Trait-based analyses for the detection of linkage between marker loci and quantitative trait loci in crosses between inbred lines

Summary Methods are presented for determining linkage between a marker locus and a nearby locus affecting a quantitative trait (quantitative trait locus=QTL), based on changes in the marker allele frequencies in selection lines derived from the F-2 of a cross between inbred lines, or in the high and low phenotypic classes of an F-2 or BC population. The power of such trait-based (TB) analyses was evaluated and compared with that of methods for determining linkage based on the mean quantitative trait value of marker genotypes in F-2 or BC populations [marker-based (MB) analyses]. TB analyses can be utilized for marker-QTL linkage determination in situations where the MB analysis is not applicable, including analysis of polygenic resistance traits where only a part of the population survives exposure to the Stressor and analysis of marker-allele frequency changes in selection lines. TB analyses may be a useful alternative to MB analyses when interest is centered on a single quantitative trait only and costs of scoring for markers are high compared with costs of raising and obtaining quantitative trait information on F-2 or BC individuals. In this case, a TB analysis will enable equivalent power to be obtained with fewer individuals scored for the marker, but more individuals scored for the quantitative trait. MB analyses remain the method of choice when more than one quantitative trait is to be analyzed in a given population.Contribution from the ARO, Bet Dagan, Israel. No. 1698-E, 1986 series     

Estimation of the contribution of quantitative trait loci (QTL) to the variance of a quantitative trait by means of genetic markers

The estimation of the contribution of an individual quantitative trait locus (QTL) to the variance of a quantitative trait is considered in the framework of an analysis of variance (ANOVA). ANOVA mean squares expectations which are appropriate to the specific case of QTL mapping experiments are derived. These expectations allow the specificities associated with the limited number of genotypes at a given locus to be taken into account. Discrepancies with classical expectations are particularly important for two-class experiments (backcross, recombinant inbred lines, doubled haploid populations) and F₂ populations. The result allows us firstly to reconsider the power of experiments (i.e. the probability of detecting a QTL with a given contribution to the variance of the trait). It illustrates that the use of classical formulae for mean squares expectations leads to a strong underestimation of the power of the experiments. Secondly, from the observed mean squares it is possible to estimate directly the variance associated with a locus and the fraction of the total variance associated to this locus (r _l ² ). When compared to other methods, the values estimated using this method are unbiased. Considering unbiased estimators increases in importance when (1) the experimental size is limited; (2) the number of genotypes at the locus of interest is large; and (3) the fraction of the variation associated with this locus is small. Finally, specific mean squares expectations allows us to propose a simple analytical method by which to estimate the confidence interval of r _l ² . This point is particularly important since results indicate that 95% confidence intervals for r _l ² can be rather wide:2–23% for a 10% estimate and 8–34% for a 20% estimate if 100 individuals are considered.     

Mapping of post-flowering drought resistance traits in grain sorghum: association between QTLs influencing premature senescence and maturity

The identification of genetic factors underlying the complex responses of plants to drought stress provides a solid basis for improving drought resistance. The stay-green character in sorghum (Sorghum bicolor L. Moench) is a post-flowering drought resistance trait, which makes plants resistant to premature senescence under drought stress during the grainfilling stage. The objective of this study was to identify quantitative trait loci (QTLs) that control premature senescence and maturity traits, and to investigate their association under post-flowering drought stress in grain sorghum. A genetic linkage map was developed using a set of recombinant inbred lines (RILs) obtained from the cross B35 × Tx430, which were scored for 142 restriction fragment length polymorphism (RFLP) markers. The RILs and their parental lines were evaluated for post-flowering drought resistance and maturity in four environments. Simple interval mapping identified seven stay-green QTLs and two maturity QTLs. Three major stay-green QTLs (SGA, SGD and SGG) contributed to 42% of the phenotypic variability (LOD 9.0) and four minor QTLs (SGB, SGI.1, SGI.2, and SGJ) significantly contributed to an additional 25% of the phenotypic variability in stay-green ratings. One maturity QTL (DFB) alone contributed to 40% of the phenotypic variability (LOD 10.0), while the second QTL (DFG) significantly contributed to an additional 17% of the phenotypic variability (LOD 4.9). Composite interval mapping confirmed the above results with an additional analysis of the QTL × Environment interaction. With heritability estimates of 0.72 for stay-green and 0.90 for maturity, the identified QTLs explained about 90% and 63% of genetic variability for stay-green and maturity traits, respectively. Although stay-green ratings were significantly correlated (r=0.22, P ≤ 0.05) with maturity, six of the seven stay-green QTLs were independent of the QTLs influencing maturity. Similarly, one maturity QTL (DFB) was independent of the stay-green QTLs. One stay-green QTL (SGG), however, mapped in the vicinity of a maturity QTL (DFG), and all markers in the vicinity of the independent maturity QTL (DFB) were significantly (P ≤ 0.1) correlated with stay-green ratings, confounding the phenotyping of stay-green. The molecular genetic analysis of the QTLs influencing stay-green and maturity, together with the association between these two inversely related traits, provides a basis for further study of the underlying physiological mechanisms and demonstrates the possibility of improving drought resistance in plants by pyramiding the favorable QTLs. Received: 10 October 1998 / Accepted: 12 July 1999     

Mapping the genome of rapeseed (Brassica napus L.). I. Construction of an RFLP linkage map and localization of QTLs for seed glucosinolate content

A linkage map of the rapeseed genome comprising 204 RFLP markers, 2 RAPD markers, and 1 phenotypic marker was constructed using a F₁ derived doubled haploid population obtained from a cross between the winter rapeseed varieties Mansholt's Hamburger Raps and Samourai. The mapped markers were distributed on 19 linkage groups covering 1441 cM. About 43% of these markers proved to be of dominant nature; 36% of the mapped marker loci were duplicated, and conserved linkage arrangements indicated duplicated regions in the rapeseed genome. Deviation from Mendelian segregation ratios was observed for 27.8% of the markers. Most of these markers were clustered in 7 large blocks on 7 linkage groups, indicating an equal number of effective factors responsible for the skewed segregations. Using cDNA probes for the genes of acyl-carrier-protein (ACP) and -ketoacyl-ACP-synthase I (KASI) we were able to map three and two loci, respectively, for these genes. The linkage map was used to localize QTLs for seed glucosinolate content by interval mapping. Four QTLs could be mapped on four linkage groups, giving a minimum number of factors involved in the genetic control of this trait. The estimated effects of the mapped QTLs explain about 74% of the difference between both parental lines and about 61.7 % of the phenotypic variance observed in the doubled haploid mapping population.     

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 dissection of tocopherol content and composition in maize grain using quantitative trait loci analysis and the candidate gene approach

Tocopherols are essential micronutrients for humans and animals, with several beneficial effects in plants. Among cereals, only maize grains contain high concentrations of tocopherols. In this investigation we analyzed, during 2004 and 2005, by high-performance liquid chromatography (HPLC), a population of 233 recombinant inbred lines (RIL) which were derived from two diverse parents and had extremely variable tocopherol content and composition. A genetic map was constructed using 208 polymorphic molecular markers including gene-targeted markers based on six candidate genes of the tocopherol biosynthesis pathway (HPPD, VTE1, VTE3, VTE4, P3VTE5, and P4VTE5). Thirty-one quantitative trait loci (QTL) associated with quantitative variation of tocopherol content and composition were identified by composite interval mapping (CIM); these were located on sixteen genomic regions covering all the chromosomes except chromosome 4. Most (65%) QTL were co-located, suggesting that in some cases the same QTL predominantly affected the amounts of more than one tocopherol. Two candidate genes, HPPD and VTE4 showed co-localization with major QTL for tocopherol content and composition whereas only one interval (umc1075–umc1304) on chromosome eight exhibited a QTL for α, δ, γ, and total tocopherols with high LOD and PVE values. The candidate genes associated with tocopherol content and with composition, especially VTE4 and HPPD, could be precisely used for alteration of the tocopherol content and composition of maize grains by development of functional markers. Other identified major QTL especially those on chromosomes 8, 1, and 2 (near candidate gene VTE5) can also be used for improvement of maize grain quality by marker-assisted selection.     

A general mixture model for mapping quantitative trait loci by using molecular markers

Summary In a segregating population a quantitative trait may be considered to follow a mixture of (normal) distributions, the mixing proportions being based on Mendelian segregation rules. A general and flexible mixture model is proposed for mapping quantitative trait loci (QTLs) by using molecular markers. A method is discribed to fit the model to data. The model makes it possible to (1) analyse non-normally distributed traits such as lifetimes, counts or percentages in addition to normally distributed traits, (2) reduce environmental variation by taking into account the effects of experimental design factors and interaction between genotype and environment, (3) reduce genotypic variation by taking into account the effects of two or more QTLs simultaneously, (4) carry out a (combined) analysis of different population types, (5) estimate recombination frequencies between markers or use known marker distances, (6) cope with missing marker observations, (7) use markers as covariables in detection and mapping of QTLs, and finally to (8) implement the mapping in standard statistical packages.     

A mixed model for the effects of single gene,polygenes and their interaction on quantitative traits

Summary A model for the effects of single gene (SG), polygenes (PG) and their interaction on quantitative traits was developed. It is a mixed model where the SG is a fixed effect and the PG is a random effect. A two-way factorial experiment, in which the SG and the PG are the main effects, is proposed. The experimental material is comprised of F₃ families derived from F₂ plants heterozygous for the SG. For this experiment an ANOVA table with expected mean square is proposed, which facilitates estimation of the components of the model and testing of their significance. A detailed method for the interpretation of results from such an experiment is proposed, with emphasis on the analysis of the SG × PG interaction. Theoretical and applied aspects of SG × PG interaction is discussed.This paper is part of a Ph.D. Thesis of the senior author to be submitted to the Hebrew University of Jerusalem     

Fine mapping of QTLs of chromosome 2 affecting the fruit architecture and composition of tomato

Negative correlations between quality traits and fruit size may hamper the breeding of fresh market tomato varieties for better organoleptic qualities. In a recent QTL analysis, QTLs with large effects on fruit weight, locule number and several quality traits were detected in the distal 50 cM of chromosome 2, but favorable alleles for fruit weight and locule number were unfavorable to quality traits. Substitution mapping was undertaken to determine whether the effects were due to a single QTL or to several tightly linked QTLs. Several chromosomal segments were characterized using near-isogenic lines. Five of them appeared to be involved in one or several traits. Considering the five segments from the top to the bottom of the region, the QTLs detected in each segment controlled the variation of: (1) fruit weight, (2) soluble solids content and dry matter weight, (3) fruit weight, (4) locule number and (5) fruit weight, dry matter weight, total sugars, titratable acidity and soluble solids content. This last cluster illustrates an antagonism between fruit weight and four quality traits, as favorable alleles are not conferred by the same parent in both cases. Nevertheless, several antagonistic QTLs were separated from each other in the first four segments, holding the promise for marker-assisted improvement of fruit quality traits without compromising the fruit size.     

Integration of genetic and genomic methods for identification of genes and gene variants encoding QTLs in the nonhuman primate

We have developed an integrated approach, using genetic and genomic methods, in conjunction with resources from the Southwest National Primate Research Center (SNPRC) baboon colony, for the identification of genes and their functional variants that encode quantitative trait loci (QTL). In addition, we use comparative genomic methods to overcome the paucity of baboon specific reagents and to augment translation of our findings in a nonhuman primate (NHP) to the human population. We are using the baboon as a model to study the genetics of cardiovascular disease (CVD). A key step for understanding gene–environment interactions in cardiovascular disease is the identification of genes and gene variants that influence CVD phenotypes. We have developed a sequential methodology that takes advantage of the SNPRC pedigreed baboon colony, the annotated human genome, and current genomic and bioinformatic tools. The process of functional polymorphism identification for genes encoding QTLs involves comparison of expression profiles for genes and predicted genes in the genomic region of the QTL for individuals discordant for the phenotypic trait mapping to the QTL. After comparison, genes of interest are prioritized, and functional polymorphisms are identified in candidate genes by genotyping and quantitative trait nucleotide analysis. This approach reduces the time and labor necessary to prioritize and identify genes and their polymorphisms influencing variation in a quantitative trait compared with traditional positional cloning methods.     

Advanced backcross QTL analysis: a method for the simultaneous discovery and transfer of valuable QTLs from unadapted germplasm into elite breeding lines

Advanced backcross QTL analysis is proposed as a method of combining QTL analysis with variety development. It is tailored for the discovery and transfer of valuable QTL alleles from unadapted donor lines (e.g., land races, wild species) into established elite inbred lines. Following this strategy, QTL analysis is delayed until the BC2 or BC3 generation and, during the development of these populations, negative selection is exercised to reduce the frequency of deleterious donor alleles. Simulations suggest that advanced backcross QTL analysis will be effective in detecting additive, dominant, partially dominant, or overdominant QTLs. Epistatic QTLs or QTLs with gene actions ranging from recessive to additive will be detected with less power than in selfing generations. QTL-NILs can be derived from advanced backcross populations in one or two additional generations and utilized to verify QTL activity. These same QTL-NILs also represent commercial inbreds improved (over the original recurrent inbred line) for one or more quantitative traits. The time lapse from QTL discovery to construction and testing of improved QTL-NILs is minimal (1–2 years). If successfully employed, advanced backcross QTL analysis can open the door to exploiting unadapted and exotic germplasm for the quantitative trait improvement of a number of crop plants.     

Analysis of the Relationships between Growth, Photosynthesis and Carbohydrate Metabolism Using Quantitative Trait Loci (QTLs) in Young Maize Plants Subjected to Water Deprivation

One hundred to 120 maize recombinant inbred lines at the mature fourth leaf stage derived from F-2 and Io parental lines were grown in a glasshouse and were deprived of water for 9 days in order to detect pertinent markers of the physiological response to water stress which may be used for breeding. Carbohydrate metabolism QTLs were compared to photosynthesis gas exchange QTLs. The locations of these QTLs were further compared with those of morphological trait QTLs when water availability varied. The traits ranged from three enzyme activities (invertase, sucrose-P synthase, ADP glucose pyrophosphorylase) and hexose, sucrose, starch content to CO₂ uptake and stomatal conductance, water status, leaf size, root/shoot ratio, and ABA (leaf, root and xylem sap). Four main results were obtained (1) only 14 % of QTLs were common to both drought and watered treatments, confirming the existence of stress specific chromosome regions, (2) the QTLs tended to form clusters, frequently consisting of QTLs from different classes (growth, photosynthesis, water status, carbohydrate metabolism and ABA), (3) carbohydrate metabolism trait QTLs were more frequently co-located with growth trait QTLs than photosynthesis related ones, especially in control conditions, (4) one co-location was observed between the three enzyme activities implied in sucrose and starch metabolism and a corresponding structural gene, which can be considered as a candidate gene for explaining part of the variability of each enzymatic trait (invertase, sucrose-P synthase, ADPglucose pyrophosphorylase). It is concluded that, carbohydrate metabolism provides valuable traits for understanding and improving maize responses to water stress.     

Hydrogen peroxide metabolism and sensing in human erythrocytes: A validated kinetic model and reappraisal of the role of peroxiredoxin II

Hydrogen peroxide (H₂O₂) metabolism in human erythrocytes has been thoroughly investigated, but unclear points persist. By integrating the available data into a mathematical model that accurately represents the current understanding and comparing computational predictions to observations we sought to (a) identify inconsistencies in present knowledge, (b) propose resolutions, and (c) examine their functional implications. The systematic confrontation of computational predictions with experimental observations of the responses of intact erythrocytes highlighted the following important discrepancy. The high rate constant (10⁷–10⁸ M⁻¹ s⁻¹) for H₂O₂ reduction determined for purified peroxiredoxin II (Prx2) and the high abundance of this protein indicate that under physiological conditions it consumes practically all the H₂O₂. However, this is inconsistent with extensive evidence that Prx2’s contribution to H₂O₂ elimination is comparable to that of catalase. Models modified such that Prx2’s effective peroxidase activity is just 10⁵ M⁻¹ s⁻¹ agree near quantitatively with extensive experimental observations. This low effective activity is probably due to a strong but readily reversible inhibition of Prx2’s peroxidatic activity in intact cells, implying that the main role of Prx2 in human erythrocytes is not to eliminate peroxide substrates. Simulations of the responses to physiological H₂O₂ stimuli highlight that a design combining abundant Prx2 with a low effective peroxidase activity spares NADPH while improving potential signaling properties of the Prx2/thioredoxin/thioredoxin reductase system.     

Tree-rings,genetics and the environment: Complex interactions at the rear edge of species distribution range

Under climate change, modifications on plants’ growth are expected to be the strongest at species margins. Therein, tree acclimation could play a key role as migration is predicted to be too slow to track shifts of bioclimatic envelops. A requirement is, however, that intra-population genetic diversity be high enough for allowing such adaptation of tree populations to climate change. In this study, we tested for the existence of relationships between genetic diversity, site environmental conditions, and the response of annual tree growth to climate of Pinus cembra at its southern limit in the Alps. Site-specific climatic and environmental factors predominantly determined the response of trees along the precipitation gradient. The growth-climate interactions were chiefly linked to mean annual precipitation and temperature, slope and tree-size, and less to genetic diversity. We show that genetic background of Pinus cembra has exclusively indirect modulating power with limited effects on tree-ring formation, and within the southern limit in the Alps, genetic variability is not necessarily well expressed in the patterns of annual tree growth. Our results may imply little adaptive capacity of these populations to future changes in the water balance.     

A physical model for the condensation and decondensation of eukaryotic chromosomes

During the eukaryotic cell cycle, chromatin undergoes several conformational changes, which are believed to play key roles in gene expression regulation during interphase, and in genome replication and division during mitosis. In this paper, we propose a scenario for chromatin structural reorganization during mitosis, which bridges all the different scales involved in chromatin architecture, from nucleosomes to chromatin loops. We build a model for chromatin, based on available data, taking into account both physical and topological constraints DNA has to deal with. Our results suggest that the mitotic chromosome condensation/decondensation process is induced by a structural change at the level of the nucleosome itself.     

Quantitative genetics of growth and development in Populus. I. A three-generation comparison of tree architecture during the first 2 years of growth

One approach to gain an insight into the genetics of tree architecture is to make use of morphologically divergent parents and study their segregating progeny in the F₂ and backcross (B₁) generations. This approach was chosen in the present study in which material of a three-generation pedigree growing side by side in a replicated plantation, was analyzed. The pedigree included Populus trichocarpa (T) and P. deltoides (D) parents, their F₁ and F₂ hybrids and their B₁ hybrids to the D parent. The trees were grown in the environment of the T parent and measured for the first 2 years of growth. Nine quantitative traits were studied at the stem, branch and leaf levels of tree architecture, in which the original parents differed. Strong F₁ hybrid vigor relative to the better parent (T) was expressed in growth and its components. Most quantitative traits in the F₂ and B₁ hybrids were intermediate between the T and D parents but displayed a wide range of variation due to segregation. The results from the analysis of variance indicated that all morphometric traits were significantly different among F₂ and B₁ clones, but the B₁ hybrids were more sensitive to replicates than the F₂. Broad-sense heritabilities (H ²) based on clonal means ranged from moderately high to high (0.50–0.90) for the traits studied, with H ² values varying over age. The H ² estimates reflected greater environmental noise in the B₁ than in the F₂, presumably due to the greater proportion of maladaptive D alleles in those hybrids. In both families, sylleptic branch number and length, and leaf size on the terminal, showed strong genetic correlations with stem growth. The large divergence between the two original parents in the traits studied, combined with the high chromosome number in Populus (2n=38), makes this pedigree well suited for the estimation of the number of quantitative trait loci (QTLs) underlying quantitative variation by Wright's biometric method (1968). Variation in several traits was found to be under the control of surprisingly few major QTLs: 3–4 in 2nd-year height and diameter growth, a single QTL in stem diameter/height ratio.     

Quantitative genetics and functional-structural plant growth models: simulation of quantitative trait loci detection for model parameters and application to potential yield optimization

BACKGROUND AND AIMS: Prediction of phenotypic traits from new genotypes under untested environmental conditions is crucial to build simulations of breeding strategies to improve target traits. Although the plant response to environmental stresses is characterized by both architectural and functional plasticity, recent attempts to integrate biological knowledge into genetics models have mainly concerned specific physiological processes or crop models without architecture, and thus may prove limited when studying genotype x environment interactions. Consequently, this paper presents a simulation study introducing genetics into a functional-structural growth model, which gives access to more fundamental traits for quantitative trait loci (QTL) detection and thus to promising tools for yield optimization. METHODS: The GREENLAB model was selected as a reasonable choice to link growth model parameters to QTL. Virtual genes and virtual chromosomes were defined to build a simple genetic model that drove the settings of the species-specific parameters of the model. The QTL Cartographer software was used to study QTL detection of simulated plant traits. A genetic algorithm was implemented to define the ideotype for yield maximization based on the model parameters and the associated allelic combination. KEY RESULTS AND CONCLUSIONS: By keeping the environmental factors constant and using a virtual population with a large number of individuals generated by a Mendelian genetic model, results for an ideal case could be simulated. Virtual QTL detection was compared in the case of phenotypic traits--such as cob weight--and when traits were model parameters, and was found to be more accurate in the latter case. The practical interest of this approach is illustrated by calculating the parameters (and the corresponding genotype) associated with yield optimization of a GREENLAB maize model. The paper discusses the potentials of GREENLAB to represent environment x genotype interactions, in particular through its main state variable, the ratio of biomass supply over demand.     

Toward the mapping of physiological and agronomic characters on a rice function map: QTL analysis and comparison between QTLs and expressed sequence tags

We have constructed a rice function map by collating the results on quantitative trait loci (QTLs) for 23 important physiological and agronomic characters (including 13 newly measured traits) obtained using backcross inbred lines of japonica Nipponbare×indica Kasalath. Using these materials, The Rice Genome project (RGP) has developed a high-density genetic map. QTLs controlling yield did not overlap with those controlling the morphological and physiological traits supposed to relate to yield, such as photosynthetic ability. This result suggests that these traits do not influence yield, at least in this genetic background and environment. QTLs controlling yield also did not overlap with the structural genes controlling carbon metabolism (rbcS, cytosolic or plastidic fructose-1,6-bisphosphate, R-enzyme, and sucrose synthase).The combination of a function map and results from the RGP can be advantageous. The utility of this map is discussed. Received: 1 October 1999 / Accepted: 28 July 2000     

Merging methods in molecular and ecological genetics to study the adaptation of plants to anthropogenic metal-polluted sites: implications for phytoremediation

Metallophyte species that occur naturally on metal-enriched soils represent major biological resources for the improvement of phytoremediation, a benign and cost-effective technology that uses plants to clean up anthropogenic metal-polluted soils. Within the last decade, molecular genetic studies carried out on several model organisms (including Arabidopsis halleri) have considerably enhanced our understanding of metal tolerance and hyperaccumulation in plants, but the identification of the genes of interest for phytoremediation purposes remains a challenge. To meet this challenge, we propose to combine '-omics' with molecular ecology methods. Using A. halleri, we confronted molecular genetic results with: (i) within-species polymorphism and large-scale population differentiation for zinc tolerance; (ii) the demographical context (e.g. migration pattern) of the species for zinc tolerance evolution; (iii) the Quantitative Trait Loci (QTL) analysis of the genetic architecture for zinc tolerance; and (iv) the fine-scale dissection of identified QTL regions, to discuss more precisely the nature of the genes potentially involved in the adaptation to zinc-polluted soils.