SRSF1-Regulated Alternative Splicing in Breast Cancer.

Splicing factor SRSF1 is upregulated in human breast tumors, and its overexpression promotes transformation of mammary cells. Using RNA-seq, we identified SRSF1-regulated alternative splicing (AS) targets in organotypic three-dimensional MCF-10A cell cultures that mimic a context relevant to breast cancer. We identified and validated hundreds of endogenous SRSF1-regulated AS events. De novo discovery of the SRSF1 binding motif reconciled discrepancies in previous motif analyses. Using a Bayesian model, we determined positional effects of SRSF1 binding on cassette exons: binding close to the 5' splice site generally promoted exon inclusion, whereas binding near the 3' splice site promoted either exon skipping or inclusion. Finally, we identified SRSF1-regulated AS events deregulated in human tumors; overexpressing one such isoform, exon-9-included CASC4, increased acinar size and proliferation, and decreased apoptosis, partially recapitulating SRSF1's oncogenic effects. Thus, we uncovered SRSF1 positive and negative regulatory mechanisms, and oncogenic AS events that represent potential targets for therapeutics development.

Assessment of Carbon Sequestration Capacity of E. ulmoides in Ruyang County and Its Ecological Suitability Zoning Based on Satellite Images of GF-6.

Eucommia ulmoides Oliver. (E. ulmoides) is a species of small tree native to China. It is a valuable medicinal herb that can be used to treat Alzheimer's disease, diabetes, hypertension, and other diseases. In addition, E. ulmoides is a source of rubber. It has both medicinal and ecological value. As ecological problems become increasingly prominent, accurate information on the cultivated area of E. ulmoides is important for understanding the carbon sequestration capacity and ecological suitability zoning of E. ulmoides. In previous tree mapping studies, no studies on the spectral characteristics of E. ulmoides and its remote sensing mapping have been seen. We use Ruyang County, Henan Province, China, as the study area. Firstly, using the 2021 Gao Fen-6 (GF-6) Wide Field of View (WFV) time series images covering the different growth stages of E. ulmoides based on the participation of red-edge bands, several band combination schemes were constructed. The optimal time window to identify E. ulmoides was selected by calculating the separability of E. ulmoides from other land cover types for different schemes. Secondly, a random forest algorithm based on several band combination schemes was investigated to map the E. ulmoides planting areas in Ruyang County. Thirdly, the annual NPP values of E. ulmoides were estimated using an improved Carnegie Ames Stanford Approach (CASA) to a light energy utilization model, which, in turn, was used to assess the carbon sequestration capacity. Finally, the ecologically suitable distribution zone of E. ulmoides under near current and future (2041-2060) climatic conditions was predicted using the MaxEnt model. The results showed that the participation of the red-edge band of the GF-6 data in the classification could effectively improve the recognition accuracy of E. ulmoides, making its overall accuracy reach 96.62%; the high NPP value of E. ulmoides was mainly concentrated in the south of Ruyang County, with a total annual carbon sequestration of 540.104835 t CM-2·a-1. The ecological suitability zone of E. ulmoides can be divided into four classes: unsuitable area, low suitable area, medium suitable area, and high suitable area. The method proposed in this paper applies to the real-time monitoring of E. ulmoides, highlighting its potential ecological value and providing theoretical reference and data support for the reasonable layout of E. ulmoides.

[Medicinal plant resources in Inner Mongolia autonomous region of China and Mongolia: a comparative study].

Inner Mongolia autonomous region of China and Mongolia are the primary regions where Chinese and Mongolian medicine and its medicinal plant resources are distributed. In this study, 133 families, 586 genera, and 1 497 species of medicinal plants in Inner Mongolia as well as 62 families, 261 genera, and 467 species of medicinal plants in Mongolia were collected through field investigation, specimen collection and identification, and literature research. And the species, geographic distribution, and influencing factors of the above medicinal plants were analyzed. The results revealed that there were more plant species utilized for medicinal reasons in Inner Mongolia than in Mongolia. Hotspots emerged in Hulunbuir, Chifeng, and Tongliao of Inner Mongolia, while there were several hotspots in Eastern province, Sukhbaatar province, Gobi Altai province, Bayankhongor province, Middle Gobi province, Kobdo province, South Gobi province, and Central province of Mongolia. The interplay of elevation and climate made a non-significant overall contribution to the diversity of plant types in Inner Mongolia and Mongolia. The contribution of each factor increased significantly when the vegetation types of Inner Mongolia and Mongolia were broadly divided into forest, grassland and desert. Thus, the distribution of medicinal plant resources and vegetation cover were jointly influenced by a variety of natural factors such as topography, climate and interactions between species, and these factors contributed to and constrained each other. This study provided reference for sustainable development and rational exploitation of medicinal plant resources in future.

Main flavor compounds and molecular regulation mechanisms in fruits and vegetables.

Fruits and vegetables (F&V) are an indispensable part of a healthy diet. The volatile and nonvolatile compounds present in F&V constitute unique flavor substances. This paper reviews the main flavor substances present in F&V, as well as the biosynthetic pathways and molecular regulation mechanisms of these compounds. A series of compounds introduced include aromatic substances, soluble sugars and organic acids, which constitute the key flavor substances of F&V. Esters, phenols, alcohols, amino acids and terpenes are the main volatile aromatic substances, and nonvolatile substances are represented by amino acids, fatty acids and carbohydrates; The combination of these ingredients is the cause of the sour, sweet, bitter, astringent and spicy taste of these foods. This provides a theoretical basis for the study of the interaction between volatile and nonvolatile substances in F&V, and also provides a research direction for the healthy development of food in the future.

Statistical and bioinformatic analysis of hemimethylation patterns in non-small cell lung cancer.

BACKGROUND: DNA methylation is an epigenetic event involving the addition of a methyl-group to a cytosine-guanine base pair (i.e., CpG site). It is associated with different cancers. Our research focuses on studying non-small cell lung cancer hemimethylation, which refers to methylation occurring on only one of the two DNA strands. Many studies often assume that methylation occurs on both DNA strands at a CpG site. However, recent publications show the existence of hemimethylation and its significant impact. Therefore, it is important to identify cancer hemimethylation patterns. METHODS: In this paper, we use the Wilcoxon signed rank test to identify hemimethylated CpG sites based on publicly available non-small cell lung cancer methylation sequencing data. We then identify two types of hemimethylated CpG clusters, regular and polarity clusters, and genes with large numbers of hemimethylated sites. Highly hemimethylated genes are then studied for their biological interactions using available bioinformatics tools. RESULTS: In this paper, we have conducted the first-ever investigation of hemimethylation in lung cancer. Our results show that hemimethylation does exist in lung cells either as singletons or clusters. Most clusters contain only two or three CpG sites. Polarity clusters are much shorter than regular clusters and appear less frequently. The majority of clusters found in tumor samples have no overlap with clusters found in normal samples, and vice versa. Several genes that are known to be associated with cancer are hemimethylated differently between the cancerous and normal samples. Furthermore, highly hemimethylated genes exhibit many different interactions with other genes that may be associated with cancer. Hemimethylation has diverse patterns and frequencies that are comparable between normal and tumorous cells. Therefore, hemimethylation may be related to both normal and tumor cell development. CONCLUSIONS: Our research has identified CpG clusters and genes that are hemimethylated in normal and lung tumor samples. Due to the potential impact of hemimethylation on gene expression and cell function, these clusters and genes may be important to advance our understanding of the development and progression of non-small cell lung cancer.

A splicing-independent function of SF2/ASF in microRNA processing.

Both splicing factors and microRNAs are important regulatory molecules that play key roles in posttranscriptional gene regulation. By miRNA deep sequencing, we identified 40 miRNAs that are differentially expressed upon ectopic overexpression of the splicing factor SF2/ASF. Here we show that SF2/ASF and one of its upregulated microRNAs (miR-7) can form a negative feedback loop: SF2/ASF promotes miR-7 maturation, and mature miR-7 in turn targets the 3'UTR of SF2/ASF to repress its translation. Enhanced microRNA expression is mediated by direct interaction between SF2/ASF and the primary miR-7 transcript to facilitate Drosha cleavage and is independent of SF2/ASF's function in splicing. Other miRNAs, including miR-221 and miR-222, may also be regulated by SF2/ASF through a similar mechanism. These results underscore a function of SF2/ASF in pri-miRNA processing and highlight the potential coordination between splicing control and miRNA-mediated gene repression in gene regulatory networks.

Translational profiling identifies a cascade of damage initiated in motor neurons and spreading to glia in mutant SOD1-mediated ALS.

Ubiquitous expression of amyotrophic lateral sclerosis (ALS)-causing mutations in superoxide dismutase 1 (SOD1) provokes noncell autonomous paralytic disease. By combining ribosome affinity purification and high-throughput sequencing, a cascade of mutant SOD1-dependent, cell type-specific changes are now identified. Initial mutant-dependent damage is restricted to motor neurons and includes synapse and metabolic abnormalities, endoplasmic reticulum (ER) stress, and selective activation of the PRKR-like ER kinase (PERK) arm of the unfolded protein response. PERK activation correlates with what we identify as a naturally low level of ER chaperones in motor neurons. Early changes in astrocytes occur in genes that are involved in inflammation and metabolism and are targets of the peroxisome proliferator-activated receptor and liver X receptor transcription factors. Dysregulation of myelination and lipid signaling pathways and activation of ETS transcription factors occur in oligodendrocytes only after disease initiation. Thus, pathogenesis involves a temporal cascade of cell type-selective damage initiating in motor neurons, with subsequent damage within glia driving disease propagation.

Mutant TDP-43 within motor neurons drives disease onset but not progression in amyotrophic lateral sclerosis.

Mutations in TDP-43 cause amyotrophic lateral sclerosis (ALS), a fatal paralytic disease characterized by degeneration and premature death of motor neurons. The contribution of mutant TDP-43-mediated damage within motor neurons was evaluated using mice expressing a conditional allele of an ALS-causing TDP-43 mutant (Q331K) whose broad expression throughout the central nervous system mimics endogenous TDP-43. TDP-43Q331K mice develop age- and mutant-dependent motor deficits from degeneration and death of motor neurons. Cre-recombinase-mediated excision of the TDP-43Q331K gene from motor neurons is shown to delay onset of motor symptoms and appearance of TDP-43-mediated aberrant nuclear morphology, and abrogate subsequent death of motor neurons. However, reduction of mutant TDP-43 selectively in motor neurons did not prevent age-dependent degeneration of axons and neuromuscular junction loss, nor did it attenuate astrogliosis or microgliosis. Thus, disease mechanism is non-cell autonomous with mutant TDP-43 expressed in motor neurons determining disease onset but progression defined by mutant acting within other cell types.

Comparing five statistical methods of differential methylation identification using bisulfite sequencing data.

We are presenting a comprehensive comparative analysis of five differential methylation (DM) identification methods: methylKit, BSmooth, BiSeq, HMM-DM, and HMM-Fisher, which are developed for bisulfite sequencing (BS) data. We summarize the features of these methods from several analytical aspects and compare their performances using both simulated and real BS datasets. Our comparison results are summarized below. First, parameter settings may largely affect the accuracy of DM identification. Different from default settings, modified parameter settings yield higher sensitivity and/or lower false positive rates. Second, all five methods show more accurate results when identifying simulated DM regions that are long and have small within-group variation, but they have low concordance, probably due to the different approaches they have used for DM identification. Third, HMM-DM and HMM-Fisher yield relatively higher sensitivity and lower false positive rates than others, especially in DM regions with large variation. Finally, we have found that among the three methods that involve methylation estimation (methylKit, BSmooth, and BiSeq), BiSeq can best present raw methylation signals. Therefore, based on these results, we suggest that users select DM identification methods based on the characteristics of their data and the advantages of each method.

HMM-DM: identifying differentially methylated regions using a hidden Markov model.

DNA methylation is an epigenetic modification involved in organism development and cellular differentiation. Identifying differential methylations can help to study genomic regions associated with diseases. Differential methylation studies on single-CG resolution have become possible with the bisulfite sequencing (BS) technology. However, there is still a lack of efficient statistical methods for identifying differentially methylated (DM) regions in BS data. We have developed a new approach named HMM-DM to detect DM regions between two biological conditions using BS data. This new approach first uses a hidden Markov model (HMM) to identify DM CG sites accounting for spatial correlation across CG sites and variation across samples, and then summarizes identified sites into regions. We demonstrate through a simulation study that our approach has a superior performance compared to BSmooth. We also illustrate the application of HMM-DM using a real breast cancer dataset.

HMM-Fisher: identifying differential methylation using a hidden Markov model and Fisher's exact test.

DNA methylation is an epigenetic event that plays an important role in regulating gene expression. It is important to study DNA methylation, especially differential methylation patterns between two groups of samples (e.g. patients vs. normal individuals). With next generation sequencing technologies, it is now possible to identify differential methylation patterns by considering methylation at the single CG site level in an entire genome. However, it is challenging to analyze large and complex NGS data. In order to address this difficult question, we have developed a new statistical method using a hidden Markov model and Fisher's exact test (HMM-Fisher) to identify differentially methylated cytosines and regions. We first use a hidden Markov chain to model the methylation signals to infer the methylation state as Not methylated (N), Partly methylated (P), and Fully methylated (F) for each individual sample. We then use Fisher's exact test to identify differentially methylated CG sites. We show the HMM-Fisher method and compare it with commonly cited methods using both simulated data and real sequencing data. The results show that HMM-Fisher outperforms the current available methods to which we have compared. HMM-Fisher is efficient and robust in identifying heterogeneous DM regions.

Targeted degradation of sense and antisense C9orf72 RNA foci as therapy for ALS and frontotemporal degeneration.

Expanded hexanucleotide repeats in the chromosome 9 open reading frame 72 (C9orf72) gene are the most common genetic cause of ALS and frontotemporal degeneration (FTD). Here, we identify nuclear RNA foci containing the hexanucleotide expansion (GGGGCC) in patient cells, including white blood cells, fibroblasts, glia, and multiple neuronal cell types (spinal motor, cortical, hippocampal, and cerebellar neurons). RNA foci are not present in sporadic ALS, familial ALS/FTD caused by other mutations (SOD1, TDP-43, or tau), Parkinson disease, or nonneurological controls. Antisense oligonucleotides (ASOs) are identified that reduce GGGGCC-containing nuclear foci without altering overall C9orf72 RNA levels. By contrast, siRNAs fail to reduce nuclear RNA foci despite marked reduction in overall C9orf72 RNAs. Sustained ASO-mediated lowering of C9orf72 RNAs throughout the CNS of mice is demonstrated to be well tolerated, producing no behavioral or pathological features characteristic of ALS/FTD and only limited RNA expression alterations. Genome-wide RNA profiling identifies an RNA signature in fibroblasts from patients with C9orf72 expansion. ASOs targeting sense strand repeat-containing RNAs do not correct this signature, a failure that may be explained, at least in part, by discovery of abundant RNA foci with C9orf72 repeats transcribed in the antisense (GGCCCC) direction, which are not affected by sense strand-targeting ASOs. Taken together, these findings support a therapeutic approach by ASO administration to reduce hexanucleotide repeat-containing RNAs and raise the potential importance of targeting expanded RNAs transcribed in both directions.

Mechanisms of activation and repression by the alternative splicing factors RBFOX1/2.

RBFOX1 and RBFOX2 are alternative splicing factors that are predominantly expressed in the brain and skeletal muscle. They specifically bind the RNA element UGCAUG, and regulate alternative splicing positively or negatively in a position-dependent manner. The molecular basis for the position dependence of these and other splicing factors on alternative splicing of their targets is not known. We explored the mechanisms of RBFOX splicing activation and repression using an MS2-tethering assay. We found that the Ala/Tyr/Gly-rich C-terminal domain is sufficient for exon activation when tethered to the downstream intron, whereas both the C-terminal domain and the central RRM are required for exon repression when tethered to the upstream intron. Using immunoprecipitation and mass spectrometry, we identified hnRNP H1, RALY, and TFG as proteins that specifically interact with the C-terminal domain of RBFOX1 and RBFOX2. RNA interference experiments showed that hnRNP H1 and TFG modulate the splicing activity of RBFOX1/2, whereas RALY had no effect. However, TFG is localized in the cytoplasm, and likely modulates alternative splicing indirectly.

DDX3X overexpression decreases dipeptide repeat proteins in a mouse model of C9ORF72-ALS/FTD.

Hexanucleotide repeat expansion in C9ORF72 (C9) is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). One of the proposed pathogenic mechanisms is the neurotoxicity arising from dipeptide repeat (DPR) proteins produced by repeat-associated non-AUG (RAN) translation. Therefore, reducing DPR levels emerges as a potential therapeutic strategy for C9ORF72-ALS/FTD. We previously identified an RNA helicase, DEAD-box helicase 3 X-linked (DDX3X), modulates RAN translation. DDX3X overexpression decreases poly-GP accumulation in C9ORF72-ALS/FTD patient-derived induced pluripotent stem cell (iPSC)-differentiated neurons (iPSNs) and reduces the glutamate-induced neurotoxicity. In this study, we examined the in vivo efficacy of DDX3X overexpression using a mouse model. We expressed exogenous DDX3X or GFP in the central nervous system (CNS) of the C9-500 ALS/FTD BAC transgenic or non-transgenic control mice using adeno-associated virus serotype 9 (AAV9). The DPR levels were significantly reduced in the brains of DDX3X-expressing C9-BAC mice compared to the GFP control even twelve months after virus delivery. Additionally, p62 aggregation was also decreased. No neuronal loss or neuroinflammatory response were detected in the DDX3X overexpressing C9-BAC mice. This work demonstrates that DDX3X overexpression effectively reduces DPR levels in vivo without provoking neuroinflammation or neurotoxicity, suggesting the potential of increasing DDX3X expression as a therapeutic strategy for C9ORF72-ALS/FTD.

KAT6A deficiency impairs cognitive functions through suppressing RSPO2/Wnt signaling in hippocampal CA3.

Intellectual disability (ID) affects ~2% of the population and ID-associated genes are enriched for epigenetic factors, including those encoding the largest family of histone lysine acetyltransferases (KAT5-KAT8). Among them is KAT6A, whose mutations cause KAT6A syndrome, with ID as a common clinical feature. However, the underlying molecular mechanism remains unknown. Here, we find that KAT6A deficiency impairs synaptic structure and plasticity in hippocampal CA3, but not in CA1 region, resulting in memory deficits in mice. We further identify a CA3-enriched gene Rspo2, encoding Wnt activator R-spondin 2, as a key transcriptional target of KAT6A. Deletion of Rspo2 in excitatory neurons impairs memory formation, and restoring RSPO2 expression in CA3 neurons rescues the deficits in Wnt signaling and learning-associated behaviors in Kat6a mutant mice. Collectively, our results demonstrate that KAT6A-RSPO2-Wnt signaling plays a critical role in regulating hippocampal CA3 synaptic plasticity and cognitive function, providing potential therapeutic targets for KAT6A syndrome and related neurodevelopmental diseases.

Elevated nuclear TDP-43 induces constitutive exon skipping.

BACKGROUND: Cytoplasmic inclusions and loss of nuclear TDP-43 are key pathological features found in several neurodegenerative disorders, suggesting both gain- and loss-of-function mechanisms of disease. To study gain-of-function, TDP-43 overexpression has been used to generate in vitro and in vivo model systems. METHODS: We analyzed RNA-seq datasets from mouse and human neurons overexpressing TDP-43 to explore species specific splicing patterns. We explored the dynamics between TDP-43 levels and exon repression in vitro. Furthermore we analyzed human brain samples and publicly available RNA datasets to explore the relationship between exon repression and disease. RESULTS: Our study shows that excessive levels of nuclear TDP-43 protein lead to constitutive exon skipping that is largely species-specific. Furthermore, while aberrant exon skipping is detected in some human brains, it is not correlated with disease, unlike the incorporation of cryptic exons that occurs after loss of TDP-43. CONCLUSIONS: Our findings emphasize the need for caution in interpreting TDP-43 overexpression data and stress the importance of controlling for exon skipping when generating models of TDP-43 proteinopathy.

Electrical impedance tomography as a bedside assessment tool for COPD treatment during hospitalization.

For patients with chronic obstructive pulmonary disease (COPD), the assessment of the treatment efficacy during hospitalization is of importance to the optimization of clinical treatments. Conventional spirometry might not be sensitive enough to capture the regional lung function development. The study aimed to evaluate the feasibility of using electrical impedance tomography (EIT) as an objective bedside evaluation tool for the treatment of acute exacerbation of COPD (AECOPD). Consecutive patients who required hospitalization due to AECOPD were included prospectively. EIT measurements were conducted at the time of admission and before the discharge simultaneously when a forced vital capacity maneuver was conducted. EIT-based heterogeneity measures of regional lung function were calculated based on the impedance changes over time. Surveys for attending doctors and patients were designed to evaluate the ease of use, feasibility, and overall satisfaction level to understand the acceptability of EIT measurements. Patient-reported outcome assessments were conducted. User's acceptance of EIT technology was investigated with a five-dimension survey. A total of 32 patients were included, and 8 patients were excluded due to the FVC maneuver not meeting the ATS criteria. Spirometry-based lung function was improved during hospitalization but not significantly different (FEV1 %pred.: 35.8% ± 6.7% vs. 45.3% ± 8.8% at admission vs. discharge; p = 0.11. FVC %pred.: 67.8% ± 0.4% vs. 82.6% ± 5.0%; p = 0.15. FEV1/FVC: 0.41 ± 0.09 vs. 0.42 ± 0.07, p = 0.71). The symptoms of COPD were significantly improved, but the correlations between the improvement of symptoms and spirometry FEV1 and FEV1/FVC were low (R = 0.1 and -0.01, respectively). The differences in blood gasses and blood tests were insignificant. All but one EIT-based regional lung function parameter were significantly improved after hospitalization. The results highly correlated with the patient-reported outcome assessment (R > 0.6, p < 0.001). The overall acceptability score of EIT measurement for both attending physicians and patients was high (4.1 ± 0.8 for physicians, 4.5 ± 0.5 for patients out of 5). These results demonstrated that it was feasible and acceptable to use EIT as an objective bedside evaluation tool for COPD treatment efficacy.

Comparing a few SNP calling algorithms using low-coverage sequencing data.

BACKGROUND: Many Single Nucleotide Polymorphism (SNP) calling programs have been developed to identify Single Nucleotide Variations (SNVs) in next-generation sequencing (NGS) data. However, low sequencing coverage presents challenges to accurate SNV identification, especially in single-sample data. Moreover, commonly used SNP calling programs usually include several metrics in their output files for each potential SNP. These metrics are highly correlated in complex patterns, making it extremely difficult to select SNPs for further experimental validations. RESULTS: To explore solutions to the above challenges, we compare the performance of four SNP calling algorithm, SOAPsnp, Atlas-SNP2, SAMtools, and GATK, in a low-coverage single-sample sequencing dataset. Without any post-output filtering, SOAPsnp calls more SNVs than the other programs since it has fewer internal filtering criteria. Atlas-SNP2 has stringent internal filtering criteria; thus it reports the least number of SNVs. The numbers of SNVs called by GATK and SAMtools fall between SOAPsnp and Atlas-SNP2. Moreover, we explore the values of key metrics related to SNVs' quality in each algorithm and use them as post-output filtering criteria to filter out low quality SNVs. Under different coverage cutoff values, we compare four algorithms and calculate the empirical positive calling rate and sensitivity. Our results show that: 1) the overall agreement of the four calling algorithms is low, especially in non-dbSNPs; 2) the agreement of the four algorithms is similar when using different coverage cutoffs, except that the non-dbSNPs agreement level tends to increase slightly with increasing coverage; 3) SOAPsnp, SAMtools, and GATK have a higher empirical calling rate for dbSNPs compared to non-dbSNPs; and 4) overall, GATK and Atlas-SNP2 have a relatively higher positive calling rate and sensitivity, but GATK calls more SNVs. CONCLUSIONS: Our results show that the agreement between different calling algorithms is relatively low. Thus, more caution should be used in choosing algorithms, setting filtering parameters, and designing validation studies. For reliable SNV calling results, we recommend that users employ more than one algorithm and use metrics related to calling quality and coverage as filtering criteria.

MethyQA: a pipeline for bisulfite-treated methylation sequencing quality assessment.

BACKGROUND: DNA methylation is an epigenetic event that adds a methyl-group to the 5' cytosine. This epigenetic modification can significantly affect gene expression in both normal and diseased cells. Hence, it is important to study methylation signals at the single cytosine site level, which is now possible utilizing bisulfite conversion technique (i.e., converting unmethylated Cs to Us and then to Ts after PCR amplification) and next generation sequencing (NGS) technologies. Despite the advances of NGS technologies, certain quality issues remain. Some of the more prevalent quality issues involve low per-base sequencing quality at the 3' end, PCR amplification bias, and bisulfite conversion rates. Therefore, it is important to conduct quality assessment before downstream analysis. To the best of our knowledge, no existing software packages can generally assess the quality of methylation sequencing data generated based on different bisulfite-treated protocols. RESULTS: To conduct the quality assessment of bisulfite methylation sequencing data, we have developed a pipeline named MethyQA. MethyQA combines currently available open-source software packages with our own custom programs written in Perl and R. The pipeline can provide quality assessment results for tens of millions of reads in under an hour. The novelty of our pipeline lies in its examination of bisulfite conversion rates and of the DNA sequence structure of regions that have different conversion rates or coverage. CONCLUSIONS: MethyQA is a new software package that provides users with a unique insight into the methylation sequencing data they are researching. It allows the users to determine the quality of their data and better prepares them to address the research questions that lie ahead. Due to the speed and efficiency at which MethyQA operates, it will become an important tool for studies dealing with bisulfite methylation sequencing data.