Long-term outcomes of neuroendoscopic cyst partial resection combined with stereotactic radiotherapy for craniopharyngioma.

PURPOSE: The aim of this study was to evaluate the treatment outcomes of neuroendoscopic cyst partial resection (ECPR) combined with stereotactic radiotherapy (SRT) for cystic craniopharyngiomas. METHODS: In this retrospective study, 22 craniopharyngioma patients undergoing ECPR combined with SRT were included. This combination therapy was indicated for suprasellar cystic craniopharyngiomas in patients whose pituitary function was preserved but would be difficult to preserve in direct surgery. The outcomes of combination therapy, including tumor control and postoperative visual and pituitary functions, were investigated. RESULTS: ECPR was safely performed, and cyst shrinkage was accomplished in all cases. After ECPR, visual function improved in 12 of 13 patients (92%) with visual field disturbance and did not deteriorate in any patients. Pituitary function was preserved in 14 patients (64%) and deteriorated in eight patients (36%) after ECPR. As a complication of ECPR, meningitis occurred because of a wound infection in one patient. In 18 of 22 patients (82%), the tumor was controlled without further treatment 19 - 87 months (median, 33 months) after SRT. Hypopituitarism was an adverse event after SRT in two of the 18 patients who achieved tumor control. Four patients (18%) had enlarged cysts after SRT. Postoperative pituitary function was significantly more likely to deteriorate in cases of extensive detachment from the ventricular wall, and retreatment was significantly more common in cases with hypothalamic extension. CONCLUSION: Although limited to some cases, ECPR combined with SRT is a less invasive and useful therapeutic option for suprasellar cystic craniopharyngiomas. However, its long-term prognosis requires further evaluation.

Recent trends in RNA informatics: a review of machine learning and deep learning for RNA secondary structure prediction and RNA drug discovery.

Computational analysis of RNA sequences constitutes a crucial step in the field of RNA biology. As in other domains of the life sciences, the incorporation of artificial intelligence and machine learning techniques into RNA sequence analysis has gained significant traction in recent years. Historically, thermodynamics-based methods were widely employed for the prediction of RNA secondary structures; however, machine learning-based approaches have demonstrated remarkable advancements in recent years, enabling more accurate predictions. Consequently, the precision of sequence analysis pertaining to RNA secondary structures, such as RNA-protein interactions, has also been enhanced, making a substantial contribution to the field of RNA biology. Additionally, artificial intelligence and machine learning are also introducing technical innovations in the analysis of RNA-small molecule interactions for RNA-targeted drug discovery and in the design of RNA aptamers, where RNA serves as its own ligand. This review will highlight recent trends in the prediction of RNA secondary structure, RNA aptamers and RNA drug discovery using machine learning, deep learning and related technologies, and will also discuss potential future avenues in the field of RNA informatics.

CyberKnife Radiosurgery for Spinal Intramedullary Arteriovenous Malformations: A Single-Center Experience.

BACKGROUND: Intramedullary spinal arteriovenous malformation (ISAVM, glomus type) is a type of spinal cord arteriovenous malformation, which is a rare disease known often to have a complex vascular supply interfering with that of the spinal cord, and is in complex anatomical relations with cord structures and nerve roots. Though microsurgical and endovascular treatment has mainly been the standard options, in high-risk cases with these treatments, stereotactic radiotherapy (SRT) might be the option of choice. METHODS: We retrospectively reviewed 10 consecutive patients with ISAVM who received SRT using CyberKnife at the Japanese Red Cross Medical Center (Tokyo, Japan) from January 2011 to March 2022. RESULTS: No case in this series suffered from hemorrhage after applying SRT. One case experienced neurological impairment 10 years after SRT, which we attributed to venous congestion due to the remaining lesion. No case of radiation myelopathy was observed in this series. In one case, the nidus volume reduction and loss of flow voids were obvious, though improvement in the neurological outcome was not apparent. No radiological changes were observed in the other 9 patients. CONCLUSIONS: Even in lesions without radiological changes, no hemorrhagic events were observed for an average period of 4 years. SRT may be a feasible option in treating ISAVM, especially for lesions in which microsurgical resection and endovascular treatment are inapplicable. To ascertain the safety and efficacy of this approach, further studies with more patients and longer follow-up is required.

RNA Secondary Structure Prediction Based on Energy Models.

This chapter introduces the RNA secondary structure prediction based on the nearest neighbor energy model, which is one of the most popular architectures of modeling RNA secondary structure without pseudoknots. We discuss the parameterization and the parameter determination by experimental and machine learning-based approaches as well as an integrated approach that compensates each other's shortcomings. Then, folding algorithms for the minimum free energy and the maximum expected accuracy using the dynamic programming technique are introduced. Finally, we compare the prediction accuracy of the method described so far with benchmark datasets.

Direct Inference of Base-Pairing Probabilities with Neural Networks Improves Prediction of RNA Secondary Structures with Pseudoknots.

Existing approaches to predicting RNA secondary structures depend on how the secondary structure is decomposed into substructures, that is, the architecture, to define their parameter space. However, architecture dependency has not been sufficiently investigated, especially for pseudoknotted secondary structures. In this study, we propose a novel algorithm for directly inferring base-pairing probabilities with neural networks that do not depend on the architecture of RNA secondary structures, and then implement this approach using two maximum expected accuracy (MEA)-based decoding algorithms: Nussinov-style decoding for pseudoknot-free structures and IPknot-style decoding for pseudoknotted structures. To train the neural networks connected to each base pair, we adopt a max-margin framework, called structured support vector machines (SSVM), as the output layer. Our benchmarks for predicting RNA secondary structures with and without pseudoknots show that our algorithm outperforms existing methods in prediction accuracy.

Hypofractionated Stereotactic Radiotherapy with CyberKnife for Large Arteriovenous Malformations and Arteriovenous Malformations Located in Eloquent Areas.

Literature has yet to establish an appropriate treatment strategy for large arteriovenous malformations (AVMs) and AVMs located in eloquent areas. In this study, the treatment outcomes of hypofractionated stereotactic radiotherapy (HSRT) with CyberKnife (CK) for large AVMs and AVMs in eloquent areas were evaluated. This study retrospectively evaluated 38 consecutive patients with AVMs treated with HSRT in the Japanese Red Cross Medical Center between August 2010 and July 2015. Obliteration rates and hemorrhage rates at 3- and 5-years of follow-up were calculated. Factors for hemorrhage and obliteration were analyzed with logistic regression analysis. Fourteen (36.8%) patients had a history of hemorrhage. Twenty (52.6%) AVMs were larger than 10 mL, and 34 (89.5%) AVMs were located in eloquent areas. The majority of the AVMs (84.2%) were classified into high grades (grades 3, 4, and 5) using the Spetzler-Martin grading scale. The median modified radiosurgery-based AVM score was 2.05, and the median Virginia Radiosurgery AVM Score was 3. The mean marginal dose was 24.5 ± 2.5 Gy. Twenty-three and 15 patients received three- and five-fraction stereotactic radiotherapy, respectively. At 3 and 5 years posttreatment, two (2.0%/year) and six (6.7%/year) patients had hemorrhage with obliteration rates of 15.2% and 16.7%, respectively. AVM localization in eloquent areas was a risk factor for obliteration failure. This study revealed that HSRT with CK for large AVMs and AVMs located in eloquent areas contributed to hemorrhage risk reduction and obliteration, at least in the early stages.

Integer programming for selecting set of informative markers in paternity inference.

BACKGROUND: Parentage information is fundamental to various life sciences. Recent advances in sequencing technologies have made it possible to accurately infer parentage even in non-model species. The optimization of sets of genome-wide markers is valuable for cost-effective applications but requires extremely large amounts of computation, which presses for the development of new efficient algorithms. RESULTS: Here, for a closed half-sib population, we generalized the process of marker loci selection as a binary integer programming problem. The proposed systematic formulation considered marker localization and the family structure of the potential parental population, resulting in an accurate assignment with a small set of markers. We also proposed an efficient heuristic approach, which effectively improved the number of markers, localization, and tolerance to missing data of the set. Applying this method to the actual genotypes of apple (Malus × domestica) germplasm, we identified a set of 34 SNP markers that distinguished 300 potential parents crossed to a particular cultivar with a greater than 99% accuracy. CONCLUSIONS: We present a novel approach for selecting informative markers based on binary integer programming. Since the data generated by high-throughput sequencing technology far exceeds the requirement for parentage assignment, a combination of the systematic marker selection with targeted SNP genotyping, such as KASP, allows flexibly enlarging the analysis up to a scale that has been unrealistic in various species. The method developed in this study can be directly applied to unsolved large-scale problems in breeding, reproduction, and ecological research, and is expected to lead to novel knowledge in various biological fields. The implementation is available at https://github.com/SoNishiyama/IP-SIMPAT .

Transgenically expressed Helicobacter pylori CagA in vascular endothelial cells accelerates arteriosclerosis in mice.

Arteriosclerosis is intimately associated with cardiovascular diseases. Recently, evidence accumulated that infection with Helicobacter pylori cagA-positive strains, which causes gastritis, peptic ulceration, and gastric cancer, is also involved in the development of arteriosclerosis. The cagA-encoded CagA protein is injected into the attached gastric epithelial cells via the type IV secretion system. We previously showed that CagA-containing exosomes are secreted from CagA-injected gastric epithelial cells and enter the systemic blood circulation, delivering CagA into endothelial cells. In the present study, transgenic mice were established in which CagA was selectively expressed in endothelial cells by Cre-loxP system. Treatment of the mice with a high-fat diet revealed that atherogenic lesions were induced in mice expressing CagA in vascular endothelial cells but not in CagA-nonexpressing mice. To investigate the effects of CagA on endothelial cells, we also established conditional CagA-expressing human vascular endothelial cells using the Tet-on system. Upon induction of CagA, a dramatic change in cell morphology was observed that was concomitantly associated with the loss of the endothelial cells to form tube-like structures. Induction of CagA also activated the pro-inflammatory transcription factor STAT3. Thus, exosome-delivered CagA deregulates signals that activates STAT3 in endothelial cells, which accelerates inflammation that promotes arteriosclerosis/atherosclerosis.

The Treatment Outcome of CyberKnife-Based Stereotactic Radiotherapy for Intracranial and Extracranial Nonvestibular Schwannomas: A Single-Center Experience.

BACKGROUND: Data on the outcomes of CyberKnife-based hypofractionated stereotactic radiosurgery (hSRS) for intracranial and extracranial nonvestibular schwannomas (nVSs) are not sufficient. METHODS: Patients who underwent hSRS for nVSs between 2010 and 2019 were retrospectively reviewed. RESULTS: A total of 39 patients with 39 nVSs were identified. The mean age was 53 (±18) years, and 20 patients (51%) were women. Twenty-five patients (64%) had previous surgeries. Seventeen patients (44%) had nVSs extending outside the cranium. The mean prescribed dose covering 95% of the planning target volume was 22 Gy (±3.7 Gy), the mean fractionation was 4 (±2), and the mean target volume was 13 cm3 (±16 cm3). The radiological tumor control rate was 100% during the mean follow-up period of 67 months (±37 months). Thirty-seven patients (95%) were clinically stable during the mean follow-up period of 72 months (±35 months). Nine patients (23%) suffered from transient adverse radiation effects (AREs), including transient tumor expansion, and 2 (5%) suffered from permanent AREs. CONCLUSIONS: We summarized the treatment outcomes of hSRS for nVSs. Although all patients achieved radiological tumor control, the risk of either transient or permanent ARE was high. Therefore, it is necessary to monitor patients for clinical deterioration due to AREs.

Prediction of RNA secondary structure including pseudoknots for long sequences.

RNA structural elements called pseudoknots are involved in various biological phenomena including ribosomal frameshifts. Because it is infeasible to construct an efficiently computable secondary structure model including pseudoknots, secondary structure prediction methods considering pseudoknots are not yet widely available. We developed IPknot, which uses heuristics to speed up computations, but it has remained difficult to apply it to long sequences, such as messenger RNA and viral RNA, because it requires cubic computational time with respect to sequence length and has threshold parameters that need to be manually adjusted. Here, we propose an improvement of IPknot that enables calculation in linear time by employing the LinearPartition model and automatically selects the optimal threshold parameters based on the pseudo-expected accuracy. In addition, IPknot showed favorable prediction accuracy across a wide range of conditions in our exhaustive benchmarking, not only for single sequences but also for multiple alignments.

A Max-Margin Model for Predicting Residue-Base Contacts in Protein-RNA Interactions.

Protein-RNA interactions (PRIs) are essential for many biological processes, so understanding aspects of the sequences and structures involved in PRIs is important for unraveling such processes. Because of the expensive and time-consuming techniques required for experimental determination of complex protein-RNA structures, various computational methods have been developed to predict PRIs. However, most of these methods focus on predicting only RNA-binding regions in proteins or only protein-binding motifs in RNA. Methods for predicting entire residue-base contacts in PRIs have not yet achieved sufficient accuracy. Furthermore, some of these methods require the identification of 3D structures or homologous sequences, which are not available for all protein and RNA sequences. Here, we propose a prediction method for predicting residue-base contacts between proteins and RNAs using only sequence information and structural information predicted from sequences. The method can be applied to any protein-RNA pair, even when rich information such as its 3D structure, is not available. In this method, residue-base contact prediction is formalized as an integer programming problem. We predict a residue-base contact map that maximizes a scoring function based on sequence-based features such as k-mers of sequences and the predicted secondary structure. The scoring function is trained using a max-margin framework from known PRIs with 3D structures. To verify our method, we conducted several computational experiments. The results suggest that our method, which is based on only sequence information, is comparable with RNA-binding residue prediction methods based on known binding data.

The Long-Term Outcome of CyberKnife-Based Stereotactic Radiotherapy for Head and Neck Paragangliomas: A Single-Center Experience.

OBJECTIVE: To assess long-term outcomes of hypofractionated stereotactic radiotherapy (hSRT) for head and neck paragangliomas (HNPGs). METHODS: Patients who underwent hSRT with CyberKnife for HNPGs from 2010 to 2019 were retrospectively reviewed. RESULTS: A total of 34 HNPGs in 29 patients were identified. Mean patient age was 50 ± 16 years, and 15 patients (52%) were female. Fifteen patients (55%) had undergone previous procedures. Four cases (14%) were functional in hormone production. According to the Fisch classification, 1 (3%) case was B, 12 (42%) cases were C, 14 (48%) cases were D, and 2 (7%) cases were unclassified.1 The median prescribed dose covering 95% of the planning target volume was 2500 cGy (interquartile range 2100-2600 cGy), and the median target volume was 10 cm3 (interquartile range 6.0-18.3 cm3). The local control rate was 97%. The median progression-free survival was 66 months (interquartile range 28-95 months), and 96% of patients were free of tumor progression at 8 years. During follow-up, 1 case (3%) resulted in permanent facial nerve palsy (House-Brackmann grade II), and another case (3%) resulted in asymptomatic cerebellar radiation necrosis. Univariate and multivariate analysis showed that no previous surgical history (odds ratio 8.58, 95% confidence interval 1.2-59.7, P = 0.03) was a positive predictor of symptomatic improvement. CONCLUSIONS: hSRT for HNPGs was an effective treatment with minimal side effects over the long term and may have a role as first-line therapy, especially for symptomatic nonfunctional HNPGs, for better symptom control.

A Web Server for Designing Molecular Switches Composed of Two Interacting RNAs.

The programmability of RNA-RNA interactions through intermolecular base-pairing has been successfully exploited to design a variety of RNA devices that artificially regulate gene expression. An in silico design for interacting structured RNA sequences that satisfies multiple design criteria becomes a complex multi-objective problem. Although multi-objective optimization is a powerful technique that explores a vast solution space without empirical weights between design objectives, to date, no web service for multi-objective design of RNA switches that utilizes RNA-RNA interaction has been proposed. We developed a web server, which is based on a multi-objective design algorithm called MODENA, to design two interacting RNAs that form a complex in silico. By predicting the secondary structures with RactIP during the design process, we can design RNAs that form a joint secondary structure with an external pseudoknot. The energy barrier upon the complex formation is modeled by an interaction seed that is optimized in the design algorithm. We benchmarked the RNA switch design approaches (MODENA+RactIP and MODENA+RNAcofold) for the target structures based on natural RNA-RNA interactions. As a result, MODENA+RactIP showed high design performance for the benchmark datasets.

The long-term outcome of CyberKnife-based stereotactic radiotherapy for central skull base meningiomas: a single-center experience.

Few reports exist demonstrating the effects of stereotactic radiotherapy (SRT) on the central skull base meningiomas (CSMs). A retrospective analysis of 113 patients was performed. The median age was 62 (IQR 50-72) years old, and 78 patients (69%) were female. Upfront SRT was performed in 41 (36%), where 17 (15%) patients were asymptomatic. The other SRT was for postoperative adjuvant therapy in 32 (28%), and for the recurrent or relapsed tumors in 40 (35%) patients. Previous operation was done in 74 patients (66%). Among the available pathology in 46 patients, 37 (80%) were WHO grade I, 8 (17%) were grade II, and 1 (2%) was grade III. The median prescribed dose covered 95% of the planning target volume was 25 (IQR 21-25) Gy, and the median target volume was 9.5 (IQR 3.9-16.9) cm3. The median progression-free survival (PFS) was 48 (IQR 23-73) months and 84% and 78% were free of tumor progression at 5 and 10 years respectively. The median follow-up was 49 (IQR 28-83) months. PFS was better in grade I than grade II (p = 0.02). No other baseline factors including the history of previous operation were associated with PD or PFS. Adverse events of radiation therapy were radiation-induced optic neuropathy (0.9%), and cerebral edema (4.4%). Asymptomatic cavernous carotid stenosis was found in three (2.7%), five (4.4%) underwent ventriculoperitoneal shunt placement for normal pressure hydrocephalus, and five (4.4%) died. SRT is useful for the management of CSMs with a low rate of adverse events.

RNA secondary structure prediction using deep learning with thermodynamic integration.

Accurate predictions of RNA secondary structures can help uncover the roles of functional non-coding RNAs. Although machine learning-based models have achieved high performance in terms of prediction accuracy, overfitting is a common risk for such highly parameterized models. Here we show that overfitting can be minimized when RNA folding scores learnt using a deep neural network are integrated together with Turner's nearest-neighbor free energy parameters. Training the model with thermodynamic regularization ensures that folding scores and the calculated free energy are as close as possible. In computational experiments designed for newly discovered non-coding RNAs, our algorithm (MXfold2) achieves the most robust and accurate predictions of RNA secondary structures without sacrificing computational efficiency compared to several other algorithms. The results suggest that integrating thermodynamic information could help improve the robustness of deep learning-based predictions of RNA secondary structure.

Neural correlates of head restraint: Unsolicited neuronal activation and dopamine release.

To minimize motion-related distortion of reconstructed images, conventional positron emission tomography (PET) measurements of the brain inevitably require a firm and tight head restraint. While such a restraint is now a routine procedure in brain imaging, the physiological and psychological consequences resulting from the restraint have not been elucidated. To address this problem, we developed a restraint-free brain PET system and conducted PET scans under both restrained and non-restrained conditions. We examined whether head restraint during PET scans could alter brain activities such as regional cerebral blood flow (rCBF) and dopamine release along with psychological stress related to head restraint. Under both conditions, 20 healthy male participants underwent [15O]H2O and [11C]Raclopride PET scans during working memory tasks with the same PET system. Before, during, and after each PET scan, we measured physiological and psychological stress responses, including the State-Trait Anxiety Inventory (STAI) scores. Analysis of the [15O]H2O-PET data revealed higher rCBF in regions such as the parahippocampus in the restrained condition. We found the binding potential (BPND) of [11C]Raclopride in the putamen was significantly reduced in the restrained condition, which reflects an increase in dopamine release. Moreover, the restraint-induced change in BPND was correlated with a shift in the state anxiety score of the STAI, indicating that less anxiety accompanied smaller dopamine release. These results suggest that the stress from head restraint could cause unsolicited responses in brain physiology and emotional states. The restraint-free imaging system may thus be a key enabling technology for the natural depiction of the mind.

Roles of the kisspeptin/GPR54 system in pathomechanisms of atherosclerosis.

AIMS: Kisspeptin-10 (KP-10), a potent vasoconstrictor and inhibitor of angiogenesis, and its receptor, GPR54, have currently received much attention with respect to atherosclerosis, since both KP-10 and GPR54 are expressed at high levels in atheromatous plaques and restenotic lesions after wire-injury. The present review introduces the emerging roles of the KP-10/GPR54 system in atherosclerosis. DATA SYNTHESIS: KP-10 suppresses migration and proliferation of human umbilical vein endothelial cells (HUVECs), and induces senescence in HUVECs. KP-10 increases adhesion of human monocytes to HUVECs. KP-10 also stimulates expression of interleukin-6, tumor necrosis factor-α, monocyte chemotactic protein-1, intercellular adhesion molecule-1, vascular cell adhesion molecule-1, and E-selectin genes in HUVECs. KP-10 enhances oxidized low-density lipoprotein-induced foam cell formation associated with upregulation of CD36 and acyl-coenzyme A: cholesterol acyltransferase-1 in human monocyte-derived macrophages. In human aortic smooth muscle cells, KP-10 suppresses angiotensin II-induced migration and proliferation, however, it enhances apoptosis and activities of matrix metalloproteinase (MMP)-2 and MMP-9 by upregulation of extracellular signal-regulated kinase 1/2, p38, Bax, and caspase-3. Four-week-infusion of KP-10 into Apoe-/- mice accelerates development of aortic atherosclerotic lesions with increased monocyte/macrophage infiltration and vascular inflammation, also, it decreases intraplaque vascular smooth muscle cell content. Proatherosclerotic effects of endogenous and exogenous KP-10 were completely attenuated upon infusion of P234, a GPR54 antagonist, in Apoe-/- mice. CONCLUSION: These findings suggest that KP-10 may contribute to acceleration of progression and to the instability of atheromatous plaques, leading to rupture of plaques. This GPR54 antagonist may be useful for the prevention and treatment of atherosclerosis. Thus, the KP-10/GPR54 system may serve as a novel therapeutic target for atherosclerotic diseases.

ß-Endorphin Mediates the Development and Instability of Atherosclerotic Plaques.

ß-Endorphin, an endogenous opioid peptide, and its µ-opioid receptor are expressed in brain, liver, and peripheral tissues. ß-Endorphin induces endothelial dysfunction and is related to insulin resistance. We clarified the effects of ß-endorphin on atherosclerosis. We assessed the effects of ß-endorphin on the inflammatory response and monocyte adhesion in human umbilical vein endothelial cells (HUVECs), foam cell formation, and the inflammatory phenotype in THP-1 monocyte-derived macrophages, and migration and proliferation of human aortic smooth muscle cells (HASMCs) in vitro. We also assessed the effects of ß-endorphin on aortic lesions in Apoe -/- mice in vivo. The µ-opioid receptor (OPRM1) was expressed in THP-1 monocytes, macrophages, HASMCs, HUVECs, and human aortic endothelial cells. ß-Endorphin significantly increased THP-1 monocyte adhesion to HUVECs and induced upregulation of intercellular adhesion molecule-1, vascular cell adhesion molecule-1, and E-selectin via nuclear factor-κB (NF-κB) and p38 phosphorylation in HUVECs. ß-Endorphin significantly increased HUVEC proliferation and enhanced oxidized low-density lipoprotein-induced foam cell formation in macrophages. ß-Endorphin also significantly shifted the macrophage phenotype to proinflammatory M1 rather than anti-inflammatory M2 via NF-κB phosphorylation during monocyte-macrophage differentiation and increased migration and apoptosis in association with c-jun-N-terminal kinase, p38, and NF-κB phosphorylation in HASMCs. Chronic ß-endorphin infusion into Apoe -/- mice significantly aggravated the development of aortic atherosclerotic lesions, with an increase in vascular inflammation and the intraplaque macrophage/smooth muscle cell ratio, an index of plaque instability. Our study provides the first evidence that ß-endorphin contributes to the acceleration of the progression and instability of atheromatous plaques. Thus, µ-opioid receptor antagonists may be useful for the prevention and treatment of atherosclerosis.

An improved de novo genome assembly of the common marmoset genome yields improved contiguity and increased mapping rates of sequence data.

BACKGROUND: The common marmoset (Callithrix jacchus) is one of the most studied primate model organisms. However, the marmoset genomes available in the public databases are highly fragmented and filled with sequence gaps, hindering research advances related to marmoset genomics and transcriptomics. RESULTS: Here we utilize single-molecule, long-read sequence data to improve and update the existing genome assembly and report a near-complete genome of the common marmoset. The assembly is of 2.79 Gb size, with a contig N50 length of 6.37 Mb and a chromosomal scaffold N50 length of 143.91 Mb, representing the most contiguous and high-quality marmoset genome up to date. Approximately 90% of the assembled genome was represented in contigs longer than 1 Mb, with approximately 104-fold improvement in contiguity over the previously published marmoset genome. More than 98% of the gaps from the previously published genomes were filled successfully, which improved the mapping rates of genomic and transcriptomic data on to the assembled genome. CONCLUSIONS: Altogether the updated, high-quality common marmoset genome assembly provide improvements at various levels over the previous versions of the marmoset genome assemblies. This will allow researchers working on primate genomics to apply the genome more efficiently for their genomic and transcriptomic sequence data.