Dataset Information

Integrating Sequence-based GWAS and RNA-Seq Provides Novel Insights into the Genetic Basis of Mastitis and Milk Production in Dairy Cattle.

ABSTRACT: Connecting genome-wide association study (GWAS) to biological mechanisms underlying complex traits is a major challenge. Mastitis resistance and milk production are complex traits of economic importance in the dairy sector and are associated with intra-mammary infection (IMI). Here, we integrated IMI-relevant RNA-Seq data from Holstein cattle and sequence-based GWAS data from three dairy cattle breeds (i.e., Holstein, Nordic red cattle, and Jersey) to explore the genetic basis of mastitis resistance and milk production using post-GWAS analyses and a genomic feature linear mixed model. At 24?h post-IMI, genes responsive to IMI in the mammary gland were preferentially enriched for genetic variants associated with mastitis resistance rather than milk production. Response genes in the liver were mainly enriched for variants associated with mastitis resistance at an early time point (3?h) post-IMI, whereas responsive genes at later stages were enriched for associated variants with milk production. The up- and down-regulated genes were enriched for associated variants with mastitis resistance and milk production, respectively. The patterns were consistent across breeds, indicating that different breeds shared similarities in the genetic basis of these traits. Our approaches provide a framework for integrating multiple layers of data to understand the genetic architecture underlying complex traits.

SUBMITTER: Fang L

PROVIDER: S-EPMC5372096 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Integrating Sequence-based GWAS and RNA-Seq Provides Novel Insights into the Genetic Basis of Mastitis and Milk Production in Dairy Cattle.

Fang Lingzhao L Sahana Goutam G Su Guosheng G Yu Ying Y Zhang Shengli S Lund Mogens Sandø MS Sørensen Peter P

Scientific reports 20170330

Connecting genome-wide association study (GWAS) to biological mechanisms underlying complex traits is a major challenge. Mastitis resistance and milk production are complex traits of economic importance in the dairy sector and are associated with intra-mammary infection (IMI). Here, we integrated IMI-relevant RNA-Seq data from Holstein cattle and sequence-based GWAS data from three dairy cattle breeds (i.e., Holstein, Nordic red cattle, and Jersey) to explore the genetic basis of mastitis resist ...[more]

PMID: 28358110

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Project description:BackgroundKetosis is a common metabolic disease during the transition period in dairy cattle, resulting in long-term economic loss to the dairy industry worldwide. While genetic selection of resistance to ketosis has been adopted by many countries, the genetic and biological basis underlying ketosis is poorly understood.ResultsWe collected a total of 24 blood samples from 12 Holstein cows, including 4 healthy and 8 ketosis-diagnosed ones, before (2 weeks) and after (5 days) calving, respectively. We then generated RNA-Sequencing (RNA-Seq) data and seven blood biochemical indicators (bio-indicators) from leukocytes and plasma in each of these samples, respectively. By employing a weighted gene co-expression network analysis (WGCNA), we detected that 4 out of 16 gene-modules, which were significantly engaged in lipid metabolism and immune responses, were transcriptionally (FDR < 0.05) correlated with postpartum ketosis and several bio-indicators (e.g., high-density lipoprotein and low-density lipoprotein). By conducting genome-wide association signal (GWAS) enrichment analysis among six common health traits (ketosis, mastitis, displaced abomasum, metritis, hypocalcemia and livability), we found that 4 out of 16 modules were genetically (FDR < 0.05) associated with ketosis, among which three were correlated with postpartum ketosis based on WGCNA. We further identified five candidate genes for ketosis, including GRINA, MAF1, MAFA, C14H8orf82 and RECQL4. Our phenome-wide association analysis (Phe-WAS) demonstrated that human orthologues of these candidate genes were also significantly associated with many metabolic, endocrine, and immune traits in humans. For instance, MAFA, which is involved in insulin secretion, glucose response, and transcriptional regulation, showed a significantly higher association with metabolic and endocrine traits compared to other types of traits in humans.ConclusionsIn summary, our study provides novel insights into the molecular mechanism underlying ketosis in cattle, and highlights that an integrative analysis of omics data and cross-species mapping are promising for illustrating the genetic architecture underpinning complex traits.

Project description:BackgroundSubclinical intramammary infection (IMI) represents a significant problem in maintaining dairy cows' health. Disease severity and extent depend on the interaction between the causative agent, environment, and host. To investigate the molecular mechanisms behind the host immune response, we used RNA-Seq for the milk somatic cells (SC) transcriptome profiling in healthy cows (n = 9), and cows naturally affected by subclinical IMI from Prototheca spp. (n = 11) and Streptococcus agalactiae (S. agalactiae; n = 11). Data Integration Analysis for Biomarker discovery using Latent Components (DIABLO) was used to integrate transcriptomic data and host phenotypic traits related to milk composition, SC composition, and udder health to identify hub variables for subclinical IMI detection.ResultsA total of 1,682 and 2,427 differentially expressed genes (DEGs) were identified when comparing Prototheca spp. and S. agalactiae to healthy animals, respectively. Pathogen-specific pathway analyses evidenced that Prototheca's infection upregulated antigen processing and lymphocyte proliferation pathways while S. agalactiae induced a reduction of energy-related pathways like the tricarboxylic acid cycle, and carbohydrate and lipid metabolism. The integrative analysis of commonly shared DEGs between the two pathogens (n = 681) referred to the core-mastitis response genes, and phenotypic data evidenced a strong covariation between those genes and the flow cytometry immune cells (r2 = 0.72), followed by the udder health (r2 = 0.64) and milk quality parameters (r2 = 0.64). Variables with r ≥ 0.90 were used to build a network in which the top 20 hub variables were identified with the Cytoscape cytohubba plug-in. The genes in common between DIABLO and cytohubba (n = 10) were submitted to a ROC analysis which showed they had excellent predictive performances in terms of discriminating healthy and mastitis-affected animals (sensitivity > 0.89, specificity > 0.81, accuracy > 0.87, and precision > 0.69). Among these genes, CIITA could play a key role in regulating the animals' response to subclinical IMI.ConclusionsDespite some differences in the enriched pathways, the two mastitis-causing pathogens seemed to induce a shared host immune-transcriptomic response. The hub variables identified with the integrative approach might be included in screening and diagnostic tools for subclinical IMI detection.

Project description:BackgroundPeople are paying more attention to the healthy and balanced diet with the improvement of their living standards. Milk fatty acids (FAs) have been reported that they were related to some atherosclerosis and coronary heart diseases in human. In our previous genome-wide association study (GWAS) on milk FAs in dairy cattle, 83 genome-wide significant single nucleotide polymorphisms (SNPs) were detected. Among them, two SNPs, ARS-BFGL-NGS-109493 and BTA-56389-no-rs associated with C18index (P = 0.0459), were located in the upstream of 1-acylglycerol-3-phosphate O-acyltransferase 3 (AGPAT3) gene. AGPAT3 is involved in glycerol-lipid, glycerol-phospholipid metabolism and phospholipase D signaling pathways. Hence, it was inferred as a candidate gene for milk FAs. The aim of this study was to further confirm the genetic effects of the AGPAT3 gene on milk FA traits in dairy cattle.ResultsThrough re-sequencing the complete coding region, and 3000 bp of 5' and 3' regulatory regions of the AGPAT3 gene, a total of 17 SNPs were identified, including four in 5' regulatory region, one in 5' untranslated region (UTR), three in introns, one in 3' UTR, and eight in 3' regulatory region. By the linkage disequilibrium (LD) analysis with Haploview4.1 software, two haplotype blocks were observed that were formed by four and 12 identified SNPs, respectively. Using SAS9.2, we performed single locus-based and haplotype-based association analysis on 24 milk FAs in 1065 Chinese Holstein cows, and discovered that all the SNPs and the haplotype blocks were significantly associated with C6:0, C8:0 and C10:0 (P < 0.0001-0.0384). Further, with Genomatix, we predicted that four SNPs in 5' regulatory region (g.146702957G > A, g.146704373A > G, g.146704618A > G and g.146704699G > A) changed the transcription factor binding sites (TFBSs) for transcription factors SMARCA3, REX1, VMYB, BRACH, NKX26, ZBED4, SP1, USF1, ARNT and FOXA1. Out of them, two SNPs were validated to impact transcriptional activity by performing luciferase assay that the alleles A of both SNPs, g.146704373A > G and g.146704618A > G, increased the transcriptional activities of AGPAT3 promoter compared with alleles G (P = 0.0004).ConclusionsIn conclusion, our findings first demonstrated the significant genetic associations of the AGPAT3 gene with milk FAs in dairy cattle, and two potential causal mutations were detected.

Project description:BACKGROUND: One major problem in dairy cattle husbandry is the prevalence of udder infections. In today's breeding programmes, top priority is being given to making animal evaluation more cost-effective and reliable and less time-consuming. We proposed tumor necrosis factor ? (TNF-?), lactoferrin (LTF) and macrophage-expressed lysozyme (mLYZ) genes as potential DNA markers in the improvement of immunity to mastitis.This study included 588 Polish Holstein-Friesian cows kept on one farm located in the north-western region of Poland. All clinical cases of mastitis in the herd under study were recorded by a qualified veterinarian employed by the farm. The following indicators were applied to determine udder immunity to mastitis in the cows under study: morbidity rate (MR), duration of mastitis (DM) and extent of mastitis (EM). TNF-?, mLYZ and LTF genotypes were identified by real-time PCR method, using SimpleProbe technology. Due to the very low frequency of mLYZ allele T, the gene was excluded from further analysis.A statistical analysis of associations between TNF-? and LTF genes and immunity to mastitis were performed using three models: 1) a parity-averaged model including only additive effects of the genes; 2) a parity-averaged model including both additive and epistatic effects of the genes; and 3) a parity-specific model including only additive effects of the genes. RESULTS: With the first and second models it was revealed that the genes effects on the applied indicators of immunity to mastitis were non-significant whereas with the third one the effects were found to be statistically significant. Particularly noteworthy was the finding that the effects of TNF-? and LTF varied depending on age (parity). The alleles which were linked to high immunity to mastitis in lower parities appeared to be less favourable in higher parities. CONCLUSIONS: These interactions might be related to inflamm-ageing, that is an increased susceptibility to infection due to immune system deregulation that progresses with age. Such pattern of interactions makes it impossible to use the genes in question in marker-assisted selection aimed at reducing heritable susceptibility to mastitis. This is because the immune mechanisms behind resistance to infections proved to be too complex.

Dataset Information

Integrating Sequence-based GWAS and RNA-Seq Provides Novel Insights into the Genetic Basis of Mastitis and Milk Production in Dairy Cattle.

Publications

Integrating Sequence-based GWAS and RNA-Seq Provides Novel Insights into the Genetic Basis of Mastitis and Milk Production in Dairy Cattle.

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