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. 2023 Jun 1;14(1):3038.
doi: 10.1038/s41467-023-38499-1.

Telomere DNA length regulation is influenced by seasonal temperature differences in short-lived but not in long-lived reef-building corals

Alice Rouan #  1   2 , Melanie Pousse #  3   4   5 , Nadir Djerbi #  3   4   5 , Barbara Porro  3   4   5 , Guillaume Bourdin  6 , Quentin Carradec  7   8 , Benjamin Cc Hume  9 , Julie Poulain  7   8 , Julie Lê-Hoang  7   8 , Eric Armstrong  7   8 , Sylvain Agostini  10 , Guillem Salazar  11 , Hans-Joachim Ruscheweyh  11 , Jean-Marc Aury  7   8 , David A Paz-García  12 , Ryan McMinds  3   13   14 , Marie-Josèphe Giraud-Panis  3   4   5 , Romane Deshuraud  3   4   5 , Alexandre Ottaviani  3   4   5 , Lycia Die Morini  3 , Camille Leone  3 , Lia Wurzer  3 , Jessica Tran  3 , Didier Zoccola  4   15 , Alexis Pey  3   4   5 , Clémentine Moulin  8   16 , Emilie Boissin  17 , Guillaume Iwankow  17 , Sarah Romac  18 , Colomban de Vargas  8   18 , Bernard Banaigs  17 , Emmanuel Boss  6 , Chris Bowler  8   19 , Eric Douville  20 , Michel Flores  21 , Stéphanie Reynaud  4   15 , Olivier P Thomas  22 , Romain Troublé  8   16 , Rebecca Vega Thurber  23 , Serge Planes  8   17 , Denis Allemand  4   15 , Stephane Pesant  24 , Pierre E Galand  8   25 , Patrick Wincker  7   8 , Shinichi Sunagawa  11 , Eric Röttinger  3   4   5 , Paola Furla  3   4   5 , Christian R Voolstra  9 , Didier Forcioli  3   4   5 , Fabien Lombard  8   26   27 , Eric Gilson  28   29   30   31
Affiliations

Telomere DNA length regulation is influenced by seasonal temperature differences in short-lived but not in long-lived reef-building corals

Alice Rouan et al. Nat Commun. .

Abstract

Telomeres are environment-sensitive regulators of health and aging. Here,we present telomere DNA length analysis of two reef-building coral genera revealing that the long- and short-term water thermal regime is a key driver of between-colony variation across the Pacific Ocean. Notably, there are differences between the two studied genera. The telomere DNA lengths of the short-lived, more stress-sensitive Pocillopora spp. colonies were largely determined by seasonal temperature variation, whereas those of the long-lived, more stress-resistant Porites spp. colonies were insensitive to seasonal patterns, but rather influenced by past thermal anomalies. These results reveal marked differences in telomere DNA length regulation between two evolutionary distant coral genera exhibiting specific life-history traits. We propose that environmentally regulated mechanisms of telomere maintenance are linked to organismal performances, a matter of paramount importance considering the effects of climate change on health.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Telomere DNA length (TL) variation among two genera of reef-building coral in 32 islands of the Pacific Ocean.
a Mean Telomere DNA length TL (in kilobases) distribution of the host (hTL, purple) and their symbionts (sTL, green) for the Pocillopora spp. samples (left) and the Porites spp. samples (right). b Maps of log-transformed mean TL averaged at the sampling site level for the host (hTL, purple) and their symbionts (sTL, green), for the Pocillopora spp. samples (left) and the Porites spp. samples (right). The results are displayed as pie-charts with each sampling site for a given island is represented as a slice. Island names are displayed, and pie-charts have been displayed to avoid overlap. Source data are provided as a Source Data file.
Fig. 2
Fig. 2. Telomere DNA length (TL) variation is determined by island.
Percentage of TL variation explained by the island of origin, Symbiodiniaceae and bacterial communities, and colony morphology (diameter) for Pocillopora spp. and Porites spp. colonies across 32 islands of the Pacific Ocean. In this analysis, i.e., mean, median, Q1, Q3 and IQ were used. n refers to the number of samples. The boxplots are defined as follows: the lower and upper bounds of the box represent the first (Q1) and the third (Q3) quartile, respectively. The entire box represents the interquartile range (IQ). The median is represented as a line across the box. Whiskers extending from Q1 and Q3 are defined as 1.5xIQ. Source data are provided as a Source Data file.
Fig. 3
Fig. 3. Relationships between environmental variables and coral telomere DNA length variation.
Results of a two-dimensions sparse partial least squares (sPLS) regression of TL (hTL and sTL) and environmental variables (contextual at the time and sampling and historical as recorded from 2002 to the sampling date). Clustered image map of the two sPLS dimensions, displaying pairwise correlations between TL (bottom) and environmental variables (right). Red and blue indicate positive and negative correlations, respectively. Hierarchical clustering was performed within the mixOmics cim function based on the sPLS regression model. Source data are provided as a Source Data file.
Fig. 4
Fig. 4. Negative correlation of coral telomere DNA length and expression of telomere genes in Pocillopora spp.
a Distribution of hTL-correlated genes for which more than 25% of the variation in their expression is explained by one of four predictor variables: the island of origin, the host species (shown as “species”), the Symbiodiniaceae communities and hTL. The number of genes in each distribution is indicated above each violin plot. b Pie-charts representing the proportion of significant (p-value < 0.05, Fisher’s exact test) Biological Process pathways for human homologs. Five categories of pathways are defined: Biological Process pathways associated with the terms telomere, cell cycle, DNA replication and DNA repair determined from the genes whose expression variance is associated with island, Symbiodiniaceae composition, host species and hTL ‘from panel a). The “Other” category gathers the remaining pathways. The full list of Biological Process pathways and the five categories that we defined are shown in Supplementary Data 3. c Venn diagram of the hTL-correlated genes found in the four categories of pathways defined in panel b: telomere, replication, cell cycle and DNA repair. Among them, the number of genes positively and negatively correlated with hTL are indicated as: n+ m– (n genes positively correlated, m genes negatively regulated. The five hTL negatively correlated genes belonging only to the telomere category are indicated: TRF and TPP1 are two subunits of the telomere capping factor shelterin, XRCC5/KU80 is a DNA repair protein involved in telomere maintenance while NAT10 and EXOSC10are two proteins reported to be invoved in telomerase regulation. d Correlogram obtained with Spearman correlation of hTL and the expression of genes belonging to the telomere category (panels b, c); all significantly correlated between each other (p < 0.05). p-values were adjusted by the Benjamini–Hochberg method. e Expression by island of telomere genes selected in panel c. The expression (TPM) of each gene is normalized to the mean expression value of I01 (Las Perlas) (n = 103 samples). The boxplots of a and e are defined as follows: the lower and upper bounds of the box represent the first (Q1) and the third (Q3) quartile, respectively. The entire box represents the interquartile range (IQ). The median is represented as a line across the box. Whiskers extending from Q1 and Q3 are defined as 1.5xIQ. Source data are provided as a Source Data file.
Fig. 5
Fig. 5. Relationships between environmental variables and telomere gene expression.
Results of a two-dimensions sparse partial least squares (sPLS) regression of telomere gene expression (measured as TPM) and environmental variables (contextual at the time and sampling and historical as recorded from 2002 to the sampling date). Clustered image map of the two sPLS dimensions, displaying pairwise correlations between genes (bottom) and environmental variables (right). Red and blue indicate positive and negative correlations, respectively. Hierarchical clustering was performed within the mixOmics cim function based on the sPLS regression model. Source data are provided as a Source Data file.
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