Quantitative trait loci for grain quality, productivity, morphological and agronomical traits in sorghum (Sorghum bicolor L. Moench)

 Quantitative trait loci (QTLs) for grain quality, yield components and other traits were investigated in two Sorghum caudatum×guinea recombinant inbred line (RIL) populations. A total of 16 traits were evaluated (plant height, panicle length, panicle compactness, number of kernels/panicle, thousand-kernel weight, kernel weight/panicle, threshing percentage, dehulling yield, kernel flouriness, kernel friability, kernel hardness, amylose content, protein content, lipid content, germination rate and molds during germination and after harvest) and related to two 113- and 100-point base genetic maps using simple (SIM) and composite (CIM) interval mapping. The number, effects and relative position of QTLs detected in both populations were generally in agreement with the distributions, heritabilities and correlations among traits. Several chromosomal segments markedly affected multiple traits and were suspected of harbouring major genes. The positions of these QTLs are discussed in relation to previously reported studies on sorghum and other grasses. Many QTLs, depending on their relative effects and position, could be used as targets for marker-assisted selection and provide an opportunity for accelerating breeding programmes. Received: 14 February 1998 / Accepted: 4 March 1998     

Inferences regarding the numbers and locations of QTLs under multiple-QTL models using interval mapping and composite interval mapping

This paper examines the properties of likelihood maps generated by interval mapping (IM) and composite interval mapping (CIM), two widely used methods for detecting quantitative trait loci (QTLs). We evaluate the usefulness of interpretations of entire maps, rather than only evaluating summary statistics that consider isolated features of maps. A simulation study was performed in which traits with varying genetic architectures, including 20-40 QTLs per chromosome, were examined with both IM and CIM under different marker densities and sample sizes. IM was found to be an unreliable tool for precise estimation of the number and locations of individual QTLs, although it has greater power for simply detecting the presence of QTLs than CIM. The ability of CIM to resolve the correct number of QTLs and to estimate their locations correctly is good if there are three or fewer QTLs per 100 centiMorgans, but can lead to erroneous inferences for more complex architectures. When the underlying genetic architecture of a trait consists of several QTLs with randomly distributed effects and locations likelihood profiles were often indicative of a few underlying genes of large effect. Studies that have detected more than a few QTLs per chromosome should be interpreted with caution.     

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

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

Characterization and molecular mapping of genes determining semidwarfism in barley

The semidwarf trait is desired in cereal breeding programs for increased lodging resistance. We characterized 27 brachytic (brh) semidwarf mutants in barley (Hordeum vulgare L.) and located the genes on barley chromosome linkage maps. All brachytic genes were transferred into the two-rowed cultivar Bowman by backcrossing four to seven times and selecting for semidwarf plants. The brachytic lines were evaluated for 10 phenotypic traits: plant height, awn, peduncle, and rachis internode length, leaf length and width, lodging, grain yield, number of kernels per spike, and kernel weight. We intercrossed the lines to determine which mutants were at independent loci and which were alleles at the same locus. F2 populations from 18 brh semidwarfs were constructed for genetic mapping using simple sequence repeat (SSR) markers. The brachytic semidwarf near-isogenic lines were significantly shorter than their normal counterparts and most had lower yields (16/27); shorter awns (26/27), peduncles (26/27), and rachis internodes (24/27); and reduced kernel weight (22/27). Twelve of the lines had shorter penultimate leaves and 15 had reduced lodging. Four lines had increased kernels per spike, while one had fewer kernels per spike. Allelism tests and mapping comparisons indicated that the 27 semidwarfs comprise 18 independent genetic loci. SSR mapping placed these loci in five of the seven barley chromosomes. Knowledge of the effects and locations of these brachytic semidwarf genes will help barley breeders select appropriate lines for barley improvement.     

Mapping of QTLs governing agronomic and yield traits in chickpea

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

Relationship between QTLs for preharvest sprouting and alpha-amylase activity in rye grain

Preharvest sprouting (PHS) and high alpha-amylase activity (AA) negatively affect quality of rye grain. The objective of this study was to reveal genetic relationship between PHS and AA by developing a consensus map of QTLs controlling each trait. A method of composite interval mapping (CIM) was used to search for QTLs within the 541 × Ot1-3 and DS2 × RXL10 F₂ mapping populations representing wide variation range of both traits. Sixteen QTLs for AA were detected on chromosomes 1R (3), 2R (2), 3R (2), 4R (3), 5R (3), 6R (2) and 7R (1). Their distribution was not random showing a tendency of QTL location in distal regions of chromosomes. Nine QTLs for AA located on chromosome arms 1RS, 2RL, 3RS, 4RL, 5RS, 5RL, 6RS, 6RL and 7RS coincided with QTLs for PHS. Seven QTLs for AA independent from PHS were detected on chromosome arms 1RL (2), 2RS, 3RL, 4RS, 4RL and 5RL. Four QTLs for PHS not associated with those for AA were identified on chromosomes 1RL, 2RL, 5RL and 7RL. Partial overlapping of the genetic systems controlling AA and PHS suggests that alpha-amylase found in sound grain of rye could be produced through at least three independent mechanisms i.e. PHS at its initial stage, late maturity alpha-amylase (LMA) and/or retained pericarp alpha-amylase (RPAA). Six QTLs co-located on both maps were found on chromosome arms 1RS, 2RS, 5RS, 5RL, 6RS and 6RL. Valuable features of line Ot1-3 i.e. resistance to preharvest sprouting and low alpha-amylase production in ripening grain can be attributed to seven major QTLs from chromosomes 1RL, 2RL, 5RL (2), 6RL and 7R (2). This set of QTLs, identified in line Ot1-3, might be useful in breeding sprouting resistant cultivars of rye.     

Genetic mapping of the ScHd1 gene in rye and an assessment of its relationship with earliness per se and plant morphology

A fragment of the ScHd1 gene derived from eight inbred lines was sequenced and showed homology to other Hd1 genes from different cereals. Sequences were analysed with respect to the presence of a single-nucleotide polymorphism (SNP) difference. A C-T transition at position 312 of the consensus sequence was found, which distinguished two lines from the remaining six. The deduced amino acid sequence revealed a high identity (93%) to a Hd1-like protein from wheat. The identified mutation allowed the localisation of ScHd1 on a genetic map of rye (6RS). A small, statistically significant linkage between ScHd1 and earliness per se (eps) and some morphological traits was also established. The chromosomal region, including the S76 allele for the ScHd1 gene was linked to earlier heading, elongated spikes, a greater number of spikelets per spike and an increased weight of 1000 kernels.     

Advanced backcross QTL analysis of a hard winter wheat × synthetic wheat population

Advanced backcross quantitative trait locus (AB-QTL) analysis was used to identify QTLs for yield and yield components in a backcross population developed from a cross between hard red winter wheat (Triticum aestivum L.) variety Karl 92 and the synthetic wheat line TA 4152-4. Phenotypic data were collected for agronomic traits including heading date, plant height, kernels per spike, kernel weight, tiller number, biomass, harvest index, test weight, grain yield, protein content, and kernel hardness on 190 BC₂F_2:4 lines grown in three replications in two Kansas environments. Severity of wheat soilborne mosaic virus (WSBMV) reaction was evaluated at one location. The population was genotyped using 151 microsatellite markers. Of the ten putative QTLs identified, seven were located on homoeologous group 2 and group 3 chromosomes. The favorable allele was contributed by cultivated parent Karl 92 at seven QTLs including a major one for WSBMV resistance, and by the synthetic parent at three QTLs: for grain hardness, kernels per spike, and tiller number. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.     

Influence of wheat and rye parents on agronomic characters in primary hexaploid and octoploid triticale

Summary Thirty-five hexaploid and twenty octoploid primary triticales (xTriticosecale Wittmack) derived from homozygous wheat and rye inbred lines were used (1) to investigate the parental wheat, rye, and interaction effects and (2) to estimate quantitative genetic parameters for agronomic traits. The winter triticales were tested in four environments in a three-replicate split-plot design with drilled 1 m² plots. Superior performance of hexaploid triticales as compared to the octoploids was revealed. Substantial genetic variation and high heritability estimates were found for nearly all of the characters investigated. Estimates of wheat, rye, and wheat×rye interaction variance components disclosed parental main effects to be the most important source of genetic variation in primary triticales. The rye parent was dominant for all characters affecting fertility, and the wheat parent was more important for vegetative development. Character correlations were very similar for triticales of both ploidy levels. The lack of association between grain yield and tillering and the positive correlation between kernels per spike and thousand kernel weight indicated physiological disorders specific for primary triticales.     

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.     

Mapping QTLs and meta-QTLs for two inflorescence architecture traits in multiple maize populations under different watering environments

Drought significantly affects the architectural development of maize inflorescence, which leads to massive losses in grain yield. However, the genetic mechanism for traits involved in inflorescence architecture in different watering environments, remains poorly understood in maize. In this study, 19 QTLs for tassel primary branch number (TBN) and ear number per plant (EN) were detected in 2 F_2:3 populations under both well-watered and water-stressed environments by single environment mapping with composite interval mapping (CIM); 11/19 QTLs were detected under water-stressed environments. Moreover, 21 QTLs were identified in the 2 F_2:3 populations by joint analysis of all environments with a mixed linear model based on composite interval mapping (MCIM), 11 QTLs were involved in QTL × environment interactions, seven epistatic interactions were identified with additive by additive/dominance effects. Remarkably, 12 stable QTLs (sQTLs) were simultaneously detected by single environment mapping with CIM and joint analysis through MCIM, which were concentrated in ten bins across the chromosomes: 1.05_1.07, 1.08_1.10, 2.01_2.04, 3.01, 4.06, 4.09, 5.06_5.07, 6.05, 7.00, and 7.04 regions. Twenty meta-QTLs (mQTLs) were detected across 19 populations under 51 watering environments using a meta-analysis, and 34 candidate genes were predicted in corresponding mQTLs regions to be involved in the regulation of inflorescence development and drought resistance. Therefore, these results provide valuable information for finding quantitative trait genes and to reveal the genetic mechanisms responsible for TBN and EN under different watering environments. Furthermore, alleles for TBN and EN provide useful targets for marker-assisted selection to generate high-yielding maize varieties.     

QTLs of cold tolerance-related traits at the booting stage for NIL-RILs in rice revealed by SSR

QTLs for cold tolerance-related traits at the booting stage using balanced population for 1525 recombinant inbred lines of near-isogenic lines (viz.NIL-RILs for BC5F3 and BC₅F₄ and BC₅F₅) over 3 years and two locations by backcrossing the strongly cold-tolerant landrace (Kunmingxiaobaigu) and a cold-sensitive cultivar (Towada) was analyzed. In this study, 676 microsatellite markers were employed to identify QTLs conferring cold tolerance at booting stage. Single marker analysis revealed that 12 markers associated with cold tolerance on chromosome 1, 4 and 5. Using a LOD significance threshold of 3.0,compositive interval mapping based on a mixed linear model revealed eight QTLs for 10 cold tolerance-related traits on chromosomes 1, 4, and 5. They were tentatively designatedqCTB-1-1, qCTB-4-1, qCTB-4-2, qCTB-4-3, qCTB-4-4, qCTB-4-5, qCTB-4-6, andqCTB-5-1. The marker intervals of them were narrowed to 0.3-6.8 cM. Genetic distances between the peaks of the QTL and nearest markers varied from 0 to 0.04 cM. We were noticed in some traits associated cold tolerance, such asqCTB-1-1 for 5 traits (plant height, panicle exsertion, spike length, blighted grains per spike and spikelet fertility),qCTB-4-1 for 8 traits (plant height, node length under spike, leaf length, leaf width, spike length, full grains per spike, total grains per spike and spikelet fertility),qCTB-4-2 for 3 traits (spike length, full grains per spike and spikelet fertility),qCTB-5-1 for 5 traits (plant height, panicle exsertion, blighted grains per spike, full grains per spike and spikelet fertility). The variance explained by a single QTL ranged from 0.80 to 16.80%. Three QTLs (qCTB-1-1, qCTB-4-1, qCTB-4-2) were detected in two or more trials. Our study sets a foundation for cloning cold-tolerance genes and provides opportunities to understand the mechanism of cold tolerance at the booting stage.     

Quantitative trait loci for low aflatoxin production in two related maize populations

Aflatoxin B(1) formed by Aspergillus flavus Fr:Link has been associated with animal disease and liver cancer in humans. We performed genetic studies in progenies derived from maize inbred Tex6, associated with relatively low levels of aflatoxin production, crossed with the historically important inbred B73. (Tex6 x B73) x B73 BC(1)S(1) and Tex6 x B73 F(2:3) mapping populations were produced and evaluated in 1996 and 1997 in Champaign, Ill. Ears were inoculated 20 to 24 days after midsilk using a pinboard method and a mixture of conidia of A. flavus Link:Fr. isolates. Aflatoxin B(1) levels in harvested ears were determined using an indirect competitive ELISA. Molecular markers were assayed on the populations and used to generate maps. Molecular marker - QTL associations for lower levels of aflatoxin production were determined using multiple regression (MR) and composite interval analysis with multiple regression (CIM MR). MR revealed sets of markers associated with lower aflatoxin production in 1996 and 1997, and CIM MR detected a smaller subset of loci significant in 1997. QTLs for lower aflatoxin were attributed to both Tex6 and B73 parental sources. Environment strongly influenced the detection of QTLs for lower aflatoxin production in different years. There were very few chromosome regions associated with QTLs in more than 1 year or population with MR analysis, and none with CIM MR analysis. In 1997, QTLs for lower aflatoxin were detected with CIM MR in bins 5.01-2 and 5.04-5 in the BC(1)S(1) population, and in bins 3.05-6, 4.07-8 and 10.05-10.07 in the F(2:3) population. These QTL associations appear the most promising for further study.     

Genome dissection of traits related to domestication in azuki bean (Vigna angularis) and comparison with other warm-season legumes

BACKGROUND: The objective of this study was to dissect into quantitative trait loci (QTLs) the large morphological and physiological differences between cultivated azuki bean (Vigna angularis) and a wild relative and to infer the commonalities of the QTLs for domestication-related traits across the Asian Vigna and with other warm-season legumes. METHODS: Two linkage maps, for the BC(1)F(1) and F(2) populations, respectively, from the same cross between azuki bean and V. nepalensis were developed. Using these linkage maps QTLs for 33 domestication-related traits were analysed and mapped. The location of mapped QTLs was compared with locations of similar QTLs in other warm-season legumes. KEY RESULTS: QTLs were detected for seed-, pod-, stem- and leaf-related traits. Most traits were controlled by between two and nine QTLs but several traits, such as pod dehiscence, were controlled by single genes. QTLs for domestication-related traits were restricted to particular regions of the azuki bean genome, especially linkage groups 1, 2, 4, 7 and 9. Linkage groups 1 and 2 had QTLs for a suite of traits including pod size, germination, seed size and lower stem length. QTLs on linkage groups 7 and 9 were associated with upper stem length, maximum leaf size and pod and seed size. Pleiotropy or close linkage of genes for domestication-related traits is suggested in these regions. While some QTLs are common to azuki bean and other warm-season legumes, many are recorded for the first time in azuki bean. CONCLUSIONS: QTLs for a large number of domestication-related traits have been mapped for the first time in azuki bean. QTLs with unexpected effect and new QTLs for traits such as seed size have been found. The results provide a foundation that will be useful for improvement of azuki bean and related legumes.     

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.     

RFLP mapping of QTLs for yield and related characters in rice (Oryza sativa L.)

Quantitative triat loci (QTLs) for yield and related traits in rice were mapped based on RFLP maps from two indica/indica F₂ populations, Tesanai 2/CB and Waiyin 2/CB. In Tesanai 2/CB, 14 intervals carrying QTLs for eight traits were detected, including 3 for grain weight per plant (GWT), 2 for number of panicles per plant (NP), 2 for number of grains per panicle (NG), 1 for total number of spikelets per panicle (TNS), 1 for spikelet fertility (SF), 3 for 1000-grain weight (TGWT), 1 for spikelet density (SD), and 1 for number of first branches per main panicle. The 3 QTLs for GWT were located on chromosomes 1, 2, and 4, with 1 in each chromosome. The additive effect of the single locus ranged from 2.0 g to 9.1 g. A major gene (np4) for NP was detected on chromosome 4 within the interval of RG143–RG214, about 4cM for RG143, and this locus explained 26.1% of the observed phenotypic variance for NP. The paternal allele of this locus was responsible for reduced panicles per plant (3 panicles per plant). In another population, Waiyin 2/CB, 12 intervals containing QTLs for six of the above-mentioned traits were detected, including 3 for GWT, 2 for each of NP, TNS, TGWT and SD, 1 for SF. Three QTLs for GWT were located on chromosome 1, 4, and 5, respectively. The additive effect of the single locus for GWT ranged from 6.7 g to 8.8 g, while the dominance effect was 1.7–11.5 g. QTL mapping in two populations with a common male parent is compared and discussed.     

Quantitative trait loci for yield and related traits in the wheat population Ning7840 × Clark

Grain yield and associated agronomic traits are important factors in wheat (Triticum aestivum L.) improvement. Knowledge regarding the number, genomic location, and effect of quantitative trait loci (QTL) would facilitate marker-assisted selection and the development of cultivars with desirable characteristics. Our objectives were to identify QTLs directly and indirectly affecting grain yield expression. A population of 132 F₁₂ recombinant inbred lines (RILs) was derived by single-seed descent from a cross between the Chinese facultative wheat Ning7840 and the US soft red winter wheat Clark. Phenotypic data were collected for 15 yield and other agronomic traits in the RILs and parental lines from three locations in Oklahoma from 2001 to 2003. Twenty-nine linkage groups, consisting of 363 AFLP and 47 SSR markers, were identified. Using composite interval mapping (CIM) analysis, 10, 16, 30, and 14 QTLs were detected for yield, yield components, plant adaptation (shattering and lodging resistance, heading date, and plant height), and spike morphology traits, respectively. The QTL effects ranged from 7 to 23%. Marker alleles from Clark were associated with a positive effect for the majority of QTLs for yield and yield components, but gene dispersion was the rule rather than the exception for this RIL population. Often, QTLs were detected in proximal positions for different traits. Consistent, co-localized QTLs were identified in linkage groups 1AL, 1B, 4B, 5A, 6A, and 7A, and less consistent but unique QTLs were identified on 2BL, 2BS, 2DL, and 6B. Results of this study provide a benchmark for future efforts on QTL identification for yield traits.     

Comparison of molecular linkage maps and QTLs for morphological traits in two reciprocal backcross populations of rice

Comparison of maps and QTLs between populations may provide us with a better understanding of molecular maps and the inheritance of traits. We developed and used two reciprocal BC1F1 populations, IP/DS//IP and IP/DS//DS, for QTL analysis. DS (Dasanbyeo) is a Korean tongil-type cultivar (derived from an indica x japonica cross and similar to indica in its genetic make-up) and IP (Ilpumbyeo) is a Korean japonica cultivar. We constructed two molecular linkage maps corresponding to each backcross population using 196 markers for each map. The length of each chromosome was longer in the IP/DS//IP population than in the IP/DS//DS population, indicating that more recombinants were produced in the IP/DS//IP population. Distorted segregation was observed for 44 and 19 marker loci for the IP/DS//IP and IP/DS//DS populations, respectively; these were mostly skewed in favor of the indica alleles. A total of 36 main effect QTLs (M-QTLs) and 15 digenic epistatic interactions (E-QTLs) were detected for the seven traits investigated. The phenotypic variation explained (PVE) by M-QTLs ranged from 3.4% to 88.2%. Total PVE of the M-QTLs for each trait was significantly higher than that of the E-QTLs. The total number of M-QTLs identified in the IP/DS//IP population was higher than in the IP/DS//DS population. However, the total PVE by the M-QTLs and E-QTLs together for each trait was similar in the two populations, suggesting that the two BC1F1 populations are equally useful for QTL analysis. Maps and QTLs in the two populations were compared. Eleven new QTLs were identified for SN, SF, GL, and GW in this study, and they will be valuable in marker-assisted selection, particularly for improving grain traits in tongil-type varieties.     

Comparative QTL analysis of early short-time drought tolerance in Polish fodder and malting spring barleys

Key message

An effective approach for the further evolution of QTL markers, may be to create mapping populations for locally adapted gene pools, and to phenotype the studied trait under local conditions.

Abstract

Mapping populations of Polish fodder and malting spring barleys (Hordeum vulgare L.) were used to analyze traits describing short-time drought response at the seedlings stage. High-throughput genotyping (Diversity Array Technology (DArT) markers) and phenotyping techniques were used. The results showed high genetic diversity of the studied populations which allowed the creation of high-density linkage maps. There was also high diversity in the physiological responses of the barleys. Quantitative trait locus (QTL) analysis revealed 18 QTLs for nine physiological traits on all chromosomes except 1H in malting barley and 15 QTLs for five physiological traits on chromosomes 2H, 4H, 5H and 6H in fodder barley. Chromosomes 4H and 5H contained QTLs which explained most of the observed phenotypic variations in both populations. There was a major QTL for net photosynthetic rate in the malting barley located on chromosome 5H and two major QTLs for overall photochemical performance (PI) located on 5H and 7H. One major QTL related to photochemical quenching of chlorophyll fluorescence was located on chromosome 4H in fodder barley. Three QTL regions were common to both mapping populations but the corresponding regions explained different drought-induced traits. One region was for QTLs related to PSII photosynthetic activity stress index in malting barley, and the corresponding region in fodder barley was related to the water content stress index. These results are in accordance with previous studies which showed that different traits were responsible for drought tolerance variations in fodder and malting barleys.     

大穗型和中穗型小麦品种光合特性的差异及其与粒重和产量的关系

选择大穗大粒型品种914391、鲁麦22（L22）和中穗中粒型品种济南17（J17）、鲁麦18（L18）,研究了不同穗粒型品种光合特性的差异及其与粒重和产量的关系。结果表明,大穗大粒型品种914391和Ｌ2叶光合速率、旗叶磷酸蔗糖合成酶活性显著高于中穗中粒型品种J17和L18,前者的单茎干重和开花后单茎、茎＋叶鞘、颖壳＋轴等器官的干物质向籽粒的转移量显著大于后者,为最终获得较高的单粒重和穗粒重奠定物质基础;中穗中粒型品种J17和L18的单位土地面积的穗数显著高于大穗大粒型品种914391和Ｌ2,以单位土地面积上旗叶平均光合速率与单茎数的乘积表示群体旗叶光合强度,J17和L18的群体旗叶光合强度、生物产量和经济系数均显著高于914391、L22,这是它们籽粒产量高的重要原因之了。