Evidence map›Paper›PMID 30180802›Full record

ArticleBMC genomics2018

Linked read technology for assembling large complex and polyploid genomes.

Alina Ott, James C Schnable, Cheng-Ting Yeh, Linjiang Wu, Chao Liu, Heng-Cheng Hu, Clifton L Dalgard, Soumik Sarkar, Patrick S Schnable

Abstract read
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Genome assemblies of IndianNAR genomics and bioinformatics · 2025
    Article
  2. Article
  3. Review
  4. Article
  5. The Bioinformatic Applications of Hi-C and Linked Reads.Genomics, proteomics & bioinformatics · 2024
    Review
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  7. Article
  8. Review
  9. Article
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  11. Review
  12. 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

9 authors.

Alina OttDepartment of Agronomy, Iowa State University, Ames, IA, 50011, USA.
James C SchnableDepartment of Agriculture and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA.
Cheng-Ting YehDepartment of Agronomy, Iowa State University, Ames, IA, 50011, USA.
Linjiang WuDepartment of Mechanical Engineering, Iowa State University, Ames, IA, 50011, USA.
Chao LiuDepartment of Mechanical Engineering, Iowa State University, Ames, IA, 50011, USA.
Heng-Cheng HuThe American Genome Center, Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA.
Clifton L DalgardThe American Genome Center, Uniformed Services University of the Health Sciences, Bethesda, MD, 20814, USA.
Soumik SarkarDepartment of Mechanical Engineering, Iowa State University, Ames, IA, 50011, USA.
Patrick S SchnableDepartment of Agronomy, Iowa State University, Ames, IA, 50011, USA. schnable@iastate.edu.

Funding

National Science Foundation DGE1247194Office of Biotechnology, Iowa State University Not applicablePlant Sciences Institute, Iowa State University (US) Not applicable
6 · The paper itself

Abstract

backgroundShort read DNA sequencing technologies have revolutionized genome assembly by providing high accuracy and throughput data at low cost. But it remains challenging to assemble short read data, particularly for large, complex and polyploid genomes. The linked read strategy has the potential to enhance the value of short reads for genome assembly because all reads originating from a single long molecule of DNA share a common barcode. However, the majority of studies to date that have employed linked reads were focused on human haplotype phasing and genome assembly.

resultsHere we describe a de novo maize B73 genome assembly generated via linked read technology which contains ~ 172,000 scaffolds with an N50 of 89 kb that cover 50% of the genome. Based on comparisons to the B73 reference genome, 91% of linked read contigs are accurately assembled. Because it was possible to identify errors with > 76% accuracy using machine learning, it may be possible to identify and potentially correct systematic errors. Complex polyploids represent one of the last grand challenges in genome assembly. Linked read technology was able to successfully resolve the two subgenomes of the recent allopolyploid, proso millet (Panicum miliaceum). Our assembly covers ~ 83% of the 1 Gb genome and consists of 30,819 scaffolds with an N50 of 912 kb.

conclusionsOur analysis provides a framework for future de novo genome assemblies using linked reads, and we suggest computational strategies that if implemented have the potential to further improve linked read assemblies, particularly for repetitive genomes.

Indexed as

Genome, PlantPolyploidyHigh-Throughput Nucleotide SequencingPlant LeavesSequence Analysis, DNAZea maysGenome assemblyLong molecule sequencingPolyploid assembly

Identifiers

PMID30180802
PMCPMC6122573

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Registered trials

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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.