Faculty Opinions recommendation of Total RNA sequencing reveals nascent transcription and widespread co-transcriptional splicing in the human brain.

Author(s):  
Karla Neugebauer
Keyword(s):  
2011 ◽  
Vol 18 (12) ◽  
pp. 1435-1440 ◽  
Author(s):  
Adam Ameur ◽  
Ammar Zaghlool ◽  
Jonatan Halvardson ◽  
Anna Wetterbom ◽  
Ulf Gyllensten ◽  
...  
Keyword(s):  

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Kristen L. Beck ◽  
Niina Haiminen ◽  
David Chambliss ◽  
Stefan Edlund ◽  
Mark Kunitomi ◽  
...  

AbstractIn this work, we hypothesized that shifts in the food microbiome can be used as an indicator of unexpected contaminants or environmental changes. To test this hypothesis, we sequenced the total RNA of 31 high protein powder (HPP) samples of poultry meal pet food ingredients. We developed a microbiome analysis pipeline employing a key eukaryotic matrix filtering step that improved microbe detection specificity to >99.96% during in silico validation. The pipeline identified 119 microbial genera per HPP sample on average with 65 genera present in all samples. The most abundant of these were Bacteroides, Clostridium, Lactococcus, Aeromonas, and Citrobacter. We also observed shifts in the microbial community corresponding to ingredient composition differences. When comparing culture-based results for Salmonella with total RNA sequencing, we found that Salmonella growth did not correlate with multiple sequence analyses. We conclude that microbiome sequencing is useful to characterize complex food microbial communities, while additional work is required for predicting specific species’ viability from total RNA sequencing.


Glia ◽  
2020 ◽  
Vol 68 (6) ◽  
pp. 1291-1303 ◽  
Author(s):  
Kelly Perlman ◽  
Charles P. Couturier ◽  
Moein Yaqubi ◽  
Arnaud Tanti ◽  
Qiao‐Ling Cui ◽  
...  

BMC Genomics ◽  
2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Amy Webb ◽  
Audrey C. Papp ◽  
Amanda Curtis ◽  
Leslie C. Newman ◽  
Maciej Pietrzak ◽  
...  

2018 ◽  
Vol 35 (11) ◽  
pp. 1877-1884
Author(s):  
Yumi Kawamura ◽  
Shinsuke Koyama ◽  
Ryo Yoshida

Cephalalgia ◽  
2018 ◽  
Vol 38 (13) ◽  
pp. 1976-1983 ◽  
Author(s):  
William Renthal

Background Migraine is a debilitating disorder characterized by severe headaches and associated neurological symptoms. A key challenge to understanding migraine has been the cellular complexity of the human brain and the multiple cell types implicated in its pathophysiology. The present study leverages recent advances in single-cell transcriptomics to localize the specific human brain cell types in which putative migraine susceptibility genes are expressed. Methods The cell-type specific expression of both familial and common migraine-associated genes was determined bioinformatically using data from 2,039 individual human brain cells across two published single-cell RNA sequencing datasets. Enrichment of migraine-associated genes was determined for each brain cell type. Results Analysis of single-brain cell RNA sequencing data from five major subtypes of cells in the human cortex (neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells) indicates that over 40% of known migraine-associated genes are enriched in the expression profiles of a specific brain cell type. Further analysis of neuronal migraine-associated genes demonstrated that approximately 70% were significantly enriched in inhibitory neurons and 30% in excitatory neurons. Conclusions This study takes the next step in understanding the human brain cell types in which putative migraine susceptibility genes are expressed. Both familial and common migraine may arise from dysfunction of discrete cell types within the neurovascular unit, and localization of the affected cell type(s) in an individual patient may provide insight into to their susceptibility to migraine.


2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Tetsutaro Hayashi ◽  
Haruka Ozaki ◽  
Yohei Sasagawa ◽  
Mana Umeda ◽  
Hiroki Danno ◽  
...  

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S33-S34
Author(s):  
Karen Ocwieja ◽  
Alexandra Stanton ◽  
Alexsia Richards ◽  
Jenna Antonucci ◽  
Travis Hughes ◽  
...  

Abstract Background The molecular mechanisms underpinning the neurologic and congenital pathologies caused by Zika virus (ZIKV) infection remain poorly understood. One barrier has been the lack of relevant model systems for the developing human brain; however, thanks to advances in the stem cell field, we can now evaluate ZIKV central nervous system infections in human stem cell-derived cerebral organoids which recapitulate complex 3-dimensional neural architecture. Methods We apply Seq-Well—a simple, portable platform for massively parallel single-cell RNA sequencing—to characterize cerebral organoids infected with ZIKV. Using this sequencing method, and published transcriptional profiles, we identify multiple cellular populations in our organoids, including neuroprogenitor cells, intermediate progenitor cells, and terminally differentiated neurons. We detect and quantify host mRNA transcripts and viral RNA with single-cell resolution, defining transcriptional features of uninfected cells and infected cells. Results In this model of the developing brain, we identify preferred tropisms of ZIKV infection and pronounced effects on cell division, differentiation, and death. Our data additionally reveal differences in cellular populations and gene expression within organoids infected by historic and contemporary ZIKV strains from a variety of geographic locations. This finding might help explain phenotypic differences attributed to the viruses, including variable propensity to cause microcephaly. Conclusion Overall, our work provides insight into normal and diseased human brain development, and suggests that both virus replication and host response mechanisms underlie the neuropathology of ZIKV infection. Disclosures All Authors: No reported Disclosures.


2012 ◽  
Author(s):  
Christine J. Sumner ◽  
Daniela Munafo ◽  
Larry McReynolds ◽  
Brad Langhorst ◽  
Ping Liu ◽  
...  

2019 ◽  
Vol 299 ◽  
pp. 8-12 ◽  
Author(s):  
Lucia Strieskova ◽  
Iveta Gazdaricova ◽  
Michal Kajsik ◽  
Katarina Soltys ◽  
Jaroslav Budis ◽  
...  

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