Genome-wide association study of conformation and milk yield in mixed-breed dairy goats

Unravelling the Genetic Architecture of Serum Biochemical Indicators in Sheep

Serum biochemical indicators serve as vital proxies that reflect the physiological state and functions of different organs. The genetic parameters and molecular mechanisms underlying serum biochemical indicators of sheep (Ovis aries) have not been well understood. Therefore, the aim of the present study was to identify the genetic architecture and genomic loci underlying ten serum biochemical indicators in sheep, including alanine transaminase, aspartate transferase, lactate dehydrogenase, cholesterol, glucose, phosphorus, calcium, creatinine, urea and total protein levels. We implemented genetic parameter estimations and GWASs for each trait in 422 Akkaraman lambs. Overall, low to moderate heritability estimates were found in the range of 0.14-0.55. Additionally, low to high genetic correlations were observed among traits. In total, 23 SNP loci were associated with serum biochemical indicators leading to 19 genes. These were SPTA1, MGST2, CACUL1, IGFBP7, PARD3, PHB1, SLC15A5, TRIM35, RGS6, NUP93, CNTNAP2, SLC7A11, B3GALT5, DPP10, HST2ST1, NRP1, LRP1B, MAP3K9 and ENSOARG00020040484.1, as well as LOC101103187, LOC101117162, LOC105611309 and LOC101118029. To our knowledge, these data provide the first associations between SPTA1 and serum cholesterol and between ENSOARG00020040484.1 and serum glucose. The current findings provide a comprehensive inventory of the relationships between serum biochemical parameters, genetic variants and disease-relevant characteristics. This information may facilitate the identification of therapeutic targets and fluid biomarkers and establish a strong framework for comprehending the pathobiology of complex diseases as well as providing targets for sheep genetic improvement programs.

Single and longitudinal genome-wide association studies for dairy traits available in goats with three recorded lactations

Milk yield and composition phenotypes are systematically recorded across several lactations in goats, but the majority of genome-wide association studies (GWAS) performed so far have rather ignored the longitudinal nature of such data. Here, we have used two different GWAS approaches to analyse data from three lactations recorded in Murciano-Granadina goats. In Analysis 1, independent GWAS have been carried out for each trait and lactation, while a single longitudinal GWAS, jointly considering all data, has been performed in Analysis 2. In both analyses, genome-wide significant QTL for lactose percentage on chromosome 2 (129.77-131.01 Mb) and for milk protein percentage on the chromosome 6 (74.8-94.6 Mb) casein gene cluster region were detected. In Analysis 1, several QTL were not replicated in all three lactations, possibly due to the existence of lactation-specific genetic determinants. In Analysis 2, we identified several genome-wide significant QTL related to milk yield and protein content that were not uncovered in Analysis 1. The increased number of QTL identified in Analysis 2 suggests that the longitudinal GWAS is particularly well suited for the genetic analysis of dairy traits. Moreover, our data confirm that variability within or close to the casein complex is the main genetic determinant of milk protein percentage in Murciano-Granadina goats.

Genome-Wide Association Study of Milk Composition in Karachai Goats

This study is first to perform a genome-wide association study (GWAS) to investigate the milk quality traits in Karachai goats. The objective of the study was to identify candidate genes associated with milk composition traits based on the identification and subsequent analysis of all possible SNPs, both genome-wide (high-confidence) and suggestive (subthreshold significance). To estimate the milk components, 22 traits were determined, including several types of fatty acids. DNA was extracted from ear tissue or blood samples. A total of 167 Karachai goats were genotyped using an Illumina GoatSNP53K BeadChip panel (Illumina Inc., San Diego, CA, USA). Overall, we identified 167 highly significant and subthreshold SNPs associated with the milk components of Karachai goats. A total of 10 SNPs were located within protein-coding genes and 33 SNPs in close proximity to them (±0.2 Mb). The largest number of genome-wide significant SNPs was found on chromosomes 2 and 8 and some of them were associated with several traits. The greatest number of genome-wide significant SNPs was identified for crude protein and lactose (6), and the smallest number-only 1 SNP-for freezing point depression. No SNPs were identified for monounsaturated and polyunsaturated fatty acids. Functional annotation of all 43 SNPs allowed us to identify 66 significant candidate genes on chromosomes 1, 2, 3, 4, 5, 8, 10, 13, 16, 18, 21, 23, 25, 26, and 27. We considered these genes potential DNA markers of the fatty acid composition of Karachai goat milk. Also, we found 12 genes that had a polygenic effect: most of them were simultaneously associated with the dry matter content and fatty acids (METTL, SLC1A 8, PHACTR1, FMO2, ECI1, PGP, ABCA3, AMDHD2). Our results suggest that the genes identified in our study affecting the milk components in Karachai goats differed from those identified in other breeds of dairy goats.

Determination of declined genetic diversity of Holstein stud bulls based on microsatellite markers

Semen importing countries are trying to select the most suitable studs according to their breeding goals, while the globally widespread use of common genetic material has been turning the loss of genetic diversity into a possible danger. The aim of this study was to evaluate the genetic diversity of 304 high-yielding Holstein stud bulls whose semen were produced in Turkiye, Europe and the Americas. The values of allele frequencies, expected heterozygosity (He), observed heterozygosity (Ho), Hardy-Weinberg (HW) Equilibrium, the number of alleles per locus (Na), allelic richness (Rs), polymorphic information content (PIC) and F-statistics were calculated and compared the results with similar studies. It was observed that some indicator values of the genetic diversity were decreased compared to the values of the other studies in Holstein breed. Especially the decrease in some values of SPS115 locus was statistically significant. It is thought that this could be as a result of SPS115 to be close to possible QTL regions associated with traits which indicates overall potential of selection in stud bulls. Therefore, while applying a selection program to populations, national genetic resource management strategies that maintain genetic diversity should not be forgotten besides gaining high yield.

Genome-wide association study of health and production traits in meat sheep

Genotypes are currently widely used in animal breeding programmes to enhance the speed of genetic progress. With sufficient data, a Genome-Wide Association Study (GWAS) can be performed to identify informative markers. The aim of this study was to investigate the genetic background of health (footrot and mastitis) and production (birth weight, weaning weight, scan weight, and fat and muscle depth) traits using the available phenotypic and Single Nucleotide Polymorphism (SNP) data collected on the UK Texel sheep population. Initially, 10 193 genotypes were subject to quality control, leaving 9 505 genotypes for further analysis. Selected genotypes, recorded on four different Illumina chip types from low density (15 k SNPs) to high density (606 006 SNPs), were imputed to a subset of 45 686 markers from 50 k array, distributed on 27 chromosomes. Phenotypes collected on 32 farms across the UK for footrot and mastitis and extracted from the UK National database (iTexel) for the production traits were used along with pre-estimated variance components to obtain de-regressed breeding values and used to perform GWAS. Results showed three SNPs being significant on the genome-wise level ('OAR8_62240378.1' on chromosome 8 for birth weight, 's14444.1' on chromosome 19 for weaning weight and 's65197.1' on chromosome 23 for scan weight). Fourteen subsequent SNPs were found to be significant at the chromosome-wise level. These SNPs are located within or close to previously reported QTLs impacting on animal health (such as faecal egg count or somatic cell count) and production (such as body or carcass weight and fat amount). These results indicate that the studied traits are highly polygenic with complex genetic architecture.

Multi-omics revealed the long-term effect of ruminal keystone bacteria and the microbial metabolome on lactation performance in adult dairy goats

BACKGROUND

The increased growth rate of young animals can lead to higher lactation performance in adult goats; however, the effects of the ruminal microbiome on the growth of young goats, and the contribution of the early-life rumen microbiome to lifelong growth and lactation performance in goats has not yet been well defined. Hence, this study assessed the rumen microbiome in young goats with different average daily gains (ADG) and evaluated its contribution to growth and lactation performance during the first lactation period.

RESULTS

Based on monitoring of a cohort of 99 goats from youth to first lactation, the 15 highest ADG (HADG) goats and 15 lowest ADG (LADG) goats were subjected to rumen fluid microbiome and metabolome profiling. The comparison of the rumen metagenome of HADG and LADG goats revealed that ruminal carbohydrate metabolism and amino acid metabolism function were enhanced in HADG goats, suggesting that the rumen fluid microbiome of HADG goats has higher feed fermentation ability. Co-occurrence network and correlation analysis revealed that Streptococcus, Candidatus Saccharimonans, and Succinivibrionaceae UCG-001 were significantly positively correlated with young goats' growth rates and some HADG-enriched carbohydrate and protein metabolites, such as propionate, butyrate, maltoriose, and amino acids, while several genera and species of Prevotella and Methanogens exhibited a negative relationship with young goats' growth rates and correlated with LADG-enriched metabolites, such as rumen acetate as well as methane. Additionally, some functional keystone bacterial taxa, such as Prevotella, in the rumen of young goats were significantly correlated with the same taxa in the rumen of adult lactation goats. Prevotella also enriched the rumen of LADG lactating goats and had a negative effect on rumen fermentation efficiency in lactating goats. Additional analysis using random forest machine learning showed that rumen fluid microbiota and their metabolites of young goats, such as Prevotellaceae UCG-003, acetate to propionate ratio could be potential microbial markers that can potentially classify high or low ADG goats with an accuracy of prediction of > 81.3%. Similarly, the abundance of Streptococcus in the rumen of young goats could be predictive of milk yield in adult goats with high accuracy (area under the curve 91.7%).

CONCLUSIONS

This study identified the keystone bacterial taxa that influence carbohydrate and amino acid metabolic functions and shape the rumen fluid microbiota in the rumen of adult animals. Keystone bacteria and their effects on rumen fluid microbiota and metabolome composition during early life can lead to higher lactation performance in adult ruminants. These findings suggest that the rumen microbiome together with their metabolites in young ruminants have long-term effect on feed efficiency and animal performance. The fundamental knowledge may allow us to develop advanced methods to manipulate the rumen microbiome and improve production efficiency of ruminants. Video Abstract.

Investigation of SNP markers for the melatonin production trait in the Hu sheep with bulked segregant analysis

BACKGROUND

As an important reproductive hormone, melatonin plays an important role in regulating the reproductive activities of sheep and other mammals. Hu sheep is a breed favoring for meat, with prolific traits. In order to explore the relationship between melatonin and reproductive function of Hu sheep, 7,694,759 SNPs were screened out through the whole genome sequencing analysis from high and low melatonin production Hu sheep.

RESULTS

A total of 68,673 SNPs, involving in 1126 genes, were identified by ED association analysis. Correlation analysis of SNPs of AANAT/ASMT gene and MTNR1A/MTNR1B gene were carried out. The melatonin level of CG genotype 7,981,372 of AANAT, GA genotype 7,981,866 of ASMT and GG genotype 17,355,171 of MTNR1A were higher than the average melatonin level of 1.64 ng/mL. High melatonin Hu sheep appear to have better multiple reproductive performance.

CONCLUSIONS

By using different methods, three SNPs which are associated with high melatonin production trait have been identified in Hu sheep. These 3 SNPs are located in melatonin synthetase AANAT/ASMT and receptor MTNR1A, respectively. Considering the positive association between melatonin production and reproductive performance in ruminants, these three SNPs can be served as the potential molecular markers for breading Hu sheep with the desirable reproductive traits.

Validation of single-step genomic BLUP random regression test-day models and SNP effects analysis on milk yield in French Saanen goats

The shape of the lactation curve is linked to an animal's health, feed requirements, and milk production throughout the year. Random regression models (RRM) are widely used for genetic evaluation of total milk production throughout the lactation and for milk yield persistency. Genomic information used with the single-step genomic BLUP method (ssGBLUP) substantially improves the accuracy of genomic prediction of breeding values in the main dairy cattle breeds. The aim of this study was to implement an RRM using ssGBLUP for milk yield in Saanen dairy goats in France. The data set consisted of 7,904,246 test-day records from 1,308,307 lactations of Saanen goats collected in France between 2000 and 2017. The performance of this type of evaluation was assessed by applying a validation step with data targeting candidate bucks. The model was compared with a nongenomic evaluation and a traditional evaluation that use cumulated performance throughout the lactation model (LM). The incorporation of genomic information increased correlations between daughter yield deviations (DYD) and estimated breeding values (EBV) obtained with a partial data set for candidate bucks. The LM and the RRM had similar correlation between DYD and EBV. However, the RRM reduced overestimation of EBV and improved the slope of the regression of DYD on EBV obtained at birth. This study shows that a genomic evaluation from a ssGBLUP RRM is possible in dairy goats in France and that RRM performance is comparable to a LM but with the additional benefit of a genomic evaluation of persistency. Variance of adjacent SNPs was studied with LM and RRM following the ssGBLUP. Both approaches converged on approximately the same regions explaining more than 1% of total variance. Regions associated with persistency were also found.

Genome-wide association study for milk production and conformation traits in Canadian Alpine and Saanen dairy goats

Increasing the productivity of Canadian dairy goats is critical to the competitiveness of the sector; however, little is known about the underlying genetic architecture of economically important traits in these populations. Consequently, the objectives of this study were as follows: (1) to perform a single-step GWAS for milk production traits (milk, protein, and fat yields, and protein and fat percentages in first and later lactations) and conformation traits (body capacity, dairy character, feet and legs, fore udder, general appearance, rear udder, suspensory ligament, and teats) in the Canadian Alpine and Saanen breeds; and (2) to identify positional and functional candidate genes related to these traits. The data available for analysis included 305-d milk production records for 6,409 Alpine and 3,434 Saanen does in first lactation and 5,827 Alpine and 2,632 Saanen does in later lactations; as well as linear type conformation records for 5,158 Alpine and 2,342 Saanen does. Genotypes were available for 833 Alpine and 874 Saanen animals. Both single-breed and multiple-breed GWAS were performed using single-trait animal models. Positional and functional candidate genes were then identified in downstream analyses. The GWAS identified 189 unique SNP that were significant at the chromosomal level, corresponding to 271 unique positional candidate genes within 50 kb up- and downstream, across breeds and traits. This study provides evidence for the economic importance of several candidate genes (e.g., CSN1S1, CSN2, CSN1S2, CSN3, DGAT1, and ZNF16) in the Canadian Alpine and Saanen populations that have been previously reported in other dairy goat populations. Moreover, several novel positional and functional candidate genes (e.g., RPL8, DCK, and MOB1B) were also identified. Overall, the results of this study have provided greater insight into the genetic architecture of milk production and conformation traits in the Canadian Alpine and Saanen populations. Greater understanding of these traits will help to improve dairy goat breeding programs.

Genome-wide analysis for the melatonin trait associated genes and SNPs in dairy goat (Capra hircus) as the molecular breeding markers

Previous studies have reported that the endogenous melatonin level is positively associated with the quality and yield of milk of cows. In the current study, a total of 34,921 SNPs involving 1,177 genes were identified in dairy goats by using the whole genome resequencing bulked segregant analysis (BSA) analysis. These SNPs have been used to match the melatonin levels of the dairy goats. Among them, 3 SNPs has been identified to significantly correlate with melatonin levels. These 3 SNPs include CC genotype 147316, GG genotype 147379 and CC genotype 1389193 which all locate in the exon regions of ASMT and MT2 genes. Dairy goats with these SNPs have approximately 5-fold-higher melatonin levels in milk and serum than the average melatonin level detected in the current goat population. If the melatonin level impacts the milk production in goats as in cows, the results strongly suggest that these 3 SNPs can serve as the molecular markers to select the goats having the improved milk quality and yield. This is a goal of our future study.

Genome-wide association study reveals novel candidate genes for litter size in Markhoz goats

Introduction

The Markhoz goat is the only breed that can produce high-quality fiber called mohair in Iran; however, the size of its population has faced a dramatic decline during the last decades, mainly due to the reluctance of farmers to rear Markhoz goats caused by a reduction in goat production income. Litter size at birth (LSB) and weaning (LSW) are two economically important reproductive traits for local goat breeders and have the potential of increasing the population growth rate. The present study was aimed to identify possible genomic regions that are associated with LSB and LSW in Markhoz goats using a genome-wide association study (GWAS).

Methods

To this end, 136 Markhoz goats with record(s) of kidding were selected for GWAS using the Illumina Caprine 50K bead chip. The individual breeding values (BV) of available LSB and LSW records estimated under an animal mixed model were used as the dependent variable in the GWAS, thereby incorporating repeated categorical variables of litter size.

Results

Four SNPs on chromosomes 2, 20 and 21 were identified to be significantly associated (FDR p < 0.05) with LSB after multiple testing correction under a Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) model. Least-square analysis was performed to investigate the effects of detected genotypes on LSB. Ultimately, the GWAS results introduced six candidate genes, including GABRA5, AKAP13, SV2B, PPP1R1C, SSFA2 and TRNAS-GCU in a 100 kb adjacent region of the identified SNPs. Previous studies proposed functional roles of GABRA5 and AKAP13 genes in reproductive processes; however, the role of other candidate genes in reproduction is not clear.

Conclusion

These findings warrant further investigation for use in marker-assisted selection programs in Markhoz goats.

Genomic Analysis of Gastrointestinal Parasite Resistance in Akkaraman Sheep

Genome-wide association studies (GWAS) have been used as an effective tool to understand the genetics of complex traits such as gastrointestinal parasite (GIP) resistance. The aim of this study was to understand the genetics of gastrointestinal parasite (nematodes, Moniezia spp., Eimeria spp.) resistance in Akkaraman sheep by performing genomic heritability estimations and conducting GWAS to uncover responsible genomic regions. This is one of the first studies to examine the genetic resistance of Akkaraman sheep to the tapeworm parasite. The samples from 475 animals were genotyped using the Axiom 50K Ovine Genotyping Array. Genomic heritability estimates ranged from 0.00 to 0.34 for parasite resistance traits. This indicates that measured phenotypes have low to moderate heritability estimates. A total of two genome-wide significant SNP associated with TNEM3 and ATRNL1 genes and 10 chromosome-wide significant SNPs related with 10 genes namely NELL1, ST6GALNAC3, HIPK1, SYT1, ALK, ZNF596, TMCO5A, PTH2R, LARGE1, and SCG2 were suggested as candidates for parasite resistance traits. The majority of these candidate genes were involved in several basic biological processes that are essential and important for immune system functions and cellular growth; specifically, inflammatory responses, cellular transport, cell apoptosis, cell differentiation, histone de-acetylation, and endocytosis. These results have implications for animal breeding program studies due to the effect that the genetic background has on parasite resistance, which underlies many productive, health, and wellness-related traits.

Estimates of genomic heritability and genome-wide association studies for blood parameters in Akkaraman sheep

The aim of this study was to estimate genomic heritability and the impact that genetic backgrounds have on blood parameters in Akkaraman sheep by conducting genome-wide association studies and regional heritability mapping analysis. Genomic heritability estimates for blood parameters ranged from 0.00 to 0.55, indicating that measured phenotypes have a low to moderate heritability. A total of 7 genome- and 13 chromosome-wide significant SNPs were associated with phenotypic changes in 15 blood parameters tested. Accordingly, SCN7A, SCN9A, MYADM-like, CCDC67, ITGA9, MGAT5, SLC19A1, AMPH, NTRK2, MSRA, SLC35F3, SIRT6, CREB3L3, and NAV3 genes as well as three undefined regions (LOC101117887, LOC106991526 and LOC105608461) were suggested as candidates. Most of the identified genes were involved in basic biological processes that are essential to immune system function and cellular growth; specific functions include cellular transport, histone deacetylation, cell differentiation, erythropoiesis, and endocytosis. The top significant SNP for HCT, MCH, and MCHC was found within a genomic region mainly populated by the MYADM-like gene family. This region was previously suggested to be under historical selection pressure in many sheep breeds from various parts of the world. These results have implications on animal breeding program studies due to the effect that the genetic background has on blood parameters, which underlying many productive and wellness related traits.

Trajectory of livestock genomics in South Asia: A comprehensive review

Livestock plays a central role in sustaining human livelihood in South Asia. There are numerous and distinct livestock species in South Asian countries. Several of them have experienced genetic development in recent years due to the application of genomic technologies and effective breeding programs. This review discusses genomic studies on cattle, buffalo, sheep, goat, pig, horse, camel, yak, mithun, and poultry. The frontiers covered in this review are genetic diversity, admixture studies, selection signature research, QTL discovery, genome-wide association studies (GWAS), and genomic selection. The review concludes with recommendations for South Asian livestock systems to increasingly leverage genomic technologies, based on the lessons learned from the numerous case studies. This paper aims to present a comprehensive analysis of the dichotomy in the South Asian livestock sector and argues that a realistic approach to genomics in livestock can ensure long-term genetic advancements.

Genetic Parameters and Genomic Regions Underlying Growth and Linear Type Traits in Akkaraman Sheep

In the current study, the genetic architecture of growth and linear type traits were investigated in Akkaraman sheep. Estimations of genomic heritability, genetic correlations, and phenotypic correlations were implemented for 17 growth and linear type traits of 473 Akkaraman lambs by the univariate and multivariate analysis of animal mixed models. Correspondingly, moderate heritability estimates, as well as high and positive genetic/phenotypic correlations were found between growth and type traits. On the other hand, 2 genome-wide and 19 chromosome-wide significant single nucleotide polymorphisms were found to be associated with the traits as a result of animal mixed model-based genome-wide association analyses. Accordingly, we propose several genes located on different chromosomes (e.g., PRDM2, PTGDR, PTPRG, KCND2, ZNF260, CPE, GRID2, SCD5, SPIDR, ZNF407, HCN3, TMEM50A, FKBP1A, TLE4, SP1, SLC44A1, and MYOM3) as putative quantitative trait loci for the 22 growth and linear type traits studied. In our study, specific genes (e.g., TLE4, PTGDR, and SCD5) were found common between the traits studied, suggesting an interplay between the genetic backgrounds of these traits. The fact that four of the proposed genes (TLE4, MYOM3, SLC44A1, and TMEM50A) are located on sheep chromosome 2 confirms the importance of these genomic regions for growth and morphological structure in sheep. The results of our study are therefore of great importance for the development of efficient selection indices and marker-assisted selection programs, as well as for the understanding of the genetic architecture of growth and linear traits in sheep.

Genome-Wide Association Study on the Hematological Phenotypic Characteristics of the Han Population from Northwest China

Background

Hematological characteristics have positive reference value as clinical indicators in the evaluation of various diseases. The purpose of this study was to determine the gene loci associated with 20 hematological phenotypes in the Han population from northwest China.

Methods

A genome-wide association study (GWAS) was conducted on hematological indicators of 1005 Han people from northwest China. Genotyping was performed with a GeneTitan multichannel instrument and Axiom Analysis Suite 6.0. Using the 1000 Genomes Project (phase 3) as a reference, haplotype imputation was performed with IMPUTE2. SNVs (single nucleotide variants) significantly associated with hematological phenotypes were identified. The top SNV (p < 5E-7) was then selected for replication detection.

Results

Ninety genetic variations identified in the GWAS were significantly associated with hematological indicators. Among them, only rs35289401 (CCDC157) was significantly associated (genome-wide) with red blood cell distribution width (RDW) (p = 4.21E-08). The fourteen top SNVs were selected for replication verification and were significantly associated with hematological phenotypes. However, only HBS1 L-MYB rs1331309 was significantly associated with the mean hemoglobin content (p = 6.42E-07). We also found that the mean corpuscular hemoglobin (MCH) level in the rs1331309 GG/GT genotype was significantly higher than that in the TT genotype (p = 0.023).

Conclusion

The GWAS identified a total of 90 genetic variants significantly associated with hematological phenotypic indicators. In particular, rs1331309 (HBS1 L-MYB) is expected to be a biomarker for monitoring the dynamics of MCH levels. This study provides a reference for related studies on the genetic structure of hematological characteristics. It provides a valuable reference for the clinical diagnosis or prediction of a variety of diseases.

Assessing genomic diversity and signatures of selection in Pinan cattle using whole-genome sequencing data

BACKGROUND

Crossbreeding is an important way to improve production beef cattle performance. Pinan cattle is a new hybrid cattle obtained from crossing Piedmontese bulls with Nanyang cows. After more than 30 years of cross-breeding, Pinan cattle show a variety of excellent characteristics, including fast growth, early onset of puberty, and good meat quality. In this study, we analyzed the genetic diversity, population structure, and genomic region under the selection of Pinan cattle based on whole-genome sequencing data of 30 Pinan cattle and 169 published cattle genomic data worldwide.  RESULTS: Estimating ancestry composition analysis showed that the composition proportions for our Pinan cattle were mainly Piedmontese and a small amount of Nanyang cattle. The analyses of nucleotide diversity and linkage disequilibrium decay indicated that the genomic diversity of Pinan cattle was higher than that of European cattle and lower than that of Chinese indigenous cattle. De-correlated composite of multiple selection signals, which combines four different statistics including θπ, CLR, F_ST, and XP-EHH, was computed to detect the signatures of selection in the Pinan cattle genome. A total of 83 genes were identified, affecting many economically important traits. Functional annotation revealed that these selected genes were related to immune (BOLA-DQA2, BOLA-DQB, LSM14A, SEC13, and NAALADL2), growth traits (CYP4A11, RPL26, and MYH10), embryo development (REV3L, NT5E, CDX2, KDM6B, and ADAMTS9), hornless traits (C1H21orf62), and climate adaptation (ANTXR2).

CONCLUSION

In this paper, we elucidated the genomic characteristics, ancestry composition, and selective signals related to important economic traits in Pinan cattle. These results will provide the basis for further genetic improvement of Pinan cattle and reference for other hybrid cattle related studies.

Genome-wide analyses reveal a strong association between LEPR gene variants and body fat reserves in ewes

BACKGROUND

Among the adaptive capacities of animals, the management of energetic body reserves (BR) through the BR mobilization and accretion processes (BR dynamics, BRD) has become an increasingly valuable attribute for livestock sustainability, allowing animals to cope with more variable environments. BRD has previously been reported to be heritable in ruminants. In the present work, we conducted genome-wide studies (GWAS) in sheep to determine genetic variants associated with BRD. BR (i.e. levels) and BRD (i.e. changes over time) were obtained through body condition score measurements at eight physiological stages throughout each productive cycle in Romane ewes (n = 1034) and were used as phenotypes for GWAS. After quality controls and imputation, 48,593 single nucleotide polymorphisms (SNP) were included in the GWAS.

RESULTS

Among the 23 QTL regions identified, a major QTL associated with BR during pregnancy and lactation was identified on chromosome 1. In this region, several significant SNPs mapped to the leptin receptor gene (LEPR), among which one SNP mapped to the coding sequence. The point mutation induces the p.P1019S substitution in the cytoplasmic domain, close to tyrosine phosphorylation sites. The frequency of the SNP associated with increased BR levels was 32%, and the LEPR genotype explained up to 5% of the variance of the trait. Higher fatness levels in ewes carrying the LEPR p.P1019S mutation were observed all along the productive cycle.

CONCLUSIONS

These results provide strong evidences for involvement of LEPR in the regulation of BR in sheep and highlight it as a major candidate gene for improving adaptive capacities by genetic selection.

Candidate Genes and Their Expressions Involved in the Regulation of Milk and Meat Production and Quality in Goats (Capra hircus)

Simple Summary

During the present decade, highly selected caprine farming has increased in popularity due to the hardiness and adaptability inherent to goats. Recent advances in genetics have enabled the improvement in goat selection efficiency. The present review explores how genetic technologies have been applied to the goat-farming sector in the last century. The main candidate genes related to economically relevant traits are reported. The major source of income in goat farming derives from the sale of milk and meat. Consequently, yield and quality must be specially considered. Meat-related traits were evaluated considering three functional groups (weight gain, carcass quality and fat profile). Milk traits were assessed in three additional functional groups (milk production, protein and fat content).

Abstract

Despite their pivotal position as relevant sources for high-quality proteins in particularly hard environmental contexts, the domestic goat has not benefited from the advances made in genomics compared to other livestock species. Genetic analysis based on the study of candidate genes is considered an appropriate approach to elucidate the physiological mechanisms involved in the regulation of the expression of functional traits. This is especially relevant when such functional traits are linked to economic interest. The knowledge of candidate genes, their location on the goat genetic map and the specific phenotypic outcomes that may arise due to the regulation of their expression act as a catalyzer for the efficiency and accuracy of goat-breeding policies, which in turn translates into a greater competitiveness and sustainable profit for goats worldwide. To this aim, this review presents a chronological comprehensive analysis of caprine genetics and genomics through the evaluation of the available literature regarding the main candidate genes involved in meat and milk production and quality in the domestic goat. Additionally, this review aims to serve as a guide for future research, given that the assessment, determination and characterization of the genes associated with desirable phenotypes may provide information that may, in turn, enhance the implementation of goat-breeding programs in future and ensure their sustainability.

Challenging Sustainable and Innovative Technologies in Cheese Production: A Review

It is well known that cheese yield and quality are affected by animal genetics, milk quality (chemical, physical, and microbiological), production technology, and the type of rennet and dairy cultures used in production. Major differences in the same type of cheese (i.e., hard cheese) are caused by the rennet and dairy cultures, which affect the ripening process. This review aims to explore current technological advancements in animal genetics, methods for the isolation and production of rennet and dairy cultures, along with possible applications of microencapsulation in rennet and dairy culture production, as well as the challenge posed to current dairy technologies by the preservation of biodiversity. Based on the reviewed scientific literature, it can be concluded that innovative approaches and the described techniques can significantly improve cheese production.

A Capra hircus chromosome 19 locus linked to milk production influences mammary conformation

Background

Economically important milk production traits including milk volume, milk fat and protein yield vary considerably across dairy goats in New Zealand. A significant portion of the variation is attributable to genetic variation. Discovery of genetic markers linked to milk production traits can be utilised to drive selection of high-performance animals.

A previously reported genome wide association study across dairy goats in New Zealand identified a quantitative trait locus (QTL) located on chromosome 19. The most significantly associated single nucleotide polymorphism (SNP) marker for this locus is located at position 26,610,610 (SNP marker rs268292132). This locus is associated with multiple milk production traits including fat, protein and volume. The predicted effect of selection for the beneficial haplotype would result in an average production increase of 2.2 kg fat, 1.9 kg protein and 73.6 kg milk yield.

An outstanding question was whether selection for the beneficial allele would co-select for any negative pleiotropic effects. An adverse relationship between milk production and udder health traits has been reported at this locus. Therefore, a genome wide association study was undertaken looking for loci associated with udder traits.

Results

The QTL and production associated marker rs268292132 was identified in this study to also be associated with several goat udder traits including udder depth (UD), fore udder attachment (FUA) and rear udder attachment (RUA). Our study replicates the negative relationship between production and udder traits with the high production allele at position 19:26,610,610 (SNP marker rs268292132) associated with an adverse change in UD, FUA and RUA.

Conclusions

Our study has confirmed the negative relationship between udder traits and production traits in the NZ goat population. We have found that the frequency of the high production allele is relatively high in the NZ goat population, indicating that its effect on udder conformation is not significantly detrimental on animal health. It will however be important to monitor udder conformation as the chromosome 19 locus is progressively implemented for marker assisted selection. It will also be of interest to determine if the gene underlying the production QTL has a direct effect on mammary gland morphology or whether the changes observed are a consequence of the increased milk volume.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40104-021-00667-y.

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

Background

Since their domestication 10,500 years ago, goat populations with distinctive genetic backgrounds have adapted to a broad variety of environments and breeding conditions. The VarGoats project is an international 1000-genome resequencing program designed to understand the consequences of domestication and breeding on the genetic diversity of domestic goats and to elucidate how speciation and hybridization have modeled the genomes of a set of species representative of the genus Capra.

Findings

A dataset comprising 652 sequenced goats and 507 public goat sequences, including 35 animals representing eight wild species, has been collected worldwide. We identified 74,274,427 single nucleotide polymorphisms (SNPs) and 13,607,850 insertion-deletions (InDels) by aligning these sequences to the latest version of the goat reference genome (ARS1). A Neighbor-joining tree based on Reynolds genetic distances showed that goats from Africa, Asia and Europe tend to group into independent clusters. Because goat breeds from Oceania and Caribbean (Creole) all derive from imported animals, they are distributed along the tree according to their ancestral geographic origin.

Conclusions

We report on an unprecedented international effort to characterize the genome-wide diversity of domestic goats. This large range of sequenced individuals represents a unique opportunity to ascertain how the demographic and selection processes associated with post-domestication history have shaped the diversity of this species. Data generated for the project will also be extremely useful to identify deleterious mutations and polymorphisms with causal effects on complex traits, and thus will contribute to new knowledge that could be used in genomic prediction and genome-wide association studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00659-6.

A near complete genome for goat genetic and genomic research

Background

Goat, one of the first domesticated livestock, is a worldwide important species both culturally and economically. The current goat reference genome, known as ARS1, is reported as the first nonhuman genome assembly using 69× PacBio sequencing. However, ARS1 suffers from incomplete X chromosome and highly fragmented Y chromosome scaffolds.

Results

Here, we present a very high-quality de novo genome assembly, Saanen_v1, from a male Saanen dairy goat, with the first goat Y chromosome scaffold based on 117× PacBio long-read sequencing and 118× Hi-C data. Saanen_v1 displays a high level of completeness thanks to the presence of centromeric and telomeric repeats at the proximal and distal ends of two-thirds of the autosomes, and a much reduced number of gaps (169 vs. 773). The completeness and accuracy of the Saanen_v1 genome assembly are also evidenced by more assembled sequences on the chromosomes (2.63 Gb for Saanen_v1 vs. 2.58 Gb for ARS1), a slightly increased mapping ratio for transcriptomic data, and more genes anchored to chromosomes. The eight putative large assembly errors (1 to ~ 7 Mb each) found in ARS1 were amended, and for the first time, the substitution rate of this ruminant Y chromosome was estimated. Furthermore, sequence improvement in Saanen_v1, compared with ARS1, enables us to assign the likely correct positions for 4.4% of the single nucleotide polymorphism (SNP) probes in the widely used GoatSNP50 chip.

Conclusions

The updated goat genome assembly including both sex chromosomes (X and Y) and the autosomes with high-resolution quality will serve as a valuable resource for goat genetic research and applications.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00668-5.

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 association studies of preweaning growth and in vivo carcass composition traits in Esme sheep

Sheep are considered as a major contributor of global food security. Moreover, sheep preweaning growth traits as well as in vivo carcass composition traits such as ultrasonic measurements of Longissimus dorsi muscle depth (UMD) and back-fat thickness (UFD) are crucially important indicators of meat yield and hot carcass composition. Despite their relative importance for productivity and profitability of a sheep production system, detected QTL for these traits are quite scarce. Therefore, we implemented GWAS for these traits using animal mixed model-based association approach provided by GenABEL in Esme sheep. Three genome-wide and 14 individual chromosome-wide associated SNPs were discovered. As a result, ESRP1, LOC105613082, ZNF641, DUSP5, TEAD1, SMOX, PTPRT, RALYL, POM121C, PHIP, LOC101106051, ZIM3, PEG3, TRPC7, FBXL4, LOC105610397, LOC105616489 and DNAAF2 were suggested as candidates. Some of the discovered genes and involved pathways were already annotated to contribute growth and development in various species including human, mice and cattle. All in all, the results of this study are expected to strongly contribute to shed a light on the underlying molecular mechanisms behind growth and carcass composition traits, with potential implications on studies aiming faster genetic improvement, targeted low-resolution SNP panel designs and genome-editing studies.

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.

Whole-genome sequencing to identify candidate genes for litter size and to uncover the variant function in goats (Capra hircus)

To select candidate genes for goat prolificacy, we managed six multi- and six single-kid female goats at the same feeding level and in the same management mode over a 4-year period. These goats showed stable differences in litter size over five continuous parturition records. Whole-genome re-sequencing was used in all 12 to select candidate genes, namely, AURKA, ENDOG, SOX2, RORA, GJA10, RXFP2, CDC25C, and NANOS3, by the strength of their differentiation signals. Most of the selected genes were enriched in the coiled coil process and ovarian development, which suggests that the coiled coil process has a potential regulatory effect on fecundity. Detection of the distribution of variants and association analyses with litter size in 400 goats showed that NANOS3 exon mutations may lead to a transformation of the protein structure. The variation in CDC25C, ENDOG, and NANOS3 showed a significant association with litter size. These results can contribute to the improvement of reproduction traits in the artificial breeding of goats.

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

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

A genome-wide association analysis for body, udder, and leg conformation traits recorded in Murciano-Granadina goats

Morphological traits are of great importance to dairy goat production given their effect on phenotypes of economic interest. However, their underlying genomic architecture has not yet been extensively characterized. Herein, we aimed to identify genomic regions associated with body, udder, and leg conformation traits recorded in 825 Murciano-Granadina goats. We genotyped this resource population using the GoatSNP50 BeadChip (Illumina Inc., San Diego, CA) and performed genome-wide association analyses using the GEMMA software. We found 2 genome-wide significant associations between markers rs268273468 [Capra hircus (CHI) 16:69617700] and rs268249346 (CHI 28:18321523) and medial suspensory ligament. In contrast, we did not detect any genome-wide significant associations for body and leg traits. Moreover, we found 12, 19, and 7 chromosome-wide significant associations for udder, body, and leg traits, respectively. Comparison of our data with previous studies revealed a low level of positional concordance between regions associated with morphological traits. In addition to technical factors, this lack of concordance could be due to a substantial level of genetic heterogeneity among breeds or to the strong polygenic background of morphological traits, which makes it difficult to detect genetic factors that have small phenotypic effects.

Bayesian Analysis of the Association between Casein Complex Haplotype Variants and Milk Yield, Composition, and Curve Shape Parameters in Murciano-Granadina Goats

Considering casein haplotype variants rather than SNPs may maximize the understanding of heritable mechanisms and their implication on the expression of functional traits related to milk production. Effects of casein complex haplotypes on milk yield, milk composition, and curve shape parameters were used using a Bayesian inference for ANOVA. We identified 48 single nucleotide polymorphisms (SNPs) present in the casein complex of 159 unrelated individuals of diverse ancestry, which were organized into 86 haplotypes. The Ali and Schaeffer model was chosen as the best fitting model for milk yield (Kg), protein, fat, dry matter, and lactose (%), while parabolic yield-density was chosen as the best fitting model for somatic cells count (SCC × 103 sc/mL). Peak and persistence for all traits were computed respectively. Statistically significant differences (p < 0.05) were found for milk yield and components. However, no significant difference was found for any curve shape parameter except for protein percentage peak. Those haplotypes for which higher milk yields were reported were the ones that had higher percentages for protein, fat, dry matter, and lactose, while the opposite trend was described by somatic cells counts. Conclusively, casein complex haplotypes can be considered in selection strategies for economically important traits in dairy goats.

Genome-wide association studies of lactation yields of milk, fat, protein and somatic cell score in New Zealand dairy goats

Background

Identifying associations between genetic markers and traits of economic importance will provide practical benefits for the dairy goat industry, enabling genomic prediction of the breeding value of individuals, and facilitating discovery of the underlying genes and mutations. Genome-wide association studies were implemented to detect genetic regions that are significantly associated with effects on lactation yields of milk (MY), fat (FY), protein (PY) and somatic cell score (SCS) in New Zealand dairy goats.

Methods

A total of 4,840 goats were genotyped with the Caprine 50 K SNP chip (Illumina Inc., San Diego, CA). After quality filtering, 3,732 animals and 41,989 SNPs were analysed assuming an additive linear model. Four GWAS models were performed, a single-SNP additive linear model and three multi-SNP BayesC models. For the single-SNP GWAS, SNPs were fitted individually as fixed covariates, while the BayesC models fit all SNPs simultaneously as random effects. A cluster of significant SNPs were used to define a haplotype block whose alleles were fitted as covariates in a Bayesian model. The corresponding diplotypes of the haplotype block were then fit as class variables in another Bayesian model.

Results

Across all four traits, a total of 43 genome-wide significant SNPs were detected from the SNP GWAS. At a genome-wide significance level, the single-SNP analysis identified a cluster of variants on chromosome 19 associated with MY, FY, PY, and another cluster on chromosome 29 associated with SCS. Significant SNPs mapped in introns of candidate genes (45%), in intergenic regions (36%), were 0-5 kb upstream or downstream of the closest gene (14%) or were synonymous substitutions (5%). The most significant genomic window was located on chromosome 19 explaining up to 9.6% of the phenotypic variation for MY, 8.1% for FY, 9.1% for PY and 1% for SCS.

Conclusions

The quantitative trait loci for yield traits on chromosome 19 confirms reported findings in other dairy goat populations. There is benefit to be gained from using these results for genomic selection to improve milk production in New Zealand dairy goats.

Analyzing the genomic and transcriptomic architecture of milk traits in Murciano-Granadina goats

Background

In this study, we aimed to investigate the molecular basis of lactation as well as to identify the genetic factors that influence milk yield and composition in goats. To achieve these two goals, we have analyzed how the mRNA profile of the mammary gland changes in seven Murciano-Granadina goats at each of three different time points, i.e. 78 d (T1, early lactation), 216 d (T2, late lactation) and 285 d (T3, dry period) after parturition. Moreover, we have performed a genome-wide association study (GWAS) for seven dairy traits recorded in the 1st lactation of 822 Murciano-Granadina goats.

Results

The expression profiles of the mammary gland in the early (T1) and late (T2) lactation were quite similar (42 differentially expressed genes), while strong transcriptomic differences (more than one thousand differentially expressed genes) were observed between the lactating (T1/T2) and non-lactating (T3) mammary glands. A large number of differentially expressed genes were involved in pathways related with the biosynthesis of amino acids, cholesterol, triglycerides and steroids as well as with glycerophospholipid metabolism, adipocytokine signaling, lipid binding, regulation of ion transmembrane transport, calcium ion binding, metalloendopeptidase activity and complement and coagulation cascades. With regard to the second goal of the study, the performance of the GWAS allowed us to detect 24 quantitative trait loci (QTLs), including three genome-wide significant associations: QTL1 (chromosome 2, 130.72-131.01 Mb) for lactose percentage, QTL6 (chromosome 6, 78.90-93.48 Mb) for protein percentage and QTL17 (chromosome 17, 11.20 Mb) for both protein and dry matter percentages. Interestingly, QTL6 shows positional coincidence with the casein genes, which encode 80% of milk proteins.

Conclusions

The abrogation of lactation involves dramatic changes in the expression of genes participating in a broad array of physiological processes such as protein, lipid and carbohydrate metabolism, calcium homeostasis, cell death and tissue remodeling, as well as immunity. We also conclude that genetic variation at the casein genes has a major impact on the milk protein content of Murciano-Granadina goats.

Genetic analysis of novel phenotypes for farm animal resilience to weather variability

BACKGROUND

Climate change is expected to have a negative impact on food availability. While most efforts have been directed to reducing greenhouse gas emissions, complementary strategies are necessary to control the detrimental effects of climate change on farm animal performance. The objective of this study was to develop novel animal resilience phenotypes using reaction norm slopes, and examine their genetic and genomic parameters. A closely monitored dairy goat population was used for this purpose.

RESULTS

Individual animals differed in their response to changing atmospheric temperature and a temperature-humidity index. Significant genetic variance and heritability estimates were derived for these animal resilience phenotypes. Furthermore, some resilience traits had a significant unfavourable genetic correlation with animal performance. Genome-wide association analyses identified several candidate genes related to animal resilience to environment change.

CONCLUSIONS

Heritable variation exists among dairy goats in their production response to fluctuating weather variables. Results may inform future breeding programmes aimed to ensure efficient animal performance under changing climatic conditions.

Recent advances in breeding and genetics for dairy goats

Goats (Capra hircus) were domesticated during the late Neolithic, approximately 10,500 years ago, and humans exerted minor selection pressure until fairly recently. Probably the largest genetic change occurring over the millennia happened via natural selection and random genetic drift, the latter causing genes to be fixed in small and isolated populations. Recent human-influenced genetic changes have occurred through biometrics and genomics. For the most part, biometrics has concentrated upon the refining of estimates of heritabilities and genetic correlations. Heritabilities are instrumental in the calculation of estimated breeding values and genetic correlations are necessary in the construction of selection indices that account for changes in multiple traits under selection at one time. Early genomic studies focused upon microsatellite markers, which are short tandem repeats of nucleic acids and which are detected using polymerase chain reaction primers flanking the microsatellite. Microsatellite markers have been very important in parentage verification, which can impact genetic progress. Additionally, microsatellite markers have been a useful tool in assessing genetic diversity between and among breeds, which is important in the conservation of minor breeds. Single nucleotide polymorphisms are a new genomic tool that have refined classical BLUP methodology (biometric) to provide more accurate genomic estimated breeding values, provided a large reference population is available.

Accuracy of genomic evaluation with weighted single-step genomic best linear unbiased prediction for milk production traits, udder type traits, and somatic cell scores in French dairy goats

Genomic evaluation of French dairy goats is routinely conducted using the single-step genomic BLUP (ssGBLUP) method. This method has the advantage of simultaneously using all phenotypes, pedigrees, and genotypes. However, ssGBLUP assumes that all SNP explain the same amount of genetic variance, which is unlikely in the case of traits whose major genes or QTL are segregating. In this study, we investigated the effect of weighted ssGBLUP and its alternatives, which give more weight to SNP associated with the trait, on the accuracy of genomic evaluation of milk production, udder type traits, and somatic cell scores. The data set included 2,955 genotyped animals and 2,543,680 pedigree animals. The number of phenotypes varied with the trait. The accuracy of genomic evaluation was assessed on 205 genotyped Alpine and 146 genotyped Saanen goats born between 2009 and 2012. For traits with unknown QTL, weighted ssGBLUP was less accurate than, or as accurate as, ssGBLUP. For traits with identified QTL (i.e., QTL only present in the Saanen breed), weighted ssGBLUP outperformed ssGBLUP by between 2 and 14%.

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).