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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing
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Sequencing HIV Diagnostic Samples to Detect Genetic Clusters and Assess Sequence Coverage Gaps.

Cara J Broshkevitch1, Shuntai Zhou2, Annalea Greifinger3

  • 1Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

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Incorporating HIV test sequences into molecular cluster analysis significantly increased the detection of active HIV clusters. This method helps identify individuals not fully represented in routine care data, improving public health surveillance.

Keywords:
HIVHIV diagnosismolecular epidemiologysequencetransmission cluster

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Area of Science:

  • Epidemiology
  • Public Health Surveillance
  • Molecular Epidemiology

Background:

  • Current HIV molecular cluster detection in the US relies on routine care sequences.
  • This method overlooks individuals not linked to care or with uncollected/unreported sequences.

Purpose of the Study:

  • To assess the impact of incorporating HIV test sequences into molecular cluster analysis.
  • To identify data gaps filled by HIV test sequences and characterize individuals included.

Main Methods:

  • Collected HIV test sequences from newly diagnosed individuals in North Carolina (2018-2021).
  • Integrated these sequences into statewide molecular cluster analysis to detect active clusters (≥5 newly diagnosed members).
  • Compared data gaps and participant characteristics between individuals with and without routine care sequences.

Main Results:

  • 847 HIV test sequences were analyzed, with one-third lacking routine care sequences.
  • Incorporating HIV test sequences led to the identification of 13 additional active clusters (33% increase) and 40 larger clusters.
  • Most individuals with test sequences but no care sequences had other care indicators, suggesting undercollection/underreporting, while 22% showed no care evidence.

Conclusions:

  • Enhanced sequence coverage improves HIV cluster detection.
  • Increased routine care sequence collection and reporting can address some data gaps.
  • Sequencing remnant HIV test samples is crucial for including individuals not linked to care.