Human Group IIA Phospholipase A2-Three Decades on from Its Discovery.

Phospholipase A2 (PLA2) enzymes were first recognized as an enzyme activity class in 1961. The secreted (sPLA2) enzymes were the first of the five major classes of human PLA2s to be identified and now number nine catalytically-active structurally homologous proteins. The best-studied of these, group IIA sPLA2, has a clear role in the physiological response to infection and minor injury and acts as an amplifier of pathological inflammation. The enzyme has been a target for anti-inflammatory drug development in multiple disorders where chronic inflammation is a driver of pathology since its cloning in 1989. Despite intensive effort, no clinically approved medicines targeting the enzyme activity have yet been developed. This review catalogues the major discoveries in the human group IIA sPLA2 field, focusing on features of enzyme function that may explain this lack of success and discusses future research that may assist in realizing the potential benefit of targeting this enzyme. Functionally-selective inhibitors together with isoform-selective inhibitors are necessary to limit the apparent toxicity of previous drugs. There is also a need to define the relevance of the catalytic function of hGIIA to human inflammatory pathology relative to its recently-discovered catalysis-independent function.

A humanized orthotopic tumor microenvironment alters the bone metastatic tropism of prostate cancer cells.

Prostate cancer (PCa) is the second most commonly diagnosed cancer in men, and bone is the most frequent site of metastasis. The tumor microenvironment (TME) impacts tumor growth and metastasis, yet the role of the TME in PCa metastasis to bone is not fully understood. We used a tissue-engineered xenograft approach in NOD-scid IL2Rγnull (NSG) mice to incorporate two levels of humanization; the primary tumor and TME, and the secondary metastatic bone organ. Bioluminescent imaging, histology, and immunohistochemistry were used to study metastasis of human PC-3 and LNCaP PCa cells from the prostate to tissue-engineered bone. Here we show pre-seeding scaffolds with human osteoblasts increases the human cellular and extracellular matrix content of bone constructs, compared to unseeded scaffolds. The humanized prostate TME showed a trend to decrease metastasis of PC-3 PCa cells to the tissue-engineered bone, but did not affect the metastatic potential of PCa cells to the endogenous murine bones or organs. On the other hand, the humanized TME enhanced LNCaP tumor growth and metastasis to humanized and murine bone. Together this demonstrates the importance of the TME in PCa bone tropism, although further investigations are needed to delineate specific roles of the TME components in this context.

KLK4 Induces Anti-Tumor Effects in Human Xenograft Mouse Models of Orthotopic and Metastatic Prostate Cancer.

Recent reports have suggested the role of kallikrein-related peptidase 4 (KLK4) to be that of remodeling the tumor microenvironment in many cancers, including prostate cancer. Notably, these studies have suggested a pro-tumorigenic role for KLK4, especially in prostate cancer. However, these have been primarily in vitro studies, with limited in vivo studies performed to date. Herein, we employed an orthotopic inoculation xenograft model to mimic the growth of primary tumors, and an intracardiac injection to induce metastatic dissemination to determine the in vivo tumorigenic effects of KLK4 overexpressed in PC3 prostate cancer cells. Notably, we found that these KLK4-expressing cells gave rise to smaller localized tumors and decreased metastases than the parent PC-3 cells. To our knowledge, this is the first report of an anti-tumorigenic effect of KLK4, particularly in prostate cancer. These findings also provide a cautionary tale of the need for in vivo analyses to substantiate in vitro experimental data.

Targeted beta therapy of prostate cancer with 177Lu-labelled Miltuximab® antibody against glypican-1 (GPC-1).

PURPOSE: Chimeric antibody Miltuximab®, a human IgG1 engineered from the parent antibody MIL-38, is in clinical development for solid tumour therapy. Miltuximab® targets glypican-1 (GPC-1), a cell surface protein involved in tumour growth, which is overexpressed in solid tumours, including prostate cancer (PCa). This study investigated the potential of 89Zr-labelled Miltuximab® as an imaging agent, and 177Lu-labelled Miltuximab® as a targeted beta therapy, in a mouse xenograft model of human prostate cancer. METHODS: Male BALB/c nude mice were inoculated subcutaneously with GPC-1-positive DU-145 PCa cells. In imaging and biodistribution studies, mice bearing palpable tumours received (a) 2.62 MBq [89Zr]Zr-DFO-Miltuximab® followed by PET-CT imaging, or (b) 6 MBq [177Lu]Lu-DOTA-Miltuximab® by Cerenkov imaging, and ex vivo assessment of biodistribution. In an initial tumour efficacy study, mice bearing DU-145 tumours were administered intravenously with 6 MBq [177Lu]Lu-DOTA-Miltuximab® or control DOTA-Miltuximab® then euthanised after 27 days. In a subsequent survival efficacy study, tumour-bearing mice were given 3 or 10 MBq of [177Lu]Lu-DOTA-Miltuximab®, or control, and followed up to 120 days. RESULTS: Antibody accumulation in DU-145 xenografts was detected by PET-CT imaging using [89Zr]Zr-DFO-Miltuximab® and confirmed by Cerenkov luminescence imaging post injection of [177Lu]Lu-DOTA-Miltuximab®. Antibody accumulation was higher (% IA/g) in tumours than other organs across multiple time points. A single injection with 6 MBq of [177Lu]Lu-DOTA-Miltuximab® significantly inhibited tumour growth as compared with DOTA-Miltuximab® (control). In the survival study, mice treated with 10 MBq [177Lu]Lu-DOTA-Miltuximab® had significantly prolonged survival (mean 85 days) versus control (45 days), an effect associated with increased cancer cell apoptosis. Tissue histopathology assessment showed no abnormalities associated with [177Lu]Lu-DOTA-Miltuximab®, in line with other observations of tolerability, including body weight stability. CONCLUSION: These findings demonstrate the potential utility of Miltuximab® as a PET imaging agent ([89Zr]Zr-DFO-Miltuximab®) and a beta therapy ([177Lu]Lu-DOTA-Miltuximab®) in patients with PCa or other GPC-1 expressing tumours.

Unsupervised discovery of phenotype-specific multi-omics networks.

MOTIVATION: Complex diseases often involve a wide spectrum of phenotypic traits. Better understanding of the biological mechanisms relevant to each trait promotes understanding of the etiology of the disease and the potential for targeted and effective treatment plans. There have been many efforts towards omics data integration and network reconstruction, but limited work has examined the incorporation of relevant (quantitative) phenotypic traits. RESULTS: We propose a novel technique, sparse multiple canonical correlation network analysis (SmCCNet), for integrating multiple omics data types along with a quantitative phenotype of interest, and for constructing multi-omics networks that are specific to the phenotype. As a case study, we focus on miRNA-mRNA networks. Through simulations, we demonstrate that SmCCNet has better overall prediction performance compared to popular gene expression network construction and integration approaches under realistic settings. Applying SmCCNet to studies on chronic obstructive pulmonary disease (COPD) and breast cancer, we found enrichment of known relevant pathways (e.g. the Cadherin pathway for COPD and the interferon-gamma signaling pathway for breast cancer) as well as less known omics features that may be important to the diseases. Although those applications focus on miRNA-mRNA co-expression networks, SmCCNet is applicable to a variety of omics and other data types. It can also be easily generalized to incorporate multiple quantitative phenotype simultaneously. The versatility of SmCCNet suggests great potential of the approach in many areas. AVAILABILITY AND IMPLEMENTATION: The SmCCNet algorithm is written in R, and is freely available on the web at https://cran.r-project.org/web/packages/SmCCNet/index.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Resequencing Study Confirms That Host Defense and Cell Senescence Gene Variants Contribute to the Risk of Idiopathic Pulmonary Fibrosis.

Rationale: Several common and rare genetic variants have been associated with idiopathic pulmonary fibrosis, a progressive fibrotic condition that is localized to the lung. Objectives: To develop an integrated understanding of the rare and common variants located in multiple loci that have been reported to contribute to the risk of disease. Methods: We performed deep targeted resequencing (3.69 Mb of DNA) in cases (n = 3,624) and control subjects (n = 4,442) across genes and regions previously associated with disease. We tested for associations between disease and 1) individual common variants via logistic regression and 2) groups of rare variants via sequence kernel association tests. Measurements and Main Results: Statistically significant common variant association signals occurred in all 10 of the regions chosen based on genome-wide association studies. The strongest risk variant is the MUC5B promoter variant rs35705950, with an odds ratio of 5.45 (95% confidence interval, 4.91-6.06) for one copy of the risk allele and 18.68 (95% confidence interval, 13.34-26.17) for two copies of the risk allele (P = 9.60 × 10-295). In addition to identifying for the first time that rare variation in FAM13A is associated with disease, we confirmed the role of rare variation in the TERT and RTEL1 gene regions in the risk of IPF, and found that the FAM13A and TERT regions have independent common and rare variant signals. Conclusions: A limited number of common and rare variants contribute to the risk of idiopathic pulmonary fibrosis in each of the resequencing regions, and these genetic variants focus on biological mechanisms of host defense and cell senescence.

Gamma-Tocotrienol Induces Apoptosis in Prostate Cancer Cells by Targeting the Ang-1/Tie-2 Signalling Pathway.

Emerging evidence suggests that gamma-tocotrienol (γ-T3), a vitamin E isomer, has potent anti-cancer properties against a wide-range of cancers. γ-T3 not only inhibited the growth and survival of cancer cells in vitro, but also suppressed angiogenesis and tumour metastasis under in vivo conditions. Recently, γ-T3 was found to target cancer stem cells (CSCs), leading to suppression of tumour formation and chemosensitisation. Despite its promising anti-cancer potential, the exact mechanisms responsible for the effects of γ-T3 are still largely unknown. Here, we report the identification of Ang-1 (Angiopoietin-1)/Tie-2 as a novel γ-T3 downstream target. In prostate cancer cells, γ-T3 treatment leads to the suppression of Ang-1 at both the mRNA transcript and protein levels. Supplementing the cells with Ang-1 was found to protect them against the anti-CSC effect of γ-T3. Intriguingly, inactivation of Tie-2, a member receptor that mediates the effect of Ang-1, was found to significantly enhance the cytotoxic effect of γ-T3 through activation of AMP-activated protein kinase (AMPK) and subsequent interruption of autophagy. Our results highlighted the therapeutic potential of using γ-T3 in combination with a Tie-2 inhibitor to treat advanced prostate cancer.

Humanization of the Prostate Microenvironment Reduces Homing of PC3 Prostate Cancer Cells to Human Tissue-Engineered Bone.

The primary tumor microenvironment is inherently important in prostate cancer (PCa) initiation, growth and metastasis. However, most current PCa animal models are based on the injection of cancer cells into the blood circulation and bypass the first steps of the metastatic cascade, hence failing to investigate the influence of the primary tumor microenvironment on PCa metastasis. Here, we investigated the spontaneous metastasis of PC3 human PCa cells from humanized prostate tissue, containing cancer-associated fibroblasts (CAFs) and prostate lymphatic and blood vessel endothelial cells (BVEC), to humanized tissue-engineered bone constructs (hTEBC) in NOD-SCID IL2Rγnull (NSG) mice. The hTEBC formed a physiologically mature organ bone which allowed homing of metastatic PCa cells. Humanization of prostate tissue had no significant effect on the tumor burden at the primary site over the 4 weeks following intraprostatic injection, yet reduced the incidence and burden of metastases in the hTEBC. Spontaneous PCa metastases were detected in the lungs and spleen with no significant differences between the humanized and non-humanized prostate groups. A significantly greater metastatic tumor burden was observed in the liver when metastasis occurred from the humanized prostate. Together, our data suggests that the presence of human-derived CAFs and BVECs in the primary PCa microenvironment influences selectively the metastatic and homing behavior of PC3 cells in this model. Our orthotopic and humanized prostate cancer model developed via convergence of cancer research and tissue engineering concepts provides an important platform to study species-specific PCa bone metastasis and to develop and test therapeutic strategies.

A large-scale analysis of bioinformatics code on GitHub.

In recent years, the explosion of genomic data and bioinformatic tools has been accompanied by a growing conversation around reproducibility of results and usability of software. However, the actual state of the body of bioinformatics software remains largely unknown. The purpose of this paper is to investigate the state of source code in the bioinformatics community, specifically looking at relationships between code properties, development activity, developer communities, and software impact. To investigate these issues, we curated a list of 1,720 bioinformatics repositories on GitHub through their mention in peer-reviewed bioinformatics articles. Additionally, we included 23 high-profile repositories identified by their popularity in an online bioinformatics forum. We analyzed repository metadata, source code, development activity, and team dynamics using data made available publicly through the GitHub API, as well as article metadata. We found key relationships within our dataset, including: certain scientific topics are associated with more active code development and higher community interest in the repository; most of the code in the main dataset is written in dynamically typed languages, while most of the code in the high-profile set is statically typed; developer team size is associated with community engagement and high-profile repositories have larger teams; the proportion of female contributors decreases for high-profile repositories and with seniority level in author lists; and, multiple measures of project impact are associated with the simple variable of whether the code was modified at all after paper publication. In addition to providing the first large-scale analysis of bioinformatics code to our knowledge, our work will enable future analysis through publicly available data, code, and methods. Code to generate the dataset and reproduce the analysis is provided under the MIT license at https://github.com/pamelarussell/github-bioinformatics. Data are available at https://doi.org/10.17605/OSF.IO/UWHX8.

Predictive modeling of miRNA-mediated predisposition to alcohol-related phenotypes in mouse.

BACKGROUND: MicroRNAs (miRNAs) are small non-coding RNAs that bind messenger RNAs and promote their degradation or repress their translation. There is increasing evidence of miRNAs playing an important role in alcohol related disorders. However, the role of miRNAs as mediators of the genetic effect on alcohol phenotypes is not fully understood. We conducted a high-throughput sequencing study to measure miRNA expression levels in alcohol naïve animals in the LXS panel of recombinant inbred (RI) mouse strains. We then combined the sequencing data with genotype data, microarry gene expression data, and data on alcohol-related behavioral phenotypes such as 'Drinking in the dark', 'Sleep time', and 'Low dose activation' from the same RI panel. SNP-miRNA-gene triplets with strong association within the triplet that were also associated with one of the 4 alcohol phenotypes were selected and a Bayesian network analysis was used to aggregate results into a directed network model. RESULTS: We found several triplets with strong association within the triplet that were also associated with one of the alcohol phenotypes. The Bayesian network analysis found two networks where a miRNA mediates the genetic effect on the alcohol phenotype. The miRNAs were found to influence the expression of protein-coding genes, which in turn influences the quantitative phenotypes. The pathways in which these genes are enriched have been previously associated with alcohol-related traits. CONCLUSION: This work enhances association studies by identifying miRNAs that may be mediating the association between genetic markers (SNPs) and the alcohol phenotypes. It suggests a mechanism of how genetic variants are affecting traits of interest through the modification of miRNA expression.

Higher-Order Inter-chromosomal Hubs Shape 3D Genome Organization in the Nucleus.

Eukaryotic genomes are packaged into a 3-dimensional structure in the nucleus. Current methods for studying genome-wide structure are based on proximity ligation. However, this approach can fail to detect known structures, such as interactions with nuclear bodies, because these DNA regions can be too far apart to directly ligate. Accordingly, our overall understanding of genome organization remains incomplete. Here, we develop split-pool recognition of interactions by tag extension (SPRITE), a method that enables genome-wide detection of higher-order interactions within the nucleus. Using SPRITE, we recapitulate known structures identified by proximity ligation and identify additional interactions occurring across larger distances, including two hubs of inter-chromosomal interactions that are arranged around the nucleolus and nuclear speckles. We show that a substantial fraction of the genome exhibits preferential organization relative to these nuclear bodies. Our results generate a global model whereby nuclear bodies act as inter-chromosomal hubs that shape the overall packaging of DNA in the nucleus.

TCIApathfinder: An R Client for the Cancer Imaging Archive REST API.

The Cancer Imaging Archive (TCIA) hosts publicly available deidentified medical images of cancer from over 25 body sites and over 30,000 patients. Over 400 published studies have utilized freely available TCIA images. Images and metadata are available for download through a web interface or a REST API. Here, we present TCIApathfinder, an R client for the TCIA REST API. TCIApathfinder wraps API access in user-friendly R functions that can be called interactively within an R session or easily incorporated into scripts. Functions are provided to explore the contents of the large database and to download image files. TCIApathfinder provides easy access to TCIA resources in the highly popular R programming environment. TCIApathfinder is freely available under the MIT license as a package on CRAN (https://cran.r-project.org/web/packages/TCIApathfinder/index.html) and from https://github.com/pamelarussell/TCIApathfinderSignificance: These findings present a new tool, TCIApathfinder, the first client for The Cancer Imaging Archive (TCIA) for use in the highly popular R computing environment, that will dramatically lower the barrier of access to the valuable tools in TCIA. Cancer Res; 78(15); 4424-6. ©2018 AACR.

miR-MaGiC improves quantification accuracy for small RNA-seq.

OBJECTIVE: Many tools have been developed to profile microRNA (miRNA) expression from small RNA-seq data. These tools must contend with several issues: the small size of miRNAs, the small number of unique miRNAs, the fact that similar miRNAs can be transcribed from multiple loci, and the presence of miRNA isoforms known as isomiRs. Methods failing to address these issues can return misleading information. We propose a novel quantification method designed to address these concerns. RESULTS: We present miR-MaGiC, a novel miRNA quantification method, implemented as a cross-platform tool in Java. miR-MaGiC performs stringent mapping to a core region of each miRNA and defines a meaningful set of target miRNA sequences by collapsing the miRNA space to "functional groups". We hypothesize that these two features, mapping stringency and collapsing, provide more optimal quantification to a more meaningful unit (i.e., miRNA family). We test miR-MaGiC and several published methods on 210 small RNA-seq libraries, evaluating each method's ability to accurately reflect global miRNA expression profiles. We define accuracy as total counts close to the total number of input reads originating from miRNAs. We find that miR-MaGiC, which incorporates both stringency and collapsing, provides the most accurate counts.

Radtools: R utilities for convenient extraction of medical image metadata.

The radiology community has adopted several widely used standards for medical image files, including the popular DICOM (Digital Imaging and Communication in Medicine) and NIfTI (Neuroimaging Informatics Technology Initiative) standards. These file formats include image intensities as well as potentially extensive metadata. The NIfTI standard specifies a particular set of header fields describing the image and minimal information about the scan. DICOM headers can include any of >4,000 available metadata attributes spanning a variety of topics. NIfTI files contain all slices for an image series, while DICOM files capture single slices and image series are typically organized into a directory. Each DICOM file contains metadata for the image series as well as the individual image slice. The programming environment R is popular for data analysis due to its free and open code, active ecosystem of tools and users, and excellent system of contributed packages. Currently, many published radiological image analyses are performed with proprietary software or custom unpublished scripts. However, R is increasing in popularity in this area due to several packages for processing and analysis of image files. While these R packages handle image import and processing, no existing package makes image metadata conveniently accessible. Extracting image metadata, combining across slices, and converting to useful formats can be prohibitively cumbersome, especially for DICOM files. We present radtools, an R package for smooth navigation of medical image data. Radtools makes the problem of extracting image metadata trivially simple, providing simple functions to explore and return information in familiar R data structures. Radtools also facilitates extraction of image data and viewing of image slices. The package is freely available under the MIT license at https://github.com/pamelarussell/radtools and is easily installable from the Comprehensive R Archive Network ( https://cran.r-project.org/package=radtools).

Extracellular Vesicles in the Adaptive Process of Prostate Cancer during Inhibition of Androgen Receptor Signaling by Enzalutamide.

Current treatments for advanced prostate cancer focus on inhibition of the androgen receptor (AR) by androgen deprivation therapy (ADT). However, complex interactions mediated by tumor suppressors, oncogenes, aberrations of AR expression, or de novo androgen production have been shown to induce the adaptive response of prostate cancer, leading to the development of castration resistant prostate cancer. In this study, we report the effects of AR antagonist, enzalutamide on the protein contents of extracellular vesicles (EVs). EVs mediate cell-to-cell communication and increasing evidence shows the role of EVs in promoting cancer survival and metastasis. We found that treatment with enzalutamide alters the secretion of EVs, one of which is a plasma membrane calcium pump, ATP2B1/PMCA ATPase, as an AR-regulated EV protein. We highlight the networks of interactions between AR, Ca2+ , and ATP2B1, where the extracellular proteins thrombospondin-1, gelsolin, and integrinß1 were previously reported as regulators for cancer progression and metastasis, indicating the potential role of EV-derived proteins in mediating calcium homoeostasis under AR inhibition by enzalutamide. Our data further highlight the cross-talk between AR signaling and EV pathways in mediating resistance toward ADT.

Modulation of paracrine signaling by CD9 positive small extracellular vesicles mediates cellular growth of androgen deprived prostate cancer.

Proliferation and maintenance of both normal and prostate cancer (PCa) cells is highly regulated by steroid hormones, particularly androgens, and the extracellular environment. Herein, we identify the secretion of CD9 positive extracellular vesicles (EV) by LNCaP and DUCaP PCa cells in response to dihydrotestosterone (DHT) and use nano-LC-MS/MS to identify the proteins present in these EV. Subsequent bioinformatic and pathway analyses of the mass spectrometry data identified pathologically relevant pathways that may be altered by EV contents. Western blot and CD9 EV TR-FIA assay confirmed a specific increase in the amount of CD9 positive EV in DHT-treated LNCaP and DUCaP cells and treatment of cells with EV enriched with CD9 after DHT exposure can induce proliferation in androgen-deprived conditions. siRNA knockdown of endogenous CD9 in LNCaPs reduced cellular proliferation and expression of AR and prostate specific antigen (PSA) however knockdown of AR did not alter CD9 expression, also implicating CD9 as an upstream regulator of AR. Moreover CD9 positive EV were also found to be significantly higher in plasma from prostate cancer patients in comparison with benign prostatic hyperplasia patients. We conclude that CD9 positive EV are involved in mediating paracrine signalling and contributing toward prostate cancer progression.

Extracellular vesicles for personalized therapy decision support in advanced metastatic cancers and its potential impact for prostate cancer.

The use of circulating tumor cells (CTCs) and circulating extracellular vesicles (EVs), such as exosomes, as liquid biopsy-derived biomarkers for cancers have been investigated. CTC enumeration using the CellSearch based platform provides an accurate insight on overall survival where higher CTC counts indicate poor prognosis for patients with advanced metastatic cancer. EVs provide information based on their lipid, protein, and nucleic acid content and can be isolated from biofluids and analyzed from a relatively small volume, providing a routine and non-invasive modality to monitor disease progression. Our pilot experiment by assessing the level of two subpopulations of small EVs, the CD9 positive and CD63 positive EVs, showed that the CD9 positive EV level is higher in plasma from patients with advanced metastatic prostate cancer with detectable CTCs. These data show the potential utility of a particular EV subpopulation to serve as biomarkers for advanced metastatic prostate cancer. EVs can potentially be utilized as biomarkers to provide accurate genotypic and phenotypic information for advanced prostate cancer, where new strategies to design a more personalized therapy is currently the focus of considerable investigation.

Localised delivery of doxorubicin to prostate cancer cells through a PSMA-targeted hyperbranched polymer theranostic.

The therapeutic potential of hyperbranched polymers targeted to prostate cancer and loaded with doxorubicin was investigated. Polyethylene glycol hyperbranched polymers were synthesised via RAFT polymerisation to feature glutamate urea targeting ligands for PSMA on the periphery. The chemotherapeutic, doxorubicin, was attached to the hyperbranched polymers through hydrazone formation, which allowed controlled release of the drug from the polymers in vitro endosomal conditions, with 90% release of the drug over 36 h. The polymers were able to target to PSMA-expressing prostate cancer cells in vitro, and demonstrated comparable cytotoxicity to free doxorubicin. The ability of the hyperbranched polymers to specifically facilitate transport of loaded doxorubicin into the cells was confirmed using live cell confocal imaging, which demonstrated that the drug was able to travel with the polymer into cells by receptor mediated internalisation, and subsequently be released into the nucleus following hydrazone degradation. Finally, the ability of the complex to induce a therapeutic effect on prostate cancer cells was investigated through a long term tumour regression study, which confirmed that the DOX-loaded polymers were able to significantly reduce the volume of subcutaneous prostate tumours in vivo in comparison to free doxorubicin and a polymer control, with no adverse toxicity to the animals. This work therefore demonstrates the potential of a hyperbranched polymer system to be utilised for prostate cancer theranostics.

Model based heritability scores for high-throughput sequencing data.

BACKGROUND: Heritability of a phenotypic or molecular trait measures the proportion of variance that is attributable to genotypic variance. It is an important concept in breeding and genetics. Few methods are available for calculating heritability for traits derived from high-throughput sequencing. RESULTS: We propose several statistical models and different methods to compute and test a heritability measure for such data based on linear and generalized linear mixed effects models. We also provide methodology for hypothesis testing and interval estimation. Our analyses show that, among the methods, the negative binomial mixed model (NB-fit), compound Poisson mixed model (CP-fit), and the variance stabilizing transformed linear mixed model (VST) outperform the voom-transformed linear mixed model (voom). NB-fit and VST appear to be more robust than CP-fit for estimating and testing the heritability scores, while NB-fit is the most computationally expensive. CP-fit performed best in terms of the coverage of the confidence intervals. In addition, we applied the methods to both microRNA (miRNA) and messenger RNA (mRNA) sequencing datasets from a recombinant inbred mouse panel. We show that miRNA and mRNA expression can be a highly heritable molecular trait in mouse, and that some top heritable features coincide with expression quantitative trait loci. CONCLUSIONS: The models and methods we investigated in this manuscript is applicable and extendable to sequencing experiments where some biological replicates are available and the environmental variation is properly controlled. The CP-fit approach for assessing heritability was implemented for the first time to our knowledge. All the methods presented, as well as the generation of simulated sequencing data under either negative binomial or compound Poisson mixed models, are provided in the R package HeritSeq.