Detection and integration of quantitative trait loci for grain yield components and oil content in two connected recombinant inbred line populations of high-oil maize

Improvement in grain yield is an important objective in high-oil maize breeding. In this study, one high-oil maize inbred was crossed with two normal maize inbreds to produce two connected recombinant inbred line (RIL) populations with 282 and 263 F_7:8 families, respectively. The field experiments were conducted under four environments, and eight grain yield components and grain oil content were evaluated. Two genetic linkage maps were constructed using 216 and 208 polymorphic SSR markers. Quantitative trait loci (QTL) were detected for all traits under each environment and in combined analysis. Meta-analysis was used to integrate genetic maps and detected QTL in both populations. A total of 199 QTL were detected, 122 in population 1 and 87 in population 2. Seven, 11 and 19 QTL showed consistency across five environments, across two RIL populations and with respective F_2:3 generations, respectively. 183 QTL were integrated in 28 meta-QTL (mQTL). QTL with contributions over 15% were consistently detected in 3–4 cases and integrated in mQTL. Each mQTL included 3–19 QTL related to 1–4 traits, reflecting remarkable QTL co-location for grain yield components and oil content. Further research and marker-assisted selection (MAS) should be concentrated on 37 consistent QTL and four genetic regions of mQTL with more than 10 QTL at bins 3.04–3.05, 7.02, 8.04–8.05 and 9.04–9.05. Near-isogenic lines for 100-grain-weight QTL at bin 7.02–7.03, for ear-length QTL at bin 7.02–7.03 and for rows-per-ear QTL at bin 3.08 are now in construction using MAS. Co-located candidate genes could facilitate the identification of candidate genes for grain yield in maize.     

Identification of agronomically favorable quantitative trait loci alleles from a dent corn inbred Dan232 using advanced backcross QTL analysis and comparison with the F<Subscript>2:3</Subscript> population in popcorn

Specific traits are an important consideration in plant breeding. In popcorn, inferior agronomic traits could be improved using dent or flint corn backcrossed with popcorn. In this study, we used advanced backcross quantitative trait locus (AB-QTL) analysis to identify trait-improving QTL alleles from a dent maize inbred Dan232, and compared the detection of QTL in the BC₂S₁ population with QTL results using F_2:3 families of the same population. Two hundred and twenty BC₂S₁ families developed from a cross between Dan232 and an elite popcorn inbred N04 were evaluated for nine plant traits in replicated field trials under two environments. Using composite interval mapping (CIM), a total of 28 significant QTL were detected, and of these, 23 (82.14%) had favorable alleles contributed by the dent corn parent Dan232. Nine QTL (32.14%) detected in the BC₂S₁ population were also located in or near the same chromosome intervals in the F_2:3 population. All of the favorable QTL alleles from Dan232 could be used in marker-assisted selection (MAS) to improve the respective plant traits in popcorn breeding. In addition, their near isogenic lines (QTL-NILs) could be obtained through selfing or another 1–2 backcross with N04. Also, N04 improved for the studied plant traits could be developed from the BC₂S₁ families used in this study. This study demonstrated that the AB-QTL method can be applied to identify favorable QTL from dent corn inbred in popcorn breeding and, once identified, the alleles could be used in marker-assisted selection to improve the respective plant traits.     

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

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

Cold Tolerance of the Photosynthetic Apparatus: Pleiotropic Relationship between Photosynthetic Performance and Specific Leaf Area of Maize Seedlings

The objective of this study was to elucidate the genetic relationship between the specific leaf area (SLA) and the photosynthetic performance of maize (Zea mays L.) as dependent on growth temperature. Three sets of genotypes: (i) 19 S₅ inbred lines, divergently selected for high or low operating efficiency of photosystem II (Φ_PSII) at low temperature, (ii) a population of 226 F_2:3 families from the cross of ETH-DL3 × ETH-DH7, and (iii) a population of 168 F_2:4 families from the cross of Lo964 × Lo1016 were tested at low (15/13 °C day/night) or at optimal (25/22 °C day/night) temperature. The latter cross was originally developed to study QTLs for root traits. At 15/13 °C the groups of S₅ inbred lines selected for high or low Φ_PSII differed significantly for all the measured traits, while at optimal temperature the groups differed only with regard to leaf greenness (SPAD). At low temperature, the SLA of these inbred lines was negatively correlated with Φ_PSII (r = − 0.56, p < 0.05) and SPAD (r = − 0.80, p < 0.001). This negative relationship was confirmed by mapping quantitative trait loci (QTL) in the two mapping populations. A co-location of three QTLs for SLA with QTLs for photosynthesis-related traits was detected in both populations at 15/13 °C, while co-location was not detected at 25/22 °C. The co-selection of SLA and Φ_PSII in the inbred lines and the co-location of QTL for SLA, SPAD, and Φ_PSII at 15/13 °C in the QTL populations strongly supports pleiotropy. There was no evidence that selecting for high Φ_PSII at low temperature leads to a constitutively altered SLA.     

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.     

QTL mapping for resistance against the European corn borer (Ostrinia nubilalis H.) in early maturing European dent germplasm

The European corn borer (ECB, Ostrinia nubilalis Hübner) is a major pest of maize in Central Europe. We mapped and characterized quantitative trait loci (QTLs) involved in resistance of maize against ECB damage, compared them with QTLs for agronomic traits, and evaluated the usefulness of marker-assisted selection (MAS) for improving ECB resistance in early maturing European maize germplasm. A total 226 F₃ families from the cross D06 (resistant) × D408 (susceptible), together with 93 RFLP and two SSR markers were used for the QTL analyses. For each F₃ family we measured the length of tunnels produced by larval stalk mining (TL), stalk damage ratings (SDR), and relative grain yield (RGY) in field experiments, with two replications in two environments in 1 year. The agronomic traits comprised grain yield under insecticide protection (GYP) and manual ECB larval infestation (GYI), the date of anthesis (ANT), and the in vitro digestibility of organic matter (IVDOM) of stover. Estimates of genotypic variance (σ² _g) were highly significant for all traits. Six QTLs for TL and five QTLs for SDR were detected, explaining about 50.0% of σ² _g. Most QTLs showed additive gene action for TL and dominance for SDR. No QTL was found for RGY. The number of QTLs detected for the agronomic traits ranged from two for GYI to 12 for ANT, explaining 12.5 to 57.3% of σ² _g, respectively. Only a single QTL was in common between the two resistance traits, as expected from the moderate trait correlation and the moderate proportions of σ² _g explained. Based on these results, MAS for improving ECB resistance can be competitive when cost-effective PCR-based marker systems are applied. However, it remains to be established whether the putative QTL regions for ECB resistance detected in the population D06 × D408 are consistent across other early maturing European maize germplasms. Received: 20 December 1999 / Accepted: 6 June 2000     

Mapping QTL for Grain Yield and Plant Traits in a Tropical Maize Population

The vast majority of reported QTL mapping for maize (Zea mays L.) traits are from temperate germplasm and, also, QTL by environment interaction (QTL × E) has not been thoroughly evaluated and analyzed in most of these papers. The maize growing areas in tropical regions are more prone to environmental variability than in temperate areas, and, therefore, genotype by environment interaction is of great concern for maize breeders. The objectives of this study were to map QTL and to test their interaction with environments for several traits in a tropical maize population. Two-hundred and fifty-six F_2:3 families evaluated in five environments, a genetic map with 139 microsatellites markers, and the multiple-environment joint analysis (mCIM) were used to map QTL and to test QTL × E interaction. Sixteen, eight, six, six, nine, and two QTL were mapped for grain yield, ears per plant, plant lodging, plant height, ear height, and number of leaves, respectively. Most of these QTL interacted significantly with environments, most of them displayed overdominance for all traits, and genetic correlated traits had a low number of QTL mapped in the same genomic regions. Few of the QTL mapped had already been reported in both temperate and tropical germplasm. The low number of stable QTL across environments imposes additional challenges to design marker-assisted selection in tropical areas, unless the breeding programs could be directed towards specific target areas.     

QTL analysis for yield components and kernel-related traits in maize across multi-environments

Huangzaosi, Qi319, and Ye478 are foundation inbred lines widely used in maize breeding in China. To elucidate genetic base of yield components and kernel-related traits in these elite lines, two F_2:3 populations derived from crosses Qi319?×?Huangzaosi (Q/H, 230 families) and Ye478?×?Huangzaosi (Y/H, 235 families), as well as their parents were evaluated in six environments including Henan, Beijing, and Xinjiang in 2007 and 2008. Correlation and hypergeometric probability function analyses showed the dependence of yield components on kernel-related traits. Three mapping procedures were used to identify quantitative trait loci (QTL) for each population: (1) analysis for each of the six environments, (2) joint analysis for each of the three locations across 2?years, and (3) joint analysis across all environments. For the eight traits measured, 90, 89, and 58 QTL for Q/H, and 72, 76, and 51 QTL for Y/H were detected by the three QTL mapping procedures, respectively. About 70% of the QTL from Q/H and 90% of the QTL from Y/H did not show significant QTL?×?environment interactions in the joint analysis across all environments. Most of the QTL for kernel traits exhibited high stability across 2?years at the same location, even across different locations. Seven major QTL detected under at least four environments were identified on chromosomes 1, 4, 6, 7, 9, and 10 in the populations. Moreover, QTL on chr. 1, chr. 4, and chr. 9 were detected in both populations. These chromosomal regions could be targets for marker-assisted selection, fine mapping, and map-based cloning in maize.     

Identification and validation of QTL for Sclerotinia midstalk rot resistance in sunflower by selective genotyping

Midstalk rot, caused by Sclerotinia sclerotiorum (Lib.) de Bary, is an important cause of yield loss in sunflower (Helianthus annuus L.). Objectives of this study were to: (1) estimate the number, genomic positions and genetic effects of quantitative trait loci (QTL) for resistance to midstalk rot in line TUB-5-3234, derived from an interspecific cross; (2) determine congruency of QTL between this line and other sources of resistance; and (3) make inferences about the efficiency of selective genotyping (SG) in detecting QTL conferring midstalk rot resistance in sunflower. Phenotypic data for three resistance (stem lesion, leaf lesion and speed of fungal growth) and two morphological (leaf length and leaf length with petiole) traits were obtained from 434 F₃ families from cross CM625 (susceptible) × TUB-5-3234 (resistant) under artificial infection in field experiments across two environments. The SG was applied by choosing the 60 most resistant and the 60 most susceptible F₃ families for stem lesion. For genotyping of the respective F₂ plants, 78 simple sequence repeat markers were used. Genotypic variances were highly significant for all traits. Heritabilities and genotypic correlations between resistance traits were moderate to high. Three to four putative QTL were detected for each resistance trait explaining between 40.8% and 72.7% of the genotypic variance ( ). Two QTL for stem lesion showed large genetic effects and corroborated earlier findings from the cross NDBLOS_sel (resistant) × CM625 (susceptible). Our results suggest that SG can be efficiently used for QTL detection and the analysis of congruency for resistance genes across populations.     

Verification of QTL for Grain Starch Content and Its Genetic Correlation with Oil Content Using Two Connected RIL Populations in High-Oil Maize

Grain oil content is negatively correlated with starch content in maize in general. In this study, 282 and 263 recombinant inbred lines (RIL) developed from two crosses between one high-oil maize inbred and two normal dent maize inbreds were evaluated for grain starch content and its correlation with oil content under four environments. Single-trait QTL for starch content in single-population and joint-population analysis, and multiple-trait QTL for both starch and oil content were detected, and compared with the result obtained in the two related F_2∶3 populations. Totally, 20 single-population QTL for grain starch content were detected. No QTL was simultaneously detected across all ten cases. QTL at bins 5.03 and 9.03 were all detected in both populations and in 4 and 5 cases, respectively. Only 2 of the 16 joint-population QTL had significant effects in both populations. Three single-population QTL and 8 joint-population QTL at bins 1.03, 1.04–1.05, 3.05, 8.04–8.05, 9.03, and 9.05 could be considered as fine-mapped. Common QTL across F_2∶3 and RIL generations were observed at bins 5.04, 8.04 and 8.05 in population 1 (Pop.1), and at bin 5.03 in population 2 (Pop.2). QTL at bins 3.02–3.03, 3.05, 8.04–8.05 and 9.03 should be focused in high-starch maize breeding. In multiple-trait QTL analysis, 17 starch-oil QTL were detected, 10 in Pop.1 and 7 in Pop.2. And 22 single-trait QTL failed to show significance in multiple-trait analysis, 13 QTL for starch content and 9 QTL for oil content. However, QTL at bins 1.03, 6.03–6.04 and 8.03–8.04 might increase grain starch content and/or grain oil content without reduction in another trait. Further research should be conducted to validate the effect of these QTL in the simultaneous improvement of grain starch and oil content in maize.     

QTL identification of grain protein concentration and its genetic correlation with starch concentration and grain weight using two populations in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

Protein is one of the three main storage chemical components in maize grains, and is negatively correlated with starch concentration (SC). Our objective was to analyse the influence of genetic backgrounds on QTL detection for protein concentration (PC) and to reveal the molecular genetic associations between PC and both SC and grain weight (GWP). Two hundred and eighty-four (Pop1) and 265 (Pop2) F_2:3 families were developed from two crosses between one high-oil maize inbred GY220 and two normal maize inbreds 8984 and 8622 respectively, and were genotyped with 185 and 173 pairs of SSR markers. PC, SC and GWP were evaluated under two environments. Composite interval mapping (CIM) and multiple interval mapping (MIM) methods were used to detect single-trait QTL for PC, and multiple-trait QTL for PC with both SC and GWP. No common QTL were shared between the two populations for their four and one PC QTL. Common QTL with opposite signs of effects for PC and SC/GWP were detected on three marker intervals at bins 6.07–6.08, 8.03 and 8.03–8.04. Multiple-traits QTL mapping showed that tightly-linked QTL, pleiotropic QTL and QTL having effects with opposite directions for PC and SC/GWP were all observed in Pop1, while all QTL reflected opposite effects in Pop2.     

Correlations and comparisons of quantitative trait loci with family per se and testcross performance for grain yield and related traits in maize

Simultaneous improvement in grain yield and related traits in maize hybrids and their parents (inbred lines) requires a better knowledge of genotypic correlations between family per se performance (FP) and testcross performance (TP). Thus, to understand the genetic basis of yield-related traits in both inbred lines and their testcrosses, two F _2:3 populations (including 230 and 235 families, respectively) were evaluated for both FP and TP of eight yield-related traits in three diverse environments. Genotypic correlations between FP and TP, $ \hat{r}_{\text{g}} $ (FP, TP), were low (0–0.16) for grain yield per plant (GYPP) and kernel number per plant (KNPP) in the two populations, but relatively higher (0.32–0.69) for the other six traits with additive effects as the primary gene action. Similar results were demonstrated by the genotypic correlations between observed and predicted TP values based on quantitative trait loci positions and effects for FP, $ \hat{r}_{\text{g}} $ (M _FP, Y _TP). A total of 88 and 35 QTL were detected with FP and TP, respectively, across all eight traits in the two populations. However, the genotypic variances explained by the QTL detected in the cross-validation analysis were much lower than those in the whole data set for all traits. Several common QTL between FP and TP that accounted for large phenotypic variances were clustered in four genomic regions (bin 1.10, 4.05–4.06, 9.02, and 10.04), which are promising candidate loci for further map-based cloning and improvement in grain yield in maize. Compared with publicly available QTL data, these QTL were also detected in a wide range of genetic backgrounds and environments in maize. These results imply that effective selection based on FP to improve TP could be achieved for traits with prevailing additive effects.     

Locating QTLs controlling several adult root traits in an elite Chinese hybrid rice

This study aimed to elucidate the genetics of the adult root system in elite Chinese hybrid rice. Several adult root traits in a recombinant inbred line (RIL) population of Xieyou 9308 and two backcross F₁ (BCF₁) populations derived from the RILs were phenotyped under hydroponic culture at heading stage for quantitative trait locus (QTL) mapping and other statistical analysis. There a total of eight QTLs detected for the root traits. Among of them, a pleiotropic QTL was repeatedly flanked by RM180 and RM5436 on the short arm of chromosome 7 for multiple traits across RILs and its BCF₁ populations, accounting for 6.88% to 25.26% of the phenotypic variances. Only additive/dominant QTLs were detected for the root traits. These results can serve as a foundation for facilitating future cloning and molecular breeding.     

Analysis of the genetic architecture of maize ear and grain morphological traits by combined linkage and association mapping

Key message

Using combined linkage and association mapping, 26 stable QTL and six stable SNPs were detected across multiple environments for eight ear and grain morphological traits in maize. One QTL, PKS2, might play an important role in maize yield improvement.

Abstract

In the present study, one bi-parental population and an association panel were used to identify quantitative trait loci (QTL) for eight ear and grain morphological traits. A total of 108 QTL related to these traits were detected across four environments using an ultra-high density bin map constructed using recombinant inbred lines (RILs) derived from a cross between Ye478 and Qi319, and 26 QTL were identified in more than two environments. Furthermore, 64 single nucleotide polymorphisms (SNPs) were found to be significantly associated with the eight ear and grain morphological traits (?log₁₀(P)?>?4) in an association panel of 240 maize inbred lines. Combining the two mapping populations, a total of 17 pleiotropic QTL/SNPs (pQTL/SNPs) were associated with various traits across multiple environments. PKS2, a stable locus influencing kernel shape identified on chromosome 2 in a genome-wide association study (GWAS), was within the QTL confidence interval defined by the RILs. The candidate region harbored a short 13-Kb LD block encompassing four SNPs (SYN11386, PHM14783.16, SYN11392, and SYN11378). In the association panel, 13 lines derived from the hybrid PI78599 possessed the same allele as Qi319 at the PHM14783.16 (GG) locus, with an average value of 0.21 for KS, significantly lower than that of the 34 lines derived from Ye478 that carried a different allele (0.25, P?<?0.05). Therefore, further fine mapping of PKS2 will provide valuable information for understanding the genetic components of grain yield and improving molecular marker-assisted selection (MAS) in maize.

     

Optimum allocation of resources for QTL detection using a nested association mapping strategy in maize

In quantitative trait locus (QTL) mapping studies, it is mandatory that the available financial resources are spent in such a way that the power for detection of QTL is maximized. The objective of this study was to optimize for three different fixed budgets the power of QTL detection 1 − β* in recombinant inbred line (RIL) populations derived from a nested design by varying (1) the genetic complexity of the trait, (2) the costs for developing, genotyping, and phenotyping RILs, (3) the total number of RILs, and (4) the number of environments and replications per environment used for phenotyping. Our computer simulations were based on empirical data of 653 single nucleotide polymorphism markers of 26 diverse maize inbred lines which were selected on the basis of 100 simple sequence repeat markers out of a worldwide sample of 260 maize inbreds to capture the maximum genetic diversity. For the standard scenario of costs, the optimum number of test environments (E _opt) ranged across the examined total budgets from 7 to 19 in the scenarios with 25 QTL. In comparison, the E _opt values observed for the scenarios with 50 and 100 QTL were slightly higher. Our finding of differences in 1 − β* estimates between experiments with optimally and sub-optimally allocated resources illustrated the potential to improve the power for QTL detection without increasing the total resources necessary for a QTL mapping experiment. Furthermore, the results of our study indicated that also in studies using the latest genomics tools to dissect quantitative traits, it is required to evaluate the individuals of the mapping population in a high number of environments with a high number of replications per environment.     

Epistasis and genotype-environment interaction for quantitative trait loci affecting flowering time in Arabidopsis thaliana

A major goal of evolutionary biology is to understand the genetic architecture of the complex quantitative traits that may lead to adaptations in natural populations. Of particular relevance is the evaluation of the frequency and magnitude of epistasis (gene–gene and gene–environment interaction) as it plays a controversial role in models of adaptation within and among populations. Here, we explore the genetic basis of flowering time in Arabidopsis thaliana using a series of quantitative trait loci (QTL) mapping experiments with two recombinant inbred line (RIL) mapping populations [Columbia (Col) x Landsberg erecta (Ler), Ler x Cape Verde Islands (Cvi)]. We focus on the response of RILs to a series of environmental conditions including drought stress, leaf damage, and apical damage. These data were explicitly evaluated for the presence of epistasis using Bayesian based multiple-QTL genome scans. Overall, we mapped fourteen QTL affecting flowering time. We detected two significant QTL–QTL interactions and several QTL–environment interactions for flowering time in the Ler x Cvi population. QTL–environment interactions were due to environmentally induced changes in the magnitude of QTL effects and their interactions across environments – we did not detect antagonistic pleiotropy. We found no evidence for QTL interactions in the Ler x Col population. We evaluate these results in the context of several other studies of flowering time in Arabidopsis thaliana and adaptive evolution in natural populations.     

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.     

Some practical considerations for using RFLP markers to aid in selection during inbreeding of maize

Summary If molecular markers are to be routinely used in maize (Zea mays L.) breeding for selection of quantitative trait loci (QTL), then consistent marker-trait associations across breeding populations are needed, as are efficient methods for weighting information from different markers. Given 15 restriction fragment length polymorphism (RFLP) markers associated with grain yield in testcrosses of 220 [BS11(FR)C7 x FRMol7] F₂ individuals to FRB73, separate weighting schemes were attempted in order to maximize the frequency of favorable marker genotypes associated with increased grain yield in selected F₂ individuals and F₂:S₄ Unes. The following principles were apparent: (1) Differential weighting among markers, in addition to weighting individual marker genotypes on the basis of associated mean effects, should be emphasized when using markers to select in breeding populations. This is due to limited population sizes that can readily be handled. (2) Relatively few markers may need to be used to screen segregating populations (e.g., F₂) of limited size for loci affecting complex traits, such as combining ability for grain yield, assuming prior knowledge of marker-QTL associations. Markers given greatest weight (largest estimates of associated effects) will determine most selections. (3) When marker-based selection is among individuals at higher levels of inbreeding (e.g., S₄) within selected families, more markers need to be used in screening because those associated with relatively small effects have an increased chance of affecting selection.These results suggest a qualitative approach for utilizing RFLP markers to aid in selection of complex traits in commercial hybrid maize breeding programs. Commercial research programs produce thousands of crosses each year aimed at inbred line development. Discovery of molecular markers with consistent QTL associations across breeding populations and close QTL linkages would allow for rapid screening of new F₂ populations at a few key markers. Early elimination of individuals with undesirable genotypes would reduce the extent of hybrid performance testing necessary during later stages of inbreeding.     

Combined linkage mapping and association analysis reveals genetic control of maize kernel moisture content

The free moisture in crop kernels after being naturally dried is referred to as kernel moisture content (KMC). Maize KMC reflects grain quality and influences transportation and storage of seeds. We used an IBM Syn10 DH maize population consisting of 249 lines and an association panel comprising 310 maize inbred lines to identify the genetic loci affecting maize KMC in three environments. Using the IBM population detected 13 QTL on seven chromosomes, which were clustered into nine common QTL. Genome-wide association analysis (GWAS) identified 16 significant SNPs across the 3 environments, which were linked to 158 genes across the three environments. Combined QTL mapping and GWAS found two SNPs that were located in two of the mapped QTL, respectively. Twenty-three genes were linked with the loci co-localized in both populations. Of these 181 genes, five have previously been reported to be associated with KMC or to regulate seed development. These associations were verified by candidate gene association analysis. Two superior alleles and one favorable haplotype for Zm00001d007774 and Zm00001d047868 were found to influence KMC. These findings provide insights into molecular mechanisms underlying maize KMC and contribute to the use of marker-assisted selection for breeding low-KMC maize.     

Mapping QTLs and candidate genes for rice root traits under different water-supply conditions and comparative analysis across three populations

To investigate the genetic factors underlying constitutive and adaptive morphological traits of roots under different water-supply conditions, a recombinant inbred line (RIL) population derived from a cross between the lowland rice variety IR1552 and the upland rice variety Azucena with 249 molecular markers, was used in cylindrical-pot experiments. Eighteen QTLs were detected for seminal root length (SRL), adventitious root number (ARN), and lateral root length (LRL) and lateral root number (LRN) on the seminal root at a soil depth of from 3 to 6 cm under flooding and upland conditions. One identical QTL was detected under both flooding and upland conditions. The relative parameters under the two water-supply conditions were also used for QTL analysis. Five QTLs for upland induced variations in the traits were detected with the positive alleles from Azucena. A comparative analysis was performed for the QTLs detected in this study and those reported from two other populations with Azucena as a parent. Several identical QTLs for root elongation were found across the three populations with positive alleles from Azucena. Candidate genes were screened from ESTs and cDNA-AFLP clones for comparative mapping with the detected QTLs. Two genes for cell expansion, OsEXP2 and endo-1,4--D-glucanase EGase, and four cDNA-AFLP clones from root tissues of Azucena, were mapped on the intervals carrying the QTLs for SRL and LRL under upland conditions, respectively.Communicated by H.C. Becker