Evidence map›Paper›PMID 37131874›Full record

ArticleArXiv2023

De novo reconstruction of satellite repeat units from sequence data.

Yujie Zhang, Justin Chu, Haoyu Cheng, Heng Li

Abstract readPreprint
In one paragraph

Article in ArXiv, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Yujie ZhangHarvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA.
Justin ChuDepartment of Data Science, Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA 02215, USA.
Haoyu ChengDepartment of Data Science, Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA 02215, USA.
Heng LiDepartment of Data Science, Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA 02215, USA.

Funding

Advanced computational methods in analyzing high-throughput sequencing dataR01HG010040 · NHGRI · DANA-FARBER CANCER INST · PI Heng Li · 2018 to 2026
$3.7M
The construction and utility of reference pan-genome graphsU01HG010961 · NHGRI · DANA-FARBER CANCER INST · PI LI, HENG, PATEN, BENEDICT · 2020 to 2023
$3.2M
NHGRI NIH HHS R01 HG010040NHGRI NIH HHS U01 HG010961
6 · The paper itself

Abstract

Satellite DNA are long tandemly repeating sequences in a genome and may be organized as high-order repeats (HORs). They are enriched in centromeres and are challenging to assemble. Existing algorithms for identifying satellite repeats either require the complete assembly of satellites or only work for simple repeat structures without HORs. Here we describe Satellite Repeat Finder (SRF), a new algorithm for reconstructing satellite repeat units and HORs from accurate reads or assemblies without prior knowledge on repeat structures. Applying SRF to real sequence data, we showed that SRF could reconstruct known satellites in human and well-studied model organisms. We also found satellite repeats are pervasive in various other species, accounting for up to 12% of their genome contents but are often underrepresented in assemblies. With the rapid progress on genome sequencing, SRF will help the annotation of new genomes and the study of satellite DNA evolution even if such repeats are not fully assembled.

Identifiers

PMID37131874
PMCPMC10153287

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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.