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      Genomic and cytogenetic analysis of the Ceratitis capitata temperature-sensitive lethal region

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          Abstract

          Genetic sexing strains (GSS) are an important tool in support of sterile insect technique (SIT) applications against insect pests and disease vectors. The yet unknown temperature-sensitive lethal ( tsl) gene and the recently identified white pupae ( wp) gene have been used as selectable markers in the most successful GSS developed so far, the Ceratitis capitata (medfly) VIENNA 8 GSS. The molecular identification of the tsl gene may open the way for its use as a marker for the development of GSS in other insect pests and disease vectors of SIT importance. Prior studies have already shown that the tsl gene is located on the right arm of chromosome 5, between the wp and Zw loci ( tsl genomic region). In the present study, we used genomic, transcriptomic, bioinformatic, and cytogenetic approaches to characterize and analyze this genomic region in wild-type and tsl mutant medfly strains. Our results suggested the presence of 561 genes, with 322 of them carrying SNPs and/or insertion–deletion (indel) mutations in the tsl genomic region. Furthermore, comparative transcriptomic analysis indicated the presence of 32 differentially expressed genes, and bioinformatic analysis revealed the presence of 33 orthologs with a described heat-sensitive phenotype of Drosophila melanogaster in this region. These data can be used in functional genetic studies to identify the tsl gene(s) and the causal mutation(s) responsible for the temperature-sensitive lethal phenotype in medfly, and potentially additional genes causing a similar phenotype.

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          Most cited references84

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          STAR: ultrafast universal RNA-seq aligner.

          Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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            edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

            Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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              Minimap2: pairwise alignment for nucleotide sequences

              Heng Li (2018)
              Recent advances in sequencing technologies promise ultra-long reads of ∼100 kb in average, full-length mRNA or cDNA reads in high throughput and genomic contigs over 100 Mb in length. Existing alignment programs are unable or inefficient to process such data at scale, which presses for the development of new alignment algorithms.
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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
                June 2023
                29 March 2023
                29 March 2023
                : 13
                : 6
                : jkad074
                Affiliations
                Insect Pest Control Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture , Friedensstrasse 1, 2444 Seibersdorf, Austria
                Department of Insect Biotechnology in Plant Protection, Justus-Liebig-University Gießen, Institute for Insect Biotechnology , Winchesterstr. 2, 35394 Gießen, Germany
                Insect Pest Control Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture , Friedensstrasse 1, 2444 Seibersdorf, Austria
                Laboratory of Systems Microbiology and Applied Genomics, Department of Sustainable Agriculture, University of Patras , 2 G. Seferi St., 30100, Agrinio, Greece
                Insect Pest Control Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture , Friedensstrasse 1, 2444 Seibersdorf, Austria
                Department of Insect Biotechnology in Plant Protection, Justus-Liebig-University Gießen, Institute for Insect Biotechnology , Winchesterstr. 2, 35394 Gießen, Germany
                McGill University Genome Centre, McGill University , Montreal, QC H3A 0G4, Canada
                Centre for Genomic Research, Institute of Integrative Biology , The Biosciences Building, Crown Street, L69 7ZB Liverpool, UK
                McGill University Genome Centre, McGill University , Montreal, QC H3A 0G4, Canada
                McGill University Genome Centre, McGill University , Montreal, QC H3A 0G4, Canada
                Laboratory of Systems Microbiology and Applied Genomics, Department of Sustainable Agriculture, University of Patras , 2 G. Seferi St., 30100, Agrinio, Greece
                Centre for Genomic Research, Institute of Integrative Biology , The Biosciences Building, Crown Street, L69 7ZB Liverpool, UK
                McGill University Genome Centre, McGill University , Montreal, QC H3A 0G4, Canada
                Department of Insect Biotechnology in Plant Protection, Justus-Liebig-University Gießen, Institute for Insect Biotechnology , Winchesterstr. 2, 35394 Gießen, Germany
                Insect Pest Control Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture , Friedensstrasse 1, 2444 Seibersdorf, Austria
                Author notes
                Corresponding author: Insect Pest Control Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Friedensstrasse 1, 2444 Seibersdorf, Austria. Email: k.bourtzis@ 123456iaea.org ; [* ]Corresponding author: Justus-Liebig-University Giessen, Department of Insect Biotechnology in Plant Protection, Winchesterstr. 2, 35394, Giessen, Germany. Email: marc.schetelig@ 123456agrar.uni-giessen.de

                Conflicts of interest The author(s) declare no conflict of interest.

                Article
                jkad074
                10.1093/g3journal/jkad074
                10234411
                36988332
                da34d4b5-c61d-4593-ab96-ca5b28b8fedb
                © 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
                : 22 December 2022
                : 16 March 2023
                : 26 April 2023
                Page count
                Pages: 31
                Funding
                Funded by: Insect Pest Control Subprogramme of the Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture;
                Funded by: contract CAN;
                Award ID: 23358
                Funded by: Canada Foundation for Innovation, DOI 10.13039/501100000196;
                Award ID: FF17000
                Funded by: Hort Frontiers Fruit Fly Fund;
                Funded by: Hort Frontiers;
                Funded by: Hort Innovation, DOI 10.13039/501100000981;
                Funded by: Macquarie University, DOI 10.13039/501100001230;
                Funded by: Australian Government, DOI 10.13039/100015539;
                Categories
                Investigation
                AcademicSubjects/SCI01180
                AcademicSubjects/SCI01140

                Genetics
                mediterranean fruit fly,sterile insect technique,genetic sexing strain,white pupae,tephritidae

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