Association mapping of phenological traits and major regulatory genes (Vrn and Ppd) in Iranian wheat germplasm
Sima Fatanatvash A , Ehsan Rabieyan B and Hadi Alipour
A *
A
B
Abstract
Wheat (Triticum aestivum L.) is an important main crop widely cultivated in various environments. Since wheat phenology determines adaptation to different environments, it is important to understand the genes underlying developmental variation.
Using Iranian wheat varieties and landraces characterised for grain yield (GY) and phenological traits, the study aimed to assess potential quantitative trait loci and genes.
In this study, one single-locus genome-wide association study (SL-GWAS) method (MLM) in conjunction with three multi-locus genome-wide association study (ML-GWAS) approaches (mrMLM, pKWmEB, and 3VmrMLM) was conducted by using a set of 260 Iranian wheat landraces and cultivars, which were each genotyped for 44,044 single nucleotide polymorphism (SNP) markers.
Three main SNPs with high pleiotropic effect (rs64682, rs27840, rs31006) were discovered along with the functional marker Ppd D1 D001-KASP, associated with days to booting (DB), days to flowering (DF), growing degree days (GDD) of days to booting (GDDDB), GDD of days to flowering (GDDDF), and grain-filling period (GF) and mapped on chromosomes 2A, 2B and 5B by both methods. Two genes, SAUR50 (TraesCS3B02G471300) and alcohol dehydrogenase-like 7 (TraesCS7B02G046700), possibly involved in plant development, grain-filling, and flowering, are candidate genes for phenological traits.
Our results identified markers that were significantly associated with more than one phenological trait by both SL-GWAS and ML-GWAS methods and mapped at genomic loci 2A, 2B, 5B, and 2D. Among them, a functional marker named Ppd-D1 associated with flowering time was identified on chromosome 2D.
Taken together, these novel significant SNP markers and candidate genes identified in this study will contribute to the accuracy of future breeding programs through marker-assisted selection.
Keywords: candidate genes, grain yield, growth degree day, functional markers, photoperiod sensitivity, quantitative trait loci, single and multi-locus GWAS, wheat adaptation.
References
Ali M, Danting S, Wang J, Sadiq H, Rasheed A, He Z, Li H (2022) Genetic diversity and selection signatures in synthetic-derived wheats and modern spring wheat. Frontiers in Plant Science 13, 877496.
| Crossref | Google Scholar | PubMed |
Alipour H, Abdi H (2021) Interactive effects of vernalization and photoperiod loci on phenological traits and grain yield and differentiation of Iranian wheat landraces and cultivars. Journal of Plant Growth Regulation 40(5), 2105-2114.
| Crossref | Google Scholar |
Alipour H, Bihamta MR, Mohammadi V, Peyghambari SA, Bai G, Zhang G (2017) Genotyping-by-sequencing (GBS) revealed molecular genetic diversity of Iranian wheat landraces and cultivars. Frontiers in Plant Science 8, 1293.
| Crossref | Google Scholar | PubMed |
Alipour H, Bai G, Zhang G, Bihamta MR, Mohammadi V, Peyghambari SA (2019) Imputation accuracy of wheat genotyping-by-sequencing (GBS) data using barley and wheat genome references. PLoS ONE 14(1), e0208614.
| Crossref | Google Scholar | PubMed |
Alipour H, Abdi H, Rahimi Y, Bihamta MR (2021) Dissection of the genetic basis of genotype-by-environment interactions for grain yield and main agronomic traits in Iranian bread wheat landraces and cultivars. Scientific Reports 11(1), 17742.
| Crossref | Google Scholar | PubMed |
Alomari DZ, Alqudah AM, Pillen K, von Wirén N, Röder MS (2021) Toward identification of a putative candidate gene for nutrient mineral accumulation in wheat grains for human nutrition purposes. Journal of Experimental Botany 72(18), 6305-6318.
| Crossref | Google Scholar | PubMed |
Arjona JM, Royo C, Dreisigacker S, Ammar K, Villegas D (2018) Effect of Ppd-A1 and Ppd-B1 allelic variants on grain number and thousand kernel weight of durum wheat and their impact on final grain yield. Frontiers in Plant Science 9, 888.
| Crossref | Google Scholar | PubMed |
Arjona JM, Villegas D, Ammar K, Dreisigacker S, Alfaro C, Royo C (2020) The effect of photoperiod genes and flowering time on yield and yield stability in durum wheat. Plants 9(12), 1723.
| Crossref | Google Scholar | PubMed |
Atamian HS, Creux NM, Brown EA, Garner AG, Blackman BK, Harmer SL (2016) Circadian regulation of sunflower heliotropism, floral orientation, and pollinator visits. Science 353(6299), 587-590.
| Crossref | Google Scholar | PubMed |
Berkman PJ, Visendi P, Lee HC, Stiller J, Manoli S, Lorenc MT, Lai K, Batley J, Fleury D, Šimková H, Kubaláková M, Weining S, Doležel J, Edwards D (2013) Dispersion and domestication shaped the genome of bread wheat. Plant Biotechnology Journal 11(5), 564-571.
| Crossref | Google Scholar | PubMed |
Bhati PK, Juliana P, Singh RP, Joshi AK, Vishwakarma MK, Poland J, Govindan V, Shrestha S, Crespo-Herrera L, Mondal S, Huerta-Espino J, Kumar U (2022) Dissecting the genetic architecture of phenology affecting adaptation of spring bread wheat genotypes to the major wheat-producing zones in India. Frontiers in Plant Science 13, 920682.
| Crossref | Google Scholar | PubMed |
Bilgrami SS, Ramandi HD, Shariati V, Razavi K, Tavakol E, Fakheri BA, Mahdi Nezhad N, Ghaderian M (2020) Detection of genomic regions associated with tiller number in Iranian bread wheat under different water regimes using genome-wide association study. Scientific Reports 10(1), 14034.
| Crossref | Google Scholar | PubMed |
Blackmore S, Wortley AH, Skvarla JJ, Rowley JR (2007) Pollen wall development in flowering plants. New Phytologist 174(3), 483-498.
| Crossref | Google Scholar | PubMed |
Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23(19), 2633-2635.
| Crossref | Google Scholar | PubMed |
Browning SR (2008) Missing data imputation and haplotype phase inference for genome-wide association studies. Human Genetics 124, 439-450.
| Crossref | Google Scholar | PubMed |
Browning BL, Browning SR (2009) A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. The American Journal of Human Genetics 84(2), 210-223.
| Crossref | Google Scholar | PubMed |
Chao S, Dubcovsky J, Dvorak J, Luo M-C, Baenziger SP, Matnyazov R, Clark DR, Talbert LE, Anderson JA, Dreisigacker S, Glover K, Chen J, Campbell K, Bruckner PL, Rudd JC, Haley S, Carver BF, Perry S, Sorrells ME, Akhunov ED (2010) Population- and genome-specific patterns of linkage disequilibrium and SNP variation in spring and winter wheat (Triticum aestivum L.). BMC Genomics 11, 727.
| Crossref | Google Scholar |
Chaurasia S, Singh AK, Songachan LS, Sharma AD, Bhardwaj R, Singh K (2020) Multi-locus genome-wide association studies reveal novel genomic regions associated with vegetative stage salt tolerance in bread wheat (Triticum aestivum L.). Genomics 112(6), 4608-4621.
| Crossref | Google Scholar | PubMed |
Chen S, Wang J, Deng G, Chen L, Cheng X, Xu H, Zhan K (2018) Interactive effects of multiple vernalization (Vrn-1)- and photoperiod (Ppd-1)-related genes on the growth habit of bread wheat and their association with heading and flowering time. BMC Plant Biology 18, 374.
| Crossref | Google Scholar |
Cheng B, Gao X, Cao N, Ding Y, Gao Y, Chen T, Xin Z, Zhang L (2020) Genome-wide association analysis of stripe rust resistance loci in wheat accessions from southwestern China. Journal of Applied Genetics 61, 37-50.
| Crossref | Google Scholar | PubMed |
Crossa J, Burgueno J, Dreisigacker S, Vargas M, Herrera-Foessel SA, Lillemo M, Singh RP, Trethowan R, Warburton M, Franco J, Reynolds M, Crouch JH, Ortiz R (2007) Association analysis of historical bread wheat germplasm using additive genetic covariance of relatives and population structure. Genetics 177(3), 1889-1913.
| Crossref | Google Scholar | PubMed |
Cui Y, Zhang F, Zhou Y (2018) The application of multi-locus GWAS for the detection of salt-tolerance loci in rice. Frontiers in Plant Science 9, 1464 https://doi.org/10.3389/fpls.2018.01464.
| Google Scholar | PubMed |
Díaz A, Zikhali M, Turner AS, Isaac P, Laurie DA (2012) Copy number variation affecting the Photoperiod-B1 and Vernalization-A1 genes is associated with altered flowering time in wheat (Triticum aestivum). PLoS ONE 7(3), e33234.
| Crossref | Google Scholar | PubMed |
Distelfeld A, Tranquilli G, Li C, Yan L, Dubcovsky J (2009) Genetic and molecular characterization of the VRN2 loci in tetraploid wheat. Plant Physiology 149(1), 245-257.
| Crossref | Google Scholar | PubMed |
Dowla MANNU, Edwards I, O’Hara G, Islam S, Ma W (2018) Developing wheat for improved yield and adaptation under a changing climate: optimization of a few key genes. Engineering 4(4), 514-522.
| Crossref | Google Scholar |
Edae EA, Bowden RL, Poland J (2015) Application of population sequencing (POPSEQ) for ordering and imputing genotyping-by-sequencing markers in hexaploid wheat. G3 Genes|Genomes|Genetics 5(12), 2547-2553.
| Crossref | Google Scholar | PubMed |
El Hassouni K, Belkadi B, Filali-Maltouf A, Tidiane-Sall A, Al-Abdallat A, Nachit M, Bassi FM (2019) Loci controlling adaptation to heat stress occurring at the reproductive stage in durum wheat. Agronomy 9(8), 414.
| Crossref | Google Scholar |
Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology 14(8), 2611-2620.
| Crossref | Google Scholar |
Grogan SM, Brown-Guedira G, Haley SD, McMaster GS, Reid SD, Smith J, Byrne PF (2016) Allelic variation in developmental genes and effects on winter wheat heading date in the US Great Plains. PLoS ONE 11(4), e0152852.
| Crossref | Google Scholar | PubMed |
Hanif U, Alipour H, Gul A, Jing L, Darvishzadeh R, Amir R, Munir F, Ilyas MK, Ghafoor A, Siddiqui SU, St. Amand P, Bernado A, Bai G, Sonder K, Rasheed A, He Z, Li H (2021) Characterization of the genetic basis of local adaptation of wheat landraces from Iran and Pakistan using genome-wide association study. The Plant Genome 14(3), e20096.
| Crossref | Google Scholar | PubMed |
Hyles J, Bloomfield MT, Hunt JR, Trethowan RM, Trevaskis B (2020) Phenology and related traits for wheat adaptation. Heredity 125(6), 417-430.
| Crossref | Google Scholar | PubMed |
Jamil M, Ali A, Gul A, Ghafoor A, Napar AA, Ibrahim AMH, Naveed NH, Yasin NA, Mujeeb-Kazi A (2019) Genome-wide association studies of seven agronomic traits under two sowing conditions in bread wheat. BMC Plant Biology 19, 149.
| Crossref | Google Scholar |
Jin Y, Zhang C, Liu W, Tang Y, Qi H, Chen H, Cao S (2016) The alcohol dehydrogenase gene family in melon (Cucumis melo L.): bioinformatic analysis and expression patterns. Frontiers in Plant Science 7, 670.
| Crossref | Google Scholar | PubMed |
Kang HM, Zaitlen NA, Wade CM, Kirby A, Heckerman D, Daly MJ, Eskin E (2008) Efficient control of population structure in model organism association mapping. Genetics 178(3), 1709-1723.
| Crossref | Google Scholar | PubMed |
Kobayashi F, Tanaka T, Kanamori H, Wu J, Katayose Y, Handa H (2016) Characterization of a mini core collection of Japanese wheat varieties using single-nucleotide polymorphisms generated by genotyping-by-sequencing. Breeding Science 66(2), 213-225.
| Crossref | Google Scholar | PubMed |
Kumar D, Chhokar V, Sheoran S, Singh R, Sharma P, Jaiswal S, Iquebal MA, Jaiswar A, Jaisri J, Angadi UB, Rai A, Singh GP, Kumar D, Tiwari R (2020a) Characterization of genetic diversity and population structure in wheat using array based SNP markers. Molecular Biology Reports 47, 293-306.
| Crossref | Google Scholar | PubMed |
Kumar D, Kumar A, Chhokar V, Gangwar OP, Bhardwaj SC, Sivasamy M, Prasad SVS, Prakasha TL, Khan H, Singh R, Sharma P, Sheoran S, Iquebal MA, Jaiswal S, Angadi UB, Singh G, Rai A, Singh GP, Kumar D, Tiwari R (2020b) Genome-wide association studies in diverse spring wheat panel for stripe, stem, and leaf rust resistance. Frontiers in Plant Science 11, 748.
| Crossref | Google Scholar | PubMed |
Law CN, Sutka J, Worland AJ (1978) A genetic study of day-length response in wheat. Heredity 41(2), 185-191.
| Crossref | Google Scholar |
Li N, Zheng H, Cui J, Wang J, Liu H, Sun J, Liu T, Zhao H, Lai Y, Zou D (2019) Genome-wide association study and candidate gene analysis of alkalinity tolerance in japonica rice germplasm at the seedling stage. Rice 12(1), 24.
| Crossref | Google Scholar |
Li M, Zhang Y-W, Zhang Z-C, Xiang Y, Liu M-H, Zhou Y-H, Zuo J-F, Zhang H-Q, Chen Y, Zhang Y-M (2022) A compressed variance component mixed model for detecting QTNs and QTN-by-environment and QTN-by-QTN interactions in genome-wide association studies. Molecular Plant 15(4), 630-650.
| Crossref | Google Scholar | PubMed |
Lippert C, Listgarten J, Liu Y, Kadie CM, Davidson RI, Heckerman D (2011) FaST linear mixed models for genome-wide association studies. Nature Methods 8(10), 833-835.
| Crossref | Google Scholar | PubMed |
Liu J, Xu Z, Fan X, Zhou Q, Cao J, Wang F, Ji G, Yang L, Feng B, Wang T (2018) A genome-wide association study of wheat spike related traits in China. Frontiers in Plant Science 9, 1584.
| Crossref | Google Scholar | PubMed |
Lozada DN, Mason RE, Babar MA, Carver BF, Guedira G-B, Merrill K, Arguello MN, Acuna A, Vieira L, Holder A, Addison C, Moon DE, Miller RG, Dreisigacker S (2017) Association mapping reveals loci associated with multiple traits that affect grain yield and adaptation in soft winter wheat. Euphytica 213, 222.
| Crossref | Google Scholar |
Luo J, Zhou J-J, Zhang J-Z (2018) Aux/IAA gene family in plants: molecular structure, regulation, and function. International Journal of Molecular Sciences 19(1), 259.
| Crossref | Google Scholar | PubMed |
Malik P, Kumar J, Singh S, Sharma S, Meher PK, Sharma MK, Roy JK, Sharma PK, Balyan HS, Gupta PK, Sharma S (2021a) Single-trait, multi-locus and multi-trait GWAS using four different models for yield traits in bread wheat. Molecular Breeding 41, 46.
| Crossref | Google Scholar |
Malik P, Kumar J, Sharma S, Sharma R, Sharma S (2021b) Multi-locus genome-wide association mapping for spike-related traits in bread wheat (Triticum aestivum L.). BMC Genomics 22(1), 597.
| Crossref | Google Scholar |
Marza FE, Bai G-H, Carver BF, Zhou W-C (2006) Quantitative trait loci for yield and related traits in the wheat population Ning7840 × Clark. Theoretical and Applied Genetics 112, 688-698.
| Crossref | Google Scholar | PubMed |
Matthies IE, Van Hintum T, Weise S, Röder MS (2012) Population structure revealed by different marker types (SSR or DArT) has an impact on the results of genome-wide association mapping in European barley cultivars. Molecular Breeding 30, 951-966.
| Crossref | Google Scholar |
Mourad AMI, Belamkar V, Baenziger PS (2020) Molecular genetic analysis of spring wheat core collection using genetic diversity, population structure, and linkage disequilibrium. BMC Genomics 21, 434.
| Crossref | Google Scholar |
Muhammad A, Li J, Hu W, Yu J, Khan SU, Khan MHU, Xie G, Wang J, Wang L (2021) Uncovering genomic regions controlling plant architectural traits in hexaploid wheat using different GWAS models. Scientific Reports 11(1), 6767.
| Crossref | Google Scholar | PubMed |
Ogbonnaya FC, Rasheed A, Okechukwu EC, Jighly A, Makdis F, Wuletaw T, Hagras A, Uguru MI, Agbo CU (2017) Genome-wide association study for agronomic and physiological traits in spring wheat evaluated in a range of heat prone environments. Theoretical and Applied Genetics 130, 1819-1835.
| Crossref | Google Scholar | PubMed |
Pradhan AK, Kumar S, Singh AK, Budhlakoti N, Mishra DC, Chauhan D, Mittal S, Grover M, Kumar S, Gangwar OP, Kumar S, Gangwar OP, Kumar S, Gupta A, Bhardwaj SC, Rai A, Singh K (2020) Identification of QTLs/defense genes effective at seedling stage against prevailing races of wheat stripe rust in India. Frontiers in Genetics 11, 572975.
| Crossref | Google Scholar | PubMed |
Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155(2), 945-959.
| Crossref | Google Scholar |
Rabieyan E, Alipour H (2021) NGS-based multiplex assay of trait-linked molecular markers revealed the genetic diversity of Iranian bread wheat landraces and cultivars. Crop & Pasture Science 72(3), 173-182.
| Crossref | Google Scholar |
Rabieyan E, Bihamta MR, Moghaddam ME, Mohammadi V, Alipour H (2022a) Imaging-based screening of wheat seed characteristics towards distinguishing drought-responsive Iranian landraces and cultivars. Crop & Pasture Science 73(4), 337-355.
| Crossref | Google Scholar |
Rabieyan E, Bihamta MR, Moghaddam ME, Mohammadi V, Alipour H (2022b) Morpho-colorimetric seed traits for the discrimination, classification and prediction of yield in wheat genotypes under rainfed and well-watered conditions. Crop & Pasture Science 74(4), 294-311.
| Crossref | Google Scholar |
Rabieyan E, Bihamta MR, Moghaddam ME, Mohammadi V, Alipour H (2022c) Genome-wide association mapping and genomic prediction for pre-harvest sprouting resistance, low α-amylase and seed color in Iranian bread wheat. BMC Plant Biology 22(1), 300.
| Crossref | Google Scholar |
Rabieyan E, Bihamta MR, Moghaddam ME, Mohammadi V, Alipour H (2022d) Genome-wide association mapping and genomic prediction of agronomical traits and breeding values in Iranian wheat under rain-fed and well-watered conditions. BMC Genomics 23(1), 831.
| Crossref | Google Scholar |
Rabieyan E, Bihamta MR, Moghaddam ME, Mohammadi V, Alipour H (2022e) Genome-wide association mapping for wheat morphometric seed traits in Iranian landraces and cultivars under rain-fed and well-watered conditions. Scientific Reports 12(1), 17839.
| Crossref | Google Scholar |
Rabieyan E, Bihamta MR, Moghaddam ME, Alipour H, Mohammadi V, Azizyan K, Javid S (2023) Analysis of genetic diversity and genome-wide association study for drought tolerance related traits in Iranian bread wheat. BMC Plant Biology 23(1), 431.
| Crossref | Google Scholar | PubMed |
Rabieyan E, Darvishzadeh R, Alipour H (2024) Genetic analyses and prediction for lodging-related traits in a diverse Iranian hexaploid wheat collection. Scientific Reports 14(1), 275.
| Crossref | Google Scholar | PubMed |
Ren H, Gray WM (2015) SAUR proteins as effectors of hormonal and environmental signals in plant growth. Molecular Plant 8(8), 1153-1164.
| Crossref | Google Scholar | PubMed |
Ren W-L, Wen Y-J, Dunwell JM, Zhang Y-M (2018) pKWmEB: integration of Kruskal–Wallis test with empirical Bayes under polygenic background control for multi-locus genome-wide association study. Heredity 120(3), 208-218.
| Crossref | Google Scholar | PubMed |
Safdar LB, Andleeb T, Latif S, Umer MJ, Tang M, Li X, Liu S, 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. Frontiers in Plant Science 11, 70.
| Crossref | Google Scholar | PubMed |
Schierenbeck M, Alqudah AM, Lohwasser U, Tarawneh RA, Simón MR, Börner A (2021) Genetic dissection of grain architecture-related traits in a winter wheat population. BMC Plant Biology 21, 417.
| Crossref | Google Scholar |
Sheoran S, Jaiswal S, Kumar D, Raghav N, Sharma R, Pawar S, Paul S, Iquebal MA, Jaiswar A, Sharma P, Singh R, Singh CP, Gupta A, Kumar N, Angadi UB, Rai A, Singh GP, Kumar D, Tiwari R (2019) Uncovering genomic regions associated with 36 agro-morphological traits in Indian spring wheat using GWAS. Frontiers in Plant Science 10, 527.
| Crossref | Google Scholar | PubMed |
Si L, Chen J, Huang X, Gong H, Luo J, Hou Q, Zhou T, Lu T, Zhu J, Shangguan Y, Chen E, Gong C, Zhao Q, Jing Y, Zhao Y, Li Y, Cui L, Fan D, Lu Y, Weng Q, Wang Y, Zhan Q, Liu K, Wei X, An K, An G, Han B (2016) OsSPL13 controls grain size in cultivated rice. Nature Genetics 48(4), 447-456.
| Crossref | Google Scholar | PubMed |
Stortenbeker N, Bemer M (2019) The SAUR gene family: the plant’s toolbox for adaptation of growth and development. Journal of Experimental Botany 70(1), 17-27.
| Crossref | Google Scholar | PubMed |
Teaster ND, Keereetaweep J, Kilaru A, Wang Y-S, Tang Y, Tran CNQ, Ayre BG, Chapman KD, Blancaflor EB (2012) Overexpression of fatty acid amide hydrolase induces early flowering in Arabidopsis thaliana. Frontiers in Plant Science 3, 32.
| Crossref | Google Scholar | PubMed |
Trevaskis B (2010) The central role of the VERNALIZATION1 gene in the vernalization response of cereals. Functional Plant Biology 37(6), 479-487.
| Crossref | Google Scholar |
Wang J, Zhang Z (2021) GAPIT version 3: boosting power and accuracy for genomic association and prediction. Genomics, Proteomics & Bioinformatics 19(4), 629-640.
| Crossref | Google Scholar | PubMed |
Wang S-B, Feng J-Y, Ren W-L, Huang B, Zhou L, Wen Y-J, Zhang J, Dunwell JM, Xu S, Zhang Y-M (2016) Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology. Scientific Reports 6(1), 19444.
| Crossref | Google Scholar |
Wani SH, Kumar V, Shriram V, Sah SK (2016) Phytohormones and their metabolic engineering for abiotic stress tolerance in crop plants. The Crop Journal 4(3), 162-176.
| Crossref | Google Scholar |
Yu Y, Zhu D, Ma C, Cao H, Wang Y, Xu Y, Zhang W, Yan Y (2016) Transcriptome analysis reveals key differentially expressed genes involved in wheat grain development. The Crop Journal 4(2), 92-106.
| Crossref | Google Scholar |
Zaitseva OI, Lemesh VA (2015) Allelic composition in the Vrn-A1, Vrn-B1, and Vrn-B3 genes of double haploid lines of hexaploid triticale. Russian Journal of Genetics 51, 653-660.
| Crossref | Google Scholar |
Zhang Y-M, Mao Y, Xie C, Smith H, Luo L, Xu S (2005) Mapping quantitative trait loci using naturally occurring genetic variance among commercial inbred lines of maize (Zea mays L.). Genetics 169(4), 2267-2275.
| Crossref | Google Scholar | PubMed |
