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The Scientific World Journal
Volume 2013 (2013), Article ID 281367, 7 pages
Recent Achievement in Gene Cloning and Functional Genomics in Soybean
1Key Laboratory of Soybean Molecular Design Breeding, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Harbin 150081, China
2Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
Received 19 August 2013; Accepted 18 September 2013
Academic Editors: C. Cilas and Y. Yu
Copyright © 2013 Zhengjun Xia et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Soybean is a model plant for photoperiodism as well as for symbiotic nitrogen fixation. However, a rather low efficiency in soybean transformation hampers functional analysis of genes isolated from soybean. In comparison, rapid development and progress in flowering time and photoperiodic response have been achieved in Arabidopsis and rice. As the soybean genomic information has been released since 2008, gene cloning and functional genomic studies have been revived as indicated by successfully characterizing genes involved in maturity and nematode resistance. Here, we review some major achievements in the cloning of some important genes and some specific features at genetic or genomic levels revealed by the analysis of functional genomics of soybean.
Soybean (Glycine max (L.) Merr.) is an important crop that provides a well-balanced source of protein and oil. In addition, most of the components of soybean such as α-linolenic acid and isoflavones have beneficial health effects. Recently, genomic studies have given more evidence that domestication of soybean began as early as five thousand years ago in China , although multiple origins of soybean domestication in the Eastern Asian region including China, the Korean peninsula, and Japan were proposed . Soybean is a wonderful model plant for photoperiodism study [3, 4]. In the 1920s, studies on the relationship between daylength and flowering time in soybean, tobacco, and other plants led to the discovery of photoperiodism. Also soybean is the only staple crop that is capable of fixing atmospheric nitrogen through symbioses with soil-borne microorganisms. However, as Arabidopsis  and rice  are becoming more popular model plants, soybean studies are somewhat lagging behind in terms of papers published with high impact factor per year possibly due to the lower efficiency in transformation and genome complexity. As sequence information of the reference genome of soybean cultivar, Williams 82, has been available since 2008 and formally published in Nature in 2010 , a new era of gene cloning and functional analysis in soybean is emerging.
2. Positional Cloning and Functional Analysis of Genes Controlling Flowering and Maturity
Flowering is one of the most important ecological and agronomical traits since it is related to the domestication, latitudinal and ecological adaption, and yield directly. About ten major quantitative trait loci (QTLs) for flowering time have been reported in soybean [8–15]. The interactions between major QTLs have been studied intensively among different environments and geographical locations. The E serials (E1 to E8) are controlling flowering time, duration of the reproductive phase (DRP) , and other physiological or agronomical traits, such as branching , yield , and chilling resistance [19, 20]. Many researchers were involved in the identification of molecular basis for E locus in soybean [21, 22]. In particular, cooperative researches from Japan and China have cloned E1, E2, E3, and E4 genes. In 1998, E4 gene was identified to encode phytochrome A2 protein, by the candidate gene approach based on the QTL position on the map . In the following year, the E3 gene was successfully cloned by positional cloning using residual heterozygous line (RHL) . Both E3 and E4 are involved in response to the light quality (red to far-red quantum (R : FR) ratios); however, their function pathways are different but overlapping [25, 26]. In addition, E3 gene has a dominant effect over E4 gene since E4 genotype only showed its own phenotype under E3 genetic background. The cloning result showed that molecular basis of E3 gene is a copy of the phytochrome, GmPhyA3. In soybean, there is a third GmphyA gene, GmPhyA1, whose function needs further characterization . Molecular basis for E2 locus was identified with the same strategy as the one used in cloning of E3 . GmGIa (Glyma10g36600) has been proven to be the genetic factor underlying the E2 locus . The GIGANTEA (GI) gene in Arabidopsis has been proven to play an important role in GI-CO-FT mediated photoperiodic flowering. However, in soybean, the flowering time phenotype difference between dominant and recessive alleles of E2 appeared to be independent of daylength, inferring that this locus is not significantly associated with photoperiodic response.
The E1 locus was genetically identified in 1971 , possibly the same locus as or locus having a major genetic effect on controlling flowering time, which was already perceived in the 1920s when people discovered the photoperiodism [8, 28, 29]. Although many researchers have tried to decipher the molecular basis E1 locus in soybean [21, 30], it ended with a plausible guess or a closed genetic distance since this gene is located in the pericentromeric region with low recombination rate [7, 31].
Successful identification of the molecular basis of the soybean maturity locus E1 will help us to understand the regulation of flowering time and maturity in soybean. After nearly ten-year effort, E1 was proven to be a legume-specific gene having a putative bipartite nuclear localization signal (NLS) coupled with a domain distantly related to B3 . The suppressed expression in short days is very much consistent with the notion that E1 is a flowering repressor and under photoperiodic regulation.
The flowering promoting factors called florigen are transported from leaves to the shoot or lateral apical meristems through the phloem in a regulated manner to provoke the initiation of floral meristems . The protein encoded by FLOWERING LOCUS T (FT) in Arabidopsis  and its ortholog in rice  were first proven to be part of the long-sought florigen. FTs are largely conserved among different plant species; however, the regulation of FT is quite diversified from species to species . Many genetic factors are controlling photoperiodic flowering in soybean through two homologs (GmFT2a and GmFT5a) of FLOWERING LOCUS T (FT) to provoke the initiation of floral meristems . For the stem termination, also known as growth habit, the main function gene is GmTFL1b [37, 38].
Although four major genes, E1 to E4 along with GmFT2a/5a and DT1, have been cloned, the flowering gene network is almost unknown. In addition, there are a vast number of Arabidopsis flowering genes in the genome of soybean . Further characterization of these sequences will shed light on our deep understanding of gene specification, diversification, and evolution of flowering genes during domestication and natural evolution.
3. Positional Cloning of Resistance Genes to Biotic and Abiotic Stresses
Soybean cyst nematode (Heterodera glycines Ichinohe) is a major constraint to soybean production worldwide. This nematode disease causes more than US$1 billion in yield losses annually in the United States . Recently, two important genes, Rhg4 and Rhg1, have been cloned and functionally characterized. Rhg4 (for resistance to Heterodera glycines 4) locus is a major quantitative trait locus contributing to resistance to this pathogen. Positional cloning reveals that the corresponding gene encodes a serine hydroxymethyltransferase, an enzyme (SHMT) that is ubiquitous in nature and structurally conserved across plant kingdoms. The enzyme functions as interconversion of serine and glycine, involved in cellular one-carbon metabolism . Various function methods, such as mutation analysis, gene silencing, and transgenic complementation, all confirmed that this gene confers resistance. On the other hand, most SCN-resistant soybeans in the Midwest, USA, are bred to contain Rhg1 (rhg1-b). After positional cloning and Rhg2-b gene silencing, genes in a 31-kilobase segment at rhg1-b encode three types of functional proteins, an amino acid transporter, an α-SNAP protein, and a WI12 (wound-inducible domain) protein, each contributes to resistance . Ten tandem copies are present in an rhg1-b haplotype; in comparison, only one copy of the 31-kilobase segment per haploid genome in susceptible varieties is existing. Overexpression of individual genes in roots is not sufficient; only overexpression of these genes together can gain enhanced SCN resistance. This result showed an interesting new insight into our understanding of disease resistance that copy number variation increases the expression of a set of dissimilar genes in a repeated multigene segment .
Soybean cultivars carrying Rps1-k locus are resistant to most races of Phytophthora sojae [42–45]. Five corresponding Rps genes, including the important Rps1-k, have been successfully mapped to the Rps1 locus, on molecular LGN of soybean genetic map. Two classes of functional coiled coil-nucleotide-binding leucine-rich repeat (CC-NB-LRR)-type resistance genes, which belong to the larger NBS-LRR resistance gene family, are confirmed to confer race-specific Phytophthora resistance through positional cloning strategy .
Rag1, dominantly conferring resistance to the soybean aphid (Aphis glycines Matsumura), was previously mapped from the cultivar Dowling to a 12 cM interval on soybean chromosome 7 (LG M). Kim et al. (2010) carried out further fine mapping and successfully delimited the region to 115 kb .
For abiotic stress, a QTL conferring Cl− accumulation in the aerial part of soybean was named in 1969 by Abel . This locus was confirmed by Lee et al. in 2004 using different genetic materials . Recently, a major salt-tolerant QTL was also mapped to LG N, putatively the same position . However, whether the salt resistant gene commonly exists between wild and cultivated soybean still needs to be confirmed. Tuyen and his team have reported a new QTL for alkaline salt tolerance and the candidate region has been narrowed using RHL line. Although the functional gene has not deciphered, the adjacent markers can be used for MAS to pyramid tolerance genes . Funatsuki et al. (2005) reported chilling-tolerant QTLs—the qCTTSW 1, 2, and 3 QTLs , and Ikeda et al. (2009) identified a new one tightly linked to Sat_162 on LG A2 and specifically involved in controlling seed development at low temperature .
Soybean is considered to be one of the most drought sensitive crops, with approximately 40% reduction of the yield in the worst years . As a consequence of global warming, the drought stress will become more serious than ever before. Several researchers have mapped QTLs for drought  or its related trait, for example, canopy wilting . Due to the complexity of this trait, unwinding of the molecular basis is still a big challenge. Other researchers identified waterlogging tolerance (WLT) .
The availability of physical and genetic maps of soybean and other legume will accelerate the cloning and functional confirmation of QTL genes conferring various agronomic traits. Over 100 traits have been mapped in the last 18 years. Current status of QTL mapping along with the other soybean genomic information can be found at SoyBase (http://soybase.org/) .
4. Other Important Traits Related to Agronomic Traits
Arabidopsis JAGGED (JAG) homolog in soybean, designated as Gm-JAGGED1, has been proven to have pleiotropic effect on narrow leaflet and fruit patterning . Positional cloning has narrowed down QTL region to a single gene level for both traits [56, 57]. Both single trait controlled by many QTL genes and individual gene having multiple pleiotropic effect make soybean genome intriguing; care needs to be taken when explaining the result of functional analysis of soybean genes.
Sayama et al. (2012) revealed that a single locus, Sg-1 encoding a UDP-sugar-dependent glycosyltransferase (Glyma07g38460), is responsible for the structural diversity of glycosylation of triterpenoid saponins of soybean .
5. Specific Features for Soybean Genome
Du et al. (2012) revealed biased accumulation of singletons in pericentromeric regions, while pair of homologs are generally residing at euchromatic region in chromosome arms, suggesting asymmetric evolution for different members of individual whole-genome duplication (WGD)-derived gene pairs . Intriguingly, the genes in pericentromeric regions where meiotic recombinations are strongly suppressed in soybean showed significantly lower rates of nonsynonymous substitution (Ka) and higher levels of expression than their homologs in chromosomal arms .
Tian et al. (2012) further demonstrated that the rates of local genetic recombination are negatively correlated with the densities of the nonreference LTR-RT insertions, but not with those of nonreference DNA TE insertions . Distinct insertional preferences were primary factors driving purifying selection.
6. Emerging Omics
As recent advances made in high-throughput DNA sequencing technologies, emerging omics, such as transcriptome, proteome, interactome, and epigenome, have been applied to soybean research. There are large numbers of next generation sequence data sets (e.g., de novo/resequencing of soybean cultivars and gene expression of different tissues or under different biotic or abiotic stresses) available at http://www.ncbi.nlm.nih.gov/.
Soybean transcriptome atlases have been developed for deposit, download, or further study of transcriptional information ; also, the database of SoyDB (http://casp.rnet.missouri.edu/soydb/) is specifically curated for soybean transcription factors . Various data sets generated using multiple tissues or different developmental stages have already been deposited. For example, we can access data generated from soybean subjected to Pseudomonas syringae infection . Thirteen and eleven differentially expressed microsomal proteins were identified from two distinct cadmium-accumulating soybean cultivars, respectively .
Soybean Knowledge Base (SoyKB) is a comprehensive all-inclusive web resource for soybean research. SoyKB is designed to handle the storage and integration of the gene, genomics, EST, microarray, transcriptomics, proteomics, metabolomics, pathway, and phenotype data . Other famous soybean or leguminous resources are also available, that is, Phytozome, http://www.phytozome.net/ ; SoyBase, http://soybase.org/ [55, 67]; Soy-TFKB (Soybean Transcription Factor Knowledge Base), http://www.igece.org/Soybean_TF/; SGMD (The Soybean Genomics and Microarray Database), http://bioinformatics.towson.edu/SGMD/ ; LegumeTFDB, http://legumetfdb.psc.riken.jp/index.pl .
To understand a basic or crucial role of a given gene product in gene regulation or signal transduction, protein-protein interaction study is fundamental. The widely used systems are yeast two hybrid (Y2H), biomolecular fluorescence complementation (BiFC), affinity pull-down coupled with mass spectrometry (AP-MS), and blue native PAGE: structural analysis of protein crystals . Among many systems available, one system can be used for detection and the others can serve for the verification of the putative interactions obtained. Interactome historically began with the literature survey . Interactome map of A. thaliana was experimentally constructed via intensive screening, yielding a total of 6200 high-confidence interactions among 2700 proteins [71, 72]. In soybean, reports of interactome related to nematode resistance and sudden death syndrome have already been published [73, 74].
An epigenome is standing for a record of the chemical changes in the DNA and histone proteins of an organism. Intriguingly, these changes might be inherited by the next generation. Changes in the epigenome can result in changes in the structure of chromatin and even the function of the genome. The epigenome is involved in regulation of gene expression, development, tissue differentiation, and suppression of transposable elements. Recently, typical research subjects include the following: histone modification; for example, Chromatin Immunoprecipitation Sequencing (ChIP-Seq) identifies genome-wide patterns of histone modifications using antibodies against the modifications; DNA methylation, for example, Whole Genome Bisulfite-Seq, Reduced Representation Bisulfite-Seq (RRBS), Methylated DNA Immunoprecipitation Sequencing (MeDIP-Seq), and Methylation-Sensitive Restriction Enzyme Sequencing (MRE-Seq) . Others are related to chromatin accessibility, for example, DNase I hypersensitive sites sequencing (DNase-Seq).
Phenotype is a general concept describing observable biological characteristics opposite to the genotype. As analytic techniques improve, phenotypes can be observed at molecular, cellular, organismal, or even population levels. The phenome generally stands for all phenotypes of an organism or a population observed. High-quality phenotypic information is so crucial for all analyses related to gene identifications, GWAS, and functional genomic and molecular breeding.
The size of a population is dependent on research purpose, for example, GWAS analysis needs a large population of over thousand individuals . The accurate quantitative contents of many physiological active metabolites, for example, α-linolenic acid and isoflavones, in seed or other tissue, are fundamental for all genetic or genomic analysis.
7. Germplasm Resource
The United States Department of Agriculture National Plant Germplasm System has a collection of over 500,000 germplasm accessions including soybean and other species. In China, recently, a platform for soybean molecular breeding based on core collections of soybean germplasm has been established .
As soybean is on the list of energy crops, worldwide demands have been increased beyond the protein, oil, and physiological compounds. However, the speed of yield increase per hectare per year is far behind that of rice and maize; soybean growing area has been shrinking shapely in China. Meanwhile, the domestic demand for soybean has increased steadily year by year, leading China to be the biggest soybean import country in the world. Chinese researchers are realizing the power of molecular breeding by design by launching several research nationwide projects in order to improve the lower efficiency of traditional breeding method for good quality and high yield.
8. Conclusion and Future Prospective
Relative soybean complexity made soybean genome sequencing and assembling difficult several years ago; however, as tremendous progress has been made in sequencing technology, soybean genome (1.1-gigabase) was reconsidered as a reasonable genome size. In consideration of nutritional and physiological contents as well as seeds that can be used as the platform for ectopic expression of recombinant protein, soybean has possibly been regarded as a new model crop for studying the genomic duplication, gene evolution, and functional diversification. The wild soybeans are greatly different from modern cultivars in terms of flowering gene network, resistance to salt or disease, and nutritional contents. Functional analysis of many Arabidopsis homologs for flowering time, resistance, and other traits related genes will lead us to understand functional and evolutional diversification at genic and genomic level. Since many QTLs for important agronomic traits are genetically mapped but not cloned yet, cloning of corresponding genes will shed light on our deeper insight into gene regulation network and specific features of soybean genome.
This research was supported by the Hundred Talents Program and KZCX2-EW-303 from the Chinese Academy of Science and National Natural Science Foundation of China (31271742 and 31301338), the Provincial Natural Science Foundations of Harbin city (RC2011XK002033) and Heilongjiang province (ZD201120), and the National Key Technologies R&D Program in the 12th 5-year plan (2011BAD35B06-2-8).
- R. M. Stupar and J. E. Specht, “Insights from the soybean (Glycine max and Glycine soja) genome: past, present, and future,” in Advances in Agronomy, vol. 118, chapter 4, pp. 177–204, 2013.
- A. Kaga, T. Shimizu, S. Watanabe et al., “Evaluation of soybean germplasm conserved in NIAS genebank and development of mini core collections,” Breeding Science, vol. 61, no. 5, pp. 566–592, 2011.
- W. W. Garner and H. A. Allard, “Effect of the relative length of day and night and other factors of the environment on growth and reproduction in plants,” Journal Agric Research, vol. 18, pp. 553–606, 1920.
- W. W. Garner and H. A. Allard, “Comparative responses of long-day and short-day plants to relative length of day and night.,” Plant Physiology, vol. 8, no. 3, pp. 347–356, 1933.
- F. Fornara, A. de Montaigu, and G. Coupland, “SnapShot: control of flowering in arabidopsis,” Cell, vol. 141, no. 3, pp. 550–e2, 2010.
- H. Itoh, Y. Nonoue, M. Yano, and T. Izawa, “A pair of floral regulators sets critical day length for Hd3a florigen expression in rice,” Nature Genetics, vol. 42, no. 7, pp. 635–638, 2010.
- J. Schmutz, S. B. Cannon, J. Schlueter et al., “Genome sequence of the palaeopolyploid soybean,” Nature, vol. 463, no. 7278, pp. 178–183, 2010.
- R. L. Bernard, “Two major genes for time of flowering and maturity in soybeans,” Crop Science, vol. 11, pp. 242–244, 1971.
- E. R. Bonato and N. A. Vello, “E6, a dominant gene conditioning early flowering and maturity in soybeans,” Genetics and Molecular Biology, vol. 22, no. 2, pp. 229–232, 1999.
- R. I. Buzzell, “Inheritance of a soybean flowering response to fluorescent-daylength conditions,” Canadian Journal of Genetics and Cytology, vol. 13, pp. 703–707, 1971.
- R. I. Buzzell and H. D. Voldeng, “Inheritance of insensitivity to long day length,” Soybean Genetics Newsletter, vol. 7, pp. 26–29, 1980.
- E. R. Cober and H. D. Voldeng, “A new soybean maturity and photoperiod-sensitivity locus linked to E1 and T,” Crop Science, vol. 41, no. 3, pp. 698–701, 2001.
- E. R. Cober, S. J. Molnar, M. Charette, and H. D. Voldeng, “A new locus for early maturity in soybean,” Crop Science, vol. 50, no. 2, pp. 524–527, 2010.
- B. A. McBlain, R. L. Bernard, C. R. Cremeens, et al., “A procedure to identify genes affecting maturity using soybean isoline testers,” Crop Science, vol. 27, pp. 1127–1132, 1987.
- J. D. Ray, K. Hinson, J. E. Mankono, and M. F. Malo, “Genetic control of a long-juvenile trait in soybean,” Crop Science, vol. 35, no. 4, pp. 1001–1006, 1995.
- S. V. Kumudini, P. K. Pallikonda, and C. Steele, “Photoperiod and e-genes influence the duration of the reproductive phase in soybean,” Crop Science, vol. 47, no. 4, pp. 1510–1517, 2007.
- T. Sayama, T.-Y. Hwang, H. Yamazaki et al., “Mapping and comparison of quantitative trait loci for soybean branching phenotype in two locations,” Breeding Science, vol. 60, no. 4, pp. 380–389, 2010.
- T. Yamada, M. Hajika, N. Yamada et al., “Effects on flowering and seed yield of dominant alleles at maturity loci E2 and E3 in a Japanese cultivar, Enrei,” Breeding Science, vol. 61, no. 5, pp. 653–660, 2011.
- H. Funatsuki, K. Kawaguchi, S. Matsuba, Y. Sato, and M. Ishimoto, “Mapping of QTL associated with chilling tolerance during reproductive growth in soybean,” Theoretical and Applied Genetics, vol. 111, no. 5, pp. 851–861, 2005.
- R. Takahashi, E. R. Benitez, H. Funatsuki, and S. Ohnishi, “Soybean maturity and pubescence color genes improve chilling tolerance,” Crop Science, vol. 45, no. 4, pp. 1387–1393, 2005.
- I. M. Tasma and R. C. Shoemaker, “Mapping flowering time gene homologs in soybean and their association with maturity (E) loci,” Crop Science, vol. 43, no. 1, pp. 319–328, 2003.
- N. Yamanaka, S. Watanabe, K. Toda et al., “Fine mapping of the FT1 locus for soybean flowering time using a residual heterozygous line derived from a recombinant inbred line,” Theoretical and Applied Genetics, vol. 110, no. 4, pp. 634–639, 2005.
- B. Liu, A. Kanazawa, H. Matsumura, R. Takahashi, K. Harada, and J. Abe, “Genetic redundancy in soybean photoresponses associated with duplication of the phytochrome A gene,” Genetics, vol. 180, no. 2, pp. 995–1007, 2008.
- S. Watanabe, R. Hideshima, X. Zhengjun et al., “Map-based cloning of the gene associated with the soybean maturity locus E3,” Genetics, vol. 182, no. 4, pp. 1251–1262, 2009.
- E. R. Cober, J. W. Tanner, and H. D. Voldeng, “Soybean photoperiod-sensitivity loci respond differentially to light quality,” Crop Science, vol. 36, no. 3, pp. 606–610, 1996.
- J. Abe, D. Xu, A. Miyano, K. Komatsu, A. Kanazawa, and Y. Shimamoto, “Photoperiod-insensitive Japanese soybean landraces differ at two maturity loci,” Crop Science, vol. 43, no. 4, pp. 1300–1304, 2003.
- S. Watanabe, Z. Xia, R. Hideshima et al., “A map-based cloning strategy employing a residual heterozygous line reveals that the GIGANTEA gene is involved in soybean maturity and flowering,” Genetics, vol. 188, no. 2, pp. 395–407, 2011.
- C. M. Woodworth, “Inheritance of growth habit, pod color, and flowering color in soybean,” Journal of American Society of Agronomy, vol. 15, pp. 485–495, 1923.
- F. V. Owen, “Inheritance studies in soybeans. II. Glabrousness, color of pubescence, time of maturity, and linkage relations,” Genetics, vol. 12, pp. 519–523, 1927.
- N. Yamanaka, S. Watanabe, K. Toda et al., “Fine mapping of the FT1 locus for soybean flowering time using a residual heterozygous line derived from a recombinant inbred line,” Theoretical and Applied Genetics, vol. 110, no. 4, pp. 634–639, 2005.
- Z. J. Xia, S. Watanabe, T. Yamada, et al., “Positional cloning and characterization reveal the molecular basis for soybean maturity locus E1 that regulates photoperiodic flowering,” The Proceedings of the National Academy of Sciences of the United States of America, vol. 109, no. 32, pp. E2155–E2164, 2012.
- L. Liu, Y. Zhu, L. Shen, and H. Yu, “Emerging insights into florigen transport,” Current Opinion in Plant Biology, vol. 16, no. 5, pp. 607–613, 2013.
- L. Corbesier, C. Vincent, S. Jang et al., “FT protein movement contributes to long-distance signaling in floral induction of Arabidopsis,” Science, vol. 316, no. 5827, pp. 1030–1033, 2007.
- S. Tamaki, S. Matsuo, L. W. Hann, S. Yokoi, and K. Shimamoto, “Hd3a protein is a mobile flowering signal in rice,” Science, vol. 316, no. 5827, pp. 1033–1036, 2007.
- R. Hayama, B. Agashe, E. Luley, R. King, and G. Coupland, “A circadian rhythm set by dusk determines the expression of FT homologs and the short-day photoperiodic flowering response in pharbitis,” The Plant Cell, vol. 19, no. 10, pp. 2988–3000, 2007.
- F. Kong, B. Liu, Z. Xia et al., “Two coordinately regulated homologs of FLowering Locus T are involved in the control of photoperiodic flowering in soybean,” Plant Physiology, vol. 154, no. 3, pp. 1220–1231, 2010.
- B. Liu, S. Watanabe, T. Uchiyama et al., “The soybean stem growth habit gene Dt1 is an ortholog of arabidopsis Terminal Flower1,” Plant Physiology, vol. 153, no. 1, pp. 198–210, 2010.
- Z. Tian, X. Wang, R. Lee et al., “Artificial selection for determinate growth habit in soybean,” Proceedings of the National Academy of Sciences of the United States of America, vol. 107, no. 19, pp. 8563–8568, 2010.
- V. Hecht, F. Foucher, C. Ferrándiz et al., “Conservation of arabidopsis flowering genes in model legumes,” Plant Physiology, vol. 137, no. 4, pp. 1420–1434, 2005.
- S. Liu, P. K. Kandoth, S. D. Warren, et al., “A soybean cyst nematode resistance gene points to a new mechanism of plant resistance to pathogens,” Nature, vol. 492, no. 7428, pp. 256–260, 2012.
- D. E. Cook, T. G. Lee, X. Guo, et al., “Copy number variation of multiple genes at Rhg1 mediates nematode resistance in soybean,” Science, vol. 338, no. 6111, pp. 1206–1209, 2012.
- H. Gao, N. N. Narayanan, L. Ellison, and M. K. Bhattacharyya, “Two classes of highly similar coiled coil-nucleotide binding-leucine rich repeat genes isolated from the Rps1-k locus encode Phytophthora resistance in soybean,” Molecular Plant-Microbe Interactions, vol. 18, no. 10, pp. 1035–1045, 2005.
- H. Gao and M. K. Bhattacharyya, “The soybean-Phytophthora resistance locus Rps1-k encompasses coiled coil-nucleotide binding-leucine rich repeat-like genes and repetitive sequences,” BMC Plant Biology, vol. 8, article 29, 2008.
- T. Kasuga, S. S. Salimath, J. Shi, M. Gijzen, R. I. Buzzell, and M. K. Bhattacharyya, “High resolution genetic and physical mapping of molecular markers linked to the Phytophthora resistance gene Rps1-k in soybean,” Molecular Plant-Microbe Interactions, vol. 10, no. 9, pp. 1035–1044, 1997.
- Q. J. Song, L. F. Marek, R. C. Shoemaker et al., “A new integrated genetic linkage map of the soybean,” Theoretical and Applied Genetics, vol. 109, no. 1, pp. 122–128, 2004.
- K.-S. Kim, S. Bellendir, K. A. Hudson et al., “Fine mapping the soybean aphid resistance gene Rag1 in soybean,” Theoretical and Applied Genetics, vol. 120, no. 5, pp. 1063–1071, 2010.
- G. H. Abel, “Inheritance of the capacity for chloride inclusion and chloride exclusion by soybeans,” Crop Science, vol. 9, pp. 697–698, 1969.
- G. J. Lee, H. R. Boerma, M. R. Villagarcia et al., “A major QTL conditioning salt tolerance in S-100 soybean and descendent cultivars,” Theoretical and Applied Genetics, vol. 109, no. 8, pp. 1610–1619, 2004.
- A. Hamwieh and D. Xu, “Conserved salt tolerance quantitative trait locus (QTL) in wild and cultivated soybeans,” Breeding Science, vol. 58, no. 4, pp. 355–359, 2008.
- D. D. Tuyen, H. M. Zhang, and D. H. Xu, “Validation and high-resolution mapping of a major quantitative trait locus for alkaline salt tolerance in soybean using residual heterozygous line,” Molecular Breeding, vol. 31, pp. 79–86, 2013.
- T. Ikeda, S. Ohnishi, M. Senda et al., “A novel major quantitative trait locus controlling seed development at low temperature in soybean (Glycine max),” Theoretical and Applied Genetics, vol. 118, no. 8, pp. 1477–1488, 2009.
- W. Du, M. Wang, S. Fu, and D. Yu, “Mapping QTLs for seed yield and drought susceptibility index in soybean (Glycine max L.) across different environments,” Journal of Genetics and Genomics, vol. 36, no. 12, pp. 721–731, 2009.
- H. Abdel-Haleem, T. E. Carter Jr., L. C. Purcell et al., “Mapping of quantitative trait loci for canopy-wilting trait in soybean (Glycine max L. Merr),” Theoretical and Applied Genetics, pp. 1–10, 2012.
- T. T. Vantoai, S. K. St. Martin, K. Chase et al., “Identification of a QTL associated with tolerance of soybean to soil waterlogging,” Crop Science, vol. 41, no. 4, pp. 1247–1252, 2001.
- D. Grant, R. T. Nelson, S. B. Cannon, and R. C. Shoemaker, “SoyBase, the USDA-ARS soybean genetics and genomics database,” Nucleic Acids Research, vol. 38, no. 1, Article ID gkp798, pp. D843–D846, 2009.
- N. Jeong, S. J. Suh, M. H. Kim, et al., “Ln is a key regulator of leaflet shape and number of seeds per pod in soybean,” The Plant Cell, vol. 24, no. 12, pp. 4807–4818, 2012.
- C. Fang, W. Li, G. Li, et al., “Cloning of Ln gene through combined approach of map-based cloning and association study in soybean,” Journal of Genetic and Genomics, vol. 40, no. 2, pp. 93–96, 2013.
- T. Sayama, E. Ono, K. Takagi, et al., “The Sg-1glycosyltransferase locus regulates structural diversity of triterpenoid saponins of soybean,” The Plant Cell, vol. 24, pp. 2123–2138, 2012.
- J. Du, Z. Tian, Y. Sui et al., “Pericentromeric effects shape the patterns of divergence, retention, and expression of duplicated genes in the paleopolyploid soybean,” The Plant Cell, vol. 24, no. 1, pp. 21–32, 2012.
- Z. Tian, M Zhao, M She, et al., “Genome-wide characterization of nonreference transposons reveals evolutionary propensities of transposons in soybean,” The Plant Cell, vol. 24, pp. 4422–4436, 2012.
- M. Libault, A. Farmer, T. Joshi et al., “An integrated transcriptome atlas of the crop model Glycine max, and its use in comparative analyses in plants,” Plant Journal, vol. 63, no. 1, pp. 86–99, 2010.
- Z. Wang, M. Libault, T. Joshi et al., “SoyDB: a knowledge database of soybean transcription factors,” BMC Plant Biology, vol. 10, article 14, 2010.
- G. Zabala, J. Zou, J. Tuteja, D. O. Gonzalez, S. J. Clough, and L. O. Vodkin, “Transcriptome changes in the phenylpropanoid pathway of Glycine max in response to Pseudomonas syringae infection,” BMC Plant Biology, vol. 6, article 26, 2006.
- N. Ahsan, T. Nakamura, and S. Komatsu, “Differential responses of microsomal proteins and metabolites in two contrasting cadmium (Cd)-accumulating soybean cultivars under Cd stress,” Amino acids, vol. 42, no. 1, pp. 317–327, 2012.
- J. Trupti, P. Kapil, R. Michael, et al., “Soybean knowledge base (SoyKB): a web resource for soybean translational genomics,” BMC Genomics, vol. 13, supplement 1, p. S15, 2012.
- D. M. Goodstein, S. Shu, R. Howson, et al., “Phytozome: a comparative platform for green plant genomics,” Nucleic Acids Research, vol. 40, pp. D1178–D1186, 2012.
- J. Du, D. Grant, Z. Tian et al., “SoyTEdb: a comprehensive database of transposable elements in the soybean genome,” BMC Genomics, vol. 11, no. 1, article 113, 2010.
- N. W. Alkharouf and B. F. Matthews, “SGMD: the soybean genomics and microarray database,” Nucleic Acids Research, vol. 32, pp. D398–D400, 2004.
- K. Mochida, T. Yoshida, T. Sakurai, K. Yamaguchi-Shinozaki, K. Shinozaki, and L.-S. P. Tran, “LegumeTFDB: an integrative database of Glycine max, lotus japonicus and medicago truncatula transcription factors,” Bioinformatics, vol. 26, no. 2, pp. 290–291, 2010.
- M. W. Li, X. Qi, M. Ni, and H. M. Lam, “Silicon era of carbon-based life: application of genomics and bioinformatics in crop stress research,” International Journal of Molecular Sciences, vol. 14, pp. 11444–11483, 2013.
- J. Cui, P. Li, G. Li et al., “AtPID: Arabidopsis thaliana protein interactome database—an integrative platform for plant systems biology,” Nucleic Acids Research, vol. 36, no. 1, pp. D999–D1008, 2008.
- Arabidopsis interactome mapping consortium, “Evidence for network evolution in an Arabidopsis interactome map,” Science, vol. 333, pp. 601–607, 2011.
- A. J. Afzal, A. Natarajan, N. Saini et al., “The nematode resistance allele at the rhg1 locus alters the proteome and primary metabolism of soybean roots,” Plant Physiology, vol. 151, no. 3, pp. 1264–1280, 2009.
- J. B. Ridenour, T. Kazi, A. M. Fakhoury, and B. H. Bluhm, “Defining the interactome underlying sudden death syndrome of soybean,” Phytopathology, vol. 101, no. 6, p. S153, 2011.
- Y. G. Song, D. Ji, S. Li, et al., “The dynamic changes of DNA methylation and histone modifications of salt responsive transcription factor genes in soybean,” Plos One, vol. 7, no. 7, 2012.
- T. Wu, E.-X. Pi, S.-N. Tsai et al., “GmPHD5 acts as an important regulator for crosstalk between histone H3K4 di-methylation and H3K14 acetylation in response to salinity stress in soybean,” BMC Plant Biology, vol. 11, article 178, 2011.
- L. Qiu, X. Li, Y. Guo, J. Wang, S. A. Jackson, and R. -Z. Chang, “A platform for soybean molecular breeding: the utilization of core collections for food security,” Plant Molecular Biology, vol. 83, no. 1, pp. 41–50, 2013.