DOI: 10.5061/dryad.bnzs7h4p2
title: Data from: Going mobile: Using portable genomic technologies for PCR-free in situ species identification and real-time molecular systematics

description: Across the globe, anthropogenic environmental changes are threatening
 animal biodiversity and contributing to the emergence of vector-borne and
 zoonotic pathogens through host range shifts. To combat these challenges,
 accurate and timely biodiversity assessments and molecular species
 monitoring efforts are critical. Here, we document how implementation of a
 portable laboratory in combination with targeted long-read nanopore
 sequencing can facilitate in situ genomic and systematic analyses across
 several animal taxa. Working at two ecologically divergent field sites in
 Guyana, South America, we collected small mammals and blood-feeding
 insects, including bats, rodents, a marsupial, mosquitoes, and a
 phlebotomine sand fly. For each specimen sampled, genomic DNA was
 extracted in the field and used for preparation of nanopore sequencing
 libraries. For field sequencing, we utilized a novel software-based
 targeted sequencing approach—nanopore adaptive sampling (NAS)—that enabled
 selective sequencing of mitochondrial reads using mitogenome assemblies of
 related taxa as enrichment targets. Basecalled reads from our field
 sequencing experiments were used to assemble complete mitogenomes and to
 generate mitochondrial biomarker consensus gene sequences for all nine
 small mammals and four blood-feeding insects sequenced. Confirmatory
 molecular identifications were made with a combination of local nucleotide
 BLAST queries and maximum likelihood analyses using biomarker consensus
 sequences. Importantly, the mitogenome-based targeted sequencing
 strategies outlined here are amplification-free and allowed us to bypass
 time-consuming and potentially troublesome PCR-based methods in the field,
 streamlining library preparation, sequencing experiments, and on-site
 analyses. Our findings describe targeted sequencing with NAS as an
 effective tool for implementation into portable laboratories to widely
 enhance field-based biodiversity monitoring and rapid molecular species
 assessments across vertebrate and invertebrate hosts of consequential
 emerging pathogens.
description: # Data from: Going mobile: Using portable genomic technologies for
 PCR-free in situ species identification and real-time molecular
 systematics Dataset DOI:
 [10.5061/dryad.bnzs7h4p2](10.5061/dryad.bnzs7h4p2) ## Description of the
 data and file structure These sequence data were generated in the field
 between 5 – 21 June 2022, at two field sites in Guyana, South America, and
 include multiple species of field-collected small mammals and
 blood-feeding insects. Libraries were prepared for sequencing on flow
 cells with R9.4.1 chemistry and using the SQK-LSK109 library prep kit with
 EXP-NBD114 barcodes. Sequencing was performed on a Linux laptop with a 16x
 11th Gen Intel Core i7 processor, Nvidia GeForce RTX 3080 Ti laptop 16 GB
 GPU, and Ubuntu 18.04 OS. Adaptive sampling was enabled during sequencing
 experiments to target mitochondrial DNA for both insects and small mammals
 using whole mitogenome assembly files obtained through NCBI RefSeq and
 deposited here in FASTA format.  Raw sequence data contained here were
 post-hoc basecalled at each field site following completion of each
 sequencing experiment using the 'HAC' basecalling model within
 ONT's guppy basecaller v6.0.7. All code and shell commands used to
 perform quality filtering, read mapping, and downstream analyses are
 contained in the included HTML notebook.  ### Files and variables ####
 File: CUL01_allhac.fastq **Description:** Concatenated and HAC-basecalled
 reads for insect sample 'CUL01' #### File: CUL06_allhac.fastq
 **Description:** Concatenated and HAC-basecalled reads for insect sample
 'CUL06' #### File: TK217506_allhac.fastq
 **Description:** Concatenated and HAC-basecalled reads for rodent sample
 'TK217506' #### File: CUL02_allhac.fastq
 **Description:** Concatenated and HAC-basecalled reads for insect sample
 'CUL02' #### File: TK217513_allhac.fastq
 **Description:** Concatenated and HAC-basecalled reads for bat sample
 'TK217513' #### File: TK217507_allhac.fastq
 **Description:** Concatenated and HAC-basecalled reads for rodent sample
 'TK217507' #### File: TK217562_allhac.fastq
 **Description:** Concatenated and HAC-basecalled reads for bat sample
 'TK217562' #### File: TK217563_allhac.fastq
 **Description:** Concatenated and HAC-basecalled reads for bat sample
 'TK217563' #### File: TK217523_allhac.fastq
 **Description:** Concatenated and HAC-basecalled reads for bat sample
 'TK217523' #### File: TK217611_allhac.fastq
 **Description:** Concatenated and HAC-basecalled reads for bat sample
 'TK217611' #### File: TK217600_allhac.fastq
 **Description:** Concatenated and HAC-basecalled reads for bat sample
 'TK217600' #### File: TK217608_allhac.fastq
 **Description:** Concatenated and HAC-basecalled reads for marsupial
 sample 'TK217608' #### File: PHL01_allhac.fastq
 **Description:** Concatenated and HAC-basecalled reads for insect sample
 'PHL01' #### File: bat_cytb_alignment.phy
 **Description:** Multiple sequence alignment used for maximum likelihood
 analysis and containing field-generated cytb consensus sequences for all
 Chiroptera samples evaluated  #### File: culicidae_COI_alignment.phy
 **Description:** Multiple sequence alignment used for maximum likelihood
 analysis and containing field-generated COI consensus sequences for all
 Culicidae samples evaluated #### File: monodelphis_cytb_ualignment.phy
 **Description:** Multiple sequence alignment used for maximum likelihood
 analysis and containing field-generated cytb consensus sequences for the
 *Monodelphis* sample evaluated #### File: rattus_cytb_alignment.phy
 **Description:** Multiple sequence alignment used for maximum likelihood
 analysis and containing field-generated cytb consensus sequences for the
 two *Rattus* samples evaluated #### File: sandfly_COI_alignment.phy
 **Description:** Multiple sequence alignment used for maximum likelihood
 analysis and containing field-generated COI consensus sequences for the
 phlebotomine sand fly sample evaluated #### File:
 Kipp_etal_Computational_Notebook.html **Description:** Computational
 notebook containing all code and shell commands used to filter raw FASTQs,
 assembled mitochondrial genomes, and perform systematic analyses  ####
 File: mammal_mito20June2022.fasta **Description:** Adaptive sampling
 enrichment file containing assorted mammal reference mitochondrial genomes
 from NCBI RefSeq #### File: insect_mitoDec2022.fasta
 **Description:** Adaptive sampling enrichment file containing assorted
 insect reference mitochondrial genomes from NCBI RefSeq ## Code/software
 Code and shell commands used are contained in the accompanying HTML
 notebook.  ## Access information Other publicly accessible locations of
 the data: * Raw data will be deposited on NCBI SRA and consensus cytb and
 COI barcode sequences will be deposited on NCBI GenBank upon publicaiton
 Data was derived from the following sources: * Mitogenome enrichment FASTA
 reference files used to perform targeted sequencing experiments were
 derived from data deposited on NCBI RefSeq