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Biology subjects

Chaffer, J.

Publications and source records attributed to Chaffer, J..

3 recordsLinked to original sources

CZ CELLxGENE Discover: A single-cell data platform for scalable exploration, analysis and modeling of aggregated data

Hundreds of millions of single cells have been analyzed to date using high throughput transcriptomic methods, thanks to technological advances driving the increasingly rapid generation of single-cell data. This provides an exciting opportunity for unlocking new insights into health and disease, made possible by meta-analysis that span diverse datasets building on recent advances in large language models and other machine learning approaches. Despite the promise of these and emerging analytical tools for analyzing large amounts of data, a major challenge remains the sheer number of datasets and inconsistent format, data models and accessibility. Many datasets are available via unique portals platforms that often lack interoperability. Here, we present CZ CellxGene Discover (cellxgene.cziscience.com), a data platform that provides curated and interoperable data. This single-cell data resource, available via a free-to-use online data portal, hosts a growing corpus of community contributed data that spans more than 50 million unique cells. Curated, standardized, and associated with consistent cell-level metadata, this collection of interoperable single-cell transcriptomic data is the largest of its kind. A suite of tools and features enables accessibility and reusability of the data via both computational and visual interfaces to allow researchers to rapidly explore individual datasets and perform cross-corpus analysis. This functionality is enabling meta-analyses of tens of millions of cells across studies and tissues and providing global views of human cells at the resolution of single cells.

cell biology↗

Tools for Quantitative Analysis of Calcium Signaling Data Using Jupyter-Lab Notebooks

Calcium signaling data analysis has become increasing complex as the size of acquired datasets increases. In this paper we present a Ca2+ signaling data analysis method that employs custom written software scripts deployed in a collection of Jupyter-Lab "notebooks" which were designed to cope with this complexity. The notebook contents are organized to optimize data analysis workflow and efficiency. The method is demonstrated through application to several different Ca2+ signaling experiment types.

cell biology↗

Centromere-associated retroelement evolution in Drosophila melanogaster reveals an underlying conflict

Centromeres are chromosomal regions essential for coordinating chromosome segregation during cell division. While centromeres are defined by the presence of a centromere-specific histone H3 variant rather than a particular DNA sequence, they are typically embedded in repeat-dense chromosomal genome regions. In many species, centromeres are associated with transposable elements, but it is unclear if these elements are selfish or if they play a role in centromere specification or function. Here we use Drosophila melanogaster as a model to understand the evolution of centromere-associated transposable elements. G2/Jockey-3 is a non-LTR retroelement in the Jockey clade and the only sequence shared by all centromeres. We study the evolution of G2/Jockey-3 using short and long read population genomic data to infer insertion polymorphisms across the genome. We combine estimates of the age, frequency, and location of insertions to infer the evolutionary processes shaping G2/Jockey-3 and its association with the centromeres. We find that G2/Jockey-3 is an active retroelement targeted by the piRNA pathway that is enriched in centromeres at least in part due to an insertion bias. We do not detect signatures of positive selection on any G2/Jockey-3 insertions that would suggest than individual copies are favored by natural selection. Instead, we infer that most insertions are neutral or weakly deleterious both inside and outside of the centromeres. Therefore, G2/Jockey-3 evolution is consistent with it being a selfish genetic element that targets centromeres. We propose that targeting centromeres helps active retroelements escape host defenses, as the unique centromeric chromatin may prevent targeting by the host silencing machinery. At the same time, centromeric TEs insertions may be tolerated or even beneficial if they also contribute to the transcriptional and chromatin environment. Thus, we suspect centromere-associated retroelements like G2/Jockey-3 reflect a balance between conflict and cooperation at the centromeres.

genomics↗