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Bhartiya Krishi Anusandhan Patrika, volume 35 issue 3 (september 2020) : 151-158

Transcriptome profiling of Indian sesame (Sissemum indicum L) and discovery of genetic region markers

Sarika Jaiswal, Rukam S. Tomar, Komal Vadukool, Uma, Meenu Chopra, Vitaa, M. Rathod, M.V. Parakhia, M.A. Iqbal, Anil Rai, Dineya Kumar
1Krishi Bioinformatics Center, ICAR-India-Indian Institute of Agricultural Research, New Delhi -110 012 India

  • Submitted10-10-2020|

  • Accepted06-11-2020|

  • First Online 07-12-2020|

  • doi 10.18805/BKAP246

Cite article:- Jaiswal Sarika, Tomar S. Rukam, Vadukool Komal, Uma, Chopra Meenu, Vitaa, Rathod M., Parakhia M.V., Iqbal M.A., Rai Anil, Kumar Dineya (2020). Transcriptome profiling of Indian sesame (Sissemum indicum L)and discovery of genetic region markers. Bhartiya Krishi Anusandhan Patrika. 35(3): 151-158. doi: 10.18805/BKAP246.

ABSTRACT

Sesame (Sesamum indicum L.), is rich source of oil, protein and potent antioxidants with wide applications. Molecular approach can be of great use for trait improvement as well more availability for this crop. The present work aims at tissue specific transcriptome profiling along with biochemical pathway analysis and genic region putative marker discovery. We report 14389, 9465 and 5490 DEGs in root, leaf and flower-bud tissues, respectively. 135, 113 and 120 cellular metabolic or signaling pathways having common 118 pathways were found in root-leaf (RL), leaf-flower (LF) and flower-root (FR), respectively. 218, 170 and 180 transcription factors were identified in root, leaf and flower transcriptome, respectively. Among DEGs, microRNA targets predicted were 534, 376, and 173 in root, leaf and flower, respectively. Genic region repeat analysis revealed 379 SSR. Further variant analysis revealed 3371, 5439 and 4975 SNPs and 2257, 2403 and 2411 INDELs in root, leaf and flower, respectively. The present study will aid in understanding the major biochemical pathways operating in different tissues. Genic region putative marker discovery can be a valuable genomic resource for future crop improvement program.

REFERENCES

  1. Auer C, Frederick R (2009). Crop improvement using small RNAs: applications and predictive ecological risk assessments. Trends Biotechnol. ;27:644–51. Available from: http://www. ncbi.nlm.nih.gov/pubmed/19796832. 
  2. Babraham Bioinformatics - FastQC A Quality Control tool for High Throughput Sequence Data. Available from: http://www.bioinformatics babraham.ac.uk/projects/fastqc/
  3. Bolger AM, Lohse M, Usadel B (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. Oxford University Press; 30:2114–    20. Available from: http://www.ncbi. nlm. nih.gov/pubmed/24695404
  4. Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin). 2012; 6:80–92. Available from:http://www.ncbi.nlm.nih.gov/pubmed/22728672. 
  5. Dai X, Zhao PX (2011). psRNATarget: a plant small RNA target analysis server. Nucleic Acids Res. ; 39:W155-9. Available from: http://www. ncbi.nlm.nih.gov/pubmed/21622958. 
  6. Gebremichael D, Parzies H (2011). Genetic variability among landraces of sesame in Ethiopia. African Crop Sci. J. African Crop Science Society (Uganda); 19. Available from: http://www.ajol. info/ index.php/acsj/article/view/68656. 
  7. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, et al (2011). Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat. Biotechnol. 29:644–52. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21572440. 
  8. Guilioni L, Wery J, Tardieu F (1997). Heat Stress-induced Abortion of Buds and Flowers in Pea: Is Sensitivity Linked to Organ Age or to Relations between Reproductive Organs? Ann. Bot. Oxford University Press; ;80:159–68. Available from: http://aob.oxford journals .org/cgi/doi/10.1006/anbo.1997.0425. 
  9. Jin J, Zhang H, Kong L, Gao G, Luo J (2014).Plant TFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors. Nucleic Acids Res. ; 42:D1182-7. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24174544. 
  10. Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M (2004). The KEGG resource for deciphering the genome. Nucleic Acids Res. 32:D277-80. Available from: http://www.ncbi.nlm.nih.gov/pubmed/14681412. 
  11. Kato MJ, Chu A, Davin LB, Lewis NG (1998). Biosynthesis of antioxidant lignans in Sesamum indicum seeds. Phytochemistry. 47:583–91. 
  12. Kim MJ, Kim J-K, Shin JS, Suh MC (2007). The SebHLH transcription factor mediates trans-activation of the SeFAD2 gene promoter through binding to E- and G-box elements. Plant Mol. Biol. 64:453–66. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17420955. 
  13. Li C, Miao H, Wei L, Zhang T, Han X, Zhang H (2014). Association mapping of seed oil and protein content in Sesamum indicum L. using SSR markers. PLoS One. ; Available from: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0105757. 
  14. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics. ; 25:2078–9.Available from: http://www.ncbi.nlm.nih.gov/pubmed/19505943
  15. Ram, R., D. Catlin, J. Romero and CC. Sesame (1990): New Approaches for Crop Improvement*. Adv. new Crop. Timber Press. Portland, OR. p. 225–228. Available from:https://hort.purdue.edu/newcrop/proceedings1990/V1-225.html. 
  16. Robinson MD, McCarthy DJ, Smyth GK (2010). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 26:139–40. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19910308. 
  17. Statistics | FAO | Food and Agriculture Organization of the United Nations. Available from: http://www.fao.org/statistics/en/. 
  18. Uzun B, Lee D, Donini P, Cagirgan MI (2003). Identification of a molecular marker linked to the closed capsule mutant trait in sesame using AFLP. Plant Breed. 122:95–7. Available from: http://doi.wiley.com/10.1046/j.1439-0523.2003.00787.x. 
  19. Wang L, Han X, Zhang Y, Li D, Wei X, Ding X, et al (2014). Deep resequencing reveals allelic variation in Sesamum indicum. BMC Plant Biol. 14:225. Available from: http://bmcplantbiol.biomedcentral.com/articles/10.1186/s12870-014-0225-3. 
  20. Zhang H, Wei L, Miao H, Zhang T, Wang C. (2012) Development and validation of genic-SSR markers in sesame by RNA-seq. BMC Genomics. ;13:316. Available from:http://www.ncbi.nlm.nih.gov/pubmed/22800194. 
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