Evidence map›Paper›PMID 31919520›Full record

ArticleGigaScience2020

Multifaceted Hi-C benchmarking: what makes a difference in chromosome-scale genome scaffolding?

Mitsutaka Kadota, Osamu Nishimura, Hisashi Miura, Kaori Tanaka, Ichiro Hiratani, Shigehiro Kuraku

Abstract read
In one paragraph

Article in GigaScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
–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

39 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Silver chimaera genome highlights lineage-specific sex chromosome and opsin gene evolution in holocephalans.DNA research : an international journal for rapid publication of reports on genes and genomes · 2026
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  7. Article
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  9. Sharks and rays have the oldest vertebrate sex chromosome with unique sex determination mechanisms.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  10. Article
  11. Review
  12. Article
  13. Read Mapping for Hi-C Analysis.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  14. CWL-Based Analysis Pipeline for Hi-C Data: From FASTQ Files to Matrices.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  15. Article
  16. Article
  17. Chromosomal DNA sequences of the Pacific saury genome: versatile resources for fishery science and comparative biology.DNA research : an international journal for rapid publication of reports on genes and genomes · 2024
    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

6 authors.

Mitsutaka KadotaLaboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research (BDR), Kobe 650-0047, Japan.
Osamu NishimuraLaboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research (BDR), Kobe 650-0047, Japan.
Hisashi MiuraLaboratory for Developmental Epigenetics, RIKEN BDR, Kobe 650-0047, Japan.
Kaori TanakaLaboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research (BDR), Kobe 650-0047, Japan.
Ichiro HirataniLaboratory for Developmental Epigenetics, RIKEN BDR, Kobe 650-0047, Japan.
Shigehiro KurakuLaboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research (BDR), Kobe 650-0047, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHi-C is derived from chromosome conformation capture (3C) and targets chromatin contacts on a genomic scale. This method has also been used frequently in scaffolding nucleotide sequences obtained by de novo genome sequencing and assembly, in which the number of resultant sequences rarely converges to the chromosome number. Despite its prevalent use, the sample preparation methods for Hi-C have not been intensively discussed, especially from the standpoint of genome scaffolding.

resultsTo gain insight into the best practice of Hi-C scaffolding, we performed a multifaceted methodological comparison using vertebrate samples and optimized various factors during sample preparation, sequencing, and computation. As a result, we identified several key factors that helped improve Hi-C scaffolding, including the choice and preparation of tissues, library preparation conditions, the choice of restriction enzyme(s), and the choice of scaffolding program and its usage.

conclusionsThis study provides the first comparison of multiple sample preparation kits/protocols and computational programs for Hi-C scaffolding by an academic third party. We introduce a customized protocol designated "inexpensive and controllable Hi-C (iconHi-C) protocol," which incorporates the optimal conditions identified in this study, and demonstrate this technique on chromosome-scale genome sequences of the Chinese softshell turtle Pelodiscus sinensis.

Indexed as

Chromosome MappingSoftwareAnimalsChromatinChromosomesComputational BiologyGene Expression ProfilingGenomicsHigh-Throughput Nucleotide SequencingIn Situ HybridizationTurtlesChromatinchromosomesgenome scaffoldingHi-Cproximity-guided assemblysoftshell turtle

Identifiers

PMID31919520
PMCPMC6952475

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.