Bulk segregant analysis with molecular markers and its use for improving drought resistance in maize

The usual method to locate and compare loci regulating quantitative traits (QTLs) requires a segregating population of plants with each one genotyped with molecular markers. However, plants from such segregating populations can also be grouped according to phenotypic expression of a trait and tested for differences in allele frequency between the population bulks: bulk segregant analysis (BSA). The same probes used for making a genetic map (e.g. isozyme, RFLP, RAPD, etc) can be used for BSA. A molecular marker showing polymorphism between the parents of the population and which is closely-linked to a major QTL regulating a particular trait will mainly co-segregate with that QTL, i.e. segregate according to the phenotype if the QTL has a large effect. Thus, if plants are grouped according to expression of the trait and extreme groups tested with that polymorphic marker, the frequency of the two marker alleles present within each of the two bulks should deviate significantly from the ratio of 1 : 1 expected for most populations. As chromosomal locations of many molecular markers have now been determined in many species, the map location of closely-linked QTLs can therefore be deduced without having to genotype every individual in segregating populations. This has been used successfully with composite populations of maize to locate QTLs associated with yield under severe drought. An inbred line derived from one of the populations selected for higher drought yield has been crossed with a drought-susceptible inbred line to produce a mapping population for QTL analysis of physiological and developmental traits likely to regulate yield under drought. Future work to identify traits having QTLs with flanking markers showing significant allele frequency differences in the GSA studies will indicate those traits likely to be important in determining yield under drought.Key words: Bulk segregant analysis (BSA), drought resistance, genetic maps, maize, molecular markers, Zea mays (L.).      

Quantitative trait locus mapping of pyrethroid resistance in Colorado potato beetle, Leptinotarsa decemlineata (Say) (Coleoptera: Chrysomelidae)

Quantitative trait locus (QTL) mapping is a valuable new tool for locating genomic regions that underlie variation in important traits such as insecticide resistance. Because QTL mapping complements a candidate gene strategy for understanding the genetic architecture of important traits, it may also facilitate the identification of genes causing important variation. After mapping the QTL locations, markers closely linked to QTL can be used for genetic analysis of population structure and to measure the spread and increase of resistance-causing QTL alleles. In this study, QTL influencing resistance to the pyrethroid insecticide esfenvalerate were mapped in the Colorado potato beetle Leptinotarsa decemlineata (Say) (CPB). Three QTL contributing to esfenvalerate resistance were identified from a mapping population of 79 individuals analyzed at 90 marker loci. One QTL had a large effect and two QTL had smaller effects. The major QTL occurs on the X chromosome, overlapping the position of a candidate gene (Leptinotarsa decemlineata Voltage sensitive sodium channel [LdVssc1]) previously implicated in pyrethroid resistance. Resistance-increasing alleles at the two minor-effect QTL originated with the susceptible parent, suggesting that alleles of small effect may be segregating in susceptible populations. Comparison of the New York population from which the susceptible parent originated with a more-susceptible population from North Carolina suggests that the minor-effect loci identified here may explain some of the variation in tolerance observed among susceptible populations. DNA sequencing of a portion of LdVssc1 shows that the resistance-conferring allele from the resistant parent does not contain the kdr mutation previously found in CPB and typically observed in other insects that are resistant to pyrethroid insecticides because of changes in this gene.     

Multiple-line cross quantitative trait locus mapping in sugar beet (Beta vulgaris L.)

Linkage mapping based on multiple-line crosses is a promising strategy for mapping quantitative trait loci (QTL) underlying important agronomic traits. The main goal of this survey was to study the advantages of QTL mapping across versus within biparental populations using experimental data from three connected sugar beet (Beta vulgaris L.) populations evaluated for beet yield and potassium and sodium content. For the combined analysis across populations, we used two approaches for cofactor selection. In Model A, we assumed identical cofactors for every segregating population. In contrast, in Model B we selected cofactors specific for every segregating population. Model A performed better than Model B with respect to the number of QTL detected and the total proportion of phenotypic variance explained. The QTL analyses across populations revealed a substantially higher number of QTL compared to the analyses of single biparental populations. This clearly emphasizes the potential to increase QTL detection power with a joint analysis across biparental populations.     

Detection of putative quantitative trait loci in line crosses under infinitesimal genetic models

Quantitative trait locus (QTL) mapping studies often employ segregating generations derived from a cross between genetically divergent inbred lines. In the analysis of such data it is customary to fit a single QTL and use a null hypothesis which assumes that the genomic region under study contributes no genetic variance. To explore the situation in which multiple linked genes contribute to the genetic variance, we simulated an F₂-mapping experiment in which the genetic difference between the two original inbred strains was caused by a large number of loci, each having equal effect on the quantitative trait. QTLs were either in coupling, dispersion or repulsion phase in the base population of inbred lines, with the expected F₂ genetic variance explained by the QTLs being equivalent in the three models. Where QTLs were in coupling phase, one inbred line was fixed for all plus alleles, and the other line was fixed for minus alleles. Where QTLs were in dispersion phase, they were assumed to be randomly fixed for one or other allele (as if the inbred lines had evolved from a common ancestor by random drift). Where QTLs were in repulsion phase alleles within an inbred line were alternating plus and minus at adjacent loci, and alternative alleles were fixed in the two inbred lines. In all these genetic models a standard interval mapping test statistic used to determine whether there is a QTL of large effect segregating in the population was inflated on average. Furthermore, the use of a threshold for QTL detection derived under the assumption that no QTLs were segregating would often lead to spurious conclusions regards the presence of genes of large effects (i.e. type I errors). The employment of an alternative model for the analysis, including linked markers as cofactors in the analysis of a single interval, reduced the problem of type I error rate, although test statistics were still inflated relative to the case of no QTLs. It is argued that in practice one should take into account the difference between the strains or the genetic variance in the F₂ population when setting significance thresholds. In addition, tests designed to probe the adequacy of a single-QTL model or of an alternative infinitesimal coupling model are described. Such tests should be applied in QTL mapping studies to help dissect the true nature of genetic variation.     

QTL detection with bidirectional and unidirectional selective genotyping: marker-based and trait-based analyses

Selective genotyping of one or both phenotypic extremes of a population can be used to detect linkage between markers and quantitative trait loci (QTL) in situations in which full-population genotyping is too costly or not feasible, or where the objective is to rapidly screen large numbers of potential donors for useful alleles with large effects. Data may be subjected to 'trait-based' analysis, in which marker allele frequencies are compared between classes of progeny defined based on trait values, or to 'marker-based' analysis, in which trait means are compared between progeny classes defined based on marker genotypes. Here, bidirectional and unidirectional selective genotyping were simulated, using population sizes and selection intensities relevant to cereal breeding. Control of Type I error was usually adequate with marker-based analysis of variance or trait-based testing using the normal approximation of the binomial distribution. Bidirectional selective genotyping was more powerful than unidirectional. Trait-based analysis and marker-based analysis of variance were about equally powerful. With genotyping of the best 30 out of 500 lines (6%), a QTL explaining 15% of the phenotypic variance could be detected with a power of 0.8 when tests were conducted at a marker 10 cM from the QTL. With bidirectional selective genotyping, QTL with smaller effects and (or) QTL farther from the nearest marker could be detected. Similar QTL detection approaches were applied to data from a population of 436 recombinant inbred rice lines segregating for a large-effect QTL affecting grain yield under drought stress. That QTL was reliably detected by genotyping as few as 20 selected lines (4.5%). In experimental populations, selective genotyping can reduce costs of QTL detection, allowing larger numbers of potential donors to be screened for useful alleles with effects across different backgrounds. In plant breeding programs, selective genotyping can make it possible to detect QTL using even a limited number of progeny that have been retained after selection.     

Dissecting the genetic architecture of agronomic traits in multiple segregating populations in rapeseed (<Emphasis Type="Italic">Brassica napus</Emphasis> L.)

Detection of QTL in multiple segregating populations is of high interest as it includes more alleles than mapping in a single biparental population. In addition, such populations are routinely generated in applied plant breeding programs and can thus be used to identify QTL which are of direct relevance for a marker-assisted improvement of elite germplasm. Multiple-line cross QTL mapping and joint linkage association mapping were used for QTL detection. We empirically compared these two different biometrical approaches with regard to QTL detection for important agronomic traits in nine segregating populations of elite rapeseed lines. The plants were intensively phenotyped in multi-location field trials and genotyped with 253 SNP markers. Both approaches detected several additive QTL for diverse traits, including flowering time, plant height, protein content, oil content, glucosinolate content, and grain yield. In addition, we identified one epistatic QTL for flowering time. Consequently, both approaches appear suited for QTL detection in multiple segregating populations.     

Detecting QTL for feed intake traits and other performance traits in growing pigs in a Piétrain-Large White backcross

Knowing the large difference in daily feed intake (DFI) between Large White (LW) and Piétrain (PI) growing pigs, a backcross (BC) population has been set up to map QTL that could be used in marker assisted selection strategies. LW × PI boars were mated with sows from two LW lines to produce 16 sire families. A total of 717 BC progeny were fed ad libitum from 30 to 108 kg BW using single-place electronic feeders. A genome scan was conducted using genotypes for the halothane gene and 118 microsatellite markers spread on the 18 porcine autosomes. Interval mapping analyses were carried out, assuming different QTL alleles between sire families to account for within breed variability using the QTLMap software. The effects of the halothane genotype and of the dam line on the QTL effect estimates were tested. One QTL for DFI (P < 0.05 at the chromosome-wide (CW) level) and one QTL for feed conversion ratio (P < 0.01 at the CW level) were mapped to chromosomes SSC6 - probably due to the halothane alleles - and SSC7, respectively. Three putative QTL for feed intake traits were detected (P < 0.06 at the CW level) on SSC2, SSC7 and SSC9. QTL on feeding traits had effects in the range of 0.20 phenotypic s.d. The relatively low number of QTL detected for these traits suggests a large QTL allele variability within breeds and/or low effects of individual loci. Significant QTL were detected for traits related to carcass composition on chromosomes SSC6, SSC15 and SSC17, and to meat quality on chromosome SSC6 (P < 0.01 at the genome-wide level). QTL effects for body composition on SSC13 and SSC17 differed according to the LW dam line, which confirmed that QTL alleles were segregating in the LW breed. An epistatic effect involving the halothane locus and a QTL for loin weight on SSC7 was identified, the estimated substitution effects for the QTL differing by 200 g between Nn and NN individuals. The interactions between QTL alleles and genetic background or particular genes suggest further work to validate QTL segregations in the populations where marker assisted selection for the QTL would be applied.     

Success and failure in replication of genotype–phenotype associations: How does replication help in understanding the genetic basis of phenotypic variation in outbred populations?

Recent developments in sequencing technologies have facilitated genomewide mapping of phenotypic variation in natural populations. Such mapping efforts face a number of challenges potentially leading to low reproducibility. However, reproducible research forms the basis of scientific progress. We here discuss the options for replication and the reasons for potential nonreproducibility. We then review the evidence for reproducible quantitative trait loci (QTL) with a focus on natural animal populations. Existing case studies of replication fall into three categories: (i) traits that have been mapped to major effect loci (including chromosomal inversion and supergenes) by independent research teams; (ii) QTL fine‐mapped in discovery populations; and (iii) attempts to replicate QTL across multiple populations. Major effect loci, in particular those associated with inversions, have been successfully replicated in several cases within and across populations. Beyond such major effect variants, replication has been more successful within than across populations, suggesting that QTL discovered in natural populations may often be population‐specific. This suggests that biological causes (differences in linkage patterns, allele frequencies or context‐dependencies of QTL) contribute to nonreproducibility. Evidence from other fields, notably animal breeding and QTL mapping in humans, suggests that a significant fraction of QTL is indeed reproducible in direction and magnitude at least within populations. However, there is also a large number of QTL that cannot be easily reproduced. We put forward that more studies should explicitly address the causes and context‐dependencies of QTL signals, in particular to disentangle linkage differences, allele frequency differences and gene‐by‐environment interactions as biological causes of nonreproducibility of QTL, especially between populations.     

Association mapping for phenological, morphological, and quality traits in canola quality winter rapeseed (Brassica napus L.)

QTL mapping by association analysis has recently gained interest in plant breeding research as an alternative to QTL mapping in segregating populations from biparental crosses. In a first experiment on whole-genome association analysis in rapeseed, 684 mapped AFLP markers were tested for association with 14 traits in a set of 84 canola quality winter rapeseed cultivars. For association analysis a general linear model was used. By testing significance of marker-trait associations against a false discovery rate of 0.2, between 1 and 34 associated markers were found for 10 of the 14 traits. Taking into account linkage disequilibrium between the significant markers, these markers represent between 1 and 22 putative QTL for the respective traits. The minimum phenotypic variance explained by the QTL for the different traits ranged from 15% to 53%. A subset of 27 markers were significantly associated with two or more traits. These markers were predominantly shared between traits that were significantly correlated at the phenotypic level. The results show clearly that in rapeseed, QTL mapping by association analysis is a viable alternative to QTL mapping in segregating populations.     

Identification of Early Vigor QTLs and QTL by Environment Interactions in Wheat (<Emphasis Type="Italic">Triticum eastivum</Emphasis> L.)

Crop productivity is highly dependent on successful seed germination and seedling establishment. This study evaluated two mapping populations, Batavia/Ernie (double haploid) and Synthetic/Opata (recombinant inbred lines), for early vigor under water stress and normal growing conditions. Significant gene, environment (water), and gene by environment interaction effects were observed. Broad sense heritability was 29 and 40% for the Batavia/Ernie and Synthetic/Opata populations, respectively. Quantitative trait loci (QTL) were analyzed based on single and multienvironment models. The two mapping populations differed in the number and locations of QTLs except qNev.uwa.4AL was identified in both populations under the non-stress condition, while qSev.uwa.3BL was specifically expressed under the stress condition in the Synthetic/Opata population. QTL by environment interaction (QEI) enabled identification of nine QTLs, including those identified by the single environment approach. Phenotypic variation expression (PVE) of QEIs ranged from 4.8 to 14.9% across the populations. Larger proportion of PVE of QEIs was explained by the additive components. Favorable alleles for three of the QTLs identified in the Synthetic/Opata population were derived from Synthetic, while Batavia contributed favorable alleles to a QTL on the long arm of chromosome 1D in the Batavia/Ernie population. QTL detected under water stress (qSev.uwa.3BL) co-located with the DREB 1 gene, which was mapped between markers Xmwg818 and Xfbb117 (58.1–77.6 cM). QTLs with high proportion of additive components can be validated for marker assisted gene pyramiding and selection.     

How species evolve collectively: implications of gene flow and selection for the spread of advantageous alleles

The traditional view that species are held together through gene flow has been challenged by observations that migration is too restricted among populations of many species to prevent local divergence. However, only very low levels of gene flow are necessary to permit the spread of highly advantageous alleles, providing an alternative means by which low-migration species might be held together. We re-evaluate these arguments given the recent and wide availability of indirect estimates of gene flow. Our literature review of F(ST) values for a broad range of taxa suggests that gene flow in many taxa is considerably greater than suspected from earlier studies and often is sufficiently high to homogenize even neutral alleles. However, there are numerous species from essentially all organismal groups that lack sufficient gene flow to prevent divergence. Crude estimates on the strength of selection on phenotypic traits and effect sizes of quantitative trait loci (QTL) suggest that selection coefficients for leading QTL underlying phenotypic traits may be high enough to permit their rapid spread across populations. Thus, species may evolve collectively at major loci through the spread of favourable alleles, while simultaneously differentiating at other loci due to drift and local selection.     

Theory for identification of marker locus-QTL associations in population by line crosses

The objective of this paper is to present genetic theory demonstrating the conditions under which it should be possible to identify molecular marker-quantitative trait locus (QTL) associations in crosses of random-mating populations to inbreds. Using as an example the cross of a corn (Zea mays L.) population to an inbred, the expected disequilibrium for testcross and per se performance of F₂, F₃, BC₁ (to the inbred) and recombinant inbred generations was derived for cases where a marker allele is linked to an unfavorable QTL allele in the inbred and where the marker allele is linked to a favorable QTL allele in the inbred. Disequilibrium in segregating generations was shown to be a function of disequilibrium in the parent population, the frequency of marker and QTL alleles in the parent population, and the recombination distance between the marker and the QTL. To maximize the opportunity to identify a favorable QTL the following procedures are suggested:

CONNECTING QTLS TO THE G-MATRIX OF EVOLUTIONARY QUANTITATIVE GENETICS

Evolutionary quantitative genetics has recently advanced in two distinct streams. Many biologists address evolutionary questions by estimating phenotypic selection and genetic (co)variances ( G matrices). Simultaneously, an increasing number of studies have applied quantitative trait locus (QTL) mapping methods to dissect variation. Both conceptual and practical difficulties have isolated these two foci of quantitative genetics. A conceptual integration follows from the recognition that QTL allele frequencies are the essential variables relating the G -matrix to marker-based mapping experiments. Breeding designs initiated from randomly selected parental genotypes can be used to estimate QTL-specific genetic (co)variances. These statistics appropriately distill allelic variation and provide an explicit population context for QTL mapping estimates. Within this framework, one can parse the G -matrix into a set of mutually exclusive genomic components and ask whether these parts are similar or dissimilar in their respective features, for example the magnitude of phenotypic effects and the extent and nature of pleiotropy. As these features are critical determinants of sustained response to selection, the integration of QTL mapping methods into G -matrix estimation can provide a concrete, genetically based experimental program to investigate the evolutionary potential of natural populations.     

Joint estimates of quantitative trait locus effect and frequency using synthetic recombinant populations of Drosophila melanogaster

We develop and implement a strategy to map QTL in two synthetic populations of Drosophila melanogaster each initiated with eight inbred founder strains. These recombinant populations allow simultaneous estimates of QTL location, effect, and frequency. Five X-linked QTL influencing bristle number were resolved to intervals of approximately 1.3 cM. We confirm previous observations of bristle number QTL distal to 4A at the tip of the chromosome and identify two novel QTL in 7F-8C, an interval that does not include any classic bristle number candidate genes. If QTL at the tip of the X are biallelic they appear to be intermediate in frequency, although there is evidence that these QTL may reside in multiallelic haplotypes. Conversely, the two QTL mapping to the middle of the X chromosome are likely rare: in each case the minor allele is observed in only 1 of the 16 founders. Assuming additivity and biallelism we estimate that identified QTL contribute 1.0 and 8.7%, respectively, to total phenotypic variation in male abdominal and sternopleural bristle number in nature. Models that seek to explain the maintenance of genetic variation make different predictions about the population frequency of QTL alleles. Thus, mapping QTL in eight-way recombinant populations can distinguish between these models.     

Genetic architecture of a selection response in Arabidopsis thaliana

Quantitative trait locus (QTL) mapping has become an established and effective method for studying the genetic architecture of complex traits. In this report, we use a QTL mapping approach in combination with data from a large selection experiment in Arabidopsis thaliana to explore a response to selection of experimental populations with differentiated genetic backgrounds. Experimental populations with genetic backgrounds derived from ecotypes Landsberg and Niederzenz were exposed to multiple generations of fertility and viability selection. This selection resulted in phenotypic shifts in a number of life-history and fitness-related characters including early development time, flowering time, dry biomass, longevity, and fruit production. Quantitative trait loci were mapped for these traits and their positions were compared to previously characterized allele frequency changes in the experimental populations (Ungerer et al. 2003). Quantitative trait locus positions largely colocalized with genomic regions under strong and consistent selection in populations with differentiated genetic backgrounds, suggesting that alleles for these traits were selected similarly in differentiated genetic backgrounds. However, one QTL region exhibited a more variable response; being positively selected on one genetic background but apparently neutral in another. This study demonstrates how QTL mapping approaches can be combined with map-based population genetic data to study how selection acts on standing genetic variation in populations.     

Linkage disequilibrium mapping of quantitative trait loci under truncation selection

As a dense map of single nucleotide polymorphism (SNP) markers are available, population-based linkage disequilibrium (LD) mapping or association study is becoming one of the major tools for identifying quantitative trait loci (QTL) and for fine gene mapping. However, in many cases, LD between the marker and trait locus is not very strong. Approaches that maximize the potential of detecting LD will be essential for the success of LD mapping of QTL. In this paper, we propose two strategies for increasing the probability of detecting LD: (1) phenotypic selection and (2) haplotype LD mapping. To provide the foundations for LD mapping of QTL under selection, we develop analytic tools for assessing the impact of phenotypic selection on allele and haplotype frequencies, and LD under three trait models: single trait locus, two unlinked trait loci, and two linked trait loci with or without epistasis. In addition to a traditional chi(2) test, which compares the difference in allele or haplotype frequencies in the selected sample and population sample, we present multiple regression methods for LD mapping of QTL, and investigate which methods are effective in employing phenotypic selection for QTL mapping. We also develop a statistical framework for investigating and comparing the power of the single marker and multilocus haplotype test for LD mapping of QTL. Finally, the proposed methods are applied to mapping QTL influencing variation in systolic blood pressure in an isolated Chinese population.     

Use of a novel outbred by inbred F1 cross to detect genetic markers for growth

A unique outbred by inbred F1 resource population was established. The population structure facilitated the unique opportunity of examining gene by genetic background interaction through crossing two modern broiler sires with dams from two unrelated inbred lines, with no selection for growth rate, to produce about 600 F1 chicks. Pools of DNA were generated from the phenotypic extremes (20% high and low) for 8-week body weight for each of the four combinations of sire and dam line. For one sire family, pools were also separately generated for each sex. The pools were genoyped with 25 informative (segregating) microsatellites. This unique F1 cross between outbred and inbred populations allowed use of the inbred alleles as an 'internal control' for polymerase chain reaction amplification quality in DNA pools. Ten microsatellites showed marked differences (P < 0.05) in allele frequencies between high and low pools, suggesting an association between marker and quantitative trait loci (QTL). These differences were verified using selective genotyping. For many markers, differences in allele frequencies between the high and the low pools, or marker effect, varied between the two dam lines and the two sexes, suggesting an interaction between some genes and the genetic background as represented by different dam lines or sexes. The suggestive marker-QTL associations identified in this F1 population demonstrate the efficiency of this population design while different QTL effects in different genetic line crosses and sexes highlight the importance of gene by genetic background interaction in QTL detection.     

Identification of several small main-effect QTLs and a large number of epistatic QTLs for drought tolerance related traits in groundnut (Arachis hypogaea L.)

Cultivated groundnut or peanut (Arachis hypogaea L.), an allotetraploid (2n = 4x = 40), is a self pollinated and widely grown crop in the semi-arid regions of the world. Improvement of drought tolerance is an important area of research for groundnut breeding programmes. Therefore, for the identification of candidate QTLs for drought tolerance, a comprehensive and refined genetic map containing 191 SSR loci based on a single mapping population (TAG 24 x ICGV 86031), segregating for drought and surrogate traits was developed. Genotyping data and phenotyping data collected for more than ten drought related traits in 2-3 seasons were analyzed in detail for identification of main effect QTLs (M-QTLs) and epistatic QTLs (E-QTLs) using QTL Cartographer, QTLNetwork and Genotype Matrix Mapping (GMM) programmes. A total of 105 M-QTLs with 3.48-33.36% phenotypic variation explained (PVE) were identified using QTL Cartographer, while only 65 M-QTLs with 1.3-15.01% PVE were identified using QTLNetwork. A total of 53 M-QTLs were such which were identified using both programmes. On the other hand, GMM identified 186 (8.54-44.72% PVE) and 63 (7.11-21.13% PVE), three and two loci interactions, whereas only 8 E-QTL interactions with 1.7-8.34% PVE were identified through QTLNetwork. Interestingly a number of co-localized QTLs controlling 2-9 traits were also identified. The identification of few major, many minor M-QTLs and QTL × QTL interactions during the present study confirmed the complex and quantitative nature of drought tolerance in groundnut. This study suggests deployment of modern approaches like marker-assisted recurrent selection or genomic selection instead of marker-assisted backcrossing approach for breeding for drought tolerance in groundnut.     

Quantitative trait locus analysis and construction of consensus genetic map for foliar disease resistance based on two recombinant inbred line populations in cultivated groundnut (Arachis hypogaea L.)

Late leaf spot (LLS) and rust have the greatest impact on yield losses worldwide in groundnut (Arachis hypogaea L.). With the objective of identifying tightly linked markers to these diseases, a total of 3,097 simple sequence repeats (SSRs) were screened on the parents of two recombinant inbred line (RIL) populations, namely TAG 24?×?GPBD 4 (RIL-4) and TG 26?×?GPBD 4 (RIL-5), and segregation data were obtained for 209 marker loci for each of the mapping populations. Linkage map analysis of the 209 loci resulted in the mapping of 188 and 181 loci in RIL-4 and RIL-5 respectively. Using 143 markers common to the two maps, a consensus map with 225 SSR loci and total map distance of 1,152.9?cM was developed. Comprehensive quantitative trait locus (QTL) analysis detected a total of 28 QTL for LLS and 15 QTL for rust. A major QTL for LLS, namely QTL(LLS)01 (GM1573/GM1009-pPGPseq8D09), with 10.27-62.34% phenotypic variance explained (PVE) was detected in all the six environments in the RIL-4 population. In the case of rust resistance, in addition to marker IPAHM103 identified earlier, four new markers (GM2009, GM1536, GM2301 and GM2079) showed significant association with the major QTL (82.96% PVE). Localization of 42 QTL for LLS and rust on the consensus map identified two candidate genomic regions conferring resistance to LLS and rust. One region present on linkage group AhXV contained three QTL each for LLS (up to 67.98% PVE) and rust (up to 82.96% PVE). The second candidate genomic region contained the major QTL with up to 62.34% PVE for LLS. Molecular markers associated with the major QTL for resistance to LLS and rust can be deployed in molecular breeding for developing groundnut varieties with enhanced resistance to foliar diseases. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11032-011-9661-z) contains supplementary material, which is available to authorized users.