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     

QTL mapping reveals genetic architectures of malting quality between Australian and Canadian malting barley (<Emphasis Type="Italic">Hordeum vulgare</Emphasis> L.)

Australia and Canada are major exporters of malting barley (Hordeum vulgare L.), with Baudin from Australia and AC Metcalfe from Canada being the benchmark varieties for premium malting quality in the past 10 years. We used the barley doubled haploid population derived from a cross of Baudin and AC Metcalfe to map quantitative trait loci (QTLs) for malting quality. The results revealed different genetic architectures controlling malting quality for the two cultivars. Sixteen QTLs were identified and located on chromosomes 1H, 2H, 5H and 7H. The Australian barley Baudin mainly contributed to the malting quality QTL traits of high diastatic power and high β-glucanase on chromosome 1H, while Canadian barley AC Metcalfe mainly contributed to the QTL traits of high hot water extract, high free amino nitrogen, high α-amylase and low malt yield in chromosome 5HL telomere region. This study demonstrated the potential to breed new barley varieties with superior malting quality by integrating genes from Australian and Canadian malting barley varieties. This paper also provides methods to anchor traditional molecular markers without sequence information, such as amplified fragment length polymorphism markers, into the physical map of barley cv. ‘Morex’.     

The detection of QTLs in barley associated with endosperm hardness, grain density, grain size and malting quality using rapid phenotyping tools

Using a barley mapping population, ‘Vlamingh’ × ‘Buloke’ (V × B), whole grain analyses were undertaken for physical seed traits and malting quality. Grain density and size were predicted by digital image analysis (DIA), while malt extract and protein content were predicted using near infrared (NIR) analysis. Validation of DIA and NIR algorithms confirmed that data for QTL analysis was highly correlated (R ² > 0.82), with high RPD values (the ratio of the standard error of prediction to the standard deviation, 2.31–9.06). Endosperm hardness was measured on this mapping population using the single kernel characterisation system. Grain density and endosperm hardness were significantly inter-correlated in all three environments (r > 0.22, P < 0.001); however, other grain components were found to interact with the traits. QTL for these traits were also found on different genomic regions, for example, grain density QTLs were found on chromosomes 2H and 6H, whereas endosperm hardness QTLs were found on 1H, 5H, and 7H. In this study, the majority of the genomic regions associated with grain texture were also coincident with QTLs for grain size, yield, flowering date and/or plant development genes. This study highlights the complexity of genomic regions associated with the variation of endosperm hardness and grain density, and their relationships with grain size traits, agronomic-related traits, and plant development loci.     

AB-QTL analysis in spring barley: III. Identification of exotic alleles for the improvement of malting quality in spring barley (<Emphasis Type="Italic">H. vulgare</Emphasis> ssp. <Emphasis Type="Italic">spontaneum</Emphasis>)

Malting quality is genetically determined by the complex interaction of numerous traits which are expressed prior to and, in particular, during the malting process. Here, we applied the advanced backcross quantitative trait locus (AB-QTL) strategy (Tanksley and Nelson, Theor Appl Genet 92:191–203, 1996), to detect QTLs for malting quality traits and, in addition, to identify favourable exotic alleles for the improvement of malting quality. For this, the BC₂DH population S42 was generated from a cross between the spring barley cultivar Scarlett and the wild barley accession ISR42-8 (Hordeum vulgare ssp. spontaneum). A QTL analysis in S42 for seven malting parameters measured in two different environments yielded 48 QTLs. The exotic genotype improved the trait performance at 18 (37.5%) of 48 QTLs. These favourable exotic alleles were detected, in particular, on the chromosome arms 3HL, 4HS, 4HL and 6HL. The exotic allele on 4HL, for example, improved α-amylase activity by 16.3%, fermentability by 0.8% and reduced raw protein by 2.4%. On chromosome 6HL, the exotic allele increased α-amylase by 16.0%, fermentability by 1.3%, friability by 7.3% and reduced viscosity by 2.9%. Favourable transgressive segregation, i.e. S42 lines exhibiting significantly better performance than the recurrent parent Scarlett, was recorded for four traits. For α-amylase, fermentability, fine-grind extract and VZ45 20, 16, 2 and 26 S42 lines, respectively, surpassed the recurrent parent Scarlett. The present study hence demonstrates that wild barley does harbour valuable alleles, which can enrich the genetic basis of cultivated barley and improve malting quality traits.     

QTLs affecting kernel size and shape in a two-rowed by six-rowed barley cross

The suitability of barley ( Hordeum vulgare L.) grain for malting depends on many criteria, including the size, shape and uniformity of the kernels. Here, image analysis was used to measure kernel size and shape attributes (area, perimeter, length, width, F-circle and F-shape) in grain samples of 140 doubled-haploid lines from a two-rowed (cv Harrington) by six-rowed (cv Morex) barley cross. Interval mapping was used to map quantitative trait loci (QTLs) affecting the means and within-sample standard deviations of these attributes using a 107-marker genome map. Regions affecting one or more kernel size and shape traits were detected on all seven chromosomes. These included one near the vrs1 locus on chromosome 2 and one near the int-c locus on chromosome 4. Some, but not all, of the QTLs exhibited interactions with the environment and some QTLs affected the within-sample variability of kernel size and shape without affecting average kernel size and shape. When QTL analysis was conducted using data from only the two-rowed lines, the region on chromosome 2 was not detected but QTLs were detected elsewhere in the genome, including some that had not been detected in the analysis of the whole population. Analysis of only the six-rowed lines did not detect any QTLs affecting kernel size and shape attributes. QTL alleles that made kernels larger and/or rounder also tended to improve malt quality and QTL alleles that increased the variability of kernel size were associated with poor malt quality.     

Dissection of a malting quality QTL region on chromosome 1 (7H) of barley

Malting and brewing are major uses of barley (Hordeum vulgare L.) worldwide, utilizing 30–40% of the crop each year. A set of complex traits determines the quality of malted barley and its subsequent use for beer. Molecular genetics technology has increased our understanding of genetic control of the many malting and brewing quality traits, most of which are quantitatively inherited. The objective of this study was to further dissect and evaluate a known major malting quality quantitative trait locus (QTL) region of about 28 cM on chromosome 1 (7H). Molecular marker-assisted backcrossing was used to develop 39 isolines originating from a Steptoe / Morex cross. Morex, a 6–row malting type, was the donor parent and Steptoe, a 6–row feed type, was the recurrent parent. The isolines and parents were grown in four environments, and the grain was micro-malted and analyzed for malting quality traits. The effect of each Morex chromosome segment in the QTL target region was determined by composite interval mapping (CIM) and confirmed and refined by multiple interval mapping (MIM). One QTL was resolved for malt extract content, and two QTLs each were resolved for -amylase activity, diastatic power, and malt -glucan content. One additional putative malt extract QTL was detected at the plus border of the target region by CIM, but not confirmed by MIM. All QTLs were resolved to intervals of 2.0 to 6.4 cM by CIM, and to intervals of 2.0 cM or less by MIM. These results should facilitate marker-assisted selection in breeding improved malting barley cultivars.     

Chromosomal loci associated with endosperm hardness in a malting barley cross

A breeding objective for the malting barley industry is to produce lines with softer, plumper grain containing moderate protein content (9–12%) as they are more likely to imbibe water readily and contain more starch per grain, which in turn produces higher levels of malt extract. In a malting barley mapping population, ‘Arapiles’ × ‘Franklin’, the most significant and robust quantitative trait locus (QTL) for endosperm hardness was observed on the short arm of chromosome 1H, across three environments over two growing seasons. This accounted for 22.6% (Horsham 2000), 26.8% (Esperance 2001), and 12.0% (Tarranyurk 2001) of the genetic variance and significantly increased endosperm hardness by 2.06–3.03 SKCS hardness units. Interestingly, Arapiles and Franklin do not vary in Ha locus alleles. Therefore, this region, near the centromere on chromosome 1H, may be of great importance when aiming to manipulate endosperm hardness and malting quality. Interestingly, this region, close to the centromere on chromosome 1H, in our study, aligns with the region of the genome that includes the HvCslF9 and the HvGlb1 genes. Potentially, one or both of these genes could be considered to be candidate genes that influence endosperm hardness in the barley grain. Additional QTLs for endosperm hardness were detected on chromosomes 2H, 3H, 6H and 7H, confirming that the hardness trait in barley is complex and multigenic, similar to many malting quality traits of interest.     

Marker-assisted analysis of three grain yield QTL in barley (Hordeum vulgare L.) using near isogenic lines

Three previously identified grain yield quantitative trait loci (QTL) on chromosomes 2S(2HS), 3C(3HC) and 5L(1HL), designated QTL-2S, QTL-3 and QTL-5L, respectively, were evaluated for their potential to increase yields of high-quality malting barley without disturbing their favorable malting quality profile. QTL mapping of yield related traits was performed and near-isogenic lines (NILs) were developed. QTL for plant height, head shattering, seed weight and number of rachis nodes/spike were detected in the QTL-3 region. NILs developed by introgressing QTL-3 from the high-yielding cv. Steptoe to the superior malting quality, moderate-yielding cv. Morex acquired reduced height, lodging and head shattering features of Steptoe without major changes in malting quality. The yield of NILs, measured by minimizing the losses due to lodging and head shattering, did not exceed that of Morex. Steptoe NILs, with the Morex QTL-2S region, flowered 10 days later than Steptoe but the grain yield was not changed. None of the 3 QTL studied altered the measured yield of the recipient genotype, per se, although QTL 2S and QTL-3 affected yield-related traits. We conclude that these yield QTL must interact with other genes for full expression. Alternatively, they affect the harvestable yield through reduced lodging, head shattering, and/or altered flowering time.     

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

Characterization of the determinants of economically important phenotypes showing complex inheritance should lead to the more effective use of genetic resources. This study was conducted to determine the number, genome location and effects of QTLs determining malting quality in the two North American barley quality standards. Using a doubled-haploid population of 140 lines from the cross of Harrington×Morex, malting quality phenotype data sets from eight environments, and a 107-marker linkage map, QTL analyses were performed using simple interval mapping and simplified composite interval mapping procedures. Seventeen QTLs were associated with seven grain and malting quality traits (percentage of plump kernels, test weight, grain protein percentage, soluble/total protein ratio, α-amylase activity, diastatic power and malt-extract percentage). QTLs for multiple traits were coincident. The loci controlling inflorescence type [vrs1 on chromosome 2(2H) and int-c on chromosome 4(4H)] were coincident with QTLs affecting all traits except malt-extract percentage. The largest effect QTLs, for the percentage of plump kernels, test weight protein percentage, S/T ratio and diastatic power, were coincident with the vrs1 locus. QTL analyses were conducted separately for each sub-population (six-rowed and two-rowed). Eleven new QTLs were detected in the subpopulations. There were significant interactions between the vrs1 and int-c loci for grain-protein percentage and S/T protein ratio. Results suggest that this mating of two different germplasm groups caused a disruption of the balance of traits. Information on the number, position and effects of QTLs determining components of malting quality may be useful for maintaining specific allele configurations that determine target quality profiles. Received: 28 May 1999 / Accepted: 9 November 1999     

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

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

QTL mapping for some grain traits in bread wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Grain traits are important agronomic attributes with the market value as well as milling yield of bread wheat. In the present study, quantitative trait loci (QTL) regulating grain traits in wheat were identified. Data for grain area size (GAS), grain width (GWid), factor form density (FFD), grain length-width ratio (GLWR), thousand grain weight (TGW), grain perimeter length (GPL) and grain length (GL) were recorded on a recombinant inbred line derived from the cross of NW1014?×?HUW468 at Meerut and Varanasi locations. A linkage map of 55 simple sequence repeat markers for 8 wheat chromosomes was used for QTL analysis by Composite interval mapping. Eighteen QTLs distributed on 8 chromosomes were identified for seven grain traits. Of these, five QTLs for GLWR were found on chromosomes 1A, 6A, 2B, and 7B, three QTLs for GPL were located on chromosomes 4A, 5A and 7B and three QTLs for GAS were mapped on 5D and 7D. Two QTLs were identified on chromosomes 4A and 5A for GL and two QTLs for GWid were identified on chromosomes 7D and 6A. Similarly, two QTLs for FFD were found on chromosomes 1A and 5D. A solitary QTL for TGW was identified on chromosome 2B. For several traits, QTLs were also co-localized on chromosomes 2B, 4A, 5A, 6A, 5D, 7B and 7D. The QTLs detected in the present study may be validated for specific crosses and then used for marker-assisted selection to improve grain quality in bread wheat.     

Quantitative trait loci of barley malting quality trait components in the Stellar/01Ab8219 mapping population

Malting barley is of high economic and scientific importance. Determining barley grains that are suitable for malting involves measuring malting quality, which is an expensive and complex process. In order to decrease the cost of phenotyping and accelerate the process of developing superior malting barley cultivars, markers for marker-assisted breeding are needed. In this study, we identified quantitative trait loci (QTLs) for malting traits in a Stellar/01Ab8219 F6:8 recombinant inbred line population grown at Aberdeen and Tetonia, Idaho, USA in 2009 and 2010. We identified QTLs associated with malt extract (ME), wort protein, soluble/total protein (S/T), diastatic power (DP), alpha-amylase, beta-glucan (BG) and free amino nitrogen (FAN) at a logarithm of odds score ≥2.5 using a high-density genetic map produced by merging Diversity Arrays Technology markers with the current single nucleotide polymorphism map. Novel QTLs were identified for DP and FAN on chromosome 5H, S/T on 6H, and BG and ME on 7H. Dissection of the genetic regions associated with malting traits suggests the involvement of multiple molecular pathways. The resulting molecular markers may prove useful for barley improvement.     

Identification of proteins associated with malting quality in a subset of wild barley introgression lines

Malted barley is an important ingredient used in the brewing and distilling industry worldwide. In this study, we used a proteomics approach to investigate the biochemical function of previously identified quantitative trait loci (QTLs) on barley chromosomes 1H and 4H that influence malting quality. Using a subset of barley introgression lines containing wild barley (Hordeum vulgare ssp. spontaneum) alleles at these QTLs, we validated that wild barley alleles at the chromosome 1H QTL reduced overall malting quality, whereas wild barley alleles at the chromosome 4H QTL improved the malting quality parameters α-amylase activity, VZ45, and Kolbach index compared to the control genotype Scarlett. 2DE was used to detect changes in protein expression during the first 72 h of micromalting associated with these QTLs. In total, 16 protein spots showed a significant change in expression between the introgression lines and Scarlett, of which 14 were successfully identified with MS. Notably, the wild barley alleles in the line containing the chromosome 4H QTL showed a sixfold increased expression of a limit dextrinase inhibitor. The possible role of the identified proteins in malting quality is discussed. The knowledge gained will assist ongoing research toward cloning the genes underlying these important QTL.     

Molecular marker-assisted selection for malting quality traits in barley

Selection for malting quality in breeding programs by micromalting and micromashing is time-consuming, and resource-intensive. More efficient and feasible approaches for identifying genotypes with good malting quality would be highly desirable. With the advent of molecular markers, it is possible to map and tag the loci affecting malting quality. The objective of this study was to assess the effectiveness of molecular marker assisted selection for malting quality traits. Two major quantitative trait loci (QTL) regions in six-row barley for malt extract percentage, -amylase activity, diastatic power, and malt -glucan content on chromosomes 1 (QTL1) and 4 (QTL2) have been previously identified. The flanking markers, Brz and Amy2, and WG622 and BCD402B, for these two major QTL regions were used in marker-assisted selection. Four alternative selection strategies; phenotypic selection, genotypic selection, tandem genotypic and phenotypic selection, and combined phenotypic and genotypic selection, were compared for both single and multiple trait selection in a population consisting of 92 doubled haploid lines derived from Steptoe × Morex crosses. Marker assisted selection for QTL1 (tandem genotypic and phenotypic selection, and combined phenotypic and genotypic selection) was more effective than phenotypic selection, but for QTL2 was not as effective as phenotypic selection due to a lack of QTL2 effects in the selection population. The effectiveness of tandem genotypic and phenotypic selection makes marker assisted selection practical for traits which are extremely difficult or expensive to measure such as most malting quality traits. It can substantially eliminate undesirable genotypes by early genotyping and keeping only desirable genotypes for later phenotypic selection.     

PEG-simulated drought stress and spike in vitro culture are used to study the impact of water stress on barley malt quality

Water deficient or drought stress is a major factor causing deterioration or instability of malt barley quality. In the studies on the influence of drought stress during grain filling on malt quality formation or metabolic changes, it is quite difficult to obtain the uniform plant individuals and water condition in pot or field experiments. In this study, we combined barley spike in vitro culture and PEG-6000 simulated drought to determine the genotypic difference in the changes of grain metabolites and the expression level of the genes encoding β-amylase and β-glucan using two Tibetan wild barley accessions and two cultivated genotypes differing in malt quality stability under drought stress. Under simulated drought, grain weight and β-glucan content were dramatically reduced and β-amylase activity was increased, and a lot of metabolites were markedly changed for all genotypes. On the whole, the changes were relatively smaller in the wild barley. Meanwhile, the expressions of Bmy1 related to β-amylase synthesis and GSL1, GSL4 and GSL7 related to β-glucan synthesis were up-regulated and down-regulated under drought stress, respectively, being consistent with the changes of β-amylase activity and β-glucan content in the four barley genotypes. The current results showed that PEG-6000 simulated drought and spike in intro culture may provide the basically similar information on grain development or metabolites as do in the field experiments, and it is suitable for use in studies on the influence of drought stress on quality traits during grain filling stage of barley or other cereal crops.     

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     

Mapping quantitative trait loci for quality factors in an inter-class cross of US and Chinese wheat

Wheat quality factors are critical in determining the suitability of wheat (Triticum aestivum L.) for end-use product and economic value, and they are prime targets for marker-assisted selection. Objectives of this study were to identify quantitative trait loci (QTLs) that ultimately influence wheat market class and milling quality. A population of 132 F₁₂ recombinant inbred lines (RILs) was derived by single-seed descent from a cross between the Chinese hard wheat line Ning7840 and the soft wheat cultivar Clark and grown at three Oklahoma locations from 2001 to 2003. Milling factors such as test weight (volumetric grain weight, TW), kernel weight (KW), and kernel diameter (KD) and market class factors such as wheat grain protein content (GPC) and kernel hardness index (HI) were characterized on the basis of a genetic map constructed from 367 SSR and 241 AFLP markers covering all 21 chromosomes. Composite interval mapping identified eight QTLs for TW, seven for KW, six for KD, two each for GPC and HI measured by near-infrared reflectance (NIR) spectroscopy, and four for HI measured by single kernel characterization system. Positive phenotypic correlations were found among milling factors. Consistent co-localized QTLs were identified for TW, KW, and KD on the short arms of chromosomes 5A and 6A. A common QTL was identified for TW and KD on the long arm of chromosome 5A. A consistent major QTL for HI peaked at the Pinb-D1 locus on the short arm of chromosome 5D and explained up to 85% of the phenotypic variation for hardness. We identified QTLs for GPC on 4B and the short arm of 3A chromosomes. The consistency of quality factor QTLs across environments reveals their potential for marker-assisted selection.     

Analysis of factors influencing milling yield and their association to other traits by QTL analysis in two hexaploid oat populations

Milling yield, or the grain weight from which 100 kg of rolled groats is obtained upon milling, is an important quality characteristic of cultivated oat (Avena sativa L.). Kernel morphology and the groat (caryopsis) percentage of the whole kernel including hull are factors that influence milling yield. We mapped QTLs for kernel area, kernel length, kernel width, and groat percentage in two populations of 137 recombinant inbred lines by RFLP and AFLP analysis to evaluate the prospects of marker-assisted selection (MAS). Phenotypic correlations between kernel morphology traits and groat percentage were not significant. For kernel morphology traits and groat percentage, one to five QTLs were detected, explaining 7.0–60.7% of the total phenotypic variance depending on the trait. One QTL for kernel length in each population and one QTL for kernel width in one population were found at the same location as a QTL for groat percentage, indicating that a change in kernel size or shape could have an influence on groat percentage. The positions and effects of QTLs for kernel morphology and groat percentage were compared to QTLs detected previously for chemical grain composition (oil andβ-glucanconcentration) and agronomic traits to evaluate the selection response on these traits through MAS. Several regions of the oat genome were identified that contained clusters of QTLs influencing two or more traits. While the allele from one parent at a QTL could simultaneously improve two or more traits in one population, it could have opposite effects on the same traits at another QTL or in the other population. Associations among traits were complex and will require careful consideration when employing QTL-marker associations in MAS to avoid negative selection response. Future research to discover candidate genes for those QTL clusters could provide information about trait associations and help in designing selection programs. Received: 17 February 2000 / Accepted: 27 October 2000     

QTL analysis for grain quality traits in 2 BC2F2 populations derived from crosses between Oryza sativa cv Swarna and 2 accessions of O. nivara

The appearance and cooking quality of rice determine its acceptability and price to a large extent. Quantitative trait loci (QTLs) for 12 grain quality traits were mapped in 2 mapping populations derived from Oryza sativa cv Swarna × O. nivara. The BC(2)F(2) population of the cross Swarna × O. nivara IRGC81848 (population 1) was evaluated during 2005 and that from Swarna × O. nivara IRGC81832 (population 2) was evaluated during 2006. Linkage maps were constructed using 100 simple sequence repeat (SSR) markers in population 1 and 75 SSR markers in population 2. In all, 21 QTLs were identified in population 1 (43% from O. nivara) and 37 in population 2 (38% QTLs from O. nivara). The location of O. nivara-derived QTLs mp1.2 for milling percent, kw6.1 for kernel width, and klac12.1 for kernel length after cooking coincided in the 2 populations and appear to be useful for Marker Assisted Selection (MAS). Four QTLs for milling percent, 1 QTL each for amylose content, water uptake, elongation ratio, 2 QTLs for kernel width, and 3 QTLs for gel consistency, each explained more than 20% phenotypic variance. Three QTL clusters for grain quality traits were close to the genes/QTLs for shattering and seed dormancy. QTLs for 4 quality traits were associated with 5 of the 7 major yield QTLs reported in the same 2 mapping populations. Useful introgression lines have been developed for several agronomic traits. It emerges that 40% O. nivara alleles were trait enhancing in both populations, and QTLs for grain quality overlapped with yield meta-QTLs and QTLs for dormancy and seed shattering.     

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