Evidence map›Paper›PMID 33900588›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2021

A Predictive Approach to Infer the Activity and Natural Variation of Retrotransposon Families in Plants.

Matthias Benoit, Hajk-Georg Drost

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
6.1field-weighted citation impact, top 4% of its field
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

11 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Reference-Guided De Novo Genome Assembly of the Flour BeetleInternational journal of molecular sciences · 2022
    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

2 authors at 2 institutions in 2 countries.

Matthias BenoitHoward Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
Hajk-Georg DrostComputational Biology Group, Department of Molecular Biology, Max Planck Institute for Developmental Biology, Tübingen, Germany. hajk-georg.drost@tuebingen.mpg.de.
Howard Hughes Medical Institute · USMax Planck Society · DE

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

Plant genomes harbor a particularly rich landscape of repetitive sequences. Transposable elements (TEs) represent a major fraction of this diversity and are intimately linked with plasticity and evolution of genomes across the tree of life (Fedoroff, Science 338:758-767, 2012). Amplification of Long Terminal Repeats (LTR) retrotransposons have shaped the genomic landscape by reshuffling genomic regions, altering gene expression, and providing new regulatory sequences, some of which have been instrumental for crop domestication and breeding (Lisch, Nat Rev Genet 14:49-61, 2013; Vitte et al., Brief Funct Genomics 13:276-295, 2014). While many retrotransposon families are still active within plant genomes, the repetitive nature of retrotransposons has hindered accurate annotation and kingdom-wide predictive assessment of their activity and molecular evolution. While it is natural for the first approach towards a genome annotation to characterize all regions of the genome and associate them with known structures such as particular genes, transposable elements, or other types of non-coding regions, such efforts can result in a large proportion of false-positive annotations when seeking for active loci. To overcome this issue, the next round of annotation efforts needs to include functional annotations based on rigorously defined sequence structures and protein domain compositions. In the context of retrotransposons, such a functional annotation can enable efforts to mobilize particular retrotransposon families in species living today and harness their mutagenic potency for crop improvement (Paszkowski, Curr Opin Biotechnol 32:200-206, 2015). For this purpose, we present a predictive analytical approach to infer the activity and natural variation of retrotransposon families in plants. This is achieved by applying a combination of software and molecular biology tools we developed for functional annotation, activity monitoring, and the assessment of the population structure of particular retrotransposon families in multiple plant species.

Indexed as

RetroelementsComputational BiologyEvolution, MolecularGenome, PlantMolecular Sequence AnnotationPlant BreedingSolanum lycopersicumRetroelementsFunctional annotationMolecular evolutionNatural variationPredictive annotationRetrotransposonsTransposable elements

Identifiers

PMID33900588
OpenAlexW3159955977

What OpenQuestion holds

Textmetadata
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.