Biology subjects

Clark, E. L.

Publications and source records attributed to Clark, E. L..

At least 19 recordsLinked to original sources

bioRxiv2026

A multi-tissue epigenomic atlas links the sheep non-coding genome to domestication and complex traits

Non-coding regulatory variation drives complex traits, domestication, and evolutionary adaptation, yet the sheep genome lacks high-resolution functional annotation. Here we present SheepEpimap, a multi-tissue regulatory atlas harmonizing 516 CUT&Tag histone modifications, ATAC-seq, and RNA-seq datasets across 43 adult tissues in sheep. We annotated 2.93 million cis-regulatory elements, yielding 557,441 enhancer-gene pairs and 145,407 variants with allele-specific effects. By training a sequence-to-function deep-learning model, we decoded the base-pair syntax of chromatin accessibility, annotated transcription factor motif instances genome-wide, and constructed 12,210 tissue-specific gene regulatory networks (GRNs). Integrating this resource with multi-tissue expression quantitative trait loci, selection sweeps, and genome-wide association studies prioritized non-coding variants driving domestication and complex traits. Finally, cross-species analysis revealed that sequence-conserved, tissue-matched enhancers were significantly enriched in the heritability of complex traits and diseases in humans. In summary, SheepEpimap (https://genome.ucsc.edu/s/mengzhu/SheepEpimap) provides an open-access foundational ecosystem for sheep functional genomics, precision breeding, and comparative biology.

genetics↗

bioRxiv2026

Comparative multi-omics of the macrophage response to infection with Mycobacterium tuberculosis complex bacteria reveals pathogen-driven epigenomic reprogramming

BackgroundBovine tuberculosis (bTB) is a chronic infectious disease primarily caused by Mycobacterium bovis, which inflicts significant economic losses on the global livestock industry worldwide and can also cause tuberculosis (TB) disease in other mammalian species, including humans. Alveolar macrophages are the host cells targeted by the pathogen during the early stages of infection. While they play a crucial role in controlling infection, the exact nature of the host-pathogen interaction and the genetic and epigenetic factors that modulate infection outcome remain poorly understood. ResultsHere, we used transcriptomics (RNA-seq), chromatin accessibility (ATAC-seq), and chromatin configuration (ChIP-seq) analyses to examine the effects of intracellular mycobacterial infection on the bovine alveolar macrophage (bAM) transcriptome and epigenome. The primary focus was M. bovis infection, but we also conducted parallel comparative analyses using M. tuberculosis (the primary cause of human TB--hTB), M. bovis BCG (the vaccine strain), and gamma-irradiated (killed) M. bovis. Integration of RNA-seq, ChIP-seq, and ATAC-seq data revealed coordinated remodelling of chromatin accessibility and histone modification landscapes underpinning transcriptional activation of key immune and metabolic pathways in response to infection. The identification of candidate genes, including ERBB4, LRCH1, MRTFA, and RNPC3, through integrative analysis with a genome-wide association study (GWAS) for M. bovis infection susceptibility underscores the functional relevance of these regulatory networks. ConclusionsOur results demonstrate that M. bovis drives extensive reprogramming of the bAM epigenome, distinct from the responses elicited by other members of the M. tuberculosis complex (MTBC). The results of this multi-omics comparison provide new insights into the function of pivotal response genes and support the hypothesis that pathogen-driven epigenetic reprogramming of the bovine host macrophage is key to M. bovis survival. It also identifies molecular targets that may inform genome-enabled breeding strategies to enhance resilience to bTB in cattle.

genomics↗

bioRxiv2025

Differential chromatin accessibility between pre- and post-natal stages highlights putative causal regulatory variants in pig skeletal muscle

Deciphering how chromatin dynamics shape the effects of regulatory variants on complex traits across development remains largely unexplored in farmed animals. Focusing on porcine skeletal muscle, we integrated chromatin accessibility (ATAC-seq), molecular QTL (molQTL), and GWAS data to identify putative stage-specific regulatory variants influencing agronomically important traits. We aggregated and analyzed 202 ATAC-seq libraries spanning prenatal (fetal) and postnatal (piglet) stages. We intersected consensus and differential peaks with cis-molQTLs from the Porcine Genotype-by-Tissue-by-Expression Atlas (PigGTEx) followed by functional enrichment analysis, promoter-focused functional annotation, integration with gene-trait pairs, and intersection with eGenes (i.e., genes whose expression is regulated by at least one cis-eQTL) to link variants previously associated with QTLs for production traits. We identified 132,275 differentially accessible peaks (DAPs) distinguishing fetal and piglet muscle. Fetal DAPs were enriched in promoter and intergenic regions, whereas piglet DAPs were enriched in intronic regions, indicating a shift from transcriptional priming to postnatal regulatory refinement. Overlaps between accessible regions and molQTLs were highly significant (p < 0.001), with the strongest eQTLs predominating in the fetal stage (14 fetal vs. 4 piglet). Gene Ontology analysis of promoter-accessible eGenes revealed enrichment for RNA metabolism and chromatin organization in fetuses, and for muscle contraction and lipid metabolism in piglets. The intersection with colocalized complex traits loci identified 107 fetal- and 30 piglet-stage regulatory elements, with only three eGenes shared between stages. These findings provide insights into developmental chromatin dynamics in skeletal muscle and an effective framework for prioritising putative regulatory variants affecting pig traits at prenatal stages.

genomics↗

bioRxiv2025

Bighorn sheep T2T genome assembly reveals differences in immune genes: a potential cause of high morbidity due to respiratory pathogens

The bighorn sheep (Ovis canadensis), despite its close relation to domestic sheep, suffer higher morbidity and mortality from respiratory disease complexes, likely due to genetic differences in immune responses. Unraveling highly repetitive regions such as immune loci and genetic differences was problematic until now. We generated a bighorn sheep telomere-to-telomere assembly, adding 14.28% of novel sequence compared to the previous reference. This enabled the first complete immune loci annotation revealing the IGL and TR loci are significantly short in bighorn sheep. Importantly, a critical immune gene GBP5 and ZNF501, involved in Golgi-mediated immune response, are lacking in bighorn but present in domestic sheep. Re-analysis of a Mycoplasma ovipneumoniae carriage study, using this assembly, identified the immune gene CAPN2 as a key genetic marker for disease carriage, not observable in the original study. This work provides a critical resource for identifying phenotype-linked genetic variation and exploring evolutionary adaptations of bighorn sheep.

genomics↗

bioRxiv2025

Accurate and robust classification of Mycobacterium bovis-infected cattle using peripheral blood RNA-seq data

Bovine tuberculosis (bTB) remains recalcitrant to eradication in many endemic countries where current diagnostics are suboptimal. Mycobacterium bovis causes bTB and is closely related to Mycobacterium tuberculosis, which causes human tuberculosis (hTB). Although blood-based mRNA biomarkers identified through machine learning can discriminate hTB-positive from hTB-negative individuals, similar approaches have not been explored for bTB. Here, we use RNA-seq and machine learning to investigate the utility of blood mRNA as a host-response biomarker for bTB. We identify a 30-gene signature and a 273-gene elastic net classifier that differentiate bTB-positive from bTB-negative cattle, achieving area under the curve (AUC) values of 0.986/0.900 for the former and 0.968/0.938 for the latter in training and testing, respectively. Additionally, we show that these classifiers distinguish bTB-positive cattle from cattle infected with other microbial pathogens (AUC [≥] 0.819). These mRNA-based classifiers represent a promising tool for augmenting current diagnostics to advance global bTB eradication efforts.

genomics↗

bioRxiv2025

A novel reusable transcriptome-wide association study workflow used to map key genes linked to important cattle traits

Transcriptome-wide association studies (TWAS) are a powerful approach for studying the genes underlying complex traits by directly integrating GWAS and gene expression datasets. In cattle, they have been previously applied to identify genes driving fertility, milk production, and health. However, these studies have also highlighted several challenges, from difficulties in reproducing these complex analyses to limitations from poor genotype calls, especially when called directly from RNA sequencing data. To address these and other challenges, for the H2020 BovReg Project, we have developed a streamlined, species-agnostic, and reusable Nextflow TWAS workflow to integrate transcriptomic and GWAS summary statistic datasets. Our workflow first generates accurate genotype calls and gene expression prediction models from transcriptomic datasets and then applies these tools to impute gene expression levels into GWAS cohorts, enabling the association of genes with traits of interest. We explore optimal strategies for calling genetic variants directly from transcriptomic data and illustrate that using imputation approaches specifically designed for low-pass sequencing data can improve variant calling over previously adopted methods. We demonstrate the utility of our TWAS workflow by applying it to both novel and publicly available GWAS cohorts for cattle, detecting novel gene-trait associations for complex traits. Using a new transcriptome annotation of the cattle genome generated for the BovReg project we also illustrate how previously un-assayable associations can be detected. The results and the workflow we present, provide a new resource for the community and contribute to a better understanding of the molecular drivers of complex traits in cattle with the goal of eventually leveraging this information in future breeding decisions.

genomics↗

bioRxiv2025

Inferring domestic goat demographic history through ancient genome imputation

Goats were among the earliest managed animals, making them a natural model to explore the genetic consequences of domestication. However, a challenge in ancient genomic analysis is the relatively low genome coverage for most samples, limiting analysis to pseudohaploid genotypes. Genotype imputation offers potential to alleviate this limitation by improving information content and accuracy in low coverage genomes. To test this we used published high coverage (>8x) goat palaeogenomes, imputing downsampled genomes using the VarGoats dataset (1,372 individuals) as a reference panel. Measuring concordance between imputed and high coverage genotypes, we find high concordance after filtering for common (>5%), high confidence variants, with 0.5x genomes reaching >0.97 concordance. There is a trade-off between coverage, genotype probability (GP) thresholds, and genotype recovery, where higher coverage and more lenient GP thresholds result in higher recovery, and a reduction in heterozygous false-positive rates with stricter thresholds. We then imputed 36 goat palaeogenomes with [≥]0.5x coverage to examine runs-of-homozygosity (ROH) and identity-by-descent (IBD) patterns. Using a novel approach combining ROH profiles across tools, we find that among Neolithic goats, ROH increases with distance from the Zagros Mountains, suggesting a large effect of the initial dispersal of managed herds. Inbreeding levels decrease across Southwest Asia in more recent periods. IBD mirrored this pattern, with less relatedness in the early herding site of Ganj Dareh compared to higher relatedness in goats from later in the dispersal process. These findings provide insights into the genetic consequences of early goat management on demography, and confirm the utility of imputation in leveraging low coverage palaeogenomes. SignificancePaleogenomics offers crucial insight into how animals were domesticated, but poor DNA preservation in ancient remains often limits the reach of genetic analyses. We utilise a cutting-edge technique, genotype imputation, to recover missing genetic information from ancient low coverage goat genomes and shine light on their domestication process. Early domestic goats showed low overall runs-of-homozygosity (ROH) and relatedness. We find that during the Neolithic, runs-of-homozygosity (ROH) and relatedness among goats increased, likely a consequence of the movement of herds beyond their natural range by humans. Inbreeding levels decline in more recent periods, potentially due to expanded herd sizes, animal trade networks, or improved husbandry practices. These findings challenge long-standing assumptions about domestication bottlenecks and highlight how ancient DNA can be used to uncover complex evolutionary histories, even from low coverage ancient samples.

genomics↗

bioRxiv2024

A multi-tissue developmental gene expression atlas towards understanding the biological basis of phenotypes in sheep

Sheep (Ovis aries) represents one of the most important livestock species for animal protein and wool production worldwide. However, little is known about the genetic and biological basis of ovine phenotypes, particularly for those of high economic value and environmental impact. Here, by generating and integrating 1,413 RNA-seq samples from 51 distinct tissues across 14 developmental time points, representing early prenatal, late prenatal, neonate, lamb, juvenile, adult, and elderly stages, we built a high-resolution developmental Gene Expression Atlas (dGEA) in sheep. We observed dynamic patterns of gene expression and regulatory networks across tissues and developmental stages. When harnessing this resource for interpreting genomic associations of 48 monogenetic and 12 complex traits in sheep, we found that genes upregulated at prenatal developmental stages played more important roles in shaping these phenotypes than those upregulated at postnatal stages. For instance, genetic associations of crimp number, mean staple length (MSL), and individual birth weight were significantly enriched in the prenatal rather than postnatal skin and immune tissues. By comprehensively integrating fine-mapping results and the sheep dGEA, we identified several key genes associated with complex traits in sheep, such as SOX9 (associated with MSL), GNRHR (associated with litter size at birth), and PRKDC (associated with live weight). These results provide novel insights into the gene regulatory and developmental architecture underlying ovine phenotypes. The dGEA (https://sheepdgea.njau.edu.cn/) will serve as an invaluable resource for sheep developmental biology, genetics, genomics, and selective breeding.

genetics↗

bioRxiv2024

Empowering bioinformatics communities with Nextflow and nf-core

Standardised analysis pipelines are an important part of FAIR bioinformatics research. Over the last decade, there has been a notable shift from point-and-click pipeline solutions such as Galaxy towards command-line solutions such as Nextflow and Snakemake. We report on recent developments in the nf-core and Nextflow frameworks that have led to widespread adoption across many scientific communities. We describe how adopting nf-core standards enables faster development, improved interoperability, and collaboration with the >8,000 members of the nf-core community. The recent development of Nextflow Domain-Specific Language 2 (DSL2) allows pipeline components to be shared and combined across projects. The nf-core community has harnessed this with a library of modules and subworkflows that can be integrated into any Nextflow pipeline, enabling research communities to progressively transition to nf-core best practices. We present a case study of nf-core adoption by six European research consortia, grouped under the EuroFAANG umbrella and dedicated to farmed animal genomics. We believe that the process outlined in this report can inspire many large consortia to seek harmonisation of their data analysis procedures.

bioinformatics↗

bioRxiv2024

Polyadenylated RNA sequencing analysis helps establish a reliable catalog of circular RNAs - a bovine example.

The aim of this study was to compare the circular transcriptome of divergent tissues in order to understand: i) the presence of circular RNAs (circRNAs) that are not exonic circRNAs, i.e. originated from backsplicing involving known exons and, ii) the origin of artificial circRNA (artif_circRNA), i.e. circRNA not generated in-vivo. CircRNA identification is mostly an in-silico process, and the analysis of data from the BovReg project (https://www.bovreg.eu/) provided an opportunity to explore new ways to identify reliable circRNAs. By considering 117 tissue samples, we characterized 23,926 exonic circRNAs, 337 circRNAs from 273 introns (191 ciRNAs, 146 intron circles), 108 circRNAs from small non-coding genes and nearly 36.6K circRNAs classified as other_circRNAs. We suggested in-vivo copying of specific exonic circRNAs by an RNA-dependent RNA polymerase (RdRP) to explain the 20 identified circRNAs with reverse-complement exons. Furthermore, for 63 of those samples we analyzed in parallel data from total-RNAseq (ribosomal RNAs depleted prior to library preparation) with paired mRNAseq (library prepared with poly(A)-selected RNAs). The high number of circRNAs detected in mRNAseq, and the significant number of novel circRNAs, mainly other_circRNAs, led us to consider all circRNAs detected in mRNAseq as artificial. This study provided evidence that there were 189 false entries in the list of exonic circRNAs: 103 artif_circRNAs identified through comparison of total-RNAseq/mRNAseq using two circRNA tools, 26 probable artif_circRNAs, and 65 identified through deep annotation analysis. This study demonstrates the effectiveness of a panel of highly expressed exonic circRNAs (5-8%) in analyzing the diversity of the bovine circular transcriptome.

genomics↗

bioRxiv2024

Integrative genomics sheds light on the immunobiology of tuberculosis in cattle

Mycobacterium bovis causes bovine tuberculosis (bTB), an infectious disease of cattle that poses a zoonotic threat to humans. Research has shown that bTB susceptibility is a heritable trait, and that the peripheral blood (PB) transcriptome is perturbed during bTB disease. Hitherto, no study has integrated PB transcriptomic, genomic and GWAS data to study bTB disease, and little is known about the genomic architecture underpinning the PB transcriptional response to M. bovis infection. Here, we perform transcriptome profiling of PB from 63 control and 60 confirmed M. bovis infected animals and detect 2,592 differently expressed genes that perturb multiple immune response pathways. Leveraging imputed genome-wide SNP data, we characterise thousands of cis- and trans-expression quantitative trait loci (eQTLs) and show that the PB transcriptome is substantially impacted by intrapopulation genomic variation. We integrate our gene expression data with summary statistics from multiple GWAS data sets for bTB susceptibility and perform the first transcriptome-wide association study (TWAS) in the context of tuberculosis disease. From this TWAS, we identify 136 functionally relevant genes (including RGS10, GBP4, TREML2, and RELT) and provide important new omics data for understanding the host response to mycobacterial infections that cause tuberculosis in mammals.

genomics↗

bioRxiv2023

High-throughput mRNA-seq atlas of human placenta shows vast transcriptome remodeling from first to third trimester

BackgroundThe placenta, composed of chorionic villi, changes dramatically across gestation. Understanding differences in ongoing pregnancies are essential to identify the role of chorionic villi at specific times in gestation and develop biomarkers and prognostic indicators of maternal- fetal health. MethodsThe normative mRNA profile is established using next-generation sequencing of 124 first trimester and 43 third trimester human placentas from ongoing healthy pregnancies. Stably expressed genes not different between trimesters and with low variability are identified. Differential expression analysis of first versus third trimester adjusted for fetal sex is performed, followed by a subanalysis with 23 matched pregnancies to control for subject variability using the same genetic and environmental background. ResultsPlacenta expresses 14,979 mRNAs above sequencing noise (TPM>0.66), with 1,545 stably expressed genes across gestation. Differentially expressed genes account for 86.7% of genes in the full cohort (FDR<0.05). Fold changes highly correlate between the full cohort and subanalysis (Pearson = 0.98). At stricter thresholds (FDR<0.001, fold change>1.5), there are 6,941 differentially expressed protein coding genes (3,206 upregulated in first and 3,735 upregulated in third trimester). ConclusionThis is the largest mRNA atlas of healthy human placenta across gestation, controlling for genetic and environmental factors, demonstrating substantial changes from first to third trimester in chorionic villi. Specific differences and stably expressed genes may be used to understand the specific role of the chorionic villi throughout gestation and develop first trimester biomarkers of placental health that transpire across gestation, which can be used for future development of biomarkers in maternal-fetal disease.

developmental biology↗

bioRxiv2023

Cellular heterogeneity of the developing worker honey bee (Apis mellifera) pupa: a single cell transcriptomics analysis

It is estimated that animals pollinate 87.5% of flowering plants worldwide and that managed honey bees (Apis mellifera) account for 30-50% of this ecosystem service to agriculture. In addition to their important role as pollinators, honey bees are well-established insect models for studying learning and memory, behaviour, caste differentiation, epigenetic mechanisms, olfactory biology, sex determination and eusociality. Despite their importance to agriculture, knowledge of honey bee biology lags behind many other livestock species. In this study we have used scRNA-Seq to map cell types to different developmental stages of the worker honey bee (prepupa at day 11 and pupa at day 15), and sought to determine their gene signatures and thereby provide potential functional annotations for as yet poorly characterized genes. To identify cell type populations we examined the cell-to-cell network based on the similarity of the single-cells transcriptomic profiles. Grouping similar cells together we identified 63 different cell clusters of which 15 clusters were identifiable at both stages. To determine genes associated with specific cell populations or with a particular biological process involved in honey bee development, we used gene co-expression analysis. We combined this analysis with literature mining, the honey bee protein atlas and Gene Ontology analysis to determine cell cluster identity. Of the cell clusters identified, 9 were related to the nervous system, 7 to the fat body, 14 to the cuticle, 5 to muscle, 4 to compound eye, 2 to midgut, 2 to hemocytes and 1 to malpighian tubule/pericardial nephrocyte. To our knowledge, this is the first whole single cell atlas of honey bees at any stage of development and demonstrates the potential for further work to investigate their biology of at the cellular level.

genomics↗

bioRxiv2023

Improving the annotation of the cattle genome by annotating transcription start sites in a diverse set of tissues and populations using CAGE sequencing

Understanding the genomic control of tissue-specific gene expression and regulation can help to inform the application of genomic technologies in farm animal breeding programmes. The fine mapping of promoters (transcription start sites [TSS]) and enhancers (divergent amplifying segments of the genome local to TSS) in different populations of cattle across a wide diversity of tissues provides information to locate and understand the genomic drivers of breed- and tissue-specific phenotypes. To this aim we used Cap Analysis Gene Expression (CAGE) sequencing to define TSS and their co-expressed short-range enhancers (<1kb) in the ARS-UCD1.2_Btau5.0.1Y reference genome (1000bulls run9) and analysed tissue- and population specificity of expressed promoters. We identified 51,295 TSS and 2,328 TSS-Enhancer regions shared across the three populations (Holstein, Charolais x Holstein and Kinsella beef composite [KC]). In addition, we performed a comparative analysis of our cattle dataset with available data for seven other species to identify TSS and TSS-Enhancers that are specific to cattle. The CAGE dataset will be combined with other transcriptomic information for the same tissues generated in the BovReg project to create a new high-resolution map of transcript diversity across tissues and populations in cattle. Here we provide the CAGE dataset and annotation tracks for TSS and TSS Enhancers in the cattle genome. This new annotation information will improve our understanding of the drivers of gene expression and regulation in cattle and help to inform the application of genomic technologies in breeding programmes.

genomics↗

bioRxiv2021

Sex differences in microRNA expression in first and third trimester human placenta

Maternal and fetal pregnancy outcomes related to placental function vary based on fetal sex, which may be the result of sexually dimorphic epigenetic regulation of RNA expression. We identified sexually dimorphic miRNA expression throughout gestation in human placentae. Next-generation sequencing was used to identify miRNA expression profiles in first and third trimester uncomplicated pregnancies using tissue obtained at chorionic villous sampling (n=113) and parturition (n=47). Sequencing and differential expression (DE) analysis identified 432 mature miRNAs expressed in the first trimester female, 425 in the first trimester male, 400 in the third trimester female, and 508 in the third trimester male placenta (baseMean >10). Of these, 11 sexually dimorphic (FDR<0.05, baseMean >10) miRNAs were identified in the first and 4 miRNAs were identified in the third trimester, including miR-361-5p, significant in both trimesters, all upregulated in females. Across gestation, 207 miRNAs were DE across gestation, common to both females and males, miR-4483, the most DE across gestation. There were twice as many female-specific differences across gestation as male-specific (44 miRNAs vs 21 miRNAs), indicating that miRNA abundance across human gestation is sexually dimorphic. Pathway enrichment analysis identified significant pathways that were differentially regulated in first and third trimester as well as across gestation. This work provides the normative sex dimorphic miRNA atlas in first and third trimester, as well as the sex independent and sex specific placenta miRNA atlas across gestation which may be used to identify biomarkers of placental function and direct functional studies investigating placental sex differences. Summary SentenceSex dimorphism in miRNA expression is more pronounced in first compared to third trimester placenta, and there are twice as many female-specific gestational differences, indicating miRNA abundance across human gestation is also sexually dimorphic.

developmental biology↗

bioRxiv2021

High-throughput miRNA-sequencing of the human placenta: expression throughout gestation

BackgroundAltered placenta miRNA abundance may impact the maternal-fetal interface and pregnancy outcomes. Understanding miRNA changes across gestation is essential before miRNAs can be used as biomarkers or prognostic indicators during pregnancy. Materials & MethodsUsing next-generation sequencing, we characterize the normative human placenta miRNA transcriptome in first (N=113) and third trimester (N=47). ResultsThere are 801 miRNAs expressed in both first and third trimester, including 182 with similar expression across gestation (P[≥]0.05) and 182 significantly different (FDR<0.05). Of placenta-specific miRNA clusters, C14MC is more upregulated in first trimester and C19MC is more highly expressed overall. ConclusionThis work provides a rich atlas of healthy pregnancies to direct functional studies investigating the epigenetic differences in first and third trimester placentae. Lay AbstractThe human body produces microRNAs which affect the expression of genes and proteins. This study uses next generation sequencing to identify the microRNA profile of first and third trimester human placentae using a large cohort (N=113 first, N=47 third trimester). All pregnancies resulted in healthy babies. We identify microRNAs with significantly different expression between first and third trimester, as well as stably expressed microRNAs. This work provides a baseline for future studies which may use microRNAs to monitor maternal-fetal health throughout pregnancy.

developmental biology↗

bioRxiv2021

Profiling of open chromatin in developing pig (Sus scrofa) muscle to identify regulatory regions

There is very little information about how the genome is regulated in domestic pigs (Sus scrofa). This lack of knowledge hinders efforts to define and predict the effects of genetic variants in pig breeding programmes. In order to address this knowledge gap, we need to identify regulatory sequences in the pig genome starting with regions of open chromatin. We have optimised the Improved Protocol for the Assay for Transposase-Accessible Chromatin (Omni-ATAC-Seq) to profile regions of open chromatin in flash frozen pig muscle tissue samples. This protocol has allowed us to identify putative regulatory regions in semitendinosus muscle from 24 male piglets. We collected samples from the smallest, average, and largest sized male piglets from each litter through five developmental time points. The ATAC-Seq data were mapped to Sscrofa11.1 using Bowtie2 and Genrich was used for post-alignment peak-calling. Of the 4,661 ATAC-Seq peaks identified that represent regions of open chromatin, >50% were within 1 kb of known transcription start sites. Differential read count analysis revealed 377 ATAC-Seq defined genomic regions where chromatin accessibility differed significantly across developmental time points. We found regions of open chromatin associated with down regulation of genes involved in muscle development that were present in small sized foetal piglets but absent in large foetal piglets at day 90 of gestation. The dataset that we have generated provides: i) a resource for studies of genome regulation in pigs, and ii) contributes valuable functional annotation information to filter genetic variants for use in genomic selection in pig breeding programmes.

genomics↗

bioRxiv2020

Global analysis of transcription start sites in the new ovine reference genome (Oar rambouillet v1.0)

The overall aim of the Ovine FAANG project is to provide a comprehensive annotation of the new highly contiguous sheep reference genome sequence (Oar rambouillet v1.0). Mapping of transcription start sites (TSS) is a key first step in understanding transcript regulation and diversity. Using 56 tissue samples collected from the reference ewe Benz2616 we have performed a global analysis of TSS and TSS- Enhancer clusters using Cap Analysis Gene Expression (CAGE) sequencing. CAGE measures RNA expression by 5 cap-trapping and has been specifically designed to allow the characterization of TSS within promoters to single-nucleotide resolution. We have adapted an analysis pipeline that uses TagDust2 for clean-up and trimming, Bowtie2 for mapping, CAGEfightR for clustering and the Integrative Genomics Viewer (IGV) for visualization. Mapping of CAGE tags indicated that the expression levels of CAGE tag clusters varied across tissues. Expression profiles across tissues were validated using corresponding polyA+ mRNA-Seq data from the same samples. After removal of CAGE tags with < 10 read counts, 39.3% of TSS overlapped with 5 ends of 31,113 transcripts that had been previously annotated by NCBI (out of a total of 56,308 from the NCBI annotation). For 25,195 of the transcripts, previously annotated by NCBI, no TSS meeting stringent criteria were identified. A further 14.7% of TSS mapped to within 50bp of annotated promoter regions. Intersecting these predicted TSS regions with annotated promoter regions ({+/-}50bp) revealed 46% of the predicted TSS were novel and previously un-annotated. Using whole genome bisulphite sequencing data from the same tissues we were able to determine that a proportion of these novel TSS were hypo-methylated (32.2%) indicating that they are likely to be reproducible rather than noise. This global analysis of TSS in sheep will significantly enhance the annotation of gene models in the new ovine reference assembly. Our analyses provide one of the highest resolution annotations of transcript regulation and diversity in a livestock species to date.

genomics↗