Identification of QTLs for resistance to anthracnose to two <Emphasis Type="Italic">Colletotrichum</Emphasis> species in pepper

Pepper (Capsicum spp.) anthracnose caused by Colletotrichum spp. is a serious disease damaging pepper production in Asian monsoon regions. For QTL mapping analyses of anthracnose resistance, an introgression BC₁F₂ population was made by interspecific crosses between Capsicum annuum ‘SP26’ (susceptible recurrent parent) and Capsicum baccatum ‘PBC81’ (resistant donor). Both green and red fruits were inoculated with C. acutatum ‘KSCa-1’ and C. capsici ‘ThSCc-1’ isolates and the disease reactions were evaluated by disease incidence, true lesion diameter, and overall lesion diameter. On the whole, distribution of anthracnose resistance was skewed toward the resistant parent. It might indicate that one or two major QTLs are present. The introgression map consisting of 13 linkage groups with a total of 218 markers (197 AFLP and 21 SSR), covering a total length of 325 cM was constructed. Composite interval mapping analysis revealed four QTLs for resistance to ‘KSCa-1’ and three QTLs for ‘ThSCc-1’ isolate, respectively. Interestingly, the major QTLs (CaR12.2 and CcR9) for resistance to C. acutatum and C. capsici, respectively, were differently positioned but there were close links between the minor QTL CcR12.2 for C. capsici and major QTL CaR12.2 as well as the minor QTL CaR9 for C. acutatum and major QTL CcR9. These results will be helpful for marker-assisted selection and pyramiding two different anthracnose-resistant genes in commercial pepper breeding.     

Construction of a genetic linkage map with SSR,AFLP and morphological markers to locate QTLs controlling pathotype-specific powdery mildew resistance in diploid roses

Disease resistance is a sought-after trait in plant breeding programmes. One strategy to make resistance more durable is to increase the number of resistance genes, thereby increasing the number of pathotypes withstood. One of the most important diseases on roses is powdery mildew (PM) (Podosphaera pannosa). Recent studies show that pathotypes of PM and different types of resistances in roses exist. The results of this study aim to contribute to PM resistance in roses by the development of pathotype-specific markers on a genetic map. A diploid rose population (90 genotypes) derived from a cross between Rosa wichurana and Rosa ‘Yesterday’ was used to construct a genetic linkage map encompassing 20 AFLP primer combinations, 43 SSR, and 2 morphological markers. By applying the F1 pseudo test cross population strategy, two parental linkage maps were constructed (parent ‘Yesterday’ 536 cM; parent R. wichurana 526 cM). Both parental maps consisted of seven linkage groups with an average length of 70 cM (Kosambi) corresponding to the seven haploid rose chromosomes. These new maps were used to identify QTLs controlling disease resistance. The offspring population was screened for resistance to two PM pathotypes, R–E and R–P. QTLs for controlling pathotype-specific disease resistance were mapped by applying Kruskal–Wallis rank-sum tests and simple interval mapping. With two pathotypes analysed, nine QTL loci were detected on linkage groups 2, 3, 5 and 6, explaining 15–73% of the phenotypic variance for pathotype-specific disease response. The genetic maps developed here will be useful for future rose breeding, pathotype-specific resistance research and development of a consensus map for roses.     

Identification of quantitative trait loci associated with resistance to foliar diseases in sorghum [<Emphasis Type="Italic">Sorghum bicolor</Emphasis> (L.) Moench]

Forage sorghum cultivars grown in India are susceptible to various foliar diseases, of which anthracnose, rust, zonate leaf spot, drechslera leaf blight and target leaf spot cause severe damage. We report here the quantitative trait loci (QTLs) conferring resistance to these foliar diseases. QTL analysis was undertaken using 168 F₇ recombinant inbred lines (RILs) of a cross between a female parental line 296B (resistant) and a germplasm accession IS18551 (susceptible). RILs and parents were evaluated in replicated field trials in two environments. A total of twelve QTLs for five foliar diseases on three sorghum linkage groups (SBI-03, SBI-04 and SBI-06) were detected, accounting for 6.9–44.9% phenotypic variance. The morphological marker Plant color (Plcor) was associated with most of the QTL across years and locations. The QTL information generated in this study will aid in the transfer of foliar disease resistance into elite susceptible sorghum breeding lines through marker-assisted selection.     

Mapping QTL tolerance to <Emphasis Type="Italic">Phytophthora</Emphasis> root rot in soybean using microsatellite and RAPD/SCAR derived markers

Broad tolerance to phytophthora root rot (PRR) caused by Phytophthora sojae has become an important goal for the improvement of soybean (Glycine max) because of the rapid spread of races that defeat the available resistance genes. The aim of this research was to identify the location of quantitative trait loci (QTL) in ‘Conrad’, a soybean cultivar with broad tolerance to many races of P. sojae. A PRR susceptible breeding line ‘OX760-6-1’was crossed with Conrad. Through single-seed-descent, 112, F₂ derived, F₇ recombinant inbred lines (RILs) were advanced. A total of 39 random amplified polymorphic DNA bands (RAPDs) and 89 type 1 microsatellite (simple sequence repeat; SSR) markers were used to construct a genetic linkage map. In the greenhouse, RILs were inoculated with four P. sojae isolates (three from China and one from Canada). Disease was measured as the percent of dead plants 20 days after germination in P. sojae inoculated vermiculite in the greenhouse. Three QTLs (QGP1, QGP2, QGP3) for PRR tolerance in the greenhouse were detected using WinQTLCart 2.0 with a log-likelihood (LOD) score 27.14 acquired through permutations (1,000 at P ≤ 0.05). QGP1 (near Satt509) was located at linkage group F and explained 13.2%, 5.9%, and 6.7% of the phenotypic variance for tolerance to the JiXi, JianSanJiang and ShuangYaShan isolates, respectively. QGP2 (near Satt334) was located in a different interval on linkage group F and explained 5.1% and 2.4% of the phenotypic variance for JiXi and ShuangYaShan isolates, respectively. QGP3 was located on linkage group D1b + W (near OPL18₈₀₀/SCL18₆₅₉) and explained 10.2% of the phenotypic variance for Woodslee isolate. QGP1 and QGP2 appeared to be associated with PRR tolerance across a range of isolates but QGP3 was active only against the Woodslee isolate. At Woodslee and Weaver (in Ontario) in 2000, the interval associated with QGP3 explained 21.6% and 16.7% of phenotypic variance in resistance to PRR, respectively and was referred as QFP1. The identified QTLs would be beneficial for marker assistant selection of PRR tolerance varieties against both China and North America P. sojae races. Yingpeng Han and Weili Teng have equal contribution to the paper.     

QTLs for Fusarium head blight response in a wheat DH population of Wangshuibai/Alondra‘s’

Summary A doubled haploid (DH) wheat population derived from the cross Wangshuibai/Alondra‘s’ was developed through chromosome doubling of haploids generated by anther culture of hybrids. Fusarium head blight (FHB) was evaluated for three years from 2001 to 2003 in Jianyang, Fujian Province, China, where epidemics of FHB have been consistently severe. After 307 pairs of simple sequence repeat (SSR) primers were screened, 110 pairs were polymorphic between Wangshuibai and Alondra`s’, and used to construct a genetic linkage map for detection of quantitative trait loci (QTLs). A stable QTL for low FHB severity was detected on chromosomes 3B over all three years, and QTLs on chromosomes 5B, 2D, and 7A were detected over two years. Additional QTLs on chromosomes 3A, 3D, 4B, 5A, 5D, 6B and 7B showed marginal significance in only one year. Six QTLs were detected when phenotypic data from three years were combined. In addition, significant additive-by-additive epistasis was detected for a QTL on 6A although its additive effect was not significant. Additive effects (A) and additive-by-additive epistasis (AA) explained a major portion of the phenotypic variation (76.5%) for FHB response. Xgwm533-3B and Xgwm335-5B were the closest markers to QTLs, and have potential to be used as selectable markers for marker-assisted selection (MAS) in wheat breeding programs.     

Identification of molecular markers associated with sugar-related traits in a <Emphasis Type="Italic">Saccharum</Emphasis> interspecific cross

The cultivated sugarcane (Saccharum spp. hybrids, 2n = 100–130) is one crop for which interspecific hybridization involving wild germplasm has provided a major breakthrough in its improvement. Few clones were used in the initial hybridization event leading to a narrow genetic base for continued cultivar development. Molecular breeding would facilitate the identification and introgression of novel alleles/genes from the wild germplasm into cultivated sugarcane. We report the identification of molecular markers associated with sugar-related traits using an F₁ population derived from a cross between S. officinarum ‘Louisiana Striped’ × S. spontaneum ‘SES 147B’, the two major progenitor species of cultivated sugarcane. Genetic linkage maps of the S. officinarum and S. spontaneum parents were produced using the AFLP, SRAP and TRAP molecular marker techniques. The mapping population was evaluated for sugar-related traits namely, Brix (B) and pol (P) at the early (E) and late (L) plant growing season in the plant cane (04) and first ratoon (05) crops (04EB, 04LB, 04LP, 05EB and 05EP). For S. officinarum, combined across all the traits, a total of 30 putative QTLs was observed with LOD scores ranging from 2.51 to 7.48. The phenotypic variation (adj. R²) explained by all QTLs per trait ranged from 22.1% (04LP) to 48.4% (04EB). For S. spontaneum, a total of 11 putative QTLs was observed with LOD scores ranging from 2.62 to 4.70 and adj. R² ranging from 9.3% (04LP) to 43.0% (04LB). Nine digenic interactions (iQTL) were observed in S. officinarum whereas only three were observed in S. spontaneum. About half of the QTLs contributed by both progenitor species were associated with effects on the trait that was contrary to expectations based on the phenotype of the parent contributing the allele. Quantitative trait loci and their associated effects were consistent across crop-years and growing seasons with very few QTLs being unique to the early season. When the data were reanalyzed using the non-parametric discriminant analysis (DA) approach, significant marker-trait associations were detected for markers that were either identical to or in the vicinity of markers previously identified using the traditional QTL approach. Discriminant analysis also pointed to previously unidentified markers some of which remained unlinked on the map. These preliminary results suggest that DA could be used as a complementary approach to traditional QTL analysis in a crop like sugarcane for which saturated linkage maps are unavailable or difficult to obtain.     

Quantitative trait loci for resistance to Fusarium head blight in recombinant inbred wheat lines from the cross Huapei 57-2 / Patterson

Fusarium head blight (FHB), primarily caused by Fusarium graminearum in North America, often results in significant losses in yield and grain quality of wheat (Triticum aestivum L.). Evaluation of FHB resistance is laborious and can be affected by environmental conditions. The development of DNA markers associated with FHB quantitative trait loci (QTL) and their use in breeding programs could greatly enhance selection. The objective of this study was to identify the location and effect of QTLs for FHB resistance using simple sequence repeat (SSR) markers. A population of wheat recombinant inbred lines derived from the cross ‘Huapei57-2’/‘Patterson’ was characterized for type II resistance in one field experiment and two tests under controlled conditions in the greenhouse. Bulked segregant analysis followed by QTL mapping was used to identify the major segregating QTLs. Results indicate that ‘Huapei 57-2’ may have the same resistance allele as ‘Sumai3’ at a QTL located on the short arm of chromosome 3B. Other QTLs of lower effect size were identified on the long arm of 3Band on chromosomes 3A and 5B. Our findings along with results from other studies demonstrate that the effect of the QTL on3BS is large and consistent across a wide range of genetic backgrounds and environments. Pyramiding this QTL with other FHB QTLs using marker-assisted selection should be effective in improving FHB resistance in a wheat breeding program. This revised version was published online in August 2006 with corrections to the Cover Date.     

Mapping and validation of QTLs for resistance to an Indian isolate of Ascochyta blight pathogen in chickpea

Ascochyta blight (AB) caused by Ascochyta rabiei, is globally the most important foliar disease that limits the productivity of chickpea (Cicer arietinum L.). An intraspecific linkage map of cultivated chickpea was constructed using an F₂ population derived from a cross between an AB susceptible parent ICC 4991 (Pb 7) and an AB resistant parent ICCV 04516. The resultant map consisted of 82 simple sequence repeat (SSR) markers and 2 expressed sequence tag (EST) markers covering 10 linkage groups, spanning a distance of 724.4 cM with an average marker density of 1 marker per 8.6 cM. Three quantitative trait loci (QTLs) were identified that contributed to resistance to an Indian isolate of AB, based on the seedling and adult plant reaction. QTL1 was mapped to LG3 linked to marker TR58 and explained 18.6% of the phenotypic variance (R ²) for AB resistance at the adult plant stage. QTL2 and QTL3 were both mapped to LG4 close to four SSR markers and accounted for 7.7% and 9.3%, respectively, of the total phenotypic variance for AB resistance at seedling stage. The SSR markers which flanked the AB QTLs were validated in a half-sib population derived from the same resistant parent ICCV 04516. Markers TA146 and TR20, linked to QTL2 were shown to be significantly associated with AB resistance at the seedling stage in this half-sib population. The markers linked to these QTLs can be utilized in marker-assisted breeding for AB resistance in chickpea.     

Molecular mapping of quantitative trait loci (QTLs) controlling aluminium tolerance in bread wheat

Aluminium (Al) toxicity is a major constraint to crop productivity in acidic soils. A quantitative trait locus (QTL) analysis was performed to identify the genetic basis of Al tolerance in the wheat cultivar ‘Chinese Spring’. A nutrient solution culture approach was undertaken with the root tolerance index (RTI) and hematoxylin staining method as parameters to assess the Al tolerance. Using a set of D genome introgression lines, a major Al tolerance QTL was located on chromosome arm 4DL, explaining 31% of the phenotypic variance present in the population. A doubled haploid population was used to map a second major Al tolerance QTL to chromosome arm 3BL. This major QTL (Qalt _CS .ipk-3B) in ‘Chinese Spring’ accounted for 49% of the phenotypic variation. Linkage of this latter QTL to SSR markers opens the possibility to apply marker-assisted selection (MAS) and pyramiding of this new QTL to improve the Al tolerance of wheat cultivars in breeding programmes.     

A quantitative trait locus influencing tolerance to Phytophthora root rot in the soybean cultivar ‘Conrad’

‘Conrad’, a soybean cultivar tolerant to Phytophthora root rot (PRR), and ‘OX760-6-1’, a breeding line with low tolerance to PRR, were crossed. F₂ derived recombinant inbred lines were advanced to F₆ to generate a population through single-seed descent. This population was used to identify quantitative trait loci (QTLs) influencing PRR tolerance in ‘Conrad’. A total of 99 simple sequence repeat (SSR), or microsatellite, markers that were polymorphic and clearly segregated in the F₆ mapping population were used for QTL detection. Based on the data of PRR in the field at two planting locations, Woodslee and Weaver, for the years 2000 and 2001, one putative QTL, designated as Qsatt414-596, was detected using MapMaker/QTL. Qsatt414-596 was flanked by two SSR markers from the linkage group MLG J, Satt414 and Satt596. Satt414 and Satt596 were also detected to be significantly (P < 0.005) associated with PRR using the SAS GLM procedure and were estimated to explain 13.7% and 21.5% of the total phenotypic variance, respectively.     

Molecular mapping of quantitative trait loci for domestication traits and β-glucan content in a wheat recombinant inbred line population

Genetic maps are useful for analysis of quantitative trait loci (QTLs) and for marker-assisted selection (MAS) in breeding. A simple sequence repeat (SSR) marker linkage map of common wheat was constructed based on recombination inbred lines (RILs) derived from a cross between Chinese Spring and spelt wheat. The map included 264 loci on all wheat chromosomes covering 2,345.2 cM with 962, 794.6, and 588.6 cM for the A, B, and D genomes, respectively. Using the RILs and the map, we detected 42 putative QTLs on 15 chromosomes for ear length, spikelet number, spike compactness, kernel length, kernel width, kernel height and β-glucan content. Each QTL explained 4–45% of the phenotypic variation. Five QTL cluster regions were detected on chromosomes 1A, 5AL, 2B, 2D, and 4D. The first QTLs for β-glucan content in wheat were identified on chromosomes 3A, 1B, 5B, and 6D.     

Population-specific QTLs and their different epistatic interactions for pod dehiscence in soybean [<Emphasis Type="Italic">Glycine max</Emphasis> (L.) Merr.]

Pod dehiscence (PD) prior to harvest results in serious yield loss in soybean. Two linkage maps with simple sequence repeat (SSR) markers were independently constructed using recombinant inbred lines (RILs) developed from Keunolkong (pod-dehiscent) × Sinpaldalkong (pod-indehiscent) and Keunolkong × Iksan 10 (pod-indehiscent). These soybean RIL populations were used to identify quantitative trait loci (QTLs) conditioning resistance to PD. While a single major QTL on linkage group (LG) J explained 46% of phenotypic variation in PD in the Keunolkong × Sinpaldalkong population with four minor QTLs, three minor QTLs were identified in the Keunolkong × Iksan 10 population. Although these two populations share the pod dehiscent parent, no common QTL has been identified. In addition, epistatic interactions among three marker loci partially explained phenotypic variation in PD in both populations. The result of this study indicates that different breeding strategies will be required for PD depending on genetic background.     

QTL mapping of net blotch resistance genes in a doubled-haploid population of six-rowed barley

Net blotch, caused by Pyrenophora teres f. teres, is a damaging foliar disease of barley worldwide. It is important to identify resistance germplasm and study their genetics. 'Chevron', a six-rowed barley used as a parent for the production of a doubled haploid (DH) population for mapping of Fusarium head blight (FHB) resistance, was also found to be resistant to net blotch. To map the resistance genes, the population was evaluated for resistance at the seedling stage in a greenhouse. The resistance data showed a two-peak distribution. Through linkage mapping, one resistance gene, tentatively called Rpt, was located on chromosome 6HS flanked by Xksua3b-Xwg719d, which was also detected by QTL mapping. This QTL explained 64% of the phenotypic variance for the resistance in this DH population. In addition, a minor QTL was found on chromosome 2HS defined by Xcdo786-Xabc156a. 'Chevron' and 'Stander' contributed the resistant alleles of Rpt and the 2HS QTL, respectively. Both QTLs together explained nearly 70% of the phenotypic variance. The markers for these QTLs are useful for marker-assisted selection of net blotch resistance in barley breeding.     

Mapping QTLs of traits contributing to yield and analysis of genetic effects in tetraploid cotton

Fiber yield and yield components – including lint index (LI), seed index (SI), lint yield (LY), seed cotton yield (SCY) and number of seeds per boll (NSPB) – were investigated on the farm of Huazhong Agricultural University in a population of 69 F₂ individuals and corresponding F_2:3 families derived from a cross between high-fiber-yield Gossypium hirsutum CV Handan 208 and a low-fiber-yield Gossypium barbadense CV Pima 90. On the basis of the genetic map constructed previously from the same population by Lin et al. (Plant Breed., 2005), quantitative trait locus (QTL) analysis was performed with the software QTL Cartographer V2.0 using composite interval mapping method (LOD ≥ 3.0). A total of 21 QTLs were identified, which were located in 15 linkage groups. The number of QTLs per trait ranged from one to seven. Of these QTLs detected, one affecting LI explained 24.3% of phenotypic variation (PV), five influencing SI explained 16.15–39.21% of PV, seven controlling LY explained 13.01–28.35% of PV, and two controlling SCY explained 22.76 and 39.97% of PV, respectively. Simultaneously, the detected six QTLs for NSPB were located on five linkage groups, which individually explained 28.01–38.32% of the total phenotypic variation. The results would give breeders further insight into the genetic basis of fiber yield.     

Identification of quantitative trait loci involved in resistance to <Emphasis Type="Italic">Pseudomonas syringae</Emphasis> pv. <Emphasis Type="Italic">syringae</Emphasis> in pea (<Emphasis Type="Italic">Pisum sativum</Emphasis> L.)

Pseudomonas syringae is the main pathogen responsible for bacterial blight disease in pea and can cause yield losses of 70%. P. syringae pv. pisi is prevalent in most countries but the importance of P. syringae pv. syringae (Psy) is increasing. Several sources of resistance to Psy have been identified but genetics of the resistance is unknown. In this study the inheritance of resistance to Psy was studied in the pea recombinant inbred line population P665 × ‘Messire’. Results suggest a polygenic control of the resistance and two quantitative trait loci (QTL) associated with resistance, Psy1 and Psy2, were identified. The QTL explained individually 22.2 and 8.6% of the phenotypic variation, respectively. In addition 21 SSR markers were included in the P665 × ‘Messire’ map, of which six had not been mapped on the pea genome in previous studies.     

QTL mapping and identification of corresponding genomic regions for black pod disease resistance to three <Emphasis Type="Italic">Phytophthora</Emphasis> species in <Emphasis Type="Italic">Theobroma cacao</Emphasis> L.

The cacao tree (Theobroma cacao L.) is a species of great importance because cacao beans are the raw material used in the production of chocolate. However, the economic success of cacao is largely limited by important diseases such as black pod, which is responsible for losses of up to 30–40% of the global cacao harvest. The discovery of resistance genes could extensively reduce these losses. Therefore, the aims of this study were to construct an integrated multipoint genetic map, align polymorphisms against the available cacao genome, and identify quantitative trait loci (QTLs) associated with resistance to black pod disease in cacao. The genetic map had a total length of 956.41 cM and included 186 simple sequence repeat (SSR) markers distributed among 10 linkage groups. The physical “in silico” map covered more than 200 Mb of the cacao genome. Based on the mixed model predicted means of Phytophthora evaluation, a total of 6 QTLs were detected for Phytophthora palmivora (1 QTL), Phytophthora citrophthora (1 QTL), and Phytophthora capsici (4 QTLs). Approximately 1.77–3.29% of the phenotypic variation could be explained by the mapped QTLs. Several SSR marker-flanking regions containing mapped QTLs were located in proximity to disease regions. The greatest number of resistance genes was detected in linkage group 6, which provides strong evidence for a QTL. This joint analysis involving multipoint and mixed-model approaches may provide a potentially promising technique for detecting genes resistant to black pod and could be very useful for future studies in cacao breeding.     

Quantitative analysis and QTL mapping for agronomic and fiber traits in an RI population of upland cotton

Genetic mapping is an essential tool for cotton (Gossypium hirsutum L.) molecular breeding and application of DNA markers for cotton improvement. In this present study, we evaluated an RI population including 188 RI lines developed from 94 F₂-derived families and their two parental lines, ‘HS 46’ and ‘MARCABUCAG8US-1-88’, at Mississippi State, MS, for two years. Fourteen agronomic and fiber traits were measured. One hundred forty one (141) polymorphic SSR markers were screened for this population and 125 markers were used to construct a linkage map. Twenty six linkage groups were constructed, covering 125 SSR loci and 965 cM of overall map distance. Twenty four linkage groups (115 SSR loci) were assigned to specific chromosomes. Quantitative genetic analysis showed that the genotypic effects accounted for more than 20% of the phenotypic variation for all traits except fiber perimeter (18%). Fifty six QTLs (LOD > 3.0) associated with 14 agronomic and fiber traits were located on 17 chromosomes. One QTL associated with fiber elongation was located on linkage group LGU01. Nine chromosomes in sub-A genome harbored 27 QTLs with 10 associated with agronomic traits and 17 with fiber traits. Eight chromosomes in D sub-genome harbored 29 QTLs with 13 associated with agronomic traits and 16 with fiber traits. Chromosomes 3, 5, 12, 13, 14, 16, 20, and 26 harbor important QTLs for both yield and fiber quality compared to other chromosomes. Since this RI population was developed from an intraspecific cross within upland cotton, these QTLs should be useful for marker assisted selection for improving breeding efficiency in cotton line development. Paper number J1116 of the Mississippi Agricultural and Forestry Experiment Station, Mississippi State University, Mississippi State, MS 39762. Mention of trademark, proprietary product, or vendor does not constitute a guarantee or warranty of the product by USDA, ARS and does not imply its approval to the exclusion of other products or vendors that may also be suitable.     

Mapping of a gene that confers short lateral branching (slb) in melon (Cucumis melo L.)

Plant architecture plays an important role in the yield, product quality, and cultivation practices of many crops. Branching pattern is one of the most important components in the plant architecture of melon (Cucumis melo L.). ‘Melon Chukanbohon Nou 4 Go’ (Nou-4) has a short-lateral-branching trait derived from a weedy melon, LB-1. This trait is reported to be controlled by a single recessive or incompletely dominant major gene called short lateral branching (slb). To find molecular markers for marker-assisted selection of this gene, we first constructed a linkage map using 94 F₂ plants derived from a cross between Nou-4 and ‘Earl’s Favourite (Harukei-3)’, a cultivar with normal branching. We then conducted quantitative trait locus (QTL) analysis and identified two loci for short lateral branching. A major QTL in linkage group (LG) XI, at which the Nou-4 allele is associated with short lateral branching, explained 50.9 % of the phenotypic variance, with a LOD score of 12.5. We suggest that this QTL corresponds to slb because of the magnitude of its effect. Another minor QTL in LG III, at which the Harukei-3 allele is associated with short lateral branching, explained 9.9 % of the phenotypic variance, with a LOD score of 4.2. Using an independent population, we demonstrated that an SSR marker linked to the QTL in LG XI (slb) could be used to select for short lateral branching. This is the first report of mapping a gene regulating the plant architecture of melon.     

Comparison and analysis of main effects,epistatic effects,and QTL × environment interactions of QTLs for agronomic traits using DH and RILs populations in rice

Two genetic linkage maps based on doubled haploid (DH) and recombinant inbred lines (RILs) populations, derived from the same indica-japonica cross ‘Samgang × Nagdong’, were constructed to analyze the quantitative trait loci (QTLs) affecting agronomic traits in rice. The segregations of agronomic traits in RILs population showed larger variations than those in DH population. A total of 10 and 12 QTLs were identified on six chromosomes using DH population and seven chromosomes using RILs population, respectively. Three stable QTLs including pl9.1, ph1.1, and gwp11.1 were detected through different years. The percentages of phenotypic variation explained by individual QTLs ranged from 8 to 18% in the DH population and 9 to 33% in the RILs population. Twenty-three epistatic QTLs were identified in the DH population, while 21 epistatic QTLs were detected in the RILs population. Epistatic interactions played an important role in controlling the agronomic traits genetically. Four significant main-effect QTLs were involved in the digenic interactions. Significant interactions between QTLs and environments (QE) were identified in two populations. The QTLs affecting grain weight per panicle (GWP) were more sensitive to the environmental changes. The comparison and QTLs analysis between two populations across different years should help rice breeders to comprehend the genetic mechanisms of quantitative traits and improve breeding programs in marker-assisted selection (MAS).     

Construction of a high-density SSR marker-based linkage map of zoysiagrass (<Emphasis Type="Italic">Zoysia japonica</Emphasis> Steud.)

A consensus genetic linkage map with 447 SSR markers was constructed for zoysiagrass (Zoysia japonica Steud.), using 86 F₁ individuals from the cross ‘Muroran 2’ × ‘Tawarayama Kita 1’. The consensus map identified 22 linkage groups and had a total length of 2,009.9 cM, with an average map density of 4.8 cM. When compared with a previous AFLP-SSR linkage map, the SSR markers from each linkage group mapped to similar positions in both maps. Eight pairs of linkage groups from the AFLP-SSR map were joined into eight new groups in the current map. This zoysiagrass consensus map contained 35 SSR markers exhibiting high homology with rice genomic sequences from known chromosomal locations. This allowed synteny to be identified between Zoysiagrass linkage groups 2, 3, 9, 19 and rice chromosomes 3, 12, 2, 7 respectively. These results provide important comparative genomics information and the new map is now available for quantitative trait locus analysis, marker-assisted selection and breeding for important traits in zoysiagrass.