This is a PDF file of a peer-reviewed paper that has been accepted for publication. Although unedited, the content has been subjected to preliminary formatting. Nature is providing this early version of the typeset paper as a service to our authors and readers. The text and figures will undergo copyediting and a proof review before the paper is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers apply.

Background-The cells that form the arterial wall contribute to multiple vascular diseases. The extent of cellular heterogeneity within these populations has not been fully characterized. Recent advances in single cell RNA-sequencing makes it possible to identify and characterize cellular subpopulations.Methods-We validate a method for generating a droplet-based single cell atlas of gene expression in a normal blood vessel. Enzymatic dissociation of four whole mouse aortas was followed by single cell sequencing of over 10,000 cells.Results-Clustering analysis of gene expression from aortic cells identified 10 populations of cells representing each of the main arterial cell types-fibroblasts, vascular smooth muscle cells (VSMCs), endothelial cells (ECs), and immune cells including monocytes, macrophages, and lymphocytes. The most significant cellular heterogeneity was seen in the 3 distinct EC populations. Gene set enrichment analysis of these EC subpopulations identified a lymphatic EC cluster and two other populations more specialized in lipoprotein handling, angiogenesis, and extracellular matrix production. These subpopulations persist and exhibit similar changes in gene expression in response to a Western diet. Immunofluorescence for Vcam1 and Cd36 demonstrates regional heterogeneity in EC populations throughout the aorta.

Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending thoracic aorta in 4.6 million cardiac magnetic resonance images from the UK Biobank. We then conducted genome-wide association studies in 39,688 individuals, identifying 82 loci associated with ascending and 47 with descending thoracic aortic diameter, of which 14 loci overlapped. Transcriptome-wide analyses, rare-variant burden tests, and human aortic single nucleus RNA sequencing prioritized genes including SVIL , which was strongly associated with descending aortic diameter. A polygenic score for ascending aortic diameter was associated with thoracic aortic aneurysm in 385,621 UK Biobank participants (HR = 1.43 per s.d.; CI 1.32-1.54; P = 3.3 × 10 −20 ). Our results illustrate the potential for rapidly defining quantitative traits with deep learning, an approach that can be broadly applied to biomedical images.

The aorta is the largest blood vessel in the body, and enlargement or aneurysm of the aorta can predispose to dissection, an important cause of sudden death. While rare syndromes have been identified that predispose to aortic aneurysm, the common genetic basis for the size of the aorta remains largely unknown. By leveraging a deep learning architecture that was originally developed to recognize natural images, we trained a model to evaluate the dimensions of the ascending and descending thoracic aorta in cardiac magnetic resonance imaging. After manual annotation of just 116 samples, we applied this model to 3,840,140 images from the UK Biobank. We then conducted a genome-wide association study in 33,420 individuals, revealing 68 loci associated with ascending and 35 with descending thoracic aortic diameter, of which 10 loci overlapped. Integration of common variation with transcriptome-wide analyses, rare-variant burden tests, and single nucleus RNA sequencing prioritized SVIL, a gene highly expressed in vascular smooth muscle, that was significantly associated with the diameter of the ascending and descending aorta. A polygenic score for ascending aortic diameter was associated with a diagnosis of thoracic aortic aneurysm in the remaining 391,251 UK Biobank participants who did not undergo imaging (HR = 1.44 per standard deviation; P = 3.7·10−12). Defining the genetic basis of the diameter of the aorta may enable the identification of asymptomatic individuals at risk for aneurysm or dissection and facilitate the prioritization of potential therapeutic targets for the prevention or treatment of aortic aneurysm. Finally, our results illustrate the potential for rapidly defining novel quantitative traits derived from a deep learning model, an approach that can be more broadly applied to biomedical imaging data.

Earthworms show a wide spectrum of regenerative potential with certain species like Eisenia fetida capable of regenerating more than two-thirds of their body while other closely related species, such as Paranais litoralis seem to have lost this ability. Earthworms belong to the phylum Annelida, in which the genomes of the marine oligochaete Capitella telata and the freshwater leech Helobdella robusta have been sequenced and studied. Herein, we report the transcriptomic changes in Eisenia fetida (Indian isolate) during regeneration. Following injury, E. fetida regenerates the posterior segments in a time spanning several weeks. We analyzed gene expression changes both in the newly regenerating cells and in the adjacent tissue, at early (15days post amputation), intermediate (20days post amputation) and late (30 days post amputation) by RNAseq based de novo assembly and comparison of transcriptomes. We also generated a draft genome sequence of this terrestrial red worm using short reads and mate-pair reads. An in-depth analysis of the miRNome of the worm showed that many miRNA gene families have undergone extensive duplications. Sox4, a master regulator of TGF-beta mediated epithelial-mesenchymal transition was induced in the newly regenerated tissue. Genes for several proteins such as sialidases and neurotrophins were identified amongst the differentially expressed transcripts. The regeneration of the ventral nerve cord was also accompanied by the induction of nerve growth factor and neurofilament genes. We identified 315 novel differentially expressed transcripts in the transcriptome, that have no homolog in any other species. Surprisingly, 82% of these novel differentially expressed transcripts showed poor potential for coding proteins, suggesting that novel ncRNAs may play a critical role in regeneration of earthworm.

No abstract

No abstract

This is the first and largest genetic map the DPYD variants associated with adverse drug reaction to 5-FU in south Asian population. Our study highlights ethnic differences in allelic frequencies.