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Computational identification of receptor-like kinases “RLK” and receptor-like proteins “RLP” in legumes
BACKGROUND: In plants, the plasma membrane is enclosed by the cell wall and anchors RLK and RLP proteins, which play a fundamental role in perception of developmental and environmental cues and are crucial in plant development and immunity. These plasma membrane receptors belong to large gene/protei...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333395/ https://www.ncbi.nlm.nih.gov/pubmed/32620079 http://dx.doi.org/10.1186/s12864-020-06844-z |
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author | Restrepo-Montoya, Daniel Brueggeman, Robert McClean, Phillip E. Osorno, Juan M. |
author_facet | Restrepo-Montoya, Daniel Brueggeman, Robert McClean, Phillip E. Osorno, Juan M. |
author_sort | Restrepo-Montoya, Daniel |
collection | PubMed |
description | BACKGROUND: In plants, the plasma membrane is enclosed by the cell wall and anchors RLK and RLP proteins, which play a fundamental role in perception of developmental and environmental cues and are crucial in plant development and immunity. These plasma membrane receptors belong to large gene/protein families that are not easily classified computationally. This detailed analysis of these plasma membrane proteins brings a new source of information to the legume genetic, physiology and breeding research communities. RESULTS: A computational approach to identify and classify RLK and RLP proteins is presented. The strategy was evaluated using experimentally-validated RLK and RLP proteins and was determined to have a sensitivity of over 0.85, a specificity of 1.00, and a Matthews correlation coefficient of 0.91. The computational approach can be used to develop a detailed catalog of plasma membrane receptors (by type and domains) in several legume/crop species. The exclusive domains identified in legumes for RLKs are WaaY, APH Pkinase_C, LRR_2, and EGF, and for RLP are L-lectin LPRY and PAN_4. The RLK-nonRD and RLCK subclasses are also discovered by the methodology. In both classes, less than 20% of the total RLK predicted for each species belong to this class. Among the 10-species evaluated ~ 40% of the proteins in the kinome are RLKs. The exclusive legume domain combinations identified are B-Lectin/PR5K domains in G. max, M. truncatula, V. angularis, and V. unguiculata and a three-domain combination B-lectin/S-locus/WAK in C. cajan, M. truncatula, P. vulgaris, V. angularis. and V. unguiculata. CONCLUSIONS: The analysis suggests that about 2% of the proteins of each genome belong to the RLK family and less than 1% belong to RLP family. Domain diversity combinations are greater for RLKs compared with the RLP proteins and LRR domains, and the dual domain combination LRR/Malectin were the most frequent domain for both groups of plasma membrane receptors among legume and non-legume species. Legumes exclusively show Pkinase extracellular domains, and atypical domain combinations in RLK and RLP compared with the non-legumes evaluated. The computational logic approach is statistically well supported and can be used with the proteomes of other plant species. |
format | Online Article Text |
id | pubmed-7333395 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-73333952020-07-06 Computational identification of receptor-like kinases “RLK” and receptor-like proteins “RLP” in legumes Restrepo-Montoya, Daniel Brueggeman, Robert McClean, Phillip E. Osorno, Juan M. BMC Genomics Research Article BACKGROUND: In plants, the plasma membrane is enclosed by the cell wall and anchors RLK and RLP proteins, which play a fundamental role in perception of developmental and environmental cues and are crucial in plant development and immunity. These plasma membrane receptors belong to large gene/protein families that are not easily classified computationally. This detailed analysis of these plasma membrane proteins brings a new source of information to the legume genetic, physiology and breeding research communities. RESULTS: A computational approach to identify and classify RLK and RLP proteins is presented. The strategy was evaluated using experimentally-validated RLK and RLP proteins and was determined to have a sensitivity of over 0.85, a specificity of 1.00, and a Matthews correlation coefficient of 0.91. The computational approach can be used to develop a detailed catalog of plasma membrane receptors (by type and domains) in several legume/crop species. The exclusive domains identified in legumes for RLKs are WaaY, APH Pkinase_C, LRR_2, and EGF, and for RLP are L-lectin LPRY and PAN_4. The RLK-nonRD and RLCK subclasses are also discovered by the methodology. In both classes, less than 20% of the total RLK predicted for each species belong to this class. Among the 10-species evaluated ~ 40% of the proteins in the kinome are RLKs. The exclusive legume domain combinations identified are B-Lectin/PR5K domains in G. max, M. truncatula, V. angularis, and V. unguiculata and a three-domain combination B-lectin/S-locus/WAK in C. cajan, M. truncatula, P. vulgaris, V. angularis. and V. unguiculata. CONCLUSIONS: The analysis suggests that about 2% of the proteins of each genome belong to the RLK family and less than 1% belong to RLP family. Domain diversity combinations are greater for RLKs compared with the RLP proteins and LRR domains, and the dual domain combination LRR/Malectin were the most frequent domain for both groups of plasma membrane receptors among legume and non-legume species. Legumes exclusively show Pkinase extracellular domains, and atypical domain combinations in RLK and RLP compared with the non-legumes evaluated. The computational logic approach is statistically well supported and can be used with the proteomes of other plant species. BioMed Central 2020-07-03 /pmc/articles/PMC7333395/ /pubmed/32620079 http://dx.doi.org/10.1186/s12864-020-06844-z Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Restrepo-Montoya, Daniel Brueggeman, Robert McClean, Phillip E. Osorno, Juan M. Computational identification of receptor-like kinases “RLK” and receptor-like proteins “RLP” in legumes |
title | Computational identification of receptor-like kinases “RLK” and receptor-like proteins “RLP” in legumes |
title_full | Computational identification of receptor-like kinases “RLK” and receptor-like proteins “RLP” in legumes |
title_fullStr | Computational identification of receptor-like kinases “RLK” and receptor-like proteins “RLP” in legumes |
title_full_unstemmed | Computational identification of receptor-like kinases “RLK” and receptor-like proteins “RLP” in legumes |
title_short | Computational identification of receptor-like kinases “RLK” and receptor-like proteins “RLP” in legumes |
title_sort | computational identification of receptor-like kinases “rlk” and receptor-like proteins “rlp” in legumes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333395/ https://www.ncbi.nlm.nih.gov/pubmed/32620079 http://dx.doi.org/10.1186/s12864-020-06844-z |
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