Despite rapid advances in sequencing technologies, accurately calling genetic variants present in an individual genome from billions of short, errorful sequence reads remains challenging. Here we show that a deep convolutional neural network can call genetic variation in aligned next-generation sequencing read data by learning statistical relationships between images of read pileups around putative variant and true genotype calls. The approach, called DeepVariant, outperforms existing state-of-the-art tools. The learned model generalizes across genome builds and mammalian species, allowing nonhuman sequencing projects to benefit from the wealth of human ground-truth data. We further show that DeepVariant can learn to call variants…
Short tandem repeat (STR) expansions have been identified as the causal DNA mutation in dozens of Mendelian diseases. Most existing tools for detecting STR variation with short reads do so within the read length and so are unable to detect the majority of pathogenic expansions. Here we present STRetch, a new genome-wide method to scan for STR expansions at all loci across the human genome. We demonstrate the use of STRetch for detecting STR expansions using short-read whole-genome sequencing data at known pathogenic loci as well as novel STR loci. STRetch is open source software, available from github.com/Oshlack/STRetch .
Recent mitochondrial phylogenomics studies have reported a sister-group relationship of the orders Capsalidea and Dactylogyridea, which is inconsistent with previous morphology- and molecular-based phylogenies. As Dactylogyridea mitochondrial genomes (mitogenomes) are currently represented by only one family, to improve the phylogenetic resolution, we sequenced and characterized two dactylogyridean parasites, Lamellodiscus spari and Lepidotrema longipenis, belonging to a non-represented family Diplectanidae.The L. longipenis mitogenome (15,433 bp) contains the standard 36 flatworm mitochondrial genes (atp8 is absent), whereas we failed to detect trnS1, trnC and trnG in L. spari (14,614 bp). Both mitogenomes exhibit unique gene orders (among the Monogenea), with a number…
Acquired genomic structural variants (SVs) are major hallmarks of cancer genomes, but they are challenging to reconstruct from short-read sequencing data. Here we exploited the long reads of the nanopore platform using our customized pipeline, Picky ( https://github.com/TheJacksonLaboratory/Picky ), to reveal SVs of diverse architecture in a breast cancer model. We identified the full spectrum of SVs with superior specificity and sensitivity relative to short-read analyses, and uncovered repetitive DNA as the major source of variation. Examination of genome-wide breakpoints at nucleotide resolution uncovered micro-insertions as the common structural features associated with SVs. Breakpoint density across the genome is associated…
Recent advances in sequencing technology have allowed us to investigate personal genomes to find structural variations, which have been studied extensively to identify their association with the physiology of diseases such as cancer. In particular, mobile genetic elements (MGEs) are one of the major constituents of the human genomes, and cause genome instability by insertion, mutation, and rearrangement.We have developed a new program, iMGEins, to identify such novel MGEs by using sequencing reads of individual genomes, and to explore the breakpoints with the supporting reads and MGEs detected. iMGEins is the first MGE detection program that integrates three algorithmic components:…
This tutorial provides an introduction to SMRT Analysis within SMRT Link. The training includes an overview of the various PacBio analysis applications and an introduction on their use.
This tutorial provides an overview of the Circular Consensus Sequence (CCS) analysis application. The CCS algorithm is used in applications that require distinguishing closely related DNA molecules in the same sample. Applications of CCS include profiling microbial communities, resolving viral populations and accurately identifying somatic variations within heterogeneous tumor cells.