A Large-Scale Zebrafish Gene Knockout Resource for the Genome-Wide Study of Gene Function

With the completion of the zebrafish genome sequencing project, it becomes possible to analyze the function of zebrafish genes in a systematic way. The first step in such an analysis is to inactivate each protein-coding gene by targeted or random mutation. Here we describe a streamlined pipeline using proviral insertions coupled with high-throughput sequencing and mapping technologies to widely mutagenize genes in the zebrafish genome. We also report the first 6144 mutagenized and archived F1’s predicted to carry up to 3776 mutations in annotated genes. Using in vitro fertilization, we have rescued and characterized ~0.5% of the predicted mutations, showing mutation efficacy and a variety of phenotypes relevant to both developmental processes and human genetic diseases. Mutagenized fish lines are being made freely available to the public through the Zebrafish International Resource Center. These fish lines establish an important milestone for zebrafish genetics research and should greatly facilitate systematic functional studies of the vertebrate genome

Mutational analysis of the tyrosine kinome in serous and clear cell endometrial cancer uncovers rare somatic mutations in TNK2 and DDR1

Background: Endometrial cancer (EC) is the 8th leading cause of cancer death amongst American women. Most ECs are endometrioid, serous, or clear cell carcinomas, or an admixture of histologies. Serous and clear ECs are clinically aggressive tumors for which alternative therapeutic approaches are needed. The purpose of this study was to search for somatic mutations in the tyrosine kinome of serous and clear cell ECs, because mutated kinases can point to potential therapeutic targets. Methods: In a mutation discovery screen, we PCR amplified and Sanger sequenced the exons encoding the catalytic domains of 86 tyrosine kinases from 24 serous, 11 clear cell, and 5 mixed histology ECs. For somatically mutated genes, we next sequenced the remaining coding exons from the 40 discovery screen tumors and sequenced all coding exons from another 72 ECs (10 clear cell, 21 serous, 41 endometrioid). We assessed the copy number of mutated kinases in this cohort of 112 tumors using quantitative real time PCR, and we used immunoblotting to measure expression of these kinases in endometrial cancer cell lines. Results: Overall, we identified somatic mutations in TNK2 (tyrosine kinase non-receptor, 2) and DDR1 (discoidin domain receptor tyrosine kinase 1) in 5.3% (6 of 112) and 2.7% (3 of 112) of ECs. Copy number gains of TNK2 and DDR1 were identified in another 4.5% and 0.9% of 112 cases respectively. Immunoblotting confirmed TNK2 and DDR1 expression in endometrial cancer cell lines. Three of five missense mutations in TNK2 and one of two missense mutations in DDR1 are predicted to impact protein function by two or more in silico algorithms. The TNK2P761Rfs*72 frameshift mutation was recurrent in EC, and the DDR1R570Q missense mutation was recurrent across tumor types. Conclusions: This is the first study to systematically search for mutations in the tyrosine kinome in clear cell endometrial tumors. Our findings indicate that high-frequency somatic mutations in the catalytic domains of the tyrosine kinome are rare in clear cell ECs. We uncovered ten new mutations in TNK2 and DDR1 within serous and endometrioid ECs, thus providing novel insights into the mutation spectrum of each gene in EC

Predisposition to Cancer Caused by Genetic and Functional Defects of Mammalian Atad5

ATAD5, the human ortholog of yeast Elg1, plays a role in PCNA deubiquitination. Since PCNA modification is important to regulate DNA damage bypass, ATAD5 may be important for suppression of genomic instability in mammals in vivo. To test this hypothesis, we generated heterozygous (Atad5+/m) mice that were haploinsuffficient for Atad5. Atad5+/m mice displayed high levels of genomic instability in vivo, and Atad5+/m mouse embryonic fibroblasts (MEFs) exhibited molecular defects in PCNA deubiquitination in response to DNA damage, as well as DNA damage hypersensitivity and high levels of genomic instability, apoptosis, and aneuploidy. Importantly, 90% of haploinsufficient Atad5+/m mice developed tumors, including sarcomas, carcinomas, and adenocarcinomas, between 11 and 20 months of age. High levels of genomic alterations were evident in tumors that arose in the Atad5+/m mice. Consistent with a role for Atad5 in suppressing tumorigenesis, we also identified somatic mutations of ATAD5 in 4.6% of sporadic human endometrial tumors, including two nonsense mutations that resulted in loss of proper ATAD5 function. Taken together, our findings indicate that loss-of-function mutations in mammalian Atad5 are sufficient to cause genomic instability and tumorigenesis

Q-Learning-Aided Offloading Strategy in Edge-Assisted Federated Learning over Industrial IoT

Federated learning (FL) is a key solution to realizing a cost-efficient and intelligent Industrial Internet of Things (IIoT). To improve training efficiency and mitigate the straggler effect of FL, this paper investigates an edge-assisted FL framework over an IIoT system by combining it with a mobile edge computing (MEC) technique. In the proposed edge-assisted FL framework, each IIoT device with weak computation capacity can offload partial local data to an edge server with strong computing power for edge training. In order to obtain the optimal offloading strategy, we formulate an FL loss function minimization problem under the latency constraint in the proposed edge-assisted FL framework by optimizing the offloading data size of each device. An optimal offloading strategy is first derived in a perfect channel state information (CSI) scenario. Then, we extend the strategy into an imperfect CSI scenario and accordingly propose a Q-learning-aided offloading strategy. Finally, our simulation results show that our proposed Q-learning-based offloading strategy can improve FL test accuracy by about 4.7% compared to the conventional FL scheme. Furthermore, the proposed Q-learning-based offloading strategy can achieve similar performance to the optimal offloading strategy and always outperforms the conventional FL scheme in different system parameters, which validates the effectiveness of the proposed edge-assisted framework and Q-learning-based offloading strategy

Cracking, Microstructure and Tribological Properties of Laser Formed and Remelted K417G Ni-Based Superalloy

The K417G Ni-based superalloy is widely used in aeroengine turbine blades for its excellent properties. However, the turbine blade root with fir tree geometry experiences early failure frequently, because of the wear problems occurring in the working process. Laser forming repairing (LFR) is a promising technique to repair these damaged blades. Unfortunately, the laser formed Ni-based superalloys with high content of (Al + Ti) have a high cracking sensitivity. In this paper, the crack characterization of the laser forming repaired (LFRed) K417G—the microstructure, microhardness, and tribological properties of the coating before and after laser remelting—is presented. The results show that the microstructure of as-deposited K417G consists of γ phase, γ′ precipitated phase, γ + γ′ eutectic, and carbide. Cracking mechanisms including solidification cracking, liquation cracking, and ductility dip cracking are proposed based on the composition of K417G and processing characteristics to explain the cracking behavior of the K417G superalloy during LFR. After laser remelting, the microstructure of the coating was refined, and the microhardness and tribological properties was improved. Laser remelting can decrease the size of the cracks in the LFRed K417G, but not the number of cracks. Therefore, laser remelting can be applied as an effective method for strengthening coatings and as an auxiliary method for controlling cracking

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

A Systems Genetics Approach Identifies <i>CXCL14</i>, <i>ITGAX</i>, and <i>LPCAT2</i> as Novel Aggressive Prostate Cancer Susceptibility Genes

<div><p>Although prostate cancer typically runs an indolent course, a subset of men develop aggressive, fatal forms of this disease. We hypothesize that germline variation modulates susceptibility to aggressive prostate cancer. The goal of this work is to identify susceptibility genes using the C57BL/6-Tg(TRAMP)8247Ng/J (TRAMP) mouse model of neuroendocrine prostate cancer. Quantitative trait locus (QTL) mapping was performed in transgene-positive (TRAMPxNOD/ShiLtJ) F2 intercross males (n = 228), which facilitated identification of 11 loci associated with aggressive disease development. Microarray data derived from 126 (TRAMPxNOD/ShiLtJ) F2 primary tumors were used to prioritize candidate genes within QTLs, with candidate genes deemed as being high priority when possessing both high levels of expression-trait correlation and a proximal expression QTL. This process enabled the identification of 35 aggressive prostate tumorigenesis candidate genes. The role of these genes in aggressive forms of human prostate cancer was investigated using two concurrent approaches. First, logistic regression analysis in two human prostate gene expression datasets revealed that expression levels of five genes (<i>CXCL14</i>, <i>ITGAX</i>, <i>LPCAT2</i>, <i>RNASEH2A</i>, and <i>ZNF322</i>) were positively correlated with aggressive prostate cancer and two genes (<i>CCL19</i> and <i>HIST1H1A</i>) were protective for aggressive prostate cancer. Higher than average levels of expression of the five genes that were positively correlated with aggressive disease were consistently associated with patient outcome in both human prostate cancer tumor gene expression datasets. Second, three of these five genes (<i>CXCL14</i>, <i>ITGAX</i>, and <i>LPCAT2</i>) harbored polymorphisms associated with aggressive disease development in a human GWAS cohort consisting of 1,172 prostate cancer patients. This study is the first example of using a systems genetics approach to successfully identify novel susceptibility genes for aggressive prostate cancer. Such approaches will facilitate the identification of novel germline factors driving aggressive disease susceptibility and allow for new insights into these deadly forms of prostate cancer.</p></div