The possibility of generating large RNA-sequencing datasets has led to development of various reference-based and de novo transcriptome assemblers with their own strengths and limitations. While reference-based tools are widely used in various transcriptomic studies, their application is limited to the organisms with finished and well-annotated genomes. De novo transcriptome reconstruction from short reads remains an open challenging problem, which is complicated by the varying expression levels across different genes, alternative splicing, and paralogous genes. Herein we describe the novel transcriptome assembler rnaSPAdes, which has been developed on top of the SPAdes genome assembler and explores computational parallels between assembly of transcriptomes and single-cell genomes. We also present quality assessment reports for rnaSPAdes assemblies, compare it with modern transcriptome assembly tools using several evaluation approaches on various RNA-sequencing datasets, and briefly highlight strong and weak points of different assemblers. Based on the performed comparison between different assembly methods, we infer that it is not possible to detect the absolute leader according to all quality metrics and all used datasets. However, rnaSPAdes typically outperforms other assemblers by such important property as the number of assembled genes and isoforms, and at the same time has higher accuracy statistics on average comparing to the closest competitors.

Annotating newly sequenced genomes and determining alternative isoforms from long-read RNA data are complex and incompletely solved problems. Here we present IsoQuant—a computational tool using intron graphs that accurately reconstructs transcripts both with and without reference genome annotation. For novel transcript discovery, IsoQuant reduces the false-positive rate fivefold and 2.5-fold for Oxford Nanopore reference-based or reference-free mode, respectively. IsoQuant also improves performance for Pacific Biosciences data.

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Summary: Possibility to generate large RNA-seq datasets has led to development of various reference-based and de novo transcriptome assemblers with their own strengths and limitations. While reference-based tools are widely used in various transcriptomic studies, their application is limited to the model organisms with finished and annotated genomes. De novo transcriptome reconstruction from short reads remains an open challenging problem, which is complicated by the varying expression levels across different genes, alternative splicing and paralogous genes. In this paper we describe a novel transcriptome assembler called rnaSPAdes, which is developed on top of SPAdes genome assembler and explores surprising computational parallels between assembly of transcriptomes and single-cell genomes. We also present quality assessment reports for rnaSPAdes assemblies, compare it with modern transcriptome assembly tools using several evaluation approaches on various RNA-Seq datasets, and briefly highlight strong and weak points of different assemblers. Availability and implementation: rnaSPAdes is implemented in C++ and Python and is freely available at cab.spbu.ru/software/rnaspades/.

Summary: Scaffolding is an important step in every genome assembly pipeline, which allows to order contigs into longer sequences using various types of linkage information, such as mate-pair libraries and long reads. In this work, we operate with a notion of a scaffold graph—a graph, vertices of which correspond to the assembled contigs and edges represent connections between them. We present a software package called Scaffold Graph ToolKit that allows to construct and visualize scaffold graphs using different kinds of sequencing data. We show that the scaffold graph appears to be useful for analyzing and assessing genome assemblies, and demonstrate several use cases that can be helpful for both assembly software developers and their users. Availability and implementation: SGTK is implemented in C++, Python and JavaScript and is freely available at https://github.com/olga24912/SGTK. Supplementary information: Supplementary data are available at Bioinformatics online.

Trace amine-associated receptors (TAAR) recognize organic compounds, including primary, secondary, and tertiary amines. The TAAR5 receptor is known to be involved in the olfactory sensing of innate socially relevant odors encoded by volatile amines. However, emerging data point to the involvement of TAAR5 in brain functions, particularly in the emotional behaviors mediated by the limbic system which suggests its potential contribution to the pathogenesis of neuropsychiatric diseases. TAAR5 expression was explored in datasets available in the Gene Expression Omnibus, Allen Brain Atlas, and Human Protein Atlas databases. Transcriptomic data demonstrate ubiquitous low TAAR5 expression in the cortical and limbic brain areas, the amygdala and the hippocampus, the nucleus accumbens, the thalamus, the hypothalamus, the basal ganglia, the cerebellum, the substantia nigra, and the white matter. Altered TAAR5 expression is identified in Down syndrome, major depressive disorder, or HIV-associated encephalitis. Taken together, these data indicate that TAAR5 in humans is expressed not only in the olfactory system but also in certain brain structures, including the limbic regions receiving olfactory input and involved in critical brain functions. Thus, TAAR5 can potentially be involved in the pathogenesis of brain disorders and represents a valuable novel target for neuropsychopharmacology.