The role of Fourier-transform mid-infrared spectroscopy in improving the prediction of new and existing traits in New Zealand dairy cattle : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Animal Science at Massey University, AL Rae Centre, Hamilton, New Zealand

Bovine milk is a rich source of dietary nutrients that are important to human health. Market demand for bovine milk is driven by its nutritional value, price, processability, and consumer expectations and perceptions about food production systems. The ability to quantify traits associated with milk quality, processability, animal health and environmental impact is critical for selective breeding and thus highly valuable to the dairy industry. However, obtaining direct measurements of such traits can be difficult and expensive. Estimation of major milk components using Fourier-transform mid-infrared (FT-MIR) spectroscopy is common practice, and spectral-based predictions of these traits are already widely used in milk payment and animal evaluation systems. Applications using FT-MIR spectra to predict other traits have increased in popularity over the last decade, and are attractive alternatives to directly measuring phenotypes because the FT-MIR spectra are readily available as a by-product of routine milk testing. The objectives of this thesis were to improve understanding of the phenotypic and genetic characteristics of FT-MIR spectra, and assess the role that such data can play in predicting new traits or improving the prediction of existing traits in New Zealand dairy cattle. We assessed different strategies for improving the quality of spectral data and demonstrated that there are limitations in predicting traits such as pregnancy status, due to confounding effects such as stage of lactation. From a genetics perspective, we reviewed the evolving role of spectral data in the improvement of dairy cattle by selection and discussed opportunities for consolidating spectral datasets with other genomic and molecular data sources. We conducted GWAS on individual FT-MIR wavenumbers and demonstrated that the individual wavenumbers provided stronger association effects and improved power for identifying candidate causal variants, compared to conducting GWAS on FT-MIR predicted traits. We also demonstrated the potential utility of spectral data for predicting and incorporating fatty acids and protein traits into breeding programs, but showed that even when genetic correlations between directly measured and FT-MIR predicted traits were high, the detectable QTL underpinning these traits were not always the same. Although there are many potential applications for FT-MIR spectral datasets, there are still challenges to developing robust prediction equations and understanding the genetic relationships between traits of interest and their FT-MIR predictions. Addressing these challenges will provide opportunities to improve the prediction of new and existing traits in dairy cattle milk production systems and breeding programs into the future

Genome-wide association analysis reveals QTL and candidate mutations involved in white spotting in cattle

International audienceAbstractBackgroundWhite spotting of the coat is a characteristic trait of various domestic species including cattle and other mammals. It is a hallmark of Holstein–Friesian cattle, and several previous studies have detected genetic loci with major effects for white spotting in animals with Holstein–Friesian ancestry. Here, our aim was to better understand the underlying genetic and molecular mechanisms of white spotting, by conducting the largest mapping study for this trait in cattle, to date.ResultsUsing imputed whole-genome sequence data, we conducted a genome-wide association analysis in 2973 mixed-breed cows and bulls. Highly significant quantitative trait loci (QTL) were found on chromosomes 6 and 22, highlighting the well-established coat color genes KIT and MITF as likely responsible for these effects. These results are in broad agreement with previous studies, although we also report a third significant QTL on chromosome 2 that appears to be novel. This signal maps immediately adjacent to the PAX3 gene, which encodes a known transcription factor that controls MITF expression and is the causal locus for white spotting in horses. More detailed examination of these loci revealed a candidate causal mutation in PAX3 (p.Thr424Met), and another candidate mutation (rs209784468) within a conserved element in intron 2 of MITF transcripts expressed in the skin. These analyses also revealed a mechanistic ambiguity at the chromosome 6 locus, where highly dispersed association signals suggested multiple or multiallelic QTL involving KIT and/or other genes in this region.ConclusionsOur findings extend those of previous studies that reported KIT as a likely causal gene for white spotting, and report novel associations between candidate causal mutations in both the MITF and PAX3 genes. The sizes of the effects of these QTL are substantial, and could be used to select animals with darker, or conversely whiter, coats depending on the desired characteristics

Genome-wide association analysis reveals QTL and candidate mutations involved in white spotting in cattle

International audienceAbstractBackgroundWhite spotting of the coat is a characteristic trait of various domestic species including cattle and other mammals. It is a hallmark of Holstein–Friesian cattle, and several previous studies have detected genetic loci with major effects for white spotting in animals with Holstein–Friesian ancestry. Here, our aim was to better understand the underlying genetic and molecular mechanisms of white spotting, by conducting the largest mapping study for this trait in cattle, to date.ResultsUsing imputed whole-genome sequence data, we conducted a genome-wide association analysis in 2973 mixed-breed cows and bulls. Highly significant quantitative trait loci (QTL) were found on chromosomes 6 and 22, highlighting the well-established coat color genes KIT and MITF as likely responsible for these effects. These results are in broad agreement with previous studies, although we also report a third significant QTL on chromosome 2 that appears to be novel. This signal maps immediately adjacent to the PAX3 gene, which encodes a known transcription factor that controls MITF expression and is the causal locus for white spotting in horses. More detailed examination of these loci revealed a candidate causal mutation in PAX3 (p.Thr424Met), and another candidate mutation (rs209784468) within a conserved element in intron 2 of MITF transcripts expressed in the skin. These analyses also revealed a mechanistic ambiguity at the chromosome 6 locus, where highly dispersed association signals suggested multiple or multiallelic QTL involving KIT and/or other genes in this region.ConclusionsOur findings extend those of previous studies that reported KIT as a likely causal gene for white spotting, and report novel associations between candidate causal mutations in both the MITF and PAX3 genes. The sizes of the effects of these QTL are substantial, and could be used to select animals with darker, or conversely whiter, coats depending on the desired characteristics

Milk Composition Phenotype Data

Milk composition records were measured as part of standard herd testing procedures. Abbreviations used: id = animal identification, sire = sire animal identification, pgsire = parternal sire animal identification, pmgsire = partern fr = friesian, je = jersey, hol = holestein, FxJ = freisian x jersey, FxH = freisian x holestein, JxH = jersey x holestein, fat = fat yield, fat_pct = fat percentage, milk = milk yield, prot = protein, prot_pct = protein percentage, ydlwt = liveweigh

Data from: Functional confirmation of PLAG1 as the candidate causative gene underlying major pleiotropic effects on body weight and milk characteristics

A major pleiotropic quantitative trait locus (QTL) located at ~25Mbp on bovine chromosome 14 affects a myriad of growth and developmental traits in Bos taurus and indicus breeds. These QTL have been attributed to two functional variants in the bidirectional promoter of PLAG1 and CHCHD7, and although PLAG1 is a good candidate for mediating these effects, its role remains uncertain given these variants are also associated with expression of five additional genes at the broader locus. In the current study, we conducted expression QTL (eQTL) mapping of this region using a large, high depth mammary RNAseq dataset representing 375 lactating cows. Here we show that of the seven previously implicated genes, only PLAG1 and LYN are differentially expressed by QTL genotype, and only PLAG1 bears the same association signature of the growth and body weight QTLs. For the first time, we also report significant association of PLAG1 genotype with milk production traits, including milk fat, volume, and protein yield. Collectively, these data confirm PLAG1 as the causative gene underlying this diverse range of physiological QTLs, and indicate new effects for the locus on lactation phenotypes

Animal Genotypes for eQTL analysis at liveweight locus

Animal genotypes for the 432 Illumina BovineHD BeadChip markers at the chromosome 14 liveweight locus. Animals were genotyped using this panel directly, apart from 29 animals which were genotyped using the Illumina BovineSNP50 and imputed up to the HDChip density using Beagle. These genotypes were used for association analysis with gene expression phenotypes from the lactating mammary tissue biospies. PLINK was used to recode the genotypes to 0,1,2 to represent the number of alternative allele copies for each marker. anml_id = anonymised animal identificatio

Animal Genotypes for milk production analysis at liveweight locus

Animal genotypes for the 432 Illumina BovineHD BeadChip markers at the chromosome 14 liveweight locus. Animals were genotyped either using this panel directly, or were genotyped using the Illumina BovineSNP50 and imputed to the HDChip markers using Beagle. These genotypes were used for association analysis with milk production phenotypes generated as part of standard herd test procedures. PLINK was used to recode the genotypes to 0,1,2 to represent the number of alternative allele copies for each marker. anml_id = anonymised animal identificatio

Gene Expression Data

Gene expression data for genes at the chromosome 14 liveweight locus from lactating mammary tissue biopsies. RNAseq read counts have been normalised using variance-stabilisation transformation. Abbreviations used: id = animal identification, sire = sire animal identification, pgsire = parternal sire animal identification, pmgsire = partern fr = friesian, je = jersey, hol = holestein, FxJ = freisian x jersey, FxH = freisian x holestein, JxH = jersey x holestein

imputed-seq-genotypes-Chr1.153640000-154640000.vcf

Imputed genotypes for variants within 1Mbp of the Chr1:153.96 LC QTL, for 357 animals

imputed-seq-genotypes-12k-Chr16.67270000-68270000.vcf

Imputed genotypes for variants within 1Mbp of the Chr16:67.77 LC QTL, for 12,000 animals