Molecular EcologyGenomicsPeer-reviewed journal article
Sex matters in Massive Parallel Sequencing: Evidence for biases in genetic parameter estimation and investigation of sex determination systems
Laura BenestaniD, Jean‐Sébastien MooreiD, Ben J. G. SutherlandiD, Jérémy Le LuyeriD, Halim MaaroufiiD, Clément RougeuxiD, Éric NormandeauiD, Nathan Rycroft, Jelle Atema, Les N. HarrisiD, Ross F. TallmaniD, Spencer J. GreenwoodiD, Fraser K. Clark, Louis BernatcheziD
Abstract
Using massively parallel sequencing data from two species with different life history traits -- American lobster (Homarus americanus) and Arctic Char (Salvelinus alpinus) -- we highlighted how an unbalanced sex ratio in the samples combined with a few sex-linked markers may lead to false interpretations of population structure and thus to potentially erroneous management recommendations. Multivariate analyses revealed two genetic clusters that separated males and females instead of showing the expected pattern of genetic differentiation among ecologically divergent (inshore vs. offshore in lobster) or geographically distant (east vs. west in Arctic Char) sampling locations. We created several subsamples artificially varying the sex ratio in the inshore/offshore and east/west groups, and then demonstrated that significant genetic differentiation could be observed despite panmixia for lobster, and that Fst values were overestimated for Arctic Char. This pattern was due to 12 and 94 sex-linked markers driving differentiation for lobster and Arctic Char, respectively. Removing sex-linked markers led to nonsignificant genetic structure (lobster) and a more accurate estimation of Fst (Arctic Char). We further characterized the putative functions of sex-linked markers. Given that only 9.6% of all marine/diadromous population genomic studies to date reported sex information, we urge researchers to collect and consider individual sex information. In summary, we argue that sex information is useful to (i) control sex ratio in sampling, (ii) overcome \"sex-ratio bias\" that can lead to spurious genetic differentiation signals and (iii) fill knowledge gaps regarding sex determining systems.
- organism: Arabidopsis
- assay: whole-genome sequencing
- research focus: benchmarking
- approach: statistical model
- Citations
- 87
- FWCI
- 4.71
- Field percentile
- top 4%
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