Quantitative trait loci for yield and correlated traits under high and low soil nitrogen conditions in tropical maize

The first objective of this study was to map and characterize quantitative trait loci (QTL) for grain yield (GY) and for secondary traits under varying nitrogen (N) supply. To achieve this objective, a segregating F_2:3 population previously developed for QTL mapping under water-limited conditions was used. The population was evaluated in Mexico under low N conditions in the dry winter season and under low and high N conditions in the wet summer season. From eight QTLs identified for GY under low N conditions, two were also detected under high N conditions. Five QTLs were stable across the two low N environments and five co-localized with QTLs identified for the anthesis-silking interval (ASI) or for the number of ears per plant (ENO) under low N conditions. The percentage of the phenotypic variance expressed by all QTLs for ASI and ENO was quite different when evaluated under low N conditions during the dry winter (40% for ASI and 22% for ENO) and the wet summer seasons (22% for ASI and 46% for ENO). The results suggest optimizing different breeding strategies based on selection index depending on the growing season. Good QTL colocalization was observed for ASI (four QTLs) and ENO (three QTLs) when looking at QTL identified under low N and water-limited conditions in the same population. The results suggest that that both secondary traits can be used in breeding programs for simultaneous improvement of maize against low N and drought stresses.     

Detection of Quantitative Trait Loci for Yield and Drought Tolerance Traits in Soybean Using a Recombinant Inbred Line Population

To investigate the genetic basis of drought tolerance in soybean ( Glycine max L. Merr.) a recombinant inbred population with 184 F_2:7:11 lines developed from a cross between Kefeng1 (drought tolerant) and Nannong1138-2 (drought sensitive) were tested under water-stressed and well-watered conditions in field and greenhouse trials. Traits measured included leaf wilting coefficient, excised leaf water loss and relative water content as indicators of plant water status and seed yield. A total of 40 quantitative trait loci (QTLs) were identified: 17 for leaf water status traits under drought stress and 23 for seed yield under well-watered and drought-stressed conditions in both field and greenhouse trials. Two seed yield QTLs were detected under both well-watered and drought-stressed conditions in the field on molecular linkage group H and D1b, while two seed yield QTLs on molecular linkage group C2 were found under greenhouse conditions. Several QTLs for traits associated with plant water status were identified in both field and greenhouse trials, including two leaf wilting coefficient QTLs on molecular linkage group A2 and one excised leaf water loss QTL on molecular linkage group H. Phenotypic correlations of traits suggested several QTLs had pleiotropic or location-linked associations. These results will help to elucidate the genetic basis of drought tolerance in soybean, and could be incorporated into a marker-assisted selection breeding program to develop high-yielding soybean cultivars with improved tolerance to drought stress.     

QTL mapping in three tropical maize populations reveals a set of constitutive and adaptive genomic regions for drought tolerance

Despite numerous published reports of quantitative trait loci (QTL) for drought-related traits, practical applications of such QTL in maize improvement are scarce. Identifying QTL of sizeable effects that express more or less uniformly in diverse genetic backgrounds across contrasting water regimes could significantly complement conventional breeding efforts to improve drought tolerance. We evaluated three tropical bi-parental populations under water-stress (WS) and well-watered (WW) regimes in Mexico, Kenya and Zimbabwe to identify genomic regions responsible for grain yield (GY) and anthesis-silking interval (ASI) across multiple environments and diverse genetic backgrounds. Across the three populations, on average, drought stress reduced GY by more than 50 % and increased ASI by 3.2 days. We identified a total of 83 and 62 QTL through individual environment analyses for GY and ASI, respectively. In each population, most QTL consistently showed up in each water regime. Across the three populations, the phenotypic variance explained by various individual QTL ranged from 2.6 to 17.8 % for GY and 1.7 to 17.8 % for ASI under WS environments and from 5 to 19.5 % for GY under WW environments. Meta-QTL (mQTL) analysis across the three populations and multiple environments identified seven genomic regions for GY and one for ASI, of which six mQTL on chr.1, 4, 5 and 10 for GY were constitutively expressed across WS and WW environments. One mQTL on chr.7 for GY and one on chr.3 for ASI were found to be ‘adaptive’ to WS conditions. High throughput assays were developed for SNPs that delimit the physical intervals of these mQTL. At most of the QTL, almost equal number of favorable alleles was donated by either of the parents within each cross, thereby demonstrating the potential of drought tolerant × drought tolerant crosses to identify QTL under contrasting water regimes.     

Identification of quantitative trait loci under drought conditions in tropical maize. 1. Flowering parameters and the anthesis-silking interval

Drought is an important climatic phenomenon which, after soil infertility, ranks as the second most severe limitation to maize production in developing countries. When drought stress occurs just before or during the flowering period, a delay in silking is observed, resulting in an increase in the length of the anthesis-silking interval (ASI) and in a decrease in grain yield. Selection for reduced ASI in tropical open-pollinated varieties has been shown to be correlated with improved yields under drought stress. Since efficient selection for drought tolerance requires carefully managed experimental conditions, molecular markers were used to identify the genomic segments responsible for the expression of ASI, with the final aim of developing marker-assisted selection (MAS) strategies. An F₂population of 234 individuals was genotyped at 142 loci and F₃ families were evaluated in the field under several water regimes for male flowering (MFLW), male sterility (STER), female flowering (FFLW) and ASI. The genetic variance of ASI increased as a function of the stress intensity, and the broad-sense heritabilites of MFLW, FFLW and ASI were high under stress conditions, being 86%, 82% and 78%, respectively. Putative quantitative trait loci (QTLs) involved in the expression of MFLW and/or FFLW under drought were detected on chromosomes 1, 2, 4, 5, 8, 9 and 10, accounting for around 48% of the phenotypic variance for both traits. For ASI, six putative QTLs were identified under drought on chromosomes 1, 2, 5, 6, 8 and 10, and together accounted for approximately 47% of the phenotypic variance. Under water stress conditions, four QTLs were common for the expression of MFLW and FFLW, one for the expression of ASI and MFLW, and four for the expression of ASI and FFLW. The number of common QTLs for two traits was related to the level of linear correlation between these two traits. Segregation for ASI was found to be transgressive with the drought-susceptible parent contributing alleles for reduced ASI (4 days) at two QTL positions. Alleles contributed by the resistant line at the other four QTLs were responsible for a 7-day reduction of ASI. These four QTLs represented around 9% of the linkage map, and were stable over years and stress levels. It is argued that MAS based on ASI QTLs should be a powerful tool for improving drought tolerance of tropical maize inbred lines.     

A comprehensive analysis of QTL for abdominal fat and breast muscle weights on chicken chromosome 5 using a multivariate approach

Quantitative trait loci (QTL) influencing the weight of abdominal fat (AF) and of breast muscle (BM) were detected on chicken chromosome 5 (GGA5) using two successive F₂ crosses between two divergently selected 'Fat' and 'Lean' INRA broiler lines. Based on these results, the aim of the present study was to identify the number, location and effects of these putative QTL by performing multitrait and multi-QTL analyses of the whole available data set. Data concerned 1186 F₂ offspring produced by 10 F₁ sires and 85 F₁ dams. AF and BM traits were measured on F₂ animals at slaughter, at 8 (first cross) or 9 (second cross) weeks of age. The F₀, F₁ and F₂ birds were genotyped for 11 microsatellite markers evenly spaced along GGA5. Before QTL detection, phenotypes were adjusted for the fixed effects of sex, F₂ design, hatching group within the design, and for body weight as a covariable. Univariate analyses confirmed the QTL segregation for AF and BM on GGA5 in male offspring, but not in female offspring. Analyses of male offspring data using multitrait and linked-QTL models led us to conclude the presence of two QTL on the distal part of GGA5, each controlling one trait. Linked QTL models were applied after correction of phenotypic values for the effects of these distal QTL. Several QTL for AF and BM were then discovered in the central region of GGA5, splitting one large QTL region for AF into several distinct QTL. Neither the 'Fat' nor the 'Lean' line appeared to be fixed for any QTL genotype. These results have important implications for prospective fine mapping studies and for the identification of underlying genes and causal mutations.     

QTLs affecting morph-physiological traits related to drought tolerance detected in overlapping introgression lines of rice (Oryza sativa L.)

Plant photosynthetic traits such as net photosynthetic rate (P_n), stomata conductance (g_s), transpiration rate (T_r), and intercellular CO₂ concentration (C_i), are known to relate to drought tolerance in plants, but the genetic basis of these traits remains largely uncharacterized because of the difficulty in phenotyping physiological traits in a large mapping population. In this study, a set of 55 overlapping introgression lines (ILs) in the Teqing (indica) background were used to genetically dissect several morph-physiological traits and their relationship with grain yield under water stress and non-stress conditions. These traits included specific leaf weight (SLW), chlorophyll content (CC), leaf stomata frequency (SF), P_n, g_s, T_r, and C_i. A total of 40 QTLs affecting the measured traits were identified and mapped to 21 genomic regions in the rice genome. Clustered QTLs affecting P_n, g_s, T_r, and C_i in the same genomic regions suggest common genetic bases for the physiological traits. Low or no phenotypic correlations between leaf morphological traits and photosynthetic traits and between morph-physiological traits and grain yield (GY) appeared to be due to inconsistence in QTL effect for clustered QTLs, unlinked QTLs affecting different traits, and to possible epistasis that could not be adequately addressed in this study. Our results indicate that improving drought tolerant (DT) of rice by selecting any single secondary traits is not expected to be effective and the identified QTLs for GY and related morph-physiological traits should be carefully confirmed before to be used for improving DT in rice by MAS.     

Identification of quantitative trait loci under drought conditions in tropical maize. 2. Yield components and marker-assisted selection strategies

In most maize-growing areas yield reductions due to drought have been observed. Drought at flowering time is, in some cases, the most damaging. In the experiment reported here, trials with F₃ families, derived from a segregating F₂ population, were conducted in the field under well-watered conditions (WW) and two other water-stress regimes affecting flowering (intermediate stress, IS, and severe stress, SS). Several yield components were measured on equal numbers of plants per family: grain yield (GY), ear number (ENO), kernel number (KNO), and 100-kernel weight (HKWT). Correlation analysis of these traits showed that they were not independent of each other. Drought resulted in a 60% decrease of GY under SS conditions. By comparing yield under WW and SS conditions, the families that performed best under WW conditions were found to be proportionately more affected by stress, and the yield reductions due to SS conditions were inversely proportional to the performance under drought. Moreover, no positive correlation was observed between a drought-tolerance index (DTI) and yield under WW conditions. The correlation between GY under WW and SS conditions was 0.31. Therefore, in this experiment, selection for yield improvement under WW conditions only, would not be very effective for yield improvement under drought. Quantitative trait loci (QTLs) were identified for GY, ENO and KNO using composite interval mapping (CIM). No major QTLs, expressing more then 13% of the phenotypic variance, were detected for any of these traits, and there were inconsistencies in their genomic positions across water regimes. The use of CIM allowed the evaluation of QTL-by-environment interactions (Q×E) and could thus identify “stable” QTLs CIMMYT, Apartado Postal 6-641, 06600 Mexico D.F., Mexico across drought environments. Two such QTLs for GY, on chromosomes 1 and 10, coincided with two stable QTLs for KNO. Moreover, four genomic regions were identified for the expression of both GY and the anthesis-silking interval (ASI). In three of these, the allelic contributions were for short ASI and GY increase, while for that on chromosome 10 the allelic contribution for short ASI corresponded to a yield reduction. From these results, we hypothesize that to improve yield under drought, marker-assisted selection (MAS) using only the QTLs involved in the expression of yield components appears not to be the best strategy, and neither does MAS using only QTLs involved in the expression of ASI. We would therefore favour a MAS strategy that takes into account a combination of the “best QTLs” for different traits. These QTLs should be stable across target environments, represent the largest percentage possible of the phenotypic variance, and, though not involved directly in the expression of yield, should be involved in the expression of traits significantly correlated with yield, such as ASI.     

Mapping of QTL on chromosome X for fat deposition, muscling and growth traits in a wild boar x Meishan F2 family using a high-density gene map

Quantitative trait loci (QTL) for fat deposition, growth and muscling traits have been previously mapped on the basis of low-density linkage maps in a wild boar × Meishan F₂ family to the chromosome X region flanked by SW2456 and SW1943 . Improved QTL resolution was possible using data for F₂ animals with a marker density of 2.7 cM distance in the SW2456 to SW1943 region, including AR , SERPINA7 and ACSL4 as candidate genes. The resolution of the QTL scan was increased substantially, as evidenced by the higher F -ratio values for all QTL. Maxima of F -ratio values for fat deposition, muscling and growth traits were 28.6, 18.2 and 16.5 respectively, and those QTL positions accounted for 7.9%, 5.0% and 4.5% of the F₂ phenotypic variance (VF₂) respectively. QTL for fatness and growth and for most muscling traits mapped near ACSL4 , with the exception of the QTL for ham traits that mapped proximally, in the vicinity of AR . An analysis performed separately for F₂ male animals showed the predominant QTL affecting fat deposition traits (up to 13.6% VF₂) near AR and two QTL for muscling traits (up to 9.9% VF₂) mapped close to ACSL4 . In the F₂ female animals, QTL affecting muscling (up to 12.1% VF₂) mapped at ACSL4 and SW2456 , and QTL for fat deposition (10% VF₂) and growth (up to 10.5% VF₂) mapped at ACSL4 .     

Genetic analysis of drought tolerance in maize by molecular markers. II. Plant height and flowering

Drought is a serious agronomic problem, and one of the most important factors contributing to crop yield loss. In maize grown in temperate areas, drought stress occurs just before and during the flowering period; consequently, tolerance to water stress in this species is largely determined by events that occur at or shortly after flowering. The purposes of our investigation were: (1)?to identify the chromosomal regions where factors conferring drought tolerance for traits related to plant development and flowering are located and (2)?to compare these regions with those carrying QTLs controlling these traits, in order to get indirect information on the genetic and physiological basis of maize response to water stress. To this aim, we performed a linkage analysis between the expression of male and female flowering time, anthesis-silking interval (ASI), plant height and molecular markers. The experiment was carried out under two environmental conditions, well-watered and water-stressed, on a maize population of 142 recombinant inbred lines obtained by selfing the F₁ between lines B73 and H99 and genotyped by RFLP, microsatellites (SSR) and AFLP markers, for a total of 153 loci. Linkage analysis revealed that, for male flowering time and plant height, most of the QTLs detected were the same under control and stress conditions. In contrast, with respect to female flowering time and ASI diverse QTLs appeared to be expressed either under control conditions or under stress. All of the QTLs conferring tolerance to drought were located in a different chromosome position as compared to the map position of the factors controlling the trait per se. This suggests that plant tolerance, in its different components, is not attributable to the presence of favourable allelic combinations controlling the trait but is based on physiological characteristics not directly associated with the control of the character.     

Mapping QTLs for Component Traits Influencing Drought Stress Tolerance of Maize (Zea mays L) in India

The present study was aimed at mapping of Quantitative Trait Loci (QTL) for various traits influencing the performance of maize genotypes under drought stress conditions in India. A set of 210 Recombinant Inbred Lines (RILs) developed at CIMMYT (Mexico) was analyzed in drought trials undertaken at Karimnagar (2002-03) and Hyderabad (2003-04). Analyses of the RIL datasets using Composite Interval Mapping (CIM) models led to the detection of 52 QTLs, including 22 QTLs under the control conditions and 30 QTLs under drought stress conditions at Karimnagar, and 14 QTLs influencing various characters under drought stress conditions at Hyderabad. A significant digenic epistatic QTL effect, other than the main effect QTLs, was detected for kernel number per ear under drought stress conditions. A comparison of the QTL information obtained from independent analyses of the Karimnagar and Hyderabad datasets revealed colocalization of QTLs on chromosomes 1, 2, 8 and 10 in the RILs influencing specific characters under drought stress conditions. Comparison of the QTL information with that reported from previous analyses of the same set of RILs at Mexico, Kenya and Zimbabwe revealed some ‘consensus QTLs’, which could be of significance in molecular marker-assisted breeding for drought tolerance in maize, besides functional genomics.     

Identification of QTLs for root characteristics in maize grown in hydroponics and analysis of their overlap with QTLs for grain yield in the field at two water regimes

We investigated the overlap among quantitative trait loci (QTLs) in maize for seminal root traits measured in hydroponics with QTLs for grain yield under well-watered (GY-WW) and water-stressed (GY-WS) field conditions as well as for a drought tolerance index (DTI) computed as GY-WS/GY-WW. In hydroponics, 11, 7, 9, and 10 QTLs were identified for primary root length (R1L), primary root diameter (R1D), primary root weight (R1W), and for the weight of the adventitious seminal roots (R2W), respectively. In the field, 7, 8, and 9 QTLs were identified for GY-WW, GY-WS, and DTI, respectively. Despite the weak correlation of root traits in hydroponics with GY-WW, GY-WS, and DTI, a noticeable overlap between the corresponding QTLs was observed. QTLs for R2W most frequently and consistently overlapped with QTLs for GY-WW, GY-WS, and/or DTI. At four QTL regions, an increase in R2W was positively associated with GY-WW, GY-WS, and/or DTI. A 10 cM interval on chromosome 1 between PGAMCTA205 and php20644 showed the strongest effect on R1L, R1D, R2W, GY-WW, GY-WS, and DTI. These results indicate the feasibility of using hydroponics in maize to identify QTL regions controlling root traits at an early growth stage and also influencing GY in the field. A comparative analysis of the QTL regions herein identified with those described in previous studies investigating root traits in different maize populations revealed a number of QTLs in common.     

Genetic analysis of seed size, yield and days to flowering in a chickpea recombinant inbred line population derived from a Kabuli × Desi cross

Quantitative traits, seed size, yield and days to flowering were studied in a chickpea intraspecific recombinant inbred line (RIL) population (F_6:7) derived from a Kabuli × Desi cross. The population was evaluated in two locations over 2 years. Days to flowering was also evaluated in the greenhouse under short-day conditions. Seed size was the most heritable trait (0.90), followed by days to flowering (0.36) and yield (0.14). Negative and significant correlation was found between yield and seed size in the second year where environmental homogeneity was tested by analysing the controls included in each assay. During the first year, the environment was not considered homogeneous for yield in either location. Quantitative trait loci (QTLs) for the three characters were detected in linkage group (LG) 4. In relation to seed size, two QTLs were located in LG4 (QTL_SW1) and LG8 (QTL_SW2). QTL_SW1 accounted 20.3% of the total phenotypic variation and QTL_SW2 explained 10.1%. A QTL for yield (QTL_YD) was located in LG4 explaining around 13% of variation. QTL_YD might be pleiotropic with QTL_SW1. For days to flowering, a QTL (QTL_DF1) was located in LG4 for all environments analysed explaining around 20% of variation. QTL_DF1 was closely linked to QTL_SW1 and QTL_YD in LG4.     

Identification of chromosomal regions associated with growth and carcass traits in an F3 full sib intercross line originating from a cross of chicken lines divergently selected on body weight

An F₃ resource population originating from a cross between two divergently selected lines for high (D+ line) or low (D− line) body weight at 8-weeks of age (BW55) was generated and used for Quantitative Trait Locus (QTL) mapping. From an initial cross of two founder F₀ animals from D(+) and D(−) lines, progeny were randomly intercrossed over two generations following a full sib intercross line (FSIL) design. One hundred and seventy-five genome-wide polymorphic markers were employed in the DNA pooling and selective genotyping of F₃ to identify markers with significant effects on BW55. Fifty-three markers on GGA2, 5 and 11 were then genotyped in the whole F₃ population of 503 birds, where interval mapping with GridQTL software was employed. Eighteen QTL for body weight, carcass traits and some internal organ weights were identified. On GGA2, a comparison between 2-QTL vs. 1-QTL analysis revealed two separate QTL regions for body, feet, breast muscle and carcass weight. Given co-localization of QTL for some highly correlated traits, we concluded that there were 11 distinct QTL mapped. Four QTL localized to already mapped QTL from other studies, but seven QTL have not been previously reported and are hence novel and unique to our selection line. This study provides a low resolution QTL map for various traits and establishes a genetic resource for future fine-mapping and positional cloning in the advanced FSIL generations.     

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.     

Quantitative trait loci influencing drought tolerance in grain sorghum (Sorghum bicolor L. Moench)

Drought is a major constraint in sorghum production worldwide. Drought-stress in sorghum has been characterized at both pre-flowering and post-flowering stages resulting in a drastic reduction in grain yield. In the case of post-flowering drought stress, lodging further aggravates the problem resulting in total loss of crop yield in mechanized agriculture. The present study was conducted to identify quantitative trait loci (QTLs) controlling post-flowering drought tolerance (stay green), pre-flowering drought tolerance and lodging tolerance in sorghum using an F₇ recombinant inbred line (RIL) population derived from the cross SC56×Tx7000. The RIL lines, along with parents, were evaluated for the above traits in multiple environments. With the help of a restriction fragment length polymorphism (RFLP) map, which spans 1,355 cM and consists of 144 loci, nine QTLs, located over seven linkage groups were detected for stay green in several environments using the method of composite interval mapping. Comparison of the QTL locations with the published results indicated that three QTLs located on linkage groups A, G and J were consistent. This is considered significant since the stay green line SC56 used in our investigation is from a different source compared to B35 that was used in all the earlier investigations. Comparative mapping has shown that two stay green QTLs identified in this study corresponded to stay green QTL regions in maize. These genomic regions were also reported to be congruent with other drought-related agronomic and physiological traits in maize and rice, suggesting that these syntenic regions might be hosting a cluster of genes with pleiotropic effects implicated in several drought tolerance mechanisms in these grass species. In addition, three and four major QTLs responsible for lodging tolerance and pre-flowering drought tolerance, respectively, were detected. This investigation clearly revealed the important and consistent stay green QTLs in a different stay green source that can logically be targeted for positional cloning. The identification of QTLs and markers for pre-flowering drought tolerance and lodging tolerance will help plant breeders in manipulating and pyramiding those traits along with stay green to improve drought tolerance in sorghum. Received: 2 June 2000 / Accepted: 15 November 2000     

Mapping of quantitative trait loci on porcine chromosome 4

A F₂ population derived from a cross between European Large White and Chinese Meishan pigs was established in order to study the genetic basis of breed differences for growth and fat traits. Chromosome 4 was chosen for initial study as previous work had revealed quantitative trait loci (QTLs) on this chromosome affected growth and fat traits in a Wild Boar × Large White cross. Individuals in the F₂ population were typed for nine markers spanning a region of approximately 124 c m . We found evidence for QTLs affecting growth between weaning and the end of test (additive effect: 43·4 g/day) and fat depth measured in the mid-back position (additive effect: 1·82 mm). There was no evidence of interactions between the QTLs and sex, grandparents or F₁ sires, suggesting that the detected QTLs were fixed for alternative alleles in the Meishan and Large White breeds. Comparison of locations suggests that these QTLs could be the same as those found in the Wild Boar × Large White cross.     

QTL mapping for yield and photosynthetic related traits under different water regimes in wheat

The improvement for drought tolerance requires understanding of the genetic control of wheat (Triticum aestivum L.) reaction to drought. In this study, a set of 131 recombinant inbred lines of wheat were investigated under well-watered (WW) and drought stress (DS) environments across 2 years to map quantitative trait loci (QTLs) for yield and physiological traits. A total of 225 QTLs were detected, including 32 non-environment-specific loci that were significant in both DS and WW, one drought-specific locus and two watering-specific loci. Three consistently-expressed QTLs (QTkw-3A.2, QTss-1A, and QScn-7A.1) were identified in at least three environments and the QTkw-1D.1 was significant in DS across the 2 years. By unconditional and conditional QTL analysis, spike number per plant and kernel number per spike were more important than thousand-kernel weight for grain yield (GY) at the given genetic background. Meta-analysis identified 67 meta-QTLs that contained QTLs for at least two traits. High frequency co-location of QTLs was found among either the spike-related traits or the six physiological traits. Four photosynthesis traits (CHL, LWUE, P _N, and C _i) were co-located with GY and/or yield components on various MQTLs. The results provided QTLs that warrant further study for drought tolerance breeding and are helpful for understanding the genetic basis of drought tolerance and the genetic contribution of yield components to GY at individual QTL level in wheat.     

玉米雌雄开花间隔天数、结穗率与产量的数量性状位点(QTL)分析

采用SSR标记连锁图谱和复合区间作图法在山西灌溉和干旱胁迫条件下,对玉米(Zea mays L.)自交系黄早四×掖107组合的F3群体雌雄开花间隔天数(ASI)、结穗率和籽粒产量进行了数量性状位点(QTL)定位及基因效应分析.结果表明,在两种水分处理下,ASI、结穗率与籽粒产量的相关性均达到显著水平(P＜0.05).在灌溉和干旱胁迫下,分别检测到3个和2个控制ASI的QTL,位于第1、2、3和第2、5染色体上.在灌溉条件下,在第3和第6染色体上各检测到1个控制结穗率的QTL,基因作用方式呈加性或部分显性,可解释19.9%的表型变异;在干旱条件下,在第3、 7、10染色体上共检测到4个控制结穗率的QTL,基因作用方式为显性或部分显性,可解释60.4%的表型变异.在灌溉和干旱胁迫下,控制产量的QTL分别定位在第3、6、7和第1、2、4、8染色体上,基因作用方式均以加性或部分显性为主,可解释的表型变异为7.3%～22.0%.在干旱条件下,借助连锁分子标记和基因效应分析,可构建包含ASI、结穗率和产量QTL的选择指数,用于分子标记辅助育种.     

Mapping quantitative trait loci regulating chicken body composition traits

Genome scans were conducted on an F₂ resource population derived from intercross of the White Plymouth Rock with the Silkies Fowl to detect QTL affecting chicken body composition traits. The population was genotyped with 129 microsatellite markers and phenotyped for 12 body composition traits on 238 F₂ individuals from 15 full-sib families. In total, 21 genome-wide QTL were found to be responsible for 11 traits, including two newly studied traits of proventriculus weight and shank girth. Three QTL were genome-wide significant: at 499 c m on GGA1 (explained 3.6% of phenotypic variance, P  < 0.01) and 51 c m on GGA5 (explained 3.3% of phenotypic variance, P  < 0.05) for the shank & claw weight and 502 c m on GGA1 (explained 1.4% of phenotypic variance, P  < 0.05) for wing weight. The QTL on GGA1 seemed to have pleiotropic effects, also affecting gizzard weight at 490 c m , shank girth at 489 c m and intestine length at 481 c m . It is suggested that further efforts be made to understand the possible pleiotropic effects of the QTL on GGA1 and that on GGA5 for two shank-related traits.