Study Reveals Hidden Negative Selection in Human Noncoding Genome
A new statistical analysis of human genetic variation data suggests that at least 7% of the human genome is under negative selection, exceeding the ~5% estimate from traditional conservation-based methods. The study, posted as a preprint on bioRxiv, introduces a method to detect 'cryptic selection' — purifying selection acting on sites that are not conserved across species because their function has turned over evolutionarily. This matters because it challenges a foundational assumption in evolutionary genetics and suggests that many variants currently treated as neutral may actually be functionally significant.
Researchers have developed a statistical test to identify negative selection in the human genome that is invisible to standard comparative genomics approaches. Traditional methods estimate that roughly 5% of the human genome is constrained by identifying positions conserved across multiple species, but this misses sites where biological function has evolved in some lineages but not others — a phenomenon called functional turnover. By analyzing polymorphism data from the 1000 Genomes Project and comparing putatively functional noncoding regions to putatively neutral ones, the authors detected widespread signals of cryptic selection even after removing the top 70% of conserved sites. Their simulations and estimates suggest at least 7% of the human genome is under negative selection genome-wide, with a substantial fraction of constrained sites having gone undetected by conservation-based tools. The findings have direct implications for how researchers designate 'neutral' variants in population genetics studies, GWAS analyses, and the interpretation of noncoding variation in disease contexts.
What's missing
As a preprint, this work has not yet undergone peer review. The authors' 7% estimate is described as an approximation derived from simulations with varying levels of cryptic selection, and the true figure could differ depending on modeling assumptions. The study does not fully characterize which specific functional categories or biological processes are driving the cryptic selection signals, nor does it quantify false-positive rates under all realistic demographic scenarios.
What different sources said
- bioRxivCenter
Inference of elevated mutation rates and variant effects using 700k exomes
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