Publications
View Google Scholar Profile for Dr. Galas
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).
The following software produced by PNRI is based on information theory for computationally identifying sister spores derived from the same meiotic tetrad. The method exploits specific DNA sequence features of tetrads that result from meiotic centromere and allele segregation patterns. Because the method uses only the genomic sequence, it alleviates the need for tetrad-specific barcodes or other genetic modifications to the strains. Using this method, strains derived from randomly arrayed spores can be efficiently grouped back into tetrads.
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).
Schmitz, A. and Galas, D. J., “The Interaction of RNA Polymerase and lac Repressor with the lac Control Region,” Nucleic Acids Res., 6:111-137 (1979).
Galas, D. J. and Chandler, M., “On the Molecular Mechanisms of Transposition,” Proc. Nat. Acad. Sci. (USA), 78:4858-4862 (1981).
Waterman, M., Arratia, R. and Galas, D., “Pattern Recognition in Several Sequences: Consensus and Alignment,” Bull. Math. Biol., 46:515-527 (1984).
Galas, D., Eggert, M. and Waterman, M., “Rigorous Pattern Recognition Methods for DNA Sequences: Analysis of Promoter Sequences for E. coli,” J. Mol. Biol., 186:117-128 (1985).
Prentki, P., Chandler, M. and Galas, D., “E. coli Integration Host Factor Bends the DNA at the Ends of IS1 and in an Insertion Hotspot with Multiple IHF Binding Sites,” EMBO Journ., 6:2479-2487, (1987).
Galas, D. and Chandler, M., “Bacterial Insertion Sequences” (review) Chapter 4 in Mobile DNA, pp. 109-162, American Society for Microbiology, Washington, D.C., (1989).
Collins, F. and Galas, D. J., “A New Five-year Plan for the U. S. Human Genome Project,” Science, 262:43-46, (1993).
Levy-Lahad E., Wasco W., Poorkaj P., Ramano D., Oshima J., Pettingell W., Yu C., Jondro P., Schmidt S., Wang K., Crowley A., Fu YH., Guenette S., Galas D., Nemens E., Wijsman E., Bird T., Schellenberg G., and Tanzi R., “Candidate Gene for the Chromosone 1 Familial Alzheimer’s Disease Locus,” Science, 269:973-977, (1995).
Galas, D. J., “New Genetic Tools: Their Roles in Drug Discovery and Development,” International Journal of Pharmaceutical Medicine, 12:13-18 (1998).
Brunkow, M., Gardner, J., Van Ness, J., Paeper, B., Kovacevich, B., Proll, S., Skonier, J., Zhao, L., Sabo, P.J., Fu, Y., Alisch, R., Gillett, L., Colbert, T., Tacconi, P., Galas, D., Hamersma, H., Beighton, P., and Mulligan, J., “Bone Dysplasia Sclerosteosis Results from Loss of the SOST Gene Product, a Novel Cystine Knot-Containing Protein,” American Journal of Human Genetics, 68:577-589 (2001).
Galas, D.J., “The Invention of Footprinting”, Trends in Biochemical Sciences, 26:690-693 (2001).
Chung, F., Dewey, T.G., Lu Liang, and Galas, D. J., “Duplication Models and Biological Networks,”Journal of Computational Biology, 10(5):667-687 (2003).
Van Ness, J., Van Ness, L., and Galas, D.J., “Isothermal Reactions for the Amplification of Oligonucleotides,” Proc. Nat. Acad. Sci. USA, 100:4504-4509 (2003).
Wang, K., Zhang, S., Marzolf, B., Troisch, P., Brightman, A., Hu, Z., Hood, L.E., and Galas, D.J., “Circulating microRNAs, potential biomarkers for drug-induced liver injury,” Proc. Nat. Acad. Sci. (USA), 106(11):4402-4407 (2009).
Carter, G.W., Galitski, T. and Galas, D.J., “Maximal Extraction of Biological Information from Genetic Interaction Data,” PLoS Computational Biology, 5(4):e1000347 (2009).
Wang, K., Zhang, S., Weber, J., Baxter, D., and Galas, D.J., “Mammalian cells in culture actively export specific microRNAs,” Nucleic Acids Research, 38(20):7248-7259 (2010).
Roach, J.C., Glusman, G., Smit, A.F.A., Huff, C.D., Hubley, R., Shannon, P.T., Rowen, L., Pant, K.P., Goodman, N., Bamshad, M., Shendure, J., Drmanac, R., Jorde, L.B., Hood, L., and Galas, D.J., “Analysis of Genetic Inheritance in a Family Quartet by Whole Genome Sequencing,” Science, 328(5978):636-639 (2010).
Wang, K., Li, H., Yuan, Y., Etheridge, A., Huang, D., Wilmes, P., and Galas, D.J., “The Complex Exogenous RNA Spectra in Human Plasma: an Interface with Human Gut Microbiome?”, PLoS ONE, 7(12):e51009. doi:10.1371/journal.pone.0051009 (2012).
2021 Publications from the Galas Lab
Niinistö, S., Erlund, I., Lee, HS. et al. Children’s erythrocyte fatty acids are associated with the risk of islet autoimmunity. Sci Rep, 11, 3627; https://doi.org/10.1038/s41598-021-82200-9 (2021).
Kunert-Graf, J., Sakhanenko, N.A., Galas, D.J. “Optimized Permutation Testing for Information Theoretic Measures of Multi-Gene Interactions”, BMC Bioinformatics, 7;22(1):180. doi: 10.1186/s12859-021-04107-6 (2021).
Lusardi, T.A., Sandau, U.S., Sakhanenko, N.A., Baker, S.C.B., Wiedrick, J.T., Lapidus, J.A., Raskind, M.A., Li, G., Peskind, E.R., Galas, D.J., Quinn, J.F., Saugstad, J.A. “Cerebrospinal Fluid MicroRNA Changes in Cognitively Normal Veterans With a History of Deployment-Associated Mild Traumatic Brain Injury”, Front Neurosci, 9;15:720778. doi: 10.3389/fnins.2021.720778. PMID: 34580583; PMCID: PMC8463659 (eCollection, 2021).
2020 Publications from the Galas Lab
Kunert-Graf, J., Sakhanenko, N.A., Galas, D.J. “Partial Information Decomposition and the Information Delta: A Geometric Unification Disentangling Non-Pairwise Information”, Entropy, 22(12), 1333; https://doi.org/10.3390/e22121333, (2020).
Uechi, L., Jalali, M., Wilbur, J.D., French, J.L., Jumbe, N.L., Meaney, M.J., Gluckman, P.D., Kamani, N., Sakhanenko, N.A., Galas, D.J. “Complex genetic dependencies among growth and neurological phenotypes in healthy children: towards deciphering developmental mechanisms”, PLoS One, 15(12): e0242684. https://doi.org/10.1371/journal.pone.0242684 (2020).
Galas, D.J., Kunert-Graf, J., Uechi, L., Sakhanenko, N.A. “Towards an information theory of quantitative genetics”, J Comp Biol, 28(0), 1-33. DOI: 10.1089/cmb.2020.0032 (2020).
2019 Publications from the Galas Lab
James Michael Kunert-Graf, Kristian Eschenburg, David Galas, J. Nathan Kutz, Swati Rane, Bingni Wen Brunton, “Extracting Reproducible Time-Resolved Resting State Networks using Dynamic Mode Decomposition”, Frontiers In Computational Neuroscience, 13:75. doi: 10.3389/fncom.2019.00075. eCollection 2019 (October 2019)
Paula M Godoy, Andrea J Barczak, Peter DeHoff, Srimeenakshi Srinivasan, Alton Etheridge, David Galas, Saumya Das, David J Erle, Louise Laurent, MD/PhD, “Comparison of reproducibility, accuracy, sensitivity, and specificity of miRNA quantification platforms”, Cell Reports, 29(12), 4212-4222.e5 (December 2019)
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).
Shaffi, S.K., Galas, D.J., Etheridge, A., Argyropoulos, C., “Role of microRNAs in Renal Parenchymal Diseases – A New Dimension”, International Journal of Molecular Sciences, 19(6), 1797; https://doi.org/10.3390/ijms19061797 (2018).
Giraldez, M.D., Spengler, R.M., Etheridge, A., Godoy, P.M., Barczak, A.J., Srinivasan, S., De Hoff, P.L.,Tanriverdi, K., Courtright, A., Lu, S., Khoory, J., Rubio, R., Baxter, D., Driedonks, T.A.P., Buermans, H.P.J., Nolte-‘t Hoen, E.N.M., Jiang, H., Wang, K., Ghiran, I., Wang, Y., Van Keuren-Jensen, K., Freedman, J.E.,Woodruff, P.G., Laurent L.C., Erle, D.J., Galas, D.J., Tewari, M., “Comprehensive multi-center assessment of accuracy, reproducibility and bias of small RNA-seq methods for quantitative miRNA profiling”, Nature Biotechnology, 36;746–757 (2018).
Malabirade, A., Habier, J., Heintz-Buschart, A., May, P., Halder, R., Etheridge, A., Galas, D.J., Wilmes, P., and Fritz, J.V., “The RNA complement of outer membrane vesicles from Salmonella enterica serovar Typhimurium under distinct culture conditions”, Frontiers Microbiol, 30 August; https://doi.org/10.3389/fmicb.2018.02015 (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).
Argyropoulos, C., Etheridge, A., Sakhanenko, N.A., Galas, D.J., “Modeling bias and variation in the stochastic processes of small RNA sequencing,” Nucl Acids Res, Jun 20;45(11):e104. doi: 10.1093/nar/gkx199 (2017).
Galas, D.J., Dewey, Kunert-Graf, J., Sakhanenko, N.A., “Expansion of the Kullback-Leibler Divergence, and a new class of information metrics”, Axioms, Axioms 2017, 6(2), 8; doi:10.3390/axioms6020008 (2017).
Galas, D.J., Patrinos, A. amd DeLisi, C, “Notes from a Revolution: Lessons from the Human Genome Project,” Issues in Science and Technology, Spring (2017).
Chen, Z., Chang, W.Y., Etheridge, A., Strickfaden, H., Jin, Z., Palidwor, G., Cho, J.H., Wang, K., Kwon, S.Y., Doré, C., Raymond, A., Hotta, A., Ellis, J., Kandel, R.A., Dilworth, F.J., Perkins, T.J., Hendzel, M.J., Galas, D.J., Stanford, W.L., “Reprogramming progeria fibroblasts re-establishes a normal epigenetic landscape”, Aging Cell, Aug;16(4):870-887. doi: 10.1111/acel.12621 (2017).
Wu, X., Kim, T-K, Baxter, D., Scherler, K., Gordon, A., Fong, O., Etheridge, A., Galas, D.J., Wang, K., “sRNAnalyzer – A flexible and customizable small RNA sequencing data analysis pipeline”, Nucl Acids Res, Dec 1;45(21):12140-12151 (2017).
Sakhanenko, N.A., Kunert-Graf, J., Galas, D.J., “The information content of discrete functions and their application in genetic data analysis”, J Comput Biol, Dec 24(12): 1153–1178. doi: 10.1089/cmb.2017.0143 (2017)
