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Handling multi-mapped reads in RNA-seq

Journal

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
Volume 18, Issue -, Pages 1569-1576

Publisher

ELSEVIER
DOI: 10.1016/j.csbj.2020.06.014

Keywords

RNA-seq; Multi-mapped reads; Duplicated genes; Noncoding RNAs; Gene isoforms; Expectation-maximization algorithm

Funding

  1. Natural Science and Engineering Research Council of Canada [NSERC] [RGPIN-2018-05412]
  2. Alexander-Graham-Bell Doctoral scholarship from NSERC
  3. NSERC Masters scholarship
  4. Fonds de Recherche du Quebec - Sante (FRQS) Research Scholar Junior 2 Career Award

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Many eukaryotic genomes harbour large numbers of duplicated sequences, of diverse biotypes, resulting from several mechanisms including recombination, whole genome duplication and retro-transposition. Such repeated sequences complicate gene/transcript quantification during RNA-seq analysis due to reads mapping to more than one locus, sometimes involving genes embedded in other genes. Genes of different biotypes have dissimilar levels of sequence duplication, with long-noncoding RNAs and messenger RNAs sharing less sequence similarity to other genes than biotypes encoding shorter RNAs. Many strategies have been elaborated to handle these multi-mapped reads, resulting in increased accuracy in gene/transcript quantification, although separate tools are typically used to estimate the abundance of short and long genes due to their dissimilar characteristics. This review discusses the mechanisms leading to sequence duplication, the biotypes affected, the computational strategies employed to deal with multi-mapped reads and the challenges that still remain to be overcome. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.

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