QTL analysis in multiple sorghum populations facilitates the dissection of the genetic and physiological control of tillering

Key message

A QTL model for the genetic control of tillering in sorghum is proposed, presenting new opportunities for sorghum breeders to select germplasm with tillering characteristics appropriate for their target environments.

Abstract

Tillering in sorghum can be associated with either the carbon supply–demand (S/D) balance of the plant or an intrinsic propensity to tiller (PTT). Knowledge of the genetic control of tillering could assist breeders in selecting germplasm with tillering characteristics appropriate for their target environments. The aims of this study were to identify QTL for tillering and component traits associated with the S/D balance or PTT, to develop a framework model for the genetic control of tillering in sorghum. Four mapping populations were grown in a number of experiments in south east Queensland, Australia. The QTL analysis suggested that the contribution of traits associated with either the S/D balance or PTT to the genotypic differences in tillering differed among populations. Thirty-four tillering QTL were identified across the populations, of which 15 were novel to this study. Additionally, half of the tillering QTL co-located with QTL for component traits. A comparison of tillering QTL and candidate gene locations identified numerous coincident QTL and gene locations across populations, including the identification of common non-synonymous SNPs in the parental genotypes of two mapping populations in a sorghum homologue of MAX1, a gene involved in the control of tiller bud outgrowth through the production of strigolactones. Combined with a framework for crop physiological processes that underpin genotypic differences in tillering, the co-location of QTL for tillering and component traits and candidate genes allowed the development of a framework QTL model for the genetic control of tillering in sorghum.     

Stripe rust and leaf rust resistance QTL mapping,epistatic interactions,and co-localization with stem rust resistance loci in spring wheat evaluated over three continents

Key message

In wheat, advantageous gene-rich or pleiotropic regions for stripe, leaf, and stem rust and epistatic interactions between rust resistance loci should be accounted for in plant breeding strategies.

Abstract

Leaf rust (Puccinia triticina Eriks.) and stripe rust (Puccinia striiformis f. tritici Eriks) contribute to major production losses in many regions worldwide. The objectives of this research were to identify and study epistatic interactions of quantitative trait loci (QTL) for stripe and leaf rust resistance in a doubled haploid (DH) population derived from the cross of Canadian wheat cultivars, AC Cadillac and Carberry. The relationship of leaf and stripe rust resistance QTL that co-located with stem rust resistance QTL previously mapped in this population was also investigated. The Carberry/AC Cadillac population was genotyped with DArT^® and simple sequence repeat markers. The parents and population were phenotyped for stripe rust severity and infection response in field rust nurseries in Kenya (Njoro), Canada (Swift Current), and New Zealand (Lincoln); and for leaf rust severity and infection response in field nurseries in Canada (Swift Current) and New Zealand (Lincoln). AC Cadillac was a source of stripe rust resistance QTL on chromosomes 2A, 2B, 3A, 3B, 5B, and 7B; and Carberry was a source of resistance on chromosomes 2B, 4B, and 7A. AC Cadillac contributed QTL for resistance to leaf rust on chromosome 2A and Carberry contributed QTL on chromosomes 2B and 4B. Stripe rust resistance QTL co-localized with previously reported stem rust resistance QTL on 2B, 3B, and 7B, while leaf rust resistance QTL co-localized with 4B stem rust resistance QTL. Several epistatic interactions were identified both for stripe and leaf rust resistance QTL. We have identified useful combinations of genetic loci with main and epistatic effects. Multiple disease resistance regions identified on chromosomes 2A, 2B, 3B, 4B, 5B, and 7B are prime candidates for further investigation and validation of their broad resistance.     

Bayesian QTL analyses using pedigreed families of an outcrossing species,with application to fruit firmness in apple

Key message

Proof of concept of Bayesian integrated QTL analyses across pedigree-related families from breeding programs of an outbreeding species. Results include QTL confidence intervals, individuals’ genotype probabilities and genomic breeding values.

Abstract

Bayesian QTL linkage mapping approaches offer the flexibility to study multiple full sib families with known pedigrees simultaneously. Such a joint analysis increases the probability of detecting these quantitative trait loci (QTL) and provide insight of the magnitude of QTL across different genetic backgrounds. Here, we present an improved Bayesian multi-QTL pedigree-based approach on an outcrossing species using progenies with different (complex) genetic relationships. Different modeling assumptions were studied in the QTL analyses, i.e., the a priori expected number of QTL varied and polygenic effects were considered. The inferences include number of QTL, additive QTL effect sizes and supporting credible intervals, posterior probabilities of QTL genotypes for all individuals in the dataset, and QTL-based as well as genome-wide breeding values. All these features have been implemented in the FlexQTL^? software. We analyzed fruit firmness in a large apple dataset that comprised 1,347 individuals forming 27 full sib families and their known ancestral pedigrees, with genotypes for 87 SSR markers on 17 chromosomes. We report strong or positive evidence for 14 QTL for fruit firmness on eight chromosomes, validating our approach as several of these QTL were reported previously, though dispersed over a series of studies based on single mapping populations. Interpretation of linked QTL was possible via individuals’ QTL genotypes. The correlation between the genomic breeding values and phenotypes was on average 90 %, but varied with the number of detected QTL in a family. The detailed posterior knowledge on QTL of potential parents is critical for the efficiency of marker-assisted breeding.     

Genetic characterization of the Ma locus with pH and titratable acidity in apple

Apple fruit flavor is greatly affected by the level of malic acid, which is the major organic acid in mature apple fruit. To understand the genetic and molecular basis of apple fruit acidity, fruit juice pH and/or titratable acidity (TA) were measured in two half-sib populations GMAL 4595 [Royal Gala?×?PI (Plant Introduction) 613988] and GMAL 4590 (Royal Gala?×?PI 613971) of 438 trees in total. The maternal parent Royal Gala is a commercial variety and the paternal parents are two M. sieversii (the progenitor species of domestic apple) elite accessions. The low-acid trait segregates recessively and the overall acidity variations in the two populations were primarily controlled by the Ma (malic acid) locus, a major gene discovered in the 1950s (Nybom in Hereditas 45:332?C350, 1959) and later mapped to linkage group 16 (Maliepaard et al. in Theor Appl Genet 97:60?C73, 1998). The allele Ma has a strong additive effect in increasing fruit acidity and is incompletely dominant over ma. QTL (quantitative trait locus) analyses in GMAL 4595 mapped the major QTL Ma in both Royal Gala and PI 613988, the effects of which explained 17.0?C42.3% of the variation in fruit pH and TA. In addition, two minor QTL, tentatively designated M2 and M3, were also detected for fruit acidity, with M2 on linkage group 6 of Royal Gala and M3 on linkage group 1 of PI 613988. By exploring the genome sequences of apple, eight new simple sequence repeat markers tightly linked to Ma were developed, leading to construction of a fine genetic map of the Ma locus that defines it to a physical region no larger than 150?kb in the Golden Delicious genome.     

Multiple-line cross QTL mapping for biomass yield and plant height in triticale (× Triticosecale Wittmack)

Key message

QTL mapping in multiple families identifies trait-specific and pleiotropic QTL for biomass yield and plant height in triticale.

Abstract

Triticale shows a broad genetic variation for biomass yield which is of interest for a range of purposes, including bioenergy. Plant height is a major contributor to biomass yield and in this study, we investigated the genetic architecture underlying biomass yield and plant height by multiple-line cross QTL mapping. We employed 647 doubled haploid lines from four mapping populations that have been evaluated in four environments and genotyped with 1710 DArT markers. Twelve QTL were identified for plant height and nine for biomass yield which cross-validated explained 59.6 and 38.2 % of the genotypic variance, respectively. A major QTL for both traits was identified on chromosome 5R which likely corresponds to the dominant dwarfing gene Ddw1. In addition, we detected epistatic QTL for plant height and biomass yield which, however, contributed only little to the genetic architecture of the traits. In conclusion, our results demonstrate the potential of genomic approaches for a knowledge-based improvement of biomass yield in triticale.     

Combined use of bulked segregant analysis and microarrays reveals SNP markers pinpointing a major QTL for resistance to Phytophthora capsici in pepper

Key message

Bulked segregant analysis (BSA) using Affymetrix GeneChips revealed candidate genes underlying the major QTL for Phytophthora capsici resistance in Capsicum . Using the candidate genes, reliable markers for Phytophthora resistance were developed and validated.

Abstract

Phytophthora capsici L. is one of the most destructive pathogens of pepper (Capsicum spp.). Resistance of pepper against P. capsici is controlled by quantitative trait loci (QTL), including a major QTL on chromosome 5 that is the predominant contributor to resistance. Here, to maximize the effect of this QTL and study its underlying genes, an F₂ population and recombinant inbred lines were inoculated with P. capsici strain JHAI1-7 zoospores at a low concentration (3 × 10³/mL). Resistance phenotype segregation ratios for the populations fit a 3:1 and 1:1 (resistant:susceptible) segregation model, respectively, consistent with a single dominant gene model. Bulked segregant analysis (BSA) using Affymetrix GeneChips revealed a single position polymorphism (SPP) marker mapping to the major QTL. When this SPP marker (Phyto5SAR) together with other SNP markers located on chromosome 5 was used to confirm the position of the major QTL, Phyto5SAR showed the highest LOD value at the QTL. A scaffold sequence (scaffold194) containing Phyto5SAR was identified from the C. annuum genome database. The scaffold contained two putative NBS-LRR genes and one SAR 8.2A gene as candidates for contributing to P. capsici resistance. Markers linked to these genes were developed and validated by testing 100 F₁ commercial cultivars. Among the markers, Phyto5NBS1 showed about 90 % accuracy in predicting resistance phenotypes to a low-virulence P. capsici isolate. These results suggest that Phyto5NBS1 is a reliable marker for P. capsici resistance and can be used for identification of a gene(s) underlying the major QTL on chromosome 5.     

QTL mapping in autotetraploids using SNP dosage information

Key message

Dense linkage maps derived by analysing SNP dosage in autotetraploids provide detailed information about the location of, and genetic model at, quantitative trait loci.

Abstract

Recent developments in sequencing and genotyping technologies enable researchers to generate high-density single nucleotide polymorphism (SNP) genotype data for mapping studies. For polyploid species, the SNP genotypes are informative about allele dosage, and Hackett et al. (PLoS ONE 8:e63939, 2013) presented theory about how dosage information can be used in linkage map construction and quantitative trait locus (QTL) mapping for an F₁ population in an autotetraploid species. Here, QTL mapping using dosage information is explored for simulated phenotypic traits of moderate heritability and possibly non-additive effects. Different mapping strategies are compared, looking at additive and more complicated models, and model fitting as a single step or by iteratively re-weighted modelling. We recommend fitting an additive model without iterative re-weighting, and then exploring non-additive models for the genotype means estimated at the most likely position. We apply this strategy to re-analyse traits of high heritability from a potato population of 190 F₁ individuals: flower colour, maturity, height and resistance to late blight (Phytophthora infestans (Mont.) de Bary) and potato cyst nematode (Globodera pallida), using a map of 3839 SNPs. The approximate confidence intervals for QTL locations have been improved by the detailed linkage map, and more information about the genetic model at each QTL has been revealed. For several of the reported QTLs, candidate SNPs can be identified, and used to propose candidate trait genes. We conclude that the high marker density is informative about the genetic model at loci of large effects, but that larger populations are needed to detect smaller QTLs.     

Construction of an integrative linkage map and QTL mapping of grain yield-related traits using three related wheat RIL populations

Key message

A novel high-density consensus wheat genetic map was obtained based on three related RIL populations, and the important chromosomal regions affecting yield and related traits were specified.

Abstract

A prerequisite for mapping quantitative trait locus (QTL) is to build a genetic linkage map. In this study, three recombinant inbred line populations (represented by WL, WY, and WJ) sharing one common parental line were used for map construction and subsequently for QTL detection of yield-related traits. PCR-based and diversity arrays technology markers were screened in the three populations. The integrated genetic map contains 1,127 marker loci, which span 2,976.75 cM for the whole genome, 985.93 cM for the A genome, 922.16 cM for the B genome, and 1,068.65 cM for the D genome. Phenotypic values were evaluated in four environments for populations WY and WJ, but three environments for population WL. Individual and combined phenotypic values across environments were used for QTL detection. A total of 165 putative additive QTL were identified, 22 of which showed significant additive-by-environment interaction effects. A total of 65 QTL (51.5 %) were stable across environments, and 23 of these (35.4 %) were common stable QTL that were identified in at least two populations. Notably, QTkw-5B.1, QTkw-6A.2, and QTkw-7B.1 were common major stable QTL in at least two populations, exhibiting 11.28–16.06, 5.64–18.69, and 6.76–21.16 % of the phenotypic variance, respectively. Genetic relationships between kernel dimensions and kernel weight and between yield components and yield were evaluated. Moreover, QTL or regions that commonly interact across genetic backgrounds were discussed by comparing the results of the present study with those of previous similar studies. The present study provides useful information for marker-assisted selection in breeding wheat varieties with high yield.     

Identification of quantitative trait loci and candidate genes for specific cellular resistance responses against Didymella pinodes in pea

Key message

Phenotyping of specific cellular resistance responses and improvement of previous genetic map allowed the identification of novel genomic regions controlling cellular mechanisms involved in pea resistance to ascochyta blight and provided candidate genes suitable for MAS.

Abstract

Didymella pinodes, causing ascochyta blight, is a major pathogen of the pea crop and is responsible for serious damage and yield losses. Resistance is inherited polygenically and several quantitative trait loci (QTLs) have been already identified. However, the position of these QTLs should be further refined to identify molecular markers more closely linked to the resistance genes. In previous works, resistance was scored visually estimating the final disease symptoms; in this study, we have conducted a more precise phenotyping of resistance evaluating specific cellular resistance responses at the histological level to perform a more accurate QTL analysis. In addition, P665 × Messire genetic map used to identify the QTLs was improved by adding 117 SNP markers located in genes. This combined approach has allowed the identification, for the first time, of genomic regions controlling cellular mechanisms directly involved in pea resistance to ascochyta blight. Furthermore, the inclusion of the gene-based SNP markers has allowed the identification of candidate genes co-located with QTLs and has provided robust markers for marker-assisted selection.     

Use of synteny to identify candidate genes underlying QTL controlling stomatal traits in faba bean (Vicia faba L.)

Key message

We have identified QTLs for stomatal characteristics on chromosome II of faba bean by applying SNPs derived from M. truncatula , and have identified candidate genes within these QTLs using synteny between the two species.

Abstract

Faba bean (Vicia faba L.) is a valuable food and feed crop worldwide, but drought often limits its production, and its genome is large and poorly mapped. No information is available on the effects of genomic regions and genes on drought adaptation characters such as stomatal characteristics in this species, but the synteny between the sequenced model legume, Medicago truncatula, and faba bean can be used to identify candidate genes. A mapping population of 211 F₅ recombinant inbred lines (Mélodie/2 × ILB 938/2) were phenotyped to identify quantitative trait loci (QTL) affecting stomatal morphology and function, along with seed weight, under well-watered conditions in a climate-controlled glasshouse in 2013 and 2014. Canopy temperature (CT) was evaluated in 2013 under water-deficit (CTd). In total, 188 polymorphic single nucleotide polymorphisms (SNPs), developed from M. truncatula genome data, were assigned to nine linkage groups that covered ~928 cM of the faba bean genome with an average inter-marker distance of 5.8 cM. 15 putative QTLs were detected, of which eight (affecting stomatal density, length and conductance and CT) co-located on chromosome II, in the vicinity of a possible candidate gene—a receptor-like protein kinase found in the syntenic interval of M. truncatula chromosome IV. A ribose-phosphate pyrophosphokinase from M. truncatula chromosome V, postulated as a possible candidate gene for the QTL for CTd, was found some distance away in the same chromosome. These results demonstrate that genomic information from M. truncatula can successfully be translated to the faba bean genome.     

QTL analysis of frost damage in pea suggests different mechanisms involved in frost tolerance

Key message

Avoidance mechanisms and intrinsic resistance are complementary strategies to improve winter frost tolerance and yield potential in field pea.

Abstract

The development of the winter pea crop represents a major challenge to expand plant protein production in temperate areas. Breeding winter cultivars requires the combination of freezing tolerance as well as high seed productivity and quality. In this context, we investigated the genetic determinism of winter frost tolerance and assessed its genetic relationship with yield and developmental traits. Using a newly identified source of frost resistance, we developed a population of recombinant inbred lines and evaluated it in six environments in Dijon and Clermont-Ferrand between 2005 and 2010. We developed a genetic map comprising 679 markers distributed over seven linkage groups and covering 947.1 cM. One hundred sixty-one quantitative trait loci (QTL) explaining 9–71 % of the phenotypic variation were detected across the six environments for all traits measured. Two clusters of QTL mapped on the linkage groups III and one cluster on LGVI reveal the genetic links between phenology, morphology, yield-related traits and frost tolerance in winter pea. QTL clusters on LGIII highlighted major developmental gene loci (Hr and Le) and the QTL cluster on LGVI explained up to 71 % of the winter frost damage variation. This suggests that a specific architecture and flowering ideotype defines frost tolerance in winter pea. However, two consistent frost tolerance QTL on LGV were independent of phenology and morphology traits, showing that different protective mechanisms are involved in frost tolerance. Finally, these results suggest that frost tolerance can be bred independently to seed productivity and quality.     

Mapping of quantitative adult plant field resistance to leaf rust and stripe rust in two European winter wheat populations reveals co-location of three QTL conferring resistance to both rust pathogens

Key message

We detected several, most likely novel QTL for adult plant resistance to rusts. Notably three QTL improved resistance to leaf rust and stripe rust simultaneously indicating broad spectrum resistance QTL.

Abstract

The rusts of wheat (Puccinia spp.) are destructive fungal wheat diseases. The deployment of resistant cultivars plays a central role in integrated rust disease management. Durability of resistance would be preferred, but is difficult to analyse. The Austrian winter wheat cultivar Capo was released in the 1989 and grown on a large acreage during more than two decades and maintained a good level of quantitative leaf rust and stripe rust resistance. Two bi-parental mapping populations: Capo × Arina and Capo × Furore were tested in multiple environments for severity of leaf rust and stripe rust at the adult plant stage in replicated field experiments. Quantitative trait loci associated with leaf rust and stripe rust severity were mapped using DArT and SSR markers. Five QTL were detected in multiple environments associated with resistance to leaf rust designated as QLr.ifa-2AL, QLr.ifa-2BL, QLr.ifa-2BS, QLr.ifa-3BS, and QLr.ifa-5BL, and five for resistance to stripe rust QYr.ifa-2AL, QYr.ifa-2BL, QYr.ifa-3AS, QYr.ifa-3BS, and QYr.ifa-5A. For all QTL apart from two (QYr.ifa-3AS, QLr.ifa-5BL) Capo contributed the resistance improving allele. The leaf rust and stripe rust resistance QTL on 2AL, 2BL and 3BS mapped to the same chromosome positions, indicating either closely linked genes or pleiotropic gene action. These three multiple disease resistance QTL (QLr.ifa-2AL/QYr.ifa-2AL, QLr.ifa.2BL/QYr.ifa-2BL, QLr.ifa-3BS/QYr.ifa.3BS) potentially contribute novel resistance sources for stripe rust and leaf rust. The long-lasting resistance of Capo apparently rests upon a combination of several genes. The described germplasm, QTL and markers are applicable for simultaneous resistance improvement against leaf rust and stripe rust.     

Genome-wide QTL and bulked transcriptomic analysis reveals new candidate genes for the control of tuber carotenoid content in potato (Solanum tuberosum L.)

Key message

Genome-wide QTL analysis of potato tuber carotenoid content was investigated in populations of Solanum tuberosum Group Phureja that segregate for flesh colour, revealing a novel major QTL on chromosome 9.

Abstract

The carotenoid content of edible plant storage organs is a key nutritional and quality trait. Although the structural genes that encode the biosynthetic enzymes are well characterised, much less is known about the factors that determine overall storage organ content. In this study, genome-wide QTL mapping, in concert with an efficient ‘genetical genomics’ analysis using bulked samples, has been employed to investigate the genetic architecture of potato tuber carotenoid content. Two diploid populations of Solanum tuberosum Group Phureja were genotyped (AFLP, SSR and DArT markers) and analysed for their tuber carotenoid content over two growing seasons. Common to both populations were QTL that explained relatively small proportions of the variation in constituent carotenoids and a major QTL on chromosome 3 explaining up to 71 % of the variation in carotenoid content. In one of the populations (01H15), a second major carotenoid QTL was identified on chromosome 9, explaining up to 20 % of the phenotypic variation. Whereas the major chromosome 3 QTL was likely to be due to an allele of a gene encoding β-carotene hydroxylase, no known carotenoid biosynthetic genes are located in the vicinity of the chromosome 9 QTL. A unique expression profiling strategy using phenotypically distinct bulks comprised individuals with similar carotenoid content provided further support for the QTL mapping to chromosome 9. This study shows the potential of using the potato genome sequence to link genetic maps to data arising from eQTL approaches to enhance the discovery of candidate genes underlying QTLs.     

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.     

Genome-wide analysis and characterization of molecular evolution of the <Emphasis Type="Italic">HCT</Emphasis> gene family in pear (<Emphasis Type="Italic">Pyrus bretschneideri</Emphasis>)

Lignin is a major component of stone cells in pear fruit, which significantly affects fruit quality. Hydroxycinnamoyl CoA: shikimate hydroxycinnamoyl transferase (HCT), a recently discovered enzyme in plants, is an important gene that participates in the formation of lignin. Although HCT gene cloning and expression patterns have been studied in several species, including pear, there is still no extensive genome-wide bioinformatics analysis on the whole gene family, and the evolutionary history of HCT gene family is still unknown. A total of 82 HCT genes were identified in pear, most of which have one or two exons, and all with the conserved HXXXD motif and transferase domains. Based on the structural characteristics and phylogenetic analysis of these sequences, the HCT gene family genes could be classified into four main groups. Structural analysis also revealed that 25 % of HCT genes share a MYB binding site. Expansion of the HCT gene family mostly occurred before the divergence between Arabidopsis and Rosaceae, with whole-genome duplication or segmental duplication events playing the most important role in the expansion of the HCT gene family in pear. At the same time, purifying selection also played a critical role in the evolution of HCT genes. Five of the 82 HCT genes were verified by qRT-PCR to correspond to the pattern of stone cell formation during pear fruit development. The genome-wide identification, chromosome localization, gene structures, synteny, and expression analyses of pear HCT genes provide an overall insight into HCT gene family and their potential involvement in growth and development of stone cells.     

Fine mapping of a preharvest sprouting QTL interval on chromosome 2B in white wheat

Key message

Fine mapping by recombinant backcross populations revealed that a preharvest sprouting QTL on 2B contained two QTLs linked in coupling with different effects on the phenotype.

Abstract

Wheat preharvest sprouting (PHS) occurs when grain germinates on the plant before harvest, resulting in reduced grain quality. Previous mapping of quantitative trait locus (QTL) revealed a major PHS QTL, QPhs.cnl-2B.1, located on chromosome 2B significant in 16 environments that explained from 5 to 31 % of the phenotypic variation. The objective of this project was to fine map the QPhs.cnl-2B.1 interval. Fine mapping was carried out in recombinant backcross populations (BC₁F₄ and BC₁F₅) that were developed by backcrossing selected doubled haploids to a recurrent parent and self-pollinating the BC₁F₄ and BC₁F₅ generations. In each generation, three markers in the QPhs.cnl-2B.1 interval were used to screen for recombinants. Fine mapping revealed that the QPhs.cnl-2B.1 interval contained two PHS QTLs linked in coupling. The distal PHS QTL, located between Wmc453c and Barc55, contributed 8 % of the phenotypic variation and also co-located with a major seed dormancy QTL determined by germination index. The proximal PHS QTL, between Wmc474 and CNL415-rCDPK, contributed 16 % of the variation. Several candidate genes including Mg-chelatase H subunit family protein, GTP-binding protein and calmodulin/Ca²⁺-dependent protein kinase were linked to the PHS QTL. Although many recombinant lines were identified, the lack of polymorphism for markers in the QTL interval prevented the localization of the recombination breakpoints and identification of the gene underlying the phenotype.     

Association mapping of resistance to Puccinia hordei in Australian barley breeding germplasm

Key message

“To find stable resistance using association mapping tools, QTL with major and minor effects on leaf rust reactions were identified in barley breeding lines by assessing seedlings and adult plants.”

Abstract

Three hundred and sixty (360) elite barley (Hordeum vulgare L.) breeding lines from the Northern Region Barley Breeding Program in Australia were genotyped with 3,244 polymorphic diversity arrays technology markers and the results used to map quantitative trait loci (QTL) conferring a reaction to leaf rust (Puccinia hordei Otth). The F_3:5 (Stage 2) lines were derived or sourced from different geographic origins or hubs of international barley breeding ventures representing two breeding cycles (2009 and 2011 trials) and were evaluated across eight environments for infection type at both seedling and adult plant stages. Association mapping was performed using mean scores for disease reaction, accounting for family effects using the eigenvalues from a matrix of genotype correlations. In this study, 15 QTL were detected; 5 QTL co-located with catalogued leaf rust resistance genes (Rph1, Rph3/19, Rph8/14/15, Rph20, Rph21), 6 QTL aligned with previously reported genomic regions and 4 QTL (3 on chromosome 1H and 1 on 7H) were novel. The adult plant resistance gene Rph20 was identified across the majority of environments and pathotypes. The QTL detected in this study offer opportunities for breeding for more durable resistance to leaf rust through pyramiding multiple genomic regions via marker-assisted selection.     

Quantitative trait loci that control the oil content variation of rapeseed (Brassica napus L.)

Key message

This report describes an integrative analysis of seed-oil-content quantitative trait loci (QTL) in Brassica napus , using a high-density genetic map to align QTL among different populations.

Abstract

Rapeseed (Brassica napus) is an important source of edible oil and sustainable energy. Given the challenge involved in using only a few genes to substantially increase the oil content of rapeseed without affecting the fatty acid composition, exploitation of a greater number of genetic loci that regulate the oil content variation among rapeseed germplasm is of fundamental importance. In this study, we investigated variation in the seed-oil content among two related genetic populations of Brassica napus, the TN double-haploid population and its derivative reconstructed-F₂ population. Each population was grown in multiple experiments under different environmental conditions. Mapping of quantitative trait loci (QTL) identified 41 QTL in the TN populations. Furthermore, of the 20 pairs of epistatic interaction loci detected, approximately one-third were located within the QTL intervals. The use of common markers on different genetic maps and the TN genetic map as a reference enabled us to project QTL from an additional three genetic populations onto the TN genetic map. In summary, we used the TN genetic map of the B. napus genome to identify 46 distinct QTL regions that control seed-oil content on 16 of the 19 linkage groups of B. napus. Of these, 18 were each detected in multiple populations. The present results are of value for ongoing efforts to breed rapeseed with high oil content, and alignment of the QTL makes an important contribution to the development of an integrative system for genetic studies of rapeseed.