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Gene regulatory divergence between species can result from cis-acting local changes to regulatory element DNA sequences or global trans-acting changes to the regulatory environment. Understanding how these mechanisms drive regulatory evolution has been limited by challenges in identifying trans-acting changes. We present a comprehensive approach to directly identify cis- and trans-divergent regulatory elements between human and rhesus macaque lymphoblastoid cells using assay for transposase-accessible chromatin coupled to self-transcribing active regulatory region (ATAC-STARR) sequencing. In addition to thousands of cis changes, we discover an unexpected number (∼10,000) of trans changes and show that cis and trans elements exhibit distinct patterns of sequence divergence and function. We further identify differentially expressed transcription factors that underlie ∼37% of trans differences and trace how cis changes can produce cascades of trans changes. Overall, we find that most divergent elements (67%) experienced changes in both cis and trans, revealing a substantial role for trans divergence-alone and together with cis changes-in regulatory differences between species.

Phenotypic variation among species is a product of evolutionary changes to developmental programs1,2. However, how these changes generate novel morphological traits remains largely unclear. Here we studied the genomic and developmental basis of the mammalian gliding membrane, or patagium-an adaptative trait that has repeatedly evolved in different lineages, including in closely related marsupial species. Through comparative genomic analysis of 15 marsupial genomes, both from gliding and non-gliding species, we find that the Emx2 locus experienced lineage-specific patterns of accelerated cis-regulatory evolution in gliding species. By combining epigenomics, transcriptomics and in-pouch marsupial transgenics, we show that Emx2 is a critical upstream regulator of patagium development. Moreover, we identify different cis-regulatory elements that may be responsible for driving increased Emx2 expression levels in gliding species. Lastly, using mouse functional experiments, we find evidence that Emx2 expression patterns in gliders may have been modified from a pre-existing program found in all mammals. Together, our results suggest that patagia repeatedly originated through a process of convergent genomic evolution, whereby regulation of Emx2 was altered by distinct cis-regulatory elements in independently evolved species. Thus, different regulatory elements targeting the same key developmental gene may constitute an effective strategy by which natural selection has harnessed regulatory evolution in marsupial genomes to generate phenotypic novelty.

Adaptation to extreme environments often involves the evolution of dramatic physiological changes. To better understand how organisms evolve these complex phenotypic changes, the repeatability and predictability of evolution, and possible constraints on adapting to an extreme environment, it is important to understand how adaptive variation has evolved. Poeciliid fishes represent a particularly fruitful study system for investigations of adaptation to extreme environments due to their repeated colonization of toxic hydrogen sulfide-rich springs across multiple species within the clade. Previous investigations have highlighted changes in the physiology and gene expression in specific species that are thought to facilitate adaptation to hydrogen sulfide-rich springs. However, the presence of adaptive nucleotide variation in coding and regulatory regions and the degree to which convergent evolution has shaped the genomic regions underpinning sulfide tolerance across taxa are unknown. By sampling across seven independent lineages in which nonsulfidic lineages have colonized and adapted to sulfide springs, we reveal signatures of shared evolutionary rate shifts across the genome. We found evidence of genes, promoters, and putative enhancer regions associated with both increased and decreased convergent evolutionary rate shifts in hydrogen sulfide-adapted lineages. Our analysis highlights convergent evolutionary rate shifts in sulfidic lineages associated with the modulation of endogenous hydrogen sulfide production and hydrogen sulfide detoxification. We also found that regions with shifted evolutionary rates in sulfide spring fishes more often exhibited convergent shifts in either the coding region or the regulatory sequence of a given gene, rather than both.

Transcriptional silencing in Saccharomyces cerevisiae involves the generation of a chromatin state that stably represses transcription. Using multiple reporter assays, a diverse set of upstream activating sequence enhancers and core promoters were investigated for their susceptibility to silencing. We show that heterochromatin stably silences only weak and stress-induced regulatory elements but is unable to stably repress housekeeping gene regulatory elements, and the partial repression of these elements did not result in bistable expression states. Permutation analysis of enhancers and promoters indicates that both elements are targets of repression. Chromatin remodelers help specific regulatory elements to resist repression, most probably by altering nucleosome mobility and changing transcription burst duration. The strong enhancers/promoters can be repressed if silencer-bound Sir1 is increased. Together, our data suggest that the heterochromatic locus has been optimized to stably silence the weak mating-type gene regulatory elements but not strong housekeeping gene regulatory sequences.

Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 open chromatin regions, including thousands of sequences with cell type-specific accessibility and variants associated with brain gene regulation. In primary cells, we identified 46,802 active enhancer sequences and 164 variants that alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.

BACKGROUND: A number of deep learning models have been developed to predict epigenetic features such as chromatin accessibility from DNA sequence. Model evaluations commonly report performance genome-wide; however, cis regulatory elements (CREs), which play critical roles in gene regulation, make up only a small fraction of the genome. Furthermore, cell type-specific CREs contain a large proportion of complex disease heritability. RESULTS: We evaluate genomic deep learning models in chromatin accessibility regions with varying degrees of cell type specificity. We assess two modeling directions in the field: general purpose models trained across thousands of outputs (cell types and epigenetic marks) and models tailored to specific tissues and tasks. We find that the accuracy of genomic deep learning models, including two state-of-the-art general purpose models-Enformer and Sei-varies across the genome and is reduced in cell type-specific accessible regions. Using accessibility models trained on cell types from specific tissues, we find that increasing model capacity to learn cell type-specific regulatory syntax-through single-task learning or high capacity multi-task models-can improve performance in cell type-specific accessible regions. We also observe that improving reference sequence predictions does not consistently improve variant effect predictions, indicating that novel strategies are needed to improve performance on variants. CONCLUSIONS: Our results provide a new perspective on the performance of genomic deep learning models, showing that performance varies across the genome and is particularly reduced in cell type-specific accessible regions. We also identify strategies to maximize performance in cell type-specific accessible regions.

The genetic basis of human facial variation and craniofacial birth defects remains poorly understood. Distant-acting transcriptional enhancers control the fine-tuned spatiotemporal expression of genes during critical stages of craniofacial development. However, a lack of accurate maps of the genomic locations and cell type-resolved activities of craniofacial enhancers prevents their systematic exploration in human genetics studies. Here, we combine histone modification, chromatin accessibility, and gene expression profiling of human craniofacial development with single-cell analyses of the developing mouse face to define the regulatory landscape of facial development at tissue- and single cell-resolution. We provide temporal activity profiles for 14,000 human developmental craniofacial enhancers. We find that 56% of human craniofacial enhancers share chromatin accessibility in the mouse and we provide cell population- and embryonic stage-resolved predictions of their in vivo activity. Taken together, our data provide an expansive resource for genetic and developmental studies of human craniofacial development.

Mechanisms underlying phenotypic divergence across species remain unresolved. In this issue of Cell Genomics, Hansen, Fong, et al.1 systematically dissect human and rhesus macaque gene expression divergence by screening tens of thousands of orthologous elements for enhancer activity in lymphoblastoid cell lines, revealing a much greater role for trans divergence at levels equal to those of cis effects, counter to the prevailing consensus in the field.

CD8+ T cells provide host protection against pathogens by differentiating into distinct effector and memory cell subsets, but how chromatin is site-specifically remodeled during their differentiation is unclear. Due to its critical role in regulating chromatin and enhancer accessibility through its nucleosome remodeling activities, we investigated the role of the canonical BAF (cBAF) chromatin remodeling complex in antiviral CD8+ T cells during infection. ARID1A, a subunit of cBAF, was recruited early after activation and established de novo open chromatin regions (OCRs) at enhancers. Arid1a deficiency impaired the opening of thousands of activation-induced enhancers, leading to loss of TF binding, dysregulated proliferation and gene expression, and failure to undergo terminal effector differentiation. Although Arid1a was dispensable for circulating memory cell formation, tissue-resident memory (Trm) formation was strongly impaired. Thus, cBAF governs the enhancer landscape of activated CD8+ T cells that orchestrates TF recruitment and activity and the acquisition of specific effector and memory differentiation states.

The recent clinical and commercial success of lipid nanoparticles (LNPs) for nucleic acid delivery has incentivized the development of new technologies to manufacture LNPs. As new technologies emerge, researchers must determine which technologies to assess and how to perform comparative evaluations. In this article, we use a quality-by-design approach to systematically investigate how the mixer technology used to form LNPs influences LNPstructure. Specifically, a coaxial turbulent jet mixer and a staggered herringbone microfluidic mixer were systematically compared via matched formulation and process conditions. A full-factorial design-of-experiments study with three factors and three levels was executed for each mixer to compare process robustness in the production of antisense oligonucleotide (ASO) LNPs. ASO-LNPs generated with the coaxial turbulent jet mixer were consistently smaller, had a narrower particle size distribution, and had a higher ASO encapsulation as compared to the microfluidic mixer, but had a greater variation in internal structure with less ordered cores. A subset of the study was replicated for mRNA-LNPs with comparable trends in particle size and encapsulation, but more frequent bleb features for LNPs produced by the coaxial turbulent jet mixer. The study design used here provides a road map for how researchers may compare different mixer technologies (or process changes more broadly) and how such studies can inform process robustness and manufacturing control strategies.

Cis-regulatory elements (CREs) can be classified by the shapes of their transcription start site (TSS) profiles, which are indicative of distinct regulatory mechanisms. Massively parallel reporter assays (MPRAs) are increasingly being used to study CRE regulatory mechanisms, yet the degree to which MPRAs replicate individual endogenous TSS profiles has not been determined. Here, we present a new low-input MPRA protocol (TSS-MPRA) that enables measuring TSS profiles of episomal reporters as well as after lentiviral reporter chromatinization. To sensitively compare MPRA and endogenous TSS profiles, we developed a novel dissimilarity scoring algorithm (WIP score) that outperforms the frequently used earth movers distance on experimental data. Using TSS-MPRA and WIP scoring on 500 unique reporter inserts, we found that short (153 bp) MPRA promoter inserts replicate the endogenous TSS patterns of ∼60% of promoters. Lentiviral reporter chromatinization did not improve fidelity of TSS-MPRA initiation patterns, and increasing insert size frequently led to activation of extraneous TSS in the MPRA that are not active in vivo. We discuss the implications of our findings, which highlight important caveats when using MPRAs to study transcription mechanisms. Finally, we illustrate how TSS-MPRA and WIP scoring can provide novel insights into the impact of transcription factor motif mutations and genetic variants on TSS patterns and transcription levels.

Postnatal cell fate is postulated to be primarily determined by the local tissue microenvironment. Here, we find that Mediator 1 (Med1) dependent epigenetic mechanisms dictate tissue-specific lineage commitment and progression of dental epithelia. Deletion of Med1, a key component of the Mediator complex linking enhancer activities to gene transcription, provokes a tissue extrinsic lineage shift, causing hair generation in incisors. Med1 deficiency gives rise to unusual hair growth via primitive cellular aggregates. Mechanistically, we find that MED1 establishes super-enhancers that control enamel lineage transcription factors in dental stem cells and their progenies. However, Med1 deficiency reshapes the enhancer landscape and causes a switch from the dental transcriptional program towards hair and epidermis on incisors in vivo, and in dental epithelial stem cells in vitro. Med1 loss also provokes an increase in the number and size of enhancers. Interestingly, control dental epithelia already exhibit enhancers for hair and epidermal key transcription factors; these transform into super-enhancers upon Med1 loss suggesting that these epigenetic mechanisms cause the shift towards epidermal and hair lineages. Thus, we propose a role for Med1 in safeguarding lineage specific enhancers, highlight the central role of enhancer accessibility in lineage reprogramming and provide insights into ectodermal regeneration.

The vast majority of disease-associated single nucleotide polymorphisms (SNP) identified from genome-wide association studies (GWAS) are localized in non-coding regions. A significant fraction of these variants impact transcription factors binding to enhancer elements and alter gene expression. To functionally interrogate the activity of such variants we developed snpSTARRseq, a high-throughput experimental method that can interrogate the functional impact of hundreds to thousands of non-coding variants on enhancer activity. snpSTARRseq dramatically improves signal-to-noise by utilizing a novel sequencing and bioinformatic approach that increases both insert size and the number of variants tested per loci. Using this strategy, we interrogated known prostate cancer (PCa) risk-associated loci and demonstrated that 35% of them harbor SNPs that significantly altered enhancer activity. Combining these results with chromosomal looping data we could identify interacting genes and provide a mechanism of action for 20 PCa GWAS risk regions. When benchmarked to orthogonal methods, snpSTARRseq showed a strong correlation with in vivo experimental allelic-imbalance studies whereas there was no correlation with predictive in silico approaches. Overall, snpSTARRseq provides an integrated experimental and computational framework to functionally test non-coding genetic variants.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy in need of new therapeutic options. Using unbiased analyses of super-enhancers (SEs) as sentinels of core genes involved in cell-specific function, here we uncover a druggable SE-mediated RNA-binding protein (RBP) cascade that supports PDAC growth through enhanced mRNA translation. This cascade is driven by a SE associated with the RBP heterogeneous nuclear ribonucleoprotein F, which stabilizes protein arginine methyltransferase 1 (PRMT1) to, in turn, control the translational mediator ubiquitin-associated protein 2-like. All three of these genes and the regulatory SE are essential for PDAC growth and coordinately regulated by the Myc oncogene. In line with this, modulation of the RBP network by PRMT1 inhibition reveals a unique vulnerability in Myc-high PDAC patient organoids and markedly reduces tumor growth in male mice. Our study highlights a functional link between epigenetic regulation and mRNA translation and identifies components that comprise unexpected therapeutic targets for PDAC.

The discovery of cancer driver mutations is a fundamental goal in cancer research. While many cancer driver mutations have been discovered in the protein-coding genome, research into potential cancer drivers in the non-coding regions showed limited success so far. Here, we present a novel comprehensive framework Dr.Nod for detection of non-coding cis-regulatory candidate driver mutations that are associated with dysregulated gene expression using tissue-matched enhancer-gene annotations. Applying the framework to data from over 1500 tumours across eight tissues revealed a 4.4-fold enrichment of candidate driver mutations in regulatory regions of known cancer driver genes. An overarching conclusion that emerges is that the non-coding driver mutations contribute to cancer by significantly altering transcription factor binding sites, leading to upregulation of tissue-matched oncogenes and down-regulation of tumour-suppressor genes. Interestingly, more than half of the detected cancer-promoting non-coding regulatory driver mutations are over 20 kb distant from the cancer-associated genes they regulate. Our results show the importance of tissue-matched enhancer-gene maps, functional impact of mutations, and complex background mutagenesis model for the prediction of non-coding regulatory drivers. In conclusion, our study demonstrates that non-coding mutations in enhancers play a previously underappreciated role in cancer and dysregulation of clinically relevant target genes.

Although plastid genome (plastome) structure is highly conserved across most seed plants, investigations during the past two decades have revealed several disparately related lineages that experienced substantial rearrangements. Most plastomes contain a large inverted repeat and two single-copy regions, and a few dispersed repeats; however, the plastomes of some taxa harbour long repeat sequences (>300 bp). These long repeats make it challenging to assemble complete plastomes using short-read data, leading to misassemblies and consensus sequences with spurious rearrangements. Single-molecule, long-read sequencing has the potential to overcome these challenges, yet there is no consensus on the most effective method for accurately assembling plastomes using long-read data. We generated a pipeline, plastid Genome Assembly Using Long-read data (ptGAUL), to address the problem of plastome assembly using long-read data from Oxford Nanopore Technologies (ONT) or Pacific Biosciences platforms. We demonstrated the efficacy of the ptGAUL pipeline using 16 published long-read data sets. We showed that ptGAUL quickly produces accurate and unbiased assemblies using only ~50× coverage of plastome data. Additionally, we deployed ptGAUL to assemble four new Juncus (Juncaceae) plastomes using ONT long reads. Our results revealed many long repeats and rearrangements in Juncus plastomes compared with basal lineages of Poales. The ptGAUL pipeline is available on GitHub: https://github.com/Bean061/ptgaul.

Transcriptional regulation exhibits extensive robustness, but human genetics indicates sensitivity to transcription factor (TF) dosage. Reconciling such observations requires quantitative studies of TF dosage effects at trait-relevant ranges, largely lacking so far. TFs play central roles in both normal-range and disease-associated variation in craniofacial morphology; we therefore developed an approach to precisely modulate TF levels in human facial progenitor cells and applied it to SOX9, a TF associated with craniofacial variation and disease (Pierre Robin sequence (PRS)). Most SOX9-dependent regulatory elements (REs) are buffered against small decreases in SOX9 dosage, but REs directly and primarily regulated by SOX9 show heightened sensitivity to SOX9 dosage; these RE responses partially predict gene expression responses. Sensitive REs and genes preferentially affect functional chondrogenesis and PRS-like craniofacial shape variation. We propose that such REs and genes underlie the sensitivity of specific phenotypes to TF dosage, while buffering of other genes leads to robust, nonlinear dosage-to-phenotype relationships.

A comprehensive characterization of regulatory elements in the chicken genome across tissues will have substantial impacts on both fundamental and applied research. Here, we systematically identified and characterized regulatory elements in the chicken genome by integrating 377 genome-wide sequencing datasets from 23 adult tissues. In total, we annotated 1.57 million regulatory elements, representing 15 distinct chromatin states, and predicted about 1.2 million enhancer-gene pairs and 7662 super-enhancers. This functional annotation of the chicken genome should have wide utility on identifying regulatory elements accounting for gene regulation underlying domestication, selection, and complex trait regulation, which we explored. In short, this comprehensive atlas of regulatory elements provides the scientific community with a valuable resource for chicken genetics and genomics.

MicroRNAs (miRs) may contribute to disease etiology by influencing gene expression. Numerous databases are available for miR target prediction and validation, but their functionality is varied, and outputs are not standardized. The purpose of this review is to identify and describe databases for cataloging validated miR targets. Using Tools4miRs and PubMed, we identified databases with experimentally validated targets, human data, and a focus on miR-messenger RNA (mRNA) interactions. Data were extracted about the number of times each database was cited, the number of miRs, the target genes, the interactions per database, experimental methodology and key features of each database. The search yielded 10 databases, which in order of most cited to least were: miRTarBase, starBase/The Encyclopedia of RNA Interactomes, DIANA-TarBase, miRWalk, miRecords, miRGator, miRSystem, miRGate, miRSel and targetHub. Findings from this review suggest that the information presented within miR target validation databases can be enhanced by adding features such as flexibility in performing queries in multiple ways, downloadable data, ongoing updates and integrating tools for further miR-mRNA target interaction analysis. This review is designed to aid researchers, especially those new to miR bioinformatics tools, in database selection and to offer considerations for future development and upkeep of validation tools. Database URL http://mirtarbase.cuhk.edu.cn/.

The function of regulatory elements is highly dependent on the cellular context, and thus for understanding the function of elements associated with psychiatric diseases these would ideally be studied in neurons in a living brain. Massively Parallel Reporter Assays (MPRAs) are molecular genetic tools that enable functional screening of hundreds of predefined sequences in a single experiment. These assays have not yet been adapted to query specific cell types in vivo in a complex tissue like the mouse brain. Here, using a test-case 3UTR MPRA library with genomic elements containing variants from autism patients, we developed a method to achieve reproducible measurements of element effects in vivo in a cell type-specific manner, using excitatory cortical neurons and striatal medium spiny neurons as test cases. This targeted technique should enable robust, functional annotation of genetic elements in the cellular contexts most relevant to psychiatric disease.

We previously reported Paired-Tag, a combinatorial indexing-based method that can simultaneously map histone modifications and gene expression at single-cell resolution at scale. However, the lengthy procedure of Paired-Tag has hindered its general adoption in the community. To address this bottleneck, we developed a droplet-based Paired-Tag protocol that is faster and more accessible than the previous method. Using cultured mammalian cells and primary brain tissues, we demonstrate its superior performance at identifying candidate cis-regulatory elements and associating their dynamic chromatin state to target gene expression in each constituent cell type in a complex tissue.

BackgroundEnhancers are essential in defining cell fates through the control of cell-type-specific gene expression. Enhancer activation is a multi-step process involving chromatin remodelers and histone modifiers including the monomethylation of H3K4 (H3K4me1) by MLL3 (KMT2C) and MLL4 (KMT2D). MLL3/4 are thought to be critical for enhancer activation and cognate gene expression including through the recruitment of acetyltransferases for H3K27.ResultsHere we test this model by evaluating the impact of MLL3/4 loss on chromatin and transcription during early differentiation of mouse embryonic stem cells. We find that MLL3/4 activity is required at most if not all sites that gain or lose H3K4me1 but is largely dispensable at sites that remain stably methylated during this transition. This requirement extends to H3K27 acetylation (H3K27ac) at most transitional sites. However, many sites gain H3K27ac independent of MLL3/4 or H3K4me1 including enhancers regulating key factors in early differentiation. Furthermore, despite the failure to gain active histone marks at thousands of enhancers, transcriptional activation of nearby genes is largely unaffected, thus uncoupling the regulation of these chromatin events from transcriptional changes during this transition. These data challenge current models of enhancer activation and imply distinct mechanisms between stable and dynamically changing enhancers.ConclusionsCollectively, our study highlights gaps in knowledge about the steps and epistatic relationships of enzymes necessary for enhancer activation and cognate gene transcription.

Noncoding RNAs with secondary structures play important roles in CRISPR-Cas systems. Many of these structures likely remain undiscovered. We used a large-scale comparative genomics approach to predict 156 novel candidate structured RNAs from 36,111 CRISPR-Cas systems. A number of these were found to overlap with coding genes, including palindromic candidates that overlapped with a variety of Cas genes in type I and III systems. Among these 156 candidates, we identified 46 new models of CRISPR direct repeats and 1 tracrRNA. This tracrRNA model occasionally overlapped with predicted cas9 coding regions, emphasizing the importance of expanding our search windows for novel structure RNAs in coding regions. We also demonstrated that the antirepeat sequence in this tracrRNA model can be used to accurately assign thousands of predicted CRISPR arrays to type II-C systems. This study highlights the importance of unbiased identification of candidate structured RNAs across CRISPR-Cas systems.

Gene regulatory elements play a key role in orchestrating gene expression during cellular differentiation, but what determines their function over time remains largely unknown. Here, we perform perturbation-based massively parallel reporter assays at seven early time points of neural differentiation to systematically characterize how regulatory elements and motifs within them guide cellular differentiation. By perturbing over 2,000 putative DNA binding motifs in active regulatory regions, we delineate four categories of functional elements, and observe that activity direction is mostly determined by the sequence itself, while the magnitude of effect depends on the cellular environment. We also find that fine-tuning transcription rates is often achieved by a combined activity of adjacent activating and repressing elements. Our work provides a blueprint for the sequence components needed to induce different transcriptional patterns in general and specifically during neural differentiation.

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ruff, S. E. Editorial: microbial communities and metabolisms involved in the degradation of cellular and extracellular organic biopolymers. Frontiers in Microbiology, 12, (2022): 802619, https://doi.org/10.3389/fmicb.2021.802619., Most organic matter on Earth occurs in the form of macromolecules and complex biopolymers, which include the building blocks of every organism. Plant, animal, fungal, and microbial cells largely consist of macromolecules belonging to four compound classes: proteins, polysaccharides, nucleic acids, and lipids (Figure 1). The percentage of these compounds per dry weight can vary greatly between lineages, but also between individuals of the same species or developmental stages of the same organism. Living and lysing cells release a substantial quantity and variety of macromolecules to the environment. These compounds often contain nitrogen, phosphorus, and sulfur, in addition to carbon, and are thus ideal food sources for heterotrophic organisms. Although the degradation of biopolymers and macromolecules has received considerable attention, many knowledge gaps remain, particularly in very complex ecosystems such as soils and sediments.

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ruff, S. E. Editorial: microbial communities and metabolisms involved in the degradation of cellular and extracellular organic biopolymers. Frontiers in Microbiology, 12, (2022): 802619, https://doi.org/10.3389/fmicb.2021.802619., Most organic matter on Earth occurs in the form of macromolecules and complex biopolymers, which include the building blocks of every organism. Plant, animal, fungal, and microbial cells largely consist of macromolecules belonging to four compound classes: proteins, polysaccharides, nucleic acids, and lipids (Figure 1). The percentage of these compounds per dry weight can vary greatly between lineages, but also between individuals of the same species or developmental stages of the same organism. Living and lysing cells release a substantial quantity and variety of macromolecules to the environment. These compounds often contain nitrogen, phosphorus, and sulfur, in addition to carbon, and are thus ideal food sources for heterotrophic organisms. Although the degradation of biopolymers and macromolecules has received considerable attention, many knowledge gaps remain, particularly in very complex ecosystems such as soils and sediments.

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ruff, S. E. Editorial: microbial communities and metabolisms involved in the degradation of cellular and extracellular organic biopolymers. Frontiers in Microbiology, 12, (2022): 802619, https://doi.org/10.3389/fmicb.2021.802619., Most organic matter on Earth occurs in the form of macromolecules and complex biopolymers, which include the building blocks of every organism. Plant, animal, fungal, and microbial cells largely consist of macromolecules belonging to four compound classes: proteins, polysaccharides, nucleic acids, and lipids (Figure 1). The percentage of these compounds per dry weight can vary greatly between lineages, but also between individuals of the same species or developmental stages of the same organism. Living and lysing cells release a substantial quantity and variety of macromolecules to the environment. These compounds often contain nitrogen, phosphorus, and sulfur, in addition to carbon, and are thus ideal food sources for heterotrophic organisms. Although the degradation of biopolymers and macromolecules has received considerable attention, many knowledge gaps remain, particularly in very complex ecosystems such as soils and sediments.

Gene regulatory elements play a key role in orchestrating gene expression during cellular differentiation, but what determines their function over time remains largely unknown. Here, we perform perturbation-based massively parallel reporter assays at seven early time points of neural differentiation to systematically characterize how regulatory elements and motifs within them guide cellular differentiation. By perturbing over 2,000 putative DNA binding motifs in active regulatory regions, we delineate four categories of functional elements, and observe that activity direction is mostly determined by the sequence itself, while the magnitude of effect depends on the cellular environment. We also find that fine-tuning transcription rates is often achieved by a combined activity of adjacent activating and repressing elements. Our work provides a blueprint for the sequence components needed to induce different transcriptional patterns in general and specifically during neural differentiation.

AU-rich elements (AREs) are 3' UTR cis-regulatory elements that regulate the stability of mRNAs. Consensus ARE motifs have been determined, but little is known about how differences in 3' UTR sequences that conform to these motifs affect their function. Here, we use functional annotation of sequences from 3' UTRs (fast-UTR), a massively parallel reporter assay (MPRA), to investigate the effects of 41,288 3' UTR sequence fragments from 4653 transcripts on gene expression and mRNA stability in Jurkat and Beas2B cells. Our analyses demonstrate that the length of an ARE and its registration (the first and last nucleotides of the repeating ARE motif) have significant effects on gene expression and stability. Based on this finding, we propose improved ARE classification and concomitant methods to categorize and predict the effect of AREs on gene expression and stability. Finally, to investigate the advantages of our general experimental design we examine other motifs including constitutive decay elements (CDEs), where we show that the length of the CDE stem-loop has a significant impact on steady-state expression and mRNA stability. We conclude that fast-UTR, in conjunction with our analytical approach, can produce improved yet simple sequence-based rules for predicting the activity of human 3' UTRs.

R-loops play versatile roles in many physiological and pathological processes, and are of great interest to scientists in multiple fields. However, controversy about their genomic localization and incomplete understanding of their regulatory network raise great challenges for R-loop research. Here, we present R-loopBase (https://rloopbase.nju.edu.cn) to tackle these pressing issues by systematic integration of genomics and literature data. First, based on 107 high-quality genome-wide R-loop mapping datasets generated by 11 different technologies, we present a reference set of human R-loop zones for high-confidence R-loop localization, and spot conservative genomic features associated with R-loop formation. Second, through literature mining and multi-omics analyses, we curate the most comprehensive list of R-loop regulatory proteins and their targeted R-loops in multiple species to date. These efforts help reveal a global regulatory network of R-loop dynamics and its potential links to the development of cancers and neurological diseases. Finally, we integrate billions of functional genomic annotations, and develop interactive interfaces to search, visualize, download and analyze R-loops and R-loop regulators in a well-annotated genomic context. R-loopBase allows all users, including those with little bioinformatics background to utilize these data for their own research. We anticipate R-loopBase will become a one-stop resource for the R-loop community.

Noncoding RNAs with secondary structures play important roles in CRISPR-Cas systems. Many of these structures likely remain undiscovered. We used a large-scale comparative genomics approach to predict 156 novel candidate structured RNAs from 36,111 CRISPR-Cas systems. A number of these were found to overlap with coding genes, including palindromic candidates that overlapped with a variety of Cas genes in type I and III systems. Among these 156 candidates, we identified 46 new models of CRISPR direct repeats and 1 tracrRNA. This tracrRNA model occasionally overlapped with predicted cas9 coding regions, emphasizing the importance of expanding our search windows for novel structure RNAs in coding regions. We also demonstrated that the antirepeat sequence in this tracrRNA model can be used to accurately assign thousands of predicted CRISPR arrays to type II-C systems. This study highlights the importance of unbiased identification of candidate structured RNAs across CRISPR-Cas systems.

Epigenomics is the study of molecular signatures associated with discrete regions within genomes, many of which are important for a wide range of nuclear processes. The ability to profile the epigenomic landscape associated with genes, repetitive regions, transposons, transcription, differential expression, cis-regulatory elements, and 3D chromatin interactions has vastly improved our understanding of plant genomes. However, many epigenomic and single-cell genomic assays are challenging to perform in plants, leading to a wide range of data quality issues; thus, the data require rigorous evaluation prior to downstream analyses and interpretation. In this commentary, we provide considerations for the evaluation of plant epigenomics and single-cell genomics data quality with the aim of improving the quality and utility of studies using those data across diverse plant species.

Existing human genome assemblies have almost entirely excluded repetitive sequences within and near centromeres, limiting our understanding of their organization, evolution, and functions, which include facilitating proper chromosome segregation. Now, a complete, telomere-to-telomere human genome assembly (T2T-CHM13) has enabled us to comprehensively characterize pericentromeric and centromeric repeats, which constitute 6.2% of the genome (189.9 megabases). Detailed maps of these regions revealed multimegabase structural rearrangements, including in active centromeric repeat arrays. Analysis of centromere-associated sequences uncovered a strong relationship between the position of the centromere and the evolution of the surrounding DNA through layered repeat expansions. Furthermore, comparisons of chromosome X centromeres across a diverse panel of individuals illuminated high degrees of structural, epigenetic, and sequence variation in these complex and rapidly evolving regions.

Mobile elements and repetitive genomic regions are sources of lineage-specific genomic innovation and uniquely fingerprint individual genomes. Comprehensive analyses of such repeat elements, including those found in more complex regions of the genome, require a complete, linear genome assembly. We present a de novo repeat discovery and annotation of the T2T-CHM13 human reference genome. We identified previously unknown satellite arrays, expanded the catalog of variants and families for repeats and mobile elements, characterized classes of complex composite repeats, and located retroelement transduction events. We detected nascent transcription and delineated CpG methylation profiles to define the structure of transcriptionally active retroelements in humans, including those in centromeres. These data expand our insight into the diversity, distribution, and evolution of repetitive regions that have shaped the human genome.

We present fluorogenic cationic organo chalcogens that are highly selective to RNA. We have demonstrated that the conformational dynamics and subsequently the optical properties of these dyes can be controlled to facilitate efficient bioimaging. We report the application of organoselenium and organosulfur-based cell-permeable red-emissive probes bearing a favorable cyclic sidearm for selective and high contrast imaging of cell nucleoli. The probes exhibit high quantum yield upon interacting with RNA in an aqueous solution. An in-depth multiscale simulation study reveals that the prominent rotational freezing of the electron-donating sidearm of the probes in the microenvironment of RNA helps in attaining more planar conformation when compared to DNA. It exerts a greater extent of intramolecular charge transfer and hence leads to enhanced fluorescence emission. A systematic structure-interaction relationship study highlighted the impact of heavy-chalcogens toward the improved emissive properties of the probes., QC 20221109

Nascent RNA-sequencing tracks transcription at nucleotide resolution. The genomic distribution of engaged transcription complexes, in turn, uncovers functional genomic regions. Here, we provide analytical steps to (1) identify transcribed regulatory elements de novo genome-wide, (2) quantify engaged transcription complexes at enhancers, promoter-proximal regions, divergent transcripts, gene bodies, and termination windows, and (3) measure distribution of transcription machineries and regulatory proteins across functional genomic regions. This protocol tracks engaged transcription complexes across functional genomic regions demonstrated in human K562 erythroleukemia cells. For complete details on the use and execution of this protocol, please refer to Vihervaara et al. (2021)., QC 20220930

scDesign2 is a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured. This article shows how to download and install the scDesign2 R package, how to fit probabilistic models (one per cell type) to real data and simulate synthetic data from the fitted models, and how to use scDesign2 to guide experimental design and benchmark computational methods. Finally, a note is given about cell clustering as a preprocessing step before model fitting and data simulation.

Genome editing technologies introduce targeted chromosomal modifications in organisms yet are constrained by the inability to selectively modify repetitive genetic elements. Here we describe filtered editing, a genome editing method that embeds group 1 self-splicing introns into repetitive genetic elements to construct unique genetic addresses that can be selectively modified. We introduce intron-containing ribosomes into the E. coli genome and perform targeted modifications of these ribosomes using CRISPR/Cas9 and multiplex automated genome engineering. Self-splicing of introns post-transcription yields scarless RNA molecules, generating a complex library of targeted combinatorial variants. We use filtered editing to co-evolve the 16S rRNA to tune the ribosome's translational efficiency and the 23S rRNA to isolate antibiotic-resistant ribosome variants without interfering with native translation. This work sets the stage to engineer mutant ribosomes that polymerize abiological monomers with diverse chemistries and expands the scope of genome engineering for precise editing and evolution of repetitive DNA sequences.

Androgen receptor (AR) drives prostate cancer (PCa) development and progression. AR chromatin binding profiles are highly plastic and form recurrent programmatic changes that differentiate disease stages, subtypes and patient outcomes. While prior studies focused on concordance between patient subgroups, inter-tumor heterogeneity of AR enhancer selectivity remains unexplored. Here we report high levels of AR chromatin binding heterogeneity in human primary prostate tumors, that overlap with heterogeneity observed in healthy prostate epithelium. Such heterogeneity has functional consequences, as somatic mutations converge on commonly-shared AR sites in primary over metastatic tissues. In contrast, less-frequently shared AR sites associate strongly with AR-driven gene expression, while such heterogeneous AR enhancer usage also distinguishes patients outcome. These findings indicate that epigenetic heterogeneity in primary disease is directly informative for risk of biochemical relapse. Cumulatively, our results illustrate a high level of AR enhancer heterogeneity in primary PCa driving differential expression and clinical impact.

The most common inherited cause of two genetically and clinico-pathologically overlapping neurodegenerative diseases, amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), is the presence of expanded GGGGCC intronic hexanucleotide repeats in the C9orf72 gene. Aside from haploinsufficiency and toxic RNA foci, another non-exclusive disease mechanism is the non-canonical translation of the repeat RNA into five different dipeptide repeat proteins (DPRs), which form neuronal inclusions in affected patient brains. While evidence from cellular and animal models supports a toxic gain-of-function of pathologic poly-GA, poly-GR, and poly-PR aggregates in promoting deposition of TDP-43 pathology and neurodegeneration in affected brain areas, the relative contribution of DPRs to the disease process in c9FTD/ALS patients remains unclear. Here we have used the proximity-dependent biotin identification (BioID) proximity proteomics approach to investigate the formation and collective composition of DPR aggregates using cellular models. While interactomes of arginine rich poly-GR and poly-PR aggregates overlapped and were enriched for nucleolar and ribosomal proteins, poly-GA aggregates demonstrated a distinct association with proteasomal components, molecular chaperones (HSPA1A/HSP70, HSPA8/HSC70, VCP/p97), co-chaperones (BAG3, DNAJA1A) and other factors that regulate protein folding and degradation (SQSTM1/p62, CALR, CHIP/STUB1). Experiments in cellular models of poly-GA pathology show that molecular chaperones and co-chaperones are sequestered to the periphery of dense cytoplasmic aggregates, causing depletion from their typical cellular localization. Their involvement in the pathologic process is confirmed in autopsy brain tissue, where HSPA8, BAG3, VCP, and its adapter protein UBXN6 show a close association with poly-GA aggregates in the frontal cortex, temporal cortex, and hippocampus of c9FTLD and c9ALS cases. The association of heat shock proteins and c

To determine the impact of genetic variants on the brain, we used genetically informed brain atlases in genome-wide association studies of regional cortical surface area and thickness in 39,898 adults and 9136 children. We uncovered 440 genome-wide significant loci in the discovery cohort and 800 from a post hoc combined meta-analysis. Loci in adulthood were largely captured in childhood, showing signatures of negative selection, and were linked to early neurodevelopment and pathways associated with neuropsychiatric risk. Opposing gradations of decreased surface area and increased thickness were associated with common inversion polymorphisms. Inferior frontal regions, encompassing Broca's area, which is important for speech, were enriched for human-specific genomic elements. Thus, a mixed genetic landscape of conserved and human-specific features is concordant with brain hierarchy and morphogenetic gradients.

Improved scale, multiplexing and resolution are establishing spatial nucleic acid and protein profiling methods as a major pillar for cellular atlas building of complex samples, from tissues to full organisms. Emerging methods yield omics measurements at resolutions covering the nano- to microscale, enabling the charting of cellular heterogeneity, complex tissue architectures and dynamic changes during development and disease. We present an overview of the developing landscape of in situ spatial genome, transcriptome and proteome technologies, exemplify their impact on cell biology and translational research, and discuss current challenges for their community-wide adoption. Among many transformative applications, we envision that spatial methods will map entire organs and enable next-generation pathology., QC 20230421

Within primates, the great apes are outliers both in terms of body size and lifespan, since they include the largest and longest-lived species in the order. Yet, the molecular bases underlying such features are poorly understood. Here, we leveraged an integrated approach to investigate multiple sources of molecular variation across primates, focusing on over 10,000 genes, including approximately 1,500 previously associated with lifespan, and additional approximately 9,000 for which an association with longevity has never been suggested. We analyzed dN/dS rates, positive selection, gene expression (RNA-seq), and gene regulation (ChIP-seq). By analyzing the correlation between dN/dS, maximum lifespan, and body mass, we identified 276 genes whose rate of evolution positively correlates with maximum lifespan in primates. Further, we identified five genes, important for tumor suppression, adaptive immunity, metastasis, and inflammation, under positive selection exclusively in the great ape lineage. RNA-seq data, generated from the liver of six species representing all the primate lineages, revealed that 8% of approximately 1,500 genes previously associated with longevity are differentially expressed in apes relative to other primates. Importantly, by integrating RNA-seq with ChIP-seq for H3K27ac (which marks active enhancers), we show that the differentially expressed longevity genes are significantly more likely than expected to be located near a novel "ape-specific" enhancer. Moreover, these particular ape-specific enhancers are enriched for young transposable elements, and specifically SINE-Vntr-Alus. In summary, we demonstrate that multiple evolutionary forces have contributed to the evolution of lifespan and body size in primates.

Concerted alteration of immune and metabolic homeostasis underlies several inflammation-related pathologies, ranging from metabolic syndrome to infectious diseases. Here, we explored the coordination of nucleic acid-dependent inflammatory responses and metabolic homeostasis. We reveal that the STING (stimulator of interferon genes) protein regulates metabolic homeostasis through inhibition of the fatty acid desaturase 2 (FADS2) rate-limiting enzyme in polyunsaturated fatty acid (PUFA) desaturation. STING ablation and agonist-mediated degradation increased FADS2-associated desaturase activity and led to accumulation of PUFA derivatives that drive thermogenesis. STING agonists directly activated FADS2-dependent desaturation, promoting metabolic alterations. PUFAs in turn inhibited STING, thereby regulating antiviral responses and contributing to resolving STING-associated inflammation. Thus, we have unveiled a negative regulatory feedback loop between STING and FADS2 that fine-tunes inflammatory responses. Our results highlight the role of metabolic alterations in human pathologies associated with aberrant STING activation and STING-targeting therapies., SCOPUS: ar.j, info:eu-repo/semantics/published

Non-coding RNAs (ncRNA) are essential for all life, and their functions often depend on their secondary (2D) and tertiary structure. Despite the abundance of software for the visualisation of ncRNAs, few automatically generate consistent and recognisable 2D layouts, which makes it challenging for users to construct, compare and analyse structures. Here, we present R2DT, a method for predicting and visualising a wide range of RNA structures in standardised layouts. R2DT is based on a library of 3,647 templates representing the majority of known structured RNAs. R2DT has been applied to ncRNA sequences from the RNAcentral database and produced >13 million diagrams, creating the world's largest RNA 2D structure dataset. The software is amenable to community expansion, and is freely available at https://github.com/rnacentral/R2DT and a web server is found at https://rnacentral.org/r2dt .

The cost of sequencing the genome is dropping at a much faster rate compared to assembling and finishing the genome. The use of lightly sampled genomes (genome-skims) could be transformative for genomic ecology, and results using k-mers have shown the advantage of this approach in identification and phylogenetic placement of eukaryotic species. Here, we revisit the basic question of estimating genomic parameters such as genome length, coverage, and repeat structure, focusing specifically on estimating the k-mer repeat spectrum. We show using a mix of theoretical and empirical analysis that there are fundamental limitations to estimating the k-mer spectra due to ill-conditioned systems, and that has implications for other genomic parameters. We get around this problem using a novel constrained optimization approach (Spline Linear Programming), where the constraints are learned empirically. On reads simulated at 1X coverage from 66 genomes, our method, REPeat SPECTra Estimation (RESPECT), had 2.2% error in length estimation compared to 27% error previously achieved. In shotgun sequenced read samples with contaminants, RESPECT length estimates had median error 4%, in contrast to other methods that had median error 80%. Together, the results suggest that low-pass genomic sequencing can yield reliable estimates of the length and repeat content of the genome. The RESPECT software will be publicly available at https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_shahab-2Dsarmashghi_RESPECT.git&d=DwIGAw&c=-35OiAkTchMrZOngvJPOeA&r=ZozViWvD1E8PorCkfwYKYQMVKFoEcqLFm4Tg49XnPcA&m=f-xS8GMHKckknkc7Xpp8FJYw_ltUwz5frOw1a5pJ81EpdTOK8xhbYmrN4ZxniM96&s=717o8hLR1JmHFpRPSWG6xdUQTikyUjicjkipjFsKG4w&e=.

Identifying 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.

Gene regulatory elements are central drivers of phenotypic variation and thus of critical importance towards understanding the genetics of complex traits. The Functional Annotation of Animal Genomes consortium was formed to collaboratively annotate the functional elements in animal genomes, starting with domesticated animals. Here we present an expansive collection of datasets from eight diverse tissues in three important agricultural species: chicken (Gallus gallus), pig (Sus scrofa), and cattle (Bos taurus). Comparative analysis of these datasets and those from the human and mouse Encyclopedia of DNA Elements projects reveal that a core set of regulatory elements are functionally conserved independent of divergence between species, and that tissue-specific transcription factor occupancy at regulatory elements and their predicted target genes are also conserved. These datasets represent a unique opportunity for the emerging field of comparative epigenomics, as well as the agricultural research community, including species that are globally important food resources.

Genome-wide profiling of histone modifications can reveal not only the location and activity state of regulatory elements, but also the regulatory mechanisms involved in cell-type-specific gene expression during development and disease pathology. Conventional assays to profile histone modifications in bulk tissues lack single-cell resolution. Here we describe an ultra-high-throughput method, Paired-Tag, for joint profiling of histone modifications and transcriptome in single cells to produce cell-type-resolved maps of chromatin state and transcriptome in complex tissues. We used this method to profile five histone modifications jointly with transcriptome in the adult mouse frontal cortex and hippocampus. Integrative analysis of the resulting maps identified distinct groups of genes subject to divergent epigenetic regulatory mechanisms. Our single-cell multiomics approach enables comprehensive analysis of chromatin state and gene regulation in complex tissues and characterization of gene regulatory programs in the constituent cell types.