Making the most of RNA-seq: Pre-processing sequencing data with Opossum for reliable SNP variant detection

PATZ1-Rearranged Tumors of the Central Nervous System: Characterization of a Pediatric Series of Seven Cases

PATZ1-rearranged sarcomas are well-recognized tumors as part of the family of round cell sarcoma with EWSR1-non-ETS fusions. Whether PATZ1-rearranged central nervous system (CNS) tumors are a distinct tumor type is debatable. We thoroughly characterized a pediatric series of PATZ1-rearranged CNS tumors by chromosome microarray analysis (CMA), DNA methylation analysis, gene expression profiling and, when frozen tissue is available, optical genome mapping (OGM). The series consisted of 7 cases (M:F=1.3:1, 1-17 years, median 12). On MRI, the tumors were supratentorial in close relation to the lateral ventricles (intraventricular or iuxtaventricular), preferentially located in the occipital lobe. Two major histologic groups were identified: one (4 cases) with an overall glial appearance, indicated as "neuroepithelial" (NET) by analogy with the corresponding methylation class (MC); the other (3 cases) with a predominant spindle cell sarcoma morphology, indicated as "sarcomatous" (SM). A single distinct methylation cluster encompassing both groups was identified by multidimensional scaling analysis. Despite the epigenetic homogeneity, unsupervised clustering analysis of gene expression profiles revealed 2 distinct transcriptional subgroups correlating with the histologic phenotypes. Interestingly, genes implicated in epithelial-mesenchymal transition and extracellular matrix composition were enriched in the subgroup associated to the SM phenotype. The combined use of CMA and OGM enabled the identification of chromosome 22 chromothripsis in all cases suitable for the analyses, explaining the physical association of PATZ1 to EWSR1 or MN1. Six patients are currently disease-free (median follow-up 30 months, range 12-92). One patient of the SM group developed spinal metastases at 26 months from diagnosis and is currently receiving multimodal therapy (42 months). Our data suggest that PATZ1-CNS tumors are defined by chromosome 22 chromothripsis as causative of PATZ1 fusion, show peculiar MRI features (eg, relation to lateral ventricles, supratentorial frequently posterior site), and, although epigenetically homogenous, encompass 2 distinct histologic and transcriptional subgroups.

Striated muscle-specific base editing enables correction of mutations causing dilated cardiomyopathy

Dilated cardiomyopathy is the second most common cause for heart failure with no cure except a high-risk heart transplantation. Approximately 30% of patients harbor heritable mutations which are amenable to CRISPR-based gene therapy. However, challenges related to delivery of the editing complex and off-target concerns hamper the broad applicability of CRISPR agents in the heart. We employ a combination of the viral vector AAVMYO with superior targeting specificity of heart muscle tissue and CRISPR base editors to repair patient mutations in the cardiac splice factor Rbm20, which cause aggressive dilated cardiomyopathy. Using optimized conditions, we repair >70% of cardiomyocytes in two Rbm20 knock-in mouse models that we have generated to serve as an in vivo platform of our editing strategy. Treatment of juvenile mice restores the localization defect of RBM20 in 75% of cells and splicing of RBM20 targets including TTN. Three months after injection, cardiac dilation and ejection fraction reach wild-type levels. Single-nuclei RNA sequencing uncovers restoration of the transcriptional profile across all major cardiac cell types and whole-genome sequencing reveals no evidence for aberrant off-target editing. Our study highlights the potential of base editors combined with AAVMYO to achieve gene repair for treatment of hereditary cardiac diseases.

A deep-learning-based RNA-seq germline variant caller

Summary

RNA sequencing (RNA-seq) can be applied to diverse tasks including quantifying gene expression, discovering quantitative trait loci and identifying gene fusion events. Although RNA-seq can detect germline variants, the complexities of variable transcript abundance, target capture and amplification introduce challenging sources of error. Here, we extend DeepVariant, a deep-learning-based variant caller, to learn and account for the unique challenges presented by RNA-seq data. Our DeepVariant RNA-seq model produces highly accurate variant calls from RNA-sequencing data, and outperforms existing approaches such as Platypus and GATK. We examine factors that influence accuracy, how our model addresses RNA editing events and how additional thresholding can be used to facilitate our models' use in a production pipeline.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

RNA-Seq-Pop: Exploiting the sequence in RNA sequencing-A Snakemake workflow reveals patterns of insecticide resistance in the malaria vector Anopheles gambiae

We provide a reproducible and scalable Snakemake workflow, called RNA-Seq-Pop, which provides end-to-end analysis of RNA sequencing data sets. The workflow allows the user to perform quality control, perform differential expression analyses and call genomic variants. Additional options include the calculation of allele frequencies of variants of interest, summaries of genetic variation and population structure, and genome-wide selection scans, together with clear visualizations. RNA-Seq-Pop is applicable to any organism, and we demonstrate the utility of the workflow by investigating pyrethroid resistance in selected strains of the major malaria mosquito, Anopheles gambiae. The workflow provides additional modules specifically for An. gambiae, including estimating recent ancestry and determining the karyotype of common chromosomal inversions. The Busia laboratory colony used for selections was collected in Busia, Uganda, in November 2018. We performed a comparative analysis of three groups: a parental G24 Busia strain; its deltamethrin-selected G28 offspring; and the susceptible reference strain Kisumu. Measures of genetic diversity reveal patterns consistent with that of laboratory colonization and selection, with the parental Busia strain exhibiting the highest nucleotide diversity, followed by the selected Busia offspring, and finally, Kisumu. Differential expression and variant analyses reveal that the selected Busia colony exhibits a number of distinct mechanisms of pyrethroid resistance, including the Vgsc-995S target-site mutation, upregulation of SAP genes, P450s and a cluster of carboxylesterases. During deltamethrin selections, the 2La chromosomal inversion rose in frequency (from 33% to 86%), supporting a previous link with pyrethroid resistance. RNA-Seq-Pop is hosted at: github.com/sanjaynagi/rna-seq-pop. We anticipate that the workflow will provide a useful tool to facilitate reproducible, transcriptomic studies in An. gambiae and other taxa.

Antigens Expressed by Breast Cancer Cells Undergoing EMT Stimulate Cytotoxic CD8+ T Cell Immunity

Simple Summary

The transition of cells with epithelial characteristics to those with mesenchymal characteristics (termed EMT) facilitates breast cancer invasive capacity. The EMT program can also contribute to immunosuppressive and immunoevasive properties, altering susceptibility to immune cell recognition and killing. The goal of our study was to manipulate EMT to reveal potential neoantigens that might affect the ability of tumor cells to circumvent immune escape and/or be utilized as an anticancer vaccine to kill cancer cells exhibiting the cellular plasticity that permits therapy resistance and metastatic progression. We identified potential neoantigens resulting from EMT-associated altered gene expression and alternative splicing events and observed increased immunogenicity and susceptibility to killing of the more epithelial-like cancer cells. Although the tested peptides did not protect from tumor growth, a limited number of predicted neoantigens derived from intron retention events were tested. In the future, refined prediction programs may facilitate exciting antigen discoveries.

Abstract

Antigenic differences formed by alterations in gene expression and alternative splicing are predicted in breast cancer cells undergoing epithelial to mesenchymal transition (EMT) and the reverse plasticity known as MET. How these antigenic differences impact immune interactions and the degree to which they can be exploited to enhance immune responses against mesenchymal cells is not fully understood. We utilized a master microRNA regulator of EMT to alter mesenchymal-like EO771 mammary carcinoma cells to a more epithelial phenotype. A computational approach was used to identify neoantigens derived from the resultant differentially expressed somatic variants (SNV) and alternative splicing events (neojunctions). Using whole cell vaccines and peptide-based vaccines, we find superior cytotoxicity against the more-epithelial cells and explore the potential of neojunction-derived antigens to elicit T cell responses through experiments designed to validate the computationally predicted neoantigens. Overall, results identify EMT-associated splicing factors common to both mouse and human breast cancer cells as well as immunogenic SNV- and neojunction-derived neoantigens in mammary carcinoma cells.

Identifying plant genes shaping microbiota composition in the barley rhizosphere

A prerequisite to exploiting soil microbes for sustainable crop production is the identification of the plant genes shaping microbiota composition in the rhizosphere, the interface between roots and soil. Here, we use metagenomics information as an external quantitative phenotype to map the host genetic determinants of the rhizosphere microbiota in wild and domesticated genotypes of barley, the fourth most cultivated cereal globally. We identify a small number of loci with a major effect on the composition of rhizosphere communities. One of those, designated the QRMC-3HS, emerges as a major determinant of microbiota composition. We subject soil-grown sibling lines harbouring contrasting alleles at QRMC-3HS and hosting contrasting microbiotas to comparative root RNA-seq profiling. This allows us to identify three primary candidate genes, including a Nucleotide-Binding-Leucine-Rich-Repeat (NLR) gene in a region of structural variation of the barley genome. Our results provide insights into the footprint of crop improvement on the plant’s capacity of shaping rhizosphere microbes.

A prerequisite to exploiting soil microbes for sustainable crop production is the identification of the plant genes shaping microbiota composition in the rhizosphere. Here, the authors report QTLs and the associated candidate genes underlying rhizosphere microbiome composition in barley.

iMyoblasts for ex vivo and in vivo investigations of human myogenesis and disease modeling

Skeletal muscle myoblasts (iMyoblasts) were generated from human induced pluripotent stem cells (iPSCs) using an efficient and reliable transgene-free induction and stem cell selection protocol. Immunofluorescence, flow cytometry, qPCR, digital RNA expression profiling, and scRNA-Seq studies identify iMyoblasts as a PAX3+/MYOD1+ skeletal myogenic lineage with a fetal-like transcriptome signature, distinct from adult muscle biopsy myoblasts (bMyoblasts) and iPSC-induced muscle progenitors. iMyoblasts can be stably propagated for >12 passages or 30 population doublings while retaining their dual commitment for myotube differentiation and regeneration of reserve cells. iMyoblasts also efficiently xenoengrafted into irradiated and injured mouse muscle where they undergo differentiation and fetal-adult MYH isoform switching, demonstrating their regulatory plasticity for adult muscle maturation in response to signals in the host muscle. Xenograft muscle retains PAX3+ muscle progenitors and can regenerate human muscle in response to secondary injury. As models of disease, iMyoblasts from individuals with Facioscapulohumeral Muscular Dystrophy revealed a previously unknown epigenetic regulatory mechanism controlling developmental expression of the pathological DUX4 gene. iMyoblasts from Limb-Girdle Muscular Dystrophy R7 and R9 and Walker Warburg Syndrome patients modeled their molecular disease pathologies and were responsive to small molecule and gene editing therapeutics. These findings establish the utility of iMyoblasts for ex vivo and in vivo investigations of human myogenesis and disease pathogenesis and for the development of muscle stem cell therapeutics.

An Oil Hyper-Accumulator Mutant Highlights Peroxisomal ATP Import as a Regulatory Step for Fatty Acid Metabolism in Aurantiochytrium limacinum

Thraustochytrids are marine protists that naturally accumulate triacylglycerol with long chains of polyunsaturated fatty acids, such as ω3-docosahexaenoic acid (DHA). They represent a sustainable response to the increasing demand for these "essential" fatty acids (FAs). Following an attempt to transform a strain of Aurantiochytrium limacinum, we serendipitously isolated a clone that did not incorporate any recombinant DNA but contained two to three times more DHA than the original strain. Metabolic analyses indicated a deficit in FA catabolism. However, whole transcriptome analysis did not show down-regulation of genes involved in FA catabolism. Genome sequencing revealed extensive DNA deletion in one allele encoding a putative peroxisomal adenylate transporter. Phylogenetic analyses and yeast complementation experiments confirmed the gene as a peroxisomal adenylate nucleotide transporter (AlANT1), homologous to yeast ScANT1 and plant peroxisomal adenylate nucleotide carrier AtPNC genes. In yeast and plants, a deletion of the peroxisomal adenylate transporter inhibits FA breakdown and induces FA accumulation, a phenotype similar to that described here. In response to this metabolic event, several compensatory mechanisms were observed. In particular, genes involved in FA biosynthesis were upregulated, also contributing to the high FA accumulation. These results support AlANT1 as a promising target for enhancing DHA production in Thraustochytrids.

Demystifying emerging bulk RNA-Seq applications: the application and utility of bioinformatic methodology

Significant innovations in next-generation sequencing techniques and bioinformatics tools have impacted our appreciation and understanding of RNA. Practical RNA sequencing (RNA-Seq) applications have evolved in conjunction with sequence technology and bioinformatic tools advances. In most projects, bulk RNA-Seq data is used to measure gene expression patterns, isoform expression, alternative splicing and single-nucleotide polymorphisms. However, RNA-Seq holds far more hidden biological information including details of copy number alteration, microbial contamination, transposable elements, cell type (deconvolution) and the presence of neoantigens. Recent novel and advanced bioinformatic algorithms developed the capacity to retrieve this information from bulk RNA-Seq data, thus broadening its scope. The focus of this review is to comprehend the emerging bulk RNA-Seq-based analyses, emphasizing less familiar and underused applications. In doing so, we highlight the power of bulk RNA-Seq in providing biological insights.

RNA-Seq Data for Reliable SNP Detection and Genotype Calling: Interest for Coding Variant Characterization and Cis-Regulation Analysis by Allele-Specific Expression in Livestock Species

In addition to their common usages to study gene expression, RNA-seq data accumulated over the last 10 years are a yet-unexploited resource of SNPs in numerous individuals from different populations. SNP detection by RNA-seq is particularly interesting for livestock species since whole genome sequencing is expensive and exome sequencing tools are unavailable. These SNPs detected in expressed regions can be used to characterize variants affecting protein functions, and to study cis-regulated genes by analyzing allele-specific expression (ASE) in the tissue of interest. However, gene expression can be highly variable, and filters for SNP detection using the popular GATK toolkit are not yet standardized, making SNP detection and genotype calling by RNA-seq a challenging endeavor. We compared SNP calling results using GATK suggested filters, on two chicken populations for which both RNA-seq and DNA-seq data were available for the same samples of the same tissue. We showed, in expressed regions, a RNA-seq precision of 91% (SNPs detected by RNA-seq and shared by DNA-seq) and we characterized the remaining 9% of SNPs. We then studied the genotype (GT) obtained by RNA-seq and the impact of two factors (GT call-rate and read number per GT) on the concordance of GT with DNA-seq; we proposed thresholds for them leading to a 95% concordance. Applying these thresholds to 767 multi-tissue RNA-seq of 382 birds of 11 chicken populations, we found 9.5 M SNPs in total, of which ∼550,000 SNPs per tissue and population with a reliable GT (call rate ≥ 50%) and among them, ∼340,000 with a MAF ≥ 10%. We showed that such RNA-seq data from one tissue can be used to (i) detect SNPs with a strong predicted impact on proteins, despite their scarcity in each population (16,307 SIFT deleterious missenses and 590 stop-gained), (ii) study, on a large scale, cis-regulations of gene expression, with ∼81% of protein-coding and 68% of long non-coding genes (TPM ≥ 1) that can be analyzed for ASE, and with ∼29% of them that were cis-regulated, and (iii) analyze population genetic using such SNPs located in expressed regions. This work shows that RNA-seq data can be used with good confidence to detect SNPs and associated GT within various populations and used them for different analyses as GTEx studies.

Protein synthesis inhibitor omacetaxine is effective against hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the sixth most common and the fourth most deadly cancer worldwide. The development cost of new therapeutics is a major limitation in patient outcomes. Importantly, there is a paucity of preclinical HCC models in which to test new small molecules. Herein, we implemented potentially novel patient-derived organoid (PDO) and patient-derived xenografts (PDX) strategies for high-throughput drug screening. Omacetaxine, an FDA-approved drug for chronic myelogenous leukemia (CML), was found to be a top effective small molecule in HCC PDOs. Next, omacetaxine was tested against a larger cohort of 40 human HCC PDOs. Serial dilution experiments demonstrated that omacetaxine is effective at low (nanomolar) concentrations. Mechanistic studies established that omacetaxine inhibits global protein synthesis, with a disproportionate effect on short–half-life proteins. High-throughput expression screening identified molecular targets for omacetaxine, including key oncogenes, such as PLK1. In conclusion, by using an innovative strategy, we report — for the first time to our knowledge — the effectiveness of omacetaxine in HCC. In addition, we elucidate key mechanisms of omacetaxine action. Finally, we provide a proof-of-principle basis for future studies applying drug screening PDOs sequenced with candidate validation in PDX models. Clinical trials could be considered to evaluate omacetaxine in patients with HCC.

Extensive Variation in Drought-Induced Gene Expression Changes Between Loblolly Pine Genotypes

Drought response is coordinated through expression changes in a large suite of genes. Interspecific variation in this response is common and associated with drought-tolerant and -sensitive genotypes. The extent to which different genetic networks orchestrate the adjustments to water deficit in tolerant and sensitive genotypes has not been fully elucidated, particularly in non-model or woody plants. Differential expression analysis via RNA-seq was evaluated in root tissue exposed to simulated drought conditions in two loblolly pine (Pinus taeda L.) clones with contrasting tolerance to drought. Loblolly pine is the prevalent conifer in southeastern U.S. and a major commercial forestry species worldwide. Significant changes in gene expression levels were found in more than 4,000 transcripts [drought-related transcripts (DRTs)]. Genotype by environment (GxE) interactions were prevalent, suggesting that different cohorts of genes are influenced by drought conditions in the tolerant vs. sensitive genotypes. Functional annotation categories and metabolic pathways associated with DRTs showed higher levels of overlap between clones, with the notable exception of GO categories in upregulated DRTs. Conversely, both differentially expressed transcription factors (TFs) and TF families were largely different between clones. Our results indicate that the response of a drought-tolerant loblolly pine genotype vs. a sensitive genotype to water limitation is remarkably different on a gene-by-gene level, although it involves similar genetic networks. Upregulated transcripts under drought conditions represent the most diverging component between genotypes, which might depend on the activation and repression of substantially different groups of TFs.

Transcriptomic and genomic variants between koala populations reveals underlying genetic components to disorders in a bottlenecked population

Historical hunting pressures on koalas in the southern part of their range in Australia have led to a marked genetic bottleneck when compared with their northern counterparts. There are a range of suspected genetic disorders such as testicular abnormalities, oxalate nephrosis and microcephaly reported at higher prevalence in these genetically restricted southern animals. This paper reports analysis of differential expression of genes from RNAseq of lymph nodes, SNPs present in genes and the fixation index (population differentiation due to genetic structure) of these SNPs from two populations, one in south east Queensland, representative of the northern genotype and one in the Mount Lofty Ranges South Australia, representative of the southern genotype. SNPs that differ between these two populations were significantly enriched in genes associated with brain diseases. Genes which were differentially expressed between the two populations included many associated with brain development or disease, and in addition a number associated with testicular development, including the androgen receptor. Finally, one of the 8 genes both differentially expressed and with a statistical difference in SNP frequency between populations was SLC26A6 (solute carrier family 26 member 6), an anion transporter that was upregulated in SA koalas and is associated with oxalate transport and calcium oxalate uroliths in humans. Together the differences in SNPs and gene expression described in this paper suggest an underlying genetic basis for several disorders commonly seen in southern Australian koalas, supporting the need for further research into the genetic basis of these conditions, and highlighting that genetic selection in managed populations may need to be considered in the future.

LncRBase V.2: an updated resource for multispecies lncRNAs and ClinicLSNP hosting genetic variants in lncRNAs for cancer patients

The recent discovery of long non-coding RNA as a regulatory molecule in the cellular system has altered the concept of the functional aptitude of the genome. Since our publication of the first version of LncRBase in 2014, there has been an enormous increase in the number of annotated lncRNAs of multiple species other than Human and Mouse. LncRBase V.2 hosts information of 549,648 lncRNAs corresponding to six additional species besides Human and Mouse, viz. Rat, Fruitfly, Zebrafish, Chicken, Cow and C.elegans. It provides additional distinct features such as (i) Transcription Factor Binding Site (TFBS) in the lncRNA promoter region, (ii) sub-cellular localization pattern of lncRNAs (iii) lnc-pri-miRNAs (iv) Possible small open reading frames (sORFs) within lncRNA. (v) Manually curated information of interacting target molecules and disease association of lncRNA genes (vi) Distribution of lncRNAs across multiple tissues of all species. Moreover, we have hosted ClinicLSNP within LncRBase V.2. ClinicLSNP has a comprehensive catalogue of lncRNA variants present within breast, ovarian, and cervical cancer inferred from 561 RNA-Seq data corresponding to these cancers. Further, we have checked whether these lncRNA variants overlap with (i)Repeat elements,(ii)CGI, (iii)TFBS within lncRNA loci (iv)SNP localization in trait-associated Linkage Disequilibrium(LD) region, (v)predicted the potentially pathogenic variants and (vi)effect of SNP on lncRNA secondary structure. Overall, LncRBaseV.2 is a user-friendly database to survey, search and retrieve information about multi-species lncRNAs. Further, ClinicLSNP will serve as a useful resource for cancer specific lncRNA variants and their related information. The database is freely accessible and available at http://dibresources.jcbose.ac.in/zhumur/lncrbase2/.

Uveal Melanoma-Derived Extracellular Vesicles Display Transforming Potential and Carry Protein Cargo Involved in Metastatic Niche Preparation

Extracellular vesicles (EVs) carry molecules derived from donor cells and are able to alter the properties of recipient cells. They are important players during the genesis and progression of tumors. Uveal melanoma (UM) is the most common primary intraocular tumor in adults and is associated with a high rate of metastasis, primarily to the liver. However, the mechanisms underlying this process are poorly understood. In the present study, we analyzed the oncogenic potential of UM-derived EVs and their protein signature. We isolated and characterized EVs from five UM cell lines and from normal choroidal melanocytes (NCMs). BRCA1-deficient fibroblasts (Fibro-BKO) were exposed to the EVs and analyzed for their growth in vitro and their reprograming potential in vivo following inoculation into NOD-SCID mice. Mass spectrometry of proteins from UM-EVs and NCM-EVs was performed to determine a protein signature that could elucidate potential key players in UM progression. In-depth analyses showed the presence of exosomal markers, and proteins involved in cell-cell and focal adhesion, endocytosis, and PI3K-Akt signaling pathway. Notably, we observed high expression levels of HSP90, HSP70 and integrin V in UM-EVs. Our data bring new evidence on the involvement of UM-EVs in cancer progression and metastasis.

Development and comparison of RNA-sequencing pipelines for more accurate SNP identification: practical example of functional SNP detection associated with feed efficiency in Nellore beef cattle

Background

Optimization of an RNA-Sequencing (RNA-Seq) pipeline is critical to maximize power and accuracy to identify genetic variants, including SNPs, which may serve as genetic markers to select for feed efficiency, leading to economic benefits for beef production. This study used RNA-Seq data (GEO Accession ID: PRJEB7696 and PRJEB15314) from muscle and liver tissue, respectively, from 12 Nellore beef steers selected from 585 steers with residual feed intake measures (RFI; n = 6 low-RFI, n = 6 high-RFI). Three RNA-Seq pipelines were compared including multi-sample calling from i) non-merged samples; ii) merged samples by RFI group, iii) merged samples by RFI and tissue group. The RNA-Seq reads were aligned against the UMD3.1 bovine reference genome (release 94) assembly using STAR aligner. Variants were called using BCFtools and variant effect prediction (VeP) and functional annotation (ToppGene) analyses were performed.

Results

On average, total reads detected for Approach i) non-merged samples for liver and muscle, were 18,362,086.3 and 35,645,898.7, respectively. For Approach ii), merging samples by RFI group, total reads detected for each merged group was 162,030,705, and for Approach iii), merging samples by RFI group and tissues, was 324,061,410, revealing the highest read depth for Approach iii). Additionally, Approach iii) merging samples by RFI group and tissues, revealed the highest read depth per variant coverage (572.59 ± 3993.11) and encompassed the majority of localized positional genes detected by each approach. This suggests Approach iii) had optimized detection power, read depth, and accuracy of SNP calling, therefore increasing confidence of variant detection and reducing false positive detection. Approach iii) was then used to detect unique SNPs fixed within low- (12,145) and high-RFI (14,663) groups. Functional annotation of SNPs revealed positional candidate genes, for each RFI group (2886 for low-RFI, 3075 for high-RFI), which were significantly (P < 0.05) associated with immune and metabolic pathways.

Conclusion

The most optimized RNA-Seq pipeline allowed for more accurate identification of SNPs, associated positional candidate genes, and significantly associated metabolic pathways in muscle and liver tissues, providing insight on the underlying genetic architecture of feed efficiency in beef cattle.

Genome-Wide Development and Validation of Cost-Effective KASP Marker Assays for Genetic Dissection of Heat Stress Tolerance in Maize

Maize is the third most important cereal crop worldwide. However, its production is vulnerable to heat stress, which is expected to become more and more severe in coming years. Germplasm resilient to heat stress has been identified, but its underlying genetic basis remains poorly understood. Genomic mapping technologies can fill the void, provided robust markers are available to tease apart the genotype-phenotype relationship. In the present investigation, we used data from an RNA-seq experiment to identify single nucleotide polymorphisms (SNPs) between two contrasting lines, LM11 and CML25, sensitive and tolerant to heat stress, respectively. The libraries for RNA-seq were made following heat stress treatment from three separate tissues/organs, comprising the top leaf, ovule, and pollen, all of which are highly vulnerable to damage by heat stress. The single nucleotide variants (SNVs) calling used STAR mapper and GATK caller pipelines in a combined approach to identify highly accurate SNPs between the two lines. A total of 554,423, 410,698, and 596,868 SNVs were discovered between LM11 and CML25 after comparing the transcript sequence reads from the leaf, pollen, and ovule libraries, respectively. Hundreds of these SNPs were then selected to develop into genome-wide Kompetitive Allele-Specific PCR (KASP) markers, which were validated to be robust with a successful SNP conversion rate of 71%. Subsequently, these KASP markers were used to effectively genotype an F₂ mapping population derived from a cross of LM11 and CML25. Being highly cost-effective, these KASP markers provide a reliable molecular marker toolkit to not only facilitate the genetic dissection of the trait of heat stress tolerance but also to accelerate the breeding of heat-resilient maize by marker-assisted selection (MAS).

RNAIndel: discovering somatic coding indels from tumor RNA-Seq data

MOTIVATION

Reliable identification of expressed somatic insertions/deletions (indels) is an unmet need due to artifacts generated in PCR-based RNA-Seq library preparation and the lack of normal RNA-Seq data, presenting analytical challenges for discovery of somatic indels in tumor transcriptome.

RESULTS

We present RNAIndel, a tool for predicting somatic, germline and artifact indels from tumor RNA-Seq data. RNAIndel leverages features derived from indel sequence context and biological effect in a machine-learning framework. Except for tumor samples with microsatellite instability, RNAIndel robustly predicts 88-100% of somatic indels in five diverse test datasets of pediatric and adult cancers, even recovering subclonal (VAF range 0.01-0.15) driver indels missed by targeted deep-sequencing, outperforming the current best-practice for RNA-Seq variant calling which had 57% sensitivity but with 14 times more false positives.

AVAILABILITY AND IMPLEMENTATION

RNAIndel is freely available at https://github.com/stjude/RNAIndel.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genomic Dissection of a Wild Region in a Superior Solanum pennellii Introgression Sub-Line with High Ascorbic Acid Accumulation in Tomato Fruit

The Solanum pennellii introgression lines (ILs) have been exploited to map quantitative trait loci (QTLs) and identify favorable alleles that could improve fruit quality traits in tomato varieties. Over the past few years, ILs exhibiting increased content of ascorbic acid in the fruit have been selected, among which the sub-line R182. The aims of this work were to identify the genes of the wild donor S. pennellii harbored by the sub-line and to detect genes controlling ascorbic acid accumulation by using genomics tools. A Genotyping-By-Sequencing (GBS) approach confirmed that no wild introgressions were present in the sub-line besides one region on chromosome 7. By using a dense single nucleotide polymorphism (SNP) map obtained by RNA sequencing (RNA-Seq), the wild region of the sub-line was finely identified; thus, defining 39 wild genes that replaced 33 genes of the ILs genetic background (cv. M82). The differentially expressed genes mapping in the region and the variants detected among the cultivated and the wild alleles evidenced the potential role of the novel genes present in the wild region. Interestingly, one upregulated gene, annotated as a major facilitator superfamily protein, showed a novel structure in R182, with respect to the parental lines. These genes will be further investigated using gene editing strategies.

Identifying Transcription Error-Enriched Genomic Loci Using Nuclear Run-on Circular-Sequencing Coupled with Background Error Modeling

RNA polymerase transcribes certain genomic loci with higher errors rates. These transcription error-enriched genomic loci (TEELs) have implications in disease. Current deep-sequencing methods cannot distinguish TEELs from post-transcriptional modifications, stochastic transcription errors, and technical noise, impeding efforts to elucidate the mechanisms linking TEELs to disease. Here, we describe background error model-coupled precision nuclear run-on circular-sequencing (EmPC-seq) to discern genomic regions enriched for transcription misincorporations. EmPC-seq innovatively combines a nuclear run-on assay for capturing nascent RNA before post-transcriptional modifications, a circular-sequencing step that sequences the same nascent RNA molecules multiple times to improve accuracy, and a statistical model for distinguishing error-enriched regions among stochastic polymerase errors. Applying EmPC-seq to the ribosomal RNA transcriptome, we show that TEELs of RNA polymerase I are not randomly distributed but clustered together, with higher error frequencies at nascent transcript 3' ends. Our study establishes a reliable method of identifying TEELs with nucleotide precision, which can help elucidate their molecular origins.

Tumor Fusion Burden as a Hallmark of Immune Infiltration in Prostate Cancer

Prostate cancer is the second leading cause of cancer-related death in men. Despite having a relatively lower tumor mutational burden than most tumor types, multiple gene fusions such as TMPRSS2:ERG have been characterized and linked to more aggressive disease. Individual tumor samples have been found to contain multiple fusions, and it remains unknown whether these fusions increase tumor immunogenicity. Here, we investigated the role of fusion burden on the prevalence and expression of key molecular and immune effectors in prostate cancer tissue specimens that represented the different stages of disease progression and androgen sensitivity, including hormone-sensitive and castration-resistant prostate cancer. We found that tumor fusion burden was inversely correlated with tumor mutational burden and not associated with disease stage. High fusion burden correlated with high immune infiltration, PD-L1 expression on immune cells, and immune signatures, representing activation of T cells and M1 macrophages. High fusion burden inversely correlated with immune-suppressive signatures. Our findings suggest that high tumor fusion burden may be a more appropriate biomarker than tumor mutational burden in prostate cancer, as it more closely associates with immunogenicity, and suggests that tumors with high fusion burden could be potential candidates for immunotherapeutic agents.

Intraspecific Diversity in the Cold Stress Response of Transposable Elements in the Diatom Leptocylindrus aporus

Transposable elements (TEs), activated as a response to unfavorable conditions, have been proposed to contribute to the generation of genetic and phenotypic diversity in diatoms. Here we explore the transcriptome of three warm water strains of the diatom Leptocylindrus aporus, and the possible involvement of TEs in their response to changing temperature conditions. At low temperature (13 °C) several stress response proteins were overexpressed, confirming low temperature to be unfavorable for L. aporus, while TE-related transcripts of the LTR retrotransposon superfamily were the most enriched transcripts. Their expression levels, as well as most of the stress-related proteins, were found to vary significantly among strains, and even within the same strains analysed at different times. The lack of overexpression after many months of culturing suggests a possible role of physiological plasticity in response to growth under controlled laboratory conditions. While further investigation on the possible central role of TEs in the diatom stress response is warranted, the strain-specific responses and possible role of in-culture evolution draw attention to the interplay between the high intraspecific variability and the physiological plasticity of diatoms, which can both contribute to the adaptation of a species to a wide range of conditions in the marine environment.

Variant analysis pipeline for accurate detection of genomic variants from transcriptome sequencing data

The wealth of information deliverable from transcriptome sequencing (RNA-seq) is significant, however current applications for variant detection still remain a challenge due to the complexity of the transcriptome. Given the ability of RNA-seq to reveal active regions of the genome, detection of RNA-seq SNPs can prove valuable in understanding the phenotypic diversity between populations. Thus, we present a novel computational workflow named VAP (Variant Analysis Pipeline) that takes advantage of multiple RNA-seq splice aware aligners to call SNPs in non-human models using RNA-seq data only. We applied VAP to RNA-seq from a highly inbred chicken line and achieved high accuracy when compared with the matching whole genome sequencing (WGS) data. Over 65% of WGS coding variants were identified from RNA-seq. Further, our results discovered SNPs resulting from post transcriptional modifications, such as RNA editing, which may reveal potentially functional variation that would have otherwise been missed in genomic data. Even with the limitation in detecting variants in expressed regions only, our method proves to be a reliable alternative for SNP identification using RNA-seq data. The source code and user manuals are available at https://modupeore.github.io/VAP/.

Colorectal cancer-derived extracellular vesicles induce transformation of fibroblasts into colon carcinoma cells

BACKGROUND

We reported that horizontal transfer of malignant traits to target cells is a potential pathway to explain cancer dissemination. Although these results were encouraging, they were never corroborated by data showing the molecular mechanisms responsible for the observed phenomenon.

METHODS

In the present study, we exposed BRCA1-KO fibroblasts to extracellular vesicles (EVs) isolated from a colon cancer cell line (HT29) and from sera of patients with colorectal cancer. Three weeks after exposure, fibroblasts were injected subcutaneously into NOD-SCID mice. Whole genome sequencing, transcriptome analysis and RNA sequencing of cancer EVs and fibroblasts prior and after exposure to cancer EVs were performed.

RESULTS

Phenotypical transformation of the fibroblasts into colon cancer cells was confirmed by histopathological study of the xenotransplants. We observed that EV-mediated transfer of cancer microRNAs was responsible for the transition from a mesenchymal to an epithelial phenotype (MET) in the treated fibroblasts as well as activation of cell cycle progression and cell survival pathways. DNA and RNA sequencing suggested that cancer DNA was transferred and possibly transcribed in target cells. Furthermore, injection of colon cancer EVs in the tail vein of NOD-SCID mice determined neoplastic transformation and metastases in the lungs of the mice confirming for the first time the hypothesis that transfer of malignant epithelial cancer traits to distant target cells is a concept applicable to in vivo models.

CONCLUSIONS

These discoveries shed new light into the molecular mechanisms behind the horizontal transfer of malignant traits and confirm the notion that metastatic disease might be reproduced through transfer of circulating genetic material.

Reproducible bioinformatics project: a community for reproducible bioinformatics analysis pipelines

Background

Reproducibility of a research is a key element in the modern science and it is mandatory for any industrial application. It represents the ability of replicating an experiment independently by the location and the operator. Therefore, a study can be considered reproducible only if all used data are available and the exploited computational analysis workflow is clearly described. However, today for reproducing a complex bioinformatics analysis, the raw data and the list of tools used in the workflow could be not enough to guarantee the reproducibility of the results obtained. Indeed, different releases of the same tools and/or of the system libraries (exploited by such tools) might lead to sneaky reproducibility issues.

Results

To address this challenge, we established the Reproducible Bioinformatics Project (RBP), which is a non-profit and open-source project, whose aim is to provide a schema and an infrastructure, based on docker images and R package, to provide reproducible results in Bioinformatics. One or more Docker images are then defined for a workflow (typically one for each task), while the workflow implementation is handled via R-functions embedded in a package available at github repository. Thus, a bioinformatician participating to the project has firstly to integrate her/his workflow modules into Docker image(s) exploiting an Ubuntu docker image developed ad hoc by RPB to make easier this task. Secondly, the workflow implementation must be realized in R according to an R-skeleton function made available by RPB to guarantee homogeneity and reusability among different RPB functions. Moreover she/he has to provide the R vignette explaining the package functionality together with an example dataset which can be used to improve the user confidence in the workflow utilization.

Conclusions

Reproducible Bioinformatics Project provides a general schema and an infrastructure to distribute robust and reproducible workflows. Thus, it guarantees to final users the ability to repeat consistently any analysis independently by the used UNIX-like architecture.

Indel sensitive and comprehensive variant/mutation detection from RNA sequencing data for precision medicine

Background

RNA-seq is the most commonly used sequencing application. Not only does it measure gene expression but it is also an excellent media to detect important structural variants such as single nucleotide variants (SNVs), insertion/deletion (Indels) or fusion transcripts. However, detection of these variants is challenging and complex from RNA-seq. Here we describe a sensitive and accurate analytical pipeline which detects various mutations at once for translational precision medicine.

Methods

The pipeline incorporates most sensitive aligners for Indels in RNA-Seq, the best practice for data preprocessing and variant calling, and STAR-fusion is for chimeric transcripts. Variants/mutations are annotated, and key genes can be extracted for further investigation and clinical actions. Three datasets were used to evaluate the performance of the pipeline for SNVs, indels and fusion transcripts.

Results

For the well-defined variants from NA12878 by GIAB project, about 95% and 80% of sensitivities were obtained for SNVs and indels, respectively, in matching RNA-seq. Comparison with other variant specific tools showed good performance of the pipeline. For the lung cancer dataset with 41 known and oncogenic mutations, 39 were detected by the pipeline with STAR aligner and all by the GSNAP aligner. An actionable EML4 and ALK fusion was also detected in one of the tumors, which also demonstrated outlier ALK expression. For 9 fusions spiked-into RNA-seq libraries with different concentrations, the pipeline was able to detect all in unfiltered results although some at very low concentrations may be missed when filtering was applied.

Conclusions

The new RNA-seq workflow is an accurate and comprehensive mutation profiler from RNA-seq. Key or actionable mutations are reliably detected from RNA-seq, which makes it a practical alternative source for personalized medicine.

Electronic supplementary material

The online version of this article (10.1186/s12920-018-0391-5) contains supplementary material, which is available to authorized users.

A 2-transcript host cell signature distinguishes viral from bacterial diarrhea and it is influenced by the severity of symptoms

Recently, a biomarker signature consisting of 2-transcript host RNAs was proposed for discriminating bacterial from viral infections in febrile children. We evaluated the performance of this signature in a different disease scenario, namely a cohort of Mexican children (n = 174) suffering from acute diarrhea of different infectious etiologies. We first examined the admixed background of the patients, indicating that most of them have a predominantly Native American genetic ancestry with a variable amount of European background (ranging from 0% to 57%). The results confirm that the RNA test can discriminate between viral and bacterial causes of infection (t-test; P-value = 6.94×10⁻¹¹; AUC = 80%; sensitivity: 68% [95% CI: 55%–79%]; specificity: 84% [95% CI: 78%–90%]), but the strength of the signal differs substantially depending on the causal pathogen, with the stronger signal being that of Shigella (P-value = 3.14 × 10⁻¹²; AUC = 89; sensitivity: 70% [95% CI: 57%–83%]; specificity: 100% [95% CI: 100%–100%]). The accuracy of this test improves significantly when excluding mild cases (P-value = 2.13 × 10⁻⁶; AUC = 85%; sensitivity: 79% [95% CI: 58%–95%]; specificity: 78% [95% CI: 65%–88%]). The results broaden the scope of previous studies by incorporating different pathogens, variable levels of disease severity, and different ancestral background of patients, and add confirmatory support to the clinical utility of these 2-transcript biomarkers.