BarkBase: Epigenomic Annotation of Canine Genomes.
Kate MegquierDiane P GenereuxJessica P HekmanRoss SwoffordJason Turner-MaierJeremy JohnsonJacob AlonsoXue LiKathleen MorrillLynne J AnguishMichele KoltookianBrittney LoganClaire Rebecca SharpLluis FerrerKerstin Lindblad-TohVicki N Meyers-WallenAndrew HoffmanElinor K KarlssonPublished in: Genes (2019)
Dogs are an unparalleled natural model for investigating the genetics of health and disease, particularly for complex diseases like cancer. Comprehensive genomic annotation of regulatory elements active in healthy canine tissues is crucial both for identifying candidate causal variants and for designing functional studies needed to translate genetic associations into disease insight. Currently, canine geneticists rely primarily on annotations of the human or mouse genome that have been remapped to dog, an approach that misses dog-specific features. Here, we describe BarkBase, a canine epigenomic resource available at barkbase.org. BarkBase hosts data for 27 adult tissue types, with biological replicates, and for one sample of up to five tissues sampled at each of four carefully staged embryonic time points. RNA sequencing is complemented with whole genome sequencing and with assay for transposase-accessible chromatin using sequencing (ATAC-seq), which identifies open chromatin regions. By including replicates, we can more confidently discern tissue-specific transcripts and assess differential gene expression between tissues and timepoints. By offering data in easy-to-use file formats, through a visual browser modeled on similar genomic resources for human, BarkBase introduces a powerful new resource to support comparative studies in dogs and humans.
Keyphrases
- gene expression
- genome wide
- copy number
- dna methylation
- single cell
- endothelial cells
- rna seq
- induced pluripotent stem cells
- transcription factor
- healthcare
- electronic health record
- public health
- big data
- pluripotent stem cells
- papillary thyroid
- high throughput
- mental health
- dna damage
- case control
- oxidative stress
- deep learning
- risk assessment
- health information
- young adults
- childhood cancer
- lymph node metastasis
- human health
- climate change