scholarly journals Profiling of open chromatin in developing pig (Sus scrofa) muscle to identify regulatory regions

2021 ◽  
Author(s):  
Mazdak Salavati ◽  
Shernae A. Woolley ◽  
Yennifer Cortés Araya ◽  
Michelle M. Halstead ◽  
Claire Stenhouse ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Sus Scrofa ◽  
Prediction Models ◽  
Developmental Time ◽  
Open Chromatin ◽  
Regulatory Sequences ◽  
Specific Information ◽  
Regulatory Regions ◽  
Breeding Programmes ◽  
Accessible Chromatin

AbstractThere is very little species-specific information about how the genome is regulated in domestic pigs (Sus scrofa). This lack of knowledge hinders efforts to define and predict the effects of genetic variants in pig breeding programmes. In order to address this knowledge gap, we need to identify regulatory sequences in the pig genome starting with regions of open chromatin. We have optimised the ‘Improved Protocol for the Assay for Transposase-Accessible Chromatin (Omni-ATAC-seq)’ to profile regions of open chromatin in flash frozen pig muscle tissue samples. This protocol has allowed us to identify putative regulatory regions in semitendinosus muscle from 24 male piglets. We collected samples from the smallest, average, and largest sized male piglets from each litter through five developmental time points. The ATAC-Seq data were mapped to Sscrofa11.1 with Bowtie2 and Genrich were used for post-alignment peak-calling. Of the 4661 putative regions of accessible chromatin identified, >50% were within 1 kb of known transcription start sites. The size of each open chromatin region varied according to the developmental time point. At day 90 of gestation, we investigated chromatin openness relative to foetal piglet size. In parallel we measured genome-wide gene expression and allele-specific expression using RNA-Seq analysis of the same muscle samples. We found regions of open chromatin associated with down regulation of genes involved in muscle development in small sized foetal piglets. The dataset that we have generated here provides: i) a resource for studies of genome regulation in pigs, and ii) contributes valuable functional annotation information to filter genetic variants for use in genomic selection in pig breeding programmes. Future work could leverage the ATAC-Seq data with very large datasets of genetic variants from phenotyped pigs. This approach could inform chromatin aware genomic prediction models and determine whether regions of open chromatin are enriched for trait-linked variants, and especially for muscle and meat traits.

scholarly journals Profiling of open chromatin in developing pig (Sus scrofa) muscle to identify regulatory regions

2021 ◽  
Author(s):  
Mazdak Salavati ◽  
Shernae A Woolley ◽  
Yennifer Cortés Araya ◽  
Michelle M Halstead ◽  
Claire Stenhouse ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Sus Scrofa ◽  
Muscle Development ◽  
Developmental Time ◽  
Open Chromatin ◽  
Regulatory Sequences ◽  
Semitendinosus Muscle ◽  
Regulatory Regions ◽  
Time Points ◽  
Breeding Programmes

Abstract There is very little information about how the genome is regulated in domestic pigs (Sus scrofa). This lack of knowledge hinders efforts to define and predict the effects of genetic variants in pig breeding programmes. In order to address this knowledge gap, we need to identify regulatory sequences in the pig genome starting with regions of open chromatin. We used the ‘Improved Protocol for the Assay for Transposase-Accessible Chromatin (Omni-ATAC-Seq)’ to identify putative regulatory regions in flash frozen semitendinosus muscle from 24 male piglets. We collected samples from the smallest, average, and largest sized male piglets from each litter through five developmental time points. Of the 4,661 ATAC-Seq peaks identified that represent regions of open chromatin, >50% were within 1 kb of known transcription start sites. Differential read count analysis revealed 377 ATAC-Seq defined genomic regions where chromatin accessibility differed significantly across developmental time points. We found regions of open chromatin associated with down regulation of genes involved in muscle development that were present in small sized foetal piglets but absent in large foetal piglets at day 90 of gestation. The dataset that we have generated provides: a resource for studies of genome regulation in pigs, and contributes valuable functional annotation information to filter genetic variants for use in genomic selection in pig breeding programmes.

scholarly journals methyl-ATAC-seq measures DNA methylation at accessible chromatin

2018 ◽  
Author(s):  
R Spektor ◽  
ND Tippens ◽  
CA Mimoso ◽  
PD Soloway
Keyword(s):  
Dna Methylation ◽  
Binding Sites ◽  
Open Chromatin ◽  
Regulatory Sequences ◽  
Protein Binding Sites ◽  
3 Dimensional ◽  
Genome Wide ◽  
Gene Regulatory ◽  
Nucleosome Location ◽  
Accessible Chromatin

ABSTRACTChromatin features are characterized by genome-wide assays for nucleosome location, protein binding sites, 3-dimensional interactions, and modifications to histones and DNA. For example, Assay for Transposase Accessible Chromatin sequencing (ATAC-seq) identifies nucleosome-depleted (open) chromatin, which harbors potentially active gene regulatory sequences; and bisulfite sequencing (BS-seq) quantifies DNA methylation. When two distinct chromatin features like these are assayed separately in populations of cells, it is impossible to determine, with certainty, where the features are coincident in the genome by simply overlaying datasets. Here we describe methyl-ATAC-seq (mATAC-seq), which implements modifications to ATAC-seq, including subjecting the output to BS-seq. Merging these assays into a single protocol identifies the locations of open chromatin, and reveals, unambiguously, the DNA methylation state of the underlying DNA. Such combinatorial methods eliminate the need to perform assays independently and infer where features are coincident.

scholarly journals Terminal selectors organize postmitotic chromatin accessibility for acquisition of serotonergic identity

2021 ◽  
Author(s):  
Xinrui L Zhang ◽  
William C Spencer ◽  
Nobuko Tabuchi ◽  
Evan S Deneris
Keyword(s):  
Single Cell ◽  
Chromatin Accessibility ◽  
Open Chromatin ◽  
Regulatory Sequences ◽  
Early Maturation ◽  
Accessible Chromatin

Assembly of transcriptomes encoding unique neuronal identities requires selective accessibility of regulatory inputs to cis-regulatory sequences in nucleosome-embedded chromatin. Yet the mechanisms involved in shaping postmitotic neuronal chromatin are poorly understood. Here we used ATAC-seq, ChIPmentation, and single-cell analyses to show that unique distal enhancers and super-enhancers define the Pet1 neuron lineage that generates serotonin (5-HT) neurons. Heterogeneous single cell chromatin landscapes are established early in postmitotic Pet1 neurons and reveal the regulatory programs driving Pet1 neuron subtype identities. Terminal selectors, Pet1 and Lmx1b, control chromatin accessibility in Pet1 neurons to select enhancers for 5-HT neurotransmission and synaptogenesis. In addition, these factors are required to maintain chromatin accessibility during early maturation suggesting that postmitotic open chromatin is unstable and requires continuous terminal selector input. Together our findings reveal a previously unrecognized function of terminal selectors in organizing postmitotic accessible chromatin for the development of specialized neuronal identities.

scholarly journals HiCoP, a simple and robust method for detecting interactions of regulatory regions

2020 ◽  
Author(s):  
Yan Zhang ◽  
Zhaoqiang Li ◽  
Shasha Bian ◽  
Hao Zhao ◽  
Delong Feng ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Regulatory Elements ◽  
High Signal ◽  
Open Chromatin ◽  
Regulatory Regions ◽  
Essential Information ◽  
Histone H3k27 ◽  
Development And Differentiation ◽  
Physical Interactions ◽  
Accessible Chromatin

Abstract Background: Chromatin physical interactions provides essential information for understanding the regulation of cis -elements like enhancers, promoters, and insulators in cell development and differentiation. The Hi-C assay is a technique detecting chromatin structures of the whole genome but not sensitive to interactions of regulatory elements. Several methods, like HiChIP, DNase-C, and OCEAN-C, have been developed for enriching interactions of regulatory regions, but all of them have some shortcomings. New simple, efficient, and robust methods are still in need of detecting interactions of regulatory regions. Results: We developed a new, simple, and robust assay called CoP ( Co lumn P urified chromatin) for profiling of open chromatin regions by directly purifying fragmentized crosslinked chromatin with a DNA purification column. The open chromatin regions, including active enhancers, promoters, and insulators, were significantly enriched in CoP chromatin. The CoP-seq assay can efficiently detect open chromatin regions, especially active promoters, with a high signal-to-noise ratio. We integrated the CoP-seq and Hi-C technique (Hi-CoP) for the detection of interactions of accessible chromatin regions, which represent active cis -regulatory elements in cells. We observed that the HiCoP captured the peaks in the promoters-associated enhancer regions, and the chromatin features identified by HiCoP were similar to HiChIP of histone H3K27 acetylation rather than Hi-C. HiCoP detected more promoter-enhancer (P-E), promoter-promoter (P-P), and enhancer-enhancer (E-E) interactions within 20kb-5Mb than Hi-C. Most of the loops identified by HiCoP were associated with the expressed genes. Conclusion: CoP assay can efficiently enrich open chromatin regions. When CoP assay was integrated with Hi-C assay, it provides a simple, robust, alternative technique for profiling accessible chromatin regions and chromatin conformation simultaneously.

scholarly journals Allele-specific open chromatin in human iPSC neurons elucidates functional disease variants

Science ◽  
2020 ◽  
Vol 369 (6503) ◽  
pp. 561-565 ◽  
Author(s):  
Siwei Zhang ◽  
Hanwen Zhang ◽  
Yifan Zhou ◽  
Min Qiao ◽  
Siming Zhao ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Target Genes ◽  
Disease Risk ◽  
Induced Pluripotent Stem Cell ◽  
Open Chromatin ◽  
Regulatory Sequences ◽  
Functional Interpretation ◽  
Neuropsychiatric Disease ◽  
Risk Variants ◽  
Allele Specific

Most neuropsychiatric disease risk variants are in noncoding sequences and lack functional interpretation. Because regulatory sequences often reside in open chromatin, we reasoned that neuropsychiatric disease risk variants may affect chromatin accessibility during neurodevelopment. Using human induced pluripotent stem cell (iPSC)–derived neurons that model developing brains, we identified thousands of genetic variants exhibiting allele-specific open chromatin (ASoC). These neuronal ASoCs were partially driven by altered transcription factor binding, overrepresented in brain gene enhancers and expression quantitative trait loci, and frequently associated with distal genes through chromatin contacts. ASoCs were enriched for genetic variants associated with brain disorders, enabling identification of functional schizophrenia risk variants and their cis-target genes. This study highlights ASoC as a functional mechanism of noncoding neuropsychiatric risk variants, providing a powerful framework for identifying disease causal variants and genes.

scholarly journals HiCoP, a simple and robust method for detecting interactions of regulatory regions

2020 ◽  
Author(s):  
Yan Zhang ◽  
Zhaoqiang Li ◽  
Shasha Bian ◽  
Hao Zhao ◽  
Delong Feng ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Regulatory Elements ◽  
High Signal ◽  
Open Chromatin ◽  
Regulatory Regions ◽  
Essential Information ◽  
Histone H3k27 ◽  
Development And Differentiation ◽  
Physical Interactions ◽  
Accessible Chromatin

Abstract Background: Chromatin physical interactions provide essential information for understanding the regulation of cis-elements like enhancers, promoters, and insulators in cell development and differentiation. The Hi-C assay is a technique detecting chromatin structures of the whole genome but not sensitive to interactions of regulatory elements. Several methods, like HiChIP, DNase-C, and OCEAN-C, have been developed for enriching interactions of regulatory regions, but all of them have some shortcomings. New simple, efficient, and robust methods are still in need of detecting interactions of regulatory regions. Results: We developed a new, simple, and robust assay called CoP (Column Purified chromatin) for profiling of open chromatin regions by directly purifying fragmentized crosslinked chromatin with a DNA purification column. The accessible chromatin regions, including active enhancers, promoters, and insulators, were significantly enriched in CoP chromatin. The CoP-seq assay can efficiently detect open chromatin regions, especially active promoters, with a high signal-to-noise ratio. We integrated the CoP-seq and Hi-C technique (HiCoP) for the detection of interactions of accessible chromatin regions, which represent active cis-regulatory elements in cells. We observed that the HiCoP captured the peaks in the promoters-associated enhancer regions, and the chromatin features identified by HiCoP were similar to HiChIP of histone H3K27 acetylation rather than Hi-C. HiCoP detected more promoter-enhancer (P-E), promoter-promoter (P-P), and enhancer-enhancer (E-E) interactions within 20kb-5Mb than Hi-C. Most of the loops identified by HiCoP were associated with the expressed genes. Conclusion: CoP assay can efficiently enrich open chromatin regions. When CoP assay was integrated with Hi-C assay, it provides a simple, robust, alternative technique for profiling accessible chromatin regions and chromatin conformation simultaneously.

scholarly journals HiCoP, a simple and robust method for detecting interactions of regulatory regions

2020 ◽  
Author(s):  
Yan Zhang ◽  
Zhaoqiang Li ◽  
Shasha Bian ◽  
Hao Zhao ◽  
Delong Feng ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Regulatory Elements ◽  
High Signal ◽  
Open Chromatin ◽  
Robust Methods ◽  
Regulatory Regions ◽  
Essential Information ◽  
Development And Differentiation ◽  
Physical Interactions ◽  
Accessible Chromatin

Abstract Background: Chromatin physical interactions provide essential information for understanding the regulation of cis-elements like enhancers, promoters, and insulators in cell development and differentiation. The Hi-C assay is a technique detecting chromatin structures of the whole genome but not sensitive to interactions of regulatory elements. Several methods, like HiChIP, DNase-C, and OCEAN-C, have been developed for enriching interactions of regulatory regions, but all of them have some shortcomings. New simple, efficient, and robust methods are still in need of detecting interactions of regulatory regions. Results: We developed a new, simple, and robust assay called CoP (Column Purified chromatin) for profiling of open chromatin regions by directly purifying fragmentized crosslinked chromatin with a DNA purification column. The accessible chromatin regions, including active enhancers, promoters, and insulators, were significantly enriched in CoP chromatin. The CoP-seq assay can efficiently detect open chromatin regions, especially active promoters, with a high signal-to-noise ratio. We integrated the CoP-seq and Hi-C technique (HiCoP) to detect interactions of accessible chromatin regions, which represent active cis-regulatory elements in cells. We observed that the HiCoP captured the peaks in the promoters-associated enhancer regions. HiCoP detected more promoter-enhancer (P-E), promoter-promoter (P-P), and enhancer-enhancer (E-E) interactions within 20kb-5Mb than Hi-C. Most of the loops identified by HiCoP are associated with the expressed genes. Conclusion: CoP assay can efficiently enrich open chromatin regions. When CoP assay was integrated with Hi-C assay, it provides a simple, robust, alternative technique for profiling accessible chromatin regions and chromatin conformation simultaneously.

scholarly journals Multi-omics-based prediction of hybrid performance in canola

2021 ◽  
Author(s):  
Dominic Knoch ◽  
Christian R. Werner ◽  
Rhonda C. Meyer ◽  
David Riewe ◽  
Amine Abbadi ◽  
...  
Keyword(s):  
Hilbert Space ◽  
Genetic Markers ◽  
Reproducing Kernel ◽  
Prediction Models ◽  
Agronomic Traits ◽  
Reproducing Kernel Hilbert Space ◽  
Hybrid Performance ◽  
Hybrid Prediction ◽  
Gaussian Kernels ◽  
Breeding Programmes

Abstract Key message Complementing or replacing genetic markers with transcriptomic data and use of reproducing kernel Hilbert space regression based on Gaussian kernels increases hybrid prediction accuracies for complex agronomic traits in canola. In plant breeding, hybrids gained particular importance due to heterosis, the superior performance of offspring compared to their inbred parents. Since the development of new top performing hybrids requires labour-intensive and costly breeding programmes, including testing of large numbers of experimental hybrids, the prediction of hybrid performance is of utmost interest to plant breeders. In this study, we tested the effectiveness of hybrid prediction models in spring-type oilseed rape (Brassica napus L./canola) employing different omics profiles, individually and in combination. To this end, a population of 950 F1 hybrids was evaluated for seed yield and six other agronomically relevant traits in commercial field trials at several locations throughout Europe. A subset of these hybrids was also evaluated in a climatized glasshouse regarding early biomass production. For each of the 477 parental rapeseed lines, 13,201 single nucleotide polymorphisms (SNPs), 154 primary metabolites, and 19,479 transcripts were determined and used as predictive variables. Both, SNP markers and transcripts, effectively predict hybrid performance using (genomic) best linear unbiased prediction models (gBLUP). Compared to models using pure genetic markers, models incorporating transcriptome data resulted in significantly higher prediction accuracies for five out of seven agronomic traits, indicating that transcripts carry important information beyond genomic data. Notably, reproducing kernel Hilbert space regression based on Gaussian kernels significantly exceeded the predictive abilities of gBLUP models for six of the seven agronomic traits, demonstrating its potential for implementation in future canola breeding programmes.

Transporters, TBC1D4, and ARID5B Variants to Explain Glycated Hemoglobin Variability in Patients with Type 2 Diabetes

Pharmacology ◽  
2021 ◽  
pp. 1-9
Author(s):  
Vanessa Gonzalez-Covarrubias ◽  
Héctor Sánchez-Ibarra ◽  
Karla Lozano-Gonzalez ◽  
Sergio Villicaña ◽  
Tomas Texis ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Glucose Control ◽  
Plasma Levels ◽  
Prediction Models ◽  
Glycated Hemoglobin ◽  
Clinical Chemistry ◽  
Diabetic Patients ◽  
Genetic Associations ◽  
Hemoglobin Variability

<b><i>Introduction:</i></b> Genetic variants could aid in predicting antidiabetic drug response by associating them with markers of glucose control, such as glycated hemoglobin (HbA1c). However, pharmacogenetic implementation for antidiabetics is still under development, as the list of actionable markers is being populated and validated. This study explores potential associations between genetic variants and plasma levels of HbA1c in 100 patients under treatment with metformin. <b><i>Methods:</i></b> HbA1c was measured in a clinical chemistry analyzer (Roche), genotyping was performed in an Illumina-GSA array and data were analyzed using PLINK. Association and prediction models were developed using R and a 10-fold cross-validation approach. <b><i>Results:</i></b> We identified genetic variants on <i>SLC47A1, SLC28A1, ABCG2, TBC1D4,</i> and <i>ARID5B</i> that can explain up to 55% of the interindividual variability of HbA1c plasma levels in diabetic patients under treatment. Variants on <i>SLC47A1</i>, <i>SLC28A1</i>, and <i>ABCG2</i> likely impact the pharmacokinetics (PK) of metformin, while the role of the two latter can be related to insulin resistance and regulation of adipogenesis. <b><i>Conclusions:</i></b> Our results confirm previous genetic associations and point to previously unassociated gene variants for metformin PK and glucose control.

scholarly journals Polygenic risk prediction models for colorectal cancer: a systematic review

BMC Cancer ◽  
2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Michele Sassano ◽  
Marco Mariani ◽  
Gianluigi Quaranta ◽  
Roberta Pastorino ◽  
Stefania Boccia
Keyword(s):  
Colorectal Cancer ◽  
Risk Factors ◽  
Systematic Review ◽  
Prediction Model ◽  
Risk Prediction ◽  
Genetic Variants ◽  
Prediction Models ◽  
Risk Prediction Models ◽  
Discriminatory Accuracy ◽  
Traditional Risk Factors

Abstract Background Risk prediction models incorporating single nucleotide polymorphisms (SNPs) could lead to individualized prevention of colorectal cancer (CRC). However, the added value of incorporating SNPs into models with only traditional risk factors is still not clear. Hence, our primary aim was to summarize literature on risk prediction models including genetic variants for CRC, while our secondary aim was to evaluate the improvement of discriminatory accuracy when adding SNPs to a prediction model with only traditional risk factors. Methods We conducted a systematic review on prediction models incorporating multiple SNPs for CRC risk prediction. We tested whether a significant trend in the increase of Area Under Curve (AUC) according to the number of SNPs could be observed, and estimated the correlation between AUC improvement and number of SNPs. We estimated pooled AUC improvement for SNP-enhanced models compared with non-SNP-enhanced models using random effects meta-analysis, and conducted meta-regression to investigate the association of specific factors with AUC improvement. Results We included 33 studies, 78.79% using genetic risk scores to combine genetic data. We found no significant trend in AUC improvement according to the number of SNPs (p for trend = 0.774), and no correlation between the number of SNPs and AUC improvement (p = 0.695). Pooled AUC improvement was 0.040 (95% CI: 0.035, 0.045), and the number of cases in the study and the AUC of the starting model were inversely associated with AUC improvement obtained when adding SNPs to a prediction model. In addition, models constructed in Asian individuals achieved better AUC improvement with the incorporation of SNPs compared with those developed among individuals of European ancestry. Conclusions Though not conclusive, our results provide insights on factors influencing discriminatory accuracy of SNP-enhanced models. Genetic variants might be useful to inform stratified CRC screening in the future, but further research is needed.

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