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      Improving Transgenesis Efficiency and CRISPR-Associated Tools Through Codon Optimization and Native Intron Addition in Pristionchus Nematodes

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          Abstract

          A lack of appropriate molecular tools is one obstacle that prevents in-depth mechanistic studies in many organisms. Transgenesis, clustered regularly interspaced short palindromic repeats (CRISPR)-associated engineering, and related tools are fundamental in the modern life sciences, but their applications are still limited to a few model organisms. In the phylum Nematoda, transgenesis can only be performed in a handful of species other than Caenorhabditis elegans, and additionally, other species suffer from significantly lower transgenesis efficiencies. We hypothesized that this may in part be due to incompatibilities of transgenes in the recipient organisms. Therefore, we investigated the genomic features of 10 nematode species from three of the major clades representing all different lifestyles. We found that these species show drastically different codon usage bias and intron composition. With these findings, we used the species Pristionchus pacificus as a proof of concept for codon optimization and native intron addition. Indeed, we were able to significantly improve transgenesis efficiency, a principle that may be usable in other nematode species. In addition, with the improved transgenes, we developed a fluorescent co-injection marker in P. pacificus for the detection of CRISPR-edited individuals, which helps considerably to reduce associated time and costs.

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          featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

          Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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            HISAT: a fast spliced aligner with low memory requirements.

            HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.
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              Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data

              Massively-parallel cDNA sequencing has opened the way to deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here, we present the Trinity methodology for de novo full-length transcriptome reconstruction, and evaluate it on samples from fission yeast, mouse, and whitefly – an insect whose genome has not yet been sequenced. Trinity fully reconstructs a large fraction of the transcripts present in the data, also reporting alternative splice isoforms and transcripts from recently duplicated genes. In all cases, Trinity performs better than other available de novo transcriptome assembly programs, and its sensitivity is comparable to methods relying on genome alignments. Our approach provides a unified and general solution for transcriptome reconstruction in any sample, especially in the complete absence of a reference genome.
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                Author and article information

                Journal
                Genetics
                Genetics
                genetics
                genetics
                genetics
                Genetics
                Genetics Society of America
                0016-6731
                1943-2631
                December 2020
                15 October 2020
                15 October 2020
                : 216
                : 4
                : 947-956
                Affiliations
                [1]Max Planck Institute for Developmental Biology, Tuebingen 72076, Germany
                Author notes
                [2 ]Corresponding author: Max Planck Institute for Developmental Biology, Department for Integrative Evolutionary Biology, Max-Planck-Ring 9, 72076 Tübingen, Germany. E-mail: ralf.sommer@ 123456tuebingen.mpg.de
                Author information
                http://orcid.org/0000-0001-8341-0678
                http://orcid.org/0000-0002-2438-0015
                http://orcid.org/0000-0002-5835-2135
                http://orcid.org/0000-0003-1503-7749
                Article
                303785
                10.1534/genetics.120.303785
                7768246
                33060138
                31487400-b4f1-443f-b1c1-d734ac191f0f
                Copyright © 2020 by the Genetics Society of America

                Available freely online through the author-supported open access option.

                History
                : 09 September 2020
                : 14 October 2020
                Page count
                Figures: 4, Tables: 1, Equations: 0, References: 71, Pages: 10
                Categories
                Investigations
                Communications

                Genetics
                nematodes,c. elegans,p. pacificus,transgenesis,crispr editing,codon usage bias,intron-mediated enhancement,parasitic nematodes

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