Genotype first: Clinical genomics research through a reverse phenotyping approach.

Although genomic research has predominantly relied on phenotypic ascertainment of individuals affected with heritable disease, the falling costs of sequencing allow consideration of genomic ascertainment and reverse phenotyping (the ascertainment of individuals with specific genomic variants and subsequent evaluation of physical characteristics). In this research modality, the scientific question is inverted: investigators gather individuals with a genomic variant and test the hypothesis that there is an associated phenotype via targeted phenotypic evaluations. Genomic ascertainment research is thus a model of predictive genomic medicine and genomic screening. Here, we provide our experience implementing this research method. We describe the infrastructure we developed to perform reverse phenotyping studies, including aggregating a super-cohort of sequenced individuals who consented to recontact for genomic ascertainment research. We assessed 13 studies completed at the National Institutes of Health (NIH) that piloted our reverse phenotyping approach. The studies can be broadly categorized as (1) facilitating novel genotype-disease associations, (2) expanding the phenotypic spectra, or (3) demonstrating ex vivo functional mechanisms of disease. We highlight three examples of reverse phenotyping studies in detail and describe how using a targeted reverse phenotyping approach (as opposed to phenotypic ascertainment or clinical informatics approaches) was crucial to the conclusions reached. Finally, we propose a framework and address challenges to building collaborative genomic ascertainment research programs at other institutions. Our goal is for more researchers to take advantage of this approach, which will expand our understanding of the predictive capability of genomic medicine and increase the opportunity to mitigate genomic disease.

A chromosome-scale epigenetic map of the Hydra genome reveals conserved regulators of cell state.

The epithelial and interstitial stem cells of the freshwater polyp Hydra are the best-characterized stem cell systems in any cnidarian, providing valuable insight into cell type evolution and the origin of stemness in animals. However, little is known about the transcriptional regulatory mechanisms that determine how these stem cells are maintained and how they give rise to their diverse differentiated progeny. To address such questions, a thorough understanding of transcriptional regulation in Hydra is needed. To this end, we generated extensive new resources for characterizing transcriptional regulation in Hydra, including new genome assemblies for Hydra oligactis and the AEP strain of Hydra vulgaris, an updated whole-animal single-cell RNA-seq atlas, and genome-wide maps of chromatin interactions, chromatin accessibility, sequence conservation, and histone modifications. These data revealed the existence of large kilobase-scale chromatin interaction domains in the Hydra genome that contain transcriptionally coregulated genes. We also uncovered the transcriptomic profiles of two previously molecularly uncharacterized cell types: isorhiza-type nematocytes and somatic gonad ectoderm. Finally, we identified novel candidate regulators of cell type-specific transcription, several of which have likely been conserved at least since the divergence of Hydra and the jellyfish Clytia hemisphaerica more than 400 million years ago.

Mapping genomic features of tiling microarray data by TileMapper.

The recent revolution of genomics techniques has allowed the detection of various sequence features and biological variations on whole-genome scale. However, these high-resolution data present significant challenges for experimental biologists to understand and analyze. The conventional way is to use genome browsers to locate and visualize regions of interest. But it lacks user-friendly data mining functionality. Here we present a protocol that allows rapid annotation of genomic coordinate data by using TileMapper. Interesting biological annotations from large-scale genomic data, such as transcriptome analysis, chromatin immunoprecipitation on chip, or methyl-DNA immunoprecipitation (MeDIP) studies generated from the tiling microarrays and other platforms, could be analyzed without requiring computational skills. The outputs are saved in tabulated format, which permit flexible and simple processing in spreadsheet software, or to be exported to other pipelines for subsequent analysis.

GonadSAGE: a comprehensive SAGE database for transcript discovery on male embryonic gonad development.

SUMMARY: Serial analysis of gene expression (SAGE) provides an alternative, with additional advantages, to microarray gene expression studies. GonadSAGE is the first publicly available web-based SAGE database on male gonad development that covers six male mouse embryonic gonad stages, including E10.5, E11.5, E12.5, E13.5, E15.5 and E17.5. The sequence coverage of each SAGE library is beyond 150K, 'which is the most extensive sequence-based male gonadal transcriptome to date'. An interactive web interface with customizable parameters is provided for analyzing male gonad transcriptome information. Furthermore, the data can be visualized and analyzed with the other genomic features in the UCSC genome browser. It represents an integrated platform that leads to a better understanding of male gonad development, and allows discovery of related novel targets and regulatory pathways.

GermSAGE: a comprehensive SAGE database for transcript discovery on male germ cell development.

GermSAGE is a comprehensive web-based database generated by Serial Analysis of Gene Expression (SAGE) representing major stages in mouse male germ cell development, with 150,000 sequence tags in each SAGE library. A total of 452,095 tags derived from type A spermatogonia (Spga), pachytene spermatocytes (Spcy) and round spermatids (Sptd) were included. GermSAGE provides web-based tools for browsing, comparing and searching male germ cell transcriptome data at different stages with customizable searching parameters. The data can be visualized in a tabulated format or further analyzed by aligning with various annotations available in the UCSC genome browser. This flexible platform will be useful for gaining better understanding of the genetic networks that regulate spermatogonial cell renewal and differentiation, and will allow novel gene discovery. GermSAGE is freely available at http://germsage.nichd.nih.gov/