The epigenetic background of pluripotent stem cells can influence transcriptional and functional behavior. Most of these data have been obtained in standard monolayer cell culture systems. In this study, we used exome sequencing, array comparative genomic hybridization (CGH), miRNA array, DNA methylation array, three-dimensional (3D) tissue engineering, and immunostaining to conduct a comparative analysis of two induced pluripotent stem cell (iPSC) lines used in engineering of 3D human epidermal equivalent (HEE), which more closely approximates epidermis. Exome sequencing and array CGH suggested that their genome was stable following 3 months of feeder-free culture. While the miRNAome was also not affected, ≈7% of CpG sites were differently methylated between the two lines. Analysis of the epidermal differentiation complex, a region on chromosome 1 that contains multiple genes involved in skin barrier maturation (including trichohyalin, TCHH), found that in one of the iPSC clones (iKCL004), TCHH retained a DNA methylation signature characteristic of the original somatic cells, whereas in other iPSC line (iKCL011), the TCHH methylation signature matched that of the human embryonic stem cell line KCL034. The difference between the two iPSC clones in TCHH methylation did not have an obvious effect on its expression in 3D HEE, suggesting that differentiation and tissue formation may mitigate variations in the iPSC methylome.

To provide a temporal framework for the genoarchitecture of brain development, we generated in situ hybridization data for embryonic and postnatal mouse brain at seven developmental stages for ∼2,100 genes, which were processed with an automated informatics pipeline and manually annotated. This resource comprises 434,946 images, seven reference atlases, an ontogenetic ontology, and tools to explore coexpression of genes across neurodevelopment. Gene sets coinciding with developmental phenomena were identified. A temporal shift in the principles governing the molecular organization of the brain was detected, with transient neuromeric, plate-based organization of the brain present at E11.5 and E13.5. Finally, these data provided a transcription factor code that discriminates brain structures and identifies the developmental age of a tissue, providing a foundation for eventual genetic manipulation or tracking of specific brain structures over development. The resource is available as the Allen Developing Mouse Brain Atlas (http://developingmouse.brain-map.org).

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.