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Leible, S.

Publications and source records attributed to Leible, S..

2 recordsLinked to original sources

Gene expression atlas of a developing tissue by single cell expression correlation analysis

The Drosophila wing disc has been a fundamental model system for the discovery of key signaling pathways and for our understanding of developmental processes. However, a complete map of gene expression in this tissue is lacking. To obtain a complete gene expression atlas in the wing disc, we employed single-cell sequencing (scRNA-seq) and developed a new method for analyzing scRNA-seq data based on gene expression correlations rather than cell mappings. This enables us to discover 824 genes with spatially restricted expression patterns, and to compute expression maps for all genes in the wing disc. This approach identifies both known and new clusters of genes with similar expression patterns and functional relevance. As proof of concept, we characterize the previously unstudied gene CG5151 and show it regulates Wnt signaling. This novel method will enable the leveraging of scRNA-seq data for generating expression atlases of undifferentiated tissues during development.

developmental biology

Sorting & Sequencing Flies By Size: Identification Of Novel TOR Regulators And Parameters For Successful Sorting

As DNA sequencing throughput increases, novel strategies for discovering genes that affect traits of interest become available. One strategy starts with a population of animals and selects individuals over multiple generations for a particular trait. Subsequent whole genome sequencing should identify loci affecting this trait. We apply this strategy by sorting flies for wing length over 18 generations, obtaining two populations that differ in wing length by 20%. Flies with longer wings had increased overall body sizes and elevated TOR activity, suggesting that genetic variation targets TOR signaling to influence body size. High-throughput sequencing of big and small flies identified thousands of single nucleotide polymorphisms that differed between the two populations, leading us to identify five novel regulators of TOR signaling. Surprisingly, stochastic simulations of the process show that large fractions of the genetic differences between the big and small flies are probably biological false positives, selected by chance by random drift. We employ these computer simulations to identify experimental setup parameters to improve the signal-to-noise ratio for successfully running sort-and-sequence experiments - a resource which will hopefully be useful for the community.

genetics