QTL mapping of resistance to Fusarium ear rot using a RIL population in maize

Fusarium ear rot is a prevalent disease in maize, reducing grain yields and quality. Resistance breeding is an efficient way to minimize losses caused by the disease. In this study, 187 lines from a RIL population along with the resistant (87-1) and susceptible (Zong 3) parents were planted in Zhengzhou and Beijing with three replications in years 2004 and 2006. Each line was artificially inoculated using the nail-punch method. Significant genotypic variation in response to Fusarium ear rot was detected in both years. Based on a genetic map containing 246 polymorphic SSR markers with average genetic distances of 9.1 cM, the ear-rot resistance QTL were firstly analyzed by composite interval mapping (CIM). Three QTL were detected in both Zhengzhou and Beijing in 2004; and three and four QTL, respectively, were identified in 2006. The resistant parent contributed all resistance QTL. By using composite interval mapping and a mixed model (MCIM), significant epistatic effects on Fusarium ear rot as well as interactions between mapped loci and environments were observed across environments. Two QTL on chromosome 3 (3.04 bin) were consistently identified across all environments by the two methods. The major resistant QTL with the largest effect was flanked by markers umc1025 and umc1742 on chromosome 3 (3.04 bin), explaining 13–22% of the phenotypic variation. The SSR markers closely flanking the major resistance QTL will facilitate marker-assisted selection (MAS) of resistance to Fusarium ear rot in maize breeding programs.     

Detection and verification of quantitative trait loci for resistance to Fusarium ear rot in maize

Fusarium ear rot caused by Fusarium verticillioides is a prevalent disease in maize which can severely reduce grain yields and quality. Identification of stable quantitative trait loci (QTL) for resistance to Fusarium ear rot is a basic prerequisite for understanding the genetic mechanism of resistance and for the use of marker-assisted selection. In this study, two hundred and ten F _2:3 families were developed from a cross between resistant inbred line BT-1 and susceptible inbred line Xi502, and were genotyped with 178 simple sequence repeat markers. The resistance of each line was evaluated in two environments by artificial inoculation using the nail-punch method. The resistance QTL were detected using the composite interval mapping method. Three QTL were detected on chromosomes 4, 5 and 10. Of them, the QTL on chromosome 4 (bin 4.05/06) had the largest resistance to Fusarium ear rot, and could explain 17.95?% of the phenotypic variation. For further verification of the QTL effect, we developed near-isogenic lines (NILs) carrying the QTL region on chromosome 4 using parental line Xi502 as the recurrent parent. In the NIL background, this QTL can increase the resistance by 33.7?C35.2?% if the resistance region is homozygous, and by 17.8?C26.5?% if the resistance region contains the heterozygous allele. The stable and significant resistance effect of the QTL on chromosome 4 lays the foundation for further marker-assisted selection and map-based cloning in maize.     

Precise mapping of quantitative trait loci for resistance to southern leaf blight, caused by Cochliobolus heterostrophus race O, and flowering time using advanced intercross maize lines

The intermated B73 × Mo17 (IBM) population, an advanced intercross recombinant inbred line population derived from a cross between the maize lines B73 (susceptible) and Mo17 (resistant), was evaluated in four environments for resistance to southern leaf blight (SLB) disease caused by Cochliobolus heterostrophus race O. Two environments were artificially inoculated, while two were not inoculated and consequently had substantially lower disease pressure. Four common SLB resistance quantitative trait loci (QTL) were identified in all environments, two in bin 3.04 and one each in bins 1.10 and 8.02/3. There was no significant correlation between disease resistance and days to anthesis. A direct comparison was made between SLB QTL detected in two populations, independently derived from the same parental cross: the IBM advanced intercross population and a conventional recombinant inbred line population. Several QTL for SLB resistance were detected in both populations, with the IBM providing between 5 and, in one case, 50 times greater mapping resolution.     

The Identification of Two Head Smut Resistance-Related QTL in Maize by the Joint Approach of Linkage Mapping and Association Analysis

Head smut, caused by the fungus Sphacelotheca reiliana (Kühn) Clint, is a devastating threat to maize production. In this study, QTL mapping of head smut resistance was performed using a recombinant inbred line (RIL) population from a cross between a resistant line “QI319” and a susceptible line “Huangzaosi” (HZS) with a genetic map constructed from genotyping-by-sequencing (GBS) data and composed of 1638 bin markers. Two head smut resistance QTL were identified, located on Chromosome 2 (q2.09HR) and Chromosome 5 (q5.03HR), q2.09HR is co-localized with a previously reported QTL for head smut resistance, and the effect of q5.03HR has been validated in backcross populations. It was also observed that pyramiding the resistant alleles of both QTL enhanced the level of resistance to head smut. A genome-wide association study (GWAS) using 277 diverse inbred lines was processed to validate the mapped QTL and to identify additional head smut resistance associations. A total of 58 associated SNPs were detected, which were distributed in 31 independent regions. SNPs with significant association to head smut resistance were detected within the q2.09HR and q5.03HR regions, confirming the linkage mapping results. It was also observed that both additive and epistastic effects determine the genetic architecture of head smut resistance in maize. As shown in this study, the combined strategy of linkage mapping and association analysis is a powerful approach in QTL dissection for disease resistance in maize.     

Mapping QTL associated with photoperiod sensitivity and assessing the importance of QTL×environment interaction for flowering time in maize

Background

An understanding of the genetic determinism of photoperiod response of flowering is a prerequisite for the successful exchange of germplasm across different latitudes. In order to contribute to resolve the genetic basis of photoperiod sensitivity in maize, a set of 201 recombinant inbred lines (RIL), derived from a temperate and tropical inbred line cross were evaluated in 5 field trials spread in short- and long-day environments.

Methodology/Principal Findings

Firstly, QTL analyses for flowering time and photoperiod sensitivity in maize were conducted in individual photoperiod environments separately, and then, the total genetic effect was partitioned into additive effect (A) and additive-by-environment interaction effect (AE) by using a mixed-model-based composite interval mapping (MCIM) method.

Conclusions/Significance

Seven putative QTL were found associated with DPS thermal time based on the data estimated in individual environments. Nine putative QTL were found associated with DPS thermal time across environments and six of them showed significant QTL×enviroment (QE) interactions. Three QTL for photoperiod sensitivity were identified on chromosome 4, 9 and 10, which had the similar position to QTL for DPS thermal time in the two long-day environment. The major photoperiod sensitive loci qDPS10 responded to both short and long-day photoperiod environments and had opposite effects in different photoperiod environment. The QTL qDPS3, which had the greatest additive effect exclusively in the short-day environment, were photoperiod independent and should be classified in autonomous promotion pathway.     

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.     

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

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

A new QTL for resistance to Fusarium ear rot in maize

Understanding the inheritance of resistance to Fusarium ear rot is a basic prerequisite for an efficient resistance breeding in maize. In this study, 250 recombinant inbred lines (RILs) along with their resistant (BT-1) and susceptible (N6) parents were planted in Zhengzhou with three replications in 2007 and 2008. Each line was artificially inoculated using the nail-punch method. Significant genotypic variation in response to Fusarium ear rot was detected in both years. Based on a genetic map containing 207 polymorphic simple sequence repeat (SSR) markers with average genetic distances of 8.83?cM, the ear rot resistance quantitative trait loci (QTL) were analyzed by composite interval mapping with a mixed model (MCIM) across the environments. In total, four QTL were detected on chromosomes 3, 4, 5, and 6. The resistance allele at each of these four QTL was contributed by resistant parent BT-1, and accounted for 2.5-10.2% of the phenotypic variation. However, no significant epistasis interaction effect was detected after a two-dimensional genome scan. Among the four QTL, one QTL with the largest effect on chromosome 4 (bin 4.06) can be suggested to be a new locus for resistance to Fusarium ear rot, which broadens the genetic base for resistance to the disease and can be used for further genetic improvement in maize-breeding programs.     

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.     

Mapping QTLs and meta-QTLs for two inflorescence architecture traits in multiple maize populations under different watering environments

Drought significantly affects the architectural development of maize inflorescence, which leads to massive losses in grain yield. However, the genetic mechanism for traits involved in inflorescence architecture in different watering environments, remains poorly understood in maize. In this study, 19 QTLs for tassel primary branch number (TBN) and ear number per plant (EN) were detected in 2 F_2:3 populations under both well-watered and water-stressed environments by single environment mapping with composite interval mapping (CIM); 11/19 QTLs were detected under water-stressed environments. Moreover, 21 QTLs were identified in the 2 F_2:3 populations by joint analysis of all environments with a mixed linear model based on composite interval mapping (MCIM), 11 QTLs were involved in QTL × environment interactions, seven epistatic interactions were identified with additive by additive/dominance effects. Remarkably, 12 stable QTLs (sQTLs) were simultaneously detected by single environment mapping with CIM and joint analysis through MCIM, which were concentrated in ten bins across the chromosomes: 1.05_1.07, 1.08_1.10, 2.01_2.04, 3.01, 4.06, 4.09, 5.06_5.07, 6.05, 7.00, and 7.04 regions. Twenty meta-QTLs (mQTLs) were detected across 19 populations under 51 watering environments using a meta-analysis, and 34 candidate genes were predicted in corresponding mQTLs regions to be involved in the regulation of inflorescence development and drought resistance. Therefore, these results provide valuable information for finding quantitative trait genes and to reveal the genetic mechanisms responsible for TBN and EN under different watering environments. Furthermore, alleles for TBN and EN provide useful targets for marker-assisted selection to generate high-yielding maize varieties.     

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

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

<Emphasis Type="Italic">qNCLB7.02</Emphasis>, a novel QTL for resistance to northern corn leaf blight in maize

Northern corn leaf blight (NCLB), which is caused by the hemibiotrophic fungal pathogen Setosphaeria turcica, is a devastating foliar disease that results in considerable maize yield losses. In the present study, quantitative trait locus (QTL) analysis was conducted across two environments using an ultra-high-density bin map constructed using recombinant inbred lines (RILs) derived from a cross between Ye478 and Qi319. A total of 11 QTLs, located on chromosomes 1, 4, 5, 6, 7, 8, 9, and 10, were detected that confer resistance to physiological race 0 of NCLB. Each QTL could explain 3.53–15.29% of the total phenotypic variation in disease resistance after artificial inoculation in two environments. Among these QTL, qNCLB7.02, which is located on chromosome 7, had the largest effect, accounting for 10.11 and 15.29% of the phenotypic variation in resistance in two field trials and BLUP. The common confidence interval (CI) for qNCLB7.02 was 1.4 Mb, according to the B73 RefGen_v3 sequence. The resistance effect of qNCLB7.02 was validated in 2016 by using chromosome segment substitution lines (CSSLs) derived from Qi319 as the donor in the genetic background of Ye478. The type 6 CSSL, which harbors introgressed qNCLB7.02, was found to be significantly associated with resistance to NCLB by linked marker bnlg1808 and exhibited greater resistance than the other CSSLs that did not carry this QTL (P?=?0.0008). The combination of linkage mapping in RILs and validation in CSSLs is a powerful approach for the dissection of QTL for disease resistance in maize.     

Identification of quantitative trait loci controlling resistance to maize chlorotic dwarf virus

Ineffective screening methods and low levels of disease resistance have hampered genetic analysis of maize (Zea mays L.) resistance to disease caused by maize chlorotic dwarf virus (MCDV). Progeny from a cross between the highly resistant maize inbred line Oh1VI and the susceptible inbred line Va35 were evaluated for MCDV symptoms after multiple virus inoculations, using the viral vector Graminella nigrifrons. Symptom severity scores from three rating dates were used to calculate area under the disease progress curve (AUDPC) scores for vein banding, leaf twist and tear, and whorl chlorosis. AUDPC scores for the F₂ population indicated that MCDV resistance was quantitatively inherited. Genotypic and phenotypic analyses of 314 F₂ individuals were compared using composite interval mapping (CIM) and analysis of variance. CIM identified two major quantitative trait loci (QTL) on chromosomes 3 and 10 and two minor QTL on chromosomes 4 and 6. Resistance was additive, with alleles from Oh1VI at the loci on chromosomes 3 and 10 contributing equally to resistance.     

Mapping QTLs contributing to <Emphasis Type="Italic">Ustilago maydis</Emphasis> resistance in specific plant tissues of maize

Quantitative trait loci (QTL) contributing to the frequency and severity of Ustilago maydis infection in the leaf, ear, stalk, and tassel of maize plants were mapped using an A188 × CMV3 and W23 × CMV3 recombinant inbred (RI) populations. QTLs mapped to genetic bins 2.04 and 9.04–9.05 of the maize genome contributed strongly (R ² = 18–28%) to variation in the frequency and severity of U. maydis infection over the entire plant in both populations and within the majority of environments. QTLs mapped to bins 3.05, 3.08, and 8.00 in the A188 × CMV3 population and bin 4.05 in both populations significantly contributed to the frequency or severity of infection in only the tassel tissue. QTLs mapped to bin 1.07 in the A188 × CMV3 population and bin 7.00 in the W23 × CMV3 population contributed to U. maydis resistance in only the ear tissue. Interestingly, the CMV3 allele of the QTL mapped to bin 1.10 in the A188 × CMV3 population significantly contributed to U. maydis susceptibility in the ear and stalk but significantly increased resistance in the tassel tissue. Digenic epistatic interactions between the QTL mapped to bin 5.08 and four distinct QTLs significantly contributed to the frequency and severity of infection over the entire plant and within the tassel tissue of the A188 × CMV3 population. Several QTLs detected in this study mapped to regions of the maize genome containing previously mapped U. maydis resistance QTLs and genes involved in plant disease resistance. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Confirming quantitative trait loci for aflatoxin resistance from Mp313E in different genetic backgrounds

The fungus Aspergillus flavus (Link:Fr) causes ear rot of maize (Zea mays L.) and produces the toxic metabolic product aflatoxin. One particularly effective method of controlling the fungus is via host plant resistance, but while several resistant breeding lines have been identified, transferring the resistance genes from these lines into elite cultivars has been less effective than needed. A high number of genes involved with resistance, each with a small effect, and some only found under certain environmental conditions, has hampered resistance breeding. The identification of markers linked to genomic regions associated with resistance would aid in this effort. The goals of this study were to identify and characterize quantitative trait loci (QTL) conferring resistance to aflatoxin accumulation from resistant maize donor Mp313E in a background of the susceptible inbred line Va35; to compare them to the QTL identified from Mp313E in a background of B73; and to test the stability of the QTL identified in Mp313E × Va35 in multiple environments by remapping the phenotypic tails of the Mp313E × Va35 mapping population in new locations. Twenty different QTL were found in this study, 11 of which were also found in different environments using the phenotypic tail subset mapping population, and five of which were likely the same as those reported in the Mp313E × B73 mapping population. This indicates that many of the QTL are stable over the environments and genetic backgrounds tested, which will make them more valuable in breeding efforts.     

Identification of a major quantitative trait locus for resistance to maize rough dwarf virus in a Chinese maize inbred line X178 using a linkage map based on 514 gene-derived single nucleotide polymorphisms

Maize rough dwarf disease (MRDD) is a worldwide viral disease and causes significant yield losses in maize (Zea mays L.) production. In this study, we mapped and characterized quantitative trait loci (QTL) conferring resistance to MRDD using 89 F8 recombinant inbred lines derived from a cross between X178 (resistant parent) and B73 (susceptible). The population was evaluated for MRDD resistance in Baoding, Hebei Province, China (a hot spot of MRDD incidence) under natural infection in 2008 and 2009 and artificial inoculation in 2010. Genotypic variances for disease severity index (DSI) were highly significant in the population. Heritability estimates for DSI evaluation were 0.472 and 0.467 in 2008 and 2009, respectively. The linkage map was constructed using 514 gene-derived single nucleotide polymorphisms (SNPs) and 72 simple sequence repeat markers, spanning a genetic distance of 1,059.72?cM with an average interval of 1.8?cM between adjacent markers. Multiple-QTL model mapping detected a major QTL for MRDD resistance on chromosome 8, explaining 24.6?C37.3% of the phenotypic variation across three environments. In 2010, an additional QTL was detected on chromosome 10, explaining 15.8% of the phenotypic variation. The major QTL on chromosome 8 and the SNP markers (SNP31, SNP548, and SNP284) co-located with the QTL peak have potential for further functional genomic analysis and use in molecular marker-assisted selection for MRDD resistance in maize.     

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.

     

Mapping of QTLs governing agronomic and yield traits in chickpea

Chickpea is one of the most important leguminous cool season food crops, cultivated prevalently in South Asia and Middle East. The main objective of this study was to identify quantitative trait loci (QTLs) associated with seven agronomic and yield traits in two recombinant inbred line populations of chickpea derived from the crosses JG62 × Vijay (JV population) and Vijay × ICC4958 (VI population) from at least three environments. Single locus QTL analysis involved composite interval mapping (CIM) for individual traits and multiple-trait composite interval mapping (MCIM) for correlated traits to detect pleiotropic QTLs. Two-locus analysis was conducted to identify the main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL × environment interactions. Through CIM analysis, a total of 106 significant QTLs (41 in JV and 65 in VI populations) were identified for the seven traits, of which one QTL each for plant height and days to maturity was common in both the populations. Six pleiotropic QTLs that were consistent over the environments were also identified. LG2 in JV and LG1a in VI contained at least one QTL for each trait. Hence, concentrating on these LGs in molecular breeding programs is most likely to bring simultaneous improvement in these traits.     

Identification of quantitative trait loci for leaf area and chlorophyll content in maize (Zea mays) under low nitrogen and low phosphorus supply

To investigate responses to nitrogen and phosphorus stress, 218 recombinant inbred maize (Zea mays L.) lines were grown under low nitrogen, low phosphorus, and control (i.e., nitrogen and phosphorus sufficient) conditions and evaluated at the silking stage for various traits, including leaf area, leaf chlorophyll content, flowering time, the interval between anthesis and silking, and grain yield. Among the 83 quantitative trait loci (QTL) detected, 29 were for controls, another 29 were for low nitrogen, and 25 were low phosphorus. These loci indicate that there were both common and specific genetic mechanisms underlying the investigated traits. Overlapping QTL for leaf size (area, length, and width) leaf chlorophyll level, flowering time, anthesis?Csilking interval, and grain yield were located at chromosome bin 2.03/2.04, bin 2.06/2.07/2.08, bin 4.01/4.02, bin 5.03/5.04, bin 6.07, bin 9.03, and bin 10.03/10.04. Many of these loci overlapped with previously reported loci controlling root growth as well as tolerance or response to nutrient deficiency. These QTL identify chromosome regions as targets for genetic improvement of low nitrogen and low phosphorus tolerance.     

Identification of large-effect QTL for kernel row number has potential for maize yield improvement

The kernel row number (KRN) per ear is an important component of maize (Zea mays L.) yield. In this study, a line with six kernel rows, MT-6, was used to investigate the genetic basis of KRN by quantitative trait locus (QTL) mapping. MT-6 was derived from a maize inbred line Mo17 and a teosinte entry X26-4 (Zea mays ssp. mexicana), with 23 % of its genome being homologous to X26-4. An MT-6/B73 F₂ segregating population consisting of 266 individuals was genotyped using 192 molecular markers spread evenly across the genome. The same F₂ population, together with its F_2:3 population, was phenotyped for KRN in three environments. Five individual QTL for KRN, including three substantially consistent major QTL detected in all environments, were identified on chromosomes 1, 2, 3, 4, and 5, respectively. These QTL accounted for 39.5–65.0 % of the KRN variation in these populations. Additionally, one pair of epistatic interaction between two loci with additive effects was detected and accounted for about 3 % of KRN variation. These results demonstrate that a few major QTL could substantially affect the evolution of maize KRNs and therefore provide valuable information for our understanding of the mechanism of KRN and the improvement in maize grain yield by molecular breeding.