Period of ineptitude now : INSIDE THE BOX: Solutions for Data Sharing in Life Sciences - Bio-IT World

http://www.bio-itworld.com/news/07/16/12/Inside-the-Box-Solutions-data-sharing-life-sciences.html

Coming from a wet lab background, I am amused that there's a consensus that current journal publications do not enable the sharing of data in an easily accessible manner.
At the dawn of molecular biology, where cloning a single gene warrants a publication in JBC, sharing is well, rare. :-)
Short of a few labs, I think few labs will readily share their cloned transcripts, cell lines or antibodies.
Part of the reason is of course logistics, which may include lengthy MTA discussions with the university or perhaps it might represent problems with customs with different countries.
There's of course the selfish (gene) hypothesis. If you have ongoing research, it's natural to not want another lab to have a head start to catch up with your post grad student who has been slogging to get his/her publication out.

But I think that it's great that we are all moving towards an era of open science, both in publishing in readily accessible journals and openly sharing data and looking for open collaborations.

It's quite awkward to have competition for publicly funded science, as it seems to suggest we have ran out of interesting questions to ask of the world.
if someone sees a potential for my data, that I overlooked, I will be most happy if something came out of that same data. Because sharing is caring :-)

Nat Genet. 2012 Dec 23. doi: 10.1038/ng.2507. [Epub ahead of print]

Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion.

Huyghe JR, Jackson AU, Fogarty MP, Buchkovich ML, Stančáková A, Stringham HM, Sim X, Yang L, Fuchsberger C, Cederberg H,Chines PS, Teslovich TM, Romm JM, Ling H, McMullen I, Ingersoll R, Pugh EW, Doheny KF, Neale BM, Daly MJ, Kuusisto J, Scott LJ,Kang HM, Collins FS, Abecasis GR, Watanabe RM, Boehnke M, Laakso M, Mohlke KL.

Source

Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Abstract

Insulin secretion has a crucial role in glucose homeostasis, and failure to secrete sufficient insulin is a hallmark of type 2 diabetes. Genome-wide association studies (GWAS) have identified loci contributing to insulin processing and secretion; however, a substantial fraction of the genetic contribution remains undefined. To examine low-frequency (minor allele frequency (MAF) 0.5-5%) and rare (MAF < 0.5%) nonsynonymous variants, we analyzed exome array data in 8,229 nondiabetic Finnish males using the Illumina HumanExome Beadchip. We identified low-frequency coding variants associated with fasting proinsulin concentrations at the SGSM2 and MADD GWAS loci and three new genes with low-frequency variants associated with fasting proinsulin or insulinogenic index: TBC1D30, KANK1 and PAM. We also show that the interpretation of single-variant and gene-based tests needs to consider the effects of noncoding SNPs both nearby and megabases away. This study demonstrates that exome array genotyping is a valuable approach to identify low-frequency variants that contribute to complex traits.

PMID:

 

23263489

 

[PubMed - as supplied by publisher]

Top Scientific Discoveries of 2012 | Wired Science | Wired.com

http://www.wired.com/wiredscience/2012/12/top-discoveries-2012/?pid=5738&viewall=true

Seems odd that rare variants is listed there as a top discovery.

New AWS high storage instance

The High Storage Eight Extra Large (hs1.8xlarge) instances are a great fit for applications that require high storage depth and high sequential I/O performance. Each instance includes 117 GiB of RAM, 16 virtual cores (providing 35 ECU of compute performance), and 48 TB of instance storage across 24 hard disk drives capable of delivering up to 2.4 GB per second of I/O performance.

Genome Biology | Abstract | Ray Meta: scalable de novo metagenome assembly and profiling

http://genomebiology.com/2012/13/12/R122/abstract

Abstract (provisional)
Voluminous parallel sequencing datasets, especially metagenomic experiments, require distributed computing for de novo assembly and taxonomic profiling. Ray Meta is a massively distributed metagenome assembler that is coupled with Ray Communities, which profiles microbiomes based on uniquely-colored k-mers. It can accurately assemble and profile a three billion read metagenomic experiment representing 1,000 bacterial genomes of uneven proportions in 15 hours with 1,024 processor cores, using only 1.5 GB per core. The software will facilitate the processing of large and complex datasets, and will help in generating biological insights on specific environments. Ray Meta is open source and available at http://denovoassembler.sf.net.

Article: Gattaca Alert? Or Should We Welcome the New Age of Eugenics?

http://www.forbes.com/sites/jonentine/2012/11/26/gattaca-alert-or-should-we-welcome-the-new-age-of-eugenics/

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The Evolution of Cavities – Phenomena: The Loom

http://phenomena.nationalgeographic.com/2012/12/21/the-evolution-of-cavities/

Interesting article on S. mutans which causes cavities.
Wonder what are the 148 unique to human microbiome genes that were picked up.

I doubt that removing S mutans will be an entirely good idea though, it will create a void for another species to exploit and who knows what diseases worse than cavities will prevail