Genetic Ancestry Correlates with Somatic Differences in a Real-World Clinical Cancer Sequencing Cohort.

Accurate ancestry inference is critical for identifying genetic contributors of cancer disparities among populations. Although methods to infer genetic ancestry have historically relied upon genome-wide markers, the adaptation to targeted clinical sequencing panels presents an opportunity to incorporate ancestry inference into routine diagnostic workflows. We show that global ancestral contributions and admixture of continental populations can be quantitatively inferred using markers captured by the MSK-IMPACT clinical panel. In a pan-cancer cohort of 45,157 patients, we observed differences by ancestry in the frequency of somatic alterations, recapitulating known associations and revealing novel associations. Despite the comparable overall prevalence of driver alterations by ancestry group, the proportion of patients with clinically actionable alterations was lower for African (30%) compared with European (33%) ancestry. Although this result is largely explained by population-specific cancer subtype differences, it reveals an inequity in the degree to which different populations are served by existing precision oncology interventions. SIGNIFICANCE: We performed a comprehensive analysis of ancestral associations with somatic mutations in a real-world pan-cancer cohort, including >5,000 non-European individuals. Using an FDA-authorized tumor sequencing panel and an FDA-recognized oncology knowledge base, we detected differences in the prevalence of clinically actionable alterations, potentially contributing to health care disparities affecting underrepresented populations. This article is highlighted in the In This Issue feature, p. 2483.

A complete temporal transcription factor series in the fly visual system.

The brain consists of thousands of neuronal types that are generated by stem cells producing different neuronal types as they age. In Drosophila, this temporal patterning is driven by the successive expression of temporal transcription factors (tTFs)1-6. Here we used single-cell mRNA sequencing to identify the complete series of tTFs that specify most Drosophila optic lobe neurons. We verify that tTFs regulate the progression of the series by activating the next tTF(s) and repressing the previous one(s), and also identify more complex mechanisms of regulation. Moreover, we establish the temporal window of origin and birth order of each neuronal type in the medulla and provide evidence that these tTFs are sufficient to explain the generation of all of the neuronal diversity in this brain region. Finally, we describe the first steps of neuronal differentiation and show that these steps are conserved in humans. We find that terminal differentiation genes, such as neurotransmitter-related genes, are present as transcripts, but not as proteins, in immature larval neurons. This comprehensive analysis of a temporal series of tTFs in the optic lobe offers mechanistic insights into how tTF series are regulated, and how they can lead to the generation of a complete set of neurons.

Enhanced Emission from Interlayer Excitons Coupled to Plasmonic Gap Cavities.

The emergence of interlayer excitons (IEs) from atomic layered transition metal dichalcogenides (TMDCs) heterostructures has drawn tremendous attention due to their unique and exotic optoelectronic properties. Coupling the IEs into optical cavities provides distinctive electromagnetic environments which plays an important role in controlling multiple optical processes such as optical nonlinear generation or photoluminescence enhancement. Here, the integration of IEs in TMDCs into plasmonic nanocavities based on a nanocube on a metallic mirror is reported. Spectroscopic studies reveal an order of magnitude enhancement of the IE at room temperature and a 5-time enhancement in fluorescence at cryogenic temperatures. Cavity modeling reveals that the enhancement of the emission is attributed to both increased excitation efficiency and Purcell effect from the cavity. The results show a novel method to control the excitonic processes in TMDC heterostructures to build high performance photonics and optoelectronics devices.

Control of tissue development and cell diversity by cell cycle-dependent transcriptional filtering.

Cell cycle duration changes dramatically during development, starting out fast to generate cells quickly and slowing down over time as the organism matures. The cell cycle can also act as a transcriptional filter to control the expression of long gene transcripts, which are partially transcribed in short cycles. Using mathematical simulations of cell proliferation, we identify an emergent property that this filter can act as a tuning knob to control gene transcript expression, cell diversity, and the number and proportion of different cell types in a tissue. Our predictions are supported by comparison to single-cell RNA-seq data captured over embryonic development. Additionally, evolutionary genome analysis shows that fast-developing organisms have a narrow genomic distribution of gene lengths while slower developers have an expanded number of long genes. Our results support the idea that cell cycle dynamics may be important across multicellular animals for controlling gene transcript expression and cell fate.

Tempora: Cell trajectory inference using time-series single-cell RNA sequencing data.

Single-cell RNA sequencing (scRNA-seq) can map cell types, states and transitions during dynamic biological processes such as tissue development and regeneration. Many trajectory inference methods have been developed to order cells by their progression through a dynamic process. However, when time series data is available, most of these methods do not consider the available time information when ordering cells and are instead designed to work only on a single scRNA-seq data snapshot. We present Tempora, a novel cell trajectory inference method that orders cells using time information from time-series scRNA-seq data. In performance comparison tests, Tempora inferred known developmental lineages from three diverse tissue development time series data sets, beating state of the art methods in accuracy and speed. Tempora works at the level of cell clusters (types) and uses biological pathway information to help identify cell type relationships. This approach increases gene expression signal from single cells, processing speed, and interpretability of the inferred trajectory. Our results demonstrate the utility of a combination of time and pathway information to supervise trajectory inference for scRNA-seq based analysis.

A Single Chiral Nanoparticle Induced Valley Polarization Enhancement.

Valley polarization is among the most critical attributes of atomically thin materials. However, increasing contrast from monolayer transition metal dichalcogenides (TMDs) has so far been challenging. In this work, a large degree of circular polarization up to 45% from a monolayer WS2 is achieved at room temperature by using a single chiral plasmonic nanoparticle. The increased contrast is attributed to the selective enhancement of both the excitation and the emission rate having one particular handedness of the circular polarization, together with accelerated radiative recombination of valley excitons due to the Purcell effect. The experimental results are corroborated by the optical simulation using the finite-difference time-domain (FDTD) method. Additionally, the single chiral nanoparticle enables the observation of valley-polarized luminescence with a linear excitation. The results provide a promising pathway to enhance valley contrast from monolayer TMDs and utilize them for nanophotonic devices.

Mechanism for the Binding of Netropsin to Hairpin DNA Revealed Using Nanoscale Ion Emitters in Native Mass Spectrometry.

Netropsin is one of the first ligands to be discovered that selectively binds to the minor groove of DNA and is actively used as a scaffold for developing potential anticancer and antibiotic agents. The mechanism by which netropsin binds to hairpin DNA remains controversial with two competing mechanisms having been proposed. In one mechanism, netropsin binding induces a hairpin-to-duplex DNA transition. Alternatively, netropsin binds in two thermodynamically different modes at a single duplexed AATT site. Here, results from native mass spectrometry (MS) with nanoscale ion emitters indicate that netropsin can simultaneously and sequentially bind to both hairpin and duplex DNA. Duplex DNA was not detected using conventional MS with larger emitters because nanoscale emitters significantly reduce the extent of salt adduction to ligand-DNA complex ions, including in the presence of relatively high concentrations of nonvolatile salts. Based on native MS and polyacrylamide gel electrophoresis results, the abundances of hairpin and duplex DNA are unaffected by the addition of netropsin. By native MS, the binding affinities for five ligand-DNA and DNA-DNA interactions can be rapidly obtained simultaneously. This research indicates a "simultaneous binding mechanism" for the interactions of netropsin with DNA.

Nanoscale Ion Emitters in Native Mass Spectrometry for Measuring Ligand-Protein Binding Affinities.

Electrospray ionization (ESI) mass spectrometry (MS) is a crucial method for rapidly determining the interactions between small molecules and proteins with ultrahigh sensitivity. However, nonvolatile molecules and salts that are often necessary to stabilize the native structures of protein-ligand complexes can readily adduct to protein ions, broaden spectral peaks, and lower signal-to-noise ratios in native MS. ESI emitters with narrow tip diameters (∼250 nm) were used to significantly reduce the extent of adduction of salt and nonvolatile molecules to protein complexes to more accurately measure ligand-protein binding constants than by use of conventional larger-bore emitters under these conditions. As a result of decreased salt adduction, peaks corresponding to protein-ligand complexes that differ in relative molecular weight by as low as 0.06% can be readily resolved. For low-molecular-weight anion ligands formed from sodium salts, anion-bound and unbound protein ions that differ in relative mass by 0.2% were completely baseline resolved using nanoscale emitters, which was not possible under these conditions using conventional emitters. Owing to the improved spectral resolution obtained using narrow-bore emitters and an analytically derived equation, K d values were simultaneously obtained for at least six ligands to a single druggable protein target from one spectrum for the first time. This research suggests that ligand-protein binding constants can be directly and accurately measured from solutions with high concentrations of nonvolatile buffers and salts by native MS.