Assigning biological functions to rice genes by genome annotation, expression analysis and mutagenesis

Abstract

Rice is the first cereal genome to be completely sequenced. Since the completion of its genome sequencing, considerable progress has been made in multiple areas including the whole genome annotation, gene expression profiling, mutant collection, etc. Here, we summarize the current status of rice genome annotation and review the methodology of assigning biological functions to hundreds of thousands of rice genes as well as discuss the major limitations and the future perspective in rice functional genomics. Available data analysis shows that the rice genome encodes around 32,000 protein-coding genes. Expression analysis revealed at least 31,000 genes with expression evidence from full-length cDNA/EST collection or other transcript profiling. In addition, we have summarized various strategies to generate mutant population including natural, physical, chemical, T-DNA, transposon/retrotransposon or gene silencing based mutagenesis. Currently, more than 1 million of mutants have been generated and 27,551 of them have their flanking sequence tags. To assign biological functions to hundreds of thousands of rice genes, global co-operations are required, various genetic resources should be more easily accessible and diverse data from transcriptomics, proteomics, epigenetics, comparative genomics and bioinformatics should be integrated to better understand the functions of these genes and their regulatory mechanisms.

Identification and molecular characterization of tissue-preferred rice genes and their upstream regularly sequences on a genome-wide level

“…In rice, at least 31,382 genes showed expression evidence by microarray, cDNA/EST, and MPSS [ 45 ]. More genes were detected with expression signal by custom microarray analysis [ 46 ].…”

Genome-Wide Survey on Genomic Variation, Expression Divergence, and Evolution in Two Contrasting Rice Genotypes under High Salinity Stress

“…On the other hand, the rice genome was completely sequenced and annotated in its encoding genes (http://rice.plantbiology.msu.edu; Kawahara et al 2013). Based on the various Affymetrix microarray-based expression analyses, only around 23,821 annotated genes were expressed (Jiang and Ramachandran 2010). This might be partially due to the fact that no probe has been printed in the Affymetrix chips for many annotated rice genes.…”

“…In a previous report, around 31,382 genes were detected with expression signal using microarray, massively parallel signature sequencing or by cDNA/EST (Jiang and Ramachandran 2010). By comparing these published data, our custom microarray analysis detected 16,230 (7,797 non-TE and 8,433 TE) genes in Nipponbare and 16,313 (7,863 non-E and 8,450 TE) genes in Pokkali, which were not probed or detected with expression signal in previous studies (Jiang and Ramachandran 2010). On the other hand, we only used 250 mM NaCl solution for high salinity stress.…”

“…These data suggested that expression divergence should also be regarded as an index to evaluate genetic diversity in rice. Furthermore, studies showed that upregulation or downregulation of certain genes in transgenic rice plants significantly altered their tolerance to salinity stress (Jiang and Ramachandran 2010; Nakashima et al 2012), and some of these genes also showed expression divergence between Nipponbare and Pokkali under normal and salinity stress conditions. The data suggested that expression divergence might contribute to cultivar improvement in salinity tolerance during rice domestication.…”

Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach

“…With over 50% of the genes in rice lacking annotation for biological processes ( Rhee and Mutwil, 2014 ), there is an urgent need for annotation pipelines to be developed. Several approaches such as artificial mutagenesis followed by the analysis of phenotypic variations ( Jiang and Ramachandran, 2010 ), systems-level annotations of genes to characterize the tissue, condition and developmental stage-specificity ( Childs et al, 2011 ; Movahedi et al, 2011 ), and sequence homology-based annotation pipelines ( Conesa and Götz, 2008 ) have been used in the functional characterization of genes. Moreover, systems level information, viz.…”