Legume Research

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Legume Research, volume 44 issue 8 (august 2021) : 867-874

Identification of QTLs Associated with Two-seed Pod Length and Width in Soybean

D.P. Shan1, J.G. Xie1, Y. Yu2, R. Zhou1, Z.L. Cui1, Q.S. Chen1,*, F.L. Meng1,*
1Key Laboratory of Soybean Biology of Chinese Ministry of Education, Key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry, College of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang, People’s Republic of China.
2Changchun Sci-Tech University, Changchun, 130600, China.
  • Submitted06-02-2021|

  • Accepted19-04-2021|

  • First Online 23-07-2021|

  • doi 10.18805/LR-615

Cite article:- Shan D.P., Xie J.G., Yu Y., Zhou R., Cui Z.L., Chen Q.S., Meng F.L. (2021). Identification of QTLs Associated with Two-seed Pod Length and Width in Soybean . Legume Research. 44(8): 867-874. doi: 10.18805/LR-615.
Background: Two-seed pod length and width (TSPL and TSPW, respectively) are the traits underlying seed size, which is an important factor influencing soybean yield.

Methods: A population comprising 213 chromosome segment substitution lines from a cross between ‘Suinong14’ (SN14) and ZYD00006 was used for a quantitative trait locus (QTL) analysis. The QTLs were identified on the basis of the phenotypes from 2016 to 2019. Additionally, IciMapping 4.2 was used to analyze the phenotypic and genetic data. Genes were annotated using the KEGG and Phytozome databases.

Result: Five QTLs for TSPL and four QTLs for TSPW were identified. One QTL on chromosome 17 was detected for TSPL in 2017 and 2018 as well for TSPW in 2018 and 2019. Analyses of the additive × additive epistatic effects of QTLs revealed six stable loci pairs for epistatic effects on the two traits. On the basis of an alignment of the parental gene sequences and the gene annotation information, Glyma.04G188800, Glyma.11G164700, Glyma.13G132700, Glyma.17G156100 and Glyma.13G133200 were selected as candidate genes for TSPL, whereas Glyma.13G174400, Glyma.13G174700, Glyma.16G012500, Glyma.17G156100, Glyma.19G161700 and Glyma.19G161800 were selected as candidate genes for TSPW. These results may be relevant for future attempts to modify soybean seed traits.
As an important oil crop and the largest source of plant proteins, soybean [Glycine max (L.) Merr.] is commonly cultivated worldwide (Li et al., 2019). High and stable yields have always been the main goals of soybean breeding programs. Previous research revealed a significant positive correlation between seed yield and pod length (Basavaraja et al., 2010). The soybean pod length and width are believed to be significantly positively correlated with seed size (Fraser et al., 1982). Additionally, pod width is the most effective trait for indirect selection (Frank and Fehr, 1981).
Quantitative trait locus (QTL) mapping has been used to examine quantitative traits in many crops, including plant height in maize, seed yield in soybean and grain weight in rice (Bian et al., 2013). Some studies proved that epistatic effects are the main genetic basis for quantitative traits (Chase et al., 1997; Ha et al., 2012). For self-bred crops, additive × additive epistatic effects can be stably inherited via selective breeding. Moreover, if additive × additive epistatic effects exist, then additional genetic gains would be generated during selective breeding (Kulwal et al., 2005). An earlier investigation confirmed the utility of an epistatic QTL analysis for mining important QTLs that cannot be detected using classical mapping methods (Bocianowski, 2013).
In this study, a population comprising 213 chromosome segment substitution lines (CSSL) were constructed by crossing soybean cultivar ‘Suinong14’ (SN14) with wild soybean ZYD00006 for the QTL mapping of two-seed pod length (TSPL) and two-seed pod width (TSPW). We studied the epistatic effects of loci to obtain stably interacting loci pairs. The results of this study provide the theoretical basis for marker-assisted breeding of soybean lines with enhanced pod traits.
Plant material planting and phenotypic determination
The donor and recurrent parents of the CSSL were respectively wild soybean ZYD00006 and SN14, which is the main soybean cultivar grown in Heilongjiang province, China. In October of each year (2016-2019), five similarly growing individuals in each line were selected for TSPL and TSPW measurements in the field. Two-seed pods were randomly selected for measurements. On the basis of a variance analysis, the AOV model in the QTL IciMapping (version 4.2) program was used to test the correlation between TSPL and TSPW.
QTL analysis in the CSSL population
The molecular marker information for the QTLs was obtained from a published report (Li et al., 2019). The CSL module of the IciMapping 4.2 program was used for QTL mapping. Phenotypic data were analyzed in a permutation test (1,000 permutations) and the significance threshold was set at P = 0.05 for detecting QTLs (Sun et al., 2013). The QTLs were named as previously described (McCouch et al., 1997). More specifically, QTL names consisted of the following: q + trait + LG or LG number + QTL number. All genes in QTL intervals were extracted and their functions were annotated on the basis of the Kyoto Encyclopedia of Genes and Genomes (KEGG) (https://www.kegg.jp/), gene ontology (GO) (https:// www.ebi.ac.uk/QuickGO/) and Pfam (https://pfam.xfam.org/) databases.
Analysis of candidate genes
Amino acid sequences were predicted using the ExPASy website (https://web.expasy.org/translate/). The cis-elements in the 3,000-bp promoter upstream of genes were analyzed using the PlantCARE online tools (http://bioinformatics. psb.ugent.be/ webtools/plantcare/html/). The SoyBase (https://www.soybase.org/) and Phytozome (https://phytozome.jgi. doe.gov/pz/ portal.html) databases were used to examine the expression of various genes in soybean.
Phenotypic data for TSPL and TSPW
Over the 4-year study period, the average TSPL ranged from 3.25 to 3.63 (Table 1). The average TSPW ranged from 0.91 to 0.97 and the CV was between 6.2% and 7.6%. The four QTLs associated with TSPL from 2016 to 2019 were distributed on linkage groups Chrom11, Chrom13, Chrom17, Chrom04 and Gm17 (Table 2). The PVE% (i.e., the contribution of the QTLs) for all QTLs ranged from 5.17 to 35.29 and the LOD was between 4.41 and 25.68. The QTLs varied in size from 22.24 kb to 54.82 kb. Additionally, qTSPL-D2-1, which was detected in 2017 and 2018, was distributed between 13,261,056 bp and 13,283,299 bp on the D2 linkage group, with the highest PVE%, LOD and additive effect (35.29, 25.68 and 0.35, respectively) as well as the smallest interval (22.24 kb) in 2018.

Table 1: TSPL and TSPW of the parents and a CSSL population analyzed from 2016 to 2019.


Table 2: Details regarding the QTLs identified for TSPL and TSPW.

Fig 1: Frequency distribution of TSPL and TSPW in the CSSL population from 2016 to 2019.

From 2016 to 2019, four QTLs affecting TSPW were identified on four linkage groups, namely Chrom13 (1), Chrom16 (1), Chrom19 (1) and Chrom17 (2) (Table 2). In this study, the locations of four QTLs for TSPL and four QTLs for TSPW were determined. The qTSPL-B1-1 region included a QTL for soybean pod maturity that was previously identified in 2 consecutive years (PVE of 21.1% and 13.7%) (Lee et al., 2015). The qTSPL-F-1 region also contained a previously detected QTL for soybean pod maturity (Bachlava et al., 2009). The qTSPL-D2-1 and qTSPW-D2-1 region included a QTL underlying the number of pods (Li et al., 2010) as well as a QTL for seed weight (Kuroda et al., 2013). The qTSPW-F-1 region comprised QTLs related to seed size (Hyten et al., 2004) and grain weight (Yan et al., 2014). The qTSPW-L-1 region included a QTL for seed width (Salas et al., 2006). Because of the correlation between pods and seeds, these regions may contain important gene(s) controlling pod and seed development. Two QTLs (qTSPL-D2-1 and qTSPW-D2-1) were localized to the same position and their additive effects and PVE were higher than those of the other QTLs. Furthermore, the additive effects were positive, implying the two traits are related at both the phenotypic and genetic levels.
Analysis of the epistatic effects on TSPL and TSPW in the CSSL population
A total of 428 loci pairs had epistatic effects on TSPL (Table 3). Some of the QTLs detected during the analysis of epistatic effects were not included among the identified additive effect QTLs (Fig 2). Six pairs of stable QTLs were detected for TSPL and TSPW in 2017, 2018 and 2019. Additionally, qTSPL-D2-1 and qTSPW-D2-1, which were revealed as additive effect QTLs, had epistatic effects with non-additive effect QTLs, including qTSPW-D1b-1, qTSPW-D1a-1 and qTSPL-D2-2 (Table 4).

Table 3: Summary of the analysis of the epistatic effects on soybean TSPL and TSPW.


Table 4: Stable loci pairs for epistatic effects on soybean TSPL and TSPW.


Fig 2: (a) Loci pairs with additive × additive epistatic effects on TSPL in the CSSL population. (b) Loci pairs with additive × additive epistatic effects on TSPW in the CSSL population. Green, red, blue and orange lines represent additive × additive epistatic effects for TSPW and TSPL in 2016, 2017, 2018 and 2019, respectively.

Analysis of candidate genes
The additive effect QTL intervals comprised 23 genes (Fig 3, Table 5). The amino sequences encoded by these 23 candidate genes in SN14 and ZYD00006 were predicted and analyzed, which revealed sequence variations between the parents in the proteins encoded by the following seven genes (Fig 4): Glyma.13G132700, Glyma.13G132800, Glyma.13G133200, Glyma.13G174400, Glyma.13G174700, Glyma.16G012500 and Glyma.19G161700. Twelve genes were identified with variations in the promoter and coding region (Figs 5, 6 and Table 6).

Table 5: Annotated genes in candidate intervals.


Table 6: Candidate gene promoter cis-elements in the parents.


Fig 3: Gene distributions in QTL intervals.


Fig 4: Amino acid sequence variations between the parents.


Fig 5: Heat map of the expression levels of the candidate genes in various soybean tissues and developmental stages.


Fig 6: Heat map of the expression levels of the candidate genes in various soybean tissues and developmental stages.

The Arabidopsis thaliana RGE1 gene encodes a GDSL lipase, which influences plant growth and development. An earlier study indicated this gene is expressed in the endosperm and may regulate embryo development (Kondou et al., 2008). The EXL4 gene, which also belongs to the GDSL lipase family, encodes an extracellular lipase localized to the pollen wall, wherein it regulates pollen tube development. Previous research confirmed Glyma.04G188800 is a WNK family member that regulates the growth of soybean lateral roots through ABA signaling pathways (Wang et al., 2010). In A. thaliana, WNK3 is an important kinase for regulating the cell volume and/or intracellular chloride concentration (Diana and Gerardo, 2011). The Glyma.19G161700 gene was identified as a homolog of AT2G30580, which belongs to the DREB2A-interacting protein 2 family (Sakuma et al., 2006). Moreover, Glyma.11G164700 participates in the phenylpropanoid biosynthesis pathway (Peer and Murphy, 2007), whereas Glyma.13G133200 encodes a kinesin family member. A previous study indicated that kinesins help regulate cell division (Piao et al., 2016). Furthermore, Glyma.13G174700 is a NAC family gene. The effects of the NAC family on plant drought resistance and the regulation of ABA signaling have been characterized (Nguyen et al., 2018). Friedrichsen identified three closely related basic helix-loop-helix (bHLH) transcription factors (BEE1, BEE2 and BEE3) encoded by early response genes required for a complete BR response. A comparison of the phenotypes of plants overexpressing BEE1 and bee1 bee2 bee3 triple-knockout mutant plants suggested that BEE1, BEE2 and BEE3 are functionally redundant positive regulators of BR signaling. Rybel proposed that an auxin-regulated bHLH transcription factor dimer is a critical regulator of vascular development (Rybel et al., 2013). In A. thaliana, the bHLH-type transcription factor AtAIB positively regulates ABA responses (Li et al., 2007). The Glyma.19G161800 gene is a member of the PRA1 gene family. The fact that PRA1 homologs are ubiquitous in human tissues reflects their importance for development (Schweneker et al., 2005). The A. thaliana AtPRA1 genes are expressed in stomata, trichomes and vascular tissues, implying they can contribute to rapid cell expansion and growth. The protein encoded by Glyma.13G174400 bears a Fork-head-associated (FHA) domain, which is a phosphoprotein-binding sequence in diverse signaling proteins that bind to proteins with phosphorylated threonine or serine residues. The FHA domain of the kinase-associated protein phosphatase in A. thaliana negatively regulates the receptor-like kinase signaling pathways, which are important for plant development. The pathway associated with Glyma.13G132700 is K01099 (phosphatidylinositol-bisphosphatase; EC:, suggesting it plays a key role in the formation of cotyledon veins (Carland and Nelson, 2004).
Seed traits have critical effects on soybean yield. On the basis of our QTL analysis, we identified five QTLs for TSPL and four QTLs for TSPW. We selected Glyma.04G188800, Glyma.11G164700, Glyma.13G132700, Glyma.17G156100 and Glyma.13G133200 as candidate genes for TSPL, whereas Glyma.13G174400, Glyma.13G174700, Glyma.16G012500, Glyma.17G156100, Glyma.19G161700 and Glyma.19G161800 were selected as candidate genes for TSPW. These candidate genes should be investigated further in future studies on soybean seed traits.
The funding name and accesion number is 'The project of science and technology for the education department of Jilin province (Project number:JJKH20211432KJ)'.

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