Evolutionary gain and loss of a plant pattern-recognition receptor for HAMP recognition
- University of Washington, United States
- Salk Institute for Biological Studies, United States
- Utah Valley University, United States
Abstract
As a first step in innate immunity, pattern recognition receptors (PRRs) recognize distinct pathogen and herbivore-associated molecular patterns and mediate activation of immune responses, but specific steps in the evolution of new PRR sensing functions are not well understood. We employed comparative genomic and functional analyses to define evolutionary events leading to the sensing of the herbivore-associated peptide inceptin (In11) by the PRR Inceptin Receptor (INR) in legume plant species. Existing and de novo genome assemblies revealed that the presence of a functional INR gene corresponded with ability to respond to In11 across ~53 million years (my) of evolution. In11 recognition is unique to the clade of Phaseoloid legumes, and only a single clade of INR homologues from Phaseoloids was functional in a heterologous model. The syntenic loci of several non-Phaseoloid outgroup species nonetheless contain non-functional INR-like homologues, suggesting that an ancestral gene insertion event and diversification preceded the evolution of a specific INR receptor function ~28 mya. Chimeric and ancestrally reconstructed receptors indicated that 16 amino acid differences in the C1 leucine-rich repeat domain and C2 intervening motif mediate gain of In11 recognition. Thus, high PRR diversity was likely followed by a small number of mutations to expand innate immune recognition to a novel peptide elicitor. Analysis of INR evolution provides a model for functional diversification of other germline-encoded PRRs.
Data availability
Sequencing data and genome assemblies have been deposited on NCBI under the following bioprojects: PRJNA817236, PRJNA817235, PRJNA817241, PRJNA817237 and PRJNA817234.Figure 1 - Suppl. data 2 contains the numerical data used to generate this figure.
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Hylodesmum podocarpum, de novogenome assemblyNCBI BioProject, PRJNA817236.
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Canavalia ensiformis, genome assemblyNCBI BioProject, PRJNA817235.
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Macroptilium lathyroides Raw sequence readsNCBI BioProject, PRJNA817241.
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Cyamopsis tetragonoloba, de novo genome assemblyNCBI BioProject, PRJNA817237.
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Pachyrhizus erosus, de novo genome assemblyNCBI BioProject, PRJNA817234.
Article and author information
Author details
Anthony G K Garcia
Funding
Belgian American Educational Foundation (/)
- Simon Snoeck
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Rebecca Bart, The Donald Danforth Plant Science Center, United States
Publication history
- Preprint posted: April 1, 2022 (view preprint)
- Received: June 14, 2022
- Accepted: October 28, 2022
- Accepted Manuscript published: November 15, 2022 (version 1)
- Version of Record published: December 2, 2022 (version 2)
Copyright
© 2022, Snoeck et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Evolutionary gain and loss of a plant pattern-recognition receptor for HAMP recognition
eLife 11:e81050.
https://doi.org/10.7554/eLife.81050
Further reading
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Cardiometabolic diseases encompass a range of interrelated conditions that arise from underlying metabolic perturbations precipitated by genetic, environmental, and lifestyle factors. While obesity, dyslipidaemia, smoking, and insulin resistance are major risk factors for cardiometabolic diseases, individuals still present in the absence of such traditional risk factors, making it difficult to determine those at greatest risk of disease. Thus, it is crucial to elucidate the genetic, environmental, and molecular underpinnings to better understand, diagnose, and treat cardiometabolic diseases. Much of this information can be garnered using systems genetics, which takes population-based approaches to investigate how genetic variance contributes to complex traits. Despite the important advances made by human genome-wide association studies (GWAS) in this space, corroboration of these findings has been hampered by limitations including the inability to control environmental influence, limited access to pertinent metabolic tissues, and often, poor classification of diseases or phenotypes. A complementary approach to human GWAS is the utilisation of model systems such as genetically diverse mouse panels to study natural genetic and phenotypic variation in a controlled environment. Here, we review mouse genetic reference panels and the opportunities they provide for the study of cardiometabolic diseases and related traits. We discuss how the post-GWAS era has prompted a shift in focus from discovery of novel genetic variants to understanding gene function. Finally, we highlight key advantages and challenges of integrating complementary genetic and multi-omics data from human and mouse populations to advance biological discovery.
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Background: Causality between plasma triglyceride (TG) levels and atherosclerotic cardiovascular disease (ASCVD) risk remains controversial despite more than four decades of study and two recent landmark trials, STRENGTH and REDUCE-IT. Further unclear is the association between TG levels and non-atherosclerotic diseases across organ systems.
Methods: Here, we conducted a phenome-wide, two-sample Mendelian randomization (MR) analysis using inverse-variance weighted (IVW) regression to systematically infer the causal effects of plasma TG levels on 2,600 disease traits in the European ancestry population of UK Biobank. For replication, we externally tested 221 nominally significant associations (p < 0.05) in an independent cohort from FinnGen. To account for potential horizontal pleiotropy and the influence of invalid instrumental variables, we performed sensitivity analyses using MR-Egger regression, weighted median estimator, and MR-PRESSO. Finally, we used multivariable MR controlling for correlated lipid fractions to distinguish the independent effect of plasma TG levels.
Results: Our results identified 7 disease traits reaching Bonferroni-corrected significance in both the discovery (p < 1.92 × 10-5) and replication analyses (p < 2.26 × 10-4), suggesting a causal relationship between plasma TG levels and ASCVDs, including coronary artery disease (OR 1.33, 95% CI 1.24-1.43, p = 2.47 × 10-13). We also identified 12 disease traits that were Bonferroni-significant in the discovery or replication analysis and at least nominally significant in the other analysis (p < 0.05), identifying plasma TG levels as a novel potential risk factor for 9 non-ASCVD diseases, including uterine leiomyoma (OR 1.19, 95% CI 1.10-1.29, p = 1.17 × 10-5).
Conclusions: Taking a phenome-wide, two-sample MR approach, we identified causal associations between plasma TG levels and 19 disease traits across organ systems. Our findings suggest unrealized drug repurposing opportunities or adverse effects related to approved and emerging TG-lowering agents, as well as mechanistic insights for future studies.
Funding: RD is supported by the National Institute of General Medical Sciences of the National Institutes of Health (NIH) (R35-GM124836) and the National Heart, Lung, and Blood Institute of the NIH (R01-HL139865 and R01-HL155915).
