IC4R007-miRNA-2014-24315823
Contents
Project Title
Identification and characterization of salt responsive miRNA-SSR markers in rice (Oryza sativa)
The Background of This Project
- Salinity is an important abiotic stress that affects agricultural production and productivity. It is a complex trait that is regulated by different molecular mechanisms. miRNAs are non-coding RNAs which are highly conserved andregulategene expression.Simplesequencerepeats(SSRs) are robustmolecular markers for studyinggenetic diversity. Although several SSR markers are available now, challenge remains to identify the trait-specific SSRs which can be used for marker assisted breeding.
- High salinity causes multifarious effects on plant growth and development in the form of disturbed cell expansion, impaired metabolism, necrosis and limited protein synthesis that eventually leads to the enhancement of cell death. Soil salinity is one of the major limitation factors that alone causes 5% yield loss. To counteract salinity stresses, plants utilize number of defence mechanisms, ultimately leading to stress tolerance. This comprises a range of physiological and biochemical adjustments in plants including leafwilting,leafarea reduction,leafabscission,rootgrowthstimulation, and alterations in relative water content. Molecular responses to abiotic stress on the other hand include perception of the particular stress, signal transduction, gene expression and ultimately metabolic changes in the plant thus providing stress tolerance. Among the different regulatory elements, miRNAs are wide-spread class of newly discovered, about21 bp long, non-coding RNAs that silence the gene expression at post-transcriptional level in plants. More specifically, miRNAs cleave the target genes to prevent gene expression in plants . Several recent findings are reminiscent of the fact that miRNAs contribute significantly to the plant adaptation to salt stress. Developingsalt tolerant plant through marker assisted breeding has added advantage over either conventional breeding or through transgenic technology. Due to their dense distribution throughout the genome, high reproducibility, co-dominant alleles and highly variable nature, microsatellites or simple sequence repeats (SSRs) meet the requirements of an ideal genetic marker. Subsequently, they have become markers of choice for genome mapping, finger-printing and population analysis as well as in evolutionary studies.
Plant Culture & Treatment
- Twenty four rice genotypes comprised of one salt tolerant and one saltsusceptiblepanel,eachwith12genotypes, wereusedin thepresent study.DNA wasextracted from 100 mggreenleaftissueusing cetyltrimethyl ammonium bromide (CTAB). Briefly, tissues were homogenized with a pestle in a CTAB buffer (CTAB 2%; 0.1 M Tris, pH 8; 0.02 M EDTA pH 8; 1.4 M NaCl) and incu-batedat60 °Cfor45 min.TheDNAwasextractedfromthelysismixture with chloroform/isoamylalcohol (24/1;v/v)andprecipitatedbyadding isopropanol (v/v) to the DNA containing phase. After centrifugation (10,000 ×g, 15 min), the pellet was rinsed with 70% ethanol, air-dried, re-suspended in 1X TE (10 mM Tris Base and 1 mM EDTA) buffer. The DNA samples were stored at −20 °C until PCR amplification. The quality and purity of RNAase-treated DNA were checked in 0.8% agarose 1X TAE (40 mM Tris–acetate and 1 mM EDTA) gel. Isolated purified DNA was quantified using spectrophotometer (Thermo Scientific Nano drop 1000) and diluted with double distilled water to the final concentration of 25 ng/μl.
Research Findings
- Based on theliterature search,we identified 47 miRNAs family comprisedof 130members that wereresponsive to salinity stress in various plantssuch as Arabidopsis,rice,maize, tobacco, andCaragana intermedia etc. Two rice miRNAs namely osa-miR16 and osa-miR29 and six Populus miRNAs such as peu-miR1, peu-miR4, pto-miR6, pto-miR12, pto-miR16 and pto-miR17 were though salt responsive (Supplementary Table 1) but not reported in miRBase, hence, excluded for the repeat search. Similarly two Arabidopsis miRNAs such as ath-miR319c and ath-miR402 were also excluded due to high E value during BLAST hit in Gramene. While 52 sequences did not have any repeat motif, rest of the sequences generated a wide range of repeats which varied from a maximum of tetra-nucleotide repeated of 6 times, to a minimum of di-nucleotide, repeated 27 times. However, overall,di-nucleotiderepeatswerefoundtobethehighest(69),followedbytri-nucleotide(18)andtwotetrdnucleotidewerealsofoundtobe the lowest.
- Spanning to these nucleotides, we finally found out 16 sequences that had more than 7 repeats and used to design the SSRs markers. Outofthese,totalof12miR SSRsproducedsatisfactory,clear,reproducible banding pattern in all the 24 genotypes at their respective loci(Figures. 1a and b). A total of 88 alleles were scored with 16 SSRs, 74 were polymorphic (84.09% polymorphic) accounting an average of 6.1 polymorphic alleles/marker. While miR156g-SSR, miR166d-SSR and miR-171a-SSR showed the highest number of 8 alleles each, miR169n-SSR produced a lowest of single allele (Table 2) which was monomorphic. The differences in molecular size between the smallest and the largest allele for a given SSR locus varied from 14 bp (miR156g-SSR) to 98 bp (miR396a-SSR). While the lowest amplicon size (159 bp) was produced by miR167f-SSR, the highest amplicon size (268 bp) was produced by miR396a-SSR (Table 2). Out of the 12 polymorphic markers, the highest PIC value (0.269) was shown by miR169j-SSR and the lowest one (0.178) was produced by miR167a-SSR. It has been also found that the average PIC value of salt susceptible panel (0.249) was higher than tolerant panel (0.179) indicating that miRNA genes of susceptible panel were more diverse than the tolerant one. Markers miR396a-SSR and miR172b-SSR were found to be the superior for the analysis ofoverall genetic diversity atthe respective lociasthese two markers showed more size differences in the corresponding bands amongthemajority of thestudied genotypes, therefore givinga diverse look of germplasm.
- The data from miR-SSR profiling were used to study the genetic diversity among the 24 genotypes through analysis of clusters and principal coordinates. The UPGMA-based dendrogram obtained from the binary miR-SSR data deduced from the corresponding DNA profiles of the analysed genotypes divided the genotypes into four groups/clusters (Figure. 2). First cluster i.e. cluster-1 comprised 6 genotypes of highly salt tolerant improved varieties. Similarly cluster-II comprised of 6 salt tolerancegenotypesmostly landraces. They were Kalarota, Kalanuniya, Nona Bokra, Pokkali and FL478 and CSR 30. Interestingly Pokkali and FL478 cultivars formed a separate sub-cluster within the cluster-II. Therefore, clearly these two clusters accommodated all the salt tolerant genotypes. On the other hand, Cluster-III comprised of 6 genotypes and all of them weresusceptible genotypes. Similarlycluster-IValsoformed with 6 susceptible genotypes. Hence it was very clear from the dendrogram that the genotypes with known salt sensitivity were grouped together. The Jaccard's similarity index between the pairs of rice genotypes ranged from 8% to 100% with a mean similarity index of 54%. From the similarity matrix, it was evident that on average the salt tolerantgenotypesweremoresimilartotheircorrespondingtraitcoun-terparts and so do the salt susceptible genotypes. Moreover, off-springs are more related to at least one of their parents e.g. FL478 which showedthe highestsimilaritywithPokkali (50%),CSR27showed a substantial similarity (50%) with one of its parent Nona Bokra (though on the whole CSR27 was the most similar with CSR10), IR50 showed a 100% similarity with one of its parent IR36. On the other hand, Kalarata and Nona Bokra were theleast similaraccordingtothematrix.
Labs working on this Project
- Division of Genomic Resource, National Bureau of Plant Genetic Resource, Pusa, New Delhi 110012, India
Corresponding Author
- Tapan Kumar Mondal(mondaltk@yahoo.com)
