National Center for Soybean Improvement

Nanjing, China

National Center for Soybean Improvement

Nanjing, China

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Huang Z.,Henan Institute of Science and Technology | Tong C.,Nanjing Forestry University | Bo W.,Beijing Forestry University | Pang X.,Beijing Forestry University | And 5 more authors.
Briefings in Bioinformatics | Year: 2014

Despite a tremendous effort to map quantitative trait loci (QTLs) responsible for agriculturally and biologically important traits in plants, our understanding of how a QTL governs the developmental process of plant seeds remains elusive. In this article, we address this issue by describing a model for functional mapping of seed development through the incorporation of the relationship between vegetative and reproductive growth. The time difference of reproductive from vegetative growth is described by Reeve and Huxley's allometric equation. Thus, the implementation of this equation into the framework of functional mapping allows dynamic QTLs for seed development to be identified more precisely. By estimating and testing mathematical parameters that define Reeve and Huxley's allometric equations of seed growth, the dynamic pattern of the genetic effects of the QTLs identified can be analyzed. We used the model to analyze a soybean data, leading to the detection of QTLs that control the growth of seed dry weight. Three dynamic QTLs, located in two different linkage groups, were detected to affect growth curves of seed dry weight. The QTLs detected may be used to improve seed yield with marker-assisted selection by altering the pattern of seed development in a hope to achieve a maximum size of seeds at a harvest time. © The Author 2013. Published by Oxford University Press.

Wang W.,Nanjing Agricultural University | Wang W.,National Center for Soybean Improvement | Wang W.,Key Laboratory of Biology and Genetic Improvement of Soybean General | Liu M.,Nanjing Agricultural University | And 18 more authors.
Frontiers in Plant Science | Year: 2016

Annual wild soybean (Glycine soja Sieb. and Zucc.), the wild progenitor of the cultivatedsoybean [Glycine max (L.) Merr.], is valuable for improving the later. The construction of a linkage map is crucial for studying the genetic differentiation between these species, but marker density is the main factor limiting the accuracy of such a map. Recent advances in next-generation sequencing technologies allow for the generation of high-density linkage maps. Here, two sets of inter-specific recombinant inbred line populations, named NJIRNP and NJIR4P, composed of 284 and 161 lines, respectively, were generated from the same wild male parent, PI 342618B, and genotyped by restriction-site-associated DNA sequencing. Two linkage maps containing 5,728 and 4,354 bins were constructed based on 89,680 and 80,995 single nucleotide polymorphisms, spanning a total genetic distance of 2204.6 and 2136.7 cM, with an average distance of 0.4 and 0.5 cM between neighboring bins in NJRINP and NJRI4P, respectively. With the two maps, seven well-studied loci, B1 for seed bloom; G and I for seed coat color; E2, E3, qDTF16.1 and two linked FLOWERING LOCUS T for days to flowering, were detected. In addition, two SB and two DTF loci were newly identified in wild soybean. Using two high-density maps, the mapping resolution was enhanced, e.g., G was narrowed to a region of 0.4 Mb on chromosome 1, encompassing 54 gene models, among which only Glyma01g40590 was predicted to be involved in anthocyanin accumulation, and its interaction with I was verified in both populations. In addition, five genes, Glyma16g03030, orthologous to Arabidopsis Phytochrome A (PHYA); Glyma13g28810, Glyma13g29920, and Glyma13g30710 predicted to encode the APETALA 2 (AP2) domain; and Glyma02g00300, involved in response to red or far red light, might be candidate DTF genes. Our results demonstrate that RAD-seq is a cost-effective approach for constructing high-density and high-quality bin maps that can be used to map QTLs/genes into such small enough regions that their candidate genes can be predicted. © 2016 Wang, Liu, Wang, Li, Cheng, Shu, Yu, Kong, Zhao and Gai.

Bo W.,Beijing Forestry University | Fu G.,Utah State University | Wang Z.,Pennsylvania State University | Xu F.,Beijing Forestry University | And 8 more authors.
Briefings in Bioinformatics | Year: 2014

The recent availability of high-throughput genetic and genomic data allows the genetic architecture of complex traits to be systematically mapped. The application of these genetic results to design and breed new crop types can be made possible through systems mapping. Systems mapping is a computational model that dissects a complex phenotype into its underlying components, coordinates different components in terms of biological laws through mathematical equations and maps specific genes that mediate each component and its connection with other components. Here, we present a new direction of systems mapping by integrating this tool with carbon economy. With an optimal spatial distribution of carbon fluxes between sources and sinks, plants tend to maximize whole-plant growth and competitive ability under limited availability of resources. We argue that such an economical strategy for plant growth and development, once integrated with systems mapping, will not only provide mechanistic insights into plant biology, but also help to spark a renaissance of interest in ideotype breeding in crops and trees. © The Author 2013. Published by Oxford University Press.

Yang C.,Nanjing Agricultural University | Yang C.,National Center for Soybean Improvement | Yang C.,National Key Laboratory of Crop Genetics and Germplasm Enhancement | Zhao T.,Nanjing Agricultural University | And 8 more authors.
Plant Molecular Biology Reporter | Year: 2011

It is well accepted that somatic embryogenesis serves a primary role in plant regeneration. However, it is also a model system to explore the regulatory and morphogenetic events in the life of a plant. To date, a suite of genes that serve important roles in somatic embryogenesis have been isolated and identified. In the present study, a novel gene designated as GmSERK1 was isolated from soybean (Glycine max (L.) Merr). Sequence and structural analysis determined that the GmSERK1 protein, which encodes 624 amino acids, belongs to the somatic embryogenesis receptor-like kinase (SERK) gene family. GmSERK1 shared all the characteristic domains of the SERK family, including five leucine-rich repeats, one proline-rich region motif, transmembrane domain, and kinase domains. DNA gel blot analysis indicated that a single copy of the GmSERK1 gene resides in the soybean genome. The GmSERK1 tissue-specific and induced expression patterns were explored using quantitative real-time PCR. Dissimilar expression levels in various tissues under different treatments were found. In addition, transient expression experiments in onion epidermal cells indicated that the GmSERK1 protein was located on the plasma membrane. The results from this study suggested that GmSERK1, a member of the SERK gene family, exhibits a broader role in various aspects of plant development and function, in addition to its basic functions in somatic embryogenesis. © 2010 Springer-Verlag.

Meng S.,Nanjing Agricultural University | Meng S.,National Center for Soybean Improvement | He J.,Nanjing Agricultural University | He J.,National Center for Soybean Improvement | And 19 more authors.
Theoretical and Applied Genetics | Year: 2016

Key message: Utilizing an innovative GWAS in CSLRP, 44 QTL 199 alleles with 72.2 % contribution to SIFC variation were detected and organized into a QTL-allele matrix for cross design and gene annotation.Abstract: The seed isoflavone content (SIFC) of soybeans is of great importance to health care. The Chinese soybean landrace population (CSLRP) as a genetic reservoir was studied for its whole-genome quantitative trait loci (QTL) system of the SIFC using an innovative restricted two-stage multi-locus genome-wide association study procedure (RTM-GWAS). A sample of 366 landraces was tested under four environments and sequenced using RAD-seq (restriction-site-associated DNA sequencing) technique to obtain 116,769 single nucleotide polymorphisms (SNPs) then organized into 29,119 SNP linkage disequilibrium blocks (SNPLDBs) for GWAS. The detected 44 QTL 199 alleles on 16 chromosomes (explaining 72.2 % of the total phenotypic variation) with the allele effects (92 positive and 107 negative) of the CSLRP were organized into a QTL-allele matrix showing the SIFC population genetic structure. Additional differentiation among eco-regions due to the SIFC in addition to that of genome-wide markers was found. All accessions comprised both positive and negative alleles, implying a great potential for recombination within the population. The optimal crosses were predicted from the matrices, showing transgressive potentials in the CSLRP. From the detected QTL system, 55 candidate genes related to 11 biological processes were χ2-tested as an SIFC candidate gene system. The present study explored the genome-wide SIFC QTL/gene system with the innovative RTM-GWAS and found the potentials of the QTL-allele matrix in optimal cross design and population genetic and genomic studies, which may have provided a solution to match the breeding by design strategy at both QTL and gene levels in breeding programs. © 2016 Springer-Verlag Berlin Heidelberg

Chang S.,National Center for Soybean Improvement | Chang S.,Key Laboratory of Biology and Genetic Improvement of Soybean | Chang S.,Nanjing Agricultural University | Wang Y.,Nanjing Agricultural University | And 13 more authors.
PLoS ONE | Year: 2013

Determining mitochondrial genomes is important for elucidating vital activities of seed plants. Mitochondrial genomes are specific to each plant species because of their variable size, complex structures and patterns of gene losses and gains during evolution. This complexity has made research on the soybean mitochondrial genome difficult compared with its nuclear and chloroplast genomes. The present study helps to solve a 30-year mystery regarding the most complex mitochondrial genome structure, showing that pairwise rearrangements among the many large repeats may produce an enriched molecular pool of 760 circles in seed plants. The soybean mitochondrial genome harbors 58 genes of known function in addition to 52 predicted open reading frames of unknown function. The genome contains sequences of multiple identifiable origins, including 6.8 kb and 7.1 kb DNA fragments that have been transferred from the nuclear and chloroplast genomes, respectively, and some horizontal DNA transfers. The soybean mitochondrial genome has lost 16 genes, including nine protein-coding genes and seven tRNA genes; however, it has acquired five chloroplast-derived genes during evolution. Four tRNA genes, common among the three genomes, are derived from the chloroplast. Sizeable DNA transfers to the nucleus, with pericentromeric regions as hotspots, are observed, including DNA transfers of 125.0 kb and 151.6 kb identified unambiguously from the soybean mitochondrial and chloroplast genomes, respectively. The soybean nuclear genome has acquired five genes from its mitochondrial genome. These results provide biological insights into the mitochondrial genome of seed plants, and are especially helpful for deciphering vital activities in soybean. © 2013 Chang et al.

He J.,Nanjing Agricultural University | He J.,National Center for Soybean Improvement | He J.,Key Laboratory of Biology and Genetic Improvement of Soybean | Li J.,Nanjing Agricultural University | And 13 more authors.
PLoS ONE | Year: 2015

Experimental error control is very important in quantitative trait locus (QTL) mapping. Although numerous statistical methods have been developed for QTL mapping, a QTL detection model based on an appropriate experimental design that emphasizes error control has not been developed. Lattice design is very suitable for experiments with large sample sizes, which is usually required for accurate mapping of quantitative traits. However, the lack of a QTL mapping method based on lattice design dictates that the arithmetic mean or adjusted mean of each line of observations in the lattice design had to be used as a response variable, resulting in low QTL detection power. As an improvement, we developed a QTL mapping method termed composite interval mapping based on lattice design (CIMLD). In the lattice design, experimental errors are decomposed into random errors and block-within-replication errors. Four levels of block-within-replication errors were simulated to show the power of QTL detection under different error controls. The simulation results showed that the arithmetic mean method, which is equivalent to a method under random complete block design (RCBD), was very sensitive to the size of the block variance and with the increase of block variance, the power of QTL detection decreased from 51.3% to 9.4%. In contrast to the RCBD method, the power of CIMLD and the adjusted mean method did not change for different block variances. The CIMLD method showed 1.2- to 7.6-fold higher power of QTL detection than the arithmetic or adjusted mean methods. Our proposed method was applied to real soybean (Glycine max) data as an example and 10 QTLs for biomass were identified that explained 65.87% of the phenotypic variation, while only three and two QTLs were identified by arithmetic and adjusted mean methods, respectively. © 2015 He et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Korir P.C.,Nanjing Agricultural University | Korir P.C.,National Center for Soybean Improvement | Korir P.C.,National Key Laboratory for Crop Genetics and Germplasm Enhancement | Zhao T.,Nanjing Agricultural University | And 5 more authors.
Frontiers of Agriculture in China | Year: 2010

To determine an appropriate indicator and a suitable stage for evaluating tolerance of soybeans to aluminum (Al) toxin is one of the keys to effective breeding for the trait. Seventeen accessions selected as tolerant from a previous test program by using average membership index (FAi) as indicator, plus one tolerant (PI.416937) and one sensitive (NN1138-2) check, were assayed in sand culture pot experiments, totaling four experiments, each for evaluation at V3, V5, V7 and V9 stage, respectively, each in a randomized complete block design with three replications, and each genotype exposed to two Al levels (0 and 480 μM). The relative values of shoot dry weight (RSDW), root dry weight (RRDW), total plant dry weight (RTDW), total root length (RTRL) and total root surface area (RRSA) as the tolerance indicators as well as FAi were compared. All the indicators showed significant variation in Al tolerance among genotypes over and across the leaf stages, but Genotype × Stage interactions were significant only for RTRL and RRSA, indicating that they were less stable among stages than RTDW, RSDW and RRDW. Among the latter three, RTDW was chosen as the major indicator of Al tolerance due to its relatively better stability, higher correlation with other indicators and easier measuring procedure than the others. The seedling age applicable for screening was not definitive, but V5 appeared to compromise between time spent resulting from screening the relatively older seedlings at later stages and low variation among genotypes at a younger stage. The differences of Al tolerance among the tested accessions were further detected by using RTDW, and superior Al tolerant accessions identified were PI.509080 (South Korea), N23533 and N24282 (Northeast China) and PI.159322 (USA), comparable to the putative tolerant check PI.416937 (Japan) at all vegetative stages. © 2010 Higher Education Press and Springer-Verlag Berlin Heidelberg.

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