dataesr/scientific-paragraphs-categorization huggingface dataset:
Another region contributing to grain quality (grain fructan content  [16] ) provides a second target region. In the assembly reported in the present paper, the centromere, generally considered one of the most challenging regions of the genome to assemble, was also considered using Bionano  [17]  maps to both confirm the assembly and to provide direction for resolving inconsistencies between cytological and assembly data. Manual annotation was performed based on the automated annotations  [1]  (RefSeq annotation v1. 1), using alignments of available RNA-seq data  [3, 18]  to ensure gene models were consistent with transcriptome evidence. In the present study, we used the Gydle bioinformatics (https://www. gydle. com/) software suite to produce an independent assembly of chromosome 7A which integrated a new BAC-based assembly, high-resolution genetic and Bionano map assemblies, as well as chromosome-specific mate-pair data and BAC-based physical maps.
Physical map assembly Flow-sorted 7AS and 7AL telosomes (Additional file 1) were used to construct BAC libraries, comprising 58,368 and 61,056 clones respectively, which were all fingerprinted as described in  [19]. LTC software  [20]  was used to establish ordered assemblies of the BAC clones from the DNA fingerprint information in order to select an MTP BAC set for sequencing (Additional file 2: Figure  S3 ). The following procedure was carried out for 7AS and 7AL independently: a network of "overlaps" was constructed using Sulston score cutoff 1e -10. Five iterations of increased stringency were applied in increments of 1e -5 , as well as Q-clones being identified at each step  [20]. BAC contigs with less than 5 clones were not included in the final outputs. The physical assembly comprised 380 BAC contigs on 7AS (352 on 7AL) and contained 42,244 clones on 7AS (47,776 on 7AL), from which an MTP of 5280 clones for 7AS (5832 on 7AL) was defined with an estimated total length for 7AS of 353 Mb (402 Mb for 7AL).
BAC set assemblies The 732 MTP BAC sets were sequenced in 813 pools, with each pool comprising no more than 40 BACs (the median number of BACs per pool was 11). This generated 1. 67 billion paired reads, which were first assembled independently for each BAC set using ABySS  [21]  to produce a stage 1 assembly of 882 Mb of sequence in 74,572 contigs. These contigs were used to seed a stage 2 assembly based on the use of Nuclear, Resolve and Vision software (https://www. gydle. com/). These tools allow the sensitive alignment of raw data and resolution of conflicts with raw data, together with real-time visualization, to assemble BAC sets simultaneously using all available datasets. The datasets included the BAC set paired-end reads, mate-pair reads from whole genome and flow-sorted 7AS and 7AL telosomes and the raw data from the 7AS and 7AL survey sequencing  [2].
Bionano map assembly and island construction Bionano optical data were generated from independently flow-sorted 7AS and 7AL telosomes producing 360,390 molecules on 7AS (416,563 on 7AL), representing 192× coverage on 7AS (238× on 7AL). The Bionano IrysView software was used to assemble the 178,217 7AS molecules into 783 optical maps (145,207 molecules into 330 maps for 7AL). The total length of the optical maps was 447 Mb for 7AS (413 Mb for 7AL) with an N50 length of 1. 55 Mb on 7AS (2. 07 Mb on 7AL). These data and the BAC set stage 2 scaffolds were combined using Gydle optical mapping and assembly software to produce islands, representing connected sets of sequence scaffolds and optical maps. This process included a map validation step using molecule alignments to identify a set of high-confidence maps (272 maps on 7AS, 270 on Fig.
BAC set finishing and assembly integration Several regions of the chromosome were selected for designing our finishing process (stage 3), using the Gydle software with an emphasis on complete data integration and systematic human visual review in order to achieve BAC set assembly completion: namely, a single, gapless contig of finished-quality sequence per BAC set supported by the consistency of sequence, physical mapping and optical data at the raw and assembled level, including the resolution of close repeats. We finished 30 BAC sets (representing 25 Mb) with this process and extended it to allow the inclusion of IWGSC (assembly and raw) data to compare, qualify and integrate the assemblies, with the view to being able to finish a sequence for the whole chromosome (i. e. outside BAC sets as well).
Using Nuclear software (see Methods and Additional file 4) to align IWGSC RefSeq v1. 0 contigs (27,651 contigs; length 724. 64 Mb) to the Gydle assembly v3. 0 and stringent mapping parameters, we found 11,050 contigs that matched the Gydle assembly exactly (193. 35 Mb) and 13,539 contigs that had a partial (> 90%) sequence match (484. 54 Mb), while the remaining 3062 contigs (46. 75 Mb) had no matching sequence in the Gydle assembly (consistent with the missing sequence between BAC sets). Using a stringent approach, these alignments were used to identify potential gap sequences, where only gaps between consecutive mappings of IWGSC RefSeq v1. 0 contigs within Gydle contigs were selected both within scaffold and between scaffold gaps. We were able to bridge 82 of the 193 scaffold-scaffold gaps in the IWGSC RefSeq v1.
If the physical contig evidence was unambiguous, the markers were set aside for reconsideration in light of more evidence being obtained. b An example of a locally finished sequence (BAC pool 7AS-11826; 655 Kb) showing integration of multiple data types: paired-end Illumina data from BACs (top, green); three independent mate-pair libraries; Minimum tiling path (MTP) BAC start and end points, based on mapping junction with vector; Bionano optical map alignments. Note that coverage of BAC pool data varies depending on double and triple coverage of BACs in MTP. Sequence is contiguous with no gaps. The assembled sequence joined two Bionano maps. This 655 Kb contig included the P450 gene, TaCYP78A3, shown to be associated with variation in grain size  [48]  sequences are often present in existing datasets.
0 7A pseudomolecule, which we targeted for complete sequence finishing (Fig. 4 ). The region is covered by two scaffolds (scaf-fold274331-1 and scaffold91613) in IWGSC RefSeq v1. 0  [1] , where the 2. 262 Mb pseudomolecule sequence contains 37,065 uncalled bases (N) in 101 gaps. In the Gydle assembly, the core region, contained within a single island, was covered at 94% by 5 non-overlapping BAC sets (7AL-12138, 7AL-05057, 7AL-12241, 7AL-00419 and 7AL-11456). We performed finishing on these BAC sets to produce 2,125,896 bp of the region, then finished the intervals between BAC sets using the raw sequence data (IWGSC and our 7A mate-pair libraries) combined with Bionano to resolve 144,424 bp. The finished core yield QTL region is a gapless contig of 2,270,131 bp (Additional file 10). Manual curation of all the IWGSC gene models across this region enabled many small annotation inconsistencies to be detected and corrected, most of which arose because of micro-assembly ambiguities.
0 (gray) from 340 Mb to 370 Mb. The break in both the Gydle and Bionano maps in the 349 Mb region is referenced in the text as well as Fig. 6a   the Gydle assembly around this region in IWGSC RefSeq v1. 0 identified a gap in coverage of BAC data on the 7AL side of the assembly (Fig. 5a ). Alignment of raw IWGSC CSS data across the region (Fig. 6c, d ) showed a sharp drop in coverage to background levels at exactly the same location; however, alignment of the raw data used in the IWGSC RefSeq v1. 0 assembly indicated this region was present in the whole genome data (Additional file 2: Figure  S7 ), implying a deletion of around 2 Mb in the 7AL ditelosomic stock (Fig. 6 ). Although the 7AS telosome appears to be missing a major CENH3 binding domain, records for tracking the transmission of the two telosomes in the Wheat Genetics Resource Center, Kansas State University showed the transmission rates for the two telosomes were similar, implying that 7AS must also have an active centromere.
The Bionano maps were particularly valuable as an independent source of linear sequence information when assemblies conflicted. Two target regions of chromosome 7A were studied in detail to explore the requirements for finishing the genome sequence of the reference assembly at a broader level. These sequences are the largest complete sequences available in wheat and highlight that merging sequences from multiple assemblies to achieve complete finishing is possible but will require the re-referencing, preferably simultaneously rather than sequentially, of the multiple raw datasets and types to provide final validation where assembles agree, and to provide information to resolve conflicts between assemblies as these are found. One of the 2. 5 Mb regions that was finished overlapped the QTL initially defined by Huynh et al.
Independent assembly of chromosome 7A The BAC library of 119,424 BACs (58,368 and 61,056 on 7AS and 7AL, respectively) from flow-sorted chromosome arm 7A DNA was fingerprinted using the SNap-Shot method  [19]  and assembled into physical contigs using LTC software  [20]. The physical map comprised 732 BAC contigs and an MTP of 11,451 BACs totalling an estimated 755 Mb. For each physical contig, the MTP BACs were pooled into groups of no more than 20 BACs. These BAC pools were then shotgun sequenced using Illumina paired-end technology. The BAC pool sequence data were first assembled separately for each physical contig using ABySS, totalling 882 Mb in 74,572 contigs. The BAC pool-based contigs provided the starting point for integrating the various datasets using Gydle software (Philippe Rigault, Gydle Inc.
, Quebec City, Canada, https://www. gydle. com/bioinformatics; [34, 35] ). An initial multiple alignment was produced using the Nuclear software (Gydle Inc. ) as part of the hybrid assembly of the available datasets. Reprocessing of BAC pool assemblies identified BAC ends and removed low-quality reads, and thus allowed BAC clones to be identified that were not true components of the respective pools. Vision software (Gydle Inc. ) was used to visualize assemblies in a semi-manual curation process with assembly metrics calculated using Perl, R and Shell scripts. An iterative process provided the basis for integrating extensive mate-pair data, Bionano data and Key-Gene Whole Genome Profiling (WGP™) tags  [1]. The three stages can be summarized as (1) integrating the BAC pool mapping and sequencing data with multiple mate-pair datasets (see also Additional file 1); (2) extending and refining scaffolds based on iterative realignments of the sequence data; and (3) cross-validating the sequence assembly with physical mapping data to link scaffolds with physical contigs, identifying missing BACs, contaminations and physical contig errors, and allowing for selected regions to undergo interactive editing and visualization in order to produce a locally finished, manually reviewed sequence.
It was possible to connect consecutive BAC pool sequence assemblies using Bionano optical maps generated from flow-sorted Chinese Spring 7AS/7AL telosomic lines with the sequence structure visualized by fluorescent labelling of Nt. BspQI nickase (GCTCTTC) sites (details below), to construct scaffolds or "islands" covering 735. 1 Mb. The 18 largest islands comprised more than 50% of the total sequence. The Gydle website (https://www. gydle. com/) provides information on accessing the software as well as the solutions and services provided by the Gydle company. The scale and novelty of this work required not only capabilities that were (and still are) not available in any other product (open source or commercial) but also specific developments to accommodate both the integration of specific data and their vizualization (e.
De novo assembly of Bionano maps was performed by a pairwise comparison of all single molecules and graph building  [36]. A p-value threshold of 1e -10 was used during the pairwise assembly, 1e -10 for extension and refinement steps, and 1e -15 for final refinement. The use of Bionano data in the 7A assembly is a significant advance over the work of Staňková et al. [17] , as the Gydle software performs a scalable and true hybrid optical/sequence assembly enabling local sequence resolution (e. g. gaps, tandem repeats) based on systematic comparisons of distances in optical and sequence space, as well as map validation using molecule data.
Linkage disequilibrium analysis A diverse spring bread wheat collection (n = 863) comprising landraces and elite cultivars was used in this study to understand the haplotype structure and extent of linkage disequilibrium (LD) in the yield QTL region on 7A, coordinates 671,200,000-675,300,000 bp. LD values were estimated and visualized using the Haploview software  [37] , and only common SNPs with high minor allele frequency (MAF > 0. 3) and present within 2000 bp on either side of the gene were included in this analysis. A total of 203 SNPs within 35 gene models (plus 2000 bp on either side) spanning the whole region were identified. We could not detect any common SNPs in the remaining 18 genes in the QTL region. The associations (Fig. 4 ) were colour coded as follows: bright red D' = 1. 0 and LOD > 2.
Defining the centromere To confirm the presence of a large missing CENH3 binding domain in the 7AS di-telosomic stock we aligned the 7AS (SRR697699, SRR697706, SRR697723) and 7AL (SRR697675, SRR697676, SRR697680), 101 bp paired-end Illumina reads generated for the CSS assembly to the chromosome 7A assembly using Nuclear software (Gydle) with filtering for minimum base quality of Phred 20, minimum length per side of 50 and paired reads only, and mapping parameters allowing a single mismatch in an HSP of length 50, a minimum alignment length of 50 bp, a sensitivity of 25 and a k of 13 (~98% identity). See also Additional files 12 and 13.
Acknowledgements The authors are grateful to  DM Appels  for her dedication in establishing the early molecular genetic maps for chromosome 7A. Bernd Friebe  is acknowledged for his guidance in the cytological studies of  7AS  and  7AL. Etienne Paux  is acknowledged for his guidance with the genetic and physical map alignments. Part of this work was supported by resources provided by the  Pawsey Supercomputing Centre  with funding from the  Australian Government and the Government of Western Australia. The authors are grateful to  Professor Jia Jizeng  for discussion in relation to the genome assembly of Aikang 58.
Availability of data and material The data and material used are as follows: Wheat chromosome 7A mate-pair data from flowsorted chromosomes  [38]  IWGSC Wheat Chromosome 7A BACs sequenced in pools based on the physical map minimum tiling path (MTP) with Illumina HiSeq 2500  [39]  Sequencing of a Chinese Spring wheat with 7EL addition from Thinopyrum elongatum  [40]  Stage 3 Gydle assembly of chromosome 7A in fasta format and Bionano assemblies  [41].
The best frames are selected by software tools popular in the amateur community such as AutoStakkert  (Kraaikamp, 2016)  and stacked into high signal to noise ratio images. The stacks are processed with either high-pass filters or wavelet sharpening software resulting in enhanced images  (Mousis et al. , 2014). Consequently, public repositories of amateur images of the planets are now widely used by professional astronomers to complement or guide their observations with professional telescopes  (Hueso et al. , 2010a (Hueso et al. , , 2018a)). One of the key contributions of amateur astronomers is their capacity to obtain large amounts of observations sampling the timedomain with a high temporal cadence from the collaboration of many individual observers. Therefore, amateur astronomers can discover unexpected or unpredictable events in Solar System science serendipitously even though many planets have dedicated space missions orbiting them.
Additionally, if a plume is observed, the SSA program provides tools that allow checking if transients in the solar wind have reached Mars previously to the event. In particular, the Heliospheric Weather Expert Service Centre Propagation Tool (PROPTOOL;  Rouillard et al. , 2017)  developed by the Centre de Données de la Physique des Plasmas (CDPP), allows easy access to data from different space probes and provides graphic tools (see Fig. 3 ) that permit a characterization of solar wind transients and a calculation of estimated times of arrival of CME to planets and probes. Other spaces agencies provide also space weather alerts and prediction tools. The NOAA Space Weather Prediction Center (SPWC) gives access to a complete set of alerts and forecasts, and NASA's Integrated Space Weather Analysis System (iSWA), provides a very flexible and easy to use web-based system that gives access to space weather information.
3 lm images at least until December 2009. If such an event were observed again in favorable conditions close to Jupiter's opposition, the better sensitivity of  cameras currently used by amateur observers in the near infrared would allow a longer time-line of observations of the debris dispersal using filters centered in the strong methane absorption band at 890 nm (cameras used by amateur observers since 2016 have increased by a factor of 4 their quantum efficiency in the near infrared when compared with cameras used in 2009). Smaller debris fields produced by smaller and more frequent impacts can also be observable with the current technology and the larger number of amateur observers performing high-quality observations or even using 1-m size telescopes. An overall comparison of amateur observations of Jupiter from 2009 to 2018 from images archived in the Planetary Virtual Observatory and Laboratory (PVOL) database  (Hueso et al.
, 2010a (Hueso et al. , , 2018a) )  shows excellent perspectives in this regard. This database contains almost 40 000 observations of Solar System planets since the year 2000 and can be consulted online on its own website (http://pvol2. ehu. eus) or through the Virtual European Space Planetary Access (VESPA) query interface (http://vespa. obspm. fr/) (Erard et al. , 2018). While PVOL has been designed for scientific use of the data, we acknowledge the existence of similar databases like that of the Association of Lunar and Planetary Observers (ALPO) (http://alpo-j. asahikawa-med. ac. jp/), and many national astronomical databases like that of the Societé Astronomique de France (SAF) (http:// www. astrosurf. com/planetessaf/). An inspection of images in these databases and image repositories shows that, instead of a large increase in quality in the images acquired by the best observers, the main advantage of modern amateur data compared with amateur data obtained 10 years ago are: (i) the better overall quality and the larger number of excellent observers able to attain diffraction-limited images and, (ii) observations acquired by a few excellent observers with access to telescopes with apertures of 50 cm or larger.
Additionally, statistical analysis of data stored in the PVOL database shows that modern amateur observations of Jupiter in 2016-2017 are 2. 5 times more numerous in visible wavelengths and 15 times more numerous in the methane absorption filter than in 2009. These methane band images are particularly useful for the discovery and long-term track of impact debris. Considerable uncertainty exists in the current impact rate on Jupiter. Hueso et al. (2018b)  present arguments suggesting that dark debris fields on Jupiter's atmosphere from intermediate size objects could be found once every 4-12 years.
There is an additional difficulty in detecting Jovian flashing impacts. Even if Jupiter is observed while an impact happens, and a video of the event is recorded with a reasonable signal to noise ratio, it may still skip detection. The reason is that most amateur observers obtain their video observations over long observing sessions in order to build ''stacked'' images of the planet that can be processed to build high-resolution images  (Mousis et al. , 2014; Hueso et al. , 2018a). The task of transforming a video into a final images is generally performed by automatic software tools that stack minutes of data  (Kraaikamp, 2016)  erasing the potential signal of a short-time visible impact in the final image. Additionally, only a small proportion of amateurs carefully check their video observations while they are running a long observation run.
Detection software Impacts can be automatically detected using differential photometry algorithms in which each video frame is compared with a reference image showing the impact location. Software tools aimed to detect impacts exist indeed for the analysis of videos of the non-illuminated observable part of the Moon like the MIDAS software  (Madiedo et al. , 2015). However, Jupiter observations have different requirements (large magnification and strong influence of the atmospheric seeing, bright background in the pixels where the impact happen, large variety of acquisition cameras and video formats). While it would be almost impossible to set-up a server where individual observers could upload their raw observations for analysis (that would require a large infrastructure capable of analyzing hundreds of Terabytes of data), we have developed an open source software tool called DeTeCt that performs this task and that can be distributed to individual observers willing to perform the search of impacts.
Because of historical reasons there are two versions of the software being used by the amateur community DeTeCt2 (a Windows/Linux application running from the command line) and DeTeCt3. 1 (a Windows application with a Graphical User Interface that has been developed to make the software easier to use for a wider audience). The development of DeTeCt3. 1 has been one of the virtual activities of the Planetary Space Weather Services (PSWS) offered by the Europlanet H2020 Research Infrastructure  (André et al. , 2018). Both software tools can analyze hundreds of video files recursively from a specified folder and both run essentially the same detection algorithm. In both cases, they produce ''detection images'' and log files that are sent to one of us (M. D. ) for statistical analysis of the nondetections.
Updated results are published online on: http:// www. astrosurf. com/planetessaf/doc/project_detect. shtml Considerable efforts were put in the software to analyze the large range of video formats produced by cameras used by amateur astronomers. The software and its source code are available at the PVOL database (http://pvol2. ehu. es/psws/ jovian_impacts) together with background scientific information and a software guide with detailed instructions. The source code is also available in the github platform with the project name: ''DeTeCt-PSWS'' under license GNU AGPLv3 (see https://github. com/DeTeCt-PSWS/DeTeCt-MFC). The software is open source, documented, and can be modified accordingly. We now give a summarized description of the algorithms and steps followed by DeTeCt to analyze video observations and find short flashes of light.
Success rates for the 11 video recording are: 55% for the detection algorithm and 90% for the automatic analysis of detection images. Direct observation of the videos is only accurate if the observer is willing to spend his time reviewing observations. However, the main advantage of the DeTeCt software is that it can be used without any interaction from the user to analyze large collections of video files. Thus, the user should only spend his time reviewing the detection images and log files. The use of the software by a large number of amateurs may result in detections of new impacts but also of.