dataesr/scientific-paragraphs-categorization huggingface dataset:
Of these predicted proteins, only MVLG_03089 was differentially expressed under the conditions examined and was up-regulated in MI-late relative to growth in vitro in rich medium. In addition, four predicted proteins with iron/manganese superoxide dismutase domains (PF02777 and PF00081), glutaredoxin (PF00462) or catalase (PF00199) domains were found (MVLG_00659, MVLG_06630, MVLG_06939, MVLG_04131). Finally, pathway analysis via MetaCyc predictions (http://fungicyc. broadinstitute. org/) suggests that M. lychnidis-dioicae contains components of the glutathione-mediated detoxification pathway: Glutathione transferase (EC 2. 5. 1. 18: MVLG_05985, MVLG_04790) and membrane alanyl aminopeptidase (EC 3. 4. 11. 2: MVLG_03673). However, there appears to be a missing component  (3. 4. 19. 9)  in this pathway to facilitate formation of an intermediate of a glutathione-toxin conjugate.
Secreted proteins (SP) and candidate effectors A total of 279 secreted proteins (SPs) were predicted in M. lychnidis-dioicae and their expression and conservation examined to identify candidates for interacting with the host (Table  5 , Additional file 22). Among the 71 SPs that were smaller than 250 amino acids (small secreted proteins, SSPs), 46 were species specific in our comparative set and further do not share sequence similarity (e-value <1e-3) with any protein in the NCBI protein database. SSPs indeed often appear species-specific, likely because they co-evolve rapidly in an arms race with their hosts  [43]. Notably, 48 of the SSPs were significantly upregulated during plant infection (MI-late compared to rich media), but were not differentially expressed when comparing expression on rich and nutrient limited agar (Table  5 ), suggesting that these SSPs may play a specific role during plant infection.
A small subset of Cysteine-rich proteins contains known protein domains. Two proteins (MVLG_02283 and MVLG_02288) contain the Cysteine-rich secretory protein family domain (PF00188). In addition, a total of 9 proteins contain the fungal-specific Cysteine rich CFEM domain (PF05730). All of these CFEM proteins were predicted to be secreted; four of these were significantly induced and three were repressed in MI-late relative to rich and nutrient limited agar. To identify genes that could provide a mechanism for linking flower development to fungal development, we compared expression of the predicted secreted proteins with the S. latifolia EST library produced from flowers  [73]. A total of 37 genes share sequence similarity with S. latifolia ESTs; ten secreted proteins matched plant ESTs with at least an e-value of e-19.
Two cysteine-rich secreted proteins (MVLG_02288 and MVLG_02283) matched a S. latifolia flower EST annotated as having similarity with the plant PR-1 class of pathogenesis related proteins (PRs); these are proteins defined as encoded by the host plant but induced only in pathological or related situations (possibly of nonpathogenic origin). To be included among the PRs, a protein must be induced upon infection but not necessarily in all pathological conditions  [75]. Another S. latifolia gene of interest, SLM2, is expressed in the stamens of smut infected flowers but not uninfected flowers  [22] ; four M. lychnidis-dioicae proteins showed blast similarity with e-value less than e-6. All of the hits were hypothetical proteins that contained the SRF-type transcription factor domain (PF00319), and three of the four were predicted to be targeted to the nucleus (MVLG_04297, MVLG_06278, and MVLG_07052).
Response to oxidative environments Laccase-like multi-copper oxidase proteins are capable of degrading phenolic compounds like polymeric lignin and humic substances  [76]  and may be involved in the interacton of fungal pathogens with their host plants. Four proteins in M. lychnidis-dioicae contain the three multicopper oxidase (MCO) domains (PF07731, PF07732, PF00394). Two MCO proteins were predicted to be secreted, and another MCO was predicted to have a GPIanchor to the membrane. The fourth MCO was a membrane-anchored protein (MVLG_03092), with the Nterminus of the polypeptide outside the cell. The glyoxal oxidase catalyses the oxidation of aldehydes to carboxylic acid and is an essential component of the extracellular lignin degradation pathway of the root rot fungus, Phanerochaete chrysosporium.
Of a total of seven M. lychnidis-dioicae proteins that contain the glyoxal oxidase N-terminal domain (PF07250), two are predicted to be secreted and four have a predicted GPIanchor. While two of these glyoxal oxidase genes are adjacent in the genome, they do not form a gene cluster with any MCO as observed at the lignin peroxidase gene cluster in P. chrysosporium.
Genes similar to plant hormone synthesis genes Since M. lychnidis-dioicae infection of female S. latifolia hosts can alter normal flower development so as to produce pseudomale flowers, we investigated whether the genome might contain genes for pathways that could be associated with such changes. The predicted M. lychnidisdioicae protein database was examined for components of biosynthesis pathways of eight plant hormones (Additional file 23), as well as for other signaling pathways that could have an impact on host gene expression or development. Based on sequence similarity to components for these pathways from plants and microbes, as well as additional confirmation of some complete pathways using MetaCyc predictions (http://fungicyc. broadinstitute. org/), we found evidence that M. lychnidis-dioicae encodes enzymes that could participate in hormone biosynthetic pathways, such as polyamine biosynthesis pathways, which produces compounds known to play developmental and stress-response roles in plant physiology  [77]  (see proposed model in Fig.
2; MVLG_00642); this gene is linked to two other genes associated with nitrate assimilation, a nitrite reductase (MVLG_00638) and a nitrate reductase (MVLG_00637). All three genes involved in nitrate assimilation were significantly up-regulated during infection. In evaluating the expression of the 279 proteins predicted to be secreted, 48 were induced in planta. Several cysteine-rich secreted proteins were induced during infection. A pair of linked cysteine rich small secreted proteins (MVLG_04106 and MVLG_04107) was induced during infection. Four other proteins (MVLG_00115, MVLG_00802, MVLG_00815, and MVLG_00859) with the Cys-rich CFEM domain-containing family (PF05730) were significantly induced in infection. These proteins are good candidates for being potential effectors, based on proteins with similar properties that have been shown to be effectors in other systems  [80].
Cell wall degrading enzymes may play a role in the infection, particularly during the stage where the fungus causes necrosis of host plant tissue. A total of nine glycoside hydrolases were up-regulated in MI-late; among GH families, GH28 polygalacturonase proteins are mostly highly enriched during infection (p < 0. 08). Polygalacturonase is required for the second part of the homogalacturonan pathway implicated in pollen dehiscence. MVLG proteins that contain a glyoxal oxidase domain (PF07250) were also significantly enriched (p < 0. 009) in genes induced during MI-late. Mated cells of M. lychnidis-dioicae respond to corn oil, in addition to the other lipids previously reported  [45]. This supports the hypothesis that lipid response may be important for the development of this species. Although we observed no alteration of phenotype for un-mated haploid cells treated with lipids, three predicted cytoplasmic proteins with a secretory lipase domain (MVLG_07229, 07284, and 07291) were highly induced in haploids grown on nutrient limited agar compared to rich media or MI-late infections.
Methods Microbotryum lychnidis-dioicae lineage(s) and Silene latifolia host(s) The focal lineage of M. lychnidis-dioicae for this work is the most studied in the context of disease ecology ("Lamole strain": GenBank I00-15Lamole. 1; [9, 11] ) and belongs to the recently-refined species designation M. lychnidis-dioicae, parasitizing Silene latifolia. From the original isolate, haploid sporidial strains were generated via micromanipulation of the meiotic products from a single tetrad, yielding the strains Lamole p1A1 and p1A2 that differ in electrophoretic karyotypes only in the mating-specific chromosome. For the work in this report, the haploid p1A1 strain (mating-type a1) was used as the source of the focal genome. Additionally, the focal genome contains size-heteromorphic sex chromosomes that share many features with sex chromosomes in plant and animal systems  [11].
For quality assessment before Illumina sequencing, 5 μg of DNase-treated RNA was reverse transcribed with SuperScript III First Strand Synthesis System for RT-PCR (Life Technologies, cat no: 18080-051). PCR was performed using TaKaRa Ex Taq Hot-Start DNA Polymerase (Takara, cat. no: RR001B) using 25 μl reaction volume. To check for DNA contamination and possible inhibitory substances in the RNA, three sets of housekeeping primers (Eurofins/MWG/Operon) were used. Amplification of a region of the S. latifolia partial wdr1x gene for a putative WD-repeat protein (GenBank IDs Y18519, Aj310656) was used to assess host cDNA and contaminating genomic DNA; the forward primer, 5′-CTCTG CTGGAGGTGGAACAT-3′ and reverse primer, 5′-AG CACTGAACACCCCAACTT-3′; this case a 253 bp fragment would be produced for cDNA, vs.
This was expected as these samples also contain the host Silene RNAs. To assemble transcripts for use in annotation, RNA-Seq reads were aligned to the assembly with Blat, and then assembled using Inchworm  [95]  in the genome-guided mode. To predict genes, we first generated a high confidence training set of 775 transcripts of at least 900 nt using Genemark  [96]  and the assembled RNA-Seq data. This was used to train Augustus  [97]  and Glimmerhmm  [98]. RNA-Seq data was processed by PASA  [99]  to generate longer transcripts, and ORFs of at least 600 nt were predicted. Available ESTs from Genbank and Microbase were also utilized. EVM  [99]  was then used to select a preliminary gene set from the ab initio gene calls (Augustus, Genemark, GlimmerHmm, and SNAP), Genewise  [100] , ESTs, PASA ORFs, and the training set, with the highest weight given to the RNA-Seq based PASA ORFs.
Differential expression analysis We used differential expression analysis scripts in the Trinity pipeline  [95, 101]  to process RNA-Seq data generated from the three conditions (nutrient limited, rich, and MI-late). Briefly, we first extracted protein coding gene sequences from the M. lychnidis-dioicae genome sequence based on coordinates of gene models, added 100 bases of flanking sequence on each side to approximate UTRs. Then the RNA-Seq reads from each of the three samples were aligned to the extracted coding sequences using bowtie  [102]. The alignment files were used to quantify transcript abundances by RSEM  [103]. Differential gene expression analysis was conducted using edgeR with TMM normalization  [104, 105]  using a corrected p-value  [106]  cutoff of 1e-3. In comparing all pairs of the three conditions, a total of 1,413 genes were differentially expressed across the comparisons (Additional file 24).
Search for signature of transition type (C to T) mutation bias We performed pairwise alignments between each copy and respective consensus to finally provide multiple alignments for each family (consensus) using in-house scripts. TE copies with less than 80 % of identity with consensus and smaller than 400 bp were filtered out. We also filtered out TE families with less than 5 sequences in the multiple alignments. RIPCAL  [112]  was run on each multiple alignment to count both potential single mutations (transitions and transversions) and di-nucleotide target used in all possible transitions. Results were analysed using in-house R scripts to select most reliable mutated copies (if transition rate > 2 * transversion rate). For 40 % of copies exhibiting a transition mutation bias (of 2298 total copies, 179 consensus families (Additional file 10)), we considered that dinucleotide targets (CA + TG 1 , CC + GG 1 , CG + CG 1 , CT + AG 1 ; 1 for reverse complement), were preferentially used if they represent a minimum of 30 % of the addition of the four possible.
Measurement of distance between genes and TEs We computed the distance from each gene to the closest TE (case 1), or from each TE to the closest gene (case 2) using getDistance. py from S-MART package  [113]. Only distances up to 10 kb were considered. For case 1, we also compared the subset of genes encoding predicted secreted proteins with the set of all other genes for different classes of distance intervals. For the case 2, we compared different TE categories in two classes of distance intervals (<1kbp and >1kbp). A chi 2 test of homogeneity (Pearson's chi-squared) was computed to test that the observed difference between the sets did not occur by chance (p-value < 0. 05). The graphics and statistical test were performed using in-house R-Scripts.
sourceforge. net/) to validate assemblies and identify scaffolds corresponding to the mating-type chromosome in the whole genome assembly. The regions corresponding to autosomal contamination were identified by uneven and low read coverage and were excluded from further analyses; mitochondrial DNA was also excluded (GenBank NC_020353). All whole-genome scaffolds with more than 20-fold depth of the enriched mating-type chromosome sequence were confidently assigned to the matingtype chromosomes (Additional file 11). It was not possible to anchor the scaffolds onto the available optical map of the a 1 mating-type chromosome  [12]  due to the small sizes of the contigs relative to spacing of the restriction enzyme cut sites in the map. Annotation for mapped supercontigs regions was parsed from the genome-level annotation.
TE content was assessed using de novo TE annotation as described above. TE content was compared between the nonrecombining part of the mating-type chromosome (Table  1 ), the PARs, and the autosomes. GC content was compared between the non-recombining region of the mating-type chromosome, the PARs and the autosomes. Significance of the mean difference was assessed using a t-test and a nonparametric Wilcoxon test. In a second step, the GC content at the 3rd codon positions was inspected separately in identified coding regions. Mean GC contents at the 3rd codon positions were compared between the CDS on the non-recombining part of the mating-type chromosome, the PARs and the autosomal coding regions. All GC content analyses were conducted using in-house python and R scripts.
Prediction of the secretome To predict a high confidence set of secreted proteins, results from several different software tools were integrated. These include TargetP1. 1  [114] , SignalP3. 0, [115] , SignalP4. 0 (http://www. cbs. dtu. dk/services/SignalP/) [116] , TMHMM2. 0  [117] , PredGPI  [118] , Phobius  [119] , NucPred  [120] , Prosite  [121] , and WoLF PSORT  [122]. A subset of these tools were used to first exclude proteins as not secreted if they had transmembrane domains (two or more, from TMHMM or Phobius), an ER retention signal (0. 00014 from Prosite), GPI anchor (specificity of >99. 5 % using the general model of PredGPI), or nuclear localization (>0. 8 threshold in NucPred). Secreted proteins were then predicted based on passing four of the six thresholds examined (TargetP secreted localization, SignalP3.
0 NN Dscore > 0. 43, SignalP3. 0 HMM Sprob > 0. 8, SignalP4. 0 D-score > 0. 45, WoLFPsort 'Extr' listed as major neighbor, or Phobius secreted localization). Additional criteria were used for ambiguous predictions. If both TMHMM and Phobius agreed on the existence of 1-2 transmembrane (TM) domains in the protein, the protein was excluded from the probable secretome pool. If a protein was predicted to have a lowly probable GPI linkage (PredGPI specificity >99. 0 % and <99. 5 %) and a TM predicted by TMHMM and/or Phobius around the same region, this served as corroborating evidence for GPI anchorage to the membrane. Where evidence conflicted or was insufficient for determining secretome status, BLASTp and Pfam domains were used to establish probable orthologs, followed by referencing the UniProtKB  [123, 124]  and FunSecKB  [125]  database for confirmation of localization of the orthologs, where available.
Out of 7,360 predicted proteins, 6,899 proteins were excluded from the pool of the secretome based on the criteria described above. Of the remainder, 189 proteins had no contradictory calls in the positive prediction for SP. Another 272 went through further confirmation, of which 182 of these were confirmed to be non-SP and 63 were SP. Of the rest, 27 of them could not be finalized due to lack of ortholog matches in the NCBI database and lack of conserved domain for reference.
placenta, missing 410 and 393 of these highly conserved clusters, respectively. domains within each gene were identified using Hmmer3  [127] , and gene ontology terms were assigned using BLAS-T2GO  [128]. To examine gene duplication history, the phylome, or complete collection of phylogenetic trees for each gene in a genome, was reconstructed for Microbotryum lychnidisdioicae and 19 other fungi, including those used for OrthoMCL (Additional file 13) and Serpula lacrymans. Phylomes were reconstructed using the previously described pipeline  [129]. All trees and alignments have been deposited in PhylomeDB  [129]  and can be browsed online (www. phylomedb. org, phylome code 180). Trees were scanned to detect and date duplication events  [130]. RNAi components from other other fungi were used as Blast queries to find homologs in M.
lychnidis-dioicae; the queries used include U. hordei RdRp (CCF48827. 1), C. neoformans Ago1 (XP_003194007), and N. crassa Dcl2 (Q75CC1. 3) and Dcl1 (Q758J7. 1). The putative function was confirmed by examining protein domains. The identified domains for each protein include: Piwi, PAZ and DUF1785 found in both copies of Argonaute (MVLG_06823, MVLG_06899); DEAD/DEAH helicase, double-stranded RNA binding, and RNAseIII (MVLG_01202). Sugar transporters were identified based on homology to the Ustillago maydis Srt1t transporter (Genbank: XP_758521) and the Uromyces viciae-fabae Hxt1 (Genbank: CAC41332). The M. lychnidis-dioicae protein models corresponding to carbohydrate-active enzymes were assigned to families of glycoside hydrolases (GH), polysaccharide lyases (PL), carbohydrate esterases (CE), carbohydratebinding modules (CBM), auxiliary activities (AA) and glycosyltransferases (GT) listed by the CAZy database  [64] , exactly as previously done for the analyses of dozens of fungal genomes  [39, 66, 131, 132].
Acknowledgements We acknowledge the  Broad Institute Sequencing Platform  for generating all DNA and RNA sequence described here, and  Sinéad Chapman  for coordinating the sequencing. We thank  Mark Lawrence  for sharing the Rhodotorula glutinis ATCC 204091 genome and annotation methods prior to publication. This project was supported by  NSF  award # 0947963  to MHP, DJS, and  CAC , the  ANR-09-BLAN-064  and  ERC GenomeFun 309403  grants to TG, and  BIO2012-37161  and  NPRP 5-298-3-086  to TGE. We would also like to thank  Vincent Lombard ,  Elodie Drula  and  Anthony Levasseur  for their help with the day-to-day development of the CAZy database.
Rainfall Data The gridded rainfall dataset from Climate Research Unit (CRU) version TS3. 10. 1, which presents a larger time cover with a wide spatial representation over West Africa, has been used for the study. This data is composed of 1224 observational grid-points for the 1901-2009 periods with 0. 5 × 0. 5 degree resolution. The precipitation data have been compiled by the CRU over the last 20 years  [21]   [22]. The original data have been subjected to comprehensive quality control over the years. Updates for more recent years and additional station data collated by the CRU have also been checked for homogeneity and outliers. The correction of individual records requires detailed local meteorological and station meteorological information, which are not readily available  [23].
The AVHRR instruments on NOAA-6 and NOAA-7 were the first in the TIROS-N series of satellites to have non-overlapping channel 1 and channel 2 spectral bands. Overlapping red and near infrared spectral bands precludes calculating a NDVI. The NDVI is calculated as NDVI5 (channel 2 -channel 1)/(channel 2 + channel 1)  (Tucker, 2005). The NDVI has become the most used product derived from NOAA AVHRR data  [28] , largely from the use of NDVI datasets formed via maximum value compositing  [31]. The latest version, termed the third generation NDVI data set (GIMMS NDVI3g) has been recently produced for the period July 1981 to December 2011 with AVHRR sensor data from NOAA 7 to 18 satellites  [24].
Our measurements sound a broad region of the upper mesosphere and lower thermosphere of Venus ranging from 10 -2 -10 -5 mb (which in the Venus International Reference Atmosphere, VIRA, is approximately 100-150 km during the daytime) and show a maximum around 195 ± 10 K in the subsolar region, decreasing with latitude and local time towards the terminator. This is in qualitative agreement with predictions by a Venus Thermospheric General Circulation Model (VTGCM) after a proper averaging of altitudes for meaningful comparisons, although our temperatures are colder than the model by about 25 K throughout. We estimate a thermal gradient of about 35 K between the subsolar and antisolar points when comparing our data with nightside temperatures measured at similar altitudes by SPICAV, another instrument on Venus Express (VEx).
Measurements and NLTE modelling The instrument VIRTIS on board VEx  (Drossart et al. 2007; Gilli et al. 2015 ) is a dual instrument consisting of two channels named VIRTIS-H and VIRTIS-M. The first one is an infrared echelle spectrometer with a spectral ranging 1. 8-5. 0 µm and a moderate spectral resolution (R ∼ 1200), and the second is a mapping spectrometer working in the visible (0. 27-1. 1 µm) and in the infrared (1. 0-5. 2 µm) with lower spectral resolution (R ∼ 200), but a much wider field of view. Despite the clear advantages of using the spectral cubes from VIRTIS-M to infer the horizontal distribution of temperatures, we discarded VIRTIS-M data due to problems of calibration in the spectral range of interest. We used the complete database of nadir spectra taken by VIRTIS-H during the whole VEx mission of about five years of observations, implying a total of 200, 036 spectra after restricting the solar zenith angle (SZA) and emission angle (EA) to values lower than 80 • (due to noise).
This data set is much larger than the VIRTIS-H set of limb observations. As a result of VEx eccentric orbits, the projected spatial resolution of VIRTIS-H observations can change dramatically within the same orbit, varying from a few hundreds of meters to dozens of kilometers, as the satellite moves from periapsis to the apoapsis, respectively  (Gilli et al. 2015). Hence, caution must be taken for limb observations. However, in nadir viewing this is not that critical; we show later that the dimension of the spatial averages used in this work are larger than the field of view of the observations with worse spatial resolution. The VIRTIS-H spectra are subdivided in eight spectral orders, with 432 elements in each one, covering infrared wavelengths from 1. 88 to 5. 03 µm  (Drossart et al. 2007 ).