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Quick mapping and characterization of a co-located kernel length and thousand-kernel weight-related QTL in wheat

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Abstract

Key message

A co-located KL and TKW-related QTL with no negative effect on PH and AD was rapidly identified using BSA and wheat 660 K SNP array. Its effect was validated in a panel of 218 wheat accessions.

Abstract

Kernel length (KL) and thousand-kernel weight (TKW) of wheat (Triticum aestivum L.) contribute significantly to kernel yield. In the present study, a recombinant inbred line (RIL) population derived from the cross between the wheat line S849-8 with larger kernels and more spikelets per spike and the line SY95-71 was developed. Further, of both the bulked segregant analysis (BSA) and the wheat 660 K single nucleotide polymorphism (SNP) array were used to rapidly identify genomic regions for kernel-related traits from this RIL population. Kompetitive Allele Specific PCR markers were further developed in the SNP-enriched region on the 2D chromosome to construct a genetic map. Both QKL.sicau-SSY-2D for KL and QTKW.sicau-SSY-2D for TKW were identified at multiple environments on chromosome arm 2DL. These two QTLs explained 9.68–23.02% and 6.73–18.32% of the phenotypic variation, respectively. The effects of this co-located QTL were successfully verified in a natural population consisting of 218 Sichuan wheat accessions. Interestingly, the major QTL was significantly and positively correlated with spike length, but did not negatively affect spikelet number per spike (SNS), plant height, or anthesis date. These results indicated that it is possible to synchronously improve kernel weight and SNS by using this QTL. Additionally, several genes associated with kernel development and filling rate were predicted and sequenced in the QTL-containing physical intervals of reference genomes of ‘Chinese spring’ and Aegilops tauschii. Collectively, these results provide a QTL with great breeding potential and its linked markers which should be helpful for fine mapping and molecular breeding.

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Data availability

All data generated or analyzed during this study are included in this published article and its supplementary information files, and further inquiries can be directed to the corresponding author.

Abbreviations

KL:

Kernel length

TKW:

Thousand-kernel weight

BSA:

Bulked segregant analysis

SNP:

A single nucleotide polymorphism

RIL:

Recombinant inbred line

KASP:

Kompetitive Allele Specific PCR

BLUP:

Best linear unbiased prediction

QTL:

Quantitative trait loci

KW:

Kernel width

KT:

Kernel thickness

SWC:

Sichuan wheat cultivars

SWL:

Sichuan wheat landraces

References

  • Chastain TG, Ward KJ, Wysocki DJ (1995) Stand establishment responses of soft white winter wheat to seedbed residue and seed size. Crop Sci 35:213–218

    Article  Google Scholar 

  • Cui F, Ding A, Jun LI, Zhao C, Xingfeng LI, Feng D, Wang X, Wang L, Gao J, Wang H (2011) Wheat kernel dimensions: How do they contribute to kernel weight at an individual QTL level? J Genet 90:409–425

    Article  PubMed  Google Scholar 

  • Dinkar V, Jha SK, Mallick N, Niranjana M, Agarwal P, Sharma JB, Vinod (2020) Molecular mapping of a new recessive wheat leaf rust resistance gene originating from Triticum spelta. Sci Rep 10:22113

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Dong E, Liu C, Bai Y, Mei X, Zhao Z, Zhu S, Zhang J, Cai Y (2022) A new network containing MYB109-ZmCesA5 is involved in kernel development. Biochem Biophys Res Commun 602:15–20

    Article  CAS  PubMed  Google Scholar 

  • Dubcovsky J, Dvorak J (2007) Genome plasticity a key factor in the success of polyploid wheat under domestication. Science 316:1862–1866

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Feldman M, Levy AA, Fahima T, Korol A (2012) Genomic asymmetry in allopolyploid plants: wheat as a model. J Exp Bot 63:5045–5059

    Article  CAS  PubMed  Google Scholar 

  • Gegas VC, Nazari A, Griffiths S, Simmonds J, Fish L, Orford S, Sayers L, Doonan JH, Snape JW (2010) A genetic framework for grain size and shape variation in wheat. Plant Cell 22:1046–1056

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kong W, Wang L, Cao P, Li X, Ji J, Dong P, Yan X, Wang C, Wang H, Sun J (2020) Identification and genetic analysis of EMS-mutagenized wheat mutants conferring lesion-mimic premature aging. BMC Genet 21:88

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kosambi DD (1943) The estimation of map distances from recombination values. Ann Eugenics 12:172–175

    Article  Google Scholar 

  • Li Y, Xiong H, Guo H, Zhou C, Xie Y, Zhao L, Gu J, Zhao S, Ding Y, Liu L (2020) Identification of the vernalization gene VRN-B1 responsible for heading date variation by QTL mapping using a RIL population in wheat. BMC Plant Biol 20:331

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Li S, Wang L, Meng Y, Hao Y, Xu H, Hao M, Lan S, Zhang Y, Lv L, Zhang K, Peng X, Lan C, Li X, Zhang Y (2021) Dissection of genetic basis underpinning kernel weight-related traits in common wheat. Plants 10(4):713

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lin Y, Jiang X, Hu H, Zhou K, Wang Q, Yu S, Yang X, Wang Z, Wu F, Liu S, Li C, Deng M, Ma J, Chen G, Wei Y, Zheng Y, Liu Y (2021) QTL mapping for grain number per spikelet in wheat using a high-density genetic map. Crop J 9:1108–1114

    Article  Google Scholar 

  • Liu J, Tang H, Qu X, Liu H, Li C, Tu Y, Li S, Habib A, Mu Y, Dai S, Deng M, Jiang Q, Liu Y, Chen G, Wang J, Chen G, Li W, Jiang Y, Wei Y, Lan X, Zheng Y, Ma J (2020) A novel, major, and validated QTL for the effective tiller number located on chromosome arm 1BL in bread wheat. Plant Mol Biol 104:173–185

    Article  CAS  PubMed  Google Scholar 

  • Liu C, Song J, Liu S, Liu J, Xu D, Tian X, Bian Y, Dong Y, Wang F, Wang R, He Z, Xia X, Cao S (2021) Molecular mapping and characterization of QBpcaas-3BL for black point resistance in wheat (Triticum aestivum L.). Theor Appl Genet 134(10):3279–86

    Article  CAS  PubMed  Google Scholar 

  • Lizana XC, Riegel R, Gomez LD, Herrera J, Calderini DF (2010) Expansions expression is associated with grain size dynamics in wheat (Triticum aestivum L.). J Exp Bot 61:1147–1157

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Luo Q, Zheng Q, Hu P, Liu L, Yang G, Li H, Li B, Li Z (2021) Mapping QTL for agronomic traits under two levels of salt stress in a new constructed RIL wheat population. Theor Appl Genet 134:171–189

    Article  CAS  PubMed  Google Scholar 

  • Ma J, Zhang H, Li S, Zou Y, Li T, Liu J, Ding P, Mu Y, Tang H, Deng M, Liu Y, Jiang Q, Chen G, Kang H, Li W, Pu Z, Wei Y, Zheng Y, Lan X (2019) Identification of quantitative trait loci for kernel traits in a wheat cultivar Chuannong16. BMC Genet 20:77

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Ma S, Wang M, Wu J, Guo W, Chen Y, Li G, Wang Y, Shi W, Xia G, Fu D, Kang Z, Ni F (2021) WheatOmics: a platform combining multiple omics data to accelerate functional genomics studies in wheat. Mol Plant 14:1965–1968

    Article  CAS  PubMed  Google Scholar 

  • Mahmoud AF, Hassan MI, Amein KA (2015) Resistance potential of bread wheat genotypes against yellow rust disease under egyptian climate. Plant Pathol J 31:402–413

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mayer KF, Rogers J, Doleel J, Pozniak C, Praud S (2014) A chromosome-based draft sequence of the hexaploid bread wheat (Triticum aestivum) genome. Science 345:1251788

    Article  CAS  Google Scholar 

  • Michelmore RW, Paran I, Kesseli RV (1991) Identification of markers linked to disease-resistance genes by bulked segregant analysis: a rapid method to detect markers in specific genomic regions by using segregating populations. Proc Natl Acad Sci 88:9828–9832

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mohler V, Albrecht T, Castell A, Diethelm M, Schweizer G, Hartl L (2016) Considering causal genes in the genetic dissection of kernel traits in common wheat. J Appl Genet 57:467–476

    Article  CAS  PubMed  Google Scholar 

  • Okamoto Y, Nguyen AT, Yoshioka M, Iehisa JC, Takumi S (2013) Identification of quantitative trait loci controlling grain size and shape in the D genome of synthetic hexaploid wheat lines. Breed Sci 63:423–429

    Article  PubMed  PubMed Central  Google Scholar 

  • Ooijen Van JW (2004) MapQTL version 5.0, software for the mapping of quantitative trait loci in experimental populations. Wageningen, Kyazma BV

    Google Scholar 

  • Prashant R, Kadoo N, Desale C, Kore P, Dhaliwal HS, Chhuneja P, Gupta V (2012) Kernel morphometric traits in hexaploid wheat (Triticum aestivum L.) are modulated by intricate QTL × QTL and genotype × environment interactions. J Cereal Sci 56:432–439

    Article  CAS  Google Scholar 

  • Qu X, Liu J, Xie X, Xu Q, Tang H, Mu Y, Pu Z, Li Y, Ma J, Gao Y, Jiang Q, Liu Y, Chen G, Wang J, Qi P, Habib A, Wei Y, Zheng Y, Lan X, Ma J (2021) Genetic mapping and validation of loci for kernel-related traits in wheat (Triticum aestivum L.). Front Plant Sci 12:667493

    Article  PubMed  PubMed Central  Google Scholar 

  • Qureshi N, Bariana H, Kumran VV, Muruga S, Forrest KL, Hayden MJ, Bansal U (2018) A new leaf rust resistance gene Lr79 mapped in chromosome 3BL from the durum wheat landrace Aus26582. Theor Appl Genet 131:1091–1098

    Article  CAS  PubMed  Google Scholar 

  • Rasheed A, Xia X, Ogbonnaya F, Mahmood T, Zhang Z, Mujeeb-Kazi A, He Z (2014) Genome-wide association for grain morphology in synthetic hexaploid wheats using digital imaging analysis. BMC Plant Biol 14:128

    Article  PubMed  PubMed Central  Google Scholar 

  • Röder MS, Huang XQ, Börner A (2008) Fine mapping of the region on wheat chromosome 7D controlling grain weight. Funct Integr Genomics 8:79–86

    Article  PubMed  CAS  Google Scholar 

  • Russo MA, Ficco D, Laidò G, Marone D, Papa R, Blanco A, Gadaleta A, Vita PD, Mastrangelo AM (2014) A dense durum wheat × T. dicoccum linkage map based on SNP markers for the study of seed morphology. Mol Breeding 34:1579–1597

    Article  Google Scholar 

  • Simmonds J, Scott P, Brinton J, Mestre TC, Bush M, Del Blanco A, Dubcovsky J, Uauy C (2016) A splice acceptor site mutation in TaGW2-A1 increases thousand grain weight in tetraploid and hexaploid wheat through wider and longer grains. Theor Appl Genet 129:1099–1112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Slafer GA (2003) Genetic basis of yield as viewed from a crop physiologist’s perspective. Ann Appl Biol 142(2):117–128

    Article  Google Scholar 

  • Sun X-Y, Wu K, Zhao Y, Kong F-M, Han G-Z, Jiang H-M, Huang X-J, Li R-J, Wang H-G, Li S-S (2008) QTL analysis of kernel shape and weight using recombinant inbred lines in wheat. Euphytica 165:615

    Article  CAS  Google Scholar 

  • Sun C, Dong Z, Zhao L, Ren Y, Zhang N, Chen F (2020) The Wheat 660K SNP array demonstrates great potential for marker-assisted selection in polyploid wheat. Plant Biotechnol J 18:1354–1360

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Voorrips RE (2002) MapChart: software for the graphical presentation of linkage maps and QTLs. J Hered 93:77–78

    Article  CAS  PubMed  Google Scholar 

  • Winfield MO, Allen AM, Burridge AJ, Barker G, Edwards KJ (2016) High-density SNP genotyping array for hexaploid wheat and its secondary and tertiary gene pool. Plant Biotechnol J 14(5):1195–206

    Article  CAS  PubMed  Google Scholar 

  • Wu J, Wang Q, Xu L, Chen X, Li B, Mu J, Zeng Q, Huang L, Han D, Kang Z (2018) Combining single nucleotide polymorphism genotyping array with bulked segregant analysis to map a gene controlling adult plant resistance to stripe rust in wheat line 03031-1-5 H62. Phytopathology 108:103–113

    Article  CAS  PubMed  Google Scholar 

  • Xin F, Zhu T, Wei S, Han Y, Zhao Y, Zhang D, Ma L, Ding Q (2020) QTL mapping of kernel traits and validation of a major QTL for kernel length-width ratio using SNP and bulked segregant analysis in wheat. Sci Rep 10:25

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Yang H, Liu L, Wu K, Liu S, Liu X, Tian Y, Wang Y, Duan E, Lei J, Bao X, Chen R, Chen X, Ji Y, Zhang Y, Wang Y, Wan J (2021) Floury and shrunken endosperm 6 Encodes a glycosyltransferase and is essential for the development of rice endosperm. J Plant Biol 65(3):187–198

    Article  CAS  Google Scholar 

  • Ye X, Li J, Cheng Y, Yao F, Long L, Yu C, Wang Y, Wu Y, Li J, Wang J, Jiang Q, Li W, Ma J, Wei Y, Zheng Y, Chen G (2019) Genome-wide association study of resistance to stripe rust (Puccinia striiformis f. sp. tritici) in Sichuan wheat. BMC Plant Biol 19:147

    Article  PubMed  PubMed Central  Google Scholar 

  • Zeng Q, Wu J, Liu S, Huang S, Wang Q, Mu J, Yu S, Han D, Kang Z (2019) A major QTL co-localized on chromosome 6BL and its epistatic interaction for enhanced wheat stripe rust resistance. Theor Appl Genet 132:1409–1424

    Article  CAS  PubMed  Google Scholar 

  • Zhang G, Wang Y, Guo Y, Zhao Y, Kong F, Li S (2015) Characterization and mapping of QTLs on chromosome 2D for grain size and yield traits using a mutant line induced by EMS in wheat. Crop J 3:135–144

    Article  CAS  Google Scholar 

  • Zhao G, Zou C, Li K, Wang K, Li T, Gao L, Zhang X, Wang H, Yang Z, Liu X, Jiang W, Mao L, Kong X, Jiao Y, Jia J (2017) The Aegilops tauschii genome reveals multiple impacts of transposons. Nat Plants 3:946–955

    Article  CAS  PubMed  Google Scholar 

  • Zhao YF, Peng T, Sun HZ, Teotia S, Wen HL, Du YX, Zhang J, Li JZ, Tang GL, Xue HW, Zhao QZ (2019) miR1432-OsACOT (Acyl-CoA thioesterase) module determines grain yield via enhancing grain filling rate in rice. Plant Biotechnol J 17:712–723

    Article  CAS  PubMed  Google Scholar 

  • Zheng X, Wen X, Qiao L, Zhao J, Zhang X, Li X, Zhang S, Yang Z, Chang Z, Chen J, Zheng J (2019) A novel QTL QTrl.saw-2D.2 associated with the total root length identified by linkage and association analyses in wheat (Triticum aestivum L.). Planta 250:129–143

    Article  CAS  PubMed  Google Scholar 

  • Zhou X, Jian MA, Wei L, Jiang Y, Min S, Yang Y, Jiang Q, Liu Y, Chen G, Wei Y (2016) QTL mapping for kernel morphology traits of tibetan semi-wild wheat (in Chinese). Journal of Triticeae Crops 36:27–35

    CAS  Google Scholar 

  • Zhou C-y, Xiong H-c, Li Y-t, Guo H-j, Xie Y-d, Zhao L-s, Gu J-y, Zhao S-r, Ding Y-p, Song X-y, Liu L (2020) Genetic analysis and QTL mapping of a novel reduced height gene in common wheat (Triticum aestivum L.). J Integr Agr 19:1721–1730

    Article  CAS  Google Scholar 

  • Zhu T, Wang L, Rimbert H, Rodriguez JC, Deal KR, De Oliveira R, Choulet F, Keeble-Gagnère G, Tibbits J, Rogers J (2021) Optical maps refine the bread wheat Triticum aestivum cv. Chinese Spring Genome Assembly Plant J 107:303–314

    CAS  PubMed  Google Scholar 

  • Zou C, Wang P, Xu Y (2016) Bulked sample analysis in genetics, genomics and crop improvement. Plant Biotechnol J 14:1941–1955

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank the anonymous referees for critical reading and revising this manuscript.

Funding

This work is supported by the National Natural Science Foundation of China (31970243 and 31971937), the Key Research and Development Program of Sichuan Province (2022ZDZX0014), the International Science and Technology Cooperation and Exchanges Program of Science and Technology Department of Sichuan Province (2022YFH0053 and 2021YFH0083), and the Applied Basic Research Programs of Science and Technology Department of Sichuan Province (2021YJ0503 and 2022NSFSC1729).

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  1. Xiangru Qu and Cong Li contributed equally to this paper.

Authors and Affiliations

  1. State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Chengdu, 611130, China

    Qiang Xu, Qiantao Jiang, Guoyue Chen, Pengfei Qi, Yunfeng Jiang, Yuming Wei & Jian Ma

  2. Triticeae Research Institute, Sichuan Agricultural University, Chengdu, 611130, China

    Xiangru Qu, Cong Li, Hang Liu, Jiajun Liu, Wei Luo, Qiang Xu, Huaping Tang, Yang Mu, Mei Deng, Qiantao Jiang, Guoyue Chen, Pengfei Qi, Yunfeng Jiang, Yuming Wei, Youliang Zheng, Xiujin Lan & Jian Ma

  3. College of Agronomy, Sichuan Agricultural University, Chengdu, 611130, China

    Zhien Pu

  4. College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China

    Jun Ma

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  1. Xiangru Qu
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Contributions

XRQ finished the study and wrote this manuscript. CL participated in field work and analyzed data. HL, JJL, and WL helped phenotype measurement and data analysis. QX and HPT did field work and data analysis. YM, MD, ZEP, and JunM collected and analyzed data. QTJ, GYC, PFQ, and YFJ helped with data analysis. YMW revised the manuscript. YLZ and XJL discussed results and revised the manuscript. JianM designed the experiments, guided the entire study, participated in data analysis, wrote, and extensively revised this manuscript. All authors participated in the research and approved the final manuscript.

Corresponding author

Correspondence to Jian Ma.

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All authors declare that there is no conflict of interest.

Ethical approval

All experiments and data analyses were conducted in Sichuan. All authors contributed to the study and approved the final version for submission. The manuscript has not been submitted to any other journal.

Additional information

Communicated by Philomin Juliana.

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Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (XLSX 1169 KB)

Schematic diagram of construction mixed pools (TIF 1513 KB)

122_2022_4154_MOESM3_ESM.tif

Frequency distributions for kernel length (KL), kernel width (KW), kernel thickness (KT), thousand-kernel weight (TKW), kernel length–width ratio (LWR), kernel size (KS), and factor form density (FFD) in different environments (TIF 2053 KB)

LOD value of major QTL QKL.sicau-SSY-2D and QTKW.sicau-SSY-2D (TIF 1317 KB)

Expression analysis of predictive genes in the interval of QKL.sicau-SSY-2D and QTKW.sicau-SSY-2D (TIF 1407 KB)

Gene sequence analysis of TraesCS2D03G0920800 (TIF 15419 KB)

Gene sequence analysis of TraesCS2D03G0923000 (TIF 15093 KB)

Gene sequence analysis of TraesCS2D03G0919600 (TIF 20093 KB)

Gene sequence analysis of TraesCS2D03G0923000 (TIF 18550 KB)

122_2022_4154_MOESM10_ESM.tif

Analysis of the effect of QKL.sicau-SSY-2D/QTKW.sicau-SSY-2D on agronomic traits. (A) Anthesis date (AD); (B) Plant height (PH); (C) Spikelet number per spike (SNS); (D) Productive tiller number (PTN); (E) Spike length (SL). ‘+’ and ‘-’ represent homozygous lines carrying ‘S849-8’ and ‘SY95-71’ alleles, respectively. **Significance at the 0.01 probability level. Significant difference was detected between the two groups in AD, PH, SNS and PTN. Note: PH: 2021WJ data; PH, SNS, PTN and SL: BLUP data (TIF 980 KB)

Protein sequences analysis of TraesCS2D03G0919600 and TraesCS2D03G0923000 (TIF 12150 KB)

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Qu, X., Li, C., Liu, H. et al. Quick mapping and characterization of a co-located kernel length and thousand-kernel weight-related QTL in wheat. Theor Appl Genet 135, 2849–2860 (2022). https://doi.org/10.1007/s00122-022-04154-4

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