Validation and high-resolution mapping of a major quantitative trait locus for alkaline salt tolerance in soybean using residual heterozygous line

Alkaline soil restricts soybean plant growth and yield. In our previous study, a major alkaline salt tolerance quantitative trait locus (QTL) was identified in soybean on chromosome 17. In this study, the residual heterozygous line (RHL46), which was selected from a population of F6 recombinant inbred lines (RILs) derived from a cross between an alkaline salt-sensitive soybean cultivar Jackson and a tolerant wild soybean accession JWS156-1, was used for validation and high-resolution mapping of the QTL. In a large segregating population (n = 1,109), which was produced by self-pollinating heterozygotes of RHL46, segregation of alkaline salt tolerance showed a continuous distribution, and the tolerant plants were predominant. Linkage mapping analysis revealed a major QTL with a large dominant effect for alkaline salt tolerance, and the highest LOD score was detected between the single sequence repeat (SSR) markers GM17-12.2 and Satt447. Furthermore, 10 fixed recombinant lines carrying chromosome fragments of different lengths in the QTL region were selected from the RHL46 progeny. Phenotype evaluation and SSR marker analysis of the recombinant lines narrowed down the QTL to a 3.33-cM interval region between the markers GM17-11.6 and Satt447 with a physical map length of approximately 771 kb. High-resolution mapping of the alkaline salt tolerance QTL will be useful not only for marker-assisted selection in soybean breeding programs but also for map-based cloning of the alkaline salt tolerance gene in order to understand alkaline salt tolerance in soybean and other plant species.     

Increasing the density of markers around a major QTL controlling resistance to angular leaf spot in common bean

Angular leaf spot (ALS) causes major yield losses in the common bean (Phaseolus vulgaris L.), an important protein source in the human diet. This study describes the saturation around a major quantitative trait locus (QTL) region, ALS10.1, controlling resistance to ALS located on linkage group Pv10 and explores the genomic context of this region using available data from the P. vulgaris genome sequence. DArT-derived markers (STS-DArT) selected by bulk segregant analysis and SCAR and SSR markers were used to increase the resolution of the QTL, reducing the confidence interval of ALS10.1 from 13.4 to 3.0 cM. The position of the SSR ATA220 coincided with the maximum LOD score of the QTL. Moreover, a new QTL (ALS10.2^UC) was identified at the end of the same linkage group. Sequence analysis using the P. vulgaris genome located ten SSRs and seven STS-DArT on chromosome 10 (Pv10). Coincident linkage and genome positions of five markers enabled the definition of a core region for ALS10.1 spanning 5.3 Mb. These markers are linked to putative genes related to disease resistance such as glycosyl transferase, ankyrin repeat-containing, phospholipase, and squamosa-promoter binding protein. Synteny analysis between ALS10.1 markers and the genome of soybean suggested a dynamic evolution of this locus in the common bean. The present study resulted in the identification of new candidate genes and markers closely linked to a major ALS disease resistance QTL, which can be used in marker-assisted selection, fine mapping and positional QTL cloning.     

Identification and analysis of QTLs controlling cold tolerance at the reproductive stage and validation of effective QTLs in cold-tolerant genotypes of rice (Oryza sativa L.)

Low temperature or cold stress is one of the major constraints of rice production and productivity in temperate rice-growing countries and high-altitude areas in the tropics. Even though low temperature affects the rice plant in all stages of growth, the percent seed set is damaged severely by cold and this reduces the yield potential of cultivars significantly. In this study, a new source of cold-tolerant line, IR66160-121-4-4-2, was used as a donor parent with a cold-sensitive cultivar, Geumobyeo, to produce 153 F₈ recombinant inbred lines (RILs) for quantitative trait locus (QTL) analysis. QTL analysis with 175 polymorphic simple sequence repeat (SSR) markers and composite interval mapping identified three main-effect QTLs (qPSST-3, qPSST-7, and qPSST-9) on chromosomes 3, 7, and 9. The SSR markers RM569, RM1377, and RM24545 were linked to the identified QTLs for cold tolerance with respect to percent seed set using cold-water (18–19°C) irrigation in the field and controlled air temperature (17°C) in the greenhouse. The total phenotypic variation for cold tolerance contributed by the three QTLs was 27.4%. RILs with high percent seed set under cold stress were validated with linked DNA markers and by haplotype analysis that revealed the contribution of progenitor genomes from the tropical japonica cultivar Jimbrug (Javanica) and temperate japonica cultivar Shen-Nung89-366. Three QTLs contributed by the cold-tolerant parent were identified which showed additive effect on percent seed set under cold treatment. This study demonstrated the utility of a new phenotyping method as well as the identification of SSR markers associated with QTLs for selection of cold-tolerant genotypes to improve temperate rice production.     

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 QTLs with Additive,Epistatic, and QTL × Seed Maturity Interaction Effects for Seed Vigor in Rice

Seed maturity is a critical process of seed vigor establishment. In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed vigor, including the germination potential (GP), germination rate (GR), germination index (GI), and time for 50 % of germination (T₅₀), at 4, 5, and 6 weeks after heading in 2 years. Significant differences of seed vigor were observed among two parents and RIL population; the heritability of four traits was more than 90 % at three maturity stages. A total of 19 additive and 2 epistatic quantitative trait loci (QTL) for seed vigor were identified using QTL Cartographer and QTLNetwork program, respectively, in 2012, while 16 simple sequence repeat (SSR) markers associated with seed vigor were detected using bulked segregant analysis (BSA) in 2013. The phenotypic variation explained by each additive, epistatic QTL, and QTL × seed maturity interaction ranged from 9.19 to 22.94 %, 7.23 to 7.75 %, and 0.05 to 0.63 %, respectively. Ten additive QTLs were stably expressed in 2 years which might play important roles in establishment of seed vigor in different environments. By comparing chromosomal positions of ten stably expressed additive QTLs with those previously identified, they might be true QTLs for seed vigor; the regions of QTLs for seed vigor are likely to coincide with QTLs for seed dormancy, seed reserve mobilization, low-temperature germinability, and seedling growth. Using four selected RILs, three cross-combinations were predicted to improve seed vigor; 9 to 10 elite alleles could be pyramided by each combination. The selected RILs and the identified QTLs might be applicable for the improvement of seed vigor by marker-assisted selection (MAS) in rice.     

A major QTL controlling seed dormancy and pre-harvest sprouting resistance on chromosome 4A in a Chinese wheat landrace

Wheat pre-harvest sprouting (PHS) can cause significant reduction in yield and end-use quality of wheat grains in many wheat-growing areas worldwide. To identify a quantitative trait locus (QTL) for PHS resistance in wheat, seed dormancy and sprouting of matured spikes were investigated in a population of 162 recombinant inbred lines (RILs) derived from a cross between the white PHS-resistant Chinese landrace Totoumai A and the white PHS-susceptible cultivar Siyang 936. Following screening of 1,125 SSR primers, 236 were found to be polymorphic between parents, and were used to screen the mapping population. Both seed dormancy and PHS of matured spikes were evaluated by the percentage of germinated kernels under controlled moist conditions. Twelve SSR markers associated with both PHS and seed dormancy were located on the long arm of chromosome 4A. One QTL for both seed dormancy and PHS resistance was detected on chromosome 4AL. Two SSR markers, Xbarc 170 and Xgwm 397, are 9.14 cM apart, and flanked the QTL that explained 28.3% of the phenotypic variation for seed dormancy and 30.6% for PHS resistance. This QTL most likely contributed to both long seed dormancy period and enhanced PHS resistance. Therefore, this QTL is most likely responsible for both seed dormancy and PHS resistance. The SSR markers linked to the QTL can be used for marker-assisted selection of PHS-resistant white wheat cultivars. Shi-Bin Cai and Cui-Xia Chen contributed equally to this work.     

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 SNPs tightly linked to the QTL for pod shattering in soybean

The pod shattering or dehiscence is essential for the propagation of pod-bearing plant species in the wild, but it causes significant yield losses during harvest of domesticated crop plants. Identifying novel molecular makers, which are linked to seed-shattering genes, is needed to employ the molecular marker-assisted selection for efficiently developing shattering-resistant soybean varieties. In this study, a genetic linkage map was constructed using 115 recombinant inbred lines (RILs) developed from crosses between the pod shattering susceptible variety, Keunol, and resistant variety, Sinpaldal. A 180 K Axiom® SoyaSNPs data and pod shattering data from two environments in 2001 and 2015 were used to identify quantitative trait loci (QTL) for pod shattering. A major QTL was identified between two flanking single nucleotide polymorphism (SNP) markers, AX-90320801 and AX-90306327 on chromosome 16 with 1.3 cM interval, 857 kb of physical range. In sequence, genotype distribution analysis was conducted using extreme phenotype RILs. This could narrow down the QTL down to 153 kb on the physical map and was designated as qPDH1-KS with 6 annotated gene models. All exons within qPDH1-KS were sequenced and the 6 polymorphic SNPs affecting the amino acid sequence were identified. To develop universally available molecular markers, 38 Korean soybean cultivars were investigated by the association study using the 6 identified SNPs. Only two SNPs were strongly associated with the pod shattering. These two identified SNPs will help to identify the pod shattering responsible gene and to develop pod shattering-resistant soybean plants using marker-assisted selection.     

Identification of QTLs Underlying Water-Logging Tolerance in Soybean

Soil water-logging can cause severe damage to soybean [Glycine max (L.) Merr.] and results in significant yield reduction. The objective of this study was to identify quantitative trait loci (QTL) that condition water-logging tolerance (WLT) in soybean. Two populations with 103 and 67 F_6:11 recombinant inbred lines (RILs) from A5403 × Archer (Population 1) and P9641 × Archer (Population 2), respectively, were used as the mapping populations. The populations were evaluated for WLT in manually flooded fields in 2001, 2002, and 2003. Significant variation was observed for WLT among the lines in the two populations. No transgressive tolerant segregants were observed in either population. Broad-sense heritability of WLT for populations 1 and 2 were 0.59 and 0.43, respectively. The tolerant and sensitive RILs from each population were selected to create a tolerant bulk and a sensitive bulk, respectively. The two bulks and the parents of each population were tested with 912 simple sequence repeat (SSR) markers to select candidate regions on the linkage map that were associated with WLT. Markers from the candidate regions were used to genotype the RILs in both populations. Both single marker analysis (SMA) and composite interval mapping (CIM) were used to identify QTL for WLT. Seventeen markers in Population 1 and 15 markers in Population 2 were significantly (p <0.0001) associated with WLT in SMA. Many of these markers were linked to Rps genes or QTL conferring resistance to Phytophthora sojae Kaufmann and Gerdemann. Five markers, Satt599 on linkage group (LG) A1, Satt160, Satt269, and Satt252 on LG F, and Satt485 on LG N, were significant (p <0.0001) for WLT in both populations. With CIM, a WLT QTL was found close to the marker Satt385 on LG A1 in Population 1 in 2003. This QTL explained 10% of the phenotypic variation and the allele that increased WLT came from Archer. In Population 2 in 2002, a WLT QTL was located near the marker Satt269 on LG F. This QTL explained 16% of the phenotypic variation and the allele that increased WLT also came from Archer.     

Identification of simple sequence repeat markers linked to lipoxygenase-1 gene in soybean

Off-flavour generated in soy products is ascribed to soybean seed lipoxygenase-1, lipoxygenase-2 and lipoxygenase-3, controlled by single dominant genes Lox1, Lox2 and Lox3, respectively. Lox2 locus has already been mapped and reported to be tightly linked with Lox1 locus. The objective of the present study was to map Lox1 locus by investigating the SSR markers reported to be linked with Lox2 locus and the neighbouring SSR markers in two mapping populations of 116 and 91 plants developed from LSb1 × PI408251 and JS335 × PI408251, respectively. Parental polymorphism was surveyed using SSR markers Sat_074, Satt522 reported to be linked with Lox2 locus and the SSR markers in its proximity. F_2:3 seeds were used for assaying lipoxygenase-1 to identify the genotype of the F₂ individuals. SSR marker Satt656 was found to be tightly linked with Lox1 locus at distance of 3.6 and 4.8 cM in the mapping population of LSb1 × PI408251 and JS335 × PI408251, respectively. SSR marker Satt656 can be useful for marker assisted selection for transferring recessive allele of lipoxygenase-1 in the background of high yielding soybean genotypes.     

Identification of QTL in soybean underlying resistance to herbivory by Japanese beetles (Popillia japonica, Newman)

Soybean [Glycine max (L.) Merr.] was one of the most important legume crops in the world in 2010. Japanese beetles (JB; Popillia japonica, Newman) in the US were an introduced and potentially damaging insect pest for soybean. JBs are likely to spread across the US if global warming occurs. Resistance to JB in soybean was previously reported only in plant introductions. The aims here were to identify loci underlying resistance to JB herbivory in recombinant inbred lines (RILs) derived from the cross of Essex × Forrest cultivars (EF94) and to correlate those with loci with factors that confer insect resistance in soybean cultivars. The RIL population was used to map 413 markers, 238 satellite markers and 177 other DNA markers. Field data were from two environments over 2 years. Pest severity (PS) measured defoliation on a 0–9 scale. Pest incidence (PI) was the percentage of plants within each RIL with beetles on them. Antibiosis and antixenosis data were from feeding assays with detached leaves in petri plates. Five QTL were detected for the mean PS field trait (16% < R ² < 27%). The loci were within the intervals Satt632–A2D8 on linkage group (LG) A2 (chromosome 8); Satt583–Satt415 on LG B1 (11); Satt009–Satt530 on LG N (3); and close to two markers OB02_140 (LG E; 20 cM from Satt572) and OZ15_150 LG (19 cM from Satt291 C2). Two QTL were detected for the mean PI field trait (16% < R ² < 18%) close to Satt385 on LG A1 and Satt440 on LG I. The no choice feeding studies detected three QTL that were significant; two for antixenosis (22% < R ² < 24%) between Satt632–A2D8 on LG A2 (8) and Sat_039–Satt160 on LG F (13); and a major locus effect (R ² = 54%) for antibiosis on LG D2 (17) between Satt464–Satt488. Therefore, loci underlying resistance to JB herbivory were a mixture of major and minor gene effects. Some loci were within regions underlying resistance to soybean cyst nematode (LGs A2 and I) and root knot nematode (LG F) but not other major loci underlying resistance to nematode or insect pests (LGs G, H and M).     

SSR markers closely associated with genes for resistance to root-knot nematode on chromosomes 11 and 14 of Upland cotton

Molecular markers closely linked to genes that confer a high level of resistance to root-knot nematode (RKN) [Meloidogyne incognita (Kofoid & White) Chitwood] in cotton (Gossypium hirsutum L.) germplasm derived from Auburn 623 RNR would greatly facilitate cotton breeding programs. Our objectives were to identify simple sequence repeat (SSR) markers linked to RKN resistance quantitative trait loci (QTL) and map these markers to specific chromosomes. We developed three recombinant inbred line (RIL) populations by single seed descent from the crosses of RKN-resistant parents M-240 RNR (M240), developed from the Auburn 623 RNR source, moderately resistant Clevewilt 6 (CLW6), one of the parents of Auburn 623 RNR, and susceptible parent Stoneville 213 (ST213). These crosses were CLW6 × ST213, M240 × CLW6, and M240 × ST213. RILs from these populations were grown under greenhouse conditions, inoculated with RKN eggs, scored for root gall index, eggs plant⁻¹, and eggs g⁻¹ root. Plants were also genotyped with SSR markers. Results indicated that a minimum of two major genes were involved in the RKN resistance of M240. One gene was localized to chromosome 11 and linked to the marker CIR 316-201. This CIR 316-201 allele was also present in CLW6 but not in Mexico Wild (MW) (PI593649), both of which are parents of Auburn 623 RNR. A second RKN resistance gene was localized to the short arm of chromosome 14 and was linked to the SSR markers BNL3545-118 and BNL3661-185. These two marker alleles were not present in CLW6 but were present in MW. Our data also suggest that the chromosome 11 resistance QTL primarily affects root galling while the QTL on chromosome 14 mediates reduced RKN egg production. The SSRs identified in this study should be useful to select plants with high levels of RKN resistance in segregating populations derived from Auburn 623 RNR.     

Genetic analysis of shoot fresh weight in a cross of wild (<Emphasis Type="Italic">G. soja</Emphasis>) and cultivated (<Emphasis Type="Italic">G. max</Emphasis>) soybean

Shoot fresh weight (SFW) is one of the parameters, used to estimate the total plant biomass yield in soybean. In the present study, a total of 188 F_5:8 recombinant inbred lines (RIL) derived from an interspecific cross of PI 483463 (Glycine soja) and Hutcheson (Glycine max) were investigated for SFW variation in the field for three consecutive years. The parental lines and RILs were phenotyped in the field at the R6 stage by measuring total biomass in kg/plot to identify the QTLs for SFW. Three QTLs qSFW6_1, qSFW15_1, and qSFW19_1 influencing SFW were identified on chromosome 6, 15, and 19, respectively. The QTL qSFW19_1 flanked between the markers BARC-044913-08839 and BARC-029975-06765 was the stable QTL expressed in all the three environments. The phenotypic variation explained by the QTLs across all environments ranged from 6.56 to 21.32 %. The additive effects indicated contribution of alleles from both the parents and additive × environment interaction effects affected the expression of SFW QTL. Screening of the RIL population with additional SSRs from the qSFW19_1 region delimited the QTL between the markers SSR19-1329 and BARC-29975-06765. QTL mapping using bin map detected two QTLs, qSFW19_1A and qSFW19_1B. The QTL qSFW19_1A mapped close to the Dt1 gene locus, which affects stem termination, plant height, and floral initiation in soybean. Potential candidate genes for SFW were pinpointed, and sequence variations within their sequences were detected using high-quality whole-genome resequencing data. The findings in this study could be useful for understanding genetic basis of SFW in soybean.     

Mapping of durable stripe rust resistance in a durum wheat cultivar Wollaroi

Wollaroi, an Australian durum wheat cultivar, produced a low stripe rust response and the alternative parent Bansi was highly susceptible. The Wollaroi/Bansi recombinant inbred line (RIL) population was phenotyped across three consecutive crop seasons. A genetic map of the Wollaroi/Bansi RIL population comprising 799 markers (diversity arrays technology and simple sequence repeat markers) was used to determine the genomic location of stripe rust resistance genes carried by the cultivar Wollaroi. Composite interval mapping detected three consistent quantitative trait loci (QTL) in chromosomes 2A, 3B and 5B. These QTL were named QYr.sun-2A, QYr.sun-3B and QYr.sun-5B. Another QTL, QYr.sun-1B, was detected only in the 2009 crop season. QTL in chromosomes 1B, 2A, 3B and 5B explained on average 6, 9.3, 26.7 and 8.7 %, respectively, of the variation in stripe rust response. All QTL were contributed by Wollaroi. RILs carrying these QTL singly produced intermediate stripe rust severities ranging from 46.2 to 55.7 %, whereas RILs with all four QTL produced the lowest disease severity (34.3 %). The consistently low stripe rust response of Wollaroi for 20 years demonstrated the durability of the resistance loci involved. The QTL combination detected in this study is being transferred to common wheat.     

Quantitative trait loci controlling sulfur containing amino acids, methionine and cysteine, in soybean seeds

Soybean [Glycine max (L.) Merr.] is the single largest source of protein in animal feed. However, a major limitation of soy proteins is their deficiency in sulfur-containing amino acids, methionine (Met) and cysteine (Cys). The objective of this study was to identify quantitative trait loci (QTL) associated with Met and Cys concentration in soybean seed. 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. Ground soybean seed samples were analyzed for Met and Cys concentration using a near infrared spectroscopy instrument. Data were analyzed using SAS software and QTL Cartographer. RIL differed (P<0.01) in Met and Cys concentrations, with a range of 5.1–7.3 (g kg⁻¹ seed dry weight) for Cys and 4.4–8.8 (g kg⁻¹ seed dry weight) for Met. Heritability estimates on an entry mean basis were 0.14 and 0.57 for Cys and Met, respectively. A total of 94 polymorphic simple sequence repeat molecular genetic markers were screened in the RIL. Single factor ANOVA was used to identify candidate QTL, which were confirmed by composite interval mapping using QTL Cartographer. Four QTL linked to molecular markers Satt235, Satt252, Satt427 and Satt436 distributed on three molecular linkage groups (MLG) D1a, F and G were associated with Cys and three QTL linked to molecular markers Satt252, Satt564 and Satt590 distributed on MLG F, G and M were associated with Met concentration in soybean seed. QTL associated with Met and Cys in soybean seed will provide important information to breeders targeting improvements in the nutritional quality of soybean.     

QTL mapping of slow-rusting, adult plant resistance to race Ug99 of stem rust fungus in PBW343/Muu RIL population

Races of stem rust fungus pose a major threat to wheat production worldwide. We mapped adult plant resistance (APR) to Ug99 in 141 lines of a PBW343/Muu recombinant inbred lines (RILs) population by phenotyping them for three seasons at Njoro, Kenya in field trials and genotyping them with Diversity Arrays Technology (DArT) markers. Moderately susceptible parent PBW343 and APR parent Muu displayed mean stem rust severities of 66.6 and 5 %, respectively. The mean disease severity of RILs ranged from 1 to 100 %, with an average of 23.3 %. Variance components for stem rust severity were highly significant (p < 0.001) for RILs and seasons and the heritability (h ²) for the disease ranged between 0.78 and 0.89. Quantitative trait loci (QTL) analysis identified four consistent genomic regions on chromosomes 2BS, 3BS, 5BL, and 7AS; three contributed by Muu (QSr.cim-2BS, QSr.cim-3BS and QSr.cim-7AS) and one (QSr.cim-5BL) derived from PBW343. RILs with flanking markers for these QTLs had significantly lower severities than those lacking the markers, and combinations of QTLs had an additive effect, significantly enhancing APR. The QTL identified on chromosome 3BS mapped to the matching region as the known APR gene Sr2. Four additional QTLs on chromosomes 1D, 3A, 4B, and 6A reduced disease severity significantly at least once in three seasons. Our results show a complex nature of APR to stem rust where Sr2 and other minor slow rusting resistance genes can confer a higher level of resistance when present together.     

Association analysis of seed longevity in rice under conventional and high-temperature germination conditions

Seed longevity varies considerably in cultivated rice, but the underlying mechanism of longevity is not well understood. To measure seed longevity, we performed an aging treatment at 45 °C on seeds maintained at 14 % moisture content for 14 days. We measured the percentage germination of both treated and normal seeds at 25 °C as a control of seed longevity using four replications over 2 years. In total, 140 accessions from a core collection with diverse origins were genotyped using 204 SSR markers, which distributed into 12 chromosomes, to identify marker–trait associations with seed longevity. An analysis of the population structure revealed four subgroups. The r ² values ranged from 0.0 to 0.8901 for all intrachromosomal loci pairs, with an average of 0.0773. Linkage disequilibrium (LD) between linked markers decreased with distance and displayed a substantial drop in LD decay values between 20 and 50 cM. Marker–trait associations were investigated using a mixed linear model approach, considering both population structure (Q) and kinship (K). Twelve marker–trait associations (P < 0.01) were common between the two germination treatments and over the 2-year study, explaining more than 10 % of the total variation. These ten different markers were distributed on five chromosomes. The significant associated SSR markers identified will be useful to seed-bank managers to ensure collections are maintained at high levels of viability to avoid loss of genotypes from the population and for marker-assisted selection.     

Association mapping for seed size and shape traits in soybean cultivars

Seed size and shape traits are closely related to seed yield and appearance quality in soybean (Glycine max L.). Previous studies were mainly derived from bi-parental segregating populations and relatively little is known about the results in soybean cultivars. In this study, 257 soybean cultivars obtained by stratified random sampling from six geographic ecotypes in China were used to carry out association mapping for these traits using information from 135 simple sequence repeat markers and an epistatic association mapping approach implemented using an empirical Bayes algorithm. In this analysis, seed size was measured by seed length (SL), width (SW) and thickness (ST), and seed shape was evaluated by seed length-to-width (SLW), length-to-thickness (SLT) and width-to-thickness (SWT) ratios, in 2008–2010. A total of 59 main-effect quantitative trait loci (QTL) and 31 QTL-by-environment interactions were identified. Among them, 25 QTL were associated simultaneously with at least two traits; 80 QTL (90 %) could be confirmed by enriched compression mixed linear model analysis; and the size for a large number of detected QTL was minor, except for qSL-5, qSW-7e, qST-5-2 and qSLW-2. According to the estimates for the allelic effects of the detected QTL, elite alleles could be mined: for example, the 307-bp allele of QTL linked to satt453 was the best for seed length. These elite alleles could be used to design parental combinations; e.g., the cross of Zhenghezhibanzi and Nannongdahuangdou might improve seed length, and the combination of cultivars Lindou10, Deqingxiangzhudou, Ninghaixiazhidou, Zhenghezhibanzi, 0803, Shangqiu7605 and 0831 might pyramid 42 elite alleles.     

Quantitative trait loci (QTL) mapping of blush skin and flowering time in a European pear (<Emphasis Type="Italic">Pyrus communis</Emphasis>) progeny of ‘Flamingo’ × ‘Abate Fetel’

Blush skin and flowering time are agronomic traits of interest to the Agricultural Research Council (ARC) Infruitec-Nietvoorbij pear breeding programme. The genetic control of these traits was investigated in the pear progeny derived from ‘Flamingo’ (blush cultivar) × ‘Abate Fetel’ (slightly blush) made up of 121 seedlings. Blush skin was scored phenotypically over three seasons and flowering time was scored over two seasons. A total of 160 loci from 137 simple sequence repeat (SSR) markers were scored in the progeny and used to construct parental genetic linkage maps. Quantitative trait loci (QTL) analysis revealed two QTLs for blush skin, a major QTL on linkage group (LG) 5 in ‘Flamingo’, and a major QTL on LG9 in ‘Abate Fetel’. Two SSR markers, NB101a and SAmsCO865954, were closely linked with the major QTL on LG5 in ‘Flamingo’, with alleles 139 bp and 462 bp in coupling, respectively. These markers were present in approximately 90% of the seedlings scored as good blush (class 4) based on the average data set. These two markers were used to genotype other pear accessions to validate the QTL on LG5 with the view of marker-assisted selection. Two candidate genes, MYB86 and UDP-glucosyl transferase, were associated with the QTL on LG5 and MYB21 and MYB39 were associated with the QTL on LG9. QTL analysis for flowering time revealed a major QTL located on LG9 in both parents. Marker GD142 with allele 161 bp from ‘Flamingo’ was present in approximately 88% of the seedlings that flowered earlier than either parent, based on the average data set. The QTLs and linked markers will facilitate marker-assisted selection for the improvement of these complex traits.     

Genetic mapping revealed two loci for soybean aphid resistance in PI 567301B

The soybean aphid (Aphis glycines Matsumura) is the most damaging insect pest of soybean [Glycine max (L.) Merr.] in North America. New soybean aphid biotypes have been evolving quickly and at least three confirmed biotypes have been reported in USA. These biotypes are capable of defeating most known aphid resistant soybean genes indicating the need for identification of new genes. Plant Introduction (PI) 567301B was earlier identified to have antixenosis resistance against biotype 1 and 2 of the soybean aphid. Two hundred and three F_7:9 recombinant inbred lines (RILs) developed from a cross of soybean aphid susceptible cultivar Wyandot and resistant PI 567301B were used for mapping aphid resistance genes using the quantitative trait loci (QTL) mapping approach. A subset of 94 RILs and 516 polymorphic SNP makers were used to construct a genome-wide molecular linkage map. Two candidate QTL regions for aphid resistance were identified on this linkage map. Fine mapping of the QTL regions was conducted with SSR markers using all 203 RILs. A major gene on chromosome 13 was mapped near the previously identified Rag2 gene. However, an earlier study revealed that the detached leaves of PI 567301B had no resistance against the soybean aphids while the detached leaves of PI 243540 (source of Rag2) maintained aphid resistance. These results and the earlier finding that PI 243540 showed antibiosis resistance and PI 567301B showed antixenosis type resistance, indicating that the aphid resistances in the two PIs are not controlled by the same gene. Thus, we have mapped a new gene near the Rag2 locus for soybean aphid resistance that should be useful in breeding for new aphid-resistant soybean cultivars. Molecular markers closely linked to this gene are available for marker-assisted breeding. Also, the minor locus found on chromosome 8 represents the first reported soybean aphid-resistant locus on this chromosome.