Quantitative trait loci analysis of soluble sugar contents in soybean

The soluble sugar content in soybean seeds, mainly sucrose, stachyose, raffinose and trace amounts of glucose and fructose, is important for the increasing global market demand for various soyfoods including tofu, soymilk, natto, bean sprouts and edamame due to their nutritional value and health benefits. The objective of this study was to conduct quantitative trait loci (QTL) analysis and identify molecular markers for soluble sugar content in soybean seeds for marker‐assisted selection (MAS) in soybean breeding. The content of the five previously mentioned sugars were measured and associated QTLs were mapped based on a F₂ population that was derived from a cross between V97‐3000 and V99‐5089. Eleven QTLs were detected for the five sugar contents: one for glucose, three each for fructose and sucrose, and two each for raffinose and stachyose. However, only one QTL for sucrose, one QTL for raffinose, and two QTLs for stachyose were identified with LOD > 3.0 and R² > 10% from this research. The QTL on chromosome 11 [linkage group (LG) B1] was identified as associated with sucrose, raffinose and stachyose in the same region as previously reported for sucrose and stachyose. The SSR marker, Satt359, on the QTL B1 region had an significant association with sucrose (LOD = 5.192; R² = 0.134), raffinose (LOD = 3.95; R² = 0.104), and stachyose (LOD = 13.572; R² = 0.314); therefore it can be used to assist breeding selection for sucrose, raffinose and stachyose contents simultaneously.     

Identification and confirmation of quantitative trait loci for stachyose content in soybean seed

Stachyose is an unfavorable sugar in soybean meal that causes flatulence for non‐ruminant animals. Understanding the genetic control of stachyose in soybean will facilitate the modification of stachyose content at the molecular level. The objective of this study was to identify quantitative trait loci (QTL) associated with seed stachyose content using simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers. A normal stachyose cultivar, ‘Osage’, was crossed with a low stachyose line, V99‐5089, to develop a QTL mapping population. Two parents were screened with 33 SSR and 37 SNP markers randomly distributed on chromosome 10, and 20 SSR and 19 SNP markers surrounding a previously reported stachyose QTL region on chromosome 11. Of these, 5 SSR and 16 SNP markers were used to screen the F_3:4 lines derived from ‘Osage’ x V99‐5089. Seed samples from F_3:5 and F_3:6 lines were analyzed for stachyose content using high‐performance liquid chromatography (HPLC). Composite interval mapping analysis indicated that two stachyose QTL were mapped to chromosome 10 and 11, explaining 11% and 79% of phenotypic variation for stachyose content, respectively. The SSR/SNP markers linked to stachyose QTL could be used in breeding soybean lines with desired stachyose contents. Chi‐square tests further indicated that these two QTL probably represent two independent genes for stachyose content. Therefore, a major QTL was confirmed on chromosome 11 and a novel QTL was found on chromosome 10 for stachyose content.     

Identification of quantitative trait loci controlling soybean seed weight in recombinant inbred lines derived from PI 483463 (Glycine soja) × ‘Hutcheson’ (G. max)

The objective of this study was to identify quantitative trait loci (QTLs) controlling 100‐seed weight in soybean using 188 recombinant inbred lines (RIL) derived from a cross of PI 483463 and ‘Hutcheson’. The parents and RILs were grown for 4 years (2010–2013), and mature, dry seeds were used for 100‐seed weight measurement. The variance components of genotype (a), environment (e) and a × e interactions for seed weight were highly significant. The QTL analysis identified 14 QTLs explaining 3.83–12.23% of the total phenotypic variation. One of the QTLs, qSW17‐2, was found to be the stable QTL, being identified in all the environments with high phenotypic variation as compared to the other QTLs. Of the 14 QTLs, 10 QTLs showed colocalization with the seed weight QTLs identified in earlier reports, and four QTLs, qSW5‐1, qSW14‐1, qSW15‐1 and qSW15‐2, found to be the novel QTLs. A two‐dimensional genome scan revealed 11 pairs of epistatic QTLs across 11 chromosomes. The QTLs identified in this study may be useful in genetic improvement of soybean seed weight.     

Identification of quantitative trait loci for seed storability in rice (Oryza sativa L.)

In the present study, quantitative trait loci (QTLs) controlling seed storability based on relative germination rate (%) were dissected using a saturated linkage map and a recombinant inbred lines (RILs) derived from a cross of japonica cultivar Asominori (Oryza sativa L.) and indica cultivar IR24 (Oryza sativa L.). A total of three QTLs (qRGR-1, qRGR-3 and qRGR-9) were detected on chromosomes 1, 3 and 9 with LOD score ranging from 3.45 to 6.95 and the phenotypic variance explained from 16.72% to 28.63%. The IR24 alleles were all associated with seed storability at all the three QTLs. The existence of these QTLs was confirmed using IR24 chromosome segment substitution lines (CSSLs) in Asominori genetic background (AIS). By QTL comparative analysis, the QTL, qRGR-9 on chromosomes 9 appeared to be consistent with another rice population, this region may provide an important region for isolating this responsible gene. These results also provide the possibilities of enhancing Seed storability in rice breeding program by marker-assisted selection (MAS) and pyramiding QTLs. Y. Xue and S. Q. Zhang—joint first authors.     

Genetic analysis and map-based delimitation of a major locus qSS3 for seed size in soybean

Seed size is a major determinant of grain yield in soybean, however their genetic basis remains largely unknown. In order to delimit map-based position of a major locus qSS3 , we evaluated three mapping populations, including RILs, NILs and a sub-F₂ in three environments for six seed size-related traits. For these traits, the kurtosis and skewness ranged between 0.0 and 1.16, while h²_b ranged from 0.75 to 0.96, indicating that this RIL population is suitable for QTL analysis. QTL analysis identified 12 loci which consist of 30 significant QTLs with PVE% and LOD values of 6.6%–26.2% and 2.50–5.61, respectively. Among them, qSS3 was a major and stable locus explaining 7.3%–26.2% of the variation in 5 of the 6 traits, with the respective LOD values falling in the range of 2.72–5.61. Additionally, qSS3 effects were confirmed in NILs and delimited to an interval of ~1,126 kb containing 123 annotated genes. Overall, this study may assist efforts aiming to improve soybean seed traits by identifying valuable genetic resources which can be used in future MAS breeding programmes.     

Mapping quantitative trait loci controlling soybean seed starch content in an interspecific cross of ‘Williams 82’ (Glycine max) and ‘PI 366121’ (Glycine soja)

Seed starch content (SSC) greatly affects the taste, flavour and processing properties of soy foods. The objective in this study was to identify quantitative trait loci (QTL) for SSC in soybean. A total in 169 recombinant inbred lines (RILs) derived from a cross in ‘Williams 82’ and ‘PI 366121’ were grown for three consecutive years. The SSC of the RILs displayed continuous variation with transgressive segregation and hence amenable for QTL mapping. Nine significant QTL exhibiting 5.6–11.3% of the total phenotypic variation (PVE) were identified. The QTL qSTR06_2 showed highest PVE (9.1–11.3%) at LOD values of 4.25–5.39. No stable QTL over 3 years were identified, indicating strong environmental influence on SSC. The QTL qSTR11_1 and qSTR20_1 were found to colocalize with some of the previously reported QTL for sucrose content in soybean, implying the interrelationship between starch and sucrose biosynthesis. As the carbohydrate components may affect key constituents such as oil and protein in soybean seed, findings of the study may be useful in breeding soybeans with improved seed composition.     

QTL mapping of a partial resistance to the corn delphacid‐transmitted viruses in Lepidopteran‐resistant maize line Mp705

A partial resistance to maize mosaic virus (MMV) and maize stripe virus (MStV) was mapped in a RILs population derived from a cross between lines MP705 (resistant) and B73 (susceptible). A genetic map constructed from 131 SSR markers spanned 1399 cM with an average distance of 9.6 cM. A total of 10 QTL were detected for resistance to MMV and MStV, using composite interval mapping. A major QTL explaining 34–41% of the phenotypic variance for early resistance to MMV was detected on chromosome 1. Another major QTL explaining up to 30% of the phenotypic variation for all traits of resistance to MStV was detected in the centromeric region of chromosome 3 (3.05 bin). After adding supplementary SSR markers, this region was found to correspond well to the one where a QTL of resistance to MStV already was located in a previous mapping study using an F₂ population derived from a cross between Rev81 and B73. These results suggested that these QTL of resistance to MStV detected on chromosome 3 could be allelic in maize genome.     

Quantitative trait loci associated with drought tolerance in the model legume Medicago truncatula

Water shortage and heterogeneity in precipitation constitute the essential limiting factors for agricultural production in the Mediterranean basin. To understand the complex inheritance of tolerance to drought stress in Medicago truncatula, quantitative trait loci (QTLs) analysis was performed using a set of recombinant inbred lines (RILs) derived from a cross between the susceptible line Jemalong A17 and the tolerant line F83005.5. We conducted two experiments where the RILs and parental lines were grown in 0 mM and 75 mM of mannitol (D-) in tubes and in control and 33% of the field capacity (FC) in pots. In both experiments, line and line by water treatment interaction were significant. QTLs analysis showed that several putative genomic regions are involved in the variation of measured traits under the two water treatments in tubes and pots. A total of 21 QTLs on 8 linkage groups were detected for the measured traits in both experiments, 11 of them were in tubes conditions. Eight of these 11 QTLs were identified in control treatment and three in mannitol. While the number of QTLs identified in tubes under control conditions was more than under mannitol conditions, the highest number of QTLs was detected in water-stressed conditions in pots. The percentage of phenotypic variance explained by a single QTL (R ²) ranges from 11.7 to 26.3% in tubes and from 11.2 to 18.4% in pots depending on the trait, with 6 QTLs in each condition explaining <15% of the phenotypic variance. The number of common QTLs under two water treatments was one for length of stems (LS), number of internodes (NIN) and aerial dry weight (ADW) in tubes, and zero for NIN and one for LS and leaf area (LA) in pots. However, a few overlapping QTLs were found in tubes and pots on linkage groups 5 and 7 for LS and NIN.     

Identification and validation of a major QTL for salt tolerance in soybean

To identify quantitative trait loci (QTLs) conditioning salt tolerance in soybean (Glycine max (L.) Merr.), two recombinant inbred line (RIL) populations derived from crosses of FT-Abyara × C01 and Jin dou No. 6 × 0197 were used in this study. The FT-Abyara × C01 population consisted of 96 F₇ RILs, and the Jin dou No. 6 × 0197 population included 81 F₆ RILs. The salt tolerant parents FT-Abyara and Jin dou No. 6 were originally from Brazil and China, respectively. The QTL analysis identified a major salt-tolerant QTL in molecular linkage group N, which accounted for 44.0 and 47.1% of the total variation for salt tolerance, in the two populations. In the FT-Abyara × C01 population, three RILs were found to be heterozygous around the detected QTL region. By selfing the three residual heterozygous lines, three sets of near isogenic lines (NILs) for salt tolerance were developed. An evaluation of salt tolerance of the NILs revealed that all the lines with FT-Abyara chromosome segment at the QTL region showed significantly higher salt tolerance than the lines without the FT-Abyara chromosome segment. Results of the NILs validated the salt tolerance QTL detected in the RIL populations.     

Quantitative trait loci controlling rice seed germination under salt stress

Salt tolerance of rice (Oryza sativa L.) at the seed germination stage is one of the major determinants for the stable stand establishment in salinity soil. One population of recombinant inbred lines (RILs, F_2:9), derived from a cross between a japonica rice landrace tolerant to salt stress and a sensitive indica rice variety, was used to determine the germination traits including imbibition rate and germination percentage under control (water) and salt stress (100 mM NaCl) for 10 days at 30 °C. The multiple interval mapping (MIM) were applied to conduct QTL for the traits. The results showed that seed germination was a quantitative trait controlled by several genes, and strongly affected by salt stress. A total of 16 QTLs were detected in this study, and each QTL could explain 4.6–43.7% of the total phenotypic variance. The expression of these QTLs might be developmentally regulated and growth stage-specific. In addition, only one digenic interaction was detected under salt stress, showing small effect on germination percentage with R² 2.7%. Among sixteen QTLs detected in this study, four were major QTLs with R² > 30%, and some novel alleles of salt tolerance genes in rice. The results demonstrated that the japonica rice Jiucaiqing is a good source of gene(s) for salt tolerance and the major or minor QTLs identified could be used to improve the salt tolerance by marker-assisted selection (MAS) in rice.     

Localization of QTL for basal root thickness in <Emphasis Type="Italic">japonica</Emphasis> rice and effect of marker-assisted selection for a major QTL

Root traits are key components of plant adaptation to drought environment. By using a 120 recombined inbred lines (RILs) rice population derived from a cross between IRAT109, a japonica upland rice cultivar and Yuefu, a japonica lowland rice cultivar, a complete genetic linkage map with 201 molecular markers covering 1,833.8 cM was constructed and quantitative trait loci (QTLs) associated with basal root thickness (BRT) were identified. A major QTL, conferring thicker BRT, located on chromosome 4, designated brt4, explained phenotypic variance of 20.6%, was selected as target QTL to study the effects of marker-assisted selection (MAS) using two early segregating populations derived from crosses between IRAT109 and two lowland rice cultivars. The results showed that the flanking markers of brt4 were genetically stable in populations with different genetic backgrounds. In the two populations under upland conditions, the difference between the means of BRT of plants carrying positive and negative favorable alleles at brt4 flanking markers loci was significant. Phenotypic effects of BRT QTL brt4 were 5.05–8.16%. When selected plants for two generations were planted at Beijing and Hainan locations under upland conditions, MAS effects for BRT QTL brt4 were 4.56–18.56% and 15.46–26.52% respectively. The means of BRT for the homozygous plants were greater than that of heterozygous plants. This major QTL might be useful for rice drought tolerance breeding. L. Liu and P. Mu are contributed equally to this work.     

Identification of quantitative trait loci and candidate genes controlling the tocopherol synthesis pathway in soybean (Glycine max)

A recombinant inbred line (RIL) population was used to identify quantitative trait loci (QTLs) and their candidate genes controlling the tocopherol (Toc) synthesis pathway. The RIL population was cultivated in field conditions in 3 years. A genetic map constructed using 1624 DNA markers was used for QTL analysis. We identified 22 QTLs for seed tocopherol contents and their ratios, of which two QTL clusters on chromosomes (Chr) 9 and 14 exerted consistent large effects on tocopherol composition across the 3 years. The QTL cluster localized on Chr 9 might correspond to γ-TMT3, which controls the conversion of γ-Toc into α-Toc. The QTL cluster localized on Chr 14 was novel, which might regulate the conversion of MPBQ (a precursor of δ-Toc) into DMPBQ (the precursor of γ-Toc). The effect of the QTL cluster on Chr 14 was validated in a pair of near isogenic lines, and its candidate gene was mined. The identified QTLs and their candidate genes might be used in breeding programmes to improve α-Toc content in soybean seeds.     

QTL mapping of the domestication traits pre-harvest sprouting and dormancy in wheat (<Emphasis Type="BoldItalic">Triticum aestivum L.</Emphasis>)

A set of 75 recombinant inbred lines (RILs) of the ITMI mapping population was grown under field conditions in Gatersleben. The lines were evaluated for the domestication traits pre-harvest sprouting and dormancy (germinability). Main QTLs could be localized for pre-harvest sprouting on chromosome 4AL and dormancy on chromosome 3AL. In addition, 85 Triticum aestivum cv. “Chinese Spring”-Aegilops tauschii introgression lines grown under greenhouse conditions were researched. No QTL could be found for pre-harvest sprouting but a major QTL could be detected for dormancy on chromosome 6DL.     

Major QTLs associated with green stem disorder insensitivity of soybean (Glycine max (L.) Merr.)

Green stem disorder (GSD) is one of the most serious syndromes affecting soybean (Glycine max) cultivation in Japan. In GSD, stems remain green even when pods mature. When soybean plants develop GSD, seed surfaces are soiled by tissue fluid and seed quality is deteriorated during machine harvesting. We performed quantitative trait locus (QTL) analyses for GSD insensitivity using recombinant inbred lines (RILs; n = 154) derived from a cross between an insensitive line (‘Touhoku 129’) and a sensitive leading cultivar (‘Tachinagaha’) during a 6-year evaluation. Three effective QTLs were detected. The influences of these QTLs were in the following order: qGSD1 (LG_H) > qGSD2 (LG_F) > qGSD3 (LG_L). At these three QTLs, ‘Touhoku 129’ genotypes exhibited more GSD insensitivity than ‘Tachinagaha’ genotypes. The lower incidence of GSD for ‘Touhoku129’ was attributable primarily to these three QTLs because RILs harboring a ‘Touhoku 129’ genotype at the three QTLs exhibited a GSD incidence similar to that of ‘Touhoku 129.’ Although a limitation of this study is that only one mapping population was evaluated, this QTL information and the flanking markers of these QTLs would be effective tools for resolving GSD in soybean breeding programs.     

Genomewide association analysis of salt tolerance in soybean [Glycine max (L.) Merr.]

Salinity is a common abiotic stress causing soybean [Glycine max (L.) Merr.] yield loss worldwide. The use of tolerant cultivars is an effective and economic approach to coping with this stress. Towards this, research is needed to identify salt‐tolerant germplasm and better understand the genetic and molecular basis of salt tolerance in soybean. The objectives of this study were to identify salt‐tolerant genotypes, to search for single‐nucleotide polymorphisms (SNPs) and QTLs associated with salt tolerance. A total of 192 diverse soybean lines and cultivars were screened for salt tolerance in the glasshouse based on visual leaf scorch scores after 15–18 days of 120 mM NaCl stress. These genotypes were further genotyped using the SoySNP50K iSelect BeadChip. Genomewide association mapping showed that 62 SNP markers representing six genomic regions on chromosomes (Chr.) 2, 3, 5, 6, 8 and 18, respectively, were significantly associated with salt tolerance (p < 0.001). A total of 52 SNP markers on Chr. 3 are mapped at or near the major salt tolerance QTL previously identified in S‐100 (Lee et al., 2014). Three SNPs on Chr. 18 map near the salt tolerance QTL previously identified in Nannong1138‐2 (Chen, Cui, Fu, Gai, & Yu, 2008). The other significant SNPs represent four putative minor QTLs for salt tolerance, newly identified in this study. The results above lay the foundation for fine mapping, cloning and molecular breeding for soybean salt tolerance.     

利用重组自交群体检测水稻抗亚铁毒胁迫的QTLs

潜育性水稻田广泛分布于中国、斯里兰卡、印度、印度尼西亚、塞拉里昂、利比亚、尼日利亚、哥伦比亚和菲律宾等国，其中我国南方稻区就有670万公顷低产潜育性水稻田。该类水稻田还原性强，矿质营养失调，尤以Fe2+ 过量积累，对水稻生长发育产生不良的逆境胁迫作用。培育抗亚铁毒的水稻品种是简便、经济有效地提高稻谷产量的重     

Detection and validation of QTLs associated with seed longevity in rice (Oryza sativa L.)

Seed longevity in rice is a major determinant in seed production and germplasm preservation. In this paper, a recombinant inbred line (RIL) population consisting of 172 lines derived from the cross between Xiang743 and ‘Katy’ was used to map quantitative trait loci (QTLs) for seed longevity (SL) after seed storage for 18 and 30 months under ambient conditions. Two putative QTLs, qSL‐2 and qSL‐8, were detected and located on chromosomes 2 and 8, respectively. qSL‐2 is an allele from Xiang743 allele and increases seed longevity. qSL‐8 was a novel QTL from ‘Katy’ allele and increases seed longevity. qSL‐8 explained 15.29% and 17.35% of the phenotypic variance after seed storage for 18 and 30 months, respectively. Furthermore, qSL‐8 was validated in a secondary population developed by self‐pollination of a residual heterozygous line (RHL) selected from the RIL population, which explained 25.93% of the phenotypic contribution. These results provide an opportunity for map‐based cloning of qSL‐8. Furthermore, qSL‐8 may be a target for improving seed longevity by marker‐assisted selection (MAS) in rice.     

Genetic analysis of genotype × iron nutrition interaction on coleoptile elongation rate in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

High iron levels in rice soils represent a major problem for seedling establishment and crop growth, and rapid coleoptile elongation is the mechanism for the rice to cope with the induced stress. Quantitative trait loci (QTLs) analysis for coleoptile elongation rate (CER) in rice (Oryza sativa L.) was performed to study the inheritance of CER and its response to Fe nutrition. A recombinant inbred line (RIL) population of 244 lines derived from the cross zhenshan97B/miyang46 was germinated in 2004 under four Fe concentrations (0, 1.79, 7.16, and 14.32 mM). Seven QTLs with additive effects of stimulating CER were detected under the four Fe concentrations and they were localized on chromosome 1, 4, 5 and 7 with LOD ranging from 2.88 to 15.94 and their contribution to total phenotypic variance ranging from 4.17% to 15.87%, respectively. In addition, 21 QTLs with additive × additive epistasis were detected on all chromosomes but 4 and 9. The detected QTLs with additive effect mainly came from the male parent ZS97B. The detected number of QTLs with additive and epistatic effects for CER varied with Fe concentration. An additive QTL with G × Fe effect was detected between RZ460 and RZ730 markers of chromosome 1 using multi-environmental model of QTL Mapper 1.6 and considering Fe concentration as an environmental factor. The pattern of CER in the different Fe concentrations was well characterized by the genetic model of quantitative traits. It was found that some RILs had higher CER than both parents in each Fe concentration.     

不同生长环境下水稻结实率数量性状位点的检测

以籼稻密阳23与粳稻吉冷1号配制所获得的F_2:3群体200个家系作为作图群体，在北京、昆明、三亚、公主岭和韩国春川等5个点进行水稻结实率的鉴定，并利用SSR标记对水稻结实率数量性状位点进行检测。结果表明，水稻结实率表型值及其在F₃家系群中的分布以及所检测到的QTL数目因生长环境不同而有较大差异，说明QTL与环境有明显的互作效应。水稻结实率在F₃家系群中呈接近正态或偏态的连续分布，是多个基因所控制的数量性状。共检测到与水稻结实率相关的QTL 14个，分布于第1、2、3、4、6、7、8、10和12染色体上，对表型变异的贡献率为4.9%～15.3%。分别位于第1、2、6和12染色体RM1~RM259、RM263~RM6、RM340~RM30、RM270~RM17区间的qSSR1、qSSR2、qSSR6和qSSR12至少在2种生长环境下均检测到，对表型变异的贡献率分别为4.9%～8.4%、4.8%～7.2%、7.6%～10.7%和7.4%～10.4%。以上多数QTL增效等位基因均来自吉冷1号，基因作用方式主要为部分显性或显性或超显性。     

杂草稻种子休眠数量性状位点的定位

利用杂草稻与粳稻品种衍生的分离群体对控制种子休眠性的遗传基础进行了研究。检测到4个控制种子休眠性的QTL, 分别位于第1、第2和第6(2个)染色体上, 贡献率分别为7.8%、7.1%、5.5%和4.5%, 其中第2染色体上的QTL可能是一个新的控制种子休眠性的位点, 多项方差分析表明这4个位点的作用具有累加效应。种子发芽率与开花时间存在显著的负相关关系, 检测到的唯一一个控制抽穗期的QTL与位于第6染色体上的一个控制种子休眠性的QTL连锁或具有多效性, 这可能是造成其显著相关的主要原因。