Comparison of Stranded and Non-stranded RNA-Seq in Predicting Small RNAs in a Non-model Bacterium

التفاصيل البيبلوغرافية
العنوان: Comparison of Stranded and Non-stranded RNA-Seq in Predicting Small RNAs in a Non-model Bacterium
المؤلفون: Karel Sedlar, Ralf Zimmer
المصدر: Bioinformatics and Biomedical Engineering ISBN: 9783031078019
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Bioinformatics and Biomedical Engineering
ORCID
ZENODO
Lecture Notes in Computer Science. 2022, vol. 13347, issue II., p. 45-56.
بيانات النشر: Springer International Publishing, 2022.
سنة النشر: 2022
مصطلحات موضوعية: Small non-coding RNA, genome annotation, Clostridium beijerinckii NRRL B-598, RNA-Seq, Genome annotation, small non-coding RNA
الوصف: Thanks to their diversity, non-model bacteria represent an inexhaustible resource for microbial biotechnology. Their utilization is only limited by our lack of knowledge regarding the regulation of processes they are capable to perform. The problem lies in non-coding regulators, for example small RNAs, that are not so widely studied as coding genes. One possibility to overcome this hurdle is to use standard RNA-Seq data, gathered primarily to study gene expression, for the prediction of non-coding elements. Although computational tools to perform this task already exist, they require the utilization of stranded RNA-Seq data that must not be available for non-model organisms. Here, we showed that trans-encoded small RNAs can be predicted from non-stranded data with comparable sensitivity to stranded data. We used two RNA-Seq datasets of non-type strain Clostridium beijerinckii NRRL B-598, which is a promising hydrogen and butanol producer, and obtained comparable results for stranded and non-stranded datasets. Nevertheless, the non-stranded approach suffered from lower precision. Thus, the results must be interpreted with caution. In general, more benchmarking for tools performing direct prediction of small RNAs from standard RNA-Seq data is needed so these techniques could be adopted for automatic detection.
وصف الملف: text; application/pdf
ردمك: 978-3-031-07801-9
978-3-031-07802-6
تدمد: 0302-9743
1611-3349
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b89bc83a2487585f541121b35ba64f8dTest
https://doi.org/10.1007/978-3-031-07802-6_4Test
حقوق: OPEN
رقم الانضمام: edsair.doi.dedup.....b89bc83a2487585f541121b35ba64f8d
قاعدة البيانات: OpenAIRE
الوصف
ردمك:9783031078019
9783031078026
تدمد:03029743
16113349