Biology subjects

Meadows, J. R. S.

Publications and source records attributed to Meadows, J. R. S..

9 recordsLinked to original sources

bioRxiv2026

Dog-human gene network colocalization links synaptic signalling and ubiquitination to compulsive disorders

Obsessive-compulsive disorder (OCD) is highly polygenic, and the largest genome-wide association study (GWAS), with 53,660 cases and 2,044,417 controls, identified only 30 loci, a small fraction of loci estimated to explain its heritability - too few to resolve biological pathways. Pet dogs develop a compulsive disorder (dogCD) similar to OCD. In a GWAS of dogCD with 2,584 dogs from the community science project Darwin's Ark, each dog locus explains at least 40-fold more phenotypic variance than each human OCD locus, giving power equivalent to the human GWAS with 80-fold fewer individuals. Combining the two GWAS identifies a 165-gene network undetectable in humans at current sample sizes. This network is enriched for genes expressed in neurons, particularly in the amygdala and cortex, and comprises four biological processes: excitatory-inhibitory synaptic transmission, axon guidance and neuron recognition, protein ubiquitination, and adenylyl cyclase-activating G-protein-coupled receptor signaling. Like most complex human traits, dogCD risk is likely driven by regulatory variation: fine-mapped dogCD SNPs are non-coding, and dogCD loci are enriched in candidate cis-regulatory elements (cCREs) in a new dog epigenomic atlas spanning eight brain regions. The cross-species network implicates an inherited risk architecture largely outside current OCD pharmacotherapy, and establishes pet dogs as a model for gene network discovery, particularly for conditions underpowered in human studies.

genetics↗

bioRxiv2026

A single nuclei expression resource for exploring dog brain cell transcriptomic diversity

Domesticated dogs present a unique case in nature where mutualism with and selective breeding by humans has led to profound changes in their environment, physiology, and behaviour compared to their wolf-like ancestors. Dog tameness, sociability, and trainability have likely evolved due to significant alterations to brain function. Exploring the effects of domestication on the dog brain will be facilitated by the characterisation of dog brain cell diversity, a task which is not yet complete. To fill this gap, we use single-nucleus RNA sequencing and survey cell types across the dog brain. We present transcriptomes from almost 60,000 cells sampled from the cerebellum, thalamus, and three regions of the cerebrum. Our analysis identified 24 major clusters representing 21 broad cell types, and 131 subclusters revealing regional variation. Comparisons with human and mouse datasets revealed a high level of conservation in neurons across mammalian brains, and greater divergence in glial cells, particularly oligodendrocytes. We demonstrate the utility of the dataset for interrogating specific gene expression patterns across the brain, including genes implicated in dog domestication, behavioural traits, and disease. We discover distinct differences in the expression of opioid receptors in the brains of dogs, compared to humans and mice, providing a potential explanation for dogs' higher tolerance and lower risk of severe adverse effects of opioid drugs. The data from this project are released via a web application for use by the wider community.

genomics↗

bioRxiv2024

Characterization of nuclear mitochondrial insertions in canine genome assemblies

BackgroundThe presence of mitochondrial sequences in the nuclear genome (Numts) confounds analyses of mitochondrial sequence variation and is a potential source of false positives in disease studies. To improve the analysis of mitochondrial variation in canines, we completed a systematic assessment of Numt content across genome assemblies, canine populations and the carnivore lineage. ResultsCentering our analysis on the UU_Cfam_GSD_1.0/canFam4/Mischka assembly, a commonly used reference in dog genetic variation studies, we find a total of 321 Numts, located throughout the nuclear genome and encompassing the entire sequence of the mitochondria. Comparison to 14 canine genome assemblies identified 63 Numts with presence-absence dimorphism among dogs, wolves, and a coyote. Further, a subset of Numts were maintained across carnivore evolutionary time (arctic fox, polar bear, cat), with 8 sequences likely more than 10 million years old, and shared with the domestic cat. On a population level, using structural variant data from the Dog10K Consortium for 1,879 dogs and wolves, we identified 11 Numts that are absent in at least one sample as well as 53 Numts that are absent from the Mischka assembly. ConclusionsWe highlight scenarios where the presence of Numts is a potentially confounding factor and provide an annotation of these sequences in canine genome assemblies. This resource will aid the identification and interpretation of polymorphisms in both somatic and germline mitochondrial studies in canines.

genomics↗

bioRxiv2024

Interpreting mammalian evolutionary constraint at synonymous sites in light of the unwanted transcript hypothesis

The unwanted transcript hypothesis presents a potential explanation for cryptic evolutionary constraint at synonymous sites in species with low effective population sizes, such as humans and other mammals. Selection for higher GC content and against mutations that alter splicing in native transcripts is predicted to shape synonymous site content and protect against unwanted transcripts. Here, we interpret mammalian synonymous site constraint in this context. Utilising the largest alignment of 240 placental mammal genomes and single-base resolution constraint scores, we show that 20.8% of four-fold degenerate sites are under significant constraint across mammals. There is a strong bias for guanine (G) and cytosine (C) at constrained sites, marked constraint near splice sites, and variation in human populations shows a bias against mutations that reduce synonymous site GC content. We find evidence for higher constraint on four-fold degenerate sites in species with small historic effective population sizes and high young transposable element genome content. Genes enriched for synonymous site constraint, including those forming CpG sites, are tightly regulated and integral to organismal viability through their involvement in embryo development and transcriptional regulation.

evolutionary biology↗

bioRxiv2023

Title: Leveraging Base Pair Mammalian Constraint to Understand Genetic Variation and Human Disease

Although thousands of genomic regions have been associated with heritable human diseases, attempts to elucidate biological mechanisms are impeded by a general inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function that is agnostic to cell type or disease mechanism. Here, single base phyloP scores from the whole genome alignment of 240 placental mammals identified 3.5% of the human genome as significantly constrained, and likely functional. We compared these scores to large-scale genome annotation, genome-wide association studies (GWAS), copy number variation, clinical genetics findings, and cancer data sets. Evolutionarily constrained positions are enriched for variants explaining common disease heritability (more than any other functional annotation). Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.

genomics↗

bioRxiv2023

Evolutionary constraint and innovation across hundreds of placental mammals

Evolutionary constraint and acceleration are powerful, cell-type agnostic measures of functional importance. Previous studies in mammals were limited by species number and reliance on human-referenced alignments. We explore the evolution of placental mammals, including humans, through reference-free whole-genome alignment of 240 species and protein-coding alignments for 428 species. We estimate 10.7% of the human genome is evolutionarily constrained. We resolve constraint to single nucleotides, pinpointing functional positions, and refine and expand by over seven-fold the catalog of ultraconserved elements. Overall, 48.5% of constrained bases are as yet unannotated, suggesting yet-to-be-discovered functional importance. Using species-level phenotypes and an updated phylogeny, we associate coding and regulatory variation with olfaction and hibernation. Focusing on biodiversity conservation, we identify genomic metrics that predict species at risk of extinction.

genomics↗

bioRxiv2021

Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data

Transcriptomic analyses are commonly used to identify differentially expressed genes between patients and controls, or within individuals across disease courses. These methods, whilst effective, cannot encompass the combinatorial effects of genes driving disease. We applied rule-based machine learning (RBML) models and rule networks (RN) to an existing paediatric Systemic Lupus Erythematosus (SLE) blood expression dataset, with the goal of developing gene networks to separate low and high disease activity (DA1 and DA3). The resultant model had an 81% accuracy to distinguish between DA1 and DA3, with unsupervised hierarchical clustering revealing additional subgroups indicative of the immune axis involved or state of disease flare. These subgroups correlated with clinical variables, suggesting that the gene sets identified may further the understanding of gene networks that act in concert to drive disease progression. This included roles for genes i) induced by interferons (IFI35 and OTOF), ii) key to SLE cell types (KLRB1 encoding CD161), or iii) with roles in autophagy and NF-{kappa}B pathway responses (CKAP4). As demonstrated here, RBML approaches have the potential to reveal novel gene patterns from within a heterogeneous disease, facilitating patient clinical and therapeutic stratification.

bioinformatics↗

bioRxiv2020

A new long-read dog assembly uncovers thousands of exons and functional elements missing in the previous reference

Here we present a new high-quality canine reference genome with gap number reduced 41-fold, from 23,836 to 585. Analysis of existing and novel data, RNA-seq, miRNA-seq and ATAC-seq, revealed a large proportion of these harboured previously hidden elements, including genes, promoters and miRNAs. Short-read dark regions were detected, and genomic regions completed, including the DLA, TCR and 366 cancer genes. 10x sequencing of 27 dogs uncovered a total of 22.1 million SNPs, Indels and larger structural variants (SVs). 1.4% overlap with protein coding genes and could provide a source of normal or aberrant phenotypic modifications.

genomics↗

bioRxiv2019

SweHLA: the high confidence HLA typing bio-resource drawn from 1 000 Swedish genomes

There is a need to accurately call human leukocyte antigen (HLA) genes from existing short-read sequencing data, however there is no single solution that matches the gold standard of lab typing. Here we aimed to combine results from available software, minimising the biases of applied algorithm and HLA reference. The result is a robust HLA population resource for the published 1 000 Swedish genomes, and a framework for future HLA interrogation. HLA 2-field alleles were called using four imputation and inference methods for the classical eight genes (class I: HLA-A, -B, -C; class II: HLA-DPA1, -DPB1, -DQA1, -DQB1, -DRB1). A high confidence population set (SweHLA) was determined using an n-1 concordance rule for class I (four software) and class II (three software) alleles. Results were compared across populations and individual programs benchmarked to SweHLA. Per allele, 875 to 988 of the 1 000 samples were genotyped in SweHLA; 920 samples had at least seven loci. While a small fraction of reference alleles were common to all software (class I=1.9% and class II=4.1%), this did not affect the overall call rate. Gene-level concordance was high compared to European populations (>0.83%), with COX and PGF the dominant SweHLA haplotypes. We noted that 15/18 discordant alleles (delta allele frequency > 2) were previously reported as disease-associated. These differences could in part explain across-study genetic replication failures, reinforcing the need to use multiple software. SweHLA demonstrates a way to use existing NGS data to generate a population resource agnostic to individual HLA software biases.

genetics↗