This repository contains the data specified in the paper entitled "A refined picture of the native Amine Dehydrogenase family revealed by extensive biodiversity screening". It includes:1. NAD-dependent_enzymes.fa.gz - The library of 20,315,745 sequences of NADPH-dependent enzymes recovered from genomic and metagenomic sequence databases.2. ref-AmDHs17959_nr.fa.gz - The library of 17,959 ref-AmDH sequences recovered from genomic and metagenomic sequence databases. Considered as the updated nat-AmDH family.3. NAD_subfams_HMMs.tar.gz - The library of 104,686 Hidden Markov Models (HMMs) of NADPH-dependent protein subfamilies. As described in the paper, those HMMs were obtained by clustering the set uploaded here as NAD-dependent_enzymes.fa.gz and building one HMM per subfamily.4. ref-AmDHs_HMMs.tar.gz - This repertory includes the HMMs used to update the nat-AmDH family (all_ASMC_no_nad,hmm and all_ASMC_nad_dom.hmm) as well as the ones used to search for distant homologs; HMMs designed for the phylogenetic and structure-based groups built from the set uploaded here as ref-AmDHs17959_nr.fa.gz (asmc_*.hmm and phylo_*.hmm) .5. ref-AmDH_ASMC_models.tar.gz - The library of 9886 ref-AmDH models built using the ASMC pipeline.6. 72_ref-AmDH_seqs_representatives.txt.gz - Sequences of the 72 representative ref-AmDHs experimentally tested and found to be active.7. 17_nat-AmDH_seqs_specific_feature.txt.gz - Sequences of the 17 nat-AmDHs with specific feature that have been heterologously expressed and tested.

This repository contains the data specified in the paper entitled "A refined picture of the native Amine Dehydrogenase family revealed by extensive biodiversity screening". It includes:1. NAD-dependent_enzymes.fa.gz - The library of 20,315,745 sequences of NADPH-dependent enzymes recovered from genomic and metagenomic sequence databases.2. ref-AmDHs17959_nr.fa.gz - The library of 17,959 ref-AmDH sequences recovered from genomic and metagenomic sequence databases. Considered as the updated nat-AmDH family.3. NAD_subfams_HMMs.tar.gz - The library of 104,686 Hidden Markov Models (HMMs) of NADPH-dependent protein subfamilies. As described in the paper, those HMMs were obtained by clustering the set uploaded here as NAD-dependent_enzymes.fa.gz and building one HMM per subfamily.4. ref-AmDHs_HMMs.tar.gz - This repertory includes the HMMs used to update the nat-AmDH family (all_ASMC_no_nad,hmm and all_ASMC_nad_dom.hmm) as well as the ones used to search for distant homologs; HMMs designed for the phylogenetic and structure-based groups built from the set uploaded here as ref-AmDHs17959_nr.fa.gz (asmc_*.hmm and phylo_*.hmm) .5. ref-AmDH_ASMC_models.tar.gz - The library of 9886 ref-AmDH models built using the ASMC pipeline.6. 72_ref-AmDH_seqs_representatives.txt.gz - Sequences of the 72 representative ref-AmDHs experimentally tested and found to be active.7. 17_nat-AmDH_seqs_specific_feature.txt.gz - Sequences of the 17 nat-AmDHs with specific feature that have been heterologously expressed and tested.

This dataset contains 27 MAGs from the family of Endozoicomonadaceae generated from a subset of Tara Pacific metagenomes. Contextual information of the MAGs can be found in the associated publication: Ecology of Endozoicomonadaceae in three coral species across the Pacific Ocean, Hochart et al, submitted

This dataset contains 27 MAGs from the family of Endozoicomonadaceae generated from a subset of Tara Pacific metagenomes. Contextual information of the MAGs can be found in the associated publication: Ecology of Endozoicomonadaceae in three coral species across the Pacific Ocean, Hochart et al, submitted

This data is the result of the primary analysis of the 16S rRNA gene sequencing data collected from all islands as part of the Tara Pacific expedition. The analysis was conducted using cutadapt/snakemake/dada2 and usearch. A full README is contained within the data upload. Taxonomic abundance tables (ASVs, OTUs) released together with the TARA Pacific publications can be found in Version 1.1.0 of this repository.

This data is the result of the primary analysis of the 16S rRNA gene sequencing data collected from all islands as part of the Tara Pacific expedition. The analysis was conducted using cutadapt/snakemake/dada2 and usearch. A full README is contained within the data upload. Taxonomic abundance tables (ASVs, OTUs) released together with the TARA Pacific publications can be found in Version 1.1.0 of this repository.

Summary To obtain a proxy for the stress level of collected corals, we checked for previous occurrences of bleaching events at sampled reef sites by matching island GPS coordinates to the Reef Check dataset (reefcheck.org) obtained from Sully et al (2019). For each Tara Pacific island coordinate, we determined the Reef Check site that was closest (in terms of distance in km); we only considered Reef Check data that was within a 10 km circumference. We further determined short- and long-term climate variables that are known to affect coral stress resilience for all Tara Pacific collection sites that are available from Lombard et al (2022). These data allow to assess if corals from a given site were exposed higher/lower prevalence of thermal stress events and bleaching prior to sampling (over previous years). References Sully, S., Burkepile, D. E., Donovan, M. K., Hodgson, G. & van Woesik, R. A global analysis of coral bleaching over the past two decades. Nature Communications 10, 1264 (2019). Fabien Lombard, Guillaume Bourdin, Stephane Pesant, Sylvain Agostini, Alberto Baudena, Emilie Boissin, Nicolas Cassar, Megan Clampitt, Pascal Conan, Ophélie Da Silva, Celine Dimier, Eric Douville, Amanda Elineau, Jonathan Fin, J. Michel Flores, Jean François Ghiglione, Benjamin C.C. Hume, Laetitia Jalabert, Seth G. John, Rachel L. Kelly, Ilan Koren, Yajuan Lin, Dominique Marie, Ryan McMinds, Zoé Mériguet, Nicolas Metzl, David A. Paz-García, Maria Luiza Pedrotti, Julie Poulain, Mireille Pujo-Pay, Josephine Ras, Gilles Reverdin, Sarah Romac, Eric Röttinger, Assaf Vardi, Christian R. Voolstra, Clémentine Moulin, Guillaume Iwankow, Bernard Banaigs, Chris Bowler, Colomban de Vargas, Didier Forcioli, Paola Furla, Pierre E. Galand, Eric Gilson, Stéphanie Reynaud, Shinichi Sunagawa, Olivier Thomas, Romain Troublé, Rebecca Vega Thurber, Patrick Wincker, Didier Zoccola, Denis Allemand, Serge Planes, Emmanuel Boss, Gaby Gorsky. Open science resources from the Tara Pacific expedition across the surface ocean and coral reef ecosystems. Submitted (2022)

Summary To obtain a proxy for the stress level of collected corals, we checked for previous occurrences of bleaching events at sampled reef sites by matching island GPS coordinates to the Reef Check dataset (reefcheck.org) obtained from Sully et al (2019). For each Tara Pacific island coordinate, we determined the Reef Check site that was closest (in terms of distance in km); we only considered Reef Check data that was within a 10 km circumference. We further determined short- and long-term climate variables that are known to affect coral stress resilience for all Tara Pacific collection sites that are available from Lombard et al (2022). These data allow to assess if corals from a given site were exposed higher/lower prevalence of thermal stress events and bleaching prior to sampling (over previous years). References Sully, S., Burkepile, D. E., Donovan, M. K., Hodgson, G. & van Woesik, R. A global analysis of coral bleaching over the past two decades. Nature Communications 10, 1264 (2019). Fabien Lombard, Guillaume Bourdin, Stephane Pesant, Sylvain Agostini, Alberto Baudena, Emilie Boissin, Nicolas Cassar, Megan Clampitt, Pascal Conan, Ophélie Da Silva, Celine Dimier, Eric Douville, Amanda Elineau, Jonathan Fin, J. Michel Flores, Jean François Ghiglione, Benjamin C.C. Hume, Laetitia Jalabert, Seth G. John, Rachel L. Kelly, Ilan Koren, Yajuan Lin, Dominique Marie, Ryan McMinds, Zoé Mériguet, Nicolas Metzl, David A. Paz-García, Maria Luiza Pedrotti, Julie Poulain, Mireille Pujo-Pay, Josephine Ras, Gilles Reverdin, Sarah Romac, Eric Röttinger, Assaf Vardi, Christian R. Voolstra, Clémentine Moulin, Guillaume Iwankow, Bernard Banaigs, Chris Bowler, Colomban de Vargas, Didier Forcioli, Paola Furla, Pierre E. Galand, Eric Gilson, Stéphanie Reynaud, Shinichi Sunagawa, Olivier Thomas, Romain Troublé, Rebecca Vega Thurber, Patrick Wincker, Didier Zoccola, Denis Allemand, Serge Planes, Emmanuel Boss, Gaby Gorsky. Open science resources from the Tara Pacific expedition across the surface ocean and coral reef ecosystems. Submitted (2022)

The Tara Pacific expedition (2016-2018) sampled coral ecosystems at 111 sampling sites around 32 islands in the Pacific Ocean, and sampled the surface of oceanic waters at 249 locations, resulting in the collection of nearly 58,000 samples (Gorsky et al. 2019, Planes et al. 2019, Flores et al. 2020). The expedition was designed to systematically study corals, fish, plankton, and seawater, and included the collection of samples for advanced biogeochemical, molecular, and imaging analysis. Here we provide a high-resolution historical dataset that spans from 2002 to each sites’ sampling date and gives an overview of past climate variability and heatwaves experienced by corals sampled at each site. Ocean skin temperature (11 and 12 µm spectral bands longwave algorithm) was extracted from 1km resolution level-2 MODIS-Aqua and MODIS-Terra from 2002 to the sampling date and from level-2 VIIRS-SNPP from 2012 to the sampling date. Day and night overpasses were used to maximize data recovery. Following recommendations from NASA Ocean Color (OB.DAAC), only SST products of quality 0 and 1 were used. The 9 closest pixels to the sampling sites of each scene were extracted. All the extracted pixels from the 3 satellites were then averaged daily to obtain daily SST averages and standard deviations time series for each sampling site, from 2002 to the sampling date. Each time series was first averaged on a Julian day basis to provide a seasonal average. This yearly seasonal average was triplicated and concatenated into a 3-year seasonal cycle to apply a digital low pass filter on the middle year without generating artifacts. A digital low pass filter (filter order 3, pass band ripple 0.1; “filfilt” function in matlab) with 36 Julian days windows was applied to the concatenated time series to remove high frequency noise. The middle year was then extracted from the concatenated time series to recover the seasonal cycle. The sea surface temperature anomaly was calculated as the SST minus the seasonal cycle over the full time series. Considering the short periods of missing data (mean of the 95th percentile of the duration of consecutive days with missing data: 9.8 ± 4.1 days), the missing values in the SST and SST anomaly time series were linearly interpolated in order to calculate thermal stress indices. The SST anomaly frequency was calculated as the number of days over the past 52 weeks when the SST anomaly is greater than or equal to 1 °C. Thermal stress indices relevant to coral reef health were then calculated using methodology developed for the Coral Reef Temperature Anomaly Database (CoRTAD) data base (Saha et al. 2019). Events of cold temperature accumulation were also reported to cause bleaching and mortality (Lirman et al. 2011; González-Espinosa & Donner 2020), therefore, the same set of indices were calculated for cold stress adapting the CoRTAD method, but using the minimum weekly climatologies. A condensed table containing single values associated with each sampling site was created ('TaraPacific_SST_timeseries_mean_products') extracting the minimum, maximum, sum, averages, standard deviations, and value recorded at the sampling day of each of these indices (detailed in the readme file provided with the dataset 'README_TaraPacific_historical_SST.md'). Additional metrics of the last heating and cooling events as well as the time of recovery is also provided to represent the state of thermal stress at the day of sampling.

The Tara Pacific expedition (2016-2018) sampled coral ecosystems at 111 sampling sites around 32 islands in the Pacific Ocean, and sampled the surface of oceanic waters at 249 locations, resulting in the collection of nearly 58,000 samples (Gorsky et al. 2019, Planes et al. 2019, Flores et al. 2020). The expedition was designed to systematically study corals, fish, plankton, and seawater, and included the collection of samples for advanced biogeochemical, molecular, and imaging analysis. Here we provide a high-resolution historical dataset that spans from 2002 to each sites’ sampling date and gives an overview of past climate variability and heatwaves experienced by corals sampled at each site. Ocean skin temperature (11 and 12 µm spectral bands longwave algorithm) was extracted from 1km resolution level-2 MODIS-Aqua and MODIS-Terra from 2002 to the sampling date and from level-2 VIIRS-SNPP from 2012 to the sampling date. Day and night overpasses were used to maximize data recovery. Following recommendations from NASA Ocean Color (OB.DAAC), only SST products of quality 0 and 1 were used. The 9 closest pixels to the sampling sites of each scene were extracted. All the extracted pixels from the 3 satellites were then averaged daily to obtain daily SST averages and standard deviations time series for each sampling site, from 2002 to the sampling date. Each time series was first averaged on a Julian day basis to provide a seasonal average. This yearly seasonal average was triplicated and concatenated into a 3-year seasonal cycle to apply a digital low pass filter on the middle year without generating artifacts. A digital low pass filter (filter order 3, pass band ripple 0.1; “filfilt” function in matlab) with 36 Julian days windows was applied to the concatenated time series to remove high frequency noise. The middle year was then extracted from the concatenated time series to recover the seasonal cycle. The sea surface temperature anomaly was calculated as the SST minus the seasonal cycle over the full time series. Considering the short periods of missing data (mean of the 95th percentile of the duration of consecutive days with missing data: 9.8 ± 4.1 days), the missing values in the SST and SST anomaly time series were linearly interpolated in order to calculate thermal stress indices. The SST anomaly frequency was calculated as the number of days over the past 52 weeks when the SST anomaly is greater than or equal to 1 °C. Thermal stress indices relevant to coral reef health were then calculated using methodology developed for the Coral Reef Temperature Anomaly Database (CoRTAD) data base (Saha et al. 2019). Events of cold temperature accumulation were also reported to cause bleaching and mortality (Lirman et al. 2011; González-Espinosa & Donner 2020), therefore, the same set of indices were calculated for cold stress adapting the CoRTAD method, but using the minimum weekly climatologies. A condensed table containing single values associated with each sampling site was created ('TaraPacific_SST_timeseries_mean_products') extracting the minimum, maximum, sum, averages, standard deviations, and value recorded at the sampling day of each of these indices (detailed in the readme file provided with the dataset 'README_TaraPacific_historical_SST.md'). Additional metrics of the last heating and cooling events as well as the time of recovery is also provided to represent the state of thermal stress at the day of sampling.