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
A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
Research article
Bo Zheng
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5337-5477
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: The CLV3 / ESR-RELATED ( CLE ) gene family encodes small secreted peptides (SSPs) and plays vital roles in plant growth and development through cell-to-cell communication. The prediction and classification of CLE genes is challenging because of their low sequence similarity.
Results: We developed a machine learning-aided method for predicting CLE genes by using a CLE motif-specific residual score matrix and a novel clustering method based on the Euclidean distance of the 12 amino acid residues from CLE motifs in a site-weight dependent manner. In total, 2156 CLE candidates—including 627 novel candidates—were predicted from 69 plant species. The results from our CLE motif-based clustering are consistent with previous reports using the entire pre-propeptide. Characterization of CLE candidates provided systematic statistics on protein lengths, signal peptides, relative motif positions, amino acid compositions of different parts of the CLE precursor proteins, and decisive factors of CLE prediction. The approach taken here provides information on the evolution of the CLE gene family and provides evidence that the CLE and IDA/IDL genes share a common ancestor.
Conclusions: Our new approach is applicable to SSPs or other proteins with short conserved domains and hence, provides a useful tool for gene prediction, classification and evolutionary analysis.
Keywords
Peptide hormone, CLE, Machine learning, Euclidean distance, Gene prediction, Gene clustering, Evolution
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
This is a list of supplementary files associated with this preprint. Click to download.
- Additionalfile5.pdf
- Additionalfile19.xls
- Additionalfile9.pdf
- Additionalfile10.pdf
- Additionalfile6.pdf
- Additionalfile20.xls
- Additionalfile11.pdf
- Additionalfile15.xls
- Additionalfile12.xls
- Additionalfile16.xls
- Additionalfile17.xls
- Additionalfile7.pdf
- Additionalfile8.pdf
- Additionalfile18.xls
- Additionalfile13.xls
- Additionalfile14.xls
- Additionalfile4.pdf
- Additionalfile3.pdf
- Additionalfile1.pdf
- Additionalfile2.pdf
Loading...
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
Submission checks complete
On 01 Oct, 2020
Editorial decision: Accept
On 29 Sep, 2020
No comments provided
Review #1 received
Received 16 Sep, 2020
Reviewer #1 agreed
On 15 Sep, 2020
Editor assigned
On 14 Sep, 2020
Reviewers invited
Invitations sent on 14 Sep, 2020
Submission checks complete
On 13 Sep, 2020
Editor invited
On 13 Sep, 2020
Version 1
Posted 22 Jan, 2020
No comments provided
Editorial decision: Minor revision
On 21 Aug, 2020
Review #2 received
Received 17 Aug, 2020
Reviewer #2 agreed
On 03 Aug, 2020
Review #1 received
Received 08 Jun, 2020
Reviewer #1 agreed
On 09 Feb, 2020
Reviewers invited
Invitations sent on 06 Feb, 2020
Editor assigned
On 14 Jan, 2020
Submission checks complete
On 13 Jan, 2020
Editor invited
On 13 Jan, 2020
First submitted
On 11 Jan, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Epigenetics & Genomics
Learn more about our company.
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
Bo Zheng
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5337-5477
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
Submission checks complete
On 01 Oct, 2020
Editorial decision: Accept
On 29 Sep, 2020
No comments provided
Review #1 received
Received 16 Sep, 2020
Reviewer #1 agreed
On 15 Sep, 2020
Editor assigned
On 14 Sep, 2020
Reviewers invited
Invitations sent on 14 Sep, 2020
Submission checks complete
On 13 Sep, 2020
Editor invited
On 13 Sep, 2020
Version 1
Posted 22 Jan, 2020
No comments provided
Editorial decision: Minor revision
On 21 Aug, 2020
Review #2 received
Received 17 Aug, 2020
Reviewer #2 agreed
On 03 Aug, 2020
Review #1 received
Received 08 Jun, 2020
Reviewer #1 agreed
On 09 Feb, 2020
Reviewers invited
Invitations sent on 06 Feb, 2020
Editor assigned
On 14 Jan, 2020
Submission checks complete
On 13 Jan, 2020
Editor invited
On 13 Jan, 2020
First submitted
On 11 Jan, 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: The CLV3 / ESR-RELATED ( CLE ) gene family encodes small secreted peptides (SSPs) and plays vital roles in plant growth and development through cell-to-cell communication. The prediction and classification of CLE genes is challenging because of their low sequence similarity.
Results: We developed a machine learning-aided method for predicting CLE genes by using a CLE motif-specific residual score matrix and a novel clustering method based on the Euclidean distance of the 12 amino acid residues from CLE motifs in a site-weight dependent manner. In total, 2156 CLE candidates—including 627 novel candidates—were predicted from 69 plant species. The results from our CLE motif-based clustering are consistent with previous reports using the entire pre-propeptide. Characterization of CLE candidates provided systematic statistics on protein lengths, signal peptides, relative motif positions, amino acid compositions of different parts of the CLE precursor proteins, and decisive factors of CLE prediction. The approach taken here provides information on the evolution of the CLE gene family and provides evidence that the CLE and IDA/IDL genes share a common ancestor.
Conclusions: Our new approach is applicable to SSPs or other proteins with short conserved domains and hence, provides a useful tool for gene prediction, classification and evolutionary analysis.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
This is a list of supplementary files associated with this preprint. Click to download.
- Additionalfile5.pdf
- Additionalfile19.xls
- Additionalfile9.pdf
- Additionalfile10.pdf
- Additionalfile6.pdf
- Additionalfile20.xls
- Additionalfile11.pdf
- Additionalfile15.xls
- Additionalfile12.xls
- Additionalfile16.xls
- Additionalfile17.xls
- Additionalfile7.pdf
- Additionalfile8.pdf
- Additionalfile18.xls
- Additionalfile13.xls
- Additionalfile14.xls
- Additionalfile4.pdf
- Additionalfile3.pdf
- Additionalfile1.pdf
- Additionalfile2.pdf
Loading...