The decline of global honeybee populations are a major environment concern, because of their vital role in our food systems and pollination of flowering plants. Twenty first century ‘Omics is coming to the rescue, and published in GigaScience this week is an article that presents the genome and proteome of a mahor threat to bee […]
This year has been an eventful one, probably too eventful for many. For GigaScience it has been eventful too, although fortunately in a much more positive way than many have experienced. While there are fears of us entering a “post-truth” era, there is more need than ever for our role as promoters of transparency, reproducibility and providers of cold-hard data. We celebrated our birthday with Mickey Mouse, and experienced many other milestones. On the technical front, this year we have brought you better integration with citable and updatable methods, bigger better and broader data types, and much more. In the tradition of end-of-year-introspection, here is a summary of some of our 2016 achievements as we continue to push the boundaries of innovative publishing of all research objects and reproducible research.
New in GigaScience is an article that presents the genome sequence of Ginkgo biloba, the oldest extant tree species. The research was carried out by a team of scientists at BGI, Zheijiang University and the Chinese Academy of Sciences, who tackled and analyzed an exceptionally large genome, totalling more than 10Gb. Ginkgo is considered by some as a “living fossil”, its form and structure having changed very little in 270 million years. Its unique position in the evolutionary tree of life means the ginkgo genome will provide an extensive resource for studying early events in tree development and evolution.
Halloween may be over, but this November GigaScience will be continuing to fight the zombie (paper) apocalypse and binge on sweet sweet brains (research outputs).
Individual human genomes are diploid in nature, with half of the homologous chromosomes derived from each parent. The context in which variations occur on each individual chromosome has profound effects on the action and clinical importance of the genes on it, but this “haplotype” information has been mostly ignored in genomics research to date. A wealth of new data released from the Personal Genome Project via a new Data Note helps fill this gap by releasing the largest set of high coverage whole human genome assemblies with experimentally determined haplotypes to date.
Here is a Q&A with the first author of our first camera trap dataset published in our Data-Intensive Ecology series. Taylor shares his thoughts on why he’s so interested in the endangered blunt-nosed leopard lizard, the usefulness of camera traps in ecology, as well as challenges with big data.
The Galaxy community is one that shares similar reproducibility goals with GigaScience, having a computational platform that allows users to share workflows, histories and wrapped computational tools in an easy-to-use and open source interface. Björn Grüning and The Intergalactic Utilities Commission of Galaxy have a guest posting here to announce new changes that will make development and presentation of tools and pipelines through Galaxy even more reproducible and usable.
The genome of the ocean sunfish (Mola mola), the world’s largest bony fish, has been just been published in GigaScience by researchers at A*STAR, Singapore, and China National Genebank. Here we talk to the researchers, including Nobel Laureate Sydney Brenner, on how the project came together, the slightly unusual sample collection, and how hope this work helps to provide insight into the fish’s extraordinary growth rate and unique body shape.
The latest apple launch event is not for a new mobile phone or tablet, but in this case a new, much improved reference genome. Just published is a new “long-read” golden delicious genome, and Hans Zauner (the latest addition to the GigaScience team) explains why it is important.
David Johnson and the PhenoMeNal consortium have a guest posting on their efforts in building an open, community-supported, e-infrastructure for medical metabolomics data, and how they are seeking community feedback on the requirements for the data infrastructures needed.