Life Sciences Commons^™

Rapid-Query For Fast Identity By Descent Search And Genealogical Analysis, Yuan Wei, Ardalan Naseri, Degui Zhi, Shaojie Zhang

Faculty, Staff and Student Publications

MOTIVATION: Due to the rapid growth of the genetic database size, genealogical search, a process of inferring familial relatedness by identifying DNA matches, has become a viable approach to help individuals finding missing family members or law enforcement agencies locating suspects. A fast and accurate method is needed to search an out-of-database individual against millions of individuals. Most existing approaches only offer all-versus-all within panel match. Some prototype algorithms offer one-versus-all query from out-of-panel individual, but they do not tolerate errors.

RESULTS: A new method, random projection-based identity-by-descent (IBD) detection (RaPID) query, is introduced to make fast genealogical search possible. …

Dissociation Protocols Used For Sarcoma Tissues Bias The Transcriptome Observed In Single-Cell And Single-Nucleus Rna Sequencing, Danh D Truong, Salah-Eddine Lamhamedi-Cherradi, Robert W Porter, Sandhya Krishnan, Jyothishmathi Swaminathan, Amber Gibson, Alexander J Lazar, J Andrew Livingston, Vidya Gopalakrishnan, Nancy Gordon, Najat C Daw, Nicholas E Navin, Richard Gorlick, Joseph A Ludwig

Faculty, Staff and Student Publications

BACKGROUND: Single-cell RNA-seq has emerged as an innovative technology used to study complex tissues and characterize cell types, states, and lineages at a single-cell level. Classification of bulk tumors by their individual cellular constituents has also created new opportunities to generate single-cell atlases for many organs, cancers, and developmental models. Despite the tremendous promise of this technology, recent evidence studying epithelial tissues and diverse carcinomas suggests the methods used for tissue processing, cell disaggregation, and preservation can significantly bias gene expression and alter the observed cell types. To determine whether sarcomas - tumors of mesenchymal origin - are subject to …

An Ecological Perspective Of American Rodent-Borne Orthohantavirus Surveillance, Nathaniel Mull

Graduate Theses and Dissertations

Orthohantaviruses are a global group of viruses found primarily in rodents, though several viruses have also been found in shrews and moles. Many rodent-borne orthohantaviruses are capable of causing one of several diseases in humans, and the mortality associated with these diseases ranges from < 0.1% - 50% depending on the specific etiological virus. In North and South America, orthohantavirus research was ignited by an outbreak of severe disease in the Four Corners region of the United States in 1993. However, despite the discovery of over 20 orthohantaviruses in the Americas, our understanding of orthohantavirus ecology and virus-host dynamics in this region is still limited, and orthohantavirus surveillance is generally restricted in scope to select regions and small portions of host distributional ranges. In Chapter I, I present a literature review on the current understanding of American rodent-borne orthohantavirus ecology. This review focused on under-studied orthohantaviruses, addressing gaps in knowledge by extrapolating information from well-studied orthohantaviruses, general rodent ecology, and occassionally from Eurasian orthohantavirus-host ecology. There were several key conclusions generated from this review that warrant further research: 1) the large number of putative orthohantaviruses and gaps in orthohantavirus evolution necessitate further surveillance and characterization, 2) orthohantavirus traits differ and are more generalizable based on host taxonomy rather than geography, and 3) orthohantavirus host species are disproportionately found in grasslands and disturbed habitats. In Chapter II, I present a prioritized list of rodent species to target for orthohantavirus surveillance based on predictive modeling using machine learning. Probable orthohantavirus hosts were predicted based on traits of known orthohantavirus hosts using two different types of evidence: RT-PCR and virus isolation. Predicted host distributions were also mapped to identify geographic hotspots to spatially guide future surveillance efforts. In Chapter III, I present a framework for understanding and predicting orthohantavirus traits based on reservoir host phylogeny, as opposed to the traditional geographic dichotomy used to group orthohantaviruses. This framework establishes three distinct orthohantavirus groups: murid-borne orthohantaviruses, arvicoline-borne orthohantaviruses, and non-arvicoline cricetid-borne orthohantaviruses, which differ in several key traits, including the human disease they cause, transmission routes, and virus-host fidelity. In Chapter IV, I compare rodent communities and orthohantavirus prevalence among grassland management regimes. Sites that were periodically burned had high rodent diversity and a high proportion of grassland species. However, rodent seroprevalence for orthohantavirus was also highest in burned sites, representing a trade-off in habitat management outcomes. The high seroprevalence in burned sites is likely due to the robust populations supported by the high quality habitat resulting from prescribed burning. In Chapters V and VI, I describe Ozark virus and Sager Creek virus, two novel orthohantaviruses discovered from specimens collected during Chapter IV. Both chapters report full genome sequences of the respective viruses and compare both nucleotide and protein phylogenies with related orthohantaviruses. Additionally in Chapter VI, I support the genetic analyses with molecular and ecological characterizations, including seasonal fluctuations in host abundance, correlates of prevalence, evidence of virus shedding, and information on host cell susceptibility to Sager Creek virus.

Comparative Analysis Of Dimension Reduction Methods For Cytometry By Time-Of-Flight Data, Kaiwen Wang, Yuqiu Yang, Fangjiang Wu, Bing Song, Xinlei Wang, Tao Wang

Faculty, Staff and Student Publications

While experimental and informatic techniques around single cell sequencing (scRNA-seq) are advanced, research around mass cytometry (CyTOF) data analysis has severely lagged behind. CyTOF data are notably different from scRNA-seq data in many aspects. This calls for the evaluation and development of computational methods specific for CyTOF data. Dimension reduction (DR) is one of the critical steps of single cell data analysis. Here, we benchmark the performances of 21 DR methods on 110 real and 425 synthetic CyTOF samples. We find that less well-known methods like SAUCIE, SQuaD-MDS, and scvis are the overall best performers. In particular, SAUCIE and scvis …

Decs: A Tool For Systematic Cell Type Annotations Of Single-Cell Rna Sequencing Data Among Human Tissues, Guangsheng Pei, Fangfang Yan, Lukas M Simon, Yulin Dai, Peilin Jia, Zhongming Zhao

Faculty, Staff and Student Publications

Single-cell RNA sequencing (scRNA-seq) is revolutionizing the study of complex and dynamic cellular mechanisms. However, cell type annotation remains a main challenge as it largely relies on a priori knowledge and manual curation, which is cumbersome and subjective. The increasing number of scRNA-seq datasets, as well as numerous published genetic studies, has motivated us to build a comprehensive human cell type reference atlas.Here, we present decoding Cell type Specificity (deCS), an automatic cell type annotation method augmented by a comprehensive collection of human cell type expression profiles and marker genes. We used deCS to annotate scRNA-seq data from various tissue …

Protocols For Single-Cell Rna-Seq And Spatial Gene Expression Integration And Interactive Visualization, Surbhi Sona, Matthew Bradley, Angela H Ting

Faculty, Staff and Student Publications

There is a wealth of software that utilizes single-cell RNA-seq (scRNA-seq) data to deconvolve spatial transcriptomic spots, which currently are not yet at single-cell resolution. Here we provide protocols for implementing Seurat and Giotto packages to elucidate cell-type distribution in our example human ureter scRNA-seq dataset. We also describe how to create a stand-alone interactive web application using Seurat libraries to visualize and share our results. For complete details on the use and execution of this protocol, please refer to Fink et al. (2022).

A Comprehensive Assessment Of Cell Type-Specific Differential Expression Methods In Bulk Data, Guanqun Meng, Wen Tang, Emina Huang, Ziyi Li, Hao Feng

Faculty, Staff and Student Publications

Accounting for cell type compositions has been very successful at analyzing high-throughput data from heterogeneous tissues. Differential gene expression analysis at cell type level is becoming increasingly popular, yielding biomarker discovery in a finer granularity within a particular cell type. Although several computational methods have been developed to identify cell type-specific differentially expressed genes (csDEG) from RNA-seq data, a systematic evaluation is yet to be performed. Here, we thoroughly benchmark six recently published methods: CellDMC, CARseq, TOAST, LRCDE, CeDAR and TCA, together with two classical methods, csSAM and DESeq2, for a comprehensive comparison. We aim to systematically evaluate the performance …

Syllable-Pbwt For Space-Efficient Haplotype Long-Match Query, Victor Wang, Ardalan Naseri, Shaojie Zhang, Degui Zhi

Faculty, Staff and Student Publications

MOTIVATION: The positional Burrows-Wheeler transform (PBWT) has led to tremendous strides in haplotype matching on biobank-scale data. For genetic genealogical search, PBWT-based methods have optimized the asymptotic runtime of finding long matches between a query haplotype and a predefined panel of haplotypes. However, to enable fast query searches, the full-sized panel and PBWT data structures must be kept in memory, preventing existing algorithms from scaling up to modern biobank panels consisting of millions of haplotypes. In this work, we propose a space-efficient variation of PBWT named Syllable-PBWT, which divides every haplotype into syllables, builds the PBWT positional prefix arrays on …

The Challenges And Opportunities Of Scrna-Seq In Covid-19 Research And Clinical Translation, Wendao Liu, Xiaohua Ye, Zhiqiang An, Zhongming Zhao

Faculty, Staff and Student Publications

The application of single-cell RNA sequencing in COVID-19 research has greatly improved our understanding of COVID-19 pathogenesis and immunological characteristics. In this commentary, we discuss the current challenges, limitations, and perspectives in harnessing the power of single-cell RNA sequencing to accelerate both basic research and therapeutic development for COVID-19 and other emerging infectious diseases.

A Machine Learning-Based Method For Automatically Identifying Novel Cells In Annotating Single-Cell Rna-Seq Data, Ziyi Li, Yizhuo Wang, Irene Ganan-Gomez, Simona Colla, Kim-Anh Do

Faculty, Staff and Student Publications

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) has been widely used to decompose complex tissues into functionally distinct cell types. The first and usually the most important step of scRNA-seq data analysis is to accurately annotate the cell labels. In recent years, many supervised annotation methods have been developed and shown to be more convenient and accurate than unsupervised cell clustering. One challenge faced by all the supervised annotation methods is the identification of the novel cell type, which is defined as the cell type that is not present in the training data, only exists in the testing data. Existing methods usually …

Mochi: A Comprehensive Cross-Platform Tool For Amplicon-Based Microbiota Analysis, Jun-Jie Zheng, Po-Wen Wang, Tzu-Wen Huang, Yao-Jong Yang, Hua-Sheng Chiu, Pavel Sumazin, Ting-Wen Chen

Children’s Nutrition Research Center Staff Publications

Motivation: Microbiota analyses have important implications for health and science. These analyses make use of 16S/18S rRNA gene sequencing to identify taxa and predict species diversity. However, most available tools for analyzing microbiota data require adept programming skills and in-depth statistical knowledge for proper implementation. While long-read amplicon sequencing can lead to more accurate taxa predictions and is quickly becoming more common, practitioners have no easily accessible tools with which to perform their analyses.

Results: We present MOCHI, a GUI tool for microbiota amplicon sequencing analysis. MOCHI preprocesses sequences, assigns taxonomy, identifies different abundant species and predicts species diversity and …

Single-Cell Rna Sequencing Reveals Molecular Features Of Heterogeneity In The Murine Retinal Pigment Epithelium., Ravi S Pandey, Mark P. Krebs, Mohan Bolisetty, Jeremy R. Charette, Juergen K. Naggert, Paul Robson, Patsy M. Nishina, Gregory W. Carter

Faculty Research 2022

Transcriptomic analysis of the mammalian retinal pigment epithelium (RPE) aims to identify cellular networks that influence ocular development, maintenance, function, and disease. However, available evidence points to RPE cell heterogeneity within native tissue, which adds complexity to global transcriptomic analysis. Here, to assess cell heterogeneity, we performed single-cell RNA sequencing of RPE cells from two young adult male C57BL/6J mice. Following quality control to ensure robust transcript identification limited to cell singlets, we detected 13,858 transcripts among 2667 and 2846 RPE cells. Dimensional reduction by principal component analysis and uniform manifold approximation and projection revealed six distinct cell populations. All …

Webcsea: Web-Based Cell-Type-Specific Enrichment Analysis Of Genes, Yulin Dai, Ruifeng Hu, Andi Liu, Kyung Serk Cho, Astrid Marilyn Manuel, Xiaoyang Li, Xianjun Dong, Peilin Jia, Zhongming Zhao

Faculty, Staff and Student Publications

Human complex traits and common diseases show tissue- and cell-type- specificity. Recently, single-cell RNA sequencing (scRNA-seq) technology has successfully depicted cellular heterogeneity in human tissue, providing an unprecedented opportunity to understand the context-specific expression of complex trait-associated genes in human tissue-cell types (TCs). Here, we present the first web-based application to quickly assess the cell-type-specificity of genes, named Web-based Cell-type Specific Enrichment Analysis of Genes (WebCSEA, available at https://bioinfo.uth.edu/webcsea/). Specifically, we curated a total of 111 scRNA-seq panels of human tissues and 1,355 TCs from 61 different general tissues across 11 human organ systems. We adapted our previous decoding tissue-specificity …

Comprehensive Characterization Of Tumor Immune Landscape Following Oncolytic Virotherapy By Single-Cell Rna Sequencing, Divya Ravirala, Guangsheng Pei, Zhongming Zhao, Xiaoliu Zhang

Faculty, Staff and Student Publications

An important mechanism of oncolytic virotherapy in ameliorating cancer immunotherapy is by inducing significant changes in the immune landscape in the tumor microenvironment (TME). Despite this notion and the potential therapeutic implications, a comprehensive analysis of the immune changes in carcinomas induced by virotherapy has not yet been elucidated. We conducted single-cell RNA sequencing analysis on carcinomas treated with an HSV-2-based oncolytic virus to characterize the immunogenic changes in the TME. We specifically analyzed and compared the immune cell composition between viral treated and untreated tumors. We also applied CellChat to analyze the complex interactions among the infiltrated immune cells. …

Novel And Extendable Genotyping System For Human Respiratory Syncytial Virus Based On Whole-Genome Sequence Analysis, Jiani Chen, Xueting Qiu, Vasanthi Avadhanula, Samuel S Shepard, Do-Kyun Kim, James Hixson, Pedro A Piedra, Justin Bahl

Faculty, Staff and Student Publications

BACKGROUND: Human respiratory syncytial virus (RSV) is one of the leading causes of respiratory infections, especially in infants and young children. Previous RSV sequencing studies have primarily focused on partial sequencing of G gene (200-300 nucleotides) for genotype characterization or diagnostics. However, the genotype assignment with G gene has not recapitulated the phylogenetic signal of other genes, and there is no consensus on RSV genotype definition.

METHODS: We conducted maximum likelihood phylogenetic analysis with 10 RSV individual genes and whole-genome sequence (WGS) that are published in GenBank. RSV genotypes were determined by using phylogenetic analysis and pair-wise node distances.

RESULTS: …

Svanna: Efficient And Accurate Pathogenicity Prediction Of Coding And Regulatory Structural Variants In Long-Read Genome Sequencing., Daniel Danis, Julius O B Jacobsen, Parithi Balachandran, Qihui Zhu, Feyza Yilmaz, Justin Reese, Matthias Haimel, Gholson J Lyon, Ingo Helbig, Christopher J Mungall, Christine R Beck, Charles Lee, Damian Smedley, Peter N Robinson

Faculty Research 2022

Structural variants (SVs) are implicated in the etiology of Mendelian diseases but have been systematically underascertained owing to sequencing technology limitations. Long-read sequencing enables comprehensive detection of SVs, but approaches for prioritization of candidate SVs are needed. Structural variant Annotation and analysis (SvAnna) assesses all classes of SVs and their intersection with transcripts and regulatory sequences, relating predicted effects on gene function with clinical phenotype data. SvAnna places 87% of deleterious SVs in the top ten ranks. The interpretable prioritizations offered by SvAnna will facilitate the widespread adoption of long-read sequencing in diagnostic genomics. SvAnna is available at https://github.com/TheJacksonLaboratory/SvAnn a …

Chromosomal Imbalances Detected Via Rna-Sequencing In 28 Cancers, Zuhal Ozcan, Francis A San Lucas, Justin W Wong, Kyle Chang, Konrad H Stopsack, Jerry Fowler, Yasminka A Jakubek, Paul Scheet

Faculty, Staff and Student Publications

Motivation: RNA-sequencing (RNA-seq) of tumor tissue is typically only used to measure gene expression. Here, we present a statistical approach that leverages existing RNA-seq data to also detect somatic copy number alterations (SCNAs), a pervasive phenomenon in human cancers, without a need to sequence the corresponding DNA.

Results: We present an analysis of 4942 participant samples from 28 cancers in The Cancer Genome Atlas (TCGA), demonstrating robust detection of SCNAs from RNA-seq. Using genotype imputation and haplotype information, our RNA-based method had a median sensitivity of 85% to detect SCNAs defined by DNA analysis, at high specificity (∼95%). As an …

Mako: A Graph-Based Pattern Growth Approach To Detect Complex Structural Variants., Jiadong Lin, Xiaofei Yang, Walter Kosters, Tun Xu, Yanyan Jia, Songbo Wang, Qihui Zhu, Mallory Ryan, Li Guo, Chengsheng Zhang, The Human Genome Structural Variation Consortium, Charles Lee, Scott E Devine, Evan E Eichler, Kai Ye

Faculty Research 2022

Complex structural variants (CSVs) are genomic alterations that have more than two breakpoints and are considered as the simultaneous occurrence of simple structural variants. However, detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match strategy. As a result, there has been limited progress for CSV discovery compared with simple structural variants. Here, we systematically analyzed the multi-breakpoint connection feature of CSVs, and proposed Mako, utilizing a bottom-up guided model-free strategy, to detect CSVs from paired-end short-read sequencing. Specifically, we implemented a graph-based pattern growth approach, where the graph depicts potential breakpoint connections, and pattern growth …

In Situ Chromatin Interaction Analysis Using Paired-End Tag Sequencing., Ping Wang, Yuliang Feng, Kun Zhu, Haoxi Chai, Ya-Ting Chang, Xiaofei Yang, Xiyuan Liu, Chen Shen, Eva Gega, Byoungkoo Lee, Minji Kim, Xiaoan Ruan, Yijun Ruan

Faculty Research 2021

Chromatin Interaction Analysis Using Paired-End Tag Sequencing (ChIA-PET) is an established method to map protein-mediated chromatin interactions. A limitation, however, is that it requires a hundred million cells per experiment, which hampers its broad application in biomedical research, particularly in studies in which it is impractical to obtain a large number of cells from rare samples. To reduce the required input cell number while retaining high data quality, we developed an in situ ChIA-PET protocol, which requires as few as 1 million cells. Here, we describe detailed step-by-step procedures for performing in situ ChIA-PET from cultured cells, including both an …

A Computational Pipeline To Infer Alternative Poly-Adenylation From 3′ Sequencing Data, Hari Krishna Yalamanchili, Nathan D Elrod, Madeline K Jensen, Ping Ji, Ai Lin, Eric J Wagner, Zhandong Liu

Children’s Nutrition Research Center Staff Publications

An increasing number of investigations have established alternative polyadenylation (APA) as a key mechanism of gene regulation through altering the length of 3' untranslated region (UTR) and generating distinct mRNA termini. Further, appreciation for the significance of APA in disease contexts propelled the development of several 3' sequencing techniques. While these RNA sequencing technologies have advanced APA analysis, the intrinsic limitation of 3' read coverage and lack of appropriate computational tools constrain precise mapping and quantification of polyadenylation sites. Notably, Poly(A)-ClickSeq (PAC-seq) overcomes limiting factors such as poly(A) enrichment and 3' linker ligation steps using click-chemistry. Here we provide an …

Assessment Of The Gut Bacterial Microbiome And Metabolome Of Girls And Women With Rett Syndrome, Santosh Thapa, Alamelu Venkatachalam, Nabeel Khan, Mohammed Naqvi, Miriam Balderas, Jessica K Runge, Anthony Haag, Kathleen M Hoch, Daniel G Glaze, Ruth Ann Luna, Kathleen J Motil

Children’s Nutrition Research Center Staff Publications

Background: Gastrointestinal problems affect the health and quality of life of individuals with Rett syndrome (RTT) and pose a medical hardship for their caregivers. We hypothesized that the variability in the RTT phenotype contributes to the dysbiosis of the gut microbiome and metabolome in RTT, predisposing these individuals to gastrointestinal dysfunction.

Objectives: We characterized the gut bacterial microbiome and metabolome in girls and young women with RTT (n = 44) and unaffected controls (n = 21), and examined the relation between the composition of the microbiome and variations in the RTT phenotype.

Methods: Demographics and clinical information, including growth and …

Genetic Variant Effects On Gene Expression In Human Pancreatic Islets And Their Implications For T2d., Ana Viñuela, Arushi Varshney, Martijn Van De Bunt, Rashmi B Prasad, Olof Asplund, Amanda Bennett, Michael Boehnke, Andrew A Brown, Michael R Erdos, João Fadista, Ola Hansson, Gad Hatem, Cédric Howald, Apoorva K Iyengar, Paul Johnson, Ulrika Krus, Patrick E Macdonald, Anubha Mahajan, Jocelyn E Manning Fox, Narisu Narisu, Vibe Nylander, Peter Orchard, Nikolay Oskolkov, Nikolaos I Panousis, Anthony Payne, Michael L. Stitzel, Swarooparani Vadlamudi, Ryan Welch, Francis S Collins, Karen L Mohlke, Anna L Gloyn, Laura J Scott, Emmanouil T Dermitzakis, Leif Groop, Stephen C J Parker, Mark I Mccarthy

Faculty Research 2020

Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, key tissues and cell-types required for functional inference are absent from large-scale resources. Here we explore the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using data from 420 donors. We find: (a) 7741 cis-eQTLs in islets with a replication rate across 44 GTEx tissues between 40% and 73%; (b) marked overlap between islet cis-eQTL signals and active regulatory sequences in islets, with reduced eQTL effect size observed in …

Fishermp: Fully Parallel Algorithm For Detecting Combinatorial Motifs From Large Chip-Seq Datasets., Shaoqiang Zhang, Ying Liang, Xiangyun Wang, Zhengchang Su, Yong Chen

College of Science & Mathematics Departmental Research

Detecting binding motifs of combinatorial transcription factors (TFs) from chromatin immunoprecipitation sequencing (ChIP-seq) experiments is an important and challenging computational problem for understanding gene regulations. Although a number of motif-finding algorithms have been presented, most are either time consuming or have sub-optimal accuracy for processing large-scale datasets. In this article, we present a fully parallelized algorithm for detecting combinatorial motifs from ChIP-seq datasets by using Fisher combined method and OpenMP parallel design. Large scale validations on both synthetic data and 350 ChIP-seq datasets from the ENCODE database showed that FisherMP has not only super speeds on large datasets, but also …

Transcriptome And Physiological Analyses For Revealing Genes Involved In Wheat Response To Endoplasmic Reticulum Stress., Xing Yu, Tanchun Wang, Meichen Zhu, Liting Zhang, Fengzhi Zhang, Enen Jing, Yongzhe Ren, Zhiqiang Wang, Zeyu Xin, Tongbao Lin

Touro College of Osteopathic Medicine (Middletown) Publications and Research

BACKGROUND: Wheat production is largely restricted by adverse environmental stresses. Under many undesirable conditions, endoplasmic reticulum (ER) stress can be induced. However, the physiological and molecular responses of wheat to ER stress remain poorly understood. We used dithiothreitol (DTT) and tauroursodeoxycholic acid (TUDCA) to induce or suppress ER stress in wheat cells, respectively, with the aim to reveal the molecular background of ER stress responses using a combined approach of transcriptional profiling and morpho-physiological characterization.

METHODS: To understand the mechanism of wheat response to ER stress, three wheat cultivars were used in our pre-experiments. Among them, the cultivar with a …

Red Panda: A Novel Method For Detecting Variation In Single-Cell Rna Sequencing, Adam Cornish

Theses & Dissertations

Single-cell sequencing enables the rapid acquisition of genomic and transcriptomic data from individual cells to better understand genetic diseases, such as cancer or autoimmune disorders, which are often affected by changes in rare cells. Currently, no existing software is aimed at identifying single nucleotide variations or micro (1-50bp) insertions and deletions in single-cell RNA sequencing (scRNA-seq) data. However, generating high quality data is vital to the study of the aforementioned diseases, among others. Our goal is to create such a tool and use in-house sequencing to validate its effectiveness. Our software employs the unique information found in scRNA-seq data to …

Embryonic Origin And Genetic Basis Of Cave Associated Phenotypes In The Isopod Crustacean Asellus Aquaticus., Hafasa Mojaddidi, Franco Fernandez, Priscilla A. Erickson, Meredith E. Protas

Natural Sciences and Mathematics | Faculty Scholarship

Characteristics common to animals living in subterranean environments include the reduction or absence of eyes, lessened pigmentation and enhanced sensory systems. How these characteristics have evolved is poorly understood for the majority of cave dwelling species. In order to understand the evolution of these changes, this study uses an invertebrate model system, the freshwater isopod crustacean, Asellus aquaticus, to examine whether adult differences between cave and surface dwelling individuals first appear during embryonic development. We hypothesized that antennal elaboration, as well as eye reduction and pigment loss, would be apparent during embryonic development. We found that differences in pigmentation, eye …

Comparing Apples And Oranges?: Next Generation Sequencing And Its Impact On Microbiome Analysis, Adam G. Clooney, Fiona Fouhy, Roy D. Sleator, Aisling O'Driscoll, Stanton Catherine, Paul D. Cotter, Marcus J. Claesson

Department of Biological Sciences Publications

Rapid advancements in sequencing technologies along with falling costs present widespread opportunities for microbiome studies across a vast and diverse array of environments. These impressive technological developments have been accompanied by a considerable growth in the number of methodological variables, including sampling, storage, DNA extraction, primer pairs, sequencing technology, chemistry version, read length, insert size, and analysis pipelines, amongst others. This increase in variability threatens to compromise both the reproducibility and the comparability of studies conducted. Here we perform the first reported study comparing both amplicon and shotgun sequencing for the three leading next-generation sequencing technologies. These were applied to …

High Throughput Genomic Sequencing Of Bioaerosols In Broiler Chicken Production Facilities, Kate M. O’Brien, Michael S. Chimenti, Morgan Farnell, Tom Tabler, Thomas Bair, Joey Lynn Bray, Matthew W. Nonnenmann

Faculty Publications

Chronic inhalation exposure to agricultural dust promotes the development of chronic respiratory diseases among poultry workers. Poultry dust is composed of dander, chicken feed, litter bedding and microbes. However, the microbial composition and abundance has not been fully elucidated. Genomic DNA was extracted from settled dust and personal inhalable dust collected while performing litter sampling or mortality collection tasks. DNA libraries were sequenced using a paired-end sequencing-by-synthesis approach on an Illumina HiSeq 2500. Sequencing data showed that poultry dust is predominantly composed of bacteria (64–67%) with a small quantity of avian, human and feed DNA (< 2% of total reads). Staphylococcus sp. AL1, Salinicoccus carnicancri and Lactobacillus crispatus were the most abundant bacterial species in personal exposure samples of inhalable dust. Settled dust had a moderate relative abundance of these species as well as Staphylococcus lentus and Lactobacillus salivarius. There was a statistical difference between the microbial composition of aerosolized and settled dust. Unlike settled dust composition, aerosolized dust composition had little variance between samples. These data provide an extensive analysis of the microbial composition and relative abundance in personal inhalable poultry dust and settled poultry dust.

Climp: Clustering Motifs Via Maximal Cliques With Parallel Computing Design., Shaoqiang Zhang, Yong Chen

College of Science & Mathematics Departmental Research

A set of conserved binding sites recognized by a transcription factor is called a motif, which can be found by many applications of comparative genomics for identifying over-represented segments. Moreover, when numerous putative motifs are predicted from a collection of genome-wide data, their similarity data can be represented as a large graph, where these motifs are connected to one another. However, an efficient clustering algorithm is desired for clustering the motifs that belong to the same groups and separating the motifs that belong to different groups, or even deleting an amount of spurious ones. In this work, a new motif …

Rfx Transcription Factors Are Essential For Hearing In Mice, Ran Elkon, Beatrice Milon, Laura Morrison, Manan Shah, Sarath Vijayakumar, Manoj Racherla, Carmen C. Leitch, Lorna Silipino, Shadan Hadi, Michèle Weiss-Gayet, Emmanuèle Barras, Christoph D. Schmid, Aouatef Ait-Lounis, Ashley Barnes, Yang Song, David J. Eisenman, Efrat Eliyahu, Gregory I. Frolenkov, Scott E. Strome, Bénédicte Durand, Norann A. Zaghloul, Sherri M. Jones, Walter Reith, Ronna Hertzano

Physiology Faculty Publications

Sensorineural hearing loss is a common and currently irreversible disorder, because mammalian hair cells (HCs) do not regenerate and current stem cell and gene delivery protocols result only in immature HC-like cells. Importantly, although the transcriptional regulators of embryonic HC development have been described, little is known about the postnatal regulators of maturating HCs. Here we apply a cell type-specific functional genomic analysis to the transcriptomes of auditory and vestibular sensory epithelia from early postnatal mice. We identify RFX transcription factors as essential and evolutionarily conserved regulators of the HC-specific transcriptomes, and detect Rfx1,2,3,5 and 7 in the developing HCs. …