Peregrine and saker falcon genome sequences provide insights into evolution of a predatory lifestyle

As top predators, falcons possess unique morphological, physiological and behavioral adaptations that allow them to be successful hunters: for example, the peregrine is renowned as the world's fastest animal. To examine the evolutionary basis of predatory adaptations, we sequenced the genomes of both the peregrine (Falco peregrinus) and saker falcon (Falco cherrug), and we present parallel, genome-wide evidence for evolutionary innovation and selection for a predatory lifestyle. The genomes, assembled using Illumina deep sequencing with greater than 100-fold coverage, are both approximately 1.2 Gb in length, with transcriptome-assisted prediction of approximately 16,200 genes for both species. Analysis of 8,424 orthologs in both falcons, chicken, zebra finch and turkey identified consistent evidence for genome-wide rapid evolution in these raptors. SNP-based inference showed contrasting recent demographic trajectories for the two falcons, and gene-based analysis highlighted falcon-specific evolutionary novelties for beak development and olfaction and specifically for homeostasis-related genes in the arid environment–adapted saker

Silencing of DLGAP5 by siRNA Significantly Inhibits the Proliferation and Invasion of Hepatocellular Carcinoma Cells

<div><p>Background</p><p>The dysregulation of oncogenes and tumor suppressor genes plays an important role in many cancers, including hepatocellular carcinoma (HCC), which is one of the most common cancers in the world. In a previous microarray experiment, we found that DLGAP5 is overexpressed in HCCs. However, whether the up-regulation of DLGAP5 contributes to hepatocarcinogenesis remains unclear. </p> <p>Methodology/Principal Findings</p><p>In this study, we showed that DLGAP5 was significantly up-regulated in 76.4% (168 of 220) of the analyzed HCC specimens when compared with adjacent liver tissue. DLGAP5 overexpression was evident in 25% (22 of 88) of the HCC specimens without AFP expression, suggesting that DLGAP5 may be a novel biomarker for HCC pathogenesis. The silencing of DLGAP5 gene expression by RNA interference significantly suppressed cell growth, migration and colony formation in vitro. The expression level of DLGAP5 was also found to be related to the methylation level of its promoter in the HCC specimens. </p> <p>Conclusions/Significance</p><p>Taken together, these data suggest that the expression of DLGAP5 is regulated by methylation and that the up-regulation of DLGAP5 contributes to HCC tumorigenesis by promoting cell proliferation.</p> </div

mRNA expression pattern of DLGAP5 in HCC specimens.

<p>(A) Representative results of the semi-quantitative RT-PCR analysis of DLGAP5 in 20 pairs of HCC (C) and adjacent non-cancerous liver tissues (N). β-Actin was used as an internal control. Each PCR was performed for 35 cycles, and the PCR products were visualized by electrophoresis on 2% agarose gels. (B) Real-time RT-PCR analysis of DLGAP5 in 220 paired HCC and adjacent non-cancerous liver tissues. For each sample, the relative mRNA level of DLGAP5 was normalized to the level of β-actin. The line within each box represents the median –ΔCt value; the upper and lower edges of each box represent the 75th and 25th percentile, respectively; the upper and lower bars indicate the highest and lowest values determined, respectively. (C) The distribution of the DLGAP5 and AFP expression levels in the 220 HCC specimens. The numbers indicate the percentages of DLGAP5- and/or AFP-positive HCC specimens, as detected by real-time RT-PCR. (D)/(E) Disease-free survival rate (D) and Overall survival rate (E) of patients with HCC. High expression of DLGAP5 mRNA was significantly associated with worse prognosis (<i>P</i>=0.010). DLGAP5 high: 2^−ΔΔCT>1 (or –ΔΔCT>0); DLGAP5 low: 2^−ΔΔCT≤1 (or −ΔΔCT≤0). </p

Protein expression pattern of DLGAP5 in HCC specimens.

<p>(A) Representative immunohistochemical DLGAP5 staining of a HCC specimen and its corresponding non-cancerous tissue from a tissue array containing 96 pairs of HCC specimens. The nuclei were counterstained with hematoxylin. Original magnification: The left (×200) and right side (×400) (normal, non-HCC and HCC). (B) Statistical analysis was performed using the chi-square test to compare the relative levels of DLGAP5 between HCC with PVTT and HCC without PVTT (<i>P</i>=0.037).</p

Effect of DLGAP5 silencing on HCC cell growth.

<p>(A and B) western blot confirmation of DLGAP5 knockdown in SMMC-7721 (A) and HepG2 (B) cells via transient transfection with siRNA2. siRNA-NC was used as the control. (C and D) The growth curves of the SMMC-7721 (C) and HepG2 (D) cells after DLGAP5 knockdown by siRNA2 were plotted based on the CCK-8 assay. siRNA-NC served as a control. The experiments were repeated at least three times, and the data points represent the average values of triplicate wells, with standard deviations (SDs) included for each mean value.</p

Effect of DLGAP5 on HCC cell migration, invasion and adhesive ratio.

<p>(A and B) Wound closure of SMMC-7721 (A) and HepG2 (B) cells that were transfected with siRNA2 in a wound-healing experiment, with siRNA-NC serving as a control. (C and D) Invasion of SMMC-7721 (C) and HepG2 (D) cells that were transfected with siRNA2 in a Matrigel assay, with siRNA-NC serving as a control. The cell numbers represent the mean values per field (from at least five fields) from three independent experiments (right panel) (mean ± SD). (E and F) Effect of DLGAP5 gene on SMMC-7721 and HepG2 cell adhesive ratio using RNAi.</p

Personalized Tuning of a Reinforcement Learning Control Algorithm for Glucose Regulation

Artificial pancreas is in the forefront of research towards the automatic insulin infusion for patients with type 1 diabetes. Due to the high inter- and intra-variability of the diabetic population, the need for personalized approaches has been raised. This study presents an adaptive, patient-specific control strategy for glucose regulation based on reinforcement learning and more specifically on the Actor-Critic (AC) learning approach. The control algorithm provides daily updates of the basal rate and insulin-to-carbohydrate (IC) ratio in order to optimize glucose regulation. A method for the automatic and personalized initialization of the control algorithm is designed based on the estimation of the transfer entropy (TE) between insulin and glucose signals. The algorithm has been evaluated in silico in adults, adolescents and children for 10 days. Three scenarios of initialization to i) zero values, ii) random values and iii) TE-based values have been comparatively assessed. The results have shown that when the TE-based initialization is used, the algorithm achieves faster learning with 98%, 90% and 73% in the A+B zones of the Control Variability Grid Analysis for adults, adolescents and children respectively after five days compared to 95%, 78%, 41% for random initialization and 93%, 88%, 41% for zero initial values. Furthermore, in the case of children, the daily Low Blood Glucose Index reduces much faster when the TE-based tuning is applied. The results imply that automatic and personalized tuning based on TE reduces the learning period and improves the overall performance of the AC algorithm

Peregrine and saker falcon genome sequences provide insights into evolution of a predatory lifestyle. Nat Genet 45: 563–566. Available: http://www.ncbi.nlm.nih.gov/pubmed

6 3 l e t t e r s As top predators, falcons possess unique morphological, physiological and behavioral adaptations that allow them to be successful hunters: for example, the peregrine is renowned as the world&apos;s fastest animal. To examine the evolutionary basis of predatory adaptations, we sequenced the genomes of both the peregrine (Falco peregrinus) and saker falcon (Falco cherrug), and we present parallel, genome-wide evidence for evolutionary innovation and selection for a predatory lifestyle. The genomes, assembled using Illumina deep sequencing with greater than 100-fold coverage, are both approximately 1.2 Gb in length, with transcriptome-assisted prediction of approximately 16,200 genes for both species. Analysis of 8,424 orthologs in both falcons, chicken, zebra finch and turkey identified consistent evidence for genome-wide rapid evolution in these raptors. SNP-based inference showed contrasting recent demographic trajectories for the two falcons, and gene-based analysis highlighted falcon-specific evolutionary novelties for beak development and olfaction and specifically for homeostasisrelated genes in the arid environment-adapted saker