Analysis of quantitative trait loci underlying the traits related to chlorophyll content of the flag leaf in rice

A population of 117 doubled haploid (DH) lines derived from the cross of Zhaiyeqing 8 (indica) x Jingxi 17 (japonica) was employed to map quantitative trait loci (QTL) underlying four physiological traits related to chlorophyll contents of the flag leaf. There were significantly positive correlations among chlorophyll a, chlorophyll b and chlorophyll a+ b content. Chlorophyll a/b ratio was significantly negatively correlated with chlorophyll b content. These four traits were normally distributed with transgressive segregation, suggesting that they were controlled by multiple minor genes. A total of 11 QTLs were detected for the four traits and they lay on six chromosomes. Each of them explained 9.2%-19.6% of the phenotypic variations, respectively. Of these, two QTLs controlling chlorophyll a content were mapped on chromosomes 2 and 5; four QTLs underlying chlorophyll b content were mapped on chromosomes 2, 3, 5 and 9; three QTLs underlying chlorophyll a+b amount were mapped on chromosomes 3, 5 and 9; two QTLs under-lying chlorophyll a/b ratio were mapped on chromosomes 6 and 1 1. The intrinsic relationship among the four traits and the practical implication in rice breeding are discussed.     

QTL analysis of leaf morphology in tetraploid Gossypium (cotton)

Molecular markers were used to map and characterize quantitative trait loci (QTLs) determining cotton leaf morphology and other traits, in 180 F₂ plants from an interspecific cross between a Gossypium hirsutum genotype carrying four morphological mutants, and a wild-type Gossypium barbadense. The prominent effects of a single region of chromosome 15, presumably the classical ”Okra-leaf” locus, were modified by QTLs on several other chromosomes affecting leaf size and shape. For most traits, each parent contained some alleles with positive effects and others with negative effects, suggesting a large potential for adapting leaf size and shape to the needs of particular production regimes. Twenty one QTLs/loci were found for the morphological traits at LOD≥3.0 and P≤0.001, among which 14 (63.6%) mapped to D-subgenome chromosomes. Forty one more possible QTLs/loci were suggested with 2.0≤LOD<3.0 and 0.001<P≤0.01. Among all of the 62 possible QTLs (found at LOD≥2.0 and P≤0.01) for the 14 morphological traits in this study, 38 (61.3%) mapped to D-subgenome chromosomes. This reinforces the findings of several other studies in suggesting that the D-subgenome of tetraploid cotton has been subject to a relatively greater rate of evolution than the A-subgenome, subsequent to polyploid formation. Received: 26 April 1999 / Accepted: 30 July 1999     

Analysis of quantitative trait loci affecting chlorophyll content of rice leaves in a double haploid population and two backcross populations

Chlorophyll content, one of the most important physiological parameters related to plant photosynthesis, is usually used to predict yield potential. To map the quantitative trait loci (QTLs) underlying the chlorophyll content of rice leaves, a double haploid (DH) population was developed from an indica/japonica (Zhenshan 97/Wuyujing 2) crossing and two backcross populations were established subsequently by backcrossing DH lines with each of their parents. The contents of chlorophyll a and chlorophyll b were determined by using a spectrophotometer to directly measure the leaf chlorophyll extracts. To determine the leaf chlorophyll retention along with maturation, all measurements were performed on the day of heading and were repeated 30 days later. A total of 60 QTLs were resolved for all the traits using these three populations. These QTLs were distributed on 10 rice chromosomes, except chromosomes 5 and 10; the closer the traits, the more clustering of the QTLs residing on common rice chromosomal regions. In general, the majority of QTLs that specify chlorophyll a content also play a role in determining chlorophyll b content. Strangely, chlorophyll content in this study was found mostly to be lacking or to have a negative correlation with yield. In both backcross F₁ populations, overdominant (or underdominant) loci were more important than complete or partially dominant loci for main-effect QTLs and epistatic QTLs, thereby supporting previous findings that overdominant effects are the primary genetic basis for depression in inbreeding and heterosis in rice.     

Genetic dissection of sex determinism, inflorescence morphology and downy mildew resistance in grapevine

A genetic linkage map of grapevine was constructed using a pseudo-testcross strategy based upon 138 individuals derived from a cross of Vitis vinifera Cabernet Sauvignon × Vitis riparia Gloire de Montpellier. A total of 212 DNA markers including 199 single sequence repeats (SSRs), 11 single strand conformation polymorphisms (SSCPs) and two morphological markers were mapped onto 19 linkage groups (LG) which covered 1,249 cM with an average of 6.7 cM between markers. The position of SSR loci in the maps presented here is consistent with the genome sequence. Quantitative traits loci (QTLs) for several traits of inflorescence and flower morphology, and downy mildew resistance were investigated. Two novel QTLs for downy mildew resistance were mapped on linkage groups 9 and 12, they explain 26.0–34.4 and 28.9–31.5% of total variance, respectively. QTLs for inflorescence morphology with a large effect (14–70% of total variance explained) were detected close to the Sex locus on LG 2. The gene of the enzyme 1-aminocyclopropane-1-carboxylic acid synthase, involved in melon male organ development and located in the confidence interval of all QTLs detected on the LG 2, could be considered as a putative candidate gene for the control of sexual traits in grapevine. Co-localisations were found between four QTLs, detected on linkage groups 1, 14, 17 and 18, and the position of the floral organ development genes GIBBERELLIN INSENSITIVE1, FRUITFULL, LEAFY and AGAMOUS. Our results demonstrate that the sex determinism locus also determines both flower and inflorescence morphological traits.     

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.     

Mapping of main and epistatic effect QTLs associated to grain protein and gluten strength using a RIL population of durum wheat

Quality, specifically protein content and gluten strength are among the main objectives of a durum wheat breeding program. The aim of this work was to validate quantitative trait loci (QTLs) associated with grain protein content (GPC) and gluten strength measured by SDS sedimentation volume (SV) and to find additional QTLs expressed in Argentinean environments. Also, epistatic QTL and QTL x environmental interactions were analyzed. A mapping population of 93 RILs derived from the cross UC1113 x Kofa showing extreme values in gluten quality was used. Phenotypic data were collected along six environments (three locations, two years). Main effect QTLs associated with GPC were found in equivalent positions in two environments on chromosomes 3BS (R² = 21.0-21.6%) and 7BL (R² = 12.1-13%), and in one environment on chromosomes 1BS, 2AL, 2BS, 3BL, 4AL, 5AS, 5BL and 7AS. The most important and stable QTL affecting SV was located on chromosome 1BL (Glu-B1) consistently detected over the six environments (R² = 20.9- 54.2%). Additional QTLs were found in three environments on chromosomes 6AL (R² = 6.4-12.5%), and in two environments on chromosomes 6BL (R² = 11.5-12.1%), 7AS (R² = 8.2-10.2%) and 4BS (R² = 11–16.4%). In addition, pleiotropic effects were found affecting grain yield, test weight, thousand-kernel- weight and days to heading in some of these QTLs. Epistatic QTLs and QTL x environment interactions were found for both quality traits, mostly for GPC. The flanking markers of the QTLs detected in this work could be efficient tools to select superior genotypes for the mentioned traits.     

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.     

玉米叶绿素含量的QTL定位

为了探讨玉米叶绿素含量的遗传规律, 以A150-3-2×Mo17杂交组配的189个F2单株作为作图群体, 构建了具有112个标记位点的玉米分子遗传图谱, 于喇叭口期和开花期分别进行了玉米叶绿素a含量(chla), 叶绿素b含量(chlb), 其他叶绿素含量(chlc)和叶绿素总含量(chlz)4个性状的测定, 并进行QTL分析。在喇叭口期和开花期共检测到32个QTL, 分布在除第6和10染色体以外的其他染色体上。在喇叭口期检测到24个QTL, 分布于第1、2、3、5、7、8和9染色体上, 叶绿素a、叶绿素b、其他叶绿素和叶绿素总含量各检测到6个QTL, 在同一区间内检测到的4个性状的QTL之间的距离在0~2 cM之间。喇叭口期检测到控制叶绿素a、叶绿素b、其他叶绿素和叶绿素总含量的4个主效QTL位于第5染色体上的umc1098~bnlg557区间, 分别可解释表型变异的11.63%、10.3%、10.77%和11.51%。开花期检测到8个QTL, 分布于第4和5染色体上。其中叶绿素a、叶绿素b、其他叶绿素和叶绿素总含量各2个QTL。标记umc1098和bnlg557之间同时存在控制喇叭口期4个叶绿素含量性状的QTL和开花期控制叶绿素a和叶绿素b的QTL。标记umc2308和bnlg386之间只存在控制开花期4个叶绿素含量性状的QTL。     

Genetic architecture of adiposity in the cross of LG/J and SM/J inbred mice

The genetic basis of variation in obesity in human populations is thought to be owing to many genes of relatively small effect and their interactions. The LG/J by SM/J intercross of mouse inbred strains provides an excellent model system in which to investigate multigenic obesity. We previously mapped a large number of quantitative trait loci (QTLs) affecting adult body weight in this cross. We map body composition traits, adiposity, and skeletal size, in a replicate F₂ intercross of the same two strains containing 510 individuals. Using interval-mapping methods, we located eight QTLs affecting adiposity (Adip1–8). Two of these adiposity loci also affected tail length (Adip4 and Adip6) along with seven additional tail length QTLs (Skl1–7). A further four QTLs (Wt1–4) affect adult weight but not body composition. These QTLs have relatively small effects, typically about 0.2–0.4 standard deviation units, and account for between 3% and 10% of the variance in individual characters. All QTLs participated in epistatic interactions with other QTLs. Most of these interactions were due to additive-by-additive epistasis, which can nullify the apparent effects of single loci in our population. Adip8 interacts with all the other adiposity QTLs and seems to play a central role in the genetic system affecting obesity in this cross. Only two adiposity QTLs, Adip4 and Adip6, also affect tail length, indicating largely separate genetic control of variation in adiposity and skeletal size. Body size and obesity QTLs in the same locations as those discovered here are commonly found in mapping experiments with other mouse strains. Received: 11 January 2000 / Accepted: 17 August 2000     

The QTL analysis on maternal and endosperm genome and their environmental interactions for characters of cooking quality in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L<Emphasis Type="Italic">.</Emphasis>)

Investigations to identify quantitative trait loci (QTLs) governing cooking quality traits including amylose content, gel consistency and gelatinization temperature (expressed by the alkali spread value) were conducted using a set of 241 RIL populations derived from an elite hybrid cross of “Zhenshan 97” × “Minghui 63” and their reciprocal backcrosses BC₁F₁ and BC₂F₁ populations in two environments. QTLs and QTL × environment interactions were analyzed by using the genetic model with endosperm and maternal effects and environmental interaction effects on quantitative traits of seed in cereal crops. The results suggested that a total of seven QTLs were associated with cooking quality of rice, which were subsequently mapped to chromosomes 1, 4 and 6. Six of these QTLs were also found to have environmental interaction effects.     

水稻叶绿素含量的QTL定位

利用由两个籼稻品种Acc8558和H359杂交构建的一个包含131个株系(F19)的重组自交系群体,及其相应的包含147个RFLP和78个AFLP标记的遗传图谱,采用多性状复合区间定位方法,对控制水稻叶绿素含量的QTL进行了定位分析。对叶绿素a和叶绿素b含量各检测到6个QTL,其中5个QTL在两性状问是相同的。这些QTL主要分布在第1和第4染色体上,因此这两条染色体对叶绿素含量是重要的。QTL qChlAlc／qChlBlb(二者位置相同)在4个观测时期均表现较大效应,且在最后的剑叶期贡献最大,因此对叶绿素含量最为重要。另两个QTL(qCh-LA4a／qChlB4a和qChlA4b／qChlB4b)只在第2次观测时期效应显著,表明它们只在特定发育阶段发挥作用。     

Molecular dissection of Tomato leaf curl virus resistance in tomato line TY172 derived from Solanum peruvianum

Tomato yellow leaf curl virus (TYLCV) is devastating to tomato (Solanum lycopersicum) crops and resistant cultivars are highly effective in controlling the disease. The breeding line TY172, originating from Solanum peruvianum, is highly resistant to TYLCV. To map quantitative trait loci (QTLs) controlling TYLCV resistance in TY172, appropriate segregating populations were analyzed using 69 polymorphic DNA markers spanning the entire tomato genome. Results show that TYLCV resistance in TY172 is controlled by a previously unknown major QTL, originating from the resistant line, and four additional minor QTLs. The major QTL, we term Ty-5, maps to chromosome 4 and accounts for 39.7–46.6% of the variation in symptom severity among segregating plants (LOD score 33–35). The minor QTLs, originated either from the resistant or susceptible parents, were mapped to chromosomes 1, 7, 9 and 11, and contributed 12% to the variation in symptom severity in addition to Ty-5.     

Mapping genes controlling root morphology and root distribution in a doubled-haploid population of rice

 A deep thick root system has been demonstrated to have a positive effect on yield of upland rice under water stress conditions. Molecular-marker-aided selection could be helpful for the improvement of root morphological traits, which are otherwise difficult to score. We studied a doubled-haploid population of 105 lines derived from an indica×japonica cross and mapped the genes controlling root morphology and distribution (root thickness, maximum root length, total root weight, deep root weight, deep root weight per tiller, and deep root to shoot ratio). Most putative QTL activity was concentrated in fairly compact regions on chromosomes 1, 2, 3, 6, 7, 8 and 9, but was widely spread on chromosome 5 and largely absent on chromosomes 4, 10, 11 and 12. Between three and six QTLs were identified on different chromosomes for each trait. Individual QTLs accounted for between 4 and 22% of the variation in the traits. Multiple QTL models accounted for between 14 and 49%. The main QTLs were common between traits, showing that it should be possible to modify several aspects of root morphology simultaneously. There was evidence of interaction between marker locations in determining QTL expression. Interacting locations were mostly on different chromosomes and showed antagonistic effects with magnitudes large enough to mask QTL detection. The comparison of QTL locations with another population showed that one to three common QTLs per trait were recovered, among which the most significant was in one or other population. These results will allow the derivation of isogenic lines introgressed with these common segments, separately in the indica and japonica backgrounds. Received: 12 August 1996 / Accepted: 15 November 1996     

Mapping QTLs for root traits in a recombinant inbred population from two indica ecotypes in rice

Evaluation of root traits in rainfed lowland rice is very difficult. Molecular genetic markers could be used as an alternative strategy to phenotypic selection for the improvement of rice root traits. This research was undertaken to map QTLs associated with five root traits using RFLP and AFLP markers. Recombinant inbred lines (RILs) were developed from two indica parents, IR58821–23-B-1–2-1 and IR52561-UBN-1–1-2, that were adapted to rainfed lowland production systems. Using wax-petrolatum layers to simulate a hardpan in the soil, 166 RILs were evaluated for total root number (TRN), penetrated root number (PRN), root penetration index (RPI, the ratio of PRN to TRN), penetrated root thickness (PRT) and penetrated root length (PRL) under greenhouse conditions during the summer and the fall of 1997. A genetic linkage map of 2022 cM length was constructed comprising 303 AFLP and 96 RFLP markers with an average marker space of 5.0 cM. QTL analysis via interval mapping detected 28 QTLs for these five root traits, which were located on chromosomes 1, 2, 3, 4, 6, 7, 10 and 11. Individual QTLs accounted for between 6 and 27% of the phenotypic variation. Most of the favorable alleles were derived from the parent IR58821–23-B-1–2-1, which was phenotypically superior in root traits related to drought resistance. Three out of six QTLs for RPI were detected in both summer and fall experiments and they also were associated with PRN in both experiments. Out of eight QTLs for RPT, five were common in both seasons. Two genomic regions on chromosome 2 were associated with three root traits (PRN, PRT and RPI), whereas three genomic regions on chromosomes 2 and 3 were associated with two root traits (PRT and RPI). Two QTLs affecting RPI and two QTLs affecting PRT were also found in similar genomic regions in other rice populations. The consistent QTLs across genetic backgrounds and the common QTLs detected in both experiments should be good candidates for marker-assisted selection toward the incorporation of root traits in a drought resistance breeding program, especially for rainfed lowland rice. Received: 17 November 1999 / Accepted: 19 March 2000     

QTL mapping for seedling traits in wheat grown under varying concentrations of N,P and K nutrients

Nutrient use efficiency (NuUE), comprising nutrient uptake and utilization efficiency, is regarded as one of the most important factors for wheat yield. In the present study, six morphological, nine nutrient content and nine nutrient utilization efficiency traits were investigated at the seedling stage using a set of recombinant inbred lines (RILs), under hydroponic culture of 12 treatments including single nutrient levels and two- and three-nutrient combinations treatments of N, P and K. For the 12 designed treatments, a total of 380 quantitative trait loci (QTLs) on 20 chromosomes for the 24 traits were detected. Of these, 87, 149 and 144 QTLs for morphological, nutrient content and nutrient utilization efficiency traits were found, respectively. Using the data of the average value (AV) across 12 treatments, 70 QTLs were detected for 23 traits. Most QTLs were located in new marker regions. Twenty-six important QTL clusters were mapped on 13 chromosomes, 1A, 1B, 1D, 2B, 3A, 3B, 4A, 4B, 5D, 6A, 6B, 7A and 7B. Of these, ten clusters involved 147 QTLs (38.7%) for investigated traits, indicating that these 10 loci were more important for the NuUE of N, P and K. We found evidence for cooperative uptake and utilization (CUU) of N, P and K in the early growth period at both the phenotype and QTL level. The correlation coefficients (r) between nutrient content and nutrient utilization efficiency traits for N, P and K were almost all significantly positive correlations. A total of 32 cooperative CUU loci (L1–L32) were found, which included 190 out of the 293 QTLs (64.8%) for the nutrient uptake and utilization efficiency traits, indicating that the CUU-QTLs were common for N, P and K. The CUU-QTLs in L3, L7, L16 and L28 were relatively stable. The CUU-QTLs may explain the CUU phenotype at the QTL level.     

Fine structure mapping of the barley chromosome-1 centromere region containing malting-quality QTLs

 Current techniques for quantitative trait locus (QTLs) analyses provide only approximate locations of QTLs on chromosomes. Further resolution of identified QTL regions is often required for detailed characterization. An important region containing malting-quality QTLs on barley (Hordeum vulgare L.) chromosome 1 was identified by previous QTL analyses in a Steptoe×Morex cross. This region contains two putative adjacent overlapping QTLs, each of which has effects on malt-extract percentage, α-amylase activity, diastatic power, and malt β-glucan content. All favorable alleles for these traits are attributed to Morex. The objective of the present study was fine structure mapping of this complex QTL region to elucidate whether these two putative overlapping QTLs are really one QTL. Another question was whether the apparently overlapping QTLs are due to the pleiotropic effects of a single gene, or the independent effects of several genes. A high-resolution map in the target region was developed which spans approximately 27 cM. Molecular-marker-assisted backcrossing was employed to create isogenic lines with a Steptoe background differing only in the region containing the QTLs of interest. A total of 32 different recombinants were identified, of which eight most-informative isogenic lines plus one reconstructed Steptoe control were selected for field testing. The additive effects on malt-extract percentage, α-amylase activity, diastatic power, and malt β-glucan content from eight isogenic lines were calculated based on malting data from three locations. By comparing the significant additive effects among isogenic lines carrying different Morex fragments, two QTLs each for malt extract and for α-amylase, and two to three for diastatic power were identified in certain environments and resolved into 1–8-cM genome fragments. There was a significant QTL×environment interaction for diastatic power, and there are indications that epistatic interactions for malt β-glucan content occur between the QTLs on chromosome 1 and QTLs on other chromosomes. Received : 4 June 1997 / Accepted : 19 June 1997     

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.     

Quantitative Trait Loci Mapping for ChlorophyⅡ Fluorescence and Associated Traits in Wheat （ Triticum aestivum）

Parameters of chlorophyll fluorescence kinetics （PCFKs） under drought stress condition are generally used to characterize instincts for dehydration tolerance in wheat （Triticum aestivum L.）. Therefore, it is important to map quantitative trait loci （QTLs） for PCFKs in wheat genetic improvement for drought tolerance. A doubled haploid （DH） population with 150 lines, derived from a cross between two common wheat varieties, Hanxuan 10 and Lumai 14, was used to analyze the correlation between PCFKs and chlorophyll content （CHIC） and to map QTLs at the grainfilling stage under conditions of both rainfed （drought stress, DS） and well-watered （WW）, respectively. QTLs for these traits were detected by QTLMapper version 1.0 based on the composite Interval mapping method of the mixed-linear model. The results showed a very significant positive correlation between Fv, Fm, Fv/Fm and Fv/Fo. The correlation coefficients were generally higher under WW than under DS. Also, there was a significant or a highly significant positive correlation between Fv, Fm, Fv/Fm, Fv/Fo and CHIC. The correlation coefficients were higher in the DS group than the WW group. A total of 14 additive QTLs （nine QTLs detected under DS and five QTLs under WW） and 25 pairs of eplstatlc QTLs （15 pairs detected under DS and 10 pairs under WW） for PCFKs were mapped on chromosomes 6A, 7A, 1B, 3B, 4D and 7D. The contributions of additive QTLs for PCFKs to phenotype variation were from 8.40% to 72.72%. Four additive QTLs （two QTLs detected under DS and WW apiece） controlling Chic were mapped on chromosomes 1A, 5A and 7A. The contributions of these QTLs for ChIC to phenotype variation were from 7.27% to 11.68%. Several QTL clusters were detected on chromosomes 1B, 7A and 7D, but no shared chromosomal regions for them were identified under different water regimes, indicating that these QTLs performed different expression patterns under rainfed and well-watered conditions.     

Quantitative trait loci and underlying candidate genes controlling agronomical and fruit quality traits in octoploid strawberry <Emphasis Type="Italic">(Fragaria</Emphasis> × <Emphasis Type="Italic">ananassa</Emphasis>)

Breeding for fruit quality traits in strawberry (Fragaria × ananassa, 2n = 8x = 56) is complex due to the polygenic nature of these traits and the octoploid constitution of this species. In order to improve the efficiency of genotype selection, the identification of quantitative trait loci (QTL) and associated molecular markers will constitute a valuable tool for breeding programs. However, the implementation of these markers in breeding programs depends upon the complexity and stability of QTLs across different environments. In this work, the genetic control of 17 agronomical and fruit quality traits was investigated in strawberry using a F₁ population derived from an intraspecific cross between two contrasting selection lines, ‘232’ and ‘1392’. QTL analyses were performed over three successive years based on the separate parental linkage maps and a pseudo-testcross strategy. The integrated strawberry genetic map consists of 338 molecular markers covering 37 linkage groups, thus exceeding the 28 chromosomes. 33 QTLs were identified for 14 of the 17 studied traits and approximately 37% of them were stable over time. For each trait, 1–5 QTLs were identified with individual effects ranging between 9.2 and 30.5% of the phenotypic variation, indicating that all analysed traits are complex and quantitatively inherited. Many QTLs controlling correlated traits were co-located in homoeology group V, indicating linkage or pleiotropic effects of loci. Candidate genes for several QTLs controlling yield, anthocyanins, firmness and l-ascorbic acid are proposed based on both their co-localization and predicted function. We also report conserved QTLs among strawberry and other Rosaceae based on their syntenic location.     

Identification of quantitative trait loci controlling rice mature seed culturability using chromosomal segment substitution lines

The genetic transformation efficiency of a rice variety is largely determined by its tissue culturability. Establishment of a highly efficient tissue-culture system has greatly accelerated the wide spread application of transgenic japonica varieties. However, such process for indica rice was hampered because this type of variety is recalcitrant to in vitro culture. This study aimed to map the quantitative trait loci (QTLs) for mature seed culturability using a chromosomal segment substitution lines (CSSL) population derived from a cross between an indica variety “Zhenshan 97B” and a japonica variety “Nipponbare”. The CSSLs consist of 139 lines each containing a single or a few introgression segments, and together covering the whole “Nipponbare” genome. Every CSSL was tested by culturing on the two medium systems developed for the respective indica and japonica parental varieties. The performance of culturability was evaluated by four indices: frequency of callus induction (CIF), callus subculture capability (CSC), frequency of plant regeneration (PRF) and the mean plantlet number per regenerated callus (MNR). All four traits displayed continuous variation among the CSSLs. With the culture system for japonica rice, three CIF QTLs, three CSC QTLs, three PRF QTLs and three MNR QTLs were detected. With the culture system for indica variety, six CIF QTLs, two CSC QTLs, three PRF QTLs and six MNR QTLs were identified, and these QTLs distributed on nine rice chromosomes. Two QTLs of CIF and two QTLs of MNR were detected in both the japonica and indica rice culture system. The correlation coefficients of all the four traits varied depending on the culture systems. These results provide the possibilities of enhancing the culturability of indica rice by marker-assisted breeding with those desirable alleles from the japonica. Lina Zhao and Hongju Zhou have contributed equally to this work.