Exploring genetic regulatory networks in metazoan development: methods and models

2002 ◽  
Vol 10 (3) ◽  
pp. 131-143 ◽  
Author(s):  
Marc S. Halfon ◽  
Alan M. Michelson
Keyword(s):  
Regulatory Networks ◽  
Sequence Data ◽  
Transcriptional Profiling ◽  
Computational Prediction ◽  
Regulatory Elements ◽  
Genetic Regulatory Networks ◽  
Genomic Research ◽  
Whole Genome Sequence ◽  
Biological Research ◽  
Starting Point

One of the foremost challenges of 21st century biological research will be to decipher the complex genetic regulatory networks responsible for embryonic development. The recent explosion of whole genome sequence data and of genome-wide transcriptional profiling methods, such as microarrays, coupled with the development of sophisticated computational tools for exploiting and analyzing genomic data, provide a significant starting point for regulatory network analysis. In this article we review some of the main methodological issues surrounding genome annotation, transcriptional profiling, and computational prediction of cis-regulatory elements and discuss how the power of model genetic organisms can be used to experimentally verify and extend the results of genomic research.

scholarly journals Bayesian inference of infectious disease transmission from whole genome sequence data

2013 ◽  
Author(s):  
Xavier Didelot ◽  
Jennifer Gardy ◽  
Caroline Colijn
Keyword(s):  
Disease Transmission ◽  
Sequence Data ◽  
Disease Outbreaks ◽  
Genomic Data ◽  
Realistic Model ◽  
Host Population ◽  
Whole Genome Sequence ◽  
Genomic Epidemiology ◽  
Starting Point ◽  
Source Case

Genomics is increasingly being used to investigate disease outbreaks, but an important question remains unanswered -- how well do genomic data capture known transmission events, particularly for pathogens with long carriage periods or large within-host population sizes? Here we present a novel Bayesian approach to reconstruct densely-sampled outbreaks from genomic data whilst considering within-host diversity. We infer a time-labelled phylogeny using BEAST, then infer a transmission network via a Monte-Carlo Markov Chain. We find that under a realistic model of within-host evolution, reconstructions of simulated outbreaks contain substantial uncertainty even when genomic data reflect a high substitution rate. Reconstruction of a real-world tuberculosis outbreak displayed similar uncertainty, although the correct source case and several clusters of epidemiologically linked cases were identified. We conclude that genomics cannot wholly replace traditional epidemiology, but that Bayesian reconstructions derived from sequence data may form a useful starting point for a genomic epidemiology investigation.

scholarly journals Fungal Genomic Resources for Strain Identification and Diversity Analysis of 1900 Fungal Species

2021 ◽  
Vol 7 (4) ◽  
pp. 288
Author(s):  
Mir Asif Iquebal ◽  
Sarika Jaiswal ◽  
Vineet Kumar Mishra ◽  
Rahul Singh Jasrotia ◽  
Ulavappa B. Angadi ◽  
...  
Keyword(s):  
Genome Sequence ◽  
In Silico ◽  
Sequence Data ◽  
Fungal Species ◽  
Genomic Research ◽  
Whole Genome Sequence ◽  
Strain Identification ◽  
Diversity Analysis ◽  
Whole Genome

Identification and diversity analysis of fungi is greatly challenging. Though internal transcribed spacer (ITS), region-based DNA fingerprinting works as a “gold standard” for most of the fungal species group, it cannot differentiate between all the groups and cryptic species. Therefore, it is of paramount importance to find an alternative approach for strain differentiation. Availability of whole genome sequence data of nearly 2000 fungal species are a promising solution to such requirement. We present whole genome sequence-based world’s largest microsatellite database, FungSatDB having >19M loci obtained from >1900 fungal species/strains using >4000 assemblies across globe. Genotyping efficacy of FungSatDB has been evaluated by both in-silico and in-vitro PCR. By in silico PCR, 66 strains of 8 countries representing four continents were successfully differentiated. Genotyping efficacy was also evaluated by in vitro PCR in four fungal species. This approach overcomes limitation of ITS in species, strain signature, and diversity analysis. It can accelerate fungal genomic research endeavors in agriculture, industrial, and environmental management.

Construction of Probabilistic Boolean Networks from a Prescribed Transition Probability Matrix: A Maximum Entropy Rate Approach

2011 ◽  
Vol 1 (2) ◽  
pp. 132-154 ◽  
Author(s):  
Xi Chen ◽  
Wai-Ki Ching ◽  
Xiao-Shan Chen ◽  
Yang Cong ◽  
Nam-Kiu Tsing
Keyword(s):  
Inverse Problem ◽  
Maximum Entropy ◽  
Regulatory Networks ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Boolean Networks ◽  
Genetic Regulatory Networks ◽  
Genomic Research ◽  
Long Run ◽  
Probabilistic Boolean Networks

AbstractModeling genetic regulatory networks is an important problem in genomic research. Boolean Networks (BNs) and their extensions Probabilistic Boolean Networks (PBNs) have been proposed for modeling genetic regulatory interactions. In a PBN, its steady-state distribution gives very important information about the long-run behavior of the whole network. However, one is also interested in system synthesis which requires the construction of networks. The inverse problem is ill-posed and challenging, as there may be many networks or no network having the given properties, and the size of the problem is huge. The construction of PBNs from a given transition-probability matrix and a given set of BNs is an inverse problem of huge size. We propose a maximum entropy approach for the above problem. Newton's method in conjunction with the Conjugate Gradient (CG) method is then applied to solving the inverse problem. We investigate the convergence rate of the proposed method. Numerical examples are also given to demonstrate the effectiveness of our proposed method.

scholarly journals Similarity between soybean and Arabidopsis seed methylomes and loss of non-CG methylation does not affect seed development

2017 ◽  
Vol 114 (45) ◽  
pp. E9730-E9739 ◽  
Author(s):  
Jer-Young Lin ◽  
Brandon H. Le ◽  
Min Chen ◽  
Kelli F. Henry ◽  
Jungim Hur ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Seed Development ◽  
Significant Role ◽  
Regulatory Networks ◽  
Storage Proteins ◽  
Seed Proteins ◽  
Regulatory Elements ◽  
Genetic Regulatory Networks ◽  
Global Changes ◽  
Seed Formation

We profiled soybean and Arabidopsis methylomes from the globular stage through dormancy and germination to understand the role of methylation in seed formation. CHH methylation increases significantly during development throughout the entire seed, targets primarily transposable elements (TEs), is maintained during endoreduplication, and drops precipitously within the germinating seedling. By contrast, no significant global changes in CG- and CHG-context methylation occur during the same developmental period. An Arabidopsis ddcc mutant lacking CHH and CHG methylation does not affect seed development, germination, or major patterns of gene expression, implying that CHH and CHG methylation does not play a significant role in seed development or in regulating seed gene activity. By contrast, over 100 TEs are transcriptionally de-repressed in ddcc seeds, suggesting that the increase in CHH-context methylation may be a failsafe mechanism to reinforce transposon silencing. Many genes encoding important classes of seed proteins, such as storage proteins, oil biosynthesis enzymes, and transcription factors, reside in genomic regions devoid of methylation at any stage of seed development. Many other genes in these classes have similar methylation patterns, whether the genes are active or repressed. Our results suggest that methylation does not play a significant role in regulating large numbers of genes important for programming seed development in both soybean and Arabidopsis. We conclude that understanding the mechanisms controlling seed development will require determining how cis-regulatory elements and their cognate transcription factors are organized in genetic regulatory networks.

scholarly journals Genome-wide scan for selection signatures reveals novel insights into the adaptive capacity in local North African cattle

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Slim Ben-Jemaa ◽  
Salvatore Mastrangelo ◽  
Seung-Hwan Lee ◽  
Jun Heon Lee ◽  
Mekki Boussaha
Keyword(s):  
Adaptive Capacity ◽  
Molecular Mechanisms ◽  
Sequence Data ◽  
Regulatory Elements ◽  
Whole Genome Sequence ◽  
North African ◽  
Selection Signatures ◽  
Extended Haplotype ◽  
The North ◽  
African Cattle

Abstract Natural-driven selection is supposed to have left detectable signatures on the genome of North African cattle which are often characterized by the fixation of genetic variants associated with traits under selection pressure and/or an outstanding genetic differentiation with other populations at particular loci. Here, we investigate the population genetic structure and we provide a first outline of potential selection signatures in North African cattle using single nucleotide polymorphism genotyping data. After comparing our data to African, European and indicine cattle populations, we identified 36 genomic regions using three extended haplotype homozygosity statistics and 92 outlier markers based on Bayescan test. The 13 outlier windows detected by at least two approaches, harboured genes (e.g. GH1, ACE, ASIC3, HSPH1, MVD, BCL2, HIGD2A, CBFA2T3) that may be involved in physiological adaptations required to cope with environmental stressors that are typical of the North African area such as infectious diseases, extended drought periods, scarce food supply, oxygen scarcity in the mountainous areas and high-intensity solar radiation. Our data also point to candidate genes involved in transcriptional regulation suggesting that regulatory elements had also a prominent role in North African cattle response to environmental constraints. Our study yields novel insights into the unique adaptive capacity in these endangered populations emphasizing the need for the use of whole genome sequence data to gain a better understanding of the underlying molecular mechanisms.

scholarly journals A comparative analysis of heart microRNAs in vertebrates brings novel insights into the evolution of genetic regulatory networks

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Pedro G. Nachtigall ◽  
Luiz A. Bovolenta ◽  
James G. Patton ◽  
Bastian Fromm ◽  
Ney Lemke ◽  
...  
Keyword(s):  
Heart Development ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Developmental Process ◽  
Regulatory Elements ◽  
Genetic Regulatory Networks ◽  
Genomic Context ◽  
Specific Expression ◽  
Control Of Gene Expression ◽  
Expression Levels

Abstract Background During vertebrate evolution, the heart has undergone remarkable changes that lead to morphophysiological differences in the fully formed heart of these species, such as chamber septation, heart rate frequency, blood pressure, and cardiac output volume. Despite these differences, the heart developmental process is guided by a core gene set conserved across vertebrates. Nonetheless, the regulatory mechanisms controlling the expression of genes involved in heart development and maintenance are largely uncharted. MicroRNAs (miRNAs) have been described as important regulatory elements in several biological processes, including heart biology. These small RNA molecules are broadly conserved in sequence and genomic context in metazoans. Mutations may occur in miRNAs and/or genes that contribute to the establishment of distinct repertoires of miRNA-target interactions, thereby favoring the differential control of gene expression and, consequently, the origin of novel phenotypes. In fact, several studies showed that miRNAs are integrated into genetic regulatory networks (GRNs) governing specific developmental programs and diseases. However, studies integrating miRNAs in vertebrate heart GRNs under an evolutionary perspective are still scarce. Results We comprehensively examined and compared the heart miRNome of 20 species representatives of the five major vertebrate groups. We found 54 miRNA families with conserved expression and a variable number of miRNA families with group-specific expression in fishes, amphibians, reptiles, birds, and mammals. We also detected that conserved miRNAs present higher expression levels and a higher number of targets, whereas the group-specific miRNAs present lower expression levels and few targets. Conclusions Both the conserved and group-specific miRNAs can be considered modulators orchestrating the core and peripheral genes of heart GRNs of vertebrates, which can be related to the morphophysiological differences and similarities existing in the heart of distinct vertebrate groups. We propose a hypothesis to explain evolutionary differences in the putative functional roles of miRNAs in the heart GRNs analyzed. Furthermore, we present new insights into the molecular mechanisms that could be helping modulate the diversity of morphophysiology in the heart organ of vertebrate species.

Next-Generation Sequencing: An Emerging Tool for Drug Designing

2019 ◽  
Vol 25 (31) ◽  
pp. 3350-3357 ◽  
Author(s):  
Pooja Tripathi ◽  
Jyotsna Singh ◽  
Jonathan A. Lal ◽  
Vijay Tripathi
Keyword(s):  
Next Generation Sequencing ◽  
High Throughput ◽  
Large Scale ◽  
Massively Parallel Sequencing ◽  
Genomic Research ◽  
Biological Research ◽  
Next Generation ◽  
Human Welfare ◽  
Drug Designing ◽  
Generation Sequencing

Background: With the outbreak of high throughput next-generation sequencing (NGS), the biological research of drug discovery has been directed towards the oncology and infectious disease therapeutic areas, with extensive use in biopharmaceutical development and vaccine production. Method: In this review, an effort was made to address the basic background of NGS technologies, potential applications of NGS in drug designing. Our purpose is also to provide a brief introduction of various Nextgeneration sequencing techniques. Discussions: The high-throughput methods execute Large-scale Unbiased Sequencing (LUS) which comprises of Massively Parallel Sequencing (MPS) or NGS technologies. The Next geneinvolved necessarily executes Largescale Unbiased Sequencing (LUS) which comprises of MPS or NGS technologies. These are related terms that describe a DNA sequencing technology which has revolutionized genomic research. Using NGS, an entire human genome can be sequenced within a single day. Conclusion: Analysis of NGS data unravels important clues in the quest for the treatment of various lifethreatening diseases and other related scientific problems related to human welfare.

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