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1. A high-throughput skim-sequencing approach for genotyping, dosage estimation and identifying translocations

   https://doi.org/10.1038/s41598-022-19858-2  

   Adhikari, Laxman; Shrestha, Sandesh; Wu, Shuangye; Crain, Jared; Gao, Liangliang; Evers, Byron; Wilson, Duane; Ju, Yoonha; Koo, Dal-Hoe; Hucl, Pierre; et al (October 2022, Scientific Reports)

   Abstract The development of next-generation sequencing (NGS) enabled a shift from array-based genotyping to directly sequencing genomic libraries for high-throughput genotyping. Even though whole-genome sequencing was initially too costly for routine analysis in large populations such as breeding or genetic studies, continued advancements in genome sequencing and bioinformatics have provided the opportunity to capitalize on whole-genome information. As new sequencing platforms can routinely provide high-quality sequencing data for sufficient genome coverage to genotype various breeding populations, a limitation comes in the time and cost of library construction when multiplexing a large number of samples. Here we describe a high-throughput whole-genome skim-sequencing (skim-seq) approach that can be utilized for a broad range of genotyping and genomic characterization. Using optimized low-volume Illumina Nextera chemistry, we developed a skim-seq method and combined up to 960 samples in one multiplex library using dual index barcoding. With the dual-index barcoding, the number of samples for multiplexing can be adjusted depending on the amount of data required, and could be extended to 3,072 samples or more. Panels of doubled haploid wheat lines (Triticum aestivum, CDC Stanley x CDC Landmark), wheat-barley (T.aestivumxHordeum vulgare) and wheat-wheatgrass (Triticum durum x Thinopyrum intermedium) introgression lines as well as known monosomic wheat stocks were genotyped using the skim-seq approach. Bioinformatics pipelines were developed for various applications where sequencing coverage ranged from 1 × down to 0.01 × per sample. Using reference genomes, we detected chromosome dosage, identified aneuploidy, and karyotyped introgression lines from the skim-seq data. Leveraging the recent advancements in genome sequencing, skim-seq provides an effective and low-cost tool for routine genotyping and genetic analysis, which can track and identify introgressions and genomic regions of interest in genetics research and applied breeding programs. 

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2. Sequencing Illumina libraries at high accuracy on the ONT MinION using R2C2

   https://doi.org/10.1101/gr.277031.122  

   Zee, Alexander; Deng, Dori Z.Q.; Adams, Matthew; Schimke, Kayla D.; Corbett-Detig, Russell; Russell, Shelbi L.; Zhang, Xuan; Schmitz, Robert J.; Vollmers, Christopher (November 2022, Genome Research)

   High-throughput short-read sequencing has taken on a central role in research and diagnostics. Hundreds of different assays take advantage of Illumina short-read sequencers, the predominant short-read sequencing technology available today. Although other short-read sequencing technologies exist, the ubiquity of Illumina sequencers in sequencing core facilities and the high capital costs of these technologies have limited their adoption. Among a new generation of sequencing technologies, Oxford Nanopore Technologies (ONT) holds a unique position because the ONT MinION, an error-prone long-read sequencer, is associated with little to no capital cost. Here we show that we can make short-read Illumina libraries compatible with the ONT MinION by using the rolling circle to concatemeric consensus (R2C2) method to circularize and amplify the short library molecules. This results in longer DNA molecules containing tandem repeats of the original short library molecules. This longer DNA is ideally suited for the ONT MinION, and after sequencing, the tandem repeats in the resulting raw reads can be converted into high-accuracy consensus reads with similar error rates to that of the Illumina MiSeq. We highlight this capability by producing and benchmarking RNA-seq, ChIP-seq, and regular and target-enriched Tn5 libraries. We also explore the use of this approach for rapid evaluation of sequencing library metrics by implementing a real-time analysis workflow. 

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3. Untangling an insect’s virome from its endogenous viral elements

   https://doi.org/10.1186/s12864-023-09737-z  

   Rozo-Lopez, Paula; Brewer, William; Käfer, Simon; Martin, McKayla M.; Parker, Benjamin J. (October 2023, BMC Genomics)

   Abstract BackgroundInsects are an important reservoir of viral biodiversity, but the vast majority of viruses associated with insects have not been discovered. Recent studies have employed high-throughput RNA sequencing, which has led to rapid advances in our understanding of insect viral diversity. However, insect genomes frequently contain transcribed endogenous viral elements (EVEs) with significant homology to exogenous viruses, complicating the use of RNAseq for viral discovery. MethodsIn this study, we used a multi-pronged sequencing approach to study the virome of an important agricultural pest and prolific vector of plant pathogens, the potato aphidMacrosiphum euphorbiae. We first used rRNA-depleted RNAseq to characterize the microbes found in individual insects. We then used PCR screening to measure the frequency of two heritable viruses in a local aphid population. Lastly, we generated a quality draft genome assembly forM. euphorbiaeusing Illumina-corrected Nanopore sequencing to identify transcriptionally active EVEs in the host genome. ResultsWe found reads from two insect-specific viruses (aFlavivirusand anAmbidensovirus) in our RNAseq data, as well as a parasitoid virus (Bracovirus), a plant pathogenic virus (Tombusvirus), and two phages (Acinetobacter and APSE). However, our genome assembly showed that part of the ‘virome’ of this insect can be attributed to EVEs in the host genome. ConclusionOur work shows that EVEs have led to the misidentification of aphid viruses from RNAseq data, and we argue that this is a widespread challenge for the study of viral diversity in insects. 

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4. Rapid and cost-effective generation of single specimen multilocus barcoding data from whole arthropod communities by multiple levels of multiplexing

   https://doi.org/10.1038/s41598-019-54927-z  

   de Kerdrel, Guillemette A.; Andersen, Jeremy C.; Kennedy, Susan R.; Gillespie, Rosemary; Krehenwinkel, Henrik (January 2020, Scientific Reports)

   Abstract In light of the current biodiversity crisis, molecular barcoding has developed into an irreplaceable tool. Barcoding has been considerably simplified by developments in high throughput sequencing technology, but still can be prohibitively expensive and laborious when community samples of thousands of specimens need to be processed. Here, we outline an Illumina amplicon sequencing approach to generate multilocus data from large collections of arthropods. We reduce cost and effort up to 50-fold, by combining multiplex PCRs and DNA extractions from pools of presorted and morphotyped specimens and using two levels of sample indexing. We test our protocol by generating a comprehensive, community wide dataset of barcode sequences for several thousand Hawaiian arthropods from 14 orders, which were collected across the archipelago using various trapping methods. We explore patterns of diversity across the Archipelago and compare the utility of different arthropod trapping methods for biodiversity explorations on Hawaii, highlighting undergrowth beating as highly efficient method. Moreover, we show the effects of barcode marker, taxonomy and relative biomass of the targeted specimens and sequencing coverage on taxon recovery. Our protocol enables rapid and inexpensive explorations of diversity patterns and the generation of multilocus barcode reference libraries across whole ecosystems. 

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5. Sequencing Strategy to Ensure Accurate Plasmid Assembly - Data

   https://doi.org/10.6084/m9.figshare.25033706.v7  

   Hernandez, Sarah; Berezin, Casey-Tyler; Peccoud, Jean; Miller, Katie; Peccoud, Samuel J (January 2024, figshare)

   The raw data and generated assemblies from Illumina MiSeq, Oxford Nanopore MinION, and Sanger Sequencing. 

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