DRAGoM: Classification and Quantification of Noncoding RNA in Metagenomic Data

Autor: Ben Liu, Sirisha Thippabhotla, Jun Zhang, Cuncong Zhong
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Frontiers in Genetics, Vol 12 (2021)
Druh dokumentu: article
ISSN: 1664-8021
DOI: 10.3389/fgene.2021.669495
Popis: Noncoding RNAs (ncRNAs) play important regulatory and functional roles in microorganisms, such as regulation of gene expression, signaling, protein synthesis, and RNA processing. Hence, their classification and quantification are central tasks toward the understanding of the function of the microbial community. However, the majority of the current metagenomic sequencing technologies generate short reads, which may contain only a partial secondary structure that complicates ncRNA homology detection. Meanwhile, de novo assembly of the metagenomic sequencing data remains challenging for complex communities. To tackle these challenges, we developed a novel algorithm called DRAGoM (Detection of RNA using Assembly Graph from Metagenomic data). DRAGoM first constructs a hybrid graph by merging an assembly string graph and an assembly de Bruijn graph. Then, it classifies paths in the hybrid graph and their constituent readsinto differentncRNA families based on both sequence and structural homology. Our benchmark experiments show that DRAGoMcan improve the performance and robustness over traditional approaches on the classification and quantification of a wide class of ncRNA families.
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