Mechanisms of mutational robustness in transcriptional regulation

CelEst: a unified gene regulatory network for estimating transcription factor activities in C. elegans

Transcription factors (TFs) play a pivotal role in orchestrating critical intricate patterns of gene regulation. Although gene expression is complex, differential expression of hundreds of genes is often due to regulation by just a handful of TFs. Despite extensive efforts to elucidate TF-target regulatory relationships in Caenorhabditis elegans, existing experimental datasets cover distinct subsets of TFs and leave data integration challenging. Here, I introduce CelEst, a unified gene regulatory network designed to estimate the activity of 487 distinct C. elegans TFs-∼58% of the total-from gene expression data. To integrate data from ChIP-seq, DNA-binding motifs, and eY1H screens, optimal processing of each data type was benchmarked against a set of TF perturbation RNA-seq experiments. Moreover, I showcase how leveraging TF motif conservation in target promoters across genomes of related species can distinguish highly informative interactions, a strategy which can be applied to many model organisms. Integrated analyses of data from commonly studied conditions including heat shock, bacterial infection, and sex differences validates CelEst's performance and highlights overlooked TFs that likely play major roles in coordinating the transcriptional response to these conditions. CelEst can infer TF activity on a standard laptop computer within minutes. Furthermore, an R Shiny app with a step-by-step guide is provided for the community to perform rapid analysis with minimal coding required. I anticipate that widespread adoption of CelEsT will significantly enhance the interpretive power of transcriptomic experiments, both present and retrospective, thereby advancing our understanding of gene regulation in C. elegans and beyond.

Chromatin-based memory as a self-stabilizing influence on cell identity

Cell types are traditionally thought to be specified and stabilized by gene regulatory networks. Here, we explore how chromatin memory contributes to the specification and stabilization of cell states. Through pervasive, local, feedback loops, chromatin memory enables cell states that were initially unstable to become stable. Deeper appreciation of this self-stabilizing role for chromatin broadens our perspective of Waddington's epigenetic landscape from a static surface with islands of stability shaped by evolution, to a plasticine surface molded by experience. With implications for the evolution of cell types, stabilization of resistant states in cancer, and the widespread plasticity of complex life.

Understanding developmental system drift

Developmental system drift (DSD) occurs when the genetic basis for homologous traits diverges over time despite conservation of the phenotype. In this Review, we examine the key ideas, evidence and open problems arising from studies of DSD. Recent work suggests that DSD may be pervasive, having been detected across a range of different organisms and developmental processes. Although developmental research remains heavily reliant on model organisms, extrapolation of findings to non-model organisms can be error-prone if the lineages have undergone DSD. We suggest how existing data and modelling approaches may be used to detect DSD and estimate its frequency. More direct study of DSD, we propose, can inform null hypotheses for how much genetic divergence to expect on the basis of phylogenetic distance, while also contributing to principles of gene regulatory evolution.

Promoters Constrain Evolution of Expression Levels of Essential Genes in Escherichia coli

Variability in expression levels in response to random genomic mutations varies among genes, influencing both the facilitation and constraint of phenotypic evolution in organisms. Despite its importance, both the underlying mechanisms and evolutionary origins of this variability remain largely unknown due to the mixed contributions of cis- and trans-acting elements. To address this issue, we focused on the mutational variability of cis-acting elements, that is, promoter regions, in Escherichia coli. Random mutations were introduced into the natural and synthetic promoters to generate mutant promoter libraries. By comparing the variance in promoter activity of these mutant libraries, we found no significant difference in mutational variability in promoter activity between promoter groups, suggesting the absence of a signature of natural selection for mutational robustness. In contrast, the promoters controlling essential genes exhibited a remarkable bias in mutational variability, with mutants displaying higher activities than the wild types being relatively rare compared to those with lower activities. Our evolutionary simulation on a rugged fitness landscape provided a rationale for this vulnerability. These findings suggest that past selection created nonuniform mutational variability in promoters biased toward lower activities of random mutants, which now constrains the future evolution of downstream essential genes toward higher expression levels.

The Effects of De Novo Mutation on Gene Expression and the Consequences for Fitness in Chlamydomonas reinhardtii

Mutation is the ultimate source of genetic variation, the bedrock of evolution. Yet, predicting the consequences of new mutations remains a challenge in biology. Gene expression provides a potential link between a genotype and its phenotype. But the variation in gene expression created by de novo mutation and the fitness consequences of mutational changes to expression remain relatively unexplored. Here, we investigate the effects of >2,600 de novo mutations on gene expression across the transcriptome of 28 mutation accumulation lines derived from 2 independent wild-type genotypes of the green algae Chlamydomonas reinhardtii. We observed that the amount of genetic variance in gene expression created by mutation (Vm) was similar to the variance that mutation generates in typical polygenic phenotypic traits and approximately 15-fold the variance seen in the limited species where Vm in gene expression has been estimated. Despite the clear effect of mutation on expression, we did not observe a simple additive effect of mutation on expression change, with no linear correlation between the total expression change and mutation count of individual MA lines. We therefore inferred the distribution of expression effects of new mutations to connect the number of mutations to the number of differentially expressed genes (DEGs). Our inferred DEE is highly L-shaped with 95% of mutations causing 0-1 DEG while the remaining 5% are spread over a long tail of large effect mutations that cause multiple genes to change expression. The distribution is consistent with many cis-acting mutation targets that affect the expression of only 1 gene and a large target of trans-acting targets that have the potential to affect tens or hundreds of genes. Further evidence for cis-acting mutations can be seen in the overabundance of mutations in or near differentially expressed genes. Supporting evidence for trans-acting mutations comes from a 15:1 ratio of DEGs to mutations and the clusters of DEGs in the co-expression network, indicative of shared regulatory architecture. Lastly, we show that there is a negative correlation with the extent of expression divergence from the ancestor and fitness, providing direct evidence of the deleterious effects of perturbing gene expression.

Less-is-more: selecting transcription factor binding regions informative for motif inference

Numerous statistical methods have emerged for inferring DNA motifs for transcription factors (TFs) from genomic regions. However, the process of selecting informative regions for motif inference remains understudied. Current approaches select regions with strong ChIP-seq signal for a given TF, assuming that such strong signal primarily results from specific interactions between the TF and its motif. Additionally, these selection approaches do not account for non-target motifs, i.e. motifs of other TFs; they presume the occurrence of these non-target motifs infrequent compared to that of the target motif, and thus assume these have minimal interference with the identification of the target. Leveraging extensive ChIP-seq datasets, we introduced the concept of TF signal 'crowdedness', referred to as C-score, for each genomic region. The C-score helps in highlighting TF signals arising from non-specific interactions. Moreover, by considering the C-score (and adjusting for the length of genomic regions), we can effectively mitigate interference of non-target motifs. Using these tools, we find that in many instances, strong ChIP-seq signal stems mainly from non-specific interactions, and the occurrence of non-target motifs significantly impacts the accurate inference of the target motif. Prioritizing genomic regions with reduced crowdedness and short length markedly improves motif inference. This 'less-is-more' effect suggests that ChIP-seq region selection warrants more attention.

Deep molecular learning of transcriptional control of a synthetic CRE enhancer and its variants

Massively parallel reporter assay measures transcriptional activities of various cis-regulatory modules (CRMs) in a single experiment. We developed a thermodynamic computational model framework that calculates quantitative levels of gene expression directly from regulatory DNA sequences. Using the framework, we investigated the molecular mechanisms of cis-regulatory mutations of a synthetic enhancer that cause abnormal gene expression. We found that, in a human cell line, competitive binding between family transcription factors (TFs) with slightly different binding preferences significantly increases the accuracy of recapitulating the transcriptional effects of thousands of single- or multi-mutations. We also discovered that even if various harmful mutations occurred in an activator binding site, CRM could stably maintain or even increase gene expression through a certain form of competitive binding between family TFs. These findings enhance understanding the effect of SNPs and indels on CRMs and would help building robust custom-designed CRMs for biologics production and gene therapy.

Extreme restructuring of cis -regulatory regions controlling a deeply conserved plant stem cell regulator

A striking paradox is that genes with conserved protein sequence, function and expression pattern over deep time often exhibit extremely divergent cis -regulatory sequences. It remains unclear how such drastic cis -regulatory evolution across species allows preservation of gene function, and to what extent these differences influence how cis- regulatory variation arising within species impacts phenotypic change. Here, we investigated these questions using a plant stem cell regulator conserved in expression pattern and function over ∼125 million years. Using in-vivo genome editing in two distantly related models, Arabidopsis thaliana (Arabidopsis) and Solanum lycopersicum (tomato), we generated over 70 deletion alleles in the upstream and downstream regions of the stem cell repressor gene CLAVATA3 ( CLV3 ) and compared their individual and combined effects on a shared phenotype, the number of carpels that make fruits. We found that sequences upstream of tomato CLV3 are highly sensitive to even small perturbations compared to its downstream region. In contrast, Arabidopsis CLV3 function is tolerant to severe disruptions both upstream and downstream of the coding sequence. Combining upstream and downstream deletions also revealed a different regulatory outcome. Whereas phenotypic enhancement from adding downstream mutations was predominantly weak and additive in tomato, mutating both regions of Arabidopsis CLV3 caused substantial and synergistic effects, demonstrating distinct distribution and redundancy of functional cis -regulatory sequences. Our results demonstrate remarkable malleability in cis -regulatory structural organization of a deeply conserved plant stem cell regulator and suggest that major reconfiguration of cis -regulatory sequence space is a common yet cryptic evolutionary force altering genotype-to-phenotype relationships from regulatory variation in conserved genes. Finally, our findings underscore the need for lineage-specific dissection of the spatial architecture of cis -regulation to effectively engineer trait variation from conserved productivity genes in crops.

Author summary

We investigated the evolution of cis -regulatory elements (CREs) and their interactions in the regulation of a plant stem cell regulator gene, CLAVATA3 (CLV3) , in Arabidopsis and tomato. Despite diverging ∼125 million years ago, the function and expression of CLV3 is conserved in these species; however, cis -regulatory sequences upstream and downstream have drastically diverged, preventing identification of conserved non-coding sequences between them. We used CRISPR-Cas9 to engineer dozens of mutations within the cis -regulatory regions of Arabidopsis and tomato CLV3. In tomato, our results show that tomato CLV3 function primarily relies on interactions among CREs in the 5' non-coding region, unlike Arabidopsis CLV3 , which depends on a more balanced distribution of functional CREs between the 5' and 3' regions. Therefore, despite a high degree of functional conservation, our study demonstrates divergent regulatory strategies between two distantly related CLV3 orthologs, with substantial alterations in regulatory sequences, their spatial arrangement, and their relative effects on CLV3 regulation. These results suggest that regulatory regions are not only extremely robust to mutagenesis, but also that the sequences underlying this robustness can be lineage-specific for conserved genes, due to the complex and often redundant interactions among CREs that ensure proper gene function amidst large-scale sequence turnover.

The evolution and mutational robustness of chromatin accessibility in Drosophila

BACKGROUND

The evolution of genomic regulatory regions plays a critical role in shaping the diversity of life. While this process is primarily sequence-dependent, the enormous complexity of biological systems complicates the understanding of the factors underlying regulation and its evolution. Here, we apply deep neural networks as a tool to investigate the sequence determinants underlying chromatin accessibility in different species and tissues of Drosophila.

RESULTS

We train hybrid convolution-attention neural networks to accurately predict ATAC-seq peaks using only local DNA sequences as input. We show that our models generalize well across substantially evolutionarily diverged species of insects, implying that the sequence determinants of accessibility are highly conserved. Using our model to examine species-specific gains in accessibility, we find evidence suggesting that these regions may be ancestrally poised for evolution. Using in silico mutagenesis, we show that accessibility can be accurately predicted from short subsequences in each example. However, in silico knock-out of these sequences does not qualitatively impair classification, implying that accessibility is mutationally robust. Subsequently, we show that accessibility is predicted to be robust to large-scale random mutation even in the absence of selection. Conversely, simulations under strong selection demonstrate that accessibility can be extremely malleable despite its robustness. Finally, we identify motifs predictive of accessibility, recovering both novel and previously known motifs.

CONCLUSIONS

These results demonstrate the conservation of the sequence determinants of accessibility and the general robustness of chromatin accessibility, as well as the power of deep neural networks to explore fundamental questions in regulatory genomics and evolution.

Transcription factor expression is the main determinant of variability in gene co-activity

Many genes are co-expressed and form genomic domains of coordinated gene activity. However, the regulatory determinants of domain co-activity remain unclear. Here, we leverage human individual variation in gene expression to characterize the co-regulatory processes underlying domain co-activity and systematically quantify their effect sizes. We employ transcriptional decomposition to extract from RNA expression data an expression component related to co-activity revealed by genomic positioning. This strategy reveals close to 1,500 co-activity domains, covering most expressed genes, of which the large majority are invariable across individuals. Focusing specifically on domains with high variability in co-activity reveals that contained genes have a higher sharing of eQTLs, a higher variability in enhancer interactions, and an enrichment of binding by variably expressed transcription factors, compared to genes within non-variable domains. Through careful quantification of the relative contributions of regulatory processes underlying co-activity, we find transcription factor expression levels to be the main determinant of gene co-activity. Our results indicate that distal trans effects contribute more than local genetic variation to individual variation in co-activity domains.

Characterizing the landscape of gene expression variance in humans

Gene expression variance has been linked to organismal function and fitness but remains a commonly neglected aspect of molecular research. As a result, we lack a comprehensive understanding of the patterns of transcriptional variance across genes, and how this variance is linked to context-specific gene regulation and gene function. Here, we use 57 large publicly available RNA-seq data sets to investigate the landscape of gene expression variance. These studies cover a wide range of tissues and allowed us to assess if there are consistently more or less variable genes across tissues and data sets and what mechanisms drive these patterns. We show that gene expression variance is broadly similar across tissues and studies, indicating that the pattern of transcriptional variance is consistent. We use this similarity to create both global and within-tissue rankings of variation, which we use to show that function, sequence variation, and gene regulatory signatures contribute to gene expression variance. Low-variance genes are associated with fundamental cell processes and have lower levels of genetic polymorphisms, have higher gene-gene connectivity, and tend to be associated with chromatin states associated with transcription. In contrast, high-variance genes are enriched for genes involved in immune response, environmentally responsive genes, immediate early genes, and are associated with higher levels of polymorphisms. These results show that the pattern of transcriptional variance is not noise. Instead, it is a consistent gene trait that seems to be functionally constrained in human populations. Furthermore, this commonly neglected aspect of molecular phenotypic variation harbors important information to understand complex traits and disease.

The evolution and mutational robustness of chromatin accessibility in Drosophila

The evolution of regulatory regions in the genome plays a critical role in shaping the diversity of life. While this process is primarily sequence-dependent, the enormous complexity of biological systems has made it difficult to understand the factors underlying regulation and its evolution. Here, we apply deep neural networks as a tool to investigate the sequence determinants underlying chromatin accessibility in different tissues of Drosophila. We train hybrid convolution-attention neural networks to accurately predict ATAC-seq peaks using only local DNA sequences as input. We show that a model trained in one species has nearly identical performance when tested in another species, implying that the sequence determinants of accessibility are highly conserved. Indeed, model performance remains excellent even in distantly-related species. By using our model to examine species-specific gains in chromatin accessibility, we find that their orthologous inaccessible regions in other species have surprisingly similar model outputs, suggesting that these regions may be ancestrally poised for evolution. We then use in silico saturation mutagenesis to reveal evidence of selective constraint acting specifically on inaccessible chromatin regions. We further show that chromatin accessibility can be accurately predicted from short subsequences in each example. However, in silico knock-out of these sequences does not qualitatively impair classification, implying that chromatin accessibility is mutationally robust. Subsequently, we demonstrate that chromatin accessibility is predicted to be robust to large-scale random mutation even in the absence of selection. We also perform in silico evolution experiments under the regime of strong selection and weak mutation (SSWM) and show that chromatin accessibility can be extremely malleable despite its mutational robustness. However, selection acting in different directions in a tissue-specific manner can substantially slow adaptation. Finally, we identify motifs predictive of chromatin accessibility and recover motifs corresponding to known chromatin accessibility activators and repressors. These results demonstrate the conservation of the sequence determinants of accessibility and the general robustness of chromatin accessibility, as well as the power of deep neural networks as tools to answer fundamental questions in regulatory genomics and evolution.

Environment-dependent epistasis increases phenotypic diversity in gene regulatory networks

Mutations to gene regulatory networks can be maladaptive or a source of evolutionary novelty. Epistasis confounds our understanding of how mutations affect the expression patterns of gene regulatory networks, a challenge exacerbated by the dependence of epistasis on the environment. We used the toolkit of synthetic biology to systematically assay the effects of pairwise and triplet combinations of mutant genotypes on the expression pattern of a gene regulatory network expressed in Escherichia coli that interprets an inducer gradient across a spatial domain. We uncovered a preponderance of epistasis that can switch in magnitude and sign across the inducer gradient to produce a greater diversity of expression pattern phenotypes than would be possible in the absence of such environment-dependent epistasis. We discuss our findings in the context of the evolution of hybrid incompatibilities and evolutionary novelties.

Mutational scans reveal differential evolvability of Drosophila promoters and enhancers

Rapid enhancer and slow promoter evolution have been demonstrated through comparative genomics. However, it is not clear how this information is encoded genetically and if this can be used to place evolution in a predictive context. Part of the challenge is that our understanding of the potential for regulatory evolution is biased primarily toward natural variation or limited experimental perturbations. Here, to explore the evolutionary capacity of promoter variation, we surveyed an unbiased mutation library for three promoters in Drosophila melanogaster. We found that mutations in promoters had limited to no effect on spatial patterns of gene expression. Compared to developmental enhancers, promoters are more robust to mutations and have more access to mutations that can increase gene expression, suggesting that their low activity might be a result of selection. Consistent with these observations, increasing the promoter activity at the endogenous locus of shavenbaby led to increased transcription yet limited phenotypic changes. Taken together, developmental promoters may encode robust transcriptional outputs allowing evolvability through the integration of diverse developmental enhancers.

This article is part of the theme issue ‘Interdisciplinary approaches to predicting evolutionary biology’.

Robustness and innovation in synthetic genotype networks

Genotype networks are sets of genotypes connected by small mutational changes that share the same phenotype. They facilitate evolutionary innovation by enabling the exploration of different neighborhoods in genotype space. Genotype networks, first suggested by theoretical models, have been empirically confirmed for proteins and RNAs. Comparative studies also support their existence for gene regulatory networks (GRNs), but direct experimental evidence is lacking. Here, we report the construction of three interconnected genotype networks of synthetic GRNs producing three distinct phenotypes in Escherichia coli. Our synthetic GRNs contain three nodes regulating each other by CRISPR interference and governing the expression of fluorescent reporters. The genotype networks, composed of over twenty different synthetic GRNs, provide robustness in face of mutations while enabling transitions to innovative phenotypes. Through realistic mathematical modeling, we quantify robustness and evolvability for the complete genotype-phenotype map and link these features mechanistically to GRN motifs. Our work thereby exemplifies how GRN evolution along genotype networks might be driving evolutionary innovation.

The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × ∼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Mechanisms of robustness in gene regulatory networks involved in neural development

The functions of living organisms are affected by different kinds of perturbation, both internal and external, which in many cases have functional effects and phenotypic impact. The effects of these perturbations become particularly relevant for multicellular organisms with complex body patterns and cell type heterogeneity, where transcriptional programs controlled by gene regulatory networks determine, for example, the cell fate during embryonic development. Therefore, an essential aspect of development in these organisms is the ability to maintain the functionality of their genetic developmental programs even in the presence of genetic variation, changing environmental conditions and biochemical noise, a property commonly termed robustness. We discuss the implication of different molecular mechanisms of robustness involved in neurodevelopment, which is characterized by the interplay of many developmental programs at a molecular, cellular and systemic level. We specifically focus on processes affecting the function of gene regulatory networks, encompassing transcriptional regulatory elements and post-transcriptional processes such as miRNA-based regulation, but also higher order regulatory organization, such as gene network topology. We also present cases where impairment of robustness mechanisms can be associated with neurodevelopmental disorders, as well as reasons why understanding these mechanisms should represent an important part of the study of gene regulatory networks driving neural development.

Rebuilding ships while at sea-Character individuality, homology, and evolutionary innovation

How novel traits originate in evolution is still one of the most perplexing questions in Evolutionary Biology. Building on a previous account of evolutionary innovation, I here propose that evolutionary novelties are those individualized characters that are not homologous to any characters in the ancestor. To clarify this definition, I here provide a detailed analysis of the concepts of "character individuality" and "homology" first, before addressing their role for our understanding of evolutionary innovation. I will argue (1) that functional as well as structural considerations are important for character individualization; and (2) that compositional (structural) and positional homology need to be clearly distinguished to properly describe the evolutionary transformations of hierarchically structured characters. My account will therefore integrate functional and structural perspectives and put forward a new multi-level view of character identity and transformation.

Massively parallel reporter assays and variant scoring identified functional variants and target genes for melanoma loci and highlighted cell-type specificity

The most recent genome-wide association study (GWAS) of cutaneous melanoma identified 54 risk-associated loci, but functional variants and their target genes for most have not been established. Here, we performed massively parallel reporter assays (MPRAs) by using malignant melanoma and normal melanocyte cells and further integrated multi-layer annotation to systematically prioritize functional variants and susceptibility genes from these GWAS loci. Of 1,992 risk-associated variants tested in MPRAs, we identified 285 from 42 loci (78% of the known loci) displaying significant allelic transcriptional activities in either cell type (FDR < 1%). We further characterized MPRA-significant variants by motif prediction, epigenomic annotation, and statistical/functional fine-mapping to create integrative variant scores, which prioritized one to six plausible candidate variants per locus for the 42 loci and nominated a single variant for 43% of these loci. Overlaying the MPRA-significant variants with genome-wide significant expression or methylation quantitative trait loci (eQTLs or meQTLs, respectively) from melanocytes or melanomas identified candidate susceptibility genes for 60% of variants (172 of 285 variants). CRISPRi of top-scoring variants validated their cis-regulatory effect on the eQTL target genes, MAFF (22q13.1) and GPRC5A (12p13.1). Finally, we identified 36 melanoma-specific and 45 melanocyte-specific MPRA-significant variants, a subset of which are linked to cell-type-specific target genes. Analyses of transcription factor availability in MPRA datasets and variant-transcription-factor interaction in eQTL datasets highlighted the roles of transcription factors in cell-type-specific variant functionality. In conclusion, MPRAs along with variant scoring effectively prioritized plausible candidates for most melanoma GWAS loci and highlighted cellular contexts where the susceptibility variants are functional.

Promoter sequence and architecture determine expression variability and confer robustness to genetic variants

Genetic and environmental exposures cause variability in gene expression. Although most genes are affected in a population, their effect sizes vary greatly, indicating the existence of regulatory mechanisms that could amplify or attenuate expression variability. Here, we investigate the relationship between the sequence and transcription start site architectures of promoters and their expression variability across human individuals. We find that expression variability can be largely explained by a promoter's DNA sequence and its binding sites for specific transcription factors. We show that promoter expression variability reflects the biological process of a gene, demonstrating a selective trade-off between stability for metabolic genes and plasticity for responsive genes and those involved in signaling. Promoters with a rigid transcription start site architecture are more prone to have variable expression and to be associated with genetic variants with large effect sizes, while a flexible usage of transcription start sites within a promoter attenuates expression variability and limits genotypic effects. Our work provides insights into the variable nature of responsive genes and reveals a novel mechanism for supplying transcriptional and mutational robustness to essential genes through multiple transcription start site regions within a promoter.

Purifying selection enduringly acts on the sequence evolution of highly expressed proteins in Escherichia coli

The evolutionary speed of a protein sequence is constrained by its expression level, with highly expressed proteins evolving relatively slowly. This negative correlation between expression levels and evolutionary rates (known as the E–R anticorrelation) has already been widely observed in past macroevolution between species from bacteria to animals. However, it remains unclear whether this seemingly general law also governs recent evolution, including past and de novo, within a species. However, the advent of genomic sequencing and high-throughput phenotyping, particularly for bacteria, has revealed fundamental gaps between the 2 evolutionary processes and has provided empirical data opposing the possible underlying mechanisms which are widely believed. These conflicts raise questions about the generalization of the E–R anticorrelation and the relevance of plausible mechanisms. To explore the ubiquitous impact of expression levels on molecular evolution and test the relevance of the possible underlying mechanisms, we analyzed the genome sequences of 99 strains of Escherichia coli for evolution within species in nature. We also analyzed genomic mutations accumulated under laboratory conditions as a model of de novo evolution within species. Here, we show that E–R anticorrelation is significant in both past and de novo evolution within species in E. coli. Our data also confirmed ongoing purifying selection on highly expressed genes. Ongoing selection included codon-level purifying selection, supporting the relevance of the underlying mechanisms. However, the impact of codon-level purifying selection on the constraints in evolution within species might be smaller than previously expected from evolution between species.

Controlling gene expression with deep generative design of regulatory DNA

Design of de novo synthetic regulatory DNA is a promising avenue to control gene expression in biotechnology and medicine. Using mutagenesis typically requires screening sizable random DNA libraries, which limits the designs to span merely a short section of the promoter and restricts their control of gene expression. Here, we prototype a deep learning strategy based on generative adversarial networks (GAN) by learning directly from genomic and transcriptomic data. Our ExpressionGAN can traverse the entire regulatory sequence-expression landscape in a gene-specific manner, generating regulatory DNA with prespecified target mRNA levels spanning the whole gene regulatory structure including coding and adjacent non-coding regions. Despite high sequence divergence from natural DNA, in vivo measurements show that 57% of the highly-expressed synthetic sequences surpass the expression levels of highly-expressed natural controls. This demonstrates the applicability and relevance of deep generative design to expand our knowledge and control of gene expression regulation in any desired organism, condition or tissue.

Design of de novo synthetic regulatory DNA is a promising avenue to control gene expression in biotechnology and medicine. Here the authors present EspressionGAN, a generative adversarial network that uses genomic and transcriptomic data to generate regulatory sequences.

Experimental exploration of a ribozyme neutral network using evolutionary algorithm and deep learning

A neutral network connects all genotypes with equivalent phenotypes in a fitness landscape and plays an important role in the mutational robustness and evolvability of biomolecules. In contrast to earlier theoretical works, evidence of large neutral networks has been lacking in recent experimental studies of fitness landscapes. This suggests that evolution could be constrained globally. Here, we demonstrate that a deep learning-guided evolutionary algorithm can efficiently identify neutral genotypes within the sequence space of an RNA ligase ribozyme. Furthermore, we measure the activities of all 2¹⁶ variants connecting two active ribozymes that differ by 16 mutations and analyze mutational interactions (epistasis) up to the 16th order. We discover an extensive network of neutral paths linking the two genotypes and reveal that these paths might be predicted using only information from lower-order interactions. Our experimental evaluation of over 120,000 ribozyme sequences provides important empirical evidence that neutral networks can increase the accessibility and predictability of the fitness landscape.

Neutral networks, which are sets of genotypes connected via single mutations that share the same phenotype, are important for evolvability. Here, the authors provide experimental evidence of a neutral network in an RNA enzyme using a high-throughput assay and deep learning.

Incomplete Penetrance and Variable Expressivity: From Clinical Studies to Population Cohorts

The same genetic variant found in different individuals can cause a range of diverse phenotypes, from no discernible clinical phenotype to severe disease, even among related individuals. Such variants can be said to display incomplete penetrance, a binary phenomenon where the genotype either causes the expected clinical phenotype or it does not, or they can be said to display variable expressivity, in which the same genotype can cause a wide range of clinical symptoms across a spectrum. Both incomplete penetrance and variable expressivity are thought to be caused by a range of factors, including common variants, variants in regulatory regions, epigenetics, environmental factors, and lifestyle. Many thousands of genetic variants have been identified as the cause of monogenic disorders, mostly determined through small clinical studies, and thus, the penetrance and expressivity of these variants may be overestimated when compared to their effect on the general population. With the wealth of population cohort data currently available, the penetrance and expressivity of such genetic variants can be investigated across a much wider contingent, potentially helping to reclassify variants that were previously thought to be completely penetrant. Research into the penetrance and expressivity of such genetic variants is important for clinical classification, both for determining causative mechanisms of disease in the affected population and for providing accurate risk information through genetic counseling. A genotype-based definition of the causes of rare diseases incorporating information from population cohorts and clinical studies is critical for our understanding of incomplete penetrance and variable expressivity. This review examines our current knowledge of the penetrance and expressivity of genetic variants in rare disease and across populations, as well as looking into the potential causes of the variation seen, including genetic modifiers, mosaicism, and polygenic factors, among others. We also considered the challenges that come with investigating penetrance and expressivity.

Liverwort oil bodies: diversity, biochemistry, and molecular cell biology of the earliest secretory structure of land plants

Liverworts are known for their large chemical diversity. Much of this diversity is synthesized and enclosed within oil bodies (OBs), a synapomorphy of the lineage. OBs contain the enzymes to biosynthesize and store large quantities of sesquiterpenoids and other compounds while limiting their cytotoxicity. Recent important biochemical and molecular discoveries related to OB formation, diversity, and biochemistry allow comparison with other secretory structures of land plants from an evo-devo perspective. This review addresses and discusses the most recent advances in OB origin, development, and function towards understanding the importance of these organelles in liverwort physiology and adaptation to changing environments. Our mapping of OB types and chemical compounds to the current liverwort phylogeny suggests that OBs were present in the most recent common ancestor of liverworts, supporting that OBs evolved as the first secretory structures in land plants. Yet, we require better sampling to define the macroevolutionary pattern governing the ancestral type of OB. We conclude that current efforts to find molecular mechanisms responsible for the morphological and chemical diversity of secretory structures will help understand the evolution of each major group of land plants, and open new avenues in biochemical research on bioactive compounds in bryophytes and vascular plants.

Evolution of binding preferences among whole-genome duplicated transcription factors

Throughout evolution, new transcription factors (TFs) emerge by gene duplication, promoting growth and rewiring of transcriptional networks. How TF duplicates diverge was studied in a few cases only. To provide a genome-scale view, we considered the set of budding yeast TFs classified as whole-genome duplication (WGD)-retained paralogs (~35% of all specific TFs). Using high-resolution profiling, we find that ~60% of paralogs evolved differential binding preferences. We show that this divergence results primarily from variations outside the DNA-binding domains (DBDs), while DBD preferences remain largely conserved. Analysis of non-WGD orthologs revealed uneven splitting of ancestral preferences between duplicates, and the preferential acquiring of new targets by the least conserved paralog (biased neo/sub-functionalization). Interactions between paralogs were rare, and, when present, occurred through weak competition for DNA-binding or dependency between dimer-forming paralogs. We discuss the implications of our findings for the evolutionary design of transcriptional networks.

Notch-dependent DNA cis-regulatory elements and their dose-dependent control of C. elegans stem cell self-renewal

A long-standing biological question is how DNA cis-regulatory elements shape transcriptional patterns during metazoan development. Reporter constructs, cell culture assays and computational modeling have made major contributions to answering this question, but analysis of elements in their natural context is an important complement. Here, we mutate Notch-dependent LAG-1 binding sites (LBSs) in the endogenous Caenorhabditis elegans sygl-1 gene, which encodes a key stem cell regulator, and analyze the consequences on sygl-1 expression (nascent transcripts, mRNA, protein) and stem cell maintenance. Mutation of one LBS in a three-element cluster approximately halved both expression and stem cell pool size, whereas mutation of two LBSs essentially abolished them. Heterozygous LBS mutant clusters provided intermediate values. Our results lead to two major conclusions. First, both LBS number and configuration impact cluster activity: LBSs act additively in trans and synergistically in cis. Second, the SYGL-1 gradient promotes self-renewal above its functional threshold and triggers differentiation below the threshold. Our approach of coupling CRISPR/Cas9 LBS mutations with effects on both molecular and biological readouts establishes a powerful model for in vivo analyses of DNA cis-regulatory elements.

The evolution, evolvability and engineering of gene regulatory DNA

Mutations in non-coding regulatory DNA sequences can alter gene expression, organismal phenotype and fitness^1-3. Constructing complete fitness landscapes, in which DNA sequences are mapped to fitness, is a long-standing goal in biology, but has remained elusive because it is challenging to generalize reliably to vast sequence spaces^4-6. Here we build sequence-to-expression models that capture fitness landscapes and use them to decipher principles of regulatory evolution. Using millions of randomly sampled promoter DNA sequences and their measured expression levels in the yeast Saccharomyces cerevisiae, we learn deep neural network models that generalize with excellent prediction performance, and enable sequence design for expression engineering. Using our models, we study expression divergence under genetic drift and strong-selection weak-mutation regimes to find that regulatory evolution is rapid and subject to diminishing returns epistasis; that conflicting expression objectives in different environments constrain expression adaptation; and that stabilizing selection on gene expression leads to the moderation of regulatory complexity. We present an approach for using such models to detect signatures of selection on expression from natural variation in regulatory sequences and use it to discover an instance of convergent regulatory evolution. We assess mutational robustness, finding that regulatory mutation effect sizes follow a power law, characterize regulatory evolvability, visualize promoter fitness landscapes, discover evolvability archetypes and illustrate the mutational robustness of natural regulatory sequence populations. Our work provides a general framework for designing regulatory sequences and addressing fundamental questions in regulatory evolution.

Non-coding driver mutations in human cancer

Tumour formation involves random mutagenic events and positive evolutionary selection acting on a subset of such events, referred to as driver mutations. A decade of careful surveying of tumour DNA using exome-based analyses has revealed a multitude of protein-coding somatic driver mutations, some of which are clinically actionable. Today, a transition towards whole-genome analysis is well under way, technically enabling the discovery of potential driver mutations occurring outside protein-coding sequences. Mutations are abundant in this vast non-coding space, which is more than 50 times larger than the coding exome, but reliable identification of selection signals in non-coding DNA remains a challenge. In this Review, we discuss recent findings in the field, where the emerging landscape is one in which non-coding driver mutations appear to be relatively infrequent. Nevertheless, we highlight several notable discoveries. We consider possible reasons for the relative absence of non-coding driver events, as well as the difficulties associated with detecting signals of positive selection in non-coding DNA.

EBF1 and PAX5 control pro-B cell expansion via opposing regulation of the Myc gene

Genes encoding B lineage-restricted transcription factors are frequently mutated in B-lymphoid leukemias, suggesting a close link between normal and malignant B-cell development. One of these transcription factors is early B-cell factor 1 (EBF1), a protein of critical importance for lineage specification and survival of B-lymphoid progenitors. Here, we report that impaired EBF1 function in mouse B-cell progenitors results in reduced expression of Myc. Ectopic expression of MYC partially rescued B-cell expansion in the absence of EBF1 both in vivo and in vitro. Using chromosome conformation analysis in combination with ATAC-sequencing, chromatin immunoprecipitation-sequencing, and reporter gene assays, six EBF1-responsive enhancer elements were identified within the Myc locus. CRISPR-Cas9-mediated targeting of EBF1-binding sites identified one element of key importance for Myc expression and pro-B cell expansion. These data provide evidence that Myc is a direct target of EBF1. Furthermore, chromatin immunoprecipitation-sequencing analysis revealed that several regulatory elements in the Myc locus are targets of PAX5. However, ectopic expression of PAX5 in EBF1-deficient cells inhibits the cell cycle and reduces Myc expression, suggesting that EBF1 and PAX5 act in an opposing manner to regulate Myc levels. This hypothesis is further substantiated by the finding that Pax5 inactivation reduces requirements for EBF1 in pro-B-cell expansion. The binding of EBF1 and PAX5 to regulatory elements in the human MYC gene in a B-cell acute lymphoblastic leukemia cell line indicates that the EBF1:PAX5:MYC regulatory loop is conserved and may control both normal and malignant B-cell development.

B Lymphocyte Specification Is Preceded by Extensive Epigenetic Priming in Multipotent Progenitors

B lymphocyte development is dependent on the interplay between the chromatin landscape and lineage-specific transcription factors. It has been suggested that B lineage commitment is associated with major changes in the nuclear chromatin environment, proposing a critical role for lineage-specific transcription factors in the formation of the epigenetic landscape. In this report, we have used chromosome conformation capture in combination with assay for transposase-accessible chromatin sequencing analysis to enable highly efficient annotation of both proximal and distal transcriptional control elements to genes activated in B lineage specification in mice. A large majority of these genes were annotated to at least one regulatory element with an accessible chromatin configuration in multipotent progenitors. Furthermore, the majority of binding sites for the key regulators of B lineage specification, EBF1 and PAX5, occurred in already accessible regions. EBF1 did, however, cause a dynamic change in assay for transposase-accessible chromatin accessibility and was critical for an increase in distal promoter-enhancer interactions. Our data unravel an extensive epigenetic priming at regulatory elements annotated to lineage-restricted genes and provide insight into the interplay between the epigenetic landscape and transcription factors in cell specification.

A Genomic Survey of Signalling in the Myxococcaceae

As prokaryotes diverge by evolution, essential 'core' genes required for conserved phenotypes are preferentially retained, while inessential 'accessory' genes are lost or diversify. We used the recently expanded number of myxobacterial genome sequences to investigate the conservation of their signalling proteins, focusing on two sister genera (Myxococcus and Corallococcus), and on a species within each genus (Myxococcus xanthus and Corallococcus exiguus). Four new C. exiguus genome sequences are also described here. Despite accessory genes accounting for substantial proportions of each myxobacterial genome, signalling proteins were found to be enriched in the core genome, with two-component system genes almost exclusively so. We also investigated the conservation of signalling proteins in three myxobacterial behaviours. The linear carotenogenesis pathway was entirely conserved, with no gene gain/loss observed. However, the modular fruiting body formation network was found to be evolutionarily plastic, with dispensable components in all modules (including components required for fruiting in the model myxobacterium M. xanthus DK1622). Quorum signalling (QS) is thought to be absent from most myxobacteria, however, they generally appear to be able to produce CAI-I (cholerae autoinducer-1), to sense other QS molecules, and to disrupt the QS of other organisms, potentially important abilities during predation of other prokaryotes.

Functional effects of protein variants

Genetic and other variations frequently affect protein functions. Scientific articles can contain confusing descriptions about which function or property is affected, and in many cases the statements are pure speculation without any experimental evidence. To clarify functional effects of protein variations of genetic or non-genetic origin, a systematic conceptualisation and framework are introduced. This framework describes protein functional effects on abundance, activity, specificity and affinity, along with countermeasures, which allow cells, tissues and organisms to tolerate, avoid, repair, attenuate or resist (TARAR) the effects. Effects on abundance discussed include gene dosage, restricted expression, mis-localisation and degradation. Enzymopathies, effects on kinetics, allostery and regulation of protein activity are subtopics for the effects of variants on activity. Variation outcomes on specificity and affinity comprise promiscuity, specificity, affinity and moonlighting. TARAR mechanisms redress variations with active and passive processes including chaperones, redundancy, robustness, canalisation and metabolic and signalling rewiring. A framework for pragmatic protein function analysis and presentation is introduced. All of the mechanisms and effects are described along with representative examples, most often in relation to diseases. In addition, protein function is discussed from evolutionary point of view. Application of the presented framework facilitates unambiguous, detailed and specific description of functional effects and their systematic study.

Canalization and Robustness in Human Genetics and Disease

Canalization refers to the evolution of populations such that the number of individuals who deviate from the optimum trait, or experience disease, is minimized. In the presence of rapid cultural, environmental, or genetic change, the reverse process of decanalization may contribute to observed increases in disease prevalence. This review starts by defining relevant concepts, drawing distinctions between the canalization of populations and robustness of individuals. It then considers evidence pertaining to three continuous traits and six domains of disease. In each case, existing genetic evidence for genotype-by-environment interactions is insufficient to support a strong inference of decanalization, but we argue that the advent of genome-wide polygenic risk assessment now makes an empirical evaluation of the role of canalization in preventing disease possible. Finally, the contributions of both rare and common variants to congenital abnormality and adult onset disease are considered in light of a new kerplunk model of genetic effects.

Using optogenetics to tackle systems-level questions of multicellular morphogenesis

Morphogenesis of multicellular systems is governed by precise spatiotemporal regulation of biochemical reactions and mechanical forces which together with environmental conditions determine the development of complex organisms. Current efforts in the field aim at decoding the system-level principles underlying the regulation of developmental processes. Toward this goal, optogenetics, the science of regulation of protein function with light, is emerging as a powerful new tool to quantitatively perturb protein function in vivo with unprecedented precision in space and time. In this review, we provide an overview of how optogenetics is helping to address system-level questions of multicellular morphogenesis and discuss future directions.

Disparate expression specificities coded by a shared Hox-C enhancer

Can a single regulatory sequence be shared by two genes undergoing functional divergence? Here we describe a single promiscuous enhancer within the Drosophila Antennapedia Complex, EO053, that directs aspects of the expression of two adjacent genes, pb (a Hox2 ortholog) and zen2 (a divergent Hox3 paralog), with disparate spatial and temporal expression patterns. We were unable to separate the pb-like and zen2-like specificities within EO053, and we identify sequences affecting both expression patterns. Importantly, genomic deletion experiments demonstrate that EO053 cooperates with additional pb- and zen2-specific enhancers to regulate the mRNA expression of both genes. We examine sequence conservation of EO053 within the Schizophora, and show that patterns of synteny between the Hox2 and Hox3 orthologs in Arthropods are consistent with a shared regulatory relationship extending prior to the Hox3/zen divergence. Thus, EO053 represents an example of two genes having evolved disparate outputs while utilizing this shared regulatory region.

Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

GATA3-Controlled Nucleosome Eviction Drives MYC Enhancer Activity in T-cell Development and Leukemia

Long-range enhancers govern the temporal and spatial control of gene expression; however, the mechanisms that regulate enhancer activity during normal and malignant development remain poorly understood. Here, we demonstrate a role for aberrant chromatin accessibility in the regulation of MYC expression in T-cell lymphoblastic leukemia (T-ALL). Central to this process, the NOTCH1-MYC enhancer (N-Me), a long-range T cell-specific MYC enhancer, shows dynamic changes in chromatin accessibility during T-cell specification and maturation and an aberrant high degree of chromatin accessibility in mouse and human T-ALL cells. Mechanistically, we demonstrate that GATA3-driven nucleosome eviction dynamically modulates N-Me enhancer activity and is strictly required for NOTCH1-induced T-ALL initiation and maintenance. These results directly implicate aberrant regulation of chromatin accessibility at oncogenic enhancers as a mechanism of leukemic transformation. SIGNIFICANCE: MYC is a major effector of NOTCH1 oncogenic programs in T-ALL. Here, we show a major role for GATA3-mediated enhancer nucleosome eviction as a driver of MYC expression and leukemic transformation. These results support the role of aberrant chromatin accessibility and consequent oncogenic MYC enhancer activation in NOTCH1-induced T-ALL.This article is highlighted in the In This Issue feature, p. 1631.

Plasticity of Promoter-Core Sequences Allows Bacteria to Compensate for the Loss of a Key Global Regulatory Gene

Transcription regulatory networks (TRNs) are of central importance for both short-term phenotypic adaptation in response to environmental fluctuations and long-term evolutionary adaptation, with global regulatory genes often being targets of natural selection in laboratory experiments. Here, we combined evolution experiments, whole-genome resequencing, and molecular genetics to investigate the driving forces, genetic constraints, and molecular mechanisms that dictate how bacteria can cope with a drastic perturbation of their TRNs. The crp gene, encoding a major global regulator in Escherichia coli, was deleted in four different genetic backgrounds, all derived from the Long-Term Evolution Experiment (LTEE) but with different TRN architectures. We confirmed that crp deletion had a more deleterious effect on growth rate in the LTEE-adapted genotypes; and we showed that the ptsG gene, which encodes the major glucose-PTS transporter, gained CRP (cyclic AMP receptor protein) dependence over time in the LTEE. We then further evolved the four crp-deleted genotypes in glucose minimal medium, and we found that they all quickly recovered from their growth defects by increasing glucose uptake. We showed that this recovery was specific to the selective environment and consistently relied on mutations in the cis-regulatory region of ptsG, regardless of the initial genotype. These mutations affected the interplay of transcription factors acting at the promoters, changed the intrinsic properties of the existing promoters, or produced new transcription initiation sites. Therefore, the plasticity of even a single promoter region can compensate by three different mechanisms for the loss of a key regulatory hub in the E. coli TRN.

Physiology of Electrolyte Transport in the Gut: Implications for Disease

We now have an increased understanding of the genetics, cell biology, and physiology of electrolyte transport processes in the mammalian intestine, due to the availability of sophisticated methodologies ranging from genome wide association studies to CRISPR-CAS technology, stem cell-derived organoids, 3D microscopy, electron cryomicroscopy, single cell RNA sequencing, transgenic methodologies, and tools to manipulate cellular processes at a molecular level. This knowledge has simultaneously underscored the complexity of biological systems and the interdependence of multiple regulatory systems. In addition to the plethora of mammalian neurohumoral factors and their cross talk, advances in pyrosequencing and metagenomic analyses have highlighted the relevance of the microbiome to intestinal regulation. This article provides an overview of our current understanding of electrolyte transport processes in the small and large intestine, their regulation in health and how dysregulation at multiple levels can result in disease. Intestinal electrolyte transport is a balance of ion secretory and ion absorptive processes, all exquisitely dependent on the basolateral Na⁺ /K⁺ ATPase; when this balance goes awry, it can result in diarrhea or in constipation. The key transporters involved in secretion are the apical membrane Cl^- channels and the basolateral Na⁺ -K⁺ -2Cl^- cotransporter, NKCC1 and K⁺ channels. Absorption chiefly involves apical membrane Na⁺ /H⁺ exchangers and Cl^- /HCO₃ ^- exchangers in the small intestine and proximal colon and Na⁺ channels in the distal colon. Key examples of our current understanding of infectious, inflammatory, and genetic diarrheal diseases and of constipation are provided. © 2019 American Physiological Society. Compr Physiol 9:947-1023, 2019.

Complex Relationships between Chromatin Accessibility, Sequence Divergence, and Gene Expression in Arabidopsis thaliana

Variation in regulatory DNA is thought to drive phenotypic variation, evolution, and disease. Prior studies of regulatory DNA and transcription factors across animal species highlighted a fundamental conundrum: Transcription factor binding domains and cognate binding sites are conserved, while regulatory DNA sequences are not. It remains unclear how conserved transcription factors and dynamic regulatory sites produce conserved expression patterns across species. Here, we explore regulatory DNA variation and its functional consequences within Arabidopsis thaliana, using chromatin accessibility to delineate regulatory DNA genome-wide. Unlike in previous cross-species comparisons, the positional homology of regulatory DNA is maintained among A. thaliana ecotypes and less nucleotide divergence has occurred. Of the ∼50,000 regulatory sites in A. thaliana, we found that 15% varied in accessibility among ecotypes. Some of these accessibility differences were associated with extensive, previously unannotated sequence variation, encompassing many deletions and ancient hypervariable alleles. Unexpectedly, for the majority of such regulatory sites, nearby gene expression was unaffected. Nevertheless, regulatory sites with high levels of sequence variation and differential chromatin accessibility were the most likely to be associated with differential gene expression. Finally, and most surprising, we found that the vast majority of differentially accessible sites show no underlying sequence variation. We argue that these surprising results highlight the necessity to consider higher-order regulatory context in evaluating regulatory variation and predicting its phenotypic consequences.

Evolution and Diversification of FRUITFULL Genes in Solanaceae

Ecologically and economically important fleshy edible fruits have evolved from dry fruit numerous times during angiosperm diversification. However, the molecular mechanisms that underlie these shifts are unknown. In the Solanaceae there has been a major shift to fleshy fruits in the subfamily Solanoideae. Evidence suggests that an ortholog of FRUITFULL (FUL), a transcription factor that regulates cell proliferation and limits the dehiscence zone in the silique of Arabidopsis, plays a similar role in dry-fruited Solanaceae. However, studies have shown that FUL orthologs have taken on new functions in fleshy fruit development, including regulating elements of tomato ripening such as pigment accumulation. FUL belongs to the core eudicot euFUL clade of the angiosperm AP1/FUL gene lineage. The euFUL genes fall into two paralogous clades, euFULI and euFULII. While most core eudicots have one gene in each clade, Solanaceae have two: FUL1 and FUL2 in the former, and MBP10 and MBP20 in the latter. We characterized the evolution of the euFUL genes to identify changes that might be correlated with the origin of fleshy fruit in Solanaceae. Our analyses revealed that the Solanaceae FUL1 and FUL2 clades probably originated through an early whole genome multiplication event. By contrast, the data suggest that the MBP10 and MBP20 clades are the result of a later tandem duplication event. MBP10 is expressed at weak to moderate levels, and its atypical short first intron lacks putative transcription factor binding sites, indicating possible pseudogenization. Consistent with this, our analyses show that MBP10 is evolving at a faster rate compared to MBP20. Our analyses found that Solanaceae euFUL gene duplications, evolutionary rates, and changes in protein residues and expression patterns are not correlated with the shift in fruit type. This suggests deeper analyses are needed to identify the mechanism underlying the change in FUL ortholog function.

Integrating molecular networks with genetic variant interpretation for precision medicine

More reliable and cheaper sequencing technologies have revealed the vast mutational landscapes characteristic of many phenotypes. The analysis of such genetic variants has led to successful identification of altered proteins underlying many Mendelian disorders. Nevertheless the simple one‐variant one‐phenotype model valid for many monogenic diseases does not capture the complexity of polygenic traits and disorders. Although experimental and computational approaches have improved detection of functionally deleterious variants and important interactions between gene products, the development of comprehensive models relating genotype and phenotypes remains a challenge in the field of genomic medicine. In this context, a new view of the pathologic state as significant perturbation of the network of interactions between biomolecules is crucial for the identification of biochemical pathways associated with complex phenotypes. Seminal studies in systems biology combined the analysis of genetic variation with protein–protein interaction networks to demonstrate that even as biological systems evolve to be robust to genetic variation, their topologies create disease vulnerabilities. More recent analyses model the impact of genetic variants as changes to the “wiring” of the interactome to better capture heterogeneity in genotype–phenotype relationships. These studies lay the foundation for using networks to predict variant effects at scale using machine‐learning or algorithmic approaches. A wealth of databases and resources for the annotation of genotype–phenotype relationships have been developed to support developments in this area. This overview describes how study of the molecular interactome has generated insights linking the organization of biological systems to disease mechanism, and how this information can enable precision medicine.

This article is categorized under:

Translational, Genomic, and Systems Medicine > Translational Medicine

Biological Mechanisms > Cell Signaling

Models of Systems Properties and Processes > Mechanistic Models

Analytical and Computational Methods > Computational Methods

Plant Lineage-Specific Amplification of Transcription Factor Binding Motifs by Miniature Inverted-Repeat Transposable Elements (MITEs)

Transposable elements are one of the main drivers of plant genome evolution. Transposon insertions can modify the gene coding capacity or the regulation of their expression, the latter being a more subtle effect, and therefore particularly useful for evolution. Transposons have been show to contain transcription factor binding sites that can be mobilized upon transposition with the potential to integrate new genes into transcriptional networks. Miniature inverted-repeat transposable elements (MITEs) are a type of noncoding DNA transposons that could be particularly suited as a vector to mobilize transcription factor binding sites and modify transcriptional networks during evolution. MITEs are small in comparison to other transposons and can be excised, which should make them less mutagenic when inserting into promoters. On the other hand, in spite of their cut-and-paste mechanisms of transposition, they can reach very high copy numbers in genomes. We have previously shown that MITEs have amplified and redistributed the binding motif of the E2F transcription factor in different Brassicas. Here, we show that MITEs have amplified and mobilized the binding motifs of the bZIP60 and PIF3 transcription factors in peach and Prunus mume, and the TCP15/23 binding motif in tomato. Our results suggest that MITEs could have rewired new genes into transcriptional regulatory networks that are responsible for important adaptive responses and breeding traits in plants, such as stress responses, flowering time, or fruit ripening. The results presented here therefore suggest a general impact of MITEs in the evolution of transcriptional regulatory networks in plants.

Expression of SULTR2;2, encoding a low-affinity sulphur transporter, in the Arabidopsis bundle sheath and vein cells is mediated by a positive regulator

The bundle sheath provides a conduit linking veins and mesophyll cells. In the C3 plant Arabidopsis thaliana, it also plays important roles in oxidative stress and sulphur metabolism. However, the mechanisms responsible for the patterns of gene expression that underpin these metabolic specializations are poorly understood. Here, we used the Arabidopsis SULTR2;2 gene as a model to better understand mechanisms that restrict expression to the bundle sheath. Deletion analysis indicated that the SULTR2;2 promoter contains a short region necessary for expression in the bundle sheath and veins. This sequence acts as a positive regulator and is tolerant to multiple consecutive deletions indicating considerable redundancy in the cis-elements involved. It is highly conserved in SULTR2;2 genes of the Brassicaceae and is functional in the distantly related C4 species Flaveria bidentis that belongs to the Asteraceae. We conclude that expression of SULTR2;2 in the bundle sheath and veins is underpinned by a highly redundant sequence that likely represents an ancient and conserved mechanism found in families as diverse as the Asteraceae and Brassicaceae.

Epigenetic and Cellular Diversity in the Brain through Allele-Specific Effects

The benefits of diploidy are considered to involve masking partially recessive mutations and increasing genetic diversity. Here, we review new studies showing evidence for diverse allele-specific expression and epigenetic states in mammalian brain cells, which suggest that diploidy expands the landscape of gene regulatory and expression programs in cells. Allele-specific expression has been thought to be restricted to a few specific classes of genes. However, new studies show novel genomic imprinting effects that are brain-region-, cell-type- and age-dependent. In addition, novel forms of random monoallelic expression that impact many autosomal genes have been described in vitro and in vivo. We discuss the implications for understanding the benefits of diploidy, and the mechanisms shaping brain development, function, and disease.

RNA-mediated gene regulation is less evolvable than transcriptional regulation

Cells regulate the activity of genes in a variety of ways. For example, they regulate transcription through DNA binding proteins called transcription factors, and they regulate mRNA stability and processing through RNA binding proteins. Based on current knowledge, transcriptional regulation is more widespread and is involved in many more evolutionary adaptations than posttranscriptional regulation. The reason could be that transcriptional regulation is studied more intensely. We suggest instead that transcriptional regulation harbors an intrinsic evolutionary advantage: when mutations change transcriptional regulation, they are more likely to bring forth novel patterns of such regulation. That is, transcriptional regulation is more evolvable. Our analysis suggests a reason why a specific kind of gene regulation is especially abundant in the living world.

Much of gene regulation is carried out by proteins that bind DNA or RNA molecules at specific sequences. One class of such proteins is transcription factors, which bind short DNA sequences to regulate transcription. Another class is RNA binding proteins, which bind short RNA sequences to regulate RNA maturation, transport, and stability. Here, we study the robustness and evolvability of these regulatory mechanisms. To this end, we use experimental binding data from 172 human and fruit fly transcription factors and RNA binding proteins as well as human polymorphism data to study the evolution of binding sites in vivo. We find little difference between the robustness of regulatory protein–RNA interactions and transcription factor–DNA interactions to DNA mutations. In contrast, we find that RNA-mediated regulation is less evolvable than transcriptional regulation, because mutations are less likely to create interactions of an RNA molecule with a new RNA binding protein than they are to create interactions of a gene regulatory region with a new transcription factor. Our observations are consistent with the high level of conservation observed for interactions between RNA binding proteins and their target molecules as well as the evolutionary plasticity of regulatory regions bound by transcription factors. They may help explain why transcriptional regulation is implicated in many more evolutionary adaptations and innovations than RNA-mediated gene regulation.

Pathogens and Disease Play Havoc on the Host Epiproteome-The "First Line of Response" Role for Proteomic Changes Influenced by Disorder

Organisms face stress from multiple sources simultaneously and require mechanisms to respond to these scenarios if they are to survive in the long term. This overview focuses on a series of key points that illustrate how disorder and post-translational changes can combine to play a critical role in orchestrating the response of organisms to the stress of a changing environment. Increasingly, protein complexes are thought of as dynamic multi-component molecular machines able to adapt through compositional, conformational and/or post-translational modifications to control their largely metabolic outputs. These metabolites then feed into cellular physiological homeostasis or the production of secondary metabolites with novel anti-microbial properties. The control of adaptations to stress operates at multiple levels including the proteome and the dynamic nature of proteomic changes suggests a parallel with the equally dynamic epigenetic changes at the level of nucleic acids. Given their properties, I propose that some disordered protein platforms specifically enable organisms to sense and react rapidly as the first line of response to change. Using examples from the highly dynamic host-pathogen and host-stress response, I illustrate by example how disordered proteins are key to fulfilling the need for multiple levels of integration of response at different time scales to create robust control points.

K2P TASK-2 and KCNQ1-KCNE3 K+ channels are major players contributing to intestinal anion and fluid secretion

KEY POINTS

K⁺ channels are important in intestinal epithelium as they ensure the ionic homeostasis and electrical potential of epithelial cells during anion and fluid secretion. Intestinal epithelium cAMP-activated anion secretion depends on the activity of the (also cAMP dependent) KCNQ1-KCNE3 K⁺ channel, but the secretory process survives after genetic inactivation of the K⁺ channel in the mouse. Here we use double mutant mice to investigate which alternative K⁺ channels come into action to compensate for the absence of KCNQ1-KCNE3 K⁺ channels. Our data establish that whilst Ca²⁺ -activated K_Ca 3.1 channels are not involved, K_2P two-pore domain TASK-2 K⁺ channels are major players providing an alternative conductance to sustain the intestinal secretory process. Work with double mutant mice lacking both TASK-2 and KCNQ1-KCNE3 channels nevertheless points to yet-unidentified K⁺ channels that contribute to the robustness of the cAMP-activated anion secretion process.

ABSTRACT

Anion and fluid secretion across the intestinal epithelium, a process altered in cystic fibrosis and secretory diarrhoea, is mediated by cAMP-activated CFTR Cl^- channels and requires the simultaneous activity of basolateral K⁺ channels to maintain cellular ionic homeostasis and membrane potential. This function is fulfilled by the cAMP-activated K⁺ channel formed by the association of pore-forming KCNQ1 with its obligatory KCNE3 β-subunit. Studies using mice show sizeable cAMP-activated intestinal anion secretion in the absence of either KCNQ1 or KCNE3 suggesting that an alternative K⁺ conductance must compensate for the loss of KCNQ1-KCNE3 activity. We used double mutant mouse and pharmacological approaches to identify such a conductance. Ca²⁺ -dependent anion secretion can also be supported by Ca²⁺ -dependent K_Ca 3.1 channels after independent CFTR activation, but cAMP-dependent anion secretion is not further decreased in the combined absence of K_Ca 3.1 and KCNQ1-KCNE3 K⁺ channel activity. We show that the K_2P K⁺ channel TASK-2 is expressed in the epithelium of the small and large intestine. Tetrapentylammonium, a TASK-2 inhibitor, abolishes anion secretory current remaining in the absence of KCNQ1-KCNE3 activity. A double mutant mouse lacking both KCNQ1-KCNE3 and TASK-2 showed a much reduced cAMP-mediated anion secretion compared to that observed in the single KCNQ1-KCNE3 deficient mouse. We conclude that KCNQ1-KCNE3 and TASK-2 play major roles in the intestinal anion and fluid secretory phenotype. The persistence of an, admittedly reduced, secretory activity in the absence of these two conductances suggests that further additional K⁺ channel(s) as yet unidentified contribute to the robustness of the intestinal anion secretory process.

Evolution of floral diversity: genomics, genes and gamma

A salient feature of flowering plant diversification is the emergence of a novel suite of floral features coinciding with the origin of the most species-rich lineage, Pentapetalae. Advances in phylogenetics, developmental genetics and genomics, including new analyses presented here, are helping to reconstruct the specific evolutionary steps involved in the evolution of this clade. The enormous floral diversity among Pentapetalae appears to be built on a highly conserved ground plan of five-parted (pentamerous) flowers with whorled phyllotaxis. By contrast, lability in the number and arrangement of component parts of the flower characterize the early-diverging eudicot lineages subtending Pentapetalae. The diversification of Pentapetalae also coincides closely with ancient hexaploidy, referred to as the gamma whole-genome triplication, for which the phylogenetic timing, mechanistic details and molecular evolutionary consequences are as yet not fully resolved. Transcription factors regulating floral development often persist in duplicate or triplicate in gamma-derived genomes, and both individual genes and whole transcriptional programmes exhibit a shift from broadly overlapping to tightly defined expression domains in Pentapetalae flowers. Investigations of these changes associated with the origin of Pentapetalae can lead to a more comprehensive understanding of what is arguably one of the most important evolutionary diversification events within terrestrial plants.This article is part of the themed issue 'Evo-devo in the genomics era, and the origins of morphological diversity'.