Lineage-specific selection and the evolution of virulence in the Candida clade.

Candida albicans is the most common cause of systemic fungal infections in humans and is considerably more virulent than its closest known relative, Candida dubliniensis. To investigate this difference, we constructed interspecies hybrids and quantified mRNA levels produced from each genome in the hybrid. This approach systematically identified expression differences in orthologous genes arising from cis-regulatory sequence changes that accumulated since the two species last shared a common ancestor, some 10 million y ago. We documented many orthologous gene-expression differences between the two species, and we pursued one striking observation: All 15 genes coding for the enzymes of glycolysis showed higher expression from the C. albicans genome than the C. dubliniensis genome in the interspecies hybrid. This pattern requires evolutionary changes to have occurred at each gene; the fact that they all act in the same direction strongly indicates lineage-specific natural selection as the underlying cause. To test whether these expression differences contribute to virulence, we created a C. dubliniensis strain in which all 15 glycolysis genes were produced at modestly elevated levels and found that this strain had significantly increased virulence in the standard mouse model of systemic infection. These results indicate that small expression differences across a deeply conserved set of metabolism enzymes can play a significant role in the evolution of virulence in fungal pathogens.

Oct4 is required ~E7.5 for proliferation in the primitive streak.

Oct4 is a widely recognized pluripotency factor as it maintains Embryonic Stem (ES) cells in a pluripotent state, and, in vivo, prevents the inner cell mass (ICM) in murine embryos from differentiating into trophectoderm. However, its function in somatic tissue after this developmental stage is not well characterized. Using a tamoxifen-inducible Cre recombinase and floxed alleles of Oct4, we investigated the effect of depleting Oct4 in mouse embryos between the pre-streak and headfold stages, ~E6.0-E8.0, when Oct4 is found in dynamic patterns throughout the embryonic compartment of the mouse egg cylinder. We found that depletion of Oct4 ~E7.5 resulted in a severe phenotype, comprised of craniorachischisis, random heart tube orientation, failed turning, defective somitogenesis and posterior truncation. Unlike in ES cells, depletion of the pluripotency factors Sox2 and Oct4 after E7.0 does not phenocopy, suggesting that ~E7.5 Oct4 is required within a network that is altered relative to the pluripotency network. Oct4 is not required in extraembryonic tissue for these processes, but is required to maintain cell viability in the embryo and normal proliferation within the primitive streak. Impaired expansion of the primitive streak occurs coincident with Oct4 depletion ∼E7.5 and precedes deficient convergent extension which contributes to several aspects of the phenotype.

A quantitative atlas of polyadenylation in five mammals.

We developed PolyA-seq, a strand-specific and quantitative method for high-throughput sequencing of 3' ends of polyadenylated transcripts, and used it to globally map polyadenylation (polyA) sites in 24 matched tissues in human, rhesus, dog, mouse, and rat. We show that PolyA-seq is as accurate as existing RNA sequencing (RNA-seq) approaches for digital gene expression (DGE), enabling simultaneous mapping of polyA sites and quantitative measurement of their usage. In human, we confirmed 158,533 known sites and discovered 280,857 novel sites (FDR < 2.5%). On average 10% of novel human sites were also detected in matched tissues in other species. Most novel sites represent uncharacterized alternative polyA events and extensions of known transcripts in human and mouse, but primarily delineate novel transcripts in the other three species. A total of 69.1% of known human genes that we detected have multiple polyA sites in their 3'UTRs, with 49.3% having three or more. We also detected polyadenylation of noncoding and antisense transcripts, including constitutive and tissue-specific primary microRNAs. The canonical polyA signal was strongly enriched and positionally conserved in all species. In general, usage of polyA sites is more similar within the same tissues across different species than within a species. These quantitative maps of polyA usage in evolutionarily and functionally related samples constitute a resource for understanding the regulatory mechanisms underlying alternative polyadenylation.

Critical evaluation of imprinted gene expression by RNA-Seq: a new perspective.

In contrast to existing estimates of approximately 200 murine imprinted genes, recent work based on transcriptome sequencing uncovered parent-of-origin allelic effects at more than 1,300 loci in the developing brain and two adult brain regions, including hundreds present in only males or females. Our independent replication of the embryonic brain stage, where the majority of novel imprinted genes were discovered and the majority of previously known imprinted genes confirmed, resulted in only 12.9% concordance among the novel imprinted loci. Further analysis and pyrosequencing-based validation revealed that the vast majority of the novel reported imprinted loci are false-positives explained by technical and biological variation of the experimental approach. We show that allele-specific expression (ASE) measured with RNA-Seq is not accurately modeled with statistical methods that assume random independent sampling and that systematic error must be accounted for to enable accurate identification of imprinted expression. Application of a robust approach that accounts for these effects revealed 50 candidate genes where allelic bias was predicted to be parent-of-origin-dependent. However, 11 independent validation attempts through a range of allelic expression biases confirmed only 6 of these novel cases. The results emphasize the importance of independent validation and suggest that the number of imprinted genes is much closer to the initial estimates.

Global analysis of the evolution and mechanism of echinocandin resistance in Candida glabrata.

The evolution of drug resistance has a profound impact on human health. Candida glabrata is a leading human fungal pathogen that can rapidly evolve resistance to echinocandins, which target cell wall biosynthesis and are front-line therapeutics for Candida infections. Here, we provide the first global analysis of mutations accompanying the evolution of fungal drug resistance in a human host utilizing a series of C. glabrata isolates that evolved echinocandin resistance in a patient treated with the echinocandin caspofungin for recurring bloodstream candidemia. Whole genome sequencing identified a mutation in the drug target, FKS2, accompanying a major resistance increase, and 8 additional non-synonymous mutations. The FKS2-T1987C mutation was sufficient for echinocandin resistance, and associated with a fitness cost that was mitigated with further evolution, observed in vitro and in a murine model of systemic candidemia. A CDC6-A511G(K171E) mutation acquired before FKS2-T1987C(S663P), conferred a small resistance increase. Elevated dosage of CDC55, which acquired a C463T(P155S) mutation after FKS2-T1987C(S663P), ameliorated fitness. To discover strategies to abrogate echinocandin resistance, we focused on the molecular chaperone Hsp90 and downstream effector calcineurin. Genetic or pharmacological compromise of Hsp90 or calcineurin function reduced basal tolerance and resistance. Hsp90 and calcineurin were required for caspofungin-dependent FKS2 induction, providing a mechanism governing echinocandin resistance. A mitochondrial respiration-defective petite mutant in the series revealed that the petite phenotype does not confer echinocandin resistance, but renders strains refractory to synergy between echinocandins and Hsp90 or calcineurin inhibitors. The kidneys of mice infected with the petite mutant were sterile, while those infected with the HSP90-repressible strain had reduced fungal burden. We provide the first global view of mutations accompanying the evolution of fungal drug resistance in a human host, implicate the premier compensatory mutation mitigating the cost of echinocandin resistance, and suggest a new mechanism of echinocandin resistance with broad therapeutic potential.

Systematic detection of polygenic cis-regulatory evolution.

The idea that most morphological adaptations can be attributed to changes in the cis-regulation of gene expression levels has been gaining increasing acceptance, despite the fact that only a handful of such cases have so far been demonstrated. Moreover, because each of these cases involves only one gene, we lack any understanding of how natural selection may act on cis-regulation across entire pathways or networks. Here we apply a genome-wide test for selection on cis-regulation to two subspecies of the mouse Mus musculus. We find evidence for lineage-specific selection at over 100 genes involved in diverse processes such as growth, locomotion, and memory. These gene sets implicate candidate genes that are supported by both quantitative trait loci and a validated causality-testing framework, and they predict a number of phenotypic differences, which we confirm in all four cases tested. Our results suggest that gene expression adaptation is widespread and that these adaptations can be highly polygenic, involving cis-regulatory changes at numerous functionally related genes. These coordinated adaptations may contribute to divergence in a wide range of morphological, physiological, and behavioral phenotypes.

Pharmacogenomic discovery of genetically targeted cancer therapies optimized against clinical outcomes.

Despite the clinical success of dozens of genetically targeted cancer therapies, the vast majority of patients with tumors caused by loss-of-function (LoF) mutations do not have access to these treatments. This is primarily due to the challenge of developing a drug that treats a disease caused by the absence of a protein target. The success of PARP inhibitors has solidified synthetic lethality (SL) as a means to overcome this obstacle. Recent mapping of SL networks using pooled CRISPR-Cas9 screens is a promising approach for expanding this concept to treating cancers driven by additional LoF drivers. In practice, however, translating signals from cell lines, where these screens are typically conducted, to patient outcomes remains a challenge. We developed a pharmacogenomic (PGx) approach called "Clinically Optimized Driver Associated-PGx" (CODA-PGX) that accurately predicts genetically targeted therapies with clinical-stage efficacy in specific LoF driver contexts. Using approved targeted therapies and cancer drugs with available real-world evidence and molecular data from hundreds of patients, we discovered and optimized the key screening principles predictive of efficacy and overall patient survival. In addition to establishing basic technical conventions, such as drug concentration and screening kinetics, we found that replicating the driver perturbation in the right context, as well as selecting patients where those drivers are genuine founder mutations, were key to accurate translation. We used CODA-PGX to screen a diverse collection of clinical stage drugs and report dozens of novel LoF genetically targeted opportunities; many validated in xenografts and by real-world evidence. Notable examples include treating STAG2-mutant tumors with Carboplatin, SMARCB1-mutant tumors with Oxaliplatin, and TP53BP1-mutant tumors with Etoposide or Bleomycin.

Global survey of escape from X inactivation by RNA-sequencing in mouse.

X inactivation equalizes the dosage of gene expression between the sexes, but some genes escape silencing and are thus expressed from both alleles in females. To survey X inactivation and escape in mouse, we performed RNA sequencing in Mus musculus x Mus spretus cells with complete skewing of X inactivation, relying on expression of single nucleotide polymorphisms to discriminate allelic origin. Thirteen of 393 (3.3%) mouse genes had significant expression from the inactive X, including eight novel escape genes. We estimate that mice have significantly fewer escape genes compared with humans. Furthermore, escape genes did not cluster in mouse, unlike the large escape domains in human, suggesting that expression is controlled at the level of individual genes. Our findings are consistent with the striking differences in phenotypes between female mice and women with a single X chromosome--a near normal phenotype in mice versus Turner syndrome and multiple abnormalities in humans. We found that escape genes are marked by the absence of trimethylation at lysine 27 of histone H3, a chromatin modification associated with genes subject to X inactivation. Furthermore, this epigenetic mark is developmentally regulated for some mouse genes.

SMAUG is a major regulator of maternal mRNA destabilization in Drosophila and its translation is activated by the PAN GU kinase.

In animals, egg activation triggers a cascade of posttranscriptional events that act on maternally synthesized RNAs. We show that, in Drosophila, the PAN GU (PNG) kinase sits near the top of this cascade, triggering translation of SMAUG (SMG), a multifunctional posttranscriptional regulator conserved from yeast to humans. Although PNG is required for cytoplasmic polyadenylation of smg mRNA, it regulates translation via mechanisms that are independent of its effects on the poly(A) tail. Analyses of mutants suggest that PNG relieves translational repression by PUMILIO (PUM) and one or more additional factors, which act in parallel through the smg mRNA's 3' untranslated region (UTR). Microarray-based gene expression profiling shows that SMG is a major regulator of maternal transcript destabilization. SMG-dependent mRNAs are enriched for gene ontology annotations for function in the cell cycle, suggesting a possible causal relationship between failure to eliminate these transcripts and the cell cycle defects in smg mutants.

Digital transcriptome profiling using selective hexamer priming for cDNA synthesis.

We developed a procedure for the preparation of whole transcriptome cDNA libraries depleted of ribosomal RNA from only 1 microg of total RNA. The method relies on a collection of short, computationally selected oligonucleotides, called 'not-so-random' (NSR) primers, to obtain full-length, strand-specific representation of nonribosomal RNA transcripts. In this study we validated the technique by profiling human whole brain and universal human reference RNA using ultra-high-throughput sequencing.

Global survey of genomic imprinting by transcriptome sequencing.

Genomic imprinting restricts gene expression to a paternal or maternal allele. To date, approximately 90 imprinted transcripts have been identified in mouse, of which the majority were detected after intense interrogation of clusters of imprinted genes identified by phenotype-driven assays in mice with uniparental disomies [1]. Here we use selective priming and parallel sequencing to measure allelic bias in whole transcriptomes. By distinguishing parent-of-origin bias from strain-specific bias in embryos derived from a reciprocal cross of mice, we constructed a genome-wide map of imprinted transcription. This map was able to objectively locate over 80% of known imprinted loci and allowed the detection and confirmation of six novel imprinted genes. Even in the intensely studied embryonic day 9.5 developmental stage that we analyzed, more than half of all imprinted single-nucleotide polymorphisms did not overlap previously discovered imprinted transcripts; a large fraction of these represent novel noncoding RNAs within known imprinted loci. For example, a previously unnoticed, maternally expressed antisense transcript was mapped within the Grb10 locus. This study demonstrates the feasibility of using transcriptome sequencing for mapping of imprinted gene expression in physiologically normal animals. Such an approach will allow researchers to study imprinting without restricting themselves to individual loci or specific transcripts.

A systematic characterization of Cwc21, the yeast ortholog of the human spliceosomal protein SRm300.

Cwc21 (complexed with Cef1 protein 21) is a 135 amino acid yeast protein that shares homology with the N-terminal domain of human SRm300/SRRM2, a large serine/arginine-repeat protein shown previously to associate with the splicing coactivator and 3'-end processing stimulatory factor, SRm160. Proteomic analysis of spliceosomal complexes has suggested a role for Cwc21 and SRm300 at the core of the spliceosome. However, specific functions for these proteins have remained elusive. In this report, we employ quantitative genetic interaction mapping, mass spectrometry of tandem affinity-purified complexes, and microarray profiling to investigate genetic, physical, and functional interactions involving Cwc21. Combined data from these assays support multiple roles for Cwc21 in the formation and function of splicing complexes. Consistent with a role for Cwc21 at the core of the spliceosome, we observe strong genetic, physical, and functional interactions with Isy1, a protein previously implicated in the first catalytic step of splicing and splicing fidelity. Together, the results suggest multiple functions for Cwc21/SRm300 in the splicing process, including an important role in the activation of splicing in association with Isy1.

Identifying tumorigenic non-coding mutations through altered cis-regulation.

Identification of non-coding mutations driving tumorigenesis requires alternative approaches to coding mutations. Enriched associations between mutated regulatory elements and altered cis-regulation in tumors are a promising approach to stratify candidate non-coding driver mutations. Here we provide a bioinformatics pipeline to mine data from the Cancer Genomic Commons (GDC) for such associations. The pipeline integrates RNA and whole-genome sequencing with genotyping data to reveal putative non-coding driver mutations by cancer type. For complete information on the generation and use of this protocol, please refer to Cheng et al. (2021).

Cis-regulatory mutations with driver hallmarks in major cancers.

Despite the recent availability of complete genome sequences of tumors from thousands of patients, isolating disease-causing (driver) non-coding mutations from the plethora of somatic variants remains challenging, and only a handful of validated examples exist. By integrating whole-genome sequencing, genetic data, and allele-specific gene expression from TCGA, we identified 320 somatic non-coding mutations that affect gene expression in cis (FDR<0.25). These mutations cluster into 47 cis-regulatory elements that modulate expression of their subject genes through diverse molecular mechanisms. We further show that these mutations have hallmark features of non-coding drivers; namely, that they preferentially disrupt transcription factor binding motifs, are associated with a selective advantage, increased oncogene expression and decreased tumor suppressor expression.

Genetic validation of whole-transcriptome sequencing for mapping expression affected by cis-regulatory variation.

BACKGROUND: Identifying associations between genotypes and gene expression levels using microarrays has enabled systematic interrogation of regulatory variation underlying complex phenotypes. This approach has vast potential for functional characterization of disease states, but its prohibitive cost, given hundreds to thousands of individual samples from populations have to be genotyped and expression profiled, has limited its widespread application. RESULTS: Here we demonstrate that genomic regions with allele-specific expression (ASE) detected by sequencing cDNA are highly enriched for cis-acting expression quantitative trait loci (cis-eQTL) identified by profiling of 500 animals in parallel, with up to 90% agreement on the allele that is preferentially expressed. We also observed widespread noncoding and antisense ASE and identified several allele-specific alternative splicing variants. CONCLUSION: Monitoring ASE by sequencing cDNA from as little as one sample is a practical alternative to expression genetics for mapping cis-acting variation that regulates RNA transcription and processing.

Using expression profiling data to identify human microRNA targets.

We demonstrate that paired expression profiles of microRNAs (miRNAs) and mRNAs can be used to identify functional miRNA-target relationships with high precision. We used a Bayesian data analysis algorithm, GenMiR++, to identify a network of 1,597 high-confidence target predictions for 104 human miRNAs, which was supported by RNA expression data across 88 tissues and cell types, sequence complementarity and comparative genomics data. We experimentally verified our predictions by investigating the result of let-7b downregulation in retinoblastoma using quantitative reverse transcriptase (RT)-PCR and microarray profiling: some of our verified let-7b targets include CDC25A and BCL7A. Compared to sequence-based predictions, our high-scoring GenMiR++ predictions had much more consistent Gene Ontology annotations and were more accurate predictors of which mRNA levels respond to changes in let-7b levels.

Prediction and verification of mouse tRNA gene families.

BACKGROUND: Transfer RNA (tRNA) gene predictions are complicated by challenges such as structural variation, limited sequence conservation and the presence of highly reiterated short interspersed sequences (SINEs) that originally derived from tRNA genes or tRNA-like transcription units. Annotation of "tRNA genes" in sequenced genomes generally have not been accompanied by experimental verification of the expression status of predicted sequences. RESULTS: To address this for mouse tRNA genes, we have employed two programs, tRNAScan-SE and ARAGORN, to predict the tRNA genes in the nuclear genome, resulting in diverse but overlapping predicted gene sets. From these, we removed known SINE repeats and sorted the genes into predicted families and single-copy genes. In particular, four families of intron-containing tRNA genes were predicted for the first time in mouse, with introns in positions and structures similar to the well characterized intron-containing tRNA genes in yeast. We verified the expression of the predicted tRNA genes by microarray analysis. We then confirmed the expression of appropriately sized RNA for the four intron-containing tRNA gene families, as well as the other 30 tRNA gene families creating an index of expression-verified mouse tRNAs. CONCLUSIONS: These confirmed tRNA genes represent all anticodons and all known mammalian tRNA structural groups, as well as a variety of predicted "rogue" tRNA genes within families with altered anticodon identities.

A one-step tRNA-CRISPR system for genome-wide genetic interaction mapping in mammalian cells.

Mapping genetic interactions in mammalian cells is limited due to technical obstacles. Here we describe a method called TCGI (tRNA-CRISPR for genetic interactions) to generate a high-efficient, barcode-free and scalable pairwise CRISPR libraries in mammalian cells for identifying genetic interactions. We have generated a genome- wide library to identify genes genetically interacting with TAZ in cell viability regulation. Validation of candidate synergistic genes reveals the screening accuracy of 85% and TAZ-MCL1 is characterized as combinational drug targets for non-small cell lung cancer treatments. TCGI has dramatically improved the current methods for mapping genetic interactions and screening drug targets for combinational therapies.

Considerations in the identification of functional RNA structural elements in genomic alignments.

BACKGROUND: Accurate identification of novel, functional noncoding (nc) RNA features in genome sequence has proven more difficult than for exons. Current algorithms identify and score potential RNA secondary structures on the basis of thermodynamic stability, conservation, and/or covariance in sequence alignments. Neither the algorithms nor the information gained from the individual inputs have been independently assessed. Furthermore, due to issues in modelling background signal, it has been difficult to gauge the precision of these algorithms on a genomic scale, in which even a seemingly small false-positive rate can result in a vast excess of false discoveries. RESULTS: We developed a shuffling algorithm, shuffle-pair.pl, that simultaneously preserves dinucleotide frequency, gaps, and local conservation in pairwise sequence alignments. We used shuffle-pair.pl to assess precision and recall of six ncRNA search tools (MSARI, QRNA, ddbRNA, RNAz, Evofold, and several variants of simple thermodynamic stability on a test set of 3046 alignments of known ncRNAs. Relative to mononucleotide shuffling, preservation of dinucleotide content in shuffling the alignments resulted in a drastic increase in estimated false-positive detection rates for ncRNA elements, precluding evaluation of higher order alignments, which cannot not be adequately shuffled maintaining both dinucleotides and alignment structure. On pairwise alignments, none of the covariance-based tools performed markedly better than thermodynamic scoring alone. Although the high false-positive rates call into question the veracity of any individual predicted secondary structural element in our analysis, we nevertheless identified intriguing global trends in human genome alignments. The distribution of ncRNA prediction scores in 75-base windows overlapping UTRs, introns, and intergenic regions analyzed using both thermodynamic stability and EvoFold (which has no thermodynamic component) was significantly higher for real than shuffled sequence, while the distribution for coding sequences was lower than that of corresponding shuffles. CONCLUSION: Accurate prediction of novel RNA structural elements in genome sequence remains a difficult problem, and development of an appropriate negative-control strategy for multiple alignments is an important practical challenge. Nonetheless, the general trends we observed for the distributions of predicted ncRNAs across genomic features are biologically meaningful, supporting the presence of secondary structural elements in many 3' UTRs, and providing evidence for evolutionary selection against secondary structures in coding regions.

Global analysis of yeast RNA processing identifies new targets of RNase III and uncovers a link between tRNA 5' end processing and tRNA splicing.

We used a microarray containing probes that tile all known yeast noncoding RNAs (ncRNAs) to investigate RNA biogenesis on a global scale. The microarray verified a general loss of Box C/D snoRNAs in the TetO7-BCD1 mutant, which had previously been shown for only a handful of snoRNAs. We also monitored the accumulation of improperly processed flank sequences of pre-RNAs in strains depleted for known RNA nucleases, including RNase III, Dbr1p, Xrn1p, Rat1p and components of the exosome and RNase P complexes. Among the hundreds of aberrant RNA processing events detected, two novel substrates of Rnt1p (the RUF1 and RUF3 snoRNAs) were identified. We also identified a relationship between tRNA 5' end processing and tRNA splicing, processes that were previously thought to be independent. This analysis demonstrates the applicability of microarray technology to the study of global analysis of ncRNA synthesis and provides an extensive directory of processing events mediated by yeast ncRNA processing enzymes.