Research articles
 

By Mr. Krishnanand P Kulkarni , Mr. Shantanu S Kulkarni , Mr. Mallik Gedda , Mrs. Manusha Bandevar , Dr. Humira Sonah , Dr. Raju N Gacche , Dr. Nilesh K Deshmukh , Dr. Rupesh K Deshmukh
Corresponding Author Dr. Rupesh K Deshmukh
School of Life Sciences, Swami Ramanand Teerth Marathwada University, Nanded, - India
Submitting Author Mr. Krishnanand P Kulkarni
Other Authors Mr. Krishnanand P Kulkarni
School of Life Sciences, Swami Ramanand Teerth Marathwada University, Nanded, - India

Mr. Shantanu S Kulkarni
School of Life Sciences, Swami Ramanand Teerth Marathwada University, - India

Mr. Mallik Gedda
Department of Biochemistry, Banaras Hindu University, Varanasi, - India

Mrs. Manusha Bandevar
Department of Biotechnology and Bioinformatics, MGM College of Computer Science & Information Tech, - India

Dr. Humira Sonah
Division of Biotechnology, Banasthali University, Jaipur, - India

Dr. Raju N Gacche
School of Life Sciences, Swami Ramanand Teerth Marathwada University, - India

Dr. Nilesh K Deshmukh
School of Computational Sciences, Swami Ramanand Teerth Marathwada University, - India

BIOINFORMATICS

Rice, Gene, Homologue, Simple Sequence Repeats, Molecular Markers

Kulkarni KP, Kulkarni SS, Gedda M, Bandevar M, Sonah H, Gacche RN, et al. In Silico Identification of Rice Gene Homologues in Brachypodium, Sorghum and Maize: Insight into Development of Gene Specific Markers. WebmedCentral BIOINFORMATICS 2012;3(4):WMC003258
doi: 10.9754/journal.wmc.2012.003258

This is an open-access article distributed under the terms of the Creative Commons Attribution License(CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Submitted on: 19 Apr 2012 09:17:34 AM GMT
Published on: 28 Apr 2012 10:08:55 AM GMT

Abstract


Rice, one of the important cereal species, is considered as a model for studying grass family. Whole rice genome is recently sequenced, fully annotated and hundreds of genes are characterized. Molecular resources in rice are ever increasing since the draft became publicly available and the information is being utilized to study other cereal genomes as well. This study presents a comprehensive identification of rice genes for important traits like biotic and abiotic stress tolerance and grain yield and design of gene-specific PCR-based markers. A total of 925 functionally characterized genes were identified through literature and searched for their homologue counterparts in three different cereal genomes. The identified homologs found to be syntenic in their relationship with rice and may have shared a common ancestor. Selected set of genes was mined for presence of microsatellite repeat motifs and primers were designed flanking those repeat motifs. These markers will find great usage in phenotyping for stress tolerance or any other trait of interest in related cereal crops and in selecting genotypes in breeding program aimed at transferring a particular gene in an elite genetic background. In addition, these markers can be used as probes in comparative genome analyses.

Introduction


Rice (Oryza sativa L.) is the most important cereal crop of the developing world feeding more than two billion people as a staple food. It has also emerged as a model crop for comparative genomic and molecular biological studies because of availability of its complete genome sequence (Bennetzen, 2007; Devos, 2010). Besides, re-sequencing efforts using gene-chip technology have added value to the reference genome sequence by uncovering the wealth of genomic variation (Jackson et al., 2006). Together, sequencing and resequening data has been accumulating very fast thereby assisting in the identification of agronomically important genes in cereal crops like maize, wheat, oats, sorghum and millet. This enormous progress in rice genomics has made it possible structural and functional comparisons of genes involved in various biological and developmental processes in rice and other cereals (Shimamoto and Kyozuka, 2002).  It has been observed through comparative mapping analysis of closely related grass species that some of the genes have been conserved within large chromosomal segments of the members of grass family genomes (Devos and Gale, 1997; Gale and Devos, 1998). These conserved regions are thought to be derived from a common ancestor and to be collinear (Keller and Feuillet, 2000). Colinearity has been observed in more distant species also thus, providing space for increasing the horizon for comparison of gene organization. Several researchers performed comparative mapping analyses using a defined set of markers or probes to evaluate degree of colinearity among different species. In an experiment, Varshney et al. mapped EST-SSRs to a rye genetic linkage map, which positioned in the expected orthologous region compared to their position in barley (Varshney et al., 2005). Such studies have shown the application of comparative mapping strategies in identifying useful genes and inferring the basic elements of genome evolution. Furthermore, these studies can guide in identifying the novel alleles of genes of interests among close as well as distant species so that the best alleles can be utilized in crop improvement programs.

Sequence comparison methods brought into play extensively since the confirmation that human and mouse genomes are 80% similar at genomic level and such studies were later employed to study genomes of other organisms. Several gene families have been identified in grasses through sequence comparisons and evolutionary relationships have been established. Data mining and sequence comparison method using both indica and japonica strains have helped in identifying several hundred CytP450 genes in rice and were analyzed before the rice genome sequence made publicly available (Nelson et al., 2004). Sequence comparisons have helped in identifying the putative homologs (hd1, LFY, FTL1, etc) and orthologs (AGA-MOUS, MADS-Box genes etc) of several important genes in rice (Kyozuka and Shimamoto, 2002; Kyozuka et al., 2000; Rao et al., 2008). Conversely, rice homologs have also been identified in other related cereals such as maize (Zea mays) and barley (Hordeum vulgare). Low Silicon Rice 2 (Lsi2)-like Si efflux transporters have been identified in maize and barley which may have different Si uptake system from that in rice (Mitani et al., 2009b). These results have shown that comparative analysis of expression patterns of genes in rice and other crops may suggest a range of similar to distinct roles played by these genes in respective plants. With the availability of huge sequence resources in cereal crops, comparative analysis may provide insights into the structural and functional details of various gene families and may find valuable in future research and breeding programs.       

Recent mapping experiments have revealed that the comparative studies might be further difficult for those genes like leaf resistance genes in wheat that evolve rapidly. Chromosome rearrangements like inversions, translocations and insertions may not specify the evolutionary relationships and may not help in defining the gene order (Keller and Feuillet, 2000). To circumvent such exceptions, it would be better to increase the number of markers or probes to be used. Further, these probe sets should be based on genes which are conserved and which codes for a variety of traits. Thus, it is necessary have a large number of gene-based markers that can be cross-transferrable. It has been observed in various studies that a limited gene transfer among grasses using sexual crosses has added a number of important traits to the modern cereal cultivars. Moreover, key genes and quantitative trait loci (QTL) for several important traits, such as plant height, flowering time and shattering reported to share orthologous relationships in barley, wheat, maize and rice. However, the vast majority of genes and traits in single grass species have never been used in other species. Thus, gene-specific markers can be designed for their used in phenotyping of plants for various agronomically important traits as well as comparative analyses. In this report we have identified a total of 925 rice homologs in three cereal crops viz. Brachypodium, Maize and Sorghum and gene-specific PCR-based markers were designed.

Methods


Sequence data retrieval, BLAST analysis and functional annotation
Function annotated and well characterized rice genes were searched from literature and public databases. All the DNA sequences related to the gene loci were retrieved in FASTA format using the Batch Entrez retrieval system from GenBank and BLASTn tool (http://www.ncbi.nlm.nih.gov/blast) against TIGR gene models to get locus identifier (http://rice.plantbiology.msu.edu/). The coding DNA sequence (CDS) corresponding to the selected rice genes were retrieved from TIGR. The CDS sequences of Sorghum, Maize, and Brachypodium were downloaded from Phytozome (http://www.phytozome.org/) and subsequently used for the development of local database named as 'Bramas'. Homologous genes in these three cereal species were searched using rice CDS as query sequences against Bramas by BLASTn with cutoff bit score >200 and e-value ofwww.blast2go.org/). The sequences were annotated for biological process, cellular component and molecular function and plotted using Web Gene Ontology Annotation (WEGO) (Ye et al., 2006).  

Comparative physical mapping
Syntenic relationships among these cereal species for the selected set of homologous genes were verified manually in Microsoft Excel using their genomic location information. These gene were then mapped onto respective chromosomes using Mapchart 2.1, a freely available computer package for MS-Windows®  (http://www.biometris.wur.nl/uk/Software/MapChart/).

Detection of microsatellite repeats motifs in homologous genes and primer design
Mining of di-, tri-, tetra-, penta-, and hexanucleotide perfect microsatellite repeat motifs as well as non-interrupted and interrupted compound microsatellites from these homologous sequences was carried out using a Perl-based program, MISA (MIcroSAtellite identification tool; http://pgrc.ipk-gatersleben.de/misa). MISA is a freely downloadable Perl script available on internet. Primer pairs flanking the microsatellite repeat motifs were developed using Primer3 Plus (http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi) software tool. The parameters were changed according to own interest. The primer size parameter was changed to min-17, opt-21 and max-27. The GC% was changed to min-45%, max-65%. Then the SSRs were searched for both forward and reverse primers.

Results and Discussion


Grasses has been the most studied family in plant kingdom. Recent progress in the high-throughput sequencing and genotyping technologies have helped in comparative analysis of genomes of related species. These revolutions facilitated the gene discovery and have helped in revealing associations between genotype and phenotype. Because of large amount of sequence availability in almost every cereal crop, homolog-based gene identification has taken much interest of researchers of this generation. Genes having homologs in related species have been identified in different species such as arabidopsis, rice, cotton, maize, barley and grapevine (Fulton et al., 2002; Mitani et al., 2009a; Park et al., 2010; Shelden et al., 2009). These genes have greater as they can be used for phenotyping of different traits in related crops. Keeping this in view, we identified rice homologs in brachypodium, maize and sorghum and designed Simple Sequence Repeat (SSR)-based gene-specific markers for them in the present study.

Well characterized rice genes were thoroughly searched in literature and found a total of 925 genes which were used to find their homologous counterparts in other related organisms. We have chosen three cereal crops for study whose genome sequence is publicly available. The length of genes varied from 573bp to 5658bp with average length of 1529. Their annotation and functional characterization was done using an offline tool Blast2GO (www.blast2go.org/) to have an account of functional role of selected genes in various developmental and cellular mechanisms. Out of 925 selected rice genes, 534 (57.73%) had matches to genes or sequences of known function. These were assigned to the one of the three categories and plotted using WEGO (Illustration 1). A major proportion of the assigned loci represent genes that appear to be involved in several metabolic processes, such as energy-generating processes and the biosynthesis and deprivation of cellular building blocks. Thus, it is evident from this study that the selected genes signify various aspects of cellular metabolism and have remained highly conserved across plant species (Yang et al., 1999). To understand their positional organization, we located them onto 12 rice chromosomes based on their physical positions and found that they formed clusters in different regions of the chromosomes (Illustration 2). This was expected as few genes are known to be present in clusters and gene-rich hotspots have been documented in different cereal genomes.          

Both comparative mapping and sequence comparisons among the cereal crops have indicated that sequencing and functional analysis of the rice and other sequenced genomes have a significant impact in terms of gene identification and crop improvement. Gene identification through map-based cloning approach has been difficult in cereals and therefore we must look for other approaches that are quite feasible. One of the approaches is through comparative genome analyses, which can be performed in organisms whose genomes are completely or partially sequenced. However it would require large set of markers, especially those ones which are tightly linked to a phenotype of desired interest and which have been relatively stable in both sequence and copy number. Different dominant and codominant marker systems have been applied in mapping, marker assisted breeding and germplasm evaluation experiments (Xu et al., 2005). SSRs have been the preferred marker systems primarily because they are codominant, thereby revealing allelic variation. Moreover, it is quite easy to identify different repeat motifs in a complete as well as partial genome sequences and to design a marker flanking that repeat motif.  Therefore we mined selected genes for SSR motifs and found all types of di-, tri-, tetra-, penta-, and hexanucleotide perfect microsatellite repeat motifs. Non-interrupted and interrupted compound microsatellites have also been observed, although in lesser numbers.  Of about 89% of the repeat motifs were tri-nucleotide repeats and di-nucleotide repeats were least in numbers. Tri-nucleotide repeats have been found in very large numbers inside these genes because they have less selection pressure, compared to other nucleotide repeats. Primers were designed flanking these repeat motifs and keeping their product size range in between 100-300bp (Supplementary file-1). The positional relationships of these loci were evident when we analyzed the physical positions of these loci in all the species under consideration and found that these are syntenic. Particulars of syntenic relevance of these loci for rice chromosome 1 with other systems are shown in the illustration 3. These sets of conserved sequences can also find application in comparative genome analyses and to provide information the evolutionary aspects of convergence or divergence of a species.

Conclusions


We have analyzed a set of 925 rice genes for revealing presence of their homologue counterparts in three different cereal crop systems. As the genomes of all these crops systems have been sequenced, we could analyze sequence similarity searches, thereby identifying conserved blocks in coding parts of genomes. The conserved regions in genomes are assumed to have come from a common ancestor and they may have lesser sequence variations because of high selection pressure. Therefore, the markers or probes that are designed based on these sequences are expected to be cross-transferrable across species and this to have an application in all the related species. Therefore we believe that the gene-specific markers designed in this study utilized in various crop improvement programs and can be used a probes for comparative genome analyses.

References


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Source(s) of Funding


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Competing Interests


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