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Data storage in DNA has recently emerged as a promising archival solution, offering space-efficient and long-lasting digital storage solutions. Recent studies suggest leveraging the inherent redundancy of synthesis and sequencing technologies by using composite DNA alphabets. A major challenge of this approach involves the noisy inference process, obstructing large composite alphabets. This paper introduces a novel approach for DNA-based data storage, offering, in some implementations, a 6.5-fold increase in logical density over standard DNA-based storage systems, with near-zero reconstruction error. Combinatorial DNA encoding uses a set of clearly distinguishable DNA shortmers to construct large combinatorial alphabets, where each letter consists of a subset of shortmers. We formally define various combinatorial encoding schemes and investigate their theoretical properties. These include information density and reconstruction probabilities, as well as required synthesis and sequencing multiplicities. We then propose an end-to-end design for a combinatorial DNA-based data storage system, including encoding schemes, two-dimensional (2D) error correction codes, and reconstruction algorithms, under different error regimes. We performed simulations and show, for example, that the use of 2D Reed-Solomon error correction has significantly improved reconstruction rates. We validated our approach by constructing two combinatorial sequences using Gibson assembly, imitating a 4-cycle combinatorial synthesis process. We confirmed the successful reconstruction, and established the robustness of our approach for different error types. Subsampling experiments supported the important role of sampling rate and its effect on the overall performance. Our work demonstrates the potential of combinatorial shortmer encoding for DNA-based data storage and describes some theoretical research questions and technical challenges. Combining combinatorial principles with error-correcting strategies, and investing in the development of DNA synthesis technologies that efficiently support combinatorial synthesis, can pave the way to efficient, error-resilient DNA-based storage solutions.

Controlling off-target editing activity is one of the central challenges in making CRISPR technology accurate and applicable in medical practice. Current algorithms for analyzing off-target activity do not provide statistical quantification, are not sufficiently sensitive in separating signal from noise in experiments with low editing rates, and do not address the detection of translocations. Here we present CRISPECTOR, a software tool that supports the detection and quantification of on- and off-target genome-editing activity from NGS data using paired treatment/control CRISPR experiments. In particular, CRISPECTOR facilitates the statistical analysis of NGS data from multiplex-PCR comparative experiments to detect and quantify adverse translocation events. We validate the observed results and show independent evidence of the occurrence of translocations in human cell lines, after genome editing. Our methodology is based on a statistical model comparison approach leading to better false-negative rates in sites with weak yet significant off-target activity. The control of off-target activity is a challenge for adapting CRISPR to therapeutic use. Here the authors present CRISPECTOR, a software tool to detect, evaluate and quantify editing activity, including translocations, from NGS data.

Embryos in a particular phylum of the animal kingdom tend to most resemble one another at a stage in the middle of embryogenesis known as the phylotypic period; a transcriptional analysis of embryogenesis from single embryos of ten different phyla reveals that the transcripts expressed at the phylotypic stage (or mid-developmental transition) differ greatly between phyla, and a ‘phylum’ may be defined as a set of species sharing the same signals and transcription factor networks during the mid-developmental transition. Stage set for defining a phylum Embryos in a particular phylum tend to resemble one another closely at some point in the middle of embryogeny. This is known as the phylotypic stage, and it has been established that embryos at this stage tend to express a conserved set of genes that are evolutionarily older than the genes expressed before and after. This, however, only applies within a phylum, as Yanai and colleagues demonstrate in an analysis of transcriptomes from individual embryos of ten disparate phyla. Considered across the whole animal kingdom, the transcripts expressed at the phylotypic stage differ greatly between phyla and could be said to define the characters of a particular phylum. This work also provides an operational definition for a phylum as a set of species — with a common ancestor — that share the same molecular mechanisms at the phylotypic stage. Animals are grouped into ~35 ‘phyla’ based upon the notion of distinct body plans 1 , 2 , 3 , 4 . Morphological and molecular analyses have revealed that a stage in the middle of development—known as the phylotypic period—is conserved among species within some phyla 5 , 6 , 7 , 8 , 9 . Although these analyses provide evidence for their existence, phyla have also been criticized as lacking an objective definition, and consequently based on arbitrary groupings of animals 10 . Here we compare the developmental transcriptomes of ten species, each annotated to a different phylum, with a wide range of life histories and embryonic forms. We find that in all ten species, development comprises the coupling of early and late phases of conserved gene expression. These phases are linked by a divergent ‘mid-developmental transition’ that uses species-specific suites of signalling pathways and transcription factors. This mid-developmental transition overlaps with the phylotypic period that has been defined previously for three of the ten phyla, suggesting that transcriptional circuits and signalling mechanisms active during this transition are crucial for defining the phyletic body plan and that the mid-developmental transition may be used to define phylotypic periods in other phyla. Placing these observations alongside the reported conservation of mid-development within phyla, we propose that a phylum may be defined as a collection of species whose gene expression at the mid-developmental transition is both highly conserved among them, yet divergent relative to other species.

Cultured meat presents a sustainable alternative to traditional meat production but faces significant challenges in scalability and cost efficiency. A key limitation is the restricted proliferation capacity of bovine mesenchymal stem cells (bMSCs), a widely used cell source in the field. Using a pooled, lentiviral CRISPR knockout screen, we interrogated 3000 CRISPR guides targeting 600 genes involved in stem cell regulation or proliferation. Notably, knockouts of TP53 and PTEN significantly increased proliferation rates and delayed senescence. Validation with individual gene knockouts confirms these effects, showing enhanced growth but reduced differentiation potential. We also identified chondrogenic differentiation as a promising target whose repression may further promote MSC expansion. These findings demonstrate the utility of CRISPR screening for optimizing bovine stem cell traits and offer a path toward more scalable cultured meat production in the future. Pooled CRISPR knockout screening in bovine mesenchymal stem cells identifies TP53 and PTEN as key regulators of proliferation, offering a genetic strategy to enhance cell expansion and address scalability challenges in cultured meat production.

The density and long-term stability of DNA make it an appealing storage medium, particularly for long-term data archiving. Existing DNA storage technologies involve the synthesis and sequencing of multiple nominally identical molecules in parallel, resulting in information redundancy. We report the development of encoding and decoding methods that exploit this redundancy using composite DNA letters. A composite DNA letter is a representation of a position in a sequence that consists of a mixture of all four DNA nucleotides in a predetermined ratio. Our methods encode data using fewer synthesis cycles. We encode 6.4 MB into composite DNA, with distinguishable composition medians, using 20% fewer synthesis cycles per unit of data, as compared to previous reports. We also simulate encoding with larger composite alphabets, with distinguishable composition deciles, to show that 75% fewer synthesis cycles are potentially sufficient. We describe applicable error-correcting codes and inference methods, and investigate error patterns in the context of composite DNA letters.

Single-cell transcriptomics requires a method that is sensitive, accurate, and reproducible. Here, we present CEL-Seq2, a modified version of our CEL-Seq method, with threefold higher sensitivity, lower costs, and less hands-on time. We implemented CEL-Seq2 on Fluidigm’s C1 system, providing its first single-cell, on-chip barcoding method, and we detected gene expression changes accompanying the progression through the cell cycle in mouse fibroblast cells. We also compare with Smart-Seq to demonstrate CEL-Seq2’s increased sensitivity relative to other available methods. Collectively, the improvements make CEL-Seq2 uniquely suited to single-cell RNA-Seq analysis in terms of economics, resolution, and ease of use.

Solid tumors are characterized by complex interactions between the tumor, the immune system and the microenvironment. These interactions and intra-tumor variations have both diagnostic and prognostic significance and implications. However, quantifying the underlying processes in patient samples requires expensive and complicated molecular experiments. In contrast, H&E staining is typically performed as part of the routine standard process, and is very cheap. Here we present HIPI (H&E Image Interpretation and Protein Expression Inference) for predicting cell marker expression from tumor H&E images. We process paired H&E and CyCIF images taken from serial sections of colorectal cancers to train our model. We show that our model accurately predicts the spatial distribution of several important cell markers, on both held-out tumor regions as well as new tumor samples taken from different patients. Moreover, using only the tissue image morphology, HIPI is able to colocalize the interactions between different cell types, further demonstrating its potential clinical significance.

Recent developments in personalized medicine are based on molecular measurement steps that guide personally adjusted medical decisions. A central approach to molecular profiling consists of measuring DNA, RNA, and/or proteins in tissue samples, most notably in and around tumors. This measurement yields molecular biomarkers that are potentially predictive of response and of tumor type. Current methods in cancer therapy mostly use tissue biopsy as the starting point of molecular profiling. Tissue biopsies involve a physical resection of a small tissue sample, leading to localized tissue injury, bleeding, inflammation and stress, as well as to an increased risk of metastasis. Here we developed a technology for harvesting biomolecules from tissues using electroporation. We show that tissue electroporation, achieved using a combination of high-voltage short pulses, 50 pulses 500 V cm −1 , 30 µs, 1 Hz, with low-voltage long pulses 50 pulses 50 V cm −1 , 10 ms, delivered at 1 Hz, allows for tissue-specific extraction of RNA and proteins. We specifically tested RNA and protein extraction from excised kidney and liver samples and from excised HepG2 tumors in mice. Further in vivo development of extraction methods based on electroporation can drive novel approaches to the molecular profiling of tumors and of tumor environment and to related diagnosis practices.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The evolution of development has been studied through the lens of gene regulation by examining either closely related species or extremely distant animals of different phyla. In nematodes, detailed cell-and stage-specific expression analyses are focused on the model Caenorhabditis elegans, in part leading to the view that the developmental expression of gene cascades in this species is archetypic for the phylum. Here, we compared two species of an intermediate evolutionary distance: the nematodes C. elegans (clade V) and Acrobeloides nanus (clade IV). To examine A. nanus molecularly, we sequenced its genome and identified the expression profiles of all genes throughout embryogenesis. In comparison with C. elegans, A. nanus exhibits a much slower embryonic development and has a capacity for regulative compensation of missing early cells. We detected conserved stages between these species at the transcriptome level, as well as a prominent middevelopmental transition, at which point the two species converge in terms of their gene expression. Interestingly, we found that genes originating at the dawn of the Ecdysozoa super-group show the least expression divergence between these two species. This led us to detect a correlation between the time of expression of a gene and its phylogenetic age: evolutionarily ancient and young genes are enriched for expression in early and late embryogenesis, respectively, whereas Ecdysozoa-specific genes are enriched for expression during the middevelopmental transition. Our results characterize the developmental constraints operating on each individual embryo in terms of developmental stages and genetic evolutionary history.