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We visualized large-scale synteny between these pairs using dotplots.
To assess the functional similarity between these pairs, using co-regulation criterion, we parsed the Ecocyc database [ 34] to obtain a network of 541 operons and 806 experimentally verified transcription interactions.
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Coordinated movement emerged between the pairs using two different hetero-medaka strains that gave the same result (Fig. 2B, Fig. S1D and S1E).
The Rec program identified recombinants by scoring the percentage mismatch between sequence pairs using a sliding window.
We calculated sequence identity between paralogous pairs using the Needleman Wunsch algorithm (Python module nwalign v0.3.1).
We estimated gene flow (m = proportion of migrants) between population pairs using BayesASS+ v.1.3 [ 48].
After completion of data acquisition process, we calculated the similarity between Jamu pairs using correlation measure.
36 We also extended the definition of interaction between target pairs using shared scaffolds.
We determined orthology relationships between gene pairs using the BLAST Bi-Directional Best Hits (BBH) approach [ 35].
We calculated the mean relatedness per population and compared the mean relatedness across populations using an anova, and between population pairs using t-tests.
This was applied to the GO Biological Process hierarchy as a quantitative measure of functionality similarity between gene pairs using the R package GOSemSim [ 36].
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