Y-Box-Binding Proteins Have a Dual Impact on Cellular Translation.

Y-box-binding proteins (YB proteins) are multifunctional DNA- and RNA-binding proteins that play an important role in the regulation of gene expression. The high homology of their cold shock domains and the similarity between their long, unstructured C-terminal domains suggest that Y-box-binding proteins may have similar functions in a cell. Here, we consider the functional interchangeability of the somatic YB proteins YB-1 and YB-3. RNA-seq and Ribo-seq are used to track changes in the mRNA abundance or mRNA translation in HEK293T cells solely expressing YB-1, YB-3, or neither of them. We show that YB proteins have a dual effect on translation. Although the expression of YB proteins stimulates global translation, YB-1 and YB-3 inhibit the translation of their direct CLIP-identified mRNA targets. The impact of YB-1 and YB-3 on the translation of their mRNA targets is similar, which suggests that they can substitute each other in inhibiting the translation of their mRNA targets in HEK293T cells.

Evaluation and optimization of sequence-based gene regulatory deep learning models.

Neural networks have emerged as immensely powerful tools in predicting functional genomic regions, notably evidenced by recent successes in deciphering gene regulatory logic. However, a systematic evaluation of how model architectures and training strategies impact genomics model performance is lacking. To address this gap, we held a DREAM Challenge where competitors trained models on a dataset of millions of random promoter DNA sequences and corresponding expression levels, experimentally determined in yeast, to best capture the relationship between regulatory DNA and gene expression. For a robust evaluation of the models, we designed a comprehensive suite of benchmarks encompassing various sequence types. While some benchmarks produced similar results across the top-performing models, others differed substantially. All top-performing models used neural networks, but diverged in architectures and novel training strategies, tailored to genomics sequence data. To dissect how architectural and training choices impact performance, we developed the Prix Fixe framework to divide any given model into logically equivalent building blocks. We tested all possible combinations for the top three models and observed performance improvements for each. The DREAM Challenge models not only achieved state-of-the-art results on our comprehensive yeast dataset but also consistently surpassed existing benchmarks on Drosophila and human genomic datasets. Overall, we demonstrate that high-quality gold-standard genomics datasets can drive significant progress in model development.

HOCOMOCO in 2024: a rebuild of the curated collection of binding models for human and mouse transcription factors.

We present a major update of the HOCOMOCO collection that provides DNA binding specificity patterns of 949 human transcription factors and 720 mouse orthologs. To make this release, we performed motif discovery in peak sets that originated from 14 183 ChIP-Seq experiments and reads from 2554 HT-SELEX experiments yielding more than 400 thousand candidate motifs. The candidate motifs were annotated according to their similarity to known motifs and the hierarchy of DNA-binding domains of the respective transcription factors. Next, the motifs underwent human expert curation to stratify distinct motif subtypes and remove non-informative patterns and common artifacts. Finally, the curated subset of 100 thousand motifs was supplied to the automated benchmarking to select the best-performing motifs for each transcription factor. The resulting HOCOMOCO v12 core collection contains 1443 verified position weight matrices, including distinct subtypes of DNA binding motifs for particular transcription factors. In addition to the core collection, HOCOMOCO v12 provides motif sets optimized for the recognition of binding sites in vivo and in vitro, and for annotation of regulatory sequence variants. HOCOMOCO is available at https://hocomoco12.autosome.org and https://hocomoco.autosome.org.

rs71327024 Associated with COVID-19 Hospitalization Reduces CXCR6 Promoter Activity in Human CD4+ T Cells via Disruption of c-Myb Binding.

Single-nucleotide polymorphism rs71327024 located in the human 3p21.31 locus has been associated with an elevated risk of hospitalization upon SARS-CoV-2 infection. The 3p21.31 locus contains several genes encoding chemokine receptors potentially relevant to severe COVID-19. In particular, CXCR6, which is prominently expressed in T lymphocytes, NK, and NKT cells, has been shown to be involved in the recruitment of immune cells to non-lymphoid organs in chronic inflammatory and respiratory diseases. In COVID-19, CXCR6 expression is reduced in lung resident memory T cells from patients with severe disease as compared to the control cohort with moderate symptoms. We demonstrate here that rs71327024 is located within an active enhancer that augments the activity of the CXCR6 promoter in human CD4+ T lymphocytes. The common rs71327024(G) variant makes a functional binding site for the c-Myb transcription factor, while the risk rs71327024(T) variant disrupts c-Myb binding and reduces the enhancer activity. Concordantly, c-Myb knockdown in PMA-treated Jurkat cells negates rs71327024's allele-specific effect on CXCR6 promoter activity. We conclude that a disrupted c-Myb binding site may decrease CXCR6 expression in T helper cells of individuals carrying the minor rs71327024(T) allele and thus may promote the progression of severe COVID-19 and other inflammatory pathologies.

LegNet: a best-in-class deep learning model for short DNA regulatory regions.

MOTIVATION: The increasing volume of data from high-throughput experiments including parallel reporter assays facilitates the development of complex deep-learning approaches for modeling DNA regulatory grammar. RESULTS: Here, we introduce LegNet, an EfficientNetV2-inspired convolutional network for modeling short gene regulatory regions. By approaching the sequence-to-expression regression problem as a soft classification task, LegNet secured first place for the autosome.org team in the DREAM 2022 challenge of predicting gene expression from gigantic parallel reporter assays. Using published data, here, we demonstrate that LegNet outperforms existing models and accurately predicts gene expression per se as well as the effects of single-nucleotide variants. Furthermore, we show how LegNet can be used in a diffusion network manner for the rational design of promoter sequences yielding the desired expression level. AVAILABILITY AND IMPLEMENTATION: https://github.com/autosome-ru/LegNet. The GitHub repository includes Jupyter Notebook tutorials and Python scripts under the MIT license to reproduce the results presented in the study.

Crol contributes to PRE-mediated repression and Polycomb group proteins recruitment in Drosophila.

The Polycomb group (PcG) proteins are fundamental epigenetic regulators that control the repressive state of target genes in multicellular organisms. One of the open questions is defining the mechanisms of PcG recruitment to chromatin. In Drosophila, the crucial role in PcG recruitment is thought to belong to DNA-binding proteins associated with Polycomb response elements (PREs). However, current data suggests that not all PRE-binding factors have been identified. Here, we report the identification of the transcription factor Crooked legs (Crol) as a novel PcG recruiter. Crol is a C2H2-type Zinc Finger protein that directly binds to poly(G)-rich DNA sequences. Mutation of Crol binding sites as well as crol CRISPR/Cas9 knockout diminish the repressive activity of PREs in transgenes. Like other PRE-DNA binding proteins, Crol co-localizes with PcG proteins inside and outside of H3K27me3 domains. Crol knockout impairs the recruitment of the PRC1 subunit Polyhomeotic and the PRE-binding protein Combgap at a subset of sites. The decreased binding of PcG proteins is accompanied by dysregulated transcription of target genes. Overall, our study identified Crol as a new important player in PcG recruitment and epigenetic regulation.

Human Tissues Exhibit Diverse Composition of Translation Machinery.

While protein synthesis is vital for the majority of cell types of the human body, diversely differentiated cells require specific translation regulation. This suggests the specialization of translation machinery across tissues and organs. Using transcriptomic data from GTEx, FANTOM, and Gene Atlas, we systematically explored the abundance of transcripts encoding translation factors and aminoacyl-tRNA synthetases (ARSases) in human tissues. We revised a few known and identified several novel translation-related genes exhibiting strict tissue-specific expression. The proteins they encode include eEF1A1, eEF1A2, PABPC1L, PABPC3, eIF1B, eIF4E1B, eIF4ENIF1, and eIF5AL1. Furthermore, our analysis revealed a pervasive tissue-specific relative abundance of translation machinery components (e.g., PABP and eRF3 paralogs, eIF2B and eIF3 subunits, eIF5MPs, and some ARSases), suggesting presumptive variance in the composition of translation initiation, elongation, and termination complexes. These conclusions were largely confirmed by the analysis of proteomic data. Finally, we paid attention to sexual dimorphism in the repertoire of translation factors encoded in sex chromosomes (eIF1A, eIF2γ, and DDX3), and identified the testis and brain as organs with the most diverged expression of translation-associated genes.

EpiFactors 2022: expansion and enhancement of a curated database of human epigenetic factors and complexes.

We present an update of EpiFactors, a manually curated database providing information about epigenetic regulators, their complexes, targets, and products which is openly accessible at http://epifactors.autosome.org. An updated version of the EpiFactors contains information on 902 proteins, including 101 histones and protamines, and, as a main update, a newly curated collection of 124 lncRNAs involved in epigenetic regulation. The amount of publications concerning the role of lncRNA in epigenetics is rapidly growing. Yet, the resource that compiles, integrates, organizes, and presents curated information on lncRNAs in epigenetics is missing. EpiFactors fills this gap and provides data on epigenetic regulators in an accessible and user-friendly form. For 820 of the genes in EpiFactors, we include expression estimates across multiple cell types assessed by CAGE-Seq in the FANTOM5 project. In addition, the updated EpiFactors contains information on 73 protein complexes involved in epigenetic regulation. Our resource is practical for a wide range of users, including biologists, bioinformaticians and molecular/systems biologists.

Positional weight matrices have sufficient prediction power for analysis of noncoding variants.

The position weight matrix, also called the position-specific scoring matrix, is the commonly accepted model to quantify the specificity of transcription factor binding to DNA. Position weight matrices are used in thousands of projects and software tools in regulatory genomics, including computational prediction of the regulatory impact of single-nucleotide variants. Yet, recently Yan et al. reported that "the position weight matrices of most transcription factors lack sufficient predictive power" if applied to the analysis of regulatory variants studied with a newly developed experimental method, SNP-SELEX. Here, we re-analyze the rich experimental dataset obtained by Yan et al. and show that appropriately selected position weight matrices in fact can adequately quantify transcription factor binding to alternative alleles.

Diverse Regulation of YB-1 and YB-3 Abundance in Mammals.

YB proteins are DNA/RNA binding proteins, members of the family of proteins with cold shock domain. Role of YB proteins in the life of cells, tissues, and whole organisms is extremely important. They are involved in transcription regulation, pre-mRNA splicing, mRNA translation and stability, mRNA packaging into mRNPs, including stress granules, DNA repair, and many other cellular events. Many processes, from embryonic development to aging, depend on when and how much of these proteins have been synthesized. Here we discuss regulation of the levels of YB-1 and, in part, of its homologs in the cell. Because the amount of YB-1 is immediately associated with its functioning, understanding the mechanisms of regulation of the protein amount invariably reveals the events where YB-1 is involved. Control over the YB-1 abundance may allow using this gene/protein as a therapeutic target in cancers, where an increased expression of the YBX1 gene often correlates with the disease severity and poor prognosis.

RNA-Seq data of ALKBH5 and FTO double knockout HEK293T human cells.

N6-methyladenosine (m6A) is the most abundant, highly dynamic mRNA modification that regulates mRNA splicing, stability, and translation. The m6A epigenetic mark is erased by RNA demethylases ALKBH5 (AlkB Homolog 5) and FTO (Fat mass and obesity-associated protein). The ALKBH5 and FTO RNA demethylases recognize m6A in similar nucleotide contexts. Therefore, these proteins can partially substitute for each other. To assess the impact of total m6A demethylation failure we performed high-throughput sequencing of cytoplasmic RNA from ALKBH5 and FTO double knockout and wild type HEK293T cells. The RNA-Seq libraries were sequenced on Illumina NextSeq 500, trimmed, and mapped to the human genome. The consequent read counting and differential expression analysis in the R environment detected 5871 differentially expressed and 166 alternatively spliced genes comparing double knockout against wild type HEK293T cells. Raw data are deposited in NCBI Gene Expression Omnibus (GEO) repository under GEO accession GSE198050.

ANANASTRA: annotation and enrichment analysis of allele-specific transcription factor binding at SNPs.

We present ANANASTRA, https://ananastra.autosome.org, a web server for the identification and annotation of regulatory single-nucleotide polymorphisms (SNPs) with allele-specific binding events. ANANASTRA accepts a list of dbSNP IDs or a VCF file and reports allele-specific binding (ASB) sites of particular transcription factors or in specific cell types, highlighting those with ASBs significantly enriched at SNPs in the query list. ANANASTRA is built on top of a systematic analysis of allelic imbalance in ChIP-Seq experiments and performs the ASB enrichment test against background sets of SNPs found in the same source experiments as ASB sites but not displaying significant allelic imbalance. We illustrate ANANASTRA usage with selected case studies and expect that ANANASTRA will help to conduct the follow-up of GWAS in terms of establishing functional hypotheses and designing experimental verification.

Ribosomal leaky scanning through a translated uORF requires eIF4G2.

eIF4G2 (DAP5 or Nat1) is a homologue of the canonical translation initiation factor eIF4G1 in higher eukaryotes but its function remains poorly understood. Unlike eIF4G1, eIF4G2 does not interact with the cap-binding protein eIF4E and is believed to drive translation under stress when eIF4E activity is impaired. Here, we show that eIF4G2 operates under normal conditions as well and promotes scanning downstream of the eIF4G1-mediated 40S recruitment and cap-proximal scanning. Specifically, eIF4G2 facilitates leaky scanning for a subset of mRNAs. Apparently, eIF4G2 replaces eIF4G1 during scanning of 5' UTR and the necessity for eIF4G2 only arises when eIF4G1 dissociates from the scanning complex. In particular, this event can occur when the leaky scanning complexes interfere with initiating or elongating 80S ribosomes within a translated uORF. This mechanism is therefore crucial for higher eukaryotes which are known to have long 5' UTRs with highly frequent uORFs. We suggest that uORFs are not the only obstacle on the way of scanning complexes towards the main start codon, because certain eIF4G2 mRNA targets lack uORF(s). Thus, higher eukaryotes possess two distinct scanning complexes: the principal one that binds mRNA and initiates scanning, and the accessory one that rescues scanning when the former fails.

The gene regulation knowledge commons: the action area of GREEKC.

As computational modeling becomes more essential to analyze and understand biological regulatory mechanisms, governance of the many databases and knowledge bases that support this domain is crucial to guarantee reliability and interoperability of resources. To address this, the COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.org) organized nine workshops in a four-year period, starting September 2016. The workshops brought together a wide range of experts from all over the world working on various steps in the knowledge management process that focuses on understanding gene regulatory mechanisms. The discussions between ontologists, curators, text miners, biologists, bioinformaticians, philosophers and computational scientists spawned a host of activities aimed to standardize and update existing knowledge management workflows and involve end-users in the process of designing the Gene Regulation Knowledge Commons (GRKC). Here the GREEKC consortium describes its main achievements in improving this GRKC.

Ribo-Seq and RNA-Seq of TMA46 ( DFRP1) and GIR2 ( DFRP2) knockout yeast strains.

In eukaryotes, stalled and collided ribosomes are recognized by several conserved multicomponent systems, which either block protein synthesis in situ and resolve the collision locally, or trigger a general stress response. Yeast ribosome-binding GTPases RBG1 (DRG1 in mammals) and RBG2 (DRG2) form two distinct heterodimers with TMA46 (DFRP1) and GIR2 (DFRP2), respectively, both involved in mRNA translation. Accumulated evidence suggests that the dimers play partially redundant roles in elongation processivity and resolution of ribosome stalling and collision events, as well as in the regulation of GCN1-mediated signaling involved in ribosome-associated quality control (RQC). They also genetically interact with SLH1 (ASCC3) helicase, a key component of RQC trigger (RQT) complex disassembling collided ribosomes. Here, we present RNA-Seq and ribosome profiling (Ribo-Seq) data from S. cerevisiae strains with individual deletions of the TMA46 and GIR2 genes. Raw RNA-Seq and Ribo-Seq data as well as gene-level read counts are available in NCBI Gene Expression Omnibus (GEO) repository under GEO accession GSE185458 and GSE185286.

A standard knockout procedure alters expression of adjacent loci at the translational level.

The Saccharomyces cerevisiae gene deletion collection is widely used for functional gene annotation and genetic interaction analyses. However, the standard G418-resistance cassette used to produce knockout mutants delivers strong regulatory elements into the target genetic loci. To date, its side effects on the expression of neighboring genes have never been systematically assessed. Here, using ribosome profiling data, RT-qPCR, and reporter expression, we investigated perturbations induced by the KanMX module. Our analysis revealed significant alterations in the transcription efficiency of neighboring genes and, more importantly, severe impairment of their mRNA translation, leading to changes in protein abundance. In the 'head-to-head' orientation of the deleted and neighboring genes, knockout often led to a shift of the transcription start site of the latter, introducing new uAUG codon(s) into the expanded 5' untranslated region (5' UTR). In the 'tail-to-tail' arrangement, knockout led to activation of alternative polyadenylation signals in the neighboring gene, thus altering its 3' UTR. These events may explain the so-called neighboring gene effect (NGE), i.e. false genetic interactions of the deleted genes. We estimate that in as much as ∼1/5 of knockout strains the expression of neighboring genes may be substantially (>2-fold) deregulated at the level of translation.

A GO catalogue of human DNA-binding transcription factors.

To control gene transcription, DNA-binding transcription factors recognise specific sequence motifs in gene regulatory regions. A complete and reliable GO annotation of all DNA-binding transcription factors is key to investigating the delicate balance of gene regulation in response to environmental and developmental stimuli. The need for such information is demonstrated by the many lists of transcription factors that have been produced over the past decade. The COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC) Consortium brought together experts in the field of transcription with the aim of providing high quality and interoperable gene regulatory data. The Gene Ontology (GO) Consortium provides strict definitions for gene product function, including factors that regulate transcription. The collaboration between the GREEKC and GO Consortia has enabled the application of those definitions to produce a new curated catalogue of over 1400 human DNA-binding transcription factors, that can be accessed at https://www.ebi.ac.uk/QuickGO/targetset/dbTF. This catalogue has facilitated an improvement in the GO annotation of human DNA-binding transcription factors and led to the GO annotation of almost sixty thousand DNA-binding transcription factors in over a hundred species. Thus, this work will aid researchers investigating the regulation of transcription in both biomedical and basic science.

VTC4 Polyphosphate Polymerase Knockout Increases Stress Resistance of Saccharomyces cerevisiae Cells.

Inorganic polyphosphate (polyP) is an important factor of alkaline, heavy metal, and oxidative stress resistance in microbial cells. In yeast, polyP is synthesized by Vtc4, a subunit of the vacuole transporter chaperone complex. Here, we report reduced but reliably detectable amounts of acid-soluble and acid-insoluble polyPs in the Δvtc4 strain of Saccharomyces cerevisiae, reaching 10% and 20% of the respective levels of the wild-type strain. The Δvtc4 strain has decreased resistance to alkaline stress but, unexpectedly, increased resistance to oxidation and heavy metal excess. We suggest that increased resistance is achieved through elevated expression of DDR2, which is implicated in stress response, and reduced expression of PHO84 encoding a phosphate and divalent metal transporter. The decreased Mg2+-dependent phosphate accumulation in Δvtc4 cells is consistent with reduced expression of PHO84. We discuss a possible role that polyP level plays in cellular signaling of stress response mobilization in yeast.

Enhanced C/EBP binding to G·T mismatches facilitates fixation of CpG mutations in cancer and adult stem cells.

Somatic mutations in regulatory sites of human stem cells affect cell identity or cause malignant transformation. By mining the human genome for co-occurrence of mutations and transcription factor binding sites, we show that C/EBP binding sites are strongly enriched with [C > T]G mutations in cancer and adult stem cells, which is of special interest because C/EBPs regulate cell fate and differentiation. In vitro protein-DNA binding assay and structural modeling of the CEBPB-DNA complex show that the G·T mismatch in the core CG dinucleotide strongly enhances affinity of the binding site. We conclude that enhanced binding of C/EBPs shields CpG·TpG mismatches from DNA repair, leading to selective accumulation of [C > T]G mutations and consequent deterioration of the binding sites. This mechanism of targeted mutagenesis highlights the effect of a mutational process on certain regulatory sites and reveals the molecular basis of putative regulatory alterations in stem cells.