The completion of the Mammalian Gene Collection (MGC)

The HisRS-like domain of GCN2 is a pseudoenzyme that can bind uncharged tRNA

GCN2 is a stress response kinase that phosphorylates the translation initiation factor eIF2α to inhibit general protein synthesis when activated by uncharged tRNA and stalled ribosomes. The presence of a HisRS-like domain in GCN2, normally associated with tRNA aminoacylation, led to the hypothesis that eIF2α kinase activity is regulated by the direct binding of this domain to uncharged tRNA. Here we solved the structure of the HisRS-like domain in the context of full-length GCN2 by cryoEM. Structure and function analysis shows the HisRS-like domain of GCN2 has lost histidine and ATP binding but retains tRNA binding abilities. Hydrogen deuterium exchange mass spectrometry, site-directed mutagenesis and computational docking experiments support a tRNA binding model that is partially shifted from that employed by bona fide HisRS enzymes. These results demonstrate that the HisRS-like domain of GCN2 is a pseudoenzyme and advance our understanding of GCN2 regulation and function.

Conserved chromatin and repetitive patterns reveal slow genome evolution in frogs

Frogs are an ecologically diverse and phylogenetically ancient group of anuran amphibians that include important vertebrate cell and developmental model systems, notably the genus Xenopus. Here we report a high-quality reference genome sequence for the western clawed frog, Xenopus tropicalis, along with draft chromosome-scale sequences of three distantly related emerging model frog species, Eleutherodactylus coqui, Engystomops pustulosus, and Hymenochirus boettgeri. Frog chromosomes have remained remarkably stable since the Mesozoic Era, with limited Robertsonian (i.e., arm-preserving) translocations and end-to-end fusions found among the smaller chromosomes. Conservation of synteny includes conservation of centromere locations, marked by centromeric tandem repeats associated with Cenp-a binding surrounded by pericentromeric LINE/L1 elements. This work explores the structure of chromosomes across frogs, using a dense meiotic linkage map for X. tropicalis and chromatin conformation capture (Hi-C) data for all species. Abundant satellite repeats occupy the unusually long (~20 megabase) terminal regions of each chromosome that coincide with high rates of recombination. Both embryonic and differentiated cells show reproducible associations of centromeric chromatin and of telomeres, reflecting a Rabl-like configuration. Our comparative analyses reveal 13 conserved ancestral anuran chromosomes from which contemporary frog genomes were constructed.

The evolutionary divergence of receptor guanylyl cyclase C has implications for preclinical models for receptor-directed therapeutics

Mutations in receptor guanylyl cyclase C (GC-C) cause severe gastrointestinal disease, including meconium ileus, early onset acute diarrhea, and pediatric inflammatory bowel disease that continues into adulthood. Agonists of GC-C are US Food and Drug Administration-approved drugs for the treatment of constipation and irritable bowel syndrome. Therapeutic strategies targeting GC-C are tested in preclinical mouse models, assuming that murine GC-C mimics human GC-C in its biochemical properties and downstream signaling events. Here, we reveal important differences in ligand-binding affinity and GC activity between mouse GC-C and human GC-C. We generated a series of chimeric constructs of various domains of human and mouse GC-C to show that the extracellular domain of mouse GC-C contributed to log-orders lower affinity of mouse GC-C for ligands than human GC-C. Further, the Vmax of the murine GC domain was lower than that of human GC-C, and allosteric regulation of the receptor by ATP binding to the intracellular kinase-homology domain also differed. These altered properties are reflected in the high concentrations of ligands required to elicit signaling responses in the mouse gut in preclinical models and the specificity of a GC inhibitor towards human GC-C. Therefore, our studies identify considerations in using the murine model to test molecules for therapeutic purposes that work as either agonists or antagonists of GC-C, and vaccines for the bacterial heat-stable enterotoxin that causes watery diarrhea in humans.

A comprehensive Drosophila resource to identify key functional interactions between SARS-CoV-2 factors and host proteins

Development of effective therapies against SARS-CoV-2 infections relies on mechanistic knowledge of virus-host interface. Abundant physical interactions between viral and host proteins have been identified, but few have been functionally characterized. Harnessing the power of fly genetics, we develop a comprehensive Drosophila COVID-19 resource (DCR) consisting of publicly available strains for conditional tissue-specific expression of all SARS-CoV-2 encoded proteins, UAS-human cDNA transgenic lines encoding established host-viral interacting factors, and GAL4 insertion lines disrupting fly homologs of SARS-CoV-2 human interacting proteins. We demonstrate the utility of the DCR to functionally assess SARS-CoV-2 genes and candidate human binding partners. We show that NSP8 engages in strong genetic interactions with several human candidates, most prominently with the ATE1 arginyltransferase to induce actin arginylation and cytoskeletal disorganization, and that two ATE1 inhibitors can reverse NSP8 phenotypes. The DCR enables parallel global-scale functional analysis of SARS-CoV-2 components in a prime genetic model system.

A positive statistical benchmark to assess network agreement

Current computational methods for validating experimental network datasets compare overlap, i.e., shared links, with a reference network using a negative benchmark. However, this fails to quantify the level of agreement between the two networks. To address this, we propose a positive statistical benchmark to determine the maximum possible overlap between networks. Our approach can efficiently generate this benchmark in a maximum entropy framework and provides a way to assess whether the observed overlap is significantly different from the best-case scenario. We introduce a normalized overlap score, Normlap, to enhance comparisons between experimental networks. As an application, we compare molecular and functional networks, resulting in an agreement network of human as well as yeast network datasets. The Normlap score can improve the comparison between experimental networks by providing a computational alternative to network thresholding and validation.

Rapid, scalable, combinatorial genome engineering by marker-less enrichment and recombination of genetically engineered loci in yeast

A major challenge to rationally building multi-gene processes in yeast arises due to the combinatorics of combining all of the individual edits into the same strain. Here, we present a precise and multi-site genome editing approach that combines all edits without selection markers using CRISPR-Cas9. We demonstrate a highly efficient gene drive that selectively eliminates specific loci by integrating CRISPR-Cas9-mediated double-strand break (DSB) generation and homology-directed recombination with yeast sexual assortment. The method enables marker-less enrichment and recombination of genetically engineered loci (MERGE). We show that MERGE converts single heterologous loci to homozygous loci at ∼100% efficiency, independent of chromosomal location. Furthermore, MERGE is equally efficient at converting and combining multiple loci, thus identifying compatible genotypes. Finally, we establish MERGE proficiency by engineering a fungal carotenoid biosynthesis pathway and most of the human α-proteasome core into yeast. Therefore, MERGE lays the foundation for scalable, combinatorial genome editing in yeast.

Intra-Exon Motif Correlations as a Proxy Measure for Mean Per-Tile Sequence Quality Data in RNA-Seq

Given the wide variability in the quality of next-generation sequencing data submitted to public repositories, it is essential to identify methods that can perform quality control on these data sets when additional quality control data, such as mean tile data, are missing from public repositories. In this study, we present evidence that correlating counts of reads corresponding to pairs of motifs separated over specific distances on individual exons can be used as a proxy mean tile data in the data sets we analyzed and hence could be used when mean tile data are not available. As test data sets we use the Homo sapiens in vitro transcribed (IVT) data set, and a Drosophila melanogaster data set comprising wild and mutant types. We find that a FastQC analysis of the available parts of these data sets demonstrates that the per-tile sequencing quality is good for all the data sets apart from the mutant-type data where the mutant-r3 data are worse than the mutant-r2 data. Correspondingly, intra-exon motif correlations are reasonably large for all data sets except this latter case where the mutant-r2 correlations are low and the mutant-r3 correlations close to zero. We propose that these extremely low correlations are indicative of bias of technical origin, such as flowcell errors. In addition to this, the intra-exon motif correlations as a function of both guanosine-cytosine (GC) content parameters are somewhat higher and less dependent on the GC content parameters in the IVT-Plasmids messenger RNA (mRNA) selection free RNA-Seq sample (control) than in the other RNA-Seq samples that did undergo mRNA selection: both ribosomal depletion (IVT-Only) and PolyA selection (IVT-PolyA, wild type, and mutant).

Structure-guided isoform identification for the human transcriptome

Recently developed methods to predict three-dimensional protein structure with high accuracy have opened new avenues for genome and proteome research. We explore a new hypothesis in genome annotation, namely whether computationally predicted structures can help to identify which of multiple possible gene isoforms represents a functional protein product. Guided by protein structure predictions, we evaluated over 230,000 isoforms of human protein-coding genes assembled from over 10,000 RNA sequencing experiments across many human tissues. From this set of assembled transcripts, we identified hundreds of isoforms with more confidently predicted structure and potentially superior function in comparison to canonical isoforms in the latest human gene database. We illustrate our new method with examples where structure provides a guide to function in combination with expression and evolutionary evidence. Additionally, we provide the complete set of structures as a resource to better understand the function of human genes and their isoforms. These results demonstrate the promise of protein structure prediction as a genome annotation tool, allowing us to refine even the most highly curated catalog of human proteins. More generally we demonstrate a practical, structure-guided approach that can be used to enhance the annotation of any genome.

Revised eutherian gene collections

Objectives

The most recent research projects in scientific field of eutherian comparative genomics included intentions to sequence every extant eutherian species genome in foreseeable future, so that future revisions and updates of eutherian gene data sets were expected.

Data description

Using 35 public eutherian reference genomic sequence assemblies and free available software, the eutherian comparative genomic analysis protocol RRID:SCR_014401 was published as guidance against potential genomic sequence errors. The protocol curated 14 eutherian third-party data gene data sets, including, in aggregate, 2615 complete coding sequences that were deposited in European Nucleotide Archive. The published eutherian gene collections were used in revisions and updates of eutherian gene data set classifications and nomenclatures that included gene annotations, phylogenetic analyses and protein molecular evolution analyses.

Accurate prediction of functional states of cis-regulatory modules reveals common epigenetic rules in humans and mice

BACKGROUND

Predicting cis-regulatory modules (CRMs) in a genome and their functional states in various cell/tissue types of the organism are two related challenging computational tasks. Most current methods attempt to simultaneously achieve both using data of multiple epigenetic marks in a cell/tissue type. Though conceptually attractive, they suffer high false discovery rates and limited applications. To fill the gaps, we proposed a two-step strategy to first predict a map of CRMs in the genome, and then predict functional states of all the CRMs in various cell/tissue types of the organism. We have recently developed an algorithm for the first step that was able to more accurately and completely predict CRMs in a genome than existing methods by integrating numerous transcription factor ChIP-seq datasets in the organism. Here, we presented machine-learning methods for the second step.

RESULTS

We showed that functional states in a cell/tissue type of all the CRMs in the genome could be accurately predicted using data of only 1~4 epigenetic marks by a variety of machine-learning classifiers. Our predictions are substantially more accurate than the best achieved so far. Interestingly, a model trained on a cell/tissue type in humans can accurately predict functional states of CRMs in different cell/tissue types of humans as well as of mice, and vice versa. Therefore, epigenetic code that defines functional states of CRMs in various cell/tissue types is universal at least in humans and mice. Moreover, we found that from tens to hundreds of thousands of CRMs were active in a human and mouse cell/tissue type, and up to 99.98% of them were reutilized in different cell/tissue types, while as small as 0.02% of them were unique to a cell/tissue type that might define the cell/tissue type.

CONCLUSIONS

Our two-step approach can accurately predict functional states in any cell/tissue type of all the CRMs in the genome using data of only 1~4 epigenetic marks. Our approach is also more cost-effective than existing methods that typically use data of more epigenetic marks. Our results suggest common epigenetic rules for defining functional states of CRMs in various cell/tissue types in humans and mice.

Genetic variation associated with condensate dysregulation in disease

A multitude of cellular processes involve biomolecular condensates, which has led to the suggestion that diverse pathogenic mutations may dysregulate condensates. Although proof-of-concept studies have identified specific mutations that cause condensate dysregulation, the full scope of the pathological genetic variation that affects condensates is not yet known. Here, we comprehensively map pathogenic mutations to condensate-promoting protein features in putative condensate-forming proteins and find over 36,000 pathogenic mutations that plausibly contribute to condensate dysregulation in over 1,200 Mendelian diseases and 550 cancers. This resource captures mutations presently known to dysregulate condensates, and experimental tests confirm that additional pathological mutations do indeed affect condensate properties in cells. These findings suggest that condensate dysregulation may be a pervasive pathogenic mechanism underlying a broad spectrum of human diseases, provide a strategy to identify proteins and mutations involved in pathologically altered condensates, and serve as a foundation for mechanistic insights into disease and therapeutic hypotheses.

A comprehensive SARS-CoV-2-human protein-protein interactome network identifies pathobiology and host-targeting therapies for COVID-19

Physical interactions between viral and host proteins are responsible for almost all aspects of the viral life cycle and the host's immune response. Studying viral-host protein-protein interactions is thus crucial for identifying strategies for treatment and prevention of viral infection. Here, we use high-throughput yeast two-hybrid and affinity purification followed by mass spectrometry to generate a comprehensive SARS-CoV-2-human protein-protein interactome network consisting of both binary and co-complex interactions. We report a total of 739 high-confidence interactions, showing the highest overlap of interaction partners among published datasets as well as the highest overlap with genes differentially expressed in samples (such as upper airway and bronchial epithelial cells) from patients with SARS-CoV-2 infection. Showcasing the utility of our network, we describe a novel interaction between the viral accessory protein ORF3a and the host zinc finger transcription factor ZNF579 to illustrate a SARS-CoV-2 factor mediating a direct impact on host transcription. Leveraging our interactome, we performed network-based drug screens for over 2,900 FDA-approved/investigational drugs and obtained a curated list of 23 drugs that had significant network proximities to SARS-CoV-2 host factors, one of which, carvedilol, showed promising antiviral properties. We performed electronic health record-based validation using two independent large-scale, longitudinal COVID-19 patient databases and found that carvedilol usage was associated with a significantly lowered probability (17%-20%, P < 0.001) of obtaining a SARS-CoV-2 positive test after adjusting various confounding factors. Carvedilol additionally showed anti-viral activity against SARS-CoV-2 in a human lung epithelial cell line [half maximal effective concentration (EC ₅₀ ) value of 4.1 µM], suggesting a mechanism for its beneficial effect in COVID-19. Our study demonstrates the value of large-scale network systems biology approaches for extracting biological insight from complex biological processes.

Humanized yeast to model human biology, disease and evolution

For decades, budding yeast, a single-cellular eukaryote, has provided remarkable insights into human biology. Yeast and humans share several thousand genes despite morphological and cellular differences and over a billion years of separate evolution. These genes encode critical cellular processes, the failure of which in humans results in disease. Although recent developments in genome engineering of mammalian cells permit genetic assays in human cell lines, there is still a need to develop biological reagents to study human disease variants in a high-throughput manner. Many protein-coding human genes can successfully substitute for their yeast equivalents and sustain yeast growth, thus opening up doors for developing direct assays of human gene function in a tractable system referred to as 'humanized yeast'. Humanized yeast permits the discovery of new human biology by measuring human protein activity in a simplified organismal context. This Review summarizes recent developments showing how humanized yeast can directly assay human gene function and explore variant effects at scale. Thus, by extending the 'awesome power of yeast genetics' to study human biology, humanizing yeast reinforces the high relevance of evolutionarily distant model organisms to explore human gene evolution, function and disease.

High throughput screening for compounds to the orphan nuclear receptor NR2F6

NR2F6 is considered an orphan nuclear receptor since its endogenous ligand has yet to be identified. Recently, NR2F6 has emerged as a novel cancer therapeutic target. NR2F6 has been demonstrated to be upregulated or overexpressed in several cancers. Importantly, Nr2f6^-/- mice spontaneously reject tumors and develop host-protective immunological memory, a consequence of NR2F6 acting as an immune checkpoint in effector T cells. Collectively, these data suggest that modulation of NR2F6 activity may have important clinical applications in the fight against cancer. The nuclear receptor superfamily of ligand-regulated transcription factors has proven to be an excellent source of targets for therapeutic intervention of a broad range of diseases. Approximately 15% of FDA approved drugs target NRs, demonstrating their clinical efficacy. To identify small molecule regulators of NR2F6 activity, with the overall goal of immuno-oncology, we developed and initiated a high-throughput cell-based assay that specifically measures the transcriptional activity of NR2F6. We completed automated screening of approximately 666,000 compounds and identified 5,008 initial hits. Further screening efforts, including counterscreening assays, confirmed 128 of these hits, most of which had IC₅₀s of equal to or less than 5μM potencies. Here, we report, for the first time, the identification of several small molecule compounds to the orphan nuclear receptor, NR2F6.

Drosophila functional screening of de novo variants in autism uncovers damaging variants and facilitates discovery of rare neurodevelopmental diseases

Individuals with autism spectrum disorder (ASD) exhibit an increased burden of de novo mutations (DNMs) in a broadening range of genes. While these studies have implicated hundreds of genes in ASD pathogenesis, which DNMs cause functional consequences in vivo remains unclear. We functionally test the effects of ASD missense DNMs using Drosophila through "humanization" rescue and overexpression-based strategies. We examine 79 ASD variants in 74 genes identified in the Simons Simplex Collection and find 38% of them to cause functional alterations. Moreover, we identify GLRA2 as the cause of a spectrum of neurodevelopmental phenotypes beyond ASD in 13 previously undiagnosed subjects. Functional characterization of variants in ASD candidate genes points to conserved neurobiological mechanisms and facilitates gene discovery for rare neurodevelopmental diseases.

Evolutionarily conserved inhibitory uORFs sensitize Hox mRNA translation to start codon selection stringency

Translation start site selection in eukaryotes is influenced by context nucleotides flanking the AUG codon and by levels of the eukaryotic translation initiation factors eIF1 and eIF5. In a search of mammalian genes, we identified five homeobox (Hox) gene paralogs initiated by AUG codons in conserved suboptimal context as well as 13 Hox genes that contain evolutionarily conserved upstream open reading frames (uORFs) that initiate at AUG codons in poor sequence context. An analysis of published cap analysis of gene expression sequencing (CAGE-seq) data and generated CAGE-seq data for messenger RNAs (mRNAs) from mouse somites revealed that the 5' leaders of Hox mRNAs of interest contain conserved uORFs, are generally much shorter than reported, and lack previously proposed internal ribosome entry site elements. We show that the conserved uORFs inhibit Hox reporter expression and that altering the stringency of start codon selection by overexpressing eIF1 or eIF5 modulates the expression of Hox reporters. We also show that modifying ribosome homeostasis by depleting a large ribosomal subunit protein or treating cells with sublethal concentrations of puromycin leads to lower stringency of start codon selection. Thus, altering global translation can confer gene-specific effects through altered start codon selection stringency.

OUP accepted manuscript

Alternative splicing is frequently involved in the diversification of protein function and can also be modulated for therapeutic purposes. Here we develop a predictive model, called Exon ByPASS (predicting Exon skipping Based on Protein amino acid SequenceS), to assess the criticality of exon inclusion based solely on information contained in the amino acid sequence upstream and downstream of the exon junctions. By focusing on protein sequence, Exon ByPASS predicts exon skipping independent of tissue and species in the absence of any intronic information. We validate model predictions using transcriptomic and proteomic data and show that the model can capture exon skipping in different tissues and species. Additionally, we reveal potential therapeutic opportunities by predicting synthetically skippable exons and neo-junctions arising in cancer cells.

Broadening the Toolkit for Quantitatively Evaluating Noncanonical Amino Acid Incorporation in Yeast

Genetic code expansion is a powerful approach for advancing critical fields such as biological therapeutic discovery. However, the machinery for genetically encoding noncanonical amino acids (ncAAs) is only available in limited plasmid formats, constraining potential applications. In extreme cases, the introduction of two separate plasmids, one containing an orthogonal translation system (OTS) to facilitate ncAA incorporation and a second for expressing a ncAA-containing protein of interest, is not possible due to a lack of the available selection markers. One strategy to circumvent this challenge is to express the OTS and protein of interest from a single vector. For what we believe is the first time in yeast, we describe here several sets of single plasmid systems (SPSs) for performing genetic code manipulation and compare the ncAA incorporation capabilities of these plasmids against the capabilities of previously described dual plasmid systems (DPSs). For both dual fluorescent protein reporters and yeast display reporters tested with multiple OTSs and ncAAs, measured ncAA incorporation efficiencies with SPSs were determined to be equal to efficiencies determined with DPSs. Click chemistry on yeast cells displaying ncAA-containing proteins was also shown to be feasible in both formats, although differences in reactivity between formats suggest the need for caution when using such approaches. Additionally, we investigated whether these reporters would support the separation of yeast strains known to exhibit distinct ncAA incorporation efficiencies. Model sorts conducted with mixtures of two strains transformed with the same SPS or DPS both led to the enrichment of a strain known to support a higher efficiency ncAA incorporation, suggesting that these reporters will be suitable for conducting screens for strains exhibiting enhanced ncAA incorporation efficiencies. Overall, our results confirm that SPSs are well behaved in yeast and provide a convenient alternative to DPSs. SPSs are expected to be invaluable for conducting high-throughput investigations of the effects of genetic or genomic changes on ncAA incorporation efficiency and, more fundamentally, the eukaryotic translation apparatus.

Human MLH1/3 variants causing aneuploidy, pregnancy loss, and premature reproductive aging

Embryonic aneuploidy from mis-segregation of chromosomes during meiosis causes pregnancy loss. Proper disjunction of homologous chromosomes requires the mismatch repair (MMR) genes MLH1 and MLH3, essential in mice for fertility. Variants in these genes can increase colorectal cancer risk, yet the reproductive impacts are unclear. To determine if MLH1/3 single nucleotide polymorphisms (SNPs) in human populations could cause reproductive abnormalities, we use computational predictions, yeast two-hybrid assays, and MMR and recombination assays in yeast, selecting nine MLH1 and MLH3 variants to model in mice via genome editing. We identify seven alleles causing reproductive defects in mice including female subfertility and male infertility. Remarkably, in females these alleles cause age-dependent decreases in litter size and increased embryo resorption, likely a consequence of fewer chiasmata that increase univalents at meiotic metaphase I. Our data suggest that hypomorphic alleles of meiotic recombination genes can predispose females to increased incidence of pregnancy loss from gamete aneuploidy.

Proper meiotic chromosome segregation requires mismatch repair genes MLH1 and MLH3, of which variants occur in the human population. Here, the authors use computational predictions and yeast assays to select human MLH1/3 variants for modelling in mice, observing reproductive defects from abnormal levels of crossing over.

In vivo functional screening for systems-level integrative cancer genomics

With the genetic portraits of all major human malignancies now available, we next face the challenge of characterizing the function of mutated genes, their downstream targets, interactions and molecular networks. Moreover, poorly understood at the functional level are also non-mutated but dysregulated genomes, epigenomes or transcriptomes. Breakthroughs in manipulative mouse genetics offer new opportunities to probe the interplay of molecules, cells and systemic signals underlying disease pathogenesis in higher organisms. Herein, we review functional screening strategies in mice using genetic perturbation and chemical mutagenesis. We outline the spectrum of genetic tools that exist, such as transposons, CRISPR and RNAi and describe discoveries emerging from their use. Genome-wide or targeted screens are being used to uncover genomic and regulatory landscapes in oncogenesis, metastasis or drug resistance. Versatile screening systems support experimentation in diverse genetic and spatio-temporal settings to integrate molecular, cellular or environmental context-dependencies. We also review the combination of in vivo screening and barcoding strategies to study genetic interactions and quantitative cancer dynamics during tumour evolution. These scalable functional genomics approaches are transforming our ability to interrogate complex biological systems.

A uniform expression library for the exploration of FOX transcription factor biology

Forkhead box (FOX) family transcription factors play essential roles in development, tissue homeostasis, and disease. Although the biology of several FOX proteins has been studied in depth, it is unclear to what extent these findings apply to even closely related family members, which frequently exert overlapping but non-redundant functions. To help address this question, we have generated a uniform, ready-to-use expression library of all 44 human FOX transcription factors with a convenient peptide tag for parallel screening assays. In addition, we have generated multiple universal forkhead box reporter plasmids, which can be used to monitor the transcriptional activity of most FOX proteins with high fidelity. As a proof-of-principle, we use our plasmid library to identify the DNA repair protein XRCC6/Ku70 as a selective FOX interaction partner and regulator of FOX transcriptional activity. We believe that these tools, which we make available via the Addgene plasmid repository, will considerably expedite the investigation of FOX protein biology.

CRISPR-mediated transcriptional activation with synthetic guide RNA

The CRISPR-Cas9 system has been adapted for transcriptional activation (CRISPRa) and several second-generation CRISPRa systems (including VPR, SunTag, and SAM) have been developed to recruit different transcriptional activators to a deactivated Cas9, which is guided to a transcriptional start site via base complementarity with a target guide RNA. Multiple studies have shown the benefit of CRISPRa using plasmid or lentiviral expressed guide RNA, but the use of synthetic guide RNA has not been reported. Here we demonstrate the effective use of synthetic guide RNA for gene activation via CRISPRa. CRISPRa crRNA may be used with a canonical tracrRNA using the VPR or SunTag activation systems or with an extended tracrRNA containing an aptamer sequence for the SAM system. Transcriptional activation with synthetic crRNA:tracrRNA is comparable to activation achieved with expression vectors and combining several crRNA sequences targeting the same gene can enhance transcriptional activation. The use of synthetic crRNA is also ideal for simultaneous activation of multiple genes or use with dCas9-VPR mRNA when viral transduction is not feasible. Here, we perform a proof-of-principle arrayed screen using a CRISPRa crRNA library consisting of 153 cytokine receptor targets to identify regulators of IL-6 cytokine secretion. Together, these results demonstrate the suitability of synthetic CRISPRa guide RNA for high throughput, arrayed screening applications which allow for more complex phenotypic readouts to complement viability and drug resistance assays typically used in a pooled screening format.

Systematic Humanization of the Yeast Cytoskeleton Discerns Functionally Replaceable from Divergent Human Genes

Many gene families have been expanded by gene duplications along the human lineage, relative to ancestral opisthokonts, but the extent to which the duplicated genes function similarly is understudied. Here, we focused on structural cytoskeletal genes involved in critical cellular processes, including chromosome segregation, macromolecular transport, and cell shape maintenance. To determine functional redundancy and divergence of duplicated human genes, we systematically humanized the yeast actin, myosin, tubulin, and septin genes, testing ∼81% of human cytoskeletal genes across seven gene families for their ability to complement a growth defect induced by inactivation or deletion of the corresponding yeast ortholog. In five of seven families-all but α-tubulin and light myosin, we found at least one human gene capable of complementing loss of the yeast gene. Despite rescuing growth defects, we observed differential abilities of human genes to rescue cell morphology, meiosis, and mating defects. By comparing phenotypes of humanized strains with deletion phenotypes of their interaction partners, we identify instances of human genes in the actin and septin families capable of carrying out essential functions, but failing to fully complement the cytoskeletal roles of their yeast orthologs, thus leading to abnormal cell morphologies. Overall, we show that duplicated human cytoskeletal genes appear to have diverged such that only a few human genes within each family are capable of replacing the essential roles of their yeast orthologs. The resulting yeast strains with humanized cytoskeletal components now provide surrogate platforms to characterize human genes in simplified eukaryotic contexts.

Secretome-Based Screening in Target Discovery

Secreted proteins and their cognate plasma membrane receptors regulate human physiology by transducing signals from the extracellular environment into cells resulting in different cellular phenotypes. Systematic use of secretome proteins in assays enables discovery of novel biology and signaling pathways. Several secretome-based phenotypic screening platforms have been described in the literature and shown to facilitate target identification in drug discovery. In this review, we summarize the current status of secretome-based screening. This includes annotation, production, quality control, and sample management of secretome libraries, as well as how secretome libraries have been applied to discover novel target biology using different disease-relevant cell-based assays. A workflow for secretome-based screening is shared based on the AstraZeneca experience. The secretome library offers several advantages compared with other libraries used for target discovery: (1) screening using a secretome library directly identifies the active protein and, in many cases, its cognate receptor, enabling a rapid understanding of the disease pathway and subsequent formation of target hypotheses for drug discovery; (2) the secretome library covers significant areas of biological signaling space, although the size of this library is small; (3) secretome proteins can be added directly to cells without additional manipulation. These factors make the secretome library ideal for testing in physiologically relevant cell types, and therefore it represents an attractive approach to phenotypic target discovery.

Humanization of yeast genes with multiple human orthologs reveals functional divergence between paralogs

Despite over a billion years of evolutionary divergence, several thousand human genes possess clearly identifiable orthologs in yeast, and many have undergone lineage-specific duplications in one or both lineages. These duplicated genes may have been free to diverge in function since their expansion, and it is unclear how or at what rate ancestral functions are retained or partitioned among co-orthologs between species and within gene families. Thus, in order to investigate how ancestral functions are retained or lost post-duplication, we systematically replaced hundreds of essential yeast genes with their human orthologs from gene families that have undergone lineage-specific duplications, including those with single duplications (1 yeast gene to 2 human genes, 1:2) or higher-order expansions (1:>2) in the human lineage. We observe a variable pattern of replaceability across different ortholog classes, with an obvious trend toward differential replaceability inside gene families, and rarely observe replaceability by all members of a family. We quantify the ability of various properties of the orthologs to predict replaceability, showing that in the case of 1:2 orthologs, replaceability is predicted largely by the divergence and tissue-specific expression of the human co-orthologs, i.e., the human proteins that are less diverged from their yeast counterpart and more ubiquitously expressed across human tissues more often replace their single yeast ortholog. These trends were consistent with in silico simulations demonstrating that when only one ortholog can replace its corresponding yeast equivalent, it tends to be the least diverged of the pair. Replaceability of yeast genes having more than 2 human co-orthologs was marked by retention of orthologous interactions in functional or protein networks as well as by more ancestral subcellular localization. Overall, we performed >400 human gene replaceability assays, revealing 50 new human-yeast complementation pairs, thus opening up avenues to further functionally characterize these human genes in a simplified organismal context.

Extensive disruption of protein interactions by genetic variants across the allele frequency spectrum in human populations

Each human genome carries tens of thousands of coding variants. The extent to which this variation is functional and the mechanisms by which they exert their influence remains largely unexplored. To address this gap, we leverage the ExAC database of 60,706 human exomes to investigate experimentally the impact of 2009 missense single nucleotide variants (SNVs) across 2185 protein-protein interactions, generating interaction profiles for 4797 SNV-interaction pairs, of which 421 SNVs segregate at > 1% allele frequency in human populations. We find that interaction-disruptive SNVs are prevalent at both rare and common allele frequencies. Furthermore, these results suggest that 10.5% of missense variants carried per individual are disruptive, a higher proportion than previously reported; this indicates that each individual's genetic makeup may be significantly more complex than expected. Finally, we demonstrate that candidate disease-associated mutations can be identified through shared interaction perturbations between variants of interest and known disease mutations.

In Vivo Functional Study of Disease-associated Rare Human Variants Using Drosophila

Advances in sequencing technology have made whole-genome and whole-exome datasets more accessible for both clinical diagnosis and cutting-edge human genetics research. Although a number of in silico algorithms have been developed to predict the pathogenicity of variants identified in these datasets, functional studies are critical to determining how specific genomic variants affect protein function, especially for missense variants. In the Undiagnosed Diseases Network (UDN) and other rare disease research consortia, model organisms (MO) including Drosophila, C. elegans, zebrafish, and mice are actively used to assess the function of putative human disease-causing variants. This protocol describes a method for the functional assessment of rare human variants used in the Model Organisms Screening Center Drosophila Core of the UDN. The workflow begins with gathering human and MO information from multiple public databases, using the MARRVEL web resource to assess whether the variant is likely to contribute to a patient's condition as well as design effective experiments based on available knowledge and resources. Next, genetic tools (e.g., T2A-GAL4 and UAS-human cDNA lines) are generated to assess the functions of variants of interest in Drosophila. Upon development of these reagents, two-pronged functional assays based on rescue and overexpression experiments can be performed to assess variant function. In the rescue branch, the endogenous fly genes are "humanized" by replacing the orthologous Drosophila gene with reference or variant human transgenes. In the overexpression branch, the reference and variant human proteins are exogenously driven in a variety of tissues. In both cases, any scorable phenotype (e.g., lethality, eye morphology, electrophysiology) can be used as a read-out, irrespective of the disease of interest. Differences observed between reference and variant alleles suggest a variant-specific effect, and thus likely pathogenicity. This protocol allows rapid, in vivo assessments of putative human disease-causing variants of genes with known and unknown functions.

Next-generation genome annotation: we still struggle to get it right

While the genome sequencing revolution has led to the sequencing and assembly of many thousands of new genomes, genome annotation still uses very nearly the same technology that we have used for the past two decades. The sheer number of genomes necessitates the use of fully automated procedures for annotation, but errors in annotation are just as prevalent as they were in the past, if not more so. How are we to solve this growing problem?

The NCATS BioPlanet - An Integrated Platform for Exploring the Universe of Cellular Signaling Pathways for Toxicology, Systems Biology, and Chemical Genomics

Chemical genomics aims to comprehensively define, and ultimately predict, the effects of small molecule compounds on biological systems. Chemical activity profiling approaches must consider chemical effects on all pathways operative in mammalian cells. To enable a strategic and maximally efficient chemical profiling of pathway space, we have created the NCATS BioPlanet, a comprehensive integrated pathway resource that incorporates the universe of 1,658 human pathways sourced from publicly available, manually curated sources, which have been subjected to thorough redundancy and consistency cross-evaluation. BioPlanet supports interactive browsing, retrieval, and analysis of pathways, exploration of pathway connections, and pathway search by gene targets, category, and availability of corresponding bioactivity assay, as well as visualization of pathways on a 3-dimensional globe, in which the distance between any two pathways is proportional to their degree of gene component overlap. Using this resource, we propose a strategy to identify a minimal set of 362 biological assays that can interrogate the universe of human pathways. The NCATS BioPlanet is a public resource, which will be continually expanded and updated, for systems biology, toxicology, and chemical genomics, available at http://tripod.nih.gov/bioplanet/.

Opening options for material transfer

The Open Material Transfer Agreement is a material-transfer agreement that enables broader sharing and use of biological materials by biotechnology practitioners working within the practical realities of technology transfer.

DeepGSR: an optimized deep-learning structure for the recognition of genomic signals and regions

MOTIVATION

Recognition of different genomic signals and regions (GSRs) in DNA is crucial for understanding genome organization, gene regulation, and gene function, which in turn generate better genome and gene annotations. Although many methods have been developed to recognize GSRs, their pure computational identification remains challenging. Moreover, various GSRs usually require a specialized set of features for developing robust recognition models. Recently, deep-learning (DL) methods have been shown to generate more accurate prediction models than 'shallow' methods without the need to develop specialized features for the problems in question. Here, we explore the potential use of DL for the recognition of GSRs.

RESULTS

We developed DeepGSR, an optimized DL architecture for the prediction of different types of GSRs. The performance of the DeepGSR structure is evaluated on the recognition of polyadenylation signals (PAS) and translation initiation sites (TIS) of different organisms: human, mouse, bovine and fruit fly. The results show that DeepGSR outperformed the state-of-the-art methods, reducing the classification error rate of the PAS and TIS prediction in the human genome by up to 29% and 86%, respectively. Moreover, the cross-organisms and genome-wide analyses we performed, confirmed the robustness of DeepGSR and provided new insights into the conservation of examined GSRs across species.

AVAILABILITY AND IMPLEMENTATION

DeepGSR is implemented in Python using Keras API; it is available as open-source software and can be obtained at https://doi.org/10.5281/zenodo.1117159.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Molecular Determinants of Substrate Specificity in Human Insulin-Degrading Enzyme

Insulin-degrading enzyme (IDE) is a 110 kDa chambered zinc metalloendopeptidase that degrades insulin, amyloid β, and other intermediate-sized aggregation prone peptides that adopt β-structures. Structural studies of IDE in complex with multiple physiological substrates have suggested a role for hydrophobic and aromatic residues of the IDE active site in substrate binding and catalysis. Here, we examine functional requirements for conserved hydrophobic and aromatic IDE active site residues that are positioned within 4.5 Å of IDE-bound insulin B chain and amyloid β peptides in the reported crystal structures for the respective enzyme-substrate complexes. Charge, size, hydrophobicity, aromaticity, and other functional group requirements for substrate binding IDE active site residues were examined through mutational analysis of the recombinant human enzyme and enzyme kinetic studies conducted using native and fluorogenic derivatives of human insulin and amyloid β peptides. A functional requirement for IDE active site residues F115, A140, F141, Y150, W199, F202, F820, and Y831 was established, and specific contributions of residue charge, size, and hydrophobicity to substrate binding, specificity, and proteolysis were demonstrated. IDE mutant alleles that exhibited enhanced or diminished proteolytic activity toward insulin or amyloid β peptides and derivative substrates were identified.

Towards a map of cis-regulatory sequences in the human genome

Accumulating evidence indicates that transcription factor (TF) binding sites, or cis-regulatory elements (CREs), and their clusters termed cis-regulatory modules (CRMs) play a more important role than do gene-coding sequences in specifying complex traits in humans, including the susceptibility to common complex diseases. To fully characterize their roles in deriving the complex traits/diseases, it is necessary to annotate all CREs and CRMs encoded in the human genome. However, the current annotations of CREs and CRMs in the human genome are still very limited and mostly coarse-grained, as they often lack the detailed information of CREs in CRMs. Here, we integrated 620 TF ChIP-seq datasets produced by the ENCODE project for 168 TFs in 79 different cell/tissue types and predicted an unprecedentedly completely map of CREs in CRMs in the human genome at single nucleotide resolution. The map includes 305 912 CRMs containing a total of 1 178 913 CREs belonging to 736 unique TF binding motifs. The predicted CREs and CRMs tend to be subject to either purifying selection or positive selection, thus are likely to be functional. Based on the results, we also examined the status of available ChIP-seq datasets for predicting the entire regulatory genome of humans.

Functional requirement for human pitrilysin metallopeptidase 1 arginine 183, mutated in amyloidogenic neuropathy

Here we report the enzymologic characterization of recombinant human pitrilysin metallopeptidase 1 (Pitrm1) and derivative mutants including the arginine-to-glutamine substitution mutant Pitrm1 R183Q, which has been implicated in inherited amyloidogenic neuropathy. Recombinant Pitrm1 R183Q was readily expressed in and purified from Escherichia coli, but was less active than the recombinant wild-type enzyme against recombinant amyloid beta-peptide (Aβ 1-40). A novel fluorogenic substrate derived from the reported Aβ 1-40 core peptide cleavage sequence, Mca-KLVFFAEDK-(Dnp)-OH, was synthesized and applied to real-time kinetic study of Pitrm1 and derivative mutants including Pitrm1 R183Q. The Pitrm1 R183Q mutant exhibited significantly decreased rate of fluorogenic peptide hydrolysis, yet retained similar binding affinity by comparison with the wild-type enzyme. Targeted mutagenic analysis revealed a functional requirement for uncharged or electropositive residues in place of Pitrm1 R183. Residue R183 is positioned within an N-terminal strand-loop-strand motif that is conserved among M16C, but not M16A or M16B family metallopeptidases. Truncation analysis revealed that this strand-loop-strand motif inclusive of residue R183 is essential Pitrm1 function. A requirement for charged residues within 4.5 Å of residue R183 was demonstrated, and Pitrm1 R183Q was found to exhibit increased sensitivity to heat inactivation. Our findings indicate that charge sharing in the vicinity of Pitrm1 R183 is critical to enzyme activity, providing potential insight into a molecular basis of Pitrm1 dysfunction.

Protein localization screening in vivo reveals novel regulators of multiciliated cell development and function

Multiciliated cells (MCCs) drive fluid flow in diverse tubular organs and are essential for the development and homeostasis of the vertebrate central nervous system, airway and reproductive tracts. These cells are characterized by dozens or hundreds of motile cilia that beat in a coordinated and polarized manner. In recent years, genomic studies have not only elucidated the transcriptional hierarchy for MCC specification but also identified myriad new proteins that govern MCC ciliogenesis, cilia beating and cilia polarization. Interestingly, this burst of genomic data has also highlighted that proteins with no obvious role in cilia do, in fact, have important ciliary functions. Understanding the function of proteins with little prior history of study presents a special challenge, especially when faced with large numbers of such proteins. Here, we define the subcellular localization in MCCs of ∼200 proteins not previously implicated in cilia biology. Functional analyses arising from the screen provide novel links between actin cytoskeleton and MCC ciliogenesis.

Zebrafish Transcription Factor ORFeome for Gene Discovery and Regulatory Network Elucidation

The completion of the zebrafish genome sequence and advances in miniaturization and multiplexing were essential to the creation of techniques such as RNA-seq, ChIP-seq, and high-throughput behavioral and chemical screens. Multiplexing was also instrumental in the recent enhancement of the classic yeast one-hybrid interaction techniques to provide unprecedented discovery capabilities for protein-DNA interactions. Unfortunately its use for zebrafish research is currently hampered by the lack of an open reading frame (ORF) clone collection. As a first step toward a complete collection, we describe a small library of transcriptional regulatory proteins comprising 142 ORFs and its potential applications.

Model Organisms Facilitate Rare Disease Diagnosis and Therapeutic Research

Efforts to identify the genetic underpinnings of rare undiagnosed diseases increasingly involve the use of next-generation sequencing and comparative genomic hybridization methods. These efforts are limited by a lack of knowledge regarding gene function, and an inability to predict the impact of genetic variation on the encoded protein function. Diagnostic challenges posed by undiagnosed diseases have solutions in model organism research, which provides a wealth of detailed biological information. Model organism geneticists are by necessity experts in particular genes, gene families, specific organs, and biological functions. Here, we review the current state of research into undiagnosed diseases, highlighting large efforts in North America and internationally, including the Undiagnosed Diseases Network (UDN) (Supplemental Material, File S1) and UDN International (UDNI), the Centers for Mendelian Genomics (CMG), and the Canadian Rare Diseases Models and Mechanisms Network (RDMM). We discuss how merging human genetics with model organism research guides experimental studies to solve these medical mysteries, gain new insights into disease pathogenesis, and uncover new therapeutic strategies.

Construction and Screening of a Lentiviral Secretome Library

Over 2,000 human proteins are predicted to be secreted, but the biological function of the many of these proteins is still unknown. Moreover, a number of these proteins may act as new therapeutic agents or be targets for the development of therapeutic antibodies. To further explore the extracellular proteome, we have developed a secretome-enriched open reading frame (ORF) library that can be readily screened for autocrine activity in cell-based phenotypic or reporter assays. Next-generation sequencing (NGS) and database analysis predict that the library contains approximately 900 ORFs encoding known secreted proteins (accounting for 77.8% of the library), as well as genes encoding potentially unknown secreted proteins. In a proof-of-principle study, human TF-1 cells were screened for proliferative factors, and the known cytokine GMCSF was identified as a dominant hit. This library offers a relatively low-cost and straightforward approach for functional autocrine screens of secreted proteins.

Identifying pathogenicity of human variants via paralog-based yeast complementation

To better understand the health implications of personal genomes, we now face a largely unmet challenge to identify functional variants within disease-associated genes. Functional variants can be identified by trans-species complementation, e.g., by failure to rescue a yeast strain bearing a mutation in an orthologous human gene. Although orthologous complementation assays are powerful predictors of pathogenic variation, they are available for only a few percent of human disease genes. Here we systematically examine the question of whether complementation assays based on paralogy relationships can expand the number of human disease genes with functional variant detection assays. We tested over 1,000 paralogous human-yeast gene pairs for complementation, yielding 34 complementation relationships, of which 33 (97%) were novel. We found that paralog-based assays identified disease variants with success on par with that of orthology-based assays. Combining all homology-based assay results, we found that complementation can often identify pathogenic variants outside the homologous sequence region, presumably because of global effects on protein folding or stability. Within our search space, paralogy-based complementation more than doubled the number of human disease genes with a yeast-based complementation assay for disease variation.

Functional complementation assays of human disease-associated gene variants can reveal many more human disease variants at high confidence than current computational approaches, even using highly-diverged model organisms. However, this has generally only been possible for a minority of human disease genes for which orthologous complementation is known in the relevant model organism, so that alternative assays are urgently needed. Here we show that complementation relationships can be found for many additional human disease genes by exploiting paralogous human-yeast gene relationships, and that disease variant identification using paralogy-based assays performs on par with orthology-based assays.

Engineering and Functional Characterization of Fusion Genes Identifies Novel Oncogenic Drivers of Cancer

Oncogenic gene fusions drive many human cancers, but tools to more quickly unravel their functional contributions are needed. Here we describe methodology permitting fusion gene construction for functional evaluation. Using this strategy, we engineered the known fusion oncogenes, BCR-ABL1, EML4-ALK, and ETV6-NTRK3, as well as 20 previously uncharacterized fusion genes identified in The Cancer Genome Atlas datasets. In addition to confirming oncogenic activity of the known fusion oncogenes engineered by our construction strategy, we validated five novel fusion genes involving MET, NTRK2, and BRAF kinases that exhibited potent transforming activity and conferred sensitivity to FDA-approved kinase inhibitors. Our fusion construction strategy also enabled domain-function studies of BRAF fusion genes. Our results confirmed other reports that the transforming activity of BRAF fusions results from truncation-mediated loss of inhibitory domains within the N-terminus of the BRAF protein. BRAF mutations residing within this inhibitory region may provide a means for BRAF activation in cancer, therefore we leveraged the modular design of our fusion gene construction methodology to screen N-terminal domain mutations discovered in tumors that are wild-type at the BRAF mutation hotspot, V600. We identified an oncogenic mutation, F247L, whose expression robustly activated the MAPK pathway and sensitized cells to BRAF and MEK inhibitors. When applied broadly, these tools will facilitate rapid fusion gene construction for subsequent functional characterization and translation into personalized treatment strategies. Cancer Res; 77(13); 3502-12. ©2017 AACR.

Interactome disassembly during apoptosis occurs independent of caspase cleavage

Protein-protein interaction networks (interactomes) define the functionality of all biological systems. In apoptosis, proteolysis by caspases is thought to initiate disassembly of protein complexes and cell death. Here we used a quantitative proteomics approach, protein correlation profiling (PCP), to explore changes in cytoplasmic and mitochondrial interactomes in response to apoptosis initiation as a function of caspase activity. We measured the response to initiation of Fas-mediated apoptosis in 17,991 interactions among 2,779 proteins, comprising the largest dynamic interactome to date. The majority of interactions were unaffected early in apoptosis, but multiple complexes containing known caspase targets were disassembled. Nonetheless, proteome-wide analysis of proteolytic processing by terminal amine isotopic labeling of substrates (TAILS) revealed little correlation between proteolytic and interactome changes. Our findings show that, in apoptosis, significant interactome alterations occur before and independently of caspase activity. Thus, apoptosis initiation includes a tight program of interactome rearrangement, leading to disassembly of relatively few, select complexes. These early interactome alterations occur independently of cleavage of these protein by caspases.

Human splicing diversity and the extent of unannotated splice junctions across human RNA-seq samples on the Sequence Read Archive

BACKGROUND

Gene annotations, such as those in GENCODE, are derived primarily from alignments of spliced cDNA sequences and protein sequences. The impact of RNA-seq data on annotation has been confined to major projects like ENCODE and Illumina Body Map 2.0.

RESULTS

We aligned 21,504 Illumina-sequenced human RNA-seq samples from the Sequence Read Archive (SRA) to the human genome and compared detected exon-exon junctions with junctions in several recent gene annotations. We found 56,861 junctions (18.6%) in at least 1000 samples that were not annotated, and their expression associated with tissue type. Junctions well expressed in individual samples tended to be annotated. Newer samples contributed few novel well-supported junctions, with the vast majority of detected junctions present in samples before 2013. We compiled junction data into a resource called intropolis available at http://intropolis.rail.bio . We used this resource to search for a recently validated isoform of the ALK gene and characterized the potential functional implications of unannotated junctions with publicly available TRAP-seq data.

CONCLUSIONS

Considering only the variation contained in annotation may suffice if an investigator is interested only in well-expressed transcript isoforms. However, genes that are not generally well expressed and nonetheless present in a small but significant number of samples in the SRA are likelier to be incompletely annotated. The rate at which evidence for novel junctions has been added to the SRA has tapered dramatically, even to the point of an asymptote. Now is perhaps an appropriate time to update incomplete annotations to include splicing present in the now-stable snapshot provided by the SRA.

Versatile in vivo regulation of tumor phenotypes by dCas9-mediated transcriptional perturbation

Targeted transcriptional regulation is a powerful tool to study genetic mediators of cellular behavior. Here, we show that catalytically dead Cas9 (dCas9) targeted to genomic regions upstream or downstream of the transcription start site allows for specific and sustainable gene-expression level alterations in tumor cells in vitro and in syngeneic immune-competent mouse models. We used this approach for a high-coverage pooled gene-activation screen in vivo and discovered previously unidentified modulators of tumor growth and therapeutic response. Moreover, by using dCas9 linked to an activation domain, we can either enhance or suppress target gene expression simply by changing the genetic location of dCas9 binding relative to the transcription start site. We demonstrate that these directed changes in gene-transcription levels occur with minimal off-target effects. Our findings highlight the use of dCas9-mediated transcriptional regulation as a versatile tool to reproducibly interrogate tumor phenotypes in vivo.

Bisulfite oligonucleotide-capture sequencing for targeted base- and strand-specific absolute 5-methylcytosine quantitation

Epigenetic regulation through DNA methylation (5mC) plays an important role in development, aging, and a variety of diseases. Genome-wide studies of base- and strand-specific 5mC are limited by the extensive sequencing required. Targeting bisulfite sequencing to specific genomic regions through sequence capture with complimentary oligonucleotide probes retains the advantages of bisulfite sequencing while focusing sequencing reads on regions of interest, enables analysis of more samples by decreasing the amount of sequence required per sample, and provides base- and strand-specific absolute quantitation of CG and non-CG methylation levels. As an example, an oligonucleotide capture set to interrogate 5mC levels in all rat RefSeq gene promoter regions (18,814) and CG islands, shores, and shelves (18,411) was generated. Validation using whole-genome methylation standards and biological samples demonstrates enrichment of the targeted regions and accurate base-specific quantitation of CG and non-CG methylation for both forward and reverse genomic strands. A total of 170 Mb of the rat genome is covered including 6.6 million CGs and over 67 million non-CG sites, while reducing the amount of sequencing required by ~85 % as compared to existing whole-genome sequencing methods. This oligonucleotide capture targeting approach and quantitative validation workflow can also be applied to any genome of interest.

"Reverse Genomics" Predicts Function of Human Conserved Noncoding Elements

Evolutionary changes in cis-regulatory elements are thought to play a key role in morphological and physiological diversity across animals. Many conserved noncoding elements (CNEs) function as cis-regulatory elements, controlling gene expression levels in different biological contexts. However, determining specific associations between CNEs and related phenotypes is a challenging task. Here, we present a computational "reverse genomics" approach that predicts the phenotypic functions of human CNEs. We identify thousands of human CNEs that were lost in at least two independent mammalian lineages (IL-CNEs), and match their evolutionary profiles against a diverse set of phenotypes recently annotated across multiple mammalian species. We identify 2,759 compelling associations between human CNEs and a diverse set of mammalian phenotypes. We discuss multiple CNEs, including a predicted ear element near BMP7, a pelvic CNE in FBN1, a brain morphology element in UBE4B, and an aquatic adaptation forelimb CNE near EGR2, and provide a full list of our predictions. As more genomes are sequenced and more traits are annotated across species, we expect our method to facilitate the interpretation of noncoding mutations in human disease and expedite the discovery of individual CNEs that play key roles in human evolution and development.

Pooled-matrix protein interaction screens using Barcode Fusion Genetics

High‐throughput binary protein interaction mapping is continuing to extend our understanding of cellular function and disease mechanisms. However, we remain one or two orders of magnitude away from a complete interaction map for humans and other major model organisms. Completion will require screening at substantially larger scales with many complementary assays, requiring further efficiency gains in proteome‐scale interaction mapping. Here, we report Barcode Fusion Genetics‐Yeast Two‐Hybrid (BFG‐Y2H), by which a full matrix of protein pairs can be screened in a single multiplexed strain pool. BFG‐Y2H uses Cre recombination to fuse DNA barcodes from distinct plasmids, generating chimeric protein‐pair barcodes that can be quantified via next‐generation sequencing. We applied BFG‐Y2H to four different matrices ranging in scale from ~25 K to 2.5 M protein pairs. The results show that BFG‐Y2H increases the efficiency of protein matrix screening, with quality that is on par with state‐of‐the‐art Y2H methods.

Widespread Expansion of Protein Interaction Capabilities by Alternative Splicing

While alternative splicing is known to diversify the functional characteristics of some genes, the extent to which protein isoforms globally contribute to functional complexity on a proteomic scale remains unknown. To address this systematically, we cloned full-length open reading frames of alternatively spliced transcripts for a large number of human genes and used protein-protein interaction profiling to functionally compare hundreds of protein isoform pairs. The majority of isoform pairs share less than 50% of their interactions. In the global context of interactome network maps, alternative isoforms tend to behave like distinct proteins rather than minor variants of each other. Interaction partners specific to alternative isoforms tend to be expressed in a highly tissue-specific manner and belong to distinct functional modules. Our strategy, applicable to other functional characteristics, reveals a widespread expansion of protein interaction capabilities through alternative splicing and suggests that many alternative "isoforms" are functionally divergent (i.e., "functional alloforms").