dataesr/scientific-paragraphs-categorization huggingface dataset:
Fossil calibrations To calibrate the cycad tree, we used two fossil datasets. First, we followed Nagalingum et al. [6]  and used four cycad fossil constraints (FC1-4), which were retrieved from a careful examination of the cycad fossil record (  [32] ; Figure  1 ). These four fossils have also been used by Salas-Leiva et al. [43]. Hereafter this fossil dataset is referred to as the 'traditional fossil dataset' (FC1-4). Second we used these four fossils and added two fossils based on the phylogenetic analyses of Hermsen et al. [32]  and Martínez et al. [59]. The fossil record was reexamined after new fossils from the Cretaceous were discovered, which did not affect overall fossil assignments, but allowed the use of new fossils to calibrate the cycad tree  [59] , two of which are tentatively used here.
Hereafter this fossil dataset is referred to as 'new fossil dataset' (FC1-6). Based on the presence of synapomorphies linking the fossils to the extant clades, all fossils were used as minimum age constraints for specific nodes (  [32, 59] , Figure  1 ). However, since synapomorphies can evolve anywhere along the stem branch and the fossil may attach anywhere along this branch  [60] , we used a commonly employed approach whereby the fossils constrain the stem rather than crown node  [61, 62]. The absolute fossil ages we used (detailed below) are slightly different from those used in Nagalingum et al. [6] , mainly due to an updated geological timescale  [63]. Dating fossils older than ~50,000 years is difficult, which means that those fossils are typically assigned to a stratigraphic interval, for example, the late Miocene.
Phylogenetic reconstructions To obtain a starting tree for the dating analyses, Bayesian inferences were performed with MrBayes 3. 2. 3 [72]. To determine the best-fit partitioning scheme of molecular evolution for our dataset, we used PartitionFinder 1. 1. 1 [73]. For the PartitionFinder analyses, branch lengths were unlinked to allow them to be independently estimated for each partition. The searched for best model, among those available in MrBayes, was performed under the greedy algorithm based on the Bayesian Information Criterion model metric. We used the partitioning scheme and among-site rate variation suggested by PartitionFinder, but instead of selecting one substitution model a priori, we used reversible-jump Markov Chain Monte Carlo (rj-MCMC) to allow sampling across the entire substitution rate model space  [74].
This procedure ensures better convergence of the tree topology (S. Ho, pers. comm. ). Other parameters were kept to their default prior distribution or were indirectly specified through other parameters. We designed four distinct BEAST analyses by mixing the fossil dataset and the BPP as follows (i) use of the 'traditional fossil dataset' and the Yule model as BPP; (ii) use of the 'traditional fossil dataset' and the birth-death process as BPP; (iii) use of the 'new fossil dataset' and the Yule model as BPP; and (iv) use of the 'new fossil dataset' and the birth-death process as BPP. For each fossil dataset, we included all fossils for dating the tree, and did not perform cross-validation analyses because Warnock et al. [78]  questioned the cross-validation approach to measure consistency among calibrations based on minimum constraints  [61, 79].
Hence, we think that it is crucially important to assess the effect of BPP prior choice on these estimates, and to discuss them in the light of what is known from the cycads fossil record. BAMM is implemented in a C++ command line program and the BAMMtools R-package  [87]. We ran BAMM analyses on the timetree calibrated with the 'new-fossils dataset' , and reconstructed with either the Yule or the birth-death prior. We set four rj-MCMC running for 50 million generations and sampled every 50,000 generations. A compound Poisson process is implemented in BAMM for the prior probability of a rate shift along any branch. We used a prior value of 1. 0 implying a null hypothesis of no rate shift across the phylogeny, as recommended by Rabosky  [87]. We accounted for incomplete taxon sampling using the implemented analytical correction, with a sampling fraction set to 0.
Divergence time estimates and model selection for the branching process prior Convergence of the dating analyses was ensured by ESS values above 200 for all parameters (with many >1000) for the post burn-in trees (Table  1 ) and Tracer plots indicated that BEAST runs reached convergence before the burn-in threshold. The choice of branching process prior had a striking effect on age estimates (Figures  2  and 3 ; Table  1 ). Analyses with the Yule prior inferred much older ages for cycad genera (Figure  4 ). Genuslevel crown ages were on average three times older with a Yule than with a birth-death prior (3. 2-fold difference with the 'traditional fossil dataset' and 2. 9-fold with the 'new fossil dataset'). This difference was quite striking, with non-overlapping credibility intervals (95% highest posterior density) for the genus crown ages (Figure  4 ).
Of the two pairs of BEAST analyses (four FC and six FC), BF values are above the standard threshold: BF 4FC = 26. 66 between the Yule and birth-death prior, and BF 6FC = 36. 3 between the Yule and birth-death prior. On the contrary, the HME found the opposite, that is the Yule model is the best prior for both datasets for all analyses (Table  1 ). The results for the cycads thus support previous results showing that the HME estimator is not reliable  [76].
Finally our results are in agreement with paleobotanical evidence indicating that cycads first appeared in the late Permian and became more abundant and diverse in the Triassic  [33, 39, 40]. Cycads proliferated during the Mesozoic, an era characterized by an increased occurrence and diversity of fossil cycads, broadly distributed throughout the relatively uniform climate of the supercontinent Pangaea  [42]. Notably, the Triassic record of Cycadales is among the most well-known of cycad history, not only because The diversification scenarios obtained with one versus the other prior are strikingly different. Note the differences for the estimated speciation and extinction rates with each tree prior (rates are twice higher with the tree constrained with a birthdeath process). P, Permian; T, Triassic; J, Jurassic; K, Cretaceous; Pg, Paleogene; N, Neogene.
Acknowledgements We thank the Associate Editor  Rafael Zardoya , and the two referees  Susanne Renner  and  Diego San Mauro  who provided insightful comments on the study. We also thank  Frédéric Delsuc  and  Gael Kergoat  for discussions, and  Simon Ho  and  Guy Baele  for technical comments on the Bayesian analyses. We also thank  Daniel Rabosky  for the workshop on the BAMM approach, and  Mario Coiro  for discussions and feedbacks on the fossil record of cycads. Funding was provided by grant  ANR CHEX ECOEVOBIO  awarded to HM.
This research was funded by a  European Research Council   Starting Grant  ( FP7/2007-2013 , grant  260729 EndoSexDet ) to RC and intramural funds from the  Centre National de la Recherche Scientifique (CNRS)  and the  French Ministère de l'Education Nationale, de l'Enseignement Supérieur et de la Recherche. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
A negative film of the adaxial epidermis of the same leaf 6 as the one measured in surface was obtained after evaporation of a varnish spread on its surface. These imprints were analyzed using a microscope (Leitz DM RB; Leica) supported by the image-analysis software Optimas. Mean epidermal cell density [cells mm -2 ] was estimated by counting the number of epidermal cells in two zones (at the tip and base) of each leaf. Total epidermal cell number in the leaf was estimated from epidermal cell density and leaf area. Mean epidermal cell area [m 2 ] was measured from 25 epidermal cells in two zones (at the tip and base) of each leaf. For rosette growth measurements, at each date of harvest all leaves with an area larger than 2 mm 2 from five rosettes were imaged with a scanner. The number of leaves was counted and total rosette area was calculated as the sum of each individual leaf area measured on the scan with the Image J software.
Tiling array transcript data and quantitative iTRAQ proteomics data Gene expression in leaves of the four developmental stages and at the two diurnal time points in the long day optimal water (LD) experiment and in a reference mixed rosette sample was profiled as described previously  [18]  using AGRONOMICS1 microarrays  [23]  and analyzed using a TAIR10 CDF file  [24]. All log2-transformed sample/reference ratios without p-value filtering were used in the analyses. Microarray raw and processed data are available via ArrayExpress (E-MTAB-2480). Proteins in the same samples were quantified using the 8plex iTRAQ isobaric tagging reagent  [25, 26]  as described in detail previously  [18]  according to the labelling scheme in Supporting Table  S5. The resulting spectra were searched against the TAIR10 protein database  [27]  with concatenated decoy database and supplemented with common contaminants with Mascot (Mascot Science, London, UK).
The peptide spectrum assignments were filtered for peptide unambiguity in the pep2pro database  [28, 29]. Accepting only unambiguous peptides with an ion score greater than 24 and an expect value smaller than 0. 05 resulted in 70 979 assigned spectra at a spectrum false discovery rate (FDR) of 0. 07%. Quantitative information for all reporter ions was available in 50 947 of these spectra leading to the quantification of 1788 proteins based on 6178 distinct peptides (Supporting Table  S6 ). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral. proteomexchange. org) via the PRIDE partner repository  [30]  with the dataset identifier PXD000908 and DOI 10. 6019/PXD000908. The data are also available in the pep2pro database at www. pep2pro.
Diurnal transcript level changes are less pronounced in a LD photoperiod To account for the observed phenotypic and metabolic differences between SD and LD we analyzed quantitative protein and transcript data in detail. We first performed a Principal Component Analysis (PCA) to estimate the main factors that determine changes in transcript and protein levels in LD. The main contribution to the variance in the transcript data in the first two principal components is the difference between stage 1 and the later stages 2-4, which accounted for over 60% of the total variance (Fig. 4A ). The EOD and EON samples are separated only in the third principal component, which accounted for about 8% of the total variance (Fig. 4B ). This is in contrast to a PCA of the transcripts in SD conditions, where the time of harvest was the main contribution to the variation in the data in the first and second principal components  [18].
SD increases transcript levels for sugar transport and photosystem proteins Transcripts that are significantly higher in SD than LD encode twelve members of the monosaccharide transporter (MST)(-like) gene family  [50]  and the SUCROSE-PROTON SYMPORTER 9 (SUC9, AT5G06170). Accordingly, the bin sugar. transport is overrepresented in SD (Fig. 6 , Supporting Table  S4 ). The members of the MST(-like) gene family are classified into seven distinct subfamilies and have roles in both long-distance sugar partitioning and sub-cellular sugar distribution  [50]. POLYOL/MONOSACCHARIDE TRANSPORTER 2 (PMT2, AT2G16130) and SUGAR TRANSPORTER 1 (STP1, AT1G11260) are located in the plasma membrane and were suggested to import monosaccharides into guard cells during the night and function in osmoregulation during the day  [51].
Acknowledgements We thank the  Functional Genomics Center Zurich (FGCZ)  for providing infrastructure and technical support,  Pascal Schläpfer  and  Johannes Fütterer  ( ETH Zurich ) for helpful discussions and critical reading of the manuscript. We thank  Nicole Krohn  and  Beatrice Encke (MPIMP)  for metabolite analyses. This work was supported by the  AGRON-OMICS  integrated project funded in the European Framework Programme 6 ( LSHG-CT-2006-037704 ). The  UMR EEF  is supported by the  French National Research Agency through the Laboratory of Excellence ARBRE  ( ANR-12-LABXARBRE-01 ).
To break putative long branches within the tribe Rattini, the two karst-specialist genera Saxatilomys paulinae and Tonkinomys daoventieni from the Dacnomys division (Table  S1a ) were included in this study. We also mined 170 cytb, 190 IRBP, 137 GHR, 74 BRCA1 sequences representing 191 murine species available from previously published studies (see references above; Table  S1b ). In total, our dataset includes 196 murine species representing a total of 100 genera following  Musser & Carleton's classification (2005). We included 17 representatives of Deomyinae, Gerbillinae and Lophiomyinae (Table  S1b ) as outgroups  (Michaux & Catzeflis, 2000; Steppan et al. , 2004b). We used SEAVIEW  (Galtier et al. , 1996).
Phylogenetic analyses on the individual and concatenated genes Phylogenetic trees were reconstructed using two probabilistic methods: maximum likelihood (ML) and Bayesian inference (BI). ML analyses were first carried out on each marker independently using RAXML 7. 2. 8-ALPHA (Stamatakis, 2006). Each gene considered separately does not result in a robust phylogeny of Murinae: mitochondrial marker helps to resolve terminal nodes, while nuclear genes lend support to deepest ones. But, since the 4 markers yielded consistent, compatible topologies, sequences were concatenated and phylogenetic analyses were then carried out using the combined dataset. As the model choice is limited in RAXML, the general time-reversible GTR+G model (option -m GTRGAMMA) was selected and robustness of each tree was assessed using the rapid bootstrap (Bp) procedure (option -f a) with 1,000 replications (option -# numberOfRuns)  (Stamatakis et al.
Molecular dating Divergence times among species were estimated from the combined supermatrix of nuclear and mitochondrial sequences. A Bayesian relaxed molecular clock method was used to estimate divergence dates whilst accounting for changes in evolutionary rates through time by allowing for independent models of sequence evolution for each gene partition. The best fitting substitution models for each partition were selected using JMODELTEST results. We used BEAST V1. 7. 4  (Drummond & Rambaut, 2007 ) assuming a Yule model of speciation and an uncorrelated log-normal distribution molecular clock as tree priors. Clock models were unlinked across gene partitions in order to account for missing data  (Lemmon et al. , 2009). We ran MCMC chains for 200 million generations, with trees sampled every 5,000 generations.
The program TRACER was used to assess algorithm convergence. We removed the first 15% of trees before the algorithm had reached stability as a burn in. Trees from each of the 4 independent runs were combined into a maximum clade credibility tree with mean node heights calculated using TREEANNOTATOR. To calibrate the phylogeny, we selected five fossil constraints, as described from previous studies  (Jansa et al. , 2006; Lecompte et al. , 2008; Rowe et al. , 2011; Rowe et al. , 2008; Steppan et al. , 2004a). In order to take the uncertainty in the phylogenetic position of these fossils into account, all constraints were set using hard minimum and soft upper boundaries, using a lognormal prior, as suggested by recent paleontological studies  (Benton & Donoghue, 2007; Benton et al. , 2009; Parham et al.
Ancestral state reconstruction We reconstructed ancestral states for the dental key character, previously used to define the Micromys and Pithecheir divisions: the cusp t7 (Figure  1 ). Based on  Musser and Newcomb (1983)  (see page 537, character 27), this trait was coded as '1' if "a cusp t7 derived and if present, found on each first molar, usually on the second, and on the third" and as '0' otherwise ("no cusp t7 (also called posterointernal or posterolabial cusp) on any upper molar"). Taxa with uncertain or unknown character state were coded as "missing". The resulting classification of all species in our study dataset is available in the SI data (Figure  S3 ). The presence of an opposable first digit on the hindfoot (hallux) comprises another potential criteria for examining the morphological evolution of these arboreal rodents.
An opposable hallux has been attributed to Chiropodomys, Hapalomys, Vandeleuria, Vernaya, Pithecheir and Haeromys representatives  (Musser, 1979). However, because the hallux of some arboreal murids bears a nail instead of a claw, that hallux may be pseudo-opposable, rather than fully   Musser, 1979). We therefore did not use this character for ancestral reconstruction. Ancestral character state reconstructions (ASR) was based on stochastic character mapping as implemented in the make. simmap function in the R software package PHYTOOL  (Bollback, 2006; Revell, 2012). This SIMMAP approach reconstructs possible states at all ancestral nodes, accounting for the uncertainty through MCMC sampling. We used the default parameter settings and run 1,000 simulations. The make. simmap approach is similar to the empirical Bayes approach for ASR introduced by  Pagel & Meade (2004) , in which character rate models are set to ML estimates.
2. 6 PLIO. [11. 60-15. 89] 12. 48 Myr  [10. 87-14. 42] 8. 99 Myr  ** Six species of Chiropodomys are currently recognized  (Musser & Carleton, 2005). Only one species occurs in continental Southeast Asia, C. gliroides. According to Mammal Species of the World, its distribution is extremely large and extends from W China to islands of the Sunda Shelf (recorded in Burma, Thailand, Laos, Vietnam, Malay Peninsula, S Sumatra, Pulau Nias, Kepulauan Tujuh, Kepulauan Natuna, Java, and Bali; probably also occurs on other small islands of the Sunda Shelf and in Cambodia). Karyotype of a Thai specimen, R5238, was published by  Badenhorst et al. , 2009  as having 2n=42 and NFa=40. The authors reported that these results are in partial agreement with previous data concerning this very poorly documented species.
Old Pithecheir Division Old Micromys Division pasquieri was previously described from Xieng Khouang in Northern Laos but is currently considered as a subspecies of H. delacouri by  Musser ad Carleton (2005). No sequence has been published from the Vietnamese specimen, meaning that no molecular comparison could be achieved to disentangle these discrepancies. Further investigations have to be carried out to refine the taxonomy of Chiropodomys and Hapalomys. However, these taxonomic uncertainties do not challenge our results concerning the relationships of these genera with the other murine representatives nor the polyphyly of the Micromys division. b) Sequences extracted from GenBank:   The best-fit partitioning schemes (considering the three different codon positions of the four coding genes) and models of molecular evolution were deeper investigated using PARTITIONFINDER  (Lanfear et al.
Ancient DNA work was performed in an independent room dedicated to ancient DNA analysis (degraded DNA platform, Labex CeMEB), following the standard procedures and using specific equipment and personal protections (e. g. Pääbo et al. , 2004). DNA of the four Pithecheir samples was extracted at the same time than those of nine Gerbillus samples from museum. At this position all the murid species of our dataset harbour a C or a T. Fragment 2: a single successful PCR attempt for MNHN-ZM-MO 1977-251. Because of failure to reproduce this sequence, this fragment was not considered in the subsequent analyses.
We would like to acknowledge the Ambrose Monell Cryo Collection (AMCC) at the American Museum of Natural History, New York, for their support in our research. P. H. F. was funded by a Marie-Curie fellowship (PIOF-GA-2012-330582-CANARIP-RAT). ). P. -H. F. acknowledges the SYNTHESYS Foundation for funding his work in the BMNH collections (GB-TAF-2735 and GB-TAF-5026). M. P. was funded by an FRS-FNRS fellowship (Belgian Fund for Scientific Research). A. M. was supported by the Mohamed bin Zayed Species Conservation fund (Project Number: 0925478). Analyses were performed on the CBGP HPC computational platform and CIPRES portal web. This project was supported by the network "Bibliothèque du Vivant" funded by the CNRS, the Muséum National d'Histoire Naturelle, the INRA and the CEA (Centre National de Séquençage).
Wells et al. , 2007s considered in this study and GenBank accession numbers of sequences. Tissue samples provided by Dr. Ken Aplin and Dr. Jean-Pierre Quéré are housed at the Centre de Biologie et de Gestion des Populations at Montpellier, France, with a part of the CeroPath collection. Samples from Borneo (A48, O09 and N92) were collected from life captures with a biopsy punch and have not been vouchered. Supplementary information on animal captures and handling are detailed inWells et al. , 2007. Sample of Margaretamys christinae (original field number MK14) corresponds to the holotype specimen(Mortelliti et al. , 2012), deposited in the Museum Zoologicum Bogoriense-LIPI, Cibinong, Java.
Acknowledgments We thank  Ken Aplin ,  Eric Bazin ,  Alexandre Dehne-Garcia ,  Emmanuel Douzery ,  Lionel Hautier ,  Kristofer Helgen ,  Guy G. Musser  and  Kevin C. Rowe  for helpful discussions. Thanks to  Riccardo Castiglia  for processing Margaretamys specimens. We are grateful to  François Catzeflis  for his comments and access to the Montpellier mammal skeleton and tissue collection. We thank the team of the CERoPath Project (www. ceropath. org)(and specially the drivers and the students) for sample collection, in particular  Hul Vibol ,  Kim Aun ,  Kim Blasdell  and  Philippe Buchy in Cambodia, Kittipong Chaisiri in Thailand and Kone in Lao.
Additional information could be retrieved via the following database webpages: http://www. ceropath. org/ a) Information about samples handled in this study (new data) http://sci-web-001. amnh. org/db/emuwebamnh/ http://research. amnh. org/genomics/Facilities/AMCC/database/ https://science. mnhn. fr/institution/mnhn/collection/zm/item/search/form Division Genus Species Common Name Voucher Locality Collection Rattus Saxatylomys paulinae Paulina's Limestone Rat LK217 Khammouane, Laos CERoPath Rattus Saxatylomys paulinae Paulina's Limestone Rat LK218 Khammouane, Laos CERoPath Rattus Saxatylomys paulinae Paulina's Limestone Rat LK219 Khammouane, Laos CERoPath Rattus Tonkinomys daoventieni Daovantien's Limestone Rat DPL1662 (M-275575) Huu Lien District, Lang Son Province, Vietnam AMNH / AMCC Micromys Micromys minutus Eurasian Harvest Mouse 72 (MK0509 BZ02) China JP.
Rho1 and Pkc1 stabilize the septin ring Although the involvement of Rho1/RhoA in the assembly and contraction of the actomyosin ring is well established, no data linked its function to septins. We therefore tested directly the effect of Rho1 and Pkc1 on septin dynamics. The septin ring was visualized by expression of GFP-Cdc12 and its stability analyzed by FRAP. As which carries a synonymic mutation to RHO1-D72N, could suppress the temperature sensitivity of dma1 dma2 cla4-75 triple-mutant or cdc12 single-mutant cells. Expression of CDC42-D65N had no effect on cell division of dma1 dma2 cla4-75 triple-mutant and cdc12-6 single-mutant cells, whereas it was detrimental for cdc12-1 cells growing at the permissive temperature (Supplemental Figure  S2,  D-F ). Consistent with these data, GTP-locked Cdc42 negatively regulates septin polymerization in budding yeast  (Gladfelter et al.