Evidence map›Paper›PMID 34418978›Full record

ArticleBMC genomics2021

Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing.

Henrik Christiansen, Franz M Heindler, Bart Hellemans, Quentin Jossart, Francesca Pasotti, Henri Robert, Marie Verheye, Bruno Danis, Marc Kochzius, Frederik Leliaert and 6 more

Abstract read
In one paragraph

Article in BMC genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. SNP-RFLP Markers for the Study ofEcology and evolution · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Henrik ChristiansenLaboratory of Biodiversity and Evolutionary Genomics, KU Leuven, Leuven, Belgium. henrik.christiansen@kuleuven.be.
Franz M HeindlerLaboratory of Biodiversity and Evolutionary Genomics, KU Leuven, Leuven, Belgium.
Bart HellemansLaboratory of Biodiversity and Evolutionary Genomics, KU Leuven, Leuven, Belgium.
Quentin JossartMarine Biology Group, Vrije Universiteit Brussel (VUB), Brussels, Belgium.
Francesca PasottiMarine Biology Research Group, Ghent University, Ghent, Belgium.
Henri RobertOD Nature, Royal Belgian Institute of Natural Sciences, Brussels, Belgium.
Marie VerheyeOD Nature, Royal Belgian Institute of Natural Sciences, Brussels, Belgium.
Bruno DanisMarine Biology Laboratory, Université Libre de Bruxelles (ULB), Brussels, Belgium.
Marc KochziusMarine Biology Group, Vrije Universiteit Brussel (VUB), Brussels, Belgium.
Frederik LeliaertMarine Biology Research Group, Ghent University, Ghent, Belgium.
Camille MoreauMarine Biology Laboratory, Université Libre de Bruxelles (ULB), Brussels, Belgium.
Tasnim PatelOD Nature, Royal Belgian Institute of Natural Sciences, Brussels, Belgium.
Anton P Van de PutteLaboratory of Biodiversity and Evolutionary Genomics, KU Leuven, Leuven, Belgium.
Ann VanreuselMarine Biology Research Group, Ghent University, Ghent, Belgium.
Filip A M VolckaertLaboratory of Biodiversity and Evolutionary Genomics, KU Leuven, Leuven, Belgium.
Isa SchönOD Nature, Royal Belgian Institute of Natural Sciences, Brussels, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenome-wide data are invaluable to characterize differentiation and adaptation of natural populations. Reduced representation sequencing (RRS) subsamples a genome repeatedly across many individuals. However, RRS requires careful optimization and fine-tuning to deliver high marker density while being cost-efficient. The number of genomic fragments created through restriction enzyme digestion and the sequencing library setup must match to achieve sufficient sequencing coverage per locus. Here, we present a workflow based on published information and computational and experimental procedures to investigate and streamline the applicability of RRS.

resultsIn an iterative process genome size estimates, restriction enzymes and size selection windows were tested and scaled in six classes of Antarctic animals (Ostracoda, Malacostraca, Bivalvia, Asteroidea, Actinopterygii, Aves). Achieving high marker density would be expensive in amphipods, the malacostracan target taxon, due to the large genome size. We propose alternative approaches such as mitogenome or target capture sequencing for this group. Pilot libraries were sequenced for all other target taxa. Ostracods, bivalves, sea stars, and fish showed overall good coverage and marker numbers for downstream population genomic analyses. In contrast, the bird test library produced low coverage and few polymorphic loci, likely due to degraded DNA.

conclusionsPrior testing and optimization are important to identify which groups are amenable for RRS and where alternative methods may currently offer better cost-benefit ratios. The steps outlined here are easy to follow for other non-model taxa with little genomic resources, thus stimulating efficient resource use for the many pressing research questions in molecular ecology.

Indexed as

MetagenomicsResearch DesignAnimalsGenomeGenomicsHumansSequence Analysis, DNABiodiversityGenome scanGenotyping by sequencingIn silico digestionRADseqSouthern Ocean

Identifiers

PMID34418978
PMCPMC8380342

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.