Background: Corals are capable of launching diverse immune defenses at the site of direct contact with pathogens, but the molecular mechanisms of this activity and the colony-wide effects of such stressors remain poorly understood. Here we compared gene expression profiles in eight healthy Acropora hyacinthus colonies against eight colonies exhibiting tissue loss commonly associated with white syndromes, all collected from a natural reef environment near Palau. Two types of tissues were sampled from diseased corals: visibly affected and apparently healthy. Results: Tag-based RNA-Seq followed by weighted gene co-expression network analysis identified groups of co-regulated differentially expressed genes between all health states (disease lesion, apparently healthy tissues of diseased colonies, and fully healthy). Differences between healthy and diseased tissues indicate activation of several innate immunity and tissue repair pathways accompanied by reduced calcification and the switch towards metabolic reliance on stored lipids. Unaffected parts of diseased colonies, although displaying a trend towards these changes, were not significantly different from fully healthy samples. Still, network analysis identified a group of genes, suggestive of altered immunity state, that were specifically up-regulated in unaffected parts of diseased colonies. Conclusions: Similarity of fully healthy samples to apparently healthy parts of diseased colonies indicates that systemic effects of white syndromes on A. hyacinthus are weak, which implies that the coral colony is largely able to sustain its physiological performance despite disease. The genes specifically up-regulated in unaffected parts of diseased colonies, instead of being the consequence of disease, might be related to the originally higher susceptibility of these colonies to naturally occurring white syndromes.

BackgroundModel-based analysis of data from quantitative reverse-transcription PCR (qRT-PCR) is potentially more powerful and versatile than traditional methods. Yet existing model-based approaches cannot properly deal with the higher sampling variances associated with low-abundant targets, nor do they provide a natural way to incorporate assumptions about the stability of control genes directly into the model-fitting process.ResultsIn our method, raw qPCR data are represented as molecule counts, and described using generalized linear mixed models under Poisson-lognormal error. A Markov Chain Monte Carlo (MCMC) algorithm is used to sample from the joint posterior distribution over all model parameters, thereby estimating the effects of all experimental factors on the expression of every gene. The Poisson-based model allows for the correct specification of the mean-variance relationship of the PCR amplification process, and can also glean information from instances of no amplification (zero counts). Our method is very flexible with respect to control genes: any prior knowledge about the expected degree of their stability can be directly incorporated into the model. Yet the method provides sensible answers without such assumptions, or even in the complete absence of control genes. We also present a natural Bayesian analogue of the “classic” analysis, which uses standard data pre-processing steps (logarithmic transformation and multi-gene normalization) but estimates all gene expression changes jointly within a single model. The new methods are considerably more flexible and powerful than the standard delta-delta Ct analysis based on pairwise t-tests.ConclusionsOur methodology expands the applicability of the relative-quantification analysis protocol all the way to the lowest-abundance targets, and provides a novel opportunity to analyze qRT-PCR data without making any assumptions concerning target stability. These procedures have been implemented as the MCMC.qpcr package in R.

Success and impact metrics in science are based on a system that perpetuates sexist and racist “rewards” by prioritizing citations and impact factors. These metrics are flawed and biased against already marginalized groups and fail to accurately capture the breadth of individuals’ meaningful scientific impacts. We advocate shifting this outdated value system to advance science through principles of justice, equity, diversity, and inclusion. We outline pathways for a paradigm shift in scientific values based on multidimensional mentorship and promoting mentee well-being. These actions will require collective efforts supported by academic leaders and administrators to drive essential systemic change.

Disease causes significant coral mortality worldwide; however, factors responsible for intraspecific variation in disease resistance remain unclear. We exposed fragments of eight Acropora millepora colonies (genotypes) to putatively pathogenic bacteria (Vibrio spp.). Genotypes varied from zero to >90% mortality, with bacterial challenge increasing average mortality rates 4–6 fold and shifting the microbiome in favor of stress-associated taxa. Constitutive immunity and subsequent immune and transcriptomic responses to the challenge were more prominent in high-mortality individuals, whereas low-mortality corals remained largely unaffected and maintained expression signatures of a healthier condition (i.e., did not launch a large stress response). Our results suggest that lesions appeared due to changes in the coral pathobiome (multiple bacterial species associated with disease) and general health deterioration after the biotic disturbance, rather than the direct activity of any specific pathogen. If diseases in nature arise because of weaknesses in holobiont physiology, instead of the virulence of any single etiological agent, environmental stressors compromising coral condition might play a larger role in disease outbreaks than is currently thought. To facilitate the diagnosis of compromised individuals, we developed and independently cross-validated a biomarker assay to predict mortality based on genes whose expression in asymptomatic individuals coincides with mortality rates.

Background: Corals are capable of launching diverse immune defenses at the site of direct contact with pathogens, but the molecular mechanisms of this activity and the colony-wide effects of such stressors remain poorly understood. Here we compared gene expression profiles in eight healthy Acropora hyacinthus colonies against eight colonies exhibiting tissue loss commonly associated with white syndromes, all collected from a natural reef environment near Palau. Two types of tissues were sampled from diseased corals: visibly affected and apparently healthy. Results: Tag-based RNA-Seq followed by weighted gene co-expression network analysis identified groups of co-regulated differentially expressed genes between all health states (disease lesion, apparently healthy tissues of diseased colonies, and fully healthy). Differences between healthy and diseased tissues indicate activation of several innate immunity and tissue repair pathways accompanied by reduced calcification and the switch towards metabolic reliance on stored lipids. Unaffected parts of diseased colonies, although displaying a trend towards these changes, were not significantly different from fully healthy samples. Still, network analysis identified a group of genes, suggestive of altered immunity state, that were specifically up-regulated in unaffected parts of diseased colonies. Conclusions: Similarity of fully healthy samples to apparently healthy parts of diseased colonies indicates that systemic effects of white syndromes on A. hyacinthus are weak, which implies that the coral colony is largely able to sustain its physiological performance despite disease. The genes specifically up-regulated in unaffected parts of diseased colonies, instead of being the consequence of disease, might be related to the originally higher susceptibility of these colonies to naturally occurring white syndromes.