Polygenic Risk in Families With Spontaneous Coronary Artery Dissection.

Importance: Spontaneous coronary artery dissection (SCAD) is a poorly understood cause of acute coronary syndrome that predominantly affects women. Evidence to date suggests a complex genetic architecture, while a family history is reported for a minority of cases. Objective: To determine the contribution of rare and common genetic variants to SCAD risk in familial cases, the latter via the comparison of a polygenic risk score (PRS) with those with sporadic SCAD and healthy controls. Design, Setting, and Participants: This genetic association study analyzed families with SCAD, individuals with sporadic SCAD, and healthy controls. Genotyping was undertaken for all participants. Participants were recruited between 2017 and 2021. A PRS for SCAD was calculated for all participants. The presence of rare variants in genes associated with connective tissue disorders (CTD) was also assessed. Individuals with SCAD were recruited via social media or from a single medical center. A previously published control database of older healthy individuals was used. Data were analyzed from January 2022 to October 2023. Exposures: PRS for SCAD comprised of 7 single-nucleotide variants. Main Outcomes and Measures: Disease status (familial SCAD, sporadic SCAD, or healthy control) associated with PRS. Results: A total of 13 families with SCAD (27 affected and 12 unaffected individuals), 173 individuals with sporadic SCAD, and 1127 healthy controls were included. A total of 188 individuals with SCAD (94.0%) were female, including 25 of 27 with familial SCAD and 163 of 173 with sporadic SCAD; of 12 unaffected individuals from families with SCAD, 6 (50%) were female; and of 1127 healthy controls, 672 (59.6%) were female. Compared with healthy controls, the odds of being an affected family member or having sporadic SCAD was significantly associated with a SCAD PRS (where the odds ratio [OR] represents an increase in odds per 1-SD increase in PRS) (affected family member: OR, 2.14; 95% CI, 1.78-2.50; adjusted P = 1.96 × 10-4; sporadic SCAD: OR, 1.63; 95% CI, 1.37-1.89; adjusted P = 5.69 × 10-4). This association was not seen for unaffected family members (OR, 1.03; 95% CI, 0.46-1.61; adjusted P = .91) compared with controls. Further, those with familial SCAD were overrepresented in the top quintile of the control PRS distribution (OR, 3.70; 95% CI, 2.93-4.47; adjusted P = .001); those with sporadic SCAD showed a similar pattern (OR, 2.51; 95% CI, 1.98-3.04; adjusted P = .001). Affected individuals within a family did not share any rare deleterious variants in CTD-associated genes. Conclusions and Relevance: Extreme aggregation of common genetic risk appears to play a significant role in familial clustering of SCAD as well as in sporadic case predisposition, although further study is required.

Whole-Brain Calcium Imaging in Drosophila during Sleep and Wake.

Genetically encoded calcium indicators (GECIs) allow for the noninvasive evaluation of neuronal activity in vivo, and imaging GECIs in Drosophila has become commonplace for understanding neural functions and connectivity in this system. GECIs can also be used as read-outs for studying sleep in this model organism. Here, we describe a methodology for tracking the activity of neurons in the fly brain using a two-photon (2p) microscopy system. This method can be adapted to perform functional studies of neural activity in Drosophila under both spontaneous and evoked conditions, as well as during spontaneous or induced sleep. We first describe a tethering and surgical procedure that allows survival under the microscopy conditions required for long-term recordings. We then outline the steps and reagents required for optogenetic activation of sleep-promoting neurons while simultaneously recording neural activity from the fly brain. We also describe the procedure for recording from two different locations-namely, the top of the head (e.g., to record mushroom body calyx activity) or the back of the head (e.g., to record central complex activity). We also provide different strategies for recording from GECIs confined to the cell body versus the entire neuron. Finally, we describe the steps required for analyzing the multidimensional data that can be acquired. In all, this protocol shows how to perform calcium imaging experiments in tethered flies, with a focus on acquiring spontaneous and induced sleep data.

Whole-Brain Electrophysiology and Calcium Imaging in Drosophila during Sleep and Wake.

Sleep is likely a whole-brain phenomenon, with most of the brain probably benefiting from this state of decreased arousal. Recent advances in our understanding of some potential sleep functions, such as metabolite clearance and synaptic homeostasis, make it evident why the whole brain is likely impacted by sleep: All neurons have synapses, and all neurons produce waste metabolites. Sleep experiments in the fly Drosophila melanogaster suggest that diverse sleep functions appear to be conserved across all animals. Studies of brain activity during sleep in humans typically involve multidimensional data sets, such as those acquired by electroencephalograms (EEGs) or functional magnetic resonance imaging (fMRI), and these whole-brain read-outs often reveal important qualities of different sleep stages, such as changes in frequency dynamics or connectivity. Recently, various techniques have been developed that allow for the recording of neural activity simultaneously across multiple regions of the fly brain. These whole-brain-recording approaches will be important for better understanding sleep physiology and function, as they provide a more comprehensive view of neural dynamics during sleep and wake in a relevant model system. Here, we present a brief summary of some of the findings derived from sleep activity recording studies in sleeping Drosophila flies and discuss the value of electrophysiological versus calcium imaging techniques. Although these involve very different preparations, they both highlight the value of multidimensional data for studying sleep in this model system, like the use of both EEG and fMRI in humans.

Neural Ensemble Fragmentation in the Anesthetized Drosophila Brain.

General anesthetics cause a profound loss of behavioral responsiveness in all animals. In mammals, general anesthesia is induced in part by the potentiation of endogenous sleep-promoting circuits, although "deep" anesthesia is understood to be more similar to coma (Brown et al., 2011). Surgically relevant concentrations of anesthetics, such as isoflurane and propofol, have been shown to impair neural connectivity across the mammalian brain (Mashour and Hudetz, 2017; Yang et al., 2021), which presents one explanation why animals become largely unresponsive when exposed to these drugs. It remains unclear whether general anesthetics affect brain dynamics similarly in all animal brains, or whether simpler animals, such as insects, even display levels of neural connectivity that could be disrupted by these drugs. Here, we used whole-brain calcium imaging in behaving female Drosophila flies to investigate whether isoflurane anesthesia induction activates sleep-promoting neurons, and then inquired how all other neurons across the fly brain behave under sustained anesthesia. We were able to track the activity of hundreds of neurons simultaneously during waking and anesthetized states, for spontaneous conditions as well as in response to visual and mechanical stimuli. We compared whole-brain dynamics and connectivity under isoflurane exposure to optogenetically induced sleep. Neurons in the Drosophila brain remain active during general anesthesia as well as induced sleep, although flies become behaviorally inert under both treatments. We identified surprisingly dynamic neural correlation patterns in the waking fly brain, suggesting ensemble-like behavior. These become more fragmented and less diverse under anesthesia but remain wake-like during induced sleep.SIGNIFICANCE STATEMENT When humans are rendered immobile and unresponsive by sleep or general anesthetics, their brains do not shut off - they just change how they operate. We tracked the activity of hundreds of neurons simultaneously in the brains of fruit flies that were anesthetized by isoflurane or genetically put to sleep, to investigate whether these behaviorally inert states shared similar brain dynamics. We uncovered dynamic patterns of neural activity in the waking fly brain, with stimulus-responsive neurons constantly changing through time. Wake-like neural dynamics persisted during induced sleep but became more fragmented under isoflurane anesthesia. This suggests that, like larger brains, the fly brain might also display ensemble-like behavior, which becomes degraded rather than silenced under general anesthesia.

Insights into the genetic architecture underlying complex, critical congenital heart disease.

Congenital heart disease (CHD) has a multifactorial aetiology, raising the possibility of an underlying genetic burden, predisposing to disease but also variable expression, including variation in disease severity, and incomplete penetrance. Using whole genome sequencing (WGS), the findings of this study, indicate that complex, critical CHD is distinct from other types of disease due to increased genetic burden in common variation, specifically among established CHD genes. Additionally, these findings highlight associations with regulatory genes and environmental "stressors" in the final presentation of disease.

Exploring the Genetic Architecture of Spontaneous Coronary Artery Dissection Using Whole-Genome Sequencing.

BACKGROUND: Spontaneous coronary artery dissection (SCAD) is a cause of acute coronary syndrome that predominantly affects women. Its pathophysiology remains unclear but connective tissue disorders (CTD) and other vasculopathies have been observed in many SCAD patients. A genetic component for SCAD is increasingly appreciated, although few genes have been robustly implicated. We sought to clarify the genetic cause of SCAD using targeted and genome-wide methods in a cohort of sporadic cases to identify both common and rare disease-associated variants. METHODS: A cohort of 91 unrelated sporadic SCAD cases was investigated for rare, deleterious variants in genes associated with either SCAD or CTD, while new candidate genes were sought using rare variant collapsing analysis and identification of novel loss-of-function variants in genes intolerant to such variation. Finally, 2 SCAD polygenic risk scores were applied to assess the contribution of common variants. RESULTS: We identified 10 cases with at least one rare, likely disease-causing variant in CTD-associated genes, although only one had a CTD phenotype. No genes were significantly associated with SCAD from genome-wide collapsing analysis, however, enrichment for TGF (transforming growth factor)-ß signaling pathway genes was found with analysis of 24 genes harboring novel loss-of-function variants. Both polygenic risk scores demonstrated that sporadic SCAD cases have a significantly elevated genetic SCAD risk compared with controls. CONCLUSIONS: SCAD shares some genetic overlap with CTD, even in the absence of any major CTD phenotype. Consistent with a complex genetic architecture, SCAD patients also have a higher burden of common variants than controls.

Benchmarking the Effectiveness and Accuracy of Multiple Mitochondrial DNA Variant Callers: Practical Implications for Clinical Application.

Mitochondrial DNA (mtDNA) mutations contribute to human disease across a range of severity, from rare, highly penetrant mutations causal for monogenic disorders to mutations with milder contributions to phenotypes. mtDNA variation can exist in all copies of mtDNA or in a percentage of mtDNA copies and can be detected with levels as low as 1%. The large number of copies of mtDNA and the possibility of multiple alternative alleles at the same DNA nucleotide position make the task of identifying allelic variation in mtDNA very challenging. In recent years, specialized variant calling algorithms have been developed that are tailored to identify mtDNA variation from whole-genome sequencing (WGS) data. However, very few studies have systematically evaluated and compared these methods for the detection of both homoplasmy and heteroplasmy. A publicly available synthetic gold standard dataset was used to assess four mtDNA variant callers (Mutserve, mitoCaller, MitoSeek, and MToolBox), and the commonly used Genome Analysis Toolkit "best practices" pipeline, which is included in most current WGS pipelines. We also used WGS data from 126 trios and calculated the percentage of maternally inherited variants as a metric of calling accuracy, especially for homoplasmic variants. We additionally compared multiple pathogenicity prediction resources for mtDNA variants. Although the accuracy of homoplasmic variant detection was high for the majority of the callers with high concordance across callers, we found a very low concordance rate between mtDNA variant callers for heteroplasmic variants ranging from 2.8% to 3.6%, for heteroplasmy thresholds of 5% and 1%. Overall, Mutserve showed the best performance using the synthetic benchmark dataset. The analysis of mtDNA pathogenicity resources also showed low concordance in prediction results. We have shown that while homoplasmic variant calling is consistent between callers, there remains a significant discrepancy in heteroplasmic variant calling. We found that resources like population frequency databases and pathogenicity predictors are now available for variant annotation but still need refinement and improvement. With its peculiarities, the mitochondria require special considerations, and we advocate that caution needs to be taken when analyzing mtDNA data from WGS data.

Whole genome sequencing in transposition of the great arteries and associations with clinically relevant heart, brain and laterality genes.

BACKGROUND: The most common cyanotic congenital heart disease (CHD) requiring management as a neonate is transposition of great arteries (TGA). Clinically, up to 50% of TGA patients develop some form of neurodevelopmental disability (NDD), thought to have a significant genetic component. A "ciliopathy" and links with laterality disorders have been proposed. This first report of whole genome sequencing in TGA, sought to identify clinically relevant variants contributing to heart, brain and laterality defects. METHODS: Initial whole genome sequencing analyses on 100 TGA patients focussed on established disease genes related to CHD (n = 107), NDD (n = 659) and heterotaxy (n = 74). Single variant as well as copy number variant analyses were conducted. Variant pathogenicity was assessed using the American College of Medical Genetics and Genomics-Association for Molecular Pathology guidelines. RESULTS: Fifty-five putatively damaging variants were identified in established disease genes associated with CHD, NDD and heterotaxy; however, no clinically relevant variants could be attributed to disease. Notably, case-control analyses identified significantly more predicted-damaging, silent and total variants in TGA cases than healthy controls in established CHD genes (P < .001), NDD genes (P < .001) as well as across the three gene panels (P < .001). CONCLUSION: We present compelling evidence that the majority of TGA is not caused by monogenic rare variants and is most likely oligogenic and/or polygenic in nature, highlighting the complex genetic architecture and multifactorial influences on this CHD sub-type and its long-term sequelae. Assessment of variant burden in key heart, brain and/or laterality genes may be required to unravel the genetic contributions to TGA and related disabilities.

Maternal iron deficiency perturbs embryonic cardiovascular development in mice.

Congenital heart disease (CHD) is the most common class of human birth defects, with a prevalence of 0.9% of births. However, two-thirds of cases have an unknown cause, and many of these are thought to be caused by in utero exposure to environmental teratogens. Here we identify a potential teratogen causing CHD in mice: maternal iron deficiency (ID). We show that maternal ID in mice causes severe cardiovascular defects in the offspring. These defects likely arise from increased retinoic acid signalling in ID embryos. The defects can be prevented by iron administration in early pregnancy. It has also been proposed that teratogen exposure may potentiate the effects of genetic predisposition to CHD through gene-environment interaction. Here we show that maternal ID increases the severity of heart and craniofacial defects in a mouse model of Down syndrome. It will be important to understand if the effects of maternal ID seen here in mice may have clinical implications for women.

Syntaxin1A Neomorphic Mutations Promote Rapid Recovery from Isoflurane Anesthesia in Drosophila melanogaster.

BACKGROUND: Mutations in the presynaptic protein syntaxin1A modulate general anesthetic effects in vitro and in vivo. Coexpression of a truncated syntaxin1A protein confers resistance to volatile and intravenous anesthetics, suggesting a target mechanism distinct from postsynaptic inhibitory receptor processes. Hypothesizing that recovery from anesthesia may involve a presynaptic component, the authors tested whether syntaxin1A mutations facilitated recovery from isoflurane anesthesia in Drosophila melanogaster. METHODS: A truncated syntaxin1A construct was expressed in Drosophila neurons. The authors compared effects on isoflurane induction versus recovery in syntaxin1A mutant animals by probing behavioral responses to mechanical stimuli. The authors also measured synaptic responses from the larval neuromuscular junction using sharp intracellular recordings, and performed Western blots to determine whether the truncated syntaxin1A is associated with presynaptic core complexes. RESULTS: Drosophila expressing a truncated syntaxin1A (syx, n = 40) were resistant to isoflurane induction for a behavioral responsiveness endpoint (ED50 0.30 ± 0.01% isoflurane, P < 0.001) compared with control (0.240 ± 0.002% isoflurane, n = 40). Recovery from isoflurane anesthesia was also faster, with syx-expressing flies showing greater levels of responsiveness earlier in recovery (reaction proportion 0.66 ± 0.48, P < 0.001, n = 68) than controls (0.22 ± 0.42, n = 68 and 0.33 ± 0.48, n = 66). Measuring excitatory junction potentials of larvae coexpressing the truncated syntaxin1A protein showed a greater recovery of synaptic function, compared with controls (17.39 ± 3.19 mV and 10.29 ± 4.88 mV, P = 0.014, n = 8 for both). The resistance-promoting truncated syntaxin1A was not associated with presynaptic core complexes, in the presence or absence of isoflurane anesthesia. CONCLUSIONS: The same neomorphic syntaxin1A mutation that confers isoflurane resistance in cell culture and nematodes also produces isoflurane resistance in Drosophila. Resistance in Drosophila is, however, most evident at the level of recovery from anesthesia, suggesting that the syntaxin1A target affects anesthesia maintenance and recovery processes rather than induction. The absence of truncated syntaxin1A from the presynaptic complex suggests that the resistance-promoting effect of this molecule occurs before core complex formation.

Spliceogen: an integrative, scalable tool for the discovery of splice-altering variants.

MOTIVATION: In silico prediction tools are essential for identifying variants which create or disrupt cis-splicing motifs. However, there are limited options for genome-scale discovery of splice-altering variants. RESULTS: We have developed Spliceogen, a highly scalable pipeline integrating predictions from some of the individually best performing models for splice motif prediction: MaxEntScan, GeneSplicer, ESRseq and Branchpointer. AVAILABILITY AND IMPLEMENTATION: Spliceogen is available as a command line tool which accepts VCF/BED inputs and handles both single nucleotide variants (SNVs) and indels (https://github.com/VCCRI/Spliceogen). SNV databases with prediction scores are also available, covering all possible SNVs at all genomic positions within all Gencode-annotated multi-exon transcripts. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Scavenger: A pipeline for recovery of unaligned reads utilising similarity with aligned reads.

Read alignment is an important step in RNA-seq analysis as the result of alignment forms the basis for downstream analyses. However, recent studies have shown that published alignment tools have variable mapping sensitivity and do not necessarily align all the reads which should have been aligned, a problem we termed as the false-negative non-alignment problem. Here we present Scavenger, a python-based bioinformatics pipeline for recovering unaligned reads using a novel mechanism in which a putative alignment location is discovered based on sequence similarity between aligned and unaligned reads. We showed that Scavenger could recover unaligned reads in a range of simulated and real RNA-seq datasets, including single-cell RNA-seq data. We found that recovered reads tend to contain more genetic variants with respect to the reference genome compared to previously aligned reads, indicating that divergence between personal and reference genomes plays a role in the false-negative non-alignment problem. Even when the number of recovered reads is relatively small compared to the total number of reads, the addition of these recovered reads can impact downstream analyses, especially in terms of estimating the expression and differential expression of lowly expressed genes, such as pseudogenes.

Identification of clinically actionable variants from genome sequencing of families with congenital heart disease.

PURPOSE: Congenital heart disease (CHD) affects up to 1% of live births. However, a genetic diagnosis is not made in most cases. The purpose of this study was to assess the outcomes of genome sequencing (GS) of a heterogeneous cohort of CHD patients. METHODS: Ninety-seven families with probands born with CHD requiring surgical correction were recruited for genome sequencing. At minimum, a proband-parents trio was sequenced per family. GS data were analyzed via a two-tiered method: application of a high-confidence gene screen (hcCHD), and comprehensive analysis. Identified variants were assessed for pathogenicity using the American College of Medical Genetics and Genomics-Association for Molecular Pathology (ACMG-AMP) guidelines. RESULTS: Clinically relevant genetic variants in known and emerging CHD genes were identified. The hcCHD screen identified a clinically actionable variant in 22% of families. Subsequent comprehensive analysis identified a clinically actionable variant in an additional 9% of families in genes with recent disease associations. Overall, this two-tiered approach provided a clinically relevant variant for 31% of families. CONCLUSIONS: Interrogating GS data using our two-tiered method allowed identification of variants with high clinical utility in a third of our heterogeneous cohort. However, association of emerging genes with CHD etiology, and development of novel technologies for variant assessment and interpretation, will increase diagnostic yield during future reassessment of our GS data.

Acute control of the sleep switch in Drosophila reveals a role for gap junctions in regulating behavioral responsiveness.

Sleep is a dynamic process in most animals, involving distinct stages that probably perform multiple functions for the brain. Before sleep functions can be initiated, it is likely that behavioral responsiveness to the outside world needs to be reduced, even while the animal is still awake. Recent work in Drosophila has uncovered a sleep switch in the dorsal fan-shaped body (dFB) of the fly's central brain, but it is not known whether these sleep-promoting neurons also govern the acute need to ignore salient stimuli in the environment during sleep transitions. We found that optogenetic activation of the sleep switch suppressed behavioral responsiveness to mechanical stimuli, even in awake flies, indicating a broader role for these neurons in regulating arousal. The dFB-mediated suppression mechanism and its associated neural correlates requires innexin6 expression, suggesting that the acute need to reduce sensory perception when flies fall asleep is mediated in part by electrical synapses.

Using Drosophila to Understand General Anesthesia: From Synapses to Behavior.

Investigating mechanisms of general anesthesia requires access to multiple levels of neuronal function, from effects at individual synapses to responses in behaving animals. Drosophila melanogaster provides an excellent model to test different theories for general anesthesia because it offers robust methods for testing local as well as global target processes, in an animal that is similarly impacted by these diverse drugs as humans. Here, we outline methods to quantify two such endpoints, neurotransmission and behavioral responsiveness, focusing on the intravenous drug propofol.

Oscillatory brain activity in spontaneous and induced sleep stages in flies.

Sleep is a dynamic process comprising multiple stages, each associated with distinct electrophysiological properties and potentially serving different functions. While these phenomena are well described in vertebrates, it is unclear if invertebrates have distinct sleep stages. We perform local field potential (LFP) recordings on flies spontaneously sleeping, and compare their brain activity to flies induced to sleep using either genetic activation of sleep-promoting circuitry or the GABAA agonist Gaboxadol. We find a transitional sleep stage associated with a 7-10 Hz oscillation in the central brain during spontaneous sleep. Oscillatory activity is also evident when we acutely activate sleep-promoting neurons in the dorsal fan-shaped body (dFB) of Drosophila. In contrast, sleep following Gaboxadol exposure is characterized by low-amplitude LFPs, during which dFB-induced effects are suppressed. Sleep in flies thus appears to involve at least two distinct stages: increased oscillatory activity, particularly during sleep induction, followed by desynchronized or decreased brain activity.

Scalability and Validation of Big Data Bioinformatics Software.

This review examines two important aspects that are central to modern big data bioinformatics analysis - software scalability and validity. We argue that not only are the issues of scalability and validation common to all big data bioinformatics analyses, they can be tackled by conceptually related methodological approaches, namely divide-and-conquer (scalability) and multiple executions (validation). Scalability is defined as the ability for a program to scale based on workload. It has always been an important consideration when developing bioinformatics algorithms and programs. Nonetheless the surge of volume and variety of biological and biomedical data has posed new challenges. We discuss how modern cloud computing and big data programming frameworks such as MapReduce and Spark are being used to effectively implement divide-and-conquer in a distributed computing environment. Validation of software is another important issue in big data bioinformatics that is often ignored. Software validation is the process of determining whether the program under test fulfils the task for which it was designed. Determining the correctness of the computational output of big data bioinformatics software is especially difficult due to the large input space and complex algorithms involved. We discuss how state-of-the-art software testing techniques that are based on the idea of multiple executions, such as metamorphic testing, can be used to implement an effective bioinformatics quality assurance strategy. We hope this review will raise awareness of these critical issues in bioinformatics.

Transient Dysregulation of Dopamine Signaling in a Developing Drosophila Arousal Circuit Permanently Impairs Behavioral Responsiveness in Adults.

The dopamine ontogeny hypothesis for schizophrenia proposes that transient dysregulation of the dopaminergic system during brain development increases the likelihood of this disorder in adulthood. To test this hypothesis in a high-throughput animal model, we have transiently manipulated dopamine signaling in the developing fruit fly Drosophila melanogaster and examined behavioral responsiveness in adult flies. We found that either a transient increase of dopamine neuron activity or a transient decrease of dopamine receptor expression during fly brain development permanently impairs behavioral responsiveness in adults. A screen for impaired responsiveness revealed sleep-promoting neurons in the central brain as likely postsynaptic dopamine targets modulating these behavioral effects. Transient dopamine receptor knockdown during development in a restricted set of ~20 sleep-promoting neurons recapitulated the dopamine ontogeny phenotype, by permanently reducing responsiveness in adult animals. This suggests that disorders involving impaired behavioral responsiveness might result from defective ontogeny of sleep/wake circuits.

CIDR: Ultrafast and accurate clustering through imputation for single-cell RNA-seq data.

Most existing dimensionality reduction and clustering packages for single-cell RNA-seq (scRNA-seq) data deal with dropouts by heavy modeling and computational machinery. Here, we introduce CIDR (Clustering through Imputation and Dimensionality Reduction), an ultrafast algorithm that uses a novel yet very simple implicit imputation approach to alleviate the impact of dropouts in scRNA-seq data in a principled manner. Using a range of simulated and real data, we show that CIDR improves the standard principal component analysis and outperforms the state-of-the-art methods, namely t-SNE, ZIFA, and RaceID, in terms of clustering accuracy. CIDR typically completes within seconds when processing a data set of hundreds of cells and minutes for a data set of thousands of cells. CIDR can be downloaded at https://github.com/VCCRI/CIDR .

Falco: a quick and flexible single-cell RNA-seq processing framework on the cloud.

Summary: Single-cell RNA-seq (scRNA-seq) is increasingly used in a range of biomedical studies. Nonetheless, current RNA-seq analysis tools are not specifically designed to efficiently process scRNA-seq data due to their limited scalability. Here we introduce Falco, a cloud-based framework to enable paralellization of existing RNA-seq processing pipelines using big data technologies of Apache Hadoop and Apache Spark for performing massively parallel analysis of large scale transcriptomic data. Using two public scRNA-seq datasets and two popular RNA-seq alignment/feature quantification pipelines, we show that the same processing pipeline runs 2.6-145.4 times faster using Falco than running on a highly optimized standalone computer. Falco also allows users to utilize low-cost spot instances of Amazon Web Services, providing a ∼65% reduction in cost of analysis. Availability and Implementation: Falco is available via a GNU General Public License at https://github.com/VCCRI/Falco/. Contact: j.ho@victorchang.edu.au. Supplementary information: Supplementary data are available at Bioinformatics online.