Andrew A. Hardigan

aRNApipe: a balanced, efficient and distributed pipeline for processing RNA-seq data in high-performance computing environments

Summary: The wide range of RNA‐seq applications and their high‐computational needs require the development of pipelines orchestrating the entire workflow and optimizing usage of available computational resources. We present aRNApipe, a project‐oriented pipeline for processing of RNA‐seq data in high‐performance cluster environments. aRNApipe is highly modular and can be easily migrated to any high‐performance computing (HPC) environment. The current applications included in aRNApipe combine the essential RNA‐seq primary analyses, including quality control metrics, transcript alignment, count generation, transcript fusion identification, alternative splicing and sequence variant calling. aRNApipe is project‐oriented and dynamic so users can easily update analyses to include or exclude samples or enable additional processing modules. Workflow parameters are easily set using a single configuration file that provides centralized tracking of all analytical processes. Finally, aRNApipe incorporates interactive web reports for sample tracking and a tool for managing the genome assemblies available to perform an analysis. Availability and documentation: https://github.com/HudsonAlpha/aRNAPipe; DOI: 10.5281/zenodo.202950 Contact: rmyers@hudsonalpha.org Supplementary information: Supplementary data are available at Bioinformatics online.

RNA sequencing-based cell proliferation analysis across 19 cancers identifies a subset of proliferation-informative cancers with a common survival signature

Despite advances in cancer diagnosis and treatment strategies, robust prognostic signatures remain elusive in most cancers. Cell proliferation has long been recognized as a prognostic marker in cancer, but the generation of comprehensive, publicly available datasets allows examination of the links between cell proliferation and cancer characteristics such as mutation rate, stage, and patient outcomes. Here we explore the role of cell proliferation across 19 cancers (n = 6,581 patients) by using tissue-based RNA sequencing data from The Cancer Genome Atlas Project and calculating a ‘proliferative index’ derived from gene expression associated with Proliferating Cell Nuclear Antigen (PCNA) levels. This proliferative index is significantly associated with patient survival (Cox, p-value < 0.05) in 7 of 19 cancers, which we have defined as “proliferation-informative cancers” (PICs). In PICs, the proliferative index is strongly correlated with tumor stage and nodal invasion. PICs demonstrate reduced baseline expression of proliferation machinery relative to non-PICs. Additionally, we find the proliferative index is significantly associated with gross somatic mutation burden (Spearman, p = 1.76 × 10−23) as well as with mutations in individual driver genes. This analysis provides a comprehensive characterization of tumor proliferation indices and their association with disease progression and prognosis in multiple cancer types and highlights specific cancers that may be particularly susceptible to improved targeting of this classic cancer hallmark.

Decoding transcriptional enhancers: Evolving from annotation to functional interpretation.

Deciphering the intricate molecular processes that orchestrate the spatial and temporal regulation of genes has become an increasingly major focus of biological research. The differential expression of genes by diverse cell types with a common genome is a hallmark of complex cellular functions, as well as the basis for multicellular life. Importantly, a more coherent understanding of gene regulation is critical for defining developmental processes, evolutionary principles and disease etiologies. Here we present our current understanding of gene regulation by focusing on the role of enhancer elements in these complex processes. Although functional genomic methods have provided considerable advances to our understanding of gene regulation, these assays, which are usually performed on a genome-wide scale, typically provide correlative observations that lack functional interpretation. Recent innovations in genome editing technologies have placed gene regulatory studies at an exciting crossroads, as systematic, functional evaluation of enhancers and other transcriptional regulatory elements can now be performed in a coordinated, high-throughput manner across the entire genome. This review provides insights on transcriptional enhancer function, their role in development and disease, and catalogues experimental tools commonly used to study these elements. Additionally, we discuss the crucial role of novel techniques in deciphering the complex gene regulatory landscape and how these studies will shape future research.

Blocking of targeted microRNAs from next-generation sequencing libraries

Highly abundant microRNAs (miRNAs) in small RNA sequencing libraries make it difficult to obtain efficient measurements of more lowly expressed species. We present a new method that allows for the selective blocking of specific, abundant miRNAs during preparation of sequencing libraries. This technique is specific with little off-target effects and has no impact on the reproducibility of the measurement of non-targeted species. In human plasma samples, we demonstrate that blocking of highly abundant hsa-miR-16–5p leads to improved detection of lowly expressed miRNAs and more precise measurement of differential expression overall. Furthermore, we establish the ability to target a second abundant miRNA and to multiplex the blocking of two miRNAs simultaneously. For small RNA sequencing, this technique could fill a similar role as do ribosomal or globin removal technologies in messenger RNA sequencing.

Mutations in EBF3 disturb transcriptional profiles and underlie a novel syndrome of intellectual disability, ataxia and facial dysmorphism

From a GeneMatcher-enabled international collaboration, we identified ten individuals with intellectual disability, speech delay, ataxia and facial dysmorphism and a mutation in EBF3, encoding a transcription factor required for neuronal differentiation. Structural assessments, transactivation assays, in situ fractionation, RNA-seq and ChlP-seq experiments collectively show that the mutations are deleterious and impair EBF3 transcriptional regulation. These findings demonstrate that EBF3-mediated dysregulation of gene expression has profound effects on neuronal development in humans.

Post-mortem molecular profiling of three psychiatric disorders reveals widespread dysregulation of cell-type associated transcripts and refined disease-related transcription changes

Background Psychiatric disorders are multigenic diseases with complex etiology contributing significantly to human morbidity and mortality. Although clinically distinct, several disorders share many symptoms suggesting common underlying molecular changes exist that may implicate important regulators of pathogenesis and new therapeutic targets. Results We compared molecular signatures across brain regions and disorders in the transcriptomes of postmortem human brain samples. We performed RNA sequencing on tissue from the anterior cingulate cortex, dorsolateral prefrontal cortex, and nucleus accumbens from three groups of 24 patients each diagnosed with schizophrenia, bipolar disorder, or major depressive disorder, and from 24 control subjects, and validated the results in an independent cohort. The most significant disease differences were in the anterior cingulate cortex of schizophrenia samples compared to controls. Transcriptional changes were assessed in an independent cohort, revealing the transcription factor EGR1 as significantly down regulated in both cohorts and as a potential regulator of broader transcription changes observed in schizophrenia patients. Additionally, broad down regulation of genes specific to neurons and concordant up regulation of genes specific to astrocytes was observed in SZ and BPD patients relative to controls. We also assessed the biochemical consequences of gene expression changes with untargeted metabolomic profiling and identified disruption of GABA levels in schizophrenia patients. Conclusions We provide a comprehensive post-mortem transcriptome profile of three psychiatric disorders across three brain regions. We highlight a high-confidence set of independently validated genes differentially expressed between schizophrenia and control patients in the anterior cingulate cortex and integrate transcriptional changes with untargeted metabolite profiling.

De novo mutations in the GTP/GDP-binding region of RALA, a RAS-like small GTPase, cause intellectual disability and developmental delay

Mutations that alter signaling of RAS/MAPK-family proteins give rise to a group of Mendelian diseases known as RASopathies, but the matrix of genotype-phenotype relationships is still incomplete, in part because there are many RAS-related proteins, and in part because the phenotypic consequences may be variable and/or pleiotropic. Here, we describe a cohort of ten cases, drawn from six clinical sites and over 16,000 sequenced probands, with de novo protein-altering variation in RALA, a RAS-like small GTPase. All probands present with speech and motor delays, and most have intellectual disability, low weight, short stature, and facial dysmorphism. The observed rate of de novo RALA variants in affected probands is significantly higher (p=4.93 × 10−11) than expected from the estimated mutation rate. Further, all de novo variants described here affect conserved residues within the GTP/GDP-binding region of RALA; in fact, six alleles arose at only two codons, Val25 and Lys128. We directly assayed GTP hydrolysis and RALA effector-protein binding, and all but one tested variant significantly reduced both activities. The one exception, S157A, reduced GTP hydrolysis but significantly increased RALA-effector binding, an observation similar to that seen for oncogenic RAS variants. These results show the power of data sharing for the interpretation and analysis of rare variation, expand the spectrum of molecular causes of developmental disability to include RALA, and provide additional insight into the pathogenesis of human disease caused by mutations in small GTPases. Author Summary While many causes of developmental disabilities have been identified, a large number of affected children cannot be diagnosed despite extensive medical testing. Previously unknown genetic factors are likely to be the culprits in many of these cases. Using DNA sequencing, and by sharing information among many doctors and researchers, we have identified a set of individuals with developmental problems who all have changes to the same gene, RALA. The affected individuals all have similar symptoms, including intellectual disability, speech delay (or no speech), and problems with motor skills like walking. In nearly all of these cases (10 of 11), the genetic change found in the child was not inherited from either parent. The locations and biological properties of these changes suggest that they are likely to disrupt the normal functions of RALA and cause significant health problems. We also performed experiments to show that the genetic changes found in these individuals alter two key functions of RALA. Together, we have provided evidence that genetic changes in RALA can cause DD/ID. These results will allow doctors and researchers to identify additional children with the same condition, providing a clinical diagnosis to these families and leading to new research opportunities.

CRISPR/Cas9-targeted removal of unwanted sequences from small-RNA sequencing libraries

In small RNA (smRNAs) sequencing studies, highly abundant molecules such as adapter dimer products and tissue-specific microRNAs (miRNAs) inhibit accurate quantification of lowly expressed species. We previously developed a method to selectively deplete highly abundant miRNAs. However, this method does not deplete adapter dimer ligation products that, unless removed by gelseparation, comprise most of the library. Here, we have adapted and modified recently described methods for CRISPR/Cas9–based Depletion of Abundant Species by Hybridization (“DASH”) to smRNA-seq, which we have termed miRNA and Adapter Dimer - DASH (MAD-DASH). In MAD-DASH, Cas9 is complexed with sgRNAs targeting adapter dimer ligation products, alongside highly expressed tissue-specific smRNAs, for cleavage in vitro. This process dramatically reduces (>90%) adapter dimer and targeted smRNA sequences, is multiplexable, shows minimal off-target effects, improves the quantification of lowly expressed miRNAs from human plasma and tissue derived RNA, and obviates the need for gel-separation, greatly increasing sample throughput. Additionally, the method is fully customizable to other smRNA-seq preparation methods. Like depletion of ribosomal RNA for mRNA-seq and mitochondrial DNA for ATAC-seq, our method allows for greater proportional read-depth of nontargeted sequences.

Discovery and Validation of Circulating Biomarkers of Colorectal Adenoma by High-Depth Small RNA Sequencing

Purpose: Colorectal cancer is the third most common cancer worldwide, causing approximately 700,000 deaths each year. The majority of colorectal cancers begin as adenomas. Definitive screening for colorectal adenomas is currently accomplished through colonoscopy but, owing largely to costs and invasiveness, is typically limited to patient groups at higher risk by virtue of age or family history. We sought to determine if blood-based small RNA markers could detect colorectal adenoma. Experimental Design: We applied high-depth small RNA sequencing to plasma from a large (n = 189) cohort of patients, balanced for age, sex, and ancestry. Our analytical methodology allowed for the detection of both microRNAs and other small RNA species. We replicated sequencing results by qPCR on plasma samples from an independent cohort (n = 140). Results: We found several small RNA species with significant associations to colorectal adenoma, including both microRNAs and non-microRNA small RNAs. These associations were robust to correction for patient covariates, including age. Among the adenoma-associated small RNAs, two, a miR-335-5p isoform and an un-annotated small RNA, were validated by qPCR in an independent cohort. A classifier trained on measures of these two RNAs in the discovery cohort yields an AUC of 0.755 (0.775 with age) for adenoma detection in the independent cohort. This classifier accurately detects adenomas in patients under 50 and is robust to sex or ancestry. Conclusions: Circulating small RNAs (including but not limited to miRNAs) discovered by sequencing and validated by qPCR identify patients with colorectal adenomas effectively. Clin Cancer Res; 24(9); 2092–9. ©2018 AACR.

A genome-wide interactome of DNA-associated proteins in the human liver

Large-scale efforts like the ENCODE Project have made tremendous progress in cataloging the genomic binding patterns of DNA-associated proteins (DAPs), such as transcription factors (TFs). However, most chromatin immunoprecipitation-sequencing (ChIP-seq) analyses have focused on a few immortalized cell lines whose activities and physiology differ in important ways from endogenous cells and tissues. Consequently, binding data from primary human tissue are essential to improving our understanding of in vivo gene regulation. Here, we identify and analyze more than 440,000 binding sites using ChIP-seq data for 20 DAPs in two human liver tissue samples. We integrated binding data with transcriptome and phased WGS data to investigate allelic DAP interactions and the impact of heterozygous sequence variation on the expression of neighboring genes. Our tissue-based data set exhibits binding patterns more consistent with liver biology than cell lines, and we describe uses of these data to better prioritize impactful noncoding variation. Collectively, our rich data set offers novel insights into genome function in human liver tissue and provides a valuable resource for assessing disease-related disruptions.