dataesr/scientific-paragraphs-categorization huggingface dataset:
Long fragment paired-end reads simulation We used the in-house SimSeqG software to simulate long fragment paired-end reads from the tampered reference sequence and the TAIR10 reference sequence. The SimSeqG simulator aims to reproduce the position-dependent sequencing error rate, shortfragment paired-end contamination and chimeric read rate found in a particular long-fragment paired-end sequencing. As such, a first phase will draw a sample from a BAM file and compute several descriptive statistics, this will allow to calculate two of the three error rates and apply it to the second phase, which is the simulation in itself. The first phase proceeds as follows: For each base position, the software will calculate the empirical probabilities of observing all possible quality values. This results in the computing of as many histograms as there are bases in a read, the number of classes in each histogram being equal to the number of possible base qualities according to the standard used (phred-33 or phred-64) The software will compute the insert size distribution of all unambiguously mapped pairs, which usually yields a bimodal distribution corresponding to a mixture of 1) the short fragment contamination and 2) the long-fragment library of interest.
Acknowledgments This work was supported by the  French National Agency for Research  ( ANR-09-BLAN-0237 EPIMOBILE  to V. C. and P. W. ; Investissements d? Avenir  ANR-10-LABX-54   MEMO LIFE  and  ANR-11-IDEX-0001-02 PSL* Research University  to V. C); the  European Union  ( EpiGeneSys FP7 Network of Excellence number   257082  to V. C). M. E. was supported by a Ph. D. studentship from the Minist?re de l? Enseignement Sup? rieur and together with L. Q. by a postdoctoral fellowship from  MEMOLIFE. T. H. was supported by a postdoctoral fellowship form EpiGeneSys.
Availability of supporting data The data sets supporting the results of this article are available in the European Nucleotide Archive (ENA) repository under accession: ERS389787 (epiRIL 60), ERS38 9793 (epiRIL 55), ERS392388 (epiRIL 454), ERS392386 (epiRIL MEJ07) and ERS392380 (epiRIL 439).
Acknowledgments Medical writing and editorial assistance in the preparation of this manuscript was provided by apothecom scopemedical ltd, Sevenoaks, UK, and was supported by  Janssen. The authors have not received payment from  Janssen  for their involvement in preparing this article. The authors would like to acknowledge the contribution made by the attendees of the expert meetings and large educational meeting that helped to shape the content of this publication. The authors would also like to acknowledge the significant contributions  Professor René S Kahn ,  Professor Tom Burns ,  Professor Bill Deakin , and  Professor Gavin Reynolds  made to the discussions and development of the framework presented here.
© 2014 Haar et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons. org/licenses/by/4. 0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons. org/publicdomain/zero/1. 0/) applies to the data made available in this article, unless otherwise stated.
The oven program was 80uC for 1 min and 5uC/min to 240uC using a SupelcoWax-10 column (30 m60. 25 mm i. d. 60. 25 mm film; Supelco, USA). Tentative identification of volatiles was based on the comparison of retention indices and mass spectra with data from the literature and a spectral library (NIST-02). All tentative identifications were confirmed by coinjections with authentic standards. Samples of volatiles of T. infestans and P. megistus were first obtained three hours after the collection of feces (i. e. , from fresh feces) and afterwards, every 24 hours during the subsequent five days (dry feces). The samples of T. brasiliensis were obtained during days 0 (fresh feces), 1, 3 and 5 (dry feces). In all cases, samples of feces were collected from bugs that had been fed one week earlier.
96% and no plasmid. A total of 7158 genomic objects were identified: 7,054 proteincoding, 10 rRNAs, 77 tRNAs, and 12 miscRNAs genes. The average gene length was 964 bp with an average intergenic distance of 126 bp. After manual validation of the automatic annotation, 61. 5% (4338 CDSs) of the genes were assigned a biological function while 38. 5% were registered as open reading frames (ORFs) with an unknown function. Based on the G+C skew analysis and position of dnaA, the probable origin of replication (oriC), was mapped close to the ribosomal protein rpmH. A circular representation of the M. lupini chromosome is provided in Figure  2  indicating some of the features described above. The genomic characteristics of strain Lupac 08 and three additional Micromonospora genomes deposited in the public databases including Micromonospora sp.
Diversity of Micromonosporae: core vs. flexible gene pool Using the Micromonospora genomes of strains M. lupini Lupac 08, M. aurantiaca ATCC 27029 T and that of Micromonospora sp. L5 available in the NCBI  [19] , the core genome was calculated using the SiLix software  [26]. The core genome was composed of 2294 CDSs, which correspond to approximately 32% of the predicted proteome. In addition, M. lupini Lupac 08 contained the highest number of strain specific CDSs, 4702 (66. 6%), which is a very high value when compared to Micromonospora sp. L5 and M. aurantiaca ATCC 27029 T (13-14%, Figure  4 ), which both share a high gene similarity (85-86%). Horizontal gene transfer is universally recognized as an efficient mechanism for microorganisms to acquire functions that enable them to adapt to environments with different selective pressures.
Two main groups were obtained, the proteobacteria and actinobacteria. Within the actinobacteria, three clusters were clearly identified: the first one contained strains that belonged to the family Micromonosporaceae, the second cluster corresponded to various streptomycetes and the third cluster included the three Frankia genomes. Surprisingly, Micromonospora lupini Lupac 08 showed a closer metabolic relationship with the three Frankia strains (ACN14a, CcI3 and EAN1pec) than with the other two Micromonospora genomes. Plant/Soil-associated life style Transport systems. Organisms living in endophytic associations need to share resources with their host. Membrane transport systems play essential roles in cellular metabolism and activities. Current data suggest a correlation of transporter profiles to both evolutionary history and the overall physiology and lifestyles of organisms  [27].
Genome sequencing, annotation and analysis The genome sequence of M. lupini Lupac 08 was determined using the 454 FLX system and Titanium platform (454 Life Sciences) as previously reported  [96]. Sequences were assembled into 50 contigs and four scaffolds ranging from 583 to 7,083,659 nucelotides using the MaGe (Magnifying Genomes) interface  [97]. This Whole Genome Shotgun project has been deposited at European Nucleotide Archive under accession number NZ_CAIE00000000. 01.
Comparative genome analysis Genome rearrangement of the Micromonospora strains M. lupini Lupac 08, Micromonospora sp. L5, M. aurantiaca ATCC 27029 T and Micromonospora sp. ATCC 39149 were carried out using MAUVE software  [102]. The number of shared and unique genes present in the respective genomes were calculated and represented by a Venn-diagram using the EDGAR software  [103]. Potential horizontally transferred genes were predicted using the ''Region of Genomic Plasticity Finder'' method implemented on the MicroScope platform. First we selected genomes included in the PkGDB and NCBI RefSeq databases that presented high synteny percentages with the Lupac 08 strain. Automatic results were manually curated according to several features such as base composition, DNA repetitions, presence of near mobile elements and information provided by SIGI and IVON programs  [104].
Percentage areas of gonadic tubules, connective tissue and digestive gland were then determined on each histological section. Slides were scanned with a digital scanner (hp scanjet 7400 c) and the images saved in *. TIFF format. Tissue areas were then measured using image analysis software (Imaq Vision Builder, National Instruments Corp. ). Gonad area percentage was estimated as pixel number, from gonad / pixel number on total sections, as described in  [18]. 35 individuals corresponding to five gonad samples of each reproductive stage and sex were chosen for RNA-sequencing.
Animal sampling for microarray analysis Twenty clams from two wild populations -Ria Formosa (South of Portugal) and Ria de Aveiro (Northern of Portugal) -were sampled monthly between July 2011 and July 2012. At each sampling date the gonads of the collected clams were immediately dissected for RNA extraction and a transversal section of the gonadal area fixed for histological analysis, as described above. Gene expression analysis was done on 64 individual gonads representative of all the reproductive stages and sexes from both populations, chosen on the basis of histological data (Figure  1 ; Figure  2 ; Table  1 ).
cDNA libraries were constructed, amplified and sequenced at BGI Tech (Shenzhen, China). All the Illumina reads were analyzed with FastaQC software in order to assess the sequence quality. Illumina reads have been deposited in GenBank (SRA) with the accession numbers SRR974930, SRR974931, SRR974932, SRR97493, SRR974934, SRR974935, SRR974936.
decussatus (Pauletto et al, Novoa et al. unpublished data). All these data were merged also with publicly available Sanger sequences and nearly 500,000 reads obtained with 454 sequencing of larvae, gonads and several adult tissues (MGE011 and cDN18; SRA058431;  [13] ). A summary of the origin of R. decussatus sequences and assembly information are shown in Table  S1. Assembly was performed separately for each library by using MIRA3 or CLC Genomic Workbench for 454 and Illumina reads, respectively. A total of 990,111 contigs were then merged to reduce the redundancy by using CAP3, resulting in a total of 503,705 contigs (unpublished data). 454 and Illumina reads have been assembled by CLC Genomic Workbench, MIRA 3 and CAP3 with default parameters. A preliminary annotation was obtained for 141,001 contigs through Blast similarity searches conducted against several protein databases (e-value 1 E-5, see Table  S2 ).
Microarray design All databases used for the annotation step (see Table  S2 ) were considered to reduce the redundancy in annotated contigs. A total of 44,333 contigs found non-redundant (with a unique annotation) in at least one reference database have been considered for microarray design. Putative sense-strand orientation was inferred from the matching protein-coding gene in reference data bases. For 915 contigs that showed ambiguous orientation two probes with opposite orientations (sense and antisense) were designed. For the remaining 43,418 contigs with putatively unambigous orientation a single (sense) probe was designed. Since the microarray format could accommodate approximately 60,000 probes, non-annotated contigs that showed the highest expression in gonads based on RNA-seq data (see below) were included in the microarray design.
In total 7,376 non-annotated contigs were added, and for each of them, two probes with opposite orientation (sense and antisense) were designed. Probe design was carried out using the Agilent eArray interface (https:// earray. chem. agilent. com/earray/), which applies proprietary prediction algorithms to design 60-mer probes. A total of 59,951 out of 60,000 probes were successfully obtained, representing 51,709 different R. decussatus contigs. The sequences of the 51,709 contigs representing in R. decussatus DNA microarray platform have been provided in Table  S3. The percentage of annotated transcripts represented on the microarray was 85. 7%. In Table  S4  has been reported the annotation of each probe represented in DNA microarray platform. Probe sequences and other details on the microarray platform can be found in the GEO database (http:// www.
Data acquisition, correction and normalization Hybridized slides were scanned at 2 mm resolution using an Agilent G2565BA DNA microarray scanner. Default settings were modified to scan the same slide twice at two different sensitivity levels (XDR Hi 100% and XDR Lo 10%). The two linked images generated were analyzed together and data was extracted and background subtracted using the standard procedures contained in the Agilent Feature Extraction (FE) Software version 10. 7. 3. 1. The software returns a series of spot quality measures in order to evaluate the quality and the reliability of spot intensity estimates. All control features (positive, negative, etc. ), except for Spike-in (Spike-in Viral RNAs), were excluded from subsequent analyses. Raw gene expression data of all 64 analyzed individual gonads (Table  1 ) were deposited in the GEO database under accession number GSE51150.
Data analysis Differences in percentage gonad area were analysed using oneway analysis of variance after angular transformation. Comparisons of sex and gametogenic stage distributions between lines were made using Chi-square tests. A principal component analysis (PCA) using the TMeV 4. 5. 1 (TIGR MULTIEXPERIMENT VIEWER)  [19]  was applied to assess the distribution of the studied groups. Statistical tests implemented in the program Significance Analysis of Microarray (SAM) were used to identify differentially expressed probes between the two clam populations. The same approach was used   to identify differentially expressed probes in both populations between males and females. A SAM quantitative correlation analysis was also performed to identify genes with a correlation between mRNA levels and gonad area, after angular transformation.
A Pavlidis template matching (PTM) analysis was implemented using the TMeV 4. 5. 1 in order to verify whether the expression of specific genes increased during gonad development. A one-way ANOVA parametric test was used to identify the probes whose expression changed during gonad development in the two populations, using a p-value cut-off of 0. 01 and an adjusted Benjamini & Hochberg correction using R software v2. 15. 2. Hierarchical clustering was performed using TMeV on statistically significant transcripts, to group experimental samples together based on similarity of the overall experimental expression profiling. A more systematic and functional interpretation for significant gene lists was obtained using an enrichment analysis with the Database for Annotation, Visualisation, and Integrated Discovery (DAVID) software (Huang et al.
, 2009). ''KEGG Pathway'', ''Biological process'' (BP), ''Molecular function'' (MF) and ''Cellular component'' (CC) analyses were carried out by setting the gene count equal to 2 and the ease equal to 0. 1. Because the DAVID database contains functional annotation data for a limited number of species, it was necessary to link R. decussatus transcripts with sequence identifiers that could be recognized in DAVID. This process was accomplished using dedicated Blast searches performed with Blastx against zebrafish Ensembl proteins. Finally, Danio rerio Ensembl Gene IDs were obtained from the corresponding Ensembl protein entries using the BIOMART data mining tool (http://www. ensembl. org/biomart/martview/). D. rerio IDs corresponding to differentially transcribed clam genes as well as all of the transcripts that were presented on the array were then used to define a ''gene list'' and a ''background'' in DAVID, respectively.
Prevalent Gene Expression Patterns A Principal Component Analysis (PCA) was applied to the entire gene expression database (59,951 probes) for the 64 clams (Figure  3 ). We observed a clear clustering of the different sexes and gametogenic stages determined by histological methods. Along the first axis, PC1, which explained 35% of the variation, male and female individuals were discriminated. Gonad developmental stages were organized along the second axis, PC2 (15%). A significant divergence in expression patterns between male and female gonads was observed in stages III and IV (PC2). At these later stages, males and females predictably possess the most distinctive expression profiles, while at stages I and II this separation is not as clear along the second axis.
5 to 255, while a total of 9,751 differentially expressed probes were upregulated in the females gonads with a FC ranging from 1. 5 to 374. A putative annotation with zebrafish Ensembl Gene IDs was obtained for 6,506 probes that were differentially expressed between the two sexes. These annotated transcripts were used to define a gene list for functional annotation with DAVID. Enrichment analysis showed 9 KEGG, 95 BP terms, 22 CC terms, and 45 MF terms to be significantly over-represented (Table  S6 ). ''Cell cycle'' (dre04110), ''oocyte meiosis'' (04114) and ''Progesterone-mediated oocyte maturation'' (dre04914) were the most represented in the enriched KEGG pathway terms, with 49, 45 and 38 genes respectively. Cyclin B1 (CCNB1) and cyclin B2 (CCNB2); Cyclin-Dependent Kinase 2 (CDK2); Mitotic arrest deficient-like 1 (Mad2l1) and several genes of the Calmodulin family (CaM) were found among the differentially expressed genes.
Identification of Stage-specific Expressed Genes In order to identify those transcripts whose expression changed during gonad development in the two populations, a one-way ANOVA (p,0. 01, adjusted Benjamini & Hochberg correction) was performed. This analysis identified 13,218 probes that exhibited a significant change in expression over the reproductive cycle of male and female gonads (Table  S7 ). A putative annotation with Danio rerio Ensembl Gene IDs was obtained for 6,451 probes that were differentially expressed between gametogenic stages. Enrichment analysis showed 9 KEGG, 20 BP terms, 12 CC terms, and 40 MF terms to be significantly over-represented (Table  S8 ). ''Focal adhesion'' (dre04510) and ''Regulation of actin cytoskeleton'' (dre04810) were the most represented within enriched KEGG pathway terms, with 74 and 62 genes respectively.
Identification of genes with a correlation between mRNA levels and gonad area Quantitative correlations between microarray data and values of gonad area of stages II, III and IV from males and females, separately, after angular transformation, were evaluated via a SAM quantitative correlation analysis (FDR = 5%). Females showed a total of 10,415 probes significantly (direct or inverse) correlated with the gonad areas (Table  S9 ). Of these probes, 7,226 were annotated by similarity and associated with a known protein. We noticed the presence of positively correlated genes coding for Forkhead box protein L2 (Foxl2), VTG, condensing 2, Mitotic apparatus protein p62 and Cep57. In relation to male gonads, a total of 18,730 probes showed a significant (direct or inverse) correlation with gonad area (Table  S10 ).
Comparison between populations using two-unpaired class Significance Analysis of Microarray (SAM) In order to compare gene expression between the two sampled populations of R. decussatus, considering all stages and sexes, a twounpaired class Significance Analysis of Microarray (SAM) test was carried out on normalized data, enforcing a False Discovery Rate (FDR) of 5% and a Fold Change threshold of 1. 5. A list of 2,900 significant probes, corresponding to 2,228 unique transcripts, was obtained. A putative annotation with Danio rerio Ensembl Gene IDs was obtained for 1,777 probes out of the 2,228 differentially expressed transcripts between the two populations (Table  S11 ). Enrichment analysis revealed a total of 2 KEGG pathways, 23 BP terms, 15 CC terms, and 25 MF terms significantly over-represented among the differentially expressed probes (Table  S12 ).
Other important differentially expressed genes were also identified, such as the cdc16, cdc20, cdc27. Genes like CCNB1, cyclin E2 (CCNE2), and cdk2 were also present in both pathways. Another comparison that revealed an important number of differentially expressed probes, at the population level, was between stage II males. A list of 5,801 significant probes, corresponding to 3,588 unique transcripts was obtained (Table  S15 ). A putative annotation with Danio rerio Ensembl Gene IDs was obtained for 3,181 probes. An enrichment functional annotation analyses has been performed by DAVID, revealing 14 KEGG pathways, 56 BP terms, 23 CC terms, and 50 MF terms significantly over-represented (Table  S16 ). ''Insulin signaling pathway'' (dre04910) was the most represented in the enriched KEGG pathway terms.
Expression of DNA damage and cell organization-related genes is already altered in juvenile SCRbKO testes. We performed a gene microarray analysis between control and SC-RbKO testis at PND10 (GEO accession no. GSE22234). At this age, the confounding effect caused by difference in tissue composition was avoided, and the number of SC was identical in both groups (Supplementary Figure  S4A ). Out of a total of 114 genes with significant differences in expression; there were 32 downregulated and 82 upregulated genes in SC-RbKO testes. We analysed the complete gene list with QIAGEN's Ingenuity Pathway Analysis (IPA, QIAGEN, Redwood City, CA, USA; www. qiagen. com/ingenuity). The most relevant molecular and cellular functions were: cellular assembly and organization, cellular growth and proliferation, cell death, and cell cycle (Supplementary Figure  S4C ).
Sections were incubated with the TUNEL reaction mixture for 60 min at 37 1C, and reaction was stopped using 300 mM NaCl and 30 mM NaCitrate. Unspecific binding of the primary antibody was blocked with 3% BSA in TBS and primary antibody WT-1 (180, Santa Cruz Biotechnologies, Santa Cruz, CA, USA) diluted in block incubated overnight at 4 1C. Next a sequential incubation of AvidinTexasRed (Vector Laboratories) and AlexaFluor488 anti-rabbit antibody was performed. DAPI was used as a nucleic counterstain. Positive control was prepared by adding 1 U/ml DNAse for 30 min at 37 1C and from negative control terminal deoxynucleotidyl transferase (TdT) was omitted. The number of apoptotic cells per section was determined by counting intratubular TUNEL-positive cells across entire cross-sections selected at random within 6-and 12-week-old animals, and data are presented as the number of cells per square millimetre.
RNA samples were then treated with DNase (DNase I Amplification Grade Kit, Invitrogen, Life Technologies, Paisley, UK). cDNA synthesis and quantitative RT-PCR were performed using the DyNAmo HS two-step SYBR Green qRT-PCR kit (Finnzymes Oy, Espoo, Finland). The data were normalized by relating gene expression to the mouse ribosomal protein L19 and peptidyl-prolyl isomerase A (PPIA, cyclophilin A) using Pfaffl method. Primer sequences are listed in Supplementary Table  S4. Microarray analysis. We isolated total RNA with TRIZOL reagent (Invitrogen) from PND10 male control, SC-Rb þ / À , and SC-RbKO mice and precleaned them with an RNeasy MinElute Cleanup Kit (Qiagen). The RNA concentrations were measured with Nanodrop ND-1000 (Thermo Fisher Scientific, Waltham, MA, USA), and RNA quality was controlled by Experion analysis (Bio-Rad Laboratories).
Normalization and statistical analyses of the microarray data were performed using the statistical software R package limma (http://www. R-project. org) or Sigma Stat 3. 1 (SPSS Inc. , Chicago, IL, USA). The fold change ranging from À 1. 60 to þ 2. 59 versus controls was set according to hierarchical clustering and principal component analysis. Knockdown of E2F3 by specific shRNA silencing. For silencing the expression of E2F3 (E2F3a, E2F3b), an expression vector containing shRNA that can specifically inhibit both E2F3 gene isoforms was constructed using a previously published sequence,  42  and compared it to a sequence of mouse E2F3 mRNA (NM_010093), before designing a pair of oligonucleotides (60 nt); E2F3 primers: sense primer: 5 0 -GATCCCCGACCAAACTGTTATAGTTGTTCAAGAGAC AACTATAACAGTTTGGTCTTTTTA-3 0 and antisense primer: 0 -AGCTTAAAA AGACCAAACTGTTATAGTTGTCTCTTGAACAACTATAACAGTTTGGTCGGG-3 0.