Fine-mapping sequence mutations with a major effect on oligosaccharide content in bovine milk

Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle

Many quantitative trait loci (QTLs) are in non-coding regions. Therefore, QTLs are assumed to affect gene regulation. Gene expression and RNA splicing are primary steps of transcription, so DNA variants changing gene expression (eVariants) or RNA splicing (sVariants) are expected to significantly affect phenotypes. We quantify the contribution of eVariants and sVariants detected from 16 tissues (n = 4,725) to 37 traits of ∼120,000 cattle (average magnitude of genetic correlation between traits = 0.13). Analyzed in Bayesian mixture models, averaged across 37 traits, cis and trans eVariants and sVariants detected from 16 tissues jointly explain 69.2% (SE = 0.5%) of heritability, 44% more than expected from the same number of random variants. This 69.2% includes an average of 24% from trans e-/sVariants (14% more than expected). Averaged across 56 lipidomic traits, multi-tissue cis and trans e-/sVariants also explain 71.5% (SE = 0.3%) of heritability, demonstrating the essential role of proximal and distal regulatory variants in shaping mammalian phenotypes.

Creation of a milk oligosaccharide database, MilkOligoDB, reveals common structural motifs and extensive diversity across mammals

The carbohydrate fraction of most mammalian milks contains a variety of oligosaccharides that encompass a range of structures and monosaccharide compositions. Human milk oligosaccharides have received considerable attention due to their biological roles in neonatal gut microbiota, immunomodulation, and brain development. However, a major challenge in understanding the biology of milk oligosaccharides across other mammals is that reports span more than 5 decades of publications with varying data reporting methods. In the present study, publications on milk oligosaccharide profiles were identified and harmonized into a standardized format to create a comprehensive, machine-readable database of milk oligosaccharides across mammalian species. The resulting database, MilkOligoDB, includes 3193 entries for 783 unique oligosaccharide structures from the milk of 77 different species harvested from 113 publications. Cross-species and cross-publication comparisons of milk oligosaccharide profiles reveal common structural motifs within mammalian orders. Of the species studied, only chimpanzees, bonobos, and Asian elephants share the specific combination of fucosylation, sialylation, and core structures that are characteristic of human milk oligosaccharides. However, agriculturally important species do produce diverse oligosaccharides that may be valuable for human supplementation. Overall, MilkOligoDB facilitates cross-species and cross-publication comparisons of milk oligosaccharide profiles and the generation of new data-driven hypotheses for future research.

Genetic variation in histone modifications and gene expression identifies regulatory variants in the mammary gland of cattle

BACKGROUND

Causal variants for complex traits, such as eQTL are often found in non-coding regions of the genome, where they are hypothesised to influence phenotypes by regulating gene expression. Many regulatory regions are marked by histone modifications, which can be assayed by chromatin immunoprecipitation followed by sequencing (ChIP-seq). Sequence reads from ChIP-seq form peaks at putative regulatory regions, which may reflect the amount of regulatory activity at this region. Therefore, eQTL which are also associated with differences in histone modifications are excellent candidate causal variants.

RESULTS

We assayed the histone modifications H3K4Me3, H3K4Me1 and H3K27ac and mRNA in the mammary gland of up to 400 animals. We identified QTL for peak height (histone QTL), exon expression (eeQTL), allele specific expression (aseQTL) and allele specific binding (asbQTL). By intersecting these results, we identify variants which may influence gene expression by altering regulatory regions of the genome, and may be causal variants for other traits. Lastly, we find that these variants are found in putative transcription factor binding sites, identifying a mechanism for the effect of many eQTL.

CONCLUSIONS

We find that allele specific and traditional QTL analysis often identify the same genetic variants and provide evidence that many eQTL are regulatory variants which alter activity at regulatory regions of the bovine genome. Our work provides methodological and biological updates on how regulatory mechanisms interplay at multi-omics levels.

Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle

BACKGROUND

Fourier-transform mid-infrared (FT-MIR) spectroscopy provides a high-throughput and inexpensive method for predicting milk composition and other novel traits from milk samples. While there have been many genome-wide association studies (GWAS) conducted on FT-MIR predicted traits, there have been few GWAS for individual FT-MIR wavenumbers. Using imputed whole-genome sequence for 38,085 mixed-breed New Zealand dairy cattle, we conducted GWAS on 895 individual FT-MIR wavenumber phenotypes, and assessed the value of these direct phenotypes for identifying candidate causal genes and variants, and improving our understanding of the physico-chemical properties of milk.

RESULTS

Separate GWAS conducted for each of 895 individual FT-MIR wavenumber phenotypes, identified 450 1-Mbp genomic regions with significant FT-MIR wavenumber QTL, compared to 246 1-Mbp genomic regions with QTL identified for FT-MIR predicted milk composition traits. Use of mammary RNA-seq data and gene annotation information identified 38 co-localized and co-segregating expression QTL (eQTL), and 31 protein-sequence mutations for FT-MIR wavenumber phenotypes, the latter including a null mutation in the ABO gene that has a potential role in changing milk oligosaccharide profiles. For the candidate causative genes implicated in these analyses, we examined the strength of association between relevant loci and each wavenumber across the mid-infrared spectrum. This revealed shared association patterns for groups of genomically-distant loci, highlighting clusters of loci linked through their biological roles in lactation and their presumed impacts on the chemical composition of milk.

CONCLUSIONS

This study demonstrates the utility of FT-MIR wavenumber phenotypes for improving our understanding of milk composition, presenting a larger number of QTL and putative causative genes and variants than found from FT-MIR predicted composition traits. Examining patterns of significance across the mid-infrared spectrum for loci of interest further highlighted commonalities of association, which likely reflects the physico-chemical properties of milk constituents.

Bovine Milk Triacylglycerol Regioisomer Ratio Shows Remarkable Inter-Breed and Inter-Cow Variation

Regioisomers (or positional isomers) of triacylglycerols (TAGs) of milk are known to show differential outcome in relation to human absorption. Quantitation of TAG regioisomers remains a big challenge due to the lack of facile chromatographic separation technique. The feasibility of using fragment ion intensity ratio to determine the ratio of co-eluting AAB/ABA-type regioisomer pairs was confirmed in this study. The ability of C30 stationary phase in resolving interfering TAG isomers was demonstrated for the first time. This allowed us to reveal the complexity of using fragment ion intensity to quantify 1,2-olein-3-palmitin (OOP), 1,3-olein-2-palmitin (OPO), 1,2-olein-3-stearin (OOS), and 1,3-olein-2-stearin (OSO) regioisomers in milk samples. A novel algorithm was proposed to consider the contribution of OPO/OOP and OSO/OOS double bond (DB)-isomers and to eliminate the interference of isobaric ions from other isomers, an aspect overlooked in previous studies. This liquid chromatography-mass spectrometry method that requires no pre-fractioning and a moderate chromatographic separation time of 36 min is simple and, thus, suitable for screening a large number of samples for genetic analysis of this trait. Preliminary results using a small cohort of animals showed that OPO/OOP ratio differs significantly between Jersey and Holstein cows, and a large variation was also observed across individual Holstein cows.

Design of experiments for fine-mapping quantitative trait loci in livestock populations

BACKGROUND

Single nucleotide polymorphisms (SNPs) which capture a significant impact on a trait can be identified with genome-wide association studies. High linkage disequilibrium (LD) among SNPs makes it difficult to identify causative variants correctly. Thus, often target regions instead of single SNPs are reported. Sample size has not only a crucial impact on the precision of parameter estimates, it also ensures that a desired level of statistical power can be reached. We study the design of experiments for fine-mapping of signals of a quantitative trait locus in such a target region.

METHODS

A multi-locus model allows to identify causative variants simultaneously, to state their positions more precisely and to account for existing dependencies. Based on the commonly applied SNP-BLUP approach, we determine the z-score statistic for locally testing non-zero SNP effects and investigate its distribution under the alternative hypothesis. This quantity employs the theoretical instead of observed dependence between SNPs; it can be set up as a function of paternal and maternal LD for any given population structure.

RESULTS

We simulated multiple paternal half-sib families and considered a target region of 1 Mbp. A bimodal distribution of estimated sample size was observed, particularly if more than two causative variants were assumed. The median of estimates constituted the final proposal of optimal sample size; it was consistently less than sample size estimated from single-SNP investigation which was used as a baseline approach. The second mode pointed to inflated sample sizes and could be explained by blocks of varying linkage phases leading to negative correlations between SNPs. Optimal sample size increased almost linearly with number of signals to be identified but depended much stronger on the assumption on heritability. For instance, three times as many samples were required if heritability was 0.1 compared to 0.3. An R package is provided that comprises all required tools.

CONCLUSIONS

Our approach incorporates information about the population structure into the design of experiments. Compared to a conventional method, this leads to a reduced estimate of sample size enabling the resource-saving design of future experiments for fine-mapping of candidate variants.

Identification of the complete coding cDNAs and expression analysis of B4GALT1, LALBA, ST3GAL5, ST6GAL1 in the colostrum and milk of the Garganica and Maltese goat breeds to reveal possible implications for oligosaccharide biosynthesis

Background

Milk sialylated oligosaccharides (SOS) play crucial roles in many biological processes. The most abundant free SOS in goat’s milk are 3’sialyllactose (3′-SL), 6’sialyllactose (6′-SL) and disialyllactose (DSL). The production of these molecules is determined genetically by the expression of glycosyltransferases and by the availability of nucleotide sugar substrates, but the precise mechanisms regulating the differential patterns of milk oligosaccharides are not known. We aimed to identify the complete cDNAs of candidate genes implicated in SOS biosynthesis (B4GALT1, LALBA, ST3GAL5, ST6GAL1) and to analyse their expression during lactation in the Garganica and Maltese goat breeds. Moreover, we analysed the colostrum and milk contents of 3′-SL, 6′-SL and disialyllactose (DSL) and the possible correlations between expressed genes and SOS.

Results

We identified the complete coding cDNAs of B4GALT1 (HQ700335.1), ST3GAL5 (KF055858.2), and ST6GAL1 (HQ709167.1), the single nucleotide polymorphism (SNPs) of these genes and 2 splicing variants of the ST6GAL1 cDNA. RT-qPCR analysis showed that LALBA and ST6GAL1 were the genes with the highest and lowest expression in both breeds, respectively. The interaction effects of the breeds and sampling times were associated with higher levels of B4GALT1 and ST3GAL5 gene expression in Garganica than in Maltese goats at kidding. B4GALT1, LALBA, and ST3GAL5 gene expression changed from kidding to 60 and 120 days in Maltese goats, while in Garganica goats, a difference was observed only for the LALBA gene. Breed and lactation effects were also found for SOS contents. Positive correlations of B4GALT1, LALBA, ST3GAL5, and ST6GAL1 with 3′-SL/6′SL and DSL were found.

Conclusions

The genetic effect on the oligosaccharide content of milk was previously highlighted in bovines, and this study is the first to investigate this effect in two goat breeds (Garganica and Maltese) during lactation. The genetic variability of candidate genes involved in SOS biosynthesis highlights their potential role in affecting gene expression and ultimately biological function. The investigation of gene regulatory regions as well as the examination of other sialyltransferase genes will be needed to identify the genetic pattern leading to a higher SOS content in the autochtonous Garganica breed and to protect it using a focused breeding strategy.

Structures and Metabolic Properties of Bovine Milk Oligosaccharides and Their Potential in the Development of Novel Therapeutics

Among the many bioactive components in human milk, the free oligosaccharides (OS) have been intensely studied in recent decades due to their unique ability to selectively modulate the infant gut microbiota, in addition to providing numerous other health benefits. In light of the demonstrated value of these compounds, recent studies have set out to characterize the structures and properties of the similar and more widely-available OS in the dairy industry. This mini review gives a brief overview of the common analytical techniques used to characterize bovine milk OS and highlights several recent, key studies that have identified valuable physiological and metabolic effects of these molecules in vivo. Although traditionally considered indigestible by human enzymes, evidence now suggests that milk OS are partially absorbed in the intestines and likely contribute to the development of molecular structures in the brain. Furthermore, aside from their prebiotic effects, these compounds show promise as therapeutics that could alleviate numerous metabolic abnormalities, including undernutrition, obesity, and excessive intestinal permeability. The need for novel treatments to address these and related health issues is motivating the development of scalable techniques to produce large quantities of milk OS for use as food ingredients. The safety and tolerability of high dosages of bovine milk OS have been demonstrated in two independent human studies, which potentially opens the door for further research aiming to utilize these molecules to alleviate common metabolic health issues.