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Moore, E.

Publications and source records attributed to Moore, E..

3 recordsLinked to original sources

Variation in pigmentation gene expression is associated with distinct aposematic color morphs in the poison frog, Dendrobates auratus

Color and pattern phenotypes have clear implications for survival and reproduction in many species. However, the mechanisms that produce this coloration are still poorly characterized, especially at the genomic level. Here we have taken a transcriptomics-based approach to elucidate the underlying genetic mechanisms affecting color and pattern in a highly polytypic poison frog. We sequenced RNA from the skin from four different color morphs during the final stage of metamorphosis and assembled a de novo transcriptome. We then investigated differential gene expression, with an emphasis on examining candidate color genes from other taxa. Overall, we found differential expression of a suite of genes that control melanogenesis, melanocyte differentiation, and melanocyte proliferation (e.g., tyrpl, lefl, leol, and mitf) as well as several differentially expressed genes involved in purine synthesis and iridophore development (e.g., arfgapl, arfgap2, airc, and gairt). Our results provide evidence that several gene networks known to affect color and pattern in vertebrates play a role in color and pattern variation in this species of poison frog.

evolutionary biology

Forecasting seasonal influenza in the U.S.: A collaborative multi-year, multi-model assessment of forecast performance

Influenza infects an estimated 9 to 35 million individuals each year in the United States and is a contributing cause for between 12,000 and 56,000 deaths annually. Seasonal outbreaks of influenza are common in temperate regions of the world, with highest incidence typically occurring in colder and drier months of the year. Real-time forecasts of influenza transmission can inform public health response to outbreaks. We present the results of a multi-institution collaborative effort to standardize the collection and evaluation of forecasting models for influenza in the US for the 2010/2011 through 2016/2017 influenza seasons. For these seven seasons, we assembled weekly real-time forecasts of 7 targets of public health interest from 22 different models. We compared forecast accuracy of each model relative to a historical baseline seasonal average. Across all regions of the US, over half of the models showed consistently better performance than the historical baseline when forecasting incidence of influenza-like illness 1, 2 and 3 weeks ahead of available data and when forecasting the timing and magnitude of the seasonal peak. In some regions, delays in data reporting were strongly and negatively associated with forecast accuracy. More timely reporting and an improved overall accessibility to novel and traditional data sources are needed to improve forecasting accuracy and its integration with real-time public health decision-making.

epidemiology

Selecting Short DNA Fragments In Plasma Improves Detection Of Circulating Tumour DNA

Introductory paragraphNon-invasive analysis of cancer genomes using cell-free circulating tumour DNA (ctDNA) is being widely implemented for clinical indications. The sensitivity for detecting the presence of ctDNA and genomic changes in ctDNA is limited by its low concentration compared to cell-free DNA of non-tumour origin. We studied the feasibility for enrichment of ctDNA by size selection, in plasma samples collected before and during chemotherapy treatment in 13 patients with recurrent high-grade serous ovarian cancer. We evaluated the effects using targeted and whole genome sequencing. Selecting DNA fragments between 90-150 bp before analysis yielded enrichment of mutated DNA fraction of up to 11-fold. This allowed identification of adverse copy number alterations, including MYC amplification, otherwise not observed. Size selection allows detection of tumour alterations masked by non-tumour DNA in plasma and could help overcome sensitivity limitations of liquid biopsy for applications in early diagnosis, detection of minimal residual disease, and genomic profiling.

genomics