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

Identification of candidate genes associated with milk production and mastitis based on transcriptome-wide association study

Genetic research for the assessment of mastitis and milk production traits simultaneously has a long history. The main issue that arises in this context is the known existence of a positive correlation between the risk of mastitis and lactation performance due to selection. The transcriptome-wide association study (TWAS) approach endeavors to combine the expression quantitative trait loci and genome-wide association study summary statistics to decode complex traits or diseases. Accordingly, we used the farmgtex project results as a complete bovine database for mastitis and milk production. The results of colocalization and TWAS approaches were used for the detection of functional associated candidate genes with milk production and mastitis traits on multiple tissue-based transcriptome records. Also, we used the david database for gene ontology to identify significant terms and associated genes. For the identification of interaction networks, the genemania and string databases were used. Also, the available z-scores in TWAS results were used for the calculation of the correlation between tissues. Therefore, the present results confirm that LYNX1, DGAT1, C14H8orf33, and LY6E were identified as significant genes associated with milk production in eight, six, five, and five tissues, respectively. Also, FBXL6 was detected as a significant gene associated with mastitis trait. CLN3 and ZNF34 genes emerged via both the colocalization and TWAS approaches as significant genes for milk production trait. It is expected that TWAS and colocalization can improve our perception of the potential health status control mechanism in high-yielding dairy cows.

Transcriptomic Changes and Regulatory Networks Associated with Resistance to Mastitis in Xinjiang Brown Cattle

Xinjiang brown cattle are highly resistant to disease and tolerant of roughage feeding. The identification of genes regulating mastitis resistance in Xinjiang brown cattle is a novel means of genetic improvement. In this study, the blood levels of IL-1β, IL-6, IL-10, TNF-α, and TGF-β in Xinjiang brown cattle with high and low somatic cell counts (SCCs) were investigated, showing that cytokine levels were higher in cattle with high SCCs. The peripheral blood transcriptomic profiles of healthy and mastitis-affected cattle were constructed by RNA-seq. Differential expression analysis identified 1632 differentially expressed mRNAs (DE-mRNAs), 1757 differentially expressed lncRNAs (DE-lncRNAs), and 23 differentially expressed circRNAs (DE-circRNAs), which were found to be enriched in key pathways such as PI3K/Akt, focal adhesion, and ECM-receptor interactions. Finally, ceRNA interaction networks were constructed using the differentially expressed genes and ceRNAs. It was found that keynote genes or mRNAs were also enriched in pathways such as PI3K-Akt, cholinergic synapses, cell adhesion molecules, ion binding, cytokine receptor activity, and peptide receptor activity, suggesting that the key genes and ncRNAs in the network may play an important role in the regulation of bovine mastitis.

Multi-omics integration identifies regulatory factors underlying bovine subclinical mastitis

BACKGROUND

Mastitis caused by multiple factors remains one of the most common and costly disease of the dairy industry. Multi-omics approaches enable the comprehensive investigation of the complex interactions between multiple layers of information to provide a more holistic view of disease pathogenesis. Therefore, this study investigated the genomic and epigenomic signatures and the possible regulatory mechanisms underlying subclinical mastitis by integrating RNA sequencing data (mRNA and lncRNA), small RNA sequencing data (miRNA) and DNA methylation sequencing data of milk somatic cells from 10 healthy cows and 20 cows with naturally occurring subclinical mastitis caused by Staphylococcus aureus or Staphylococcus chromogenes.

RESULTS

Functional investigation of the data sets through gene set analysis uncovered 3458 biological process GO terms and 170 KEGG pathways with altered activities during subclinical mastitis, provided further insights into subclinical mastitis and revealed the involvement of multi-omics signatures in the altered immune responses and impaired mammary gland productivity during subclinical mastitis. The abundant genomic and epigenomic signatures with significant alterations related to subclinical mastitis were observed, including 30,846, 2552, 1276 and 57 differential methylation haplotype blocks (dMHBs), differentially expressed genes (DEGs), lncRNAs (DELs) and miRNAs (DEMs), respectively. Next, 5 factors presenting the principal variation of differential multi-omics signatures were identified. The important roles of Factor 1 (DEG, DEM and DEL) and Factor 2 (dMHB and DEM), in the regulation of immune defense and impaired mammary gland functions during subclinical mastitis were revealed. Each of the omics within Factors 1 and 2 explained about 20% of the source of variation in subclinical mastitis. Also, networks of important functional gene sets with the involvement of multi-omics signatures were demonstrated, which contributed to a comprehensive view of the possible regulatory mechanisms underlying subclinical mastitis. Furthermore, multi-omics integration enabled the association of the epigenomic regulatory factors (dMHBs, DELs and DEMs) of altered genes in important pathways, such as 'Staphylococcus aureus infection pathway' and 'natural killer cell mediated cytotoxicity pathway', etc., which provides further insights into mastitis regulatory mechanisms. Moreover, few multi-omics signatures (14 dMHBs, 25 DEGs, 18 DELs and 5 DEMs) were identified as candidate discriminant signatures with capacity of distinguishing subclinical mastitis cows from healthy cows.

CONCLUSION

The integration of genomic and epigenomic data by multi-omics approaches in this study provided a better understanding of the molecular mechanisms underlying subclinical mastitis and identified multi-omics candidate discriminant signatures for subclinical mastitis, which may ultimately lead to the development of more effective mastitis control and management strategies.

A transcriptomic analysis of skeletal muscle tissues reveals promising candidate genes and pathways accountable for different daily weight gain in Hanwoo cattle

Cattle traits like average daily weight gain (ADG) greatly impact profitability. Selecting based on ADG considering genetic variability can lead to economic and genetic advancements in cattle breeding. This study aimed to unravel genetic influences on ADG variation in Hanwoo cattle at the skeletal muscle transcriptomic level. RNA sequencing was conducted on longissimus dorsi (LD), semimembranosus (SB), and psoas major (PM) muscles of 14 steers assigned to same feed, grouped by low (≤ 0.71 kg) and high (≥ 0.77 kg) ADG. At P ≤ 0.05 and log2fold > 1.5, the distinct pattern of gene expression was identified with 184, 172, and 210 differentially expressed genes in LD, SB, and PM muscles, respectively. Tissue-specific responses to ADG variation were evident, with myogenesis and differentiation associated JAK-STAT signaling pathway and prolactin signaling pathways enriched in LD and SB muscles, while adipogenesis-related PPAR signaling pathways were enriched in PM muscle. Key hub genes (AXIN2, CDKN1A, MYC, PTGS2, FZD5, SPP1) were upregulated and functionally significant in muscle growth and differentiation. Notably, DPP6, CDKN1A, and FZD5 emerged as possible candidate genes linked to ADG variation. These findings enhance our understanding of genetic factors behind ADG variation in Hanwoo cattle, illuminating skeletal muscle mechanisms influencing ADG.

Karrow N, Mao Y. Identification and Classification of Long Non-Coding RNAs in the Mammary Gland of the Holstein Cow

The mammary glands, responsible for milk secretion, are regulated at a local level by various hormones, growth factors, non-coding RNAs, and other elements. Recent research has discovered the presence of lncRNAs in these glands, with suggestions that they may be essential for the maintenance and function of mammary glands. Besides directly controlling the gene and protein expression, lncRNAs are believed to play a significant part in numerous physiological and pathological processes. This study focused on examining the mammary gland tissues of Chinese Holstein cows, to identify and categorize long non-coding RNAs (lncRNAs). The research intended to distinguish lncRNAs in the mammary tissues of Holstein cows and contrast them between lactation and non-lactation periods. In this study, mammary gland tissues were sampled from three Holstein cows in early lactation (n = 3, 30 days postpartum) and non-lactation (n = 3, 315 days postpartum) on a large dairy farm in Jiangsu province. Mammary tissue samples were collected during early lactation and again during non-lactation. In total, we detected 1905 lncRNAs, with 57.3% being 500 bp and 612 intronic lncRNAs. The exon count for lncRNAs varied from 2 to 10. It was observed that 96 lncRNA expressions markedly differed between the two stages, with 83 genes being upregulated and 53 downregulated. Enrichment analysis results revealed that Gene Ontology (GO) analysis was primarily abundant in cellular processes. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that target genes were predominantly abundant in metabolic pathways, fatty acid biosynthesis, the immune system, and glycosphingolipid biosynthesis. This study analyzed the expression profile and characteristics of lncRNAs in the mammary gland tissues of Holstein cows during both lactation and non-lactation stages, forming a foundation for further investigation into the functional roles of lncRNAs in Holstein cows throughout lactation.

Integrated analysis of inflammatory mRNAs, miRNAs, and lncRNAs elucidates the molecular interactome behind bovine mastitis

Mastitis is known as intramammary inflammation, which has a multifactorial complex phenotype. However, the underlying molecular pathogenesis of mastitis remains poorly understood. In this study, we utilized a combination of RNA-seq and miRNA-seq techniques, along with computational systems biology approaches, to gain a deeper understanding of the molecular interactome involved in mastitis. We retrieved and processed one hundred transcriptomic libraries, consisting of 50 RNA-seq and 50 matched miRNA-seq data, obtained from milk-isolated monocytes of Holstein-Friesian cows, both infected with Streptococcus uberis and non-infected controls. Using the weighted gene co-expression network analysis (WGCNA) approach, we constructed co-expressed RNA-seq-based and miRNA-seq-based modules separately. Module-trait relationship analysis was then performed on the RNA-seq-based modules to identify highly-correlated modules associated with clinical traits of mastitis. Functional enrichment analysis was conducted to understand the functional behavior of these modules. Additionally, we assigned the RNA-seq-based modules to the miRNA-seq-based modules and constructed an integrated regulatory network based on the modules of interest. To enhance the reliability of our findings, we conducted further analyses, including hub RNA detection, protein-protein interaction (PPI) network construction, screening of hub-hub RNAs, and target prediction analysis on the detected modules. We identified a total of 17 RNA-seq-based modules and 3 miRNA-seq-based modules. Among the significant highly-correlated RNA-seq-based modules, six modules showed strong associations with clinical characteristics of mastitis. Functional enrichment analysis revealed that the turquoise module was directly related to inflammation persistence and mastitis development. Furthermore, module assignment analysis demonstrated that the blue miRNA-seq-based module post-transcriptionally regulates the turquoise RNA-seq-based module. We also identified a set of different RNAs, including hub-hub genes, hub-hub TFs (transcription factors), hub-hub lncRNAs (long non-coding RNAs), and hub miRNAs within the modules of interest, indicating their central role in the molecular interactome underlying the pathogenic mechanisms of S. uberis infection. This study provides a comprehensive insight into the molecular crosstalk between immunoregulatory mRNAs, miRNAs, and lncRNAs during S. uberis infection. These findings offer valuable directions for the development of molecular diagnosis and biological therapies for mastitis.

RNA-Seq Analysis of Peripheral Whole Blood from Dairy Bulls with High and Low Antibody-Mediated Immune Responses-A Preliminary Study

Enhancing the immune response through breeding is regarded as an effective strategy for improving animal health, as dairy cattle identified as high immune responders are reported to have a decreased prevalence of economically significant diseases. The identification of differentially expressed genes (DEGs) associated with immune responses might be an effective tool for breeding healthy dairy cattle. In this study, antibody-mediated immune responses (AMIRs) were induced by the immunization of hen egg white lysozyme (HEWL) in six Chinese Holstein dairy bulls divided into high- and low-AMIR groups based on their HEWL antibody level. Then, RNA-seq was applied to explore the transcriptome of peripheral whole blood between the two comparison groups. As a result, several major upregulated and downregulated genes were identified and attributed to the regulation of locomotion, tissue development, immune response, and detoxification. In addition, the result of the KEGG pathway analysis revealed that most DEGs were enriched in pathways related to disease, inflammation, and immune response, including antigen processing and presentation, Staphylococcus aureus infection, intestinal immune network for IgA production, cytokine-cytokine receptor interaction, and complement and coagulation cascades. Moreover, six genes (BOLA-DQA5, C5, CXCL2, HBA, LTF, and COL1A1) were validated using RT-qPCR, which may provide information for genomic selection in breeding programs. These results broaden the knowledge of the immune response mechanism in dairy bulls, which has strong implications for breeding cattle with an enhanced AMIR.

Review: Genetic mutations affecting bull fertility

Cattle are a well-suited "model organism" to study the genetic underpinnings of variation in male reproductive performance. The adoption of artificial insemination and genomic prediction in many cattle breeds provide access to microarray-derived genotypes and repeated measurements for semen quality and insemination success in several thousand bulls. Similar-sized mapping cohorts with phenotypes for male fertility are not available for most other species precluding powerful association testing. The repeated measurements of the artificial insemination bulls' semen quality enable the differentiation between transient and biologically relevant trait fluctuations, and thus, are an ideal source of phenotypes for variance components estimation and genome-wide association testing. Genome-wide case-control association testing involving bulls with either aberrant sperm quality or low insemination success revealed several causal recessive loss-of-function alleles underpinning monogenic reproductive disorders. These variants are routinely monitored with customised genotyping arrays in the male selection candidates to avoid the use of subfertile or infertile bulls for artificial insemination and natural service. Genome-wide association studies with quantitative measurements of semen quality and insemination success revealed quantitative trait loci for male fertility, but the underlying causal variants remain largely unknown. Moreover, these loci explain only a small part of the heritability of male fertility. Integrating genome-wide association studies with gene expression and other omics data from male reproductive tissues is required for the fine-mapping of candidate causal variants underlying variation in male reproductive performance in cattle.

Emerging roles of noncoding micro RNAs and circular RNAs in bovine mastitis: Regulation, breeding, diagnosis, and therapy

Bovine mastitis is one of the most troublesome and costly problems in the modern dairy industry, which is not only difficult to monitor, but can also cause economic losses while having significant implications on public health. However, efficacious preventative methods and therapy are still lacking. Moreover, new drugs and therapeutic targets are in increasing demand due to antibiotic restrictions. In recent years, noncoding RNAs have gained popularity as a topic in pathological and genetic studies. Meanwhile, there is growing evidence that they play a role in regulating various biological processes and developing novel treatment platforms. In light of this, this review focuses on two types of noncoding RNAs, micro RNAs and circular RNAs, and summarizes their characterizations, relationships, potential applications as selection markers, diagnostic or treatment targets and potential applications in RNA-based therapy, in order to shed new light on further research.

Single-Cell Chromatin Accessibility Data Combined with GWAS Improves Detection of Relevant Cell Types in 59 Complex Phenotypes

Several disease risk variants reside on non-coding regions of DNA, particularly in open chromatin regions of specific cell types. Identifying the cell types relevant to complex traits through the integration of chromatin accessibility data and genome-wide association studies (GWAS) data can help to elucidate the mechanisms of these traits. In this study, we created a collection of associations between the combinations of chromatin accessibility data (bulk and single-cell) with an array of 201 complex phenotypes. We integrated the GWAS data of these 201 phenotypes with bulk chromatin accessibility data from 137 cell types measured by DNase-I hypersensitive sequencing and found significant results (FDR adjusted p-value ≤ 0.05) for at least one cell type in 21 complex phenotypes, such as atopic dermatitis, Graves’ disease, and body mass index. With the integration of single-cell chromatin accessibility data measured by an assay for transposase-accessible chromatin with high-throughput sequencing (scATAC-seq), taken from 111 adult and 111 fetal cell types, the resolution of association was magnified, enabling the identification of further cell types. This resulted in the identification of significant correlations (FDR adjusted p-value ≤ 0.05) between 15 categories of single-cell subtypes and 59 phenotypes ranging from autoimmune diseases like Graves’ disease to cardiovascular traits like diastolic/systolic blood pressure.

Emerging Roles of Noncoding RNAs in Bovine Mastitis Diseases

Non-coding RNAs (ncRNAs) are an abundant class of RNA with varying nucleotide lengths. They have been shown to have great potential in eutherians/human disease diagnosis and treatments and are now gaining more importance for the improvement of diseases in livestock. To date, thousands of ncRNAs have been discovered in the bovine genome and the continuous advancement in deep sequencing technologies and various bioinformatics tools has enabled the elucidation of their roles in bovine health. Among farm animals' diseases, mastitis, a common inflammatory disease in cattle, has caused devastating economic losses to dairy farmers over the last few decades. Here, we summarize the biology of bovine mastitis and comprehensively discuss the roles of ncRNAs in different types of mastitis infection. Based on our findings and relevant literature, we highlighted various evidence of ncRNA roles in mastitis. Different approaches (in vivo versus in vitro) for exploring ncRNA roles in mastitis are emphasized. More particularly, the potential applications of emerging genome editing technologies, as well as integrated omics platforms for ncRNA studies and implications for mastitis are presented.

Comparative transcriptome in large-scale human and cattle populations

BACKGROUND

Cross-species comparison of transcriptomes is important for elucidating evolutionary molecular mechanisms underpinning phenotypic variation between and within species, yet to date it has been essentially limited to model organisms with relatively small sample sizes.

RESULTS

Here, we systematically analyze and compare 10,830 and 4866 publicly available RNA-seq samples in humans and cattle, respectively, representing 20 common tissues. Focusing on 17,315 orthologous genes, we demonstrate that mean/median gene expression, inter-individual variation of expression, expression quantitative trait loci, and gene co-expression networks are generally conserved between humans and cattle. By examining large-scale genome-wide association studies for 46 human traits (average n = 327,973) and 45 cattle traits (average n = 24,635), we reveal that the heritability of complex traits in both species is significantly more enriched in transcriptionally conserved than diverged genes across tissues.

CONCLUSIONS

In summary, our study provides a comprehensive comparison of transcriptomes between humans and cattle, which might help decipher the genetic and evolutionary basis of complex traits in both species.

An Integrative Genomic Prediction Approach for Predicting Buffalo Milk Traits by Incorporating Related Cattle QTLs

Background: The 90K Axiom Buffalo SNP Array is expected to improve and speed up various genomic analyses for the buffalo (Bubalus bubalis). Genomic prediction is an effective approach in animal breeding to improve selection and reduce costs. As buffalo genome research is lagging behind that of the cow and production records are also limited, genomic prediction performance will be relatively poor. To improve the genomic prediction in buffalo, we introduced a new approach (pGBLUP) for genomic prediction of six buffalo milk traits by incorporating QTL information from the cattle milk traits in order to help improve the prediction performance for buffalo. Results: In simulations, the pGBLUP could outperform BayesR and the GBLUP if the prior biological information (i.e., the known causal loci) was appropriate; otherwise, it performed slightly worse than BayesR and equal to or better than the GBLUP. In real data, the heritability of the buffalo genomic region corresponding to the cattle milk trait QTLs was enriched (fold of enrichment > 1) in four buffalo milk traits (FY270, MY270, PY270, and PM) when the EBV was used as the response variable. The DEBV as the response variable yielded more reliable genomic predictions than the traditional EBV, as has been shown by previous research. The performance of the three approaches (GBLUP, BayesR, and pGBLUP) did not vary greatly in this study, probably due to the limited sample size, incomplete prior biological information, and less artificial selection in buffalo. Conclusions: To our knowledge, this study is the first to apply genomic prediction to buffalo by incorporating prior biological information. The genomic prediction of buffalo traits can be further improved with a larger sample size, higher-density SNP chips, and more precise prior biological information.

Single-cell transcriptomic and chromatin accessibility analyses of dairy cattle peripheral blood mononuclear cells and their responses to lipopolysaccharide

Background

Gram-negative bacteria are important pathogens in cattle, causing severe infectious diseases, including mastitis. Lipopolysaccharides (LPS) are components of the outer membrane of Gram-negative bacteria and crucial mediators of chronic inflammation in cattle. LPS modulations of bovine immune responses have been studied before. However, the single-cell transcriptomic and chromatin accessibility analyses of bovine peripheral blood mononuclear cells (PBMCs) and their responses to LPS stimulation were never reported.

Results

We performed single-cell RNA sequencing (scRNA-seq) and single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) in bovine PBMCs before and after LPS treatment and demonstrated that seven major cell types, which included CD4 T cells, CD8 T cells, and B cells, monocytes, natural killer cells, innate lymphoid cells, and dendritic cells. Bioinformatic analyses indicated that LPS could increase PBMC cell cycle progression, cellular differentiation, and chromatin accessibility. Gene analyses further showed significant changes in differential expression, transcription factor binding site, gene ontology, and regulatory interactions during the PBMC responses to LPS. Consistent with the findings of previous studies, LPS induced activation of monocytes and dendritic cells, likely through their upregulated TLR4 receptor. NF-κB was observed to be activated by LPS and an increased transcription of an array of pro-inflammatory cytokines, in agreement that NF-κB is an LPS-responsive regulator of innate immune responses. In addition, by integrating LPS-induced differentially expressed genes (DEGs) with large-scale GWAS of 45 complex traits in Holstein, we detected trait-relevant cell types. We found that selected DEGs were significantly associated with immune-relevant health, milk production, and body conformation traits.

Conclusion

This study provided the first scRNAseq and scATAC-seq data for cattle PBMCs and their responses to the LPS stimulation to the best of our knowledge. These results should also serve as valuable resources for the future study of the bovine immune system and open the door for discoveries about immune cell roles in complex traits like mastitis at single-cell resolution.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08562-0.

Transcriptional atlas analysis from multiple tissues reveals the expression specificity patterns in beef cattle

Background

A comprehensive analysis of gene expression profiling across tissues can provide necessary information for an in-depth understanding of their biological functions. We performed a large-scale gene expression analysis and generated a high-resolution atlas of the transcriptome in beef cattle.

Results

Our transcriptome atlas was generated from 135 bovine tissues in adult beef cattle, covering 51 tissue types of major organ systems (e.g., muscular system, digestive system, immune system, reproductive system). Approximately 94.76% of sequencing reads were successfully mapped to the reference genome assembly ARS-UCD1.2. We detected a total of 60,488 transcripts, and 32% of them were not reported before. We identified 2654 housekeeping genes (HKGs) and 477 tissue-specific genes (TSGs) across tissues. Using weighted gene co-expression network analysis, we obtained 24 modules with 237 hub genes (HUBGs). Functional enrichment analysis showed that HKGs mainly maintain the basic biological activities of cells, while TSGs were involved in tissue differentiation and specific physiological processes. HKGs in bovine tissues were more conserved in terms of expression pattern as compared to TSGs and HUBGs among multiple species. Finally, we obtained a subset of tissue-specific differentially expressed genes (DEGs) between beef and dairy cattle and several functional pathways, which may be involved in production and health traits.

Conclusions

We generated a large-scale gene expression atlas across the major tissues in beef cattle, providing valuable information for enhancing genome assembly and annotation. HKGs, TSGs, and HUBGs further contribute to better understanding the biology and evolution of multiple tissues in cattle. DEGs between beef and dairy cattle also fill in the knowledge gaps about differential transcriptome regulation of bovine tissues underlying economically important traits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01269-4.

The Candidate Chromosomal Regions Responsible for Milk Yield of Cow: A GWAS Meta-Analysis

Milk yield (MY) is highly heritable and an economically important trait in dairy livestock species. To increase power to detect candidate genomic regions for this trait, we carried out a meta-analysis of genome-wide association studies (GWAS). In the present study, we identified 19 studies in PubMed for the meta-analysis. After review of the studies, 16 studies passed the filters for meta-analysis, and the number of chromosomes, detected markers and their positions, number of animals, and p-values were extracted from these studies and recorded. The final data set based on 16 GWAS studies had 353,698 cows and 3950 markers and was analyzed using METAL software. Our findings revealed 1712 significant (p-value < 2.5 × 10−6) genomic loci related to MY, with markers associated with MY found on all autosomes and sex chromosomes and the majority of them found on chromosome 14. Furthermore, gene ontology (GO) annotation was used to explore biological functions of the genes associated with MY; therefore, different regions of this chromosome may be suitable as genomic regions for further research into gene expression.

Multi-Omics Integration and Network Analysis Reveal Potential Hub Genes and Genetic Mechanisms Regulating Bovine Mastitis

Mastitis, inflammation of the mammary gland, is the most prevalent disease in dairy cattle that has a potential impact on profitability and animal welfare. Specifically designed multi-omics studies can be used to prioritize candidate genes and identify biomarkers and the molecular mechanisms underlying mastitis in dairy cattle. Hence, the present study aimed to explore the genetic basis of bovine mastitis by integrating microarray and RNA-Seq data containing healthy and mastitic samples in comparative transcriptome analysis with the results of published genome-wide association studies (GWAS) using a literature mining approach. The integration of different information sources resulted in the identification of 33 common and relevant genes associated with bovine mastitis. Among these, seven genes—CXCR1, HCK, IL1RN, MMP9, S100A9, GRO1, and SOCS3—were identified as the hub genes (highly connected genes) for mastitis susceptibility and resistance, and were subjected to protein-protein interaction (PPI) network and gene regulatory network construction. Gene ontology annotation and enrichment analysis revealed 23, 7, and 4 GO terms related to mastitis in the biological process, molecular function, and cellular component categories, respectively. Moreover, the main metabolic-signalling pathways responsible for the regulation of immune or inflammatory responses were significantly enriched in cytokine–cytokine-receptor interaction, the IL-17 signaling pathway, viral protein interaction with cytokines and cytokine receptors, and the chemokine signaling pathway. Consequently, the identification of these genes, pathways, and their respective functions could contribute to a better understanding of the genetics and mechanisms regulating mastitis and can be considered a starting point for future studies on bovine mastitis.

The statistical power of genome-wide association studies for threshold traits with different frequencies of causal variants

This study aimed to investigate the effects of incidence rate, heritability, and polygenic variance on the statistical power of genome-wide association studies (GWAS) for threshold traits. Different incidence rates of threshold trait (1, 3, 5, 10, 25, 40, 50, 60, 75 and 90%), heritability (10 and 25%), and polygenic variance ratio (0 and 25%) were simulated separately for common (MAF ≥ 0.05), low-frequency (0.05 > MAF ≥ 0.01), and rare (MAF < 0.01) variants. Association studies were performed by logistic and linear mixed models. The highest statistical powers were observed in common and low-frequency variants with an incidence of 25-50% and 10-40%, respectively, but for rare variants, the highest statistical power was observed at low incidence. For all causal variant frequencies, the estimated heritability decline with an increase in incidence rate. We found high statistical power for traits with high heritability. In contrast, those with a high polygenic variance ratio have lower statistical power to detect common causal variants using a linear mixed model. These results demonstrate that the incidence rate of threshold traits, heritability, and polygenic variance may affect the statistical power of GWAS. Therefore, it is recommended that the effect of incidence rate, heritability, and polygenic variance be considered in designing GWAS for threshold traits.

Johne's Disease in Dairy Cattle: An Immunogenetic Perspective

Johne's disease (JD), also known as paratuberculosis, is a severe production-limiting disease with significant economic and welfare implications for the global cattle industry. Caused by infection with Mycobacterium avium subspecies paratuberculosis (MAP), JD manifests as chronic enteritis in infected cattle. In addition to the economic losses and animal welfare issues associated with JD, MAP has attracted public health concerns with potential association with Crohn's disease, a human inflammatory bowel disease. The lack of effective treatment options, such as a vaccine, has hampered JD control resulting in its increasing global prevalence. The disease was first reported in 1895, but in recognition of its growing economic impact, extensive recent research facilitated by a revolution in technological approaches has led to significantly enhanced understanding of the immunological, genetic, and pathogen factors influencing disease pathogenesis. This knowledge has been derived from a variety of diverse models to elucidate host-pathogen interactions including in vivo and in vitro experimental infection models, studies measuring immune parameters in naturally-infected animals, and by studies conducted at the population level to enable the estimation of genetic parameters, and the identification of genetic markers and quantitative trait loci (QTL) putatively associated with susceptibility or resistance to JD. The main objectives of this review are to summarize these recent developments from an immunogenetics perspective and attempt to extract the principal and common findings emerging from this wealth of recent information. Based on these analyses, and in light of emerging technologies such as gene-editing, we conclude by discussing potential future avenues for effectively mitigating JD in cattle.

Identification of loci associated with susceptibility to Mycobacterium avium subsp. paratuberculosis infection in Holstein cattle using combinations of diagnostic tests and imputed whole-genome sequence data

Bovine paratuberculosis (PTB) is a chronic inflammatory disease caused by Mycobacterium avium susbp. paratuberculosis (MAP). Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) significantly associated with susceptibility to bovine PTB. The main objective of this study was to identify quantitative trait loci (QTLs) associated with MAP infection in Spanish Holstein cows (N = 983) using combinations of diagnostic tests and imputed whole-genome sequence (WGS) data. The infection status of these animals was defined by three diagnostic methods including ELISA for MAP-antibodies detection, and tissue culture and PCR for MAP detection. The 983 cows included in this study were genotyped with the Bovine MD SNP50 Bead Chip, and the corresponding genotypes were imputed to WGS using the 1,000 Bull genomes reference population. In total, 33.77 million SNP variants per animal were identified across the genome. Linear mixed models were used to calculate the heritability (h²) estimates for each diagnostic test and test combinations. Next, we performed a case-control GWAS using the imputed WGS datasets and the phenotypes and combinations of phenotypes with h² estimates > 0.080. After performing the GWAS, the test combinations that showed SNPs with a significant association (P_FDR ≤ 0.05), were the ELISA-tissue PCR-tissue culture, ELISA-tissue culture, and ELISA-tissue PCR. A total of twelve quantitative trait loci (QTLs) highly associated with MAP infection status were identified on the Bos taurus autosomes (BTA) 4, BTA5, BTA11, BTA12, BTA14, BTA23, BTA24, and BTA28, and some of these QTLs were linked to immune-modulating genes. The identified QTLs on BTA23 spanning from 18.81 to 22.95 Mb of the Bos taurus genome overlapped with several QTLs previously found to be associated with PTB susceptibility, bovine tuberculosis susceptibility, and clinical mastitis. The results from this study provide more clues regarding the molecular mechanisms underlying susceptibility to PTB infection in cattle and might be used to develop national genetic evaluations for PTB in Spain.

Data of bacterial community dynamics resulting from total rumen content exchange in beef cattle

OBJECTIVES

Extensive efforts have been made to characterize the rumen microbiome under various conditions. However, few studies have addressed the long-term impacts of ruminal microbiome dysbiosis and the extent of host control over microbiome stability. These data can also inform host-microbial symbioses. The objective was to develop preliminary data to measure the changes that occur in the rumen bacterial communities following a rumen content exchange to understand the effects major perturbations may impart upon the rumen microbiome, which may be host-driven.

DATA DESCRIPTION

We report here an initial rumen content exchange between two SimAngus (Simmental/Angus) non-pregnant, non-lactating cows of ~ 6 years of age weighing 603.4 ± 37.5 kg. To measure bacterial community succession and acclimation following the exchange, rumen content was collected via rumen cannula at the beginning of the study immediately prior to and following the rumen content exchange, and weekly for 12 weeks. The V4 hypervariable region of the 16S rRNA gene was targeted for DNA sequencing and bacterial analysis. Over 12 weeks, numerous genera and diversity varied, before partial return to pre-exchange metrics. These preliminary data help support potential host control for the rumen microbiome, aiding in efforts to define bovine host-microbe relationships.

A 12 kb multi-allelic copy number variation encompassing a GC gene enhancer is associated with mastitis resistance in dairy cattle

Clinical mastitis (CM) is an inflammatory disease occurring in the mammary glands of lactating cows. CM is under genetic control, and a prominent CM resistance QTL located on chromosome 6 was reported in various dairy cattle breeds. Nevertheless, the biological mechanism underpinning this QTL has been lacking. Herein, we mapped, fine-mapped, and discovered the putative causal variant underlying this CM resistance QTL in the Dutch dairy cattle population. We identified a ~12 kb multi-allelic copy number variant (CNV), that is in perfect linkage disequilibrium with a lead SNP, as a promising candidate variant. By implementing a fine-mapping and through expression QTL mapping, we showed that the group-specific component gene (GC), a gene encoding a vitamin D binding protein, is an excellent candidate causal gene for the QTL. The multiplicated alleles are associated with increased GC expression and low CM resistance. Ample evidence from functional genomics data supports the presence of an enhancer within this CNV, which would exert cis-regulatory effect on GC. We observed that strong positive selection swept the region near the CNV, and haplotypes associated with the multiplicated allele were strongly selected for. Moreover, the multiplicated allele showed pleiotropic effects for increased milk yield and reduced fertility, hinting that a shared underlying biology for these effects may revolve around the vitamin D pathway. These findings together suggest a putative causal variant of a CM resistance QTL, where a cis-regulatory element located within a CNV can alter gene expression and affect multiple economically important traits.

Integration of a single-step genome-wide association study with a multi-tissue transcriptome analysis provides novel insights into the genetic basis of wool and weight traits in sheep

BACKGROUND

Genetic improvement of wool and growth traits is a major goal in the sheep industry, but their underlying genetic architecture remains elusive. To improve our understanding of these mechanisms, we conducted a weighted single-step genome-wide association study (WssGWAS) and then integrated the results with large-scale transcriptome data for five wool traits and one growth trait in Merino sheep: mean fibre diameter (MFD), coefficient of variation of the fibre diameter (CVFD), crimp number (CN), mean staple length (MSL), greasy fleece weight (GFW), and live weight (LW).

RESULTS

Our dataset comprised 7135 individuals with phenotype data, among which 1217 had high-density (HD) genotype data (n = 372,534). The genotypes of 707 of these animals were imputed from the Illumina Ovine single nucleotide polymorphism (SNP) 54 BeadChip to the HD Array. The heritability of these traits ranged from 0.05 (CVFD) to 0.36 (MFD), and between-trait genetic correlations ranged from - 0.44 (CN vs. LW) to 0.77 (GFW vs. LW). By integrating the GWAS signals with RNA-seq data from 500 samples (representing 87 tissue types from 16 animals), we detected tissues that were relevant to each of the six traits, e.g. liver, muscle and the gastrointestinal (GI) tract were the most relevant tissues for LW, and leukocytes and macrophages were the most relevant cells for CN. For the six traits, 54 quantitative trait loci (QTL) were identified covering 81 candidate genes on 21 ovine autosomes. Multiple candidate genes showed strong tissue-specific expression, e.g. BNC1 (associated with MFD) and CHRNB1 (LW) were specifically expressed in skin and muscle, respectively. By conducting phenome-wide association studies (PheWAS) in humans, we found that orthologues of several of these candidate genes were significantly (FDR < 0.05) associated with similar traits in humans, e.g. BNC1 was significantly associated with MFD in sheep and with hair colour in humans, and CHRNB1 was significantly associated with LW in sheep and with body mass index in humans.

CONCLUSIONS

Our findings provide novel insights into the biological and genetic mechanisms underlying wool and growth traits, and thus will contribute to the genetic improvement and gene mapping of complex traits in sheep.

Short Time-Series Expression Transcriptome Data Reveal the Gene Expression Patterns of Dairy Cow Mammary Gland as Milk Yield Decreased Process

The existing research on dairy cow mammary gland genes is extensive, but there have been few reports about dynamic changes in dairy cow mammary gland genes as milk yield decrease. For the first time, transcriptome analysis based on short time-series expression miner (STEM) and histological observations were performed using the Holstein dairy cow mammary gland to explore gene expression patterns in this process of decrease (at peak, mid-, and late lactation). Histological observations suggested that the number of mammary acinous cells at peak/mid-lactation was significantly higher than that at mid-/late lactation, and the lipid droplets area secreted by dairy cows was almost unaltered across the three stages of lactation (p > 0.05). Totals of 882 and 1439 genes were differentially expressed at mid- and late lactation, respectively, compared to peak lactation. Function analysis showed that differentially expressed genes (DEGs) were mainly related to apoptosis and energy metabolism (fold change ≥ 2 or fold change ≤ 0.5, p-value ≤ 0.05). Transcriptome analysis based on STEM identified 16 profiles of differential gene expression patterns, including 5 significant profiles (false discovery rate, FDR ≤ 0.05). Function analysis revealed DEGs involved in milk fat synthesis were downregulated in Profile 0 and DEGs in Profile 12 associated with protein synthesis. These findings provide a foundation for future studies on the molecular mechanisms underlying mammary gland development in dairy cows.

Genome Wide Prediction, Mapping and Development of Genomic Resources of Mastitis Associated Genes in Water Buffalo

Water buffalo (Bubalus bubalis) are an important animal resource that contributes milk, meat, leather, dairy products, and power for plowing and transport. However, mastitis, a bacterial disease affecting milk production and reproduction efficiency, is most prevalent in populations having intensive selection for higher milk yield, especially where the inbreeding level is also high. Climate change and poor hygiene management practices further complicate the issue. The management of this disease faces major challenges, like antibiotic resistance, maximum residue level, horizontal gene transfer, and limited success in resistance breeding. Bovine mastitis genome wide association studies have had limited success due to breed differences, sample sizes, and minor allele frequency, lowering the power to detect the diseases associated with SNPs. In this work, we focused on the application of targeted gene panels (TGPs) in screening for candidate gene association analysis, and how this approach overcomes the limitation of genome wide association studies. This work will facilitate the targeted sequencing of buffalo genomic regions with high depth coverage required to mine the extremely rare variants potentially associated with buffalo mastitis. Although the whole genome assembly of water buffalo is available, neither mastitis genes are predicted nor TGP in the form of web-genomic resources are available for future variant mining and association studies. Out of the 129 mastitis associated genes of cattle, 101 were completely mapped on the buffalo genome to make TGP. This further helped in identifying rare variants in water buffalo. Eighty-five genes were validated in the buffalo gene expression atlas, with the RNA-Seq data of 50 tissues. The functions of 97 genes were predicted, revealing 225 pathways. The mastitis proteins were used for protein-protein interaction network analysis to obtain additional cross-talking proteins. A total of 1,306 SNPs and 152 indels were identified from 101 genes. Water Buffalo-MSTdb was developed with 3-tier architecture to retrieve mastitis associated genes having genomic coordinates with chromosomal details for TGP sequencing for mining of minor alleles for further association studies. Lastly, a web-genomic resource was made available to mine variants of targeted gene panels in buffalo for mastitis resistance breeding in an endeavor to ensure improved productivity and the reproductive efficiency of water buffalo.

Integrative genomics of the mammalian alveolar macrophage response to intracellular mycobacteria

Background

Bovine TB (bTB), caused by infection with Mycobacterium bovis, is a major endemic disease affecting global cattle production. The key innate immune cell that first encounters the pathogen is the alveolar macrophage, previously shown to be substantially reprogrammed during intracellular infection by the pathogen. Here we use differential expression, and correlation- and interaction-based network approaches to analyse the host response to infection with M. bovis at the transcriptome level to identify core infection response pathways and gene modules. These outputs were then integrated with genome-wide association study (GWAS) data sets to enhance detection of genomic variants for susceptibility/resistance to M. bovis infection.

Results

The host gene expression data consisted of RNA-seq data from bovine alveolar macrophages (bAM) infected with M. bovis at 24 and 48 h post-infection (hpi) compared to non-infected control bAM. These RNA-seq data were analysed using three distinct computational pipelines to produce six separate gene sets: 1) DE genes filtered using stringent fold-change and P-value thresholds (DEG-24: 378 genes, DEG-48: 390 genes); 2) genes obtained from expression correlation networks (CON-24: 460 genes, CON-48: 416 genes); and 3) genes obtained from differential expression networks (DEN-24: 339 genes, DEN-48: 495 genes). These six gene sets were integrated with three bTB breed GWAS data sets by employing a new genomics data integration tool—gwinteR. Using GWAS summary statistics, this methodology enabled detection of 36, 102 and 921 prioritised SNPs for Charolais, Limousin and Holstein-Friesian, respectively.

Conclusions

The results from the three parallel analyses showed that the three computational approaches could identify genes significantly enriched for SNPs associated with susceptibility/resistance to M. bovis infection. Results indicate distinct and significant overlap in SNP discovery, demonstrating that network-based integration of biologically relevant transcriptomics data can leverage substantial additional information from GWAS data sets. These analyses also demonstrated significant differences among breeds, with the Holstein-Friesian breed GWAS proving most useful for prioritising SNPS through data integration. Because the functional genomics data were generated using bAM from this population, this suggests that the genomic architecture of bTB resilience traits may be more breed-specific than previously assumed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07643-w.

Single-cell transcriptomic analyses of dairy cattle ruminal epithelial cells during weaning

Using the 10× Genomics Chromium Controller, we obtained scRNA-seq data of 5064 and 1372 individual cells from two Holstein calf ruminal epithelial tissues before and after weaning, respectively. We detected six distinct cell clusters, designated their cell types, and reported their marker genes. We then examined these clusters' underlining cell types and relationships by performing cell cycle, pseudotime trajectory, regulatory network, weighted gene co-expression network and gene ontology analyses. By integrating these cell marker genes with Holstein GWAS signals, we found they were enriched for animal production and body conformation traits. Finally, we confirmed their cell identities by comparing them with human and mouse stomach epithelial cells. This study presents an initial effort to implement single-cell transcriptomic analysis in cattle, and demonstrates ruminal tissue epithelial cell types and their developments during weaning, opening the door for new discoveries about tissue/cell type roles in complex traits at single-cell resolution.

An integrated approach in gene-expression landscape profiling to identify housekeeping and tissue-specific genes in cattle

Context High-throughput transcriptome sequencing (RNA-Seq) has been widely applied in cattle studies. Public databases such as the National Center for Biotechnology Information (NCBI) contain large collections of gene expression data from various cattle tissues that can be used in gene expression analysis research Aims This study was conducted to investigate patterns of transcriptome variation across tissues of cattle through large-scale identification of housekeeping genes (i.e. those crucial to maintaining basic cellular activity) and tissue-specific genes in cattle tissues. Methods Using data available in the NCBI Sequence Read Archive database, we analysed 1377 transcriptome data sequences from 60 bovine tissue types, identified tissue-specific and housekeeping genes, and set up a web-based bovine gene expression analysis tool. Key results We found 101 genes widely expressed in almost all tissue and screened out five housekeeping genes: RPL35A, eIF4A2, GAPDH, IPO5 and PAK2. Focusing on 12 major organs, we found 861 genes specifically expressing in these tissues. Furthermore, 187 significantly differentially expressed genes were found among six types of muscle tissues. All expression data were made available at our new website http://cattleExp.org, which can be freely accessed for future gene expression analyses. Conclusions The housekeeping genes and tissue-specific genes identified will provide more information for researchers studying gene expression in cattle. Implications The web-based cattle gene expression analysis tool will make it easy for researchers to access large public datasets. Users can easily access all publicly available RNA data and upload their own RNA-Seq data.

Genome-Wide Association Analysis Coupled With Transcriptome Analysis Reveals Candidate Genes Related to Salt Stress in Alfalfa (Medicago sativa L.)

Salt stress is the main abiotic factor affecting alfalfa yield and quality. However, knowledge of the genetic basis of the salt stress response in alfalfa is still limited. Here, a genome-wide association study (GWAS) involving 875,023 single-nucleotide polymorphisms (SNPs) was conducted on 220 alfalfa varieties under both normal and salt-stress conditions. Phenotypic analysis showed that breeding status and geographical origin play important roles in the alfalfa salt stress response. For germination ability under salt stress, a total of 15 significant SNPs explaining 9%-14% of the phenotypic variation were identified. For tolerance to salt stress in the seedling stage, a total of 18 significant SNPs explaining 12%-23% of the phenotypic variation were identified. Transcriptome analysis revealed 2,097 and 812 differentially expressed genes (DEGs) that were upregulated and 2,445 and 928 DEGs that were downregulated in the leaves and roots, respectively, under salt stress. Among these DEGs, many encoding transcription factors (TFs) were found, including MYB-, CBF-, NAC-, and bZIP-encoding genes. Combining the results of our GWAS analysis and transcriptome analysis, we identified a total of eight candidate genes (five candidate genes for tolerance to salt stress and three candidate genes for germination ability under salt stress). Two SNPs located within the upstream region of MsAUX28, which encodes an auxin response protein, were significantly associated with tolerance to salt stress. The two significant SNPs within the upstream region of MsAUX28 existed as three different haplotypes in this panel. Hap 1 (G/G, A/A) was under selection in the alfalfa domestication and improvement process.

Breastfeeding and the origins of health: Interdisciplinary perspectives and priorities

Breastfeeding and human milk (HM) are critically important to maternal, infant and population health. This paper summarizes the proceedings of a workshop that convened a multidisciplinary panel of researchers to identify key priorities and anticipated breakthroughs in breastfeeding and HM research, discuss perceived barriers and challenges to achieving these breakthroughs and propose a constructive action plan to maximize the impact of future research in this field. Priority research areas identified were as follows: (1) addressing low breastfeeding rates and inequities using mixed methods, community partnerships and implementation science approaches; (2) improving awareness of evidence-based benefits, challenges and complexities of breastfeeding and HM among health practitioners and the public; (3) identifying differential impacts of alternative modes of HM feeding including expressed/pumped milk, donor milk and shared milk; and (4) developing a mechanistic understanding of the health effects of breastfeeding and the contributors to HM composition and variability. Key barriers and challenges included (1) overcoming methodological limitations of epidemiological breastfeeding research and mechanistic HM research; (2) counteracting 'breastfeeding denialism' arising from negative personal breastfeeding experiences; (3) distinguishing and aligning research and advocacy efforts; and (4) managing real and perceived conflicts of interest. To advance research on breastfeeding and HM and maximize the reach and impact of this research, larger investments are needed, interdisciplinary collaboration is essential, and the scientific community must engage families and other stakeholders in research planning and knowledge translation.

Confirmed effects of candidate variants for milk production, udder health, and udder morphology in dairy cattle

Background

Over the last years, genome-wide association studies (GWAS) based on imputed whole-genome sequences (WGS) have been used to detect quantitative trait loci (QTL) and highlight candidate genes for important traits. However, in general this approach does not allow to validate the effects of candidate mutations or determine if they are truly causative for the trait(s) in question. To address these questions, we applied a two-step, within-breed GWAS approach on 15 traits (5 linked with milk production, 2 with udder health, and 8 with udder morphology) in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) cattle. We detected the most-promising candidate variants (CV) using imputed WGS of 2515 MON, 2203 NOR, and 6321 HOL bulls, and validated their effects in three younger populations of 23,926 MON, 9400 NOR, and 51,977 HOL cows.

Results

Bull sequence-based GWAS detected 84 QTL: 13, 10, and 30 for milk production traits; 3, 0, and 2 for somatic cell score (SCS); and 8, 2 and 16 for udder morphology traits, in MON, NOR, and HOL respectively. Five genomic regions with effects on milk production traits were shared among the three breeds whereas six (2 for production and 4 for udder morphology and health traits) had effects in two breeds. In 80 of these QTL, 855 CV were highlighted based on the significance of their effects and functional annotation. The subsequent GWAS on MON, NOR, and HOL cows validated 8, 9, and 23 QTL for production traits; 0, 0, and 1 for SCS; and 4, 1, and 8 for udder morphology traits, respectively. In 47 of the 54 confirmed QTL, the CV identified in bulls had more significant effects than single nucleotide polymorphisms (SNPs) from the standard 50K chip. The best CV for each validated QTL was located in a gene that was functionally related to production (36 QTL) or udder (9 QTL) traits.

Conclusions

Using this two-step GWAS approach, we identified and validated 54 QTL that included CV mostly located within functional candidate genes and explained up to 6.3% (udder traits) and 37% (production traits) of the genetic variance of economically important dairy traits. These CV are now included in the chip used to evaluate French dairy cattle and can be integrated into routine genomic evaluation.

A Fixed Cohort Field Study of Gene Expression in Circulating Leukocytes From Dairy Cows With and Without Mastitis

Specifically designed gene expression studies can be used to prioritize candidate genes and identify novel biomarkers affecting resilience against mastitis and other diseases in dairy cattle. The primary goal of this study was to assess whether specific peripheral leukocyte genes expressed differentially in a previous study of dairy cattle with postpartum disease, also would be expressed differentially in peripheral leukocytes from a diverse set of different dairy cattle with moderate to severe clinical mastitis. Four genes were selected for this study due to their differential expression in a previous transcriptomic analysis of circulating leukocytes from dairy cows with and without evidence of early postpartum disease. An additional 15 genes were included based on their cellular, immunologic, and inflammatory functions associated with resistance and tolerance to mastitis. This fixed cohort study was conducted on a conventional dairy in Washington state. Cows >50 days in milk (DIM) with mastitis (n = 12) were enrolled along with healthy cows (n = 8) selected to match the DIM and lactation numbers of mastitic cows. Blood was collected for a complete blood count (CBC), serum biochemistry, leukocyte isolation, and RNA extraction on the day of enrollment and twice more at 6 to 8-days intervals. Latent class analysis was performed to discriminate healthy vs. mastitic cows and to describe disease resolution. RNA samples were processed by the Primate Diagnostic Services Laboratory (University of Washington, Seattle, WA). Gene expression analysis was performed using the Nanostring System (Nanostring Technologies, Seattle, Washington, USA). Of the four genes (C5AR1, CATHL6, LCN2, and PGLYRP1) with evidence of upregulation in cows with mastitis, three of those genes (CATHL6, LCN2, and PGLYRP1) were investigated due to their previously identified association with postpartum disease. These genes are responsible for immunomodulatory molecules that selectively enhance or alter host innate immune defense mechanisms and modulate pathogen-induced inflammatory responses. Although further research is warranted to explain their functional mechanisms and bioactivity in cattle, our findings suggest that these conserved elements of innate immunity have the potential to bridge disease states and target tissues in diverse dairy populations.

Genome-Wide Association Study and Pathway Analysis for Female Fertility Traits in Iranian Holstein Cattle

Female fertility is an important trait that contributes to cow’s profitability and it can be improved by genomic information. The objective of this study was to detect genomic regions and variants affecting fertility traits in Iranian Holstein cattle. A data set comprised of female fertility records and 3,452,730 pedigree information from Iranian Holstein cattle were used to predict the breeding values, which were then employed to estimate the de-regressed proofs (DRP) of genotyped animals. A total of 878 animals with DRP records and 54k SNP markers were utilized in the genome-wide association study (GWAS). The GWAS was performed using a linear regression model with SNP genotype as a linear covariate. The results showed that an SNP on BTA19, ARS-BFGL-NGS-33473, was the most significant SNP associated with days from calving to first service. In total, [69] significant SNPs were located within 27 candidate genes. Novel potential candidate genes include OSTN, DPP6, EphA5, CADPS2, Rfc1, ADGRB3, Myo3a, C10H14orf93, KIAA1217, RBPJL, SLC18A2, GARNL3, NCALD, ASPH, ASIC2, OR3A1, CHRNB4, CACNA2D2, DLGAP1, GRIN2A and ME3. These genes are involved in different pathways relevant to female fertility and other characteristics in mammals. Gene set enrichment analysis showed that thirteen GO terms had significant overrepresentation of genes statistically associated with female fertility traits. The results of network analysis identified CCNB1 gene as a hub gene in the progesterone-mediated oocyte maturation pathway, significantly associated with age at first calving. The candidate genes identified in this study can be utilized in genomic tests to improve reproductive performance in Holstein cattle.

Genome-Wide Association Study Using Individual Single-Nucleotide Polymorphisms and Haplotypes for Erythrocyte Traits in Alpine Merino Sheep

Adaptation to high-altitude hypoxia is essential for domestic animals, such as yak, Tibetan chicken, and Tibetan sheep, living on high plateaus, as it ensures efficient oxygen absorption and utilization. Red blood cells are the primary medium for transporting oxygen in the blood. However, little is known about the genetic mechanism of erythrocyte traits. Genome-wide association studies (GWASs) based on single markers or haplotypes have identified potential mechanisms for genetic variation and quantitative traits. To identify loci associated with erythrocyte traits, we performed a GWAS based on the method of the single marker and haplotype in 498 Alpine Merino sheep for six erythrocyte traits: red blood cell count (RBC), hemoglobin (HGB), hematocrit (HCT), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and RBC volume distribution width coefficient of variation (RWD_CV). Forty-two significant single-nucleotide polymorphisms (SNPs) associated with the six erythrocyte traits were detected by means of a single-marker GWAS, and 34 significant haplotypes associated with five erythrocyte traits were detected by means of haplotype analysis. We identified six genes (DHCR24, SPATA9, FLI1, PLCB1, EFNB2, and SH2B3) as potential genes of interest via gene function annotations, location, and expression variation. In particular, FLI1 and PLCB1 were associated with hematopoiesis and erythropoiesis, respectively. These results provide a theoretical basis for analyzing erythrocyte traits and high-altitude hypoxia adaptation in Alpine Merino sheep and will be a useful reference for future studies of plateau-dwelling livestock.

Integrating RNA-Seq with GWAS reveals novel insights into the molecular mechanism underpinning ketosis in cattle

Background

Ketosis 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.

Results

We 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.

Conclusions

In 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.

Epigenomics and genotype-phenotype association analyses reveal conserved genetic architecture of complex traits in cattle and human

Background

Lack of comprehensive functional annotations across a wide range of tissues and cell types severely hinders the biological interpretations of phenotypic variation, adaptive evolution, and domestication in livestock. Here we used a combination of comparative epigenomics, genome-wide association study (GWAS), and selection signature analysis, to shed light on potential adaptive evolution in cattle.

Results

We cross-mapped 8 histone marks of 1300 samples from human to cattle, covering 178 unique tissues/cell types. By uniformly analyzing 723 RNA-seq and 40 whole genome bisulfite sequencing (WGBS) datasets in cattle, we validated that cross-mapped histone marks captured tissue-specific expression and methylation, reflecting tissue-relevant biology. Through integrating cross-mapped tissue-specific histone marks with large-scale GWAS and selection signature results, we for the first time detected relevant tissues and cell types for 45 economically important traits and artificial selection in cattle. For instance, immune tissues are significantly associated with health and reproduction traits, multiple tissues for milk production and body conformation traits (reflecting their highly polygenic architecture), and thyroid for the different selection between beef and dairy cattle. Similarly, we detected relevant tissues for 58 complex traits and diseases in humans and observed that immune and fertility traits in humans significantly correlated with those in cattle in terms of relevant tissues, which facilitated the identification of causal genes for such traits. For instance, PIK3CG, a gene highly specifically expressed in mononuclear cells, was significantly associated with both age-at-menopause in human and daughter-still-birth in cattle. ICAM, a T cell-specific gene, was significantly associated with both allergic diseases in human and metritis in cattle.

Conclusion

Collectively, our results highlighted that comparative epigenomics in conjunction with GWAS and selection signature analyses could provide biological insights into the phenotypic variation and adaptive evolution. Cattle may serve as a model for human complex traits, by providing additional information beyond laboratory model organisms, particularly when more novel phenotypes become available in the near future.

Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle

By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testis-specific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.

New Insights From Imputed Whole-Genome Sequence-Based Genome-Wide Association Analysis and Transcriptome Analysis: The Genetic Mechanisms Underlying Residual Feed Intake in Chickens

Poultry feed constitutes the largest cost in poultry production, estimated to be up to 70% of the total cost. Moreover, there is pressure on the poultry industry to increase production to meet the protein demand of humans and simultaneously reduce emissions to protect the environment. Therefore, improving feed efficiency plays an important role to improve profits and the environmental footprint in broiler production. In this study, using imputed whole-genome sequencing data, genome-wide association analysis (GWAS) was performed to identify single-nucleotide polymorphisms (SNPs) and genes associated with residual feed intake (RFI) and its component traits. Furthermore, a transcriptomic analysis between the high-RFI and the low-RFI groups was performed to validate the candidate genes from GWAS. The results showed that the heritability estimates of average daily gain (ADG), average daily feed intake (ADFI), and RFI were 0.29 (0.004), 0.37 (0.005), and 0.38 (0.004), respectively. Using imputed sequence-based GWAS, we identified seven significant SNPs and five candidate genes [MTSS I-BAR domain containing 1, folliculin, COP9 signalosome subunit 3, 5′,3′-nucleotidase (mitochondrial), and gametocyte-specific factor 1] associated with RFI, 20 significant SNPs and one candidate gene (inositol polyphosphate multikinase) associated with ADG, and one significant SNP and one candidate gene (coatomer protein complex subunit alpha) associated with ADFI. After performing a transcriptomic analysis between the high-RFI and the low-RFI groups, both 38 up-regulated and 26 down-regulated genes were identified in the high-RFI group. Furthermore, integrating regional conditional GWAS and transcriptome analysis, ras-related dexamethasone induced 1 was the only overlapped gene associated with RFI, which also suggested that the region (GGA14: 4767015–4882318) is a new quantitative trait locus associated with RFI. In conclusion, using imputed sequence-based GWAS is an efficient method to identify significant SNPs and candidate genes in chicken. Our results provide valuable insights into the genetic mechanisms of RFI and its component traits, which would further improve the genetic gain of feed efficiency rapidly and cost-effectively in the context of marker-assisted breeding selection.

Analyzing the genomic and transcriptomic architecture of milk traits in Murciano-Granadina goats

Background

In this study, we aimed to investigate the molecular basis of lactation as well as to identify the genetic factors that influence milk yield and composition in goats. To achieve these two goals, we have analyzed how the mRNA profile of the mammary gland changes in seven Murciano-Granadina goats at each of three different time points, i.e. 78 d (T1, early lactation), 216 d (T2, late lactation) and 285 d (T3, dry period) after parturition. Moreover, we have performed a genome-wide association study (GWAS) for seven dairy traits recorded in the 1st lactation of 822 Murciano-Granadina goats.

Results

The expression profiles of the mammary gland in the early (T1) and late (T2) lactation were quite similar (42 differentially expressed genes), while strong transcriptomic differences (more than one thousand differentially expressed genes) were observed between the lactating (T1/T2) and non-lactating (T3) mammary glands. A large number of differentially expressed genes were involved in pathways related with the biosynthesis of amino acids, cholesterol, triglycerides and steroids as well as with glycerophospholipid metabolism, adipocytokine signaling, lipid binding, regulation of ion transmembrane transport, calcium ion binding, metalloendopeptidase activity and complement and coagulation cascades. With regard to the second goal of the study, the performance of the GWAS allowed us to detect 24 quantitative trait loci (QTLs), including three genome-wide significant associations: QTL1 (chromosome 2, 130.72-131.01 Mb) for lactose percentage, QTL6 (chromosome 6, 78.90-93.48 Mb) for protein percentage and QTL17 (chromosome 17, 11.20 Mb) for both protein and dry matter percentages. Interestingly, QTL6 shows positional coincidence with the casein genes, which encode 80% of milk proteins.

Conclusions

The abrogation of lactation involves dramatic changes in the expression of genes participating in a broad array of physiological processes such as protein, lipid and carbohydrate metabolism, calcium homeostasis, cell death and tissue remodeling, as well as immunity. We also conclude that genetic variation at the casein genes has a major impact on the milk protein content of Murciano-Granadina goats.

Using SNP Weights Derived From Gene Expression Modules to Improve GWAS Power for Feed Efficiency in Pigs

The "large p small n" problem has posed a significant challenge in the analysis and interpretation of genome-wide association studies (GWAS). The use of prior information to rank genomic regions and perform SNP selection could increase the power of GWAS. In this study, we propose the use of gene expression data from RNA-Seq of multiple tissues as prior information to assign weights to SNP, select SNP based on a weight threshold, and utilize weighted hypothesis testing to conduct a GWAS. RNA-Seq libraries from hypothalamus, duodenum, ileum, and jejunum tissue of 30 pigs with divergent feed efficiency phenotypes were sequenced, and a three-way gene x individual x tissue clustering analysis was performed, using constrained tensor decomposition, to obtain a total of 10 gene expression modules. Loading values from each gene module were used to assign weights to 49,691 commercial SNP markers, and SNP were selected using a weight threshold, resulting in 10 SNP sets ranging in size from 101 to 955 markers. Weighted GWAS for feed intake in 4,200 pigs was performed separately for each of the 10 SNP sets. A total of 36 unique significant SNP associations were identified across the ten gene modules (SNP sets). For comparison, a standard unweighted GWAS using all 49,691 SNP was performed, and only 2 SNP were significant. None of the SNP from the unweighted analysis resided in known QTL related to swine feed efficiency (feed intake, average daily gain, and feed conversion ratio) compared to 29 (80.6%) in the weighted analyses, with 9 SNP residing in feed intake QTL. These results suggest that the heritability of feed intake is driven by many SNP that individually do not attain genome-wide significance in GWAS. Hence, the proposed procedure for prioritizing SNP based on gene expression data across multiple tissues provides a promising approach for improving the power of GWAS.

Digital gene expression analyses of mammary glands from meat ewes naturally infected with clinical mastitis

Clinical mastitis in sheep has gravely restrained production performance for a long time. Knowledge of mechanisms of its pathogenesis and resistance in meat sheep mammary gland with clinical mastitis are not yet understood, especially for clinical mastitis caused by natural infection. In this work, RNA-sequencing was firstly used to screen the differentially expressed genes (DEGs) in clinical mastitic mammary tissues (CMMTs) when compared with healthy mammary tissues (HMTs) from meat sheep flocks. We identified 420 DEGs including 316 upregulated and 104 downregulated genes in CMMTs. Gene ontology annotation revealed these DEGs were mainly engaged in immune response and inflammation response. Pathway enrichment showed they were primarily enriched in pathways relevant to inflammation, immune response and metabolism. Alternative splicing analysis showed most common differential splicing genes in CMMTs and HMTs were implicated in immune response. Immunostaining for three immune response-related proteins encoded by DEGs were mainly observed in mammary epithelium from both CMMTs and HMTs, and their positive signals were more intensive in CMMTs than those in HMTs. These findings provide experimental basis and reference for further researching the molecular genetic mechanisms, particularly immune defence mechanisms, of sheep mammary gland during clinical mastitis.

The GATK joint genotyping workflow is appropriate for calling variants in RNA-seq experiments

The Genome Analysis Toolkit (GATK) is a popular set of programs for discovering and genotyping variants from next-generation sequencing data. The current GATK recommendation for RNA sequencing (RNA-seq) is to perform variant calling from individual samples, with the drawback that only variable positions are reported. Versions 3.0 and above of GATK offer the possibility of calling DNA variants on cohorts of samples using the HaplotypeCaller algorithm in Genomic Variant Call Format (GVCF) mode. Using this approach, variants are called individually on each sample, generating one GVCF file per sample that lists genotype likelihoods and their genome annotations. In a second step, variants are called from the GVCF files through a joint genotyping analysis. This strategy is more flexible and reduces computational challenges in comparison to the traditional joint discovery workflow. Using a GVCF workflow for mining SNP in RNA-seq data provides substantial advantages, including reporting homozygous genotypes for the reference allele as well as missing data. Taking advantage of RNA-seq data derived from primary macrophages isolated from 50 cows, the GATK joint genotyping method for calling variants on RNA-seq data was validated by comparing this approach to a so-called “per-sample” method. In addition, pair-wise comparisons of the two methods were performed to evaluate their respective sensitivity, precision and accuracy using DNA genotypes from a companion study including the same 50 cows genotyped using either genotyping-by-sequencing or with the Bovine SNP50 Beadchip (imputed to the Bovine high density). Results indicate that both approaches are very close in their capacity of detecting reference variants and that the joint genotyping method is more sensitive than the per-sample method. Given that the joint genotyping method is more flexible and technically easier, we recommend this approach for variant calling in RNA-seq experiments.

Weighting sequence variants based on their annotation increases the power of genome-wide association studies in dairy cattle

Background

Genome-wide association studies (GWAS) are widely used to identify regions of the genome that harbor genetic determinants of quantitative traits. However, the multiple-testing burden from scanning tens of millions of whole-genome sequence variants reduces the power to identify associated variants, especially if sample size is limited. In addition, factors such as inaccuracy of imputation, complex linkage disequilibrium structures, and multiple closely-located causal variants may result in an identified causative mutation not being the most significant single nucleotide polymorphism in a particular genomic region. Therefore, the use of information from different sources, particularly variant annotations, was proposed to enhance the fine-mapping of causal variants. Here, we tested whether applying significance thresholds based on variant annotation categories increases the power of GWAS compared with a flat Bonferroni multiple-testing correction.

Results

Whole-genome sequence variants in dairy cattle were categorized according to type and predicted impact. Then, GWAS between markers and 17 quantitative traits were analyzed for enrichment for association of each annotation category. By using annotation categories that were determined with the variants effect predictor software and datasets indicating regions of open chromatin, “low impact” variants were found to be highly enriched. Moreover, when the variants annotated as “modifier” and not located at open chromatin regions were further classified into different types of potential regulatory elements, the high impact variants, moderate impact variants, variants located in the 3′ and 5′ untranslated regions, and variants located in potential non-coding RNA regions exhibited relatively more enrichment. In contrast, a similar study on human GWAS data reported that enrichment of association signals was highest with high impact variants. We observed an increase in power when these variant category-based significance thresholds were applied for GWAS results on stature in Nordic Holstein cattle, as more candidate genes from previous large GWAS meta-analysis for cattle stature were confirmed.

Conclusions

Use of variant category-based genome-wide significance thresholds can marginally increase the power to detect the candidate genes in cattle. With the continued improvements in annotation of the bovine genome, we anticipate that the growing usefulness of variant category-based significance thresholds will be demonstrated.

Electronic supplementary material

The online version of this article (10.1186/s12711-019-0463-9) contains supplementary material, which is available to authorized users.

Comparative Analysis of the Liver Transcriptome among Cattle Breeds Using RNA-seq

Global gene expression in liver transcriptome varies among cattle breeds. The present investigation was aimed to identify the differentially expressed genes (DEGs), metabolic gene networks and metabolic pathways in bovine liver transcriptome of young bulls. In this study, we comparatively analyzed the bovine liver transcriptome of dairy (Polish Holstein Friesian (HF); n = 6), beef (Hereford; n = 6), and dual purpose (Polish-Red; n = 6) cattle breeds. This study identified 895, 338, and 571 significant (p < 0.01) differentially expressed (DE) gene-transcripts represented as 745, 265, and 498 hepatic DE genes through the Polish-Red versus Hereford, Polish-HF versus Hereford, and Polish-HF versus Polish-Red breeds comparisons, respectively. By combining all breeds comparisons, 75 hepatic DE genes (p < 0.01) were identified as commonly shared among all the three breed comparisons; 70, 160, and 38 hepatic DE genes were commonly shared between the following comparisons: (i) Polish-Red versus Hereford and Polish-HF versus Hereford; (ii) Polish-Red versus Hereford and Polish-HF versus Polish-Red; and (iii) Polish-HF versus Hereford and Polish-HF versus Polish-Red, respectively. A total of 440, 82, and 225 hepatic DE genes were uniquely observed for the Polish-Red versus Hereford, Polish-HF versus Hereford, and Polish-Red versus Polish-HF comparisons, respectively. Gene ontology (GO) analysis identified top-ranked enriched GO terms (p < 0.01) including 17, 16, and 31 functional groups and 151, 61, and 140 gene functions that were DE in all three breed liver transcriptome comparisons. Gene network analysis identified several potential metabolic pathways involved in glutamine family amino-acid, triglyceride synthesis, gluconeogenesis, p38MAPK cascade regulation, cholesterol biosynthesis (Polish-Red versus Hereford); IGF-receptor signaling, catecholamine transport, lipoprotein lipase, tyrosine kinase binding receptor (Polish-HF versus Hereford), and PGF-receptor binding, (Polish-HF versus Polish-Red). Validation results showed that the relative expression values were consistent to those obtained by RNA-seq, and significantly correlated between the quantitative reverse transcription PCR (RT-qPCR) and RNA-seq (Pearson’s r  > 0.90). Our results provide new insights on bovine liver gene expressions among dairy versus dual versus beef breeds by identifying the large numbers of DEGs markers submitted to NCBI gene expression omnibus (GEO) accession number GSE114233, which can serve as useful genetic tools to develop the gene assays for trait-associated studies as well as, to effectively implement in genomics selection (GS) cattle breeding programs in Poland.

Genetic and epigenetic architecture of paternal origin contribute to gestation length in cattle

The length of gestation can affect offspring health and performance. Both maternal and fetal effects contribute to gestation length; however, paternal contributions to gestation length remain elusive. Using genome-wide association study (GWAS) in 27,214 Holstein bulls with millions of gestation records, here we identify nine paternal genomic loci associated with cattle gestation length. We demonstrate that these GWAS signals are enriched in pathways relevant to embryonic development, and in differentially methylated regions between sperm samples with long and short gestation length. We reveal that gestation length shares genetic and epigenetic architecture in sperm with calving ability, body depth, and conception rate. While several candidate genes are detected in our fine-mapping analysis, we provide evidence indicating ZNF613 as a promising candidate for cattle gestation length. Collectively, our findings support that the paternal genome and epigenome can impact gestation length potentially through regulation of the embryonic development.

Lingzhao Fang et al. studied the paternal genetic variants that affect gestational length in cattle. They found that paternal genes from pathways involved in embryonic development were associated with gestation length, and that these were often found in differentially methylated regions of the genome.

The genetic background of clinical mastitis in Holstein-Friesian cattle

Mastitis is an inflammatory disease of the mammary gland, which has a significant economic impact and is an animal welfare concern. This work examined the association between single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) with the incidence of clinical mastitis (CM). Using information from 16 half-sib pairs of Holstein-Friesian cows (32 animals in total) we searched for genomic regions that differed between a healthy (no incidence of CM) and a mastitis-prone (multiple incidences of CM) half-sib. Three cows with average sequence depth of coverage below 10 were excluded, which left 13 half-sib pairs available for comparisons. In total, 191 CNV regions were identified, which were deleted in a mastitis-prone cow, but present in its healthy half-sib and overlapped in at least nine half-sib pairs. These regions overlapped with exons of 46 genes, among which APP (BTA1), FOXL2 (BTA1), SSFA2 (BTA2), OTUD3 (BTA2), ADORA2A (BTA17), TXNRD2 (BTA17) and NDUFS6 (BTA20) have been reported to influence CM. Moreover, two duplicated CNV regions present in nine healthy individuals and absent in their mastitis-affected half-sibs overlapped with exons of a cholinergic receptor nicotinic α 10 subunit on BTA15 and a novel gene (ENSBTAG00000008519) on BTA27. One CNV region deleted in nine mastitis-affected sibs overlapped with two neighbouring long non-coding RNA sequences located on BTA12. Single nucleotide polymorphisms with differential genotypes between a healthy and a mastitis-affected sib included 17 polymorphisms with alternate alleles in eight affected and healthy half-sib families. Three of these SNPs were located introns of genes: MET (BTA04), RNF122 (BTA27) and WRN (BTA27). In summary, structural polymorphisms in form of CNVs, putatively play a role in susceptibility to CM. Specifically, sequence deletions have a greater effect on reducing resistance against mastitis, than sequence duplications have on increasing resistance against the disease.

Integrative Analysis of Transcriptome and GWAS Data to Identify the Hub Genes Associated With Milk Yield Trait in Buffalo

The mammary gland is the production organ in mammals that is of great importance for milk production and quality. However, characterization of the buffalo mammary gland transcriptome and identification of the valuable candidate genes that affect milk production is limited. Here, we performed the differential expressed genes (DEGs) analysis of mammary gland tissue on day 7, 50, 140, and 280 after calving and conducted gene-based genome-wide association studies (GWAS) of milk yield in 935 Mediterranean buffaloes. We then employed weighted gene co-expression network analysis (WGCNA) to identify specific modules and hub genes related to milk yield based on gene expression profiles and GWAS data. The results of the DEGs analysis showed that a total of 1,420 DEGs were detected across different lactation points. In the gene-based analysis, 976 genes were found to have genome-wide association (P ≤ 0.05) that could be defined as the nominally significant GWAS geneset (NSGG), 9 of which were suggestively associated with milk yield (P < 10⁻⁴). Using the WGCNA analysis, 544 and 225 genes associated with milk yield in the turquoise module were identified from DEGs and NSGG datasets, respectively. Several genes (including BNIPL, TUBA1C, C2CD4B, DCP1B, MAP3K5, PDCD11, SRGAP1, GDPD5, BARX2, SCARA3, CTU2, and RPL27A) were identified and considered as the hub genes because they were involved in multiple pathways related to milk production. Our findings provide an insight into the dynamic characterization of the buffalo mammary gland transcriptome, and these potential candidate genes may be valuable for future functional characterization of the buffalo mammary gland.

Novel insights into the genetic basis of buffalo reproductive performance

Background

Fertility is a complex trait that has a major impact on the development of the buffalo industry. Genome-wide association study (GWAS) has increased the ability to detect genes influencing complex traits, and many important genes related to reproductive traits have been identified in ruminants. However, reproductive traits are influenced by many factors. The development of the follicle is one of the most important internal processes affecting fertility. Genes found by GWAS to be associated with follicular development may directly affect fertility. The present study combined GWAS and RNA-seq of follicular granulosa cells to identify important genes which may affect fertility in the buffalo.

Results

The 90 K Affymetrix Axiom Buffalo SNP Array was used to identify the SNPs, genomic regions, and genes that were associated with reproductive traits. A total of 40 suggestive loci (related to 28 genes) were identified to be associated with six reproductive traits (first, second and third calving age, calving interval, the number of services per conception and open days). Interestingly, the mRNA expressions of 25 of these genes were also observed in buffalo follicular granulosa cells. The IGFBP7 gene showed high level of expression during whole antral follicle growth. The knockdown of IGFBP7 in buffalo granulosa cells promoted cell apoptosis and hindered cell proliferation, and increased the production of progesterone and estradiol. Furthermore, a notable signal was detected at 2.3–2.7 Mb on the equivalent of bovine chromosome 5 associated with age at second calving, calving interval, and open days.

Conclusions

The genes associated with buffalo reproductive traits in this study may have effect on fertility by regulating of follicular growth. These results may have important implications for improving buffalo breeding programs through application of genomic information.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5208-6) contains supplementary material, which is available to authorized users.