Mechanisms of intron gain and loss in Drosophila

<p>Abstract</p> <p>Background</p> <p>It is widely accepted that orthologous genes have lost or gained introns throughout evolution. However, the specific mechanisms that generate these changes have proved elusive. Introns are known to affect nearly every level of gene expression. Therefore, understanding their mechanism of evolution after their initial fixation in eukaryotes is pertinent to understanding the means by which organisms develop greater regulation and complexity.</p> <p>Results</p> <p>To investigate possible mechanisms of intron gain and loss, we identified 189 intron gain and 297 intron loss events among 11 Drosophila species. We then investigated these events for signatures of previously proposed mechanisms of intron gain and loss. This work constitutes the first comprehensive study into the specific mechanisms that may generate intron gains and losses in Drosophila. We report evidence of intron gain via transposon insertion; the first intron loss that may have occurred via non-homologous end joining; intron gains via the repair of a double strand break; evidence of intron sliding; and evidence that internal or 5' introns may not frequently be deleted via the self-priming of reverse transcription during mRNA-mediated intron loss. Our data also suggest that the transcription process may promote or result in intron gain.</p> <p>Conclusion</p> <p>Our findings support the occurrence of intron gain via transposon insertion, repair of double strand breaks, as well as intron loss via non-homologous end joining. Furthermore, our data suggest that intron gain may be enabled by or due to transcription, and we shed further light on the exact mechanism of mRNA-mediated intron loss.</p

Examining Ways to Handle Non-Random Missingness in CEA through Econometric and Statistics Lenses

Missing data in experiments can bias estimates if not appropriately addressed. This is of particular concern in cost-effectiveness analysis where bias in either the cost or effect estimate could bias the entire cost effectiveness estimate. Complicated experimental designs, such as cluster randomized trials (CRT) or longitudinal data call for even greater care when addressing missingness. The purpose of this paper is to compare two sample selection models designed to address bias resulting from non-random missingless when applied to a longitudinal CRT. From the statistics literature we consider the Diggle Kenward model and from the econometrics literature we consider the Heckman model. Both of these models will be used to analyze the twelve-month outcomes of a worksite weight loss program, as well as used in a simulation experiment

An in vivo functional genomics screen of nuclear receptors and their co-regulators identifies FOXA1 as an essential gene in lung tumorigenesis

Using a mini-library of 1,062 lentiviral shRNAs targeting 40 nuclear hormone receptors and 70 of their co-regulators, we searched for potential therapeutic targets that would be important during in vivo tumor growth using a parallel in vitro and in vivo shRNA screening strategy in the non-small cell lung cancer (NSCLC) line NCI-H1819. We identified genes essential for in vitro growth, including BRCA1, CCND1, MED1, PHB, HNRNPU, PELP1. By contrast, nine genes were required for tumor survival in vivo, but not in vitro: NCOR2, FOXA1, HDAC1, RXRA, RORB, RARB, MTA2, ETV4, and NR1H2. We focused on FOXA1, since it lies within the most frequently amplified genomic region in lung adenocarcinomas. We found that 14q-amplification in NSCLC cell lines was a biomarker for FOXA1 dependency for both in vivo xenograft growth and colony formation, but not mass culture growth in vitro. FOXA1 knockdown identified genes involved in electron transport among the most differentially regulated, indicating FOXA1 loss may lead to a decrease in cellular respiration. In support of this, FOXA1 amplification was correlated with increased sensitivity to the complex I inhibitor phenformin, suggesting that FOXA1 helps support cellular respiration in this genetic context. Integrative ChipSeq analyses reveal that this regulatory function may be at least partially independent of NKX2-1. Our findings are consistent with a neomorphic function for amplified FOXA1, driving an oncogenic transcriptional program in this context. These data provide new insight into the functional consequences of FOXA1 amplification in lung adenocarcinomas and identify new transcriptional networks for exploration of therapeutic vulnerabilities in this patient population