DOI: 10.5061/dryad.51c59zwh3
title: Climate adaptation and genetic differentiation in the mosquito species <em>Culex tarsalis</em>

description: The increasing prevalence of vector-borne diseases around the world
 highlights the pressing need for an in-depth exploration of the genetic
 and environmental factors that shape the adaptability and widespread
 distribution of mosquito populations. This research focuses on Culex
 tarsalis, a principal vector for various viral diseases, including West
 Nile Virus (WNV). Through the development of a new reference genome and
 the examination of Restriction-Site Associated DNA sequencing (RAD-seq)
 data from over 300 individuals and 28 locations, we demonstrate that
 variables such as temperature, evaporation rates, and the density of
 vegetation significantly impact the genetic makeup of Cx. tarsalis
 populations. Among the alleles most strongly associated with environmental
 factors is a nonsynonymous mutation in a key gene related to circadian
 rhythms.  These results offer new insights into the mechanisms of
 spread and adaptation in a key North American vector species, which is
 poised to become a growing health threat to both humans and animals in the
 face of ongoing climate change.
description: <strong>Sample Collection</strong>
 Individual mosquitoes were trapped and collected from 28
 different locations across the United States and Canada as part of the
 North American Mosquito Project (NAMP).  All samples used in this study
 were collected in 2012 between the months of April and October.
 <strong>Genome Sequencing, Assembly, and
 Annotation</strong> An F4  population was used to
 generate the reference genome assembly, and high molecular weight DNA was
 extracted and sequenced on a Pacific Biosciences (PacBio) RS II
 (University of Delaware). Thirty-five SMRT cells were generated. The
 resulting reads provided 76X coverage of the ~790Mb Cx. tarsalis genome,
 and were assembled with MECAT. Gene annotation was completed by MAKER
 using EST and protein data from the Culex quinquefasciatus and Aedes
 aegypti mosquitoes. Sequences were downloaded from the NCBI Taxonomy
 database and both Trinotate and InterProScan were used for functional
 annotation of the MAKER predicted genes.  The annotated assembly was
 assessed for completeness and quality using BUSCO and QUAST.
 <strong>RAD-Seq Library Preparation, Sequencing, and SNP
 Calling</strong> DNA was extracted from
 individual mosquitoes and libraries were constructed for Restriction-site
 Associated DNA Sequencing (RAD-Seq) according to previously established
 protocols.  The SbfI enzyme was used to digest purified DNA, and
 individual samples were barcoded prior to Illumina sequencing.  Raw
 sequencing reads were subsequently filtered to remove any reads with an
 uncalled base, an error in the restriction enzyme cut site, or with an
 average Phred quality score less than 20 over 15 consecutive nucleotides. 
 Filtered reads were then de-multiplexed using the Stacks software
 package. After de-multiplexing, raw reads from each
 individual were aligned to the draft assembly of the Cx. tarsalis genome
 using BWA MEM, and individuals with poor mapping rates (less than 50%)
 were excluded from subsequent analyses.  The mapped reads for the
 remaining 378 samples were then merged using the Samtools pipeline and
 SNPs were called using the GATK HaplotypeCaller.  The SNPs were filtered
 using VCFtools v0.1.12a to retain only sites with a minimum average
 individual read depth of 10X and a maximum of 20% missing data, resulting
 in a total of 457,387 sites.  Individual samples were then filtered again
 to remove individuals with missing data at more than 50% of the remaining
 SNP sites, leaving 322 samples from 28 different locations for further
 analysis.<br> <br> <strong>Environmental
 data</strong> Climate data was extracted from the
 ERA5-Land monthly averaged dataset provided by the Copernicus Climate
 Change Service. The original dataset was characterized by a temporal
 resolution of 1 hour and a native spatial resolution of 9 km on a reduced
 Gaussian grid (TCo1279). To facilitate broader accessibility and
 suitability for diverse analyses, the data underwent regridding to a
 regular lat-lon grid with a finer resolution of 0.1x0.1 degrees.
description: # Climate adaptation and genetic differentiation in the mosquito species
 *Culex tarsalis*
 [https://doi.org/10.5061/dryad.51c59zwh3](https://doi.org/10.5061/dryad.51c59zwh3) ## Description of the data and file structure The data were stored in 8 different files. 1. bi_20missing_filtSNP_maf_005.recode.vcf File Details * File Name: `bi_10missing_filtSNP_maf_005.recode.vcf` * File Format: VCF (Variant Call Format) v4.2 * Reference genome: `culex.60x.contigs.fasta` (from header `##reference=...`) * Source software (inferred): GATK-style headers present (e.g., `QD`, `MQ`, `FS`, `ReadPosRankSum`, `RGQ`, `PL`, `SB`, `END`, `NON_REF`) suggest generation with GATK/HaplotypeCaller (gVCF→VCF workflow). * Samples: 7 individuals → `13-2, 13-3, 13-4, 13-5, 13-6, 13-7, 13-8` Data Description   -The VCF contains standard columns: * \#CHROM – Contig/chromosome * POS – 1-based position * ID – Variant identifier * REF – Reference allele * ALT – Alternate allele(s) (header includes `NON_REF`, typical of gVCF provenance) * QUAL – Variant quality * FILTER – Filter status (e.g., `PASS`, `LowQual`) * INFO – Site-level annotations (see below) * FORMAT – Per-sample field definitions * Sample columns (7): one column per sample with genotype/coverage fields  Specific Fields in INFO (observed in header) * AN (Integer): Total number of called alleles * BaseQRankSum (Float): Alt vs Ref base quality Z-score * ClippingRankSum (Float): Alt vs Ref hard-clip Z-score * DP (Integer): Approximate read depth * DS (Flag): Downsampled indicator * END (Integer): End of gVCF block (present due to gVCF origin) * ExcessHet (Float): Excess heterozygosity (Phred-scaled p-value) * FS (Float): Strand bias (Fisher’s test, Phred-scaled) * HaplotypeScore (Float): Two-haplotype consistency (legacy) * InbreedingCoeff (Float): Inbreeding coefficient * MLEAC (A,Integer): MLE allele counts (per ALT) * MLEAF (A,Float): MLE allele frequencies (per ALT) * MQ (Float): RMS mapping quality * MQRankSum (Float): Alt vs Ref mapping quality Z-score * QD (Float): Quality by depth * RAW_MQ (Float): Raw MQ * ReadPosRankSum (Float): Alt vs Ref read position Z-score * SOR (Float): Strand odds ratio   Specific Fields in FORMAT (observed in header) * GT (String): Genotype (e.g., `0/0`, `0/1`, `1/1`) * GQ (Integer): Genotype quality * AD (R,Integer): Allelic depths (REF, ALT[, ALT2...]) * DP (Integer): Sample read depth * PL (G,Integer): Phred-scaled genotype likelihoods * MIN_DP (Integer): Minimum depth within gVCF block * PGT (String): Physical phase genotype tag * PID (String): Physical phase group ID * RGQ (Integer): Ref genotype confidence (gVCF) * SB (4,Integer): Strand-bias components per sample How to Open and Analyze  Common tools you can use: * bcftools – view headers/records, filter, reindex, summarize * vcftools – site/sample filters, summary stats * GATK – additional filtering/annotation (matches header conventions) * IGV – visualize variants against `culex.60x.contigs.fasta` * PLINK/PLINK 2 – convert to BED/PGEN for population analyses 2. land_monthly_climate_2009_2012_partial_canada.nc This file is a 4-year monthly climate forcing dataset (2009–2012) on a ~0.25° grid, containing wind, temperature, precipitation, radiation, evaporation, soil water, and vegetation indices, produced by ECMWF and stored in NetCDF format. Dataset Summary File format: NetCDF (CF-1.6 conventions)\ Engine: netCDF4\ Temporal coverage: January 2009 – December 2012 (240 monthly time steps)\ Spatial coverage: Latitude 281 points (degrees north), Longitude 601 points (degrees east)\ Resolution: 0.25° × 0.25° grid (approximate, inferred from 281 × 601 grid over continental region) Dimensions * time: 240 (monthly steps from Jan 2009 to Dec 2012) * latitude: 281 points 1. longitude: 601 points Variables All variables are stored as 3D arrays with dimensions `(time, latitude, longitude)`. * u10: 10 m U wind component (m s⁻¹) * v10: 10 m V wind component (m s⁻¹) * t2m: 2 m air temperature (K) * evabs: Evaporation from bare soil (m of water equivalent) * lai_hv: Leaf area index, high vegetation (m² m⁻²) * lai_lv: Leaf area index, low vegetation (m² m⁻²) * src: Skin reservoir content (m of water equivalent) * sf: Snowfall (liquid water equivalent, m of water equivalent) * ssr: Surface net solar radiation (J m⁻²) * sro: Surface runoff (m) * e: Total evaporation (m of water equivalent) * tp: Total precipitation (m) * swvl1: Volumetric soil water, top layer (m³ m⁻³) -how to open this file The dataset is provided in NetCDF format (CF-1.6 conventions), which is a self-describing, machine-independent format widely used in climate and environmental sciences. You can open and explore the file using a variety of software: * Python: with the [xarray](https://docs.xarray.dev) or netCDF4 libraries 3. The Culex-tarsalis-v1.0.a1-merged-2019-08-30-4-45-01.gff3 * Annotation file for the assembled *Culex tarsalis* genome, it is in the gene feature format (.gff3), generated by MAKER. This file can be read by most text editors and should be recognized by standard bioinformatics software designed to run on genomic files.   4. Culex-tarsalis-v1.0.a1.5d6405151b078-interproscan.tab  This is the output of InterProScan which uses public databases to predict functions of annotated genes and proteins. This file is in tab-delimited text format and can be read by most standard text editors. 5.  Ctarsalis_sample_w_GPS_climate_average_new_filtered_id_region.csv Format: Tab-delimited text (TSV)\ Rows: One row per biological sample / site (IDs align with your VCF sample IDs)\ Columns: Site metadata, land-cover composition (%), and climate variables averaged over 2009–2012 at each site’s coordinates\ Coordinate system: Latitude/Longitude in decimal degrees (WGS84)\ Temporal coverage of climate means: Jan 2009 – Dec 2012 extracted from land_monthly_climate_2009_2012_partial_canada.nc 6. Ctar-Clemson_vs_Davis_Assembly_Orthogroups.txt This is the output of OrthoFinder. It was generated using predicted protein sequences from 2 different versions of the *Cx. tarsalis* genome (the one generated in this paper and another earlier published genome from Main et al. 2021). This is a tab-delimited text format file with one row for each orthogroup and columns listing all genes in that orthogroup. 7. Culex_vs_Drosophila_Orthogroups.txt This is the output of OrthoFinder. It was generated using predicted protein sequences from the *Cx. tarsalis* in this paper and the most recent version of the *Drosophila melanogaster* genome. This is a tab-delimited text format file with one row for each orthogroup and columns listing all genes in that orthogroup. 8. culex_assembly.fasta This is the assembled genome used in the manuscript. This was generated using MECAT and it is standard fasta format. The raw sequence data used in the assembly is available in NCBI under PRJNA1124366. ## Code/Software The code uses the data above are presented in github: [https://github.com/Afei99357/Culex_Tarsalis_GWAS_manuscript.git](https://github.com/Afei99357/Culex_Tarsalis_GWAS_manuscript.git) ## Version changes **24-April-2025:** Added additional 2 files. the first 1 (Ctar-Clemson_vs_Davis_Assembly_Orthogroups.txt) is the orthogroup results betwen Culex tarsalis and Davis assembly. The second file (Culex_vs_Drosophila_Orthogroups.txt) is the orthgroup results between Culex and Drosophila. **25-September-2025**: Added 1 file for Cx. tarsalis genome assembly FASTA file