Detailed phenotyping identifies genes with pleiotropic effects on body composition

Genomic Regions Associated with Resistance to Gastrointestinal Parasites in Australian Merino Sheep

The objective of this study was to identify genomic regions and genes associated with resistance to gastrointestinal nematodes in Australian Merino sheep in Uruguay, using the single-step GWAS methodology (ssGWAS), which is based on genomic estimated breeding values (GEBVs) obtained from a combination of pedigree, genomic, and phenotypic data. This methodology converts GEBVs into SNP effects. The analysis included 26,638 animals with fecal egg count (FEC) records obtained in two independent parasitic cycles (FEC1 and FEC2) and 1700 50K SNP genotypes. The comparison of genomic regions was based on genetic variances (gVar(%)) explained by non-overlapping regions of 20 SNPs. For FEC1 and FEC2, 18 and 22 genomic windows exceeded the significance threshold (gVar(%) ≥ 0.22%), respectively. The genomic regions with strong associations with FEC1 were located on chromosomes OAR 2, 6, 11, 21, and 25, and for FEC2 on OAR 5, 6, and 11. The proportion of genetic variance attributed to the top windows was 0.83% and 1.9% for FEC1 and FEC2, respectively. The 33 candidate genes shared between the two traits were subjected to enrichment analysis, revealing a marked enrichment in biological processes related to immune system functions. These results contribute to the understanding of the genetics underlying gastrointestinal parasite resistance and its implications for other productive and welfare traits in animal breeding programs.

Genomic regions, candidate genes, and pleiotropic variants associated with physiological and anatomical indicators of heat stress response in lactating sows

BACKGROUND

Heat stress (HS) poses significant threats to the sustainability of livestock production. Genetically improving heat tolerance could enhance animal welfare and minimize production losses during HS events. Measuring phenotypic indicators of HS response and understanding their genetic background are crucial steps to optimize breeding schemes for improved climatic resilience. The identification of genomic regions and candidate genes influencing the traits of interest, including variants with pleiotropic effects, enables the refinement of genotyping panels used to perform genomic prediction of breeding values and contributes to unraveling the biological mechanisms influencing heat stress response. Therefore, the main objectives of this study were to identify genomic regions, candidate genes, and potential pleiotropic variants significantly associated with indicators of HS response in lactating sows using imputed whole-genome sequence (WGS) data. Phenotypic records for 18 traits and genomic information from 1,645 lactating sows were available for the study. The genotypes from the PorcineSNP50K panel containing 50,703 single nucleotide polymorphisms (SNPs) were imputed to WGS and after quality control, 1,622 animals and 7,065,922 SNPs were included in the analyses.

RESULTS

A total of 1,388 unique SNPs located on sixteen chromosomes were found to be associated with 11 traits. Twenty gene ontology terms and 11 biological pathways were shown to be associated with variability in ear skin temperature, shoulder skin temperature, rump skin temperature, tail skin temperature, respiration rate, panting score, vaginal temperature automatically measured every 10 min, vaginal temperature measured at 0800 h, hair density score, body condition score, and ear area. Seven, five, six, two, seven, 15, and 14 genes with potential pleiotropic effects were identified for indicators of skin temperature, vaginal temperature, animal temperature, respiration rate, thermoregulatory traits, anatomical traits, and all traits, respectively.

CONCLUSIONS

Physiological and anatomical indicators of HS response in lactating sows are heritable but highly polygenic. The candidate genes found are associated with important gene ontology terms and biological pathways related to heat shock protein activities, immune response, and cellular oxidative stress. Many of the candidate genes with pleiotropic effects are involved in catalytic activities to reduce cell damage from oxidative stress and cellular mechanisms related to immune response.

Single-Cell Transcriptome Sequence Profiling on the Morphogenesis of Secondary Hair Follicles in Ordos Fine-Wool Sheep

The Ordos fine-wool sheep is a high-quality breed in China that produces superior natural textiles and raw materials such as wool and lamb meat. However, compared to the Australian Merino sheep, there is still a gap in terms of the wool fiber fineness and wool yield. The hair follicle is the main organ that controls the type of wool fiber, and the morphological changes in the secondary hair follicle are crucial in determining wool quality. However, the process and molecular mechanisms of hair follicle morphogenesis in Ordos fine-wool sheep are not yet clear. Therefore, analyzing the molecular mechanisms underlying the process of follicle formation is of great significance for improving the fiber diameter and wool production of Ordos fine-wool sheep. The differential expressed genes, APOD, POSTN, KRT5, and KRT15, which related to primary hair follicles and secondary hair follicles, were extracted from the dermal papillae. Based on pseudo-time analysis, the differentiation trajectories of dermal lineage cells and epidermal lineage cells in the Ordos fine-wool sheep were successfully constructed, providing a theoretical basis for breeding research in Ordos fine-wool sheep.

Genomic signatures of selection, local adaptation and production type characterisation of East Adriatic sheep breeds

BACKGROUND

The importance of sheep breeding in the Mediterranean part of the eastern Adriatic has a long tradition since its arrival during the Neolithic migrations. Sheep production system is extensive and generally carried out in traditional systems without intensive systematic breeding programmes for high uniform trait production (carcass, wool and milk yield). Therefore, eight indigenous Croatian sheep breeds from eastern Adriatic treated here as metapopulation (EAS), are generally considered as multipurpose breeds (milk, meat and wool), not specialised for a particular type of production, but known for their robustness and resistance to certain environmental conditions. Our objective was to identify genomic regions and genes that exhibit patterns of positive selection signatures, decipher their biological and productive functionality, and provide a "genomic" characterization of EAS adaptation and determine its production type.

RESULTS

We identified positive selection signatures in EAS using several methods based on reduced local variation, linkage disequilibrium and site frequency spectrum (eROHi, iHS, nSL and CLR). Our analyses identified numerous genomic regions and genes (e.g., desmosomal cadherin and desmoglein gene families) associated with environmental adaptation and economically important traits. Most candidate genes were related to meat/production and health/immune response traits, while some of the candidate genes discovered were important for domestication and evolutionary processes (e.g., HOXa gene family and FSIP2). These results were also confirmed by GO and QTL enrichment analysis.

CONCLUSIONS

Our results contribute to a better understanding of the unique adaptive genetic architecture of EAS and define its productive type, ultimately providing a new opportunity for future breeding programmes. At the same time, the numerous genes identified will improve our understanding of ruminant (sheep) robustness and resistance in the harsh and specific Mediterranean environment.

Genome-wide association study reveals candidate genes for traits related to meat quality in Colombian Creole hair sheep

Genome-wide association studies (GWAS) allow identifying genomic regions related to traits of economic importance in animals of zootechnical interest. The objective of this research was to conduct a genome-wide association study on meat quality traits using the Illumina OvineSNPs50 BeadChip array. The animals were sampled in the departments of Córdoba, Cesar, and Valle del Cauca. The genotypes obtained with the Illumina OvineSNP50 BeadChip microarray were analyzed SNP (single-nucleotide polymorphism) data to conduct a GWAS for pH and water-holding capacity (WHC) traits measured after 7 days of maturation, in the Longissimus dorsi (LD) muscle, in 167 Creole hair sheep of 12 months old belonging to Pelibuey (CHSP, n = 60), Ethiopian (CHSE, n = 44), and Sudan (CHSS, n = 63) breeds. The GWAS was done using a mixed linear model (MLMA) and based on the Ovis aries v3.1 genome. The CHSE showed the lowest meat juice release and, consequently, the highest water-holding capacity (WHC = 30.6 ± 0.1), suggesting that this breed has better performance in the meat industry compared with CHSS (WHC = 41.7 ± 0.1) and CHSP (WHC = 36.8 ± 0.1), since there is a relationship between WHC and juiciness. For the character pH, it was not possible to annotate genes related to meat quality, while, for the WHC, they have obtained 11 candidate genes associated (ELOVL2, ARAP2, LOC101102527, SHOC2, AIPL1, CSRNP3, IFRD, KDM8, NANS, DAPK1, IBN2, TPM2). Particularly, ELOVL2, ARAP2, IBN2, and TPM2 genes are involved in muscle contraction and fatty acid composition in sheep. In this study, we generated a baseline for GWAS related to meat quality traits in Colombian Creole hair sheep that can be used for future genomic selection plans.

NCAPG Regulates Myogenesis in Sheep, and SNPs Located in Its Putative Promoter Region Are Associated with Growth and Development Traits

Previously, NCAPG was identified as a candidate gene associated with sheep growth traits. This study aimed to investigate the direct role of NCAPG in regulating myogenesis in embryonic myoblast cells and to investigate the association between single-nucleotide polymorphisms (SNPs) in its promoter region and sheep growth traits. The function of NCAPG in myoblast proliferation and differentiation was detected after small interfering RNAs (siRNAs) knocked down the expression of NCAPG. Cell proliferation was detected using CCK-8 assay, EdU proliferation assay, and flow cytometry cell cycle analysis. Cell differentiation was detected via cell immunofluorescence and the quantification of myogenic regulatory factors (MRFs). SNPs in the promoter region were detected using Sanger sequencing and genotyped using the improved multiplex ligation detection reaction (iMLDR®) technique. As a result, a notable decrease (p < 0.01) in the percentage of EdU-positive cells in the siRNA-694-treated group was observed. A significant decrease (p < 0.01) in cell viability after treatment with siRNA-694 for 48 h and 72 h was detected using the CCK-8 method. The quantity of S-phase cells in the siRNA-694 treatment group was significantly decreased (p < 0.01). After interfering with NCAPG in myoblasts during induced differentiation, the relative expression levels of MRFs were markedly (p < 0.05 or p < 0.01) reduced compared with the control group on days 5-7. The myoblast differentiation in the siRNA-694 treatment group was obviously suppressed compared with the control group. SNP1, SNP2, SNP3, and SNP4 were significantly (p < 0.05) associated with all traits except body weight measured at birth and one month of age. SNP5 was significantly (p < 0.05) associated with body weight, body height, and body length in six-month-old sheep. In conclusion, interfering with NCAPG can inhibit the proliferation and differentiation of ovine embryonic myoblasts. SNPs in its promoter region can serve as potential useful markers for selecting sheep growth traits.

Uncovering the candidate genes related to sheep body weight using multi-trait genome-wide association analysis

In sheep, body weight is an economically important trait. This study sought to map genetic loci related to weaning weight and yearling weight. To this end, a single-trait and multi-trait genome-wide association study (GWAS) was performed using a high-density 600 K single nucleotide polymorphism (SNP) chip. The results showed that 43 and 56 SNPs were significantly associated with weaning weight and yearling weight, respectively. A region associated with both weaning and yearling traits (OARX: 6.74-7.04 Mb) was identified, suggesting that the same genes could play a role in regulating both these traits. This region was found to contain three genes (TBL1X, SHROOM2 and GPR143). The most significant SNP was Affx-281066395, located at 6.94 Mb (p = 1.70 × 10-17), corresponding to the SHROOM2 gene. We also identified 93 novel SNPs elated to sheep weight using multi-trait GWAS analysis. A new genomic region (OAR10: 76.04-77.23 Mb) with 22 significant SNPs were discovered. Combining transcriptomic data from multiple tissues and genomic data in sheep, we found the HINT1, ASB11 and GPR143 genes may involve in sheep body weight. So, multi-omic anlaysis is a valuable strategy identifying candidate genes related to body weight.

Copy Number Variation Regions Differing in Segregation Patterns Span Different Sets of Genes

Copy number variations regions (CNVRs) can be classified either as segregating, when found in both parents, and offspring, or non-segregating. A total of 65 segregating and 31 non-segregating CNVRs identified in at least 10 individuals within a dense pedigree of the Gochu Asturcelta pig breed was subjected to enrichment and functional annotation analyses to ascertain their functional independence and importance. Enrichment analyses allowed us to annotate 1018 and 351 candidate genes within the bounds of the segregating and non-segregating CNVRs, respectively. The information retrieved suggested that the candidate genes spanned by segregating and non-segregating CNVRs were functionally independent. Functional annotation analyses allowed us to identify nine different significantly enriched functional annotation clusters (ACs) in segregating CNVR candidate genes mainly involved in immunity and regulation of the cell cycle. Up to five significantly enriched ACs, mainly involved in reproduction and meat quality, were identified in non-segregating CNVRs. The current analysis fits with previous reports suggesting that segregating CNVRs would explain performance at the population level, whereas non-segregating CNVRs could explain between-individuals differences in performance.

Genome-Wide Search for Associations with Meat Production Parameters in Karachaevsky Sheep Breed Using the Illumina BeadChip 600 K

In a group of Karachaevsky rams, a genome-wide associations analysis of single nucleotide polymorphisms (SNPs) with live parameters of meat production was performed. We used for genotyping the Ovine Infinium HD BeadChip 600 K, which consists of points to detection of 606,000 polymorphisms. A total of 12 SNPs was found to be significantly associated with live meat quality parameters of the corpus and legs and ultrasonic traits. In this case, 11 candidate genes were described, the polymorphic variants of which can change in sheep body parameters. We found SNPs in the exons, introns, and other regions of some genes and transcripts: CLVS1, EVC2, KIF13B, ENSOART00000000511.1, KCNH5, NEDD4, LUZP2, MREG, KRT20, KRT23 and FZD6. The described genes involved in the metabolic pathways of cell differentiation, proliferation and apoptosis are connected with the regulation of the gastrointestinal, immune and nervous systems. In known productivity genes (MSTN, MEF2B, FABP4, etc.), loci were not found to be a significant presence of influence on the meat productivity of the Karachaevsky sheep phenotypes. Our study confirms the possible involvement of the identified candidate genes in the formation of the phenotypes of productivity traits in sheep and indicates the need for new research into candidate genes structure in point to detect their polymorphisms.

Identification of Candidate Genes and Functional Pathways Associated with Body Size Traits in Chinese Holstein Cattle Based on GWAS Analysis

Body size is one of the most economically important traits of dairy cattle, as it is significantly associated with cow longevity, production, health, fertility, and environmental adaptation. The identification and application of genetic variants using a novel genetic approach, such as genome-wide association studies (GWASs), may give more insights into the genetic architecture of complex traits. The identification of genes, single nucleotide polymorphisms (SNPs), and pathways associated with the body size traits may offer a contribution to genomic selection and long-term planning for selection in dairy cows. In this study, we performed GWAS analysis to identify the genetic markers and genes associated with four body size traits (body height, body depth, chest width, and angularity) in 1000 Chinese Holstein cows. We performed SNPs genotyping in 1000 individuals, based on the GeneSeek Genomic Profiler Bovine 100 K. In total, we identified 11 significant SNPs in association with body size traits at the threshold of Bonferroni correction (5.90 × 10−7) using the fixed and random model circulating probability unification (FarmCPU) model. Several genes within 200 kb distances (upstream or downstream) of the significant SNPs were identified as candidate genes, including MYH15, KHDRBS3, AIP, DCC, SQOR, and UBAP1L. Moreover, genes within 200 kb of the identified SNPs were significantly enriched (p ≤ 0.05) in 25 Gene Ontology terms and five Kyoto Encyclopedia of Genes and Genomes pathways. We anticipate that these results provide a foundation for understanding the genetic architecture of body size traits. They will also contribute to breeding programs and genomic selection work on Chinese Holstein cattle.

Genome-Wide Association Analysis Identified Variants Associated with Body Measurement and Reproduction Traits in Shaziling Pigs

With the increasing popularity of genomic sequencing, breeders pay more attention to identifying the crucial molecular markers and quantitative trait loci for improving the body size and reproduction traits that could affect the production efficiency of pig-breeding enterprises. Nevertheless, for the Shaziling pig, a well-known indigenous breed in China, the relationship between phenotypes and their corresponding genetic architecture remains largely unknown. Herein, in the Shaziling population, a total of 190 samples were genotyped using the Geneseek Porcine 50K SNP Chip, obtaining 41857 SNPs for further analysis. For phenotypes, two body measurement traits and four reproduction traits in the first parity from the 190 Shaziling sows were measured and recorded, respectively. Subsequently, a genome-wide association study (GWAS) between the SNPs and the six phenotypes was performed. The correlation between body size and reproduction phenotypes was not statistically significant. A total of 31 SNPs were found to be associated with body length (BL), chest circumference (CC), number of healthy births (NHB), and number of stillborns (NSB). Gene annotation for those candidate SNPs identified 18 functional genes, such as GLP1R, NFYA, NANOG, COX7A2, BMPR1B, FOXP1, SLC29A1, CNTNAP4, and KIT, which exert important roles in skeletal morphogenesis, chondrogenesis, obesity, and embryonic and fetal development. These findings are helpful to better understand the genetic mechanism for body size and reproduction phenotypes, while the phenotype-associated SNPs could be used as the molecular markers for the pig breeding programs.

Screening Indels from the whole genome to identify the candidates and their association with economic traits in several goat breeds

In the present study, the re-sequencing of our previous whole-genome sequencing (WGS) for selected individuals of Dazu-black goat (DBG) and Inner-Mongolia Cashmere goat (IMCG) breeds was used to detect and compare the differentiation in Indels depending on the reference genome of goat. Then, three selected candidate Indels rs668795676, rs657996810, and rs669452874 of the three genes SUFU, SYCP2L and GLIPR1L1, respectively, have been chosen, based on the results of prior GWAS across the genome, and examined for their association with body weight and dimensions (body height, body length, heart girth, chest width, cannon circumference, and chest depth) by kompetitive allele specific PCR assay for 342 goats from the three studied goat breeds (DBG, n = 203; ♂99, ♀104), IMCG (n = 65; 15♂, 50♀), and Hechuan white goat (HWG, n = 74; 34♂, 40♀) breeds. The analysis of 192.747 Gb WGS revealed an average 334,151 Indels in the whole genome of DBG and IMCG breeds. Chromosome 1 had a maximum number of mutations (Indels) of 58,497 and 55,527 for IMCG and DBG, respectively, while chromosome 25 had the least number of mutations of 15,680 and 16,103 for IMCG and DBG, respectively. The majority of Indels were either Ins or Del of short fragments of 1-5 bp, which covered 79.06 and 71.78% of the total number of Indels mutations in IMCG and DBG, respectively. Comparing the differences of Indels between the studied goat breeds revealed 100 and 110 unique Indels for IMCG and DBG, respectively. The Indels loci in the intron region were unique for both studied goat breeds which were related to 30 and 38 candidate genes in IMCG and DBG, respectively, including SUFU, SYCP2L, and GLIPR1L1 genes. Concerning rs669452874 locus, body height and body length of Del/Del genotype in DBG were significantly higher (P < 0.05) than that of Ins/Del genotype, while body height and body length of Del/Del genotype in IMCG were significantly higher (P < 0.01) than those of Ins/Ins genotype, whereas body height and body length and heart girth of Del/Del genotype in HWG were significantly higher (P < 0.01) than those of the Ins/Del and Ins/Ins genotypes. Thus, Del/Del genotype of rs669452874 locus can be used as a candidate molecular marker related to the body dimensions in the studied goat breeds.

Genome-Wide Association Study for Body Conformation Traits and Fitness in Czech Holsteins

The aim of this study was a genome-wide association study (GWAS) on conformation traits using 25,486 genotyped Czech Holsteins, with 35,227 common SNPs for each genotype. Linear trait records were collected between 1995 and 2020. The Interbull information from Multiple Across Country Evaluation (MACE) was included for bulls that mostly had daughter records in a foreign country. When using the Bonferroni correction, the number of SNPs that were either significant or approached the significance threshold was low-dairy capacity composite on BTA4, feet and legs composite BTA21, total score BTA10, stature BTA24, body depth BTA6, angularity BTA20, fore udder attachment BTA10. Without the Bonferroni correction, the total number of significant or near of significance SNPs was 32. The SNPs were localized on BTA1,2,4,5,6,7,8,18,22,25,26,28 for dairy capacity composite, BTA15,21 for feet and legs composite, BTA10 for total score, BTA24 stature, BTA6,23 body depth, BTA20 angularity, BTA2 rump angle, BTA9,10 rear legs rear view, BTA2,19 rear legs side view, BTA10 fore udder attachment, BTA2 udder depth, BTA10 rear udder height, BTA12 central alignment, BTA24 rear teat placement, BTA8,29 rear udder width. The results provide biological information for the improvement of body conformation and fitness in the Holstein population.

Genetics of the phenotypic evolution in sheep: a molecular look at diversity-driving genes

BACKGROUND

After domestication, the evolution of phenotypically-varied sheep breeds has generated rich biodiversity. This wide phenotypic variation arises as a result of hidden genomic changes that range from a single nucleotide to several thousands of nucleotides. Thus, it is of interest and significance to reveal and understand the genomic changes underlying the phenotypic variation of sheep breeds in order to drive selection towards economically important traits.

REVIEW

Various traits contribute to the emergence of variation in sheep phenotypic characteristics, including coat color, horns, tail, wool, ears, udder, vertebrae, among others. The genes that determine most of these phenotypic traits have been investigated, which has generated knowledge regarding the genetic determinism of several agriculturally-relevant traits in sheep. In this review, we discuss the genomic knowledge that has emerged in the past few decades regarding the phenotypic traits in sheep, and our ultimate aim is to encourage its practical application in sheep breeding. In addition, in order to expand the current understanding of the sheep genome, we shed light on research gaps that require further investigation.

CONCLUSIONS

Although significant research efforts have been conducted in the past few decades, several aspects of the sheep genome remain unexplored. For the full utilization of the current knowledge of the sheep genome, a wide practical application is still required in order to boost sheep productive performance and contribute to the generation of improved sheep breeds. The accumulated knowledge on the sheep genome will help advance and strengthen sheep breeding programs to face future challenges in the sector, such as climate change, global human population growth, and the increasing demand for products of animal origin.

New Insight into the Role of the Leucine Aminopeptidase 3 (LAP3) in Cell Proliferation and Myogenic Differentiation in Sheep Embryonic Myoblasts

Previous genome-wide association studies (GWAS) have found that LAP3 may have the potential function to impact sheep muscle development. In order to further explore whether LAP3 expression has an important role in the development of sheep embryonic myoblasts, we conducted the spatiotemporal expression profile analysis of LAP3 at the tissue and cellular level. Then we used small interfering RNA and eukaryotic recombinant vectors to perform gain/loss-of-function analysis of LAP3. CCK-8 detection, EdU staining, and flow cytometry were used to investigate the impact of LAP3 knockdown or overexpression on the proliferation of embryonic myoblasts. In addition, cell phenotype observation, MyHC indirect immunofluorescence, and quantitative detection of the expression changes of myogenic regulatory factors (MRFs) were used to explore the effect of LAP3 on myogenic differentiation. The results showed that the LAP3 expression level in muscle tissue of fetuses was significantly higher than that in newborn lambs and adult sheep, and its expression level on day 3 of differentiation was also significantly higher than that in the proliferation phase and other differentiation time points. LAP3 silencing could significantly increase cell viability and EdU-positive cells, as well as prolonging the length of S phase of myoblasts to promote proliferation, while the results were reversed when LAP3 was overexpressed. Moreover, LAP3 silencing significantly hindered myotube formation and down-regulated the expression levels of MRFs from day 5 to day 7 of terminal differentiation, while the results were reversed when LAP3 was highly expressed. Overall, our results suggested that the expression of LAP3 impacts on the development of sheep embryonic myoblasts which provides an important theoretical basis for molecular breeding of meat production in sheep.

The GWAS-MAP|ovis platform for aggregation and analysis of genome-wide association study results in sheep

In recent years, the number of genome-wide association studies (GWAS) carried out for various economically important animal traits has been increasing. GWAS discoveries provide summary statistics that can be used both for targeted marker-oriented selection and for studying the genetic control of economically important traits of farm animals. In contrast to research in human genetics, GWAS on farm animals often does not meet generally accepted standards (availability of information about effect and reference alleles, the size and direction of the effect, etc.). This greatly complicates the use of GWAS results for breeding needs. Within the framework of human genetics, there are several technological solutions for researching the harmonized results of GWAS, including one of the largest, the GWAS-MAP platform. For other types of living organisms, including economically important agricultural animals, there are no similar solutions. To our knowledge, no similar solution has been proposed to date for any of the species of economically important animals. As part of this work, we focused on creating a platform similar to GWAS-MAP for working with the results of GWAS of sheep, since sheep breeding is one of the most important branches of agriculture. By analogy with the GWAS-MAP platform for storing, unifying and analyzing human GWAS, we have created the GWAS-MAP|ovis platform. The platform currently contains information on more than 34 million associations between genomic sequence variants and traits of meat production in sheep. The platform can also be used to conduct colocalization analysis, a method that allows one to determine whether the association of a particular locus with two different traits is the result of pleiotropy or whether these traits are associated with different variants that are in linkage disequilibrium. This platform will be useful for breeders to select promising markers for breeding, as well as to obtain information for the introduction of genomic breeding and for scientists to replicate the results obtained.

Detection of selection signatures in South African Mutton Merino sheep using whole-genome sequencing data

The South African Mutton Merino (SAMM), a dual-purpose (meat and wool) sheep breed, is characterized by its excellent performance on growth, carcass traits and meat quality compared to other fine-wool Merino breeds. Nowadays, the SAMM breed has been widely used to cross with commercial and indigenous fine-wool or coarse-wool breeds to improve the growth and meat performance in many countries. To date, however, little is known about the genetic basis for its prominent characteristics. In this study, whole-genome sequences of 10 SAMM were sequenced and the selection signatures were analyzed together with those of 39 Australian Merino and Chinese Merino (wool-type Merino) by F_ST , iHS, and XP-EHH methods. In total, 313 genes in 277 regions were identified by at least 2 methods with the signal of selection and 21 of them were identified by all three methods. We highlighted a list of interesting genes, including GHR, LCORL, SMO, NCAPG, DCC, IBSP, PPARGC1A, PACRGL, PRDM5, XYLB, AHCYL2, TEFM, AFG1L, and FAM184B, which have been shown to be involved in growth, carcass traits, and meat quality by previous studies. Herein, GHR, encoding a transmembrane receptor for growth hormone, is the most notable one. We report the first study on selection signatures analysis of SAMM at whole-genome sequence level. These results provide new insights into the genetic mechanisms underlying the growth and carcass traits in SAMM.

Runs of homozygosity analysis reveals consensus homozygous regions affecting production traits in Chinese Simmental beef cattle

BACKGROUND

Genomic regions with a high frequency of runs of homozygosity (ROH) are related to important traits in farm animals. We carried out a comprehensive analysis of ROH and evaluated their association with production traits using the BovineHD (770 K) SNP array in Chinese Simmental beef cattle.

RESULTS

We detected a total of 116,953 homozygous segments with 2.47Gb across the genome in the studied population. The average number of ROH per individual was 99.03 and the average length was 117.29 Mb. Notably, we detected 42 regions with a frequency of more than 0.2. We obtained 17 candidate genes related to body size, meat quality, and reproductive traits. Furthermore, using Fisher's exact test, we found 101 regions were associated with production traits by comparing high groups with low groups in terms of production traits. Of those, we identified several significant regions for production traits (P < 0.05) by association analysis, within which candidate genes including ECT2, GABRA4, and GABRB1 have been previously reported for those traits in beef cattle.

CONCLUSIONS

Our study explored ROH patterns and their potential associations with production traits in beef cattle. These results may help to better understand the association between production traits and genome homozygosity and offer valuable insights into managing inbreeding by designing reasonable breeding programs in farm animals.

A conditional multi-trait sequence GWAS discovers pleiotropic candidate genes and variants for sheep wool, skin wrinkle and breech cover traits

Background

Imputation to whole-genome sequence is now possible in large sheep populations. It is therefore of interest to use this data in genome-wide association studies (GWAS) to investigate putative causal variants and genes that underpin economically important traits. Merino wool is globally sought after for luxury fabrics, but some key wool quality attributes are unfavourably correlated with the characteristic skin wrinkle of Merinos. In turn, skin wrinkle is strongly linked to susceptibility to “fly strike” (Cutaneous myiasis), which is a major welfare issue. Here, we use whole-genome sequence data in a multi-trait GWAS to identify pleiotropic putative causal variants and genes associated with changes in key wool traits and skin wrinkle.

Results

A stepwise conditional multi-trait GWAS (CM-GWAS) identified putative causal variants and related genes from 178 independent quantitative trait loci (QTL) of 16 wool and skin wrinkle traits, measured on up to 7218 Merino sheep with 31 million imputed whole-genome sequence (WGS) genotypes. Novel candidate gene findings included the MAT1A gene that encodes an enzyme involved in the sulphur metabolism pathway critical to production of wool proteins, and the ESRP1 gene. We also discovered a significant wrinkle variant upstream of the HAS2 gene, which in dogs is associated with the exaggerated skin folds in the Shar-Pei breed.

Conclusions

The wool and skin wrinkle traits studied here appear to be highly polygenic with many putative candidate variants showing considerable pleiotropy. Our CM-GWAS identified many highly plausible candidate genes for wool traits as well as breech wrinkle and breech area wool cover.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00651-0.

Integration of a single-step genome-wide association study with a multi-tissue transcriptome analysis provides novel insights into the genetic basis of wool and weight traits in sheep

BACKGROUND

Genetic improvement of wool and growth traits is a major goal in the sheep industry, but their underlying genetic architecture remains elusive. To improve our understanding of these mechanisms, we conducted a weighted single-step genome-wide association study (WssGWAS) and then integrated the results with large-scale transcriptome data for five wool traits and one growth trait in Merino sheep: mean fibre diameter (MFD), coefficient of variation of the fibre diameter (CVFD), crimp number (CN), mean staple length (MSL), greasy fleece weight (GFW), and live weight (LW).

RESULTS

Our dataset comprised 7135 individuals with phenotype data, among which 1217 had high-density (HD) genotype data (n = 372,534). The genotypes of 707 of these animals were imputed from the Illumina Ovine single nucleotide polymorphism (SNP) 54 BeadChip to the HD Array. The heritability of these traits ranged from 0.05 (CVFD) to 0.36 (MFD), and between-trait genetic correlations ranged from - 0.44 (CN vs. LW) to 0.77 (GFW vs. LW). By integrating the GWAS signals with RNA-seq data from 500 samples (representing 87 tissue types from 16 animals), we detected tissues that were relevant to each of the six traits, e.g. liver, muscle and the gastrointestinal (GI) tract were the most relevant tissues for LW, and leukocytes and macrophages were the most relevant cells for CN. For the six traits, 54 quantitative trait loci (QTL) were identified covering 81 candidate genes on 21 ovine autosomes. Multiple candidate genes showed strong tissue-specific expression, e.g. BNC1 (associated with MFD) and CHRNB1 (LW) were specifically expressed in skin and muscle, respectively. By conducting phenome-wide association studies (PheWAS) in humans, we found that orthologues of several of these candidate genes were significantly (FDR < 0.05) associated with similar traits in humans, e.g. BNC1 was significantly associated with MFD in sheep and with hair colour in humans, and CHRNB1 was significantly associated with LW in sheep and with body mass index in humans.

CONCLUSIONS

Our findings provide novel insights into the biological and genetic mechanisms underlying wool and growth traits, and thus will contribute to the genetic improvement and gene mapping of complex traits in sheep.

Non-additive association analysis using proxy phenotypes identifies novel cattle syndromes

Mammalian species carry ~100 loss-of-function variants per individual^1,2, where ~1-5 of these impact essential genes and cause embryonic lethality or severe disease when homozygous³. The functions of the remainder are more difficult to resolve, although the assumption is that these variants impact fitness in less manifest ways. Here we report one of the largest sequence-resolution screens of cattle to date, targeting discovery and validation of non-additive effects in 130,725 animals. We highlight six novel recessive loci with impacts generally exceeding the largest-effect variants identified from additive genome-wide association studies, presenting analogs of human diseases and hitherto-unrecognized disorders. These loci present compelling missense (PLCD4, MTRF1 and DPF2), premature stop (MUS81) and splice-disrupting (GALNT2 and FGD4) mutations, together explaining substantial proportions of inbreeding depression. These results demonstrate that the frequency distribution of deleterious alleles segregating in selected species can afford sufficient power to directly map novel disorders, presenting selection opportunities to minimize the incidence of genetic disease.

Multivariate Analysis Identifies Eight Novel Loci Associated with Meat Productivity Traits in Sheep

Despite their economic value, sheep remain relatively poorly studied animals in terms of the number of known loci and genes associated with commercially important traits. This gap in our knowledge can be filled in by performing new genome-wide association studies (GWAS) or by re-analyzing previously documented data using novel powerful statistical methods. This study is focused on the search for new loci associated with meat productivity and carcass traits in sheep. With a multivariate approach applied to publicly available GWAS results, we identified eight novel loci associated with the meat productivity and carcass traits in sheep. Using an in silico follow-up approach, we prioritized 13 genes in these loci. One of eight novel loci near the FAM3C and WNT16 genes has been replicated in an independent sample of Russian sheep populations (N = 108). The novel loci were added to our regularly updated database increasing the number of known loci to more than 140.

Expression quantitative trait loci in sheep liver and muscle contribute to variations in meat traits

Background

Variants that regulate transcription, such as expression quantitative trait loci (eQTL), have shown enrichment in genome-wide association studies (GWAS) for mammalian complex traits. However, no study has reported eQTL in sheep, although it is an important agricultural species for which many GWAS of complex meat traits have been conducted. Using RNA sequence data produced from liver and muscle from 149 sheep and imputed whole-genome single nucleotide polymorphisms (SNPs), our aim was to dissect the genetic architecture of the transcriptome by associating sheep genotypes with three major molecular phenotypes including gene expression (geQTL), exon expression (eeQTL) and RNA splicing (sQTL). We also examined these three types of eQTL for their enrichment in GWAS of multi-meat traits and fatty acid profiles.

Results

Whereas a relatively small number of molecular phenotypes were significantly heritable (h² > 0, P < 0.05), their mean heritability ranged from 0.67 to 0.73 for liver and from 0.71 to 0.77 for muscle. Association analysis between molecular phenotypes and SNPs within ± 1 Mb identified many significant cis-eQTL (false discovery rate, FDR < 0.01). The median distance between the eQTL and transcription start sites (TSS) ranged from 68 to 153 kb across the three eQTL types. The number of common variants between geQTL, eeQTL and sQTL within each tissue, and the number of common variants between liver and muscle within each eQTL type were all significantly (P < 0.05) larger than expected by chance. The identified eQTL were significantly (P < 0.05) enriched in GWAS hits associated with 56 carcass traits and fatty acid profiles. For example, several geQTL in muscle mapped to the FAM184B gene, hundreds of sQTL in liver and muscle mapped to the CAST gene, and hundreds of sQTL in liver mapped to the C6 gene. These three genes are associated with body composition or fatty acid profiles.

Conclusions

We detected a large number of significant eQTL and found that the overlap of variants between eQTL types and tissues was prevalent. Many eQTL were also QTL for meat traits. Our study fills a gap in the knowledge on the regulatory variants and their role in complex traits for the sheep model.

Runs of homozygosity analysis of South African sheep breeds from various production systems investigated using OvineSNP50k data

Background

Population history, production system and within-breed selection pressure impacts the genome architecture resulting in reduced genetic diversity and increased frequency of runs of homozygosity islands. This study tested the hypothesis that production systems geared towards specific traits of importance or natural or artificial selection pressures influenced the occurrence and distribution of runs of homozygosity (ROH) in the South African sheep population. The Illumina OvineSNP50 BeadChip was used to genotype 400 sheep belonging to 13 breeds from South Africa representing mutton, pelt and mutton and wool dual-purpose breeds, including indigenous non-descript breeds that are reared by smallholder farmers. To get more insight into the autozygosity and distribution of ROH islands of South African breeds relative to global populations, 623 genotypes of sheep from worldwide populations were included in the analysis. Runs of homozygosity were computed at cut-offs of 1–6 Mb, 6–12 Mb, 12–24 Mb, 24–48 Mb and > 48 Mb, using the R package detectRUNS. The Golden Helix SVS program was used to investigate the ROH islands.

Results

A total of 121,399 ROH with mean number of ROH per animal per breed ranging from 800 (African White Dorper) to 15,097 (Australian Poll Dorset) were obtained. Analysis of the distribution of ROH according to their size showed that, for all breeds, the majority of the detected ROH were in the short (1–6 Mb) category (88.2%). Most animals had no ROH > 48 Mb. Of the South African breeds, the Nguni and the Blackhead Persian displayed high ROH based inbreeding (F_ROH) of 0.31 ± 0.05 and 0.31 ± 0.04, respectively. Highest incidence of common runs per SNP across breeds was observed on chromosome 10 with over 250 incidences of common ROHs. Mean proportion of SNPs per breed per ROH island ranged from 0.02 ± 0.15 (island ROH224 on chromosome 23) to 0.13 ± 0.29 (island ROH175 on chromosome 15). Seventeen (17) of the islands had SNPs observed in single populations (unique ROH islands). The MacArthur Merino (MCM) population had five unique ROH islands followed by Blackhead Persian and Nguni with three each whilst the South African Mutton Merino, SA Merino, White Vital Swakara, Karakul, Dorset Horn and Chinese Merino each had one unique ROH island. Genes within ROH islands were associated with predominantly metabolic and immune response traits and predomestic selection for traits such as presence or absence of horns.

Conclusions

Overall, the frequency and patterns of distribution of ROH observed in this study corresponds to the breed history and implied selection pressures exposed to the sheep populations under study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07314-2.

All sheeps and sizes: a genetic investigation of mature body size across sheep breeds reveals a polygenic nature

Mature body size is genetically correlated with growth rate, an important economic trait in the sheep industry. Mature body size has been studied extensively in humans as well as cattle and other domestic animal populations but not in sheep. Six‐hundred and sixteen ewes, across 22 breeds, were measured for 28 linear measurements representing various skeletal parts. PCA from these measures generated principal components 1 and 2 which represented 66 and 7% of the phenotypic variation respectively. Two‐hundred and twenty sheep were genotyped on the Illumina Ovine HD beadchip for a GWAS investigating mature body size and linear body measurements. Forty‐six (Bonferroni P < 0.05) SNP associations across 14 chromosomes were identified utilizing principal component 1, representing overall body size, revealing mature body size to have fewer loci of large effect than other domestic species such as dogs and horses. Genome‐wide associations for individual linear measures identified major quantitative trait loci for withers height and ear length. Withers height was associated (Bonferroni P < 0.05) with 12 SNPs across six chromosomes whereas ear length was associated with a single locus on chromosome 3, containing MSRB3. This analysis identified several loci known to be associated with mature body size in other species such as NCAPG, LCORL, and HMGA2. Mature body size is more polygenic in sheep than other domesticated species, making the development of genomic selection for the trait the most efficient option for maintaining or reducing mature body size in sheep.

Meta-analysis of GWAS in canola blackleg (Leptosphaeria maculans) disease traits demonstrates increased power from imputed whole-genome sequence

Blackleg disease causes yield losses in canola (Brassica napus L.). To identify resistance genes and genomic regions, genome-wide association studies (GWAS) of 585 diverse winter and spring canola accessions were performed using imputed whole-genome sequence (WGS) and transcriptome genotype-by-sequencing (GBSt). Blackleg disease phenotypes were collected across three years in six trials. GWAS were performed in several ways and their respective power was judged by the number of significant single nucleotide polymorphisms (SNP), the false discovery rate (FDR), and the percentage of SNP that validated in additional field trials in two subsequent years. WGS GWAS with 1,234,708 million SNP detected a larger number of significant SNP, achieved a lower FDR and a higher validation rate than GBSt with 64,072 SNP. A meta-analysis combining survival and average internal infection resulted in lower FDR but also lower validation rates. The meta-analysis GWAS identified 79 genomic regions (674 SNP) conferring potential resistance to L. maculans. While several GWAS signals localised in regions of known Rlm genes, fifty-three new potential resistance regions were detected. Seventeen regions had underlying genes with putative functions related to disease defence or stress response in Arabidopsis thaliana. This study provides insight into the genetic architecture and potential molecular mechanisms underlying canola L. maculans resistance.

Genetic correlations between meat quality traits and growth and carcass traits in Merino sheep1

Genetic correlations between 16 meat quality and nutritional value traits and live weight at various ages, live ultrasound fat and muscle depth, carcass measures, and carcass dissection traits were estimated for Merino sheep in the Information Nucleus (IN). Genetic correlations between live weight at various ages and the carcass traits are also reported. The IN comprised 8 genetically linked flocks managed across a range of Australian sheep environments. Meat quality traits included between 1,200 and 1,300 records for progeny from over 170 sires for intramuscular fat (IMF), lean meat yield (LMY), shear force (SF5), pH, meat color, and meat nutritional value traits including iron and zinc levels and long-chain omega-3 and omega-6 polyunsaturated fatty acid levels. The genetic correlations indicated that selection of Merino sheep to either reduce fat or increase muscle using ultrasound assessments will result in little change in IMF and SF5. Myoglobin levels would tend to be reduced following selection for reduced ultrasound fat depth (0.35 ± 0.21, 0.43 ± 0.14), whereas increases in myoglobin levels would occur due to selection for increased ultrasound muscle depth (0.25 ± 0.24, 0.38 ± 0.15). Selection for increased live weight will result in favorable correlated responses in hot carcass weight (0.76 to 0.97), dressing percentage (0.13 to 0.47), and carcass muscle (0.37 to 0.95), but unfavorable responses of increases in carcass fatness (0.13 to 0.65) and possible small reductions in muscle oxidative activity (-0.13 ± 0.14 to -0.73 ± 0.33) and iron content (-0.14 ± 0.15 to -0.38 ± 0.16), and a possible deterioration of shear force from selection at later ages (0.15 ± 0.26, 0.27 ± 0.24). Negligible changes are generally expected for LMY and meat color traits following selection for increased live weight (most genetic correlations less than 0.20 in size). Selection for increased LMY would tend to result in unfavorable changes in several aspects of meat quality, including reduced IMF (-0.27 ± 0.18), meat tenderness (0.53 ± 0.26), and meat redness (-0.69 ± 0.40), as well as reduced iron levels (-0.25 ± 0.22). These genetic correlations are a first step in assisting the development of breeding values for new traits to be incorporated into genetic evaluation programs to improve meat production from Merino sheep and other dual-purpose sheep breeds.

Recent advances in understanding genetic variants associated with growth, carcass and meat productivity traits in sheep (Ovis aries): an update

Identification of quantitative trait loci (QTLs) and candidate genes that affect growth intensity is a prerequisite for the marker-assisted selection of economically important traits. The number of QTL studies on sheep is relatively small in comparison to those on cattle and pigs. The current QTL sheep database - Sheep QTLdb - contains information on 1658 QTLs for 225 different traits. A few genes and markers associated with growth, carcass and meat productivity traits have been reported. The information about QTLs from the Sheep QTLdb cannot be directly used in marker-assisted selection due to the lack of essential information such as effective and reference alleles, the effect direction etc., and it requires manual curation and validation. In this study we performed a comprehensive search for QTLs focusing on single nucleotide polymorphisms (SNPs) associated with growth and meat traits in sheep. The database contains information about 156 SNP-trait associations (123 unique SNPs) and a list of 165 associated genes. The updated information is freely available at https://github.com/Defrag1236/Ovines_2018 (last access: 18 September 2019). This information can be useful for further association studies and preliminary estimation of genetic variability for economically important traits in different breeds.

Using imputed whole-genome sequence data to improve the accuracy of genomic prediction for parasite resistance in Australian sheep

Background

This study aimed at (1) comparing the accuracies of genomic prediction for parasite resistance in sheep based on whole-genome sequence (WGS) data to those based on 50k and high-density (HD) single nucleotide polymorphism (SNP) panels; (2) investigating whether the use of variants within quantitative trait loci (QTL) regions that were selected from regional heritability mapping (RHM) in an independent dataset improved the accuracy more than variants selected from genome-wide association studies (GWAS); and (3) comparing the prediction accuracies between variants selected from WGS data to variants selected from the HD SNP panel.

Results

The accuracy of genomic prediction improved marginally from 0.16 ± 0.02 and 0.18 ± 0.01 when using all the variants from 50k and HD genotypes, respectively, to 0.19 ± 0.01 when using all the variants from WGS data. Fitting a GRM from the selected variants alongside a GRM from the 50k SNP genotypes improved the prediction accuracy substantially compared to fitting the 50k SNP genotypes alone. The gain in prediction accuracy was slightly more pronounced when variants were selected from WGS data compared to when variants were selected from the HD panel. When sequence variants that passed the GWAS \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$- log_{10} (p\,value)$$\end{document}-log10(pvalue) threshold of 3 across the entire genome were selected, the prediction accuracy improved by 5% (up to 0.21 ± 0.01), whereas when selection was limited to sequence variants that passed the same GWAS \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$- log_{10} (p\,value)$$\end{document}-log10(pvalue) threshold of 3 in regions identified by RHM, the accuracy improved by 9% (up to 0.25 ± 0.01).

Conclusions

Our results show that through careful selection of sequence variants from the QTL regions, the accuracy of genomic prediction for parasite resistance in sheep can be improved. These findings have important implications for genomic prediction in sheep.

Dissecting closely linked association signals in combination with the mammalian phenotype database can identify candidate genes in dairy cattle

BACKGROUND

Genome-wide association studies (GWAS) have been successfully implemented in cattle research and breeding. However, moving from the associations to identify the causal variants and reveal underlying mechanisms have proven complicated. In dairy cattle populations, we face a challenge due to long-range linkage disequilibrium (LD) arising from close familial relationships in the studied individuals. Long range LD makes it difficult to distinguish if one or multiple quantitative trait loci (QTL) are segregating in a genomic region showing association with a phenotype. We had two objectives in this study: 1) to distinguish between multiple QTL segregating in a genomic region, and 2) use of external information to prioritize candidate genes for a QTL along with the candidate variants.

RESULTS

We observed fixing the lead SNP as a covariate can help to distinguish additional close association signal(s). Thereafter, using the mammalian phenotype database, we successfully found candidate genes, in concordance with previous studies, demonstrating the power of this strategy. Secondly, we used variant annotation information to search for causative variants in our candidate genes. The variant information successfully identified known causal mutations and showed the potential to pinpoint the causative mutation(s) which are located in coding regions.

CONCLUSIONS

Our approach can distinguish multiple QTL segregating on the same chromosome in a single analysis without manual input. Moreover, utilizing information from the mammalian phenotype database and variant effect predictor as post-GWAS analysis could benefit in candidate genes and causative mutations finding in cattle. Our study not only identified additional candidate genes for milk traits, but also can serve as a routine method for GWAS in dairy cattle.

Association between the GHR, GHRHR, and IGF1 gene polymorphisms and milk yield and quality traits in Sarda sheep

The growth hormone receptor (GHR), the growth hormone releasing hormone receptor (GHRHR), and the insulin-like growth factor 1 (IGF1) genes are known to modulate growth, reproduction, and lactation traits in livestock. The aim of the current work was to investigate if the variation of the sheep GHR, GHRHR, and IGF1 genes is associated with milk yield and quality traits. Three hundred eighty dairy Sarda sheep were genotyped for 36 single nucleotide polymorphisms (SNP) mapping to these 3 loci, and records for milk yield and daily fat and protein yield, as well as for fat, protein, casein, lactose, and milk urea contents, pH, somatic cell score, logarithmic bacterial count, and milk energy were obtained. The linkage disequilibrium analysis was performed only for GHR, as both GHRHR and IGF1 had only 1 polymorphic SNP. Haplotype analysis revealed the existence of 7 haplotype blocks in GHR. Two haplotype blocks, including part of the intron 1 and the upstream region, were clearly separated from the remaining 5 blocks by SNP rs412986330, which may be a recombination hotspot. The latter 5 blocks were contiguous, spanning from intron 2 to exon 10. Statistical analysis revealed that the GHR polymorphism is significantly associated with milk traits for daily fat and protein yield and fat, milk urea, and lactose content. Moreover, variation in IGF1 was associated with milk protein and casein content. Data generated in this research provide new insights into the allelic effects of the ovine GHRHR, GHR, and IGF1 genes on milk production and quality traits, information that may be useful in gene-assisted selection programs.

Genome variants associated with RNA splicing variations in bovine are extensively shared between tissues

Background

Mammalian phenotypes are shaped by numerous genome variants, many of which may regulate gene transcription or RNA splicing. To identify variants with regulatory functions in cattle, an important economic and model species, we used sequence variants to map a type of expression quantitative trait loci (expression QTLs) that are associated with variations in the RNA splicing, i.e., sQTLs. To further the understanding of regulatory variants, sQTLs were compare with other two types of expression QTLs, 1) variants associated with variations in gene expression, i.e., geQTLs and 2) variants associated with variations in exon expression, i.e., eeQTLs, in different tissues.

Results

Using whole genome and RNA sequence data from four tissues of over 200 cattle, sQTLs identified using exon inclusion ratios were verified by matching their effects on adjacent intron excision ratios. sQTLs contained the highest percentage of variants that are within the intronic region of genes and contained the lowest percentage of variants that are within intergenic regions, compared to eeQTLs and geQTLs. Many geQTLs and sQTLs are also detected as eeQTLs. Many expression QTLs, including sQTLs, were significant in all four tissues and had a similar effect in each tissue. To verify such expression QTL sharing between tissues, variants surrounding (±1 Mb) the exon or gene were used to build local genomic relationship matrices (LGRM) and estimated genetic correlations between tissues. For many exons, the splicing and expression level was determined by the same cis additive genetic variance in different tissues. Thus, an effective but simple-to-implement meta-analysis combining information from three tissues is introduced to increase power to detect and validate sQTLs. sQTLs and eeQTLs together were more enriched for variants associated with cattle complex traits, compared to geQTLs. Several putative causal mutations were identified, including an sQTL at Chr6:87392580 within the 5th exon of kappa casein (CSN3) associated with milk production traits.

Conclusions

Using novel analytical approaches, we report the first identification of numerous bovine sQTLs which are extensively shared between multiple tissue types. The significant overlaps between bovine sQTLs and complex traits QTL highlight the contribution of regulatory mutations to phenotypic variations.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4902-8) contains supplementary material, which is available to authorized users.

Estimates of genomic heritability and genome-wide association study for fatty acids profile in Santa Inês sheep

BACKGROUND

Despite the health concerns and nutritional importance of fatty acids, there is a relative paucity of studies in the literature that report genetic or genomic parameters, especially in the case of sheep populations. To investigate the genetic architecture of fatty acid composition of sheep, we conducted genome-wide association studies (GWAS) and estimated genomic heritabilities for fatty acid profile in Longissimus dorsi muscle of 216 male sheep.

RESULTS

Genomic heritability estimates for fatty acid content ranged from 0.25 to 0.46, indicating that substantial genetic variation exists for the evaluated traits. Therefore, it is possible to alter fatty acid profiles through selection. Twenty-seven genomic regions of 10 adjacent SNPs associated with fatty acids composition were identified on chromosomes 1, 2, 3, 5, 8, 12, 14, 15, 16, 17, and 18, each explaining ≥0.30% of the additive genetic variance. Twenty-three genes supporting the understanding of genetic mechanisms of fat composition in sheep were identified in these regions, such as DGAT2, TRHDE, TPH2, ME1, C6, C7, UBE3D, PARP14, and MRPS30.

CONCLUSIONS

Estimates of genomic heritabilities and elucidating important genomic regions can contribute to a better understanding of the genetic control of fatty acid deposition and improve the selection strategies to enhance meat quality and health attributes.

Dissecting closely linked association signals in combination with the mammalian phenotype database can identify candidate genes in dairy cattle

Background

Genome-wide association studies (GWAS) have been successfully implemented in cattle research and breeding. However, moving from the associations to identifying the causal variants and revealing underlying mechanisms have proven complicated. In dairy cattle populations, we face a challenge due to long-range linkage disequilibrium (LD) arising from close familial relationships in the studied individuals. Long range LD makes it difficult to distinguish if one or multiple quantitative trait loci (QTL) are segregating in a genomic region showing association with a phenotype. We had two objectives in this study: 1) to distinguish between multiple QTL segregating in a genomic region, and 2) use of external information to prioritize candidate genes for a QTL along with the candidate variant.

Results

We observed fixing the lead SNP as a covariate can help to distinguish additional close association signal(s). Thereafter, using the mammalian phenotype database, we successfully found candidate genes, in concordance with previous studies, demonstrating the power of this strategy. Secondly, we used variant annotation information to search for causative variants in our candidate genes. The variant information successfully identified known causal mutations and showed the potential to pinpoint the causative mutation(s) which are located in coding regions.

Conclusions

Our approach can distinguish multiple QTL segregating on the same chromosome in a single analysis without manual input. Moreover, utilizing information from the mammalian phenotype database and variant effect predictor as post-GWAS analysis could benefit in candidate genes and causative mutations finding in cattle. Our study not only identified additional candidate genes for milk traits, but also can serve as a routine method for GWAS in dairy cattle.

Electronic supplementary material

The online version of this article (10.1186/s12863-018-0620-0) contains supplementary material, which is available to authorized users.

Genetic correlations between wool traits and meat quality traits in Merino sheep

Genetic correlations between 29 wool production and quality traits and 25 meat quality and nutritional value traits were estimated for Merino sheep from an Information Nucleus (IN). Genetic correlations among the meat quality and nutritional value traits are also reported. The IN comprised 8 flocks linked genetically and managed across a range of sheep production environments in Australia. The wool traits included over 5,000 yearling and 3,700 adult records for fleece weight, fiber diameter, staple length, staple strength, fiber diameter variation, scoured wool color, and visual scores for breech and body wrinkle. The meat quality traits were measured on samples from the and included over 1,200 records from progeny of over 170 sires for intramuscular fat (IMF), shear force of meat aged for 5 d (SF5), 24 h postmortem pH (pHLL; also measured in the , pHST), fresh and retail meat color and meat nutritional value traits such as iron and zinc levels, and long-chain omega-3 and omega-6 polyunsaturated fatty acid levels. Estimated heritabilities for IMF, SF5, pHLL, pHST, retail meat color lightness (), myoglobin, iron, zinc and across the range of long-chain fatty acids were 0.58 ± 0.11, 0.10 ± 0.09, 0.15 ± 0.07, 0.20 ± 0.10, 0.59 ± 0.15, 0.31 ± 0.09, 0.20 ± 0.09, 0.11 ± 0.09, and range of 0.00 (eicosapentaenoic, docosapentaenoic, and arachidonic acids) to 0.14 ± 0.07 (linoleic acid), respectively. The genetic correlations between the wool production and meat quality traits were low to negligible and indicate that wool breeding programs will have little or no effect on meat quality. There were moderately favorable genetic correlations between important yearling wool production traits and the omega-3 fatty acids that were reduced for corresponding adult wool production traits, but these correlations are unlikely to be important in wool/meat breeding programs because they have high SE, and the omega-3 traits have little or no genetic variance. Significant genetic correlations among the meat quality traits included IMF with SF5 (-0.76 ± 0.24), fresh meat color * (0.50 ± 0.18), and zinc (0.41 ± 0.19). Selection to increase IMF will improve meat tenderness and color which may address some of the issues with Merino meat quality. These estimated parameters allow Merino breeders to combine wool and meat objectives without compromising meat quality.

First High-Density Linkage Map and Single Nucleotide Polymorphisms Significantly Associated With Traits of Economic Importance in Yellowtail Kingfish Seriola lalandi

The genetic resources available for the commercially important fish species Yellowtail kingfish (YTK) (Seriola lalandi) are relative sparse. To overcome this, we aimed (1) to develop a linkage map for this species, and (2) to identify markers/variants associated with economically important traits in kingfish (with an emphasis on body weight). Genetic and genomic analyses were conducted using 13,898 single nucleotide polymorphisms (SNPs) generated from a new high-throughput genotyping by sequencing platform, Diversity Arrays Technology (DArTseq^TM) in a pedigreed population comprising 752 animals. The linkage analysis enabled to map about 4,000 markers to 24 linkage groups (LGs), with an average density of 3.4 SNPs per cM. The linkage map was integrated into a genome-wide association study (GWAS) and identified six variants/SNPs associated with body weight (P < 5e^-8) when a multi-locus mixed model was used. Two out of the six significant markers were mapped to LGs 17 and 23, and collectively they explained 5.8% of the total genetic variance. It is concluded that the newly developed linkage map and the significantly associated markers with body weight provide fundamental information to characterize genetic architecture of growth-related traits in this population of YTK S. lalandi.

Genome-wide comparative analyses of correlated and uncorrelated phenotypes identify major pleiotropic variants in dairy cattle

While single nucleotide polymorphisms (SNPs) associated with multiple phenotype have been reported, the knowledge of pleiotropy of uncorrelated phenotype is minimal. Principal components (PCs) and uncorrelated Cholesky transformed traits (CT) were constructed using 25 raw traits (RTs) of 2841 dairy bulls. Multi-trait meta-analyses of single-trait genome-wide association studies for RT, PC and CT in bulls were validated in 6821 cows. Most PCs and CTs had substantial estimates of heritability, suggesting that genes affect phenotype via diverse pathways. Phenotypic orthogonalizations did not eliminate pleiotropy: the meta-analysis achieved an agreement of significant pleiotropic SNPs (p < 1 × 10-5, n = 368) between RTs (416), PCs (466) and CTs (425). From this overlap we identified 21 lead SNPs with 100% validation rate containing two clusters: one consisted of DGAT1 (chr14:1.8 M+), MGST1 (chr5:93 M+), PAEP (chr11:103 M+) and GPAT4 (chr27:36 M+) affecting protein, milk and fat yield and the other included CSN2 (chr6:87 M+), MUC1 (chr3:15.6 M), GHR (chr20:31.2 M+) and SDC2 (chr14:70 M+) affecting protein and milk yield. Combining beef cattle data identified correlated SNPs representing CAPN1 (chr29:44 M+) and CAST (chr 7:96 M+) loci affecting beef tenderness, showing pleiotropic effects in dairy cattle. Our findings show that SNPs with a large effect on one trait are likely to have small effects on other uncorrelated traits.

Multiple-trait QTL mapping and genomic prediction for wool traits in sheep

BACKGROUND

The application of genomic selection to sheep breeding could lead to substantial increases in profitability of wool production due to the availability of accurate breeding values from single nucleotide polymorphism (SNP) data. Several key traits determine the value of wool and influence a sheep's susceptibility to fleece rot and fly strike. Our aim was to predict genomic estimated breeding values (GEBV) and to compare three methods of combining information across traits to map polymorphisms that affect these traits.

METHODS

GEBV for 5726 Merino and Merino crossbred sheep were calculated using BayesR and genomic best linear unbiased prediction (GBLUP) with real and imputed 510,174 SNPs for 22 traits (at yearling and adult ages) including wool production and quality, and breech conformation traits that are associated with susceptibility to fly strike. Accuracies of these GEBV were assessed using fivefold cross-validation. We also devised and compared three approximate multi-trait analyses to map pleiotropic quantitative trait loci (QTL): a multi-trait genome-wide association study and two multi-trait methods that use the output from BayesR analyses. One BayesR method used local GEBV for each trait, while the other used the posterior probabilities that a SNP had an effect on each trait.

RESULTS

BayesR and GBLUP resulted in similar average GEBV accuracies across traits (~0.22). BayesR accuracies were highest for wool yield and fibre diameter (>0.40) and lowest for skin quality and dag score (<0.10). Generally, accuracy was higher for traits with larger reference populations and higher heritability. In total, the three multi-trait analyses identified 206 putative QTL, of which 20 were common to the three analyses. The two BayesR multi-trait approaches mapped QTL in a more defined manner than the multi-trait GWAS. We identified genes with known effects on hair growth (i.e. FGF5, STAT3, KRT86, and ALX4) near SNPs with pleiotropic effects on wool traits.

CONCLUSIONS

The mean accuracy of genomic prediction across wool traits was around 0.22. The three multi-trait analyses identified 206 putative QTL across the ovine genome. Detailed phenotypic information helped to identify likely candidate genes.

Genetic correlations between wool traits and carcass traits in Merino sheep

Genetic correlations between 29 wool production and quality traits and 14 whole carcass measures and carcass component traits were estimated from the Information Nucleus of 8 flocks managed across a range of Australian sheep production environments and genetically linked. Wool data were from over 5,000 Merino progeny born over 5 yr, whereas carcass data were from over 1,200 wether progeny of over 176 sires, slaughtered at about 21 kg carcass weight, on average. Wool traits included yearling and adult records for wool weight, fiber diameter, fiber diameter variation, staple strength, scoured color, and visual scores for breech and body wrinkle. Whole carcass measures included HCW, dressing percentage (DP), and various measures of fat depth and eye muscle dimensions. Carcass components were obtained by dissection, and lean meat yield (LMY) was predicted. Heritability estimates for whole carcass measures ranged from 0.12 ± 0.08 to 0.35 ± 0.10 and ranged from 0.17 ± 0.10 to 0.46 ± 0.10 for carcass dissection traits, with no evidence of important genotype × environment interactions. Genetic correlations indicated that selection for increased clean wool weight will result in reduced carcass fat (-0.17 to -0.34) and DP (-0.48 ± 0.15), with little effect on carcass muscle. Selection for lower fiber diameter will reduce HCW (-0.48 ± 0.15) as well as carcass fat (0.14 to 0.27) and muscle (0.21 to 0.50). There were high genetic correlations between live animal measures of fat and muscle depth and the carcass traits (generally greater than 0.5 in size). Selection to increase HCW (and DP) will result in sheep with fewer wrinkles on the body (-0.57 ± 0.10) and barer breeches (-0.74 ± 0.12, favorable), with minor deterioration in scoured wool color (reduced brightness and increased yellowness). Selection for reduced fat will also result in sheep with fewer body wrinkles (-0.42 to -0.79). Increasing LMY in Merinos through selection would result in a large reduction in carcass fat and DP (-0.66 to -0.84), with a smaller increase in carcass muscle and some increase in wool weight and wrinkles. Although no major antagonisms are apparent between the wool and carcass traits, developing selection indexes for dual-purpose wool and meat breeding objectives will require accurate estimates of genetic parameters to ensure that unfavorable relationships are suitably considered. The findings will aid development of dual-purpose wool and meat breeding objectives.

Combined GWAS and 'guilt by association'-based prioritization analysis identifies functional candidate genes for body size in sheep

Background

Body size in sheep is an important indicator of productivity, growth and health as well as of environmental adaptation. It is a composite quantitative trait that has been studied with high-throughput genomic methods, i.e. genome-wide association studies (GWAS) in various mammalian species. Several genomic markers have been associated with body size traits and genes have been identified as causative candidates in humans, dog and cattle. A limited number of related GWAS have been performed in various sheep breeds and have identified genomic regions and candidate genes that partly account for body size variability. Here, we conducted a GWAS in Frizarta dairy sheep with phenotypic data from 10 body size measurements and genotypic data (from Illumina ovineSNP50 BeadChip) for 459 ewes.

Results

The 10 body size measurements were subjected to principal component analysis and three independent principal components (PC) were constructed, interpretable as width, height and length dimensions, respectively. The GWAS performed for each PC identified 11 significant SNPs, at the chromosome level, one on each of the chromosomes 3, 8, 9, 10, 11, 12, 19, 20, 23 and two on chromosome 25. Nine out of the 11 SNPs were located on previously identified quantitative trait loci for sheep meat, production or reproduction. One hundred and ninety-seven positional candidate genes within a 1-Mb distance from each significant SNP were found. A guilt-by-association-based (GBA) prioritization analysis (PA) was performed to identify the most plausible functional candidate genes. GBA-based PA identified 39 genes that were significantly associated with gene networks relevant to body size traits. Prioritized genes were identified in the vicinity of all significant SNPs except for those on chromosomes 10 and 12. The top five ranking genes were TP53, BMPR1A, PIK3R5, RPL26 and PRKDC.

Conclusions

The results of this GWAS provide evidence for 39 causative candidate genes across nine chromosomal regions for body size traits, some of which are novel and some are previously identified candidates from other studies (e.g. TP53, NTN1 and ZNF521). GBA-based PA has proved to be a useful tool to identify genes with increased biological relevance but it is subjected to certain limitations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-017-0316-3) contains supplementary material, which is available to authorized users.

Genomic prediction of reproduction traits for Merino sheep

Economically important reproduction traits in sheep, such as number of lambs weaned and litter size, are expressed only in females and later in life after most selection decisions are made, which makes them ideal candidates for genomic selection. Accurate genomic predictions would lead to greater genetic gain for these traits by enabling accurate selection of young rams with high genetic merit. The aim of this study was to design and evaluate the accuracy of a genomic prediction method for female reproduction in sheep using daughter trait deviations (DTD) for sires and ewe phenotypes (when individual ewes were genotyped) for three reproduction traits: number of lambs born (NLB), litter size (LSIZE) and number of lambs weaned. Genomic best linear unbiased prediction (GBLUP), BayesR and pedigree BLUP analyses of the three reproduction traits measured on 5340 sheep (4503 ewes and 837 sires) with real and imputed genotypes for 510 174 SNPs were performed. The prediction of breeding values using both sire and ewe trait records was validated in Merino sheep. Prediction accuracy was evaluated by across sire family and random cross-validations. Accuracies of genomic estimated breeding values (GEBVs) were assessed as the mean Pearson correlation adjusted by the accuracy of the input phenotypes. The addition of sire DTD into the prediction analysis resulted in higher accuracies compared with using only ewe records in genomic predictions or pedigree BLUP. Using GBLUP, the average accuracy based on the combined records (ewes and sire DTD) was 0.43 across traits, but the accuracies varied by trait and type of cross-validations. The accuracies of GEBVs from random cross-validations (range 0.17-0.61) were higher than were those from sire family cross-validations (range 0.00-0.51). The GEBV accuracies of 0.41-0.54 for NLB and LSIZE based on the combined records were amongst the highest in the study. Although BayesR was not significantly different from GBLUP in prediction accuracy, it identified several candidate genes which are known to be associated with NLB and LSIZE. The approach provides a way to make use of all data available in genomic prediction for traits that have limited recording.