Extracellular vesicles from mouse trophoblast cells: Effects on neural progenitor cells and potential participants in the placenta-brain axis†.

The fetal brain of the mouse is thought to be dependent upon the placenta as a source of serotonin (5-hydroxytryptamine; 5-HT) and other factors. How factors reach the developing brain remains uncertain but are postulated here to be part of the cargo carried by placental extracellular vesicles (EV). We have analyzed the protein, catecholamine, and small RNA content of EV from mouse trophoblast stem cells (TSC) and TSC differentiated into parietal trophoblast giant cells (pTGC), potential primary purveyors of 5-HT. Current studies examined how exposure of mouse neural progenitor cells (NPC) to EV from either TSC or pTGC affect their transcriptome profiles. The EV from trophoblast cells contained relatively high amounts of 5-HT, as well as dopamine and norepinephrine, but there were no significant differences between EV derived from pTGC and from TSC. Content of miRNA and small nucleolar (sno)RNA, however, did differ according to EV source, and snoRNA were upregulated in EV from pTGC. The primary inferred targets of the microRNA (miRNA) from both pTGC and TSC were mRNA enriched in the fetal brain. NPC readily internalized EV, leading to changes in their transcriptome profiles. Transcripts regulated were mainly ones enriched in neural tissues. The transcripts in EV-treated NPC that demonstrated a likely complementarity with miRNA in EV were mainly up- rather than downregulated, with functions linked to neuronal processes. Our results are consistent with placenta-derived EV providing direct support for fetal brain development and being an integral part of the placenta-brain axis.

Fine mapping of major QTL qshgd1 for spontaneous haploid genome doubling in maize (Zea mays L.).

KEY MESSAGE: A large-effect QTL was fine mapped, which revealed 79 gene models, with 10 promising candidate genes, along with a novel inversion. In commercial maize breeding, doubled haploid (DH) technology is arguably the most efficient resource for rapidly developing novel, completely homozygous lines. However, the DH strategy, using in vivo haploid induction, currently requires the use of mutagenic agents which can be not only hazardous, but laborious. This study focuses on an alternative approach to develop DH lines-spontaneous haploid genome duplication (SHGD) via naturally restored haploid male fertility (HMF). Inbred lines A427 and Wf9, the former with high HMF and the latter with low HMF, were selected to fine-map a large-effect QTL associated with SHGD-qshgd1. SHGD alleles were derived from A427, with novel haploid recombinant groups having varying levels of the A427 chromosomal region recovered. The chromosomal region of interest is composed of 45 megabases (Mb) of genetic information on chromosome 5. Significant differences between haploid recombinant groups for HMF were identified, signaling the possibility of mapping the QTL more closely. Due to suppression of recombination from the proximity of the centromere, and a newly discovered inversion region, the associated QTL was only confined to a 25 Mb region, within which only a single recombinant was observed among ca. 9,000 BC1 individuals. Nevertheless, 79 gene models were identified within this 25 Mb region. Additionally, 10 promising candidate genes, based on RNA-seq data, are described for future evaluation, while the narrowed down genome region is accessible for straightforward introgression into elite germplasm by BC methods.

Foster thy young: enhanced prediction of orphan genes in assembled genomes.

Proteins encoded by newly-emerged genes ('orphan genes') share no sequence similarity with proteins in any other species. They provide organisms with a reservoir of genetic elements to quickly respond to changing selection pressures. Here, we systematically assess the ability of five gene prediction pipelines to accurately predict genes in genomes according to phylostratal origin. BRAKER and MAKER are existing, popular ab initio tools that infer gene structures by machine learning. Direct Inference is an evidence-based pipeline we developed to predict gene structures from alignments of RNA-Seq data. The BIND pipeline integrates ab initio predictions of BRAKER and Direct inference; MIND combines Direct Inference and MAKER predictions. We use highly-curated Arabidopsis and yeast annotations as gold-standard benchmarks, and cross-validate in rice. Each pipeline under-predicts orphan genes (as few as 11 percent, under one prediction scenario). Increasing RNA-Seq diversity greatly improves prediction efficacy. The combined methods (BIND and MIND) yield best predictions overall, BIND identifying 68% of annotated orphan genes, 99% of ancient genes, and give the highest sensitivity score regardless dataset in Arabidopsis. We provide a light weight, flexible, reproducible, and well-documented solution to improve gene prediction.

Systematic in vitro specificity profiling reveals nicking defects in natural and engineered CRISPR-Cas9 variants.

Cas9 is an RNA-guided endonuclease in the bacterial CRISPR-Cas immune system and a popular tool for genome editing. The commonly used Streptococcus pyogenes Cas9 (SpCas9) is relatively non-specific and prone to off-target genome editing. Other Cas9 orthologs and engineered variants of SpCas9 have been reported to be more specific. However, previous studies have focused on specificity of double-strand break (DSB) or indel formation, potentially overlooking alternative cleavage activities of these Cas9 variants. In this study, we employed in vitro cleavage assays of target libraries coupled with high-throughput sequencing to systematically compare cleavage activities and specificities of two natural Cas9 variants (SpCas9 and Staphylococcus aureus Cas9) and three engineered SpCas9 variants (SpCas9 HF1, HypaCas9 and HiFi Cas9). We observed that all Cas9s tested could cleave target sequences with up to five mismatches. However, the rate of cleavage of both on-target and off-target sequences varied based on target sequence and Cas9 variant. In addition, SaCas9 and engineered SpCas9 variants nick targets with multiple mismatches but have a defect in generating a DSB, while SpCas9 creates DSBs at these targets. Overall, these differences in cleavage rates and DSB formation may contribute to varied specificities observed in genome editing studies.

CRISPR-Cas12a has widespread off-target and dsDNA-nicking effects.

Cas12a (Cpf1) is an RNA-guided endonuclease in the bacterial type V-A CRISPR-Cas anti-phage immune system that can be repurposed for genome editing. Cas12a can bind and cut dsDNA targets with high specificity in vivo, making it an ideal candidate for expanding the arsenal of enzymes used in precise genome editing. However, this reported high specificity contradicts Cas12a's natural role as an immune effector against rapidly evolving phages. Here, we employed high-throughput in vitro cleavage assays to determine and compare the native cleavage specificities and activities of three different natural Cas12a orthologs (FnCas12a, LbCas12a, and AsCas12a). Surprisingly, we observed pervasive sequence-specific nicking of randomized target libraries, with strong nicking of DNA sequences containing up to four mismatches in the Cas12a-targeted DNA-RNA hybrid sequences. We also found that these nicking and cleavage activities depend on mismatch type and position and vary with Cas12a ortholog and CRISPR RNA sequence. Our analysis further revealed robust nonspecific nicking of dsDNA when Cas12a is activated by binding to a target DNA. Together, our findings reveal that Cas12a has multiple nicking activities against dsDNA substrates and that these activities vary among different Cas12a orthologs.

SequelTools: a suite of tools for working with PacBio Sequel raw sequence data.

BACKGROUND: PacBio sequencing is an incredibly valuable third-generation DNA sequencing method due to very long read lengths, ability to detect methylated bases, and its real-time sequencing methodology. Yet, hitherto no tool was available for analyzing the quality of, subsampling, and filtering PacBio data. RESULTS: Here we present SequelTools, a command-line program containing three tools: Quality Control, Read Subsampling, and Read Filtering. The Quality Control tool quickly processes PacBio Sequel raw sequence data from multiple SMRTcells producing multiple statistics and publication-quality plots describing the quality of the data including N50, read length and count statistics, PSR, and ZOR. The Read Subsampling tool allows the user to subsample reads by one or more of the following criteria: longest subreads per CLR or random CLR selection. The Read Filtering tool provides options for normalizing data by filtering out certain low-quality scraps reads and/or by minimum CLR length. SequelTools is implemented in bash, R, and Python using only standard libraries and packages and is platform independent. CONCLUSIONS: SequelTools is a program that provides the only free, fast, and easy-to-use quality control tool, and the only program providing this kind of read subsampling and read filtering for PacBio Sequel raw sequence data, and is available at https://github.com/ISUgenomics/SequelTools .

GenomeQC: a quality assessment tool for genome assemblies and gene structure annotations.

BACKGROUND: Genome assemblies are foundational for understanding the biology of a species. They provide a physical framework for mapping additional sequences, thereby enabling characterization of, for example, genomic diversity and differences in gene expression across individuals and tissue types. Quality metrics for genome assemblies gauge both the completeness and contiguity of an assembly and help provide confidence in downstream biological insights. To compare quality across multiple assemblies, a set of common metrics are typically calculated and then compared to one or more gold standard reference genomes. While several tools exist for calculating individual metrics, applications providing comprehensive evaluations of multiple assembly features are, perhaps surprisingly, lacking. Here, we describe a new toolkit that integrates multiple metrics to characterize both assembly and gene annotation quality in a way that enables comparison across multiple assemblies and assembly types. RESULTS: Our application, named GenomeQC, is an easy-to-use and interactive web framework that integrates various quantitative measures to characterize genome assemblies and annotations. GenomeQC provides researchers with a comprehensive summary of these statistics and allows for benchmarking against gold standard reference assemblies. CONCLUSIONS: The GenomeQC web application is implemented in R/Shiny version 1.5.9 and Python 3.6 and is freely available at https://genomeqc.maizegdb.org/ under the GPL license. All source code and a containerized version of the GenomeQC pipeline is available in the GitHub repository https://github.com/HuffordLab/GenomeQC.

phylostratr: a framework for phylostratigraphy.

MOTIVATION: The goal of phylostratigraphy is to infer the evolutionary origin of each gene in an organism. This is done by searching for homologs within increasingly broad clades. The deepest clade that contains a homolog of the protein(s) encoded by a gene is that gene's phylostratum. RESULTS: We have created a general R-based framework, phylostratr, to estimate the phylostratum of every gene in a species. The program fully automates analysis: selecting species for balanced representation, retrieving sequences, building databases, inferring phylostrata and returning diagnostics. Key diagnostics include: detection of genes with inferred homologs in old clades, but not intermediate ones; proteome quality assessments; false-positive diagnostics, and checks for missing organellar genomes. phylostratr allows extensive customization and systematic comparisons of the influence of analysis parameters or genomes on phylostrata inference. A user may: modify the automatically generated clade tree or use their own tree; provide custom sequences in place of those automatically retrieved from UniProt; replace BLAST with an alternative algorithm; or tailor the method and sensitivity of the homology inference classifier. We show the utility of phylostratr through case studies in Arabidopsis thaliana and Saccharomyces cerevisiae. AVAILABILITY AND IMPLEMENTATION: Source code available at https://github.com/arendsee/phylostratr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

fagin: synteny-based phylostratigraphy and finer classification of young genes.

BACKGROUND: With every new genome that is sequenced, thousands of species-specific genes (orphans) are found, some originating from ultra-rapid mutations of existing genes, many others originating de novo from non-genic regions of the genome. If some of these genes survive across speciations, then extant organisms will contain a patchwork of genes whose ancestors first appeared at different times. Standard phylostratigraphy, the technique of partitioning genes by their age, is based solely on protein similarity algorithms. However, this approach relies on negative evidence ─ a failure to detect a homolog of a query gene. An alternative approach is to limit the search for homologs to syntenic regions. Then, genes can be positively identified as de novo orphans by tracing them to non-coding sequences in related species. RESULTS: We have developed a synteny-based pipeline in the R framework. Fagin determines the genomic context of each query gene in a focal species compared to homologous sequence in target species. We tested the fagin pipeline on two focal species, Arabidopsis thaliana (plus four target species in Brassicaseae) and Saccharomyces cerevisiae (plus six target species in Saccharomyces). Using microsynteny maps, fagin classified the homology relationship of each query gene against each target genome into three main classes, and further subclasses: AAic (has a coding syntenic homolog), NTic (has a non-coding syntenic homolog), and Unknown (has no detected syntenic homolog). fagin inferred over half the "Unknown" A. thaliana query genes, and about 20% for S. cerevisiae, as lacking a syntenic homolog because of local indels or scrambled synteny. CONCLUSIONS: fagin augments standard phylostratigraphy, and extends synteny-based phylostratigraphy with an automated, customizable, and detailed contextual analysis. By comparing synteny-based phylostrata to standard phylostrata, fagin systematically identifies those orphans and lineage-specific genes that are well-supported to have originated de novo. Analyzing within-species genomes should distinguish orphan genes that may have originated through rapid divergence from de novo orphans. Fagin also delineates whether a gene has no syntenic homolog because of technical or biological reasons. These analyses indicate that some orphans may be associated with regions of high genomic perturbation.

The genome of the soybean cyst nematode (Heterodera glycines) reveals complex patterns of duplications involved in the evolution of parasitism genes.

BACKGROUND: Heterodera glycines, commonly referred to as the soybean cyst nematode (SCN), is an obligatory and sedentary plant parasite that causes over a billion-dollar yield loss to soybean production annually. Although there are genetic determinants that render soybean plants resistant to certain nematode genotypes, resistant soybean cultivars are increasingly ineffective because their multi-year usage has selected for virulent H. glycines populations. The parasitic success of H. glycines relies on the comprehensive re-engineering of an infection site into a syncytium, as well as the long-term suppression of host defense to ensure syncytial viability. At the forefront of these complex molecular interactions are effectors, the proteins secreted by H. glycines into host root tissues. The mechanisms of effector acquisition, diversification, and selection need to be understood before effective control strategies can be developed, but the lack of an annotated genome has been a major roadblock. RESULTS: Here, we use PacBio long-read technology to assemble a H. glycines genome of 738 contigs into 123 Mb with annotations for 29,769 genes. The genome contains significant numbers of repeats (34%), tandem duplicates (18.7 Mb), and horizontal gene transfer events (151 genes). A large number of putative effectors (431 genes) were identified in the genome, many of which were found in transposons. CONCLUSIONS: This advance provides a glimpse into the host and parasite interplay by revealing a diversity of mechanisms that give rise to virulence genes in the soybean cyst nematode, including: tandem duplications containing over a fifth of the total gene count, virulence genes hitchhiking in transposons, and 107 horizontal gene transfers not reported in other plant parasitic nematodes thus far. Through extensive characterization of the H. glycines genome, we provide new insights into H. glycines biology and shed light onto the mystery underlying complex host-parasite interactions. This genome sequence is an important prerequisite to enable work towards generating new resistance or control measures against H. glycines.

Evidence for a Unique DNA-Dependent RNA Polymerase in Cereal Crops.

Gene duplication is an important driver for the evolution of new genes and protein functions. Duplication of DNA-dependent RNA polymerase (Pol) II subunits within plants led to the emergence of RNA Pol IV and V complexes, each of which possess unique functions necessary for RNA-directed DNA Methylation. Comprehensive identification of Pol V subunit orthologs across the monocot radiation revealed a duplication of the largest two subunits within the grasses (Poaceae), including critical cereal crops. These paralogous Pol subunits display sequence conservation within catalytic domains, but their carboxy terminal domains differ in length and character of the Ago-binding platform, suggesting unique functional interactions. Phylogenetic analysis of the catalytic region indicates positive selection on one paralog following duplication, consistent with retention via neofunctionalization. Positive selection on residue pairs that are predicted to interact between subunits suggests that paralogous subunits have evolved specific assembly partners. Additional Pol subunits as well as Pol-interacting proteins also possess grass-specific paralogs, supporting the hypothesis that a novel Pol complex with distinct function has evolved in the grass family, Poaceae.

Insights into teleost sex determination from the Seriola dorsalis genome assembly.

BACKGROUND: The assembly and annotation of a genome is a valuable resource for a species, with applications ranging from conservation genomics to gene discovery. Genomic resource development is especially important for species in culture, such as the California Yellowtail (Seriola dorsalis), the likely candidate for the establishment of commercial offshore aquaculture production in southern California. Genomic resource development for this species will improve the understanding of sex and other phenotypic traits, and allow for rapid increases in genetic improvement for and economic gain in culture production. RESULTS: We describe the assembly and annotation of the S. dorsalis genome, and present resequencing data from 45 male and 45 female wild-caught S. dorsalis used to identify a sex-determining region and marker in this species. The genome assembly captured approximately 93% of the total 685 MB genome with an average coverage depth of 180×. Using the assembled genome, resequencing data from the 90 fish were aligned to place boundaries on the sex-determining region. Sex-specific markers were developed based on a female-specific, 61 nucleotide deletion identified in that region. We hypothesize that Estradiol 17-beta-dehydrogenase is the putative sex-determining gene and propose a plausible genetic mechanism for ZW sex determination in S. dorsalis involving a female-specific deletion of a transcription factor binding motif that may be targeted by Sox3. CONCLUSIONS: Understanding the mechanism of sex determination and development of assays to determine sex is critical both for management of wild fisheries and for development of efficient and sustainable aquaculture practices. In addition, this genome assembly for S. dorsalis will be a substantial resource for a variety of future research applications.

CRISPR interference and priming varies with individual spacer sequences.

CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR associated) systems allow bacteria to adapt to infection by acquiring 'spacer' sequences from invader DNA into genomic CRISPR loci. Cas proteins use RNAs derived from these loci to target cognate sequences for destruction through CRISPR interference. Mutations in the protospacer adjacent motif (PAM) and seed regions block interference but promote rapid 'primed' adaptation. Here, we use multiple spacer sequences to reexamine the PAM and seed sequence requirements for interference and priming in the Escherichia coli Type I-E CRISPR-Cas system. Surprisingly, CRISPR interference is far more tolerant of mutations in the seed and the PAM than previously reported, and this mutational tolerance, as well as priming activity, is highly dependent on spacer sequence. We identify a large number of functional PAMs that can promote interference, priming or both activities, depending on the associated spacer sequence. Functional PAMs are preferentially acquired during unprimed 'naïve' adaptation, leading to a rapid priming response following infection. Our results provide numerous insights into the importance of both spacer and target sequences for interference and priming, and reveal that priming is a major pathway for adaptation during initial infection.

A study on the distribution of 37 well conserved families of C2H2 zinc finger genes in eukaryotes.

BACKGROUND: The C2H2 zinc-finger (ZNF) containing gene family is one of the largest and most complex gene families in metazoan genomes. These genes are known to exist in almost all eukaryotes, and they constitute a major subset of eukaryotic transcription factors. The genes of this family usually occur as clusters in genomes and are thought to have undergone a massive expansion in vertebrates by multiple tandem duplication events (BMC Evol Biol 8:176, 2008). RESULTS: In this study, we combined two popular approaches for homolog detection, Reciprocal Best Hit (RBH) (Proc Natl Acad Sci USA 95:6239-6244, 1998) and Hidden-Markov model (HMM) profiles search (Bioinformatics 14:755-763, 1998), on a diverse set of complete genomes of 124 eukaryotic species ranging from excavates to humans to identify all detectable members of 37 C2H2 ZNF gene families. We succeeded in identifying 3,890 genes as distinct members of 37 C2H2 gene families. These 37 families are distributed among the eukaryotes as progressive additions of gene blocks with increasing complexity of the organisms. The first block featuring the protists had 7 families, the second block featuring plants had 2 families, the third block featuring the fungi had 2 families (one of which was also present in plants) and the final block consisted of metazoans with 25 families. Among the metazoans, the simpler unicellular metazoans had just 15 of the 25 families while most of the bilaterians had all 25 families making up a total of 37 families. Multiple potential examples of lineage-specific gene duplications and gene losses were also observed. CONCLUSIONS: Our hybrid approach combines features of the both RBH and HMM methods for homolog detection. This largely automated technique is much faster than manual methods and is able to detect homologs accurately and efficiently among a diverse set of organisms. Our analysis of the 37 evolutionarily conserved C2H2 ZNF gene families revealed a stepwise appearance of ZNF families, agreeing well with the phylogenetic relationship of the organisms compared and their presumed stepwise increase in complexity (Science 300:1694, 2003).

Hybrid allele-specific ChIP-seq analysis identifies variation in brassinosteroid-responsive transcription factor binding linked to traits in maize.

BACKGROUND: Genetic variation in regulatory sequences that alter transcription factor (TF) binding is a major cause of phenotypic diversity. Brassinosteroid is a growth hormone that has major effects on plant phenotypes. Genetic variation in brassinosteroid-responsive cis-elements likely contributes to trait variation. Pinpointing such regulatory variations and quantitative genomic analysis of the variation in TF-target binding, however, remains challenging. How variation in transcriptional targets of signaling pathways such as the brassinosteroid pathway contributes to phenotypic variation is an important question to be investigated with innovative approaches. RESULTS: Here, we use a hybrid allele-specific chromatin binding sequencing (HASCh-seq) approach and identify variations in target binding of the brassinosteroid-responsive TF ZmBZR1 in maize. HASCh-seq in the B73xMo17 F1s identifies thousands of target genes of ZmBZR1. Allele-specific ZmBZR1 binding (ASB) has been observed for 18.3% of target genes and is enriched in promoter and enhancer regions. About a quarter of the ASB sites correlate with sequence variation in BZR1-binding motifs and another quarter correlate with haplotype-specific DNA methylation, suggesting that both genetic and epigenetic variations contribute to the high level of variation in ZmBZR1 occupancy. Comparison with GWAS data shows linkage of hundreds of ASB loci to important yield and disease-related traits. CONCLUSION: Our study provides a robust method for analyzing genome-wide variations of TF occupancy and identifies genetic and epigenetic variations of the brassinosteroid response transcription network in maize.

A happy accident: a novel turfgrass reference genome.

Poa pratensis, commonly known as Kentucky bluegrass, is a popular cool-season grass species used as turf in lawns and recreation areas globally. Despite its substantial economic value, a reference genome had not previously been assembled due to the genome's relatively large size and biological complexity that includes apomixis, polyploidy, and interspecific hybridization. We report here a fortuitous de novo assembly and annotation of a P. pratensis genome. Instead of sequencing the genome of a C4 grass, we accidentally sampled and sequenced tissue from a weedy P. pratensis whose stolon was intertwined with that of the C4 grass. The draft assembly consists of 6.09 Gbp with an N50 scaffold length of 65.1 Mbp, and a total of 118 scaffolds, generated using PacBio long reads and Bionano optical map technology. We annotated 256K gene models and found 58% of the genome to be composed of transposable elements. To demonstrate the applicability of the reference genome, we evaluated population structure and estimated genetic diversity in P. pratensis collected from three North American prairies, two in Manitoba, Canada and one in Colorado, USA. Our results support previous studies that found high genetic diversity and population structure within the species. The reference genome and annotation will be an important resource for turfgrass breeding and study of bluegrasses.

A randomized controlled study to compare first stick success with Instaflash technology: The FIRSST study.

BACKGROUND: Peripheral intravenous catheters (PIVCs) are frequently used in clinical settings for intravenous access. Multiple attempts of PIVC insertions leads to patient discomfort, delay in treatment, associated complications, and extensive expenditure cost. Reduced number of attempts causes patient/nursing personnel satisfaction and expenditure costs. The present study evaluated performance efficacy of BD Venflon™ I with Instaflash needle technology (investigational device) as compared to the BD Venflon™ without Instaflash needle technology (control device). METHODOLOGY: The PIVC insertions were randomized in the ratio 1:1 using either investigational or control device and were monitored for first stick success rate, ease of insertion, and patient satisfaction. Data was analyzed using R 4.0.3 and Microsoft Excel. Chi square test was used to establish association between two categorical variables. RESULTS: In total, 1402 patients were analyzed for first attempt insertion success which showed 98.72% success rate in investigational device as compared to 88.87% success rate in case of the control device (p = 0.0004). Marginal differences were observed in ease of insertion in investigational (98.71%) and control devices (99%) signifying high satisfaction levels of nursing personnels. Positive responses were observed in investigational (98.01%) and control devices (99%) underlining satisfactory performances of overall patient experiences. CONCLUSION: The present study showed that BD Venflon™ I with Instaflash needle technology enhanced first attempt insertion success rate along with marginal differences in its efficacy in comparison with the BD Venflon™ without Instaflash needle technology thus enhancing patient and nursing personnel satisfaction in turn making it a better alternative to be used in hospitals.

The product of BMP-directed differentiation protocols for human primed pluripotent stem cells is placental trophoblast and not amnion.

The observation that trophoblast (TB) can be generated from primed pluripotent stem cells (PSCs) by exposure to bone morphogenetic protein-4 (BMP4) when FGF2 and ACTIVIN signaling is minimized has recently been challenged with the suggestion that the procedure instead produces amnion. Here, by analyzing transcriptome data from multiple sources, including bulk and single-cell data, we show that the BMP4 procedure generates bona fide TB with similarities to both placental villous TB and TB generated from TB stem cells. The analyses also suggest that the transcriptomic signatures between embryonic amnion and different forms of TB have commonalities. Our data provide justification for the continued use of TB derived from PSCs as a model for investigating placental development.

pyrpipe: a Python package for RNA-Seq workflows.

The availability of terabytes of RNA-Seq data and continuous emergence of new analysis tools, enable unprecedented biological insight. There is a pressing requirement for a framework that allows for fast, efficient, manageable, and reproducible RNA-Seq analysis. We have developed a Python package, (pyrpipe), that enables straightforward development of flexible, reproducible and easy-to-debug computational pipelines purely in Python, in an object-oriented manner. pyrpipe provides access to popular RNA-Seq tools, within Python, via high-level APIs. Pipelines can be customized by integrating new Python code, third-party programs, or Python libraries. Users can create checkpoints in the pipeline or integrate pyrpipe into a workflow management system, thus allowing execution on multiple computing environments, and enabling efficient resource management. pyrpipe produces detailed analysis, and benchmark reports which can be shared or included in publications. pyrpipe is implemented in Python and is compatible with Python versions 3.6 and higher. To illustrate the rich functionality of pyrpipe, we provide case studies using RNA-Seq data from GTEx, SARS-CoV-2-infected human cells, and Zea mays. All source code is freely available at https://github.com/urmi-21/pyrpipe; the package can be installed from the source, from PyPI (https://pypi.org/project/pyrpipe), or from bioconda (https://anaconda.org/bioconda/pyrpipe). Documentation is available at (http://pyrpipe.rtfd.io).