Hari Krishna Yalamanchili

Extensive cryptic splicing upon loss of RBM17 and TDP43 in neurodegeneration models

Splicing regulation is an important step of post-transcriptional gene regulation. It is a highly dynamic process orchestrated by RNA-binding proteins (RBPs). RBP dysfunction and global splicing dysregulation have been implicated in many human diseases, but the in vivo functions of most RBPs and the splicing outcome upon their loss remain largely unexplored. Here we report that constitutive deletion of Rbm17, which encodes an RBP with a putative role in splicing, causes early embryonic lethality in mice and that its loss in Purkinje neurons leads to rapid degeneration. Transcriptome profiling of Rbm17-deficient and control neurons and subsequent splicing analyses using CrypSplice, a new computational method that we developed, revealed that more than half of RBM17-dependent splicing changes are cryptic. Importantly, RBM17 represses cryptic splicing of genes that likely contribute to motor coordination and cell survival. This finding prompted us to re-analyze published datasets from a recent report on TDP-43, an RBP implicated in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), as it was demonstrated that TDP-43 represses cryptic exon splicing to promote cell survival. We uncovered a large number of TDP-43-dependent splicing defects that were not previously discovered, revealing that TDP-43 extensively regulates cryptic splicing. Moreover, we found a significant overlap in genes that undergo both RBM17- and TDP-43-dependent cryptic splicing repression, many of which are associated with survival. We propose that repression of cryptic splicing by RBPs is critical for neuronal health and survival. CrypSplice is available at www.liuzlab.org/CrypSplice.

Transcriptional Regulation by ATOH1 and its Target SPDEF in the Intestine

Background & Aims The transcription factor atonal homolog 1 (ATOH1) controls the fate of intestinal progenitors downstream of the Notch signaling pathway. Intestinal progenitors that escape Notch activation express high levels of ATOH1 and commit to a secretory lineage fate, implicating ATOH1 as a gatekeeper for differentiation of intestinal epithelial cells. Although some transcription factors downstream of ATOH1, such as SPDEF, have been identified to specify differentiation and maturation of specific cell types, the bona fide transcriptional targets of ATOH1 still largely are unknown. Here, we aimed to identify ATOH1 targets and to identify transcription factors that are likely to co-regulate gene expression with ATOH1. Methods We used a combination of chromatin immunoprecipitation and messenger RNA–based high-throughput sequencing (ChIP-seq and RNA-seq), together with cell sorting and transgenic mice, to identify direct targets of ATOH1, and establish the epistatic relationship between ATOH1 and SPDEF. Results By using unbiased genome-wide approaches, we identified more than 700 genes as ATOH1 transcriptional targets in adult small intestine and colon. Ontology analysis indicated that ATOH1 directly regulates genes involved in specification and function of secretory cells. De novo motif analysis of ATOH1 targets identified SPDEF as a putative transcriptional co-regulator of ATOH1. Functional epistasis experiments in transgenic mice show that SPDEF amplifies ATOH1-dependent transcription but cannot independently initiate transcription of ATOH1 target genes. Conclusions This study unveils the direct targets of ATOH1 in the adult intestines and illuminates the transcriptional events that initiate the specification and function of intestinal secretory lineages.

Comparative and quantitative proteomics reveal the adaptive strategies of oyster larvae to ocean acidification.

Decreasing pH due to anthropogenic CO2 inputs, called ocean acidification (OA), can make coastal environments unfavorable for oysters. This is a serious socioeconomical issue for China which supplies >70% of the worlds edible oysters. Here, we present an iTRAQ‐based protein profiling approach for the detection and quantification of proteome changes under OA in the early life stage of a commercially important oyster, Crassostrea hongkongensis. Availability of complete genome sequence for the pacific oyster (Crassostrea gigas) enabled us to confidently quantify over 1500 proteins in larval oysters. Over 7% of the proteome was altered in response to OA at pHNBS 7.6. Analysis of differentially expressed proteins and their associated functional pathways showed an upregulation of proteins involved in calcification, metabolic processes, and oxidative stress, each of which may be important in physiological adaptation of this species to OA. The downregulation of cytoskeletal and signal transduction proteins, on the other hand, might have impaired cellular dynamics and organelle development under OA. However, there were no significant detrimental effects in developmental processes such as metamorphic success. Implications of the differentially expressed proteins and metabolic pathways in the development of OA resistance in oyster larvae are discussed. The MS proteomics data have been deposited to the ProteomeXchange with identifiers PXD002138 (http://proteomecentral.proteomexchange.org/dataset/PXD002138).

Data Analysis Pipeline for RNA‐seq Experiments: From Differential Expression to Cryptic Splicing

RNA sequencing (RNA‐seq) is a high‐throughput technology that provides unique insights into the transcriptome. It has a wide variety of applications in quantifying genes/isoforms and in detecting non‐coding RNA, alternative splicing, and splice junctions. It is extremely important to comprehend the entire transcriptome for a thorough understanding of the cellular system. Several RNA‐seq analysis pipelines have been proposed to date. However, no single analysis pipeline can capture dynamics of the entire transcriptome. Here, we compile and present a robust and commonly used analytical pipeline covering the entire spectrum of transcriptome analysis, including quality checks, alignment of reads, differential gene/transcript expression analysis, discovery of cryptic splicing events, and visualization. Challenges, critical parameters, and possible downstream functional analysis pipelines associated with each step are highlighted and discussed. This unit provides a comprehensive understanding of state‐of‐the‐art RNA‐seq analysis pipeline and a greater understanding of the transcriptome.

Forniceal deep brain stimulation induces gene expression and splicing changes that promote neurogenesis and plasticity

Clinical trials are currently underway to assess the efficacy of forniceal deep brain stimulation (DBS) for improvement of memory in Alzheimer’s patients, and forniceal DBS has been shown to improve learning and memory in a mouse model of Rett syndrome (RTT), an intellectual disability disorder caused by loss-of-function mutations in MECP2. The mechanism of DBS benefits has been elusive, however, so we assessed changes in gene expression, splice isoforms, DNA methylation, and proteome following acute forniceal DBS in wild-type mice and mice lacking Mecp2. We found that DBS upregulates genes involved in synaptic function, cell survival, and neurogenesis and normalized expression of ~25% of the genes altered in Mecp2-null mice. Moreover, DBS induced expression of 17–24% of the genes downregulated in other intellectual disability mouse models and in post-mortem human brain tissue from patients with Major Depressive Disorder, suggesting forniceal DBS could benefit individuals with a variety of neuropsychiatric disorders.

An ultra-fast and scalable quantification pipeline for transposable elements from next generation sequencing data

Transposable elements (TEs) are DNA sequences which are capable of moving from one location to another and represent a large proportion (45%) of the human genome. TEs have functional roles in a variety of biological phenomena such as cancer, neurodegenerative disease, and aging. Rapid development in RNA-sequencing technology has enabled us, for the first time, to study the activity of TE at the systems level.However, efficient TE analysis tools are not yet developed. In this work, we developed SalmonTE, a fast and reliable pipeline for the quantification of TEs from RNA-seq data. We benchmarked our tool against TEtranscripts, a widely used TE quantification method, and three other quantification methods using several RNA-seq datasets from Drosophila melanogaster and human cell-line. We achieved 20 times faster execution speed without compromising the accuracy. This pipeline will enable the biomedical research community to quantify and analyze TEs from large amounts of data and lead to novel TE centric discoveries.

Apparent bias toward long gene misregulation in MeCP2 syndromes disappears after controlling for baseline variations

Recent studies have suggested that genes longer than 100 kb are more likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism and Rett syndrome. These length-dependent transcriptional changes are modest in MeCP2-mutant samples, but, given the low sensitivity of high-throughput transcriptome profiling technology, here we re-evaluate the statistical significance of these results. We find that the apparent length-dependent trends previously observed in MeCP2 microarray and RNA-sequencing datasets disappear after estimating baseline variability from randomized control samples. This is particularly true for genes with low fold changes. We find no bias with NanoString technology, so this long gene bias seems to be particular to polymerase chain reaction amplification-based platforms. In contrast, authentic long gene effects, such as those caused by topoisomerase inhibition, can be detected even after adjustment for baseline variability. We conclude that accurate characterization of length-dependent (or other) trends requires establishing a baseline from randomized control samples.Recent studies have suggested that long genes (>100 kb) are more likely to be misregulated in some neurological diseases, such as autism and Rett syndrome. Here the authors find that the apparent length-dependent trends previously observed in MeCP2 microarray and RNA-sequencing datasets disappeared after controlling for baseline variations.

RBM17 Interacts with U2SURP and CHERP to Regulate Expression and Splicing of RNA-Processing Proteins

SUMMARY RNA splicing entails the coordinated interaction of more than 150 proteins in the spliceosome, one of the most complex of the cell’s molecular machines. We previously discovered that the RNA-binding motif protein 17 (RBM17), a component of the spliceosome, is essential for survival and cell maintenance. Here, we find that it interacts with the spliceosomal factors U2SURP and CHERP and that they reciprocally regulate each other’s stability, both in mouse and in human cells. Individual knockdown of each of the three proteins induces overlapping changes in splicing and gene expression of transcripts enriched for RNA-processing factors. Our results elucidate the function of RBM17, U2SURP, and CHERP and link the activity of the spliceosome to the regulation of downstream RNA-binding proteins. These data support the hypothesis that, beyond driving constitutive splicing, spliceosomal factors can regulate alternative splicing of specific targets.

Bias toward long gene misregulation in synaptic disorders can be an artefact of amplification-based methods

Several recent studies have suggested that genes that are longer than 100 kilobases are more likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism and Rett syndrome. These length-dependent transcriptional changes are modest in Mecp2-mutant samples, but, given the low sensitivity of high-throughput transcriptome profiling technology, the statistical significance of these results needs to be re-evaluated. Here, we show that the apparent length-dependent trends previously observed in MeCP2 microarray and RNA-Sequencing datasets, particularly in genes with low fold-changes, disappeared after accounting for baseline variability estimated from randomized control samples. As we found no similar bias with NanoString technology, this long-gene bias seems to be particular to PCR amplification-based platforms. In contrast, authentic long gene effects, such as those caused by topoisomerase inhibition, can be detected even after adjustment for baseline variability. Accurate detection of length-dependent trends requires establishing a baseline from randomized control samples. HIGHLIGHTS Length-dependent gene misregulation is not intrinsic to Mecp2 disruption. Topoisomerase inhibition produces an authentic long gene bias. PCR amplification-based high-throughput datasets are biased toward long genes.