Identification of QTL underlying the resistance of soybean to pod borer, <Emphasis Type="Italic">Leguminivora glycinivorella</Emphasis> (Mats.) obraztsov,and correlations with plant,pod and seed traits

Soybean (Glycine max L. Merr.) pod borer (Leguminivora glycinivorella (Mats.) Obraztsov) (SPB) results in severe loss in soybean yield and quality in certain regions of the world, especially in Northeastern China, Japan and Russia. The aim here was to evaluate the inheritance of pod borer resistance and to identify quantitative trait loci (QTL) underlying SPB resistance for the acceleration of the control of this pest. Used were the 129 recombinant inbred lines (RILs) of the F_5:6 derived population from ‘Dong Nong 1068’ × ‘Dong Nong 8004’ and 131 SSR markers. Correlations between the percentage of damaged seeds (PDS) by pod borer and plant, pod and seed traits that were potentially related to SPB resistance were analyzed. The results showed highly significant correlations between PDS by pod borer and plant height (PH), maturity date (MA), pod color (PC), pubescence density (PB), 100-seed weight (SW) and protein content existed. Soybeans with dwarf stem, light color of pod coat, small seeds, lower density of pubescence, early maturity and low content of protein seemed to have higher resistance to SPB. The correlated traits had potential to inhibit egg deposition and thereby to decrease the damage by SPB. Three QTL directly associated with the resistance to SPB judged by PDS at harvest were identified. qRspb-1 (Satt541–Satt253) and qRspb-2 (Satt253–Satt314) were both on linkage group (LG) H and qRspb-3 (Satt288–Satt199) on LG G. The three QTL explained 10.96, 9.73 and 11.59% of the phenotypic variation for PDS, respectively. In addition, 12 QTL that underlay 10 of 13 traits potentially related with SPB resistance were found. These QTL detected jointly provide potential for marker assisted selection to improve cultivar resistance to SPB. Guiyun Zhao, Jian Wang, and Yingpeng Han have equal contribution to the paper.     

Dynamic quantitative trait loci underlies isoflavone accumulation in soybean seed

Most of quantitative trait loci (QTL) underlying soybean seed isoflavone contents were derived from the harvest stage of plant development, which uncover the genetic effects that were expressed in earlier seed developmental stages. The aim of this study was to detect conditional QTL associated with isoflavone accumulation during the entire seed development. A total of 112 recombinant inbred lines developed from the cross between ‘Zhongdou 27’ (higher seed isoflavone content) and ‘Jiunong 20’ (lower seed isoflavone content) were used for the conditional QTL analysis of daidzein (DZ), genistein (GT), glycitein (GC) and total isoflavone (TI) accumulations through composite interval mapping with mixed genetic model. The results indicated that the number and type of QTL and their additive effects for individual and total isoflavone accumulations were different among R3 to R8 developmental stages. Three unconditional QTL and six conditional QTL for DZ, four unconditional QTL and five conditional QTL for GT, six unconditional QTL and five conditional QTL for GC, six unconditional QTL and seven conditional QTL for TI were identified at different developmental stages, respectively. Unconditional and conditional QTL that affect individual and total isoflavone accumulations exhibited multiple expression patterns, implying that some QTL are active for long period and others are transient. Two genomic regions, Satt144‐Satt569 in linkage group F (LG F; chromosome 13, chr 13) for DZ, GC, GT and TI accumulations and Satt540‐Sat_240 in LG M (chr 07) for TI and GC accumulations, were found to significantly affect individual and total isoflavone accumulations in multiple developmental stages, suggesting that the accumulation of soybean seed isoflavones is governed by time‐dependent gene expression.     

Dissection of genetic architecture for oil content in soybean seed using two backcross populations

Soybean seed oil was valued in foods, animal feed and some industrial applications. Molecular marker‐assisted selection (MAS) for high‐oil‐content cultivars was an important method for soybean breeders. The objective of this study was to identify quantitative trait loci (QTL) and epistatic QTL underlying the seed oil content of soybeans across two backcross (BC) populations (with one common male parent ‘Dongnong47’) and two different environments. Two molecular genetic maps were constructed. They encompassed 1046.8 cM [with an average distance of 6.75 cM in the ‘Dongnong47’  ×  ‘Jiyu89’ (DJ) population] and 846.10 cM [with an average distance of 5.76 cM in the ‘Dongnong47’  ×  ‘Zaoshu18’ (DZ) population]. Nine and seven QTL were identified to be associated with oil content in the DJ and DZ populations, respectively. The phenotypic variation explained by most of the QTL was usually less than 10%. Among the identified QTL, those stable ones across multiple environments and populations often had stronger additive effects. In addition, three stable QTL in the DZ populations were identified in the similar genomic region of the three QTL in the DJ population [qDJE and qDZE‐1 were located near Satt151 of Chromosome 15 (Chr15), qDJA1 and qDZA1 were located near Satt200 of Chr15 (LG A1), and qDJD2‐1 and qDZD2‐1 were located near Sat365 of Chr17]. In conclusion, MAS will be able more effectively to combine beneficial alleles of the different donors to design new genotypes with higher soybean seed oil content using the BC populations.     

A SNP genetic linkage map based on the ‘Hamilton’ by ‘Spencer’ recombinant inbred line population identified QTL for seed isoflavone contents in soybean

Soybean is one of the most important crops worldwide for its protein and oil as well as the health beneficial phytoestrogens or isoflavone. This study reports a relatively dense single nucleotide polymorphism (SNP)‐based genetic map based on ‘Hamilton’ by ‘Spencer’ recombinant inbred line population and quantitative trait loci (QTL) for seed isoflavone contents. The genetic map is composed of 1502 SNP markers and covers about 1423.72 cM of the soybean genome. Two QTL for seed isoflavone contents have been identified in this population. One major QTL that controlled both daidzein (qDZ1) and total isoflavone contents (qTI1) was found on LG C2 (Chr 6). And a second QTL for glycitein content (qGT1) was identified on the LG G (Chr 18). These two QTL in addition to others identified in soybean could be used in soybean breeding to optimize isoflavone content. This newly assembled soybean linkage map is a useful tool to identify and map QTL for important agronomic traits and enhance the identification of the genes involved in these traits.     

Identification and validation of an over‐dominant QTL controlling soybean seed weight using populations derived from Glycine max × Glycine soja

Heterosis, or hybrid vigour, has been used to improve seed yield in several important crops for decades and it has potential applications in soybean. The discovery of over‐dominant quantitative trait loci (QTL) underlying yield‐related traits, such as seed weight, will facilitate hybrid soybean breeding via marker‐assisted selection. In this study, F₂ and F_2 : 3 populations derived from the crosses of ‘Jidou 12’ (Glycine max) × ‘ZYD2738’ (Glycine soja) and ‘Jidou 9’ (G. max) × ‘ZYD2738’ were used to identify over‐dominant QTL associated with seed weight. A total of seven QTL were identified. Among them, qSWT_13_1, mapped on chromosome 13 and linked with Satt114, showed an over‐dominant effect in two populations for two successive generations. This over‐dominant effect was further examined by six subpopulations derived from ‘Jidou12’ × ‘ZYD2738’. The seed weight for heterozygous individuals was 1.1‐ to 1.6‐fold higher than that of homozygous individuals among the six validation populations examined in different locations and years. Therefore, qSWT_13_1 may be a useful locus to improve the yield of hybrid soybean and to understand the molecular mechanism of heterosis in soybean.     

Molecular mapping of soybean seed tocopherols in the cross ‘OAC Bayfield’ × ‘OAC Shire’

Soybean (Glycine max [L.] Merr.) is cultivated primarily for its protein and oil in the seed. In addition, soybean seeds contain nutraceutical compounds such as tocopherols (vitamin E), which are powerful antioxidants with health benefits. The objective of this study was to identify molecular markers linked to quantitative trait loci (QTL) that affect accumulation of soybean seed tocopherols. A recombinant inbred line (RIL) population derived from the cross ‘OAC Bayfield’ × ‘OAC Shire’ was grown in three locations over 2 years. A total of 151 SSR markers were polymorphic of which a one‐way analysis of variance identified 42 markers whereas composite interval mapping identified 26 markers linked to tocopherol QTL across 17 chromosomes. Individual QTL explained from 7% to 42% of the total phenotypic variation. Significant two‐locus epistatic interactions were identified for a total of 122 combinations in 2009 and 152 in 2010. The multiple‐locus models explained 18.4–72.2% of the total phenotypic variation. The reported QTL may be used in marker‐assisted selection (MAS) to develop high tocopherol soybean cultivars.     

Identification of quantitative trait loci underlying soybean (Glycine max [L.] Merr.) seed weight including main,epistatic and QTL × environment effects in different regions of Northeast China

Seed weight (SW) is the important soybean (Glycine max [L.] Merr.), yield component and also affected the quality of soybean‐derived foods. The aim of this study was to identify the quantitative trait loci (QTL) underlying SW through 112 recombinant inbred lines (RILs) derived from the cross between “Zhongdou27” (G. max, designated by its bigger seed size, 21.9 g/100 seeds) and “Jiunong 20” (G. max, smaller seed size, 17.5 g/100 seeds). Phenotypic data were collected from this RIL population after it was grown in the sixteen tested environments. A total of eight QTL (QSW1‐1, QSW2‐1, QSW2‐2, QSW5‐1, QSW15‐1, QSW17‐1, QSW19‐1 and QSW20‐1) were identified, and they could explain 4.23%–14.65% of the phenotypic variation. Among these eight QTL, three QTL (QSW1‐1 located on the interval of Sat_159‐Satt603 of chromosome (Chr) 1 (LGD1a), QSW19‐1 located on the interval of Sat_340‐Satt523 of Chr 19 (LGL) and QSW20‐1 located on Sat_418‐Sat_105 of Chr 20 (LGI)) were newly identified and could explain 4.235%–10.08%, 8.45%–13.49% and 8.08%–10.18% of the phenotypic variation, respectively. Six of the eight identified QTL including QSW2‐2, QSW5‐1, QSW15‐1, QSW17‐1, QSW19‐1 and QSW20‐1 exhibited a significant additive (a) effect, while two QTL (QSW2‐1 and QSW19‐1) only displayed significant additive‐by‐environment (ae) effects. A total of four epistatic pairwise QTL for SW were identified in the different environments. These eight QTL and their genetic information obtained here were valuable for molecular marker‐assisted selection and the realization of a reasonable SW breeding programme in soybean.     

Quantitative trait loci for agronomic traits in soybean

There continues to be improvement in seed yields of soybean by conventional breeding, but molecular techniques may provide faster genetic gains. The objective of this study was to identify quantitative trait loci (QTL) associated with the agronomic traits seed yield, lodging, plant height, seed filling period and plant maturity in soybean. To achieve this objective, 101 F₆‐derived recombinant inbred lines (RIL) from a population developed from a cross of N87‐984‐16 × TN93‐99 were used. Experiments were conducted in six environments during 2002–2003. Heritability estimates on an entry mean basis from data combined across environments ranged from 0.12 to 0.65 for seed yield and seed filling period, respectively. Composite interval mapping detected one QTL for yield (near Satt076), two for lodging (near Satt225 and Satt593) and four for maturity (near Satt263, Satt292, Satt293 and Satt591) in this population. Additional environmentally sensitive QTL for these traits, and for seed filling period and plant height are also reported. The QTL associated with agronomic traits that we report and the recently released germplasm (PI 636460) from this population may be useful in soybean breeding programmes.     

Molecular tagging of Asiatic soybean rust resistance in exotic genotype EC 241780 reveals complementation of two genes

Asian soybean rust (ASR) caused by Phakopsora pachyrhizi severely reduces seed yield in soybean. Molecular tagging of ASR resistance can help in the process of resistance breeding. In this study, an F₂ population of cross (susceptible cultivar ‘NRC 7’ × resistant exotic genotype EC 241780) was used for bulked segregant analysis (BSA) with 25 SSR (simple sequence repeat) primers linked with six Rpp genes. Among them, five polymorphic SSR markers, viz., Sct 187, SSR 1859, Satt 191 (Rpp1b like loci) and Satt 215, Sat_361 (Rpp2 loci) distinguished the ASR resistant and susceptible bulks and individuals. In combined marker analysis, the markers Satt 191 (Rpp1b like loci) and Satt 215 (Rpp2 loci) were linked with ASR severity score and were also confirmed in individual 110 F₂ segregants. Hence, these markers could be utilized in the marker assisted rust resistance breeding of Rpp1b like and Rpp2 genes. In silico candidate gene analysis for hypersensitive response revealed that Satt 191 linked region was rich in genes encoding apoptotic ATPase having leucine‐rich repeat (LRR) domain.     

Identification of quantitative trait loci for seed isoflavone concentration in soybean (Glycine max) against soybean cyst nematode stress

Isoflavones are plant secondary metabolites produced in soybean (Glycine max), which provide plant defense against pathogens and are beneficial to human health. Soybean cyst nematode (SCN) is a major yield‐limiting pest in most soybean‐producing area across the world. Traits, seed isoflavones and SCN resistance are quantitative in nature, and their phenotypic evaluations are expensive. Quantitative trait loci (QTL) underlying the two traits will be helpful to develop SCN‐resistant lines with elevated isoflavones using marker‐assisted‐selection (MAS). This study aims to identify isoflavones and SCN‐related QTL in a soybean population consisting of 109 RILs, which was developed from a cross between two commercial soybean cultivars viz. ‘RCAT1004’ and ‘DH4202’ and grown in four non‐SCN and SCN‐infested fields during 2015 and 2016. While single marker ANOVA identified 10 QTL for isoflavones and five for SCN (p < 0.01), simple interval and multiple QTL mappings identified four QTL associated with isoflavones (LOD ≥ 2.2). These results contribute to a better understanding of the genetics of the two traits and provide molecular markers that can be used in MAS to facilitate developing SCN‐resistant soybeans with increased isoflavones.     

Mapping quantitative trait loci (QTLs) underlying seed vitamin E content in soybean with main,epistatic and QTL × environment effects

Soybean (Glycine max (L.) Merr.) seed contains small amounts of tocopherol, a non‐enzymatic antioxidant known as lipid‐soluble vitamin E (VE). Dietary VE contributes to a decreased risk of chronic diseases in humans and has several beneficial effects on resistance to stress in plants, and increasing VE content is an important breeding goal for increasing the nutritional value of soybean. In this study, quantitative trait loci (QTLs) underlying VE content with main, epistatic and QTL × environment effects were identified in a population of F_5 : 6 recombinant inbred lines from a cross between ‘Hefeng 25’ (a low‐VE cultivar) and ‘OAC Bayfield’ (a high‐VE cultivar). A total of 18 QTLs were detected that showed additive main effects (a) and/or additive × environment interaction effects (ae) in different environments. Moreover, 19 epistatic pairs of QTLs were found to be associated with α‐tocopherol (α‐Toc), γ‐tocopherol (γ‐Toc), δ‐tocopherol (δ‐Toc) and total VE (TE) contents. The QTLs identified in multienvironments could provide more information about QTL by environment interactions and could be useful for the marker‐assistant selection of soybean cultivars with high seed VE contents.     

Unconditional and conditional QTL underlying the genetic interrelationships between soybean seed isoflavone,and protein or oil contents

Selection for soybean (Glycine max L. Merr.) rich in isoflavones, protein and oil has been difficult due to negative genetic interrelationships. In this study, genetic interrelationships among seed isoflavones and protein and oil contents were evaluated using both unconditional and conditional QTL mapping. Daidzein (DZ), genistein (GT), glycitein (GC) and total isoflavone (TI) contents were analysed in F_5:6, F_5:7 and F_5:8 recombinant inbred lines (RILs) derived from a cross between ‘Zhongdou 27’(TI 3791 μg/g; protein content 42.84%; oil content 18.73%) and ‘Jiunong 20’ (TI 2061 μg/g; protein content 34.05%; oil content 21.42%). When DZ, GT, GC and TI were analysed for their genetic relationships with protein or oil contents, eight conditional QTL were detected, which included DZ|pro, GC|pro, GT|pro, TI|pro, DZ|oil, GC|oil, GT|oil and TI|oil. Seventeen QTL that had significant genetic associations between seed isoflavone, and seed protein or oil contents were found, including two for DZ conditioned on protein (qDZ|proK‐1, qDZ|proF‐2); one for GC conditioned on protein (qGC|proM‐1); three for GT conditioned on protein (qGT|proM‐1, qGT|proA2‐1, qGT|proL‐1); three for TI conditioned on protein (qTI|proM‐1, qTI|proA2‐1, qTI|proF‐2); one for DZ conditioned on oil (qDZ∣oil K_1); one for GC conditioned on oil (qGC∣oilI_1); four for GT conditioned on oil (qGT∣oil A2_1, qGT∣oil F_1, qGTF_2, qGT∣oilD2_1); three for TI conditioned on oil (qTI∣oilA2‐1, qTI∣oilE‐1, qTI∣oilL‐1). Few epistatic interactions among loci were detected. These loci may be valuable for improving seed isoflavone, protein and oil contents.     

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.     

Modifier QTL for fatty acid composition in soybean oil

Soybean [Glycine max (L.) Merr.] is the principal oilseed crop in the world. Soybean oil has various industrial and food applications. The quality of soybean oil is determined by its fatty acid composition. Palmitic, stearic, oleic, linoleic and linolenic are the predominant fatty acids in soybean oil. The objective of this study was to determine the associations of simple sequence repeat (SSR) molecular markers with minor differences in fatty acids in soybean oil thereby detecting modifier quantitative trait loci (QTL) which could further improve soybean oil quality. To achieve this objective, 101 F₆-derived recombinant inbred lines (RIL) from a population whose parents did not contain major mutant fatty acid alleles were developed from a cross of N87-984-16 × TN93-99. Fatty acids were determined by gas chromatography. Heritability estimates on an entry mean basis for fatty acids ranged from 65.8 to 77.3% for palmitic and linoleic acids, respectively. Molecular marker Satt537 located on molecular linkage group (MLG) D1b was associated with palmitic acid and Satt168 and Satt249 located on MLG B2 and J, respectively were associated with stearic acid. Molecular markers Satt185 or Satt268 (which are within 0.6 cM of each other) located on MLG E were consistently associated with oleic and linoleic acid, and Satt263 and Satt235 located on MLG E and G, respectively were associated with linolenic acid. The lack of markers associated with multiple fatty acids suggests the possibility of independently changing fatty acid levels to achieve a desirable composition, except for regions common to all saturated fatty acids. Phenotypic variation explained by the fatty acids modifier QTL ranged from 10 to 22.5%. These modifier QTL may be useful in making minor improvements to further enhance the quality of soybean oil.     

Backcross breeding for improved resistance to common bacterial blight in pinto bean (Phaseolus vulgaris L.)

Common bacterial blight (CBB) caused by Xanthomonas campestris pv. phaseoli reduces common bean (Phaseolus vulgaris L.) yield and quality worldwide. Genetic resistance provides effective disease control; however. a high level of resistance is difficult to attain and does not exist in pinto bean, the most important dry bean market class in North America. Our objective was to determine if a backcross breeding approach with the aid of molecular markers linked to quantitative trait loci (QTL) for resistance to CBB in a donor parent could be used to attain higher levels of resistance to CBB in pinto bean. QTL conditioning CBB resistance from the donor parent XAN 159 were introgressed into the recurrent parent‘Chase’using classical backcross breeding and intermittent marker‐assisted selection.‘Chase’pinto bean is moderately resistant and the breeding line XAN 159 is highly resistant to Xanthomonas campestris. Marker assays confirmed the presence of independent QTL from GN no. 1 Sel 27 and XAN 159 in advanced backcross‐derived pinto bean lines with improved CBB resistance. Agronomic characteristics of‘Chase’were fully recovered in the backcross‐derived lines. An important QTL for CBB resistance from XAN 159 on linkage group B6 was not introgressed because tight linkage between this QTL and the dominant V allele that causes an unacceptable black‐mottled seed coat colour pattern in pinto bean could not be broken.     

Association analysis using SSR markers to find QTL for seed protein content in soybean

Association analysis studies can be used to test for associations between molecular markers and quantitative trait loci (QTL). In this study, a genome-wide scan was performed using 150 simple sequence repeat (SSR) markers to identify QTL associated with seed protein content in soybean. The initial mapping population consisted of two subpopulations of 48 germplasm accessions each, with high or low protein levels based on data from the USDA’s Germplasm Resources Information Network website. Intrachromosomal LD extended up to 50 cM with r ² > 0.1 and 10 cM with r ² > 0.2 across the accessions. An association map consisting of 150 markers was constructed on the basis of differences in allele frequency distributions between the two subpopulations. Eleven putative QTL were identified on the basis of highly significant markers. Nine of these are in regions where protein QTL have been mapped, but the genomic regions containing Satt431 on LG J and Satt551 on LG M have not been reported in previous linkage mapping studies. Furthermore, these new putative protein QTL do not map near any QTL known to affect maturity. Since biased population structure was known to exist in the original association analysis population, association analyses were also conducted on two similar but independent confirmation populations. Satt431 and Satt551 were also significant in those analyses. These results suggest that our association analysis approach could be a useful alternative to linkage mapping for the identification of unreported regions of the soybean genome containing putative QTL.     

Analysis of quantitative trait loci underlying the period of reproductive growth stages in soybean (<Emphasis Type="Italic">Glycine max</Emphasis> [L.] Merr.)

Quantitative trait loci (QTLs) underlying reproductive growth stages are important for molecular breeding of soybeans [Glycine max (L.) Merr.]. Most of these QTLs identified so far derived from a single environment, and thus may be influenced by specific environmental conditions. In this study (from 2004 to 2005), analysis of QTLs underlying the period to reach a given reproductive growth stage was performed in three different environments (Harbin, Heilongjiang Province, China). QTL analysis was achieved with a recombination inbred line (RIL) population consisting of 153 lines. The RIL population derived from a cross between an American semi-dwarf cultivar (cv. Charleston) and a Chinese line with a short growth stage (cv. Dongnong 594). The growth stage data of soybean was recorded for each day. QTLs for all eight reproductive growth stages of soybean (R1 to R8) were analyzed by a composite interval mapping method combined with a mixed genetic model. Fifty-four QTLs displayed main effects and 56 QTL pairs showed epistatic effects. Two marker intervals (Satt173–Satt581, Satt402–Satt267), located on the linkage group O and D1a respectively, strongly influenced plant developmental processes during reproductive growth stages. The findings of this study open the possibility to modulate the structure of soybean growth stages by marker-assisted selection and pyramiding QTL analysis. H.-M. Qiu and D.-W. Xin contributed equally to this work.     

大豆不同环境下脂肪酸组分含量的QTL分析

大豆油的品质取决于脂肪酸各组分在大豆中的比例, 为发掘控制大豆5种脂肪酸含量的数量性状位点(QTL), 利用冀豆12和黑豆重组自交系群体构建遗传图谱, 采用Windows QTL Cartographer 2.5和QTL Network-2.0软件的CIM和MCIM法对大豆5种脂肪酸组分进行数量性状定位。结果表明,在石家庄和三亚各环境下共检测到16个QTL, 位于连锁群A2、B2、C2、F、G、I、L上。对2个环境联合分析, 检测到13个QTL, 其中9个用2种方法被检测到, 但这13个位点与环境互作的贡献率明显小于加性效应。其中在B2连锁群Satt168~Satt556控制硬脂酸的QTL Ste-1在河北石家庄和海南三亚均能被检测到, 贡献率均为12%, 在双尾群体和间隔挑选群体中也能检测到控制硬脂酸的QTL Ste-1, 说明这一QTL稳定存在于本组合群体中, 为今后大豆硬脂酸的QTL精细定位奠定了基础。     

Molecular mapping of a new gene for resistance to frogeye leaf spot of soya bean in 'Peking'

Amplified fragment length polymorphism (AFLP) and microsatellite (simple sequence repeat, SSR) techniques were used to map the _RGSp_eking gene, which is resistant to most isolates of Cercospora sojina in the soya bean cultivar ‘Peking’. The mapping was conducted using a defined F₂ population derived from the cross of ‘Peking’(resistant) בLee’(susceptible). Of 64 EcoRI and MseI primer combinations, 30 produced polymorphisms between the two parents. The F₂ population, consisting of 116 individuals, was screened with the 30 AFLP primer pairs and three mapped SSR markers to detect markers possibly linked to Rcs_Peking. One AFLP marker amplified by primer pair E‐AAC/M‐CTA and one SSR marker Satt244 were identified to be linked to Res_Peking. The gene was located within a 2.1‐cM interval between markers AACCTA178 and Satt244, 1.1 cM from Satt244 and 1.0 cM from AACCTA178. Since the SSR markers Satt244 and Satt431 have been mapped to molecular linkage group (LG) J of soya bean, the Res_Peking resistance gene was putatively located on the LG J. This will provide soya bean breeders an opportunity to use these markers for marker‐assisted selection for frogeye leaf spot resistance in soya bean.     

大豆粒形性状QTL的精细定位

在溧水中子黄豆×南农493-1衍生的504个F_2:6家系中选择Satt331~Satt592目标区间7个杂合单株和168个重组单株,衍生成356株RHL-F₂个体(群体I)和168个重组体家系(群体II)。群体II来自142个F_2:6家系,若每个F_2:6家系只保留1个重组家系则构成群体III。采用lasso和复合区间作图(CIM)法检测3个群体粒形性状2种指标的QTL。结果表明, lasso法检测到的粒长关联标记是O19和S21/Satt331,而CIM检测到的QTL区间是S21~S22和O23~O19;lasso法检测到的粒宽关联标记是O19/O21,而CIM检测到的QTL区间是O23~O19/O19~O21;长宽比与S21~S22关联是由于粒长QTL引起的,与O23~O19 /O19~O21关联是由于粒长和粒宽QTL引起的。将原Satt331~Satt592目标区间的粒长QTL剖分为与标记S21~S22和O23~O19/O19~O21关联的2个多效性QTL。根据大豆基因注释数据库,Glyma10g35240和Glyma10g34980可能是控制粒形性状发育的候选基因。