dataesr/scientific-paragraphs-categorization huggingface dataset:
Both Hdh +/+ and Hdh ex4-5 were analysed for karyotypic abnormalities (Q-banding) and they showed several common  [36]  chromosomal alterations at the cell population level (the most frequent were duplications of chromosomes 1, 8, 11, and 14). HTT knock-out gRNA2p and gRNA5i (supplementary dataset S23), respectively annealing 250 bp upstream and 430 bp downstream HTT exon1, were used to drive its precise deletion in E14 +/+ mES cells  [37]. Alt-R® CRISPR-Cas9 tracrRNA (IDT) and the two designed Alt-R® CRISPR-Cas9 crRNAs were separately assembled in vitro and added to the Alt-R® S. p. Cas9 nuclease (IDT) following manufacturer's instruction. A mix containing 1. 8 pmol of each ribonucleoprotein (RNP) complex was introduced by reverse lipofection in 320,000 E14 +/+ mES cells using Lipofectamine® RNAiMAX (Thermo Fisher).
Clones were isolated and screened by PCR for the presence of the small expected knock-out band with oligos crHTTexon1kofw and crHTTexon1korev (supplementary dataset S23). Three primers-based PCR assay enabled to better discriminate between homozygous and heterozygous clones (Fig. S7A , B and Supplementary dataset S23). Two validated clones for each genotype were exposed to neural rosette assay.
HTT knock-in Two gRNAs cutting 1. 5 kb upstream (Cas9 HAL) and 2 kb downstream (Cas9 HAR) HTT exon1 were used to integrate the RMCE cassette by homologous-directed recombination (HDR) (supplementary dataset S23). Two million E14 +/+ mES cells were nucleofected using Amaxa TM mES nucleofector kit (Lonza) with a mix containing 20 pmol of each in vitro assembled RNP complex, 10 μl nucleofector enhancer (IDT) and 1 μg RMCE-Htt-PuroTK donor cassette (synthetized by GenScript and cloned in pUC57). The HDR donor vector contained 1 kb homology arms and the RMCE cassette, that comprises the FRT and F3 sites specific for the Flp recombinase and the positive/negative selectable marker PuroRΔTK under the human PGK promoter (supplementary dataset S23). Cells were seeded 35,000 cells/cm 2 and grown in presence of 1 μM SCR7 ligase IV inhibitor for 24 h after nucleofection to promote repair by HDR.
Clones resistant to 2 μg/ml puromycin were isolated and screened by PCR for the integration of the RMCE cassette without random insertion of the donor vector at first and subsequently for genotyping the second allele (primer pairs used listed in supplementary dataset S23). We selected one RMCE/-clone in which we integrated by Flp-mediated recombination 0Q, 2Q, 4Q, 7Q, 10Q, 13Q, and 17Q RMCE constructs (synthetized by GenScript and cloned in pUC57 vector) to reconstitute the whole genomic portion removed by the PuroRΔTK RMCE cassette. To this aim, 2 million RMCE/-cells were nucleofected using Amaxa TM mES nucleofector kit (Lonza) with 4 μg RMCE donor construct (either 0Q, 2Q, 4Q, 7Q, 10Q, 13Q, or 17Q) and 4 μg pCAG-Flpe:GFP (Addgene, plasmid #13788). Cells were seeded at low density (4-8000 cells/cm 2 ) and exposed to 1 μM ganciclovir selection 72 h after nucleofection.
Clone validation Sequencing of HTT locus. PCR products from HTT locus were purified using QIAquick PCR-purification Kit (QIAGEN) and Sanger sequenced (GATC-Eurofins). HTT expression. RNA was isolated from clones of interest with TRIzol reagent according to the manufacture's instruction (Life Technologies) and reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad). The presence of HTT mRNA was evaluated using primers amplifying exon 3-6 cDNA (supplementary dataset S23) and HTT expression was checked by western blot analysis using D7F7 antibodies (Cell Signaling Technology).
Rosette and neuron quantification Rosette quantification. In the E14 cell differentiation experiments, the rosette lumen areas were quantified on day 8-9 of neural differentiation after staining for NESTIN and PALS1. CellProfiler software was used to automatically quantify rosette lumens (PALS1 positive areas). In the R1 cell differentiation experiments, rosettes were quantified on day 7 of neural differentiation after staining for NESTIN and ZO1. For the measurement of the % of NESTIN+ cells inside rosettes a previously established protocol was applied  [18]. For rosette and lumen size, the contour of each rosette (as highlighted by marker NESTIN) and lumen (as highlighted by marker ZO1) was outlined using ImageJ software and two lists of regions of interest (ROIs) were measured to calculate rosette mean areas and lumen mean areas, respectively.
Neuron quantification. In the E14 cell terminal differentiation experiments, the neurons were analysed on day28 of neural differentiation after staining for MAP2, TUBB3, P27, and NEUN. CellProfiler software was used to automatically quantify MAP2 and TUBB3 positive areas as well as P27 and NEUN positive cells. The relative number of P27 and NEUN positive cells was calculated as a percentage of total Hoechst positive cells.
RNA extraction (for real-time qPCR or RNA-seq analyses) RNA was isolated using TRIzol reagent according to the manufacture's instruction (Life Technologies). RNA was quantified with Nanodrop and then the integrity was evaluated. Potential contaminating DNA was removed by DNA-free kit (Ambion). RNA was reverse transcribed using iScript cDNA Synthesis Kit (Bio-Rad). Real-time qPCR qPCR was performed using the CFX96 Real-Time System (Bio-Rad). All reactions were performed in 15 μl containing 50 ng (or 100 ng for SHH and PLAGL1) cDNA and SsoFast EVAGreen Supermix (Bio-Rad). Primer pairs used were listed in supplementary dataset S23.
98, with gene annotation GENCODE M25) using STAR v2. 5. 2b  [40]  with default parameters. RNA-seq data processing. Differential expression analysis was performed with DESeq2  [41]. To take into account experimental batches, replicates were added as additional variables and included into the design formula. At the rosette and neuronal stages all the possible pairwise comparisons were performed (0Q vs. 2Q, 0Q vs. 4Q, 0Q vs. 7Q, 2Q vs. 4Q, 2Q vs. 7Q, and 4Q vs. 7Q). Genes were considered differentially expressed if the adjusted p-value (Benjamini Hochberg) was lower than 0. 05 and the absolute log2 fold change was higher than 1. Genes with low base mean [<1 CPM (counts per million)] were not considered in the analysis. Functional analysis. Enrichment analysis for Gene Ontology (GO) terms was performed using TopGO  [42] , focusing on the "Biological Process" category.
GO terms with Fisher test corrected p-values <0. 05 were considered as significant. The GOplot package  [43]  was used to generate circular plot and compute z-scores (number of upregulated genes minus the number of downregulated genes divided by the square root of the count). "Jaccard similarity" index. The analysis was performed by comparing the top 100 Differentially Expressed Genes (DEGs) between rosettes (early stage) and neurons (terminal stage) of 0Q, 2Q, 4Q, and 7Q neuronal cultures with the top 100 unique DEGs from bulk RNA-seq data of human fetal cortical (CTX), striatal (Lateral Ganglionic Eminence, LGE) and pallidal (Medial Ganglionic Eminence, MGE) tissues  [44].
RESULTS The HTT polyQ tract is under purifying natural selection We started by investigating whether long-term patterns of conservation and change for HTT CAG repeats have been subjected to selective pressures. To this aim, we assembled a Multiple Sequence Alignment (MSA) of HTT exon1 sequences from more than 200 chordate species-108 de novo sequenced orthologs and 101 sequences retrieved from online databases or published studies (Supplementary datasets S1 and S2). Our MSA displays variation in the length of the HTT polyQ tract across chordate groups (Fig. S1 ). To understand whether selective pressures contributed to these patterns, we measured first the ratio of nonsynonymous to synonymous substitutions (dN/dS ratio) for each position of this locus. A low rate of between-species nonsynonymous substitution-that is a nucleotide mutation that alters the amino acid sequence of a protein-reflects the action of purifying selection within species to eliminate mildly deleterious mutations and preserve the tract intact.
In our analyses we estimated the substitution occurrences for 163 non-redundant (unique) highly confident exon1 sequences (Supplementary dataset S3). Importantly, we found that only two of the 291 inferred non-synonymous substitutions within the exon1 locus fall within the polyQ tract (Fig. 1A ). Second, for a more rigorous conservation/selective pressure analysis on the polyQ tract, we quantified the dN/dS ratio. When there are substantial variations in CAG repeat length between species-driven by repeat expansion/contraction events-the region could not be reliably aligned because the Nth CAG (or Q) in one species could not be orthologous to the Nth CAG repeat in a different species. Being aware of this possible limitation, we assessed dN/dS ratio on non-mammalian sequences with stable 4Q repeats (n = 84 species) (Supplementary dataset S4)-as the absence of indels allows confident alignment across their entire length.
1C , S2B, D and Supplementary dataset S5). Furthermore, possible evolutionary scenarios (negative, neutral, and positive selection) were evaluated by FUBAR method on the HTT exon1 as a whole (Fig. S3 ). The distribution of substitution rates probability in Fig. S3A , B displayed that the higher (red) probability for HTT exon1 fell exclusively into the negative selection area (Fig. S3A, B ) indicating that HTT exon1, as a whole, is under purifying selection. This is the first time a wide set of orthologs has been taken into consideration to represent aspects of HTT's unique evolutionary history, among the polyQ-containing proteins under selective pressures  [45] , and to demonstrate that HTT exon 1 as a whole and its polyQ tract underwent purifying selection. The HTT polyQ tract has been subjected to the strongest selective pressures throughout evolution compared to other polyQ-containing genes In order to investigate whether similar selective pressures might also act on the other polyQ, we tested the polyQ stretch of Ataxin-3 (ATXN3) which is associated with the second most common polyQ disease, Spinocerebellar ataxia type 3 (SCA3)  [46].
To this end, we generated an alignment of the ATXN3 polyQ locus from 53 taxa for which both ATXN3 and HTT sequences were available, thus sharing phylogenetic relationships and timescales (Supplementary datasets S6-8). Figure  S4A, B  show, for the same taxa, the distribution of substitutions around the polyQ region of ATXN3 and HTT, respectively. While 53 synonymous and 43 nonsynonymous substitutions were found in the ATXN3 polyQ stretch, also in this sample only 21 synonymous substitutions were observed in the HTT polyQ stretch. FUBAR identified that 12. 5%, for ATXN3, and 44. 4%, for HTT, of Qs were under significant purifying selection (Fig S4C  , D ). This suggests that the HTT polyQ tract is under stricter selective pressures compared to the ATXN3 polyQ locus. We then performed selective pressure analysis on the polyQ tract of the other seven brain disease-related proteins  [47] , and of two proteins not-associated with any disease (POU6F2 and ZNF384) (Fig.
1D  and S5 and Supplementary datasets S9-17). Comparative SLAC analysis revealed that the HTT polyQ tract is the first in terms of low presence of synonymous and nonsynonymous substitutions (Fig. 1D , and S4A, B and S5A). The analysis also revealed that this tract has one of the highest percentages of Q residues under significant purifying selection, ranking third after POU6F2 and TBP (Fig. 1D  and S4C, D and S5B). Recent findings showed that HD pathogenesis is influenced by the size of the uninterrupted CAG repeat sequence  [6]. In particular, it is known that the stretch of CAG in the human HTT gene is interrupted by a penultimate CAA codon. Studies from the last few years have demonstrated that the loss of this interruption, or the duplication of the ultimate CAA-CAG codons, are associated with an earlier or later-respectively-age of disease onset  [6, 7] , suggesting CAG purity is a causal driver of CAG somatic instability in HD  [6, 7].
We therefore decided to explore mammalian genomes to compare HTT CAG purity and length with those of other genes encoding polyQ-containing proteins. We retrieved from the Ensembl database 248 sets of mammalian protein orthologs, containing at least one tract of four or more consecutive Qs for which length variability among mammalian species is observed, and collectively obtained 367 polyQ tracts because some proteins bear multiple polyQ tracts (Fig. S6A ). For each individual polyQ tract, we calculated the z-scores (see methods) for (i) length of polyQ (LQ), (ii) longest uninterrupted CAG repeat (LNI), and (iii) polyQ tract "purity" (proportion of CAG/ CAA codons) with respect to orthologous sequences. We found that the human HTT polyQ tract behaved as an outlier both in terms of LQ (Fig. S6B  and Supplementary dataset S18) and LNI (Fig.
S6C  and Supplementary dataset S18), as shown by its position in the right-most end tail of the distributions. The human HTT polyQ tract also displays an exceptionally low presence of CAA "impurity" compared to polyQ stretches of other proteins (Fig. S6D  and Supplementary dataset S18). Indeed, human HTT displays the highest length and purity of the CAG tract compared to orthologs of known polyCAG/CAA disease-associated genes (Fig. 1E ), such as ATXN3 (as also expected from the previous polyQ conservation analysis; Fig. S4A, C ). These results indicate that strong purifying selection acts on the CAG/CAA repeat region of the HTT gene to maintain its capacity to encode glutamine residues. Our data also indicates that the human HTT polyQ encoding tract stands out for its length and purity of CAG codons with respect to other polyQ tracts in mammals.
In conclusion, this level of conservation and purity in the HTT polyQ could have paved the way for its evolutionary expansion  [7, [48] [49] [50]. The structure of a de novo identified HTT pseudogene confirms that purifying selection acts on the CAG repeat region In our sequencing effort, we also serendipitously identified a processed HTT pseudogene (pHTT) in the marmoset Callithrix jacchus, which had escaped previous identification  [51] , and whose sequence allows the description of the mutational dynamics of this DNA sequence in the absence of selective constraints. Callithrix jacchus pHTT consists of the first nine HTT exons and lays within the third intron of the CNTNAP3 gene (Fig. 2A, B  and Supplementary dataset S19). Three point-mutations (one non-synonymous) and several indels, including a frameshift inducing insertion, were observed between the CAG tract of Callithrix jacchus pHTT and HTT (Fig.
2C ). Numerous indels were also observed between the proline-rich domain (PRD) of the Callithrix jacchus pHTT and other primate HTT sequences (Fig. 2D ). These observations likely reflect the absence of purifying selection acting on the pseudogene sequence and hint at the underlying mutability of sequences encoding the PRD. Interestingly, pHTT exon1 in Callithrix jacchus is far more prone to point substitutions than the rest of the pseudogene exons, consistent with studies indicating that point substitution rates are higher around indel sites  [52]  (Fig. 2E  and Supplementary dataset S20) and further attesting to the purifying selection acting on HTT exon1. The length and purity of the polyQ tract affects HTT neuronal function Since long polyQ tracts are enriched in genes with neuronal functions  [53] , and since HTT is implicated in neurogenesis  [18, 54] , we looked for evidence of polyQ activity itself in in vitro neural cell assays.
5A  and S12 ), with a specific focus between 0Q and 7Q lines. We detected differentially expressed genes (DEGs) between 0Q and 7Q genotypes at both rosette and neuron stages, with a higher number of DEGs in the latter (Fig. 5B, C ). A total of 41 DEGs in 0Q versus 7Q rosettes are enriched in GO terms related to neuro-development (Fig. 5B, D, E  and Supplementary dataset S21). Among these genes, we found NNAT, PLAGL1 (also known as ZAC1), LBX1 and OLIG2, which are implicated in the organization of neuroepithelial progenitors during neurogenesis (Fig. 5B )  [59] [60] [61] [62] [63] [64]. We confirmed by qPCR that 0Q neural progenitors show abnormally elevated expression of neurogenic factors NNAT and PLAGL1 (Fig. 5H ), whose dysregulation may affect the ability of 0Q cells to correctly generate neural rosettes.
When 0Q and 7Q cultures were compared at the more mature neuronal stage, 145 DEGs were detected. Among them, we found in the 0Q line a deregulation of genes implicated in neuronal maturation, cell fate, and synaptic activity (Fig. 5C, F, G  and Supplementary dataset S21), reflecting the increased capacity of the 7Q line of acquiring more mature neuronal signatures. Among neuronal maturation DEGs, we confirmed by qPCR that NNAT and PLAGL1 were elevated in 0Q compared to 7Q neurons (Fig. 5H ) with Fig. 4  PolyQ length-sensitive influence in transcriptional programs governing in vitro neuronal differentiation. A Experimental scheme of gene expression analysis by RNA-seq at rosette and neuron stage among 0, 2, 4, and 7Q cell lines. B Schematic pipeline of whole transcriptomics-based analysis designed to identify genes whose expression increase or decrease stepwise (0Q > 2Q > 4Q > 7Q or 0Q < 2Q < 4Q < 7Q) and linearly (Spearman's correlation) with CAG-length in 0, 2, 4, and 7Q transcriptomes.
C Heatmaps of the expression levels for genes identified applying the pipeline depicted in B. The data was normalized and scaled. D GO dot plots of the top significant GO terms (ranked on their p-value from a classic Fisher test) of the genes, identified in B, which are upregulated (upper panel) or downregulated (bottom panel) in neurons with increasing number of Qs. For the full lists of DEGs see Supplementary dataset S21. E-G Violin plots of genes from B showing significant Q length-correlated expression selected for nervous system development (GO:0007399 term) (E), synaptic activity (GO:0099537, GO:0050808, GO:0035418 terms) (F) or cilium formation processes (GO:0060271 and GO:0044782 terms) (G) in 0Q, 2Q, 4Q, and 7Q neurons. Each dot represents the z-score value for each gene (z-score values were calculated by subtracting the population mean of expression levels from the sample mean of the raw expression levels and, then, dividing by the population standard deviation).
7Q. For the details of the plot see E. H qPCR validation analyses of significant DEGs between 0Q vs. 7Q cell lines at rosette (D8) and neuron (D28) stage. Bar plots display the mean values ± SEM from n ≥ 3 biological replicates; *P < 0. 05, **P < 0. 01, ***P < 0. 001, ****P < 0. 0001, one-way ANOVA test followed by Tukey. Values of the logFCs are scaled. For the full lists of DEGs see Supplementary dataset S21. mutations. Purifying natural selection is a hallmark of functional biological sequences and the non-pathogenic CAG-polyglutamine repeats HTT must confer advantageous traits to the protein. Consistent with this, we discovered that the HTT non-pathogenic polyQ tract has neuronal activities. In line with our finding, previous studies have shown that Q deletion in mice causes cognitive deficits in specific tests  [65].
ACKNOWLEDGEMENTS We thank all the suppliers from  Academic Institution , Zoos and Bioparks that kindly provided us with tissues and genomic DNA. Specifically,  Johannes Erritøze  ( House of Bird Research, Danmark ) for providing bird tissue samples;  Nicoletta Ancona  ( Acquario e Civica Stazione Idrobiologica Milano-Italy ) for providing fish tissue samples (Labridae; Sparidae; Caproidae; Carangidae);  Roberta Castiglioni  ( Parco Faunistico "Le Cornelle"-Italy ) for providing body hairs of Callithrichinae (Saguinus oedipus);  Silvia Colmegna  ( Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna-Italy ) for providing tissue samples from  Galliformes (Gallus gallus) ;  Enrico Merli  ( Ente forestale di Piacenza-Italy ) for contributing to provide tissue samples from birds and mammals (Leporidae; Mustelidae);  Maurizio Casiraghi  ( Department of Biotechnology and Biosciences, Università degli Studi di Milano Bicocca-Italy ) and  Adriano Martinoli , ( Department of Theoretical and Applied Sciences, Università degli studi dell'Insubria-Italy ) for providing tissue samples and genomic DNA from Chiropetera;  Claudia Romeo  ( Department of Veterinary Sciences and Public Health, Università degli Studi di Milano-Italy ) for providing mammal tissue samples (Sciuridae);  Maristella Giurisato  ( Banca Tessuti Mammiferi Marini del Mediterraneo, Università di Padova-Italy ) for providing samples of Delphinidae;  Adriana Bellati  ( Department of Earth and Environmental Sciences, Università degli Studi di Pavia-Italy ) for providing genomic DNA and tissues from reptiles (Phyllodactylidae) and birds;  Riccardo Castiglia  ( Department of Biology and Biotechnology, Università di Roma La Sapienza-Italy ) and  Giovanni Amori  ( CNR-Institute of Ecosystem Study, Department of Biology and Biotechnology "C.
Simulation Configuration: The simulations used for this study were forced with imposed historical 13-PFT vegetation (ESA-LUH2 v1. 2), CRU-NCEP v8 17 climatology and atmospheric CO 2 concentrations at 0. 5° resolution with SPITFIRE activated and hydrological river routing deactivated. Deforestation fires were deactivated and agricultural fires in the output ignored to simplify analysis. A 50 year 'spinup' run on a loop of the years 1901-1920 for the above input forcing datasets was first performed to bring the biosphere and fire cycle to a quasi-steady state under the closest pre-20 th Century climatology we can approximate with our climate data. The same model was then run continuously over years 1901-2010. Fire C loss terms were estimated from derived variables in the simulation output. Deforestation fires were not activated for in these simulations as the legacy effects of these events remain poorly understood and quantified.
The resulting gridded  !" !"# dataset is then used to estimate the proportion of tropical vegetation affected by fire by multiplying the probability that a fire in a given pixel comes from a given PFT by the burned fraction of that PFT (  ): 𝑭𝒊𝒓𝒆𝑽𝑪 𝑨𝑮 𝑷𝑭𝑻 = 𝑽𝑪 𝑨𝑮 𝑷𝑭𝑻 * 𝒑(𝑭𝒊𝒓𝒆) 𝑷𝑭𝑻 * 𝒇𝑩𝒖𝒓𝒏 𝑷𝒊𝒙 (9) To capture only those areas that may have experienced drought and hence drought induced fire mortality, we employ the standardised precipitation index (SPI)  19  , which derives a generic wet-dry index for any location by fixing a gamma probability density function to a timeseries of precipitation for a given location (in this case a given pixel containing a tropical forest PFT). To calculate the SPI for all grid cells over the timeseries of the study simulation, we use a pre-existing SPI function available in the NCAR Command Language (NCL)  20.
The SPI defines different thresholds for wet and dry conditions according to a continuous positive and negative scale, in which all SPI values under SPI<-1. 5 are indicative of a location experiencing severe to extreme drought. Averaging the SPI annually, we mask out pixels in the dataset  !" !"# which do not satisfy the SPI <-1. 5 condition. We then assume that total post-fire mortality loss is approximated from the mean literature value of -24. 8% (±6. 9%)  21 and define this fraction as the total C-loss. However, since this biomass should be recoverable by the biosphere if BRI<FRI, only those pixels in which BRI>FRI are considered time-integrated losses, and only by the fraction given by the ratio of the two. To this loss is added the vegetative carbon-derived CO 2 emissions in the original droughtinduced fire which is likewise reduced by the (BRI:FRI) ratio.