorphisms (SNPs) was performed in a Baluchi sheep population. Association with greasy fleece weights was tested using the software Plink. The results of our GWAS provided three novel SNP markers and candidate genes associated with greasy fleece weight. A total of three chromosome-wide significant associations were detected for SNP on chromosomes 17 and 20 affecting greasy fleece weight across the four shearing. One of the significant SNP markers was located within ovine known genes namely FAM101A. Further investigation of these identified regions in validation studies will facilitate the identification of strong candidate genes for wool production in sheep.

Variants in the 3' untranslated region of the ovine acetyl-coenzyme A acyltransferase 2 gene are associated with dairy traits and exhibit differential allelic expression

The acetyl-CoA acyltransferase 2 (ACAA2) gene encodes an enzyme of the thiolase family that is involved in mitochondrial fatty acid elongation and degradation by catalyzing the last step of the respective β-oxidation pathway. The increased energy needs for gluconeogenesis and triglyceride synthesis during lactation are met primarily by increased fatty acid oxidation. Therefore, the ACAA2 enzyme plays an important role in the supply of energy and carbon substrates for lactation and may thus affect milk production traits. This study investigated the association of the ACAA2 gene with important sheep traits and the putative functional involvement of this gene in dairy traits. A single nucleotide substitution, a T to C transition located in the 3' untranslated region of the ACAA2 gene, was used in mixed model association analysis with milk yield, milk protein yield and percentage, milk fat yield and percentage, and litter size at birth. The single nucleotide polymorphism was significantly associated with total lactation production and milk protein percentage, with respective additive effects of 6.81 ± 2.95 kg and -0.05 ± 0.02%. Additionally, a significant dominance effect of 0.46 ± 0.21 kg was detected for milk fat yield. Homozygous TT and heterozygous CT animals exhibited higher milk yield compared with homozygous CC animals, whereas the latter exhibited increased milk protein percentage. Expression analysis from age-, lactation-, and parity-matched female sheep showed that mRNA expression of the ACAA2 gene from TT animals was 2.8- and 11.8-fold higher in liver and mammary gland, respectively. In addition, by developing an allelic expression imbalance assay, it was estimated that the T allele was expressed at an average of 18% more compared with the C allele in the udder of randomly selected ewes. We demonstrated for the first time that the variants in the 3' untranslated region of the ovine ACAA2 gene are differentially expressed in homozygous ewes of each allele and exhibit allelic expression imbalance within heterozygotes in a tissue-specific manner, supporting the existence of cis-regulatory DNA variation in the ovine ACAA2 gene. This is the first study reporting differential allelic imbalance expression of a candidate gene associated with milk production traits in dairy sheep.

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.

Variant discovery in the sheep milk transcriptome using RNA sequencing

BACKGROUND

The identification of genetic variation underlying desired phenotypes is one of the main challenges of current livestock genetic research. High-throughput transcriptome sequencing (RNA-Seq) offers new opportunities for the detection of transcriptome variants (SNPs and short indels) in different tissues and species. In this study, we used RNA-Seq on Milk Sheep Somatic Cells (MSCs) with the goal of characterizing the genetic variation within the coding regions of the milk transcriptome in Churra and Assaf sheep, two common dairy sheep breeds farmed in Spain.

RESULTS

A total of 216,637 variants were detected in the MSCs transcriptome of the eight ewes analyzed. Among them, a total of 57,795 variants were detected in the regions harboring Quantitative Trait Loci (QTL) for milk yield, protein percentage and fat percentage, of which 21.44% were novel variants. Among the total variants detected, 561 (2.52%) and 1,649 (7.42%) were predicted to produce high or moderate impact changes in the corresponding transcriptional unit, respectively. In the functional enrichment analysis of the genes positioned within selected QTL regions harboring novel relevant functional variants (high and moderate impact), the KEGG pathway with the highest enrichment was "protein processing in endoplasmic reticulum". Additionally, a total of 504 and 1,063 variants were identified in the genes encoding principal milk proteins and molecules involved in the lipid metabolism, respectively. Of these variants, 20 mutations were found to have putative relevant effects on the encoded proteins.

CONCLUSIONS

We present herein the first transcriptomic approach aimed at identifying genetic variants of the genes expressed in the lactating mammary gland of sheep. Through the transcriptome analysis of variability within regions harboring QTL for milk yield, protein percentage and fat percentage, we have found several pathways and genes that harbor mutations that could affect dairy production traits. Moreover, remarkable variants were also found in candidate genes coding for major milk proteins and proteins related to milk fat metabolism. Several of the SNPs found in this study could be included as suitable markers in genotyping platforms or custom SNP arrays to perform association analyses in commercial populations and apply genomic selection protocols in the dairy production industry.

Unveiling genomic regions that underlie differences between Afec-Assaf sheep and its parental Awassi breed

BACKGROUND

Sheep production in Israel has improved by crossing the fat-tailed local Awassi breed with the East Friesian and later, with the Booroola Merino breed, which led to the formation of the highly prolific Afec-Assaf strain. This strain differs from its parental Awassi breed in morphological traits such as tail and horn size, coat pigmentation and wool characteristics, as well as in production, reproductive and health traits. To identify major genes associated with the formation of the Afec-Assaf strain, we genotyped 41 Awassi and 141 Afec-Assaf sheep using the Illumina Ovine SNP50 BeadChip array, and analyzed the results with PLINK and EMMAX software. The detected variable genomic regions that differed between Awassi and Afec-Assaf sheep (variable genomic regions; VGR) were compared to selection signatures that were reported in 48 published genome-wide association studies in sheep. Because the Afec-Assaf strain, but not the Awassi breed, carries the Booroola mutation, association analysis of BMPR1B used as the test gene was performed to evaluate the ability of this study to identify a VGR that includes such a major gene.

RESULTS

Of the 20 detected VGR, 12 were novel to this study. A ~7-Mb VGR was identified on Ovies aries chromosome OAR6 where the Booroola mutation is located. Similar to other studies, the most significant VGR was detected on OAR10, in a region that contains candidate genes affecting horn type (RXFP2), climate adaptation (ALOX5AP), fiber diameter (KATNAl1), coat pigmentation (FRY) and genes associated with fat distribution. The VGR on OAR2 included BNC2, which is also involved in controlling coat pigmentation in sheep. Six other VGR contained genes that were shown to be involved in coat pigmentation by analyzing their mammalian orthologues. Genes associated with fat distribution in humans, including GRB14 and COBLL1, were located in additional VGR. Sequencing DNA from Awassi and Afec-Assaf individuals revealed non-synonymous mutations in some of these candidate genes.

CONCLUSIONS

Our results highlight VGR that differentiate the Awassi breed from the Afec-Assaf strain, some of which may include genes that confer an advantage to Afec-Assaf and Assaf over Awassi sheep with respect to intensive sheep production under Mediterranean conditions.

Variations at regulatory regions of the milk protein genes are associated with milk traits and coagulation properties in the Sarda sheep

Regulatory variation at the ovine casein genes could have important effects on the composition and coagulation properties of milk. Herewith, we have partially resequenced the promoters and the 3'-UTR of the four casein genes in 25 Sarda sheep. Alignment of these sequences allowed us to identify a total of 29 SNPs. This level of polymorphism (one SNP every 250 bp) is remarkably high if compared with SNP densities estimated in human genic regions (approximately one SNP per bp). The 29 SNPs identified in our resequencing experiment, plus three previously reported SNPs mapping to the lactalbumin, alpha (LALBA) and β-lactoglobulin (BLG, also known as progestagen-associated endometrial protein, PAEP) genes, were genotyped with a multiplex TaqMan Open Array Real-Time PCR assay in 760 Sarda sheep with records for milk composition and coagulation properties. Association analysis revealed the existence of significant associations of CSN1S2 and CSN3 genotypes with milk protein and casein contents. Moreover, genotypes at CSN1S1 were significantly associated with rennet coagulation time, curd firming time and curd firmness, whereas CSN2 was associated with curd firming time. These results suggest that SNPs mapping to the promoters and 3'-UTRs of ovine casein genes may exert regulatory effects on gene expression and that they could be used for improving sheep milk quality and technological traits at the population level through marker assisted selection.

Implementation of an extended ZINB model in the study of low levels of natural gastrointestinal nematode infections in adult sheep

Background

In this study, two traits related with resistance to gastrointestinal nematodes (GIN) were measured in 529 adult sheep: faecal egg count (FEC) and activity of immunoglobulin A in plasma (IgA). In dry years, FEC can be very low in semi-extensive systems, such as the one studied here, which makes identifying animals that are resistant or susceptible to infection a difficult task. A zero inflated negative binomial model (ZINB) model was used to calculate the extent of zero inflation for FEC; the model was extended to include information from the IgA responses.

Results

In this dataset, 64 % of animals had zero FEC while the ZINB model suggested that 38 % of sheep had not been recently infected with GIN. Therefore 26 % of sheep were predicted to be infected animals with egg counts that were zero or below the detection limit and likely to be relatively resistant to nematode infection. IgA activities of all animals were then used to decide which of the sheep with zero egg counts had been exposed and which sheep had not been recently exposed. Animals with zero FEC and high IgA activity were considered resistant while animals with zero FEC and low IgA activity were considered as not recently infected. For the animals considered as exposed to the infection, the correlations among the studied traits were estimated, and the influence of these traits on the discrimination between unexposed and infected animals was assessed.

Conclusions

The model presented here improved the detection of infected animals with zero FEC. The correlations calculated here will be useful in the development of a reliable index of GIN resistance that could be of assistance for the study of host resistance in studies based on natural infection, especially in adult sheep, and also the design of breeding programs aimed at increasing resistance to parasites.

Electronic supplementary material

The online version of this article (doi:10.1186/s12917-016-0723-7) contains supplementary material, which is available to authorized users.

Detection and replication of QTL underlying resistance to gastrointestinal nematodes in adult sheep using the ovine 50K SNP array

BACKGROUND

Persistence of gastrointestinal nematode (GIN) infection and the related control methods have major impacts on the sheep industry worldwide. Based on the information generated with the Illumina OvineSNP50 BeadChip (50 K chip), this study aims at confirming quantitative trait loci (QTL) that were previously identified by microsatellite-based genome scans and identifying new QTL and allelic variants that are associated with indicator traits of parasite resistance in adult sheep. We used a commercial half-sib population of 518 Spanish Churra ewes with available data for fecal egg counts (FEC) and serum levels of immunoglobulin A (IgA) to perform different genome scan QTL mapping analyses based on classical linkage analysis (LA), a combined linkage disequilibrium and linkage analysis (LDLA) and a genome-wide association study (GWAS).

RESULTS

For the FEC and IgA traits, we detected a total of three 5 % chromosome-wise significant QTL by LA and 63 significant regions by LDLA, of which 13 reached the 5 % genome-wise significance level. The GWAS also revealed 10 significant SNPs associated with IgAt, although no significant associations were found for LFEC. Some of the significant QTL for LFEC that were detected by LA and LDLA on OAR6 overlapped with a highly significant QTL that was previously detected in a different half-sib population of Churra sheep. In addition, several new QTL and SNP associations were identified, some of which show correspondence with effects that were reported for different populations of young sheep. Other significant associations that did not coincide with previously reported associations could be related to the specific immune response of adult animals.

DISCUSSION

Our results replicate a FEC-related QTL located on OAR6 that was previously reported in Churra sheep and provide support for future research on the identification of the allelic variant that underlies this QTL. The small proportion of genetic variance explained by the detected QTL and the large number of functional candidate genes identified here are consistent with the hypothesis that GIN resistance/susceptibility is a complex trait that is not determined by individual genes acting alone but rather by complex multi-gene interactions. Future studies that combine genomic variation analysis and functional genomic information may help elucidate the biology of GIN disease resistance in sheep.

Genome-Wide Analysis Reveals Novel Regulators of Growth in Drosophila melanogaster

Organismal size depends on the interplay between genetic and environmental factors. Genome-wide association (GWA) analyses in humans have implied many genes in the control of height but suffer from the inability to control the environment. Genetic analyses in Drosophila have identified conserved signaling pathways controlling size; however, how these pathways control phenotypic diversity is unclear. We performed GWA of size traits using the Drosophila Genetic Reference Panel of inbred, sequenced lines. We find that the top associated variants differ between traits and sexes; do not map to canonical growth pathway genes, but can be linked to these by epistasis analysis; and are enriched for genes and putative enhancers. Performing GWA on well-studied developmental traits under controlled conditions expands our understanding of developmental processes underlying phenotypic diversity.

Genetic studies in Drosophila have elucidated conserved signaling pathways and environmental factors that together control organismal size. In humans, hundreds of genes are associated with height variation, but these associations have not been performed in a controlled environment. As a result we are still lacking an understanding of the mechanisms creating size variability within a species. Here, under carefully controlled environmental conditions, we identify naturally occurring genetic variants that are associated with size diversity in Drosophila. We identify a cluster of associations close to the kek1 locus, a well-characterized growth regulator, but otherwise find that most variants are located in or close to genes that do not belong to the conserved pathways but may interact with these in a biological network. We validate 33 novel growth regulatory genes that participate in diverse cellular processes, most notably cellular metabolism and cell polarity. This study is the first genome-wide association analysis of natural variants underlying size in Drosophila and our results complement the knowledge we have accumulated on this trait from mutational studies of single genes.

Characterization and Comparative Analysis of the Milk Transcriptome in Two Dairy Sheep Breeds using RNA Sequencing

This study presents a dynamic characterization of the sheep milk transcriptome aiming at achieving a better understanding of the sheep lactating mammary gland. Transcriptome sequencing (RNA-seq) was performed on total RNA extracted from milk somatic cells from ewes on days 10, 50, 120 and 150 after lambing. The experiment was performed in Spanish Churra and Assaf breeds, which differ in their milk production traits. Nearly 67% of the annotated genes in the reference genome (Oar_v3.1) were expressed in ovine milk somatic cells. For the two breeds and across the four lactation stages studied, the most highly expressed genes encoded caseins and whey proteins. We detected 573 differentially expressed genes (DEGs) across lactation points, with the largest differences being found, between day 10 and day 150. Upregulated GO terms at late lactation stages were linked mainly to developmental processes linked to extracellular matrix remodeling. A total of 256 annotated DEGs were detected in the Assaf and Churra comparison. Some genes selectively upregulated in the Churra breed grouped under the endopeptidase and channel activity GO terms. These genes could be related to the higher cheese yield of this breed. Overall, this study provides the first integrated overview on sheep milk gene expression.

Meta-analysis of genome-wide association from genomic prediction models

Genome-wide association (GWA) studies based on GBLUP models are a common practice in animal breeding. However, effect sizes of GWA tests are small, requiring larger sample sizes to enhance power of detection of rare variants. Because of difficulties in increasing sample size in animal populations, one alternative is to implement a meta-analysis (MA), combining information and results from independent GWA studies. Although this methodology has been used widely in human genetics, implementation in animal breeding has been limited. Thus, we present methods to implement a MA of GWA, describing the proper approach to compute weights derived from multiple genomic evaluations based on animal-centric GBLUP models. Application to real datasets shows that MA increases power of detection of associations in comparison with population-level GWA, allowing for population structure and heterogeneity of variance components across populations to be accounted for. Another advantage of MA is that it does not require access to genotype data that is required for a joint analysis. Scripts related to the implementation of this approach, which consider the strength of association as well as the sign, are distributed and thus account for heterogeneity in association phase between QTL and SNPs. Thus, MA of GWA is an attractive alternative to summarizing results from multiple genomic studies, avoiding restrictions with genotype data sharing, definition of fixed effects and different scales of measurement of evaluated traits.

Variability of the caprine whey protein genes and their association with milk yield, composition and renneting properties in the Sarda breed. 1. The LALBA gene

The 5' flanking region and 3' UTR of the caprine LALBA gene were analysed by SSCP and sequencing. A total of nine SNPs were detected: three in the promoter region, two were synonymous coding SNPs at exon-1, and four SNPs were in exon-4, within the 3'UTR. The nucleotide changes located in the promoter region (c.-358T>C, c.-163G>A, c.-121T>G) were genotyped by SSCP in 263 Sarda goats to evaluate their possible effect on milk yield, composition and renneting properties. We observed an effect of the three SNPs on milk yield and lactose content. Genotypes TT and CT at c.-358T>C (P A (P C and c.-121T>G were part of transcription factors binding sites, potentially involved in modulating the LALBA gene expression. The LALBA genotype affected renneting properties (P < 0.001), as heterozygotes c.-358CT and c.-163GA were characterised by delayed rennet coagulation time and curd firming time and the lowest value of curd firmness. The present investigation increases the panel of SNPs and adds new information about the effects of the caprine LALBA gene polymorphism.

Major Histocompatibility Complex class IIB polymorphism in an ancient Spanish breed

Genes from the Major Histocompatibility Complex class II region are involved in the presentation of antigens. Therefore, they have the key role in regulating the immune response and in the resistance to infections. We investigated the Major Histocompatibility Complex class IIB genes, DRB and DQB, in Churra sheep, one of the most important indigenous breeds of Spain. These genes are among the most polymorphic in the mammalian genome. Furthermore, often different numbers of class IIB genes per haplotype exist, complicating the genotyping and sequencing of these genes. Especially the DQB region is only partially characterized in sheep and the repertoire of DRB and DQB alleles in Churra sheep, an ancient breed, is unknown. Here, we sequenced the class IIB genes for 15 rams that are the pedigree heads of a selection Nucleus herd. In total, we found 12 DRB and 25 DQB alleles. From these, 3 and 15 were new, respectively. Fourteen haplotypes carrying one or two DQB alleles could be deduced and the evolutionary relationship of these was investigated by phylogenetic trees. Based on the sequences of these most common class II alleles, a more efficient genotyping system for larger numbers of Churra sheep will be developed.

Genome-wide association study for wool production traits in a Chinese Merino sheep population

Genome-wide association studies (GWAS) provide a powerful approach for identifying quantitative trait loci without prior knowledge of location or function. To identify loci associated with wool production traits, we performed a genome-wide association study on a total of 765 Chinese Merino sheep (JunKen type) genotyped with 50 K single nucleotide polymorphisms (SNPs). In the present study, five wool production traits were examined: fiber diameter, fiber diameter coefficient of variation, fineness dispersion, staple length and crimp. We detected 28 genome-wide significant SNPs for fiber diameter, fiber diameter coefficient of variation, fineness dispersion, and crimp trait in the Chinese Merino sheep. About 43% of the significant SNP markers were located within known or predicted genes, including YWHAZ, KRTCAP3, TSPEAR, PIK3R4, KIF16B, PTPN3, GPRC5A, DDX47, TCF9, TPTE2, EPHA5 and NBEA genes. Our results not only confirm the results of previous reports, but also provide a suite of novel SNP markers and candidate genes associated with wool traits. Our findings will be useful for exploring the genetic control of wool traits in sheep.

Genome-wide SNP scan in a porcine Large White×Minzhu intercross population reveals a locus influencing muscle mass on chromosome 2

A high-density single nucleotide polymorphism (SNP) array containing 62 163 markers was employed for a genome-wide association study (GWAS) to identify variants associated with lean meat in ham (LMH, %) and lean meat percentage (LMP, %) within a porcine Large White×Minzhu intercross population. For each individual, LMH and LMP were measured after slaughter at the age of 240±7 days. A total of 557 F2 animals were genotyped. The GWAS revealed that 21 SNPs showed significant genome-wide or chromosome-wide associations with LMH and LMP by the Genome-wide Rapid Association using Mixed Model and Regression-Genomic Control approach. Nineteen significant genome-wide SNPs were mapped to the distal end of Sus Scrofa Chromosome (SSC) 2, where a major known gene responsible for muscle mass, IGF2 is located. A conditioned analysis, in which the genotype of the strongest associated SNP is included as a fixed effect in the model, showed that those significant SNPs on SSC2 were derived from a single quantitative trait locus. The two chromosome-wide association SNPs on SSC1 disappeared after conditioned analysis suggested the association signal is a false association derived from using a F2 population. The present result is expected to lead to novel insights into muscle mass in different pig breeds and lays a preliminary foundation for follow-up studies for identification of causal mutations for subsequent application in marker-assisted selection programs for improving muscle mass in pigs.