Genome-Wide Association Studies for Methane Production in Dairy Cattle.
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ABSTRACT:
SUBMITTER: Calderon-Chagoya R
PROVIDER: S-EPMC6969927 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Mastitis is one of the most frequently encountered diseases in dairy cattle, negatively affecting animal welfare and milk production. For this reason, contributions to understanding its genomic architecture are of great interest. Genome-wide association studies (GWAS) have identified multiple loci associated with somatic cell score (SCS) and mastitis in cattle. However, most of the studies have been conducted in different parts of the world on various breeds, and none of the investigations have studied the genetic architecture of mastitis in Romanian dairy cattle breeds up to this point in time. In this study, we report the first GWAS for SCS in dairy cattle breeds from Romania. For GWAS, we used an Axiom Bovine v3 SNP-chip (>63,000 Single Nucleotide Polymorphism -SNPs) and 33,330 records from 690 cows belonging to Romanian Spotted (RS) and Romanian Brown (RB) cattle. The results found one SNP significantly associated with SCS in the RS breed and 40 suggestive SNPs with -log10 (p) from 4 to 4.9 for RS and from 4 to 5.4 in RB. From these, 14 markers were located near 12 known genes (AKAP8, CLHC1, MEGF10, SATB2, GATA6, SPATA6, COL12A1, EPS8, LUZP2, RAMAC, IL12A and ANKRD55) in RB cattle, 3 markers were close to ZDHHC19, DAPK1 and MMP7 genes, while one SNP overlapped the HERC3 gene in RS cattle. Four genes (HERC3, LUZP2, AKAP8 and MEGF10) associated with SCS in this study were previously reported in different studies. The most significant SNP (rs110749552) associated with SCS was located within the HERC3 gene. In both breeds, the SNPs and position of association signals were distinct among the three parities, denoting that mastitis is controlled by different genes that are dependent according to parity. The current results contribute to an expansion in the body of knowledge regarding the proportion of genetic variability explained by SNPs for SCS in dairy cattle.
| S-EPMC8535694 | biostudies-literature
Project description:Most single nucleotide polymorphisms (SNPs) detected by genome-wide association studies (GWAS), explain only a small fraction of phenotypic variation. Pathway-based GWAS were proposed to improve the proportion of genes for some human complex traits that could be explained by enriching a mass of SNPs within genetic groups. However, few attempts have been made to describe the quantitative traits in domestic animals. In this study, we used a dataset with approximately 7,700,000 SNPs from 807 Simmental cattle and analyzed live weight and longissimus muscle area using a modified pathway-based GWAS method to orthogonalise the highly linked SNPs within each gene using principal component analysis (PCA). As a result, of the 262 biological pathways of cattle collected from the KEGG database, the gamma aminobutyric acid (GABA)ergic synapse pathway and the non-alcoholic fatty liver disease (NAFLD) pathway were significantly associated with the two traits analyzed. The GABAergic synapse pathway was biologically applicable to the traits analyzed because of its roles in feed intake and weight gain. The proposed method had high statistical power and a low false discovery rate, compared to those of the smallest P-value and SNP set enrichment analysis methods.
| S-EPMC4682090 | biostudies-other
Project description:Sole ulcers (SU) and white line disease (WLD) are noninfectious claw lesions that arise due to compromised horn production and are common causes of lameness in dairy cattle, imposing welfare and profitability concerns. The low to moderate heritability estimates of SU and WLD susceptibility indicate that genetic selection could reduce their prevalence. To identify loci associated with SU and WLD susceptibility, generalized linear mixed model (GLMM) regression and random forest (RF) genome-wide association studies (GWAS) were performed. Cows from five commercial dairies in California were classified as sound controls having no instances of lameness and above six years of age (n = 102) or cases having SU (n = 152), WLD (n = 117), SU and/or WLD (SU+WLD, n = 198), or any type of noninfectious claw lesion (n = 217). Top SNPs were defined as those passing Bonferroni-corrected suggestive and significance thresholds in the GLMM analysis or those that a validated RF model considered important. Effects of top SNPs were quantified using Bayesian estimation. Linkage disequilibrium (LD) blocks defined by top SNPs were explored for candidate genes and previously identified, functionally relevant quantitative trait loci. The GLMM GWAS revealed regions of association on BTA8 for SU and BTA13 common to WLD, SU+WLD, and noninfectious claw lesions. Bayesian estimation of effect sizes indicated that these SNPs had effects significantly different from zero, indicating their small but notable contribution to susceptibility. Promising candidate genes identified in these regions were involved in wound healing, skin lesions, bone growth and mineralization, adipose tissue, and keratinization. The LD block defined by the most significant SNP on BTA8 for SU included a SNP previously reported to be associated with SU. The RF models were overfitted, indicating that SNP effects were very small and thereby preventing meaningful interpretation of SNPs with the highest importance values and downstream analyses. These findings suggested that variants associated with a variety of physiological systems may contribute to susceptibility for noninfectious claw lesions, demonstrating the complexity of genetic predisposition.
2021-07-23 | GSE165945 | GEO
Project description:BackgroundGenome-wide association studies (GWAS) are a powerful tool for detecting genomic regions explaining variation in phenotype. The objectives of the present study were to identify or refine the positions of genomic regions affecting milk production, milk components and fertility traits in Canadian Holstein cattle, and to use these positions to identify genes and pathways that may influence these traits.ResultSeveral QTL regions were detected for milk production (MILK), fat production (FAT), protein production (PROT) and fat and protein deviation (FATD, PROTD respectively). The identified QTL regions for production traits (including milk production) support previous findings and some overlap with genes with known relevant biological functions identified in earlier studies such as DGAT1 and CPSF1. A significant region on chromosome 21 overlapping with the gene FAM181A and not previous linked to fertility in dairy cattle was identified for the calving to first service interval and days open. A functional enrichment analysis of the GWAS results yielded GO terms consistent with the specific phenotypes tested, for example GO terms GO:0007595 (lactation) and GO:0043627 (response to estrogen) for milk production (MILK), GO:0051057 (positive regulation of small GTPase mediated signal transduction) for fat production (FAT), GO:0040019 (positive regulation of embryonic development) for first service to calving interval (CTFS) and GO:0043268 (positive regulation of potassium ion transport) for days open (DO). In other cases the connection between the enriched GO terms and the traits were less clear, for example GO:0003279 (cardiac septum development) for FAT and GO:0030903 (notochord development) for DO trait.ConclusionThe chromosomal regions and enriched pathways identified in this study confirm several previous findings and highlight new regions and pathways that may contribute to variation in production or fertility traits in dairy cattle.
| S-EPMC4901445 | biostudies-literature
Project description:Sole ulcers (SUs) and white line disease (WLD) are two common noninfectious claw lesions (NICL) that arise due to a compromised horn production and are frequent causes of lameness in dairy cattle, imposing welfare and profitability concerns. Low to moderate heritability estimates of SU and WLD susceptibility indicate that genetic selection could reduce their prevalence. To identify the susceptibility loci for SU, WLD, SU and/or WLD, and any type of noninfectious claw lesion, genome-wide association studies (GWAS) were performed using generalized linear mixed model (GLMM) regression, chunk-based association testing (CBAT), and a random forest (RF) approach. Cows from five commercial dairies in California were classified as controls having no lameness records and ≥6 years old (n = 102) or cases having SU (n = 152), WLD (n = 117), SU and/or WLD (SU + WLD, n = 198), or any type of noninfectious claw lesion (n = 217). The top single nucleotide polymorphisms (SNPs) were defined as those passing the Bonferroni-corrected suggestive and significance thresholds in the GLMM analysis or those that a validated RF model considered important. Effects of the top SNPs were quantified using Bayesian estimation. Linkage disequilibrium (LD) blocks defined by the top SNPs were explored for candidate genes and previously identified, functionally relevant quantitative trait loci. The GLMM and CBAT approaches revealed the same regions of association on BTA8 for SU and BTA13 common to WLD, SU + WLD, and NICL. These SNPs had effects significantly different from zero, and the LD blocks they defined explained a significant amount of phenotypic variance for each dataset (6.1-8.1%, p < 0.05), indicating the small but notable contribution of these regions to susceptibility. These regions contained candidate genes involved in wound healing, skin lesions, bone growth and mineralization, adipose tissue, and keratinization. The LD block defined by the most significant SNP on BTA8 for SU included a SNP previously associated with SU. The RF models were overfitted, indicating that the SNP effects were very small, thereby preventing meaningful interpretation of SNPs and any downstream analyses. These findings suggested that variants associated with various physiological systems may contribute to susceptibility for NICL, demonstrating the complexity of genetic predisposition.
| S-EPMC8194352 | biostudies-literature
Project description:BackgroundMethane emission by ruminants has contributed considerably to the global warming and understanding the genomic architecture of methane production may help livestock producers to reduce the methane emission from the livestock production system. The goal of our study was to identify genomic regions affecting the predicted methane emission (PME) from volatile fatty acids (VFAs) indicators and VFA traits using imputed whole-genome sequence data in Iranian Holstein cattle.ResultsBased on the significant-association threshold (p < 5 × 10- 8), 33 single nucleotide polymorphisms (SNPs) were detected for PME per kg milk (n = 2), PME per kg fat (n = 14), and valeric acid (n = 17). Besides, 69 genes were identified for valeric acid (n = 18), PME per kg milk (n = 4) and PME per kg fat (n = 47) that were located within 1 Mb of significant SNPs. Based on the gene ontology (GO) term analysis, six promising candidate genes were significantly clustered in organelle organization (GO:0004984, p = 3.9 × 10- 2) for valeric acid, and 17 candidate genes significantly clustered in olfactory receptors activity (GO:0004984, p = 4 × 10- 10) for PME traits. Annotation results revealed 31 quantitative trait loci (QTLs) for milk yield and its components, body weight, and residual feed intake within 1 Mb of significant SNPs.ConclusionsOur results identified 33 SNPs associated with PME and valeric acid traits, as well as 17 olfactory receptors activity genes for PME traits related to feed intake and preference. Identified SNPs were close to 31 QTLs for milk yield and its components, body weight, and residual feed intake traits. In addition, these traits had high correlations with PME trait. Overall, our findings suggest that marker-assisted and genomic selection could be used to improve the difficult and expensive-to-measure phenotypes such as PME. Moreover, prediction of methane emission by VFA indicators could be useful for increasing the size of reference population required in genome-wide association studies and genomic selection.
| S-EPMC7684878 | biostudies-literature
Project description:BackgroundGenome wide association studies (GWAS) in most cattle breeds result in large genomic intervals of significant associations making it difficult to identify causal mutations. This is due to the extensive, low-level linkage disequilibrium within a cattle breed. As there is less linkage disequilibrium across breeds, multibreed GWAS may improve precision of causal variant mapping. Here we test this hypothesis in a Holstein and Jersey cattle data set with 17,925 individuals with records for production and functional traits and 632,003 SNP markers.ResultsBy using a cross validation strategy within the Holstein and Jersey data sets, we were able to identify and confirm a large number of QTL. As expected, the precision of mapping these QTL within the breeds was limited. In the multibreed analysis, we found that many loci were not segregating in both breeds. This was partly an artefact of power of the experiments, with the number of QTL shared between the breeds generally increasing with trait heritability. False discovery rates suggest that the multibreed analysis was less powerful than between breed analyses, in terms of how much genetic variance was explained by the detected QTL. However, the multibreed analysis could more accurately pinpoint the location of the well-described mutations affecting milk production such as DGAT1. Further, the significant SNP in the multibreed analysis were significantly enriched in genes regions, to a considerably greater extent than was observed in the single breed analyses. In addition, we have refined QTL on BTA5 and BTA19 to very small intervals and identified a small number of potential candidate genes in these, as well as in a number of other regions.ConclusionWhere QTL are segregating across breed, multibreed GWAS can refine these to reasonably small genomic intervals. However, such QTL appear to represent only a fraction of the genetic variation. Our results suggest a significant proportion of QTL affecting milk production segregate within rather than across breeds, at least for Holstein and Jersey cattle.
| S-EPMC3905911 | biostudies-literature
Project description:BackgroundGenome-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.ResultsWhole-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.ConclusionsUse 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.
| S-EPMC6511139 | biostudies-literature
Project description:BackgroundBovine tuberculosis is a significant veterinary and financial problem in many parts of the world. Although many factors influence infection and progression of the disease, there is a host genetic component and dissection of this may enlighten on the wider biology of host response to tuberculosis. However, a binary phenotype of presence/absence of infection presents a noisy signal for genomewide association study.Methodology/principal findingsWe calculated a composite phenotype of genetic merit for TB susceptibility based on disease incidence in daughters of elite sires used for artificial insemination in the Irish dairy herd. This robust measure was compared with 44,426 SNP genotypes in the most informative 307 subjects in a genome wide association analysis. Three SNPs in a 65 kb genomic region on BTA 22 were associated (i.e. p<10(-5), peaking at position 59588069, p?=?4.02×10(-6)) with tuberculosis susceptibility.Conclusions/significanceA genomic region on BTA 22 was suggestively associated with tuberculosis susceptibility; it contains the taurine transporter gene SLC6A6, or TauT, which is known to function in the immune system but has not previously been investigated for its role in tuberculosis infection.
| S-EPMC3280253 | biostudies-literature
Project description:BackgroundKetosis in dairy cattle has been shown to cause a high morbidity in the farm and substantial financial losses to dairy farmers. Ketosis symptoms, however, are difficult to identify, therefore, the amount of ketone bodies (mainly β-hydroxybutyric acid, BHB) is used as an indicator of subclinical ketosis in cows. It has also been shown that milk BHB concentrations have a strong correlation with ketosis in dairy cattle. Mid-infrared spectroscopy (MIR) has recently became a fast, cheap and high-throughput method for analyzing milk components. The aim of this study was to perform a genome-wide association study (GWAS) on the MIR-predicted milk BHB to identify genomic regions, genes and pathways potentially affecting subclinical ketosis in North American Holstein dairy cattle.ResultsSeveral significant regions were identified associated with MIR-predicted milk BHB concentrations (indicator of subclinical ketosis) in the first lactation (SCK1) and second and later lactations (SCK2) in Holstein dairy cows. The strongest association was located on BTA6 for SCK1 and BTA14 on SCK2. Several SNPs on BTA6 were identified in regions and variants reported previously to be associated with susceptibility to ketosis and clinical mastitis in Jersey and Holstein dairy cattle, respectively. One highly significant SNP on BTA14 was found within the DGAT1 gene with known functions on fat metabolism and inflammatory response in dairy cattle. A region on BTA6 and three SNPs on BTA20 were found to overlap between SCK1 and SCK2. However, a novel region on BTA20 (55-63 Mb) for SCK2 was also identified, which was not reported in previous association studies. Enrichment analysis of the list of candidate genes within the identified regions for MIR-predicted milk BHB concentrations yielded molecular functions and biological processes that may be involved in the inflammatory response and lipid metabolism in dairy cattle.ConclusionsThe results of this study confirmed several SNPs and genes identified in previous studies as associated with ketosis susceptibility and immune response, and also found a novel region that can be used for further analysis to identify causal variations and key regulatory genes that affect clinical/ subclinical ketosis.
| S-EPMC6636026 | biostudies-literature