Quantitative trait loci mapping in five new large recombinant inbred line populations of Arabidopsis thaliana genotyped with consensus single-nucleotide polymorphism markers

Quantitative approaches conducted in a single mapping population are limited by the extent of genetic variation distinguishing the parental genotypes. To overcome this limitation and allow a more complete dissection of the genetic architecture of complex traits, we built an integrated set of 15 new large Arabidopsis thaliana recombinant inbred line (RIL) populations optimized for quantitative trait loci (QTL) mapping, having Columbia as a common parent crossed to distant accessions. Here we present 5 of these populations that were validated by investigating three traits: flowering time, rosette size, and seed production as an estimate of fitness. The large number of RILs in each population (between 319 and 377 lines) and the high density of evenly spaced genetic markers scored ensure high power and precision in QTL mapping even under a minimal phenotyping framework. Moreover, the use of common markers across the different maps allows a direct comparison of the QTL detected within the different RIL sets. In addition, we show that following a selective phenotyping strategy by performing QTL analyses on genotypically chosen subsets of 164 RILs (core populations) does not impair the power of detection of QTL with phenotypic contributions >7%.     

QTL detection in maize testcross progenies as affected by related and unrelated testers

The evaluation of recombinant inbred lines (RILs) per se can be biased by inbreeding depression in case of allogamous species. To overcome this drawback, RILs can be evaluated in combination with testers; however, testers can carry dominant alleles at the quantitative trait loci (QTL), thus hampering their detection. This study was conducted on the maize (Zea mays L.) population of 142 RILs derived from the single cross B73 × H99 to evaluate the role of different testers in affecting: (1) QTL detection, (2) the estimates of their effects, and (3) the consistency of such estimates across testers. Testcrosses (TCs) were produced by crossing RILs with inbred testers B73 [TC(B)], H99 [TC(H)], and Mo17 [TC(M)]. TCs were field tested in three environments. TC(B) mean was higher than TC(H) mean for all traits, while TC(M) mean was the highest for plant vigor traits and grain yield. As to the number of detected QTL, tester Mo17 was superior to H99 and B73 for traits with prevailing additive effects. Several overlaps among the QTL were detected in two or all the three TC populations with QTL effects being almost always consistent (same sign). For traits with prevailing dominance–overdominance effects, as grain yield, the poor performing tester H99 was clearly the most effective; fewer overlaps were found and some of them were inconsistent (different sign). Epistatic interactions were of minor importance. In conclusion, the three testers proved to affect QTL detection and estimation of their effects, especially for traits showing high dominance levels. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Molecular mapping for resistance to pea rust caused by <Emphasis Type="Italic">Uromyces fabae</Emphasis> (Pers.) de-Bary

Pea rust caused by Uromyces fabae (Pers.) de-Bary is a major problem in warm humid regions causing huge economic losses. A mapping population of 136 F_6:7 recombinant inbred lines (RILs) derived from the cross between pea genotypes, HUVP 1 (susceptible) and FC 1 (resistant) was evaluated in polyhouse as well as under field conditions during two consecutive years. Infection frequency (IF) and area under disease progress curve (AUDPC) were used for evaluation of rust reaction of the RILs. A linkage map was constructed with 57 polymorphic loci selected from 148 simple sequence repeats (SSRs), 3 sequence tagged sites (STS), and 2 random amplified polymorphic (RAPD) markers covering 634 cM of genetic distance on the seven linkage groups of pea with an average interval length of 11.3 cM. Composite interval mapping (CIM) revealed one major (Qruf) and one minor (Qruf1) QTL for rust resistance on LGVII. The LOD (5.2–15.8) peak for Qruf was flanked by SSR markers, AA505 and AA446 (10.8 cM), explaining 22.2–42.4% and 23.5–58.8% of the total phenotypic variation for IF and AUDPC, respectively. The minor QTL was environment-specific, and it was detected only in the polyhouse (LOD values 4.2 and 4.8). It was flanked by SSR markers, AD146 and AA416 (7.3 cM), and explained 11.2–12.4% of the total phenotypic variation. The major QTL Qruf was consistently identified across all the four environments. Therefore, the SSR markers flanking Qruf would be useful for marker-assisted selection for pea rust (U. fabae) resistance.     

Selection of a core set of RILs from Forrest × Williams 82 to develop a framework map in soybean

Soybean BAC-based physical maps provide a useful platform for gene and QTL map-based cloning, EST mapping, marker development, genome sequencing, and comparative genomic research. Soybean physical maps for “Forrest” and “Williams 82” representing the southern and northern US soybean germplasm base, respectively, have been constructed with different fingerprinting methods. These physical maps are complementary for coverage of gaps on the 20 soybean linkage groups. More than 5,000 genetic markers have been anchored onto the Williams 82 physical map, but only a limited number of markers have been anchored to the Forrest physical map. A mapping population of Forrest × Williams 82 made up of 1,025 F₈ recombinant inbred lines (RILs) was used to construct a reference genetic map. A framework map with almost 1,000 genetic markers was constructed using a core set of these RILs. The core set of the population was evaluated with the theoretical population using equality, symmetry and representativeness tests. A high-resolution genetic map will allow integration and utilization of the physical maps to target QTL regions of interest, and to place a larger number of markers into a map in a more efficient way using a core set of RILs.     

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

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

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

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

Quantitative trait loci mapping for yield and its components by using two immortalized populations of a heterotic hybrid in Gossypium hirsutum L.

Quantitative trait loci (QTL) mapping provides a powerful tool for unraveling the genetic basis of yield and yield components as well as heterosis in upland cotton. In this research, a molecular linkage map of Xiangzamian 2 (Gossypium hirsutum L.)-derived recombinant inbred lines (RILs) was reconstructed based on increased expressed sequence tag–simple sequence repeat markers. Both the RILs and immortalized F2s (IF2) developed through intermating between RILs were grown under multiple environments. Yield and yield components including seed-cotton yield, lint yield, bolls/plant, boll weight, lint percentage, seed index, lint index and fruit branch number were measured and their QTL were repeatedly identified across environments by the composite interval mapping (CIM) method. From a total of 111 non-redundant QTL, 23 were detected in both two populations. In the meantime, multi-marker joint analyses showed that 16 of these QTL had significant environmental interaction. QTL for correlated traits tended to be collocated and most of the QTL for seed-cotton yield and lint yield were associated with QTL for at least one yield component, consistent with the results observed in correlation analyses. For many QTL with significant additive effects, positive alleles from CRI12, the inferior parent with lower yield performance, were associated with trait improvement. Trait performance of IF2s and the large number of QTL with positive dominant effects implied that dominance plays an important role in the genetic basis of heterosis in Xiangzamian 2 and that non-additive inheritance is also an important genetic mode for lint percentage in the population. These QTL can provide the bases for marker-assisted breeding programs of upland cotton.     

Genotypic variation and chromosomal location of QTLs for somatic embryogenesis revealed by epidermal layers culture of recombinant inbred lines in the sunflower (Helianthus annuus L.)

The present study was conducted to identify the genetic factors controlling somatic embryogenesis in the sunflower. Two traits, the number of embryogenic explants per 40 explants plated (EE/40 E) and the number of embryos per 40 explants (E/40 E), were scored in 74 recombinant inbred lines (RILs) from a cross between ’PAC-2’ and ’RHA-266’. The experiment was designed as a randomized complete block with 76 genotypes (74 recombinant inbred lines and two parents) and three replications. Each replication consisted of three Erlenmeyer flasks with 40 epidermal layers (explants). Analyses of variance indicated the existence of highly significant differences among parental genotypes and their RILs. Heritabilities for the somatic embryogenesis traits studied, EE/40 E and E/40 E, were high (0.64 and 0.77 respectively) and the genetic gain, in percentage of the best parent for 10% of selected RILs, was significant. Four QTLs for EE/40 E (tee) and seven for E/40 E (ete) were detected using composite interval mapping and AFLP mapping. The QTLs for EE/40 E explained 48% of the phenotypic variation while the QTLs for E/40 E explained about 89% of the variation. Received:14 December 1999 / Accepted:18 May 2000     

Mapping of resistance to spot blotch disease caused by Bipolaris sorokiniana in spring wheat

Spot blotch caused by Bipolaris sorokiniana is a destructive disease of wheat in warm and humid wheat growing regions of the world. The development of disease resistant cultivars is considered as the most effective control strategy for spot blotch. An intervarietal mapping population in the form of recombinant inbred lines (RILs) was developed from a cross ‘Yangmai 6’ (a Chinese source of resistance) × ‘Sonalika’ (a spot blotch susceptible cultivar). The 139 single seed descent (SSD) derived F₆, F₇, F₈ lines of ‘Yangmai 6’ × ‘Sonalika’ were evaluated for resistance to spot blotch in three blocks in each of the 3 years. Joint and/or single year analysis by composite interval mapping (CIM) and likelihood of odd ratio (LOD) >2.2, identified four quantitative trait loci (QTL) on the chromosomes 2AL, 2BS, 5BL and 6DL. These QTLs were designated as QSb.bhu-2A, QSb.bhu-2B, QSb.bhu-5B and QSb.bhu-6D, respectively. A total of 63.10% of phenotypic variation was explained by these QTLs based on the mean over years. Two QTLs on chromosomes 2B and 5B with major effects were consistent over 3 years. All QTL alleles for resistance were derived from the resistant parent ‘Yangmai 6’.     

Fine mapping of a resistance gene to bacterial leaf pustule in soybean

Soybean bacterial leaf pustule (BLP) is a prevalent disease caused by Xanthomonas axonopodis pv. glycines. Fine mapping of the BLP resistant gene, rxp, is needed to select BLP resistant soybean cultivars by marker-assisted selection (MAS). We used a total of 227 recombinant inbred lines (RILs) derived from a cross between ‘Taekwangkong’ (BLP susceptible) and ‘Danbaekkong’ (BLP resistant) for rxp fine mapping and two different sets of near isogenic lines (NILs) from Hwangkeumkong × SS2-2 and Taekwangkong × SS2-2 were used for confirmation. Using sequences between Satt372 and Satt486 flanking rxp from soybean genome sequences, eight simple sequence repeats (SSR) and two single nucleotide polymorphism (SNP) markers were newly developed in a 6.2-cM interval. Linkage mapping with the RILs and NILs allowed us to map the rxp region with high resolution. The genetic order of all markers was completely consistent with their physical order. QTL analysis by comparison of the BLP phenotyping data with all markers showed rxp was located between SNUSSR17_9 and SNUSNP17_12. Gene annotation analysis of the 33 kb region between SNUSSR17_9 and SNUSNP17_12 suggested three predicted genes, two of which could be candidate genes of BLP resistance: membrane protein and zinc finger protein. Candidate genes showed high similarity with their paralogous genes, which were located on the duplicated regions obtaining BLP resistance QTLs. High-resolution map in rxp region with eight SSR and two SNP markers will be useful for not only MAS of BLP resistance but also characterization of rxp.     

Identification and characterization of large-effect quantitative trait loci for grain yield under lowland drought stress in rice using bulk-segregant analysis

An F_4:5 population of 490 recombinant inbred lines (RILs) from the cross Apo/^2*Swarna was used to detect quantitative trait loci (QTL) with large effects on grain yield under drought stress using bulk-segregant analysis (BSA). Swarna is an important rainfed lowland rice variety grown on millions of hectares in Asia, but is highly susceptible to drought and aerobic soil conditions. Apo is an aerobic-adapted variety with moderate tolerance to drought. Two rice microsatellite (RM) markers, RM324, and RM416, located on chromosomes 2 and 3, respectively, were shown via BSA to be strongly associated with yield under lowland drought stress. The effects of these QTL were tested in a total of eight hydrological environments over a period of 3 years. The QTL linked to RM416 (DTY _3.1 ) had a large effect on grain yield under severe lowland drought stress, explaining about 31% of genetic variance for the trait (P < 0.0001). It also explained considerable variance for yield under mild stress in lowland conditions and aerobic environments. To our knowledge this is the first reported QTL that has a large effect on yield in both lowland drought and aerobic environments. The QTL linked to RM324 (DTY _2.1 ) had a highly significant effect on grain yield in lowland drought stress (R ² = 13–16%) and in two aerobic trials. The effect of these QTL on grain yield was verified to be not mainly due to phenology differences. Effects of DTY _3.1 on yield under stress have been observed in several other rice mapping populations studied at IRRI. Results of this study indicate that BSA is an effective method of identifying QTL alleles with large effects on rice yield under severe drought stress. The Apo alleles for these large-effect QTL for grain yield under drought and aerobic conditions may be immediately exploited in marker-assisted-breeding to improve the drought tolerance of Swarna.     

Mapping QTL main and interaction influences on milling quality in elite US rice germplasm

Rice (Oryza sativa L.) head-rice yield (HR) is a key export and domestic quality trait whose genetic control is poorly understood. With the goal of identifying genomic regions influencing HR, quantitative-trait-locus (QTL) mapping was carried out for quality-related traits in recombinant inbred lines (RILs) derived from crosses of common parent Cypress, a high-HR US japonica cultivar, with RT0034, a low-HR indica line (129 RILs) and LaGrue, a low-HR japonica cultivar (298 RILs), grown in two US locations in 2005–2007. Early heading increased HR in the Louisiana (LA) but not the Arkansas (AR) location. Fitting QTL-mapping models to separate QTL main and QTL × environment interaction (QEI) effects and identify epistatic interactions revealed six main-effect HR QTLs in the two crosses, at four of which Cypress contributed the increasing allele. Multi-QTL models accounted for 0.36 of genetic and 0.21 of genetic × environment interaction of HR in MY1, and corresponding proportions of 0.25 and 0.37 in MY2. The greater HR advantage of Cypress in LA than in AR corresponded to a genomewide pattern of opposition of HR-increasing QTL effects by AR-specific effects, suggesting a selection strategy for improving this cultivar for AR. Treating year–location combinations as independent environments resulted in underestimation of QEI effects, evidently owing to lower variation among years within location than between location. Identification of robust HR QTLs in elite long-grain germplasm is suggested to require more detailed attention to the interaction of plant and grain development parameters with environmental conditions than has been given to date.     

The Power of QTL Mapping with RILs

QTL (quantitative trait loci) mapping is commonly used to identify genetic regions responsible to important phenotype variation. A common strategy of QTL mapping is to use recombinant inbred lines (RILs), which are usually established by several generations of inbreeding of an F1 population (usually up to F6 or F7 populations). As this inbreeding process involves a large amount of labor, we are particularly interested in the effect of the number of inbreeding generations on the power of QTL mapping; a part of the labor could be saved if a smaller number of inbreeding provides sufficient power. By using simulations, we investigated the performance of QTL mapping with recombinant inbred lines (RILs). As expected, we found that the power of F4 population could be almost comparable to that of F6 and F7 populations. A potential problem in using F4 population is that a large proportion of RILs are heterozygotes. We here introduced a new method to partly relax this problem. The performance of this method was verified by simulations with a wide range of parameters including the size of the segregation population, recombination rate, genome size and the density of markers. We found our method works better than the commonly used standard method especially when there are a number of heterozygous markers. Our results imply that in most cases, QTL mapping does not necessarily require RILs at F6 or F7 generations; rather, F4 (or even F3) populations would be almost as useful as F6 or F7 populations. Because the cost to establish a number of RILs for many generations is enormous, this finding will cause a reduction in the cost of QTL mapping, thereby accelerating gene mapping in many species.     

Mapping QTL for drought stress-induced premature senescence and maturity in cowpea [Vigna unguiculata (L.) Walp.]

Cowpea is an important crop for subsistence farmers in arid regions of Africa, Asia, and South America. Efforts to develop cultivars with improved productivity under drought conditions are constrained by lack of molecular markers associated with drought tolerance. Here, we report the mapping of 12 quantitative trait loci (QTL) associated with seedling drought tolerance and maturity in a cowpea recombinant inbred (RIL) population. One hundred and twenty-seven F₈ RILs developed from a cross between IT93K503-1 and CB46 were screened with 62 EcoR1 and Mse1 primer combinations to generate 306 amplified fragment length polymorphisms for use in genetic linkage mapping. The same population was phenotyped for maintenance of stem greenness (stg) and recovery dry weight (rdw) after drought stress in six greenhouse experiments. In field experiments conducted over 3 years, visual ratings and dry weights were used to phenotype drought stress-induced premature senescence in the RIL population. Kruskall–Wallis and multiple-QTL model mapping analysis were used to identify QTL associated with drought response phenotypes. Observed QTL were highly reproducible between stg and rdw under greenhouse conditions. Field studies confirmed all ten drought-response QTL observed under greenhouse conditions. Regions harboring drought-related QTL were observed on linkage groups 1, 2, 3, 5, 6, 7, 9, and 10 accounting for between 4.7 and 24.2% of the phenotypic variance (R ²). Further, two QTL for maturity (R ² = 14.4–28.9% and R ² = 11.7–25.2%) mapped on linkage groups 7 and 8 separately from drought-related QTL. These results provide a platform for identification of genetic determinants of seedling drought tolerance in cowpea. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Genetic dissection of early-season cold tolerance in sorghum (<Emphasis Type="Italic">Sorghum bicolor</Emphasis> (L.) Moench)

Soil temperatures at 15°C or below limit germination and seedling establishment for warm season cereal crops such as sorghum (Sorghum bicolor (L.) Moench) during early-season planting. To better understand the genetics of early-season cold tolerance in sorghum, mapping of quantitative trait loci (QTL) associated with germination, emergence and vigor using a recombinant inbred mapping population was carried out. A mapping population consisting of 171 F₇–F₈ recombinant inbred lines (RILs) derived from the cross between RTx430 (cold-sensitive) and PI610727 (cold-tolerant) was developed and a genetic map was constructed using 141 microsatellites or simple sequence repeat (SSR) markers. The RILs were evaluated for cold and optimal temperature germinability in the laboratory, field emergence, and seedling vigor in two locations during early-season planting. Two or more QTL were detected for all traits, except for seedling vigor, with only one QTL was detected in the population. A QTL for cold germinability (Germ 12-2.1) showed the highest LOD value and was also associated with optimal germinability. One of the QTL for field emergence, Fearlygerm-9.3, a contribution from PI610727, was found significant in both locations used for the study. This study showed alignment of QTL in SBi1 (Fearlygerm-1.2 and FGerm30-1.2) with previously reported QTL associated with late field emergence identified from a different mapping population. This indicates that PI617027 shares some common loci with other known early-season cold-tolerant sorghum germplasm but also harbors novel QTL that could be useful in introgression of enhanced laboratory germination and early-season field emergence.     

Mapping of post-flowering drought resistance traits in grain sorghum: association between QTLs influencing premature senescence and maturity

The identification of genetic factors underlying the complex responses of plants to drought stress provides a solid basis for improving drought resistance. The stay-green character in sorghum (Sorghum bicolor L. Moench) is a post-flowering drought resistance trait, which makes plants resistant to premature senescence under drought stress during the grainfilling stage. The objective of this study was to identify quantitative trait loci (QTLs) that control premature senescence and maturity traits, and to investigate their association under post-flowering drought stress in grain sorghum. A genetic linkage map was developed using a set of recombinant inbred lines (RILs) obtained from the cross B35 × Tx430, which were scored for 142 restriction fragment length polymorphism (RFLP) markers. The RILs and their parental lines were evaluated for post-flowering drought resistance and maturity in four environments. Simple interval mapping identified seven stay-green QTLs and two maturity QTLs. Three major stay-green QTLs (SGA, SGD and SGG) contributed to 42% of the phenotypic variability (LOD 9.0) and four minor QTLs (SGB, SGI.1, SGI.2, and SGJ) significantly contributed to an additional 25% of the phenotypic variability in stay-green ratings. One maturity QTL (DFB) alone contributed to 40% of the phenotypic variability (LOD 10.0), while the second QTL (DFG) significantly contributed to an additional 17% of the phenotypic variability (LOD 4.9). Composite interval mapping confirmed the above results with an additional analysis of the QTL × Environment interaction. With heritability estimates of 0.72 for stay-green and 0.90 for maturity, the identified QTLs explained about 90% and 63% of genetic variability for stay-green and maturity traits, respectively. Although stay-green ratings were significantly correlated (r=0.22, P ≤ 0.05) with maturity, six of the seven stay-green QTLs were independent of the QTLs influencing maturity. Similarly, one maturity QTL (DFB) was independent of the stay-green QTLs. One stay-green QTL (SGG), however, mapped in the vicinity of a maturity QTL (DFG), and all markers in the vicinity of the independent maturity QTL (DFB) were significantly (P ≤ 0.1) correlated with stay-green ratings, confounding the phenotyping of stay-green. The molecular genetic analysis of the QTLs influencing stay-green and maturity, together with the association between these two inversely related traits, provides a basis for further study of the underlying physiological mechanisms and demonstrates the possibility of improving drought resistance in plants by pyramiding the favorable QTLs. Received: 10 October 1998 / Accepted: 12 July 1999     

Genetic dissection of grain weight in bread wheat through quantitative trait locus interval and association mapping

Genetic dissection of grain weight in bread wheat was undertaken through both genome-wide quantitative trait locus (QTL) interval mapping and association mapping. QTL interval mapping involved preparation of a framework linkage map consisting of 294 loci {194 simple sequence repeats (SSRs), 86 amplified fragment length polymorphisms (AFLPs) and 14 selective amplifications of microsatellite polymorphic loci (SAMPL)} using a bi-parental recombinant inbred line (RIL) mapping population derived from Rye Selection111 × Chinese Spring. Using the genotypic data and phenotypic data on grain weight (GW) of RILs collected over six environments, genome-wide single locus QTL analysis was conducted to identify main effect QTL. This led to identification of as many as ten QTL including four major QTL (three QTL were stable), each contributing >20% phenotypic variation (PV) for GW. The above study was supplemented with association mapping, which allowed identification of 11 new markers in the genomic regions that were not reported earlier to harbour any QTL for GW. It also allowed identification of closely linked markers for six known QTL, and validation of eight QTL reported earlier. The QTL identified through QTL interval mapping and association mapping may prove useful in marker-assisted selection (MAS) for the development of cultivars with high GW in bread wheat.     

A multiparental cross population for mapping QTL for agronomic traits in durum wheat (Triticum turgidum ssp. durum)

Multiparental cross designs for mapping quantitative trait loci (QTL) provide an efficient alternative to biparental populations because of their broader genetic basis and potentially higher mapping resolution. We describe the development and deployment of a recombinant inbred line (RIL) population in durum wheat (Triticum turgidum ssp. durum) obtained by crossing four elite cultivars. A linkage map spanning 2664 cM and including 7594 single nucleotide polymorphisms (SNPs) was produced by genotyping 338 RILs. QTL analysis was carried out by both interval mapping on founder haplotype probabilities and SNP bi‐allelic tests for heading date and maturity date, plant height and grain yield from four field experiments. Sixteen QTL were identified across environments and detection methods, including two yield QTL on chromosomes 2BL and 7AS, with the former mapped independently from the photoperiod response gene Ppd‐B1, while the latter overlapped with the vernalization locus VRN‐A3. Additionally, 21 QTL with environment‐specific effects were found. Our results indicated a prevalence of environment‐specific QTL with relatively small effect on the control of grain yield. For all traits, functionally different QTL alleles in terms of direction and size of genetic effect were distributed among parents. We showed that QTL results based on founder haplotypes closely matched functional alleles at known heading date loci. Despite the four founders, only 2.1 different functional haplotypes were estimated per QTL, on average. This durum wheat population provides a mapping resource for detailed genetic dissection of agronomic traits in an elite background typical of breeding programmes.     

QTL mapping for combining ability in different population-based NCII designs: a simulation study

The NCII design (North Carolina mating design II) has been widely applied in studies of combining ability and heterosis. The objective of our research was to estimate how different base populations, sample sizes, testcross numbers and heritability influence QTL analyses of combining ability and heterosis. A series of Monte Carlo simulation experiments with QTL mapping were then conducted for the base population performance, testcross population phenotypic values and the general combining ability (GCA), specific combining ability (SCA) and Hmp (midparental heterosis) datasets. The results indicated that: (i) increasing the number of testers did not necessarily enhance the QTL detection power for GCA, but it was significantly related to the QTL effect. (ii) The QTLs identified in the base population may be different from those from GCA dataset. Similar phenomena can be seen from QTL detected in SCA and Hmp datasets. (iii) The QTL detection power for GCA ranked in the order of DH(RIL) based > F₂ based > BC based NCII design, when the heritability was low. The recombinant inbred lines (RILs) (or DHs) allows more recombination and offers higher mapping resolution than other populations. Further, their testcross progeny can be repeatedly generated and phenotyped. Thus, RIL based (or DH based) NCII design was highly recommend for combining ability QTL analysis. Our results expect to facilitate selecting elite parental lines with high combining ability and for geneticists to research the genetic basis of combining ability.     

QTL consistency and meta-analysis for grain yield components in three generations in maize

Grain yield is the most important and complex trait in maize. In this study, a total of 258 F₉ recombinant inbred lines (RIL), derived from a cross between dent corn inbred Dan232 and popcorn inbred N04, were evaluated for eight grain yield components under four environments. Quantitative trait loci (QTL) and their epistatic interactions were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL across three generations (RIL, F_2:3 and BC₂F₂) derived from the same cross. In total, 103 QTL, 42 pairs of epistatic interactions and 16 meta-QTL (mQTL) were detected. Twelve out of 13 QTL with contributions (R ²) over 15% were consistently detected in 3–4 environments (or in combined analysis) and integrated in mQTL. Only q100GW-7-1 was detected in all four environments and in combined analysis. 100qGW-1-1 had the largest R ² (19.3–24.6%) in three environments and in combined analysis. In contrast, 35 QTL for 6 grain yield components were detected in the BC₂F₂ and F_2:3 generations, no common QTL across three generations were located in the same marker intervals. Only 100 grain weight (100GW) QTL on chromosome 5 were located in adjacent marker intervals. Four common QTL were detected across the RIL and F_2:3 generations, and two between the RIL and BC₂F₂ generations. Each of five important mQTL (mQTL7-1, mQTL10-2, mQTL4-1, mQTL5-1 and mQTL1-3) included 7–12 QTL associated with 2–6 traits. In conclusion, we found evidence of strong influence of genetic structure and environment on QTL detection, high consistency of major QTL across environments and generations, and remarkable QTL co-location for grain yield components. Fine mapping for five major QTL (q100GW-1-1, q100GW-7-1, qGWP-4-1, qERN-4-1 and qKR-4-1) and construction of single chromosome segment lines for genetic regions of five mQTL merit further studies and could be put into use in marker-assisted breeding.