dataesr/scientific-paragraphs-categorization huggingface dataset:
Changes in S. schenckii and S. brasiliensis gene families were inferred based on domain expansions or contractions assigned by Interpro, Pfam and SMART databases and statistically tested by hypergeometric comparisons (P < 0. 05 -Figure  5 , Additional file 3: Figure  S2 , Additional file 4: Figure  S3  and Additional file 5: Figure  S4 ) and the reported p-values were used for multiple testing using q-value. We have not observed the enrichment of peptidases genes in Sporothrix lineage, specifically the MEROPS families M35 or M36, which are expanded in dimorphic fungal pathogens as adaptation to mammalian hosts  [29, 41]. On the other hand, we observe a lack of polysaccharide lyase genes which are associated with decay of plants (CAZy PL family) when compared to other Sordariomycetes (Figure  6A , Additional file 2: Table  S5 ).
Small GTPases are an independent superfamily of GTP-binding proteins, sharing a common enzymatic activity and producing GDP by the hydrolysis of GTP, and play pivotal roles in cell division and signaling, vesicle fusion and protein synthesis  [54]. These proteins are also involved in filamentation, mating, growth at 37°C and virulence in C. neoformans  [55, 56]. Significant expansions in Ras, Rho and Rab Small GTPase superfamilies (IPR020849, IPR003578 and IPR003579) were observed in the Sporothrix lineage when compared to other Ascomycetes (Figure  5 , Additional file 2: Table  S4 ). Judging from the phylogenetic trees of small GTPases, the majority of branches harboring Sporothrix homologues suggests a higher diversity among the Ascomycetes we analyzed (Additional file 4: Figures S3, Additional file 5: Figure  S4 , Additional file 7: Figure  S5 ).
To date, such a high diversity of Small GTPase proteins as found in the Sporothrix lineage has not been reported from any other class of fungi. Another group that was expanded by INTERPRO and SMART domain counts in the Sporothrix lineage is the polyketide synthase (PKS), enoylreductase (IPR020843) family (Figure  5 , Additional file 2: Tables  S3, S4 ). Polyketides comprises diverse fungal secondary metabolites such as antibiotics, pigments, and mycotoxins that are formed from simple carbon precursor acids catalyzed by polyketide synthases (PKSs)  [57]. Filamentous fungi are producers of polyketide metabolites, several of which of pharmacological or agricultural interest  [58, 59]. Fungal PKSs are in general a linear succession of ketosynthetase (KS), acyltransferase (AT), dehydratase (DH), enoyl reductase (ER), ketoreductase (KR), acyl carrier protein (ACP), and thioesterase (TE) domains  [60].
We also identified expanded clades harboring Sporothrix and dimorphic fungi with high branch support values, suggesting a great diversity of this protein family. Another large expansion found in the Sporothrix lineage is a fungal trichothecene efflux pump (Pfam PF06609), an evidence of detoxification via mycotoxin pump  [62]. Apart from that, fungal genomes generally harbor a lower content of Leucine-rich repeat (LRR) proteins than other ophistokonts  [63]. Gene expansions of several LRR superfamilies were identified in the Sporothrix lineage (Additional file 2: Tables  S3, S4 ). LRR proteins expansions are commonly found in eukaryotic parasites such as Trypanosoma and Giardia  [64, 65]. These domains consist of 2-45 motifs of 20-30 amino acids in length providing a structural framework for protein-protein interactions.
Chitin synthesis in fungi is a rather complex process, regulated by multigene families encoding chitin synthase isoenzymes, whose activities may be spatially regulated to fulfill the multitude of roles ascribed to them  [83]. Based on differences in regions of high sequence conservation, chitin synthases have been attributed to seven classes  [83, 84] , whose functional implications are not yet clear in all cases. Despite the low chitin content reported for S. schenckii  [81] , genomic analysis showed the presence of seven CHS genes, in S. schenckii as well as in S. brasiliensis genomes. A cluster analysis of their putative products, including 36 fungal chitin synthases, revealed that each of the translation products of the seven CHS Sporothrix genes identified in genomic databases (CHS1 to CHS7), could be ascribed to each of the seven chitin synthase classes known (I to VII) (Additional file 12: Figure  S10 , Additional file 2: Table  S10 ).
Ab initio Gene prediction, annotation and protein family classification Gene predictions were performed using three different approaches: SNAP  [108] , AUGUSTUS  [109]  and EXON-ERATE  [110]  using ORF's identified in the G. clavigera strain kw1407/UAMH 11150  [26]  as reference and for training and genomic comparisons. Proteins deduced for G. clavigera proteome were aligned to the S. brasiliensis and S. schenckii assembled genomes using Exonerate (percent threshold equal 50) with the model protein2genome. Gene predictions (SNAP and AUGUSTUS) and protein (EXONERATE) alignments were used as input in order to identify consensus gene structures using EVi-denceModeler  [111]. Consensus ORF's were subjected to Blast searches against NCBI refseq_protein, KEGG and SwissProt databases. Automatic annotations were performed using SABIA -upgraded for eukaryotic organisms  [112]  and validated ORF's were considered with minimum query/subject coverage of 60% and minimum positive 50%.
Secreted proteins were identified using SignalP3. 0 (http://www. cbs. dtu. dk/services/SignalP/) using hidden Markov model. The prediction of mobile genetic entities was performed by similarity searches using the following approaches and databases: a) Nucleotide Blast against Repbase version 17. 10 (http://www. girinst. org/repbase/) [113] , Dfam database version 1. 1  [114]  and Gypsy database version 2. 0 (GyDB)  [115] ; b) PSI-BLAST (Position-Specific Iterated BLAST) using profiles of proteins corresponding to major clades/families of Transposable Elements (TEs) implemented with TransposonPSI tool (http://transposonpsi. sourceforge. net/); c) reverse position-specific BLAST algorithm (RPSBLAST) against Conserved Domain Database (CDD) version March 2013  [116] ; and d) tblastn taking specific protein subsets against the Sporothrix genome.
These subsets were built from NCBI Non Redundant (NR) database version March 2011 using particular description terms related to transposable elements including (apurinic/ apyrimidinic endonuclease, aspartic proteinase, ATPase, endonuclease, envelope, GAG protein, helicase, integrase, polymerase B, replication protein A, reverse transcriptase, RNase, transposase, tyrosine transposase/recombinase). In addition, the Tandem repeat finder (TRF) algorithm was used for finding tandem repeats  [117]. Transposable elements were classified accordingly  [118]. All results were obtained using locally compiled databases. Perl scripts were built for automation of genome scans, report generation and data integration. Artemis sequence visualization and annotation tool  [119]  was used for manual curation and annotation of transposable elements.
Whole genome gene families were identified using InterproScan combined with Pfam domain assignments. Annotation of carbohydrate-active enzymes was performed in a two-step procedure where the translated protein sequences were compared to the full length sequences derived from the Carbohydrate-Active enZymes (CAZy) database (www. cazy. org; [120] ) using BLAST  [121]. The query sequences that had an e-value <0. 1 were subjected to a BLAST search against sequence fragments corresponding to individual catalytic and carbohydrate-binding modules described in CAZy, along with a HMMer search  [122]  using hidden Markov models corresponding to each CAZy module family. A family assignment was considered reliable when the two methods gave the same result. Borderline cases were resolved by inspection of conserved features such as the presence of known catalytic residues.
Gene family expansion and contractions Gene families were determined using OrthoMCL approach comparing with other 13 fungi (Additional file 2: Table  S1 ). Domains were annotated for each orthologous cluster using Interpro  [123] , Pfam  [124]  and SMART  [125]  databases. Significant enrichment or depletion of domains in the Sporothrix lineage were calculated based on hypergeometric comparisons (P < 0. 05) and the reported p-values are adjusted for multiple testing using q-value  [126, 127]. The expanded families with highest discrepancies between Sporothrix and other compared fungi were individually analyzed. Protein sequences of LysM, PKS enoyl reductase, Ras, Rab and Rho small gtpases we individually aligned using ClustalW  [128]  and the domains were manually checked. Uninformative positions of the alignment were eliminated using trimal  [129]  and the best-fit protein substitution model was inferred based on likelihood values under AIC criteria, implemented in ProtTest  [130].
Blast reciprocal best hit and phylogenomic analysis Bidirectinoal-best Blast Hit (BBH) were performed using two different datasets: first we performed the comparisons between S. schenckii, S. brasiliensis and G. clavigera genomes in order to identify the unique genes in Sporothrix lineage. In addition, Blast reciprocal best hits were performed to identify common orthologues in 25 fungal genomes (Additional file 2: Table  S1 ) using minimum query/subject coverage of 50% and e-value of E ≤ 1×10 -20. A total of 395 orthologs were found in all species analyzed and were aligned using MAFFT  [133]  and retrieved alignments were trimmed using Trimal  [129]  in order to exclude spurious sequences or poorly aligned regions. Phylogenomic analysis was performed using RAxML  [134]  and the Dayhoff aminoacid substitution model was selected according ProtTest  [130].
Autophagy, peroxisome and endocytosis The initial tool used for this annotation was the KEGG automatic classification, which adequately identified genes involved in peroxisome biogenesis. However, the automatic annotation algorithms only picked up a few genes involved in autophagosome biogenesis and endocytosis, so different approaches were necessary. For the genes involved in autophagy, we started by collecting on the SGD all protein sequences annotated as involved in autophagy and autophagosome biogenesis in Saccharomyces cerevisiae. All of these sequences were blasted against the S. schenckii and S. brasiliensis databases in order to correctly identify homologous protein sequences. To narrow down the list, we focused the analysis on 17 genes that are necessary for autophagosome biogenesis in yeast  [141]  plus those that are shown on KEGG.
Regarding endocytosis, the KEGG table only showed two genes involved in the process itself and several genes involved in vacuolar degradation. To overcome this limitation, the genes that were used for annotation were those listed in a review article as being involved in clathrin-mediated endocytosis in S. cerevisiae  [142]. All protein sequences encoded by these genes were blasted against the S. schenckii and S. brasiliensis databases.
Acknowledgments We are grateful to  FAP-DF ,  CNPq and Capes  for the financial support and fellowships of the projects Pronex (grant number  193000569/2009 ) and  Genoprot  (grant number  559572/2009-3 ). HMMM is supported by  CONACyT, México  (grant number  CB2011-166860 ). BH is an  Honorary Professor of Glycomics at the Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.
This observation suggests that, as with the family 1 casposons, there could have been exchange of PolB genes between family 2 casposons and other types of MGE. Cas1 proteins of all family 2 casposons contain a conserved C-terminal fusion of an HTH domain which is not found in any other Cas1 proteins. Notably, a similar HTH domain is also found in the C-termini of PolBs of family 2 casposons. Although family 2 casposons vary considerably in size (6 to 16 kb) and gene content, most of them share a core of five genes which encode Cas1, PolB, an HNH endonuclease and two distinct HTH proteins (Figure  2 ). One of the conserved HTH proteins contains a C-terminal HEAT repeat domain (PF02985); HEAT repeats form rod-like helical structures that mediate various protein-protein interactions  [54]. The conserved HTH proteins and the HNH endonuclease might be involved in the target site recognition and subsequent casposon integration, in concert with Cas1.
Methods Casposon protein sequences were analyzed using PSI-BLAST  [66] , CD-Search  [67] , and HHpred  [68]. Inverted and direct repeats flanking the casposons were analyzed using Unipro UGENE  [69]. The palindromic repeats within the casposon TIR sequences were identified using Mfold  [70]. Insertion sequences were analyzed using ISfinfer  [71]. Multiple sequences alignments were built using Promals3D  [72]  and Muscle  [73]. The Polinton/Maverick PolB sequences were recovered from the Repbase Update database  [74]. For phylogenetic analysis, gapped columns (more than 30% of gaps) and columns with low information content were removed from the alignment  [75]. Phylogenetic analysis was carried out by using FastTree  [76] , with the Jones-Taylor-Thornton model of amino acid evolution and γ-CAT estimation of evolutionary rates across sites.
Acknowledgements MK was partly supported by the  European Molecular Biology Organization  ( ASTF 82-2014 ). EVK and KSM are supported by intramural funds of the  US Department of Health and Human Services  (to the  National Library of Medicine). PF is supported by the  European Union 's  Seventh Framework Program  (FP/2007-2013) / Project  EVOMOBIL -ERC Grant  Agreement no. 340440. DP is supported by the  Agence nationale de la recherche (ANR)  program  BLANC , project  EXAVIR.
Acknowledgements. The authors would like to express their gratitude for the access granted to the HPC resources of [CCRT/TGCC/CINES/IDRIS] under the allocation 2012-t2012012201 made by  GENCI  ( Grand Equipement National de Calcul Intensif ). We would also like to thank  Brigitte Koffi  for fruitful discussions about clouds and aerosol vertical profiles. This study has been supported by the  European Commission framework contracts EUCAARI  (no. 036833-2 ) and  ECLIPSE  (no. 282688 ). Edited by:  D. Shindell The publication of this article is financed by  CNRS-INSU.
Eclogite-facies metamorphism The absence of kyanite in the eclogite TINZ 3 does not allow an independent estimate of pressure and temperature. The garnetclinopyroxene geothermometer of  Ravna (2000)  has been used to estimate the equilibrium temperature of the omphacite-garnet pairs. Two assemblages were used for calculations: (i) composition of omphacitic inclusions into garnet and the core composition of the latter; (ii) omphacite from the matrix and adjacent garnet rim. Results obtained are similar for both assemblages: a temperature range of 580-660 • C with a mean at 630 • C (for a pressure fixed at 20 kbar, the temperature dependence on pressure being 2. 5 • C/kbar). The PT evolution of the eclogite was investigated using P-T phase diagram for a fixed composition corresponding to the bulk   Holland and Powell (1998, revised in 2003)  and the free Gibbs energy minimization procedure with the software Perple X  (Connolly, 2005; Connolly, 2009).
13 ). These compositions are slightly more radiogenic than the depleted MORB mantle (DMM) at 700 Ma which is at +7. 5 (calculated using the data from  Workman and Hart (2005)  considering a single stage linear evolution). Tidéridjaouine samples have more radiogenic composition, ε Nd down to -6 and ( 87 Sr/ 86 Sr) i up to 0. 7173 (Table  4 , Fig. 13 ). As there is no geochemical or isotopic data on the basement rocks from the Tassendjanet terrane, a quantitative estimation of crustal contamination in the mantle source (source contamination) of the igneous precursors or during magma emplacement (crustal assimilation) cannot be performed. Two qualitative mixing models were computed on the Sr-Nd plot (Fig. 13 ) using data from the Depleted MORB Mantle (DMM) and mean Upper Continental Crust (UCC).
Arc terrane? (now under sedimentary cover at the North of In Ouzzal) Fig. 17. Interpretative sketch summarizing the geodynamic evolution of the Tassendjanet-Tidéridjaouine terrane deduced from data collected on eclogite and garnet amphibolites. Caby et al. , 1977). The post-collisional northward movement of the In Ouzzal terrane, located east of the suture zone, is at least of 150 km (and possibly much more if we consider that it was adjacent to the Iforas granulitic unit, 300 km to the south, both having probably moved together towards the north before being separated). With this configuration, possible arc relics would have been transported also toward the North and no more in their original location. The Gora Akofou andesites (Fig. 1a ) lying upon the northern edge of the In Ouzzal terrane have continental arc affinities  (Chikhaoui et al.
This exhumation is related to a westward transport of HP units meaning that the subducting slab was dipping eastward. Syn-collisional exhumation was probably rapidly (within a few million years) followed by transpressive shearing along the suture zone linked to the northward movement of the In Ouzzal terrane. Sinistral strike-slip shearing in the Tassendjanet-Tidéridjaouine area probably began as soon as 620 Ma but geochronological data are still needed to constrain the timing of northward motion of the In Ouzzal terrane and the time laps between syn-collisional and post-collisional tectonics. ratio of 0. 17917 and a 207 Pb/ 206 Pb ratio of 0. 07488 equivalent to ages of 1062 Ma and 1065 Ma, respectively. The standard was measured four times each five unknowns in a sequence of 2 standards, 5 unknowns and 2 standards (see  Bosch et al.
Acknowledgments The fantastic 2005 fieldtrip in the Western Hoggar would not have been possible without the enthusiastic support of the  "Centre de Recherche en Astronomie, Astrophysique et Géophysique" (CRAAG ), USTHB fellows ( Safouane Djemai ,  Saïda Aït-Djafer ,  Amar Drareni  and  Zouhir Adjerid ),  Gaston Godard  ( Institut de Physique du Globe, Paris ) and the team of Tuareg drivers. Patricia Hermand  and  Christine Gilson  ( Royal Museum for Central Africa ) are thanked for their precious help on Sr-Nd isotopic analysis. We acknowledge the three anonymous reviewers for their insightful comments.
The non-sequential raytracing module of the commercial software Zemax (Radiant Zemax, Redmond, WA, USA) is used. An illustration of raytracing, involving only a few rays for clarity, is presented in Figure  2. The energy absorbed in the illuminated chamber is mostly located close to the waveguide exit and a part of the energy, of the order of several percent, is deposited in the non-illuminated chamber  [14].
2 µm (peak absorption cross section: 1. 42  10 -17 cm 2 /molecule from HITRAN database  [22] , concentration: 397 ppm). The rate equation is solved for three different values of the relaxation time constant spanning three orders of magnitude. At the intermediate value, 11 µs, corresponding to the relaxation time of carbon dioxide in nitrogen  [23] , around 40% of the heat source modulation is lost. For 100 µs, more than 90% of the modulation is lost. These results are consistent with the dependency obtained by analytical analysis  [24]. The modulation loss is accompanied by a phase shift, also visible on the figure. The model has been further adapted to non-harmonic wavelength modulation (Figure  4b ), by assuming a sinusoidal scan of the absorption peak of interest, modeled by a Lorentzian function, and no simultaneous amplitude modulation.
The intensity, peak frequency and width of the Lorentzian function are excerpted from the HITRAN database. The modulation loss is more pronounced as, for 11 µs relaxation time, only about 25% of the modulation is kept. The previous computations have been performed assuming a uniform illumination of the chamber. However, in the µ-PA case, due to beam divergence, the latter is highly variable throughout the illuminated chamber. Thus, it would be useful to get the more precise picture obtained with a local rate equation formulation. The local conservation equation can be derived from Equation (1) by replacing n(t) and I(t) by their space dependent counterparts n(r,t) and I(r,t). Let us first note that the two contributions corresponding to the diffusion of the excited molecules and their convection by the acoustic velocity field can be neglected.
Vegetation susceptible to burning Fire behavior and the amount of trace gases and aerosols emitted by a given fire strongly depend on the burned vegetation (type and density of fuel). For specific areas and specific fires, this information may be provided by forestry services. However, for large regions, it is necessary to rely on more systematic and self-consistent landuse databases and modeling of the carbon cycle and vegetation dynamics (e. g. ,  Sitch et al. , 2003; Krinner et al. , 2005; Li et al. , 2012). This section briefly describes the approach used in this work.
Vegetation type databases Several land cover databases are available. In this study, the main constraint was to use a high-resolution land cover map to attribute as precisely as possible the type of vegetation burned for Europe. For Europe, we have chosen to use the satellite-based CORINE (coordination of information on the environment) land cover database (CLC)  (EEA, 2007). It provides the land cover class at a resolution of 250 m. The 2006 database is used when available, the 2000 database otherwise (Greece for instance). The 44 original classes have been merged into 13 vegetation classes, listed in Table  1. Artificial and sparsely vegetated classes are also included but are not allowed to burn (assume false detection). For convenience, the CLC database has been regridded to a 1 km × 1 km grid.
The fraction of each vegetation type within each grid cell is then used for landuse attribution. Outside of the region covered by this database, we use the yearly percent vegetation cover from the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite instrument, and the MCD12Q1 collection 5 land cover type product (referred to as MODIS MCD12 in the following)  (Friedl et al. , 2010). The year 2006 is used here, but the code can run with a year-specific database. Among the provided vegetation types, we arbitrarily chose to use the IGPB (International Geosphere-Biosphere Program) land cover classification. The fraction of vegetation cover, represented on a 0. 1 • × 0. 1 • grid, is shown in Fig. 2  for both CLC and MODIS MCD12 databases. While the general patterns are consistent for all databases (dominance of forest, especially north of 50 • N, croplands and grasslands in the mid-latitudes and of shrublands in the Mediterranean area), there are significant differences in the relative fractions and distributions in some regions.
The sensitivity to using either one of these distributions in the calculation of the emissions is tested in Sect. 7. 2. Note that neither the MCD12 nor the USGS classification includes peat bogs. For these databases, wetlands are used as a proxy for peatlands in the calculation of the emissions. For a more precise analysis of the impact of peat burning in western Russia, the mires vegetation type (also classified in the wetlands) from the Eurasian mapping of  Bartalev et al. (2003)  was used. The MODIS vegetation continuous field (VCF) data at 500 m resolution (MOD44B L3 data set)  (Hansen et al. , 2003) , providing the fraction of pixels covered by vegetation, are also used for area burned processing.