Mapping of QTLs for lycopene and other fruit traits in a Lycopersicon esculentum × L. pimpinellifolium cross and comparison of QTLs across tomato species

Quantitative trait loci (QTLs) for several fruit traits in tomato were mapped and characterized in a backcross population of an interspecific cross between Lycopersicon esculentum fresh-marker breeding line NC84173 and L. pimpinellifolium accession LA722. A molecular linkage map of this cross that was previously constructed based on 119 BC1 individuals and 151 RFLP markers was used for the QTL mapping. The parental lines and 119 BC1S1 families (self-pollinated progeny of BC1 individuals) were grown under field conditions at two locations, Rock Spring, PA, and Davis, CA, and fruits were scored for weight (FW), polar (PD) and equatorial diameters (ED), shape (FS), total soluble solids content (SSC), pH and lycopene content (LYC). For each trait, between 4 and 10 QTLs were identified with individual effects ranging between 4.4% and 32.9% and multilocus QTL effects ranging between 39% and 75% of the total phenotypic variation. Most QTL effects were predictable from the parental phenotypes, and several QTLs were identified that affected more than one trait. A few pairwise epistatic interactions were detected between QTL-linked and QTL-unlinked markers. Despite great differences between PA and CA growing conditions, the majority of FW QTLs (78%) and SSC QTLs (75%) in the two locations shared similar genomic positions. Almost all of the QTLs that were identified in the present study for FW and SSC were previously identified in six other studies that used different interspecific crosses of tomato; this indicates conservation of QTLs for fruit traits across tomato species. Altogether, the seven studies identified at least 28 QTLs for FW and 32 QTLs for SSC on the 12 tomato chromosomes. However, for each trait a few major QTLs were commonly identified in 4 or more studies; such ‘popular’ QTLs should be of considerable interest for breeding purposes as well as basic research towards cloning of QTLs. Notably, a majority of QTLs for increased SSC also contributed to decreased fruit size. Therefore, to significantly increase SSC of the cultivated tomato, some compromise in fruit size may be unavoidable. This revised version was published online in June 2006 with corrections to the Cover Date.     

RFLP Mapping in Soybean: Association between Marker Loci and Variation in Quantitative Traits

Quantitative trait loci (QTLs) have been mapped to small intervals along the chromosomes of tomato (Lycopersicon esculentum), by a method we call substitution mapping. The size of the interval to which a QTL can be mapped is determined primarily by the number and spacing of previously mapped genetic markers in the region surrounding the QTL. We demonstrate the method using tomato genotypes carrying chromosomal segments from Lycopersicon chmielewskii, a wild relative of tomato with high soluble solids concentration but small fruit and low yield. Different L. chmielewskii chromosomal segments carrying a common restriction fragment length polymorphism were identified, and their regions of overlap determined using all available genetic markers. The effect of these chromosomal segments on soluble solids concentration, fruit mass, yield, and pH, was determined in the field. Many overlapping chromosomal segments had very different phenotypic effects, indicating QTLs affecting the phenotype(s) to lie in intervals of as little as 3 cM by which the segments differed. Some associations between different traits were attributed to close linkage between two or more QTLs, rather than pleiotropic effects of a single QTL: in such cases, recombination should separate desirable QTLs from genes with undesirable effects. The prominence of such trait associations in wide crosses appears partly due to infrequent reciprocal recombination between heterozygous chromosomal segments flanked by homozygous regions. Substitution mapping is particularly applicable to gene introgression from wild to domestic species, and generally useful in narrowing the gap between linkage mapping and physical mapping of QTLs.     

High Resolution of Quantitative Traits into Multiple Loci via Interval Mapping

A very general method is described for multiple linear regression of a quantitative phenotype on genotype [putative quantitative trait loci (QTLs) and markers] in segregating generations obtained from line crosses. The method exploits two features, (a) the use of additional parental and F(1) data, which fixes the joint QTL effects and the environmental error, and (b) the use of markers as cofactors, which reduces the genetic background noise. As a result, a significant increase of QTL detection power is achieved in comparison with conventional QTL mapping. The core of the method is the completion of any missing genotypic (QTL and marker) observations, which is embedded in a general and simple expectation maximization (EM) algorithm to obtain maximum likelihood estimates of the model parameters. The method is described in detail for the analysis of an F(2) generation. Because of the generality of the approach, it is easily applicable to other generations, such as backcross progenies and recombinant inbred lines. An example is presented in which multiple QTLs for plant height in tomato are mapped in an F(2) progeny, using additional data from the parents and their F(1) progeny.     

Mapping of yield-related QTLs in pepper in an interspecific cross of <Emphasis Type="Italic">Capsicum annuum</Emphasis> and <Emphasis Type="Italic">C. frutescens</Emphasis>

An advanced backcross QTL study was performed in pepper using a cross between the cultivated species Capsicum annuum cv. Maor and the wild C. frutescens BG 2816 accession. A genetic map from this cross was constructed, based on 248 BC(2) plants and 92 restriction fragment length polymorphism (RFLP) markers distributed throughout the genome. Ten yield-related traits were analyzed in the BC(2) and BC(2)S(1) generations, and a total of 58 quantitative trait loci (QTLs) were detected; the number of QTLs per trait ranged from two to ten. Most of the QTLs were found in 11 clusters, in which similar QTL positions were identified for multiple traits. Unlike the high percentage of favorable QTL alleles discovered in wild species of tomato and rice, only a few such QTL alleles were detected in BG 2816. For six QTLs (10%), alleles with effects opposite to those expected from the phenotype were detected in the wild species. The use of common RFLP markers in the pepper and tomato maps enabled possible orthologous QTLs in the two species to be determined. The degree of putative QTL orthology for the two main fruit morphology traits-weight and shape-varied considerably. While all eight QTLs identified for fruit weight in this study could be orthologous to tomato fruit weight QTLs, only one out of six fruit shape QTLs found in this study could be orthologous to tomato fruit shape QTLs.     

A Sequential Quantitative Trait Locus Fine-Mapping Strategy Using Recombinant-Derived Progeny

A thorough understanding of the quantitative trait loci(QTLs)that underlie agronomically important traits in crops would greatly increase agricultural productivity.Although advances have been made in QTL cloning,the majority of QTLs remain unknown because of their low heritability and minor contributions to phenotypic performance.Here we summarize the key advantages and disadvantages of current QTL fine-mapping methodologies,and then introduce a sequential QTL fine-mapping strategy based on both genotypes and phenotypes of progeny derived from recombinants.With this mapping strategy,experimental errors could be dramatically diminished so as to reveal the authentic genetic effect of target QTLs.The number of progeny required to detect QTLs atvarious R~2 values was calculated,and the backcross generation suitable to start QTL fine-mapping was also estimated.This mapping strategy has proved to be very powerful in narrowing down QTL regions,particularly minor-effect QTLs,as revealed by fine-mapping of various resistance QTLs in maize.Application of this sequential QTL mapping strategy should accelerate cloning of agronomically important QTLs,which is currently a substantial challenge in crops.     

Mapping QTLs conferring salt tolerance during germination in tomato by selective genotyping

This study was conducted to identify genomic regions (quantitative trait loci, QTLs) affecting salt tolerance during germination in tomato. Germination response of an F2 population of a cross between UCT5 (Lycopersicon esculentum, salt-sensitive) and LA716 (L. pennellii, salt-tolerant) was evaluated at a salt-stress level of 175 mM NaCl + 17.5 mM CaCl2 (water potential ca. –950 kPa). Germination was scored visually as radicle protrusion at 6 h intervals for 30 consecutive days. Individuals at both extremes of the response distribution (i.e., salt-tolerant and salt-sensitive individuals) were selected. The selected individuals were genotyped at 84 genetic markers including 16 isozymes and 68 restriction fragment length polymorphisms (RFLPs). Trait-based marker analysis (TBA) which measures changes (differences) in marker allele frequencies in selected lines was used to identify marker-linked QTLs. Eight genomic regions were identified on seven tomato chromosomes bearing genes (QTLs) with significant effects on this trait. The results confirmed our previous suggestion that salt tolerance during germination in tomato is polygenically controlled. The salt-tolerant parent contributed favorable QTL alleles on chromosomes 1, 3, 9 and 12 whereas the salt sensitive parent contributed favorable QTL alleles on chromosomes 2, 7 and 8. The identification of favorable alleles in both parents suggests the likelihood of recovering transgressive segregants in progeny derived from these parental genotypes. The results can be used for marker-assisted selection and breeding of salt-tolerant tomatoes.     

QTL analysis of morphological traits in a tomato recombinant inbred line population.

Quantitative trait loci (QTLs) influencing morphological traits were identified by restriction fragment length polymorphism (RFLP) analysis in a population of recombinant inbred lines (RILs) derived from a cross of the cultivated tomato Lycopersicon esculentum with a related wild species, Lycopersicon cheesmanii. One hundred and thirty-two RFLP loci spaced throughout the tomato genome were used as DNA probes on genomic DNA from 97 RIL families. Morphological traits, including plant height, plant fresh mass, number of branches, number of nodes, first flower-bearing node, and leaf length, were evaluated in two controlled environment trials in 1992 and 1993. QTLs were detected via regression analyses at multiple marker loci for each morphological trait. A total of 41 markers were significantly associated with the traits examined. Large additive effects were measured at many of these loci. QTLs for multiple traits were detected on chromosomes 3 (TG74) and 4 (CT188), suggesting the possible association of these chromosome segments with genes controlling growth and development in tomato. These chromosomal regions were also associated with multiple morphological traits in a L. esculentum x Lycopersicon pennellii cross. A total of 13% of the QTLs identified for traits common to both studies occupied similar map positions.     

RFLP mapping of QTLs conferring cold tolerance during seed germination in an interspecific cross of tomato

Most cultivars of tomato, Lycopersicon esculentum, are sensitive to low (chilling) temperatures (0–15 °C) during seed germination; however, genetic sources of cold (chilling) tolerance have been identified within the related wild species. The purpose of this study was to identify quantitative trait loci (QTLs) that contribute to cold tolerance during germination in tomato using a backcross population of an interspecific cross between a cold-sensitive tomato line (NC84173, recurrent parent) and a L. pimpinellifolium accession (LA722) that germinates rapidly under low temperatures. A total of 119 BC1 individuals were genotyped for 151 restriction fragment length polymorphism (RFLP) markers and a genetic linkage map was constructed. The parental lines and 119 BC1S1 families (self-pollinated progeny of the BC1 individuals) were evaluated for germination at a low temperature (11±0.5 °C). Germination was scored visually as radicle protrusion at 8 h intervals for 28 consecutive days. Germination response was analyzed by the survival analysis and the times to 25, 50 and 75% germination were calculated. In addition, a germination index (GI) was calculated as the weighted mean of the time from imbibition to germination for each family/line. Two QTL mapping techniques, interval mapping (using MAPMAKER/QTL) and single-point analysis (using QGENE), were used to identify QTLs. The results of both methods were similar and two chromosomal locations (3–5 putative QTLs) with significant effects on low temperature germination were identified. The L. pimpinellifolium accession had favorable QTL alleles on chromosomes 1 and NC84173 had favorable QTL alleles on chromosome 4. The percentage of phenotypic variation explained (PVE) by individual QTLs ranged from 11.9% to 33.4%. Multilocus analysis indicated that the cumulative action of all significant QTLs accounted for 43.8% of the total phenotypic variance. Digenic epistatic interactions were evident between two of the QTL-linked markers and two unlinked markers. Transgressive phenotypes were observed in the direction of cold sensitivity. The results indicate that low temperature germination of tomato seed can be improved by marker-assisted selection.     

Morphological variation in tomato: a comprehensive study of quantitative trait loci controlling fruit shape and development

Variation in fruit morphology is a prevalent characteristic among cultivated tomato. The genetic and developmental mechanisms underlying similarities and differences in shape between the fruit of two elongated tomato varieties were investigated. Fruit from two F2 populations constructed from either Solanum lycopersicum cv. Howard German or cv. Banana Legs crossed with S. pimpinellifolium accession LA1589, and one BC1 population constructed with S. lycopersicum Howard German as the recurrent parent, were analysed for shape by using a new software program Tomato Analyzer. Quantitative trait loci (QTLs) controlling 15 individual shape attributes were mapped by both single and multitrait composite interval mapping in each population. In addition, principal components analysis and canonical discriminant analysis were conducted on these shape attributes to determine the greatest sources of variation among and between the populations. Individual principal components and canonical variates were subjected to QTL analysis to map regions of the genome influencing fruit shape in the cultivars. Common and unique regions, as well as previously known and novel QTLs, underlying fruit morphology in tomato were identified. Four major loci were found to control multiple fruit shape traits, principal components, and canonical variates in the populations. In addition, QTLs associated with the principal components better revealed regions of the genome that varied among populations than did the QTL associated with canonical variates. The QTL identified can be compared across additional populations of tomato and other fruit-bearing crop species.     

Genetic mapping of quantitative trait loci controlling fruit size and shape in papaya

Papaya (Carica papaya L.) is a pan-tropical tree that bears fruit exhibiting a wide range of size and shape. Depending on variety and environment, papaya fruit may weigh from 0.2 kg up to 10 kg. Papaya fruit shape is a sex-linked trait ranging from spherical to ovate, cylindrical or pyriform. An F2 mapping population, produced from a cross between the Thai variety Khaek Dum, bearing 1.2 kg, red-fleshed fruit, and variety 2H94, a Hawaii Solo type bearing a 0.2 kg, yellow-fleshed fruit, was used to identify quantitative trait loci (QTLs) that influence papaya fruit characters including weight, diameter, length and shape. Fruit phenotype data, collected from two subpopulations planted in successive growing seasons, showed striking differences by year indicating significant genotype × environment interactions. Fourteen QTL with phenotypic effects ranging from 5 to 23% were identified across six linkage groups (LGs) with clusters of two or more QTL on LGs 02, 03, 07 and 09. These loci contain homologs to the tomato fruit QTL ovate, sun and fw2.2 regulating fruit size and shape. The papaya fruit QTL provide a starting point for dissecting the genetic pathways leading to extreme fruit size and shape and may prove useful for papaya breeders attempting to tailor new varieties to specific consumer markets.     

QTLs for tomato powdery mildew resistance (Oidium lycopersici) in Lycopersicon parviflorum G1.1601 co-localize with two qualitative powdery mildew resistance genes

Tomato (Lycopersicon esculentum) is susceptible to the powdery mildew Oidium lycopersici, but several wild relatives such as Lycopersicon parviflorum G1.1601 are completely resistant. An F2 population from a cross of Lycopersicon esculentum cv. Moneymaker x Lycopersicon parviflorum G1.1601 was used to map the O. lycopersici resistance by using amplified fragment length polymorphism markers. The resistance was controlled by three quantitative trait loci (QTLs). Ol-qtl1 is on chromosome 6 in the same region as the Ol-1 locus, which is involved in a hypersensitive resistance response to O. lycopersici. Ol-qtl2 and Ol-qtl3 are located on chromosome 12, separated by 25 cM, in the vicinity of the Lv locus conferring resistance to another powdery mildew species, Leveillula taurica. The three QTLs, jointly explaining 68% of the phenotypic variation, were confirmed by testing F3 progenies. A set of polymerase chain reaction-based cleaved amplified polymorphic sequence and sequence characterized amplified region markers was generated for efficient monitoring of the target QTL genomic regions in marker assisted selection. The possible relationship between genes underlying major and partial resistance for tomato powdery mildew is discussed.     

Quantitative genetic analysis of flowering time in tomato.

Artificial selection of cultivated tomato (Solanum lycopersicum L.) has resulted in the generation of early-flowering, day-length-insensitive cultivars, despite its close relationship to other Solanum species that need more time and specific photoperiods to flower. To investigate the genetic mechanisms controlling flowering time in tomato and related species, we performed a quantitative trait locus (QTL) analysis for flowering time in an F2 mapping population derived from S. lycopersicum and its late-flowering wild relative S. chmielewskii. Flowering time was scored as the number of days from sowing to the opening of the first flower (days to flowering), and as the number of leaves under the first inflorescence (leaf number). QTL analyses detected 2 QTLs affecting days to flowering, which explained 55.3% of the total phenotypic variance, and 6 QTLs for leaf number, accounting for 66.7% of the corresponding phenotypic variance. Four of the leaf number QTLs had not previously been detected for this trait in tomato. Colocation of some QTLs with flowering-time genes included in the genetic map suggests PHYB2, FALSIFLORA, and a tomato FLC-like sequence as candidate genes that might have been targets of selection during the domestication of tomato.     

Using the mixed model for interval mapping of quantitative trait loci in outbred line crosses

Interval mapping by simple regression is a powerful method for the detection of quantitative trait loci (QTLs) in line crosses such as F2 populations. Due to the ease of computation of the regression approach, relatively complex models with multiple fixed effects, interactions between QTLs or between QTLs and fixed effects can easily be accommodated. However, polygenic effects, which are not targeted in QTL analysis, cannot be treated as random effects in a least squares analysis. In a cross between true inbred lines this is of no consequence, as the polygenic effect contributes just to the residual variance. In a cross between outbred lines, however, if a trait has high polygenic heritability, the additive polygenic effect has a large influence on variation in the population. Here we extend the fixed model for the regression interval mapping method to a mixed model using an animal model. This makes it possible to use not only the observations from progeny (e.g. F2), but also those from the parents (F1) to evaluate QTLs and polygenic effects. We show how the animal model using parental observations can be applied to an outbred cross and so increase the power and accuracy of QTL analysis. Three estimation methods, i.e. regression and an animal model either with or without parental observations, are applied to simulated data. The animal model using parental observations is shown to have advantages in estimating QTL position and additive genotypic value, especially when the polygenic heritability is large and the number of progeny per parent is small.     

Stability over genetic backgrounds, generations and years of quantitative trait locus (QTLs) for organoleptic quality in tomato

The efficiency of marker-assisted backcross for the introgression of a quantitative trait locus (QTL) from a donor line into a recipient line depends on the stability of QTL expression. QTLs for six quality traits in tomato (fruit weight, firmness, locule number, soluble solid content, sugar content and titratable acidity) were studied in order to investigate their individual effect and their stability over years, generations and genetic backgrounds. Five chromosome regions carrying fruit quality QTLs were transferred following a marker-assisted backcross scheme from a cherry tomato line into three modern lines with larger fruits. Three sets of genotypes corresponding to three generations were compared: (1) an RIL population, which contained 50% of each parental genome, (2) three BC3S1 populations which segregated simultaneously for the five regions of interest but were almost fully homozygous for the recipient genome on the eight chromosomes carrying no QTL and (3) three sets of QTL-NILs (BC3S3 lines) which differed from the recipient line only in one of the five regions. QTL detection was performed in each generation, in each genetic background and during 2 successive years for QTL-NILs. About half of the QTLs detected in QTL-NILs were detected in both years. Eight of the ten QTLs detected in RILs were recovered in the QTL-NILs with the genetic background used for the initial QTL mapping experiment, with the exception of two QTLs for fruit firmness. Several new QTLs were detected. In the two other genetic backgrounds, the number of QTLs in common with the RILs was lower, but several new QTLs were also detected in advanced generations.     

Genetic control of fruit vitamin C contents

An F(1) progeny derived from a cross between the apple (Malus x domestica) cultivars Telamon and Braeburn was used to identify quantitative trait loci (QTL) linked to the vitamin C (l-ascorbate [l-AA]) contents of fruit skin and flesh (cortex) tissues. We identified up to three highly significant QTLs for both the mean l-AA and the mean total l-AA contents of fruit flesh on both parental genetic linkage maps, confirming the quantitative nature of these traits. These QTLs account for up to a maximum of 60% of the total population variation observed in the progeny, and with a maximal individual contribution of 31% per QTL. QTLs common to both parents were identified on linkage groups (LGs) 6, 10, and 11 of the Malus reference map, while each parent also had additional unique QTLs on other LGs. Interestingly, one strong QTL on LG-17 of the Telamon linkage map colocalized with a highly significant QTL associated with flesh browning, and a minor QTL for dehydroascorbate content, supporting earlier work that links fruit l-AA contents with the susceptibility of hardfruit to postharvest browning. We also found significant minor QTLs for skin l-AA and total l-AA (l-AA + dehydroascorbate) contents in Telamon. Currently, little is known about the genetic determinants underlying tissue l-AA homeostasis, but the presence of major, highly significant QTL in both these apple genotypes under field conditions suggests the existence of common control mechanisms, allelic heterozygosity, and helps outline strategies and the potential for the molecular breeding of these traits.     

QTL analysis of fruit components in the progeny of a Rennell Island Tall coconut (Cocos nucifera L.) individual

We investigated the genetic factors controlling fruit components in coconut by performing QTL analyses for fruit component weights and ratios in a segregating progeny of a Rennell Island Tall genotype. The underlying linkage map of this population was already established in a previous study, as well as QTL analyses for fruit production, which were used to complement our results. The addition of 53 new markers (mainly SSRs) led to minor amendments in the map. A total of 52 putative QTLs were identified for the 11 traits under study. Thirty-four of them were grouped in six small clusters, which probably correspond to single pleiotropic genes. Some additional QTLs located apart from these clusters also had relatively large effects on the individual traits. The QTLs for fruit component weight, endosperm humidity and fruit production were found at different locations in the genome, suggesting that efficient marker-assisted selection for yield can be achieved by selecting QTLs for the individual components. The detected QTLs descend from a genotype belonging to the “Pacific” coconut group. Based on the known molecular and phenotypic differences between “Pacific” and “Indo-Atlantic” coconuts, we suggest that a large fraction of coconut genetic diversity is still to be investigated by studying populations derived from crosses between these groups. Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users.     

QTL mapping analysis of plant height and ear height of maize (Zea mays L.)

Genetic map containing 103 microsatellite loci obtained on 200 F2 plants derived from the cross R15 x 478 was used for quantitative trait loci (QTL) mapping in maize. QTL were characterized in a population of 200 F2:4 lines, derived from selfing the F2 plants, and were evaluated with two replications in two environments. QTL determinations were made from the mean of these two environments. Plant height (PH) and ear height (EH) were measured. Using composite interval mapping (CIM) method, a total of 14 distinct QTLs were identified: nine for PH and five for EH. Additive, partial dominance, dominance, and overdominance actions existed among all detected QTL affecting plant height and ear height. The QTL explained 78.27% of the phenotypic variance of PH and 41.50% of EH. The 14 QTLs displayed mostly dominance or partial dominance gene action and mapped to chromosomes 2, 3, 4, 8 and 9.     

QTL analysis of plant development and fruit traits in pepper and performance of selective phenotyping

A QTL analysis was performed to determine the genetic basis of 13 horticultural traits conditioning yield in pepper (Capsicum annuum). The mapping population was a large population of 297 recombinant inbred lines (RIL) originating from a cross between the large-fruited bell pepper cultivar ‘Yolo Wonder’ and the small-fruited chilli pepper ‘Criollo de Morelos 334’. A total of 76 QTLs were detected for 13 fruit and plant traits, grouped in 28 chromosome regions. These QTLs explained together between 7% (internode growth time) and 91% (fruit diameter) of the phenotypic variation. The QTL analysis was also performed on two subsets of 141 and 93 RILs sampled using the MapPop software. The smaller populations allowed for the detection of a reduced set of QTLs and reduced the overall percentage of trait variation explained by QTLs. The frequency of false positives as well as the individual effect of QTLs increased in reduced population sets as a result of reduced sampling. The results from the QTL analysis permitted an overall glance over the genetic architecture of traits considered by breeders for selection. Colinearities between clusters of QTLs controlling fruit traits and/or plant development in distinct pepper species and in related solanaceous crop species (tomato and eggplant) suggests that shared mechanisms control the shape and growth of different organs throughout these species.     

Detection of Obesity QTLs on Mouse Chromosomes 1 and 7 by Selective DNA Pooling

The inheritance of obesity has been analyzed in an intercross between the lean 129/Sv mouse strain and the obesity-prone EL/Suz mouse strain. The weights of three major fat pads were determined on 4-month-old mice, and the sum of these weights, divided by body weight, was used as an adiposity index. The strategy of selective DNA pooling was used as a primary screen to identify putative quantitative trait loci (QTLs) affecting adiposity index. DNA pools representing the leanest 15% and fattest 15% of the F2 progeny were compared for differential allelic enrichment using widely dispersed microsatellite variants. To evaluate putative QTLs, individual genotyping and interval mapping were employed to estimate QTL effects and assess statistical significance. One QTL affecting adiposity index, which accounted for 12.3% of phenotypic variance in gender-merged data, was mapped to the central region of Chromosome (Chr) 7. The QTL allele inherited from EL conferred increased adiposity. A second QTL that accounts for 6.3% of phenotypic variance was identified on Chr 1 nearD1Mit211.At both QTLs, the data are consistent with dominant inheritance of the allele contributing to obesity. The possible relationships between these QTLs and previously described obesity QTLs, major obesity mutations, and candidate genes are discussed.     

The genetic basis of adaptive population differentiation: a quantitative trait locus analysis of fitness traits in two wild barley populations from contrasting habitats

We used a quantitative trait locus (QTL) approach to study the genetic basis of population differentiation in wild barley, Hordeum spontaneum. Several ecotypes are recognized in this model species, and population genetic studies and reciprocal transplant experiments have indicated the role of local adaptation in shaping population differences. We derived a mapping population from a cross between a coastal Mediterranean population and a steppe inland population from Israel and assessed F3 progeny fitness in the natural growing environments of the two parental populations. Dilution of the local gene pool, estimated as the proportion of native alleles at 96 marker loci in the recombinant lines, negatively affected fitness traits at both sites. QTLs for fitness traits tended to differ in the magnitude but not in the direction of their effects across sites, with beneficial alleles generally conferring a greater fitness advantage at their native site. Several QTLs showed fitness effects at one site only, but no opposite selection on individual QTLs was observed across the sites. In a common-garden experiment, we explored the hypothesis that the two populations have adapted to divergent nutrient availabilities. In the different nutrient environments of this experiment, but not under field conditions, fitness of the F3 progeny lines increased with the number of heterozygous marker loci. Comparison of QTL-effects that underlie genotype x nutrient interaction in the common-garden experiment and genotype x site interaction in the field suggested that population differentiation at the field sites may have been driven by divergent nutrient availabilities to a limited extent. Also in this experiment no QTLs were observed with opposite fitness effects in contrasting environments. Our data are consistent with the view that adaptive differentiation can be based on selection on multiple traits changing gradually along ecological gradients. This can occur without QTLs showing opposite fitness effects in the different environments, that is, in the absence of genetic trade-offs in performance between environments.