Glen M. Borchert

Bio: Glen M. Borchert is an academic researcher from University of South Alabama. The author has contributed to research in topics: Small nucleolar RNA & microRNA. The author has an hindex of 18, co-authored 58 publications receiving 2448 citations. Previous affiliations of Glen M. Borchert include University of Iowa & Florida State University College of Arts and Sciences.

RNA polymerase III transcribes human microRNAs

Abstract: Prior work demonstrates that mammalian microRNA (miRNA or miR) expression requires RNA polymerase II (Pol II). However, the transcriptional requirements of many miRNAs remain untested. Our genomic analysis of miRNAs in the human chromosome 19 miRNA cluster (C19MC) revealed that they are interspersed among Alu repeats. Because Alu transcription occurs through RNA Pol III recruitment, and we found that Alu elements upstream of C19MC miRNAs retain sequences important for Pol III activity, we tested the promoter requirements of C19MC miRNAs. Chromatin immunoprecipitation and cell-free transcription assays showed that Pol III, but not Pol II, is associated with miRNA genomic sequence and sufficient for transcription. Moreover, the mature miRNA sequences of approximately 50 additional human miRNAs lie within Alu and other known repetitive elements. These findings extend the current view of miRNA origins and the transcriptional machinery driving their expression.

The western painted turtle genome, a model for the evolution of extreme physiological adaptations in a slowly evolving lineage

Abstract: Background: We describe the genome of the western painted turtle, Chrysemys picta bellii, one of the most widespread, abundant, and well-studied turtles. We place the genome into a comparative evolutionary context, and focus on genomic features associated with tooth loss, immune function, longevity, sex differentiation and determination, and the species’ physiological capacities to withstand extreme anoxia and tissue freezing. Results: Our phylogenetic analyses confirm that turtles are the sister group to living archosaurs, and demonstrate an extraordinarily slow rate of sequence evolution in the painted turtle. The ability of the painted turtle to withstand complete anoxia and partial freezing appears to be associated with common vertebrate gene networks, and we identify candidate genes for future functional analyses. Tooth loss shares a common pattern of pseudogenization and degradation of tooth-specific genes with birds, although the rate of accumulation of mutations is much slower in the painted turtle. Genes associated with sex differentiation generally reflect phylogeny rather than convergence in sex determination functionality. Among gene families that demonstrate exceptional expansions or show signatures of strong natural selection, immune function and musculoskeletal patterning genes are consistently over-represented. Conclusions: Our comparative genomic analyses indicate that common vertebrate regulatory networks, some of which have analogs in human diseases, are often involved in the western painted turtle’s extraordinary physiological capacities. As these regulatory pathways are analyzed at the functional level, the painted turtle may offer important insights into the management of a number of human health disorders.

Adenosine deamination in human transcripts generates novel microRNA binding sites

Abstract: Animals regulate gene expression at multiple levels, contributing to the complexity of the proteome. Among these regulatory events are post-transcriptional gene silencing, mediated by small non-coding RNAs (e.g. microRNAs), and adenosine-to-inosine (A-to-I) editing, generated by adenosine deaminases that act on double-stranded RNA (ADAR). Recent data suggest that these regulatory processes are connected at a fundamental level. A-to-I editing can affect Drosha processing or directly alter the microRNA (miRNA) sequences responsible for mRNA targeting. Here, we analyzed the previously reported adenosine deaminations occurring in human cDNAs, and asked if there was a relationship between A-to-I editing events in the mRNA 3' untranslated regions (UTRs) and mRNA:miRNA binding. We find significant correlations between A-to-I editing and changes in miRNA complementarities. In all, over 3000 of the 12 723 distinct adenosine deaminations assessed were found to form 7-mer complementarities (known as seed matches) to a subset of human miRNAs. In 200 of the ESTs, we also noted editing within a specific 13 nucleotide motif. Strikingly, deamination of this motif simultaneously creates seed matches to three (otherwise unrelated) miRNAs. Our results suggest the creation of miRNA regulatory sites as a novel function for ADAR activity. Consequently, many miRNA target sites may only be identifiable through examining expressed sequences.

An oxidative DNA “damage” and repair mechanism localized in the VEGF promoter is important for hypoxia-induced VEGF mRNA expression

Abstract: In hypoxia, mitochondria-generated reactive oxygen species not only stimulate accumulation of the transcriptional regulator of hypoxic gene expression, hypoxia inducible factor-1 (Hif-1), but also cause oxidative base modifications in hypoxic response elements (HREs) of hypoxia-inducible genes. When the hypoxia-induced base modifications are suppressed, Hif-1 fails to associate with the HRE of the VEGF promoter, and VEGF mRNA accumulation is blunted. The mechanism linking base modifications to transcription is unknown. Here we determined whether recruitment of base excision DNA repair (BER) enzymes in response to hypoxia-induced promoter modifications was required for transcription complex assembly and VEGF mRNA expression. Using chromatin immunoprecipitation analyses in pulmonary artery endothelial cells, we found that hypoxia-mediated formation of the base oxidation product 8-oxoguanine (8-oxoG) in VEGF HREs was temporally associated with binding of Hif-1α and the BER enzymes 8-oxoguanine glycosylase 1 (Ogg1) and redox effector factor-1 (Ref-1)/apurinic/apyrimidinic endonuclease 1 (Ape1) and introduction of DNA strand breaks. Hif-1α colocalized with HRE sequences harboring Ref-1/Ape1, but not Ogg1. Inhibition of BER by small interfering RNA-mediated reduction in Ogg1 augmented hypoxia-induced 8-oxoG accumulation and attenuated Hif-1α and Ref-1/Ape1 binding to VEGF HRE sequences and blunted VEGF mRNA expression. Chromatin immunoprecipitation-sequence analysis of 8-oxoG distribution in hypoxic pulmonary artery endothelial cells showed that most of the oxidized base was localized to promoters with virtually no overlap between normoxic and hypoxic data sets. Transcription of genes whose promoters lost 8-oxoG during hypoxia was reduced, while those gaining 8-oxoG was elevated. Collectively, these findings suggest that the BER pathway links hypoxia-induced introduction of oxidative DNA modifications in promoters of hypoxia-inducible genes to transcriptional activation.

Burgeoning evidence indicates that microRNAs were initially formed from transposable element sequences.

Abstract: MicroRNAs (miRNAs) constitute a recently discovered class of noncoding RNAs that play key roles in the regulation of gene expression. Despite being only ~20 nucleotides in length, these highly versatile molecules have been shown to play pivotal roles in development, basic cellular metabolism, apoptosis, and disease. While over 24,000 miRNAs have been characterized since they were first isolated in mammals in 2001, the functions of the majority of these miRNAs remain largely undescribed. That said, many now suggest that characterization of the relationships between miRNAs and transposable elements (TEs) can help elucidate miRNA functionality. Strikingly, over 20 publications have now reported the initial formation of thousands of miRNA loci from TE sequences. In this review we chronicle the findings of these reports, discuss the evolution of the field along with future directions, and examine how this information can be used to ascertain insights into miRNA transcriptional regulation and how it can be exploited to facilitate miRNA target prediction.

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Biogenesis of small RNAs in animals.

Abstract: Small RNAs of 20-30 nucleotides can target both chromatin and transcripts, and thereby keep both the genome and the transcriptome under extensive surveillance. Recent progress in high-throughput sequencing has uncovered an astounding landscape of small RNAs in eukaryotic cells. Various small RNAs of distinctive characteristics have been found and can be classified into three classes based on their biogenesis mechanism and the type of Argonaute protein that they are associated with: microRNAs (miRNAs), endogenous small interfering RNAs (endo-siRNAs or esiRNAs) and Piwi-interacting RNAs (piRNAs). This Review summarizes our current knowledge of how these intriguing molecules are generated in animal cells.

Many roads to maturity: microRNA biogenesis pathways and their regulation

Abstract: MicroRNAs are important regulators of gene expression that control both physiological and pathological processes such as development and cancer. Although their mode of action has attracted great attention, the principles governing their expression and activity are only beginning to emerge. Recent studies have introduced a paradigm shift in our understanding of the microRNA biogenesis pathway, which was previously believed to be universal to all microRNAs. Maturation steps specific to individual microRNAs have been uncovered, and these offer a plethora of regulatory options after transcription with multiple proteins affecting microRNA processing efficiency. Here we review the recent advances in knowledge of the microRNA biosynthesis pathways and discuss their impact on post-transcriptional microRNA regulation during tumour development.

Integrative Genomics Viewer

Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.