Advanced backcross-QTL analysis in spring barley (H. vulgare ssp. spontaneum) comparing a REML versus a Bayesian model in multi-environmental field trials

A common difficulty in mapping quantitative trait loci (QTLs) is that QTL effects may show environment specificity and thus differ across environments. Furthermore, quantitative traits are likely to be influenced by multiple QTLs or genes having different effect sizes. There is currently a need for efficient mapping strategies to account for both multiple QTLs and marker-by-environment interactions. Thus, the objective of our study was to develop a Bayesian multi-locus multi-environmental method of QTL analysis. This strategy is compared to (1) Bayesian multi-locus mapping, where each environment is analysed separately, (2) Restricted Maximum Likelihood (REML) single-locus method using a mixed hierarchical model, and (3) REML forward selection applying a mixed hierarchical model. For this study, we used data on multi-environmental field trials of 301 BC2DH lines derived from a cross between the spring barley elite cultivar Scarlett and the wild donor ISR42-8 from Israel. The lines were genotyped by 98 SSR markers and measured for the agronomic traits “ears per m²,” “days until heading,” “plant height,” “thousand grain weight,” and “grain yield”. Additionally, a simulation study was performed to verify the QTL results obtained in the spring barley population. In general, the results of Bayesian QTL mapping are in accordance with REML methods. In this study, Bayesian multi-locus multi-environmental analysis is a valuable method that is particularly suitable if lines are cultivated in multi-environmental field trials

Optimum allocation of resources for QTL detection using a nested association mapping strategy in maize

In quantitative trait locus (QTL) mapping studies, it is mandatory that the available financial resources are spent in such a way that the power for detection of QTL is maximized. The objective of this study was to optimize for three different fixed budgets the power of QTL detection 1 − β* in recombinant inbred line (RIL) populations derived from a nested design by varying (1) the genetic complexity of the trait, (2) the costs for developing, genotyping, and phenotyping RILs, (3) the total number of RILs, and (4) the number of environments and replications per environment used for phenotyping. Our computer simulations were based on empirical data of 653 single nucleotide polymorphism markers of 26 diverse maize inbred lines which were selected on the basis of 100 simple sequence repeat markers out of a worldwide sample of 260 maize inbreds to capture the maximum genetic diversity. For the standard scenario of costs, the optimum number of test environments (Eopt) ranged across the examined total budgets from 7 to 19 in the scenarios with 25 QTL. In comparison, the Eopt values observed for the scenarios with 50 and 100 QTL were slightly higher. Our finding of differences in 1 − β* estimates between experiments with optimally and sub-optimally allocated resources illustrated the potential to improve the power for QTL detection without increasing the total resources necessary for a QTL mapping experiment. Furthermore, the results of our study indicated that also in studies using the latest genomics tools to dissect quantitative traits, it is required to evaluate the individuals of the mapping population in a high number of environments with a high number of replications per environment

Efficient QTL detection for nonhost resistance in wild lettuce: backcross inbred lines versus F2 population

In plants, several population types [F2, recombinant inbred lines, backcross inbred lines (BILs), etc.] are used for quantitative trait locus (QTL) analyses. However, dissection of the trait of interest and subsequent confirmation by introgression of QTLs for breeding purposes has not been as successful as that predicted from theoretical calculations. More practical knowledge of different QTL mapping approaches is needed. In this recent study, we describe the detection and mapping of quantitative resistances to downy mildew in a set of 29 BILs of cultivated lettuce (L. sativa) containing genome segments introgressed from wild lettuce (L. saligna). Introgression regions that are associated with quantitative resistance are considered to harbor a QTL. Furthermore, we compare this with results from an already existing F2 population derived from the same parents. We identified six QTLs in our BIL approach compared to only three in the F2 approach, while there were two QTLs in common. We performed a simulation study based on our actual data to help us interpret them. This revealed that two newly detected QTLs in the BILs had gone unnoticed in the F2, due to a combination of recessiveness of the trait and skewed segregation, causing a deficit of the wild species alleles. This study clearly illustrates the added value of extended genetic studies on two different population types (BILs and F2) to dissect complex genetic traits

Extent and structure of linkage disequilibrium in canola quality winter rapeseed (Brassica napus L.)

Linkage disequilibrium was investigated in canola quality winter rapeseed to analyze (1) the prospects for whole-genome association analyses and (2) the impact of the recent breeding history of rapeseed on linkage disequilibrium. A total of 845 mapped AFLP markers with allele frequencies ≥0.1 were used for the analysis of linkage disequilibrium in a population of 85 canola quality winter rapeseed genotypes. A low overall level of linkage disequilibrium was found with a mean r2 of only 0.027 over all 356,590 possible marker pairs. At a significance threshold of P = 2.8 × 10−7, which was derived by a Bonferroni correction from a global α-level of 0.1, only 0.78% of the marker pairs were in significant linkage disequilibrium. Among physically linked marker pairs, the level of linkage disequilibrium was about five times higher with more than 10% of marker pairs in significant linkage disequilibrium. Linkage disequilibrium decayed rapidly with distance between linked markers with high levels of linkage disequilibrium extending only for about 2 cM. Owing to the rapid decay of linkage disequilibrium with distance association analyses in canola quality rapeseed will have a significantly higher resolution than QTL analyses in segregating populations by interval mapping, but much larger number of markers will be necessary to cover the whole genome. A major impact of the recent breeding history of rapeseed on linkage disequilibrium could not be observed

Statistical epistasis between candidate gene alleles for complex tuber traits in an association mapping population of tetraploid potato

Association mapping using DNA-based markers is a novel tool in plant genetics for the analysis of complex traits. Potato tuber yield, starch content, starch yield and chip color are complex traits of agronomic relevance, for which carbohydrate metabolism plays an important role. At the functional level, the genes and biochemical pathways involved in carbohydrate metabolism are among the best studied in plants. Quantitative traits such as tuber starch and sugar content are therefore models for association genetics in potato based on candidate genes. In an association mapping experiment conducted with a population of 243 tetraploid potato varieties and breeding clones, we previously identified associations between individual candidate gene alleles and tuber starch content, starch yield and chip quality. In the present paper, we tested 190 DNA markers at 36 loci scored in the same association mapping population for pairwise statistical epistatic interactions. Fifty marker pairs were associated mainly with tuber starch content and/or starch yield, at a cut-off value of q ≤ 0.20 for the experiment-wide false discovery rate (FDR). Thirteen marker pairs had an FDR of q ≤ 0.10. Alleles at loci encoding ribulose-bisphosphate carboxylase/oxygenase activase (Rca), sucrose phosphate synthase (Sps) and vacuolar invertase (Pain1) were most frequently involved in statistical epistatic interactions. The largest effect on tuber starch content and starch yield was observed for the paired alleles Pain1-8c and Rca-1a, explaining 9 and 10% of the total variance, respectively. The combination of these two alleles increased the means of tuber starch content and starch yield. Biological models to explain the observed statistical epistatic interactions are discussed

Diversity and linkage disequilibrium analysis within a selected set of cultivated tomatoes

Within the Dutch genomics initiative the “Centre for Biosystems Genomics” (CBSG) a major research effort is directed at the identification and unraveling of processes and mechanisms affecting fruit quality in tomato. The basis of this fruit quality program was a diverse set of 94 cultivated tomato cultivars, representing a wide spectrum of phenotypes for quality related traits. This paper describes a diversity study performed on these cultivars, using information of 882 AFLP markers, of which 304 markers had a known map position. The AFLP markers were scored as much as possible in a co-dominant fashion. We investigated genome distribution and coverage for the mapped markers and conclude that it proved difficult to arrive at a dense and uniformly distributed coverage of the genome with markers. Mapped markers and unmapped markers were used to investigate population structure. A clear substructure was observed which seemed to coincide with a grouping based on fruit size. Finally, we studied amount and decay of linkage disequilibrium (LD) along the chromosomes. LD was observed over considerable (genetic) distances. We discuss the feasibility of marker-trait association studies and conclude that the amount of genetic variation in our set of cultivars is limited, but that there exists scope for association studies

Association mapping for yield and grain quality traits in rice (Oryza sativa L.)

Association analysis was applied to a panel of accessions of Embrapa Rice Core Collection (ERiCC) with 86 SSR and field data from two experiments. A clear subdivision between lowland and upland accessions was apparent, thereby indicating the presence of population structure. Thirty-two accessions with admixed ancestry were identified through structure analysis, these being discarded from association analysis, thus leaving 210 accessions subdivided into two panels. The association of yield and grain-quality traits with SSR was undertaken with a mixed linear model, with markers and subpopulation as fixed factors, and kinship matrix as a random factor. Eight markers from the two appraised panels showed significant association with four different traits, although only one (RM190) maintained the marker-trait association across years and cultivation. The significant association detected between amylose content and RM190 was in agreement with previous QTL analyses in the literature. Herein, the feasibility of undertaking association analysis in conjunction with germplasm characterization was demonstrated, even when considering low marker density. The high linkage disequilibrium expected in rice lines and cultivars facilitates the detection of marker-trait associations for implementing marker assisted selection, and the mining of alleles related to important traits in germplasm

Genetic Diversity and Linkage Disequilibrium in Chinese Bread Wheat (Triticum aestivum L.) Revealed by SSR Markers

Two hundred and fifty bread wheat lines, mainly Chinese mini core accessions, were assayed for polymorphism and linkage disequilibrium (LD) based on 512 whole-genome microsatellite loci representing a mean marker density of 5.1 cM. A total of 6,724 alleles ranging from 1 to 49 per locus were identified in all collections. The mean PIC value was 0.650, ranging from 0 to 0.965. Population structure and principal coordinate analysis revealed that landraces and modern varieties were two relatively independent genetic sub-groups. Landraces had a higher allelic diversity than modern varieties with respect to both genomes and chromosomes in terms of total number of alleles and allelic richness. 3,833 (57.0%) and 2,788 (41.5%) rare alleles with frequencies of <5% were found in the landrace and modern variety gene pools, respectively, indicating greater numbers of rare variants, or likely new alleles, in landraces. Analysis of molecular variance (AMOVA) showed that A genome had the largest genetic differentiation and D genome the lowest. In contrast to genetic diversity, modern varieties displayed a wider average LD decay across the whole genome for locus pairs with r2>0.05 (P<0.001) than the landraces. Mean LD decay distance for the landraces at the whole genome level was <5 cM, while a higher LD decay distance of 5–10 cM in modern varieties. LD decay distances were also somewhat different for each of the 21 chromosomes, being higher for most of the chromosomes in modern varieties (<5∼25 cM) compared to landraces (<5∼15 cM), presumably indicating the influences of domestication and breeding. This study facilitates predicting the marker density required to effectively associate genotypes with traits in Chinese wheat genetic resources

Genome-wide SNPs and re-sequencing of growth habit and inflorescence genes in barley: implications for association mapping in germplasm arrays varying in size and structure

<p>Abstract</p> <p>Background</p> <p>Considerations in applying association mapping (AM) to plant breeding are population structure and size: not accounting for structure and/or using small populations can lead to elevated false-positive rates. The principal determinants of population structure in cultivated barley are growth habit and inflorescence type. Both are under complex genetic control: growth habit is controlled by the epistatic interactions of several genes. For inflorescence type, multiple loss-of-function alleles in one gene lead to the same phenotype. We used these two traits as models for assessing the effectiveness of AM. This research was initiated using the CAP Core germplasm array (n = 102) assembled at the start of the Barley Coordinated Agricultural Project (CAP). This array was genotyped with 4,608 SNPs and we re-sequenced genes involved in morphology, growth and development. Larger arrays of breeding germplasm were subsequently genotyped and phenotyped under the auspices of the CAP project. This provided sets of 247 accessions phenotyped for growth habit and 2,473 accessions phenotyped for inflorescence type. Each of the larger populations was genotyped with 3,072 SNPs derived from the original set of 4,608.</p> <p>Results</p> <p>Significant associations with SNPs located in the vicinity of the loci involved in growth habit and inflorescence type were found in the CAP Core. Differentiation of true and spurious associations was not possible without <it>a priori </it>knowledge of the candidate genes, based on re-sequencing. The re-sequencing data were used to define allele types of the determinant genes based on functional polymorphisms. In a second round of association mapping, these synthetic markers based on allele types gave the most significant associations. When the synthetic markers were used as anchor points for analysis of interactions, we detected other known-function genes and candidate loci involved in the control of growth habit and inflorescence type. We then conducted association analyses - with SNP data only - in the larger germplasm arrays. For both vernalization sensitivity and inflorescence type, the most significant associations in the larger data sets were found with SNPs coincident with the synthetic markers used in the CAP Core and with SNPs detected via interaction analysis in the CAP Core.</p> <p>Conclusions</p> <p>Small and highly structured collections of germplasm, such as the CAP Core, are cost-effectively phenotyped and genotyped with high-throughput markers. They are also useful for characterizing allelic diversity at loci in germplasm of interest. Our results suggest that discovery-oriented exercises in AM in such small arrays may generate a large number of false-positives. However, if haplotypes in candidate genes are available, they may be used as anchors in an analysis of interactions to identify other candidate regions harboring genes determining target traits. Using larger germplasm arrays, genome regions where the principal genes determining vernalization sensitivity and row type are located were identified.</p