Biology subjects

Liorni, N.

Publications and source records attributed to Liorni, N..

3 recordsLinked to original sources

bioRxiv2023

APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants

APOGEE 2 is a mitochondrially-centered ensemble method designed to improve the accuracy of pathogenicity predictions for interpreting missense mitochondrial variants. Built on the joint consensus recommendations by the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP), APOGEE 2 features an improved machine learning method and a curated training set for enhanced performance metrics. It offers region-wise assessments of genome fragility and mechanistic analyses of specific amino acids that cause perceptible long-range effects on protein structure. With clinical and research use in mind, APOGEE 2 scores and pathogenicity probabilities are precompiled and available in MitImpact. APOGEE 2s ability to address challenges in interpreting mitochondrial missense variants makes it an essential tool in the field of mitochondrial genetics.

bioinformatics↗

bioRxiv2023

Investigating mitochondrial gene expression patterns in Drosophila melanogaster using network analysis to understand aging mechanisms

The process of aging is a complex phenomenon that involves a progressive decline in physiological functions required for survival and fertility. To better understand the mechanisms underlying this process, the scientific community has utilized several tools. Among them, mitochondrial DNA has emerged as a crucial factor in biological aging, given that mitochondrial dysfunction is thought to significantly contribute to this phenomenon. Additionally, Drosophila melanogaster has proven to be a valuable model organism for studying aging due to its low cost, capacity to generate large populations, and ease of genetic manipulation and tissue dissection. Moreover, graph theory has been employed to understand the dynamic changes in gene expression patterns associated with aging and to investigate the interactions between aging and aging-related diseases. In this study, we have integrated these approaches to examine the patterns of gene co-expression in Drosophila melanogaster at various stages of development. By applying graph-theory techniques, we have identified modules of co-expressing genes, highlighting those that contain a significantly high number of mitochondrial genes. We found important mitochondrial genes involved in aging and age-related diseases in Drosophila melanogaster, including UQCR-C1, ND-B17.2, ND-20, and Pdhb. Our findings shed light on the role of mitochondrial genes in the aging process and demonstrate the utility of Drosophila melanogaster as a model organism and graph theory in aging research.

bioinformatics↗

bioRxiv2022

Integrative Cut&Tag/RNA-Seq analysis of histone variant macroH2A1-dependent orchestration of human iPSCs reprogramming

Human-induced pluripotent stem cells (iPSCs) can be derived from adult stem cells by forced expression of defined transcription factors. This paves the way for autologous iPSC-derived therapies, which, however, are not yet considered safe. Moreover, reprogramming of somatic cells into iPSCs is an inefficient process, in the range of 0.1%-1%. The epigenetic mechanisms implicated in iPSCs reprogramming are not well understood. The substitution of canonical histone H2A with macroH2A1 histone variant exon-spliced isoforms (macroH2A1.1 and macroH2A1.2) appears as an emerging regulator of iPSCs identity. In particular, we have previously shown that overexpression of macroH2A1.1 led to a more efficient iPSCs reprogramming, by not fully defined mechanisms. Cleavage under targets and tagmentation (CUT&Tag) is a recent methodology used for robust epigenomic profiling of a limited amount of cells. Here, we performed the first integrative CUT&Tag/RNA-Seq analysis of the histone variant macroH2A1-dependent orchestration of iPSCs reprogramming using human umbilical vein endothelial cells (HUVEC) during their reprogramming into iPSC over-expressing tagged macroH2A1.1 or macroH2A1.2. Our results demonstrate a higher and more widespread genome occupancy and a greater number of differentially expressed genes orchestrated by macroH2A1.1 in HUVEC undergoing reprogramming as compared to macroH2A1.2, which involved pervasive functions related to the three embryonic germ layers and increased overlap with CTCF, FOS, GATA2, and POLR2A transcription factor binding sites. In particular, all predicted macroH2A1.1 activating pathways were related to ectoderm/neural processes. As macroH2A1 isoforms have been previously associated with pathologies of the nervous system, our findings may provide relevant molecular insights for modeling neurodegenerative diseases using iPSCs.

bioinformatics↗