In a small worm, a close-up image of where genes work – ScienceDaily



Scientists have long appreciated the roundworm Caenorhabditis elegans as a model for studying the biology of multicellular organisms. The millimeters long worms are easy to grow in the laboratory and genetically engineer and have only about 1,000 cells, making them a powerful system for investigating the complexity of development, behavior and metabolism.

Now a team of Lewis-Sigler Institute for Integrative Genomics from Princeton has produced new sources C. elegans research: a comprehensive overview of which genes are active in each of the four major tissues of adult worms, as well as a tool for predicting gene activity across 76 more specific cell types. The team, led by co-senior authors Professor of Molecular Biology Coleen Murphy and Professor of Computer Science Olga Troyanskaya, reported their results in an August 10 article in the journal PLOS Genetics.

The work builds on a collaboration dating back to 2009, when the two labs first worked together to analyze the activity of genes in C. elegans tissues. "Olga and I both had an interest in the specificity of the tissue. Most of the biology we hear is done in whole organisms, but the truth is that if you have a disease it is usually from a certain tissue," said Murphy, who is Princeton's Glenn Center for Quantitative Aging Research. "In front of C. elegans we know, for example, that insulin signaling in the brain or the intestine of the animal can affect the life span of the entire animal. "

Researchers have previously analyzed the activity of the more than 20,000 genes of the worm under different conditions in embryos, larvae or whole adult worms, but the separation of the tissues from adult animals for such experiments was difficult because of the anatomy of the worm. Rachel Kaletsky, a related research scientist in Murphy's laboratory and co-lead author of the work, developed a technique to isolate specific tissues. Kaletsky, Murphy and their colleagues have used the method for the first time in 2015 to study memory-related genes in neurons. Here they used to perform a global analysis of gene activity, or expression, in the four main tissues of the adult worm: muscles, neurons, intestines and epidermis tissues.

"This really lets us refine our hypotheses," Kaletsky said. "We can now ask questions about what happens in neurons, for example, under a whole series of disorders that affect different diseases or things that happen with age, and we can answer these questions right away."

After separating cells from the four major tissues of the worms, the researchers isolated the sequence of the messenger RNAs of the cells, whose intermediate molecules ensured that the information encoded in the DNA of genes could be converted into proteins, which execute the basis and more of a cell. specialized functions. Only one subset of genes is actively expressed in each cell – meaning that messenger RNA only exists for the subset of genes that are active in that tissue.

Analysis of the RNA data revealed different patterns of gene expression in each tissue. Intestinal cells, for example, showed high levels of genes associated with digestion, while genes related to learning and memory were strongly expressed in neurons. More than 5,000 genes were expressed in all tissue types; these were involved in such universal processes such as glucose metabolism or stress reactions.

Comparing the results with human gene expression profiles yielded some unexpected insights. For example the C. elegans epidermis did not express genes that are similar to those that are active in human skin, as researchers have long assumed. On the contrary, epidermal cells express many metabolic genes that are similar to those that are active in the human liver. "This is the kind of thing that might inform studies on organ-specific diseases in humans, using worms as a model," Murphy said.

But what about examining which genes are expressed in the main muscle cells or sensory neurons of the worm? Or in his excretion system? To get a high-resolution image of gene expression across cell types and life stages, Murphy's group collaborated with Troyanskaya and Victoria Yao, a recently graduated Ph.D. student of the Troyanskaya laboratory and co-first author of the work.

The team applied computational methods to analyze data of more than 4,000 publicly available C. elegans gene expression experiments – including data from the current study on the four major tissues of the worm. Although most of these experiments were performed on whole animals, the researchers developed a machine-learning approach to unravel tissue-specific patterns. The method combines the high-throughput datasets with the best available information from small-scale experiments that show that a gene is expressed in a certain tissue.

"We can not fully characterize any small cell type in any way," Yao explained. "The idea is that all of those whole-worm expression data sets still contain useful information – it looks like everything that was smacked in a blender, but we can use computational methods to try to produce which genes may be expressed in which tissues. " Researchers have access to the prediction tool for genetic activity on worm.princeton.edu.

As a case study, the team used the prediction tool to examine genes controlled by CREB, a gene that serves as an important regulator of both metabolism and long-term memory, which Murphy's lab studied for its role in aging processes. Although CREB's activities in neurons are well known, this research suggested that CREB also regulates genes in the epidermis, intestines and reproductive organs of the worm.

Murphy stressed that the paper contains only a few examples of new findings made possible by the tissue-specific gene expression data and the predictive tool of the team. "We really hope that people in the worm research community will use this to find things we have not even thought of," she said.

Other co-authors were April Williams, who received a Ph.D. in quantitative and computational biology at Princeton in 2015; Alexi Runnels, a Ph.D. to graduate; Alicja Tadych, a scientific software engineer at the Lewis Sigler Institute; and Shiyi Zhou, a graduate student in molecular biology.

The work was partially supported by the National Institutes of Health and the Glenn Foundation for Medical Research.


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