dataesr/scientific-paragraphs-categorization huggingface dataset:
Identification of genes potentially involved in lignin and vanillin biosynthesis Lignin is a phenylpropanoid polymer commonly found in terrestrial plant secondary cell walls. Lignin is assembled by oxidative polymerization of three major monolignols, p-hydroxycinnamyl alcohol (H unit), coniferyl alcohol (guaiacyl or G unit) and sinapyl alcohol (S unit). However, during the early stages of seed development in V. planifolia, a newly discovered polymer (C-lignin) is deposited to high concentrations in the seed coat. This lignin is naturally synthesized from the unusual monolignol caffeyl alcohol, whereas lignin in the vegetative tissues of V. planifolia is of the normal guaiacyl/syringyl (G/S) type  [5]. To address potential pathways of C-lignin biosynthesis, we used annotated lignin pathway genes in Arabidopsis as query sequences (Figure  7A ), searched by BlastX with the threshold as E-value <1E-5, and searched against the NCBI NR, GO and KEGG databases with the annotation of lignin pathway.
The sequences of the primers used for RT-PCR are given in Additional file 15. Consistent with the digital expression database, PAL, 4CL, CCR, CAD and C4H displayed very high transcript levels in 8 week seeds and relatively high levels in 10 week seeds, while low transcript levels in dark and light mesocarp tissues. In contrast, CCoAOMT transcripts were detected in dark and light mesocarp tissues, but barely in seed tissues (Figure  8 ). The low level of CCoAOMT transcripts is likely the biochemical basis for the production of the novel non-methylated C-lignin in the vanilla seed coats  [5]. This result is consistent with our earlier finding of low OMT enzyme activities in the C-lignin containing seed coat of Cleome hassleriana  [32]. The digital expression database contains transcript level values for all potential lignin pathway genes in additional pod tissues such as hairs and placenta at later stages of pod development.
Conclusions Next-generation sequencing and computational data mining tools have been used for high-throughput transcriptomic profiling of developing vanilla beans. The combined 454/Illumina RNA-seq platforms provide both deep sequence coverage and high quality de novo transcriptome assembly for this non-model crop species. The annotated sequence data provide a foundation for understanding multiple aspects of the biochemistry and development of the vanilla bean, as exemplified by the identification of candidate genes involved in an unusual lignin biosynthesis pathway in vanilla seed. Our transcriptome data indicate that C-lignin formation in the seed coat involves coordinate expression of monolignol biosynthetic genes with the exception of those encoding the caffeoyl coenzyme A 3-O-methyltransferase for conversion of caffeoyl to feruloyl moieties.
25. A combined assembly of all 26 Illumina samples  (3, 439, 193 ,362 reads total) was produced using Velvet 1. 2. 03 with a k-mer length of 27, producing 6,371,646 contig sequences. A library of 1,678,293 454 reads (mean length =397. 5 bp) was also produced and quality trimmed using a cut-off score of 20. The 454 reads and Illumina contigs were then assembled together with MIRA 3. 2. 1  [17] , using the "normal" quality parameters for a de novo 454 EST assembly. To estimate transcript expression levels in each of the 26 Illumina libraries, the reads were mapped back to the assembled transcript sequences using Bowtie2 2. 0. 0 (beta 7)  [19]  with the "sensitive" end-to-end alignment parameters. The number of reads mapped to each transcript was then counted and used to calculate the RPKM value for every transcript in each library.
Sequence analysis and gene annotation The resulting 301,459 transcripts from de novo combined assembly were annotated via alignment with the NCBI NR database, the Conserved Domains Database, and the Arabidopsis, rice, and sorghum proteomes (ftp:// ftp. ncbi. nlm. nih. gov/). Tissue specific genes were detected in R 3. 0. 1  [34]  with the package "rsgcc"  [23]. Tissue specific genes were further annotated with default parameter values using Blast2Go  [35]. After the Blast2Go mapping process, EC numbers from the KEGG pathway (http:// www. genome. jp/kegg/) and GO terms were generated.
Real-time quantitative RT-PCR Total RNA was isolated from seed, mesocarp and stem tissues as described above. cDNA synthesis was performed using DNase I-treated RNAs and Superscript III reverse transcriptase (Invitrogen). Primer pairs for real-time qRT-PCR were designed using GenScript Real-time PCR Primer Design software (https://www. genscript. com/ssl-bin/app/primer) with the default parameters (Additional file 15). qRT-PCR was performed in duplicate for each sample and at least two biological replicates were evaluated for each gene tested. The qRT-PCR reactions were performed in an optical 96-well plate with a PikoReal. Real-Time PCR System (Thermo Scientific), using SYBR Green Master Mix reagent (Simga) with PCR program as previously described  [36]. Data were collected and analysed using PikoReal Software (Thermo Scientific).
Deep sequencing data analysis. Sequencing reads were preprocessed and annotated using a set of custom Python scripts encompassing different tools. First of all, the Dustmasker program  (25)  and FASTX-Toolkit (http:// hannonlab. cshl. edu/fastx toolkit) were successively applied to filter out low complexity reads and remove instances of the 3 adapter. Degenerate bases incorporated during the library preparation protocol were also trimmed at this step. Remaining reads ≥15 nt in length were then mapped simultaneously to the human (assembly version hg19 -UCSC repository) and KSHV (accession number NC 009333. 1 -RefSeq database) genomes using Bowtie 0. 12. 7  (26) , permitting up to 2 mismatches in total with no more than 1 mismatch in the first 15 nucleotides of each read. Only alignments from the lowest mismatch stratum were recorded and reads that could map to more than 50 loci were discarded.
In parallel, two sequencing reactions were done with 1 pmol of non-treated RNAs (per reaction), using ddATP and NED R labeled primer, or ddGTP and positron emission tomography labeled primer. ddNTP were at 5. 56 M and dNTP at 42 M. All four reverse transcription reactions were pooled, then cDNAs were purified by phenol/chloroform extraction, ethanol precipitated and finally dissolved in 10 l deionized formamide. SHAPE Data processing. Fluorophore labeled cDNAs were resolved by capillary electrophoresis using ABI 3130xl Genetic Analyzer, capillary size 50 cm. The resulting electropherograms were converted into SHAPE reactivities using SHAPE Finder software and normalized  (34). This procedure has been described in detail in Athavale et al. (35). For the normalization of SHAPE reactivities, the 2% highest values from the pool were removed.
RNA secondary structure prediction and modelisation. We folded the entire cluster RNA (3157 nt) using the thermodynamics-based free energy minimization algorithm in the RNAstructure software package, version 5. 3  (36). For the minimum free energy structure, we used the pseudoenergy constraints specific for SHAPE data with default values for the SHAPE slope (2. 6 kcal/mol) and SHAPE intercept (-0. 8 kcal/mol). The maximum pairing distances were set at 200 nucleotides. The final structure of pri-miR-K10/12 was drawn with Assemble 2 program, available at http://bioinformatics. org/assemble  (37).
To further explore the contribution of the genomic context for the relative accumulation of each miRNA, we also compared their expression level in transiently transfected HEK293Grip cells using constructs containing either the K10/12 cluster or a portion of it containing only one single pre-miRNA. As shown in Figure  1B , this resulted in notable differences in mature miRNA expression ranging from a complete loss of expression (miR-K2) to a more than 2fold up-regulation (miR-K8). Two major differences were observed in the KSHV miRNA profiles of the three cell lines: the absence of miR-K9-5p and -3p in BC-3 and of miR-K11-3p in DG-75-K10/12. As previously reported  (38) , sequencing of the viral genomic DNA identified several mutations within the pre-miR-K9 sequence in BC-3 compared to the sequence from RefSeq database (NC 009333.
1) or to the BCBL-1 genomic sequence (Supplementary Figure  S3 ). Whether these mutations may alter Drosha processing is currently not known. The DG-75-K10/12 cell line was generated by integrating in its genome the 10 intronic clustered miRNAs from BCBL-1 cells. We therefore expected to observe the same viral miRNA expression profile in the two cell lines. However, miR-K11-3p, which is one of the most abundant miRNAs in BCBL-1, does not accumulate in the DG-75-K10/12 cells. We verified that no mutation occurred at the genomic DNA level in the pre-miR-K11 region (Supplementary Figure  S3 ). Surprisingly, this lack of expression seems to be specific of the DG-75 cell line since miR-K11-3p significantly accumulated in the FLP-K10/12 HEK293 derived cell line ((21) and data not shown). Finally, we compared our deep sequencing and quantitative northern blot data (Figure  2 ).
We could not conclude regarding the existence of a core domain in the KSHV cluster. However, miR-K3 and -K9 stem-loops may be involved in tertiary interactions via stretches of adenosines in their respective apical loop, rendering them less accessible to Drosha. Moreover, sequences or structural features distinct from miRNA stem-loops may also constitute regulatory elements for Drosha cleavage. Finally, the processing of one miRNA may influence the subsequent processing of adjacent miRNAs. Our data provide evidence that the secondary structure of the pri-miRNA is important for the good expression of clustered miRNAs. There are, however, limitations to our approach as we assessed the secondary structure of the pri-miR-K10/12 cluster using naked RNA. Indeed, some accessory proteins may act by inducing conformational changes in the RNA to satisfy or prevent the structural requirements for Drosha processing.
FUNDING Agence Nationale pour la Recherche [labex netRNA ,  ANR-10-LABX-36 ];  European Union  [ ERC Starting Grant  ncRNAVIR  260767 ,  ERG Career Grant   268301 ];  Fondation pour la Recherche Médicale. M. C. is supported by a fellowship from the  Ligue Nationale contre le Cancer. Source of open access funding:  ERC Starting Grant  [ncRNAVIR 260767].
Continued research of this area will obviously be critical to the development of therapeutic strategies for C. neoformans. The first symposial session, "Infectious Fungal Diseases", followed neatly on, thematically, from the first keynote address. Morwenna Boddington (Faculty of Health, Engineering and Sciences, University of Southern Queensland) opened the "Fungal Systematics" session with  to more fully understand the interactions between fungi and natural and managed environments. Laszlo Irinyi (Molecular Mycology Research Laboratory, Westmead Hospital) concluded the session with an outline of the establishment of an online database of 2700 ITS sequences of 416 medically important fungi. This database may be expanded to include alternative genetic loci for a number of taxa. A session on "Applied Mycology" outlined some of the significant roles fungi can have in industry, forestry and agriculture.
ACKNOWLEDGEMENTS We acknowledge the stakeholders who participated in the workshops and are grateful for the insights they provided. This study was supported by  EuroGentest  (EuroGentest 2, Unit 2: Genetic testing as part of health care, Work package 6 ( WH Rogowski ), grant number  Health-F4-2010-261469 ). It was further supported by the grant ' Individualized Health Care: Ethical, Economic and Legal Implications  for the  German Health Care System' of the German Federal Ministry of Education and Research (BMBF , grant numbers  01GP1006A  and B).
Samples and datasets Twenty breast cancer patients treated with radiation during 2002-2005 were included in our study. All patients had inoperable breast cancer stage 3-4 or local relapse, with no standard treatment established. Some patients had received systemic treatment before the RT. The volume targeted was the mammary gland and affected lymph nodes when present. Total dose prescribed was 25 3 2 Gy with photons or 23 3 2 Gy with photons and 2 3 2 Gy with electrons. Biopsies were collected both before radiation (n 5 20) and after receiving 10-24 Gy (n 5 19) of photon irradiation, depending on practicalities in biopsy sampling and scheduling. The response to radiation was evaluated after treatment completion, based on alterations in the clinically evaluated tumor size and categorized as good response, partial response, no response or progression.
Side effects were evaluated according to RTOG/EORTC Late Radiation Morbidity Scoring Scheme. 9 ll clinical information is presented in Supporting Information Table  S1 , which is an updated description of the clinical material that Helland et al. used when studying gene expression. 10 Breast tissue from nine healthy women who underwent breast tissue reduction was used as reference material (denoted as normal controls). The methylation array data are available in the Gene Expression Omnibus (GEO) (http://www. ncbi. nlm. nih. gov/geo) with accession number GSE50220.
DNA methylation The EpiTectV R Bisulphite Kit 48 (Qiagen, California, USA) (Source: EpiTectV R Bisulphite Handbook, QIAGEN 09/2009) was used to treat DNA with bisulfite, and the amount of converted DNA was measured by real-time polymerase chain reaction (PCR), as previously described. 11 The methylation analysis was performed by using Illumina Infinium Human-Methylation27 BeadChip Kits, Genome Build 36 (27K). 12 ecause of low DNA concentration, the total elution volume of the bisulfite-treated DNA (30-40 lL) was used instead of the recommended 4 lL. To ensure complete denaturation, 30 lL 0. 1 M NaOH was used instead of 4 lL as outlined in the methylation 40 protocol guide. The rest of the procedure was performed according to the protocol (Illumina, San Diego, USA Part#11322371 Rev. A). Methylation scores for each CpG site are referred to as "beta" values (using the BeadStudio software from Illumina) ranging from 0 (unmethylated, U) to 1 (fully methylated, M) on a continuous scale, and are calculated from the intensity of the M and U alleles as the ratio of fluorescent signals, b 5 Max(M,0)/(Max(M,0) 1 Max(U,0 1 100)).
Statistical analysis The array dataset was quality controlled and normalized. Bead studio software was used for the initial processing of the methylation data. Probes for which a score was missing for any array were discarded (n 5 10). Raw data were normalized according to a three-step process: color bias correction, background level correction and quantile normalization. Only those beta values associated with significant p-values were selected for comparing locus methylation status of the data. Individual loci were scored as differentially methylated if the difference between median beta values was greater than or equal to 20% of methylation. A paired analysis of the samples was utilized with a significance analysis of microarrays (SAM) in J-express (http:// www. molmine. com/) (log2-transformation, 2000 permutations).
Next, a group comparison based on the beta-values from the array was performed. The dataset was divided into two groups consisting of (i) nonirradiated samples and (ii) irradiated samples, and a Prediction Analysis of Microarrays (PAM) was performed in R (ver. 2. 12. 2 http://cran. r-project. org/). The "nearest shrunken method" was used to identify those genes best characterizing each class. 14 By defining a threshold, a misclassification table for the samples and number of genes with false discovery rate (FDR) were obtained. The threshold giving the lowest overall error (OER) and the minimum misclassified samples was chosen. To test the robustness of the gene list, a "leave one out test" (LOO) was performed in R. Extracted lists based on the PAM analysis were further analyzed by supervised hierarchical clustering in J-express (http://www.
molmine. com/) (average linkage and Spearman rank correlation) and ingenuity pathway analysis (IPA; IngenuityV R Systems, http://www. ingenuity. com). A Spearman's rho correlation analysis between given doses and changes in the degree of methylation was performed by using R (ver. 2. 15. 1). The Mann-Whitney U-test, Fisher's exact test and Spearman's correlation analysis (IBM SPSS Statistics 18) were used when appropriate. Criteria for significance for all analyses were p < 0. 05. Furthermore, to investigate the difference between good and poor responses for "before IR" and "after IR" groups, the following statistical procedure was applied: (i) A methylation index (z-score) of the data was obtained by calculating for each sample the deviation from the mean methylation level divided by the standard deviation for each gene.
DNA methylation associated with RT Genome-wide DNA methylation data from breast tumor samples (n 5 39) and normal controls (n 5 9) were obtained with the use of the Illumina Infinium 27K array. By using PAM, 140 probes representing 138 genes (referred to as PAM140 list; see Supporting Information Table  S4 ) were identified as differentially methylated in the nonirradiated samples versus the irradiated samples (FDR 5 8. 7). For PAM140, OER was 27. 8%, indicating that as many as six of 19 after IR samples and five of 20 before IR samples were misclassified. Supervised hierarchical clustering was performed by using the PAM140 list (see Fig. 1a ). Six of the paired samples clustered together (102, 112, 113, 117, 121 and 125 marked with a beige box in the cluster), indicating that these after IR samples shared more similarities with its respective sample partner than with the irradiated group.
The surrounding tissue is central for processes such as the inflammatory response, found enriched in our dataset. Within the dose-dependent gene list, a significant change in methylation pattern for pathways associated with cellular immune response, cell cycle regulation and apoptosis was found, representing mechanisms known to be important in radiation response. This is consistent with the results from Zheng et al. , who, when studying irradiated mice, found activated pathways mediating repair, apoptosis, coagulation and cell cycle control. 23 Interestingly, when looking at negative and positive dose-correlated probes separately, the positively correlated pathways (demethylated) had a lower FDR, suggesting that demethylation of genes is more prominent after irradiation. We found that irradiation resulted in demethylation of pathways either involved in the immune system response or in cell proliferation and survival.
CUORE-0 is a cryogenic detector that uses an array of tellurium dioxide bolometers to search for neutrinoless double-beta decay of 130 Te. We present the first data analysis with 7. 1 kg • y of total TeO 2 exposure focusing on background measurements and energy resolution. The background rates in the neutrinoless double-beta decay region of interest (2. 47 to 2. 57 MeV) and in the α backgrounddominated region (2. 70 to 3. 90 MeV) have been measured to be 0. 071 ± 0. 011 and 0. 019 ± 0. 002 counts/(keV • kg • y), respectively. The latter result represents a factor of 6 improvement from a predecessor experiment, Cuoricino. The results verify our understanding of the background sources in CUORE-0, which is the basis of extrapolations to the full CUORE detector. The obtained energy resolution (full width at half maximum) in the region of interest is 5.
2% at the 0νDBD Q-value. 0νDBD data taking with CUORE-0 began in March 2013. CUORE-0 also serves as a technical prototype for CUORE (Cryogenic Underground Observatory of Rare Events)  [17] , which will consist of 19 towers identical to the single CUORE-0 tower. CUORE-0 is the first tower produced on the CUORE assembly line, and its successful commissioning represents a major milestone towards CUORE. CUORE is in the advanced stages of detector construction at the time of this writing and is scheduled to begin data taking in 2015. derground facility in Italy. As shown in Figure  1a , the tower consists of 13 planes of four 5 × 5 × 5 cm 3 crystals, held securely inside a copper frame by specially designed polytetrafluoroethylene (PTFE) brackets. The copper frame serves as a thermal bath to cool the crystals through the weak thermal coupling provided by PTFE.
CUORE-0 performance and background The CUORE-0 data reported in this article was collected between March and September 2013, with interruptions for dilution refrigerator maintenance. To account for temporary degraded performances on each individual bolometer due to large baseline excursions or elevated noise levels, we reject low-quality data intervals on a channel-by-channel basis. Consequently, the total exposure is obtained by summing the individual exposures of each bolometer. The accumulated TeO 2 exposure on 49 fully active channels is 7. 1 kg • y for a 130 Te isotopic exposure of 2. 0 kg • y, excluding all lowquality data intervals. CUORE-0 data analysis follows the same procedure as was used for Cuoricino  [12]. This includes amplitude evaluation, gain correction, energy calibration, and time coincidence analysis among the bolometers.
This probability has been estimated by simulation to be 87. 4 ± 1. 1%  [12]. Taking into account the 99. 00 ± 0. 01% signal trigger efficiency, which is evaluated on pulser events, the total 0νDBD detection efficiency of CUORE-0 is 80. 4 ± 1. 9%. This result is compatible with the value obtained from Cuoricino, which was found to be 82. 8 ± 1. 1%  [12]. The top panel in Figure  2  shows the energy spectrum obtained using the 232 Th calibration source. The spectrum is the sum of all 49 fully functional channels. The histogram in the bottom panel shows the background spectrum of CUORE-0 for the analysis presented. The presence of the pronounced γ-ray peaks from 214 Bi decay, a daughter nucleus of 222 Rn, is attributed to the inclusion of data taken without the nitrogen gas purge in the Faraday cage around the dilution refrigerator.
Since the number of 2615 keV γ-ray events is much larger than that of possible 0νDBD events, the blinding algorithm produces an artificial peak around the 0νDBD Q-value and blinds the real 0νDBD rate of 130 Te. This method of blinding the data preserves the integrity of the possible 0νDBD events while maintaining the spectral characteristics with measured energy resolution and introducing no discontinuities in the spectrum. The background rate in the ROI is evaluated using the blinded spectrum in the energy range 2470 -2570 keV. This region includes the 60 Co sum-peak at 2506 keV and the salted peak at the 0νDBD Q-value, as shown in Figure  3. We use an unbinned maximum-likelihood fit to estimate the background rate in the ROI. The likelihood function consists of the sum of a 60 Co Gaussian peak, a salted 0νDBD Gaussian peak, and a flat background.
As a technical prototype for CUORE, CUORE-0 demonstrates the feasibility of instrumenting an ultra-pure ton-scale bolometer array with 988 channels. By enhancing the procedure of the on-going CUORE assembly, we have improved assembly success rate to close to 100%, which is a crucial achievement for large arrays such as CUORE. We have started implementing the noise decorrelation algorithms into the CUORE-0/CUORE data analysis package, with the aim of further improving energy resolution. CUORE-0 reconfirms the effectiveness of the copper cleaning technique and clean assembly procedure developed for CUORE. Compared to CUORE-0, the larger array of CUORE affords more powerful time coincidence analysis and more effective self-shielding from external backgrounds, particularly those originating from the copper thermal shields or cryostat.