Combined linkage and linkage disequilibrium QTL mapping in multiple families of maize (Zea mays L.) line crosses highlights complementarities between models based on parental haplotype and single locus polymorphism

Advancements in genotyping are rapidly decreasing marker costs and increasing marker density. This opens new possibilities for mapping quantitative trait loci (QTL), in particular by combining linkage disequilibrium information and linkage analysis (LDLA). In this study, we compared different approaches to detect QTL for four traits of agronomical importance in two large multi-parental datasets of maize (Zea mays L.) of 895 and 928 testcross progenies composed of 7 and 21 biparental families, respectively, and genotyped with 491 markers. We compared to traditional linkage-based methods two LDLA models relying on the dense genotyping of parental lines with 17,728 SNP: one based on a clustering approach of parental line segments into ancestral alleles and one based on single marker information. The two LDLA models generally identified more QTL (60 and 52 QTL in total) than classical linkage models (49 and 44 QTL in total). However, they performed inconsistently over datasets and traits suggesting that a compromise must be found between the reduction of allele number for increasing statistical power and the adequacy of the model to potentially complex allelic variation. For some QTL, the model exclusively based on linkage analysis, which assumed that each parental line carried a different QTL allele, was able to capture remaining variation not explained by LDLA models. These complementarities between models clearly suggest that the different QTL mapping approaches must be considered to capture the different levels of allelic variation at QTL involved in complex traits.     

Replication and refinement of a quantitative trait locus influencing milk protein percentage on ovine chromosome 3

A previous genome scan that was conducted in Spanish Churra sheep identified a significant quantitative trait locus (QTL) for milk protein percentage (PP) on chromosome 3 (OAR3), between markers KD103 and OARVH34. The aim of this study was to replicate these results and to refine the mapped position of this QTL. To accomplish this goal, we analysed 14 new half‐sib families of Spanish Churra sheep including 1661 ewes from 29 different flocks. These animals were genotyped for 21 microsatellite markers mapping to OAR3. In addition to a classical linkage analysis (LA), a combined linkage disequilibrium and linkage analysis (LDLA) was performed with the aim of enhancing the resolution of the QTL mapping. The LA that was performed in this sheep population identified the presence of a highly significant QTL for PP near marker KD103 (P_c < 0.001; P_exp < 0.001). The phenotypic variance that was owing to the QTL was 2.74%. Two segregating families for the target QTL were identified in this population with QTL effect estimates of 0.47 and 0.95 SD. The LDLA identified the same QTL as the previous analyses with a high level of statistical significance (P = 9.184 E‐11) and narrowed the confidence interval (CI) to a 13 cM region. These results confirm the segregation of the previously identified OAR3 QTL that influences PP in Spanish Churra sheep. Future research will aim to increase the marker density across the refined CI and to analyse the corresponding candidate genes to identify the allelic variant or variants that underlie this genetic effect.     

Usefulness of Multiparental Populations of Maize (Zea mays L.) for Genome-Based Prediction

The efficiency of marker-assisted prediction of phenotypes has been studied intensively for different types of plant breeding populations. However, one remaining question is how to incorporate and counterbalance information from biparental and multiparental populations into model training for genome-wide prediction. To address this question, we evaluated testcross performance of 1652 doubled-haploid maize (Zea mays L.) lines that were genotyped with 56,110 single nucleotide polymorphism markers and phenotyped for five agronomic traits in four to six European environments. The lines are arranged in two diverse half-sib panels representing two major European heterotic germplasm pools. The data set contains 10 related biparental dent families and 11 related biparental flint families generated from crosses of maize lines important for European maize breeding. With this new data set we analyzed genome-based best linear unbiased prediction in different validation schemes and compositions of estimation and test sets. Further, we theoretically and empirically investigated marker linkage phases across multiparental populations. In general, predictive abilities similar to or higher than those within biparental families could be achieved by combining several half-sib families in the estimation set. For the majority of families, 375 half-sib lines in the estimation set were sufficient to reach the same predictive performance of biomass yield as an estimation set of 50 full-sib lines. In contrast, prediction across heterotic pools was not possible for most cases. Our findings are important for experimental design in genome-based prediction as they provide guidelines for the genetic structure and required sample size of data sets used for model training.     

Combined linkage disequilibrium and linkage mapping: Bayesian multilocus approach

Quantitative trait loci (QTL) affecting the phenotype of interest can be detected using linkage analysis (LA), linkage disequilibrium (LD) mapping or a combination of both (LDLA). The LA approach uses information from recombination events within the observed pedigree and LD mapping from the historical recombinations within the unobserved pedigree. We propose the Bayesian variable selection approach for combined LDLA analysis for single-nucleotide polymorphism (SNP) data. The novel approach uses both sources of information simultaneously as is commonly done in plant and animal genetics, but it makes fewer assumptions about population demography than previous LDLA methods. This differs from approaches in human genetics, where LDLA methods use LA information conditional on LD information or the other way round. We argue that the multilocus LDLA model is more powerful for the detection of phenotype–genotype associations than single-locus LDLA analysis. To illustrate the performance of the Bayesian multilocus LDLA method, we analyzed simulation replicates based on real SNP genotype data from small three-generational CEPH families and compared the results with commonly used quantitative transmission disequilibrium test (QTDT). This paper is intended to be conceptual in the sense that it is not meant to be a practical method for analyzing high-density SNP data, which is more common. Our aim was to test whether this approach can function in principle.     

Genome wide QTL mapping to identify candidate genes for carcass traits in Hanwoo (Korean Cattle)

Meat quality traits are the most economically important traits affecting the beef industry in Korea. We performed a whole genome quantitative trait locus (QTL) mapping study of carcass data in Hanwoo Korean cattle. Two hundred sixty-six Hanwoo steers from 65 sires were genotyped using a 10K Affymetrix SNP chip. The average SNP interval across the bovine genome was 1.5Mb. Associations between each individual SNP and four carcass traits [carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling (MAR)] were assessed using a linear mixed model of each trait. Combined linkage and linkage disequilibrium analysis (LDLA) detected six potential QTL on BTA04, 06, 13, 16, 17, and 23 at the chromosome-wise level (P<0.05). Two MAR QTL were detected at 52.2 cM of BTA06 and 46.04 cM of BTA17. We identified three genes (ARAP2, LOC539460, and LOC511424) in the QTL region of BTA06 and seven genes (RPS14, SCARB1, LOC782103, BRI3BP, AACS, DHX37, and UBC) in the QTL region of BTA17. One significant QTL for CWT was detected at 100 cM on BTA04 and the corresponding QTL region spanned 1.7 cM from 99.7 to 101.4 cM. For EMA QTL, one significant QTL was detected at 3.9 cM of BTA23 and the most likely QTL interval was 1.4 cM, placing 15 candidate genes in the marker bracket. Finally, two QTL for BFT were identified at 68 cM on BTA13 and 24 cM on BTA16. The LPIN3 gene, which is functionally associated with lipodystrophy in humans, is located in the BFT QTL on BTA13. Thus, two potential candidate genes, acetoacetyl-CoA synthetase (AACS) and lipin (LPIN), were detected in QTL regions on BTA17 for MAR and BTA13 for BFT, respectively. In conclusion, LDLA analysis can be used to detect chromosome regions harboring QTL and candidate genes with a low density SNP panel, yielding relatively narrow confidence intervals regarding location.     

A multiparental cross population for mapping QTL for agronomic traits in durum wheat (Triticum turgidum ssp. durum)

Multiparental cross designs for mapping quantitative trait loci (QTL) provide an efficient alternative to biparental populations because of their broader genetic basis and potentially higher mapping resolution. We describe the development and deployment of a recombinant inbred line (RIL) population in durum wheat (Triticum turgidum ssp. durum) obtained by crossing four elite cultivars. A linkage map spanning 2664 cM and including 7594 single nucleotide polymorphisms (SNPs) was produced by genotyping 338 RILs. QTL analysis was carried out by both interval mapping on founder haplotype probabilities and SNP bi‐allelic tests for heading date and maturity date, plant height and grain yield from four field experiments. Sixteen QTL were identified across environments and detection methods, including two yield QTL on chromosomes 2BL and 7AS, with the former mapped independently from the photoperiod response gene Ppd‐B1, while the latter overlapped with the vernalization locus VRN‐A3. Additionally, 21 QTL with environment‐specific effects were found. Our results indicated a prevalence of environment‐specific QTL with relatively small effect on the control of grain yield. For all traits, functionally different QTL alleles in terms of direction and size of genetic effect were distributed among parents. We showed that QTL results based on founder haplotypes closely matched functional alleles at known heading date loci. Despite the four founders, only 2.1 different functional haplotypes were estimated per QTL, on average. This durum wheat population provides a mapping resource for detailed genetic dissection of agronomic traits in an elite background typical of breeding programmes.     

Fine mapping of quantitative trait loci for mastitis resistance on bovine chromosome 11

Quantitative trait loci (QTL) affecting clinical mastitis (CM) and somatic cell score (SCS) were mapped on bovine chromosome 11. The mapping population consisted of 14 grandsire families belonging to three Nordic red cattle breeds: Finnish Ayrshire (FA), Swedish Red and White (SRB) and Danish Red. The families had previously been shown to segregate for udder health QTL. A total of 524 progeny tested bulls were included in the analysis. A linkage map including 33 microsatellite and five SNP markers was constructed. We performed combined linkage disequilibrium and linkage analysis (LDLA) using the whole data set. Further analyses were performed for FA and SRB separately to study the origin of the identified QTL/haplotype and to examine if it was common in both populations. Finally, different two-trait models were fitted. These postulated either a pleiotropic QTL affecting both traits; two linked QTL, each affecting one trait; or one QTL affecting a single trait. A QTL affecting CM was fine-mapped. In FA, a haplotype having a strong association with a high negative effect on mastitis resistance was identified. The mapping precision of an earlier detected SCS-QTL was not improved by the LDLA analysis because of lack of linkage disequilibrium between the markers used and the QTL in the region.     

QTL and gene expression analyses identify genes affecting carcass weight and marbling on BTA14 in Hanwoo (Korean Cattle)

Causal mutations affecting quantitative trait variation can be good targets for marker-assisted selection for carcass traits in beef cattle. In this study, linkage and linkage disequilibrium analysis (LDLA) for four carcass traits was undertaken using 19 markers on bovine chromosome 14. The LDLA analysis detected quantitative trait loci (QTL) for carcass weight (CWT) and eye muscle area (EMA) at the same position at around 50?cM and surrounded by the markers FABP4SNP2774C>G and FABP4_??sat3237. The QTL for marbling (MAR) was identified at the midpoint of markers BMS4513 and RM137 in a 3.5-cM marker interval. The most likely position for a second QTL for CWT was found at the midpoint of tenth marker bracket (FABP4SNP2774C>G and FABP4_??sat3237). For this marker bracket, the total number of haplotypes was 34 with a most common frequency of 0.118. Effects of haplotypes on CWT varied from a ?5-kg deviation for haplotype 6 to +8?kg for haplotype 23. To determine which genes contribute to the QTL effect, gene expression analysis was performed in muscle for a wide range of phenotypes. The results demonstrate that two genes, LOC781182 (p?=?0.002) and TRPS1 (p?=?0.006) were upregulated with increasing CWT and EMA, whereas only LOC614744 (p?=?0.04) has a significant effect on intramuscular fat (IMF) content. Two genetic markers detected in FABP4 were the most likely QTL position in this QTL study, but FABP4 did not show a significant effect on both traits (CWT and EMA) in gene expression analysis. We conclude that three genes could be potential causal genes affecting carcass traits CWT, EMA, and IMF in Hanwoo.     

Editor's choice: High-Resolution Linkage and Quantitative Trait Locus Mapping Aided by Genome Survey Sequencing: Building Up An Integrative Genomic Framework for a Bivalve Mollusc

Genetic linkage maps are indispensable tools in genetic and genomic studies. Recent development of genotyping-by-sequencing (GBS) methods holds great promise for constructing high-resolution linkage maps in organisms lacking extensive genomic resources. In the present study, linkage mapping was conducted for a bivalve mollusc (Chlamys farreri) using a newly developed GBS method—2b-restriction site-associated DNA (2b-RAD). Genome survey sequencing was performed to generate a preliminary reference genome that was utilized to facilitate linkage and quantitative trait locus (QTL) mapping in C. farreri. A high-resolution linkage map was constructed with a marker density (3806) that has, to our knowledge, never been achieved in any other molluscs. The linkage map covered nearly the whole genome (99.5%) with a resolution of 0.41 cM. QTL mapping and association analysis congruously revealed two growth-related QTLs and one potential sex-determination region. An important candidate QTL gene named PROP1, which functions in the regulation of growth hormone production in vertebrates, was identified from the growth-related QTL region detected on the linkage group LG3. We demonstrate that this linkage map can serve as an important platform for improving genome assembly and unifying multiple genomic resources. Our study, therefore, exemplifies how to build up an integrative genomic framework in a non-model organism.     

Mapping carcass and meat quality QTL on Sus Scrofa chromosome 2 in commercial finishing pigs

Quantitative trait loci (QTL) affecting carcass and meat quality located on SSC2 were identified using variance component methods. A large number of traits involved in meat and carcass quality was detected in a commercial crossbred population: 1855 pigs sired by 17 boars from a synthetic line, which where homozygous (A/A) for IGF2. Using combined linkage and linkage disequilibrium mapping (LDLA), several QTL significantly affecting loin muscle mass, ham weight and ham muscles (outer ham and knuckle ham) and meat quality traits, such as Minolta-L* and -b*, ultimate pH and Japanese colour score were detected. These results agreed well with previous QTL-studies involving SSC2. Since our study is carried out on crossbreds, different QTL may be segregating in the parental lines. To address this question, we compared models with a single QTL-variance component with models allowing for separate sire and dam QTL-variance components. The same QTL were identified using a single QTL variance component model compared to a model allowing for separate variances with minor differences with respect to QTL location. However, the variance component method made it possible to detect QTL segregating in the paternal line (e.g. HAMB), the maternal lines (e.g. Ham) or in both (e.g. pHu). Combining association and linkage information among haplotypes improved slightly the significance of the QTL compared to an analysis using linkage information only.     

Power of QTL mapping experiments in commercial Atlantic salmon populations, exploiting linkage and linkage disequilibrium and effect of limited recombination in males

Whereas detection and positioning of genes that affect quantitative traits (quantitative trait loci (QTL)) using linkage mapping uses only information from recombinants in the genotyped generations, linkage disequilibrium (LD) mapping uses historical recombinants. Thus, whereas linkage mapping requires large family sizes to detect and accurately position QTL, LD mapping is more dependent on the number of families sampled from the population. In commercial Atlantic salmon breeding programmes, only a small number of individuals per family are routinely phenotyped for traits such as disease resistance and meat colour. In this paper, we assess the power and accuracy of combined linkage disequilibrium linkage analysis (LDLA) to detect QTL in the commercial population using simulation. When 15 half-sib sire families (each sire mated to 30 dams, each dam with 10 progeny) were sampled from the population for genotyping, we were able to detect a QTL explaining 10% of the phenotypic variance in 85% of replicates and position this QTL within 3 cM of the true position in 70% of replicates. When recombination was absent in males, a feature of the salmon genome, power to detect QTL increased; however, the accuracy of positioning the QTL was decreased. By increasing the number of sire families sampled from the population to be genotyped to 30, we were able to increase both the proportion of QTL detected and correctly positioned (even with no recombination in males). QTL with much smaller effect could also be detected. The results suggest that even with the existing recording structure in commercial salmon breeding programmes, there is considerable power to detect and accurately position QTL using LDLA.     

A comparison of methods for whole-genome QTL mapping using dense markers in four livestock species

Background

With dense genotyping, many choices exist for methods to detect quantitative trait loci (QTL) in livestock populations. However, no across-species study has been conducted on the performance of different methods using real data. We compared three methods that correct for relatedness either implicitly or explicitly: linkage and linkage disequilibrium haplotype-based analysis (LDLA), efficient mixed-model association (EMMA) analysis, and Bayesian whole-genome regression (BayesC). We analyzed one chromosome in each of five datasets (dairy cattle, beef cattle, sheep, horses, and pigs) using real genotypes based on dense single nucleotide polymorphisms and phenotypes. The P values corrected for multiple testing or Bayes factors greater than 150 were considered to be significant. To complete the real data study, we also simulated quantitative trait loci (QTL) for the same datasets based on the real genotypes. Several scenarios were chosen, with different QTL effects and linkage disequilibrium patterns. A pseudo-null statistical distribution was chosen to make the significance thresholds comparable across methods.

Results

For the real data, the three methods generally agreed within 1 or 2 cM for the locations of QTL regions and disagreed when no signals were significant (e.g. in pigs). For certain datasets, LDLA had more significant signals than EMMA or BayesC, but they were concentrated around the same peaks. Therefore, the three methods detected approximately the same number of QTL regions. For the simulated data, LDLA was slightly less powerful and accurate than either EMMA or BayesC but this depended strongly on how thresholds were set in the simulations.

Conclusions

All three methods performed similarly for real and simulated data. No method was clearly superior across all datasets or for any particular dataset. For computational efficiency and ease of interpretation, EMMA is recommended, but using more than one method is suggested.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0087-7) contains supplementary material, which is available to authorized users.     

Potential of a tomato MAGIC population to decipher the genetic control of quantitative traits and detect causal variants in the resequencing era

Identification of the polymorphisms controlling quantitative traits remains a challenge for plant geneticists. Multiparent advanced generation intercross (MAGIC) populations offer an alternative to traditional linkage or association mapping populations by increasing the precision of quantitative trait loci (QTL) mapping. Here, we present the first tomato MAGIC population and highlight its potential for the valorization of intraspecific variation, QTL mapping and causal polymorphism identification. The population was developed by crossing eight founder lines, selected to include a wide range of genetic diversity, whose genomes have been previously resequenced. We selected 1536 SNPs among the 4 million available to enhance haplotype prediction and recombination detection in the population. The linkage map obtained showed an 87% increase in recombination frequencies compared to biparental populations. The prediction of the haplotype origin was possible for 89% of the MAGIC line genomes, allowing QTL detection at the haplotype level. We grew the population in two greenhouse trials and detected QTLs for fruit weight. We mapped three stable QTLs and six specific of a location. Finally, we showed the potential of the MAGIC population when coupled with whole genome sequencing of founder lines to detect candidate SNPs underlying the QTLs. For a previously cloned QTL on chromosome 3, we used the predicted allelic effect of each founder and their genome sequences to select putative causal polymorphisms in the supporting interval. The number of candidate polymorphisms was reduced from 12 284 (in 800 genes) to 96 (in 54 genes), including the actual causal polymorphism. This population represents a new permanent resource for the tomato genetics community.     

Genetic mapping of quantitative trait loci for resistance to Haemonchus contortus in sheep

This paper presents results from a mapping experiment to detect quantitative trait loci (QTL) for resistance to Haemonchus contortus infestation in merino sheep. The primary trait analysed was faecal worm egg count in response to artificial challenge at 6 months of age. In the first stage of the experiment, whole genome linkage analysis was used for broad-scale mapping. The animal resource used was a designed flock comprising 571 individuals from four half-sib families. The average marker spacing was about 20 cM. For the primary trait, 11 QTL (as chromosomal/family combinations) were significant at the 5% chromosome-wide level, with allelic substitution effects of between 0.19 and 0.38 phenotypic standard deviation units. In general, these QTL did not have a significant effect on faecal worm egg count recorded at 13 months of age. In the second stage of the experiment, three promising regions (located on chromosomes 1, 3 and 4) were fine-mapped. This involved typing more closely spaced markers on individuals from the designed flock as well as an additional 495 individuals selected from a related population with a deeper pedigree. Analysis was performed using a linkage disequilibrium–linkage approach, under additive, dominant and multiple QTL models. Of these, the multiple QTL model resulted in the most refined QTL positions, with resolutions of <10 cM achieved for two regions. Because of the moderate size of effect of the QTL, and the apparent age and/or immune status specificity of the QTL, it is suggested that a panel of QTL will be required for significant genetic gains to be achieved within industry via marker-assisted selection.     

A strong quantitative trait locus for wing length on chromosome 2 in a wild population of great reed warblers

Wing length is a key character for essential behaviours related to bird flight such as migration and foraging. In the present study, we initiate the search for the genes underlying wing length in birds by studying a long-distance migrant, the great reed warbler (Acrocephalus arundinaceus). In this species wing length is an evolutionary interesting trait with pronounced latitudinal gradient and sex-specific selection regimes in local populations. We performed a quantitative trait locus (QTL) scan for wing length in great reed warblers using phenotypic, genotypic, pedigree and linkage map data from our long-term study population in Sweden. We applied the linkage analysis mapping method implemented in GridQTL (a new web-based software) and detected a genome-wide significant QTL for wing length on chromosome 2, to our knowledge, the first detected QTL in wild birds. The QTL extended over 25 cM and accounted for a substantial part (37%) of the phenotypic variance of the trait. A genome scan for tarsus length (a body-size-related trait) did not show any signal, implying that the wing-length QTL on chromosome 2 was not associated with body size. Our results provide a first important step into understanding the genetic architecture of avian wing length, and give opportunities to study the evolutionary dynamics of wing length at the locus level.     

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

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

A Consensus Microsatellite-Based Linkage Map for the Hermaphroditic Bay Scallop (Argopecten irradians) and Its Application in Size-Related QTL Analysis

Bay scallop (Argopecten irradians) is one of the most economically important aquaculture species in China. In this study, we constructed a consensus microsatellite-based genetic linkage map with a mapping panel containing two hybrid backcross-like families involving two subspecies of bay scallop, A. i. irradians and A. i. concentricus. One hundred sixty-one microsatellite and one phenotypic (shell color) markers were mapped to 16 linkage groups (LGs), which corresponds to the haploid chromosome number of bay scallop. The sex-specific map was 779.2 cM and 781.6 cM long in female and male, respectively, whereas the sex-averaged map spanned 849.3 cM. The average resolution of integrated map was 5.9 cM/locus and the estimated coverage was 81.3%. The proportion of distorted markers occurred more in the hybrid parents, suggesting that the segregation distortion was possibly resulted from heterospecific interaction between genomes of two subspecies of bay scallop. The overall female-to-male recombination rate was 1.13∶1 across all linked markers in common to both parents, and considerable differences in recombination also existed among different parents in both families. Four size-related traits, including shell length (SL), shell height (SH), shell width (SW) and total weight (TW) were measured for quantitative trait loci (QTL) analysis. Three significant and six suggestive QTL were detected on five LGs. Among the three significant QTL, two (qSW-10 and qTW-10, controlling SW and TW, respectively) were mapped on the same region near marker AiAD121 on LG10 and explained 20.5% and 27.7% of the phenotypic variance, while the third (qSH-7, controlling SH) was located on LG7 and accounted for 15.8% of the phenotypic variance. Six suggestive QTL were detected on four different LGs. The linkage map and size-related QTL obtained in this study may facilitate marker-assisted selection (MAS) in bay scallop.     

QTL mapping for brown rot (Monilinia fructigena) resistance in an intraspecific peach (Prunus persica L. Batsch) F1 progeny

Brown rot (BR) caused by Monilinia spp. leads to significant post-harvest losses in stone fruit production, especially peach. Previous genetic analyses in peach progenies suggested that BR resistance segregates as a quantitative trait. In order to uncover genomic regions associated with this trait and identify molecular markers for assisted selection (MAS) in peach, an F1 progeny from the cross “Contender” (C, resistant)?×?“Elegant Lady” (EL, susceptible) was chosen for quantitative trait loci (QTL) analysis. Over two phenotyping seasons, skin (SK) and flesh (FL) artificial infections were performed on fruits using a Monilinia fructigena isolate. For each treatment, infection frequency (if) and average rot diameter (rd) were scored. Significant seasonal and intertrait correlations were found. Maturity date (MD) was significantly correlated with disease impact. Sixty-three simple sequence repeats (SSRs) plus 26 single-nucleotide polymorphism (SNP) markers were used to genotype the C?×?EL population and to construct a linkage map. C?×?EL map included the eight Prunus linkage groups (LG), spanning 572.92 cM, with an average interval distance of 6.9 cM, covering 78.73 % of the peach genome (V1.0). Multiple QTL mapping analysis including MD trait as covariate uncovered three genomic regions associated with BR resistance in the two phenotyping seasons: one containing QTLs for SK resistance traits near M1a (LG C?×?EL-2, R ²?=?13.1–31.5 %) and EPPISF032 (LG C?×?EL-4, R ²?=?11–14 %) and the others containing QTLs for FL resistance, near markers SNP_IGA_320761 and SNP_IGA_321601 (LG3, R ²?=?3.0–11.0 %). These results suggest that in the C?×?EL F1 progeny, skin resistance to fungal penetration and flesh resistance to rot spread are distinguishable mechanisms constituting BR resistance trait, associated with different genomic regions. Discovered QTLs and their associated markers could assist selection of new cultivars with enhanced resistance to Monilinia spp. in fruit.