
This report summarizes the first year of development and deployment of the Growth-based Quantitative Sequencing (GROQ-seq) platform, a pooled functional assay pipeline for large-scale, reproducible measurement of protein variant libraries. Developed by The Align Foundation in collaboration with academic and automation partners, GROQ-seq enables high-throughput, barcoded fitness measurements across 100,000–500,000 protein variants per assay. Key 2024 milestones include: Beginning onboarding of six new protein function assays, with a seventh (DHFR) slated for 2025 Expansion to two automation sites: The DAMP Lab (Boston) and NIST's Living Measurement Systems Foundry (DC) Public release of all protocols via Protocols.io Improved modularity and reproducibility across assay stages, from plasmid design to data validation The platform supports data collection across diverse functional domains, including transcription factors, proteases, aminoacyl-tRNA synthetases, T7 RNA polymerases, histidine kinases, single-chain antibody fragments, and dihydrofolate reductases. Each function follows a standardized five-stage onboarding pipeline, facilitating circuit design, dynamic range tuning, and calibration ladder development. This document also introduces the functional archipelago framework for mapping the protein function landscape and outlines the GROQ-seq project's N=2 reproducibility model for cross-site data validation. As part of Align’s open science mission, all methods, data, and tools are being shared to enable collaborative benchmarking and predictive model development. Suggested citation:The Align Foundation. Year One Report: Growth-based Quantitative Sequencing (GROQ-seq) Platform. https://doi.org/10.5281/zenodo.15723203 (2025).
GROQ-seq, open science, barcoded assays, sequence-function mapping, synthetic biology, protein function, high-throughput screening, predictive modeling
GROQ-seq, open science, barcoded assays, sequence-function mapping, synthetic biology, protein function, high-throughput screening, predictive modeling
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
