Scientia Agricultura Sinica ›› 2008, Vol. 41 ›› Issue (6): 1567-1574 .doi: 10.3864/j.issn.0578-1752.2008.06.001

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS •     Next Articles

The Prediction of Rice Gene by Fgenesh

  

  1. 西北农林科技大学农学院/陕西省作物杂种优势研究与利用重点实验室
  • Received:2007-03-26 Revised:2007-05-17 Online:2008-06-10 Published:2008-06-10

Abstract: Abstract: 【Objective】To give some scientifically reasons for genome annotation, shorten the annotating time and improve the results of gene prediction, this study has been done.【Method】Taking the sequence of chromosome no. 6, which has more length sequences than others of Oryza sativa L. ssp. japonica cv. Nipponbare, as analysis data in this research, the gene prediction of monocots module, rice, has been done by using Fgenesh version 2.0 and the predicting results have been explored particularly by bioinformatics methods. 【Result】The number of predicted genes for this chromosome is very closely to the number of TIGR annotated genes; The majority of the predicted genes are multi-exon genes which have a percentage of 77.52; Length range is very big in the predicted genes; According to the significant match number, multi-exon genes can be predicted more veracity than single exon genes and the support can be reach to 100% by TIGR annotation and to 78% by cDNA; From the angle of predicted exons location of multi-exon genes, the internal exons and last exons have a high support of cDNA; The length of internal exons is relatively short in high (>95%length, >78%similarity) cDNA and/or TIGR annotation support multi-exon genes, but the first exons and last exons on the reverse; The majority of single exon genes which have more than 95% in length and 78% in similarity support by cDNA and/or TIGR annotation is relatively short in length; From the angle of exon number, the majority of the multi-exon genes of high (>95%length, >78%similarity) cDNA and/or TIGR annotation support have the exon number no more than 5. 【Conclusion】The rice gene prediction by Fgenesh is very good, but need modified manually to some extent according to cDNA support after aligning the predicting sequence of genes with cDNA database of rice.

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