#Transcriptome analysis [focusing on brain tissue]
using…long-read[s]…reveals…co-association of
distant…exonshttp://www.nature.com/nbt/journal/vaop/ncurrent/abs/nbt.3242.html
Mostly protein coding genes
His brain, her brain? http://www.sciencemag.org/content/346/6212/915.summary Neurosexism potentially results from multiple testing & only publishing positives
Convergent…specializations in brains of humans & songbirds http://www.sciencemag.org/content/346/6215/1256846.long Both have matching expression patterns across regions
Brain boosting: It’s not just grey matter that matters http://www.newscientist.com/article/mg22530090.600-brain-boosting-its-not-just-grey-matter-that-matters.html Learning involves changes to myelin sheaths, not just synapses
Genotype to phenotype relationships in ASD http://www.nature.com/neuro/journal/v18/n2/abs/nn.3907.html Expression differences in #brain development for LOF-containing, M v F, &c
Also, netbag finds subnets assoc w autism
The discovery of integrated gene networks for autism and related disorders
Fereydoun Hormozdiari
Osnat Penn
Elhanan Borenstein
Evan E. Eichler
Published in Advance November 5, 2014, doi:10.1101/gr.178855.114 Genome Res. 2015. 25: 142-154
QT:{{”
Motivated by this observation, we have developed a novel method that simultaneously integrates information from both PPI and coexpression networks to identify highly connected modules in both types of networks that are also enriched in mutations in cases and not in controls. We call this method MAGI, short for merging affected genes into integrated networks. MAGI is based on a combinatorial
optimization algorithm that aims to maximize the number of mutations in the modules while accounting for gene length and distribution of putative LoF and missense mutations in cases and controls. MAGI is generic and can be applied to any disease, given a list of de novo mutations in cases and relevant coexpression information. Using neurodevelopmental RNA-seq data from the BrainSpan Atlas
(http://www.brainspan.org/), we have applied it to exome sequence data generated from ASD, ID, epilepsy, and schizophrenia, providing a comprehensive comparison of common and specific gene modules for these diseases.
“}}
Splicing changes along the blood lineage, good ex. of the
state-of-the-art in human transcriptomics
http://www.sciencemag.org/content/345/6204/1251033.abstract
Science 26 September 2014:
Vol. 345 no. 6204
DOI: 10.1126/science.1251033
Transcriptional diversity during lineage commitment of human blood progenitors
Chen et al.
Linial: ClanTox (www.clantox.cs.huji.ac.il) to classify short peptides as toxins. #ismb #kn1
TOLIPS relevant to brain, neuropeptides
Linial mentions NeuroPID: a predictor for identifying neuropeptide precursors from metazoan proteomes
http://bioinformatics.oxfordjournals.org/content/early/2014/03/05/bioinformatics.btt725.abstract #ismb #kn1
Neuroscience
Scientific American 310, 70 – 77 (2014)
Published online: 18 March 2014 | doi:10.1038/scientificamerican0414-70
The Genetic Geography of the Brain
Ed Lein & Mike Hawrylycz
http://www.scientificamerican.com/article/genetic-maps-of-the-brain-lead-to-surprises