Evidence map›Paper›PMID 28137744›Full record

ArticleGenome biology and evolution2017

Targeted Capture of Complete Coding Regions across Divergent Species.

Ryan K Schott, Bhawandeep Panesar, Daren C Card, Matthew Preston, Todd A Castoe, Belinda S W Chang

Abstract read
In one paragraph

Article in Genome biology and evolution, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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  15. Capturing variation inApplications in plant sciences · 2018
    Article
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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

6 authors.

Ryan K SchottDepartment of Ecology and Evolutionary Biology, University of Toronto, Ontario, Canada.
Bhawandeep PanesarDepartment of Cell and Systems Biology, University of Toronto, Ontario, Canada.
Daren C CardDepartment of Biology, University of Texas at Arlington, Arlington, TX.
Matthew PrestonDepartment of Cell and Systems Biology, University of Toronto, Ontario, Canada.
Todd A CastoeDepartment of Biology, University of Texas at Arlington, Arlington, TX.
Belinda S W ChangDepartment of Ecology and Evolutionary Biology, University of Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite continued advances in sequencing technologies, there is a need for methods that can efficiently sequence large numbers of genes from diverse species. One approach to accomplish this is targeted capture (hybrid enrichment). While these methods are well established for genome resequencing projects, cross-species capture strategies are still being developed and generally focus on the capture of conserved regions, rather than complete coding regions from specific genes of interest. The resulting data is thus useful for phylogenetic studies, but the wealth of comparative data that could be used for evolutionary and functional studies is lost. Here, we design and implement a targeted capture method that enables recovery of complete coding regions across broad taxonomic scales. Capture probes were designed from multiple reference species and extensively tiled in order to facilitate cross-species capture. Using novel bioinformatics pipelines we were able to recover nearly all of the targeted genes with high completeness from species that were up to 200 myr divergent. Increased probe diversity and tiling for a subset of genes had a large positive effect on both recovery and completeness. The resulting data produced an accurate species tree, but importantly this same data can also be applied to studies of molecular evolution and function that will allow researchers to ask larger questions in broader phylogenetic contexts. Our method demonstrates the utility of cross-species approaches for the capture of full length coding sequences, and will substantially improve the ability for researchers to conduct large-scale comparative studies of molecular evolution and function.

Indexed as

Evolution, MolecularOpen Reading FramesAlgorithmsAnimalsBirdsReptilesSequence AlignmentSequence Analysis, DNAcomparative studies of protein-coding genescross-species sequence capturehybrid enrichment of complete coding sequences

Identifiers

PMID28137744
PMCPMC5381602

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.