Detection and stability of quantitative trait loci (QTL) in Eucalyptus globulus

Eucalyptus globulus Labill. ssp. globulus is an important tree species for the pulp and paper industry, and several breeding programmes throughout the world are striving to improve key traits such as growth and wood density. This study aimed to detect quantitative trait loci (QTL) for growth, wood density, relative bark thickness and early flowering in a single full-sib E. globulus family grown across seven sites. Growth was measured a number of times over a 6-year period, enabling temporal stability of growth QTL to be studied. Ten putative QTL (LOD > 2.0) were detected in the single family, which was of moderate size. Based on permutations of the trait data, six of these QTL were significant at the experimentwise significance level of 0.1 for at least one of the four models implemented in analysis to remove site effects. For wood density, two putative QTL explained 20% of the variance for the trait, indicating that a small number of QTL might explain a reasonable proportion of the trait variance. One of these QTL was found to be independent of QTL for growth whereas the second QTL co-segregated with a QTL for relative incremental growth. The marker nearest to this QTL was associated with fast growth but low wood density. A putative growth QTL at year 6 was found to be relatively stable across ages. In addition, it was found that residuals from models based on measurements from across all families across all sites in the trial detected QTL with greater experimentwise significance.     

Fine structure mapping of the barley chromosome-1 centromere region containing malting-quality QTLs

 Current techniques for quantitative trait locus (QTLs) analyses provide only approximate locations of QTLs on chromosomes. Further resolution of identified QTL regions is often required for detailed characterization. An important region containing malting-quality QTLs on barley (Hordeum vulgare L.) chromosome 1 was identified by previous QTL analyses in a Steptoe×Morex cross. This region contains two putative adjacent overlapping QTLs, each of which has effects on malt-extract percentage, α-amylase activity, diastatic power, and malt β-glucan content. All favorable alleles for these traits are attributed to Morex. The objective of the present study was fine structure mapping of this complex QTL region to elucidate whether these two putative overlapping QTLs are really one QTL. Another question was whether the apparently overlapping QTLs are due to the pleiotropic effects of a single gene, or the independent effects of several genes. A high-resolution map in the target region was developed which spans approximately 27 cM. Molecular-marker-assisted backcrossing was employed to create isogenic lines with a Steptoe background differing only in the region containing the QTLs of interest. A total of 32 different recombinants were identified, of which eight most-informative isogenic lines plus one reconstructed Steptoe control were selected for field testing. The additive effects on malt-extract percentage, α-amylase activity, diastatic power, and malt β-glucan content from eight isogenic lines were calculated based on malting data from three locations. By comparing the significant additive effects among isogenic lines carrying different Morex fragments, two QTLs each for malt extract and for α-amylase, and two to three for diastatic power were identified in certain environments and resolved into 1–8-cM genome fragments. There was a significant QTL×environment interaction for diastatic power, and there are indications that epistatic interactions for malt β-glucan content occur between the QTLs on chromosome 1 and QTLs on other chromosomes. Received : 4 June 1997 / Accepted : 19 June 1997     

Fine Mapping QTL for Drought Resistance Traits in Rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) Using Bulk Segregant Analysis

Drought stress is a major limitation to rice (Oryza sativa L.) yields and its stability, especially in rainfed conditions. Developing rice cultivars with inherent capacity to withstand drought stress would improve rainfed rice production. Mapping quantitative trait loci (QTLs) linked to drought resistance traits will help to develop rice cultivars suitable for water-limited environments through molecular marker-assisted selection (MAS) strategy. However, QTL mapping is usually carried out by genotyping large number of progenies, which is labour-intensive, time-consuming and cost-ineffective. Bulk segregant analysis (BSA) serves as an affordable strategy for mapping large effect QTLs by genotyping only the extreme phenotypes instead of the entire mapping population. We have previously mapped a QTL linked to leaf rolling and leaf drying in recombinant inbred (RI) lines derived from two locally adapted indica rice ecotypes viz., IR20/Nootripathu using BSA. Fine mapping the QTL will facilitate its application in MAS. BSA was done by bulking DNA of 10 drought-resistant and 12 drought-sensitive RI lines. Out of 343 rice microsatellites markers genotyped, RM8085 co-segregated among the RI lines constituting the respective bulks. RM8085 was mapped in the middle of the QTL region on chromosome 1 previously identified in these RI lines thus reducing the QTL interval from 7.9 to 3.8 cM. Further, the study showed that the region, RM212–RM302–RM8085–RM3825 on chromosome 1, harbours large effect QTLs for drought-resistance traits across several genetic backgrounds in rice. Thus, the QTL may be useful for drought resistance improvement in rice through MAS and map-based cloning.     

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.     

Shaping melons: agronomic and genetic characterization of QTLs that modify melon fruit morphology

The consistency of quantitative trait locus (QTL) effects among genetic backgrounds is a key factor for introgressing QTLs from initial mapping experiments into applied breeding programs. We have selected four QTLs (fs6.4, fw4.3, fw4.4 and fw8.1) involved in melon fruit morphology that had previously been detected in a collection of introgression lines derived from the cross between a Spanish cultivar, “Piel de Sapo,” and the Korean accession PI161375 (Songwan Charmi). Introgression lines harboring these QTLs were crossed with an array of melon inbred lines representative of the most important cultivar types. Hybrids of the introgression and inbred lines, with the appropriate controls, were evaluated in replicated agronomic trials. The effects of the QTLs were consistent among the different genetic backgrounds, demonstrating the utility of these QTLs for applied breeding programs in modifying melon fruit morphology. Three QTLs, fw4.4, fs6.4 and fs12.1 were subjected to further study in order to map them more accurately by substitution mapping using a new set of introgression lines with recombination events within the QTL chromosome region. The position of the QTLs was narrowed down to 36–5 cM, depending on the QTL. The results presented in the current study set the basis for the use of these QTLs in applied breeding programs and for the molecular characterization of the genes underlying them.     

Integration genetic linkage map construction and several potential QTLs mapping of Chinese shrimp (<Emphasis Type="Italic">Fenneropenaeus chinensis</Emphasis>) based on three types of molecular markers

In this study, totally 54 selected polymorphic SSR loci of Chinese shrimp (Fenneropenaeus chinensis), in addition with the previous linkage map of AFLP and RAPD markers, were used in consolidated linkage maps that composed of SSR, AFLP and RAPD markers of female and male construction, respectively. The female linkage map contained 236 segregating markers, which were linked in 44 linkage groups, and the genome coverage was 63.98%. The male linkage map contained 255 segregating markers, which were linked in 50 linkage groups, covering 63.40% of F. chinensis genome. There were nine economically important traits and phenotype characters of F. chinensis were involved in QTL mapping using multiple-QTL mapping strategy. Five potential QTLs associated with standard length (q-standardl-01), with cephalothorax length (q-cephal-01), with cephaloghorax width (q-cephaw-01), with the first segment length (q-firsel-01) and with anti-WSSV (q-antiWSSV-01) were detected on female LG1 and male LG44 respectively with LOD > 2.5. The QTL q-firsel-01 was at 73.603 cM of female LG1. Q-antiWSSV-01 was at 0 cM of male LG44. The variance explained of these five QTLs was from 19.7–33.5% and additive value was from −15.9175 to 7.3675. The closest markers to these QTL were all SSR, which suggested SSR marker was superior to AFLP and RAPD in the QTL mapping.     

Mapping of QTLs governing agronomic and yield traits in chickpea

Chickpea is one of the most important leguminous cool season food crops, cultivated prevalently in South Asia and Middle East. The main objective of this study was to identify quantitative trait loci (QTLs) associated with seven agronomic and yield traits in two recombinant inbred line populations of chickpea derived from the crosses JG62 × Vijay (JV population) and Vijay × ICC4958 (VI population) from at least three environments. Single locus QTL analysis involved composite interval mapping (CIM) for individual traits and multiple-trait composite interval mapping (MCIM) for correlated traits to detect pleiotropic QTLs. Two-locus analysis was conducted to identify the main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL × environment interactions. Through CIM analysis, a total of 106 significant QTLs (41 in JV and 65 in VI populations) were identified for the seven traits, of which one QTL each for plant height and days to maturity was common in both the populations. Six pleiotropic QTLs that were consistent over the environments were also identified. LG2 in JV and LG1a in VI contained at least one QTL for each trait. Hence, concentrating on these LGs in molecular breeding programs is most likely to bring simultaneous improvement in these traits.     

A intervarietal genetic map and QTL analysis for yield traits in wheat

A new genetic linkage map was constructed based on recombinant inbred lines (RILs) derived from the cross between the Chinese winter wheat (Triticum aestivum L.) varieties, Chuang 35050 and Shannong 483 (ChSh). The map included 381 loci on all the wheat chromosomes, which were composed of 167 SSR, 94 EST-SSR, 76 ISSR, 26 SRAP, 15 TRAP, and 3 Glu loci. This map covered 3636.7 cM with 1327.7 cM (36.5%), 1485.5 cM (40.9%), and 823.5 cM (22.6%) for A, B, and D genome, respectively, and contained 13 linkage gaps. Using the RILs and the map, we detected 46 putative QTLs on 12 chromosomes for grain yield (GY) per m², thousand-kernel weight (TKW), spike number (SN) per m², kernel number per spike (KNS), sterile spikelet number per spike (SSS), fertile spikelet number per spike (FSS), and total spikelet number per spike (TSS) in four environments. Each QTL explained 4.42–70.25% phenotypic variation. Four QTL cluster regions were detected on chromosomes 1D, 2A, 6B, and 7D. The most important QTL cluster was located on chromosome 7D near the markers of Xwmc31, Xgdm67, and Xgwm428, in which 8 QTLs for TKW, SN, SSS and FSS were observed with very high contributions (27.53–67.63%).     

Dynamic QTL Analysis of Rice Protein Content and Protein Index Using Recombinant Inbred Lines

Protein content (PC) and protein index (PI) play important roles in determining nutritional quality in rice (Oryza sativa L.). We used 71 lines derived from “Asominori/IR24” to analyze the developmental behavior of PC and PI through unconditional and conditional QTL mapping methods. In all, 10 unconditional QTLs and 6 conditional QTLs for PC, and 11 unconditional QTLs and 9 conditional QTLs for PI, were identified at four stages of grain filling. More were identified in the first three stages than at the final stage. Temporal patterns of gene expression for PC and PI differed over time, with several QTLs being expressed across two or three stages but many being expressed at only one stage. Some of these QTLs were closely linked with maturity QTLs reported previously. Many QTLs for PC and PI were co-localized, supporting the significant correlation found between PC and PI. Our results suggest that dynamic QTL mapping might be a valid means for revealing more genetic information about protein accumulations during seed development.     

Identification of quantitative trait loci for wood quality and growth across eight full-sib coastal Douglas-fir families

Typical linkage and quantitative trait locus (QTL) analyses in forest trees have been conducted in single pedigrees with sex-averaged linkage maps. The results of a QTL analysis for wood quality and growth traits of coastal Douglas-fir using eight full-sib families, each consisting of 40 progeny, replicated on four sites are presented. The resulting map of segregating genetic markers consisted of 120 amplified fragment length polymorphism (AFLP) loci distributed across 19 linkage groups. The wood quality traits represent the widest suite of traits yet examined for QTL analysis in a tree species in a single study. Wood fiber traits showed the lowest number of QTLs (3) with relatively small effect (ca. 4%); wood density traits also showed just three QTLs but with slightly larger effect; wood chemistry traits showed more QTLs (7), while ring density traits showed many QTLs with large numbers of QTLs (78) and interesting patterns of temporal variation. Growth traits gave just five QTLs but of major effect (10–16%). Trees, with their long generation times, provide a rich resource for studies of temporal variation of QTL expression.     

Unconditional and conditional QTL mapping for the developmental behavior of tiller number in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

A single segment substitution population of 26 lines and their recipient parent Hua-jing-xian 74 (HJX74) were selected as experimental materials for analyzing the developmental behavior of tiller number in rice. By the unconditional QTL (quantitative trait locus) mapping method, a total number of 14 SSSLs were detected with QTLs controlling rice tiller number. The number of QTLs significantly affecting tiller number and their effect values estimated differed across measuring stages. More QTLs could be detected based on time-dependent measures of different stages. By the conditional QTL mapping method, it is possible to reveal net expression of gene in a time interval. 14 QTLs on tiller number expressed their effects in dynamic patterns of themselves during whole ontogeny. They exhibited mainly negative effects within 7 days after transplanting. During 7–21 days, QTLs were in active status and expressed larger positive effects. In the mid-period of 21–35 days, they had opposite genetic effects to wither tillers. Since then these QTLs expressed positive effects again to cause the appearance of noneffective tillers. The dynamics of QTL effects was in agreement with the actual change of tillers. Mapping QTL combining unconditional with conditional analysis for time-dependent measures is helpful to understand roundly the genetic bases for the development of quantitative traits.     

Impact of epistasis and QTL×environment interaction on the developmental behavior of plant height in rice (Oryza sativa L.)

QTLs with epistatic effects and environmental interaction effects for the developmental behavior of plant height in rice were studied by conventional and conditional methods for quantitative trait loci (QTLs) by mapping with a doubled-haploid population of 123 lines from IR64/Azucena in three environments. The results showed that epistatic effects were important and most epistasis could be detected only by conditional QTL mapping, while most non–epistatic QTLs could be detected by both conventional and conditional methods. Many modificative QTLs showed only epistatic effects without their own additive effects at some stages. QTL×environment (QE) interaction effects were detected more often than QTL main effects for plant-height behavior, which might indicate that gene expression could be greatly affected by the environment. No QTLs had effects during the whole of ontogeny. Conditional QTL mapping might be a valid way to reveal dynamic gene expression for the development of quantitative traits, especially for epistatic effects. Received: 19 May 2000 / Accepted: 27 October 2000     

Genomic mapping and testing for quantitative trait loci in tea (<Emphasis Type="Italic">Camellia sinensis</Emphasis> (L.) O. Kuntze)

The tea industry is significant in the economies of tea-growing countries. Prospects of improving yield of made tea genomic information were explored using clones from a cross between clones TRFCA SFS150 and AHP S15/10. The 42 clones were tested in two distinct tea-growing regions in Kenya. Bulk segregant analysis was performed followed by complete genotyping. Out of 260 informative markers, 100 markers that showed 1:1 segregation were used to construct a linkage map. The map contained 30 (19 maternal and 11 paternal) linkage groups that spanned 1,411.5 cM with mean interval of 14.1 cM between loci. Based on the map, quantitative trait loci (QTL) analysis was done on yield data over 2003–2007 across the two sites, Timbilil and Kangaita. Twenty-three putative QTLs were detected, 16 in five different linkage groups for Timbilil, two in two groups for Kangaita, and the rest were associated with unassigned markers. No QTL was detected at both sites, which showed strong genotype × site interaction (G × E) but highly effective within-site heritability ([^(h)]² {\hat{h}^2} generally > 0.7). Problems of overestimated and spurious QTL effects arising from the smallness of the population should be mitigated by generally high within-site heritability. At least two unassigned markers associated with yield at Kangaita over the whole study period, suggesting potential as candidate markers for site-specific marker-assisted selections. Implications of the results with respect to mapping population, G × E, and marker-assisted selection are discussed.     

Genetic linkage maps of two interspecific grape crosses (Vitis spp.) used to localize quantitative trait loci for downy mildew resistance

Two populations (Pop) segregating quantitatively for resistance to downy mildew (DM), caused by Plasmopara viticola, were used to construct genetic maps and to carry out quantitative trait locus (QTL) analysis. Pop1 comprised of 174 F₁ individuals from a cross of ‘Moscato Bianco’, a susceptible Vitis vinifera cultivar, and a resistant individual of Vitis riparia. Pop2 consisted of 94 progeny from a cross of two interspecific hybrids, ‘VRH3082 1-42’ and ‘SK77 5/3’, with resistance traits inherited from Vitis rotundifolia and Vitis amurensis, respectively. Resistance of progeny was measured in field and greenhouse conditions by visual evaluation of disease symptoms on leaves. Linkage maps of 1037.2 and 651 cM were built essentially with simple sequence repeat markers and were enriched with gene-derived single-strand conformational polymorphism and single-nucleotide polymorphism markers. Simple interval mapping and Kruskall–Wallis analysis detected a stable QTL involved in field resistance to DM on linkage group (LG) 7 of the Pop1 integrated map co-localized with a putative Caffeoyl-CoA O-methyltransferase-derived marker. Additional QTLs were detected on LGs 8, 12 and 17. We were able to identify genetic factors correlated with resistance to P. viticola with lower statistical significance on LGs 1, 6 and 7 of the Pop2 map. Finally, no common QTLs were found between the two crosses analyzed. A search of the grapevine genome sequence revealed either homologues to non-host-, host- or defense-signalling genes within the QTL intervals. These positional candidate genes may provide new information about chromosomal regions hosting phenotypic loci.     

A QTL study on late leaf spot and rust revealed one major QTL for molecular breeding for rust resistance in groundnut (Arachis hypogaea L.)

Late leaf spot (LLS) and rust are two major foliar diseases of groundnut (Arachis hypogaea L.) that often occur together leading to 50–70% yield loss in the crop. A total of 268 recombinant inbred lines of a mapping population TAG 24 × GPBD 4 segregating for LLS and rust were used to undertake quantitative trait locus (QTL) analysis. Phenotyping of the population was carried out under artificial disease epiphytotics. Positive correlations between different stages, high to very high heritability and independent nature of inheritance between both the diseases were observed. Parental genotypes were screened with 1,089 simple sequence repeat (SSR) markers, of which 67 (6.15%) were found polymorphic. Segregation data obtained for these markers facilitated development of partial linkage map (14 linkage groups) with 56 SSR loci. Composite interval mapping (CIM) undertaken on genotyping and phenotyping data yielded 11 QTLs for LLS (explaining 1.70–6.50% phenotypic variation) in three environments and 12 QTLs for rust (explaining 1.70–55.20% phenotypic variation). Interestingly a major QTL associated with rust (QTL_rust01), contributing 6.90–55.20% variation, was identified by both CIM and single marker analysis (SMA). A candidate SSR marker (IPAHM 103) linked with this QTL was validated using a wide range of resistant/susceptible breeding lines as well as progeny lines of another mapping population (TG 26 × GPBD 4). Therefore, this marker should be useful for introgressing the major QTL for rust in desired lines/varieties of groundnut through marker-assisted backcrossing.     

Functional mapping of quantitative trait loci associated with rice tillering

Several biologically significant parameters that are related to rice tillering are closely associated with rice grain yield. Although identification of the genes that control rice tillering and therefore influence crop yield would be valuable for rice production management and genetic improvement, these genes remain largely unidentified. In this study, we carried out functional mapping of quantitative trait loci (QTLs) for rice tillering in 129 doubled haploid lines, which were derived from a cross between IR64 and Azucena. We measured the average number of tillers in each plot at seven developmental stages and fit the growth trajectory of rice tillering with the Wang–Lan–Ding mathematical model. Four biologically meaningful parameters in this model––the potential maximum for tiller number (K), the optimum tiller time (t ₀), and the increased rate (r), or the reduced rate (c) at the time of deviation from t ₀––were our defined variables for multi-marker joint analysis under the framework of penalized maximum likelihood, as well as composite interval mapping. We detected a total of 27 QTLs that accounted for 2.49–8.54% of the total phenotypic variance. Nine common QTLs across multi-marker joint analysis and composite interval mapping showed high stability, while one QTL was environment-specific and three were epistatic. We also identified several genomic segments that are associated with multiple traits. Our results describe the genetic basis of rice tiller development, enable further marker-assisted selection in rice cultivar development, and provide useful information for rice production management.     

Premature progression of anther early developmental programs accompanied by comprehensive alterations in transcription during high-temperature injury in barley plants

Kernel number per spike is one of the most important yield components of wheat. To map QTLs related to kernel number including spike length (SPL), spikelet number per spike (SPN), fertile spikelet number (FSPN), sterile spikelet number (SSPN) and compactness, and to characterize the inheritance modes of the QTLs and two-locus interactions, 136 recombinant inbred lines (RILs) derived from ‘Nanda2419’ x ‘Wangshuibai’ and an immortalized F₂ population (IF₂) generated by randomly permutated intermating of these RILs were investigated. QTL mapping made use of the previously constructed over 3300 cM linkage map of the RIL population. Three, five, two, two and six chromosome regions were identified, respectively, for their association with SPL, SPN, FSPN, SSPN, and compactness in at least two of the three environments examined. All compactness QTLs but one shared the respective intervals of QSpn.nau-5A and the SPL QTLs. Xcfd46–Xwmc702 interval on chromosome 7D was related to all traits but SSPN and had consistently the largest effects. The fact that not all the compactness QTL intervals were related to both SPL and SPN indicates that compactness is regulated by different mechanisms. Interval coincidence between QTLs of SPL and SPN and between QTLs of FSPN and SSPN was minimal. For all the traits, favorable alleles exist in both parents. Inheritance modes from additiveness to overdominance of the QTLs were revealed and two-locus interactions were detected, implying that the traits studied are under complex genetic control. The results could contribute to wheat yield improvement and better use of Wangshuibai and Nanda2419 the two special germplasms in wheat breeding program.     

QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat

In bread wheat, single-locus and two-locus QTL analyses were conducted for seven yield and yield contributing traits using two different mapping populations (P I and P II). Single-locus QTL analyses involved composite interval mapping (CIM) for individual traits and multiple-trait composite interval mapping (MCIM) for correlated yield traits to detect the pleiotropic QTLs. Two-locus analyses were conducted to detect main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL × environment interactions (QE and QQE). Only a solitary QTL for spikelets per spike was common between the above two populations. HomoeoQTLs were also detected, suggesting the presence of triplicate QTLs in bread wheat. Relatively fewer QTLs were detected in P I than in P II. This may be partly due to low density of marker loci on P I framework map (173) than in P II (521) and partly due to more divergent parents used for developing P II. Six QTLs were important which were pleiotropic/coincident involving more than one trait and were also consistent over environments. These QTLs could be utilized efficiently for marker assisted selection (MAS).     

Identification and verification of QTLs for agronomic traits using wild barley introgression lines

A set of 39 wild barley introgression lines (hereafter abbreviated with S42ILs) was subjected to a QTL study to verify genetic effects for agronomic traits, previously detected in the BC₂DH population S42 (von Korff et al. 2006 in Theor Appl Genet 112:1221–1231) and, in addition, to identify new QTLs and favorable wild barley alleles. Each line within the S42IL set contains a single marker-defined chromosomal introgression from wild barley (Hordeum vulgare ssp. spontaneum), whereas the remaining part of the genome is exclusively derived from elite spring barley (H. vulgare ssp. vulgare). Agronomic field data of the S42ILs were collected for seven traits from three different environments during the 2007 growing season. For detection of putative QTLs, a two-factorial mixed model ANOVA and, subsequently, a Dunnett test with the recurrent parent as a control were conducted. The presence of a QTL effect on a wild barley introgression was accepted, if the trait value of a particular S42IL was significantly (P < 0.05) different from the control, either across all environments and/or in a particular environment. A total of 47 QTLs were localized in the S42IL set, among which 39 QTLs were significant across all tested environments. For 19 QTLs (40.4%), the wild barley introgression was associated with a favorable effect on trait performance. Von Korff et al. (2006 in Theor Appl Genet 112:1221–1231) mapped altogether 44 QTLs for six agronomic traits to genomic regions, which are represented by wild barley introgressions of the S42IL set. Here, 18 QTLs (40.9%) revealed a favorable wild barley effect on the trait performance. By means of the S42ILs, 20 out of the 44 QTLs (45.5%) and ten out of the 18 favorable effects (55.6%) were verified. Most QTL effects were confirmed for the traits days until heading and plant height. For the six corresponding traits, a total of 17 new QTLs were identified, where at six QTLs (35.3%) the exotic introgression caused an improved trait performance. In addition, eight QTLs for the newly studied trait grains per ear were detected. Here, no QTL from wild barley exhibited a favorable effect. The introgression line S42IL-107, which carries an introgression on chromosome 2H, 17–42 cM is an example for S42ILs carrying several QTL effects simultaneously. This line exhibited improved performance across all tested environments for the traits days until heading, plant height and thousand grain weight. The line can be directly used to transfer valuable Hsp alleles into modern elite cultivars, and, thus, for breeding of improved varieties.     

Quantitative trait loci analysis for the developmental behavior of tiller number in rice (Oryza sativa L.)

 A doubled-haploid rice population of 123 lines from Azucena/IR64 was used for analyzing the developmental behavior of tiller number by conditional and unconditional QTL mapping methods. It was indicated that the number of QTLs significantly affecting tiller number was different at different measuring stages. Many QTLs controlling tiller growth identified at the early stages were undetectable at the final stage. Only one QTL could be detected across the whole growth period. By conditional QTL mapping, more QTLs for tiller number could be detected than that by unconditional mapping. The temporal patterns of gene expression for tiller number could be different at different stages. Even an individual gene or genes at the same genomic region might have opposite genetic effects at various growth stages. Received: 7 July 1997 / Accepted: 10 February 1998