Genetic variants that disrupt protein-coding DNA are ubiquitous in the human population, with ~100 such loss-of-function variants per individual. While most loss-of-function variants are rare, a subset have risen to high frequency and occur in a homozygous state in healthy individuals. It is unknown why these common variants are well-tolerated, even though some affect essential genes implicated in Mendelian disease. Here, we combine genomic, proteomic, and biochemical data to demonstrate that many common nonsense variants do not ablate protein production from their host genes. We provide direct evidence for previously proposed mechanisms of gene rescue such as alternative splicing and C-terminal truncation. Furthermore, we identify novel mechanisms of rescue, including alternative translation initiation at non-canonical start codons and stop codon readthrough. Our results suggest a molecular explanation for the mild fitness costs of common nonsense variants, and indicate that translational plasticity plays a prominent role in shaping human genetic diversity.
Evolutionary dynamics of selfish DNA generates pseudo-linguistic features of genomes
Michael Sheinman, Anna Ramisch, Florian Massip, Peter F. Arndt
(Submitted on 4 Feb 2016)
Since the sequencing of large genomes, many statistical features of their sequences have been found. One intriguing feature is that certain subsequences are much more abundant than others. In fact, abundances of subsequences of a given length are distributed with a scale-free power-law tail, resembling properties of human texts, such as the Zipf’s law. Despite recent efforts, the understanding of this phenomenon is still lacking. Here we find that selfish DNA elements, such as those belonging to the Alu family of repeats, dominate the power-law tail. Interestingly, for the Alu elements the power-law exponent increases with the length of the considered subsequences. Motivated by these observations, we develop a model of selfish DNA expansion. The predictions of this model qualitatively and quantitatively agree with the empirical observations. This allows us to estimate parameters for the process of selfish DNA spreading in a genome during its evolution. The obtained results shed light on how evolution of selfish DNA elements shapes non-trivial statistical properties of genomes.