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RESCOT: Restriction Enzyme Set and Combination Optimization Tools for rNMP Capture Techniques.
Xu, Penghao; Storici, Francesca.
Afiliación
  • Xu P; School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
  • Storici F; School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Theor Comput Sci ; 894: 203-213, 2021 Nov.
Article en En | MEDLINE | ID: mdl-34924677
ABSTRACT
The incorporation of ribonucleoside monophosphates (rNMPs) in genomic DNA is a frequent phenomenon in many species, often associated with genome instability and disease. The ribose-seq technique is one of a few techniques designed to capture and map rNMPs embedded in genomic DNA. The first step of ribose-seq is restriction enzyme (RE) fragmentation, which cuts the genome into smaller fragments for subsequent rNMP capture. The RE selection chosen for genomic DNA fragmentation in the first step of the rNMP-capture techniques determines the genomic regions in which the rNMPs can be captured. Here, we designed a computational method, Restriction Enzyme Set and Combination Optimization Tools (RESCOT), to calculate the genomic coverage of rNMP-captured regions for a given RE set and to optimize the RE set to significantly increase the rNMP-captured-region coverage. Analyses of ribose-seq libraries for which the RESCOT tools were applied reveal that many rNMPs were captured in the expected genomic regions. Since different rNMP-mapping techniques utilize RE fragmentation and purification steps based on size-selection of the DNA fragments in the protocol, we discuss the possible usage of RESCOT for other rNMP-mapping techniques. In summary, RESCOT generates optimized RE sets for the fragmentation step of many rNMP capture techniques to maximize rNMP capture rate and thus enable researchers to better study characteristics of rNMP incorporation.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Theor Comput Sci Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Theor Comput Sci Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos
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