Abstract
Wheat, an important cereal crop globally, faces major challenges due to increasing global population and changing climates. The production and productivity are challenged by several biotic and abiotic stresses. There is also a pressing demand to enhance grain yield and quality/nutrition to ensure global food and nutritional security. To address these multifaceted concerns, researchers have conducted numerous meta-QTL (MQTL) studies in wheat, resulting in the identification of candidate genes that govern these complex quantitative traits. MQTL analysis has successfully unraveled the complex genetic architecture of polygenic quantitative traits in wheat. Candidate genes associated with stress adaptation have been pinpointed for abiotic and biotic traits, facilitating targeted breeding efforts to enhance stress tolerance. Furthermore, high-confidence candidate genes (CGs) and flanking markers to MQTLs will help in marker-assisted breeding programs aimed at enhancing stress tolerance, yield, quality and nutrition. Functional analysis of these CGs can enhance our understanding of intricate trait-related genetics. The discovery of orthologous MQTLs shared between wheat and other crops sheds light on common evolutionary pathways governing these traits. Breeders can leverage the most promising MQTLs and CGs associated with multiple traits to develop superior next-generation wheat cultivars with improved trait performance. This review provides a comprehensive overview of MQTL analysis in wheat, highlighting progress, challenges, validation methods and future opportunities in wheat genetics and breeding, contributing to global food security and sustainable agriculture.
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References
Acuña-Galindo MA, Mason RE, Subramanian NK, Hays DB (2015) Meta-analysis of wheat QTL regions associated with adaptation to drought and heat stress. Crop Sci 55:477–492. https://doi.org/10.1094/PDIS-05-20-1087-RE
Aduragbemi A, Soriano JM (2021) Unraveling consensus genomic regions conferring leaf rust resistance in wheat via meta-QTL analysis. BMC Genome 15(1):e20185. https://doi.org/10.1101/2021.05.11.443557
Agarwal P, Khurana P (2020) TaZnF, a C3HC4 type RING zinc finger protein from Triticum aestivum is involved in dehydration and salinity stress. J Plant Biochem Biotechnol 29:395–406. https://doi.org/10.1007/s13562-019-00546-8
Akio Amorim LL, da Fonseca dos Santos R, Pacifco Bezerra Neto J, Guida-Santos M, Crovella S, Maria Benko-Iseppon A (2017) Transcription factors involved in plant resistance to pathogens. Curr Protein Pept Sci 18:335–351
Amo A, Soriano JM (2022) Unraveling consensus genomic regions conferring leaf rust resistance in wheat via meta-QTL analysis. Plant Genome 15(1):e20185. https://doi.org/10.1002/tpg2.20185
Anderson JP, Gleason CA, Foley RC, Thrall PH, Burdo JB, Singh KB (2010) Plants versus pathogens: an evolutionary arms race. Funct Plant Biol 37(6):499–512. https://doi.org/10.1071/FP09304
Arabi MIE, Jawhar M, Mir Ali N (2007) The effects of Mycosphaerella graminicola infection on wheat protein content and quality. Cereal Res Commun 35:81–88. https://doi.org/10.1556/crc.35.2007.1.10
Arcade A, Labourdette A, Falque M, Mangin B, Chardon F, Charcosset A, Joets J (2004) BioMercator: integrating genetic maps and QTL towards discovery of candidate genes. Bioinformatics 20(14):2324–2326. https://doi.org/10.1093/bioinformatics/bth230
Arriagada O, Gadaleta A, Marcotuli I, Maccaferri M, Campana M, Reveco S et al (2022) A comprehensive meta-QTL analysis for yield-related traits of durum wheat (Triticum turgidum L. var. durum) grown under different water regimes. Front Plant Sci 13:3329. https://doi.org/10.3389/fpls.2022.984269
Azadi A, Mardi M, Hervan EM, Mohammadi SA, Moradi F, Tabatabaee MT, Mohammadi-Nejad G (2015) QTL map** of yield and yield components under normal and salt-stress conditions in bread wheat (Triticum aestivum L.). Plant Mol Biol Rep 33:102–120
Bakala HS, Mandahal KS, Sarao LK, Srivastava P (2021) Breeding wheat for biotic stress resistance: achievements, challenges and prospects. In: Ansari MR (ed) Current trends in wheat research. Intechopen, London
Bhathal JS, Loughman R, Speijers J (2003) Yield reduction in wheat in relation to leaf disease from yellow (tan) spot and septoria nodorum blotch. Eur J Plant Pathol 109(5):435. https://doi.org/10.1023/A:1024277420773
Bilgrami SS, Ramandi HD, Shariati V, Razavi K, Tavakol E, Fakheri BA, Ghaderian M (2020) Detection of genomic regions associated with tiller number in Iranian bread wheat under different water regimes using genome-wide association study. Sci Rep 10(1):1–17. https://doi.org/10.1038/s41598-020-69442-9
Buerstmayr M, Steiner B, Buerstmayr H (2020) Breeding for Fusarium head blight resistance in wheat—progress and challenges. Plant Breed 139(3):429–454. https://doi.org/10.1111/pbr.12797
Cai J, Wang S, Su Z, Li T, Zhang X, Bai G (2019) Meta-analysis of QTL for Fusarium head blight resistance in Chinese wheat landraces. Crop J 7(6):784–798. https://doi.org/10.1016/j.cj.2019.05.003
Cao YY, Yang JF, Liu TY, Su ZF, Zhu FY, Chen MX, Fan T, Ye NH, Feng Z, Wang LJ, Hao GF (2017) A phylogenetically informed comparison of GH1 hydrolases between Arabidopsis and rice response to stressors. Front Plant Sci 8:350. https://doi.org/10.3389/fpls.2017.00350
Challinor AJ, Watson J, Lobell DB, Howden SM, Smith DR, Chhetri N (2014) A meta-analysis of crop yield under climate change and adaptation. Nat Clim Change 4(4):287–291
Chen X, Min D, Yasir TA, Hu YG (2012) Evaluation of 14 morphological, yield-related and physiological traits as indicators of drought tolerance in Chinese winter bread wheat revealed by analysis of the membership function value of drought tolerance (MFVD). Field Crops Res 137:195–201
Chung CL, Jamann T, Longfellow J, Nelson R (2010) Characterization and fine-map** of a resistance locus for northern leaf blight in maize bin 8.06. Theor Appl Genet 121(2):205–227
Cooleya MB, Pathiranaa S, Wua HKP, Klessig DF (2000) Members of the Arabidopsis HRT/RPP8 family of resistance genes confer resistance to both viral and oomycete pathogens. Plant Cell 12(5):663–676. https://doi.org/10.1105/tpc.12.5.663
Cools HJ, Fraaije BA (2008) Are azole fungicides losing ground against Septoria wheat disease? Resistance mechanisms in Mycosphaerella graminicola. Pest Manag Sci Former Pestic Sci 64(7):681–684. https://doi.org/10.1002/ps.1568
Crespo-Herrera LA, Crossa J, Huerta-Espino J, Autrique E, Mondal S, Velu G, Vargas M, Braun HJ, Singh RP (2018) Genetic yield gains in CIMMYT’s international elite spring wheat yield trials by modelling the genotype × environment interaction. Crop Sci 57:789–801. https://doi.org/10.2135/cropsci2016.06.0553
Cuthbert PA, Somers DJ, Brulé-Babel A (2007) Map** of Fhb2 on chromosome 6BS: a gene controlling Fusarium head blight field resistance in bread wheat (Triticum aestivum L.). Theor Appl Genet 114(3):429–437
Daba SD, Liu X, Aryal U, Mohammadi M (2020) A proteomic analysis of grain yield-related traits in wheat. AoB Plants 12(5):plaa042. https://doi.org/10.1093/aobpla/plaa042
Dang PM, Lamb MC, Bowen KL, Chen CY (2019) Identifcation of expressed R-genes associated with leaf spot diseases in cultivated peanut. Mol Biol Rep 46:225–239. https://doi.org/10.1007/s11033-018-4464-5
Daware AV, Srivastava R, Singh AK, Parida SK, Tyagi AK (2017) Regional association analysis of metaQTLs delineates candidate grain size genes in rice. Front Plant Sci 8:807. https://doi.org/10.3389/fpls.2017.00807
Deppe JP, Rabbat R, Hörtensteiner S, Keller B, Martinoia E, Lopéz-Marqués RL (2018) The wheat ABC transporter Lr34 modifes the lipid environment at the plasma membrane. J Biol Chem 293:18667–18679. https://doi.org/10.1074/jbc.RA118.002532
Dhokane D, Karre S, Kushalappa AC, McCartney C (2016) Integrated metabolo-transcriptomics reveals Fusarium head blight candidate resistance genes in wheat QTL-Fhb2. PLoS ONE 11(5):e0155851. https://doi.org/10.1371/journal.pone.0155851
Dordas C (2009) Nonsymbiotic hemoglobins and stress tolerance in plants. Plant Sci 176(4):433–440. https://doi.org/10.1016/j.plantsci.2009.01.003
Du B, Wu J, Islam MS, Sun C, Lu B, Wei P, Chen C (2022) Genome-wide meta-analysis of QTL for morphological related traits of flag leaf in bread wheat. PLoS ONE 17(10):e0276602. https://doi.org/10.1371/journal.pone.0276602
Dubin HJ and Ginkel MV (1991) The status of wheat diseases and disease research in warmer areas. In: Wheat for the non-traditional warm areas: a proceedings of the international conference July 29–August Page 21/35 3 Foz do Iguaçu, Brazil, pp 125–45 CIMMYT. https://doi.org/10.1159/000446523
Dweba CC, Figlan S, Shimelis HA, Motaung TE, Sydenham S, Mwadzingeni L, Tsilo TJ (2017) Fusarium head blight of wheat: pathogenesis and control strategies. Crop Prot 91:114–122. https://doi.org/10.1016/j.cropro.2016.10.002
Endelman JB (2011) New algorithm improves fine structure of the barley consensus SNP map. BMC Genom 12:1–9
Endelman JB, Plomion C (2014) LPmerge: an R package for merging genetic maps by linear programming. Bioinformatics 30(11):1623–1624. https://doi.org/10.1093/bioinformatics/btu091
Etzel CJ, Guerra R (2002) Meta-analysis of genetic-linkage analysis of quantitative-trait loci. Am J HumGenet 71(1):56–65. https://doi.org/10.1086/341126
Fang Y, **e K, **ong L (2014) Conserved miR164-targeted NAC genes negatively regulate drought resistance in rice. J Exp Bot 65:2119–2135. https://doi.org/10.1093/jxb/eru072
Faris JD, Liu Z, Xu SS (2013) Genetics of tan spot resistance in wheat. Theor Appl Genet 126(9):2197–2217
Flagella Z, Giuliani M, Giuzio L, Volpi C, Masci S (2010) Influence of water deficit on durum wheat storage protein composition and technological quality. Eur J Agron 33:197–207. https://doi.org/10.1016/j.eja.2010.05.006
Foroud NA, Pordel R, Goyal RK, Ryabova D, Eranthodi A, Chatterton S, Kovalchuk I (2019) Chemical activation of the ethylene signaling pathway promotes Fusarium graminearum resistance in detached wheat heads. Phytopathology 109(5):796–803. https://doi.org/10.1094/PHYTO-08-18-0286-R
Gautam T, Saripalli G, Gahlaut V, Kumar A, Sharma P, Balyan HS, Gupta PK (2019) Further studies on sugar transporter (SWEET) genes in wheat (Triticum aestivum L.). Mol Biol Rep 46(2):2327–2353. https://doi.org/10.1007/s11033-019-04691-0
Gegas VC, Nazari A, Griffiths S, Simmonds J, Fish L, Orford S, Snape JW (2010) A genetic framework for grain size and shape variation in wheat. Plant Cell 22(4):1046–1056. https://doi.org/10.1105/tpc.110.074153
Genc Y, Taylor J, Rongala J, Oldach K (2014) A major locus for chloride accumulation on chromosome 5A in bread wheat. PLoS ONE 9(6):e98845. https://doi.org/10.1371/journal.pone.0098845
Goffinet B, Gerber S (2000) Quantitative trait loci: a meta-analysis. Genetics 155(1):463–473. https://doi.org/10.1093/genetics/155.1.463
Golabadi M, Arzani A, Mirmohammadi Maibody SAM, Sayed Tabatabaei BE, Mohammadi SA (2011) Identification of microsatellite markers linked with yield components under drought stress at terminal growth stages in durum wheat. Euphytica 177:207–221
Goodwin SB, McDonald BA, Kema GHJ (2003) The Mycosphaerella sequencing initiative. In: Global Insights into the septoria and stagonospora diseases of cereals: proceedings of the sixth international symposium on septoria and stagonospora diseases of cereals, pp 149–151
Goudemand E, Laurent V, Duchalais L, Tabib Ghaffary SM, Kema GH, Lonnet P, Robert O (2013) Association map** and meta-analysis: two complementary approaches for the detection of reliable Septoria tritici blotch quantitative resistance in bread wheat (Triticum aestivum L.). Mol Breed 32(3):563–584
Griffiths S, Simmonds J, Leverington M, Wang Y, Fish L, Sayers L, Snape J (2009) Meta-QTL analysis of the genetic control of ear emergence in elite European winter wheat germplasm. Theor Appl Genet 119(3):383–395
Griffiths S, Simmonds J, Leverington M, Wang Y, Fish L, Sayers L, Snape J (2012) Meta-QTL analysis of the genetic control of crop height in elite European winter wheat germplasm. Mol Breed 29(1):159–171
Guarin JR, Martre P, Ewert F, Webber H, Dueri S, Calderini D, Asseng S (2022) Evidence for increasing global wheat yield potential. Environ Res Lett 17(12):124045. https://doi.org/10.1088/1748-9326/aca77c
Gudi S, Saini DK, Singh G, Halladakeri P, Kumar P, Shamshad M, Sharma A (2022) Unraveling consensus genomic regions associated with quality traits in wheat using meta-analysis of quantitative trait loci. Planta 255(6):1–19
Gullner G, Komives T, Király L, Schröder P (2018) Glutathione S-transferase enzymes in plant-pathogen interactions. Front Plant Sci 9:1836. https://doi.org/10.3389/fpls.2018.01836
Gunupuru LR, Arunachalam C, Malla KB, Kahla A, Perochon A, Jia J, Doohan FM (2018) A wheat cytochrome P450 enhances both resistance to deoxynivalenol and grain yield. PLoS ONE 13(10):e0204992. https://doi.org/10.1371/journal.pone.0204992
Guo K, Chen T, Zhang P, Liu Y, Che Z, Shahinnia F, Yang D (2023) Meta-QTL analysis and in-silico transcriptome assessment for controlling chlorophyll traits in common wheat. Plant Genome 16(1):e20294. https://doi.org/10.1002/tpg2.20294
Gupta PK, Rustgi S, Mir RR (2013a) Array-based high-throughput DNA markers and genoty** platforms for cereal genetics and genomics. In: Gupta PK, Varshney RK (eds) Cereal genomics II. Springer, Cham. https://doi.org/10.1007/978-94-007-6401-9_2
Gupta PK, Kulwal PL, Mir RR (2013b) QTL map**: methodology and applications in cereal breeding. In: Gupta PK, Varshney RK (eds) Cereal genomics II. Springer, Cham. https://doi.org/10.1007/978-94-007-6401-9_11
Gupta A, Rico-Medina A, Ana I, Caño-Delgado AI (2020a) The physiology of plant responses to drought. Science 368:266–269
Gupta PK, Balyan HS, Sharma S, Kumar R (2020b) Genetics of yield, abiotic stress tolerance and biofortification in wheat (Triticum aestivum L.). Theor Appl Genet 133:1569–1602. https://doi.org/10.1007/s00122-020-03583-3
Häberle J, Holzapfel J, Schweizer G, Hartl L (2009) A major QTL for resistance against Fusarium head blight in European winter wheat. Theor Appl Genet 119(2):325–332
Hafeez AN, Arora S, Ghosh S, Gilbert D, Bowden RL, Wulff BBH (2021) Creation and judicious application of a wheat resistance gene atlas. Mol Plant 14(7):1053–1070. https://doi.org/10.1016/j.molp.2021.05.014
Hanocq E, Laperche A, Jaminon O, Lainé AL, Le Gouis J (2007) Most significant genome regions involved in the control of earliness traits in bread wheat, as revealed by QTL meta-analysis. Theor Appl Genet 114(3):569–584
Hasan MI, Kibria MG, Jahiruddin M, Murata Y, Hoque MA (2015) Improvement of salt tolerance in maize by exogenous application of proline. J Environ Sci Nat Resour 8(1):13–18. https://doi.org/10.3329/jesnr.v8i1.24626
Hasanuzzaman M, Nahar K, Rahman A, Anee TI, Alam MU, Bhuiyan TF, Oku H, Fujita M (2017) Approaches to enhance salt stress tolerance in wheat. In: Wanyera R, Owuoche J (eds) Wheat improvement, management and utilization. Intechopen, London, pp 151–187
He Y, Ahmad D, Zhang X, Zhang Y, Wu L, Jiang P, Ma H (2018) Genome-wide analysis of family-1 UDP glycosyltransferases (UGT) and identification of UGT genes for FHB resistance in wheat (Triticum aestivum L.). BMC Plant Biol 18(1):1–20. https://doi.org/10.1186/s12870-018-1286-5
Herrera-Foessel SA, Singh RP, Lillemo M, Huerta-Espino J, Bhavani S, Singh S, Lagudah ES (2014) Lr67/Yr46 confers adult plant resistance to stem rust and powdery mildew in wheat. Theor Appl Genet 127(4):781–789
Hossain A, Skalicky M, Brestic M, Maitra S, Ashraful Alam M, Syed MA, Islam T (2021) Consequences and mitigation strategies of abiotic stresses in wheat (Triticum aestivum L.) under the changing climate. Agronomy 11(2):241. https://doi.org/10.3390/agronomy11020241
Hu J, Wang X, Zhang G, Jiang P, Chen W, Hao Y, Ma X, Xu S, Jia J, Kong L, Wang H (2020) QTL map** for yield-related traits in wheat based on four RIL populations. Theor Appl Genet 133:917–933
Huerta-Espino J, Singh RP, German S, McCallum BD, Park RF, Chen WQ, Bhardwaj SC, Goyeau H (2011) Global status of wheat leaf rust caused by Puccinia triticina. Euphytica 179:143–160
Huerta-Espino J, Singh R, Crespo-Herrera LA, Villaseñor-Mir HE, Rodriguez-Garcia MF, Dreisigacker S, Lagudah E (2020) Adult plant slow rusting genes confer high levels of resistance to rusts in bread wheat cultivars from Mexico. Front Plant Sci 11:824. https://doi.org/10.3389/fpls.2020.00824
Hulbert SH, Webb CA, Smith SM, Sun Q (2001) Resistance gene complexes: evolution and utilization. Annu Rev Phytopathol 39:285–312. https://doi.org/10.1146/annurev.phyto.39.1.285
Ilyas N, Mazhar R, Yasmin H, Khan W, Iqbal S, Enshasy HE, Dailin DJ (2020) Rhizobacteria isolated from saline soil induce systemic tolerance in wheat (Triticum aestivum L.) against salinity stress. Agronomy 10(7):989. https://doi.org/10.3390/agronomy10070989
Ioannidis J, Ntzani EE, Trikalinos TA, Contopoulos-Ioannidis DG (2001) Replication validity of genetic association studies. Nat Genet 29(3):306–309
Ioannidis JP, Trikalinos TA, Ntzani EE, Contopoulos-Ioannidis DG (2003) Genetic associations in large versus small studies: an empirical assessment. Lancet 361(9357):567–571. https://doi.org/10.1016/S0140-6736(03)12516-0
IPCC (2018) Summary for policymakers. Global warming of 1.5°C. An IPCC special report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways. Context strength glob response to threat climate change sustain development efforts to eradicate poverty. World Meteorological Organization, Geneva. Available https://www.ipcc.ch/site/assets/uploads/sites/2/2018/07/SR15_SPM_version_stand_alone_LR.pdf
Iqbal Z, Iqbal MS, Hashem A, AbdAllah EF, Ansari MI (2021) Plant defense responses to biotic stress and its interplay with fluctuating dark/light conditions. Front Plant Sci 12:631810. https://doi.org/10.3389/fpls.2021.631810
Jackson BN, Schnable PS, Aluru S (2008) Consensus genetic maps as median orders from inconsistent sources. IEEE ACM Trans Comput Biol Bioinform 5(2):161–171. https://doi.org/10.1109/TCBB.2007.70221
Jan I, Saripalli G, Kumar K, Kumar A, Singh R, Batra R, Sharma PK, Balyan HS, Gupta PK (2021) Meta-QTLs and genes for stripe rust resistance in wheat. Sci Rep 11:1–13. https://doi.org/10.1038/s41598-021-02049-w
Jansen RC, Stam P (1994) High resolution of quantitative traits into multiple loci via interval map**. Genetics 136(4):1447–1455. https://doi.org/10.1093/genetics/136.4.1447
Jia H, Li M, Li W, Liu L, Jian Y, Yang Z, Zhang Z (2020) A serine/threonine protein kinase encoding gene KERNEL NUMBER PER ROW6 regulates maize grain yield. Nat Commun 11(1):1–11. https://doi.org/10.1038/s41467-020-14746-7
** X, Sun T, Wang X, Su P, Ma J, He G, Yang G (2016) Wheat CBL—interacting protein kinase 25 negatively regulates salt tolerance in transgenic wheat. Sci Rep 6:1–12. https://doi.org/10.1038/srep28884
Joshi LM, Singh DV, Srivastava KD (1985) Status of rusts and smuts in India. Barley, Wheat and Triticale Newsletter. ISSN: 0255–6421
Joshi AK, Mishra B, Chatrath R, Ferrara GO, Singh RP (2007) Wheat improvement in India: present status, emerging challenges and future prospects. Euphytica 157:431–446
Kaur B, Sandhu KS, Kamal R, Kaur K, Singh J, Röder MS, Muqaddasi QH (2021) Omics for the improvement of abiotic, biotic, and agronomic traits in major cereal crops: applications, challenges, and prospects. Plants 10:1989. https://doi.org/10.3390/plants10101989
Kaur S, Das A, Sheoran S, Rakshit S (2023) QTL meta-analysis: an approach to detect robust and precise QTL. Trop Plant Biol 21:1–9
Khahani B, Tavakol E, Shariati V, Fornara F (2020) Genome wide screening and comparative genome analysis for meta-QTLs, ortho-MQTLs and candidate genes controlling yield and yield-related traits in rice. BMC Genom 21(1):1–24. https://doi.org/10.1186/s12864-020-6702-1
Knott DR (1989) The effect of transfers of alien genes for leaf rust resistance on the agronomic and quality characteristics of wheat. Euphytica 44:65–72
Kosina P, Reynolds M, Dixon J, Joshi A (2007) Stakeholder perception of wheat production constraints, capacity building needs, and research partnerships in develo** countries. Euphytica 157:475–483. https://doi.org/10.1007/s10681-007-9529-9
Krattinger SG, Lagudah ES, Spielmeyer W, Singh RP, Huerta-Espino J, McFadden H, Keller B (2009) A putative ABC transporter confers durable resistance to multiple fungal pathogens in wheat. Science 323(5919):1360–1363. https://doi.org/10.1126/science.1166453
Kuchel H, Williams K, Langridge P, Eagles H, Jefferies S (2007) Genetic dissection of grain yield in bread wheat. II. QTL-by-environment interaction. Theor Appl Genet 115:1015–1027. https://doi.org/10.1007/s00122-007-0628-8
Kumar A, Saripalli G, Jan I, Kumar K, Sharma PK, Balyan HS, Gupta PK (2020) Meta-QTL analysis and identification of candidate genes for drought tolerance in bread wheat (Triticum aestivum L.). Physiol Mol Biol Plants 26:1713–1725. https://doi.org/10.1007/s12298-020-00847-6
Kumar S, Singh VP, Saini DK, Sharma H, Saripalli G, Kumar S, Gupta PK (2021) Meta-QTLs, ortho-MQTLs, and candidate genes for thermotolerance in wheat (Triticum aestivum L.). Mol Breed 41(11):1–22. https://doi.org/10.1007/s11032-021-01264-7
Kumar S, Saini DK, Jan F, Jan S, Tahir M, Djalovic I, Mir RR (2023) Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat. BMC Genom 24(1):1–19. https://doi.org/10.1186/s12864-023-09336-y
Lander ES, Botstein D (1989) Map** mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121(1):185–199. https://doi.org/10.1093/genetics/121.1.185
Lesk C, Rowhani P, Ramankutty N (2016) Influence of extreme weather disasters on global crop production. Nature 529:84–87
Li Y, Wei K (2020) Comparative functional genomics analysis of cytochrome P450 gene superfamily in wheat and maize. BMC Plant Biol 20(1):1–22. https://doi.org/10.1186/s12870-020-2288-7
Li X, Shin S, Heinen S, Dill-Macky R, Berthiller F, Nersesian N, Muehlbauer GJ (2015) Transgenic wheat expressing a barley UDP-glucosyltransferase detoxifies deoxynivalenol and provides high levels of resistance to Fusarium graminearum. Mol Plant Microbe Interact 28(11):1237–1246. https://doi.org/10.1094/MPMI-03-15-0062-R
Li N, Miao Y, Ma J, Zhang P, Chen T, Liu Y, Yang D (2023) Consensus genomic regions for grain quality traits in wheat revealed by meta-QTL analysis and in silico transcriptome integration. Plant Genome 16:e20336. https://doi.org/10.1002/tpg2.20336
Limbalkar OM, Meena K, Singh M, Sunil Kumar VP (2018) Genetic improvement of wheat for biotic and abiotic stress tolerance. Int J Curr Microbiol Appl Sci 7(12):1962–1971. https://doi.org/10.20546/ijcmas.2018.712.226
Liu S, Zhang X, Pumphrey MO, Stack RW, Gill BS, Anderson JA (2006) Complex micro collinearity among wheat, rice, and barley revealed by fine map** of the genomic region harboring a major QTL for resistance to Fusarium head blight in wheat. Funct Integr Genom 6(2):83–89
Liu S, Hall MD, Griffey CA, McKendry AL (2009) Meta-analysis of QTL associated with Fusarium head blight resistance in wheat. Crop Sci 49(6):1955–1968. https://doi.org/10.2135/cropsci2009.03.0115
Liu H, Mullan D, Zhang C, Zhao S, Li X, Zhang A, Yan G (2020a) Major genomic regions responsible for wheat yield and its components as revealed by meta-QTL and genotype–phenotype association analyses. Planta 252(4):1–22. https://doi.org/10.1007/s00425-020-03466-3
Liu Y, Salsman E, Wang R, Galagedara N, Zhang Q, Fiedler JD, Li X (2020b) Meta-QTL analysis of tan spot resistance in wheat. Theor Appl Genet 133(8):2363–2375. https://doi.org/10.1007/s00122-020-03604-1
Löffler M, Schön CC, Miedaner T (2009) Revealing the genetic architecture of FHB resistance in hexaploid wheat (Triticum aestivum L.) by QTL meta-analysis. Mol Breed 23:473–488
Lu P, Liang Y, Li D, Wang Z, Li W, Wang G, Liu Z (2016) Fine genetic map** of spot blotch resistance gene Sb3 in wheat (Triticum aestivum L.). Theor Appl Genet 129(3):577–589. https://doi.org/10.1007/s00122-015-2649-z
Ma J, Liu Y, Zhang P, Chen T, Tian T, Wang P, Yang D (2022) Identification of quantitative trait loci (QTL) and meta-QTL analysis for kernel size-related traits in wheat (Triticum aestivum L.). BMC Plant Biol 22(1):1–18. https://doi.org/10.1186/s12870-022-03989-9
Mago R, Tabe L, McIntosh RA, Pretorius Z, Kota R, Paux E, Spielmeyer W (2011) A multiple resistance locus on chromosome arm 3BS in wheat confers resistance to stem rust (Sr2), leaf rust (Lr27) and powdery mildew. Theor Appl Genet 123(4):615–623
Mao SL, Wei YM, Cao W, Lan XJ, Yu M, Chen ZM, Zheng YL (2010) Confirmation of the relationship between plant height and Fusarium head blight resistance in wheat (Triticum aestivum L.) by QTL meta-analysis. Euphytica 174(3):343–356
Mapuranga J, Zhang N, Zhang L, Liu W, Chang J, Yang W (2022) Harnessing genetic resistance to rusts in wheat and integrated rust management methods to develop more durable resistant cultivars. Front Plant Sci 13:951095
Marchal C et al (2018) BED-domain containing immune receptors confer diverse resistance spectra to yellow rust. Nat Plant 4:662–668
Mason RE, Mondal S, Beecher F, Hays D (2011) Genetic loci linking improved heat tolerance in wheat (Triticum aestivum L.) to lower leaf and spike temperatures under controlled conditions. Euphytica 180:181–194. https://doi.org/10.1007/s10681-011-0349-6
McDonald MC, Ahren D, Simpfendorfer S, Milgate A, Solomon PS (2018) The discovery of the virulence gene ToxA in the wheat and barley pathogen Bipolaris sorokiniana. Mol Plant Pathol 19(2):432–439. https://doi.org/10.1111/mpp.12535
Mehta YR (1998) Constraints on the integrated management of spot blotch of wheat. In: Helminthosporium blight of wheat: spot blotch and tan spot, pp 18–27
Meng X, Zhang S (2013) MAPK cascades in plant disease resistance signalling. Annu Rev Phytopathol 51:245–266. https://doi.org/10.1146/annurev-phyto-082712-102314
Miao Y, **g F, Ma J, Liu Y, Zhang P, Chen T, Yang D (2022) Major genomic regions for wheat grain weight as revealed by QTL linkage map** and meta-analysis. Front Plant Sci 13:802310–802310. https://doi.org/10.3389/fpls.2022.802310
Michalska K, Gale J, Joachimiak G, Chang C, Hatzos-Skintges C, Nocek B, Joachimiak A (2019) Conservation of the structure and function of bacterial tryptophan synthases. IUCrJ 6(4):649–664. https://doi.org/10.1107/S2052252519005955
Min DH, Zhao Y, Huo DY, Li LC, Chen M, Xu ZS, Ma YZ (2013) Isolation and identification of a wheat gene encoding a zinc finger protein (TaZnFP) responsive to abiotic stresses. Acta Physiol Plant 35:1597–1604
Moore JW, Herrera-Foessel S, Lan C et al (2015) A recently evolved hexose transporter variant confers resistance to multiple pathogens in wheat. Nat Genet 47:1494–1498. https://doi.org/10.1038/ng.3439
Munnik T, Meijer HJ, Ter Riet B, Hirt H, Frank W, Bartels D (2000) Hyperosmotic stress stimulates phospholipase D activity and elevates the levels of phosphatidic acid and diacylglycerol pyrophosphate. Plant J 22:147–154. https://doi.org/10.1046/j.1365-313x.2000.00725.x
Nadolska-Orczyk A, Rajchel IK, Orczyk W, Gasparis S (2017) Major genes determining yield-related traits in wheat and barley. Theor Appl Genet 130(6):1081–1098. https://doi.org/10.1007/s00122-017-2880-x
Navathe S, Yadav PS, Chand R, Mishra VK, Vasistha NK, Meher PK, Gupta PK (2020) ToxA–Tsn1 interaction for spot blotch susceptibility in Indian wheat: an example of inverse gene-for-gene Page 26/35 relationship. Plant Dis 104(1):71–81. https://doi.org/10.1094/PDIS-05-19-1066-RE
Nemati M, Zare N, Hedayat-Evrigh N, Asghari R (2022) Meta-analysis of common wheat physiological response to biotic stresses. Zemdirbyste Agric 109(3):245–250. https://doi.org/10.13080/z-a.2022.109.031
Nezhad NM, Kamali MJ, McIntyre CL, Fakheri BA, Omidi M, Masoudi B (2019) Map** QTLs with main and epistatic effect on Seri ‘M829 Babax ‘wheat population under salt stress. Euphytica 215:1–19. https://doi.org/10.1007/s10681-019-2450-1
Niño-González M, Novo-Uzal E, Richardson DN, Barros PM, Duque P (2019) More transporters, more substrates: the Arabidopsis major facilitator superfamily revisited. Mol Plant 12(9):1182–1202. https://doi.org/10.1016/j.molp.2019.07.003
Nuttall JG, O’leary GJ, Panozzo JF, Walker CK, Barlow KM, Fitzgerald GJ (2017) Models of grain quality in wheat—a review. Field Crops Res 202:136–145. https://doi.org/10.1016/j.fcr.2015.12.011
Oliver RP (2014) A reassessment of the risk of rust fungi develo** resistance to fungicides. Pest Manag Sci 70:1641–1645. https://doi.org/10.1002/ps.3767
Ortiz R, Sayre KD, Govaerts B, Gupta R, Subbarao GV, Ban T et al (2008) Climate change: Can wheat beat the heat? Agric Ecosyst Environ 126:46–58. https://doi.org/10.1016/j.agee.2008.01.019
Ouyang SQ, Liu YF, Liu P, Lei G, He SJ, Ma B, Zhang WK, Zhang JS, Chen SY (2010) Receptor-like kinase OsSIK1 improves drought and salt stress tolerance in rice (Oryza sativa) plants. Plant J 62:316–329. https://doi.org/10.1111/j.1365-313X.2010.04146.x
Pal N, Saini DK, Kumar S (2021) Meta-QTLs, ortho-MQTLs and candidate genes for the traits contributing to salinity stress tolerance in common wheat (Triticum aestivum L.). Physiol Mol Biol Plants 27(12):2767–2786. https://doi.org/10.1007/s12298-021-01112-0
Pal N, Saini DK, Kumar S (2022a) Breaking yield ceiling in wheat: progress and future prospects. Int Open, London. https://doi.org/10.5772/intechopen.102919
Pal N, Jan I, Saini DK, Kumar K, Kumar A, Sharma PK, Gupta PK (2022b) Meta-QTLs for multiple disease resistance involving three rusts in common wheat (Triticum aestivum L.). Theor Appl Genet 135(7):2385–2405
Peleg Z, Fahima T, Krugman T, Abbo S, Yakir D, Korol AB et al (2009) Genomic dissection of drought resistance in durum wheat ́ wild emmer wheat recombinant inbred line population. Plant Cell Environ 32:758–779. https://doi.org/10.1111/j.1365-3040.2009.01956.x
Pinto RS, Reynolds MP, Mathews KL, McIntyre CL, Olivares-Villegas JJ, Chapman SC (2010) Heat and drought adaptive QTL in a wheat population designed to minimize confounding agronomic effects. Theor Appl Genet 121:1001–1021. https://doi.org/10.1007/s00122-010-1351-4
Poppenberger B, Berthiller F, Lucyshyn D, Sieberer T, Schuhmacher R, Krska R, Adam G (2003) Detoxification of the Fusarium mycotoxin deoxynivalenol by a UDP-glucosyltransferase from Arabidopsis thaliana. J Biol Chem 278(48):47905–47914. https://doi.org/10.1074/jbc.M307552200
Prakash NR, Lokeshkumar BM, Rathor S, Warraich AS, Yadav S, Vinaykumar NM, Sharma PC (2022) Meta-analysis and validation of genomic loci governing seedling and reproductive stage salinity tolerance in rice. Physiol Plant 174(1):e13629. https://doi.org/10.1111/ppl.13629
Prescott JM, Burnett PA, Saari EE, Ransom JK, Bowman JD, De Milliano W, Geleta AB (1986) Wheat diseases and pests: a guide for field identification
Pumphrey MO, Bernardo R, Anderson JA (2007) Validating the Fhb1 QTL for Fusarium head blight resistance in near-isogenic wheat lines developed from breeding populations. Crop Sci 47(1):200–206. https://doi.org/10.2135/cropsci2006.03.0206
Quraishi UM, Murat F, Abrouk M, Pont C, Confolent C, Oury FX, Salse J (2011) Combined meta-genomics analyses unravel candidate genes for the grain dietary fiber content in bread wheat (Triticum aestivum L.). Funct Integr Genom 11(1):71–83
Quraishi UM, Pont C, Ain QU, Flores R, Burlot L, Alaux M, Salse J (2017) Combined genomic and genetic data integration of major agronomic traits in bread wheat (Triticum aestivum L.). Front Plant Sci 8:1843. https://doi.org/10.3389/fpls.2017.01843
Rahimi Y, Khahani B, Jamali A, Alipour H, Bihamta MR, Ingvarsson PK (2023) Genome-wide association study to identify genomic loci associated with early vigor in bread wheat under simulated water deficit complemented with quantitative trait loci meta-analysis. G Genes Genomes Genet 13(2):jkac320. https://doi.org/10.1093/g3journal/jkac320
Raj SRG, Nadarajah K (2022) QTL and candidate genes: techniques and advancement in abiotic stress resistance breeding of major cereals. Int J Mol Sci 24(1):6. https://doi.org/10.3390/ijms24010006
Rana M, Kaldate R, Nabi SU, Wani SH, Khan H (2021) Marker-assisted breeding for resistance against wheat rusts. In: Wani SH, Mohan A, Singh GP (eds) Physiological, molecular, and genetic perspectives of wheat improvement. Springer, Cham, pp 229–262
Ray DK, Mueller ND, West PC, Foley JA (2013) Yield trends are insufficient to double global crop production by 2050. PLoS ONE 8:8. https://doi.org/10.1371/journal.pone.0066428
Roelfs AP (1992) Rust diseases of wheat: concepts and methods of disease management. Cimmyt
Rong J, Feltus FA, Waghmare VN, Pierce GJ, Chee PW, Draye X, Paterson AH (2007) Meta-analysis of polyploid cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development. Genetics 176(4):2577–2588. https://doi.org/10.1534/genetics.107.074518
Roselló M, Royo C, Álvaro F, Villegas D, Nazco R, Soriano JM (2018) Pasta-making quality QTLome from Mediterranean durum wheat landraces. Front Plant Sci 9:1512. https://doi.org/10.3389/fpls.2018.01512
Safdar LB, Andleeb T, Latif S, Umer MJ, Tang M, Li X, Quraishi UM (2020) Genome-wide association study and QTL meta-analysis identified novel genomic loci controlling potassium use efficiency and agronomic traits in bread wheat. Front Plant Sci 11:70. https://doi.org/10.3389/fpls.2020.00070
Saini DK, Chopra Y, Pal N, Chahal A, Srivastava P, Gupta PK (2021) Meta-QTLs, ortho-MQTLs and candidate genes for nitrogen use efficiency and root system architecture in bread wheat (Triticum aestivum L.). Physiol Mol Biol Plants 27:2245–2267. https://doi.org/10.1007/s12298-021-01085-0
Saini DK, Chopra Y, Singh J, Sandhu KS, Kumar A, Bazzer S, Srivastava P (2022a) Comprehensive evaluation of map** complex traits in wheat using genome-wide association studies. Mol Breed 42(1):1–52
Saini P, Sheikh I, Saini DK, Mir RR, Dhaliwal HS, Tyagi V (2022b) Consensus genomic regions associated with grain protein content in hexaploid and tetraploid wheat. Front Genet 13:1021180. https://doi.org/10.3389/fgene.2022.1021180
Saini DK, Chahal A, Pal N, Srivastava P, Gupta PK (2022c) Meta-analysis reveals consensus genomic regions associated with multiple disease resistance in wheat (Triticum aestivum L.). Mol Breed 42(3):1–23
Saini DK, Srivastava P, Pal N, Gupta PK (2022d) Meta-QTLs, ortho-meta-QTLs and candidate genes for grain yield and associated traits in wheat (Triticum aestivum L.). Theor Appl Genet 135(3):1049–1081
Sakuma S, Golan G, Guo Z, Ogawa T, Tagiri A, Sugimoto K, Komatsuda T (2018) Unleashing floret fertility by a mutated homeobox gene improved grain yield during wheat evolution under domestication. Biorxiv 434985
Salih H, Adelson DL (2009) QTL global meta-analysis: Are trait determining genes clustered? BMC Genom 10(1):1–8. https://doi.org/10.1186/1471-2164-10-184
Serra TS, Figueiredo DD, Cordeiro AM, Almeida DM, Lourenc OT, Abreu IA, Sebastian A, Fernandes L, Contreras-Moreira B, Oliveira MM, Saibo NJ (2013) OsRMC, a negative regulator of salt stress response in rice, is regulated by two AP2/ERF transcription factors. Plant Mol Biol 82:439–455
Shabeer A, Bockus WW (1988) Tan spot effects on yield and yield components relative to growth stage in winter wheat. Plant Dis 72(7):599–602. https://doi.org/10.1094/PD-72-0599
Shahid SA, Zaman M, Heng L (2018) Soil salinity: historical perspectives and a world overview of the problem. In: Zaman M, Shahid SA, Heng L (eds) Guideline for salinity assessment, mitigation and adaptation using nuclear and related techniques. Springer, Cham. https://doi.org/10.1007/978-3-319-96190-3
Shariatipour N, Heidari B, Richards CM (2021a) Meta-analysis of QTLome for grain zinc and iron contents in wheat (Triticum aestivum L.). Euphytica 217(5):1–14. https://doi.org/10.1007/s10681-021-02818-8
Shariatipour N, Heidari B, Tahmasebi A, Richards C (2021b) Comparative genomic analysis of quantitative trait loci associated with micronutrient contents, grain quality, and agronomic traits in wheat (Triticum aestivum L.). Front Plant Sci. https://doi.org/10.3389/fpls.2021.709817
Sharma V, Vasistha NK (2022) Meta-QTL analysis and identification of candidate genes for spot blotch resistance in bread wheat. https://doi.org/10.21203/rs.3.rs-2041344/v1
Sharma M, Singh A, Shankar ALKA, Pandey A, Baranwal V, Kapoor S, Tyagi AK, Pandey GK (2014) Comprehensive expression analysis of rice Armadillo gene family during abiotic stress and development. DNA Res 21:267–283. https://doi.org/10.1093/dnares/dst056
Sidhu BS (2022) Likely impacts of the 2022 heatwave on India’s wheat production
Simón MR, Börner A, Struik PC (2021) Fungal wheat diseases: etiology, breeding, and integrated management. Front Plant Sci 12:671. https://doi.org/10.3389/fpls.2021.671060
Singh K, Batra R, Sharma S, Saripalli G, Gautam T, Singh R, Gupta PK (2021) WheatQTLdb: a QTL database for wheat. Mol Genet Genom 296(5):1051–1056. https://doi.org/10.1007/s00438-021-01796-9
Singh R, Saripalli G, Gautam T, Kumar A, Jan I, Batra R et al (2022) Meta-QTLs, ortho-MetaQTLs and candidate genes for grain Fe and Zn contents in wheat (Triticum aestivum L.). Physiol Mol Biol Plants 28(3):637–650
Soko T, Bender CM, Prins R, Pretorius ZA (2018) Yield loss associated with different levels of stem rust resistance in bread wheat. Plant Dis 102:2531–2538. https://doi.org/10.1094/PDIS-02-18-0307-RE
Soriano JM, Alvaro F (2019) Discovering consensus genomic regions in wheat for root-related traits by QTL meta-analysis. Sci Rep 9(1):1–14. https://doi.org/10.1038/s41598-019-47038-2
Soriano JM, Royo C (2015) Dissecting the genetic architecture of leaf rust resistance in wheat by QTL MQTL analysis. Phytopathology 105:1585–1593. https://doi.org/10.1094/PHYTO-05-15-0130-R
Soriano JM, Malosetti M, Roselló M, Sorrells ME, Royo C (2017) Dissecting the old Mediterranean durum wheat genetic architecture for phenology, biomass and yield formation by association map** and QTL meta-analysis. PLoS ONE 12(5):e0178290. https://doi.org/10.1371/journal.pone.0178290
Soriano JM, Colasuonno P, Marcotuli I, Gadaleta A (2021) Meta-QTL analysis and identification of candidate genes for quality, abiotic and biotic stress in durum wheat. Sci Rep 11:1–15. https://doi.org/10.1038/s41598-021-91446-2
Swamy BPM, Vikram P, Dixit S, Ahmed HU, Kumar A (2011) Meta- analysis of grain yield QTL identified during agricultural drought in grasses showed consensus. BMC Genom 12:319. https://doi.org/10.1186/1471-2164-12-319
Tanin MJ, Saini DK, Sandhu KS, Pal N, Gudi S, Chaudhary J, Sharma A (2022) Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding. Sci Rep 12(1):1–17. https://doi.org/10.1038/s41598-022-18149-0
Truntzler M, Barrière Y, Sawkins MC, Lespinasse D, Betran J, Charcosset A, Moreau L (2010) Meta-analysis of QTL involved in silage quality of maize and comparison with the position of candidate genes. Theor Appl Genet 121(8):1465–1482
Tuteja N, Peter Singh L, Gill SS, Gill R, Tuteja R (2012) Salinity stress: a major constraint in crop production. In: Tuteja N, Gill SS, Tiburcio AF, Tuteja R (eds) Improving crop resistance to abiotic stress. Wiley, New York, pp 71–96
Tyagi S, Gupta PK (2012) Meta-analysis of QTLs involved in pre-harvest sprouting tolerance and dormancy in bread wheat. Triticeae Genom Genet 3(1):9–24. https://doi.org/10.5376/tgg.2012.03.0002
Tyagi S, Mir RR, Balyan HS, Gupta PK (2015) Interval map** and meta-QTL analysis of grain traits in common wheat (Triticum aestivum L.). Euphytica 201(3):367–380
van Dijk M, Morley T, Rau ML, Saghai Y (2021) A meta-analysis of projected global food demand and population at risk of hunger for the period 2010–2050. Nat Food 2:494. https://doi.org/10.1038/s43016-021-00322-9
Venske E, Dos Santos RS, Farias DDR, Rother V, Da Maia LC, Pegoraro C, Costa de Oliveira A (2019) Meta-analysis of the QTLome of Fusarium head blight resistance in bread wheat: refining the current puzzle. Front Plant Sci 10:727. https://doi.org/10.3389/fpls.2019.00727
Veyrieras JB, Goffinet B, Charcosset A (2007) MetaQTL: a package of new computational methods for the meta-analysis of QTL map** experiments. BMC Bioinform 8(1):1–16. https://doi.org/10.1186/1471-2105-8-49
Vikram P et al (2021) Genome wide association analysis of Mexican bread wheat landraces for resistance to yellow and stem rust. PLoS ONE 16:e0246015. https://doi.org/10.1371/journal.pone.0246015
Wang S, Wong D, Forrest K, Allen A, Chao S, Huang BE, Akhunov E (2014) Characterization of polyploid wheat genomic diversity using a high-density 90000 single nucleotide polymorphism array. Plant Biotechnol J 12(6):787–796. https://doi.org/10.1111/pbi.12183
Wang L, Li Q, Coulter JA, **e J, Luo Z, Zhang R, Li L (2020) Winter wheat yield and water use efficiency response to organic fertilization in northern China: a meta-analysis. Agric Water Manag 229:105934. https://doi.org/10.1016/j.agwat.2019.105934
Wiesner-Hanks T, Nelson R (2016) Multiple disease resistance in plants. Ann Rev Phytopath 54:229–252. https://doi.org/10.1146/annurev-phyto-080615-100037
Wisser RJ, Sun Q, Hulbert SH, Kresovich S, Nelson RJ (2005) Identification and characterization of regions of the rice genome associated with broad-spectrum, quantitative disease resistance. Genetics 169(4):2277–2293. https://doi.org/10.1534/genetics.104.036327
Wu Y, Close TJ, Lonardi S (2010) Accurate construction of consensus genetic maps via integer linear programming. IEEE/ACM Trans Comput Biol Bioinform 8(2):381–394. https://doi.org/10.1109/TCBB.2010.35
Wu F, Sheng P, Tan J, Chen X, Lu G, Ma W, Heng Y, Lin Q, Zhu S, Wang J, Wang J, Guo X, Zhang X, Lei C, Wan J (2015) Plasma membrane receptor-like kinase leaf panicle 2 acts downstream of the DROUGHT AND SALT TOLERANCE transcription factor to regulate drought sensitivity in rice. J Exp Bot 66:271–281. https://doi.org/10.1093/jxb/eru417
**n MA, Du XY, Liu GJ, Yang ZD, Hou WQ, Wang HW, Kong LR (2015) Cloning and characterization of a novel UDP-glycosyltransferase gene induced by DON from wheat. J Integr Agric 14(5):830–838. https://doi.org/10.1016/S2095-3119(14)60857-1
Xynias IN et al (2020) Durum wheat breeding in the mediterranean region: current status and future prospects. Agronomy 10:432. https://doi.org/10.3390/agronomy10030432
Yang X, Li P, Zhang S, Sun B, ** C (2011) Long-term-fertilization effects on soil organic carbon, physical properties, and wheat yield of a loess soil. J Plant Nutr Soil Sci 174(5):775–784. https://doi.org/10.1002/jpln.201000134
Yang Y, Amo A, Wei D, Chai Y, Zheng J, Qiao P, Hu YG (2021) Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat. Theor Appl Genet 134(9):3083–3109. https://doi.org/10.1007/s00122-021-03881-4
Zhang LY, Liu DC, Guo XL, Yang WL, Sun JZ, Wang DW, Zhang A (2010) Genomic distribution of quantitative trait loci for yield and yield-related traits in common wheat. J Integr Plant Biol 52(11):996–1007. https://doi.org/10.1111/j.1744-7909.2010.00967.x
Zhang H et al (2014) Large-scale transcriptome comparison reveals distinct gene activations in wheat responding to stripe rust and powdery mildew. BMC Genom 15:1–4
Zhao L, Ma X, Su P, Ge W, Wu H, Guo X, Kong L (2018) Cloning and characterization of a specific UDP-glycosyltransferase gene induced by DON and Fusarium graminearum. Plant Cell Rep 37(4):641–652
Zheng BS, Le Gouis J, Leflon M, Rong WY, Laperche A, Brancourt-Hulme M (2010) Using probe genotypes to dissect QTL ́ environ- ment interactions for grain yield components in winter wheat. Theor Appl Genet 121:1501–1517. https://doi.org/10.1007/s00122-010-1406-6
Zheng T, Hua C, Li L, Sun Z, Yuan M, Bai G, Li T (2021) Integration of meta-QTL discovery with omics: towards a molecular breeding platform for improving wheat resistance to Fusarium head blight. Crop J 9(4):739–749. https://doi.org/10.1016/j.cj.2020.10.006
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The authors are grateful to the Indian Council of Agricultural Research, Government of India, for supporting this research under the ICAR-NBPGR-DBT Wheat Network Project (No. BT/Ag/Network/Wheat/2019-20).
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SK, DS, AK, GPS and AKS were involved in conceptualization.DS, AK, AS, PS, AS, ZAM, AKP and AY were involved in writing—original draft preparation.DS, AK, PS, NB, UK, AKP, SJ, MP, RRM, PB, DCM, NB, MCY and KBG were involved in writing—review and revision.AS, AS, PS, ZAM, AY, UK, RRM, KBG, PB, DCM, NB, SK and MCY visualization.SK, NB, AKS and GPS were involved in supervision.
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Sharma, D., Kumari, A., Sharma, P. et al. Meta-QTL analysis in wheat: progress, challenges and opportunities. Theor Appl Genet 136, 247 (2023). https://doi.org/10.1007/s00122-023-04490-z
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DOI: https://doi.org/10.1007/s00122-023-04490-z