Volume 14 Issue 4, April 2017

Deep brain imaging with three-photon microscopy and a swim from the US to China.

Tabulating the number of objects in categories of interest dates back to the earliest records of commerce and population censuses.

MotionCor2 software corrects for beam-induced sample motion, improving the resolution of cryo-EM reconstructions.

Automated tracing algorithms can extract neuronal morphology from fluorescent or brightfield images. UltraTracer scales up the capability of existing tracing algorithms to handle datasets of ever-increasing size.

Trans-synaptic tracing that starts from a single neuron provides a detailed view of that neuron's inputs.

A new approach measures nanoscale distances based on magnetic resonance tuning.

Thin slices through nuclei provide an unbiased view of the complex 3D organization of mammalian genomes.

Bessel focus scanning and stereoscopy speed up volumetric brain imaging.

Cryptic, widespread DNA damage is commonly interpreted as sequence variation.

Many possibilities for parsing cancer emerge when labs combine gene editing and screens. And RNAi retains its spot in the menu of options.

Advanced signal processing techniques enable the genome-wide analysis of methylation in native DNA using nanopore sequencing.

Yang and Yuste review currently available technologies for optical imaging of neural circuits, comparing them to help researchers choose optimal ones for their applications.

This Review introduces the fundamental considerations for building a light sheet microscope, describes the pros and cons associated with available implementations, and offers practical advice for users.

This Perspective introduces the development and use of adaptive optics in correcting aberrations in deep optical imaging applications.

A comparison framework applied to 15 single-cell RNA-seq protocols reveals differences in accuracy and sensitivity and discusses the utility of RNA spike-in standards.

Ouzounov et al. report calcium imaging with three-photon microscopy in the mouse brain. The approach enabled noninvasive recording of activity with high spatial and temporal resolution from GCaMP6-labeled neurons located as deep as the hippocampus.

A photocleavable protein (PhoCl) that spontaneously dissociates into two fragments after illumination with violet light expands the toolkit for cellular optogenetics.

Seq-Well provides similar scale and data quality to massively parallel, droplet-based single-cell RNA-seq methods in an easy to use, inexpensive and portable microwell format compatible with low-input samples.

Fragmentation of large, imperfect crystals into nanocrystals by sonication, vortexing, or vigorous pipetting facilitates atomic-resolution analysis by the cryo-EM method MicroED.

A deep learning approach enables fast and robust prediction of hematopoietic stem cell lineage choice in time-lapse imaging three generations before conventional marker onset.

A hidden Markov model (HMM)-based tool enables detection of 5-methylcytosine (5-mC) from single-molecule nanopore-sequencing data generated directly from human genomic DNA without chemical treatment.

A tool based on hidden Markov model and hierarchical Dirichlet process (HMM-HDP) can call two methylated cytosine variants and a methylated adenine variant directly from genomic DNA using nanopore sequencing data.

The SIMLR software identifies similarities between cells across a range of single-cell RNA-seq data, enabling effective dimension reduction, clustering and visualization.

Salmon is a computational tool that uses sample-specific models and a dual-phase inference procedure to correct biases in RNA-seq data and rapidly quantify transcript abundances.

vTwINS enables high-speed volumetric calcium imaging via a V-shaped point spread function and a dedicated data-processing algorithm. Song et al. apply this strategy to image population activity in the mouse visual cortex and hippocampus.

New fluorescent biosensors enable the first super-resolution imaging of enzyme activity in live cells via fluorescence fluctuation increase by contact (FLINC).

SyConn is a computational framework that infers the synaptic wiring of neurons in volume electron microscopy data sets with machine learning. It has been applied to zebra finch, mouse and zebrafish neuronal tissue samples.

A robust acoustic droplet ejection–drop-on-tape method delivers samples to an X-ray free-electron laser source for combined serial femtosecond crystallography and X-ray emission spectroscopy analysis, providing detailed insights into macromolecular reaction dynamics.

Selection-linked integration in the Plasmodium genome allows for rapid selection of genes inserted at a genomic locus or induction of the inactivation of gene products.