dataesr/scientific-paragraphs-categorization huggingface dataset:
Bacterial Cell Distributions on Roots Overall, the analysis procedure resulted in reliable spatial data of bacterial cells colonizing the rhizoplane in different regions of the roots that matched well with earlier reports on microbial root colonization. The bacterial densities found here were of the same order of magnitude as those quantified manually on soil-grown rice roots  (Schmidt and Eickhorst, 2014). Previous observations of increased bacterial densities at the base of lateral roots (e. g. ,  James et al. , 1994; Faoro et al. , 2017)  were in agreement with additional z-stacks analyzed in this study (Supplementary Figure  S1 ), which supports the notion that lateral root junctions provide entry points for nitrogen-fixing bacteria with a facultative endophytic lifestyle. Although our dataset is limited to a small number of roots, in all observed images, bacterial cell distributions were not homogeneous, i.
We used Matchmaker Exchange (MME)  8  to connect the four international centers, which had each independently identified WASF1 as The American Journal of Human Genetics 103, 144-153, July 5, 2018 145 Because the initial genetic tests were negative, all affected individuals had either exome sequencing or whole-genome sequencing (WGS) performed at their respective centers. Details of the methods used for each affected individual are provided in Table  S1. Genomic coordinates throughout this report refer to GRCh37, and coding sequence and protein coordinates refer to the canonical transcript (Ensembl: ENST00000392589; GenBank: NM_003931. 2). Trio exome sequencing was performed on individual P1 and his parents as part of the Care4Rare Canada research program according to our standard approach as previously described.
9 After filtering for rare variants (with a frequency less than 0. 1% in gnomAD and present fewer than six times in our in-house controls), all variants in known disease-related genes were assessed, but no variants that could explain this individual's phenotype were identified. In the search for potential novel genes, possible biallelic or X-linked recessive variants were examined, but there were no rare homozygous or hemizygous variants. Compound-heterozygous variants were identified in CROCC (MIM: 615776), but this gene was ruled out as a likely candidate because it has many loss-of-function variants in control databases (Table  S2 ). Finally, de novo variants in WASF1, ATP5J (MIM: 603152), SLC38A4 (MIM: 608065), and ZNF175 (MIM: 601139) were identified (Table  S2 ). Assessment of protein localization patterns and function and in silico mutation predictions determined that ATP5J, SLC38A4, and ZNF175 were unlikely to be responsible for this condition (refer to Table  S2  for further details).
(C) Western blot analysis using an antibody with an epitope in the N-terminal region of WASF1 showed the presence of the full-length and truncated WASF1 in affected fibroblasts. The truncated WASF1 was not present in control fibroblasts. All experiments were performed with fibroblasts derived from three healthy control individuals. Western blots were performed in triplicate, and band intensity was quantified with Image Lab Software (Bio-Rad). Error bars indicate the range of measurement of triplicate samples. (c. 1516C>T [Ensembl: ENST00000392589]). Three of the four individuals have VUSs in other genes in addition to the WASF1 variants. Population-level sequencing initiatives have enabled increased recognition of the prevalence of recurrent benign de novo mutations. 25 Although it is unlikely, the possibility that they contribute to the respective individuals' phenotypes cannot be excluded.
Acknowledgments We thank the four affected individuals involved in this study and their families. This work was supported by the  Cambridge Biomedical Research Centre  and the  National Institute for Health Research (NIHR)  for the  NIHR BioResource  (grant number  RG65966 ). This work was supported by the  Care4Rare Canada Consortium (Enhanced Care for Rare Genetic Diseases in Canada ), which is funded by  Genome Canada , the  Canadian Institutes of Health Research , the  Ontario Genomics Institute , the  Ontario Research Fund ,  Genome Quebec , and the  Children's Hospital of Eastern Ontario Foundation.
Resumo O objetivo deste trabalho foi estimar a contribuição do efeito da idade, do período e da coorte de nascimento na mortalidade por câncer colorretal. Foram analisados dados de óbitos pela neoplasia entre indivíduos com mais de 35 anos de idade do Estado do Rio de Janeiro, Brasil, extraídos do Sistema de Informações sobre Mortalidade (SIM) entre 1980 e 2014. As taxas de mortalidade foram calculadas por gênero e faixa etária. O efeito da idade, período e coorte de nascimento foi estimado pelo método que utiliza funções estimáveis: desvios, curvaturas e drift, na biblioteca Epi do software R. As taxas de mortalidade por câncer colorretal padronizadas foram 27,37/100 mil homens e 21,83/100 mil mulheres em 2014. Verificou-se aumento da mortalidade pela neoplasia entre 1980 e 2014, sendo as taxas de mortalidade entre homens superiores às das mulheres após a década de 1990.
A contribuição dos efeitos foi avaliada pela comparação da deviance do modelo estimado com o efeito específico em relação ao modelo completo (idade-período-coorte). Mudanças nessa estatística entre dois modelos assume uma distribuição χ 2 com graus de liberdade iguais à diferença do número de parâmetros dos dois modelos  12. Foram considerados estatisticamente significativos os valores de p ≤ 0,05. Para as análises estatísticas foi utilizada a biblioteca Epi 2. 0 (https://CRAN. R-project. org/ package=Epi) no software livre R versão 3. 3. 2 (The R Foundation for Statistical Computing, Viena, Áustria; http://www. r-project. org). Este estudo foi aprovado pelo Comitê de Ética em Pesquisa da Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz (CAAE n o 51697215. 6. 0000. 5240).
Abstract The aim of this study was to estimate the contribution of the effect of age, period, and birth cohort on mortality from colorectal cancer. The study analyzed data on deaths from this cancer in individuals over 35 years of age in Rio de Janeiro State, Brazil, obtained from the Mortality Information System (SIM) from 1980 to 2014. Mortality rates were calculated by gender and age bracket. The effect of age, period, and birth cohort was estimated by the method that uses estimable functions: deviations, curves, and drift in the Epi library of the R software. Standardized mortality rates from colorectal cancer were 27. 37/100,000 men and 21. 83/100,000 women in 2014. The data showed an increase in mortality from this cancer from 1980 to 2014, and mortality rates were higher in men than in women after the 1990s.
Resumen El objetivo de este trabajo fue estimar la contribución del efecto de la edad, del período y de la cohorte de nacimiento en la mortalidad por cáncer colorrectal. Se analizaron datos de óbitos por la neoplasia entre individuos con más de 35 años de edad del estado de Río de Janeiro, Brasil, extraídos del Sistema de Informaciones sobre Mortalidad (SIM) entre 1980 y 2014. Las tasas de mortalidad fueron calculadas por género y franja de edad. El efecto de la edad, período y cohorte de nacimiento fue estimada por el método que utiliza funciones estimables: desvíos, curvaturas y drift, en la biblioteca Epi del software R. Las tasas de mortalidad por cáncer colorrectal estandarizadas fueron 27,37/100 mil hombres y 21,83/100 mil mujeres en 2014. Se verificó un aumento de la mortalidad por la neoplasia entre 1980 y 2014, siendo las tasas de mortalidad entre hombres superiores a las de las mujeres tras la década de 1990.
Proteins of the LEA_3 Family Are Expected to Be Mitochondrial In Arabidopsis, the LEA_3 family comprises four proteins, with three of them (including LEA38) being exclusively mitochondrial, while the fourth (LEA2) is cytosolic  [25]. This suggests that LEA2, which is paralogous to LEA38, could have lost its mitochondrial localization during evolution. To support this hypothesis, we first examined whether mitochondrial localization could possibly be the rule for LEA_3 proteins. The LEA38 sequence was used as a query in a BLASTP search of the NCBI Reference Sequence protein database. With an E-value cut-off of 10, the analysis yielded 390 hits (370 hits with e-value < 0. 01). All the sequences were from higher plants, and a search for PFAM matches confirmed that all these sequences belonged to the PFAM family LEA_3 (PF03242).
This strongly suggests that this protein family is specific to higher plants. The 390 protein sequences were then subjected to subcellular localization prediction using PProwler, which proved to be the more accurate prediction program for LEA proteins  [25]. The program computes probabilities for localization in the secretory pathway, mitochondrion, chloroplast, peroxisome, and others (nucleus, cytoplasmic, or otherwise). The box plot shown in Figure  1  clearly reveals that the mitochondrion is by far the most probable subcellular destination of LEA_3 proteins. Therefore, it is likely that within the LEA38/LEA2 couple of paralogs, LEA38 has retained its mitochondrial localization, while LEA2 has lost it.
4 (cytosolic) but not in LEA2. 5 (mitochondrial). Since the other mutations introduced to redirect LEA2 to mitochondria were localized in the first alpha-helix, helical projections with the Heliquest program were performed to address the structural impact of mutations (Figure  4 ). The projection of residues 7-24 of LEA38 revealed an amphiphilic helix, with two positively charged residues in the hydrophilic face (VAVVL) and a negatively charged residue (Glu) at the border between the hydrophobic and hydrophilic faces. In LEA2, the projection of residues 5-23 did not reveal a clear amphiphilic face, in spite of the grouping of four residues (AGAL). As found for the corresponding helix in LEA38, three charged residues are present but with a different disposition (Figure  4 ). The negatively charged residue (Glu) was located at the opposite end of the AGAL region, and the positively charged residues were facing each other, at 90 • of the Glu.
Comparison of Experimental Data and In Silico Predictions Six online subcellular location prediction programs (iPSORT, MITOPROTII, MitoFates, PProwler, Predotar, and TargetP1. 1) were used to predict the location of LEA2 and LEA38 and related GFP constructs (Table  2 ). Most programs suggested mitochondrial localization (32 out of 42 combinations in Table  2 ) for the seven proteins, although four of these are empirically cytosolic. More of the programs predicted a mitochondrial localization for LEA2, which is cytosolic, than for the Higher amounts of mature LEA38-GFP protein were immunopurified from leaf mitochondria of the overexpressing line, and the N-terminus was determined by Edman microsequencing. The results revealed that cleavage of the presequence occurred at two adjacent sites, after Y28 and A29, and thus upstream of the 11 amino acid segment ( 33 AQGSVSSGGRS), which is specific to LEA38 (see Figure  1 ).
36). This program was the least accurate with this set of proteins since LEA2, LEA38, LEA38-GFP, and LEA2. 5-GFP were predicted as chloroplastic proteins and LEA38del-GFP as a secreted protein. The overall comparison of predictions with experimental localizations, including the series of mutant proteins, confirms that none of the programs are sufficiently accurate to predict the subcellular localisation of polypeptides with confidence (Table  2 ). Three of the programs include the predicted length of pre-sequences in their analysis. As shown in Table  2 , predicted MTS displayed various lengths (28 to 43 amino-acids), with cleavage sites upstream or downstream from the 11 amino acid sequence that is required for correct mitochondrial targeting of LEA38-GFP. The MitoFates program provided the best results with the prediction of the genuine cleavage site of LEA38 (after Y28).
Bioinformatics Sequence alignments were performed with the LALIGN software (http://www. ebi. ac. uk/ Tools/psa/lalign/)  [44] , Clustal Omega software (http://www. ebi. ac. uk/Tools/msa/clustalo/)  [45] , and EMBOSS Needle (https://www. ebi. ac. uk/Tools/psa/emboss_needle/nucleotide. html) [46]. Search for orthologs of LEA38 within the NCBI Reference Sequence protein database was performed with BLASTP 2. 8. 0 (https://blast. ncbi. nlm. nih. gov/Blast. cgi) using BLOSUM62 matrix and default parameters  [47]. The HMMER software (https://www. ebi. ac. uk/Tools/hmmer/) was used to search for Pfam matches  [48]. Subcellular localisations and pre-sequence cleavage site predictions were performed using IPSORT (http://psort. hgc. jp/form. html) [49] , MITOPROT II (http://ihg. gsf. de/ihg/ mitoprot.
html) [50] , TargetP 1. 1 (http://www. cbs. dtu. dk/services/TargetP/) [51] , Predotar (https: //urgi. versailles. inra. fr/predotar/) [52] , PProwler (http://bioinf. scmb. uq. edu. au:8080/pprowler_ webapp_1-2/)  [53] , and MitoFates (http://mitf. cbrc. jp/MitoFates/cgi-bin/top. cgi)  [54]  software with default settings. Molecular weight and theoretical pI were calculated using ProMoST (http: //proteomics. mcw. edu/promost. html) [55]. Secondary structure predictions were performed with Jpred4 (http://www. compbio. dundee. ac. uk/jpred/)  [56]. Alpha-helix projections were obtained with the HeliQuest Web server (http://heliquest. ipmc. cnrs. fr/) [57] , using the Analysis module with default parameters (helix type set to alpha) and a window size set to FULL. Supplementary Materials: Supplementary materials can be found at http://www.
We therefore performed de novo genome sequencing using the PacBio technology for selected Malian strains recently isolated  (2010) (2011) (2012) (2013)  in the Office du Niger rice growing region with the aim of maximizing diversity in terms of virulence profile, genotype of the host of origin and tal haplotype. Hierarchical genome assembly of the PacBio data yielded a complete circular chromosomal sequence for all eight Malian strains with coverage above ∼130× (Table  1 ). Next, to examine the position of these strains in the established phylogeny of X. oryzae, a set of core genome SNPs was obtained using the parsnp module of the Harvest suite for genome multiple alignments  (Treangen et al. , 2014). On average, the core genome amounted to 67% of a genome sequence and a set of 129,898 SNPs could be called from this alignment.
Interestingly, MAI134, the only strain isolated from tissues sampled from the perennial grass O. longistaminata (Table  1 ) branches out earlier and is the most divergent African Xoo in this dataset. The other seven genomes fall in a single group separate from the MAI1 reference and appear to be highly related with a number of polymorphic positions in pairwise comparisons of core SNPs haplotypes between strains of this group ranging only from 1 to 22 (Supplementary Figure  S3 ). Accordingly, multiple genome alignment of the African Xoo sequences performed with Mauve  (Darling et al. , 2010)  revealed a high degree of shared synteny and, with the exception of CFBP1947, as pointed out before  (Tran et al. , 2018) , no major structural rearrangement (Supplementary Figure  S4 ). In conclusion, genomic analysis of the finished genomes obtained from eight Malian isolates confirms that they genetically belong to the African Xoo group and that, with the exception of MAI134, they form a highly related group.
Comparative Analysis of Malian Strains tal Effector Gene Repertoires We then focused on the comparative analysis of tal effector gene repertoires to evaluate the nature and extent of TALE diversity in this set of genomes. To this end, the Malian genomes were searched for tal coding sequences (Supplementary Table  S1 ). As before for strains MAI1, BAI3, and CFBP1947  (Tran et al. , 2018) , each was found to harbor nine tal genes that are highly syntenic (Supplementary Figure  S5 ). These CDS were extracted and classified using the DisTAL module of the QueTAL suite that attempts to reconstruct evolutionary lineages based on the relatedness of the strings of unique repeat units amino acid sequences in the TALEs central region  (Pérez-Quintero et al. , 2015). The neighbor-joining tree obtained using DisTAL distances among African TALEs reproduced in Figure  5A  indicates that TALEs from this new set of genomes belong to one of the nine African TALE groups previously defined by  Tran et al.
(2018). Furthermore, all genomes code for a single member of each group. Thus, the newly sequenced Malian genomes do not reveal any unrelated TALE defining a new African group. However, the analysis of either RVD sequences (Figure  5B ) or unique repeat units strings ('DisTAL sequences') (Supplementary Figure  S6 ) similarity to measure intra-group diversity identified several new variants and yields some insight on tal repertoires variability across strains. As depicted in Figure  5B , when considering RVD sequences, new variants could be identified in our set of genomes in all but two TALE groups. For example, contemporary Malian strains encode a new variant of the TalD and TalG groups that were previously shown to be conserved across MAI1, BAI3, and CFBP1947  (Tran et al. , 2018). Likewise, we found two new variants for the TalI and TalB groups.
Interestingly, Xoo MAI134 is the most divergent genome belonging to the African Xoo group and it clusters separately from the other Malian strains. To our knowledge, it is the first Xoo genome of a strain isolated from a wild rice species, in that case, O. longistaminata. The apparent divergence relative to other Malian genomes could be a consequence of a separate evolutionary path for specialization on this wild host. Sequencing the genome of additional Xoo strains isolated from wild rice would help address this question. Our analysis of the finished Malian Xoo genomes extends previous foundational work on three African Xoo genomes from strains isolated in Cameroon, Burkina Faso, and Mali  (Huguet-Tapia et al. , 2016; Tran et al. , 2018). We further characterized the nature and extent of the diversity of the genomic repertoires of tal effector gene homologs in a larger dataset.
, 2018)  appear to be variable as well. The observed differences within TALE groups encompass repeat amino acid sequence polymorphism outside the RVD, polymorphic RVDs and insertion/deletion events of stretches of repeat units. As the number of tal sequences in databases is dramatically increasing the molecular mechanisms responsible for tal sequence variation are beginning to be deciphered and seem to include both point mutation and recombination between repeats  (Erkes et al. , 2017; Pérez-Quintero, 2017; Tran et al. , 2018). Long-read sequencing has made TALE diversity mining a straightforward task. As this diversity in Xoo populations is being increasingly recognized, new fundamental issues about TALEs biology and evolution are emerging. These questions will also be relevant for rice breeding because they may inform genetic disease resistance design and deployment strategies.
Wilkins et al. (2015)  have observed a conservation of the specificity for confirmed target(s) of a reference Xoc TALE when variants within that group differed by no more than six RVDs. Reminiscent of our findings regarding African Xoo TalB variants, another study reported on several Xoc TALE groups where different variants may have contrasted abilities to induce predicted targets  (Erkes et al. , 2017). In the future, relational databases such as daTALbase  (Pérez-Quintero et al. , 2017) , that integrate massive TALE-centered 'omic' information should facilitate even more comprehensive inquiries, and help explore for example whether 'divergent' variants of a TALE group are predicted to gain the capacity to induce a polymorphic version of the target in another rice genome.
RNA Isolation and qRT-PCR To assess the induction of the OsSWEET14 gene, leaves of 3week-old plants were infiltrated with a needleless syringe with sterilized water or bacterial suspensions at an OD600 adjusted to 0. 5 in water. Segments of inoculated leaf were collected 48 h after inoculation. Samples were ground into powder using the Qiagen Tissue-Lyser system. Total RNA was extracted using Trizol reagent (Invitrogen) following the manufacturer's instructions. After TURBO DNase treatment (Ambion), 1 µg RNA was reverse transcribed into cDNA using SuperScript III (Invitrogen). Realtime PCR was carried on a Lightcycler 480 System (Roche) with primer pairs specific for OsSWEET14, OsTFX1, OsERF#123 or EF-1 alpha (GenBank accession: GQ848072. 1) as described before  (Blanvillain-Baufumé et al.
Statistical Analysis Statistical tests for mean comparisons were performed in R (R Core Team, 2010) using standard functions. The R package nlme  (Pinheiro et al. , 2017)  was used to perform linear mixed-effects modeling of OsSWEET14 expression with log 2transformed qRT-PCR values computed as the response variable. This transformation was necessary to ensure homogeneity. The dataset included one value for each 'strain' and 'rice line' factor combinations obtained from four independent replicates of the whole experiment. The fixed effects of the final model included the variables 'strain' and 'rice line' and their interaction term. The structure of the random component consisted of a random intercept and a random slope for the 'rice line' factor both conditioned on a 'replicate experiment ID' factor.
Genome Sequencing and Assembly The X. oryzae pv. oryzae genome sequences were obtained using the SMRT technology  (Eid et al. , 2009). 20 kb SMRTbell templates libraries were sequenced on a PacBio RS II instrument with the P6-C4 chemistry at the Icahn Institute for Genomics and Multiscale Biology (New York, NY, United States). For each strain, 1-2 SMRT cells were employed to generate sequencing data equivalent to more than 100× genome coverage. Genome assembly was performed with version 3 of the HGAP pipeline  (Rank et al. , 2013)  using default parameters. Circularization of the HGAP contigs was performed with Circlator  (Hunt et al. , 2015). In some instances (MAI134, MAI95), it was necessary to iteratively trim the ends of the initial HGAP contig by 2 kb increments until Circlator successfully circularize the sequence.
For strain MAI99, circularization was achieved with the minimus2 pipeline 1. The absence of obvious structural anomaly was manually verified by inspecting the coverage plot of mapped reads on the SMRT View browser. Genome sequence finishing included several rounds of Quiver polishing (RS_Resequencing protocol) until the count of variant ceased to decrease in additional polishing rounds. Polished sequenced were submitted to GenBank under the accession numbers indicated in Table  1  and automatically annotated with the NCBI Prokaryotic Genome Annotation Pipeline. The displayed multiple-whole genome alignment was generated with progressiveMauve and visualized using Mauve 2. 4. 0  (Darling et al. , 2010).
Phylogenetic Analysis In addition to the Malian genome sequences determined in this study, the following reference genomes (with GB accession or Bioproject ID) where obtained from GenBank: Xoo MAI1 (PRJNA427174), Xoo CFBP1947 (NZ_CP013666), Xoo, BAI3 (PRJNA427174), Xoo NAI8 (NZ_AYSX01000001. 1), Xoo PXO99A (NC_010717. 2), Xoo PXO86 (NZ_CP007166. 1), Xoo KACC10331 (AE013598. 1), Xoc BLS256 (NC_017267. 2), Xoc RS105 (NZ_CP011961. 1), Xoc CFBP7341 (NZ_CP011959. 1), Xoc CFBP7342 (NZ_CP007221. 1), X. campestris NCPPB4346 (NZ_LHUK01000001. 1), X. oryzae X11-5A (LHUJ01000001. 1). The core genome SNPs matrix for strains under analysis was generated with the aligner module parsnp of the Harvest suite v1. 1. 2 (Treangen et al. , 2014)  enabling the -x flag to filter out SNPs in regions of recombination.