TKSM: highly modular, user-customizable, and scalable transcriptomic sequencing long-read simulator.

MOTIVATION: Transcriptomic long-read (LR) sequencing is an increasingly cost-effective technology for probing various RNA features. Numerous tools have been developed to tackle various transcriptomic sequencing tasks (e.g. isoform and gene fusion detection). However, the lack of abundant gold-standard datasets hinders the benchmarking of such tools. Therefore, the simulation of LR sequencing is an important and practical alternative. While the existing LR simulators aim to imitate the sequencing machine noise and to target specific library protocols, they lack some important library preparation steps (e.g. PCR) and are difficult to modify to new and changing library preparation techniques (e.g. single-cell LRs). RESULTS: We present TKSM, a modular and scalable LR simulator, designed so that each RNA modification step is targeted explicitly by a specific module. This allows the user to assemble a simulation pipeline as a combination of TKSM modules to emulate a specific sequencing design. Additionally, the input/output of all the core modules of TKSM follows the same simple format (Molecule Description Format) allowing the user to easily extend TKSM with new modules targeting new library preparation steps. AVAILABILITY AND IMPLEMENTATION: TKSM is available as an open source software at https://github.com/vpc-ccg/tksm.

Genion, an accurate tool to detect gene fusion from long transcriptomics reads.

BACKGROUND: The advent of next-generation sequencing technologies empowered a wide variety of transcriptomics studies. A widely studied topic is gene fusion which is observed in many cancer types and suspected of having oncogenic properties. Gene fusions are the result of structural genomic events that bring two genes closely located and result in a fused transcript. This is different from fusion transcripts created during or after the transcription process. These chimeric transcripts are also known as read-through and trans-splicing transcripts. Gene fusion discovery with short reads is a well-studied problem, and many methods have been developed. But the sensitivity of these methods is limited by the technology, especially the short read length. Advances in long-read sequencing technologies allow the generation of long transcriptomics reads at a low cost. Transcriptomic long-read sequencing presents unique opportunities to overcome the shortcomings of short-read technologies for gene fusion detection while introducing new challenges. RESULTS: We present Genion, a sensitive and fast gene fusion detection method that can also detect read-through events. We compare Genion against a recently introduced long-read gene fusion discovery method, LongGF, both on simulated and real datasets. On simulated data, Genion accurately identifies the gene fusions and its clustering accuracy for detecting fusion reads is better than LongGF. Furthermore, our results on the breast cancer cell line MCF-7 show that Genion correctly identifies all the experimentally validated gene fusions. CONCLUSIONS: Genion is an accurate gene fusion caller. Genion is implemented in C++ and is available at https://github.com/vpc-ccg/genion .

A novel sorting method for the enrichment of early human spermatocytes from clinical biopsies.

OBJECTIVE: To determine if early spermatocytes can be enriched from a human testis biopsy using fluorescence-activated cell sorting (FACS). DESIGN: Potential surface markers for early spermatocytes were identified using bioinformatics analysis of single-cell RNA-sequenced human testis tissue. Testicular sperm extraction samples from three participants with normal spermatogenesis were digested into single-cell suspensions and cryopreserved. Two to four million cells were obtained from each and sorted by FACS as separate biologic replicates using antibodies for the identified surface markers. A portion from each biopsy remained unsorted to serve as controls. The sorted cells were then characterized for enrichment of early spermatocytes. SETTING: A laboratory study. PATIENTS: Three men with a diagnosis of obstructive azoospermia (age range, 30-40 years). INTERVENTION: None. MAIN OUTCOME MEASURES: Sorted cells were characterized for RNA expression of markers encompassing the stages of spermatogenesis. Sorting markers were validated by their reactivity on human testis formalin-fixed paraffin-embedded tissue. RESULTS: Serine protease 50 (TSP50) and SWI5-dependent homologous recombination repair protein 1 were identified as potential surface proteins specific for early spermatocytes. After FACS sorting, the TSP50-sorted populations accounted for 1.6%-8.9% of total populations and exhibited the greatest average-fold increases in RNA expression for the premeiotic marker stimulated by retinoic acid (STRA8), by 23-fold. Immunohistochemistry showed the staining pattern for TSP50 to be strong in premeiotic undifferentiated embryonic cell transcription factor 1-/doublesex and Mab-3 related transcription factor 1-/STRA8+ spermatogonia as well as SYCP3+/protamine 2- spermatocytes. CONCLUSION: This work shows that TSP50 can be used to enrich early STRA8-expressing spermatocytes from human testicular biopsies, providing a means for targeted single-cell RNA sequencing analysis and in vitro functional interrogation of germ cells during the onset of meiosis. This could enable investigation into details of the regulatory pathways underlying this critical stage of spermatogenesis, previously difficult to enrich from whole tissue samples.

An androgen receptor switch underlies lineage infidelity in treatment-resistant prostate cancer.

Cancers adapt to increasingly potent targeted therapies by reprogramming their phenotype. Here we investigated such a phenomenon in prostate cancer, in which tumours can escape epithelial lineage confinement and transition to a high-plasticity state as an adaptive response to potent androgen receptor (AR) antagonism. We found that AR activity can be maintained as tumours adopt alternative lineage identities, with changes in chromatin architecture guiding AR transcriptional rerouting. The epigenetic regulator enhancer of zeste homologue 2 (EZH2) co-occupies the reprogrammed AR cistrome to transcriptionally modulate stem cell and neuronal gene networks-granting privileges associated with both fates. This function of EZH2 was associated with T350 phosphorylation and establishment of a non-canonical polycomb subcomplex. Our study provides mechanistic insights into the plasticity of the lineage-infidelity state governed by AR reprogramming that enabled us to redirect cell fate by modulating EZH2 and AR, highlighting the clinical potential of reversing resistance phenotypes.

VALOR2: characterization of large-scale structural variants using linked-reads.

Most existing methods for structural variant detection focus on discovery and genotyping of deletions, insertions, and mobile elements. Detection of balanced structural variants with no gain or loss of genomic segments, for example, inversions and translocations, is a particularly challenging task. Furthermore, there are very few algorithms to predict the insertion locus of large interspersed segmental duplications and characterize translocations. Here, we propose novel algorithms to characterize large interspersed segmental duplications, inversions, deletions, and translocations using linked-read sequencing data. We redesign our earlier algorithm, VALOR, and implement our new algorithms in a new software package, called VALOR2.