dataesr/scientific-paragraphs-categorization huggingface dataset:
Material examined. Remarks. The collected specimen USNM 1618844 closely resembles the description of C. donmoorei from the Virgin Islands (Mitchell-Tapping 1979), however microsculptural data for comparison is missing. Our molecular data suggests the species identity among specimens with less separated, strongly flattened rings and almost vanishing interspaces (e. g. , in juvenile USNM 1618857). The same has been observed for the confusingly similar species C. quadratum,  Carpenter (1855 Carpenter ( -1857: 322, pl. 34, fig. 370): 322, pl. 34, fig. 370). It can also exhibit a considerable variety of shell morphologies  (Lightfoot 1993a) , however it origins from the Eastern Pacific. And a second highly similar species, C. regulare (see above) is clearly distinguished herein based on molecular data.
The separate species status of C. strangulatum and C. teres (see below) is not supported via our molecular species delineation (see Fig. 4 ). Both are sister clades in phylogenetic analyses (see Fig. 3 ), but the monophyly of both lineages is not reflected on mitochondrial 16S rRNA (Fig. 4 ). Both species can be distinguished by morphological features (i. e. , a noticeably more pronounced shell structure and a slimmer mucro), but share a unique microsculptural pattern (Fig. 7D ). We currently lack comparative data on COI to evaluate whether the results in species delineation on 16S rRNA present a case of incomplete lineage sorting in this recent split between the two sister species or both belong to one genetically and morphologically diverse species. Due to this lack of data, we currently refrain from synonymizing the two yet existing species until more data is available to text species boundaries and the degree of intraspecific variability in shell morphology.
Taxonomic consequences for Caecidae and the fate of Meioceras The Caecidae are currently classified in ten genera (MolluscaBase 2019) of which two, Caecum and Meioceras, can be found in the Central American region. We investigated two species classified as Meioceras and 15 Caecum species, including one species new to science (C. invisibile sp. nov. ), and two candidate species (MOTU I and II). Three individuals that were originally assigned to Meioceras are resolved among species of the genus Caecum in our molecular phylogenetic analyses and, moreover, have independent evolutionary origins within Caecum (Fig. 3 ). Our data confirms the existence of at least two valid Meioceras species (i. e. , M. nitidum and M. cubitatum), which however, based on our data should be reassigned genus Caecum.
The molecular analyses presented in this study show that barcoding markers (i. e. , partial mitochondrial COI and 16S rRNA genes) are a valuable tool to address the challenges of caecid taxonomy and that molecular species delineation analyses can reliably identify groups of closely related specimens, therewith providing objective data on intraspecific variability of shell characters. Above all, they enable an unambiguous assignment of juvenile forms in different growth stages to their fully developed adult morphologies (see e. g. , C. heptagonum in Fig. 5G, C. pulchellum and C. cf. teres in Fig. 7A, D ). Based on a purely morphological approach, these juveniles would have remained unidentified and unaccounted for in biodiversity data, and their contribution to caecid diversity would have been lost.
However, in some cases, juveniles could not be matched to their adult counterparts using molecular data since we had no adult animals in our sample. These taxa identified by the molecular data could not be named (e. g. , Caecum sp. MOTU II). These examples highlight, how the successful identification of juveniles lacking morphological diagnostic features by means of their genetic fingerprints requires an extensive barcode library of Central American Caecidae as a taxonomic reference. The barcodes of the morphospecies investigated here are the first contribution to such a reference library that can help to provide a baseline and enhance future identification. In general, the poor taxonomic coverage of gastropods and marine invertebrates in public molecular databases such as NCBI GenBank has been identified as a major obstacle to making effective use of molecular barcoding approaches (e.
Many thanks to João Brazão and Gianluca De Moro at the Centro de Ciências do Mar (CCMAR) Portugal for their support in molecular phylogenetic analyses. The SNSB-Zoological State Collection (ZSM), Munich, Germany, the Smithsonian Natural History Museum, Washington D. C. , USA and the Muséum national d'Histoire naturelle Paris, France generously contributed specimens, DNA extracts and sequences. Sampling in Belize and Panama was supported by facilities of the Smithsonian Institution and funded by a Smithsonian Institution Marine Science Network award to JLN (Belize 2010, Panama 2010, 2011) and by Global Genome Initiative (GGI) Award (Grant No. GGI-Rolling-2015-020) to FL. For the material contributed by the Muséum national d'Histoire naturelle Paris we thank the crew of the Madibenthos Survey for collecting the material and preserving the specimens.
List of investigated Caecidae specimens, museums numbers (ZSM: SNSB-Bavarian State Collection, MNHN: Muséum National d'Histoire Naturelle, USMN: Smithsonian Institution), and NCBI GenBank accession numbers of sequenced genes and the type of voucher of the material of Caecidae analyzed in the present study. An asterisk (*) marks individuals used for SEM scans.
Species Field-code Locality code Specimen catalog number Voucher GenBank number COI 16S rRNA 28S rRNA Caecum cf. PA_A07 PA14 USNM 1618864 DNA MT727068 MT704287 MT731721 strangulatum Caecum cf. PA_11B PA14 ZSM-Mol-20200028 DNA* MT704282 MT731716 semilaeve Caecum cf. PA_30C PA23a ZSM-Mol-20200034 DNA* MT704285 MT731719 semilaeve Caecum sp. PA_H05 PA15 USNM 1618862 DNA MT704292 MT731728 Caecum sp. PA_E06 PA14 USNM 1618885 DNA MT704288 MT731723 Caecum sp. PA_F06 PA14 USNM 1618886 DNA MT727071 MT704290 MT731725 Caecum sp. PA_H06 PA14 USNM 1618863 DNA MT727073 MT704293 Caecum pulchellum SL_01 SL1 ZSM-Mol-20090485 DNA* MT727074 MT704300 MT731729 Caecum cooperi Gu12_20 GS32 MNHN- DNA, MT704297 MT731713 IM-2019-32 shell* Caecum cf. Gu12_06 GM01 MNHN- DNA, MT704294 MT731710 clathratum IM-2019-17 shell* Caecum debile Gu12_15 GS32 MNHN-IM-2019- DNA, MT704295 MT731711 27a shell* Caecum debile Gu12_16 GS32 MNHN-IM-2019- DNA, MT704296 MT731712 27b shell Meioceras nitidum Ma16_01 AB102 MNHN-IM-2013- DNA, MT704298 MT731714 2087a shell* Meioceras nitidum Ma16_02 AB102 MNHN-IM-2013- DNA, MT704299 MT731715 2087b shell Meioceras cubitatum CBC_44 CBC15 USNM 1618851 DNA MT727067 MT731709.
Egger & Jörger, sp. nov. DNA bank: r462p14f2t91; GenBank: MT727054, MT704267, MT731696; ZSM- Mol-20200109. Belize • 2; same data as for holotype; ZSM-Mol-20200111, ZSM- Mol-20200112. Other material Belize • 10; same data as for holotype; DNA voucher; GenBank: MT727056-MT727065, MT704269-MT704279, MT731698- MT731707; USNM 1618839, USNM 1618840, USNM 1618841, USNM 1618842, USNM 1618843, USNM 1618846, USNM 1618847, USNM 1618848, USNM 1618849. Panama • 1; Bocas del Toro; 9. 2140, -81. 9318; depth 8. 5 m; 5 Jun 2010; USNM BRS2010 exped. ; Stat. BRS104; DNA voucher; GenBank: MT727049, MT704264, MT731689; USNM 1618856. • 1; Bocas del Toro; 9. 3507, -82. 1724; depth 3 m; 13 Jun 2010; USNM BRS2010 exped. ; Stat. BRS200; DNA voucher; GenBank: MT727052, MT731694; USNM 1618859. http://zoobank. org/4183679F-44F4-4817-A2E1-7325687E5F0A Material examined.
Holotype Belize • 1 (Fig. 5O-R); Carrie Bow Cay; 16. 8015, -88. 0790; depth 10 m; 14 Jan 2010; USNM Belize2010 exped. ; Stat. CBC1b; DNA voucher; DNA bank: r462p15f2t91; GenBank: MT727055, MT704268, MT731697; ZSM-Mol-20100320. Paratypes Belize • 1; same data as for holotype; DNA voucher;.
Central American Caecidae Caecum heptagonum Carpenter, 1857 Caecum heptagonum Carpenter, 1857: 319, t. 1524. Type locality: Mazatlán [Mexico]. Material examined. Panama • 1 juv. (Fig. 6B-E); Achotines; 7. 6349, -79. 9968; depth 10 m; 6 Mar 2016; USNM Achotines2016 exped. ; Stat. PA23a; DNA voucher; DNA bank: r462p4f2t91, GenBank: MT704283, MT731717; ZSM-Mol-20200030. • 1 juv. (Fig. 6A); same collection data as for preceding; DNA voucher; GenBank: MT704291, MT731726; USNM 1618866. • 1 juv. ; same collection data as for pre- ceding; ZSM-Mol-20200116. • 1 juv. ; same collection data as for preceding; ZSM- Mol-20200117. • 1 juv. ; Achotines; 7. 6346, -79. 9965; depth 10 m; 6 Mar 2016; USNM Achotines2016 exped. ; Stat. PA23b; ZSM-Mol-20200115.
Caecum insignede Folin, 1867: 52, 53, pl. 2, fig. 4; Caecum sculptum de Folin, 1881: 15, pl. I, figs 1, 2. Shell opaque, yellowish. Lighter color in interspaces, darker colored ridges of prominent rhombic pattern (Fig. Material examined. Belize • 1 (Fig. 1, specimen to the left); Carrie Bow Cay; 16. 8037, -88. 0769; depth 31 m; 15 Jan 2010; USNM Belize2010 exped. ; DNA voucher; GenBank: MT727051, MT704281; USNM 1618850. Panama • 1; Bo- cas del Toro; 9. 4333, -82. 3467; depth 3 m; 5 Jun 2010; USNM BRS2010 exped. ; DNA voucher; GenBank: MT704261; USNM 1618852. • 1; Bocas del Toro; 9. 3222, -82. 2215; depth 4. 5 m; 5 Jun 2010; USNM BRS2010 exped. ; DNA voucher; Gen- Bank: MT727047; USNM 1618854. • 1; same collection data as for preceding; Gen- Bank: MT727048; USNM 1618855. Shell morphology. 69, fig.
Type locality: northern part of Gardiner's Bay, four or five fathoms [United States]. Caecum costatum A. E. Verrill, 1872: 283, pl. 6, fig. 6, Caecum smithi Cooper, 1872. Material examined. French Antilles • 1 (Fig. 6F-I); Guadeloupe; 16. 3558, -61. 5965; depth 2 m; 24 May 2012; MNHN KARUBENTHOS exped. ; Stat. GS32; GenBank: MT704297, MT731713; MNHN-IM-2019-32.
Type locality: Bermuda, Ship Channel and Bailey Bay, in 12 to 40 feet. Material examined. French Antilles • 1 (Fig. 6J-M); Guadeloupe; 16. 3558, -61. 5965; depth 2 m; 24 May 2012; MNHN KARUBENTHOS exped. ; Stat. GS32 GenBank: MT704295, MT731711; MNHN-IM-2019-27a. • 1; same collection data as for preceding; GenBank: MT704296, MT731712; MNHN-IM-2019-27b.
). Type locality: Baie de Bahia[Bahia Bay, Brazil]. Material examined. Belize • 1; Carrie Bow Cay; 16. 8024, -88. 0776; depth 19 m; 25 Jan 2010; USNM Belize2010 exped. ; Stat. CBC24; DNA voucher; GenBank: MT727061, MT704275; USNM 1618845. • 1 (Fig. 6N-Q); same collection data as for preceding; ZSM-Mol-20100322.
: 322, pl. 34, figs 269, 1528. Type locality: Mazatlán [Mexico]. Material examined. French Antilles • 1 (Fig. 6R-U); Guadeloupe; 16. 2235, -61. 5305; depth 1 m; 2 May 2012; MNHN KARUBENTHOS exped. ; Stat. GM01; GenBank: MT704294, MT731710; MNHN-IM-2019-17.
: 36, pl. 2, fig. 3. Type locality: New England, Buzzard's Bay [New Bedford Harbor, Massachusetts]. Caecum capitanum de Folin, 1874: 227, 228, pl. 9, fig. 8; Caecum conjunctum de Folin, 1867: 46, pl. 4, figs 5, 6, Caecum curtatum de Folin, 1867: 20, pl. 2, figs 4, 5 Material examined. Saint Lucia • 1 (Fig. 7A, C, E, F); Soufriere Bay; 13. 8494, -61. 0675; depth 8-9 m; 19 Feb 2009; ZSM stuff leg. ; DNA voucher; DNA bank: r462p- 19f2t91; GenBank: MT727074, MT704300, MT731729; ZSM-Mol-20090485. • 1, juv. (Fig. 7B, D); same collection data as for preceding; DNA voucher; DNA bank: r462p20f2t91; ZSM-Mol-20200118.
: 428-429, pl. 69. Type locality: W. Indies (Woodward) [Caribbean]. Material examined. Panama • 1, juv. ; Bocas del Toro; 9. 2141, -81. 9318; depth 8. 5 m; 5 Jun 2010; USNM BRS2010 exped. ; Stat. BRS108; DNA voucher; GenBank: MT727050, MT731690; USNM 1618883. Belize • 1, juv. (Fig. 7H-K); Carrie Bow Cay; 16. 7911, -88. 0761; depth 15 m; 24 Jan 2010; USNM Belize2010 exped. ; Stat. CBC22; DNA voucher; DNA bank: r462p17f2t91; GenBank: MT704280, MT731708; ZSM- Mol-20100321. • 1, juv. ; same collection data as for preceding; ZSM-Mol-20200114.
). Type locality: Iles aux Perles, dans la baie de Panama[Pearl Islands, Panama]. Shell fragile, color frosted translucent (Fig. Material examined. Panama • 1 juv. ; Achotines; 7. 6349, -79. 9968; depth 10 m; 6 Mar 2016; USNM Achotines2016 exped. ; Stat. PA23a; DNA voucher; GenBank: MT727072, MT731727; USNM 1618884. • 1 juv. (Fig. 7O, P, R, T); same collection data as for preceding; ZSM-Mol-20200038. • 1 juv. ; Achotines; 7. 6207, -80. 0013; depth 12 m; 29 Feb 2016; USNM Achotines2016 exped. ; Stat. PA14; DNA voucher; GenBank: MT727068, MT704287, MT731721; USNM 1618864. Shell morphology.
Type locality: Mazatlán [Mexico]. Material examined. Panama • 1 juv. ; Achotines; 7. 6349, -79. 9968; depth 10 m; 6 Mar 2016; USNM Achotines 2016 exped. ; Stat. PA23a; DNA voucher; GenBank: MT727070, MT704289, MT731724; USNM 1618865. • 1 juv. (Fig. 7L); same col- lection data as for preceding; DNA voucher; DNA bank: r462p7f2t91; GenBank: MT704284, MT731718; ZSM-Mol-20200033. • 1 juv. ; same collection data as for preceding; DNA voucher; DNA bank: r462p11f2t91; GenBank: MT704286, MT731720; ZSM-Mol-20200037. • 1 juv. (Fig. 7M, N, Q, S); same collection data as for preceding; ZSM-Mol-20200032. • 1 juv. ; Achotines; 7. 6207, -80. 0013; depth 12 m; 29 Feb 2016; USNM Achotines2016 exped. ; Stat. PA14; ZSM-Mol-20200027.
The genomics-based molecular classifications aim at identifying more homogeneous classes than immunohistochemistry, associated with a more uniform clinical outcome. We conducted an in silico analysis on a meta-dataset including gene expression data from 5342 clinically defined ER+/HER2-breast cancers (BC) and DNA copy number/mutational and proteomic data. We show that the Basal (16%) versus Luminal (74%) subtypes as defined using the 80-gene signature differ in terms of response/vulnerability to systemic therapies of BC. The Basal subtype is associated with better chemosensitivity, lesser benefit from adjuvant hormone therapy, and likely better sensitivity to PARP inhibitors, platinum salts and immune therapy, and other targeted therapies under development such as FGFR inhibitors. The Luminal subtype displays potential better sensitivity to CDK4/6 inhibitors and vulnerability to targeted therapies such as PIK3CA, AR and Bcl-2 inhibitors.
1%), the Basal samples displayed lower ESR1 mRNA expression and increased relative ERΔ7 dominant-negative variant expression, shorter 3-year distant relapse-free interval (DRFI), and higher pathological complete response rate (pCR) to chemotherapy (CT). But the authors pointed to a few limitations: the limited number of ER+ Basal patients (54 for DRFI, 70 for pCR), the short median 34-months follow-up, and absence of information regarding the sensitivity to hormone therapy (HT). To reinforce these results and extend them to the response and/or potential vulnerability to HT and other systemic therapies of BC, and to assess the degree of difference between these subtypes, we analyzed in silico a meta-dataset including gene expression data from 8982 nonredundant BCs  6  , and DNA copy number/mutational and proteomic data from TCGA.
Breast cancer samples, gene profiling and data analysis We analyzed our BC gene expression database 6 pooled from 36 public datasets (Table  S8 ), comprising 8982 invasive primary BCs. The details of Institutional Review Board and Ethical Committee approval and patients' consent for all 36 studies are present in their corresponding publications listed in Table  S8. The preanalytic data processing was done as described  6. We also collected DNA and proteomic data from TCGA (WES data, array-CGH, HRD score, RPPA)  11  and the PIK3CA and TP53 mutational statutes of TCGA and Metabric  28. ER and HER2 statutes were preferentially determined by study annotation when in agreement with the recent ASCO guidelines  29, 30. Where unavailable, the normalized gene expression data were used to infer the receptor status.
This was made possible thanks to the bimodal distribution of mRNA expression level. The mRNA threshold was verified on the 5548 samples of our database ER-annotated according to the 1% ASCO guideline IHC cut-off: the concordance rate was 93%, suggesting good performance. Out of the 8982 samples of our database, 6563 were defined as ER+ (5342 according to IHC and 1221 according to inferred stratus). The same process was applied for defining the HER2 status, the cut-off of which was based on the recent ASCO guidelines  29. In accordance with this guideline, the samples were considered HER2+ when they reached an IHC score of 3+ or 2+ with FISH amplification. A HER2 IHC score of +1 or 0 was considered negative. When the information was not available, and thanks to the bimodal distribution of mRNA expression level, the HER2 status was inferred from the mRNA expression level as described for ER  31.
The mRNA threshold was verified within the 6563 ER+ samples on the 3050 HER2-annotated according to the ASCO guidelines: the concordance rate was 91%, suggesting good performance. Out of the 6563 ER+ samples of our database, 727 were defined as HER2+ (421 according to IHC and 306 according to inferred stratus), leaving 5836 ER +/HER2samples. We applied to each dataset separately several GES: 80-GS 5 and PAM50  32  , and the surrogate signatures of three commercial prognostic signatures (Recurrence Score 33 , Mammaprint 34 , EndoPredict  35  ), Gatza's ER and PR pathways activation signatures  36  , E2F4-activation signature associated with resistance to HT 8 , two scores associated with resistance to CDK4/6 inhibitors on preclinical models for RBsig  9  and on clinical samples of PALOMA-3 trial for E2F regulon 10 , several Bindea's expression modules  14  representing different immune cell populations, the immunologic constant of rejection (ICR) signature  6  , and two signatures related to mammary epithelial cell hierarchy and stem cells  17, 18.
Statistical analysis The data generated and analyzed during this study are described in  37  and correspond to 36 publicly available datasets that are listed in Supplementary Table  8  (all datasets) and in data refs  7, 11, 28, 34,. The pr gnostic clinicopathological variables tested included the patients' age (≤50 years versus >50), and pathological type (ductal versus lobular versus other), grade (1 versus 2 versus 3), tumor size (pT1 versus pT2 versus pT3), and axillary lymph node status (negative versus positive), and use of adjuvant HT and CT (yes versus no). Distant relapse-free interval was calculated from the date of diagnosis until the date of distant relapse or death from breast cancer. Event-free patients lost to follow-up or dead from unspecified cause or from cause unrelated to breast cancer were censored at time of last contact.
DATA AVAILABILITY The data generated and analyzed during this study are described in the following data record: https://doi. org/10. 6084/m9. figshare. 11558676. The dataset Breast_can-cer_classifications. csv supporting Fig. 1 , Table  1 , and Supplementary Tables  1 2 3 , and containing the clinicopathological and molecular data of tumors analyzed, is publicly available in the figshare repository as part of the data record mentioned above. (GEO, Array Express and EGA datasets).
The proper assembly of the FeS cluster of HYDA relies on three maturase proteins (HYDE, HYDF, and HYDG). In some bacteria, HYDA functions with two other proteins, HYDB and HYDC-homologs of the NUOF and NUOE subunits of CI of the respiratory chain, respectively-in a trimeric confurcating hydrogenase complex. This complex couples the favorable and unfavorable oxidations of ferredoxin (Fd; E0′ ≈ -450 mV) and NADH (reduced form of nicotinamide adenine dinucleotide) (E0′ ≈ -320 mV), respectively, to reduce protons (E0′ ≈ -420 mV)  (13). In some anaerobic and microaerophilic microbial eukaryotes, PFOmediated acetylCoA production and HYDA mediated H 2 production occur in the cyto plasm  (14) , plastid  (15) , and/or mitochondrial compartment  (16, 17). While many of these eukaryotes have lost all genes that encode the respiratory chain (i.
Annotation and orthology clustering Protein sequences were annotated according to the strategy laid out by Dharamshi et al. (28). In short, annotations include: top hits against National Center for Biotechnology Information nonredundant (nr) protein database using DIAMOND aligner v0. 9. 19. 120 (45) blastp ("moresensitive") alongside taxonomic classification of sequences [lowest common ancestor (LCA) algorithm, "f 102"], assignment of protein domain annotations using InterProScan (46) version 5. 2261. 0 [e. g. , Protein Families (Pfam)  (47)  and InterPro (IPR)  (48)  domains], and assignment to both rootlevel "d NOG" and bacteriallevel "d BACT" nonsupervised orthologous groups (NOGs) using eggNOGmapper  (49)  with the eggNOG database  (50). The presence of KEGG (Kyoto Encyclopedia of Genes and Ge nomes)  (51, 52)  modules connected to various metabolic pathways related to energy generation and electron transfer (Fig.
1  and fig. S4 ) were assessed across Chlamydiae species representatives (data S1) through the assignment of KEGG orthology (KO) numbers by GhostKOALA  (53). Pfam domains  (47)  allowed the identification of several additional proteins of interest (data S1), including CIII of the electron transport chain (PF00033). The presence of specific pro teins across Chlamydiae included in phylogenetic trees (see below) is also indicated in data S1. The presence of specific pathways related to energy genera tion found across Chlamydiae was also assessed in several anaerobic eukaryote representatives (e. g. , A. castellani, GCF_000313135. 1; T. vaginalis, GCF_000002825. 2; Chlamydomonas reinhardtii, GCF_ 000002595. 1; Blastocystis sp. ST 1, GCA_001651215. 1; and Pygsuia biforma, GCRY00000000. 1) using GhostKOALA  (53)  or manual inspection (see data S1).
Gene content unique to or enriched in Anoxychlamydiales rela tive to other chlamydiae was assessed by mapping protein sequences to NOGs. eggNOGmapper (49) version 4. 5 was used to map all pro tein sequences from Chlamydiae species representatives (data S1) to rootlevel NOGs ("d NOG"). NOGs unique to Anoxychlamydiales in comparison to other chlamydiae and found across the group (in at least five members) are outlined in fig. S2 (data S1 ) and are or dered by Clusters of Orthologous Genes (COG) category  (54). Those enriched in Anoxychlamydiales, in at least five members and up to three other chlamydiae, can be found in data S1.
Phylogenetic analysis of genes encoding anaerobiosis-associated proteins We selected orthologous groups related to anaerobiosis that were found in the Anoxychlamydiales MAGs and typically absent from other chlamydiae. To generate the phylogenetic datasets, we used each of the Anoxychlamydiales sequences as a query against GenBank nr (January 2019), the Marine Microbial Eukaryote Transcriptome Sequencing Project [MMETSP;  (55) ], and other sequencing projects  (22, 56)  using BLAST  (57)  to retrieve the best 2000 hits with an e value lower than 1 × 10 -5. For HYDA phylogenies, we retrieved 2000 addi tional hits using the large HYDA domain of T. vaginalis (XP_ 001322682. 1), Nyctotherus ovalis (CAA76373. 1), and Thalassiosira pseudonana (XP_002295160. 1). All HYDA sequences were classified with HYDDB (58), and only group 1A HYDAs were retained.
HMMer version h3. 1b2 (www. hmmer. org) (59)  and the hidden Markov model (HMM) for the large HYDA domain (PF02906) were used to iden tify and extract only the large HYDA domain from each sequence for further analysis. For all datasets, taxonomy was assigned to each sequence using ETE version 3. 0. 0 (60), and CDHIT version 4. 6  (61)  was used to reduce the dataset at the 80% amino acid sequence identity level. MAFFT v7 (a multiple alignment program for amino acid or nucleotide sequences) (62) using the "auto" flag was used to build initial alignments, and BMGE (Block Mapping and Gathering with Entropy) version 1. 12 (63) was used to mask ambiguously aligned residues (i. e. , entropy scores greater than 0. 6) using the BLOSUM30 matrix. Initial trees were generated using FastTree version 2.