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Posts Tagged ‘Genome-wide analysis of gene expression’


 

THE 3RD STAT4ONC ANNUAL SYMPOSIUM APRIL 25-27, 2019, HILTON, HARTFORD, CONNECTICUT, 315 Trumbull St, Hartford, CT 06103

Reporter: Stephen J. Williams, Ph.D.

SYMPOSIUM OBJECTIVES

The three-day symposium aims to bring oncologists and statisticians together to share new research, discuss novel ideas, ask questions and provide solutions for cancer clinical trials. In the era of big data, precision medicine, and genomics and immune-based oncology, it is crucial to provide a platform for interdisciplinary dialogues among clinical and quantitative scientists. The Stat4Onc Annual Symposium serves as a venue for oncologists and statisticians to communicate their views on trial design and conduct, drug development, and translations to patient care. To be discussed includes big data and genomics for oncology clinical trials, novel dose-finding designs, drug combinations, immune oncology clinical trials, and umbrella/basket oncology trials. An important aspect of Stat4Onc is the participation of researchers across academia, industry, and regulatory agency.

Meeting Agenda will be announced coming soon. For Updated Agenda and Program Speakers please CLICK HERE

The registration of the symposium is via NESS Society PayPal. Click here to register.

Other  2019 Conference Announcement Posts on this Open Access Journal Include:

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Layers of Human Brain

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Human Brain Peeled Back to Its Transcriptional Core

http://www.genengnews.com/gen-news-highlights/human-brain-peeled-back-to-its-transcriptional-core/81251987/

 

http://www.genengnews.com/Media/images/GENHighlight/thumb_Nov17_2015_AllenIst_HumanBrain6811542443.jpg

The Allen Human Brain Atlas, a data set derived from analyses of tissue samples such as the one shown here, was used in an investigation of differential transcription across 132 structures in six individual brains. The investigation revealed that a set of just 32 gene-expression signatures defines, in large part, a common network architecture that is conserved across the human population. [Allen Institute for Brain Science]

 

The human brain has so many organizational layers that you might wonder whether there is, deep down, a core that we all share, however diverse our brains are in other respects. It turns out that there is a core, report scientists at the Allen Institute for Brain Science. This core, the scientists say, is transcriptional and surprisingly compact—just 32 gene-expression signatures.

The Allen Institute scientists decided that the highly stereotyped character of the human brain implied that a conserved molecular program was responsible for the brain’s development, cellular structure, and function. “So much research focuses on the variations between individuals, but we turned that question on its head to ask, what makes us similar?” explained Ed Lein, Ph.D., investigator at the Allen Institute for Brain Science. “What is the conserved element among all of us that must give rise to our unique cognitive abilities and human traits?”

Using a microarray profiling dataset from the Allen Human Brain Atlas, Dr. Lein and colleagues found that many genes showed highly consistent patterns of transcriptional regulation across brain regions as quantified using a metric called differential stability (DS). DS is the tendency for a gene to exhibit reproducible differential expression relationships across brain structures.

This approach allowed the investigators to identify molecular patterns that dominate gene expression in the human brain and appear to be common to all individuals. The investigators detailed their work November 16 in the journal Nature Neuroscience, in an article entitled, “Canonical genetic signatures of the adult human brain.”

“[We assessed] reproducibility of gene expression patterning across 132 structures in six individual brains, revealing mesoscale genetic organization,” wrote the authors. “The genes with the highest differential stability are highly biologically relevant, with enrichment for brain-related annotations, disease associations, drug targets and literature citations.”

“[These genes appear to] represent a functionally critical set whose transcriptional regulation is tightly controlled,” the authors continued. “Taking this concept of conserved patterning from genes to gene networks, we demonstrate the existence of a relatively small (32) set of consensus coexpression gene networks that explain most (90.1%, ρ > 0.4) transcriptional variation across adult brain regions.”

In other words, most of the patterns of gene usage across all 20,000 genes could be characterized by just 32 expression patterns. While many of these patterns were similar in human and mouse, the dominant genetic model organism for biomedical research, many genes showed different patterns in human. Surprisingly, genes associated with neurons were most conserved across species, while those for the supporting glial cells showed larger differences.

The most highly stable genes—the genes that were most consistent across all brains—include those that are associated with diseases and disorders like autism and Alzheimer’s and include many existing drug targets. These patterns provide insights into what makes the human brain distinct and raise new opportunities to target therapeutics for treating disease.

Finally, the investigators noted that highly consistent transcriptional architecture in neocortex is correlated with resting state functional connectivity. According to the investigators, this suggests a link between conserved gene expression and functionally relevant circuitry.

“The human brain is phenomenally complex,” said Christof Koch, Ph.D., president and CSO at the Allen Institute for Brain Science. “There could easily have been thousands of patterns, or none at all. This gives us an exciting way to look further at the functional activity that underlies the uniquely human brain.”

 

Canonical genetic signatures of the adult human brain

Michael HawrylyczJeremy A MillerVilas MenonDavid FengTim DolbeareAngela L Guillozet-BongaartsAnil G Jegga, et al.

Nature Neuroscience (2015)          http://dx.doi.org:/10.1038/nn.4171

The structure and function of the human brain are highly stereotyped, implying a conserved molecular program responsible for its development, cellular structure and function. We applied a correlation-based metric called differential stability to assess reproducibility of gene expression patterning across 132 structures in six individual brains, revealing mesoscale genetic organization. The genes with the highest differential stability are highly biologically relevant, with enrichment for brain-related annotations, disease associations, drug targets and literature citations. Using genes with high differential stability, we identified 32 anatomically diverse and reproducible gene expression signatures, which represent distinct cell types, intracellular components and/or associations with neurodevelopmental and neurodegenerative disorders. Genes in neuron-associated compared to non-neuronal networks showed higher preservation between human and mouse; however, many diversely patterned genes displayed marked shifts in regulation between species. Finally, highly consistent transcriptional architecture in neocortex is correlated with resting state functional connectivity, suggesting a link between conserved gene expression and functionally relevant circuitry.

 

Genetic variability in the regulation of gene expression in ten regions of the human brain

Adaikalavan RamasamyDaniah TrabzuniSebastian GuelfiVibin VargheseColin SmithRobert WalkerTisham DeUK Brain Expression ConsortiumNorth American Brain Expression Consortium,  et al.

Nature Neuroscience  2014;  17; 1418–1428    http://dx.doi.org:/10.1038/nn.3801

Germ-line genetic control of gene expression occurs via expression quantitative trait loci (eQTLs). We present a large, exon-specific eQTL data set covering ten human brain regions. We found thatcis-eQTL signals (within 1 Mb of their target gene) were numerous, and many acted heterogeneously among regions and exons. Co-regulation analysis of shared eQTL signals produced well-defined modules of region-specific co-regulated genes, in contrast to standard coexpression analysis of the same samples. We report cis-eQTL signals for 23.1% of catalogued genome-wide association study hits for adult-onset neurological disorders. The data set is publicly available via public data repositories and via http://www.braineac.org/. Our study increases our understanding of the regulation of gene expression in the human brain and will be of value to others pursuing functional follow-up of disease-associated variants.

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