DOI: 10.5061/dryad.jf29v
title: Data from: Dynamics of copy number variation in host races of the pea aphid

description: Copy number variation (CNV) makes a major contribution to overall genetic
 variation and is suspected to play an important role in adaptation.
 However, aside from a few model species, the extent of CNV in natural
 populations has seldom been investigated. Here, we report on CNV in the
 pea aphid Acyrthosiphon pisum, a powerful system for studying the genetic
 architecture of host plant adaptation and speciation thanks to multiple
 host races forming a continuum of genetic divergence. Recent studies have
 highlighted the potential importance of chemosensory genes, including the
 gustatory and olfactory receptor gene families (Grs and Ors,
 respectively), in the process of host race formation. We used targeted
 re-sequencing to achieve a very high depth of coverage, and thereby
 revealed the extent of CNV of 434 genes, including 150 chemosensory genes,
 in 104 individuals distributed across eight host races of the pea aphid.
 We found that CNV was widespread in our global sample, with a
 significantly higher occurrence in multigene families, especially in Ors,
 and a decrease in the probability of complete gene duplication or deletion
 (CDD) with increase in coding sequence length. Genes with CDD variants
 were usually more polymorphic for copy number, especially in the P450 gene
 family where toxin resistance may be related to gene dosage. We found that
 Grs were over-represented among genes discriminating host races, as were
 CDD genes and pseudogenes. Our observations shed new light on CNV dynamics
 and are consistent with CNV playing a role in both local adaptation and
 speciation.
description: 01 - Output files from
 Picard "CalculateHsMetrics"Raw coverage estimate
 per subtarget (aka "baits") per individual estimated by the
 Picard tool "CalculateHsMetrics". For each individual, two files
 are available. 1) A "*.HsMetrics" file containing the global
 Hsmetrics information (see
 http://picard.sourceforge.net/picard-metric-definitions.shtml#HsMetrics).
 2) A "*.HsMetrics.Targets" file containing the coverage
 information per subtarget.RawCoverageCount_PicardCalculateHsMetrics.rar02 - R matrix of normalized read count dataMatrix of normalized read count data in R format. Few formating steps have been performed here (see main MBE paper and script "./01_GetData/script.R" in the pipeline). 1) Normalisation of the read counts. 2) Remove targets with more than 5% of reads with PHRED score&lt;10. Note that these data are those BEFORE the squared root and polynomial transformations.NormalizedCoverageData.Rdata03 - Squared root and transformed read count dataR list resulting from the script "./02_PreProcessing/script.R" in the pipeline). This list contain several sets of data and information including the matrix of squared root and polynomially transformed read count data (i.e. the data used in the estimation of CNV).02_PreProcessing.Rdata04 - Matrix of raw alpha valuesMatrix of raw alpha values (i.e. CNV estimates) obtained from the function "findOptimalSegmentations" (package "optimalCaptureSegmentation"). The values are not rounded here.RawAlphaMatrix_OptimalSegmentation.R05 - Data for and results of GLMM1R file containing the data frame and GLMM results of the first GLMM of the paper. Response variable: CNV presence/absence - a gene was considered to show CNV in a race if at least one of its subtargets presented a CN variant (i.e. CN≠1X) in at least one individual of this race.14_Binom_Polym_Div-Rel.Rdata06 - Data for and results of GLMM2R file containing the data frame and GLMM results of the second GLMM of the paper. Response variable: complete duplication or deletion (CDD) vs partial duplication/deletion - a gene was considered CDD if all of its subtargets showed CN variants in at least one individual in the race.15_Binom_Dup-CpDup_Div-Rel.Rdata07 - Data for and results of GLMM3R file containing the data frame and GLMM results of the third GLMM of the paper. Response variable: CNV frequency - the proportion of individuals in a race with CN≠1X.16_Binom_fqcy_Div-Rel.Rdata09 - NJ tree of CNV per capture pools and sequencing lanesNJ tree based on CNV data (data used: square rooted and polynomial transformed read counts, alpha rounded to the closest half unit). Capture pools and sequencing lanes are shown. The distance matrix was computed using usual Euclidean distance (by opposition to the distance matrix obtained from the Random Forest analysis).Res_CNV-NJ_PoolsAndLanes.pdf08 - RandomForest results and gene family importanceR file contatining all the information concerning the RF analysis and the estimation of gene family importance in discriminating host races. Although this piece of information has been realease for transparency, beware that the R files contain many objects and is quite difficult to investigate. Please refer to the script "./08_GeneFamImptceTest/script.R" or contact the main authors for more information.08_GeneFamImptceTest.Rdata10 - ExtendedFigure1_CNValongCHR_AllTargetsIncludedExtended Figure 1. CNV along chromosomes for all targeted loci. Each line represents an individual (one colour per race plus Medicago standard in purple). For clarity, values of alpha represented here are those before rounding to the closest half unit (the red box represents the area in which alpha values were rounded to one). Vertical light grey shaded areas represent targets as originally designed whereas bottom dark grey and gold boxes represent subtargets excluded and retained for final analyses, respectively. Retained subtargets are linked by full lines when from the same target and by dotted lines where not. Gene names (and scaffold numbers) are indicated above each plot. Control genes are shown with their alias names. The “P” in gene names stands for pseudogene. The “*” symbol indicates genes partially represented due to the absence of targets upstream or downstream filtered out during cleaning steps.Link to FigS2_CNV_along_CHR.pdf