scholarly journals Cis-regulatory basis of sister cell type divergence in the vertebrate retina

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Daniel P Murphy ◽  
Andrew EO Hughes ◽  
Karen A Lawrence ◽  
Connie A Myers ◽  
Joseph C Corbo

Multicellular organisms evolved via repeated functional divergence of transcriptionally related sister cell types, but the mechanisms underlying sister cell type divergence are not well understood. Here, we study a canonical pair of sister cell types, retinal photoreceptors and bipolar cells, to identify the key cis-regulatory features that distinguish them. By comparing open chromatin maps and transcriptomic profiles, we found that while photoreceptor and bipolar cells have divergent transcriptomes, they share remarkably similar cis-regulatory grammars, marked by enrichment of K50 homeodomain binding sites. However, cell class-specific enhancers are distinguished by enrichment of E-box motifs in bipolar cells, and Q50 homeodomain motifs in photoreceptors. We show that converting K50 motifs to Q50 motifs represses reporter expression in bipolar cells, while photoreceptor expression is maintained. These findings suggest that partitioning of Q50 motifs within cell type-specific cis-regulatory elements was a critical step in the evolutionary divergence of the bipolar transcriptome from that of photoreceptors.

2019 ◽  
Author(s):  
Daniel Murphy ◽  
Andrew. E.O. Hughes ◽  
Karen A. Lawrence ◽  
Connie A. Myers ◽  
Joseph C. Corbo

AbstractMulticellular organisms evolved via repeated functional divergence of transcriptionally related sister cell types, but the mechanisms underlying sister cell type divergence are not well understood. Here, we study a canonical pair of sister cell types, retinal photoreceptors and bipolar cells, to identify the key cis-regulatory features that distinguish them. By comparing open chromatin maps and transcriptomic profiles, we found that while photoreceptor and bipolar cells have divergent transcriptomes, they share remarkably similar cis-regulatory grammars, marked by enrichment of K50 homeodomain binding sites. However, cell class-specific enhancers are distinguished by enrichment of E-box motifs in bipolar cells, and Q50 homeodomain motifs in photoreceptors. We show that converting K50 motifs to Q50 motifs represses reporter expression in bipolar cells, while photoreceptor expression is maintained. These findings suggest that partitioning of Q50 motifs within cell type-specific cis-regulatory elements was a critical step in the divergence of the bipolar transcriptome from that of photoreceptors.


2020 ◽  
Vol 29 (11) ◽  
pp. 1922-1932
Author(s):  
Priyanka Nandakumar ◽  
Dongwon Lee ◽  
Thomas J Hoffmann ◽  
Georg B Ehret ◽  
Dan Arking ◽  
...  

Abstract Hundreds of loci have been associated with blood pressure (BP) traits from many genome-wide association studies. We identified an enrichment of these loci in aorta and tibial artery expression quantitative trait loci in our previous work in ~100 000 Genetic Epidemiology Research on Aging study participants. In the present study, we sought to fine-map known loci and identify novel genes by determining putative regulatory regions for these and other tissues relevant to BP. We constructed maps of putative cis-regulatory elements (CREs) using publicly available open chromatin data for the heart, aorta and tibial arteries, and multiple kidney cell types. Variants within these regions may be evaluated quantitatively for their tissue- or cell-type-specific regulatory impact using deltaSVM functional scores, as described in our previous work. We aggregate variants within these putative CREs within 50 Kb of the start or end of ‘expressed’ genes in these tissues or cell types using public expression data and use deltaSVM scores as weights in the group-wise sequence kernel association test to identify candidates. We test for association with both BP traits and expression within these tissues or cell types of interest and identify the candidates MTHFR, C10orf32, CSK, NOV, ULK4, SDCCAG8, SCAMP5, RPP25, HDGFRP3, VPS37B and PPCDC. Additionally, we examined two known QT interval genes, SCN5A and NOS1AP, in the Atherosclerosis Risk in Communities Study, as a positive control, and observed the expected heart-specific effect. Thus, our method identifies variants and genes for further functional testing using tissue- or cell-type-specific putative regulatory information.


2020 ◽  
Vol 117 (45) ◽  
pp. 28422-28432
Author(s):  
Alexey Kozlenkov ◽  
Marit W. Vermunt ◽  
Pasha Apontes ◽  
Junhao Li ◽  
Ke Hao ◽  
...  

The human cerebral cortex contains many cell types that likely underwent independent functional changes during evolution. However, cell-type–specific regulatory landscapes in the cortex remain largely unexplored. Here we report epigenomic and transcriptomic analyses of the two main cortical neuronal subtypes, glutamatergic projection neurons and GABAergic interneurons, in human, chimpanzee, and rhesus macaque. Using genome-wide profiling of the H3K27ac histone modification, we identify neuron-subtype–specific regulatory elements that previously went undetected in bulk brain tissue samples. Human-specific regulatory changes are uncovered in multiple genes, including those associated with language, autism spectrum disorder, and drug addiction. We observe preferential evolutionary divergence in neuron subtype-specific regulatory elements and show that a substantial fraction of pan-neuronal regulatory elements undergoes subtype-specific evolutionary changes. This study sheds light on the interplay between regulatory evolution and cell-type–dependent gene-expression programs, and provides a resource for further exploration of human brain evolution and function.


2019 ◽  
Author(s):  
Priyanka Nandakumar ◽  
Dongwon Lee ◽  
Thomas J. Hoffmann ◽  
Georg B. Ehret ◽  
Dan Arking ◽  
...  

AbstractHundreds of loci have been associated with blood pressure traits from many genome-wide association studies. We identified an enrichment of these loci in aorta and tibial artery expression quantitative trait loci in our previous work in ∼100,000 Genetic Epidemiology Research on Aging (GERA) study participants. In the present study, we subsequently focused on determining putative regulatory regions for these and other tissues of relevance to blood pressure, to both fine-map these loci by pinpointing genes and variants of functional interest within them, and to identify any novel genes.We constructed maps of putative cis-regulatory elements using publicly available open chromatin data for the heart, aorta and tibial arteries, and multiple kidney cell types. Sequence variants within these regions may be evaluated quantitatively for their tissue- or cell-type-specific regulatory impact using deltaSVM functional scores, as described in our previous work. In order to identify genes of interest, we aggregate these variants in these putative cis-regulatory elements within 50Kb of the start or end of genes considered as “expressed” in these tissues or cell types using publicly available gene expression data, and use the deltaSVM scores as weights in the well-known group-wise sequence kernel association test (SKAT). We test for association with both blood pressure traits as well as expression within these tissues or cell types of interest, and identify several genes, including MTHFR, C10orf32, CSK, NOV, ULK4, SDCCAG8, SCAMP5, RPP25, HDGFRP3, VPS37B, and PPCDC. Although our study centers on blood pressure traits, we additionally examined two known genes, SCN5A and NOS1AP involved in the cardiac trait QT interval, in the Atherosclerosis Risk in Communities Study (ARIC), as a positive control, and observed an expected heart-specific effect. Thus, our method may be used to identify variants and genes for further functional testing using tissue- or cell-type-specific putative regulatory information.Author SummarySequence change in genes (“variants”) are linked to the presence and severity of different traits or diseases. However, as genes may be expressed in different tissues and at different times and degrees, using this information is expected to more accurately identify genes of interest. Variants within the genes are essential, but also in the sequences (“regulatory elements”) that control the genes’ expression in different tissues or cell types. In this study, we aim to use this information about expression and variants potentially involved in gene expression regulation to better pinpoint genes and variants in regulatory elements of interest for blood pressure regulation. We do so by taking advantage of such data that are publicly available, and use methods to combine information about variants in aggregate within a gene’s putative regulatory elements in tissues thought to be relevant for blood pressure, and identify several genes, meant to enable experimental follow-up.


Author(s):  
Hanqing Liu ◽  
Jingtian Zhou ◽  
Wei Tian ◽  
Chongyuan Luo ◽  
Anna Bartlett ◽  
...  

SummaryMammalian brain cells are remarkably diverse in gene expression, anatomy, and function, yet the regulatory DNA landscape underlying this extensive heterogeneity is poorly understood. We carried out a comprehensive assessment of the epigenomes of mouse brain cell types by applying single nucleus DNA methylation sequencing to profile 110,294 nuclei from 45 regions of the mouse cortex, hippocampus, striatum, pallidum, and olfactory areas. We identified 161 cell clusters with distinct spatial locations and projection targets. We constructed taxonomies of these epigenetic types, annotated with signature genes, regulatory elements, and transcription factors. These features indicate the potential regulatory landscape supporting the assignment of putative cell types, and reveal repetitive usage of regulators in excitatory and inhibitory cells for determining subtypes. The DNA methylation landscape of excitatory neurons in the cortex and hippocampus varied continuously along spatial gradients. Using this deep dataset, an artificial neural network model was constructed that precisely predicts single neuron cell-type identity and brain area spatial location. Integration of high-resolution DNA methylomes with single-nucleus chromatin accessibility data allowed prediction of high-confidence enhancer-gene interactions for all identified cell types, which were subsequently validated by cell-type-specific chromatin conformation capture experiments. By combining multi-omic datasets (DNA methylation, chromatin contacts, and open chromatin) from single nuclei and annotating the regulatory genome of hundreds of cell types in the mouse brain, our DNA methylation atlas establishes the epigenetic basis for neuronal diversity and spatial organization throughout the mouse brain.


Author(s):  
Zhen Miao ◽  
Michael S. Balzer ◽  
Ziyuan Ma ◽  
Hongbo Liu ◽  
Junnan Wu ◽  
...  

AbstractDetermining the epigenetic program that generates unique cell types in the kidney is critical for understanding cell-type heterogeneity during tissue homeostasis and injury response.Here, we profiled open chromatin and gene expression in developing and adult mouse kidneys at single cell resolution. We show critical reliance of gene expression on distal regulatory elements (enhancers). We define key cell type-specific transcription factors and major gene-regulatory circuits for kidney cells. Dynamic chromatin and expression changes during nephron progenitor differentiation demonstrated that podocyte commitment occurs early and is associated with sustained Foxl1 expression. Renal tubule cells followed a more complex differentiation, where Hfn4a was associated with proximal and Tfap2b with distal fate. Mapping single nucleotide variants associated with human kidney disease identified critical cell types, developmental stages, genes, and regulatory mechanisms.We provide a global single cell resolution view of chromatin accessibility of kidney development. The dataset is available via interactive public websites.


Nature ◽  
2021 ◽  
Vol 598 (7879) ◽  
pp. 120-128 ◽  
Author(s):  
Hanqing Liu ◽  
Jingtian Zhou ◽  
Wei Tian ◽  
Chongyuan Luo ◽  
Anna Bartlett ◽  
...  

AbstractMammalian brain cells show remarkable diversity in gene expression, anatomy and function, yet the regulatory DNA landscape underlying this extensive heterogeneity is poorly understood. Here we carry out a comprehensive assessment of the epigenomes of mouse brain cell types by applying single-nucleus DNA methylation sequencing1,2 to profile 103,982 nuclei (including 95,815 neurons and 8,167 non-neuronal cells) from 45 regions of the mouse cortex, hippocampus, striatum, pallidum and olfactory areas. We identified 161 cell clusters with distinct spatial locations and projection targets. We constructed taxonomies of these epigenetic types, annotated with signature genes, regulatory elements and transcription factors. These features indicate the potential regulatory landscape supporting the assignment of putative cell types and reveal repetitive usage of regulators in excitatory and inhibitory cells for determining subtypes. The DNA methylation landscape of excitatory neurons in the cortex and hippocampus varied continuously along spatial gradients. Using this deep dataset, we constructed an artificial neural network model that precisely predicts single neuron cell-type identity and brain area spatial location. Integration of high-resolution DNA methylomes with single-nucleus chromatin accessibility data3 enabled prediction of high-confidence enhancer–gene interactions for all identified cell types, which were subsequently validated by cell-type-specific chromatin conformation capture experiments4. By combining multi-omic datasets (DNA methylation, chromatin contacts, and open chromatin) from single nuclei and annotating the regulatory genome of hundreds of cell types in the mouse brain, our DNA methylation atlas establishes the epigenetic basis for neuronal diversity and spatial organization throughout the mouse cerebrum.


Author(s):  
Chaitanya Srinivasan ◽  
BaDoi N. Phan ◽  
Alyssa J. Lawler ◽  
Easwaran Ramamurthy ◽  
Michael Kleyman ◽  
...  

ABSTRACTRecent large genome-wide association studies (GWAS) have identified multiple confident risk loci linked to addiction-associated behavioral traits. Genetic variants linked to addiction-associated traits lie largely in non-coding regions of the genome, likely disrupting cis-regulatory element (CRE) function. CREs tend to be highly cell type-specific and may contribute to the functional development of the neural circuits underlying addiction. Yet, a systematic approach for predicting the impact of risk variants on the CREs of specific cell populations is lacking. To dissect the cell types and brain regions underlying addiction-associated traits, we applied LD score regression to compare GWAS to genomic regions collected from human and mouse assays for open chromatin, which is associated with CRE activity. We found enrichment of addiction-associated variants in putative regulatory elements marked by open chromatin in neuronal (NeuN+) nuclei collected from multiple prefrontal cortical areas and striatal regions known to play major roles in reward and addiction. To further dissect the cell type-specific basis of addiction-associated traits, we also identified enrichments in human orthologs of open chromatin regions of mouse neuron subtypes: cortical excitatory, PV, D1, and D2. Lastly, we developed machine learning models from mouse cell type-specific regions of open chromatin to further dissect human NeuN+ open chromatin regions into cortical excitatory or striatal D1 and D2 neurons and predict the functional impact of addiction-associated genetic variants. Our results suggest that different neuron subtypes within the reward system play distinct roles in the variety of traits that contribute to addiction.Significance StatementOur study on cell types and brain regions contributing to heritability of addiction-associated traits suggests that the conserved non-coding regions within cortical excitatory and striatal medium spiny neurons contribute to genetic predisposition for nicotine, alcohol, and cannabis use behaviors. This computational framework can flexibly integrate epigenomic data across species to screen for putative causal variants in a cell type- and tissue-specific manner across numerous complex traits.


2021 ◽  
Author(s):  
Kai Zhang ◽  
James D. Hocker ◽  
Michael Miller ◽  
Xiaomeng Hou ◽  
Joshua Chiou ◽  
...  

SUMMARYCurrent catalogs of regulatory sequences in the human genome are still incomplete and lack cell type resolution. To profile the activity of human gene regulatory elements in diverse cell types and tissues in the human body, we applied single cell chromatin accessibility assays to 25 distinct human tissue types from multiple donors. The resulting chromatin maps comprising ∼500,000 nuclei revealed the status of open chromatin for over 750,000 candidate cis-regulatory elements (cCREs) in 54 distinct cell types. We further delineated cell type-specific and tissue-context dependent gene regulatory programs, and developmental stage specificity by comparing with a recent human fetal chromatin accessibility atlas. We finally used these chromatin maps to interpret the noncoding variants associated with complex human traits and diseases. This rich resource provides a foundation for the analysis of gene regulatory programs in human cell types across tissues and organ systems.


2017 ◽  
Author(s):  
Kelsey A. Maher ◽  
Marko Bajic ◽  
Kaisa Kajala ◽  
Mauricio Reynoso ◽  
Germain Pauluzzi ◽  
...  

ABSTRACTThe transcriptional regulatory structure of plant genomes remains poorly defined relative to animals. It is unclear how many cis-regulatory elements exist, where these elements lie relative to promoters, and how these features are conserved across plant species. We employed the Assay for Transposase-Accessible Chromatin (ATAC-seq) in four plant species (Arabidopsis thaliana, Medicago truncatula, Solanum lycopersicum, and Oryza sativa) to delineate open chromatin regions and transcription factor (TF) binding sites across each genome. Despite 10-fold variation in intergenic space among species, the majority of open chromatin regions lie within 3 kb upstream of a transcription start site in all species. We find a common set of four TFs that appear to regulate conserved gene sets in the root tips of all four species, suggesting that TF-gene networks are generally conserved. Comparative ATAC-seq profiling of Arabidopsis root hair and non-hair cell types revealed extensive similarity as well as many cell type-specific differences. Analyzing TF binding sites in differentially accessible regions identified a MYB-driven regulatory module unique to the hair cell, which appears to control both cell fate regulators and abiotic stress responses. Our analyses revealed common regulatory principles among species and shed light on the mechanisms producing cell type-specific transcriptomes during development.


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