Identification of quantitative trait loci controlling sucrose content in soybean (Glycine max)

Sucrose is a primary constituent of soybean (Glycine max) seed; however, little information concerning the inheritance of seed sucrose in soybean is available. The objective of this research was to use molecular markers to identify genomic regions significantly associated with quantitative trait loci (QTL) controlling sucrose content in a segregating F₂ population. DNA samples from 149 F₂ individuals were analyzed with 178 polymorphic genetic markers, including RFLPs, SSRs, and RAPDs. Sucrose content was measured on seed harvested from each of 149 F_2:3 lines from replicated field experiments in 1993 and 1995. Seventeen marker loci, mapping to seven different genomic regions, were significantly associated with sucrose variation at P<0.01. Individually, these markers explained from 6.1% to 12.4% of the total phenotypic variation for sucrose content in this population. In a combined analysis these genomic regions; explained 53% of total variation for sucrose content. No significant evidence of epistasis among QTLs was observed. Comparison of our QTL mapping results for sucrose content and those previously reported for protein and oil content (the other major seed constituents in soybean), suggests that seed quality traits are inherited as clusters of linked loci or that `major' QTLs with pleiotropic effects may control all three traits. Of the seven genomic regions having significant effects on sucrose content, three were associated with significant variation for protein content and three were significantly associated with oil content.     

Novel major quantitative trait loci regulating the content of isoflavone in soybean seeds

Despite their medicinal, pharmaceutical, and nutritional importance of isoflavones, the genetic basis controlling the amounts of isoflavones in soybean seeds is still not well understood. The main obstacle is the great variability in the content of isoflavone in seeds harvested from different environments. In this study, quantitative trait loci (QTL) for the content of different isoflavones including daidzein, genistein, and glycitein were investigated in a population of recombinant inbred lines derived from the cross of “Hwangkeum” (Glycine max) by “IT182932” (Glycine soja). Seeds analyzed were harvested in three different experimental environments. QTL analyses for isoflavone content were conducted by composite interval mapping across a genomewide genetic map. Two major QTL were mapped to soybean chromosomes 5 and 8, which were designated QDZGT1 and QDZGT2, respectively. Both loci have not been previously reported in other isoflavone sources. The results from this study will be useful in cloning genes that can control the contents of isoflavones in soybean and for the development of soybean lines containing a high or low isoflavone content.     

Putative quantitative trait loci associated with calcium content in soybean seed

Seed calcium content is an important quality attribute of specialty soybean [Glycine max (L.) Merr.] for soyfoods. However, analyzing seed for calcium content is time consuming and labor intensive. Knowing quantitative trait loci (QTL) for seed calcium will facilitate the development of elite cultivars with proper calcium content through marker-assisted selection (MAS). The objective of this study was to identify major QTL associated with calcium content in soybean seed. Calcium content was tested in 178 F(2:3) and 157 F(2:4) lines derived from the cross of SS-516 (low calcium) x Camp (high calcium). The F(2:3) lines were genotyped with 148 simple sequence repeat markers in a previous study on seed hardness, and the genotypic data were used in the QTL analysis of the current study. Four QTL designated as Ca1, Ca2, Ca3, and Ca4 on linkage groups (LGs) A2, I, and M were identified by both single-marker analysis and composite-interval mapping, and the QTL accounted for 10.7%, 16.3%, 14.9%, and 9.7% of calcium content variation, respectively. In addition, multiple-interval mapping analysis revealed a significant dominant-by-dominant interaction effect between Ca1 and Ca3, which accounted for 4.3% calcium content variation. These QTL will facilitate the implementation of MAS for calcium content in soybean-breeding programs.     

QTL analysis of soybean seed weight across multi-genetic backgrounds and environments

Seed weight, measured as mass per seed, is an important yield component of soybean and is generally positively correlated with seed yield (Burton et al, Crop Sci 27:1093, 1987). In previous reports, quantitative trait loci (QTL) associated with seed weight, were identified in single genetic background. The objective of the present study was to identify QTL and epistatic QTL underlying soybean seed weight in three RIL populations (with one common male parent 'Hefeng25') and across three different environments. Overall, 18, 11, and 17 seed weight QTL were identified in HC ('Hefeng25' × 'Conrad'), HM ('Hefeng25' × 'Maple Arrow'), and HB ('Hefeng25' × 'Bayfield') populations, respectively. The amount of phenotypic variation explained by a single QTL underlying seed weight was usually less than 10 %. The environment and background-independent QTL often had higher additive (a) effects. In contrast, the environment or background-dependent QTL were probably due to weak expression of QTL. QTL by environment interaction effects were in the opposite direction of a effects and/or epistasis effects. Four QTL and one QTL could be identified (2.0 < LOD < 9.06) in the HC and HB populations, respectively, across three environments (swHCA2-1, swHCC2-1, swHCD1b-1, swHCA2-2 (linked to Satt233, Satt424, Satt460, Satt428, respectively) and swHBA1-1(Satt449). Seven QTL could be identified in all three RIL populations in at least one location. Two QTL could be identified in the three RIL populations across three environments. These two QTL may have greater potential for use in marker-assisted selection of seed weight in soybean.     

A major and stable QTL associated with seed weight in soybean across multiple environments and genetic backgrounds

Key message

We detected a QTL for single seed weight in soybean that was stable across multiple environments and genetic backgrounds with the use of two recombinant inbred line populations.

Abstract

Single seed weight (SSW) in soybean is a key determinant of both seed yield and the quality of soy food products, and it exhibits wide variation. SSW is under genetic control, but the molecular mechanisms of such control remain unclear. We have now investigated quantitative trait loci (QTLs) for SSW in soybean and have identified such a QTL that is stable across multiple environments and genetic backgrounds. Two populations of 225 and 250 recombinant inbred lines were developed from crosses between Japanese and US cultivars of soybean that differ in SSW by a factor of ~2, and these populations were grown in at least three different environments. A whole-genome panel comprising 304 simple sequence repeat (SSR) loci was applied to mapping in each population. We identified 15 significant QTLs for SSW dispersed among 11 chromosomes in the two populations. One QTL located between Sat_284 and Sat_292 on chromosome 17 was detected (3.6 < LOD < 14.1) in both populations grown in all environments. This QTL, tentatively designated qSw17-1, accounted for 9.4–20.9 % of phenotypic variation in SSW, with a dominant allele being associated with increased SSW. Given its substantial effect on SSW, qSw17-1 is an attractive target for positional cloning, and SSR markers closely associated with this locus may prove useful for marker-assisted selection for SSW control in soybean.     

Identification of quantitative trait loci controlling gene expression during the innate immunity response of soybean

Microbe-associated molecular pattern-triggered immunity (MTI) is an important component of the plant innate immunity response to invading pathogens. However, most of our knowledge of MTI comes from studies of model systems with relatively little work done with crop plants. In this work, we report on variation in both the microbe-associated molecular pattern-triggered oxidative burst and gene expression across four soybean (Glycine max) genotypes. Variation in MTI correlated with the level of pathogen resistance for each genotype. A quantitative trait locus analysis on these traits identified four loci that appeared to regulate gene expression during MTI in soybean. Likewise, we observed that both MTI variation and pathogen resistance were quantitatively inherited. The approach utilized in this study may have utility for identifying key resistance loci useful for developing improved soybean cultivars.     

Identification for quantitative trait loci controlling grain shattering in rice

Seed shattering is an important factor causing loss of grain yield before and during rice harvest. In the present study, the quantitative trait loci regarding shattering scale, breaking tensile strength (BTS) and abscission layer (AL), the parameters evaluating seed shattering habit by hand gripping, a digital force gauge and observation on AL, respectively, were identified by using an doubled haploid line (DHL) population from a cross between a loose-shattering type Tongil variety, ‘Samgang’, and a moderately difficult shattering japonica variety, ‘Nagdong’. Eight QTLs consisted in four QTLs for shattering scale, two QTLs for AL, each one QTL for pulling and bending strength were detected on six chromosomes, respectively. Among them, Qss1 with flanking markers RM6696 and RM476 explained 31% of phenotype variation in shattering scale. Furthermore, two new QTLs controlling shattering habit, Qss5-2 and Qal5-1, were located on chromosome 5 at the interval 5028–5037 and 5021-RM289. They explained 10% and 12% of phenotype variations, respectively. A total of eleven digenic epistatic loci were identified for four parameters. The identification of QTLs affecting seed shattering habits is favorable to thoroughly dissect the genetic mechanism of the shattering habit and to apply for marker-assisted selection in rice breeding system of specific regions.     

Identification of quantitative trait loci controlling rice mature seed culturability using chromosomal segment substitution lines

The genetic transformation efficiency of a rice variety is largely determined by its tissue culturability. Establishment of a highly efficient tissue-culture system has greatly accelerated the wide spread application of transgenic japonica varieties. However, such process for indica rice was hampered because this type of variety is recalcitrant to in vitro culture. This study aimed to map the quantitative trait loci (QTLs) for mature seed culturability using a chromosomal segment substitution lines (CSSL) population derived from a cross between an indica variety “Zhenshan 97B” and a japonica variety “Nipponbare”. The CSSLs consist of 139 lines each containing a single or a few introgression segments, and together covering the whole “Nipponbare” genome. Every CSSL was tested by culturing on the two medium systems developed for the respective indica and japonica parental varieties. The performance of culturability was evaluated by four indices: frequency of callus induction (CIF), callus subculture capability (CSC), frequency of plant regeneration (PRF) and the mean plantlet number per regenerated callus (MNR). All four traits displayed continuous variation among the CSSLs. With the culture system for japonica rice, three CIF QTLs, three CSC QTLs, three PRF QTLs and three MNR QTLs were detected. With the culture system for indica variety, six CIF QTLs, two CSC QTLs, three PRF QTLs and six MNR QTLs were identified, and these QTLs distributed on nine rice chromosomes. Two QTLs of CIF and two QTLs of MNR were detected in both the japonica and indica rice culture system. The correlation coefficients of all the four traits varied depending on the culture systems. These results provide the possibilities of enhancing the culturability of indica rice by marker-assisted breeding with those desirable alleles from the japonica. Lina Zhao and Hongju Zhou have contributed equally to this work.     

Identification and validation of quantitative trait loci for seed yield,oil and protein contents in two recombinant inbred line populations of soybean

Soybean seeds contain high levels of oil and protein, and are the important sources of vegetable oil and plant protein for human consumption and livestock feed. Increased seed yield, oil and protein contents are the main objectives of soybean breeding. The objectives of this study were to identify and validate quantitative trait loci (QTLs) associated with seed yield, oil and protein contents in two recombinant inbred line populations, and to evaluate the consistency of QTLs across different environments, studies and genetic backgrounds. Both the mapping population (SD02-4-59 × A02-381100) and validation population (SD02-911 × SD00-1501) were phenotyped for the three traits in multiple environments. Genetic analysis indicated that oil and protein contents showed high heritabilities while yield exhibited a lower heritability in both populations. Based on a linkage map constructed previously with the mapping population and using composite interval mapping and/or interval mapping analysis, 12 QTLs for seed yield, 16 QTLs for oil content and 11 QTLs for protein content were consistently detected in multiple environments and/or the average data over all environments. Of the QTLs detected in the mapping population, five QTLs for seed yield, eight QTLs for oil content and five QTLs for protein content were confirmed in the validation population by single marker analysis in at least one environment and the average data and by ANOVA over all environments. Eight of these validated QTLs were newly identified. Compared with the other studies, seven QTLs for seed yield, eight QTLs for oil content and nine QTLs for protein content further verified the previously reported QTLs. These QTLs will be useful for breeding higher yield and better quality cultivars, and help effectively and efficiently improve yield potential and nutritional quality in soybean.     

Identification of the quantitative trait loci (QTL) underlying water soluble protein content in soybean

Water soluble protein content (SPC) plays an important role in the functional efficacy of protein in food products. Therefore, for the identification of quantitative trait loci (QTL) associated with SPC, 212 F_2:9 lines of the recombinant inbred line (RIL) population derived from the cross of ZDD09454 × Yudou12 were grown along with the parents, in six different environments (location × year) to determine inheritance and map solubility-related genes. A linkage map comprising of 301 SSR markers covering 3,576.81 cM was constructed in the RIL population. Seed SPC was quantified with a macro-Kjeldahl procedure in samples collected over multiple years from three locations (Nantong in 2007 and 2008, Zhengzhou in 2007 and 2008, and Xinxiang in 2008 and 2009). SPC demonstrated transgressive segregation, indicating a complementary genetic structure between the parents. Eleven putative QTL were associated with SPC explaining 4.5–18.2 % of the observed phenotypic variation across the 6 year/location environments. Among these, two QTL (qsp8-4, qsp8-5) near GMENOD2B and Sat_215 showed an association with SPC in multiple environments, suggesting that they were key QTL related to protein solubility. The QTL × environment interaction demonstrated the complex genetic mechanism of SPC. These SPC-associated QTL and linked markers in soybean will provide important information that can be utilized by breeders to improve the functional quality of soybean varieties.     

Identification of QTL underlying isoflavone contents in soybean seeds among multiple environments

Soybean isoflavones are valued in certain medicines, cosmetics, foods and feeds. Selection for high-isoflavone content in seeds along with agronomic traits is a goal of many soybean breeders. The aim of the study was to identify the quantitative trait loci (QTL) underlying seed isoflavone content in soybean among seven environments in China. A cross was made between ‘Zhongdou 27’, a soybean cultivar with higher mean isoflavone content in the seven environments (daidzein, DZ, 1,865 μg g⁻¹; genistein, GT, 1,614 μg g⁻¹; glycitein, GC, 311 μg g⁻¹ and total isoflavone, TI, 3,791 μg g⁻¹) and ‘Jiunong 20’, a soybean cultivar with lower isoflavone content (DZ, 844 μg g⁻¹; GT, 1,046 μg g⁻¹; GC, 193 μg g⁻¹ and TI, 2,061 μg g⁻¹). Through single-seed-descent, 130 F₅-derived F₆ recombinant inbred lines were advanced. A total of 99 simple-sequence repeat markers were used to construct a genetic linkage map. Seed isoflavone contents were analyzed using high-performance liquid chromatography for multiple years and locations (Harbin in 2005, 2006 and 2007, Hulan in 2006 and 2007, and Suihua in 2006 and 2007). Three QTL were associated with DZ content, four with GT content, three with GC content, and five with TI content. For all QTL detected the beneficial allele was from Zhongdou 27. QTL were located on three (DZ), three (GC), four (GT) and five (TI) molecular linkage groups (LG). A novel QTL was detected with marker Satt144 on LG F that was associated with DZ (0.0014 > P > 0.0001, 5% < R ² < 11%; 254 < DZ < 552 μg g⁻¹), GT (0.0027 > P > 0.0001; 4% < R ² < 9%; 262 < GT < 391 μg g⁻¹), and TI (0.0011 > P > 0.0001; 4% < R ² < 15%; 195 < TI < 871 μg g⁻¹) across the various environments. A previously reported QTL on LG M detected by Satt540 was associated with TI across four environments and TI mean (0.0022 > P > 0.0001; 3% < R ² < 8%; 182 < TI < 334 μg g⁻¹) in China. Because both beneficial alleles were from Zhongdou 27, it was concluded that these two QTL would have the greatest potential value for marker-assisted selection for high-isoflavone content in soybean seed in China. G. Zeng, D. Li and Y. Han have equal contributions to the paper.     

RFLP mapping of quantitative trait loci controlling seed aliphatic-glucosinolate content in oilseed rape (Brassica napus L)

We report the RFLP mapping of quantitative trait loci (QTLs) which regulate the total seed aliphaticglucosinolate content in Brassica napus L. A population of 99 F₁-derived doubled-haploid (DH) recombinant lines from a cross between the cultivars Stellar (low-glucosinolate) and Major (high-glucosinolate) was used for singlemarker analysis and the interval mapping of QTLs associated with total seed glucosinolates. Two major loci, GSL-1 and GSL-2, with the largest influence on total seed aliphatic-glucosinolates, were mapped onto LG 20 and LG 1, respectively. Three loci with smaller effects, GSL-3, GSL-4 and GSL-5, were tentatively mapped to LG 18, LG 4 and LG 13, respectively. The QTLs acted in an additive manner and accounted for 71 % of the variation in total seed glucosinolates, with GSL-1 and GSL-2 accounting for 33% and 17%, respectively. The recombinant population had aliphatic-glucosinolate levels of between 6 and 160 moles per g^-1 dry wt of seed. Transgressive segregation for high seed glucosinolate content was apparent in 25 individuals. These phenotypes possessed Stellar alleles at GSL-3 and Major alleles at the four other GSL loci demonstrating that low-glucosinolate genotypes (i.e. Stellar) may possess alleles for high glucosinolates which are only expressed in particular genetic backgrounds. Gsl-elong and Gsl-alk, loci which regulate the ratio of individual aliphatic glucosinolates, were also mapped. Gsl-elong-1 and Gsl-elong-2, which control elongation of the -amino-acid precursors, mapped to LG 18 and LG 20 and were coincident with GSL loci which regulate total seed aliphatic glucosinolates. A third tentative QTL, which regulates side-chain elongation, was tentatively mapped to LG 12. Gsl-alk, which regulates H₃CS-removal and side-chain de-saturation, mapped to LG 20.     

Mapping of quantitative trait loci for kernel row number in maize across seven environments

Genetic factors controlling quantitative inheritance of grain yield and its components have been intensively investigated during recent decades using diverse populations in maize (Zea mays L.). Notwithstanding this, quantitative trait loci (QTL) for kernel row number (KRN) with large and consistent effect have not been identified. In this study, a linkage map of 150 simple sequence repeat (SSR) loci was constructed by using a population of 500 F2 individuals derived from a cross between elite inbreds Ye478 and Dan340. The linkage map spanned a total of 1478 cM with an average interval of 10.0 cM. A total of 397 F2:3 lines were evaluated across seven diverse environments for mapping QTL for KRN. Some QTL for grain yield and its components had previously been confirmed with this population across environments. A total of 13 QTL for KRN were identified, with each QTL explaining from 3.0 to 17.9% of phenotypic variance. The gene action for KRN was mainly additive to partial dominance. A large-effect QTL (qkrn7) with partial dominance effect accounting for 17.9% of the phenotypic variation for KRN was identified on chromosome 7 near marker umc1865 with consistent gene effect across seven diverse environments. This study has laid a foundation for map-based cloning of this major QTL and for developing molecular markers for marker-assisted selection of high KRN.     

Identification of quantitative trait loci controlling developmental characteristics of Brassica oleracea L

A segregating population of F₁-derived doubled haploid (DH) lines of Brassica oleracea was used to detect and locate QTLs controlling 27 morphological and developmental traits, including leaf, flowering, axillary bud and stem characters. The population resulted from a cross between two very different B. oleracea crop types, an annual cauliflower and a biennial Brussels sprout. A principal component analysis (PCA), based on line means, allowed all the traits to be grouped into distinct categories according to the first five Principal Components. These were: leaf traits (PC1), flowering traits (PC2), axillary bud traits (PC3 and 5) and stem traits (PC4). Between zero and four putative QTL were located per trait, which individually explained between 6% and 43% of the additive genetic variation, using the multiple-marker regression approach to QTL mapping. For lamina width, bare petiole length and stem length two QTL with opposite effects were detected on the same linkage groups. Intra- and inter-specific comparative mapping using RFLP markers identified a QTL on linkage group O8 accounting for variation in vernalisation, which is probably synonymous with a QTL detected on linkage group N19 of Brassica napus. In addition, a QTL for petiole length detected on O3 of this study appeared to be homologous to a QTL detected on another B. oleracea genetic map (Camargo et al. 1995). Received: 28 March 2001 / Accepted: 25 June 2001     

np2QTL: networking phenotypic plasticity quantitative trait loci across heterogeneous environments

Despite its critical importance to our understanding of plant growth and adaptation, the question of how environment‐induced plastic response is affected genetically remains elusive. Previous studies have shown that the reaction norm of an organism across environmental index obeys the allometrical scaling law of part‐whole relationships. The implementation of this phenomenon into functional mapping can characterize how quantitative trait loci (QTLs) modulate the phenotypic plasticity of complex traits to heterogeneous environments. Here, we assemble functional mapping and allometry theory through Lokta?Volterra ordinary differential equations (LVODE) into an R‐based computing platform, np²QTL, aimed to map and visualize phenotypic plasticity QTLs. Based on LVODE parameters, np²QTL constructs a bidirectional, signed and weighted network of QTL?QTL epistasis, whose emergent properties reflect the ecological mechanisms for genotype?environment interactions over any range of environmental change. The utility of np²QTL was validated by comprehending the genetic architecture of phenotypic plasticity via the reanalysis of published plant height data involving 3502 recombinant inbred lines of maize planted in multiple discrete environments. np²QTL also provides a tool for constructing a predictive model of phenotypic responses in extreme environments relative to the median environment.     

Identification of quantitative trait loci controlling resistance to maize chlorotic dwarf virus

Ineffective screening methods and low levels of disease resistance have hampered genetic analysis of maize (Zea mays L.) resistance to disease caused by maize chlorotic dwarf virus (MCDV). Progeny from a cross between the highly resistant maize inbred line Oh1VI and the susceptible inbred line Va35 were evaluated for MCDV symptoms after multiple virus inoculations, using the viral vector Graminella nigrifrons. Symptom severity scores from three rating dates were used to calculate area under the disease progress curve (AUDPC) scores for vein banding, leaf twist and tear, and whorl chlorosis. AUDPC scores for the F₂ population indicated that MCDV resistance was quantitatively inherited. Genotypic and phenotypic analyses of 314 F₂ individuals were compared using composite interval mapping (CIM) and analysis of variance. CIM identified two major quantitative trait loci (QTL) on chromosomes 3 and 10 and two minor QTL on chromosomes 4 and 6. Resistance was additive, with alleles from Oh1VI at the loci on chromosomes 3 and 10 contributing equally to resistance.     

Mapping quantitative trait loci controlling seed longevity in rice ( Oryza sativa L.)

Quantitative trait loci (QTLs) controlling seed longevity in rice were identified using 98 backcross inbred lines (BILs) derived from a cross between a japonica variety Nipponbare and an indica variety Kasalath. Seeds of each BIL were kept for 12 months at 30 degrees C in dry conditions to promote loss of viability. To measure seed longevity, we performed an additional aging-processing treatment for 2 months at 30 degrees C maintaining seeds at 15% moisture content. We measured the germination percent of these treated seeds at 25 degrees C for 7 days as the degree of seed longevity. The germination of BILs ranged from 0 to 100% with continuous variation. Three putative QTLs for seed longevity, qLG-2, qLG-4 and qLG-9, were detected on chromosome 2, 4 and 9, respectively. Kasalath alleles increased the seed longevity at these QTLs. The QTL with the largest effect, qLG-9, explained 59.5% of total phenotypic variation in BILs. The other two QTLs, qLG-2 and qLG-4, explained 13.4 and 11.6% of the total phenotypic variation, respectively. We also verified the effect of the Kasalath allele of qLG-9 using chromosome segment substitution lines. Furthermore, QTLs for seed dormancy were identified on chromosomes 1, 3, 5, 7 and 11. Based on the comparison of the chromosomal location of QTLs for seed longevity and seed dormancy, these traits seem to be controlled by different genetic factors.