Reproductive performance is a key indicator of the long-term sustainability of any livestock production system. Testicular hypoplasia (TH) is a morphological and functional reproductive disorder that affects bulls around the world and consequently causes major economic losses due to reduced fertility rates. Despite the improvements in management practices to enhance performance of affected animals, the use of hypoplastic animals for reproduction might contribute to expand the prevalence of this disorder. The aim of this study was to identify genomic regions that are associated with TH in Nellore cattle by performing a genome-wide association study (GWAS) and functional analyses. Phenotypic and pedigree data from 47,563 animals and genotypes (500,689 Single Nucleotide Polymorphism, SNPs) from 265 sires were used in this study. TH was evaluated as a binary trait measured at 18 months of age. The estimated breeding values (EBVs) were calculated by fitting a single-trait threshold animal model using a Bayesian approach. The SNP effects were estimated using the Bayes C method and de-regressed EBVs for TH as the response variable (pseudo-phenotype). The top-15 ranking windows (5-adjacent SNPs) that explained the highest proportion of variance were identified for further functional and biological network analyses. The posterior mean (95% highest posterior density) of the heritability for TH was 0.16 (0.08; 0.23). The most important genomic windows were located on BTA1, BTA3, BTA4, BTA5, BTA9, BTA22, BTA23, and BTA25. These windows explained together 22.69% of the total additive genetic variance for TH. Strong candidate genes associated with metabolism and synthesis of steroids, cell survival, spermatogenesis process and sperm motility were identified, which might play an important role in the expression of TH. Our findings contribute to a better biological understanding of TH and future characterization of causal variants might enable improved genomic prediction of this trait in beef cattle.

Next-generation sequencing is an efficient method that allows for substantially more markers than previous technologies, providing opportunities for building high-density genetic linkage maps, which facilitate the development of nonmodel species' genomic assemblies and the investigation of their genes. However, constructing genetic maps using data generated via high-throughput sequencing technology (e.g., genotyping-by-sequencing) is complicated by the presence of sequencing errors and genotyping errors resulting from missing parental alleles due to low sequencing depth. If unaccounted for, these errors lead to inflated genetic maps. In addition, map construction in many species is performed using full-sibling family populations derived from the outcrossing of two individuals, where unknown parental phase and varying segregation types further complicate construction. We present a new methodology for modeling low coverage sequencing data in the construction of genetic linkage maps using full-sibling populations of diploid species, implemented in a package called GUSMap. Our model is based on the Lander-Green hidden Markov model but extended to account for errors present in sequencing data. We were able to obtain accurate estimates of the recombination fractions and overall map distance using GUSMap, while most existing mapping packages produced inflated genetic maps in the presence of errors. Our results demonstrate the feasibility of using low coverage sequencing data to produce genetic maps without requiring extensive filtering of potentially erroneous genotypes, provided that the associated errors are correctly accounted for in the model.

Accurate imputation plays a major role in genomic studies of livestock industries, where the number of genotyped or sequenced animals is limited by costs. This study explored methods to create an ideal reference population for imputation to Next Generation Sequencing data in cattle.

Our aim was to identify genomic regions via genome-wide association studies (GWAS) to improve the predictability of genetic merit in Holsteins for 10 calving and 28 body conformation traits. Animals were genotyped using the Illumina Bovine 50 K BeadChip and imputed to the Illumina BovineHD BeadChip (HD). GWAS were performed on 601,717 real and imputed single nucleotide polymorphism (SNP) genotypes using a single-SNP mixed linear model on 4841 Holstein bulls with breeding value predictions and followed by gene identification and in silico functional analyses. The association results were further validated using five scenarios with different numbers of SNPs.

Improving swine climatic resilience through genomic selection has the potential to minimize welfare issues and increase the industry profitability. The main objective of this study was to investigate the genetic and genomic determinism of tolerance to heat stress in four independent purebred populations of swine. Three female reproductive traits were investigated: total number of piglets born (TNB), number of piglets born alive (NBA) and average birth weight (ABW). More than 80,000 phenotypic and 12,000 genotyped individuals were included in this study. Genomic random-regression models were fitted regressing the phenotypes of interest on a set of 95 environmental covariates extracted from public weather station records. The models yielded estimates of (genomic) reactions norms for individual pigs, as indicator of heat tolerance. Heat tolerance is a heritable trait, although the heritabilities are larger under comfortable than heat-stress conditions (larger than 0.05 vs. 0.02 for TNB; 0.10 vs. 0.05 for NBA; larger than 0.20 vs. 0.10 for ABW). TNB showed the lowest genetic correlation (-38%) between divergent climatic conditions, being the trait with the strongest impact of genotype by environment interaction, while NBA and ABW showed values slightly negative or equal to zero reporting a milder impact of the genotype by environment interaction. After estimating genetic parameters, a genome-wide association study was performed based on the single-step GBLUP method. Heat tolerance was observed to be a highly polygenic trait. Multiple and non-overlapping genomic regions were identified for each trait based on the genomic breeding values for reproductive performance under comfortable or heat stress conditions. Relevant regions were found on chromosomes (SSC) 1, 3, 5, 6, 9, 11, and 12, although there were important regions across all autosomal chromosomes. The genomic region located on SSC9 appears to be of particular interest since it was identified for two traits (TNB and NBA) and in two independent populations. Heat tolerance based on reproductive performance indicators is a heritable trait and genetic progress for heat tolerance can be achieved through genetic or genomic selection. Various genomic regions and candidate genes with important biological functions were identified, which will be of great value for future functional genomic studies.

Inner-Mongolia Sanhe cattle are well-adapted to low-temperature conditions, but the metabolic mechanisms underlying their climatic resilience are still unknown. Based on the 1H Nuclear Magnetic Resonance platform, 41 metabolites were identified and quantified in the serum of 10 heifers under thermal neutrality (5 °C), and subsequent exposure to hyper-cold temperature (-32 °C) for 3 h. Subsequently, 28 metabolites were pre-filtrated, and they provided better performance in multivariate analysis than that of using 41 metabolites. This indicated the need for pre-filtering of the metabolome data in a paired experimental design. In response to the cold exposure challenge, 19 metabolites associated with cold stress response were identified, mainly enriched in "aminoacyl-tRNA biosynthesis" and "valine, leucine, and isoleucine degradation". A further integration of metabolome and gene expression highlighted the functional roles of the DLD (dihydrolipoamide dehydrogenase), WARS (tryptophanyl-tRNA synthetase), and RARS (arginyl-tRNA synthetase) genes in metabolic pathways of valine and leucine. Furthermore, the essential regulations of SLC30A6 (solute carrier family 30 (zinc transporter), member 6) in metabolic transportation for propionate, acetate, valine, and leucine under severe cold exposure were observed. Our findings presented a comprehensive characterization of the serum metabolome of Inner-Mongolia Sanhe cattle, and contributed to a better understanding of the crucial roles of regulations in metabolites and metabolic pathways during cold stress events in cattle.

There is an increasing need to account for genotype-by-environment (G × E) interactions in livestock breeding programs to improve productivity and animal welfare across environmental and management conditions. This is even more relevant for pigs because selection occurs in high-health nucleus farms, while commercial pigs are raised in more challenging environments. In this study, we used single-step homoscedastic and heteroscedastic genomic reaction norm models (RNM) to evaluate G × E interactions in Large White pigs, including 8686 genotyped animals, for reproduction (total number of piglets born, TNB; total number of piglets born alive, NBA; total number of piglets weaned, NW), growth (weaning weight, WW; off-test weight, OW), and body composition (ultrasound muscle depth, MD; ultrasound backfat thickness, BF) traits. Genetic parameter estimation and single-step genome-wide association studies (ssGWAS) were performed for each trait.

Understanding the biological mechanisms of climatic adaptation is of paramount importance for the optimization of breeding programs and conservation of genetic resources. The aim of this study was to investigate genetic diversity and unravel genomic regions potentially under selection for heat and/or cold tolerance in thirty-two worldwide cattle breeds, with a focus on Chinese local cattle breeds adapted to divergent climatic conditions, Datong yak (Bos grunniens; YAK), and Bali (Bos javanicus) based on dense SNP data. In general, moderate genetic diversity levels were observed in most cattle populations. The proportion of polymorphic SNP ranged from 0.197 (YAK) to 0.992 (Mongolian cattle). Observed and expected heterozygosity ranged from 0.023 (YAK) to 0.366 (Sanhe cattle; SH), and from 0.021 (YAK) to 0.358 (SH), respectively. The overall average inbreeding (±SD) was: 0.118 ± 0.028, 0.228 ± 0.059, 0.194 ± 0.041, and 0.021 ± 0.004 based on the observed versus expected number of homozygous genotypes, excess of homozygosity, correlation between uniting gametes, and runs of homozygosity (ROH), respectively. Signatures of selection based on multiple scenarios and methods (F ST, HapFLK, and ROH) revealed important genomic regions and candidate genes. The candidate genes identified are related to various biological processes and pathways such as heat-shock proteins, oxygen transport, anatomical traits, mitochondrial DNA maintenance, metabolic activity, feed intake, carcass conformation, fertility, and reproduction. This highlights the large number of biological processes involved in thermal tolerance and thus, the polygenic nature of climatic resilience. A comprehensive description of genetic diversity measures in Chinese cattle and YAK was carried out and compared to 24 worldwide cattle breeds to avoid potential biases. Numerous genomic regions under positive selection were detected using three signature of selection methods and candidate genes potentially under positive selection were identified. Enriched function analyses pinpointed important biological pathways, molecular function and cellular components, which contribute to a better understanding of the biological mechanisms underlying thermal tolerance in cattle. Based on the large number of genomic regions identified, thermal tolerance has a complex polygenic inheritance nature, which was expected considering the various mechanisms involved in thermal stress response.

Facial eczema (FE) is a significant metabolic disease that affects New Zealand ruminants. Ingestion of the mycotoxin sporidesmin leads to liver and bile duct damage, which can result in photosensitisation, reduced productivity and death. Strategies used to manage the incidence and severity of the disease include breeding. In sheep, there is considerable genetic variation in the response to FE. A commercial testing program is available for ram breeders who aim to increase tolerance, determined by the concentration of the serum enzyme, gamma-glutamyltransferase 21 days after a measured sporidesmin challenge (GGT21). Genome-wide association studies were carried out to determine regions of the genome associated with GGT21. Two regions on chromosomes 15 and 24 are reported, which explain 5% and 1% of the phenotypic variance in the response to FE, respectively. The region on chromosome 15 contains the β-globin locus. Of the significant SNPs in the region, one is a missense variant within the haemoglobin subunit β (HBB) gene. Mass spectrometry of haemoglobin from animals with differing genotypes at this locus indicated that genotypes are associated with different forms of adult β-globin. Haemoglobin haplotypes have previously been associated with variation in several health-related traits in sheep and warrant further investigation regarding their role in tolerance to FE in sheep. We show a strategic approach to the identification of regions of importance for commercial breeding programs with a combination of discovery, statistical and biological validation. This study highlights the power of using increased density genotyping for the identification of influential genomic regions, combined with subsequent inclusion on lower density genotyping platforms.

Given the economic relevance of fertility and reproductive traits for the beef cattle industry, investigating their genetic background and developing effective breeding strategies are paramount. Considering their late and sex-dependent phenotypic expression, genomic information can contribute to speed up the rates of genetic progress per year. In this context, the main objectives of this study were to estimate variance components and genetic parameters, including heritability and genetic correlations, for fertility, female precocity, and semen production and quality (andrological attributes) traits in Nellore cattle incorporating genomic information.

An improved estimator of genomic relatedness using low-depth high-throughput sequencing data for autopolyploids is developed. Its outputs strongly correlate with SNP array-based estimates and are available in the package GUSrelate. High-throughput sequencing (HTS) methods have reduced sequencing costs and resources compared to array-based tools, facilitating the investigation of many non-model polyploid species. One important quantity that can be computed from HTS data is the genetic relatedness between all individuals in a population. However, HTS data are often messy, with multiple sources of errors (i.e. sequencing errors or missing parental alleles) which, if not accounted for, can lead to bias in genomic relatedness estimates. We derive a new estimator for constructing a genomic relationship matrix (GRM) from HTS data for autopolyploid species that accounts for errors associated with low sequencing depths, implemented in the R package GUSrelate. Simulations revealed that GUSrelate performed similarly to existing GRM methods at high depth but reduced bias in self-relatedness estimates when the sequencing depth was low. Using a panel consisting of 351 tetraploid potato genotypes, we found that GUSrelate produced GRMs from genotyping-by-sequencing (GBS) data that were highly correlated with a GRM computed from SNP array data, and less biased than existing methods when benchmarking against the array-based GRM estimates. GUSrelate provides researchers with a tool to reliably construct GRMs from low-depth HTS data.

Basic understanding of linkage disequilibrium (LD) and population structure, as well as the consistency of gametic phase across breeds is crucial for genome-wide association studies and successful implementation of genomic selection. However, it is still limited in goats. Therefore, the objectives of this research were: (i) to estimate genome-wide levels of LD in goat breeds using data generated with the Illumina Goat SNP50 BeadChip; (ii) to study the consistency of gametic phase across breeds in order to evaluate the possible use of a multi-breed training population for genomic selection and (iii) develop insights concerning the population history of goat breeds.

Genotyping-by-sequencing (GBS) is becoming an attractive alternative to array-based methods for genotyping individuals for a large number of single nucleotide polymorphisms (SNPs). Costs can be lowered by reducing the mean sequencing depth, but this results in genotype calls of lower quality. A common analysis strategy is to filter SNPs to just those with sufficient depth, thereby greatly reducing the number of SNPs available. We investigate methods for estimating relatedness using GBS data, including results of low depth, using theoretical calculation, simulation and application to a real data set.

Identification of genomic regions that have been targets of selection for phenotypic traits is one of the most important and challenging areas of research in animal genetics. However, currently there are relatively few genomic regions identified that have been subject to positive selection. In this study, a genome-wide scan using ~50,000 Single Nucleotide Polymorphisms (SNPs) was performed in an attempt to identify genomic regions associated with fat deposition in fat-tail breeds. This trait and its modification are very important in those countries grazing these breeds.

Over the past 40 years New Zealand (NZ) aquaculture has grown into a significant primary industry. Tonnage is small on a global scale, but the industry has built an international reputation for the supply of high quality seafood to many overseas markets. Since the early 1990s the industry has recognized the potential gains from selective breeding and the challenge has been to develop programs that can overcome biological obstacles (such as larval rearing and mortality) and operate cost-effectively on a relatively small scale while still providing significant gains in multiple traits of economic value. This paper provides an overview of the current status, and a perspective on genomic technology implementation, for the family based genetic improvement programs established for the two main species farmed in NZ: Chinook (king) salmon (Oncorhynchus tshawytscha) and GreenshellTM mussel (Perna canaliculus). These programs have provided significant benefit to the industry in which we are now developing genomic resources based on genotyping-by-sequencing to complement the breeding programs, enable evaluation of the genetic diversity and identify the potential benefits of genomic selection. This represents an opportunity to increase genetic gain and more effectively utilize the potential for within family selection.

Investments in genetic selection have played a major role in the New Zealand sheep industry competitiveness. Selection may erode genetic diversity, which is a crucial factor for the success of breeding programs. Better understanding of linkage disequilibrium (LD) and ancestral effective population size (Ne) through quantifying this diversity and comparison between populations allows for more informed decisions with regards to selective breeding taking population genetic diversity into account. The estimation of N e can be determined via genetic markers and requires knowledge of genetic distances between these markers. Single nucleotide polymorphisms (SNP) data from a sample of 12,597 New Zealand crossbred and purebred sheep genotyped with the Illumina Ovine SNP50 BeadChip was used to perform a genome-wide scan of LD and N e . Three methods to estimate genetic distances were investigated: 1) M1: a ratio fixed across the whole genome of one Megabase per centiMorgan; 2) M2: the ratios of genetic distance (using M3, below) over physical distance fixed for each chromosome; and, 3) M3: a genetic map of inter-SNP distances estimated using CRIMAP software (v2.503).

In utero heat stress alters postnatal physiological and behavioral stress responses in pigs. However, the mechanisms underlying these alterations have not been determined. The study objective was to characterize the postnatal hypothalamic-pituitary-adrenal axis response of in utero heat-stressed pigs. Pigs were subjected to a dexamethasone suppression test followed by a corticotrophin releasing hormone challenge at 10 and 15 weeks of age. Following the challenge, hypothalamic, pituitary, and adrenal tissues were collected from all pigs for mRNA abundance analyses. At 10 weeks of age, in utero heat-stressed pigs had a reduced (P < 0.05) cortisol response to the corticotrophin releasing hormone challenge versus controls. Additionally, the cortisol response tended to be greater overall (P < 0.10) in 15 versus 10-week-old pigs in response to the dexamethasone suppression test. The cortisol response tended to be reduced overall (P < 0.10) in 15 versus 10-week-old pigs in response to the corticotrophin releasing hormone challenge. Hypothalamic corticotropin releasing hormone mRNA abundance tended to be greater (P < 0.10) in in utero heat-stressed versus control pigs at 15-weeks of age. In summary, in utero heat stress altered some aspects of the hypothalamic-pituitary-adrenal axis related to corticotropin releasing hormone signaling, and age influenced this response.

Thermal stress (heat and cold) has large economic and welfare implications for the worldwide dairy industry. Therefore, it is paramount to understand the genetic background of coping mechanism related to thermal stress for the implementation of effective genetic selection schemes in dairy cattle. We performed an association study between 11 single nucleotide polymorphisms having minor allelic frequency (MAF > 0.05) in the HSP70 gene with blood biochemical parameters. The concentrations of growth hormone (GH), lactate (LA), prolactin (PRL), and superoxide dismutase (SOD) in blood were significantly higher (p < 0.05), while the concentrations of blood urea nitrogen (BUN), c-reactive protein (CRP), potassium (K+), lactate dehydrogenase (LDH), lipid peroxide (LPO), and norepinephrine (NE) were significantly lower (p < 0.05) in heat-stressed animals as compared to the control group. A significant (p < 0.05) increase in the concentrations of cortisol (COR), corticosterone (CORT), and potassium (K+) was observed (p < 0.05), while the concentrations of adrenocorticotrophic hormone (ACTH), dopamine (DA), GH, LDH, NE, PRL, and SOD were significantly lower in cold-stressed animals as compared to the control group (p < 0.05). Furthermore, SNP A-12G and C181T were significantly associated with LA (p < 0.05), while A72G was linked with LPO (p < 0.05) in heat-stressed animals. Moreover, the SNPs A-12G and SNP C131G were significantly associated (p < 0.05) with DA and SOD under cold stress condition, respectively. These SNPs markers significantly associated with fluctuations in blood biochemical parameters under thermal stress provide a better insight into the genetic mechanisms underlying climatic resilience in Holstein cattle.

In this study, we chose 17 worldwide sheep populations of eight breeds, which were intensively selected for different purposes (meat, milk, or wool), or locally-adapted breeds, in order to identify and characterize factors impacting the detection of runs of homozygosity (ROH) and heterozygosity-rich regions (HRRs) in sheep. We also applied a business intelligence (BI) tool to integrate and visualize outputs from complementary analyses. We observed a prevalence of short ROH, and a clear distinction between the ROH profiles across populations. The visualizations showed a fragmentation of medium and long ROH segments. Furthermore, we tested different scenarios for the detection of HRR and evaluated the impact of the detection parameters used. Our findings suggest that HRRs are small and frequent in the sheep genome; however, further studies with higher density SNP chips and different detection methods are suggested for future research. We also defined ROH and HRR islands and identified common regions across the populations, where genes related to a variety of traits were reported, such as body size, muscle development, and brain functions. These results indicate that such regions are associated with many traits, and thus were under selective pressure in sheep breeds raised for different purposes. Interestingly, many candidate genes detected within the HRR islands were associated with brain integrity. We also observed a strong association of high linkage disequilibrium pattern with ROH compared with HRR, despite the fact that many regions in linkage disequilibrium were not located in ROH regions.

Junipers (Juniperus spp.) are woody native, invasive plants that have caused encroachment problems in the U.S. western rangelands, decreasing forage productivity and biodiversity. A potential solution to this issue is using goats in targeted grazing programs. However, junipers, which grow in dry and harsh environmental conditions, use chemical defense mechanisms to deter herbivores. Therefore, genetically selecting goats for increased juniper consumption is of great interest for regenerative rangeland management. In this context, the primary objectives of this study were to: 1) estimate variance components and genetic parameters for predicted juniper consumption in divergently selected Angora (ANG) and composite Boer x Spanish (BS) goat populations grazing on Western U.S. rangelands; and 2) to identify genomic regions, candidate genes, and biological pathways associated with juniper consumption in these goat populations.