scholarly journals Large-scale gene losses underlie the genome evolution of parasitic plant Cuscuta australis

2018 ◽  
Author(s):  
Guiling Sun ◽  
Yuxing Xu ◽  
Hui Liu ◽  
Ting Sun ◽  
Jingxiong Zhang ◽  
...  
Keyword(s):  
Large Scale ◽  
Expression Patterns ◽  
Morning Glory ◽  
Protein Coding ◽  
Accelerated Evolution ◽  
Wide Range ◽  
Parasitic Lifestyle ◽  
Evo Devo ◽  
Globally Distributed ◽  
Genome Triplication

Dodders (Cuscuta spp., Convolvulaceae) are globally distributed root- and leafless parasitic plants that parasitize a wide range of hosts. The physiology, ecology, and evolution of these obligate parasites are still poorly understood. A high-quality reference genome (size 266.74 Mb and contig N50 of 3.63 Mb) of Cuscuta australis was assembled. Our analyses reveal that Cuscuta experienced accelerated evolution, and Cuscuta and the convolvulaceous morning glory (Ipomoea) shared a common whole-genome triplication event before their divergence. Importantly, C. australis genome harbors only 19805 protein-coding genes, and 11.7% of the conserved orthologs in autotrophic plants are lost in C. australis. Many of these gene loss events likely result from the plant’s parasitic lifestyle and large changes in its body plan. Moreover, comparison of the gene expression patterns in Cuscuta prehaustoria/haustoria and various tissues of closely related autotrophic plants suggests that Cuscuta haustorium genes largely evolved from roots. The C. australis genome provides important resources for studying the evolution of parasitism, regressive evolution, and evo-devo in plant parasites.

scholarly journals Characterization and identification of long non-coding RNAs based on feature relationship

2018 ◽  
Author(s):  
Guangyu Wang ◽  
Hongyan Yin ◽  
Boyang Li ◽  
Chunlei Yu ◽  
Fan Wang ◽  
...  
Keyword(s):  
Prior Knowledge ◽  
Large Scale ◽  
Gc Content ◽  
Training Data ◽  
Significant Advance ◽  
Protein Coding ◽  
Reading Frame ◽  
Wide Range ◽  
Non Coding Rnas ◽  
Computational Identification

ABSTRACTThe significance of long non-coding RNAs (lncRNAs) in many biological processes and diseases has gained intense interests over the past several years. However, computational identification of lncRNAs in a wide range of species remains challenging; it requires prior knowledge of well-established sequences and annotations or species-specific training data, but the reality is that only a limited number of species have high-quality sequences and annotations. Here we first characterize lncRNAs by contrast to protein-coding RNAs based on feature relationship and find that the feature relationship between ORF (open reading frame) length and GC content presents universally substantial divergence in lncRNAs and protein-coding RNAs, as observed in a broad variety of species. Based on the feature relationship, accordingly, we further present LGC, a novel algorithm for identifying lncRNAs that is able to accurately distinguish lncRNAs from protein-coding RNAs in a cross-species manner without any prior knowledge. As validated on large-scale empirical datasets, comparative results show that LGC outperforms existing algorithms by achieving higher accuracy, well-balanced sensitivity and specificity, and is robustly effective (>90% accuracy) in discriminating lncRNAs from protein-coding RNAs across diverse species that range from plants to mammals. To our knowledge, this study, for the first time, differentially characterizes lncRNAs and protein-coding RNAs based on feature relationship, which is further applied in computational identification of lncRNAs. Taken together, our study represents a significant advance in characterization and identification of lncRNAs and LGC thus bears broad potential utility for computational analysis of lncRNAs in a wide range of species.

scholarly journals MetaMap: An atlas of metatranscriptomic reads in human disease-related RNA-seq data

2018 ◽  
Author(s):  
LM Simon ◽  
S Karg ◽  
AJ Westermann ◽  
M Engel ◽  
AHA Elbehery ◽  
...  
Keyword(s):  
High Performance Computing ◽  
Human Disease ◽  
High Performance ◽  
Large Scale ◽  
Expression Patterns ◽  
Rna Seq ◽  
Wide Range ◽  
Eukaryotic Gene ◽  
Public Repositories ◽  
Performance Computing

AbstractBackgroundWith the advent of the age of big data in bioinformatics, large volumes of data and high performance computing power enable researchers to perform re-analyses of publicly available datasets at an unprecedented scale. Ever more studies imply the microbiome in both normal human physiology and a wide range of diseases. RNA sequencing technology (RNA-seq) is commonly used to infer global eukaryotic gene expression patterns under defined conditions, including human disease-related contexts, but its generic nature also enables the detection of microbial and viral transcripts.FindingsWe developed a bioinformatic pipeline to screen existing human RNA-seq datasets for the presence of microbial and viral reads by re-inspecting the non-human-mapping read fraction. We validated this approach by recapitulating outcomes from 6 independent controlled infection experiments of cell line models and comparison with an alternative metatranscriptomic mapping strategy. We then applied the pipeline to close to 150 terabytes of publicly available raw RNA-seq data from >17,000 samples from >400 studies relevant to human disease using state-of-the-art high performance computing systems. The resulting data of this large-scale re-analysis are made available in the presented MetaMap resource.ConclusionsOur results demonstrate that common human RNA-seq data, including those archived in public repositories, might contain valuable information to correlate microbial and viral detection patterns with diverse diseases. The presented MetaMap database thus provides a rich resource for hypothesis generation towards the role of the microbiome in human disease.

scholarly journals Characterization and identification of long non-coding RNAs based on feature relationship

2019 ◽  
Vol 35 (17) ◽  
pp. 2949-2956 ◽  
Author(s):  
Guangyu Wang ◽  
Hongyan Yin ◽  
Boyang Li ◽  
Chunlei Yu ◽  
Fan Wang ◽  
...  
Keyword(s):  
Prior Knowledge ◽  
Large Scale ◽  
Gc Content ◽  
Training Data ◽  
Supplementary Information ◽  
Significant Advance ◽  
Protein Coding ◽  
Wide Range ◽  
Non Coding Rnas ◽  
Computational Identification

Abstract Motivation The significance of long non-coding RNAs (lncRNAs) in many biological processes and diseases has gained intense interests over the past several years. However, computational identification of lncRNAs in a wide range of species remains challenging; it requires prior knowledge of well-established sequences and annotations or species-specific training data, but the reality is that only a limited number of species have high-quality sequences and annotations. Results Here we first characterize lncRNAs in contrast to protein-coding RNAs based on feature relationship and find that the feature relationship between open reading frame length and guanine-cytosine (GC) content presents universally substantial divergence in lncRNAs and protein-coding RNAs, as observed in a broad variety of species. Based on the feature relationship, accordingly, we further present LGC, a novel algorithm for identifying lncRNAs that is able to accurately distinguish lncRNAs from protein-coding RNAs in a cross-species manner without any prior knowledge. As validated on large-scale empirical datasets, comparative results show that LGC outperforms existing algorithms by achieving higher accuracy, well-balanced sensitivity and specificity, and is robustly effective (>90% accuracy) in discriminating lncRNAs from protein-coding RNAs across diverse species that range from plants to mammals. To our knowledge, this study, for the first time, differentially characterizes lncRNAs and protein-coding RNAs based on feature relationship, which is further applied in computational identification of lncRNAs. Taken together, our study represents a significant advance in characterization and identification of lncRNAs and LGC thus bears broad potential utility for computational analysis of lncRNAs in a wide range of species. Availability and implementation LGC web server is publicly available at http://bigd.big.ac.cn/lgc/calculator. The scripts and data can be downloaded at http://bigd.big.ac.cn/biocode/tools/BT000004. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Evaluation of animal model congruence to human depression based on large-scale gene expression patterns of the CNS

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Stephen C. Gammie
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Animal Models ◽  
Large Scale ◽  
Mitochondrial Gene ◽  
Expression Patterns ◽  
Conditional Knockout ◽  
Gene Expression Patterns ◽  
Male And Female ◽  
Wide Range

AbstractDepression is a complex mental health disorder that is difficult to study. A wide range of animal models exist and for many of these data on large-scale gene expression patterns in the CNS are available. The goal of this study was to evaluate how well animal models match human depression by evaluating congruence and discordance of large-scale gene expression patterns in the CNS between almost 300 animal models and a portrait of human depression created from male and female datasets. Multiple approaches were used, including a hypergeometric based scoring system that rewards common gene expression patterns (e.g., up-up or down-down in both model and human depression), but penalizes opposing gene expression patterns. RRHO heat maps, Uniform Manifold Approximation Plot (UMAP), and machine learning were used to evaluate matching of models to depression. The top ranked model was a histone deacetylase (HDAC2) conditional knockout in forebrain neurons. Also highly ranked were various models for Alzheimer’s, including APPsa knock-in (2nd overall), APP knockout, and an APP/PS1 humanized double mutant. Other top models were the mitochondrial gene HTRA2 knockout (that is lethal in adulthood), a modified acetylcholinesterase, a Huntington’s disease model, and the CRTC1 knockout. Over 30 stress related models were evaluated and while some matched highly with depression, others did not. In most of the top models, a consistent dysregulation of MAP kinase pathway was identified and the genes NR4A1, BDNF, ARC, EGR2, and PDE7B were consistently downregulated as in humans with depression. Separate male and female portraits of depression were also evaluated to identify potential sex specific depression matches with models. Individual human depression datasets were also evaluated to allow for comparisons across the same brain regions. Heatmap, UMAP, and machine learning results supported the hypergeometric ranking findings. Together, this study provides new insights into how large-scale gene expression patterns may be similarly dysregulated in some animals models and humans with depression that may provide new avenues for understanding and treating depression.

Electron microscopy study of reactively sputter-deposited Ti/N films on silicon

1992 ◽  
Vol 50 (2) ◽  
pp. 1362-1363
Author(s):  
V. C. Kannan ◽  
A. K. Singh ◽  
R. B. Irwin ◽  
S. Chittipeddi ◽  
F. D. Nkansah ◽  
...  
Keyword(s):  
Integrated Circuits ◽  
Large Scale ◽  
Hexagonal Phase ◽  
Microscopy Study ◽  
Electron Microscopy Study ◽  
Process Conditions ◽  
Tin Films ◽  
Wide Range ◽  
Fcc Phase ◽  
Circuits Vlsi

Titanium nitride (TiN) films have historically been used as diffusion barrier between silicon and aluminum, as an adhesion layer for tungsten deposition and as an interconnect material etc. Recently, the role of TiN films as contact barriers in very large scale silicon integrated circuits (VLSI) has been extensively studied. TiN films have resistivities on the order of 20μ Ω-cm which is much lower than that of titanium (nearly 66μ Ω-cm). Deposited TiN films show resistivities which vary from 20 to 100μ Ω-cm depending upon the type of deposition and process conditions. TiNx is known to have a NaCl type crystal structure for a wide range of compositions. Change in color from metallic luster to gold reflects the stabilization of the TiNx (FCC) phase over the close packed Ti(N) hexagonal phase. It was found that TiN (1:1) ideal composition with the FCC (NaCl-type) structure gives the best electrical property.

THE SOME QUESTIONS OF AUTONOMOUS MOTION AND MANAGEMENT OF LAND-MOBILE ROBOTIC COMPLEXES FOR UKRAINIAN GROUND FORCESE

2019 ◽  
pp. 53-58
Author(s):  
О. Кravchuk ◽  
V. Symonenkov ◽  
I. Symonenkova ◽  
O. Hryhorev
Keyword(s):  
Large Scale ◽  
Armed Forces ◽  
Distributed Information ◽  
Wide Range ◽  
Highly Effective ◽  
Information Management Systems ◽  
Robotic Devices ◽  
Principles And Standards ◽  
And Control ◽  
The Eu

Today, more than forty countries of the world are engaged in the development of military-purpose robots. A number of unique mobile robots with a wide range of capabilities are already being used by combat and intelligence units of the Armed forces of the developed world countries to conduct battlefield intelligence and support tactical groups. At present, the issue of using the latest information technology in the field of military robotics is thoroughly investigated, and the creation of highly effective information management systems in the land-mobile robotic complexes has acquired a new phase associated with the use of distributed information and sensory systems and consists in the transition from application of separate sensors and devices to the construction of modular information subsystems, which provide the availability of various data sources and complex methods of information processing. The purpose of the article is to investigate the ways to increase the autonomy of the land-mobile robotic complexes using in a non-deterministic conditions of modern combat. Relevance of researches is connected with the necessity of creation of highly effective information and control systems in the perspective robotic means for the needs of Land Forces of Ukraine. The development of the Armed Forces of Ukraine management system based on the criteria adopted by the EU and NATO member states is one of the main directions of increasing the effectiveness of the use of forces (forces), which involves achieving the principles and standards necessary for Ukraine to become a member of the EU and NATO. The inherent features of achieving these criteria will be the transition to a reduction of tasks of the combined-arms units and the large-scale use of high-precision weapons and land remote-controlled robotic devices. According to the views of the leading specialists in the field of robotics, the automation of information subsystems and components of the land-mobile robotic complexes can increase safety, reliability, error-tolerance and the effectiveness of the use of robotic means by standardizing the necessary actions with minimal human intervention, that is, a significant increase in the autonomy of the land-mobile robotic complexes for the needs of Land Forces of Ukraine.

Stirring and aeration system for the upgrading of small waste water treatment plants

1994 ◽  
Vol 29 (12) ◽  
pp. 149-156 ◽  
Author(s):  
Marcus Höfken ◽  
Katharina Zähringer ◽  
Franz Bischof
Keyword(s):  
Waste Water ◽  
Water Treatment ◽  
Large Scale ◽  
Waste Water Treatment ◽  
Water Treatment Plants ◽  
Waste Water Treatment Plants ◽  
Basic Fluid ◽  
Aeration System ◽  
Technical Realization ◽  
Wide Range

A novel agitating system has been developed which allows for individual or combined operation of stirring and aeration processes. Basic fluid mechanical considerations led to the innovative hyperboloid design of the stirrer body, which ensures high efficiencies in the stirring and the aeration mode, gentle circulation with low shear forces, excellent controllability, and a wide range of applications. This paper presents the basic considerations which led to the operating principle, the technical realization of the system and experimental results in a large-scale plant. The characteristics of the system and the differences to other stirring and aeration systems are illustrated. Details of the technical realization are shown, which conform to the specific demands of applications in the biological treatment of waste water. Special regard is given to applications in the upgrading of small compact waste water treatment plants.

Thin structure of heterogeneous and multiphase fluid flows

2012 ◽  
Vol 9 (1) ◽  
pp. 175-180
Author(s):  
Yu.D. Chashechkin
Keyword(s):  
Large Scale ◽  
Fundamental System ◽  
Fluid Flows ◽  
Regular Solutions ◽  
Flow Models ◽  
Group Methods ◽  
Wide Range ◽  
Thin Structure ◽  
Multiphase Fluid ◽  
Complete Solutions

According to the results of visualization of streams, the existence of structures in a wide range of scales is noted: from galactic to micron. The use of a fundamental system of equations is substantiated based on the results of comparing symmetries of various flow models with the usage of theoretical group methods. Complete solutions of the system are found by the methods of the singular perturbations theory with a condition of compatibility, which determines the characteristic equation. A comparison of complete solutions with experimental data shows that regular solutions characterize large-scale components of the flow, a rich family of singular solutions describes formation of the thin media structure. Examples of calculations and observations of stratified, rotating and multiphase media are given. The requirements for the technique of an adequate experiment are discussed.

Integrative Data Analysis from a Unifying Research Synthesis Perspective

2018 ◽  
Author(s):  
Eun-Young Mun ◽  
Anne E. Ray
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Research Synthesis ◽  
Alcohol Intervention ◽  
Data Set ◽  
Integrative Data Analysis ◽  
Level Data ◽  
Model Complex ◽  
Wide Range ◽  
Individual Participant

Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors’ experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.

Quantum Optomechanics and Nanomechanics

2020 ◽  
Keyword(s):  
Gravitational Wave ◽  
Summer School ◽  
Large Scale ◽  
Quantum Noise ◽  
Foundations Of Quantum Mechanics ◽  
Wide Range ◽  
Measurement Laser ◽  
Quantum Limits ◽  
Quantum Optomechanics ◽  
Quantum Ground State

The Les Houches Summer School 2015 covered the emerging fields of cavity optomechanics and quantum nanomechanics. Optomechanics is flourishing and its concepts and techniques are now applied to a wide range of topics. Modern quantum optomechanics was born in the late 70s in the framework of gravitational wave interferometry, initially focusing on the quantum limits of displacement measurements. Carlton Caves, Vladimir Braginsky, and others realized that the sensitivity of the anticipated large-scale gravitational-wave interferometers (GWI) was fundamentally limited by the quantum fluctuations of the measurement laser beam. After tremendous experimental progress, the sensitivity of the upcoming next generation of GWI will effectively be limited by quantum noise. In this way, quantum-optomechanical effects will directly affect the operation of what is arguably the world’s most impressive precision experiment. However, optomechanics has also gained a life of its own with a focus on the quantum aspects of moving mirrors. Laser light can be used to cool mechanical resonators well below the temperature of their environment. After proof-of-principle demonstrations of this cooling in 2006, a number of systems were used as the field gradually merged with its condensed matter cousin (nanomechanical systems) to try to reach the mechanical quantum ground state, eventually demonstrated in 2010 by pure cryogenic techniques and a year later by a combination of cryogenic and radiation-pressure cooling. The book covers all aspects—historical, theoretical, experimental—of the field, with its applications to quantum measurement, foundations of quantum mechanics and quantum information. Essential reading for any researcher in the field.

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