Non-base-contacting residues enable kaleidoscopic evolution of metazoan C2H2 zinc finger DNA binding

New Drosophila promoter-associated architectural protein Mzfp1 interacts with CP190 and is required for housekeeping gene expression and insulator activity

In Drosophila, a group of zinc finger architectural proteins recruits the CP190 protein to the chromatin, an interaction that is essential for the functional activity of promoters and insulators. In this study, we describe a new architectural C2H2 protein called Madf and Zinc-Finger Protein 1 (Mzfp1) that interacts with CP190. Mzfp1 has an unusual structure that includes six C2H2 domains organized in a C-terminal cluster and two tandem MADF domains. Mzfp1 predominantly binds to housekeeping gene promoters located in both euchromatin and heterochromatin genome regions. In vivo mutagenesis studies showed that Mzfp1 is an essential protein, and both MADF domains and the CP190 interaction region are required for its functional activity. The C2H2 cluster is sufficient for the specific binding of Mzfp1 to regulatory elements, while the second MADF domain is required for Mzfp1 recruitment to heterochromatin. Mzfp1 binds to the proximal part of the Fub boundary that separates regulatory domains of the Ubx and abd-A genes in the Bithorax complex. Mzfp1 participates in Fub functions in cooperation with the architectural proteins Pita and Su(Hw). Thus, Mzfp1 is a new architectural C2H2 protein involved in the organization of active promoters and insulators in Drosophila.

Emergence of the ZNF675 Gene During Primate Evolution-Influenced Human Neurodevelopment Through Changing HES1 Autoregulation

In this study, we investigated recurrent copy number variations (CNVs) in the 19p12 locus, which are associated with neurodevelopmental disorders. The two genes in this locus, ZNF675 and ZNF681, arose via gene duplication in primates, and their presence in several pathological CNVs in the human population suggests that either or both of these genes are required for normal human brain development. ZNF675 and ZNF681 are members of the Krüppel-associated box zinc finger (KZNF) protein family, a class of transcriptional repressors important for epigenetic silencing of specific genomic regions. About 170 primate-specific KZNFs are present in the human genome. Although KZNFs are primarily associated with repressing retrotransposon-derived DNA, evidence is emerging that they can be co-opted for other gene regulatory processes. We show that genetic deletion of ZNF675 causes developmental defects in cortical organoids, and our data suggest that part of the observed neurodevelopmental phenotype is mediated by a gene regulatory role of ZNF675 on the promoter of the neurodevelopmental gene Hes family BHLH transcription factor 1 (HES1). We also find evidence for the recently evolved regulation of genes involved in neurological disorders, microcephalin 1 and sestrin 3. We show that ZNF675 interferes with HES1 auto-inhibition, a process essential for the maintenance of neural progenitors. As a striking example of how some KZNFs have integrated into preexisting gene expression networks, these findings suggest the emergence of ZNF675 has caused a change in the balance of HES1 autoregulation. The association of ZNF675 CNV with human developmental disorders and ZNF675-mediated regulation of neurodevelopmental genes suggests that it evolved into an important factor for human brain development.

An integrative approach to protein sequence design through multiobjective optimization

With recent methodological advances in the field of computational protein design, in particular those based on deep learning, there is an increasing need for frameworks that allow for coherent, direct integration of different models and objective functions into the generative design process. Here we demonstrate how evolutionary multiobjective optimization techniques can be adapted to provide such an approach. With the established Non-dominated Sorting Genetic Algorithm II (NSGA-II) as the optimization framework, we use AlphaFold2 and ProteinMPNN confidence metrics to define the objective space, and a mutation operator composed of ESM-1v and ProteinMPNN to rank and then redesign the least favorable positions. Using the two-state design problem of the foldswitching protein RfaH as an in-depth case study, and PapD and calmodulin as examples of higher-dimensional design problems, we show that the evolutionary multiobjective optimization approach leads to significant reduction in the bias and variance in RfaH native sequence recovery, compared to a direct application of ProteinMPNN. We suggest that this improvement is due to three factors: (i) the use of an informative mutation operator that accelerates the sequence space exploration, (ii) the parallel, iterative design process inherent to the genetic algorithm that improves upon the ProteinMPNN autoregressive sequence decoding scheme, and (iii) the explicit approximation of the Pareto front that leads to optimal design candidates representing diverse tradeoff conditions. We anticipate this approach to be readily adaptable to different models and broadly relevant for protein design tasks with complex specifications.

An integrative approach to protein sequence design through multiobjective optimization

With recent methodological advances in the field of computational protein design, in particular those based on deep learning, there is an increasing need for frameworks that allow for coherent, direct integration of different models and objective functions into the generative design process. Here we demonstrate how evolutionary multiobjective optimization techniques can be adapted to provide such an approach. With the established Non-dominated Sorting Genetic Algorithm II (NSGA-II) as the optimization framework, we use AlphaFold2 and ProteinMPNN confidence metrics to define the objective space, and a mutation operator composed of ESM-1v and ProteinMPNN to rank and then redesign the least favorable positions. Using the multistate design problem of the foldswitching protein RfaH as an in-depth case study, we show that the evolutionary multiobjective optimization approach leads to significant reduction in the bias and variance in RfaH native sequence recovery, compared to a direct application of ProteinMPNN. We suggest that this improvement is due to three factors: (i) the use of an informative mutation operator that accelerates the sequence space exploration, (ii) the parallel, iterative design process inherent to the genetic algorithm that improves upon the ProteinMPNN autoregressive sequence decoding scheme, and (iii) the explicit approximation of the Pareto front that leads to optimal design candidates representing diverse tradeoff conditions. We anticipate this approach to be readily adaptable to different models and broadly relevant for protein design tasks with complex specifications.

Uncovering nutrients and energy related gene functions of black soldier fly Hermetia illucens strain KUP

The black soldier fly (Hermetia illucens) has emerged as a significant insect species in the decomposition of organic waste for sustainable agricultural practices. Due to its remarkable characteristics and performance, H. illucens is increasingly utilised for insect farming, particularly for industrial-scale rearing throughout the world. In this study, we employed whole-genome sequencing to annotate the gene and protein functions of H. illucens and to explore the functional genomics related to nutrients and energy. As a result, a genome size of H. illucens strain KUP 1.68 Gb with a GC content of 42.13 % was achieved. Of the 14,036 coding sequences, we determined the function of 12,046 protein-coding genes. Based on metabolic functional assignment, we classified 4,218 protein-coding genes; the main category was metabolism (32.86 %). Comparative genomic analysis across the other H. illucens strain and insect species revealed that the major metabolic gene functions and pathways related to nutrient and energy sources of H. illucens KUP are involved in key amino acid metabolism (e.g., cysteine and methionine) as well as fatty acid biosynthesis and glycerolipid metabolism. These findings underscore the metabolic capability and versatility of H. illucens, which is regarded as a potential source of proteins and lipids. Our study contributes to the knowledge regarding the feed utilisation of H. illucens and offers insights into transforming waste into valuable products. H. illucens has the potential to create globally sustainable nutrients and environmentally friendly solutions, aligning with the goal of responsible resource utilisation.

Transposable elements drive the evolution of metazoan zinc finger genes

Cys2-His2 zinc finger genes (ZNFs) form the largest family of transcription factors in metazoans. ZNF evolution is highly dynamic and characterized by the rapid expansion and contraction of numerous subfamilies across the animal phylogeny. The forces and mechanisms underlying rapid ZNF evolution remain poorly understood, but there is growing evidence that, in tetrapods, the targeting and repression of lineage-specific transposable elements (TEs) plays a critical role in the evolution of the Krüppel-associated box ZNF (KZNF) subfamily. Currently, it is unknown whether this function and coevolutionary relationship is unique to KZNFs or is a broader feature of metazoan ZNFs. Here, we present evidence that genomic conflict with TEs has been a central driver of the diversification of ZNFs in animals. Sampling from 3221 genome assemblies, we show that the copy number of retroelements correlates with that of ZNFs across at least 750 million years of metazoan evolution. Using computational predictions, we show that ZNFs preferentially bind TEs in diverse animal species. We further investigate the largest ZNF subfamily found in cyprinid fish, which is characterized by a conserved sequence we dubbed the fish N-terminal zinc finger-associated (FiNZ) domain. Zebrafish possess approximately 700 FiNZ-ZNFs, many of which are evolving adaptively under positive selection. Like mammalian KZNFs, most zebrafish FiNZ-ZNFs are expressed at the onset of zygotic genome activation, and blocking their translation using morpholinos during early embryogenesis results in derepression of transcriptionally active TEs. Together, these data suggest that ZNF diversification has been intimately connected to TE expansion throughout animal evolution.

Genetic features and genomic targets of human KRAB-zinc finger proteins

Krüppel-associated box (KRAB) domain-containing zinc finger proteins (KZFPs) are one of the largest groups of transcription factors encoded by tetrapods, with 378 members in human alone. KZFP genes are often grouped in clusters reflecting amplification by gene and segment duplication since the gene family first emerged more than 400 million years ago. Previous work has revealed that many KZFPs recognize transposable element (TE)-embedded sequences as genomic targets, and that KZFPs facilitate the co-option of the regulatory potential of TEs for the benefit of the host. Here, we present a comprehensive survey of the genetic features and genomic targets of human KZFPs, notably completing past analyses by adding data on close to a hundred family members. General principles emerge from our study of the TE-KZFP regulatory system, which point to multipronged evolutionary mechanisms underlaid by highly complex and combinatorial modes of action with strong influences on human speciation.

RNA-binding proteins that lack canonical RNA-binding domains are rarely sequence-specific

Thousands of RNA-binding proteins (RBPs) crosslink to cellular mRNA. Among these are numerous unconventional RBPs (ucRBPs)-proteins that associate with RNA but lack known RNA-binding domains (RBDs). The vast majority of ucRBPs have uncharacterized RNA-binding specificities. We analyzed 492 human ucRBPs for intrinsic RNA-binding in vitro and identified 23 that bind specific RNA sequences. Most (17/23), including 8 ribosomal proteins, were previously associated with RNA-related function. We identified the RBDs responsible for sequence-specific RNA-binding for several of these 23 ucRBPs and surveyed whether corresponding domains from homologous proteins also display RNA sequence specificity. CCHC-zf domains from seven human proteins recognized specific RNA motifs, indicating that this is a major class of RBD. For Nudix, HABP4, TPR, RanBP2-zf, and L7Ae domains, however, only isolated members or closely related homologs yielded motifs, consistent with RNA-binding as a derived function. The lack of sequence specificity for most ucRBPs is striking, and we suggest that many may function analogously to chromatin factors, which often crosslink efficiently to cellular DNA, presumably via indirect recruitment. Finally, we show that ucRBPs tend to be highly abundant proteins and suggest their identification in RNA interactome capture studies could also result from weak nonspecific interactions with RNA.

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.

Adaptive evolvability through direct selection instead of indirect, second-order selection

Can evolvability itself be the product of adaptive evolution? To answer this question is challenging, because any DNA mutation that alters only evolvability is subject to indirect, "second order" selection on the future effects of this mutation. Such indirect selection is weaker than "first-order" selection on mutations that alter fitness, in the sense that it can operate only under restrictive conditions. Here I discuss a route to adaptive evolvability that overcomes this challenge. Specifically, a recent evolution experiment showed that some mutations can enhance both fitness and evolvability through a combination of direct and indirect selection. Unrelated evidence from gene duplication and the evolution of gene regulation suggests that mutations with such dual effects may not be rare. Through such mutations, evolvability may increase at least in part because it provides an adaptive advantage. These observations suggest a research program on the adaptive evolution of evolvability, which aims to identify such mutations and to disentangle their direct fitness effects from their indirect effects on evolvability. If evolvability is itself adaptive, Darwinian evolution may have created more than life's diversity. It may also have helped create the very conditions that made the success of Darwinian evolution possible.

Function and Evolution of C1-2i Subclass of C2H2-Type Zinc Finger Transcription Factors in POPLAR

C2H2 zinc finger (C2H2-ZF) transcription factors participate in various aspects of normal plant growth regulation and stress responses. C1-2i C2H2-ZFs are a special subclass of conserved proteins that contain two ZnF-C2H2 domains. Some C1-2i C2H2-ZFs in Arabidopsis (ZAT) are involved in stress resistance and other functions. However, there is limited information on C1-2i C2H2-ZFs in Populus trichocarpa (PtriZATs). To analyze the function and evolution of C1-2i C2H2-ZFs, eleven PtriZATs were identified in P. trichocarpa, which can be classified into two subgroups. The protein structure, conserved ZnF-C2H2 domains and QALGGH motifs, showed high conservation during the evolution of PtriZATs in P. trichocarpa. The spacing between two ZnF-C2H2 domains, chromosomal locations and cis-elements implied the original proteins and function of PtriZATs. Furthermore, the gene expression of different tissues and stress treatment showed the functional differentiation of PtriZATs subgroups and their stress response function. The analysis of C1-2i C2H2-ZFs in different Populus species and plants implied their evolution and differentiation, especially in terms of stress resistance. Cis-elements and expression pattern analysis of interaction proteins implied the function of PtriZATs through binding with stress-related genes, which are involved in gene regulation by via epigenetic modification through histone regulation, DNA methylation, ubiquitination, etc. Our results for the origin and evolution of PtriZATs will contribute to understanding the functional differentiation of C1-2i C2H2-ZFs in P. trichocarpa. The interaction and expression results will lay a foundation for the further functional investigation of their roles and biological processes in Populus.

DeepZF: improved DNA-binding prediction of C2H2-zinc-finger proteins by deep transfer learning

MOTIVATION

Cys2His2 zinc-finger (C2H2-ZF) proteins are the largest class of human transcription factors and hence play central roles in gene regulation and cell function. C2H2-ZF proteins are characterized by a DNA-binding domain containing multiple ZFs. A subset of the ZFs bind diverse DNA triplets. Despite their central roles, little is known about which of their ZFs are binding and how the DNA-binding preferences are encoded in the amino acid sequence of each ZF.

RESULTS

We present DeepZF, a deep-learning-based pipeline for predicting binding ZFs and their DNA-binding preferences given only the amino acid sequence of a C2H2-ZF protein. To the best of our knowledge, we compiled the first in vivo dataset of binding and non-binding ZFs for training the first ZF-binding classifier. Our classifier, which is based on a novel protein transformer, achieved an average AUROC of 0.71. Moreover, we took advantage of both in vivo and in vitro datasets to learn the recognition code of ZF-DNA binding through transfer learning. Our newly developed model, which is the first to utilize deep learning for the task, achieved an average Pearson correlation greater than 0.94 over each of the three DNA binding positions. Together, DeepZF outperformed extant methods in the task of C2H2-ZF protein DNA-binding preferences prediction: it achieved an average Pearson correlation of 0.42 in motif similarity compared with an average correlation smaller than 0.1 achieved by extant methods. By applying established interpretability techniques, we show that DeepZF inferred biologically relevant binding principles, such as the effect of amino acid residue positions on ZF DNA-binding potential.

AVAILABILITY AND IMPLEMENTATION

DeepZF code, model, and results are available via github.com/OrensteinLab/DeepZF.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identification of putative enhancer-like elements predicts regulatory networks active in planarian adult stem cells

Planarians have become an established model system to study regeneration and stem cells, but the regulatory elements in the genome remain almost entirely undescribed. Here, by integrating epigenetic and expression data we use multiple sources of evidence to predict enhancer elements active in the adult stem cell populations that drive regeneration. We have used ChIP-seq data to identify genomic regions with histone modifications consistent with enhancer activity, and ATAC-seq data to identify accessible chromatin. Overlapping these signals allowed for the identification of a set of high-confidence candidate enhancers predicted to be active in planarian adult stem cells. These enhancers are enriched for predicted transcription factor (TF) binding sites for TFs and TF families expressed in planarian adult stem cells. Footprinting analyses provided further evidence that these potential TF binding sites are likely to be occupied in adult stem cells. We integrated these analyses to build testable hypotheses for the regulatory function of TFs in stem cells, both with respect to how pluripotency might be regulated, and to how lineage differentiation programs are controlled. We found that our predicted GRNs were independently supported by existing TF RNAi/RNA-seq datasets, providing further evidence that our work predicts active enhancers that regulate adult stem cells and regenerative mechanisms.

Altering the Double-Stranded DNA Specificity of the bZIP Domain of Zta with Site-Directed Mutagenesis at N182

Zta, the Epstein-Barr virus bZIP transcription factor (TF), binds both unmethylated and methylated double-stranded DNA (dsDNA) in a sequence-specific manner. We studied the contribution of a conserved asparagine (N182) to sequence-specific dsDNA binding to four types of dsDNA: (i) dsDNA with cytosine in both strands ((DNA(C|C)), (ii, iii) dsDNA with 5-methylcytosine (5mC, M) or 5-hydroxymethylcytosine (5hmC, H) in one strand and cytosine in the second strand ((DNA(5mC|C) and DNA(5hmC|C)), and (iv) dsDNA with methylated cytosine in both strands in all CG dinucleotides ((DNA(5mCG)). We replaced asparagine with five similarly sized amino acids (glutamine (Q), serine (S), threonine (T), isoleucine (I), or valine (V)) and used protein binding microarrays to evaluate sequence-specific dsDNA binding. Zta preferentially binds the pseudo-palindrome TRE (AP1) motif (T^-4G^-3A^-2G/_C ⁰T²C³A⁴ ). Zta (N182Q) changes binding to A³ in only one half-site. Zta(N182S) changes binding to G³ in one or both halves of the motif. Zta(N182S) and Zta(N182Q) have 34- and 17-fold weaker median dsDNA binding, respectively. Zta(N182V) and Zta(N182I) have increased binding to dsDNA(5mC|C). Molecular dynamics simulations rationalize some of these results, identifying hydrogen bonds between glutamine and A³ , but do not reveal why serine preferentially binds G³ , suggesting that entropic interactions may mediate this new binding specificity.

Transcription Factor Binding Affinities and DNA Shape Readout

An essential event in gene regulation is the binding of a transcription factor (TF) to its target DNA. Models considering the interactions between the TF and the DNA geometry proved to be successful approaches to describe this binding event, while conserving data interpretability. However, a direct characterization of the DNA shape contribution to binding is still missing due to the lack of accurate and large-scale binding affinity data. Here, we use a binding assay we recently established to measure with high sensitivity the binding specificities of 13 Drosophila TFs, including dinucleotide dependencies to capture non-independent amino acid-base interactions. Correlating the binding affinities with all DNA shape features, we find that shape readout is widely used by these factors. A shape readout/TF-DNA complex structure analysis validates our approach while providing biological insights such as positively charged or highly polar amino acids often contact nucleotides that exhibit strong shape readout.

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The DNA shape contribution to Drosophila TFs-DNA binding is directly characterized

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Zeroth- and first-order TF-DNA binding specificities are measured with high accuracy

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DNA shape readout is widely used by these TFs

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A shape readout/structural correlation analysis provides biological insights

Characterization and evolutionary origin of novel C2H2 zinc finger protein (ZNF648) required for both erythroid and megakaryocyte differentiation in humans

Human ZNF648 is a novel poly C-terminal C2H2 zinc finger protein identified amongst the most dysregulated proteins in erythroid cells differentiated from iPSC. Its nuclear localisation and structure indicate it is likely a DNA-binding protein. Using a combination of ZNF648 overexpression in an iPSC line and primary adult erythroid cells, ZNF648 knockdown in primary adult erythroid cells and megakaryocytes, comparative proteomics and transcriptomics we show that ZNF648 is required for both erythroid and megakaryocyte differentiation. Orthologues of ZNF648 were detected across Mammals, Reptilia, Actinopterygii, in some Aves, Amphibia and Coelacanthiformes suggesting the gene originated in the common ancestor of Osteichthyes (Euteleostomi or bony fish). Conservation of the C-terminal zinc finger domain is higher, with some variation in zinc finger number but a core of at least six zinc fingers conserved across all groups, with the N-terminus recognisably similar within but not between major lineages. This suggests the N-terminus of ZNF648 evolves faster than the C-terminus, however this is not due to exon-shuffling as the entire coding region of ZNF648 is within a single exon. As for other such transcription factors, the N-terminus likely carries out regulatory functions, but showed no sequence similarity to any known domains. The greater functional constraint on the zinc finger domain suggests ZNF648 binds at least some similar regions of DNA in the different organisms. However, divergence of the N-terminal region may enable differential expression, allowing adaptation of function in the different organisms.

Bioinformatics of Metalloproteins and Metalloproteomes

Trace metals are inorganic elements that are required for all organisms in very low quantities. They serve as cofactors and activators of metalloproteins involved in a variety of key cellular processes. While substantial effort has been made in experimental characterization of metalloproteins and their functions, the application of bioinformatics in the research of metalloproteins and metalloproteomes is still limited. In the last few years, computational prediction and comparative genomics of metalloprotein genes have arisen, which provide significant insights into their distribution, function, and evolution in nature. This review aims to offer an overview of recent advances in bioinformatic analysis of metalloproteins, mainly focusing on metalloprotein prediction and the use of different metals across the tree of life. We describe current computational approaches for the identification of metalloprotein genes and metal-binding sites/patterns in proteins, and then introduce a set of related databases. Furthermore, we discuss the latest research progress in comparative genomics of several important metals in both prokaryotes and eukaryotes, which demonstrates divergent and dynamic evolutionary patterns of different metalloprotein families and metalloproteomes. Overall, bioinformatic studies of metalloproteins provide a foundation for systematic understanding of trace metal utilization in all three domains of life.

The geometric influence on the Cys2His2 zinc finger domain and functional plasticity

The Cys₂His₂ zinc finger is the most common DNA-binding domain expanding in metazoans since the fungi human split. A proposed catalyst for this expansion is an arms race to silence transposable elements yet it remains poorly understood how this domain is able to evolve the required specificities. Likewise, models of its DNA binding specificity remain error prone due to a lack of understanding of how adjacent fingers influence each other's binding specificity. Here, we use a synthetic approach to exhaustively investigate binding geometry, one of the dominant influences on adjacent finger function. By screening over 28 billion protein–DNA interactions in various geometric contexts we find the plasticity of the most common natural geometry enables more functional amino acid combinations across all targets. Further, residues that define this geometry are enriched in genomes where zinc fingers are prevalent and specificity transitions would be limited in alternative geometries. Finally, these results demonstrate an exhaustive synthetic screen can produce an accurate model of domain function while providing mechanistic insight that may have assisted in the domains expansion.

The Arms Race Between KRAB–Zinc Finger Proteins and Endogenous Retroelements and Its Impact on Mammals

Nearly half of the human genome consists of endogenous retroelements (EREs) and their genetic remnants, a small fraction of which carry the potential to propagate in the host genome, posing a threat to genome integrity and cell/organismal survival. The largest family of transcription factors in tetrapods, the Krüppel-associated box domain zinc finger proteins (KRAB-ZFPs), binds to specific EREs and represses their transcription. Since their first appearance over 400 million years ago, KRAB-ZFPs have undergone dramatic expansion and diversification in mammals, correlating with the invasions of new EREs. In this article we review our current understanding of the structure, function, and evolution of KRAB-ZFPs and discuss growing evidence that the arms race between KRAB-ZFPs and the EREs they target is a major driving force for the evolution of new traits in mammals, often accompanied by domestication of EREs themselves.

The causes of evolvability and their evolution

Evolvability is the ability of a biological system to produce phenotypic variation that is both heritable and adaptive. It has long been the subject of anecdotal observations and theoretical work. In recent years, however, the molecular causes of evolvability have been an increasing focus of experimental work. Here, we review recent experimental progress in areas as different as the evolution of drug resistance in cancer cells and the rewiring of transcriptional regulation circuits in vertebrates. This research reveals the importance of three major themes: multiple genetic and non-genetic mechanisms to generate phenotypic diversity, robustness in genetic systems, and adaptive landscape topography. We also discuss the mounting evidence that evolvability can evolve and the question of whether it evolves adaptively.

Disease-associated missense variants in ZBTB18 disrupt DNA binding and impair the development of neurons within the embryonic cerebral cortex

The activities of DNA-binding transcription factors, such as the multi-zinc-finger protein ZBTB18 (also known as RP58, or ZNF238), are essential to coordinate mammalian neurodevelopment, including the birth and radial migration of newborn neurons within the fetal brain. In humans, the majority of disease-associated missense mutations in ZBTB18 lie within the DNA-binding zinc-finger domain and are associated with brain developmental disorder, yet the molecular mechanisms explaining their role in disease remain unclear. To address this, we developed in silico models of ZBTB18, bound to DNA, and discovered that half of the missense variants map to residues (Asn461, Arg464, Glu486) predicted to be essential to sequence-specific DNA contact, whereas others map to residues (Leu434, Tyr447, Arg495) with limited contributions to DNA binding. We studied pathogenic variants to residues with close (N461S) and limited (R495G) DNA contact and found that each bound DNA promiscuously, displayed altered transcriptional regulatory activity in vitro, and influenced the radial migration of newborn neurons in vivo in different ways. Taken together, our results suggest that altered transcriptional regulation could represent an important pathological mechanism for ZBTB18 missense variants in brain developmental disease.

Similarity regression predicts evolution of transcription factor sequence specificity

Transcription factor (TF) binding specificities (motifs) are essential for the analysis of gene regulation. Accurate prediction of TF motifs is critical, because it is infeasible to assay all TFs in all sequenced eukaryotic genomes. There is ongoing controversy regarding the degree of motif diversification among related species that is, in part, because of uncertainty in motif prediction methods. Here we describe similarity regression, a significantly improved method for predicting motifs, which we use to update and expand the Cis-BP database. Similarity regression inherently quantifies TF motif evolution, and shows that previous claims of near-complete conservation of motifs between human and Drosophila are inflated, with nearly half of the motifs in each species absent from the other, largely due to extensive divergence in C2H2 zinc finger proteins. We conclude that diversification in DNA-binding motifs is pervasive, and present a new tool and updated resource to study TF diversity and gene regulation across eukaryotes.

The bZIP mutant CEBPB (V285A) has sequence specific DNA binding propensities similar to CREB1

The bZIP homodimers CEBPB and CREB1 bind DNA containing methylated cytosines differently. CREB1 binds stronger to the C/EBP half-site GCAA when the cytosine is methylated. For CEBPB, methylation of the same cytosine does not affect DNA binding. The X-ray structure of CREB1 binding the half site GTCA identifies an alanine in the DNA binding region interacting with the methyl group of T, structurally analogous to the methyl group of methylated C. This alanine is replaced with a valine in CEBPB. To explore the contribution of this amino acid to binding with methylated cytosine of the GCAA half-site, we made the reciprocal mutants CEBPB(V285A) and CREB1(A297V) and used protein binding microarrays (PBM) to examine binding to four types of double-stranded DNA (dsDNA): 1) DNA with cytosine in both strands (DNA(C|C)), 2) DNA with 5-methylcytosine (M) in one strand and cytosine in the second strand (DNA(M|C)), 3) DNA with 5-hydroxymethylcytosine (H) in one strand and cytosine in the second strand (DNA(H|C)), and 4) DNA with both cytosines in all CG dinucleotides containing 5-methylcytosine (DNA(5mCG)). When binding to DNA(C|C), CEBPB (V285A) preferentially binds the CRE consensus motif (TGACGTCA), similar to CREB1. The reciprocal mutant, CREB1(A297V) binds DNA with some similarity to CEBPB, with strongest binding to the methylated PAR site 8-mer TTACGTAA. These data demonstrate that V285 residue inhibits CEBPB binding to methylated cytosine of the GCAA half-site.

Comparative genomics and metagenomics of the metallomes

Recent achievements and advances in comparative genomic and metagenomic analyses of trace metals were reviewed and discussed.

Computational Methods for Analysis of the DNA-Binding Preferences of Cys2His2 Zinc-Finger Proteins

Cys₂His₂ zinc-finger proteins (C2H2-ZFPs) constitute the largest class of human transcription factors (TFs) and also the least characterized one. Determining the DNA sequence preferences of C2H2-ZFPs is an important first step toward elucidating their roles in transcriptional regulation. Among the most promising approaches for obtaining the sequence preferences of C2H2-ZFPs are those that combine machine-learning predictions with in vivo binding maps of these proteins. Here, we provide a protocol and guidelines for predicting the DNA-binding preferences of C2H2-ZFPs from their amino acid sequences using a machine learning-based recognition code. This protocol also describes the tools and steps to combine these predictions with ChIP-seq data to remove inaccuracies, identify the zinc-finger domains within each C2H2-ZFP that engage with DNA in vivo, and pinpoint the genomic binding sites of the C2H2-ZFPs.