Influence of dent corn genetic backgrounds on QTL detection for plant-height traits and their relationships in high-oil maize

QTL mapping for plant-height traits has not been hitherto reported in high-oil maize. A high-oil maize inbred ‘GY220’ was crossed with two dent maize inbreds (‘8984’ and ‘8622’) to generate two connected F_2:3 populations. Four plant-height traits were evaluated in 284 and 265 F_2:3 families. Single-trait QTL mapping and multiple-trait joint QTL mapping was used to detect QTLs for the traits and the genetic relationship between plant height (PH) and two other plant-height traits. A total of 28 QTLs and 12 pairs of digenic interactions among detected QTLs for four traits were detected in the two F_2:3 families. Only one marker was shared between the two populations. Joint analysis of PH with ear height (EH) and PH with top height (TH) detected 32 additional QTLs. Our results showed that QTL detection for PH was dependent on the genetic background of dent corn inbreds. Multiple-trait joint QTL analysis could increase the number of detected QTLs.     

Identification and stability of QTLs for fruit quality traits in apple

Breeding for fruit quality traits is complex due to the polygenic (quantitative) nature of the genetic control of these traits. Therefore, to improve the speed and efficiency of genotype selection, attention in recent years has focused on the identification of quantitative trait loci (QTLs) and molecular markers associated with these QTLs. However, despite the huge potential of molecular markers in breeding programmes, their implementation in practice has been limited by the lack of information on the stability of QTLs across different environments and within different genetic backgrounds. Here, we present the results from a comprehensive analysis of the inheritance of fruit quality traits within a population derived from a cross between the apple cultivars ‘Telamon’ and ‘Braeburn’ over two successive seasons. A total of 74 different QTLs were identified for all the major fruit physiological traits including fruit height, diameter, weight and stiffness, flesh firmness, rate of flesh browning, acidity, the oBrix content and harvest date. Seventeen of these QTLs were ‘major’ QTLs, accounting for over 20% of the observed population variance of the trait. However, only one third (26) of the identified QTLs were stable over both harvest years, and of these year-stable QTLs only one was a major QTL. A direct comparison with published QTL results obtained using other populations (King et al., Theor Appl Genet 102:1227–1235, 2001; Liebhard et al., Plant Mol Biol 52:511–526, 2003) is difficult because the linkage maps do not share a sufficient number of common markers and due to differences in the trait evaluation protocols. Nonetheless, our results suggest that for the six fruit quality traits which were measured in all populations, nine out of a total of 45 QTLs were common or stable across all population × environments combinations. These results are discussed in the framework of the development and application of molecular markers for fruit quality trait improvement.     

Identification and molecular mapping of loci controlling fruit ripening time in tomato

Using RAPD marker analysis, two quantitative trait loci (QTLs) associated with earliness due to reduced fruit-ripening time (days from anthesis to ripening = DTR) were identified and mapped in an F₂ population derived from a cross between Lycopersicon esculentum’E6203’ (normal ripening) and Lycopersicon esculentum’Early Cherry’ (early ripening). One QTL, on chromosome 5, was associated with a reduction in both ripening time (5 days) and fruit weight (29.3%) and explained 15.8 and 13% of the total phenotypic variation for DTR and fruit weight, respectively. The other QTL, on chromosome 12, was primarily associated with a reduction only in ripening time (7 days) and explained 12.3% of the total phenotypic variation for DTR. The gene action at this QTL was found to be partially dominant (d/a=0.41). Together, these two QTLs explained 25.1% of the total phenotypic variation for DTR. Additionally, two QTLs associated with fruit weight were identified in the same F₂ population and mapped to chromosomes 4 and 6, respectively. Together, these two QTLs explained 30.9% of the total phenotypc variation for fruit weight. For all QTLs, the ’Early Cherry’ alleles caused reductions in both ripening time and fruit weight. The polymorphic band for the most significant RAPD marker (OPAB-06), linked to the reduced ripening time QTL on chromosome 12, was converted to a cleaved amplified polymorphism (CAP) assay for marker-aided selection and further introgression of early ripening time (DTR) into cultivated tomato. Received: 15 March 1999 / Accepted: 29 April 1999     

Quantitative trait loci and underlying candidate genes controlling agronomical and fruit quality traits in octoploid strawberry <Emphasis Type="Italic">(Fragaria</Emphasis> × <Emphasis Type="Italic">ananassa</Emphasis>)

Breeding for fruit quality traits in strawberry (Fragaria × ananassa, 2n = 8x = 56) is complex due to the polygenic nature of these traits and the octoploid constitution of this species. In order to improve the efficiency of genotype selection, the identification of quantitative trait loci (QTL) and associated molecular markers will constitute a valuable tool for breeding programs. However, the implementation of these markers in breeding programs depends upon the complexity and stability of QTLs across different environments. In this work, the genetic control of 17 agronomical and fruit quality traits was investigated in strawberry using a F₁ population derived from an intraspecific cross between two contrasting selection lines, ‘232’ and ‘1392’. QTL analyses were performed over three successive years based on the separate parental linkage maps and a pseudo-testcross strategy. The integrated strawberry genetic map consists of 338 molecular markers covering 37 linkage groups, thus exceeding the 28 chromosomes. 33 QTLs were identified for 14 of the 17 studied traits and approximately 37% of them were stable over time. For each trait, 1–5 QTLs were identified with individual effects ranging between 9.2 and 30.5% of the phenotypic variation, indicating that all analysed traits are complex and quantitatively inherited. Many QTLs controlling correlated traits were co-located in homoeology group V, indicating linkage or pleiotropic effects of loci. Candidate genes for several QTLs controlling yield, anthocyanins, firmness and l-ascorbic acid are proposed based on both their co-localization and predicted function. We also report conserved QTLs among strawberry and other Rosaceae based on their syntenic location.     

Genetic basis and mapping of the resistance to rice yellow mottle virus. II. Evidence of a complementary epistasis between two QTLs

 The genetic basis of resistance to rice yellow mottle virus (RYMV) was studied in a doubled-haploid (DH) population derived from a cross between the very susceptible indica variety ‘IR64’ and the resistant upland japonica variety Azucena. As a quantitative trait locus (QTL) involved in virus content estimated with an ELISA test has been previously identified on chromosome 12, we performed a wide search for interactions between this QTL and the rest of the genome, and between this QTL and morphological traits segregating in the population. Multiple regression with all identified genetic factors was used to validate the interactions. Significant epistasis accounting for a major part of the total genetic variation was observed. A complementary epistasis between the QTL located on chromosome 12 and a QTL located on chromosome 7 could be the major genetic factor controlling the virus content. Resistance was also affected by a morphology-dependent mechanism since tillering was interfering with the resistance mechanism conditioned by the epistasis between the two QTLs. Marker-assisted backcross breeding was developed to introgress the QTLs of chromosome 7 and chromosome 12 in the susceptible ‘IR64’ genetic background. First results confirmed that if both QTLs do not segregate in a backcross-derived F₂ population, then the QTL of chromosome 12 cannot explain differences in virus content. A near-isogenic line (NIL) approach is currently being developed to confirm the proposed genetic model of resistance to RYMV. Received: 20 April 1990 / Accepted: 30 April 1998     

Identification and linkage mapping of complementary recessive genes causing hybrid breakdown in an intraspecific rice cross

One outcome of hybrid breakdown is poor growth, which we observed as a reduction in the number of panicles per plant and in culm length in an F₂ population derived from a cross between the genetically divergent rice (Oryza sativa L.) cultivars ‘Sasanishiki’ (japonica) and ‘Habataki’ (indica). Quantitative trait locus (QTL) analysis of the two traits and two-way ANOVA of the detected QTLs suggested that the poor growth was due mainly to an epistatic interaction between genes at QTLs located on chromosomes 2 and 11. The poor growth was likely to result when a plant was homozygous for the ‘Habataki’ allele at the QTL on chromosome 2 and homozygous for the ‘Sasanishiki’ allele at the QTL on chromosome 11. The results suggest that the poor growth found in the F₂ population was due to hybrid breakdown of a set of complementary genes. To test this hypothesis and determine the precise chromosomal location of the genes causing the hybrid breakdown, we performed genetic analyses using a chromosome segment substitution line, in which a part of chromosome 2 from ‘Habataki’ was substituted into the genetic background of ‘Sasanishiki’. The segregation patterns of poor growth in plants suggested that both of the genes underlying the hybrid breakdown were recessive. The gene on chromosome 2, designated hybrid breakdown 2 (hbd2), was mapped between simple sequence repeat markers RM3515 and RM3730. The gene on chromosome 11, hbd3, was mapped between RM5824 and RM1341. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Quantitative trait loci for resistance to spot blotch caused by Bipolarissorokiniana in wheat (T.aestivum L.) lines ‘Ning 8201’ and ‘Chirya 3’

Spot blotch caused by Bipolaris sorokiniana is a destructive disease of wheat in warm and humid wheat growing regions of the world. To identify quantitative trait loci (QTLs) for spot blotch resistance, two mapping populations were developed by making the crosses between common susceptible cultivar ‘Sonalika’ with the resistant breeding lines ‘Ning 8201’ and ‘Chirya 3’. Single seed descent derived F₆, F₇, F₈ lines of the first cross ‘Ning 8201’ × ‘Sonalika’ were evaluated for resistance to spot blotch in three blocks in each of the 3 years. After screening of 388 pairs of simple sequence repeat primers between the two parents, 119 polymorphic markers were used to genotype the mapping population. Four QTLs were identified on the chromosomes 2AS, 2BS, 5BL and 7DS and explained 62.9% of phenotypic variation in a simultaneous fit. The QTL on chromosome 2A was detected only in 1 year and explained 22.7% of phenotypic variation. In the second cross (‘Chirya 3’ × ‘Sonalika’), F₇ and F₈ population were evaluated in three blocks in each of the 2 years. In this population, five QTLs were identified on chromosomes 2BS, 2DS, 3BS, 7BS and 7DS. The QTLs identified in the ‘Chirya 3’ × ‘Sonalika’ population explained 43.4% of phenotypic variation in a simultaneous fit. The alleles for reduced disease severity in both the populations were derived from the respective resistant parent. The QTLs QSb.bhu-2B and QSb.bhu-7D from both populations were placed in the same deletion bins, 2BS1-0.53-0.75 and 7DS5-0.36-0.61, respectively. The closely linked markers Xgwm148 to the QTL on chromosome 2B and Xgwm111 to the QTL on chromosome 7D are potentially diagnostic markers for spot blotch resistance.     

Detection and verification of malting quality QTLs using wild barley introgression lines

A malting quality quantitative trait locus (QTL) study was conducted using a set of 39 wild barley introgression lines (hereafter abbreviated with S42ILs). Each S42IL harbors a single marker-defined chromosomal segment from the wild barley accession ‘ISR 42-8’ (Hordeum vulgare ssp. spontaneum) within the genetic background of the elite spring barley cultivar ‘Scarlett’ (Hordeum vulgare ssp. vulgare). The aim of the study was (1) to verify genetic effects previously identified in the advanced backcross population S42, (2) to detect new QTLs, and (3) to identify S42ILs exhibiting multiple QTL effects. For this, grain samples from field tests in three different environments were subjected to micro malting. Subsequently, a line × phenotype association study was performed with the S42ILs in order to localize putative QTL effects. A QTL was accepted if the trait value of a particular S42IL was significantly (P < 0.05) different from the recurrent parent as a control, either across all tested environments or in a particular environment. For eight malting quality traits, altogether 40 QTLs were localized, among which 35 QTLs (87.5%) were stable across all environments. Six QTLs (15.0%) revealed a trait improving wild barley effect. Out of 36 QTLs detected in a previous advanced backcross QTL study with the parent BC₂DH population S42, 18 QTLs (50.0%) could be verified with the S42IL set. For the quality parameters α-amylase activity and Hartong 45°C, all QTLs assessed in population S42 were verified by S42ILs. In addition, eight new QTL effects and 17 QTLs affecting two newly investigated traits were localized. Two QTL clusters harboring simultaneous effects on eight and six traits, respectively, were mapped to chromosomes 1H and 4H. In future, fine-mapping of these QTL regions will be conducted in order to shed further light on the genetic basis of the most interesting QTLs.     

Genetic Relationships Among Panicle Characteristics of Rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) Using Unconditional and Conditional QTL Analyses

Using mixed-model-based composite interval mapping and conditional statistical methods, we studied quantitative trait loci (QTLs) with epistatic effects and QTLs by environment interaction effects for rice seed set percent (SSP), filled grain number per plant (FGP), and panicle length (PL). A population of 241 recombinant inbred lines was used which was derived from a cross between “Zhenshan 97” and “Minghui 63.” Its linkage map included 221 molecular markers. Our QTL analysis detected 28, 25, and 32 QTLs for SSP, FGP, and PL, respectively. Each QTL explained 1.37%∼13.19% of the mean phenotypic variation. A comparison of conventional and conditional mapping provided information about the genetic control system involved in the synthetic process of SSP, FGP, and PL at the level of individual QTLs. Conditional QTLs with reduced (or increased) effects were identified for SSP, which were significantly influenced by FGP or PL. Some QTLs could express independently for the given traits, thereby providing possibilities for simultaneous improvement of SSR and PL, and SSR and FGP. Epistasis was more sensitive to environmental conditions than were additive effects.     

QTL mapping of yield, agronomic and quality traits in tetraploid potato (Solanum tuberosum subsp. tuberosum)

Interval mapping of quantitative trait loci (QTL) for 16 yield, agronomic and quality traits in potato was performed on a tetraploid full-sib family comprising 227 clones from a cross between processing clone 12601ab1 and table cultivar Stirling. Thirty-eight AFLP primer combinations and six SSRs provided 514 informative markers which formed a molecular marker map comprising 12 linkage groups (LGs) in 12601ab1 (nine with four homologous chromosomes) which were aligned with 12 in Stirling (11 with four homologous chromosomes), with four partial groups remaining in 12601ab1. Two LGs were identified unequivocally as chromosomes IV and V and eight others were tentatively assigned with chromosomes VII and X unidentified. All of the traits scored had moderately high heritabilities with 54–92% of the variation in clone means over 3 years and two replicates being due to genetic differences. A total of 39 QTLs were identified. A QTL for maturity was identified on chromosome V which explained 56% of the phenotypic variance, whereas the other QTLs individually explained between 5.4 and 16.5%. However, six QTLs were detected for after-cooking blackening and four for each of regularity of tuber shape, fry colour both after storage at 4 and 10°C and sprouting. Just two QTLs were found for each of yield, the two ‘overall’ scores, crop emergence, tuber size and common scab and just one QTL was detected for each of dry matter content, keeping quality, growth cracks and internal condition. The implications for practical potato breeding and for practical linkage and QTL analysis in autotetraploids are discussed.     

QTL mapping of aroma compounds analysed by headspace solid-phase microextraction gas chromatography in the apple progeny ‘Discovery’ × ‘Prima’

Improving fruit quality of apple varieties is an important but complex breeding goal. Flavour is among the key factors of apple fruit quality but in spite of the analytical and biochemical knowledge about volatiles little is known about the genetic and molecular bases of apple aroma. The aim of this study was to use a saturated molecular linkage map of apple to identify QTLs for aroma compounds such as alcohols, esters and terpenes, but also for a number of unidentified volatile compounds (non-targeted analysis approach). Two parental genetic maps were constructed for the apple cultivars ‘Discovery’ and ‘Prima’ by using mainly AFLP and SSR markers. ‘Discovery’ and ‘Prima’ showed very different volatile patterns, and ‘Discovery’ mostly had the higher volatile concentrations in comparison with the Vf-scab resistant ‘Prima’ which has its origin in the small-fruited apple species Malus floribunda. About 50 putative QTLs for a total of 27 different apple fruit volatiles were detected through interval mapping by using genotypic data of 150 F₁ individuals of the mapping population ‘C3’ together with phenotypic data obtained by head-space solid phase microextraction gas chromatography. QTLs for volatile compounds putatively involved in apple aroma were found on 12 out of the 17 apple chromosomes, but they were not evenly dispersed. QTLs were mainly clustered on linkage groups LG 2, 3 and 9. In a first attempt, a LOX (lipoxygenase) candidate gene, putatively involved in volatile metabolism, was mapped on LG 9, genetically associated with a cluster of QTLs for ester-type volatiles. Implications for aroma breeding in apple are discussed.     

Mapping of yield-related QTLs in pepper in an interspecific cross of <Emphasis Type="Italic">Capsicum annuum</Emphasis> and <Emphasis Type="Italic">C. frutescens</Emphasis>

An advanced backcross QTL study was performed in pepper using a cross between the cultivated species Capsicum annuum cv. Maor and the wild C. frutescens BG 2816 accession. A genetic map from this cross was constructed, based on 248 BC(2) plants and 92 restriction fragment length polymorphism (RFLP) markers distributed throughout the genome. Ten yield-related traits were analyzed in the BC(2) and BC(2)S(1) generations, and a total of 58 quantitative trait loci (QTLs) were detected; the number of QTLs per trait ranged from two to ten. Most of the QTLs were found in 11 clusters, in which similar QTL positions were identified for multiple traits. Unlike the high percentage of favorable QTL alleles discovered in wild species of tomato and rice, only a few such QTL alleles were detected in BG 2816. For six QTLs (10%), alleles with effects opposite to those expected from the phenotype were detected in the wild species. The use of common RFLP markers in the pepper and tomato maps enabled possible orthologous QTLs in the two species to be determined. The degree of putative QTL orthology for the two main fruit morphology traits-weight and shape-varied considerably. While all eight QTLs identified for fruit weight in this study could be orthologous to tomato fruit weight QTLs, only one out of six fruit shape QTLs found in this study could be orthologous to tomato fruit shape QTLs.     

Identification of QTL for increased fibrous roots in soybean

Drought stress adversely affects soybean at various developmental stages, which collectively results in yield reduction. Unpredictable rainfall has been reported to contribute about 36% to variation of yield difference between the rain-fed and irrigated fields. Among the drought resistance mechanisms, drought avoidance in genotypes with fibrous roots was recognized to be associated with drought resistance in soybean. Plant introduction PI416937 was shown to possess fibrous roots and has been used as a parent in breeding programs to improve soybean productivity. Little information is available on relative contribution and chromosomal location of quantitative trait loci (QTL) conditioning fibrous roots in soybean. To identify the genomic locations and genetic bases of this trait, a recombinant inbred line population was derived from a cross between PI416937 and ‘Benning’. To detect associated QTLs, phenotypic data were collected and analyzed for 2 years under rain-fed field conditions. The selective genotyping approach was used to reduce the costs and work associated with conducting the QTL analysis. A total of five QTLs were identified on chromosomes Gm01 (Satt383), Gm03 (Satt339), Gm04 (Sct_191), Gm08 (Satt429), and Gm20 (Sat_299), and together explained 51% of the variation in root score. Detected QTLs were co-localized with QTLs related to root morphology, suggesting that fibrous roots QTL may be associated with other morpho-physiological traits and seed yield in soybean. Genetic dissection of the fibrous roots trait at the individual marker loci will allow for marker-assisted selection to develop soybean genotypes with enhanced levels of fibrous roots.     

Accumulation of additive effects generates a strong photoperiod sensitivity in the extremely late-heading rice cultivar ‘Nona Bokra’

Many rice cultivars that originated from lower-latitude regions exhibit a strong photoperiod sensitivity (PS) and show extremely late heading under long-day conditions. Under natural day-length conditions during the cropping season in Japan, the indica rice cultivar ‘Nona Bokra’ from India showed extremely late heading (202 days to heading) compared to the japonica cultivar ‘Koshihikari’ (105 days), from Japan. To elucidate the genetic factors associated with such extremely late heading, we performed quantitative trait locus (QTL) analyses of heading date using an F₂ population and seven advanced backcross progeny (one BC₁F₂ and six BC₂F₂) derived from a cross between ‘Nona Bokra’ and ‘Koshihikari’. The analyses revealed 12 QTLs on seven chromosomes. The ‘Nona Bokra’ alleles of all QTLs contributed to an increase in heading date. Digenic interactions were rarely observed between QTLs. Based on the genetic parameters of the QTLs, such as additive effects and percentage of phenotypic variance explained, these 12 QTLs are likely generate a large proportion of the phenotypic variation observed in the heading dates between ‘Nona Bokra’ and ‘Koshihikari’. Comparison of chromosomal locations between heading date QTLs detected in this study and QTLs previously identified in ‘Nipponbare’ × ‘Kasalath’ populations revealed that eight of the heading date QTLs were recognized nearby the Hd1, Hd2, Hd3a, Hd4, Hd5, Hd6, Hd9, and Hd13. These results suggest that the strong PS in ‘Nona Bokra’ was generated mainly by the accumulation of additive effects of particular alleles at previously identified QTLs.     

Genetic dissection of fruit quality traits in the octoploid cultivated strawberry highlights the role of homoeo-QTL in their control

Fruit quality traits are major breeding targets in the Rosaceae. Several of the major Rosaceae species are current or ancient polyploids. To dissect the inheritance of fruit quality traits in polyploid fleshy fruit species, we used a cultivated strawberry segregating population comprising a 213 full-sibling F1 progeny from a cross between the variety ‘Capitola’ and the genotype ‘CF1116’. We previously developed the most comprehensive strawberry linkage map, which displays seven homoeology groups (HG), including each four homoeology linkage groups (Genetics 179:2045–2060, 2008). The map was used to identify quantitative trait loci (QTL) for 19 fruit traits related to fruit development, texture, colour, anthocyanin, sugar and organic acid contents. Analyses were carried out over two or three successive years on field-grown plants. QTL were detected for all the analysed traits. Because strawberry is an octopolyploid species, QTL controlling a given trait and located at orthologous positions on different homoeologous linkage groups within one HG are considered as homoeo-QTL. We found that, for various traits, about one-fourth of QTL were putative homoeo-QTL and were localised on two linkage groups. Several homoeo-QTL could be detected the same year, suggesting that several copies of the gene underlying the QTL are functional. The detection of some other homoeo-QTL was year-dependent. Therefore, changes in allelic expression could take place in response to environmental changes. We believe that, in strawberry as in other polyploid fruit species, the mechanisms unravelled in the present study may play a crucial role in the variations of fruit quality.     

Molecular-marker analysis of quantitative traits for growth and development in juvenile apple trees

Random amplified polymorphic DNAs (RAPDs) were used in combination with a double pseudo-testcross mapping strategy to estimate the position and effects of quantitative trait loci (QTLs) for traits influencing juvenile tree growth and development in two apple cultivars. The mapping population consisted of 172 F₁ trees from a cross between the columnar mutant ‘Wijcik McIntosh’ and a standard form disease-resistant selection NY 75441-58. Significant associations were found between markers and height increment, internode number, internode length, base diameter increment, base diameter after 9 years of growth, branch number, and leaf break. The number of genomic regions associated with each trait varied from one to eight. The amount of variation explained by linear regression on individual marker loci (R²) ranged from 3.9 to 24.3%, with an average of 7%. Multiple regression using markers for each putative QTL explained from 6.6 to 41.6% of the phenotypic variation, with an average value of 24.3%. A large number of traits had significant variation associated with the map position of the dominant columnar gene, Co. QTL stability over years was estimated by comparing the locations of putative QTLs for traits measured in multiple years. The majority of genomic regions were associated with a trait in only a single year, although regions associated with a trait in more than 1 year were also detected. The limitations of dominant markers and an outbred mapping pedigree for QTL analysis are discussed. Received: 27 August 1997 / Accepted: 10 February 1998     

QTL mapping of fruit-related traits in pepper (Capsicum annuum)

QTL analysis of pepper fruit characters was performed in an F₃ population derived from a cross between two Capsicum annuum genotypes, the bell-type cultivar Maor and the Indian small-fruited line Perennial. RFLP, AFLP^®1, RAPD and morphological markers (a total of 177) were used to construct a comparative pepper-tomato genetic map for this cross, and 14 quantitatively inherited traits were evaluated in 180 F₃ families. A total of 55 QTL were identified by interval analysis using LOD 3.0 as the threshold for QTL detection. QTL for several traits including fruit diameter and weight, pericarp thickness and pedicel diameter were often located in similar chromosomal regions, thus reflecting high genetic correlations among these traits. A major QTL that accounts for more than 60% of the phenotypic variation for fruit shape (ratio of fruit length to fruit diameter) was detected in chromosome 3. This chromosome also contained QTL for most of the traits scored in the population. Markers in linkage groups 2, 3, 8 and 10 were associated with QTL for multiple traits, thereby suggesting their importance as loci that control developmental processes in pepper. Several QTL in pepper appeared to correspond to positions in tomato for loci controlling the same traits, suggesting the hypothesis that these QTL may be orthologous in the two species.     

Identification of molecular markers linked to quantitative trait loci for soybean resistance to corn earworm

 One hundred and thirty nine restriction fragment length polymorphisms (RFLPs) were used to construct a soybean (Glycine max L. Merr.) genetic linkage map and to identify quantitative trait loci (QTLs) associated with resistance to corn earworm (Helicoverpa zea Boddie) in a population of 103 F₂-derived lines from a cross of ‘Cobb’ (susceptible) and PI229358 (resistant). The genetic linkage map consisted of 128 markers which converged onto 30 linkage groups covering approximately 1325 cM. There were 11 unlinked markers. The F₂-derived lines and the two parents were grown in the field under a plastic mesh cage near Athens, Ga., in 1995. The plants were artificially infested with corn earworm and evaluated for the amount of defoliation. Using interval-mapping analysis for linked markers and single-factor analysis of variance (ANOVA), markers were tested for an association with resistance. One major and two minor QTLs for resistance were identified in this population. The PI229358 allele contributed insect resistance at all three QTLs. The major QTL is linked to the RFLP marker A584 on linkage group (LG) ‘M’ of the USDA/Iowa State University public soybean genetic map. It accounts for 37% of the total variation for resistance in this cross. The minor QTLs are linked to the RFLP markers R249 (LG ‘H’) and Bng047 (LG ‘D1’). These markers explain 16% and 10% of variation, respectively. The heritability (h²) for resistance was estimated as 64% in this population. Received: 15 October 1997 / Accepted: 4 November 1997     

QTLs mapping for fruit size and shape in chromosomes 2 and 4 in pepper and a comparison of the pepper QTL map with that of tomato

Quantitative trait locus (QTL) mapping for fruit weight and shape in pepper (Capsicum spp.) was performed using C. chinense and C. frutescens introgression lines of chromosomes 2 and 4. In chromosome 2, a single major fruit-weight QTL, fw2.1, was detected in both populations that explained 62% of the trait variation. This QTL, as well as a fruit-shape QTL, fs2.1, which had a more minor effect, were localized to the tomato fruit-shape gene ovate. The cloned tomato fruit-weight QTL, fw2.2, did not play a major role in controlling fruit size variations in pepper. In chromosome 4, two fruit-weight QTLs, fw4.1 and fw4.2, were detected in the same genomic regions in both mapping populations. In addition, a single fruit-shape QTL was detected in each of the mapping populations that co-localized with one of the fruit-weight QTLs, suggesting pleiotropy or close linkage of the genes controlling size and shape. fw2.1 and fw4.2 represent major fruit-weight QTLs that are conserved in the three Capsicum species analyzed to date for fruit-size variations. Co-localization of the pepper QTLs with QTLs identified for similar traits in tomato suggests that the pepper and tomato QTLs are orthologous. Compared to fruit-shape QTLs, fruit-weight QTLs were more often conserved between pepper and tomato. This implies that different modes of selection were employed for these traits during domestication of the two Solanaceae species.S. Zygier and A. Ben Chaim contributed equally to this work.     

Identification of a new QTL for <Emphasis Type="Italic">Fusarium</Emphasis> head blight resistance in the wheat genotype “Wang shui-bai”

Fusarium head blight (FHB) is one of the most devastating wheat diseases, causing both yield loss and quality reduction. To detect quantitative trait loci (QTL) responsible for FHB resistance, plants of the F _2:3 population derived from a ‘Wangshui-bai’ × ‘Sy95-7’ cross were artificially inoculated. Of 396 simple sequence repeats (SSRs), 125 amplified fragment length polymorphisms were used for FHB resistance QTL analysis. Five QTLs for FHB resistance were detected on chromosomes 3B, 6B, 7A, 1B and 2D. The effect of the QTL located on chromosome 3B on phenotypic variation was 31.69%, while that of the QTL found on 2D was the smallest and only accounted for 4.98% of the variation. The resistance alleles originated from ‘Wangshibai’ and association of the QTLs using these SSR markers may facilitate marker-assisted selection to improve FHB resistance in the wheat breeding programs of southwest China.