dataesr/scientific-paragraphs-categorization huggingface dataset:
Background and Aims Plant survival under extreme drought events has been associated with xylem vulnerability to embolism (the disruption of water transport due to air bubbles in conduits). Despite the ecological and economic importance of herbaceous species, studies focusing on hydraulic failure in herbs remain scarce. Here, we assess the vulnerability to embolism and anatomical adaptations in stems of seven herbaceous Brassicaceae species occurring in different vegetation zones of the island of Tenerife, Canary Islands, and merged them with a similar hydraulic-anatomical data set for herbaceous Asteraceae from Tenerife. • Methods Measurements of vulnerability to xylem embolism using the in situ flow centrifuge technique along with light and transmission electron microscope observations were performed in stems of the herbaceous species.
, 2008)  and the dependency on grazed grasslands for our livestock. The main reason for neglecting herb hydraulics is that their fragile stems and often low hydraulic conductance make vulnerability curves technically more challenging. However, recent fine-tuning of the high-throughput in situ flow centrifuge method (cavitron;  Lens et al. , 2016; Dória et al. , 2018)  and the new optical vulnerability technique  (Skelton et al. , 2017)  have yielded stem P 50 data of herbaceous species, which opens up new opportunities to boost the virtually neglected aspect of herb hydraulics and predict future crop productivity and survival  (Challinor et al. , 2009) , especially in a world facing climate change  (Rahmstorf and Coumou, 2012; Dai, 2013). In addition to the understudied aspect of herb hydraulics, we also investigate stem anatomical characters to assess poorly known structure-function relationships in herbaceous stems.
Plant material and climate data We collected the Brassicaceae specimens throughout the island of Tenerife, in different vegetation zones with different mean annual precipitation and aridity indices. The climatic data of precipitation and temperature for each of the sampling sites were provided by Agencia Estatal de Meteorología (AEMET, Spanish Government), covering a period from 110 to 30 years depending on the meteorological station. We received the data from five different meteorological stations (Anaga San Andrés, Arico Bueno, Arafo, Laguna Instituto and Vilaflor) matching the five sampling sites (Supplementary Data Fig. S1 ). We used the mean annual precipitation for each site, and calculated the potential evapotranspiration using the  Thornthwaite equation (1948). The aridity indices were calculated as a ratio of mean annual precipitation to mean annual potential evapotranspiration  (UNEP, 1997).
The specimens of H. incana and S. orientale were collected from two different populations occurring in contrasting environments. The northern area of La Laguna (mean annual precipitation = 526. 9 mm; aridity index = 0. 68) and the southern area of Vilaflor (mean annual precipitation = 396. 3 mm; aridity index = 0. 53) were the wetter collection sites for H. incana and S. orientale populations, respectively. The drier sites were the southern areas of Guímar (mean annual precipitation = 311. 8 mm; aridity index = 0. 39) and the region of Arico Bueno (mean annual precipitation = 264. 3 mm; aridity index = 0. 34), for H. incana and S. orientale, respectively (Supplementary Data Fig. S1 ). The four annual species of Asteraceae, Cladanthus mixtus (L. ) Oberpr. & Vogt. , Coleostephus myconis (L. ) Cass.
The rotation speed of the centrifuge was then gradually increased by -0. 5 or -1 MPa to lower xylem pressure. The percentage loss of conductivity (PLC) of the stem was determined at each pressure step following the equation: PLC = 100 Å 1 - K K max ã (1) where K max represents the maximum conductance of the stem and K represents the conductance associated at each pressure step. The vulnerability curves, showing the change in percentage loss of conductivity according to the xylem pressure, were obtained using the Cavisoft software (Cavisoft v1. 5, University of Bordeaux, Bordeaux, France). A sigmoid function  (Pammenter and Van der Willigen, 1998)  was fitted to the data from each sample, using the following equation with SAS 9. 4 (SAS 9. 4, SAS Institute, Cary, NC, USA): PLC = 100 1 + exp S 25 * (P i -P 50 ) (2) where S (% MPa -1 ) is the slope of the vulnerability curve at the inflexion point, P is the xylem pressure value used at each step, and P 50 is the xylem pressure inducing 50 % loss of hydraulic conductivity.
Statistical analyses We tested the effect of both species and mean annual precipitation on the various hydraulic parameters (P 12 , P 50 , P 88 and slope) using an analysis of covariance (ANCOVA). A log transformation, when necessary, was applied to the predictive variables to deal with heteroscedasticity and/or non-normality  (Zuur et al. , 2007). A post-hoc Tukey's HSD test, from the R package Agricolae  (Mendiburu, 2017) , was used to test whether hydraulic parameters differ amongst species. To test the difference in P 50 between the two Brassicaceae populations growing in contrasting environments (H. incana and S. orientale), we used linear mixed effects model, with the factor species as random effect, from the nlme R package  (Pinheiro et al. , 2018). We applied simple linear regressions to test for the relationship between P 50 , climate data and anatomical variables.
The anatomical characters and P 50 are the response variables (rank transformed) and the mean annual precipitation is the predictive variable. PERMANOVA was performed using the adonis function in the Vegan R package  (Oksanen et al. , 2015) , based on Euclidean distances and 999 permutations. Later, a principal component analysis (PCA) was conducted using the function rda in the package Vegan, to observe simultaneously the relationships amongst the species, the main stem anatomical variables, the physiological variable (P 50 ) and the mean annual precipitation (P R ). We tested the relationship between some of the stem anatomical variables used in PCA with Pearson's coefficient correlation. All analyses were performed using R version 3. 4. 3 (R Core Team, 2017) in R  Studio version 1. 1. 414 (R Studio Team, 2016).
Structure-function relationships in the herbaceous stems show correlation between embolism resistance and anatomy The stem anatomical variables that best explain the variation in P 50 are the proportion of lignified area per total stem area (P LIG ; which is a measure of stem woodiness) (Fig. 4 ) and the thickness of the intervessel pit membrane (T PM ) (Fig. 5 ) (P < 0. 001; R 2 = 0. 6783) (Supplementary Data Tables  S2  and S4 ). The P 50 -P LIG relationship remains significant for the separate data sets (P < 0. 001; R 2 = 0. 58 for Brassicaceae and P < 0. 01; R 2 = 0. 48 for Asteraceae), while the P 50 -T PM correlation disappears when analysing the Brassicaceae and Asteraceae data sets separately (P = 0. 2164, R 2 = 0. 040 vs. P = 0. 6175, R 2 = -0. 099, respectively). In addition, P LIG is the main variable explaining 69 % of the P 50 variation, while T PM explains the remaining 31 % (Supplementary Data Tables  S4 ).
The S. orientale population growing in the drier sampling site shows a higher proportion of lignified area per total stem area (P LIG ), thicker intervessel pit membranes (T PM ) and thicker intervessel walls (T VW ) than the population growing in the more humid sampling site (Fig. 6 ; Table  1 ) (Supplementary Data Table  S2 ). No significant anatomical differences were found between the two populations of H. incana growing in contrasting environments. All Brassicaceae observed have vestured pits (Fig. 5B -D and 6C, D), while these are absent in the Asteraceae species. No differences in the level of vesturing are observed amongst the embolism-resistant vs. vulnerable Brassicaceae species.
Interspecific and intraspecific stem P 50 variation across herbaceous eudicots is strongly linked to precipitation Our data set, comprising 11 herbaceous species of Brassicaceae and Asteraceae from five different habitats in Tenerife with a mean annual precipitation from 252 to 527 mm, shows a 2-fold range of stem P 50 values that match the precipitation values of the sampling sites: the most vulnerable species (P 50 -2. 1 MPa) was collected from wetter environments and the most resistant species (P 50 -4. 9 MPa) was sampled from drier vegetation types (Figs  1  and 2 ). The explanatory power of mean annual precipitation towards stem P 50 supports the functional relevance of resistance to xylem embolism as an adaptive response to water deficit, as has been repeatedly demonstrated for woody trees  (Maherali et al.
2018 ). These findings are in accordance with our results for the two populations of S. orientale collected in contrasting environments (Table  1 ; Fig. 6 ): the more resistant population shows a higher proportion of lignified area in the stem, thicker intervessel wall, and thicker intervessel pit membranes. However, the T PM -lignification correlation disappears in our entire data set (including Asteraceae and Brassicaceae species), showing that increased lignification characters are not necessarily linked to thicker intervessel pit membranes. The mean precipitation explains both P 50 and anatomical variation in stems of herbaceous eudicots Mean annual precipitation explains both the variation in stem P 50 and the variation in stem anatomical characters across the herbaceous species studied.
, 2006; Zanne et al. , 2010; Pratt and Jacobsen, 2017). However, in our data set, P 50 is not correlated with D H , with T VW or with T W D V , meaning that the vessel diameter and thickness-to-span ratio of vessels do not impact embolism resistance in our herbaceous data set. In conclusion, this study investigated structure-function relationships in stems of seven herbaceous Brassicaceae occurring in different vegetation zones across the island of Tenerife and merged the data set produced with a similar data set for herbaceous Asteraceae growing on the same island. The 2-fold difference in embolism resistance found here shows that stems of herbaceous eudicots are able to deal with a range of negative pressures inside xylem conduits, although the P 50 range in woody trees remains considerably higher.
ACKNOWLEDGEMENTS We thank the  Cabildo de Tenerife  ( AFF 147/13  no. Sigma ,  2013-00748 ;  AFF 429/13  no. Sigma ,  2013-02030 ;  AFF 149/15  no. Sigma ,  2015-00925 ;  AFF 85/16  no. Sigma ,  2016-00838 ) and  Teide National Park  (no. 152587 , REUS 27257, 2013; no. 536556 , REUS 83804, 2013; Res. no. 222/2015 ) for the collection permits, and the  AEMET -Agencia Estatal de Meteorología ,  Spanish Government , for providing meteorological data. We also acknowledge the technical support of.
(d) Host clam acclimation response to prolonged high-temperature exposure A gene co-expression network was built using the normalized RNA-seq data from which lowexpression genes had been eliminated, and five modules correlated significantly (p<0. 05) with temperature, clade composition, and/or physiological data (including oxygen production, Symbiodinium spp. density, photosynthetic rate, and host dry weight; Figure  1 ). No module was correlated with sampling time, O 2 consumption, or shell extension. Two host modules positively (R=0. 82) and negatively (R=-0. 46) correlated with temperature, namely the pink host and the magenta host modules, respectively (Figure  1 ). The magenta host module also correlated positively with photosynthetic rate Fv/Fm (R=0. 63) while the pink host module correlated negatively with it (R=-0.
We tested for specific module conservation across datasets for the Symbiodinium spp. transcriptomic response in the small giant clams. Overall, few modules were conserved between datasets (Figure  2 ). We observed that the pink symbiont module was moderately conserved in freeliving Symbiodinium spp. (Zsummary=2. 9) but not in the coral datasets (Zsummary=-0. 5). Whereas the magenta symbiont tended to be conserved in corals (Zsummary=1. 9), it was not conserved in free-living individuals (Zsummary=1. 3). Interestingly, module lightgreen symbiont was not conserved across datasets despite being the Symbiodinium spp. module that was most strongly correlated with temperature in small giant clams (Figure  1 ). One module only, the darkmagenta symbiont , was, however, preserved across all datasets (Zsummary=4.
(f) Multivariate analysis and co-expression network for free-living datasets against the clade C1 reference genome We used db-RDA to document gene expression variation among free-living Symbiodinium spp. , with temperature and cladal breakdown as the explanatory variables. The model was highly significant (p<0. 001), and the adjusted R 2 was 0. 80 (Figure  3 ). Partial db-RDAs showed that the transcriptomic response was largely lineage-specific (adj. R 2 =0. 77; F=179. 88, p<0. 001). However, temperature also had a significant effect on total gene expression variation, independent of Symbiodinium genotype (adj. R 2 =0. 05; F=12. 42, p<0. 001). We conducted independent WGCNA analyses to assess acclimatory responses in free-living Symbiodinium spp. based on genome C1 specific  (41). We found the largest modules (blue (n= 8,739 genes) and turquoise (n = 10,061 genes) to be correlated with lineage (Supplementary figure  S3 ), independent of the temperature response; this is congruent with the db-RDA analysis (see Supplementary material for details.
However, how these changes would affect fine-scale interactions between the host and symbionts remains to be explored; hence further proteomic data that directly speak to changes in cell physiology should be acquired in future studies of giant clam-Symbiodinium symbioses. (c) Symbiodinium spp. response to prolonged elevated temperature exposure in hospite Overall, Symbiodinium spp. gene expression decreased with prolonged elevated temperature exposure, and some of the modules were correlated with the lower Symbiodinium photosynthetic yield and cell densities documented at elevated temperatures. Physiological studies have previously shown that high temperature led to diminished photosynthetic yield in several clades of Symbiodinium spp. (74). Herein we also found that genes encoding certain components of the photosynthetic machinery, especially photosystem II (PSII), were tune down in elevated temperature condition.
It is thus most likely that clams allowed to feed both autotrophically and heterotrophically might, then, have an even superior capacity for hightemperature acclimation. Although the effects of clade and/or experiment on Symbiodinium gene expression were much greater than the temperature effect, temperature significantly impacted gene expression even when controlling for clade genotypes. This suggests that acclimation to a long-term temperature increase has a conserved basis among different lineages despite large evolutionary distance between clades  (10, 77). Differences in gene expression between clades might also be associated with distinctive thermotolerance capacities. We found that few gene modules were preserved across datasets: in hospite with clams vs. free-living vs. in hospite with corals.
One methodological factor that may warrant a cautious interpretation of our results is the major experimental design differences between datasets; in the case of our own study, as well as that of Mayfield et al. (39) , sub-lethal temperatures were used, whereas in exposure time were more reduce in Levin et al. (37)  and Gierz et al. (36)  and it is most likely that individuals were still experiencing stress. However, the fact that we were still able to detect a module related to photosynthesis in all studies suggests that certain molecular pathways underlying the photosynthetic activity of Symbiodinium are temperature sensitive, regardless of whether the Symbiodinium are free-living or associated with corals or giant clams. Exposure to elevated temperature was associated with an up-regulation of phytohormones and methylation-related genes.
Indeed, an increase in ABA biosynthesis is associated with upregulation of ABA signaling genes in several plant species  (82). Herein we showed that the same gene module enriched for methylation regulation was also enriched for ABA signaling/metabolism, and this response was conserved in free-living Symbiodinium cells. Additionally, independent data from thermo-sensitive and thermo-tolerant phenotypes of freeliving Symbiodinium (clade C1) revealed that the only biological function associated with thermal tolerance was the regulation of methylation and response to acid chemical most likely related to ABA signaling. Considering the pivotal role of ABA in a variety of plant systems, we propose that ABA signaling might also be a key driver of acclimation to long-term elevated temperature exposure, and, more generally, thermal tolerance in Symbiodinium spp.
Conclusion The co-expression network analysis proved to be a powerful tool for dissecting compartmentspecific transcriptomic responses in symbiotic systems. This is especially true when looking for acclimatory signatures that, in contrast to short-term stress responses, are characterized by rather subtle changes over longer periods. Indeed, our data from a long-term high temperature study revealed that different cellular processes are impacted in the host clam and in hospite Symbiodinium compartments; genes encoding key photosynthesis proteins were particularly temperature sensitive in not only Symbiodinium in hospite, but also in culture. Future studies focusing on the range of optimal thermal conditions of the T. maxima species may improve our understanding on the thermal tolerance of the small giant clams and their symbionts.
(h) Transcriptomes assembly Raw reads provided by RNA-Seq were filtered for quality and length using Trimmomatic v. 0. 36  (85)  with minimum length, trailing, and leading quality parameters set to 60 bp, 20, and 20, respectively. Illumina's adaptors and residual cloning vectors were removed via the UNIVEC database (https://www. ncbi. nlm. nih. gov/tools/vecscreen/univec/). Paired-end filtered reads were assembled de novo using Trinity v2. 6. 6  (86)  with a default k-mer size of 25 bp and minimum transcript length of 200 bp. Raw transcripts (n=726,689; 420 Gbp) were filtered for presence of open reading frames (ORFs) (length≥300 bp), longest isoform matches, and mapping rate (≥0. 5 transcripts per million; TPM). Transcripts matching Refseq entries from archaea, plasmid, virus, and bacteria (BLASTn; e-value<10 -10 ), as well those transcripts that aligned significantly (e-value<10 -4 ) only to bacterial sequences on the NCBI nt database (max target seqs=5) were discarded in an effort to reduce putative contamination.
To segregate between symbiont and host sources, the meta-transcriptome was blasted (BLASTn; e-value<10 -4 ) against a pool of Symbiodinium spp. genomes and transcriptomes including clades A, C, and F  (40). By default, all hits with no match were considered as originating from the host. For quality checks, the de novo transcriptome's completeness was assessed with BUSCO's v2 metazoa and v2 eukaryotes databases for clam and Symbiodinium spp. , respectively  (87). Transcriptomes were annotated by BLAST search against the Uniprot-Swissprot database (BLASTx; e-value<10 -4 ). A schematic representation of the overall analysis pipeline has been provided in the Github repository (https://github. com/jleluyer/acclimabest).
(i) Co-expression network analysis for host and symbionts and functional enrichment of gene modules Signed co-expression networks were built for the host and symbiont datasets independently using the R package WGCNA following the protocol developed by Langfelder and Horvath (88) based on normalized log-transformed expressions values (log2 count per million; log2CPM). The datasets were previously filtered for residually expressed transcripts (>1 CPM in 4 individuals) and minimum overall variance (>10%). Normalization was conducted on library sizes for host and symbiont datasets separately. In an effort to normalize for Symbiodinium cells we also tested specific housekeeping genes validated from previous thermal stress experiments  (89). Since both approaches gave similar results (data not shown), only library size normalization has been presented herein.
The main goal of this analysis was to cluster genes in modules correlated with time, temperature, and relevant physiological responses (Figure  1 ). Briefly, we fixed a "soft" threshold power of 6 and 26 for the host and symbiont datasets, respectively, using the scale-free topology criterion to reach a model fit (|R|) of 0. 81 and 0. 90 for host and symbionts, respectively. The modules were defined using the "cutreeDynamic" function (minimum of 30 genes by module and default cutting-height=0. 99) based on the topological overlap matrix, and a module Eigengene distance threshold of 0. 25 was used to merge highly similar modules. For each module, we defined the module membership (kME=correlation between module Eigengene value and gene expression values). Only modules with p<0. 05 were conserved for downstream functional analysis (Figure  1 ).
Gene ontology (GO) enrichment analyses were conducted for each module separately using GOAtools (90) implemented with the "go_enrichment" pipeline (https://github. com/enormandeau/go_enrichment) and based on go-basic. obo data (downloaded on  May 30, 2018). GO terms were considered enriched at p<0. 05 (minimum of three genes). GO redundancy reduction was conducted using the "revigo" online tool  (91).
(j) Meta-analysis on free-living Symbiodinium and coral transcriptomes We integrated publicly available datasets featuring similar experimental designs (i. e. increased temperature over a long-term timescale) to further unravel the host, symbiont, and holobiont Symbiodinium (clade F) to a 31°C heat stress (control temperature=24. 5°C) over a 28-day period  (36) , while Levin et al. exposed clade C1 Symbiodinium (both thermo-tolerant and thermosensitive sub-types) to a 32°C heat stress (control temperature=27°C) over a 13-day period  (37). Finally, Mayfield et al. (39)  exposed corals housing Symbiodinium (clade C) to 30°C over a 9month period (control temperature=27°C), and both the coral hosts and in hospite Symbiodinium appeared to have acclimated to this temperature. Raw data processing and mapping to the newly assembled Symbiodinium transcriptome followed the same procedure as described above albeit adapted for single-end reads.
In parallel, analysis of free-living datasets was also conducted against the recently published and assembled Symbiodinium clade C1 reference genome for comparisons  (41). Mapping and downstream coexpression network analysis results are detailed in the Supplementary Material and Supplementary figure  S3. We assessed module preservation using the "modulePreservation" function (200 permutations) implemented in the WGCNA R package based on the Zsummary composite statistic, taking into account preservation of both connectivity and density in a module  (88). Modules were considered low to moderately conserved for Zsummary values between 2 and 5 and conserved for Zsummary values > 5 (Figure  2 ). In order to determine whether genotype (clade), time, and/or temperature had a significant effect on Symbiodinium spp.
gene expression variation in free-living individuals and to assess the proportion of variance explained by each factor, we used a redundant-discriminant analysis (RDA; Figure  3 ). Briefly, a principal components analysis (PCA) was first carried out with a Euclidean distance matrix of the log2-transformed expression levels of the 20,449 genes (log2CPM) using the Ape R package "daisy" and "pcoa" functions  (92). Because no axis could be selected according to the broken-stick distribution, we selected all axes explaining at least 2. 75% of the variation (4 axes explained 69. 5% of the total variance. ) according to a previously described method  (93, 94). A distance-based redundancy analysis (db-RDA) was then undertaken with the gene expression variation explained by these PCA factors (response matrix), with genotype, temperature, and time as explanatory variables.