dataesr/scientific-paragraphs-categorization huggingface dataset:
study design, data collection and analysis, decision to publish, or preparation of the manuscript. Funding for the project was provided to HH by baseline funding project  BAS/1/1062  of the  King Abdullah University of Science and Technology. Investissement d' Avenir Infrastructures Nationales en Biologie et Santeprogram  ( ProFI  project,  ANR-10-INBS-08 ) to DP (http://www. agence-nationale-recherche. fr/en/international-cooperation/).
Objective and strategy We investigated the density dependence of both asexual and sexual reproductive mechanisms in Z. tritici, a relevant fungal model organism for such eco-epidemiological investigations. What impact does lesion density in host tissues have on sexual reproduction at the leaf scale? Could we generate empirical data for the establishment of a density-dependence relationship? Would this relationship be monotonic or more complex, due to competition for resources between the two modes of reproduction? This study addressed these questions. We first analyzed epidemiological datasets collected in field conditions, to confirm our initial assumptions. We then assessed the intensities of asexual and sexual reproduction after five Z. tritici biparental crosses on adult wheat plants over a period of three years.
Preliminary analysis of field epidemiological data Field epidemiological data were analyzed to assess the impact of disease severity (proxy of asexual multiplication intensity) and the vertical position of the host tissues on the intensity of subsequent sexual reproduction, during the epidemic period and then during the interepidemic period. We reanalyzed a dataset obtained in Danish field conditions by Eriksen & Munk  [16] , together with the data obtained in our three-year experiment in France. Epidemic period -The relationship between the proportion of pseudothecia among the total fruiting bodies (pycnidia and pseudothecia) on wheat leaves during a growing season and mean disease severity (expressed as the percentage of the leaf area covered by pycnidia and pseudothecia) were determined with the experimental data for the field experiment performed by Eriksen & Munk  [16]  (Table  1 ).
Data analysis and visualization Statistical analysis -ANOVA or Kruskal-Wallis test when relevant and post hoc multiple comparisons -were performed using the R software. A quadratic equation (eq. 2) was used to visualize the relationship between sexual reproduction intensity (SRI) and asexual multiplication intensity (AMI). SRI = a. AMI 2 + b. AMI + c eq. 2 where a, b and c are parameters. An alternative equation integrating two types of density-dependent constraints (eq. 3) was also used. It was based on a logistic function f(α,,,AMI) (eq. 4) describing a positive density-dependent mechanism and coupled with a function g(,,,AMI) (eq. 5) describing a negative density-dependent mechanism. SRI = f(α, , , AMI) × g(, , , AMI) eq. 3 f(α, , , AMI) = α. e (-β. e -γ. IAM ) eq. 4 g(, , , AMI) = μ -(μ -σ) (e (-ln μ.
These empirical observations thus complete the results obtained by reanalyzing the dataset of Eriksen & Munk  [16]. * * * Traits relating to asexual multiplication in planta, such as the density and exudation capacity of pycnidia, are affected by competition between the two parental isolates for resources. This result is consistent with the lower level of pycnidial coverage observed after inoculation with mixtures of isolates than after inoculation with single isolates  [28, 29]. The competitive disequilibrium between the two parental isolates may also account for the density dependence of asexual development in Z. tritici. This finding is consistent with previous results obtained in the same experimental conditions in a previous study  [23] , in which an interval of two to three weeks between inoculation with the first parental isolate and inoculation with the second was found to be detrimental to ascosporogenesis.
The complete dataset is given in Table  S1. Fig. 11  Theoretical relationship between asexual multiplication intensity in Zymoseptoria tritici (disease severity assessed as a percentage of necrotic area) and sexual reproduction intensity (normalized number of ascospores produced per g of wheat tissue), assuming that the conidia of two compatible parental isolates were deposited in equal proportions on leaves. Grey areas represent the decrease in sexual reproduction intensity due to: (1) an Allee effect (difficulty finding the opposite mating type at low population densities); (2) induced resistance (activation of host defense mechanisms by one of the parental isolates, leading to a mating-type disequilibrium); (3) competition for host resource allocation between asexual multiplication and sexual reproduction.
Furthermore, specific modes of epigenetic regulation may operate at the different 5S rRNA loci, exemplified by the role of RNA polymerase V in controlling transcription and chromatin organization of the 5S rRNA gene copies situated on chromosome 4  (17). However, so far detailed information on potential differences in epigenetic marks between the three 5S rRNA gene loci and their role in the control of 5S rRNA gene transcription are missing. Using Next Generation Sequencing (NGS) datasets, we show here that the Col-0 genome comprises over 2000 5S rRNA gene copies distributed in three major loci. While 5S rRNA gene sequences situated on chromosome 3 are the most polymorphic and enriched in repressive histone marks, gene copies of chromosome 5--and to a lesser extent of chromosome 4--are moderately enriched in transcriptionally permissive marks.
In agreement, the locus on chromosome 5 is the major source of the atypical 5S-210 transcript, indicating a more open chromatin configuration. A similar in-depth analysis of a different ecotype, Landsberg erecta (Ler), revealed different enrichment in epigenetic marks and distinct prevalence of 5S-210 transcripts among 5S loci, indicating differential usage of 5S rRNA gene loci among ecotypes. In silico analysis of NGS datasets of a large number of ecotypes further revealed conservation of chromosome-specific transcription termination sequences in 5S rRNA genes coupled to important copy number variations, while 5S rDNA copy numbers are stably maintained during shorter time scales within the same ecotype. Finally, by combining in silico analysis, linkage mapping in a segregating population, chromosome-specific FISH and qPCR we characterized novel 5S rDNA insertions in the Ler genome and in several mutants in the RNA-directed DNA methylation (RdDM) pathway.
DNA extraction and qPCR conditions The aerial parts of about five 3-week-old plants for each of the three biological replicates were shock frozen in liquid nitrogen, ground to powder and incubated at 65 • C in extraction buffer (Tris pH 8 0. 1 M, EDTA pH 8 50 mM, NaCl 500 mM, SDS 1. 23%), potassium acetate was then added to a final concentration of 7. 45 mM before centrifugation at 16 000g. DNA was precipitated in isopropanol. The pellet was resuspended into Tris-EDTA buffer and ethanol precipitated. The final DNA pellet was resuspended in water and stored at -20 • C. DNA purity and quantity was assessed with a Nanodrop. 500 ng of purified DNA were used per 10 l reaction in the Lightcycler 480 (Roche) with the LightCycler ® 480 SYBR Green I Master mix (Roche). For each biological replicate, a mean of two technical replicates was assessed and qPCR data were analyzed using the Ct method.
Bioinformatics analyses Copy number estimation. To estimate 5S rRNA gene copy number through next-generation-sequencing (NGS), we divided the average coverage along the 120 bp transcribed sequence of the 5S rRNA by the average coverage along 16 reference genes (At1g13320, At1g58050, At1g59830, At2g28390, At2g32170, At3g01150, At3g53090, At4g26410, At4g27960, At4g33380, At4g34270, At4g38070, At5g08290, At5g15710, At5g46630 and At5g55840  (25) ), in addition to the genes At2g36060 and At4g29130 used for qPCR normalization in this study. For each individual dataset analyzed in this study we mapped 50 bp single-end (SE) reads separately to a single reference consisting of the 120 bp transcribed sequence of the 5S rRNA gene and to the Arabidopsis TAIR10 reference genome with BWA-MEM (v0. 7. 8) (26; Li, arXiv:1303.
Extraction of T-stretch signatures. To determine the sequence of the different T-stretch signatures downstream of the 120 bp transcribed sequence without an a priori, we generated an in-house pipeline (https://gist. github. com/ laurianesimon/0ae2dd7b8c34c23cdacec217aeaab79c). This pipeline maps 50 bp reads using BWA-ALN with low stringency settings (allowing four mismatches in the last 15 nucleotides) against a single reference consisting of the consensus 120 bp transcribed sequence of the 5S rRNA gene prolonged in 3 by 30 Ns and extracts the downstream sequence. The T-stretch sequence for each read was then affected manually to its locus of origin based on sequence information from chromosome-specific YACs  (11). For reads longer than 50 pb, reads were trimmed. The same pipeline was applied to determine the T-stretches in 5S-210 RNA-Seq datasets.
Identification of chromosome-specific polymorphisms. To determine the polymorphisms in the 5S rRNA genes in a chromosome specific manner, we developed a pipeline that isolates flashed reads from the Mi-Seq dataset using grep on an exhaustive list of the identified T-stretches (https://gist. github. com/laurianesimon/ a9fc44aa83305c576e914710cae75f87). The isolated reads were then mapped using BWA-MEM to multiple references of 160 bp in length, which comprise the 120 bp transcribed sequence of the 5S rRNA gene as well as 20 nucleotides upstream and downstream; the latter including the specific T-stretches. Only reads covering the whole 120 bp transcribed sequence were retained to determine the polymorphisms in the transcribed sequence. The observed polymorphisms for each reference were extracted and quantified.
Quantification of enrichment in epigenetic marks. To analyze the enrichment of different epigenetic marks, available raw ChIP-seq data (Supplemental Table  S3 ) have been reanalyzed: For the immunoprecipitation (IP) we extracted the number of reads mapped by BWA ALN to ACT2, HXK1, Ta3 and the 120 bp transcribed sequence of the 5S rRNA gene divided by the total number of reads of the ChIP-Seq dataset. For normalization by the length of the gene of interest or the 5S copy number, this value was divided by the mean read number from three Col-0 input DNA datasets  (32, 33) , as most of the ChIP-seq datasets were not provided with an internal input DNA control. To determine the enrichment at each 5S locus, specific T-stretch signatures were extracted from each ChIP-Seq dataset as above and normalized to the proportion of 5S reads from a particular chromosome in the input datasets.
To determine more precisely 5S rRNA gene copy number in the Col-0 genome, we used high coverage NGS data. We generated an Illumina Mi-Seq dataset with 300 bp paired-end reads and fragments of roughly 500 bp in size (74. 5% reads >QC 30) and analyzed two publicly available Illumina Hi-Seq datasets (Supplemental Table  S2 ) for Col-0  (28, 34, 35). Read mapping to the consensus of the 120 bp transcribed sequence of the 5S rRNA gene (Figure  1A , Supplemental Figure  S1B ) revealed ∼2000 5S rRNA gene copies per haploid genome, which were confirmed by qPCR (Figure  1B ). Sanger sequencing of YAC-DNA previously showed the existence of particular T-rich termination sequences, termed T-stretch signatures, at the three main 5S rDNA loci situated on chromosomes 3, 4 and 5 (Figure  1C )  (11). To obtain a high-resolution view of these T-stretch signatures in the Col-0 genome we extracted all sequences 3 of the 120 bp transcribed sequence from the Mi-Seq dataset using an in house Perl script.
T-stretch sequences could be identified as belonging to chromosome 3 by the specific stretch characterized by CGG(Nx)CTC, to chromosome 4 by the uninterrupted T-stretch or to chromosome 5 by the motif ATG(Nx)AACC. Besides the major DNA-signatures (Figure  1D ), we revealed recurrent single nucleotide polymorphisms (SNPs) in the T-stretches, particularly for the polymorphic 5S rRNA genes assigned to chromosome 3 (Supplemental Figure  S1C ). To confirm that the different T-stretches are indeed specific to a particular chromosome, we then confronted the identified T-stretch sequences to sequencing datasets of six YACs (36) that comprise 5S rDNA sequences assigned to the genetic map  (11). Indeed, T-stretches are specific, as we never find T-stretch signatures assigned to a specific chromosome in the 5S loci from other chromosomes (Supplemental Figure  S1D ).
5S rRNA gene loci are differentially enriched in certain histone marks and histone variants To investigate whether the distinct sequence features at the three 5S rDNA loci are reflected at the level of their chromatin organization, we exploited available ChIP-seq datasets (Supplemental Table  S3 ) to quantify nucleosome occupancy, enrichment in histone modifications and the presence of certain histone variants at the 5S rRNA genes (Figure  3A  and B, Supplemental Figure  S3A  and B ). First, enrichment at all 5S rRNA genes was compared to two active genes with different expression levels (Supplemental Figure  S3C ) as well as the silent Ta3 retrotransposon, situated in the pericentromeric region of chromosome 1. In contrast to active genes and similarly to Ta3, 5S rRNA genes globally show elevated nucleosome occupancy and are enriched in H3K9me2 and the histone variant H2A.
Since 5S-210 transcripts are suggested to represent read-through transcripts by RNA polymerase III and to be a marker for a more permissive chromatin organization  (18, 20) , this indicates that 5S rDNA copies from the chromosome 5 locus are the main contributors to the 5S rRNA pool. Taken as a whole, occurrence of single nucleotide polymorphisms, including the -26 T-G mutation in the TATAbox on chromosome 4, chromatin modifications and RNA-Seq datasets, suggest that the locus in chromosome 5 has a more open chromatin configuration and is the major source of 5S rRNA in Col-0.
The additional 5S rRNA gene locus on chromosome 3 in Landsberg erecta (Ler) plants carries the chromosome 5specific T-stretch signature To further investigate the variations in 5S rRNA gene loci organization, we analyzed in more detail the Landsberg erecta (Ler) ecotype. Ler has been selected after irradiation from the original Landsberg line  (42, 43) , and it is the only other ecotype for which a fully independently assembled genome is available  (43). Interestingly, Ler plants comprise a 5S rRNA gene locus on the long arm of chromosome 3, but the origin of this locus remains unknown. An analysis of publicly available Ler Illumina NGS datasets  (44)  showed neither T-stretch signatures nor polymorphisms characteristic for Col-0 chromosome 3 (Supplemental Figure  S2A ). This result confirms previous FISH studies that failed to reveal a 5S rDNA locus in the pericentromeric regions of chromosome 3 in Landsberg (La-0) and Ler  (2, 43) , and suggests that the 5S rRNA gene locus on chromosome 3 in Ler does not have the same origin as in Col-0.
Furthermore, in the pool of 5S-210 transcripts, the percentage of transcripts with uninterrupted T-stretches characteristic for chromosome 4 is higher in Ler (19. 1% versus 9. 3%, P < 0. 05, Figure  6C ), which argues for a more open chromatin state at the 5S rDNA locus from chromosome 4 in Ler. Moreover, analysis of the Ler NGS datasets revealed no evidence for -26 T-G mutations in the TATA-box (Supplemental Figure  S2D ), while in Col-0 they were frequent in 5S rRNA genes of chromosome 4. Finally, we investigated whether the altered position of 5S rRNA gene loci affects nuclear organization in interphase. FISH with a 5S rDNA probe detecting all 5S rRNA gene loci and the centromeric 180 bp probe to mark chromocenters revealed that ∼80% of Col-0 nuclei show six independent 5S rDNA FISH signals partly co-localizing with chromocenters (Figure  6D  and E ).
DISCUSSION 5S ribosomal RNA is of critical importance for protein synthesis and contributes substantially to the total cellular RNA pool. Present in excess in the genome, only a subset of 5S rRNA genes is actively transcribed at a given time, prompting interesting questions on the mode of gene choice and regulation. Here, using DNA, RNA and ChIPsequencing datasets we reveal variation in 5S rRNA gene sequences as well as differential chromatin profiles and 5S rRNA transcripts between loci and ecotypes, suggesting preferential expression of specific sets of genes among ecotypes. Based on our exhaustive characterization of T-stretch signatures in different whole genome datasets and in subsets of 5S rDNA loci cloned in YACs combined with the detection of specific T-stretches by FISH, we conclude that 5S rRNA genes with the same T-stretch characteristics cluster within the same locus.
Using independent approaches including linkage mapping in the MAGIC population, in silico analysis of available Illumina sequencing datasets, qPCR analysis and FISH studies we characterized a novel locus on the long arm of chromosome 3 in Ler as originating from chromosome 5. Mapping narrowed down the position of this locus to ∼6. 24 Mb, close to a large-scale inversion of 170 kb recently found in the Ler genome  (43). Irradiation of the original Landsberg line that resulted in L. erecta  (51)  might therefore have induced an inversion on chromosome 3 as well as translocation of part of the 5S rDNA locus of chromosome 5. Furthermore, differences in 5S rDNA locus positions between WT and ago4 or dcl mutants illustrate the mobility of 5S rRNA gene copies. Together, these observations support the notion that 5S rRNA genes show frequent reorganization and may therefore be only under low selective pressure during evolution  (52).
Together, this implies that this locus predominantly contributes to the 5S rRNA pool in Col-0. In yeast, transcription of rRNA genes favors recombination resulting in rRNA copy number variation  (66, 67). This is particular interesting in light of our observation that copy numbers of 5S rRNA genes with the chromosome 5-specific signature are highly variable among ecotypes and that they engage in translocations in ago4 mutants, in which chromatin organization is affected  (16). In comparison to Col-0, the 5S rRNA genes of chromosome 4 in Ler show a more permissive chromatin environment and relatively more 5S-210 transcripts originate from this locus. This hints to a combination of sequence variation and epigenetic regulation in the transcriptional control of 5S rDNA loci. While the polymorphisms in the RNA-seq dataset did not allow us to unequivocally assign the different reads to a specific 5S rDNA locus, the prevalence of the different SNPs nevertheless indicates the expression of distinct sets of genes in different ecotypes, similar to the variation in 45S rDNA cluster-usage  (31).
Consistent with our linkage mapping results, these are the only four founder lines of this population for which we detected, in the NGS sequencing, chromosome 3 specific T-stretch signatures. This demonstrates that these specific signatures are← -------------------------------------------0 (major 5S rRNA genes), 1, 2 and more than 2 polymorphisms (minor 5S rRNA genes) in the transcribed sequence relative to the 5S rRNA consensus sequence. (B) Frequency of single nucleotide polymorphisms (SNPs) along the 120 bp transcribed sequence determined from the Mi-Seq NGS dataset. For the most frequent SNPs, the exchanged nucleotide at the given position is indicated in color. The consensus sequence is indicated below each graph. (C) (Top) Linkage mapping of the abundance of the G to A single nucleotide polymorphism at position 99 estimated by NGS in 393 individuals of the MAGIC population.
ACKNOWLEDGEMENTS We are grateful to  J-P Pichon  ( Biogemma ) for valuable advice in library preparation and for performing the highthroughput sequencing of Col-0 DNA. We thank  C. Poncet  ( GENTYANE sequencing facility ) for advice and help with DNA shearing using the Covaris technology and  P. Vera  for having kindly donated ago4-2 seeds. We thank  P. Arnaud ,  M. Benhamed ,  Y. Bidet ,  F. Choulet ,  F. Pontvianne ,  J. Saez-Vasquez ,  S. Tutois  and in particular  S. Tourmente  for insightful discussions.
FUNDING  Region Auvergne ;  Agence National de Recherche ['Dynam' Het '  ANR-11 JSV2 009 01 , ' SINUDYN '  ANR-12 ISV6 0001  to AVP]; European Union's  Horizon 2020 research and innovation program  [ Marie Sklodowska-Curie  grant agreement no. 752846  to FAR];  Centre National de la Recherche Scientifique , the  Institut National de la Santé et de la Recherche Médicale  and the  University Clermont Auvergne. Funding for open access charge:  Agence National de Recherche  [ ANR-12 ISV6 0001 ].
DATA AVAILABILITY The bioinformatic pipelines to extract specific T-stretch signatures is available on (https://gist. github. com/ laurianesimon/0ae2dd7b8c34c23cdacec217aeaab79c) and (https://gist. github. com/laurianesimon/ a9fc44aa83305c576e914710cae75f87). The Col-0 DNA Mi-Seq data, the 5S-210 RNA-Seq data, the 5S-120 RNA-Seq data as well as the sequencing data from the six YACs have been deposited under PRJNA369183, PRJNA369190, PRJNA378941 and PR-JNA378941 respectively.
Quantitative PCR Quantitative PCR was used to produce an unbiased measure of the quantity of the various microbial taxa in our sample, following a previously established protocol  [14]. Twenty microliters qPCR reactions were carried out on a LightCycler ® 480 II (Roche Diagnostic, Switzerland) with LightCycler 480 SYBR Green I Master (Roche Diagnostic, Switzerland) and specific primers as indicated in Additional file 1: Table  S1. Each reaction consisted of 10 μl of LightCycler 480 SYBR Green I Master (Roche Diagnostic, Switzerland), 0. 8 µl of each primer (0. 4 µM), 6. 4 µl of water and 2 µl of DNA. All samples were analysed in duplicate. For each symbiont, one non-template control (NTC) was used to check the PCR performance. The following LightCycler experiment was used: denaturation program (95 °C for 5 min), followed by 45 cycles of (94 °C for 10 s, 60 °C for 30 s, 72 °C for 20 s with a single fluorescence measurement), and finally a cooling step to 40 °C.
Melting curve analysis was conducted to confirm the purity of the qPCR products for each targeted symbiont, at a constant temperature increase (60-95 °C), recording fluorescence every 10 s. To determine the crossing point (CP) for each sample (that is, the point at which the fluorescence rises appreciably above the background fluorescence), a fit point method was applied using the LightCycler software 1. 5 (Roche Diagnostic). Data analyses were performed using LightCycler 480 software (Roche Diagnostic, Switzerland). Relative quantity of bacterial gene copy per aphid gene copy was calculated using mathematical delta-delta method  [15]. The mean of the two technical replicates per symbiont was used to measure the relative quantity.
Results and discussion In the present study, we compared the performance, with respect to microbial community profiling, of two commonly used broad range 16S rDNA primer pairs with 16S rDNA gene capture approach. Table  1  provides a summary of the number of reads per experiment. We first evaluated the suitability of the two strategies to qualitatively describe the composition of this low-complexity insect microbiota. After quality assessment, amplicons and targeted capture reads were aligned to SILVA SSU reference alignment (see Additional file 2 for further details on sequence data processing). In order to accurately compare the different methods, the first step was to retrieve reads overlapping with the hypervariable V4 region of the 16S rDNA gene for defining Operational Taxonomic Units (OTUs) at a 97% sequence identity threshold.