Here we conducted an integrative multi-omics analysis to understand how cancers harbor various types of aberrations at the genomic, epigenomic and transcriptional levels. In order to elucidate biological relevance of the aberrations and their mutual relations, we performed whole-genome sequencing, RNA-Seq, bisulfite sequencing and ChIP-Seq of 26 lung adenocarcinoma cell lines. The collected multi-omics data allowed us to associate an average of 536 coding mutations and 13,573 mutations in promoter or enhancer regions with aberrant transcriptional regulations. We detected the 385 splice site mutations and 552 chromosomal rearrangements, representative cases of which were validated to cause aberrant transcripts. Averages of 61, 217, 3687 and 3112 mutations are located in the regulatory regions which showed differential DNA methylation, H3K4me3, H3K4me1 and H3K27ac marks, respectively. We detected distinct patterns of aberrations in transcriptional regulations depending on genes. We found that the irregular histone marks were characteristic to EGFR and CDKN1A, while a large genomic deletion and hyper-DNA methylation were most frequent for CDKN2A. We also used the multi-omics data to classify the cell lines regarding their hallmarks of carcinogenesis. Our datasets should provide a valuable foundation for biological interpretations of interlaced genomic and epigenomic aberrations.

Here, we review single-cell sequencing techniques for individual and multiomics profiling in single cells. We mainly describe single-cell genomic, epigenomic, and transcriptomic methods, and examples of their applications. For the integration of multilayered data sets, such as the transcriptome data derived from single-cell RNA sequencing and chromatin accessibility data derived from single-cell ATAC-seq, there are several computational integration methods. We also describe single-cell experimental methods for the simultaneous measurement of two or more omics layers. We can achieve a detailed understanding of the basic molecular profiles and those associated with disease in each cell by utilizing a large number of single-cell sequencing techniques and the accumulated data sets.

BackgroundThe Solanaceae family includes several economically important vegetable crops. The tomato (Solanum lycopersicum) is regarded as a model plant of the Solanaceae family. Recently, a number of tomato resources have been developed in parallel with the ongoing tomato genome sequencing project. In particular, a miniature cultivar, Micro-Tom, is regarded as a model system in tomato genomics, and a number of genomics resources in the Micro-Tom-background, such as ESTs and mutagenized lines, have been established by an international alliance.ResultsTo accelerate the progress in tomato genomics, we developed a collection of fully-sequenced 13,227 Micro-Tom full-length cDNAs. By checking redundant sequences, coding sequences, and chimeric sequences, a set of 11,502 non-redundant full-length cDNAs (nrFLcDNAs) was generated. Analysis of untranslated regions demonstrated that tomato has longer 5'- and 3'-untranslated regions than most other plants but rice. Classification of functions of proteins predicted from the coding sequences demonstrated that nrFLcDNAs covered a broad range of functions. A comparison of nrFLcDNAs with genes of sixteen plants facilitated the identification of tomato genes that are not found in other plants, most of which did not have known protein domains. Mapping of the nrFLcDNAs onto currently available tomato genome sequences facilitated prediction of exon-intron structure. Introns of tomato genes were longer than those of Arabidopsis and rice. According to a comparison of exon sequences between the nrFLcDNAs and the tomato genome sequences, the frequency of nucleotide mismatch in exons between Micro-Tom and the genome-sequencing cultivar (Heinz 1706) was estimated to be 0.061%.ConclusionThe collection of Micro-Tom nrFLcDNAs generated in this study will serve as a valuable genomic tool for plant biologists to bridge the gap between basic and applied studies. The nrFLcDNA sequences will help annotation of the tomato whole-genome sequence and aid in tomato functional genomics and molecular breeding. Full-length cDNA sequences and their annotations are provided in the database KaFTom http://www.pgb.kazusa.or.jp/kaftom/ via the website of the National Bioresource Project Tomato http://tomato.nbrp.jp.

Communicated by E.A.NiggMitogen-activated protein kinase (MAPK) is activated by MAPK kinase (MAPKK) in a variety of signaling pathways. This kinase cascade has been shown to function in cell proliferation and differentiation, but its role in early vertebrate development remains to be investigated. During early vertebrate embryogenesis, the induction and patterning of mesoderm are thought to be determined by signals from intercellular factors such as members of the fibroblast growth factor (FGF) family and members of the transforming growth factorf family. Here we show that the microinjection of either mRNA encoding a constitutively active mutant of MAPKK or mRNA encoding a constitutively active form of STE11, a MAPKK kinase, leads to the induction of mesoderm in ectodermal explants from Xenopus embryos. Moreover, the expression of MAPK phosphatase-1 (MKP-1, also called CL100) blocks the growth factor-stimulated mesoderm induction. Furthermore, injection of CL100 mRNA into two-cell stage embryos causes severe defects in gastrulation and posterior development. The effects induced by CL100 can be rescued by co-injection of wild-type MAPK mRNA. Thus, the MAPK cascade may play a crucial role in early vertebrate embryogenesis, especially during mesoderm induction.

The current RNA-Seq method analyses fragments of mRNAs, from which it is occasionally difficult to reconstruct the entire transcript structure. Here, we performed and evaluated the recent procedure for full-length cDNA sequencing using the Nanopore sequencer MinION. We applied MinION RNA-Seq for various applications, which would not always be easy using the usual RNA-Seq by Illumina. First, we examined and found that even though the sequencing accuracy was still limited to 92.3%, practically useful RNA-Seq analysis is possible. Particularly, taking advantage of the long-read nature of MinION, we demonstrate the identification of splicing patterns and their combinations as a form of full-length cDNAs without losing precise information concerning their expression levels. Transcripts of fusion genes in cancer cells can also be identified and characterized. Furthermore, the full-length cDNA information can be used for phasing of the SNPs detected by WES on the transcripts, providing essential information to identify allele-specific transcriptional events. We constructed a catalogue of full-length cDNAs in seven major organs for two particular individuals and identified allele-specific transcription and splicing. Finally, we demonstrate that single-cell sequencing is also possible. RNA-Seq on the MinION platform should provide a novel approach that is complementary to the current RNA-Seq.