Biology subjects

Dalrymple, B. P.

Publications and source records attributed to Dalrymple, B. P..

3 recordsLinked to original sources

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↗

bioRxiv2020

Tracing the origin of a new organ by inferring the genetic basis of rumen evolution

The rumen is the hallmark organ of ruminants and hosts a diverse ecosystem of microorganisms that facilitates efficient digestion of plant fibers. We used 897 transcriptomes from three Cetartiodactyla lineages: ruminants, camels and cetaceans, as well as data from ruminant comparative genomics and functional assays to explore the genetic basis of rumen origin and evolution. Comparative analyses reveal that the rumen and the first-chamber stomachs of camels and cetaceans shared a common tissue origin from the esophagus. The rumen recruited genes from other tissues/organs and up-regulated many esophagus genes to aquire functional innovations involving epithelium absorption, improvement of the ketone body metabolism and regulation of microbial community. These innovations involve such genetic changes as ruminant-specific conserved elements, newly evolved genes and positively selected genes. Our in vitro experiements validate the functions of one enhancer, one positively selected gene and two newly evolved antibacterial genes. Our study provides novel insights into the origin and evolution of a complex organ.

evolutionary biology↗

bioRxiv2017

Mammalian genomic regulatory regions predicted by utilizing human genomics, transcriptomics and epigenetics data

Genome sequences for hundreds of mammalian species are available, but an understanding of their genomic regulatory regions, which control gene expression, is only beginning. A comprehensive prediction of potential active regulatory regions is necessary to functionally study the roles of the majority of genomic variants in evolution, domestication, and animal production. We developed a computational method to predict regulatory DNA sequences (promoters, enhancers and transcription factor binding sites) in production animals (cows and pigs) and extended its broad applicability to other mammals. The method utilizes human regulatory features identified from thousands of tissues, cell lines, and experimental assays to find homologous regions that are conserved in sequences and genome organization and are enriched for regulatory elements in the genome sequences of other mammalian species. Importantly, we developed a filtering strategy, including a machine learning classification method, to utilize a very small number of species-specific experimental datasets available to select for the likely active regulatory regions. The method finds the optimal combination of sensitivity and accuracy to unbiasedly predict regulatory regions in mammalian species. Furthermore, we demonstrated the utility of the predicted regulatory datasets in cattle for prioritizing variants associated with multiple production and climate change adaptation traits, and identifying potential genome editing targets.

genomics↗