تعداد نشریات | 19 |
تعداد شمارهها | 379 |
تعداد مقالات | 3,114 |
تعداد مشاهده مقاله | 4,219,403 |
تعداد دریافت فایل اصل مقاله | 2,826,353 |
Association mapping of morpho-physiological traits in bread wheat under drought-stressed and non-stressed conditions | ||
Iranian Journal of Genetics and Plant Breeding | ||
دوره 11، شماره 1 - شماره پیاپی 21، مرداد 2022، صفحه 35-52 اصل مقاله (975.64 K) | ||
نوع مقاله: Research paper | ||
شناسه دیجیتال (DOI): 10.30479/ijgpb.2023.18854.1343 | ||
نویسنده | ||
Farzad Ahakpaz* | ||
Department of Agronomy and Plant Breeding, Miandoab Branch, Islamic Azad University, Miandoab, Iran. | ||
تاریخ دریافت: 10 خرداد 1402، تاریخ بازنگری: 02 تیر 1402، تاریخ پذیرش: 17 تیر 1402 | ||
چکیده | ||
Drought is one of the main abiotic stresses limiting wheat growth and productivity worldwide. The main objective of this work was to determine population structure and marker-trait association (MTA) of 13 morpho-physiological traits of bread wheat for drought-tolerance breeding. To this end, twenty-five diverse wheat cultivars and promising lines were genotyped using AFLP. The phenotype evaluation steps of studding wheat genotypes were performed under normal and drought-stress conditions during 3 years. Low heritability estimates were obtained for spike length, heading date (DTH), and shoot biomass (24.87-28.8%) while, a high heritability was observed for the number of kernels per spike (KPS) (89.21-90.55%). The results exhibited high polymorphic level ranged from 84.62 to 100%, proving that AFLP method can be an effective tool in assessing genetic variability in any wheat breeding programs. Population structure analysis showed five subpopulations with at least 65% membership ancestry to their allocated sub-clusters, which was highly consistent with the results of cluster analysis. Mixed linear method association analysis identified 66 significant MTAs with p-values 10−06 to 10−04, justifying 7.8 to 38.7% of the phenotypic variation, observed under both environmental conditions. There were two pleiotropic markers for grain yield (GY) and KPS under normal and one pleiotropic marker for GY, thousand kernel weight (TKW) and KPS under stress conditions. The common MTAs were detected for DTH, plant height, peduncle length, and TKW under both environmental conditions. The identified linked markers with GY and its components in this study could be desirable candidate genes for future studies and marker assisted selection to develop drought-tolerant genotypes in wheat breeding programs. | ||
کلیدواژهها | ||
Bread wheat؛ Drought tolerance؛ Marker-trait association؛ Structure analysis | ||
عنوان مقاله [English] | ||
نقشه ارتباطی صفات مورفوفیزیولوژیکی گندم نان تحت شرایط تنش خشکی و بدون تنش | ||
نویسندگان [English] | ||
فرزاد آهک پز | ||
گروه زراعت و اصلاح نباتات، دانشگاه آزاد اسلامی، واحد میاندوآب، میاندوآب، ایران. | ||
چکیده [English] | ||
خشکی یکی از اصلیترین تنش های غیرزیستی است که رشد و بهره وری گندم را در سراسر جهان محدود میکند. هدف اصلی این پژوهش تعیین ساختار جمعیت و نقشه ارتباطی 13 صفت مورفو-فیزیولوژیکی گندم نان جهت اصلاح تحمل به خشکی بود. بدین منظور، 25 رقم و لاین امیدبخش گندم با استفاده از نشانگرهای AFLP مورد بررسی قرار گرفتند. ژنوتیپ های گندم تحت شرایط عادی و تنش خشکی به مدت 3 سال بررسی شدند. وراثتپذیری پایینی برای طول سنبله، تاریخ خوشهدهی و زیستتوده اندام هوایی (87/24-8/28٪) بدست آمد، در حالیکه، برای تعداد دانه در سنبله (21/89-55/90٪) وراثتپذیری بالایی مشاهده شد. نتایج سطح بالای چندشکلی از 62/84 تا 100 را نشان داد که ثابت میکرد روش AFLP میتواند ابزاری موثر در برنامههای اصلاحی گندم باشد. تجزیه ساختار جمعیت، پنج زیرجمعیت با حداقل 65 درصد عضویت در زیرجمعیتها را نشان داد که تطابق بالایی با نتایج حاصل از تجزیه خوشهای داشت. تجزیه ارتباط به روش خطی مختلط، 66 MTA معنیدار با مقادیر p-value از 6-10 تا 4-10 را شناسایی کرد که 8/7 تا 7/38 درصد از تغییرات فنوتیپی را در هر دو شرایط محیطی مورد مطالعه توجیه میکرد. دو نشانگر پلیوتروپیک برای عملکرد دانه و تعداد دانه در سنبله در شرایط عادی و یک نشانگر پلیوتروپیک برای عملکرد دانه، وزن هزاردانه و تعداد دانه در سنبله در شرایط تنش شناسایی شد. MTAهای مشترک برای تاریخ خوشهدهی، ارتفاع بوته، طول پدانکل و وزن هزاردانه در هر دو شرایط محیطی بدست آمد. نشانگرهای شناسایی شده مرتبط با عملکرد دانه و اجزای آن در این مطالعه میتوانند کاندیدای مطلوب برای مطالعات آتی و انتخاب به کمک نشانگر جهت توسعه ژنوتیپهای مقاوم به خشکی در برنامههای اصلاحی گندم باشند | ||
کلیدواژهها [English] | ||
ارتباط نشانگر-صفت, تجزیه ساختار, تحمل خشکی, گندم نان | ||
مراجع | ||
Abou-Elwafa S. F. (2016). Association mapping for drought tolerance in barley at the reproductive stage. Comptes Rendus Biologies, 339: 51-59. Abou-Elwafa S., and Shehzad T. (2020). Genetic diversity, GWAS and prediction for drought and terminal heat stress tolerance in bread wheat (Triticum aestivum L.). Genetic Resources and Crop Evolution, 68: 711-728. Ahmed H., Iqbal M., Iqbal M., Zeng Y., Ullah A., Iqbal M., Raza H., Yar M., Sarwar N., Imran M., and Hussain S. (2021). Genome-wide association mapping for stomata and yield indices in bread wheat under water limited conditions. Agronomy, 11: 1646. Ahmed H., Zeng Y., Iqbal M., Rashid M., Raza H., Ullah A., Ali M., Yar M., and Shah A. (2022). Genome-wide association mapping of bread wheat genotypes for sustainable food security and yield potential under limited water conditions. PLoS One, 17(9): e0274147. Alqudaha A., Sallam A., Baenziger P., and Borner A. (2020). GWAS: Fast-forwarding gene identification and characterization in temperate cereals: lessons from Barley–A review. Journal of Advanced Research, 22: 119-135. Archangi A., Heidari B., and Mohammadi Nejad G. (2019). Association between seed yield-related traits and cDNA-AFLP markers in cumin (Cuminum cyminum) under drought and irrigation regimes. Industrial Crops and Products, 133: 276-283. Ayalew H., Liu H., Borner A., Kobiljski B., Liu C., and Yan G. (2018). Genome-wide association mapping of major root length QTLs under PEG induced water stress in wheat. Frontiers in Plant Science, 9: 1759-1763. Bac-Molenaar J., Granier C., Keurentjes J., and Vreugdenhil D. (2016). Genome-wide association mapping of time-dependent growth responses to moderate drought stress in Arabidopsis. Plant, Cell and Environment, 39: 88-102. Ballesta P., Mora F., and Del Pozo A. (2019). Association mapping of drought tolerance indices in wheat: QTL-rich regions on chromosome 4A. Scientia Agricola, 77(2): 1-8. Balta H., Karakas O., Senturk F., Ertugrul F., Hasancebi S., Aydin Y., Akan K., Mert Z., Turet M., and Altinkut A. (2014). Identification of an AFLP marker linked with yellow rust resistance in wheat (Triticum aestivum L.). Turkish Journal of Biology, 38: 371-379. Bijalwan P., Sharma M., and Kaushik P. (2022). Review of the effects of drought stress on plants: A systematic approach. Preprints, 202202.0014(1): 1-21. Bennani S., Birouk A., Jlibene M., Sanchez-Garcia M., Nsarellah N., Gaboun F., and Tadesse W. (2022). Drought-tolerance QTLs associated with grain yield and related traits in spring bread wheat. Plants, 11: 986. Bhatta M., Shamanin V., Shepelev S., Baenziger P., Pozherukova V., Pototskaya I., and Morgounov A. (2020). Marker-trait associations for enhancing agronomic performance, disease resistance, and grain quality in synthetic and bread wheat accessions in western Siberia. Genes, Genomes, Genetics, 9(12): 4209-4222. Bhatta M., Shamanin V., Shepelev S., Baenziger P., Pozherukova V., Pototoskaya I., and Morgounov A. (2019). Genetic diversity and population structure analysis of synthetic and bread wheat accessions in Western Siberia. Journal of Applied Genetics, 60: 283-289. Bhatta M., Morgounov A., Belamkar V., and Baenziger P. S. (2018). Genome-wide association study reveals novel genomic regions for grain yield and yield-related traits in drought-stressed synthetic hexaploid wheat. International Journal of Molecular Sciences, 19(10): 3011. Bradbury P., Zhang Z., Kroon D., Casstevens T., Ramdoss Y., and Buckler E. (2007). TASSEL: Software for association mapping of complex traits in diverse samples. Bioinformatics, 23: 2633-2635. Dadras A., Sabouri H., Mohammadi Nejad G., Sabouri A., and Shoai-Deylami M. (2014). Association analysis, genetic diversity and structure analysis of tobacco based on AFLP markers. Molecular Biology Reports, 41(5): 3317-3329. Dalal A., Attia Z., and Moshelion M. (2017). To produce or to survive: how plastic is your crop stress physiology? Frontiers in Plant Science, 8: 2067. Dodig D., Zoric M., Kobiljski B., Savic J., Kandic V., Quarrie S., and Barnes J. (2012). Genetic and association mapping study of wheat agronomic traits under contrasting water regimes. International Journal of Molecular Sciences, 13: 6167-6188. Earl D. A., and Vonholdt B. M. (2012). Structure Harvester: a website and program for visualizing Structure output and implementing the Evanno method. Conserv. Genetics Research, 4: 359-361. Ebrahimi F., Majidi M., Arzani A., and Mohammadi Nejad G. (2017). Association analysis of molecular markers with traits under drought stress in safflower. Crop and Pasture Science, 68: 167-175. Eid M. (2009). Estimation of heritability and genetic advance of yield traits in wheat (Triticum aestivum L.) under drought condition. International Journal of Genetics and Molecular Biology, 1(7): 115-120. Ejaz M., Qidi Z., Gaisheng Z., Na N., Huiyan Z., and Qunzhua W. (2015). Analysis of genetic diversity identified by amplified fragment length polymorphism marker in hybrid wheat. Genetics and Molecular Research, 14(3): 8935-8946. El-Esawi M., Al-Ghamdi A., Ali H., Alayafi A., Witczak J., and Ahmad M. (2018). Analysis of genetic variation and enhancement of salt tolerance in French Pea (Pisum Sativum L.). International Journal of Molecular Sciences, 19: 2433. Soumya P., Burridge A., Singh N., Batra R., Pandey R., Kalia S., Rai V., and Edwards K. (2021). Population structure and genome-wide association studies in bread wheat for phosphorus efficiency traits using 35K Wheat Breeder’s Affymetrix array. Scientific Reports, 11: 7601. Evanno G., Regnaut S., and Goudet J. (2005). Detecting the number of clusters of individuals using the software Structure: a simulation study. Molecular Ecology, 14: 2611-2620. Firouzian A., Shafeinia A., Ghaffary S., Mohammadi V., and Sadat S. (2023). Terminal heat tolerance in bread wheat determined by agronomical traits and SSR markers. Journal of Plant Growth Regulation, 42: 2041-2052. Food and Agriculture Organization of the United Nations (FAO), Faostat (2021). Gao L., Meng C., Yi T., Xu K., Cao H., Zhang S., Yang X., and Zhao Y. (2021). Genome-wide association study reveals the genetic basis of yield- and quality-related traits in wheat. BMC Plant Biology, 21: 144. Giordani W., Scapim C., Ruas P., Ruas C., Soto R., Coan M., Fonseca I., and Goncalves L. (2019). Genetic diversity, population structure and AFLP markers associated with maize reaction to southern rust. Bragantia, 78(2): 183-196. Govta, N., Polda, I., Sela, H., Cohen Y., Beckles D., Korol A., Fahima T., Saranga Y., and Krugman T. (2022). Genome-wide association study in bread wheat identifies genomic regions associated with grain yield and quality under contrasting water availability. International Journal of Molecular Sciences, 23: 10575. Gouy M., Rousselle Y., Thong Chane A., Anglade A., Royaert S., Nibouche S., and Costet L., (2015). Genome wide association mapping of agro-morphological and disease resistance traits in sugarcane. Euphytica, 202: 269-284. Guo Z., Yang W., Chang Y., Ma X., Tu H., and Xiong F. (2018). Genome-wide association studies of image traits reveal genetic architecture of drought resistance in rice. Molecular Plant, 11(6): 789-805. Guo J., Zhang Y., Shi W., Zhang B., Zhang J., Xu Y., Cheng X., Cheng K., Zhang X., Hao C., and Cheng S. (2015). Association analysis of grain-setting rates in apical and basal spikelets in bread wheat (Triticum aestivum L.). Frontiers in Plant Science, 6: 1029. Gupta S., Kumari K., Muthamilarasan M., Parida S., and Prasad M. (2014). Population structure and association mapping of yield contributing agronomic traits in foxtail millet. Plant Cell Reports, 33(6): 881-893. Gupta M., Verma B., Kumar N., Chahota R., Rathour R., Sharma S., Bhatia S., and Sharma T. (2012). Construction of intersubspecific molecular genetic map of lentil based on ISSR, RAPD and SSR markers. Journal of Genetics, 91: 279-287. Hardy O. J., and Vekemans X. (2002). SPAGeDi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Molecular Ecology Notes, 2(4): 618-20. Hartl D. L., and Clark A. G. (1989). Principles of population genetics. (2nd Ed.), Sinauer Associates is an Imprint of Oxford University Press, pp. 672. Hu P., Zheng Q., Luo Q., Teng W., Li H., Li B., and Li Z. (2021). Genome-wide association study of yield and related traits in common wheat under salt-stress conditions. BMC Plant Biology, 21: 27. Jamali S. H., Mohammadi A., and Sadeghzadeh B. (2017). Association mapping for morphological traits relevant to registration of barley varieties. Spanish Journal of Agricultural Research, 15(4): 1-13. Jones C., Edwards K., Castaglion S., Winfield M., Sala F., Van de Wiel C., Bredemeijer G., and Vosman B. (1997). Reproducibility testing of RAPD, AFLP and SSR markers in plants by a network of European laboratories. Moleculare Breeding, 3: 381-390. Kang Y., Sakiroglu M., Krom N., Stanton‐Geddes J., Wang M., and Lee Y. C. (2015). Genome‐wide association of drought‐related and biomass traits with HapMap SNPs in Medicago truncatula. Plant Cell Environironment, 38: 1997-2011. Khalid M., Afzal F., Gul A., Amir R., Subhani A., Ahmed Z., Mahmood Z., Xia X., Rasheed A., and He Z. (2019). Molecular characterization of 87 functional genes in Wheat diversity panel and their association with phenotypes under well-watered and water-limited conditions. Frontiers in Plant Science, 10: 717. Kumar S., Ambreen H., Murali T., Bali S., Agarwal M., Kumar A., Goel S., and Jagannath A. (2015). Assessment of genetic diversity and population structure in a global reference collection of 531 accessions of Carthamus tinctorius L. (safflower) using AFLP markers. Plant Molecular Biology 33: 1299-1313. Kumar K., Anjoy P., Sahu S., Durgesh K., Das A., Tribhuvan K., Sevanthi A., Joshi R., Jain P., Rao A., and Gaikwad K. (2022). Single trait versus principal component based association analysis for flowering related traits in pigeonpea. Scientific Reports, 12: 10453. Lakew B., Henry R., Ceccarelli S., Grando S., Eglinton J., and Baum M. (2013). Genetic analysis and phenotypic associations for drought tolerance in Hordeum spontaneum introgression lines using SSR and SNP markers. Euphytica, 189: 9-29. Lewontin R. C. (1972). The apportionment of human diversity. Evolutionary Biology, Vol. 6, Springer US, 381-398. Lin Y., Yi X., Tang S., Chen W., Wu F., Yang X., Jiang X., Shi H., Ma J., Chen G., Chen G., Zheng Y., Wei Y., and Liu Y. (2019). Dissection of phenotypic and genetic variation of drought-related traits in diverse Chinese wheat landraces. Plant Genome, 12: 190025. Liu J., Huang L., Wang C., Liu Y., Hong Z., Wang Z., Xiang L., Zhong X., Gong F., Zheng Y., Liu D., and Wu B. (2019). Genome-wide association study reveals novel genomic regions associated with high grain protein content in wheat lines derived from wild emmer wheat. Frontiers in Plant Science, 10: 464. Liu S., and Qin F. (2022). Genome-wide association analyses to identify SNPs related to drought tolerance. In: Yoshida, T. (Eds.) Abscisic Acid. Methods in Molecular Biology, Vol. 2462, Humana, New York, NY. Lv T., Harris A., Liu Y., Liu T., Liang R., Ma Z., and Su X. (2021). Population genetic structure and evolutionary history of Psammochloa villosa (Trin.) Bor (Poaceae) revealed by AFLP marker. Ecology and Evolution, 11(15): 10258-10276. Mangini G., Blanco A., Nigro D., Signorile M., and Simeone R. (2021). Candidate genes and quantitative trait loci for grain yield and seed size in durum wheat. Plants, 10: 312. Marzougui S., Kharrat M., and Younes M. (2019). Marker-trait associations of yield related traits in bread wheat (Triticum aestivum L.) under a semi-arid climate. Czech Journal of Genetics and Plant Breeding, 55: 138-145. Mathew I., Shimelis H., Shayanowako A., Laing M., and Chaplot V. (2019). Genome-wide association study of drought tolerance and biomass allocation in wheat. Plos One, 14(12): 1-21. Maulana F., Huang W., Anderson J., and Ma X. (2020). Genome-wide association mapping of seedling drought tolerance in winter wheat. Frontiers Plant Science, 11: 573786. Merida-Garcia R., Bentley A., Galvez S., Dorado G., Solis I., Ammar K., and Hernandez P. (2020). Mapping agronomic and quality traits in elite durum wheat lines under differing water regimes. Agronomy, 10: 144. Mohammadi R., Etminan A., and shoshtari L. (2018). Agro-physiological characterization of durum wheat genotypes under drought conditions. Experimental Agriculture, 55(3): 484-499. Mohammadi Maibody A., and Golkar P. (2019). Application of DNA molecular markers in plant breeding (review article). Plant Genetic Researches, 6(1): 1-30. Mwadzingeni L., Shimelis H., Rees D., and Tsilo T. (2017). Genome-wide association analysis of agronomic traits in wheat under drought-stressed and non-stressed conditions. Plos One, 12(2): 1-13. Negisho K., Shibru S., Matros A., Pillen K., Ordon F., and Wehner G. (2022) Association mapping of drought tolerance indices in Ethiopian durum wheat (Triticum turgidum ssp. durum). Frontiers in Plant Science, 13: 838088. Nei M. (1973). Analysis of gene diversity in subdivided populations. In: Proceedings of the National Academy of Sciences of the United States of America, USA, 70: 3321-3323. Nyquist W. (1991). Estimation of heritability and prediction of selection response in plant populations. Critical Reviews in Plant Sciences, 10: 235-322. Pask A., Pietragalla J., Mullan D., and Reynolds M. (2012). Physiological Breeding II: A Field Guide to Wheat Phenotyping. Mexico, CIMMYT. Paun O., and Schonswetter P. (2012). Amplified fragment length polymorphism: an invaluable fingerprinting technique for genomic, transcriptomic, and epigenetic studies. Methods in Molecular Biology, 862: 75-87. Peakall R., and Smouse P. (2012). GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics, 28: 2537-2539. Pritchard J., Stephens M., and Donnelly P. (2000). Inference of population structure using multi-locus genotype data. Genetics, 155: 945-959. Qaseem M., Qureshi R., Muqaddasi Q., Shaheen H., Kousar R., and Roder M. (2018). Genome-wide association mapping in bread wheat subjected to independent and combined high temperature and drought stress. Plos One, 13(6): 1-22. Rabieyan E., Bihamta M., Moghaddam M., Mohammadi V., and Alipour H. (2022) 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: 831. Reshma R., and Das D. N. (2021). Advances in animal genomics. In: Mondal S., and Singh R. (Eds.), Molecular markers and its application in animal breeding, 123-140. Ritchie S. W., Nguyen H. T., and Holady A. S. (1990). Leaf water content and gas-exchenge parameters of two wheat genotypes differing in drought resistance. Crop Science, 30: 105-111. Roldan-Ruiz I., Dendauw J., Bockstaele E., Depicker A., and Loose M. (2000). AFLP markers reveal high polymorphic rates in ryegrasses (Lolium spp.). Molecular Breeding, 6: 125-134. Roncallo P., Beaufort V., Larsen A., Dreisigacker S., and Echenique V. (2019). Genetic diversity and linkage disequilibrium using SNP (KASP) and AFLP markers in a worldwide durum wheat (Triticum turgidum L. var durum) collection. Plos One, 14(6): 1-33. Rufo R., Alvaro F., Royo C., and Soriano J. M. (2019). From landraces to improved cultivars: Assessment of genetic diversity and population structure of Mediterranean wheat using SNP markers. Plos One, 14(7): 1-19. Saeed A., and Darvishzadeh R. (2016). Genetic diversity in a minicore collection of Cicer accessions using amplified fragment length polymorphism (AFLP). Archives of Agronomy and Soil Science, 12: 1711-1721. Saeed A., and Darvishzadeh R. (2017). Association analysis of biotic and abiotic stressesresistance in chickpea (Cicer spp.) using AFLP markers. Biotechnology and Biotechnological Equipment, 4: 698-708. Saghai-Maroof M., Soliman K., Jorgensen R., and Allard R. (1984). Ribosomal DNA spacer-length polymorphisms in barley: Mendelian inheritance, chromosomal location, and population dynamics. Proceedings of the National Academy of Sciences of the United States of America, 81: 8014-8018. Said A., MacQueen A., Shawky H., Reynolds M., Juenger T., and Soda M. (2022). Genome-wide association mapping of genotype-environment interactions affecting yield-related traits of spring wheat grown in three watering regimes. Environmental and Experimental Botany, 194: 104740. Sallam A., Alqudah A. M., Dawood M., Baenziger P. S., and Borner A. (2019). Drought stress tolerance in wheat and barley: Advances in physiology, breeding and genetics research. International Journal of Molecular Sciences, 20: 1-36. Sehgal D., Autrique E., Singh R., Ellis M., Singh S., and Dreisigacker S. (2017). Identification of genomic regions for grain yield and yield stability and their epistatic interactions. Scientific Reports, 7: 41578. Segura V., Vilhjalmsson B. J., Platt A., Korte A., Seren U., Long Q., and Nordborg M. (2012). An efficient multi-locus mixed-model approach for genome-wide association studies in structured populations. Nature Genetics, 44(7): 825-30. Serba D. D., and Yadav R. S. (2016). Genomic tools in pearl millet breeding for drought tolerance: status and prospects. Frontiers in Plant Science, 7: 1724. Shamuyarira K., Shimelis H., Tapera T., and Tsilo T. (2019). Genetic advancement of newly developed wheat populations under drought-stressed and non-stressed conditions. Journal of Crop Science and Biotechnology, 22(2): 169-176. Sukumaran S., Reynolds M. P., and Sansaloni C. (2018a). Genome-wide association analyses identify QTL hotspots for yield and component traits in durum wheat grown under yield potential, drought, and heat stress environments. Frontiers in Plant Science, 9: 81. Sukumaran S., Lopes M., Dreisigacker S., and Reynolds M. (2018b). Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number. Theoretical and Applied Genetics, 131: 985-998. Sun J., Poland J. A., Mondal S., Crossa J., Juliana P., Singh R., Rutkoski J., Jannink J., Crespo-Herrera L., Velu G., Huerta-Espino J., and Sorrells M. (2019). High-throughput phenotyping platforms enhance genomic selection for wheat grain yield across populations and cycles in early stage. Theoretical and Applied Genetics, 132: 1705-1720. Thabet G., Moursi S., Karam A., Graner A., and Alqudah M. (2018). Genetic basis of drought tolerance during seed germination in barley. Plos One, 13(11): 1-21. Thomas S. G. (2017). Novel Rht-1 dwarfing genes: tools for wheat breeding and dissecting the function of DELLA proteins. Journal of Experimental Botany, 68(3): 354-358. Touzy G., Lafarge S., Redondo E., Lievin V., Decoopman X., Gouis J., and Praud S. (2022). Identification of QTLs affecting post-anthesis heat stress responses in European bread wheat. Theoretical and Applied Genetics, 135: 947-964. Varshney R., Chabane K., Hendre P., Aggarwal R., and Graner A. (2007). Comparative assessment of EST-SSR, EST-SNP and AFLP markers for evaluation of genetic diversity and conservation of genetic resources using wild, cultivated and elite barleys. Plant Science, 173: 638-649. Verslues P. E., Lasky J. R., Juenger T. E., Liu T. W., and Kumar M. N. (2014). Genome‐wide association mapping combined with reverse genetics identifies new effectors of low water potential‐induced proline accumulation in Arabidopsis. Plant Physiology, 164: 144-159. Vos P., Hogers R., Bleeker M., Reijens M., Lee T., Hornes M., Friters A., Pot J., Paleman J., Kuiper M., and Zabeau M. (1995). AFLP: a new technique for DNA fingerprinting. Nucleic Acids Research, 21: 4407-4414. Vos-Fels K., Qian L., Parra-Londono S., Uptmoor R., Frisch M., Keeble-Gagnere G., Appels R., and Snowdon R. J. (2017). Linkage drag constrains the roots of modern wheat. Plant, Cell and Environment, 40(5): 717-25. Wang X., Luo G., Yang W., Li Y., Sun J., Zhan K., Liu D., and Zhang A. (2017). Genetic diversity, population structure and marker-trait associations for agronomic and grain traits in wild diploid wheat Triticum urartu. BMC Plant Biology, 17: 112. Wei P., Feng H., Feng Z., Li C., Liu Z., Wang Y., Ji R., Zou T., and Ji S. (2009). Identification of AFLP markers linked to Ms, a genetic multiple allele inherited male-sterile gene in Chinese cabbage. Breeding Science, 59: 333-339. Yang R. C., Jana S., and Clark J. M. (1991). Phenotypic diversity and associations of some potentially drought response characters in durum wheat. Crop Science, 31: 1484-1491. Yu J., Pressoir G., Briggs W. H., Bi I. V., Yamasaki M., Doebley J. F., McMullen M. D., Gaut B. S., Nielsen D. M., Holland J. B., Kresovich S., Buckler E. S., and Holland J. B. (2006). A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics, 38: 203-208. Zhang P., Zhong K., Shahid M., and Tong H. (2016). Association analysis in Rice: From application to utilization. Frontiers in Plant Science, 7: 1202. Zhu Q., Zhang X., Ejaz M., Zhang G., Wang S., Song Q., Yang S., and Zhang L. (2013). Analysis of three wheat cytoplasmic male sterile lines mitochondrial DNA by AFLP. Chinese Journal of Biotechnology, 29: 646-656. Zhu Z., Chen L., Zhang W., Yang L., Zhu W., Li J., Liu Y., Tong H., Fu L., Liu J., Rasheed A., Xia X., He Z., Hao Y., and Gao C. (2020) Genome-wide association analysis of fusarium head blight resistance in chinese elite wheat lines. Frontiers in Plant Science, 11: 206. | ||
آمار تعداد مشاهده مقاله: 316 تعداد دریافت فایل اصل مقاله: 163 |