Quantitative Trait Loci and Candidate Genes That Control Seed Sugars Contents in the Soybean ‘Forrest’ by ‘Williams 82’ Recombinant Inbred Line Population
by
, , , , , and
Dounya Knizia
1,
Nacer Bellaloui
2,
Jiazheng Yuan
3,
Naoufal Lakhssasi
1,
Erdem Anil
1,
Tri Vuong
4,
Mohamed Embaby
1,
Henry T. Nguyen
4
,
Alemu Mengistu
5,
Khalid Meksem
1 and
My Abdelmajid Kassem
3,* 1
School of Agricultural Sciences, Southern Illinois University, Carbondale, IL 62901, USA
2
USDA, Agriculture Research Service, Crop Genetics Research Unit, 141 Experiment Station Road, Stoneville, MS 38776, USA
3
Plant Genomics and Biotechnology Lab, Department of Biological and Forensic Sciences, Fayetteville State University, Fayetteville, NC 28301, USA
4
Division of Plant Science and Technology, University of Missouri, Columbia, MO 65211, USA
5
USDA, Agriculture Research Service, Crop Genetics Research Unit, 605 Airways Blvd, Jackson, TN 38301, USA
*
Author to whom correspondence should be addressed.
Plants 2023, 12(19), 3498; https://doi.org/10.3390/plants12193498
Submission received: 29 August 2023
/
Revised: 3 October 2023
/
Accepted: 6 October 2023
/
Published: 8 October 2023
(This article belongs to the Special Issue QTL Mapping of Seed Quality Traits in Crops)
Abstract
:Soybean seed sugars are among the most abundant beneficial compounds for human and animal consumption in soybean seeds. Higher seed sugars such as sucrose are desirable as they contribute to taste and flavor in soy-based food. Therefore, the objectives of this study were to use the ‘Forrest’ by ‘Williams 82’ (F × W82) recombinant inbred line (RIL) soybean population (n = 309) to identify quantitative trait loci (QTLs) and candidate genes that control seed sugar (sucrose, stachyose, and raffinose) contents in two environments (North Carolina and Illinois) over two years (2018 and 2020). A total of 26 QTLs that control seed sugar contents were identified and mapped on 16 soybean chromosomes (chrs.). Interestingly, five QTL regions were identified in both locations, Illinois and North Carolina, in this study on chrs. 2, 5, 13, 17, and 20. Amongst 57 candidate genes identified in this study, 16 were located within 10 Megabase (MB) of the identified QTLs. Amongst them, a cluster of four genes involved in the sugars’ pathway was collocated within 6 MB of two QTLs that were detected in this study on chr. 17. Further functional validation of the identified genes could be beneficial in breeding programs to produce soybean lines with high beneficial sucrose and low raffinose family oligosaccharides.
Keywords:
soybean; RIL; Forrest; Williams 82; linkage map; RFOs; sucrose; raffinose; stachyose; SNPs1. Introduction
Sugars, including sucrose, stachyose, glucose, raffinose, galactose, fructose, rhamnose, and starch, play a major role in seed and fruit development and seed desiccation tolerance (DT) [1,2,3,4]. Sucrose and raffinosaccharides (raffinose and stachyose), also called raffinose family oligosaccharides (RFOs), make up 5–7%, 1%, and 3–4% of total carbohydrates, respectively, of soybean seed dry weights [5]. RFOs are synthesized from sucrose through a series of additions of galactinol units and are involved in DT, freezing, stress tolerance, and seed longevity [6,7,8,9]. Galactinol synthase (GolS) is the key enzyme in the RFO biosynthetic pathway converting galactinol and myo-inositol as the main precursors to form RFOs. Galactinol synthase (GolS) converts myo-inositol and UDP-galactose into galactinol, while sucrose and galactinol are converted into raffinose by raffinose synthase [9,10]. In addition to being involved in stress tolerance, RFOs are reported to play a role in several signal transduction pathways [11], exports of specific mRNAs [12], and trafficking of certain vesicle membranes [13].
Like most seed components, seed sugars [4] are influenced by many factors, including abiotic and biotic stresses, and environmental factors, such as temperature, soil moisture, freezing, seed maturity, and growth conditions [1,14,15,16,17,18,19]. It was shown that stachyose contents increased drastically in drying seeds but not in seeds kept at high humidity levels, which reveals the critical role of stachyose in DT [1]. The effect of water deficit (WD) on enzymes involved in sugar biosynthetic pathways in soybean nodules was investigated. Sucrose synthase activity declined drastically with increased WD while sucrose content increased [14]. Other studies showed that WD impacts negatively on sucrose biosynthesis and translocation from sources to sinks more than other sugars’ (raffinose and stachyose) biosynthesis [16,19]. Investigating ‘Clark’ and ‘Harosoy’ near-isogenic lines (NILs) revealed that Clark’s sugar contents decreased with increased days of maturity for both cultivars while both positive and negative effects were observed concerning the effects of temperature in two different years (2004 and 2005) [15]. In 2004, seed sugar contents increased with temperature increase, while the contents decreased with increased temperatures in 2005 [15]. The effect of WD on several seed components, including sugars, was investigated in several susceptible and resistant Phomopsis soybean cultivars. Sugar (sucrose, raffinose, and stachyose) contents were higher in seeds of resistant maturity group III cultivars than their susceptible counterparts [16]. A recent study investigated the effect of soil moisture on seed sugars (sucrose, raffinose, stachyose) and starch contents among other compounds in two soybean cultivars in maturity group V (Asgrow, AG6332, and Progeny 5333RY) and showed that sucrose, stachyose, and raffinose contents, in addition to the mineral nutrient (N, P, K, and Ca) contents, decreased with increased soil moisture in both cultivars [17].
During recent decades, more than 53 QTLs that control seed sucrose and RFOs, other sugars (glucose, galactose, fructose, fucose, rhamnose), and starch contents have been reported using different biparental and natural populations and mapping methods including single marker analysis, interval mapping (IM), composite interval mapping (CIM), and genome-wide association studies (GWASs) [18,20]. However, to our knowledge, only a few of these studies identified candidate genes within these QTL regions, as summarized in [18]. There is Glyma.01g127600, which encodes for a protein phosphatase on chr. 1; Glyma.03g019300, which encodes for a MADS-box protein; Glyma.03g064700, which encodes for a phosphatidylinositol monophosphate-5-kinase on chr. 3; and Glyma.06g194200, which encodes for a gibberellin-regulated protein on chr. 6 [18,21].
To improve seed quality, several attempts to manipulate seed sugars, phytic acid, and the contents of other beneficial compounds have been made in recent years [22,23,24]. Monogastric animals (such as poultry and pigs) and humans do not produce α-galactosidase and cannot digest RFOs, which reduces gastrointestinal performance, flatulence, and diarrhea. Therefore, reducing raffinose and stachyose and increasing sucrose in soybean seed contents are desirable and the main goals in breeding programs [22,23,24,25,26,27]. The objective of this study was to genetically map QTLs for seed sucrose, raffinose, and stachyose contents using the ‘Forrest’ by ‘Williams 82’ RIL population, in addition to identifying candidate genes involved in soybean seed sugar biosynthesis.
2. Materials and Methods
2.1. Plant Materials
The ‘Forrest’ × ‘Williams 82’ RIL population (F × W82, n = 309) was previously studied and described in detail in our previous research [28,29]. The parents and RILs were evaluated in two locations: Spring Lake, NC (35.17° N, 78.97° W, 2018) and Carbondale, IL (37° N, 89° W, 2020). Briefly, seed parents and RIL seeds were grown in a randomized block design with 25 cm row spaces and three replicates. More details about growth conditions, crop management, and seed harvesting were described earlier [28,29].
2.2. Seed Sugar Quantification
RILs, parents (Forrest and Williams 82), and soybean germplasm seeds were harvested at maturity, and sugar (sucrose, raffinose, and stachyose) contents (%) were quantified using near-infrared reflectance (NIR) with an AD 7200 array feed analyzer (Perten, Springfield, IL, USA) as described earlier [15,30].
2.3. DNA Isolation, SNP Genotyping, and Genetic Map Construction
Parents’ and RILs’ genomic DNA was extracted using the cetyltrimethylammonium bromide (CTAB) method as previously described [31]. A NanoDrop spectrophotometer (NanoDrop Technologies Inc., Centreville, DE, USA) was used to quantify DNA samples (50 ng/µL), and genotyping was performed using the Illumina Infinium SoySNP6K BeadChips (Illumina, Inc., San Diego, CA, USA) as described earlier [15] at the Soybean Genomics and Improvement Laboratory (USDA-ARS, Beltsville, MD, USA). The F × W82 genetic linkage map was constructed using JoinMap 4.0 [28,32] as previously described to detect QTLs for seed isoflavones [28] and seed tocopherol contents [29].
2.4. Sugar QTL Detection
WinQTL Cartographer [33] interval mapping (IM) and composite interval mapping (CIM) methods were used to identify QTLs that control seed sugar (sucrose, stachyose, and raffinose) contents in this RIL population. The following parameters were used: Model 6, 1 cM step size, 10 cM window size, 5 control markers, and 1000 permutations. Furthermore, chromosomes were drawn using MapChart 2.2 [34].
2.5. Sugars Biosynthesis Candidate Genes’ Identification
The Glyma numbers of the sucrose and RFO biosynthesis genes were obtained via reverse BLAST of the genes underlying the RFO pathway in Arabidopsis using the available data in SoyBase. The sequences of the Arabidopsis genes were obtained from the Phytozome database (https://phytozome-next.jgi.doe.gov; accessed on 15 August 2023). These sequences were used for Blast in SoyBase. The obtained genes that control the RFO pathway were mapped to the identified sugars’ QTLs.
2.6. Expression Analysis
The expression analysis of the identified candidate genes was performed using the publicly available data from SoyBase [20] to produce the expression profiles of these candidate genes in the soybean reference genome Williams 82 in the Glyma1.0 Gene Models version.
2.7. Comparison of the Williams 82 and Forrest Sequences
Sequences of Forrest and Williams 82 cv. were obtained from the variant calling and haplotyping analysis, which was performed using 108 soybean germplasm sequenced lines as described previously [35].
3. Results
3.1. Sugar Frequency Distribution
The frequency distributions among sucrose, raffinose, and stachyose contents were quite different in the F × W82 RIL population based on the Shapiro–Wilk method for the normality test. Raffinose (2018), stachyose (2018), and sucrose (2020) were normally distributed. Only positive or negative skewness were identified in the RIL population, and all kurtosis values of these variables were positive (Table 1; Figure 1). In terms of coefficient of variation (CV), the value of sucrose 2018 showed the highest percentage of variation (62.86%) compared to other assessed traits, and the rest of the CVs appeared to be less varied within these two years. The histogram of sucrose 2018 was extremely skewed, and the other traits evaluated were normally distributed.
The broad-sense heritability (h2b) of seed sugar weight for sucrose, raffinose, and stachyose contents across two different environments appeared quite different. Stachyose had the highest heritability (92%), and the h2b for sucrose was 36.8% (Table 2). However, no negative h2b values for sugar contents were observed. The RIL–year interactions still played a significant role in the molecular formation among the three sugar contents in soybean seeds. The Sum Sq and Mean Sq to determine σG2 and σGE2 for each trait (Table 2) using the type I sum of squares (ANOVA (model)) function in the R program were implemented.
3.2. Sugars Contents’ QTLs
IM and CIM were used to identify QTLs for seed sugar contents in this F × W82 RIL population; however, only QTLs identified by CIM are presented here. The QTLs identified with the IM method are reported in Tables S1 and S2. A total of 26 QTLs that control seed sugar contents were identified in both NC-2018 (19 QTLs) and IL-2020 (7 QTLs) via CIM (Table 3 and Table 4; Figure S1).
In Spring Lake, NC in 2018 (NC-2018), 12 QTLs that control seed sucrose content (qSUC-1–qSUC-12) were identified and mapped on Chrs. 1, 2, 3, 4, 5, 6, 9, 10, 13, 17, 18, and 19; 4 QTLs that control seed stachyose content (qSTA-1–qSTA-4) were identified and mapped on Chrs. 13 and 19; and 3 QTLs that control seed raffinose content (qRAF-1–qRAF-3) were identified and mapped on Chr. 9 and 12 (Table 3 and Table 5; Figure S1). Likewise, in Carbondale, IL in 2020 (IL-2020), 3 QTLs that control seed sucrose content (qSUC-1–qSUC-3) were identified and mapped on Chrs. 2, 5, and 8; and 4 QTLs that control seed stachyose content (qSTA-1–qSTA-4) were identified and mapped on Chrs. 13, 16, 17, and 20 (Table 4 and Table 6; Figure S1). No QTL that controls seed raffinose content was identified in this location.
No QTL for seed sugar contents was identified in other studies within the QTL regions on chr. 4 (qSUC-4-NC-2018, 6.5–16.5 cM), chr. 10 (qSUC-8-NC-2018, 214.1–216.1 cM), or chr. 18 (qSUC-11-NC-2018, 20.1–17.5 cM), which indicates they are novel QTL regions.
3.3. In Silico Sucrose, Raffinose, and Stachyose Biosynthetic Pathway Genes in Soybean
In the literature, the sugar (sucrose, raffinose, and stachyose) biosynthetic pathway was studied in many plants, including the plant model Arabidopsis thaliana [36,37] and the leguminous model Medicago sativa L. [38]. A reverse BLAST of the genes identified in Arabidopsis thaliana was conducted using SoyBase [20] to reconstruct the sugar (sucrose, raffinose, and stachyose) biosynthetic pathway in soybean (Figure 2).
A total of fifty-seven candidate genes were identified to underly the sugar (sucrose, raffinose, and stachyose) biosynthetic pathway (Figure 2). In this pathway, twelve candidate genes were identified for invertase: Glyma.05G185500, Glyma.20G177200, Glyma.08G043800, Glyma.10G214700, Glyma.08G143500, Glyma.05G236600, Glyma.17G037400, Glyma.10G145600, Glyma.20G095200, Glyma.07G236000, Glyma.02G016700, and Glyma.10G017300. Twelve candidate genes were identified for sucrose synthase: Glyma.02G240400, Glyma.03G216300, Glyma.09G073600, Glyma.09G167000, Glyma.13G114000, Glyma.14G209900, Glyma.15G151000, Glyma.16G217200, Glyma.17G045800, Glyma.19G212800, Glyma.11G212700, and Glyma.15G182600. Twelve candidate genes were identified for UDP-D-Glucose-4-Epimerase: Glyma.08G023100, Glyma.01G225800, Glyma.05G204700, Glyma.05G217100, Glyma.07G237700, Glyma.07G271200, Glyma.08G011800, Glyma.11G017100, Glyma.12G162600, Glyma.17G035800, Glyma.18G145700, and Glyma.18G211700. For galactinol synthase, six candidate genes were identified: Glyma.03G222000, Glyma.03G229800, Glyma.10G145300, Glyma.19G219100, Glyma.19G227800, and Glyma.20G094500. Fourteen candidate genes were identified for raffinose synthase: Glyma.03G137900, Glyma.04G145800, Glyma.19G140700, Glyma.04G190000, Glyma.02G303300, Glyma.05G003900, Glyma.06G175500, Glyma.09G016600, Glyma.13G160100, Glyma.14G010500, Glyma.17G111400, Glyma.19G004400, Glyma.05G040300, and Glyma.06G179200. For stachyose synthase, only one candidate gene was identified: Glyma.19G217700 (Figure 2).
3.4. Association between the Identified Sugar (Sucrose, Raffinose, and Stachyose) Biosynthetic Pathway Candidate Genes and Reported QTLs
The identified genes for sugar (sucrose, raffinose, and stachyose) biosynthesis in soybean were mapped to the identified QTLs. Amongst fifty-seven candidate genes, sixteen were located less than 10 MB from the identified QTLs on chrs. 2, 5, 6, 8, 9, 10, 17, and 19 (Table 3, Table 4, Table 5 and Table 6).
The sucrose synthase candidate gene Glyma.09G073600 and the raffinose synthase candidate gene Glyma.09G016600 are positioned close to qSUC-7-IL-2018, qRAF-1-IL-2018, and qRAF-2-IL-2018 on Chr.9 (Table 3, Table 4, Table 5 and Table 6). The invertase candidate gene Glyma.02G016700 is located 3.6 and 0.2 MB away from qSUC-1-IL-2018 and qSUC-1-NC-2020, respectively, on Chr. 2 (Table 3, Table 4, Table 5 and Table 6). The raffinose synthase candidate genes Glyma.05G003900 and Glyma.05G040300 are located close to qSUC-5-IL-2018 and qSUC-2-NC-2020 on Chr. 5 (Table 3, Table 4, Table 5 and Table 6). On chr. 6, the raffinose synthase candidate gene Glyma.06G175500 is located close to qSUC-6-IL-2018 (Table 3, Table 4, Table 5 and Table 6). The invertase candidate genes Glyma.08G043800 and Glyma.08G143500, and the UDP-D-Glucose-4-Epimerase candidate genes Glyma.08G011800 and Glyma.08G023100 on chr. 8 are located close to qSUC-3-NC-2020 (Table 3, Table 4, Table 5 and Table 6, Tables S3 and S4). On chr. 10, the invertase candidate gene Glyma.10G017300 is located close to qSUC-8-IL-2018 (Table 3, Table 4, Table 5 and Table 6). On Chr. 17, a cluster of four genes involved in the sugar pathway is collocated within 6 MB of two QTLs (qSUC-10-NC-2018 and qSTA-3-IL-2020) that were identified in this study. These genes are Glyma.17G037400 encoding for an invertase, Glyma.17G045800 encoding for sucrose synthase, Glyma.17G111400 encoding for raffinose synthase, and Glyma.17G035800 encoding for UDP-D-glucose-4-epimerase (Table 3, Table 4, Table 5 and Table 6, Figure S3). The raffinose synthase candidate gene Glyma.19G004400 is positioned close to qSTA-3-IL-2018 and qSTA-4-IL-2018 (Table 3, Table 4, Table 5 and Table 6), as well as qRAF-8-IL-2018 and qRAF-9-IL-2018 identified using the IM method (Table 3 and Table 4).
3.5. Association between the Identified Candidate Genes and the Previously Reported QTLs
Several studies have identified and mapped QTLs underlying the seed sugar content using different populations and mapping methods [39,40,41,42], as summarized in [18].
The identified genes have been mapped to the previously reported QTL regions associated with the seed sugar content using data from SoyBase [18,20,43]. In this study, 6 candidate genes were located within the identified seed sugar QTLs and 18 were located <9 MB away from these regions (Table 7). Among them is the invertase candidate gene Glyma.08G143500, which is located within the seed sucrose 1-2 QTL on Chr. 8 [20,39]. Also, the galactinol-sucrose galactosyl-transferase 6-related candidate gene Glyma.13G160100 is situated within the seed sucrose 1-5 QTL [20,39] (Table 7). Likewise, the raffinose synthase candidate gene Glyma.19G140700 is collocated within the seed sucrose 1-8 QTL [20,39], less than <0.5 MB away from seed sucrose 2-11 and seed sucrose 2-10 [20,41], and 1.9 MB from seed oligosaccharide 2-7 [20,40].
The sucrose synthase candidate gene Glyma.02G240400 was located close (<1.5 MB) to two QTLs controlling seed sugar contents, the seed sucrose 2-2 and seed oligosaccharide 1-1 [20,41]. Moreover, the raffinose synthase candidate gene Glyma.05G003900 is located less than <4 MB away from the seed sucrose 1-1 [20,39]. The raffinose synthase candidate gene Glyma.19G004400 is located less than 9 MB away from four QTLs controlling the sugar contents, namely seed sucrose 2-3, seed oligosaccharide 1-2, seed sucrose 2-6, and seed oligosaccharide 1-5 [20,41] (Table 7). On chr. 8, the seed sucrose 1-3 and seed sucrose 1-13 are located close to the invertase candidate genes Glyma.08G043800, and Glyma.08G143500, as well as UDP-D-glucose-4-epimerase candidate genes Glyma.08G011800 and Glyma.08G023100 [20,39] (Table 7). The sucrose synthase candidate gene Glyma.09G073600 and the raffinose candidate gene Glyma.09G016600 are positioned less than <2 MB away from the seed sucrose 4-2 [20,44] (Table 7). Interestingly, the sucrose synthase candidate genes Glyma.15G182600 and Glyma.15G151000 are located less than <1.25 MB from the seed sucrose 3-3 and seed oligosaccharide 2-3 [20,40].
3.6. Organ-Specific Expression of the Identified Candidate Genes
The expression pattern of the identified candidate genes was investigated in Williams 82 cv. using the RNA-seq data available in SoyBase [20]. The dataset includes several plant tissues, including leaves, nodules, roots, pods, and seeds (Figure 3A,B and Figure S2). Four of the fifty-seven identified candidate genes have no available RNA-seq data, including the sucrose synthase candidate genes Glyma.03G216300, Glyma.17G045800, and Glyma.19G212800, as well as the UDP-D-glucose-4-epimerase candidate gene Glyma.18G211700 (Figure S2). The raffinose synthase candidate gene Glyma.04G145800 was not expressed in any of the analyzed tissues, whilst the rest of the identified genes showed different expression patterns.
The sucrose synthase candidate genes Glyma.09G073600 and Glyma.13G114000 presented a high expression profile in all the analyzed tissues except for the young leaves, while the raffinose synthase candidate gene Glyma.17G111400 was abundantly expressed in all the analyzed tissues except for the seeds and nodules. Interestingly, the sucrose synthase candidate gene Glyma.15G182600 was highly expressed in all the tissues excluding the young leaves and the nodules. The raffinose synthase candidate gene Glyma.03G137900 was abundantly expressed in flowers, nodules, and roots. The raffinose synthase candidate gene Glyma.14G010500 and the invertase candidate gene Glyma.05G236600 were highly expressed in the flowers and pods. Also, the UDP-D-glucose-4-epimerase candidate gene Glyma.05G204700 was abundantly expressed in the flowers and seeds. While the invertase candidate gene Glyma.20G177200 was highly expressed in nodules and roots, the raffinose synthase candidate gene Glyma.06G179200 was found to be highly expressed in seeds (Figure 3A and Figure S2).
Seventeen of the identified candidate genes were situated less than 10 MB away from the identified QTL regions. Glyma.09G073600 was highly expressed in seeds in Williams 82 cv., followed by Glyma.17G111400, Glyma.17G035800, and Glyma.08G043800 with a moderated expression profile. The remaining genes had lower expression patterns, excluding the Glyma.02G016700, Glyma.06G175500, Glyma.09G016600, Glyma.10G017300, and Glyma.19G004400 genes, which were not expressed in seeds in Williams 82 cv.
4. Comparison of the Williams 82 and Forrest Sequences
The sequences of the candidate genes located less than 10 MB from the identified QTLs were compared. The results showed that six of them had SNPs and InDels between the Forrest and Williams 82 sequences: Glyma.09G073600, Glyma.08G143500, Glyma.05G003900, Glyma.17G035800, Glyma.17G111400, and Glyma.09G016600 (Table S4, Figure 4).
The sucrose synthase Glyma.09G073600 had in total 28 SNPs and 7 InDels; three of these SNPs were located upstream of the 5′UTR, two are downstream of the 3′UTR, and seven were located in the exons (Table S4, Figure 4). For the invertase candidate gene Glyma.08G143500, there were 20 SNPs and 5 InDels. One of these SNPs was located in exon 7, causing a missense mutation, and two SNPs were located upstream of the 5′UTR (Table S4, Figure 4). The raffinose synthase candidate gene Glyma.05G003900 had nine SNPs and one InDel; four of those SNPs were in the exons, from which two SNPs resulted in missense mutations (Table S4, Figure 4). Likewise, the raffinose synthase candidate gene Glyma.09G016600 possessed 12 SNPs and 2 InDels. Amongst these SNPs, there were two located in exons, which resulted in missense mutations, in addition to the two InDels located in the exons (Table S4, Figure 4). For the raffinose candidate gene Glyma.17G111400, eight SNPs were found, of which one was located upstream of the 5′ UTR, another one was downstream of the 3′UTR, and the last six were in exons causing silent mutations (Table S4, Figure 4). Finally, the UDP-D-Glucose-4-Epimerase candidate gene Glyma.17G035800 had two SNPs that were positioned in introns (Table S4).
5. Discussion
Soybean seed sugars play a major role in seed and fruit development. Recently, soy products became very popular as a result of a growing demand for vegan diets [45]. The quality and taste of these products are determined by the soybean seed sugar content [39]. These sugars include sucrose, raffinose, and stachyose which make up 5–7%, 1%, and 3–4% of total carbohydrates, respectively [5]. However, the raffinose and stachyose fermentation by human and monogastric animal intestine microbes leads to a reduced gastrointestinal performance, flatulence, and diarrhea. Thus, reducing raffinose and stachyose and increasing sucrose in soybean seed content are desirable [22,27].
Given the importance of the soybean seed sucrose content for the quality of soybean-based products for food and feed, breeding programs are focused on developing soybean seeds with a high sucrose content and low RFO content [43,46]. Thus, soybean varieties with a high sucrose content are valuable for soybean food and feed products [47].
The identification of QTLs associated with sugar components using different types of molecular markers is one of the breeding-process approaches that researchers use to breed for a high-sucrose soybean. In soybean and other crops, it is well established that seed sugar contents are complex polygenic traits, and many studies including this study have mapped QTLs for sugar contents using various mapping populations including biparental populations where parents may not necessarily have contrasting amounts of sugar contents, such as in the “MD96-5722” by “Spencer” RIL population [30].
In the current study, all seed sugar (sucrose, raffinose, and stachyose) phenotypic data, except one (sucrose, 2018), exhibited normal distributions in all environments studied (years and locations), showing that these traits are polygenic and complex, as shown previously [21,39,40,41,44,47,48,49,50,51,52,53].
The SNP-based genetic linkage map facilitated the identification of several QTLs including QTLs for seed isoflavone contents [28], seed tocopherol contents [29], and seed sugar (sucrose, stachyose, and raffinose) contents, as reported in the current study.
The heritability (H2) of sucrose, stachyose, and raffinose was estimated to be 37.5%, 73.9%, and 92%, respectively. There is no doubt that the environment and the interactions of genotype and environment play a major role in the heritability of traits [28,29,43,54,55]. A trait biosynthesis that involves several genes is expected to have a lower heritability than a trait biosynthesis that involves fewer genes. Figure 2 shows the number of potential genes that are involved in sucrose biosynthesis versus those involved in raffinose and stachyose; it seems like there is a correlation between the heritability values and the number of genes involved in the biosynthesis pathway.
Among the identified sugar QTLs, there are novel QTL regions (qSUC-4, qSUC-8, and qSUC-11). All the other QTLs have been located within or very close to the previously reported sugar QTLs [30,39,40,41,44], as summarized in [18]. Five other genomic regions on chrs. 2, 6, 12, 16, and 19 harboring sugar QTLs either from this study or from other studies are of particular interest. On chr. 2, qSUC-2-NC-2018 may correspond to suc 1-1 identified previously [39]. This QTL region contains the Glyma.02G016700 candidate gene that encodes for invertase.
Interestingly, several QTLs have been identified previously, including a QTL that controls seed raffinose content within the qSUC-1-NC-2018 region (chr. 1) [30], two QTLs (suc 2-2 and suc 3-2) that control seed sucrose content within the qSUC-2-NC-2018 region (chr. 2) [20,40,41], a QTL that controls seed sucrose content (suc-001) within the qSUC-3-NC-2018 region (chr. 3), [30], 2 QTLs that control seed sucrose (suc 1-1 and suc 4-1) content within the qSUC-5-NC-2018 region (chr. 5) [39,44], a QTL that controls seed raffinose content (raf003 and raf004) within the qSUC-6-NC-2018 and qSUC-7-NC-2018 regions (chrs. 6 and 9) [30], a QTL that controls seed sucrose (suc 1-5) content within the qSUC-9-NC-2018 region (chr. 13) [39], and a QTL that controls seed sucrose (suc 1-4) content within the qSUC-12-NC-2018 region (chr. 20) [39].
Likewise, several other QTLs have been identified previously: a QTL that controls seed sucrose (suc 2-2, 3-2) content within the qSUC-1-IL-2020 region (chr. 2) [40,41], a QTL that control seed sucrose (suc 1-1, 4-1) content within the qSUC-2-IL-2020 (chr. 5) [39,44] and qSUC-3-IL-2020 (chr. 8) regions, and a QTL that control seed sucrose (suc 1-2, 1-3, 1-13) content within the qSUC-3-IL-2020 region (chr. 8) [39]. Within the QTL regions that were found to control seed stachyose contents (qSTA-1-IL-2020, qSTA-2-IL-2020, and qSTA-4-IL-2020) reported in the current study on chrs. 13, 16, and 19, several QTLs that control seed sucrose (suc 1-4, 1-5, 3-5, 3-6) and seed raffinose (raff007) contents have been identified previously [39,40,41].
On chr. 6, qSUC-6-NC-2018 most likely corresponds to suc 2-2 [41] and raffinose (raf003) QTL regions identified previously [30,39]. The QTL region contains the Glyma.06G175500 candidate gene encoding for raffinose synthase. Interestingly, the genomic region on chr. 19 comprising a cluster of sucrose QTLs (suc 1-6 to 1-8, 2-3 to 2-11) [39,41] also contains two stachyose QTLs identified in this study (qSTA-3-NC-2018 and qSTA-4-NC-2018). The candidate gene Glyma.19G004400, which also encodes for raffinose synthase, was identified within this QTL region.
No candidate genes have been identified on chrs. 12 (qRAF-3-NC-2018), 16 (qSTA-2-NC-2018), or 20 (qSTA-4-NC-2018).
Remarkably, within the novel QTL regions reported here on chrs. 4, 10, and 18, seven candidate genes were identified, including the Glyma.18G145700 encoding for UDP-D-glucose-4-epimerase on chr. 18 (Table 5 and Table 6, and Figure 2).
Interestingly, five QTL regions were detected in both locations, IL and NC. The first QTL region contains qSUC-5-NC-2018 and qSUC-2-IL-2020, which were detected in the same location on chr. 5. Additionally, qSUC-9-NC-2018, qSTA-1-NC-2018, and qSTA-2-NC-2018 were located only 1 MB away from qSTA-1-IL-2020 on chr.13. Moreover, qSUC-12-NC-2018 was 1.3 MB away from qSTA-4-IL-2020 on chr. 20. Furthermore, qSUC-10-NC-2018 and qSTA-3-IL-2020 were positioned 3.1 MB away from each other on chr. 17. Additionally, qSUC-2-NC-2018 and qSUC-1-IL-2020 were located ~4 MB away on chr. 2. The QTL regions that were not detected in both locations may be affected by environmental conditions.
In a previous study [54], 31,245 SNPs and 323 soybean germplasm accessions grown in three different environments were used to identify 72 QTLs associated with individual sugars and 14 associated with total sugar [54]. In addition, ten candidate genes that are within the 100 Kb flanking regions of the lead SNPs in six chromosomes were significantly associated with sugar content in soybean, eight of which are involved in the sugar metabolism in soybean [54]. Amongst these candidate genes, the raffinose synthase gene Glyma.05G003900 was also reported in this study.
A recent study used an RIL population from a cross of ZD27 by HF25 to identify 16 QTLs controlling seed sucrose and soluble sugar contents in soybean [43]. Amongst these QTLs, qSU1701 [43] with an LOD = 7.61 and phenotypic variation explained (PVE) = 16.8% was identified on chr. 17 to be associated with the seed sucrose content. This QTL region is collocated with qSUC-10-NC-2018 identified in this study for the same trait with an LOD = 33.2 and an R2 = 20.5. On the same chr., qSS1701 [43] and qSS1702, identified to be associated with the seed soluble sugar content, are collocated with qSTA-3-IL-2020. These QTLs are positioned less than 8 MB away from a cluster of four genes involved in the sugars’ pathway, including Glyma.17G037400 encoding for invertase, Glyma.17G045800 encoding for sucrose synthase, Glyma.17G111400 encoding for raffinose synthase (showing 7 SNP variations in exons) (Figure 4), and Glyma.17G035800 encoding for UDP-D-glucose-4-epimerase. Our results confirm that this region on chr. 17 is a major QTL associated with seed sugar contents in soybean. In the same study [43], qSU2001 identified on chr. 20 with LOD = 3.38 and PVE = 5.6% was collocated with qSUC-12-NC-2018, and it was 0.3 MB away from qSTA-4-IL-2020. The invertase candidate gene Glyma.20G177200 is positioned within qSU2002 [43] identified on chr. 20 with LOD = 7.9 and PVE = 14.4%. These results confirm that this region on chr. 20 is involved in soybean seed sugar contents. On chr. 3, qSS0301 was previously identified [43] to be associated with soluble sugar contents in soybean with an LOD = 5.2 and PVE = 11.8. This QTL is located 1.4 MB away from qSUC-3-NC-2018.
The sucrose synthase gene Glyma.09G073600 was highly expressed in seeds, followed by Glyma.17G111400, Glyma.17G035800, and Glyma.08G043800 with moderated expression patterns in seeds. Glyma.09G073600 and Glyma.09G016600 are located close to qSUC-7-IL-2018, qRAF-1-IL-2018, and qRAF-2-IL-2018 on chr. 9. Glyma.08G143500 is located close to qSUC-3-NC-2020, and Glyma.05G003900 is positioned close to qSUC-5-IL-2018 and qSUC-2-NC-2020 on chr. 5. These genes could be useful in gene editing technology or breeding programs to develop soybean cultivars with reduced amounts of RFOs and high amounts of sucrose, which is beneficial for human consumption and animal feed.
Further studies are needed to characterize these genes, identify their enzymes and protein products, and understand their roles in the sugar biosynthetic pathway in soybean.
6. Conclusions
In summary, we have identified 26 QTLs associated with the seed sugar contents and 57 candidate genes involved in the sucrose, raffinose, and stachyose biosynthetic pathway. Amongst these candidate genes, 16 were located less than 10 MB away from the QTL regions identified in this study.
On chr. 17, a cluster of four genes controlling the sugar pathway is collocated within 6 MB of two QTLs (qSUC-10-NC-2018 and qSTA-3-IL-2020) that were identified in this study. Moreover, the raffinose synthase candidate gene Glyma.06G175500 is 9.7MB away from qSUC-6-NC-2018 QTL on chr. 6. The invertase candidate gene Glyma.02G016700 is located 3.6 and 0.2 MB away from qSUC-1-NC-2018 (R2 = 47.9) and qSUC-1-IL-2020 (R2 = 3.6), respectively, on chr. 2. Moreover, the sucrose synthase candidate gene Glyma.09G073600 and the raffinose synthase candidate gene Glyma.09G016600 were found close to qSUC-7-IL-2018, qRAF-1-IL-2018, qRAF-2-IL-2018, and qRAF-1-IL-2018 on chr. 9.
Five QTL regions were commonly identified in the two environments, NC and IL, on chrs. 2, 5, 13, 17 and 20 ((qSUC-5-NC-2018 and qSUC-2-IL-2020), (qSUC-9-NC-2018, qSTA-1-NC-2018, and qSTA-1-IL-2020), (qSUC-12-NC-2018 and qSTA-4-IL-2020), (qSUC-10-NC-2018 and qSTA-3-IL-2020), and (qSUC-2-NC-2018 and qSUC-1-IL-2020)).
Five genes (Glyma.09G073600, Glyma.08G143500, Glyma.17G111400, Glyma.05G003900, and Glyma.09G016600) have SNPs and InDels between the Forrest and Williams 82 sequences. These SNPs could potentially explain the difference in sugar content between Forrest and Williams 82 cultivars.
Further studies are required to functionally characterize these genes so we can understand and validate their roles in the sugar biosynthetic pathway in soybean before they are used in breeding programs to produce soybean lines with high beneficial sucrose and low RFOs.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants12193498/s1, Table S1: Quantitative trait loci (QTL) that control sugars (sucrose, stachyose, and raffinose) contents in F × W82 RIL population in Spring Lake, NC in 2018; Table S2: Quantitative trait loci (QTL) that control sugars (sucrose, stachyose, and raffinose) contents in F × W82 RIL population in Carbondale, IL in 2020; Table S3: Comparison of the Williams 82 and Forrest cv. Sequences of the Glyma.09G073600, Glyma.08G143500, Glyma.17G111400, Glyma.17G035800, Glyma.09G016600 and Glyma.05G003900 candidate genes; Figure S1: Positions of QTL that control seed sucrose (qSUC), stachyose (qSTA), and raffinose (qRAF) contents on Chrs; Figure S2: Expression profiles of the sugars (sucrose, raffinose, and stachyose) pathway candidate genes in soybean based on RNAseq data available from RNAsequencing data; Figure S3. Physical positions corresponding to the Glyma.17G037400 encoding for an invertase, Glyma.17G045800 encoding for sucrose synthase, Glyma.17G111400 encoding for raffinose synthase, and Glyma.17G035800 encoding for UDP-D-glucose-4-epimerase, and the identified seed sugars QTL identified in this study on chr. 17 are shown.
Author Contributions
Conceptualization, K.M. and M.A.K.; methodology, D.K., J.Y., T.V., N.L., A.M., E.A., N.B. and M.E.; validation, M.A.K., K.M. and H.T.N.; formal analysis, D.K., J.Y. and N.B.; investigation, K.M. and M.A.K.; resources and data curation, K.M., M.A.K. and H.T.N.; writing—original draft preparation, D.K., M.A.K. and K.M.; review and editing, D.K., J.Y., N.B., N.L., T.V., M.A.K., K.M. and H.T.N.; supervision, M.A.K. and K.M.; project administration, M.A.K., K.M., and H.T.N. All authors have read and agreed to the published version of the manuscript.
Funding
This research was partially funded by the U.S. Department of Agriculture, Agricultural Research Service Project 6066-21220-014-000D. This project was also partially funded by the United Soybean Board, project # 2220-152-0104, and Southern Illinois University at Carbondale.
Data Availability Statement
The data presented in this study are available upon request from the corresponding author.
Acknowledgments
Technical support provided by Sandra Mosley is appreciated. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the United States Department of Agriculture (USDA). The USDA is an equal opportunity provider and employer.
Conflicts of Interest
The authors declare no conflict of interest.
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Figure 1.
Frequency distribution of sugars (sucrose, raffinose, and stachyose) in the F × W82 RIL population grown in two environments over two years (Spring Lake, NC in 2018 and Carbondale, IL in 2020).
Figure 1.
Frequency distribution of sugars (sucrose, raffinose, and stachyose) in the F × W82 RIL population grown in two environments over two years (Spring Lake, NC in 2018 and Carbondale, IL in 2020).
Figure 2.
The sugar (sucrose, raffinose, and stachyose) biosynthetic pathway with the identified candidate genes in soybean. The genes are in Wm82.a2.v1 annotation.
Figure 2.
The sugar (sucrose, raffinose, and stachyose) biosynthetic pathway with the identified candidate genes in soybean. The genes are in Wm82.a2.v1 annotation.
Figure 3.
(A) Tissue-specific expression of the identified sugar candidate genes. (B) Expression HeatMap of the identified candidate genes located within 10 MB of the identified sugar QTL regions in Williams 82 (RPKM) were retrieved from publicly available RNA-seq data from the Soybase database [20]. RNA-seq data are not available in Soybase for the Glyma.17G045800 candidate gene.
Figure 3.
(A) Tissue-specific expression of the identified sugar candidate genes. (B) Expression HeatMap of the identified candidate genes located within 10 MB of the identified sugar QTL regions in Williams 82 (RPKM) were retrieved from publicly available RNA-seq data from the Soybase database [20]. RNA-seq data are not available in Soybase for the Glyma.17G045800 candidate gene.
Figure 4.
Positions of SNPs between Forrest and Williams 82 cultivars in Glyma.09G073600, Glyma.08G143500, Glyma.05G003900, Glyma.17G111400, and Glyma.09G016600 coding sequences. In the gene model diagram, the light blue/light green boxes represent exons, blue/green bars represent introns, and dark blue/dark green boxes represent 3′UTR or 5′UTR. SNPs were positioned relative to the genomic position in the genome version W82.a2.
Figure 4.
Positions of SNPs between Forrest and Williams 82 cultivars in Glyma.09G073600, Glyma.08G143500, Glyma.05G003900, Glyma.17G111400, and Glyma.09G016600 coding sequences. In the gene model diagram, the light blue/light green boxes represent exons, blue/green bars represent introns, and dark blue/dark green boxes represent 3′UTR or 5′UTR. SNPs were positioned relative to the genomic position in the genome version W82.a2.
Table 1.
Seed sugar contents’ means, ranges, CVs, skewness, and kurtosis in the F × W82 RIL population evaluated in Spring Lake, NC (2018) and Carbondale, IL (2020). Mean and range values are expressed in µg/g of seed weight. ** p < 0.01, *** p < 0.001.
Table 1.
Seed sugar contents’ means, ranges, CVs, skewness, and kurtosis in the F × W82 RIL population evaluated in Spring Lake, NC (2018) and Carbondale, IL (2020). Mean and range values are expressed in µg/g of seed weight. ** p < 0.01, *** p < 0.001.
| Year | Sugar | Mean | Range | CV (%) | SE | Skewness | Kurtosis | W Value (p < 0.05) |
|---|---|---|---|---|---|---|---|---|
| 2018 | Sucrose | 2.58 | 22.7 | 62.86 | 0.12 | 12.2 | 161.38 | 0.22 *** |
| Raffinose | 0.67 | 0.26 | 9.16 | 0.01 | 0.18 | 3.26 | 0.99 | |
| Stachyose | 2.23 | 2.55 | 21.74 | 0.03 | −0.07 | 2.85 | 0.99 | |
| 2020 | Sucrose | 4.92 | 4.98 | 17.2 | 0.05 | −0.13 | 3.15 | 0.99 |
| Raffinose | 0.83 | 0.41 | 7.28 | 0.01 | 0.65 | 4.83 | 0.97 *** | |
| Stachyose | 3.61 | 2.15 | 9.06 | 0.02 | −0.48 | 3.8 | 0.98 ** |
Table 2.
Two-way ANOVA of seed sugar (sucrose, stachyose, and raffinose) contents in the F × W82 RIL population evaluated in Spring Lake, NC (2018) and Carbondale, IL (2020).
Table 2.
Two-way ANOVA of seed sugar (sucrose, stachyose, and raffinose) contents in the F × W82 RIL population evaluated in Spring Lake, NC (2018) and Carbondale, IL (2020).
| Response: Sucrose | ||||
| Df | Sum Sq | Mean Seq | H2 | |
| Line | 369 | 1134.22 | 3.0738 | 0.378 |
| Year | 1 | 5.6 | 5.5975 | |
| Line × Year | 2 | 3.82 | 1.9108 | |
| Residuals | 0 | 0 | NA | |
| Response: Raffinose | ||||
| Df | Sum Sq | Mean Seq | H2 | |
| Line | 369 | 3.4552 | 0.0093891 | 0.739 |
| Year | 1 | 0.0253 | 0.0253139 | |
| Line × Year | 2 | 0.0048 | 0.0023972 | |
| Residuals | 0 | 0 | NA | |
| Response: Stachyose | ||||
| Df | Sum Sq | Mean Seq | H2 | |
| Line | 369 | 246.73 | 0.66865 | 0.92 |
| Year | 1 | 1.611 | 1.61115 | |
| Line × Year | 2 | 0.106 | 0.05307 | |
| Residuals | 0 | 0 | NA | |
Table 3.
Quantitative trait loci (QTLs) that control sugar (sucrose, stachyose, and raffinose) contents in F × W82 RIL population in Spring Lake, NC in 2018. These QTLs were identified via CIM method. * Indicates novel QTL.
Table 3.
Quantitative trait loci (QTLs) that control sugar (sucrose, stachyose, and raffinose) contents in F × W82 RIL population in Spring Lake, NC in 2018. These QTLs were identified via CIM method. * Indicates novel QTL.
| Sugar | QTL | Chr. | Marker/Interval | Position (cM) | LOD | R2 | Add. Eff. |
|---|---|---|---|---|---|---|---|
| Sucrose | qSUC-1 | 1 | Gm01_3504836-Gm01_3466825 | 0.01–12.1 | 39.19 | 20.46 | −3.05 |
| qSUC-2 | 2 | Gm02_5155733-Gm02_9925870 | 128.5–142.2 | 42.77 | 47.90 | 4.42 | |
| qSUC-3 | 3 | Gm03_4595422-Gm03_4113546 | 39.2–39.8 | 32.62 | 20.50 | 3.05 | |
| qSUC-4 * | 4 | Gm04_7672403 | 6.5–16.5 | 54.35 | 37.50 | 4.62 | |
| qSUC-5 | 5 | Gm05_3867435-Gm05_3273418 | 31.5–37.01 | 20.65 | 17.51 | 2.60 | |
| qSUC-6 | 6 | Gm06_1737718-Gm06_5014399 | 48.5–52.4 | 5.36 | 10.50 | −1.37 | |
| qSUC-7 | 9 | Gm09_1888876 | 173.9–178.1 | 32.62 | 20.50 | 3.05 | |
| qSUC-8 * | 10 | Gm10_621706 | 214.01–216.01 | 34.25 | 19.10 | −4.48 | |
| qSUC-9 | 13 | Gm13_3891723-Gm13_3524828 | 0.2–58.2 | 19.12 | 17.51 | 2.60 | |
| qSUC-10 | 17 | Gm17_4967175-Gm17_5294475 | 0.4–1.0 | 33.22 | 20.50 | 3.05 | |
| qSUC-11 * | 18 | Gm18_1620585-Gm18_2020823 | 94.7–96.5 | 20.10 | 17.51 | 2.60 | |
| qSUC-12 | 20 | Gm19_2552468 | 172.11 | 6.98 | 9.10 | 1.41 | |
| Stachyose | qSTA-1 | 13 | Gm13_3524828 | 96.2–98.2 | 2.52 | 14.8 | 0.19 |
| qSTA-2 | 13 | Gm13_3884070-Gm13_3803273 | 121.8–123.2 | 2.60 | 5.2 | 0.11 | |
| qSTA-3 | 19 | Gm19_3789399-Gm19_4362616 | 98.01–124.1 | 4.21 | 8.5 | −0.16 | |
| qSTA-4 | 19 | Gm19_4946208-Gm19_5032228 | 184.1–186.1 | 2.53 | 5.3 | 0.11 | |
| Raffinose | qRAF-1 | 9 | Gm09_4024436-Gm09_4082234 | 108.01–110.9 | 2.26 | 4.6 | −0.01 |
| qRAF-2 | 9 | Gm09_1888876 | 173.9–178.1 | 2.47 | 7.6 | 0.08 | |
| qRAF-3 | 12 | Gm12_6023395-Gm12_2379195 | 114.6–118.6 | 2.15 | 4.7 | −0.01 |
Table 4.
Quantitative trait loci (QTLs) that control sugar (sucrose, stachyose, and raffinose) contents in F × W82 RIL population in Carbondale, IL in 2020. These QTLs were identified via CIM method.
Table 4.
Quantitative trait loci (QTLs) that control sugar (sucrose, stachyose, and raffinose) contents in F × W82 RIL population in Carbondale, IL in 2020. These QTLs were identified via CIM method.
| Sugar | QTL | Chr. | Marker | Position (cM) | LOD | R2 | Add. Eff. |
|---|---|---|---|---|---|---|---|
| Sucrose | qSUC-1 | 2 | Gm02_1199805-Gm02_1373746 | 196.4–205.6 | 2.63 | 3.60 | −0.16 |
| qSUC-2 | 5 | Gm05_3803682-Gm05_3748078 | 18.01–22.1 | 2.10 | 0.03 | −0.14 | |
| qSUC-3 | 8 | Gm08_5960619-Gm08_8268861 | 47.1–55.9 | 2.37 | 0.04 | 0.16 | |
| Stachyose | qSTA-1 | 13 | Gm13_2748576 | 0.5–4.5 | 2.03 | 0.09 | 0.21 |
| qSTA-2 | 16 | Gm16_3183754-Gm16_3010888 | 81.6–94.7 | 2.85 | 3.92 | 0.10 | |
| qSTA-3 | 17 | Gm17_8449684-Gm17_8352493 | 136.5–136.7 | 2.37 | 3.00 | −0.08 | |
| qSTA-4 | 20 | Gm20_294157-Gm20_1133712 | 145.4–148.5 | 3.59 | 4.50 | −0.12 |
Table 5.
QTLs and candidate genes that control sugar (sucrose, stachyose, and raffinose) contents in F × W82 RIL population in Spring Lake, NC in 2018. These QTLs were identified via CIM method.
Table 5.
QTLs and candidate genes that control sugar (sucrose, stachyose, and raffinose) contents in F × W82 RIL population in Spring Lake, NC in 2018. These QTLs were identified via CIM method.
| Sugar | QTL | Marker/Interval | LOD | R2 | Wm82.a2.v1 | Start | End | Wm82.a1.v1.1 | Start | End | Dis. (MB) |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Sucrose | qSUC-1 | Gm01_3504836-Gm01_3466825 | 39.19 | 20.46 | . | . | . | . | . | . | . |
| qSUC-2 | Gm02_5155733-Gm02_9925870 | 42.77 | 47.9 | Glyma.02G016700 | 1490049 | 1491170 | Glyma02g02030 | 1475851 | 1476528 | 3.6 | |
| qSUC-3 | Gm03_4595422-Gm03_4113546 | 32.62 | 20.5 | . | . | . | . | . | . | . | |
| qSUC-4 | Gm04_7672403 | 54.35 | 37.5 | . | . | . | . | . | . | . | |
| qSUC-5 | Gm05_3867435-Gm05_3273418 | 20.65 | 17.51 | Glyma.05G040300 | 3593378 | 3598821 | Glyma05g02510 | 1870330 | 1875692 | 1.3 | |
| Glyma.05G003900 | 307460 | 312091 | Glyma05g08950 | 8806144 | 8810647 | 4.9 | |||||
| qSUC-6 | Gm06_1737718-Gm06_5014399 | 5.36 | 10.5 | Glyma.06G175500 | 14845358 | 14849994 | Glyma06g18480 | 14802178 | 14807061 | 9.7 | |
| Glyma.06G179200 | 15217419 | 15223877 | Glyma06g18890 | 15175181 | 15181763 | 10.16 | |||||
| qSUC-7 | Gm09_1888876 | 32.62 | 20.5 | Glyma.09G073600 | 7809852 | 7816248 | Glyma09g08550 | 7845409 | 7851685 | 5.9 | |
| Glyma.09G016600 | 1285132 | 1290884 | Glyma09g01940 | 1270010 | 1276140 | 0.6 | |||||
| qSUC-8 | Gm10_621706 | 34.25 | 19.1 | Glyma.10G017300 | 1523661 | 1524691 | Glyma10g02170 | 1519053 | 1519546 | 0.8 | |
| qSUC-9 | Gm13_3891723-Gm13_3524828 | 19.12 | 17.51 | . | . | . | . | . | . | . | |
| qSUC-10 | Gm17_4967175-Gm17_5294475 | 33.22 | 20.5 | Glyma.17G037400 | 2732048 | 2737399 | Glyma17g04160 | 2739794 | 2745132 | 2.2 | |
| Glyma.17G045800 | 3404918 | 3410491 | Glyma17g05067 | 3412682 | 3418160 | 1.5 | |||||
| Glyma.17G035800 | 2629011 | 2639005 | Glyma17g03990 | 2637080 | 2646732 | 2.3 | |||||
| Glyma.17G111400 | 8744555 | 8747526 | Glyma17g11970 | 9015075 | 9018145 | 3.7 | |||||
| qSUC-11 | Gm18_1620585-Gm18_2020823 | 20.1 | 17.51 | . | . | . | . | . | . | . | |
| qSUC-12 | Gm19_2552468 | 6.98 | 9.1 | Glyma.19G004400 | 359933 | 363588 | Glyma19g00441 | 238429 | 242106 | 2.3 | |
| Stachyose | qSTA-1 | Gm13_3524828 | 2.52 | 14.8 | . | . | . | . | . | . | . |
| qSTA-2 | Gm13_3884070-Gm13_3803273 | 2.6 | 5.2 | . | . | . | . | . | . | . | |
| qSTA-3 | Gm19_3789399-Gm19_4362616 | 4.21 | 8.5 | Glyma.19G004400 | 359933 | 363588 | Glyma19g00440 | 241366 | 241903 | 3.5 | |
| qSTA-4 | Gm19_4946208-Gm19_5032228 | 2.53 | 5.3 | Glyma.19G004400 | 359933 | 363588 | Glyma19g00440 | 241366 | 241903 | 4.7 | |
| Raffinose | qRAF-1 | Gm09_4024436-Gm09_4082234 | 2.26 | 4.6 | Glyma.09G073600 | 7809852 | 7816248 | Glyma09g08550 | 7845409 | 7851685 | 3.7 |
| Glyma.09G016600 | 1285132 | 1290884 | Glyma09g01940 | 1270010 | 1276140 | 2.7 | |||||
| Glyma.09G167000 | 39103764 | 39109664 | Glyma09g29710 | 36530532 | 36536435 | 2.5 | |||||
| qRAF-2 | Gm09_1888876 | 2.47 | 7.6 | Glyma.09G073600 | 7809852 | 7816248 | Glyma09g08550 | 7845409 | 7851685 | 5.9 | |
| Glyma.09G016600 | 1285132 | 1290884 | Glyma09g01940 | 1270010 | 1276140 | 0.6 | |||||
| qRAF-3 | Gm12_6023395-Gm12_2379195 | 2.15 | 4.7 | . | . | . | . | . | . | . |
Table 6.
QTLs and candidate genes that control sugar (sucrose, stachyose, and raffinose) contents in F × W82 RIL population in Carbondale, IL in 2020. These QTLs were identified via CIM method.
Table 6.
QTLs and candidate genes that control sugar (sucrose, stachyose, and raffinose) contents in F × W82 RIL population in Carbondale, IL in 2020. These QTLs were identified via CIM method.
| Sugar | QTL | Marker | LOD | R2 | Wm82.a2.v1 | Start | End | Wm82.a1.v1.1 | Start | End | Dis. (MB) |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Sucrose | qSUC-1 | Gm02_1199805-Gm02_1373746 | 2.63 | 3.6 | Glyma.02G016700 | 1490049 | 1491170 | Glyma02g02030 | 1475851 | 1476528 | 0.2 |
| qSUC-2 | Gm05_3803682-Gm05_3748078 | 2.1 | 0.03 | Glyma.05G040300 | 3593378 | 3598821 | Glyma05g02510 | 1870330 | 1875692 | 1.8 | |
| Glyma.05G003900 | 307460 | 312091 | Glyma05g08950 | 8806144 | 8810647 | 5.002 | |||||
| qSUC-3 | Gm08_5960619-Gm08_8268861 | 2.37 | 0.04 | Glyma.08G043800 | 3450235 | 3451725 | Glyma08g04860 | 3446035 | 3447462 | 2.5 | |
| Glyma.08G143500 | 10949673 | 10956219 | Glyma08g15220 | 11038816 | 11045375 | 2.7 | |||||
| Glyma.08G011800 | 942037 | 944988 | Glyma08g01480 | 939512 | 942346 | 5.01 | |||||
| Glyma.08G023100 | 1852651 | 1856671 | Glyma08g02690 | 1848105 | 1853380 | 4.1 | |||||
| Stachyose | qSTA-1 | Gm13_2748576 | 2.03 | 0.09 | . | . | . | . | . | . | . |
| qSTA-2 | Gm16_3183754-Gm16_3010888 | 2.85 | 3.92 | . | . | . | . | . | . | . | |
| qSTA-3 | Gm17_8449684-Gm17_8352493 | 2.37 | 3 | Glyma.17G037400 | 2732048 | 2737399 | Glyma17g04160 | 2739794 | 2745132 | 5.6 | |
| Glyma.17G045800 | 3404918 | 3410491 | Glyma17g05067 | 3412682 | 3418160 | 4.9 | |||||
| Glyma.17G035800 | 2629011 | 2639005 | Glyma17g03990 | 2637080 | 2646732 | 5.8 | |||||
| Glyma.17G111400 | 8744555 | 8747526 | Glyma17g11970 | 9015075 | 9018145 | 0.5 | |||||
| qSTA-4 | Gm20_294157-Gm20_1133712 | 3.59 | 4.5 | . | . | . | . | . | . |
Table 7.
Candidate genes controlling sugar (sucrose, stachyose, and raffinose) contents associated with previously reported QTLs.
Table 7.
Candidate genes controlling sugar (sucrose, stachyose, and raffinose) contents associated with previously reported QTLs.
| Gene ID | Start | End | QTL | QTL Start | QTL End | Reference |
|---|---|---|---|---|---|---|
| Glyma.02G240400 | 42892680 | 42898279 | Seed sucrose 2-2 | 39547350 | 41441274 | [41] |
| Seed oligosaccharide 1-1 | 39547350 | 41441274 | [41] | |||
| Glyma.05G236600 | 41293446 | 41294570 | Seed sucrose 1-1 | 3924139 | 4279362 | [39] |
| Glyma.08G043800 | 3450235 | 3451725 | Seed sucrose 1-3 | 7892162 | 8937354 | [39] |
| Glyma.08G143500 | 10949673 | 10956219 | Seed sucrose 1-2 | 10865328 | 13126779 | [39] |
| Glyma.09G073600 | 7809852 | 7816248 | Seed sucrose 4-2 | 2973041 | 5901485 | [44] |
| Glyma.13G114000 | 22767704 | 22773231 | Seed sucrose 1-5 | 26196486 | 28912864 | [39] |
| Glyma.14G209900 | 47515899 | 47521687 | Seed sucrose 3-1 | 38859467 | 40060720 | [40] |
| Seed oligosaccharide 2-1 | 38859467 | 40060720 | [40] | |||
| Glyma.15G151000 | 12497113 | 12508050 | Seed sucrose 3-3 | 13755345 | 17021739 | [40] |
| Seed oligosaccharide 2-3 | 13755345 | 17021739 | [40] | |||
| Glyma.19G140700 | 40199041 | 40201038 | Seed sucrose 1-8 | 40205349 | 40265091 | [39] |
| Seed oligosaccharide 2-7 | 42119600 | 43329204 | [40] | |||
| Glyma.19G212800 | 46633685 | 46639818 | Seed oligosaccharide 2-7 | 42119600 | 43329204 | [40] |
| qSU1901 | 45311975 | 45464136 | [43] | |||
| Glyma.19G217700 | 47033812 | 47037286 | Seed oligosaccharide 2-7 | 42119600 | 43329204 | [40] |
| qSU1901 | 45311975 | 45464136 | [43] | |||
| Glyma.20G095200 | 33827363 | 33831352 | Seed sucrose 1-4 | 2716974 | 25498552 | [39] |
| Glyma.08G011800 | 942037 | 944988 | Seed sucrose 1-3 | 7892162 | 8937354 | [39] |
| Seed sucrose 1-13 | 8283676 | 9192408 | [39] | |||
| Glyma.08G023100 | 1852651 | 1856671 | Seed sucrose 1-3 | 7892162 | 8937354 | [39] |
| Seed sucrose 1-13 | 8283676 | 9192408 | [39] | |||
| Glyma.19G219100 | 47148224 | 47150373 | Seed sucrose 1-8 | 40205349 | 40265091 | [39] |
| Seed sucrose 2-10 | 40637071 | 41616190 | [41] | |||
| Seed sucrose 2-11 | 40637071 | 41616190 | [41] | |||
| Seed oligosaccharide 2-7 | 42119600 | 43329204 | [40] | |||
| Glyma.19G227800 | 47911129 | 47914214 | Seed sucrose 1-8 | 40205349 | 40265091 | [39] |
| Seed sucrose 2-10 | 40637071 | 41616190 | [41] | |||
| Seed sucrose 2-11 | 40637071 | 41616190 | [41] | |||
| Seed oligosaccharide 2-7 | 42119600 | 43329204 | [40] | |||
| Glyma.20G094500 | 33759416 | 33761555 | Seed sucrose 1-4 | 2716974 | 25498552 | [39] |
| Glyma.20G177200 | 41446962 | 41451980 | qSU2002 | 40523599 | 41882459 | [43] |
| Glyma.15G182600 | 17910130 | 17916426 | Seed sucrose 3-3 | 13755345 | 17021739 | [40] |
| Seed oligosaccharide 2-3 | 13755345 | 17021739 | [40] | |||
| Glyma.05G003900 | 307460 | 312091 | Seed sucrose 1-1 | 3924139 | 4279362 | [39] |
| Glyma.09G016600 | 1285132 | 1290884 | Seed sucrose 4-2 | 2973041 | 5901485 | [44] |
| Glyma.17G111400 | 8744555 | 8747526 | qSS1701 | 7470395 | 10014816 | [43] |
| qSS1702 | 7969537 | 10599548 | [43] | |||
| Glyma.13G160100 | 27576191 | 27579282 | Seed sucrose 1-5 | 26196486 | 28912864 | [39] |
| Glyma.19G004400 | 359933 | 363588 | Seed sucrose 2-3 | 4244065 | 12744826 | [41] |
| Seed oligosaccharide 1-2 | 4244065 | 12744826 | [41] | |||
| Seed sucrose 2-6 | 9284015 | 34059981 | [41] | |||
| Seed oligosaccharide 1-5 | 9284015 | 34059981 | [41] |
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Knizia, D.; Bellaloui, N.; Yuan, J.; Lakhssasi, N.; Anil, E.; Vuong, T.; Embaby, M.; Nguyen, H.T.; Mengistu, A.; Meksem, K.; et al. Quantitative Trait Loci and Candidate Genes That Control Seed Sugars Contents in the Soybean ‘Forrest’ by ‘Williams 82’ Recombinant Inbred Line Population. Plants 2023, 12, 3498. https://doi.org/10.3390/plants12193498
AMA Style
Knizia D, Bellaloui N, Yuan J, Lakhssasi N, Anil E, Vuong T, Embaby M, Nguyen HT, Mengistu A, Meksem K, et al. Quantitative Trait Loci and Candidate Genes That Control Seed Sugars Contents in the Soybean ‘Forrest’ by ‘Williams 82’ Recombinant Inbred Line Population. Plants. 2023; 12(19):3498. https://doi.org/10.3390/plants12193498
Chicago/Turabian StyleKnizia, Dounya, Nacer Bellaloui, Jiazheng Yuan, Naoufal Lakhssasi, Erdem Anil, Tri Vuong, Mohamed Embaby, Henry T. Nguyen, Alemu Mengistu, Khalid Meksem, and et al. 2023. "Quantitative Trait Loci and Candidate Genes That Control Seed Sugars Contents in the Soybean ‘Forrest’ by ‘Williams 82’ Recombinant Inbred Line Population" Plants 12, no. 19: 3498. https://doi.org/10.3390/plants12193498
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