dataesr/scientific-paragraphs-categorization huggingface dataset:
The amino acid context of polyQ regions is length-and puritydependent Since polyQ length and the presence of impurities have been proven to be threshold-dependent, we wondered whether the sequence context of the polyQ is also dependent on the threshold used to define the tracts. To study this feature we calculated the amino acid composition per position of polyQ flanking regions for each of the five thresholds. The most prevalent amino acid around the polyQ regions for all thresholds is glutamine (data not shown), suggesting that there is a soft transition between polyQ and Q-rich regions surrounding polyQ. Two other amino acids are significantly enriched in the proximity of the human polyQ: leucine and proline. This is consistent with the most abundant amino acids found as impurities within the polyQ described in the previous section.
The nucleotide landscape of polyQ regions Since the amino acid context, length and purity of the polyQ tract depend on the threshold used, we examined whether the nucleotide sequences coding for polyQ tracts and their flanking regions are also threshold-dependent. This is key to understand the presence of CAG trinucleotide expansions in evolution and disease  [20]. Therefore, we focused on the nucleotide context, the usage of polyCA[G/A] within polyQ and the characteristics of the impurities in all protein coding transcripts of the human genome. The same five thresholds used in previous sections were used to detect polyCA[G/A]. Once a polyCA[G/A] was detected, five codons N-and C-terminal to the polyQ were retrieved. We calculated the codon abundance per position À5 to +5 and normalized it with the codon abundance in the complete dataset of human transcripts.
If the focus is on retrieving functional polyQ with high precision, then we recommend using the thresholds 6/8 or 8/10. However, this rule might not apply to some species as we have seen that the properties of the polyQ are species-dependent even when using the same threshold. While we acknowledge that it does not make sense to carry out every study on homorepeats with all the thresholds shown here, or even with others, we recommend a fast scanning similar to the one in Fig. 5. Depending on the results one could make an informed decision and thus choose a threshold depending both on the needs of the study and on the dataset; i. e. if the dataset does not contain many long polyQ, choosing 8/10 will in principle be useless. Furthermore, if there were not many polyQ, whichever the threshold, it would be preferable to use 4/6 to capture as many regions as possible.
To carry out the proposed fast scanning, we have prepared a simple script called sQannner (Supplementary File 1) that takes a proteome (a protein dataset in FASTA format) and generates a plot with the number of pure and impure polyQ, and the polyQ length distribution per threshold. The whole process takes around 10 s in a standard laptop computer for the proteome of S. cerevisiae (6049 proteins), which is provided with the script as an example, and 2 min for the human proteome (74449 proteins). In addition, sQanner is available as a simple web tool in http://cbdm-01. zdv. uni-mainz. de/~munoz/sQanner/. It is important to know the biases associated with each threshold (Table  2 ). The dataset of polyQ regions resulting from the selected threshold will have inherent properties, such as containing long polyQ if 8/10 is used or containing only pure polyQ if 4/4 is used.
Funding This work was supported by  Deutsche Forschungsgemeinschaft  [ AN735/4-1  to M. A. A. N. ] and by the  European Research Councilunder the European Union 's  H2020 Framework Programme  ( 2014-2020 )/ ERC  Grant agreement nr. [648030], and  Labex EpiGenMed , an '' Investissements d'avenir" program  ( ANR-10-LABX-12-01 ) awarded to PB. The CBS is a member of  France-BioImaging (FBI)  and the  French Infrastructure for Integrated Structural Biology (FRISBI) , two national infrastructures supported by the  French National Research Agency  ( ANR-10-INBS-04-01  and  ANR-10-INBS-05 , respectively).
The O. officinalis protein variant, when compared to Nipponbare, showed maximum variability comprising 22 amino acid substitutions and absence of two peptides and two β-sheets. Further, expression profiling indicated significant differences in transcript abundance within as well as between the OsPLDα1 variants. Also, a new OsPLDα1 transcript variant having third exon missing in it, Os01t0172400-06, has been revealed. An O. officinalis accession (IRGC101152) had lowest gene expression which suggests the presence of novel allele, named as OsPLDα1-1a (GenBank accession no. MF966931). The identified novel allele could be further deployed in the breeding programs to overcome rice bran rancidity in elite cultivars. Rice (Oryza sativa L. ) bran, a by-product after milling, is composed of pericarp, aleurone, seed coat, nucellus along with the germ and a small portion of endosperm 1,2.
In addition, lipoxygenases act on the FFAs which contain a 1, 4-pentadiene structure, such as linoleic and linolenic acids, and lead to their conversion into low molecular-weight volatile products which cause a stale flavor in the product  14, 15. Hence, it has been revealed by the the earlier studies that PLD acts as a trigger for the initiation of lipid decomposition which further leads to deterioration of the rice grain and rice bran fractions. A total of 17 PLD genes including eight isoforms of PLDα, two of PLDβ, three of PLDγ, two of PLDξ, and one isoform each of PLDκ and PLDϕ has been indicated in rice genome database  16. In these isoforms, protein domain analysis has revealed several conserved domains, including the HKD (HxKxxxxD) domains (also known as PLD-C1 and PLD-C2 domains), having hydrolytic activity; the calcium/lipid-binding domain (C2 domain), resonsible for regulation of Ca 2+ -dependent enzyme activity through binding to Ca  2+  ; and (3) the PX (phox consensus sequence) and PH (pleckstrin homology) domains, located at the N-terminus of Ca  2+  independent PLDs in place of the C2 domain of Ca 2+ dependent PLDs  17.
OsPLDα1 gene expression profiling in Wild Oryza species and detection of a new OsPLDα1 transcript. To carry out expression analysis at OsPLDα1 locus, the plant development stage for RNA extraction was chosen on the basis of expression profiling of 17 PLD isoforms using the expression data from RiceXProv3. 0 database (see Supplementary Fig. S8 ). The expression analysis using various plant tissues at different developmental stages indicated that the activity of OsPLDα1 enzyme was very high during early stages of grain development. Moreover, Suzuki (2011) reported the hike of PLD content in the seeds till 3 wk after flowering, becoming stagnant afterwards. Also, no PLD protein band was observed one week after flowering in the seeds of PLD-null rice mutant (03-s108), having <0. 01% PLD activity in rice bran when compared to Nipponbare  21.
followed by O. punctata and O. latifolia (Fig. 5 ). In the O. officinalis accessions, two insertions viz. A at nucleotide position 459 and T at nucleotide position 1927 led to maximum alterations in the OsPLDα1 protein that included 14 amino acid substitutions and absence of two peptides (see Supplementary Fig. S4  and S5 ). The alterations observed in the protein could be the reason for lowest enzymatic activity in O. officinalis spp. The novel allele leading to low OsPLDα1 expression in O. officinalis accessions has been named as OsPLDα1-1a and is available in NCBI database (http://www. ncbi. nlm. nih. gov) with GenBank accession numbers MF966931, MF966932, and MF966933. In addition, significant differences were observed in the transcript abundance within the accessions for the primers designed from 5′ and 3′ ends of second exon, demonstrating the presence of 5′ and 3′ truncated mRNA (Fig.
officinalis accession (IRGC101152) i. e. , OsPLDα1-1a (GenBank accession no. MF966931), into the elite rice cultivars. 1 ). These germplasm accessions have been actively maintained at Punjab Agricultural University (PAU), Ludhiana, and were originally procured from the International Rice Research Institute (IRRI), Philippines and from National Rice Research Institute (NRRI), Cuttack. The sequence analysis in Oryza cultivars namely Punjab Rice 114 (PR 114), Nagina 22 (N22), IR64, Pusa 44, Minghui 63, Feng-Ai-Zhan, and Kitake, revealed the presence of OsPLDα1 allele. Therefore, these cultivars were used as positive checks to carry out the comparative OsPLDα1 sequence analysis with wild Oryza species accessions. Standard agronomic practices were followed to raise the crop. These practices included sowing of seeds in seedbeds and transplanting one-month-old seedlings in the field with a row-to-row distance of 70 cm and plant-to-plant distance of 45 cm; weed control using a Paddy Weeder, 15 days after transplanting and again after a fortnight; application of organic manures (15 tonnes of farmyard manure per hectare prior to transplanting of rice), bio-fertilizer (treat the nursery seedlings for 45 minutes in the solution made by dissolving 0.
Methods DNA extraction, primer designing and PCR amplification. The current study followed a modified CTAB method to isolate genomic DNA from the selected genotypes  96. 0. 8% agarose gel was used to access the quantity and quality of DNA from each sample. For further use, DNA samples were diluted with 1X TE buffer and stored at -20 °C. To PCR amplify the coding and non-coding regions of the OsPLDα1 variants, Oryza sativa japonica cv. Nipponbare sequence (GenBank accession no. AB571657. 1) was utilized to design five overlapping primer pairs (Table  4 ). Supplementary Fig. S10  shows the OsPLDα1 gene structure (RAPdb ID Os01g0172400) and positions of the designed primer pairs along the length of gene. First and last primers were designed from the upstream and downstream flanking regions of the gene to sequence the whole gene.
S11 ). The Wizard ® SV PCR Clean-Up System (Promega, USA) as per the manufacturer's protocol was followed to excise and purify the DNA fragments. The details of targeted DNA nucleotide sequence were created using separate sequencing reactions for forward and reverse primers. The ABI Big-dye Terminator v3. 1 chemistry performed the sequencing reaction and ABI Sequencer 3730XL sequenced the DNA fragments, at the School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana. Experiment was carried out in two replications to confirm the presence of single nucleotide polymorphism (SNPs). Analysis of the generated nucleotide sequences and protein prediction. For comparative sequence analysis, DNA Baser v4. 23. 0 (http://www. dnabaser. com/) software joined the contigs produced by overlapping primers, and generated the consensus sequence of OsPLDα1 gene.
This software also helps in automatic identification and clipping of poor quality regions at both ends of the sequences. ClustalX 2. 1. 1 software was undertaken to generate the multiple sequence alignment  97. OsPLDα1 sequence from 'Nipponbare' rice variety, which contains normal levels of PLD activity i. e. , 133. 2 units/mg  21  , was used as reference (wild type) in this study. The identified SNPs and InDels were then manually curated by comparing chromatogram files to the ClustalX alignment files. HMM-based FGENESH online program (http://www. softberry. com/berry. phtml?topic=fgenesh) was used to predict the gene structure and amino acid sequences in different genotypes which were further compared with the Nipponbare protein to detect amino acid substitutions and InDels. Pfam (http://pfam.
xfam. org/) online program predicted the domains and motifs in the protein variants. Bioinformatics toolkit (http://toolkit. tuebingen. mpg. de/) was used to predict the tertiary structures of protein. The MODELLER Homology modeling approach was followed  98  to determine the structure of proteins based on the known strucure of template protein. Ramachandran plots were developed using Procheck through PDBsum (http://www. ebi. ac. uk/thornton-srv/ databases/pdbsum) to check the quality of protein models. UCSF Chimera helped to visualize and compare the modeled protein structures  99. All the developed tertiary structures were superimposed to detect the structural variations. Uniprot (http://www. uniprot. org/uniprot/P84147) online program determined the catalytic sites in the protein. Phylogenetic analysis.
The MEGA7 software 100 was used to generate the phylogenetic tree using multiple sequence alignment file. The evolutionary distances were computed using the Maximum Composite Likelihood method with 1,000 bootstrap and are in the units of the number of base substitutions per site. RNA isolation, cDNA synthesis, and expression analysis using qRT-PCR. To collect the RNA sample at the same stage (one week after flowering, at milking stage of grain development) from different wild species and cultivars, flowering data was collected on the daily basis. For each genotype, tissue for RNA isolation was collected in a way that each experimental replicate represents RNA from three biological replic ates 101. The TRIzol ® reagent (Thermo Fisher Scientific) was used for RNA isolation according to the manufacturer's protocol.
The expression analysis part of the study wa s done at the School of Biology and Ecology, University of Maine, Orono, USA. NanoDrop ® ND-1000 estimated the RNA quantity for the different samples. We employed an iScript cDNA kit (Bio-Rad laboratories, CA, USA) which produces first strand cDNAs by reverse transcribing RNA. Sequences of OsPLDα1 loci and its transcript forms (Locus ID Os01g0172400), for qRT primers designing, were retrieved from RAP data base (http://rapdb. dna. affrc. go. jp/viewer/gbrowse/). Using the Primer-BLAST tool (http://www. ncbi. nlm. nih. gov/tools/primer-blast/), four exon-specific qRT-primer pairs (PLDE1, PLDE2. 1, PLDE2. 2, and PLDE3) (see Supplementary Table  S3 ) were designed from the exonic regions of OsPLDα1. qRT-primers were generated to assess the wild genotypes for variations in abundance of OsPLDα1 transcript variants (see Supplementary Fig.
Meioceras, which differs from Caecum in the general shape of the shell (i. e. , with the widest part towards the middle of the shell), was erected by  Carpenter (1858 Carpenter ( -1859) )  due to the slightly coiled shape of their juveniles. The genus was recently split into Indo-West Pacific Mauroceras and Western Atlantic Meioceras  (Vannozzi 2019). While recent taxonomic works have de-scribed the caecid fauna in the Indo-Pacific based on microsculptural investigations of the shell  (Pizzini et al. 2013; Vannozzi 2017 Vannozzi , 2019)) , knowledge of caecid diversity in Central American waters is still limited to light-microscopic identification of shells for a large majority of described species. In this study we present data on caecid diversity based on several recent collecting trips to Central America.
). Samples at the LMU were cycle sequenced on an ABI 3730 48 capillary sequencer (Applied Biosystems, Foster City, USA) using Big Dye 3. 1 (Thermo Fisher Scientific Inc. ) at the sequencing service of the Ludwig-Maximilians-Universität (LMU) Biocenter, Munich, Germany. At the SI, cycle sequencing was also conducted with BigDye     (Montagu, 1803)  and C. glabellum (A. Adams, 1868)), as well as for out-group taxa were added (Table  3 ). Outgroups were assigned based on the recent molecular phylogenetic analyses by  Golding (2014a, b)  and  Criscione and Ponder (2013). Two combined data sets were generated: (1) a concatenated alignment of all three marker genes and (2) a concatenated alignment comprising only the mitochondrial 16S rRNA gene, and COI. The data were combined into single matrices using P4  (Foster 2004).
The combined data sets were then partitioned by gene and COI codon position. Maximum likelihood (ML) and Bayesian inference (BI) were used to construct the phylogenetic tree from single genes and from combined and partitioned alignments. For each alignment jModelTest2 (vers. 2. 1. 10; Darriba et al. 2012 ) was run and the calculated likelihood scores weighted under the Akaike Information criterion (AICc)  (Hurvich and Tsai 1989)  which suggested GTR+I+G as the best fitting model. ML was performed using IQ-TREE (multicore vers. 1. 6. 7. 1 for Linux 64-bit;  Nguyen et al. 2014 ) with the GTR+G4+FO model (equivalent to GTR+G in RAxML vers. 8. 2; Stamatakis 2014) with 300 bootstrap replicates. Bayesian MCMC analyses were performed using the program  MrBayes (vers. v. 3. 2. 6; Huelsenbeck and Ronquist 2001)  with the same model.
Species delimitation and characterization based on molecular data Four different methods of species delineation were used with both the COI and 16S rRNA gene mitochondrial data sets. The Automatic Barcode Gap Discovery (ABGD) webserver was used to partition the data set into putative species based on the calculated gap between intra-and interspecific genetic differences (https://bioinfo. mnhn. fr/abi/ public/abgd/abgdweb. html;  Puillandre et al. 2012). J ModelTest2 (vers. 2. 1. 10; Darriba et al. 2012 ) was applied to the uncorrected COI and 16S rRNA gene alignments and the parameters were weighted under the corrected Akaike Information criterion (AICc)  (Hurvich and Tsai 1989). For both alignments the Jukes-Cantor (JC69) as well as Kimura (K80) model showed to be within the 100% confidence interval however, K80 had slightly higher likelihood scores.
Both models were applied with the default settings (TS/TV = 2. 0, relative gap width = 1. 5, Pmin = 0. 001, and Pmax = 0. 10) on the uncorrected COI and 16S rRNA gene alignments. To evaluate haplotype connectivity, we generated haplotype networks based on the COI as well as the 16S rRNA gene sequence alignment using the software TCS (vers. 1. 21;  Clement et al. 2000)  using the standard 95% parsimony setting. Ambiguous sites in both alignments were removed to prevent the creation of artificial haplotypes. The bPTP web server (https://species. h-its. org/) was used to conduct the Bayesian implementation of the PTP model for species delimitation  (Zhang et al. 2013 ) on the optimal ML trees of the individual and the combined COI and 16S rDNA datasets. We applied the default settings with 100000 generations, thinning for each 100 th sample with a burn-in of 10% and checked for convergence of the MCMC chains of each run.
Posterior probability (PP) support values above 0. 95 were considered as strong support. For the General Mixed Yule-Coalescent model (GMYC)  (Pons et al. 2006) , ultrametric trees from the COI, 16S rRNA gene, and combined COI and 16S rRNA gene data were obtained using a time calibrated Bayesian evolutionary analysis in  Beast (vers. 1. 7. 4; Drummond and Rambaut 2007). For the tree prior, we used a Yule process and two fossil records, Caecum cooperi and Caecum imbricatum [2. 58-1. 80 myr]  (Mansfield 1930; Cooke 1936; Ward and Blackwelder 1987)  and the in-group Caecum [50-55 myr] (Goedert and Raines 2016) with a lognormal distribution (logL). The analysis was run with the GTR substitution model and under a strict clock assumption. The analysis was started from a random tree and two Markov chains run for 10 000 000 generations with a sampling frequency of 1000.
Molecular species delineation The methods that were used for species delineation are largely congruent with regard to the assignment of taxa to molecular operational taxonomic units (MOTUs), however individual analyses deviate and evidently differences occur due to incomplete sampling of one of the markers (Fig. 4 , Table  1 ). Both PTP/ bPTP and GMYC (single threshold) delimit 21 MOTUs for the concatenated dataset of COI and 16S rRNA genes (excluding the species whose sequences were retrieved from NCBI GenBank, i. e. North Atlantic C. glabrum and Japanese C. glabellum). These results are in concordance with the preliminary species hypotheses based on morphological investigation and the molecular phylogenetic tree (Fig. 3 ) with the exception of additional splits of C. debile and C. regulare into two distinct MOTUs each.
Caecum cf. teres resulted in a single species for 16S rDNA alone, and the Bayesian implementation of bPTP split M. nitidum into two separate species based on the 16S rRNA genes (however, support value for the split is 0. 501%). The multiple threshold analyses in GMYC additionally splits C. invisibile sp. nov. of the 'C. glabrum complex' into two MOTUs, as does TCS but into differing entities. In analyses of individual datasets (numbers not directly comparable due to missing data) ABGD identified 15 MOTUs in our 16S rRNA gene dataset (Fig. 4 ), while the COI dataset resulted in a hypothesis of 10 MOTUs independent of the application of the JC69 or the K80 model. In comparison to the other methods, TCS appears to oversplit MOTUs (see e. g. , TCS analyses of the COI of C. donmoorei in Fig. 4 ).
The algorithm of this haplotype-network software splits the 16S rDNA dataset into 19 independent haplotype networks, while it recovered 13 networks for the COI dataset (Fig. 4 ). Additionally, TCS also splits MOTU II of the 'C. glabrum-like complex' into two networks and C. donmoorei into three independent networks based on 16S rRNA sequence data. Haplotype networks divided C. cf teres and C. cf. strangulatum into two unconnected networks. However, the split is not congruent with the two monophyletic sister populations of the species tree (Fig. 4 ). In summary, we consider only splits relevant, which are supported by at least two different analyses or markers, singular deviating signal might either resemble errors in analyses or might be informative in population analyses (for more details see remarks in Systematics section).
Cryptic lineages revealed in molecular analyses Twenty-four specimens from Central American waters are smooth and glossy without ornamentation except for occasional growth lines (i. e. , possess few shell characteristics), but vary in adult shell length between 0. 7 and 2. 5 mm (Figs  3, 5F-L, O-R ). Morphologically, these specimens all closely resemble Caecum glabrum  (Montagu, 1803)  which is one of the best-known species of caecids, and abundant in the northern Atlantic  (Montagu 1803; Wood and Harmer 1848; Götze 1938; Chambers 2009). Caecum glabrum was originally described from Biddlesford Bay and Barnstable, Devon, England, the included sequences from GenBank (see Table  3 ) originates from specimens collected in Norway, but own unpublished data from Roscoff, northern France, supports the wide distribution range of C.
MOTU I Material examined. Panama • 1 (Fig. 5I-L ); Bocas del Toro; 2010; USNM BRS2010 exped. ; DNA voucher; DNA bank: r462p13f2t91; GenBank: MT704263, MT731688; ZSM-Mol-20200039. Morphological characterization. Shell size 1. 3 mm long, 0. 3 mm wide. Translucent, with whitish body. Tube regularly curved and equal width. Septum hemispherical (Fig. 5K ). Aperture straight, with lip indicating an adult specimen. Operculum brownish. No sculpture or microsculpture diagnostic features (compare Fig. 5L ). Remarks. MOTU I is highly similar to the European C. glabrum (Fig. 5M ) and Caecum invisibile sp. nov. (Fig. 5O-R ). However, MOTU I shows some small morphological differences such as a bigger shell size and a tiny rim at the aperture (Fig. 5L ) which is absent in C. glabrum. The septum is further completely round and blistered (Fig.
12. 9. 19, 1858. 12. 9. 20, 1858. 12. 9. 21) and the redescription of  Moore (1972) : 888, fig. 7. The conspicuous widening of the shell very close to the aperture in our specimen investigated can be interpreted as a character of a sub-adult growth stage  (Bandel 1996) , thus not contradicting the assignment to C. regulare. A literature survey suggests at least one putative synonym of C. regulare, resp. Caecum planum,  de Folin, 1874 (de Folin and Périer 1875: 277, t. 2, pl. 10, figs 8, 9). However, the geographical distribution differs (C. regulare was originally described from the Caribbean and C. planum from Brazil), and there are no evident diagnostic differences to C. regulare. Hence, molecular data is needed for clarification. Further data also is needed for the complementary gene sequences (16S rRNA and COI) for the two investigated specimens.