Heterogeneous expression of ACE2 and TMPRRS2 in mesenchymal stromal cells.

The outbreak of COVID-19 has become a serious public health emergency. The virus targets cells by binding the ACE2 receptor. After infection, the virus triggers in some humans an immune storm containing the release of proinflammatory cytokines and chemokines followed by multiple organ failure. Several vaccines are enrolled, but an effective treatment is still missing. Mesenchymal stem cells (MSCs) have shown to secrete immunomodulatory factors that suppress this cytokine storm. Therefore, MSCs have been suggested as a potential treatment option for COVID-19. We report here that the ACE2 expression is minimal or nonexistent in MSC derived from three different human tissue sources (adipose tissue, umbilical cord Wharton`s jelly and bone marrow). In contrast, TMPRSS2 that is implicated in SARS-CoV-2 entry has been detected in all MSC samples. These results are of particular importance for future MSC-based cell therapies to treat severe cases after COVID-19 infection.

SwissPKcdw - A clinical data warehouse for the optimization of pediatric dosing regimens.

Clinical trials have been performed mainly in adults and accordingly the necessary information is lacking for pediatric patients, especially regarding dosage recommendation for approved drugs. This gap in information could be filled with results from pharmacokinetic (PK) modeling, based on data collected in daily clinical routine. In order to make this data accessible and usable for research, the Swiss Pharmacokinetics Clinical Data Warehouse (SwissPKcdw ) project has been set up, including a clinical data warehouse (CDW) and the regulatory framework for data transfer and use within. Embedded into the secure BioMedIT network, the CDW can connect to various data providers and researchers in order to collaborate on the data securely. Due to its modularity, partially containerized deployment and open-source software, each of the components can be extended, modified, and re-used for similar projects that require integrated data management, data analysis, and web tools in a secure scientific data and information technology (IT) environment. Here, we describe a collaborative and interprofessional effort to implement the aforementioned infrastructure between several partners from medical health care and academia. Furthermore, we describe a real-world use case where blood samples from pediatric patients were analyzed for the presence of genetic polymorphisms and the results were aggregated and further analyzed together with the health-related patient data in the SwissPKcdw .

Temporal activation of WNT/ß-catenin signaling is sufficient to inhibit SOX10 expression and block melanoma growth.

Despite advances in the systemic treatment of patients with metastatic melanoma using immune checkpoint and tyrosine kinase inhibitors (TKI), the majority of stage IV melanoma patients eventually succumb to the disease. We have previously identified the transcription factor Sox10 as a crucial player in melanoma, yet the underlying molecular mechanisms mediating Sox10-dependent tumorigenesis remain largely uncharacterized. Here, we show that MEK and RAF inhibitors do not suppress levels of SOX10 protein in patient-derived cells in vitro, as well as in melanoma patients in vivo. In a search for pharmacological inhibitors of SOX10, we performed a mass spectrometry-based screen in human melanoma cells. Subsequent analysis revealed that SOX10 directly interacts with ß-catenin, which is a key mediator of canonical Wnt/ß-catenin signaling. We demonstrate that inhibitors of glycogen synthase kinase 3 alpha/beta (GSK3α/ß) efficiently abrogate SOX10 protein in human melanoma cells in vitro and in melanoma mouse models in vivo. The mechanism of action of GSK3-mediated SOX10 suppression is transcription-independent and relies on the presence of a proteasome degradable form of ß-catenin. Taken together, we provide evidence that activation of canonical Wnt signaling has a profound effect on melanoma growth and is able to counteract Sox10-dependent melanoma maintenance both in vitro and in vivo.

Gene expression in chronic granulomatous disease and interferon-γ receptor-deficient cells treated in vitro with interferon-γ.

Interferon-γ (IFN-γ) plays an important role in innate and adaptive immunity against intracellular infections and is used clinically for the prevention and control of infections in chronic granulomatous disease (CGD) and inborn defects in the IFN-γ/interleukin (IL)-12 axis. Using transcriptome profiling (RNA-seq), we sought to identify differentially expressed genes, transcripts and exons in Epstein-Barr virus-transformed B lymphocytes (B-EBV) cells from CGD patients, IFN-γ receptor deficiency patients, and normal controls, treated in vitro with IFN-γ for 48 hours. Our results show that IFN-γ increased the expression of a diverse array of genes related to different cellular programs. In cells from normal controls and CGD patients, IFN-γ-induced expression of genes relevant to oxidative killing, nitric oxide synthase pathway, proteasome-mediated degradation, antigen presentation, chemoattraction, and cell adhesion. IFN-γ also upregulated genes involved in diverse stages of messenger RNA (mRNA) processing including pre-mRNA splicing, as well as others implicated in the folding, transport, and assembly of proteins. In particular, differential exon expression of WARS (encoding tryptophanyl-transfer RNA synthetase, which has an essential function in protein synthesis) induced by IFN-γ in normal and CGD cells suggests that this gene may have an important contribution to the benefits of IFN-γ treatment for CGD. Upregulation of mRNA and protein processing related genes in CGD and IFNRD cells could mediate some of the effects of IFN-γ treatment. These data support the concept that IFN-γ treatment may contribute to increased immune responses against pathogens through regulation of genes important for mRNA and protein processing.

Genes sharing the protein family domain decrease the performance of classification with RNA-seq genomic signatures.

BACKGROUND: The experience with running various types of classification on the CAMDA neuroblastoma dataset have led us to the conclusion that the results are not always obvious and may differ depending on type of analysis and selection of genes used for classification. This paper aims in pointing out several factors that may influence the downstream machine learning analysis. In particular those factors are: type of the primary analysis, type of the classifier and increased correlation between the genes sharing a protein domain. They influence the analysis directly, but also interplay between them may be important. We have compiled the gene-domain database and used it for analysis to see the differences between the genes that share a domain versus the rest of the genes in the datasets. RESULTS: The major findings are: pairs of genes that share a domain have an increased Spearman's correlation coefficients of counts; genes sharing a domain are expected to have a lower predictive power due to increased correlation. For most of the cases it can be seen with the higher number of misclassified samples; classifiers performance may vary depending on a method, still in most cases using genes sharing a domain in the training set results in a higher misclassification rate; increased correlation in genes sharing a domain results most often in worse performance of the classifiers regardless of the primary analysis tools used, even if the primary analysis alignment yield varies. CONCLUSIONS: The effect of sharing a domain is likely more a results of real biological co-expression than just sequence similarity and artifacts of mapping and counting. Still, this is more difficult to conclude and needs further research. The effect is interesting itself, but we also point out some practical aspects in which it may influence the RNA sequencing analysis and RNA biomarker use. In particular it means that a gene signature biomarker set build out of RNA-sequencing results should be depleted for genes sharing common domains. It may cause to perform better when applying classification. REVIEWERS: This article was reviewed by Dimitar Vassiliev and Susmita Datta.

Molecular insights into Cassava brown streak virus susceptibility and resistance by profiling of the early host response.

Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV) are responsible for significant cassava yield losses in eastern sub-Saharan Africa. To study the possible mechanisms of plant resistance to CBSVs, we inoculated CBSV-susceptible and CBSV-resistant cassava varieties with a mixed infection of CBSVs using top-cleft grafting. Transcriptome profiling of the two cassava varieties was performed at the earliest time point of full infection (28 days after grafting) in the susceptible scions. The expression of genes encoding proteins in RNA silencing, salicylic acid pathways and callose deposition was altered in the susceptible cassava variety, but transcriptional changes were limited in the resistant variety. In total, the expression of 585 genes was altered in the resistant variety and 1292 in the susceptible variety. Transcriptional changes led to the activation of ß-1,3-glucanase enzymatic activity and a reduction in callose deposition in the susceptible cassava variety. Time course analysis also showed that CBSV replication in susceptible cassava induced a strong up-regulation of RDR1, a gene previously reported to be a susceptibility factor in other potyvirus-host pathosystems. The differences in the transcriptional responses to CBSV infection indicated that susceptibility involves the restriction of callose deposition at plasmodesmata. Aniline blue staining of callose deposits also indicated that the resistant variety displays a moderate, but significant, increase in callose deposition at the plasmodesmata. Transcriptome data suggested that resistance does not involve typical antiviral defence responses (i.e. RNA silencing and salicylic acid). A meta-analysis of the current RNA-sequencing (RNA-seq) dataset and selected potyvirus-host and virus-cassava RNA-seq datasets revealed that the conservation of the host response across pathosystems is restricted to genes involved in developmental processes.

Benchmarking distributed data warehouse solutions for storing genomic variant information.

Database URL: https://github.com/ZSI-Bio/variantsdwh.

Corrigendum: Pramel7 mediates ground-state pluripotency through proteasomal-epigenetic combined pathways.

This corrects the article DOI: 10.1038/ncb3554.

Pramel7 mediates ground-state pluripotency through proteasomal-epigenetic combined pathways.

Naive pluripotency is established in preimplantation epiblast. Embryonic stem cells (ESCs) represent the immortalization of naive pluripotency. 2i culture has optimized this state, leading to a gene signature and DNA hypomethylation closely comparable to preimplantation epiblast, the developmental ground state. Here we show that Pramel7 (PRAME-like 7), a protein highly expressed in the inner cell mass (ICM) but expressed at low levels in ESCs, targets for proteasomal degradation UHRF1, a key factor for DNA methylation maintenance. Increasing Pramel7 expression in serum-cultured ESCs promotes a preimplantation epiblast-like gene signature, reduces UHRF1 levels and causes global DNA hypomethylation. Pramel7 is required for blastocyst formation and its forced expression locks ESCs in pluripotency. Pramel7/UHRF1 expression is mutually exclusive in ICMs whereas Pramel7-knockout embryos express high levels of UHRF1. Our data reveal an as-yet-unappreciated dynamic nature of DNA methylation through proteasome pathways and offer insights that might help to improve ESC culture to reproduce in vitro the in vivo ground-state pluripotency.

Identification of Novel Equine (Equus caballus) Tendon Markers Using RNA Sequencing.

Although several tendon-selective genes exist, they are also expressed in other musculoskeletal tissues. As cell and tissue engineering is reliant on specific molecular markers to discriminate between cell types, tendon-specific genes need to be identified. In order to accomplish this, we have used RNA sequencing (RNA-seq) to compare gene expression between tendon, bone, cartilage and ligament from horses. We identified several tendon-selective gene markers, and established eyes absent homolog 2 (EYA2) and a G-protein regulated inducer of neurite outgrowth 3 (GPRIN3) as specific tendon markers using RT-qPCR. Equine tendon cells cultured as three-dimensional spheroids expressed significantly greater levels of EYA2 than GPRIN3, and stained positively for EYA2 using immunohistochemistry. EYA2 was also found in fibroblast-like cells within the tendon tissue matrix and in cells localized to the vascular endothelium. In summary, we have identified EYA2 and GPRIN3 as specific molecular markers of equine tendon as compared to bone, cartilage and ligament, and provide evidence for the use of EYA2 as an additional marker for tendon cells in vitro.

In vivo profiling reveals immunomodulatory effects of sorafenib and dacarbazine on melanoma.

Sorafenib is a multi-kinase inhibitor used alone or in combination with dacarbazine to treat metastasized melanoma. Our study investigated the relationship between metabolic response assessed by PET-CT and global transcriptome changes during sorafenib and dacarbazine therapy in patients with advanced melanoma. We conducted an open-label, investigator-initiated study that enrolled 13 sorafenib-naïve Stage IV melanoma patients, whose metastases were accessible for repeated biopsies. Treatment regimen included orally administered sorafenib and intravenous dacarbazine. Biopsies of skin or superficial lymph node metastases were taken before treatment (baseline), during sorafenib and after dacarbazine therapy and used for transcriptional profiling and validation experiments. Serum samples were evaluated for cytokine production. Metabolic response to therapy was observed in 45.5% of patients. The study drugs were well tolerated. We observed a clear upregulation of interferon (IFN)-stimulated immune response genes in profiled metastases. The IFNγ-induced gene signature seemed to be enhanced after addition of dacarbazine to sorafenib. Serum IFNγ also increased during therapy, particularly after addition of dacarbazine. Induction of IFNγ stimulated genes correlating with increased serum IFNγ was predictive of better clinical outcome and responders who had significantly higher serum IFNγ levels lived longer. Our data reveal in situ changes in melanoma metastases during treatment with sorafenib and dacarbazine and suggest an additional mechanism of action through immunomodulation.

Transcriptional analysis of South African cassava mosaic virus-infected susceptible and tolerant landraces of cassava highlights differences in resistance, basal defense and cell wall associated genes during infection.

BACKGROUND: Cassava mosaic disease is caused by several distinct geminivirus species, including South African cassava mosaic virus-[South Africa:99] (SACMV). To date, there is limited gene regulation information on viral stress responses in cassava, and global transcriptome profiling in SACMV-infected cassava represents an important step towards understanding natural host responses to plant geminiviruses. RESULTS: A RNA-seq time course (12, 32 and 67 dpi) study, monitoring gene expression in SACMV-challenged susceptible (T200) and tolerant (TME3) cassava landraces, was performed using the Applied Biosystems (ABI) SOLiD next-generation sequencing platform. The multiplexed paired end sequencing run produced a total of 523 MB and 693 MB of paired-end reads for SACMV-infected susceptible and tolerant cDNA libraries, respectively. Of these, approximately 50.7% of the T200 reads and 55.06% of TME3 reads mapped to the cassava reference genome available in phytozome. Using a log2 fold cut-off (p<0.05), comparative analysis between the six normalized cDNA libraries showed that 4181 and 1008 transcripts in total were differentially expressed in T200 and TME3, respectively, across 12, 32 and 67 days post infection, compared to mock-inoculated. The number of responsive transcripts increased dramatically from 12 to 32 dpi in both cultivars, but in contrast, in T200 the levels did not change significantly at 67 dpi, while in TME3 they declined. GOslim functional groups illustrated that differentially expressed genes in T200 and TME3 were overrepresented in the cellular component category for stress-related genes, plasma membrane and nucleus. Alterations in the expression of other interesting genes such as transcription factors, resistance (R) genes, and histone/DNA methylation-associated genes, were observed. KEGG pathway analysis uncovered important altered metabolic pathways, including phenylpropanoid biosynthesis, sucrose and starch metabolism, and plant hormone signalling. CONCLUSIONS: Molecular mechanisms for TME3 tolerance are proposed, and differences in patterns and levels of transcriptome profiling between T200 and TME3 with susceptible and tolerant phenotypes, respectively, support the hypothesis that viruses rearrange their molecular interactions in adapting to hosts with different genetic backgrounds.

SparkSeq: fast, scalable and cloud-ready tool for the interactive genomic data analysis with nucleotide precision.

UNLABELLED: Many time-consuming analyses of next -: generation sequencing data can be addressed with modern cloud computing. The Apache Hadoop-based solutions have become popular in genomics BECAUSE OF: their scalability in a cloud infrastructure. So far, most of these tools have been used for batch data processing rather than interactive data querying. The SparkSeq software has been created to take advantage of a new MapReduce framework, Apache Spark, for next-generation sequencing data. SparkSeq is a general-purpose, flexible and easily extendable library for genomic cloud computing. It can be used to build genomic analysis pipelines in Scala and run them in an interactive way. SparkSeq opens up the possibility of customized ad hoc secondary analyses and iterative machine learning algorithms. This article demonstrates its scalability and overall fast performance by running the analyses of sequencing datasets. Tests of SparkSeq also prove that the use of cache and HDFS block size can be tuned for the optimal performance on multiple worker nodes. AVAILABILITY AND IMPLEMENTATION: Available under open source Apache 2.0 license: https://bitbucket.org/mwiewiorka/sparkseq/.

A comprehensive look at transcription factor gene expression changes in colorectal adenomas.

BACKGROUND: Biological processes are controlled by transcription networks. Expression changes of transcription factor (TF) genes in precancerous lesions are therefore crucial events in tumorigenesis. Our aim was to obtain a comprehensive picture of these changes in colorectal adenomas. METHODS: Using a 3-pronged selection procedure, we analyzed transcriptomic data on 34 human tissue samples (17 adenomas and paired samples of normal mucosa, all collected with ethics committee approval and written, informed patient consent) to identify TFs with highly significant tumor-associated gene expression changes whose potential roles in colorectal tumorigenesis have been under-researched. Microarray data were subjected to stringent statistical analysis of TF expression in tumor vs. normal tissues, MetaCore-mediated identification of TF networks displaying enrichment for genes that were differentially expressed in tumors, and a novel quantitative analysis of the publications examining the TF genes' roles in colorectal tumorigenesis. RESULTS: The 261 TF genes identified with this procedure included DACH1, which plays essential roles in the proper proliferation and differentiation of retinal and leg precursor cell populations in Drosophila melanogaster. Its possible roles in colorectal tumorigenesis are completely unknown, but it was found to be markedly overexpressed (mRNA and protein) in all colorectal adenomas and in most colorectal carcinomas. However, DACH1 expression was absent in some carcinomas, most of which were DNA mismatch-repair deficient. When networks were built using the set of TF genes identified by all three selection procedures, as well as the entire set of transcriptomic changes in adenomas, five hub genes (TGFB1, BIRC5, MYB, NR3C1, and TERT) where identified as putatively crucial components of the adenomatous transformation process. CONCLUSION: The transcription-regulating network of colorectal adenomas (compared with that of normal colorectal mucosa) is characterized by significantly altered expression of over 250 TF genes, many of which have never been investigated in relation to colorectal tumorigenesis.

Early insights into the function of KIAA1199, a markedly overexpressed protein in human colorectal tumors.

We previously reported that the expression of KIAA1199 in human colorectal tumors (benign and malignant) is markedly higher than that in the normal colonic mucosa. In this study, we investigated the functions of the protein encoded by this gene, which are thus far unknown. Immunostaining studies were used to reveal its subcellular localization, and proteomic and gene expression experiments were conducted to identify proteins that might interact with KIAA1199 and molecular pathways in which it might play roles. Using colon cancer cell lines, we showed that both endogenous and ectopically expressed KIAA1199 is secreted into the extracellular environment. In the cells, it was found mainly in the perinuclear space (probably the ER) and cell membrane. Both cellular compartments were also over-represented in lists of proteins identified by mass spectrometry as putative KIAA1199 interactors and/or proteins encoded by genes whose transcription was significantly changed by KIAA1199 expression. These proteomic and transcriptomic datasets concordantly link KIAA1199 to several genes/proteins and molecular pathways, including ER processes like protein binding, transport, and folding; and Ca(2+), G-protein, ephrin, and Wnt signaling. Immunoprecipitation experiments confirmed KIAA1199's interaction with the cell-membrane receptor ephrin A2 and with the ER receptor ITPR3, a key player in Ca(2+) signaling. By modulating Ca(2+) signaling, KIAA1199 could affect different branches of the Wnt network. Our findings suggest it may negatively regulate the Wnt/CTNNB1 signaling, and its expression is associated with decreased cell proliferation and invasiveness.

Precise breakpoint localization of large genomic deletions using PacBio and Illumina next-generation sequencers.

Herein we present the applicability of single-molecule (PacBio RS) and second-generation sequencing technology (Illumina) to the characterization of large genomic deletions. By testing samples previously characterized using a Sanger approach, our methods determined that both next-generation sequencing platforms were able to identify the position of deletion breakpoints. Our results point out various advantages of next-generation sequencing platforms when characterizing genomic deletions; however, special attention must be dedicated to identical sequences flanking the breakpoints, such as poly(N) motifs.

Cross-species genome wide expression analysis during pluripotent cell determination in mouse and rat preimplantation embryos.

The transition between morula and blastocyst stage during preimplantation development represents the first differentiation event of embryogenesis. Morula cells undergo the first cellular specialization and produce two well-defined populations of cells, the trophoblast and the inner cell mass (ICM). Embryonic stem cells (ESCs) with unlimited self-renewal capacity are believed to represent the in vitro counterpart of the ICM. Both mouse and rat ESCs can be derived from the ICM cells, but their in vitro stability differs. In this study we performed a microarray analysis in which we compared the transcriptome of mouse and rat morula, blastocyst, and ICM. This cross-species comparison represents a good model for understanding the differences in derivation and cultivation of ESCs observed in the two species. In order to identify alternative regulation of important molecular mechanisms the investigation of differential gene expression between the two species was extended at the level of signaling pathways, gene families, and single selected genes of interest. Some of the genes differentially expressed between the two species are already known to be important factors in the maintenance of pluripotency in ESCs, like for example Sox2 or Stat3, or play a role in reprogramming somatic cells to pluripotency like c-Myc, Klf4 and p53 and therefore represent interesting candidates to further analyze in vitro in the rat ESCs. This is the first study investigating the gene expression changes during the transition from morula to blastocyst in the rat preimplantation development. Our data show that in the pluripotent pool of cells of the rat and mouse preimplantation embryo substantial differential regulation of genes is present, which might explain the difficulties observed for the derivation and culture of rat ESCs using mouse conditions.

PGC-1α determines light damage susceptibility of the murine retina.

The peroxisome proliferator-activated receptor γ coactivator 1 (PGC-1) proteins are key regulators of cellular bioenergetics and are accordingly expressed in tissues with a high energetic demand. For example, PGC-1α and PGC-1ß control organ function of brown adipose tissue, heart, brain, liver and skeletal muscle. Surprisingly, despite their prominent role in the control of mitochondrial biogenesis and oxidative metabolism, expression and function of the PGC-1 coactivators in the retina, an organ with one of the highest energy demands per tissue weight, are completely unknown. Moreover, the molecular mechanisms that coordinate energy production with repair processes in the damaged retina remain enigmatic. In the present study, we thus investigated the expression and function of the PGC-1 coactivators in the healthy and the damaged retina. We show that PGC-1α and PGC-1ß are found at high levels in different structures of the mouse retina, most prominently in the photoreceptors. Furthermore, PGC-1α knockout mice suffer from a striking deterioration in retinal morphology and function upon detrimental light exposure. Gene expression studies revealed dysregulation of all major pathways involved in retinal damage and apoptosis, repair and renewal in the PGC-1α knockouts. The light-induced increase in apoptosis in vivo in the absence of PGC-1α was substantiated in vitro, where overexpression of PGC-1α evoked strong anti-apoptotic effects. Finally, we found that retinal levels of PGC-1 expression are reduced in different mouse models for retinitis pigmentosa. We demonstrate that PGC-1α is a central coordinator of energy production and, importantly, all of the major processes involved in retinal damage and subsequent repair. Together with the observed dysregulation of PGC-1α and PGC-1ß in retinitis pigmentosa mouse models, these findings thus imply that PGC-1α might be an attractive target for therapeutic approaches aimed at retinal degeneration diseases.

Preferred analysis methods for single genomic regions in RNA sequencing revealed by processing the shape of coverage.

The informational content of RNA sequencing is currently far from being completely explored. Most of the analyses focus on processing tables of counts or finding isoform deconvolution via exon junctions. This article presents a comparison of several techniques that can be used to estimate differential expression of exons or small genomic regions of expression, based on their coverage function shapes. The problem is defined as finding the differentially expressed exons between two samples using local expression profile normalization and statistical measures to spot the differences between two profile shapes. Initial experiments have been done using synthetic data, and real data modified with synthetically created differential patterns. Then, 160 pipelines (5 types of generator × 4 normalizations × 8 difference measures) are compared. As a result, the best analysis pipelines are selected based on linearity of the differential expression estimation and the area under the ROC curve. These platform-independent techniques have been implemented in the Bioconductor package rnaSeqMap. They point out the exons with differential expression or internal splicing, even if the counts of reads may not show this. The areas of application include significant difference searches, splicing identification algorithms and finding suitable regions for QPCR primers.

rnaSeqMap: a Bioconductor package for RNA sequencing data exploration.

BACKGROUND: The throughput of commercially available sequencers has recently significantly increased. It has reached the point where measuring the RNA expression by the depth of coverage has become feasible even for largest genomes. The development of software tools is constantly following the progress of biological hardware. In particular, as RNA sequencing software can be regarded genome browsers, exon junction tools and statistical tools operating on counts of reads in predefined regions. The library rnaSeqMap, freely available via Bioconductor, is an RNA sequencing software which is independent of any biological hardware platform. It is based upon standard Bioconductor infrastructure for sequencing data and includes several novel features focused on deeper understanding of coverage expression profiles and discovery of novel transcription regions. RESULTS: rnaSeqMap is a toolbox for analyses that may be performed with the use of gene annotations or alternatively, in an unsupervised mode, on any genomic region to find novel or non-standard transcripts. The data back-end may be a MySQL database or a set of files in standard BAM format. The processing in R can be run on a machine without any particular hardware requirements, and scales linearly with the number of genomic loci and number of samples analyzed. The main features of rnaSeqMap include coverage operations, discovering irreducible regions of high expression, significance search and splicing analyses with nucleotide granularity. CONCLUSIONS: This software may be used for a range of applications related to RNA sequencing by building customized analysis pipelines. The applicability and precision is expected to increase in parallel with the progress of the genome coverage in sequencers.