Biology subjects

Labib, T.

Publications and source records attributed to Labib, T..

3 recordsLinked to original sources

bioRxiv2025

HaploExplore, first software specifically designed for the detection of minor allele (MiA-) Haploblocks

MotivationHaplotype blocks in the genome are informative of evolutionary processes and they play a pivotal role in describing the genomic variability across human populations and susceptibility/resistance to diseases. Several software have been developed for haplotype blocks detection, but they do not distinguish between the impacts of major and minor SNP alleles. In this study, we present a powerful haploblock detection software, specifically designed for identifying haploblocks associated with SNP minor allele haploblocks (MiA-haploblocks). These haploblocks are particularly important as they can significantly influence phenotypic traits, offering a novel approach for studying genetic associations and complex traits. ResultsHaploExplore operates on VCF files containing phased data, exhibiting rapid processing times and generating user-friendly outputs. Its results are convergent for populations starting from 100 individuals. A comparative analysis of HaploExplore against other haploblock detection software revealed its superiority in terms of either simplicity, or flexibility, or speed, with the unique capability to target minor alleles. HaploExplore will be very useful for evolutionary genomics and for GWAS analysis in human diseases, given that the effects of genetic associations may accumulate within a specific haploblock.

genomics↗

bioRxiv2025

Transcriptomic analysis of chronic chikungunya in the Reunionese CHIKGene cohort uncovers a shift in gene expression more than 10 years after infection

AimIn 2005-2006, a chikungunya epidemic of unprecedented magnitude hit Reunion Island, which raised a public health concern through the substantial proportions of long-lasting manifestations. To understand the pathophysiology underlying chronic chikungunya (CC), we designed the CHIKGene cohort study and collected blood samples from 133 subjects diagnosed with CC and from 86 control individuals that had recovered within 3 months, 12-to-15 years after exposure. MethodsWe conducted bulk RNAseq analysis on peripheral blood mononuclear cells to find differentially expressed genes (DEGs), gene set enrichment analysis (GSEA) and gene ontologies to uncover top-level enriched terms associated with DEGs, and weighted gene correlation network analysis (WGCNA) to elucidate underlying cellular processes. ResultsAmong 1549 DEGs, gene expression analysis identified 10 top genes including NR4A2 and TRIM58 (upregulated in CC), IGHG3 and IGHV3-49 (downregulated in CC) linked to immune regulation, OSBP2 (upregulated in CC) and SEMA6B (downregulated in CC) linked to neuronal homeostasis and axon guidance, respectively. GSEA and WGCNA unveiled cellular processes such as "Metabolism of RNA" and "Cell Cycle". ConclusionsThis study uncovers a shift in gene expression of CC subjects. IGHG3 and IGHV3-49 gene shut-offs spotlight the importance of neutralizing antibodies against chikungunya virus in the progression to chronic disease. Human diseases associations highlight connections to rheumatoid arthritis, nervous and cardiac systems. GSEA and WGCNA bounce the hypotheses of a persistent viral reservoir or an increased susceptibility to RNA viral pathogens with new onset infections. Together, our findings might offer potential targets for therapeutic options aimed at alleviating chronic chikungunya.

bioinformatics↗

bioRxiv2024

Deep analysis of the Major Histocompatibility Complex associations using covariate analysis and haploblocks unravels new mechanisms for the molecular etiology of Elite Control in AIDS

IntroductionWe have reanalyzed the genomic data from the International Collaboration for the Genomics of HIV (ICGH), focusing on HIV-1 Elite Controllers (EC). MethodsA genome-wide association study (GWAS) was performed, comparing 543 HIV-1 EC individuals with 3,272 uninfected controls (CTR) of European ancestry. 8 million single nucleotide polymorphisms (SNPs) and HLA class I and class II gene alleles were imputed to compare EC and CTR. Results2,626 SNPs were associated with EC (p<5.10-8), all located within the Major Histocompatibility Complex (MHC) region. Stepwise regression analysis narrowed this list to 17 SNPs. In parallel, 22 HLA class I and II alleles were associated with EC. Through meticulous mapping of the LD between all identified signals and employing reciprocal covariate analyses, we delineated a final set of 6 independent SNPs and 3 HLA class I gene alleles that accounted for most of the associations observed with EC. Our study revealed the presence of cumulative haploblock effects (SNP rs9264942 contributing to the HLA-B*57:01 effect) and that several HLA allele associations were in fact caused by SNPs in linkage disequilibrium (LD). Upon investigating SNPs in LD with the selected 6 SNPs and 3 HLA class I alleles for their impact on protein function (either damaging or differential expression), we identified several compelling mechanisms potentially explaining EC among which: a multi-action mechanism of HLA-B*57:01 involving MICA mutations and MICB differential expression overcoming the HIV-1 blockade of NK cell response, and overexpression of ZBTB12 with a possible anti-HIV-1 effect through HERV-K interference; a deleterious mutation in PPP1R18 favoring viral budding associated with rs1233396. ConclusionOur results show that MHC influence on EC likely extends beyond traditional HLA class I or class II allele associations, encompassing other MHC SNPs with various biological impacts. They point to the key role of NK cells in preventing HIV-1 infection. Our analysis shows that HLA-B*57:01 is indeed associated with a partially functional NK cell response which could also explain this markers involvement in other diseases such as psoriasis. More broadly, our findings suggest that within any HLA class I and II association in diseases, there may exist distinct causal SNPs within this crucial, gene-rich, and LD-rich MHC region.

immunology↗