RESEARCH

RICE ROOT DEVELOPMENT

       A. Genome Analysis

Root system of rice is complex consisting of seminal, adventitious and lateral roots. Genetic control of root growth is complex and polygenic. The underlying mechanisms of root development, both intrinsic and in response to environment, is poorly understood. Contrasting root development characteristics exist in lowland and upland varieties of indica and japonica rice. Such varieties with contrasting root characteristics have been crossed, mapping populations developed and a number of QTLs in different chromosomes have been identified. As most of these studies used different set of markers and many of the QTLs identified are long regions of chromosomes, it is difficult to exploit the varietal difference for improved drought tolerance by marker assisted selection and for identification of the concerned alleles.

The availability of the rice genomes has opened new avenues to look back at the large number of QTLs reported to control root development. In this study we made an effort to physically integrate various QTLs reported, with the japonica genome (RAP Build-4). We could integrate a majority of root QTLs computationally to the japonica genome .Overall a higher number of QTLs, governing root development are present in chromosome 1. There are fewer QTLs in some of the chromosomes. Many of the QTLs reported from different mapping poulations are found to be overlapping with each other, or found within some of the larger QTLs reported. Alignment of the overlapping QTL regions showed that many QTL regions are common in different mapping populations. Some of the longer QTLs could be resolved into multiple QTLs as different regions of the long QTLs aligned with different QTLs from other mapping populations.

To analyze the putative candidate genes governing root development in these QTLs, the genomic regions spanning different QTLs were extracted, all genes present in these regions were located and their putative functions were computationally analyzed. In some of the QTL regions fewer numbers of genes, 200-300, are present while in larger QTLs 600-800 genes were found .Computational analysis of the genes revealed that there are many candidate genes governing root development in the QTLs.

These genes belong to the categories of a). transcription factors, b). auxin metabolism and transport genes, c). auxin responsive genes, d). auxin related proteosome pathway genes, e) environmental sensors and f) biotic and abiotic stress tolerance genes.

B. Development of the database Rootbrowse

As the data generated is of practical importance for genomic research in rice an online digital resource named ROOTBROWSE has been developed. The Rootbrowse tool can be accessed at the address: http://www.ricebrowse.org. The data degenerated in the genome-wide analyses and the genome sequence of rice were used for construction of a relational database using MySQL relational database management system and Bio::DB::GFF schema. The database is linked to the GBrowse visualization tool which consists of several components: At the top level is a CGI (Common Gateway Interface) script named gbrowse, which is responsible for managing the user interface. This script generates the HTML forms that the end-users interact with, accepts and processes requests, manages the cookies that preserve users' preferences from session to session, and displays the rendered images of annotated regions. The genome browser graphically displays a section of the genome and all features annotated on it. The user can zoom in and out and scroll through the genome and click on features to obtain more detailed information. Users can specify a genome segment for displaying, e.g. chr1:1000..9000, or query the database by entering a keyword including wild card characters, e.g. root*. This query will return a list of matches to the search term. The QTLs can be searched using the trait name (eg. Deep root), variety (eg. Azucena) and author name (eg. Yadav). The QTLs can be displayed along with SSR markers all protein coding genes or selected categories of genes like auxin metabolism genes for prediction of probable candidate genes.

C. Functional Validation of  Predicted candidate genes

Selected candidate genes are being validated  using molecular markers and RNAI based gene silencing (work in progress - details will be added later)

 TRANSLATIONAL REGULATION IN PLANTS

A. Genome-wide analysis of rice and Arabidopsis cDNAs for translational signals

Eukaryotes possess complex regulatory mechanisms of mRNA translation for modulating gene expression in a wide range of biological situations. Well developed translational regulation is made possible by separating translation from transcription, accomplished by the nuclear membrane, and by the use of different start and stop sites for transcription and translation. A consequence of the latter organization is the existence of additional gene structures called untranslated regions (UTRs) present at both ends of the messenger RNA.

UTRs contain elements that in combination with proteins or small RNAs modulate translation of individual mRNAs without affecting global protein synthesis. Several features of the 5’-leader sequence can influence mRNA translational efficiency, of which the nucleotide sequence or context surrounding the AUG codon and the presence of AUGs / open reading frames (ORFs) upstream of the main translation initiation site are the most important (these are termed uAUGs and uORFs).

To assess the level of 5’-UTR mediated translational regulation in rice, a genome-wide computational analysis of rice 5’-UTRs was carried out. Combinatorial analyses of start-codon context, uAUG context and context of uAUGs of upstream open reading frames of individual genes indicate that about 34 % of genes in rice are likely to be influenced at translational level by signals present in 5’-UTR as they possess uAUG/uORFs with sequence context conforming to the consensus sequence

B. Development of Translatebase - the database of translational signals in plants

The data generated in the genome-wide analyses and the genome sequence of rice were used for construction of a relational database using MySQL relational database management system and Bio::DB::GFF schema. The database is linked to the Gbrowse visualization tool which consists of several components: At the top level is a CGI (Common Gateway Interface) script named gbrowse, which is responsible for managing the user interface. This script generates the HTML forms that the end-users interact with, accepts and processes requests, manages the cookies that preserve users' preferences from session to session, and displays the rendered images of annotated regions.

Currently the Translatebase database contains 5’-UTR based translational signal annotations for the japonica rice genes. The translational signal annotations are shown in the context of the general genome annotations provided by the rice annotation project which was from RAP-DB. For each signal the genomic location, strand, AUG sequence context, context strength and the reading frame with respect to the cDNA. The number of full length cDNA represented in the database are 1,80,376. All redundant / splice variant cDNAs are included.

The Translatebase database can be accessed at the address: http://www.ricebrowse.org. The database uses the Generic genome browser as an engine. The genome browser graphically displays a section of the genome and all features annotated on it. The user can zoom in and out and scroll through the genome and click on features to obtain more detailed information. Users can specify a genome segment for displaying, e.g. chr1:1000..9000, or query the database by entering a keyword including wild card characters, e.g. alkaline*. This query will return a list of matches to the search term. For example, to find the translational signals, start codon, uAUG and uORF for the gene AK069738 one would query the database with AK069738 (which will fetch the cDNA and all signals associated with this cDNA). For specific querying of translational signals the accession number (AK069738) is appended with –AUG, -uAUG and -uORF, for the start codon, upstream AUG and upstream ORF, respectively. By clicking on one of the signals in the list the user will see the section of the genome where the signal occurs. Annotated translational signals are displayed as segments (boxes).  Each feature (segment representing the AUG, uAUG, uORF) is labeled by an identifier which is the RAP accession number (of the cDNA to which it belongs) appended with –AUG (for the start codon), -uAUG (for the upstream AUG) and -uORF (for the upstream ORF). Double clicking the cursor on the segment opens a page with detailed information about the signal. For the start codon and upstream AUG this information includes the chromosomal position, sequence context, sequence context strength and the reading frame. For the upstream ORF, chromosomal position, its start codon sequence context, its start codon sequence context strength, the reading frame and the ORF sequence. TRANSLATEBASE is being tested

C. Laboratory validation  predicted translational signals

                              Work in progress

 

More to be added