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3秒自动关闭窗口Transcriptional regulation of aquaporins in accessions of Arabidops...
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):650-60. doi: 10.1111/j.09.04087.x. Epub
2009 Nov 26.Transcriptional regulation of aquaporins in accessions of Arabidopsis in response to drought stress.1, , , , , , .1Department of Biochemistry, Center for Molecular Protein Science, Lund University, PO Box 124, SE-221 00, Lund, Sweden.AbstractAquaporins facilitate water transport over cellular membranes, and are therefore believed to play an important role in water homeostasis. In higher plants aquaporin-like proteins, also called major intrinsic proteins (MIPs), are divided into five subfamilies. We have previously shown that MIP transcription in Arabidopsis thaliana is generally downregulated in leaves upon drought stress, apart from two members of the plasma membrane intrinsic protein (PIP) subfamily, AtPIP1;4 and AtPIP2;5, which are upregulated. In order to assess whether this regulation is general or accession-specific we monitored the gene expression of all PIPs in five Arabidopsis accessions. The overall drought regulation of PIPs was well conserved for all five accessions tested, suggesting a general and fundamental physiological role of this drought response. In addition, significant differences among accessions were identified for transcripts of three PIP genes. Principal component analysis showed that most of the PIP transcriptional variation during drought stress could be explained by one variable linked to leaf water content. Promoter-GUS constructs of AtPIP1;4, AtPIP2;5 and also AtPIP2;6, which is unresponsive to drought stress, had distinct expression patterns concentrated in the base of the leaf petioles and parts of the flowers. The presence of drought stress response elements within the 1.6-kb promoter regions of AtPIP1;4 and AtPIP2;5 was demonstrated by comparing transcription of the promoter reporter construct and the endogenous gene upon drought stress. Analysis by ATTED-II and other web-based bioinformatical tools showed that several of the MIPs downregulated upon drought are strongly co-expressed, whereas AtPIP1;4, AtPIP2;5 and AtPIP2;6 are not co-expressed.PMID:
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):51-8. doi: 10.1038/ng.2470. Epub
2012 Nov 25.The draft genome of watermelon (Citrullus lanatus) and resequencing of 20 diverse accessions.1, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , .1National Engineering Research Center for Vegetables, Beijing Academy of Agriculture and Forestry Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Beijing, China.AbstractWatermelon, Citrullus lanatus, is an important cucurbit crop grown throughout the world. Here we report a high-quality draft genome sequence of the east Asia watermelon cultivar 97103 (2n = 2× = 22) containing 23,440 predicted protein-coding genes. Comparative genomics analysis provided an evolutionary scenario for the origin of the 11 watermelon chromosomes derived from a 7-chromosome paleohexaploid eudicot ancestor. Resequencing of 20 watermelon accessions representing three different C. lanatus subspecies produced numerous haplotypes and identified the extent of genetic diversity and population structure of watermelon germplasm. Genomic regions that were preferentially selected during domestication were identified. Many disease-resistance genes were also found to be lost during domestication. In addition, integrative genomic and transcriptomic analyses yielded important insights into aspects of phloem-based vascular signaling in common between watermelon and cucumber and identified genes crucial to valuable fruit-quality traits, including sugar accumulation and citrulline metabolism.Comment inPMID:
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Research article
Molecular footprints of domestication and improvement in soybean revealed by whole genome re-sequencing
Ying-hui Li†, Shan-cen Zhao†, Jian-xin Ma†, Dong Li†, Long Yan, Jun Li, Xiao-tian Qi, Xiao-sen Guo, Le Zhang, Wei-ming He, Ru-zhen Chang, Qin-si Liang, Yong Guo, Chen Ye, Xiao-bo Wang, Yong Tao, Rong-xia Guan, Jun-yi Wang, Yu-lin Liu, Long-guo Jin, Xiu-qing Zhang, Zhang-xiong Liu, Li-juan Zhang, Jie Chen, Ke-jing Wang, Rasmus Nielsen, Rui-qiang Li, Peng-yin Chen, Wen-bin Li, Jochen C Reif, Michael Purugganan, Jian Wang, Meng-chen Zhang, Jun Wang* and Li-juan Qiu*
Corresponding authors:
† Equal contributors
Institute of Crop Science, The National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) / Key Lab of Germplasm Utilization (MOA), Chinese Academy of Agricultural Sciences, 100081 Beijing, China
Shenzhen Key Laboratory of Transomics Biotechnologies, BGI-Shenzhen, 518083 Shenzhen, China
Department of Agronomy, Purdue University, 47907, West Lafayette, IN, USA
Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences / Shijiazhuang Branch Center of National Center for Soybean Improvement / the Key Laboratory of Crop Genetics and Breeding, 050031 Shijiazhuang, China
Department of Biology, University of Copenhagen, Copenhagen, Denmark
The State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, National Centre for Plant Gene Research, Beijing, China
Department of Integrative Biology and Department of Statistics, University of California Berkeley, 94820 Berkeley, CA, USA
Department of Crop, Soil, and Environmental Sciences, University of Arkansas, 72701 Fayetteville, Arkansas, USA
Key Laboratory of Soybean Biology in Chinese Ministry of Education, Northeast Agricultural University, 150030 Harbin, China
State Plant Breeding Institute, University of Hohenheim, Hohenheim, Germany
Department of Biology and Centre for Genomics and Systems Biology, 12 Waverly Place, New York University, 10003 New York, USA
For all author emails, please .
BMC Genomics 2013, 14:579&
doi:10.64-14-579
The electronic version of this article is the complete one and can be found online at:
Received:27 July 2012
Accepted:4 July 2013
Published:28 August 2013
& 2013 Li et al.; licensee BioMed Central Ltd.
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 work is properly cited.
Background
Artificial selection played an important role in the origin of modern Glycine max cultivars from the wild soybean Glycine soja. To elucidate the consequences of artificial selection accompanying the domestication
and modern improvement of soybean, 25 new and 30 published whole-genome re-sequencing
accessions, which represent wild, domesticated landrace, and Chinese elite soybean
populations were analyzed.
A total of 5,102,244 single nucleotide polymorphisms (SNPs) and 707,969 insertion/deletions
were identified. Among the SNPs detected, 25.5% were not described previously. We
found that artificial selection during domestication led to more pronounced reduction
in the genetic diversity of soybean than the switch from landraces to elite cultivars.
Only a small proportion (2.99%) of the whole genomic regions appear to be affected
by artificial selection for preferred agricultural traits. The selection regions were
not distributed randomly or uniformly throughout the genome. Instead, clusters of
selection hotspots in certain genomic regions were observed. Moreover, a set of candidate
genes (4.38% of the total annotated genes) significantly affected by selection underlying
soybean domestication and genetic improvement were identified.
Conclusions
Given the uniqueness of the soybean germplasm sequenced, this study drew a clear picture
of human-mediated evolution of the soybean genomes. The genomic resources and information
provided by this study would also facilitate the discovery of genes/loci underlying
agronomically important traits.
Keywords: A E G P SoybeanBackground
The modern cultivated soybean [Glycine max (L.) Merr.], which contains high protein and oil content, is an important crop worldwide.
Soybean was domesticated from its wild progenitor, Glycine soja Sieb. & Zucc. ~5,000&years ago []. Although the cultivated and wild soybeans show little reproductive isolation and
have very similar genomes in both size and content [], they exhibit substantial morphological difference (Figure&a). The pre-domesticated wild soybean accessions (G. soja) have weedy prostrate growth habits and small black seeds, and the domesticated landraces
produce smaller plants with less vegetative growth and often are slightly prostrate.
In contrast, the elite cultivars developed by modern breeding practices have erect
and compact stem architecture with reduced branching, high harvest indices, and high
seed yield.
The photo of 25 re-sequenced soybean accessions. The photo of (a) typical wild, landrace and elite soybean plant and (b) seed of 25 re-sequenced soybean accessions.
The emergence of cultivated crops from their wild progenitors was achieved primarily
by artificial selection for a wide range of desirable traits to meet human needs [,]. Although domestication traits were often controlled by a relatively small number
of genes, including major quantitative trait loci (QTL) and/or Mendelian loci, selection
for such traits would have resulted in a progressive reduction of genetic diversity
throughout the genome []. Genetic diversity was further reduced following domestication by modern breeding
practices []. The genetic bottlenecks associated with the domestication and genetic improvement
of soybean had been illustrated by analysis of 111 fragments from 102 genes []. To date, several agronomically important genes including the Dt1 locus controlling soybean stem growth habit and E genes (E1-E4) controlling flowering time have been cloned by homology-based or map-based approaches
[-]. Nevertheless, little is known about how genetic diversity across the whole genome
of soybean was shaped by domestication.
The availability of the soybean genome sequence [] and high throughput sequencing technologies provides an unprecedented opportunity
to track the evolutionary history of domesticated soybean, and to dissect the genetic
bases for soybean domestication and varietal diversification. Recently, for example,
31 soybean accessions, representing wild and cultivated gene pools, had been re-sequenced
and analyzed []. This study shed light on the nature and extent of genetic differentiation between
wild and cultivated soybean species. Nevertheless, no information about landraces
– the bridge between wild soybean (domestication) and elite cultivars (improvement)
was provided. Investigations of the loss and recovery of genetic diversity in the
course of soybean domestication and breeding would provide guidelines and strategies
for utilization of landraces and/or wild accessions for soybean enhancement. Moreover,
comparative genomics analyses among wild, landrace, and elite soybeans would identify
genes under selection. The knowledge obtained from these analyses will facilitate
the introgression of beneficial alleles from wild soybean and landraces to elite cultivars.
In this study, we re-sequenced 25 diverse soybean accessions, which represent three
distinct gene pools: the pre-domesticated annual wild progenitor species (G. soja), domesticated local landraces (G. max), and modern elite cultivars (G. max). To achieve a more comprehensive analysis, we integrated these re-sequencing data
with the re-sequencing data previously generated from 14 wild and 17 cultivated soybean
genomes []. Our study not only elucidated the trends of molecular diversity, but also identified
distinct footprints in the soybean genomes associated with artificial selection during
soybean domestication and elite cultivar development.
Results and discussion
High quality sequence data was generated for 25 diverse soybean accessions
We used 25 diverse soybean accessions in this study: eight wild soybeans, eight landraces,
and nine modern elite cultivars. To maximally represent the genetic diversity and
wide geographic distribution, this panel of accessions was selected based on intensive
molecular and phenotypic characterization, which reflect the major operational taxonomic
units (OTUs) of soybeans in China [] (Figure&b, Additional file
and Additional file ). Using the genome-wide re-sequencing approach, a total of 1.356 billion high-quality
paired-end reads (93.55 Gb) were generated (Additional file ), covering 98.2% of the genome sequences (c.v., Williams 82, Glyma1.01). To overcome
potential ambiguity caused by sample size and low-pass sequencing in detecting SNPs
[], we downloaded the 31 soybean re-sequencing data through the NCBI Short Read Archive
(accession number: SRA020131). After calibrating the SNP calling quality by all the
55 accessions (except the neutron-mutated line C16 from NCBI) and discarding singletons
and most doubletons according to rigorous filtering criteria [,], we identified 5,102,244 high quality SNPs in our sequenced accessions (Additional
), which was slightly lower than that discovered previously in the 31 soybean accessions
( ). Among these, 25.5% (1,299,265) SNPs were newly reported here. Additionally, we
identified 701,792 small (&5&bp) insertion/deletions (InDels), which provide useful
markers for mapping genes, and 6,177 large deletions (&200&bp), with a mean length
of 3,615&bp. We validated 106 SNPs from ten randomly selected genes using the Sanger
method, and the accuracy of SNP calling reached 97.3%, suggesting that potential miscalling
of SNPs in this study was minimal.
Additional file 1. The geographical, ecotype and domestication-related traits information of 25 soybean
accessions worldwide.
Format: XLS
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Additional file 2. The geographic distributions of 25 soybean accessions. Glycine soja is represented by the green hollow circle, landrace is the red hollow rhombus and
elite cultivar is the blue triangle. The sky-blue lines divide China into four regions:
Northeast, North, Huanghuai and South regions. The black lines represent the Yellow
and Yangtze rivers.
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Additional file 3. Sequencing of 25 soybean accessions represented wild, landrace and elite gene pools.
Format: XLS
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Bayesian clustering revealed introgression of the wild into the cultivated soybeans
Phylogenetic relationships of the 25 accessions and Williams 82 [] were established using another legume model, Medicago truncatula[] as an out-group. The cultivated and the wild soybeans were separated into two groups
(Figure&, Additional file ), suggesting that the domestication event promoted the genetic differentiation within
the subgenera Soja. Within the cultivated accessions, the lines L3, L4, L7 and L8 were separated from
the other cultivated accessions.
Phylogenetic tree and population structure of 25 re-sequenced soybean accessions.
a, Neighbor-joining tree of soybean accessions. Northeast region. South region. Middle
part of Huanghuai region. North part of Huanghuai region. South part of Huanghuai
region. W82, Williams 82. b, Population structure inferred by ADMIXTURE. Each accession shown as a vertical line
partitioned into K colored components represents inferred membership in K genetic clusters. Blue, red, green, elite cultivars.
Additional file 4. SNP distribution in the wild, landrace and elite soybean gene pools.
Format: XLS
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The Bayesian clustering approach revealed different degrees of introgression between
the cultivated and the wild groups (Figure&b). It is particularly interesting that the four landraces (L3, L4, L7 and L8) with
mosaic pattern at K = 2 were found to have at least one of the wild traits, such as small seed size,
dark seed-coat color, and seed-coat bloom (typical wild phenotypes). In contrast,
two wild accessions (S1 and S3) showing admixture carrying one of correspopnding typical
cultivated phenotypes (Additional file ). A recent study revealed that the Oryza sativa indica, a cultivated rice subspecies, was developed from crosses between the other
cultivated rice subspecies, O. sativa japonica and its wild progenitor O. rufipogon[] suggesting that introgression between the wild and cultivated species and re-selection
for desirable agronomic traits may be a common process for crop domestication. Further
re-sequencing of larger populations of representative wild and cultivated soybeans
such as core collections would allow full elucidation of such evolutionary events
occurred during soybean domestication.
Within the cultivated soybean group, the landraces were not separated from elite cultivars
distinctly (Figure&a, Additional file ). Instead, individuals from the same geographical region tended to cluster together,
which reflected isolation by distance during evolution and/or parallel selections
in similar ecological habitats accompanied by gene flow.
Genome diversity was more impacted by domestication than by genetic improvement
Number of SNPs as well as nucleotide diversity substantially decreased throughout
the domestication process from the wild to the cultivated soybeans, which was consistent
with previous studies [,,,]. Our data revealed that 1,661,945 SNPs in wild soybean were not polymorphic in the
landraces (Figure&). Of these SNPs, 5.7% (94,793) were located in the CDS regions of genic sequences
and 4.0% (66,637) were non-synonymous sites. In addition, we observed a reduction
of 31% and 26% of genetic diversity from the wild soybeans to landraces, as measured
by θπ and θw respectively [] (Additional file ). These observations contrasted with a previous study, which reported a reduction
of nucleotide diversity from G. soja to landraces at 34% and 51%, measured by θπ and θw, respectively []. Different samples and different sets of genes were investigated in these two studies,
which might explain the different levels of reduction of genetic diversity detected
in the two studies.
Overlap of (a) total SNPs, (b) SNPs in CDS region, and (c) non-synonymous SNPs in
three soybean gene pools (wild, landrace and elite cultivar).
Additional file 5. Principal component analysis (PCA) of 25 soybean accessions from wild, landrace and
elite cultivar gene pools.
Format: PDF
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It is hypothesized that modern plant breeding reduces genetic diversity in elite cultivars,
consequently jeopardizing future crop improvement []. Although this conception appears to be true for most crop species, our data showed
limited effects of breeding on reduction of genetic diversity. We found that the elite
gene pool harbored a high proportion of the genetic diversity (83.8% for θπ and 87.8% for θw) presented in the landraces (Additional file ), contrasting with a previous study by Hyten et al. [], which demonstrated that the elite cultivars retained 78% (θπ) and 72% (θw) of the diversity present in the landraces. This difference may indeed reflect the
relative levels of genetic diversity of the two sets of elite soybean cultivars investigated
in both studies.
The number of fixed SNPs from landraces to elite cultivars (899,865) was only half
(54%) of the number of fixed SNPs during domestication (Figure&, Additional file ). Similar patterns were observed when only one gene component, such as intron, CDS,
or UTR, was analyzed (Figure&, Additional file ). Together, these observations indicated that the impact of intensive selection by
modern soybean breeding on reduction of genetic diversity was less severe than that
of selection by the domestication process, suggesting that the wild soybean gene pool
was the major reservoir that retained genes/alleles lost during domestication and
modern breeding practice. We would like to point out that this interpretation would
be largely affected by the genetic base of ancestral landraces that were used for
the development of elite cultivars investigated in this study. Nevertheless, similar
observations were also observed in maize. A recent study by Hufford et al. demonstrated
a remarkably weak genome-wide genetic bottleneck by mordern maize breeding [].
Decrease in the haplotype diversity during domestication
The extent of linkage disequilibrium can be interpreted as a measurement of haplotype
diversity in a population. We observed a drastic increase in linkage disequilibrium
(LD) across the whole genome from wild to landraces and elite cultivars (Additional
file ) pointing to a severe loss of haplotype diversity. This observation reflects the
genetic bottleneck during domestication, which reduced the genetic diversity throughout
the genome by eliminating some recombinant lineages. It is likely that the lower level
of outcrossing rate of the cultivated soybean relative to the wild soybean [] contributed to an increase in LD in the former. By contrast, the LD pattern of the
landraces differed only slightly from modern elite cultivars (Additional file ). As a result, the resolution of genome-wide association mapping for panels of landraces
or elite cultivars was much lower than that for the wild soybeans. We also observed
a large variation in extent of LD among different chromosomes (Additional file ), suggesting that molecular markers designed for genotyping strategies should be
specific to genomic regions in association mapping analyses. For example, relatively
low density of markers is needed for the regions with relatively extensive LD.
Additional file 6. Pairwise nucleotide diversity (θw and θπ) on the genome-wide level.
Format: XLSX
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Footprints of domestication in the soybean genome
The loss of genetic diversity during domestication and genetic improvement is likely
due to the fixation and sweep of alleles caused by population bottlenecks or artificial
selection. We scanned a combined dataset of 55 accessions to identify genome-wide
signatures of artificial selection following a bottom-up genetic approach []. To detect the reduction of genetic diversity caused by domestication, we employed
a sliding window strategy to estimate θπ[] and Tajima’s D []. The regions that showed significantly lower θπ in landrace relative to the wild group (Z test, P & 0.05) and significantly lower Tajima’s D (Z test, P & 0.05) in landraces relative to the wild group were considered as putative domestication-related
regions. This approach has been used to study domestication event in silkworms [] and rice []. The genome scan revealed that only 1.47% of the whole genome (950&M), comprising
394 regions distributed on individual chromosomes (Figure&a), appeared to have been affected by selection during domestication. The length of
these regions ranged from 20 kbp to 280 kbp and the polymorphism levels of these regions
relative to the whole genome were relatively low (Figure&b). A total of 928 genes were located in the regions with footprints of artificial
selection, accounting for 2.0% of the 46,430 predicted genes in the cultivated soybean
genome [].
Detection of candidate genome region and genes underwent selection during domestication
and genetic improvement. The distribution of domestication (a) and genetic improvement (c) regions and genes on the soybean chromosomes. Rectangular bar,
line, number of genes. Polymorphism distribution between cultivated (landrace plus
elite) and wild populations (b), as well as between elite and wild groups (d) in candidate region (green line) versus the whole genome (red line).
It was reported that some QTLs controlling mesdotication-related traits located in
syntenic regions among different species []. We found that some candidate genes related with soybean domestication detected in
this study had homologs, which were also affected by artificial selection in other
crops, such as rice and sunflower. For example, Glyma03g35520.1, which is probably involved in the carbohydrate metabolism pathway, was found to
be an orthologous gene of Grain Incomplete Filling 1 (GIF1), a domestication gene identified in rice []. GIF1 encodes a cell-wall invertase that regulates sugar levels for cell division and growth
during grain development, resulting in higher seed weight – an important trait for
rice domestication. In addition, we found a strong selection signal for Glyma03g35250.1, an orthologous gene of Terminal Flower 1 (TFL1), which experienced selective sweeps in the domestication of sunflower []. As the closest paralogous gene of Glyma03g35250.1 in soybean, GmTfl1 (Glyma19g37890.1) was identified to control the agronomically important trait indeterminacy (Dt1/Dt1), which is associated with soybean domestication and varietal differentiation [,]. Nucleotide diversity analysis of 20 wild and 89 cultivated soybeans detected five
SNPs in the wild population, but none of them were found in the cultivated population,
suggesting that Glyma03g35250.1 had experienced artificial selection [].
Footprints of intensive breeding in the soybean genome
Population branch statistics (PBS) is an effective method to detect signatures of
recent natural selection []. Taking wild soybeans as a control in the PBS approach, we found that 306 regions
were associated with significant signs (P & 0.001) of artificial selection by the modern breeding practice (Figure&c, Figure&d). These regions spanned a total of 14,462 kbp in length, corresponding to 1.52%
of the whole genome (950&M). Of these 306 regions, 271 were found to harbor a total
of 1,106 genes showing signatures of selection, which account for 2.4% of all the
genes located in these 271 regions []. No genes were annotated in the remaining 35 regions.
The black seed-coat progressively changed to various colors during domestication,
with positive selection for yellow in the following improvement. Multiple alleles
at the I locus were found to be associated with an unusual cluster of five chalcone synthase
genes (CHS1, CHS3, CHS4, CHS5, and CHS9) that controlled the distribution of seed-coat color by inhibiting coloration over
the entire seed coat [,]. In this study, three (Glyma08g11520.1, Glyma08g11530.1 and Glyma08g11610.1) of these five candidate CHS genes showed strong selection signals.
The evolution of flowering time was crucial for developing cultivars adapted to a
wider geographical regions [,]. We found that two genes related to flowering time, GmCRY1a (Glyma04g11010.1) and Glyma10g42090.1, exhibited selection signals. GmCRY1a was a major regulator of photoperiodic flowering in soybean and had an important
role in determining latitudinal distribution of soybean [] while Glyma10g42090.1 was a homologous gene of CONSTANS (CO), which was found to encod a key protein involved in photoperiod sensing in Arabidopsis[].
In total, 4.38% of the annotated genes were impacted by artificial selection for agricultural
traits. Polymorphism levels in the detected selection regions were relatively low
compared to that of the whole genome (Figure&b, Figure&d). The percentage of candidate genes impacted by artificial selection was similar
to that was estimated in maize (about 2% to 4%) [,]. However, this was slightly lower than that reported (~5%) by Lam et al. [] probably due to the sampling effects and different analytical methods employed. Only
two regions located on Gm03 and Gm15 showed selection signatures for both domestication
and subsequent modern breeding practice. The selected genes appeared to be distributed
in clusters in certain genomic regions (Additional file ), similar to the distribution pattern of domestication-related QTLs defined by QTL
mapping []. The domestication and improvement related genes were clustered into 386 gene families
by OrthoMCL []. Of these 386 genes, 230 were shared by both processes.
Additional file 7. LD decay determined by squared correlation coefficient of allele frequencies (r2) in against distance among three soybean gene pools on whole genome level (a) and
at each chromosome (b).
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Using the KEGG (Kyoto Encyclopedia of Genes and Genomes) [] database, potential functions of the selected genes were predicted. We found that
the selected genes were significantly (χ2 test, P & 0.05) involved in lipid metabolism, transcription factors, SNAREs (soluble N-ethyl-maleimide
sensitive factor attachment protein receptor), solute carrier family, and transport
and catabolism (Figure&). Growing demand for vegetable oil is a paramount objective of soybean domestication
and genetic improvement, which has focused selection toward cultivars with high accumulation
of lipids [,]. A high frequency of selected genes involved in lipid metabolism was also observed
during both processes (Additional file ). This indicates that continuous artificial selection had occurred in the pursuit
of preferred-quality soybean seed. These preliminary data would allow us to prioritize
further analyses with an emphasis on understanding of the biological functions of
selected genes.
Accumulation of domestication and improvement genes in different pathways of KEGG
(χ2 test, P & 0.05). CW: EL: GNM: genome wide genes.
Additional file 8. The diversity pattern of artificial selection regions during domestication and genetic
improvement based on Fst, Tajima’s D, π, or PBS’s analysis (between Landraces and
elite cultivars). The square frames along the chromosome indicate regions selected during domestication
(green) and genetic improvement (purple).
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Similar to described in maize [], transcription factors were enriched in the candidate genes with selection signaturs,
suggesting that these regulatory genes had been the major target of selection. Of
the 19 domestication-related genes identified in any plant species to date, [-], 12 were transcription factor genes [,,]. These genes were responsible for major morphology differentiation between cultivated
crops and their progenitors, such as branch (tb1) and glume architecture (tga1) in maize [,], seed size (fw2.2) and style length (Style2.1) in tomato [,], seed color (R and Q) genes in wheat [,], six-rowed spike (vsr1) in barley [], seed shattering (qSH1, sh4 and APETALA2) [,,] in rice and in cereal including sorghum, rice and maize (Sh1) [], fruit opening and seed dispersal (RPL) in Brassicaceae []. A recent study accounted well for this observation which observed that the regulatory
genes with stronger regulatory action on the other genes are the targets of selection
within the complex regulatory networks inferred from a simulation study using a matrix
Discovering genes with an integrated QTL mapping and re-sequencing approach
Although genomic regions and genes, most likely affected by artificial selection,
had been identified, the functions and phenotypes of these genes remained elusive
[]. To validate footprints of selection during domestication and genetic improvement,
we compared the genomic regions with previously mapped QTLs, which were identified
from interspecific populations and intraspecific populations developed by crossing
landrace and cultivar, respectively (Additional file ). A total of 21 candidate domestication regions including 60 genes were covered by
the mapped domestication QTLs or their adjacent regions [-]. Important agronomic traits included yield, plant height, lodging, maturity time,
seed weight, seed hardness, seed-coat color, and flower color. And a total of 20 candidate
improvement regions including 106 genes were covered by improvement QTLs or their
adjacent regions [-].
Additional file 9. Pathway analysis for domestication and improvement genes by KEGG. The pathway marked with “&” was deduced from KEGG PATHWAY database and marked with
“#” deduced from KEGG BRITE database.
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Additional file 10. Domestication regions and genes covered by or near reported QTLs for important domestication
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In addition, the integration of selection regions identified using population genetic
analysis method with QTLs region identified using an bi-parents populations may be
a useful approach to narrow down the broad QTLs []. We conducted a linkage mapping study in an interspecific F2:3 population consisting of two of the parents included in our survey and searched for
QTL for seed size, one of the most prevailing domestication phenotypes (Figure&b). Among the detected QTL we observed one at linkage map of LG F (Gm13), which accounted
for 15.1% of seed size variation. The genomic distance between the two flanking markers
Satt425 and Satt114 was 4.8&Mb (from 22,874,022&bp to 27,718,828&bp of Gm13). The
selection signals were further identified in eight internal regions (258 kbp) using
500 kbp sliding windows in the QTL (Figure&a). Within the narrowed regions, 17 genes were potentially responsible for seed size
variation. Four regions (190 kbp) were identified as footprints of intensive breeding
in this QTL region and a seed size QTL was also discovered nearby using an intraspecific
cultivated soybean population [], indicating that artificial selection occurs continuously in or near the QTL in the
pursuit of higher production. We further identified selection signals within another
QTL on Gm13, which is responsible for the typical soybean domestication trait, seed
blooming (B1) [] (Additional file ). In 2.7&Mb of this QTL region, three nearby candidate domestication regions consist
of 234 kbp DNA were identified (Figure&b). This approach offers potential application for cloning candidate genes underlying
the domestication traits of soybean as well as other crops.
The gene diversity of genomic regions of seed size (a) and seed coat blooming (b)
on chromosome 13. Top, Tajima’s D (green line); LE PBS (gray shading). Genomic diversity of wild group
(red dotted line) and cultivated group (blue dotted line) displayed by π (pi) are
plotted using 500 kbp sliding windows. The square frames along the chromosome indicate
regions selected during domestication (green) and genetic improvement (purple).
Conclusions
Soybean has undergone a series of selections over time, natural or artificial, intentional
or unintentional, leading to the decrease in genetic diversity from the wild progenitor
to landraces and from landraces to the modern elite cultivars. We reported that whole
genome re-sequencing analysis enhanced our understanding of genetic diversity in wild
and cultivated soybeans, and unraveled the processes how this important legume species
was domesticated. In present study, the strength of genetic bottlenecks caused by
domestication and modern breeding were demonstrated. The continuing reduction of genetic
diversity in the cultivated soybean has become a bottleneck for improvement of soybean
cultivars. We currently have unprecedented opportunities to exploit genetic diversity
in the wild soybean and landraces for sustainable enhancement of soybeans.
A set of candidate genes/regions were identified, significantly impacted by selection,
for constructing preferred traits underlying soybean domestication and genetic improvement.
Comparison of candidate domestication and crop improvement-related genes with previous
QTL mapping results, as well as their homologs, provides information on potential
function(s) of genes under artificial selection. In particular, we found genes related
to seed-coat color, growth habit, flowering time and seed size, which had been confirmed
as continuously changing from wild soybeans to landraces and then elite cultivars.
Further analysis is required to identify how variation in these candidate genes affect
phenotypes using QTL mapping e.g. in maize [], association mapping e.g. in barley [], gene expression assays e.g. in sunflower [], and gene-knock-out methods []. Our findings, however, promote development of more efficient approaches to identify
the genes underlying domestication-related traits. This study also contribut0065 to
construct a large-scale soybean haplotype map and discover important trait related
genes using genome-wide association studies. Our understanding of the nature of genetic
diversity in wild and cultivated soybeans, and the impact of domestication and breeding
on genome diversity, will aid future breeding of elite cultivars to improve soybean
production and meet the increasing worldwide demands for feed, vegetable oil, soyfood
and biofuels.
Sample collection for whole genome sequencing
We selected eight landraces and nine elite cultivars/lines from the Chinese soybean
mini-core collection [,] and five G. soja accessions on the basis of geographic distribution and genotypic diversity. These
represent all major operational taxonomic units (OTUs) of the Chinese soybean germplasm
and 98.8% of gene diversity []. To ensure balanced geographic distribution, three annual wild soybeans were collected.
Most of the elite cultivars/lines are widely cultivated in China. Our panel of 25
accessions originates from the Northeast region, Huanghuai region (including north,
middle and south parts) and South region of China, from 24.1 to 46.4 °N and from 102.4
to 126.6 °E, which represent the four major soybean cultivation areas in China []. These accessions were obtained from the Chinese National Soybean GenBank.
We also integrated the 30 (except C16, a neutron-mutated line) soybean re-sequencing
data of Lam et al., from the NCBI Short Read Archive (accession number: SRA020131) [], in SNP calling procedures and screening of selection regions. The information of
these 30 accessions can be found in the website:
(personnal communication with Prof. H.M. Lam at The Chinese University of Hong King).
QTL mapping population
A total of 85&F2 generation progenies were derived from the cross between the G. max cultivar E9 (Jidou12) and a G. soja accession S8 (ZYD02738). All of the F2 plants were selfed to develop F2:3 using pedigree method. Field trials were conducted at the sandy soil in the Dishang
Experimental Station of the Institute of Cereal and Oil Crops in Hebei, China (114.29°E,
38.04°N) in 2009. The F2:3 population and the parents were grown in a randomized complete block design with
three replications. Each plot consisted of one row with 1.0&m wide and 3.0&m long
with a space of 30&cm between two plants. Standard agronomic practice including were
followed to maintain a weed-free field. Seven plants in each row were used to measure
100-seed weights and extract DNA.
Whole genome sequencing and alignment
For each sample, total genomic DNA was extracted from fresh leaves of dark-grown plants
at the first trifoliolate stage using the DNeasy Plant Mini Kit (QIAGEN). The DNA
library for sequencing was prepared following the manufacturer’s instructions (Illumina).
Short reads were derived from the raw image files by applying Illumina base-calling
Pipeline (SolexaPipeline 1.3.4). These were subsequently aligned onto the soybean
reference genome (Glycine max var. Williams 82,
) [] using SOAP2 [] with parameters: -a –b –D –o -2 –u –m –x –v –l 32 –s 40. A maximum of five mismatches
were allowed for the 75&bp read and three for the 44&bp read. The alignment results
were classified into three types: unique mapped, repeat mapped and unmapped reads.
PCR duplication reads during sequencing, which affect the sequencing depth and variation
detection, were excluded by an in-house script.
SNP/InDel calling and validation
Both the Bayesian theory and the maximum likelihood estimation method were applied
to population SNP calling. Genotype likelihood of each genomic site for each line
was calculated by SOAPsnp [], which considers four main attributes: 1) ok,
2) qk, 3) ck, and 4) tk, the tk-th observation of the same allele from reads with the same mapping location. For
each assumed genotype H, the likelihood P(dk|H) = P((ok, qk, ck)|H) = P((ok, ck)|(H, qk)) * P(qk|H). Here, we used dk to represent the attributes, ok, qk, ck and tk.
All individual likelihood results were integrated to generate pseudo-chromosomes for
every site of all samples by maximum likelihood estimation. Finally, for each site,
certain criteria were used to improve accuracy: 1) the depth &20 && &160; 2) the copy
number & =1.5; 3) the quality score given by SOAPsnp &20; and 4) examination of each
heterozygous site by rank sum test based on the quality values of mapped bases. To
validate our results, we randomly selected ten genes containing 106 SNP sites for
PCR-Sanger sequencing using the AB 3730XL.
Small insertion and deletion (InDel) calling was also processed using a previously
described method []. Three steps were followed to call InDels: 1) reads were realigned with SOAP2 allowing
2) considering the supporting reads for each site, at least one individual InDel
exist 3) allotted InDels back to each individual.
Population structure and phylogenetic analysis
We constructed a phylogenetic tree by a neighbor-joining method in the software PHYLIP
(version 3.68) []. A total of 1,000 replicates generated the bootstrap values. We then used a likelihood-based
method with the program ADMIXTURE [] to investigate the ancestry information of soybean genotypes, using PLINK [] for genotype quality control. Using the principal component analysis (PCA), the population
subdivision pattern was then inferred [].
Linkage disequilibrium (LD)
To evaluate the LD pattern in wild, landrace, and elite soybean groups, we estimated
the squared allele frequency correlation (r2) of alleles using Haploview 1.4 [], setting the parameters as: -maxdistance 1000 -dprime -minGeno 0.6 -minMAF 0.1 –hwcutoff
0. The LD decay graphs were plotted using R script for each population and for individual
chromosomes.
Genome diversity and selection
To estimate the genetic diversity, we calculated the average pairwise divergence within
a population (θπ) and the Watterson’s estimator (θw) [] for the whole genome of wild, landrace, and elite populations. The 20 kbp sliding
window with 2 kbp step-size along the genome was used to estimate these two parameters
with an in-house PERL script.
To identify genomic footprints of artificial selection, we used an outlier approach
looking for genetic bottlenecks. We applied two methods to identify candidate selection
regions in the genome. First, using a 20 kbp sliding window (2 kbp step-size), we
compared sequence diversity between wild annual and cultivated soybean groups. For
each window, we estimated θπ and Tajima’s D. Those regions that had significantly low θπ.cultivated/θπ.wild and low D values (Z test, P & 0.05 for both) in cultivars were putative selected regions. Additionally, the pair-wise
nucleotide diversity and Tajima’s D were also applied to evaluate genome diversity
of different populations. Second, we chose the population branch statistic on the
basis of Fst[] to infer the selective footprints from landrace to elite cultivar. This approach
had been shown to be effective in identifying recent artificial selection [] considering the very short divergence time between landrace and elite cultivar.
QTL mapping
Ten simple sequence repeats (SSRs) from linkage group F (Gm13) ( ) were used to genotype the F2:3 population derived from the E9 (Jidou12) × S8 (ZYD02738) cross. QTL (LOD & 2.5) were
detected by single marker analysis and interval composite interval mapping (ICIM),
implemented by QTL IciMapping v3.0 ( ). For ICIM, the scanning step-size was set at 1, and the probabilities for markers
moving into and out of the model were set at 0.05 and 0.10, respectively.
Data availability
All sequence read data was deposited in Sequence Read Archive (SRA) under accession
number SRP015830. The SNPs were also available in Database of Short Genetic Variations
(dbSNP) with batch id 1058942.
Abbreviations
CHS: C CO: CONSTANS; Gb: G G. max: Glycine max (L.) Merr.; G. soja: Glycine soja Sieb. & Zucc.; GIF1: Grain incomplete filling 1; ICIM: Interval composite interval
InDels: Insertion/ KEGG: Kyoto encyclopedia
LD: Li OTUs: Operati PBS: Population branch
PCA: Principa QTL: Qua SNAREs:
Soluble n-ethyl-maleimide sensitive factor attachm SNPs: Single
nucl SSRs: Sim TFL1: Terminal flower i.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
L-J Qiu, J Wang, R-Z Chang and J Wang d Y-H Li, L Yan, X-T Qi,
L Zhang, Y Guo, X-B Wang, R-X Guan, Y-L Liu, K-J Wang, L-G Jin, Z-X Liu, L-J Zhang,
X-Q Zhang and J-X Li performed the research. Y-H Li, S-C Zhao, D Li, J-Y Wang, J Li,
X-S Guo, W-M He, Q-S Liang, C Ye, J Chen, W-B Li, M-C Zhang, Y Tao, and R Nielsen
analyzed the data. Y-H Li, S-C Zhao, D Li, J-X Ma, P-Y Chen, R-Q Li, J C Reif, M Purugganan
and L-J Qiu wrote the manuscript. All authors read and approved the final manuscript.
Acknowledgments
This research was supported by the State Key Basic Research and Development Plan of
China (973) (No.,
and ), the Academy and Institute
Foundation for Basic Scientific Research in Institute of Crop Science, Chinese Academy
of Agricultural Sciences, International Science and Technology Cooperation and Exchanges
Projects (No.2008DFA30550) and the Shenzhen Municipal Government of China and grants
from the Shenzhen Bureau of Science Technology & Information, China (No.ZYCA
and CXBA). We thank Dr. Qijian Song (USDA-ARS; University of Maryland,
USA) and Shouyi Chen (Institute of Genetics and Developmental Biology, Chinese Academy
of Sciences, China) for critical reading and useful suggestions.
References
Hymowitz T:
Speciation and cytogenetics. In Soybeans: Improvement, Production and Uses.
3rd edition.
Edited by Boerma HR, Specht JE.
Wisconsin, USA: M
Hymowitz T:
Soybean genetic resources and crop improvement. Genome 1999,
42:605-616.
Doebley JF,
The molecular genetics of crop domestication. Cell 2006,
Purugganan M:
The molecular population genetics of regulatory genes. Mol Ecol 2000,
Tanksley SD,
McCouch SR:
Seed banks and molecular maps: unlocking genetic potential from the wild. Science 1997,
277(5329):.
Nelson RL,
Specht JE,
Shoemaker RC,
Cregan PB:
Impacts of genetic bottlenecks on soybean genome diversity. Proc Natl Acad Sci USA 2006,
Specht JE,
Nelson RL,
McClean PE,
Artificial selection for determinate growth habit in soybean. Proc Natl Acad Sci USA 2010,
Watanabe S,
Uchiyama T,
Kanazawa A,
Nagamatsu A,
Kitamura K:
The soybean stem growth habit gene Dt1 is an ortholog of Arabidopsis TERMINAL FLOWER1. Plant Physiol 2010,
153(1):198-210.
Watanabe S,
Hideshima R,
Tsubokura Y,
Nakamoto Y,
Yamanaka N,
Takahashi R,
Ishimoto M,
Map-based cloning of the gene associated with the soybean maturity locus E3. Genetics 2009,
Kanazawa A,
Matsumura H,
Takahashi R,
Genetic redundancy in soybean photoresponses associated with duplication of the phytochrome A gene. Genetics 2008,
180(2):995-1007.
Watanabe S,
Hideshima R,
Tsubokura Y,
Yamanaka N,
Takahashi R,
Kitamura K:
A map-based cloning strategy employing a residual heterozygous line reveals that the
GIGANTEA gene is involved in soybean maturity and flowering. Genetics 2011,
188(2):395-407.
Watanabe S,
Tsubokura Y,
Nakashima H,
Yamazaki T,
Positional cloning and characterization reveal the molecular basis for soybean maturity
locus E1 that regulates photoperiodic flowering. Proc Nat Acad Sci USA 2012,
Schmutz J,
Cannon SB,
Schlueter J,
Thelen JJ,
Cheng J, et al.:
Genome sequence of the palaeopolyploid soybean. Nature 2010,
463(7278):178-183.
Wang B, et al.:
Resequencing of 31 wild and cultivated soybean genomes identifies patterns of genetic
diversity and selection. Nat Genet 2010,
Genetic diversity in domesticated soybean (Glycine max) and its wild progenitor (Glycine soja) for simple sequence repeat and single-nucleotide polymorphism loci. New Phytol 2010,
188:242-253.
Kristiansen K:
SNP detection for massively parallel whole-genome resequencing. Genome Res 2009,
Complete resequencing of 40 genomes reveals domestication events and genes in silkworm
(Bombyx). Science 2009,
326(5951):433-436.
Jensen JD,
Gutenkunst RN,
Resequencing 50 accessions of cultivated and wild rice yields markers for identifying
agronomically important genes. Nat Biotechnol 2012,
30:105-111.
Debellé F,
Oldroyd GED,
Cannon SB,
Udvardi MK,
Benedito VA,
Mayer KFX,
The Medicago genome provides insight into the evolution of rhizobial symbioses. Nature 2011,
480(7378):520-524.
Genetic diversity of wild and cultivated soybeans growing in China revealed by RAPD
analysis. Plant Breeding 2003,
122(6):503-506.
A single origin and moderate bottleneck during domestication of soybean (Glycine max): implications from microsatellites and nucleotide sequences. Ann Bot-London 2010,
106(3):505-514.
Watterson GA:
On the number of segregating sites in genetical models without recombination. Theor Popul Biol 1975,
7:256-276.
Hufford MB,
Van Heerwaarden J,
Pyh?j?rvi T,
Cartwright RA,
Elshire RJ,
Glaubitz JC,
Kaeppler SM, et al.:
Comparative population genomics of maize domestication and improvement. Nat Genet 2012,
44(7):808-811.
Shoemaker RC,
Nelson RL,
Specht JE,
Cregan PB:
Highly variable patterns of linkage disequilibrium in multiple soybean populations. Genetics 2007,
Ross-Ibarra J,
Morrell PL,
Plant domestication, a unique opportunity to identify the genetic basis of adaptation. Proc Natl Acad Sci USA 2007,
104(Suppl 1):.
Evolutionary relationship of the DNA sequences in finite populations. Genetics 1983,
105:437-460.
Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 1989,
123(3):585-595.
Ross-Ibarra J:
Quantitative trait loci and the study of plant domestication. Genetics of Adaptation 2005,
123:197-204.
Control of rice grain-filling and yield by a gene with a potential signature of domestication. Nat Genet 2008,
Blackman BK,
Rasmussen DA,
Strasburg JL,
Raduski AR,
Michaels SD,
Rieseberg LH:
Contributions of flowering time genes to sunflower domestication and improvement. Genetics 2011,
187(1):271-287.
Huerta-Sanchez E,
Vinckenbosch N,
Korneliussen TS:
Sequencing of 50 human exomes reveals adaptation to high altitude. Science 2010,
329(5987):75-78.
Matsumura H,
Watanabe S,
Kawasaki S,
Dubouzet E,
Takahashi R:
Molecular linkage mapping and phylogeny of the chalcone synthase multigene family
in soybean. Theor Appl Genet 2005,
Tuteja JHV,
Structural features of the endogenous silencing and target loci in the soybean genome. Crop Sci 2008,
Supplement_1
Lorenzen L,
Shoemaker R:
Mapping genetic loci for flowering time, maturity, and photoperiod insensitivity in
soybean. Mol Breeding 2001,
8(1):25-35.
Association of the circadian rhythmic expression of GmCRY1a with a latitudinal cline in photoperiodic flowering of soybean. Proc Natl Acad Sci USA 2008,
Suárez-López P,
Wheatley K,
Onouchi H,
Valverde F,
Coupland G:
CONSTANS mediates between the circadian clock and the control of flowering in Arabidopsis. Nature 2001,
410(6832):.
Schroeder S,
Yamasaki M,
Doebley J,
McMullen M,
The effects of artificial selection on the maize genome. Science 2005,
308(5726):.
Stoeckert CJ,
OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res 2003,
Kanehisa M,
KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000,
Correlation between isoflavones content and protein and oil content in different soybean
germplasms. Soybean Sci 2007,
25(6):705-708.
A study on variability of fat-related traits in cultivated and wild soybean germplasm
in China. Sci Agri Sin 2008,
Thuillet AC,
Uhlmann NK,
Rafalski JA,
Doebley J:
The role of regulatory genes during maize domestication: evidence from nucleotide
polymorphism and gene expression. Genetics 2008,
BRANDENBURG JT,
Austerlitz F:
Impact of selection on genes involved in regulatory network: a modelling study. J Evolution Biol 2011,
Lawrenson T,
?stergaard L,
Sablowski R:
The same regulatory point mutation changed seed-dispersal structures in evolution
and domestication. Curr Biol 2011,
Shangguan Y,
Genetic control of seed shattering in rice by the APETALA2 transcription factor SHATTERING ABORTION1. Plant Cell 2012,
Shangguan Y,
Genetic control of a transition from black to straw-white seed hull in rice domestication. Plant Physiol 2011,
Genetic perspectives on crop domestication. Trends Plant Sci 2010,
15(9):529-537.
Yamasaki M,
Katagiri S,
Matsumoto T:
Artificial selection for a green revolution gene during japonica rice domestication. Proc Natl Acad Sci USA 2011,
Shannon LM,
Clemente TE:
Parallel domestication of the Shattering1 genes in cereals. Nature Genet 2012,
44(6):720-724.
Komatsuda T,
Pourkheirandish M,
Azhaguvel P,
Kanamori H,
Perovic D,
Six-rowed barley originated from a mutation in a homeodomain-leucine zipper I-class
homeobox gene. Proc Natl Acad Sci USA 2007,
Nussbaum-Wagler T,
Vigouroux Y,
Bomblies K,
Doebley JF:
The origin of the naked grains of maize. Nature 2005,
436(7051):714-719.
Doebley J,
Hubbard L:
The evolution of apical dominance in maize. Nature 1997,
396:485-488.
Nesbitt TC,
Grandillo S,
van der Knaap E,
Alpert KB:
fw2. 2: a quantitative trait locus key to the evolution of tomato fruit size. Science 2000,
289(5476):85-88.
Vrebalov J,
Tanksley SD:
Changes in regulation of a transcription factor lead to autogamy in cultivated tomatoes. ScienceE 2007,
318(5850):643-645.
Red grain colour gene (R) of wheat is a Myb-type transcription factor. Euphytica 2005,
143(3):239-242.
Simons KJ,
Fellers JP,
Molecular characterization of the major wheat domestication gene Q. Genetics 2006,
172(1):547-555.
Rice domestication by reducing shattering. Science 2006,
311(5769):.
Konishi S,
An SNP caused loss of seed shattering during rice domestication. Science 2006,
312(5778):.
Cornelius PL,
Pfeiff er TW:
Soybean QTL for yield and yield components associated with Glycine soja alleles. Crop Sci 2008,
48:571-581.
Palmer RG,
Genetic analysis of genes controlling natural variation of seed coat and flower colors
in soybean. J Hered 2010,
101(6):757-768.
Procopiuk A,
Identification of putative QTL that underlie yield in interspecific soybean backcross
populations. Theor Appl Genet 2004,
108(3):458-467.
Sakamoto S,
QTL mapping of domestication-related traits in soybean (Glycine max). Ann Bot-London 2007,
Cannon SB,
Graham MA,
Farmer AD,
Muehlbauer GJ,
Specht JE,
Complementary genetic and genomic approaches help characterize the linkage group I
seed protein QTL in soybean. BMC Plant Biol 2010,
Mapping quantitative trait loci for 100-Seed weight in soybean (Glycine max L. Merr.). Acta Agron Sin 2010,
Watanabe S,
Tajuddin T,
Yamanaka N,
Hayashi M,
Analysis of QTLs for reproductive development and seed quality traits in soybean using
recombinant inbred lines. Breeding Sci 2004,
54(4):399-407.
Identification of genomic regions determining flower and pod numbers development in
soybean (Glycine max L.). J Genet Genomics 2010,
37(8):545-556.
Yamasaki M,
Wright SI,
McMullen MD:
Genomic screening for artificial selection during domestication and improvement in
maize. Ann Bot 2007,
100(5):967-973.
QTL analyses of seed weight during the development of soybean (Glycine max L. Merr.). Heredity 2008,
102:372-380.
Shoemaker R:
Four genes affecting seed traits in soybeans map to linkage group F. J Hered 1998,
89(3):211-215.
Quijada P,
Shannon LM,
Glaubitz JC,
Studer AJ,
Doebley J:
Characterization of a major maize domestication QTL on the short arm of chromosome
1. Maydica 2009,
54(4):401-408.
Haseneyer G,
Stracke S,
Piepho HP,
Geiger HH,
DNA polymorphisms and haplotype patterns of transcription factors involved in barley
endosperm development are associated with key agronomic traits. BMC Plant Biol 2010,
Establishment, representative testing and research progress of soybean core collection
and mini core collection. Acta Agron Sin 2009,
35(4):571-579.
Establishment of Chinese soybean Glycine max core collections with agronomic traits and SSR markers. Euphytica 2006,
151(2):215-223.
Genetic structure and diversity of cultivated soybean (Glycine max (L.) Merr.) landraces in China. Theor Appl Genet 2008,
117(6):857-871.
Kristiansen K,
SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics 2009,
Felsenstein J:
PHYLIP - Phylogeny Inference Package (Version 3.2). Cladistics 1989,
5:164-166.
Alexander DH,
Novembre J,
Fast model-based estimation of ancestry in unrelated individuals. Genome Res 2009,
Purcell S,
Todd-Brown K,
Ferreira MAR,
De Bakker PIW,
PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007,
81(3):559-575.
Patterson N,
Population structure and eigenanalysis. PLoS Genet 2006,
2(12):e190.
Barrett J,
Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005,
21(2):263.
A modified algorithm for the improvement of composite interval mapping. Genetics 2006,
175:361-374.
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