Genome-wide association mapping of total antioxidant capacity, phenols, tannins, and flavonoids in a panel of Sorghum bicolor and S. bicolor × S. halepense populations using multi-locus models
Autoři:
Ephrem Habyarimana aff001; Michela Dall’Agata aff001; Paolo De Franceschi aff001; Faheem S. Baloch aff002
Působiště autorů:
CREA Research Center for Cereal and Industrial Crops, Bologna, Italy
aff001; Department of Field Crops, Faculty of Agricultural and Natural Sciences, Abant Izzet Baysal University, Bolu, Turkey
aff002
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0225979
Souhrn
Sorghum is widely used for producing food, feed, and biofuel, and it is increasingly grown to produce grains rich in health-promoting antioxidants. The conventional use of grain color as a proxy to indirectly select against or for antioxidants polyphenols in sorghum grain was hampered by the lack of consistency between grain color and the expected antioxidants concentration. Marker-assisted selection built upon significant loci identified through linkage disequilibrium studies showed interesting potential in several plant breeding and animal husbandry programs, and can be used in sorghum breeding for consumer-tailored antioxidant production. The purpose of this work was therefore to conduct genome-wide association study of sorghum grain antioxidants using single nucleotide polymorphisms in a novel diversity panel of Sorghum bicolor landraces and S. bicolor × S. halepense recombinant inbred lines. The recombinant inbred lines outperformed landraces for antioxidant production and contributed novel polymorphism. Antioxidant traits were highly correlated and showed very high broad-sense heritability. The genome-wide association analysis uncovered 96 associations 55 of which were major quantitative trait loci (QTLs) explaining 15 to 31% of the observed antioxidants variability. Eight major QTLs localized in novel chromosomal regions. Twenty-four pleiotropic major effect markers and two novel functional markers (Chr9_1550093, Chr10_50169631) were discovered. A novel pleiotropic major effect marker (Chr1_61095994) explained the highest proportion (R2 = 27–31%) of the variance observed in most traits evaluated in this work, and was in linkage disequilibrium with a hotspot of 19 putative glutathione S-transferase genes conjugating anthocyanins into vacuoles. On chromosome four, a hotspot region was observed involving major effect markers linked with putative MYB-bHLH-WD40 complex genes involved in the biosynthesis of the polyphenol class of flavonoids. The findings in this work are expected to help the scientific community particularly involved in marker assisted breeding for the development of sorghum cultivars with consumer-tailored antioxidants concentration.
Klíčová slova:
Alleles – Antioxidants – Genetic loci – Genome-wide association studies – Phenols – Quantitative trait loci – Sorghum – Fens
Zdroje
1. Habyarimana E, Lorenzoni C, Marudelli M, Redaelli R, Amaducci S. A meta-analysis of bioenergy conversion relevant traits in sorghum landraces, lines and hybrids in the Mediterranean region. Ind Crops Prod. 2016;81: 100–109. doi: 10.1016/j.indcrop.2015.11.051
2. Alfieri M, Balconi C, Cabassi G, Habyarimana E, Redaelli R. Antioxidant activity in a set of sorghum landraces and breeding lines. Maydica. 2017;62: 1–7.
3. Habyarimana E, Bonardi P, Laureti D, Di Bari V, Cosentino S, Lorenzoni C. Multilocational evaluation of biomass sorghum hybrids under two stand densities and variable water supply in Italy. Ind Crops Prod. 2004;20: 3–9. doi: 10.1016/j.indcrop.2003.12.020
4. Habyarimana E, Piccard I, Catellani M, De Franceschi P, Dall’Agata M. Towards Predictive Modeling of Sorghum Biomass Yields Using Fraction of Absorbed Photosynthetically Active Radiation Derived from Sentinel-2 Satellite Imagery and Supervised Machine Learning Techniques. Agronomy. 2019;9: 203. doi: 10.3390/agronomy9040203
5. Singh M, Kumar S, editors. Broadening the genetic base of grain cereals. New Delhi: Springer; 2016. doi: 10.1007/978-81-322-3613-9
6. Cox TS, Van Tassel DL, Cox CM, Dehaan LR. Progress in breeding perennial grains. Crop Pasture Sci. 2010;61: 513–521. doi: 10.1071/CP09201
7. FAO. Perennial crops for food security. Proceedings of the Fao Expert Workshop. 2013; 390.
8. Habyarimana E, Lorenzoni C, Redaelli R, Alfieri M, Amaducci S, Cox S. Towards a perennial biomass sorghum crop: A comparative investigation of biomass yields and overwintering of Sorghum bicolor x S. halepense lines relative to long term S. bicolor trials in northern Italy. Biomass and Bioenergy. 2018;111: 187–195. doi: 10.1016/j.biombioe.2017.03.004
9. Piper JK, Kulakow PA. Seed yield and biomass allocation in Sorghum bicolor and F 1 and backcross generations of S. bicolor × S. halepense hybrids. Can J Bot. 2007;72: 468–474. doi: 10.1139/b94-062
10. Cox S, Nabukalu P, Paterson AH, Kong W, Nakasagga S. Development of perennial grain sorghum. Sustain. 2018;10: 172. doi: 10.3390/su10010172
11. Kong W, Kim C, Goff VH, Zhang D, Paterson AH. Genetic analysis of rhizomatousness and its relationship with vegetative branching of recombinant inbred lines of Sorghum bicolor x S. propinquum. Am J Bot. 2015;102: 718–724. doi: 10.3732/ajb.1500035 26022486
12. Kong W, Jin H, Franks CD, Kim C, Bandopadhyay R, Rana MK, et al. Genetic Analysis of Recombinant Inbred Lines for Sorghum bicolor × Sorghum propinquum. G3: Genes|Genomes|Genetics. 2013;3: 101–108. doi: 10.1534/g3.112.004499 23316442
13. Cox TS, Bender M, Picone C, Van Tassel DL, Holland JB, Brummer EC, et al. Breeding perennial grain crops. Crit Rev Plant Sci. 2002;21: 59–91. doi: 10.1080/0735-260291044188
14. Paterson AH. Genomics of sorghum. Int J Plant Genomics. 2008;2008: 362451. doi: 10.1155/2008/362451 18483564
15. Nabukalu P, Cox TS. Response to selection in the initial stages of a perennial sorghum breeding program. Euphytica. 2016;209: 103–111. doi: 10.1007/s10681-016-1639-9
16. Dweikat I. A diploid, interspecific, fertile hybrid from cultivated sorghum, Sorghum bicolor, and the common Johnsongrass weed Sorghum halepense. Mol Breed. 2005;16: 93–101. doi: 10.1007/s11032-005-5021-1
17. Cox S, Nabukalu P, Paterson AH, Kong W, Auckland S, Rainville L, et al. High proportion of diploid hybrids produced by interspecific diploid × tetraploid Sorghum hybridization. Genet Resour Crop Evol. 2018;65: 387–390. doi: 10.1007/s10722-017-0580-7
18. Przybylska-Balcerek A, Frankowski J, Stuper-Szablewska K. Bioactive compounds in sorghum. Eur Food Res Technol. 2019;245: 1075–1080. doi: 10.1007/s00217-018-3207-0
19. Awika JM, Rooney LW. Sorghum phytochemicals and their potential impact on human health. Phytochemistry. 2004;65: 1199–1221. doi: 10.1016/j.phytochem.2004.04.001 15184005
20. Dykes L, Rooney LW. Phenolic compounds in cereal grains and their health benefits. Cereal Foods World. 2007;52: 105–111. doi: 10.1094/CFW-52-3-0105
21. Rice-Evans CA, Miller NJ, Paganga G. Structure-antioxidant activity relationships of flavonoids and phenolic acids. Free Radic Biol Med. 1996;20: 933–956. doi: 10.1016/0891-5849(95)02227-9 8743980
22. Heinonen IM, Meyer AS, Frankel EN. Antioxidant Activity of Berry Phenolics on Human Low-Density Lipoprotein and Liposome Oxidation. J Agric Food Chem. 1998;46: 4107–4112. doi: 10.1021/jf980181c
23. Setchell KDR, Cassidy A. Dietary Isoflavones: Biological Effects and Relevance to Human Health. J Nutr. 2018;129: 758S–767S. doi: 10.1093/jn/129.3.758s 10082786
24. Del Rio D, Rodriguez-Mateos A, Spencer JPE, Tognolini M, Borges G, Crozier A. Dietary (Poly)phenolics in Human Health: Structures, Bioavailability, and Evidence of Protective Effects Against Chronic Diseases. Antioxid Redox Signal. 2013;18: 1818–1892. doi: 10.1089/ars.2012.4581 22794138
25. Dykes L, Rooney LW. Sorghum and millet phenols and antioxidants. J Cereal Sci. 2006;44: 236–251. doi: 10.1016/j.jcs.2006.06.007
26. Debeaujon I, Léon-Kloosterziel KM, Koornneef M. Influence of the Testa on Seed Dormancy, Germination, and Longevity in Arabidopsis. Plant Physiol. 2000;122: 403–414. doi: 10.1104/pp.122.2.403 10677433
27. Esele JP, Frederiksen RA, Miller FR. The Association of Genes Controlling Caryopsis Traits with Grain Mold Resistance in Sorghum. Phytopathology. 1993;83: 490. doi: 10.1094/phyto-83-490
28. McMillian WW, Wiseman BR, Burns RE, Harris HB, Greene GL. Bird Resistance in Diverse Germplasm of Sorghum. Agron J. 1972;64: 821. doi: 10.2134/agronj1972.00021962006400060036x
29. Santos‐Buelga C, Scalbert A. Proanthocyanidins and tannin-like compounds–nature, occurrence, dietary intake and effects on nutrition and health. J Sci Food Agric. 2000;80: 1094–1117. doi: 10.1002/(SICI)1097-0010(20000515)80:7<1094::AID-JSFA569>3.0.CO;2–1
30. Wu Y, Li X, Xiang W, Zhu C, Lin Z, Wu Y, et al. Presence of tannins in sorghum grains is conditioned by different natural alleles of Tannin1. Proc Natl Acad Sci. 2012;109: 10281–10286. doi: 10.1073/pnas.1201700109 22699509
31. Rhodes DH, Hoffmann L, Rooney WL, Ramu P, Morris GP, Kresovich S. Genome-wide association study of grain polyphenol concentrations in global sorghum [Sorghum bicolor (L.) Moench] germplasm. J Agric Food Chem. 2014;62: 10916–10927. doi: 10.1021/jf503651t 25272193
32. Salas Fernandez MG, Hamblin MT, Li L, Rooney WL, Tuinstra MR, Kresovich S. Quantitative trait loci analysis of endosperm color and carotenoid content in sorghum grain. Crop Sci. 2008;48: 1732–1743. doi: 10.2135/cropsci2007.12.0684
33. Bekele WA, Fiedler K, Shiringani A, Schnaubelt D, Windpassinger S, Uptmoor R, et al. Unravelling the genetic complexity of sorghum seedling development under low-temperature conditions. Plant, Cell Environ. 2014;37: 707–723. doi: 10.1111/pce.12189 24033406
34. Boyles RE, Pfeiffer BK, Cooper EA, Zielinski KJ, Myers MT, Rooney WL, et al. Quantitative trait loci mapping of agronomic and yield traits in two grain sorghum biparental families. Crop Sci. 2017;57: 2443–2456. doi: 10.2135/cropsci2016.12.0988
35. Chopra R, Burow G, Burke JJ, Gladman N, Xin Z. Genome-wide association analysis of seedling traits in diverse Sorghum germplasm under thermal stress. BMC Plant Biol. 2017;17: 12. doi: 10.1186/s12870-016-0966-2 28086798
36. Mace ES, Jordan DR. Location of major effect genes in sorghum (Sorghum bicolor (L.) Moench). Theor Appl Genet. 2010;121: 1339–1356. doi: 10.1007/s00122-010-1392-8 20585750
37. Rhodes D, Gadgil P, Perumal R, Tesso T, Herald TJ. Natural variation and genome-wide association study of antioxidants in a diverse sorghum collection. Cereal Chem. 2017;94: 190–198. doi: 10.1094/CCHEM-03-16-0075-R
38. Zhang D, Kong W, Robertson J, Goff VH, Epps E, Kerr A, et al. Genetic analysis of inflorescence and plant height components in sorghum (Panicoidae) and comparative genetics with rice (Oryzoidae). BMC Plant Biol. 2015;15: 107. doi: 10.1186/s12870-015-0477-6 25896918
39. Mace E, Innes D, Hunt C, Wang X, Tao Y, Baxter J, et al. The Sorghum QTL Atlas: a powerful tool for trait dissection, comparative genomics and crop improvement. Theor Appl Genet. 2018; 1–16. doi: 10.1007/s00122-018-3212-5 30343386
40. Boddu J, Svabek C, Ibraheem F, Jones AD, Chopra S. Characterization of a deletion allele of a sorghum Myb gene yellow seed1 showing loss of 3-deoxyflavonoids. Plant Sci. 2005;169: 542–552. doi: 10.1016/j.plantsci.2005.05.007
41. Federer WT. Augmented (or hoonuiaku) designs. Hawaiian Plant Rec. 1956;55: 191–208.
42. Alfieri M, Cabassi G, Habyarimana E, Quaranta F, Balconi C, Redaelli R. Discrimination and prediction of polyphenolic compounds and total antioxidant capacity in sorghum grains. J Near Infrared Spectrosc. 2019;27: 46–53. doi: 10.1177/0967033518825351
43. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call format and VCFtools. Bioinformatics. 2011;27: 2156–2158. doi: 10.1093/bioinformatics/btr330 21653522
44. Tang Y, Liu X, Wang J, Li M, Wang Q, Tian F, et al. GAPIT Version 2: An Enhanced Integrated Tool for Genomic Association and Prediction. Plant Genome. 2016;9: 0. doi: 10.3835/plantgenome2015.11.0120 27898829
45. Shakoor N, Ziegler G, Dilkes BP, Brenton Z, Boyles R, Connolly EL, et al. Integration of Experiments across Diverse Environments Identifies the Genetic Determinants of Variation in Sorghum bicolor Seed Element Composition. Plant Physiol. 2016;170: 1989–1998. doi: 10.1104/pp.15.01971 26896393
46. Sharma SK, MacKenzie K, McLean K, Dale F, Daniels S, Bryan GJ. Linkage Disequilibrium and Evaluation of Genome-Wide Association Mapping Models in Tetraploid Potato. G3: Genes|Genomes|Genetics. 2018;8: 3185–3202. doi: 10.1534/g3.118.200377 30082329
47. VanRaden PM. Efficient Methods to Compute Genomic Predictions. J Dairy Sci. 2008;91: 4414–4423. doi: 10.3168/jds.2007-0980 18946147
48. Liu X, Huang M, Fan B, Buckler ES, Zhang Z. Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies. Listgarten J, editor. PLoS Genet. 2016;12: e1005767. doi: 10.1371/journal.pgen.1005767 26828793
49. Wang Q, Tian F, Pan Y, Buckler ES, Zhang Z. A SUPER powerful method for genome wide association study. Li Y, editor. PLoS One. 2014;9: e107684. doi: 10.1371/journal.pone.0107684 25247812
50. Xu Y, Yang T, Zhou Y, Yin S, Li P, Liu J, et al. Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models. Front Plant Sci. 2018;9. doi: 10.3389/fpls.2018.01311 30233634
51. Goodstein DM, Shu S, Howson R, Neupane R, Hayes RD, Fazo J, et al. Phytozome: A comparative platform for green plant genomics. Nucleic Acids Res. 2012;40: D1178–D1186. doi: 10.1093/nar/gkr944 22110026
52. Pourcel L, Routaboul JM, Cheynier V, Lepiniec L, Debeaujon I. Flavonoid oxidation in plants: from biochemical properties to physiological functions. Trends Plant Sci. 2007. pp. 29–36. doi: 10.1016/j.tplants.2006.11.006 17161643
53. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2018.
54. Xu S, Zhu D, Zhang Q. Predicting hybrid performance in rice using genomic best linear unbiased prediction. Proc Natl Acad Sci. 2014;111: 12456–12461. doi: 10.1073/pnas.1413750111 25114224
55. Simeone R, Misztal I, Aguilar I, Legarra A. Evaluation of the utility of diagonal elements of the genomic relationship matrix as a diagnostic tool to detect mislabelled genotyped animals in a broiler chicken population. J Anim Breed Genet. 2011;128: 386–393. doi: 10.1111/j.1439-0388.2011.00926.x 21906184
56. Marees AT, de Kluiver H, Stringer S, Vorspan F, Curis E, Marie-Claire C, et al. A tutorial on conducting genome-wide association studies: Quality control and statistical analysis. Int J Methods Psychiatr Res. 2018;27: e1608. doi: 10.1002/mpr.1608 29484742
57. Liu J, Shikano T, Leinonen T, Cano JM, Li M-H, Merilä J. Identification of Major and Minor QTL for Ecologically Important Morphological Traits in Three-Spined Sticklebacks (Gasterosteus aculeatus). G3: Genes|Genomes|Genetics. 2014;4: 595–604. doi: 10.1534/g3.114.010389 24531726
58. Marrs KA, Alfenito MR, Lloyd AM, Walbot V. A glutathione S-transferase involved in vacuolar transfer encoded by the maize gene Bronze-2. Nature. 1995;375: 397–400. doi: 10.1038/375397a0 7760932
59. Xu W, Dubos C, Lepiniec L. Transcriptional control of flavonoid biosynthesis by MYB-bHLH-WDR complexes. Trends Plant Sci. 2015;20: 176–185. doi: 10.1016/j.tplants.2014.12.001 25577424
60. Goodman CD, Casati P, Walbot V. A Multidrug Resistance–Associated Protein Involved in Anthocyanin Transport in Zea mays. Plant Cell. 2004;16: 1812–1826. doi: 10.1105/tpc.022574 15208386
61. Nagao A, Maeda M, Lim BP, Kobayashi H, Terao J. Inhibition of β-carotene-15,15’-dioxygenase activity by dietary flavonoids. J Nutr Biochem. 2000;11: 348–355. doi: 10.1016/s0955-2863(00)00090-5 11002132
62. Dia VP, Pangloli P, Jones L, McClure A, Patel A. Phytochemical concentrations and biological activities of: Sorghum bicolor alcoholic extracts. Food Funct. 2016;7: 3410–3420. doi: 10.1039/c6fo00757k 27406291
63. López-Contreras JJ, Zavala-García F, Urías-Orona V, Martínez-Ávila GCG, Rojas R, Niño-Medina G. Chromatic, phenolic and antioxidant properties of Sorghum bicolor genotypes. Not Bot Horti Agrobot Cluj-Napoca. 2015;43: 366–370. doi: 10.15835/nbha4329949
64. Dykes L, Rooney LW, Waniska RD, Rooney WL. Phenolic compounds and antioxidant activity of sorghum grains of varying genotypes. J Agric Food Chem. 2005;53: 6813–6818. doi: 10.1021/jf050419e 16104804
65. Ragaee S, Abdel-Aal ESM, Noaman M. Antioxidant activity and nutrient composition of selected cereals for food use. Food Chem. 2006;98: 32–38. doi: 10.1016/j.foodchem.2005.04.039
66. Awika JM, Rooney LW, Wu X, Prior RL, Cisneros-Zevallos L. Screening Methods to Measure Antioxidant Activity of Sorghum (Sorghum bicolor) and Sorghum Products. J Agric Food Chem. 2003;51: 6657–6662. doi: 10.1021/jf034790i 14582956
67. Kaur R, Soodan AS. Reproductive biology of Sorghum halepense (L.) Pers. (Poaceae; Panicoideae; Andropogoneae) in relation to invasibility. Flora Morphol Distrib Funct Ecol Plants. 2017;229: 32–49. doi: 10.1016/j.flora.2017.02.009
68. Yuan Y, Cairns JE, Babu R, Gowda M, Makumbi D, Magorokosho C, et al. Genome-wide association mapping and genomic prediction analyses reveal the genetic architecture of grain yield and flowering time under drought and heat stress conditions in maize. Front Plant Sci. 2019;9: 1919. doi: 10.3389/fpls.2018.01919 30761177
69. Diaz C, Saliba-Colombani V, Loudet O, Belluomo P, Moreau L, Daniel-Vedele F, et al. Leaf yellowing and anthocyanin accumulation are two genetically independent strategies in response to nitrogen limitation in Arabidopsis thaliana. Plant Cell Physiol. 2006;47: 74–83. doi: 10.1093/pcp/pci225 16284408
70. Rakshit S, Ganapathy KN, Visarada KBRS. Cytogenetics of Sorghum. The Sorghum Genome. 2016. pp. 47–75. doi: 10.1007/978-3-319-47789-3_3
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