Biology subjects

Yokoyama, T. T.

Publications and source records attributed to Yokoyama, T. T..

4 recordsLinked to original sources

bioRxiv2024

Efficient indexing and querying of annotations in a pangenome graph

The current reference genome is the backbone of diverse and rich annotations. Simple text formats, like VCF or BED, have been widely adopted and helped the critical exchange of genomic information. There is a dire need for tools and formats enabling pangenomic annotation to facilitate such enrichment of pangenomic references. The Graph Alignment Format (GAF) is a text format, tab-delimited like BED/VCF files, which was proposed to represent alignments. GAF could also be used to store paths representing annotations in a pangenome graph, but there are no tools to index and query them efficiently. Here, we present extensions to vg and HTSlib that provide efficient sorting, indexing, and querying for GAF files. With this approach, annotations overlapping a subgraph can be extracted quickly. Paths are sorted based on the IDs of traversed nodes, compressed with BGZIP, and indexed with HTSlib/tabix via our extensions for the GAF format. Compared to the binary GAM format, GAF files are easier to edit or inspect because they are plain text, and we show that they are twice as fast to sort and half as large on disk. In addition, we updated vg annotate, which takes BED or GFF3 annotation files relative to linear sequences and projects them into the pangenome. It can now produce GAF files representing these annotations paths through the pangenome. We showcase these new tools on several applications. We projected annotations for all Human Pangenome Reference Consortium Year 1 haplotypes, including genes, segmental duplications, tandem repeats and repeats annotations, into the Minigraph-Cactus pangenome (GRCh38-based v1.1). We also projected known variants from the GWAS Catalog and expression QTLs from the GTEx project into the pangenome. Finally, we reanalyzed ATAC-seq data from ENCODE to demonstrate what a coverage track could look like in a pangenome graph. These rich annotations can be quickly queried with vg and visualized using existing tools like the Sequence Tube Map or Bandage.

bioinformatics↗

bioRxiv2023

A chromosome-level genome assembly of amodel conifer plant, the Japanese cedar,Cryptomeria japonica D. Don

Japanese cedar (Cryptomeria japonica D. Don) is the most important Japanese forest tree, occupying about 44% of artificial forests in Japan, and planted in East Asia, Azores Archipelago, and some islands in the Indian Ocean. Although the huge genome of the species (ca. 11 Gb) with abundant repeat elements might have been an obstacle for genetic analysis, the species is easily propagated by cutting, flowered by plant hormones like gibberellic acid, transformed by agrobacterium, and edited by CRISPR/Cas9. These characteristics of C. japonica are preferable to make the species a model conifer for which reference genome sequences are necessary. In this study, we report the first chromosome-level assembly for C. japonica (2n = 22) using a third generation selfed progeny with an estimated homozygosity of 0.96. Young leaf tissue was used to extract high-molecular-weight DNA (>50 kb) for HiFi PacBio long read sequencing and to construct Hi-C/Omni-C library for Illumina short read sequencing. Using the 29x and 26x genome coverage of HiFi and Illumina reads, respectively, de novo assembly resulted in 2,650 contigs (9.1 Gb in total) with N50 contig size of 12.0 Mb. The Hi-C analysis mapped 97% of the nucleotides on the 11 chromosomes. The assembly was verified by comparing with a consensus linkage map of 7,785 markers. The BUSCO analysis confirmed ~91% of conserved genes. Annotations of genes, repeat elements and synteny with other Cupressaceae and Pinaceae species were performed, providing fundamental resources for genomic research of conifers.

genomics↗

bioRxiv2019

Long read sequencing reveals a novel class of structural aberrations in cancers: identification and characterization of cancerous local amplifications

Here we report identification of a new class of local structural aberrations in lung cancers. The whole-genome sequencing of cell lines using a long read sequencer, PromethION, demonstrated that typical cancerous mutations, such as point mutations, large deletions and gene fusions can be detected also on this platform. Unexpectedly, we revealed unique structural aberrations consisting of complex combinations of local duplications, inversions and micro deletions. We further analyzed and found that these mutations also occur in vivo, even in key cancer-related genes. These mutations may elucidate the molecular etiology of patients for whom causative cancerous events and therapeutic strategies remain elusive.

genomics↗

bioRxiv2019

MoMI-G: Modular Multi-scale Integrated Genome Graph Browser

Long-read sequencing allows more sensitive and accurate discovery of structural variants (SVs). While more and more SVs are being identified, a number of them are difficult to visualize using existing SV visualization tools. Therefore, methods to visualize SVs such as nested or large SVs of over a megabase pair need to be developed. To this end, we developed MOdular Multi-scale Integrated Genome graph browser, MoMI-G, a web-based genome browser to visualize SVs, genes, repeats, and other annotations as a variation graph with paths. This browser allows more intuitive recognition of large, nested, and potentially more complex SVs. MoMI-G has view modules for different scales, which allow users to view the whole genome down to nucleotide-level alignments of long reads. Alignments spanning reference alleles and those spanning alternative alleles are shown in the same view. Users can customize the view, if they are not satisfied with the preset views. In addition, MoMI-G has Interval Card Deck, a feature for rapid manual inspection of hundreds of SVs. Herein, we describe the utility of MoMI-G by using representative examples of large and nested SVs found in two cell lines, LC-2/ad and CHM1. MoMI-G is freely available at https://github.com/MoMI-G/MoMI-G under the MIT license.

bioinformatics↗