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Audouin, K.

Publications and source records attributed to Audouin, K..

2 recordsLinked to original sources

Natural variations of aging of cardiac performance in Drosophila identifies a central function for the PAR domain bZIP transcription factor Pdp1/dHLF in cardiac senescence

The identification of genetic factors influencing cardiac senescence in natural populations is central to our understanding of cardiac aging and to identify the etiology of associated cardiac disorders in human populations. However, the genetic underpinning of complex traits in human is almost impossible, due to the infeasibility to control genetic background and gene-environment interactions. Drosophila has striking similarities in cardiac aging with humans, highlighting the conserved nature of cardiac aging for organisms with a heart. Leveraging on a large collection of inbred lines from the Drosophila Genetic Reference Panel (DGRP), we provide an accurate analysis of cardiac senescence in a natural population of flies. This permitted the discovery of an unprecedented number of variants and associated genes significantly associated to the natural variation of cardiac aging. We focused on the function of the PAR-domain bZIP transcription factor Pdp1 for which several variants were found associated with natural variation of the aging of multiple cardiac functional traits. We demonstrated that Pdp1 cell autonomously plays a central role in cardiac senescence and might do so by regulating mitochondria homeostasis. Overall, our work provides a unique resource regarding the genetics of cardiac aging in a natural population.

genetics↗

TrEMOLO: Accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches

Transposable Element MOnitoring with LOng-reads (TrEMOLO) is a new software that combines assembly- and mapping-based approaches to robustly detect genetic elements called transposable elements (TEs). Using high- or low-quality genome assemblies, TrEMOLO can detect most TE insertions and deletions and estimate their allele frequency in populations. Benchmarking with simulated data revealed that TrEMOLO outperforms other state-of-the-art computational tools. TE detection and frequency estimation by TrEMOLO were validated using simulated and experimental datasets. Therefore, TrEMOLO is a comprehensive and suitable tool to accurately study TE dynamics. TrEMOLO is available under GNU GPL3.0 at https://github.com/DrosophilaGenomeEvolution/TrEMOLO.

bioinformatics↗