Please wait a minute...
Journal of Integrative Agriculture  2022, Vol. 21 Issue (7): 1886-1902    DOI: 10.1016/S2095-3119(21)63653-5
Special Issue: 油料作物合辑Oil Crops
Crop Science Advanced Online Publication | Current Issue | Archive | Adv Search |
Identification of candidate genes related to soluble sugar contents in soybean seeds using multiple genetic analyses
PAN Wen-jing1*, HAN Xue2*, HUANG Shi-yu1, YU Jing-yao1, ZHAO Ying1, QU Ke-xin1, ZHANG Ze-xin1, YIN Zhen-gong1, QI Hui-dong1, YU Guo-long1, ZHANG Yong3, XIN Da-wei1, ZHU Rong-sheng1, LIU Chun-yan1, WU Xiao-xia1, JIANG Hong-wei1, HU Zhen-bang1, ZUO Yu-hu2, CHEN Qing-shan1, QI Zhao-ming1
1 College of Agriculture, Northeast Agricultural University, Harbin 150030, P.R.China
2 Heilongjiang Bayi Agricultural University, Daqing 163000, P.R.China
3 Keshan Branch of Heilongjiang Academy of Agricultural Sciences, Qiqihar 161300, P.R.China
Download:  PDF in ScienceDirect  
Export:  BibTeX | EndNote (RIS)      
摘要  

本研究从历史数据以及公开文章中收集了57个与大豆种子可溶性糖含量相关的数量性状位点(QTLs)。通过meta、overview和共线性分析来细化QTL区间,共得到8个共有QTL。使用染色体片段代换系(CSSLs)群体对这些共有QTL进行验证,选择了两个包含共有QTL和有导入片段的品系:其中一个与共有QTL区间相关的一个品系可溶性糖含量较高,另一个品系可溶性糖含量较低。在种子发育的早期、中期和晚期对这两个品系进行转录组测序,分别鉴定出158个、109个和329个差异表达基因。通过重测序数据和共有QTL区间分析,在野生大豆遗传导入片段中鉴定出3个候选基因Glyma.19G146800Glyma.19G122500Glyma.19G128500。通过对两个CSSL亲本SN14和ZYD00006的序列比对,发现Glyma.19G122500编码序列发生单核苷酸多态性(SNP)突变,导致氨基酸序列发生非同义突变,影响了蛋白质结构。基于这一SNP,我们开发了竞争性等位基因特异性PCR (KASP)标记,并将其用于CSSL品系的鉴定。这些结果为进一步鉴定大豆可溶性糖相关基因及进一步育种奠定了基础




Abstract  Soluble sugar content in seeds is an important quality trait of soybean.  In this study, 57 quantitative trait loci (QTLs) related to soluble sugar contents in soybean seeds were collected from databases and published papers.  After meta-overview-collinearity integrated analysis to refine QTL intervals, eight consensus QTLs were identified.  To further verify the consensus QTLs, a population of chromosome segment substitution lines (CSSLs) was analyzed.  Two lines containing fragments covering the regions of consensus QTLs and the recurrent parent were selected: one line showed high soluble sugar contents associated with a consensus QTL fragment, and the other line showed low soluble sugar contents.  Transcriptome sequencing was conducted for these two lines at the early, middle, and late stages of seed development, which identified 158, 109 and 329 differentially expressed genes, respectively.  Based on the analyses of re-sequencing data of the CSSLs and the consensus QTL region, three candidate genes (Glyma.19G146800, Glyma.19G122500, and Glyma.19G128500) were identified in the genetic fragments introduced from wild soybean.  Sequence comparisons between the two CSSL parents SN14 and ZYD00006 revealed a single nucleotide polymorphism (SNP) mutation in the coding sequence of Glyma.19G122500, causing a non-synonymous mutation in the amino acid sequence that affected the predicted protein structure.  A Kompetitive allele-specific PCR (KASP) marker was developed based on this SNP and used to evaluate the CSSLs.  These results lay the foundation for further research to identify genes related to soluble sugar contents in soybean seeds and for future soybean breeding.
Keywords:  soybean soluble sugar contents        consensus QTL        meta-overview-collinearity integrated analysis        population validation        RNA-seq and candidate gene mining  
Received: 15 October 2020   Accepted: 19 February 2021
Fund: This study was financially supported by the National Natural Science Foundation of China (31701449, 31971968, 31971899, and 31501332), the Natural Science Foundation of Heilongjiang, China (QC2017013), the National Key R&D Program of China (2016YFD0100500, 2016YFD0100300 and 2016YFD0100201-21), the Special Financial Aid to Post-Doctor Research Fellow in Heilongjiang, China (LBH-TZ1714), the International Postdoctoral Exchange Fellowship Program of China Postdoctoral Council (20180004), the China Post Doctoral Project, China (2015M581419), the Post-Doctoral Project of Northeast Agricultural University, China (NEAUBH-19002), the Heilongjiang Funds for Distinguished Young Scientists, China (JC2016004 and JC2017006), the Dongnongxuezhe Project, China (to Chen Qingshan), and the the Backbone of Young Talent Scholar Project (to Qi Zhaoming, 18XG01) of Northeast Agricultural University, China.

About author:  Correspondence CHEN Qing-shan, Tel: +86-451-55191945, E-mail: qshchen@126.com; ZUO Yu-hu, E-mail: zuoyhu@163.com; QI Zhao-ming, Tel: +86-451-55191945, E-mail: qizhaoming1860@126.com * These authors contributed equally to this study.

Cite this article: 

PAN Wen-jing, HAN Xue, HUANG Shi-yu, YU Jing-yao, ZHAO Ying, QU Ke-xin, ZHANG Ze-xin, YIN Zhen-gong, QI Hui-dong, YU Guo-long, ZHANG Yong, XIN Da-wei, ZHU Rong-sheng, LIU Chun-yan, WU Xiao-xia, JIANG Hong-wei, HU Zhen-bang, ZUO Yu-hu, CHEN Qing-shan, QI Zhao-ming. 2022. Identification of candidate genes related to soluble sugar contents in soybean seeds using multiple genetic analyses. Journal of Integrative Agriculture, 21(7): 1886-1902.

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.
Bensasson D, Griffithsjones S, Collins F S, Lander E S, Rogers J, Waterson R H. 2004. Finishing the euchromatic sequence of the human genome. Nature, 431, 931–945.
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.
Chen Q S, Zhang Z C, Liu C Y, Xin D W, Qiu H M, Shan D P, Shan C Y, Hu G H. 2007. QTL analysis of major agronomic traits in soybean. Agricultural Sciences in China, 6, 399–405.
Chen W, Yao Q, Patil G, Agarwal G, Deshmukh R, Lin L, Wang B, Wang Y, Prince S J, Song L. 2016. Identification and comparative analysis of differential gene expression in soybean leaf tissue under drought and flooding stress revealed by RNA-Seq. Frontiers in Plant Science, 7, 1044–1044.
Concibido V C, Diers B W, Arelli P R. 2004. A decade of QTL mapping for cyst nematode resistance in soybean. Crop Science, 44, 1121–1131.
Crittenden R A, Playne M J. 1996. Production, properties and applications of food-grade oligosaccharides. Trends in Food Science & Technology, 7, 353–361.
Darvasi A, Soller M. 1997. A simple method to calculate resolving power and confidence interval of QTL map location. Behavior Genetics, 27, 125–132.
Eshed Y, Zamir D. 1995. An introgression line population of Lycopersicon pennellii in the cultivated tomato enables the identification and fine mapping of yield-associated QTL. Genetics, 141, 1147–1162.
Espinosa-Martos I, Rupérez P. 2006. Soybean oligosaccharides. Potential as new ingredients in functional food. Nutricion Hospitalaria, 21, 92–96.
Fei B B, Ling L, Hua C, Ren S Y. 2014. Effects of soybean oligosaccharides on antioxidant enzyme activities and insulin resistance in pregnant women with gestational diabetes mellitus. Food Chemistry, 158, 429–432.
Francis S E, Ersoy R A, Ahn J W, Atwell B J, Roberts T H. 2012. Serpins in rice: Protein sequence analysis, phylogeny and gene expression during development. BMC Genomics, 13, 449–449.
Gaiero P, Van De Belt J, Vilaró F, Schranz M E, Speranza P, de Jong H. 2016. Collinearity between potato (Solanum tuberosum L.) and wild relatives assessed by comparative cytogenetic mapping. Genome, 60, 228–240.
Glass G V. 1976. Primary, secondary, and meta-analysis of research. Educational Researcher, 5, 3–8.
Goffinet B, Gerber S. 2000. Quantitative trait loci: A meta-analysis. Genetics, 155, 463–473.
Gong Q C, Yu H X, Mao X R, Qi H D, Yan S, Xiang W, Chen Q S, Qi Z M. 2018. Meta-analysis of soybean amino acid QTLs and candidate gene mining. Journal of Integrative Agriculture, 17, 1074–1084.
Griffiths S, Simmonds J, Leverington M, Wang Y, Fish L, Sayers L, Alibert L, Orford S, Wingen L, Herry L. 2009. Meta-QTL analysis of the genetic control of ear emergence in elite European winter wheat germplasm. Theoretical and Applied Genetics, 119, 383–395.
Hayakawa K, Mizutani J, Wada K, Masai T, Yoshihara I, Mitsuoka T. 1990. Effects of soybean oligosaccharides on human faecal flora. Microbial Ecology in Health and Disease, 3, 293–303.
Huang S, Yu J, Li Y, Wang J, Wang X, Qi H, Xu M, Qin H, Yin Z, Mei H. 2018. Identification of soybean genes related to soybean seed protein content based on quantitative trait loci collinearity analysis. Journal of Agricultural and Food Chemistry, 67, 258–274.
Hymowitz T, Collins F, Panczner J, Walker W. 1972. Relationship between the content of oil, protein, and sugar in soybean seed. Agronomy Journal, 64, 613–616.
Hyten D L, Pantalone V R, Saxton A M, Schmidt M E, Sams C E. 2004. Molecular mapping and identification of soybean fatty acid modifier quantitative trait loci. Journal of the American Oil Chemists’ Society, 81, 1115–1118.
Joshi T, Valliyodan B, Wu J, Lee S, Xu D, Nguyen H T. 2013. Genomic differences between cultivated soybean, G. max and its wild relative G. soja. BMC Genomics, 14, 1–11.
Jun T H, Van K, Kim M Y, Lee S H, Walker D R. 2008. Association analysis using SSR markers to find QTL for seed protein content in soybean. Euphytica, 162, 179–191.
Kiær L P, Skovgaard I M, Østergård H. 2009. Grain yield increase in cereal variety mixtures: A meta-analysis of field trials. Field Crops Research, 114, 361–373.
Kullen M J, Khil J, Busta F F, Gallaher D D, Brady L J. 1998. Carbohydrate source and bifidobacteria influence the growth of Clostridium perfringens in vivo and in vitro. Nutrition Research, 18, 1889–1897.
Lambirth K C, Whaley A M, Blakley I C, Schlueter J A, Bost K L, Loraine A E, Piller K J. 2015. A comparison of transgenic and wild type soybean seeds: Analysis of transcriptome profiles using RNA-Seq. BMC Biotechnology, 15, 89–89.
Lan L H, Ka Z Z, Qi B M, Hai N, Cun Y Y. 2011. Integrated QTLs map of phosphorus efficiency in soybean by Meta-analysis. Chinese Journal of Oil Crop Sciences, 33, 25–32. (in Chinese)
Liu H, Sachidanandam R, Stein L. 2001. Comparative genomics between rice and Arabidopsis shows scant collinearity in gene order. Genome Research, 11, 2020–2026.
Liu J, Jung C, Xu J, Wang H, Deng S, Bernad L, Arenashuertero C, Chua N. 2012. Genome-wide analysis uncovers regulation of long intergenic noncoding RNAs in Arabidopsis. The Plant Cell, 24, 4333–4345.
Lynch M, Walsh B. 1998. Genetics and Analysis of Quantitative Traits. Sinauer Associates, Sunderland, Massachusetts, USA. 
Ma W Y, Liu W, Hou W S, Sun S, Jiang B J, Han T F, Feng Y J, Wu C X. 2019. GmNMH7, a MADS-box transcription factor, inhibits root development and nodulation of soybean (Glycine max [L.] Merr.). Journal of Integrative Agriculture, 18, 553–562.
Matus I, Corey A, Filichkin T, Hayes P, Vales M, Kling J, Riera-Lizarazu O, Sato K, Powell W, Waugh R. 2003. Development and characterization of recombinant chromosome substitution lines (RCSLs) using Hordeum vulgare subsp. spontaneum as a source of donor alleles in a Hordeum vulgare subsp. vulgare background. Genome 46, 1010–1023.
Maughan P, Maroof M S, Buss G. 2000. Identification of quantitative trait loci controlling sucrose content in soybean (Glycine max). Molecular Breeding, 6, 105–111.
Muller P Y, Janovjak H, Miserez A R, Dobbie Z. 2002. Short technical report processing of gene expression data generated by quantitative real-time RT-PCR. Biotechniques, 32, 1372–1379.
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, 721.
Patterson E L, Fleming M B, Kessler K C, Nissen S J, Gaines T A. 2017. A KASP genotyping method to identify northern watermilfoil, eurasian watermilfoil, and their interspecific hybrids. Frontiers in Plant Science, 8, 752.
Qi Z, Zhang Z, Wang Z, Yu J, Qin H, Mao X, Jiang H, Xin D, Yin Z, Zhu R. 2018. Meta-analysis and transcriptome profiling reveal hub genes for soybean seed storage composition during seed development. Plant Cell and Environment, 41, 2109–2127.
Qi Z M, Wu Q, Han X, Sun Y N, Du X Y, Liu C Y, Jiang H W, Hu G H, Chen Q S. 2011. Soybean oil content QTL mapping and integrating with meta-analysis method for mining genes. Euphytica, 179, 499–514.
Qiang X, Yong L C, Qian B W. 2009. Health benefit application of functional oligosaccharides. Carbohydrate Polymers, 77, 435–441.
Qin H, Liu Z, Wang Y, Xu M, Mao X, Qi H, Yin Z, Li Y, Jiang H, Hu Z. 2018. Meta-analysis and overview analysis of quantitative trait locis associated with fatty acid content in soybean for candidate gene mining. Plant Breeding, 137, 181–193.
Rivero U M, Santamaria O A. 2001. Oligosaccharides: Application in infant food. Early Human Development, 65, S43-S52.
Rotundo J L, Westgate M E. 2009. Meta-analysis of environmental effects on soybean seed composition. Field Crops Research, 110, 147–156.
Saito Y, Takano T, Rowland I. 1992. Effects of soybean oligosaccharides on the human gut microflora in in vitro culture. Microbial Ecology in Health and Disease, 5, 105–110.
Santachiara G, Salvagiotti F, Rotundo J L. 2019. Nutritional and environmental effects on biological nitrogen fixation in soybean: A meta-analysis. Field Crops Research, 240, 106–115.
Schmutz J, Cannon S B, Schlueter J A, Ma J, Mitros T, Nelson W, Hyten D L, Song Q, Thelen J J, Cheng J. 2010. Genome sequence of the palaeopolyploid soybean. Nature, 463, 178–183.
Severin A J, Woody J L, Bolon Y, Joseph B, Diers B W, Farmer A D, Muehlbauer G J, Nelson R T, Grant D, Specht J E. 2010. RNA-Seq atlas of Glycine max: A guide to the soybean transcriptome. BMC Plant Biology, 10, 160–160.
Shi Z, Liu S, Noe J, Arelli P, Meksem K, Li Z. 2015. SNP identification and marker assay development for high-throughput selection of soybean cyst nematode resistance. BMC Genomics, 16, 314.
Tang H, Bowers J E, Wang X, Ming R, Alam M, Paterson A H. 2008. Synteny and collinearity in plant genomes. Science, 320, 486–488.
Visscher P M, Thompson R, Haley C S. 1996. Confidence intervals in QTL mapping by bootstrapping. Genetics, 143, 1013–1020.
Wang P, Ding Y, Lu Q, Guo W, Zhang T. 2008. Development of Gossypium barbadense chromosome segment substitution lines in the genetic standard line TM-1 of Gossypium hirsutum. Chinese Science Bulletin, 53, 1512–1517. 
Wang X Y, Li Q Y, Zhang Q, Huang S Y, Qi Z M. 2019. Identification of soybean genes related to fatty acid content based on a soybean genome collinearity analysis. Plant Breeding, 138, 2.
Wang Y, Tang H, DeBarry J D, Tan X, Li J, Wang X, Lee T H, Jin H, Marler B, Guo H. 2012. MCScanX: A toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Research, 40, 49.
Wu J, Wang Q, Kang Z, Liu S, Li H, Mu J, Dai M, Han D, Zeng Q, Chen X. 2017. Development and validation of KASP-SNP markers for QTL underlying resistance to stripe rust in common wheat cultivar P10057. Plant Disease, 101, 2079–2087.
Xin D W, Qi Z M, Jiang H W, Hu Z B, Zhu R S, Liu C Y, Chen Q S. 2016. QTL location and epistatic effect analysis of 100-seed weight using wild soybean (Glycine soja Sieb. & Zucc.) chromosome segment substitution lines. PLoS ONE, 11, 3.
Xu M Y, Liu Z X, Qin H T, Qi H D, Wang Z Y, Mao X R, Xin D W, Hu Z B, Wu X X, Jiang H W. 2018. Identification of novel soybean oil content-related genes using QTL-based collinearity analysis from the collective soybean genome. Journal of Integrative Agriculture, 17, 1727–1735.
Zhan S, Ho S C. 2005. Meta-analysis of the effects of soy protein containing isoflavones on the lipid profile. The American Journal of Clinical Nutrition, 81, 397–408.
Zhang C, Lin C, Fu F, Zhong X, Peng B, Yan H, Zhang J, Zhang W, Wang P, Ding X. 2017. Comparative transcriptome analysis of flower heterosis in two soybean F1 hybrids by RNA-seq. PLoS ONE, 12, 7.
Zhang H, Meltzer P, Davis S. 2013. RCircos: An R package for Circos 2D track plots. BMC Bioinformatics, 14, 244.

No related articles found!
No Suggested Reading articles found!