dataesr/scientific-paragraphs-categorization huggingface dataset:
RESULTS We looked for pathway associations using the GSEA pipeline based on 160 pathways selected from KEGG database  (Kanehisa et al. , 2017)  and the four outcomes of skin aging: photoaging, solar lentigines, wrinkling, and sagging. We first selected the pathways with an FDR < 0. 05, and then, the pathways with an FDR < 0. 25 in common with two or more outcomes. For the four phenotypes analyzed, five pathways reached the 0. 05 FDR threshold. The wrinkling phenotype was associated with the "nucleotide excision repair" (P = 2 × 10 -4 , FDR = 0. 02) and "proteasome" (P = 8 × 10 -4 , FDR = 0. 04) pathways. For these two pathways selected by GSEA, it was interesting to look at their top ranked genes (with associated p values < 0. 01), they were, respectively, XPC, MNAT1, and DDB1, and PSMB3, PSMA1, PSMC2, PSMD2, PSMB5, and PSMD4 (Supplementary S1).
For each outcome, we performed an enrichment analysis by comparing the distribution of significant pathways (with FDR < 0. 25) in the six categories of KEGG ("environmental information processing," "cellular processes," "metabolism," "organismal system," "genetic information processing," and, "human disease") to the pathway distribution in the categories in the whole KEGG database. Figure  2  illustrates this analysis showing the ratio (R) of the percentage of significant pathways in a category found for each outcome to the percentage of pathways in that category over the whole KEGG database. Using Fisher's exact test based on hypergeometric distributions, we have computed the statistical significance of the enrichments observed in Figure  2  (see Methods). For wrinkles, "genetic information processing" pathways were over-represented (R = 4.
98, p = 1. 49 × 10 -2 ). "Organismal system" was over-represented for solar lentigines with nearly half (42. 31%, see Supplementary Figure  S3 ) of the associated pathways in this category (R = 2. 25, p = 2. 3 × 10 -3 , Figure  2 ). Moreover, 44. 6% of the pathways of the category "organismal system" found for the solar lentigines phenotype belonged to the sub-category, "immune system," whereas photoaging, sagging, and wrinkling phenotypes obtained, respectively, 0, 16. 6, and 0% of associated pathways in this sub-category (data not shown). Finally, the "metabolism" category is underrepresented for the lentigine outcomes compared to the KEGG database with R = 0. 31 and p = 2. 1 × 10 -3 (Figure  2 ).
In contrast, we observed an over-representation of pathways from the "genetic information processing" category associated with wrinkles (compared with KEGG). This observation may recall the influence of UV exposure on aging for the induction of DNA damage and development of wrinkles  (Moskalev et al. , 2013). Finally, "organismal system" was the most represented category for lentigines (Supplementary Figure  S3 , Figure  2 ). For the solar lentigines phenotype, the subclass "immune system" represented 45. 4% of the pathways from "organismal system" (five pathways), underlying a putative involvement of the immune system for the solar lentigines in accordance with previous reports  (Aoki et al. , 2007; Laville et al. , 2016). The pathway-based approach is powerful but has a few limitations. For this analysis, we used the pathways from the KEGG database, and since the understanding of human gene function is incomplete and some genes are not yet characterized, the curated pathways of the database may not be fully representative of all the biological networks.
Target protein preparation The 3D crystal structures of SARS-CoV-2 main protease (6LU7; 2. 16 Å), were collected from the Protein Data Bank (https://www. rcsb. org/). The unnecessary molecules such as ions, inhibitors, ligands, heteroatoms, and water molecules were removed from the COVID-19 target protein structure using BIOVIA Discovery Studio. The target pro- tein structures were loaded in PyRx version 0. 8 and converted into PDBQT format [19].
Ligand preparation The marine active compounds (preclinical and clinical levels) were used for ligand preparation (Table  1 ). The 3D structures of the selected marine bioactive were collected from the PubChem Database (https://pubchem. ncbi. nlm. nih. gov/) in SDF file format. Initially, the ligand files were loaded and energy was minimized by Open Babel (MMFF94 method). After the energy minimization process, the ligand files were converted into PDBQT format. These energy-minimized ligands were subjected to further docking analysis  [20].
Druglikeness calculations The Druglikeness analysis was performed to analyze the structural and physicochemical properties of potent hits such as atom molar refractivity (AMR), octanol-water partition coefficient (AlogP), H-bond acceptor (HBA), H-bond donor (HBD), partition coefficient (logP), molecular weight (MW), number of rotatable bonds (nRB), number of Atom, total polar surface area (TPSA), etc. , using DruLiTo software. The different molecular property filters such as CMC-50-like rule [AlogP (1.
A transcriptional switch to enable myofibril and sarcomere assembly As a first step to investigate the molecular changes at day 7 of differentiation, we analysed a previously generated transcriptomics dataset comparing similar proliferative cultures (SKGM-2 medium) with day 7 and day 15 of myogenic differentiation (KCTiP medium)  [19]. After verifying the high quality of the transcriptomics data set with principal components analysis (Figure  S4A , B, Table  S1 ) we performed Mfuzz clustering  [22] , choosing 10 clusters as optimal for our data set (see methods). Mfuzz clustering assigned all expressed genes to one of the ten clusters which exhibit different expression dynamics (Figure  3A , Table  S1 , see methods). We found three gene clusters that are upregulated at day 7 of differentiation, two of which are enriched for muscle specific GO-terms (Figure  3A, B ).
1% Tween20 for 2 hours at room temperature. Myocultures were then washed three times with 1× PBS supplemented by 0. 1% Tween20 (Sigma-Aldrich, Cat. P9416). The culture inserts were removed to allow mounting with a top coverslip and appropriate mounting media. Samples were sealed with nail polish and stored at 4 °C until imaging. The following primary antibodies were used: rabbit-anti-titin (N-term) (Sigma, Cat. HPA007042, 1:50), mouse anti-MyHC (DSHB, Clone A4. 1025, 5 ng/µL), rat anti-β1integrin (DSHB, Clone AIIB2, 5 ng/µL), mouse anti-paxillin (Invitrogen, Cat. AHO0492, 1:5), mouseanti-NCAM1 (DSHB, Clone 5-1H11, 5 ng/µL). The following secondary antibodies were used: goat anti-mouse Alexa405 (Invitrogen, Cat. A31553, 1:250), goat anti-rabbit Alexa405 (Invitrogen, Cat. A31556, 1:250), goat anti-rabbit Alexa488 (Life Technologies, Cat.
Transcriptomics analysis The bulk RNA-seq data analysis was performed on the already analysed data available under the GEO accession number GSE164874. Starting from the raw count matrix file "GSE164874_SecondaryDifferentiation_raw_counts. xlsx", we kept here only the relevant conditions, namely the three replicates for the SKGM-2, KCTiP at 7 days and KCTiP at 15 days of differentiation. In order to compare each time point to a baseline level we artificially generated three pseudo-replicates for the baseline condition. For each of the three pseudoreplicates we computed a baseline value by averaging different replicates of the three time points. Raw count matrix filtered for the conditions of interest and with pseudo-replicates can be found in the Table  S1. Normalization, rlog transformation and differential expression analysis were done in the R environment (v3.
Acknowledgements We thank members of the  Schnorrer group , the  Pourquié group , the IBDM and the  Centuri community  for helpful discussions and feedback. We thank  C. E. Seidman  ( Harvard University ) and  J. G. Seidman  ( Harvard University ) for the gift of GFP-titin iPSC line,  B. Friedrich  ( TU Dresden ) for valuable inputs on algorithms for vector field analysis, the  IBDM imaging facility  for microscopy support, and  D. Massey-Harroche  (IBDM),  E. Bazellières  (IBDM),  V. Dupuis  (IBDM) and  S. Tlili  ( IBDM ) for cell culture support.
Funding This work is supported by a  Human Frontiers Science Program  Grant to F. S. and O. P. ( HFSP ,  RGP0052/2018 ). The Schnorrer lab is supported by the  Centre National de la Recherche Scientifique (CNRS) , the  European Research Council  under the European Union's  Horizon 2020 Programme  ( ERC-2019-SyG 856118 ), the  excellence initiative Aix-Marseille University A*MIDEX  ( ANR-11-IDEX-0001-02 ), the  French National Research Agency  with  ANR-ACHN   MUSCLE-FORCES  and  ANR-18-CE45-0016-01 MITO-DYNAMICS , the  Bettencourt Foundation , the  France-BioImaging national research infrastructure  ( ANR-10-INBS-04-01 ) and the  Investissements d'Avenir, French Government program  managed by the  French National Research Agency  ( ANR-16-CONV-0001 ) and from  Excellence Initiative  of  Aix-Marseille University -A*MIDEX (Turing Centre  for Living Systems).
M. D. C. was funded by grant  F31HD100033  from the  Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)  of the  National Institutes of Health  and the  NASEM Ford Foundation Dissertation Fellowship. A. R. R. has received funding from  "la Caixa " foundation (ID  100010434 ), under agreement  LCF/BQ/AA18/11680032. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
For each individual, the adductor muscle was carefully severed to separate the two valves, without damaging the gonad, and a sample of the mantle was taken. Sex and gonadal maturation stage were determined with a dissecting microscope (x100 to x400). For each individual, two types tissue samples were collected, a gonadic sample and a somatic sample (mantle). All tissue samples were flashfrozen in liquid nitrogen, and then stored at -80°C until DNA extraction. At each step of this protocol, dissecting tools and bench surfaces were thoroughly cleaned in successive baths of 10 % bleach, demineralized water, and 95 % EtOH as to avoid DNA cross-contamination. Using this dataset, we checked that male mitochondria were limited to male gonads (i. e. absent from other male tissues and from females); thus making molecular sexing permissible (Le Cam et al in prep).
13 and 1. 09 for high mutation rates, Figure  S2 ). π a /π s estimates, on the other hand, were always higher for cox1m, suggesting a smaller Ne for this marker compared to cox1f regardless of the group considered. BSP further suggested that historical N e dynamics differed between markers (Figure  4  for the high mutation rate and figure  S2  for the low mutation rate). Southern populations exhibited N e ranging between 1 and 4. 5 M individuals with similar median values (2. 3 and 2. 5 M for cox1m and cox1f, respectively), with similar population growth that started about 200,000 years ago for cox1f (about 122,000 years ago based on the fastest mutation rate). ESS values for the estimated parameters are excellent for the southern group (e. g. posterior ESS between 270 and 422). Northern M-type and F-type datasets exhibited significantly different patterns, with similar N e for cox1f and cox1m prior to about 155,600 years ago (about 107,300 for the highest mutation rate), followed by an exponential N e increase for cox1m only.
Genetic diversity: differential latitudinal variation between m and f genes Male-type mtDNA was almost up to twice as polymorphic as its female counterpart, with more haplotypes, more haplotypes represented by a single male and more segregating sites. Higher polymorphism in the M-type mtDNA, both within and between species that are maladaptive in southern environments) seems to better fit the cox1f dataset. Gene flow between populations towards the range limit should be lower under H1 and higher under H2. While populations across the Cotentin were more differentiated at cox1m than populations across the Finistère at cox1f, Pairwise Φ ST were higher between southern populations at cox1f than cox1m. Genetic diversity should be low (decreasing toward the range limit) under H1 and high under H2, which is met for cox1m and cox1f, respectively.
These two groups, separated by the Vilaine River, were identified as significantly differentiated based on microsatellites, but not cox1f in the study of  Becquet et al (2012) , which was based on individuals from both sexes, while our study focused on males exclusively. We may therefore benefit from higher statistical power to detect differences in differentiation across the Vilaine River. This implies that genetic structure among males at cox1f is higher than in females. Although we did not include females in our study, we did compare pairwise φ ST values between sampling sites that were common between our study and Becquet's. F ST and φ ST were both significantly higher in the dataset composed of males exclusively, compared to the dataset composed of males and females (Figure  5 ). This pattern can be attributed to stochastic genetic variation (effects of mutations and drift) and/or differences of gene flow between sexes.
Cotentin hybrid zone. Sample sizes were 102 and 42 males, respectively. First, we estimated a molecular clock for the male and female cox1 gene by calculating the genetic distance among sequences of L. balthica and Donax, another Tellinoidea characterized by DUI (Theologidis et al 2008; Gusman et al 2016). For L. balthica, we used m and f haplotypes from Umea and Arcachon as extremes on the haplotypes networks (Fig 1). For Donax, we used GenBank records for D. faba (AB040843 and AB040844 for m and f cox1, respectively) and for D. cuneatus (AB040841 and AB040842 for m and f cox1, respectively). The mean genetic distance (Kimura 2-parameters distance, Kimura 1980) between all Limecola / Donax sequence pairs were used to calculate a marker-specific molecular clock, given a divergence time of 90 to 140 My between the two genera (as in Luttikhuisen et al 2003, based on fossil dating in Pohlo 1982).
To run the Bayesian skyline analysis, we followed the protocol of Müller and du Plessis (Barido-Sottani et al 2018). For each dataset (male and female) and for each extreme of the estimated molecular clocks, we ran BEAST v2. 6. 3 (Bouckaert et al 2019) using a GTR+G+I site model, a strict clock model, 800M generations with a pre-burnin of 80M generations. The number of dimensions (groups of coalescent events) was set to 3 after test runs with 3 to 5 dimensions. Other priors were left at their default values. Convergence was checked in Tracer v1. 7. 1. Ne estimates are presented as median values for the retained runs for the low mutation rate, unless otherwise noted. Generation time for L. balthica is 2 yrs (Beukema et al 2001). Results A total of 666 individuals from 17 sampling sites of the French Atlantic coast were dissected and optical microscopy sexing reported 248 males, 185 females and 233 undifferentiated individuals.
1994) have to effectively function exclusively in the male germ line and gametes (different 'arenas of selection' sensu Stewart et al 1996). According to the maledriven evolution hypothesis, higher germ cell divisions in males (Shimmin et al 1993) could result in an enhanced replication rate of the M-type mitochondria during spermatogenesis, providing more opportunities for mutations to accumulate (Rawson and Hilbish 1995 and Stewart et al 1995). In addition, oxidative damage might be important in sperm (Zouros 2013), and/or selection pressures on chaperonins and DNA repair genes might be relaxed. We can also expect sex-linked demographic differences to influence polymorphism, if the effective population size differs between males and females; this is supported by our dataset to a large extent at historical (e.
Whether these breaks are involved in primary intergradation or secondary contact (by geographically stabilizing endogenous genetic barriers; Bierne et al 2011) remains to be answered (we attempted to test scenario of isolation with migration using the present dataset without success). We can nevertheless note that divergence of populations on either side of the Finistère-Cotentin break occurred between 0. 11 to 2. 6 Myr ago (Luttikhuisen et al 2003), while population expansion on either side of the break took place 107 to 200 k years ago.
Acknowledgements The authors thank  Mélanie Rocroy ,  Patrick Triplet ,  Thierry Ruellet ,  Rolet Céline  ( Association GEMEL, Picardie ),  Anthony STURBOIS  ( RNN Baie de Saint-Brieuc, VivArmor Nature ) and  Xavier de Montaudouin (Station Marine d'Arcachon ,  UMR 5805 EPOC ,  Université de Bordeaux/CNRS)  for their help with sample collection. This work was funded by the  ANR  ( DRIVE  project, grant n. ANR-18-CE02-0004-01 ) and by the  contrat de plan Etat-Région (CPER/FEDER)  ECONAT (RPC DYPOMAR). We thank the participants of the  Biocombe project ("The impact of BIOdiversity changes in COastal Marine Benthic Ecosystems ;" contract n. EVK3-CT-2002-00072 ; Research n. OND1290723). Lab work was performed at the  Molecular Core Facility  at the  University of La Rochelle. We thank the bioinformatics platform  Toulouse Midi-Pyrénées  ( Bioinfo GenoToul ).
Finistère/ Cotentin hybrid zone. Sample sizes were 102 and 42 males, respectively. First, we estimated a molecular clock for the male and female cox1 gene by calculating the genetic distance among sequences of L. balthica and Donax, another Tellinoidea characterized by DUI (Theologidis et al 2008; Gusman et al 2016). For L. balthica, we used m and f haplotypes from Umea and Arcachon as extremes on the haplotypes networks (Fig 1). For Donax, we used GenBank records for D. faba (AB040843 and AB040844 for m and f cox1, respectively) and for D. cuneatus (AB040841 and AB040842 for m and f cox1, respectively). The mean genetic distance (Kimura 2-parameters distance, Kimura 1980) between all Limecola / Donax sequence pairs were used to calculate a marker-specific molecular clock, given a divergence time of 90 to 140 My between the two genera (as in Luttikhuisen et al 2003, based on fossil dating in Pohlo 1982).
Haplotype networks and frequencies for the truncated cox1m dataset are presented in Fig S1 and revealed similar pattern of high diversity (64 haplotypes) and divergence (9 mutation steps were estimated between the main central haplotype and the northern one for cox1f against 18 for cox1m). We estimated divergence rates of 0. 47 s/s and 0. 24 s/s for the m and f datasets, respectively. This difference is significant based on the relative-rates test (100% significant comparisons out of 2368 https://github. com/lyy005/Relative-Rate-Test). This resulted in molecular clocks of 0. 0033 and 40 mutation steps separated the most divergent haplotypes for cox1f and cox1m-long, and 0. 0017 s/s/My for cox1m and cox1f, respectively, considering a 140My divergence between values (Table.
Three Candidate Variants Were Identified by Whole Genome Sequencing, Whole Exome Sequencing and Positional Cloning We conducted whole genome sequencing (WGS) and whole exome sequencing (WES) of family HC438 and data were analyzed conjointly. Using a dedicated in-house Python pipeline, 22 variants within the family meeting the filtering criteria (variant quality, frequency, localization, segregation with ADH, predicted consequence and genotype quality; see Section 4. 2) were identified in the heterozygous state. Four variants were transmitted from the mother (I-2) to the three affected children (II-1, II-4 and II-7) corresponding to three missense variants in CYP7A1, KIFC2 and LRP6, and one intronic variant in SLC39A4. Three missense variants in the LDLRAP1, GOLGA4 and AP2A1 genes were transmitted from the father (I-1) to the two more severely affected children (II-1 and II-7).
The effect of LRP6-WT or the mutated plasmids on the membrane expression of the LDL receptor was also evaluated in transfected HEK293T cells and no significant changes were observed (Figure  S5 ). Theses confusing contradictory results suggest that each of these variants does not individually have a major effect on cellular LDL uptake and LDL-C circulating levels. Proteins were extracted from transfected cells, separated by electrophoresis and then transferred onto PVDF membrane. The membrane was incubated with primary antibody (anti-LRP6), followed by incubation with secondary antibody before detection using the iBright TM FL1500 imaging system. Protein was quantified by ImageJ software. Equal loading was confirmed using the ß-actin antibody. Data represent three independent assays. (F) LDL uptake in HEK293T after transfection with an empty vector, LRP6-WT or mutated plasmid.
The median fluorescence intensity of 100,000 events was acquired for each sample, but only the median fluorescence intensity of living cells is presented. The fluorescence of each sample was normalized using the empty vector (PcM) as a reference. Data represent three independent assays, each performed in triplicate. In all experiments, the difference between conditions was determined by Bonferroni's Multiple Comparison Test in one-way ANOVA and * p < 0. 05, ** p < 0. 01, *** p < 0. 001 were considered as statistically significant. Results are shown as mean ± SD. Error bars represent ± SD.
003) based on the information available in the public databases (genome aggregation database (gnomAD) and 1000 genomes project version of August 2015); (  5 ) their segregation with the disease in the 5 family members analyzed; and (6) their localization in a gene involved in at least 1 of the 7 pathways in which ADH genes are involved (Reactome (https://reactome. org (accessed on 6 November 2020)), which are cholesterol biosynthesis (R-HSA-191273), regulation of cholesterol biosynthesis by SREBP (R-HSA-1655829), clathrin-mediated endocytosis (R-HSA-8856828), vesicle-mediated transport (R-HSA-5653656), transport of small molecules (R-HSA-382551), digestion and absorption (R-HSA-8963743), bile acid and bile salt metabolism (R-HSA-194068)). Finally, variants in candidate genes were sequenced in the whole family to test their segregation with the disease under the hypothesis of an autosomal dominant inheritance.
Positional Cloning In parallel with WES and WGS, a positional cloning approach using a genome-wide scan in 14 family members was performed with 1035 polymorphic microsatellite markers from deCODE Genetics, Iceland. Parametric linkage analyses were performed with accepted parameters for ADH, which were dominant transmission of the trait, penetrance of 0. 6 for heterozygotes and a frequency of the disease allele of 0. 01%. The power of the family for linkage was evaluated using the FastSlink v2. 51 software  [44]. We used Pedcheck  [45]  to detect Mendelian inheritance errors. SuperLink v1. 5v  [46]  and SimWalk v2. 91  [47]  softwares were used to compute two-point and multipoint LOD scores. All these softwares were run using the easyLinkage Plus v5. 00 package  [48].
Sequencing and In Silico Analysis of the Variants The coding exons of LRP6, CYP7A1, and LDLRAP1 and their flanking exon-intron boundaries (100 pb surrounding each exon boundary) were sequenced by Sanger or by nextgeneration sequencing  [49]. The coverage was >99% for the coding bases of the LRP6 and CYP7A1 genes and 90% for LDLRAP1, in the 160 unrelated ADH probands. The reference sequences were NM_002336. 3 for LRP6, NM_000780. 4 for CYP7A1 and NM_015627. 3 for LDLRAP1 (GRCh37/hg19 in UCSC Genome Browser). Novel variants were mapped to known functional domains obtained using the UniPro-tKB database (UniProt Knowledgebase; www. uniprot. org (accessed on 6 November 2020)). The presence and frequency of these variants in a control group representative of the French population was verified using the French Exome Project database (FREX; www.