Biology subjects

Park, S. G.

Publications and source records attributed to Park, S. G..

3 recordsLinked to original sources

bioRxiv2018

The jellyfish genome sheds light on the early evolution of active predation

BackgroundUnique among cnidarians, jellyfish have remarkable morphological and biochemical innovations that allow them to actively hunt in the water column. One of the first animals to become free-swimming, jellyfish employ pulsed jet propulsion and venomous tentacles to capture prey.\n\nResultsTo understand these key innovations, we sequenced the genome of the giant Nomuras jellyfish (Nemopilema nomurai), the transcriptomes of its bell and tentacles, and transcriptomes across tissues and developmental stages of the Sanderia malayensis jellyfish. Analyses of Nemopilema and other cnidarian genomes revealed adaptations associated with swimming, marked by codon bias in muscle contraction and expansion of neurotransmitter genes, along with expanded Myosin type II family and venom domains; possibly contributing to jellyfish mobility and active predation. We also identified gene family expansions of Wnt and posterior Hox genes, and discovered the important role of retinoic acid signaling in this ancient lineage of metazoans, which together may be related to the unique jellyfish body plan (medusa formation).\n\nConclusionsTaken together, the jellyfish genome and transcriptomes genetically confirm their unique morphological and physiological traits that have combined to make these animals one of the worlds earliest and most successful multi-cellular predators.

genomics↗

bioRxiv2018

The whale shark genome reveals how genomic and physiological properties scale with body size

The endangered whale shark (Rhincodon typus) is the largest fish on Earth and is a long-lived member of the ancient Elasmobranchii clade. To characterize the relationship between genome features and biological traits, we sequenced and assembled the genome of the whale shark and compared its genomic and physiological features to those of 81 animals and yeast. We examined scaling relationships between body size, temperature, metabolic rates, and genomic features and found both general correlations across the animal kingdom and features specific to the whale shark genome. Among animals, increased lifespan is positively correlated to body size and metabolic rate. Several genomic features also significantly correlated with body size, including intron and gene length. Our large-scale comparative genomic analysis uncovered general features of metazoan genome architecture: GC content and codon adaptation index are negatively correlated, and neural connectivity genes are longer than average genes in most genomes. Focusing on the whale shark genome, we identified multiple features that significantly correlate with lifespan. Among these were very long gene length, due to large introns highly enriched in repetitive elements such as CR1-like LINEs, and considerably longer neural genes of several types, including connectivity, activity, and neurodegeneration genes. The whale sharks genome had an expansion of gene families related to fatty acid metabolism and neurogenesis, with the slowest evolutionary rate observed in vertebrates to date. Our comparative genomics approach uncovered multiple genetic features associated with body size, metabolic rate, and lifespan, and showed that the whale shark is a promising model for studies of neural architecture and lifespan.

genomics↗

bioRxiv2018

Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy

Most patients with advanced cancer eventually acquire resistance to targeted therapies, spurring extensive efforts to identify molecular events mediating therapy resistance. Many of these events involve synthetic rescue (SR) interactions, where the reduction in cancer cell viability caused by targeted gene inactivation is rescued by an adaptive alteration of another gene (the rescuer). Here we perform a genome-wide prediction of SR rescuer genes by analyzing tumor transcriptomics and survival data of 10,000 TCGA cancer patients. Predicted SR interactions are validated in new experimental screens. We show that SR interactions can successfully predict cancer patients response and emerging resistance. Inhibiting predicted rescuer genes sensitizes resistant cancer cells to therapies synergistically, providing initial leads for developing combinatorial approaches to overcome resistance proactively. Finally, we show that the SR analysis of melanoma patients successfully identifies known mediators of resistance to immunotherapy and predicts novel rescuers.

cancer biology↗