Paralog dependency indirectly affects the robustness of human cells

Frequent loss of FAM126A expression in colorectal cancer results in selective FAM126B dependency

Most advanced colorectal cancer (CRC) patients cannot benefit from targeted therapy due to lack of actionable targets. By mining data from the DepMap, we identified FAM126B as a specific vulnerability in CRC cell lines exhibiting low FAM126A expression. Employing a combination of genetic perturbation and inducible protein degradation techniques, we demonstrate that FAM126A and FAM126B function in a redundant manner to facilitate the recruitment of PI4KIIIα to the plasma membrane for PI4P synthesis. Examination of data from TCGA and GTEx revealed that over 7% of CRC tumor samples exhibited loss of FAM126A expression, contrasting with uniform FAM126A expression in normal tissues. In both CRC cell lines and tumor samples, promoter hypermethylation correlated with the loss of FAM126A expression, which could be reversed by DNA methylation inhibitors. In conclusion, our study reveals that loss of FAM126A expression results in FAM126B dependency, thus proposing FAM126B as a therapeutic target for CRC treatment.

Mutational biases favor complexity increases in protein interaction networks after gene duplication

Biological systems can gain complexity over time. While some of these transitions are likely driven by natural selection, the extent to which they occur without providing an adaptive benefit is unknown. At the molecular level, one example is heteromeric complexes replacing homomeric ones following gene duplication. Here, we build a biophysical model and simulate the evolution of homodimers and heterodimers following gene duplication using distributions of mutational effects inferred from available protein structures. We keep the specific activity of each dimer identical, so their concentrations drift neutrally without new functions. We show that for more than 60% of tested dimer structures, the relative concentration of the heteromer increases over time due to mutational biases that favor the heterodimer. However, allowing mutational effects on synthesis rates and differences in the specific activity of homo- and heterodimers can limit or reverse the observed bias toward heterodimers. Our results show that the accumulation of more complex protein quaternary structures is likely under neutral evolution, and that natural selection would be needed to reverse this tendency.

A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization

Genetic screens in cancer cell lines inform gene function and drug discovery. More comprehensive screen datasets with multi-omics data are needed to enhance opportunities to functionally map genetic vulnerabilities. Here, we construct a second-generation map of cancer dependencies by annotating 930 cancer cell lines with multi-omic data and analyze relationships between molecular markers and cancer dependencies derived from CRISPR-Cas9 screens. We identify dependency-associated gene expression markers beyond driver genes, and observe many gene addiction relationships driven by gain of function rather than synthetic lethal effects. By combining clinically informed dependency-marker associations with protein-protein interaction networks, we identify 370 anti-cancer priority targets for 27 cancer types, many of which have network-based evidence of a functional link with a marker in a cancer type. Mapping these targets to sequenced tumor cohorts identifies tractable targets in different cancer types. This target prioritization map enhances understanding of gene dependencies and identifies candidate anti-cancer targets for drug development.

LTP2 hypomorphs show genotype-by-environment interaction in early seedling traits in Arabidopsis thaliana

Isogenic individuals can display seemingly stochastic phenotypic differences, limiting the accuracy of genotype-to-phenotype predictions. The extent of this phenotypic variation depends in part on genetic background, raising questions about the genes involved in controlling stochastic phenotypic variation. Focusing on early seedling traits in Arabidopsis thaliana, we found that hypomorphs of the cuticle-related gene LIPID TRANSFER PROTEIN 2 (LTP2) greatly increased variation in seedling phenotypes, including hypocotyl length, gravitropism and cuticle permeability. Many ltp2 hypocotyls were significantly shorter than wild-type hypocotyls while others resembled the wild-type. Differences in epidermal properties and gene expression between ltp2 seedlings with long and short hypocotyls suggest a loss of cuticle integrity as the primary determinant of the observed phenotypic variation. We identified environmental conditions that reveal or mask the increased variation in ltp2 hypomorphs and found that increased expression of its closest paralog LTP1 is necessary for ltp2 phenotypes. Our results illustrate how decreased expression of a single gene can generate starkly increased phenotypic variation in isogenic individuals in response to an environmental challenge.

Paralog dispensability shapes homozygous deletion patterns in tumor genomes

Genomic instability is a hallmark of cancer, resulting in tumor genomes having large numbers of genetic aberrations, including homozygous deletions of protein coding genes. That tumor cells remain viable in the presence of such gene loss suggests high robustness to genetic perturbation. In model organisms and cancer cell lines, paralogs have been shown to contribute substantially to genetic robustness-they are generally more dispensable for growth than singletons. Here, by analyzing copy number profiles of > 10,000 tumors, we test the hypothesis that the increased dispensability of paralogs shapes tumor genome evolution. We find that genes with paralogs are more likely to be homozygously deleted and that this cannot be explained by other factors known to influence copy number variation. Furthermore, features that influence paralog dispensability in cancer cell lines correlate with paralog deletion frequency in tumors. Finally, paralogs that are broadly essential in cancer cell lines are less frequently deleted in tumors than non-essential paralogs. Overall, our results suggest that homozygous deletions of paralogs are more frequently observed in tumor genomes because paralogs are more dispensable.

Single-cell imaging of protein dynamics of paralogs reveals mechanisms of gene retention

Gene duplication is common across the tree of life, including yeast and humans, and contributes to genomic robustness. In this study, we examined changes in the subcellular localization and abundance of proteins in response to the deletion of their paralogs originating from the whole-genome duplication event, which is a largely unexplored mechanism of functional divergence. We performed a systematic single-cell imaging analysis of protein dynamics and screened subcellular redistribution of proteins, capturing their localization and abundance changes, providing insight into forces determining paralog retention. Paralogs showed dependency, whereby proteins required their paralog to maintain their native abundance or localization, more often than compensation. Network feature analysis suggested the importance of functional redundancy and rewiring of protein and genetic interactions underlying redistribution response of paralogs. Translation of non-canonical protein isoform emerged as a novel compensatory mechanism. This study provides new insights into paralog retention and evolutionary forces that shape genomes.

LTP2 hypomorphs show genotype-by-environment interaction in early seedling traits in Arabidopsis thaliana

Isogenic individuals can display seemingly stochastic phenotypic differences, limiting the accuracy of genotype-to-phenotype predictions. The extent of this phenotypic variation depends in part on genetic background, raising questions about the genes involved in controlling stochastic phenotypic variation. Focusing on early seedling traits in Arabidopsis thaliana, we found that hypomorphs of the cuticle-related gene LTP2 greatly increased variation in seedling phenotypes, including hypocotyl length, gravitropism and cuticle permeability. Many ltp2 hypocotyls were significantly shorter than wild-type hypocotyls while others resembled the wild type. Differences in epidermal properties and gene expression between ltp2 seedlings with long and short hypocotyls suggest a loss of cuticle integrity as the primary determinant of the observed phenotypic variation. We identified environmental conditions that reveal or mask the increased variation in ltp2 hypomorphs, and found that increased expression of its closest paralog LTP1 is necessary for ltp2 phenotypes. Our results illustrate how decreased expression of a single gene can generate starkly increased phenotypic variation in isogenic individuals in response to an environmental challenge.

Proteins with amino acid repeats constitute a rapidly evolvable and human-specific essentialome

Protein products of essential genes, indispensable for organismal survival, are highly conserved and bring about fundamental functions. Interestingly, proteins that contain amino acid homorepeats that tend to evolve rapidly are enriched in eukaryotic essentialomes. Why are proteins with hypermutable homorepeats enriched in conserved and functionally vital essential proteins? We solve this functional versus evolutionary paradox by demonstrating that human essential proteins with homorepeats bring about crosstalk across biological processes through high interactability and have distinct regulatory functions affecting expansive global regulation. Importantly, essential proteins with homorepeats rapidly diverge with the amino acid substitutions frequently affecting functional sites, likely facilitating rapid adaptability. Strikingly, essential proteins with homorepeats influence human-specific embryonic and brain development, implying that the presence of homorepeats could contribute to the emergence of human-specific processes. Thus, we propose that homorepeat-containing essential proteins affecting species-specific traits can be potential intervention targets across pathologies, including cancers and neurological disorders.

Paralog-based synthetic lethality: rationales and applications

Tumor cells can result from gene mutations and over-expression. Synthetic lethality (SL) offers a desirable setting where cancer cells bearing one mutated gene of an SL gene pair can be specifically targeted by disrupting the function of the other genes, while leaving wide-type normal cells unharmed. Paralogs, a set of homologous genes that have diverged from each other as a consequence of gene duplication, make the concept of SL feasible as the loss of one gene does not affect the cell's survival. Furthermore, homozygous loss of paralogs in tumor cells is more frequent than singletons, making them ideal SL targets. Although high-throughput CRISPR-Cas9 screenings have uncovered numerous paralog-based SL pairs, the unclear mechanisms of targeting these gene pairs and the difficulty in finding specific inhibitors that exclusively target a single but not both paralogs hinder further clinical development. Here, we review the potential mechanisms of paralog-based SL given their function and genetic combination, and discuss the challenge and application prospects of paralog-based SL in cancer therapeutic discovery.

Promoter evolution of mammalian gene duplicates

BACKGROUND

Gene duplication is thought to be a central process in evolution to gain new functions. The factors that dictate gene retention following duplication as well paralog gene divergence in sequence, expression and function have been extensively studied. However, relatively little is known about the evolution of promoter regions of gene duplicates and how they influence gene duplicate divergence. Here, we focus on promoters of paralog genes, comparing their similarity in sequence, in the sets of transcription factors (TFs) that bind them, and in their overall promoter architecture.

RESULTS

We observe that promoters of recent duplications display higher sequence similarity between them and that sequence similarity rapidly declines between promoters of more ancient paralogs. In contrast, similarity in cis-regulation, as measured by the set of TFs that bind promoters of both paralogs, does not simply decrease with time from duplication and is instead related to promoter architecture-paralogs with CpG Islands (CGIs) in their promoters share a greater fraction of TFs, while CGI-less paralogs are more divergent in their TF binding set. Focusing on recent duplication events and partitioning them by their duplication mechanism enables us to uncover promoter properties associated with gene retention, as well as to characterize the evolution of promoters of newly born genes: In recent retrotransposition-mediated duplications, we observe asymmetry in cis-regulation of paralog pairs: Retrocopy genes are lowly expressed and their promoters are bound by fewer TFs and are depleted of CGIs, in comparison with the original gene copy. Furthermore, looking at recent segmental duplication regions in primates enable us to compare successful retentions versus loss of duplicates, showing that duplicate retention is associated with fewer TFs and with CGI-less promoter architecture.

CONCLUSIONS

In this work, we profiled promoters of gene duplicates and their inter-paralog divergence. We also studied how their characteristics are associated with duplication time and duplication mechanism, as well as with the fate of these duplicates. These results underline the importance of cis-regulatory mechanisms in shaping the evolution of new genes and their fate following duplication.

Alternative splicing mediates the compensatory upregulation of MBNL2 upon MBNL1 loss-of-function

Loss of gene function can be compensated by paralogs with redundant functions. An example of such compensation are the paralogs of the Muscleblind-Like (MBNL) family of RNA-binding proteins that are sequestered and lose their function in Myotonic Dystrophy Type 1 (DM1). Loss of MBNL1 increases the levels of its paralog MBNL2 in tissues where Mbnl2 expression is low, allowing MBNL2 to functionally compensate for MBNL1 loss. Here, we show that loss of MBNL1 increases the inclusion of Mbnl2 exon 6 and exon 9. We find that inclusion of Mbnl2 exon 6 increases the translocation of MBNL2 to the nucleus, while the inclusion of Mbnl2 exon 9 shifts the reading frame to an alternative C-terminus. We show that the C-terminus lacking exon 9 contains a PEST domain which causes proteasomal degradation. Loss of MBNL1 increases the inclusion of exon 9, resulting in an alternative C-terminus lacking the PEST domain and the increase of MBNL2. We further find that the compensatory mechanism is active in a mouse DM1 model. Together, this study uncovers the compensatory mechanism by which loss of MBNL1 upregulates its paralog MBNL2 and highlights a potential role of the compensatory mechanism in DM1.

Paralog Explorer: A resource for mining information about paralogs in common research organisms

Paralogs are genes which arose via gene duplication, and when such paralogs retain overlapping or redundant function, this poses a challenge to functional genetics research. Recent technological advancements have made it possible to systematically probe gene function for redundant genes using dual or multiplex gene perturbation, and there is a need for a simple bioinformatic tool to identify putative paralogs of a gene(s) of interest. We have developed Paralog Explorer (https://www.flyrnai.org/tools/paralogs/), an online resource that allows researchers to quickly and accurately identify candidate paralogous genes in the genomes of the model organisms D. melanogaster, C. elegans, D. rerio, M. musculus, and H. sapiens. Paralog Explorer deploys an effective between-species ortholog prediction software, DIOPT, to analyze within-species paralogs. Paralog Explorer allows users to identify candidate paralogs, and to navigate relevant databases regarding gene co-expression, protein-protein and genetic interaction, as well as gene ontology and phenotype annotations. Altogether, this tool extends the value of current ortholog prediction resources by providing sophisticated features useful for identification and study of paralogous genes.

Mendelian gene identification through mouse embryo viability screening

BACKGROUND

The diagnostic rate of Mendelian disorders in sequencing studies continues to increase, along with the pace of novel disease gene discovery. However, variant interpretation in novel genes not currently associated with disease is particularly challenging and strategies combining gene functional evidence with approaches that evaluate the phenotypic similarities between patients and model organisms have proven successful. A full spectrum of intolerance to loss-of-function variation has been previously described, providing evidence that gene essentiality should not be considered as a simple and fixed binary property.

METHODS

Here we further dissected this spectrum by assessing the embryonic stage at which homozygous loss-of-function results in lethality in mice from the International Mouse Phenotyping Consortium, classifying the set of lethal genes into one of three windows of lethality: early, mid, or late gestation lethal. We studied the correlation between these windows of lethality and various gene features including expression across development, paralogy and constraint metrics together with human disease phenotypes. We explored a gene similarity approach for novel gene discovery and investigated unsolved cases from the 100,000 Genomes Project.

RESULTS

We found that genes in the early gestation lethal category have distinct characteristics and are enriched for genes linked with recessive forms of inherited metabolic disease. We identified several genes sharing multiple features with known biallelic forms of inborn errors of the metabolism and found signs of enrichment of biallelic predicted pathogenic variants among early gestation lethal genes in patients recruited under this disease category. We highlight two novel gene candidates with phenotypic overlap between the patients and the mouse knockouts.

CONCLUSIONS

Information on the developmental period at which embryonic lethality occurs in the knockout mouse may be used for novel disease gene discovery that helps to prioritise variants in unsolved rare disease cases.

How gene duplication diversifies the landscape of protein oligomeric state and function

Oligomeric proteins are central to cellular life and the duplication and divergence of their genes is a key driver of evolutionary innovations. The duplication of a gene coding for an oligomeric protein has numerous possible outcomes, which motivates questions on the relationship between structural and functional divergence. How do protein oligomeric states diversify after gene duplication? In the simple case of duplication of a homo-oligomeric protein gene, what properties can influence the fate of descendant paralogs toward forming independent homomers or maintaining their interaction as a complex? Furthermore, how are functional innovations associated with the diversification of oligomeric states? Here, we review recent literature and present specific examples in an attempt to illustrate and answer these questions.

Pan-cancer proteomic map of 949 human cell lines

The proteome provides unique insights into disease biology beyond the genome and transcriptome. A lack of large proteomic datasets has restricted the identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types are analyzed by mass spectrometry. Deploying a workflow to quantify 8,498 proteins, these data capture evidence of cell-type and post-transcriptional modifications. Integrating multi-omics, drug response, and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline reveals thousands of protein biomarkers of cancer vulnerabilities that are not significant at the transcript level. The power of the proteome to predict drug response is very similar to that of the transcriptome. Further, random downsampling to only 1,500 proteins has limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger) is a comprehensive resource available at https://cellmodelpassports.sanger.ac.uk.

Extended disordered regions of ribosome-associated NAC proteins paralogs belong only to the germline in Drosophila melanogaster

The nascent polypeptide-associated complex (NAC) consisting of α- and β-subunits is an essential ribosome-associated protein conserved in eukaryotes. NAC is a ubiquitously expressed co-translational regulator of nascent protein folding and sorting providing for homeostasis of cellular proteins. Here we report on discovering the germline-specific NACαβ paralogs (gNACs), whose β-subunits, non-distinguishable by ordinary immunodetection, are encoded by five highly homologous gene copies, while the α-subunit is encoded by a single αNAC gene. The gNAC expression is detected in the primordial embryonic and adult gonads via immunostaining. The germline-specific α and β subunits differ from the ubiquitously expressed paralogs by the extended intrinsically disordered regions (IDRs) acquired at the N- and C-termini of the coding regions, predicted to be phosphorylated. The presence of distinct phosphorylated isoforms of gNAC-β subunits is confirmed by comparing of their profiles by 2D-isoeletrofocusing resolution before and after phosphatase treatment of testis ribosomes. We revealed that the predicted S/T sites of phosphorylation in the individual orthologous IDRs of gNAC-β sequences of Drosophila species are positionally conserved despite these disordered regions are drastically different. We propose the IDR-dependent molecular crowding and specific coordination of NAC and other proteostasis regulatory factors at the ribosomes of germinal cells. Our findings imply that there may be a functional crosstalk between the germinal and ubiquitous α- and β-subunits based on assessing their depletion effects on the fly viability and gonad development.

Investigating the effects of compound paralogous EPHB receptor mutations on mouse facial development

BACKGROUND

Variation in facial shape may arise from the combinatorial or overlapping actions of paralogous genes. Given its many members, and overlapping expression and functions, the EPH receptor family is a compelling candidate source of craniofacial morphological variation. We performed a detailed morphometric analysis of an allelic series of E14.5 Ephb1-3 receptor mutants to determine the effect of each paralogous receptor gene on craniofacial morphology.

RESULTS

We found that Ephb1, Ephb2, and Ephb3 genotypes significantly influenced facial shape, but Ephb1 effects were weaker than Ephb2 and Ephb3 effects. Ephb2^-/- and Ephb3^-/- mutations affected similar aspects of facial morphology, but Ephb3^-/- mutants had additional facial shape effects. Craniofacial differences across the allelic series were largely consistent with predicted additive genetic effects. However, we identified a potentially important nonadditive effect where Ephb1 mutants displayed different morphologies depending on the combination of other Ephb paralogs present, where Ephb1^+/- , Ephb1^-/- , and Ephb1^-/- ; Ephb3^-/- mutants exhibited a consistent deviation from their predicted facial shapes.

CONCLUSIONS

This study provides a detailed assessment of the effects of Ephb receptor gene paralogs on E14.5 mouse facial morphology and demonstrates how the loss of specific receptors contributes to facial dysmorphology.

Interrogation of cancer gene dependencies reveals paralog interactions of autosome and sex chromosome-encoded genes

Genetic networks are characterized by extensive buffering. During tumor evolution, disruption of functional redundancies can create de novo vulnerabilities that are specific to cancer cells. Here, we systematically search for cancer-relevant paralog interactions using CRISPR screens and publicly available loss-of-function datasets. Our analysis reveals >2,000 candidate dependencies, several of which we validate experimentally, including CSTF2-CSTF2T, DNAJC15-DNAJC19, FAM50A-FAM50B, and RPP25-RPP25L. We provide evidence that RPP25L can physically and functionally compensate for the absence of RPP25 as a member of the RNase P/MRP complexes in tRNA processing. Our analysis also reveals unexpected redundancies between sex chromosome genes. We show that chrX- and chrY-encoded paralogs, such as ZFX-ZFY, DDX3X-DDX3Y, and EIF1AX-EIF1AY, are functionally linked. Tumor cell lines from male patients with loss of chromosome Y become dependent on the chrX-encoded gene. We propose targeting of chrX-encoded paralogs as a general therapeutic strategy for human tumors that have lost the Y chromosome.

Conserved exchange of paralog proteins during neuronal differentiation

Paralog proteins promote fine tuning of protein complexes. The author identified a specific paralog signature conserved across vertebrate neuronal differentiation. Altering the ratio of SEC23 paralogs in the COPII complex influences neuronal differentiation in a opposite way.

Gene duplication enables the emergence of new functions by lowering the evolutionary pressure that is posed on the ancestral genes. Previous studies have highlighted the role of specific paralog genes during cell differentiation, for example, in chromatin remodeling complexes. It remains unexplored whether similar mechanisms extend to other biological functions and whether the regulation of paralog genes is conserved across species. Here, we analyze the expression of paralogs across human tissues, during development and neuronal differentiation in fish, rodents and humans. Whereas ∼80% of paralog genes are co-regulated, a subset of paralogs shows divergent expression profiles, contributing to variability of protein complexes. We identify 78 substitutions of paralog pairs that occur during neuronal differentiation and are conserved across species. Among these, we highlight a substitution between the paralogs SEC23A and SEC23B members of the COPII complex. Altering the ratio between these two genes via RNAi-mediated knockdown is sufficient to influence neuron differentiation. We propose that remodeling of the vesicular transport system via paralog substitutions is an evolutionary conserved mechanism enabling neuronal differentiation.

Functional buffering via cell-specific gene expression promotes tissue homeostasis and cancer robustness

Functional buffering that ensures biological robustness is critical for maintaining tissue homeostasis, organismal survival, and evolution of novelty. However, the mechanism underlying functional buffering, particularly in multicellular organisms, remains largely elusive. Here, we proposed that functional buffering can be mediated via expression of buffering genes in specific cells and tissues, by which we named Cell-specific Expression-BUffering (CEBU). We developed an inference index (C-score) for CEBU by computing C-scores across 684 human cell lines using genome-wide CRISPR screens and transcriptomic RNA-seq. We report that C-score-identified putative buffering gene pairs are enriched for members of the same duplicated gene family, pathway, and protein complex. Furthermore, CEBU is especially prevalent in tissues of low regenerative capacity (e.g., bone and neuronal tissues) and is weakest in highly regenerative blood cells, linking functional buffering to tissue regeneration. Clinically, the buffering capacity enabled by CEBU can help predict patient survival for multiple cancers. Our results suggest CEBU as a potential buffering mechanism contributing to tissue homeostasis and cancer robustness in humans.

Retention of duplicated genes in evolution

Gene duplication is a prevalent phenomenon across the tree of life. The processes that lead to the retention of duplicated genes are not well understood. Functional genomics approaches in model organisms, such as yeast, provide useful tools to test the mechanisms underlying retention with functional redundancy and divergence of duplicated genes, including fates associated with neofunctionalization, subfunctionalization, back-up compensation, and dosage amplification. Duplicated genes may also be retained as a consequence of structural and functional entanglement. Advances in human gene editing have enabled the interrogation of duplicated genes in the human genome, providing new tools to evaluate the relative contributions of each of these factors to duplicate gene retention and the evolution of genome structure.

Identification of discriminative gene-level and protein-level features associated with pathogenic gain-of-function and loss-of-function variants

Identifying whether a given genetic mutation results in a gene product with increased (gain-of-function; GOF) or diminished (loss-of-function; LOF) activity is an important step toward understanding disease mechanisms because they may result in markedly different clinical phenotypes. Here, we generated an extensive database of documented germline GOF and LOF pathogenic variants by employing natural language processing (NLP) on the available abstracts in the Human Gene Mutation Database. We then investigated various gene- and protein-level features of GOF and LOF variants and applied machine learning and statistical analyses to identify discriminative features. We found that GOF variants were enriched in essential genes, for autosomal-dominant inheritance, and in protein binding and interaction domains, whereas LOF variants were enriched in singleton genes, for protein-truncating variants, and in protein core regions. We developed a user-friendly web-based interface that enables the extraction of selected subsets from the GOF/LOF database by a broad set of annotated features and downloading of up-to-date versions. These results improve our understanding of how variants affect gene/protein function and may ultimately guide future treatment options.

Comprehensive prediction of robust synthetic lethality between paralog pairs in cancer cell lines

Pairs of paralogs may share common functionality and, hence, display synthetic lethal interactions. As the majority of human genes have an identifiable paralog, exploiting synthetic lethality between paralogs may be a broadly applicable approach for targeting gene loss in cancer. However, only a biased subset of human paralog pairs has been tested for synthetic lethality to date. Here, by analyzing genome-wide CRISPR screens and molecular profiles of over 700 cancer cell lines, we identify features predictive of synthetic lethality between paralogs, including shared protein-protein interactions and evolutionary conservation. We develop a machine-learning classifier based on these features to predict which paralog pairs are most likely to be synthetic lethal and to explain why. We show that our classifier accurately predicts the results of combinatorial CRISPR screens in cancer cell lines and furthermore can distinguish pairs that are synthetic lethal in multiple cell lines from those that are cell-line specific. A record of this paper's transparent peer review process is included in the supplemental information.

Discovery of synthetic lethal and tumor suppressor paralog pairs in the human genome

CRISPR screens have accelerated the discovery of important cancer vulnerabilities. However, single-gene knockout phenotypes can be masked by redundancy among related genes. Paralogs constitute two-thirds of the human protein-coding genome, so existing methods are likely inadequate for assaying a large portion of gene function. Here, we develop paired guide RNAs for paralog genetic interaction mapping (pgPEN), a pooled CRISPR-Cas9 single- and double-knockout approach targeting more than 2,000 human paralogs. We apply pgPEN to two cell types and discover that 12% of human paralogs exhibit synthetic lethality in at least one context. We recover known synthetic lethal paralogs MEK1/MEK2, important drug targets CDK4/CDK6, and other synthetic lethal pairs including CCNL1/CCNL2. Additionally, we identify ten tumor suppressor paralog pairs whose compound loss promotes cell proliferation. These findings nominate drug targets and suggest that paralog genetic interactions could shape the landscape of positive and negative selection in cancer.

SynLeGG: analysis and visualization of multiomics data for discovery of cancer 'Achilles Heels' and gene function relationships

Achilles’ heel relationships arise when the status of one gene exposes a cell's vulnerability to perturbation of a second gene, such as chemical inhibition, providing therapeutic opportunities for precision oncology. SynLeGG (www.overton-lab.uk/synlegg) identifies and visualizes mutually exclusive loss signatures in ‘omics data to enable discovery of genetic dependency relationships (GDRs) across 783 cancer cell lines and 30 tissues. While there is significant focus on genetic approaches, transcriptome data has advantages for investigation of GDRs and remains relatively underexplored. SynLeGG depends upon the MultiSEp algorithm for unsupervised assignment of cell lines into gene expression clusters, which provide the basis for analysis of CRISPR scores and mutational status in order to propose candidate GDRs. Benchmarking against SynLethDB demonstrates favourable performance for MultiSEp against competing approaches, finding significantly higher area under the Receiver Operator Characteristic curve and between 2.8-fold to 8.5-fold greater coverage. In addition to pan-cancer analysis, SynLeGG offers investigation of tissue-specific GDRs and recovers established relationships, including synthetic lethality for SMARCA2 with SMARCA4. Proteomics, Gene Ontology, protein-protein interactions and paralogue information are provided to assist interpretation and candidate drug target prioritization. SynLeGG predictions are significantly enriched in dependencies validated by a recently published CRISPR screen.

Genome-wide CRISPRi/a screens in human neurons link lysosomal failure to ferroptosis

Single-cell transcriptomics provide a systematic map of gene expression in different human cell types. The next challenge is to systematically understand cell-type-specific gene function. The integration of CRISPR-based functional genomics and stem cell technology enables the scalable interrogation of gene function in differentiated human cells. Here we present the first genome-wide CRISPR interference and CRISPR activation screens in human neurons. We uncover pathways controlling neuronal response to chronic oxidative stress, which is implicated in neurodegenerative diseases. Unexpectedly, knockdown of the lysosomal protein prosaposin strongly sensitizes neurons, but not other cell types, to oxidative stress by triggering the formation of lipofuscin, a hallmark of aging, which traps iron, generating reactive oxygen species and triggering ferroptosis. We also determine transcriptomic changes in neurons after perturbation of genes linked to neurodegenerative diseases. To enable the systematic comparison of gene function across different human cell types, we establish a data commons named CRISPRbrain.

Yeast cell fate control by temporal redundancy modulation of transcription factor paralogs

Recent single-cell studies have revealed that yeast stress response involves transcription factors that are activated in pulses. However, it remains unclear whether and how these dynamic transcription factors temporally interact to regulate stress survival. Here we show that budding yeast cells can exploit the temporal relationship between paralogous general stress regulators, Msn2 and Msn4, during stress response. We find that individual pulses of Msn2 and Msn4 are largely redundant, and cells can enhance the expression of their shared targets by increasing their temporal divergence. Thus, functional redundancy between these two paralogs is modulated in a dynamic manner to confer fitness advantages for yeast cells, which might feed back to promote the preservation of their redundancy. This evolutionary implication is supported by evidence from Msn2/Msn4 orthologs and analyses of other transcription factor paralogs. Together, we show a cell fate control mechanism through temporal redundancy modulation in yeast, which may represent an evolutionarily important strategy for maintaining functional redundancy between gene duplicates.

Dosage-sensitive molecular mechanisms are associated with the tissue-specificity of traits and diseases

Hereditary diseases and complex traits often manifest in specific tissues, whereas their causal genes are expressed in many tissues that remain unaffected. Among the mechanisms that have been suggested for this enigmatic phenomenon is dosage-sensitive compensation by paralogs of causal genes. Accordingly, tissue-selectivity stems from dosage imbalance between causal genes and paralogs that occurs particularly in disease-susceptible tissues. Here, we used a large-scale dataset of thousands of tissue transcriptomes and applied a linear mixed model (LMM) framework to assess this and other dosage-sensitive mechanisms. LMM analysis of 382 hereditary diseases consistently showed evidence for dosage-sensitive compensation by paralogs across diseases subsets and susceptible tissues. LMM analysis of 135 candidate genes that are strongly associated with 16 tissue-selective complex traits revealed a similar tendency among half of the trait-associated genes. This suggests that dosage-sensitive compensation by paralogs affects the tissue-selectivity of complex traits, and can be used to illuminate candidate genes' modes of action. Next, we applied LMM to analyze dosage imbalance between causal genes and three classes of genetic modifiers, including regulatory micro-RNAs, pseudogenes, and genetic interactors. Our results propose modifiers as a fundamental axis in tissue-selectivity of diseases and traits, and demonstrates the power of LMM as a statistical framework for discovering treatment avenues.

Genome-scale molecular principles of mRNA half-life regulation in yeast

Precise control of protein and messenger RNA (mRNA) degradation is essential for cellular metabolism and homeostasis. Controlled and specific degradation of both molecular species necessitates their engagements with the respective degradation machineries; this engagement involves a disordered/unstructured segment of the substrate traversing the degradation tunnel of the machinery and accessing the catalytic sites. However, while molecular factors influencing protein degradation have been extensively explored on a genome scale, and in multiple organisms, such a comprehensive understanding remains missing for mRNAs. Here, we analyzed multiple genome-scale experimental yeast mRNA half-life data in light of experimentally derived mRNA secondary structures and protein binding data, along with high-resolution X-ray crystallographic structures of the RNase machines. Results unraveled a consistent genome-scale trend that mRNAs comprising longer terminal and/or internal unstructured segments have significantly shorter half-lives; the lengths of the 5'-terminal, 3'-terminal, and internal unstructured segments that affect mRNA half-life are compatible with molecular structures of the 5' exo-, 3' exo-, and endoribonuclease machineries. Sequestration into ribonucleoprotein complexes elongates mRNA half-life, presumably by burying ribonuclease engagement sites under oligomeric interfaces. After gene duplication, differences in terminal unstructured lengths, proportions of internal unstructured segments, and oligomerization modes result in significantly altered half-lives of paralogous mRNAs. Side-by-side comparison of molecular principles underlying controlled protein and mRNA degradation in yeast unravels their remarkable mechanistic similarities and suggests how the intrinsic structural features of the two molecular species, at two different levels of the central dogma, regulate their half-lives on genome scale.

Multiplex enCas12a screens detect functional buffering among paralogs otherwise masked in monogenic Cas9 knockout screens

BACKGROUND

Pooled library CRISPR/Cas9 knockout screening across hundreds of cell lines has identified genes whose disruption leads to fitness defects, a critical step in identifying candidate cancer targets. However, the number of essential genes detected from these monogenic knockout screens is low compared to the number of constitutively expressed genes in a cell.

RESULTS

Through a systematic analysis of screen data in cancer cell lines generated by the Cancer Dependency Map, we observe that half of all constitutively expressed genes are never detected in any CRISPR screen and that these never-essentials are highly enriched for paralogs. We investigated functional buffering among approximately 400 candidate paralog pairs using CRISPR/enCas12a dual-gene knockout screening in three cell lines. We observe 24 synthetic lethal paralog pairs that have escaped detection by monogenic knockout screens at stringent thresholds. Nineteen of 24 (79%) synthetic lethal interactions are present in at least two out of three cell lines and 14 of 24 (58%) are present in all three cell lines tested, including alternate subunits of stable protein complexes as well as functionally redundant enzymes.

CONCLUSIONS

Together, these observations strongly suggest that functionally redundant paralogs represent a targetable set of genetic dependencies that are systematically under-represented among cell-essential genes in monogenic CRISPR-based loss of function screens.

A Division of Labor between YAP and TAZ in Non-Small Cell Lung Cancer

Lung cancer is the leading cause of cancer-related deaths worldwide. The paralogous transcriptional cofactors Yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ, also called WWTR1), the main downstream effectors of the Hippo signal transduction pathway, are emerging as pivotal determinants of malignancy in lung cancer. Traditionally, studies have tended to consider YAP and TAZ as functionally redundant transcriptional cofactors with similar biological impact. However, there is growing evidence that each of them also possesses distinct attributes. Here we sought to systematically characterize the division of labor between YAP and TAZ in non-small cell lung cancer (NSCLC), the most common histological subtype of lung cancer. Representative NSCLC cell lines as well as patient-derived data showed that the two paralogs orchestrated nonoverlapping transcriptional programs in this cancer type. YAP preferentially regulated gene sets associated with cell division and cell-cycle progression, whereas TAZ preferentially regulated genes associated with extracellular matrix organization. Depletion of YAP resulted in growth arrest, whereas its overexpression promoted cell proliferation. Likewise, depletion of TAZ compromised cell migration, whereas its overexpression enhanced migration. The differential effects of YAP and TAZ on key cellular processes were also associated with differential response to anticancer therapies. Uncovering the different activities and downstream effects of YAP and TAZ may thus facilitate better stratification of patients with lung cancer for anticancer therapies. SIGNIFICANCE: Thease findings show that oncogenic paralogs YAP and TAZ have distinct roles in NSCLC and are associated with differential response to anticancer drugs, knowledge that may assist lung cancer therapy decisions.

Functional Genomics for Cancer Drug Target Discovery

Functional genomics describes a field of biology that uses a range of approaches for assessing gene function with high-throughput molecular, genetic, and cellular technologies. The near limitless potential for applying these concepts to study the activities of all genetic loci has completely upended how today's cancer biologists tackle drug target discovery. We provide an overview of contemporary functional genomics platforms, highlighting areas of distinction and complementarity across technologies, so as to aid in the development or interpretation of cancer-focused screening efforts.