Identification of QTLs affecting traits of agronomic importance in a recombinant inbred population derived from a subspecific rice cross

To detect QTLs controlling traits of agronomic importance in rice, two elite homozygous lines 9024 and LH422, which represent the indica and japonica subspecies of rice (Oryza sativa), were crossed. Subsequently a modified single-seed-descent procedure was employed to produce 194 recombinant inbred lines (F₈). The 194 lines were genotyped at 141 RFLP marker loci and evaluated in a field trial for 13 quantitative traits including grain yield. Transgressive segregants were observed for all traits examined. The number of significant QTLs (LOD 2.0) detected affecting each trait ranged from one to six. The percentage of phenotypic variance explained by each QTL ranged from 5.1% to 73.7%. For those traits for which two or more QTLs were detected, increases in the traits were conditioned by indica alleles at some QTLs Japonica alleles at others. No significant evidence was found for epistasis between markers associated with QTLs and all the other markers. Pleitropic effects of single QTLs on different traits are suggested by the observation of clustering of QTLs. No QTL for traits was found to map to the vicinity of major gene loci governing the same traits qualitatively. Evidence for putative orthologous QTLs across rice, maize, oat, and barley is discussed.     

Molecular-marker-facilitated studies of morphological traits in maize. II: Determination of QTLs for grain yield and yield components

Genetic factors controlling quantitative inheritance of grain yield and its components have not previously been investigated by using replicated lines of an elite maize (Zea mays L.) population. The present study was conducted to identify quantitative trait loci (QTLs) associated with grain yield and grain-yield components by using restriction fragment length polymorphism (RFLP) markers. A population of 150 random F₂₃ lines was derived from the single cross of inbreds Mo17 and H99, which are considered to belong to the Lancaster heterotic group. Trait values were measured in a replicated trial near Ames, Iowa, in 1989. QTLs were located on a linkage map constructed with one morphological and 103 RFLP loci. QTLs were found for grain yield and all yield components. Partial dominance to overdominance was the primary mode of gene action. Only one QTL, accounting for 35% of the phenotypic variation, was identified for grain yield. Two to six QTLs were identified for the other traits. Several regions with pleiotropic or linked effects on several of the yield components were detected.     

水稻籼粳交DH群体收获指数及源库性状的QTL分析

以 1个水稻籼粳交 (圭 6 30 0 2 4 2 8)来源的DH群体为材料 ,利用 1张含有 2 32个标记的RFLP连锁图谱和基于混合线性模型的定位软件QTLMapper1 0对水稻收获指数及生物量、籽粒产量、库容量和株高 5个性状进行QTL分析 ,共检测到 2 1个主效应QTLs和 9对上位性互作位点。其中 ,控制籽粒产量的 3个QTLs合计贡献率为 4 2 % ,LOD值为 7 10 ;这 3个QTLs或者与收获指数的QTL同位 ,或者与生物量的QTL同位 ,且加性效应的方向一致 ,从而揭示了“籽粒产量 =生物量×收获指数”的遗传基础所在。控制收获指数的 4个QTLs合计贡献率为 4 6 % ,LOD值为 10 3;控制生物量的 4个QTLs合计贡献率为 6 4 % ,LOD值为 14 0 9;收获指数的 4个QTLs与生物量的 4个QTLs均不同位。因此 ,通过基因重组 ,可能实现控制收获指数和生物量的增效基因的聚合 ,由此获得收获指数和生物量“双高”的基因型。检测到 5个株高QTLs,其合计贡献率为 6 4 % ,LOD值为 11 6 2 ;其中 ,有 3个效应较小的QTLs与生物量、库容量和 或籽粒产量QTLs同位 ,且同位QTLs的加性效应方向一致 ;未发现株高QTLs与收获指数QTLs的同位性。由此表明 ,株高与“源 流 库”概念中的“源”和“库”在遗传上有一定程度的关联 ,而与“流”无关联。此外还发现 ,在上述同位性QTL     

QTLs for agronomic traits in the Mediterranean environment identified in recombinant inbred lines of the cross 'Arta' × <Emphasis Type="Italic">H. spontaneum</Emphasis> 41-1

A genetic linkage map has been developed for recombinant inbred lines (RILs) of the cross 'Arta' × Hordeum spontaneum 41-1. One hundred and ninety four RILs, randomly chosen from a population of 494 RILs, were mapped with 189 markers including one morphological trait (btr = brittle rachis locus). The linkage map extended to 890 cM. Agronomic traits such as grain yield, biological yield, days to heading, plant height, cold tolerance and others were evaluated at the ICARDA research stations Tel Hadya and Breda during the years 1996–97 and 1997–98. QTLs for agronomic traits related to drought resistance were localized. For the most-important character 'plant height under drought stress', QTLs on 2H, 3H and 7H were detected. The 'plant height' QTLs, specially the one on 3H, showed pleiotropic effects on traits such as days to heading, grain yield and biological yield. QTLs were also identified for other traits associated with adaptation to the Mediterranean environment such as cold tolerance, days to heading and tiller number. The identification of QTLs for agronomic traits is a first step to analyze and to dissect complex characters such as adaptation to drought tolerance.Comunicated by R. Hagemann     

QTL analysis of agronomic traits in barley based on the doubled haploid progeny of two elite North American varieties representing different germplasm groups

A better understanding of the genetics of complex traits, such as yield, may be achieved by using molecular tools. This study was conducted to estimate the number, genome location, effect and allele phase of QTLs determining agronomic traits in the two North American malting barley (Hordeum vulgare L.) quality variety standards. Using a doubled haploid population of 140 lines from the cross of two-rowed Harrington×six-rowed Morex, agronomic phenotypic data sets from nine environments, and a 107-marker linkage map, we performed QTL analyses using simple interval mapping and simplified composite interval mapping procedures. Thirty-five QTLs were associated, either across environments or in individual environments, with five grain and agronomic traits (yield, kernel plumpness, test weight, heading date, and plant height). Significant QTL×environment interaction was detected for all traits. These interactions resulted from both changes in the magnitude of response and changes in the sign of the allelic effect. QTLs for multiple traits were coincident. The vrs1 locus on chromosome 2 (2H), which determines inflorescence row type, was coincident with the largest-effect QTL determining four traits (yield, kernel plumpness, test weight, and plant height). QTL analyses were also conducted separately for each sub-population (six-rowed and two-rowed). Seven new QTLs were detected in the sub-populations. Positive transgressive segregants were found for all traits, but they were more prevalent in the six-rowed sub-population.QTL analysis should be useful for identifying candidate genes and introgressing favorable alleles between germplasm groups. Received: 18 August 2000 / Accepted: 15 December 2000     

In an elite cross of maize a major quantitative trait locus controls one-fourth of the genetic variation for grain yield

Quantitative trait loci (QTLs) for grain yield, dry matter content and test weight were identified in an F₂ segregating population derived from a single cross between two elite maize lines (B73 and A7) and testcrossed to two genetically divergent in breds. Most of the QTLs inferred were consistent across locations, indicating that the expression of the genes influencing the traits under investigation was largely independent of the environment. By using two different tester lines we found that QTLs exhibited by one tester may not necessarily be detected with the second one. Only loci with larger effects were consistent across testers, suggesting that interaction with tester alleles may contribute to the identification of QTLs in a specific fashion. Analysis across both testers revealed four significant QTLs for grain yield that explained more than 35% of the phenotypic variation and showed an overall phenotypic effect of more than 2t/ha. The major QTL for grain yield, located in the proximity of the Nucleolus Organiser Region, accounted for 24.5% of the phenotypic variation for grain yield and showed an average effect of allele substitution of approximately 1 t/ha. Marker-assisted introgression of the superior A7 allele at this locus in the B73 genetic background will not differ from qualitative trait introgression and will eventually lead to new lines having superior testcross performance.     

Detection of grain protein content QTLs across environments in tetraploid wheats

Grain protein content (GPC) is an important quality factor in both durum and bread wheats. GPC is considered to be a polygenic trait influenced by environmental factors and management practice. The objectives of this study were both to compare the quantitative trait loci (QTL) for GPC in a population of 65 recombinant inbred lines of tetraploid wheats evaluated in three locations for several years (eight data sets), and to investigate the genetic relationship among GPC and grain yield. QTLs were determined based on the Messapia × dicoccoides linkage map which covers 217 linked loci on the 14 chromosomes with 42 additional loci as yet unassigned to linkage groups. The map extends to 1352 cM; the average distance between adjacent markers was 6.3 cM. Seven QTLs for GPC, located on the chromosome arms 4BS, 5AL, 6AS (two loci), 6BS, 7AS and 7BS, were detected that were significant in at least one environment at P<0.001 or in at least two environments at P<0.01. One QTL was significant in all but one environment, two were significant in four or five environments, and four were significant in two out of eight environments. Six out of seven protein content QTLs had pleiotropic effects or were associated to QTLs for grain yield and explained the negative correlation among GPC and yield components. The present results support the concept that studies conducted in a single environment are likely to underestimate the number of QTLs that can influence a trait and that the phenotypic data for a quantitative trait should be collected over a range of locations to identify putative QTLs and determine their phenotypic effects.     

Plastid genome characterisation in Brassica and Brassicaceae using a new set of nine SSRs

The objective of the present study was to identify favourable exotic Quantitative Trait Locus (QTL) alleles for the improvement of agronomic traits in the BC₂DH population S42 derived from a cross between the spring barley cultivar Scarlett and the wild barley accession ISR42-8 (Hordeum vulgare ssp. spontaneum). QTLs were detected as a marker main effect and/or a marker × environment interaction effect (M × E) in a three-factorial ANOVA. Using field data of up to eight environments and genotype data of 98 SSR loci, we detected 86 QTLs for nine agronomic traits. At 60 QTLs the marker main effect, at five QTLs the M × E interaction effect, and at 21 QTLs both the effects were significant. The majority of the M × E interaction effects were due to changes in magnitude and are, therefore, still valuable for marker assisted selection across environments. The exotic alleles improved performance in 31 (36.0%) of 86 QTLs detected for agronomic traits. The exotic alleles had favourable effects on all analysed quantitative traits. These favourable exotic alleles were detected, in particular on the short arm of chromosome 2H and the long arm of chromosome 4H. The exotic allele on 4HL, for example, improved yield by 7.1%. Furthermore, the presence of the exotic allele on 2HS increased the yield component traits ears per m² and thousand grain weight by 16.4% and 3.2%, respectively. The present study, hence, demonstrated that wild barley does harbour valuable alleles, which can enrich the genetic basis of cultivated barley and improve quantitative agronomic traits.     

The genetics of nitrogen use in hexaploid wheat: N utilisation, development and yield

A genetic study is presented for traits relating to nitrogen use in wheat. Quantitative trait loci (QTLs) were established for 21 traits relating to growth, yield and leaf nitrogen (N) assimilation during grain fill in hexaploid wheat (Triticum aestivum L.) using a mapping population from the cross Chinese Spring × SQ1. Glutamine synthetase (GS) isozymes and estimated locations of 126 genes were placed on the genetic map. QTLs for flag leaf GS activity, soluble protein, extract colour and fresh weight were found in similar regions implying shared control of leaf metabolism and leaf size. Flag leaf traits were negatively associated with days to anthesis both phenotypically and genetically, demonstrating the complex interactions of metabolism with development. One QTL cluster for GS activity co-localised with a GS2 gene mapped on chromosome 2A, and another with the mapped GSr gene on 4A. QTLs for GS activity were invariably co-localised with those for grain N, with increased activity associated with higher grain N, but with no or negative correlations with grain yield components. Peduncle N was positively correlated, and QTLs co-localised, with grain N and flag leaf N assimilatory traits, suggesting that stem N can be indicative of grain N status in wheat. A major QTL for ear number per plant was identified on chromosome 6B which was negatively co-localised with leaf fresh weight, peduncle N, grain N and grain yield. This locus is involved in processes defining the control of tiller number and consequently assimilate partitioning and deserves further examination. Electronic Supplementary Material The online version of this article () contains supplementary material, which is available to authorized users.     

Salt tolerance in Lycopersicon species. V. Does genetic variability at quantitative trait loci affect their analysis?

 Salt tolerance was studied comparatively in three families derived from crosses between Lycopersicon esculentum Mill. and two related wild species [two accessions of Lycopersicon pimpinellifolium (Jusl.) Mill. and one accession of Lycopersicon chesmannii f.minor (Hook.f.) Mull.] by means of QTL analysis of fruit yield and earliness under conditions of salinity. From six polymorphic genomic regions involved in salt tolerance, three contained segregant salt-tolerant QTLs for the three families; two were found only in both families derived from L.pimpinellifolium; and one, involved in fruit number, was detected only in one of the L.pimpinellifolium families. Some differences regarding the effects of the wild alleles at orthologous QTLs were found. These effects were always negative in the L. chesmannii family. Comparing both L. pimpinellifolium families, the “wild” alleles at two out of nine common QTLs for fruit number and weight had effects with opposite directions, and the mode of gene action was clearly different at five of them. QTL analysis of earliness revealed the largest genotypic differences among families. Most drastic differences were found for the epistatic interactions in which all genomic regions containing QTLs were involved. These interactions between unlinked genes increased the range of variation of means, mainly upwards, as compared with genotypes at individual QTLs. Only one (affecting fruit weight) out of 27 interactions was detected in both L.pimpinellifolium families. Heterotic effects found for salt tolerance in one of the families can be explained by the presence of overdominant (or pseudo-overdominant) and dominant gene effects at QTLs controlling final fruit yield under conditions of salinity. Allelic variation at salt-tolerant QTLs exists, changing the additive and, mainly, the non-additive components of the genotypic value. Consequently, it may negatively affect the general applicability (or efficiency) of marker-assisted selection to improve salt tolerance in other segregant populations where QTLs were not studied. The use of more informative co-dominant markers, like microsatelites, might overcome these problems. Received: 5 August 1996/Accepted: 25 October 1996     

Genetic basis of pre-harvest sprouting tolerance using single-locus and two-locus QTL analyses in bread wheat

Quantitative trait loci (QTL) analysis for pre-harvest sprouting tolerance (PHST) in bread wheat was conducted following single-locus and two-locus analyses, using data on a set of 110 recombinant inbred lines (RILs) of the International Triticeae Mapping Initiative population grown in four different environments. Single-locus analysis following composite interval mapping (CIM) resolved a total of five QTLs with one to four QTLs in each of the four individual environments. Four of these five QTLs were also detected following two-locus analysis, which resolved a total of 14 QTLs including 8 main effect QTLs (M-QTLs), 8 epistatic QTLs (E-QTLs) and 5 QTLs involved in QTL × environment (QE) or QTL × QTL × environment (QQE) interactions, some of these QTLs being common. The analysis revealed that a major fraction (76.68%) of the total phenotypic variation explained for PHST is due to M-QTLs (47.95%) and E-QTLs (28.73%), and that only a very small fraction of variation (3.24%) is due to QE and QQE interactions. Thus, more than three-quarters of the genetic variation for PHST is fixable and would contribute directly to gains under selection. Two QTLs that were detected in more than one environment and at LOD scores above the threshold values were located on 3BL and 3DL presumably in the vicinity of the dormancy gene TaVp1. Another QTL was found to be located on 3B, perhaps in close proximity to the R gene for red grain colour. However, these associations of QTLs for PHST with genes for dormancy and grain colour are only suggestive. The results obtained in the present study suggest that PHST is a complex trait controlled by large number of QTLs, some of them interacting among themselves or with the environment. These QTLs can be brought together through marker-aided selection, leading to enhanced PHST.     

Genetic analysis of grain protein-content,grain yield and thousand-kernel weight in bread wheat

Grain yield and grain protein content are two very important traits in bread wheat. They are controlled by genetic factors, but environmental conditions considerably affect their expression. The aim of this study was to determine the genetic basis of these two traits by analysis of a segregating population of 194 F(7) recombinant inbred lines derived from a cross between two wheat varieties, grown at six locations in France in 1999. A genetic map of 254 loci was constructed, covering about 75% of the bread wheat genome. QTLs were detected for grain protein-content (GPC), yield and thousand-kernel weight (TKW). 'Stable' QTLs (i.e. detected in at least four of the six locations) were identified for grain protein-content on chromosomes 2A, 3A, 4D and 7D, each explaining about 10% of the phenotypic variation of GPC. For yield, only one important QTL was found on chromosome 7D, explaining up to 15.7% of the phenotypic variation. For TKW, three QTLs were detected on chromosomes 2B, 5B and 7A for all environments. No negative relationships between QTLs for yield and GPC were observed. Factorial Regression on GxE interaction allowed determination of some genetic regions involved in the differential reaction of genotypes to specific climatic factors, such as mean temperature and the number of days with a maximum temperature above 25 degrees C during grain filling.     

Genetic variation for N-remobilization and postsilking N-uptake in a set of maize recombinant inbred lines. 3. QTL detection and coincidences

The objective of this study was to map and characterize QTLs for traits related to nitrogen utilization efficiency (NUE), grain N yield, N-remobilization and post-silking N-uptake. Furthermore, to examine whether QTLs detected with recombinant inbred lines (RILs) crossed to a tester are common to those detected with line per se evaluation, both types of evaluations were developed from the same set of RILs. The material was studied over two years at high N-input, and one year at low N-input. We used (15)N-labelling to evaluate with accuracy the proportion of N remobilized from stover to kernels and the proportion of postsilking N-uptake allocated to kernels. With 59 traits studied in three environments, 608 QTLs were detected. Using a method of QTL clustering, 72 clusters were identified, with few QTLs being specific to one environment or to the type of plant material (lines or testcross families). However, considering each trait separately, few QTLs were common to both line per se and testcross evaluation. This shows that genetic variability is expressed differently according to the type of progeny. Studies of coincidences among QTLs within the clusters showed an antagonism between N-remobilization and N-uptake in several QTL-clusters. QTLs for N-uptake, root system architecture and leaf greenness coincided positively in eight clusters. QTLs for remobilization mainly coincided in clusters with QTLs for leaf senescence. On the whole, sign of coincidences between QTLs underlined the role of a "stay-green" phenotype in favouring N-uptake capacity, and thus grain yield and N grain yield.     

QTL mapping of root traits in phosphorus-deficient soils reveals important genomic regions for improving NDVI and grain yield in barley

Key message

Major QTLs for root rhizosheath size are not correlated with grain yield or yield response to phosphorus. Important QTLs were found to improve phosphorus efficiency.

Abstract

Root traits are important for phosphorus (P) acquisition, but they are often difficult to characterize and their breeding values are seldom assessed under field conditions. This has shed doubts on using seedling-based criteria of root traits to select and breed for P efficiency. Eight root traits were assessed under controlled conditions in a barley doubled-haploid population in soils differing in P levels. The population was also phenotyped for grain yield, normalized difference vegetation index (NDVI), grain P uptake and P utilization efficiency at maturity (PutE_GY) under field conditions. Several quantitative traits loci (QTLs) from the root screening and the field trials were co-incident. QTLs for root rhizosheath size and root diameter explained the highest phenotypic variation in comparison to QTLs for other root traits. Shared QTLs were found between root diameter and grain yield, and total root length and PutE_GY. A common major QTL for rhizosheath size and NDVI was mapped to the HvMATE gene marker on chromosome 4H. Collocations between major QTLs for NDVI and grain yield were detected on chromosomes 6H and 7H. When results from BIP and MET were combined, QTLs detected for grain yield were also those QTLs found for NDVI. QTLs qGY5H, qGY6H and qGY7Hb on 7H were robust QTLs in improving P efficiency. A selection of multiple loci may be needed to optimize the breeding outcomes due to the QTL x Environment interaction. We suggest that rhizosheath size alone is not a reliable trait to predict P efficiency or grain yield.

     

Detection of QTLs for grain protein content in durum wheat

Grain protein content (GPC) of durum wheat (Triticum turgidum L. var. durum) is an important trait for the nutritional value of grain and for influencing the technological property of flour. Protein content is a quantitative trait negatively correlated with grain yield, thus increase in protein quantity usually results in yield reduction. This study was initiated to introgress alleles for high GPC from var. dicoccoides into durum wheat germplasm by the backcross inbred line (BIL) method and to identify molecular markers linked to high GPC alleles not associated with depressing effects on yield. The backcross line 3BIL-85 with high GPC and similar grain yield to the recurrent parent was backcrossed to Latino, and the generations F₂, F₃ and F₄ were evaluated for GPC and yield per spike (GYS) in three field trials. Three QTLs with major effects on GPC were detected on chromosome arms 2AS, 6AS and 7BL, identified by the markers Xcfa2164, XP39M37 ₍₂₅₀₎ and Xgwm577 _, respectively. Multiple regression analysis indicated that the three QTLs explained all the genetic variances of the trait. The high GPC parental line 3BIL-85 was not significantly different from the recurrent parent Latino for GYS, but the phenotypic correlation coefficient between GPC and GYS had negative values (from −0.02 to −0.28) in each trial, although it was statistically significant only in the F3 progeny trial. No co-located QTL for GYS was detected, excluding the hypothesis that the putative QTLs for GPC were indirect QTLs for low grain yield. The negative protein-yield response could be due to: (a) co-location of grain yield per spike QTLs with reduced phenotypic effects not detectable by the experimental design or statistical procedures, or to (b) opposite pleiotropic gene effects due to the major bio-energetic requirements for synthesis of protein then carbohydrates. Mapping loci by BILs should enable the production of near-isogenic lines in which the individual effects of each QTL can be examined in detail without confounding variations due to other putative QTLs. An erratum to this article can be found at     

QTL mapping for the paste viscosity characteristics in rice (Oryza sativa L.)

In order to understand the genetic basis of the paste viscosity characteristics (RVA profile, which is tested on the Rapid Visco Analyser) of the rice grain, we mapped QTLs for RVA profile parameters using a DH population derived from a cross between an indica variety, Zai-Ye-Qing 8 (ZYQ8), and a japonica variety, Jing-Xi 17 (JX17). Evidence of genotype-by-environment interaction was found by comparing the mapped QTLs between two locations, Hainan (HN) and Hangzhou (HZ). A total of 20 QTLs for six parameters of the RVA profiles were identified at least one location. Only the waxy locus (wx) located on chromosome 6 was detected significantly at both environments for five traits, i.e. hot paste viscosity (HPV), cool paste viscosity (CPV), breakdown viscosity (BDV), consistency viscosity (CSV) and setback viscosity (SBV). This locus explained 19.5%–63.7% of the total variations at both environments, suggesting that the RVA profiles were mainly controlled by the wx gene. HPV, CPV, BDV, CSV and SBV were also controlled by other QTLs whose effects on the respective parameter were detected only in one environment, while for the peak viscosity (PKV), only 2 QTLs, 1 at HN,the other at HZ, were identified. These results indicate that RVA profiles are obviously affected by environment. Received: 18 July 1999 / Accepted: 27 August 1999     

Identification of quantitative trait loci for yield and yield components in an advanced backcross population derived from the<Emphasis Type="Italic"> Oryza sativa</Emphasis> variety IR64 and the wild relative<Emphasis Type="Italic"> O. rufipogon</Emphasis>

A BC₂F₂ population developed from an interspecific cross between Oryza sativa (cv IR64) and O. rufipogon (IRGC 105491) was used in an advanced backcross QTL analysis to identify and introduce agronomically useful genes from this wild relative into the cultivated gene pool. The objectives of this study were: (1) to identify putative yield and yield component QTLs that can be useful to improve the elite cultivar IR64; (2) to compare the QTLs within this study with previously reported QTLs in rice as the basis for identifying QTLs that are stable across different environments and genetic backgrounds; and (3) to compare the identified QTLs with previously reported QTLs from maize to examine the degree of QTL conservation across the grass family. Two hundred eighty-five families were evaluated in two field environments in Indonesia, with two replications each, for 12 agronomic traits. A total of 165 markers consisting of 131 SSRs and 34 RFLPs were used to construct the genetic linkage map. By employing interval mapping and composite interval mapping, 42 QTLs were identified. Despite its inferior performance, 33% of the QTL alleles originating from O. rufipogon had a beneficial effect for yield and yield components in the IR64 background. Twenty-two QTLs (53.4%) were located in similar regions as previously reported rice QTLs, suggesting the existence of stable QTLs across genetic backgrounds and environments. Twenty QTLs (47.6%) were exclusively detected in this study, uncovering potentially novel alleles from the wild, some of which might improve the performance of the tropical indica variety IR64. Additionally, several QTLs for plant height, grain weight, and flowering time detected in this study corresponded to homeologous regions in maize containing previously detected maize QTLs for these traits.     

Identification of Quantitative Trait Loci for Bacterial Blight Resistance Derived from Oryza meyeriana and Agronomic Traits in Recombinant Inbred Lines of Oryza sativa

Bacterial blight (BB) is one of the major diseases that affect rice productivity. In previous studies, BB resistance was transferred to cultivated rice Oryza sativa from wild rice Oryza meyeriana using asymmetric somatic hybridization. One of the resistant hybrid progenies (Y73) has also been shown to possess novel resistance gene(s) different from any of those previously associated with BB resistance. We have mapped quantitative trait loci (QTLs) for BB resistance in a recombinant inbred line (RIL) population derived from a cross between Y73 and a BB‐susceptible cv. IR24. Five QTLs were detected where Y73 alleles contributed to increased BB resistance. Three minor QTLs were identified on chromosomes 3, 10 and 11, and two major QTLs on chromosomes 1 and 5, respectively. QTL on chromosome 5, designated qBBR5, had the strongest effect on BB resistance, explaining approximately 37% of the phenotypic variance. Using the same RIL population, we also mapped QTLs for agronomic traits including plant height (PH), heading date (HD), plant yield (PYD) and PYD component traits. A total of 21 QTLs were identified, of which four were detected for PH, six for HD, three for panicle number per plant (PNPP), one for spikelets per panicle (SPP), six for 1000‐grain weight (TGW) and one for PYD. qPH1 (a QTL for PH) was found in the same interval as qBBR1 for BB resistance, and qHD11 for HD and qBBR11 for BB resistance also shared a similar interval. Additionally, BB resistance was significantly correlated with PH or HD in the RIL population. This suggests that the resistance genes may have pleiotropic effects on, or close linkage to, genes controlling PH or HD. These results will help deduce the resistance mechanisms of the novel resistance gene(s) and provide the basis for cloning them and using them in marker‐assisted breeding.     

AFLP mapping of quantitative trait loci for yield-determining physiological characters in spring barley

 An amplified fragment length polymorphism (AFLP) map covering 965 cM was constructed using 94 recombinant inbred lines of a cross between the spring barley varieties Prisma and Apex. This map was employed to identify quantitative trait loci (QTLs) controlling plant height, yield and yield-determining physiological characters using an approximate multiple-QTL model, the MQM method. The seven physiological traits were parameters used in a process-based crop-growth model that predicts barley biomass production as affected by daily temperature and radiation. The traits were measured in experiments conducted over 2 years. Except for the relative growth rate of leaf area, all traits examined had at least one QTL in each year. QTLs and their effects were found to vary with developmental stages for one trait, the fraction of shoot biomass partitioned to leaves, that was measured at several stages. Most of the traits were associated, though to different extents, with the denso dwarfing gene (the height-reducing allele in Prisma) located on the long arm of chromosome 3. Some of the QTLs were mapped to similar positions in both years. The results in relation to effects of the dwarfing gene, the physiological basis for QTL×environment interaction, and the relative importance of the parameter traits with respect to yield, are discussed. Received: 17 September 1998 / Accepted: 28 December 1998     

Mapping QTLs controlling grain yield and its components on chromosome 5A of wheat

Chromosome 5A of wheat is known to carry a number of genes affecting adaptability and productivity. To localize quantitative trait loci (QTLs) controlling grain yield and its components, an RFLP map was constructed from 118 single-chromosome recombinant lines derived from the F₁ between Chinese Spring (Cappelle-Desprez 5A) and Chinese Spring (Triticum spelta 5A). The map was combined with the field-trial data scored over 3 years. A total of five regions in chromosome 5A contributed effects on yield traits. Increases in grain yield, 50-grain weight and spikelet number/ear were determined by complementary QTL alleles from both parents. The effects associated with the vernalization requirement gene Vrn-A1 or a closely linked QTL were significant only in the favorable growing season where the later-flowering vrn-A1 allele from Cappelle-Desprez 5A produced a higher tiller number/plant and spikelet number/ear. The effects of the ear morphology gene q or closely linked QTL(s) were detected for grain yield and ear grain weight. Three other QTLs with minor effects were dispersed along chromosome 5A. These QTLs had large interactions with years due to changes in the magnitude of the significant response. The alleles from T. spelta, however, conferred a higher yield performance. Received: 18 August 1999 / Accepted: 25 March 2000