Evidence map›Paper›PMID 39838028›Full record

ReviewNature reviews. Genetics2025

Diversity and consequences of structural variation in the human genome.

Ryan L Collins, Michael E Talkowski

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing 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

47 citing papers in PubMed.

  1. Article
  2. Article
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  4. Review
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  6. Review
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  8. Article
  9. Genetic influences on haematopoiesis.Nature reviews. Genetics · 2026
    Review
  10. Somatic mutations and genome mosaicism in aging and disease.Experimental & molecular medicine · 2026
    Review
  11. Review
  12. Germline determinants of risk and molecular subtype in young-onset lung cancer.medRxiv : the preprint server for health sciences · 2026
    Article
  13. Article
  14. DNA Replication Errors Drive Genome-Wide Small Inverted Triplication Dynamics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  15. Observational
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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.

Ryan L CollinsCenter for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Michael E TalkowskiCenter for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA. talkowsk@broadinstitute.org.ORCID http://orcid.org/0000-0003-2889-0992

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The biomedical community is increasingly invested in capturing all genetic variants across human genomes, interpreting their functional consequences and translating these findings to the clinic. A crucial component of this endeavour is the discovery and characterization of structural variants (SVs), which are ubiquitous in the human population, heterogeneous in their mutational processes, key substrates for evolution and adaptation, and profound drivers of human disease. The recent emergence of new technologies and the remarkable scale of sequence-based population studies have begun to crystalize our understanding of SVs as a mutational class and their widespread influence across phenotypes. In this Review, we summarize recent discoveries and new insights into SVs in the human genome in terms of their mutational patterns, population genetics, functional consequences, and impact on human traits and disease. We conclude by outlining three frontiers to be explored by the field over the next decade.

Indexed as

Genetic VariationGenome, HumanGenomic Structural VariationEvolution, MolecularGenetics, PopulationHumansMutationPhenotype

Identifiers

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.