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1. A long-read and short-read transcriptomics approach provides the first high-quality reference transcriptome and genome annotation for Pseudotsuga menziesii (Douglas-fir)

   https://doi.org/10.1093/g3journal/jkac304  

   Velasco, Vera Marjorie; Ferreira, Alyssa; Zaman, Sumaira; Noordermeer, Devin; Ensminger, Ingo; Wegrzyn, Jill L (December 2022, G3 Genes|Genomes|Genetics)

   Holland, J. (Ed.)

   Abstract Douglas-fir (Pseudotsuga menziesii) is native to western North America. It grows in a wide range of environmental conditions and is an important timber tree. Although there are several studies on the gene expression responses of Douglas-fir to abiotic cues, the absence of high-quality transcriptome and genome data is a barrier to further investigation. Like for most conifers, the available transcriptome and genome reference dataset for Douglas-fir remains fragmented and requires refinement. We aimed to generate a highly accurate, and complete reference transcriptome and genome annotation. We deep-sequenced the transcriptome of Douglas-fir needles from seedlings that were grown under nonstress control conditions or a combination of heat and drought stress conditions using long-read (LR) and short-read (SR) sequencing platforms. We used 2 computational approaches, namely de novo and genome-guided LR transcriptome assembly. Using the LR de novo assembly, we identified 1.3X more high-quality transcripts, 1.85X more “complete” genes, and 2.7X more functionally annotated genes compared to the genome-guided assembly approach. We predicted 666 long noncoding RNAs and 12,778 unique protein-coding transcripts including 2,016 putative transcription factors. We leveraged the LR de novo assembled transcriptome with paired-end SR and a published single-end SR transcriptome to generate an improved genome annotation. This was conducted with BRAKER2 and refined based on functional annotation, repetitive content, and transcriptome alignment. This high-quality genome annotation has 51,419 unique gene models derived from 322,631 initial predictions. Overall, our informatics approach provides a new reference Douglas-fir transcriptome assembly and genome annotation with considerably improved completeness and functional annotation. 

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2. Stacks 2: Analytical methods for paired‐end sequencing improve RADseq‐based population genomics

   https://doi.org/10.1111/mec.15253  

   Rochette, Nicolas C.; Rivera‐Colón, Angel G.; Catchen, Julian M. (October 2019, Molecular Ecology)

   Abstract For half a century population genetics studies have put type II restriction endonucleases to work. Now, coupled with massively‐parallel, short‐read sequencing, the family of RAD protocols that wields these enzymes has generated vast genetic knowledge from the natural world. Here, we describe the first software natively capable of using paired‐end sequencing to derive short contigs from de novo RAD data. Stacks version 2 employs a de Bruijn graph assembler to build and connect contigs from forward and reverse reads for each de novo RAD locus, which it then uses as a reference for read alignments. The new architecture allows all the individuals in a metapopulation to be considered at the same time as each RAD locus is processed. This enables a Bayesian genotype caller to provide precise SNPs, and a robust algorithm to phase those SNPs into long haplotypes, generating RAD loci that are 400–800 bp in length. To prove its recall and precision, we tested the software with simulated data and compared reference‐aligned and de novo analyses of three empirical data sets. Our study shows that the latest version of Stacks is highly accurate and outperforms other software in assembling and genotyping paired‐end de novo data sets. 

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3. Welcome to the big leaves: Best practices for improving genome annotation in non‐model plant genomes

   https://doi.org/10.1002/aps3.11533  

   Vuruputoor, Vidya S.; Monyak, Daniel; Fetter, Karl C.; Webster, Cynthia; Bhattarai, Akriti; Shrestha, Bikash; Zaman, Sumaira; Bennett, Jeremy; McEvoy, Susan L.; Caballero, Madison; et al (July 2023, Applications in Plant Sciences)

   Abstract PremiseRobust standards to evaluate quality and completeness are lacking in eukaryotic structural genome annotation, as genome annotation software is developed using model organisms and typically lacks benchmarking to comprehensively evaluate the quality and accuracy of the final predictions. The annotation of plant genomes is particularly challenging due to their large sizes, abundant transposable elements, and variable ploidies. This study investigates the impact of genome quality, complexity, sequence read input, and method on protein‐coding gene predictions. MethodsThe impact of repeat masking, long‐read and short‐read inputs, and de novo and genome‐guided protein evidence was examined in the context of the popular BRAKER and MAKER workflows for five plant genomes. The annotations were benchmarked for structural traits and sequence similarity. ResultsBenchmarks that reflect gene structures, reciprocal similarity search alignments, and mono‐exonic/multi‐exonic gene counts provide a more complete view of annotation accuracy. Transcripts derived from RNA‐read alignments alone are not sufficient for genome annotation. Gene prediction workflows that combine evidence‐based and ab initio approaches are recommended, and a combination of short and long reads can improve genome annotation. Adding protein evidence from de novo assemblies, genome‐guided transcriptome assemblies, or full‐length proteins from OrthoDB generates more putative false positives as implemented in the current workflows. Post‐processing with functional and structural filters is highly recommended. DiscussionWhile the annotation of non‐model plant genomes remains complex, this study provides recommendations for inputs and methodological approaches. We discuss a set of best practices to generate an optimal plant genome annotation and present a more robust set of metrics to evaluate the resulting predictions. 

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4. Sequencing Strategy to Ensure Accurate Plasmid Assembly

   https://doi.org/10.1021/acssynbio.4c00539  

   Hernandez, Sarah I; Berezin, Casey-Tyler; Miller, Katie M; Peccoud, Samuel J; Peccoud, Jean (November 2024, ACS Synthetic Biology)

   Despite the wide use of plasmids in research and clinical production, the need to verify plasmid sequences is a bottleneck that is too often underestimated in the manufacturing process. Although sequencing platforms continue to improve, the method and assembly pipeline chosen still influence the final plasmid assembly sequence. Furthermore, few dedicated tools exist for plasmid assembly, especially for de novo assembly. Here, we evaluated short-read, long-read, and hybrid (both short and long reads) de novo assembly pipelines across three replicates of a 24-plasmid library. Consistent with previous characterizations of each sequencing technology, short-read assemblies had issues resolving GC-rich regions, and long-read assemblies commonly had small insertions and deletions, especially in repetitive regions. The hybrid approach facilitated the most accurate, consistent assembly generation and identified mutations relative to the reference sequence. Although Sanger sequencing can be used to verify specific regions, some GC-rich and repetitive regions were difficult to resolve using any method, suggesting that easily sequenced genetic parts should be prioritized in the design of new genetic constructs. 

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5. Evaluating Illumina-, Nanopore-, and PacBio-based genome assembly strategies with the bald notothen, Trematomus borchgrevinki

   https://doi.org/10.1093/g3journal/jkac192  

   Rayamajhi, Niraj; Cheng, Chi-Hing Christina; Catchen, Julian M (July 2022, G3 Genes|Genomes|Genetics)

   Abstract For any genome-based research, a robust genome assembly is required. De novo assembly strategies have evolved with changes in DNA sequencing technologies and have been through at least three phases: i) short-read only, ii) short- and long-read hybrid, and iii) long-read only assemblies. Each of the phases has their own error model. We hypothesized that hidden scaffolding errors in short-read assembly and erroneous long-read contigs degrades the quality of short- and long-read hybrid assemblies. We assembled the genome of T. borchgrevinki from data generated during each of the three phases and assessed the quality problems we encountered. We developed strategies such as k-mer-assembled region replacement, parameter optimization, and long-read sampling to address the error models. We demonstrated that a k-mer based strategy improved short-read assemblies as measured by BUSCO while mate-pair libraries introduced hidden scaffolding errors and perturbed BUSCO scores. Further, we found that although hybrid assemblies can generate higher contiguity they tend to suffer from lower quality. In addition, we found long-read only assemblies can be optimized for contiguity by sub-sampling length-restricted raw reads. Our results indicate that long-read contig assembly is the current best choice and that assemblies from phase I and phase II were of lower quality. 

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