ArticleBMC genomics2016
Sort-seq under the hood: implications of design choices on large-scale characterization of sequence-function relations.
Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.
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Who cites it
67 citing papers in PubMed.
- N-terminal fusion length: The key to reliable and context-preserving regulatory sequence characterization.Synthetic and systems biotechnology · 2027Article
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- Combinatorial Optimization of Protein Systems in Synthetic Cells.ACS synthetic biology · 2026Article
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- The adaptive landscapes of three globaleLife · 2026Article
- Amplicon/Protein Bead Display enables quantitativebioRxiv : the preprint server for biology · 2026Article
- Image-based phenotypic sorting of synthetic cells.Science advances · 2026Article
- Deep mutational scanning of recent SARS-CoV-2 variants highlights changing amino acid preferences within epistatic hotspot residues.PLoS pathogens · 2026Article
- De novo promoters emerge more readily from random DNA than from genomic DNA.Science advances · 2026Article
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- Deep mutational scan of the pore of the cold-sensing TRPM8 channel.bioRxiv : the preprint server for biology · 2026Article
- HaloTag-based approach to quantify subcellular localization of TRPV3 channels.Biophysical journal · 2026Article
- Supervised learning of protein variant effects across large-scale mutagenesis datasets.Protein science : a publication of the Protein Society · 2026Article
- Biophysical trade-offs in antibody evolution are resolved by conformation-mediated epistasis.bioRxiv : the preprint server for biology · 2026Article
- Mapping the phenotypic landscape of a transcriptional repressor using deep mutational scanning and growth-based quantitative sequencing.Nucleic acids research · 2026Article
- Accurate variant effect estimation in FACS-based deep mutational scanning data with Lilace.Genome biology · 2026Article
- High throughput mutational characterization of the GPCR ligand C5a using yeast display and deep sequencing.Structure (London, England : 1993) · 2026Article
- Control of gene output by intron RNA structure.bioRxiv : the preprint server for biology · 2025Article
- Arrest Peptide Profiling resolves co-translational folding pathways and chaperone interactions in vivo.Nature communications · 2025Article
7 more citing papers are in PubMed but not listed here.
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundSort-seq is an effective approach for simultaneous activity measurements in a large-scale library, combining flow cytometry, deep sequencing, and statistical inference. Such assays enable the characterization of functional landscapes at unprecedented scale for a wide-reaching array of biological molecules and functionalities in vivo. Applications of sort-seq range from footprinting to establishing quantitative models of biological systems and rational design of synthetic genetic elements. Nearly as diverse are implementations of this technique, reflecting key design choices with extensive impact on the scope and accuracy the results. Yet how to make these choices remains unclear. Here we investigate the effects of alternative sort-seq designs and inference methods on the information output using mathematical formulation and simulations.
resultsWe identify key intrinsic properties of any system of interest with practical implications for sort-seq assays, depending on the experimental goals. The fluorescence range and cell-to-cell variability specify the number of sorted populations needed for quantitative measurements that are precise and unbiased. These factors also indicate cases where an enrichment-based approach that uses a single sorted population can offer satisfactory results. These predications of our model are corroborated using re-analysis of published data. We explore implications of these results for quantitative modeling and library design.
conclusionsSort-seq assays can be streamlined by reducing the number of sorted populations, saving considerable resources. Simple preliminary experiments can guide optimal experiment design, minimizing cost while maintaining the maximal information output and avoiding latent biases. These insights can facilitate future applications of this highly adaptable technique.
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