Detection of quantitative trait loci associated with drought tolerance in St. Augustinegrass


Autoři: Xingwang Yu aff001;  Jessica M. Brown aff001;  Sydney E. Graham aff001;  Esdras M. Carbajal aff001;  Maria C. Zuleta aff001;  Susana R. Milla-Lewis aff001
Působiště autorů: Department of Crop and Soil Sciences, North Carolina State University, Raleigh, North Carolina, United States of America aff001
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0224620

Souhrn

St. Augustinegrass (Stenotaphrum secundatum) is a warm-season grass species commonly utilized as turf in the southeastern US. Improvement in the drought tolerance of St. Augustinegrass has significant value within the turfgrass industry. Detecting quantitative trait loci (QTL) associated with drought tolerance will allow for advanced breeding strategies to identify St. Augustinegrass germplasm with improved performance for this trait. A multi-year and multi-environment study was performed to identify QTL in a ‘Raleigh’ x ‘Seville’ mapping population segregating for phenotypic traits associated with drought tolerance. Phenotypic data was collected from a field trial and a two-year greenhouse study, which included relative water content (RWC), chlorophyll content (CHC), leaf firing (LF), leaf wilting (LW), green cover (GC) and normalized difference vegetative index (NDVI). Significant phenotypic variance was observed and a total of 70 QTL were detected for all traits. A genomic region on linkage group R6 simultaneously harbored QTL for RWC, LF and LW in different experiments. In addition, overlapping QTL for GC, LF, LW and NDVI were found on linkage groups R1, R5, R7 and S2. Sequence alignment analysis revealed several drought response genes within these regions. The QTL identified in this study have potential to be used in the future to identify genes associated with drought tolerance and for use in marker-assisted breeding.

Klíčová slova:

Drought adaptation – Gene mapping – Chlorophyll – Leaves – Linkage mapping – Molecular genetics – Quantitative trait loci – Water resources


Zdroje

1. Sauer JD. Revision of Stenotaphrum (Gramineae: Paniceae) with attention to its historical geography. Brittonia. 1972; 24: 202–222.

2. Milla-Lewis SR, Zuleta MC, Van Esbroeck GA, Quesenberry KH, Kenworthy KE. Cytological and molecular characterization of genetic diversity in Stenotaphrum. Crop Sci. 2013; 53: 296–308.

3. Zhang J, Kenworthy K, Unruh JB, Poudel B, Erickson JE, Rowland D, et al. Physiological responses to soil drying by warm-season turfgrass species. Crop Sci. 2017; 57: S111–S118.

4. Zhang J, Poudel B, Kenworthy K, Unruh JB, Rowland D, Erickson JE, et al. Drought responses of above‐ground and below‐ground characteristics in warm‐season turfgrass. J Agron Crop Sci. 2019; 205: 1–12.

5. Farooq M, Wahid A, Kobayashi N, Fujita D, Basra SMA. Plant drought stress: effects, mechanisms and management. Agron Sustain Dev. 2009; 29: 185–212.

6. Gahlaut V, Jaiswal V, Tyagi BS, Singh G, Sareen S, Balyan HS, et al. QTL mapping for nine drought-responsive agronomic traits in bread wheat under irrigated and rain-fed environments. Plos One. 2017; 12: e0182857. doi: 10.1371/journal.pone.0182857 28793327

7. Swamy BPM, Vikram P, Dixit S, Ahmed HU, Kumar A. Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus. BMC Genomics. 2011; 12: 319. doi: 10.1186/1471-2164-12-319 21679437

8. Merewitz E, Belanger F, Warnke S, Huang B. Identification of quantitative trait loci linked to drought tolerance in a colonial × creeping bentgrass hybrid population. Crop Sci. 2012; 52: 1891–1901.

9. Jiang Y, Wang X, Yu X, Zhao X, Luo N, Pei Z, et al. Quantitative trait loci associated with drought tolerance in Brachypodium distachyon. Front Plant Sci. 2017; 8: 811. doi: 10.3389/fpls.2017.00811 28567049

10. Huang B, DaCosta M, Jiang YW. Research Advances in Mechanisms of Turfgrass Tolerance to Abiotic Stresses: From Physiology to Molecular Biology. Crit. Rev. Plant Sci. 2014; 33: 141–189.

11. Wang F, Singh R, Genovesi AD, Wai CM, Huang X, Chandra A, et al. Sequence‐tagged high‐density genetic maps of Zoysia japonica provide insights into genome evolution in Chloridoideae. Plant J. 2015; 82: 744–757. doi: 10.1111/tpj.12842 25846381

12. Huang X, Wang F, Singh R, Reinet JA, Engelke MC, Genovesi AD, et al. Construction of high-resolution genetic maps of Zoysia matrella (L.) Merrill and applications to comparative genomic analysis and QTL mapping of resistance to fall armyworm. BMC genomics. 2016; 17: 562. doi: 10.1186/s12864-016-2969-7 27501690

13. Holloway HMP, Yu XW, Dunne JC, Schwartz BM, Patton AJ, Arellano C, et al. A SNP-based high-density linkage map of zoysiagrass (Zoysia japonica Steud.) and its use for the identification of QTL associated with winter hardiness. Mol Breeding. 2018; 38: 10.

14. Yu X, Kimball JA, Milla-Lewis SR. High density genetic maps of St. Augustinegrass and applications to comparative genomic analysis and QTL mapping for turf quality traits. BMC Plant Biol. 2018; 18: 346. doi: 10.1186/s12870-018-1554-4 30541451

15. Kimball JA, Tuong TD, Arellano C, Livingston DP III, Milla-Lewis SR. Linkage analysis and identification of quantitative trait loci associated with freeze tolerance and turf quality traits in St. Augustinegrass. Mol Breeding. 2018; 38: 67.

16. Morris KN and Shearman RC. 2006. NTEP turfgrass evaluation guidelines. [Online]. www.ntep.org/pdf/ratings.pdf.

17. Schneider CA, Rasband WS, Eliceiri KW. NIH Image to ImageJ: 25 years of image analysis. Nature methods. 2012; 9: 671–675. doi: 10.1038/nmeth.2089 22930834

18. Van Ooijen JW. MapQTL 6: software for the mapping of quantitative trait loci in experimental populations of diploid species. Wageningen: Kyazma BV. 2009.

19. Jespersen D, Ma X, Bonos S, Belanger F, Raymer P, Huang B. Association of SSR and candidate gene markers with genetic variations in summer heat and drought performance for creeping bentgrass. Crop Sci. 2018; 58: 2644–2656.

20. Peirone LS, Pereyra Irujo GA, Bolton A, Erreguerena I, Aguirrezábal LAN. Assessing the efficiency of phenotyping early traits in a greenhouse automated platform for predicting drought tolerance of soybean in the field. Front Plant Sci. 2018; 9: 587. doi: 10.3389/fpls.2018.00587 29774042

21. Steinke K, Chalmers DR, Thomas JC, White RH. Summer drought effects on warm-season turfgrass canopy temperatures. Applied Turfgrass Sci. 2009; 6: 1.

22. Man D, Bao YX, Han LB. Drought tolerance associated with proline and hormone metabolism in two tall fescue cultivars. HORTSCIENCE. 2011; 46: 1027–1032.

23. Huang B, Duncan RR, Carrow RN. Drought-resistance mechanisms of seven warm-season turfgrasses under surface soil drying: II. Root aspects. Crop Sci. 1997; 37: 1863–1869.

24. Racolta A, Bryan AC, Tax FE. The receptor‐like kinases GSO1 and GSO2 together regulate root growth in Arabidopsis through control of cell division and cell fate specification. Dev Dyn. 2014; 243: 257–278. doi: 10.1002/dvdy.24066 24123341

25. Thomas CL, Schmidt D, Bayer EM, Greos R, Maule AJ. Arabidopsis plant homeodomain finger proteins operate downstream of auxin accumulation in specifying the vasculature and primary root meristem. Plant J. 2009; 59: 426–436. doi: 10.1111/j.1365-313X.2009.03874.x 19392692

26. Andersson U, Heddad M, Adamska I. Light stress-induced one-helix protein of the chlorophyll a/b-binding family associated with photosystem I. Plant Physiol. 2003; 132: 811–820. doi: 10.1104/pp.102.019281 12805611

27. Stephenson PG and Terry MJ. Light signalling pathways regulating the Mg-chelatase branchpoint of chlorophyll synthesis during de-etiolation in Arabidopsis thaliana. Photochem Photobiol Sci. 2008; 7: 1243–1252. doi: 10.1039/b802596g 18846290


Článek vyšel v časopise

PLOS One


2019 Číslo 10