Biology subjects

Couldrey, C.

Publications and source records attributed to Couldrey, C..

7 recordsLinked to original sources

bioRxiv2026

Detection and evaluation of copy number variation using both linked-read and short-read sequencing in New Zealand dairy cattle

In recent years, genetic studies have made significant progress in identifying single-nucleotide polymorphisms (SNPs) associated with cattle health and production traits. However, it is still challenging to identify and validate more complicated forms of variation, such as copy number variation (CNV) and other types of structural variation (SV). In this study, SV regions were identified using 37 New Zealand dairy cattle with linked-read sequence data. A transmission-based framework was used to validate these variants at the population scale. 62,438 putative autosomal SV regions were identified with the LongRanger pipeline following the 10x Genomics recommendations. Copy number states for these regions were subsequently estimated via a read-depth based genotyping method using CNVpytor in a population-representative cohort of 2306 animals using Illumina short-read sequencing technology. Mendelian inheritance of copy number states was assessed using linear mixed models incorporating pedigree information, and transmission levels were used to quantify the biological validity of each CNV region. Transmission levels ranged widely, with a mean of 0.5162 across all regions, where higher transmission levels were proportionally enriched for larger SVs. A total of 7218 CNV regions exhibited high transmission levels (>0.9), indicating strong evidence of inheritance. Among these, 7136 overlapped CNV regions reported in one or more public datasets, while 82 high-confidence regions represent previously unreported variants. High-transmission CNV regions tended to show clear, discrete inheritance patterns in trio families, providing the biological evidence that these CNVs are inherited within the population. Together, these results demonstrate that integrating linked-read sequencing with population-scale transmission-based validation provides a robust framework for identifying high-confidence CNV regions. This catalogue of validated CNV regions represents an important resource for downstream functional analyses and the incorporation of structural variation into genomic selection and breeding programs.

bioinformatics↗

bioRxiv2025

The RUMIGEN EpiChip: a versatile, medium density DNA methylation Beadchip for large scale population studies in cattle

BackgroundDNA methylation contributes to the elaboration of phenotypes and is hypothesized to account for interindividual variations in farm animals. Currently, methodologies available to investigate DNA methylation in cattle rely on high throughput sequencing, which cannot be applied to large cohorts. To enable large scale DNA methylation analysis, we developed the RUMIGEN EpiChip, the first DNA methylation array specifically designed for cattle. ResultsManufactured by Illumina, the EpiChip contains 43,317 CpG markers allowing analysis of phenotypes of agronomical interest as well as the study of regulatory processes. The assay design drew on data from numerous studies achieved by the scientific community, and includes CpGs where methylation varies with health status, physiological stage, fertility, and environmental challenges, as well as CpGs located in functional genomic elements (promoters, CTCF binding sites, expression quantitative trait loci). The technical performances of the EpiChip were tested on several semen and blood DNA samples and in two laboratories, showing excellent repeatability, accuracy and interoperability. Methylation values were also concordant with those obtained by reduced representation bisulfite sequencing. The EpiChip has demonstrated a good ability to explore biological processes such as genomic imprinting and differences between cell types, opening the possibility of inferring blood cell composition. Finally, analysis of longitudinal ear biopsies allowed accurate age prediction, suggesting the potential of the array to refine epigenetic clocks. ConclusionsThe RUMIGEN EpiChip is a cost-effective and versatile resource that opens new opportunities for the study of regulatory mechanisms underlying phenotypic variation and for large-scale association analyses in cattle.

genomics↗

bioRxiv2023

Absolute Quantification of Microbiota in Shotgun Sequencing Using Host Cells or Spike-Ins

BackgroundAn ongoing challenge for DNA sequencing of samples containing microorganisms is the ability to meaningfully compare different samples and to connect the results back to clinically relevant disease states. The reads of DNA sequence from each sample do not, in and of themselves, give sufficient information to calculate the absolute abundances of each observed organism. Using relative abundances alone is insufficient to determine whether absolute abundances have increased or decreased in the organisms of interest from one sample to the next. This is a well-studied problem in 16S sequencing, but solutions in shotgun sequencing are lacking. Here we show how spike-ins can be used in shotgun sequencing to calculate absolute abundances of organisms present. We also propose the use of the host cells already in the sample as an alternative calculation method. Mammalian host cells are typically of sufficient size that they can be easily and cheaply counted prior to sequencing by a variety of methods and combining this with sequencing data provides sufficient information to calculate the absolute abundances of microbial organisms. ResultsMicrobial abundances in the samples calculated via this method were consistent with manufacturer-stated values of microbial communities, with qPCR, and with our method tested against itself with regard the spike-in and host-cell based options. R2 values on the log10 scale in these tests ranged from 0.85 to 0.98, and the log10-RMSE ranged from 0.1 to 0.7. ConclusionsThe proposed method can consistently calculate absolute microbial abundances to within an order of magnitude. Both versions of the method, where spike-ins are added to the samples, or where host cells in the sample are counted, are viable. Calculating absolute abundances allows for direct comparisons to be made between different samples. If disease-thresholds have been identified, absolute abundances can quantify disease states.

microbiology↗

bioRxiv2021

Non-additive QTL mapping of lactation traits in 124,000 sequence-imputed cattle reveals novel recessive loci

Deleterious recessive conditions have primarily been studied in a Mendelian disease context. Recently, several large effect, deleterious recessive mutations were discovered via non-additive GWAS of quantitative growth and developmental traits in cattle. This showed quantitative traits can be used as proxies of genetic disorders if they are indicative of whole animal health status and susceptible to underlying genetic conditions. Lactation traits might also reflect genetic disorders in cattle, given the increased energy demands of lactation and the substantial stresses imposed on the animal. Here, we report a screen of over 124,000 cows for recessive effects based on lactation traits. We discovered novel loci associated with five large recessive impacts on milk yield traits represented by missense variants (DOCK8, IL4R, KIAA0556, and SLC25A4) or premature stop variants (ITGAL, LRCH4, and RBM34) as candidate causal mutations. On milk composition traits, we identified several small effect dominance contributions to previously reported additive QTL. In contrasting analyses of milk yield and milk composition phenotypes, we note differing genetic architectures. Milk yield phenotypes presented lower heritabilities and fewer additive QTL, but higher non-additive genetic variance and a higher proportion of loci exhibiting dominance compared to milk composition phenotypes. Large-effect recessive QTL are segregating at surprisingly high frequencies in cattle. We speculate that the differences in genetic architecture between milk yield and milk composition phenotypes derive from underlying dissimilarities in the cellular and molecular representation of these traits. Lactation yields may act as a better proxy than milk composition traits for a wide range of underlying biological disorders affecting animal fitness

genetics↗

bioRxiv2021

Development of epigenetic clocks for New Zealand livestock

Robust biological biomarkers of chronological age have been developed in humans and model mammalian species such as rats and mice using DNA methylation data. The concept of these so-called "epigenetic clocks" has emerged from a large body of literature describing the correlation between genome-wide methylation levels and age. Epigenetic clocks exploit this phenomenon and use small panels of differentially methylated cytosine (CpG) sites to make robust predictions of chronological age, independent of tissue type. Here we present highly accurate livestock epigenetic clocks whereby we have used the custom mammalian methylation array "HorvathMammalMethyl40"1 to construct the first epigenetic clock for domesticated goat (Capra hircus), cattle (Bos taurus), Red (Cervus elaphus) and Wapiti deer (Cervus canadensis) and composite-breed sheep (Ovis aries). Additionally, we have constructed a New Zealand livestock farm animal clock for all animals included in the study, which will enable robust predictions to be extended to various breeds. The farm animal clock shows similarly high accuracies to the individual species clocks (r>0.97), utilising only 217 CpG sites to estimate age (relative to the maximum lifespan of the species) with a single mathematical model. We envision that the applications of this livestock clock could extend well beyond the scope of chronological age estimates. Many independent studies have demonstrated that a deviation between true age and clock derived molecular age is indicative of past and/or present health (including stress) status. There is, therefore, untapped potential to utilise livestock clocks in breeding programmes as a predictor for age-related, production traits.

genomics↗

bioRxiv2018

Multiple QTL underlie milk phenotypes at the CSF2RB locus

BackgroundBovine milk provides an important source of nutrition in much of the Western world, forming components of many food products. Over many years, artificial selection has substantially improved milk production by cows. However, the genes underlying milk production quantitative trait loci (QTL) remain relatively poorly characterised. Here, we investigate a previously-reported QTL located at the CSF2RB locus, for several milk production phenotypes, to better understand its underlying genetic and molecular causes.\n\nResultsUsing a population of 29,350 taurine dairy cattle, we conducted association analyses for milk yield and composition traits, and identified highly significant QTL for milk yield, milk fat concentration, and milk protein concentration. Strikingly, protein concentration and milk yield appear to show co-located yet genetically distinct QTL. To attempt to understand the molecular mechanisms that might be mediating these effects, gene expression data were used to investigate eQTL for eleven genes in the broader interval. This analysis highlighted genetic impacts on CSF2RB and NCF4 expression that share similar association signatures to those observed for lactation QTL, strongly implicating one or both of these genes as the cause of these effects. Using the same gene expression dataset representing 357 lactating cows, we also identified 38 novel RNA editing sites in the 3' UTR of CSF2RB transcripts. The extent to which two of these sites were edited also appears to be genetically co-regulated with lactation QTL, highlighting a further layer of regulatory complexity implicating the CSF2RB gene.\n\nConclusionsThis chromosome 5 locus presents a diversity of molecular and lactation QTL, likely representing multiple overlapping effects that, at a minimum, highlight the CSF2RB gene as having a causal role in these processes.

genomics↗

bioRxiv2018

Widespread cis-regulation of RNA-editing in a large mammal

Post-transcriptional RNA editing may regulate transcript expression and diversity in cells, with potential impacts on various aspects of physiology and environmental adaptation. A small number of recent genome-wide studies in Drosophila, mouse, and human have shown that RNA editing can be genetically modulated, highlighting loci that quantitatively impact editing of transcripts. The potential gene expression and physiological consequences of these RNA editing quantitative trait loci (edQTL), however, are almost entirely unknown. Here, we present analyses of RNA editing in a large domestic mammal (Bos taurus), where we use whole genome and high depth RNA sequencing to discover, characterise, and conduct genetic mapping studies of novel transcript edits. Using a discovery population of nine deeply-sequenced cows, we identify 2,001 edit sites in the mammary transcriptome, the majority of which are adenosine to inosine edits (97.4%). Most sites are predicted to reside in double-stranded secondary structures (85.7%), and quantification of the rates of editing in an additional 355 cows reveals editing is negatively correlated with gene expression in the majority of cases. Genetic analyses of RNA editing and gene expression highlights 67 cis-regulated edQTL, of which seven appear to co-segregate with expression QTL effects. Trait association analyses in a separate population of 9,988 lactating cows also shows nine of the cis-edQTL coincide with at least one co-segregating lactation QTL. Together, these results enhance our understanding of RNA editing dynamics in mammals, and suggest mechanistic links by which loci may impact phenotype through RNA-editing mediated processes.

genomics↗