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1. Chromosome‐level hybrid de novo genome assemblies as an attainable option for nonmodel insects

   https://doi.org/10.1111/1755-0998.13176  

   Jaworski, Coline C. ; Allan, Carson W. ; Matzkin, Luciano M. ( June 2020 , Molecular Ecology Resources)

   The emergence of third‐generation sequencing (3GS; long‐reads) is bringing closer the goal of chromosome‐size fragments in de novo genome assemblies. This allows the exploration of new and broader questions on genome evolution for a number of nonmodel organisms. However, long‐read technologies result in higher sequencing error rates and therefore impose an elevated cost of sufficient coverage to achieve high enough quality. In this context, hybrid assemblies, combining short‐reads and long‐reads, provide an alternative efficient and cost‐effective approach to generate de novo, chromosome‐level genome assemblies. The array of available software programs for hybrid genome assembly, sequence correction and manipulation are constantly being expanded and improved. This makes it difficult for nonexperts to find efficient, fast and tractable computational solutions for genome assembly, especially in the case of nonmodel organisms lacking a reference genome or one from a closely related species. In this study, we review and test the most recent pipelines for hybrid assemblies, comparing the model organismDrosophila melanogasterto a nonmodel cactophilicDrosophila,D. mojavensis. We show that it is possible to achieve excellent contiguity on this nonmodel organism using thedbg2olcpipeline.

    

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2. deMULTIplex2: robust sample demultiplexing for scRNA-seq

   https://doi.org/10.1186/s13059-024-03177-y  

   Zhu, Qin ; Conrad, Daniel N. ; Gartner, Zev J. ( January 2024 , Genome Biology)

   Sample multiplexing enables pooled analysis during single-cell RNA sequencing workflows, thereby increasing throughput and reducing batch effects. A challenge for all multiplexing techniques is to link sample-specific barcodes with cell-specific barcodes, then demultiplex sample identity post-sequencing. However, existing demultiplexing tools fail under many real-world conditions where barcode cross-contamination is an issue. We therefore developed deMULTIplex2, an algorithm inspired by a mechanistic model of barcode cross-contamination. deMULTIplex2 employs generalized linear models and expectation–maximization to probabilistically determine the sample identity of each cell. Benchmarking reveals superior performance across various experimental conditions, particularly on large or noisy datasets with unbalanced sample compositions.

    

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3. Beyond DNA barcoding: The unrealized potential of genome skim data in sample identification

   https://doi.org/10.1111/mec.15507  

   Bohmann, Kristine ; Mirarab, Siavash ; Bafna, Vineet ; Gilbert, M. Thomas P. ( June 2020 , Molecular Ecology)

   Genetic tools are increasingly used to identify and discriminate between species. One key transition in this process was the recognition of the potential of the ca 658bp fragment of the organelle cytochrome c oxidase I (COI) as a barcode region, which revolutionized animal bioidentification and lead, among others, to the instigation of the Barcode of Life Database (BOLD), containing currently barcodes from >7.9 million specimens. Following this discovery, suggestions for other organellar regions and markers, and the primers with which to amplify them, have been continuously proposed. Most recently, the field has taken the leap from PCR‐based generation of DNA references into shotgun sequencing‐based “genome skimming” alternatives, with the ultimate goal of assembling organellar reference genomes. Unfortunately, in genome skimming approaches, much of the nuclear genome (as much as 99% of the sequence data) is discarded, which is not only wasteful, but can also limit the power of discrimination at, or below, the species level. Here, we advocate that the full shotgun sequence data can be used to assign an identity (that we term for convenience its “DNA‐mark”) for both voucher and query samples, without requiring any computationally intensive pretreatment (e.g. assembly) of reads. We argue that if reference databases are populated with such “DNA‐marks,” it will enable future DNA‐based taxonomic identification to complement, or even replace PCR of barcodes with genome skimming, and we discuss how such methodology ultimately could enable identification to population, or even individual, level.

    

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4. Minnow : a principled framework for rapid simulation of dscRNA-seq data at the read level

   https://doi.org/10.1093/bioinformatics/btz351  

   Sarkar, Hirak ; Srivastava, Avi ; Patro, Rob ( July 2019 , Bioinformatics)

   With the advancements of high-throughput single-cell RNA-sequencing protocols, there has been a rapid increase in the tools available to perform an array of analyses on the gene expression data that results from such studies. For example, there exist methods for pseudo-time series analysis, differential cell usage, cell-type detection RNA-velocity in single cells, etc. Most analysis pipelines validate their results using known marker genes (which are not widely available for all types of analysis) and by using simulated data from gene-count-level simulators. Typically, the impact of using different read-alignment or unique molecular identifier (UMI) deduplication methods has not been widely explored. Assessments based on simulation tend to start at the level of assuming a simulated count matrix, ignoring the effect that different approaches for resolving UMI counts from the raw read data may produce. Here, we present minnow, a comprehensive sequence-level droplet-based single-cell RNA-sequencing (dscRNA-seq) experiment simulation framework. Minnow accounts for important sequence-level characteristics of experimental scRNA-seq datasets and models effects such as polymerase chain reaction amplification, cellular barcodes (CB) and UMI selection and sequence fragmentation and sequencing. It also closely matches the gene-level ambiguity characteristics that are observed in real scRNA-seq experiments. Using minnow, we explore the performance of some common processing pipelines to produce gene-by-cell count matrices from droplet-bases scRNA-seq data, demonstrate the effect that realistic levels of gene-level sequence ambiguity can have on accurate quantification and show a typical use-case of minnow in assessing the output generated by different quantification pipelines on the simulated experiment.

   Supplementary data are available at Bioinformatics online.

    

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5. One Antarctic slug to confuse them all: the underestimated diversity of Doris kerguelenensis

   https://doi.org/https://doi.org/10.1071/IS21073  

   Maroni, P. J. ( June 2022 , Invertebrate systematics)

   The Antarctic marine environment, although rich in life, is predicted to experience rapid and significant effects from climate change. Despite a revolution in the approaches used to document biodiversity, less than one percent of Antarctic marine invertebrates are represented by DNA barcodes and we are at risk of losing biodiversity before discovery. The ease of sequencing mitochondrial DNA barcodes has promoted this relatively ‘universal’ species identification system across most metazoan phyla and barcode datasets are currently readily used for exploring questions of species-level taxonomy. Here we present the most well-sampled phylogeny of the direct-developing, Southern Ocean nudibranch mollusc, Doris kerguelenensis to date. This study sampled over 1000 new Doris kerguelenensis specimens spanning the Southern Ocean and sequenced the mitochondrial COI gene. Results of a maximum likelihood phylogeny and multiple subsequent species delimitation analyses identified 27 new species in this complex (now 59 in total). Using rarefaction techniques, we infer more species are yet to be discovered. Some species were only collected from southern South America or the sub-Antarctic islands, while at least four species were found spanning the Polar Front. This is contrary to dispersal predictions for species without a larval stage such as Doris kerguelenensis. Our work demonstrates the value of increasing geographic scope in sampling and highlights what could be lost given the current global biodiversity crisis. 

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