Research Article
Research Advance on Crop Phenotypic Identification by QTL Mapping Associated with Saline-alkaline Tolerance
2 Taonan Research Center, Jilin Academy of Agricultural Sciences, Taonan, 137100, China
Author Correspondence author
Molecular Plant Breeding, 2018, Vol. 9, No. 8 doi: 10.5376/mpb.2018.09.0008
Received: 20 Aug., 2018 Accepted: 10 Sep., 2018 Published: 14 Sep., 2018
Zhang C.X., Li S.F., Jin F.X., Liu W.P., Li W.J., and Li X.H., 2018, Research advance on crop phenotypic identification by QTL mapping associated with saline-alkaline tolerance, Molecular Plant Breeding, 9(8): 60-67 (doi: 10.5376/mpb.2018.09.0008)
Salt-alkali stress is one of the important abiotic stresses affecting crop yield and quality. The QTL mapping associated with crop saline-alkaline tolerance plays an important role in choosing resistant variety. Accurate phenotypic identification is the key to the success of QTL mapping. This research reviewed and discussed the progress of crop phenotypic identification by QTL mapping associated with saline-alkaline tolerance till now, which included materials, medium, stress concentration, stress period, treatment method, measured indicators and evaluation system, etc. Meanwhile, it predicted the prospect of the development of phenotypic identification technique related with crop saline-alkaline tolerance.
Background
Soil salinization has become an important problem in recent agricultural production. The area of saline-alkali soil in China is about 1×109 hm2, tending to increase year by year (Wang et al., 2007; Yang et al., 2009). Salt-alkali stress can inhibit plant growth, decrease plant photosynthetic efficiency, accelerate aging and affect crop yield and quality. The conventional method to improve soil is time and labor consuming of little effect, thus the breeding of variety with saline-alkaline tolerance is the most direct and effective method to solve this problem. Recently, with the rapid development of molecular marker technology, Paterson et al. (1988) firstly used RFLP-marked genetic linkage map to conduct QTL mapping of tomato fruit size. Since then, the study on the QTL mapping method to determine the location of QTL loci in linkage groups based on the analysis of corresponding relationship between genotype and phenotype has begun (Zhao et al., 2014). It is well known that the work of phenotype identification is the easiest to make mistakes. So accurate phenotype identification is the key to the success of QTL mapping associated with stress resistance. In recent years, the methods used by researchers in the identification of crop saline-alkaline tolerance could be divided into the direct and indirect identification methods. The direct identification method is used to observe the morphologic change of plants after salt-alkali stress. The indirect identification method is used to measure a series of physiological and biochemical indexes caused by material changes in the plant physiological metabolic process after salt-alkali stress. The accuracy of stress resistance phenotypic identification is also influenced and restricted by materials, medium, stress concentration, stress period, treatment method, measured indicators and evaluation system, etc. This study reviewed and discussed the crop phenotypic identification of QTL mapping associated with saline-alkaline tolerance at home and abroad in recent years, hoping to provide reference and help for future research in this field.
1 Research Advance on Crop Phenotypic Identification by QTL Mapping Associated with Saline-alkaline Tolerance
1.1 Rice phenotypic identification by QTL mapping associated with saline-alkaline tolerance
Rice is one of the main food crops and its saline-alkaline tolerance is controlled by several genes (Qi et al., 2008). Fore-scholars carried out a great deal of researches on the QTL mapping associated with rice saline-alkaline tolerance and summarized different phenotypic identification methods. The methods mainly including the direct observation method, morphological index detection method as well as physiological and biochemical index detection method.
The direct observation method: Gong et al. (1999) selected DH population and their parents for salt-tolerance evaluation. They were cultured in the greenhouse and stressed by 0.7% NaCl salt solution when the seedlings grew to the third leaf stage. During this period, the survival time of seedlings was determined. Lee et al. (2007) used recombinant inbred line (RIL) F8 & F9 and their parents for phenotypic identification. They were stressed by 0.5% and 0.7% NaCl solution, repectively. F8 seedlings stressed with 0.5% NaCl, were cultured in soil under lighting and stressed by 0.5% NaCl for 2 weeks when the seedlings grew between the second and third leaf stage, then to observe the symptoms after salt stress. F9 seedlings stressed with 0.7% NaCl, cultured in water without lighting for 2 weeks to observe the symptoms after salt stress (1: normal growth~9: seedlings died completely). Qian et al. (2009) used BC2F3 population for salt-tolerance evaluation. The seedlings were treated by 140 mmol/L NaCl until they grew two leaves and one bud. The salt damage grade and survival day were taken as the evaluation indicators of salt tolerance, and the salt damage grade was divided into 5 levels: 1 level (tolerant of high salt)~5 level (sensitive to high salt) (Guo et al., 2004).
The morphological index detection method: Qi et al. (2009) used F3 population and their parents for phenotypic identification. The seeds were stressed by 0.15% Na2CO3 solution every day, the emergence rate and its relative alkali damage rate as the alkali tolerance indicators of rice at the germination stage were both observed after 6 d. Wang et al. (2012) used F2:3 population and their parents for saline-alkaline tolerance evaluation. Some seeds were stressed by 25 mmol/L NaHCO3 solution, and the relative saline-alkaline tolerance indexes of germination potential, germination rate, seedling height, root length, root number, coleoptile length and raw weight were observed on the 3 d and 7 d after germination. The other seeds were firstly forced to germinate by conventional method. Then the seedlings were stressed with 25 mmol/L NaHCO3 solution when they grew two leaves and one bud. A week later, the degree of saline-alkaline damage in leaves was observed, which could be divided into 5 grades: 1 (high tolerance), 3 (tolerance), 5 (medium tolerance), 7 (sensitivity) and 9 (high sensitivity). Li et al. (2016) used BC2F3 population and their parents for the fine mapping. Rice seedlings were watered with 0.15% Na2CO3 solution when they grew two leaves and one bud, and the height of seedlings was observed after 20 d. Cheng et al. (2008a) selected DH population for alkali tolerance identification. Seeds were forced to germinate with the treatment of 0.15% Na2CO3 solution in the incubator. The number of germinated seeds was observed every day to calculate the germination potential, germination rate and germination indexes. Also, the germinated seeds were moved to a sunny place, and the root number, root length, seedling height and seedling dry weight were observed as alkali tolerance indicators. Zheng et al. (2014) used BC2F3 population as test materials. Seeds were treated by 15 mL 1.5% NaCl solution in the culture dish and the relative germination rate, relative seedling height, relative root number and relative root length were observed after 7 d. Liang et al. (2017) selected F6 and F7 population as test materials. The plants of F6 and F7 at the regreening stage were stressed by 6 ds/m NaCl and pH=9.0 alkaline solutions, respectively. The effective panicle number per plant, seed setting rate, thousand seed weight and single plant spike weight were observed as the saline-alkaline tolerance evaluation indexes.
The physiological and biochemical index detection method: Ahmadi and Fotokian (2011) used BC2F5 population and their parents for salt-tolerance identification. Seeds were stressed by 12 ds/m NaCl solution after 10 d of germination, and the concentration of Na+ and K+ as well as Na+/K+ ratio were measured by spectrophotometer two weeks later. Pandit et al. (2010) used F8 population and their parents as basic materials. Seedlings were stressed by 75 mmol/L NaCl solution and the salt concentration was increased little by little. A week later, the solution reached 100 mmol/L NaCl and the concentration of Na+, K+ and Cl- as well as Na+/K+ ratio were measured after 35 d. Xing et al. (2015) used F6 population for saline-alkaline tolerance evaluation. Seeds were treated with 140 mmol/L NaCl and 0.15% Na2CO3 solution until they grew three leaves and one bud. After 12 d of salt-alkali stress, the concentration of Na+ and K+ in the root and overground part as well as Na+/K+ ratio were measured by M410 flamephotometer. Yu et al. (2009) used RIL population as test materials. Seeds were stressed by 0.7% NaCl solution when they grew two leaves and one bud, and the contents of proline, ascorbic acid and protein were measured after 12 d. Wang et al. (2007) used RIL population and their parents as test materials. Seeds were stressed by 150 mmol/L NaCl solution and the concentration of Na+ in the overground part of seedlings after salt treatment were observed as the salt-tolerance index.
The balance of multi-method: Cheng et al. (2012) selected BC2F6 and RIL populations and their parents for salt-tolerance identification. At the second leaf stage, seedlings were stressed by 140 mmol/L NaCl solution and the salt tolerance, survival days, concentration of Na+ and K+ in the root and Na+/K+ ratio were observed. The salt tolerance of plants was divided into 5 grades (1: salt tolerance, 3, 5, 7, 9: salt sensitivity). Masood et al. (2004) used RIL population and their parents for salt-tolerance evaluation. After 17 d of germination, seedlings were stressed by 12 ds/m NaCl solution until the plant died completely. The survival days, dry weight of root and stem, concentration of Na+ and K+ in the overground part and Na+/K+ ratio were observed. Thomson et al. (2010) used RIL population and their parents as basic materials. Some seedlings were stressed by 12 ds/m NaCl solution for 14 d. Other seedlings were firstly stressed by 6 ds/m NaCl solution for 5 d and then by 12 ds/m NaCl solution for 5 d. The damage degree of seedlings (1: high salt tolerance~9: salt sensitivity) were observed, and also, the concentration of Na+ and K+ in the root and leaf, seedling height, the content of chlorophyll in the leaf were measured. Lin et al. (2004) used F3 population for phenotype identification. Seedlings were stressed by 140 mmol/L NaCl solution and the survival days, concentration of Na+ and K+, total content of Na+ and K+ in the root and stem were measured. Wang et al. (2012) used F2:9 population and their parents for phenotype identification. After 7 d of germination, seedlings were treated by 120 mmol/L NaCl solution. The content of Na+ and K+ and stress symptom of seedlings were observed and the salt-tolerance was divided into 5 grades: 0 (seedlings grew normally)~5 (seedlings died completely). Zou et al. (2013) used F2:3 family and their parents as test materials. Seedlings were stressed by 25 mmol/L alkali solution when they grew two leaves and one bud. A week later, the root number, root length, chlorophyll content and relative alkali damage rate were observed as the alkali-tolerance evalution indexes at the seedling stage of rice. Sun et al. (2007) used BC2F8 population for salt-tolerance identification. A group of water-cultured seedlings were stressed by 140 mmol /L NaCl solution when they grew two leaves and one bud. After 10 d, the salt damage level was determined based on SES standard (5 grades: 1: high salt tolerance, 9: high salt sensitity) and the survival days of seedlings were observed. Another group was stressed by 100 mmol/L NaCl solution. After 8 d, the concentration of Na+ and K+ in the overground part and root were measured. Sun et al. (2015) used F2:3 population as test materials. Seedlings after regreening were stressed by 66 mmol/L NaCl solution. The seedling height and tiller number were measured as the indicators of salt stress phenotype identification. Sun et al. (2007) used BC2F8 population as test materials. Seedlings were stressed by 140 mmol/L NaCl solution for 10 d. The salt damage grade of leaf, survival days of seedlings, concentration of Na+ and K+ in the overground part were measured as the salt-tolerance evaluation indexes. Yang et al. (2009) used two-way backcross introgression lines of rice as test materials. Seedlings were stressed by 140 mmol/L NaCl solution when they grew two leaves and one bud. After 10 d, the salt damage grade of leaf, survival days of seedlings, concentration of Na+ and K+ in the overground part as well as those concentrations in the phytotron. Wang et al. (2011) used F2 population and their parents as test materials. The water culture method was adopted for salt-tolerance identification of F2 lines at the germination and seedling stages. At the germination stage, seedlings were treated with 15 mL 1.2% NaCl solution in the culture dish and the germination potential, root number, root length, seedling height and seedling dry weight were measured. At the seedling stage, seedlings were stressed by 0.9% NaCl solution when they grew two leaves and one bud and the salt damage rate was measured after 20 d. Cheng et al. (2008b) used two different doubled haploid populations for identificaiton. Seeds were stressed by 0.15% Na2CO3 alkali solution. The relative germination potential, relative germination rate, relative germination index, relative root number, relative root length, relative seedling height, relative seedling dry weight, relative vigor index, alkali damage rates at the germination stage and early seedling stage were measured as alkali-tolerance indicators.
1.2 Soybean phenotypic identification by QTL mapping associated with saline-alkaline tolerance
Salt-alkali stress is an important factor affecting the growth and development of plants. At present, there are many methods for soybean identification by QTL mapping.
The direct observation method: Lee et al. (2004) selected F2:5 population for salt-tolerance evaluation. Seeds were cultured in sandy soils of two different environments (laboratory and field). After emergence, seedlings were treated with 100 mmol/L NaCl and 4 ds/m salinity solutions, respectively. According to the seedling condition, the salt-tolerance rate of the seedling stage was divided into three grades: 0 (complete death), 3 (yellow appearance), 5 (normal leaf). Chen et al. (2008) used F7:11 population and their parents for salt tolerance evaluation. Seedlings were stressed by 1.2% NaCl and 150 mmol/L NaCl solutions in the laboratory and field, respectively. The damage degree of seedlings was measured as the salt-tolerance evaluation index and the salt-tolerance rate was divided into three grades: 0 (complete death), 3 (partial etiolation of seedlings), 5 (healthy seedlings). Chen et al. (2011) used F7:11 family for phenotype identification. Seedlings were treated by 150 mmol/L NaCl solution when they grew two leaves and one bud and the survival time of each family was regarded as the salt-tolerance index. Li et al. (2010) used F2:3 population for phenotype identification. Seedlings were treated by 250 mmol/L NaHCO3 solution and the leaf wilting degree was observed after 3 d.
The morphological index detection method: Qiu et al. (2011) used soybean backcross introgression lines BC2F4 as materials. Seeds were stressed by 1.75% NaCl solution at the bud stage. The germination rate, germination potential and germination index of each line were calculated based on the germination standard that the bud grew up to half of the seed hilum.
The direct observation method combined with physiological and biochemical index detection method: Tuyen et al. (2010) used F2 population and their parents for alkali-tolerance evaluation. Seeds were stressed by 180 mmol/L NaHCO3 solution after they were sowed for 10 d. Three weeks later, the chlorophyll content and alkali-tolerance rate at the seedling stage were measured (Li et al., 2016) and the alkali-tolerance rate at the seedling stage was divided into 1 (complete death)~5 (normal leaf) according to the seedling condition. Hamwieh et al. (2011) used F6 and F7 population for salt-tolerance evaluation. After 10 d of greenhouse culture, seedlings were stressed by 150 mmol/L NaCl solution. 21 d later, the chlorophyll content and salt-tolerance rate were measured and the salt-tolerance rate was divided into 5 grades (1: complete death~5: healthy leaf) according to the seedling condition.
1.3 Maize phenotypic identification by QTL mapping associated with saline-alkaline tolerance
Maize is the main food crop in the world. Researchers have always attached importance to improving its yield and quality. At present, there are not so many foreign studies on the QTL mapping associated with maize saline-alkaline tolerance. While, domestic researchers have different ways of phenotype identification, mainly divided into the direct observation method and morphological index detection method.
The direct observation method: Ma et al. (2014) used F2:3 population and their parents as basic materials. Seedlings were treated by 100 mmol/L Na2CO3 solution when they grew three leaves and one bud. After 3 d, the alkali-tolerance rate of seedlings was measured as the alkali-tolerance evaluation index according to the seedling condition, divided into 5 grades: 1 (high alkali tolerance), 2 (alkali tolerance), 3 (medium alkali tolerance), 4 (sensitivity), 5 (high sensitivity).
The morphological index detection method: Wang et al. (2012) selected F8 population and their parents for salt-tolerance evaluation. Seedlings were treated by 250 mmol/L NaCl solution when they grew three leaves and one bud. After 7 d, the change rate of seedling height, change rate of raw weight, change rate of dry weight and survival time were measured as the morphological indexes of salt-tolerance identification at the seeding stage of maize. Guan (2012) selected RIL-6 and their parents as test materials. Vermiculite as medium, seeds were cultured for germination in 100 mmol/L NaCl, 25 mmol/L Na2CO3 and no added mediums, repectively. After 7 d, the length of germ and radicle were observed.
The balance of multi-method: Yin et al. (2012) used the selfing line of waxy corn as materials. The corn salt-tolerance at the bud stage and seedling stage were measured, repectively. At the bud stage, the sterilized seeds were put into vermiculite and stressed by 0.5% NaCl solution. The germination rate was measured on the 5th day, and the length of radicle and bud were measure on the 7th day. At the seedling stage, seedlings were stressed by salt when they grew three leaves and one bud. The survival time and survival rate of single plant were observed as the salt-tolerance evaluation indicators.
1.4 Wheat phenotypic identification by QTL mapping associated with saline-alkaline tolerance
The physiological and biochemical index detection method: BC1F5 population and their parents were used as materials for identification. After germination, seedlings were stressed by 150 mmol/L NaCl solution. Ten days later, the concentration of Na+ and K+ were measured by flame method.
The morphological index detection method: Ren et al. (2012) used RIL population and their parents for phenotype identification. The seeds after accelerating germination by water culture method were put onto the net. Seedlings could be transplanted after 6 d as well as stressed by salt. After 15 d, the maximum root length, root dry weight, overground dry weight and gross dry weight were observed and relative values of those traits were calculated as the evaluation criterion of salt-tolerance level. Wu et al. (2007) used F2:3 family as test materials. Seedlings were stressed by 1.5% NaCl solution by water culture method. After 7 d, the germination rate was observed and root length, seedling height and fresh weight were measured. Zhou et al. (2016) used RIL strains as test materials. Seedlings were stressed by 50 mmol/L, 100 mmol/L and 200 mmol/L NaCl solutions respectively. The seedling height, tiller number, maximum root length, root number, overground fresh weight, root fresh weight and total fresh weight were measured as indicators for phenotype identification.
The balance of multi-method: Genc et al. (2010) used DH population and their parents for phenotype identification. Seedlings were stressed by 100 mmol/L NaCl solution. Two weeks later, the concentration of Na+ and K+ in the root and stem, dry weight of plant, tiller number, chlorophyll content and leaf etiolation were measured as the indicators. Leaf etiolation was divided into 5 grades (1: healthy green leaves; 2: yellow leaves emerged; 3: some leaves became yellow; 4: most leaves became yellow; 5: all yellow leaves).
2 Discussion
In the review of all methods of phenotypic identification for QTL mapping of crops, it could be seen that the phenotypic identification technique of rice was more mature at present. Maize was only reported in China and the medium used for phenotypic identification of each crop was relatively similar. Rice and tomato were cultured in water, soybean was cultured in soil or sand and maize was cultured with vermiculite. The trefoil stage was the most important in the stress period, because the seedlings were the most sensitive to the external environment change, and would betterly show the corresponding saline-alkali symptoms, making identification results more accurate in this period. There was no uniform standard of salt and alkali stress concentration, but the set concentration must be able to evaluate the salt tolerance of all the tested populations to the maximum extent. The selection of indicators among the factors affecting the accuracy of phenotypic identification was the most diverse.
In the selection of indicators for phenotype identification of crops salt-alkali tolerance, some researchers selected a single index for evaluation, like Gong et al. (1999), Lee et al. (2007); some selected several indexes for evaluation, like Genc et al. (2010), Hamwieh et al. (2011) and Cheng et al. (2012). It could be found from recent studies that the selection of indicators has gradually developed from a single index to a number of indexes. Multiple indicators could together reflect the saline-alkali tolerance of crops and the results might be more accurate. More widely used indicators include the survival time, ionic concentration, salt-tolerance grade, chlorophyll content, germination potential, germination rate, seedling height, root length, root number, dry and fresh weight, fruit number, etc.
3 Prospect of Study on Crop Phenotypic Identification by QTL Mapping Associated with Saline-alkaline Tolerance
With the increasing cognition of plant genome, the strategy of marker-assisted selection for quantitative trait genes has been optimized, which has greatly promoted the application of QTL mapping and cloning technique in crop breeding (Yang et al., 2007). However, the phenotype of quantitative traits is difficult to identify accurately. It is still relatively lagging behind and not optimistic. Now, there was no uniform standard of saline-alkaline tolerance identification for crops, and the methods of phenotype identification also need improvement and innovation. Since 21st century, the identification of no-damage phenotypes has gradually appeared in people's vision and begun to receive attention. For example, the method for the determination of chlorophyll content was time and labor saving. It could also greatly improve work efficiency when cooperating with perfect identification system. Therefore, only through continuously perfecting the identification of saline-alkali tolerance, it might be possible to realize the fine mapping of crops, successfully clone saline-alkali tolerance genes and contribute to assistant breeding.
Authors’ contributions
ZCX, LSF, JFX, LWP, and LWJ participateed in the witing of the first draft, and the working of the investigation of Chinese reference; LXH established the strategy of reference investigatiion. All authors read and approved the final manuscript.
Acknowledgments
This research is jointly supported by The National Key Research and Development Program of China (Project No. 2016YFD0100103) and Agricultural Science and Technology Innovation Program of Jilin Province (CXGC2017JC001 & CXGC2017TD001).
Ahmadi J., and Fotokian M.H., 2011, Identification and mapping of quantitative trait loci associated with salinity tolerance in rice (Oryza sativa L.) using SSR markers, Iranian Journal of Biotechnology, 9(1): 21-30
Chen H.T., Chen X., and Yu D.Y., 2011, Inheritance analysis andmapping quantitative trait loci (QTLs) associated with salttoler ance during seedling growth in soybean, ZhongguoYouliao Zuowu Xuebao (Chinese Journal of Oil Crop Sciences), 33(3): 231-234
Chen H.T., Cui S.Y., Fu S.X., Gai J.Y., and Yu D.Y., 2008, Identification of quantitative trait loci associated with salt tolerance during seedling growth in soybean (Glycine max L.), Australian Journal of Agricultural Research, 59(12): 1086-1091
https://doi.org/10.1071/AR08104
Cheng H.T., Jiang H., Xue D.W., Guo L.B., Zeng D.L., Zhang G.H., and Qian Q., 2008a, Mapping of QTLs underlying tolerance to alkali at germination and early seedling stages in rice, Zuowu Xuebao (Acta Agronomica Sinica), 34(10): 1719-1727
https://doi.org/10.3724/SP.J.1006.2008.01719
Cheng H.T., Jiang H., Yan M.X., Dong G.J., Qian Q., and Guo L.B., 2008b, QTL-Mapping comparison of tolerance to alkaliat germination period and early seeding stage between two different double haploid populations in rice, Fenzi Zhiwu Yuzhong (Molecular Plant Breeding), 6(3): 439-450
Cheng L.R., Wang Y., Meng L.J., Hu X., Cui Y.R., Sun Y., Zhu L.H., Ali J., Xu J.L., and Li J.K., 2012, Identification of salt-tolerant QTLs with strong genetic background effect using two sets of reciprocal introgression lines in rice, Genome, 55(1): 45-55
https://doi.org/10.1139/g11-075
PMid:22181322
Genc Y., Oldach K., Verbyla A.P., Lott G., Hassan M., Tester M., Wallwork H., and McDonald G.K., 2010, Sodium exclusion QTL associated with improved seedling growth in bread wheat under salinity stress, Theor. Appl. Genet., 121(5): 877-894
https://doi.org/10.1007/s00122-010-1357-y
PMid:20490443
Gong J.M., He P., Qian Q., Shen L.S., Zhu L.H., and Chen S.Y., 1999, Identification of salt-tolerance QTL in rice (Oryza sativa L.), Chinese Science Bulletin, 44(1): 68-71
https://doi.org/10.1007/BF03182889
Guan F.X., 2012, Mapping QTL saline-alkali tolerance during bud and seedling stage using RIL in maize, Thesis for M.S., Yangzhou University, Supervisor: Deng D.X., pp.16-17
Hamwieh A., Tuyen D.D., Cong H., Benitez E.R., Takahashi R., and Xu D.H., 2011, Identification and validation of a major QTL for salt tolerance in soybean, Euphytica, 179: 451-459
https://doi.org/10.1007/s10681-011-0347-8
Lee G.J., Carter-Jr T.E., Villagarcia M.R., Li Z., Zhou X., Gibbs M.O., and Boerma H.R., 2004, A major QTL conditioning salt tolerance in S-100 soybean and descendent cultivars, Theor. Appl. Genet., 109(8): 1610-1619
https://doi.org/10.1007/s00122-004-1783-9
PMid:15365627
Lee S.Y., Ahn J.H., Cha Y.S., Yun D.W., Lee M.C., Ko J.C., Lee K.S., and Eun M.Y., 2007, Mapping QTLs related to salinity tolerance of rice at the young seedling stage, Plant Breeding, 126(1): 43-46
https://doi.org/10.1111/j.1439-0523.2007.01265.x
Li N., Sun J., Wang J.G., Liu H.L., Liang Y.P., Zhao H.W., and Zou D.T., 2016, Mapping of a new major QTL for alkaline tolerance at seedling stage in rice, Fenzi Zhiwu Yuzhong (Molecular Plant Breeding), 14(2): 417-423
Li X.W., Dong Z.M., Zhao H.K., Zhang C.B., and Dong Y.S., 2010, Genetic mapping and QTL analysis in wild soybean by SSR markers, Dongbei Nongye Kexue (Journal of Jilin Agricultural Sciences), 35(3): 15-17
Li W., Pan X.C., Yu H.X., Qi H.D., Mao X.R., Huang S.Y., Wang X.Y., Yin Z.G., Ni Z.Q., Qi Z.M., and Chen Q.S., 2016, QTL mapping for chlorophyll content and candidate gene predictionin soybean, Jiyinzuxue Yu Yingyong Shengwuxue (Genomics and Applied Biology), 35(7): 1793-1799
Liang Y.P., Sun J., Suo Y.N., Liu H.L., Wang J.G., Zheng H.L., Sun X.X., and Zou D.T., 2017, QTL mapping and QTL × Environment interaction analysis of salt and alkali tolerance-related traits in rice (Oryza sativa L.), Zhongguo Nongye Kexue (Scientia Agricultura Sinica), 50(10): 1747-1762
Lin H.X., Zhu M.Z., Yano M., Gao J.P., Liang Z.W., Su W.A., Hu X.H., Ren Z.H., and Chao D.Y., 2004, QTLs for Na+ and K+ uptake of the shoots and roots controlling rice salt tolerance, Theor. Appl. Genet., 108(2): 253-260
https://doi.org/10.1007/s00122-003-1421-y
PMid:14513218
Ma X.J., Jin F.X., Chao Q., Zhang C.X., Yang D.G., and Li X.H., 2014, Identification of QTLs for alkaline tolerance at seedling stage in maize, Yumi Kexue (Journal of Maize Sciences), 22(5): 13-19
Masood M.S., Seij I., Shinwari Z.K., and Anwar R., 2004, Mapping quantitative trait loci (QTLs) for salt tolerance in rice (Oryza sativa L.) using RFLPs, Pak. J. Bot., 36(4): 825-834
Ogbonnaya F.C., Huang S., Steadman E., Livinus E., Dreccer F., Lagudah E.S., and Munns R., eds., 2008, Mapping quantitative trait loci associated with salinity tolerance in synthetic derived backcrossed bread lines, Sydney University Press, Sydney, Australia, pp.1-3
Pandit A., Rai V., Bal S., Sinha S., Kumar V., Chauhan M., Gautam R.K., Singh R., Sharma P.C., Singh A.K., Gaikwad K., Sharma T.R., Mohapatra T., and Singh N.K., 2010, Combining QTL mapping and transcriptome profiling of bulked RILs for identification of functional polymorphism for salttolerance genes in rice (Oryza sativa L.), Mol. Genet. Genomics, 284(2): 121-136
https://doi.org/10.1007/s00438-010-0551-6
PMid:20602115
Paterson A., Lander S., Hewitt J., Peterson S., Lincoln H., and Tanksley S., 1988, Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms, Nature, 335(6192): 721-726
https://doi.org/10.1038/335721a0
PMid:2902517
Qi D.L., Guo G.Z., Lee M.C., Zhang J.G., Cao G.L., Zhang S.Y., Suh S.C., Zhou Q.Y., and Han L.Z., 2008, Identification of quantitative trait loci for the dead leaf rate and the seedling dead rate under alkaline stress in rice, J. Genet. Genomics, 35: 299-305
https://doi.org/10.1016/S1673-8527(08)60043-0
Qi D.L., Li D.L., Yang C.G., Li M.Z., Cao G.L., Zhang G.L., Zhang J.G., Zhou Q.Y., Xu X.Z., Zhang S.Y., and Han L.Z., 2009, Detection of QTL for alkali tolerance at the germination stage in japonica rice, Zhongguo Shuidao Kexue (Chinese Journal of Rice Science), 23(6): 589-594
Qian Y.L., Wang H., Chen M.Y., Zhang L.K., Chen B.R., Cui J.T., Liu H.Y., Zhu L.H., Shi Y.R., Gao Y.M., and Li Z.K., 2009, Detection of salt-tolerant QTL using BC2F3 yield selected introgression lines of rice (Oryza sativa L.), Fenzi Zhiwu Yuzhong (Molecular Plant Breeding), 7(2): 224-232
Qiu P.C., Zhang W.B., Jiang H.W., Liu C.Y., Li C.D., Fan D.M., Zeng Q.L., Han D.W., Hu G.H., and Chen Q.S., 2011, Genetic overlap between salt and low-temperature tolerance loci at germination stage of soybean, Zhongguo Nongye Kexue (Scientia Agricultura Sinica), 44(10): 1980-1988
Ren Y.Zh., Xu Y.H., Gui X.W., Ding J.P., Zhang Q.T., Ma Y.S., and Pei D.L., 2012, QTLs analysis of wheat seedling traitsunder salt stress, Zhongguo Nongye Kexue (Scientia Agricultura Sinica), 45(14): 2793-2800
Sun J., Wang J.G., Liu H.L., Xie D.W., Zheng H.L., Zhao H.W., Zou D.T., and Luan F.S., 2015, Dynamic QTL analysis ofrice seedling height and tiller number under salt stress, Henongxue Bao (Journal of Nuclear Agricultural Sciences), 29(2): 235-237, 239-243
Sun Y., Zang J.P., Wang Y., Zhu L.H., Mohammadhosein F., Xu J.L., and Li Z.K., 2007, Mining favorable salt tolerant Q from rice germplasm using a backcrossing introgression line population, Zuowu Xuebao (Acta Agronomica Sinica), 33(10): 1611-1617
Thomson M.J., Ocampo M.D., Egdane J., Rahman M.A., Sajise A.G., Adorada D.L., Tumimbang-Raiz E., Blum wald E., SerajZ.I., Singh R.K., Gregorio G.B., and Ismail A.M., 2010, Characterizing the saltol quantitative trait locus for salinity tolerance in rice, Rice, 3(2-3): 148-160
https://doi.org/10.1007/s12284-010-9053-8
Tuyen D.D., Lal S.K., and Xu D.H., 2010, Identification of a major QTL allele from wild soybean (Glycine soja Sieb. & Zucc.) for increasing alkaline salt tolerance in soybean, Theor. Appl. Genet., 121(2): 229-236
https://doi.org/10.1007/s00122-010-1304-y
PMid:20204319
Wang B., Lan T., and Wu W.R., 2007, Mapping of QTLs for Na+ content in rice seedlings under salt stress, Zhongguo Shuidao Kexue (Chinese Journal of Rice Science ), 48(3): 604-612
Wang F.B., Zhang Y.H., Wen X.R., Yuan J., Buhaliqiemu A., Zhu X.X., and Qu Y., 2011, QTLs mapping for salt tolerance at seed germination and seedling stage in Xinjiang rice (Oryza sativa L.), Xinjiang Nongye Kexue (Xinjiang Agricultural Sciences), 48(12): 2205-2210
Wang S.L., Gao S.R., Wang Z.H., Lang S.P., and Wang J.H., 2012, Mapping of QTL associated with salt tolerance inmaize inbred line during seedling stage, Anhui Nongye Kexue (Journal of Anhui Agricultural Sciences), 40(25): 12363-12366
Wang Z.F., Chen Z.W., Cheng J.P., Lai Y.Y., Wang J.F., Bao Y.M., Huang J., and Zhang H.S., 2012, QTL analysis of Na+ and K+ concentrations in roots and shoots under different levels of NaCl stress in rice (Oryza sativa L.), PLoS One, 7(12): e51202
https://doi.org/10.1371/journal.pone.0051202
PMid:23236455
PMCid:PMC3516561
Wang Z.X., Zou D.T., Liu H.L., Wang J.G., and Ma J., 2012, Study on the difference of the alkaline tolerance of northeast japonica rice at germination stage, Heilongjiang Nongye Kexue (Heilongjiang Agricultural Sciences), (8): 6-11
Wu Y.Q., Liu L.X., Guo H.J., Zhao L.S., and Zhao S.R., 2007, Mapping QTL for salt tolerant trails in wheat, Henongxue Bao (Journal of Nuclear Agricultural Sciences), 21(6): 545-549
Xing J., Chang H.L., Wang J.G., Liu H.L., Sun J., Zheng H.L., Zhao H.W., and Zou D.T., 2015, QTL analysis of Na+ and K+ concentrations in japonica rice under salt and alkaline stress, Zhongguo Nongye Kexue (Scientia Agricultura Sinica), 48(3): 604-612
Yang J., Sun Y., Chen L.R., Zhou Z., Wang Y., Zhu L.H., Cang J., Xu J.L., and Li Z.K., 2009, Genetic background effect on QTL mapping for salt tolerance revealed by a set of reciprocal introgression line populations in rice, Zuowu Xuebao (Acta Agronomica Sinica), 35(6): 974-982
https://doi.org/10.3724/SP.J.1006.2009.00974
Yang X.H., Yan J.B., Zheng Y.P., Yu J.M., and Li J.S., 2007, Reviews of association analysis for quantitative traits inplants, Zuowu Xuebao (Acta Agronomica Sinica), 33(4): 523-530
Yin Z.T., Yang Q.H., Ni Z.B., Luo B., Bian Y.L., Wang Y.J., Xu C.W., and Deng D.X., 2012, Identification of salt tolerant germplasms and screening of related molecular markers in waxy maize at germination and seedling stages, Jiangsu Nongye Xuebao (Jiangsu Journal of Agricultural Sciences), 28(2): 278-283
Yu W.D., Jiang L., Zhuang J.Y., Fan Y.Y., and Shen B., 2009, QTL mapping of some biochemical traits in rice under salt stress, Henongxue Bao (Journal of Nuclear Agricultural Sciences), 48(3): 604-612
Zhao Z.Q., Gu H.H., Sheng X.G., Yu H.F., Wang J.S., and Cao J.S., 2014, Advances and applications in crop quantitative trait locus, Henongxue Bao (Journal of Nuclear Agricultural Sciences), 28(9): 1615-1624
Zheng H.L., Liu B.W., Zhao H.W., Wang J.G., Liu H.L., Sun J., Xing J., and Zou D.T., 2014, Identification of QTLs for salt tolerance at the germination and early seedling stage using linkage and association analysis in japonica rice, Zhongguo Shuidao Kexu (Chinese Journal of Rice Science), 28(4): 358-366
Zhou S.H., Wu Q.H., Xie J.Z., Chen J.J., Chen Y.X., Fu L., Wang G.X., Yu M.H., Wang Z.Z., Zhang D.Y., Wang L., Wang L.L., Zhang Y., Liang R.Q., Han J., and Liu Z.Y., 2016, Mapping QTLs for wheat seedling traits in RILs pop ulation of Yanda 1817×Beinong 6 under normal and salt-stress conditions, Zuowu Xuebao (Acta Agronomica Sinica), 42(12): 1764-1778
https://doi.org/10.3724/SP.J.1006.2016.01764
Zou D.T., Ma J., Wang J.G., Liu H.L., Sun J., Wang Z.X., Huang Y.Y., Wu Q., and Xing W., 2013, QTL identification of alkaline tolerance at early seedling stage in japonica rice, Dongbei Nongye Daxue Xuebao (Journal of Northeast Agricultural University), 44(1): 12-17