The gut–microbiome–brain connection

http://www.nature.com/nrn/journal/v15/n2/full/nrn3669.html?WT.ec_id=NRN-201402

Nature Reviews Neuroscience

 

15,

 

65

 

(2014)

 

doi:10.1038/nrn3669

Published online

 

27 December 2013

 

Studies in mice and human patients suggest that microbial imbalances in the gut influence various social, emotional and anxiety-like behaviours. Interestingly, gastrointestinal (GI) problems are common in autism spectrum disorders (ASDs), which are associated with social interaction deficits and stereotypical behaviours. A new study in Cell provides evidence that alterations in commensal gut bacteria contribute to certain behavioural abnormalities in a mouse model of ASD, highlighting the potential benefit of probiotic therapies for some of the features of such disorders.

1. Hsiao, E. Y. et al. Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders. Cellhttp://dx.doi.org/10.1016/j.cell.2013.11.024 (2013)

Statistics on how many reads are found in the intron

Total RNA sequencing reveals nascent transcription and
widespread co-transcriptional splicing in the human brain
http://www.nature.com/nsmb/journal/v18/n12/pdf/nsmb.2143.pdf

- around 40% mapped to introns
- fetal brain > adult brain > liver

Ribo-Zero Gold Kit: improved RNA-seq results after
removal of cytoplasmic and mitochondrial ribosomal
RNA

http://www.nature.com/nmeth/journal/v8/n11/pdf/nmeth.f.352.pdf%3FWT.ec_id%3DNMETH-201111

- around 32% mapped to introns

A Continuous Semantic Space Describes the Representation of Thousands of Object and Action Categories across the Human Brain

http://www.sciencedirect.com/science/article/pii/S0896627312009348

Finding Simple Tests for Brain Disorders Turns Out to Be Complex

http://www.wbur.org/npr/198086616/MENTAL-ILLNESS-BIOMARKERS

Genes, behavior and next-generation RNA sequencing

http://onlinelibrary.wiley.com/doi/10.1111/gbb.12007/pdf

R. Hitzemann∗,†,‡, D. Bottomly¶,P.Darakjian†,N. Walter†,‡, O. Iancu†, R. Searles§,B.Wilmot¶,††and S. McWeeney¶,∗∗,††

Advances in next-generation sequencing suggest that

RNA-Seq is poised to supplant microarray-based

approaches for transcriptome analysis. This article

briefly reviews the use of microarrays in the brain-

behavior context and then illustrates why RNA-Seq is a

superior strategy. Compared with microarrays, RNA-Seq

has a greater dynamic range, detects both coding and

noncoding RNAs, is superior for gene network construc-

tion, detects alternative spliced transcripts, detects allele

specific expression and can be used to extract geno-

type information, e.g. nonsynonymous coding single

nucleotide polymorphisms. Examples of where RNA-

Seq has been used to assess brain gene expression

are provided. Despite the advantages of RNA-Seq, some

disadvantages remain. These include the high cost of

RNA-Seq and the computational complexities associated

with data analysis. RNA-Seq embraces the complexity of

the transcriptome and provides a mechanism to under-

stand the underlying regulatory code; the potential to

inform the brain-behavior relationship is substantial.

Keywords: RNA-Seq, genetics, behavior, microarrays, brain

Long noncoding RNA genes: conservation of sequence and brain expression among diverse amniotes

http://genomebiology.com/2010/11/7/R72

Abstract

Background

Long considered to be the building block of life, it is now apparent that protein is only one of many functional products generated by the eukaryotic genome. Indeed, more of the human genome is transcribed into noncoding sequence than into protein-coding sequence. Nevertheless, whilst we have developed a deep understanding of the relationships between evolutionary constraint and function for protein-coding sequence, little is known about these relationships for non-coding transcribed sequence. This dearth of information is partially attributable to a lack of established non-protein-coding RNA (ncRNA) orthologs among birds and mammals within sequence and expression databases.

Results

Here, we performed a multi-disciplinary study of four highly conserved and brain-expressed transcripts selected from a list of mouse long intergenic noncoding RNA (lncRNA) loci that generally show pronounced evolutionary constraint within their putative promoter regions and across exon-intron boundaries. We identify some of the first lncRNA orthologs present in birds (chicken), marsupial (opossum), and eutherian mammals (mouse), and investigate whether they exhibit conservation of brain expression. In contrast to conventional protein-coding genes, the sequences, transcriptional start sites, exon structures, and lengths for these non-coding genes are all highly variable.

Conclusions

The biological relevance of lncRNAs would be highly questionable if they were limited to closely related phyla. Instead, their preservation across diverse amniotes, their apparent conservation in exon structure, and similarities in their pattern of brain expression during embryonic and early postnatal stages together indicate that these are functional RNA molecules, of which some have roles in vertebrate brain development.

Andrew Schwartz: Brain Control for Artificial Limbs

http://www.businessweek.com/articles/2013-01-10/andrew-schwartz-brain-control-for-artificial-limbs

When Jan Scheuermann grasped a chocolate bar and raised it to her mouth last year, it was a neuroscience breakthrough. Scheuermann, who has lost the movement of her limbs due to a degenerative spinal condition, was piloting a mechanical arm connected to her brain, using her thoughts to replicate natural motion.

InteraXon
http://www.youtube.com/watch?v=bC2vDrhxH_0 
http://www.businessweek.com/articles/2012-10-23/mind-over-machine-use-your-brain-waves-to-control-your-computer#r=lr-fs 
When it comes to controlling our computers, the last five years has seen incredible improvements in user interfaces including amazing touchscreens and much more natural vocal recognition. Now a Toronto company wants to take the UI to the next level—by going directly to the brain. You think it, and the Muse headband will make it happen under very limited circumstances.

Reconstructing visual experiences from brain activity evoked by natural movies

http://gallantlab.org/publications/nishimoto-et-al-2011.html


Shinji Nishimoto, An T. Vu, Thomas Naselaris, Yuval Benjamini, Bin Yu & Jack L. Gallant.
Current Biology, published online September 22, 2011.

Quantitative modeling of human brain activity can provide crucial insights about cortical representations and can form the basis for brain decoding devices. Recent functional magnetic resonance imaging (fMRI) studies have modeled brain activity elicited by static visual patterns and have reconstructed these patterns from brain activity. However, blood oxygen level-dependent (BOLD) signals measured via fMRI are very slow, so it has been difficult to model brain activity elicited by dynamic stimuli such as natural movies. Here we present a new motion-energy encoding model that largely overcomes this limitation. The model describes fast visual information and slow hemodynamics by separate components. We recorded BOLD signals in occipitotemporal visual cortex of human subjects who watched natural movies and fit the model separately to individual voxels. Visualization of the fit models reveals how early visual areas represent the information in movies. To demonstrate the power of our approach, we also constructed a Bayesian decoder by combining estimated encoding models with a sampled natural movie prior. The decoder provides remarkable reconstructions of the viewed movies. These results demonstrate that dynamic brain activity measured under naturalistic conditions can be decoded using current fMRI technology.

UCSD to Use Single-Cell Sequencing to Create 3D Transcriptional Map of Brain

http://www.genomeweb.com/sequencing/ucsd-use-single-cell-sequencing-create-3d-transcriptional-map-brain?hq_e=el&hq_m=1419571&hq_l=2&hq_v=637acc240e

The project has two main components, Zhang told In Sequence. The first part involves using microdissection or flow sorting techniques to grab individual cells from brain tissue and perform RNA-seq on each of the cells. For this, the team plans to do 10,000 single-cell transcriptomes by the end of the five years.

The second part of the project involves developing an in situ RNA-seq protocol to act as a "fingerprint" for transcriptional location, so the transcriptomes of the individual cells can be placed within the context of the brain. For this part, the plan is to assemble at least 500 transcripts.

 Zhang said that they are aiming to do 10,000 cells because the human brain is so diverse. Not only are there many different cell types, but even within the same type of cell, there is a huge amount of variability. "To do a comprehensive characterization, we need to sample a large enough amount … We decided to do 10,000, because only when we get to that scale might we be able to get to an accurate picture of what's going on in the human adult brain."