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| An Integrated Quantitative Trait Locus Map of Oil Content in Soybean, Glycine max (L.) Merr., Generated Using a Meta-Analysis Method for Mining Genes |
| QI Zhao-ming, HAN Xue, SUN Ya-nan, WU Qiong, SHAN Da-peng, DU Xiang-yu, LIU Chun-yan, JIANG Hong-wei, HU Guo-hua , CHEN Qing-shan |
1.Soybean Research Institute, Northeast Agricultural University
2.Crop Research and Breeding Center of Land-Reclamation
3.Heilongjiang Academy of Agricultural Sciences, Suihua Institute |
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摘要 Soybean is a major cash crop in the world, and its oil content was one of the very important traits. Therefore, the study of gene mapping for oil content in soybean is very important for breeding application. At present, at least 130 QTL loci for soybean oil content have been published; however, the mapping results of oil content were dispersed and a coalescent public map should be established to integrate the published QTLs, and to more efficiently mine genes based on the metaanalysis method of the bioinformatics tools. This study was to construct an integrated map of QTLs for soybean oil content and accelerate the application of bioinformation resource related to oil content improvement in the practice of soybean breeding. We collected information of 130 QTLs reported over the past 20 yr for soybean oil content and used the Software BioMercator 2.1 to project QTLs from their own maps onto a reference map, which was an early-integrated map constructed by Song (2004) for oil-content quantitative trait loci (QTLs) in soybean. Gene mining was performed based on the meta-analysis by running the local ver. GENSCAN and InterProScan. The confidence interval of QTLs was efficaciously narrowed using the meta-analysis method, and 25 consensus QTLs were mapped on the reference map. Using a local version of GENSCAN, 12 805 sequences in the consensus QTL intervals were predicted. With BLAST, these predicted sequences were aligned to gene sequences from the International Protein Index database using InterProScan locally. Thirteen predicted genes were in the class of the geme ontology (GO) accession (0006631), which were involved in the fatty acid metabolic process. These genes were analyzed using BLAST at the NCBI website to examine whether they were related to oil content. Six genes were found in the oil-synthesis pathway. Twenty-five consensus QTLs and six genes were found in the oil-synthesis pathway. These results would lay the foundation for marker-assisted selection and mapping QTL precisely, and these genes will facilitate the researches on the gene mining of oil synthesis and molecular breeding in soybean.
Abstract Soybean is a major cash crop in the world, and its oil content was one of the very important traits. Therefore, the study of gene mapping for oil content in soybean is very important for breeding application. At present, at least 130 QTL loci for soybean oil content have been published; however, the mapping results of oil content were dispersed and a coalescent public map should be established to integrate the published QTLs, and to more efficiently mine genes based on the metaanalysis method of the bioinformatics tools. This study was to construct an integrated map of QTLs for soybean oil content and accelerate the application of bioinformation resource related to oil content improvement in the practice of soybean breeding. We collected information of 130 QTLs reported over the past 20 yr for soybean oil content and used the Software BioMercator 2.1 to project QTLs from their own maps onto a reference map, which was an early-integrated map constructed by Song (2004) for oil-content quantitative trait loci (QTLs) in soybean. Gene mining was performed based on the meta-analysis by running the local ver. GENSCAN and InterProScan. The confidence interval of QTLs was efficaciously narrowed using the meta-analysis method, and 25 consensus QTLs were mapped on the reference map. Using a local version of GENSCAN, 12 805 sequences in the consensus QTL intervals were predicted. With BLAST, these predicted sequences were aligned to gene sequences from the International Protein Index database using InterProScan locally. Thirteen predicted genes were in the class of the geme ontology (GO) accession (0006631), which were involved in the fatty acid metabolic process. These genes were analyzed using BLAST at the NCBI website to examine whether they were related to oil content. Six genes were found in the oil-synthesis pathway. Twenty-five consensus QTLs and six genes were found in the oil-synthesis pathway. These results would lay the foundation for marker-assisted selection and mapping QTL precisely, and these genes will facilitate the researches on the gene mining of oil synthesis and molecular breeding in soybean.
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Received: 25 June 2010
Accepted:
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| Fund: This study was supported by the Transgenic Specific Technology Programs, China (2009ZX08009-013B). |
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Corresponding Authors:
Correspondence HU Guo-hua, Professor, Tel: +86-451-55191945, E-mail: hugh757@vip.163.com; CHEN Qing-shan, Professor, Tel: +86-451-55191945, E-mail: qshchen@126.com
E-mail: hugh757@vip.163.com
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| About author: QI Zhao-ming, Ph D, E-mail: qizhaoming1860@126.com |
Cite this article:
QI Zhao-ming, HAN Xue, SUN Ya-nan, WU Qiong, SHAN Da-peng, DU Xiang-yu, LIU Chun-yan, JIANG Hong-wei, HU Guo-hua , CHEN Qing-shan .
2011.
An Integrated Quantitative Trait Locus Map of Oil Content in Soybean, Glycine max (L.) Merr., Generated Using a Meta-Analysis Method for Mining Genes . Journal of Integrative Agriculture, 10(11): 1681-1692.
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| [1]Arcade A, Labourdette A, Falque M, Mangin B, Chardon F, Charcosset A, Joets J. 2004. Biomercator: integrating genetic maps and QTL towards discovery of candidate genes. Bioinformatics, 20, 2324-2326. [2]Brummer E C, Graef G L, Orf J, Wilcox J R, Shoemaker R C. 1997. Mapping QTL for seed protein and oil content in eight soybean populations. Crop Science, 37, 370-378. [3]Buchanan B, Gruissem W, Jones R L. 2000. Biochemistry and Molecular Biology of Plants. American Society of Plant Physiologists, Rockville, Maryland. pp. 456-526. [4]Chardon F, Virlon B, Moreau L, Falque M, Joets J, Decousset L, Murigneux A, Charcosset A. 2004. Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome. Genetics, 168, 2169-2185. [5]Chen Q S, Zhang Z C, Liu C Y, Xin D W, Shan D P, Qiu H M, Shan C Y. 2007. QTL mapping of some agronomic traits of soybean. Agricultural Sciences in China, 6, 399-405. [6]Chung J, Babka H L, Graef G L, Staswick P E, Lee D J, Cregan P B, Shoemaker R C, Specht J E. 2003. The seed protein, oil, and yield QTL on soybean linkage group I. Crop Science, 43, 1053-1067. [7]Csanádi G, Vollmann J, Stift G, Lelley T. 2001. Seed quality QTLs identified in a molecular map of early maturing soybean. Theoretical and Applied Genetics, 103, 912-919. [8]Darvasi A, Soller M. 1997. A simple method to calculate resolving power and confidence interval of QTL map location. Behavioral Genetics, 27, 125-132. [9]Diers B W, Keim P, Fehr W R, Shoemaker R C. 1992. RFLP analysis of soybean seed protein and oil content. Theoretical and Applied Genetics, 83, 608-612. [10]Fasoula V A, Harris D K, Boerma H R. 2004. Vaidation and designation of quantitative trait loci for seed protein, seed oil and seed weight from two soybean population. Crop Science, 44, 1218-1225. [11]Goffinet B, Gerber S. 2000. Quantitative trait loci: a metaanalysis. Genetics, 155, 463-473. [12]Guo B, Sleper D A, Lu P, Shannon J G, Nguyen H T, Arelli P R. 2006. QTLs associated with resistance to soybean cyst nematode in soybean: meta-analysis of QTL location. Crop Science, 46, 595-602. [13]Hanocq E, Laperche A, Jaminon O, Lainé A L, le Gouis J. 2007. Most significant genome regions involved in the control of earliness traits in bread wheat, as revealed by QTL metaanalysis. Theoretical and Applied Genetics, 114, 569-584. [14]Heppard E P, Kinney A J, Stecca K L, Miao G H. 1996. Developmental and growth temperature regulation of two different microsomal omega-6 desaturase genes in soybeans. Plant Physiology, 110, 311-319. [15]Hyten D L, Pantalone V R, Sams C E, Saxton A M, Landau-Ellis D, Stefaniak T R, Schmidt M E. 2004. Seed quality QTL in a prominent soybean population. Theoretical and Applied Genetics, 109, 552-561. [16]Ji H L, Li X H, Xie C X, Hao Z F, Lv X L, Shi L Y, Zhang S H. 2007. Comparative QTL mapping of resistance to Sporisorium reiliana in maize based on meta-analysis of QTL locations. Journal of Plant Genetic Resources, 8, 132-139. [17]Kabelka E A, Diers B W, Fehr W R, LeRoy A R, Baianu I C, You T, Neece D J, Nelson R L. 2004. Putative alleles for increased yield from soybean plant introduction. Crop Science, 44, 784-791. [18]Kang M S. 1998. Using genotype-by-environment interaction for crop cultivar development. Advances in Agronomy, 35, 199-240. [19]Lanaud C, Fouet O, Clement D, Boccara M, Risterucci A M, Legavre T, Surujdeo-Maharaj S, Argout X. 2009. A metaQTL analysis of disease resistance traits of Theobroma cacao L. Molecular Breeding, 24, 361-374. [20]Wang Y G, Deng Q Y, Liang F S, Xing Q H, Li J M, Xiong Y D, Sun S M, Guo B T, Yuan L P, Wang B. 2004. Molecular marker assisted selection for yield enhancing genes in the progeny of Minghui 639 Qrufipogon. Agricultural Sciences in China, 3, 89-93. [21]Lander E, Kruglyak L. 1995. Genetic dissection of complex traits: Guidelines for interpreting and reporting linkage results. Nature Genetics, 11, 241-247. [22]Lee S H, Mian M A R, Carter T E, Shipe E R, Ashley D A, Parrott W A, Hussey R S, Boerma H R, Bailey M A. 1996. RFLP loci associated with soybean seed protein and oil content across populations and locations. Theoretical and Applied Genetics, 93, 649-657. [23]Li X H, Li X H, Hao Z F, Tian Q Z, Zhang S H. 2005. Consensus map of the QTL relevant to drought tolerance of maize under drought conditions. Scientia Agricultura Sinica, 38, 882-890. (in Chinese) [24]Li Q. 2004. Targeting and mapping of protein and oil content related genes by SSR markers in soybean. MSc thesis, Nanjing Agricultural University. (in Chinese) [25]Liang S Q. 2005. Analysis by QTL for protein and oil content of soybean seed. MSc thesis, Guangxi University. (in Chinese) [26]Lv X L, Li X H, Xie C X, Hao Z F, Ji H L, Shi L Y, Zhang S H. 2008. Comparative QTL mapping of resistance to sugarcane mosaic virus in maize based on bioinformatics. Hereditas, 30, 101-108. [27]Lv Z Z. 2006. Construction of soybean genetic map, QTL mapping of agronomic traits, and identification on excellent gene. Ph D thesis, Shandong Agricultural University. (in Chinese) [28]Mansur L M, Lark K G, Kross H, Oliveira A. 1993. Interval mapping of quantitative trait loci for reproductive, morphological, and seed traits of soybean (Glycine max L.). Theoretical and Applied Genetics, 86, 907-913. [29]Mansur L M, Orf J H, Chase K, Jarvik T, Cregan P B, Lark K G. 1996. Genetic mapping of agronomic traits using recombinant inbred lines of soybean. Crop Science, 36, 1327-1336. [30]Orf J H, Chase K, Jarvik T, Mansur L M, Cregan P B, Adler F R, Lark K G. 1999. Genetics of soybean agronomic traits: I. Comparison of three related recombinant inbred populations. Crop Science, 39, 1642-1651. [31]Panthee D R, Pantalone V R, West D R, Saxton A M, Sams C E. 2005. Quantitative trait loci for seed protein and oil concentration, and seed size in soybean. Crop Science, 45, 2015-2022. [32]Paterson A H, Lander E S, Hewitt J D, Peterson S, Lincoln S E, Tanksley S D. 1988. Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms. Nature, 335, 721726. [33]Qiu B X, Arelli P R, Sleper D A. 1999. RFLP markers associated with soybean cyst nematode resistance and seed composition in a ‘Peking’בEssex’ population. Theoretical and Applied Genetics, 98, 356-364. [34]Ren B, Li Y. 2005. Research advances on fatty acid biogynthesis metabolism in soybean seed. Molecular Plant Breeding, 3, 301-306. [35]Romagosa I, Han F, Ullrich S E, Hayes P M, Wesenberg D M. 1999. Verification of yield QTL through realized molecular marker-assisted selection responses in a barley cross. Molecular Breeding, 5, 143-152. [36]Rong J K, Feltus F A, Waghmare V N, Pierce G J, Chee P W, Draye X, Saranga Y, Wright R J, Wilkins T A, May O L, et al. 2007. Meta-analysis of polyploid cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development. Genetics, 176, 2577-2588. [37]Rudner L M, Glass G V, Evartt D L, Emery P J. 2002. A user’s Guide to the Meta-Analysis of Research Studies: Meta-Stat, Software to Aid in the Meta-Analysis of Research Findings. Educational Resources Information Center, Clearinghouse on Assessment and Evaluation, University of Maryland, College Park, MD. [38]Sebolt A M, Shoemaker R C, Diers B W. 2000. Analysis of a quantitative trait locus allele from wild soybean that increases seed protein concentration in soybean. Crop Science, 40, 1438-1444. [39]Shan D P, Qi Z M, Qiu H M, Shan C Y, Liu C Y, Hu G H, Chen Q S. 2008. Epistatic effects of QTLs and QE interaction effects on oil content in soybean. Acta Agronomica Sinica, 34, 952-957. [40]Shi D Q, Zhou Y H, Chen Z H. 2002. Manipulation of plant fatty acid. Chinese Bulletin of Sciences, 14, 291-296. [41]Shi L Y, Li X H, Hao Z F, Xie C X, Ji H L, Lv X L, Zhang S H, Pan G T. 2007. Comparative QTL mapping of resistance to gray leaf spot in maize based on bioinformatics. Agricultural Sciences in China, 6, 1411-1419. [42]Smith K J, Huyser W. 1987. World distribution and significance of soybean. In: Wilcox J R, ed., Soybeans: Improvement, Production, and Uses. 2nd ed. American Society of Agronomy, Madison, WI, USA. pp. 23-48. [43]Somerville C, Browse J, Jaworski J G, Ohlrogge J. 2000. Biochemistry and Molecular Biology of Plants. American Society of Plant Physiologists. pp. 456-527. [44]Song Q J, Marek L F, Shoemaker R C, Lark K G, Concibido V C, Delannay X, Specht J E, Cregan P B. 2004. A new integrated genetic linkage map of the soybean. Theoretical and Applied Genetics, 109, 122-128. [45]Specht J E, Chase K, Macrander M, Graef G L, Chung J, Markwell J P, Germann M, Orf J H, Lark K G. 2001. Soybean response to water: a QTL analysis of drought tolerance. Crop Science, 41, 493-509. [46]Tajuddin T, Watanabe S, Yamanaka N. 2003. Analysis of quantitative trait loci for protein and lipid contents in soybean seeds using recombinant inbred lines. Breeding Science, 53, 133-140. [47]Thomson M J, Tai T H, McClung A M, Lai X H, Hinga M E, Lobos K B, Xu Y, Martinez C P, McCouch S R. 2003. Mapping quantitative trait loci for yield, yield components and morphological traits in an advanced backcross population between Oryza rufipogon and the Oryza sativa cultivar Jefferson. Theoretical and Applied Genetics, 107, 479-493. [48]Wang Y G, Deng Q Y, Liang F S, Xing Q H, Li J M, Xiong Y D, Sun S M, Guo B T, Yuan L P, Wang B. 2004. Molecular marker assisted selection for yield enhancing genes in the progeny of Minghui 639 O. rufipogon. Agricultural Sciences in China, 3, 89-93. [49]Wang Y J. 2001. Establishment and adjustment of RIL population and its application to map construction, mapping genes resistant to SMV and QTL analysis of agronomic and quality traits in soybeans. Ph D thesis, Nanjing Agricultural University. (in Chinese) [50]Wang X S, Paigen B. 2002. Quantitative trait loci and candidate genes regulating HDL cholesterol: a murine chromosome map. Arteriosclerosis,Thrombosis, and Vascular Biology, 22, 1390-1401. [51]Wang X Z, Zhou R, Zhang X J, Shan Z H, Sha A H, Chen H F, Qiu D Z, Li P W, Zhou X A. 2008. Map construction and QTL analysis of oil content in soybean. Chinese Journal of Oil Crop Science, 30, 272-278. (in Chinese) [52]Wang Y, Yao J, Zhang Z F, Zheng Y L. 2006. The comparative analysis based on maize integrated QTL map and metaanalysis of plant height QTLs. Chinese Science Bulletin, 51, 2219-2230. [53]Warthmann N, Das S, Lanz C, Weigel D. 2008. Comparative analysis of the MIR319a microRNA locus in Arabidopsis and related Brassicaceae. Molecular Biology and Evolution, 25, 892-902. [54]Wu X L, Wang Y J, He C Y, Chen S Y, Gai J Y, Wang X C. 2001. QTL mapping of some agronomic traits of soybean. Hereditas, 28, 947-955. [55]Xu P, Wang H, Li Q, Gai J Y, Yu D Y. 2007. QTL positioning of oil content in soybean. Hereditas, 29, 92-96. [56]Yang Z, Guan R X, Wang Y Q, Liu Z X, Chang R Z, Wang S M, Qiu L J. 2004. Construction of genetic map and QTL analysis for some agronomic traits in soybean. Acta Agronomica Sinica, 30, 413-418. [57]Zhang W K, Wang Y J, Luo G Z, Zhang J S, He C Y, Wu X L, Gai J Y, Chen S Y. 2004. QTL mapping of ten agronomic traits on the soybean (Glycine max L. Merr.) genetic map and their association with EST markers. Theoretical and Applied Genetics, 108, 1131-1139. [58]Zhang Z C, Zhan X L, Chen Q S, Teng W L, Yang Q K, Li W B. 2004. QTL mapping seed oil and protein content of soybean. Soybean Science, 23, 81-85. [59]Zhang X M. 2004. Genetic diversity and QTL analysis of soybean germplasm in Russia and China. MSc thesis, Northeast Agricultural University. (in Chinese) [60]Zhu X L. 2006. Constructing of genetic linkage map and QTL mapping of important agronomic traits in two soybean populations. MSc thesis, Northeast Agricultural University. (in Chinese) |
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