TY - JOUR
T1 - LEMONS - A tool for the identification of splice junctions in transcriptomes of organisms lacking reference genomes
AU - Levin, Liron
AU - Bar-Yaacov, Dan
AU - Bouskila, Amos
AU - Chorev, Michal
AU - Carmel, Liran
AU - Mishmar, Dan
N1 - Publisher Copyright:
© 2015 Levin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2015/11
Y1 - 2015/11
N2 - RNA-seq is becoming a preferred tool for genomics studies of model and non-model organisms. However, DNA-based analysis of organisms lacking sequenced genomes cannot rely on RNA-seq data alone to isolate most genes of interest, as DNA codes both exons and introns. With this in mind, we designed a novel tool, LEMONS, that exploits the evolutionary conservation of both exon/intron boundary positions and splice junction recognition signals to produce high throughput splice-junction predictions in the absence of a reference genome. When tested on multiple annotated vertebrate mRNA data, LEMONS accurately identified 87% (average) of the splice-junctions. LEMONS was then applied to our updated Mediterranean chameleon transcriptome, which lacks a reference genome, and predicted a total of 90,820 exon-exon junctions. We experimentally verified these splice-junction predictions by amplifying and sequencing twenty randomly selected genes from chameleon DNA templates. Exons and introns were detected in 19 of 20 of the positions predicted by LEMONS. To the best of our knowledge, LEMONS is currently the only experimentally verified tool that can accurately predict splice-junctions in organisms that lack a reference genome.
AB - RNA-seq is becoming a preferred tool for genomics studies of model and non-model organisms. However, DNA-based analysis of organisms lacking sequenced genomes cannot rely on RNA-seq data alone to isolate most genes of interest, as DNA codes both exons and introns. With this in mind, we designed a novel tool, LEMONS, that exploits the evolutionary conservation of both exon/intron boundary positions and splice junction recognition signals to produce high throughput splice-junction predictions in the absence of a reference genome. When tested on multiple annotated vertebrate mRNA data, LEMONS accurately identified 87% (average) of the splice-junctions. LEMONS was then applied to our updated Mediterranean chameleon transcriptome, which lacks a reference genome, and predicted a total of 90,820 exon-exon junctions. We experimentally verified these splice-junction predictions by amplifying and sequencing twenty randomly selected genes from chameleon DNA templates. Exons and introns were detected in 19 of 20 of the positions predicted by LEMONS. To the best of our knowledge, LEMONS is currently the only experimentally verified tool that can accurately predict splice-junctions in organisms that lack a reference genome.
UR - http://www.scopus.com/inward/record.url?scp=84960194534&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0143329
DO - 10.1371/journal.pone.0143329
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C2 - 26606265
AN - SCOPUS:84960194534
SN - 1932-6203
VL - 10
JO - PLoS ONE
JF - PLoS ONE
IS - 11
M1 - e0143329
ER -