A cost-effective blood DNA methylation-based age estimation method in domestic cats, Tsushima leopard cats (Prionailurus bengalensis euptilurus) and Panthera species, using targeted bisulphite sequencing and machine learning models.

Individual age can be used to design more efficient and suitable management plans in both in situ and ex situ conservation programmes for targeted wildlife species. DNA methylation is a promising marker of epigenetic ageing that can accurately estimate age from small amounts of biological material, which can be collected in a minimally invasive manner. In this study, we sequenced five targeted genetic regions and used 8-23 selected CpG sites to build age estimation models using machine learning methods at only about $3-7 per sample. Blood samples of seven Felidae species were used, ranging from small to big, and domestic to endangered species: domestic cats (Felis catus, 139 samples), Tsushima leopard cats (Prionailurus bengalensis euptilurus, 84 samples) and five Panthera species (96 samples). The models achieved satisfactory accuracy, with the mean absolute error of the most accurate models recorded at 1.966, 1.348 and 1.552 years in domestic cats, Tsushima leopard cats and Panthera spp. respectively. We developed the models in domestic cats and Tsushima leopard cats, which were applicable to individuals regardless of health conditions; therefore, these models are applicable to samples collected from individuals with diverse characteristics, which is often the case in conservation. We also showed the possibility of developing universal age estimation models for the five Panthera spp. using only two of the five genetic regions. We do not recommend building a common age estimation model for all the target species using our markers, because of the degraded performance of models that included all species.

Quality assessment of enzymatic methyl-seq library constructed using crude cell lysate.

Enzymatic methyl-seq (EM-seq), an enzyme-based method, identifies genome-wide DNA methylation, which enables us to obtain reliable methylome data from purified genomic DNA by avoiding bisulfite-induced DNA damage. However, the loss of DNA during purification hinders the methylome analysis of limited samples. The crude DNA extraction method is the quickest and minimal sample loss approach for obtaining useable DNA without requiring additional dissolution and purification. However, it remains unclear whether crude DNA can be used directly for EM-seq library construction. In this study, we aimed to assess the quality of EM-seq libraries prepared directly using crude DNA. The crude DNA-derived libraries provided appropriate fragment sizes and concentrations for sequencing similar to those of the purified DNA-derived libraries. However, the sequencing results of crude samples exhibited lower reference sequence mapping efficiencies than those of the purified samples. Additionally, the lower-input crude DNA-derived sample exhibited a marginally lower cytosine-to-thymine conversion efficiency and hypermethylated pattern around gene regulatory elements than the higher-input crude DNA- or purified DNA-derived samples. In contrast, the methylation profiles of the crude and purified samples exhibited a significant correlation. Our findings indicate that crude DNA can be used as a raw material for EM-seq library construction.

LuxHMM: DNA methylation analysis with genome segmentation via hidden Markov model.

BACKGROUND: DNA methylation plays an important role in studying the epigenetics of various biological processes including many diseases. Although differential methylation of individual cytosines can be informative, given that methylation of neighboring CpGs are typically correlated, analysis of differentially methylated regions is often of more interest. RESULTS: We have developed a probabilistic method and software, LuxHMM, that uses hidden Markov model (HMM) to segment the genome into regions and a Bayesian regression model, which allows handling of multiple covariates, to infer differential methylation of regions. Moreover, our model includes experimental parameters that describe the underlying biochemistry in bisulfite sequencing and model inference is done using either variational inference for efficient genome-scale analysis or Hamiltonian Monte Carlo (HMC). CONCLUSIONS: Analyses of real and simulated bisulfite sequencing data demonstrate the competitive performance of LuxHMM compared with other published differential methylation analysis methods.

Baseline composition and microbial quality assessment of raw milk from small ruminants and Maghrebi camels in the oasis area of Tunisia.

The milk quality and characteristics of the local Gharbi sheep and autochthonous goat population were studied and compared to those of the local Maghrebi camel. Milk samples from 378 lactating animals raised in the Tunisian oasis region were obtained and processed for various physicochemical compositions (pH, density, acidity, dry matter, fat, protein, lactose, casein, ash, and casein-protein ratio), mineral concentrations (Ca, P, Na, and K), and bacteriological properties (total mesophilic aerobic bacteria (TMAB), total coliform count (TCC), lactic acid bacteria (LAB), sulfite-reducing Clostridium (CSR), yeast and molds (Y/M), Staphylococcus aureus (S. aureus), Escherichia coli (E. coli), and Salmonella) using standard methods. Milk from sheep breeds had a higher average of all physical parameters (pH, density, and dornic acidity) than milk from goat species. The sheep population produced milk with a similar pH to the camel population, but with a higher density and acidity content. The pH and acidity were higher in Neggas than in goat species, while density was similar in both. For chemical composition, the results showed significant heterogeneity in milk content across all species. Except for the casein-protein ratio, which favors goat species, the analysis indicates that sheep species were superior to populations of goats and camels in all chemical compositions. The present results showed considerable variation in the mineral content of milk from different species. The levels of calcium and phosphorus are higher in sheep than in goat and camel milk. Compared to small ruminants, milk from camels is the richest in Na and K. Additionally, more calcium is present in the milk of camels than that of goats. Goat milk, the lowest in Ca and Na, contains more P than camel milk and more K than sheep's milk on average. The poorest microbial quality was that of camel milk for all bacterial counts. Based on TMAB, TCC, and E. coli counts, the microbiological quality of goat milk was higher than that of ovine milk, while ovine milk had better quality based on LAB, Y/M, and S. aureus values. For Escherichia coli and Staphylococcus aureus, there were no significant variations between the species studied. Results showed that all milk samples studied were completely free of two dangerous pathogens, Salmonella and sulfite-reducing Clostridium. The bacteriological quality of small ruminant's milk was acceptable and met the regulatory limits set by Tunisian dairy legislation. Regarding camel milk, the microbial analysis revealed poor quality that exceeds standard criteria.

Emission of volatile sulphur compounds during swine manure composting: Source identification, odour mitigation and assessment.

This study aimed to identify the sources of volatile sulphur compounds (VSCs) and evaluate their mitigation by ferric oxide (Fe2O3) during swine manure composting. Four chemicals, including l-cysteine, l-methionine, sodium sulphite, and sodium sulphate, were further added to simulate organic and inorganic sulphur-containing substances in swine manure to track VSC sources during composting. Results show that sulphur simulants induced the emission of six common VSCs, including methyl sulphide (Me2S), dimethyl sulphide (Me2SS), carbonyl sulphide (COS), carbon disulphide (CS2), methyl mercaptan (MeSH), and ethyl mercaptan (EtSH), during swine manure composting. Of them, COS, CS2, MeSH and Me2SS were predominantly contributed by the biodegradation of methionine and cysteine, while Me2S and EtSH were dominated by the reduction of sulphite and sulphate. Further Fe2O3 addition at 1.5 % of total wet weight of composting materials immobilized elemental sulphur and inhibited sulphate reduction to reduce the emission of VSCs by 46.7-80.9 %. Furthermore, odour assessment indicated that adding Fe2O3 into composting piles significantly reduced the odour intensity level to below 4, the odour value of VSCs by 47.1-81.3 %, and thus the non-carcinogenic risk by 68.4 %.

Efficient degradation and deiodination of iopamidol by UV/sulfite process: Assessment of typical process parameters and transformation paths.

Iopamidol (IPM) is widely used in medical clinical examination and treatment and has immeasurable harm to the ecological environment. The combination of UV and sulfite (UV/sulfite) process was developed to degrade IPM in this study. In contrast to that almost no removal of IPM was observed under sulfite reduction alone, the UV/sulfite process could efficiently reductively degrade IPM with the observed rate constant (kobs) of 2.08 min-1, which was nearly 4 times that of UV irradiation alone. The major active species in the UV/sulfite process were identified as hydrated electrons (eaq-) by employing active species scavengers. The influence of the initial pH, sulfite dosage, IPM concentration, UV intensity and common water matrix were evaluated. The degradation of IPM reached nearly 100% within only 2.5 min at pH 9, and kobs increased at higher initial sulfite dosages and greater UV intensities. HCO3- had a limited effect on the degradation of IPM, while humic acid (HA) was found to be a strong inhibitor in the UV/sulfite process. With the synergistic action of UV/sulfite, most of the iodine in IPM was found to release in the form of iodide ions (up to approximately 98%), and a few formed iodide-containing organic compounds, reducing significantly the toxicity of degradation products. Under direct UV irradiation and free radical reduction (mainly eaq-), 15 transformation intermediates of IPM were produced by amide hydrolysis, deiodination, hydroxyl radical addition and hydrogen abstraction reactions, in which free radical attack accounted for the main part. Consequently, the UV/sulfite process has a strong potential for IPM degradation in aquatic environments.

Direct red 89 dye degradation by advanced oxidation process using sulfite and zero valent under ultraviolet irradiation: Toxicity assessment and adaptive neuro-fuzzy inference systems modeling.

Sulfate-based advanced oxidation process mediated by zero-valent iron (ZVI) and ultraviolet radiation for the decomposition of sulfite salts resulted in the formation of strong oxidizing species (sulfate and hydroxide radicals) in aqueous solution is reported. Degradation of direct red 89 (DR89) dye via UV/ZVI/sulfite process was systematically investigated to evaluate the effect of pH, ZVI dose, sulfite, initial DR89 concentration, and reaction time on DR89 degradation. The synergy factor of UV/ZVI/sulfite process was found to be 2.23-times higher than the individual processes including ZVI, sulfite and UV. By increasing the ZVI dose from 100 mg/L to 300 mg/L, dye degradation was linearly enhanced from 67.12 ± 3.36% to 82.40 ± 4.12% by the UV/ZVI/sulfite process due to enhanced ZVI corrosion and sulfite activation. The highest degradation efficiency of 99.61 ± 0.02% was observed at pH of 5.0, [ZVI]0 = 300 mg/L, and [sulfite]0 = 400 mg/L. Toxicity assessment by Lepidium sativum demonstrated that treated dye solution by UV/ZVI/sulfite was within the non-toxic range. The application of optimal adaptive neuro-fuzzy inference system (ANFIS) to predict DR89 degradation indicated high accuracy of ANFIS model (R2 = 0.97 and RMSE = 0.051) via the UV/ZVI/sulfite process. It is suggested that UV/ZVI/sulfite process is suitable for industrial wastewater treatment.

Analysis and Performance Assessment of the Whole Genome Bisulfite Sequencing Data Workflow: Currently Available Tools and a Practical Guide to Advance DNA Methylation Studies.

DNA methylation is associated with transcriptional repression, genomic imprinting, stem cell differentiation, embryonic development, and inflammation. Aberrant DNA methylation can indicate disease states, including cancer and neurological disorders. Therefore, the prevalence and location of 5-methylcytosine in the human genome is a topic of interest. Whole-genome bisulfite sequencing (WGBS) is a high-throughput method for analyzing DNA methylation. This technique involves library preparation, alignment, and quality control. Advancements in epigenetic technology have led to an increase in DNA methylation studies. This review compares the detailed experimental methodology of WGBS using accessible and up-to-date analysis tools. Practical codes for WGBS data processing are included as a general guide to assist progress in DNA methylation studies through a comprehensive case study.

Improvement of Floxin photocatalytic degradability in the presence of sulfite: Performance, kinetic, degradation pathway, energy consumption and total cost of system.

In this study, photocatalytic degradability of Floxin antibiotic by UV/ZnO/sulfite (UZS) advanced oxidation process was evaluated. The degradation rate of Floxin antibiotic by UV/ZnO (UZ) and UV alone processes were 30% and 15%, respectively, within 5 min. It was observed sulfite has a synergistic effect on the performance of UZ, as the complete destruction of Floxin was achieved when sulfite was introduced into the photocatalytic medium. The complete degradation of Floxin by UZS was obtained at pH of 12.0, sulfite/ZnO molar ratio of 1:3 after 5 min of reaction. According to kinetic studies, the observed rate of Floxin degradation (robs (mg L-1 min)) by UZS was 63 and 25 times that of UV alone and UZS, respectively. The values of energy consumption and the total cost for UV alone, UZ and UZS processes were estimated to be (50 kWh m-3 and 1.4 $ m-3), (20 kWh m-3 and 0.98 $ m-3) and (0.78 kWh m-3 and 0.82 $ m-3), respectively.

Sulfite pretreatment enhances the biodegradability of primary sludge and waste activated sludge towards cost-effective and carbon-neutral sludge treatment.

Sulfite pretreatment is effective for enhancing the biodegradability of waste activated sludge (WAS). However, the mixture of primary sludge (PS) and WAS is normally collected and treated together, and the effect of sulfite on the sludge mixture remains unclear. Here, we reported that sulfite pretreatment could disintegrate the flocs of the sludge mixture and improve sludge biodegradability. The substrate release from the sludge mixture after sulfite pretreatment (100, 300, and 500 mg SO32--S/L) could be enhanced with soluble chemical oxygen demand by up to 1.58 times, soluble nitrogen by up to 1.38 times, soluble polysaccharides by up to 3.04 times and proteins by up to 6.08 times. Further analysis on flocs structure suggests that sulfite may destruct the functional groups of proteins and amino acids and lyse the main structure of sludge cell walls. Moreover, methane production from the sludge mixture could be enhanced by 16% after pretreated by sulfite at 500 mg S/L (i.e., 123.59 CH4/kg VSadded), whereas the digested sludge volume could be reduced by 1.51 times. Environmental implications suggest that sulfite pretreatment could save sludge treatment costs by 1.06 $/PE/y and reduce CO2-equivalent emissions by 5.19 kg CO2/PE/y, demonstrating its potential as a cost-effective and carbon-neutral technology for sludge management.

Targeted bisulfite sequencing: A novel tool for the assessment of DNA methylation with high sensitivity and increased coverage.

DNA methylation analysis is increasingly used in stress research. Available methods are expensive, laborious and often limited by either the analysis of short CpG stretches or low assay sensitivity. Here, we present a cost-efficient next generation sequencing-based strategy for the simultaneous investigation of multiple candidate genes in large cohorts. To illustrate the method, we present analysis of four candidate genes commonly assessed in psychoneuroendocrine research: Glucocorticoid receptor (NR3C1), Serotonin transporter (SLC6A4), FKBP Prolyl isomerase 5 (FKBP5), and the Oxytocin receptor (OXTR). DNA methylation standards (100 %; 75 %; 50 %; 25 % and 0 %) and DNA of a female and male donor were bisulfite treated in three independent trials and were used to generate sequencing libraries for 42 CpGs from the NR3C1 1 F promoter region, 84 CpGs of the SLC6A4 5' regulatory region, 5 CpGs located in FKBP5 intron 7, and additional 12 CpGs located in a potential enhancer element in intron 3 of the OXTR. In addition, DNA of 45 patients with borderline personality disorder (BPD) and 45 healthy controls was assayed. Multiplex libraries of all samples were sequenced on a MiSeq system and analyzed for mean methylation values of all CpG sites using amplikyzer2 software. Results indicated excellent accuracy of the assays when investigating replicates generated from the same bisulfite converted DNA, and very high linearity (R2 > 0.9) of the assays shown by the analysis of differentially methylated DNA standards. Comparing DNA methylation between BPD and healthy controls revealed no biologically relevant differences. The technical approach as described here facilitates targeted DNA methylation analysis and represents a highly sensitive, cost-efficient and high throughput tool to close the gap between coverage and precision in epigenetic research of stress-associated phenotypes.

A cost-effective approach to DNA methylation detection by Methyl Sensitive DArT sequencing.

Several studies suggest the relation of DNA methylation to diseases in humans and important phenotypes in plants drawing attention to this epigenetic mark as an important source of variability. In the last decades, several methodologies were developed to assess the methylation state of a genome. However, there is still a lack of affordable and precise methods for genome wide analysis in large sample size studies. Methyl sensitive double digestion MS-DArT sequencing method emerges as a promising alternative for methylation profiling. We developed a computational pipeline for the identification of DNA methylation using MS-DArT-seq data and carried out a pilot study using the Eucalyptus grandis tree sequenced for the species reference genome. Using a statistic framework as in differential expression analysis, 72,515 genomic sites were investigated and 5,846 methylated sites identified, several tissue specific, distributed along the species 11 chromosomes. We highlight a bias towards identification of DNA methylation in genic regions and the identification of 2,783 genes and 842 transposons containing methylated sites. Comparison with WGBS, DNA sequencing after treatment with bisulfite, data demonstrated a precision rate higher than 95% for our approach. The availability of a reference genome is useful for determining the genomic context of methylated sites but not imperative, making this approach suitable for any species. Our approach provides a cost effective, broad and reliable examination of DNA methylation profile on MspI/HpaII restriction sites, is fully reproducible and the source code is available on GitHub (https://github.com/wendelljpereira/ms-dart-seq).

A hidden markov model for identifying differentially methylated sites in bisulfite sequencing data.

DNA methylation studies have enabled researchers to understand methylation patterns and their regulatory roles in biological processes and disease. However, only a limited number of statistical approaches have been developed to provide formal quantitative analysis. Specifically, a few available methods do identify differentially methylated CpG (DMC) sites or regions (DMR), but they suffer from limitations that arise mostly due to challenges inherent in bisulfite sequencing data. These challenges include: (1) that read-depths vary considerably among genomic positions and are often low; (2) both methylation and autocorrelation patterns change as regions change; and (3) CpG sites are distributed unevenly. Furthermore, there are several methodological limitations: almost none of these tools is capable of comparing multiple groups and/or working with missing values, and only a few allow continuous or multiple covariates. The last of these is of great interest among researchers, as the goal is often to find which regions of the genome are associated with several exposures and traits. To tackle these issues, we have developed an efficient DMC identification method based on Hidden Markov Models (HMMs) called "DMCHMM" which is a three-step approach (model selection, prediction, testing) aiming to address the aforementioned drawbacks. Our proposed method is different from other HMM methods since it profiles methylation of each sample separately, hence exploiting inter-CpG autocorrelation within samples, and it is more flexible than previous approaches by allowing multiple hidden states. Using simulations, we show that DMCHMM has the best performance among several competing methods. An analysis of cell-separated blood methylation profiles is also provided.

Optimization of metals extraction from spent lithium-ion batteries by sulphuric acid and sodium metabisulphite through a techno-economic evaluation.

The main factors that affect the extraction of metals from spent lithium-ion batteries by acid leaching using H2SO4, and sodium metabisulphite, were evaluated and optimized through a set of experiments, framed by a techno-economic approach. The maximum value of the profit response was obtained with the highest possible values of acid concentration (2.5 M) and time (2 h), a liquid/solid ratio of 5 L/kg, and the lowest possible value of temperature (40 °C). After leaching, the electrodes active material contained in the metals decreased, while it was still significant in the graphite, as observed by scanning electron microscopy-energy dispersive spectrometry and x-ray powder diffraction. Even though the performed economic evaluation was a summarized outline it can be considered suitable to compare different leaching conditions and to determine the possible best combinations of factors that can optimize the profit response.

Whole-genome bisulfite sequencing with improved accuracy and cost.

DNA methylation patterns in the genome both reflect and help to mediate transcriptional regulatory processes. The digital nature of DNA methylation, present or absent on each allele, makes this assay capable of quantifying events in subpopulations of cells, whereas genome-wide chromatin studies lack the same quantitative capacity. Testing DNA methylation throughout the genome is possible using whole-genome bisulfite sequencing (WGBS), but the high costs associated with the assay have made it impractical for studies involving more than limited numbers of samples. We have optimized a new transposase-based library preparation assay for the Illumina HiSeq X platform suitable for limited amounts of DNA and providing a major cost reduction for WGBS. By incorporating methylated cytosines during fragment end repair, we reveal an end-repair artifact affecting 1%-2% of reads that we can remove analytically. We show that the use of a high (G + C) content spike-in performs better than PhiX in terms of bisulfite sequencing quality. As expected, the loci with transposase-accessible chromatin are DNA hypomethylated and enriched in flanking regions by post-translational modifications of histones usually associated with positive effects on gene expression. Using these transposase-accessible loci to represent the cis-regulatory loci in the genome, we compared the representation of these loci between WGBS and other genome-wide DNA methylation assays, showing WGBS to outperform substantially all of the alternatives. We conclude that it is now technologically and financially feasible to perform WGBS in larger numbers of samples with greater accuracy than previously possible.

HAM-TBS: high-accuracy methylation measurements via targeted bisulfite sequencing.

BACKGROUND: The ability to accurately and efficiently measure DNA methylation is critical to advance the understanding of this epigenetic mechanism and its contribution to common diseases. Here, we present a highly accurate method to measure methylation using bisulfite sequencing (termed HAM-TBS). This novel method is able to assess DNA methylation in multiple samples with high accuracy in a cost-effective manner. We developed this assay for the FKBP5 locus, an important gene in the regulation of the stress system and previously linked to stress-related disorders, but the method is applicable to any locus of interest. RESULTS: HAM-TBS enables multiplexed analyses of up to 96 samples and regions spanning 10 kb using the Illumina MiSeq. It incorporates a triplicate bisulfite conversion step, pooled target enrichment via PCR, PCR-free library preparation and a minimum coverage of 1000×. TBS was able to resolve DNA methylation levels with a mean accuracy of 0.72%. Using this method, we designed and validated a targeted panel to specifically assess regulatory regions within the FKBP5 locus that are not covered in commercially available DNA methylation arrays. CONCLUSIONS: HAM-TBS represents a highly accurate, medium-throughput sequencing approach for robust detection of DNA methylation changes in specific target regions.

METHimpute: imputation-guided construction of complete methylomes from WGBS data.

BACKGROUND: Whole-genome bisulfite sequencing (WGBS) has become the standard method for interrogating plant methylomes at base resolution. However, deep WGBS measurements remain cost prohibitive for large, complex genomes and for population-level studies. As a result, most published plant methylomes are sequenced far below saturation, with a large proportion of cytosines having either missing data or insufficient coverage. RESULTS: Here we present METHimpute, a Hidden Markov Model (HMM) based imputation algorithm for the analysis of WGBS data. Unlike existing methods, METHimpute enables the construction of complete methylomes by inferring the methylation status and level of all cytosines in the genome regardless of coverage. Application of METHimpute to maize, rice and Arabidopsis shows that the algorithm infers cytosine-resolution methylomes with high accuracy from data as low as 6X, compared to data with 60X, thus making it a cost-effective solution for large-scale studies. CONCLUSIONS: METHimpute provides methylation status calls and levels for all cytosines in the genome regardless of coverage, thus yielding complete methylomes even with low-coverage WGBS datasets. The method has been extensively tested in plants, but should also be applicable to other species. An implementation is available on Bioconductor.

A survey of the approaches for identifying differential methylation using bisulfite sequencing data.

DNA methylation is an important epigenetic mechanism that plays a crucial role in cellular regulatory systems. Recent advancements in sequencing technologies now enable us to generate high-throughput methylation data and to measure methylation up to single-base resolution. This wealth of data does not come without challenges, and one of the key challenges in DNA methylation studies is to identify the significant differences in the methylation levels of the base pairs across distinct biological conditions. Several computational methods have been developed to identify differential methylation using bisulfite sequencing data; however, there is no clear consensus among existing approaches. A comprehensive survey of these approaches would be of great benefit to potential users and researchers to get a complete picture of the available resources. In this article, we present a detailed survey of 22 such approaches focusing on their underlying statistical models, primary features, key advantages and major limitations. Importantly, the intrinsic drawbacks of the approaches pointed out in this survey could potentially be addressed by future research.

Methyl-CpG-Binding Domain Sequencing: MBD-seq.

Detailed biological knowledge about the potential importance of the methylome is typically lacking for common diseases. Therefore, methylome-wide association studies (MWAS) are critical to detect disease relevant methylation sites. Methyl-CpG-binding domain sequencing (MBD-seq) offers potential advantages compared to antibody-based enrichment, but performance depends critically on using an optimal protocol. Using an optimized protocol, MBD-seq can approximate the sensitivity/specificity obtained with whole-genome bisulfite sequencing, but at a fraction of the costs and time to complete the project. Thus, MBD-seq offers a comprehensive first pass at the CpG methylome and is economically feasible with the samples sizes required for MWAS.

Association testing of bisulfite-sequencing methylation data via a Laplace approximation.

MOTIVATION: Epigenome-wide association studies can provide novel insights into the regulation of genes involved in traits and diseases. The rapid emergence of bisulfite-sequencing technologies enables performing such genome-wide studies at the resolution of single nucleotides. However, analysis of data produced by bisulfite-sequencing poses statistical challenges owing to low and uneven sequencing depth, as well as the presence of confounding factors. The recently introduced Mixed model Association for Count data via data AUgmentation (MACAU) can address these challenges via a generalized linear mixed model when confounding can be encoded via a single variance component. However, MACAU cannot be used in the presence of multiple variance components. Additionally, MACAU uses a computationally expensive Markov Chain Monte Carlo (MCMC) procedure, which cannot directly approximate the model likelihood. RESULTS: We present a new method, Mixed model Association via a Laplace ApproXimation (MALAX), that is more computationally efficient than MACAU and allows to model multiple variance components. MALAX uses a Laplace approximation rather than MCMC based approximations, which enables to directly approximate the model likelihood. Through an extensive analysis of simulated and real data, we demonstrate that MALAX successfully addresses statistical challenges introduced by bisulfite-sequencing while controlling for complex sources of confounding, and can be over 50% faster than the state of the art. AVAILABILITY AND IMPLEMENTATION: The full source code of MALAX is available at https://github.com/omerwe/MALAX . CONTACT: omerw@cs.technion.ac.il or ehalperin@cs.ucla.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.