Genome-Wide Nucleosome Positioning Is Orchestrated by Genomic Regions Associated with DNase I Hypersensitivity in Rice

AbstractWe present a deformation energy model for predicting nucleosome positioning, in which a position-dependent structural parameter set derived from crystal structures of nucleosomes was used to calculate the DNA deformation energy. The model is successful in predicting nucleosome occupancy genome-wide in budding yeast, nucleosome free energy, and rotational positioning of nucleosomes. Our model also indicates that the genomic regions underlying the MNase-sensitive nucleosomes in budding yeast have high deformation energy and, consequently, low nucleosome-forming ability, while the MNase-sensitive non-histone particles are characterized by much lower DNA deformation energy and high nucleosome preference. In addition, we also revealed that remodelers, SNF2 and RSC8, are likely to act in chromatin remodeling by binding to broad nucleosome-depleted regions that are intrinsically favorable for nucleosome positioning. Our data support the important role of position-dependent physical properties of DNA in nucleosome positioning.

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Genome-wide Prediction of DNase I Hypersensitivity Using Gene Expression

10.1101/035808 ◽

2016 ◽

Author(s):

Weiqiang Zhou ◽

Ben Sherwood ◽

Zhicheng Ji ◽

Fang Du ◽

Jiawei Bai ◽

...

Keyword(s):

Gene Expression ◽

Prediction Models ◽

Regulatory Element ◽

Gene Expression Omnibus ◽

Dnase I ◽

Dnase I Hypersensitivity ◽

Genome Wide ◽

High Dimensional Problem ◽

Data Regression ◽

Whole Transcriptome

We evaluate the feasibility of using a biological sample’s transcriptome to predict its genome-wide regulatory element activities measured by DNase I hypersensitivity (DH). We develop BIRD, Big Data Regression for predicting DH, to handle this high-dimensional problem. Applying BIRD to the Encyclopedia of DNA Element (ENCODE) data, we found that gene expression to a large extent predicts DH, and information useful for prediction is contained in the whole transcriptome rather than limited to a regulatory element’s neighboring genes. We show that the predicted DH predicts transcription factor binding sites (TFBSs), prediction models trained using ENCODE data can be applied to gene expression samples in Gene Expression Omnibus (GEO) to predict regulome, and one can use predictions as pseudo-replicates to improve the analysis of high-throughput regulome profiling data. Besides improving our understanding of the regulome-transcriptome relationship, this study suggests that transcriptome-based prediction can provide a useful new approach for regulome mapping.

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Genome-wide prediction of DNase I hypersensitivity using gene expression

Nature Communications ◽

10.1038/s41467-017-01188-x ◽

2017 ◽

Vol 8 (1) ◽

Cited By ~ 14

Author(s):

Weiqiang Zhou ◽

Ben Sherwood ◽

Zhicheng Ji ◽

Yingchao Xue ◽

Fang Du ◽

...

Keyword(s):

Gene Expression ◽

Dnase I ◽

Dnase I Hypersensitivity ◽

Genome Wide

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Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color

Science Advances ◽

10.1126/sciadv.abd1239 ◽

2021 ◽

Vol 7 (11) ◽

pp. eabd1239

Author(s):

Mark Simcoe ◽

Ana Valdes ◽

Fan Liu ◽

Nicholas A. Furlotte ◽

David M. Evans ◽

...

Keyword(s):

Association Study ◽

Genome Wide Association Study ◽

Color Variation ◽

Genome Wide Association ◽

Nucleotide Polymorphisms ◽

Melanin Pigmentation ◽

Eye Color ◽

Human Eye ◽

Genome Wide ◽

Genomic Regions

Human eye color is highly heritable, but its genetic architecture is not yet fully understood. We report the results of the largest genome-wide association study for eye color to date, involving up to 192,986 European participants from 10 populations. We identify 124 independent associations arising from 61 discrete genomic regions, including 50 previously unidentified. We find evidence for genes involved in melanin pigmentation, but we also find associations with genes involved in iris morphology and structure. Further analyses in 1636 Asian participants from two populations suggest that iris pigmentation variation in Asians is genetically similar to Europeans, albeit with smaller effect sizes. Our findings collectively explain 53.2% (95% confidence interval, 45.4 to 61.0%) of eye color variation using common single-nucleotide polymorphisms. Overall, our study outcomes demonstrate that the genetic complexity of human eye color considerably exceeds previous knowledge and expectations, highlighting eye color as a genetically highly complex human trait.

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Epigenome-Wide Study Identified Methylation Sites Associated with the Risk of Obesity

Nutrients ◽

10.3390/nu13061984 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1984

Author(s):

Majid Nikpay ◽

Sepehr Ravati ◽

Robert Dent ◽

Ruth McPherson

Keyword(s):

Quantitative Trait Locus ◽

Quantitative Trait ◽

Rare Variants ◽

Genome Wide ◽

A Genome ◽

Genome Wide Search ◽

Risk Snps ◽

Trait Locus ◽

Genomic Regions ◽

Eqtl Data

Here, we performed a genome-wide search for methylation sites that contribute to the risk of obesity. We integrated methylation quantitative trait locus (mQTL) data with BMI GWAS information through a SNP-based multiomics approach to identify genomic regions where mQTLs for a methylation site co-localize with obesity risk SNPs. We then tested whether the identified site contributed to BMI through Mendelian randomization. We identified multiple methylation sites causally contributing to the risk of obesity. We validated these findings through a replication stage. By integrating expression quantitative trait locus (eQTL) data, we noted that lower methylation at cg21178254 site upstream of CCNL1 contributes to obesity by increasing the expression of this gene. Higher methylation at cg02814054 increases the risk of obesity by lowering the expression of MAST3, whereas lower methylation at cg06028605 contributes to obesity by decreasing the expression of SLC5A11. Finally, we noted that rare variants within 2p23.3 impact obesity by making the cg01884057 site more susceptible to methylation, which consequently lowers the expression of POMC, ADCY3 and DNAJC27. In this study, we identify methylation sites associated with the risk of obesity and reveal the mechanism whereby a number of these sites exert their effects. This study provides a framework to perform an omics-wide association study for a phenotype and to understand the mechanism whereby a rare variant causes a disease.

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Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat

Theoretical and Applied Genetics ◽

10.1007/s00122-021-03881-4 ◽

2021 ◽

Author(s):

Yang Yang ◽

Aduragbemi Amo ◽

Di Wei ◽

Yongmao Chai ◽

Jie Zheng ◽

...

Keyword(s):

Association Study ◽

Candidate Genes ◽

Bread Wheat ◽

Large Scale ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Genome Wide ◽

Large Scale Integration ◽

Scale Integration ◽

Genomic Regions

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Drosophila Gain-of-Function Mutant RTK Torso Triggers Ectopic Dpp and STAT Signaling

Genetics ◽

10.1093/genetics/164.1.247 ◽

2003 ◽

Vol 164 (1) ◽

pp. 247-258 ◽

Cited By ~ 1

Author(s):

Jinghong Li ◽

Willis X Li

Keyword(s):

Tyrosine Kinases ◽

Target Genes ◽

Tor Signaling ◽

Gain Of Function ◽

Essential Requirement ◽

Downstream Target ◽

Rtk Signaling ◽

Genome Wide ◽

A Genome ◽

Genomic Regions

Abstract Overactivation of receptor tyrosine kinases (RTKs) has been linked to tumorigenesis. To understand how a hyperactivated RTK functions differently from wild-type RTK, we conducted a genome-wide systematic survey for genes that are required for signaling by a gain-of-function mutant Drosophila RTK Torso (Tor). We screened chromosomal deficiencies for suppression of a gain-of-function mutation tor (torGOF), which led to the identification of 26 genomic regions that, when in half dosage, suppressed the defects caused by torGOF. Testing of candidate genes in these regions revealed many genes known to be involved in Tor signaling (such as those encoding the Ras-MAPK cassette, adaptor and structural molecules of RTK signaling, and downstream target genes of Tor), confirming the specificity of this genetic screen. Importantly, this screen also identified components of the TGFβ (Dpp) and JAK/STAT pathways as being required for TorGOF signaling. Specifically, we found that reducing the dosage of thickveins (tkv), Mothers against dpp (Mad), or STAT92E (aka marelle), respectively, suppressed torGOF phenotypes. Furthermore, we demonstrate that in torGOF embryos, dpp is ectopically expressed and thus may contribute to the patterning defects. These results demonstrate an essential requirement of noncanonical signaling pathways for a persistently activated RTK to cause pathological defects in an organism.

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Natural variation in fecundity is correlated with species-wide levels of divergence in Caenorhabditis elegans

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab168 ◽

2021 ◽

Author(s):

Gaotian Zhang ◽

Jake D Mostad ◽

Erik C Andersen

Keyword(s):

Life History ◽

Caenorhabditis Elegans ◽

Life History Traits ◽

Life History Trait ◽

Selective Sweeps ◽

C Elegans ◽

Genome Wide ◽

Genetic Complexity ◽

Genomic Regions ◽

Global Population

Abstract Life history traits underlie the fitness of organisms and are under strong natural selection. A new mutation that positively impacts a life history trait will likely increase in frequency and become fixed in a population (e.g. a selective sweep). The identification of the beneficial alleles that underlie selective sweeps provides insights into the mechanisms that occurred during the evolution of a species. In the global population of Caenorhabditis elegans, we previously identified selective sweeps that have drastically reduced chromosomal-scale genetic diversity in the species. Here, we measured the fecundity of 121 wild C. elegans strains, including many recently isolated divergent strains from the Hawaiian islands and found that strains with larger swept genomic regions have significantly higher fecundity than strains without evidence of the recent selective sweeps. We used genome-wide association (GWA) mapping to identify three quantitative trait loci (QTL) underlying the fecundity variation. Additionally, we mapped previous fecundity data from wild C. elegans strains and C. elegans recombinant inbred advanced intercross lines that were grown in various conditions and detected eight QTL using GWA and linkage mappings. These QTL show the genetic complexity of fecundity across this species. Moreover, the haplotype structure in each GWA QTL region revealed correlations with recent selective sweeps in the C. elegans population. North American and European strains had significantly higher fecundity than most strains from Hawaii, a hypothesized origin of the C. elegans species, suggesting that beneficial alleles that caused increased fecundity could underlie the selective sweeps during the worldwide expansion of C. elegans.

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Learning a genome-wide score of human–mouse conservation at the functional genomics level

Nature Communications ◽

10.1038/s41467-021-22653-8 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Soo Bin Kwon ◽

Jason Ernst

Keyword(s):

Mouse Model ◽

Functional Genomics ◽

Functional Genomic ◽

Transcriptomic Data ◽

Model Studies ◽

Genome Wide ◽

A Genome ◽

Important Challenge ◽

Genomic Regions ◽

Human And Mouse

AbstractIdentifying genomic regions with functional genomic properties that are conserved between human and mouse is an important challenge in the context of mouse model studies. To address this, we develop a method to learn a score of evidence of conservation at the functional genomics level by integrating information from a compendium of epigenomic, transcription factor binding, and transcriptomic data from human and mouse. The method, Learning Evidence of Conservation from Integrated Functional genomic annotations (LECIF), trains neural networks to generate this score for the human and mouse genomes. The resulting LECIF score highlights human and mouse regions with shared functional genomic properties and captures correspondence of biologically similar human and mouse annotations. Analysis with independent datasets shows the score also highlights loci associated with similar phenotypes in both species. LECIF will be a resource for mouse model studies by identifying loci whose functional genomic properties are likely conserved.

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Genome-Wide Analyses Identifies Known and New Markers Responsible of Chicken Plumage Color

Animals ◽

10.3390/ani10030493 ◽

2020 ◽

Vol 10 (3) ◽

pp. 493

Author(s):

Salvatore Mastrangelo ◽

Filippo Cendron ◽

Gianluca Sottile ◽

Giovanni Niero ◽

Baldassare Portolano ◽

...

Keyword(s):

Genome Wide Association Study ◽

Snp Array ◽

Fixation Index ◽

Phenotypic Traits ◽

Plumage Color ◽

Phenotypic Marker ◽

Genome Wide ◽

A Genome ◽

The Difference ◽

Genomic Regions

Through the development of the high-throughput genotyping arrays, molecular markers and genes related to phenotypic traits have been identified in livestock species. In poultry, plumage color is an important qualitative trait that can be used as phenotypic marker for breed identification. In order to assess sources of genetic variation related to the Polverara chicken breed plumage colour (black vs. white), we carried out a genome-wide association study (GWAS) and a genome-wide fixation index (FST) scan to uncover the genomic regions involved. A total of 37 animals (17 white and 20 black) were genotyped with the Affymetrix 600 K Chicken single nucleotide polymorphism (SNP) Array. The combination of results from GWAS and FST revealed a total of 40 significant markers distributed on GGA 01, 03, 08, 12 and 21, and located within or near known genes. In addition to the well-known TYR, other candidate genes have been identified in this study, such as GRM5, RAB38 and NOTCH2. All these genes could explain the difference between the two Polverara breeds. Therefore, this study provides the basis for further investigation of the genetic mechanisms involved in plumage color in chicken.

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