Laboratoire de Biologie Moléculaire de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, Université de Lyon, Lyon, France.
Trends Genet. 2014 Feb;30(2):49-56. doi: 10.1016/j.tig.2013.11.002. Epub 2013 Dec 6.
Genotype-phenotype relations are usually inferred from a deterministic point of view. For example, quantitative trait loci (QTL), which describe regions of the genome associated with a particular phenotype, are based on a mean trait difference between genotype categories. However, living systems comprise huge numbers of cells (the 'particles' of biology). Each cell can exhibit substantial phenotypic individuality, which can have dramatic consequences at the organismal level. Now, with technology capable of interrogating individual cells, it is time to consider how genotypes shape the probability laws of single cell traits. The possibility of mapping single cell probabilistic trait loci (PTL), which link genomic regions to probabilities of cellular traits, is a promising step in this direction. This approach requires thinking about phenotypes in probabilistic terms, a concept that statistical physicists have been applying to particles for a century. Here, I describe PTL and discuss their potential to enlarge our understanding of genotype-phenotype relations.
表型-基因型关系通常是从确定性的角度推断出来的。例如，描述与特定表型相关的基因组区域的数量性状位点（QTL），是基于基因型类别之间的平均性状差异。然而，生命系统包含大量的细胞（生物学的“粒子”）。每个细胞都可以表现出显著的表型个体性，这在生物体水平上可能会产生巨大的影响。现在，随着能够检测单个细胞的技术的出现，是时候考虑基因型如何塑造单细胞特征的概率规律了。将基因组区域与细胞特征的概率联系起来的单细胞概率特征基因座（PTL）的映射成为可能，这是朝着这个方向迈出的有希望的一步。这种方法需要用概率的术语来考虑表型，统计物理学家一个世纪以来一直在将这个概念应用于粒子。在这里，我描述了 PTL，并讨论了它们扩大我们对表型-基因型关系的理解的潜力。
