Quantitative trait loci mapping in dairy cattle: review and meta-analysis

Validation of Bos taurus SNPs for Milk Productivity of Sahiwal Breed (Bos indicus), Pakistan

The aim of the present study was the validation of the already reported Bos taurus SNPs in the Sahiwal breed. A total of nine SNPs of the casein gene were studied. Out of nine, seven Bos taurus SNPs of casein protein genes were found to be significantly associated with milk productivity traits. The genomic DNA was extracted from the mammary alveolar endothelial cells of a flock of 80 purebred Sahiwal lactating dams available at Khizrabad Farm near Sargodha. New allele-specific primers were designed from the NCBI annotated sequence database of Bos taurus to obtain 100 nt-long PCR products. Each dam was tested separately for all the SNPs investigated. Animals with genotype GG for the SNPs rs43703010, rs10500451, and 110323127, respectively, exhibited high milk yield. Similarly, animals with genotype AA for the SNPs rs11079521, rs43703016, and rs43703017 showed high milk yield consistently. For the SNP rs43703015, animals with genotype CC showed high milk productivity. These above-mentioned SNPs have previously been reported to significantly up-regulate casein protein contents in Bos taurus. Our results indicated SNPs that significantly affect the milk protein contents may also significantly increase per capita milk yield. These finding suggest that the above-mentioned reported SNPs can also be used as genetic markers of milk productivity in Sahiwal cattle.

Genetic variation in bovine LAP3 and SIRT1 genes associated with fertility traits in dairy cattle

BACKGROUND

The genetic progress of fertility and reproduction traits in dairy cattle has been constrained by the low heritability of these traits. Identifying candidate genes and variants associated with fertility and reproduction could enhance the accuracy of genetic selection and expedite breeding process of dairy cattle with low-heritability traits. While the bovine LAP3 and SIRT1 genes exhibit well-documented associations with milk production traits in dairy cattle, their effect on cow fertility have not yet been explored. Eleven single nucleotide polymorphisms (SNPs), comprising five in the promoter (rs717156555: C > G, rs720373055: T > C, rs516876447: A > G, rs461857269: C > T and rs720349928: G > A), two in 5'UTR (rs722359733: C > T and rs462932574: T > G), two in intron 12 (rs110932626: A > G and rs43702363: C > T), and one in 3'UTR of exon 13 (rs41255599: C > T) in LAP3 and one in SIRT1 (rs718329990:T > C) genes, have previously been reported to be associated with various traits of milk production and clinical mastitis in Sahiwal and Karan Fries dairy cattle. In this study, the analysis primarily aimed to assess the impact of SNPs within LAP3 and SIRT1 genes on fertility traits in Sahiwal and Karan Fries cattle. Association studies were conducted using mixed linear models, involving 125 Sahiwal and 138 Karan Fries animals in each breed. The analysis utilized a designated PCR-RFLP panel.

RESULTS

In the promoter region of the LAP3 gene, all variants demonstrated significant (P < 0.05) associations with AFC, except for rs722359733: C > T. However, specific variants with the LAP3 gene's promoter region, namely rs722359733: C > T, rs110932626: A > G, rs43702363: C > T, and rs41255599: C > T, showed significant associations with CI and DO in Sahiwal and Karan Fries cows, respectively. The SNP rs718329990: T > C in the promoter region of SIRT1 gene exhibited a significant association with CI and DO in Sahiwal cattle. Haplotype-based association analysis revealed significant associations between haplotype combinations and AFC, CI and DO in the studied dairy cattle population. Animals with H2H3 and H2H4 haplotype combination exhibited higher AFC, CI and DO than other combinations.

CONCLUSIONS

These results affirm the involvement of the LAP3 and SIRT1 genes in female fertility traits, indicating that polymorphisms within these genes are linked to the studied traits. Overall, the significant SNPs and haplotypes identified in this study could have the potential to enhance herd profitability and ensure long-term sustainability on dairy farms by enabling the selection of animals with early age first calving and enhance reproductive performance in the dairy cattle breeding program.

Dynamic Profile of the Yak Mammary Transcriptome during the Lactation Cycle

The objective of this study was to assess the transcriptome of the mammary tissue of four yaks during the whole lactation cycle. For this purpose, biopsies of the mammary gland were performed at -30, -15, 1, 15, 30, 60, 120, 180, and 240 days relative to parturition (d). The transcriptome analysis was performed using a commercial bovine microarray platform and the results were analyzed using several bioinformatic tools. The statistical analysis using an overall false discovery rate ≤ 0.05 for the effect of whole lactation and p < 0.05 for each comparison identified >6000 differentially expressed genes (DEGs) throughout lactation, with a large number of DEGs observed at the onset (1 d vs. -15 d) and at the end of lactation (240 d vs. 180 d). Bioinformatics analysis revealed a major role of genes associated with BTA3, BTA4, BTA6, BTA9, BTA14, and BTA28 in lactation. Functional analysis of DEG underlined an overall induction of lipid metabolism, suggesting an increase in triglycerides synthesis, likely regulated by PPAR signaling. The same analysis revealed an induction of amino acid metabolism and secretion of protein, with a concomitant decrease in proteasome, indicating a major role of amino acid handling and reduced protein degradation in the synthesis and secretion of milk proteins. Glycan biosynthesis was induced for both N-glycan and O-glycan, suggesting increased glycan content in the milk. The cell cycle and immune response, especially antigen processing and presentation, were strongly inhibited during lactation, suggesting that morphological changes are minimized during lactation, while the mammary gland prevents immune hyper-response. Transcripts associated with response to radiation and low oxygen were enriched in the down-regulated DEG affected by the stage of lactation. Except for this last finding, the functions affected by the transcriptomic adaptation to lactation in mammary tissue of yak are very similar to those observed in dairy cows.

Genome-wide association study revealed suggestive QTLs for production and reproduction traits in Indian Murrah buffalo

The present study was aimed to identify the genome-wide SNPs associated with production and reproduction traits in 96 Indian Murrah buffalo genotyped based on ddRAD approach using Genome-Wide Association Study (GWAS) along with phenotypes of contemporary animals using mixed linear model for production and reproduction traits. A total of 27,735 SNPs identified using ddRAD approach in 96 Indian Murrah buffaloes were used for GWAS. A total of 28 SNPs were found to be associated with production and reproductive traits. Among these, 14 SNPs were present in the intronic region of AK5, BACH2, DIRC2, ECPAS, MPZL1, MYO16, QRFPR, RASGRF1, SLC9A4, TANC1, and TRIM67 genes and one SNP in long non-coding region of LOC102414911. Out of these 28 SNPs, 9 SNPs were found to have pleiotropic effect over milk production traits and were present in chromosome number BBU 1, 2, 4, 6, 9, 10, 12, 19, and 20. SNPs in the intronic region of AK5, TRIM67 genes were found to be associated with milk production traits. Eleven and five SNPs in the intergenic region were associated with milk production and reproduction traits respectively. The above genomic information may be used for selection of Murrah animals for genetic improvement.

Genetic variation in promoter region of the bovine LAP3 gene associated with estimated breeding values of milk production traits and clinical mastitis in dairy cattle

The purpose of this study was to identify genetic variants in the promoter and 5'UTR regions of bovine leucine amino peptidase three (LAP3) gene and analysed their associations with estimated breeding values (EBVs) of milk production traits and clinical mastitis in Sahiwal and Karan Fries cattle. Eleven SNPs were identified within the region under study of the LAP3 gene, including seven promoter variants (rs717156555: C>G, rs720373055: T>C, rs715189731: A>G, rs516876447: A>G, rs461857269: C>T, rs136548163: C>T, and rs720349928: G>A) and four 5'UTR variants (rs717884982: C>T, rs722359733: C>T, rs481631804: C>T and rs462932574: T>G). Out of them, 10 SNPs variants were found in both Sahiwal and Karan Fries cattle, with one SNP variant (rs481631804: C>T) being unique to Karan Fries cattle. Seven of these identified SNPs were chosen for association analyses. Individual SNP based association analysis revealed that two SNPs (rs720373055: T>C and rs720349928: G>A) were significantly associated with EBVs of lactation milk yield (LMY), 305-day milk yield (305dMY), and one significant association of SNP rs722359733: C>T with lactation length (LL) was observed. Haplotype based association analysis indicated that diplotypes are significantly associated with EBVs of LMY, 305dMY, and LL, individuals with H1H3 (CTACGCT/GCGTACG) being linked to higher lactation performance than other diplotypes. Further logistic regression analysis revealed that, animals with diplotype H1H3 was less susceptible to the incidence of clinical mastitis than other cows, as the odds ratio for the non-incidence of clinical mastitis was found to be low. Altogether, variations in the LAP3 gene promoter could be used as a genetic marker, most notably diplotype H1H3, may greatly benefit the simultaneous improvement of mastitis resistance and milk yield traits in dairy cattle. Moreover, bioinformatics analysis predicted that the SNPs rs720373055: T>C, rs715189731:A>G and rs720349928: G>A is located in the core promoter region and in TFBs, play key role in regulation of studied phenotypes.

Feedomics provides bidirectional omics strategies between genetics and nutrition for improved production in cattle

Increasing the efficiency and sustainability of cattle production is an effective way to produce valuable animal proteins for a growing human population. Genetics and nutrition are the 2 major research topics in selecting cattle with beneficial phenotypes and developing genetic potentials for improved performance. There is an inextricable link between genetics and nutrition, which urgently requires researchers to uncover the underlying molecular mechanisms to optimize cattle production. Feedomics integrates a range of omic techniques to reveal the mechanisms at different molecular levels related to animal production and health, which can provide novel insights into the relationships of genes and nutrition/nutrients. In this review, we summarized the applications of feedomics techniques to reveal the effect of genetic elements on the response to nutrition and investigate how nutrients affect the functional genome of cattle from the perspective of both nutrigenetics and nutrigenomics. We highlighted the roles of rumen microbiome in the interactions between host genes and nutrition. Herein, we discuss the importance of feedomics in cattle nutrition research, with a view to ensure that cattle exhibit the best production traits for human consumption from both genetic and nutritional aspects.

Genome-wide association study reveals the genetic basis of growth trait in yellow catfish with sexual size dimorphism

Sexual size dimorphism has been widely observed in a large number of animals including fish species. Genome-wide association study (GWAS) is a powerful tool to dissect the genetic basis of complex traits, whereas the sex-differences in the genomics of animal complex traits have been ignored in the GWAS analysis. Yellow catfish (Pelteobagrus fulvidraco) is an important aquaculture fish in China with significant sexual size dimorphism. In this study, GWAS was conducted to identify candidate SNPs and genes related to body length (BL) and body weight (BW) in 125 female yellow catfish from a breeding population. In total, one BL-related SNP and three BW-related SNPs were identified to be significantly associated with the traits. Besides, one of these SNPs (Chr15:19195072) was shared in both the BW and BL traits in female yellow catfish, which was further validated in 185 male individuals and located on the exon of stat5b gene. Transgenic yellow catfish and zebrafish that expressed yellow catfish stat5b showed increased growth rate and reduction of sexual size dimorphism. These results not only reveal the genetic basis of growth trait and sexual size dimorphism in fish species, but also provide useful information for the marker-assisted breeding in yellow catfish.

Single nucleotide polymorphisms and metabolic biochemical profile of productive markers characterize three European breeds of dairy cattle

The objective of this study was to investigate polymorphisms of DGAT1, FABP, OLR1 and ATP1A1 genes using PCR-DNA sequencing, and to associate these genetic structures to changes in metabolic biochemical markers and milk composition indicators in a total of 90 dairy cows of the Holstein, Simmental, and Brown Swiss breeds (30 cows each). PCR was carried out for amplification of 411-bp of DGAT1, 525-bp of FABP, 582-bp of OLR1, and 300-bp of ATP1A1 genes. Three breeds’ nucleotide sequence variations in the form of single nucleotide polymorphisms (SNPs) were detailed by DNA sequencing analysis. Chisquare analysis showed that the distribution of all discovered SNPs varied significantly (P < 0.001). Biochemical indices in cow’s serum revealed no significant difference in serum total protein, albumin, and total cholesterol among the three breeds. However, triglyceride showed a significant increase in Simmental compared to either Holsteins or Brown Swiss, while the highest mean value of triiodothyronine (T3) and tetraiodothyronine (T4) was detected in Holstein dairy cows The milk composition indicators analysis revealed that milk protein, sugar, and density were significantly higher in Holsteins than both Simmental and Brown Swiss. Meanwhile, milk fat and total solids revealed a significantly higher increase in Simmental than both brown Swiss and Holstein. As a result, the metabolic biochemical markers profile along with the identified SNPs could be used as a candidate and a reference guide for effective characterization of the Holstein, Simmental, and Brown Swiss breeds, leading to the creation of a marker-assisted selection system for production traits in dairy cattle breeds.

Evaluation of non-synonym mutation in DGAT1 K232A as a marker for milk production traits in Ongole cattle and Murrah buffalo from Southern India

Various candidate genes have been reported to affect milk yield and composition in dairy cattle. A non-synonymous mutation in the DGAT1 gene, i.e., K232A was reported to have a strong association with milk yield and milk composition of Bos taurus. A study has been undertaken on 502 unrelated individuals belonging to indigenous Ongole cattle, crossbred cattle, and Murrah buffaloes from the Indian sub-continent with the objective to determine the polymorphism of the K232A locus and their association with milk yield and composition. Typing DGAT1 K232A allelic variation by PCR-RFLP using CfrI restriction enzyme revealed three genotypes in crossbred cattle. Genotype KK was more prevalent (0.60) in Jersey crossbred, whereas in Holstein Friesian crossbred it was KA genotype (0.48). In Ongole cattle and Murrah buffaloes, the locus did not exhibit polymorphism. The least-square mean of milk yields pooled over lactations across the DGAT1 variants was significantly (P < 0.05) higher among the homozygous (AA) genotypes, both in Jersey crossbred and HF crossbred cattle after adjusting for the effects of farm, parity, and season. The fat, SNF, and protein content values of AA genotypes were less than the KK genotypes in both the genetic groups (P > 0.05). The fixation of the DGAT1^K allele at the locus in Bos indicus cattle and Bubalus bubalis in the present study did not support its use as a reliable universal marker for milk production and composition traits.

Beta-Casein Gene Polymorphism in Serbian Holstein-Friesian Cows and Its Relationship with Milk Production Traits

The most common types of beta-casein in cow’s milk are A1 and A2, which differ in one amino acid. During the gastrointestinal proteolysis of A1 beta-casein in humans this difference results in the release of beta-casomorphin-7, an opioid which may lead to severe effects on human health, causing various ailments (type-1 diabetes mellitus, ischemic heart disease, arteriosclerosis, sudden infant death syndrome, autism, schizophrenia, gastrointestinal digestive discomfort, as well as increased gastrointestinal transit time). By contrast, A2 beta-casein cannot exert these effects owing to its different composition and metabolism. Furthermore, studies have shown that it can influence milk productivity traits. Our research aimed to screen the frequency of A1 and A2 alleles of beta-casein gene in a population of Serbian Holstein-Friesian cows and to detect how the genotypes influence milk production, and milk protein and fat yields. Out of 106 animals, 13 (12.26%) were of A1A1 genotype, 58 (54.72%) of A1A2, and 35 (33.02%) of A2A2 genotype. Milk yield was significantly (P<0.01) higher in A2A2 compared to both A1A1 and A1A2 genotypes. Milk protein concentrations were significantly (P<0.01) higher in A2A2 compared to A1A2 genotype, while milk fat concentrations were significantly (P<0.01) higher in A2A2 compared to both A1A1 and A1A2 genotypes.

Marker-assisted selection vis-à-vis bull fertility: coming full circle-a review

Bull fertility is considered an indispensable trait, as far as farm economics is concerned since it is the successful conception in a cow that provides calf crop, along with the ensuing lactation. This ensures sustainability of a dairy farm. Traditionally, bull fertility did not receive much attention by the farm managers and breeding animals were solely evaluated based on phenotypic predictors, namely, sire conception rate and seminal parameters in bull. With the advent of the molecular era in animal breeding, attempts were made to unravel the genetic complexity of bull fertility by the identification of genetic markers related to the trait. Marker-Assisted Selection (MAS) is a methodology that aims at utilizing the genetic information at markers and selecting improved populations for important traits. Traditionally, MAS was pursued using a candidate gene approach for identifying markers related to genes that are already known to have a physiological function related to the trait but this approach had certain shortcomings like stringent criteria for significance testing. Now, with the availability of genome-wide data, the number of markers identified and variance explained in relation to bull fertility has gone up. So, this presents a unique opportunity to revisit MAS by selection based on the information of a large number of genome-wide markers and thus, improving the accuracy of selection.

Distinguishing pleiotropy from linked QTL between milk production traits and mastitis resistance in Nordic Holstein cattle

BACKGROUND

Production and health traits are central in cattle breeding. Advances in next-generation sequencing technologies and genotype imputation have increased the resolution of gene mapping based on genome-wide association studies (GWAS). Thus, numerous candidate genes that affect milk yield, milk composition, and mastitis resistance in dairy cattle are reported in the literature. Effect-bearing variants often affect multiple traits. Because the detection of overlapping quantitative trait loci (QTL) regions from single-trait GWAS is too inaccurate and subjective, multi-trait analysis is a better approach to detect pleiotropic effects of variants in candidate genes. However, large sample sizes are required to achieve sufficient power. Multi-trait meta-analysis is one approach to deal with this problem. Thus, we performed two multi-trait meta-analyses, one for three milk production traits (milk yield, protein yield and fat yield), and one for milk yield and mastitis resistance.

RESULTS

For highly correlated traits, the power to detect pleiotropy was increased by multi-trait meta-analysis compared with the subjective assessment of overlapping of single-trait QTL confidence intervals. Pleiotropic effects of lead single nucleotide polymorphisms (SNPs) that were detected from the multi-trait meta-analysis were confirmed by bivariate association analysis. The previously reported pleiotropic effects of variants within the DGAT1 and MGST1 genes on three milk production traits, and pleiotropic effects of variants in GHR on milk yield and fat yield were confirmed. Furthermore, our results suggested that variants in KCTD16, KCNK18 and ENSBTAG00000023629 had pleiotropic effects on milk production traits. For milk yield and mastitis resistance, we identified possible pleiotropic effects of variants in two genes, GC and DGAT1.

CONCLUSIONS

Multi-trait meta-analysis improves our ability to detect pleiotropic interactions between milk production traits and identifies variants with pleiotropic effects on milk production traits and mastitis resistance. In particular, this should contribute to better understand the biological mechanisms that underlie the unfavorable genetic correlation between milk yield and mastitis.

Effects of FABP4 variation on milk fatty-acid composition for dairy cattle grazed on pasture in late lactation

This research communication describes associations between variation in the fatty acid binding protein 4 gene (FABP4) and milk fat composition in New Zealand Holstein-Friesian × Jersey cross dairy cows. After correcting for the effect of the amino acid substitution p.K232A in diacylglycerol O-acyltransferase 1 (DGAT1), which is associated with variation in many milk fatty acid (FA) component levels, the effect of FABP4 c.328A/G on milk FA levels was typically small. For the five genotypes analysed, the AB cows produced more medium-chain fatty acids than CC cows (P < 0.05), and more C14:0 FA than AA and AC cows (P < 0.05). The AA and AC cows produced less C22:0 FA (P < 0.01) than the BC cows, and the AC cows produced more C24:0 FA (P < 0.05) than was produced by the BC cows. Cows of genotype CC produce more long-chain fatty acids than cows of genotype BC (P < 0.05).

Bioactive peptides from milk: animal determinants and their implications in human health

Milk is an important protein source in human diets, providing around 32 g protein/l (for bovine milk, which constitutes some 85% of global consumption). The most abundant milk proteins are α-lactalbumin, β-lactoglobulin, αs-casein, β-casein, and κ-casein. Besides their nutritional value, milk proteins play a crucial role in the processing properties of milk, such as solubility, water bonding, heat stability, renneting and foaming, among others. In addition, and most importantly for this review, these proteins are the main source of bioactive components in milk. Due to the wide range of proposed beneficial effects on human health, milk proteins are considered as potential ingredients for the production of health-promoting functional foods. However, most of the evidence for bioactive effects comes from in vitro studies, and there is a need for further research to fully evaluate the true potential of milk-derived bioactive factors. Animal genetics and animal nutrition play an important role in the relative proportions of milk proteins and could be used to manipulate the concentration of specific bioactive peptides in milk from ruminants. Unfortunately, only a few studies in the literature have focused on changes in milk bioactive peptides associated to animal genetics and animal nutrition. The knowledge described in the present review may set the basis for further research and for the development of new dairy products with healthy and beneficial properties for humans.

Overlap between eQTL and QTL associated with production traits and fertility in dairy cattle

Background

Identifying causative mutations or genes through which quantitative trait loci (QTL) act has proven very difficult. Using information such as gene expression may help to identify genes and mutations underlying QTL. Our objective was to identify regions associated both with production traits or fertility and with gene expression, in dairy cattle. We used three different approaches to discover QTL that are also expression QTL (eQTL): 1) estimate the correlation between local genomic estimated breeding values (GEBV) and gene expression, 2) investigate whether the 300 intervals explaining most genetic variance for a trait contain more eQTL than 300 randomly selected intervals, and 3) a colocalisation analysis. Phenotypes and genotypes up to sequence level of 35,775 dairy bulls and cows were used for QTL mapping, and gene expression and genotypes of 131 cows were used to identify eQTL.

Results

With all three approaches, we identified some overlap between eQTL and QTL, though the majority of QTL in our dataset did not seem to be eQTL. The most significant associations between QTL and eQTL were found for intervals on chromosome 18, where local GEBV for all traits showed a strong association with the expression of the FUK and DDX19B. Intervals whose local GEBV for a trait correlated highly significantly with the expression of a nearby gene explained only a very small part of the genetic variance for that trait. It is likely that part of these correlations were due to linkage disequilibrium (LD) in the interval. While the 300 intervals explaining most genetic variance explained most of the GEBV variance, they contained only slightly more eQTL than 300 randomly selected intervals that explained a minimal portion of the GEBV variance. Furthermore, some variants showed a high colocalisation probability, but this was only the case for few variants.

Conclusions

Several reasons may have contributed to the low level of overlap between QTL and eQTL detected in our study, including a lack of power in the eQTL study and long-range LD making it difficult to separate QTL and eQTL. Furthermore, it may be that eQTL explain only a small fraction of QTL.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5656-7) contains supplementary material, which is available to authorized users.

Genomic Analysis To Identify Signatures of Artificial Selection and Loci Associated with Important Economic Traits in Duroc Pigs

Identifying genetic basis of domestication and improvement in livestock contributes to our understanding of the role of artificial selection in shaping the genome. Here we used whole-genome sequencing and the genotyping by sequencing approach to detect artificial selection signatures and identify the associated SNPs of two economic traits in Duroc pigs. A total of 38 candidate selection regions were detected by combining the fixation index and the Composite Likelihood Ratio methods. Further genome-wide association study revealed seven associated SNPs that were related with intramuscular fat content and feed conversion ratio traits, respectively. Enrichment analysis suggested that the artificial selection regions harbored genes, such as MSTN, SOD2, MC5R and CD83, which are responsible for economic traits including lean muscle mass, fertility and immunization. Overall, this study found a series of candidate genes putatively associated with the breeding improvement of Duroc pigs and the polygenic basis of adaptive evolution, which can provide important references and fundamental information for future breeding programs.

Osteopontin gene polymorphism association with milk traits and its expression analysis in milk of riverine buffalo

Osteopontin gene is regarded as a plausible candidate in mammary gland differentiation and development, expressed by variety of cells, tissues, and biological fluids including milk. The current study was performed in two phases. In the first phase, Osteopontin gene polymorphisms were identified and associated with milk composition such as ash, milk fat, SNF, lactose, and protein. In the second phase, milk samples from five healthy mastitis-free Nili Ravi buffaloes were analyzed for expression of Osteopontin gene at transition (day 15), mid (day 90), and end (day 250) stage of their second lactation. Briefly, blood samples were collected from Nili Ravi buffalo to isolate the genomic DNA, specific primers were designed for PCR amplification. The amplified PCR products were sequenced bi-directionally. Six polymorphisms were identified in the coding region and four in the intronic region of the gene. The results showed that SNP g.38329758 T > C causing substitution of valine to alanine (V127A) was associated with high milk protein. For mRNA expression analysis, somatic cells were separated from milk samples for RNA isolation. Analysis of differential gene expression data has permitted us to illustrate the expression pattern of osteopontin gene in lactating buffalo. The Osteopontin gene was found to be transcribed among all three lactation stages, but expression was observed with the highest value (fold change) in peak lactation and remained elevated till the end of lactation. Identified gene marker may be helpful for the prediction of superior animal for selection. The presented study also gave an insight into the genetic screening and lactation biology of riverine buffalo, offering direction for future research in lactating buffalo.

Invited review: A perspective on the future of genomic selection in dairy cattle

Genomic evaluation has been successfully implemented in the United States, Canada, Great Britain, Ireland, New Zealand, Australia, France, the Netherlands, Germany, and the Scandinavian countries. Adoption of this technology in the major dairy producing countries has led to significant changes in the worldwide dairy industry. Gradual elimination of the progeny test system has led to a reduction in the number of sires with daughter records and fewer genetic ties between years. As genotyping costs decrease, the number of cows genotyped will continue to increase, and these records will become the basic data used to compute genomic evaluations, most likely via application of "single-step" methodologies. Although genomic selection has been successful in increasing rates of genetic gain, we still know very little about the genetic architecture of quantitative variation. Apparently, a very large number of genes affect nearly all economic traits, in accordance with the infinitesimal model for quantitative traits. Less emphasis in selection goals will be placed on milk production traits, and more on health, reproduction, and efficiency traits and on environmentally friendly production with reduced waste and gas emission. Genetic variance for economic traits is maintained by the increase in frequency of rare alleles, new mutations, and changes in selection goals and management. Thus, it is unlikely that a selection plateau will be reached in the near future.

Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

A comprehensive linkage atlas for seed yield in rapeseed. Most agronomic traits of interest for crop improvement (including seed yield) are highly complex quantitative traits controlled by numerous genetic loci, which brings challenges for comprehensively capturing associated markers/genes. We propose that multiple trait interactions underlie complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual quantitative trait loci (QTL) effects more effectively and improve yield predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed a large set of trait data generated in 19 independent experiments to investigate correlations between seed yield and other complex traits, and further identified QTL in this population with a SNP-based genetic bin map. A total of 1904 consensus QTL accounting for 22 traits, including 80 QTL directly affecting seed yield, were anchored to the B. napus reference sequence. Through trait association analysis and QTL meta-analysis, we identified a total of 525 indivisible QTL that either directly or indirectly contributed to seed yield, of which 295 QTL were detected across multiple environments. A majority (81.5%) of the 525 QTL were pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting genetic effects, as well as 31 QTL with minor complementary effects. Implementation of the 525 QTL in genomic prediction models improved seed yield prediction accuracy. Dissecting the genetic and phenotypic interrelationships underlying complex quantitative traits using this method will provide valuable insights for genomics-based crop improvement.

Breeding animals for quality products: not only genetics

The effect of the Developmental Origins of Health and Disease on the spread of non-communicable diseases is recognised by world agencies such as the United Nations and the World Health Organization. Early environmental effects on offspring phenotype also apply to domestic animals and their production traits. Herein, we show that maternal nutrition not only throughout pregnancy, but also in the periconception period can affect offspring phenotype through modifications of gametes, embryos and placental function. Because epigenetic mechanisms are key processes in mediating these effects, we propose that the study of epigenetic marks in gametes may provide additional information for domestic animal selection.

Combined Genomic and Genetic Data Integration of Major Agronomical Traits in Bread Wheat (Triticum aestivum L.)

The high resolution integration of bread wheat genetic and genomic resources accumulated during the last decades offers the opportunity to unveil candidate genes driving major agronomical traits to an unprecedented scale. We combined 27 public quantitative genetic studies and four genetic maps to deliver an exhaustive consensus map consisting of 140,315 molecular markers hosting 221, 73, and 82 Quantitative Trait Loci (QTL) for respectively yield, baking quality, and grain protein content (GPC) related traits. Projection of the consensus genetic map and associated QTLs onto the wheat syntenome made of 99,386 genes ordered on the 21 chromosomes delivered a complete and non-redundant repertoire of 18, 8, 6 metaQTLs for respectively yield, baking quality and GPC, altogether associated to 15,772 genes (delivering 28,630 SNP-based makers) including 37 major candidates. Overall, this study illustrates a translational research approach in transferring information gained from grass relatives to dissect the genomic regions hosting major loci governing key agronomical traits in bread wheat, their flanking markers and associated candidate genes to be now considered as a key resource for breeding programs.

Sequence variants selected from a multi-breed GWAS can improve the reliability of genomic predictions in dairy cattle

Background

Sequence data can potentially increase the reliability of genomic predictions, because such data include causative mutations instead of relying on linkage disequilibrium (LD) between causative mutations and prediction variants. However, the location of the causative mutations is not known, and the presence of many variants that are in low LD with the causative mutations may reduce prediction reliability. Our objective was to investigate whether the use of variants at quantitative trait loci (QTL) that are identified in a multi-breed genome-wide association study (GWAS) for milk, fat and protein yield would increase the reliability of within- and multi-breed genomic predictions in Holstein, Jersey and Danish Red cattle. A wide range of scenarios that test different strategies to select prediction markers, for both within-breed and multi-breed prediction, were compared.

Results

For all breeds and traits, the use of variants selected from a multi-breed GWAS resulted in substantial increases in prediction reliabilities compared to within-breed prediction using a 50 K SNP array. Reliabilities depended highly on the choice of the prediction markers, and the scenario that led to the highest reliability varied between breeds and traits. While genomic correlations across breeds were low for genome-wide sequence variants, the effects of the QTL variants that yielded the highest reliabilities were highly correlated across breeds.

Conclusions

Our results show that the use of sequence variants, which are located near peaks of QTL that are detected in a multi-breed GWAS, can increase reliability of genomic predictions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-016-0259-0) contains supplementary material, which is available to authorized users.

Using Sequence Variants in Linkage Disequilibrium with Causative Mutations to Improve Across-Breed Prediction in Dairy Cattle: A Simulation Study

Sequence data are expected to increase the reliability of genomic prediction by containing causative mutations directly, especially in cases where low linkage disequilibrium between markers and causative mutations limits prediction reliability, such as across-breed prediction in dairy cattle. In practice, the causative mutations are unknown, and prediction with only variants in perfect linkage disequilibrium with the causative mutations is not realistic, leading to a reduced reliability compared to knowing the causative variants. Our objective was to use sequence data to investigate the potential benefits of sequence data for the prediction of genomic relationships, and consequently reliability of genomic breeding values. We used sequence data from five dairy cattle breeds, and a larger number of imputed sequences for two of the five breeds. We focused on the influence of linkage disequilibrium between markers and causative mutations, and assumed that a fraction of the causative mutations was shared across breeds and had the same effect across breeds. By comparing the loss in reliability of different scenarios, varying the distance between markers and causative mutations, using either all genome wide markers from commercial SNP chips, or only the markers closest to the causative mutations, we demonstrate the importance of using only variants very close to the causative mutations, especially for across-breed prediction. Rare variants improved prediction only if they were very close to rare causative mutations, and all causative mutations were rare. Our results show that sequence data can potentially improve genomic prediction, but careful selection of markers is essential.

Genome-wide association study for endocrine fertility traits using single nucleotide polymorphism arrays and sequence variants in dairy cattle

Endocrine fertility traits, which are defined from progesterone concentration levels in milk, are interesting indicators of dairy cow fertility because they more directly reflect the cows own reproductive physiology than classical fertility traits, which are more biased by farm management decisions. The aim of this study was to detect quantitative trait loci (QTL) for 7 endocrine fertility traits in dairy cows by performing a genome-wide association study with 85k single nucleotide polymorphisms (SNP), and then fine-map targeted QTL regions, using imputed sequence variants. Two classical fertility traits were also analyzed for QTL with 85k SNP. The association between a SNP and a phenotype was assessed by single-locus regression for each SNP, using a linear mixed model that included a random polygenic effect. A total of 2,447 Holstein Friesian cows with 5,339 lactations with both phenotypes and genotypes were used for association analysis. Heritability estimates ranged from 0.09 to 0.15 for endocrine fertility traits and 0.03 to 0.10 for classical fertility traits. The genome-wide association study identified 17 QTL regions for endocrine fertility traits on Bos taurus autosomes (BTA) 2, 3, 8, 12, 15, 17, 23, and 25. The highest number (5) of QTL regions from the genome-wide association study was identified for the endocrine trait "proportion of samples with luteal activity." Overlapping QTL regions were found between endocrine traits on BTA 2, 3, and 17. For the classical trait calving to first service, 3 QTL regions were identified on BTA 3, 15, and 23, and an overlapping region was identified on BTA 23 with endocrine traits. Fine-mapping target regions for the endocrine traits on BTA 2 and 3 using imputed sequence variants confirmed the QTL from the genome-wide association study, and identified several associated variants that can contribute to an index of markers for genetic improvement of fertility. Several potential candidate genes underlying endocrine fertility traits were also identified in the target regions and are discussed. However, due to high linkage disequilibrium, it was not possible to specify genes or polymorphisms as causal factors for any of the regions.

A Meta-Assembly of Selection Signatures in Cattle

Since domestication, significant genetic improvement has been achieved for many traits of commercial importance in cattle, including adaptation, appearance and production. In response to such intense selection pressures, the bovine genome has undergone changes at the underlying regions of functional genetic variants, which are termed “selection signatures”. This article reviews 64 recent (2009–2015) investigations testing genomic diversity for departure from neutrality in worldwide cattle populations. In particular, we constructed a meta-assembly of 16,158 selection signatures for individual breeds and their archetype groups (European, African, Zebu and composite) from 56 genome-wide scans representing 70,743 animals of 90 pure and crossbred cattle breeds. Meta-selection-scores (MSS) were computed by combining published results at every given locus, within a sliding window span. MSS were adjusted for common samples across studies and were weighted for significance thresholds across and within studies. Published selection signatures show extensive coverage across the bovine genome, however, the meta-assembly provides a consensus profile of 263 genomic regions of which 141 were unique (113 were breed-specific) and 122 were shared across cattle archetypes. The most prominent peaks of MSS represent regions under selection across multiple populations and harboured genes of known major effects (coat color, polledness and muscle hypertrophy) and genes known to influence polygenic traits (stature, adaptation, feed efficiency, immunity, behaviour, reproduction, beef and dairy production). As the first meta-assembly of selection signatures, it offers novel insights about the hotspots of selective sweeps in the bovine genome, and this method could equally be applied to other species.

Association study of single nucleotide polymorphisms in JAK2 and STAT5B genes and their differential mRNA expression with mastitis susceptibility in Chinese Holstein cattle

The JAK-STAT pathway plays a key role in mediating immune responses. The genetic effects of single nucleotide polymorphisms (SNPs) in JAK2 and STAT5B were investigated for serum cytokines, mastitis indicators and productions traits in a population of 468 Chinese Holstein cattle. Pooled DNA sequencing revealed one SNP (BTA8:g.39645396A>G) in JAK2 and two SNPs (BTA19:g.43673888A>G and BTA19:g.43660093T>C) in STAT5B. A fixed effect model considering the effects of SNPs, parity, herd, season and year of calving was used by way of the general linear model procedure of sas. Genotype frequencies of these SNPs in the population were in Hardy-Weinberg equilibrium (P > 0.05). A novel SNP (g.39645396A>G) in JAK2 was predicted to change the amino acid from lysine to asparagine and was significantly associated with the somatic cell count (SCC) and somatic cell score (SCS), whereas g.43673888A>G in STAT5B was significantly associated with SCC, SCS and interleukin-4 (IL-4) (P < 0.05). The dominant effect of g.39645396A>G in JAK2 was significant for SCS, and its additive effect was significant for SCC, whereas the dominant effect of g.43673888A>G in STAT5B was significant for SCS and IL-4 (P < 0.05). The combination of g.39645396A>G in JAK2 and g.43673888A>G in STAT5B showed a significant effect on SCC, SCS, IL-4 and TNF-α (P < 0.05). As for mRNA expression analysis, the AA genotype g.39645396A>G and GG genotype g.43673888A>G indicated higher mRNA expression level and were significantly different from other genotypes (P < 0.05). The results imply that JAK2 and STAT5B genes could be useful candidate genes, and the identified polymorphisms might potentially be strong genetic markers for selection of dairy cattle against mastitis development.

African Indigenous Cattle: Unique Genetic Resources in a Rapidly Changing World

At least 150 indigenous African cattle breeds have been named, but the majority of African cattle populations remain largely uncharacterized. As cattle breeds and populations in Africa adapted to various local environmental conditions, they acquired unique features. We know now that the history of African cattle was particularly complex and while several of its episodes remain debated, there is no doubt that African cattle population evolved dramatically over time. Today, we find a mosaic of genetically diverse population from the purest Bos taurus to the nearly pure Bos indicus. African cattle are now found all across the continent, with the exception of the Sahara and the river Congo basin. They are found on the rift valley highlands as well as below sea level in the Afar depression. These unique livestock genetic resources are in danger to disappear rapidly following uncontrolled crossbreeding and breed replacements with exotic breeds. Breeding improvement programs of African indigenous livestock remain too few while paradoxically the demand of livestock products is continually increasing. Many African indigenous breeds are endangered now, and their unique adaptive traits may be lost forever. This paper reviews the unique known characteristics of indigenous African cattle populations while describing the opportunities, the necessity and urgency to understand and utilize these resources to respond to the needs of the people of the continent and to the benefit of African farmers.

Variation in the bovine FABP4 gene affects milk yield and milk protein content in dairy cows

Fatty acid binding proteins (FABPs) bind long-chain fatty acids and are involved in their intracellular transport. Of the known bovine FABP genes, FABP4 has been mapped to a region on chromosome 14 that contains quantitative trait loci for milk traits. This study investigated the association of FABP4 haplotypes with milk production traits in 719 Holstein-Friesian × Jersey cows. Polymerase chain reaction-single strand conformational polymorphism (PCR-SSCP) analysis of a variable region of the gene revealed three haplotypes (A, B and C). Five single nucleotide polymorphisms (SNPs) were identified: two in exon 3 and three in intron 3. A was associated (P = 0.032) with increased milk protein percentage (present: 4.00 ± 0.02%; absent: 3.95 ± 0.02%) and B was associated (P = 0.009) with increased milk yield (present: 23.81 ± 0.23 kg/d; absent: 23.06 ± 0.21 kg/d), but tended to be associated with a decrease in protein percentage and an increase in protein yield. Cows with genotypes AA, AB and AC produced less milk, but with a higher protein percentage than BC cows. This suggest that FABP4 affects milk yield and milk protein content, both economically important traits, and that further study of this gene is warranted.

The genetic architecture of growth and fillet traits in farmed Atlantic salmon (Salmo salar)

BACKGROUND

Performance and quality traits such as harvest weight, fillet weight and flesh color are of economic importance to the Atlantic salmon aquaculture industry. The genetic factors underlying these traits are of scientific and commercial interest. However, such traits are typically polygenic in nature, with the number and size of QTL likely to vary between studies and populations. The aim of this study was to investigate the genetic basis of several growth and fillet traits measured at harvest in a large farmed salmon population by using SNP markers. Due to the marked heterochiasmy in salmonids, an efficient two-stage mapping approach was applied whereby QTL were detected using a sire-based linkage analysis, a sparse SNP marker map and exploiting low rates of recombination, while a subsequent dam-based analysis focused on the significant chromosomes with a denser map to confirm QTL and estimate their position.

RESULTS

The harvest traits all showed significant heritability, ranging from 0.05 for fillet yield up to 0.53 for the weight traits. In the sire-based analysis, 1695 offspring with trait records and their 20 sires were successfully genotyped for the SNPs on the sparse map. Chromosomes 13, 18, 19 and 20 were shown to harbor genome-wide significant QTL affecting several growth-related traits. The QTL on chr. 13, 18 and 20 were detected in the dam-based analysis using 512 offspring from 10 dams and explained approximately 6-7 % of the within-family variation in these traits.

CONCLUSIONS

We have detected several QTL affecting economically important complex traits in a commercial salmon population. Overall, the results suggest that the traits are relatively polygenic and that QTL tend to be pleiotropic (affecting the weight of several components of the harvested fish). Comparison of QTL regions across studies suggests that harvest trait QTL tend to be relatively population-specific. Therefore, the application of marker or genomic selection for improvement in these traits is likely to be most effective when the discovery population is closely related to the selection candidates (e.g. within-family genomic selection).

Association of novel SNPs in the candidate genes affecting caprine milk fatty acids related to human health

In the present investigation, 618 milk samples of Sirohi breed of goat were collected, and analyzed for conjugated linoleic acid (CLA, C18:2) and other fatty acids. The CLA in studied goat milk samples was 4.87 mg/g of milk fat and C18:2 cis-9, trans-11 contributes 2.9 mg/g of milk fat and trans10 cis12 contributes 0.82 mg/g of milk fat. The saturated fatty acids in the milk accounted for 69.55% and unsaturated fatty acid accounted for 28.50%. The unsaturated fatty acid was constituted by monounsaturated fatty acid (24.57%) and polyunsaturated fatty acids (3.96%.). The major contribution (45.56%) in total fatty acid was of C12:0, C14:0 and C16:0. C18:0 and short chain ones (C4:0, C6:0, C8:0, and C10:0) have a neutral or cholesterol-decreasing effect. The DNA sequence analysis of the genes (DGAT1, SCAP, PPARG, OLR, FABP3 and PRL) in a random panel of 8 Sirohi goats revealed 38 SNPs across the targeted regions. Out of the studied SNPs (38) across these genes, 22 SNPs had significant effect on one or a group of fatty acids including CLA. The genotypes at these loci showed significant differences in the least square means of a particular fatty acid or a group of fatty acids including CLA and its isomers.

The Association of Bovine Osteopontin (OPN) Gene with Milk Production Traits in Iranian Holstein Bulls

BACKGROUND

The Osteopontin (OPN) is a highly phosphorylated glycoprotein in numbers of bovine tissues and milk. OPN has been reported to be associated with milk production in cattle.

OBJECTIVE

The genotype and allelic frequencies for OPN and its association with milk production will be evaluated in Iranian Holstein Bulls.

MATERIALS AND METHODS

Bulls DNA (100) was isolated. Oligo was used for primer design. Polymerase Chain Reaction was implemented to amplify a 826 bp fragment and the amplicon was digested by BsrI. Restricted Maximum likelihood (REML) method based on average information algorithm using ASRMEL programs (version 3.1) was employed to estimate the genetic parameters and variance of components. The association of OPN genotypes with milk production traits were analysed by the least square method as applied in the general linear model (GLM) procedure of SAS. Allele substitution effects were performed by regression analyses.

RESULTS

Allele frequencies of T and C were 0.59±0.03 and 0.41±0.03, respectively. Genotype frequencies of TT, CT and CC were 34.69, 48.62, and 16.69, respectively. The chi-square test showed the deviation from Hardy-Weinberg equilibrium. Estimated heritability for milk yield, fat yield and its percent, protein yield and its percent were 0.28±0.0061, 0.21±0.0064, 0.22±0.0086, 0.32±0.0065 and 0.34±0.0096 respectively. Allelic substitution effects and differences between genotypes were not significant for milk production traits.

CONCLUSIONS

This study suggested that the C allele frequency of OPN was noticeable in Iranian proven bull Holstein population, but was not associated with milk production traits. However, before being practical for the breeding improvement of Iranian Holsteins a larger sample size is required.

Linkage disequilibrium in crossbred and pure line chickens

BACKGROUND

Both genome-wide association (GWA) studies and genomic selection depend on the level of non-random association of alleles at different loci, i.e. linkage disequilibrium (LD), across the genome. Therefore, characterizing LD is of fundamental importance to implement both approaches. In this study, using a 60K single nucleotide polymorphism (SNP) panel, we estimated LD and haplotype structure in crossbred broiler chickens and their component pure lines (one male and two female lines) and calculated the consistency of LD between these populations.

RESULTS

The average level of LD (measured by r(2)) between adjacent SNPs across the chicken autosomes studied here ranged from 0.34 to 0.40 in the pure lines but was only 0.24 in the crossbred populations, with 28.4% of adjacent SNP pairs having an r(2) higher than 0.3. Compared with the pure lines, the crossbred populations consistently showed a lower level of LD, smaller haploblock sizes and lower haplotype homozygosity on macro-, intermediate and micro-chromosomes. Furthermore, correlations of LD between markers at short distances (0 to 10 kb) were high between crossbred and pure lines (0.83 to 0.94).

CONCLUSIONS

Our results suggest that using crossbred populations instead of pure lines can be advantageous for high-resolution QTL (quantitative trait loci) mapping in GWA studies and to achieve good persistence of accuracy of genomic breeding values over generations in genomic selection. These results also provide useful information for the design and implementation of GWA studies and genomic selection using crossbred populations.

Single nucleotide polymorphism of FGF2 gene in Iranian Holstein proven bulls

Fibroblast growth factor 2 (FGF2) serves in the uterine endometrium during estrous presenting in the bovine mammary gland which is responsible to express interferon-T (IFNT), and is an important agent to encourage the continuation of pregnancy in the ruminants. Significant associations have been found between genes affected by IFNT and genes that are responsible for milk production traits. Semen samples from 101Iranian Holstein proven bulls were collected to extract the genomic DNA. Forward and reverse primers were designed and a 710-base-pair fragment in intron 1 was amplified using PCR technique. To detect single nucleotide polymorphism (SNP), all samples were sequenced. Three positions including 11474 (C/G), 11513 (C/G) and 11646 (A/G) were considered. The 11474C, 11513C and 11646A alleles are known as wild type alleles. In this study all animals were distinguished as the11474C, 11513C and 11646A alleles. Furthermore, amplified fragments were under consideration to detect new SNPs. Only one new SNP in one sample was observed at position 11863 resulting substitution of thymine to cytosine. This new mutation has been registered on the NCBI database with accession number HM597774.

Recent developments in cattle, pig, sheep and horse breeding - a review

The aim of this review was to summarize new genetic approaches and techniques in the breeding of cattle, pigs, sheep and horses. Often production and reproductive traits are treated separately in genetic evaluations, but advantages may accrue to their joint evaluation. A good example is the system in pig breeding. Simplified breeding objectives are generally no longer appropriate and consequently becoming increasingly complex. The goal of selection for improved animal performance is to increase the profit of the production system; therefore, economic selection indices are now used in most livestock breeding programmes. Recent developments in dairy cattle breeding have focused on the incorporation of molecular information into genetic evaluations and on increasing the importance of longevity and health in breeding objectives to maximize the change in profit. For a genetic evaluation of meat yield (beef, pig, sheep), several types of information can be used, including data from performance test stations, records from progeny tests and measurements taken at slaughter. The standard genetic evaluation method of evaluation of growth or milk production has been the multi-trait animal model, but a test-day model with random regression is becoming the new standard, in sheep as well. Reviews of molecular genetics and pedigree analyses for performance traits in horses are described. Genome – wide selection is becoming a world standard for dairy cattle, and for other farm animals it is under development.

Genomic signatures reveal new evidences for selection of important traits in domestic cattle

We investigated diverse genomic selections using high-density single nucleotide polymorphism data of five distinct cattle breeds. Based on allele frequency differences, we detected hundreds of candidate regions under positive selection across Holstein, Angus, Charolais, Brahman, and N'Dama. In addition to well-known genes such as KIT, MC1R, ASIP, GHR, LCORL, NCAPG, WIF1, and ABCA12, we found evidence for a variety of novel and less-known genes under selection in cattle, such as LAP3, SAR1B, LRIG3, FGF5, and NUDCD3. Selective sweeps near LAP3 were then validated by next-generation sequencing. Genome-wide association analysis involving 26,362 Holsteins confirmed that LAP3 and SAR1B were related to milk production traits, suggesting that our candidate regions were likely functional. In addition, haplotype network analyses further revealed distinct selective pressures and evolution patterns across these five cattle breeds. Our results provided a glimpse into diverse genomic selection during cattle domestication, breed formation, and recent genetic improvement. These findings will facilitate genome-assisted breeding to improve animal production and health.

Genetic variances of SNP loci for milk yield in dairy cattle

Regression coefficients and genetic variances for 40,890 single nucleotide polymorphisms (SNPs) for milk yield were calculated using mixed model equations, with deregressed proof (DRP) as the dependent variable. Bulls were genotyped using the Illumina BovineSNP50 v2 BeadChip and SNPs were edited according the minor allele frequency (MAF) and high incidence of missing genotype. Evaluation was conducted in two rounds. In the preliminary round, the direct genetic values (DGVs) of all genotyped bulls (2,904) were computed and the absolute difference between the DGV and the input DRP of each bull was investigated. Bulls with an absolute difference greater than the mean absolute difference plus two standard deviations were eliminated from the data set prior to the final analysis (2,766 bulls remaining). SNP regression coefficients from the final analysis had a mean absolute value of 0.506 kg and a standard deviation of 0.409 kg. The SNP with the highest regression coefficient and genetic variance was ARSBFGLNGS4939 on chromosome 14. This SNP is located within the gene DGAT1 (diacylglycerol O-acyltransferase 1). Other SNPs with high regression coefficients and genetic variance are localised in proximity to DGAT1. The mean genetic variance of an individual SNP was 0.170, with a standard deviation of 0.384 and a mean heterozygosity of 0.372. The sum of genetic variances of all SNPs was only 6,968.8, probably because of the existence of genetic covariances between loci. The largest sum of genetic variances was on chromosome 14 (498.4, 7.15 % of the total). After the final analysis, the correlation between the DGV and the input DRP was 0.951 for all bulls. The variance of the predicted DGV was 98.11 % of the variance of the input estimated breeding value (EBV) and 63.65 % of the variance of the DRP.

Identification of selection signatures in livestock species

The identification of regions that have undergone selection is one of the principal goals of theoretical and applied evolutionary genetics. Such studies can also provide information about the evolutionary processes involved in shaping genomes, as well as physical and functional information about genes/genomic regions. Domestication followed by breed formation and selection schemes has allowed the formation of very diverse livestock breeds adapted to a wide variety of environments and with special characteristics. The advances in genomics in the last five years have enabled the development of several methods to detect selection signatures and have resulted in the publication of a considerable number of studies involving livestock species. The aims of this review are to describe the principal effects of natural/artificial selection on livestock genomes, to present the main methods used to detect selection signatures and to discuss some recent results in this area. This review should be useful also to research scientists working with wild animals/non-domesticated species and plant biologists working with breeding and evolutionary biology.

A joint analysis to identify loci underlying variation in nematode resistance in three European sheep populations

Gastrointestinal nematode infections are one of the main health/economic issues in sheep industries, worldwide. Indicator traits for resistance such as faecal egg count (FEC) are commonly used in genomic studies; however, published results are inconsistent among breeds. Meta (or joint)-analysis is a tool for aggregating information from multiple independent studies. The aim of this study was to identify loci underlying variation in FEC, as an indicator of nematode resistance, in a joint analysis using data from three populations (Scottish Blackface, Sarda × Lacaune and Martinik Black-Belly × Romane), genotyped with the ovine 50k SNP chip. The trait analysed was the average animal effect for Strongyles and Nematodirus FEC data. Analyses were performed with regional heritability mapping (RHM), fitting polygenic effects with either the whole genomic relationship matrix or matrices excluding the chromosome being interrogated. Across-population genomic covariances were set to zero. After quality control, 4123 animals and 38 991 SNPs were available for the analysis. RHM identified genome-wide significant regions on OAR4, 12, 14, 19 and 20, with the latter being the most significant. The OAR20 region is close to the major histocompatibility complex, which has often been proposed as a functional candidate for nematode resistance. This region was significant only in the Sarda × Lacaune population. Several other regions, on OAR1, 3, 4, 5, 7, 12, 19, 20 and 24, were significant at the suggestive level.

Fine mapping of a quantitative trait locus for bovine milk fat composition on Bos taurus autosome 19

A major quantitative trait locus (QTL) for milk fat content and fatty acids in both milk and adipose tissue has been detected on Bos taurus autosome 19 (BTA19) in several cattle breeds. The objective of this study was to refine the location of the QTL on BTA19 for bovine milk fat composition using a denser set of markers. Opportunities for fine mapping were provided by imputation from 50,000 genotyped single nucleotide polymorphisms (SNP) toward a high-density SNP panel with up to 777,000 SNP. The QTL region was narrowed down to a linkage disequilibrium block formed by 22 SNP covering 85,007 bp, from 51,303,322 to 51,388,329 bp on BTA19. This linkage disequilibrium block contained 2 genes: coiled-coil domain containing 57 (CCDC57) and fatty acid synthase (FASN). The gene CCDC57 is minimally characterized and has not been associated with bovine milk fat previously, but is expressed in the mammary gland. The gene FASN has been associated with bovine milk fat and fat in adipose tissue before. This gene is a likely candidate for the QTL on BTA19 because of its involvement in de novo fat synthesis. Future studies using sequence data of both CCDC57 and FASN, and eventually functional studies, will have to be pursued to assign the causal variant(s).

Modeling tenderness for genetic and quantitative trait loci analyses

Tenderness is the one of the most important attributes of beef with regards to the intent of consumers to repurchase. Beef tenderness is frequently measured objectively as Warner-Bratzler shear force. However, to better understand the genetics underlying tenderness, better descriptors were derived herein. Two traits, adjusted shear force and aging rate, were calculated to incorporate measures of Warner-Bratzler shear force repeated over aging time of 2 muscles, longissimus dorsi (LD) and semitendinosus (ST). Analysis of these traits indicated that the shear forces of the 2 muscles are lowly correlated and aging rate, as calculated, was not correlated with adjusted shear force. Breed, SNP, and QTL effects were analyzed for the 4 traits (2 traits × 2 muscles). For adjusted shear force, the QTL were located on cattle chromosomes BTA 5, 18, 25, and 29. With the exception of the QTL on BTA 5, the adjusted shear force QTL were observed for either the LD or the ST but not both muscles. The QTL for aging rate were located on BTA 1, 4, 7, 11, 13, 19, and 20.

A genome-wide association study for somatic cell score using the Illumina high-density bovine beadchip identifies several novel QTL potentially related to mastitis susceptibility

Mastitis is an inflammation-driven disease of the bovine mammary gland that occurs in response to physical damage or infection and is one of the most costly production-related diseases in the dairy industry worldwide. We performed a genome-wide association study (GWAS) to identify genetic loci associated with somatic cell score (SCS), an indicator trait of mammary gland inflammation. A total of 702 Holstein-Friesian bulls were genotyped for 777,962 single nucleotide polymorphisms (SNPs) and associated with SCS phenotypes. The SCS phenotypes were expressed as daughter yield deviations (DYD) based on a large number of progeny performance records. A total of 138 SNPs on 15 different chromosomes reached genome-wide significance (corrected p-value ≤ 0.05) for association with SCS (after correction for multiple testing). We defined 28 distinct QTL regions and a number of candidate genes located in these QTL regions were identified. The most significant association (p-value = 1.70 × 10⁻⁷) was observed on chromosome 6. This QTL had no known genes annotated within it, however, the Ensembl Genome Browser predicted the presence of a small non-coding RNA (a Y RNA gene) in this genomic region. This Y RNA gene was 99% identical to human RNY4. Y RNAs are a rare type of non-coding RNA that were originally discovered due to their association with the autoimmune disease, systemic lupus erythematosus. Examining small-RNA sequencing (RNAseq) data being generated by us in multiple different mastitis-pathogen challenged cell-types has revealed that this Y RNA is expressed (but not differentially expressed) in these cells. Other QTL regions identified in this study also encoded strong candidate genes for mastitis susceptibility. A QTL region on chromosome 13, for example, was found to contain a cluster of β-defensin genes, a gene family with known roles in innate immunity. Due to the increased SNP density, this study also refined the boundaries for several known QTL for SCS and mastitis.

The mammary gland in domestic ruminants: a systems biology perspective

Milk and dairy products are central elements in the human diet. It is estimated that 108kg of milk per year are consumed per person worldwide. Therefore, dairy production represents a relevant fraction of the economies of many countries, being cattle, sheep, goat, water buffalo, and other ruminants the main species used worldwide. An adequate management of dairy farming cannot be achieved without the knowledge on the biological mechanisms behind lactation in ruminants. Thus, understanding the morphology, development and regulation of the mammary gland in health, disease and production is crucial. Presently, innovative and high-throughput technologies such as genomics, transcriptomics, proteomics and metabolomics allow a much broader and detailed knowledge on such issues. Additionally, the application of a systems biology approach to animal science is vastly growing, as new advances in one field of specialization or animal species lead to new lines of research in other areas or/and are expanded to other species. This article addresses how modern research approaches may help us understand long-known issues in mammary development, lactation biology and dairy production.

BIOLOGICAL SIGNIFICANCE

Dairy production depends upon the knowledge of the morphology and regulation of the mammary gland and lactation. High-throughput technologies allow a much broader and detailed knowledge on the biology of the mammary gland. This paper reviews the major contributions that genomics, transcriptomics, metabolomics and proteomics approaches have provided to understand the regulation of the mammary gland in health, disease and production. In the context of mammary gland "omics"-based research, the integration of results using a Systems Biology Approach is of key importance.