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Manley, T.

Publications and source records attributed to Manley, T..

2 recordsLinked to original sources

UBA1-CDK16: A Sex-Specific Chimeric RNA and Its Role in Immune Sexual Dimorphism

RNA processing mechanisms, such as alternative splicing and RNA editing, have been recognized as critical means to expand the transcriptome. Chimeric RNAs formed by intergenic splicing provide another potential layer of RNA diversification. By analyzing a large set of RNA-Seq data and validating results in over 1,200 blood samples, we identified UBA1-CDK16, a female-specific chimeric transcript. Intriguingly, both parental genes, are expressed in males and females. Mechanistically, UBA1-CDK16 is produced by cis-splicing between the two adjacent X-linked genes, originating from the inactive X chromosome. A female-specific chromatin loop, formed between the junction sites, facilitates the alternative splicing of its readthrough precursor. This unique chimeric transcript exhibits evolutionary conservation, evolving to be female-specific from non-human primates to humans. Furthermore, our investigation reveals that UBA1-CDK16 is enriched in the myeloid lineage and plays a regulatory role in myeloid differentiation. Notably, female COVID-19 patients who tested negative for this chimeric transcript displayed higher counts of neutrophils, highlighting its potential role in disease pathogenesis. These findings support the notion that chimeric RNAs represent a new repertoire of transcripts that can be regulated independently from the parental genes, and a new class of RNA variance with potential implications in sexual dimorphism and immune responses.

genomics↗

RTCpredictor: Identification of Read-Through Chimeric RNAs from RNA Sequencing Data

Read-through chimeric RNAs are gaining attention in cancer and other research fields, yet current tools often fail in predicting them. We have thus developed the first read-through chimeric RNA specific prediction method, RTCpredictor, utilizing a fast ripgrep algorithm to search for all possible exon-exon combinations of parental gene pairs. Compared with other ten popular tools, RTCpredictor achieved top performance on both simulated and real datasets. We randomly selected up to 30 candidate read-through chimeras predicted from each software method and experimentally validated a total of 109 read-throughs and on this set, RTCpredictor outperformed all the other methods. In addition, RTCpredictor (https://github.com/sandybioteck/RTCpredictor) has less memory requirements and faster execution time.

genomics↗