Bigtools: a high-performance BigWig and BigBed library in Rust.

MOTIVATION: The BigWig and BigBed file formats were originally designed for the visualization of next-generation sequencing data through a genome browser. Due to their versatility, these formats have long since become ubiquitous for the storage of processed sequencing data and regularly serve as the basis for downstream data analysis. As the number and size of sequencing experiments continues to accelerate, there is an increasing demand to efficiently generate and query BigWig and BigBed files in a scalable and robust manner, and to efficiently integrate these functionalities into data analysis environments and third-party applications. RESULTS: Here, we present Bigtools, a feature-complete, high-performance, and integrable software library for generating and querying both BigWig and BigBed files. Bigtools is written in the Rust programming language and includes a flexible suite of command line tools as well as bindings to Python. AVAILABILITY AND IMPLEMENTATION: Bigtools is cross-platform and released under the MIT license. It is distributed on Crates.io, Bioconda, and the Python Package Index, and the source code is available at https://github.com/jackh726/bigtools.

Bigtools: a high-performance BigWig and BigBed library in Rust.

The BigWig and BigBed file formats were originally designed for the visualization of next-generation sequencing data through a genome browser. Due to their versatility, these formats have long since become ubiquitous for the storage of processed sequencing data and regularly serve as the basis for downstream data analysis. As the number and size of sequencing experiments continues to accelerate, there is an increasing demand to efficiently generate and query BigWig and BigBed files in a scalable and robust manner, and to efficiently integrate these functionalities into data analysis environments and third-party applications. Here, we present Bigtools, a feature-complete, high-performance, and integrable software library for generating and querying both BigWig and BigBed files. Bigtools is written in the Rust programming language and includes a flexible suite of command line tools as well as bindings to Python. Bigtools is cross-platform and released under the MIT license. It is distributed on Crates.io and the Python Package Index, and the source code is available at https://github.com/jackh726/bigtools.

Generation and molecular characterization of human pluripotent stem cell-derived pharyngeal foregut endoderm.

Approaches to study human pharyngeal foregut endoderm-a developmental intermediate that is linked to various human syndromes involving pharynx development and organogenesis of tissues such as thymus, parathyroid, and thyroid-have been hampered by scarcity of tissue access and cellular models. We present an efficient stepwise differentiation method to generate human pharyngeal foregut endoderm from pluripotent stem cells. We determine dose and temporal requirements of signaling pathway engagement for optimized differentiation and characterize the differentiation products on cellular and integrated molecular level. We present a computational classification tool, "CellMatch," and transcriptomic classification of differentiation products on an integrated mouse scRNA-seq developmental roadmap confirms cellular maturation. Integrated transcriptomic and chromatin analyses infer differentiation stage-specific gene regulatory networks. Our work provides the method and integrated multiomic resource for the investigation of disease-relevant loci and gene regulatory networks and their role in developmental defects affecting the pharyngeal endoderm and its derivatives.

Integration of single-cell transcriptomes and chromatin landscapes reveals regulatory programs driving pharyngeal organ development.

Maldevelopment of the pharyngeal endoderm, an embryonic tissue critical for patterning of the pharyngeal region and ensuing organogenesis, ultimately contributes to several classes of human developmental syndromes and disorders. Such syndromes are characterized by a spectrum of phenotypes that currently cannot be fully explained by known mutations or genetic variants due to gaps in characterization of critical drivers of normal and dysfunctional development. Despite the disease-relevance of pharyngeal endoderm, we still lack a comprehensive and integrative view of the molecular basis and gene regulatory networks driving pharyngeal endoderm development. To close this gap, we apply transcriptomic and chromatin accessibility single-cell sequencing technologies to generate a multi-omic developmental resource spanning pharyngeal endoderm patterning to the emergence of organ-specific epithelia in the developing mouse embryo. We identify cell-type specific gene regulation, distill GRN models that define developing organ domains, and characterize the role of an immunodeficiency-associated forkhead box transcription factor.

The DnaA inhibitor SirA acts in the same pathway as Soj (ParA) to facilitate oriC segregation during Bacillus subtilis sporulation.

DNA replication and chromosome segregation must be carefully regulated to ensure reproductive success. During Bacillus subtilis sporulation, chromosome copy number is reduced to two, and cells divide asymmetrically to produce the future spore (forespore) compartment. For successful sporulation, oriC must be captured in the forespore. New rounds of DNA replication are prevented in part by SirA, a protein that utilizes residues in its N-terminus to directly target Domain I of the bacterial initiator, DnaA. Using a quantitative forespore chromosome organization assay, we show that SirA also acts in the same pathway as another DnaA regulator, Soj, to promote oriC capture in the forespore. By analyzing loss-of-function variants of both SirA and DnaA, we observe that SirA's ability to inhibit DNA replication can be genetically separated from its role in oriC capture. In addition, we identify substitutions near the C-terminus of SirA and in DnaA Domain III that enhance interaction between the two proteins. One such variant, SirAP141T , remained functional in regard to inhibiting replication, but was unable to support oriC capture. Collectively, our results support a model in which SirA targets DnaA Domain I to inhibit DNA replication, and DnaA Domain III to facilitate Soj-dependent oriC capture in the forespore.