Whole-genome sequencing reveals the molecular implications of the stepwise progression of lung adenocarcinoma.

The mechanism underlying the development of tumors, particularly at early stages, still remains mostly elusive. Here, we report whole-genome long and short read sequencing analysis of 76 lung cancers, focusing on very early-stage lung adenocarcinomas such as adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma. The obtained data is further integrated with bulk and spatial transcriptomic data and epigenomic data. These analyses reveal key events in lung carcinogenesis. Minimal somatic mutations in pivotal driver mutations and essential proliferative factors are the only detectable somatic mutations in the very early-stage of AIS. These initial events are followed by copy number changes and global DNA hypomethylation. Particularly, drastic changes are initiated at the later AIS stage, i.e., in Noguchi type B tumors, wherein cancer cells are exposed to the surrounding microenvironment. This study sheds light on the pathogenesis of lung adenocarcinoma from integrated pathological and molecular viewpoints.

De Novo Genome Assembly of Japanese Black Cattle as Model of an Economically Relevant Animal.

A genetic analysis of Japanese Black cattle using short reads and guided by the reference genome from Western breeds would miss the structural variation and/or other unique characteristics of Japanese Black cattle. To overcome this difficulty, a de novo genome assembly independent from the reference genome is required. This chapter describes the technical developments, with respect to both experimental and bioinformatics procedures, including the use of short and long reads, required for de novo genome assembly of Japanese Black cattle.

Long-Read Whole-Genome Sequencing Using a Nanopore Sequencer and Detection of Structural Variants in Cancer Genomes.

Long-read sequencing technologies enable us to precisely identify structural variants (SVs), which would be occasionally associated with various types of diseases, including cancers. In this section, we introduce experimental and computational procedures for conducting long-read whole-genome sequencing (WGS) of cancer genomes from fresh frozen tissues/cells. We also demonstrate the analysis of SVs in cancer genomes using long-read WGS data from lung cancer cell lines by several representative computational tools, such as cuteSV and Sniffles2, as examples.

Single-cell analytical technologies: uncovering the mechanisms behind variations in immune responses.

The immune landscape varies among individuals. It determines the immune response and results in surprisingly diverse symptoms, even in response to similar external stimuli. However, the detailed mechanisms underlying such diverse immune responses have remained mostly elusive. The utilization of recently developed single-cell multimodal analysis platforms has started to answer this question. Emerging studies have elucidated several molecular networks that may explain diversity with respect to age or other factors. An elaborate interplay between inherent physical conditions and environmental conditions has been demonstrated. Furthermore, the importance of modifications by the epigenome resulting in transcriptome variation among individuals is gradually being revealed. Accordingly, epigenomes and transcriptomes are direct indicators of the medical history and dynamic interactions with environmental factors. Coronavirus disease 2019 (COVID-19) has recently become one of the most remarkable examples of the necessity of in-depth analyses of diverse responses with respect to various factors to improve treatment in severe cases and to prevent viral transmission from asymptomatic carriers. In fact, determining why some patients develop serious symptoms is still a pressing issue. Here, we review the current "state of the art" in single-cell analytical technologies and their broad applications to healthy individuals and representative diseases, including COVID-19.