Development of SCAR markers related to heat tolerance in Kentucky bluegrass

Mingyue TU; Yali  HE; Xiaoli LI; Ying ZOU; Xiaojun  YUAN

doi:10.15835/nbha48211659

Authors

Mingyue TU Shanghai University, School of Life Science, Shanghai Key Laboratory of Bio-Energy Crops, Shanghai 200444 (CN)
Yali HE Shanghai Jiaotong University, School of Agriculture and Biology, Shanghai 200240 (CN)
Xiaoli LI Shanghai University, School of Life Science, Shanghai Key Laboratory of Bio-Energy Crops, Shanghai 200444 (CN)
Ying ZOU Shanghai University, School of Life Science, Shanghai Key Laboratory of Bio-Energy Crops, Shanghai 200444 (CN)
Xiaojun YUAN Shanghai University, School of Life Science, Shanghai Key Laboratory of Bio-Energy Crops, Shanghai 200444 (CN)

DOI:

https://doi.org/10.15835/nbha48211659

Keywords:

heat tolerance; Poa pratensis; SCAR marker; SRAP marker; SSR marker

Abstract

As a high-quality cool-season grass, Kentucky bluegrass (Poa pratensis) is facing increasing threat of high temperature, so improving its heat tolerance (HT) has become an important breeding target. In this study, the HT of 84 materials was identified in the artificial climate chamber, and 15 most heat-tolerant and 15 most heat-sensitive materials were selected respectively to construct two DNA pools. There was a significant difference in high-temperature tolerance time between the plants in the two pools, which was more than 22 days. A total of 304 sequence-related amplified polymorphism (SRAP) and 88 simple sequence repeat (SSR) markers were used to screen the polymorphic bands between the two pools. Then, these bands were transformed into sequence characterized amplified region (SCAR) markers, and finally 12 SCAR dominant markers related to HT were obtained, which could detect the heat-sensitive materials efficiently. Among them, S-me8×em2 and S-me52×em5 had the best identification effect, and the consistency between the absence of these two markers and the heat-sensitive phenotype was 87%. According to the comparison with NCBI database, the sequences of 12 SCAR markers had no homology with known HT related genes. Next, we would further verify the HT identification efficiency of these SCAR markers in single plants within materials, and try to use them in molecular marker-assisted breeding.

Metrics

Metrics Loading ...

References

Aghaei Z, Talebi M, Rahimmalek M (2017). Assessment of genetic diversity within and among sage (Salvia) species using SRAP markers. Plant Genetic Resources 15(3):279-282. https://doi.org/10.1017/S1479262115000593

Akkaya MS, Bhagwat AA, Cregan PB (1992). Length polymorphisms of simple sequence repeat DNA in soybean. Genetics 132:1131-1139.

Budak H, Shearman RC, Gaussoin RE, Dweikat I (2004a). Application of sequence-related ampliﬁed polymorphism markers for characterization of turfgrass species. HortScience 39(5):955-958. https://doi.org/10.21273/HORTSCI.39.5.955

Budak H, Shearman RC, Parmaksiz I, Gaussoin RE, Riordan TP, Dweikat I (2004b). Molecular characterization of buffalograss germplasm using sequence-related ampliﬁed polymorphism markers. Theoretical and Applied Genetics 108:328-334. https://doi.org/10.1007/s00122-003-1428-4

Clark MS (1997). Plant molecular biology: A laboratory manual. Springer-Verlag, Berlin Heidelberg pp 8-9.

El-Rawy MAE, Youssef M (2014). Evaluation of drought and heat tolerance in wheat based on seedling traits and molecular analysis. Journal of Crop Science and Biotechnology 17(3):183-189. https://doi.org/10.1007/s12892-014-0053-x

Ferriol M, Pico B, Nuez F (2003). Genetic diversity of a germplasm collection of Cucubita pepo using SRAP and AFLP markers. Theoretical and Applied Genetics 107:271-282. https://doi.org/10.1007/s00122-003-1242-z

Gan L, Di R, Chao YH, Han LB, Chen XW, Wu C, Yin SX (2016). De novo transcriptome analysis for Kentucky bluegrass dwarf mutants induced by space mutation. PLoS One 11(5):e0151768. https://doi.org/10.1371/journal.pone.0151768

Guo YW, Wu YQ, Anderson JA, Moss JQ, Zhu L, Fu JM (2017). SSR marker development, linkage mapping, and QTL analysis for establishment rate in common bermudagrass. The Plant Genome 10(1):1-11. https://doi.org/10.3835/plantgenome2016.07.0074

Hansen J, Sato M, Ruedy R, Lo K, Lea DW, Medina-Elizade M (2006). Global temperature change. Proceedings of the National Academy of Science 103(39):14288-14293. https://doi.org/10.1073/pnas.0606291103

Honig JA, Bonos SA, Meyer WA (2010). Isolation and characterization of 88 polymorphic microsatellite markers in Kentucky bluegrass (Poa pratensis L.). HortScience 45(11):1759-1763. https://doi.org/10.21273/HORTSCI.45.11.1759

Honig JA, Kubik C, Averello V, Vaiciunas J, Meyer WA, Bonos SA (2016). Classification of bentgrass (Agrostis) cultivars and accessions based on microsatellite (SSR) markers. Genetic Resources and Crop Evolution 63:1139-1160. https://doi.org/10.1007/s10722-015-0307-6

Huang LK, Zhang XQ, Xie WG, Zhang J, Cheng L, Yan HD (2012). Molecular diversity and population structure of the forage grass Hemarthria compressa (Poaceae) in south China based on SRAP markers. Genetics and Molecular Research 11(3):2441-2450. https://doi.org/10.4238/2012.may.24.3

Huang LK, Yan HD, Zhao XX, Zhang XQ, Wang J, Frazier T, . . . Liu W (2015). Identifying differentially expressed genes under heat stress and developing molecular markers in orchardgrass (Dactylis glomerata L.) through transcriptome analysis. Molecular Ecology Resources 15:1497-1509. https://doi.org/10.1111/1755-0998.12418

Huang Z, Zhang XX, Jiang SH, Qin MF, Zhao N, Lang LN, . . . Xu AX (2017). Analysis of cold resistance and identification of SSR markers linked to cold resistance genes in Brassica rapa L. Breeding Science 67(3):213-220. https://doi.org/10.1270/jsbbs.16161

Jespersen D, Ma XQ, Bonos SA, Belanger FC, Raymer P, Huang BR (2018). Association of SSR and candidate gene markers with genetic variations in summer heat and drought performance for creeping bentgrass. Crop Science 58:2644-2656. https://doi.org/10.2135/cropsci2018.05.0299

Karl TR, Kukla G, Razuvayev VN, Changery MJ, Quayle RG, Heim RR, … Fu CB (1991). Global warming: Evidence for asymmetric diurnal temperature change. Geophysical Research Letters 18(12):2253-2256. https://doi.org/10.1029/91GL02900

Kempf K, Malisch CS, Grieder C, Widmer F, Kölliker R (2017). Marker-trait association analysis for agronomic and compositional traits in sainfoin (Onobrychis viciifolia). Genetics and Molecular Research 16 (1):gmr16019483. https://doi.org/10.4238/gmr16019483

Kozub PC, Barboza K, Cavagnaro JB, Cavagnaro PF (2018). Development and characterization of SSR markers for Trichloris crinita using sequence data from related grass species. Revista de la Facultad de Ciencias Agrarias 50(1):1-16.

Li G, Quiros CF (2001). Sequence-related amplified polymorphism (SRAP), a new marker system based on a simple PCR reaction: its application to mapping and gene tagging in Brassica. Theoretical and Applied Genetics 103:455-461. https://doi.org/10.1007/s001220100570

Li G, Gao M, Yang B, Quiros CF (2003). Gene for gene alignment between the Brassica and Arabidopsis genomes by direct transcriptome mapping. Theoretical and Applied Genetics 107:168-180. https://doi.org/10.1007/s00122-003-1236-x

Li Q, He YL, Tu MY, Yan JH, Yu LL, Qi WW, Yuan XJ (2019). Transcriptome sequencing of two Kentucky bluegrass (Poa pratensis L.) genotypes in response to heat Stress. Notulae Botanicae Horti Agrobotanici Cluj-Napoca 47(2):328-338. https://doi.org/10.15835/nbha47111365

Meyer WA, Hoffman L, Bonos SA (2017). Breeding cool-season turfgrass cultivars for stress tolerance and sustainability in a changing environment. International Turfgrass Society Research Journal 13:3-10. https://doi.org/10.2134/itsrj2016.09.0806

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 Biology 15:122. https://doi.org/10.1186/s12870-015-0498-1

Moustafa KA, Saleh M, Al-Doss AA, Elshafei AA, Salem AK, Al-Qurainy FH, Barakat MN (2014). Identification of TRAP and SRAP markers linked with yield components under drought stress in wheat (Triticum aestivum L.). Plant Omics Journal 7(4):253-259.

Nie G, Tang L, Zhang YJ, Huang LK, Ma X, Cao X, . . . Zhang XQ (2017). Development of SSR markers based on transcriptome sequencing and association analysis with drought tolerance in perennial grass Miscanthus from China. Frontiers in Plant Science 8:801. https://doi.org/10.3389/fpls.2017.00801

Paran I, Michelmore RW (1993). Development of reliable PCR-based markers linked to downy mildew resistance genes in lettuce. Theoretical and Applied Genetics 85:985-993. https://doi.org/10.1007/BF00215038

Priya M, Siddique KHM, Dhankhar OP, Prasad PVV, Rao BH, Nair RM, Nayyar H (2018). Molecular breeding approaches involving physiological and reproductive traits for heat tolerance in food crops. Indian Journal of Plant Physiology 23(4):697-720. https://doi.org/10.1007/s40502-018-0427-z

Reddy INBL, Kim SM, Kim BK, Yoon IS, Kwon TR (2017). Identification of rice accessions associated with K+/Na+ ratio and salt tolerance based on physiological and molecular responses. Rice Science 24(6):360-364. https://doi.org/10.1016/j.rsci.2017.10.002

Said AA, Hamada A, Youssef M (2015). Assessment of heat tolerance in bread wheat using some agronomic traits and SRAP markers. Egyptian Journal of Plant Breeding 19(3):979-994. https://doi.org/10.12816/0031573

Sun XY, Du ZM, Ren J, Amombo E, Hu T, Fu JM (2015a). Association of SSR markers with functional traits from heat stress in diverse tall fescue accessions. BMC Plant Biology 15:116. https://doi.org/10.1186/s12870-015-0494-5

Sun XY, Xie Y, Bi YF, Liu JP, Amombo E, Hu T, Fu JM (2015b). Comparative study of diversity based on heat tolerant-related morpho-physiological traits and molecular markers in tall fescue accessions. Scientific Reports 5:18213. https://doi.org/10.1038/srep18213

Vos P, Hogers R, Bleeker M, Reijans M, van de Lee T, Hornes M, . . . Zabeau M (1995). AFLP: a new technique for DNA fingerprinting. Nucleic Acids Research 23(21): 4407-4414. https://doi.org/10.1093/nar/23.21.4407

Wang G, Pan JS, Li XZ, He HL, Wu AZ, Cai R (2005). Construction of a cucumber genetic linkage map with SRAP markers and location of the genes for lateral branch traits. Science in China Series C: Life Sciences 48(3):213-220. https://doi.org/10.1007/BF03183614

Wang ZY, Liao L, Yuan XJ, Guo A, Liu JX (2011). Genetic relationships of bermudagrass (Cynodon dactylon var. dactylon) from different countries revealed by sequence-related amplified polymorphism (SRAP) analysis. African Journal of Biotechnology 10(75):17106-17115. https://doi.org/10.5897/ajb11.1422

Williams JG, Kubelik AR, Livak KJ, Rafalski JA, Tingey SV (1990). DNA polymorphisms amplified by arbitrary primes are useful as genetic markers. Nucleic Acids Research 18(22):6531-6535. https://doi.org/10.1093/nar/18.22.6531

Yuan XJ, Tu MY, He YL, Wang WQ, Li J, Zhou SM (2018). Analysis of genetic diversity in 73 Kentucky bluegrass materials by SSR and SRAP Markers. Notulae Botanicae Horti Agrobotanici Cluj-Napoca 46(2):327-335. https://doi.org/10.15835/nbha46210916

Zheng YQ, Xu SJ, Liu J, Zhao Y, Liu JX (2017). Genetic diversity and population structure of Chinese natural bermudagrass [Cynodon dactylon (L.) Pers.] germplasm based on SRAP markers. PLoS One 12(5): e0177508. https://doi.org/10.1371/journal.pone.0177508

Zhu YQ, Wang X, Huang LK, Lin CW, Zhang XQ, Xu WZ, . . . Peng DD (2017). Transcriptomic identification of drought-related genes and SSR markers in Sudan grass based on RNA-Seq. Frontiers in Plant Science 8:687. https://doi.org/10.3389/fpls.2017.01518