Evidence map›Paper›PMID 36526983›Full record

ArticleBMC bioinformatics2022

NPGREAT: assembly of human subtelomere regions with the use of ultralong nanopore reads and linked-reads.

Eleni Adam, Desh Ranjan, Harold Riethman

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 4 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Eleni AdamDepartment of Computer Science, Old Dominion University, Norfolk, VA, USA. eadam002@odu.edu.
Desh RanjanDepartment of Computer Science, Old Dominion University, Norfolk, VA, USA.
Harold RiethmanMedical Diagnostic and Translational Sciences, Old Dominion University, Norfolk, VA, USA.
Old Dominion University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHuman subtelomeric DNA regulates the length and stability of adjacent telomeres that are critical for cellular function, and contains many gene/pseudogene families. Large evolutionarily recent segmental duplications and associated structural variation in human subtelomeres has made complete sequencing and assembly of these regions difficult to impossible for many loci, complicating or precluding a wide range of genetic analyses to investigate their function.

resultsWe present a hybrid assembly method, NanoPore Guided REgional Assembly Tool (NPGREAT), which combines Linked-Read data with mapped ultralong nanopore reads spanning subtelomeric segmental duplications to potentially overcome these difficulties. Linked-Read sets of DNA sequences identified by matches with 1-copy subtelomere sequence adjacent to segmental duplications are assembled and extended into the segmental duplication regions using Regional Extension of Assemblies using Linked-Reads (REXTAL). Mapped telomere-containing ultralong nanopore reads are then used to provide contiguity and correct orientation for matching REXTAL sequence contigs as well as identification/correction of any misassemblies. Our method was tested for a subset of representative subtelomeres with ultralong nanopore read coverage in the haploid human cell line CHM13. A 10X Linked-Read dataset from CHM13 was combined with ultralong nanopore reads from the same genome to provide improved subtelomere assemblies. Comparison of Nanopore-only assemblies using SHASTA with our NPGREAT assemblies in the distal-most subtelomere regions showed that NPGREAT produced higher-quality and more complete assemblies than SHASTA alone when these regions had low ultralong nanopore coverage (such as cases where large segmental duplications were immediately adjacent to (TTAGGG) tracts).

conclusionIn genomic regions with large segmental duplications adjacent to telomeres, NPGREAT offers an alternative economical approach to improving assembly accuracy and coverage using linked-read datasets when more expensive HiFi datasets of 10-20 kb reads are unavailable.

Indexed as

NanoporesGenomicsHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNATelomereHybrid assemblyLinked-readsNanoporeSegmental duplicationsSubtelomeresTandem repeatsTelomeres

Identifiers

PMID36526983
PMCPMC9758922
OpenAlexW4312066974

What OpenQuestion holds

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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.