Synthetic collinearization of a chromosome segment enables genetic dissection of incompatibility between distant genera
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Updated: Oct 30, 2026

2D and 3D Chromosome Painting in Malaria Mosquitoes
Published on: January 6, 2014
Shawn H Yang1, Alexandra H Christensen1, Alessandro L V Coradini1
1Department of Molecular and Cellular Biosciences, University of Southern California, Los Angeles, CA 90089, USA.
Abstract:
Reproductive barriers and genomic structural differences hinder genetic analysis between highly divergent organisms. Here, we examined whether these challenges can be overcome by collinearization, the synthesis of chromosomes that retain the native gene content and organization of a host organism while incorporating the DNA sequences of another organism. We applied collinearization to Kluyveromyces marxianus, a yeast species that is both distantly related to and has a distinct genome structure from the model yeast Saccharomyces cerevisiae. We generated a ∼35-kb K. marxianus DNA segment that was collinear with one-sixth of a S. cerevisiae chromosome and contained 17 protein-coding genes. Although this synthetic chromosome segment successfully substituted for its native counterpart in an S. cerevisiae cell, it imposed a significant growth cost due to the incompatibility of two K. marxianus proteins with the host proteome. We attempted to predict disrupted protein-protein interactions using AlphaFold and fully or partially alleviated the resulting fitness costs by supplementing orthologous protein partners from K. marxianus. Furthermore, we completely eliminated the growth cost by replacing the incompatible K. marxianus genes with their S. cerevisiae orthologs. These findings demonstrate that collinearization can facilitate the creation of chimeric genomes to dissect the genetic basis of incompatibility and traits between organisms that cannot naturally hybridize. They also suggest that many genetic incompatibilities likely exist between S. cerevisiae and K. marxianus, reflecting disrupted protein-protein interactions that may to some degree be predictable in silico.
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