ArticleNature protocols2018
Long-read sequencing data analysis for yeasts.
Article in Nature protocols, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
35 citing papers in PubMed.
- Genomic Evidence of Early-Diverging Domesticated Lineages in Norwegian Farmhouse Yeast.Genome biology and evolution · 2026Article
- Diversity and Distribution of the Subtelomeric Y' Elements Across Saccharomyces cerevisiae Strains.Genome biology and evolution · 2026Article
- The adaptive molecular landscape of reprogrammed telomeric sequences.Nature communications · 2026Article
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- Genomic adaptation of an autochthonous cider yeast strain to buckwheat and barley wort under stressful brewing conditions.Applied and environmental microbiology · 2025Article
- Striking mycotoxin tolerance and zearalenone elimination capacity of the decaying wood associated yeast Sugiyamaella novakii (Trichomonascaceae).BMC microbiology · 2025Article
- Advancing the Indian cattle pangenome: characterizing non-reference sequences in Bos indicus.Journal of animal science and biotechnology · 2025Article
- Optogenetic control of horizontally acquired genes prevent stuck fermentations in yeast.Microbiology spectrum · 2025Article
- ScRAPdb: an integrated pan-omics database for the Saccharomyces cerevisiae reference assembly panel.Nucleic acids research · 2025Article
- An integrative taxonomy approach reveals Saccharomyces chiloensis sp. nov. as a newly discovered species from Coastal Patagonia.PLoS genetics · 2024Article
- Convergent genomic signatures associated with vertebrate viviparity.BMC biology · 2024Article
- Domestication signatures in the non-conventional yeastmSystems · 2024Article
- Divergence in the Saccharomyces Species' Heat Shock Response Is Indicative of Their Thermal Tolerance.Genome biology and evolution · 2023Article
- Genome instability footprint under rapamycin and hydroxyurea treatments.PLoS genetics · 2023Article
- A high-quality reference genome for the fission yeast Schizosaccharomyces osmophilus.G3 (Bethesda, Md.) · 2023Article
- Genetically controlled mtDNA deletions prevent ROS damage by arresting oxidative phosphorylation.eLife · 2022Article
- Heme Oxygenase-1 (Journal of fungi (Basel, Switzerland) · 2022Article
- Unlocking the functional potential of polyploid yeasts.Nature communications · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Long-read sequencing technologies have become increasingly popular due to their strengths in resolving complex genomic regions. As a leading model organism with small genome size and great biotechnological importance, the budding yeast Saccharomyces cerevisiae has many isolates currently being sequenced with long reads. However, analyzing long-read sequencing data to produce high-quality genome assembly and annotation remains challenging. Here, we present a modular computational framework named long-read sequencing data analysis for yeasts (LRSDAY), the first one-stop solution that streamlines this process. Starting from the raw sequencing reads, LRSDAY can produce chromosome-level genome assembly and comprehensive genome annotation in a highly automated manner with minimal manual intervention, which is not possible using any alternative tool available to date. The annotated genomic features include centromeres, protein-coding genes, tRNAs, transposable elements (TEs), and telomere-associated elements. Although tailored for S. cerevisiae, we designed LRSDAY to be highly modular and customizable, making it adaptable to virtually any eukaryotic organism. When applying LRSDAY to an S. cerevisiae strain, it takes ∼41 h to generate a complete and well-annotated genome from ∼100× Pacific Biosciences (PacBio) running the basic workflow with four threads. Basic experience working within the Linux command-line environment is recommended for carrying out the analysis using LRSDAY.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.