DOI: 10.5061/dryad.bg79cnpf7
title: Data from: Whole genomes reveal evolutionary relationships and mechanisms underlying gene-tree discordance in Neodiprion sawflies

description: Rapidly evolving taxa are excellent models for understanding the
 mechanisms that give rise to biodiversity. However, developing an accurate
 historical framework for comparative analysis of such lineages remains a
 challenge due to ubiquitous incomplete lineage sorting and introgression.
 Here, we use a whole-genome alignment, multiple locus-sampling strategies,
 and summary-tree and SNP-based species-tree methods to infer a species
 tree for eastern North American Neodiprion species, a clade of
 pine-feeding sawflies (Order: Hymenopteran; Family: Diprionidae). We
 recovered a well-supported species tree that—except for three uncertain
 relationships—was robust to different strategies for analyzing
 whole-genome data. Nevertheless, underlying gene-tree discordance was
 high. To understand this genealogical variation, we used multiple linear
 regression to model site concordance factors estimated in 50-kb windows as
 a function of several genomic predictor variables. We found that site
 concordance factors tended to be higher in regions of the genome with more
 parsimony-informative sites, fewer singletons, less missing data, lower GC
 content, more genes, lower recombination rates, and lower D-statistics
 (less introgression). Together, these results suggest that incomplete
 lineage sorting, introgression, and genotyping error all shape the genomic
 landscape of gene-tree discordance in Neodiprion. More generally, our
 findings demonstrate how combining phylogenomic analysis with knowledge of
 local genomic features can reveal mechanisms that produce topological
 heterogeneity across genomes.
description: DNA was extracted from field-caught larvae. Then, Illumina
 libraries were prepared and sequenced on an Illumina NextSeq 500 with
 PE150 reads, which produced 14-27 million reads per individual.
 To obtain a multi-genome alignment, we used a
 pseudo-reference-based approach, with an annotated, reference quality
 <em>N. lecontei</em> genome (iyNeoLeco1.1 RefSeq
 GCF_021901455.1) serving as the reference. Briefly, we first used bowtie2
 v2.4.1 to map reads from each species to the <em>N.
 lecontei</em> reference genome. To allow for divergence between
 reads and the <em>N. lecontei</em> reference, we initially
 allowed a mismatch in the seed and “local” mapping options in bowtie2. New
 variants (excluding indels) were incorporated using samtools v1.10  and
 bcftools v1.10.2. In a second round of mapping, this process was repeated
 using the first iteration of the genome for each species as the new
 reference genome. The third round of mapping removed the seed mismatch.
 The fourth and fifth iterations required end-to-end mapping. After the
 fifth iteration, we replaced any nucleotide that had a read depth less
 than 4 or that had excessively high mapping depth (highest 1% of depths
 for each species) with an “N” using a custom script. All bioinformatics
 commands and scripts can be found on the LinnenLab GitHub page under the
 Herrig_etal_NeodiprionPhylogeny repository (https://github.com/LinnenLab/Herrig_etal_NeodiprionPhylogeny and Zenodo). This approach produced FASTA files for each species, with genome sequences in <em>N. lecontei</em> coordinates. All FASTA files are provided here. We next used the FASTA files to produce additional datasets for analysis. First, we used bedtools v2.30.0  to divide the seven <em>Neodiprion</em> chromosomes into non-overlapping windows of 50 kb. Second, to approximate a dataset of protein-coding genes analogous to an RNAseq or exon-capture phylogenomic dataset, we used gffread v0.11.7 with the –w flag to write fasta files with spliced exons for each transcript for each species using the NCBI <em>Neodiprion lecontei </em>Annotation Release (iyNeoLeco1.1 RefSeq GCF_021901455.1). Windowed and gene datasets are provided as nexus files that contain individual window/gene alignments. These can also be regenerated using scripts (available on GitHub: https://github.com/LinnenLab/Herrig_etal_NeodiprionPhylogeny and Zenodo) to cut up the genome into desired loci (windows or genes) and convert these to nexus format. Third, we called single nucleotide polymorphisms (SNPs) across the entire genome using SNP-sites v2.5.1. We then filtered the data to exclude SNPs that were absent in more than 10% of species and sites with more than two alleles. In addition to analyzing all SNPs (which likely contain tightly linked sites), we produced additional datasets with one SNP sampled every 1 kb, 5 kb, 10 kb, 50 kb, or 100 kb using SNP-sites, with more sparsely sampled SNPs on par with a dataset that might be generated via RADseq. We transformed each of the six datasets into nexus format. All six SNP nexus files are provided and can be used as input for SVDquartets.  To investigate sources of phylogenetic discordance, we also generated estimates of site concordance factors in 50-kb windows and estimated 7 genomic predictor variables in for these same 50-kb windows, including: # parsimony informative sites, # singletons, proportion missing data, GC content, D-statistics, gene density, and recombination rate. This dataset is available as a csv file.
description: All files are either in FASTA or NEXUS format. FASTA format is a
 standard text format for nucleotide sequences. FASTA genome files are
 provided for each <em>Neodiprion</em> species. Using freely
 available scripts (https://github.com/LinnenLab/Herrig_etal_NeodiprionPhylogeny), these can be used to produce window-based and gene-based datasets in nexus format. Nexus is a standard format for character data for phylogenetic analysis. These can be used as input for many different phylogenetic programs. 
description: # Title of Dataset: ## Data From: Whole Genomes Reveal Evolutionary
 Relationships and Mechanisms Underlying Gene-Tree Discordance in
 Neodiprion Sawflies This project uses whole-genome data to infer
 evolutionary relationships in pine sawflies in the genus Neodiprion and
 understand the causes of gene-tree discordance. The data consist of a new
 chromosome-level assembly for one species (Neodiprion lecontei) and
 resequencing data for 18 additional species in the eastern North American
 Lecontei clade (N. abbotii, N. compar, N. dubious, N. excitans, N.
 fabricii, N. hetricki, N. knereri, N. maurus, N. merkeli, N. nigroscutum,
 N. pinetum, N. pinusrigidae, N. pratti, N. rugifrons, N. swainei, N.
 taedae, N. virginianus, and N. warreni) and a western North American
 outgroup species, Neodiprion autumnalis. To produce datasets for
 phylogenetic analysis, pseudo-genomes (reference based genome assemblies
 in N. lecontei physical coordinates) were produced for each of the 19
 species other than N. lecontei. The N. lecontei genome is available on
 NCBI (iyNeoLeco1.1 RefSeq GCF_021901455.1) and also provided here in FASTA
 format. The remaining 19 pseudo-genomes are provided here in FASTA format,
 with each species having end-to-end sequences for each of seven
 chromosomes, all in the same physical coordinate space as the N. lecontei
 genome (equivalent to a whole-genome alignment). We then used these
 genomes to produce phylogenomic datasets of several types: * a windowed
 dataset in which the genomes were sliced into non-overlapping windows of
 50kb * a gene-based dataset in which the N. lecontei gene annotation was
 used to pull out coding regions in all the genomes * SNP-based datasets in
 which all bi-allelic SNPs were called across the 20 species (N. lecontei +
 19 other Neodiprion), then filtered with various spacing requirements
 (none=all snps, every 1kb, 5kb, 10kb, 50kb, and 100kb). The widow-based
 and gene-based datasets produced thousands of nexus files, which are
 provided as zip archives (50kb.zip and filtered_transcripts.zip). The 6
 SNP datasets are provided as 6 nexus files. All scripts used to generate
 (a) pseudo-reference genomes, (b) windowed dataset, (c) gene dataset, and
 (d) snp datasets are provided as four zip archives that each include a
 read me file. We also summarized genomic variables in each window to
 explore predictors of site concordance factors. We then used a multiple
 regression approach to see which variables predicted discordance with the
 species trees. A csv file with scf for each node in the tree and each
 predictor variable is provided, as is the R code used to paint chromosomes
 by scf and perform multiple regression analyses. ## Description of the
 Data and file structure There are 4 types of files uploaded to Dryad:
 1.Fasta files for each of the 19 "pseudo-reference" Neodiprion
 genomes, plus the reference Neodiprion lecontei genome (end in
 ".fa"). We also include a gene annotation file for the reference
 genome (ends in "gff").  * for pseudo-reference genomes, the
 first term in the title is the species name. * All files have been
 filtered in the same way (indiciated by remaining terms in the file
 names): * heterozygous sites are coded using IUPAC sequencing codes *
 fifth iteration of the analysis pipeline * mimimum read depth of 4 *
 unusually high read depth (top 1%) coded as missing data 2.Nexus files for
 each of 6 SNP datasets (end in: ".nex") * first term in file
 indicates any required spacing between SNPs: * For all datasets, we
 excluded SNPs that were absent in more than 10% of the species and that
 had more than 2 alleles * allkb_genome.nex: All SNPs included (no minimum
 spacing) \_ 1kb_genome.nex: at least 1kb between SNPs * 5kb_genome.nex: at
 least 5kb between SNPs * 10kb_genome.nex: at least 10kb between SNPs *
 50kb_genome.nex: at least 50kb between SNPs * 100kb_genome.nex: at least
 100kb between SNPs 3.Zipped files containing alignments cut into 50kb
 windows (50kb.zip) and genes (filtered_transcripts.zip)- these can be used
 for downstream analyses in IQtree and ASTRAL 4.CSV file containing site
 concordance factors for each branch in a reference species tree and
 several genomic predictor variables. ## Sharing/access Information Links
 to other publicly accessible locations of the data: N. lecontei reference
 genome:
 [https://www.ncbi.nlm.nih.gov/genome/39861?genome_assembly_id=1780404](https://www.ncbi.nlm.nih.gov/genome/39861?genome_assembly_id=1780404) Code for generating datasets from pseudo-reference genomes: [https://github.com/LinnenLab/Herrig_etal_NeodiprionPhylogeny](https://github.com/LinnenLab/Herrig_etal_NeodiprionPhylogeny) Was data derived from another source? No If yes, list source(s): N/A