Single-nuclei transcriptomes from human adrenal gland reveal distinct cellular identities of low and high-risk neuroblastoma tumors

Childhood neuroblastoma has a remarkable variability in outcome. Age at diagnosis is one of the most important prognostic factors, with children less than 1 year old having favorable outcomes. Here we study single-cell and single-nuclei transcriptomes of neuroblastoma with different clinical risk groups and stages, including healthy adrenal gland. We compare tumor cell populations with embryonic mouse sympatho-adrenal derivatives, and post-natal human adrenal gland. We provide evidence that low and high-risk neuroblastoma have different cell identities, representing two disease entities. Low-risk neuroblastoma presents a tran- scriptome that resembles sympatho- and chromaffin cells, whereas malignant cells enriched in high-risk neuroblastoma resembles a subtype of TRKB+cholinergic progenitor population identified in human post-natal gland. Analyses of these populations reveal different gene expression programs for worst and better survival in correlation with age at diagnosis. Our findings reveal two cellular identities and a composition of human neuroblastoma tumors reflecting clinical heterogeneity and outcome

Correction: AGAPE (Automated Genome Analysis PipelinE) for Pan-Genome Analysis of Saccharomyces cerevisiae

The characterization and public release of genome sequences from thousands of organisms is expanding the scope for genetic variation studies. However, understanding the phenotypic consequences of genetic variation remains a challenge in eukaryotes due to the complexity of the genotype-phenotype map. One approach to this is the intensive study of model systems for which diverse sources of information can be accumulated and integrated. Saccharomyces cerevisiae is an extensively studied model organism, with well-known protein functions and thoroughly curated phenotype data. To develop and expand the available resources linking genomic variation with function in yeast, we aim to model the pan-genome of S. cerevisiae. To initiate the yeast pan-genome, we newly sequenced or re-sequenced the genomes of 25 strains that are commonly used in the yeast research community using advanced sequencing technology at high quality. We also developed a pipeline for automated pan-genome analysis, which integrates the steps of assembly, annotation, and variation calling. To assign strain-specific functional annotations, we identified genes that were not present in the reference genome. We classified these according to their presence or absence across strains and characterized each group of genes with known functional and phenotypic features. The functional roles of novel genes not found in the reference genome and associated with strains or groups of strains appear to be consistent with anticipated adaptations in specific lineages. As more S. cerevisiae strain genomes are released, our analysis can be used to collate genome data and relate it to lineage-specific patterns of genome evolution. Our new tool set will enhance our understanding of genomic and functional evolution in S. cerevisiae, and will be available to the yeast genetics and molecular biology community

AGAPE (Automated Genome Analysis PipelinE) for Pan-Genome Analysis of Saccharomyces cerevisiae

The characterization and public release of genome sequences from thousands of organ- isms is expanding the scope for genetic variation studies. However, understanding the phenotypic consequences of genetic variation remains a challenge in eukaryotes due to the complexity of the genotype-phenotype map. One approach to this is the intensive study of model systems for which diverse sources of information can be accumulated and integrated. Saccharomyces cerevisiae is an extensively studied model organism, with well-known protein functions and thoroughly curated phenotype data. To develop and expand the available resources linking genomic variation with function in yeast, we aim to model the pan-genome of S. cerevisiae. To initiate the yeast pan-genome, we newly sequenced or re- sequenced the genomes of 25 strains that are commonly used in the yeast research community using advanced sequencing technology at high quality. We also developed a pipe- line for automated pan-genome analysis, which integrates the steps of assembly, annotation, and variation calling. To assign strain-specific functional annotations, we identified genes that were not present in the reference genome. We classified these according to their presence or absence across strains and characterized each group of genes with known functional and phenotypic features. The functional roles of novel genes not found in the reference genome and associated with strains or groups of strains appear to be consistent with anticipated adaptations in specific lineages. As more S . cerevisiae strain genomes are released, our analysis can be used to collate genome data and relate it to lineage-specific patterns of genome evolution. Our new tool set will enhance our understanding of genomic and functional evolution in S. cerevisiae, and will be available to the yeast genetics and molecular biology community

Genetic diversity and population structure of the endangered marsupial Sarcophilus harrisii (Tasmanian devil)

The Tasmanian devil (Sarcophilus harrisii) is threatened with extinction because of a contagious cancer known as Devil Facial Tumor Disease. The inability to mount an immune response and to reject these tumors might be caused by a lack of genetic diversity within a dwindling population. Here we report a whole-genome analysis of two animals originating from extreme northwest and southeast Tasmania, the maximal geographic spread, together with the genome from a tumor taken from one of them. A 3.3-Gb de novo assembly of the sequence data from two complementary next-generation sequencing platforms was used to identify 1 million polymorphic genomic positions, roughly one-quarter of the number observed between two genetically distant human genomes. Analysis of 14 complete mitochondrial genomes from current and museum specimens, as well as mitochondrial and nuclear SNP markers in 175 animals, suggests that the observed low genetic diversity in today's population preceded the Devil Facial Tumor Disease disease outbreak by at least 100 y. Using a genetically characterized breeding stock based on the genome sequence will enable preservation of the extant genetic diversity in future Tasmanian devil populations

Galaxy tools to study genome diversity

BACKGROUND: Intra-species genetic variation can be used to investigate population structure, selection, and gene flow in non-model vertebrates; and due to the plummeting costs for genome sequencing, it is now possible for small labs to obtain full-genome variation data from their species of interest. However, those labs may not have easy access to, and familiarity with, computational tools to analyze those data. RESULTS: We have created a suite of tools for the Galaxy web server aimed at handling nucleotide and amino-acid polymorphisms discovered by full-genome sequencing of several individuals of the same species, or using a SNP genotyping microarray. In addition to providing user-friendly tools, a main goal is to make published analyses reproducible. While most of the examples discussed in this paper deal with nuclear-genome diversity in non-human vertebrates, we also illustrate the application of the tools to fungal genomes, human biomedical data, and mitochondrial sequences. CONCLUSIONS: This project illustrates that a small group can design, implement, test, document, and distribute a Galaxy tool collection to meet the needs of a particular community of biologists

A Coffee Berry Borer (Coleoptera: Curculionidae: Scolytinae) Bibliography

Native to Africa, the coffee berry borer, Hypothenemus hampei (Ferrari) (Coleoptera: Curculionidae: Scolytinae), has gradually invaded most coffee-growing areas worldwide. Adult females colonize the coffee berry and oviposit within galleries in the coffee seeds. Larvae and adults consume the seeds, resulting in drastic reductions in yields and quality, negatively affecting the income of approximately 20 million coffee-growing families (~100 million people) in ~80 countries, with losses surpassing more than $500 million annually (Vega et al. 2015). It has become evident that the coffee berry borer scientific community could greatly benefit from having access to a bibliography of the literature related to the insect. Such an information source would allow scientists to find out what research areas have been explored throughout the many coffee berry borer-infested countries after more than 100 years of research on the topic. It could also help to direct lead future research efforts into novel areas, and away from topics and ideas that have been thoroughly investigated in the past