Biomedical subjects

Nagendra K Singh

Publications and source records attributed to Nagendra K Singh.

6 recordsLinked to original sources

PubMed2007

Curated genome annotation of Oryza sativa ssp. japonica and comparative genome analysis with Arabidopsis thaliana.

We present here the annotation of the complete genome of rice Oryza sativa L. ssp. japonica cultivar Nipponbare. All functional annotations for proteins and non-protein-coding RNA (npRNA) candidates were manually curated. Functions were identified or inferred in 19,969 (70%) of the proteins, and 131 possible npRNAs (including 58 antisense transcripts) were found. Almost 5000 annotated protein-coding genes were found to be disrupted in insertional mutant lines, which will accelerate future experimental validation of the annotations. The rice loci were determined by using cDNA sequences obtained from rice and other representative cereals. Our conservative estimate based on these loci and an extrapolation suggested that the gene number of rice is approximately 32,000, which is smaller than previous estimates. We conducted comparative analyses between rice and Arabidopsis thaliana and found that both genomes possessed several lineage-specific genes, which might account for the observed differences between these species, while they had similar sets of predicted functional domains among the protein sequences. A system to control translational efficiency seems to be conserved across large evolutionary distances. Moreover, the evolutionary process of protein-coding genes was examined. Our results suggest that natural selection may have played a role for duplicated genes in both species, so that duplication was suppressed or favored in a manner that depended on the function of a gene.

Arabidopsis↗

PubMed2006

Single-copy genes define a conserved order between rice and wheat for understanding differences caused by duplication, deletion, and transposition of genes.

The high-quality rice genome sequence is serving as a reference for comparative genome analysis in crop plants, especially cereals. However, early comparisons with bread wheat showed complex patterns of conserved synteny (gene content) and colinearity (gene order). Here, we show the presence of ancient duplicated segments in the progenitor of wheat, which were first identified in the rice genome. We also show that single-copy (SC) rice genes, those representing unique matches with wheat expressed sequence tag (EST) unigene contigs in the whole rice genome, show more than twice the proportion of genes mapping to syntenic wheat chromosome as compared to the multicopy (MC) or duplicated rice genes. While 58.7% of the 1,244 mapped SC rice genes were located in single syntenic wheat chromosome groups, the remaining 41.3% were distributed randomly to the other six non-syntenic wheat groups. This could only be explained by a background dispersal of genes in the genome through transposition or other unknown mechanism. The breakdown of rice-wheat synteny due to such transpositions was much greater near the wheat centromeres. Furthermore, the SC rice genes revealed a conserved primordial gene order that gives clues to the origin of rice and wheat chromosomes from a common ancestor through polyploidy, aneuploidy, centromeric fusions, and translocations. Apart from the bin-mapped wheat EST contigs, we also compared 56,298 predicted rice genes with 39,813 wheat EST contigs assembled from 409,765 EST sequences and identified 7,241 SC rice gene homologs of wheat. Based on the conserved colinearity of 1,063 mapped SC rice genes across the bins of individual wheat chromosomes, we predicted the wheat bin location of 6,178 unmapped SC rice gene homologs and validated the location of 213 of these in the telomeric bins of 21 wheat chromosomes with 35.4% initial success. This opens up the possibility of directed mapping of a large number of conserved SC rice gene homologs in wheat. Overall, only 46.4% of these SC genes code for proteins with known functional domains; the remaining 53.6% have unknown function, and hence, represent an important, but yet, under explored category of genes.

Gene Deletion↗

PubMed2006

Unigene derived microsatellite markers for the cereal genomes.

Unigene derived microsatellite (UGMS) markers have the advantage of assaying variation in the expressed component of the genome with unique identity and positions. We characterized the microsatellite motifs present in the unigenes of five cereal species namely, rice, wheat, maize, Sorghum and barley and compared with those in Arabidopsis. The overall UGMS frequency in the five cereal species was 1/7.6 kb. The maximum UGMS frequency was in rice (1/3.6 kb) and the lowest in wheat (1/10.6 kb). GC-rich trinucleotide repeat motifs coding for alanine followed by arginine and the dinucleotide repeat motif GA were found to be abundant UGMS classes across all the five cereal species. Primers could be designed for 95% (wheat and barley) to 97% (rice) of the identified microsatellites. The proportion and frequency of occurrence of long hypervariable class I (> or = 20 nucleotides) and potentially variable class II (12-20 nucleotides) UGMS across five cereal species were characterized. The class I UGMS markers were physically mapped in silico on to the finished rice genome and bin-mapped in wheat. Comparative mapping based on class I UGMS markers in rice and wheat revealed syntenic relationships between the two genomes. High degree of conservation and cross-transferability of the class I UGMS markers were evident among the five cereal species, which was validated experimentally. The class I UGMS-conserved orthologous set (COS) markers identified in this study would be useful for understanding the evolution of genes and genomes in cereals.

Arabidopsis↗

PubMed2005

SSR-based detection of genetic variability in the charcoal root rot pathogen Macrophomina phaseolina.

Macrophomina phaseolina, the causal agent of charcoal root or collar rot, is an important plant pathogen especially in soybean and cotton. Single primers of simple sequence repeats (SSR) or microsatellite markers have been used for the characterization of genetic variability of different populations of M. phaseolina obtained from soybean and cotton grown in India and the USA. Genetic similarity between isolates was calculated, and cluster analysis was used to generate a dendrogram showing relationships between isolates collected from the two hosts. Forty isolates could be clustered into three major groups corresponding to their hosts and geographical region. The wide distribution of microsatellites in M. phaseolina genome was assessed by agarose gel electrophoresis of the PCR products generated by direct amplification of inter SSR regions DNA. This is the first report of the use of microsatellite markers to characterize the charcoal root rot pathogen. The SSR fingerprints (0.25-3.5 kb) generated using DNA from different populations of M. phaseolina of two hosts indicated that these repeats are interspersed within the genome of this pathogen. The variability found within closely related isolates of M. phaseolina indicated that such microsatellites are useful in population studies and represents a step towards identification of potential isolate diagnostic markers specific to soybean and cotton.

Ascomycota↗

PubMed2004

Sequence analysis of the long arm of rice chromosome 11 for rice-wheat synteny.

The DNA sequence of 106 BAC/PAC clones in the minimum tiling path (MTP) of the long arm of rice chromosome 11, between map positions 57.3 and 116.2 cM, has been assembled to phase 2 or PLN level. This region has been sequenced to 10x redundancy by the Indian Initiative for Rice Genome Sequencing (IIRGS) and is now publicly available in GenBank. The region, excluding overlaps, has been predicted to contain 2,932 genes using different software. A gene-by-gene BLASTN search of the NCBI wheat EST database of over 420,000 cDNA sequences revealed that 1,143 of the predicted rice genes (38.9%) have significant homology to wheat ESTs (bit score >/= 100). Further BLASTN search of these 1,143 rice genes with the GrainGenes database of sequence contigs containing bin-mapped wheat ESTs allowed 113 of the genes to be placed in bins located on wheat chromosomes of different homoeologous groups. The largest number of genes, about one-third, mapped to the homoeologous group 4 chromosomes of wheat, suggesting a common evolutionary origin. The remaining genes were located on wheat chromosomes of different groups with significantly higher numbers for groups 3 and 5. Location of bin-mapped wheat contigs to chromosomes of all the seven homoeologous groups can be ascribed to movement of genes (transpositions) or chromosome segments (translocations) within rice or the hexaploid wheat genomes. Alternatively, it could be due to ancient duplications in the common ancestral genome of wheat and rice followed by selective elimination of genes in the wheat and rice genomes. While there exists definite conservation of gene sequences and the ancestral chromosomal identity between rice and wheat, there is no obvious conservation of the gene order at this level of resolution. Lack of extensive colinearity between rice and wheat genomes suggests that there have been many insertions, deletions, duplications and translocations that make the synteny comparisons much more complicated than earlier thought. However, enhanced resolution of comparative sequence analysis may reveal smaller conserved regions of colinearity, which will facilitate selection of markers for saturation mapping and sequencing of the gene-rich regions of the wheat genome.

Base Sequence↗

PubMed2002

An integrated physical and genetic map of the rice genome.

Rice was chosen as a model organism for genome sequencing because of its economic importance, small genome size, and syntenic relationship with other cereal species. We have constructed a bacterial artificial chromosome fingerprint-based physical map of the rice genome to facilitate the whole-genome sequencing of rice. Most of the rice genome ( approximately 90.6%) was anchored genetically by overgo hybridization, DNA gel blot hybridization, and in silico anchoring. Genome sequencing data also were integrated into the rice physical map. Comparison of the genetic and physical maps reveals that recombination is suppressed severely in centromeric regions as well as on the short arms of chromosomes 4 and 10. This integrated high-resolution physical map of the rice genome will greatly facilitate whole-genome sequencing by helping to identify a minimum tiling path of clones to sequence. Furthermore, the physical map will aid map-based cloning of agronomically important genes and will provide an important tool for the comparative analysis of grass genomes.

Chromosomes, Artificial, Bacterial↗