The Pennsylvania State University

The Graduate School

Eberly College of Science

UNDERSTANDING TEMPERATURE ACCLIMATION IN SYMBIODINIUM:

AN INTERDISCIPLINARY APPROACH

A Dissertation in Biology by Erika Díaz-Almeyda

© 2016 Erika Díaz-Almeyda

Submitted in Partial Fulfillment of the Requirements for the Degree of

Doctor of Philosophy

December 2016

The dissertation of Erika Díaz-Almeyda was reviewed and approved* by the following:

Monica Medina Associate Professor of Biology The Pennsylvania State University Dissertation Advisor

Charles R. Fisher Professor and Distinguished Senior Scholar of Biology The Pennsylvania State University Chair of Committee

Todd C. LaJeunesse Associate Professor of Biology The Pennsylvania State University

Mark Guiltinan Professor of Plant Molecular Biology and Adjunct Professor of Biology The Pennsylvania State University

Tracy Langkilde Professor of Biology The Pennsylvania State University Department Head of Biology

*Signatures are on file in the Graduate School

ii Abstract

I quantified the thermotolerance in 11 cultures from different populations of five species of Symbiodinium clade A. we grew cultures at 26°C and 32°C over 18 days, measuring growth and photochemical efficiency (Fv/Fm). Thermotolerance was not restricted to a single species but it was widespread across species and cultures, showing a gradient from susceptible to tolerant. All cultures at 32°C decreased growth and Fv/Fm. To test the synergistic effect of temperature and light, we cultured three strains (tolerant, intermediate, and susceptible) in five different light intensities at 26°C and 32°C. Strains surviving stressful light and temperature exhibited less growth and quicker damage by light. To investigate the mechanisms behind thermoacclimation, we cultured S. microadriaticum (CassKB8) with intermediate thermotolerance at 26°C and 32°C. Gene expression was explored first using cDNA microarrays before (day -2), and during acclimation (day 6 and 16). Differentially expressed genes (DEG) due to increased temperature were time dependent. DEG on day 16 were likely a result of the start of the stationary phase in culture. Similarly, RNA-Seq data (day 5 and 7) suggest temporal variation in gene expression with major changes in heat-shock proteins and chaperones.

Retrotransposons were highly expressed on day 7, indicating high stress during thermal exposure. Adaptation to higher temperatures is not restricted to a single clade or species but it is widespread within species. However, acclimating to higher temperatures compromises health and increases chaperone activity.

iii Table of Contents

List of Figures ...... vii

List of Tables ...... x

Acknowledgments ...... xii

Chapter 1. Introduction ...... 1 Symbiodinium diversity ...... 2 Symbiodinium gene expression changes under high temperature conditions...... 4 Symbiodinium as a model organism to understand the effects of climate change ..... 6 Table ...... 8 References ...... 9

Chapter 2. Within and among species variation in thermotolerance and photoacclimation in Symbiodinium dinoflagellates ...... 17 Abstract ...... 17 Introduction ...... 17 Methods ...... 20 Symbiodinium cultures: growth conditions ...... 20 High temperature acclimation: experimental design ...... 21 High temperature acclimation and photoacclimation: experimental design ...... 21 Photochemical Efficiency ...... 22 Population Growth ...... 22 Statistical analysis ...... 22 Results ...... 23 Extensive variation in temperature sensitivity within and among species ...... 23 The ability to acclimate to high temperature is not species specific ...... 24 High temperature acclimation has a cost ...... 24 The effect of light and temperature in photochemistry and growth ...... 25 Discussion ...... 26 Widespread thermotolerance variation within species from clade A lineage ...... 26 Combined effect of light and temperature in physiological acclimation ...... 28 Conclusions ...... 28

iv Tables ...... 30 Figures ...... 33 Supplementary Figures ...... 38 References ...... 41

Chapter 3. Temporal transcriptomic response of Symbiodinium microadriaticum (CassKB8) under high temperature acclimation ...... 47 Introduction ...... 47 Materials & Methods ...... 50 Symbiodinium growth and experimental design ...... 50 Physiological measurements ...... 50 Microarray experiment ...... 51 RNAseq experiment ...... 52 Results ...... 54 Symbiodinium microadriaticum acclimates to high temperature...... 54 RNA-Seq libraries quality and assembly ...... 55 Differential expression is higher over time than between temperatures ...... 55 Functions differentially expressed at high temperature during multiple time points .. 56 Time-dependent gene expression ...... 58 Photosynthetic functions under thermal acclimation ...... 59 Nitrogen metabolism ...... 60 Chaperone and heat-shock proteins express time and temperature specific ...... 60 Other important DEG ...... 61 Discussion ...... 61 Physiological acclimation to high temperature has a cost in growth...... 61 Differential expression is higher with time rather than with high temperature ...... 62 Thermal acclimation affects photosynthetic functions under thermal stress ...... 62 Temporal dependent gene expression ...... 63 Chaperones and heat-shock proteins ...... 64 Other important DEG ...... 66 Conclusions ...... 68 Figures ...... 70 Tables ...... 80 Supplemental Figures ...... 89

v Supplemental Tables ...... 91 References ...... 102

Chapter 4. Discussion ...... 111

vi List of Figures

Figure 2. 1 Average growth rate (A) and photochemical efficiency (B) at 32 ºC of five Symbiodinium spp. over a 17-day period. SspA4 = Symbiodinium sp. A4 (1 strain), Smic = S. microadriaticum (n=3 pooled strains), Snec = S. necroappetens (2 pooled strains), Spil = S. pilosum (3 pooled strains), Stri = S. tridacnidorum (2 pooled strains), and All (11 strains pooled). Bars depict one standard deviation of the mean...... 33

Figure 2. 2 Multinomial logistic model showing the cumulative probability of each strain as a function of growth rate (A) and photochemical efficiency of 17 days of experiment (B). Growth rate was measured at 32 ºC (k, Whole model test, DF=1, p< 0.0001) Photochemical efficiency was measured at 32 ºC (Fv/Fm, Whole model test, DF=1, p< 0.0001). Smic = Symbiodinium microadriaticum, Spil = S. pilosum, SspA4 = Symbiodinium sp. A4, Snec = S. necroappetens, Stri= S. tridacnidorum. Color indicates strains thermotolerance from dark blue (thermotolerant) to dark red (sensitive)...... 34

Figure 2. 3 Simplified phylogeny of Symbiodinium clade A phylogeny inferred from ITS1, ITS2, and 5.8S rDNA sequences (LaJeunesse, 2001, LaJeunesse 2015, Lee et al, 2015). All data for growth rate and three days of Fv/Fm measurements after 12 days at 32 ºC is showed for each strain. (One-Way ANOVA, F10,310= 3604.73 , p< 0.0001, Tukey-Kramer HSD)...... 35

Figure 2. 4 Relative growth rate vs. photochemical efficiency (Fv/Fm) showing that no strain, growing at high temperature (32 ºC) was better than growing at the control temperature (26 ºC). Relative growth rate was calculated dividing growth rate, k, at 32 ºC by k at 26 ºC. Only values of Fv/Fm at 32 ºC for the last three days of the experiment are shown...... 36

Figure 2. 5 Relative photochemical efficiency of three strains with different thermotolerance under different light conditions. Relative light was calculated by subtracting the total light dose of the experimental conditions (65, 80, 100, 240 and 443 µmol quanta m2s-1) to the initial light conditions (100 µmol quanta m2s-1). Relative photochemical efficiency was calculated with the initial Fv/Fm minus the value after 12 hrs at the light/temperature conditions. Tolerant strain (blue = Smic3), intermediate strain (purple = Smic2), and sensitive strain (red = Stri1). Linear regression with confidence curve fit. Blue line depicts normal growth temperature (26 ºC), red depicts high growth temperature (32 ºC)...... 37

vii Figure S2. 1 Average cell density changes between eleven strains of clade A under different growth temperatures. Bars depict standard error. Data in blue indicate control temperature (26 ºC) and data in red indicates high temperature (32 ºC). Both treatments were grown under light of 100 µmol quanta m-2s-1. Cell density scale is the same for all cultures except for Snec2...... 38

Figure S2. 2 Average Fv/Fm changes between eleven strains of clade A under different growth temperatures. Bars depict standard error. Data in blue indicate control temperature (26 ºC) and data in red indicate high temperature (32 ºC). Both treatments were grown under light of 100 µmol quanta m-2s-1...... 39

Figure S2. 3 Average Fv/Fm changes between three strains of clade A under different growth lights and temperatures. Bars depict standard error. Data in blue indicate control temperature (26 ºC) and data in red indicate high temperature (32 ºC). Darker color indicates low light of 65 µmol quanta m-2s-1. Intermediate colors indicate light levels of 80, 100, 240 µmol quanta m-2s-1).Lighter color indicates high light of 423 µmol quanta m-2s-1...... 40

Figure 3. 1 Experimental design. Symbiodinium microadriaticum (CassKB8) was grown at normal temperature 26 ºC (blue line, control) and temperature was increased gradually to 32 ºC (red line, high temperature treatment). Cultures were grown at each temperature with three replicates under 50µM quanta m-2 s-1, 12:12 light:dark cycle. Green boxes indicate the time points where RNA samples were collected and analyzed with cDNA microarrays to measure gene expression before experimental treatment, six days after thermal acclimation, and 16 days after thermal acclimation. Orange boxes indicate the time points where RNA samples were collected and analyzed with RNA-Seq to measure gene expression around day six (five days and seven days) since it was found to have high number of differential expressed genes...... 70

Figure 3. 2 Symbiodinium microadriaticum (CassKB8) grown under high temperature has a slower growth rate than when grown at normal temperature for 23 days, with aliquots measured every two-three days. Blue bar depicts normal growth temperature (26 ºC), red bar depicts high growth temperature (32 ºC). Bars depict standard error. Student t test showed significant differences between treatments (p <0.0001)...... 71

Figure 3. 3 No significant difference was found in photochemical efficiency (Fv/Fm) of Symbiodinium microadriaticum (CassKB8) when grown under normal and high temperature conditions. Blue line represent normal growth temperature (26 ºC), red line represents high growth temperature (32 ºC). Error bars depict standard error. . 72

viii Figure 3. 4 High growth temperature increased thermotolerance of Symbiodinium microadriaticum (CassKB8). Cultures were grown at 26 ºC (blue) and 32 ºC (red). Photochemical efficiency (Fv/Fm) was measured after five minutes of incubation at the experimental temperatures and a control temperature. Change in photochemical efficiency was calculated as relative to control samples incubated at 26 ºC. Data were collected from three independent experiments per growth temperature, with three independent replicates per experimental treatment...... 73

Figure 3. 5 A two-factor ANOVA showed that time was the factor that produced higher number of differentially expressed genes compared to temperature. (p<0.05, 1000 iterations)...... 74

Figure 3. 8 Differential expressed genes of samples sequenced by RNA-Seq pairwise comparisons of samples (n=3) at two temperatures (control 26 ºC and high temperature 32 ºC) in two time points (5 days and 7 days after high temperature). Up-regulation of genes was more frequent than down-regulation in all pairwise comparisons. Temporal comparisons showed higher transcriptional response than temperature comparisons...... 77

Figure 3. 9 Pairwise comparisons of differential expressed genes. Time generates a higher differential expression of genes. Small arrows next to numbers indicate the number of genes up-regulated (arrow up) or down-regulated (arrow down). A. Temperature comparisons show higher differential expression during day seven compared to day five. B. Time comparisons showed higher number of DEGs at 26 ºC than at 32 ºC. 78

Figure 3. 10 High temperature affects photosynthetic genes differently over time. Log2 values are compared to control temperature (26 ºC). Arrow indicates up-regulation or down-regulation...... 79

Figure S3. 1 Cell density of Symbiodinium microadriaticum (CassKB8). Linear regression with confidence curve fit. Blue line depicts normal growth temperature (26 ºC), red depicts high growth temperature (32 ºC). Whole model test for 26 ºC: F 2 33, 2678 = 747.99, p < 0.0001, R = 0.895. Whole model test for 32 ºC: F 33, 2678 = 208.24, p < 0.0001, R2= 0.703...... 89

Figure S3. 2 Venn diagrams comparing replicate samples per temperature per day. The identity of all reads were compared for each sample against their replicas from each treatment. Numbers show the number of transcripts at each intersection. The intersection between the three replicates shows the number of sequences present in all samples, and the total percentage that these sequences represent...... 90

ix List of Tables

Table 1. 1 Summary of genomic and gene expression studies performed in Symbiodinium ...... 8

Table 2. 1 Cultures used in this study, culture collection code, ITS2 type, collection type, animal species from which the culture was obtained, and geographic location where the culture was collected. * BURR Collection at SUNNY Buffalo, **Trench collection at The Pennsylvania State University...... 30

Table 2. 2 ANCOVA analysis examining the photochemical efficiency response (Fv/Fm ) and cell density response of eleven strains of dinoflagellates to temperature. Cell densities and photochemical efficiency (Fv/Fm) showed similar results where temperature was the major source of variability. Cell densities were measured on days 0, 6, 9, 13, 17 in three replicates per culture per treatment (n= 18). Fv/Fm was measured every day for 17 days with six technical replicates. Fv/Fm was measured at least two times for all strains and three times for four of them in independent repetitions of the experiment. Cultures were grown at 100 µmol quanta m2s-1, under two temperatures: control (26 ºC), and high temperature (32 ºC)...... 31

Table 2. 3 Cell densities and photochemical efficiency (Fv/Fm) showed similar results, being temperature the major source of variability above other sources. ANCOVA analysis examined the combined effect of temperature and light on Symbiodinium. Cell densities were measured on the first and seventh day following experimental treatment, with three technical replicates per culture per treatment. Fv/Fm was measured after 12 hours of exposure to light/temperature treatments six technical replicates. Cultures were grown under control (26 ºC), and high temperature (32 ºC), and five light intensities 65, 80, 100, 240, 423 µmol quanta m2s-1...... 32

Table 3. 1 Changes in gene expression regarding nitrogen metabolism with growth temperature. Log2 values of differentially expressed genes are showed. Negative log2 values represent down-regulation of gene compared to the condition mentioned...... 80

Table 3. 2 Changes in gene expression regarding nitrogen metabolism over time. Log2 values of differentially expressed genes are showed. Negative log2 values represent down-regulation of gene compared to the condition mentioned. 5d= day five of the RNA-Seq experiment; 7d= day seven of the RNA-Seq experiment...... 81

x Table 3. 3 Changes in gene expression of chaperones with high temperature. Log2 values of differentially expressed genes are showed. Negative log2 values represent down- regulation of gene compared to the condition mentioned...... 82

Table 3. 4 Changes in gene expression of chaperones over time. Log2 values of differentially expressed genes are showed. Negative log2 values represent down- regulation of gene compared to the condition mentioned. 5d= day five of the RNA- Seq experiment; 7d= day seven of the RNA-Seq experiment...... 83

Table 3. 5 Retrotransposable elements and related genes differentially expressed. Log2 values of differentially expressed genes are showed. Negative log2 values represent down-regulation of gene compared to the condition mentioned. 5d= day five of the RNA-Seq experiment; 7d= day seven of the RNA-Seq experiment...... 85

Table 3. 6 Differentially expressed glycoproteins only found to change at the control temperature. Log2 values of differentially expressed genes are showed. Negative log2 values represent down-regulation of gene compared to the condition mentioned. 5d= day five of the RNA-Seq experiment; 7d= day seven of the RNA- Seq experiment...... 87

Table S3. 1 Detailed read counts used during data processing. Remaining adapter after trimmomatic was not included as it was 0 in all cases...... 91

Table S3. 2 Final number of sequences mapped to the reference containing all samples from this experiment, assembled with Trinity. Mapping was performed with the MEM algorithm of BWA. 5d= five days of treatment; 7d= seven days of treatment...... 92

Table S3. 3 Temporal changes in gene expression of photosynthetic pathway. Log2 values of differentially expressed genes are showed. Negative log2 values represent down-regulation of gene compared to the condition mentioned...... 93

Table S3. 4 Temperature changes in photosynthetic pathway. Log2 values of differentially expressed genes are showed. Negative log2 values represent down- regulation of gene compared to the condition mentioned. 5d= day five of the RNA- Seq experiment; 7d= day seven of the RNA-Seq experiment...... 96

xi Acknowledgments

I would like to thank my family and friends for their support.

Deep thanks to Monica Medina, my academic advisor, for her patience and support. I want to thank my committee members Todd LaJeunesse, Chuck Fisher, and Mark Guiltinan for their useful comments and constant mentoring. I want to thank external faculty Ariel Escobar, Carolin Frank, Benoît Dayrat, Miriam Barlow, Roberto Iglesias- Prieto, Tomás Carlo and Patricia Thomé for their constant encouragement and support. Special thanks to Naomi Altman and Monika Michalovová for their help with bioinformatics.

Special thanks to the members of the Medina Lab postdocs Carlos Prada, Michele Weber, Emmanuel Buschiazzo, Chris Voolstra, and Kevin Portune for their feedback. Thanks to the graduate students Michael DeSalvo, Shinichi Sunawaga, Elizabeth Green, Collin Closek, Bishoy Hanna, Aki Odhera, Viridiana Ávila, Ana María González, and Aubrie O’Rourke for their help.

This work wouldn't been possible without the help and hard work of the undergraduate students Nicole Masouka, Yogesh Narayanan, Siobhan Kelly, Myriam Zavalza, Kristen Valentine, Heather Moran, Ashley Porter, Victoria Wu, and Gabrielle Swain.

I want to thank everyone at University of California, Merced and Penn State University for nurturing me during my Ph.D.

Finally, I want to thank to my funding sources CONACYT Scholarship for tuition and salary (Registration number 305321), Miguel Velez Fellowship from University of California, Merced, Quantitative Systems Biology Fellowship from University of California, Merced, and Henry Popp Graduate Assistantship.

xii Chapter 1. Introduction

Coral reefs are one of the most productive ecosystems on Earth (Bellwood 1994), containing high biodiversity (Birkeland 1997). Over 400 million people globally depend on goods and services provided by coral reefs (Hoegh-Guldberg et al. 2007). The coral reef ecosystem services and economic goods are valued at over $20 trillion dollars annually (Costanza et al. 1997). Reefs ecosystems are dominated by symbiotic associations between invertebrates (cnidarians, sponges, mollusks) or protists (foraminifera, ciliates) and dinoflagellates (Symbiodinium) (Wood 1993). In cnidarians, symbiotic dinoflagellates live within an animal organelle called the symbiosome located mainly in the endoderm cells of the host (Trench 1987). This partnership contributed to the success of scleractinian corals over the last 250 million years, and one hypothesis accounting for that success is that symbiosis helps increase the rate of calcification by the host (Colombo-Pallota et al. 2010). Symbiotic dinoflagellates provide sugars, amino acids, carbohydrates and small peptides, while the dinoflagellate obtains ammonium, phosphate and other waste products from coral metabolism (Muscatine 1990, Trench 1987). Symbiotic dinoflagellates also collect light more efficiently than they would as free-living cells because of the structure of the coral skeleton (Enríquez et al. 2005).

Coral reefs, despite their biological and economic importance, are currently threatened by local factors such as coastal development that causes increased nutrient input, increased sedimentation, damage to supporting habitats such as mangroves, and overexploitation of fisheries. Global anthropogenic factors that also impact reefs include: climate change, acidification of the oceans, and the increase in the intensity (and possibly frequency) of hurricanes (Hoegh-Guldberg et al. 2007).

The breakdown of symbiosis between cnidarians and dinoflagellates in nature has been described as bleaching. Coral bleaching is the loss of coloration of the host due to a decrease in cell density of symbiotic dinoflagellates or loss of photosynthetic pigments of the symbiont (Hoegh-Guldberg 1989). Corals bleach in response to environmental stress (temperature, light, salinity, or nutrients) and recently bleaching events have become

1 more frequent and severe (Eakin et al. 2010); large-scale bleaching in response to thermal stress is typically associated with an increase of 0.5ºC to 1.5 ºC average temperature of the sea surface for several weeks (Glynn 1993, Hoegh-Guldberg et al. 2007 and references therein). Besides the increase in temperature, the exposure time also affects coral response (Fitt et al. 2001). Temperature and exposure time are are factors that determine whether or not the organism has the capacity to recover (Iglesias-Prieto et al. 1992, Fitt et al. 2001). Increments of 4 ºC to 5 ºC higher than the average summer temperature for 1 to 2 days cause bleaching, followed by high mortality, while an increase of 2 ºC to 3 ºC for the same period of time may result in a less extensive and more gradual bleaching that is less extensive and less fatal (Jokiel and Coles 1990).

Not all coral species are equally affected by increased temperature (Ulstrup et al. 2006, Penin et al. 2007), and even within the same morphological species, not all colonies bleach under the same levels of stress. This may be related in part to the differences in the thermal sensitivity of the different dinoflagellate symbionts (Iglesias-Prieto et al., 1992, Warner et al. 1999 Tchernov 2004). The differential sensitivity is partially related to the photosynthetic membrane fluidity (Iglesias-Prieto et al., 1992, Tchernov et al. 2004), which seems to be species-specific (Díaz-Almeyda et al. 2011). The effect of temperature on the structure and function of the photosynthetic apparatus has been studied using chlorophyll fluorescence (as described in Govindje, 1995). Incubating corals and dinoflagellate symbionts at high temperatures initiated the degradation of proteins, damage of photosystem II, and after the stress was removed, incomplete recovery of photosynthetic proteins, synthesis of heat shock proteins, oxidative stress, and inhibition of protein synthesis antenna (Iglesias-Prieto et al. 1992, Warner et al. 1999, Jones et al. 1998, Takahashi et al. 2008).

Symbiodinium diversity

Dinoflagellates are a group of marine and freshwater, flagellated, single cell eukaryotes. They can be found in a variety of environments, with diverse ecologies and physiologies (Graham and Wilcox 2000). Symbiodinium is a lineage of dinoflagellates within the

2 group Suessiales and according to molecular clock methods calibrated using soritid foraminifera, it evolved in the Early Eocene (Pochon et al. 2006). The majority of diversity within Symbiodinium evolved since the mid-Miocene (15mya) and there are 9 modern lineages are currently recognized.

Symbiodinium was initially discovered and defined as a genus of dinoflagellates that live in symbiosis with marine invertebrates and described as a single species: Symbiodinium microadriaticum (Freuthental 1962). Symbiodinium live as symbionts in Cnidaria, Platyhelminths, Mollusca, Porifera, and Foraminifera (Stat et al. 2006) and also live in sand on the reef (Reimer et al. 2010). Blank & Trench (1985) initially documented Symbiodinium diversity using isoenzymes, behavior, physiology, biochemistry and traditional morphological characters.

One of the first efforts to describe the molecular genetic diversity of Symbiodinium was done by Rowan and Powers (1991). They sequenced 18S rDNA and other authors used 28S rDNA (Santos et al. 2003). The mitochondrial markers cytochrome b and chloroplast 23S produce congruent trees (Takabayashi et al. 2004). Currently, nine clades (A-I) are recognized (Pochon & Gates 2010). Faster evolving markers have been used to describe lineages within each of the major lettered clades. These loci include: D/D2 domain of 28S rDNA (Baker & Rowan 1997, Rodriguez-Lanetty et al. 2001), internal transcribed spacer regions of the rDNA (ITS1 and ITS2) (LaJeunesse 2001 and others), hypervariable domain V of 23S rDNA (Santos et al. 2002, 2003) and microsatellite flanking regions (Santos et al. 2004). Although the clades are now well defined, there have been multiple efforts to understand subclade diversity. Sampayo et al. (2009) used a combination of methods to study Symbiodinium clade C, improving the resolution of the phylogenies with an ecological and evolutionary meaning.

Formal species descriptions for this genus used to include just 12 to 17 species (review by Baker et al. 2003, LaJeunesse et al. 2005, LaJeunesse et al., 2012) and the rest of the diversity lacks formal taxonomy. Recent efforts have increased the number of described species, unraveling the ecological, physiological and genetic diversity inside this genus.

3 Examples of this diversity are S. fitti, S. trenchii, S. glynni, S. minutum, S. psygmophylum, Symbiodinium voratum.

Symbiodinium belonging to clade A, which is the focus of this dissertation, is consistently basal, strongly supported by all genetic markers (Pochon et al. 2006). Symbionts belonging to this clade can be found in cnidarians and mollusks but haven’t been found in foraminifera. Symbiodinium clade A are most abundant in the Western Atlantic Region (Baker & Rowan 1997) and in the Red Sea (Barneah et al. 2004, Karako-Lampert et al. 2004). ITS2 type A1 has been found in the Pacific, Caribbean and Red Sea at 0.5 to 20 meters depth in symbiosis with corals, jellyfish and nudibranchs (Franklin et al, 2011).

S. fitti is a clade A species, ITS2 type A3. This species was described by Pinzón et al. (2011) as being common in giant clams in the Indo-Pacific and in the Caribbean coral Acropora. S. trenchii and S. glynni are members of clade D which originally was thought to be thermotolerant. After its description by Wham et al. (2011) it was clarified that there were at least two lineages with different ecology inside this clade. Recently, the existence of several species was confirmed (LaJeunesse et al. 2015, Lee et al. 2015)

S. minutum and S. psygmophylum are members of clade B (LaJeunesse et al., 2012) part of a well-studied clade with other closely related species, a high genomic divergence as well as ecological diversity (Parkinson et al. unpublished). Symbiodinium voratum is a free-living species that feeds phagotropically. This species is the only known member of clade E. The first Kofoidian plate formula was developed for Symbiodinium based on this species (Jeong et al., 2014). Currently additional species of clade A and clade B are being described, unfolding high genetic and ecological diversity in this genus (LaJeunesse et al. 2015, Lee et al. 2015). The descriptions of some of these species are summarized in Chapter 3, which focuses on most of the species recently described for clade A.

Symbiodinium gene expression changes under high temperature conditions.

Several gene expression studies have addressed understanding Symbiodinium changes under different environmental conditions (Table 1.1). Leggat et al. 2007 published the

4 first expression sequence tags (EST) under a variety of stressors including short-term high temperature (increase of 7 ºC for seven hours), long-term heat stress (increase of 4 ºC for 4 days), ammonium supplementation, and changing inorganic carbon concentrations. Two years later, a larger EST library was created for two species of S. microadriaticum and S. minutum comparing orthologous genes (Voolstra et al. 2009). These authors suggest that the symbiotic lifestyle might affect population structure and the strength of evolutionary selection.

More recently, thanks to high-throughput technologies, multiple transcriptomes were sequenced in a short amount of time. A more detailed library was generated for S. microadriaticum and S. minutum (Bayer et al., 2012) describing mainly their unique transcriptional regulation mechanisms which differ from other eukaryotes. Another comparison between multiple strains was made for Symbiodinium strain C3K and the thermotolerant strain D2 in Acropora hyacinthus under different temperatures (Ladner et al., 2012). Differential expression was found between strains creating a more comprehensive library focused on thermotolerance related functions. Several genes have been suggested to be linked to thermotolerance such as fatty acid desaturases, molecular chaperones, and photosynthesis and thylakoidal membrane proteins. A similar follow up study was performed comparing transcription of these thermotolerant and non- thermotolerant strains after three days of high temperature stress (Barshis et al., 2014). Authors did not find transcriptional differences between treatments, but gene expression differences were attributed to each strain, involving heat-shock proteins and chloroplast membrane components. In all these later cases, the genetic variability between the lineages compared is extremely high. Comparing a strain from the A and B lineages involves a divergence of 50-65 million years. While the divergence of the lineages C and D is around 40-50 million years, leading to comparisons being useful but too general. (see Tchernov et al. 2004 and Pochon et al. 2010 for divergence times). In an effort to find the core pathways common to all Symbiodinium, several transcriptomes comparing four strains of three ITS2 types (A, B, C, and D) were sequenced recently (Rosic et al. 2014). The authors described common pathways including conserved genes involving stress response and photosynthetic proteins among lineages.

5 Thermal and light stress affects on gene expression have also been studied for Symbiodinium in smaller, less exploratory experiments. Karako-Lampert and collaborators (Karako-Lampert et al., 2006) reported differential gene expression for Symbiodinium microadriaticum (Clade B) under temperature stress utilizing RT-PCR. They amplified seven transcripts and identified a molecule involved in cell matrix adhesion, but their experimental design included high temperature that are not comparable to those reported to have an important effect in previous studies (i.e. Iglesias- Prieto et al. 1992 and others). Takahashi et al. (2008) observed a decrease in the mRNA of acpPC protein, a major antennae protein component, when Symbiodinium was incubated at high temperature. Rosic et al., (2011) evaluated the expression of two heat- shock proteins Hsp70 and Hsp90, under gradual and fast thermal stress. The authors suggested that Hsp90 might have a reduced role in heat acclimation. Using qPCR, Leggat and collaborators (Leggat et al., 2011) investigated the changes in gene expression of six genes daily during eight days of thermal stress. They focused on specific genes related to stress and carbon metabolism. These genes were differentially expressed at different time points along the experiment. Finally, another useful study was performed specifically focusing on genes from core photosystems, psbA and psaA (McGinley et al., 2012). The authors compared the expression of these genes in a thermotolerant and a temperature sensitive strain under high temperature (32 ºC) measuring its transcription every other day during seven days. Down-regulation of these genes was observed for the temperature sensitive strain, suggesting these genes are key for thermotolerance.

Symbiodinium as a model organism to understand the effects of climate change

To understand the adaptation to high temperatures, first we need to understand the short- term events happening at an ecological scale. These changes are commonly called acclimation when these changes occur in controlled environmental conditions. The study of these changes in a natural habitat, where multiple variables might be changing in addition to the one we am aiming to study, is called acclimatization. Understanding the

6 acclimation potential of these organisms is crucial to explaining the adaptation potential to climate change.

Symbiodinium is a well-defined group with a diverse ecology and genetics. Some strains of this genus can be cultured in controlled conditions. This allows studying how diverse genotypes might be able to acclimate to diverse environmental conditions. In this investigation, we focus on two main approaches to understand this phenotypic plasticity. The first one is physiology and the other one is transcriptomics. Using these tools we gain a deeper understanding of the temperature acclimation process or the failure to acclimate.

7 Table Table 1. 1 Summary of genomic and gene expression studies performed in Symbiodinium

ITS2 Species name Type Source Resource type Publication Transcriptomic studies Symbiodinium sp. C3 Acropora aspera EST lbrary Leggat et al. 2007 S. minutum B1 culture Mf1.05b EST lbrary Voolstra et al. 2009 S. microadriaticum A1 culture CassKB8 S. minutum B1 culture Mf1.05b mRNA Bayer et al. 2012 S. microadriaticum A1 culture CassKB8 transcriptome Symbiodinium sp. C3k mRNA Acropora hyacinthus Ladner et al. 2012 Symbiodinium sp. D2 transcriptome Symbiodinium sp. C3k mRNA Acropora hyacinthus Symbiodinium sp. D2 transcriptome Barshis et al. 2014 Symbiodinium sp. A2 cultured from Zoanthus sociatus

Symbiodinium sp. B2 cultured from Oculina diffusa mRNA Rosic et al. 2014 cultured from Discosoma transcriptome Symbiodinium sp. C1 sanctithomae Symbiodinium sp. D1 cultured from Porites annae mRNA and smRNA Baumgarten et al. S. microadriaticum A1 Culture RT-370 (CCMP2468) transcriptome 2013 Focused experiments Karako-Lampert et S. microadriaticum B cultured from Condylactis gigantea RT-PCR al. 2006 Symbiodinium sp. A OTcH-1 Takahashi et al. qPCR Symbiodinium sp. A CS-73 2008 Symbiodinium sp. C3 Acropora aspera qPCR Leggat et al. 2011 Symbiodinium sp. C3 Acropora millepora qPCR Rosic et al. 2011 A13, A20, B1, McGinley et al. Symbiodinium sp. F2 cultures qPCR 2012 C1b-c, Symbiodinium sp. D1 in hospite Pocillopora spp.

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16 Chapter 2. Within and among species variation in thermotolerance and photoacclimation in Symbiodinium dinoflagellates

Abstract

I quantified thermotolerance in 11 cultures from different populations of five species of Symbiodinium clade A. We grew cultures at 26 °C (control) and 32 °C (high temperature) over 18 days, measuring growth and photochemical efficiency (Fv/Fm). Thermotolerance was not restricted to a single species but it was widespread across species and cultures, showing a gradient from susceptible to tolerant. All cultures at 32°C decreased growth and Fv/Fm. To test the synergistic effect of temperature and light, we cultured three strains with different levels of thermotolerance (tolerant, intermediate, and susceptible) in five different light intensities at 26 °C and 32 °C. The combined effect of light and high temperature exacerbate stress, particularly in thermosensitive populations. We demonstrate that species delineation within the genus Symbiodinium is crucial to explore thermotolerance mechanisms, and predict physiological responses in hospite in natural environments.

Introduction

Carbon dioxide has increased globally as a result of anthropogenic emissions (MacFarling Meure et al. 2006), increasing global temperatures (Thompson et al. 2006, Rhein et al. 2013). The resulting higher sea surface temperature (SST) induces coral bleaching, which has increased in frequency and intensity, reducing coral cover and degrading reefs worldwide (Hoegh-Guldberg et al. 2007, Eakin et al. 2010). Coral bleaching is caused by the disruption of the coral-Symbiodinium symbiosis, resulting in reductions of symbiont cells within coral hosts and/or the loss of Symbiodinium pigmentation. While other stressors such as changes in salinity, irradiance and nutrients can also cause bleaching, increasing SST is recognized as the main driver of coral bleaching (Brown & Dunne 2016), which can dramatically affect coral coverage. For

17 example, temperature increases of from 0.5 °C to 1.5 °C can lead to bleaching events, (Glynn 1993, Hoegh- Guldberg et al. 2007) yet not all coral species are equally affected (Ulstrup et al. 2006, Penin et al. 2007). Even when bleaching is widespread, colonies within an affected population may not always exhibit signs of bleaching, despite experiencing the same stress as their conspecifics. These differences are in part due to Symbiodinium variation across coral colonies (Kemp et al. 2014).

Physiological and genetic diversity within Symbiodinium is vast (Robison and Warner 2006, Hennige et al. 2009, LaJeunesse et al. 2001). Nine clades (A-I) are currently recognized within the genus (Pochon & Gates 2010), and though clades are well defined, we are just beginning to understand subclade diversity (LaJeunesse et al. 2015, Lee et al. 2015, Parkinson et al. 2015). For example, clade C may contain hundreds of undescribed species occurring in all major ocean basins and establishing symbiosis with a wide array of coral and non-coral species (Thornhill et al. 2014). Similarly, within clade B there are tens of species that often associate with anthozoan partners (Goulet and Coffroth 2003a, 2003b, Finney 2010, Prada et al. 2014, Parkison et al. 2015). Even within well-studied species such Symbiodinium microadriaticum there is cryptic variation that allows a host to explore new ecological niches (Lee et al. 2015). While the diversity within one of the richest algal genera – Symbiodinium - is just beginning to be unveiled, its physiological variability remains little understood.

Part of the physiological variability within Symbiodinium is linked to thermal stress (Iglesias-Prieto et al. 1992, Iglesias-Prieto and Trench 1993 and 1997, Tchernov et al. 2004, Robison and Warner, 2006, Takahashi et al. 2008, Díaz-Almeyda et al. 2011, Takahashi et al. 2013). It was hypothesized that coral associations with thermotolerant variants of Symbiodinium species may help coral reefs to cope with climate change (Baker et al. 2004, Stat et al. 2010). However, symbioses in a large number of reef building corals appear to be less labile and species specific (LaJeunesse et al. 2014).

Thermotolerance was first described in Symbiodinium from clade D (Baker et al. 2004). Kemp et al. (2014) found Symbiodinium belonging to stress tolerant clade D to be most abundant in corals after bleaching events in the Caribbean. Subsequent studies suggest

18 Symbiodinium species in other clades also tolerate higher temperatures (Hume et al. 2015, Sawall et al. 2014). In the Persian Gulf where SSTs can reach a maximum of 34-36 ºC, several coral taxa harbor S. thermophilum, a thermotolerant lineage belonging to subclade C3. In the Red Sea coral reefs experience the most extensive seasonal and latitudinal thermal gradients (21-33 ºC) worldwide. Variation of symbiont populations in Pocillopora verrucosa along this gradient also exhibit thermotolerant symbionts belonging to clade A and C at higher temperatures (27-33ºC) (Sawall et al. 2014). Beyond variation among clades, the degree of physiological thermotolerance among strains within populations or among populations within species remains largely unknown. Populations within Symbiodinium spp. seem to have different physiological behaviors under various light conditions (Hennige et al. 2009) but intraspecific physiological variability at this fine-scale is not well understood.

For example, while some Symbiodinium appear to live close to their limits of thermal tolerance (Sawall et al. 2015), others survive at temperatures that seem too high for a functional symbiosis to be maintained (Barshis et al. 2014, Hume et al. 2015). This raises the question of whether Symbiodinium is capable of acclimating by modulating its physiological response to environmental change (Hochachka & Somero 2002). The thermal acclimation potential of Symbiodinium spp. is known to vary across clades (Robison and Warner, 2006, Díaz-Almeyda et al. 2011, Takahashi et al. 2013). Yet, the strength and tempo of acclimation responses within and across species,are unknown.

Symbiodinium clade A is an ideal lineage to quantify acclimation variation within and among species. It is the most basal clade in the Symbiodinium tree with at least 17 distinct lineages (LaJeunesse 2009). Clade A has worldwide distribution and diverse host taxa; as well as many described species some of which are cultivable (see Table 2.1) (Lee 2015). Clade A can also acclimate to various light levels and presents an unparalleled opportunity to study the dual effects of light and temperature. Under variable light, it is known that different species have unique physiological responses and those species can also have different tolerance when exposed to high temperatures. For example, S. pilosum and S. microadriaticum vary in their photoacclimatory responses (Iglesias-Prieto and

19 Trench 1994, 1997). S. microadriaticum is thermosensitive at 32 ºC (Iglesias-Prieto et al. 1992). S. microadriaticum is more thermosensitive than S. necroappetens under light stress (Robinson and Warner (2006). Even when exposed to acute stress of 32ºC, clade A species often show differences in thermotolerance (Takahashi et al. 2008, McGinley et al., 2012). Responses are so variable that even single cultures often have unique physiological signatures under variable light conditions (Hennige et al. 2009).

Here we conducted experiments to study the acclimation potential to temperature and light within and among species of Symbiodinium Clade A – a phylogenetically well- characterized group. We used 11 cultures from different populations corresponding to five species of clade A: S. microadriaticum, S. pilosum, S. tridacnidorum, Symbiodinium sp. A4 and S. necroappetens. We specifically tested if intraspecific variation is comparable to that found among species, and the occurrence of thermotolerance among species. We also evaluated the effects of temperature and light on Symbiodinium growth and photochemistry. Our results suggest that thermotolerance is not restricted to individual species but instead it is widespread throughout clade A, and that species often adjust to variations in light. Species surviving under stressful light and thermal conditions often incur in physiological costs that slow down growth and accelerate photodamage.

Methods

Symbiodinium cultures: growth conditions

To quantify physiological responses, we cultured Symbiodinium in ASP-8A medium (Blank 1987) at 26 ºC with full spectrum fluorescent lights at 100 µmol quanta m-2s-1 with a 12:12 (light:dark) photoperiod. Light intensities were measured inside the culture flasks with a 4π sensor (Biospherical, USA). Cultures were maintained at logarithmic phase by replacing the culture media every 1.5-2 weeks. Symbiodinium strains were obtained from the Trench collection maintained by Todd LaJeunesse at The Pennsylvania State University and the BURR collection at SUNY Buffalo maintained by Mary Alice Coffroth. Herein we follow a binomial nomenclature for Symbiodinium species

20 (LaJeunnese 2001, Lee 2015, LaJeunesse 2015) but see Table 2.1 for culture collection and strain designations.

High temperature acclimation: experimental design

To test for acclimation to high temperature, we used 11 cultures from clade A that included five species: three cultures of S. microadriaticum (ITS2 type A1), two cultures of S. necroappetens (ITS2 type A13), three cultures of S. pilosum (ITS2 type A2), two cultures of S. tridacnidorum (ITS2 type A13), and one culture of Symbiodinium sp. (ITS2 type A4) (Table 2.1). We inoculated cultures at an initial concentration of 1x106 cells/ml in 15 ml tubes containing 8 ml of culture (day zero). To elevate temperature to 32ºC, we increased from 28.5 ºC and then gradually rose by 0.5ºC every 6 hours until 32 ºC was reached (day two). We counted cell densities every three days and measured maximum quantum yield of photochemistry (Fv/Fm) daily (see below) for 17 days in four replicates per culture per temperature (control: 26 ºC and high temperature: 32 ºC) by triplicate. We obtained a total of 2,312 observations for cell densities.

High temperature acclimation and photoacclimation: experimental design

To test for the effects of interaction between temperature and light on Symbiodinium health, we selected three cultures with different levels of physiological thermotolerance: a tolerant S. microadriaticum (Smic3); an intermediate S. microadriaticum (Smic2) and sensitive S. tridacnidorum (Stri1). We inoculated cultures at a 1x106 cells/ml in 15 ml tubes, containing 8 ml of culture, initially grown at 100 µmol quanta m-2s-1 at 26 ºC. We set the high temperature treatment at 32 ºC (without ramping) and the control temperature treatment at 26 ºC. Light levels were adjusted to five different intensities: 65, 80, 100, 240 and 443 µmol quanta m2s-1 using mesh fabric to produce shade. We incubated fifteen replicates per culture at each of the ten treatments (150 observations in total).

21 Photochemical Efficiency

To quantify photochemical activity, we measured the maximum quantum yield of charge separation of photosystem II (Fv/Fm) with a MiniPAM fluorometer (Walz, USA) after 30-50 minutes of dark acclimation at the end of the light cycle. We measured daily Fv/Fm in five independent tubes without disturbing the sample. For the species comparisons with eleven strains, these five measurements were performed at least two times for all cultures and three times for four of these cultures (RT-080, CassKB8, CassEL1, and RT-024).

Population Growth

To evaluate the performance of eleven strains during high temperature acclimation, we measured cell density by fixing 1 ml aliquots of culture in 10% Lugol every three days and counted them using a hematocytometer. Nine replicates were counted for each sample at each time point. Cell densities were measured for day 0, 6, 9, 13, and 17. Growth rate (k, divisions per day) was calculated for all days according to Guillard (1973) with the formula:

� ∙ Σ � ∙ � − Σt ∙ Σt � = � � ∙ Σ �! − Σt !

� = 3.322 ��

For general comparisons, we used growth rates grouped by species (Figure 2.1) and by strain (Figure 2.2, 2.3, 2.4). For fine detail, we used cell densities to compare cultures (Table 2.2).

Statistical analysis

I examined how growth rates and photochemical efficiency (Fv/Fm) were affected by Symbiodinium strain, temperature (28.5, 29, 29.5, 30, 30.5, 31, 31.5, & 32 ºC), time

22 (days 0, 6, 9, 13, and 17), and/or light intensity (65, 80, 100, 240 and 443 µmol quanta m2s-1) using one-way ANOVAs and ANCOVAs (fixed-effects, LS). In the models to analyze the effect of light and temperature we included all two-way interactions. Strains with means that were significantly different from each other in photochemical efficiency and growth rates following a Tukey-Kramer HSD test were classified into distinct thermotolerance groups and coded with the same color (Figure 2.2, 2.3). For example, at 32°C, more tolerant strains (shown in blue) had growth rates that ranged between 0.40 and 0.43. Strains showing intermediate tolerance (shown in purple) had values ranging between 0.35 and 0.19. Last, growth rates of sensitive strains (red) showed growth rates between 0 and 0.01. We then used multinomial logistic regression models to examine how well tolerance classifications and strains were predicted based on their growth and Fv/Fm. Ordinal logistic regression model the cumulative probability that each strain group had as a function of their growth rates and Fv/Fm at 32°C. We used JMP Pro 11 for all analyses (SAS Institute, Cary, NC 2014).

Results

Extensive variation in temperature sensitivity within and among species

Our linear models identified all factors and two-way interactions as having a significant effect on the growth rates and Fv/Fm of Symbiodinium. But most of the variability was explained by “temperature”, explaining a staggering 70.6% of variance in growth rates responses, and 68.1% of the variance in Fv/Fm, responses (see F ratios, Table 2.2). Variation in thermotolerance among strains within species and across species was also observed with varied physiological responses across cultures (Figure 2.2, 2.3). Growth and Fv/Fm also varied within and among species. The only exception was S. tridacnidorum, where both strains were temperature sensitive with similar physiological outcomes.

Variation in the temperature response using this model can be categorized into three groups: tolerant, intermediate and sensitive. A logistic model on growth rate (Figure

23 2.2A) and photosynthetic efficiency (Figure 2.2B) probabilistically delineate the ability of each strain to acclimate to high temperature.

The tolerant group showed no significant difference in Fv/Fm and/or growth rate when comparing control and high temperature treatments, indicating its ability to acclimate successfully. The intermediate group showed significant decrease in Fv/Fm and growth rate, demonstrating an ability to acclimate but with a cost in fitness. The sensitive group did not survive to the end of the experiment, indicating the inability to cope with high temperature.

The ability to acclimate to high temperature is not species specific

The ability to acclimate to high temperature was observed within species and therefore is spread across the phylogeny (Figure 2.3). From the three strains of S. microadriaticum tested, two strains Smic1 and Smic2 showed an intermediate tolerance. Smic3 showed full tolerance to high temperature. For S. pilosum strains, Spil1 showed an intermediate tolerance while Spil2 and Spil3 showed full tolerance. For S. tridacnidorum, the two strains tested Stri1 and Stri2 are not thermotolerant (sensitive). For Symbiodinium sp. A4, SspA4 has intermediate tolerance. Finally, for S. necroappetens, Snec2 showed intermediate tolerance while Snec1 was sensitive.

High temperature acclimation has a cost

In all cases fitness was higher at control temperature than at high temperature (Figure 2.4), indicating that acclimating to high temperature has a cost. Acclimation to higher temperatures did decrease population growth for all strains. Growth rate was affected more than Fv/Fm at higher temperatures. In S. microadriaticum for example, the two intermediate tolerance strains Smic1 and Smic2 decreased in cell density with Smic1 showing greater decrease in density than Smic2 (average 3.9x104 cells/ml, versus 22.6x104 cells/ml at day 17 of the experiment). In both cases, we also observed a Fv/Fm decrease (Figure S2.1 and S2.2). Even when the cell densities were low, the remaining cells still showed some physiological activity (Fv/Fm 0.310 and 0.489 in average). In

24 contrast, Smic3 was able to acclimate to heat stress with a slight decrease in growth observed at the end of the experiment. Fv/Fm remained similar to the control when grown at high temperatures.

In S. necroappetens, one strain, Snec1, showed intermediate tolerance while the other one, Snec2, was sensitive to high temperature. The intermediate strain decreased in cell density with a slight decrease of Fv/Fm under high temperature (Figure 2.2, 2.3). Snec2 died under high temperature conditions. Whereas in S. pilosum, the strain Spil1, showed intermediate tolerance with decrease in growth. Cell densities remained stable until day 13, followed by a reduction in growth rates (Figure S1). Photochemical efficiency was slightly lower at high temperature but cells remained physiologically active (Fv/Fm = 0.534 vs. 0.339). The other two thermotolerant strains showed only a small decrease in growth. Both strains Spil2 and Spil3 had similar cell density under the two temperature treatments, however Spil2 had a slight decrease by the end of the experiment. They also showed slightly lower Fv/Fm under high temperature (Figure 2.2).

Finally, in S. tridacnidorum, the two strains died when exposed to high temperature (Figure 2.2, 2.3). The decrease in cell density and Fv/Fm started briefly after the high temperature treatment was initiated (Figure S2.1, S2.2). The single strain of Symbiodinium sp. A4 tested showed low growth rates, even under the control temperature, when compared to other clade A species. Under high temperature, cell density remained constant over time (Figure S2.1). The cultures were physiologically functional with lower Fv/Fm at 32 ºC than at 26 ºC (Figure S2.2).

The effect of light and temperature in photochemistry and growth

Three species with different thermal tolerance were chosen to evaluate the combined effect of light and temperature (i.e. Smic2, Smic3 and Stri1). Most of the variability was explained by “temperature” and not by “light” (Table 2.3). All three strains had a linear photoacclimation response independent of temperature (Figure 2.5). Fv/Fm was highest at low light and decreased at high light. This linear response had similar slopes for both control and high temperature. However, the levels of photochemical efficiency were

25 variable among strains. For the tolerant strain, the Fv/Fm change equally under both temperatures and different light intensities. But the intermediate and sensitive strains decreased Fv/Fm, maintaining the same slope under high temperature conditions. This decrease was larger for the sensitive strain than for the intermediate strain. After seven days of experiment, Fv/Fm remained constant for the tolerant and intermediate strains. The sensitive strain under high temperature vastly decreased Fv/Fm and no live cells remained at the end of the experiment (Figure S2.3).

Discussion

Intraspecific variation for thermal tolerance is high for different species of Symbiodinium clade A. Populations within species can be classified as sensitive, intermediate, and tolerant to thermal stress. However, we were unable to determine a species as thermotolerant or not; with the possible exception of S. tridacnidorum. The ability to acclimate to high temperature is widespread across species, and intraspecific thermotolerance variation is high. Still, exposure to high temperature, when not lethal decreases growth rate. Light and temperature act synergistically and can accelerate the negative effects in strains with intermediate and no tolerance to high temperature.

Widespread thermotolerance variation within species from clade A lineage

Our data show that some degree of thermotolerance is present in at least one population within all the clade A species examined, except the two populations within S. tridacnidorum. These results imply that genetic or physiological variation is high within species and most will perform well under 32 ºC. Our observations indicate that thermotolerance is not phylogenetically restricted to certain lineages and is instead extensive across the genus (Figure 2.3). In addition, while earlier studies have shown limited within cladal variation in thermal stress (Tchernov et al. 2004, Robison & Warner 2006, Hume et al. 2015, Sawall et al. 2015), our results provide the first in depth physiological evidence for widespread variation at lower taxonomic levels (i.e. within species) than previously expected.

26 Extensive variation to thermal tolerance within species hints at genetically encoded variation among populations. Comparing molecular mechanisms across species and across clades may be less fruitful than comparisons within species given the amount of genetic divergence within the genus. Major Symbiodinium clades diverged between 50 to 60 MYA (Tchernov et al. 2004, Pochon et al. 2006), a divergence time similar to bird (Härlid et al. 1997) and primate families (Steiper and Young 2004). It is thus not surprising that contradictory results have been reported on the molecular mechanisms underlying thermotolerance (Ladner et al. 2012, Barshis et al. 2014). Comparative transcriptomics of sensitive (Symbiodinium C3K) vs. thermotolerant (Symbiodinium D2) species (i.e. from separate clades) could not postulate a clear mechanism for thermal acclimation due to the long divergence time between clade C and D (40 MYA according to Pochon et al. 2006). Similarly, Rosic et al. (2014) were unable to see converging molecular patterns of thermotolerance across Symbiodinium belonging to A2, B2, C1, and D1, again a comparison across highly divergent lineages. In this study, we demonstrate that comparative analysis at lower taxonomic levels (i.e. within species) will be necessary if we want to understand the mechanism responsible for variation in thermotolerance.

In all clade A species examined, we find that 26 ºC is closer to the optimal growth temperature than 32 ºC. At 32 ºC, Symbiodinium show a decreased growth rate and lower Fv/Fm. Growth rate appears to be much more affected than Fv/Fm by high temperature. The adverse effects of high temperature (above 32 ºC) on photosynthesis have been extensively characterized for Symbiodinium growing in culture (Iglesias-Prieto et al. 1992, Robison and Warner 2006, Tchernov et al. 2004, Takahashi et al. 2008, 2013). For instance, in a strain of S. microadriaticum, photosynthesis impairment occurs at temperatures above 30 ºC, stopping completely at higher temperatures of 34-36 ºC (Iglesias-Prieto et al., 1992). Our results show that for eleven populations distributed across five species of Symbiodinium clade A, a temperature of 32 ºC was high enough to distinguish between sensitive and thermotolerant strains. Notably, thermotolerance is not phylogenetically constrained and instead there are sensitive, intermediate and tolerant populations within species. Although we were able to statistically categorize thermotolerance into these three groups, a clear gradient of thermotolerance can be

27 observed (Figure 2.4). Some species might fall into the tolerant side of the gradient, such as S. pilosum and S. microadriaticum while others such as S. necroappetens fall into the sensitive side of the tolerance gradient.

Combined effect of light and temperature in physiological acclimation

Several authors have highlighted the importance of considering the role of multiple stressors in order to improve predictions regarding physiological responses to climate change (Todgham & Stillman 2013). It has been observed that during coral bleaching, high temperatures are usually interacting with high levels of light (Hoegh-Guldberg et al. 2007), variation in available nutrients (Coles and Brown 2003). Multiple physiological parameters related to fitness might have different responses to diverse environmental factors and might determine tolerance of an organism to environmental change. Having the ability to acclimate to multiple stressors might come at a cost. Studying these environmental factors separately and in combination aids the understanding of these costs and their consequences for the health of the symbiosis.

Our results showed that tolerant strains had the ability to photoacclimate independently of temperature. The strains with intermediate tolerance have a temperature effect in photoacclimation. Finally, the sensitive strain Stri1 shows that during high temperature, damage is accelerated with the addition of high light. Multiple factors such as light acclimation and the ability to establish symbiosis successfully should also be considered in closely related species of Symbiodinium. These factors might be variable, and the overlap of all of them will determine species fitness in a specific environments (Chevin et al. 2010). Understanding the additive or synergistic effects of temperature and light conditions is crucial for our understanding of coral bleaching and adaptation potential to climate change.

Conclusions

The physiological diversity among and within Symbiodinium species shows that thermotolerance is not species-specific but rather widespread among clade A lineages.

28 Acclimation to high temperature in Symbiodinium comes at the cost of decreased photochemical activity and reduced growth. The combined effect of light and temperature exacerbate stress, particularly in thermosensitive populations. We demonstrate the value of our comparative framework –among closely related species and among populations within species– under which to explore underlying mechanisms of thermal tolerance. Caution should be exerted when categorizing Symbiodinium species as tolerant or sensitive; even more so when supraspecific taxonomic ranks such as clades are being discussed. Physiological, cellular or ‘omic’ studies of thermal stress response will be better addressed using comparisons at lower taxonomic levels. Species delineation within the genus Symbiodinium becomes therefore of primary importance to better predict lineage specific physiological responses in hospite under field conditions.

29 Tables Table 2. 1 Cultures used in this study, culture collection code, ITS2 type, collection type, animal species from which the culture was obtained, and geographic location where the culture was collected. * BURR Collection at SUNNY Buffalo, **Trench collection at The Pennsylvania State University.

Code Species name Culture Type Collected from Origin Smic 1 S. microadriaticum CassKB8 A1 * Cassiopeia xamachana North Pacific Smic 2 S. microadriaticum RT-061 A1 ** Cassiopeia xamachana Caribbean Smic 3 S. microadriaticum RT-362 A1 ** Cassiopeia andromeda Red Sea Snec 1 S. necroappetens RT-80 A13 ** Condylactis gigantea Caribbean Snec 2 S. necroappetens MAC4-225 A13 * Porites astreoides Caribbean Spil 1 S. pilosum RT-024 A2 ** Bartholomea annulata Caribbean Spil 2 S. pilosum RT-104 A2 ** Heliopora sp. West Pacific Spil 3 S. pilosum RT-130 A2 ** Meandrina sp. Caribbean Stri 1 S. tridacnidorum RT-292 A3 ** Tridacna maxima West Pacific Stri 2 S. tridacnidorum CassEl-1 A3 * Cassiopeia sp. North Pacific SspA4 Symbiodinium sp. RT-379 A4 ** Plexaura homamalla Caribbean

30 Table 2. 2 ANCOVA analysis examining the photochemical efficiency response (Fv/Fm ) and cell density response of eleven strains of dinoflagellates to temperature. Cell densities and photochemical efficiency (Fv/Fm) showed similar results where temperature was the major source of variability. Cell densities were measured on days 0, 6, 9, 13, 17 in three replicates per culture per treatment (n= 18). Fv/Fm was measured every day for 17 days with six technical replicates. Fv/Fm was measured at least two times for all strains and three times for four of them in independent repetitions of the experiment. Cultures were grown at 100 µmol quanta m2s-1, under two temperatures: control (26 ºC), and high temperature (32 ºC).

Prob > Response Source DF F Ratio F Cell densities Strain 10 304.982 *** Temperature 1 6040.697 *** Day 1 1048.311 *** Strain*Temperature 10 319.7055 *** Strain*Day 10 27.8232 *** Temperature*Day 1 815.532 *** 2 Whole model test: F 33, 2678 = 447.3, p < 0.0001, R = 0.846. Photochemical efficiency Strain 10 413.379 *** Temperature 1 534.5921 *** Day 1 3938.295 *** Strain*Temperature 10 29.871 *** Strain*Day 10 203.1659 *** Temperature*Day 1 658.8297 *** 2 Whole model test: F 33, 2278 = 378.1, p < 0.0001, R = 0.846.

*** p < 0.0001

31 Table 2. 3 Cell densities and photochemical efficiency (Fv/Fm) showed similar results, being temperature the major source of variability above other sources. ANCOVA analysis examined the combined effect of temperature and light on Symbiodinium. Cell densities were measured on the first and seventh day following experimental treatment, with three technical replicates per culture per treatment. Fv/Fm was measured after 12 hours of exposure to light/temperature treatments six technical replicates. Cultures were grown under control (26 ºC), and high temperature (32 ºC), and five light intensities 65, 80, 100, 240, 423 µmol quanta m2s-1.

Prob > Response Source DF F Ratio F Photochemical efficiency Strain 2 67.85 *** Temperature 1 138.118 *** Relative light 1 49.565 ***

Strain*Temperature 2 66.3663 *** Strain*Relative light 2 8.1871 0.0004 Temp*Relative light 1 4.3963 0.0378

Whole model test: F 9,140 = 52.987 p<0.0001, R2= 0.773

Growth rate Strain 2 206.8603 *** Temperature 1 388.9599 ***

Relative light 1 6.8053 0.0093 Strain*Temperature 2 109.6959 ***

Strain*Relative light 2 0.8426 0.431 Temp*Relative light 1 20.2236 ***

Whole model test: F 9,803 = 116.851 p<0.0001, R2= 0.567

*** p < 0.0001

32 Figures A B 0.6 0.6 ) Fv/Fm 0.4 0.4

0.2 0.2 Growthrate(µ/day) Photochemical efficiency ( Photochemicalefficiency 0 0 Smic Snec Spil SspA4 Stri All Smic Snec Spil SspA4 Stri All

Figure 2. 1 Average growth rate (A) and photochemical efficiency (B) at 32 ºC of five Symbiodinium spp. over a 17-day period. SspA4 = Symbiodinium sp. A4 (1 strain), Smic = S. microadriaticum (n=3 pooled strains), Snec = S. necroappetens (2 pooled strains), Spil = S. pilosum (3 pooled strains), Stri = S. tridacnidorum (2 pooled strains), and All (11 strains pooled). Bars depict one standard deviation of the mean.

33 A B 1.00 1.00

0.75 0.75

0.50 0.50 order Order

0.25 0.25 Cummulativeprobability Cummulativeprobability

0.00 0.00 0 0.1 0.2 0.3 0.4 0.5 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 K Fv/Fm Growth rate (µ/day) Photochemical efficiency (Fv/Fm)

Figure 2. 2 Multinomial logistic model showing the cumulative probability of each strain as a function of growth rate (A) and photochemical efficiency of 17 days of experiment (B). Growth rate was measured at 32 ºC (k, Whole model test, DF=1, p< 0.0001) Photochemical efficiency was measured at 32 ºC (Fv/Fm, Whole model test, DF=1, p< 0.0001). Smic = Symbiodinium microadriaticum, Spil = S. pilosum, SspA4 = Symbiodinium sp. A4, Snec = S. necroappetens, Stri= S. tridacnidorum. Color indicates strains thermotolerance from dark blue (thermotolerant) to dark red (sensitive).

34 Smic 1 d Smic 1 cd

Smic 2 a Smic 2 a

Smic 3 f Smic 3 de

Snec 1 c Snec 1 bc

Snec 2 g Snec 2 f

Ssp. 1 e Ssp. 1 cd

Stri 1 g Stri 1 f

Stri 2 g Stri 2 g

Spil 1 d Spil 1 e

Spil 2 b Spil 2 a

Spil 3 b Spil 3 a 5 changes 0 0.1 0.2 0.3 0.4 0.5 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Growth rate (μ/day) Photochemical efficiency (Fv/Fm)

Figure 2. 3 Simplified phylogeny of Symbiodinium clade A phylogeny inferred from ITS1, ITS2, and 5.8S rDNA sequences (LaJeunesse, 2001, LaJeunesse 2015, Lee et al, 2015). All data for growth rate and three days of Fv/Fm measurements after 12 days at 32 ºC is showed for each strain. (One-Way ANOVA, F10,310= 3604.73 , p< 0.0001, Tukey-Kramer HSD).

35

1 Smic2 Spil3 Spil1

Snec1 0.8 Smic1 SspA4 Spil2

0.6

Smic3

0.4 Relative Growth Rate Growth Relative

0.2

Snec2 Stri1 Stri2 0 0 0.1 0.2 0.3 0.4 0.5 0.6 Photochemical efficiency (Fv/Fm)

Figure 2. 4 Relative growth rate vs. photochemical efficiency (Fv/Fm) showing that no strain, growing at high temperature (32 ºC) was better than growing at the control temperature (26 ºC). Relative growth rate was calculated dividing growth rate, k, at 32 ºC by k at 26 ºC. Only values of Fv/Fm at 32 ºC for the last three days of the experiment are shown.

36 0.1 0.1 0.1

0 0 0

-0.1 -0.1 -0.1 Fv/Fm -0.2 -0.2 -0.2

-0.3 -0.3 -0.3

Relative -0.4 -0.4 -0.4 -5 0 5 10 -5 0 5 10 -5 0 5 10 Relative light

0.1 0.1 0.1 0 0 0 ciency ciency ciency ffi ffi ffi

Fv/Fm -0.1 -0.1 -0.1 -0.2 -0.2 -0.2

Relative Photochemical e -0.3 Relative Photochemical e -0.3 Relative Photochemical e -0.3 Relative -0.4 -0.4 -0.4 -5 0 5 10 -5 0 5 10 -5 0 5 10 Relative light dose Relative light dose Relative light dose Relative light

Figure 2. 5 Relative photochemical efficiency of three strains with different thermotolerance under different light conditions. Relative light was calculated by subtracting the total light dose of the experimental conditions (65, 80, 100, 240 and 443 µmol quanta m2s-1) to the initial light conditions (100 µmol quanta m2s-1). Relative photochemical efficiency was calculated with the initial Fv/Fm minus the value after 12 hrs at the light/temperature conditions. Tolerant strain (blue = Smic3), intermediate strain (purple = Smic2), and sensitive strain (red = Stri1). Linear regression with confidence curve fit. Blue line depicts normal growth temperature (26 ºC), red depicts high growth temperature (32 ºC).

37 Supplementary Figures

Smic1 Smic2 Smic3

Snec1 Snec2 Slin1

cells/ml)

4 10

Spil1 Spil2 Spil3 Cell density ( ( density Cell

Stri1 Stri2

Days

Figure S2. 1 Average cell density changes between eleven strains of clade A under different growth temperatures. Bars depict standard error. Data in blue indicate control temperature (26 ºC) and data in red indicates high temperature (32 ºC). Both treatments were grown under light of 100 µmol quanta m-2s-1. Cell density scale is the same for all cultures except for Snec2.

38 Smic1 Smic2 Smic3

) Fv/Fm

Snec1 Snec2 Slin1

Spil1 Spil2 Spil3 Photochemical efficiency ( efficiency Photochemical

Stri1 Stri2

Days

Figure S2. 2 Average Fv/Fm changes between eleven strains of clade A under different growth temperatures. Bars depict standard error. Data in blue indicate control temperature (26 ºC) and data in red indicate high temperature (32 ºC). Both treatments were grown under light of 100 µmol quanta m-2s-1.

39 0.8 A 0.8 B

0.6 0.6

0.4 0.4

0.2 0.2 ) 0 0 0 2 4 0 2 4 0.8 C 0.8 D Fv/Fm

0.6 0.6

0.4 0.4

0.2 0.2

0 0 0 2 4 0 2 4 0.8 E 0.8 F

0.6 0.6

Photochemical efficiency ( Photochemicalefficiency 0.4 0.4

0.2 0.2

0 0 0 2 4 0 2 4 Days

Figure S2. 3 Average Fv/Fm changes between three strains of clade A under different growth lights and temperatures. Bars depict standard error. Data in blue indicate control temperature (26 ºC) and data in red indicate high temperature (32 ºC). Darker color indicates low light of 65 µmol quanta m-2s-1. Intermediate colors indicate light levels of 80, 100, 240 µmol quanta m-2s-1).Lighter color indicates high light of 423 µmol quanta m- 2s-1.

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46 Chapter 3. Temporal transcriptomic response of Symbiodinium microadriaticum (CassKB8) under high temperature acclimation

Introduction

Coral reefs are one of the most biodiverse and productive ecosystems on Earth (Bellwood 1994), with species from most phyla present (Birkeland 1997). This unique level of biodiversity provides goods and services for over 400 million people (Hoegh-Guldberg et al. 2007). Coral reefs are sustained by a symbiotic association between scleractinian corals (cnidarians) and dinoflagellates in the genus Symbiodinium. This partnership has ensured the success of reef-building corals for the last 200 million years by facilitating higher host calcification rates (Stanley 2006). Symbiotic dinoflagellates aid coral calcification by supplying sugars, amino acids, carbohydrates and small peptides, while recycling ammonium and phosphate, a waste resulting from coral metabolism (Muscatine 1990, Trench 1987). Nutrient supply in coral-associated Symbiodinium is increased as the coral skeleton forms a high efficiency light collector, enhancing photosynthesis and carbon production (Enríquez et al. 2005). However, coral reefs are currently threatened by increased nutrient input and sedimentation, coastal deforestation, and an increase in intensity of hurricanes and uncontrolled fisheries. Coral reefs also face challenges due to climate change with more acidic and warmer oceans leading to increased frequency in disruption of the coral-Symbiodinium symbiosis, causing higher rates of lethal bleaching events (Hoegh-Guldberg et al. 2007).

Coral bleaching, the whitening of corals, is the breakdown of the symbiosis between host and dinoflagellate and is evidenced by a decrease in Symbiodinium cell density and/or photosynthetic pigments (Hoegh-Guldberg 1989). Bleaching is a typical response to environmental variation such as temperature, light, salinity, and nutrients but has become more frequent and severe in the last three decades. Bleaching events have been extensively studied in the context of thermal stress and are typically associated with an increase of 0.5 °C to 1.5 °C in average sea surface temperatures (Glynn 1993, Hoegh-

47 Guldberg et al. 2007), especially during prolonged periods (Fitt et al. 2001). Both magnitude and time of exposure to the thermal stress can increase the risk for coral bleaching (Berkelmans and van Oppen, 2006) and are correlated with whether a colony is able to recover (Iglesias-Prieto et al. 1992, Fitt et al. 2001). For example, increments of 3 °C to 4 °C higher than the average summer temperature for 2 days will cause bleaching followed by high mortality, while an increase of 1 °C to 2 °C for 3 to 4 weeks results in gradual bleaching and low mortality (Jokiel and Coles 1990).

While an increase in temperature often induces bleaching, there are variations in response to temperature across reef habitats, geography, and species. During bleaching events, not all coral species in the same area are equally affected by increased temperature, and the degree of bleaching within a species can also be variable (Ulstrup et al. 2006, Penin et al. 2007). Bleaching heterogeneity is related in part to the differences in the thermal sensitivity of the different Symbiodinium species (Iglesias-Prieto et al., 1992, Warner et al. 1999 Tchernov 2004). Differential sensitivity across Symbiodinium species appears to be related to the photosynthetic membrane fluidity (Iglesias-Prieto et al., 1992, Tchernov et al. 2004), but this might not be the case for all species (e.g. Díaz-Almeyda et al. 2011). The effect of temperature on the photosynthetic apparatus is well studied, often using chlorophyll fluorescence techniques (Govindje 1995, Suggett et al. 2011). During thermal physiological stress in corals, there is often a degradation of photosynthetic proteins, synthesis of heat shock proteins, oxidative stress, and inhibition of protein synthesis antenna (Iglesias- Prieto et al. 1992, Iglesias-Prieto and Trench 1997, Warner et al. 1999, Jones et al. 1998, Takahashi et al. 2008, Takahashi et al., 2013). Physiological studies in Symbiodinium can now be contrasted with studies in gene expression in corals, and some of them suggest heat shock proteins and are also implicated during thermal stress, specifically Hsp70 and Hsp90 (Rosic et al., 2011).

Despite the extensive research on the effects of thermal stress on Symbiodinium and its effects on the coral transcriptome, few studies have investigated the effect of high temperature on Symbiodinium gene expression. Karako-Lampert et al. (2006) reported differential gene expression for Symbiodinium under temperature stress amplifying seven

48 transcripts, identifying a molecule involved in cell matrix adhesion. Rosic et al. (2011) evaluated the expression of nine selected putative housekeeping genes under thermal and light stress using RT-PCR. The authors found that the gene expression was relatively stable with few or no changes in gene expression, focusing more on suggesting useful reference genes. Other studies have measured transcriptional changes in a small number of genes under thermal stress (Leggat et al. 2011, McGinley et al., 2012), observing changes on gene expression.

A study of thermal stress measuring gene expression of Symbiodinium in hospite (Barshis et al., 2014) found no-significant differences in gene expression of two strains of Symbiodinium after three days of high temperature. However, these corals were bleached, meaning that the density of symbionts was low and they only measured the gene expression of the few dinoflagellates that remain inside the host. This emphasizes the importance of understanding the effects of temperature in controlled experiments before studying this complex phenomenon in the holobiont. Currently, no study has evaluated global gene expression in culture conditions under high temperature except for the study of Baumgarten et al., (2013), which primarly focused on small RNA expression and its effects on mRNA expression. The authors focused on heat shock rather than acclimation of the algae, using short temperature treatments at 34 °C for twelve hours and 36 °C for four hours.

In the current study work, we took advantage of the well-understood physiology of Symbiodinium microadriaticum and tested the temporal variation in gene expression before and after high temperature acclimation. To avoid environmental noise in gene expression, we cultured the algae in environmental chambers, allowing acclimation by increasing the temperature gradually up to 32 °C. Physiological changes were assessed during 16 days of temperature acclimation. Gene expression of some genes was measured with microarrays at different intervals: before the temperature treatment, six days after temperature treatment, and 16 days after temperature treatment; we used RNA-Seq for measuring gene transcription five and seven days during the acclimation. Our results suggest that changes in gene expression due to the increase in temperature were time

49 dependent. This outcome demonstrates the importance of performing studies during multiple time points to efficiently capture the process of temperature acclimation.

Materials & Methods

Symbiodinium growth and experimental design

Symbiodinium microadriaticum (CassKB8, ITS type A1, SUNY Buffalo collection), originally isolated from Cassiopeia xamachana, was cultured in ASP-8A medium (Guillard and Keller cited in Blank 1987) at 26 °C with all spectrum lights (50 µmol quanta m-2s-1) with 12 hour light–dark cycle in Innovator 44 incubators (New Brunswick, USA). Light intensities were measured inside the culture flasks with a PAM sensor (Walz, USA). Cultures were maintained in logarithmic phase by replacing media every two weeks with an initial concentration of 2x106cells/ml. Control treatments were kept at 26 °C. For high temperature treatment, the growth temperature of the cultures were raised by 0.5 °C every 6 hours until 32 °C was reached (See Figure 3.1). A total of tirty three flasks were used for the experiements: 6 for physiological measurements, 15 for microarray analysis, and 12 for RNA-Seq.

Physiological measurements

To assess for physiological acclimation, growth rate and photochemical activity were measured at high temperature. Additionally, photochemical efficiency was measured as the photosynthetic quantum yield of photosystem II (Fv/Fm) with a MiniPAM fluorometer (Walz, USA) after 30-50 minutes of dark acclimation at the end of the light cycle. Fv/Fm was measured in three independent cultures every day during the first seven days of the experiment.

To evaluate the growth of the culture at each treatment, cell densities were measured by fixing an aliquot of replicate culture (n=3) under two temperatures (control and high temperature) in 10% Lugol solution every three days and counting them with a hematocytometer. Nine independent replicates were counted for each sample. Cell

50 densities were measured for day -2, 2, 4, 6, 9, 11, 13, 16 and 21. Growth rate (k, divisions per day) was calculated for all aliquots according to Guillard (1973) with the following formula:

M ∙ Σ t ∙ Y - Σt ∙ Σt a = ! M ∙ Σ t! - Σt !

k = 3.322 a!

Microarray experiment

Microarrays were used to analyze gene expression over a span of 18 days under two temperature conditions. To evaluate gene expression, three samples were collected two days (-2d) before temperature treatment. The rest of the samples (n=12) were split and additional samples were collected six days (6d) and 16 days (16d) after high temperature treatment started (Figure 3.1). All samples for cell accounts and for RNA isolation were collected at their physiological noon to prevent circadian rhythm variations.

Cells were collected by centrifuging each aliquot for 30 seconds and immediately flash frozen in liquid nitrogen. RNA was extracted by first disrupting the cells using a mix of 0.1 and 0.5 mm zirconia/silica beads (BioSpec Products, Inc.) in QIAZOL lysis reagent (QIAGEN) with a bead beater, followed by a phenol:chloroform extraction (DeSalvo et al. (2008). RNA was quantified with a NanoDrop ND-1000 spectrophotometer (Nanodrop technologies) and amplified with the MessageAmp II aRNA Kit (Ambion) following the manufacturer’s instructions.

Microarrays were designed in-house based on a Symbiodinium microadriaticum (MAC- CassKB8) cDNA library of expressed sequence tags described in Voolstra et al. (2009). We chose 853 clones based on insert size, which were printed on a dual microarray chip containing Symbiodinium spp. and coral (Orbicella faveolata) cDNA clones (DeSalvo et al. 2010).

51 To prepare samples for hybridization, aRNA was reverse transcribed and hydrolyzed. mRNA samples were coupled with fluorescent dyes Cy3 and compared to a pooled reference containing all mRNA samples from this experiment (-2d-26 °C, 6d-26 °C, 6d- 32 °C, 16d-26 °C, and 16d-32 °C), coupled with Cy5 (Amersham). Fluorescent-labeled mRNA samples were hybridized by incubation at 65 °C for 16 hours (DeSalvo et al. (2008). Microarrays were scanned using an Axon 4100B scanner (Molecular Devices) and images were processed with GenePix 6.0 software (Axon). Analyzed data were converted into a MEV format using TIGR Express Converter software (version 1.7). This output was normalized using TIGR MIDAS (Quackenbush 2002). Statistical analysis was performed using Log2 expression values in MultiExperiment Viewer (TM4 Microarray Software Suite, Saaed et al. 2006). To evaluate gene expression changes across treatments, a one-way ANOVA was performed across five conditions. To evaluate the effect of time and temperature in the differential expression, a two-factor ANOVA was calculated (p-values based on 1000 permutations, cut off p < 0.05). Only treatment time points were included for this analysis (6d and 16d) since -2d was collected before high temperature treatment and no sample at high temperature existed yet. All hybridized transcripts were annotated using Blast2GO (Conesa et al., 2005) against InterPro database. Transcripts were compared with a Symbiodinium microadriaticum transcriptome from Bayer et al. (2012). We performed a blastx analysis against the Symbiodinium minitum genome (Shoguchi et al., 2013) and protein domains inferred using HMMER.

RNAseq experiment

When using cDNA microarrays, day six (6d) showed high differential expression with temperature, thus samples around this time point were subsequently sequenced via Illumina HiSeq to asses gene expression. Samples were split into two groups: control temperature (26 °C) and treatment (32 °C), with six replicates per treatment. Temperature was gradually raised by 0.5 °C every 6 hours until 32 °C was reached. Three samples were collected from both temperature treatments at 5 days (5d) and 7 days (7d) after the temperature increase (Figure 3.1). Cell densities were determined by fixing an aliquot of

52 culture in 4% lugol solution every other day. Counts were preformed using a hematocytometer, with a total of nine replicates counted per aliquot per time point.

Total RNA was extracted following the Qiazol protocol as described above. A total of twelve libraries were prepared. From 3.0µg of total RNA, mRNA was purified with the DynaBeads mRNA Purification kit (Ambion) following the manufacturer’s protocol. Successful purification was determined with a Bioanalyzer (Agilent Technologies). mRNA was fragmented using 10x Fragmentation reagent (Ambion) following the manufacturer's protocol. Samples were purified using AMPure RNAClean XP beads at 1.4X concentration. The resulting product was verified by running an Agilent RNA 6000 pico chip to confirm the presence of a peak ranging from 200-250 nucleotides to ensure fragments can overlap. cDNA was synthesized using SuperScript II Reverse Transcriptase (Invitrogen) with a random hexamer (MBI Fermentas) with the following conditions: 45 °C for 50 min, 70 °C for 10 min. Excess dNTP was removed using AMPure XP SPRI beads at 1.4X concentration. Second strand synthesis was performed with T4 DNA polymerase. The product was purified using double AMPure XP SPRI beads at 0.85X. A second selection was performed at 1.4X. Libraries were created with an Illumina TruSeq Library Kit (Illumina, FC-121) following the manufacturer's instructions. Blunt-end DNA fragments were generated by adding end-repair mix. These fragments were phosphorylated and an A-tail mix was added to prepare for ligation. Adapters were ligated to allow multiplexing of all the samples from this experiment. Finally, the library was PCR amplified and the product was purified with AMPure XP beads at 0.9X. The quality of the libraries and the complete removal of adapter were verified by running an Agilent High Sensitivity DNA chip. All samples were pooled and sequenced on a HiSeq 100bp SE reads (Illumina).

Raw data was filtered with the software Illumina CASAVA 1.8 FASTQ filter. In all cases, no more than 30% of the reads were removed from each sample. Low quality sequences were removed using Trimmomatic (Bolger et al.; 2014). Leaving a minimum length of 50bp, sequences were trimmed with quality threshold 3 from the leading and trailing sequence. All transcripts were assembled using Trinity (Grabherr et al.; 2011)

53 with standard parameters. The final assembly was used as a reference for comparisons against individual samples. Coverage was estimated with the Lander/Waterman equation (Lander & Waterman 1988) using CassKB8 transcriptome length calculated of 61,920,532 bp previously calculated (Bayer et al. 2012). Sample replication was evaluated by generating Venn diagrams comparing identity of all reads for each sample against their replicas from each treatment.

The reference was indexed and mapped using Burrows-Wheeler Alignment Tool (Li and Durbin; 2009) with the MEM algorithm. The output was converted to a binary version, sorted and indexed with the Samtools package (Li et al.; 2009). Sequences with low read counts (< 10 for all experiment) were removed from the analysis. Data were normalized and statistical analysis was performed with the R Bioconductor package DESeq (Anders and Huber; 2010). Differential gene expression was assessed via pairwise comparisons. For Differentially Expressed Genes (DEG) analysis with temperature, the comparisons were: 5d-6 °C vs. 5d-32 °C, 7d-26 °C vs. 7d-32 °C with an adjusted p-value cut off of 0.05. For DEG with time the comparisons were: 5d-26 °C vs. 7d-26 °C, 5d-32 °C vs. 7d- 32 °C with an adjusted p-value cut off of 0.05. Overlap of genes between comparisons was determined using Gen-Venn (http://genevenn.sourceforge.net/). The transcriptome was annotated using tBLASTx against the swissprot database. Differentially expressed transcripts were re-annotated using Blast2GO. Additionally, pathways with DEG were searched by the E.C. number and mapped with Kyoto Encyclopedia of Genes and Genomes (KEGG) mapper (Kanehisa et al.; 2000, 2014).

Results

Symbiodinium microadriaticum acclimates to high temperature.

Symbiodinium microadriaticum was able to acclimate to 32 ºC, the temperature at which most corals bleach. The growth rate data (Figure 3.2) showed that both the control and the high temperature treatment cultures were still growing (Figure S3.1), although at high temperature this rate was significantly lower (t-test p<0.0001). Photochemical efficiency

54 was not significantly different between growth temperatures over a period of seven days (Figure 3.3). High growth temperature increased thermotolerance (Figure 3.4).

RNA-Seq libraries quality and assembly

All libraries were successfully sequenced and adapters were successfully removed in silico from all samples (Table S3.1). The raw sequencing read counts ranged from 9,315,895 to 39,516,846. Percentage of adapter sequence was relative low (0-2.5%) except for the sample K2 (26%). Some of these percentages increased after CASAVA filtering. After filtering, the number of reads ranged from 6,786,973 to 28,729,375 with less than 30% of sequences removed at this step. After trimming, no more than 20% of the sequences were removed, indicating an overall good quality run. Adapter sequences remained after the CASAVA filter, but were completely removed after Trimmomatic software. The final high quality read counts used for the remainder of the analysis ranged from 4,716,499 to 25,467,492. In all cases, there were no remaining adapters in the samples. Our assembly showed 128,654 genes total. Percentage of reads mapped to our assembly ranged from 92% to 96%. The average length for all sequences was 86.49 base pairs (Table S3.2). Sequencing coverage was estimated on 194.97 times the total transcriptome reported for Symbiodinium microadriaticum (CassKB8). Sample replication was evaluated comparing the present sequences for each treatment. Overlap of sequences between replicates (n=3 per day) at 26 ºC was 90.05% and 95.33% for day 5 and day 9 respectively. At 32 ºC, overlap of sequences between replicates (n=3 per day) on day five was 88.67% and 97.71% for day 9 (Figure S3.2).

Differential expression is higher over time than between temperatures

Microarrays showed differential expression when comparing three time points at two growth temperatures. Of the 853 genes on the chip, 221 hybridized with our samples with our Symbiodinium 93 features (42 %) being differentially expressed (p<0.05) between time points (6d and 16d). Fifty-two features were found to be differentially expressed when analyzed with one-way ANOVA. More variation in transcriptional response was seen with time, rather than temperature (Figure 3.5). Between temperature (26 ºC vs. 32

55 ºC), 3 transcripts were differentially expressed, while 14 were differentially expressed by the interaction of time and temperature. Some of these genes overlapped between factors (Figure 3.5) so we were able to discriminate the ones that were exclusively affected by each factor. Given that microarray data showed more differential expressed genes at high temperature during 6d, time points around this day were selected for the RNA-Seq analysis.

Data from RNA-Seq still showed higher transcriptional response to time compared to growth temperature (Figure 3.8, 3.9). Pairwise comparisons between temperatures showed an up-regulation of 377 and a down-regulation of 78 genes when comparing 26 ºC versus 32 ºC at 5d (0.33% DEG). At 7d, 821 genes were up-regulated and 191 were down-regulated (1%). Temporal pairwise comparisons showed an up-regulation of 2,668 and a down regulation of 596 genes when comparing 5d versus 7d at 26 ºC (2.5% DEG). When doing this same comparison at 32 ºC, 1,548 genes were up-regulated and 662 were down-regulated (1.7% DEG).

Functions differentially expressed at high temperature during multiple time points

Microarray data showed that increases in temperature generated variation in expression in 19 genes (consistently differentially expressed by temperature, Figure 3.6A). Of the 19 genes, the annotated genes are: CAXB1227 (exoglucanase type 1; P13860), CAXB2664 (protein RCC2; Q9P258), CAXB1877 (Poly ADP-ribose polymerase 10; Q53GL7). CAXB1227 was found to be down-regulated during 6d at 32 ºC and remained down- regulated through 16d. Exoglucanase type 1 is known to be involved in cellulose degradation. CAXB2664 (protein RCC2; Q9P258) is necessary for completion of mitosis and cytokinesis. CAXB1877 (Poly ADP-ribose polymerase 10; Q53GL7) is related to DNA repair and cell death, and might be required for cell cycle progression. We observed a down-regulation of CAXB1227 (similar to gene CBH1, P13860) with the increase in temperature. We also observed and additional exoglucanase, CAXB2672 (gene CEL1, Q00328), increased expression over time, independent of temperature. The similarity of these transcript and CAXB1227 (exoglucanase type 1; P13860, Figure 3.7) suggests that they are related. However, we could not find a complete domain in the second transcript

56 to hypothesize its function. Additionally, we observed genes that showed a significant decrease in gene expression, (CAXB1402, CAXB1224, CAXB1256, CAXB866, CAXB867, and CAXB1016) specifically at 32 ºC at 6d, and with a similar trend during 16d. The function of these genes remains unknown but they might hold an important key for understanding temperature acclimation.

Genes found to be differentially expressed by the interaction of time and temperature with annotations are: CAXB1806 (Kinesin light chain; P46822), AOSF566 (14-3-3 like protein GF14-F), CAXB773 (LOC100005405 protein; B3DIL1), CAXB1391 (Kynurenine 3-monooxygenase; Q6C9M8) and CAXB1306 (protein cbbY; P95649) (Figure 3.6B). In addition to the genes mentioned above, others also showed changes in expression during 6d at 32ºC but returned during 16d to a similar level of expression as - 2d, independent of temperature (Figure 3.6C – changing by the interaction and time). An example of this case is CAXB1254 (tubulin beta chain; P41352).

Multiple genes without a known function were differentially expressed. For example, the microarray data showed two genes of unknown function (CAXB671 and CAXB538) that were differentially expressed when overlapping all effects. CAXB671 expression was found to decrease significantly over time but more intensely during 6d. CAXB538 shows a down-regulation only during 16d at 32 ºC.

Pairwise comparisons between differentially expressed transcripts at 26 ºC and 32 ºC showed an overlap of 7.5% between time points (Figure 3.9 A). Comparing transcriptomes at different time points also showed an overlap of 24.8% between temperatures (Figure 3.9B). In both cases, the genes that overlapped between treatments did not keep the same expression pattern. Few genes were differentially expressed at high temperature in both time points, only 10 genes showed the same expression patter in 5d and 7d. The possible function of only five of these genes was inferred. Down-regulation of a nitrite-reductase large subunit was found under high temperature, in both time points (log2 value of -1.68 during 5d and -2.8 during 7d). Also, in both time points at high temperature, two copies of aldehyde dehydrogenase and a quinoprotein ethanol dehydrogenase were down-regulated. These enzymes are involved in glycolysis and

57 antibiotic production. Also potentially involved in antibiotic production, we found the gene adenylosuccinate lyase up-regulated at high temperature in both time points.

RNA-Seq data also had many differentially expressed genes with high temperature and unknown function. Investigating the function of these genes may contribute to understanding the processes that are occurring during temperature acclimation.

Time-dependent gene expression

With the microarray data, we identified gene expression changes in 50 genes and were able to infer function for 18 genes (Figure 3.7). From the annotated genes, we focused on genes down-regulated at -2d and 6d but up-regulated at 16d with enhanced expression at 32 ºC. We then described the genes that were initially up-regulated at -2d and 6d and later down-regulated at 16d.

In the first group, we found a homologous potassium voltage-gated channel from the subfamily H member 8 KCNH8 (Q96L42), Ankyrin-3 (CAXB1027; Q12955), mRNA- binding protein puf3 (CAXB1241; O94462), Cytochrome b (CAXB1458; O99256), HSP31(CAXB1786; Q04432), exoglucanase CAXB2672 (gene CEL1, Q00328), and glycolysis pathway enzyme 2,3-bisphosphoglycerate-dependent phosphoglycerate mutase (CAXB407; B3QPN8). Our second group of genes with decreasing expression at 16d have CAXB1648 (DnaJ homolog subfamily C member 16; Q5ZKZ4) also known as HSP40, E3 ubiquitin-protein ligase (CAXB1201; Q9LVW9), UDP-N-acetyl-D- mannosamine dehydrogenase (CAXB1387; Q57871) which is involved in acetomido sugar biosynthesis, N-acetylated-alpha-linked acidic dipeptidase 2 (CAXB1498; Q9CZR2) also known as glutamate carboxypeptidase II is involved in post-translation modification, and possible paired amphipathic helix (CAXB649; Q018M0).

There is up-regulation in -2d and 6d, and down-regulation in 16d of both 40S ribosomal protein S2 (AOSC490) and 60S ribosomal protein L11 (AOSC809) with no effect of temperature in their transcription. There was a decrease in tubulinβchain (CAXB1254)

58 over time, compared to -2d, and a decrease of transcript of tubulin α chain at 6d with a later increase at 16d (CAXB709).

Photosynthetic functions under thermal acclimation

Microarray data did not contain differentially expressed genes related to photosynthetic functions. However, RNA-Seq data showed several genes changing expression at high temperature and over time. During 5d of the experiment, an up-regulation of fucoxanthin- chlorophyll a-c protein A, B, and F were up-regulated compared to the control temperature (Figure 3.10). These proteins were not differentially expressed at high temperature during 7d. However, proteins associated with the light reactions of photosynthesis were found to be down-regulation during 7d. Proteins belonging to the core of photosystem II were found to be down-regulated, such as psbE. Additionally, some proteins (psbC and psbB) associated with photosystem II were also down-regulated. Down-regulation of proteins associated with cytochrome b6f complex also occurred at high temperature after seven days of treatment. These genes are cytochrome b6-f complex subunit 4 (petD) and cytochrome b6 (petB). Photosystem I associated proteins were also down-regulated during the second time point: photosystem I P700 chlorophyll a apoprotein A1 (psaA) and photosystem I P700 chlorophyll a apoprotein A2 (psaB). And finally, we identified a gene annotated as an ATP synthase, ATP synthase subunit beta, chloroplastic (atpB), which is also down-regulated under high temperature in 7d (Figure 3.10, Table S3.3). Most of these genes appear to be also significantly down-regulated over time, at 32 ºC.

Genes belonging to the carbon fixation pathway were also found to be differentially expressed. Four genes belonging to the Calvin cycle were found to be up-regulated on day 5 : multiple putative copies of Ribulose biphosphate carboxylase (Rubisco), pyruvate phosphate dikinase, aconitate hydratase 2, and glyceraldehyde-3-phosphate dehydrogenase. Only glyceraldehyde-3-phosphate dehydrogenase remained up-regulated on day 7.

59 Other genes were also differentially expressed over time. At 26 ºC we found overexpression with time of fucoxanthin-chlorophyll a-c protein A, B, E, and F, glutamate synthase, and RUBISCO, and ATP-dependent zinc metalloprotease among others.

Another protein that was also up-regulated with high temperature on 7d is a chloroplast uncharacterized protein ORF91 (Q3BAI2). This protein also appears to be up-regulated over time, at both temperatures (Table S3.4).

Nitrogen metabolism

Several genes were differentially expressed regarding nitrogen metabolism (Table 3.1 and 3.2). Glutamate synthase was up-regulated only with high temperature at 5d or at 26 ºC when comparing 5d versus 7d. Glutamine synthetase was up-regulated only with high temperature at 5d or at 32 ºC when comparing 5d versus 7d. Nitrate reductase was down- regulated at high temperature in both time points, but also when comparing 5d versus 7d at 32 ºC. Finally, nitrite reductase was down-regulated during 7d at high temperature and at 32 ºC when comparing 5d versus 7d.

Chaperone and heat-shock proteins express time and temperature specific

Multiple chaperones and heat-shock proteins were differentially expressed with temperature changes and at different time points. Our microarray data included only two of these genes. HSP31 was found to be up-regulated at 16d, having a higher expression under high temperature (Figure 3.7). A DnaJ C16 (HSP40) was found to be down- regulated at 16d, having a lower expression at high temperature. Our RNA-Seq data showed a high number of heat-shock proteins and chaperones differentially expressed, suggesting a unique time-temperature dependent signature, being more variable over time than with temperature.

At high temperature, during 5d there was an up-regulation of the nuclear DnaJ-C2, the cytoplasmic HtpG and HSP90, and the mitochondrial HSP60-1. Down-regulation of

60 another cytoplasmic HSP90. At 7d, only the up-regulation of HtpG and the down- regulation of a cytoplasmic HSP90 were maintained (Table 3.3). At 26 ºC between time points, we observed that by 7d up-regulation of the following genes: cytoplasmic HSP90, mitochondrial HSP60-1, chloroplast DnaK, and nuclear DnaJ-C2; and down-regulation of mitochondrial HSP60-1, chaperones YciC and BCS1, and cytoplasmic DnaJ (Table 3.4). A similar pattern was observed at 32 ºC, particularly for the genes down-regulated. Up- regulated cytoplasmic 10kDa, 60kDan chaperonines, DnaJ-B7, DnaJ-C, and HtpG were observed.

Other important DEG

New genetic variation might be generated through retrotransposable elements that were overexpressed at high temperature (Table 3.5). Several retrotransposable elements and reverse transcriptase were up-regulated after 7d at high temperature.

Under control conditions, differential expression of secreted and cell wall proteins was observed. In 7d at 26 ºC, multiple cell surface glycoprotein 1, and cell wall protein DAN4 were down-regulated. Up-regulation of others cell surface glycoprotein1, histidine-rich glycoproteins, and protein pmp6 was observed (Table 3.6). None of these changes were observed under high temperature conditions.

Discussion

Physiological acclimation to high temperature has a cost in growth.

Symbiodinium microadriaticum (CassKB8) was able to acclimate to high temperature. Cultures grown at high temperature increased thermotolerance as previously described by Takahashi et al. (2009) and Díaz-Almeyda et al. (2011). Although cultures under high temperature still showed a photochemical efficiency similar to the control temperature, the growth rate was lower at high temperature, thereby temperature compromised overall health of the culture.

61 Differential expression is higher with time rather than with high temperature

The ability to acclimate to lethal temperatures can be impacted by the history of temperatures experienced by the organism (Middlebrook et al. 2008). It has been observed that the gradual increase in temperature (compared to shock) increases the number of transcripts, and has been debated by several authors (see Bowler 2005 for review). Other studies have shown low gene expression changes under high temperature conditions in Symbiodinium (Baumgarten et al., 2013, Barshis et al., 2014) and other dinoflagellates, and similar changes in gene expression were observed (Morey et al., 2011, Johnson et al., 2012, Wang et al., 2014). These changes were higher when comparing the different time points rather than the high temperature treatment itself. Temporal changes in gene expression due to high temperature were observed for the coral Acropora hyacinthus, observing a higher differential expression one hour after heat exposure (27% of genes) compared to a later time point 15 hours after (12%) in a bleaching experiment (Seneca and Palumbi, 2015). Our observations demonstrate that the algal symbiont also shows a temporal pattern in response to high temperature.

Thermal acclimation affects photosynthetic functions under thermal stress

Increase in accessory pigments such as β-carotene and xanthophyll in relation to chlorophyll a is an established mechanisms conferring photoprotection to Symbiodinium (Krämer et al. 2012). This increase in pigments, specifically of xanthophyll, has been observed in Acropora yongeii after five days of thermal stress (Roth et al., 2012). Furthermore, strains of Symbiodinium with the ability to tolerate high temperatures have been documented to have higher concentrations of antioxidants and xanthophylls (Krämer et al., 2012). A xanthophyll protein, the fucoxanthin-chlorophyll a-c protein A, B, and F were found to be up-regulated in 5d at high temperature, suggesting that this photoprotection mechanism is activated with no change in light conditions.

After seven days of thermal acclimation, down-regulation of multiple proteins associated with photosystem II, cytochrome b6f, photosystem I, and ATP synthase were observed. The down-regulation of several of these proteins has been documented previously

62 (McGinley et al., 2012), where they showed down-regulation of psbA after six days at 32 ºC for a Symbiodinium ITS2 type C1-bc. However this strain is not thermotolerant, indicated by the decrease in maximum quantum yield of photosystem II (Fv/Fm) under high temperature. In contrast, down-regulation was not observed for the thermotolerant Symbiodinium ITS2 type D1. In this same study, a psaA gene was down-regulated after 24 hours of incubation at 32 ºC. In our study, all genes related to photosynthetic function that were down-regulated at 7d were predicted to belong to the chloroplast genome (Barbrook et al., 2014). McGinley et al. (2012) suggested that the decrease in expression of these photosynthetic genes might be due to failure in the transcription machinery in the chloroplast. In our case, since this decrease was observed in a thermotolerant strain, we suggest that this decrease in expression is a response mechanism to avoid oxidative stress by reducing the amount of photosynthetic reactions. Oxidative stress is hypothesized to occur after high temperature exposure as a consequence of damage in photosystem II protein D1 (Tchernov et al., 2004), causing an energy imbalance and over-excitation of photosystem II (Huner et al. 1998). An initial quick response to avoid damage by oxidative stress can be the xanthophyll cycle. A more long-term response to acclimation is the modification of the photosynthetic pathway, altering the expression of genes in the chloroplast genome.

Temporal dependent gene expression

The transcriptome of other dinoflagellates, mainly agents of red tides, have been studied for Karenia brevis culture during aging and cell death (Johnson 2012), during N and P depletion (Morey 2011), and for Prorocentrum minimum interacting with bacteria (Wang 2014). Some of the genes differentially expressed in these investigations are also found in our time-dependent gene expression data.

Our microarray data showed high differential expression with time. Some of the differential expressed changes observed in our microarray experiment suggest the beginning of the stationary phase at 16d of the experiment. For example, there was up- regulation in -2d and 6d, and down-regulation in 16d of both 40S ribosomal protein S2 (AOSC490) and 60S ribosomal protein L11 (AOSC809). We did not observe any effect

63 of temperature in their transcription. Johnson and collaborators (2012) also observed an initial down-regulation, then an up-regulation and a final down-regulation at a stationary phase in Karenia brevis of similar transcripts. Since these two genes did not show an effect in transcription related to high temperature, they might be used as housekeeping genes with the consideration that 60S ribosomal protein L11 has been found to change transcription as a response to cold stress in cyanobacteria Synechocystis (Los and Murata, 2004).

When Symbiodinium is grown in culture, we find the majority of cells transitioning from non-flagellated coccoid cells at night to flagellated motile stage during the day (Muscatine et al. 1998). The duration of the motile stage can vary between species and the percentage of motile cells decrease over time within a culture. The observed changes in gene expression of tubulin and actin appear to corroborate previous findings of decreases in motile cells over time ((Fitt and Trench, 1983, for review see Stat et al. 2006). This fact might explain why we observe a decrease in tubulin β chain (CAXB1254) over time, compared to -2d, and a decrease of transcript of tubulin α chain at 6d with a later increase during 16d (CAXB709). In addition to changes in expression occurring between time points, a change can also be observed between temperatures. Changes in tubulin expression have been described mainly for morphological differentiation of cells to become 3T3 adipocytes from preadipocytes (Spiegelman and Farmer 1982). These specific differential expressions appear to happen independently of the temperature treatment for the tubulin a chain. In the case of the tubulin β chain, at t1 there was a significant decrease of transcript.

Chaperones and heat-shock proteins

Microarray and RNA-Seq data showed a particular set of chaperons and heat shock proteins being expressed with high temperature but more variably as time response.

For CAXB1786 (Q04432) we hypothesize its function as HSP31, which has been shown to protect against reactive oxygen species in Saccharomyces cerevisiae (Skoneczna et al. 2007). Several heat shock proteins have been found to be down-regulated in the middle

64 point of a growth curve and become up-regulated closer to the stationary phase in Karenia brevis (Johnson et al., 2012). The up-regulation CAXB1786 during 16d suggests that this time point was the beginning of our stationary phase and that the temperature treatment might speed up this process. This gene has also been shown to be expressed in a circadian oscillation pattern (Sorek et al., 2014). Our second group of genes decreasing transcription at 16d have CAXB1648 (DnaJ homolog subfamily C member 16; Q5ZKZ4) also known as HSP40. This is similar to the decrease described by Johnson et al. (2012) during the stationary phase. An increase of two of these chaperons with the addition of N03 has been described by Morey et al. (2011). It is expected that over time there is a decrease of nutrients such as nitrates and a decrease of light due to self-shading (Rodríguez-Román and Iglesias-Prieto, 2005) so this suggests it is a response of the decrease of NO3. This process is important since this gene has elevated dN/dS in the thermotolerant Symbiodinium clade D (Ladner et al., 2012).

The chaperone protein HtpG is required for optimal recovery after exposure to high temperature in Escherichia coli (Thomas and Baneyx, 1998). The constant up-regulation of this gene in the two time points tested in this study (Table 3.4) suggests that it may be a good candidate to test if different symbionts might have the ability to acclimate to high temperature. Although HtpG was up-regulated in both time points during 6d and 16 d, increasing in expression over time.

Heat shock proteins (HSPs) and chaperones were also observed in the RNA-Seq data, where different set of HSPs and chaperones are up-regulated at 5d compared with 7d. Previously, several heat shock proteins, such as HSP40, HSP70, HSP90 (two isoforms) and dnaJ (four isoforms) were characterized as being expressed during stress (heat, light, nutrient and inorganic carbon addition (Leggat et al. 2007). Using qPCR, the transcription of some of these genes was evaluated under a controlled bleaching experiment using the coral Acropora aspera nubbins infected with Symbiodinium ITS2 type C3 (Leggat et al., 2011). The authors observed gene expression of HSP70 and HSP90 under high temperature treatment. HSP90 was down-regulated after two days of exposure to high temperature. In another experiment, with the coral Acropora millepora,

65 a similar pattern was observed; HSP90 was down-regulated after one day of high temperature (32 ºC) in culture and in hospite (Rosic et al., 2011). In the dinoflagellate Prorocentrum minimum, up-regulation of HSP90 was observed with an increase in temperature (Guo and Ki, 2012). The up-regulation of this gene seems to enhance the activity of a nitric oxide synthase that is possibly linked with high temperature bleaching in the coral Eunicea fusca (Ross 2014). In our data set, HPS90 expression was up- regulated at 5d and down-regulated at 7d; no expressional changes in nitric oxide synthase were observed. HSP70 was up-regulated at the first day of high temperature treatment (32 ºC) after a gradual increase in temperature in a controlled bleaching experiment but no expression changes were observed for later time points (Leggat et al. 2011). Up-regulation was also observed one and three days after high temperature treatment in Acropora millepora, in addition to a slight increase in expression after five days of high temperature treatment. In our data set, this gene is up-regulated at 5d but not at 7d. HSP70 has been implicated in the assembly and repair of proteins of the photosystem II after light damage (Schroda et al. 1999, 2001). HSP70 appears to be regulated by proteins of the DnaJ family. DnaJ was up-regulated at 7d, while a gene from the same family, dnajc, was also up-regulated at 5d. DnaJ genes and HSP90 have a higher dN/dS in a thermotolerant clade D Symbiodinium when compared to a non- thermotolerant clade C strain (Ladner et al., 2012). Although HSP70 and HSP90 genes are conserved in multiple lineages of Symbiodinium (Rosic et al., 2014), variation might be found among thermotolerant and temperature sensitive strains (Barshis et al., 2014).

As observed in table 3.4, the up-regulated chaperones and HSPs at 5d differs from those that are up-regulated at 7d, with the exception of HtpG. This suggests that a different set of chaperones is required at different times during thermal acclimation. We hypothesize that the chaperones and heat-shock proteins at 5d, seem to be related to stress while those that are differentially expressed at 7d are related to acclimation.

Other important DEG

Temporal changes might suggest that Symbiodinium is carefully sensing the available nitrogen source remaining. Nitrogen metabolism changes over time. It has been

66 hypothesized that cell density and pigment concentration is controlled though nitrogen limitation in hospite (Falkowski et al. 1993). Nitrates concentration in cultures has been shown to decrease after 8 to 15 days, depending on the species (Rodriguez-Román and Iglesias-Prieto, 2005). In our case, the cultures were unlikely to be old enough to be limited by nitrogen. However, two differentially expressed genes, belonging to nitrogen metabolism pathway, were identified as a nitrite reductase (comp81826_c0_seq1) and a glutamine synthetase (comp28254_c0_seq1). The first gene, nitrite reductase large subunit, was found to be down-regulated at high temperatures for both time points. This enzyme is part of a nitrogen reduction pathway, catalyzing the reduction of nitirite to ammonia. The glutamine synthetase cytosolic isozyme is up-regulated with high temperature in both time points

DNA transposons and retrotransposons have been detected in Symbiodinium minitum genome (Shoguchi et al. 2013) accounting for 0.503% and 1.054% respectively. This value is significantly lower than what is being found in other organisms (van Oppen et al. 2009). New genetic variation might be generated through retrotransposable elements that were overexpressed at high temperature (Table 3.5). Capy et al. (2000) described that transposable elements might be able to generate new genetic variability as a long-term response to stress. Hochachka and Somero et al. (2002) previously demonstrated that mutations in specific genes support specific long-term temperature adaptations. In this case, although new genetic variability might appear, several genes might be involved in long-term temperature adaptation, so mutations in multiple genes might be needed. Mutations induced by transposable elements have been shown to be involved in environmental adaptation (for review see Casacuberta & Gonzalez 2013).

Finally, glycoprotein type 1 is differentially expressed under mixotrophic conditions (Xiang et al. 2015) which appear be correlated with the smoothness of the cell surface. The transcriptional changes we observed only occurred at normal temperature over time. These changes might be related with changing levels of nutrients in their media. Additionally, Bay et al. (2011) suggested that glycoproteins play a role in post- phagocytosis during the early onset of the coral Acropora tenuis and its symbiont. Since

67 none of these changes were observed at high temperature, our results suggest that might be worth it to investigate possible changes in smoothness of cell surface and implications of these changes during the establishment of symbiosis.

Conclusions

Symbiodinium microadriaticum (CassKB8) was able to acclimate to high temperature under low light conditions. The health of this strain was compromised when grown under 32 ºC, showing a decrease in fitness. S. microadriaticum transcriptomic response presents insights into the mechanisms behind thermoacclimation at different time points. Gene expression profiles changed more over time than under temperature treatments. Sampling at one in time only might either highlight processes that are not important later on, or hide other processes that may be critical for thermal stress response at a different time point. A clear example is gene expression of photosynthetic functions with high temperature. In an initial time point (5d) only photoprotective mechanisms such as fuxoxanthin-chlorophyll a-c binding proteins are differentially expressed. In a later time point (7d), almost all proteins part of the light-dependent photosynthetic pathway were differentially expressed. This particular process might be a key mechanism for successful temperature acclimation. Retrotransposon activity indicates high stress during thermal exposure, which can generate new genetic variation long term. This hypothesis requires further investigation. Microarray data showed that cultures around 18 days old might start to be close to a stationary phase. Our results suggest that at this time point transcriptional changes might be occurring as a result of: sensing and adjusting to small environmental changes such as nitrite and nitrate available in media, changes in life cycle stages going from flagellated to coccoid, and the start of the stationary phase in culture.

Future studies should include more than one time point. Caution should be exerted when choosing time points for physiological and transcriptomic analyses, as time points will likely reveal major differences. In order to better understand the synergistic effects of high temperate and high light, future experiments should incorporate multiple light

68 conditions. Such a combined approach will provide a more realistic approximation to organismal response in natural bleaching events.

69 Figures

Figure 3. 1 Experimental design. Symbiodinium microadriaticum (CassKB8) was grown at normal temperature 26 ºC (blue line, control) and temperature was increased gradually to 32 ºC (red line, high temperature treatment). Cultures were grown at each temperature with three replicates under 50µM quanta m-2 s-1, 12:12 light:dark cycle. Green boxes indicate the time points where RNA samples were collected and analyzed with cDNA microarrays to measure gene expression before experimental treatment, six days after thermal acclimation, and 16 days after thermal acclimation. Orange boxes indicate the time points where RNA samples were collected and analyzed with RNA-Seq to measure gene expression around day six (five days and seven days) since it was found to have high number of differential expressed genes.

70 0.4 ) K 0.3

0.2

0.1 Growth rate ( Growth 0 26ºC 32ºC Growth temperature

Figure 3. 2 Symbiodinium microadriaticum (CassKB8) grown under high temperature has a slower growth rate than when grown at normal temperature for 23 days, with aliquots measured every two-three days. Blue bar depicts normal growth temperature (26 ºC), red bar depicts high growth temperature (32 ºC). Bars depict standard error. Student t test showed significant differences between treatments (p <0.0001).

71 0.8

0.6

0.4 Fv / Fm 0.2

0 1 2 3 4 5 6 7 Days Figure 3. 3 No significant difference was found in photochemical efficiency (Fv/Fm) of Symbiodinium microadriaticum (CassKB8) when grown under normal and high temperature conditions. Blue line represent normal growth temperature (26 ºC), red line represents high growth temperature (32 ºC). Error bars depict standard error.

72 100!

80!

60!

40!

! Efficiency(Fv/Fm) 20! Relative Photochemical 0! 33! 34! 35! 36! 37! 38! 39! 40! 41! 42! Experimental temperature (º C)!

Figure 3. 4 High growth temperature increased thermotolerance of Symbiodinium microadriaticum (CassKB8). Cultures were grown at 26 ºC (blue) and 32 ºC (red). Photochemical efficiency (Fv/Fm) was measured after five minutes of incubation at the experimental temperatures and a control temperature. Change in photochemical efficiency was calculated as relative to control samples incubated at 26 ºC. Data were collected from three independent experiments per growth temperature, with three independent replicates per experimental treatment.

73

Figure 3. 5 A two-factor ANOVA showed that time was the factor that produced higher number of differentially expressed genes compared to temperature. (p<0.05, 1000 iterations).

74 Figure 3. 6 Heatmap showing results from differentially expressed features comparing samples at three time points at two temperatures. Two-factor ANOVA (p<0.05, 1000 iterations) includes samples from day 6 and day 16. One-way ANOVA (p<0.05, 1000 iterations) are marked with a star, includes all samples. A. DEG affected only by temperature. B. DEG affected by the time and temperature. C. DEG affected by temperature and the interaction of both factors. D. DEG affected by the interaction of time and temperature. E. DEG affected by time and the interaction of both factors. F. DEG affected by all factors.

75 Figure 3. 7 Heatmap showing results from differentially expressed features comparing samples at three time points at two temperatures. Two-factor ANOVA (p<0.05, 1000 iterations) includes samples from day six and day 16. One-way ANOVA (p<0.05, 1000 iterations) are marked with a star, includes all samples. DEG affected only by the factor time.

76

Figure 3. 6 Differential expressed genes of samples sequenced by RNA-Seq pairwise comparisons of samples (n=3) at two temperatures (control 26 ºC and high temperature 32 ºC) in two time points (5 days and 7 days after high temperature). Up-regulation of genes was more frequent than down-regulation in all pairwise comparisons. Temporal comparisons showed higher transcriptional response than temperature comparisons.

77

Figure 3. 7 Pairwise comparisons of differential expressed genes. Time generates a higher differential expression of genes. Small arrows next to numbers indicate the number of genes up-regulated (arrow up) or down-regulated (arrow down). A. Temperature comparisons show higher differential expression during day seven compared to day five. B. Time comparisons showed higher number of DEGs at 26 ºC than at 32 ºC.

78

Figure 3. 8 High temperature affects photosynthetic genes differently over time. Log2 values are compared to control temperature (26 ºC). Arrow indicates up-regulation or down-regulation.

79 Tables Table 3. 1 Changes in gene expression regarding nitrogen metabolism with growth temperature. Log2 values of differentially expressed genes are showed. Negative log2 values represent down-regulation of gene compared to the condition mentioned.

Day 5 Day 7 Uniprot Contig 26ºCvs.32ºC 26ºCvs.32ºC ID Annotation Location comp107939_c0_seq1 -5.383 Q06457 Nitrate reductase Nitrite reductase (NADH) large comp46426_c0_seq1 -3.452 P08201 subunit comp85968_c0_seq1 -3.105 P42435 Nitrite reductase [NAD(P)H] Nitrite reductase [NAD(P)H] large comp29832_c0_seq1 -2.537 Q06458 subunit Nitrite reductase [NAD(P)H] large comp81826_c0_seq1 -1.681 -2.804 Q06458 subunit Glutamine synthetase (Glutamate-- comp144466_c0_seq1 -1.529 P22248 ammonia ligase) Cytoplasm comp15485_c0_seq2 0.737 Q9LV03 Glutamate synthase 1 Chloroplast comp27274_c0_seq1 0.757 Q03460 Glutamate synthase [NADH] Chloroplast Glutamine synthetase cytosolic comp86872_c0_seq1 1.432 P14656 isozyme 1-1 Cytoplasm

80 Table 3. 2 Changes in gene expression regarding nitrogen metabolism over time. Log2 values of differentially expressed genes are showed. Negative log2 values represent down-regulation of gene compared to the condition mentioned. 5d= day five of the RNA- Seq experiment; 7d= day seven of the RNA-Seq experiment.

26ºC 32ºC Uniprot Contig d5 vs. d7 d5 vs. d7 ID Annotation Location Small nuclear ribonucleoprotein Sm comp33922_c0_seq1 -0.966 Q9UUC6 D3 Nucleus comp28802_c0_seq2 0.381 Q9LV03 Glutamate synthase 1 [NADH] Chloroplast comp28996_c0_seq4 0.452 Q03460 Glutamate synthase [NADH] Chloroplast comp28802_c0_seq1 0.475 Q9LV03 Glutamate synthase 1 [NADH] Chloroplast comp31867_c0_seq1 -1.137 Q07538 Serine/threonine-protein kinase prp4 comp39944_c0_seq1 -0.930 P36841 Nitrate reductase [NADH] comp11692_c0_seq1 -0.827 P36841 Nitrate reductase [NADH] comp74907_c0_seq1 1.476 P04772 Glutamine synthetase 2 Cytoplasm comp18690_c0_seq1 1.598 P22248 Glutamine synthetase Cytoplasm comp155160_c0_seq1 1.804 O54053 Nitrogen regulatory protein P-II comp124283_c0_seq1 1.941 P43518 Glutamine synthetase Cytoplasm comp18690_c0_seq2 2.988 Q59747 Glutamine synthetase 1 Cytoplasm

81 Table 3. 3 Changes in gene expression of chaperones with high temperature. Log2 values of differentially expressed genes are showed. Negative log2 values represent down- regulation of gene compared to the condition mentioned.

Day 5 Day 7 Uniprot Contig 26ºCvs.32ºC 26ºCvs.32ºC ID Annotation Location comp10843 DnaJ homolog subfamily C _c0_seq1 1.055 Q6NWJ4 member 2 Nucleus comp61145 _c0_seq1 1.167 3.597 P0C938 Chaperone protein HtpG Cytoplasm comp29369 _c0_seq6 1.180 -0.995 O44001 Heat shock protein 90 Cytoplasm comp15432 _c0_seq1 1.805 4.068 P0CJ84 Chaperone protein htpG Cytoplasm comp23711 Chaperonin CPN60-1, _c0_seq2 2.168 Q05045 mitochondrial (HSP60-1) Mitochondrion. comp20180 Heat shock cognate 90 kDa _c0_seq1 -1.100 P54651 protein Cytoplasm comp26417 _c0_seq2 1.372 Q45585 ECF RNA polymerase sigma factor SigW comp26417 _c0_seq1 1.383 Q45585 ECF RNA polymerase sigma factor SigW comp71996 _c0_seq1 1.431 B0SBH9 RNA-binding protein Hfq

82 Table 3. 4 Changes in gene expression of chaperones over time. Log2 values of differentially expressed genes are showed. Negative log2 values represent down- regulation of gene compared to the condition mentioned. 5d= day five of the RNA-Seq experiment; 7d= day seven of the RNA-Seq experiment.

26ºC 32ºC Uniprot d5 vs. d5 vs. Contig d7 d7 ID Annotation Location comp46202_c0_seq1 -1.391 -1.085 P94400 Putative metal chaperone YciC Mitochondrial Mitochondrion comp22067_c0_seq1 -0.967 -1.433 Q9Y276 chaperone BCS1 inner membrane Chaperone protein comp20401_c0_seq3 -0.940 -0.871 B0CAZ0 DnaJ Cytoplasm Chaperonin CPN60-1, comp20401_c0_seq5 -0.819 P29185 mitochondrial Mitochondrion. Chaperonin CPN60-1, comp32898_c0_seq1 -0.753 Q05045 mitochondrial Mitochondrion. Inositol 1,4,5- Endoplasmic trisphosphate receptor reticulum comp22273_c0_seq1 -0.737 Q63269 type 3 membrane Peptidyl-prolyl cis- trans isomerase Cytoplasm. comp35348_c0_seq1 -0.730 Q9FJL3 FKBP65 Nucleus. Q1XDH Chaperone protein Plastid, comp28044_c0_seq1 0.459 2 dnaK chloroplast. Q6NWJ DnaJ homolog comp29935_c0_seq1 0.768 -0.814 4 subfamily C member 2 Nucleus comp21562_c0_seq1 0.808 P39864 Nitrate reductase [NADPH] Peptidyl-prolyl cis- trans isomerase comp21395_c0_seq2 0.970 Q38931 FKBP62 Cytoplasm Peptidyl-prolyl cis- trans isomerase comp69865_c0_seq2 1.019 Q38931 FKBP62 Cytoplasm Cold shock domain- comp27746_c0_seq2 1.217 1.072 Q38896 containing protein 4 Cytoplasm Chaperonin CPN60-1, comp98451_c0_seq1 1.613 Q05045 mitochondrial Mitochondrion.

83 comp110040_c0_seq Cytoplasm, 1 1.656 Q12798 Centrin-1 cytoskeleton comp29369_c0_seq7 1.677 O44001 Heat shock protein 90 Cytoplasm comp29369_c0_seq6 1.746 O44001 Heat shock protein 90 Cytoplasm comp29369_c0_seq3 1.806 O44001 Heat shock protein 90 Cytoplasm 60S ribosomal protein comp10718_c0_seq1 -0.877 P49166 L37-A Cytoplasm Cold shock domain- comp27746_c0_seq1 0.975 Q38896 containing protein 4 Cytoplasm comp105393_c0_seq Q7Z6W 1 1.065 7 DnaJ homolog subfamily B member 7 Chaperone protein comp61145_c0_seq1 1.922 P0C938 HtpG Cytoplasm comp155664_c0_seq T-complex protein 1 1 1.931 Q76NU3 subunit zeta Cytoplasm Chaperone protein comp21584_c0_seq1 2.256 Q64VI7 DnaJ Cytoplasm Chaperone protein comp15432_c0_seq1 2.860 P0CJ84 htpG Cytoplasm comp87409_c0_seq1 3.320 Q8A6P7 10 kDa chaperonin Cytoplasm A0M7D comp84922_c0_seq1 3.475 9 60 kDa chaperonin Cytoplasm comp167035_c0_seq 1 3.688 Q1GJ36 60 kDa chaperonin Cytoplasm comp242678_c0_seq Q9XCA 1 3.747 9 60 kDa chaperonin Cytoplasm comp255728_c0_seq 1 3.784 P95678 60 kDa chaperonin Cytoplasm comp341238_c0_seq 1 3.948 Q1QIL6 60 kDa chaperonin 3 Cytoplasm comp313587_c0_seq 1 4.190 B4S6H2 60 kDa chaperonin Cytoplasm comp241573_c0_seq Q9XCB 1 4.524 0 10 kDa chaperonin Cytoplasm comp192072_c0_seq A0M7D 1 4.947 9 60 kDa chaperonin Cytoplasm

84 Table 3. 5 Retrotransposable elements and related genes differentially expressed. Log2 values of differentially expressed genes are showed. Negative log2 values represent down-regulation of gene compared to the condition mentioned. 5d= day five of the RNA- Seq experiment; 7d= day seven of the RNA-Seq experiment.

26ºC 32ºC Uniprot Contig d5 vs. d7 d5 vs. d7 ID Annotation Retrovirus-related Pol polyprotein from type-1 retrotransposable element R2 comp29704_c0_seq1 0.778 Q03278 (Fragment) Retrovirus-related Pol polyprotein from type-1 retrotransposable element R2 comp29704_c0_seq3 0.816 Q03278 (Fragment) comp28898_c0_seq1 0.854 O30409 Tyrocidine synthase 3 Retrovirus-related Pol polyprotein from comp29704_c0_seq4 0.955 Q03278 type-1 retrotransposable element R2 comp259181_c0_seq 1 2.615 P33883 Acyl-homoserine-lactone synthase comp26642_c0_seq1 1.672 P08548 LINE-1 reverse transcriptase homolog LINE-1 retrotransposable element ORF2 comp28080_c0_seq2 1.975 P11369 protein LINE-1 retrotransposable element ORF2 comp28080_c0_seq1 2.026 P11369 protein comp24023_c0_seq1 2.032 P08548 LINE-1 reverse transcriptase homolog comp182564_c0_seq 1 2.119 P08548 LINE-1 reverse transcriptase homolog LINE-1 retrotransposable element ORF2 comp28281_c0_seq1 2.222 P11369 protein comp25885_c0_seq1 2.271 P08548 LINE-1 reverse transcriptase homolog LINE-1 retrotransposable element ORF2 comp22531_c0_seq1 2.291 P11369 protein comp22962_c0_seq1 2.296 P08548 LINE-1 reverse transcriptase homolog LINE-1 retrotransposable element ORF2 comp4897_c0_seq1 2.361 P11369 protein comp22767_c0_seq1 2.428 P08548 LINE-1 reverse transcriptase homolog comp27296_c0_seq1 2.451 P08548 LINE-1 reverse transcriptase homolog comp23977_c0_seq1 2.597 P08548 LINE-1 reverse transcriptase homolog comp3169_c0_seq1 2.622 P08548 LINE-1 reverse transcriptase homolog

85 LINE-1 retrotransposable element ORF2 comp28092_c0_seq1 2.640 P11369 protein LINE-1 retrotransposable element ORF2 comp21067_c0_seq1 2.644 P11369 protein comp26642_c0_seq2 2.647 P08548 LINE-1 reverse transcriptase homolog comp247967_c0_seq LINE-1 retrotransposable element ORF2 1 2.759 P11369 protein comp20202_c0_seq1 -1.031 Q1E1H4 Stress response protein NST1 comp287435_c0_seq LINE-1 retrotransposable element ORF1 1 2.468 P11260 protein

86 Table 3. 6 Differentially expressed glycoproteins only found to change at the control temperature. Log2 values of differentially expressed genes are showed. Negative log2 values represent down-regulation of gene compared to the condition mentioned. 5d= day five of the RNA-Seq experiment; 7d= day seven of the RNA-Seq experiment.

26ºC Uniprot Contig d5 vs. d7 ID Annotation Location Secreted, cell wall, S- comp27255_c0_seq1 -1.393 Q06852 Cell surface glycoprotein 1 layer. Secreted, cell wall, S- comp29703_c0_seq1 -1.267 Q06852 Cell surface glycoprotein 1 layer. Secreted, cell wall, S- comp29678_c0_seq1 -1.240 Q06852 Cell surface glycoprotein 1 layer. comp29635_c0_seq3 -1.219 P47179 Cell wall protein DAN4 Secreted, cell wall Uncharacterized threonine- rich GPI-anchored comp29580_c0_seq1 -1.212 Q96WV6 glycoprotein PJ4664 Cell membrane Secreted, cell wall, S- comp29678_c0_seq2 -1.116 Q06852 Cell surface glycoprotein 1 layer. comp29635_c0_seq4 -1.102 P47179 Cell wall protein DAN4 Secreted, cell wall Secreted, cell wall, S- comp27921_c0_seq1 -1.060 Q06852 Cell surface glycoprotein 1 layer. Secreted, cell wall, S- comp29462_c0_seq1 -1.045 Q06852 Cell surface glycoprotein 1 layer. Sodium-dependent phosphate transport protein Membrane; Multi-pass comp26362_c0_seq1 -1.034 Q06495 2A membrane protein. Secreted, cell wall, S- comp29759_c0_seq3 -1.023 Q06852 Cell surface glycoprotein 1 layer. Secreted, cell wall, S- comp29635_c0_seq1 -0.968 Q06852 Cell surface glycoprotein 1 layer. Secreted, cell wall, S- comp29759_c0_seq4 -0.919 Q06852 Cell surface glycoprotein 1 layer. Secreted, cell wall, S- comp29759_c0_seq2 -0.905 Q06852 Cell surface glycoprotein 1 layer. Secreted, cell wall, S- comp29759_c0_seq1 -0.870 Q06852 Cell surface glycoprotein 1 layer. comp29635_c0_seq2 -0.765 Q06852 Cell surface glycoprotein 1 Secreted, cell wall, S-

87 layer. Secreted, cell wall, S- comp27761_c0_seq1 -0.740 Q06852 Cell surface glycoprotein 1 layer. comp13547_c0_seq1 0.664 P04929 Histidine-rich glycoprotein comp13735_c0_seq1 0.862 P04929 Histidine-rich glycoprotein Probable outer membrane Secreted, cell wall. Cell comp88302_c0_seq1 0.877 Q9Z899 protein pmp6 outer membrane Membrane; Single-pass comp20005_c0_seq2 0.891 Q01102 P-selectin type I membrane protein. comp57141_c0_seq1 1.071 P04929 Histidine-rich glycoprotein

88 Supplemental Figures Figure S3. 1 Cell density of Symbiodinium microadriaticum (CassKB8). Linear regression with confidence curve fit. Blue line depicts normal growth temperature (26 ºC), red depicts high growth temperature (32 ºC). Whole model test for 26 ºC: F 33, 2678 = 2 747.99, p < 0.0001, R = 0.895. Whole model test for 32 ºC: F 33, 2678 = 208.24, p < 0.0001, R2= 0.703.

89 Figure S3. 2 Venn diagrams comparing replicate samples per temperature per day. The identity of all reads were compared for each sample against their replicas from each treatment. Numbers show the number of transcripts at each intersection. The intersection between the three replicates shows the number of sequences present in all samples, and the total percentage that these sequences represent.

90 Supplemental Tables Table S3. 1 Detailed read counts used during data processing. Remaining adapter after trimmomatic was not included as it was 0 in all cases.

Raw number Raw Illumina Sequences after Remaining Sequences after Sample of sequences adapter CASAVA filter Illumina adapter trimmomatic t1 26 ºC K1 18,005,461 2% 13,660,258 2.17% 11,976,389 t1 26 ºC K2 12,522,263 26% 9,065,756 34.90% 4,716,499 t1 26 ºC K3 17,089,579 0.40% 13,158,175 0.27% 11,699,139 t1 32 ºC K4 18,802,850 0% 13,711,358 0% 12,155,281 t1 32 ºC K5 9,315,895 2.50% 6,786,973 2.60% 5,674,251 t1 32 ºC K6 28,511,649 0.60% 20,439,040 0.60% 17,530,063 t2 26 ºC K7 19,737,330 0.10% 14,503,029 0.10% 12,799,100 t2 26 ºC K8 18,353,726 1.50% 13,231,130 1.47% 11,371,956 t2 26 ºC K9 39,516,846 0.23% 28,729,375 0.23% 25,467,492 t2 32 ºC K10 17,003,345 1.50% 12,156,484 1.75% 10,401,224 t2 32 ºC K11 15,450,176 7% 10,573,432 7.30% 7,993,562 t2 32 ºC K12 22,632,831 0.40% 16,402,039 0.44% 14,258,350

91 Table S3. 2 Final number of sequences mapped to the reference containing all samples from this experiment, assembled with Trinity. Mapping was performed with the MEM algorithm of BWA. 5d= five days of treatment; 7d= seven days of treatment.

Mapping Number of sequences Average Sample Percentage mapped to reference length

5d 26 ºC K1 95% 12,068,394 86.27 5d 26 ºC K2 94% 4,764,648 86.16 5d 26 ºC K3 96% 11,781,822 86.82 5d 32 ºC K4 96% 12,259,447 86.52 5d 32 ºC K5 94% 5,759,728 85.98 5d 32 ºC K6 95% 17,753,254 86.29 7d 26 ºC K7 94% 12,890,603 86.71 7d 26 ºC K8 92% 11,497,822 86.54 7d 26 ºC K9 95% 25,717,149 86.93 7d 32 ºC K10 92% 10,523,136 86.45 7d 32 ºC K11 93% 8,077,947 85.72 7d 32 ºC K12 93% 14,372,572 86.29

TOTAL 94% 147,466,522 86.49

92 Table S3. 3 Temporal changes in gene expression of photosynthetic pathway. Log2 values of differentially expressed genes are showed. Negative log2 values represent down-regulation of gene compared to the condition mentioned.

Day 5 Day 7 Uniprot 26ºCvs.32º 26ºCvs.32º Contig C C ID Annotation Fucoxanthin-chlorophyll a-c binding comp29772_c0_seq4 0.800 Q40300 protein F Fucoxanthin-chlorophyll a-c binding comp29911_c0_seq1 1.524 Q40296 protein B Cytochrome b559 subunit alpha comp29802_c0_seq1 -1.677 A0T0A3 (PSII reaction center subunit V) Cytochrome b559 subunit alpha comp16074_c0_seq1 -1.425 P05333 (PSII reaction center subunit V) Photosystem II CP43 reaction center comp82205_c0_seq1 -0.837 Q6B917 protein (Protein P6) Photosystem I P700 chlorophyll a comp28389_c0_seq1 -0.811 P48112 apoprotein A1] (PsaA) Q9XQV Photosystem I P700 chlorophyll a comp28871_c0_seq1 -0.810 2 apoprotein A2 (PsaB) Q9XQV Photosystem I P700 chlorophyll a comp27948_c0_seq1 -0.799 2 apoprotein A2 (PsaB) Photosystem II CP47 chlorophyll comp26146_c0_seq1 -0.770 A2T359 apoprotein (Protein CP-47) ATP synthase subunit beta (F- comp10682_c0_seq1 -0.769 Q06J29 ATPase subunit beta) Photosystem II CP47 chlorophyll comp10684_c0_seq1 -0.745 A2T359 apoprotein Cytochrome b6-f complex subunit 4 comp24481_c0_seq1 -0.727 A0T0T7 (17 kDa polypeptide) Q9XQU comp22983_c0_seq1 -0.678 7 Cytochrome b6 Photosystem I P700 chlorophyll a comp27948_c0_seq2 -0.645 Q6B8U6 apoprotein A1 (PsaA) Q9XQU comp19641_c0_seq1 -0.631 7 Cytochrome b6 comp119715_c0_seq -0.589 Q06J29 ATP synthase subunit beta (F-

93 1 ATPase subunit beta) Photosystem II CP43 reaction center comp29786_c0_seq1 -0.554 P49472 protein (Protein P6) comp29450_c0_seq2 6 1.118 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq8 1.234 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq1 2 1.305 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq2 3 1.324 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq1 6 1.333 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq1 3 1.348 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq1 8 1.362 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq2 7 1.383 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq1 7 1.408 Q3BAI2 Uncharacterized protein ORF91 comp29450_c0_seq2 5 1.408 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq4 1.410 Q3BAI2 Uncharacterized protein ORF91 comp29450_c0_seq2 8 1.417 Q3BAI2 Uncharacterized protein ORF91 comp29450_c0_seq3 2 1.418 Q3BAI2 Uncharacterized protein ORF91 comp29450_c0_seq4 3 1.420 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq2 8 1.429 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq3 0 1.445 Q3BAI2 Uncharacterized protein ORF91 comp29450_c0_seq5 1.470 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq2 2 1.473 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq2 1.488 Q3BAI2 Uncharacterized protein ORF91

94 9 comp29722_c3_seq9 1.503 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq1 0 1.509 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq6 1.511 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq2 0 1.533 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq7 1.572 Q3BAI2 Uncharacterized protein ORF91

95 Table S3. 4 Temperature changes in photosynthetic pathway. Log2 values of differentially expressed genes are showed. Negative log2 values represent down- regulation of gene compared to the condition mentioned. 5d= day five of the RNA-Seq experiment; 7d= day seven of the RNA-Seq experiment.

26ºC 32ºC Uniprot d5 vs. d5 vs. Contig d7 d7 ID Annotation Phosphoenolpyruvate/phosphate comp24209_c0_seq1 -0.768 Q5VQL3 translocator 3, chloroplastic Glutamate synthase 1 [NADH], comp28802_c0_seq2 0.381 Q9LV03 chloroplastic comp28996_c0_seq4 0.452 Q03460 Glutamate synthase [NADH], amyloplastic Ribulose bisphosphate carboxylase comp29735_c1_seq1 0.467 Q41406 (Fragment) Glutamate synthase 1 [NADH], comp28802_c0_seq1 0.475 Q9LV03 chloroplastic Fucoxanthin-chlorophyll a-c binding protein comp29298_c0_seq9 0.491 Q40296 B, chloroplastic comp29658_c0_seq1 Fucoxanthin-chlorophyll a-c binding protein 2 0.500 Q40297 A, chloroplastic ATP-dependent zinc metalloprotease FTSH, comp29104_c1_seq2 0.569 Q39444 chloroplastic (Fragment) Presequence protease 1, comp51115_c0_seq1 0.571 Q9LJL3 chloroplastic/mitochondrial ATP-dependent zinc metalloprotease FTSH, comp29104_c1_seq1 0.593 Q39444 chloroplastic (Fragment) Caroteno-chlorophyll a-c-binding protein comp24712_c0_seq1 0.600 P55738 (Fragment) Fucoxanthin-chlorophyll a-c binding protein comp29298_c0_seq6 0.611 Q40300 F, chloroplastic (Fragment) Ribulose bisphosphate carboxylase comp29748_c1_seq3 0.625 Q41406 (Fragment) ATP-dependent zinc metalloprotease FTSH, comp26543_c0_seq1 0.656 Q39444 chloroplastic (Fragment) Fucoxanthin-chlorophyll a-c binding protein comp20177_c0_seq2 0.695 Q40296 B, chloroplastic comp21979_c0_seq1 0.712 Q9M8D3 Probable

96 phosphoribosylformylglycinamidine synthase, chloroplastic/mitochondrial ATP-dependent zinc metalloprotease FTSH, comp26543_c0_seq2 0.721 Q39444 chloroplastic (Fragment) Granule-bound starch synthase 1, comp25322_c0_seq1 0.751 A2Y8X2 chloroplastic/amyloplastic comp112328_c0_seq Fucoxanthin-chlorophyll a-c binding protein 1 0.778 Q40297 A, chloroplastic Fucoxanthin-chlorophyll a-c binding protein comp26581_c0_seq1 0.783 Q40300 F, chloroplastic (Fragment) comp29658_c0_seq2 Fucoxanthin-chlorophyll a-c binding protein 1 0.816 Q40300 F, chloroplastic (Fragment) Granule-bound starch synthase 1, comp27025_c0_seq2 0.828 P04713 chloroplastic/amyloplastic Fucoxanthin-chlorophyll a-c binding protein comp45443_c0_seq1 0.836 Q40300 F, chloroplastic (Fragment) Fucoxanthin-chlorophyll a-c binding protein comp28686_c0_seq2 0.844 Q40296 B, chloroplastic Fucoxanthin-chlorophyll a-c binding protein comp29513_c0_seq6 0.851 Q40297 A, chloroplastic comp198866_c0_seq A6MW3 1 0.866 3 Protein PsbN Q9SDM Chlorophyll a-b binding protein 1B-21, comp29481_c0_seq3 0.871 1 chloroplastic comp27650_c0_seq4 0.881 P08212 ATP synthase subunit c, chloroplastic comp53463_c0_seq1 0.885 Q8LKI3 Inner membrane ALBIN comp6205_c0_seq1 0.899 O34627 Blue-light photoreceptor Fucoxanthin-chlorophyll a-c binding protein comp22834_c0_seq2 0.900 Q40301 E, chloroplastic comp29022_c0_seq4 Ribulose bisphosphate carboxylase, 0 0.935 Q5ENN5 chloroplastic 1,4-alpha-glucan-branching enzyme 2-2, comp15000_c0_seq1 0.967 Q9LZS3 chloroplastic/amyloplastic Magnesium transporter MRS2-11, comp66518_c0_seq1 0.971 Q058N4 chloroplastic Fucoxanthin-chlorophyll a-c binding protein comp21689_c0_seq1 1.056 Q40297 A, chloroplastic

97 Fucoxanthin-chlorophyll a-c binding protein comp11396_c0_seq2 1.063 Q40301 E, chloroplastic ATP-dependent zinc metalloprotease FTSH, comp26543_c0_seq3 1.064 Q39444 chloroplastic (Fragment) Fucoxanthin-chlorophyll a-c binding protein comp59622_c0_seq1 1.085 Q40296 B, chloroplastic Fucoxanthin-chlorophyll a-c binding protein comp94543_c0_seq1 1.096 Q40301 E, chloroplastic Fucoxanthin-chlorophyll a-c binding protein comp67256_c0_seq1 1.108 Q40296 B, chloroplastic comp16074_c0_seq1 1.294 P05333 Cytochrome b559 subunit alpha Ribulose bisphosphate carboxylase comp11435_c0_seq1 1.297 Q41406 (Fragment) comp29658_c0_seq1 Fucoxanthin-chlorophyll a-c binding protein 7 1.811 Q40296 B, chloroplastic comp29802_c0_seq1 -2.093 A0T0A3 Cytochrome b559 subunit alpha Q9XQV Photosystem I P700 chlorophyll a comp27948_c0_seq1 -1.713 2 apoprotein A2 Q9XQV Photosystem I P700 chlorophyll a comp28871_c0_seq1 -1.552 2 apoprotein A2 comp24481_c0_seq1 -1.438 A0T0T7 Cytochrome b6-f complex subunit 4 Photosystem II CP43 chlorophyll comp29786_c0_seq1 -1.199 P49472 apoprotein Photosystem II CP43 chlorophyll comp10206_c0_seq1 -1.150 P49472 apoprotein comp35713_c0_seq1 -1.080 Q55318 Ferredoxin--NADP reductase Photosystem I P700 chlorophyll a comp28389_c0_seq1 -0.996 P48112 apoprotein A1 comp211888_c0_seq 1 -0.976 B0BZL2 ATP synthase subunit alpha 1 Photosystem II CP43 chlorophyll comp82205_c0_seq1 -0.976 Q6B917 apoprotein Photosystem II CP47 chlorophyll comp10684_c0_seq1 -0.947 A2T359 apoprotein comp29779_c0_seq1 -0.942 A0T0T0 Photosystem II D2 protein comp7377_c0_seq1 -0.923 A0T0T0 Photosystem II D2 protein comp19641_c0_seq1 -0.912 Q9XQU Cytochrome b6

98 7 Photosystem II CP47 chlorophyll comp26146_c0_seq1 -0.829 A2T359 apoprotein Q1ACM comp29934_c0_seq1 -0.814 8 ATP synthase subunit alpha, chloroplastic Photosystem I P700 chlorophyll a comp27948_c0_seq2 -0.802 Q6B8U6 apoprotein A1 Caroteno-chlorophyll a-c-binding protein comp28719_c0_seq1 0.850 P55738 (Fragment) comp26591_c0_seq1 0.959 A0T0L2 Photosystem I iron-sulfur center comp33822_c0_seq1 1.132 Q4G381 Cytochrome b559 subunit beta comp13363_c0_seq1 1.224 Q42564 L-ascorbate peroxidase 3, peroxisomal comp156476_c0_seq 1 2.274 Q5LNN9 ATP synthase subunit alpha comp321441_c0_seq 1 2.275 A0M791 ATP synthase subunit beta comp316161_c0_seq 1 2.651 Q1GEU6 ATP synthase subunit alpha comp283788_c0_seq 1 2.786 Q9ZS97 UPF0051 protein ABCI8, chloroplastic comp145802_c0_seq Acyl-[acyl-carrier-protein] desaturase 5, 1 2.801 A2XSL4 chloroplastic comp139877_c0_seq 1 2.904 Q1GEU6 ATP synthase subunit alpha comp227_c0_seq1 3.170 P13357 ATP synthase subunit beta comp145214_c0_seq 1 3.714 P37395 Thioredoxin comp225165_c0_seq 1 4.209 A0M791 ATP synthase subunit beta comp28884_c0_seq1 2 0.882 0.897 P08212 ATP synthase subunit c, chloroplastic comp29450_c0_seq2 5 0.887 2.421 Q3BAI2 Uncharacterized protein ORF91 comp29450_c0_seq5 0.927 2.238 Q3BAI2 Uncharacterized protein ORF91 comp29450_c0_seq4 3 0.928 2.373 Q3BAI2 Uncharacterized protein ORF91 comp29450_c0_seq3 0.983 2.446 Q3BAI2 Uncharacterized protein ORF91

99 2 comp29450_c0_seq2 8 1.012 2.571 Q3BAI2 Uncharacterized protein ORF91 comp29450_c0_seq2 4 1.078 2.531 Q3BAI2 Uncharacterized protein ORF91 comp29450_c0_seq2 6 1.103 2.129 Q3BAI2 Uncharacterized protein ORF91 comp29450_c0_seq1 5 1.151 2.435 Q3BAI2 Uncharacterized protein ORF91 comp29351_c0_seq1 1.155 2.497 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq6 1.171 2.450 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq2 0 1.183 2.446 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq1 3 1.184 2.528 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq3 0 1.193 2.472 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq2 9 1.198 2.463 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq1 6 1.202 2.546 Q3BAI2 Uncharacterized protein ORF91 comp19833_c0_seq1 1.202 1.794 P08212 ATP synthase subunit c, chloroplastic comp29722_c3_seq2 2 1.202 2.446 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq9 1.206 2.365 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq1 8 1.245 2.589 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq7 1.253 2.366 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq2 8 1.263 2.740 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq2 7 1.287 2.610 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq2 3 1.329 2.565 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq1 0 1.332 2.570 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq4 1.362 2.411 Q3BAI2 Uncharacterized protein ORF91

100 comp29450_c0_seq1 2 1.390 2.565 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq8 1.407 2.655 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq1 7 1.587 2.810 Q3BAI2 Uncharacterized protein ORF91 comp29722_c3_seq1 2 1.640 2.874 Q3BAI2 Uncharacterized protein ORF91 Fucoxanthin-chlorophyll a-c binding protein comp16992_c0_seq1 1.648 1.306 Q40297 A, chloroplastic comp29430_c0_seq2 1.760 3.663 Q3BAI2 Uncharacterized protein ORF91 comp29430_c0_seq5 1.927 3.707 Q3BAI2 Uncharacterized protein ORF91 comp27666_c0_seq1 2.914 4.539 Q3BAI2 Uncharacterized protein ORF91

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110 Chapter 4. Discussion

This dissertation focused on characterizing the physiology and transcriptomics of high temperature acclimation of the symbiotic dinoflagellate Symbiodinium.

In chapter one, I review the current knowledge on the effects of high temperature as one of the causes of coral bleaching. Temperature affects mainly Symbiodinium, a symbiotic dinoflagellate associated with corals and other cnidarians. This group of algae is extremely diverse. The lack of morphological characters delayed our understanding of this diversity. With the help of molecular markers, this diversity has been documented, dividing Symbiodinium into clades (clade A-I). Species descriptions are limited but recent progress has unveiled that Symbiodinium has a wide range of hosts and different life styles such as symbiotic, free-living, and opportunistic. Given this, focusing in one specific lineage is necessary to truly understand physiological differences between strains. Gene expression of some of these dinoflagellates under high temperature conditions was also reviewed. Recent progress in next-generation sequencing has resulted in multiple studies tackling high temperature effects in Symbiodinium. However, must of this research have focus on finding core genes that allow thermal acclimation. Most of these efforts haven’t been completely successful for two reasons. One, the transcriptomic comparisons have been made in far-related species, having low overlap in the genetic makeup of the species. Two, experimental temperatures used are too high compared to what this algae usually experience, causing highly apoptotic responses rather than acclimation responses. Finally, Symbiodinium being a group with high physiological and genetic diversity offers the possibility to be a model organism to understand the effects of climate change. This review allowed recognizing current gaps in knowledge, and design experiments that improves current methodological approaches, to better understand temperature acclimation.

In chapter 2, I characterized temperature acclimation of a specific lineage of Symbiodinium. Eleven strains representing five species of the lineage clade A were grown under high temperature conditions. My results showed that Symbiodinium can be

111 classified as: tolerant (same fitness under control and high growth temperature), with intermediate tolerance (detrimental effect in fitness), and sensitive to high temperature (dying). The intraspecific variation in thermotolerance is as high as the interspecific variation. This thermotolerance was not phylogenetically constrained, meaning that is not restricted to only one group. I also evaluated the photoacclimation capacity under control and high temperature, showing that under high light stress accelerates the damage of high temperature. The strains tested in my experiments showed that some of them posses the ability to acclimate to high temperature, being wide spread across most of the species of this lineages. However, acclimation to high temperature decreases growth. Finer-scale resolution such as species but even at population level might be able to help elucidate mechanisms of thermal acclimation. Future research can use this phylogenetic framework to do more meaningful comparisons among thermotolerant/non-thermotolerant strains.

My third chapter address in detailed the transcriptomic response of high temperature acclimation. For this purpose, we chose a strain with intermediate tolerance and evaluated in detail the physiology of temperature acclimation and the gene transcription changes through time. Physiological data showed that Symbiodinium microadriaticum acclimated to high temperature successfully under low light conditions, with a small decrease in fitness. Gene transcription was evaluated two days before temperature treatment, six days, and 16 days after a gradual increase of temperature, finding that transcription had a higher temporal response than the one compared to temperature response. Temperature transcriptional response was higher in day six. RNA-Seq, transcription was evaluated in day five and day seven of temperature acclimation. The temporal transcriptional response was still high, demonstrating an important effect on nitrogen changes, and life cycle changes. Several photosynthetic functions, chaperones, and heat-shock proteins appear to be key for successful temperature acclimation. Retrotransposon activity might be a mechanism to generate new variation under high temperature stress, but additional research is needed to test this hypothesis.

Future studies should consider the vast genetic and physiological diversity of Symbiodinium. When performing transcriptional experiments, one should be cautions

112 when choosing time points for physiological and transcriptomic data. Time series appear to be particularly important for Symbiodinium growing in culture. Particularly, these differences are due to accumulation of high temperature damage and changes in stages of their life cycle.

Caution should be taken when using this information for bringing these conclusions to practice when managing of coral reef ecosystems.

113 Erika Díaz-Almeyda

Professional Education

2013 – 2016 The Pennsylvania State University, Department of Biology University Park, PA Ph.D. Biology with Dr. Monica Medina 2009-2013 University of California, Quantitative Systems Biology Merced, CA Ph.D. Candidate with Dr. Monica Medina – transferred 2007 University of North Carolina Wilmington, NC Coral Reef Field Research Semester 2008 Universidad Nacional Autónoma de México, Instituto de Ciencias del Puerto Morelos, Mar y Limnología Quintana Roo, MX M.Sc. Marine Sciences and Limnology with Dr. Patricia Thomé 2002 Universidad Nacional Autónoma de México, Facultad de Ciencias, Mexico City, MX Instituto de Ecología BS: Biology with Dr. Daniel Piñero

Fellowships and Awards Henry Popp Graduate Assistantship The Pennsylvania State University 2014 QSB Summer Fellowship University of California, Merced 2013 QSB Summer Fellowship University of California, Merced 2012 Miguel Velez Fellowship University of California, Merced 2012-2013 Travel Award American Society of Microbiology 2010 CONACYT Scholarship for Ph. D. studies Tuition and salary, 305321 2009-2013 Study abroad support UNAM DGEP 2007 CONACYT Scholarship for Masters studies Salary, registration number: 2005-2007 202239. Research support 2004 Undergraduate dissertation support 2001-2002

Publications

Jordán-Garza A.G., Maruri M.C., Martos-Fernández F.J., Maldonado-Cuevas M.A., Díaz- Almeyda E., van Woesik R. Recovery of the endangered Acropora palmata in the Gulf of Mexico and Mexican Caribbean (Accepted). Sorek M., Díaz-Almeyda E.M., Medina M., Levy O. 2014. Circadian clocks in symbiotic corals: The duet between Symbiodinium algae and their coral host. Marine Genomics. Díaz-Almeyda E., Thomé P.E., El Hafidi M., Iglesias-Prieto R. 2010. Differential stability of photosynthetic membranes and fatty acid composition at elevated temperature in Symbiodinium. Coral Reefs 10.1007/s00338-010-0691-5. Jordán-Garza A.G., Díaz-Almeyda E.M., Iglesias-Prieto R., Maldonado M.A., Ortega J. 2009. Mass mortality of Canthigaster rostrata at the northeast coast of the Yucatan Peninsula. Coral Reefs Online First. Hernandez-Becerril, D.U., Díaz-Almeyda E.M. The Nitzschia bicapitata group, new records of the genus Nitzschia, and further studies on species of Pseudo-nitzschia (Bacillariophyta) from Mexican Pacific coasts. in "Microalgal biology, evolution and ecology" Ed.: Richard M. Crawford, Brian Moss, David G. Mann and Hans R. Preisig. Nova Hedwigia Beiheft 130, 2006, 392 pp.