Board-invited review: Applications of genomic information in livestock

Elucidation of population stratifying markers and selective sweeps in crossbred Landlly pig population using genome-wide SNP data

The present study was aimed at the identification of population stratifying markers from the commercial porcine SNP 60K array and elucidate the genome-wide selective sweeps in the crossbred Landlly pig population. Original genotyping data, generated on Landlly pigs, was merged in various combinations with global suid breeds that were grouped as exotic (global pig breeds excluding Indian and Chinese), Chinese (Chinese pig breeds only), and outgroup pig populations. Post quality control, the genome-wide SNPs were ranked for their stratifying power within each dataset in TRES (using three different criteria) and FIFS programs and top-ranked SNPs (0.5K, 1K, 2K, 3K, and 4K densities) were selected. PCA plots were used to assess the stratification power of low-density panels. Selective sweeps were elucidated in the Landlly population using intra- and inter-population haplotype statistics. Additionally, Tajima's D-statistics were calculated to determine the status of balancing selection in the Landlly population. PCA plots showed 0.5K marker density to effectively stratify Landlly from other pig populations. The A-score in DAPC program revealed the Delta statistic of marker selection to outperform other methods (informativeness and FST methods) and that 3000-marker density was suitable for stratification of Landlly animals from exotic pig populations. The results from selective sweep analysis revealed the Landlly population to be under selection for mammary (NAV2), reproductive efficiency (JMY, SERGEF, and MAP3K20), body conformation (FHIT, WNT2, ASRB, DMGDH, and BHMT), feed efficiency (CSRNP1 and ADRA1A), and immunity (U6, MYO3B, RBMS3, and FAM78B) traits. More than two methods suggested sweeps for immunity and feed efficiency traits, thus giving a strong indication for selection in this direction. The study is the first of its kind in Indian pig breeds with a comparison against global breeds. In conclusion, 500 markers were able to effectively stratify the breeds. Different traits under selective sweeps (natural or artificial selection) can be exploited for further improvement.

Livestock species as emerging models for genomic imprinting

Genomic imprinting is an epigenetically-regulated process of central importance in mammalian development and evolution. It involves multiple levels of regulation, with spatio-temporal heterogeneity, leading to the context-dependent and parent-of-origin specific expression of a small fraction of the genome. Genomic imprinting studies have therefore been essential to increase basic knowledge in functional genomics, evolution biology and developmental biology, as well as with regard to potential clinical and agrigenomic perspectives. Here we offer an overview on the contribution of livestock research, which features attractive resources in several respects, for better understanding genomic imprinting and its functional impacts. Given the related broad implications and complexity, we promote the use of such resources for studying genomic imprinting in a holistic and integrative view. We hope this mini-review will draw attention to the relevance of livestock genomic imprinting studies and stimulate research in this area.

Genome-Wide Identification of Candidate Genes for Milk Production Traits in Korean Holstein Cattle

Simple Summary

Milk production traits that are economically important in the dairy industry have been considered the main selection criteria for breeding. The present genome-wide association study was performed to identify chromosomal loci and candidate genes with potential effects on milk production phenotypes in a Korean Holstein population. A total of eight significant quantitative trait locus regions were identified for milk yield (Bos taurus autosome (BTA) 7 and 14), adjusted 305-d fat yield (BTA 3, 5, and 14), adjusted 305-d protein yield (BTA 8), and somatic cell score (BTA 8 and 23) of milk production traits. Furthermore, we discovered three main candidate genes (diacylglycerol O-acyltransferase 1 (DGAT1), phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) through bioinformatics analysis. These genes may help to understand better the underlying genetic and molecular mechanisms for milk production phenotypes in the Korean Holstein population.

Abstract

We performed a genome-wide association study and fine mapping using two methods (single marker regression: frequentist approach and Bayesian C (BayesC): fitting selected single nucleotide polymorphisms (SNPs) in a Bayesian framework) through three high-density SNP chip platforms to analyze milk production phenotypes in Korean Holstein cattle (n = 2780). We identified four significant SNPs for each phenotype in the single marker regression model: AX-311625843 and AX-115099068 on Bos taurus autosome (BTA) 14 for milk yield (MY) and adjusted 305-d fat yield (FY), respectively, AX-428357234 on BTA 18 for adjusted 305-d protein yield (PY), and AX-185120896 on BTA 5 for somatic cell score (SCS). Using the BayesC model, we discovered significant 1-Mb window regions that harbored over 0.5% of the additive genetic variance effects for four milk production phenotypes. The concordant significant SNPs and 1-Mb window regions were characterized into quantitative trait loci (QTL). Among the QTL regions, we focused on a well-known gene (diacylglycerol O-acyltransferase 1 (DGAT1)) and newly identified genes (phosphodiesterase 4B (PDE4B), and anoctamin 2 (ANO2)) for MY and FY, and observed that DGAT1 is involved in glycerolipid metabolism, fat digestion and absorption, metabolic pathways, and retinol metabolism, and PDE4B is involved in cAMP signaling. Our findings suggest that the candidate genes in QTL are strongly related to physiological mechanisms related to the fat production and consequent total MY in Korean Holstein cattle.

Genome-wide association studies reveal novel loci associated with carcass and body measures in beef cattle

Genomic selection has an essential role in the livestock economy by increasing selection productivity. Genomics provides a mechanism to increase the rate of genetic gain using marker-assisted selection. Various quantitative trait loci (QTL) associated with body, carcass and meat quality traits in beef cattle have been found. It is widely accepted that QTL traits in livestock species are regulated by several genes and factors from the environment. Genome-wide association studies (GWAS) are a powerful approach in identifying QTL and to establish genomic regions harboring the genes and polymorphisms associated with specific characteristics in beef cattle. Due to their impact on economic returns, growth, carcass and meat quality traits of cattle are frequently used as essential criteria in selection in breeding programs., GWAS has been used in beef cattle breeding and genetic program and some progress has been made. Furthermore, numerous genes and markers related to productivity traits in beef cattle have been found. This review summarizes the advances in the use of GWAS in beef cattle production and outlines the associations with growth, carcass, and meat quality.

Cyberbiosecurity: A New Perspective on Protecting U.S. Food and Agricultural System

Our national data and infrastructure security issues affecting the "bioeconomy" are evolving rapidly. Simultaneously, the conversation about cyber security of the U.S. food and agricultural system (cyber biosecurity) is incomplete and disjointed. The food and agricultural production sectors influence over 20% of the nation's economy ($6.7T) and 15% of U.S. employment (43.3M jobs). The food and agricultural sectors are immensely diverse and they require advanced technologies and efficiencies that rely on computer technologies, big data, cloud-based data storage, and internet accessibility. There is a critical need to safeguard the cyber biosecurity of our bio economy, but currently protections are minimal and do not broadly exist across the food and agricultural system. Using the food safety management Hazard Analysis Critical Control Point system concept as an introductory point of reference, we identify important features in broad food and agricultural production and food systems: dairy, food animals, row crops, fruits and vegetables, and environmental resources (water). This analysis explores the relevant concepts of cyber biosecurity from food production to the end product user (such as the consumer) and considers the integration of diverse transportation, supplier, and retailer networks. We describe common challenges and unique barriers across these systems and recommend solutions to advance the role of cyber biosecurity in the food and agricultural sectors.

Differences in gene expression profiles for subcutaneous adipose, liver, and skeletal muscle tissues between Meishan and Landrace pigs with different backfat thicknesses

Backfat thickness is one of the most important traits of commercially raised pigs. Meishan pigs are renowned for having thicker backfat than Landrace pigs. To examine the genetic factors responsible for the differences, we first produced female crossbred pig lines by mating Landrace (L) × Large White (W) × Duroc (D) females (LWD) with Landrace (L) or Meishan (M) boars (i.e., LWD × L = LWDL for Landrace offspring and LWD × M = LWDM for the Meishan offspring). We confirmed that LWDM pigs indeed had a thicker backfat than LWDL pigs. Next, we performed gene expression microarray analysis in both genetic lines to examine differentially expressed genes (DEGs) in energy metabolism-related tissues, subcutaneous adipose (fat), liver, and longissimus dorsi muscle tissues. We analyzed the annotation of DEGs (2-fold cutoff) to functionally categorize them by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways. The number of DEGs in muscle tissues of both lines was much less than that in fat and liver tissues, indicating that DEGs in muscle tissues may not contribute much to differences in backfat thickness. In contrast, several genes related to muscle (in fat tissue) and lipid metabolism (in liver tissue) were more upregulated in LWDM pigs than LWDL pigs, indicating that those DEGs might be responsible for differences in backfat thickness. The different genome-wide gene expression profiles in the fat, liver, and muscle tissues between genetic lines can provide useful information for pig breeders.

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).

Building strong relationships between conservation genetics and primary industry leads to mutually beneficial genomic advances

Several reviews in the past decade have heralded the benefits of embracing high-throughput sequencing technologies to inform conservation policy and the management of threatened species, but few have offered practical advice on how to expedite the transition from conservation genetics to conservation genomics. Here, we argue that an effective and efficient way to navigate this transition is to capitalize on emerging synergies between conservation genetics and primary industry (e.g., agriculture, fisheries, forestry and horticulture). Here, we demonstrate how building strong relationships between conservation geneticists and primary industry scientists is leading to mutually-beneficial outcomes for both disciplines. Based on our collective experience as collaborative New Zealand-based scientists, we also provide insight for forging these cross-sector relationships.

Updating the reference population to achieve constant genomic prediction reliability across generations

The reliability of genomic breeding values (DGV) decays over generations. To keep the DGV reliability at a constant level, the reference population (RP) has to be continuously updated with animals from new generations. Updating RP may be challenging due to economic reasons, especially for novel traits involving expensive phenotyping. Therefore, the goal of this study was to investigate a minimal RP update size to keep the reliability at a constant level across generations. We used a simulated dataset resembling a dairy cattle population. The trait of interest was not included itself in the selection index, but it was affected by selection pressure by being correlated with an index trait that represented the overall breeding goal. The heritability of the index trait was assumed to be 0.25 and for the novel trait the heritability equalled 0.2. The genetic correlation between the two traits was 0.25. The initial RP (n=2000) was composed of cows only with a single observation per animal. Reliability of DGV using the initial RP was computed by evaluating contemporary animals. Thereafter, the RP was used to evaluate animals which were one generation younger from the reference individuals. The drop in the reliability when evaluating younger animals was then assessed and the RP was updated to re-gain the initial reliability. The update animals were contemporaries of evaluated animals (EVA). The RP was updated in batches of 100 animals/update. First, the animals most closely related to the EVA were chosen to update RP. The results showed that, approximately, 600 animals were needed every generation to maintain the DGV reliability at a constant level across generations. The sum of squared relationships between RP and EVA and the sum of off-diagonal coefficients of the inverse of the genomic relationship matrix for RP, separately explained 31% and 34%, respectively, of the variation in the reliability across generations. Combined, these parameters explained 53% of the variation in the reliability across generations. Thus, for an optimal RP update an algorithm considering both relationships between reference and evaluated animals, as well as relationships among reference animals, is required.

Comparison of linkage disequilibrium levels in Iranian indigenous cattle using whole genome SNPs data

BACKGROUND

Knowledge of linkage disequilibrium (LD) levels among different populations can be used to detect genetic diversity and to investigate the historical changes in population sizes. Availability of large numbers of SNP through new sequencing technologies has provided opportunities for extensive researches in quantifying LD patterns in cattle breeds. The aim of this study was to compare the extent of linkage disequilibrium among Iranian cattle breeds using high density SNP genotyping data.

RESULTS

A total of 70 samples, representing seven Iranian indigenous cattle breeds, were genotyped for 777962 SNPs. The average values of LD based on the r(2) criterion were computed by grouping all syntenic SNP pairwises for inter-marker distances from 0 Kb up to 1 Mb using three distance sets. Average r(2) above 0.3 was observed at distances less than 30 Kb for Sistani and Kermani, 20 Kb for Najdi, Taleshi, Kurdi and Sarabi, and 10 Kb for Mazandarani. The LD levels were considerably different among the Iranian cattle breeds and the difference in LD extent was more detectable between the studied breeds at longer distances. Lower level of LD was observed for Mazandarani breed as compared to other breeds indicating larger ancestral population size in this breed. Kermani breed continued to have more slowly LD decay than all of the other breeds after 3 Kb distances. More slowly LD decay was observed in Kurdi and Sarabi breeds at larger distances (>100 Kb) showing that population decline has been more intense in more recent generations for these populations.

CONCLUSIONS

A wide genetic diversity and different historical background were well reflected in the LD levels among Iranian cattle breeds. More LD fluctuation was observed in the shorter distances (less than 10 Kb) in different cattle populations. Despite of the sample size effects, High LD levels found in this study were in accordance with the presence of inbreeding and population decline in Iranian cattle breeds.

Two novel polymorphisms of bovine SIRT2 gene are associated with higher body weight in Nanyang cattle

Identification of polymorphisms associated with economic traits is important for successful marker-assisted selection in cattle breeding. The family of mammalian sirtuin regulates many biological functions, such as life span extension and energy metabolism. SIRT2, a most abundant sirtuin in adipocytes, acts as a crucial regulator of adipogenic differentiation and plays a key role in controlling adipose tissue function and mass. Here we investigated single nucleotide polymorphisms (SNPs) of bovine SIRT2 in 1226 cattle from five breeds and further evaluated the effects of identified SNPs on economically important traits of Nanyang cattle. Our results revealed four novel SNPs in bovine SIRT2, one was located in intronic region and the other three were synonymous mutations. Linkage disequilibrium and haplotype analyses based on the identified SNPs showed obvious difference between crossbred breed and the other four beef breeds. Association analyses demonstrated that SNPs g.17333C > T and g.17578A > G have a significantly effect on 18-months-old body weight of Nanyang population. Animals with combined genotype TTGG at the above two loci exhibited especially higher body weight. Our data for the first time demonstrated that polymorphisms in bovine SIRT2 are associated with economic traits of Nanyang cattle, which will be helpful for future cattle selection practices.

A comparison of principal component regression and genomic REML for genomic prediction across populations

BACKGROUND

Genomic prediction faces two main statistical problems: multicollinearity and n ≪ p (many fewer observations than predictor variables). Principal component (PC) analysis is a multivariate statistical method that is often used to address these problems. The objective of this study was to compare the performance of PC regression (PCR) for genomic prediction with that of a commonly used REML model with a genomic relationship matrix (GREML) and to investigate the full potential of PCR for genomic prediction.

METHODS

The PCR model used either a common or a semi-supervised approach, where PC were selected based either on their eigenvalues (i.e. proportion of variance explained by SNP (single nucleotide polymorphism) genotypes) or on their association with phenotypic variance in the reference population (i.e. the regression sum of squares contribution). Cross-validation within the reference population was used to select the optimum PCR model that minimizes mean squared error. Pre-corrected average daily milk, fat and protein yields of 1609 first lactation Holstein heifers, from Ireland, UK, the Netherlands and Sweden, which were genotyped with 50 k SNPs, were analysed. Each testing subset included animals from only one country, or from only one selection line for the UK.

RESULTS

In general, accuracies of GREML and PCR were similar but GREML slightly outperformed PCR. Inclusion of genotyping information of validation animals into model training (semi-supervised PCR), did not result in more accurate genomic predictions. The highest achievable PCR accuracies were obtained across a wide range of numbers of PC fitted in the regression (from one to more than 1000), across test populations and traits. Using cross-validation within the reference population to derive the number of PC, yielded substantially lower accuracies than the highest achievable accuracies obtained across all possible numbers of PC.

CONCLUSIONS

On average, PCR performed only slightly less well than GREML. When the optimal number of PC was determined based on realized accuracy in the testing population, PCR showed a higher potential in terms of achievable accuracy that was not capitalized when PC selection was based on cross-validation. A standard approach for selecting the optimal set of PC in PCR remains a challenge.

Peptide Arrays for Kinome Analysis of Livestock Species

Reversible protein phosphorylation is a central mechanism for both the transfer of intracellular information and the initiation of cellular responses. Within human medicine, considerable emphasis is placed on understanding and controlling the enzymes (kinases) that are responsible for catalyzing these modifications. This is evident in the prominent use of kinase inhibitors as drugs as well as the trend to understand complex biology and identify biomarkers via characterizations of global kinase (kinome) activity. Despite the demonstrated value of focusing on kinome activity, the application of this perspective to livestock has been restricted by the absence of appropriate research tools. In this review, we discuss the development of software platforms that facilitate the development and application of species-specific peptide arrays for kinome analysis of livestock. Examples of the application of kinomic approaches to a number of priority species (cattle, pigs, and chickens) in a number of biological contexts (infections, biomarker discovery, and food quality) are presented as are emerging trends for kinome analysis of livestock.

Impact of whole-genome amplification on the reliability of pre-transfer cattle embryo breeding value estimates

Background

Genome-wide profiling of single-nucleotide polymorphisms is receiving increasing attention as a method of pre-implantation genetic diagnosis in humans and of commercial genotyping of pre-transfer embryos in cattle. However, the very small quantity of genomic DNA in biopsy material from early embryos poses daunting technical challenges. A reliable whole-genome amplification (WGA) procedure would greatly facilitate the procedure.

Results

Several PCR-based and non-PCR based WGA technologies, namely multiple displacement amplification, quasi-random primed library synthesis followed by PCR, ligation-mediated PCR, and single-primer isothermal amplification were tested in combination with different DNA extractions protocols for various quantities of genomic DNA inputs. The efficiency of each method was evaluated by comparing the genotypes obtained from 15 cultured cells (representative of an embryonic biopsy) to unamplified reference gDNA. The gDNA input, gDNA extraction method and amplification technology were all found to be critical for successful genome-wide genotyping. The selected WGA platform was then tested on embryo biopsies (n = 226), comparing their results to that of biopsies collected after birth. Although WGA inevitably leads to a random loss of information and to the introduction of erroneous genotypes, following genomic imputation the resulting genetic index of both sources of DNA were highly correlated (r = 0.99, P<0.001).

Conclusion

It is possible to generate high-quality DNA in sufficient quantities for successful genome-wide genotyping starting from an early embryo biopsy. However, imputation from parental and population genotypes is a requirement for completing and correcting genotypic data. Judicious selection of the WGA platform, careful handling of the samples and genomic imputation together, make it possible to perform extremely reliable genomic evaluations for pre-transfer embryos.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-889) contains supplementary material, which is available to authorized users.

Advances in European sea bass genomics and future perspectives

Only recently available sequenced and annotated teleost fish genomes were restricted to a few model species, none of which were for aquaculture. The application of marker assisted selection for improved production traits had been largely restricted to the salmon industry and genetic and Quantitative Trait Loci (QTL) maps were available for only a few species. With the advent of next generation sequencing the landscape is rapidly changing and today the genomes of several aquaculture species have been sequenced. The European sea bass, Dicentrarchus labrax, is a good example of a commercially important aquaculture species in Europe for which in the last decade a wealth of genomic resources, including a chromosomal scale genome assembly, physical and linkage maps as well as relevant QTL have been generated. The current challenge is to stimulate the uptake of the resources by the industry so that the full potential of this scientific endeavor can be exploited and produce benefits for producers and the public alike.

Genomic selection: Status in different species and challenges for breeding

Technical advances and development in the market for genomic tools have facilitated access to whole-genome data across species. Building-up on the acquired knowledge of the genome sequences, large-scale genotyping has been optimized for broad use, so genotype information can be routinely used to predict genetic merit. Genomic selection (GS) refers to the use of aggregates of estimated marker effects as predictors which allow improved individual differentiation at young age. Realizable benefits of GS are influenced by several factors and vary in quantity and quality between species. General characteristics and challenges of GS in implementation and routine application are described, followed by an overview over the current status of its use, prospects and challenges in important animal species. Genetic gain for a particular trait can be enhanced by shortening of the generation interval, increased selection accuracy and increased selection intensity, with species- and breed-specific relevance of the determinants. Reliable predictions based on genetic marker effects require assembly of a reference for linking of phenotype and genotype data to allow estimation and regular re-estimation. Experiences from dairy breeding have shown that international collaboration can set the course for fast and successful implementation of innovative selection tools, so genomics may significantly impact the structures of future breeding and breeding programmes. Traits of great and increasing importance, which were difficult to improve in the conventional systems, could be emphasized, if continuous availability of high-quality phenotype data can be assured. Equally elaborate strategies for genotyping and phenotyping will allow tailored approaches to balance efficient animal production, sustainability, animal health and welfare in future.

The integration of 'omic' disciplines and systems biology in cattle breeding

Enormous progress has been made in the selection of animals, including cattle, for specific traits using traditional quantitative genetics approaches. Nevertheless, considerable variation in phenotypes remains unexplained, and therefore represents potential additional gain for animal production. In addition, the paradigm shift in new disciplines now being applied to animal breeding represents a powerful opportunity to prise open the 'black box' underlying the response to selection and fully understand the genetic architecture controlling the traits of interest. A move away from traditional approaches of animal breeding toward systems approaches using integrative analysis of data from the 'omic' disciplines represents a multitude of exciting opportunities for animal breeding going forward as well as providing alternatives for overcoming some of the limitations of traditional approaches such as the expressed phenotype being an imperfect predictor of the individual's true genetic merit, or the phenotype being only expressed in one gender or late in the lifetime of an animal. This review aims to discuss these opportunities from the perspective of their potential application and contribution to cattle breeding. Harnessing the potential of this paradigm shift also poses some new challenges for animal scientists - and they will also be discussed.

A catalogue of validated single nucleotide polymorphisms in bovine orthologs of mammalian imprinted genes and associations with beef production traits

Genetic (or 'genomic') imprinting, a feature of approximately 100 mammalian genes, results in monoallelic expression from one of the two parentally inherited chromosomes. To date, most studies have been directed on imprinted genes in murine or human models; however, there is burgeoning interest in the effects of imprinted genes in domestic livestock species. In particular, attention has focused on imprinted genes that influence foetal growth and development and that are associated with several economically important production traits in cattle, sheep and pigs. We have re-sequenced regions in 20 candidate bovine imprinted genes in order to validate single nucleotide polymorphisms (SNPs) that may influence important production traits in cattle. Putative SNPs detected via re-sequencing were subsequently re-formatted for high-throughput SNP genotyping in 185 cattle samples comprising 138 performance-tested European Bos taurus (all Limousin bulls), 29 African B. taurus and 18 Indian B. indicus samples. Analysis of the resulting genotypic data identified 117 validated SNPs. Preliminary genotype-phenotype association analyses using 83 SNPs that were polymorphic in the Limousin samples with minor allele frequencies ⩾0.05 revealed significant associations between two candidate bovine imprinted genes and a range of important beef production traits: average daily gain, average feed intake, live weight, feed conversion ratio, residual feed intake and residual gain. These genes were the Ras protein-specific guanine nucleotide releasing factor gene (RASGRF1) and the zinc finger, imprinted 2 gene (ZIM2). Despite the relatively small sample size used in these analyses, the observed associations with production traits are supported by the purported biological function of the RASGRF1 and ZIM2 gene products. These results support the hypothesis that imprinted genes contribute significantly to important complex production traits in cattle. Furthermore, these SNPs may be usefully incorporated into future marker-assisted and genomic selection breeding schemes.

Changes in gene expression in a porcine preadipocyte cell line during differentiation

Adipocyte differentiation plays an important role in the formation of fat tissues in pigs and affects meat quality and productivity. Clarification of the nature of the pig genes that participate in adipocyte differentiation will provide a clue to the regulation of fat content and thickness in pig carcases by dietary control; it will also help to find target genes for exploring potentially useful polymorphisms for molecular breeding aimed at fat traits. We constructed a DNA oligomer microarray based on pig transcripts, and we used the array to investigate time-dependent changes in gene expression in the PSPA porcine preadipocyte cell line during differentiation into adipocytes. We selected genes with markedly altered expression (at least fivefold difference in comparison with expression in undifferentiated cells) and classified them into five groups according to gene expression pattern. In the early stage after stimulation of adipocyte differentiation, we observed up-regulation of many genes encoding proteins involved in regulating cell proliferation and transcription. Among the probes corresponding to transcripts that showed marked changes in expression, 27 were located within previously reported QTL regions for traits related to adipose tissues. These results will be valuable resources for finding the genes responsible for fat-related traits that have been identified in previous studies using various pig resource families.

Use of female information in dairy cattle genomic breeding programs

Genomic selection has the potential to increase the accuracy of selection and, therefore, genetic gain, as well as reducing the rate of inbreeding, yet few studies have evaluated the potential benefit of the contribution of females in genomic selection programs. The objective of this study was to determine the effect on genetic gain, accuracy of selection, generation interval, and inbreeding, of including female genotypes in a genomic selection breeding program. A population of approximately 3,500 females and 500 males born annually was simulated and split into an elite and commercial tier representation of the Irish national herd. Several alternative breeding schemes were evaluated to quantify the potential benefit of female genomic information within dairy breeding schemes. Results showed that the inclusion of female phenotypic and genomic information can lead to a 3-fold increase in the rate of genetic gain compared with a traditional BLUP breeding program and decrease the generation interval of the males by 3.8 yr, while maintaining a reasonable rate of inbreeding. The accuracy of the selected males was increased by 73% in the final 3 yr of the genomic schemes compared with the traditional BLUP scheme. The results of this study have several implications for national breeding schemes. Although an investment in genotyping a large population of animals is required, these costs can be offset by the greater genetic gain achievable through the increased accuracy of selection and decreased generation intervals associated with genomic selection.

A genome scan for quantitative trait loci influencing carcass, post-natal growth and reproductive traits in commercial Angus cattle

To gain insight into the number of loci of large effect that underlie variation in cattle, a quantitative trait locus (QTL) scan for 14 economically important traits was performed in two commercial Angus populations using 390 microsatellites, 11 single nucleotide polymorphisms (SNPs) and one duplication loci. The first population comprised 1769 registered Angus bulls born between 1955 and 2003, with Expected Progeny Differences computed by the American Angus Association. The second comprised 38 half-sib families containing 1622 steers with six post-natal growth and carcass phenotypes. Linkage analysis was performed by half-sib least squares regression with gridqtl or Bayesian Markov chain Monte Carlo analysis of complex pedigrees with loki. Of the 673 detected QTL, only 118 have previously been reported, reflecting both the conservative approach to QTL reporting in the literature, and the more liberal approach taken in this study. From 33 to 71% of the genetic variance and 35 to 56% of the phenotypic variance in each trait was explained by the detected QTL. To analyse the effects of 11 SNPs and one duplication locus within candidate genes on each trait, a single marker analysis was performed by fitting an additive allele substitution model in both mapping populations. There were 53 associations detected between the SNP/duplication loci and traits with -log(10) P(nominal) ≥ 4.0, where each association explained 0.92% to 4.4% of the genetic variance and 0.01% to 1.86% of the phenotypic variance. Of these associations, only six SNP/duplication loci were located within 8 cM of a QTL peak for the trait, with two being located at the QTL peak: SST_DG156121:c.362A>G for ribeye muscle area and TG_X05380:c.422C>T for calving ease. Strong associations between several SNP/duplication loci and trait variation were obtained in the absence of any detected linked QTL. However, we reject the causality of several commercialized DNA tests, including an association between TG_X05380:c.422C>T and marbling in Angus cattle.

Biochemical and in vitro biological significance of natural sequence variation in the ovine leptin gene

The hormone leptin is involved in diverse biological processes, including regulation of food intake, body-weight homeostasis and energy balance. Sequence variation in the bovine leptin gene has been found to be associated with variations in carcass fat content and average daily gain, as well as in milk yield, milk somatic cell count and several traits governing reproduction. We sequenced genomic DNA and cDNA samples of individuals from three divergent sheep breeds and revealed synonymous as well as novel non-synonymous allelic variation at the third exon of the ovine leptin gene (oLEP) as compared to the sequence published at Accession No. U84247 (reference sequence). In addition, two alternatively spliced oLEP transcripts were found in the abdominal fat tissue. The biochemical and the in vitro biological significance of the sequence variation in the oLEP was examined by generating recombinant oLEP-protein variants namely: p.Q28del, p.N78S, p.R84Q, p.P99Q, p.V123L and p.R138Q, carrying the corresponding sequence variation. Surface plasmon resonance experiments revealed, in most cases, reduced affinity of the oLEP protein variants examined, to human leptin-binding domain (hLBD), relative to the reference variant, being 0.75, 0.60, 0.60, 0.89, 0.92 and 1.03, respectively. In competitive binding assays between biotinylated oLEP and the recombinant leptin protein variants, p.N78S and p.R84Q variants exhibited the lowest affinity to hLBD (0.18 and 0.41, respectively) as compared to the reference hormone. We then tested the protein variants' ability to induce proliferation in Baf-3 cells stably expressing the long form of the human leptin receptor: significant differences in proliferative activity were only found for p.N78S (1.8-fold higher) and p.R138Q (4.2-fold lower) relative to the reference oLEP variant.

Allied industry approaches to alter intramuscular fat content and composition in beef animals

Biochemical and biophysical research tools are used to define the developmental dynamics of numerous cell lineages from a variety of tissues relevant to meat quality. With respect to the adipose cell lineage, much of our present understanding of adipogenesis and lipid metabolism was initially determined through the use of these methods, even though the in vitro or molecular environments are far removed from the tissues of meat animals. This concise review focuses on recent cellular and molecular biology-related research with adipocytes, and how the research might be extended to the endpoint of altering red meat quality. Moreover, economic and policy impacts of such in animal production regimens is discussed. These issues are important, not only with respect to palatability, but also to offer enhanced health benefits to the consumer by altering content of bioactive components in adipocytes.

Two-stage genome-wide association study identifies integrin beta 5 as having potential role in bull fertility

Background

Fertility is one of the most critical factors controlling biological and financial performance of animal production systems and genetic improvement of lines. The objective of this study was to identify molecular defects in the sperm that are responsible for uncompensable fertility in Holstein bulls. We performed a comprehensive genome wide analysis of single nucleotide polymorphisms (SNP) for bull fertility followed by a second-stage replication in additional bulls for a restricted set of markers.

Results

In the Phase I association study, we genotyped the genomic sperm DNA of 10 low-fertility and 10 high-fertility bulls using Bovine SNP Gene Chips containing approximately 10,000 random SNP markers. In these animals, 8,207 markers were found to be polymorphic, 97 of which were significantly associated with fertility (p < 0.01). In the Phase II study, we tested the four most significant SNP from the Phase I study in 101 low-fertility and 100 high-fertility bulls, with two SNPs (rs29024867 and rs41257187) significantly replicated. Rs29024867 corresponds to a nucleotide change of C → G 2,190 bp 3' of the collagen type I alpha 2 gene on chromosome 4, while the rs41257187 (C → T) is in the coding region of integrin beta 5 gene on chromosome 1. The SNP rs41257187 induces a synonymous (Proline → Proline), suggesting disequilibrium with the true causative locus (i), but we found that the incubation of bull spermatozoa with integrin beta 5 antibodies significantly decreased the ability to fertilize oocytes. Our findings suggest that the bovine sperm integrin beta 5 protein plays a role during fertilization and could serve as a positional or functional marker of bull fertility.

Conclusion

We have identified molecular markers associated with bull fertility and established that at least one of the genes harboring such variation has a role in fertility. The findings are important in understanding mechanisms of uncompensatory infertility in bulls, and in other male mammals. The findings set the stage for more hypothesis-driven research aimed at discovering the role of variation in the genome that affect fertility and that can be used to identify molecular mechanisms of development.

Reproductive biotechniques in buffaloes (Bubalus bubalis): status, prospects and challenges

The swamp buffalo holds tremendous potential in the livestock sector in Asian and Mediterranean countries. Current needs are the faster multiplication of superior genotypes and the conservation of endangered buffalo breeds. Recent advances in assisted reproductive technologies, including in vitro embryo production methodologies, offer enormous opportunities to not only improve productivity, but also to use buffaloes to produce novel products for applications to human health and nutrition. The use of molecular genomics will undoubtedly advance these technologies for their large-scale application and resolve the key problems currently associated with advanced reproductive techniques, such as animal cloning, stem cell technology and transgenesis. Preliminary success in the application of modern reproductive technologies warrants further research at the cellular and molecular levels before their commercial exploitation in buffalo breeding programmes.

Promoter region of the bovine growth hormone receptor gene: single nucleotide polymorphism discovery in cattle and association with performance in Brangus bulls

Expression of the GH receptor (GHR) gene and its binding with GH is essential for growth and fat metabolism. A GT microsatellite exists in the promoter of bovine GHR segregating short (11 bp) and long (16 to 20 bp) allele sequences. To detect SNP and complete an association study of genotype to phenotype, we resequenced a 1,195-bp fragment of DNA including the GT microsatellite and exon 1A. Resequencing was completed in 48 familialy unrelated Holstein, Jersey, Brown Swiss, Simmental, Angus, Brahman, and Brangus cattle. Nine SNP were identified. Phylogeny analyses revealed minor distance (i.e., <5%) in DNA sequence among the 5 Bos taurus breeds; however, sequence from Brahman cattle averaged 27.4 +/- 0.07% divergence from the Bos taurus breeds, whereas divergence of Brangus was intermediate. An association study of genotype to phenotype was completed with data from growing Brangus bulls (n = 553 from 96 sires) and data from 4 of the SNP flanking the GT microsatellite. These SNP were found to be in Hardy-Weinberg equilibrium and in phase based on linkage disequilibrium analyses (r(2) = 0.84 and D'= 0.92). An A/G tag SNP was identified (ss86273136) and was located in exon 1A, which began 88 bp downstream from the GT microsatellite. Minor allele frequency of the tag SNP was greater than 10%, and Mendelian segregation was verified in 3 generation pedigrees. The A allele was derived from Brahman, and the G allele was derived from Angus. This tag SNP genotype was a significant effect in analyses of rib fat data collected with ultrasound when bulls were ~365 d of age. Specifically, bulls of the GG genotype had 6.1% more (P = 0.0204) rib fat than bulls of the AA and AG genotypes, respectively. Tag SNP (ss86273136), located in the promoter of GHR, appears to be associated with a measure of corporal fat in Bos taurus x Bos indicus composite cattle.

Impacts of animal science research on United States sheep production and predictions for the future

One hundred years ago, there were more than 48 million sheep in the United States. In 1910, they were valued at $4/head, with 43% of income coming from the sale of sheep, lambs, and meat and 57% coming from wool. Over the years, fluctuations in this ratio have challenged the breeder and researcher alike. By 2007, sheep numbers had declined to 6.2 million, with the average sheep shearing 3.4 kg of wool (representing <10% of income), 0.2 kg more than in 1909 but 0.5 kg less than fleeces in 1955. Sheep operations have declined by more than 170,000 in the past 40 yr. A cursory examination of this information might lead one to conclude that animal science research has made little impact on sheep production in the United States. On the contrary, lamb crops in the new millennium (range = 109 to 115%) are greater than those recorded in the 1920s (85 to 89%) and dressed lamb weights increased from 18 to 32 kg from 1940 to the present. In the past century, researchers conducted thousands of investigations, with progress reported in new, existing, and crossbreed evaluations, quantitative and molecular genetics, selection, nutrition, fiber, meat, hides, milk, growth, physiology, reproduction, endocrinology, management, behavior, the environment, disease, pharmacology, toxicology, and range, pasture, and forage utilization such that a vast amount of new information was accrued. Our understanding of sheep has benefited also from research conducted on other species, and vice versa. Many factors that have contributed to the decline in the sheep industry are not influenced easily by academic research (e.g., low per capita consumption of lamb meat, predation, reluctance to adopt new technologies, cost and availability of laborers with sheep-related skills, and fewer young people pursuing careers in agriculture). The size of the US sheep industry is expected to remain stable, with possible slow growth in the foreseeable future. To remain profitable, producers will take advantage of new (or previously unused) technologies, the desire of the public for things natural, domestic niche and international fiber markets, and the ability of the sheep to control noxious weeds and thrive in suboptimal ecosystems.