Allelic Combinations of Soybean Maturity Loci E1, E2, E3 and E4 Result in Diversity of Maturity and Adaptation to Different Latitudes

Soybean cultivars are extremely diverse in time to flowering and maturation as a result of various photoperiod sensitivities. The underlying molecular genetic mechanism is not fully clear, however, four maturity loci E1, E2, E3 and E4 have been molecularly identified. In this report, cultivars were selected with various photoperiod sensitivities from different ecological zones, which covered almost all maturity groups (MG) from MG 000 to MG VIII and MG X adapted from latitude N 18° to N 53°. They were planted in the field under natural daylength condition (ND) in Beijing, China or in pots under different photoperiod treatments. Maturity-related traits were then investigated. The four E maturity loci were genotyped at the molecular level. Our results suggested that these four E genes have different impacts on maturity and their allelic variations and combinations determine the diversification of soybean maturity and adaptation to different latitudes. The genetic mechanisms underlying photoperiod sensitivity and adaptation in wild soybean seemed unique from those in cultivated soybean. The allelic combinations and functional molecular markers for the four E loci will significantly assist molecular breeding towards high productivity.     

Identification of mega‐environments in Europe and effect of allelic variation at maturity E loci on adaptation of European soybean

Soybean cultivation holds great potential for a sustainable agriculture in Europe, but adaptation remains a central issue. In this large mega‐environment (MEV) study, 75 European cultivars from five early maturity groups (MGs 000–II) were evaluated for maturity‐related traits at 22 locations in 10 countries across Europe. Clustering of the locations based on phenotypic similarity revealed six MEVs in latitudinal direction and suggested several more. Analysis of maturity identified several groups of cultivars with phenotypic similarity that are optimally adapted to the different growing regions in Europe. We identified several haplotypes for the allelic variants at the E1, E2, E3 and E4 genes, with each E haplotype comprising cultivars from different MGs. Cultivars with the same E haplotype can exhibit different flowering and maturity characteristics, suggesting that the genetic control of these traits is more complex and that adaptation involves additional genetic pathways, for example temperature requirement. Taken together, our study allowed the first unified assessment of soybean‐growing regions in Europe and illustrates the strong effect of photoperiod on soybean adaptation and MEV classification, as well as the effects of the E maturity loci for soybean adaptation in Europe.     

Molecular markers for the E2 and E3 genes controlling flowering and maturity in soybean

Natural variation in flowering time may play a role in the adaptation of plants to various environments, and understanding the genetic basis of flowering and maturity would facilitate the development of early maturing cultivars. Molecular markers for the E2 and E3 loci, which control the time of flowering and maturity in soybean (Glycine max), were developed in this study. Single nucleotide-amplified polymorphism (SNAP) markers were developed from the nonsense mutation in E2 (GmGIa), which is a circadian clock-controlled gene. The E2- and e2-specific SNAP markers were validated using six E2 isolines. The soybean E3 gene is a photoreceptor phytochrome A (GmPhyA3) gene, and a co-dominant marker was designed based on sequence deletions within the E3 allele. A multiplex PCR assay using three primers for the E3 gene allowed allelic discrimination based on the sizes of PCR products. Furthermore, this E3 marker successfully detected two alleles in a single reaction when two types of DNA were pooled. These markers determined the genotypes of our mapping population previously reported to detect flowering quantitative trait loci close to the E2 and E3 loci, confirming that the mutations are responsible for the early flowering phenotype. The use of SNAP markers for E2 and a co-dominant marker for E3 is a simple, fast, and reproducible method, requiring only PCR and agarose gel electrophoresis. The molecular resources developed in this study could accelerate marker-assisted selection and cultivar development for short-season areas in a soybean breeding program.     

Natural variation in the genes responsible for maturity loci E1, E2, E3 and E4 in soybean

Background and Aims

The timing of flowering has a direct impact on successful seed production in plants. Flowering of soybean (Glycine max) is controlled by several E loci, and previous studies identified the genes responsible for the flowering loci E1, E2, E3 and E4. However, natural variation in these genes has not been fully elucidated. The aims of this study were the identification of new alleles, establishment of allele diagnoses, examination of allelic combinations for adaptability, and analysis of the integrated effect of these loci on flowering.

Methods

The sequences of these genes and their flanking regions were determined for 39 accessions by primer walking. Systematic discrimination among alleles was performed using DNA markers. Genotypes at the E1–E4 loci were determined for 63 accessions covering several ecological types using DNA markers and sequencing, and flowering times of these accessions at three sowing times were recorded.

Key Results

A new allele with an insertion of a long interspersed nuclear element (LINE) at the promoter of the E1 locus (e1-re) was identified. Insertion and deletion of 36 bases in the eighth intron (E2-in and E2-dl) were observed at the E2 locus. Systematic discrimination among the alleles at the E1–E3 loci was achieved using PCR-based markers. Allelic combinations at the E1–E4 loci were found to be associated with ecological types, and about 62–66 % of variation of flowering time could be attributed to these loci.

Conclusions

The study advances understanding of the combined roles of the E1–E4 loci in flowering and geographic adaptation, and suggests the existence of unidentified genes for flowering in soybean,     

Major Soybean Maturity Gene Haplotypes Revealed by SNPViz Analysis of 72 Sequenced Soybean Genomes

In this Genomics Era, vast amounts of next-generation sequencing data have become publicly available for multiple genomes across hundreds of species. Analyses of these large-scale datasets can become cumbersome, especially when comparing nucleotide polymorphisms across many samples within a dataset and among different datasets or organisms. To facilitate the exploration of allelic variation and diversity, we have developed and deployed an in-house computer software to categorize and visualize these haplotypes. The SNPViz software enables users to analyze region-specific haplotypes from single nucleotide polymorphism (SNP) datasets for different sequenced genomes. The examination of allelic variation and diversity of important soybean [Glycine max (L.) Merr.] flowering time and maturity genes may provide additional insight into flowering time regulation and enhance researchers'' ability to target soybean breeding for particular environments. For this study, we utilized two available soybean genomic datasets for a total of 72 soybean genotypes encompassing cultivars, landraces, and the wild species Glycine soja. The major soybean maturity genes E1, E2, E3, and E4 along with the Dt1 gene for plant growth architecture were analyzed in an effort to determine the number of major haplotypes for each gene, to evaluate the consistency of the haplotypes with characterized variant alleles, and to identify evidence of artificial selection. The results indicated classification of a small number of predominant haplogroups for each gene and important insights into possible allelic diversity for each gene within the context of known causative mutations. The software has both a stand-alone and web-based version and can be used to analyze other genes, examine additional soybean datasets, and view similar genome sequence and SNP datasets from other species.     

Maturity Group Classification and Maturity Locus Genotyping of Early-Maturing Soybean Varieties from High-Latitude Cold Regions

Background

With the migration of human beings, advances of agricultural sciences, evolution of planting patterns and global warming, soybeans have expanded to both tropical and high-latitude cold regions (HCRs). Unlike other regions, HCRs have much more significant and diverse photoperiods and temperature conditions over seasons or across latitudes, and HCR soybeans released there show rich diversity in maturity traits. However, HCR soybeans have not been as well classified into maturity groups (MGs) as other places. Therefore, it is necessary to identify MGs in HCRs and to genotype the maturity loci.

Methods

Local varieties were collected from the northern part of Northeast China and the far-eastern region of Russia. Maturity group reference (MGR) soybeans of MGs MG000, MG00, and MG0 were used as references during field experiments. Both local varieties and MGR soybeans were planted for two years (2010-2011) in Heihe (N 50°15′, E 127°27′, H 168.5 m), China. The days to VE (emergence), R1 (beginning bloom) and R7 (beginning maturity) were recorded and statistically analyzed. Furthermore, some varieties were further genotyped at four molecularly-identified maturity loci E1, E2, E3 and E4.

Results

The HCR varieties were classified into MG0 or even more early-maturing. In Heihe, some varieties matured much earlier than MG000, which is the most early-maturing known MG, and clustered into a separate group. We designated the group as MG0000, following the convention of MGs. HCR soybeans had relatively stable days to beginning bloom from emergence. The HCR varieties diversified into genotypes of E1, E2, E3 and E4. These loci had different effects on maturity.

Conclusion

HCRs diversify early-maturing MGs of soybean. MG0000, a new MG that matures much earlier than known MGs, was developed. HCR soybean breeding should focus more on shortening post-flowering reproductive growth. E1, E2, E3, and E4 function differentially.     

Diurnal Expression Pattern,Allelic Variation,and Association Analysis Reveal Functional Features of the E1 Gene in Control of Photoperiodic Flowering in Soybean

Although four maturity genes, E1 to E4, in soybean have been successfully cloned, their functional mechanisms and the regulatory network of photoperiodic flowering remain to be elucidated. In this study, we investigated how the diurnal expression pattern of the E1 gene is related to photoperiodic length; and to what extent allelic variation in the B3-like domain of the E1 gene is associated with flowering time phenotype. The bimodal expression of the E1 gene peaked first at around 2 hours after dawn in long-day condition. The basal expression level of E1 was enhanced by the long light phase, and decreased by duration of dark. We identified a 5bp (3 SNP and 2-bp deletion) mutation, referred to an e1-b3a, which occurs in the middle of B3 domain of the E1 gene in the early flowering cultivar Yanhuang 3. Subcellular localization analysis showed that the putative truncated e1-b3a protein was predominately distributed in nuclei, indicating the distribution pattern of e1-b3a was similar to that of E1, but not to that of e1-as. Furthermore, genetic analysis demonstrated allelic variations at the E1 locus significantly underlay flowering time in three F₂ populations. Taken together, we can conclude the legume specific E1 gene confers some special features in photoperiodic control of flowering in soybean. Further characterization of the E1 gene will extend our understanding of the soybean flowering pathway in soybean.     

The alleles at the E1 locus impact the expression pattern of two soybean FT-like genes shown to induce flowering in Arabidopsis

A small gene family of phosphatidyl ethanolamine-binding proteins (PEBP) has been shown to function as key regulators in flowering; in Arabidopsis thaliana the FT protein promotes flowering whilst the closely related TFL1 protein represses flowering. Control of flowering time in soybean [Glycine max (L.) Merrill] is important for geographic adaptation and maximizing yield. Soybean breeders have identified a series of loci, the E-genes, that control photoperiod-mediated flowering time, yet how these loci control flowering is poorly understood. The objectives of this study were to evaluate the expression of GmFT-like genes in the E1 near-isogenic line (NIL) background. Of the 20 closely related PEBP proteins in the soybean genome, ten are similar to the Arabidopsis FT protein. Expression analysis of these ten GmFT-like genes confirmed that only two are detectable in the conditions tested. Further analysis of these two genes in the E1 NILs grown under short-day (SD) and long-day (LD) conditions showed a diurnal expression and tissue specificity expression commensurate with soybean flowering time under SD and LD conditions, suggesting that these were good candidates for flowering induction in soybean. Arabidopsis ft mutant lines flowered early when transformed with the two soybean genes, suggesting that the soybean genes can complement the Arabidopsis FT function. Flowering time in E1 NILs is consistent with the differential expression of the two GmFT-like genes under SD and LD conditions, suggesting that the E1 locus, at least in part, impacts time to flowering through the regulation of soybean FT expression.     

Simple sequence repeat (SSR) markers linked to E1, E3, E4, and E7 maturity genes in soybean.

Soybean near isogenic lines (NILs), contrasting for maturity and photoperiod sensitivity loci, were genotyped with approximately 430 mapped simple sequence repeats (SSRs), also known as microsatellite markers. By analysis of allele distributions across the NILs, it was possible to confirm the map location of the Dt1 indeterminate growth locus, to refine the SSR mapping of the T tawny pubescence locus, to map E1 and E3 maturity loci with molecular markers, and to map the E4 and E7 maturity loci for the first time. Molecular markers flanking these loci are now available for marker-assisted breeding for these traits. Analysis of map locations identified a putative homologous relationship among four chromosomal regions; one in the middle of linkage group (LG) C2 carrying E1 and E7, one on LG I carrying E4, one at the top of LG C2, at which there is a reproductive period quantitative trait locus (QTL), and the fourth on LG B1. Other evidence suggests that homology also exists between the E1 + E7 region on LG C2 and a region on LG L linked to a pod maturity QTL. Homology relationships predict possible locations in the soybean genome of additional maturity loci, as well as which maturity loci may share a common evolutionary origin and similar mechanism(s) of action.     

Mapping and identification of a potential candidate gene for a novel maturity locus, <Emphasis Type="Italic">E10</Emphasis>, in soybean

Key message

E10 is a new maturity locus in soybean and FT4 is the predicted/potential functional gene underlying the locus.

Abstract

Flowering and maturity time traits play crucial roles in economic soybean production. Early maturity is critical for north and west expansion of soybean in Canada. To date, 11 genes/loci have been identified which control time to flowering and maturity; however, the molecular bases of almost half of them are not yet clear. We have identified a new maturity locus called “E10” located at the end of chromosome Gm08. The gene symbol E10e10 has been approved by the Soybean Genetics Committee. The e10e10 genotype results in 5–10 days earlier maturity than E10E10. A set of presumed E10E10 and e10e10 genotypes was used to identify contrasting SSR and SNP haplotypes. These haplotypes, and their association with maturity, were maintained through five backcross generations. A functional genomics approach using a predicted protein–protein interaction (PPI) approach (Protein–protein Interaction Prediction Engine, PIPE) was used to investigate approximately 75 genes located in the genomic region that SSR and SNP analyses identified as the location of the E10 locus. The PPI analysis identified FT4 as the most likely candidate gene underlying the E10 locus. Sequence analysis of the two FT4 alleles identified three SNPs, in the 5′UTR, 3′UTR and fourth exon in the coding region, which result in differential mRNA structures. Allele-specific markers were developed for this locus and are available for soybean breeders to efficiently develop earlier maturing cultivars using molecular marker assisted breeding.

     

Genetic and physical mapping of flowering time loci in canola (Brassica napus L.)

We identified quantitative trait loci (QTL) underlying variation for flowering time in a doubled haploid (DH) population of vernalisation—responsive canola (Brassica napus L.) cultivars Skipton and Ag-Spectrum and aligned them with physical map positions of predicted flowering genes from the Brassica rapa genome. Significant genetic variation in flowering time and response to vernalisation were observed among the DH lines from Skipton/Ag-Spectrum. A molecular linkage map was generated comprising 674 simple sequence repeat, sequence-related amplified polymorphism, sequence characterised amplified region, Diversity Array Technology, and candidate gene based markers loci. QTL analysis indicated that flowering time is a complex trait and is controlled by at least 20 loci, localised on ten different chromosomes. These loci each accounted for between 2.4 and 28.6 % of the total genotypic variation for first flowering and response to vernalisation. However, identification of consistent QTL was found to be dependant upon growing environments. We compared the locations of QTL with the physical positions of predicted flowering time genes located on the sequenced genome of B. rapa. Some QTL associated with flowering time on A02, A03, A07, and C06 may represent homologues of known flowering time genes in Arabidopsis; VERNALISATION INSENSITIVE 3, APETALA1, CAULIFLOWER, FLOWERING LOCUS C, FLOWERING LOCUS T, CURLY LEAF, SHORT VEGETATIVE PHASE, GA3 OXIDASE, and LEAFY. Identification of the chromosomal location and effect of the genes influencing flowering time may hasten the development of canola varieties having an optimal time for flowering in target environments such as for low rainfall areas, via marker-assisted selection.     

Map-Based Cloning of the Gene Associated With the Soybean Maturity Locus E3

Photosensitivity plays an essential role in the response of plants to their changing environments throughout their life cycle. In soybean [Glycine max (L.) Merrill], several associations between photosensitivity and maturity loci are known, but only limited information at the molecular level is available. The FT3 locus is one of the quantitative trait loci (QTL) for flowering time that corresponds to the maturity locus E3. To identify the gene responsible for this QTL, a map-based cloning strategy was undertaken. One phytochrome A gene (GmPhyA3) was considered a strong candidate for the FT3 locus. Allelism tests and gene sequence comparisons showed that alleles of Misuzudaizu (FT3/FT3; JP28856) and Harosoy (E3/E3; PI548573) were identical. The GmPhyA3 alleles of Moshidou Gong 503 (ft3/ft3; JP27603) and L62-667 (e3/e3; PI547716) showed weak or complete loss of function, respectively. High red/far-red (R/FR) long-day conditions enhanced the effects of the E3/FT3 alleles in various genetic backgrounds. Moreover, a mutant line harboring the nonfunctional GmPhyA3 flowered earlier than the original Bay (E3/E3; PI553043) under similar conditions. These results suggest that the variation in phytochrome A may contribute to the complex systems of soybean flowering response and geographic adaptation.FLOWERING represents the transition from the vegetative to the reproductive phase in plants. Various external cues, such as photoperiod and temperature, are known to initiate plant flowering under the appropriate seasonal conditions. Of these cues, light is the most important, being received by several photoreceptors, including the red light (R) and the far-red light (FR)-absorbing phytochromes and the blue/UV-A absorbing cryptochromes and phototorpins (Chen et al. 2004).Phytochrome is the best characterized of these photoreceptors. All higher plant phytochromes are thought to exist as specific dimer combinations (Sharrock and Clack 2004), with each monomer being attached to a light-absorbing linear tetrapyrrole, phytochromobilin. The phytochrome apoproteins are synthesized within the cytosol and assemble autocatalytically with a chromophore to form the phytochrome holoproteins. The R-absorbing form (Pr) is thought to be inactive but is then converted to the active FR-absorbing form (Pfr) by R absorption. The absorption of light triggers the transfer of the phytochrome to the nucleus, where it regulates gene expression. In most plant species, the phytochrome apoproteins are encoded by a small gene family. Type I phytochrome is degraded in the light and is abundant in dark-grown seedlings, whereas type II phytochrome is relatively stable in the light (reviewed by Bae and Choi 2008). In Arabidopsis, five phytochromes (PhyA–E) have been characterized (Clack et al. 1994; Quail et al. 1995). PhyA is type I and is responsible for the very low fluence response and high irradiance response, whereas the other phytochromes are type II and are responsible for red-far/red reversible low fluence response (reviewed by Whitelam et al. 1998).It is well known that mutations in the phytochrome A gene affect the photoperiodic control of flowering. In Arabidopsis, a phyA mutant flowered later in either long-day or short-day conditions with a night break (Johnson et al. 1994; Reed et al. 1994). In rice, combinations of mutant alleles of phytochrome genes conferred various effects on the flowering phenotype. For example, the phyA phyB and phyA phyC double mutants grown under natural-day-length conditions showed earlier flowering phenotypes than wild-type plants (Takano et al. 2005). In pea, a long-day plant, loss- or gain-of-function phyA mutants displayed late or early flowering phenotypes, respectively (Weller et al. 1997, 2001). It is likely that photoperiodic response via phyA signaling is important for crop adaptation to a wide range of growing conditions.In soybean [Glycine max (L.) Merrill], several maturity loci, designated as E loci (Cober et al. 1996a), have been characterized by classical methods. These are E1 and E2 (Bernard 1971), E3 (Buzzell 1971), E4 (Buzzell and Voldeng 1980), E5 (McBlain and Bernard 1987), E6 (Bonato and Vello 1999), and E7 (Cober and Voldeng 2001). Of these, the E1, E3, and E4 loci have been suggested to be related to photoperiod sensitivity under various light conditions (Saidon et al. 1989; Cober et al. 1996b; Abe et al. 2003). In previous studies, using the same populations as in this study, three flowering-time quantitative trait loci (QTL)—FT1, FT2, and FT3 loci—were identified and considered to be identical with the maturity loci E1, E2, and E3, respectively (Yamanaka et al. 2001; Watanabe et al. 2004). Although many loci related to soybean flowering and maturity have been identified, and some candidate genes were recognized using near isogenic lines (NILs) (Tasma and Shoemaker 2003), most of the genes responsible for these loci have not yet been isolated except for the E4 gene. Liu et al. (2008) reported an association between phytochrome A and photoperiod sensitivity. A retrotransposon sequence inserted into the exon of the e4 allele conferred an early flowering phenotype under long-day conditions extended by incandescent lighting.A relationship between the E3 gene and some photoreceptor genes was suggested from different photosensitivity responses of various soybean NILs (Cober et al. 1996a). Cober and Voldeng (1996) also reported a linkage relationship between the E3 and Dt1 loci, which is related to a determinate or indeterminate growth habit phenotype. Additionally, Molnar et al. (2003) reported that Satt229, on linkage group (LG) L, was a proximal simple sequence repeat (SSR) marker to the E3 loci. According to the Soybean Genome Database (Shultz et al. 2006a,b, 2007; http://soybeangenome.siu.edu/) and the Legume Information System (LIS; http://www.comparative-legumes.org/), there are numerous QTL and >60 loci associated with various agronomic traits in the region between Dt1 and Satt373 (∼30–40 cM). This extremely large number of QTL may be the result of linkage between the Dt1 and E3 loci because both loci can affect many aspects of plant morphology. Among these QTL, several associations with the E3 gene have been reported (Mansur et al. 1996; Orf et al. 1999; Funatsuki et al. 2005; Kahn et al. 2008).To identify the genes responsible for the target QTL, fine mapping and map-based cloning strategies are necessary (Salvi and Tuberosa 2005). QTL analysis using intercross-derived populations, such as F₂ and recombinant inbred lines (RILs), have some limitations in genome resolution (10–30 cM) because of the simultaneous segregation of several loci affecting the same trait (Kearsey and Farquhar 1998). Additional strategies are therefore required to locate QTL more precisely. The use of NILs that differ at a single QTL is an effective approach for fine mapping and characterization of an individual locus (Salvi and Tuberosa 2005). However, the development of NILs through repeated backcrossing is time-consuming and laborious (Tuinstra et al. 1997). The use of a residual heterozygous line (RHL), as proposed by Yamanaka et al. (2004), and which is derived from RIL, is a powerful tool for precisely evaluating QTL (Haley et al. 1994). An RHL harbors a heterozygous region where the target QTL is located and a homozygous background in most other regions of the genome. Tuinstra et al. (1997) used a similar term, heterogeneous inbred family, for a selfed RHL population to identify the QTL associated with seed weight in sorghum.This RHL strategy has already been used to identify loci underlying resistance to pathogens in soybean (Njiti et al. 1998; Meksem et al. 1999; Triwitayakorn et al. 2005). After identification of the target loci, novel DNA markers tightly linked to the loci were developed using the amplified fragment length polymorphism (AFLP) method (Meksem et al. 2001a,b). Physical contigs, screened by sequence-characterized amplified region (SCAR) markers converted from these AFLP fragments, are ideal sources for identifying candidate genes for the target traits (Ruben et al. 2006).The aim of this study is to characterize the FT3 locus using a map-based cloning strategy and to confirm the gene responsible for the E3/FT3 locus by allelism tests through comparisons of gene sequences and photosensitivity of several alleles.     

Molecular mechanisms for the photoperiodic regulation of flowering in soybean

Photoperiodic flowering is one of the most important factors affecting regional adaptation and yield in soybean (Glycine max). Plant adaptation to long-day conditions at higher latitudes requires early flowering and a reduction or loss of photoperiod sensitivity; adaptation to short-day conditions at lower latitudes involves delayed flowering, which prolongs vegetative growth for maximum yield potential. Due to the influence of numerous major loci and quantitative trait loci (QTLs), soybean has broad adaptability across latitudes. Forward genetic approaches have uncovered the molecular basis for several of these major maturity genes and QTLs. Moreover, the molecular characterization of orthologs of Arabidopsis thaliana flowering genes has enriched our understanding of the photoperiodic flowering pathway in soybean. Building on early insights into the importance of the photoreceptor phytochrome A, several circadian clock components have been integrated into the genetic network controlling flowering in soybean: E1, a repressor of FLOWERING LOCUS T orthologs, plays a central role in this network. Here, we provide an overview of recent progress in elucidating photoperiodic flowering in soybean, how it contributes to our fundamental understanding of flowering time control, and how this information could be used for molecular design and breeding of high-yielding soybean cultivars.     

Genomic selection in soybean: accuracy and time gain in relation to phenotypic selection

Genomic selection (GS) can potentially accelerate genetic improvement of soybean [Glycine max L. (Merrill)] by reducing the time to complete breeding cycles. The objectives of this study were to (1) explore the accuracy of GS in soybean, (2) evaluate the contribution of intrapopulational structure to the accuracy of GS, and (3) compare the efficiencies of phenotypic selection and GS in soybean. For this, phenotypic and genotypic data were collected from 324 soybean genotypes (243 recombinant inbred lines and 81 cultivars) and GS was performed for five yield related traits. BayesB methodology with a 10-fold cross-validation was used to compute accuracies. The GS accuracies were evaluated for grain yield, plant height, insertion of first pod, days to maturity, and 1000-grain weight at eight locations. We found that GS can reduce the time required to complete a selection cycle in soybean, which can lead to increased production of this commercially important crop. Furthermore, genotypic accuracy was similar regardless of population structure correction.     

Nucleotide diversity of the upstream region of the putative MADS-box gene controlling soybean maturity

MADS-box genes are involved in plant reproductive development. However, the role of gene nucleotide diversity in soybean flowering and maturity remains unknown. Therefore, in this study, the distribution of DNA polymorphisms in the putative MADS-box gene located near the quantitative trait loci (QTL) for flowering time and maturity was targeted for association analysis using Glycine max (cultivated soybean) and Glycine soja (wild soybean). Sixteen single nucleotide polymorphisms identified in the upstream region of the putative MADS-box gene around QTL Pod mat 13-7 and Fflr 4-2 on chromosome 7 were found to be highly associated with maturity in soybean. The genetic diversity between cultivated soybeans and the wild relative was comparable, although the early maturity group (EMG) was less diverse than the late maturity group (LMG) of the cultivated soybean. Population size changes of the MADS-box gene in this soybean germplasm appeared to result from non-random selection. A selective pressure seemed to act on this gene in the EMG, while the LMG and G. soja were in genetic equilibrium. Neutrality tests and the constructed neighbor-joining tree indicate that the EMG of G. max has experienced strong artificial selection for its domestication and genetic improvement.