Whole-organism eQTL mapping at cellular resolution with single-cell sequencing.

DNA sequences that differ between individuals often change the activation pattern of genes. That is, they change how, when, or why genes switch on and off. We call such DNA sequences 'expression quantitative trait loci', or eQTLs for short. Many of these eQTLs affect biological traits, but their effects are not always easy to predict. In fact, these effects can change with time, with different stress levels, and even in different types of cells. This makes studying eQTLs challenging, especially in organisms with many different types of cells. Standard methods of studying eQTLs involve separately measuring which genes switch on or off under every condition and in each cell. However, a technology called single cell sequencing makes it possible to profile many cells simultaneously, determining which genes are switched on or off in each one. Applying this technology to eQTL discovery could make a challenging problem solvable with a straightforward experiment. To test this idea, Ben-David et al. worked with the nematode worm Caenorhabditis elegans, a frequently-used experimental animal which has a small number of cells with well-defined types. The experiment included tens of thousands of cells from tens of thousands of genetically distinct worms. Using single cell sequencing, Ben-David et al. were able to find eQTLs across all the different cell types in the worms. These included many eQTLs already identified using traditional approaches, confirming that the new method worked. To understand the effects of some of these eQTLs in more detail, Ben-David et al. took a closer look at the cells of the nervous system. This revealed that eQTL effects not only differ between cell types, but also between individual cells. In one example, an eQTL changed the expression of the same gene in opposite directions in two different nerve cells. There is great interest in studying eQTLs because they provide a common mechanism by which changes in DNA can affect biological traits, including diseases. These experiments highlight the need to compare eQTLs in all conditions and tissues of interest, and the new technique provides a simpler way to do so. As single-cell technology matures and enables profiling of larger numbers of cells, it should become possible to analyze more complex organisms. This could one day include mammals.