نقشه‎یابی نواحی ژنومی کنترل‎کننده ویژگی‎های زراعی جمعیت هاپلوئید مضاعف جو تحت شرایط نرمال و تنش شوری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه اصلاح نباتات و بیوتکنولوژی، دانشکده کشاورزی، دانشگاه زابل، زابل، ایران

2 گروه اصلاح نباتات و بیوتکنولوژی، دانشکده کشاورزی، دانشگاه زابل، زابل، ایران

3 بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی خراسان رضوی، سازمان تحقیقات، آموزش و ترویج کشاورزی، مشهد، ایران

چکیده

به‎منظور شناسایی نواحی ژنومی کنترل‎کننده صفات اگرومورفولوژیک و نشانگرهای مرتبط با آن‎ها تحت شرایط نرمال و تنش شوری، آزمایشی با 136 لاین هاپلوئید مضاعف جو و والدین آن‎ها (Nure و Tremois) در قالب طرح آلفا لاتیس با دو تکرار در سال زراعی1400-1399 در مرکز تحقیقات کشاورزی زابل انجام شد. صفات تعداد پنجه در بوته، تعداد سنبله در بوته، تعداد دانه در سنبله، طول ریشک، طول میانگره، تعداد گره، ارتفاع بوته، وزن هزار دانه و عملکرد دانه اندازه‌گیری شدند. تأثیر ژنوتیپ برای همه صفات مورد بررسی معنی‎دار بود و بیشترین همبستگی بین عملکرد دانه با تعداد پنجه و تعداد سنبله در بوته مشاهده شد. تجزیه QTL به روش نقشه‌یابی فاصله‎ای مرکب برای شرایط نرمال و تنش و میانگین آن‎ها به صورت جداگانه انجام گرفت. در مجموع 24 جایگاه واجد QTL شناسایی شد که 8 تا 16 درصد از واریانس فنوتیپی (R2) را توجیه نمودند. بالاترین مقدار LOD برای صفت تعداد دانه در سنبله و روی کروموزوم 2H در شرایط تنش شوری بود. از 7 QTL بزرگ اثر شناسایی شده در این مطالعه، واضح‎ترین QTL مربوط به تعداد سنبله در بوته (Qng2Hma) روی کروموزوم 2H در مجاورت نشانگر E42M38_235-2H بود که 16 درصد از واریانس فنوتیپی را توجیه نمود. تنها یک QTL (Qtgw1H) برای وزن هزار دانه متصل به مارکر WMC1E8 به‎عنوان QTL پایدار شناخته شد. این مناطق ژنومی شناسایی‎شده پس از اعتبار سنجی در شرایط محیطی و زمینه‎های ژنتیکی متفاوت می‎توانند در برنامه‌های به‎نژادی انتخاب به کمک مارکر برای تحمل به شوری در جو مورد استفاده قرار گیرند.

کلیدواژه‌ها


عنوان مقاله [English]

Mapping genomic regions controlling agronomic characteristics of doubled haploid population of barley under normal and salinity stress conditions

نویسندگان [English]

  • Moussa khammari 1
  • Mahmoud Solouki 2
  • Barat Ali Fakheri 2
  • Reza Aghnoum 3
  • Nafiseh Mahdinezhad 2
  • Leila Mehravaran 2
1 PhD Student, Department of Plant Breeding and Biotechnology, Faculty of Agriculture, University of Zabol, Zabol, Iran
2 Department of Plant Breeding and Biotechnology, Faculty of Agriculture, University of Zabol, Zabol, Iran
3 Field and Horticultural Crops Research Department, Khorasan Razavi Agricultural and Natural Resources Research and Education Center, AREEO, Mashhad, Iran
چکیده [English]

Introduction: Salinity is one of the main obstacles to increasing crop yield. The most severe problems in soil salinity occur in arid and semiarid regions. Barley (Hordeum vulgare L.) is widely planting in the arid and semiarid regions. It is the fourth most important cereal crop worldwide, and it has a long history as a model for genetic studies. It is the most salt tolerant cereal. Salt tolerance in crop plants is a genetic and physiological complex trait and is controlled by several quantitative trait loci. Both genetic diversity and the adaptation to a broad spectrum of micro-ecological conditions including water availability, temperature, soil type and altitude have strongly influenced the development of salt tolerance in barley.
Materials and Methods: In order to identify genomic regions controlling the agro-morphological characteristics and markers linked to them under normal and salinity stress conditions, an experiment with 136 double haploid lines of barley and their parents (Nure and Tremois) was conducted based on alpha lattice design with two replications at the Agricultural Research Center of Zabol, during 2020-2021 crop year. Agronomic traits were including tiller number per plant, spike number per plant, grain number per spike, awn length, internode length, node number, plant height, 1000-grain weight and grain yield. The combined analysis of variance, correlation coefficients between the traits and descriptive statistics calculated for normal and salt stress conditions. The data were analyses by the SAS (ver. 9.2) statistical software. QTL analysis was conducted by composite interval mapping (CIM) method using QTL Cartographer v2.5 for each of the normal and stress conditions and their averages separately (with threshold value (LOD) 2.5, minimum distance 2 cM between QTL).
Result and Discussion: The combined analysis of variance indicated significant differences among the genotypes for all studied traits. This indicates high levels of genetic diversity in this population. Since the population is double haploid lines, therefore, the diversity observed in this population is often caused by additive effects. Maximum correlations were observed between grain yield with tiller number, as well as spike number per plant. The high correlation between the traits may be due to the similar loci controlling QTLs or due to their linkage. According to the table of descriptive statistics, the studied double haploids are representative of all the possible double haploids resulting from the crossing of Tremois and Nure, and the studied traits are controlled by the additive effects of genes. In total, 24 QTL loci were identified for the studied traits: 9 QTLs were obtained under normal conditions, 8 QTLs were identified under stress conditions, and 7 QTLs were identified in the average of the two conditions. These QTLs explained 8 to 16% of the phenotypic variance (R2). The LOD value ranged of 2.5 - 5.04. The highest and lowest LOD values were related to QTLs of number of seeds per spike on chromosome 2H and number of nodes under stress conditions. Regarding marker-assisted selection, the stability of QTLs across different environments and genetic backgrounds is of utmost importance. Out of the 24 identified QTLs, only the QTL associated with the thousand seed weight trait (Qtgw1H) demonstrated stability, making it suitable for marker selection. The markers identified for this trait not only exhibit close linkage with the gene responsible for the thousand seed weight trait but also possess high heritability and are easily detectable. The markers associated with stable QTLs can be utilized in future studies.
Conclusion: Based on the findings of this research, significant statistical differences were observed among all genotypes. Transgressive segregation, both high and low, was evident across all traits. Two traits, namely the number of tillers per plant and the number of spikes per plant, exhibited QTLs at the same location, indicating a linkage and correlation between these traits. Among the 7 major QTLs identified in this study, the most prominent one was associated with the number of spikes per plant (Qng2Hma) on chromosome 2H, linked with marker E42M38_235-2H, which accounted for 16% of the phenotypic variance. Only one QTL (Qtgw1H) for 1000-grain weight, linked with marker WMC1E8, was identified as a stable QTL. These genomic regions, once validated across various genetic backgrounds and environments for salinity tolerance in barley, can be utilized in marker-assisted breeding.

کلیدواژه‌ها [English]

  • Grain yield
  • QTL mapping
  • Salt tolerance
  • Yeald components
Aghnoum, R., Marcel, T.C., Johrde, A., Pecchioni, N., Schweizer, P. and Niks, R.E. 2010. Basal host resistance of barley to powdery mildew: Connecting quantitative trait loci and candidate genes. Molecular Plant-Microbe Interactions, 23, pp.91-10. doi: 10.1094/mpmi-23-1-0091
Ahmadi-Ochtapeh, H., Soltanloo, H., Ramazanpour, S.S., Naghavi, M.R., Nikkhah, H.R. and Yoosefi Rad, S. 2015. QTL mapping for salt tolerance in barley at seedling growth stage. Biologia Plantarum, 59(2), pp.283-290. doi: 10.1007/s10535-015-0496-z
Aminfar, Z., Dadmehr, M., Korouzhdehi, B., Siahsar, B.A. and Heidari, M. 2011. Determination ofchromosomes that control physiological traits associated with salt tolerance in barley at the seedling stage. African Journal of. Biotechnology, 10(44), pp.8794-8799. doi: 10.5897/ajb10.1538
Baghizadeh, A., Taeei, A.R. and Naghavi, M.R. 2007. QTL analysis for some agronomic traits in
Barley (Hordeum vulgare L.). Journal of Agriculture and Biology, 2, pp.372-374.
Barati, A., Moghadam, M., Mohammadi, S.A., Ghazvini, H.A. and Sadeghzadeh, B. 2017. Identification of QTLs associated with agronomic and physiological traits under salinity stress in barley. Journal of Agricultural Science and Technology, 19, pp.185-200.
Dudley, J.W. 1997. Quantitative genetic and plant breeding. Advanced Agronomy, 59, pp.1-23.
Fakheri, B.A. and Mehravaran, L. 2013. Locating QTLs Controlling Agronomic Traits of “Steptoe×Morex” Derived Double Haploid Population of Barley under Drought Stress Conditions. Iranian Journal of Field Crop Science, 44(1), pp.47-57. [In Persian]. doi: 10.22059/ijfcs.2013.30483
Fakheri, B.A. and Mehravaran, L. 2014. QTLs mapping of physiological and biochemical traits of barley under drought stress condition. Iranian Journal of Sciences, 4(60), pp.367-386. [In Persian].
FAO. 2008. FAOSTAT. Land and plant nutrition management service. Available at http://www.fao.org/ag/Agl/agll/spuch.
FAO. 2013. FAOSTAT. The state of food and agriculture, Food system for better nutrition. http://faostat.fao.org/site.
Farokhzadeh, S., Fakheri, B.A., Mahdinejad, N., Tahmasebi, S. and Mirsoleimani, A. 2019. Mapping QTLs of flag leaf morphological and physiological traits related to aluminum tolerance in wheat (Triticum aestivum L.). Physiology and Molecular Biology of Plants, 25(4), pp. 975-990. doi: 10.1007/s12298-019-00670-8
Farokhzadeh, S., Fakheri, B.A., Mahdinejad, N., Tahmasebi, S., Mirsoleimani, A. and Heidari, B. 2020. Mapping QTLs associated with grain yield and yield-related traits under aluminum stress in bread wheat. Crop and Pasture Science, 71(5), pp.429-444. doi: 10.1071/cp19511
Feizi, M., Solouki, M., Sadeghzadeh, B., Fakheri, B. and Mohammadi, S.A. 2019. QTL Mapping for Higher Seed Zn Concentration and Content in Barley using SSR Markers. Journal of Crop Breeding, 11(30), pp.58-67. [In Persian].
Francia, E., Rizza, F., Cattivelli, L., Stanca, A., Galiba, G., Toth, B., Hayes, P., Skinner, J. and Pecchioni, N. 2004. Two loci on chromosome 5H determine low-temperature tolerance in a ‘Nure’(winter)בTremois’(spring) barley map. Theoretical and Applied Genetics, 108, pp.670-680. doi: 10.1007/s00122-003-1468-9
Francia, E., Barabaschi, D., Tondelli, A., Laidò, G., Rizza, F., Stanca, A.M. and Pecchioni, N. 2007. Fine mapping of a HvCBF gene cluster at the frost resistance locus Fr-H2 in barley. Theoretical and Applied Genetics, 115(8), pp.1083-1091. doi: 10.1007/s00122-007-0634-x
Francia, E., Tondelli, A., Rizza, F., Badeck, F.W., Nicosia, O.L.D., Akar, T. and Pecchioni, N. 2011. Determinants of barley grain yield in a wide range of Mediterranean environments. Field Crops Research, 120(1), pp.169-178. doi: 10.1016/j.fcr.2010.09.010
Hosseinirad, F., Jorjani, E., Sabouri, H. and Gholamalipor Alamdari, E. 2021. Detection of quantitative genes controlling of metabolic in rice seedling under salinity stress. Environmental Stresses in Crop Sciences, 13(4), pp.1271-1280. [In Persian]. doi: 10.22077/escs.2020.2344.1607
Jabbari, M., Fakheri, B.A., Aghnoum, R., Mahdi Nezhad, N. and Ataei, R. 2018. GWAS analysis in spring barley (Hordeum vulgare L.) for morphological traits exposed to drought. PloS one, 13(9), e0204952. doi: 10.1371/journal.pone.0204952
Khalili, M. and Mohammadian, R. 2016. Identifying QTLs associated with salinity tolerance in early stages of barley germination. Crop Biotechnology, 13, pp. 41-55. doi: 20.1001.1.22520783.1395.6.13.4.6
Koochakpour, Z., Solouki, M., Fakheri, B.A., Aghnoum, R., Mahdi Nezhad, N.
and Jabbari, M. 2021. Identification of genomic loci controlling phenologic and morphologic traits in barley (Hordeum vulgare L.) genotypes using association analysis. Iranian Journal of Crop Sciences, 22(4), pp.291-304. [In Persian]. doi: 10.52547/abj.22.4.291
Laidò, G., Barabaschi, D., Tondelli, A., Gianinetti, A., Stanca, A.M., Li Destri Nicosia, O. and Pecchioni, N. 2009. QTL alleles from a winter feed type can improve malting quality in barley. Plant Breeding, 128(6), pp.598-605. doi: 10.1111/j.1439-0523.2009.01636.x
Mahdinejad, N., Omidi, M., Jalalkamali, M.R., Naghavi, M.R. and Fakheri, B.A. 2014. QTL analysis of some phenological and morphological traits in Babax and Seri M82 recombinant inbred line population of wheat during salinity stress. Modern Genetics Journal, 9(2), pp.207-218. [In Persian].
Mohammadi, M. and Baom, M. 2008. QTL analysis for morphologhical traits in the population of
double Haploide barley. Journal of Science and Technology of Agriculture and Natural Resources, 45(1), pp.111-120. [In Persian].
Munns, R., James, R.A. and Lauchli, A. 2006. Approaches to increasing the salt tolerance of wheat and other cereals. Journal of Experimental Botany, 57, pp.1025-1043. doi: 10.1093/jxb/erj100
Munns, R. and Tester, M. 2008. Mechanisms of salinity tolerance. Annual Review of Plant Biology, 59: 651-681.
Mwando, E., Han, Y., Angessa, T.T., Zhou, G., Hill, C.B., Zhang, X.Q. and Li, C. 2020. Genome-wide association study of salinity tolerance during germination in barley (Hordeum vulgare L.). Frontiers in Plant Science, 11, p.118. doi: 10.1146/annurev.arplant.59.032607.092911
Peighambari, S.A., Yazdi Samadi, B., Nabipour, A., Charmet, G. and Sarrafi, A. 2005. QTL analysis for agronomic traits in barley doubled haploids population grown in Iran. Plant Science, 169, pp.1008-1013. doi: 10.1016/j.plantsci.2005.05.018
Phillinpa, P.C. 1998. The language of gene interaction. Genetics, 149, pp.1171-1167. doi: 10.1093/genetics/149.3.1167
Pitman, M.G. and Lauchli, A. 2002. Global impact of salinity and agricultural ecosystems. In: Lauchli A, Luttge U (eds.). Salinity: Environment-Plants-Molecules. Dordrecht: Kluwer, pp.3-20. doi: 10.1007/0-306-48155-3
Rabiei, B., Mardani, K.H., Sabouri, H. and Sabouri, A. 2014. The effect of rice chromosome 1 on
traits associated with drought and salinity tolerance at germination and seedling stages. Seed and Plant Improve Journal, 30, pp.1-16. [In Persian]. doi: 10.22092/spij.2017.111197
Saade, S., Negrão, S., Plett, D., Garnett, T. and Tester, M. 2018. Genomic and genetic studies of abiotic stress tolerance in barley. In The barley genome. Springer, Cham. pp. 259-286. doi: 10.1007/978-3-319-92528-8_15
Siahsar B.A., Taleii, A.R., Peighambari, S.A. and Naghavi, M.R. 2008. Mapping QTL of forage quality-related traits of barley. Iranian Journal of Field Crop Science, 40, pp.35-45. [In Persian]. doi: 10.1007/978-3-642-10616-3_8
Tondelli, A., Francia, E., Barabaschi, D., Aprile, A., Skinner, J.S., Stockinger, E.J. and Pecchioni, N. 2006. Mapping regulatory genes as candidates for cold and drought stress tolerance in barley. Theoretical and Applied Genetics, 112(3), pp.445-454. doi: 10.1007/s00122-005-0144-7
Tondelli, A., Francia, E., Visioni, A., Comadran, J., Mastrangelo, A.M., Akar, T. and Pecchioni, N. 2014. QTLs for barley yield adaptation to Mediterranean environments in the ‘Nure’בTremois’ biparental population. Euphytica, 197(1), pp.73-86. doi: 10.1007/s10681-013-1053-5
Wang, S., Basten, C.J. and Zeng, Z.B. 2007. Windows QTL cartographer 2.5. Department of Statistics, North Carolina State University, Raleigh, NC. Available at http://statgen.ncsu.edu/qtlcart/WQTLCart.htm.
Wolfe, M.S., Baresel, J.P., Desclaux, D., Goldringer, I., Hoad, S., Kovacs, G., Loschenberger, F., Miedaner, H., Stergard, E. and Lammerts, T. 2008. Developments in breeding cereals for organicagriculture. Euphytica, 163, pp.323-346. doi: 10.1007/s10681-008-9690-9
Xue, D.W., Chen, M.C. and Zhang, G.P. 2009a. Mapping of QTLs associated with cadmium tolerance and accumulation during seedling stage in rice (Oryza sativa L.). Euphytica, 165(3), pp.587-596. doi: 10.1007/s10681-008-9785-3
Xue, D.W., Huang, Y., Zhang, X., Wei, K., Westcott, S., Li, C., ... and Lance, R. 2009b. Identification of QTLs associated with salinity tolerance at late growth stage in barley. Euphytica, 169(2), pp.187-196. doi: 10.1007/s10681-009-9919-2
Xue, W., Yan, J., Zhao, G., Jiang, Y., Cheng, J., Cattivelli, L. and Tondelli, A. 2017. A major QTL on chromosome 7HS controls the response of barley seedling to salt stress in the Nure×Tremois population. BMC Genetics, 18(1), pp.1-15. doi: 10.1186/s12863-017-0545-z
Yadav, R.S., Bidinger, F.R., Hash, C.T., Yadav, Y.P., Yadav, O.P., Bhatnagar, S.K. and Howarth, C.J. 2003. Mapping and characterization of QTL×E interactions for traits determining grain and Stover yield in pearl millet. Theoretical and Applied Genetics, 106, pp.512-520. doi: 10.1007/s00122-002-1081-3
دوره 5، شماره 3 - شماره پیاپی 11
این شماره با همکاری انجمن علمی دانش کشاورزی گرمسیری ایران منتشر شده است
اسفند 1402
صفحه 689-706
  • تاریخ دریافت: 21 آذر 1400
  • تاریخ بازنگری: 16 دی 1400
  • تاریخ پذیرش: 18 دی 1400