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https://www.readbyqxmd.com/read/29228179/a-large-panel-of-drosophila-simulans-reveals-an-abundance-of-common-variants
#1
Sarah A Signor, Felicia N New, Sergey Nuzhdin
The rapidly expanding availability of large NGS datasets provides an opportunity to investigate population genetics at an unprecedented scale. Drosophila simulans is the sister species of the model organism D. melanogaster, and is often presumed to share similar demographic history. However, previous population genetic and ecological work suggest very different signatures of selection and demography. Here we sequence a new panel of 170 inbred genotypes of a North American population of D. simulans, a valuable complement to the DGRP and other D...
December 8, 2017: Genome Biology and Evolution
https://www.readbyqxmd.com/read/29226517/natural-selection-beyond-genes-identification-and-analyses-of-evolutionarily-conserved-elements-in-the-genome-of-the-collared-flycatcher-ficedula-albicollis
#2
Rory J Craig, Alexander Suh, Mi Wang, Hans Ellegren
It is becoming increasingly clear that a significant proportion of the functional sequence within eukaryotic genomes is noncoding. However, since the identification of conserved elements (CEs) has been restricted to a limited number of model organisms, the dynamics and evolutionary character of the genomic landscape of conserved, and hence likely functional, sequence is poorly understood in most species. Moreover, identification and analysis of the full suite of functional sequence is particularly important for the understanding of the genetic basis of trait loci identified in genome scans or quantitative trait locus mapping efforts...
December 11, 2017: Molecular Ecology
https://www.readbyqxmd.com/read/29224928/association-of-rare-predicted-loss-of-function-variants-in-cellular-pathways-with-sub-phenotypes-in-age-related-macular-degeneration
#3
Alexandra Pietraszkiewicz, Freekje van Asten, Alan Kwong, Rinki Ratnapriya, Goncalo Abecasis, Anand Swaroop, Emily Y Chew
PURPOSE: To investigate the association of rare predicted loss-of-function (pLoF) variants within age-related macular degeneration (AMD) risk loci and AMD sub-phenotypes. DESIGN: Case-control study. PARTICIPANTS: Participants of AREDS, AREDS2, and Michigan Genomics Initiative. METHODS: Whole genome sequencing data were analyzed for rare pLoF variants (frequency <0.1%) in the regions of previously identified 52 independent risk variants known to be associated with AMD...
December 7, 2017: Ophthalmology
https://www.readbyqxmd.com/read/29224359/a-reduced-transcriptome-approach-to-assess-environmental-toxicants-using-zebrafish-embryo-test
#4
Pingping Wang, Pu Xia, Jianghua Yang, Zhihao Wang, Ying Peng, Wei Shi, Daniel L Villeneuve, Hongxia Yu, Xiaowei Zhang
Omics approaches can monitor responses and alterations of biological pathways at genome-scale, which are useful to predict potential adverse effects by environmental toxicants. However, high throughput application of transcriptomics in chemical assessment is limited due to the high cost and lack of "standardized" toxicogenomic methods. Here, a reduced zebrafish transcriptome (RZT) approach was developed to represent the whole transcriptome and to profile bioactivity of chemical and environmental mixtures in zebrafish embryo...
December 11, 2017: Environmental Science & Technology
https://www.readbyqxmd.com/read/29222764/optimization-of-multi-omic-genome-scale-models-methodologies-hands-on-tutorial-and-perspectives
#5
Supreeta Vijayakumar, Max Conway, Pietro Lió, Claudio Angione
Genome-scale metabolic models are valuable tools for assessing the metabolic potential of living organisms. Being downstream of gene expression, metabolism is increasingly being used as an indicator of the phenotypic outcome for drugs and therapies. We here present a review of the principal methods used for constraint-based modelling in systems biology, and explore how the integration of multi-omic data can be used to improve phenotypic predictions of genome-scale metabolic models. We believe that the large-scale comparison of the metabolic response of an organism to different environmental conditions will be an important challenge for genome-scale models...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29222763/designing-optimized-production-hosts-by-metabolic-modeling
#6
Christian Jungreuthmayer, Matthias P Gerstl, David A Peña Navarro, Michael Hanscho, David E Ruckerbauer, Jürgen Zanghellini
Many of the complex and expensive production steps in the chemical industry are readily available in living cells. In order to overcome the metabolic limits of these cells, the optimal genetic intervention strategies can be computed by the use of metabolic modeling. Elementary flux mode analysis (EFMA) is an ideal tool for this task, as it does not require defining a cellular objective function. We present two EFMA-based methods to optimize production hosts: (1) the standard approach that can only be used for small and medium scale metabolic networks and (2) the advanced dual system approach that can be utilized to directly compute intervention strategies in a genome-scale metabolic model...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29222761/coupling-fluxes-enzymes-and-regulation-in-genome-scale-metabolic-models
#7
Paul A Jensen
Genome-scale models have expanded beyond their metabolic origins. Multiple modeling frameworks are required to combine metabolism with enzymatic networks, transcription, translation, and regulation. Mathematical programming offers a powerful set of tools for tackling these "multi-modality" models, although special attention must be paid to the connections between modeling types. This chapter reviews common methods for combining metabolic and discrete logical models into a single mathematical programming framework...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29222760/computational-prediction-of-synthetic-lethals-in-genome-scale-metabolic-models-using-fast-sl
#8
Karthik Raman, Aditya Pratapa, Omkar Mohite, Shankar Balachandran
In this chapter, we describe Fast-SL, an in silico approach to predict synthetic lethals in genome-scale metabolic models. Synthetic lethals are sets of genes or reactions where only the simultaneous removal of all genes or reactions in the set abolishes growth of an organism. In silico approaches to predict synthetic lethals are based on Flux Balance Analysis (FBA), a popular constraint-based analysis method based on linear programming. FBA has been shown to accurately predict the viability of various genome-scale metabolic models...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29222755/integrated-host-pathogen-metabolic-reconstructions
#9
Anu Raghunathan, Neema Jamshidi
The science and art of Genome scale metabolic network reconstructions have been explicitly documented in the literature for organisms across all the three kingdoms of life. Constraints-based models derived from such reconstructions have been used to assess metabolic phenotypes of their complex connections to genotype accurately. The problem of infectious disease is complex due to the multifactorial response of the host to the pathogen. Systems biology approaches and modeling allow one to study, understand, and predict emergent properties of such complex responses...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29222754/template-assisted-metabolic-reconstruction-and-assembly-of-hybrid-bacterial-models
#10
Tiziano Vignolini, Alessio Mengoni, Marco Fondi
Intraspecific genomic exchanges happen frequently between bacteria living in the same natural environment and can also be performed artificially in the laboratory for basic research or genetic/metabolic engineering purposes. In silico metabolic reconstruction and simulation of the metabolism of the hybrid strains that result from these processes can be used to predict the phenotypic outcome of such genomic rearrangements; this can be especially helpful as a designing tool in the purview of synthetic biology...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29222753/integration-of-comparative-genomics-with-genome-scale-metabolic-modeling-to-investigate-strain-specific-phenotypical-differences
#11
Jonathan Monk, Emanuele Bosi
Genome-scale metabolic reconstructions are powerful resources that allow translation biological knowledge and genomic information to phenotypical predictions using a number of constraint-based methods. This approach has been applied in recent years to gain deep insights into the cellular phenotype role of the genes at a systems-level, driving the design of targeted experiments and paving the way for knowledge-based synthetic biology.The identification of genetic determinants underlying the variability at the phenotypical level is crucial to understand the evolutionary trajectories of a bacterial species...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29222752/using-psamm-for-the-curation-and-analysis-of-genome-scale-metabolic-models
#12
Keith Dufault-Thompson, Jon Lund Steffensen, Ying Zhang
PSAMM is an open source software package that supports the iterative curation and analysis of genome-scale models (GEMs). It aims to integrate the annotation and consistency checking of metabolic models with the simulation of metabolic fluxes. The model representation in PSAMM is compatible with version tracking systems like Git, which allows for full documentation of model file changes and enables collaborative curations of large, complex models. This chapter provides a protocol for using PSAMM functions and a detailed description of the various aspects in setting up and using PSAMM for the simulation and analysis of metabolic models...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29222751/reconstruction-and-analysis-of-central-metabolism-in-microbes
#13
Janaka N Edirisinghe, José P Faria, Nomi L Harris, Benjamin H Allen, Christopher S Henry
Genome-scale metabolic models (GEMs) generated from automated reconstruction pipelines often lack accuracy due to the need for extensive gapfilling and the inference of periphery metabolic pathways based on lower-confidence annotations. The central carbon pathways and electron transport chains are among the most well-understood regions of microbial metabolism, and these pathways contribute significantly toward defining cellular behavior and growth conditions. Thus, it is often useful to construct a simplified core metabolic model (CMM) that is comprised of only the high-confidence central pathways...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29222749/the-mongoose-rational-arithmetic-toolbox
#14
Christopher Le, Leonid Chindelevitch
The modeling of metabolic networks has seen a rapid expansion following the complete sequencing of thousands of genomes. The constraint-based modeling framework has emerged as one of the most popular approaches to reconstructing and analyzing genome-scale metabolic models. Its main assumption is that of a quasi-steady-state, requiring that the production of each internal metabolite be balanced by its consumption. However, due to the multiscale nature of the models, the large number of reactions and metabolites, and the use of floating-point arithmetic for the stoichiometric coefficients, ensuring that this assumption holds can be challenging...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29222747/reconstructing-high-quality-large-scale-metabolic-models-with-merlin
#15
Oscar Dias, Miguel Rocha, Eugénio Campos Ferreira, Isabel Rocha
Here, the basic principles of reconstructing genome-scale metabolic models with merlin are described. This tool covers the basic stages of this process, providing several tools that allow assembling models, using the sequenced genome as a starting point. merlin has two main modules, separating the process of annotating (enzymes, transporters, and compartments) on the genome from the process of model assembly, though information from the former is integrated in the latter after curation. Moreover, merlin provides several tools to curate the model, including tools for generating reactions' gene rules and placeholder entities for biomass precursors, such as proteins (e-protein) or nucleotides (e-DNA and e-RNA) among others...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29222445/model-based-genome-wide-determination-of-rna-chain-elongation-rates-in-escherichia-coli
#16
Peter Großmann, Anja Lück, Christoph Kaleta
Dynamics in the process of transcription are often simplified, yet they play an important role in transcript folding, translation into functional protein and DNA supercoiling. While the modulation of the speed of transcription of individual genes and its role in regulation and proper protein folding has been analyzed in depth, the functional relevance of differences in transcription speeds as well as the factors influencing it have not yet been determined on a genome-wide scale. Here we determined transcription speeds for the majority of E...
December 8, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29220677/a-powerful-approach-to-estimating-annotation-stratified-genetic-covariance-via-gwas-summary-statistics
#17
Qiongshi Lu, Boyang Li, Derek Ou, Margret Erlendsdottir, Ryan L Powles, Tony Jiang, Yiming Hu, David Chang, Chentian Jin, Wei Dai, Qidu He, Zefeng Liu, Shubhabrata Mukherjee, Paul K Crane, Hongyu Zhao
Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits' genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics...
December 7, 2017: American Journal of Human Genetics
https://www.readbyqxmd.com/read/29219068/predicting-enhancers-with-deep-convolutional-neural-networks
#18
Xu Min, Wanwen Zeng, Shengquan Chen, Ning Chen, Ting Chen, Rui Jiang
BACKGROUND: With the rapid development of deep sequencing techniques in the recent years, enhancers have been systematically identified in such projects as FANTOM and ENCODE, forming genome-wide landscapes in a series of human cell lines. Nevertheless, experimental approaches are still costly and time consuming for large scale identification of enhancers across a variety of tissues under different disease status, making computational identification of enhancers indispensable. RESULTS: To facilitate the identification of enhancers, we propose a computational framework, named DeepEnhancer, to distinguish enhancers from background genomic sequences...
December 1, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/29218911/convergent-downstream-candidate-mechanisms-of-independent-intergenic-polymorphisms-between-co-classified-diseases-implicate-epistasis-among-noncoding-elements
#19
Jiali Han, Jianrong Li, Ikbel Achour, Lorenzo Pesce, Ian Foster, Haiquan Li, Yves A Lussier
Eighty percent of DNA outside protein coding regions was shown biochemically functional by the ENCODE project, enabling studies of their interactions. Studies have since explored how convergent downstream mechanisms arise from independent genetic risks of one complex disease. However, the cross-talk and epistasis between intergenic risks associated with distinct complex diseases have not been comprehensively characterized. Our recent integrative genomic analysis unveiled downstream biological effectors of disease-specific polymorphisms buried in intergenic regions, and we then validated their genetic synergy and antagonism in distinct GWAS...
2018: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/29218909/reading-between-the-genes-computational-models-to-discover-function-from-noncoding-dna
#20
Yves A Lussier, Joanne Berghout, Francesca Vitali, Kenneth S Ramos, Maricel Kann, Jason H Moore
Noncoding DNA - once called "junk" has revealed itself to be full of function. Technology development has allowed researchers to gather genome-scale data pointing towards complex regulatory regions, expression and function of noncoding RNA genes, and conserved elements. Variation in these regions has been tied to variation in biological function and human disease. This PSB session tackles the problem of handling, analyzing and interpreting the data relating to variation in and interactions between noncoding regions through computational biology...
2018: Pacific Symposium on Biocomputing
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