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1.  Genic non-coding microsatellites in the rice genome: characterization, marker design and use in assessing genetic and evolutionary relationships among domesticated groups 
BMC Genomics  2009;10:140.
Background
Completely sequenced plant genomes provide scope for designing a large number of microsatellite markers, which are useful in various aspects of crop breeding and genetic analysis. With the objective of developing genic but non-coding microsatellite (GNMS) markers for the rice (Oryza sativa L.) genome, we characterized the frequency and relative distribution of microsatellite repeat-motifs in 18,935 predicted protein coding genes including 14,308 putative promoter sequences.
Results
We identified 19,555 perfect GNMS repeats with densities ranging from 306.7/Mb in chromosome 1 to 450/Mb in chromosome 12 with an average of 357.5 GNMS per Mb. The average microsatellite density was maximum in the 5' untranslated regions (UTRs) followed by those in introns, promoters, 3'UTRs and minimum in the coding sequences (CDS). Primers were designed for 17,966 (92%) GNMS repeats, including 4,288 (94%) hypervariable class I types, which were bin-mapped on the rice genome. The GNMS markers were most polymorphic in the intronic region (73.3%) followed by markers in the promoter region (53.3%) and least in the CDS (26.6%). The robust polymerase chain reaction (PCR) amplification efficiency and high polymorphic potential of GNMS markers over genic coding and random genomic microsatellite markers suggest their immediate use in efficient genotyping applications in rice. A set of these markers could assess genetic diversity and establish phylogenetic relationships among domesticated rice cultivar groups. We also demonstrated the usefulness of orthologous and paralogous conserved non-coding microsatellite (CNMS) markers, identified in the putative rice promoter sequences, for comparative physical mapping and understanding of evolutionary and gene regulatory complexities among rice and other members of the grass family. The divergence between long-grained aromatics and subspecies japonica was estimated to be more recent (0.004 Mya) compared to short-grained aromatics from japonica (0.006 Mya) and long-grained aromatics from subspecies indica (0.014 Mya).
Conclusion
Our analyses showed that GNMS markers with their high polymorphic potential would be preferred candidate functional markers in various marker-based applications in rice genetics, genomics and breeding. The CNMS markers provided encouraging implications for their use in comparative genome mapping and understanding of evolutionary complexities in rice and other members of grass family.
doi:10.1186/1471-2164-10-140
PMCID: PMC2680414  PMID: 19335879
2.  QTL analysis of novel genomic regions associated with yield and yield related traits in new plant type based recombinant inbred lines of rice (Oryza sativa L.) 
BMC Plant Biology  2012;12:137.
Background
Rice is staple food for more than half of the world’s population including two billion Asians, who obtain 60-70% of their energy intake from rice and its derivatives. To meet the growing demand from human population, rice varieties with higher yield potential and greater yield stability need to be developed. The favourable alleles for yield and yield contributing traits are distributed among two subspecies i.e., indica and japonica of cultivated rice (Oryza sativa L.). Identification of novel favourable alleles in indica/japonica will pave way to marker-assisted mobilization of these alleles in to a genetic background to break genetic barriers to yield.
Results
A new plant type (NPT) based mapping population of 310 recombinant inbred lines (RILs) was used to map novel genomic regions and QTL hotspots influencing yield and eleven yield component traits. We identified major quantitative trait loci (QTLs) for days to 50% flowering (R2 = 25%, LOD = 14.3), panicles per plant (R2 = 19%, LOD = 9.74), flag leaf length (R2 = 22%, LOD = 3.05), flag leaf width (R2 = 53%, LOD = 46.5), spikelets per panicle (R2 = 16%, LOD = 13.8), filled grains per panicle (R2 = 22%, LOD = 15.3), percent spikelet sterility (R2 = 18%, LOD = 14.24), thousand grain weight (R2 = 25%, LOD = 12.9) and spikelet setting density (R2 = 23%, LOD = 15) expressing over two or more locations by using composite interval mapping. The phenotypic variation (R2) ranged from 8 to 53% for eleven QTLs expressing across all three locations. 19 novel QTLs were contributed by the NPT parent, Pusa1266. 15 QTL hotpots on eight chromosomes were identified for the correlated traits. Six epistatic QTLs effecting five traits at two locations were identified. A marker interval (RM3276-RM5709) on chromosome 4 harboring major QTLs for four traits was identified.
Conclusions
The present study reveals that favourable alleles for yield and yield contributing traits were distributed among two subspecies of rice and QTLs were co-localized in different genomic regions. QTL hotspots will be useful for understanding the common genetic control mechanism of the co-localized traits and selection for beneficial allele at these loci will result in a cumulative increase in yield due to the integrative positive effect of various QTLs. The information generated in the present study will be useful to fine map and to identify the genes underlying major robust QTLs and to transfer all favourable QTLs to one genetic background to break genetic barriers to yield for sustained food security.
doi:10.1186/1471-2229-12-137
PMCID: PMC3438134  PMID: 22876968

Results 1-2 (2)