Effects ofDGAT1andGHRon milk yield and milk composition in the Chinese dairy population

Prevalence of growth hormone receptor gene polymorphisms and their association with milk production and fertility-related traits of cross-bred dairy cows in Sri Lanka

This study investigated the association of selected growth hormone receptor (GHR) gene SNPs with selected fertility and milk production-related phenotypes of cross-bred dairy cows (n = 153) reared on three National Livestock Development Board farms in Sri Lanka. Selected cows were genetically screened for SNPs in the exon 08 (n = 153) and 5' upstream (n = 118) regions of the GHR gene using the target sequencing method. The relationships between different genotypes and fertility traits (average calving interval, average number of services per conception, and age at first calving) and milk production-related traits (average total lactation yield, average lactation length, and average milk yield) were analyzed using the General Linear Model in SPSS. Among the identified Four GHR SNPs, rs1099014416 was significantly associated with average calving interval and age at first calving. Cows with GG genotype exhibited younger age at first calving (918.51 ± 113.42 days) and longer calving intervals (543.41 ± 43.29 days) compared to cows with GT (1275.18 ± 38.31, 515.09 ± 24.49 days) and TT (1212.89 ± 88.22, 364.52 ± 54.01 days) genotypes. Other SNPs did not show associations with the studied traits. SNP rs109014416 has the potential to be used as a genetic marker for fertility-related traits in the selection of cross-bred dairy cows in Sri Lanka which should be validated with a larger population.

Strong evidence for association between K232A polymorphism of the DGAT1 gene and milk fat and protein contents: A meta-analysis

The relationship between K232A polymorphism of the DGAT1 gene and milk yield and composition was evaluated by meta-analysis of pooled data of more than 10,000 genotyped cattle. Four genetic models, including dominant (AA+KA vs. KK), recessive (AA vs. KA+KK), additive (AA vs. KK), and co-dominant (AA+KK vs. KA) were used to analyze the data. The standardized mean difference (SMD) was used to measure the size of the effects of the A and K alleles of K232A polymorphism on milk-related traits. The results showed that additive model was the best model for describing the effects of K232A polymorphism on studied traits. Under additive model, milk fat content was strongly decreased in cows having the AA genotype (SMD = -1.320). Furthermore, the AA genotype reduced the protein content of milk (SMD = -0.400). A significant difference in daily milk yield (SMD = 0.225) and lactation yield (SMD = 0.697) was found between cows carrying AA and KK genotypes, suggesting the positive effects of the K allele on these traits. Cook's distance measurement suggested some studies as outliers and sensitivity analyses by removing influential studies revealed that the results of meta-analyses for daily milk yield, fat content and protein content were not sensitive to outliers. However, the outcome of the meta-analysis for lactation yield was strongly influenced by outlier studies. Egger's test and Begg's funnel plots showed no evidence of publication bias in included studies. In conclusion, the K allele of K232A polymorphism showed a tremendous effect on increasing fat and protein contents in the milk of cattle, especially when 2 copies of this allele are inherited together, whereas the A allele of K232A polymorphism had negative effects on these traits.

Perspectives of gene editing for cattle farming in tropical and subtropical regions

Cattle productivity in tropical and subtropical regions can be severely affected by the environment. Reproductive performance, milk and meat production are compromised by the heat stress imposed by the elevated temperature and humidity. The resulting low productivity contributes to reduce the farmer's income and to increase the methane emissions per unit of animal protein produced and the pressure on land usage. The introduction of highly productive European cattle breeds as well as crossbreeding with local breeds have been adopted as strategies to increase productivity but the positive effects have been limited by the low adaptation of European animals to hot climates and by the reduction of the heterosis effect in the following generations. Gene editing tools allow precise modifications in the animal genome and can be an ally to the cattle industry in tropical and subtropical regions. Alleles associated with production or heat tolerance can be shifted between breeds without the need of crossbreeding. Alongside assisted reproductive biotechnologies and genome selection, gene editing can accelerate the genetic gain of indigenous breeds such as zebu cattle. This review focuses on some of the potential applications of gene editing for cattle farming in tropical and subtropical regions, bringing aspects related to heat stress, milk yield, bull reproduction and methane emissions.

Longitudinal genome-wide association studies of milk production traits in Holstein cattle using whole-genome sequence data imputed from medium-density chip data

Longitudinal traits, such as milk production traits in dairy cattle, are featured by having phenotypic values at multiple time points, which change dynamically over time. In this study, we first imputed SNP chip (50-100K) data to whole-genome sequence (WGS) data in a Chinese Holstein population consisting of 6,470 cows. The imputation accuracies were 0.88 to 0.97 on average after quality control. We then performed longitudinal GWAS in this population based on a random regression test-day model using the imputed WGS data. The longitudinal GWAS revealed 16, 39, and 75 quantitative trait locus regions associated with milk yield, fat percentage, and protein percentage, respectively. We estimated the 95% confidence intervals (CI) for these quantitative trait locus regions using the logP drop method and identified 581 genes involved in these CI. Further, we focused on the CI that covered or overlapped with only 1 gene or the CI that contained an extremely significant top SNP. Twenty-eight candidate genes were identified in these CI. Most of them have been reported in the literature to be associated with milk production traits, such as DGAT1, HSF1, MGST1, GHR, ABCG2, ADCK5, and CSN1S1. Among the unreported novel genes, some also showed good potential as candidate genes, such as CCSER1, CUX2, SNTB1, RGS7, OSR2, and STK3, and are worth being further investigated. Our study provided not only new insights into the candidate genes for milk production traits, but also a general framework for longitudinal GWAS based on random regression test-day model using WGS data.

Variation in Ovine DGAT1 and Its Association with Carcass Muscle Traits in Southdown Sheep

Diacylglycerol O-acyltransferase 1 (DGAT1) is a microsomal enzyme that plays a key role in the synthesis of triglycerides. Its gene (DGAT1) is regarded as a candidate gene for variation in milk and meat traits in cattle. The objective of this study was to use a PCR single-strand conformation polymorphism approach to explore sequence variation in two regions of ovine DGAT1 and to assess its effect on meat traits in New Zealand Southdown sheep. Three variant nucleotide sequences were identified in each region, with two single nucleotide polymorphisms (SNPs) and one nucleotide deletion being detected in intron 1 and two SNPs being found in exon 17. The effect of the exon 17 variation was not investigated due to one variant being predominant and the other two variants occurring at low frequencies. In intron 1, one variant (B₁) was found to be associated with increase loin meat yield, suggesting that this may have value as a gene marker for improving meat traits.

Genome-wide association study on milk production and somatic cell score for Thai dairy cattle using weighted single-step approach with random regression test-day model

Genome-wide association studies are a powerful tool to identify genomic regions and variants associated with phenotypes. However, only limited mutual confirmation from different studies is available. The objectives of this study were to identify genomic regions as well as genes and pathways associated with the first-lactation milk, fat, protein, and total solid yields; fat, protein, and total solid percentage; and somatic cell score (SCS) in a Thai dairy cattle population. Effects of SNPs were estimated by a weighted single-step GWAS, which back-solved the genomic breeding values predicted using single-step genomic BLUP (ssGBLUP) fitting a single-trait random regression test-day model. Genomic regions that explained at least 0.5% of the total genetic variance were selected for further analyses of candidate genes. Despite the small number of genotyped animals, genomic predictions led to an improvement in the accuracy over the traditional BLUP. Genomic predictions using weighted ssGBLUP were slightly better than the ssGBLUP. The genomic regions associated with milk production traits contained 210 candidate genes on 19 chromosomes [Bos taurus autosome (BTA) 1 to 7, 9, 11 to 16, 20 to 21, 26 to 27 and 29], whereas 21 candidate genes on 3 chromosomes (BTA 11, 16, and 21) were associated with SCS. Many genomic regions explained a small fraction of the genetic variance, indicating polygenic inheritance of the studied traits. Several candidate genes coincided with previous reports for milk production traits in Holstein cattle, especially a large region of genes on BTA14. We identified 141 and 5 novel genes related to milk production and SCS, respectively. These novel genes were also found to be functionally related to heat tolerance (e.g., SLC45A2, IRAG1, and LOC101902172), longevity (e.g., SYT10 and LOC101903327), and fertility (e.g., PAG1). These findings may be attributed to indirect selection in our population. Identified biological networks including intracellular cell transportation and protein catabolism implicate milk production, whereas the immunological pathways such as lymphocyte activation are closely related to SCS. Further studies are required to validate our findings before exploiting them in genomic selection.

Association of DGAT1 With Cattle, Buffalo, Goat, and Sheep Milk and Meat Production Traits

Milk fatty acids are essential for many dairy product productions, while intramuscular fat (IMF) is associated with the quality of meat. The triacylglycerols (TAGs) are the major components of IMF and milk fat. Therefore, understanding the polymorphisms and genes linked to fat synthesis is important for animal production. Identifying quantitative trait loci (QTLs) and genes associated with milk and meat production traits has been the objective of various mapping studies in the last decade. Consistently, the QTLs on chromosomes 14, 15, and 9 have been found to be associated with milk and meat production traits in cattle, goat, and buffalo and sheep, respectively. Diacylglycerol O-acyltransferase 1 (DGAT1) gene has been reported on chromosomes 14, 15, and 9 in cattle, goat, and buffalo and sheep, respectively. Being a key role in fat metabolism and TAG synthesis, the DGAT1 has obtained considerable attention especially in animal milk production. In addition to milk production, DGAT1 has also been a subject of interest in animal meat production. Several polymorphisms have been documented in DGAT1 in various animal species including cattle, buffalo, goat, and sheep for their association with milk production traits. In addition, the DGAT1 has also been studied for their role in meat production traits in cattle, sheep, and goat. However, very limited studies have been conducted in cattle for association of DGAT1 with meat production traits in cattle. Moreover, not a single study reported the association of DGAT1 with meat production traits in buffalo; thus, further studies are warranted to fulfill this huge gap. Keeping in view the important role of DGAT1 in animal production, the current review article was designed to highlight the major development and new insights on DGAT1 effect on milk and meat production traits in cattle, buffalo, sheep, and goat. Moreover, we have also highlighted the possible future contributions of DGAT1 for the studied species.

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.

A Comprehensive Analysis of Runs of Homozygosity of Eleven Cattle Breeds Representing Different Production Types

Simple Summary

Runs of homozygosity (ROH) regions are known to be common in the genomes of cattle and have become a subject of interest of various research in recent years. ROH can be used as a valuable tool to estimate inbreeding, which needs to be controlled in livestock populations. Moreover, analysis of ROH is considered to be an effective method of identifying genome regions that are a subject of selection pressure, which may help in understanding the genetic aspects of production traits under selection. In this study, we analyzed ROH characteristics of 11 cattle breeds, both commercial and native, maintained in Poland. We presented distinct differences in the length, quantity and frequency of ROH between the analyzed breeds as well as in the levels of genomic inbreeding. Higher levels of inbreeding were characteristic for commercial breeds, especially beef breeds. In addition, within ROH islands, we observed a number of genes with a confirmed influence on the level of production traits. The presented results and identified genes can be a basis for further research focused on the identification of genes and markers essential in the determination of the most important production traits in cattle.

Abstract

In the presented research, BovineSNP50 microarrays (Illumina) were applied to determine runs of homozygosity in the genomes of 11 cattle breeds maintained in Poland. These cattle breeds represent three basic utility types: milk, meat and dual purpose. Analysis of runs of homozygosity allowed the evaluation of the level of autozygosity within each breed in order to calculate the genomic inbreeding coefficient (F_ROH), as well as to identify regions of the genome with a high frequency of ROH occurrence, which may reflect traces of directional selectin left in their genomes. Visible differences in the length and distribution of runs of homozygosity in the genomes of the analyzed cattle breeds have been observed. The highest mean number and mean sums of lengths of runs of homozygosity were characteristic for Hereford cattle and intermediate for the Holstein-Friesian Black-and-White variety, Holstein-Friesian Red-and-White variety, Simmental, Limousin, Montbeliarde and Charolais breeds. However, lower values were observed for cattle of conserved breeds. Moreover, the selected livestock differed in the level of inbreeding estimated using the F_ROH coefficient. In regions of the genome with a high frequency of ROH occurrence, which may reflect the impact of directional selection, a number of genes were observed that can be potentially related to the production traits which are under selection pressure for specific production types. The most important detected genes were GHR, MSTN, DGAT1, FABP4, and TRH, with a known influence on the milk and meat traits of the studied cattle breeds.

Genetic and genomic analyses underpin the feasibility of concomitant genetic improvement of milk yield and mastitis resistance in dairy sheep

Milk yield is the most important dairy sheep trait and constitutes the key genetic improvement goal via selective breeding. Mastitis is one of the most prevalent diseases, significantly impacting on animal welfare, milk yield and quality, while incurring substantial costs. Our objectives were to determine the feasibility of a concomitant genetic improvement programme for enhanced milk production and resistance to mastitis. Individual records for milk yield, and four mastitis-related traits (milk somatic cell count, California Mastitis Test score, total viable bacterial count in milk and clinical mastitis presence) were collected monthly throughout lactation for 609 ewes of the Chios breed. All ewes were genotyped with a mastitis specific custom-made 960 single nucleotide polymorphism (SNP) array. We performed targeted genomic association studies, (co)variance component estimation and pathway enrichment analysis, and characterised gene expression levels and the extent of allelic expression imbalance. Presence of heritable variation for milk yield was confirmed. There was no significant genetic correlation between milk yield and mastitis traits. Environmental factors appeared to favour both milk production and udder health. There were no overlapping of SNPs associated with mastitis resistance and milk yield in Chios sheep. Furthermore, four distinct Quantitative Trait Loci (QTLs) affecting milk yield were detected on chromosomes 2, 12, 16 and 19, in locations other than those previously identified to affect mastitis resistance. Five genes (DNAJA1, GHR, LYPLA1, NUP35 and OXCT1) located within the QTL regions were highly expressed in both the mammary gland and milk transcriptome, suggesting involvement in milk synthesis and production. Furthermore, the expression of two of these genes (NUP35 and OXCT1) was enriched in immune tissues implying a potentially pleiotropic effect or likely role in milk production during udder infection, which needs to be further elucidated in future studies. In conclusion, the absence of genetic antagonism between milk yield and mastitis resistance suggests that simultaneous genetic improvement of both traits be achievable.

Identification of genetic markers associated with milk production traits in Chinese Holstein cattle based on post genome-wide association studies

With the rapid development of dairy industry, the breeding process of dairy cows has been accelerated. In previous genome-wide association studies (GWAS), a large number of genetic markers have been reported which may contribute to the selection of Holstein populations with superior milk-producing traits, but they remain to be further verified before practical application. In this study, 90 single nucleotide polymorphisms (SNPs) were selected, which were reported to be significantly associated with five milk production traits, including 305-day milk yield (305MY), 305-day milk fat percent (305FC), 305-day milk protein percent (305PC), 305-day milk fat yield (305FY) and 305-day milk protein yield (305PY). Effective 305-day data and fresh DNA samples were obtained from 295 healthy cows with gestational age of 1-4. Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) was used to perform precise genotyping of these loci, followed by site association and haplotype analysis. Results showed that 36 out of 90 loci were supported to be used as genetic markers. In particular, several novel and effective haplotypes were also presented. Overall, our results verified tens of useful markers and provided a basis for further development of breeding strategies.

Polymorphisms and genetic effects of PRLR, MOGAT1, MINPP1 and CHUK genes on milk fatty acid traits in Chinese Holstein

BACKGROUND

Our initial genome-wide association study (GWAS) identified 20 promising candidate genes for milk fatty acid (FA) traits in a Chinese Holstein population, including PRLR, MOGAT1, MINPP1 and CHUK genes. In this study, we performed whether they had significant genetic effects on milk FA traits in Chinese Holstein.

RESULTS

We re-sequenced the entire exons and 3000 bp of the 5' and 3' flanking regions, and identified 11 single nucleotide polymorphisms (SNPs), containing four in PRLR, two in MOGAT1, two in MINPP1, and three in CHUK. The SNP-based association analyses showed that all the 11 SNPs were significantly associated with at least one milk FA trait (P = 0.0456 ~ < 0.0001), and none of them had association with C11:0, C13:0, C15:0 and C16:0 (P > 0.05). By the linkage disequilibrium (LD) analyses, we found two, one, one, and one haplotype blocks in PRLR, MOGAT1, MINPP1, and CHUK, respectively, and each haplotype block was significantly associated with at least one milk FA trait (P = 0.0456 ~ < 0.0001). Further, g.38949011G > A in PRLR, and g.111599360A > G and g.111601747 T > A in MOGAT1 were predicted to alter the transcription factor binding sites (TFBSs). A missense mutation, g.39115344G > A, could change the PRLR protein structure. The g.20966385C > G of CHUK varied the binding sequences for microRNAs. Therefore, we deduced the five SNPs as the potential functional mutations.

CONCLUSION

In summary, we first detected the genetic effects of PRLR, MOGAT1, MINPP1 and CHUK genes on milk FA traits, and researched the potential functional mutations. These data provided the basis for further investigation on function validation of the four genes in Chinese Holstein.

Isolation, characterization, and SREBP1 functional analysis of mammary epithelial cell in buffalo

Compared to cow milk, buffalo milk contains more protein, fat, and vitamin. Buffalo milk is an ideal food in human life. Sterol regulatory element-binding protein 1 (SREBP1), an important transcription factor, regulates the expression and activity of enzyme and protein involved in milk fat synthesis to influence on the synthesis and secretion of triglyceride in mammary epithelial cells. In the present study, we successfully isolated buffalo mammary epithelial cell by using enzymatic digestion, and then described the growth characteristics and expression characteristics of mammary epithelial cells. Moreover, we cloned the SREBP1 gene from total RNA isolated from milk fat globule and analyzed the function of the SREBP1 gene. After infected with shRNA-SREBP1 lentiviral particle and treated with fatty acid, the expression trend of ACACA, FABP3, FAS, SCD, ERK1, ERK2, PPARy, and Insigl genes was consistent with the expression trend of SREBP1 gene. These results suggested that SREBP1 gene is a central transcription factor in regulating milk fat synthesis and SREBP1 gene may act on ERK1/ERK2 signaling pathway to regulate the expression of PPARy gene. The current study will provide a theoretical basis for further reveal the molecular mechanism of milk fat synthesis in buffalo mammary epithelial cells. PRACTICAL APPLICATIONS: This study aim to separate and analysis characterization of mammary epithelial cell in buffalo. Compared to cow milk, buffalo milk contains more protein, fat, and vitamin. Buffalo milk is an ideal food in human life. This study will provide a theoretical basis for further research on the molecular mechanism of milk fat synthesis in buffalo mammary epithelial cells.

A novel indel within goat casein alpha S1 gene is significantly associated with litter size

The ruminant casein gene family (CSNs, link as CSN1S1-CSN2-CSN1S2-CSN3) is characterized by diverse variations and has been extensively studied for ruminant milk traits, however, studies on insertion/deletion (indel) mutations within this gene family and their effects on prolificacy are extremely limited. This study aimed to detect possible novel indels within CSNs in an indigenous Chinese goat breed-Shaanbei White Cashmere goat (SBWC, n = 3047) and four other Chinese goat breeds (n = 1136) with varied litter size rates (105%-283%) and different estrus types (seasonal vs. perennial), as well as exploring the association between these potential indels and litter size. Only one novel 11-bp indel within the CSN1S1 gene was found. The association analyses uncovered that this novel indel was related to the first-birth litter size of SBWC population (n = 2690) (P < 1.0 E-8). Individuals with the II genotype (n = 676) had the best litter size when compared with those ID genotype (n = 1098) and DD genotype (n = 916) individuals. Animals with the II genotype were found to have higher relative expression level of CSN1S1 gene in the ovary (P < 0.01). Besides, Chi-square tests for different litter size and estrous cycle breeds showed that perennial-estrus breeds and multi-kids breeds had higher "I" allelic frequencies and "II" genotypic frequencies. These findings suggest the 11-bp indel within the CSN1S1 gene is significantly associated with reproduction traits and can be an effective molecular marker for litter size of goat breeding.

Genetic association of the ACACB gene with milk yield and composition traits in dairy cattle

Previously, we re-sequenced the whole genomes of eight Holstein bulls with high or low milk protein and fat percentage, and we detected two indels in the ACACB (acetyl-CoA carboxylase beta) gene that were polymorphic between the two groups. Thus, we considered ACACB as a promising candidate gene potentially affecting milk composition traits. Herein, we verified the genetic effects of ACACB on five milk traits in a Chinese Holstein population. We identified six SNPs in the 5'-promoter region, five in the 5'- untranslated region (UTR), 11 in exons, four in the 3'-UTR and three in the 3'-flanking region by re-sequencing the entire coding and regulatory regions of ACACB. One of these SNPs (ss1987461005) is reported here for the first time, and three of the SNPs (rs109482081, rs110819816 and rs109281947) were predicted to result in amino acid replacements. Genotype-phenotype association analyses showed that all the identified SNPs, except for ss1987461005, rs208919019 and rs134447911, were significantly associated with milk yield, fat yield, fat percentage, protein yield or protein percentage (P < 0.0001 to 0.0484). Linkage disequilibrium analyses were conducted among the identified SNPs to confirm the genetic associations. Two SNPs-rs135874354 (g.66218726T>C) and rs210928430 (g.66218117G>A)-were predicted to alter transcription factor binding sites in the 5'-promoter region of ACACB. A luciferase activity assay showed that the promoter activity of haplotype TG was significantly higher than that of CG (P = 0.0002) and that the promoter activity of haplotype TA was remarkably higher than that of CA (P = 7.4285E-09), showing that the T allele of rs135874354 increased promoter activity. Thus, rs135874354 was considered to be a potentially functional mutation. Our findings have, for the first time, profiled the genetic effect of ACACB on milk production traits in dairy cattle and revealed a potentially causal mutation that requires further the in-depth validation.

The patterns of genomic variances and covariances across genome for milk production traits between Chinese and Nordic Holstein populations

BACKGROUND

With the development of SNP chips, SNP information provides an efficient approach to further disentangle different patterns of genomic variances and covariances across the genome for traits of interest. Due to the interaction between genotype and environment as well as possible differences in genetic background, it is reasonable to treat the performances of a biological trait in different populations as different but genetic correlated traits. In the present study, we performed an investigation on the patterns of region-specific genomic variances, covariances and correlations between Chinese and Nordic Holstein populations for three milk production traits.

RESULTS

Variances and covariances between Chinese and Nordic Holstein populations were estimated for genomic regions at three different levels of genome region (all SNP as one region, each chromosome as one region and every 100 SNP as one region) using a novel multi-trait random regression model which uses latent variables to model heterogeneous variance and covariance. In the scenario of the whole genome as one region, the genomic variances, covariances and correlations obtained from the new multi-trait Bayesian method were comparable to those obtained from a multi-trait GBLUP for all the three milk production traits. In the scenario of each chromosome as one region, BTA 14 and BTA 5 accounted for very large genomic variance, covariance and correlation for milk yield and fat yield, whereas no specific chromosome showed very large genomic variance, covariance and correlation for protein yield. In the scenario of every 100 SNP as one region, most regions explained <0.50% of genomic variance and covariance for milk yield and fat yield, and explained <0.30% for protein yield, while some regions could present large variance and covariance. Although overall correlations between two populations for the three traits were positive and high, a few regions still showed weakly positive or highly negative genomic correlations for milk yield and fat yield.

CONCLUSIONS

The new multi-trait Bayesian method using latent variables to model heterogeneous variance and covariance could work well for estimating the genomic variances and covariances for all genome regions simultaneously. Those estimated genomic parameters could be useful to improve the genomic prediction accuracy for Chinese and Nordic Holstein populations using a joint reference data in the future.

Whole blood transcriptional profiling comparison between different milk yield of Chinese Holstein cows using RNA-seq data

Background

The objective of this research was to investigate the variation of gene expression in the blood transcriptome profile of Chinese Holstein cows associated to the milk yield traits.

Results

We used RNA-seq to generate the bovine transcriptome from the blood of 23 lactating Chinese Holstein cows with extremely high and low milk yield. A total of 100 differentially expressed genes (DEGs) (p < 0.05, FDR < 0.05) were revealed between the high and low groups. Gene ontology (GO) analysis demonstrated that the 100 DEGs were enriched in specific biological processes with regard to defense response, immune response, inflammatory response, icosanoid metabolic process, and fatty acid metabolic process (p < 0.05). The KEGG pathway analysis with 100 DEGs revealed that the most statistically-significant metabolic pathway was related with Toll-like receptor signaling pathway (p < 0.05). The expression level of four selected DEGs was analyzed by qRT-PCR, and the results indicated that the expression patterns were consistent with the deep sequencing results by RNA-Seq. Furthermore, alternative splicing analysis of 100 DEGs demonstrated that there were different splicing pattern between high and low yielders. The alternative 3’ splicing site was the major splicing pattern detected in high yielders. However, in low yielders the major type was exon skipping.

Conclusion

This study provides a non-invasive method to identify the DEGs in cattle blood using RNA-seq for milk yield. The revealed 100 DEGs between Holstein cows with extremely high and low milk yield, and immunological pathway are likely involved in milk yield trait. Finally, this study allowed us to explore associations between immune traits and production traits related to milk production.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2901-1) contains supplementary material, which is available to authorized users.

Deep Sequencing and Screening of Differentially Expressed MicroRNAs Related to Milk Fat Metabolism in Bovine Primary Mammary Epithelial Cells

Milk fat is a key factor affecting milk quality and is also a major trait targeted in dairy cow breeding. To determine how the synthesis and the metabolism of lipids in bovine milk is regulated at the miRNA level, primary mammary epithelial cells (pMEC) derived from two Chinese Holstein dairy cows that produced extreme differences in milk fat percentage were cultured by the method of tissue nubbles culture. Small RNA libraries were constructed from each of the two pMEC groups, and Solexa sequencing and bioinformatics analysis were then used to determine the abundance of miRNAs and their differential expression pattern between pMECs. Target genes and functional prediction of differentially expressed miRNAs by Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes analysis illustrated their roles in milk fat metabolism. Results show that a total of 292 known miRNAs and 116 novel miRNAs were detected in both pMECs. Identification of known and novel miRNA candidates demonstrated the feasibility and sensitivity of sequencing at the cellular level. Additionally, 97 miRNAs were significantly differentially expressed between the pMECs. Finally, three miRNAs including bta-miR-33a, bta-miR-152 and bta-miR-224 whose predicted target genes were annotated to the pathway of lipid metabolism were screened and verified by real-time qPCR and Western-blotting experiments. This study is the first comparative profiling of the miRNA transcriptome in pMECs that produce different milk fat content.

Transcriptional profiling of mammary gland in Holstein cows with extremely different milk protein and fat percentage using RNA sequencing

Background

Recently, RNA sequencing (RNA-seq) has rapidly emerged as a major transcriptome profiling system. Elucidation of the bovine mammary gland transcriptome by RNA-seq is essential for identifying candidate genes that contribute to milk composition traits in dairy cattle.

Results

We used massive, parallel, high-throughput, RNA-seq to generate the bovine transcriptome from the mammary glands of four lactating Holstein cows with extremely high and low phenotypic values of milk protein and fat percentage. In total, we obtained 48,967,376–75,572,578 uniquely mapped reads that covered 82.25% of the current annotated transcripts, which represented 15549 mRNA transcripts, across all the four mammary gland samples. Among them, 31 differentially expressed genes (p < 0.05, false discovery rate q < 0.05) between the high and low groups of cows were revealed. Gene ontology and pathway analysis demonstrated that the 31 differently expressed genes were enriched in specific biological processes with regard to protein metabolism, fat metabolism, and mammary gland development (p < 0.05). Integrated analysis of differential gene expression, previously reported quantitative trait loci, and genome-wide association studies indicated that TRIB3, SAA (SAA1, SAA3, and M-SAA3.2), VEGFA, PTHLH, and RPL23A were the most promising candidate genes affecting milk protein and fat percentage.

Conclusions

This study investigated the complexity of the mammary gland transcriptome in dairy cattle using RNA-seq. Integrated analysis of differential gene expression and the reported quantitative trait loci and genome-wide association study data permitted the identification of candidate key genes for milk composition traits.

Genetic markers of body composition and carcass quality in grazing Brangus steers

The somatotropic axis is a major regulatory pathway of energy metabolism during postnatal growth in mammals. Genes involved in this pathway influence many economically important traits. The association of selected SNPs in these genes with carcass traits was examined in grazing Brangus steers. These traits included final live weight, ultrasound backfat thickness (UBFT), rib-eye area, kidney fat weight, hot carcass weight, and intramuscular fat percentage (%IMF). Genomic DNA (N = 246) was genotyped for a panel of 15 tag SNPs located in the growth hormone receptor (GHR), insulin-like growth factor I, insulin-like growth factor-binding protein 6, pro-melanin-concentrating hormone, suppressor of cytokine signaling 2, and signal transducer and activator of transcription 6 (STAT6) genes. Allelic and haplotype frequencies were compared with those of a sample of European breeds (N = 177 steers). Two tag SNPs in the GHR affected %IMF; one of them (ss86273136) was also strongly associated with UBFT (P < 0.003). The frequency of the most favorable GHR haplotype for %IMF was lower in Brangus steers. Moreover, the haplotype carrying two unfavorable alleles was present at a frequency of 31% in this group. Four tag SNPs on STAT6 had a significant effect on UBFT. One of these, SNP ss115492467, was also associated with %IMF. The STAT6 haplotype, including all the alleles favoring UBFT, was the most abundant variant (34%) in the European cattle, while it had a frequency of 14% in the Brangus steers. The four less favorable variants (absent in the European cattle) were found at a frequency of 38% in the Brangus steers. These results support the association of GHR and STAT6 SNP with carcass traits in composite breeds, such as Brangus, under grazing conditions.

Effect of polymorphisms in the leptin, leptin receptor and acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1) genes and genetic polymorphism of milk proteins on bovine milk composition

The relations between cow genetics and milk composition have gained a lot of attention during the past years, however, generally only a few compositional traits have been examined. The aim of this study was to determine if polymorphisms in the leptin (LEP), leptin receptor (LEPR) and acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1) genes as well as genetic polymorphism of β-casein (β-CN), κ-CN and β-lactoglobulin (β-LG) impact several bovine milk composition traits. Individual milk samples from the Swedish Red and Swedish Holstein breeds were analyzed for components in the protein, lipid, carbohydrate and mineral profiles. Cow alleles were determined on the following SNP: A1457G, A252T, A59V and C963T on the LEP gene, T945M on the LEPR gene and Nt984+8(A-G) on the DGAT1 gene. Additionally, genetic variants of β-CN, κ-CN and β-LG were determined. For both the breeds, the same tendency of minor allele frequency was found for all SNPs and protein genes, except on LEPA1457G and LEPC963T. This study indicated significant (P<0·05) associations between the studied SNPs and several compositional parameters. Protein content was influenced by LEPA1457G (G>A) and LEPC963T (T>C), whereas total Ca, ionic Ca concentration and milk pH were affected by LEPA1457G, LEPA59V, LEPC963T and LEPRT945M. However, yields of milk, protein, CN, lactose, total Ca and P were mainly affected by β-CN (A2>A1) and κ-CN (A>B>E). β-LG was mainly associated with whey protein yield and ionic Ca concentration (A>B). Thus, this study shows possibilities of using these polymorphisms as markers within genetic selection programs to improve and adjust several compositional parameters.