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Synopsis Gene duplicates, or paralogs, serve as a major source of new genetic material and comprise seeds for evolutionary innovation. While originally thought to be quickly lost or nonfunctionalized following duplication, now a vast number of paralogs are known to be retained in a functional state. Daughter paralogs can provide robustness through redundancy, specialize via sub-functionalization, or neo-functionalize to play new roles. Indeed, the duplication and divergence of developmental genes have played a monumental role in the evolution of animal forms (e.g., Hox genes). Still, despite their prevalence and evolutionary importance, the precise detection of gene duplicates in newly sequenced genomes remains technically challenging and often overlooked. This presents an especially pertinent problem for evolutionary developmental biology, where hypothesis testing requires accurate detection of changes in gene expression and function, often in nontraditional model species. Frequently, these analyses rely on molecular reagents designed within coding sequences that may be highly similar in recently duplicated paralogs, leading to cross-reactivity and spurious results. Thus, care is needed to avoid erroneously assigning diverged functions of paralogs to a single gene, and potentially misinterpreting evolutionary history. This perspective aims to overview the prevalence and importance of paralogs and to shed light on the difficulty of their detection and analysis while offering potential solutions.
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This content will become publicly available on April 4, 2026
Quantifying the influence of genetic context on duplicated mammalian genes
Abstract Gene duplication is a fundamental part of evolutionary innovation. While single-gene duplications frequently exhibit asymmetric evolutionary rates between paralogs, the extent to which this applies to multi-gene duplications remains unclear. In this study, we investigate the role of genetic context in shaping evolutionary divergence within multi-gene duplications, leveraging microsynteny to differentiate source and target copies. Using a dataset of 193 mammalian genome assemblies and a bird outgroup, we systematically analyze patterns of sequence divergence between duplicated genes and reference orthologs. We find that target copies, those relocated to new genomic environments, exhibit elevated evolutionary rates compared to source copies in the ancestral location. This asymmetry is influenced by the distance between copies and the size of the target copy. We also demonstrate that the polarization of rate asymmetry in paralogs, the “choice” of the slowly evolving copy, is biased towards collective, block-wise polarization in multi-gene duplications. Our findings highlight the importance of genetic context in modulating post-duplication divergence, where differences in cis-regulatory elements and co-expressed gene clusters between source and target copies may be responsible. This study presents a large-scale test of asymmetric evolution in multi-gene duplications, offering new insight into how genome architecture shapes functional diversification of paralogs. Significance statementAfter a gene is duplicated, reduced selective constraints can lead the two copies to rapidly diverge, with one copy often evolving faster and occasionally gaining a new function. We quantify the influence of genetic context in choosing which copy of a duplicated gene has an elevated substitution rate. In a representative dataset of 193 mammalian genomes, we found strong evidence that gene copies pasted into new genomic locations tend to evolve faster than the corresponding copies in ancestral locations, suggesting an important role for the regulatory environment. The asymmetry in evolutionary rates of duplicated genes persists even for very large multigenic duplications, up to the scale of megabases, indicating that regulatory interactions frequently reach farther than previously thought.
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- Award ID(s):
- 2019745
- PAR ID:
- 10595434
- Publisher / Repository:
- bioRxiv
- Date Published:
- Format(s):
- Medium: X
- Institution:
- bioRxiv
- Sponsoring Org:
- National Science Foundation
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