Abstract
Wheat is an essential food crop and its high and stable yield is suffering from great challenges due to the limitations of current breeding technology and various stresses. Accelerating molecularly assisted stress-resistance breeding is critical. Through a meta-analysis of published loci in wheat over the last two decades, we selected 60 loci with main breeding objectives, high heritability, and reliable genotyping, such as stress resistance, yield, plant height, and resistance to spike germination. Then, using genotyping by target sequencing (GBTS) technology, we developed a liquid phase chip based on 101 functional or closely linked markers. The genotyping of 42 loci was confirmed in an extensive collection of Chinese wheat cultivars, indicating that the chip can be used in molecular-assisted selection (MAS) for target breeding goals. Besides, we can perform the preliminary parentage analysis with the genotype data. The most significant contribution of this work lies in translating a large number of molecular markers into a viable chip and providing reliable genotypes. Breeders can quickly screen germplasm resources, parental breeding materials, and intermediate materials for the presence of excellent allelic variants using the genotyping data by this chip, which is high throughput, convenient, reliable, and cost-efficient.
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Data availability
All data generated during the study are included in this published article and its supplement table.
Abbreviations
- GBTS:
-
Genotyping by target sequencing technology
- SNP:
-
Single nucleotide polymorphism
- RFLP:
-
Restriction fragment length polymorphisms
- PHS:
-
Pre-harvest sprouting
- MAS:
-
Marker-assisted selection
- QTL:
-
Quantitative trait loci
- MAF:
-
Minor allele frequency
- DS:
-
Disease severity
References
Allen AM, Winfield MO, Burridge AJ, Downie RC, Benbow HR, Barker GLA, Wilkinson PA, Coghill J, Waterfall C, Davassi A, Scopes G, Pirani A, Webster T, Brew F, Bloor C, Griffiths S, Bentley AR, Alda M, Jack P et al (2017) Characterization of a wheat breeders array suitable for high-throughput SNP genotyping of global accessions of hexaploid bread wheat (Triticum aestivum). Plant Biotechnol J 15:390–401. https://doi.org/10.1111/pbi.12635
Arjona JM, Royo C, Dreisigacker S, Ammar K, Villegas D (2018) Effect of Ppd-A1 and Ppd-B1 allelic variants on grain number and thousand kernel weight of durum wheat and their impact on final grain yield. Front Plant Sci 9:888. https://doi.org/10.3389/fpls.2018.00888
Baird NA, Etter PD, Atwood TS, Currey MC, Shiver AL, Lewis ZA, Selker EU, Cresko WA, Johnson EA, Fay JC (2008) Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS ONE 3:e3376. https://doi.org/10.1371/journal.pone.0003376
Bérard A, Le Paslier MC, Dardevet M, Exbrayat-Vinson F, Bonnin I, Cenci A, Haudry A, Brunel D, Ravel C (2009) High-throughput single nucleotide polymorphism genotyping in wheat (Triticum spp.). Plant Biotechnol J 7:364–374. https://doi.org/10.1111/j.1467-7652.2009.00404.x
Burridge AJ, Wilkinson PA, Winfield MO, Barker GLA, Allen AM, Coghill JA, Waterfall C, Edwards KJ (2018) Conversion of array-based single nucleotide polymorphic markers for use in targeted genotyping by sequencing in hexaploid wheat (Triticum aestivum). Plant Biotechnol J 16:867–876. https://doi.org/10.1111/pbi.12834
Cao P, Liang X, Zhao H, Feng B, Xu E, Wang L, Hu Y (2019) Identification of the quantitative trait loci controlling spike-related traits in hexaploid wheat (Triticum aestivum L.). Planta 250:1967–1981. https://doi.org/10.1007/s00425-019-03278-0
Cavanagh CR, Chao S, Wang S, Huang BE, Stephen S, Kiani S, Forrest K, Saintenac C, Brown-Guedira GL, Akhunova A, See D, Bai G, Pumphrey M, Tomar L, Wong D, Kong S, Reynolds M, Da Silva ML, Bockelman H et al (2013) Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars. Proc Natl Acad Sci U S A 110:8057–8062. https://doi.org/10.1073/pnas.1217133110
Chai L, Chen Z, Bian R, Zhai H, Cheng X, Peng H, Yao Y, Hu Z, Xin M, Guo W, Sun Q, Zhao A, Ni Z (2019) Dissection of two quantitative trait loci with pleiotropic effects on plant height and spike length linked in coupling phase on the short arm of chromosome 2D of common wheat (Triticum aestivum L.). Theor Appl Genet 132:1815–1831. https://doi.org/10.1007/s00122-019-03318-z
Chen S, Zhou Y, Chen Y, Gu J (2018) fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34:i884–i890. https://doi.org/10.1093/bioinformatics/bty560
Chen S, Rouse MN, Zhang W, Zhang X, Guo Y, Briggs J, Dubcovsky J (2020) Wheat gene Sr60 encodes a protein with two putative kinase domains that confers resistance to stem rust. The New phytologist 225:948–959
Collard BCY, Mackill DJ (2008) Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philosophical Transactions of the Royal Society B: Biological Sciences 363:557–572. https://doi.org/10.1098/rstb.2007.2170
Cui F, Zhang N, Fan X, Zhang W, Zhao C, Yang L, Pan R, Chen M, Han J, Zhao X, Ji J, Tong Y, Zhang H, Jia J, Zhao G, Li J (2017) Utilization of a wheat 660K SNP array-derived high-density genetic map for high-resolution mapping of a major QTL for kernel number. Sci Rep 7:3788. https://doi.org/10.1038/s41598-017-04028-6
Elshire RJ, Glaubitz JC, Sun Q, Poland JA, Kawamoto K, Buckler ES, Mitchell SE (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS ONE 6:e19379. https://doi.org/10.1371/journal.pone.0019379
Guo Z, Wang H, Tao J, Ren Y, Xu C, Wu K, Zou C, Zhang J, Xu Y (2019) Development of multiple SNP marker panels affordable to breeders through genotyping by target sequencing (GBTS) in maize. Mol Breeding 39:37. https://doi.org/10.1007/s11032-019-0940-4
Guo Z, Yang Q, Huang F, Zheng H, Sang Z, Xu Y, Zhang C, Wu K, Tao J, Prasanna BM, Olsen MS, Wang Y, Zhang J, Xu Y (2021) Development of high-resolution multiple-SNP arrays for genetic analyses and molecular breeding through genotyping by target sequencing and liquid chip. Plant Communications 2:100230. https://doi.org/10.1016/j.xplc.2021.100230
Kiseleva AA, Potokina EK, Salina EA (2017) Features of Ppd-B1 expression regulation and their impact on the flowering time of wheat near-isogenic lines. Bmc Plant Biol 17(Suppl 1):172. https://doi.org/10.1186/s12870-017-1126-z
Klymiuk V, Yaniv E, Huang L, Raats D, Fatiukha A, Chen S, Feng L, Frenkel Z, Krugman T, Lidzbarsky G, Chang W, Jääskeläinen MJ, Schudoma C, Paulin L, Laine P, Bariana H, Sela H, Saleem K, Sørensen CK et al (2018) Cloning of the wheat Yr15 resistance gene sheds light on the plant tandem kinase-pseudokinase family. Nat Commun 9:3735
Kolodziej MC, Singla J, Sánchez-Martín J, Zbinden H, Šimková H, Karafiátová M, Doležel J, Gronnier J, Poretti M, Glauser G, Zhu W, Köster P, Zipfel C, Wicker T, Krattinger SG, Keller B (2021) A membrane-bound ankyrin repeat protein confers race-specific leaf rust disease resistance in wheat. Nat Commun 12:956
Lee C, Cheon K, Shin Y, Oh H, Jeong Y, Jang H, Park Y, Kim K, Cho H, Won Y, Baek J, Cha Y, Kim S, Kim K, Ji H (2022) Development and application of a target capture sequencing SNP-genotyping platform in rice. Genes-Basel 13:794. https://doi.org/10.3390/genes13050794
Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–1760. https://doi.org/10.1093/bioinformatics/btp324
Li M, Dong L, Li B, Wang Z, Xie J, Qiu D, Li Y, Shi W, Yang L, Wu Q, Chen Y, Lu P, Guo G, Zhang H, Zhang P, Zhu K, Li Y, Zhang Y, Wang R et al (2020) A CNL protein in wild emmer wheat confers powdery mildew resistance. The New phytologist 228:1027–1037
Liu S, Wang X, Zhang Y, Jin Y, Xia Z, Xiang M, Huang S, Qiao L, Zheng W, Zeng Q, Wang Q, Yu R, Singh RP, Bhavani S, Kang Z, Han D, Wang C, Wu J (2022) Enhanced stripe rust resistance obtained by combining Yr30 with a widely dispersed, consistent QTL on chromosome arm 4BL. Theor Appl Genet 135:351–365. https://doi.org/10.1007/s00122-021-03970-4
McCombie WR, McPherson JD, Mardis ER (2019) Next-Generation Sequencing Technologies. Cold Spring Harb Perspect Med 9(11):a036798. https://doi.org/10.1101/cshperspect.a036798
McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA (2010) The genome analysis toolkit: a map reduce framework for analyzing next-generation DNA sequencing data. Genome Res 20:1297–1303. https://doi.org/10.1101/gr.107524.110
Muterko A, Kalendar R, Salina E (2016) Allelic variation at the VERNALIZATION-A1, VRN-B1, VRN-B3, and PHOTOPERIOD-A1 genes in cultivars of Triticum durum Desf. Planta 244:1253–1263. https://doi.org/10.1007/s00425-016-2584-5
Peterson R, Campbell A, Hannah A (1948) A diagrammatic scale for estimating rust intensity on leaves and stems of cereals. Can J Res 26:496–500
Rasheed A, Xia X (2019) From markers to genome-based breeding in wheat. Theor Appl Genet 132(3):767–784. https://doi.org/10.1007/s00122-019-03286-4
Rasheed A, Hao Y, Xia X, Khan A, Xu Y, Varshney RK, He Z (2017) Crop breeding chips and genotyping platforms: progress, challenges, and perspectives. Mol Plant 10:1047–1064. https://doi.org/10.1016/j.molp.2017.06.008
Ray DK, Ramankutty N, Mueller ND, West PC, Foley JA (2012) Recent patterns of crop yield growth and stagnation. Nat Commun 3:1293. https://doi.org/10.1038/ncomms2296
Ren T, Hu Y, Tang Y, Li C, Yan B, Ren Z, Tan F, Tang Z, Fu S, Li Z (2018) Utilization of a Wheat55K SNP array for mapping of major QTL for temporal expression of the tiller number. Front Plant Sci 9:333. https://doi.org/10.3389/fpls.2018.00333
Saghai-Maroof MA, Soliman KM, Jorgensen RA, Allard RW (1984) Ribosomal DNA spacer-length polymorphisms in barley: Mendelian inheritance, chromosomal location, and population dynamics. Proc Natl Acad Sci U S A 81:8014–8018
Shewry PR, Hey SJ (2015) The contribution of wheat to human diet and health. Food Energy Secur H 4:178–202
Shiferaw B, Smale M, Braun HJ, Duveiller E, Reynolds M, Muricho G (2013) Crops that feed the world 10. Past successes and future challenges to the role played by wheat in global food security. Food Security 5:291–317
Singh K, Batra R, Sharma S, Saripalli G, Gautam T, Singh R, Pal S, Malik P, Kumar M, Jan I, Singh S, Kumar D, Pundir S, Chaturvedi D, Verma A, Rani A, Kumar A, Sharma H, Chaudhary J et al (2021) WheatQTLdb: a QTL database for wheat. Mol Genet Genomics 296:1051–1056. https://doi.org/10.1007/s00438-021-01796-9
Somers DJ, Isaac P, Edwards K (2004) A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theor Appl Genet 109:1105–1114. https://doi.org/10.1007/s00122-004-1740-7
Su Z, Bernardo A, Tian B, Chen H, Wang S, Ma H, Cai S, Liu D, Zhang D, Li T, Trick H, St. Amand P, Yu J, Zhang Z, Bai G (2019) A deletion mutation in TaHRC confers Fhb1 resistance to Fusarium head blight in wheat. Nat Genet 51:1099–1105
Tamura K, Stecher G, Kumar S (2021) MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Molecular Biology and Evolution 38:3022–3027. https://doi.org/10.1093/molbev/msab120
Tanksley SD, NDYA (1989) RFLP Mapping in Plant Breeding: New Tools for an Old Science. Nature Biotechnology 7:257–264
Tilman D, Balzer C, Hill J, Befort BL (2011) Global food demand and the sustainable intensification of agriculture. Proc Natl Acad Sci U S A 108:20260–20264. https://doi.org/10.1073/pnas.1116437108
Varshney RK, Nayak SN, May GD, Jackson SA (2009) Next-generation sequencing technologies and their implications for crop genetics and breeding. Trends Biotechnol 27:522–530. https://doi.org/10.1016/j.tibtech.2009.05.006
Wallace JG, Rodgers-Melnick E, Buckler ES (2018) On the road to breeding 4.0: unraveling the good, the bad, and the boring of crop quantitative genomics. Annu Rev Genet 52:421–444. https://doi.org/10.1146/annurev-genet-120116-024846
Wang S, Wong D, Forrest K, Allen A, Chao S, Huang BE, Maccaferri M, Salvi S, Milner SG, Cattivelli L, Mastrangelo AM, Whan A, Stephen S, Barker G, Wieseke R, Plieske J, Lillemo M, Mather D, Appels R et al (2014) Characterization of polyploid wheat genomic diversity using a high-density 90000 single nucleotide polymorphism array. Plant Biotechnol J 12:787–796. https://doi.org/10.1111/pbi.12183
Wang H, Sun S, Ge W, Zhao L, Hou B, Wang K, Lyu Z, Chen L, Xu S, Guo J, Li M, Su P, Li X, Wang G, Bo C, Fang X, Zhuang W, Cheng X, Wu J et al (2020) Horizontal gene transfer of Fhb7 from fungus underliesFusarium head blight resistance in wheat. Science 368(6493)
Winfield MO, Allen AM, Burridge AJ, Barker GLA, Benbow HR, Wilkinson PA, Coghill J, Waterfall C, Davassi A, Scopes G, Pirani A, Webster T, Brew F, Bloor C, King J, West C, Griffiths S, King I, Bentley AR, Edwards KJ (2016) High-density SNP genotyping array for hexaploid wheat and its secondary and tertiary gene pool. Plant Biotechnol J 14:1195–1206. https://doi.org/10.1111/pbi.12485
Xiao J, Liu B, Yao Y, Guo Z, Jia H, Kong L, Zhang A, Ma W, Ni Z, Xu S, Lu F, Jiao Y, Yang W, Lin X, Sun S, Lu Z, Gao L, Zhao G, Cao S et al (2022) Wheat genomic study for genetic improvement of traits in China. Sci China Life Sci 65:1718–1775. https://doi.org/10.1007/s11427-022-2178-7
Xu D, Wen W, Fu L, Li F, Li J, Xie L, Xia X, Ni Z, He Z, Cao S (2019) Genetic dissection of a major QTL for kernel weight spanning the Rht-B1 locus in bread wheat. Theor Appl Genet 132:3191–3200. https://doi.org/10.1007/s00122-019-03418-w
Xu Y, Yang Q, Zheng H, Xu Y, Sang Z, Guo Z, Peng H, Zhang C, Lan H, Wang Y, Wu K, Tao J, Zhang J (2020) Genotyping by target sequencing (GBTS) and its applications. Scientia Agricultura Sinica 53(15):2983–3004. https://doi.org/10.3864/j.issn.0578-1752.2020.15.001
Xu Y, Wang B, Zhang J, Zhang J, Li J (2022) Enhancement of plant variety protection and regulation using molecular marker technology. Acta Agronomica Sinica 48:1853–1870. https://doi.org/10.3724/SP.J.1006.2022.23001
Zhang L, Zhao YL, Gao LF, Zhao GY, Zhou RH, Zhang BS, Jia JZ (2012) TaCKX6-D1, the ortholog of rice OsCKX2, is associated with grain weight in hexaploid wheat. New Phytol 195:574–584. https://doi.org/10.1111/j.1469-8137.2012.04194.x
Zhang Q, Men X, Hui C, Ge F, Ouyang F (2022) Wheat yield losses from pests and pathogens in China. Agriculture, Ecosystems & Environment 326:107821. https://doi.org/10.1016/j.agee.2021.107821
Acknowledgements
The authors thank Prof. Yunbi Xu, the Chinese Academy of Agricultural Sciences, and the International Maize and Wheat Improvement Center (CIMMYT) for valuable advice on this work.
Funding
This study was supported by the Key R&D Program of Shaanxi Province in China (2021ZDLNY0-01), the Key R&D Program of Qinghai Province in China (2022-NK-125), and the Key R&D Program of Yangling Seed Industry Innovation Center (Ylzy-xm-01).
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QZ and DH designed and conducted the experiments and analyzed the data. MX and QZ wrote the manuscript. MX, SL, YH, and YG assisted in analyzing the SNP array data. XW, MZ, WY, JW, QW, CL, WZ, and CW participated in greenhouse and field experiments. ZK conceived and directed the project and revised the manuscript.
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YH and YG are employees of Mol Breeding Biotechnology Co., Ltd.
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Xiang, M., Liu, S., Wang, X. et al. Development of breeder chip for gene detection and molecular-assisted selection by target sequencing in wheat. Mol Breeding 43, 13 (2023). https://doi.org/10.1007/s11032-023-01359-3
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DOI: https://doi.org/10.1007/s11032-023-01359-3