The overall goal of this project is to further our understanding of alternative polyadenylation (APA) in eukaryotes, including the extent to which it occurs and the mechanisms by which it is regulated. Maturation of eukaryotic mRNA requires the actions of several post-transcriptional processes, one of which is 3'-end formation. This process consists of pre-mRNA cleavage and polydenylation, where a poly(A) tail is added to the newly cleaved 3'-end of pre-mRNA. It is guided by poly(A) signal motifs on the pre-mRNA. Polyadenylation has been shown to influence mRNA stability, translatability and transportability from the nucleus to cytoplasm. To complicated matters, many eukaryotic genes have more than one poly(A) site. Alternative polyadenylation (APA) is a phenomenon in which these different poly(A) sites are utilized to generate mRNA transcripts with different 3'-ends of the same gene. Increasing evidence suggests that APA is a key contributor in regulating gene expression, affecting mRNA levels and/or functions of coded proteins. It also affects the nature and length of the 3'-UTR harboring potential cis-regulatory motifs that are important for mRNA stability and translation suppression. APA appears to be regulated by both developmental and environmental cues, and it often occurs in a tissue- and/or disease-specific manner. Mutations of poly(A) signals or polyadenylation protein factors cause severe diseases including cancers. However, there are many important unanswered questions about underlying mechanisms of APA. For example, it is unclear how developmental and environmental cues are transduced to the APA process, or what special poly(A) signals (i.e., special RNA structures) are needed to guide APA. Next-Generation sequencing (NGS) has revolutionized transcriptome sequencing, allowing us to achieve considerably higher sequence depth and coverage than could be achieved through Sanger sequencing. The resulting high-volume NGS datasets make it possible to employ innovative new methodologies into our bioinformatics analyses of polyadenylation that will advance our understanding of APA and its regulatory mechanisms. Specifically, poly(A) sites will be more accurately annotated and cataloged based on their locations (e.g. within introns vs. exons), types (e.g. antisense vs. sense), and biological consequences (e.g. non-sense mediated decay, protein product truncation, and modification of micro-RNA binding sites). We will study how APA patterns and relevant cis-regulatory motifs have changed in different species, genotypes, tissues, developmental stages and environmental stresses. We will validate our predicted findings through wet lab protocols. Finally we will release our data, protocols and software to the research community through a richly analyzed and visualized online database and web service. Completion of the aims of this project for our model organisms will pave the way to more complete understanding of these complex regulatory mechanisms in Humans and other eukaryotes.

Public Health Relevance

When eukaryotic genes are expressed, their mRNAs have to be processed during maturation, a step of which is polyadenylation: the attachment of a poly(A) tail to mark and protect the end of mRNA. However, alternative polyadenylation (APA) at a different poly(A) site of mRNA will result in information lose of the mRNA and has been linked to cause cancers and other diseases. Using Next-Generation Sequencing data, we will employ innovative methodologies to accurately annotate poly(A) sites, detect poly(A) signals, examine APA and its regulatory mechanisms, and provide biomedical/biological research communities with an information rich database that will advance our understanding of APA role in human diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Academic Research Enhancement Awards (AREA) (R15)
Project #
1R15GM094732-01A1
Application #
8102400
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Krasnewich, Donna M
Project Start
2011-05-01
Project End
2014-04-30
Budget Start
2011-05-01
Budget End
2014-04-30
Support Year
1
Fiscal Year
2011
Total Cost
$283,614
Indirect Cost
Name
Miami University Oxford
Department
Other Basic Sciences
Type
Schools of Arts and Sciences
DUNS #
041065129
City
Oxford
State
OH
Country
United States
Zip Code
45056
Raj-Kumar, Praveen-Kumar; Vallon, Olivier; Liang, Chun (2017) In silico analysis of the sequence features responsible for alternatively spliced introns in the model green alga Chlamydomonas reinhardtii. Plant Mol Biol 94:253-265
Li, Lei; Ji, Guoli; Ye, Congting et al. (2015) PlantOrDB: a genome-wide ortholog database for land plants and green algae. BMC Plant Biol 15:161
Dong, Min; Ji, Guoli; Li, Qingshun Quinn et al. (2015) Extraction of poly(A) sites from large-scale RNA-Seq data. Methods Mol Biol 1255:25-37
Zhao, Zhixin; Wu, Xiaohui; Kumar, Praveen Kumar Raj et al. (2014) Bioinformatics analysis of alternative polyadenylation in green alga Chlamydomonas reinhardtii using transcriptome sequences from three different sequencing platforms. G3 (Bethesda) 4:871-83
Sreeskandarajan, Sutharzan; Flowers, Michelle M; Karro, John E et al. (2014) A MATLAB-based tool for accurate detection of perfect overlapping and nested inverted repeats in DNA sequences. Bioinformatics 30:887-8
Mao, Rui; Raj Kumar, Praveen Kumar; Guo, Cheng et al. (2014) Comparative analyses between retained introns and constitutively spliced introns in Arabidopsis thaliana using random forest and support vector machine. PLoS One 9:e104049
Morton, James T; Abrudan, Patricia; Figueroa, Nathanial et al. (2014) SCOPE++: sequence classification of homoPolymer emissions. Genomics 104:157-62
Ma, Liuyin; Guo, Cheng; Li, Qingshun Quinn (2014) Role of alternative polyadenylation in epigenetic silencing and antisilencing. Proc Natl Acad Sci U S A 111:9-10
Ye, Congting; Ji, Guoli; Li, Lei et al. (2014) detectIR: a novel program for detecting perfect and imperfect inverted repeats using complex numbers and vector calculation. PLoS One 9:e113349
Ma, Liuyin; Pati, Pratap Kumar; Liu, Man et al. (2014) High throughput characterizations of poly(A) site choice in plants. Methods 67:74-83

Showing the most recent 10 out of 16 publications