Table 2 Quantitative genetic studies of genomic and phenotypic variation

The majority of quantitative trait locus (QTL) mapping approaches require inbred strains that have different alleles at loci affecting variation in the trait of interest and a polymorphic molecular marker linkage map. A cross between two genetically distinct parental strains or a series of crosses among parental lines produces recombinant inbred lines (RILs) or other segregating populations, such as introgression lines (IL). In most cases, the final panel is repeatedly inbred to obtain isogenic, and thus genetically stable, lines. As a consequence of random recombination events, each RIL combines different parts of the two (or more) parental genomes. In most previous research on C. elegans, the Hawaiian CB4856 strain—a strain that is highly divergent from N2 at many loci—and N2 have been used to detect QTLs [7, 70]. Various N2xCB4856 RILs and ILs present variable transgressive traits, and large genetic and phenotypic differences for a wide range of traits including reproduction, growth, and gene expression.

QTL mapping has however a number of shortcomings. Since the location of identified QTLs is indicated only by looking at which markers give the greatest differences between genotype class averages, QTL effects are often poor estimates of the true allele(s) effect. Moreover, when QTLs are far from markers—as has often been the case in earlier work when the markers are widely spaced—the mapping resolution is low. Furthermore, the network of genes as well as by environmental factors can regulate the complex dynamic process, such as disease progressing. Therefore, the QTLs or nucleotides (QTNs) that underlie a complex dynamic trait are expected to be characterized. Despite functional mapping provides a useful quantitative and testable framework for assessing the interplay between gene actions or interactions and developmental changes [105], further investigations are still needed through its opportunity to study development in a comprehensive manner and to study the dynamic network of genes that determine the physiology of an individual organism over time.

For understanding genetic pathways and gene networks, mapping of gene expression levels as quantitative trait loci (called eQTLs) has also been increasingly used for determining how a given variant affects gene expression. Sequence variants in eQTLs affect the expression of a gene, while other QTLs impact on any given trait of interest except from the trait causing by gene expression [71]. Owing to available measurement of either traits or phenotypes, eQTLs have been identified by evaluating gene expression in panels of genetically distinct genotyped individuals [29, 71].