BLASTAssemb: An approach to construct genetic elements using BLAST

Rahman, Tasnim; Chowdhury, Tasnova; Tabrejee, Shamira; Chowdhury, Masud H.; Shoyaib, Mohammad

doi:10.1109/skima.2014.7083544

Cited by 1 publication

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“…This algorithm combines the capability of BLAST (Basic local alignment search tool) (Altschul et al 1990, Zhao and Chu 2014, Oehmen and Baxter 2013, which is a well known tool in the bioinformatics community, as well as a gap filling search (GFS) algorithm (Rahman et al 2014). To validate this proposed method, we have constructed a set of promoter using the raw genome sequence of Pokkali rice variety with the help of promoter sequences of Japonica rice variety as reference sequences.…”

Section: Introductionmentioning

confidence: 99%

SeqDev: An Algorithm for Constructing Genetic Elements Using Comparative Assembly

Rahman

Heickal

Tabrejee

et al. 2016

Plant Tissue Cult. & Biotech.

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With the availability of recent next generation sequencing technologies and their low cost, genomes of different organisms are being sequenced frequently. Therefore, quick assembly of genome, transcriptome, and target contigs from the raw data generated through the sequencing technologies has become necessary for better understanding of different biological systems. This article proposes an algorithm, namely SeqDev (Sequence Developer) for constructing contigs from raw reads using reference sequences. For this, we considered a weighted frequency-based consensus mechanism named BlastAssemb for primary construction of a sequence with gaps. Then, we adopted suffix array and proposed a gap filling search (GFS) algorithm for searching the missing sequences in the primary construct. For evaluating our algorithm, we have chosen Pokkali (rice) raw genome and Japonica (rice) as our reference data. Experimental results demonstrated that our proposed algorithm accurately constructs promoter sequences of Pokkali from its raw genome data. These constructed promoter sequences were 93 -100% identical with the reference and also aligned with 96 -100% of corresponding reference sequences with eValue ranging from 0.0 -2e -14 . All these results indicated that our proposed method could be a potential algorithm to construct target contigs from raw sequences with the help of reference sequences. Further wet lab validation with specific Pokkali promoter sequence will boost this method as a robust algorithm for target contig assembly.

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