dataesr/scientific-paragraphs-categorization huggingface dataset:
S1 ]. Optimal crystal orientation was achieved by rotating the crystal on the goniometer rotation axis until the signal-tonoise ratio of the spectrum was maximal, which implies minimization of the baseline and corresponds to the light path direction as close as possible from the normal of the crystal faces along the smaller dimension. Spectra were recorded every 500 ms after light illumination for a total acquisition time of 5 min. Devices were synchronized using the ESRF OPIOM module. Spectra within a time series were smoothed through a Savitsky-Golay filter using a polynomial function of degree 3 and a window width of 21 data points, then the average absorbance between 600 and 850 nm was subtracted from every spectrum so that each shared the same baseline. An exponential decay model was then fitted on the absorbance at 390 nm from each spectrum in a series.
X-ray diffraction data collection All diffraction data were collected at room temperature on beamline  ID30A-3 (von Stetten et al. , 2020)  at the ESRF. Each crystal was manually mounted on the goniometer and, as for experiments at icOS (see above), the humidity level was maintained at 98. 5%. In this study, 27 datasets were collected, each with a 0. 3 oscillation range, corresponding to 120 total rotation, for a total exposure time of 1. 2 s. The photon flux was $1. 2 Â 10 12 photons s À1 leading to an estimated dose per dataset, as calculated with RADDOSE-3D  (Zeldin et al. , 2013) , reported in Table  S1  of the supporting information. Between two and seven individual datasets were collected at distinct positions from a total of eight crystals. The actinic LED was triggered manually from the outside of the experimental hutch via a 5 V pulse generator connected to the LED via the patch panel of the hutch.
X-ray diffraction data processing and structure refinement Diffraction data were processed using the autoPROC pipeline  (Vonrhein et al. , 2011)  and  STARANISO (Tickle et al. , 2018). Indexing and integration were performed with XDS  (Kabsch, 2010)  in the two possible space groups (P4 3 2 1 2 and P2 1 2 1 2 1 ) using the '-symm' option in autoPROC. The integrated intensities were scaled and merged in AIMLESS  (Evans & Murshudov, 2013)  and POINTLESS  (Evans, 2011)  from CCP4  (Winn et al. , 2011). Dark, photostationary and R xxxx 00 structures were solved by molecular replacement using PHASER with the PDB entry 6qqk  (Gotthard et al. , 2019)  as the search model. Structures were completed and improved in Coot  (Emsley et al. , 2010)  before refinement with phenix. refine (Liebschner et al.
3. 3. 1. Structural differences between the ground-state component D 0 0 0 of the PS equilibrium and the D-state. A characteristic of the structure of the ground state D, determined at 1. 58 A ˚resolution at room temperature in the space group P4 3 2 1 2 (Table  S1 ), is the presence of two alternate conformations A (major) and B (minor) of the C426 side chain [Fig. 3(a) ] and a well ordered C-terminus folded into a shorthelix (Fig. S2 ). We then recorded datasets under conditions yielding the PS equilibrium, i. e. under constant illumination initiated at least 1 min before data collection. The seven resulting datasets were determined in the space group P4 3 2 1 2 at a resolution between 1. 73 and 2. 23 A ˚. We deposited the best compromise in terms of resolution, data reduction quality and L-state occupancy, which varied between 60 and 90%.
The combination of two states (D 0 and L) in the crystals made model building somewhat difficult. To facilitate manual rebuilding, and because the D and PS datasets were not isomorphous, we calculated Fourier difference maps between PS datasets and datasets recorded at early time points of the time-resolved series (see thereafter), highlighting very clearly the reorganization of side chains, whole residues and stretches of residues (Fig. 4 ). We thus obtained a representative structure of the PS equilibrium, which consists of 60 to 90% L-state structure (see Section 3. 3. 2) and 10 to 40% pseudo ground D 0state structure, which differs from the D-state structure by the conformation of C426 (one single conformation A versus conformations A and B) [Fig. 3(b) ] and a fully disordered Cterminus starting from residue 496 [Fig.
3(d) ] which propagate to the C-terminus, eventually leading to disordering [Fig. 3(e) ]. The disordering of the C-terminus is concomitant with a marked reorganization of the N-terminus spearheaded by the reorientation of D491, located at the beginning of the C-terminus (Fig. S3 ). 3. 3. 3. Crystal phase transition leading to a different ground state structure D 0 0 00 0 0. While all datasets corresponding to the ground state D and to the PS equilibrium could be indexed and reduced in the space group P4 3 2 1 2 with one monomer in the asymmetric unit, the dataset corresponding to the end of the relaxation period we probed (see Fig. S3 ), and thus to a return to the ground state, can only be indexed and reduced in the space group P2 1 2 1 2 1 with a dimer in the asymmetric unit.
Probing LOV2 dynamics by time-resolved oscillation crystallography We investigated the time-dependence of photoadduct relaxation and the existence of the crystalline phase transition by recording 1. 2 s datasets at various delays after switching off actinic illumination, thus releasing the PS equilibrium. We recorded 18 datasets corresponding to delays of 2,  3, 7, 10, 13, 21, 35, 51, 62 (Â2), 67, 72, 80, 90, 130, 166, 258, 630  and 1620 s at resolutions between 1. 65 and 2. 47 A ˚. Datasets were named R 2 00 , R 3 00,. and R 1620 00. Note that R 1620 00 corresponds to the D 00 -state mentioned in Section 3. 3. Data were best reduced in the space group P4 3 2 1 2 for all datasets recorded before 67 s and for the dataset recorded at t = 80 s (Fig. 6 ). Data were best reduced in the space group P2 1 2 1 2 1 for the dataset recorded at t = 72 s and for all datasets recorded after 90 s (Fig.
6 ). This indicates that the expected crystal phase transition occurs in the 67-80 s time window, significantly earlier and narrower than identified in our preliminary experiments. For comparative analysis purposes, all datasets were eventually reduced in the space group P2 1 2 1 2 1 , so as to be able to detect any small differ- Identification of structural rearrangements around the FMN occurring during the relaxation process. Fourier difference map calculated between R 35 0 0 and a dataset for the PS equilibrium. Positive and negative peaks are displayed as blue and dark pink meshes, respectively. The L-state (green) and D 00 -state (firebrick) models are displayed as ribbons and sticks. Alternate orientations for key residues are shown as insets. ences occurring to either molecules of the dimer in the asymmetric unit at earlier time points.
3. 4. 1. Photoadduct relaxation. The variation of unit-cell parameters with time (Table  S1 ) illustrates that datasets at individual time points are not sufficiently isomorphous with others in the series to allow for the calculation of both Fourier difference maps with a high signal-to-noise ratio and reliable extrapolated structure factors. We thus devised a refinementbased method to confidently derive the proportion of the various intermediate states (L-state and D 00 -state) at each time point. A series of models were generated with two alternate conformations (one corresponding to the L-state, one to the D 0 -state) for key residues (I403, I421, C426, L429, I446, F470, Q489) and the FMN chromophore, with respective occupancies varying from 0/100% to 100/0% in steps of 5%. For each of the R xxxx 00 datasets reduced in the space group P2 1 2 1 2 1 , each of these 21 models was subject to molecular replacement, followed by rigid body and individual B-factor refinement.
F obs À F calc electron density maps were visually inspected at sigma levels down to 2. 0 to identify the likeliest combination of occupancies (Fig. S5 ). In a second step, we investigated the presence of the minor conformation of C426 (conformation B), of the -helical C-terminus observed in monomer A of the D 00 -state, the hook-shaped C-terminus observed in monomer B of the D 00 -state and the flipping of the W467 side chain. When present, these features were added to the model, which was then subject to positional and B-factor refinement. Fig. 7 (a) illustrates the evolution of the electron density over the photoadduct during the relaxation from the PS equilibrium to the D 00 -state. The 18 datasets were obtained from distinct locations of six different crystals. The build up of the PS equilibrium in each of these crystals led to variable combinations of L-state/D 0 -state occupancies.
The fact that all datasets recorded during a second illumination step can be indexed in the space group P4 3 2 1 2 demonstrates the reversibility of the space group conversion. 8(a) ]. When determining the structures corresponding to the various R xxxx 00, we already observed the progressive reappearance of electron density on the Cterminus in the early time points, i. e. before the crystal phase transition [R 62 00 snapshot of photocycle in Fig. 8(a) ]. However, immediately after the transition and the loss of a crystal symmetry element, while one monomer shows an increased level of electron density on the C-terminus (monomer A), the second monomer (monomer B) hardly shows any [R 130 00 snapshot of photocycle in Fig. 8(a) ]. Coincidently, the conformation of the C-terminus in the former monomer is that of the -helical one, and in the latter, of the hook-shaped one.
Acknowledgements The  ESRF  is acknowledged for access to beamline ID30A-3 and facilities for molecular biology via its in-house research programme. The IBS acknowledges integration into the  Interdisciplinary Research Institute of Grenoble (IRIG, CEA). Thierry Giraud ,  Philippe Jacquet ,  Igor Melnikov  and  Melissa Saı  ¨di are acknowledged for technical help.
Protein-protein interaction data extraction for 24 Enterobacterales and all bacteria We retrieved PPI information for two key datasets from STRING database v12  [57]  using R packages Rentrez v1. 2. 2  [58] , STRINGdb v2. 0. 1  [59] , and StringR v1. 4. 0  [60]  (Fig. 1 ), in a working environment using Rv4. 0. 1  [61] , RStudio v2022. 2. 3. 492 [62] , Bioconductor v3. 11  [63]. The dataset first was for three genera from the Enterobacterales order containing: Escherichia and Shigella (n = 11), Klebsiella (n = 2) and Serratia (n = 11) (Table  S1 ). Serratia belongs to the Yersiniaceae family, whereas the others are all Enterobacteriaceae. Three other potential samples in StringDB belonging to these genera were excluded because they lacked any pOXA-48-related plasmid-sample PPIs and so had no information.
The second dataset was composed of 4363 StringDB bacterial samples (including the 24 Enterobacterales from above) with valid PPI data as outlined previously  [79]  (Fig. 1 ). Using a score threshold of 400 as per previous work  [79] , the number of proteins and their PPIs were recorded. These StringDB scores come from a range of sources, including: text mining, pathway databases, co-expression research, small-scale and high-throughput experiments, and computational predictions (chromosomal proximity, phylogenetic context and gene Fig. 1. The data sources and methods summary, read from right to left. We used PPI data from StringDB related to two datasets: one with 24 Enterobacterales (middle) and another with 4363 diverse bacterial samples (top and bottom). Top: We compared the interacting host proteins and associated PPIs for four plasmids pEK204, pEK499, pEK516 and pEC958 compared to the 24 Enterobacterales samples' PPI data to assess their PPIs.
Plasmid data retrieval and quality control The IncL pOXA-48a plasmid has been strongly associated with E. coli and K. pneumoniae  [28]. To explore this plasmid type further, we downloaded accession data for all (n = 31) NCBI NucCore entries containing "pOXA-48". Plasmid pKP112 possessed a blaOXA-48 gene and therefore was considered a valid pOXA-48 plasmid in this case. These came from the three Enterobacterales species: E. coli (n = 7), K. pneumoniae (n = 22), and Serratia marcescens (n = 2). Among these 31 sequences, there were four genetically distinct pOXA-48 isoforms, all isolated from K. pneumoniae (strains named Kp11978, KP112, Kpn-30,715/15 and K8) (Table  1 ). Among these four isoforms, pOXA-48_3071 had a blaOXA-48 gene that was not properly annotated in the GenBank entry, so it was considered as a pOXA-48-positive plasmid here.
We also obtained the unique proteins of four important plasmids linked to antibiotic resistance in E. coli: pEK204 (IncI1), pEK499 (IncFII-FIA), pEK516 (IncF) and pEC958 (IncF) (Table  S2 ). Plasmids pEC958 and pEK499 have high similarity (~92%)  [74]. To assess plasmid protein similarity, we measured the amino acid sequence similarity of the translated genes of the eight plasmids in a pairwise manner using R package Biostrings v2. 60. 2  [75]. Among the proteins shared by the pOXA-48-related plasmid pairs, 94% (132 out of 138) had a match (bitscore < -100). Among the proteins shared by pEK499, pEK516 and pEC958, 94% (130 out of 140) had a match, but pEK204's comparisons with pEK499, pEK516 and pEC958 showed less similarity (18%). Comparisons between each group (pOXA-48-related vs pEK204, pEK499, pEK516 and pEC958) showed only 22% of proteinlevel similarity for shared proteins.
The PPI information for these eight plasmids was compared with StringDB PPI data for the 24 Enterobacterales and 4363 bacterial samples above using the above packages in R v4. 0. 1 and Genbankr v1. 20. 0  [76]. We computed the number of host proteins interacting with each plasmid protein, the number of host-plasmid PPIs, and the Jaccard index of the fraction of interacting host proteins compared to the combined total of sample and plasmid proteins. The number of genes per plasmid was recorded and analysed using R package UpSetR  [77]. All p values reported in this study were corrected for multiple testing using the Benjamini-Hochberg method in R.
Interactions between fimbrial adhesin operons We focused further on pEK204's pil operon, which is associated with adhesion and has 14 genes, pilI-V  [37]. We used pEK499 as a baseline because it had the most samples with PPIs (1324 out of 4363) among the other three plasmids. We found 1060 samples had detected PPIs with both pEK204 and pEK499. We examined them using a normalised log2scaled ratio of the Jaccard indices of pEK204 versus pEK499. The pairwise Pearson correlation between 14 pil genes was determined using ppcor v1. 1  [78]  based on presence-absence data for 4377 samples from across bacteria  [79]. Genes with multiple synonyms were collapsed into a single representative. These 14 pil genes were also compared to 14 fim genes and four pap genes in the same manner. We retrieved the pil, fim and pap gene synonyms and associated Pil, Fim and Pap PPIs in the gene name and PPI data for the 4363 samples.
Results To test for excess PPI rates with different hosts and plasmids, we compared the PPIs of four pOXA-48 plasmid isoforms and four key E. coli plasmids with two sample collections whose PPI data was retrieved from StringDB. The first sample collection consisted of 24 Escherichia, Klebsiella, Serratia and Shigella samples to examine genus-level plasmid links, and the second collection had 4363 samples from across bacteria to inform on wider patterns.
W sex chromosome is absent due to the sex of the karyotyped sample. c Circular representation of bHirRus1 chromosomes. All data are plotted using 200 kbp windows and the highest values were capped for visualisation whenever necessary (marked with +). PacBio long-read coverage (A); % repeat density (B); % GC (C); CpG islands density (D); gene density from NCBI annotation (E); accelerated sites density computed with phyloP (F); conserved sites density computed with phyloP (G); conserved elements (CEs) density computed from phastCons analysis (H); coverage of bHirRus1 in the Cactus HAL alignment, i. e. number of species aligned (I). Comparison between bHirRus1 and the previous scaffold-level assembly. Compared to the previous assembly (here after 'Chelidonia', scaffold NG50 26 Mbp; Additional file 1: Table  S1 ), the VGP assembly pipeline and our subsequent manual curation increased the assembly contiguity to the chromosome level (see Supplementary Note for an extended comparison).
The remaining bHirRus1 genes were found in 2 or more individuals (grey). Seventy-nine out of the 236 genes exclusive of bHirRus1 were found with BLAST (84) in at least one individual HiFi reads (violet), and therefore not properly assembled in the HiFi-based assemblies. Marker catalogue and genome-wide density. In parallel to our phylogenomic analyses, we used bHirRus1 as reference and our high coverage HiFi WGS dataset (ds1, ~20x coverage, N = 5) to generate a comprehensive catalogue of single-nucleotide polymorphisms (SNPs; Additional file 1: Supplementary Note). We complemented this information with all the publicly available genomic data for the species (Additional file 1: Figure  S11 , Table  S24 ), including two Illumina WGS datasets (28,29) (ds2 and ds3. 1, ~6. 8x, N = 159) and four ddRAD datasets (24,25,27,28) (ds3.
2 through ds6, ~0. 07x; N = 1,162). Despite the fewer individuals in HiFi WGS, the average SNP density and distribution (Fig. 3 , light blue track; 142. 37 SNPs/10 kbp; Additional file 1: Table  S25 ) was comparable to the one computed for Illumina WGS (Fig. 3 , dark blue track; 160. 34 SNPs/10 kbp; Additional file 1: Table  S25 ), suggesting that this sequencing method yields a high and accurate reads mappability even when only small datasets are available. We also performed a coverage titration experiment (Additional file 1: Supplementary Note) and found that SNP distribution was still uniform across chromosomes even when HiFi WGS were downsampled to 5x (96. 33 SNPs/10 kbp; Additional file 1: Figure  S12 , Table  25 ). Chromosome W showed the lowest SNP density among all chromosomes (HiFi WGS 3.
16 SNPs/10 kbp; HiFi WGS 5x 1. 01 SNPs/10 kbp; Illumina WGS 1. 38 SNPs/10 kbp), in line with the fact that chromosome W is present as single copy only in females (the heterogametic sex), and it has the highest content of heterochromatin and repeat elements, hindering variant calling  (85). In contrast, we identified a higher number of SNP markers on chromosome Z (HiFi WGS 31. 8 SNPs/10 kbp; HiFi WGS 5x 2. 34 SNPs/10 kbp; Illumina WGS 53. 3 SNPs/10 kbp). As expected, ddRAD exhibited very localised peaks of SNP density (0. 8 SNPs/10 kbp; Fig. 3 , red track). Particularly, ddRAD identified an extremely low number of SNPs on chromosome Z (0. 27 SNPs/10 kbp) and no SNPs on microchromosome 33 (Additional file 1: Figure  S13 ). Opposed to previous findings in humans  (86, 87) , we detected a positive correlation between chromosome GC content and SNP density in all datasets (Additional file 1: Supplementary Note).
The guide tree was taken from TimeTree (128) (Additional file 1: Figure  S7 , Supplementary Methods). The genomes were soft-masked with WindowMasker  (123)  and RepeatMasker (124) (http://www. repeatmasker. org) (50)  and then aligned (Additional file 1: Supplementary Methods). The alignment coverage was calculated with halAlignmentDepth (129) with the --noAncestors option and bHirRus1 as target species. Neutral model estimation. PHAST v1. 5  (130)  was used in combination with the HAL toolkit  (129)  for the selection analyses. An alignment in the MAF format was extracted for each bHirRus1 chromosome from the Cactus HAL output using hal2maf  (129)  with the --noAncestors and --onlyOrthologs options. The MAFs were post-processed with maf_stream (https://github. com/joelarmstrong/maf_stream), as previously described  (57).
PhyloP analysis. To detect conserved and accelerated bases, phyloP  (130)  was run on each chromosome separately using the neutral model with LRT method and in the CONACC mode. Due to the low total branch length between the aligned species (57), no significant calls were found after the false discovery rate (FDR) (52) correction with 0. 05 as significance level. We increased the statistical power of the constraint analysis by running phyloP on 10bp windows. Briefly, the aligned coordinates of bHirRus1 in the Cactus alignment were obtained and divided into 10bp windows. PhyloP was run again on the windows (LRT method and CONACC mode), and the FDR correction at 5% was applied. Windows smaller than 10bp were discarded and windows overlapping with assembly gaps were removed. Spearman nonparametric rank test  (126)  was used to correlate chromosome size and the fraction covered by phyloP sites across all chromosomes, the KaryoploteR package (137) was used, computing its value over 40 kbp intervals (Additional file 1: Supplementary Methods).
Linkage disequilibrium analysis. Genome-wide LD decay was evaluated in all Illumina WGS datasets by calculating the r 2 coefficient using Plink v1. 9  (138) , considering all marker pairs within a 55 kbp distance. To calculate average r 2 , SNP pairs were grouped according to their distance in bins of 1 kbp (range 1-55 kbp; Additional file 1: Supplementary Methods). The same approach was used to calculate average r 2 values per chromosome group (macrochromosomes, intermediate and microchromosomes), except that values were then averaged across specific distance bins (Additional file 1: Supplementary Methods). LD scans and extended haplotype homozygosity statistics. To scan chromosomes for regions containing alleles exhibiting high local LD values, Plink v1. 9 (138) was used, considering marker pairs within a 15 kbp distance maximum.
Acknowledgments This work would have not been possible without the dedication of  Prof. Nicola Saino. We received support from: the  Italian Ministry of Education, University and Research (MIUR)  for the project  PRIN2017 2017CWHLHY  (L. G. and A. T. );  Dipartimenti di Eccellenza Program  ( 2018-2022 ) - Department of Biology and Biotechnology "L. Spallanzani'' University of Pavia  (to A. O. , L. F. and A. T. ); the  CSU Program for Education & Research in Biotechnology (CSUPERB)  (to A. B. -A. ); Howard Hughes Medical Institute  (to E. D. J. );  Samuel Freeman Charitable Trust  (to T. A. M. and A. P. M. ). The work of F. T. -N. and P. M. was supported by the  Intramural Research Program of the National Library of Medicine, National Institutes of Health. We thank the  INDACO Platform team  (a project of  High Performance Computing  at the  University of Milan , http://www.
Data availability Scripts used in this paper are available on GitHub (https://github. com/SwallowGenomics/BarnSwallow). Primary and alternate assemblies used in this study are available on NCBI under accession numbers GCF_015227805. 1 and GCA_015227805. 3. All raw data supporting the genome assembly are available on GenomeArk (https://vgp. github. io/genomeark/Hirundo_rustica/), and will also be available upon publication in SRA. The HiFi data will be made available upon publication. IsoSeq and RNAseq data are available on NCBI under the accession numbers SRR13516425, SRR13516426, SRR13516427, SRR9184408 and SRR9184409. The SNPs catalogue will be available upon publication on Dryad.
The primary curated assembly was annotated with IsoSeq and RNAseq data (Additional file 1: Table  S7 , Supplementary Methods). Karyotype reconstruction. To confirm the chromosomal structure of our assembly, a karyotype for the barn swallow was generated using a cultured cell protocol (Additional file 1: Supplementary Methods). Chromosome sizes were predicted from the karyotype images and correlated with the assembly chromosome sizes (Additional file 1: Supplementary Methods). Assembly evaluation and comparison with Chelidonia. Summary assembly statistics were computed with a script included in the VGP assembly pipeline GitHub repository (https://github. com/VGP/vgp-assembly/blob/master/pipeline/stats/asm_stats. sh). The assembly was further evaluated using BUSCO  (44, 122) , Merqury  (115) , and Hi-C contact heatmaps (Additional file 1: Supplementary Methods).