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Genomics and Applied Biology 2015, Vol. 6, No. 2, 1-7
http://gab.biopublisher.ca
1
Research Article Open Access
De Novo RNA Seq Assembly and Annotation of
Vicia sativa
L. (SRR403901)
Sagar S. Patel
1
, Dipti B. Shah
1
, Hetalkumar J. Panchal
2
1 G. H. Patel Post Graduate Department of Computer Science and Technology, Sardar Patel University, Vallabh Vidyanagar, Gujarat-388120, India.
2 Gujarat Agricultural Biotechnology Institute, Navsari Agricultural University, Surat, Gujarat- 395007, India.
Corresponding author email
Genomics and Applied Biology, 2015, Vol.6, No.2 doi: 10.5376/gab.2015.06.0002
Received: 19 Nov., 2014
Accepted: 15 Jan., 2015
Published: 29 Jan., 2015
© 2015 Sagar S. Patel et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:
Sagar S. Patel et al., 2015, De Novo RNA Seq Assembly and Annotation of
Vicia sativa
L. (SRR403901), Genomics and Applied Biology, Vol.6, No.2, 1-7
(doi
Abstract
Vicia sativa
L. which is also known as common vetch is nitrogen fixing leguminous plant in the family Fabaceae.
Recently, next-generation sequencing technology, termed RNA-seq, has provided a powerful approach for analyzing the
Transcriptome. This study is focus on RNA-seq of
Vicia sativa
L. of SRR403901 from NCBI database for de novo Transcriptome
analysis. A total of 12.4 million single reads were generated with N50 of 588 bp. Sequence assembly contained total 22748 contigs
which is further search with known proteins, a total of 7652 genes were identified. Among these, only 500 unigenes were annotated
with 18761 gene ontology (GO) functional categories and sequences mapped to 122 pathways by searching against the Kyoto
Encyclopedia of Genes and Genomes pathway database (KEGG). These data will be useful for gene discovery and functional studies
and the large number of transcripts reported in the current study will serve as a valuable genetic resource of the
Vicia sativa
L..
Keywords
Transcriptome, Bioinformatics,
Vicia sativa
L..
Introduction
Next generation sequencing methods for high
throughput RNA sequencing (transcriptome) is
becoming increasingly utilized as the technology of
choice to detect and quantify known and novel
transcripts in plants. This Transcriptome analysis
method is fast and simple because it does not require
cloning of the cDNAs. Direct sequencing of these
cDNAs can generate short reads at an extraordinary
depth. After sequencing, the resulting reads can be
assembled into a genome-scale transcription profile. It
is a more comprehensive and efficient way to measure
Transcriptome composition, obtain RNA expression
patterns, and discovers new exons and genes
(Mortazavi et al., 2008; Wang et al.,2009); sequencing
data of Transcriptome was assembled using various
assembly tools, functional annotation of genes and
pathway analysis carried with various Bioinformatics
tools. The large number of transcripts reported in the
current study will serve as a valuable genetic resource
for
Vicia sativa
L.
High-throughput short-read sequencing is one of the
latest sequencing technologies to be released to the
genomics community. For example, on average a
single run on the Illumina Genome Analyser can result
in over 30 to 40 million single-end (~35 nt) sequences.
However, the resulting output can easily overwhelm
genomic analysis systems designed for the length of
traditional Sanger sequencing, or even the smaller
volumes of data resulting from 454 (Roche)
sequencing technology. Typically, the initial use of
short-read sequencing was confined to matching data
from genomes that were nearly identical to the
reference genome. Transcriptome analysis on a global
gene expression level is an ideal application of
short-read sequencing. Traditionally such analysis
involved complementary DNA (cDNA) library
construction, Sanger sequencing of ESTs, and
microarray analysis. Next generation sequencing has
become a feasible method for increasing sequencing
depth and coverage while reducing time and cost
compared to the traditional Sanger method (L J
