Using alpha wisely: improving power to detect multiple QTL

Mapping and QTL Analysis of Early-Maturity Traits in Tetraploid Potato (Solanum tuberosum L.)

Early maturity is one of the most important agronomical traits in potato breeding. To identify the DNA segment that codes for early maturity, a tetraploid potato segregation population of “Zhongshu 19” × “Zhongshu 3” was genetically analyzed, using a combination of high throughput simplified genome sequencing (2b-RAD) and bulked segregant analysis (BSA). The DNA segment related to the early-maturity trait was identified at the 3.7~4.2 Mb locus on the short arm of chromosome 5. Eight molecular markers were developed, of which five were closely linked to the early-maturity trait loci. Additionally, 42 simple sequence repeats (SSR) markers were constructed based on the reference sequence of Solanum tuberosum group Phureja DM1-3 516 R44 (DM). Using the TetraploidMap software, the linkage map of chromosome 5 was constructed with 50 markers. The total map length was 172 centiMorgan (cM), with an average genetic distance of 3.44 cM. Correlating molecular and phenotypic data of the segregating population, the mapped Quantitative Trait Loci (QTL) on the short arm of chromosome 5 contributed to 33.55% of the early-maturity phenotype. The early-maturity QTL was located at 84 cM, flanked by the SSR5-85-1 and SCAR5-8 markers. The QTL was fine-mapped to 471 kb. Using DNA sequence annotation, 34 genes were identified in this region, 12 of them with unknown function. Among the other 22 annotated genes, E3 ubiquitin ligase gene PUB14 could be related to maturity and regulation of tuber formation. The constructed QTL map is a useful basic tool for the cloning of early-maturity related genes in tetraploid potatoes.

Location-Dependent Empirical Thresholds for Quantitative Trait Mapping

The Churchill-Doerge approach toward constructing empirical thresholds has received widespread use in the genetic mapping literature through the past 16 years. The method is valued for both its simplicity and its ability to preserve the genome-wide error rate at a prespecified level. However, the Churchill-Doerge method is not designed to maintain the local (comparison-wise) error rate at a constant level except in situations that are unlikely to occur in practice. In this article, we introduce the objective of preserving the local error rate at a constant level in the context of mapping quantitative trait loci in linkage populations. We derive a method that preserves the local error rate at a constant level, provide an application via simulation on a Hordeum vulgare population, and demonstrate evidence of the relationship between recombination and location bias. Furthermore, we indicate that this method is equivalent to the Churchill-Doerge method when several assumptions are satisfied.

Linkage analysis in the next-generation sequencing era

Linkage analysis was developed to detect excess co-segregation of the putative alleles underlying a phenotype with the alleles at a marker locus in family data. Many different variations of this analysis and corresponding study design have been developed to detect this co-segregation. Linkage studies have been shown to have high power to detect loci that have alleles (or variants) with a large effect size, i.e. alleles that make large contributions to the risk of a disease or to the variation of a quantitative trait. However, alleles with a large effect size tend to be rare in the population. In contrast, association studies are designed to have high power to detect common alleles which tend to have a small effect size for most diseases or traits. Although genome-wide association studies have been successful in detecting many new loci with common alleles of small effect for many complex traits, these common variants often do not explain a large proportion of disease risk or variation of the trait. In the past, linkage studies were successful in detecting regions of the genome that were likely to harbor rare variants with large effect for many simple Mendelian diseases and for many complex traits. However, identifying the actual sequence variant(s) responsible for these linkage signals was challenging because of difficulties in sequencing the large regions implicated by each linkage peak. Current 'next-generation' DNA sequencing techniques have made it economically feasible to sequence all exons or the whole genomes of a reasonably large number of individuals. Studies have shown that rare variants are quite common in the general population, and it is now possible to combine these new DNA sequencing methods with linkage studies to identify rare causal variants with a large effect size. A brief review of linkage methods is presented here with examples of their relevance and usefulness for the interpretation of whole-exome and whole-genome sequence data.

Mapping multiple quantitative trait loci under Bayes error control

In mapping of quantitative trait loci (QTLs), performing hypothesis tests of linkage to a phenotype of interest across an entire genome involves multiple comparisons. Furthermore, linkage among loci induces correlation among tests. Under many multiple comparison frameworks, these problems are exacerbated when mapping multiple QTLs. Traditionally, significance thresholds have been subjectively set to control the probability of detecting at least one false positive outcome, although such thresholds are known to result in excessively low power to detect true positive outcomes. Recently, false discovery rate (FDR)-controlling procedures have been developed that yield more power both by relaxing the stringency of the significance threshold and by retaining more power for a given significance threshold. However, these procedures have been shown to perform poorly for mapping QTLs, principally because they ignore recombination fractions between markers. Here, I describe a procedure that accounts for recombination fractions and extends FDR control to include simultaneous control of the false non-discovery rate, i.e. the overall error rate is controlled. This procedure is developed in the Bayesian framework using a direct posterior probability approach. Data-driven significance thresholds are determined by minimizing the expected loss. The procedure is equivalent to jointly maximizing positive and negative predictive values. In the context of mapping QTLs for experimental crosses, the procedure is applicable to mapping main effects, gene-gene interactions and gene-environment interactions.

New candidate genes for sex-comb divergence between Drosophila mauritiana and Drosophila simulans

A large-effect QTL for divergence in sex-comb tooth number between Drosophila simulans and D. mauritiana was previously mapped to 73A-84AB. Here we identify genes that are likely contributors to this divergence. We first improved the mapping resolution in the 73A-84AB region using 12 introgression lines and 62 recombinant nearly isogenic lines. To further narrow the list of candidate genes, we assayed leg-specific expression and identified genes with transcript-level evolution consistent with a potential role in sex-comb divergence. Sex combs are formed on the prothoracic (front) legs, but not on the mesothoracic (middle) legs of Drosophila males. We extracted RNA from the prothoracic and mesothoracic pupal legs of two species to determine which of the genes expressed differently between leg types were also divergent for gene expression. Two good functional candidate genes, Scr and dsx, are located in one of our fine-scale QTL regions. In addition, three previously uncharacterized genes (CG15186, CG2016, and CG2791) emerged as new candidates. These genes are located in regions strongly associated with sex-comb tooth number differences and are expressed differently between leg tissues and between species. Further supporting the potential involvement of these genes in sex-comb divergence, we found a significant difference in sex-comb tooth number between co-isogenic D. melanogaster lines with and without P-element insertions at CG2791.

Mapping gene H controlling cane pubescence in raspberry and its association with resistance to cane botrytis and spur blight, rust and cane spot

Disease resistance is increasing in importance, as consumers require high-quality raspberry fruit at a time when chemical disease control is undesirable. Breeders have limited resources and rarely include a primary screen for each fungal disease. Marker-assisted breeding would facilitate the introduction of resistance into elite germplasm and breeding lines. An additional 20 simple sequence repeats have been added to the existing raspberry linkage map. Gene H, which determines cane pubescence (genotype HH or Hh), the recessive allele of which gives glabrous canes (genotype hh), has been mapped on to linkage group 2 and shown to be closely associated with resistance to cane botrytis and spur blight but not rust or cane spot. Other map regions on linkage groups 3, 5 and 6 associated with disease resistance are reported here.