EU consortium receive $15M funding to shed light on neurological diseases

The European Community have recently funded the Neuromics Consortium with €12 million for 5 years to investigate the causes of neurological and neuromuscular diseases and found new causative genes to develop diagnostic gene panels.

Headed by the University of Tubingen, the consortium of 18 European and Australian institutions will perform whole-exome sequencing of 1,100 individuals and aims to identify causative genes for at least 80% of the studied syndromes.

The Neuromics Consortium hopes its work will yield better diagnostic panels that can increase the diagnosis rate for ten main neurodegenerative and neuromuscular disease types — including ataxia, spastic paraplegia, Huntington's disease, muscular dystrophy and spinal muscular atrophy — as well as provide information on genes and pathways that could inform new treatments.

The consortium will collaborate with Iceland's Decode Genetics, that will perform the sequencing on Illumina HiSeq and provide the main data; with Agilent Technologies, to develop new diagnostic gene panels based on the HaloPlex technology; and with Ariadne Genomics, that will provide bioinformatic support for data analysis. Also RNA-seq and other omics apporaches will be used by the consortium in the second phase of diagnostic panel development and validation.

A recent post on GenomeWeb reports that in a document describing the project, the consortium wrote that at the end of the funding period, it expects "to have elucidated the genetic basis for [more than] 80 [percent] of investigated patient groups." According to the group, the new genes will be added to existing databases and used to develop the first overlapping gene panel that can be used to diagnose several of these individual diseases, "overcoming time consuming and costly single gene analysis."

PubMed Highlight: Watermelon and Pear sequenced!

We can now add watermelon and pear to the rapidly increasing list of genome sequenced fruits! The draft sequence of watermelon was recently published on Nature Genetics, while pear sequence make its appearance on Genome Research.


Both papers report the high quality draft genome sequence, together with gene-prediction and chromosomal mapping, and reconstruct evolution of the modern fruit species, also identifying the main effects of human selection.

Besides providing useful information for further genetic improvements, the increasing number of fruit genomes available will shortly allow for identification of fruit salad or mixed juice components by sequencing...Imagine this future: just get your Oxford Nanopore MinIon sequencer out of your pocket, take a drop of juice and in a matter of minutes you'll know exactly which fruits your going to drink or eat!

Ok, maybe I'm pushing the sequencing thing a little bit too further!

Proton presented @ SIGU

Flash update directly from the Conference of Italian Society of Human Genetics (SIGU). Besides a lot of interesting talks applying ngs in diagnostic protocols and for disease gene discovery (I will cover them as I've came back) and a fascinating session on ncRNA, I want to report the official presentation of life proton and ion torrent diagnostic applications...and they provides t-shirts for free also!

In situ single cell RNA-seq to build a 3D trascriptional map of the brain

Do you remember the results from the Connectome project mapping the connections in the human brain   and resulting in those beautiful images of wired colorful brains? Probably in the next 5 years we would get much further in the understanding of cells spatial organization in the brain!

A team from the University of California, San Diego, has recently won a five-year $9.3 million dollar from NIH to perform RNA-seq on 10,000 single neuron cells and reconstruct a 3D map of gene activity in the brain. The team plan to perform complete RNA-Seq, not just poly-A RNAs, on such a large amount of cells to get a complete picture of the high genetic variability of neuron cells sub-population.


What impress me the most (and almost sounds like science fiction to me) is the idea to apply an in situ RNA-seq protocol to reconstruct the expression profile of 500 genes. These profiles will act as a "fingerprint" for transcriptional location so that for any other whole transcriptome dataset from an isolated cell authors can look at these 500 genes to find the matched pattern and infer the brain localization of the sequenced cell.
The in situ RNA-seq protocol is fascinating itself. It's based on a technique developed by George Church's group at Harvard, which imply a chemical reaction to create pores on the cells, followed by the application of a customized microfluidic device to deposit sequencing reagents into the cell. The sequencing will take place within the tissue and the signal will be read out with a microscope.
The team leader Kun Zhang, an associate professor at UCSD's Department of Bioengineering and Institute for Genomic Medicine, anticipated that the group would spend the first two to three years developing and optimizing this protocol, while canonical sequencing will be conducted at Illumina.

A deeper coverage of the story on this post from GenomeWeb or see the news directly from UCSD press.

PubMed Highlight: Single-cell genetic variability in neurons

Theoretically any two cells in our body have an high probability to show some genetic diversity, due to somatic mutations and other genetic specific rearrangements activated by cell differentiation. This concept has been proposed as a key factor in neurons. These cells show great plasticity and are divided in several different sub-populations with specific molecular and cellular characteristics and maybe all this diversity should rely on some kind of genetic reorganization particularly active in brain neurons (with retrotransposable elements as best candidates). This hypothesis has been discussed in past years and now this new paper appeared on Cell could shed some light on the real state of genetic diversity in neurons. The authors applied single-cell sequencing on 300 single neurons from cerebral cortex and caudate nucleus of three normal individuals to evaluate specific insertion of LINE-1 elements. Moreover they also evaluate the presence and diffusion of a somatic mutation in AKT3 gene in single cortical cells to characterize the mosaicism in a child with hemimegalencephaly. This study showing that neuronal disorders can arise from mutations that are specific of brain tissue or even neuron sub-populations (somatic mutations appeared in some precursor) and can thus be assessed only by sequencing the neurons themselves.
Further analysis on other neuron populations could lead to definition of a genetic profile specific for each neuron type and/or patients.

Single-Neuron Sequencing Analysis of L1 Retrotransposition and Somatic Mutation in the Human Brain

Gilad D. Evrony, Xuyu Cai, Eunjung Lee, L. Benjamin Hills, Princess C. Elhosary, Hillel S. Lehmann, J.J. Parker, Kutay D. Atabay, Edward C. Gilmore, Annapurna Poduri, Peter J. Parkand Christopher A. Walsh

SUMMARY
A major unanswered question in neuroscience is whether there exists genomic variability between
individual neurons of the brain, contributing to functional diversity or to an unexplained burden of neurological disease. To address this question, we developed a method to amplify genomes of single
neurons from human brains. Because recent reports suggest frequent LINE-1 (L1) retrotransposition in
human brains, we performed genome-wide L1 insertion profiling of 300 single neurons from cerebral cortex and caudate nucleus of three normal individuals, recovering >80% of germline insertions from single neurons. While we find somatic L1 insertions, we estimate <0.6 unique somatic insertions per
neuron, and most neurons lack detectable somatic insertions, suggesting that L1 is not a major generator of neuronal diversity in cortex and caudate. We then genotyped single cortical cells to characterize the mosaicism of a somatic AKT3 mutation identified in a child with hemimegalencephaly. Single-neuron sequencing allows systematic assessment of genomic diversity in the human brain.

Pubmed highlight: 1000 Genomes Phase I published

Data from the Phase I analysis of 1000 Genomes Project have just been published in Nature! Besides data on average distributions in a genome of SNVs, indels and structural variants; the paper also provides interesting insights on population specific distribution of variants and a lot of technical details (more than 100 pages of Supplementary materials!!) that will serve as useful guidelines for NGS data analysis!

Chek this out!

An integrated map of genetic variation from 1,092 human genomes

The 1000 Genomes Project Consortium

Abstract

By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38|[thinsp]|million single nucleotide polymorphisms, 1.4|[thinsp]|million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations.