Quantitative trait loci regulating sugar moiety of acylsugars in tomato

Acylsugars are broad-spectrum insect resistance sugar esters produced at very high levels by some accessions of the wild tomato, Solanum pennellii. Transferring acylsugar production from S. pennellii LA716 to cultivated tomato through traditional breeding developed the benchmark acylsugar breeding line CU071026. The base moiety of acylsugars (sucrose vs. glucose) can vary among S. pennellii accessions. Additionally the accession S. pennellii LA716 produces almost exclusively acylglucoses, but the breeding line CU071026 derived from S. pennellii LA716 produces exclusively acylsucroses. This study uses a BC1F1 and a BC1F2 population derived from the cross CU071026 × (CU071026 × S. pennellii LA716) to identify and confirm the action of three quantitative trait loci (QTL) on chromosomes 3, 4, and 11. The QTL on chromosomes 3 and 11 are both required for acylglucose production, while addition of the chromosome 4 QTL affects the level of acylglucose produced in the presence of the QTL on chromosomes 3 and 11. A three-way interaction between these acylglucose QTL was confirmed with a post hoc ANOVA. Identification of these three QTL provides a blueprint for breeding to shift acylsucrose production to acylglucose production in tomato breeding lines. The implications of these QTL and two additional QTL affecting total acylsugar level in the BC1F2 are discussed.     

Genetic analysis of an F2 intercross between two strains of Japanese quail provided evidence for quantitative trait loci affecting carcass composition and internal organs

The purpose of this study was to identify genomic regions, quantitative trait loci (QTL), affecting carcass traits on chromosome 1 in an F2 population of Japanese quail. For this purpose, two white and wild strains of Japanese quail (16 birds) were crossed reciprocally and F1 generation (34 birds) was created. The F2 generation was produced by intercrossing of the F1 birds. Phenotypic data including carcass weight, internal organs and carcass parts were collected on F2 animals (422 birds). The total mapping population (472 birds) was genotyped for 8 microsatellite markers on chromosome 1. QTL analysis was performed with interval mapping method applying the line-cross model. Significant QTL were identified for breast weight at 0 (P < 0.01), 172 (P < 0.05) and 206 (P < 0.01), carcass weight at 91 (P < 0.05), carcass fatness at 0 (P < 0.01), pre-stomach weight at 206 (P < 0.01) and uropygial weight gland at 197 (P < 0.01) cM on chromosome 1. There was also evidence for imprinted QTL affecting breast weight (P < 0.01) on chromosome 1. The proportion of the F2 phenotypic variation explained by the significant additive, dominance and imprinted QTL effects ranged from 1.0 to 7.3 %, 1.2 to 3.3 % and 1.4 to 2.2 %, respectively.     

Cytonuclear epistatic quantitative trait locus mapping for plant height and ear height in maize

Plant height (PH) and ear height (EH) are important traits in maize (Zea mays L.) breeding. Previous research has indicated that these traits are influenced by quantitative trait loci (QTL). However, previous studies attempting to identify the genetic bases of PH and EH have ignored the possibility that cytoplasmic effects and cytonuclear interactions may influence these traits. The objectives of this study were to identify the cytonuclear epistatic QTL and to evaluate the contributions of cytoplasm and QTL × cytoplasm interactions to phenotypic variation of PH and EH. A reciprocal mating design was conducted to generate F2 mapping populations comprising 120 F2 plants from the direct cross (JB × Y53) and 120 F2 plants from the reciprocal cross (Y53 × JB). F2:3 mapping populations were further generated with 91 direct F2:3 families and 120 reciprocal F2:3 families (ten plants per family). The PH and EH of the above F2 and F2:3 mapping populations were evaluated in the same field at the same experimental station in 2007 and 2008. A genetic linkage map with 154 microsatellite markers was constructed, which covered 1,735.0 cM of the maize genome with an average marker spacing of 11.3 cM. A joint-analysis method incorporating the cytonuclear interaction mapping approach was proposed and performed to detect cytonuclear interacting QTL affecting PH and EH. We identified six cytonuclear epistatic QTL affecting PH and five affecting EH. The average phenotypic variance explained by the genetic components of the QTL × cytoplasm interaction for each QTL was 18 % for PH and 9 % for EH. In addition, we observed cytoplasmic effects contributing substantially to phenotypic variance, reaching 9 and 40 % of the phenotypic contributions to PH and EH, respectively.     

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.     

Targeted mapping of quantitative trait locus regions for rhizomatousness in chromosome SBI-01 and analysis of overwintering in a Sorghum bicolor × S. propinquum population

While rhizome formation is intimately associated with perennialism and the derived benefit of sustainability, the introduction of this trait into temperate-zone adapted Sorghum cultivars requires precise knowledge of the genetics conditioning this trait in order to minimize the risk of weediness (e.g., Johnsongrass, S. halepense) while maximizing the productivity of perennial sorghum. As an incremental step towards dissecting the genetics of perennialism, a segregating F4 heterogeneous inbred family derived from a cross between S. bicolor and S. propinquum was phenotyped in both field and greenhouse environments for traits related to over-wintering and rhizome formation. An unseasonably cold winter in 2011 provided high selection pressure, and hence 74.8 % of the population did not survive. This severe selection pressure for cold tolerance allowed the resolution of two previously unidentified over-wintering quantitative trait locus (QTL) and more powerful correlation models than previously reported. Conflicting with previous reports, a maximum of 33 % of over-wintering variation could be explained by above-ground shoot formation from rhizomes; however, every over-wintering plant exhibited rhizome growth. Thus, while rhizome formation is required for over-wintering, other factors also determine survival in this interspecific population. The fine mapping of a previously reported rhizome QTL on sorghum chromosome SBI-01 was conducted by targeting this genomic region with additional simple sequence repeat markers. Fine mapping reduced the 2-LOD rhizome QTL interval from ~59 to ~14.5 Mb, which represents a 75 % reduction in physical distance and a 53 % reduction in the number of putative genes in the locus.     

An ultra-dense integrated linkage map for hexaploid chrysanthemum enables multi-allelic QTL analysis

Key message

We constructed the first integrated genetic linkage map in a polysomic hexaploid. This enabled us to estimate inheritance of parental haplotypes in the offspring and detect multi-allelic QTL.

Abstract

Construction and use of linkage maps are challenging in hexaploids with polysomic inheritance. Full map integration requires calculations of recombination frequency between markers with complex segregation types. In addition, detection of QTL in hexaploids requires information on all six alleles at one locus for each individual. We describe a method that we used to construct a fully integrated linkage map for chrysanthemum (Chrysanthemum × morifolium, 2n = 6x = 54). A bi-parental F1 population of 406 individuals was genotyped with an 183,000 SNP genotyping array. The resulting linkage map consisted of 30,312 segregating SNP markers of all possible marker dosage types, representing nine chromosomal linkage groups and 107 out of 108 expected homologues. Synteny with lettuce (Lactuca sativa) showed local colinearity. Overall, it was high enough to number the chrysanthemum chromosomal linkage groups according to those in lettuce. We used the integrated and phased linkage map to reconstruct inheritance of parental haplotypes in the F1 population. Estimated probabilities for the parental haplotypes were used for multi-allelic QTL analyses on four traits with different underlying genetic architectures. This resulted in the identification of major QTL that were affected by multiple alleles having a differential effect on the phenotype. The presented linkage map sets a standard for future genetic mapping analyses in chrysanthemum and closely related species. Moreover, the described methods are a major step forward for linkage mapping and QTL analysis in hexaploids.

     

Identification and QTL mapping of whitefly resistance components in Solanum galapagense

Solanum galapagense is closely related to the cultivated tomato and can show a very good resistance towards whitefly. A segregating population resulting from a cross between the cultivated tomato and a whitefly resistant S. galapagense was created and used for mapping whitefly resistance and related traits, which made it possible to study the genetic basis of the resistance. Quantitative trait loci (QTL) for adult survival co-localized with type IV trichome characteristics (presence, density, gland longevity and gland size). A major QTL (Wf-1) was found for adult survival and trichome characters on Chromosome 2. This QTL explained 54.1 % of the variation in adult survival and 81.5 % of the occurrence of type IV trichomes. A minor QTL (Wf-2) for adult survival and trichome characters was identified on Chromosome 9. The major QTL was confirmed in F3 populations. Comprehensive metabolomics, based on GCMS profiling, revealed that 16 metabolites segregating in the F2 mapping population were associated with Wf-1 and/or Wf-2. Analysis of the 10 most resistant and susceptible F2 genotypes by LCMS showed that several acyl sugars were present in significantly higher concentration in the whitefly resistant genotypes, suggesting a role for these components in the resistance as well. Our results show that whitefly resistance in S. galapagense seems to inherit relatively simple compared to whitefly resistance from other sources and this offers great prospects for resistance breeding as well as elucidating the underlying molecular mechanism(s) of the resistance.     

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.     

Mapping QTL for leaf area in oil palm using genotyping by sequencing

Leaf area is an important parameter in oil palm breeding as it is positively correlated with oil yield. However, measurement of leaf area is tedious and also destructive. In the present study, a breeding population with 145 palms derived from a cross between Deli Dura and Avros Pisifera was used to construct a high-density linkage map and identify quantitative trait loci (QTL) for leaf area in oil palm. Using genotyping by sequencing, a linkage map containing 2413 SNPs was constructed. The total length of the linkage map was 1161.89 cM, with an average marker spacing of 0.48 cM. Based on the continuous phenotyping of leaf area from 2010 to 2015, two suggestive QTL for leaf area were mapped on chromosomes (Chr) 3 and 9. The allelic effects of the QTL associated with leaf area in the mapping population were estimated by linear regression using ordinary least squares method. The QTL on Chr 9 explained 13.3% of phenotypic variation for leaf area. A candidate gene, ARC5, within the narrow interval of QTL on Chr 9 was identified. The gene was significantly higher expressed in leaf than root and fruit of oil palm. This high-quality and SNP-based map supplies a base to fine map QTL for agronomic traits in oil palm, and the markers closely linked to the stable QTL may be used in marker-assisted selection in oil palm breeding.     

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.     

Validation of yield-enhancing quantitative trait loci from a low-yielding wild ancestor of rice

A set of introgression lines (ILs) containing chromosomal segments from O. rufipogon (IRGC 105491), a wild relative of O. sativa, in the genetic background of an elite US variety, cv. Jefferson, was developed to confirm the performance of six yield-enhancing quantitative trait loci (QTL). Fifty BC3F3 ILs containing homozygous O. rufipogon introgressions at each of the target QTL regions, and as few background introgressions as possible, were selected for evaluation of yield and 14 yield-related traits in field studies conducted over 2 years at four locations in the southern USA. Performance of the IL families was compared with three commercial inbreds and one hybrid variety. IL families carrying introgressions from the low-yielding wild parent at the QTL yld2.1 and yld6.1 yielded 27.7 and 26.1 % more than Jefferson, respectively. IL yld2A, which possesses yld2.1, also performed well under alternate wetting and drying conditions in two field locations. After the first year of field trials, 10 of the top-performing BC3F4 families, representing five of the QTL targets, were genotyped with an Illumina 1,536 assay to define the size and location of the wild introgressions. BC3F4 families with the fewest background introgressions were backcrossed to Jefferson and selfed. The resulting BC4F2 families were screened with targeted single nucleotide polymorphism assays to identify individuals carrying homozygous introgressions across the target QTL. Twelve ILs, representing each of the six QTL targets, have been submitted to the Genetic Stocks Oryza Collection for studies on transgressive variation and as interspecific pre-breeding lines.     

Targeted linkage map densification to improve cell wall related QTL detection and interpretation in maize

Several QTLs for cell wall degradability and lignin content were previously detected in the F288 × F271 maize RIL progeny, including a set of major QTLs located in bin 6.06. Unexpectedly, allelic sequencing of genes located around the bin 6.06 QTL positions revealed a monomorphous region, suggesting that these QTLs were likely “ghost” QTLs. Refining the positions of all QTLs detected in this population was thus considered, based on a linkage map densification in most important QTL regions, and in several large still unmarked regions. Re-analysis of data with an improved genetic map (173 markers instead of 108) showed that ghost QTLs located in bin 6.06 were then fractionated over two QTL positions located upstream and downstream of the monomorphic region. The area located upstream of bin 6.06 position carried the major QTLs, which explained from 37 to 59 % of the phenotypic variation for per se values and extended on only 6 cM, corresponding to a physical distance of 2.2 Mbp. Among the 92 genes present in the corresponding area of the B73 maize reference genome, nine could putatively be considered as involved in the formation of the secondary cell wall [bHLH, FKBP, laccase, fasciclin, zinc finger C2H2-type and C3HC4-type (two genes), NF-YB, and WRKY]. In addition, based on the currently improved genetic map, eight QTLs were detected in bin 4.09, while only one QTL was highlighted in the initial investigation. Moreover, significant epistatic interaction effects were shown for all traits between these QTLs located in bin 4.09 and the major QTLs located in bin 6.05. Three genes related to secondary cell wall assembly (ZmMYB42, COV1-like, PAL-like) underlay QTL support intervals in this newly identified bin 4.09 region. The current investigations, even if they were based only on one RIL progeny, illustrated the interest of a targeted marker mapping on a genetic map to improve QTL position.     

Linkage mapping and identification of QTL affecting deoxynivalenol (DON) content (Fusarium resistance) in oats (Avena sativa L.)

Mycotoxins caused by Fusarium spp. is a major concern on food and feed safety in oats, although Fusarium head blight (FHB) is often less apparent than in other small grain cereals. Breeding resistant cultivars is an economic and environment-friendly way to reduce toxin content, either by the identification of resistance QTL or phenotypic evaluation. Both are little explored in oats. A recombinant-inbred line population, Hurdal × Z595-7 (HZ595, with 184 lines), was used for QTL mapping and was phenotyped for 3 years. Spawn inoculation was applied and deoxynivalenol (DON) content, FHB severity, days to heading and maturity (DH and DM), and plant height (PH) were measured. The population was genotyped with DArTs, AFLPs, SSRs and selected SNPs, and a linkage map of 1,132 cM was constructed, covering all 21 oat chromosomes. A QTL for DON on chromosome 17A/7C, tentatively designated as Qdon.umb-17A/7C, was detected in all experiments using composite interval mapping, with phenotypic effects of 12.2–26.6 %. In addition, QTL for DON were also found on chromosomes 5C, 9D, 13A, 14D and unknown_3, while a QTL for FHB was found on 11A. Several of the DON/FHB QTL coincided with those for DH, DM and/or PH. A half-sib population of HZ595, Hurdal × Z615-4 (HZ615, with 91 lines), was phenotyped in 2011 for validation of QTL found in HZ595, and Qdon.umb-17A/7C was again localized with a phenotypic effect of 12.4 %. Three SNPs closely linked to Qdon.umb-17A/7C were identified in both populations, and one each for QTL on 5C, 11A and 13A were identified in HZ595. These SNPs, together with those yet to be identified, could be useful in marker-assisted selection to pyramiding resistance QTL.     

Identification of a major quantitative trait locus for resistance to fire blight in the wild apple species Malus fusca

Fire blight, caused by the Gram-negative bacterium Erwinia amylovora, is the most important bacterial disease affecting apple (Malus × domestica) and pear (Pyrus communis) production. The use of antibiotic treatment, though effective to some degree, is forbidden or strictly regulated in many European countries, and hence an alternative means of control is essential. The planting of fire blight-resistant cultivars seems to be a highly feasible strategy. In this study, we explored a segregating population derived from a cross between the wild apple species Malus fusca and the M. × domestica cultivar Idared. F1 progenies used for mapping were artificially inoculated with Erwinia amylovora strain Ea222_JKI at a concentration of 10⁹ cfu/ml in three different years. The averages of percentage lesion length of all replicates of each genotype were used as numerical traits for statistical analysis. A Kruskal–Wallis analysis was used to determine marker–phenotype association and revealed a linkage group with Diversity Arrays Technology (DArT) markers significantly linked with fire blight. After locating the positions of the DArT markers on the Golden Delicious genome, simple sequence repeat (SSR) markers were developed from chromosome 10 to replace the DArT markers and to determine the quantitative trait locus (QTL) region. Multiple QTL mapping (MQM) revealed a strong QTL (Mfu10) on linkage group 10 of M. fusca explaining about 65.6 % of the phenotypic variation. This is the first report on a fire blight resistance QTL of M. fusca.     

Zinc and iron concentration QTL mapped in a Triticum spelta × T. aestivum cross

Key message

Ten QTL underlying the accumulation of Zn and Fe in the grain were mapped in a set of RILs bred from the cross Triticum spelta × T. aestivum . Five of these loci (two for Zn and three for Fe) were consistently detected across seven environments.

Abstract

The genetic basis of accumulation in the grain of Zn and Fe was investigated via QTL mapping in a recombinant inbred line (RIL) population bred from a cross between Triticum spelta and T. aestivum. The concentration of the two elements was measured from grain produced in three locations over two consecutive cropping seasons and from a greenhouse trial. The range in Zn and Fe concentration across the RILs was, respectively, 18.8–73.5 and 25.3–59.5 ppm, and the concentrations of the two elements were positively correlated with one another (rp =+0.79). Ten QTL (five each for Zn and Fe accumulation) were detected, mapping to seven different chromosomes. The chromosome 2B and 6A grain Zn QTL were consistently expressed across environments. The proportion of the phenotype explained (PVE) by QZn.bhu-2B was >16 %, and the locus was closely linked to the SNP marker 1101425|F|0, while QZn.bhu-6A (7.0 % PVE) was closely linked to DArT marker 3026160|F|0. Of the five Fe QTL detected, three, all mapping to chromosome 1A were detected in all seven environments. The PVE for QFe.bhu-3B was 26.0 %.     

Validation and high-resolution mapping of a major quantitative trait locus for alkaline salt tolerance in soybean using residual heterozygous line

Alkaline soil restricts soybean plant growth and yield. In our previous study, a major alkaline salt tolerance quantitative trait locus (QTL) was identified in soybean on chromosome 17. In this study, the residual heterozygous line (RHL46), which was selected from a population of F6 recombinant inbred lines (RILs) derived from a cross between an alkaline salt-sensitive soybean cultivar Jackson and a tolerant wild soybean accession JWS156-1, was used for validation and high-resolution mapping of the QTL. In a large segregating population (n = 1,109), which was produced by self-pollinating heterozygotes of RHL46, segregation of alkaline salt tolerance showed a continuous distribution, and the tolerant plants were predominant. Linkage mapping analysis revealed a major QTL with a large dominant effect for alkaline salt tolerance, and the highest LOD score was detected between the single sequence repeat (SSR) markers GM17-12.2 and Satt447. Furthermore, 10 fixed recombinant lines carrying chromosome fragments of different lengths in the QTL region were selected from the RHL46 progeny. Phenotype evaluation and SSR marker analysis of the recombinant lines narrowed down the QTL to a 3.33-cM interval region between the markers GM17-11.6 and Satt447 with a physical map length of approximately 771 kb. High-resolution mapping of the alkaline salt tolerance QTL will be useful not only for marker-assisted selection in soybean breeding programs but also for map-based cloning of the alkaline salt tolerance gene in order to understand alkaline salt tolerance in soybean and other plant species.     

Genome-wide association mapping of yield and yield components of spring wheat under contrasting moisture regimes

Key message

A stable QTL that may be used in marker-assisted selection in wheat breeding programs was detected for yield, yield components and drought tolerance-related traits in spring wheat association mapping panel.

Abstract

Genome-wide association mapping has become a widespread method of quantitative trait locus (QTL) identification for many crop plants including wheat (Triticum aestivum L.). Its benefit over traditional bi-parental mapping approaches depends on the extent of linkage disequilibrium in the mapping population. The objectives of this study were to determine linkage disequilibrium decay rate and population structure in a spring wheat association mapping panel (n = 285–294) and to identify markers associated with yield and yield components, morphological, phenological, and drought tolerance-related traits. The study was conducted under fully irrigated and rain-fed conditions at Greeley, CO, USA and Melkassa, Ethiopia in 2010 and 2011 (five total environments). Genotypic data were generated using diversity array technology markers. Linkage disequilibrium decay rate extended over a longer genetic distance for the D genome (6.8 cM) than for the A and B genomes (1.7 and 2.0 cM, respectively). Seven subpopulations were identified with population structure analysis. A stable QTL was detected for grain yield on chromosome 2DS both under irrigated and rain-fed conditions. A multi-trait region significant for yield and yield components was found on chromosome 5B. Grain yield QTL on chromosome 1BS co-localized with harvest index QTL. Vegetation indices shared QTL with harvest index on chromosome 1AL and 5A. After validation in relevant genetic backgrounds and environments, QTL detected in this study for yield, yield components and drought tolerance-related traits may be used in marker-assisted selection in wheat breeding programs.     

QTL mapping for downy mildew resistance in cucumber via bulked segregant analysis using next-generation sequencing and conventional methods

Key message

QTL mapping using NGS-assisted BSA was successfully applied to an F ₂ population for downy mildew resistance in cucumber. QTLs detected by NGS-assisted BSA were confirmed by conventional QTL analysis.

Abstract

Downy mildew (DM), caused by Pseudoperonospora cubensis, is one of the most destructive foliar diseases in cucumber. QTL mapping is a fundamental approach for understanding the genetic inheritance of DM resistance in cucumber. Recently, many studies have reported that a combination of bulked segregant analysis (BSA) and next-generation sequencing (NGS) can be a rapid and cost-effective way of mapping QTLs. In this study, we applied NGS-assisted BSA to QTL mapping of DM resistance in cucumber and confirmed the results by conventional QTL analysis. By sequencing two DNA pools each consisting of ten individuals showing high resistance and susceptibility to DM from a F₂ population, we identified single nucleotide polymorphisms (SNPs) between the two pools. We employed a statistical method for QTL mapping based on these SNPs. Five QTLs, dm2.2, dm4.1, dm5.1, dm5.2, and dm6.1, were detected and dm2.2 showed the largest effect on DM resistance. Conventional QTL analysis using the F₂ confirmed dm2.2 (R ² = 10.8–24 %) and dm5.2 (R ² = 14–27.2 %) as major QTLs and dm4.1 (R ² = 8 %) as two minor QTLs, but could not detect dm5.1 and dm6.1. A new QTL on chromosome 2, dm2.1 (R ² = 28.2 %) was detected by the conventional QTL method using an F₃ population. This study demonstrated the effectiveness of NGS-assisted BSA for mapping QTLs conferring DM resistance in cucumber and revealed the unique genetic inheritance of DM resistance in this population through two distinct major QTLs on chromosome 2 that mainly harbor DM resistance.

     

Fine mapping a major QTL for kernel number per row under different phosphorus regimes in maize (Zea mays L.)

Phosphorus (P) is one of the essential macronutrients for plant growth and development. Grain yield is the primary trait of interest in maize breeding programs. Maize grain yield and yield-related traits are seriously affected by P deficiency. Kernel number per row (KN), as one of the major components of grain yield, has attracted the attention of more and more breeders. In our previous study, one major QTL (named qKN), controlling KN under different P regimes was mapped to the interval between molecular markers bnlg1360 and umc1645 on chromosome 10 using a F _2:3 population derived from the cross between maize inbreds 178 and 5,003 (107). In order to understand its genetic basis, we developed a population of near isogenic lines (NILs) and two P regimes were used to fine map and characterize qKN. The QTL qKN was finally localized in a region of ~480 kb. A single qKN allele of inbred 178 increased KN by 6.08–10.76 % in the 5,003 (107) background; qKN acted in a partially dominant manner. Our results will be instrumental for the future identification and isolation of the candidate gene underlying qKN. The tightly linked molecular markers that we developed for qKN will be useful in maize breeding programs for improving KN applying the marker-assisted selection.