Biology subjects

Pirruccello, J.

Publications and source records attributed to Pirruccello, J..

3 recordsLinked to original sources

bioRxiv2026

Chromatin topology control by a muscle-specific ribosomal protein

Three-dimensional genome organization stabilizes cell-type-specific gene expression, yet the tissue-restricted factors that maintain chromatin insulation remain poorly understood. Here, we identify the muscle-specific ribosomal protein Rpl3l as an unexpected nuclear regulator of genome architecture in atrial cardiomyocytes. Rpl3l is enriched in the nucleus and nucleolus, where it binds its own genomic locus and stabilizes a CTCF-anchored chromatin boundary that represses the T-type calcium channel gene Cacna1h. Loss of Rpl3l weakens local chromatin insulation, increases long-range contacts across the Rpl3l-Cacna1h locus, derepresses Cacna1h, and increases susceptibility to atrial fibrillation (AF), which is suppressed by pharmacological inhibition of T-type calcium channels. Furthermore, AF-associated RPL3L variants exhibit impaired nucleolar localization, reduced rRNA binding, and defective repression of CACNA1H in human iPSC-derived atrial cardiomyocytes. Together, these findings reveal a ribosomal protein-chromatin axis linking genome insulation to ion-channel dosage control and cardiac rhythm stability, expanding the repertoire of cell-type-specific genome architecture regulators. HighlightsThe muscle-specific ribosomal protein Rpl3l exhibits unexpected nuclear and nucleolar enrichment. Rpl3l stabilizes a CTCF-anchored chromatin boundary to maintain atrial-specific local genome insulation. Loss of Rpl3l derepresses Cacna1h which encodes a T-type Ca2+ channel and increases atrial fibrillation susceptibility. Atrial fibrillation-associated RPL3L variants impair nucleolar targeting and CACNA1H repression

physiology↗

bioRxiv2020

Deep learning enables genetic analysis of the human thoracic aorta

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{middle dot}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.

genomics↗

bioRxiv2020

Analysis of cardiac magnetic resonance imaging traits in 29,000 individuals reveals shared genetic basis with dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is an important cause of heart failure and the leading indication for heart transplantation. Many rare genetic variants have been associated with DCM, but common variant studies of the disease have yielded few associated loci. As structural changes in the heart are a defining feature of DCM, we conducted a genome-wide association study (GWAS) of cardiac magnetic resonance imaging (MRI)-derived left ventricular measurements in 29,041 UK Biobank participants. 26 novel loci were associated with cardiac structure and function. These loci were found near 17 genes previously shown to cause Mendelian cardiomyopathies. A polygenic score of left ventricular end systolic volume was associated with incident DCM in previously disease-free individuals (hazard ratio = 1.54 per one standard deviation increase in the polygenic score, P = 2.1x10-16). Even among carriers of truncating mutations in TTN, the polygenic score influenced the size and function of the heart. These results further implicate common genetic polymorphisms in DCM pathogenesis.

genomics↗