P. Stam

RECORD: a novel method for ordering loci on a genetic linkage map

A new method, REcombination Counting and ORDering (RECORD) is presented for the ordering of loci on genetic linkage maps. The method minimizes the total number of recombination events. The search algorithm is a heuristic procedure, combining elements of branch-and-bound with local reshuffling. Since the criterion we propose does not require intensive calculations, the algorithm rapidly produces an optimal ordering as well as a series of near-optimal ones. The latter provides insight into the local certainty of ordering along the map. A simulation study was performed to compare the performance of RECORD and JoinMap. RECORD is much faster and less sensitive to missing observations and scoring errors, since the optimisation criterion is less dependent on the position of the erroneous markers. In particular, RECORD performs better in regions of the map with high marker density. The implications of high marker densities on linkage map construction are discussed.

Use of locus-specific AFLP markers to construct a high-density molecular map in barley.

By using 25 primer combinations, 563 AFLP markers segregating in a recombinant inbred population (103 lines, F9) derived from L94/Vada were generated. The 38 AFLP markers in common to the existing AFLP/RFLP combined Proctor/Nudinka map, one STS marker, and four phenotypic markers with known map positions, were used to assign present AFLP linkage groups to barley chromosomes. The constructed high-density molecular map contains 561 AFLP markers, three morphological markers, one disease resistance gene and one STS marker, and covers a 1062-cM genetic distance, corresponding to an average of one marker per 1.9 cM. However, extremely uneven distributions of AFLP markers and strong clustering of markers around the centromere were identified in the present AFLP map. Around the centromeric region, 289 markers cover a genetic distance of 155 cM, corresponding to one marker per 0.5 cM; on the distal parts, 906 cM were covered by 277 markers, corresponding to one marker per 3.3 cM. Three gaps larger than 20 cM still exist on chromosomes 1, 3 and 5. A skeletal map with a uniform distribution of markers can be extracted from the high-density map, and can be applied to detect and map loci underlying quantitative traits. However, the application of this map is restricted to barley species since hardly any marker in common to a closely related Triticum species could be identified.

Association between relationship measures based on AFLP markers, pedigree data and morphological traits in barley

Abstract Thirty one barley lines were used to investigate the agreement between three relationship measures: genetic similarities based on 681 AFLP-markers, coefficients of co-ancestry based on pedigree data, and generalised distance based on 25 morpological characters (morphological distance). Bootstrap analysis was used to estimate the accuracy of the correlation estimates. AFLP-based genetic similarities showed a poor-to-moderate correlation with the coefficients of co-ancestry within the core set of 25 European two-row spring barleys. Morphological distance was not significantly correlated with either genetic similarity or the coefficient of co-ancestry. The precision of all correlation-coefficient estimates, however, was low. The inclusion of two European winter barleys, two North American two-row spring barleys, and two North American six-row spring barleys in the AFLP-analysis resulted in a much stronger correlation between genetic similarity and the coefficient of co-ancestry. This suggests good opportunities for the use of AFLP-markers to assess genetic diversity by distinguishing between the major ecotypes of barley. Additionally, each of the eight primer combinations used in the AFLP-analysis was able to identify all 31 lines uniquely, showing the usefulness of AFLPs for cultivar identification. Because of the inaccuracy of the investigated relationship measures, resulting in low values of the correlation-coefficient estimates, prediction of the breeding behaviour of parent combinations may be improved by the use of a combination of relationship measures, thus decreasing the effect of their individual independent errors.

Identification of QTLs for partial resistance to leaf rust (Puccinia hordei) in barley.

Abstract The partial resistance to leaf rust in barley is a quantitative resistance that is not based on hypersensitivity. To map the quantitative trait loci (QTLs) for partial resistance to leaf rust, we obtained 103 recombinant inbred lines (RILs) by single-seed descent from a cross between the susceptible parent L94 and the partially resistant parent Vada. These RILs were evaluated at the seedling and adult plant stages in the greenhouse for the latent period (LP) of the rust fungus, and in the field for the level of infection, measured as area under the disease progress curve (AUDPC). A dense genetic map based on 561 AFLP markers had been generated previously for this set of RILs. QTLs for partial resistance to leaf rust were mapped using the “Multiple Interval Mapping” method with the putative QTL markers as cofactors. Six QTLs for partial resistance were identified in this population. Three QTLs, Rphq1, Rphq2 and Rphq3, were effective at the seedling stage and contributed approximately 55% to the phenotypic variance. Five QTLs, Rph2, Rphq3, Rphq4, Rphq5, and/or Rphq6 contributed approximtely. 60% of the phenotypic variance and were effective at the adult plant stage. Therefore, only the QTLs Rphq2 and Rhpq3 were not plant-stage dependent. The identified QTLs showed mainly additive effects and only one significant interaction was detected, i.e. between Rphq1 and Rphq2. The map positions of these QTLs did not coincide with those of the race-specific resistance genes, suggesting that genes for partial resistance and genes for hypersensitive resistance represent entirely different gene families. Also, three QTLs for days to heading, of which two were also involved in plant height, were identified in the present recombinant inbred population. These QTLs had been mapped previously on the same positions in different populations. The perspectives of these results for breeding for durable resistance to leaf rust are discussed.

Isolate-specific QTLs for partial resistance to Puccinia hordei in barley

Abstract By using a high-density AFLP marker linkage map, six QTLs for partial resistance to barley leaf rust (Puccinia hordei) isolate 1.2.1. have been identified in the RIL offspring of a cross between the partially resistant cultivar ’Vada’ and the susceptible line L94. Three QTLs were effective at the seedling stage, and five QTLs were effective at the adult plant stage. To study possible isolate specificity of the resistance, seedlings and adult plants of the 103 RILs from the cross L94×’Vada’ were also inoculated with another leaf rust isolate, isolate 24. In addition to the two QTLs that were effective against isolate 1.2.1. at the seedling stage, an additional QTL for seedling resistance to isolate 24 was identified on the long arm of chromosome 7. Of the eight detected QTLs effective at the adult plant stage, three were effective in both isolates and five were effective in only one of the two isolates. Only one QTL had a substantial effect at both the seedling and the adult plant stages. The expression of the other QTLs was developmental-stage specific. The isolate specificity of the QTLs supports the hypothesis of Parlevliet and Zadoks (1977) that partial resistance may be based on a minor-gene-for-minor-gene interaction.

AFLP mapping of quantitative trait loci for yield-determining physiological characters in spring barley

Abstract An amplified fragment length polymorphism (AFLP) map covering 965 cM was constructed using 94 recombinant inbred lines of a cross between the spring barley varieties Prisma and Apex. This map was employed to identify quantitative trait loci (QTLs) controlling plant height, yield and yield-determining physiological characters using an approximate multiple-QTL model, the MQM method. The seven physiological traits were parameters used in a process-based crop-growth model that predicts barley biomass production as affected by daily temperature and radiation. The traits were measured in experiments conducted over 2 years. Except for the relative growth rate of leaf area, all traits examined had at least one QTL in each year. QTLs and their effects were found to vary with developmental stages for one trait, the fraction of shoot biomass partitioned to leaves, that was measured at several stages. Most of the traits were associated, though to different extents, with the denso dwarfing gene (the height-reducing allele in Prisma) located on the long arm of chromosome 3. Some of the QTLs were mapped to similar positions in both years. The results in relation to effects of the dwarfing gene, the physiological basis for QTL×environment interaction, and the relative importance of the parameter traits with respect to yield, are discussed.

Statistical models for genotype by environment data: from conventional ANOVA models to eco-physiological QTL models

To study the performance of genotypes under different growing conditions, plant breeders evaluate their germplasm in multi-environment trials. These trials produce genotype × environment data. We present statistical models for the analysis of such data that differ in the extent to which additional genetic, physiological, and environmental information is incorporated into the model formulation. The simplest model in our exposition is the additive 2-way analysis of variance model, without genotype × environment interaction, and with parameters whose interpretation depends strongly on the set of included genotypes and environments. The most complicated model is a synthesis of a multiple quantitative trait locus (QTL) model and an eco-physiological model to describe a collection of genotypic response curves. Between those extremes, we discuss linear-bilinear models, whose parameters can only indirectly be related to genetic and physiological information, and factorial regression models that allow direct incorporation of explicit genetic, physiological, and environmental covariables on the levels of the genotypic and environmental factors. Factorial regression models are also very suitable for the modelling of QTL main effects and QTL × environment interaction. Our conclusion is that statistical and physiological models can be fruitfully combined for the study of genotype × environment interaction.

SMOOTH: a statistical method for successful removal of genotyping errors from high-density genetic linkage data

High-density genetic linkage maps can be used for purposes such as fine-scale targeted gene cloning and anchoring of physical maps. However, their construction is significantly complicated by even relatively small amounts of scoring errors. Currently available software is not able to solve the ordering ambiguities in marker clusters, which inhibits the application of high-density maps. A statistical method named SMOOTH was developed to remove genotyping errors from genetic linkage data during the mapping process. The program SMOOTH calculates the difference between the observed and predicted values of data points based on data points of neighbouring loci in a given marker order. Highly improbable data points are removed by the program in an iterative process with a mapping algorithm that recalculates the map after cleaning. SMOOTH has been tested with simulated data and experimental mapping data from potato. The simulations prove that this method is able to detect a high amount of scoring errors and demonstrates that the program enables mapping software to successfully construct a very accurate high-density map. In potato the application of the program resulted in a reliable placement of nearly 1,000 markers in one linkage group.

The role of ecophysiological models in QTL analysis: the example of specific leaf area in barley

Crop modelling has so far contributed little to the genetic analysis of a quantitative trait. This study illustrates how a simple model for crop phenological development, which assumes that crop development rate is affected by daily effective temperature, can assist the identification of Quantitative Trait Loci (QTLs), using specific leaf area (SLA) in barley as an example. The SLA was measured in a field experiment six times during the growing season of 94 recombinant inbred lines (RILs) derived from a cross between cultivars Prisma and Apex. Of the six measurements, one was conducted at the same physiological age for all RILs (at flowering), four were undertaken at specific chronological days prior to flowering, and the last one was taken at 14 days after flowering. When the measured SLA was directly used as the quantitative trait, one to three QTLs were detected for SLA at each measurement time. The major dwarfing gene denso segregating in the population was found to affect SLA strongly at all measurement times except at flowering. If SLA of the different RILs was corrected for differences in physiological age at the time of measurement, by the use of the crop development model, QTLs were detected for SLA at only three stages. Furthermore, the effect of the denso gene was no longer significant during the preflowering stages. The effect of the denso gene detected in the first instance was therefore the consequence of its direct effect on the duration of the preflowering period. This demonstrates the important role that crop development models can play in QTL analysis of a trait that varies with developmental stage. Potential uses of ecophysiological crop growth models in QTL analysis are briefly discussed.

The evidence for abundance of QTLs for partial resistance to Puccinia hordei on the barley genome

Using AFLP markers, a linkage map was constructed based on a recombinant inbred population of barley derived from a cross between a leaf rust susceptible line, L94, and a partially resistant line, 116-5. The constructed map showed a similar marker distribution pattern as the L94 × Vada map. However, it contained more large gaps, and for some chromosome regions no markers were identified. These regions are most likely derived from L94 because 116-5 was selected from the progeny of a cross of L94 × cv. Cebada Capa. Five QTLs for partial resistance to isolate 1.2.1. were mapped on the L94 × 116-5 map. Three QTLs were effective in the seedling stage, jointly contributing 42% to the total phenotypic variance. Three QTLs were effective in the adult plant stage, collectively explaining 35% of the phenotypic variance. Evidence for two additional linked minor-effect QTLs effective in the adult plant stage was also uncovered. The major-effect QTL, Rphq3, was the only one that was effective in both developmental stages. Moreover, Rphq3, was also identified in the L94 × Vada population, being effective to two rust isolates. The other QTLs were detected in either of the two populations, providing evidence for the existence of many loci for partial resistance to leaf rust on the barley genome. To date, 13 QTLs for partial resistance have been mapped, therefore, a strategy of accumulating many resistance genes in a single cultivar, resulting in a high level of partial resistance, is feasible.