Abstract
Being a major staple food crop of the world, wheat provides nutritional food security to the global populations. Heat stress is a major abiotic stress that adversely affects wheat production throughout the world including Indo-Gangatic Plains (IGP) where four wheat growing countries viz., India, Bangladesh, Nepal and Pakistan produce 42% of the total wheat production. Therefore, identification of heat stress responsive molecular markers is imperative to marker assisted breeding programs. Information about trait specific gene based SSRs is available but there is lack of information on SSRs from non-coding regions. In the present study, we developed 177 heat-responsive gene-based SSRs (cg-SSR) and MIR gene-based SSR (miRNA-SSR) markers from wheat genome for assessing genetic diversity analysis of thirty- six contrasting wheat genotypes for heat tolerance. Of the 177 SSR loci, 144 yielded unambiguous and repeatable amplicons, however, thirty-seven were found polymorphic among the 36 wheat genotypes. The polymorphism information content (PIC) of primers used in this study ranged from 0.03–0.73, with a mean of 0.35. Number of alleles produced per primer varied from 2 to 6, with a mean of 2.58. The UPGMA dendrogram analysis grouped all wheat genotypes into four clusters. The markers developed in this study has potential application in the MAS based breeding programs for developing heat tolerant wheat cultivars and genetic diversity analysis of wheat germplasm. Identification of noncoding region based SSRs will be fruitful for identification of trait specific wheat germplasm.





Similar content being viewed by others
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.References
Al-Khatib K, Paulsen GM (1984) Mode of high temperature injury to wheat during grain development. Physiol Plant 6:363–368
Rane J, Pannu RK, Sohu VS, Saini RS, Mishra B, Shoran J, Crossa J, Vargas M, Joshi AK (2007) Performance of yield and stability of advanced wheat genotypes under heat stress environments of the indo-gangetic plains. Crop Sci 47:1561–1573
Garg D, Sareen S, Dalal S, Tiwari R, Singh R (2013) Grain filling duration and temperature pattern influence the performance of wheat genotypes under late planting. Cereal Res Comm 41(3):500–507
Pandey GC, Mehta G, Sharma P, Sharma V (2019) Terminal heat tolerance in wheat: an overview. J cereal Res 11(1):1–16
Wardlaw IF, Dawson IA, Munibi P, Fewster R (1989) The tolerance of wheat to high temperatures during reproductive growth: I. survey procedures and general response patterns. Aust J Agric Res 40:1–13
Hunt LA, Der-Poorten G, Pararajasingham A (1991) Postanthesis temperature effects on duration and rate of grain filling in some winter and spring wheats. Canadian J Plan Sci 71(3):609–617
Stone PJ, Nicholas ME (1994) Wheat cultivars vary widely in their responses of grain yield and quality to short periods of post-anthesis heat stress. Aust J Plant Physiol 21:887–900
Collins NC, Tardieu F, Tuberosa R (2008) Quantitative trait loci and crop performance under abiotic stress: where do we stand? Plant Physiol 147(2):469–486
Tiwari C, Wallwork H, Kumar U et al (2013) Molecular mapping of high temperature tolerance in bread wheat adapted to the eastern gangetic plain region of India. Field Crops Res 154:201–210
Bhusal N, Sarial AK, Sharma P, Sareen S (2017) Mapping QTLs for grain yield components in wheat under heat stress. PLoS ONE 12(12):e0189594
Varshney RK, Graner A, Sorrells ME (2005) Genic microsatellite markers in plants: features and applications. Trends Biotechnol 2:48–55
Sheoran S, Sharma P, Malik R, Apoorava Sharma D, Singh R, Tiwari R, Tiwari V, Sharma I (2015) Assessment of genetic diversity in elite indian wheat genotypes using simple sequence repeat and quality protein markers. J Wheat Res 7(1):18–26
Sharma D, Singh R, Rane J, Gupta VK, Mamrutha HM, Tiwari R (2016) Mapping quantitative trait loci associated with grain filling duration and grain number under terminal heat stress in bread wheat (Triticum aestivum L.). Plant Breed 135(5):538–545
Sareen S, Sharma P, Tiwari V, Sharma I (2014) Identifying wheat landraces as genetic resources for drought and heat tolerance. Res on Crops 15(4):846–851
Sharma P, Saini M, Sareen S, Verma A, Tyagi BS, Sharma I (2014) Assessing genetic variation for heat tolerance in synthetic wheat lines using phenotypic data and molecular markers. Aust J Crop Sci 8(4):515–522
Han B, Wang C, Tang Z et al (2015) Genome-wide analysis of microsatellite markers based on sequenced database in chinese spring wheat (Triticum aestivum L.). PLoS ONE 10(11):e0141540
Chen X, Gao W, Zhang J, Zhang X, Lin Z (2013) Linkage mapping and expression analysis of miRNAs and their target genes during fiber development in cotton. BMC Genomics 14:706
Jaiswal S, Sheoran S, Arora V et al (2017) Putative microsatellite DNA marker-based wheat genomic resource for varietal improvement and management. Front Plant Sci. https://doi.org/10.3389/fpls.2017.02009
Molla KA, Debnath AB, Ganie SA, Mondal TK (2015) Identification and analysis of novel salt responsive candidate gene based SSRs (cgSSRs) from rice (Oryza sativa L.). BMC Plant Biol 15:122
Sharma P, Geetika, G. Singroha, M. Saroha, SK Singh, Singh GP (2019) Identification and validation of new salt responsive gene/miRNAs based markers in wheat. In: Golden jubilee international conference on “Resilient agriculture in saline environments under changing climate: challenges and opportunities held at ICAR-CSSRI, Karnal w.e.f. 7(9):117–118
Barret P, Brinkman M, Dufour P, Murigneux A, Beckert M (2004) Identification of candidate genes for in vitro androgenesis induction in maize. Theor Appl Genet 109:1660–1668
Sun X, Du Z, Ren J, Amombo E, Hu T, Fu J (2015) Association of SSR markers with functional traits from heat stress in diverse tall fescue accessions. BMC Plant Biol 15:116
Kumar RR, Goswami S, Shamim M et al (2017) Exploring the heat-responsive chaperones and microsatellite markers associated with terminal heat stress tolerance in developing wheat. Funct Integr Genomics 17(6):621–640
Singh I, Smita S, Mishra DC, Kumar S, Singh BK, Rai A (2017) Abiotic stress responsive miRNA-target network and related markers (SNP, SSR) in Brassica juncea. Front Plant Sci 8:1943
Mondal TK, Ganie SA (2014) Identification and characterization of salt responsive miRNA-SSR markers in rice (Oryza sativa). Gene 535(2):204–209
Nithin C, Patwa N, Thomas A, Bahadur RP, Basak J (2015) Computational prediction of miRNAs and their targets in Phaseolus vulgaris using simple sequence repeat signatures. BMC Plant Biol 15:140
Bhandawat A, Sharma H, Pundir N et al (2020) Genome-wide identification and characterization of novel non-coding RNA-derived SSRs in wheat. Mol Biol Rep 47:6111–6125
Fischer RA, Maurer R (1978) Drought resistance in spring wheat cultivars. I. Grain yield response. Aust J Agric Res 29:897–907
Muthusamy SK (2017) Gene discovery and allele mining for thermotolerance in wheat using transcriptome analysis (PhD thesis) ICAR-Indian Agricultural Research Institute, New Delhi, India
Muthusamy SK, Dalal M, Chinnusamy V, Bansal KC (2017) Genome-wide identification and analysis of biotic and abiotic stress regulation of small heat shock protein (HSP20) family genes in bread wheat. J Plant Physiol 211:100–113
Sharma P, Muthusamy SK, Geetika G, Shefali (2017) Exploring genetic diversity for heat tolerance among bread wheat genotypes using gene/QTLs based SSR markers. In: 3rd International conference on bioenergy environment and sustainable technologies –BEST2017held at Tiruvannamalai, India
Doyle JJ, Doyle JL (1990) A rapid DNA isolation preparation procedure for fresh tissue. Focus 12:13–15
Yeh FC, Yang RC, Boyle T (1999) POPGENE 32-version 1.31. Population genetics software. http://www.ualberta.ca/fyeh/fyeh/. Accessed Sept 2018
Nei M, Tajima F, Tateno Y (1983) Accuracy of estimated phylogenetic trees from molecular data. II. Gene frequency data. J Mol Evol 19(2):153–170
Perrier X, Jacquemoud-Collet JP (2006) DARwin software http://darwin.cirad.fr/Darwin. Accessed Sept 2018
Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in excel. Population genetic software for teaching and research–an update. Bioinformatics 28(19):2537–2539
Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959
Evanno G, Reganut E, Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol 14:2611–2620
Nachimuthu VV, Muthurajan R, Duraialaguraja S et al (2015) Analysis of population structure and genetic diversity in rice germplasm using SSR markers: an initiative towards association mapping of agronomic traits in Oryza Sativa. Rice 8(1):30
Wang L, Chen H, Bai P, Wu J, Wang S, Blair M (2015) The transferability and polymorphism of mungbean SSR markers in rice bean germplasm. Mol Breed 35(2):1–10
Sharma A, Chauhan RS (2008) Identification of candidate gene-based markers (SNPs and SSRs) in the zinc and iron transporter sequences of maize (Zea mays L.). Curr Sci 95:1051–1059
Jia X, Zhang Z, Liu Y, Zhang C, Shi Y, Song Y, Wang T, Li Y (2009) Development and genetic mapping of SSR markers in foxtail millet [Setaria italica (L.) P. Beauv.]. Theor Appl Genet 118:821–829
Kanzana G, Zhang Y, Mannn T, et al. 2019 Genome-wide development of miRNA-based SSR markers in Cleistogenes songorica with their transferability analysis to gramineae and non-gramineae species. bioRxiv 9, 723544
Hazra A, Dasgupta N, Sengupta C, Das S (2017) Extrapolative microRNA precursor based SSR mining from tea EST database in respect to agronomic traits. BMC Res Notes 10:4–9
Wang X, Gui S, Pan L, Hu J, Ding Y (2016) Development and characterization of polymorphic microRNA-based microsatellite markers in Nelumbo nucifera (Nelumbonaceae). Plant Sci 4:1500091
Patil PG, Singh NV, Parashuram S et al (2020) Genome wide identification, characterization and validation of novel miRNA-based SSR markers in pomegranate (Punica granatum L.). J Physiol Mol Biol Plants 26(4):683–696
Dhaka N, Mukhopadhyay A, Paritosh K, Gupta V, Pental D, Pradhan AK (2017) Identification of genic SSRs and construction of a SSR-based linkage map in Brassica juncea. Euphytica 213(1):15
Gemayel R, Vinces MD, Legendre M, Verstrepen KJ (2010) Variable tandem repeats accelerate evolution of coding and regulatory sequences. Ann Rev Gent 44:445–477
Varshney RK, Graner A, Sorrells ME (2005) Genic microsatellite markers in plants: features and applications. Trends Biotechnol 23(1):48–55
Bej S, Basak J (2014) MicroRNAs: the potential biomarkers in plant stress response. American J Plant Sci 5:12
Botstein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet 32:314–331
Fu D, Ma BI, Naliese AN, Mason S, Xiao M, Wei L, An ZE (2013) MicroRNA-based molecular markers: a novel PCR-based genotyping technique in Brassica species. Plant Breed 132:375–381
Scott KD, Eggler P, Seaton G, Rossetto M, Ablett EM, Lee LS, Henry RJ (2000) Analysis of SSRs derived from grape ESTs. Theor Appl Genet 100:723–726
Yu K, Park SJ, Poysa V, Gepts P (2000) Integration of simple sequence repeat (SSR) markers into a molecular linkage map of common bean (Phaseolus vulgaris L.). Am Genet Assoc 91:429–434
Sharma H, Kumar P, Singh A, Aggarwal K, Roy J, Sharma V, Rawat S (2020) Development of polymorphic EST-SSR markers and their applicability in genetic diversity evaluation in Rhododendron arboreum. Mol Biol Rep 47:2447–2457
Acknowledgements
Authors would like to acknowledge the project funded by Indian Council of Agricultural Research (ICAR), New Delhi for awarding Lal Bahadur Shastri Outstanding young scientist award scheme No. Edn/34/2/2015-HRD to PS. Also, thankful to GRU for supplying seeds of wheat genotypes used in this study and Dr Garima Singroha for her help during the period.
Author information
Authors and Affiliations
Contributions
PS conceived the theme of the study and designed the experiment. GM recorded and analysed field data. Shefali did bioinformatics analysis; SKM analysed the genes and SSR data. PS, SKM, SKS and GPS drafted the manuscript. All co-authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Sharma, P., Mehta, G., Shefali et al. Development and validation of heat-responsive candidate gene and miRNA gene based SSR markers to analysis genetic diversity in wheat for heat tolerance breeding. Mol Biol Rep 48, 381–393 (2021). https://doi.org/10.1007/s11033-020-06059-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11033-020-06059-1


