ArticleBMC genomics2020
Effects of sample age on data quality from targeted sequencing of museum specimens: what are we capturing in time?
Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 24 citations in OpenAlex.
- Exploring the Quality of Historic DNA From Pinned Beetles.Ecology and evolution · 2026Article
- Improved molecular kit-based workflow to unlock the genomic potential of historical coral type specimens.BMC research notes · 2026Article
- Recovering Historical eDNA From Museum-Preserved Filter Feeders via Non-Destructive Metabarcoding.Molecular ecology resources · 2026Article
- A practical introduction to holo-omics.Cell reports methods · 2024Review
- The effect of missing data on evolutionary analysis of sequence capture bycatch, with application to an agricultural pest.Molecular genetics and genomics : MGG · 2024Article
- Retrieval of long DNA reads from herbarium specimens.AoB PLANTS · 2023Review
- Retrospective genomics highlights changes in genetic composition of tiger sharks (Galeocerdo cuvier) and potential loss of a south-eastern Australia population.Scientific reports · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
backgroundNext generation sequencing (NGS) can recover DNA data from valuable extant and extinct museum specimens. However, archived or preserved DNA is difficult to sequence because of its fragmented, damaged nature, such that the most successful NGS methods for preserved specimens remain sub-optimal. Improving wet-lab protocols and comprehensively determining the effects of sample age on NGS library quality are therefore of vital importance. Here, I examine the relationship between sample age and several indicators of library quality following targeted NGS sequencing of ~ 1300 loci using 271 samples of pinned moth specimens (Helicoverpa armigera) ranging in age from 5 to 117 years.
resultsI find that older samples have lower DNA concentrations following extraction and thus require a higher number of indexing PCR cycles during library preparation. When sequenced reads are aligned to a reference genome or to only the targeted region, older samples have a lower number of sequenced and mapped reads, lower mean coverage, and lower estimated library sizes, while the percentage of adapters in sequenced reads increases significantly as samples become older. Older samples also show the poorest capture success, with lower enrichment and a higher improved coverage anticipated from further sequencing.
conclusionsSample age has significant, measurable impacts on the quality of NGS data following targeted enrichment. However, incorporating a uracil-removing enzyme into the blunt end-repair step during library preparation could help to repair DNA damage, and using a method that prevents adapter-dimer formation may result in improved data yields.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.