Author: Sizhe Qiu
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
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Book Description
The transcriptional regulatory network (TRN) of E. coli MG1655 contains thousands of regulatory interactions between transcription factors, sigma factors and promoter sequences of genes. The membership of a regulon, in other words whether a gene is regulated by a transcription factor, has a basis in the gene's promoter. To determine the TRN, there are two primary families of methods: bottom-up identification of binding sites via methods such as ChIP-seq experiments, and top-down inference of the TRN via expression analysis methods such as independent component analysis (ICA). In this work, the promoter sequence of each gene was utilized to predict regulons with machine learning. Certain promoter features, such as TF binding site motif scores, DNA shape features, and sigma factor-related features were found to be essential to predict whether a gene is regulated by particular transcription factors. ICA and ChIP TRNs were compared to investigate factors underlying their difference, and two case studies were carried out. An FNR case study showed that ICA regulons fractionate a large ChIP regulon into several regulation types. An ArcA case study demonstrated that the ICA TRN captures diversity in binding sites' architecture. In general, through comparison, ICA TRN extracts genes of strong regulation activity from ChIP TRN. We then expanded this analysis to understand differences in the regulons of multiple strains of E. coli. A pan-regulon of Fur was reconstructed with unique, accessory and core regulons annotated. We found that genes in the core regulon have stronger regulation activity than genes in the unique regulon. Additionally, it was also found that the motif score and helix twist of DNA sequence were both significant indicators of Fur ChIP-exo peak heights, represented by S/N ratios. This study was a meaningful application of machine learning on biological problems that probed biophysical factors underlying omics data, giving directions for the genome design in synthetic biology aiming to control the phenotype by TRN tuning.
Author:
Publisher:
ISBN: 9780815332183
Category : Cells
Languages : en
Pages : 0
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Author: Donald L. Riddle
Publisher: Firefly Books
ISBN: 9780879695323
Category : Medical
Languages : en
Pages : 1252
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Book Description
Defines the current status of research in the genetics, anatomy, and development of the nematode C. elegans, providing a detailed molecular explanation of how development is regulated and how the nervous system specifies varied aspects of behavior. Contains sections on the genome, development, neural networks and behavior, and life history and evolution. Appendices offer genetic nomenclature, a list of laboratory strain and allele designations, skeleton genetic maps, a list of characterized genes, a table of neurotransmitter assignments for specific neurons, and information on codon usage. Includes bandw photos. For researchers in worm studies, as well as the wider community of researchers in cell and molecular biology. Annotation copyrighted by Book News, Inc., Portland, OR
Author: Amitabha Chattopadhyay
Publisher: CRC Press
ISBN: 1420005758
Category : Medical
Languages : en
Pages : 230
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Book Description
A number of developments spanning a multitude of techniques makes this an exciting time for research in serotonin receptors. A comprehensive review of the subject from a multidisciplinary perspective, Serotonin Receptors in Neurobiology is among the first books to include information on serotonin receptor knockout studies. With contributions from l
Author: Altuna Akalin
Publisher: CRC Press
ISBN: 1498781861
Category : Mathematics
Languages : en
Pages : 463
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Book Description
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
Author: Isla P. Garraway
Publisher:
ISBN:
Category :
Languages : en
Pages : 242
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Book Description
Author: Jane Marie Landolin
Publisher:
ISBN:
Category :
Languages : en
Pages : 186
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Book Description
Abstract: The human genome contains approximately three billion bases that instruct cells to produce proteins. Varying levels of proteins inside of cells affect the function of tissues and organs, and eventually influence the health and behavior of individuals. One of the first steps in this chain of events happens at the molecular level, when DNA is transcribed into RNA. Promoters contain the necessary and sufficient information for cells to initiate transcription. Interspersed along promoters are 6 to 10 base sequence motifs that are bound by transcription factors (TFs), which activate or repress transcription of downstream genes. Epigenetic marks such as CpG methylation and modified histones can also affect transcription by interacting with TFs. As the sequence of the Human genome is now known, and experimental techniques to map epigenetic marks genome-wide are now being attempted, we have an unprecedented opportunity to study of transcription regulation with both breadth and depth. In this dissertation, I present several studies examining regulatory signals from DNA sequence as well as epigenetic marks. The first study identifies TFs and modified histones that are important for regulating bidirectional promoters in the human genome. The second study models tissue-specific transcription regulation using TF sequence motifs and CpG methylation. Building upon the biological principles discovered in the first two studies, the third study computationally predicts TF binding footprints, which are then tested experimentally by mutagenesis. GA-binding protein (GABP) is an important TF identified in all three studies. The analysis presented in this dissertation shows that GABP is a major regulator of bidirectional promoters, and activates genes that are ubiquitously transcribed. The motif for GABP is a good predictor of in vivo binding, and mutagenesis confirms that our TF footprint predictions are indeed functional, with average 3-fold knock down of promoter activity compared to wild-type. The analysis was possible because DNA sequence signals were decoupled from epigenetic marks using a transient transfection promoter activity assay system. This work demonstrates the importance of computation in analyzing biological data from different types of high-throughput experiments, and provides the foundation for a single-base-resolution map of TF binding footprints in the Human genome.
Author: Timothy R. Hughes
Publisher: Springer Science & Business Media
ISBN: 904819069X
Category : Medical
Languages : en
Pages : 310
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Book Description
Transcription factors are the molecules that the cell uses to interpret the genome: they possess sequence-specific DNA-binding activity, and either directly or indirectly influence the transcription of genes. In aggregate, transcription factors control gene expression and genome organization, and play a pivotal role in many aspects of physiology and evolution. This book provides a reference for major aspects of transcription factor function, encompassing a general catalogue of known transcription factor classes, origins and evolution of specific transcription factor types, methods for studying transcription factor binding sites in vitro, in vivo, and in silico, and mechanisms of interaction with chromatin and RNA polymerase.
Author: Nathaniel Dixon Tippens
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Gene regulation is the central process that translates genetic code into complex cellular responses. However, we lack a full and quantitative understanding of the molecular basis for information integration across genomic space and time, especially in human genetics and disease. RNA Polymerase II (Pol2) has many features of a key signal integration complex: its regulation is highly conserved across most eukaryotes, it occupies diverse types of genomic regulatory elements, and it exhibits multi-state regulation and behaviors. It engages and transcribes not only gene promoters but also distal enhancers, suggesting possible roles beyond messenger RNA (mRNA) production. Pol2 progresses through unbound, initiating, paused, elongating, and terminating stages during the transcription cycle, and is thus uniquely situated to integrate information across diverse regulatory sites and states, as well as across relatively long molecular timescales and distances. To better understand and compare Pol2 behavior at regulatory elements, we sequenced nascent RNAs at single-molecule resolution to identify initiation, capping, and pause sites genome-wide. We find distinct sequence-specified pause classes with different capping profiles. Transcription start sites (TSSs) are predominantly found in dense clusters (transcription initiation domains, or TIDs) that show remarkably little change upon heat shock, demonstrating how large regulatory changes can occur by modulating pause release from pre-established TSS architectures. Within TIDs, TSSs appear to communicate through arrays of phased nucleosomes. These TSS ensembles define promoters and enhancers, unravel complex histone modification patterns, and indicate Pol2 may integrate information between regulatory elements. To explore the function of Pol2 at distal enhancers, we performed massively parallel reporter assays and found that gene distal TSSs are robust predictors of enhancer activity with higher resolution and specificity than histone modifications. We show that enhancer units are precisely delineated by TSSs, validate that these boundaries are sufficient to capture full activity, and confirm that core promoter sequences are required for enhancer function. Consistent with prior studies, most human promoters do not show distal enhancer activity in episomal assays, suggesting important functional differences between promoters and enhancers despite similar architectures. Finally, we dissect TIDs and find that the strongest unit within the TID is the best predictor of episomal enhancer activity. Together, these results define fundamental regulatory units of promoters and enhancers, and their behavior within TIDs. Together these data suggest Pol2 function may distinguish enhancers from promoters. Recent experiments in Drosophila demonstrate that enhancers exhibit much shorter Pol2 pausing than promoters, which could explain the lower H3K4me3 levels at enhancers. In this model, H3K4me3 levels are determined by SET1 binding to the paused Pol2 complex and would thus be sensitive to Pol2 pause behavior. For example, promoters' GC-rich sequences may stabilize Pol2 pause complexes for longer times, resulting in H3K4me3 accumulation. Positive feedback between H3K4me3 and the TAF3 subunit of the pre-initiation complex further exaggerates this effect by driving local Pol2 initiation nearby, resulting in the larger TIDs observed at promoters compared with enhancers. Finally, stable Pol2 pausing at promoters provides the time required to find and receive activation signals from enhancers. Some promoters may bypass this long pause checkpoint via frequent or direct recruitment of transcriptional activators, at the cost of reduced enhancer responsiveness. This framework situates Pol2 as a key signal processing complex at gene regulatory elements.
Author: Nadav Ahituv
Publisher: Springer Science & Business Media
ISBN: 1461416833
Category : Medical
Languages : en
Pages : 289
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Book Description
In Gene Regulatory Sequences and Human Disease, the Editor will introduce the different technological advances that led to this breakthrough. In addition, several examples will be provided of nucleotide variants in noncoding sequences that have been shown to be associated with various human diseases.
