Genetic landscape of open chromatin in yeast

Broad compatibility between yeast UAS elements and core promoters and identification of promoter elements that determine cofactor specificity

Three classes of yeast protein-coding genes are distinguished by their dependence on the transcription cofactors TFIID, SAGA, and Mediator (MED) Tail, but whether this dependence is determined by the core promoter, upstream activating sequences (UASs), or other gene features is unclear. Also unclear is whether UASs can broadly activate transcription from the different promoter classes. Here, we measure transcription and cofactor specificity for thousands of UAS-core promoter combinations and find that most UASs broadly activate promoters regardless of regulatory class, while few display strong promoter specificity. However, matching UASs and promoters from the same gene class is generally important for optimal expression. We find that sensitivity to rapid depletion of MED Tail or SAGA is dependent on the identity of both UAS and core promoter, while dependence on TFIID localizes to only the promoter. Finally, our results suggest the role of TATA and TATA-like promoter sequences in MED Tail function.

ATAC-Seq Identifies Chromatin Landscapes Linked to the Regulation of Oxidative Stress in the Human Fungal Pathogen Candida albicans

Human fungal pathogens often encounter fungicidal stress upon host invasion, but they can swiftly adapt by transcriptional reprogramming that enables pathogen survival. Fungal immune evasion is tightly connected to chromatin regulation. Hence, fungal chromatin modifiers pose alternative treatment options to combat fungal infections. Here, we present an assay for transposase-accessible chromatin using sequencing (ATAC-seq) protocol adapted for the opportunistic pathogen Candida albicans to gain further insight into the interplay of chromatin accessibility and gene expression mounted during fungal adaptation to oxidative stress. The ATAC-seq workflow not only facilitates the robust detection of genomic regions with accessible chromatin but also allows for the precise modeling of nucleosome positions in C. albicans. Importantly, the data reveal genes with altered chromatin accessibility in upstream regulatory regions, which correlate with transcriptional regulation during oxidative stress. Interestingly, many genes show increased chromatin accessibility without change in gene expression upon stress exposure. Such chromatin signatures could predict yet unknown regulatory factors under highly dynamic transcriptional control. Additionally, de novo motif analysis in genomic regions with increased chromatin accessibility upon H2O2 treatment shows significant enrichment for Cap1 binding sites, a major factor of oxidative stress responses in C. albicans. Taken together, the ATAC-seq workflow enables the identification of chromatin signatures and highlights the dynamics of regulatory mechanisms mediating environmental adaptation of C. albicans.

Formaldehyde-assisted isolation of regulatory DNA elements from Arabidopsis leaves

Eukaryotic gene transcription is associated with the eviction of nucleosomes and the formation of open chromatin, which enables the recruitment of transcriptional coactivators and other regulatory factors. Open chromatin is thus a hallmark of functional regulatory DNA elements in genomes. In recent years, formaldehyde-assisted isolation of regulatory elements (FAIRE) has proven powerful in identifying open chromatin in the genome of various eukaryotes, particularly yeast, human, and mouse. However, it has proven challenging to adapt the FAIRE protocol for use on plant material, and the few available protocols all have their drawbacks (e.g., applicability only to specific developmental stages). In this Protocol Extension, we describe a reliable FAIRE protocol for mature Arabidopsis (Arabidopsis thaliana) leaves that adapts the original protocol for use on plants. The main differences between this protocol extension and the earlier FAIRE protocol are an increased formaldehyde concentration in the chromatin crosslinking buffer, application of a repeated vacuum to increase crosslinking efficiency, and altered composition of the DNA extraction buffer. The protocol is applicable to leaf chromatin of unstressed and stressed plants and can be completed within 1 week. Here, we also describe downstream analysis using qPCR and next-generation sequencing. However, this Protocol Extension should also be compatible with downstream hybridization to a DNA microarray. In addition, it is likely that only minor adaptations will be necessary to apply this protocol to other Arabidopsis organs or plant species.

A deep auto-encoder model for gene expression prediction

BACKGROUND

Gene expression is a key intermediate level that genotypes lead to a particular trait. Gene expression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on gene expression, we build a deep auto-encoder model to assess how good genetic variants will contribute to gene expression changes. This new deep learning model is a regression-based predictive model based on the MultiLayer Perceptron and Stacked Denoising Auto-encoder (MLP-SAE). The model is trained using a stacked denoising auto-encoder for feature selection and a multilayer perceptron framework for backpropagation. We further improve the model by introducing dropout to prevent overfitting and improve performance.

RESULTS

To demonstrate the usage of this model, we apply MLP-SAE to a real genomic datasets with genotypes and gene expression profiles measured in yeast. Our results show that the MLP-SAE model with dropout outperforms other models including Lasso, Random Forests and the MLP-SAE model without dropout. Using the MLP-SAE model with dropout, we show that gene expression quantifications predicted by the model solely based on genotypes, align well with true gene expression patterns.

CONCLUSION

We provide a deep auto-encoder model for predicting gene expression from SNP genotypes. This study demonstrates that deep learning is appropriate for tackling another genomic problem, i.e., building predictive models to understand genotypes' contribution to gene expression. With the emerging availability of richer genomic data, we anticipate that deep learning models play a bigger role in modeling and interpreting genomics.

The origin of Metazoa: a unicellular perspective

The first animals evolved from an unknown single-celled ancestor in the Precambrian period. Recently, the identification and characterization of the genomic and cellular traits of the protists most closely related to animals have shed light on the origin of animals. Comparisons of animals with these unicellular relatives allow us to reconstruct the first evolutionary steps towards animal multicellularity. Here, we review the results of these investigations and discuss their implications for understanding the earliest stages of animal evolution, including the origin of metazoan genes and genome function.

Predictive long-range allele-specific mapping of regulatory variants and target transcripts

Genome-wide association studies (GWASs) have identified a large number of noncoding associations, calling for systematic mapping to causal regulatory variants and their distal target genes. A widely used method, quantitative trait loci (QTL) mapping for chromatin or expression traits, suffers from sample-to-sample experimental variation and trans-acting or environmental effects. Instead, alleles at heterozygous loci can be compared within a sample, thereby controlling for those confounding factors. Here we introduce a method for chromatin structure-based allele-specific pairing of regulatory variants and target transcripts. With phased genotypes, much of allele-specific expression could be explained by paired allelic cis-regulation across a long range. This approach showed approximately two times greater sensitivity than QTL mapping. There are cases in which allele imbalance cannot be tested because heterozygotes are not available among reference samples. Therefore, we employed a machine learning method to predict missing positive cases based on various features shared by observed allele-specific pairs. We showed that only 10 reference samples are sufficient to achieve high prediction accuracy with a low sampling variation. In conclusion, our method enables highly sensitive fine mapping and target identification for trait-associated variants based on a small number of reference samples.

Intersection of genetics and epigenetics in monozygotic twin genomes

As a final function of various epigenetic mechanisms, chromatin regulation is a transcription control process that especially demonstrates active interaction with genetic elements. Thus, chromatin structure has become a principal focus in recent genomics researches that strive to characterize regulatory functions of DNA variants related to diseases or other traits. Although researchers have been focusing on DNA methylation when studying monozygotic (MZ) twins, a great model in epigenetics research, interactions between genetics and epigenetics in chromatin level are expected to be an imperative research trend in the future. In this review, we discuss how the genome, epigenome, and transcriptome of MZ twins can be studied in an integrative manner from this perspective.

Population perspectives on functional genomic variation in yeast

Advances in high-throughput sequencing have facilitated large-scale surveys of genomic variation in the budding yeast,Saccharomyces cerevisiae These surveys have revealed extensive sequence variation between yeast strains. However, much less is known about how such variation influences the amount and nature of variation for functional genomic traits within and between yeast lineages. We review population-level studies of functional genomic variation, with a particular focus on how population functional genomic approaches can provide insights into both genome function and the evolutionary process. Although variation in functional genomics phenotypes is pervasive, our understanding of the consequences of this variation, either in physiological or evolutionary terms, is still rudimentary and thus motivates increased attention to appropriate null models. To date, much of the focus of population functional genomic studies has been on gene expression variation, but other functional genomic data types are just as likely to reveal important insights at the population level, suggesting a pressing need for more studies that go beyond transcription. Finally, we discuss how a population functional genomic perspective can be a powerful approach for developing a mechanistic understanding of the processes that link genomic variation to organismal phenotypes through gene networks.

Genetic Architecture of Transcription and Chromatin Regulation

DNA microarray and next-generation sequencing provide data that can be used for the genetic analysis of multiple quantitative traits such as gene expression levels, transcription factor binding profiles, and epigenetic signatures. In particular, chromatin opening is tightly coupled with gene transcription. To understand how these two processes are genetically regulated and associated with each other, we examined the changes of chromatin accessibility and gene expression in response to genetic variation by means of quantitative trait loci mapping. Regulatory patterns commonly observed in yeast and human across different technical platforms and experimental designs suggest a higher genetic complexity of transcription regulation in contrast to a more robust genetic architecture of chromatin regulation.

Evolution and genetic architecture of chromatin accessibility and function in yeast

Chromatin accessibility is an important functional genomics phenotype that influences transcription factor binding and gene expression. Genome-scale technologies allow chromatin accessibility to be mapped with high-resolution, facilitating detailed analyses into the genetic architecture and evolution of chromatin structure within and between species. We performed Formaldehyde-Assisted Isolation of Regulatory Elements sequencing (FAIRE-Seq) to map chromatin accessibility in two parental haploid yeast species, Saccharomyces cerevisiae and Saccharomyces paradoxus and their diploid hybrid. We show that although broad-scale characteristics of the chromatin landscape are well conserved between these species, accessibility is significantly different for 947 regions upstream of genes that are enriched for GO terms such as intracellular transport and protein localization exhibit. We also develop new statistical methods to investigate the genetic architecture of variation in chromatin accessibility between species, and find that cis effects are more common and of greater magnitude than trans effects. Interestingly, we find that cis and trans effects at individual genes are often negatively correlated, suggesting widespread compensatory evolution to stabilize levels of chromatin accessibility. Finally, we demonstrate that the relationship between chromatin accessibility and gene expression levels is complex, and a significant proportion of differences in chromatin accessibility might be functionally benign.

Genetic factors underlying discordance in chromatin accessibility between monozygotic twins

BACKGROUND

Open chromatin is implicated in regulatory processes; thus, variations in chromatin structure may contribute to variations in gene expression and other phenotypes. In this work, we perform targeted deep sequencing for open chromatin, and array-based genotyping across the genomes of 72 monozygotic twins to identify genetic factors regulating co-twin discordance in chromatin accessibility.

RESULTS

We show that somatic mutations cause chromatin discordance mainly via the disruption of transcription factor binding sites. Structural changes in DNA due to C:G to A:T transversions are under purifying selection due to a strong impact on chromatin accessibility. We show that CpGs whose methylation is specifically regulated during cellular differentiation appear to be protected from high mutation rates of 5'-methylcytosines, suggesting that the spectrum of CpG variations may be shaped fully at the developmental level but not through natural selection. Based on the association mapping of within-pair chromatin differences, we search for cases in which twin siblings with a particular genotype had chromatin discordance at the relevant locus. We identify 1,325 chromatin sites that are differentially accessible, depending on the genotype of a nearby locus, suggesting that epigenetic differences can control regulatory variations via interactions with genetic factors. Poised promoters present high levels of chromatin discordance in association with either somatic mutations or genetic-epigenetic interactions.

CONCLUSION

Our observations illustrate how somatic mutations and genetic polymorphisms may contribute to regulatory, and ultimately phenotypic, discordance.

Mapping yeast transcriptional networks

The term “transcriptional network” refers to the mechanism(s) that underlies coordinated expression of genes, typically involving transcription factors (TFs) binding to the promoters of multiple genes, and individual genes controlled by multiple TFs. A multitude of studies in the last two decades have aimed to map and characterize transcriptional networks in the yeast Saccharomyces cerevisiae. We review the methodologies and accomplishments of these studies, as well as challenges we now face. For most yeast TFs, data have been collected on their sequence preferences, in vivo promoter occupancy, and gene expression profiles in deletion mutants. These systematic studies have led to the identification of new regulators of numerous cellular functions and shed light on the overall organization of yeast gene regulation. However, many yeast TFs appear to be inactive under standard laboratory growth conditions, and many of the available data were collected using techniques that have since been improved. Perhaps as a consequence, comprehensive and accurate mapping among TF sequence preferences, promoter binding, and gene expression remains an open challenge. We propose that the time is ripe for renewed systematic efforts toward a complete mapping of yeast transcriptional regulatory mechanisms.

Regulation of the boundaries of accessible chromatin

Regulatory regions maintain nucleosome-depleted, open chromatin status but simultaneously require the presence of nucleosomes for specific histone modifications. It remains unclear how these can be achieved for proper regulatory function. Here we demonstrate that nucleosomes positioned within accessible chromatin regions near the boundaries provide platforms for histone modifications while preventing the occlusion of regulatory elements. These boundary nucleosomes were particularly enriched for active or poised regulatory marks in human, such as histone acetylations, H3K4 methylations, H3K9me3, H3K79me2, and H4K20me1. Additionally, we found that based on a genome-wide profiling of ∼100 recombinant yeast strains, the location of open chromatin borders tends to vary mostly within 150 bp upon genetic perturbation whereas this positional variation increases in proportion to the sequence preferences of the underlying DNA for nucleosome formation. More than 40% of the local boundary shifts were associated with genetic variation in cis- or trans-acting factors. A sizeable fraction of the identified genetic factors was also associated with nearby gene expression, which was correlated with the distance between the transcription start site (tss) and the boundary that faces the tss. Taken together, the variation in the width of accessible chromatin regions may arise in conjunction with the modulation of the boundary nucleosomes by post-translational modifications or by chromatin regulators and in association with the activity of nearby gene transcription.

Open chromatin formation and regulation are intimately coupled with nucleosome remodelling and modification. Regulatory regions such as promoters and enhancers maintain nucleosome-free, open chromatin states whilst at the same time the presence of nucleosomes is required for specific histone modifications. In this work, we carried out detailed analyses of our data of open chromatin maps for ∼100 different yeast strains and whole-genome nucleosome occupancy along with the public data of open chromatin and nucleosome positioning in human generated in the ENCODE project. We observed nucleosomes positioned within accessible chromatin regions near their boundaries. These boundary nucleosomes appeared to carry various histone methylations without hampering the binding of DNA regulators and sequence preferences for these nucleosomes were associated with variation in the width of accessible chromatin. The end positions of open chromatin domains, particularly with high intrinsic preferences for nucleosome formation, were more flexible than the middle point, changing mostly within 150 bp upon genetic perturbation. By using quantitative trait loci (QTL) mapping, we identified genetic variants that are associated with the variation in the width of open chromatin and examined its relationship with nearby gene expression.