Microalgae hold promise for yielding a biofuel feedstock that is sustainable, carbon-neutral, distributed, and only minimally disruptive for the production of food and feed by traditional agriculture. Amongst oleaginous eukaryotic algae, the B race of Botryococcus braunii is unique in that it produces large amounts of liquid hydrocarbons of terpenoid origin. These are comparable to fossil crude oil, and are sequestered outside the cells in a communal extracellular polymeric matrix material. Biosynthetic engineering of terpenoid bio-crude production requires identification of genes and reconstruction of metabolic pathways responsible for production of both hydrocarbons and other metabolites of the alga that compete for photosynthetic carbon and energy.

Lichens, encompassing 20,000 known species, are symbioses between specialized fungi (mycobionts), mostly ascomycetes, and unicellular green algae or cyanobacteria (photobionts). Here we describe the first parallel genomic analysis of the mycobiont Cladonia grayi and of its green algal photobiont Asterochloris glomerata. We focus on genes/predicted proteins of potential symbiotic significance, sought by surveying proteins differentially activated during early stages of mycobiont and photobiont interaction in coculture, expanded or contracted protein families, and proteins with differential rates of evolution.

Both human and mouse fibroblasts can be reprogrammed to pluripotency with Oct4, Sox2, Klf4, and c-Myc (OSKM) transcription factors. While both systems generate pluripotency, human reprogramming takes considerably longer than mouse.

3' RNA sequencing provides an alternative to whole transcript analysis. However, we do not know a priori the relative advantage of each method. Thus, a comprehensive comparison between the whole transcript and the 3' method is needed to determine their relative merits. To this end, we used two commercially available library preparation kits, the KAPA Stranded mRNA-Seq kit (traditional method) and the Lexogen QuantSeq 3' mRNA-Seq kit (3' method), to prepare libraries from mouse liver RNA. We then sequenced and analyzed the libraries to determine the advantages and disadvantages of these two approaches.

DNA cytosine methylation is an epigenetic modification that has been implicated in many biological processes. However, large-scale epigenomic studies have been applied to very few plant species, and variability in methylation among specialized tissues and its relationship to gene expression is poorly understood.

Molecular signatures are collections of genes characteristic of a particular cell type, tissue, disease, or perturbation. Signatures can also be used to interpret expression profiles generated from heterogeneous samples. Large collections of gene signatures have been previously developed and catalogued in the MSigDB database. In addition, several consortia and large-scale projects have systematically profiled broad collections of purified primary cells, molecular perturbations of cell types, and tissues from specific diseases, and the specificity and breadth of these datasets can be leveraged to create additional molecular signatures. However, to date there are few tools that allow the visualization of individual signatures across large numbers of expression profiles. Signature visualization of individual samples allows, for example, the identification of patient subcategories a priori on the basis of well-defined molecular signatures.

Complex diseases are characterized by multiple subtle perturbations to biological processes. New omics platforms can detect these perturbations, but translating the diverse molecular and statistical information into testable mechanistic hypotheses is challenging. Therefore, we set out to create a public tool that integrates these data across multiple datasets, platforms, study designs and species in order to detect the most promising targets for further mechanistic studies.