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 of QTL for resistance to the Mediterranean corn borer attack using the intermated B73 × Mo17 (IBM) population of maize

The Mediterranean corn borer or pink stem borer (MCB, Sesamia nonagrioides Lefebvre) causes important yield losses as a consequence of stalk tunneling and direct kernel damage. B73 and Mo17 are the source of the most commercial valuable maize inbred lines in temperate zones, while the intermated B73 × Mo17 (IBM) population is an invaluable source for QTL identification. However, no or few experiments have been carried out to detect QTL for corn borer resistance in the B73 × Mo17 population. The objective of this work was to locate QTL for resistance to stem tunneling and kernel damage by MCB in the IBM population. We detected a QTL for kernel damage at bin 8.05, although the effect was small and two QTL for stalk tunneling at bins 1.06 and 9.04 in which the additive effects were 4 cm, approximately. The two QTL detected for MCB resistance were close to other QTL consistently found for European corn borer (ECB, Ostrinia nubilalis Hübner) resistance, indicating mechanisms of resistance common to both pests or gene clusters controlling resistance to different plagues. The precise mapping achieved with the IBM population will facilitate the QTL pyramiding and the positional cloning of the detected QTL.     

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.     

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.     

Mapping quantitative trait loci associated with southern leaf blight resistance in maize (Zea mays L.)

Southern leaf blight (SLB) caused by the fungus Cochliobolus heterostrophus (Drechs.) Drechs. is a major foliar disease of maize worldwide. Our objectives were to identify quantitative trait loci (QTL) for resistance to SLB and flowering traits in recombinant inbred line (RIL) population derived from the cross of inbred lines LM5 (resistant) and CM140 (susceptible). A set of 207 RILs were phenotyped for resistance to SLB at three time intervals for two consecutive years. Four putative QTL for SLB resistance were detected on chromosomes 3, 8 and 9 that accounted for 54% of the total phenotypic variation. Days to silking and anthesis–silking interval (ASI) QTL were located on chromosomes 6, 7 and 9. A comparison of the obtained results with the published SLB resistance QTL studies suggested that the detected bins 9.03/02 and 8.03/8.02 are the hot spots for SLB resistance whereas novel QTL were identified in bins 3.08 and 8.01/8.04. The linked markers are being utilized for marker‐assisted mobilization of QTL conferring resistance to SLB in elite maize backgrounds. Fine mapping of identified QTL will facilitate identification of candidate genes underlying SLB resistance.     

Quantitative trait loci mapping of yield and related traits using a high-density genetic map of maize

Improving grain yield is the ultimate goal of the maize-breeding programs. In this study, analyses of conditional and unconditional quantitative trait locus (QTL) and epistatic interactions were used to elucidate the genetic architecture of yield and its related traits. A total of 15 traits of a recombinant inbred line population, including yield per plant (YPP), seven ear-related traits, and seven kernel-related traits, were measured in six different environments. Based on the genetic linkage map constructed using 2091 bins as markers, 56 main-effect QTLs for these traits were identified. These QTLs were distributed across eight genomic regions (bin 1.06, bin 4.02/4.05/4.08, bin 5.04, bin 7.04, bin 8.08, and bin 9.04), within the marker intervals of 85.45–6260.66 kb, and the phenotypic variance explained ranging from 5.69 to 11.56 %. One gene (GRMZM2G168229) encoding SBP-box domain protein was located in the small interval of qKRN4-3 and may be involved in patterning of kernel row number. Seventeen conditional QTLs identified for YPP were conditioned on its related traits and explained 6.18–23.15 % of the phenotypic variance. Conditional mapping analysis revealed that qYPP4-1, qYPP6-1, and qYPP8-1 are partially influenced by YPP-related traits at the individual QTL level. Digenic epistatic analysis identified 12 digenic interactions involving 22 loci across the whole genome. In addition, conditional digenic epistatic analysis identified 14 digenic interactions involving 21 loci. This study provides valuable information for understanding the genetic relationship between YPP and related traits and constitutes the first step toward the cloning of the relevant genes.     

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.     

Two consensus quantitative trait loci clusters controlling anthesis–silking interval, ear setting and grain yield might be related with drought tolerance in maize

Unravelling the molecular basis of drought tolerance will provide novel opportunities for improving crop yield under water-limited conditions. The present study was conducted to identify quantitative trait loci (QTLs) controlling anthesis–silking interval (ASI), ear setting percentage (ESP) and grain yield (GY). The mapping population included 234 F₂ plants derived from the cross X178 (drought tolerant) × B73 (drought susceptible). The corresponding F_2:3 progenies, along with their parents, were evaluated for the above-mentioned traits under both well-watered and water-stressed field conditions in three different trials carried out in central and southern China. Interval mapping and composite interval mapping identified 45 and 65 QTLs for the investigated traits, respectively. Two QTL clusters influencing ASI and ESP on chromosomes 1 (bin 1.03) and 9 (bins 9.03–9.05) were identified in more than two environments, showing sizeable additive effects and contribution to phenotypic variance; these two QTL clusters influenced GY only in one environment. No significant interaction was detected between the two genomic regions. A comparative analysis of these two QTL clusters with the QTLs controlling maize drought tolerance previously described in three mapping populations confirmed and extended their relevance for marker-assisted breeding to improve maize production under water-limited conditions.     

Genetic analysis and major QTL detection for maize kernel size and weight in multi-environments

Key Message

Twelve major QTL in five optimal clusters and several epistatic QTL are identified for maize kernel size and weight, some with pleiotropic will be promising for fine-mapping and yield improvement.

Abstract

Kernel size and weight are important target traits in maize (Zea mays L.) breeding programs. Here, we report a set of quantitative trait loci (QTL) scattered through the genome and significantly controlled the performance of four kernel traits including length, width, thickness and weight. From the cross V671 (large kernel) × Mc (small kernel), 270 derived F_2:3 families were used to identify QTL of maize kernel-size traits and kernel weight in five environments, using composite interval mapping (CIM) for single-environment analysis along with mixed linear model-based CIM for joint analysis. These two mapping strategies identified 55 and 28 QTL, respectively. Among them, 6 of 23 coincident were detected as interacting with environment. Single-environment analysis showed that 8 genetic regions on chromosomes 1, 2, 4, 5 and 9 clustered more than 60 % of the identified QTL. Twelve stable major QTLs accounting for over 10 % of phenotypic variation were included in five optimal clusters on the genetic region of bins 1.02–1.03, 1.04–1.06, 2.05–2.07, 4.07–4.08 and 9.03–9.04; the addition and partial dominance effects of significant QTL play an important role in controlling the development of maize kernel. These putative QTL may have great promising for further fine-mapping with more markers, and genetic improvement of maize kernel size and weight through marker-assisted breeding.     

Quantitative trait locus mapping of resistance to Aspergillus flavus infection using a recombinant inbred line population in maize

Aflatoxin contamination of maize (Zea mays L.) grain caused by Aspergillus flavus is a serious health hazard to animals and humans. Development of maize varieties resistant to A. flavus infection and/or aflatoxin production can reduce this contamination. This study was conducted to identify quantitative trait loci (QTL) associated with resistance to A. flavus infection. A recombinant inbred line population was developed derived from RA, a maize inbred line resistant to A. flavus infection, and M53, a susceptible inbred line. After inoculation with A. flavus under controlled conditions, the kernels from each plant line grown in three different environments were evaluated for infection level. Categorical inoculation data were collected for each plant line based on the percentage of the kernel surface covered by fungal conidia. Significant genotypic variation in infection level was observed in all environments. Based on a genetic map containing 916 polymorphic simple sequence repeat and single nucleotide polymorphism markers, the resistance QTL were initially analyzed by composite interval mapping (CIM) separately for each environment. One QTL in bin 5.03 was detected in all environments, and seven other QTL were identified in one environment. Next, a mixed model based on CIM (MCIM) was employed for QTL analysis using data from the three environments simultaneously. Significant epistasis and epistasis × environment interaction to A. flavus infection were revealed. The QTL in bin 5.03 was repeatedly detected by the MCIM. This QTL explained the largest phenotypic variation among all of the detected QTL and could be considered as a major QTL for use in breeding for A. flavus resistance.     

Genetic mapping and QTL analysis for yield and agronomic traits with an F2:3 population derived from a waxy corn × sweet corn cross

We constructed a framework map using SSR markers in the F₂ population derived from a cross between a waxy corn inbred line and a sweet corn inbred line. We constructed a genetic linkage map of the F_2:3 population employing 295 SSR markers on 158 F₂ individuals produced from the cross. The map comprised a total genomic length of 2,626.5 cM in 10 linkage groups and an average distance between markers of 8.9 cM. The number of loci per linkage group ranged from 27 (chr. 5) to 34 (chr. 7). The genetic distance per linkage group ranged from 213.6 cM (chr. 10) to 360.6 cM (chr. 2). Χ ² tests revealed that 254 markers (86.1 %) distributed over all 10 chromosomes exhibited a Mendelian segregation ratio of 1:2:1. A total of 14 quantitative trait loci (QTLs) for days to silking (DTS), plant height (PH), ear height (EH), ear height ratio (ER), ear length (L-ear), and setted ear length (L-sear) were found in the 158 F₂ progeny. They were mapped to chromosomes 1, 2, 3, 7, 8, and 10. Among them, one QTL was associated with DTS, three with PH, six with EH, one with ER, two with L-ear, and one QTL was related to L-sear. In our study, we found that four QTLs: qDTS1, qEH1a, qEH1b, and qPH1, were clustered between umc2390 and umc1603 on chromosome 1. These new QTLs identified by the present study could serve as useful molecular markers in selecting for yield and agronomic traits in maize. The results of this study may improve the identification and characterization of genes responsible for yield and agronomic traits in waxy corn and sweet corn.     

QTL mapping of phosphorus efficiency and relative biologic characteristics in maize (Zea mays L.) at two sites

The phosphorus efficiency, relative biologic characteristics and relative root exudations as well as the quantitative trait loci associated with these traits were determined for an F_2:3 population derived from the cross of two contrasting maize (Zea mays L.) genotypes, 082 and Ye107. A total of 241 F_2:3 families were evaluated in replicated trials under normal phosphorus (50 kg P/ha) and low phosphorus (0 kg P/ha) conditions in 2007 at two sites (Kaixian and Southwest University). The genetic map constructed by 275 SSR and 146 AFLP markers spanned 1,681.3 cM in length with an average interval of 3.84 cM. The heritability of PE, PAE, RPH, RBW, RRW, RLA, TPS, RTW, RFN, RAP and RH was all high ( $h_{\text{b}}^2 > 60\% $ ) whereas the heritability of root exudations was all low ( $h_{\text{b}}^2 > 60\% $ ).By using composite interval mapping (CIM), a total of 30 and 45 distinct QTLs were identified at Kaixian and Southwest University. At two sites, the number of same QTL located on common region was 16, five for PE (bins 1.07, 4.09, 5.05, 5.07, 5.08), three for RBW (bins 3.04, 5.04, 6.05), three for RRW (bins 5.05, 5.06, 5.07), one for RLA (bins 3.04), two for TPS (bins 3.08, 5.07), two for RTW (bins 5.05, 5.06). These QTLs explained 21% of the phenotypic variation of PE, 5–9% of RBW, 13–16% of RRW, 9% of TPS, 7% of RTW, respectively. The 16 common QTLs displayed mostly partial dominance or over-dominance gene action. Most QTL alleles conferring high values for the traits came from two parents. Mapping analysis identified chromosomal regions associated with two or more traits in a cluster, which was consistent with correlation among traits. The result showed either pleiotropy or tight linkage among QTL. Five common regions for same QTL at different site were found in the interval bnlg1556-bnlg1564 (bins 1.06), mmc0341-umc1101 (bins 4.08), mmc0282-phi333597 (bins 5.05), bnlg1346-bnlg1695 (bins 5.07) and bnlg118a-umc2136 (bins 5.08), which were important for PE. The information reported in the present paper may be useful for improving phosphorus efficiency by means of marker-assisted selection.     

Genetic basis of soybean adaptation to North American vs. Asian mega-environments in two independent populations from Canadian × Chinese crosses

One of the goals of plant breeding is to increase yield with improved quality characters. Plant introductions (PI) are a rich source of favorable alleles that could improve different characters in modern soybean [Glycine max (L.) Merril] including yield. The objectives of this study were to identify yield QTL underlying the genetic basis for differential adaptation of soybeans to the Canadian, United States or Chinese mega-environments (ME) and to evaluate the relationship and colocalization between yield and agronomic traits QTL. Two crosses between high-yielding Canadian cultivars and elite Chinese cultivars, OAC Millennium × Heinong 38 and Pioneer 9071 × #8902, were used to develop two recombinant inbred line (RIL) populations. Both populations were evaluated at different locations in Ontario, Canada; Minnesota, United States (US), Heilongjiang and Jilin, China, in 2009 and 2010. Significant variation for yield was observed among the RILs of both populations across the three hypothetical ME. Two yield QTL (linked to the interval Satt364–Satt591 and Satt277) and one yield QTL (linked to marker Sat_341) were identified by single-factor ANOVA and interval mapping across all ME in populations 1 and 2, respectively. The most frequent top ten high-yielding lines across all ME carried most of the high-yielding alleles of the QTL that were identified in two and three ME. Both parents contributed favorable alleles, which suggests that not only the adapted parent but also the PI parents are potential sources of beneficial alleles in reciprocal environments. Other QTL were detected also at two and one ME. Most of the yield QTL were co-localized with a QTL associated with an agronomic trait in one, two, or three ME in just one or in both populations. Results suggested that most of the variation observed in seed yield can be explained by the variation of different agronomic traits such a maturity, lodging and height. Novel alleles coming from PI can favorably contribute, directly or indirectly, to seed yield and the utilization of QTL detected across one, two or three ME would facilitate the new allele introgression into breeding populations in both North America and China.     

Identification of quantitative trait loci contributing to yield and seed quality parameters under terminal drought in barley advanced backcross lines

Drought is a major limiting factor for barley production, especially in the primary areas of its cultivation. Wild barley represents a major source of favourable alleles for increasing the genetic variation for multiple traits including resistance to both biotic and abiotic stresses. We used advanced backcross quantitative trait locus (AB-QTL) analysis of a BC3-doubled haploid population developed between the cultivated parent Brenda (Hordeum vulgare ssp. vulgare) and the wild accession HS584 (H. vulgare ssp. spontaneum) to study the contribution of wild barley in improving various agronomic and seed quality traits under post-anthesis drought. The experiment was carried out at two different locations (IPK, Gatersleben and Nordsaat, Böhnshausen) and terminal drought was imposed by withholding water or spraying with potassium iodide at 10 days after flowering under greenhouse or field conditions, respectively. QTL analysis indicated that wild barley contributed favourably to most of the traits studied under both control and drought conditions. A total of seven hot-spot QTL regions with co-localizing QTL for various traits harboured more than 80 % of the stable QTL detected in the present study. For yield and thousand-grain weight and their respective drought tolerance indices, most of the QTL were derived from Brenda. On the other hand, for traits like seed length and seed nitrogen content, all the QTL were contributed by HS584, the parent having higher trait value. A significantly reduced carbon/nitrogen (C/N) ratio in the selected contrasting inferior lines compared to superior ones suggests that C/N ratio could be a potential parameter for screening not just seed quality parameters but also grain weight performance under terminal drought.     

Quantitative trait loci analysis of phenotypic traits and principal components of maize tassel inflorescence architecture

Maize tassel inflorescence architecture is relevant to efficient production of F₁ seed and yield performance of F₁ hybrids. The objectives of this study were to identify genetic relationships among seven measured tassel inflorescence architecture traits and six calculated traits in a maize backcross population derived from two lines with differing tassel architectures, and identify Quantitative Trait Loci (QTL) involved in the inheritance of those tassel inflorescence architecture traits. A Principal Component (PC) analysis was performed to examine relationships among correlated traits. Traits with high loadings for PC1 were branch number and branch number density, for PC2 were spikelet density on central spike and primary branch, and for PC3 were lengths of tassel and central spike. We detected 45 QTL for individual architecture traits and eight QTL for the three PCs. For control of inflorescence architecture, important QTL were found in bins 7.02 and 9.02. The interval phi034—ramosa1 (ral) in bin 7.02 was associated with six individual architecture trait QTL and explained the largest amount of phenotypic variation (17.3%) for PC1. Interval bnlg344–phi027 in bin 9.02 explained the largest amount of phenotypic variation (14.6%) for PC2. Inflorescence architecture QTL were detected in regions with candidate genes fasciated ear2, thick tassel dwarf1, and ral. However, the vast majority of QTL mapped to regions without known candidate genes, indicating positional cloning efforts will be necessary to identify these genes.     

Mapping QTL for grain yield and other agronomic traits in post-rainy sorghum [Sorghum bicolor (L.) Moench]

Sorghum, a cereal of economic importance ensures food and fodder security for millions of rural families in the semi-arid tropics. The objective of the present study was to identify and validate quantitative trait loci (QTL) for grain yield and other agronomic traits using replicated phenotypic data sets from three post-rainy dry sorghum crop seasons involving a mapping population with 245 F₉ recombinant inbred lines derived from a cross of M35-1 × B35. A genetic linkage map was constructed with 237 markers consisting of 174 genomic, 60 genic and 3 morphological markers. The QTL analysis for 11 traits following composite interval mapping identified 91 QTL with 5–12 QTL for each trait. QTL detected in the population individually explained phenotypic variation between 2.5 and 30.3 % for a given trait and six major genomic regions with QTL effect on multiple traits were identified. Stable QTL across seasons were identified. Of the 60 genic markers mapped, 21 were found at QTL peak or tightly linked with QTL. A gene-based marker XnhsbSFCILP67 (Sb03g028240) on SBI-03, encoding indole-3-acetic acid-amido synthetase GH3.5, was found to be involved in QTL for seven traits. The QTL-linked markers identified for 11 agronomic traits may assist in fine mapping, map-based gene isolation and also for improving post-rainy sorghum through marker-assisted breeding.     

Marker-trait associations in Virginia Tech winter barley identified using genome-wide mapping

Genome-wide association studies (GWAS) provide an opportunity to examine the genetic architecture of quantitatively inherited traits in breeding populations. The objectives of this study were to use GWAS to identify chromosome regions governing traits of importance in six-rowed winter barley (Hordeum vulgare L.) germplasm and to identify single-nucleotide polymorphisms (SNPs) markers that can be implemented in a marker-assisted breeding program. Advanced hulled and hulless lines (329 total) were screened using 3,072 SNPs as a part of the US. Barley Coordinated Agricultural Project (CAP). Phenotypic data collected over 4 years for agronomic and food quality traits and resistance to leaf rust (caused by Puccinia hordei G. Otth), powdery mildew [caused by Blumeria graminis (DC.) E.O. Speer f. sp. hordei Em. Marchal], net blotch (caused by Pyrenophora teres), and spot blotch [caused by Cochliobolus sativus (Ito and Kuribayashi) Drechsler ex Dastur] were analyzed with SNP genotypic data in a GWAS to determine marker-trait associations. Significant SNPs associated with previously described quantitative trait loci (QTL) or genes were identified for heading date on chromosome 3H, test weight on 2H, yield on 7H, grain protein on 5H, polyphenol oxidase activity on 2H and resistance to leaf rust on 2H and 3H, powdery mildew on 1H, 2H and 4H, net blotch on 5H, and spot blotch on 7H. Novel QTL also were identified for agronomic, quality, and disease resistance traits. These SNP-trait associations provide the opportunity to directly select for QTL contributing to multiple traits in breeding programs.     

QTL mapping of stalk bending strength in a recombinant inbred line maize population

Stalk bending strength (SBS) is a reliable indicator for evaluating stalk lodging resistance of maize plants. Based on biomechanical considerations, the maximum load exerted to breaking (F _max), the breaking moment (M _max) and critical stress (σ _max) are three important parameters to characterize SBS. We investigated the genetic architecture of SBS by phenotyping F _max, M _max and σ _max of the fourth internode of maize plants in a population of 216 recombinant inbred lines derived from the cross B73 × Ce03005 evaluated in four environments. Heritability of F _max, M _max and σ _max was 0.81, 0.79 and 0.75, respectively. F _max and σ _max were positively correlated with several other stalk characters. By using a linkage map with 129 SSR markers, we detected two, three and two quantitative trait loci (QTL) explaining 22.4, 26.1 and 17.2 % of the genotypic variance for F _max, M _max and σ _max, respectively. The QTL for F _max, M _max and σ _max located in adjacent bins 5.02 and 5.03 as well as in bin 10.04 for F _max were detected with high frequencies in cross-validation. As our QTL mapping results suggested a complex polygenic inheritance for SBS-related traits, we also evaluated the prediction accuracy of two genomic prediction methods (GBLUP and BayesB). In general, we found that both explained considerably higher proportions of the genetic variance than the values obtained in QTL mapping with cross-validation. Nevertheless, the identified QTL regions could be used as a starting point for fine mapping and gene cloning.     

Meta-analysis of quantitative trait loci for grain yield and component traits under reproductive-stage drought stress in an upland rice population

A recombinant inbred population developed from a cross between high-yielding lowland rice (Oryza sativa L.) subspecies indica cv. IR64 and upland tropical rice subspecies japonica cv. Cabacu was used to identify quantitative trait loci (QTLs) for grain yield (GY) and component traits under reproductive-stage drought stress. One hundred fifty-four lines were grown in field trials in Indonesia under aerobic conditions by giving surface irrigation to field capacity every 4 days. Water stress was imposed for a period of 15 days during pre-flowering by withholding irrigation at 65 days after seeding. Leaf rolling was scored at the end of the stress period and eight agronomic traits were evaluated after recovery. The population was also evaluated for root pulling force, and a total of 201 single nucleotide polymorphism markers were used to construct the molecular genetic linkage map and QTL mapping. A QTL for GY under drought stress was identified in a region close to the sd1 locus on chromosome 1. QTL meta-analysis across diverse populations showed that this QTL was conserved across genetic backgrounds and co-localized with QTLs for leaf rolling and osmotic adjustment (OA). A QTL for percent seed set and grains per panicle under drought stress was identified on chromosome 8 in the same region as a QTL for OA previously identified in three different populations.     

Identification of QTLs associated with agronomic performance under nitrogen-deficient conditions using chromosome segment substitution lines of a wild rice relative, <Emphasis Type="Italic">Oryza rufipogon</Emphasis>

Improved root system architecture can enhance agronomic performance by increasing water and nitrogen (N) acquisition efficiency. However, little is known about interaction between root system architecture and agronomic performance under field environments. To gain a better understanding about the genetic basis of these relationships, we evaluated a set of chromosome segment substitution lines (CSSLs) derived from crosses between a tropical japonica rice cultivar ‘Curinga’ and a wild species Oryza rufipogon accession IRGC105491. Root system architectural traits were investigated using the CSSLs at 40 days old seedlings using the root basket method under hydroponic conditions, and agronomic performances were also tested under field conditions with different N treatments. Agronomic performances were computed as the ratio of a trait value under low to high N treatments, including grain yield and biomass yield as nitrogen-deficiency tolerance (NDT) traits. Root architecture and NDT trait QTLs were mapped using 238 SNP marker loci. A total of 13 QTLs for root system architectural, NDT and morpho-physiological traits were identified on chromosomes 1, 3, 4, 5, 7, 8, 9, 10 and 12. Interestingly, a QTL for deeper root number was identified the region of SNP markers between id1012330 and id1021697 on chromosome 1 under hydroponic conditions overlapped with a QTL for NDT trait of relative grain yield (qRGY1). These results suggest that deeper root trait is helpful to maintain grain yield under nitrogen-deficient conditions. The QTL associated root architecture could potentially be used in future rice-breeding efforts to increase agronomic performance under nitrogen-deficient conditions.