Mapping Gene Function Using Large-Scale “Perturb-Seq”

July 11, 2022

From Genotype to Phenotype

Genomic analyses are incredibly valuable tools for uncovering biological insights, but only when some evidence exists to relate genotype to phenotype- that is to say, understanding the biological function(s) related to a given gene. With a newly completed human reference genome and improving analytical tools, it’s time for new functional studies to attempt to further the functional annotation of the genome.

A New, Fully Complete Human Reference Genome

Recently published in Science, the Telomere-to-Telomere Consortium put forward a complete, updated human reference genome that includes assemblies with no gaps for all chromosomes except for Y, corrects for errors in previous sequences, and includes new sequence data, increasing the known number of genes and repeats in the human genome.

A New Generation of Functional Studies

This allows for new genome-wide functional studies like that of Replogle et. al., published last week in Cell. The authors used Perturb-seq, an approach that uses CRISPR-based interference screens to randomly perturb the genome, followed by single-cell transcriptomics to analyze the phenotypes that result from the genetic disturbances.

What makes this particular study stand out is its scale. Perturb-seq has been applied in other smaller scale studies, but these authors used Perturb-seq on a genome-wide scale on over 2.5 million human cells. 

Their results uncover functions of previously poorly characterized genes involved in central biological processes like ribosome biogenesis, transcription and mitochondrial respiration (aka cellular energy production). The genotype-phenotype map produced by this study is incredibly useful for improving functional annotation of the genome: due to its scale, it can also be used to identify aneuploidy, or copy number variations, as well as pleiotropy, when one gene has multiple phenotypic effects.

Outsourcing Bioinformatic Analyses

Analyzing sequence data, including aligning and comparing genome sequences to a reference genome and single cell transcriptomic analysis, can be a challenging computational task. Outsourcing your bioinformatic pipeline development to a bioinformatics service provider like Bridge Informatics can eliminate many common challenges for you and your research team. Book a free discovery call to discuss your project needs with us.

Jane Cook, Journalist & Content Writer, Bridge Informatics

Jane is a Content Writer at Bridge Informatics, a professional services firm that helps biotech customers implement advanced techniques in management and analysis of genomic data. Bridge Informatics focuses on data mining, machine learning, and various bioinformatic techniques to discover biomarkers and companion diagnostics. If you’re interested in reaching out, please email or


graphic of computer coding for genomic analysis

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