Profiling the Landscape of Drug Resistance Mutations in Neosubstrates to Molecular Glue Degraders

Targeted protein degradation (TPD) holds immense promise for drug discovery but mechanisms of acquired resistance to degraders remain to be fully identified. Here we used CRISPR-suppressor scanning to identify mechanistic classes of drug resistance mutations to molecular glue degraders in GSPT1 and RBM39, neosubstrates targeted by E3 ligase substrate receptors cereblon and DCAF15, respectively. While many mutations directly alter the ternary complex heterodimerization surface, distal resistance sites were also identified. Several distal mutations in RBM39 led to modest decreases in degradation yet can enable cell survival, underscoring how small differences in degradation can lead to resistance. Integrative analysis of resistance sites across GSPT1 and RBM39 revealed varying levels of sequence conservation and mutational constraint that control the emergence of different resistance mechanisms, highlighting that many regions co-opted by TPD are inessential. Altogether, our study identifies common resistance mechanisms for molecular glue degraders and outlines a general approach to survey neosubstrate requirements necessary for effective degradation.

Sequence conservation, domain architectures, and phylogenetic distribution of the HD-GYP type c-di-GMP phosphodiesterases

The HD-GYP domain, named after two of its conserved sequence motifs, was first described in 1999 as a specialized version of the widespread HD phosphohydrolase domain that had additional highly conserved amino acid residues. Domain associations of HD-GYP indicated its involvement in bacterial signal transduction and distribution patterns of this domain suggested that it could serve as a hydrolase of the bacterial second messenger c-di-GMP, in addition to or instead of the EAL domain. Subsequent studies confirmed the ability of various HD-GYP domains to hydrolyze c-di-GMP to linear pGpG and/or GMP. Certain HD-GYP-containing proteins hydrolyze another second messenger, cGAMP, and some HD-GYP domains participate in regulatory protein-protein interactions. The recently solved structures of HD-GYP domains from four distinct organisms clarified the mechanisms of c-di-GMP binding and metal-assisted hydrolysis. However, the HD-GYP domain is poorly represented in public domain databases, which causes certain confusion about its phylogenetic distribution, functions, and domain architectures. Here, we present a refined sequence model for the HD-GYP domain and describe the roles of its most conserved residues in metal and/or substrate binding. We also calculate the numbers of HD-GYPs encoded in various genomes and list the most common domain combinations involving HD-GYP, such as the RpfG (REC–HD-GYP), Bd1817 (DUF3391– HD-GYP), and PmGH (GAF–HD-GYP) protein families. We also provide the descriptions of six HD-GYP–associated domains, including four novel integral membrane sensor domains. This work is expected to stimulate studies of diverse HD-GYP-containing proteins, their N-terminal sensor domains and the signals to which they respond. IMPORTANCE The HD-GYP domain forms class II of c-di-GMP phosphodiesterases that control the cellular levels of the universal bacterial second messenger c-di-GMP and therefore affect flagellar and/or twitching motility, cell development, biofilm formation, and, often, virulence. Despite more than 20 years of research, HD-GYP domains are insufficiently characterized; they are often confused with ‘classical’ HD domains that are involved in various housekeeping activities and may participate in signaling, hydrolyzing (p)ppGpp and c-di-AMP. This work provides an updated description of the HD-GYP domain, including its sequence conservation, phylogenetic distribution, domain architectures, and the most widespread HD-GYP-containing protein families. This work shows that HD-GYP domains are widespread in many environmental bacteria and are predominant c-di-GMP hydrolases in many lineages, including clostridia and deltaproteobacteria .

ortho2align: a sensitive approach for searching for orthologues of novel lncRNAs

Background: Many novel long noncoding RNAs have been discovered in recent years due to advances in high-throughput sequencing experiments. Finding orthologues of these novel lncRNAs might facilitate clarification of their functional role in living organisms. However, lncRNAs exhibit low sequence conservation, so specific methods for enhancing the signal-to-noise ratio were developed. Nevertheless, current methods such as transcriptomes comparison approaches or searches for conserved secondary structures are not applicable to novel lncRNAs dy design. Results: We present ortho2align - a versatile sensitive synteny-based lncRNA orthologue search tool with statistical assessment of sequence conservation. This tool allows control of the specificity of the search process and optional annotation of found orthologues. ortho2align shows similar performance in terms of sensitivity and resource usage as the state-of-the-art method for aligning orthologous lncRNAs but also enables scientists to predict unannotated orthologous sequences for lncRNAs in question. Using ortho2align, we predicted orthologues of three distinct classes of novel human lncRNAs in six Vertebrata species to estimate their degree of conservation. Conclusions: Being designed for the discovery of unannotated orthologues of novel lncRNAs in distant species, ortho2align is a versatile tool applicable to any genomic regions, especially weakly conserved ones. A small amount of input files makes ortho2align easy to use in orthology studies as a single tool or in bundle with other steps that researchers will consider sensible.

Prediction of functional microexons by transfer learning

Background Microexons are a particular kind of exon of less than 30 nucleotides in length. More than 60% of annotated human microexons were found to have high levels of sequence conservation, suggesting their potential functions. There is thus a need to develop a method for predicting functional microexons. Results Given the lack of a publicly available functional label for microexons, we employed a transfer learning skill called Transfer Component Analysis (TCA) to transfer the knowledge obtained from feature mapping for the prediction of functional microexons. To provide reference knowledge, microindels were chosen because of their similarities to microexons. Then, Support Vector Machine (SVM) was used to train a classification model in the newly built feature space for the functional microindels. With the trained model, functional microexons were predicted. We also built a tool based on this model to predict other functional microexons. We then used this tool to predict a total of 19 functional microexons reported in the literature. This approach successfully predicted 16 out of 19 samples, giving accuracy greater than 80%. Conclusions In this study, we proposed a method for predicting functional microexons and applied it, with the predictive results being largely consistent with records in the literature.

A Comparative Analysis of Super-Enhancers and Broad H3K4me3 Domains in Pig, Human, and Mouse Tissues

Super-enhancers (SEs) and broad H3K4me3 domains (BDs) are crucial regulators in the control of tissue identity in human and mouse. However, their features in pig remain largely unknown. In this study, by integrative computational analyses of epigenomic and transcriptomic data, we have characterized SEs and BDs in six pig tissues and analyzed their conservation in comparison with human and mouse tissues. Similar to human and mouse, pig SEs and BDs display higher tissue specificity than their typical counterparts. Genes proximal to SEs and BDs are associated with tissue identity in most tissues. About 55–182 SEs (5–17% in total) and 99–309 BDs (8–16% in total) across pig tissues are considered as functionally conserved elements because they have orthologous SEs and BDs in human and mouse. However, these elements do not necessarily exhibit sequence conservation. The functionally conserved SEs are correlated to tissue identity in majority of pig tissues, while those conserved BDs are linked to tissue identity in a few tissues. Our study provides resources for future gene regulatory studies in pig. It highlights that SEs are more effective in defining tissue identity than BDs, which is contrasting to a previous study. It also provides novel insights on understanding the sequence features of functionally conserved elements.

Genome-wide oscillations in G + C density and sequence conservation

Eukaryotic genomes typically show a uniform G + C content among chromosomes, but on smaller scales, many species have a G + C density that fluctuates with a characteristic wavelength. This oscillation is evident in many insect species, with wavelengths ranging between 700 bp and 4 kb. Measures of evolutionary conservation oscillate in phase with G + C content, with conserved regions having higher G + C. Loci with large regulatory regions show more regular oscillations; coding sequences and heterochromatic regions show little or no oscillation. There is little oscillation in vertebrate genomes in regions with densely distributed mobile repetitive elements. However, species with few repeats show oscillation in both G + C density and sequence conservation. These oscillations may reflect optimal spacing of cis-regulatory elements.

Locating ligand binding sites in G-protein coupled receptors using combined information from docking and sequence conservation

GPCRs (G-protein coupled receptors) are the largest family of drug targets and share a conserved structure. Binding sites are unknown for many important GPCR ligands due to the difficulties of GPCR recombinant expression, biochemistry, and crystallography. We describe our approach, ConDockSite, for predicting ligand binding sites in class A GPCRs using combined information from surface conservation and docking, starting from crystal structures or homology models. We demonstrate the effectiveness of ConDockSite on crystallized class A GPCRs such as the beta2 adrenergic and A2A adenosine receptors. We also demonstrate that ConDockSite successfully predicts ligand binding sites from high-quality homology models. Finally, we apply ConDockSite to predict the ligand binding sites on a structurally uncharacterized GPCR, GPER, the G-protein coupled estrogen receptor. Most of the sites predicted by ConDockSite match those found in other independent modeling studies. ConDockSite predicts that four ligands bind to a common location on GPER at a site deep in the receptor cleft. Incorporating sequence conservation information in ConDockSite overcomes errors introduced from physics-based scoring functions and homology modeling.

Variables Influencing Differences in Sequence Conservation in the Fission Yeast Schizosaccharomyces pombe

Which variables determine the constraints on gene sequence evolution is one of the most central questions in molecular evolution. In the fission yeast Schizosaccharomyces pombe, an important model organism, the variables influencing the rate of sequence evolution have yet to be determined. Previous studies in other single celled organisms have generally found gene expression levels to be most significant, with numerous other variables such as gene length and functional importance identified as having a smaller impact. Using publicly available data, we used partial least squares regression, principal components regression, and partial correlations to determine the variables most strongly associated with sequence evolution constraints. We identify centrality in the protein–protein interactions network, amino acid composition, and cellular location as the most important determinants of sequence conservation. However, each factor only explains a small amount of variance, and there are numerous variables having a significant or heterogeneous influence. Our models explain more than half of the variance in dN, raising the possibility that future refined models could quantify the role of stochastics in evolutionary rate variation.

ExOrthist: a tool to infer exon orthologies at any evolutionary distance

Several bioinformatic tools have been developed for genome-wide identification of orthologous and paralogous genes. However, no corresponding tool allows the detection of exon homology relationships. Here, we present ExOrthist, a fully reproducible Nextflow-based software enabling inference of exon homologs and orthogroups, visualization of evolution of exon-intron structures, and assessment of conservation of alternative splicing patterns. ExOrthist evaluates exon sequence conservation and considers the surrounding exon-intron context to derive genome-wide multi-species exon homologies at any evolutionary distance. We demonstrate its use in different evolutionary scenarios: whole genome duplication in frogs and convergence of Nova-regulated splicing networks (https://github.com/biocorecrg/ExOrthist).

Significance of the p.Phe218Ser and p.Gly304Glu F5 Variants in Hereditary Factor V Deficiency

Hereditary factor V (FV) deficiency is a rare autosomal recessive bleeding disorder caused by <i>F5</i> gene mutations. The objective of this study was to investigate the p.Phe218Ser and p.Gly304Glu variants found in 2 families with hereditary FV deficiency. The FV activity (FV:C) and FV antigen (FV:Ag) were measured by clotting and ELISA, respectively. The <i>F5</i> gene and sequence conservation were analyzed by direct sequencing and ClustalX-2.1-win, respectively. One proband carried a homozygous p.Phe218Ser (c.653T&#x3e;C) mutation, with FV:C and FV:Ag decreased to 11 and 14%, respectively. The other proband carried a heterozygous p.Gly304Glu (c.911G&#x3e;A) mutation, with FV:C and FV:Ag reduced to 55 and 62%, respectively. Phe218 and Gly304 were highly conserved in the homologous gene in 9 other species. We hypothesized that the p.Phe218Ser and p.Gly304Glu variants are deleterious and responsible for the reduction in FV:C and FV:Ag.