RNA editing increases transcriptome diversity through post-transcriptional modifications of RNA. Adenosine deaminases that act on RNA (ADARs) catalyze the adenosine-to-inosine (A-to-I) conversion, the most common type of RNA editing in higher eukaryotes. Caenorhabditis elegans has two ADARs, ADR-1 and ADR-2, but their functions remain unclear. Here, we profiled the RNA editomes of C. elegans at different developmental stages of wild-type and ADAR mutants. We developed a new computational pipeline with a ''bisulfite-seq-mapping-like'' step and achieved a threefold increase in identification sensitivity. A total of 99.5% of the 47,660 A-to-I editing sites were found in clusters. Of the 3080 editing clusters, 65.7% overlapped with DNA transposons in noncoding regions and 73.7% could form hairpin structures. The numbers of editing sites and clusters were highest at the L1 and embryonic stages. The editing frequency of a cluster positively correlated with the number of editing sites within it. Intriguingly, for 80% of the clusters with 10 or more editing sites, almost all expressed transcripts were edited. Deletion of adr-1 reduced the editing frequency but not the number of editing clusters, whereas deletion of adr-2 nearly abolished RNA editing, indicating a modulating role of ADR-1 and an essential role of ADR-2 in A-to-I editing. Quantitative proteomics analysis showed that adr-2 mutant worms altered the abundance of proteins involved in aging and lifespan regulation. Consistent with this finding, we observed that worms lacking RNA editing were short-lived. Taken together, our results reveal a sophisticated landscape of RNA editing and distinct modes of action of different ADARs.

Somatic mutations have been studied extensively in the context of cancer. Recent studies have demonstrated that high-throughput sequencing data can be used to detect somatic mutations in non-tumor cells. Analysis of such mutations allows us to better understand the mutational processes in normal cells, explore cell lineages in development, and examine potential associations with age-related disease. We describe here approaches for characterizing somatic mutations in normal and non-tumor disease tissues. We discuss several experimental designs and common pitfalls in somatic mutation detection, as well as more recent developments such as phasing and linked-read technology. With the dramatically increasing numbers of samples undergoing genome sequencing, bioinformatic analysis will enable the characterization of somatic mutations and their impact on non-cancer tissues.

Although cell lineage information is fundamental to understanding organismal development, very little direct information is available for humans. We performed high-depth (250×) whole-genome sequencing of multiple tissues from three individuals to identify hundreds of somatic single-nucleotide variants (sSNVs). Using these variants as “endogenous barcodes” in single cells, we reconstructed early embryonic cell divisions. Targeted sequencing of clonal sSNVs in different organs (about 25,000×) and in more than 1000 cortical single cells, as well as single-nucleus RNA sequencing and single-nucleus assay for transposase-accessible chromatin sequencing of ~100,000 cortical single cells, demonstrated asymmetric contributions of early progenitors to extraembryonic tissues, distinct germ layers, and organs. Our data suggest onset of gastrulation at an effective progenitor pool of about 170 cells and about 50 to 100 founders for the forebrain. Thus, mosaic mutations provide a permanent record of human embryonic development at very high resolution.

The roles and characteristics of postzygotic single‐nucleotide mosaicisms (pSNMs) in autism spectrum disorders (ASDs) remain unclear. In this study of the whole exomes of 2,361 families in the Simons Simplex Collection, we identified 1,248 putative pSNMs in children and 285 de novo SNPs in children with detectable parental mosaicism. Ultra‐deep amplicon resequencing suggested a validation rate of 51%. Analyses of validated pSNMs revealed that missense/loss‐of‐function (LoF) pSNMs with a high mutant allele fraction (MAF≥ 0.2) contributed to ASD diagnoses (P = 0.022, odds ratio [OR] = 5.25), whereas missense/LoF pSNMs with a low MAF (MAF<0.2) contributed to autistic traits in male non‐ASD siblings (P = 0.033). LoF pSNMs in parents were less likely to be transmitted to offspring than neutral pSNMs (P = 0.037), and missense/LoF pSNMs in parents with a low MAF were transmitted more to probands than to siblings (P = 0.016, OR = 1.45). We estimated that pSNMs in probands or de novo mutations inherited from parental pSNMs increased the risk of ASD by approximately 6%. Adding pSNMs into the transmission and de novo association test model revealed 13 new ASD risk genes. These results expand the existing repertoire of genes involved in ASD and shed new light on the contribution of genomic mosaicisms to ASD diagnoses and autistic traits.