Dataset Information

Transcriptome wide identification and validation of calcium sensor gene family in the developing spikes of finger millet genotypes for elucidating its role in grain calcium accumulation.

ABSTRACT:

Background

In finger millet, calcium is one of the important and abundant mineral elements. The molecular mechanisms involved in calcium accumulation in plants remains poorly understood. Transcriptome sequencing of genetically diverse genotypes of finger millet differing in grain calcium content will help in understanding the trait.

Principal finding

In this study, the transcriptome sequencing of spike tissues of two genotypes of finger millet differing in their grain calcium content, were performed for the first time. Out of 109,218 contigs, 78 contigs in case of GP-1 (Low Ca genotype) and out of 120,130 contigs 76 contigs in case of GP-45 (High Ca genotype), were identified as calcium sensor genes. Through in silico analysis all 82 unique calcium sensor genes were classified into eight calcium sensor gene family viz., CaM & CaMLs, CBLs, CIPKs, CRKs, PEPRKs, CDPKs, CaMKs and CCaMK. Out of 82 genes, 12 were found diverse from the rice orthologs. The differential expression analysis on the basis of FPKM value resulted in 24 genes highly expressed in GP-45 and 11 genes highly expressed in GP-1. Ten of the 35 differentially expressed genes could be assigned to three documented pathways involved mainly in stress responses. Furthermore, validation of selected calcium sensor responder genes was also performed by qPCR, in developing spikes of both genotypes grown on different concentration of exogenous calcium.

Conclusion

Through de novo transcriptome data assembly and analysis, we reported the comprehensive identification and functional characterization of calcium sensor gene family. The calcium sensor gene family identified and characterized in this study will facilitate in understanding the molecular basis of calcium accumulation and development of calcium biofortified crops. Moreover, this study also supported that identification and characterization of gene family through Illumina paired-end sequencing is a potential tool for generating the genomic information of gene family in non-model species.

SUBMITTER: Singh UM

PROVIDER: S-EPMC4144799 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Transcriptome wide identification and validation of calcium sensor gene family in the developing spikes of finger millet genotypes for elucidating its role in grain calcium accumulation.

Singh Uma M UM Chandra Muktesh M Shankhdhar Shailesh C SC Kumar Anil A

PloS one 20140826 8

<h4>Background</h4>In finger millet, calcium is one of the important and abundant mineral elements. The molecular mechanisms involved in calcium accumulation in plants remains poorly understood. Transcriptome sequencing of genetically diverse genotypes of finger millet differing in grain calcium content will help in understanding the trait.<h4>Principal finding</h4>In this study, the transcriptome sequencing of spike tissues of two genotypes of finger millet differing in their grain calcium cont ...[more]

PMID: 25157851

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Project description:Finger millet, an orphan crop, possesses immense potential in mitigating climate change and could offer threefold security in terms of food, fodder, and nutrition. It is mostly cultivated as a subsistence crop in the marginal areas of plains and hills. Considering the changes in climate inclusive of recurrent weather vagaries witnessed every year, it is crucial to select stable, high-yielding, area-specific, finger millet cultivars. Sixty finger millet varieties released across the country were evaluated over six consecutive rainy seasons from 2011 to 2016 at the Agricultural Research Station, Vizianagaram. The genotype × environment interaction (GEI) was found to be significant in the combined ANOVA. Furthermore, the Additive Main effects and Multiplicative Interaction (AMMI) analysis asserted that genotypes and the GEI effects accounted for approximately 89% of the total variation. Strong positive associations were observed in an estimated set of eleven stability parameters which were chosen to identify stable genotypes. Furthermore, Non-parametric and Parametric Simultaneous Selection indices (NP-SSI and P-SSI) were calculated utilizing AMMI-based stability parameter (ASTAB), modified AMMI stability value (MASV), and Modified AMMI Stability Index (MASI) to identify stable high yielders. Both methods had inherent difficulties in ranking genotypes for SSI. To overcome this, the initial culling [i.e., SSI with culling strategy (C-SSI)] of genotypes was introduced for stability. In the C-SSI method, the top ten genotypes were above-average yielders, while those with below-average yield were observed in NP-SSI and P-SSI methods. Similarly, the estimation of best linear unbiased prediction (BLUP)-based simultaneous selections, such as harmonic mean of genotypic values (HMGV), relative performance of genotypic values (RPGV), and harmonic mean of relative performance of genotypic values (HMRPGV), revealed that none of the top ten entries had below-average yield. The study has proven that C-SSI and BLUP-based methods were equally worthy in the selection of high-yielding genotypes with stable performance. However, the C-SSI approach could be the best method to ensure that genotypes with a considerable amount of stability are selected. The multi-year trial SSI revealed that entries Indaf-9, Sri Chaitanya, PR-202, and A-404; and VL324 and VL146 were ascertained to be the most stable high-yielding genotypes among medium-to-late and early maturity groups, respectively.

Dataset Information

Transcriptome wide identification and validation of calcium sensor gene family in the developing spikes of finger millet genotypes for elucidating its role in grain calcium accumulation.

Background

Principal finding

Conclusion

Publications

Transcriptome wide identification and validation of calcium sensor gene family in the developing spikes of finger millet genotypes for elucidating its role in grain calcium accumulation.

Similar Datasets

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