Biology subjects

Zhuang, X.

Publications and source records attributed to Zhuang, X..

5 recordsLinked to original sources

bioRxiv2017

Multiplexed imaging of high density libraries of RNAs with MERFISH and expansion microscopy

As an image-based single-cell transcriptomics approach, multiplexed error-robust fluorescence in situ hybridization (MERFISH) allows hundreds to thousands of RNA species to be identified, counted and localized in individual cells while preserving the native spatial context of RNAs. In MERFISH, RNAs are identified via a combinatorial labeling approach that encodes RNA species with error-robust barcodes followed by sequential rounds of single-molecule FISH (smFISH) to read out these barcodes. The accuracy of RNA identification relies on spatially separated signals from individual RNA molecules, which limits the density of RNAs that can be measured and makes the multiplexed imaging of a large number of high-abundance RNAs challenging. Here we report an approach that combines MERFISH and expansion microscopy to substantially increase the total density of RNAs that can be measured. Using this approach, we demonstrate accurate identification and counting of RNAs, with a near 100% detection efficiency, in a ~130-RNA library composed of many high-abundance RNAs, the total density of which is more than 10 fold higher than previously reported. In parallel, we demonstrate the combination of MERFISH with immunofluorescence. These advances increase the versatility of MERFISH and will facilitate its application of a wide range of biological problems.

cell biology↗

bioRxiv2017

Exploring the Genetics of Lesion and Nodal Resistance in Pea (Pisum sativum L.) to Sclerotinia sclerotiorum Using Genome-wide Association Studies and RNA-Seq

The disease white mold caused by the fungus Sclerotinia sclerotiorum is a significant threat to pea production and improved resistance to this disease is needed. Nodal resistance in plants is a phenomenon where a fungal infection is prevented from passing through a node and the infection is limited to an internode region. Nodal resistance has been observed in some pathosystems such as the pea (Pisum sativum L.)-S. sclerotiorum pathosystem. Other than nodal resistance, different pea lines display different levels of stem lesion size restriction, referred to as lesion resistance. It is unclear whether the genetics of lesion resistance and nodal resistance are identical or different. This study applied genome-wide association studies (GWAS) and RNA-Seq to understand the genetic makeup of these two types of resistance. The time series RNA-Seq experiment consisted of two pea lines (the susceptible Lifter and the partially resistant PI 240515), two treatments (mock samples and S. sclerotiorum inoculated samples), and three time points (12, 24, and 48 hours post-inoculation). Integrated results from GWAS and RNA-Seq analyses identified different redox-related transcripts for lesion and nodal resistances. A transcript encoding a glutathione S-transferase was the only shared resistance source for both phenotypes. There were more leucine rich-repeat containing transcripts found for lesion resistance, while different candidate resistance transcripts such as a VQ motif-containing protein and a myo-inositol oxygenase were found for nodal resistance. This study demonstrated the robustness of combining GWAS and RNA-Seq for identifying white mold resistance in pea, and results suggest different genetics underlying lesion and nodal resistance.

plant biology↗

bioRxiv2017

Molecular Identification and Characterization of Two Rubber Dandelion Amalgaviruses

The Amalgaviridae family comprise persistent viruses that share the genome architecture of Totiviridae and gene evolutionary resemblance to Partitiviridae. Two genera have been assigned to this family, including genus Amalgavirus consisting in nine recognized species, corresponding to plant infecting viruses with dsRNA monosegmented genomes of ca. 3.4 kb. Here, we present the molecular characterization of two novel viruses detected in rubber dandelion (Taraxacum kok-saghyz). The sequenced viruses are 3,409 and 3,413 nt long, including two partially overlapping ORFs encoding a putative coat protein and an RNA-dependent RNA polymerase (RdRP). Phylogenetic insights based on the RdRP suggest them to be members of two new species within the Amalgavirus genus. Multiple independent RNAseq data suggest that the identified viruses have a dynamic distribution and low relative RNA levels in infected plants. Virus presence was not associated with any apparent symptoms on the plant hosts. We propose the names rubber dandelion latent virus 1 & 2 to the detected amalgaviruses; the first viruses to be associated to this emergent and sustainable natural rubber crop.

microbiology↗

bioRxiv2017

High-throughput, image-based screening of genetic variant libraries

Image-based, high-throughput, high-content screening of pooled libraries of genetic perturbations will greatly advance our understanding biological systems and facilitate many biotechnology applications. Here we introduce a high-throughput screening method that allows highly diverse genotypes and the corresponding phenotypes to be imaged in numerous individual cells. To facilitate genotyping by imaging, barcoded genetic variants are introduced into the cells, each cell carrying a single genetic variant connected to a unique, nucleic-acid barcode. To identify the genotype-phenotype correspondence, we perform live-cell imaging to determine the phenotype of each cell, and massively multiplexed FISH imaging to measure the barcode expressed in the same cell. We demonstrated the utility of this approach by screening for brighter and more photostable variants of the fluorescent protein YFAST. We imaged 20 million cells expressing ~60,000 YFAST mutants and identified novel YFAST variants that are substantially brighter and/or more photostable than the wild-type protein.

systems biology↗

bioRxiv2016

Analyzing Single Molecule Localization MicroscopyData Using Cubic Splines

The resolution of super-resolution microscopy based on single molecule localization is in part determined by the accuracy of the localization algorithm. In most published approaches to date this localization is done by fitting an analytical function that approximates the point spread function (PSF) of the microscope. However, particularly for localization in 3D, analytical functions such as a Gaussian, which are computationally inexpensive, may not accurately capture the PSF shape leading to reduced fitting accuracy. On the other hand, analytical functions that can accurately capture the PSF shape, such as those based on pupil functions, can be computationally expensive. Here we investigate the use of cubic splines as an alternative fitting approach. We demonstrate that cubic splines can capture the shape of any PSF with high accuracy and that they can be used for fitting the PSF with only a 2-3x increase in computation time as compared to Gaussian fitting. We provide an open-source software package that measures the PSF of any microscope and uses the measured PSF to perform 3D single molecule localization microscopy analysis with reasonable accuracy and speed.

biophysics↗