Elucidating gene expression adaptation of phylogenetically divergent coral holobionts under heat stress

Abstract

As coral reefs struggle to survive under climate change, it is crucial to know whether they have the capacity to withstand changing conditions, particularly increasing seawater temperatures. Thermal tolerance requires the integrative response of the different components of the coral holobiont (coral host, algal photosymbiont, and associated microbiome). Here, using a controlled thermal stress experiment across three divergent Caribbean coral species, we attempt to dissect holobiont member metatranscriptome responses from coral taxa with different sensitivities to heat stress and use phylogenetic ANOVA to study the evolution of gene expression adaptation. We show that coral response to heat stress is a complex trait derived from multiple interactions among holobiont members. We identify host and photosymbiont genes that exhibit lineage-specific expression level adaptation and uncover potential roles for bacterial associates in supplementing the metabolic needs of the coral-photosymbiont duo during heat stress. Our results stress the importance of integrative and comparative approaches across a wide range of species to better understand coral survival under the predicted rise in sea surface temperatures.

Reef environments shape microbial partners in a highly connected coral population

“…Alternatively, it may be evidence of genotype by genotype interactions of host and bacteria occurring in the FR and not the BR due to stronger overall environmental pressures experienced closer to shore (figure 1b; electronic supplementary material, figures S1 and S2) [5,8,13]. Greater flexibility of microbial associations correlating with greater host genetic diversity hints at functional redundancy in both the host genome and bacterial community [70]. Metabolic supplementation by bacteria is a burgeoning area of inquiry and multiomic studies cross-referencing multiple holobiont members are becoming more common [70] and will continue to lead to new discoveries.…”

“…Greater flexibility of microbial associations correlating with greater host genetic diversity hints at functional redundancy in both the host genome and bacterial community [70]. Metabolic supplementation by bacteria is a burgeoning area of inquiry and multiomic studies cross-referencing multiple holobiont members are becoming more common [70] and will continue to lead to new discoveries.…”

Transcriptomic plasticity and symbiont shuffling underpin Pocillopora acclimatization across heat-stress regimes in the Pacific Ocean

“…The combination of RNA-seq and genomic datasets in this study allowed us to test whether variation in gene expression differed significantly among species (i.e., expression divergence) and/or within species across environments (i.e., expression diversity or plasticity). By treating gene expression levels as quantitative traits, we used the expression variance and evolution model (EVE) to parameterize the ratio (β) of population (i.e., within-species) to evolutionary (i.e., among-species) expression variance (Rohlfs and Nielsen 2015;Avila-Magaña et al 2021). This, in turn, allowed us to detect genes which may be under selection or which exhibit high plasticity across environments.…”

“…By considering expression profile variation within its proper evolutionary context, we tested for evidence of expression-level adaptation among the five coral lineages identified in this study. We used the expression variance and evolution (EVE) model (Rohlfs and Nielsen 2015;Avila-Magaña et al 2021), also referred to as Phylogenetic ANOVA, to identify genes with higher variance among than within lineages (divergent expression genes) and vice versa (diverse expression genes). The former set of genes display lineage-specific shifts in baseline expression suggestive of directional selection, potentially as a result of adaptive front-loading and/or altered gene copy number, and are therefore potential candidates for expression level adaptation.…”

CANT-HYD: A Curated Database of Phylogeny-Derived Hidden Markov Models for Annotation of Marker Genes Involved in Hydrocarbon Degradation

“…Metagenomes representing diverse environments such as petroleum reservoirs ( Hu et al, 2016 ; Nie et al, 2016 ; Liu et al, 2018 ; Christman et al, 2020 ), oil spill experimental microcosms ( Tan et al, 2015 ; Dombrowski et al, 2016 ), marine systems ( Orellana et al, 2017 ; Tully et al, 2018 ; Dong et al, 2019 , 2020 ), host-associated microbiomes ( Feigelman et al, 2017 ; Herman et al, 2020 ; Avila-Magaña et al, 2021 ), and other environments ( Yao et al, 2017 ; Zorz et al, 2019 ), were downloaded either as unassembled raw data from the NCBI SRA or as predicted gene sequences from the JGI Genome Portal ( Supplementary Table 4 ). Raw reads from unassembled metagenomes were filtered using BBDuk 1 for a minimum quality of 15 and a minimum read length of 150 bp.…”