Evolution profile of 13415 SNVs in 33 language/cognition genes measured by five types of distance calculation

Abstract

This study aims to quantify the genetic similarity of different species (from fish to humans) to the human reference genome (pp6, Homo sapiens.GRCh38) based on the allele presence/absence patterns of 13,415 SNV loci from 33 language/cognition-related genes, identify key breakpoints during evolution, and evaluate the enrichment of language and cognition genes at these breakpoints. We designed a similarity calculation method relying on binary features (four columns for A/T/C/G), adopted five difference/distance measures (Sorensen, Rogers, Nei, Reynolds, and Hellinger), and converted them into similarity values (1/(1+distance)). For each method, samples were independently ranked, the first derivative of similarity was computed, and the top 12 peaks were selected as candidate breakpoints. Results show that the similarity curves from the five methods are highly consistent (correlation coefficients >0.9), with major peaks concentrated at positions 355, 363, 381, 382, 390, 400, etc., where the corresponding samples are predominantly ancient hominins and primates. Furthermore, we defined 13 peak groups (starting positions 355-401). For each peak within a group, pairwise SNV differences between the peak apex sample and its immediate left neighbor were compared, and the intersection F_INTERSECTION (shared differential loci) was obtained. For each F_INTERSECTION, we calculated the proportions of language genes and cognition genes. In addition, we computed the differential sets between adjacent groups' F_INTERSECTION to trace the gradual emergence of new loci. In F_INTERSECTION, language genes accounted for an average of 59.5%, and cognition genes for an average of 62.9%. The proportion of language genes reached a peak at position 383 (61.2%), while cognition genes peaked at position 386 (64.9%). High-frequency peak samples include c25, c27, and ja2, suggesting that language-cognition genes may have undergone independent intensification during Eurasian evolution. Differential analysis between adjacent F_INTERSECTION revealed a stepwise acquisition of new loci from position 355 to 401, with three bursts of newly added loci along the entire evolutionary axis. These molecular patterns carry implications beyond evolutionary genetics. The absence of robust enrichment for either language or cognition genes at any breakpoint is compatible with the hypothesis that language and cognition are not separable functional modules, but rather constitute an integrated symbolic-cognitive system. This distinction matters for artificial intelligence research: if language, understood as an internal symbolic system, is inseparable from cognition, then treating large language models' linguistic performance as a direct proxy for cognitive capacity may be theoretically problematic. The present study therefore provides not only a quantitative evolutionary framework based on similarity curves, but also a methodological caution for AI foundations-namely, that the competence-performance distinction must be carefully preserved when interpreting what large language models can and cannot do. The results highlight the potential importance of East Asian archaic hominins in the evolution of language-cognition genes, and suggest that future AI research may benefit from distinguishing between the mastery of deep symbolic regularities (closer to I-language) and the imitation of surface statistical patterns (closer to externalized behavior).