dataesr/scientific-paragraphs-categorization huggingface dataset:
A Supplementary information for optimized CryptoSMT Let a = (a 3 ,. , a 0 ), and b = (b 3 ,. , b 0 ) denote the input and output differences respectively, where a 0 , and b 0 are the least significant bits, and p = (p 2 , p 1 , p 0 ) is also used to encode the probability of transition a → b. We use the following CNF to model the differential behavior of CRAFT's S-box in the SMT model: (¬a 1 ∨a 0 ∨b 2 ∨¬b 1 ∨¬p 2 )∧(a 2 ∨¬a 1 ∨¬b 1 ∨b 0 ∨¬p 2 )∧(a 3 ∨a 2 ∨a 1 ∨¬b 3 ∨¬b 0 )∧(¬a 3 ∨¬a 0 ∨ b 3 ∨b 2 ∨b 1 )∧(a 3 ∨a 1 ∨a 0 ∨¬b 3 ∨¬b 2 )∧(¬a 3 ∨¬a 2 ∨b 3 ∨b 1 ∨b 0 )∧(a 2 ∨¬a 1 ∨b 2 ∨¬b 1 ∨¬p 2 )∧ (¬a 1 ∨a 0 ∨¬b 1 ∨b 0 ∨¬p 2 )∧(¬a 2 ∨¬a 0 ∨¬b 2 ∨¬b 0 ∨¬p 2 )∧(a 1 ∨¬b 3 ∨¬b 2 ∨¬b 0 )∧(¬a 3 ∨ ¬a 2 ∨¬a 0 ∨b 1 )∧(p 1 ∨¬p 0 )∧(¬p 2 ∨p 0 )∧(¬b 1 ∨p 0 )∧(a 2 ∨¬a 0 ∨b 1 ∨p 2 )∧(a 1 ∨¬b 2 ∨b 0 ∨p 2 )∧ (¬b 3 ∨p 0 )∧(b 2 ∨¬b 1 ∨b 0 ∨¬p 2 )∧(a 1 ∨b 1 ∨¬b 0 ∨p 2 )∧(¬a 2 ∨a 0 ∨b 1 ∨p 2 )∧(¬a 3 ∨b 1 ∨b 0 ∨p 2 )∧ (¬a 2 ∨¬a 0 ∨b 3 ∨b 0 ∨p 2 )∧(¬a 1 ∨p 0 )∧(a 2 ∨a 0 ∨b 2 ∨b 1 ∨b 0 ∨¬p 1 )∧(a 2 ∨a 1 ∨a 0 ∨p 2 ∨¬p 0 )∧ (¬a 2 ∨a 0 ∨¬b 2 ∨¬b 0 ∨p 2 )∧(a 1 ∨b 2 ∨¬b 0 ∨p 2 )∧(a 2 ∨a 0 ∨¬b 2 ∨¬b 0 ∨¬p 2 )∧(¬a 2 ∨¬a 0 ∨b 2 ∨ ¬b 0 ∨p 2 )∧(¬a 3 ∨a 0 ∨b 2 ∨¬b 0 ∨p 2 )∧(a 3 ∨¬a 1 ∨¬b 3 ∨¬b 1 ∨p 2 )∧(a 2 ∨¬a 0 ∨¬b 2 ∨¬b 0 ∨p 2 )∧ (¬a 1 ∨b 3 ∨¬b 2 ∨¬b 1 ∨¬b 0 ∨p 2 )∧(a 2 ∨¬a 1 ∨b 3 ∨b 2 ∨¬b 1 )∧(¬a 1 ∨a 0 ∨b 3 ∨¬b 2 ∨b 1 ∨¬p 2 )∧ (a 2 ∨¬a 1 ∨b 3 ∨b 1 ∨¬b 0 ∨¬p 2 )∧(a 1 ∨¬b 2 ∨¬b 1 ∨¬b 0 ∨¬p 2 )∧(b 3 ∨b 2 ∨b 0 ∨¬p 2 )∧(a 3 ∨a 2 ∨ a 0 ∨¬p 2 )∧(¬a 2 ∨¬a 1 ∨¬a 0 ∨b 1 ∨¬p 2 )∧(¬a 3 ∨a 2 ∨¬a 0 ∨¬b 2 ∨¬b 1 ∨b 0 )∧(a 2 ∨a 0 ∨¬b 2 ∨ ¬b 1 ∨b 0 ∨p 2 )∧(¬a 2 ∨¬a 1 ∨a 0 ∨b 3 ∨b 0 )∧(¬a 2 ∨a 0 ∨¬b 3 ∨b 2 ∨p 2 )∧(a 2 ∨¬a 0 ∨¬b 3 ∨b 0 ∨p 2 )∧ (¬a 1 ∨a 0 ∨¬b 3 ∨b 2 ∨¬b 0 ∨¬p 2 )∧(a 2 ∨¬a 1 ∨¬b 3 ∨¬b 2 ∨b 0 ∨¬p 2 )∧(¬a 0 ∨¬b 3 ∨¬b 2 ∨b 0 ∨p 2 )∧ (a 3 ∨¬a 2 ∨a 1 ∨¬b 1 ∨b 0 ∨¬p 2 )∧(a 3 ∨a 1 ∨¬a 0 ∨b 2 ∨¬b 1 ∨¬p 2 )∧(¬a 2 ∨¬a 0 ∨b 2 ∨b 1 ∨b 0 )∧ (a 3 ∨a 2 ∨¬b 2 ∨¬b 0 ∨p 2 )∧(¬a 3 ∨¬a 2 ∨a 1 ∨a 0 ∨b 3 ∨b 2 ∨¬p 2 )∧(a 3 ∨a 1 ∨a 0 ∨¬b 3 ∨b 1 ∨¬b 0 )∧ (a 3 ∨a 2 ∨a 1 ∨¬b 3 ∨¬b 2 ∨b 1 )∧(¬a 3 ∨a 1 ∨¬a 0 ∨b 3 ∨b 1 ∨b 0 )∧(¬a 3 ∨¬a 2 ∨a 0 ∨b 2 ∨¬b 1 ∨¬b 0 ) Similar to the Boolean function which is used to model the differential behaviour of an Sbox, another Boolean function can be constructed to model the linear behaviour of the given Sbox, according to the related table of squared correlations.
If a = (a 3 ,. , a 0 ), and b = (b 3 ,. , b 0 ) denote the input and output linear masks respectively, where a 0 , and b 0 are the least significant bits, and p = (p 3 , p 2 , p 1 , p 0 ) is used to encode the squared correlation of transition a → b, we use the following CNF to model the linear behavior of CRAFT's S-box in the SMT model: ( p 3 ∨p 2 )∧(p 1 ∨ p 0 )∧(p 3 ∨ p 2 )∧( p 2 ∨p 0 )∧( b 1 ∨p 0 )∧(b 3 ∨b 2 ∨b 1 ∨b 0 ∨ p 1 )∧( b 3 ∨p 0 )∧ (a 3 ∨a 2 ∨a 1 ∨a 0 ∨ p 0 )∧(a 3 ∨a 1 ∨b 3 ∨ b 0 ∨p 2 )∧(a 1 ∨a 0 ∨ b 2 ∨b 1 ∨p 2 )∧( a 1 ∨p 0 )∧(a 3 ∨ b 3 ∨ b 2 ∨b 1 ∨ b 0 )∧( a 3 ∨ a 1 ∨b 2 ∨b 1 ∨p 2 )∧(a 0 ∨b 2 ∨ b 1 ∨ b 0 ∨p 2 )∧( a 3 ∨ a 0 ∨ b 3 ∨b 0 ∨p 2 )∧ (a 0 ∨ b 3 ∨ b 2 ∨ b 1 ∨p 2 )∧( a 0 ∨b 2 ∨b 1 ∨b 0 ∨p 2 )∧(a 2 ∨ a 0 ∨ b 3 ∨ b 1 ∨p 2 )∧(a 2 ∨a 1 ∨b 1 ∨ b 0 ∨ p 2 ) ∧ ( a 3 ∨ p 0 ) ∧ (a 3 ∨ a 1 ∨ b 2 ∨ b 1 ∨ b 0 ∨ p 2 ) ∧ (a 3 ∨ a 1 ∨ a 0 ∨ b 2 ∨ b 1 ∨ p 2 ) ∧ ( a 3 ∨ a 1 ∨ b 3 ∨ b 0 ∨ p 2 ) ∧ (a 2 ∨ a 1 ∨ b 3 ∨ b 1 ∨ b 0 ∨ p 2 ) ∧ (a 3 ∨ a 2 ∨ a 0 ∨ p 2 ) ∧ (a 2 ∨ a 0 ∨ b 2 ∨ b 1 ∨ p 2 ) ∧ (a 3 ∨ a 2 ∨ a 1 ∨b 1 ∨ b 0 ∨p 2 )∧( a 3 ∨ a 2 ∨a 0 ∨b 2 ∨b 0 ∨p 2 )∧( a 3 ∨a 1 ∨ a 0 ∨ b 2 ∨ b 1 ∨p 2 )∧ (a 3 ∨a 1 ∨b 3 ∨ b 2 ∨p 2 )∧(a 3 ∨ b 3 ∨ b 2 ∨b 0 ∨ p 2 )∧( a 2 ∨ a 0 ∨b 2 ∨b 0 ∨ p 2 )∧( a 3 ∨a 2 ∨ a 0 ∨ b 3 ∨ p 2 )∧( a 3 ∨ a 2 ∨a 0 ∨b 3 ∨ p 2 )∧( a 3 ∨ a 1 ∨ b 3 ∨b 1 ∨p 2 )∧( a 3 ∨ b 3 ∨b 2 ∨ b 0 ∨p 2 )∧( a 2 ∨ b 2 ∨b 1 ∨b 0 ∨p 2 )∧(a 3 ∨ b 3 ∨b 2 ∨ b 0 ∨ p 2 )∧(a 2 ∨a 0 ∨b 2 ∨b 0 ∨ p 2 )∧( a 2 ∨ a 0 ∨ b 2 ∨ b 0 ∨ p 2 )∧ (a 2 ∨ a 0 ∨ b 2 ∨ b 0 ∨ p 2 ) ∧ (a 3 ∨ a 2 ∨ a 0 ∨ b 3 ∨ b 2 ∨ b 0 ∨ p 2 ) ∧ (b 3 ∨ b 2 ∨ b 0 ∨ p 2 ) ∧ ( a 3 ∨ a 2 ∨ a 1 ∨ a 0 ∨ b 3 ∨ b 1 ∨ p 2 ) ∧ ( a 2 ∨ a 1 ∨ a 0 ∨ b 3 ∨ b 1 ∨ p 2 ) ∧ (a 2 ∨ a 1 ∨ a 0 ∨ b 3 ∨ b 2 ∨ p 2 ) ∧ (b 3 ∨ b 2 ∨ b 0 ∨ p 2 ) ∧ (a 3 ∨ a 2 ∨ a 0 ∨ b 1 ) ∧ ( a 2 ∨ a 1 ∨ b 3 ∨ b 1 ∨ b 0 ∨ p 2 ) ∧ (a 3 ∨ a 2 ∨ a 0 ∨ p 2 )∧(a 1 ∨a 0 ∨ b 3 ∨ b 1 ∨p 2 )∧(a 3 ∨ a 2 ∨ a 1 ∨ a 0 ∨ b 2 ∨ b 0 )∧(a 3 ∨ a 2 ∨ a 0 ∨b 3 ∨b 2 ∨ b 0 )∧( a 3 ∨a 2 ∨ a 0 ∨ b 1 ∨b 0 ∨p 2 )∧(a 2 ∨a 0 ∨ b 3 ∨ b 2 ∨b 0 ∨p 2 )∧( a 1 ∨a 0 ∨ b 3 ∨b 2 ∨ b 0 ∨p 2 ) CryptoSMT, uses STP  [HMS] , as the default SMT solver to solve the obtained SMT problem, but it also supports another SMT solver, called Boolector  [NPB15].
Acknowledgments The authors gratefully thank the use of  School of Computer Science, Institute for Research in Fundamental Science (IPM)  as the computations were partially done there. We would like to thank  Christof Beierle  for his invaluable comments and suggestions in preparing the final draft of this paper. We would like also to thank all the anonymous reviewers of ToSC for their valuable comments which helped us to improve the presentation of the work significantly. We would like also to thank  Hadi Soleimany  for his invaluable comments and suggestions in preparing this paper. We would like also to thank the designers team of CRAFT, specially  Shahram Rasoolzadeh , for their valuable feedback during our communications. The work of the second author is supported by the  ANR (DeCrypt   ANR-18-CE39-0007 ).
pacificus. To investigate the phylogenetic relationships among Oryctes species from the Mascarene Islands and between them and Marronus , we used Illumina sequencing and 10X Genomics to refine the draft genome of O. borbonicus , and generated a new draft genome of Marronus. Furthermore, we used minute amounts of tissue from pinned beetle museum specimens to generate for the first time genome-wide data from extinct insect species from Mauritius and Rodrigues. The combined analysis of extant and extinct genomes permitted us to infer phylogenetic relationships, divergence times, and the colonization history of Oryctes beetles of the Mascarene Islands.
De novo assembly of Reunion's Oryctes borbonicus and Marronus borbonicus Despite the large number of beetle species (~400,000), genome sequences of only 20 species have been reported  10, 11. Available genomic data includes a draft assembly of O. borbonicus  12. Here, we sequenced DNA from two specimens of O. borbonicus and Marronus , the two extant endemic beetles from Réunion, on the 10X Genomics platform to improve the draft genome of O. borbonicus , and to generate a draft genome of Marronus. Both libraries were individually sequenced on the Illumina HiSeq 3000 platform yielding 330 million paired end reads (2x150bp), which translates into roughly 120X coverage per genome. These data were assembled into 411 Mb for O. borbonicus and 413 Mb for Marronus (Supplementary Table  1 ). In comparison to the previously published draft genome of O.
Evolutionary relationships and divergence times of Oryctes spp. and Marronus borbonicus To establish the evolutionary relationship among all beetle species, we first mapped the sequenced reads to the updated O. borbonicus draft genome, which provides a common coordinate system for all beetle species. To ascertain single nucleotide polymorphisms (SNPs) for each sample, we randomly selected one base at each segregating site. This method, also known as "pseudo-haploidization", is commonly applied to low-coverage aDNA datasets, allowing the estimation of genetic relatedness from low-coverage data  21  (See Materials and Methods). Implementing this methodology, we identified a total of 1,541,675 SNPs. Initially, we summarized the genetic variation among beetle species using principal components analysis (PCA), which showed that PC1 does not separate species by genera but, instead, clusters together Oryctes and Marronus beetles from Réunion and Mauritius, and separates the species from Mayotte and Rodrigues ( O.
Here, we took such a retrospective approach to study the phylogenetic relationships among extant and extinct beetles from the Mascarene Islands. In contrast to most aDNA studies, which usually investigate species that went extinct thousands (e. g. mammoths  32  ) or hundreds of years ago (e. g. moas  33  ), we studied species that went extinct only a few decades ago. Comparisons between recent extinctions and closely-related extant relatives will shed light on the genetic and ecological factors driving either extinction or persistence of species. To generate genome-wide datasets from historical pinned insect museum specimens, we used state-of-the-art ancient genomics methods including the use of preventive measures to avoid contamination by exogenous DNA, an extraction protocol that enriches for short DNA fragments  18  , and library preparation methods tailored for aDNA  20, 34.
Library preparation, sequencing and assembly The preparation of the linked-read sequencing library was done as described previously  37. Raw sequences were assembled into draft assemblies with the help of SuperNova 38 (v. 2. 0. 1). SuperNova was run on the full sequencing data set as well as multiple downsampled read sets. In terms of assembly contiguity, the best results were obtained using around 170 million single reads, which translates into roughly 60X coverage per genome. Assembly quality was assessed using an approach based on benchmarking of universal single copy orthologs (BUSCO  39  ). The raw genome assemblies as well as a data set of 1658 orthologous genes from 42 insect species (insecta_odb9) were taken as input of the program run_BUSCO. py (v. 3. 0. 1). To analyse the coverage profile of the previous and current O.
The resulting ORFs and protein sequences were mapped against their reference assemblies by the protein2genome program of the exonerate package (version 2. 2. 0, --bestn 1 --dnawordlen 20 --maxintron 20000 )  44. Among all gene annotations which share an identical exon, the annotation resulting in the longest protein product was taken as representative annotation. Pairwise BLASTP (v. 2. 6. 0, e-value 0. 00001) searches were done between proteins of Marronus and O. borbonicus and best reciprocal hits were extracted to estimate the median protein sequence identity between orthologous gene pairs. For further comparative genomic analyses, we obtained protein sequences for Nicrophorus vespilloides and Aethina tumida from the i5k website (https://i5k. nal. usda. gov/, accessed July, 12th 2019)  45  , Anoplophora glabripennis , Dendroctonus ponderosae , Tribolium castaneum from Ensembl Metazoa (release 44), Protaetia brevitarsis , Pyrocoelia pectoralis , Hycleus cichorii and Hycleus phaleratus from GigaDB  [46] [47] [48]  , Onthophagus taurus from the U.
Identification of segregating positions To achieve a comparable coverage between historical and fresh samples, four million raw reads from both fresh O. borbonicus and Marronus were subsampled with the program samtools view (v. 1. 4)  41. Together with the museum mapped reads, we created a single bam file with the program samtools merge (v. 1. 4)  41  and used it as the input for the discovery of variant positions using the program bsh-denovo  57. Only positions with full information were considered (flag -m = 1 ) and the alternative allele was randomly sampled (flag -a = 0. 001 ). To account for the effect of the Minimum Allele Frequency (MAF) in the evolutionary relationships, we filtered the positions with both 1/7 and 2/7. Since a MAF of 1/7 favours variant sites privative to the more genetically distinct individuals, we used a MAF of 2/7 for all downstream analyses (Supplementary Figures  5  and 6 ).
Phylogenetic analysis A matrix of pairwise Hamming distances between the individuals was calculated using Plink (v. 1. 9)  58  and PCA was computed with the function prcomp from the R package stats V. 3. 4. 4 59. Neighbor-net analysis and NJ tree calculations were performed using SplitsTree (v. 4. 14. 6) 60. To test the phylogenetic relations among the species, we used D -statistics  21, 22. Based on the results of the previous analysis, we fixed Oryctes mayottensis as outgroup species while testing for the relations between Marronus and the rest of the beetles denoted as A and B in the following configuration: D (((A, B), Marronus ), O. mayottensis ). D -statistics were calculated using popstats  61. Finally, we formally assessed the phylogeny of the scarab beetles by both a Maximum Likelihood and Bayesian-based methods.
Acknowledgements We would like to thank  R. Gutaker  for laboratory assistance, including the implementation of the DNA extraction protocol;  E. Reiter  for access to clean-room facilities and technical support;  Vrinda Venu  for technical support during linked-read library preparations;  F. Jones  for useful input during linked-read the library preparations and genome assembly;  K. Pruefer ,  A. Andres  and members of the  Burbano and Sommer laboratories  for useful discussions and input on data analysis;  D. Weigel  for supporting S. Latorre's visit to London during the final stages of the project; and  A. Andres ,  R. Gutaker ,  T. Karasov  and  M. Werner  for comments on the manuscript. We are also indebted to the  Parc national de la Réunion  and the  Office National des Forets on Réunion  for long-term support and permits; the  CIRAD at St.
Data availability Both sequencing raw data and genome assemblies for O. borbonicus and M. borbonicus have been uploaded to the European Nucleotide Archive (ENA) under the study accession number PRJEB34604. Museum specimens raw data for both UDG and non-UDG treated libraries, have been uploaded under the study accession number PRJEB36751 (Supplementary Table  2 ). Pipelines and scripts are available at: https://gitlab. com/smlatorreo/museum_phylogenomics_extinct_oryctes_beetles.
Bow n genome assembly and annotation The bow n genome was sequenced from a single adult male with a de novo genome assembly constructed using Meraculous  28  and further scaffolded with Chicago  29  and Hi-C approaches  30  using the HiRise software pipeline  29. The nal assembly (N50 = 41. 2 Mb) consists of 1,958 scaffolds including 23 superscaffolds that contain 99% of the assembly (Supplementary Fig. 1 ) and match bow n's chromosome number  16, 31  , consistent with a chromosome-level genome assembly. The nal assembly (AmiCal1, NCBI accession PESF00000000; Supplementary Table  1 ) is largely complete as reported by CEGMA  32  (98. 3%: 244/248 eukaryotic CEGs) and BUSCO  33  (100%: 303/303 eukaryotic BUSCOs). The bow n genome consists of ~22% repeats (Supplementary Table  2 ) with a transposable element pro le overall similar to that of spotted gar (repeat content ~21%  7  ).
3 ). Their involvement in the formation of both tooth enamel and scale ganoin in gar supports that these two mineralized structures evolved from a common genetic program  7, 66. Since bow n lacks ganoin, this suggests that gene regulatory shifts in enam and ambn have occurred in the bow n lineage that silenced their expression during scale development but not dental enamel formation. The total number of bow n SCPP genes (22) is considerably smaller than that of gar, which has the largest known SCPP gene repertoire among vertebrates (38)  7, 64. All 22 bow n SCPP genes have a gar ortholog. In contrast, orthologs of 16 gar SCPP genes could not be found in bow n, 9 of which are located in a cluster on gar chromosome LG2 syntenic to a reduced gene cluster on bow n superscaffold 9 (Fig. 3 ). Expression of most gar LG2 SCPP genes was weak or undetectable in tooth germs but strong in scale-forming skin  7.
Chromatin pro ling through bow n development connects gene regulation across vertebrate morphologies To increase the power and utility of the holostean genome for comparative studies on vertebrate gene regulation, we used ATAC-Seq  67  to generate an atlas of open chromatin regions (OCRs) from six developmental stages of wild-caught bow n embryos and larvae, from the conserved phylotypic stage onwards towards the end of the described larval development  68  (Supplementary Figs. 12-13, Supplementary Note 6). We identify a total of 163,771 OCRs, of which 80% (132,119) are non-coding OCRs (ncOCRs), and annotate their genomic feature location and nearest gene with HOMER  69  (Supplementary Tables  14 15 16 ). Adding RNA-Seq transcriptomes from the same stages, our dataset provides a rich resource for exploring the correlation between chromatin accessibility of putative gene regulatory elements and gene expression exempli ed by bow n ncOCRs overlapping key enhancers active during development of a variety of vertebrate tissues such as brain  70  , heart  23  , anterior and posterior n/limb  [71] [72] [73]  , and lungs  73, 74  (Fig.
4 ). Conserved Non-coding elements (CNEs) and Ultra Conserved Elements (UCEs) are used to identify candidate enhancers and genetic loci for phylogenetic inference  7, 9. We nd that 33% of both gar-centric vertebrate CNEs 7 (21,279/64,608) and bow n UCEs 9 (122/366) intersect with bow n ncOCRs (Supplementary Table  17 ), thus many CNEs/UCEs are likely gene regulatory during bow n development. To further investigate the comparative e cacy of our ATAC-Seq dataset, we identi ed the orthologous position of experimentally con rmed mammalian enhancers  70  in the bow n genome using sequence conservation (Supplementary Tables  18 19 , Supplementary Note 6). Orthologs of 61% of human enhancers (600/989) were found in bow n and over half (52%; 314/600) overlap with bow n ncOCRs. In contrast, orthology of only 45% (449/989) of human enhancers could be established in the zebra sh genome (Supplementary Table  18 ), illustrating the usefulness of the slowly evolving and 'unduplicated' bow n genome to connect accessible, non-coding, regulatory regions from human to sh.
The evolution of the vertebrate Hox14 paralog group exhibits unique patterns of conservation, loss, and pseudogenization. Members of this paralogy group are absent from tetrapods and teleosts, but present in lamprey, cartilaginous shes, paddle sh, sturgeon, and gar  7, 39, [79] [80] [81]. Gar hoxd14 is a pseudogene  7  and we nd sequence conservation with bow n within the intergenic region between evx2 and hoxd13. A large number of bow n pectoral n bud RNA-Seq reads (see below) align to this region, which also shows open chromatin status (Supplementary Fig. 15 ). We cloned two different hoxd14 transcripts from bow n pectoral n bud cDNA (Figure  5B ). RNA in situ hybridization revealed that bow n hoxd14 is expressed in stage 26 pectoral n buds in a posterior mesenchymal domain (Figure  5C ) similar to paddle sh  81.
Here, we have identi ed putative enhancers for this non-model species and illustrate that our ATAC-Seq dataset can be easily connected to orthologous enhancers in sh and more distant vertebrate lineages. Bow n not only informs genome evolution in holostean shes, but also offers valuable insights into the genomic basis of its archetypical anatomy and the many developmental and physiological phenotypes in raynned shes. While this species represents a once large taxonomic group that is now mostly extinct and thus lost for studying genomic diversity, the bow n genome adds a major sequenced branch for genetic and developmental exploration to the sh tree of life. Bow n and gars have persisted for millions of years. Fortunately, the negative perception of holosteans as "trash shes"  103  is changing to include greater appreciation for their evolutionary, ecological, and cultural importance  104  and, as shown here, their signi cance for understanding vertebrate genome biology.
Genome sequencing and assembly. DNA was extracted from blood of a single wild male, collected from the Atchafalaya River Basin, Louisiana, USA (Supplementary Note 1). A de novo assembly was constructed using a paired-end sequencing library (mean assembly-based insert size ~410 bp) with Meraculous v2. 2. 2. 5  28  (kmer size = 55). The input data consisted of 433. 5 million read pairs sequenced from the paired-end library, totaling 122 Gbp after trimming for quality, sequencing adapters, and mate pair adapters using Trimmomatic v0. 38  107. A Chicago library was prepared as described  29. Brie y, ~500ng of HMW gDNA (mean fragment length = 50Kb) was reconstituted into chromatin in vitro and xed with formaldehyde. Fixed chromatin was digested with DpnII, the 5' overhangs lled in with biotinylated nucleotides, and free blunt ends were ligated.
After ligation, crosslinks were reversed, and the DNA puri ed from protein. Puri ed DNA was treated to remove biotin that was not internal to ligated fragments. The DNA was sheared to ~350 bp mean fragment size and sequencing libraries were generated using NEBNext Ultra enzymes and Illumina-compatible adapters. Biotin-containing fragments were isolated using streptavidin beads before PCR enrichment of each library. The libraries were sequenced on an Illumina HiSeq platform to produce 527 million 2x151 bp paired end reads, which provided 22,887x physical coverage of the genome (1-50kb pairs). The input de novo assembly, shotgun, Chicago library, and HiC library reads were used as input data for HiRise  29  to scaffold genome assemblies with an iterative analysis. First, Shotgun and Chicago library sequences were aligned to the draft input assembly using a modi ed SNAP read mapper [http://snap.
cs. berkeley. edu]. The separations of Chicago read pairs mapped within draft scaffolds were analyzed by HiRise to produce a likelihood model for genomic distance between read pairs. The model was used to identify and break putative misjoins, to score prospective joins, and make joins above a likelihood threshold. After aligning and scaffolding Chicago data, Dovetail HiC library sequences were aligned and scaffolded following the same method. After scaffolding, shotgun sequences were used to close gaps between contigs to generate the nal genome assembly (AmiCal1). Repeat analysis. A custom bow n repeat database was constructed using Repeat Modeler v1. 0. 8  108  and combined with custom repeat libraries for gar  7  , platy sh 109 , coelacanth  110  , and all repeats from the Vertebrata RepBase  111.
These repeat elements were input to RepeatMasker 112 within MAKER v2. 31  35. Repeat proteins were identi ed by searching against a library packaged with MAKER via RepeatRunner  113. Gene annotation. Protein-coding genes were annotated with a bow n reference transcriptome from multiple adult tissues  7, 34  as evidence. The EST2genome function in MAKER v2. 31  35  was used identify putative bow n genes based on BLAST  114  and Exonerate 115 transcript alignments. Best scoring genes with an Annotation Edit Distance of 0. 2 or less were used to train Hidden Markov Models with SNAP  116  and AUGUSTUS 117 as described  118. Ensembl and RefSeq protein sequences from other vertebrate species were used as additional evidence: gar (LepOcu1), coelacanth (LatCha1), mouse (GRCm38. p5), chicken (Gallus_gallus-5.
0), human (GRCh38. p10), Xenopus (JGI 4. 2), anole lizard (AnoCar2. 0), zebra sh (GRCz10), medaka (HdrR), arowana (GCA_001624265. 1 ASM162426v1), and elephant shark (GCA_000165045. 2 Callorhinchus_milii-6. 1. 3). Proteins were aligned to the genome with BLAST and Exonerate, guiding gene predictions by HMMs (from SNAP and AUGUSTUS) in the MAKER work ow. MAKER output all predicted genes with and without transcript and protein evidence (MAKER-Max). Pfam protein domains  119  were identi ed within the MAKER-Max gene set using HMMER v3. 0b3 (hmmrscan evalue < 1e-5)  120. MAKER-Max genes with transcript or protein or Pfam domain support were retained as the nal MAKER-Standard gene set  121. We ran OrthoFinder v1. 1. 3  36 (fastME distance method: -t 20 -M msa -A mafft -T FastTree) to identify orthologous genes between bow n and other vertebrates using protein sequences of the longest isoforms from the same species set used for MAKER annotation.