New: Tetrad Detection Software for Yeast Genetics
February 26, 2019
In many eukaryotes, including the yeasts Saccharomyces cerevisiae, it is possible to recover all four of the haploid products of a single meiosis, tetrads. These tetrads can be characterized genetically and phenotypically. Tetrad analysis is a powerful technique that is routinely used to make associations between genetic variation and phenotype, uncover gene-gene interactions, and identify non-reciprocal meiotic recombination events (e.g. gene conversions).
Selected Major Publications for David Galas, PhD
Branscomb, E. W. and Galas, D. J., “Progressive Decrease in Protein Synthesis Accuracy Induced by Streptomycin in E. coli,” Nature, 254:161-163 (1975). (reprinted in Benchmark Papers in Genetics Series, Genes, Proteins and Cellular Aging, ed. R. Holliday, van Nostrand Reinhold Co., New York, (1976).
Galas, D. J. and Schmitz, A., “DNAase Footprinting: A Simple Method for the Detection of Protein-DNA Binding Specificity,” Nucleic Acids Res., 5:3157-3170 (1978).
2019 Publications from the Galas Lab
Sakhanenko, Cromie, Dudley, Galas, “Computational Inference Software for Tetrad Assembly from Randomly Arrayed Yeast Colonies”, G3: GENES, GENOMES, GENETICS Early online May 20, 2019; https://doi.org/10.1534/g3.119.400166 (May 2019)
Maria D. Giraldez, Ryan M. Spengler, Alton Etheridge, Annika J. Goicochea , Missy Tuck, Sung Won Choi, David J. Galas, Muneesh Tewari, “Phospho-RNA-seq: a modified small RNA-seq method that reveals circulating mRNA and lncRNA fragments as potential biomarkers in human plasma”, The EMBO Journal (2019)e101695; May 3, 2019; doi 10.15252/embj.2019101695 (May 2019)
Vikas Ghai, Taek-Kyun Kim, Alton Etheridge, Trine Nielsen, Torben Hansen, Oluf Pedersen, David Galas and Kai Wang, “Extracellular vesicle encapsulated microRNAs in patients with type 2 diabetes are affected by metformin treatment”, J. Clin. Med. 2019, 8, 617; doi:10.3390/jcm8050617 (May 2019)
Laurent, L. et al., “The Extracellular RNA Communication Consortium: Establishing Foundational Knowledge and Technologies for Extracellular RNA Research”. Cell, 177(2):231-242 (April 2019)
Oscar D. Murillo, William Thistlethwaite, Joel Rozowsky, …, Matthew E. Roth, Mark B. Gerstein, Aleksandar Milosavljevic, “exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids”, Cell, 177, 463–477 https://doi.org/10.1016/j.cell.2019.02.018(April 4, 2019)
Uechi, L., Galas, D.J., Sakhanenko, N.A., “Multivariate analysis of data sets with missing values: an information theory-based reliability function”, J Comp Biol, 26(2), 152-171; https://doi.org/10.1089/cmb.2018.0179 (February 2019).
Sakhanenko, N.A., Galas, D.J., “Symmetries among multivariate information measures explored using Möbius operators”, Entropy, 21(1), 88; https://doi.org/10.3390/e21010088 (January 2019).
2018 Publications from the Galas Lab
Etheridge, A., Wang, K., Baxter, D., Galas, D.J., “Optimized protocol for preparation of small RNA NGS libraries from biofluids”, Chapter: Methods in Molecular Biology (2018).
Heintz-Buschart, A., Yusuf, D., Kayen, A., Etheridge, A., Fritz, J., May, P., de Beaufort, C., Upadhyaya, B., Ghosal, A., Galas, D.J., Wilmes, P., “Small RNA profiling of low biomass samples: identification and removal of contaminants”, BMC Biology, 16:52 https://doi.org/10.1186/s12915-018-0522-7 (2018).
2017 Publications from the Galas Lab
Patra, B., Kon, Y., Yadav, G., Sevold, A.W., Frumkin, J.P., Vallabhajosyula, R.R., Hintze, A., Østman, B., Schossau, J., Bhan, A., Marzolf, B., Tamashiro, J.K., Kaur, A., Baliga, N.S., Grayhack, E.J., Adami, C., Galas, D.J., Raval, A., Phizicky, E.M., Ray, A., “A genome-wide dosage suppressor network reveals genomic robustness”, Nucl Acids Res, 9;45(1):255-270. doi: 10.1093/nar/gkw1148 (2017).
Kunert-Graf, J., Sakhanenko, N.A., Galas, D.J. “Complexity and Vulnerability Analysis of the C. elegans Gap Junction Connectome”, Entropy: Complexity, 19(3), 104; doi:10.3390/e19030104 (2017).