Sequence-based GWAS and post-GWAS analyses reveal a key role of SLC37A1, ANKH, and regulatory regions on bovine milk mineral content.
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ABSTRACT:
SUBMITTER: Sanchez MP
PROVIDER: S-EPMC8024349 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe power of genome-wide association studies (GWAS) is often limited by the sample size available for the analysis. Milk fatty acid (FA) traits are scarcely recorded due to expensive and time-consuming analytical techniques. Combining multi-population datasets can enhance the power of GWAS enabling detection of genomic region explaining medium to low proportions of the genetic variation. GWAS often detect broader genomic regions containing several positional candidate genes making it difficult to untangle the causative candidates. Post-GWAS analyses with data on pathways, ontology and tissue-specific gene expression status might allow prioritization among positional candidate genes.ResultsMulti-population GWAS for 16 FA traits quantified using gas chromatography (GC) in sample populations of the Chinese, Danish and Dutch Holstein with high-density (HD) genotypes detects 56 genomic regions significantly associated to at least one of the studied FAs; some of which have not been previously reported. Pathways and gene ontology (GO) analyses suggest promising candidate genes on the novel regions including OSBPL6 and AGPS on Bos taurus autosome (BTA) 2, PRLH on BTA 3, SLC51B on BTA 10, ABCG5/8 on BTA 11 and ALG5 on BTA 12. Novel genes in previously known regions, such as FABP4 on BTA 14, APOA1/5/7 on BTA 15 and MGST2 on BTA 17, are also linked to important FA metabolic processes.ConclusionIntegration of multi-population GWAS and enrichment analyses enabled detection of several novel genomic regions, explaining relatively smaller fractions of the genetic variation, and revealed highly likely candidate genes underlying the effects. Detection of such regions and candidate genes will be crucial in understanding the complex genetic control of FA metabolism. The findings can also be used to augment genomic prediction models with regions collectively capturing most of the genetic variation in the milk FA traits.
| S-EPMC6404302 | biostudies-literature
Project description:MotivationThe number of significantly associated regions reported in genome-wide association studies (GWAS) for polygenic traits typically increases with sample size. A traditional tool for quality control and identification of significant regions has been a visual inspection of how significant and correlated genetic variants cluster within a region. However, while inspecting hundreds of regions, this subjective method can misattribute significance to some loci or neglect others that are significant.ResultsThe GWAS quality score (GQS) identifies suspicious regions and prevents erroneous interpretations with an objective, quantitative and automated method. The GQS assesses all measured single nucleotide polymorphisms (SNPs) that are linked by inheritance to each other [linkage disequilibrium (LD)] and compares the significance of trait association of each SNP to its LD value for the reported index SNP. A GQS value of 1.0 ascribes a high level of confidence to the entire region and its underlying gene(s), while GQS values <1.0 indicate the need to closely inspect the outliers. We applied the GQS to published and non-published genome-wide summary statistics and report suspicious regions requiring secondary inspection while supporting the majority of reported regions from large-scale published meta-analyses.Availability and implementationThe GQS code/scripts can be cloned from GitHub (https://github.com/Xswapnil/GQS/). The analyst can use whole-genome summary statistics to estimate GQS for each defined region. We also provide an online tool (http://35.227.18.38/) that gives access to the GQS. The quantitative measure of quality attributes by GQS and its visualization is an objective method that enhances the confidence of each genomic hit.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC9891241 | biostudies-literature
Project description:BACKGROUND:Lactose provides an easily-digested energy source for neonates, and is the primary carbohydrate in milk in most species. Bovine lactose is also a key component of many human food products. However, compared to analyses of other milk components, the genetic control of lactose has been little studied. Here we present the first GWAS focussed on analysis of milk lactose traits. RESULTS:Using a discovery population of 12,000 taurine dairy cattle, we detail 27 QTL for lactose concentration and yield, and subsequently validate the effects of 26 of these loci in a distinct population of 18,000 cows. We next present data implicating causative genes and variants for these QTL. Fine mapping of these regions using imputed, whole genome sequence-resolution genotypes reveals protein-coding candidate causative variants affecting the ABCG2, DGAT1, STAT5B, KCNH4, NPFFR2 and RNF214 genes. Eleven of the remaining QTL appear to be driven by regulatory effects, suggested by the presence of co-locating, co-segregating eQTL discovered using mammary RNA sequence data from a population of 357 lactating cows. Pathway analysis of genes representing all lactose-associated loci shows significant enrichment of genes located in the endoplasmic reticulum, with functions related to ion channel activity mediated through the LRRC8C, P2RX4, KCNJ2 and ANKH genes. A number of the validated QTL are also found to be associated with additional milk volume, fat and protein phenotypes. CONCLUSIONS:Overall, these findings highlight novel candidate genes and variants involved in milk lactose regulation, whose impacts on membrane transport mechanisms reinforce the key osmo-regulatory roles of lactose in milk.
| S-EPMC5731188 | biostudies-literature
Project description:BackgroundMilk quality in dairy cattle is routinely assessed via analysis of mid-infrared (MIR) spectra; this approach can also be used to predict the milk's cheese-making properties (CMP) and composition. When this method of high-throughput phenotyping is combined with efficient imputations of whole-genome sequence data from cows' genotyping data, it provides a unique and powerful framework with which to carry out genomic analyses. The goal of this study was to use this approach to identify genes and gene networks associated with milk CMP and composition in the Montbéliarde breed.ResultsMilk cheese yields, coagulation traits, milk pH and contents of proteins, fatty acids, minerals, citrate, and lactose were predicted from MIR spectra. Thirty-six phenotypes from primiparous Montbéliarde cows (1,442,371 test-day records from 189,817 cows) were adjusted for non-genetic effects and averaged per cow. 50 K genotypes, which were available for a subset of 19,586 cows, were imputed at the sequence level using Run6 of the 1000 Bull Genomes Project (comprising 2333 animals). The individual effects of 8.5 million variants were evaluated in a genome-wide association study (GWAS) which led to the detection of 59 QTL regions, most of which had highly significant effects on CMP and milk composition. The results of the GWAS were further subjected to an association weight matrix and the partial correlation and information theory approach and we identified a set of 736 co-associated genes. Among these, the well-known caseins, PAEP and DGAT1, together with dozens of other genes such as SLC37A1, ALPL, MGST1, SEL1L3, GPT, BRI3BP, SCD, GPAT4, FASN, and ANKH, explained from 12 to 30% of the phenotypic variance of CMP traits. We were further able to identify metabolic pathways (e.g., phosphate and phospholipid metabolism and inorganic anion transport) and key regulator genes, such as PPARA, ASXL3, and bta-mir-200c that are functionally linked to milk composition.ConclusionsBy using an approach that integrated GWAS with network and pathway analyses at the whole-genome sequence level, we propose candidate variants that explain a substantial proportion of the phenotypic variance of CMP traits and could thus be included in genomic evaluation models to improve milk CMP in Montbéliarde cows.
| S-EPMC6604208 | biostudies-literature
Project description:Thirty conventional and twenty-four organic dairy farms were divided into equal numbers within system groups: high-pasture, standard-pasture, and low-pasture groups. Milk samples were collected monthly for 12 consecutive months. Milk from high-pasture organic farms contained less fat and protein than standard- and low-pasture organic farms, but more lactose than low-pasture organic farms. Grazing, concentrate feed intake and the contribution of non-Holstein breeds were the key drivers for these changes. Milk Ca and P concentrations were lower in standard-pasture conventional farms than the other conventional groups. Milk from low-pasture organic farms contained less Ca than high- and standard-pasture organic farms, while high-pasture organic farms produced milk with the highest Sn concentration. Differences in mineral concentrations were driven by the contribution of non-Holstein breeds, feeding practices, and grazing activity; but due to their relatively low numerical differences between groups, the subsequent impact on consumers' dietary mineral intakes would be minor.
| S-EPMC8620383 | biostudies-literature
Project description:The clean energy transition will require a vast increase in metal supply, yet new mineral deposit discoveries are declining, due in part to challenges associated with exploring under sedimentary and volcanic cover. Recently, several case studies have demonstrated links between lithospheric electrical conductors imaged using magnetotelluric (MT) data and mineral deposits, notably Iron Oxide Copper Gold (IOCG). Adoption of MT methods for exploration is therefore growing but the general applicability and relationship with many other deposit types remains untested. Here, we compile a global inventory of MT resistivity models from Australia, North and South America, and China and undertake the first quantitative assessment of the spatial association between conductors and three mineral deposit types commonly formed in convergent margin settings. We find that deposits formed early in an orogenic cycle such as volcanic hosted massive sulfide (VHMS) and copper porphyry deposits show weak to moderate correlations with conductors in the upper mantle. In contrast, deposits formed later in an orogenic cycle, such as orogenic gold, show strong correlations with mid-crustal conductors. These variations in resistivity response likely reflect mineralogical differences in the metal source regions of these mineral systems and suggest a metamorphic-fluid source for orogenic gold is significant. Our results indicate the resistivity structure of mineralized convergent margins strongly reflects late-stage processes and can be preserved for hundreds of millions of years. Discerning use of MT is therefore a powerful tool for mineral exploration.
| S-EPMC9114405 | biostudies-literature
Project description:BackgroundIn this study we perform a genome-wide association study (GWAS) for bovine milk fatty acids from summer milk samples. This study replicates a previous study where we performed a GWAS for bovine milk fatty acids based on winter milk samples from the same population. Fatty acids from summer and winter milk are genetically similar traits and we therefore compare the regions detected in summer milk to the regions previously detected in winter milk GWAS to discover regions that explain genetic variation in both summer and winter milk.ResultsThe GWAS of summer milk samples resulted in 51 regions associated with one or more milk fatty acids. Results are in agreement with most associations that were previously detected in a GWAS of fatty acids from winter milk samples, including eight 'new' regions that were not considered in the individual studies. The high correlation between the -log10(P-values) and effects of SNPs that were found significant in both GWAS imply that the effects of the SNPs were similar on winter and summer milk fatty acids.ConclusionsThe GWAS of fatty acids based on summer milk samples was in agreement with most of the associations detected in the GWAS of fatty acids based on winter milk samples. Associations that were in agreement between both GWAS are more likely to be involved in fatty acid synthesis compared to regions detected in only one GWAS and are therefore worthwhile to pursue in fine-mapping studies.
| S-EPMC3536661 | biostudies-literature
Project description:Capsaicinoids are unique compounds produced only in peppers (Capsicum spp.). Several studies using classical quantitative trait loci (QTLs) mapping and genomewide association studies (GWAS) have identified QTLs controlling capsaicinoid content in peppers; however, neither the QTLs common to each population nor the candidate genes underlying them have been identified due to the limitations of each approach used. Here, we performed QTL mapping and GWAS for capsaicinoid content in peppers using two recombinant inbred line (RIL) populations and one GWAS population. Whole-genome resequencing and genotyping by sequencing (GBS) were used to construct high-density single nucleotide polymorphism (SNP) maps. Five QTL regions on chromosomes 1, 2, 3, 4 and 10 were commonly identified in both RIL populations over multiple locations and years. Furthermore, a total of 109 610 SNPs derived from two GBS libraries were used to analyse the GWAS population consisting of 208 C. annuum-clade accessions. A total of 69 QTL regions were identified from the GWAS, 10 of which were co-located with the QTLs identified from the two biparental populations. Within these regions, we were able to identify five candidate genes known to be involved in capsaicinoid biosynthesis. Our results demonstrate that QTL mapping and GBS-GWAS represent a powerful combined approach for the identification of loci controlling complex traits.
| S-EPMC6097123 | biostudies-literature
Project description:Fatty acid binding proteins (FABPs) bind long-chain fatty acids and are involved in their intracellular transport. Of the known bovine FABP genes, FABP4 has been mapped to a region on chromosome 14 that contains quantitative trait loci for milk traits. This study investigated the association of FABP4 haplotypes with milk production traits in 719 Holstein-Friesian × Jersey cows. Polymerase chain reaction-single strand conformational polymorphism (PCR-SSCP) analysis of a variable region of the gene revealed three haplotypes (A, B and C). Five single nucleotide polymorphisms (SNPs) were identified: two in exon 3 and three in intron 3. A was associated (P=0.032) with increased milk protein percentage (present: 4.00 ± 0.02%; absent: 3.95 ± 0.02%) and B was associated (P=0.009) with increased milk yield (present: 23.81 ± 0.23 kg/d; absent: 23.06 ± 0.21 kg/d), but tended to be associated with a decrease in protein percentage and an increase in protein yield. Cows with genotypes AA, AB and AC produced less milk, but with a higher protein percentage than BC cows. This suggest that FABP4 affects milk yield and milk protein content, both economically important traits, and that further study of this gene is warranted.
| S-EPMC4464348 | biostudies-literature
Project description:The fatty acid (FA) profile has a considerable impact on the nutritional and technological quality of milk and dairy products. The molecular mechanism underlying the regulation of fat metabolism in bovine mammary gland have been not completely elucidated. We conducted genome-wide association studies (GWAS) across 65 milk FAs and fat percentage in 1,152 Brown Swiss cows. In total, we identified 175 significant single nucleotide polymorphism (SNPs) spanning all chromosomes. Pathway analyses revealed that 12:0 was associated with the greatest number of overrepresented categories/pathways (e.g. mitogen-activated protein kinase (MAPK) activity and protein phosphorylation), suggesting that it might play an important biological role in controlling milk fat composition. An Associated Weight Matrix approach based on SNP co-associations predicted a network of 791 genes related to the milk FA profile, which were involved in several connected molecular pathways (e.g., MAPK, lipid metabolism and hormone signalling) and undetectable through standard GWAS. Analysis of transcription factors and their putative target genes within the network identified BACH2, E2F3 and KDM5A as key regulators of milk FA metabolism. These findings contribute to increasing knowledge of FA metabolism and mammary gland functionality in dairy cows and may be useful in developing targeted breeding practices to improve milk quality.
| S-EPMC5725496 | biostudies-literature