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Author

Tamar Hashimshony

Bio: Tamar Hashimshony is an academic researcher from Technion – Israel Institute of Technology. The author has contributed to research in topics: Gene & Gene expression. The author has an hindex of 14, co-authored 22 publications receiving 3009 citations.

Papers
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Journal ArticleDOI
TL;DR: It is shown that CEL-Seq gives more reproducible, linear, and sensitive results than a PCR-based amplification method, and will be useful for transcriptomic analyses of complex tissues containing populations of diverse cell types.

1,166 citations

Journal ArticleDOI
TL;DR: Improvements in economics, resolution, and ease of use make CEL-Sequ2 uniquely suited to single-cell RNA-Seq analysis in terms of economics,resolution, and easing of use.
Abstract: Single-cell transcriptomics requires a method that is sensitive, accurate, and reproducible. Here, we present CEL-Seq2, a modified version of our CEL-Seq method, with threefold higher sensitivity, lower costs, and less hands-on time. We implemented CEL-Seq2 on Fluidigm’s C1 system, providing its first single-cell, on-chip barcoding method, and we detected gene expression changes accompanying the progression through the cell cycle in mouse fibroblast cells. We also compare with Smart-Seq to demonstrate CEL-Seq2’s increased sensitivity relative to other available methods. Collectively, the improvements make CEL-Seq2 uniquely suited to single-cell RNA-Seq analysis in terms of economics, resolution, and ease of use.

875 citations

Journal ArticleDOI
TL;DR: It is hoped that implementation of a pool test for COVID-19 would allow expanding current screening capacities thereby enabling the expansion of detection in the community, as well as in close organic groups, such as hospital departments, army units, or factory shifts.
Abstract: BACKGROUND: The recent emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to a current pandemic of unprecedented scale. Although diagnostic tests are fundamental to the ability to detect and respond, overwhelmed healthcare systems are already experiencing shortages of reagents associated with this test, calling for a lean immediately applicable protocol. METHODS: RNA extracts of positive samples were tested for the presence of SARS-CoV-2 using reverse transcription quantitative polymerase chain reaction, alone or in pools of different sizes (2-, 4-, 8-, 16-, 32-, and 64-sample pools) with negative samples. Transport media of additional 3 positive samples were also tested when mixed with transport media of negative samples in pools of 8. RESULTS: A single positive sample can be detected in pools of up to 32 samples, using the standard kits and protocols, with an estimated false negative rate of 10%. Detection of positive samples diluted in even up to 64 samples may also be attainable, although this may require additional amplification cycles. Single positive samples can be detected when pooling either after or prior to RNA extraction. CONCLUSIONS: As it uses the standard protocols, reagents, and equipment, this pooling method can be applied immediately in current clinical testing laboratories. We hope that such implementation of a pool test for coronavirus disease 2019 would allow expanding current screening capacities, thereby enabling the expansion of detection in the community, as well as in close organic groups, such as hospital departments, army units, or factory shifts.

354 citations

Journal ArticleDOI
31 Mar 2016-Nature
TL;DR: It is proposed that a phylum may be defined as a collection of species whose gene expression at the mid-developmental transition is both highly conserved among them, yet divergent relative to other species.
Abstract: Animals are grouped into ~35 'phyla' based upon the notion of distinct body plans. Morphological and molecular analyses have revealed that a stage in the middle of development--known as the phylotypic period--is conserved among species within some phyla. Although these analyses provide evidence for their existence, phyla have also been criticized as lacking an objective definition, and consequently based on arbitrary groupings of animals. Here we compare the developmental transcriptomes of ten species, each annotated to a different phylum, with a wide range of life histories and embryonic forms. We find that in all ten species, development comprises the coupling of early and late phases of conserved gene expression. These phases are linked by a divergent 'mid-developmental transition' that uses species-specific suites of signalling pathways and transcription factors. This mid-developmental transition overlaps with the phylotypic period that has been defined previously for three of the ten phyla, suggesting that transcriptional circuits and signalling mechanisms active during this transition are crucial for defining the phyletic body plan and that the mid-developmental transition may be used to define phylotypic periods in other phyla. Placing these observations alongside the reported conservation of mid-development within phyla, we propose that a phylum may be defined as a collection of species whose gene expression at the mid-developmental transition is both highly conserved among them, yet divergent relative to other species.

225 citations

Posted ContentDOI
27 Mar 2020-medRxiv
TL;DR: Testing a pooling approach for the standard RT-qPCR test, it is found that a single positive sample can be detected even in pools of up to 32 samples, with an estimated false negative rate of 10%.
Abstract: The recent emergence of SARS-CoV-2 lead to a current pandemic of unprecedented levels. Though diagnostic tests are fundamental to the ability to detect and respond, many health systems are already experiencing shortages of reagents associated with this test. Here, testing a pooling approach for the standard RT-qPCR test, we find that a single positive sample can be detected even in pools of up to 32 samples, with an estimated false negative rate of 10%. Detection of positive samples diluted in even up to 64 samples may also be attainable, though may require additional amplification cycles. As it uses the standard protocols, reagents and equipment, this pooling method can be applied immediately in current clinical testing laboratories. We hope that such implementation of a pool test for COVID-19 would allow expanding current screening capacities thereby enabling the expansion of detection in the community, as well as in close integral groups, such as hospital departments, army units, or factory shifts.

219 citations


Cited by
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01 Jun 2012
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

10,124 citations

Journal ArticleDOI
21 May 2015-Cell
TL;DR: Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together.

5,506 citations

Journal ArticleDOI
TL;DR: Monocle is described, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points that revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation.
Abstract: Defining the transcriptional dynamics of a temporal process such as cell differentiation is challenging owing to the high variability in gene expression between individual cells. Time-series gene expression analyses of bulk cells have difficulty distinguishing early and late phases of a transcriptional cascade or identifying rare subpopulations of cells, and single-cell proteomic methods rely on a priori knowledge of key distinguishing markers. Here we describe Monocle, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points. Applied to the differentiation of primary human myoblasts, Monocle revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation. We validated some of these predicted regulators in a loss-of function screen. Monocle can in principle be used to recover single-cell gene expression kinetics from a wide array of cellular processes, including differentiation, proliferation and oncogenic transformation.

4,119 citations

Journal ArticleDOI
TL;DR: Seurat is a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns, and correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups.
Abstract: Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

3,465 citations

01 May 2015
TL;DR: Drop-seq as discussed by the authors analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin, and identifies 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes.
Abstract: Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution. VIDEO ABSTRACT.

3,365 citations