dataesr/scientific-paragraphs-categorization huggingface dataset:
For visibility, the y-axis has been truncated at a -log(P) of 13. we examined as proxies SNPs in LD with the index SNP in a region (r 2 > =0. 1). For six of the novel regions detected, no polymorphic SNPs across datasets were available, preventing evaluation of replication for these regions. We calculated a significance threshold for replication of 0. 029 using Benjamini-Hochberg's FDR procedure (accounting for 27 regions tested in four replication datasets). Altogether, 26/33 regions had association P-values <0. 029 for at least one distance, in at least one of the replication datasets (22 in East Asians, 21 in Europeans and 5 in Africans; with 4 regions replicating in all three independent datasets) (Supplementary Table  4 , Supplementary Note 2-3). Follow-up of novel face regions in the mouse.
33  , and a SNP GWAS of Cole et al. 5. This sample contains 3631 Bantu African individuals aged from 3 to 21 from the Mwanza region of Tanzania. The summary statistics are available at https://github. com/meganmichelle/CNV_FaceShape and https://www. ncbi. nlm. nih. gov/projects/gap/cgi-bin/study. cgi?study_id=phs000622. v1. p1. Genotype data. The genotype data examined here are those analyzed in previous GWAS of the CANDELA sample  1, 2, [22] [23] [24]. Briefly, a blood sample was collected from each volunteer and DNA extracted following standard laboratory procedures. DNA samples were genotyped on the Illumina HumanOmniExpress chip including 730,525 SNPs. PLINK v1. 90 was used for QC. Individuals and SNPs with >5% missing genotypes, SNPs with <1% minor allele frequency, and individuals who failed the X-or Y-chromosome sex checks were excluded.
After these QC filters, ~650,000 SNPs and 5500 individuals were retained for further analyses. Human genome reference assembly GrCh37/hg19 was used. SHAPEIT2  69  was used for prephasing the chip genotype data, and IMPUTE2  70  was then used to impute variants using the 1000 Genomes Phase 3 reference panel. Imputation led to 11,532,785 SNPs being available for association testing. Markers that are monomorphic in 1000 Genomes Latin American samples were excluded from imputation. Chip genotyped SNPs having a low concordance value (<0. 7) or a large gap between info and concordance values (info_type0 -concord_type0 > 0. 1), which might be indicators of poor genotyping, were also removed, both from the imputed and chip dataset. Imputed SNPs with imputation quality scores <0. 4 were excluded. The IMPUTE2 genotype probabilities at each locus were converted into best-guess genotypes using PLINK (at the default setting of <0.
1 uncertainty). SNPs with >5% uncalled genotypes or minor allele frequency <1% were excluded. On the basis of genome-wide SNP data, we estimated European, Native American and sub-Saharan African ancestry proportions for each CANDELA individual (European and Native American ancestries being strongly negatively correlated  21  ). Phenotyping. Frontal digital photographs were taken for each CANDELA volunteer, at eye level, 1. 5 m away, using a Nikon D90 camera (12,3 Megapixels resolution) fitted with a Nikkor 50 mm fixed-focal-length lens  21. The photographs were anonymized for confidentiality, and stored on a secure cluster, where an API script available from Face++ (https://www. faceplusplus. com), implementing a pretrained deep learning model was run. Face++ placed 106 landmarks on each photograph (Supplementary Fig.
Procrustes superimposition was performed using MorphoJ  71  and pairwise ILD calculation was carried out using R  72. Since Procrustes-adjusted landmarks coordinates were symmetrized, some ILDs were identical. After removing 260 duplicates, 301 distances (labeled as 'D' followed by a number, Supplementary Table  3 ) were retained for the GWAS. To evaluate the robustness of the Face++ landmarking, we examined the accuracy of 32 landmarks which were either placed manually on a subset of 1610 photographs in a previous study  1  , or included in another commonly used automatic face landmarks detection protocol Dlib  25, 26  on the same 1610 photographs (Supplementary Table  1 ). Median Euclidean distances and ICCs between Face++ and manual landmark coordinates, and between Face++ and Dlib landmark coordinates were obtained using Matlab  73.
0, which is better suited to estimate relatedness in admixed individuals. Only one individual from any related pair (with a threshold of IBD > 0. 1, excluding third degree relatives and higher) was retained. To estimate the narrow-sense heritability (h 2 ) for each trait, we computed a genomic relationship matrix (GRM) combining genotype data for of all individuals for which data for at least one trait was available. The GRM was calculated using LDAK5  30  with default parameters. For each trait, h 2 was estimated by fitting an additive linear model with a random effect term whose variance was obtained from the GRM, and added age, sex, BMI, 6 genetic PCs and head angles as covariates. An LD-pruned set of 93,328 autosomal SNPs was used to estimate European, African and Native American ancestry proportions using supervised runs of ADMIXTURE  75.
We then have conducted the conditional analysis on totally 93 SNPs across 26 regions. We gathered all reported SNPs in each chromosome band and added those reported SNPs into the regression models of corresponding SNPs of the same chromosome band in our results. If P-value obtained was above the suggestive significant threshold (1 × 10 -5 ), this signal would be regarded as a reported signal, and conversely, it would be regarded as a new signal. Details of the results from conditional analyses could be seen in Supplementary Table  9. In the replication analysis, 76 P-values were available for 27 novel associated regions across 4 separate datasets. After correction of multiple testing with BH-FDR, the combined significance threshold in the replication cohorts was 0. 0293. Genome-wide association analyses and correction for population stratification.
A model proposed by Atkinson et al. 83  (TRACTOR) which instead of using the SNP genotypes directly, uses the SNP coding on three different local ancestry backgrounds. We examined three models: one using only genetic PCs (i. e. global ancestry), one using only local ancestry (obtained here by RFMix), and one with both local ancestry and genetic PCs as covariates. vi. An alternative to TRACTOR called SNP1 (proposed by Hou et al. 64  ), which for each SNP genotype uses the local ancestry estimates at that location as covariates. We tested two models: one using both local ancestry and genetic PCs as covariates, and one only using local ancestry but not PCs; We first contrasted GWAS results for the 148 facial distances showing significant association in the primary PLINK analyses. We ran GCTA and GENESIS on the exact same imputed genome-wide dataset used in the PLINK analyses.
For SNP1 and TRACTOR analyses were performed only on the chip data, as local ancestry estimates are only available for genotyped (not imputed) data. To compare results across all analysis approaches and models, the genomic inflation factor (lambda) was calculated for each GWAS using the chip SNP data (Supplementary Fig. 8  and Supplementary Table  10 ). Examining the distribution of lambda values, we observe that, in the absence of correction for population stratification (PLINK with no PCs, nor GRM, nor local ancestry), there is a marked inflation (Supplementary Fig. 8 ). However, we find that with any form of wholegenome-based adjustment (with PLINK, GCTA or GENESIS) this inflation is properly controlled, as the lambdas are very close to 1 (as previously observed  64, 74, 84  ). Supplementary Fig.
The Benjamini-Hochberg's FDR significance threshold equals 4. 9 × 10 -4. Neanderthal and modern human skull comparison. Distance D117 (between landmarks 12/nasion and 18/subnasal) measured in the CANDELA individuals corresponds to the cranial distance measured between nasion and subspinale landmarks (i. e. nasal height, in Howells' system of cranial measurement  94  ). We extracted nasal height from the measurements obtained by Weaver and Stringer 95 on 10 Neanderthal specimens (Amud 1, Forbes' Quarry, Guattari 1, La Chapelle-Aux-Saints, La Ferrassie 1, Saccopastore 1 and 2, Saint-Césaire, Shanidar 1, Shanidar 5). For comparison with modern humans, we extracted nasal height measured in skulls from 484 Africans, 317 Europeans and 389 Native Americans (males and females were balanced for each region), from Howells' online database (http:// web.
Implemented tool ANNOVAR was used to annotate the functional consequences on gene function on the independent SNPs and candidate SNPs. The website indicates that ANNOVAR uses all annotated transcripts in Gencode collection lifted up to hg19, and has its own prioritization criteria to report the most deleterious function. Only prioritized annotations are used for those SNPs. Gene Ontology (GO) analysis and transcription patterns in newly associated regions. We used Metascape (http://metascape. org/) to carry out a GO analysis  96  of genes nearest to the index SNPs of the novel associated regions (if an index SNP was in two genes, both genes were retained in the analysis) (Supplementary Table  4 ). To examine patterns of transcription in the vicinity of index SNPs for the novel regions identified here, we contrasted the CNCC RNA-seq data from the study of Prescott et al.
Acknowledgements Professor Gabriel Bedoya  led the CANDELA team in Colombia but passed away during preparation of this manuscript. We thank the volunteers for their enthusiastic support for this research. We also thank  Alvaro Alvarado ,  Mónica Ballesteros Romero ,  Ricardo Cebrecos ,  Miguel Ángel Contreras Sieck ,  Francisco de Ávila Becerril ,  Joyce De la Piedra ,  María Teresa Del Solar ,  William Flores ,  Martha Granados Riveros ,  Rosilene Paim ,  Ricardo Gunski ,  Sergeant João Felisberto Menezes Cavalheiro ,  Major Eugênio Correa de Souza Junior ,  Wendy Hart ,  Ilich Jafet Moreno ,  Paola León-Mimila ,  Francisco Quispealaya ,  Diana Rogel Diaz ,  Ruth Rojas , and  Vanessa Sarabia , for assistance with volunteer recruitment, sample processing and data entry. We are very grateful to the institutions that allowed the use of their facilities for the assessment of volunteers, including:  Escuela Nacional de Antropología e Historia  and  Universidad Nacional Autónoma de México (México) ;  Universidade Federal do Rio Grande do Sul (Brazil) ;  13°Companhia de Comunicações Mecanizada do Exército Brasileiro (Brazil) ;  Pontificia Universidad Católica del Perú ,  Universidad de Lima  and  Universidad Nacional Mayor de San Marcos (Perú).
We acknowledge  M Arfan Ikram ,  Tamar EC Nijsten ,  Markus A de Jong ,  Stefan Boehringer ,  Myoung Keun Lee ,  Eleanor Feingold ,  Mary L Marazita ,  Lavinia Paternoster ,  Holly Thompson ,  Gemma C Sharp ,  Sarah Lewis ,  Stephen Richmond ,  Alexei Zhurov  and  Luisa Pallares  for facilitating access to published datasets. We thank  Luisa Pallares  and  Abraham Palmer  for kindly sharing the  GWA mouse data. Centre de Calcul Intensif d'Aix-Marseille  is acknowledged for granting access to its high performance computing resources. We thank  Joanne Cole  for providing us the GWAS summary statistics from one of the African population GWAS studies, which we used as one of our replication panel. We thank the MorphoSource repository (www. morphosource. org) and the  División de Antropología, Museo de La Plata (Argentina)  for access to the skull  3D  images shown in Fig.
3. Work leading to this publication was funded by grants from: the  National Natural Science Foundation of China  (# 31771393 ), the  Scientific and Technology Committee of Shanghai Municipality  (  18490750300 ),  Ministry of Science and Technology of China  ( 2020YFE0201600 ),  Shanghai Municipal Science and Technology Major Project  ( 2017SHZDZX01 ) and the 111 Project ( B13016 ), the  Leverhulme Trust  ( F/07 134/DF ),  BBSRC  ( BB/I021213/1 ), the  Excellence Initiative of Aix-Marseille University -A*MIDEX  (a  French "Investissements d'Avenir" programme) ,  Universidad de Antioquia  (CODI sostenibilidad de grupos 2013-2014 and MASO 2013-2014),  Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul  ( Apoio a Núcleos de Excelência Program ),  Fundação de Aperfeiçoamento de Pessoal de Nível Superior  and the  National Institute of Dental and Craniofacial Research  ( R01-DE027023 ;  U01-DE020078 ;  R01-DE016148 ;  X01-HG007821 ), Santander Research & Scholarship Award.
Data availability Raw genotype or phenotype data cannot be made available due to restrictions imposed by the ethics approval. Summary statistics obtained during the current study have been deposited at GWAS central and is available at the URL http://www. gwascentral. org/ study/HGVST5029. All produced Manhattan plot and Q-Q plot are available via figshare https://doi. org/10. 6084/m9. figshare. 19728916  78. Supplementary Tables can be found in the Supplementary Data file. All other data are available from the corresponding author on reasonable request. Public data resources used: The Altai Neanderthal genome was downloaded from the website of the Max Planck Institute for Evolutionary Anthropology at http://cdna. eva. mpg. de/neandertal/altai/AltaiNeandertal/VCF/. European cohort summary statistics: https://doi.
The INDEL analysis performed by ICE software showed an average INDEL frequency of 40% for CFTR_1 sgRNA and 32% for CFTR_2 sgRNA. The percentage of INDELs reached 44% when both guide RNAs were provided by the same NB preparation. Toxicity was also evaluated by counting the number of organoids that developed 9 days after treatment in the presence or absence of the NBs (Figure  4C ). Here, again, the NBs did not induce toxicity compared with the control conditions. Moreover, the size distribution of the organoids was not significantly changed after anti-CFTR NB incubation versus no incubation with NBs (Figure  S4B ). NB-mediated gene editing was thus also highly efficient for mouse colon organoids underlining the ease and versatility of NBs for gene editing and KO generation in the mouse organoid model.
NBs do not induce INDELs at the analyzed off-target sites in murine organoids Another advantage of the NBs is that we provide Cas9 as a protein. The CRISPR-Cas9 gRNA complexes, so-called RNPs, contained in the VLPs are only transiently present once delivered into the targeted cell. 26  The fact that Cas9 is present in the cell for a limited time should decrease the number of cuts in off-target sites, as shown previously. 25  Using the Cas-OFFinder software, we predicted potential off-target sites for each of our sgRNAs (Tables  S1  and S2 ). We included in our analysis only the off-target sites containing a protospacer adjacent motif (PAM). We assessed two off-target sites for the AR_1 sgRNA with three mismatches since no off-target sites with one or two mismatches were identified by Cas-OFFinder (Figure  5A ; Table  S1 ).
This was confirmed by DECODR analysis. We also predicted the potential off-target sites for the sgRNAs CFTR_1 and CFTR_2 using the open access program Cas-OFFinder (Tables  S3  and S4 ; no more than three mismatches are listed). We proceeded as for AR gRNA off-targets and, under these experimental conditions, no off-target gene editing was detected for the four different CFTR off-target positions analyzed (Figures  5C  and 5D ).
These PCR products were then subjected to Sanger sequencing. Analysis of the resulting sequences by ICE confirmed that anti-hCFTR NBs resulted in over 90% INDELs (Figure  6B ). The high-level KO of hCFTR in HEK293T was confirmed by almost complete disappearance of hCFTR-HA-tagged surface expression (Figure  6C ). As detected previously, no cell death was induced by the NBs in 293T cells (Figure  6D ). 26  Finally, the rectal organoids were, upon dissociation, incubated solely for 10 min with these validated anti-hCFTR NBs. We amplified a genomic fragment around the loci targeted by the hCFTR sgRNA. The INDEL analysis performed by DECODR software showed an INDEL frequency up to 20% for the hCFTR genomic target site (Figures  6E  and 6F ). Finally, no apparent toxicity was detected since the number of cells developing into human organoids was similar in the absence or presence of anti-GFP or anti-hCFTR NBs (Figure  6G ).
ACKNOWLEDGMENTS Funding was received from the  CHEMAAV  ( ANR-19-CE18-0001 ) grant operated by the  French National Research Agency (ANR). This study was supported by research funding ( CRISPR screen Action ) from the  Canceropôle Provence-Alpes-Côte d'Azur , the  French National Cancer Institute (INCa) , and the  Provence-Alpes-côte d'Azur Region. A. K. and V. T. received a PhD fellowship from the  French Ministry of Research. M. B. and M. M. E. are supported by  FWO-SB (Flemish Research Foundation ) doctoral fellowships,  1SE8122N  and  1S29917N , respectively, M. S. C. by a senior post-doctoral  FWO scholarship   12Z5920N  and  KU Leuven BOFZAP professorship. Cystic Fibrosis Research  is funded by the  Belgian CF patient Association and Fund Alphonse Jean Forton  from the  King Baudouin Foundation  ( 2020-J1810150-E015 ) and by  FWO  (SBO OrganID:  S001221N ).
First, to understand how WNT status correlates with differentiation status, we examined scRNA-seq data. The analysis showed that WNT activation genes were upregulated during early anagen, especially in late-stage Oca2 + McSCs (Extended Data Fig. 11b, c ). Immunofluorescence data confirmed that Oca2 + McSCs activate WNT signalling in anagen onset HG (Extended Data Fig. 11d-f ). Notably, WNT signalling was subsequently downregulated by mid/late anagen in the bulge/ ORS up regardless of UVB irradiation (Extended Data Fig. 11d-f   43  ) showed that in this environment, these cells survived and inappropriately continued along the differentiation pathway to express pigment after translocation into the anagen bulge/ORS up (Extended Data Fig. 12a, b ). By contrast, normal Oca2 + cells reverted to an undifferentiated state (Extended Data Fig.
Mice from experimental and control groups were randomly selected from either sex for experiments. Data collection and analyses were not performed blind to the conditions of the experiments. To induce Cre recombination, tamoxifen (Sigma-Aldrich) treatment was performed as previously published  7  by intraperitoneal injection (0. 1 mg g -1 body weight) of a 20 mg ml -1 solution in corn oil per day. For the UVB experiment, dorsal fur of 3-week-old Oca2 creER ;Rosa LSL-tdTomato mice was clipped, and mice were anaesthetized. Mice were treated every other day with 600 mJ cm -2 UVB per day 3 times in total. Skin biopsies were taken from euthanized mice or under isoflurane anaesthesia. For isolation of McSCs and differentiated bulb MCs, Dct rtTA ;tetO H2B-GFP mice were administered doxycycline-containing chow (1 g kg -1 , Bio-Serv) for 4 days before euthanizing the mice for cell isolation.
Scanned images were processed using Inform (v. 2. 6. 0) software (Aloya Biosciences). For quantitative analysis, HALO (v. 3. 5) software (module Indica Labs-FISH v. 3. 2. 3) was utilized. FISH probe cell intensity (average intensity of FISH probe (×) spots and clusters per cell) was measured in tdTomato + cells in the mid-anagen bulge/ORS up and the bulb. The relative intensity of bulge/ORS up tdTomato + cells to bulb tdTomato + cells within the same sample was compared across multiple samples.
Microscopy For thin sections, images were taken at a single focal plane. For wholemount tissues and thick sections, serial z-images were collected throughout the depth of each entire HF. Wide-field fluorescence images were taken with standard narrow-pass filters with an Eclipse Ti inverted microscope (Nikon) or an upright Axioplan (Zeiss). Images were processed to reconstruct a focused image using ImageJ/Fiji, Adobe Photoshop and the extended depth of focus function in the NIS-Elements software (Nikon, v. 5. 20. 02). The z-stack fluorescent images in Figs. 2a and 3b were taken using a LSM 880 confocal microscope with a ×63 NA/1. 4 Plan Apochromat lens (Zeiss). The z-stacks were taken at 0. 3 μm steps. Volumes were reconstructed using Imaris 9. 5 software (Oxford Instruments).
The Single Cell 3′ Reagent kits v3 User Guide (Manual Part CG000201 RevA) was followed. Libraries were run on an Illumina NovaSeq 6000. The Cell Ranger Single-Cell software suite (v. 6. 0. 1) was used to perform sample de-multiplexing, barcode processing and single-cell 3′ gene counting. The cDNA insert was aligned to the mm10/GRCm38 reference genome (mm10-2020-A). The undifferentiated telogen melanocyte dataset was downloaded from the NCBI Gene Expression Omnibus (identifier GSE113502) and re-processed with the same version of the Cell Ranger Single-Cell Software Suite (v. 6. 0. 1) and mapped to the same version of reference genome (mm10-2020-A). Further analysis and visualization were performed using Seurat package (v. 4. 1. 0)  59 , using R Studio Desktop (v. 1. 4. 1717) and R (v. 4. 1.
The top 3,000 variable genes were used for calculating PCs. UMAP dimension reduction was performed on the normalized, centred, scaled nUMI count matrices using the first three PCs. To estimate the cell cycle stage of a cell, we used Seurat's cell cycle scoring. In brief, averaged relative expression of cell cycle related genes were used to calculate G2/M and S scores, which were used for binning cells into G2/M, S and G1/G0 bins. The cell cycle scores were regressed out in ScaleData step in the analysis of the anagen II melanocyte dataset alone, followed by PC calculation, UMAP dimension reduction and unbiased clustering as described above. Pseudotime analysis was performed using the slingshot package (v. 2. 2. 0)  60. The Seurat object was imported into slingshot using the as. SingleCellExperiment function.
Gene set enrichment analysis Genes differentially expressed between anagen II melanocytes compared with telogen melanocytes (P < 0. 05, log 2 (fold change) > 0. 25) were rank-ordered from high to low on the basis of their fold change. The pre-ranked gene list as queried for its enrichment in two annotated gene sets acquired from The Molecular Signature Database (MSigDB)-GOBP_DENDRITE_DEVELOPMENT and GOBP_DENDRITE_MORPHOGEN-ESIS-using the preranked gene set enrichment analysis (GSEA) analysis tool  61, 62. A false discover rate q-value of <0. 25 was deemed significant.
(g) Quantitative RT-PCR analysis of indicated SC-enriched genes in bulb Mcs and telogen McSCs. N = 5 mice. Data are represented as mean ± SEM. P-values by two-tailed unpaired t test. (h) UMAP plot with dots and lines showing pseudo-time trajectory predicted using slingshot package. Extended Data Fig. 6 | Examination of the early anagen HG scRNAseq dataset for proliferation and expression of SC-enriched genes. UMAP of early anagen McSCs after cell cycle genes regression. Featureplots of proliferation genes and SC-enriched genes in Oca2 -and Oca2 + early anagen McSCs. Extended Data Fig. 7 | Characterization of Tomato + cells in Oca2-CreER;Rosa-LSL-tdTomato mice during lineage tracing. (a) Targeting vector design of Oca2-CreERT2 knock-in mouse. (b) Cryo section image of Oca2-CreER;Rosa-LSL-tdTomato mouse back skin without TAM treatment at 6-13 weeks old.
Acknowledgements We thank  V. Greco  and  P. Myung  at  Yale University  who enabled us to examine melanocytes using in vivo imaging;  P. Manga  and  S. J. Orlow  for their help and support on pigmentation biology; staff at the  NYU Langone's Microscope Laboratory  for assistance with microscopy;  S. Y. Kim  at the  Rodent Genetic Engineering Laboratory of NYU Langone  for generating the Oca2 creER knock-in line; staff at the  NYU Langone's Genome Technology Center  for expert assistance with library preparation and Illumina sequencing; past and present members of the  Ito Laboratory  for their technical help and intellectual input;  V. N. Nivsarkar  and  A. Brinks  for help in formatting the manuscript;  J. Walczyk  for making the customized platform for in vivo imaging; and members of  NYU Langone's Experimental Pathology Research Laboratory  (RRID: SCR_017928 ), particularly  S.