Less is more in herbarium-inclusive molecular ecology

This dataset relates to the manuscript entitled "Less is more in herbarium-inclusive molecular ecology: Universal kits capture considerable intraspecific variation", available as a pre-print at BioRXiv: ... The study describes a critical comparison between customised and universal approaches of target capture sequencing in herbarium genomics below the species level. A target capture sequencing tool (Hyb-Seq) was designed for genotyping apomictic clonal lineages of dandelions (Taraxacum officinale), where loci from three approaches were included: A) loci from a previous genotyping-by-sequencing (GBS) study on Taraxacum; B) genes custom selected based on evolutionary adaptive potential; C) loci from universal kits (Angiosperms-353 and Compositae-1061). The genotyping accuracy of these different sets of loci was tested on a set of five apomictic clonal lineages (ACLs) of Taraxacum officinale, including several members with the same multi-locus microsatellite genotype. This dataset comprises important background information to the accessions used in the study, the design of the target capture sequencing tool, scripts and bioinformatic pipelines used in the design of the tool and the analysis of the pilot dataset, and detailed results that were used in the production of the manuscript. Contents: Details of the design of the target capture tool for Taraxacum officinale Pipeline for selecting loci Bioinformatic logbooks detailing the process for the selection and curation of loci to be included in the tool Final design of the tool (an overview of the loci; fasta file with sequences of all the baits) Python scripts to make BED files to split genes into introns and exons Final reference sequences (for sequence read mapping purposes) for all different categories of loci Accession information, for samples used in the generation of the pilot dataset Detailed GPS coordinates for all samples and R script for producing the distribution map in the manuscript Details of the library preparation procedure for the generation of the pilot dataset Details of the bioinformatic analysis of the pilot dataset Results of the MapDamage analysis to check for DNA damage patterns (fragmentation and deamination) in all samples Shell and R scripts detailing the steps performed in the bioinformatic analysis Trimming and filtering of low-quality reads Mapping sequence reads to reference Variant calling & filtering, and counting Analysis of Molecular Variance (AMOVA) Principal Component Analysis (PCA) Genetic distance calculations Results of the sequencing and read mapping Results of the AMOVA, PCA and genetic distance calculations Abstract for the study: Target capture sequencing has enhanced the study of plant evolution and molecular ecology, particularly through the access to degraded DNA from herbarium specimens. Universal “off-the-shelf” kits, such as Angiosperms-353, are cheap and readily available but are considered to expose insufficient variation below the species level. However, this remains to be tested in a direct comparison with customised approaches below the species level. In this study, near-identical genotypes from both herbarium and fresh material of the common dandelion (apomictic lineages in Taraxacum officinale F.H.Wigg.) are characterised with customised and universal approaches of target capture sequencing. An RNA-bait panel was designed to capture (i) highly variable loci normally obtained with a Genotyping-by-Sequencing (GBS) approach customised for dandelions; (ii) custom selected genes with potential for environmental adaptation, likely to harbour intraspecific genetic variation; (iii) conserved exons from universal kits (Angiosperms-353; Compositae-COS). Although exons from universal kits yield considerably less intraspecific genetic variation than both customised approaches, they still provided sufficient genetic variation to discriminate between near-identical genotypes of the same apomictic lineage. Given that universal kits save time, money, and the need for genomic reference data, this approach is recommended to increase the number of samples under budgetary constraints while still capturing considerable levels of intraspecific genetic variation.