Biology subjects

Liu, L.

Publications and source records attributed to Liu, L..

At least 379 records · Page 21Linked to original sources

bioRxiv2024

Negative regulation of APC/C activation by MAPK-mediated attenuation of Cdc20Slp1 under stress

Mitotic anaphase onset is a key cellular process tightly regulated by multiple kinases. The involvement of mitogen-activated protein kinases (MAPKs) in this process has been established in Xenopus egg extracts. However, the detailed regulatory cascade remains elusive, and also it is unknown whether the MAPKs-dependent mitotic regulation is evolutionarily conserved in the single cell eukaryotic organism such as fission yeast (Schizosaccharomyces pombe). Here we show that two MAPKs in S. pombe indeed act in concert to restrain anaphase-promoting complex/cyclosome (APC/C) activity upon activation of the spindle assembly checkpoint (SAC). One MAPK, Pmk1, binds and phosphorylates Slp1Cdc20, the co-activator of APC/C. Phosphorylation of Slp1Cdc20 by Pmk1, but not by Cdk1, promotes its subsequent ubiquitylation and degradation. Intriguingly, Pmk1-mediated phosphorylation event is also required to sustain SAC under environmental stress. Thus, our study establishes a new underlying molecular mechanism of negative regulation of APC/C by MAPK upon stress stimuli, and provides an unappreciated framework for regulation of anaphase entry in eukaryotic cells. One-sentence summaryInhibitory effect on the activation of anaphase promoting complex/cyclosome (APC/C) by MAPK Pmk1

cell biology↗

bioRxiv2024

Optineurin-facilitated axonal mitochondria delivery promotes neuroprotection and axon regeneration

Optineurin (OPTN) mutations are linked to amyotrophic lateral sclerosis (ALS) and normal tension glaucoma (NTG), but a relevant animal model is lacking, and the molecular mechanisms underlying neurodegeneration are unknown. We found that OPTN C-terminus truncation (OPTN{Delta}C) causes late-onset neurodegeneration of retinal ganglion cells (RGCs), optic nerve (ON), and spinal cord motor neurons, preceded by a striking decrease of axonal mitochondria. Surprisingly, we discover that OPTN directly interacts with both microtubules and the mitochondrial transport complex TRAK1/KIF5B, stabilizing them for proper anterograde axonal mitochondrial transport, in a C- terminus dependent manner. Encouragingly, overexpressing OPTN/TRAK1/KIF5B reverses not only OPTN truncation-induced, but also ocular hypertension-induced neurodegeneration, and promotes striking ON regeneration. Therefore, in addition to generating new animal models for NTG and ALS, our results establish OPTN as a novel facilitator of the microtubule-dependent mitochondrial transport necessary for adequate axonal mitochondria delivery, and its loss as the likely molecular mechanism of neurodegeneration.

neuroscience↗

bioRxiv2024

Decoding Missense Variants by Incorporating Phase Separation via Machine Learning

Computational models have made significant progress in predicting the effect of protein variants. However, deciphering numerous variants of unknown significance (VUS) located within intrinsically disordered regions (IDRs) remains challenging. To address this issue, we introduced phase separation (PS), which is tightly linked to IDRs, into the investigation of missense variants. Phase separation is vital for multiple physiological processes. By leveraging missense variants that alter phase separation propensity, we developed a machine learning approach named PSMutPred to predict the impact of missense mutations on phase separation. PSMutPred demonstrated robust performance in predicting missense variants that affect natural phase separation. In vitro experimental findings further underscore its validity. By applying PSMutPred on over 522,000 ClinVar missense variants, it significantly contributes to decoding the pathogenesis of disease variants, especially those in IDRs. Our work provides unique insights into the understanding of a vast number of VUSs in IDRs, thereby expediting clinical interpretation and diagnosis of disease variants.

bioinformatics↗

bioRxiv2024

Whole-genome resequencing revealed the Origin and Domestication of Chinese Domestic Rabbits

The evolutionary and genetic origins of Chinese indigenous rabbits (Oryctolagus cuniculus) remain largely unclear, despite being among the most recently domesticated animals. We sequenced the whole genomes of 142 individual rabbits and collected 25 resequencing accessions from the NCBI, representing six Chinese indigenous breeds, three other domesticated breeds (serving as a bridge between European wild-type and Chinese domestic populations), and two wild rabbit populations from the Iberian Peninsula and Southern France. Population and demographic analyses suggest that Chinese domestic rabbits are most likely descendants of O. c. cuniculus, native to France 800-1500 years ago. These rabbits likely first arrived in the southeast coastal areas of China through trade before spreading to inland regions. Additionally, there may be other origins for Chinese domestic rabbits. We observed considerable variation in the genetic makeup of maternal ancestry between Chinese domestic rabbits and European wild populations, with Chinese rabbits possessing unique mitochondrial haplotypes. Our analysis also highlights selective sweeps on genes affecting brain and neuronal development, which may have been under strong positive selection during domestication; genes related to starch digestion and fat metabolism, suggesting an evolutionary adaptation to digest high-starch diets; and the white coat phenotype in rabbits, resulting from selection at the melanogenesis-associated transcription factor locus. Overall, our data provide comprehensive insights into the origin and domestication of rabbits and lay the foundation for genome-based breeding.

evolutionary biology↗

bioRxiv2024

Light-gated Integrator for Highlighting Kinase Activity in Living Cells

Protein kinases are key signaling nodes that regulate fundamental biological and disease processes. Illuminating kinase signaling from multiple angles can provide deeper insights into disease mechanisms and improve therapeutic targeting. While fluorescent biosensors are powerful tools for visualizing live-cell kinase activity dynamics in real time, new molecular tools are needed that enable recording of transient signaling activities for post hoc analysis and targeted manipulation. Here, we develop a light-gated kinase activity coupled transcriptional integrator (KINACT) that converts dynamic kinase signals into "permanent" fluorescent marks. KINACT enables robust monitoring of kinase activity across scales, accurately recording subcellular PKA activity, highlighting PKA signaling heterogeneity in 3D cultures, and identifying PKA activators and inhibitors in high-throughput screens. We further leverage the ability of KINACT to drive signaling effector expression to allow feedback manipulation of the balance of GsR201C-induced PKA and ERK activation and dissect the mechanisms of oncogenic G protein signaling.

bioengineering↗

bioRxiv2024

Conditional c-MYC activation in catecholaminergic cells drives distinct neuroendocrine tumors: neuroblastoma vs somatostatinoma

The MYC proto-oncogenes (c-MYC, MYCN, MYCL) are among the most deregulated oncogenic drivers in human malignancies including high-risk neuroblastoma, 50% of which are MYCN-amplified. Genetically engineered mouse models (GEMMs) based on the MYCN transgene have greatly expanded the understanding of neuroblastoma biology and are powerful tools for testing new therapies. However, a lack of c-MYC-driven GEMMs has hampered the ability to better understand mechanisms of neuroblastoma oncogenesis and therapy development given that c-MYC is also an important driver of many high-risk neuroblastomas. In this study, we report two transgenic murine neuroendocrine models driven by conditional c-MYC induction in tyrosine hydroxylase (Th) and dopamine {beta}-hydroxylase (Dbh)-expressing cells. c-MYC induction in Th-expressing cells leads to a preponderance of Pdx1+ somatostatinomas, a type of pancreatic neuroendocrine tumor (PNET), resembling human somatostatinoma with highly expressed gene signatures of {delta} cells and potassium channels. In contrast, c-MYC induction in Dbh-expressing cells leads to onset of neuroblastomas, showing a better transforming capacity than MYCN in a comparable C57BL/6 genetic background. The c-MYC murine neuroblastoma tumors recapitulate the pathologic and genetic features of human neuroblastoma, express GD2, and respond to anti-GD2 immunotherapy. This model also responds to DFMO, an FDA-approved inhibitor targeting ODC1, which is a known MYC transcriptional target. Thus, establishing c-MYC-overexpressing GEMMs resulted in different but related tumor types depending on the targeted cell and provide useful tools for testing immunotherapies and targeted therapies for these diseases.

cancer biology↗

bioRxiv2024

The heritability and structural correlates of brain entropy

Brain entropy (BEN) quantifies the temporal complexity of spontaneous neural activity, which has been increasingly recognized as providing important insights into cognitive functions and psychiatric disorders. However, its heritability and structural underpinnings are not well understood. Here, we utilize sample entropy to calculate BEN in healthy young adults using resting-state fMRI from the Human Connectome Project. We show that BEN is significantly heritable in broad brain regions. Heritability estimates exhibit regional variability, with lower heritability in the limbic and subcortical networks than in other networks. We further relate BEN to structural features including surface area (SA), cortical myelination (CM), cortical thickness (CT), and subcortical volumes (SV). We find that BEN is negatively correlated with SA in most cortical regions, but is positively correlated with CM in the prefrontal cortex, lateral temporal lobe, precuneus, lateral parietal cortex, and cingulate cortex. Only a few cortical regions show significant correlations between BEN and CT. By decomposing correlations into genetic and environmental components, we observe that most of BEN-SA correlations are associated with shared genetic and environmental effects. BEN-CM correlations are mainly attributed to shared environmental effects. BEN-CT correlations are partly related to shared environmental effects. We find no significant associations between BEN and SV. Collectively, our work establishes the genetic basis and structural correlates of resting-state fMRI-based BEN, supporting its potential application as an endophenotype for psychiatric disorders.

neuroscience↗

bioRxiv2024

GATLncLoc+C&S: Prediction of LncRNA subcellular localization based on corrective graph attention network

Long non-coding RNAs (LncRNAs) have a wide range of regulatory roles in gene expression, and the subcellular localization identification of LncRNAs is of great value in understanding their biological functions. Graph neural networks can not only utilize sequence characteristics, but also learn hidden features from non-Euclidean data structures to obtain features with powerful characterization capabilities. To learn more fully from the limited LncRNA localization samples and efficiently exploit easily ignored label features, we propose a corrective graph attention network prediction model GATLncLoc+C&S in this paper. Compared with previous methods, the similarity of optimal features is first used to construct the graph. Then, a re-weighted graph attention network R-GAT is constructed and the soft labels obtained from it are used to correct the graph. Finally, the predicted localization label is further obtained by label propagation. Based on the combination of R-GAT and label propagation, GATLncLoc+C&S effectively solves the problems of few samples and data imbalance in LncRNA subcellular localization. The accuracy of GATLncLoc+C&S reached 95.8% and 96.8% in the experiments of 5- and 4-localization benchmark datasets, which reflects the great potential of our proposed method in predicting LncRNA subcellular localization. The source code and data of GATLncLoc+C&S are available at https://github.com/GATLncLoc-C-S/GATLncLoc-C-S.

bioinformatics↗

bioRxiv2024

SARS-CoV-2 Omicron BA.2.87.1 Exhibits Higher Susceptibility to Serum Neutralization Than EG.5.1 and JN.1

As SARS-CoV-2 continues to spread and mutate, tracking the viral evolutionary trajectory and understanding the functional consequences of its mutations remain crucial. Here, we characterized the antibody evasion, ACE2 receptor engagement, and viral infectivity of the highly mutated SARS-CoV-2 Omicron subvariant BA.2.87.1. Compared with other Omicron subvariants, including EG.5.1 and the current predominant JN.1, BA.2.87.1 exhibits less immune evasion, reduced viral receptor engagement, and comparable infectivity in Calu-3 lung cells. Intriguingly, two large deletions ({Delta}15-26 and {Delta}136-146) in the N-terminal domain (NTD) of the spike protein facilitate subtly increased antibody evasion but significantly diminish viral infectivity. Collectively, our data support the announcement by the USA CDC that the public health risk posed by BA.2.87.1 appears to be low.

microbiology↗

bioRxiv2024

Unicellular cyanobacteria rely on sodium energetics to fix N2

Diazotrophic cyanobacteria can thrive in combined nitrogen (N)-limited environments due to their ability to fix nitrogen gas (N2) from the atmosphere. Despite this, they occur in low abundance in N-limited coastal waters, which represents an ecological paradox1-3. One hypothesis is that this is partly due to elevated salinity (> 10 g/L NaCl), which inhibits cyanobacterial N2 fixation2,3. Here we show that N2 fixation in a unicellular coastal cyanobacterium is not inhibited but rather exclusively dependent on sodium (Na+) ions. In N-deficient environments, both N2 fixation and population growth were significantly inhibited at low NaCl concentrations (< 4 g/L). Additional experiments indicated that sodium energetics, rather than proton energetics, is necessary for N2 fixation, as Na+ deficiency resulted in insufficient ATP supply for N2 fixation. We show that this is due to the non-functioning Na+-coupled ATP synthase, which we found to be likely coupled to anaerobic rather than aerobic respiration. Sequence alignment analysis of the ion-coupling site of the ATP synthase revealed a high prevalence of Na+ energetics in cyanobacteria, with all unicellular N2 fixers capable of Na+ energetics. This suggests a critical role for sodium energetics in cyanobacteria. It also raises the possibility that sodium energetics is not as rare as thought, but that we may have underestimated the prevalence and importance of sodium energetics in other organisms. Finally, the low abundance of diazotrophic unicellular cyanobacteria in coastal waters may be due to insufficient NaCl levels to support N2-fixation during periods of growth-supporting high temperatures. This provides another perspective on the regulation of the oceanic N cycle that needs to be considered in times of global climate change. Changes in current patterns could lead to an overlap of periods optimal for N2 fixation and population growth, likely resulting in dense cyanobacterial blooms.

microbiology↗

bioRxiv2024

GP-HTNLoc: A Graph Prototype Head-Tail Network-based Model for Multi-label Subcellular Localization Prediction of ncRNAs

Numerous research findings demonstrated that understanding the subcellular localization of non-coding RNAs (ncRNAs) is pivotal in elucidating their roles and regulatory mechanisms in cells. Despite the existence of over ten computational models dedicated to predicting the subcellular localization of ncRNAs, a majority of these models are designed solely for single-label prediction. In reality, ncRNAs often exhibit localization across multiple subcellular compartments. Furthermore, the existing multi-label localization prediction models are insufficient in addressing the challenges posed by the scarcity of training samples and class imbalance in ncRNA dataset. This study addresses the limitations of existing models by introducing a novel multi-label localization prediction model for ncRNAs, termed GP-HTNLoc. To alleviate class imbalance, the model adopts a separate training approach for head and tail class labels. In GP-HTNLoc, a pioneering graph prototype module is introduced for capturing potential association of ncRNA samples with labels. This module efficiently learns the graph structure and aggregates sample features. Notably, only few samples are required to obtain label prototypes containing rich information. These prototypes are then utilized to train a transfer learner, facilitating the transfer of meta-knowledge from the head class to the tail class. Experimental results demonstrate that GP-HTNLoc surpasses current state-of-the-art models across all datasets. Ablation study underscore the vital role played by the graph prototype module in enhancing the performance of GP-HTNLoc. The user-friendly online GP-HTNLoc web server can be accessed at https://56s8y85390.goho.co.

bioinformatics↗

bioRxiv2024

Immunomagneto-activated hepatocyte-specific tissue vesicle profiling reveals message diversification from regenerating liver

Background & AimsThe liver possesses a remarkable regenerative capacity involving intricate intercellular communication, the mechanisms of which remain poorly understood. Extracellular vesicles (EVs) emerge as important messengers in diverse pathophysiological conditions. However, tissue-derived, cell-specific functional EV populations in regeneration have not been robustly investigated. MethodsBulk and single-cell RNA sequencing analyses of the regenerating liver after partial hepatectomy (PHx), ultrastructural examinations of in situ liver tissue EVs (LT-EVs), and nanoscale and proteomic profiling of hepatocyte-derived tissue EVs (Hep-EVs) were integrated. Targeted inhibition of Hep-EV release in vivo was performed via AAV-mediated shRNA knockdown of Rab27a, and Hep-EVs were intravenously infused for therapeutically use. Gross, histological, and immunofluorescent examinations of livers with evaluating in vivo and ex vivo hepatocyte proliferation were conducted. ResultsLT-EVs contribute to the liver regenerative process after PHx, and hepatocytes serve as the major origin of tissue EVs in the regenerating liver. Moreover, Hep-EVs play an indispensable role to orchestrate liver regeneration, which is strengthened to release with proliferative messages identified after PHx. Mechanistically, Hep-EVs from the regenerating liver reciprocally promote hepatocyte proliferation, which are hallmarked by and function based on the Cyclin dependent kinase 1 (Cdk1) activity. Importantly, replenishment of Hep-EVs from the regenerating liver holds translational promise and rescues insufficient liver regeneration. ConclusionsOur study establishes a functional and mechanistic framework that release of regenerative Hep-EVs govern rapid hepatocyte proliferation through cell cycle control, shedding light on investigation of physiological and endogenous tissue EV populations in organ regeneration and therapy.

cell biology↗

bioRxiv2024

scIDPMs: Single-cell RNA-seq imputation using diffusion probabilistic models

Single-cell RNA sequencing (scRNA-seq) technology is a high-throughput sequencing analysis method that enables the sequencing of mRNA in individual cells, thereby facilitating a more precise understanding of cellular gene expression and metabolic products. This approach reveals cell function and characteristics, making it widely applicable in biological research. However, scRNA-seq data often suffers from false zero values known as dropout events due to limitations in sequencing technology. These dropout events not only mask true gene expression levels but also significantly impact downstream analysis accuracy and reliability. To address this challenge, numerous computational approaches have been proposed for imputing missing gene expression values. Nevertheless, existing imputation methods struggle to fully capture the distribution of dropout values due to the high sparsity of scRNA-seq data and the complexity and randomness associated with gene expression patterns. Recently, probabilistic diffusion models have emerged as deep generative models capable of accurately restoring probability density distributions in domains such as image and audio processing. In this paper, we propose a method called scIDPMs, which utilizes conditional diffusion probabilistic models to impute scRNA-seq data. scIDPMs first identifies dropout sites based on the characteristics of cellular gene expression and then infers the dropout values by conditioning on the available gene expression values, which provide context information for the dropout values. To effectively capture the global features of gene expression profiles, scIDPMs employs a deep neural network with an attention mechanism to optimize the objective function. The performance of scIDPMs was evaluated using both simulated and real scRNA-seq datasets, and compared with eight other imputation methods. The experimental results clearly demonstrated that, in comparison to alternative approaches, scIDPMs exhibited exceptional performance in recovering biologically meaningful gene expression values and enhancing various downstream analyses.

bioinformatics↗

bioRxiv2024

In silico identification of putative causal genetic variants

Understanding the causal genetic architecture of complex phenotypes will fuel future research into disease mechanisms and potential therapies. Here, we illustrate the power of a novel framework: it detects, starting from summary statistics, and across the entire genome, sets of variants that carry non-redundant information on the phenotypes and are therefore more likely to be causal in a biological sense. The approach, implemented in open-source software, is also computationally efficient, requiring less than 15 minutes on a single CPU to perform genome-wide analysis. Through extensive genome-wide simulation studies, we show that the method can substantially outperform existing methods in false discovery rate control, statistical power and various fine-mapping criteria. In applications to a meta-analysis of ten large-scale genetic studies of Alzheimers disease (AD), we identified 82 loci associated with AD, including 37 additional loci missed by conventional GWAS pipeline. Massively parallel reporter assays and CRISPR-Cas9 experiments have confirmed the functionality of the putative causal variants our method points to. Finally, we retrospectively analyzed summary statistics from 67 large-scale GWAS for a variety of phenotypes. Results reveal the methods capacity to robustly discover additional loci for polygenic traits and pinpoint potential causal variants underpinning each locus beyond conventional GWAS pipeline, contributing to a deeper understanding of complex genetic architectures in post-GWAS analyses.

genetics↗

bioRxiv2024

Schlafen-11 and -9 are innate immune sensors for intracellular single-stranded DNA

Nucleic acids are major structures detected by the innate immune system. Although intracellular single-stranded DNA (ssDNA) is accumulated during pathogen infection or pathogenesis, it remains unclear whether and how intracellular ssDNA stimulates the immune system. We report that intracellular ssDNA triggers cytokine expression and cell death in a CGT motif-dependent manner. Through a genome-wide CRISPRLCas9 screen, we identified Schlafen-11 (SLFN11), which is essential for the response to endogenous and pathogen ssDNA. SLFN11 directly binds ssDNA containing CGT motifs and translocates to the cytoplasm upon ssDNA recognition. The mice deficient in SLFN9, the homologue of SLFN11, were resistant to CGT ssDNA-induced inflammation, acute hepatitis and septic shock. This study establishes CGT ssDNA and SLFN11/9 as a novel type of immunostimulatory nucleic acids and pattern recognition receptors, respectively. One-sentence summariessingle-stranded DNA inside cells can awaken Schlafens with a CGT motif to trigger cytokine expression and lytic cell death.

immunology↗

bioRxiv2024

NSD2 is a requisite subunit of the AR/FOXA1 neo-enhanceosome in promoting prostate tumorigenesis

The androgen receptor (AR) is a ligand-responsive transcription factor that binds at enhancers to drive terminal differentiation of the prostatic luminal epithelia. By contrast, in tumors originating from these cells, AR chromatin occupancy is extensively reprogrammed to drive hyper-proliferative, metastatic, or therapy-resistant phenotypes, the molecular mechanisms of which remain poorly understood. Here, we show that the tumor-specific enhancer circuitry of AR is critically reliant on the activity of Nuclear Receptor Binding SET Domain Protein 2 (NSD2), a histone 3 lysine 36 di-methyltransferase. NSD2 expression is abnormally gained in prostate cancer cells and its functional inhibition impairs AR trans-activation potential through partial off-loading from over 40,000 genomic sites, which is greater than 65% of the AR tumor cistrome. The NSD2-dependent AR sites distinctly harbor a chimeric AR-half motif juxtaposed to a FOXA1 element. Similar chimeric motifs of AR are absent at the NSD2-independent AR enhancers and instead contain the canonical palindromic motifs. Meta-analyses of AR cistromes from patient tumors uncovered chimeric AR motifs to exclusively participate in tumor-specific enhancer circuitries, with a minimal role in the physiological activity of AR. Accordingly, NSD2 inactivation attenuated hallmark cancer phenotypes that were fully reinstated upon exogenous NSD2 re-expression. Inactivation of NSD2 also engendered increased dependency on its paralog NSD1, which independently maintained AR and MYC hyper-transcriptional programs in cancer cells. Concordantly, a dual NSD1/2 PROTAC degrader, called LLC0150, was preferentially cytotoxic in AR-dependent prostate cancer as well as NSD2-altered hematologic malignancies. Altogether, we identify NSD2 as a novel subunit of the AR neo-enhanceosome that wires prostate cancer gene expression programs, positioning NSD1/2 as viable paralog co-targets in advanced prostate cancer.

cancer biology↗

bioRxiv2024

5-Aza-Cytidine Enhances Terminal Polyadenylation Site Usage for Full-Length Transcripts in Cells

As an inhibitor of DNA methyltransferases (DNMTs) and an anti-cancer drug, 5-aza-cytidine (5-azaC)s many effects on gene expression remains unclear. Here, we show that 5-azaC treatment of cultured GH3 pituitary tumour cells increases relative usage of genomic terminal exons (GTEs) across the transcriptome. This effect is largely achieved by shifting mRNA polyadenylation from proximal poly(A) sites to GTEs, which harbour a more optimal consensus motif of poly(A) signals. Consistent with this shift, 5-azaC upregulates the mRNA anti-termination factors Scaf4 and Scaf8 while downregulating the early termination enhancer E2f2. In MOLM-13 leukaemia cells, 5-azaC similarly promotes the production of full-length transcripts and regulates alternative polyadenylation factors, some of which in the same direction as observed in GH3 cells. Moreover, PCF11, a factor known to promote proximal poly(A) site usage, is upregulated in both cell lines, suggesting a homeostatic response by these cells to counteract transcript lengthening during 5-azaC treatment. Together, these findings uncover a previously unrecognized effect of 5-azaC on gene expression: directional promotion of terminal polyadenylation site usage, driving a transcriptome-wide switch from shortened to full-length mRNAs in tumour or cancer cells and consequently altering the alternative usage of multiple 3' exons.

cell biology↗

bioRxiv2024

Epigenetic Control of Adaptive or Homeostatic Splicing of Alternative Exons and Prolactin Gene Expression During Interval-Training Activities of Pituitary Cells

Interval-training activities induce adaptive cellular changes without altering their fundamental identity, but the precise underlying molecular mechanisms are not fully understood. In this study, we demonstrate that interval-training depolarization (ITD) of pituitary cells triggers distinct adaptive or homeostatic splicing responses of alternative exons. This occurs while preserving the steady-state expression of the Prolactin and other hormone genes. The nature of these splicing responses depends on the exons DNA methylation status, the methyl-C-binding protein MeCP2 and its associated CA-rich motif-binding hnRNP L. Interestingly, the steady expression of the Prolactin gene is also reliant on MeCP2, whose disruption during ITD leads to exacerbated overexpression and multi-exon aberrant splicing of the hormone gene transcripts, similar to the observed hyperprolactinemia or activity-dependent aberrant splicing in Rett Syndrome. Therefore, depending on how many times cells are stimulated, exons may exhibit different splicing responses to cell activities. During the ITD, epigenetic control is crucial for both adaptive or homeostatic splicing and the steady expression of the Prolactin hormone gene. Disruption in this regulation may have significant implications for the development of progressive diseases.

cell biology↗