Ectopic gene conversion causing quantitative trait variation
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Abstract
Why is there so much non-neutral genetic variation segregating in natural populations? We dissect function and evolution of a near-cryptic quantitative trait locus (QTL) for defense metabolites in Arabidopsis using the CRISPR/Cas9 system and nucleotide polymorphism patterns. The QTL is explained by genetic variation in a family of four tightly linked indole-glucosinolate O -methyltransferase genes. Some of this variation appears to be maintained by balancing selection, some appears to be generated by non-reciprocal transfer of sequence, also known as ectopic gene conversion (EGC), between functionally diverged gene copies. Here we elucidate how EGC, as an inevitable consequence of gene duplication, could be a general mechanism for generating genetic variation for fitness traits.
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but that selection acts against EGC near codons specifying fixed derived amino acids, i.e., mutations that differentiate Arabidopsis thaliana gene copies from those of Arabidopsis lyrata.
Very cool result!
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(Fig. 2)
It would be helpful to have colour labelled legends in the figures.
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deed, visual inspection identified numerous linked specific variants at polymorphic sites, sometimes spanning hundreds of positions, indicative of gene conversion tracts.
As you point out, it seems some of the strongest evidence for ECG is that polymorphism is not just shared, but shared polymorphisms are linked. One way you could statistically quantify this is by running a tool scanning for evidence of identity by descent (IBD), or use a tree sequence approach, treating each gene from each accession as an individual genome (like in the multiple sequence alignment you construct). This isn't strictly what IBD tools are for, but it should provide a good proxy given that A. thaliana has low polymorphism and high linkage disequilibrium. Relatedly it would help if intervals for putative EGC could be filled in, not just the limits marked …
deed, visual inspection identified numerous linked specific variants at polymorphic sites, sometimes spanning hundreds of positions, indicative of gene conversion tracts.
As you point out, it seems some of the strongest evidence for ECG is that polymorphism is not just shared, but shared polymorphisms are linked. One way you could statistically quantify this is by running a tool scanning for evidence of identity by descent (IBD), or use a tree sequence approach, treating each gene from each accession as an individual genome (like in the multiple sequence alignment you construct). This isn't strictly what IBD tools are for, but it should provide a good proxy given that A. thaliana has low polymorphism and high linkage disequilibrium. Relatedly it would help if intervals for putative EGC could be filled in, not just the limits marked as in Fig S6. This would make it easier to see what the length of EGC tracts is.
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Given this, I would suggest that this paper does not quite fit the framing of reconciling genetic variation with mutation selection balance. I think as the title suggests the strongest claim is that ECG can create quantitative trait variation, and this is the framing that makes the most sense in the introduction/discussion.
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This can explain why there is more segregating fitness variation within populations than predicted under mutation selection balance (1).
This seems to me as a fairly strong statement that doesn't quite line up with the goals/results of this study. Technically what this study shows is how ECG can contribute to standing genetic variation in a population. The specific paradox of standing genetic variation in phenotypes however, looks to reconcile why there is more variation than expected under mutation selection balance (MSB). MSB in practice is agnostic to the type of mutations, when/where they arose, simply their fitness effects. As detailed in the first reference, it is clear that SNPs alone are inconsistent with MSB which is not surprising since they are only a fraction of genetic variants found in populations. However again as …
This can explain why there is more segregating fitness variation within populations than predicted under mutation selection balance (1).
This seems to me as a fairly strong statement that doesn't quite line up with the goals/results of this study. Technically what this study shows is how ECG can contribute to standing genetic variation in a population. The specific paradox of standing genetic variation in phenotypes however, looks to reconcile why there is more variation than expected under mutation selection balance (MSB). MSB in practice is agnostic to the type of mutations, when/where they arose, simply their fitness effects. As detailed in the first reference, it is clear that SNPs alone are inconsistent with MSB which is not surprising since they are only a fraction of genetic variants found in populations. However again as detailed in the first reference, quantitative genetics approaches that use mutation accumulation experiments are agnostic to mutation type, and provide a framework for testing if MSB is sufficient to explain standing levels of genetic variation. Paradoxically they often find that MSB is not enough to explain the high variation in phenotypes (due to genetic effects) we observe (see https://doi.org/10.1098/rspb.2018.1864 for an example), implying that forces such as balancing selection must also be working to maintain excess genetic variation. What this study demonstrates is that non-SNPs can contribute to variation (as other studies have demonstrated for transposons, inversions, indels etc.). This alone does not demonstrate the sufficiency of MSB to explain observed genetic variation in phenotypes though.
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