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     

Quantitative trait locus analysis of drought tolerance and yield in Maize in China

Drought accounts for significant yield losses in crops. Maize (Zea mays L.) is particularly sensitive to water stress at reproductive stages, and breeding to improve drought tolerance has been a challenge. By use of a linkage map with 121 single sequence repeat (SSR) markers, quantitative trait loci (QTLs) for grain yield and yield components were characterized in the population of the cross X178×B73 under water-stressed and well-watered conditions. Under the well-watered regime, 2, 4, 4, 1, 2, 2, and 3 QTLs were identified for grain yield, 100-kernel weight, kernel number per ear, cob weight per ear, kernel weight per ear, ear weight, and ear number per plant, respectively, whereas under the water-stressed conditions, 1, 5, 2, 6, 1, 3, and 2 QTLs, respectively, were found. The significant phenotypic correlations among yield and yield components to some extent were observed under both water conditions, and some overlaps between the corresponding QTLs were also found. QTLs for grain yield and kernel weight per ear under well-watered conditions and ear weight under both well-watered and water-stressed conditions over-lapped, and all were located on chromosome 1.03 near marker bnlg176. Two other noticeable QTL regions were on chromosome 9.05 and 9.07 near markers umc1657 and bnlg1525; the first corresponded to grain yield, kernel weight per ear, and ear weight under well-watered conditions and kernel number per ear under both water conditions, and the second to grain yield and cob weight per ear under water-stressed conditions and ear number per plant under both water conditions. A comparative analysis of the QTLs herein identified with those described in previous studies for yield and yield components in different maize populations revealed a number of QTLs in common. These QTLs have potential use in molecular marker-assisted selection.     

Mixed model association scans of multi-environmental trial data reveal major loci controlling yield and yield related traits in Hordeum vulgare in Mediterranean environments

An association panel consisting of 185 accessions representative of the barley germplasm cultivated in the Mediterranean basin was used to localise quantitative trait loci (QTL) controlling grain yield and yield related traits. The germplasm set was genotyped with 1,536 SNP markers and tested for associations with phenotypic data gathered over 2?years for a total of 24?year?×?location combinations under a broad range of environmental conditions. Analysis of multi-environmental trial (MET) data by fitting a mixed model with kinship estimates detected from two to seven QTL for the major components of yield including 1000 kernel weight, grains per spike and spikes per m², as well as heading date, harvest index and plant height. Several of the associations involved SNPs tightly linked to known major genes determining spike morphology in barley (vrs1 and int-c). Similarly, the largest QTL for heading date co-locates with SNPs linked with eam6, a major locus for heading date in barley for autumn sown conditions. Co-localization of several QTL related to yield components traits suggest that major developmental loci may be linked to most of the associations. This study highlights the potential of association genetics to identify genetic variants controlling complex traits.     

Evaluation of barley chromosome-3 yield QTLs in a backcross F2 population using STS-PCR

Chromosome 3 displayed the two largest yield QTLs in a previous study of 150 doubled haploid lines derived from a cross of Steptoe and Morex barley varieties. Low-copy number RFLP markers, detected using Southern analysis, are excellent tools for generating robust linkage maps as demonstrated by the Steptoe and Morex map produced by the North American Barley Genome Mapping Project (SM NABGMP). However, this technique can be cumbersome when applied to practically oriented plant breeding programs. In the present report, we demonstrate the conversion of RFLPs to more practically useful PCR-based markers that are co-dominant and allelic to the barley chromosome-3 RFLP markers from which they derive. We have used these sequence-tagged-site (STS) PCR markers to evaluate the putative yield QTL components of the Steptoe chromosome 3 in a Morex backcross population. Headshattering, plant lodging, and yield measurements are reported from five replicated field experiments conducted under diverse growing conditions in Montana. Our study detected significant effects for all three traits in a chromosomal region that evidently corresponds to the larger of the two previously reported chromosome-3 QTLs. However, we failed to detect any yield or other effects which might be coincidental to the second largest yield QTL. The genetic effects of the yield QTL identified in our first backcross breeding population show similar magnitude, environmental interactions, and association with lodging and headshattering QTLs observed in the SM NABGMP experiments. Our study elucidates complex environmental conditioning for headshattering and plant lodging which probably underlie the variable yield effects observed under different growing conditions.     

Genomic regions for yield and yield parameters in Chinese winter wheat (Triticum aestivum L.) genotypes tested under varying environments correspond to QTL in widely different wheat materials

Field trials with a population of 108 doubled haploid (DH) lines of bread wheat (Triticum aestivum L.) derived from a cross between the Chinese winter wheat cultivars CA9613 and H1488 were carried out at Beijing (China) in 2000/2001 and 2001/2002. In addition, a field trial and a pot experiment were carried out at the experimental field stations of Giessen University (Germany) in the vegetation periods 2004/2005 and 2006/2007. Phenotypic data for major agronomic yield-related traits, i.e. grain weight per ear (GWE), grain number per ear (GNE), plant height and thousand-grain weight (TGW), were recorded in all experiments. In addition, biomass weight per tiller and ear weight were evaluated in the two field trials at Beijing. Based on the phenotypic data and a genetic map comprising 168 SSR markers, an analysis of quantitative trait loci (QTL) was carried out for yield and yield parameters using the composite interval mapping (CIM) approach. A total of 30 QTL were detected for these traits across four environments. Five of these QTL located on chromosomes 1A, 1B, 2B, 2D and 7D exhibited pleiotropic effects. Such pleiotropic gene loci will be very useful for understanding the homologous/homeologous relationships among QTL and designing an appropriate marker-assisted breeding programme including multi-trait selection in order to accumulate (“pyramide”) favorable alleles at different genetic loci.     

大麦产量构成模型

通过产量构成法构建了适用于不同地区不同品种的大麦产量模拟模型.以南京、昆明、武汉3个地区各试验处理中不同大麦品种最适条件下的产量因素为基础,建立了最适条件下每株穗数相对值、每穗粒数相对值、千粒重相对值与累积光合有效辐射的回归方程,构建了实际条件下的不同大麦品种每株穗数、每穗粒数和千粒重与这三者在最适条件下的潜在值和实际条件下的水肥丰缺因子等变量的函数关系.模型较为全面地考虑了大麦品种生长发育的内外因素,内因主要体现为品种遗传特性（潜在的每株穗数、潜在的每穗粒数、潜在的千粒重和灌浆期因子）,外因包括光合有效辐射和水肥丰缺因子.运用武汉、昆明、扬州3个地区不同品种、不同播期的田间试验资料对模型进行了测试和检验.结果表明,模型对大麦产量构成因子及理论产量的模拟效果较好,模拟值与观测值吻合度高,每株穗数、每穗粒数和千粒重相对误差（RE）绝对值的平均值分别为1.96%、1.88%和1.67%,对这三者及理论产量的模拟值和观测值进行y=x回归分析,相关系数（r）在0.9464～0.9987,相关性显著,说明模型具有较高的预测性和适用性.     

Quantitative trait loci for rice yield-related traits using recombinant inbred lines derived from two diverse cultivars

The thousand-grain weight and spikelets per panicle directly contribute to rice yield. Heading date and plant height also greatly influence the yield. Dissection of genetic bases of yield-related traits would provide tools for yield improvement. In this study, quantitative trait loci (QTL) mapping for spikelets per panicle, thousand-grain weight, heading date and plant height was performed using recombinant inbred lines derived from a cross between two diverse cultivars, Nanyangzhan and Chuan7. In total, 20 QTLs were identified for four traits. They were located to 11 chromosomes except on chromosome 4. Seven and five QTLs were detected for thousand-grain weight and spikelets per panicle, respectively. Four QTLs were identified for both heading date and plant height. About half the QTLs were commonly detected in both years, 2006 and 2007. Six QTLs are being reported for the first time. Two QTL clusters were identified in regions flanked by RM22065 and RM5720 on chromosome 7 and by RM502 and RM264 on chromosome 8, respectively. The parent, Nanyangzhan with heavy thousand-grain weight, carried alleles with increased effects on all seven thousand-grain weight QTL, which explained why there was no transgressive segregation for thousand-grain weight in the population. In contrast, Chuan7 with more spikelets per panicle carried positive alleles at all five spikelets per panicle QTL except qspp5. Further work on distinction between pleiotropic QTL and linked QTL is needed in two yield-related QTL clusters.     

Molecular mapping of quantitative trait loci for yield and yield components in spring wheat (Triticum aestivum L.)

An F1 derived doubled haploid (DH) population of 402 lines from the adapted spring wheat cross Superb (high yielding)/BW278 (low yielding) was developed to identify quantitative trait loci (QTL) associated with yield and yield components. A subset of the population (186 lines) was evaluated in replicated field trials in 2001 and 2002 at six locations in Manitoba and Saskatchewan, Canada. Agronomic parameters, grain yield and yield components including 1,000 grain weight, harvest index, average seed weight spike(-1), seed number spike(-1) and spikes number m(-2) were measured. A genetic map was constructed with 268 microsatellite marker loci and included two morphological genes, reduced plant height, Rht-B1b, and the presence/absence of awns, B1. Composite interval mapping was conducted to estimate the location and effect of QTL associated with the evaluated traits. A total of 53 QTL were identified on 12 chromosomes for the 9 evaluated traits with the coefficient of determination ranging from 0.03 to 0.21 of the total variation. The increase in yield and yield components ranged from 4.5 to 17.1% over the population mean. The five grain yield QTL were detected on chromosomes 1A, 2D, 3B, and 5A and showed a combined increase of 34.4%, over the population mean. The alleles from Superb were associated with increased yield for four of the five QTL. This study identified potential chromosome segments for use in marker-assisted selection to improve yield and yield components in spring wheat.     

Mapping QTL for grain yield, yield components, and spike features in a doubled haploid population of bread wheat

A doubled haploid (DH) population derived from a cross between the Japanese cultivar 'Fukuho-kumogi' and the Israeli wheat line 'Oligoculm' was used to map genome regions involved in the expression of grain yield, yield components, and spike features in wheat (Triticum aestivum L). A total of 371 markers (RAPD, SSR, RFLP, AFLP, and two morphological traits) were used to construct the linkage map that covered 4190 cM of wheat genome including 28 linkage groups. The results of composite interval mapping for all studied traits showed that some of the quantitative trait loci (QTL) were stable over experiments conducted in 2004 and 2005. The major QTL located in the Hair-Xpsp2999 interval on chromosome 1A controlled the expression of grains/spike (R(2) = 12.9% in 2004 and 22.4% in 2005), grain weight/spike (R(2) = 21.4% in 2004 and 15.8% in 2005), and spike number (R(2) = 15.6% in 2004 and 5.4% in 2005). The QTL for grain yield located on chromosomes 6A, 6B, and 6D totally accounted for 27.2% and 31.7% of total variation in this trait in 2004 and 2005, respectively. Alleles inherited from 'Oligoculm' increased the length of spikes and had decreasing effects on spike number. According to the data obtained in 2005, locus Xgwm261 was associated with a highly significant spike length QTL (R(2) = 42.33%) and also the major QTL for spikelet compactness (R(2) = 26.1%).     

Identification of genetic loci affecting amylose content and agronomic traits on chromosome 4A of wheat

 Chromosome 4A of wheat carries the Wx-B1 gene encoding the granule-bound starch synthase involved in amylose synthesis in the endosperm. To determine the pleiotropic effects of this locus and effects of independent QTLs on agronomic traits, genetical analysis of chromosome 4A was conducted using 98 single-chromosome recombinant substitution lines derived from a cross of Chinese Spring and Chinese Spring (Kanto107 4A) with a low amylose content due to the null Wx-B1b allele. For amylose content, most of the genetic variation was explained by the allelic difference at the Wx-B1 locus. An additional QTL of minor effect was mapped in the 6.2-cM Xbcd1738/Xcdo1387 interval on the short arm, where the allele from Kanto107 led to an increase in amylose content. Field trials over two seasons revealed a pleiotropic effect of Wx-B1, or else the effect of a closely linked QTL, on ear emergence time. A QTL linked to Wx-B1 was detected for plant height. For plant yield and its components, there was no evidence for significant main effects associated with Wx-B1 or adjacent regions. One plant-yield QTL was identified by RFLP markers on the short arm and this was identical to QTLs controlling spikelet number/ear and grain weight/ear. At these QTLs for agronomic traits, alleles from Kanto107 contributed to an earlier emergence time, a height reduction and an yield increase. Received: 10 August 1998 / Accepted: 3 November 1998     

Identification of QTLs for grain yield and grain-related traits of maize (Zeamays L.) using an AFLP map, different testers, and cofactor analysis

We exploited the AFLP®¹(AFLP® is a registered trademark of Keygene, N.V.) technique to map and characterise quantitative trait loci (QTLs) for grain yield and two grain-related traits of a maize segregating population. Two maize elite inbred lines were crossed to produce 229 F₂ individuals which were genotyped with 66 RFLP and 246 AFLP marker loci. By selfing the F₂ plants 229 F₃ lines were produced and subsequently crossed to two inbred testers (T1 and T2). Each series of testcrosses was evaluated in field trials for grain yield, dry matter concentration, and test weight. The efficiency of generating AFLP markers was substantially higher relative to RFLP markers in the same population, and the speed at which they were generated showed a great potential for application in marker-assisted selection. AFLP markers covered linkage group regions left uncovered by RFLPs; in particular at telomeric regions, previously almost devoided of markers. This increase of genome coverage afforded by the inclusion of the AFLPs revealed new QTL locations for all the traits investigated and allowed us to map telomeric QTLs with higher precision. The present study has also provided an opportunity to compare simple (SIM) and composite interval mapping (CIM) for QTL analysis. Our results indicated that the method of CIM employed in this study has greater power in the detection of QTLs, and provided more precise and accurate estimates of QTL positions and effects than SIM. For all traits and both testers we detected a total of 36 QTLs, of which only two were in common between testers. This suggested that the choice of a tester for identifying QTL alleles for use in improving an inbred is critical and that the expression of QTL alleles identified may be tester-specific.     

Molecular breeding for grain yield in barley: an evaluation of QTL effects in a spring barley cross

 We report results from a breeding strategy designed to accumulate favorable QTL alleles for grain yield identified in the SteptoeבMorex’ (SM) barley germplasm. Two map lines (SM73 and SM145) from the original mapping population were selected based on their marker genotype and QTL structure. When crossed, these lines would be expected to produce progeny with most favorable QTL alleles. One hundred doubled haploid (DH) lines from the F₁ hybrid of this cross were genotyped with ten RFLP markers and one morphological marker defining grain yield to monitor QTL segregation. A subset of 24 lines representing various combinations of putatively favorable and unfavorable QTL alleles, together with Steptoe, ‘Morex’, SM73, and SM145, were phenotyped for grain yield in five environments. Multiple regression procedures were used to explore phenotype and genotype relationships. Most target QTLs showed significant effects. However, significance and magnitude of QTL effects and favorable QTL allele phase varied across environments. All target QTLs showed significant QTL-by-environment interaction (QTL×E), and the QTL on chromosome 2 expressed alternative favorable QTL alleles in different environments. Digenic epistatic effects were also detected between some QTL loci. For traits such as grain yield, marker-assisted selection efforts may be better targeted at determining optimum combinations of QTL alleles rather than pyramiding alleles detected in a reference mapping population. Received: 2 June 1998 / Accepted: 17 September 1998     

Quantitative trait loci associated with adaptation to Mediterranean dryland conditions in barley

The objective of the present study was to identify quantitative trait loci (QTL) influencing agronomic performance across rain fed Mediterranean environments in a recombinant inbred line (RIL) population derived from the barley cultivars ER/Apm and Tadmor. The population was tested in four locations (two in Syria and two in Lebanon) during four consecutive years. This allowed the analysis of marker main effects as well as of marker by location and marker by year within location interactions. The analysis demonstrated the significance of crossover interactions in environments with large differences between locations and between years within locations. Alleles from the parent with the higher yield potential, ER/Apm, were associated with improved performance at all markers exhibiting main effects for grain yield. The coincidence of main effect QTL for plant height and yield indicated that average yield was mainly determined by plant height, where Tadmor's taller plants, being susceptible to lodging, yielded less. However, a number of crossover interactions were detected, in particular for yield, where the Tadmor allele improved yield in the locations with more severe drought stress. The marker with the highest number of cross-over interactions for yield and yield component traits mapped close to the flowering gene Ppd-H2 and a candidate gene for drought tolerance HVA1 on chromosome 1H. Effects of these candidate genes and QTL may be involved in adaptation to severe drought as frequently occurring in the driest regions in the Mediterranean countries. Identification of QTL and genes affecting field performance of barley under drought stress is a first step towards the understanding of the genetics behind drought tolerance.     

Detection of two major grain yield QTL in bread wheat (Triticum aestivum L.) under heat, drought and high yield potential environments

A large proportion of the worlds’ wheat growing regions suffers water and/or heat stress at some stage during the crop growth cycle. With few exceptions, there has been no utilisation of managed environments to screen mapping populations under repeatable abiotic stress conditions, such as the facilities developed by the International Wheat and Maize Improvement Centre (CIMMYT). Through careful management of irrigation and sowing date over three consecutive seasons, repeatable heat, drought and high yield potential conditions were imposed on the RAC875/Kukri doubled haploid population to identify genetic loci for grain yield, yield components and key morpho-physiological traits under these conditions. Two of the detected quantitative trait loci (QTL) were located on chromosome 3B and had a large effect on canopy temperature and grain yield, accounting for up to 22?% of the variance for these traits. The locus on chromosome arm 3BL was detected under all three treatments but had its largest effect under the heat stress conditions, with the RAC875 allele increasing grain yield by 131?kg?ha^?1 (or phenotypically, 7?% of treatment average). Only two of the eight yield QTL detected in the current study (including linkage groups 3A, 3D, 4D 5B and 7A) were previously detected in the RAC875/Kukri doubled haploid population; and there were also different yield components driving grain yield. A number of discussion points are raised to understand differences between the Mexican and southern Australian production environments and explain the lack of correlation between the datasets. The two key QTL detected on chromosome 3B in the present study are candidates for further genetic dissection and development of molecular markers.     

Genome-wide association mapping of yield and yield components of spring wheat under contrasting moisture regimes

Key message

A stable QTL that may be used in marker-assisted selection in wheat breeding programs was detected for yield, yield components and drought tolerance-related traits in spring wheat association mapping panel.

Abstract

Genome-wide association mapping has become a widespread method of quantitative trait locus (QTL) identification for many crop plants including wheat (Triticum aestivum L.). Its benefit over traditional bi-parental mapping approaches depends on the extent of linkage disequilibrium in the mapping population. The objectives of this study were to determine linkage disequilibrium decay rate and population structure in a spring wheat association mapping panel (n = 285–294) and to identify markers associated with yield and yield components, morphological, phenological, and drought tolerance-related traits. The study was conducted under fully irrigated and rain-fed conditions at Greeley, CO, USA and Melkassa, Ethiopia in 2010 and 2011 (five total environments). Genotypic data were generated using diversity array technology markers. Linkage disequilibrium decay rate extended over a longer genetic distance for the D genome (6.8 cM) than for the A and B genomes (1.7 and 2.0 cM, respectively). Seven subpopulations were identified with population structure analysis. A stable QTL was detected for grain yield on chromosome 2DS both under irrigated and rain-fed conditions. A multi-trait region significant for yield and yield components was found on chromosome 5B. Grain yield QTL on chromosome 1BS co-localized with harvest index QTL. Vegetation indices shared QTL with harvest index on chromosome 1AL and 5A. After validation in relevant genetic backgrounds and environments, QTL detected in this study for yield, yield components and drought tolerance-related traits may be used in marker-assisted selection in wheat breeding programs.     

An investigation into the relations between some growth parameters and yield of barley

Twenty-five field experiments on barley were done at four sites from 1970 to 1975, with an additional site in 1975, comparing five rates of nitrogen application. The crops were sampled at c. 14-day intervals from about the four-leaf stage to maturity to follow changes with time in the dry weights of the constituent plant parts and to measure fertile tiller number, grain number per ear and grain weight. Some data have been selected from this body of information and regression analysis has been used to assess the possible importance of pre- and post-anthesis growth in determining the yield of barley. Ear emergence was taken as an approximate indicator of anthesis. Yield was closely related (r=+0–96) and almost equal to the amount of dry matter accumulated before ear emergence for twenty-one of the experiments, with a regression coefficient of 0–95. In two of the remaining experiments the regression coefficient was greater, 1–14; and smaller in the other two, o-8i. Plant population is also shown to affect the regression coefficient. Despite these anomalies grain yield was more closely related to plant dry weight at ear emergence than to the increase in weight after ear emergence (r =+0–79). The increase in plant dry weight after ear emergence was frequently less than the yield of grain, suggesting that the plant can compensate for inadequate photosynthesis during grain filling. The result of this compensation is a reduction in straw dry weight. This implies that previously assimilated dry matter is transported to the grain, or that respiratory losses from the straw are not replaced by current photosynthesis. These observations suggest that yield may be limited by sink capacity rather than by photosynthesis after ear emergence. The main component of sink capacity, grain number per m² was closely related to yield (r =+0–95) and is known to be determined at or before anthesis. Grain size was shown to be related to grain number per ear (r= 4- 0–99), suggesting that grain size is also, at least partially, determined at ear emergence. Therefore, all the yield components are determined, wholly or partly before ear emergence.     

Identification of quantitative trait loci for nitrogen use efficiency in maize

Intensively managed crop systems are normally dependent on nitrogen input to maximize yield potential. Improvements in nitrogen- use efficiency (NUE) in crop plants may support the development of cropping systems that are more economically efficient and environment friendly. The objective of this study was to map and characterize quantitative trait loci (QTL) for NUE in a maize population. In preliminary experiments, inbred lines contrasting for NUE were identified and were used to generate populations of F2:3 families for genetic study. A total of 214 F2:3 families were evaluated in replicated trials under high nitrogen (280 kg/ha) and low nitrogen (30 kg/ha) conditions in 1996 and 1997. Analysis of ear-leaf area, plant height, grain yield, ears per plant, kernels number per ear, and kernel weight indicated significant genetic variation among F2:3 families. The heritability of these traits was found to be high (h2=0.57–0.81). The mapping population were genotyped using a set of 99 restriction fragment length polymorphism (RFLP) markers. A linkage map of these markers was developed and used to identify QTL. Between two and six loci were found to be associated with each trait. The correspondence of several genomic regions with traits measured under nitrogen limited conditions suggests the presence of QTL associated with NUE. QTLs will help breeders to improve their maize ideotype of a low-nitrogen efficiency by identifying those constitutive and adaptive traits involved in the expression of traits significantly correlated with yield, such as ear leaf area and number of ears per plant. This revised version was published online in June 2006 with corrections to the Cover Date.     

QTLs for grain dry milling properties, composition and vitreousness in maize recombinant inbred lines

Vitreousness and kernel hardness are important properties for maize processing and end-product quality. In order to examine the genetic basis of these traits, a recombinant inbred line population resulting from a cross between a flint line (F-2) and a semident line (Io) was used to search for vitreousness and kernel composition QTLs. Vitreousness was measured by image processing from a kernel section, while NIR spectroscopy was used to estimate starch, protein, cellulose, lipid and semolina yield. In addition, thousand-grain weight and grain weight per ear were measured. The MQTL method was used to map the QTLs for the different traits. An additional program allowed for the detection of interaction QTLs between markers. The total number of main-effect and interaction QTLs was similar. The QTLs were not evenly distributed but tended to cluster. Such clusters, mixing main-effect and interaction QTLs, were observed at six positions : on chromosomes 1, 2, 3, 6, 8 and 9. Two of them, on chromosomes 6 and 9, concerned both QTLs for kernel-weight traits and QTLs for kernel-composition traits (protein and cellulose). Technological-trait QTLs (vitreousness or semolina yield) were located less than 16 cM from a protein-content QTL on chromosome 2, and were co-located with lipid- and starch-content QTLs on chromosome 8. The co-location of a vitreousness and a semolina-yield QTL at the telomeric end of the chromosome 2 (Bin 2.02) is likely to be meaningful since measurement of these related traits, made by completely different methods (NIRS vs image processing), yielded very close QTLs. A similar location was previously reported independently for a kernel-friability QTL. Comparing the map location of the numerous loci for known-function genes it was shown that three zein loci were closely linked to QTLs for vitreousness on chromosome 3, for semolina yield and starch on chromosome 4, and for protein, cellulose and grain weight on chromosome 9. Some other candidate genes linked to starch precursor metabolism were also suggested on chromosomes 6 and 8. Received: 27 April 2000 / Accepted: 3 July 2000     

Identification of QTLs for Yield and Associated Traits in F₂ Population of Rice

Identification of quantitative trait loci (QTLs) controlling yield and yield-related traits in rice was performed in the F₂ mapping population derived from parental rice genotypes DHMAS and K343. A total of 30 QTLs governing nine different traits were identified using the composite interval mapping (CIM) method. Four QTLs were mapped for number of tillers per plant on chromosomes 1 (2 QTLs), 2 and 3; three QTLs for panicle number per plant on chromosomes 1 (2 QTLs) and 3; four QTLs for plant height on chromosomes 2, 4, 5 and 6; one QTL for spikelet density on chromosome 5; four QTLs for spikelet fertility percentage (SFP) on chromosomes 2, 3 and 5 (2 QTLs); two QTLs for grain length on chromosomes 1 and 8; three QTLs for grain width on chromosomes1, 3 and 8; three QTLs for 1000-grain weight (TGW) on chromosomes 1, 4 and 8 and six QTLs for yield per plant (YPP) on chromosomes 2 (3 QTLs), 4, 6 and 8. Most of the QTLs were detected on chromosome 2, so further studies on chromosome 2 could help unlock some new chapters of QTL for this cross of rice variety. Identified QTLs elucidating high phenotypic variance can be used for marker-assisted selection (MAS) breeding. Further, the exploitation of information regarding molecular markers tightly linked to QTLs governing these traits will facilitate future crop improvement strategies in rice.     

Linkage disequilibrium mapping of yield and yield stability in modern spring barley cultivars

Associations between markers and complex quantitative traits were investigated in a collection of 146 modern two-row spring barley cultivars, representing the current commercial germ plasm in Europe. Using 236 AFLP markers, associations between markers were found for markers as far apart as 10 cM. Subsequently, for the 146 cultivars the complex traits mean yield, adaptability (Finlay-Wilkinson slope), and stability (deviations from regression) were estimated from the analysis of variety trial data. Regression of those traits on individual marker data disclosed marker-trait associations for mean yield and yield stability. Support for identified associations was obtained from association profiles, i.e., from plots of P-values against chromosome positions. In addition, many of the associated markers were located in regions where earlier QTL were found for yield and yield components. To study the oligogenic genetic base of the traits in more detail, multiple linear regression of the traits on markers was carried out, using stepwise selection. By this procedure, 18-20 markers that accounted for 40-58% of the variation were selected. Our results indicate that association mapping approaches can be a viable alternative to classical QTL approaches based on crosses between inbred lines, especially for complex traits with costly measurements.