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Research article
Shin-Han Shiu
Corresponding Author
ORCiD: https://orcid.org/0000-0001-6470-235X
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
Availability of plant genome sequences has led to significant advances. However, with few exceptions, the great majority of existing genome assemblies are derived from short read sequencing technologies with highly uneven read coverages indicative of sequencing and assembly issues that could significantly impact any downstream analysis of plant genomes. In tomato for example, 0.6% (5.1 Mb) and 9.7% (79.6 Mb) of short-read based assembly had significantly higher and lower coverage compared to background, respectively.
Results
To understand what the causes may be for such uneven coverage, we first established machine learning models capable of predicting genomic regions with variable coverages and found that high coverage regions tend to have higher simple sequence repeat and tandem gene densities compared to background regions. To determine if the high coverage regions were misassembled, we examined a recently available tomato long-read based assembly and found that 27.8% (1.41 Mb) of high coverage regions were potentially misassembled of duplicate sequences, compared to 1.4% in background regions. In addition, using a predictive model that can distinguish correctly and incorrectly assembled high coverage regions, we found that misassembled, high coverage regions tend to be flanked by simple sequence repeats, pseudogenes, and transposon elements.
Conclusions
Our study provides insights on the causes of variable coverage regions and a quantitative assessment of factors contributing to plant genome misassembly when using short reads.
Keywords
Genome misassembly, read coverage, machine learning, Solanum lycopersicum
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Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Genomics.
No community comments so far
Editorial decision: Accept
On 18 Jan, 2021
Review #1 received
Received 12 Jan, 2021
Editor assigned
On 04 Jan, 2021
Reviewers invited
Invitations sent on 04 Jan, 2021
Reviewer #1 agreed
On 04 Jan, 2021
Submission checks complete
On 04 Jan, 2021
Editor invited
On 04 Jan, 2021
No comments provided
Review #2 received
Received 31 Dec, 2020
Review #1 received
Received 27 Dec, 2020
Reviewer #2 agreed
On 23 Dec, 2020
Reviewer #1 agreed
On 21 Dec, 2020
Editor assigned
On 21 Dec, 2020
Reviewers invited
Invitations sent on 21 Dec, 2020
Submission checks complete
On 21 Dec, 2020
Editor invited
On 21 Dec, 2020
Version 1
Posted 10 Jun, 2020
No comments provided
Editorial decision: Major revision
On 20 Nov, 2020
Review #2 received
Received 17 Nov, 2020
Reviewer #2 agreed
On 04 Nov, 2020
Review #1 received
Received 23 Aug, 2020
Reviewer #1 agreed
On 01 Jul, 2020
Reviewers invited
Invitations sent on 29 Jun, 2020
Editor assigned
On 29 May, 2020
Submission checks complete
On 28 May, 2020
Editor invited
On 28 May, 2020
First submitted
On 27 May, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Epigenetics & Genomics
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A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
See the published version of this preprint at BMC Genomics.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Shin-Han Shiu
Corresponding Author
ORCiD: https://orcid.org/0000-0001-6470-235X
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Genomics.
No community comments so far
Editorial decision: Accept
On 18 Jan, 2021
Review #1 received
Received 12 Jan, 2021
Editor assigned
On 04 Jan, 2021
Reviewers invited
Invitations sent on 04 Jan, 2021
Reviewer #1 agreed
On 04 Jan, 2021
Submission checks complete
On 04 Jan, 2021
Editor invited
On 04 Jan, 2021
No comments provided
Review #2 received
Received 31 Dec, 2020
Review #1 received
Received 27 Dec, 2020
Reviewer #2 agreed
On 23 Dec, 2020
Reviewer #1 agreed
On 21 Dec, 2020
Editor assigned
On 21 Dec, 2020
Reviewers invited
Invitations sent on 21 Dec, 2020
Submission checks complete
On 21 Dec, 2020
Editor invited
On 21 Dec, 2020
Version 1
Posted 10 Jun, 2020
No comments provided
Editorial decision: Major revision
On 20 Nov, 2020
Review #2 received
Received 17 Nov, 2020
Reviewer #2 agreed
On 04 Nov, 2020
Review #1 received
Received 23 Aug, 2020
Reviewer #1 agreed
On 01 Jul, 2020
Reviewers invited
Invitations sent on 29 Jun, 2020
Editor assigned
On 29 May, 2020
Submission checks complete
On 28 May, 2020
Editor invited
On 28 May, 2020
First submitted
On 27 May, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Epigenetics & Genomics
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Genomics.
Background
Availability of plant genome sequences has led to significant advances. However, with few exceptions, the great majority of existing genome assemblies are derived from short read sequencing technologies with highly uneven read coverages indicative of sequencing and assembly issues that could significantly impact any downstream analysis of plant genomes. In tomato for example, 0.6% (5.1 Mb) and 9.7% (79.6 Mb) of short-read based assembly had significantly higher and lower coverage compared to background, respectively.
Results
To understand what the causes may be for such uneven coverage, we first established machine learning models capable of predicting genomic regions with variable coverages and found that high coverage regions tend to have higher simple sequence repeat and tandem gene densities compared to background regions. To determine if the high coverage regions were misassembled, we examined a recently available tomato long-read based assembly and found that 27.8% (1.41 Mb) of high coverage regions were potentially misassembled of duplicate sequences, compared to 1.4% in background regions. In addition, using a predictive model that can distinguish correctly and incorrectly assembled high coverage regions, we found that misassembled, high coverage regions tend to be flanked by simple sequence repeats, pseudogenes, and transposon elements.
Conclusions
Our study provides insights on the causes of variable coverage regions and a quantitative assessment of factors contributing to plant genome misassembly when using short reads.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
This is a list of supplementary files associated with this preprint. Click to download.
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