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      Can plastid genome sequencing be used for species identification in Lauraceae?

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          Abstract

          Using DNA barcoding for species identification remains challenging for many plant groups. New sequencing approaches such as complete plastid genome sequencing may provide some increased power and practical benefits for species identification beyond standard plant DNA barcodes. We undertook a case study comparing standard DNA barcoding to plastid genome sequencing for species discrimination in the ecologically and economically important family Lauraceae, using 191 plastid genomes for 131 species from 25 genera, representing the largest plastome data set for Lauraceae to date. We found that the plastome sequences were useful in correcting some identification errors and for finding new and cryptic species. However, plastome data overall were only able to discriminate c. 60% of the species in our sample, with this representing a modest improvement from 40 to 50% discrimination success with the standard plant DNA barcodes. Beyond species discrimination, the plastid genome sequences revealed complex relationships in the family, with 12/25 genera being non-monophyletic and with extensive incongruence relative to nuclear ribosomal DNA. These results highlight that although useful for improving phylogenetic resolution in the family and providing some species-level insights, plastome sequences only partially improve species discrimination, and this reinforces the need for large-scale nuclear data to improve discrimination among closely related species.

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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            SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

            The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
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              BLAST+: architecture and applications

              Background Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
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                Author and article information

                Journal
                Botanical Journal of the Linnean Society
                Oxford University Press (OUP)
                0024-4074
                1095-8339
                September 01 2021
                August 10 2021
                March 22 2021
                September 01 2021
                August 10 2021
                March 22 2021
                : 197
                : 1
                : 1-14
                Affiliations
                [1 ]Plant Phylogenetics and Conservation Group, Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming, China
                [2 ]University of Chinese Academy of Sciences, Beijing, China
                [3 ]Genetics and Conservation Section, Royal Botanic Garden Edinburgh, Edinburgh, UK
                [4 ]Center of Conservation Biology, Core Botanical Gardens, Chinese Academy of Sciences, Mengla, China
                [5 ]Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, China
                [6 ]State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
                [7 ]Sino-African Joint Research Center, Chinese Academy of Sciences, Wuhan, China
                [8 ]Herbarium (KUN), Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
                [9 ]Tibet Agriculture & Animal Husbandry University, Nyingchi, China
                [10 ]Shandong Provincial Key Laboratory of Plant Stress Research, College of Life Sciences, Shandong Normal University, Ji’nan, China
                [11 ]Australian Centre for Evolutionary Biology and Biodiversity & Sprigg Geobiology Centre, School of Biological Sciences, University of Adelaide, Adelaide, Australia
                [12 ]Institute of Evolutionary Biology, Ashworth Laboratories, The University of Edinburgh, Edinburgh, UK
                [13 ]Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
                Article
                10.1093/botlinnean/boab018
                1322e7f7-a63b-4307-86d8-d02acfd074df
                © 2021

                http://creativecommons.org/licenses/by-nc-nd/4.0/

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