High-density resolution of the Kaposi's sarcoma associated herpesvirus transcriptome identifies novel transcript isoforms generated by long-range transcription and alternative splicing.

Kaposi's sarcoma-associated herpesvirus is the etiologic agent of Kaposi's sarcoma and two B-cell malignancies. Recent advancements in sequencing technologies have led to high resolution transcriptomes for several human herpesviruses that densely encode genes on both strands. However, for KSHV progress remained limited due to the overall low percentage of KSHV transcripts, even during lytic replication. To address this challenge, we have developed a target enrichment method to increase the KSHV-specific reads for both short- and long-read sequencing platforms. Furthermore, we combined this approach with the Transcriptome Resolution through Integration of Multi-platform Data (TRIMD) pipeline developed previously to annotate transcript structures. TRIMD first builds a scaffold based on long-read sequencing and validates each transcript feature with supporting evidence from Illumina RNA-Seq and deepCAGE sequencing data. Our stringent innovative approach identified 994 unique KSHV transcripts, thus providing the first high-density KSHV lytic transcriptome. We describe a plethora of novel coding and non-coding KSHV transcript isoforms with alternative untranslated regions, splice junctions and open-reading frames, thus providing deeper insights on gene expression regulation of KSHV. Interestingly, as described for Epstein-Barr virus, we identified transcription start sites that augment long-range transcription and may increase the number of latency-associated genes potentially expressed in KS tumors.

The development of the WHO Labour Care Guide: an international survey of maternity care providers.

BACKGROUND: The partograph is the most commonly used labour monitoring tool in the world. However, it has been used incorrectly or inconsistently in many settings. In 2018, a WHO expert group reviewed and revised the design of the partograph in light of emerging evidence, and they developed the first version of the Labour Care Guide (LCG). The objective of this study was to explore opinions of skilled health personnel on the first version of the WHO Labour Care Guide. METHODS: Skilled health personnel (including obstetricians, midwives and general practitioners) of any gender from Africa, Asia, Europe and Latin America were identified through a large global research network. Country coordinators from the network invited 5 to 10 mid-level and senior skilled health personnel who had worked in labour wards anytime in the last 5 years. A self-administered, anonymous, structured, online questionnaire including closed and open-ended questions was designed to assess the clarity, relevance, appropriateness of the frequency of recording, and the completeness of the sections and variables on the LCG. RESULTS: A total of 110 participants from 23 countries completed the survey between December 2018 and January 2019. Variables included in the LCG were generally considered clear, relevant and to have been recorded at the appropriate frequency. Most sections of the LCG were considered complete. Participants agreed or strongly agreed with the overall design, structure of the LCG, and the usefulness of reference thresholds to trigger further assessment and actions. They also agreed that LCG could potentially have a positive impact on clinical decision-making and respectful maternity care. Participants disagreed with the value of some variables, including coping, urine, and neonatal status. CONCLUSIONS: Future end-users of WHO Labour Care Guide considered the variables to be clear, relevant and appropriate, and, with minor improvements, to have the potential to positively impact clinical decision-making and respectful maternity care.

SQANTI-reads: a tool for the quality assessment of long read data in multi-sample lrRNA-seq experiments.

SQANTI-reads leverages SQANTI3, a tool for the analysis of the quality of transcript models, to develop a read-level quality control framework for replicated long-read RNA-seq experiments. The number and distribution of reads, as well as the number and distribution of unique junction chains (transcript splicing patterns), in SQANTI3 structural categories are informative of raw data quality. Multi-sample visualizations of QC metrics are presented by experimental design factors to identify outliers. We introduce new metrics for 1) the identification of potentially under-annotated genes and putative novel transcripts and for 2) quantifying variation in junction donors and acceptors. We applied SQANTI-reads to two different datasets, a Drosophila developmental experiment and a multi-platform dataset from the LRGASP project and demonstrate that the tool effectively reveals the impact of read coverage on data quality, and readily identifies strong and weak splicing sites. SQANTI-reads is open source and available for download at GitHub.