QTL mapping for European corn borer resistance (<Emphasis Type="Italic">Ostrinia nubilalis</Emphasis> Hb.), agronomic and forage quality traits of testcross progenies in early-maturing European maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.) germplasm

In hybrid breeding the performance of lines in hybrid combinations is more important than their performance per se. Little information is available on the correlation between individual line and testcross (TC) performances for the resistance to European corn borer (ECB, Ostrinia nubilalis Hb.) in maize (Zea mays L.). Marker assisted selection (MAS) will be successful only if quantitative trait loci (QTL) found in F₂ derived lines for ECB resistance are still expressed in hybrid combinations. The objectives of our study were: (1) to identify and characterize QTL for ECB resistance as well as agronomic and forage quality traits in a population of testcrossed F_2:3 families; (2) to evaluate the consistency of QTL for per se and TC performances; and (3) to determine the association between per se and TC performances of F_2:3 lines for these traits. Two hundred and four F_2:3 lines were derived from the cross between maize lines D06 (resistant) and D408 (susceptible). These lines were crossed to D171 and the TC progenies were evaluated for ECB resistance and agronomic performance in two locations in 2000 and 2001. Using these TC progenies, six QTL for stalk damage rating (SDR) were found. These QTL explained 27.4% of the genotypic variance in a simultaneous fit. Three QTL for SDR were detected consistently for per se and TC performance. Phenotypic and genotypic correlations were low for per se and TC performance for SDR. Correlations between SDR and quality traits were not significant. Based on these results, we conclude that MAS will not be an efficient method for improving SDR. However, new molecular tools might provide the opportunity to use QTL data as a first step to identify genes involved in ECB resistance. Efficient MAS procedures might then be based on markers designed to trace and to combine specific genes and their alleles in elite maize breeding germplasm.Communicated by G. Wenzel     

Influence of dent corn genetic backgrounds on QTL detection for plant-height traits and their relationships in high-oil maize

QTL mapping for plant-height traits has not been hitherto reported in high-oil maize. A high-oil maize inbred ‘GY220’ was crossed with two dent maize inbreds (‘8984’ and ‘8622’) to generate two connected F_2:3 populations. Four plant-height traits were evaluated in 284 and 265 F_2:3 families. Single-trait QTL mapping and multiple-trait joint QTL mapping was used to detect QTLs for the traits and the genetic relationship between plant height (PH) and two other plant-height traits. A total of 28 QTLs and 12 pairs of digenic interactions among detected QTLs for four traits were detected in the two F_2:3 families. Only one marker was shared between the two populations. Joint analysis of PH with ear height (EH) and PH with top height (TH) detected 32 additional QTLs. Our results showed that QTL detection for PH was dependent on the genetic background of dent corn inbreds. Multiple-trait joint QTL analysis could increase the number of detected QTLs.     

Mapping QTLs for popping ability in a popcorn × flint corn cross

Popping expansion volume (PEV) in popcorn (Zea mays L.) is a distinct heritable character and defined as the ratio of the volume after popping to the volume before popping. PEV is quantitatively inherited and 3–4 genes/quantitative trait loci (QTLs) have been implicated. In the present study, we have dissected the quantitative PEV into two component traits, viz., flake volume (FV) and percent unpopped kernels (UPK), and mapped QTLs using SSR markers for all three traits with 194 F₃ families derived from a popcorn (A-1-6) × flint corn (V273) cross. Heritability (broad sense) estimates for PEV, FV and UPK based on F₃ mean bases were 0.72, 0.54 and 0.68, respectively. The QTL analyses for the three traits based on combined environment data were performed by composite interval mapping using QTL cartographer. Four QTLs were identified for PEV on chromosomes 1, 3, 8 and 10, which together explained 62% of the phenotypic variance (σ²p). Four QTLs were found on chromosomes 1, 5, 9 and 10 for FV (explaining 44% of σ²p) and five QTLs for UPK on chromosomes 1, 3, 4, 5 and 9 (explaining 57% of σ²p). The relative efficiency estimates of marker-based selection in comparison to phenotypic selection for PEV (1.10), FV (1.22) and UPK (1.11) indicated that marker-based selection could be relatively more efficient. The QTL on chromosome 1S for PEV was found to be most significant, where QTLs for hard endosperm starch concentration had been detected earlier. A. Kumar and H.S. Rao contributed equally to this research work.     

Molecular detection of QTLs for agronomic and quality traits in a doubled haploid population derived from two Canadian wheats (Triticum aestivum L.)

Development of high-yielding wheat varieties with good end-use quality has always been a major concern for wheat breeders. To genetically dissect quantitative trait loci (QTLs) for yield-related traits such as grain yield, plant height, maturity, lodging, test weight and thousand-grain weight, and for quality traits such as grain and flour protein content, gluten strength as evaluated by mixograph and SDS sedimentation volume, an F₁-derived doubled haploid (DH) population of 185 individuals was developed from a cross between a Canadian wheat variety “AC Karma” and a breeding line 87E03-S2B1. A genetic map was constructed based on 167 marker loci, consisting of 160 microsatellite loci, three HMW glutenin subunit loci: Glu-A1, Glu-B1 and Glu-D1, and four STS-PCR markers. Data for investigated traits were collected from three to four environments in Manitoba, Canada. QTL analyses were performed using composite interval mapping. A total of 50 QTLs were detected, 24 for agronomic traits and 26 for quality-related traits. Many QTLs for correlated traits were mapped in the same genomic regions forming QTL clusters. The largest QTL clusters, consisting of up to nine QTLs, were found on chromosomes 1D and 4D. HMW glutenin subunits at Glu-1 loci had the largest effect on breadmaking quality; however, other genomic regions also contributed genetically to breadmaking quality. QTLs detected in the present study are compared with other QTL analyses in wheat.     

亚麻主要农艺与品质相关性状的QTL定位

为了全面了解亚麻产量和品质相关性状的遗传基础,为亚麻基因克隆和分子标记辅助育种提供理论依据,在已构建SNP连锁遗传图谱的基础上,以LH-89为父本,R43为母本构建F2:3家系QTL定位群体,用R/QTL软件采用复合区间作图法对13个农艺和品质性状进行QTL定位。结果表明:(1)该研究共检测出35个QTL位点,与粗脂肪及其组成成分相关的QTL有20个,与农艺性状相关的QTL有15个;其中:亚油酸和粗脂肪各5个,亚麻酸、千粒重各4个,棕榈酸、株高、工艺长度各3个,硬脂酸、分枝数各2个,单株果数、果粒数、单株粒重、油酸各1个。(2)共有18个QTL的表型贡献率超10%(主效基因),其中农艺性状定位8个主效基因,品质性状定位10个主效基因。     

Genetic relationships between resistance to stalk-tunneling by the European corn borer and cell-wall components in maize population B73×B52

The objective of this study was to assess the relationships among quantitative trait loci (QTL) detected for European corn borer (ECB) tunneling and cell-wall components (CWC) neutral detergent fiber (NDF), acid detergent fiber (ADF), and acid detergent lignin (ADL) content in leaf-sheath and stalk tissues in a maize recombinant inbred line population derived from inbred lines B73 and B52. Most of the QTL for ECB resistance (10/13) were at QTL positions for one or more CWC. Of the 12 QTL for NDF and ADF in leaf-sheaths, five for each trait were at or near QTL for ECB tunneling. Four of these five QTL for NDF and ADF mapped to common locations. Four of the eight leaf-sheath ADL QTL were detected in the same genomic regions as ECB QTL. For stalk tissue, four regions contained common/overlapping QTL for ECB tunneling, NDF, and ADF. Six such regions were observed for stalk ADL and ECB tunneling. Seven of the ten QTL associated with both CWC and ECB tunneling contributed to the negative correlations observed between these traits, while relatively few QTL effects were positively correlated. This suggests that while CWC contribute to ECB resistance in this population, other mechanisms and other genes also are involved. Several QTL contributing to the negative correlations between ECB tunneling and CWC in the leaf-sheaths mapped to similar positions as QTL detected in tropical maize populations for resistance to leaf-feeding by Diatraea grandiosella Dyar and Diatraea saccharalis Fabricus. These regions may contain genes involved in the synthesis of cellulose, hemicellulose, and lignin in the leaf-blades and leaf-sheaths of maize.     

QTL mapping of resistance to Sporisorium reiliana in maize

We mapped and characterized quantitative trait loci (QTL) for resistance to Sporisorium reiliana. A population of 220 F₃ families produced from the cross of two European elite inbreds (D32, D145) was evaluated with two replications at a French location with high natural incidence of S. reiliana and at a Chinese location employing artificial inoculation. The 220 F₃ families were genotyped with 87 RFLP and seven SSR markers. Using composite interval mapping, we identified two different sets of 3 and 8 QTL for the French and the Chinese locations explaining 13% and 44% of respectively. Individual QTL explained up to 14% of σ^² _p. The 11 QTL mapped to eight maize chromosomes and displayed mostly additive or partial dominant gene action. Significant digenic epistatic interactions were detected for one pair of these QTL. Only a few QTL for S. reiliana were in common with QTL for resistance to Ustilago maydis and Puccinia sorghi, identified at a German location for the same population. Consequently, in our materials resistance to these three fungal pathogens of maize seems to be inherited independently. Received: 14. December 1998 / Accepted: 30 January 1999     

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

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

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

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

Genetic dissection of vegetative propagation traits in Eucalyptus tereticornis and E. globulus

We have detected quantitative trait loci (QTLs) affecting vegetative propagation traits in Eucalyptus tereticornis and Eucalyptus globulus. Using amplified fragment length polymorphism (AFLP) genetic linkage maps, the inheritance of 199 markers was assessed in 94 F₁ individuals with extreme adventitious rooting response, and in 221 randomly chosen F₁ individuals. Phenotypes were scored in 1995 and 1996. QTL analyses were performed using chi-square tests (χ²), single-marker analysis (SMA), interval mapping (IM) and composite interval mapping (CIM). All approaches yielded similar QTL detection results. Three QTLs are hypothesized for mortality (MORT=% dead cuttings), nine for adventitious rooting (ROOT, RCT=% rooted cuttings relative to the surviving or total cuttings, respectively), four for petrification (PETR=% surviving unrooted cuttings), one for sprouting ability (SPR=number of stump sprout cuttings harvested in 1995) and four for the stability of adventitious rooting (STAB=absolute value of the difference ROOT95-ROOT96). All putative QTLs for MORT and PETR were located on the E. tereticornis map, and for SPR and STAB on the E. globulus map. We found different QTLs for MORT, ROOT, RCT, SPR and STAB. Putative QTLs accounted for 2.6–17.0% of the phenotypic variance of a trait (R²). Estimated standardized gene substitution effects varied between 0.13 and 0.49 phenotypic standard deviations (σ_p). These results indicate that the phenotypic variation in these traits has a meaningful genetic component and that stable QTLs can be found in a family of reasonable size where no previous knowledge of the trait was available. Received: 1 September 1998 / Accepted: 24 February 1999     

Identification of quantitative trait loci for agronomically important traits and their association with genic-microsatellite markers in sorghum

The identification of quantitative trait loci (QTLs) affecting agronomically important traits enable to understand their underlying genetic mechanisms and genetic basis of their complex interactions. The aim of the present study was to detect QTLs for 12 agronomic traits related to staygreen, plant early development, grain yield and its components, and some growth characters by analyzing replicated phenotypic datasets from three crop seasons, using the population of 168 F₇ RILs of the cross 296B × IS18551. In addition, we report mapping of a subset of genic-microsatellite markers. A linkage map was constructed with 152 marker loci comprising 149 microsatellites (100 genomic- and 49 genic-microsatellites) and three morphological markers. QTL analysis was performed by using MQM approach. Forty-nine QTLs were detected, across environments or in individual environments, with 1–9 QTLs for each trait. Individual QTL accounted for 5.2–50.4% of phenotypic variance. Several genomic regions affected multiple traits, suggesting the phenomenon of pleiotropy or tight linkage. Stable QTLs were identified for studied traits across different environments, and genetic backgrounds by comparing the QTLs in the study with previously reported QTLs in sorghum. Of the 49 mapped genic-markers, 18 were detected associating either closely or exactly as the QTL positions of agronomic traits. EST marker Dsenhsbm19, coding for a key regulator (EIL-1) of ethylene biosynthesis, was identified co-located with the QTLs for plant early development and staygreen trait, a probable candidate gene for these traits. Similarly, such exact co-locations between EST markers and QTLs were observed in four other instances. Collectively, the QTLs/markers identified in the study are likely candidates for improving the sorghum performance through MAS and map-based gene isolations.     

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

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

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.     

QTL mapping for maize resistance and yield under infestation with Sesamia nonagrioides

The Mediterranean corn borer (MCB) is the most important maize insect pest in the Mediterranean region. The main objective was to map quantitative trait loci (QTL) for yield performance under infestation with MCB, resistance and agronomic traits in a maize RIL population derived from an inbred cross European flint × Reid. Six QTL for resistance traits were located: one QTL for tunnel length (bin 9.03; p = 19.8 %), one QTL for stalk lodging (bin 3.07, p = 11.5 %), and four QTL for ear resistance (bins 1.07, 5.03/5.05, and 8.04; p = 25–63 %). Twelve QTL for agronomic traits were located: a QTL for yield under infestation (bin 5.03, p = 15 %); two QTL for grain moisture (bins 1.07 and 8.05); two QTL for days to anthesis (bin 1.07 and 8.05); two QTL for days to silking (bins 8.04 and 10.02); three QTL for plant height (bins 5.04, 8.05 and 9.03); and two QTL for ear height (bins 8.05 and 9.03). No genetic correlations between yield and other traits were observed. The cross validation (CV) approach showed that the estimation biases for QTL for resistance traits were higher than those for agronomic traits. This work stresses the importance of the region 9.03 for controlling corn borer resistance and suggests the presence of QTL with small effect on ear-resistance traits. At the same genomic region, there are also genes that control plant and ear height and future works could elucidate whether these genes are the same or are closely linked. The QTL for yield seem to play an important role in MCB tolerance in this genetic background. Large biases observed for QTL effects by CV were mainly due to the small sample size used and were higher for resistance traits due to their larger genetic complexity. We consider that it is more appropriate to select for grain yield under infestation instead of selecting for resistance traits because resistance to MCB could have unfavorable associations with agronomic traits.     

QTL‐seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations

The majority of agronomically important crop traits are quantitative, meaning that they are controlled by multiple genes each with a small effect (quantitative trait loci, QTLs). Mapping and isolation of QTLs is important for efficient crop breeding by marker‐assisted selection (MAS) and for a better understanding of the molecular mechanisms underlying the traits. However, since it requires the development and selection of DNA markers for linkage analysis, QTL analysis has been time‐consuming and labor‐intensive. Here we report the rapid identification of plant QTLs by whole‐genome resequencing of DNAs from two populations each composed of 20–50 individuals showing extreme opposite trait values for a given phenotype in a segregating progeny. We propose to name this approach QTL‐seq as applied to plant species. We applied QTL‐seq to rice recombinant inbred lines and F₂ populations and successfully identified QTLs for important agronomic traits, such as partial resistance to the fungal rice blast disease and seedling vigor. Simulation study showed that QTL‐seq is able to detect QTLs over wide ranges of experimental variables, and the method can be generally applied in population genomics studies to rapidly identify genomic regions that underwent artificial or natural selective sweeps.     

Identification and verification of QTLs for agronomic traits using wild barley introgression lines

A set of 39 wild barley introgression lines (hereafter abbreviated with S42ILs) was subjected to a QTL study to verify genetic effects for agronomic traits, previously detected in the BC₂DH population S42 (von Korff et al. 2006 in Theor Appl Genet 112:1221–1231) and, in addition, to identify new QTLs and favorable wild barley alleles. Each line within the S42IL set contains a single marker-defined chromosomal introgression from wild barley (Hordeum vulgare ssp. spontaneum), whereas the remaining part of the genome is exclusively derived from elite spring barley (H. vulgare ssp. vulgare). Agronomic field data of the S42ILs were collected for seven traits from three different environments during the 2007 growing season. For detection of putative QTLs, a two-factorial mixed model ANOVA and, subsequently, a Dunnett test with the recurrent parent as a control were conducted. The presence of a QTL effect on a wild barley introgression was accepted, if the trait value of a particular S42IL was significantly (P < 0.05) different from the control, either across all environments and/or in a particular environment. A total of 47 QTLs were localized in the S42IL set, among which 39 QTLs were significant across all tested environments. For 19 QTLs (40.4%), the wild barley introgression was associated with a favorable effect on trait performance. Von Korff et al. (2006 in Theor Appl Genet 112:1221–1231) mapped altogether 44 QTLs for six agronomic traits to genomic regions, which are represented by wild barley introgressions of the S42IL set. Here, 18 QTLs (40.9%) revealed a favorable wild barley effect on the trait performance. By means of the S42ILs, 20 out of the 44 QTLs (45.5%) and ten out of the 18 favorable effects (55.6%) were verified. Most QTL effects were confirmed for the traits days until heading and plant height. For the six corresponding traits, a total of 17 new QTLs were identified, where at six QTLs (35.3%) the exotic introgression caused an improved trait performance. In addition, eight QTLs for the newly studied trait grains per ear were detected. Here, no QTL from wild barley exhibited a favorable effect. The introgression line S42IL-107, which carries an introgression on chromosome 2H, 17–42 cM is an example for S42ILs carrying several QTL effects simultaneously. This line exhibited improved performance across all tested environments for the traits days until heading, plant height and thousand grain weight. The line can be directly used to transfer valuable Hsp alleles into modern elite cultivars, and, thus, for breeding of improved varieties.     

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

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

Advanced backcross QTL analysis in progenies derived from a cross between a German elite winter wheat variety and a synthetic wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis>L.)

We report here the second advanced backcross quantitative trait locus (AB-QTL) analysis carried out in winter wheat. Seven agronomic traits were studied in a BC₂F₁population derived from a cross between the German winter wheat variety Flair and the synthetic wheat line XX86 developed in Japan. We selected 111 BC₂F₁ lines and genotyped these with 197 microsatellite markers. Field data for seven agronomic traits were collected from corresponding BC₂F₃ families that were grown at up to six locations in Germany. QTL analyses for yield and yield components were performed using single-marker regression and interval mapping. A total of 57 putative QTLs derived from XX86 were detected, of which 24 (42.1%) were found to have a positive effect from the synthetic wheat XX86. These favourable QTLs were mainly associated with thousand-grain weight and grain weight per ear. Many QTLs for correlated traits were mapped in similar chromosomal regions. The AB-QTL data obtained in the present study are discussed and compared with results from previous QTL analyses.     

QTL detection for stover yield and quality traits using two connected populations in high-oil maize

Both yield and quality traits for stover portion were important for forage and biofuel production utility in maize. A high-oil maize inbred GY220 was crossed with two normal-oil dent maize inbred lines 8984 and 8622 to generate two connected F_2:3 populations with 284 and 265 F_2:3 families. Seven yield and quality traits were evaluated under two environments. The variance components of genotype (σ_g²), environment (σ_e²) and genotype × environment interactions (σ_ge²) were all significant for most traits in both populations. Different levels of correlations were observed for all traits. QTL mapping was conducted using composite interval mapping (CIM) for data under each environment and in combined analysis in both populations. Totally, 45 and 42 QTL were detected in the two populations. Only five common QTL across the two populations, and one and three common QTL across the two environments in the two populations were detected, reflecting substantial influence of genetic backgrounds and environments on the results of QTL detection for stover traits. Combined analysis across two environments failed to detect most QTL mapped using individual environmental data in both populations. Few of the detected QTL displayed digenic epistatic interactions. Common QTL among all traits were consistent with their correlations. Some QTL herein have been detected in previous researches, and linked with candidate genes for enzymes postulated to have direct and indirect roles in cell wall components biosynthesis.     

Quantitative trait loci controlling water use efficiency and related traits in Quercus robur L.

Genetic variation for intrinsic water use efficiency (W _i) and related traits was estimated in a full-sib family of Quercus robur L. over 3 years. The genetic linkage map available for this F1 family was used to locate quantitative trait loci (QTL) for W _i, as estimated by leaf carbon stable isotope composition (δ ¹³C) or the ratio of net CO₂ assimilation rate (A) to stomatal conductance to water vapour (g _w) and related leaf traits. Gas exchange measurements were used to standardize estimates of A and g _w and to model the sensitivity of g _w to leaf-to-air vapour pressure deficit (sg^VPD). δ ¹³C varied by more than 3‰ among the siblings, which is equivalent to 40% variation of W _i. Most of the studied traits exhibited high clonal mean repeatabilities (>50%; proportion of clonal mean variability in global variance). Repeatabilities for δ ¹³C, leaf mass per area (LMA) and leaf nitrogen content were higher than 70%. For δ ¹³C, ten QTLs were detected, one of which was detected repeatedly for all 3 years and consistently explained more than 20% of measured variance. Four genomic regions were found in which co-localizing traits linked variation in W _i to variations in leaf chlorophyll and nitrogen content, LMA and sg^VPD. A positive correlation using clonal means between δ ¹³C and A/g _w, as well as a co-localisation of QTL detected for both traits, can be seen as validation of the theoretical model linking the genetic architecture of these two traits.