Lingling An

Lingling An

Associate Professor, Agricultural-Biosystems Engineering
Associate Professor, Public Health
Associate Professor, Statistics-GIDP
Associate Professor, BIO5 Institute
Member of the General Faculty
Member of the Graduate Faculty
Primary Department
Department Affiliations
Contact
(520) 621-1248

Research Interest

Lingling An, PhD, conducts research in the interdisciplinary boundaries of many fields such as statistical sciences, biological and medical sciences, genomics and genetics. Her statistical group's major research interests include development and application of statistical and computational methods for analysis of high-dimensional genomic/genetic, metagenomic/ metatranscriptomic, and epigenomic data. The overlying vision is to develop rigorous, timely and useful statistical and computational methodologies to help biologists/geneticists to ask, answer, and disseminate biologically interesting information in the quest to understand the ultimate function of DNA and gene network.

Publications

Zhao, J., Wang, J., Lingling, A. n., Doerge, R. W., Chen, Z. J., Grau, C. R., Meng, J., & Osborn, T. C. (2007). Analysis of gene expression profiles in response to Sclerotinia sclerotiorum in Brassica napus. Planta, 227(1), 13-24.

PMID: 17665211;Abstract:

Sclerotinia sclerotiorum is a necrotrophic plant pathogen which causes serious disease in agronomically important crop species. The molecular basis of plant defense to this pathogen is poorly understood. We investigated gene expression changes associated with S. sclerotiorum infection in a partially resistant and a susceptible genotype of oilseed Brassica napus using a whole genome microarray from Arabidopsis. A total of 686 and 1,547 genes were found to be differentially expressed after infection in the resistant and susceptible genotypes, respectively. The number of differentially expressed genes increased over infection time with the majority being up-regulated in both genotypes. The putative functions of the differentially expressed genes included pathogenesis-related (PR) proteins, proteins involved in the oxidative burst, protein kinase, molecule transporters, cell maintenance and development, abiotic stress, as well as proteins with unknown functions. The gene regulation patterns indicated that a large part of the defense response exhibited as a temporal and quantitative difference between the two genotypes. Genes associated with jasmonic acid (JA) and ethylene signal transduction pathways were induced, but no salicylic acid (SA) responsive genes were identified. Candidate defense genes were identified by integration of the early response genes in the partially resistant line with previously mapped quantitative trait loci (QTL). Expression levels of these genes were verified by Northern blot analyses. These results indicate that genes encoding various proteins involved in diverse roles, particularly WRKY transcription factors and plant cell wall related proteins may play an important role in the defense response to S. sclerotiorum disease. © 2007 Springer-Verlag.

Long, A. A., Kim, E., Leung, H., III, E. W., Lingling, A. n., Doerge, R. W., Pak, W. L., & Broadie, K. (2008). Presynaptic calcium channel localization and calcium-dependent synaptic vesicle exocytosis regulated by the fuseless protein. Journal of Neuroscience, 28(14), 3668-3682.

PMID: 18385325;PMCID: PMC2769928;Abstract:

A systematic forward genetic Drosophila screen for electroretinogram mutants lacking synaptic transients identified the fuseless (fusl) gene, which encodes a predicted eight-pass transmembrane protein in the presynaptic membrane. Null fusl mutants display >75% reduction in evoked synaptic transmission but, conversely, an approximately threefold increase in the frequency and amplitude of spontaneous synaptic vesicle fusion events. These neurotransmission defects are rescued by a wild-type fusl transgene targeted only to the presynaptic cell, demonstrating a strictly presynaptic requirement for Fusl function. Defects in FM dye turnover at the synapse show a severely impaired exo-endo synaptic vesicle cycling pool. Consistently, ultrastructural analyses reveal accumulated vesicles arrested in clustered and docked pools at presynaptic active zones. In the absence of Fusl, calcium-dependent neurotransmitter release is dramatically compromised and there is little enhancement of synaptic efficacy with elevated external Ca2+ concentrations. These defects are causally linked with severe loss of the Cacophony voltage-gated Ca2+ channels, which fail to localize normally at presynaptic active zone domains in the absence of Fusl. These data indicate that Fusl regulates assembly of the presynaptic active zone Ca 2+ channel domains required for efficient coupling of the Ca 2+ influx and synaptic vesicle exocytosis during neurotransmission. Copyright © 2008 Society for Neuroscience.

Luo, D., Ziebell, S., & An, L. (2017). An Informative Approach on Differential Abundance Analysis for Time-course Metagenomic Sequencing Count Data. Bioinformatics. doi:https://doi.org/10.1093/bioinformatics/btw828
An, L., Niu, Y. S., Hao, N., & An, L. -. (2011). Detection of rare functional variants using group ISIS. BMC proceedings, 5 Suppl 9.

Genome-wide association studies have been firmly established in investigations of the associations between common genetic variants and complex traits or diseases. However, a large portion of complex traits and diseases cannot be explained well by common variants. Detecting rare functional variants becomes a trend and a necessity. Because rare variants have such a small minor allele frequency (e.g., 0.05), detecting functional rare variants is challenging. Group iterative sure independence screening (ISIS), a fast group selection tool, was developed to select important genes and the single-nucleotide polymorphisms within. The performance of the group ISIS and group penalization methods is compared for detecting important genes in the Genetic Analysis Workshop 17 data. The results suggest that the group ISIS is an efficient tool to discover genes and single-nucleotide polymorphisms associated to phenotypes.

West, W., Piegorsch, W. W., Pena, E., An, L. -., Wu, W., Wickens, A., Xiong, H., & Chen, W. (2012). The impact of model uncertainty on benchmark dose estimation. Environmetrics, 23, 706-716.