NGS-data analysis for netagenome cellulose- and Xylan- degrading enzymes finding - Ibrahim Ali, Noorbatcha; Hamzah, Mohd. Salleh (2017)
Abstract. For the aim of finding cellulose- and xylan-degrading enzymes needed in green industry to produce biofuel from plant biomass, a metagenomic DNA library from palm oil mill effluent (POME) was constructed and high-throughputly screened. The positive clones’ DNA were sequenced with next generation sequencing and raw data (short insert-paired) was analyzed with bioinformatic tools. First, the quality of 64.821.599 reverse and forward sequences of 101bp length raw data was identified using Fastqc. Then, raw data filtering was done by trimming low quality values and short reads and the vector sequences were removed and again the output was checked and the trimming was repeated until a high quality read sets was obtained. The second step was the de novo assembly of sequences to reconstruct 2900 contigs following de bruijn graph algorithm. Pre-assembled contigs were arranged in order, the distances between contigs were identified and oriented with SSPACE, where 2139 scaffolds have been reconstructed. 16386 genes have been identified after gene prediction using Prodigal and putative ID assignment with Blastp Vs NR protein. In these results, 17 cellulose-degrading enzymes and 2 xylan-degrading enzymes have been found. The genes encoding these enzymes will be recombinant to pBAD TOPO vector and cloned into TOP10 E. coli to express and characterize the enzymes for downstream processes.