Advertisement

Theoretical and Applied Genetics

, Volume 133, Issue 1, pp 149–162 | Cite as

Dissection of genetic factors underlying grain size and fine mapping of QTgw.cau-7D in common wheat (Triticum aestivum L.)

  • Zhaoyan Chen
  • Xuejiao Cheng
  • Lingling Chai
  • Zhihui Wang
  • Ruolin Bian
  • Jiang Li
  • Aiju Zhao
  • Mingming Xin
  • Weilong Guo
  • Zhaorong Hu
  • Huiru Peng
  • Yingyin Yao
  • Qixin Sun
  • Zhongfu NiEmail author
Original Article
  • 507 Downloads

Abstract

Key message

Thirty environmentally stable QTL controlling grain size and/or plant height were identified, among which QTgw.cau-7D was delimited into the physical interval of approximately 4.4 Mb.

Abstract

Grain size and plant height (PHT) are important agronomic traits in wheat breeding. To dissect the genetic basis of these traits, we conducted a quantitative trait locus (QTL) analysis using recombinant inbred lines (RILs). In total, 30 environmentally stable QTL for thousand grain weight (TGW), grain length (GL), grain width (GW) and PHT were detected. Notably, one major pleiotropic QTL on chromosome arm 3DS explained the highest phenotypic variance for TGW, GL and PHT, and two stable QTL (QGw.cau-4B and QGw.cau-7D) on chromosome arms 4BS and 7DS contributed greater effects for GW. Furthermore, the stable QTL controlling grain size (QTgw.cau-7D and QGw.cau-7D) were delimited into the physical interval of approximately 4.4 Mb harboring 56 annotated genes. The elite NILs of QTgw.cau-7D increased TGW by 12.79–21.75% and GW by 4.10–8.47% across all three environments. Collectively, these results provide further insight into the genetic basis of TGW, GL, GW and PHT, and the fine-mapped QTgw.cau-7D will be an attractive target for positional cloning and marker-assisted selection in wheat breeding programs.

Notes

Acknowledgements

This work was financially supported by the National Key Research and Development Program of China (Grant No. 2016YFD0100801 and 2017YFD0101000).

Authors contribution statement

ZN conceived the project; XC developed the RIL population; ZC and JL constructed the linkage map. ZC, XC, ZW, JL and RB collected data of RIL population under six environments; ZC and ZW developed markers of the QTL region of interest; ZC developed the near isogenic lines; ZC and LC performed phenotyping of the near isogenic lines; AZ, MX, WG, ZH, HP, YY and QS assisted in revising the manuscript; ZC and ZN analyzed experimental results and wrote the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

122_2019_3447_MOESM1_ESM.xlsx (2.4 mb)
Supplementary material 1 (XLSX 2486 kb)
122_2019_3447_MOESM2_ESM.tif (247 kb)
Fig. S1Histograms of the HS2/4332 recombinant inbred population for TGW, GL, GW and PHT based on the mean values. The Y-axis represents the density (the radio of frequency to group distance) of each trait. P < 0.05 indicates a significant departure from the normal distribution (Shapiro–Wilk test) (TIFF 247 kb)
122_2019_3447_MOESM3_ESM.tif (347 kb)
Fig. S2Illustration of 21 wheat chromosomes in the HS2/4332 RIL population. A centimorgan (cM) scale is shown on the left. The black lines on individual chromosomes represent SNP or SSR markers, the marker names are not shown (TIFF 347 kb)
122_2019_3447_MOESM4_ESM.tif (539 kb)
Fig. S3Comparison of TGW and GW between lines with HS2 allele and lines with 4332 allele in the RIL population of six environments and BLUP, when excluding the influence of the major QTL QTgw.cau-3D1. Significant differences are indicated by * (P < 0.05), ** (P < 0.01), **** (P < 0.0001) (Student’s t test) (TIFF 539 kb)

References

  1. Allen GC, Flores-Vergara MA, Krasynanski S, Kumar S, Thompson WF (2006) A modified protocol for rapid DNA isolation from plant tissues using cetyltrimethylammonium bromide. Nat Protoc 1:2320–2325.  https://doi.org/10.1038/nprot.2006.384 CrossRefPubMedGoogle Scholar
  2. Basten CJ, Weir BS, Zeng Z-B (1997) QTL cartographer: a reference manual and tutorial for QTL mapping. Department of Statistics, North Carolina State University, RaleighGoogle Scholar
  3. Borrill P, Ramirez-Gonzalez R, Uauy C (2016) expVIP: a customizable RNA-seq data analysis and visualization platform. Plant Physiol 170:2172–2186.  https://doi.org/10.1104/pp.15.01667 CrossRefPubMedPubMedCentralGoogle Scholar
  4. Brinton J, Simmonds J, Minter F, Leverington-Waite M, Snape J, Uauy C (2017) Increased pericarp cell length underlies a major quantitative trait locus for grain weight in hexaploid wheat. New Phytol 215:1026–1038.  https://doi.org/10.1111/nph.14624 CrossRefPubMedGoogle Scholar
  5. Cabral AL, Jordan MC, Larson G, Somers DJ, Humphreys DG, McCartney CA (2018) Relationship between QTL for grain shape, grain weight, test weight, milling yield, and plant height in the spring wheat cross RL4452/‘AC Domain’. PLoS ONE 13:e0190681CrossRefGoogle Scholar
  6. Carter AH, Garland-Campbell K, Morris CF, Kidwell KK (2012) Chromosomes 3B and 4D are associated with several milling and baking quality traits in a soft white spring wheat (Triticum aestivum L.) population. Theor Appl Genet 124:1079–1096.  https://doi.org/10.1007/s00122-011-1770-x CrossRefPubMedGoogle Scholar
  7. 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 (2018) 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 131:2621–2637.  https://doi.org/10.1007/s00122-018-3177-4 CrossRefPubMedGoogle Scholar
  8. Chen J, Chen G, Li Q, Zhang H, Shi C, Sun C, Deng Z, Liu K, Gu Z, Tian J (2014) Construction of genetic map using genotyping chips and QTL analysis of grain weight. Sci Agric Sin 47:4769–4779.  https://doi.org/10.3864/j.issn.0578-1752.2014.24.001 CrossRefGoogle Scholar
  9. Chen WG, Sun DZ, Yan X, Li RZ, Wang SG, Shi YG, Jing RL (2019) QTL analysis of wheat kernel traits, and genetic effects of qKW-6A on kernel width. Euphytica 215:11.  https://doi.org/10.1007/s10681-018-2333-x CrossRefGoogle Scholar
  10. Cheng X, Chai L, Chen Z, Xu L, Zhai H, Zhao A, Peng H, Yao Y, You M, Sun Q, Ni Z (2015) Identification and characterization of a high kernel weight mutant induced by gamma radiation in wheat (Triticum aestivum L.). BMC Genet 16:127.  https://doi.org/10.1186/s12863-015-0285-x CrossRefPubMedPubMedCentralGoogle Scholar
  11. Cheng R, Kong Z, Zhang L, Xie Q, Jia H, Yu D, Huang Y, Ma Z (2017) Mapping QTLs controlling kernel dimensions in a wheat inter-varietal RIL mapping population. Theor Appl Genet 130:1405–1414.  https://doi.org/10.1007/s00122-017-2896-2 CrossRefPubMedGoogle Scholar
  12. Cui F, Zhao C, Ding A, Li J, Wang L, Li X, Bao Y, Li J, Wang H (2014) Construction of an integrative linkage map and QTL mapping of grain yield-related traits using three related wheat RIL populations. Theor Appl Genet 127:659–675.  https://doi.org/10.1007/s00122-013-2249-8 CrossRefPubMedGoogle Scholar
  13. Cui F, Fan X, Chen M, Zhang N, Zhao C, Zhang W, Han J, Ji J, Zhao X, Yang L, Zhao Z, Tong Y, Wang T, Li J (2016) QTL detection for wheat kernel size and quality and the responses of these traits to low nitrogen stress. Theor Appl Genet 129:469–484.  https://doi.org/10.1007/s00122-015-2641-7 CrossRefPubMedGoogle Scholar
  14. Deng Z, Cui Y, Han Q, Fang W, Li J, Tian J (2017) Discovery of consistent QTLs of wheat spike-related traits under nitrogen treatment at different development stages. Front Plant Sci 8:2120.  https://doi.org/10.3389/fpls.2017.02120 CrossRefPubMedPubMedCentralGoogle Scholar
  15. Dong LL, Wang FM, Liu T, Dong ZY, Li AL, Jing RL, Mao L, Li YW, Liu X, Zhang KP, Wang DW (2014) Natural variation of TaGASR7-A1 affects grain length in common wheat under multiple cultivation conditions. Mol Breeding 34:937–947.  https://doi.org/10.1007/s11032-014-0087-2 CrossRefGoogle Scholar
  16. Dong H, Yan S, Liu J, Liu P, Sun J (2019) TaCOLD1 defines a new regulator of plant height in bread wheat. Plant Biotechnol J 17:687–699.  https://doi.org/10.1111/pbi.13008 CrossRefPubMedGoogle Scholar
  17. Duan P, Rao Y, Zeng D, Yang Y, Xu R, Zhang B, Dong G, Qian Q, Li Y (2014) SMALL GRAIN 1, which encodes a mitogen-activated protein kinase kinase 4, influences grain size in rice. Plant J 77:547–557.  https://doi.org/10.1111/tpj.12405 CrossRefPubMedGoogle Scholar
  18. Eriksen L, Borum F, Jahoor A (2003) Inheritance and localisation of resistance to Mycosphaerella graminicola causing septoria tritici blotch and plant height in the wheat (Triticum aestivum L.) genome with DNA markers. Theor Appl Genet 107:515–527.  https://doi.org/10.1007/s00122-003-1276-2 CrossRefPubMedGoogle Scholar
  19. Flintham JE, Borner A, Worland AJ, Gale MD (1997) Optimizing wheat grain yield: effects of Rht (gibberellin-insensitive) dwarfing genes. J Agric Sci 128:11–25.  https://doi.org/10.1017/S0021859696003942 CrossRefGoogle Scholar
  20. 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.  https://doi.org/10.1105/tpc.110.074153 CrossRefPubMedPubMedCentralGoogle Scholar
  21. Guan P, Lu L, Jia L, Kabir MR, Zhang J, Lan T, Zhao Y, Xin M, Hu Z, Yao Y, Ni Z, Sun Q, Peng H (2018) Global QTL analysis identifies genomic regions on chromosomes 4A and 4B harboring stable loci for yield-related traits across different environments in wheat (Triticum aestivum L.). Front Plant Sci 9:529.  https://doi.org/10.3389/fpls.2018.00529 CrossRefPubMedPubMedCentralGoogle Scholar
  22. Guan PF, Di N, Mu Q, Shen XY, Wang YF, Wang XB, Yu KH, Song WJ, Chen YM, Xin MM, Hu ZR, Guo WL, Yao YY, Ni ZF, Sun QX, Peng HR (2019) Use of near-isogenic lines to precisely map and validate a major QTL for grain weight on chromosome 4AL in bread wheat (Triticum aestivum L.). Theor Appl Genet 132:2367–2379.  https://doi.org/10.1007/s00122-019-03359-4 CrossRefPubMedGoogle Scholar
  23. Guo T, Chen K, Dong NQ, Shi CL, Ye WW, Gao JP, Shan JX, Lin HX (2018) GRAIN SIZE AND NUMBER1 negatively regulates the OsMKKK10-OsMKK4-OsMPK6 cascade to coordinate the trade-off between grain number per panicle and grain size in rice. Plant Cell 30:871–888.  https://doi.org/10.1105/tpc.17.00959 CrossRefPubMedPubMedCentralGoogle Scholar
  24. Hanif M, Gao F, Liu J, Wen W, Zhang Y, Rasheed A, Xia X, He Z, Cao S (2015) TaTGW6-A1, an ortholog of rice TGW6, is associated with grain weight and yield in bread wheat. Mol Breeding 36:1.  https://doi.org/10.1007/s11032-015-0425-z CrossRefGoogle Scholar
  25. Huang XQ, Coster H, Ganal MW, Roder MS (2003) Advanced backcross QTL analysis for the identification of quantitative trait loci alleles from wild relatives of wheat (Triticum aestivum L.). Theor Appl Genet 106:1379–1389.  https://doi.org/10.1007/s00122-002-1179-7 CrossRefPubMedGoogle Scholar
  26. Huang Y, Kong Z, Wu X, Cheng R, Yu D, Ma Z (2015) Characterization of three wheat grain weight QTLs that differentially affect kernel dimensions. Theor Appl Genet 128:2437–2445.  https://doi.org/10.1007/s00122-015-2598-6 CrossRefPubMedGoogle Scholar
  27. International Wheat Genome Sequencing C (2014) A chromosome-based draft sequence of the hexaploid bread wheat (Triticum aestivum) genome. Science 345:1251788.  https://doi.org/10.1126/science.1251788 CrossRefGoogle Scholar
  28. International Wheat Genome Sequencing C (2018) Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science.  https://doi.org/10.1126/science.aar7191 CrossRefGoogle Scholar
  29. Jiang Y, Jiang Q, Hao C, Hou J, Wang L, Zhang H, Zhang S, Chen X, Zhang X (2015) A yield-associated gene TaCWI, in wheat: its function, selection and evolution in global breeding revealed by haplotype analysis. Theor Appl Genet 128:131–143.  https://doi.org/10.1007/s00122-014-2417-5 CrossRefPubMedGoogle Scholar
  30. Jobson EM, Martin JM, Schneider TM, Giroux MJ (2018) The impact of the Rht-B1b, Rht-D1b, and Rht-8 wheat semi-dwarfing genes on flour milling, baking, and micronutrients. Cereal Chem 95:770–778.  https://doi.org/10.1002/cche.10091 CrossRefGoogle Scholar
  31. Kato K, Miura H, Sawada S (2000) Mapping QTLs controlling grain yield and its components on chromosome 5A of wheat. Theor Appl Genet 101:1114–1121.  https://doi.org/10.1007/s001220051587 CrossRefGoogle Scholar
  32. Korzun V, Roder MS, Ganal MW, Worland AJ, Law CN (1998) Genetic analysis of the dwarfing gene (Rht8) in wheat. Part I. Molecular mapping of Rht8 on the short arm of chromosome 2D of bread wheat (Triticum aestivum L.). Theor Appl Genet 96:1104–1109.  https://doi.org/10.1007/s001220050845 CrossRefGoogle Scholar
  33. Kosambi DD (1943) The estimation of map distances from recombination values. Ann Eugenic 12:172–175.  https://doi.org/10.1111/j.1469-1809.1943.tb02321.x CrossRefGoogle Scholar
  34. Kuchel H, Williams KJ, Langridge P, Eagles HA, Jefferies SP (2007) Genetic dissection of grain yield in bread wheat. I. QTL analysis. Theor Appl Genet 115:1029–1041.  https://doi.org/10.1007/s00122-007-0629-7 CrossRefPubMedGoogle Scholar
  35. Kumar A, Mantovani EE, Seetan R, Soltani A, Echeverry-Solarte M, Jain S, Simsek S, Doehlert D, Alamri MS, Elias EM, Kianian SF, Mergoum M (2016) Dissection of genetic factors underlying wheat kernel shape and size in an elite × nonadapted cross using a high density SNP linkage map. Plant Genome.  https://doi.org/10.3835/plantgenome2015.09.0081 CrossRefPubMedGoogle Scholar
  36. Kumari S, Jaiswal V, Mishra VK, Paliwal R, Balyan HS, Gupta PK (2018) QTL mapping for some grain traits in bread wheat (Triticum aestivum L.). Physiol Mol Biol Pla 24:909–920.  https://doi.org/10.1007/s12298-018-0552-1 CrossRefGoogle Scholar
  37. Li N, Li Y (2016) Signaling pathways of seed size control in plants. Curr Opin Plant Biol 33:23–32.  https://doi.org/10.1016/j.pbi.2016.05.008 CrossRefPubMedGoogle Scholar
  38. Li Q, Wan JM (2005) SSRHunter: development of a local searching software for SSR sites. Yi Chuan 27:808–810PubMedGoogle Scholar
  39. Li W, Yang B (2017) Translational genomics of grain size regulation in wheat. Theor Appl Genet 130:1765–1771.  https://doi.org/10.1007/s00122-017-2953-x CrossRefPubMedGoogle Scholar
  40. Liu G, Jia L, Lu L, Qin D, Zhang J, Guan P, Ni Z, Yao Y, Sun Q, Peng H (2014) Mapping QTLs of yield-related traits using RIL population derived from common wheat and Tibetan semi-wild wheat. Theor Appl Genet 127:2415–2432.  https://doi.org/10.1007/s00122-014-2387-7 CrossRefPubMedGoogle Scholar
  41. Liu S, Hua L, Dong S, Chen H, Zhu X, Jiang J, Zhang F, Li Y, Fang X, Chen F (2015) OsMAPK6, a mitogen-activated protein kinase, influences rice grain size and biomass production. Plant J 84:672–681.  https://doi.org/10.1111/tpj.13025 CrossRefPubMedGoogle Scholar
  42. Liu N, Liu J, Li W, Pan Q, Liu J, Yang X, Yan J, Xiao Y (2018) Intraspecific variation of residual heterozygosity and its utility for quantitative genetic studies in maize. BMC Plant Biol 18:66.  https://doi.org/10.1186/s12870-018-1287-4 CrossRefPubMedPubMedCentralGoogle Scholar
  43. Ma M, Wang Q, Li Z, Cheng H, Li Z, Liu X, Song W, Appels R, Zhao H (2015) Expression of TaCYP78A3, a gene encoding cytochrome P450 CYP78A3 protein in wheat (Triticum aestivum L.), affects seed size. Plant J 83:312–325.  https://doi.org/10.1111/tpj.12896 CrossRefPubMedGoogle Scholar
  44. Ma L, Li T, Hao C, Wang Y, Chen X, Zhang X (2016) TaGS5-3A, a grain size gene selected during wheat improvement for larger kernel and yield. Plant Biotechnol J 14:1269–1280.  https://doi.org/10.1111/pbi.12492 CrossRefPubMedGoogle Scholar
  45. Marklund S, Chaudhary R, Marklund L, Sandberg K, Andersson L (2009) Extensive mtDNA diversity in horses revealed by PCR-SSCP analysis. Anim Genet 26:193–196.  https://doi.org/10.1111/j.1365-2052.1995.tb03162.x CrossRefGoogle Scholar
  46. McCartney C, Somers D, Humphreys D, Lukow O, Ames N, Noll J, Cloutier S, McCallum B (2005) Mapping quantitative trait loci controlling agronomic traits in the spring wheat cross RL4452 × ’AC Domain’. Genome 48:870–883CrossRefGoogle Scholar
  47. McIntosh RA, Dubcovsky J, Rogers WJ, Morris C, Xia XC (2017) Catalogue of gene symbols for wheat: 2017 supplementGoogle Scholar
  48. Mo Y, Vanzetti LS, Hale I, Spagnolo EJ, Guidobaldi F, Al-Oboudi J, Odle N, Pearce S, Helguera M, Dubcovsky J (2018) Identification and characterization of Rht25, a locus on chromosome arm 6AS affecting wheat plant height, heading time, and spike development. Theor Appl Genet 131:2021–2035.  https://doi.org/10.1007/s00122-018-3130-6 CrossRefPubMedGoogle Scholar
  49. Nadolska-Orczyk A, Rajchel IK, Orczyk W, Gasparis S (2017) Major genes determining yield-related traits in wheat and barley. Theor Appl Genet 130:1081–1098.  https://doi.org/10.1007/s00122-017-2880-x CrossRefPubMedPubMedCentralGoogle Scholar
  50. Peng J, Richards DE, Hartley NM, Murphy GP, Devos KM, Flintham JE, Beales J, Fish LJ, Worland AJ, Pelica F, Sudhakar D, Christou P, Snape JW, Gale MD, Harberd NP (1999) ‘Green revolution’ genes encode mutant gibberellin response modulators. Nature 400:256–261.  https://doi.org/10.1038/22307 CrossRefPubMedGoogle Scholar
  51. Quarrie S, Pekic Quarrie S, Radosevic R, Rancic D, Kaminska A, Barnes JD, Leverington M, Ceoloni C, Dodig D (2006) Dissecting a wheat QTL for yield present in a range of environments: from the QTL to candidate genes. J Exp Bot 57:2627–2637.  https://doi.org/10.1093/jxb/erl026 CrossRefPubMedGoogle Scholar
  52. Raihan MS, Liu J, Huang J, Guo H, Pan Q, Yan J (2016) Multi-environment QTL analysis of grain morphology traits and fine mapping of a kernel-width QTL in Zheng58 x SK maize population. Theor Appl Genet 129:1465–1477.  https://doi.org/10.1007/s00122-016-2717-z CrossRefPubMedGoogle Scholar
  53. Ramirez-Gonzalez RH, Borrill P, Lang D, Harrington SA, Brinton J, Venturini L, Davey M, Jacobs J, van Ex F, Pasha A, Khedikar Y, Robinson SJ, Cory AT, Florio T, Concia L, Juery C, Schoonbeek H, Steuernagel B, Xiang D, Ridout CJ, Chalhoub B, Mayer KFX, Benhamed M, Latrasse D, Bendahmane A, International Wheat Genome Sequencing C, Wulff BBH, Appels R, Tiwari V, Datla R, Choulet F, Pozniak CJ, Provart NJ, Sharpe AG, Paux E, Spannagl M, Brautigam A, Uauy C (2018) The transcriptional landscape of polyploid wheat. Science 361:662.  https://doi.org/10.1126/science.aar6089 CrossRefGoogle Scholar
  54. Ramya P, Chaubal A, Kulkarni K, Gupta L, Kadoo N, Dhaliwal HS, Chhuneja P, Lagu M, Gupta V (2010) QTL mapping of 1000-kernel weight, kernel length, and kernel width in bread wheat (Triticum aestivum L.). J Appl Genet 51:421–429CrossRefGoogle Scholar
  55. Roder MS, Huang XQ, Borner A (2008) Fine mapping of the region on wheat chromosome 7D controlling grain weight. Funct Integr Genomics 8:79–86.  https://doi.org/10.1007/s10142-007-0053-8 CrossRefPubMedGoogle Scholar
  56. Simmonds J, Scott P, Leverington-Waite M, Turner AS, Brinton J, Korzun V, Snape J, Uauy C (2014) Identification and independent validation of a stable yield and thousand grain weight QTL on chromosome 6A of hexaploid wheat (Triticum aestivum L.). BMC Plant Biol 14:191.  https://doi.org/10.1186/s12870-014-0191-9 CrossRefPubMedPubMedCentralGoogle Scholar
  57. 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.  https://doi.org/10.1007/s00122-016-2686-2 CrossRefPubMedPubMedCentralGoogle Scholar
  58. Song XJ, Huang W, Shi M, Zhu MZ, Lin HX (2007) A QTL for rice grain width and weight encodes a previously unknown RING-type E3 ubiquitin ligase. Nat Genet 39:623–630.  https://doi.org/10.1038/ng2014 CrossRefPubMedGoogle Scholar
  59. Su Q, Zhang X, Zhang W, Zhang N, Song L, Liu L, Xue X, Liu G, Liu J, Meng D, Zhi L, Ji J, Zhao X, Yang C, Tong Y, Liu Z, Li J (2018) QTL detection for kernel size and weight in bread wheat (Triticum aestivum L.) using a high-density SNP and SSR-based linkage map. Front Plant Sci 9:1484.  https://doi.org/10.3389/fpls.2018.01484 CrossRefPubMedPubMedCentralGoogle Scholar
  60. Sukumaran S, Lopes M, Dreisigacker S, Reynolds M (2018) Correction to: genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number. Theor Appl Genet 131:999.  https://doi.org/10.1007/s00122-018-3066-x CrossRefPubMedGoogle Scholar
  61. Tian X, Li X, Zhou W, Ren Y, Wang Z, Liu Z, Tang J, Tong H, Fang J, Bu Q (2017a) Transcription factor OsWRKY53 positively regulates brassinosteroid signaling and plant architecture. Plant Physiol 175:1337–1349.  https://doi.org/10.1104/pp.17.00946 CrossRefPubMedPubMedCentralGoogle Scholar
  62. Tian X, Wen W, Xie L, Fu L, Xu D, Fu C, Wang D, Chen X, Xia X, Chen Q, He Z, Cao S (2017b) Molecular mapping of reduced plant height gene Rht24 in bread wheat. Front Plant Sci 8:1379.  https://doi.org/10.3389/fpls.2017.01379 CrossRefPubMedPubMedCentralGoogle Scholar
  63. Tuinstra MR, Ejeta G, Goldsbrough PB (1997) Heterogeneous inbred family (HIF) analysis: a method for developing near-isogenic lines that differ at quantitative trait loci. Theor Appl Genet 95:1005–1011.  https://doi.org/10.1007/s001220050654 CrossRefGoogle Scholar
  64. Van Ooijen W (2006) JoinMap 4.0: Software for the calculation of genetic linkage maps in experimental populations. Kyazma BV, WageningenGoogle Scholar
  65. Van Os H, Stam P, Visser RG, Van Eck HJ (2005) RECORD: a novel method for ordering loci on a genetic linkage map. Theor Appl Genet 112:30–40.  https://doi.org/10.1007/s00122-005-0097-x CrossRefPubMedGoogle Scholar
  66. Wang RX, Hai L, Zhang XY, You GX, Yan CS, Xiao SH (2009) QTL mapping for grain filling rate and yield-related traits in RILs of the Chinese winter wheat population Heshangmai x Yu8679. Theor Appl Genet 118:313–325.  https://doi.org/10.1007/s00122-008-0901-5 CrossRefPubMedGoogle Scholar
  67. Wang Z, Wu X, Ren Q, Chang X, Li R, Jing R (2010) QTL mapping for developmental behavior of plant height in wheat (Triticum aestivum L.). Euphytica 174:447–458.  https://doi.org/10.1007/s10681-010-0166-3 CrossRefGoogle Scholar
  68. Wang S, Basten C, Zeng Z (2012a) Windows QTL Cartographer 2.5. Department of Statistics, North Carolina State University, Raleigh 2010 Google Scholar
  69. Wang S, Wu K, Yuan Q, Liu X, Liu Z, Lin X, Zeng R, Zhu H, Dong G, Qian Q, Zhang G, Fu X (2012b) Control of grain size, shape and quality by OsSPL16 in rice. Nat Genet 44:950–954.  https://doi.org/10.1038/ng.2327 CrossRefPubMedGoogle Scholar
  70. Wang S, Wong D, Forrest K, Allen A, Chao S, Huang BE, Maccaferri M, Salvi S, Milner SG, Cattivelli L (2014) Characterization of polyploid wheat genomic diversity using a high-density 90,000 single nucleotide polymorphism array. Plant Biotechnol J 12:787–796.  https://doi.org/10.1111/pbi.12183 CrossRefPubMedPubMedCentralGoogle Scholar
  71. Winfield MO, Allen AM, Burridge AJ, Barker GL, Benbow HR, Wilkinson PA, Coghill J, Waterfall C, Davassi A, Scopes G (2016) High-density SNP genotyping array for hexaploid wheat and its secondary and tertiary gene pool. Plant Biotechnol J 14:1195–1206CrossRefGoogle Scholar
  72. Wu QH, Chen YX, Zhou SH, Fu L, Chen JJ, Xiao Y, Zhang D, Ouyang SH, Zhao XJ, Cui Y (2015) High-density genetic linkage map construction and QTL mapping of grain shape and size in the wheat population Yanda 1817 x Beinong6. PLoS ONE 10:e0118144.  https://doi.org/10.1371/journal.pone.0118144 CrossRefPubMedPubMedCentralGoogle Scholar
  73. Wurschum T, Langer SM, Longin CF (2015) Genetic control of plant height in European winter wheat cultivars. Theor Appl Genet 128:865–874.  https://doi.org/10.1007/s00122-015-2476-2 CrossRefPubMedGoogle Scholar
  74. Wurschum T, Leiser WL, Langer SM, Tucker MR, Longin CFH (2018) Phenotypic and genetic analysis of spike and kernel characteristics in wheat reveals long-term genetic trends of grain yield components. Theor Appl Genet 131:2071–2084.  https://doi.org/10.1007/s00122-018-3133-3 CrossRefPubMedGoogle Scholar
  75. Xiao Y, He S, Yan J, Zhang Y, Zhang Y, Wu Y, Xia X, Tian J, Ji W, He Z (2011) Molecular mapping of quantitative trait loci for kernel morphology traits in a non-1BL. 1RS × 1BL. 1RS wheat cross. Crop Pasture Sci 62:625–638CrossRefGoogle Scholar
  76. Xie Q, Mayes S, Sparkes DL (2015) Carpel size, grain filling, and morphology determine individual grain weight in wheat. J Exp Bot 66:6715–6730.  https://doi.org/10.1093/jxb/erv378 CrossRefPubMedPubMedCentralGoogle Scholar
  77. Yan JB, Tang H, Huang YQ, Zheng YL, Li JS (2006) Quantitative trait loci mapping and epistatic analysis for grain yield and yield components using molecular markers with an elite maize hybrid. Euphytica 149:121–131.  https://doi.org/10.1007/s10681-005-9060-9 CrossRefGoogle Scholar
  78. Yan L, Liang F, Xu H, Zhang X, Zhai H, Sun Q, Ni Z (2017) Identification of QTL for grain size and shape on the D genome of natural and synthetic allohexaploid wheats with near-identical AABB genomes. Front Plant Sci 8:1705.  https://doi.org/10.3389/fpls.2017.01705 CrossRefPubMedPubMedCentralGoogle Scholar
  79. Yang J, Zhou Y, Wu Q, Chen Y, Zhang P, Zhang Y, Hu W, Wang X, Zhao H, Dong L, Han J, Liu Z, Cao T (2019) Molecular characterization of a novel TaGL3-5A allele and its association with grain length in wheat (Triticum aestivum L.). Theor Appl Genet 132:1799–1814.  https://doi.org/10.1007/s00122-019-03316-1 CrossRefPubMedGoogle Scholar
  80. Zanke CD, Ling J, Plieske J, Kollers S, Ebmeyer E, Korzun V, Argillier O, Stiewe G, Hinze M, Neumann F, Eichhorn A, Polley A, Jaenecke C, Ganal MW, Roder MS (2015) Analysis of main effect QTL for thousand grain weight in European winter wheat (Triticum aestivum L.) by genome-wide association mapping. Front Plant Sci 6:644.  https://doi.org/10.3389/fpls.2015.00644 CrossRefPubMedPubMedCentralGoogle Scholar
  81. Zeng ZB (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468PubMedPubMedCentralGoogle Scholar
  82. Zhai HJ, Feng ZY, Li J, Liu XY, Xiao SH, Ni ZF, Sun QX (2016) QTL analysis of spike morphological traits and plant height in winter wheat (Triticum aestivum L.) using a high-density SNP and SSR-based linkage map. Front Plant Sci.  https://doi.org/10.3389/fpls.2016.01617 CrossRefPubMedPubMedCentralGoogle Scholar
  83. Zhai H, Feng Z, Du X, Song Y, Liu X, Qi Z, Song L, Li J, Li L, Peng H, Hu Z, Yao Y, Xin M, Xiao S, Sun Q, Ni Z (2018) A novel allele of TaGW2-A1 is located in a finely mapped QTL that increases grain weight but decreases grain number in wheat (Triticum aestivum L.). Theor Appl Genet 131:539–553.  https://doi.org/10.1007/s00122-017-3017-y CrossRefPubMedGoogle Scholar
  84. 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 CrossRefPubMedGoogle Scholar
  85. Zhang JJ, Dell B, Biddulph B, Drake-Brockman F, Walker E, Khan N, Wong DB, Hayden M, Appels R (2013) Wild-type alleles of Rht-B1 and Rht-D1 as independent determinants of thousand-grain weight and kernel number per spike in wheat. Mol Breeding 32:771–783.  https://doi.org/10.1007/s11032-013-9905-1 CrossRefGoogle Scholar
  86. Zhang C, Gao L, Sun J, Jia J, Ren Z (2014a) Haplotype variation of Green Revolution gene Rht-D1 during wheat domestication and improvement. J Integr Plant Biol 56:774–780.  https://doi.org/10.1111/jipb.12197 CrossRefPubMedGoogle Scholar
  87. Zhang YJ, Liu JD, Xia XC, He ZH (2014b) TaGS-D1, an ortholog of rice OsGS3, is associated with grain weight and grain length in common wheat. Mol Breeding 34:1097–1107.  https://doi.org/10.1007/s11032-014-0102-7 CrossRefGoogle Scholar
  88. Zheng J, Liu H, Wang Y, Wang L, Chang X, Jing R, Hao C, Zhang X (2014) TEF-7A, a transcript elongation factor gene, influences yield-related traits in bread wheat (Triticum aestivum L.). J Exp Bot 65:5351–5365.  https://doi.org/10.1093/jxb/eru306 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Zhaoyan Chen
    • 1
    • 2
  • Xuejiao Cheng
    • 1
    • 2
  • Lingling Chai
    • 1
    • 2
  • Zhihui Wang
    • 1
    • 2
  • Ruolin Bian
    • 1
    • 2
  • Jiang Li
    • 1
    • 2
  • Aiju Zhao
    • 3
  • Mingming Xin
    • 1
    • 2
  • Weilong Guo
    • 1
    • 2
  • Zhaorong Hu
    • 1
    • 2
  • Huiru Peng
    • 1
    • 2
  • Yingyin Yao
    • 1
    • 2
  • Qixin Sun
    • 1
    • 2
  • Zhongfu Ni
    • 1
    • 2
    Email author
  1. 1.State Key Laboratory for Agrobiotechnology, Key Laboratory of Crop Heterosis and Utilization (MOE), Key Laboratory of Crop Genetic ImprovementChina Agricultural UniversityBeijingChina
  2. 2.National Plant Gene Research CentreBeijingChina
  3. 3.Hebei Crop Genetic Breeding Laboratory, Institute of Cereal and Oil CropsHebei Academy of Agriculture and Forestry SciencesShijiazhuangChina

Personalised recommendations