It is now well documented that next-generation sequencing (NGS) can generate several millions or even dozens of millions of genetic variation data. As a consequence, these genetic variation data are so densely distributed across the genome that the genetic variation can be modeled as a function of genomic location. But, standard multivariate statistical analysis often fails with functional data. The emergence of NGS demands a paradigm shift in the analytic methods for QTL(eQTL) analysis from standard single-variate or multivariate data analysis to functional data analysis. We propose a functional linear model (FLM) as a general analytic platform for testing the association of the entire allelic spectrum of genetic variation with a quantitative trait. Simulations and real data analysis show that the FLM can substantially outperform many exiting statistics for QTL analysis with NGS data. The FLM is expected to open a new route for QTL analysis. (By Dr. Momiao Xiong, http://jmg.bmj.com/content/49/8/513.abstract?etoc )