Comparison of Stranded and Non-stranded RNA-Seq in Predicting Small RNAs in a Non-model Bacterium
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU144965" target="_blank" >RIV/00216305:26220/22:PU144965 - isvavai.cz</a>
Výsledek na webu
<a href="https://link.springer.com/chapter/10.1007/978-3-031-07802-6_4" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-07802-6_4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-07802-6_4" target="_blank" >10.1007/978-3-031-07802-6_4</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Comparison of Stranded and Non-stranded RNA-Seq in Predicting Small RNAs in a Non-model Bacterium
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Comparison of Stranded and Non-stranded RNA-Seq in Predicting Small RNAs in a Non-model Bacterium
Popis výsledku anglicky
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.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Lecture Notes in Bioinformatics
ISBN
978-3-031-07802-6
ISSN
1611-3349
e-ISSN
—
Počet stran výsledku
12
Strana od-do
45-56
Název nakladatele
Springer Nature
Místo vydání
neuveden
Místo konání akce
Gran Canaria, Spain
Datum konání akce
27. 6. 2022
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000871766000004