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NCI Team Reports High-Throughput Imaging Mapping Tech for Studying Gene Positioning


NEW YORK (GenomeWeb) – As part of an effort to uncover the molecular determinants of gene positioning within the cell nucleus, researchers from the National Cancer Institute have developed a high-throughput fluorescence in situ hybridization (FISH) platform that enables the determination of the spatial location of genome regions in 3D and at large scale.

By combining the approach with RNAi screening, the team was able to identify 50 cellular factors required for proper positioning of a set of functionally diverse genomic loci in human cells including chromatin remodelers, histone modifiers, and nuclear envelope and pore proteins.

The approach, which was detailed in this week's Cell, is expected to have utility for a wide variety of applications including the diagnosis of cancer and other diseases, Tom Misteli, an NCI research and senior author of the paper, told GenomeWeb.

The idea that genomes are organized in a non-random manner within a cell's nucleus is not new, but is largely based on "anecdotal observations" that have steadily accumulated in the literature, Misteli explained. Formalizing this concept, however, has been challenging due to technological hurdles.

For instance, FISH can be used to visualize the position of a genomic locus and track changes in its position during physiological and pathological processes, while chromosome conformation capture (3C) techniques such as Hi-C enable the mapping of intra- and inter-chromosomal interactions at the scale of entire genomes.

Yet these technologies have not proven amenable for spatial gene mapping on a high-throughput scale, preventing their use in screening experiments. "That has really limited the ability of people to [establish] the general rules" of gene positioning within the nucleus, he said.

To address this, Misteli and his team developed HIPMap — short for high-throughput imaging position mapping — which is based around a streamlined FISH protocol that has been optimized for use in a 384-well format, thereby enabling the visualization of multiple endogenous gene loci in thousands of cells and several hundred samples.

"The approach uses fluorescently labeled FISH probes in a fully automated liquid-handling FISH protocol, automated 3D image acquisition using confocal high-throughput microscopy, and a high-content image analysis pipeline," the scientists wrote in Cell. "The custom designed analysis pipeline includes image and statistical analyses to quantitatively map the distribution profile of a gene locus on a single-cell basis with high accuracy and statistical power."

To demonstrate HIPMap's potential, Misteli's group used it to conduct an RNAi screen in order to systematically identify the determinants of genome positioning in human skin fibroblast cells, reverse transfecting them in 384-well plates with a library of siRNAs targeting 669 nuclear genes. A secondary screen was also run using different siRNAs in order to rule out the possibility of off-target effects.

The screens yielded 50 hits, which were then analyzed for their functional properties and found to affect the position of a set of functionally diverse genes. Components of the replication and post-replication chromatin reassembly machinery were "prominently represented" among the gene positioning factors, the study's authors wrote, "and timely progression of cells through replication, but not mitosis, is required for correct gene positioning."

Beyond its use in determining factors involved in gene positioning, HIPMap is expected to prove useful in other applications, as well, Misteli said.

Among these is determining the frequencies of Hi-C interactions to determine how Hi-C signal strength relates to single-cell interactions. Because 3C experiments are typically performed using large numbers of cells, "when you pick up a signal, you don't know if … it is because of a strong interaction in a few cells or a weak interaction in a large number of cells," he explained.

"FISH methods are used to validate these sorts of interactions, and the problem has been that you could only do it for five, six, seven interactions," Misteli added. "We can now use [HIPMap] to systematically test what these Hi-C maps really mean, what the distances are, and what the frequencies really are. It's a more realistic assessment of what the Hi-C maps really represent."

He also sees clinical potential for HIPMap, where it could be used to look for disease-relevant low-frequency chromosomal translocations in patient cell populations, or for more frequent translocations in a large number of samples from multiple patients.

In his own lab, Misteli has already begun using the method to determine whether changes in gene position can be used to identify cancer. His group has published a study suggesting that gene repositioning can be used to differentiate breast cancer tissue from normal tissue, and is currently preparing for publication data around gene position changes and prostate cancer.