scholarly journals The effect of common inversion polymorphisms In(2L)t and In(3R)Mo on patterns of transcriptional variation in Drosophila melanogaster

2017 ◽  
Author(s):  
Erik Lavington ◽  
Andrew D. Kern
Keyword(s):  
Genetic Variation ◽  
Genomic Sequence ◽  
Position Effect ◽  
Transcript Abundance ◽  
Theoretical Models ◽  
Regulatory Elements ◽  
Sterol Uptake ◽  
Genome Wide ◽  
Transcriptional Variation ◽  
Niemann Pick

AbstractChromosomal inversions are an ubiquitous feature of genetic variation. Theoretical models describe several mechanisms by which inversions can drive adaptation and be maintained as polymorphisms. While inversions have been shown previously to be under selection, or contain genetic variation under selection, the specific phenotypic consequences of inversions leading to their maintenance remain unclear. Here we use genomic sequence and expression data from the Drosophila Genetic Reference Panel to explore the effects of two cosmopolitan inversions, In(2L)t and In(3R)Mo, on patterns of transcriptional variation. We demonstrate that each inversion has a significant effect on transcript abundance for hundreds of genes across the genome. Inversion affected loci (IAL) appear both within inversions as well as on unlinked chromosomes. Importantly, IAL do not appear to be influenced by the previously reported genome-wide expression correlation structure. We found that five genes involved with sterol uptake, four of which are Niemann-Pick Type 2 orthologs, are upregulated in flies with In(3R)Mo but do not have SNPs in LD with the inversion. We speculate that this upregulation is driven by genetic variation in mod(mdg4) that is in LD with In(3R)Mo. We find that there is little evidence for regional or position effect of inversions on gene expression at the chromosomal level but do find evidence for the distal breakpoint of In(3R)Mo interrupting one gene and possibly disassociating the two flanking genes from regulatory elements.

scholarly journals Human genetic variation within neural crest enhancers: molecular and phenotypic implications

2013 ◽  
Vol 368 (1620) ◽  
pp. 20120360 ◽  
Author(s):  
Alvaro Rada-Iglesias ◽  
Sara L. Prescott ◽  
Joanna Wysocka
Keyword(s):  
Genetic Variation ◽  
Neural Crest ◽  
Phenotypic Diversity ◽  
Regulatory Elements ◽  
Embryonic Cell ◽  
Human Genetic Variation ◽  
Nucleotide Polymorphisms ◽  
Cooperative Relationships ◽  
Developmental Gene Expression ◽  
Genome Wide

Developmental gene expression programmes are coordinated by the specialized distal cis -regulatory elements called enhancers, which integrate lineage- and signalling-dependent inputs to guide morphogenesis. In previous work, we characterized the genome-wide repertoire of active enhancers in human neural crest cells (hNCC), an embryonic cell population with critical roles in craniofacial development. We showed that in hNCC, co-occupancy of a master regulator TFAP2A with nuclear receptors NR2F1 and NR2F2 correlates with the presence of permissive enhancer chromatin states. Here, we take advantage of pre-existing human genetic variation to further explore potential cooperation between TFAP2A and NR2F1/F2. We demonstrate that isolated single nucleotide polymorphisms affecting NR2F1/F2-binding sites within hNCC enhancers can alter TFAP2A occupancy and overall chromatin features at the same enhancer allele. We propose that a similar strategy can be used to elucidate other cooperative relationships between transcription factors involved in developmental transitions. Using the neural crest and its major contribution to human craniofacial phenotypes as a paradigm, we discuss how genetic variation might modulate the molecular properties and activity of enhancers, and ultimately impact human phenotypic diversity.

scholarly journals Genetic and Epigenetic Fine Mapping of Complex Trait Associated Loci in the Human Liver

2018 ◽  
Author(s):  
Minal Çalışkan ◽  
Elisabetta Manduchi ◽  
H. Shanker Rao ◽  
Julian A Segert ◽  
Marcia Holsbach Beltrame ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
Histone Modification ◽  
Human Liver ◽  
Complex Disease ◽  
Regulation Of Gene Expression ◽  
Regulatory Elements ◽  
Chromatin Interaction ◽  
Genome Wide ◽  
The Impact

ABSTRACTDeciphering the impact of genetic variation on gene regulation is fundamental to understanding common, complex human diseases. Although histone modifications are important markers of gene regulatory regions of the genome, any specific histone modification has not been assayed in more than a few individuals in the human liver. As a result, the impacts of genetic variation that direct histone modification states in the liver are poorly understood. Here, we generate the most comprehensive genome-wide dataset of two epigenetic marks, H3K4me3 and H3K27ac, and annotate thousands of putative regulatory elements in the human liver. We integrate these findings with genome-wide gene expression data collected from the same human liver tissues and high-resolution promoter-focused chromatin interaction maps collected from human liver-derived HepG2 cells. We demonstrate widespread functional consequences of natural genetic variation on putative regulatory element activity and gene expression levels. Leveraging these extensive datasets, we fine-map a total of 77 GWAS loci that have been associated with at least one complex phenotype. Our results contribute to the repertoire of genes and regulatory mechanisms governing complex disease development and further the basic understanding of genetic and epigenetic regulation of gene expression in the human liver tissue.

scholarly journals G-quadruplex structural variations in human genome associated with single-nucleotide variations and their impact on gene activity

2021 ◽  
Vol 118 (21) ◽  
pp. e2013230118
Author(s):  
Jia-yuan Gong ◽  
Cui-jiao Wen ◽  
Ming-liang Tang ◽  
Rui-fang Duan ◽  
Juan-nan Chen ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Human Genome ◽  
Regulatory Elements ◽  
Gene Activity ◽  
Gene Expressions ◽  
Single Nucleotide ◽  
Average Load ◽  
Genome Wide ◽  
Single Nucleotide Variations ◽  
The Impact

G-quadruplexes (G4s) formed by guanine-rich nucleic acids play a role in essential biological processes such as transcription and replication. Besides the >1.5 million putative G-4–forming sequences (PQSs), the human genome features >640 million single-nucleotide variations (SNVs), the most common type of genetic variation among people or populations. An SNV may alter a G4 structure when it falls within a PQS motif. To date, genome-wide PQS–SNV interactions and their impact have not been investigated. Herein, we present a study on the PQS–SNV interactions and the impact they can bring to G4 structures and, subsequently, gene expressions. Based on build 154 of the Single Nucleotide Polymorphism Database (dbSNP), we identified 5 million gains/losses or structural conversions of G4s that can be caused by the SNVs. Of these G4 variations (G4Vs), 3.4 million are within genes, resulting in an average load of >120 G4Vs per gene, preferentially enriched near the transcription start site. Moreover, >80% of the G4Vs overlap with transcription factor–binding sites and >14% with enhancers, giving an average load of 3 and 7.5 for the two regulatory elements, respectively. Our experiments show that such G4Vs can significantly influence the expression of their host genes. These results reveal genome-wide G4Vs and their impact on gene activity, emphasizing an understanding of genetic variation, from a structural perspective, of their physiological function and pathological implications. The G4Vs may also provide a unique category of drug targets for individualized therapeutics, health risk assessment, and drug development.

scholarly journals Soil bacterial populations are shaped by recombination and gene-specific selection across a meadow

2019 ◽  
Author(s):  
Alexander Crits-Christoph ◽  
Matthew Olm ◽  
Spencer Diamond ◽  
Keith Bouma-Gregson ◽  
Jillian Banfield
Keyword(s):  
Genetic Variation ◽  
Nucleotide Diversity ◽  
De Novo ◽  
Genomic Sequence ◽  
Bacterial Species ◽  
Soil Microbial Diversity ◽  
Genome Wide ◽  
Local Soil ◽  
Soil Bacterial ◽  
Extracellular Transport

AbstractSoil microbial diversity is often studied from the perspective of community composition, but less is known about genetic heterogeneity within species and how population structures are affected by dispersal, recombination, and selection. Genomic inferences about population structure can be made using the millions of sequencing reads that are assembled de novo into consensus genomes from metagenomes, as each read pair describes a short genomic sequence from a cell in the population. Here we track genome-wide population genetic variation for 19 highly abundant bacterial species sampled from across a grassland meadow. Genomic nucleotide identity of assembled genomes was significantly associated with local geography for half of the populations studied, and for a majority of populations within-sample nucleotide diversity could often be as high as meadow-wide nucleotide diversity. Genes involved in specialized metabolite biosynthesis and extracellular transport were characterized by elevated genetic diversity in multiple species. Microbial populations displayed varying degrees of homologous recombination and recombinant variants were often detected at 7-36% of loci genome-wide. Within multiple populations we identified genes with unusually high site-specific differentiation of alleles, fewer recombinant events, and lower nucleotide diversity, suggesting recent selective sweeps for gene variants. Taken together, these results indicate that recombination and gene-specific selection commonly shape local soil bacterial genetic variation.

Genetic background of cholesterol absorption efficacy. The role of Niemann–Pick C1-like 1 receptor and its genetic variation in lipid metabolism

2010 ◽  
Vol 151 (34) ◽  
pp. 1376-1383 ◽  
Author(s):  
Mariann Harangi ◽  
István Balogh ◽  
János Harangi ◽  
György Paragh
Keyword(s):  
Genetic Variation ◽  
Lipid Metabolism ◽  
Genetic Background ◽  
Cholesterol Absorption ◽  
Niemann Pick

A Niemann–Pick C1-like-1 egy szterolfelismerő domént tartalmazó membránfehérje, amelyet nagy számban expresszálnak csúcsi felszínükön a bélhámsejtek. Az utóbbi évek vizsgálatai azt igazolták, hogy ez a fehérje szükséges a szabad koleszterin bejutásához a bélhámsejtekbe a bél lumenéből. Biokémiai vizsgálatok azt igazolták, hogy a Niemann–Pick C1-like-1-hez kötődik az ezetimib, amely egy hatékony koleszterinfelszívódást gátló szer. A bélből történő koleszterinfelszívódás ütemében és az ezetimibkezelés hatékonyságában tapasztalt egyéni eltérések hátterében felmerült néhány Niemann–Pick C1-like-1 génvariáció oki szerepe.

Artificial Intelligence for epigenetics: towards personalized medicine

2020 ◽  
Vol 27 ◽  
Author(s):  
Giulia De Riso ◽  
Sergio Cocozza
Keyword(s):  
Biological Sciences ◽  
Artificial Intelligence ◽  
Personalized Medicine ◽  
Molecular Mechanisms ◽  
Genomic Sequence ◽  
Health Care Interventions ◽  
Genome Wide ◽  
Genetic And Environmental Factors ◽  
Opening Up ◽  
Omic Data

: Epigenetics is a field of biological sciences focused on the study of reversible, heritable changes in gene function not due to modifications of the genomic sequence. These changes are the result of a complex cross-talk between several molecular mechanisms, that is in turn orchestrated by genetic and environmental factors. The epigenetic profile captures the unique regulatory landscape and the exposure to environmental stimuli of an individual. It thus constitutes a valuable reservoir of information for personalized medicine, which is aimed at customizing health-care interventions based on the unique characteristics of each individual. Nowadays, the complex milieu of epigenomic marks can be studied at the genome-wide level thanks to massive, highthroughput technologies. This new experimental approach is opening up new and interesting knowledge perspectives. However, the analysis of these complex omic data requires to face important analytic issues. Artificial Intelligence, and in particular Machine Learning, are emerging as powerful resources to decipher epigenomic data. In this review, we will first describe the most used ML approaches in epigenomics. We then will recapitulate some of the recent applications of ML to epigenomic analysis. Finally, we will provide some examples of how the ML approach to epigenetic data can be useful for personalized medicine.

scholarly journals DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome

2021 ◽  
Author(s):  
Yanrong Ji ◽  
Zhihan Zhou ◽  
Han Liu ◽  
Ramana V Davuluri
Keyword(s):  
Dna Sequences ◽  
Regulatory Elements ◽  
Ease Of Use ◽  
Fine Tuning ◽  
Supplementary Information ◽  
Sequence Motifs ◽  
Semantic Relationship ◽  
Accurate Identification ◽  
Conserved Sequence ◽  
Genome Wide

Abstract Motivation Deciphering the language of non-coding DNA is one of the fundamental problems in genome research. Gene regulatory code is highly complex due to the existence of polysemy and distant semantic relationship, which previous informatics methods often fail to capture especially in data-scarce scenarios. Results To address this challenge, we developed a novel pre-trained bidirectional encoder representation, named DNABERT, to capture global and transferrable understanding of genomic DNA sequences based on up and downstream nucleotide contexts. We compared DNABERT to the most widely used programs for genome-wide regulatory elements prediction and demonstrate its ease of use, accuracy and efficiency. We show that the single pre-trained transformers model can simultaneously achieve state-of-the-art performance on prediction of promoters, splice sites and transcription factor binding sites, after easy fine-tuning using small task-specific labeled data. Further, DNABERT enables direct visualization of nucleotide-level importance and semantic relationship within input sequences for better interpretability and accurate identification of conserved sequence motifs and functional genetic variant candidates. Finally, we demonstrate that pre-trained DNABERT with human genome can even be readily applied to other organisms with exceptional performance. We anticipate that the pre-trained DNABERT model can be fined tuned to many other sequence analyses tasks. Availability and implementation The source code, pretrained and finetuned model for DNABERT are available at GitHub (https://github.com/jerryji1993/DNABERT). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals A genome-wide map of regulatory elements in zebrafish

Lab Animal ◽  
2020 ◽  
Vol 50 (1) ◽  
pp. 17-17
Author(s):  
Alexandra Le Bras
Keyword(s):  
Regulatory Elements ◽  
Genome Wide ◽  
A Genome

scholarly journals Genomic Analyses of Globodera pallida, A Quarantine Agricultural Pathogen in Idaho

Pathogens ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 363
Author(s):  
Sulochana K. Wasala ◽  
Dana K. Howe ◽  
Louise-Marie Dandurand ◽  
Inga A. Zasada ◽  
Dee R. Denver
Keyword(s):  
Genetic Variation ◽  
Potato Production ◽  
Globodera Pallida ◽  
Fixation Index ◽  
Parasitic Nematodes ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Field Samples ◽  
Multiple Introduction

Globodera pallida is among the most significant plant-parasitic nematodes worldwide, causing major damage to potato production. Since it was discovered in Idaho in 2006, eradication efforts have aimed to contain and eradicate G. pallida through phytosanitary action and soil fumigation. In this study, we investigated genome-wide patterns of G. pallida genetic variation across Idaho fields to evaluate whether the infestation resulted from a single or multiple introduction(s) and to investigate potential evolutionary responses since the time of infestation. A total of 53 G. pallida samples (~1,042,000 individuals) were collected and analyzed, representing five different fields in Idaho, a greenhouse population, and a field in Scotland that was used for external comparison. According to genome-wide allele frequency and fixation index (Fst) analyses, most of the genetic variation was shared among the G. pallida populations in Idaho fields pre-fumigation, indicating that the infestation likely resulted from a single introduction. Temporal patterns of genome-wide polymorphisms involving (1) pre-fumigation field samples collected in 2007 and 2014 and (2) pre- and post-fumigation samples revealed nucleotide variants (SNPs, single-nucleotide polymorphisms) with significantly differentiated allele frequencies indicating genetic differentiation. This study provides insights into the genetic origins and adaptive potential of G. pallida invading new environments.

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