Biology subjects

Meller, R.

Publications and source records attributed to Meller, R..

4 recordsLinked to original sources

bioRxiv2024

Genetic ancestry and population structure in the All of Us Research Program cohort

The NIH All of Us Research Program (All of Us) aims to build one of the worlds most diverse population biomedical datasets in support of equitable precision medicine. For this study, we analyzed participant genomic variant data to assess the extent of population structure and to characterize patterns of genetic ancestry for the All of Us cohort (n=297,549). Unsupervised clustering of genomic principal component analysis (PCA) data revealed a non-uniform distribution of genetic diversity and substantial population structure in the All of Us cohort, with dense clusters of closely related participants interspersed among less dense regions of genomic PC space. Supervised genetic ancestry inference was performed using genetic similarity between All of Us participants and global reference population samples. Participants show diverse genetic ancestry, with major contributions from European (66.4%), African (19.5%), Asian (7.6%), and American (6.3%) continental ancestry components. Participant genetic similarity clusters show group-specific genetic ancestry patterns, with distinct patterns of continental and subcontinental ancestry among groups. We also explored how genetic ancestry changes over space and time in the United States (US). African and American ancestry are enriched in the southeast and southwest regions of the country, respectively, whereas European ancestry is more evenly distributed across the US. The diversity of All of Us participants genetic ancestry is negatively correlated with age; younger participants show higher levels of genetic admixture compared to older participants. Our results underscore the ancestral genetic diversity of the All of Us cohort, a crucial prerequisite for genomic health equity.

bioinformatics↗

bioRxiv2022

The interplay between lncRNAs, RNA-binding proteins and viral genome during SARS-CoV-2 infection reveals strong connections with regulatory events involved in RNA metabolism and immune response.

Viral infections are complex processes based on an intricate network of molecular interactions. The infectious agent hijacks components of the cellular machinery for its profit, circumventing the natural defense mechanisms triggered by the infected cell. The successful completion of the replicative viral cycle within a cell depends on the function of viral components versus the cellular defenses. Non-coding RNAs (ncRNAs) are important cellular modulators, either promoting or preventing the progression of viral infections. Among these ncRNAs, the long non-coding RNA (lncRNA) family is especially relevant due to their intrinsic functional properties and ubiquitous biological roles. Specific lncRNAs have been recently characterized as modulators of the cellular response during infection of human host cells by single stranded RNA viruses. However, the role of host lncRNAs in the infection by human RNA coronaviruses such as SARS-CoV-2 remains uncharacterized. In the present work, we have performed a transcriptomic study of a cohort of patients with different SARS-CoV-2 viral load. Our results revealed the existence of a SARS-CoV-2 infection-dependent pattern of transcriptional up-regulation in which specific lncRNAs are an integral component. To determine the role of these lncRNAs, we performed a functional correlation analysis complemented with the study of the validated interactions between lncRNAs and RNA-binding proteins (RBPs). This combination of in silico functional association studies and experimental evidence allowed us to identify a lncRNA signature composed of six elements - NRIR, BISPR, MIR155HG, FMR1-IT1, USP30-AS1, and U62317.2 - associated with the regulation of SARS-CoV-2 infection. We propose a competition mechanism between the viral RNA genome and the regulatory lncRNAs in the sequestering of specific RBPs that modulates the interferon response and the regulation of RNA surveillance by nonsense-mediated decay (NMD). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC="FIGDIR/small/485903v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@4368c9org.highwire.dtl.DTLVardef@1948201org.highwire.dtl.DTLVardef@e31fd9org.highwire.dtl.DTLVardef@1400805_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical abstractModel of interactions among lncRNA and cognate RNA-binding proteins in SARS-CoV-2 infection. According to our model, the viral genome can establish direct interactions with three core proteins (DDX3X, UPF1 and IGF2BP2) involved in mRNA metabolism and regulation of the interferon response, which are also components of a SARS-CoV-2 lncRNA-centered regulatory network. The competition between viral RNA and lncRNAs could act as a counteracting factor for the normal function of homeostatic lncRNA-centered regulatory networks, contributing to viral progression and replication. Black arrows depict physical interactions between network components; red arrows represent functional relationships.

bioinformatics↗

bioRxiv2022

Targeted Down Regulation Of Core Mitochondrial Genes During SARS-CoV-2 Infection

Defects in mitochondrial oxidative phosphorylation (OXPHOS) have been reported in COVID-19 patients, but the timing and organs affected vary among reports. Here, we reveal the dynamics of COVID-19 through transcription profiles in nasopharyngeal and autopsy samples from patients and infected rodent models. While mitochondrial bioenergetics is repressed in the viral nasopharyngeal portal of entry, it is up regulated in autopsy lung tissues from deceased patients. In most disease stages and organs, discrete OXPHOS functions are blocked by the virus, and this is countered by the host broadly up regulating unblocked OXPHOS functions. No such rebound is seen in autopsy heart, results in severe repression of genes across all OXPHOS modules. Hence, targeted enhancement of mitochondrial gene expression may mitigate the pathogenesis of COVID-19. One-Sentence SummaryCovid-19 is associated with targeted inhibition of mitochondrial gene transcription.

molecular biology↗

bioRxiv2020

NASA GeneLab RNA-Seq Consensus Pipeline: Standardized Processing of Short-Read RNA-Seq Data

With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility and reusability of pipeline data, to provide a template for data processing of future spaceflight-relevant datasets, and to encourage cross-analysis of data from other databases with the data available in GeneLab.

bioinformatics↗