MCProj: metacell projection for interpretable and quantitative use of transcriptional atlases.

We describe MCProj-an algorithm for analyzing query scRNA-seq data by projections over reference single-cell atlases. We represent the reference as a manifold of annotated metacell gene expression distributions. We then interpret query metacells as mixtures of atlas distributions while correcting for technology-specific gene biases. This approach distinguishes and tags query cells that are consistent with atlas states from unobserved (novel or artifactual) behaviors. It also identifies expression differences observed in successfully mapped query states. We showcase MCProj functionality by projecting scRNA-seq data on a blood cell atlas, deriving precise, quantitative, and interpretable results across technologies and datasets.

Time-aligned hourglass gastrulation models in rabbit and mouse.

The hourglass model describes the convergence of species within the same phylum to a similar body plan during development; however, the molecular mechanisms underlying this phenomenon in mammals remain poorly described. Here, we compare rabbit and mouse time-resolved differentiation trajectories to revisit this model at single-cell resolution. We modeled gastrulation dynamics using hundreds of embryos sampled between gestation days 6.0 and 8.5 and compared the species using a framework for time-resolved single-cell differentiation-flows analysis. We find convergence toward similar cell-state compositions at E7.5, supported by the quantitatively conserved expression of 76 transcription factors, despite divergence in surrounding trophoblast and hypoblast signaling. However, we observed noticeable changes in specification timing of some lineages and divergence of primordial germ cell programs, which in the rabbit do not activate mesoderm genes. Comparative analysis of temporal differentiation models provides a basis for studying the evolution of gastrulation dynamics across mammals.

Whole-Genome Amplification-Surveying Yield, Reproducibility, and Heterozygous Balance, Reported by STR-Targeting MIPs.

Whole-genome amplification is a crucial first step in nearly all single-cell genomic analyses, with the following steps focused on its products. Bias and variance caused by the whole-genome amplification process add numerous challenges to the world of single-cell genomics. Short tandem repeats are sensitive genomic markers used widely in population genetics, forensics, and retrospective lineage tracing. A previous evaluation of common whole-genome amplification targeting ~1000 non-autosomal short tandem repeat loci is extended here to ~12,000 loci across the entire genome via duplex molecular inversion probes. Other than its improved scale and reduced noise, this system detects an abundance of heterogeneous short tandem repeat loci, allowing the allelic balance to be reported. We show here that while the best overall yield is obtained using RepliG-SC, the maximum uniformity between alleles and reproducibility across cells are maximized by Ampli1, rendering it the best candidate for the comparative heterozygous analysis of single-cell genomes.

Efficient acquisition of tens of thousands of short tandem repeats in single-cell whole-genome-amplified DNA.

Short tandem repeats (STRs) are highly abundant in the human genome, but existing approaches for accurate genotyping of STRs are limited. Here, we describe a protocol for duplex molecular inversion probes for high-throughput and cost-effective STR enrichment. We have successfully tested panels targeting as many as 50K STRs in several thousands of genomic samples (e.g., HeLa cells, Du145 cells, leukemia cells, melanoma cells). However, because the protocol is plate based, the sample size is limited to a few thousand. For complete details on the use and execution of this protocol, please refer to Tao et al. (2021).

Retrospective cell lineage reconstruction in humans by using short tandem repeats.

Cell lineage analysis aims to uncover the developmental history of an organism back to its cell of origin. Recently, novel in vivo methods utilizing genome editing enabled important insights into the cell lineages of animals. In contrast, human cell lineage remains restricted to retrospective approaches, which still lack resolution and cost-efficient solutions. Here, we demonstrate a scalable platform based on short tandem repeats targeted by duplex molecular inversion probes. With this human cell lineage tracing method, we accurately reproduced a known lineage of DU145 cells and reconstructed lineages of healthy and metastatic single cells from a melanoma patient who matched the anatomical reference while adding further refinements. This platform allowed us to faithfully recapitulate lineages of developmental tissue formation in healthy cells. In summary, our lineage discovery platform can profile informative somatic mutations efficiently and provides solid lineage reconstructions even in challenging low-mutation-rate healthy single cells.

Comparison of seven single cell whole genome amplification commercial kits using targeted sequencing.

Advances in whole genome amplification (WGA) techniques enable understanding of the genomic sequence at a single cell level. Demand for single cell dedicated WGA kits (scWGA) has led to the development of several commercial kit. To this point, no robust comparison of all available kits was performed. Here, we benchmark an economical assay, comparing all commercially available scWGA kits. Our comparison is based on targeted sequencing of thousands of genomic loci, including highly mutable regions, from a large cohort of human single cells. Using this approach we have demonstrated the superiority of Ampli1 in genome coverage and of RepliG in reduced error rate. In summary, we show that no single kit is optimal across all categories, highlighting the need for a dedicated kit selection in accordance with experimental requirements.

Benchmarked approaches for reconstruction of in vitro cell lineages and in silico models of C. elegans and M. musculus developmental trees.

The recent advent of CRISPR and other molecular tools enabled the reconstruction of cell lineages based on induced DNA mutations and promises to solve the ones of more complex organisms. To date, no lineage reconstruction algorithms have been rigorously examined for their performance and robustness across dataset types and number of cells. To benchmark such methods, we decided to organize a DREAM challenge using in vitro experimental intMEMOIR recordings and in silico data for a C. elegans lineage tree of about 1,000 cells and a Mus musculus tree of 10,000 cells. Some of the 22 approaches submitted had excellent performance, but structural features of the trees prevented optimal reconstructions. Using smaller sub-trees as training sets proved to be a good approach for tuning algorithms to reconstruct larger trees. The simulation and reconstruction methods here generated delineate a potential way forward for solving larger cell lineage trees such as in mouse.

Short tandem repeat stutter model inferred from direct measurement of in vitro stutter noise.

Short tandem repeats (STRs) are polymorphic genomic loci valuable for various applications such as research, diagnostics and forensics. However, their polymorphic nature also introduces noise during in vitro amplification, making them difficult to analyze. Although it is possible to overcome stutter noise by using amplification-free library preparation, such protocols are presently incompatible with single cell analysis and with targeted-enrichment protocols. To address this challenge, we have designed a method for direct measurement of in vitro noise. Using a synthetic STR sequencing library, we have calibrated a Markov model for the prediction of stutter patterns at any amplification cycle. By employing this model, we have managed to genotype accurately cases of severe amplification bias, and biallelic STR signals, and validated our model for several high-fidelity PCR enzymes. Finally, we compared this model in the context of a naïve STR genotyping strategy against the state-of-the-art on a benchmark of single cells, demonstrating superior accuracy.

A generic, cost-effective, and scalable cell lineage analysis platform.

Advances in single-cell genomics enable commensurate improvements in methods for uncovering lineage relations among individual cells. Current sequencing-based methods for cell lineage analysis depend on low-resolution bulk analysis or rely on extensive single-cell sequencing, which is not scalable and could be biased by functional dependencies. Here we show an integrated biochemical-computational platform for generic single-cell lineage analysis that is retrospective, cost-effective, and scalable. It consists of a biochemical-computational pipeline that inputs individual cells, produces targeted single-cell sequencing data, and uses it to generate a lineage tree of the input cells. We validated the platform by applying it to cells sampled from an ex vivo grown tree and analyzed its feasibility landscape by computer simulations. We conclude that the platform may serve as a generic tool for lineage analysis and thus pave the way toward large-scale human cell lineage discovery.

Synthesis and cell-free cloning of DNA libraries using programmable microfluidics.

Microfluidics may revolutionize our ability to write synthetic DNA by addressing several fundamental limitations associated with generating novel genetic constructs. Here we report the first de novo synthesis and cell-free cloning of custom DNA libraries in sub-microliter reaction droplets using programmable digital microfluidics. Specifically, we developed Programmable Order Polymerization (POP), Microfluidic Combinatorial Assembly of DNA (M-CAD) and Microfluidic In-vitro Cloning (MIC) and applied them to de novo synthesis, combinatorial assembly and cell-free cloning of genes, respectively. Proof-of-concept for these methods was demonstrated by programming an autonomous microfluidic system to construct and clone libraries of yeast ribosome binding sites and bacterial Azurine, which were then retrieved in individual droplets and validated. The ability to rapidly and robustly generate designer DNA molecules in an autonomous manner should have wide application in biological research and development.

DNA-library assembly programmed by on-demand nano-liter droplets from a custom microfluidic chip.

Nanoscale synthetic biology can benefit from programmable nanoliter-scale processing of DNA in microfluidic chips if they are interfaced effectively to biochemical arrays such as microwell plates. Whereas active microvalve chips require complex fabrication and operation, we show here how a passive and readily fabricated microchip can be employed for customizable nanoliter scale pipetting and reaction control involving DNA. This recently developed passive microfluidic device, supporting nanoliter scale combinatorial droplet generation and mixing, is here used to generate a DNA test library with one member per droplet exported to addressed locations on microwell plates. Standard DNA assembly techniques, such as Gibson assembly, compatible with isothermal on-chip operation, are employed and checked using off-chip PCR and assembly PCR. The control of output droplet sequences and mixing performance was verified using dyes and fluorescently labeled DNA solutions, both on-chip and in external capillary channels. Gel electrophoresis of products and DNA sequencing were employed to further verify controlled combination and functional enzymatic assembly. The scalability of the results to larger DNA libraries is also addressed by combinatorial input expansion using sequential injection plugs from a multiwell plate. Hence, the paper establishes a proof of principle of the production of functional combinatorial mixtures at the nanoliter scale for one sequence per well DNA libraries.

Computational methods for the construction, editing, and error correction of DNA molecules and their libraries.

The field of synthetic biology is fueled by steady advances in our ability to produce designer genetic material on demand. This relatively new technological capability stems from advancements in DNA construction biochemistry as well as supporting computational technologies such as tools for specifying large DNA libraries, as well as planning and optimizing their actual physical construction. In particular, the design, planning, and construction of user specified, combinatorial DNA libraries are of increasing interest. Here we present some of the computational tools we have built over the past decade to support the multidisciplinary task of constructing DNA molecules and their libraries. These technologies encompass computational methods for [1] planning and optimizing the construction of DNA molecules and libraries, [2] the utilization of existing natural or synthetic fragments, [3] identification of shared fragments, [4] planning primers and overlaps, [5] minimizing the number of assembly steps required, and (6) correcting erroneous constructs. Other computational technologies that are important in the overall process of DNA construction, such as [1] computational tools for efficient specification and intuitive visualization of large DNA libraries (which aid in debugging library design pre-construction) and [2] automated liquid handling robotic programming [Linshiz et al., Mol Syst Biol 4:191, 2008; Shabi et al., Syst Synth Biol 4:227-236, 2010], which aid in the construction process itself, have been omitted due to length limitations.

Heuristic for maximizing DNA reuse in synthetic DNA library assembly.

De novo DNA synthesis is in need of new ideas for increasing production rate and reducing cost. DNA reuse in combinatorial library construction is one such idea. Here, we describe an algorithm for planning multistage assembly of DNA libraries with shared intermediates that greedily attempts to maximize DNA reuse, and show both theoretically and empirically that it runs in linear time. We compare solution quality and algorithmic performance to the best results reported for computing DNA assembly graphs, finding that our algorithm achieves solutions of equivalent quality but with dramatically shorter running times and substantially improved scalability. We also show that the related computational problem bounded-depth min-cost string production (BDMSP), which captures DNA library assembly operations with a simplified cost model, is NP-hard and APX-hard by reduction from vertex cover. The algorithm presented here provides solutions of near-minimal stages and thanks to almost instantaneous planning of DNA libraries it can be used as a metric of "manufacturability" to guide DNA library design. Rapid planning remains applicable even for DNA library sizes vastly exceeding today's biochemical assembly methods, future-proofing our method.