DOI: 10.5061/dryad.m905qfv26
title: Natural selection drives genome-wide evolution via chance genetic associations

description: Understanding selection's impact on the genome is a major theme in
 biology. Functionally-neutral genetic regions can be affected indirectly
 by natural selection, via their statistical association with genes under
 direct selection. The genomic extent of such indirect selection,
 particularly across loci not physically linked to those under direct
 selection, remains poorly understood, as does the time scale at which
 indirect selection occurs. Here we use field experiments and genomic data
 in stick insects, deer mice and stickleback fish to show that widespread
 statistical associations with genes known to affect fitness cause many
 genetic loci across the genome to be impacted indirectly by selection.
 This includes regions physically distant from those directly under
 selection. Then, focusing on the stick insect system, we show that
 statistical associations between SNPs and other unknown, causal variants
 result in additional indirect selection in general and specifically within
 genomic regions of physically linked loci. This widespread indirect
 selection necessarily makes aspects of evolution more predictable. Thus,
 natural selection combines with chance genetic associations to affect
 genome-wide evolution across linked and unlinked loci and even in
 modest-sized populations. This process has implications for the
 application of evolutionary principles in basic and applied science.
description: Whole genome DNA sequence data were previously generated from 491
 <em>Timema cristinae </em>stick insects that were part of a
 release-recapture selection experiment (available from the NCBI SRA
 PRJNA356801). For the current study, we aligned the whole genome DNA
 sequence data from each of these 491 <em>T. cristinae</em> to
 the <em>T. cristinae</em> reference genome (version 1.3) using
 the <em>bwa</em> (version 07.10-r789) <em>mem</em>
 algorithm with a band width of 100, a 20 bp seed length and a minimum
 score for output of 30. We then used<em> samtools
 </em>(version 1.5) to compress, sort and index the alignments, and
 to remove PCR duplicates. We then used the<em> GATK
 HaplotypeCaller</em> and <em>GenotypeGVCFs </em>modules
 (version 3.5) to call variants and calculate genotype likelihoods. We
 required a minimum base quality of 30, set the prior probability of
 heterozygosity to 0.001, and only called variants with a minimum
 phred-scaled confidence of 50. The following filters
 were then applied using custom Perl scripts: minimum coverage of 1Xp er
 individual (i.e., 491X coverage across all individuals), a minimum ratio
 of variant confidence to non-reference read depth of 2, a minimum mapping
 quality of 40, a maximum phred-scaled P-value of Fisher's exact test
 for strand bias of 60, and a minimum minor allele frequency of 0.01.
 Further, we only retained SNPs mapped to one of the 13 <em>T.
 cristinae</em> linkage groups. This resulted in 7,243,463 SNPs,
 which were used in subsequent analyses. Next, we
 obtained maximum likelihood estimates of allele frequencies for all
 experimental samples using an expectation-maximization (EM) algorithm as
 implemented in estpEM (version 0.1). For this, we used a convergence
 tolerance of 0.001 and allowed for a maximum of 30 EM iterations. We then
 used these allele frequency estimates and the genotype likelihoods from
 <em>GATK</em> to calculate empirical Bayesian genotype
 estimates. These point estimates range from zero to two, and are not
 constrained to be integer values. Thus, this data set
 includes the genotype estimates for the 491 individuals as well as the
 data on survival, i.e., whether or not they were re-captured at the end of
 the experiment.
description: <strong>pntest_LG_*_mod_filtered1X_tcrExperimentVariants.txt.gz (* denotes 1, 2, ... ,13)</strong> These text files contain the genotype estimates (Bayesian point estimates of the number of non-reference alleles). There is one file per chromosome (linkage group, numbered 1 to 13). Each contains one row per SNP locus and one column per individual. <strong>LG*_SNPs.txt.gz</strong> These text files provide information about the genomic location of each SNP in the genotype files described above. There is one file per chromosome (linkage group, numbered 1 to 13). Each contains one row per SNP locus with the scaffold number (1st column), linkage group number (2nd column), 3 estimates of map position (in cM, columns 3-5), and the position in base pairs. <strong>Survival.txt</strong> This text file contains one row per individual with 1 or 0 denoting whether the stick insect survived (1) or died (0). <strong>TrtmntHost.txt</strong> This text file contains one row per individual stick insect with the first column denoting the block number and the second column denoting the host plant (A = Adenostoma, C = Ceanothus).