QTL Analysis in Plants: Ancient and Modern Perspectives

Quantitative traits exhibit continuous variation, indicating their control through multiple genes. Segregating populations are used to mine out associations between phenotypic and genotypic variations. Phenotyping performed for a specific trait and its variation in the population is justified with genotypic variation obtained through genetic markers application. A snapshot of genotypic variation is strictly dependent on the number and density of the markers applied. Parental and marker information is required to correlate genetic and phenotypic data for quantitative trait loci (QTL) analysis. For many years (now becoming obsolete), it has been of core importance to identify QTL with such methodology. Failure had to be faced by the researcher because the DNA region identified for phenotypic variation was much wider, and needed to be narrowed down by further dense marker application in that area to obtain required and accurate results. Nowadays the focus is on high-throughput technologies to obtain genome-wide resolution: high-throughput sequencing (HTS) is one of them. A comprehensive map of genomic variations can be produced with resequencing or reference genome sequences. Along with expression profiling, new molecular markers can be searched out with QTL analysis. Genomic-assisted breeding by studying the evolutionary variations in crops has many applied aspects as well. As compared to the conventional biparental population, presently the focus is on raising multiparent advanced generation inter-cross (MAGIC) populations to explore the genetic basis of quantitative traits. Probabilities of alleles of interest across the whole genome are calculated through the Hidden Markov Model (HMM). Different software packages (such as R-package, Qgene) are used for the estimates. Such whole-genome approaches in QTL analysis are a powerful and recently used technique. In this chapter, all these recent and modified modern techniques are reviewed with the most recent upcoming details. Traditional and modern QTL analyses have clearly been differentiated on applicable grounds.