Evidence map›Paper›PMID 40234028›Full record

ArticleGenome research2025

Building better genome annotations across the tree of life.

Adam H Freedman, Timothy B Sackton

Abstract read
In one paragraph

Article in Genome research, 2025. 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. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. A fixed mutation in the respiratory complex I impairs mitochondrial bioenergetics in the endangered Apennine brown bear.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  7. Linking phenotype to genotype using comprehensive genomic comparisons.Current opinion in genetics & development · 2025
    Review
  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

2 authors.

Adam H FreedmanInformatics Group, Faculty of Arts and Sciences, Harvard University, Cambridge, Massachusetts 02138, USA adamfreedman@fas.harvard.edu.ORCID 0000-0003-4714-3925
Timothy B SacktonInformatics Group, Faculty of Arts and Sciences, Harvard University, Cambridge, Massachusetts 02138, USA.ORCID 0000-0003-1673-9216

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent technological advances in long-read DNA sequencing accompanied by reduction in costs have made the production of genome assemblies financially achievable and computationally feasible, such that genome assembly no longer represents the major hurdle to evolutionary analysis for most nonmodel organisms. Now, the more difficult challenge is to properly annotate a draft genome assembly once it has been constructed. The primary challenge to annotations is how to select from the myriad gene prediction tools that are currently available, determine what kinds of data are necessary to generate high-quality annotations, and evaluate the quality of the annotation. To determine which methods perform the best and to determine whether the inclusion of RNA-seq data is necessary to obtain a high-quality annotation, we generated annotations with 12 different methods for 21 different species spanning vertebrates, plants, and insects. We found that the annotation transfer method TOGA, BRAKER3, and the RNA-seq assembler StringTie were consistently top performers across a variety of metrics including BUSCO recovery, CDS length, and false-positive rate, with the exception that TOGA performed less well in some monocots with respect to BUSCO recovery. The choice of which of the top-performing methods will depend upon the feasibility of whole-genome alignment, availability of RNA-seq data, importance of capturing noncoding parts of the transcriptome, and, when whole-genome alignment is not feasible, the relative performance in BUSCO recovery between BRAKER3 and StringTie. When whole-genome alignment is not feasible, inclusion of RNA-seq data will lead to substantial improvements to genome annotations.

Indexed as

GenomeGenomicsMolecular Sequence AnnotationAnimalsHumansPlantsSoftwareVertebrates

Identifiers

PMID40234028
PMCPMC12047660

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.