Data from: Ecology shapes epistasis in a genotype-phenotype-fitness map for stick insect colour
Data files
Aug 26, 2020 version files 137.91 MB
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2019_Tchumash_transplant_table.csv
54.54 KB
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2020Tchumash_quantum_catch_epistasis.R
1.81 KB
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bayes_glm
276 B
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bayes_hglm
649 B
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calcBV.R
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cvScript.R
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cvScriptExFit.R
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cvScriptExFitAdd.R
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cvScriptExFitEp.R
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cvScriptExFitEpDom.R
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cvScriptSurv.R
995 B
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cvScriptSurvAdd.R
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cvSummary.R
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filtered2x_tchum_mel_gbs_2019.vcf.gz
15.75 MB
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ld.R
1.98 KB
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mod_g_epi_tchum.txt
40.39 MB
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mod_g_tchum_AC.txt
20.32 MB
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mod_g_tchum_MM.txt
20.10 MB
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mod_g_tchum.txt
40.31 MB
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models.R
47.98 KB
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nullSims.R
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nullSimsPl.R
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pheno_AC.txt
876 B
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pheno_color.txt
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pheno_gb_cv.txt
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pheno_MM.txt
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pheno_rg_cv.txt
73.75 KB
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pleoitropy.R
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runMapitColor.R
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runMapitSurv.R
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selectionGradBayes.R
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spetra.chumash-2.zip
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spetra.chumash.zip
239.69 KB
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Tchumash.list.epistasis.txt
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Tchumash.spectra.epistasis.txt
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tchumSnpTable.txt
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Abstract
Genetic interactions such as epistasis are widespread in nature and can shape evolutionary dynamics. Epistasis occurs due to non-linearity in biological systems, which can arise via cellular processes that convert genotype to phenotype and via selective processes that connect phenotype to fitness. Few studies in nature have connected genotype to phenotype to fitness for multiple potentially interacting genetic variants. Thus, the causes of epistasis in the wild remain poorly understood. Here, we show that epistasis for fitness is an emergent and predictable property of non-linear selective processes. We do so by measuring the genetic basis of cryptic colouration and survival in a field experiment with stick insects. We find that colouration exhibits a largely additive genetic basis, but with some effects of epistasis that enhance differentiation between colour morphs. In terms of fitness, different combinations of loci affecting colouration confer high survival in one host-plant treatment. Specifically, non-linear correlational selection for specific combinations of colour traits in this treatment drives the emergence of pairwise and higher-order epistasis for fitness at loci underlying colour. In turn, this results in a rugged fitness landscape for genotypes. In contrast, fitness epistasis was dampened in another treatment, where selection was weaker. Patterns of epistasis that are shaped by ecologically based selection could be common, and central to understanding fitness landscapes, the dynamics of evolution, and potentially other complex systems.
The experimental T. chumash were collected from Cercocarpus sp. (Mountain Mahogany, MM) in the vicinity of the locality Horse Flats 5 (HF5, N 34 15.584, W 118 6.254). Over 700 individuals were collected between June 11th and June 13th, 2019. These were kept alive in plastic containers and moved to laboratory space where 465 healthy adults were chosen for use in the transplant experiment, including photography for phenotyping and molecular genotyping.
All individuals from the transplant experiment were photographed with a digital Nikon 5600 camera equipped with a macro lens (Nikon AF-S VR Micro-Nikkor 105mm f/2.8G IF-ED) and two external flashes (Yongnuo YN560-II speedlights). The images were taken with the camera set on manual, an aperture of f/14, a shutter speed of 1/200 s, a sensitivity of 100 ISO, and flashes adjusted to 1/4+0.5 env power in S1 mode in an output angle corresponding to 24-mm focal length on full frame (~84° diagonal).DNA sequence data were generated by on an Illumina HiSeq 200 (100 bp, single-end reads) by the Genome Sequencing and Analysis Facility at the University of Texas (Austin, TX).
The following files are included in this data archive:
2019_Tchumash_transplant_table.csv = csv text file with data from the release-recapture selection experiment. The files includes one row per individual with data on treatment, block, survival (binary) and color.
selectionGradBayes.R = R script with code for fitting selection gradients with Bayesan methods.
bayes_glm and bayes_hglm = JAGS models required by selectionGradBayes.R.
spectra.chumash.zip = zip compressed directory with the raw color spectra data.
2020Tchumash_quantum_catch_epistasis.R = R script to make graphs summarizing the spectra data.