QTL analysis in plants; where are we now?

MetaQTL: a package of new computational methods for the meta-analysis of QTL mapping experiments

“…Relevancy of the colocalization between QTL and candidate genes crucially depends on the confidence interval of the QTL positions. For this purpose the reduction of the confidence interval of the QTL is an important goal [2]. The ability of our method to reduce the QTL confidence interval by taking advantage of pooling QTL results could contribute in an increased resolution in selecting candidate genes.…”

“…This is mainly due to both a few mating generations and a restricted number of sampled individuals (generally a few hundreds). From results of QTL experiments gathered over a wide range of plant species, [2] have shown that confidence intervals around most likely QTL positions are, on average, approximately 10 cM, which usually includes several hundreds of genes. More recent advents in the area of molecular biology have allowed researchers to carry out positional cloning of QTL (see for instance the review of [3]) but this approach still remains extremely expensive both in terms of time and resources.…”

“…More recent advents in the area of molecular biology have allowed researchers to carry out positional cloning of QTL (see for instance the review of [3]) but this approach still remains extremely expensive both in terms of time and resources. Also several authors [2,4] have pointed out that QTL detection is statistically biased both in the true number of QTL, which is underestimated since only QTL with large effects are detected, and in the QTL effects which are over estimated as only significant effects are reported (a phenomenon has commonly referred to as the Beavis effect [5]). Even though QTL mapping experiments must be considered with an awareness of these limitations, they have become commonplace and have greatly improved our knowledge about the genetic component of complex traits.…”

“…Yet both the method of [17] and [22] are limited to a small number of underlying QTL positions (from one to four for the former and only one for the later) which is a serious limitation for a whole genome study of QTL congruency. Even if the average number of QTL per experiment is around four in plants [2,12], one would expect that more than four genes can be involved in the trait variation on a single chromosome.…”

Mapping quantitative trait loci associated with selenate tolerance in Arabidopsis thaliana

“…QTL mapping is performed by testing for statistical associations between the genotype of molecular markers distributed across the genome and the phenotypic value of the trait of interest. This approach has become easier to implement because of the advancement of PCR-based molecular markers (Kearsey & Farquhar, 1998); new statistical procedures (Lander & Botstein, 1989;Zeng, 1993); and the availability of software programs (Basten et al ., 1994;Manly & Olson, 1999;Sen & Churchill, 2001). QTL mapping is a first step towards an understanding of the molecular genetic mechanisms behind phenotypic complexity.…”