Biology subjects

Sparklin, B. C.

Publications and source records attributed to Sparklin, B. C..

3 recordsLinked to original sources

bioRxiv2024

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↗

bioRxiv2023

Common Analysis of Direct RNA SequencinG CUrrently Leads to Misidentification of 5-Methylcytosine Modifications at GCU Motifs

RNA modifications, such as methylation, can be detected with Oxford Nanopore Technologies direct RNA sequencing. One commonly used tool for detecting 5-methylcytosine (m5C) modifications is Tombo, which uses an "Alternative Model" to detect putative modifications from a single sample. We examined direct RNA sequencing data from diverse taxa including virus, bacteria, fungi, and animals. The algorithm consistently identified a 5-methylcytosine at the central position of a GCU motif. However, it also identified a 5-methylcytosine in the same motif in fully unmodified in vitro transcribed RNA, suggesting that this a frequent false prediction. In the absence of further validation, several published predictions of 5-methylcytosine in human coronavirus and human cerebral organoid RNA in a GCU context should be reconsidered. IMPORTANCEThe detection of chemical modifications to RNA is a rapidly expanding field within epigenetics. Nanopore sequencing technology provides an attractive means of detecting these modifications directly on the RNA, but accurate modification predictions are dependent upon the software developed to interpret the sequencing results. One of these tools, Tombo, allows users to detect modifications using sequencing results from a single RNA sample. However, we find that this method falsely predicts modifications in a specific sequence context across a variety of RNA samples, including RNA that lacks modifications. Results from previous publications include predictions in human coronaviruses with this sequence context and should be reconsidered. Our results highlight the importance of using RNA modification detection tools with caution in the absence of a control RNA sample for comparison.

genomics↗

bioRxiv2020

Comparison of long read sequencing technologies in resolving bacteria and fly genomes

BackgroundThe newest generation of DNA sequencing technology is highlighted by the ability to sequence reads hundreds of kilobases in length, and the increased availability of long read data has democratized the genome sequencing and assembly process. PacBio and Oxford Nanopore Technologies (ONT) have pioneered competitive long read platforms, with more recent work focused on improving sequencing throughput and per-base accuracy. Released in 2019, the PacBio Sequel II platform advertises substantial enhancements over previous PacBio systems. ResultsWe used whole-genome sequencing data produced by two PacBio platforms (Sequel II and RS II) and two ONT protocols (Rapid Sequencing and Ligation Sequencing) to compare assemblies of the bacteria Escherichia coli and the fruit fly Drosophila ananassae. Sequel II assemblies had higher contiguity and consensus accuracy relative to other methods, even after accounting for differences in sequencing throughput. ONT RAPID libraries had the fewest chimeric reads in addition to superior quantification of E. coli plasmids versus ligation-based libraries. The quality of assemblies can be enhanced by adopting hybrid approaches using Illumina libraries for bacterial genome assemblies or combined ONT and Sequel II libraries for eukaryotic genome assemblies. Genome-wide DNA methylation could be detected using both technologies, however ONT libraries enabled the identification of a broader range of known E. coli methyltransferase recognition motifs in addition to undocumented D. ananassae motifs. ConclusionsThe ideal choice of long read technology may depend on several factors including the question or hypothesis under examination. No single technology outperformed others in all metrics examined.

genomics↗