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      The genome of the soybean gall midge ( Resseliella maxima)

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          Abstract

          The cecidomyiid fly, soybean gall midge, Resseliella maxima Gagné, is a recently discovered insect that feeds on soybean plants in the Midwestern United States. R. maxima larvae feed on soybean stems that may induce plant death and can cause considerable yield losses, making it an important agricultural pest. From three pools of 50 adults each, we used long-read nanopore sequencing to assemble a R. maxima reference genome. The final genome assembly is 206 Mb with 64.88× coverage, consisting of 1,009 contigs with an N50 size of 714 kb. The assembly is high quality with a Benchmarking Universal Single-Copy Ortholog (BUSCO) score of 87.8%. Genome-wide GC level is 31.60%, and DNA methylation was measured at 1.07%. The R. maxima genome is comprised of 21.73% repetitive DNA, which is in line with other cecidomyiids. Protein prediction annotated 14,798 coding genes with 89.9% protein BUSCO score. Mitogenome analysis indicated that R. maxima assembly is a single circular contig of 15,301 bp and shares highest identity to the mitogenome of the Asian rice gall midge, Orseolia oryzae Wood-Mason. The R. maxima genome has one of the highest completeness levels for a cecidomyiid and will provide a resource for research focused on the biology, genetics, and evolution of cecidomyiids, as well as plant–insect interactions in this important agricultural pest.

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          Most cited references29

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          Improved metagenomic analysis with Kraken 2

          Although Kraken’s k-mer-based approach provides a fast taxonomic classification of metagenomic sequence data, its large memory requirements can be limiting for some applications. Kraken 2 improves upon Kraken 1 by reducing memory usage by 85%, allowing greater amounts of reference genomic data to be used, while maintaining high accuracy and increasing speed fivefold. Kraken 2 also introduces a translated search mode, providing increased sensitivity in viral metagenomics analysis.
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            BUSCO Update: Novel and Streamlined Workflows along with Broader and Deeper Phylogenetic Coverage for Scoring of Eukaryotic, Prokaryotic, and Viral Genomes

            Methods for evaluating the quality of genomic and metagenomic data are essential to aid genome assembly procedures and to correctly interpret the results of subsequent analyses. BUSCO estimates the completeness and redundancy of processed genomic data based on universal single-copy orthologs. Here, we present new functionalities and major improvements of the BUSCO software, as well as the renewal and expansion of the underlying data sets in sync with the OrthoDB v10 release. Among the major novelties, BUSCO now enables phylogenetic placement of the input sequence to automatically select the most appropriate BUSCO data set for the assessment, allowing the analysis of metagenome-assembled genomes of unknown origin. A newly introduced genome workflow increases the efficiency and runtimes especially on large eukaryotic genomes. BUSCO is the only tool capable of assessing both eukaryotic and prokaryotic species, and can be applied to various data types, from genome assemblies and metagenomic bins, to transcriptomes and gene sets.
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              RepeatModeler2 for automated genomic discovery of transposable element families

              The accelerating pace of genome sequencing throughout the tree of life is driving the need for improved unsupervised annotation of genome components such as transposable elements (TEs). Because the types and sequences of TEs are highly variable across species, automated TE discovery and annotation are challenging and time-consuming tasks. A critical first step is the de novo identification and accurate compilation of sequence models representing all of the unique TE families dispersed in the genome. Here we introduce RepeatModeler2, a pipeline that greatly facilitates this process. This program brings substantial improvements over the original version of RepeatModeler, one of the most widely used tools for TE discovery. In particular, this version incorporates a module for structural discovery of complete long terminal repeat (LTR) retroelements, which are widespread in eukaryotic genomes but recalcitrant to automated identification because of their size and sequence complexity. We benchmarked RepeatModeler2 on three model species with diverse TE landscapes and high-quality, manually curated TE libraries: Drosophila melanogaster (fruit fly), Danio rerio (zebrafish), and Oryza sativa (rice). In these three species, RepeatModeler2 identified approximately 3 times more consensus sequences matching with >95% sequence identity and sequence coverage to the manually curated sequences than the original RepeatModeler. As expected, the greatest improvement is for LTR retroelements. Thus, RepeatModeler2 represents a valuable addition to the genome annotation toolkit that will enhance the identification and study of TEs in eukaryotic genome sequences. RepeatModeler2 is available as source code or a containerized package under an open license ( https://github.com/Dfam-consortium/RepeatModeler , http://www.repeatmasker.org/RepeatModeler/ ).
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                Author and article information

                Contributors
                Role: Editor
                Journal
                G3 (Bethesda)
                Genetics
                g3journal
                G3: Genes|Genomes|Genetics
                Oxford University Press (US )
                2160-1836
                April 2023
                02 March 2023
                02 March 2023
                : 13
                : 4
                : jkad046
                Affiliations
                Department of Entomology, College of Food, Agricultural and Natural Resource Sciences, University of Minnesota , Minneapolis, MN 55455, USA
                Department of Entomology, College of Food, Agricultural and Natural Resource Sciences, University of Minnesota , Minneapolis, MN 55455, USA
                Department of Animal Science, College of Food, Agricultural and Natural Resource Sciences, University of Minnesota , Minneapolis, MN 55455, USA
                Department of Veterinary and Biomedical Sciences, College of Veterinary Medicine, University of Minnesota , Minneapolis, MN 55455, USA
                Department of Veterinary and Biomedical Sciences, College of Veterinary Medicine, University of Minnesota , Minneapolis, MN 55455, USA
                Department of Entomology, College of Food, Agricultural and Natural Resource Sciences, University of Minnesota , Minneapolis, MN 55455, USA
                Department of Veterinary and Biomedical Sciences, College of Veterinary Medicine, University of Minnesota , Minneapolis, MN 55455, USA
                Department of Entomology, College of Food, Agricultural and Natural Resource Sciences, University of Minnesota , Minneapolis, MN 55455, USA
                Department of Entomology, College of Food, Agricultural and Natural Resource Sciences, University of Minnesota , Minneapolis, MN 55455, USA
                Department of Animal Science, College of Food, Agricultural and Natural Resource Sciences, University of Minnesota , Minneapolis, MN 55455, USA
                Department of Entomology, College of Food, Agricultural and Natural Resource Sciences, University of Minnesota , Minneapolis, MN 55455, USA
                Department of Entomology, College of Food, Agricultural and Natural Resource Sciences, University of Minnesota , Minneapolis, MN 55455, USA
                Department of Animal Science, College of Food, Agricultural and Natural Resource Sciences, University of Minnesota , Minneapolis, MN 55455, USA
                Author notes
                Corresponding author: Email: cfaulk@ 123456umn.edu

                Conflicts of interest statement The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0002-4853-3573
                https://orcid.org/0000-0003-3354-7419
                https://orcid.org/0000-0002-9749-9658
                Article
                jkad046
                10.1093/g3journal/jkad046
                10085792
                36861345
                0ab37543-9511-4d44-83fd-85fa74e8d866
                © The Author(s) 2023. Published by Oxford University Press on behalf of the Genetics Society of America.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 31 January 2023
                : 16 February 2023
                : 14 March 2023
                Page count
                Pages: 8
                Funding
                Funded by: NIH, doi 10.13039/100000002;
                Award ID: T32OD010993
                Award ID: R21AG071908
                Funded by: Impetus Grant;
                Funded by: Norn Foundation;
                Award ID: USDA-NIFA MIN-16-129
                Funded by: Minnesota Rapid Agricultural Response Fund;
                Categories
                Genome Report
                AcademicSubjects/SCI01180
                AcademicSubjects/SCI01140

                Genetics
                soybean,gall midge,nanopore,genome assembly,dna methylation
                Genetics
                soybean, gall midge, nanopore, genome assembly, dna methylation

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