Tandon G, Singh S, Kaur S, Sarika, Iquebal MA, Rai A, Kumar D. Computational deciphering of biotic stress associated genes in tomato (
Solanum lycopersicum).
Genom Data 2017;
14:82-90. [PMID:
29062693 PMCID:
PMC5643083 DOI:
10.1016/j.gdata.2017.09.003]
[Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Revised: 09/20/2017] [Accepted: 09/23/2017] [Indexed: 01/17/2023]
Abstract
Tomato (Solanum lycopersicum) is one of the major vegetable plant and a model system for fruit development. Its global importance is due to its lycopene pigment which has anti-oxidative and anti-cancerous properties. Though > 1.5 M biotic stress associated ESTs of tomato are available but cumulative analysis to predict genes is warranted. Availability of whole genome de novo assembly can advantageously be used to map them over different chromosome. Further, available 0.14 M catalogued markers can be used to introgress specific desirable genes in varietal improvement program. We report here 57 novel genes associated with biotic stress of tomato along with 50 genes having physical location over different chromosomes. We also report 52 cis-regulating elements and 69 putative miRNAs which are involved in regulation of these biotic stresses associated genes. These putative candidate genes associated with biotic stress can be used in molecular breeding in the endeavor of tomato productivity along with its sustainable germplasm management.
ESts related to biotic stress were collected and assembled into contigs.
Total 57 novel genes were computationally mined from the assembled contigs.
Among the predicted novel gene, 50 genes were mapped on tomato genome.
52 cis-regulating elements and 69 putative miRNAs were predicted for the novel genes.
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