Perspectives on Codebook: sequence specificity of uncharacterized human transcription factors.

We describe an effort ("Codebook") to determine the sequence specificity of 332 putative and largely uncharacterized human transcription factors (TFs), as well as 61 control TFs. Nearly 5,000 independent experiments across multiple and assays produced motifs for just over half of the putative TFs analyzed (177, or 53%), of which most are unique to a single TF. The data highlight the extensive contribution of transposable elements to TF evolution, both in and , and identify tens of thousands of conserved, base-level binding sites in the human genome.

Cross-platform DNA motif discovery and benchmarking to explore binding specificities of poorly studied human transcription factors.

A DNA sequence pattern, or "motif", is an essential representation of DNA-binding specificity of a transcription factor (TF). Any particular motif model has potential flaws due to shortcomings of the underlying experimental data and computational motif discovery algorithm. As a part of the Codebook/GRECO-BIT initiative, here we evaluated at large scale the cross-platform recognition performance of positional weight matrices (PWMs), which remain popular motif models in many practical applications.

GHT-SELEX demonstrates unexpectedly high intrinsic sequence specificity and complex DNA binding of many human transcription factors.

A long-standing challenge in human regulatory genomics is that transcription factor (TF) DNA-binding motifs are short and degenerate, while the genome is large. Motif scans therefore produce many false-positive binding site predictions. By surveying 179 TFs across 25 families using >1,500 cyclic selection experiments with fragmented, naked, and unmodified genomic DNA - a method we term GHT-SELEX (Genomic HT-SELEX) - we find that many human TFs possess much higher sequence specificity than anticipated.

Extensive binding of uncharacterized human transcription factors to genomic dark matter.

Most of the human genome is thought to be non-functional, and includes large segments often referred to as "dark matter" DNA. The genome also encodes hundreds of putative and poorly characterized transcription factors (TFs). We determined genomic binding locations of 166 uncharacterized human TFs in living cells.

Reconstructing the sequence specificities of RNA-binding proteins across eukaryotes.

RNA-binding proteins (RBPs) are key regulators of gene expression. Here, we introduce EuPRI (Eukaryotic Protein-RNA Interactions) - a freely available resource of RNA motifs for 34,736 RBPs from 690 eukaryotes. EuPRI includes binding data for 504 RBPs, including newly collected RNAcompete data for 174 RBPs, along with thousands of reconstructed motifs.

Fibroblast activation protein inhibitor PET/CT as an emerging diagnostic modality in interstitial lung disease and other fibrotic conditions.

Interstitial lung diseases (ILD) encompass a wide range of disorders characterized by alveolar inflammation and fibrotic tissue remodeling, marked by significant morbidity and mortality. Systemic sclerosis (SSc), among other connective tissue diseases, is a frequent cause of ILD. Assessment of pulmonary fibrosis is frequently constrained by the delayed manifestations of profibrotic activation of fibroblasts, which results in late macroscopic alterations detectable by standard imaging techniques such as computed tomography (CT) and magnetic resonance imaging (MRI) scans.

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.

Reconstruction of full-length LINE-1 progenitors from ancestral genomes.

Sequences derived from the Long INterspersed Element-1 (L1) family of retrotransposons occupy at least 17% of the human genome, with 67 distinct subfamilies representing successive waves of expansion and extinction in mammalian lineages. L1s contribute extensively to gene regulation, but their molecular history is difficult to trace, because most are present only as truncated and highly mutated fossils. Consequently, L1 entries in current databases of repeat sequences are composed mainly of short diagnostic subsequences, rather than full functional progenitor sequences for each subfamily.

Surgical Treatment in a High-Risk Pulmonary Embolism: Case Report.

We present the case of a 35-year-old woman who had a high-risk pulmonary embolism (according to ESC risk stratification for pulmonary embolism) after she had undergone a Caesarion section. Postoperatively, she presented with acute left lower limb pain, swelling and erythema. A diagnosis was made of deep vein thrombosis (DVT) of the ilio-femoral and popliteal veins.

Hsa-miR-125b Therapeutic Role in Colon Cancer Is Dependent on the Mutation Status of the TP53 Gene.

Colon cancer is the third most common cancer type worldwide and is highly dependent on DNA mutations that progressively appear and accumulate in the normal colon epithelium. Mutations in the gene appear in approximately half of these patients and have significant implications in disease progression and response to therapy. miR-125b-5p is a controversial microRNA with a dual role in cancer that has been reported to target specifically in colon adenocarcinomas.

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.

The Human Transcription Factors.

Transcription factors (TFs) recognize specific DNA sequences to control chromatin and transcription, forming a complex system that guides expression of the genome. Despite keen interest in understanding how TFs control gene expression, it remains challenging to determine how the precise genomic binding sites of TFs are specified and how TF binding ultimately relates to regulation of transcription. This review considers how TFs are identified and functionally characterized, principally through the lens of a catalog of over 1,600 likely human TFs and binding motifs for two-thirds of them.

Comparison of ChIP-Seq Data and a Reference Motif Set for Human KRAB C2H2 Zinc Finger Proteins.

KRAB C2H2 zinc finger proteins (KZNFs) are the largest and most diverse family of human transcription factors, likely due to diversifying selection driven by novel endogenous retroelements (EREs), but the vast majority lack binding motifs or functional data. Two recent studies analyzed a majority of the human KZNFs using either ChIP-seq (60 proteins) or ChIP-exo (221 proteins) in the same cell type (HEK293). The ChIP-exo paper did not describe binding motifs, however.

Motif comparison based on similarity of binding affinity profiles.

Unlabelled: Measuring motif similarity is essential for identifying functionally related transcription factors (TFs) and RNA-binding proteins, and for annotating de novo motifs. Here, we describe Motif Similarity Based on Affinity of Targets (MoSBAT), an approach for measuring the similarity of motifs by computing their affinity profiles across a large number of random sequences. We show that MoSBAT successfully associates de novo ChIP-seq motifs with their respective TFs, accurately identifies motifs that are obtained from the same TF in different in vitro assays, and quantitatively reflects the similarity of in vitro binding preferences for pairs of TFs.

Identification of C2H2-ZF binding preferences from ChIP-seq data using RCADE.

Unlabelled: Current methods for motif discovery from chromatin immunoprecipitation followed by sequencing (ChIP-seq) data often identify non-targeted transcription factor (TF) motifs, and are even further limited when peak sequences are similar due to common ancestry rather than common binding factors. The latter aspect particularly affects a large number of proteins from the Cys2His2 zinc finger (C2H2-ZF) class of TFs, as their binding sites are often dominated by endogenous retroelements that have highly similar sequences. Here, we present recognition code-assisted discovery of regulatory elements (RCADE) for motif discovery from C2H2-ZF ChIP-seq data.

Mapping and analysis of Caenorhabditis elegans transcription factor sequence specificities.

Caenorhabditis elegans is a powerful model for studying gene regulation, as it has a compact genome and a wealth of genomic tools. However, identification of regulatory elements has been limited, as DNA-binding motifs are known for only 71 of the estimated 763 sequence-specific transcription factors (TFs). To address this problem, we performed protein binding microarray experiments on representatives of canonical TF families in C.

C2H2 zinc finger proteins greatly expand the human regulatory lexicon.

Cys2-His2 zinc finger (C2H2-ZF) proteins represent the largest class of putative human transcription factors. However, for most C2H2-ZF proteins it is unknown whether they even bind DNA or, if they do, to which sequences. Here, by combining data from a modified bacterial one-hybrid system with protein-binding microarray and chromatin immunoprecipitation analyses, we show that natural C2H2-ZFs encoded in the human genome bind DNA both in vitro and in vivo, and we infer the DNA recognition code using DNA-binding data for thousands of natural C2H2-ZF domains.

Determination and inference of eukaryotic transcription factor sequence specificity.

Transcription factor (TF) DNA sequence preferences direct their regulatory activity, but are currently known for only ∼1% of eukaryotic TFs. Broadly sampling DNA-binding domain (DBD) types from multiple eukaryotic clades, we determined DNA sequence preferences for >1,000 TFs encompassing 54 different DBD classes from 131 diverse eukaryotes. We find that closely related DBDs almost always have very similar DNA sequence preferences, enabling inference of motifs for ∼34% of the ∼170,000 known or predicted eukaryotic TFs.

A compendium of RNA-binding motifs for decoding gene regulation.

RNA-binding proteins are key regulators of gene expression, yet only a small fraction have been functionally characterized. Here we report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes. The sequence specificities of RNA-binding proteins display deep evolutionary conservation, and the recognition preferences for a large fraction of metazoan RNA-binding proteins can thus be inferred from their RNA-binding domain sequence.

The DNA Barcode Linker.

DNA barcoding is based on the use of short DNA sequences to provide taxonomic tags for rapid, efficient identification of biological specimens. Currently, reference databases are being compiled. In the future, it will be important to facilitate access to these databases, especially for nonspecialist users.

Nucleotide substitution bias within the genus Drosophila affects the pattern of proteome evolution.

The availability of complete genome sequences for 12 Drosophila species provides an unprecedented resource for large-scale studies of genome evolution. In this study, we looked for correlated shifts in the patterns of genome and proteome evolution within the genus Drosophila. Specifically, we asked if the nucleotide composition of the Drosophila willistoni genome--which is significantly less GC rich than the other 11 sequenced Drosophila genomes--is reflected in an altered pattern of amino acid substitutions in the encoded proteins.

Uncorrected nucleotide bias in mtDNA can mimic the effects of positive Darwinian selection.

The relative rates of nucleotide substitution at synonymous and nonsynonymous sites within protein-coding regions have been widely used to infer the action of natural selection from comparative sequence data. It is known, however, that mutational and repair biases can affect rates of evolution at both synonymous and nonsynonymous sites. More importantly, it is also known that synonymous sites are particularly prone to the effects of nucleotide bias.