Synonymous Variants of Uncertain Silence.

Synonymous variants, traditionally regarded as silent mutations due to their lack of impact on protein sequence, structure and function, have been the subject of increasing scrutiny. This commentary explores the emerging evidence challenging the notion of synonymous variants as functionally inert. Analysis of the activity of 70 synonymous variants in the HIV Tat transcription factor revealed that 50% of the variants exhibited significant deviations from wild-type activity. Our analysis supports previous work and raises important questions about the broader impact of non-silent synonymous variants in human genes. Considering the potential functional implications, the authors propose classifying such variants as "synonymous variants of uncertain silence" (sVUS), highlighting the need for cautious interpretation and further investigations in clinical and genetic testing settings.

Accurate Prediction of Transcriptional Activity of Single Missense Variants in HIV Tat with Deep Learning.

Tat is an essential gene for increasing the transcription of all HIV genes, and affects HIV replication, HIV exit from latency, and AIDS progression. The Tat gene frequently mutates in vivo and produces variants with diverse activities, contributing to HIV viral heterogeneity as well as drug-resistant clones. Thus, identifying the transcriptional activities of Tat variants will help to better understand AIDS pathology and treatment. We recently reported the missense mutation landscape of all single amino acid Tat variants. In these experiments, a fraction of double missense alleles exhibited intragenic epistasis. However, it is too time-consuming and costly to determine the effect of the variants for all double mutant alleles through experiments. Therefore, we propose a combined GigaAssay/deep learning approach. As a first step to determine activity landscapes for complex variants, we evaluated a deep learning framework using previously reported GigaAssay experiments to predict how transcription activity is affected by Tat variants with single missense substitutions. Our approach achieved a 0.94 Pearson correlation coefficient when comparing the predicted to experimental activities. This hybrid approach can be extensible to more complex Tat alleles for a better understanding of the genetic control of HIV genome transcription.

Most synonymous allelic variants in HIV tat are not silent.

The genetic code has degenerate codons that produce no change in the translated protein sequence and are generally thought to be silent. However, some synonymous variants are clearly not silent. Herein, we questioned the frequency of non-silent synonymous variants. We tested how random synonymous variants in the HIV Tat transcription factor effect transcription of an LTR-GFP reporter. Our model system has the advantage of directly measuring the function of the gene in human cells. Approximately, 67% of synonymous variants in Tat were non-silent, either having reduced activity or were full loss-of-function alleles. Eight mutant codons had higher codon usage than wild type, accompanied by reduced transcriptional activity. These were clustered on a loop in the Tat structure. We conclude that most synonymous Tat variants are not silent in human cells, and 25% are associated with changes in codon usage, likely effecting protein folding.

The history and conceptual framework of assays and screens.

Since the 16th century, assays and screens have been essential for scientific investigation. However, most methods could be significantly improved, especially in accuracy, scalability, and often lack adequate comparisons to negative controls. There is a lack of consistency in distinguishing assays, in which accuracy is the main goal, from screens, in which scalability is prioritized over accuracy. We dissected and modernized the original definitions of assays and screens based upon recent developments and the conceptual framework of the original definitions. All methods have three components: design/measurement, performance, and interpretation. We propose a model of method development in which reproducible observations become new methods, initially assessed by sensitivity. Further development can proceed along a path to either screens or assays. The screen path focuses on scalability first, but can later prioritize analysis of negatives. Alternatively, the assay path first compares results to negative controls, assessing specificity and accuracy, later adding scalability. Both pathways converge on a high-accuracy and throughput (HAT) assay, like next generation sequencing, which we suggest should be the ultimate goal of all testing methods. Our model will help scientists better select among available methods, as well as improve existing methods, expanding their impact on science.

Data supporting a saturation mutagenesis assay for Tat-driven transcription with the GigaAssay.

The data in this article are associated with the research paper "GigaAssay - an adaptable high-throughput saturation mutagenesis assay" [1]. The raw data are sequence reads of HIV-1 Tat cDNA amplified from cellular genomic DNA in a new single-pot saturation mutagenesis assay designated the "GigaAssay". A bioinformatic pipeline and parameters used to analyze the data. Raw, processed, analyzed, and filtered data are reported. The data is processed to calculate the Tat-driven transcription activity for cells with each possible single amino acid substitution in Tat. This data can be reused to interpret Tat intermolecular interactions and HIV latency. This is one of the largest and most complete datasets regarding the impact of amino acid substitutions within a single protein on a molecular function.

GigaAssay - An adaptable high-throughput saturation mutagenesis assay platform.

High-throughput assay systems have had a large impact on understanding the mechanisms of basic cell functions. However, high-throughput assays that directly assess molecular functions are limited. Herein, we describe the "GigaAssay", a modular high-throughput one-pot assay system for measuring molecular functions of thousands of genetic variants at once. In this system, each cell was infected with one virus from a library encoding thousands of Tat mutant proteins, with each viral particle encoding a random unique molecular identifier (UMI). We demonstrate proof of concept by measuring transcription of a GFP reporter in an engineered reporter cell line driven by binding of the HIV Tat transcription factor to the HIV long terminal repeat. Infected cells were flow-sorted into 3 bins based on their GFP fluorescence readout. The transcriptional activity of each Tat mutant was calculated from the ratio of signals from each bin. The use of UMIs in the GigaAssay produced a high average accuracy (95%) and positive predictive value (98%) determined by comparison to literature benchmark data, known C-terminal truncations, and blinded independent mutant tests. Including the substitution tolerance with structure/function analysis shows restricted substitution types spatially concentrated in the Cys-rich region. Tat has abundant intragenic epistasis (10%) when single and double mutants are compared.