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Bromley, R. E.

Publications and source records attributed to Bromley, R. E..

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The UTRs of Leishmania donovani vary in length and are enriched in potential regulatory structures

Leishmania spp. regulate gene expression largely post-transcriptionally, yet untranslated regions (UTRs) remain poorly delineated. We generated high-quality genome and transcriptome datasets for Leishmania donovani strain 1S2D (Ld1S) by combining PacBio HiFi de novo assembly with Oxford Nanopore direct RNA sequencing of promastigotes and axenic amastigotes. The genome assembly consists of 65 scaffolds totaling [~]33.3 Mb. Structural comparisons to LdBPK282A1 revealed numerous rearrangements, including some reshufling genes among polycistronic transcription units and validated by polycistronic reads from RNA sequencing. Promastigote and amastigote RNA sequencing produced 469,010 and 46,729 monocistronic reads containing a spliced-leader and a polyA tail sequences, defining 8,479 transcripts and supporting 7,415 of the 7,969 annotated protein coding genes, as well as 604 putative long non-coding RNAs. We annotated UTRs for 4,921 genes and observed that putative RNA G-quadruplexes were markedly enriched in UTRs. We also noted that 31.9% and 11.5% were expressed into multiple isoforms in promastigotes and amastigotes, respectively. Collectively, these data provide a comprehensive annotation of L. donovani genes and their UTRs and reveal widespread and stage-specific UTR length polymorphisms, and, overall, points to an important role of 3 UTR in post-transcriptional regulation in L. donovani. Author SummaryLeishmania donovani parasites cause visceral leishmaniasis, a deadly disease affecting hundreds of thousands of people worldwide. Unlike most eukaryotes, these parasites do not regulate their genes mainly at the level of transcription. Instead, control happens after the genes are transcribed, and much of this regulation depends on regions of RNA that are not translated into protein, called untranslated regions (UTRs). However, UTRs in Leishmania have remained poorly characterized. Here we generated high-quality genome and transcriptome resources for a clinical strain of L. donovani. By combining state-of-the-art long-read sequencing technologies, we precisely mapped thousands of UTRs and discovered that many genes produce transcripts with variable UTR lengths that differ between parasite life stages. We also found that UTRs are enriched in RNA structures called G-quadruplexes, which are known to influence gene regulation. These findings provide the most comprehensive view to date of UTRs in Leishmania and highlight their central role in controlling how genes are expressed during the parasites life cycle. Our work lays a foundation for future studies aimed at understanding parasite biology and identifying new targets for intervention.

genomics↗

Deciphering Bacterial and Archaeal Transcriptional Dark Matter and Its Architectural Complexity

Transcripts are potential therapeutic targets, yet bacterial transcripts remain biological dark matter with uncharacterized biodiversity. We developed and applied an algorithm to predict transcripts for Escherichia coli K12 and E2348/69 strains (Bacteria:gamma-Proteobacteria) with newly generated ONT direct RNA sequencing data while predicting transcripts for Listeria monocytogenes strains Scott A and RO15 (Bacteria:Firmicute), Pseudomonas aeruginosa strains SG17M and NN2 strains (Bacteria:gamma-Proteobacteria), and Haloferax volcanii (Archaea:Halobacteria) using publicly available data. From >5 million E. coli K12 ONT direct RNA sequencing reads, 2,484 mRNAs are predicted and contain more than half of the predicted E. coli proteins. While the number of predicted transcripts varied by strain based on the amount of sequence data used for the predictions, across all strains examined, the average size of the predicted mRNAs is 1.6-1.7 kbp while the median size of the predicted bacterial 5-and 3-UTRs are 30-90 bp. Given the lack of bacterial and archaeal transcript annotation, most predictions are of novel transcripts, but we also predicted many previously characterized mRNAs and ncRNAs, including post-transcriptionally generated transcripts and small RNAs associated with pathogenesis in the E. coli E2348/69 LEE pathogenicity islands. We predicted small transcripts in the 100-200 bp range as well as >10 kbp transcripts for all strains, with the longest transcript for two of the seven strains being the nuo operon transcript, and for another two strains it was a phage/prophage transcript. This quick, easy, inexpensive, and reproducible method will facilitate the presentation of operons, transcripts, and UTR predictions alongside CDS and protein predictions in bacterial genome annotation as important resources for the research community.

genomics↗