dataesr/scientific-paragraphs-categorization huggingface dataset:
DNA sequencing and Sanger comparisons We generated ONT MinION sequences for 431 CZEUM cultures (Table  S4 ). To compare Sanger sequencing products with our ONT sequencing products, we sampled GenBank submissions generated from 136 cultures that are now in the CZEUM (Table  S3 ). The 18S rDNA ONT sequences were 99. 79% similar to 64 Sanger sequences, with a range of 97. 51-100% similarity. The 28S rDNA ONT sequences were 99. 83% similar to 131 Sanger sequences, with a range of 98. 33-100% similarity. The ITS rDNA ONT sequences were 99. 37% similar to 44 Sanger sequences, with a range of 90. 39-100% similarity. Differences between sequences were most commonly observed in single nucleotide repeats, or poorly edited primer sites and unresolved polymorphisms in the Sanger sequence.
CZEUM database The CZEUM contains 1045 publicly available cultures, with 752 proven viable. The collection represents at least 85 genera in 10 orders across the Chytridiomyceta and Blastocladiomycota. The CZEUM database is searchable online (czeum. herb. lsa. umich. edu), and for most cultures it contains information on estimated (by the collections' previous holders) or documented taxonomic assignments, many of which were putatively determined based on the comprehensive phylogeny  (Figs. 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 and 13). Also included for most cultures are recommended growth media and metadata, such as isolator of culture, locality of sample, and ex-type recognition. Further improvements on data collection, such as isolator's notes, sequence data, and DNA extract  Ordinal and generic rank based on molecular phylogenetics and isolators' notes.
Management and standard operating procedures of the CZEUM The CZEUM is registered in the World Directory of Collections of Cultures and Microorganisms (WDCM). The CZEUM is managed under the auspices of the   For Figs. 3, 4, 5, 6, 7, 8, 9, 10, 11, 12  and 13: Branches with ≥50% ML bootstrap support in bold; cultures available in the CZEUM in blue, unavailable cultures in red; G = published GenBank sequences, O = ONT sequences generated in this study, T = ex-type culture; "//" on branches indicate length reduced by half, "///" reduced to a third of full length, "////" reduced to a quarter of full length University of Michigan Herbarium. Oversight of the collection is provided by the fungal curator with advice from an external advisory board consisting of four scientists. Figure  2  outlines the current practices for handling culture acquisition and requests.
Acknowledgements Drs. Peter Letcher ,  Martha J. Powell , and  Joyce E. Longcore  thank their students and collaborators for their help, without which this and hundreds of previous projects would not have been impossible. We thank  Kevin McClusky  of the  Fungal Genetics Stock Center  for contributing the Allomyces collection of  L. Olsen. We thank  Brandon Hassett  at the  Arctic University of Norway ,  Kensuke Seto  at the  Yokohama National University , and  Jamie Voyles  at the  University of Nevada  for accessioning new cultures into the CZEUM. We thank  Kevin Chang  for technical assistance. We thank the additional culture contributors to the CZEUM, and our past and future CZEUM users that are advocates for the utility of the collection.
ACKNOWLEDGMENTS We thank  X. Morin ,  G. Le Dre  ´au, and  G. Orieux  for scientific discussions and comments on the manuscript;  X. Nicol  for the Kras sequence;  J. -M. Matter  for the Atoh7 promoter;  C. Marcelle  for the NICD-expressing plasmid; and all members of the  Livet lab  for assistance. We thank  L. Riancho  and  P. -H. Comme  `re from the  Saint-Antoine and Institut Pasteur cytometry facilities  and  A. Potey ,  C. Condroyer ,  S. Fouquet , and the  Institut de la Vision core facilities. This work was funded by fellowships from the  Uehara Memorial Foundation  and  Naito Foundation  to T. K. , the  French Ministry of Research  (F. M. and C. V. ),  Fondation pour la Recherche Medicale  ( DBI20141231328 ), the  European Research Council  ( ERC-CoG 649117 ), and  Agence Nationale de la Recherche  under contracts  ANR-10-LABX-65  ( Labex Lifesenses ),  ANR-18-IAHU-0001  ( IHU FORe-SIGHT ),  ANR-10-LABX-73-01 ,  ANR-15-CE13-0010 ,  ANR-19-CE11-0005 , and  ANR-19-CE16-0019.
The PCR products were analyzed by gel electrophoresis, cloned and sequenced to verify specificity of amplified sequence, and primer efficiency was determined. Gene expression was normalized to Sdha  [43]. For ddPCR, cDNA samples were diluted with RNAse-free water 1:10 to 1:1000 for expression analysis. ddPCR was performed using a BioRad QX100 system. A two-step thermocycling protocol [95˚C, 10 min; 40× (94˚C, 30 s, 60˚C, 60 s); 98˚C, 10 min; ramp rate set at 2. 5˚C/s] was carried out in a BioRad C1000 Touch thermal cycler. Analysis of the ddPCR data was performed with QuantaSoft analysis software (BioRad). ddPCR data were normalized to Tbp  [43]. RT-PCR analyses were performed on at least three independent biological samples. For each gene, data sets were analyzed for statistically significant differences between XX and XY expression levels using a two-tailed, unpaired t-test with confidence intervals set at 95%.
Exome sequencing, comparative genomic hybridization (CGH) and qPCR An array-CGH 244K (Agilent) was performed using the manufacturer's recommended protocols without modifications. Exome capture was performed using the SureSelect Human All Exon v3 kit (Agilent Inc). Sequencing was carried out on an Illumina HiSeq 2000 instrument. Fastq files were obtained using the Illumina CASAVA v1. 8. 1 software and processed using our "in house" bioinformatic pipeline running on the Vital-IT Center for high-performance computing of the Swiss Institute of Bioinformatics (SIB; http://www. vital-it. ch) as described in  [46]. Results did not reveal obvious pathogenic variants. The detected deletion was confirmed by quantitative PCR on genomic DNA using the primers listed in S1 Table.
Western blot analysis Purified proteins were quantified by Bradford's method. 5μg of each protein sample were subjected to 15% SDS-PAGE electrophoresis and transferred to a 0. 45μm PVDF membrane. Membranes were probed with a 1:500 dilution of a monoclonal antibody (M06) against amino acids 424-508 of human HMGCS2 (Abnova, Taipei City, Taiwan) and a 1:1000 dilution of a secondary anti-mouse antibody. The blots were developed with the Immobilon Western Chemiluminescent HRP Substrate (Millipore) kit. The images obtained were processed using Adobe Photoshop 5. 0. The relative amounts of mutated compared with wildtype (assigned 100%) HMGCS2 protein were determined using the software "Image Studio Lite Analysis Software for Western Blots".
In silico analyses For evolutionary sequence comparisons the following NCBI (https://www. ncbi. nlm. nih. gov) reference proteins were used: Homo sapiens HMGCS2 (NP_005509. 1), Mus musculus HMGCS2 (NP_032282. 2), Bos taurus HMGCS2 (NP_001039348. 1), Homo sapiens HMGCS1 (NP_001091742. 1), Mus musculus HMGCS1 (NP_666054. 2), Bos taurus HMGCS1 (NP_001193507. 1), Danio rerio HMGCS (NP_957379. 2), Drosophila melanogaster HMGCS (NP_524711. 1), and Arabidopsis thaliana HMGCS (NP_192919. 1). The reference proteins were aligned with the online program Clustal Omega (https://www. ebi. ac. uk/Tools/msa/ clustalo/). To predict the effect of the substitution p. R501P on HMGCS2 protein function the following in silico algorithms were used: PolyPhen-2 (http://genetics. bwh. harvard. edu/pph2/) [47] , SIFT (http://sift.
5 dpc shows loss of HMGCS2 protein in the knockout. Scale bar, 100 μm. All images of fetal gonad sections are oriented so that the anterior pole is at the top and the mesonephros is on the left of the gonad. Asterisks mark liver. (C) Quantitative ddRT-PCR for Hmgcs2 mRNA in 14. 5 dpc testes (blue bars) and ovaries (pink bars) from wildtype (WT) and Hmgcs2-null (Δ647 KO) mice demonstrated absence of Hmgcs2 exon 2 in the knockout. ddRT-PCR data were obtained from at least three independent samples. Error bars represent SEM. https://doi. org/10. 1371/journal. pone. 0227411. g002 sections of XX and XY wildtype controls (Fig  4A, 4B  and 4D ; WT) as well as XY compound mutant Fgfr2c -/+ :Hmgcs2 -/-(Fig  4C  and 4E ; sensitized KO) at 13. 5 and 15. 5 dpc demonstrated that mice heterozygous for Fgfr2c and homozygous null for Hmgcs2 developed testes that appeared normal compared to the wildtype control, with testis cords throughout at 13.
ddRT-PCR data were obtained from at least three independent samples. Error bars represent SEM. https://doi. org/10. 1371/journal. pone. 0227411. g003 predicted to result in a major amino acid change from arginine to proline (Grantham score: 103). All of the in silico protein predictions deemed the change to be pathogenic (PolyPhen, Mutation taster and SIFT). Although the variant is present in gnomAD; it is extremely rare (reported in 0. 0012%, 0 homozygotes), however its slightly more prevalent in the "Other East Asian" population (frequency: 0. 011%, 0 homozygotes). It should be noted that our patient is from a South Asian origin. We could not establish whether the variant was de novo as the parents were not available for analysis. There is also a ClinVar entry which describes the variant seen in our patient and concludes that it is a variant of uncertain significance.
This work was supported by an  Australian Research Council   Future Fellowship  [FT110100327] and an  Australian Research Council   discovery grant  [ DP170100045 ] to DW, a  National Health & Medical Research Council program  grant [ APP1074258 ] to AS, as well as partly funded by  Riset Unggulan Univeritas Diponegoro  [PNBP no  316-01/UN7. 5. 1/PG/2015 ] to SF, the  Swiss National Science Foundation  [joint research project  SCOPES IZ73Z0_152347/1 ] to SN and JJ and the  Diputacion General de Aragon [Grupo   B32_17R ] and  European Social Fund [FEDER ] to BP and JP. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Methods Plant material. The Nordic Genetic Resource Center, the National Small Grains Collection (US Department of Agriculture), and the IPK gene bank were inquired to access 'compositum-barley' mutants (Supplementary Data 3). Bowman NIL carrying the com1. a allele ((i. e. , BW-NIL(com1. a); syn. BW189 or CIho 11333)), its two-rowed progenitor Foma and Wt barley cv. Bowman were used for phenotypic descriptions, whole-genome shotgun sequencing (WGS) (see below, "Marker development") as well as SEM analysis. Plant material used to generate mapping populations is reported in the corresponding section for genetic mapping. For haplotype analysis, a core collection including of 146 diverse barley landraces and 90 diverse wild barleys were sequenced  28, 29. Plant phenotyping in barley. For phenotyping, the mapping population, BW-NIL (com1.
a), Bowman and the corresponding segregating populations (F 2 and F 3 ) were grown side-by-side under greenhouse conditions at the IPK. For a plant to be assigned as a branched spike mutant, spike shape in all tillers was visually inspected for presence of at least one extra spikelet at any rachis node. Grain-related characters, such as weight, number, etc. were also measured at harvest for the two parental lines of the mapping population. In case of phenotyping of the barley TILLING population (see below-TILLING analysis in barley and Supplementary Data 3), other induced mutants (Supplementary Data 3) as well as the BW-NIL (com1. a) / BW-NIL(com2. g) double mutants (see below, "Double-mutant analysis"), visual phenotyping for variation in palea structure was also applied in addition to the aforementioned phenotyping approach used for spike-branching in F 2 and F 3 progenies.
Genetic mapping and map-based cloning of com1. a. com1. a was initially proposed to be located in chromosome 5HL with unknown genetic position  12. A barley F 2 mapping population was developed by crossing Bowman NIL, i. e. , BW-NIL(com1. a), and barley cv. Bowman. For initial mapping 180 individuals were analyzed and genotyped using the aforementioned NGS based markers. The pattern of segregation between mutant and Wt F 2 plants fitted a 3:1 ratio typical for a monogenic recessive gene. Linkage analysis of segregation data was carried out using the maximum likelihood algorithm of Joinmap 4. 0. Kosambi mapping function was used to convert recombination fractions into map distances. The linkage mapping was further followed by a high-resolution genetic mapping in which almost 6,000 gametes were screened with the flanking markers NGS045 and NGS049.
For narrowing down the com1. a genetic interval the identified recombinants (a set of 109) were used. From 109, a set 15 F 2 were labeled (Supplementary Table  1  and Supplementary Data 2) to be critical recombinants for precisely defining the com1. a genetic interval. From each of the 15 critical plants, 16 F 3 progenies were evaluated for their phenotypes and marker genotypes at the com1. a candidate gene. (Supplementary Table  1  and Supplementary Data 2). Based on F 2 high-resolution mapping and F 3 genetic analysis described, two tightly linked markers, NGS084 and NGS094, were taken to harvest the available barley genome sequence data (see below, "Sequence information and analysis"). A single BAC contig spanning ~1. 4 Mb of the minimal tiling path (MTP) was identified. Genes in this region were utilized for marker development and further genetic mapping that resulted in the identification of a ~380 kb region deleted in the mutant BW-NIL (com1.
a). The deleted fragment contains a single gene (HORVU5Hr1G061270), i. e. , Allelism test of com1 mutants. Mut. 3906 mutant (Supplementary Data 3) was crossed with BW-NIL(com1. a) to test for allelism. The resultant F 1 plants showed a mutant spike phenotype confirming to be allelic with com1. All alleles showed phenotypic similarities with com1 and mutations in the COM1 gene sequences. Double-mutant analysis. Double mutants (DM) were generated by crossing mutant BW-NIL(com1. a) to BW-NIL(com2. g), followed by selfing of the F 1 progeny. All obtained 183 F 2 plants were subsequently genotyped (Supplementary Data 1). In case of com2. g mutation detection, a primer pair (Com2-Bw_SfiI_FR; Supplementary Data 1) spanning the A300C haplotype (that differentiates the Wt Bowman allele A from com2.
Barke consisting of 10,279 individuals, for which a multidimensional pool of individual DNA samples is available 46 , were screened. A primer combination (Supplementary Data 1) was used to amplify the coding region of the COM1 gene. The amplicon was subjected to standard procedures using the AdvanCE TM TIL-LING kit (advancedanalytical, IA, USA). Amplified products were digested with dsDNA cleavage kit followed by analysis via mutation discovery kit and gel-dsDNA reagent kit. Briefly, a premix was made containing a mismatch detecting CEL1 enzyme, namely dsDNA Cleavage Enzyme/T-Digest Buffer mixed in ratio 1:125. For digestion, two µL of heteroduplexes was used with two µL of the premix at 45°f or 30 min. AdvanCETM FS96 capillary electrophoresis system was used to separate the cleaved products according to manufacturer's guidelines (Advanced Analytical, IA, USA).
To distinguish the real putative mutation from the background products, sizes of two digested products after summing up were expected to give the size of the initial PCR product and only such instances were accepted. Otherwise, the original DNA pool was not considered as containing the putative mutant. All the possible mutations found using the capillary electrophoresis system were further validated by re-sequencing using Sanger sequencing and primers listed in Supplementary Data 1. TILLING analysis in Brachypodium distachyon. Mutation screenings in the TILLING collection of chemically induced (EMS) Brachypodium mutants were performed according to Dalmais et al. 39. Briefly, the method includes TILLING by NGS that consists to sequence 500 bp PCR fragments libraries prepared from 2,600 individual genomic DNA pooled in two dimensions.
To identify induced mutations, a bioinformatic pipeline called Sentinel (https://www. app. asso. fr/; under ID: IDDN. FR. 001. 240004. 000. R. P. 2016. 000. 10000) was used to analyze the data sequences. Prediction of the impact of each mutation (Supplementary Data 3) was made with SIFT 5. 2. 2. software (Sorting Intolerant from Tolerant, https://sift. bii. a-star. edu. sg/) according to the manual guideline. The amplified ORF was also re-sequenced by Sanger sequencing using primers listed in Supplementary Data 1. TILLING analysis in sorghum. A pedigreed sorghum mutant library was established in the inbred line BTx623, which was used to produce the sorghum reference genome. This mutant library consists of 6400 M4 grain pools derived from EMStreated sorghum grains by single seed descent. Whole-genome sequencing of a set of 256 lines uncovered 1.
8 million canonical EMS-induced mutations  39. We searched the sorghum ortholog of the barley COM1 in the aforementioned sequence database to identity plants carrying mutation. To confirm the mutations, the amplified ORF was also re-sequenced by Sanger sequencing using primers listed in Supplementary Data 1. Haplotype and network analysis. Genomic DNA from a core collection including 146 landrace and intermedium-spike barley accessions as well as 90 wild barleys was PCR-amplified using specific primers to amplify full coding sequence of the barley COM1 gene. Amplified fragments were used for direct PCR-sequencing (Sanger method; BigDye Terminator v3. 1 cycle sequencing kit; Applied Biosystems). A capillary-based ABI3730xl sequencing system (Applied Biosystems) at the sequencing facility of IPK was used to separate the fluorescently terminated extension products.
Real-time PCR was performed using QuantiTect SYBR green PCR kit (Qiagen) and the ABI prism 7900HT sequence detection system (Applied Biosystems). Each qRT-PCR comprised at least four technical replicates, and each sample was represented by three biological replicates. The Actin gene-based primers (Supplementary Data 1) were used as the reference sequence. qRT-PCR results were analyzed using SDS2. 2 tool (Applied Biosystems) in which the presence of a unique PCR product was verified by dissociation analysis. Significance values were calculated using Student's t-test (two-tailed). The relevant primer sequences per species are detailed in Supplementary Data 1. Phylogenetic analysis. A comprehensive analysis of TCP proteins in grasses was already available  22, 23. We, therefore, focused only on constructing a detailed phylogeny of the COM1 protein among grasses and the barley TCP genes.
Thus, barley COM1 was then queried against the Ensembl Plants database (https://plants. ensembl. org/index. html) with default parameters to retrieve its orthologs or homologs from other grasses. The same database was also used to extract all barley TCP proteins. In case of COM1, protein and DNA sequence of the paralog and homologous genes from each of the grass species were retrieved. To re-check their homology with barley COM1, the retrieved sequences were blasted back against the barley genome. For phylogenetic analysis, protein sequences were initially aligned using the algorithm implemented in CLC sequence viewer V7. 8. 1 (https://www. qiagenbioinformatics. com). UPGMA tree construction method and the distance measure of Jukes-Cantor were implemented for constructing the phylogenetic tree using sequence viewer.
The bootstrap consensus tree inferred from 1000 replicates was taken to represent the evolutionary relationship of the sequences analyzed. mRNA in situ hybridization. In case of COM1, three separated segments (excluding the TCP domain) each containing 300-360 bp were synthesized (probe 1 and 2, GenScript Biotech, Netherlands) or amplified (probe 3) using cDNAs isolated from immature spikes of cv. Bonus and specific primers (Supplementary Data 1). The resulting products were cloned into pBluescript II KS (+) vector (Stratagene, La Jolla, CA, USA and GenScript Biotech, Netherlands). Linearized clones by HindIII or NotI were used as templates to generate antisense (HindIII) and sense (NotI) probes using T3 or T7 RNA polymerase. In situ hybridization was conducted with a single pool of the three aforementioned probes.
Acknowledgements We thank the  IPK Genebank, Germany , the  Nordic Genetic Resources Center (Nord-Gen), Alnarp, Sweden  and the  US Department of Agriculture-Agricultural Research Service  ( USDA-ARS ), the  National Small Grains Collection, Aberdeen (ID)  for providing the mutants and germplasm for haplotype analysis. The authors would like to thank  Dr. Shun Sakuma  for fruitful discussions and help in conducting mRNA in situ hybridizations. We are thankful to  Anne Fiebig  for help with data submission to ENA,  Julie-Sophie Himpe  and  Andreas Bähring  for graphical image support and  Sandra Driesslein , Jenny.
05 means that a statistically significant relationship between the estimated and actual data is maintained with the independent dataset used for validation. Though the R 2 statistic (square of the correlation coefficient in Fig. 3b ) indicates that the model only explains ~ 58% of the variability of actual erosivity, the time-variability as a whole was well reproduced (Fig. 3b ). The regression parameters a = -55. 4 ± 322. 8 and b = 1. 1 ± 0. 3 indicate that some model overestimation of near-zero erosivity data can occur with the model but the Nash-Sutcliffe efficiency value equal to 0. 6 corroborates that also at the validation stage the uncertainties associated with model estimates are not large. The MAE was equal to 84 MJ mm hm -2 h -1 year -1 -which is ~ 5% of mean erosivity over the period 1981-1993-while KGE was 0.
4a ). The long-term mean value of estimated erosivity data is 1367 ± 319 (SD) MJ mm hm -2 h -1. The application of the Standard Normal Homogeneity Test for the double shift  46  (which is useful for dividing long time-series into shorter periods) suggests discontinuities (change-points) in the annual erosivity time-series at a 99% confidence interval in the years 1839 and 1858. The fingerprint of climate change was also detected with the quantile erosivity data with 30-year return period (red curve), with change points in 1838 and 1861, not dissimilar from those obtained with the erosivity data time-series. Other test statistics  [47] [48] [49] [50] [51] [52]  detected change points in 1873 and 1903 for the erosivity data, or 1876 and 1906 for the quantiles, which merely support the idea of a long transition period going from the final phase of the Little Ice Age (LIA; ~ 1300-1850 CE  53  ) to the most recent warming.
6 , both black and red numbers), because the digital National Agrometeorological Network (https ://tinyu rl. com/h4juz uv) came into operation in 1994. Prior to 1994, only some data were available for the Piedmont Region of Italy (north-western part of the MedCA), with only few sparse stations providing data since 1981. The most accurate dataset, 1994-2015, was used for model calibration, while the least accurate dataset, 1981-1993, was used for model validation (Fig. 5 , red numbers). Numerical and categorical inputs. The reconstruction of annually-resolved rainfall erosivity for the MedCA was based on seasonal precipitation data covering most of Europe (30° W-40° E/30° N-71° N) from 1500-2000 on 0. 5° by 0. 5° grid resolution  92. The GPCC (Global Precipitation Climatology Centre) provides an extension of the seasonal precipitation dataset until 2019 (retrieved from https ://tinyu rl.
Acknowledgements N. D. and G. B. performed this research as an investigator-driven study without financial support. F. C. L. was supported by the  Swedish Research Council (Vetenskapsrådet , grant no. 2018-01272 ), and conducted the work with this article as a  Pro Futura Scientia XIII Fellow  funded by the  Swedish Collegium for Advanced Study through Riksbankens Jubileumsfond. The publication cost was covered by  Stockholm University.