Whole-body regeneration of planarians is a natural wonder but how it occurs remains elusive. It requires coordinated responses from each cell in the remaining tissue with spatial awareness to regenerate new cells and missing body parts. While previous studies identified new genes essential to regeneration, a more efficient screening approach that can identify regeneration-associated genes in the spatial context is needed. Here, we present a comprehensive three-dimensional spatiotemporal transcriptomic landscape of planarian regeneration. We describe a pluripotent neoblast subtype, and show that depletion of its marker gene makes planarians more susceptible to sub-lethal radiation. Furthermore, we identified spatial gene expression modules essential for tissue development. Functional analysis of hub genes in spatial modules, such as plk1, shows their important roles in regeneration. Our three-dimensional transcriptomic atlas provides a powerful tool for deciphering regeneration and identifying homeostasis-related genes, and provides a publicly available online spatiotemporal analysis resource for planarian regeneration research.

Background: Induced pluripotent stem cells (iPSCs) and embryonic stem cells (ESCs) share many common features, including similar morphology, gene expression and in vitro differentiation profiles. However, genomic stability is much lower in iPSCs than in ESCs. In the current study, we examined whether changes in DNA damage repair in iPSCs are responsible for their greater tendency towards mutagenesis. Methods: Mouse iPSCs, ESCs and embryonic fibroblasts were exposed to ionizing radiation (4 Gy) to introduce double‐strand DNA breaks. At 4 h later, fidelity of DNA damage repair was assessed using whole‐genome re‐sequencing. We also analyzed genomic stability in mice derived from iPSCs versus ESCs. Results: In comparison to ESCs and embryonic fibroblasts, iPSCs had lower DNA damage repair capacity, more somatic mutations and short indels after irradiation. iPSCs showed greater non‐homologous end joining DNA repair and less homologous recombination DNA repair. Mice derived from iPSCs had lower DNA damage repair capacity than ESC‐derived mice as well as C57 control mice. Conclusions: The relatively low genomic stability of iPSCs and their high rate of tumorigenesis in vivo appear to be due, at least in part, to low fidelity of DNA damage repair.

Although viable mice can be generated from induced pluripotent stem cells (iPSCs), the impact of accumulated mutations on the developmental potential of the resulting iPSCs remains to be determined. Here, we demonstrate that all-iPSC mice generated through tetraploid blastocysts complementation can tolerate the accumulation of somatic mutations for up to six generations using a Tet-on inducible reprogramming system. But, the viability of the all-iPS mice decreased with increasing generations. A whole-genome sequencing survey revealed that thousands of single-nucleotide variations (SNVs), including 44 non-synonymous ones, accumulated throughout the sequential reprogramming process. Subsequent analysis provides evidence that these accumulated SNVs account for the gradual reduction in viability of the resultant all-iPSC mice. Unexpectedly, our present reprogramming system revealed that pluripotent stem cells are heterogeneous in terms of possessing a set of copy-number alterations (CNAs). These CNAs are unique for pluripotent cells and subsequently disappear in the differentiating progenies.

Numerous non-inherited somatic mutations, distinct from those of germ-line origin, occur in somatic cells during DNA replication per cell-division. The somatic mutations, recording the unique genetic cell-lineage ‘history’ of each proliferating normal cell, are important but remain to be investigated because of their ultra-low frequency hidden in the genetic background of heterogeneous cells. Luckily, the recent development of single-cell genomics biotechnologies enables the screening and collection of the somatic mutations, especial single nucleotide variations (SNVs), occurring in normal cells. Here, we established DSMNC: a database of somatic mutations in normal cells (http://dsmnc.big.ac.cn/), which provides most comprehensive catalogue of somatic SNVs in single cells from various normal tissues. In the current version, the database collected ∼0.8 million SNVs accumulated in ∼600 single normal cells (579 human cells and 39 mouse cells). The database interface supports the user-friendly capability of browsing and searching the SNVs and their annotation information. DSMNC, which serves as a timely and valuable collection of somatic mutations in individual normal cells, has made it possible to analyze the burdens and signatures of somatic mutations in various types of heterogeneous normal cells. Therefore, DSMNC will significantly improve our understanding of the characteristics of somatic mutations in normal cells.

Motivation: Copy number abbreviation (CNA) is one type of genomic aberration that is often induced by genome instability and is associated with diseases such as cancer. Determination of the genome-wide CNA profile is an important step in identifying the underlying mutation mechanisms. Genomic data based on next-generation sequencing technology are particularly suitable for determination of high-quality CNA profile. Now is an important time to reevaluate the use of sequencing techniques for CNA analysis, especially with the rapid growth of the different targeted genome and whole-genome sequencing strategies. Results: In this study, we provide a comparison of resequencing strategies, with regard to their utility, applied to the same hepatocellular carcinoma sample for copy number determination. These strategies include whole-genome, exome and restriction site-associated DNA (RAD) sequencing. The last of these strategies is a targeted sequencing technique that involves cutting the genome with a restriction enzyme and isolating the targeted sequences. Our data demonstrate that RAD sequencing is an efficient and comprehensive strategy that allows the cost-effective determination of CNAs. Further investigation of RAD sequencing data led to the finding that a precise measurement of the allele frequency would be a helpful complement to the read depth for CNA analysis for two reasons. First, knowledge of the allele frequency helps to resolve refined calculations of allele-specific copy numbers, which, in turn, identify the functionally important CNAs that are under natural selection on the parental alleles. Second, this knowledge enables deconvolution of CNA patterns in complex genomic regions. Contact:juncai@big.ac.cn or ciwu@uchicago.edu Supplementary information: Supplementary data are available at Bioinformatics online.