Biology subjects

Keil, N.

Publications and source records attributed to Keil, N..

4 recordsLinked to original sources

bioRxiv2026

Sex and Alternative Splicing in Disease: a meta-analytic approach to identify interactions

How cell type, sex and disease interact and affect gene expression and splicing is an important, but complicated question. Visualizing and testing specific hypotheses around these complex interactions is an important first step to identifying molecular components underpinning complex disease. Using a meta-analytical framework, we develop an analytical path for identifying testable molecular hypotheses of complex interactions between splicing, sex, disease and cell type. We focus on type 1 diabetes (T1D) but the approach is generalizable to any complex disease with defined candidate loci. Previous studies report T1D-associated splicing in candidate genes, differences in disease effects across immune cell types, sex effects on splicing and cell-type-specific splicing. However, identifying and interpreting complex interactions between sex, splicing and disease are challenging. Here we demonstrate how a gene expression study of T1D, designed to evaluate these interactions can be analyzed in a straightforward manner. We find that sex-dependent T1D-associated splicing is markedly more prevalent in CD4 T cells than in CD8 T cells, affecting 72% of T1D candidate genes in CD4 cells compared to 30% in CD8 cells. We pinpoint exons whose rate of inclusion is affected by the interaction of sex and disease. We use long-read RNAseq to identify novel intron retention events and splice sites which are quantified with short-reads leading to a richer description of the regulatory impact of T1D on alternative splicing. We identify a set of candidate isoforms for follow-up molecular studies in BACH2, a transcription factor known to be relevant in disease prevalence.

genomics↗

bioRxiv2026

A framework for identifying transcript orthologs: the evolution of sex bias in alternative transcript structure in Drosophila

BackgroundRecent advances in long read technologies provide an unprecedented opportunity to study transcript evolution. However, comparative evolutionary studies, even in Drosophila, are limited by inconsistent and incomplete annotation, and the lack of annotated transcript homology. ResultsIn this study of five species spanning 28 million years (D. melanogaster, D. simulans, D. yakuba, D. santomea and D. serrata), we infer transcript homology using reciprocal liftover, and orthology using network analyses, with data validation from long read RNA-seq of male and female head tissue. We build the first genus level annotation, with 15,996 genes and 56,370 transcripts. Expressed transcripts are conserved, 73% of transcript orthologs are detected in all species. Even the improved annotation underestimates the number of genes with alternative transcripts, with 75% of genes expressing multiple structurally diverse transcripts. In a replicated quantitative evaluation of [~]10,000 genes, both male and female-biased transcripts are expressed in 410 (D. melanogaster), 608 (D. simulans), and 493 (D. serrata) genes and in 118 orthologous genes in the D. melanogaster - D. simulans species pair, indicating greater potential for resolution of sexual conflict by alternative transcription than previously appreciated. We identified 605 transcript orthologs conserved for sex bias in the D. melanogaster-D. simulans species pair and of these, 22 male and 19 female-biased transcripts were conserved in sex bias with the outgroup D. serrata, including transcripts of genes involved in brain development, Sxl target Glutamine synthetase 2 and ciboulot. ConclusionsConserved alternative transcripts suggest that transcriptional diversity is a pervasive driver of the evolution of functional diversity.

genomics↗

bioRxiv2026

Non-canonical histone H3.3 and its chaperones HIRA and DAXX participate in the regulation of KSHV latency

Kaposis sarcoma-associated herpesvirus (KSHV), also named HHV-8, is the etiological agent of Kaposi sarcoma (KS), Primary effusion lymphoma (PEL), and Multicentric Castlemans disease. After de novo infection, KSHV genomes rapidly circularize and acquire a chromatin state that favors latency. During latency, the KSHV episome is decorated with distinct epigenetic marks that segregate the viral genome into transcriptionally active and repressed domains, enabling persistent silencing of lytic genes while retaining the capacity for reactivation. Transcription activity of chromatin is regulated at multiple levels, including the incorporation of histone variants such as H3.3, by a specific set of histone chaperones such as HIRA and DAXX. The interaction between LANA and these interphase active chaperones suggests that H3.3 deposition is a critical driver of early chromatinization and the long-term stability of KSHV latency. We detected rapid H3.3 deposition on KSHV episomes and on episomes within long-term infected cells. Moreover, we demonstrated that genetically disrupting the host H3.3 chaperone HIRA pathway by CRISPR/Cas9-mediated knockout impacted the regulation of LANA and maintenance of viral latency that was not altered in DAXX knockout cells. Collectively, these results support a role for HIRA-mediated H3.3 deposition in the regulation of KSHV latency.

molecular biology↗

bioRxiv2024

SQANTI-reads: a tool for the quality assessment of long read data in multi-sample lrRNA-seq experiments.

SQANTI-reads leverages SQANTI3, a tool for the analysis of the quality of transcript models, to develop a read-level quality control framework for replicated long-read RNA-seq experiments. The number and distribution of reads, as well as the number and distribution of unique junction chains (transcript splicing patterns), in SQANTI3 structural categories are informative of raw data quality. Multi-sample visualizations of QC metrics are presented by experimental design factors to identify outliers. We introduce new metrics for 1) the identification of potentially under-annotated genes and putative novel transcripts and for 2) quantifying variation in junction donors and acceptors. We applied SQANTI-reads to two different datasets, a Drosophila developmental experiment and a multi-platform dataset from the LRGASP project and demonstrate that the tool effectively reveals the impact of read coverage on data quality, and readily identifies strong and weak splicing sites. SQANTI-reads is open source and available for download at GitHub.

bioinformatics↗