Reply to “Comment on ‘Near-surface location, geometry, and velocities of the Santa Monica fault zone, Los Angeles, California’ by R. D. Catchings, G. Gandhok, M. R. Goldman, D. Okaya, M. J. Rymer, and G. W. Bawden” by T. L. Pratt and J. F. Dolan

USGS Publications Warehouse

Catchings, Rufus D.; Rymer, Michael J.; Goldman, Mark R.; Bawden, Gerald W.

2010-01-01

In a comment on our 2008 paper (Catchings, Gandhok, et al., 2008) on the Santa Monica fault in Los Angeles, California, Pratt and Dolan (2010) (herein referred to as P&D) cite numerous objections to our work, inferring that our study is flawed. However, as shown in our reply, their objections contradict their own published works, published works of others, and proven seismic methodologies. Rather than responding to each repeated invalid objection, we address their objections by topic in the subsequent sections.In Catchings, Gandhok, et al. (2008), we presented high-resolution seismic-reflection images that showed two near-surface faults in the upper 50 m beneath the grounds of the Wadsworth Veterans Administration Hospital (WVAH). Although P&D suggest we effectively duplicated their seismic acquisition, our survey was not a duplication of their efforts. Rather, we conducted a seismic-imaging survey over a similar profile as Pratt et al. (1998) but used a different data acquisition system and different data processing methods to evaluate methods of seismically imaging blind faults in the wake of the 17 January 1994 M 6.7 Northridge earthquake. We used an acquisition method that provides both tomographic seismic velocities and reflection images. Our combined-data approach allowed for shallower imaging (∼2.5 m minimum) than the ∼20-m minimum of Pratt et al. (1998), clearer images of the fault zone, and more accurate depth determinations (rather than time images). In processing the reflection images, we used prestack depth migration, which is generally accepted as the only proper imaging method for imaging subsurface structures with strong lateral velocity variations (Versteeg, 1993), a condition shown to exist at the WVAH site. We correlated our reflection images with refraction tomography images, borehole lithology, and velocity data, Interferometric Synthetic Aperture Radar images, and changes in groundwater depths. Except for some minor differences, our seismic-reflection images coincide with previously published seismic-reflection images by Dolan and Pratt (1997) and Pratt et al. (1998), and a paleoseismic study by Dolan et al. (2000). Principal differences among our interpretations and those of Pratt et al. (1998) relate to the upper 20 m and the south side of the fault, which Pratt et al. (1998) did not clearly image. In contrast, our seismic images included structures on both sides of the fault zone from about 2.5 m depth to about 100 m depth at WVAH, allowing us to interpret more details.

Observations on the Use of Textbooks in the Teaching of Principles of Economics: A Comment.

ERIC Educational Resources Information Center

Dolan, Edwin G.

1988-01-01

Responding to "Observations on the Use of Textbooks in the Teaching of Principles of Economics," Dolan agrees with Boskin's appraisal of textbooks. Explains why texts share common faults and proposes possible means of alleviating them. Examines five constraints on textbook writers, stating that by changing them, authors can change their…

Mechanisms of Recovering Low Cycle Fatigue Damage in Incoloy 901.

DTIC Science & Technology

1979-01-01

crack growth rate, da/dN, of 0.27 vim/cycle or 1.07 x 10- 4 in./cycle. Macha has determined crack growth rates as a function of AK at 400°F and 6000F...Cleveland, Ohio (1963). 61. T. J. Dolan, "Designing Structures to Resist Low-Cycle Fatigue," Metals Eng. Qtrly 10, 18-25 (November 1970). 62. D. Macha

Dredging Operations Technical Support Program. Long-Term Monitoring of Eleven Corps of Engineers Habitat Development Field Sites Built of Dredged Material, 1974-1987

DTIC Science & Technology

1989-12-01

Craig Seltzer and Joseph Shephard, Norfolk District; Messrs. Rick Medina and Dolan Dunn, Galveston District; Ms. Jody Zaitlin, San Francisco District...Thompson, B. A., and Deegan , L. A. 1984. "The Atchafalaya River Delta: A ’New’ fish Nursery with Recommendations for Management," Proceedings, 10th Annual

European Scientific Notes. Volume 38, Number 3.

DTIC Science & Technology

1984-03-01

abrasive wear studies for a broad range of materials, includ- ing amorphous metals. OCEAN SCIENCES The Geology and Biology of Coral Reefs ...Robert Dolan 133 A meeting of the International Society for Coral Reef Studies focused on the state of the world’s reefs . Of particular concern...were diseases affecting coral reefs . Oil Spills: Can Sonar Help Investigators? ............. Chester McKinney 134 High-resolution, side-scan, bottom

Computational Sensing and in vitro Classification of GMOs and Biomolecular Events

DTIC Science & Technology

2008-12-01

COMPUTATIONAL SENSING AND IN VITRO CLASSIFICATION OF GMOs AND BIOMOLECULAR EVENTS Elebeoba May1∗, Miler T. Lee2†, Patricia Dolan1, Paul Crozier1...modified organisms ( GMOs ) in the pres- ence of non-lethal agents. Using an information and coding- theoretic framework we develop a de novo method for...high through- put screening, distinguishing genetically modified organisms ( GMOs ), molecular computing, differentiating biological mark- ers

ARC-2008-ACD08-0186-005

NASA Image and Video Library

2008-07-30

NASA Ames Robotics Academy Interns at the Lunar Science Institute (LSI) building 17 Interns: David Black, Michael Zwach, Guy Chriqui, Mark Mordarski Jr., Katy Levinson, Daniela Buchman, Scott Strutner, Patrick Crownover, Neil Bhateja, Michael Buchman, John Mueller, Michelle Grau, Ben Silver, Jacques Dolan, Alex Golec Windell Jones, Colin Wilson, Joe DeBlasio, Nick Hayes, Jordan Olive, William Shaw, Ames Education Dept., Mark Leon, Ames Robotics, Josh Weiner, jack Biesiadecki, Andrew Pilloud

Littoral Combat Ship: Is it a Blue-Green Asset?

DTIC Science & Technology

2010-04-02

to Mission Package Inventories , Homeports, and Installation Sites, by Brien Alkire, John ·Birkler, Lisa Dolan, James Dryden, Bryce Mason, Gordon T...Littoral Combat Ship Concept of Operations, V3.1 (February 2003), http:/ /www.global security .org/m ilitary /Library /report/2003/LCSCONO PS. htm# Operatio ...www.proquest.com/. US Navy. Littoral Combat Ships: Relating Performance to Mission Package Inventories , Homeports, and Installation Sites, by Brien Alkire

A melting pot it's not. ACHE study finds healthcare management still dominated by whites, men despite efforts to promote greater diversity.

PubMed

Burda, David

2003-08-11

A study by the American College of Healthcare Executives reveals that efforts to promote racial and gender diversity among the industry's top ranks haven't been as successful as hoped. ACHE President and Chief Executive Officer Thomas Dolan, left, said the results should prompt healthcare executives to analyze what's happening within their own four walls.

Aspects of Information Service Management. Proceedings of the Fall Meeting of the New England On-Line Users Group (Tufts University, November 3, 1978).

ERIC Educational Resources Information Center

New England On-Line Users Group.

The proceedings of this meeting on online service administration comprise the three papers presented: one written by Helen G. Drinan concerning costing and budgeting for online information services; one by Robert McDermand on marketing, publicizing, and other service aspects of online searching; and one by Donna R. Dolan pertaining to the training…

Seismic images and fault relations of the Santa Monica thrust fault, West Los Angeles, California

USGS Publications Warehouse

Catchings, R.D.; Gandhok, G.; Goldman, M.R.; Okaya, D.

2001-01-01

In May 1997, the US Geological Survey (USGS) and the University of Southern California (USC) acquired high-resolution seismic reflection and refraction images on the grounds of the Wadsworth Veterans Administration Hospital (WVAH) in the city of Los Angeles (Fig. 1a,b). The objective of the seismic survey was to better understand the near-surface geometry and faulting characteristics of the Santa Monica fault zone. In this report, we present seismic images, an interpretation of those images, and a comparison of our results with results from studies by Dolan and Pratt (1997), Pratt et al. (1998) and Gibbs et al. (2000). The Santa Monica fault is one of the several northeast-southwest-trending, north-dipping, reverse faults that extend through the Los Angeles metropolitan area (Fig. 1a). Through much of area, the Santa Monica fault trends subparallel to the Hollywood fault, but the two faults apparently join into a single fault zone to the southwest and to the northeast (Dolan et al., 1995). The Santa Monica and Hollywood faults may be part of a larger fault system that extends from the Pacific Ocean to the Transverse Ranges. Crook et al. (1983) refer to this fault system as the Malibu Coast-Santa Monica-Raymond-Cucamonga fault system. They suggest that these faults have not formed a contiguous zone since the Pleistocene and conclude that each of the faults should be treated as a separate fault with respect to seismic hazards. However, Dolan et al. (1995) suggest that the Hollywood and Santa Monica faults are capable of generating Mw 6.8 and Mw 7.0 earthquakes, respectively. Thus, regardless of whether the overall fault system is connected and capable of rupturing in one event, individually, each of the faults present a sizable earthquake hazard to the Los Angeles metropolitan area. If, however, these faults are connected, and they were to rupture along a continuous fault rupture, the resulting hazard would be even greater. Although the Santa Monica fault represents a hazard to millions of people, its lateral extent and rupture history are not well known, due largely to limited knowledge of the fault location, geometry, and relationship to other faults. The Santa Monica fault has been obscured at the surface by alluvium and urbanization. For example, Dolan et al. (1995) could find only one 200-m-long stretch of the Santa Monica fault that was not covered by either streets or buildings. Of the 19-km length onshore section of the Santa Monica fault, its apparent location has been delineated largely on the basis of geomorphic features and oil-well drilling. Seismic imaging efforts, in combination with other investigative methods, may be the best approach in locating and understanding the Santa Monica fault in the Los Angeles region. This investigation and another recent seismic imaging investigation (Pratt et al., 1998) were undertaken to resolve the near-surface location, fault geometry, and faulting relations associated with the Santa Monica fault.

Understanding Culture in the Role of Indigenous Armies

DTIC Science & Technology

2008-03-04

proper conduct and discipline within the organization. Where possible the indigenous face within a community is best. It puts the bulk of... community and tribal leaders. Support of local leaders provides support and adds another key capability to stability operations. “ Indigenous troops act as...St ra te gy R es ea rc h Pr oj ec t UNDERSTANDING CULTURE AND THE USE OF INDIGENOUS ARMIES BY LIEUTENANT COLONEL JOHN P. DOLAN United

CCL3L1-CCR5 Genotype Improves the Assessment of AIDS Risk in HIV-1-Infected Individuals

DTIC Science & Technology

2008-09-08

J. Dolan3,4,5,6*, Sunil K. Ahuja1,2,9* 1 Veterans Administration Research Center for AIDS and HIV-1 Infection, South Texas Veterans Health Care...States of America, 3 Infectious Disease Clinical Research Program, Uniformed Services University, Bethesda, Maryland, United States of America, 4...in Translational Research . Support for the Wilford Hall Medical Center cohort was provided by the Infectious Disease Clinical Research Program (IDCRP

Bioenergetic Defects and Oxidative Damage in Transgenic Mouse Models of Neurodegenerative Disorders

DTIC Science & Technology

2004-05-01

Grafton, S. T., Mazziotta, J. C., Pahl, J. J., St George- Hyslop , P., Neurodegen. 5:27-33. Haines, J. L., Gusella, J., Hoffman, J. M., Baxter, L. R., and 61...another TCA enzyme (Porter Previous studies showed that MPTP and isoquinoline and Bright 1980 ). Systemic administration of 3-NP inhibits derivative...Brouillet E., Ferrante R., Palfi S., Dolan R., Matthews R. T. Porter D. J. T. and Bright H. J. ( 1980 ) 3-Carbanionic substrate analogues and Beal M. F

Measures of Effectiveness for Non-Lethal Weapons: Aligning Behavioral Experiments with Operational Success

DTIC Science & Technology

2015-01-01

the task effectiveness of the NLW, so that the value of the NLW to the warfighter can be extrapolated to other missions with similar tasks. At first...Kenny, J. M., Scholl, D., Murray, B., Farrer, D., Sokolowski, J., Dolan, D., Peters, D., McShea, L., & Finch , K. (2007). Establishing a framework to...3), 452–477. doi:10.1080/14702436.2012.703847 Rahimi, R., Borve, S., & Arnesen, O. H. (2013). Disrupting verbal communication with high-intensity

Supplemental Environmental Assessment of the Ambulatory Care Center at Joint Base Andrews-Naval Air Facility Washington, Maryland

DTIC Science & Technology

2011-06-01

DOLAN, GS-14, USAF Chief, Asset Management Flight MARYLAND DEPARTMENT OF THE ENVIRONMENT MDE Martin O’Malley Governor 1800 Washington Boulevard...t.e.(~;vJ ~-so- ll ( HtfM.;r-\\<.U ) -l. ~- II J~~ Ms. Anne Hodges March 29, 2011 Page Two Again, thank you for giving MDE the opportunity to...Joane D. Mueller MDE Clearinghouse Coordinator Office of Communications Enclosure cc: Bob Rosenbush, State Clearinghouse • Andrews Airforce Base

Numerical Studies of Gravitational Accretion from X-Ray Heated Stellar Winds.

DTIC Science & Technology

1981-12-01

presented by Pietsch (1980), and Dolan (1980). Pietsch found that the 4U1700-37 system exhibits flares in its luminosity of magnitude on the order of 25...by Pietsch et al. (1980) and is summarized in Table 2.1. They found slowly varying X-ray flaring time scales of about 0.5 to 1.0 hour. This flaring...N. 1972, Ap. J., 174, 499. 141 1,4 Petterson, J. 1978, Ap. J., 224, 625. Pietsch , W., Voges, W., Reppin, C., Trumper, J., Kendzierra, E., Staubert, R

The Saint Lawrence River--Past and Present. A Review of Historical Natural Resource Information and Habitat Changes in the International Section of the Saint Lawrence River.

DTIC Science & Technology

1984-04-01

o ° .’o Dixon, S. G. 1914. Journal of the American Medical Association. Dolan, A. 1982. St...rubva red elm x x A75 Table 62 .(continued) Occurrence by hbitat C C-U 0 4J 0 4-) 4- .SU) u- a W1 o Scientific~1 name Comnnae0 A V 0 *U-C CCEA Cannabie ...for space, food and spawning sites. Muskellunge host a number of parasites. Muskie are also subject to growth of cancerous red tumors, which result

Dynamical systems defined on infinite dimensional lie algebras of the ''current algebra'' or ''Kac-Moody'' type

NASA Astrophysics Data System (ADS)

Hermann, Robert

1982-07-01

Recent work by Morrison, Marsden, and Weinstein has drawn attention to the possibility of utilizing the cosymplectic structure of the dual of the Lie algebra of certain infinite dimensional Lie groups to study hydrodynamical and plasma systems. This paper treats certain models arising in elementary particle physics, considered by Lee, Weinberg, and Zumino; Sugawara; Bardacki, Halpern, and Frishman; Hermann; and Dolan. The lie algebras involved are associated with the ''current algebras'' of Gell-Mann. This class of Lie algebras contains certain of the algebras that are called ''Kac-Moody algebras'' in the recent mathematics and mathematical physics literature.

In vitro molecular machine learning algorithm via symmetric internal loops of DNA.

PubMed

Lee, Ji-Hoon; Lee, Seung Hwan; Baek, Christina; Chun, Hyosun; Ryu, Je-Hwan; Kim, Jin-Woo; Deaton, Russell; Zhang, Byoung-Tak

2017-08-01

Programmable biomolecules, such as DNA strands, deoxyribozymes, and restriction enzymes, have been used to solve computational problems, construct large-scale logic circuits, and program simple molecular games. Although studies have shown the potential of molecular computing, the capability of computational learning with DNA molecules, i.e., molecular machine learning, has yet to be experimentally verified. Here, we present a novel molecular learning in vitro model in which symmetric internal loops of double-stranded DNA are exploited to measure the differences between training instances, thus enabling the molecules to learn from small errors. The model was evaluated on a data set of twenty dialogue sentences obtained from the television shows Friends and Prison Break. The wet DNA-computing experiments confirmed that the molecular learning machine was able to generalize the dialogue patterns of each show and successfully identify the show from which the sentences originated. The molecular machine learning model described here opens the way for solving machine learning problems in computer science and biology using in vitro molecular computing with the data encoded in DNA molecules. Copyright © 2017. Published by Elsevier B.V.

DNA targeting of rhinal cortex D2 receptor protein reversibly blocks learning of cues that predict reward.

PubMed

Liu, Zheng; Richmond, Barry J; Murray, Elisabeth A; Saunders, Richard C; Steenrod, Sara; Stubblefield, Barbara K; Montague, Deidra M; Ginns, Edward I

2004-08-17

When schedules of several operant trials must be successfully completed to obtain a reward, monkeys quickly learn to adjust their behavioral performance by using visual cues that signal how many trials have been completed and how many remain in the current schedule. Bilateral rhinal (perirhinal and entorhinal) cortex ablations irreversibly prevent this learning. Here, we apply a recombinant DNA technique to investigate the role of dopamine D2 receptor in rhinal cortex for this type of learning. Rhinal cortex was injected with a DNA construct that significantly decreased D2 receptor ligand binding and temporarily produced the same profound learning deficit seen after ablation. However, unlike after ablation, the D2 receptor-targeted, DNA-treated monkeys recovered cue-related learning after 11-19 weeks. Injecting a DNA construct that decreased N-methyl-d-aspartate but not D2 receptor ligand binding did not interfere with learning associations between the cues and the schedules. A second D2 receptor-targeted DNA treatment administered after either recovery from a first D2 receptor-targeted DNA treatment (one monkey), after N-methyl-d-aspartate receptor-targeted DNA treatment (two monkeys), or after a vector control treatment (one monkey) also induced a learning deficit of similar duration. These results suggest that the D2 receptor in primate rhinal cortex is essential for learning to relate the visual cues to the schedules. The specificity of the receptor manipulation reported here suggests that this approach could be generalized in this or other brain pathways to relate molecular mechanisms to cognitive functions.

DNA targeting of rhinal cortex D2 receptor protein reversibly blocks learning of cues that predict reward

PubMed Central

Liu, Zheng; Richmond, Barry J.; Murray, Elisabeth A.; Saunders, Richard C.; Steenrod, Sara; Stubblefield, Barbara K.; Montague, Deidra M.; Ginns, Edward I.

2004-01-01

When schedules of several operant trials must be successfully completed to obtain a reward, monkeys quickly learn to adjust their behavioral performance by using visual cues that signal how many trials have been completed and how many remain in the current schedule. Bilateral rhinal (perirhinal and entorhinal) cortex ablations irreversibly prevent this learning. Here, we apply a recombinant DNA technique to investigate the role of dopamine D2 receptor in rhinal cortex for this type of learning. Rhinal cortex was injected with a DNA construct that significantly decreased D2 receptor ligand binding and temporarily produced the same profound learning deficit seen after ablation. However, unlike after ablation, the D2 receptor-targeted, DNA-treated monkeys recovered cue-related learning after 11–19 weeks. Injecting a DNA construct that decreased N-methyl-d-aspartate but not D2 receptor ligand binding did not interfere with learning associations between the cues and the schedules. A second D2 receptor-targeted DNA treatment administered after either recovery from a first D2 receptor-targeted DNA treatment (one monkey), after N-methyl-d-aspartate receptor-targeted DNA treatment (two monkeys), or after a vector control treatment (one monkey) also induced a learning deficit of similar duration. These results suggest that the D2 receptor in primate rhinal cortex is essential for learning to relate the visual cues to the schedules. The specificity of the receptor manipulation reported here suggests that this approach could be generalized in this or other brain pathways to relate molecular mechanisms to cognitive functions. PMID:15302926

Working memory involved in predicting future outcomes based on past experiences.

PubMed

Dretsch, Michael N; Tipples, Jason

2008-02-01

Deficits in working memory have been shown to contribute to poor performance on the Iowa Gambling Task [IGT: Bechara, A., & Martin, E.M. (2004). Impaired decision making related to working memory deficits in individuals with substance addictions. Neuropsychology, 18, 152-162]. Similarly, a secondary memory load task has been shown to impair task performance [Hinson, J., Jameson, T. & Whitney, P. (2002). Somatic markers, working memory, and decision making. Cognitive, Affective, & Behavioural Neuroscience, 2, 341-353]. In the present study, we investigate whether the latter findings were due to increased random responding [Franco-Watkins, A. M., Pashler, H., & Rickard, T. C. (2006). Does working memory load lead to greater impulsivity? Commentary on Hinson, Jameson, and Whitney's (2003). Journal of Experimental Psychology: Learning, Memory & Cognition, 32, 443-447]. Participants were tested under Low Working Memory (LWM; n=18) or High Working Memory (HWM; n=17) conditions while performing the Reversed IGT in which punishment was immediate and reward delayed [Bechara, A., Dolan, S., & Hindes, A. (2002). Decision making and addiction (part II): Myopia for the future or hypersensitivity to reward? Neuropsychologia, 40, 1690-1705]. In support of a role for working memory in emotional decision making, compared to the LWM condition, participants in the HWM condition made significantly greater number of disadvantageous selections than that predicted by chance. Performance by the HWM group could not be fully explained by random responding.

Fabrication of Josephson Junction without shadow evaporation

NASA Astrophysics Data System (ADS)

Wu, Xian; Ku, Hsiangsheng; Long, Junling; Pappas, David

We developed a new method of fabricating Josephson Junction (Al/AlOX/Al) without shadow evaporation. Statistics from room temperature junction resistance and measurement of qubits are presented. Unlike the traditional ``Dolan Bridge'' technique, this method requires two individual lithographies and straight evaporations of Al. Argon RF plasma is used to remove native AlOX after the first evaporation, followed by oxidation and second Al evaporation. Junction resistance measured at room temperature shows linear dependence on Pox (oxidation pressure), √{tox} (oxidation time), and inverse proportional to junction area. We have seen 100% yield of qubits made with this method. This method is promising because it eliminates angle dependence during Junction fabrication, facilitates large scale qubits fabrication.

Inhibiting DNA methylation alters olfactory extinction but not acquisition learning in Apis cerana and Apis mellifera.

PubMed

Gong, Zhiwen; Wang, Chao; Nieh, James C; Tan, Ken

2016-07-01

DNA methylation plays a key role in invertebrate acquisition and extinction memory. Honey bees have excellent olfactory learning, but the role of DNA methylation in memory formation has, to date, only been studied in Apis mellifera. We inhibited DNA methylation by inhibiting DNA methyltransferase (DNMT) with zebularine (zeb) and studied the resulting effects upon olfactory acquisition and extinction memory in two honey bee species, Apis cerana and A. mellifera. We used the proboscis extension reflex (PER) assay to measure memory. We provide the first demonstration that DNA methylation is also important in the olfactory extinction learning of A. cerana. DNMT did not reduce acquisition learning in either species. However, zeb bidirectionally and differentially altered extinction learning in both species. In particular, zeb provided 1h before acquisition learning improved extinction memory retention in A. mellifera, but reduced extinction memory retention in A. cerana. The reasons for these differences are unclear, but provide a basis for future studies to explore species-specific differences in the effects of methylation on memory formation. Copyright © 2016 Elsevier Ltd. All rights reserved.

"DNA Re-EvolutioN": A Game for Learning Molecular Genetics and Evolution

ERIC Educational Resources Information Center

Miralles, Laura; Moran, Paloma; Dopico, Eduardo; Garcia-Vazquez, Eva

2013-01-01

Evolution is a main concept in biology, but not many students understand how it works. In this article we introduce the game "DNA Re-EvolutioN" as an active learning tool that uses genetic concepts (DNA structure, transcription and translation, mutations, natural selection, etc.) as playing rules. Students will learn about molecular…

The episodic random utility model unifies time trade-off and discrete choice approaches in health state valuation

PubMed Central

Craig, Benjamin M; Busschbach, Jan JV

2009-01-01

Background To present an episodic random utility model that unifies time trade-off and discrete choice approaches in health state valuation. Methods First, we introduce two alternative random utility models (RUMs) for health preferences: the episodic RUM and the more common instant RUM. For the interpretation of time trade-off (TTO) responses, we show that the episodic model implies a coefficient estimator, and the instant model implies a mean slope estimator. Secondly, we demonstrate these estimators and the differences between the estimates for 42 health states using TTO responses from the seminal Measurement and Valuation in Health (MVH) study conducted in the United Kingdom. Mean slopes are estimates with and without Dolan's transformation of worse-than-death (WTD) responses. Finally, we demonstrate an exploded probit estimator, an extension of the coefficient estimator for discrete choice data that accommodates both TTO and rank responses. Results By construction, mean slopes are less than or equal to coefficients, because slopes are fractions and, therefore, magnify downward errors in WTD responses. The Dolan transformation of WTD responses causes mean slopes to increase in similarity to coefficient estimates, yet they are not equivalent (i.e., absolute mean difference = 0.179). Unlike mean slopes, coefficient estimates demonstrate strong concordance with rank-based predictions (Lin's rho = 0.91). Combining TTO and rank responses under the exploded probit model improves the identification of health state values, decreasing the average width of confidence intervals from 0.057 to 0.041 compared to TTO only results. Conclusion The episodic RUM expands upon the theoretical framework underlying health state valuation and contributes to health econometrics by motivating the selection of coefficient and exploded probit estimators for the analysis of TTO and rank responses. In future MVH surveys, sample size requirements may be reduced through the incorporation of multiple responses under a single estimator. PMID:19144115

Apprenticeship in science research: whom does it serve?

NASA Astrophysics Data System (ADS)

Davies, Paul

2016-12-01

This article advances the thinking of Thompson, Conaway and Dolan's "Undergraduate students' development of social, cultural, and human capital in a network research experience". Set against a background of change in the biosciences, and participation, it firstly explores ideas of what it means to be a scientist, then challenges the current view of the apprenticeship model of career trajectory, before going onto to consider the nature of participation in communities of practice and issues related to underrepresented minority groups in science. Central to this analysis is the place that the notion of habitus plays in thinking about shaping future scientists and the how this can both support, but also suppress, opportunities for individuals through a maintenance of the status quo.

Selective role for DNMT3a in learning and memory.

PubMed

Morris, Michael J; Adachi, Megumi; Na, Elisa S; Monteggia, Lisa M

2014-11-01

Methylation of cytosine nucleotides is governed by DNA methyltransferases (DNMTs) that establish de novo DNA methylation patterns in early embryonic development (e.g., DNMT3a and DNMT3b) or maintain those patterns on hemimethylated DNA in dividing cells (e.g., DNMT1). DNMTs continue to be expressed at high levels in mature neurons, however their impact on neuronal function and behavior are unclear. To address this issue we examined DNMT1 and DNMT3a expression following associative learning. We also generated forebrain specific conditional Dnmt1 or Dnmt3a knockout mice and characterized them in learning and memory paradigms as well as for alterations in long-term potentiation (LTP) and synaptic plasticity. Here, we report that experience in an associative learning task impacts expression of Dnmt3a, but not Dnmt1, in brain areas that mediate learning of this task. We also found that Dnmt3a knockout mice, and not Dnmt1 knockouts have synaptic alterations as well as learning deficits on several associative and episodic memory tasks. These findings indicate that the de novo DNA methylating enzyme DNMT3a in postmitotic neurons is necessary for normal memory formation and its function cannot be substituted by the maintenance DNA methylating enzyme DNMT1. Copyright © 2014 Elsevier Inc. All rights reserved.

Collaborative Learning in Biology: Debating the Ethics of Recombinant DNA Technology.

ERIC Educational Resources Information Center

Anderson, Rodney P.

1998-01-01

Discusses applications of recombinant DNA technology and the controversies surrounding that technique. Provides a cooperative learning project idea that involves teams of students investigating and debating these issues. (DDR)

Involvement of DNA methylation in memory processing in the honey bee.

PubMed

Lockett, Gabrielle A; Helliwell, Paul; Maleszka, Ryszard

2010-08-23

DNA methylation, an important and evolutionarily conserved epigenetic mechanism, is implicated in learning and memory processes in vertebrates, but its role in behaviour in invertebrates is unknown. We examined the role of DNA methylation in memory in the honey bee using an appetitive Pavlovian olfactory discrimination task, and by assessing the expression of DNA methyltransferase3, a key driver of epigenetic reprogramming. Here we report that DNA methyltransferase inhibition reduces acquisition retention and alters the extinction depending on treatment time, and DNA methyltransferase3 is upregulated after training. Our findings add to the understanding of epigenetic mechanisms in learning and memory, extending known roles of DNA methylation to appetitive and extinction memory, and for the first time implicate DNA methylation in memory in invertebrates.

DNA Cryptography and Deep Learning using Genetic Algorithm with NW algorithm for Key Generation.

PubMed

Kalsi, Shruti; Kaur, Harleen; Chang, Victor

2017-12-05

Cryptography is not only a science of applying complex mathematics and logic to design strong methods to hide data called as encryption, but also to retrieve the original data back, called decryption. The purpose of cryptography is to transmit a message between a sender and receiver such that an eavesdropper is unable to comprehend it. To accomplish this, not only we need a strong algorithm, but a strong key and a strong concept for encryption and decryption process. We have introduced a concept of DNA Deep Learning Cryptography which is defined as a technique of concealing data in terms of DNA sequence and deep learning. In the cryptographic technique, each alphabet of a letter is converted into a different combination of the four bases, namely; Adenine (A), Cytosine (C), Guanine (G) and Thymine (T), which make up the human deoxyribonucleic acid (DNA). Actual implementations with the DNA don't exceed laboratory level and are expensive. To bring DNA computing on a digital level, easy and effective algorithms are proposed in this paper. In proposed work we have introduced firstly, a method and its implementation for key generation based on the theory of natural selection using Genetic Algorithm with Needleman-Wunsch (NW) algorithm and Secondly, a method for implementation of encryption and decryption based on DNA computing using biological operations Transcription, Translation, DNA Sequencing and Deep Learning.

Microphysics in West African squall line with an Xband polarimetric radar and an Hydrometeor Identification Scheme: comparison with in situ measurements

NASA Astrophysics Data System (ADS)

Cazenave, F.; Gosset, M.; Kacou, M.; Alcoba, M.; Fontaine, E.

2015-12-01

A better knowledge on the microphysics of tropical continental convective systems is needed in order to improve quantitative precipitation measurements in the Tropics. Satellite passive microwave estimation of tropical rainfall could be improved with a better parameterization of the icy hydrometeors in the Bayesian RAIN estimation algorithm (BRAIN, Viltard et al., 2006) used over continental tropics. To address this important issue specific campaigns that combine aircraft based in situ microphysics probing and polarimetric radar have been organized as part of the CNES/ISRO satellite mission Megha-Tropiques. The first microphysics validation campaign was set up in Niamey in August 2010. The field deployment included the AMMA-CATH 56 rain gages, 3 disdrometers, 2 meteorological radars including the C-band MIT and the Xport X-band dual polarisation radar, and a 4 weeks campaign with the instrumented Falcon 20 from the french operator for environmental research aircrafts equipped with several microphysics probes and the 94Ghz cloud radar RASTA. The objective is to combine scales and methods to converge towards a parameterization of the ice size, mass and density laws inside continental Mesoscale Convective System (MCS). The Particle IDentification algorithm (PID) developed by the Colorado State University (CSU) adapted to the band X by B. Dolan (Dolan et al. 2009) is used to classify seven kind of particles: drizzle or light rain, moderate to heavy rain, wet and dry graupel, wet and dry aggregates and ice crystals. On a limited number of systems, the airborne microphysics sensors provide a detailed in situ reference on the Particle Size Distribution (PSD) that can be compared with the radar PID in the radar pixels located along the flight trajectory. An original approach has been developed for the radar - in situ comparison: it consists in simulating synthetic radar variables from the microphysics probe information and compare the 2 data sets in a common 'radar space'. The consistency between the 2 types of observation is good considering the differences in sampling. The time evolution of the hydrometeor types and their relative proportion in the convective and stratiform regions are analyzed for the 13rd August 2010 MCS.

DNA methylation regulates neurophysiological spatial representation in memory formation

PubMed Central

Roth, Eric D.; Roth, Tania L.; Money, Kelli M.; SenGupta, Sonda; Eason, Dawn E.; Sweatt, J. David

2015-01-01

Epigenetic mechanisms including altered DNA methylation are critical for altered gene transcription subserving synaptic plasticity and the retention of learned behavior. Here we tested the idea that one role for activity-dependent altered DNA methylation is stabilization of cognition-associated hippocampal place cell firing in response to novel place learning. We observed that a behavioral protocol (spatial exploration of a novel environment) known to induce hippocampal place cell remapping resulted in alterations of hippocampal Bdnf DNA methylation. Further studies using neurophysiological in vivo single unit recordings revealed that pharmacological manipulations of DNA methylation decreased long-term but not short-term place field stability. Together our data highlight a role for DNA methylation in regulating neurophysiological spatial representation and memory formation. PMID:25960947

Generalized query-based active learning to identify differentially methylated regions in DNA.

PubMed

Haque, Md Muksitul; Holder, Lawrence B; Skinner, Michael K; Cook, Diane J

2013-01-01

Active learning is a supervised learning technique that reduces the number of examples required for building a successful classifier, because it can choose the data it learns from. This technique holds promise for many biological domains in which classified examples are expensive and time-consuming to obtain. Most traditional active learning methods ask very specific queries to the Oracle (e.g., a human expert) to label an unlabeled example. The example may consist of numerous features, many of which are irrelevant. Removing such features will create a shorter query with only relevant features, and it will be easier for the Oracle to answer. We propose a generalized query-based active learning (GQAL) approach that constructs generalized queries based on multiple instances. By constructing appropriately generalized queries, we can achieve higher accuracy compared to traditional active learning methods. We apply our active learning method to find differentially DNA methylated regions (DMRs). DMRs are DNA locations in the genome that are known to be involved in tissue differentiation, epigenetic regulation, and disease. We also apply our method on 13 other data sets and show that our method is better than another popular active learning technique.

Cortical DNA methylation maintains remote memory.

PubMed

Miller, Courtney A; Gavin, Cristin F; White, Jason A; Parrish, R Ryley; Honasoge, Avinash; Yancey, Christopher R; Rivera, Ivonne M; Rubio, María D; Rumbaugh, Gavin; Sweatt, J David

2010-06-01

A behavioral memory's lifetime represents multiple molecular lifetimes, suggesting the necessity for a self-perpetuating signal. One candidate is DNA methylation, a transcriptional repression mechanism that maintains cellular memory throughout development. We found that persistent, gene-specific cortical hypermethylation was induced in rats by a single, hippocampus-dependent associative learning experience and pharmacologic inhibition of methylation 1 month after learning disrupted remote memory. We propose that the adult brain utilizes DNA methylation to preserve long-lasting memories.

Methionine increases BDNF DNA methylation and improves memory in epilepsy.

PubMed

Parrish, R Ryley; Buckingham, Susan C; Mascia, Katherine L; Johnson, Jarvis J; Matyjasik, Michal M; Lockhart, Roxanne M; Lubin, Farah D

2015-04-01

Temporal lobe epilepsy (TLE) patients exhibit signs of memory impairments even when seizures are pharmacologically controlled. Surprisingly, the underlying molecular mechanisms involved in TLE-associated memory impairments remain elusive. Memory consolidation requires epigenetic transcriptional regulation of genes in the hippocampus; therefore, we aimed to determine how epigenetic DNA methylation mechanisms affect learning-induced transcription of memory-permissive genes in the epileptic hippocampus. Using the kainate rodent model of TLE and focusing on the brain-derived neurotrophic factor (Bdnf) gene as a candidate of DNA methylation-mediated transcription, we analyzed DNA methylation levels in epileptic rats following learning. After detection of aberrant DNA methylation at the Bdnf gene, we investigated functional effects of altered DNA methylation on hippocampus-dependent memory formation in our TLE rodent model. We found that behaviorally driven BdnfDNA methylation was associated with hippocampus-dependent memory deficits. Bisulfite sequencing revealed that decreased BdnfDNA methylation levels strongly correlated with abnormally high levels of BdnfmRNA in the epileptic hippocampus during memory consolidation. Methyl supplementation via methionine (Met) increased BdnfDNA methylation and reduced BdnfmRNA levels in the epileptic hippocampus during memory consolidation. Met administration reduced interictal spike activity, increased theta rhythm power, and reversed memory deficits in epileptic animals. The rescue effect of Met treatment on learning-induced BdnfDNA methylation, Bdnf gene expression, and hippocampus-dependent memory, were attenuated by DNA methyltransferase blockade. Our findings suggest that manipulation of DNA methylation in the epileptic hippocampus should be considered as a viable treatment option to ameliorate memory impairments associated with TLE.

DNA Re-EvolutioN: a game for learning molecular genetics and evolution.

PubMed

Miralles, Laura; Moran, Paloma; Dopico, Eduardo; Garcia-Vazquez, Eva

2013-01-01

Evolution is a main concept in biology, but not many students understand how it works. In this article we introduce the game DNA Re-EvolutioN as an active learning tool that uses genetic concepts (DNA structure, transcription and translation, mutations, natural selection, etc.) as playing rules. Students will learn about molecular evolution while playing a game that mixes up theory and entertainment. The game can be easily adapted to different educational levels. The main goal of this play is to arrive at the end of the game with the longest protein. Students play with pawns and dices, a board containing hypothetical events (mutations, selection) that happen to molecules, "Evolution cards" with indications for DNA mutations, prototypes of a DNA and a mRNA chain with colored "nucleotides" (plasticine balls), and small pieces simulating t-RNA with aminoacids that will serve to construct a "protein" based on the DNA chain. Students will understand how changes in DNA affect the final protein product and may be subjected to positive or negative selection, using a didactic tool funnier than classical theory lectures and easier than molecular laboratory experiments: a flexible and feasible game to learn and enjoy molecular evolution at no-cost. The game was tested by majors and non-majors in genetics from 13 different countries and evaluated with pre- and post-tests obtaining very positive results. © 2013 by The International Union of Biochemistry and Molecular Biology.

Experience-Dependent Epigenomic Reorganization in the Hippocampus

ERIC Educational Resources Information Center

Duke, Corey G.; Kennedy, Andrew J.; Gavin, Cristin F.; Day, Jeremy J.; Sweatt, J. David

2017-01-01

Using a hippocampus-dependent contextual threat learning and memory task, we report widespread, coordinated DNA methylation changes in CA1 hippocampus of Sprague-Dawley rats specific to threat learning at genes involved in synaptic transmission. Experience-dependent alternations in gene expression and DNA methylation were observed as early as 1 h…

A Collaborative, Investigative Recombinant DNA Technology Course with Laboratory

ERIC Educational Resources Information Center

Pezzementi, Leo; Johnson, Joy F.

2002-01-01

A recombinant DNA technology course was designed to promote contextual, collaborative, inquiry-based learning of science where students learn from one another and have a sense of ownership of their education. The class stressed group presentations and critical reading and discussion of scientific articles. The laboratory consisted of two research…

Response demands and the recruitment of heuristic strategies in syllogistic reasoning.

PubMed

Reverberi, Carlo; Rusconi, Patrice; Paulesu, Eraldo; Cherubini, Paolo

2009-03-01

Two experiments investigated whether dealing with a homogeneous subset of syllogisms with time-constrained responses encouraged participants to develop and use heuristics for abstract (Experiment 1) and thematic (Experiment 2) syllogisms. An atmosphere-based heuristic accounted for most responses with both abstract and thematic syllogisms. With thematic syllogisms, a weaker effect of a belief heuristic was also observed, mainly where the correct response was inconsistent with the atmosphere of the premises. Analytic processes appear to have played little role in the time-constrained condition, whereas their involvement increased in a self-paced, unconstrained condition. From a dual-process perspective, the results further specify how task demands affect the recruitment of heuristic and analytic systems of reasoning. Because the syllogisms and experimental procedure were the same as those used in a previous neuroimaging study by Goel, Buchel, Frith, and Dolan (2000), the result also deepen our understanding of the cognitive processes investigated by that study.

A default Bayesian hypothesis test for mediation.

PubMed

Nuijten, Michèle B; Wetzels, Ruud; Matzke, Dora; Dolan, Conor V; Wagenmakers, Eric-Jan

2015-03-01

In order to quantify the relationship between multiple variables, researchers often carry out a mediation analysis. In such an analysis, a mediator (e.g., knowledge of a healthy diet) transmits the effect from an independent variable (e.g., classroom instruction on a healthy diet) to a dependent variable (e.g., consumption of fruits and vegetables). Almost all mediation analyses in psychology use frequentist estimation and hypothesis-testing techniques. A recent exception is Yuan and MacKinnon (Psychological Methods, 14, 301-322, 2009), who outlined a Bayesian parameter estimation procedure for mediation analysis. Here we complete the Bayesian alternative to frequentist mediation analysis by specifying a default Bayesian hypothesis test based on the Jeffreys-Zellner-Siow approach. We further extend this default Bayesian test by allowing a comparison to directional or one-sided alternatives, using Markov chain Monte Carlo techniques implemented in JAGS. All Bayesian tests are implemented in the R package BayesMed (Nuijten, Wetzels, Matzke, Dolan, & Wagenmakers, 2014).

The DNA Triangle and Its Application to Learning Meiosis

ERIC Educational Resources Information Center

Wright, L. Kate; Catavero, Christina M.; Newman, Dina L.

2017-01-01

Although instruction on meiosis is repeated many times during the undergraduate curriculum, many students show poor comprehension even as upper-level biology majors. We propose that the difficulty lies in the complexity of understanding DNA, which we explain through a new model, the DNA triangle. The "DNA triangle" integrates three…

Affordable Hands-On DNA Sequencing and Genotyping: An Exercise for Teaching DNA Analysis to Undergraduates

ERIC Educational Resources Information Center

Shah, Kushani; Thomas, Shelby; Stein, Arnold

2013-01-01

In this report, we describe a 5-week laboratory exercise for undergraduate biology and biochemistry students in which students learn to sequence DNA and to genotype their DNA for selected single nucleotide polymorphisms (SNPs). Students use miniaturized DNA sequencing gels that require approximately 8 min to run. The students perform G, A, T, C…

DNA Precursor Metabolism and Mitochondrial Genome Stability

DTIC Science & Technology

2003-04-01

mitochondrial DNA replication , to learn how the pool sizes are regulated, and to understand how perturbations of normal dNTP metabolism within the...mitochondria raises the possibility, however unlikely, that it is serving a function in addition to its role in DNA replication . The literature on non-DNA...is below since many authors do not follow the 200 word limit 14. SUBJECT TERMS Mitochondria, Genome stability, DNA precursors, Mitochondrial DNA

The DNA Triangle and Its Application to Learning Meiosis

PubMed Central

Wright, L. Kate; Catavero, Christina M.; Newman, Dina L.

2017-01-01

Although instruction on meiosis is repeated many times during the undergraduate curriculum, many students show poor comprehension even as upper-level biology majors. We propose that the difficulty lies in the complexity of understanding DNA, which we explain through a new model, the DNA triangle. The DNA triangle integrates three distinct scales at which one can think about DNA: chromosomal, molecular, and informational. Through analysis of interview and survey data from biology faculty and students through the lens of the DNA triangle, we illustrate important differences in how novices and experts are able to explain the concepts of ploidy, homology, and mechanism of homologous pairing. Similarly, analysis of passages from 16 different biology textbooks shows a large divide between introductory and advanced material, with introductory books omitting explanations of meiosis-linked concepts at the molecular level of DNA. Finally, backed by textbook findings and feedback from biology experts, we show that the DNA triangle can be applied to teaching and learning meiosis. By applying the DNA triangle to topics on meiosis we present a new framework for educators and researchers that ties concepts of ploidy, homology, and mechanism of homologous pairing to knowledge about DNA on the chromosomal, molecular, and informational levels. PMID:28798212

enDNA-Prot: identification of DNA-binding proteins by applying ensemble learning.

PubMed

Xu, Ruifeng; Zhou, Jiyun; Liu, Bin; Yao, Lin; He, Yulan; Zou, Quan; Wang, Xiaolong

2014-01-01

DNA-binding proteins are crucial for various cellular processes, such as recognition of specific nucleotide, regulation of transcription, and regulation of gene expression. Developing an effective model for identifying DNA-binding proteins is an urgent research problem. Up to now, many methods have been proposed, but most of them focus on only one classifier and cannot make full use of the large number of negative samples to improve predicting performance. This study proposed a predictor called enDNA-Prot for DNA-binding protein identification by employing the ensemble learning technique. Experiential results showed that enDNA-Prot was comparable with DNA-Prot and outperformed DNAbinder and iDNA-Prot with performance improvement in the range of 3.97-9.52% in ACC and 0.08-0.19 in MCC. Furthermore, when the benchmark dataset was expanded with negative samples, the performance of enDNA-Prot outperformed the three existing methods by 2.83-16.63% in terms of ACC and 0.02-0.16 in terms of MCC. It indicated that enDNA-Prot is an effective method for DNA-binding protein identification and expanding training dataset with negative samples can improve its performance. For the convenience of the vast majority of experimental scientists, we developed a user-friendly web-server for enDNA-Prot which is freely accessible to the public.

A DNA-based pattern classifier with in vitro learning and associative recall for genomic characterization and biosensing without explicit sequence knowledge.

PubMed

Lee, Ju Seok; Chen, Junghuei; Deaton, Russell; Kim, Jin-Woo

2014-01-01

Genetic material extracted from in situ microbial communities has high promise as an indicator of biological system status. However, the challenge is to access genomic information from all organisms at the population or community scale to monitor the biosystem's state. Hence, there is a need for a better diagnostic tool that provides a holistic view of a biosystem's genomic status. Here, we introduce an in vitro methodology for genomic pattern classification of biological samples that taps large amounts of genetic information from all genes present and uses that information to detect changes in genomic patterns and classify them. We developed a biosensing protocol, termed Biological Memory, that has in vitro computational capabilities to "learn" and "store" genomic sequence information directly from genomic samples without knowledge of their explicit sequences, and that discovers differences in vitro between previously unknown inputs and learned memory molecules. The Memory protocol was designed and optimized based upon (1) common in vitro recombinant DNA operations using 20-base random probes, including polymerization, nuclease digestion, and magnetic bead separation, to capture a snapshot of the genomic state of a biological sample as a DNA memory and (2) the thermal stability of DNA duplexes between new input and the memory to detect similarities and differences. For efficient read out, a microarray was used as an output method. When the microarray-based Memory protocol was implemented to test its capability and sensitivity using genomic DNA from two model bacterial strains, i.e., Escherichia coli K12 and Bacillus subtilis, results indicate that the Memory protocol can "learn" input DNA, "recall" similar DNA, differentiate between dissimilar DNA, and detect relatively small concentration differences in samples. This study demonstrated not only the in vitro information processing capabilities of DNA, but also its promise as a genomic pattern classifier that could access information from all organisms in a biological system without explicit genomic information. The Memory protocol has high potential for many applications, including in situ biomonitoring of ecosystems, screening for diseases, biosensing of pathological features in water and food supplies, and non-biological information processing of memory devices, among many.

EL_PSSM-RT: DNA-binding residue prediction by integrating ensemble learning with PSSM Relation Transformation.

PubMed

Zhou, Jiyun; Lu, Qin; Xu, Ruifeng; He, Yulan; Wang, Hongpeng

2017-08-29

Prediction of DNA-binding residue is important for understanding the protein-DNA recognition mechanism. Many computational methods have been proposed for the prediction, but most of them do not consider the relationships of evolutionary information between residues. In this paper, we first propose a novel residue encoding method, referred to as the Position Specific Score Matrix (PSSM) Relation Transformation (PSSM-RT), to encode residues by utilizing the relationships of evolutionary information between residues. PDNA-62 and PDNA-224 are used to evaluate PSSM-RT and two existing PSSM encoding methods by five-fold cross-validation. Performance evaluations indicate that PSSM-RT is more effective than previous methods. This validates the point that the relationship of evolutionary information between residues is indeed useful in DNA-binding residue prediction. An ensemble learning classifier (EL_PSSM-RT) is also proposed by combining ensemble learning model and PSSM-RT to better handle the imbalance between binding and non-binding residues in datasets. EL_PSSM-RT is evaluated by five-fold cross-validation using PDNA-62 and PDNA-224 as well as two independent datasets TS-72 and TS-61. Performance comparisons with existing predictors on the four datasets demonstrate that EL_PSSM-RT is the best-performing method among all the predicting methods with improvement between 0.02-0.07 for MCC, 4.18-21.47% for ST and 0.013-0.131 for AUC. Furthermore, we analyze the importance of the pair-relationships extracted by PSSM-RT and the results validates the usefulness of PSSM-RT for encoding DNA-binding residues. We propose a novel prediction method for the prediction of DNA-binding residue with the inclusion of relationship of evolutionary information and ensemble learning. Performance evaluation shows that the relationship of evolutionary information between residues is indeed useful in DNA-binding residue prediction and ensemble learning can be used to address the data imbalance issue between binding and non-binding residues. A web service of EL_PSSM-RT ( http://hlt.hitsz.edu.cn:8080/PSSM-RT_SVM/ ) is provided for free access to the biological research community.

Epigenetic regulation of BDNF gene transcription in the consolidation of fear memory.

PubMed

Lubin, Farah D; Roth, Tania L; Sweatt, J David

2008-10-15

Long-term memory formation requires selective changes in gene expression. Here, we determined the contribution of chromatin remodeling to learning-induced changes in brain-derived neurotrophic factor (bdnf) gene expression in the adult hippocampus. Contextual fear learning induced differential regulation of exon-specific bdnf mRNAs (I, IV, VI, IX) that was associated with changes in bdnf DNA methylation and altered local chromatin structure. Infusions of zebularine (a DNA methyltransferase inhibitor) significantly altered bdnf DNA methylation and triggered changes in exon-specific bdnf mRNA levels, indicating that altered DNA methylation is sufficient to drive differential bdnf transcript regulation in the hippocampus. In addition, NMDA receptor blockade prevented memory-associated alterations in bdnf DNA methylation, resulting in a block of altered bdnf gene expression in hippocampus and a deficit in memory formation. These results suggest epigenetic modification of the bdnf gene as a mechanism for isoform-specific gene readout during memory consolidation.

Solving the Curriculum Sequencing Problem with DNA Computing Approach

ERIC Educational Resources Information Center

Debbah, Amina; Ben Ali, Yamina Mohamed

2014-01-01

In the e-learning systems, a learning path is known as a sequence of learning materials linked to each others to help learners achieving their learning goals. As it is impossible to have the same learning path that suits different learners, the Curriculum Sequencing problem (CS) consists of the generation of a personalized learning path for each…

Identification of DNA-binding proteins by combining auto-cross covariance transformation and ensemble learning.

PubMed

Liu, Bin; Wang, Shanyi; Dong, Qiwen; Li, Shumin; Liu, Xuan

2016-04-20

DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. With the rapid development of next generation of sequencing technique, the number of protein sequences is unprecedentedly increasing. Thus it is necessary to develop computational methods to identify the DNA-binding proteins only based on the protein sequence information. In this study, a novel method called iDNA-KACC is presented, which combines the Support Vector Machine (SVM) and the auto-cross covariance transformation. The protein sequences are first converted into profile-based protein representation, and then converted into a series of fixed-length vectors by the auto-cross covariance transformation with Kmer composition. The sequence order effect can be effectively captured by this scheme. These vectors are then fed into Support Vector Machine (SVM) to discriminate the DNA-binding proteins from the non DNA-binding ones. iDNA-KACC achieves an overall accuracy of 75.16% and Matthew correlation coefficient of 0.5 by a rigorous jackknife test. Its performance is further improved by employing an ensemble learning approach, and the improved predictor is called iDNA-KACC-EL. Experimental results on an independent dataset shows that iDNA-KACC-EL outperforms all the other state-of-the-art predictors, indicating that it would be a useful computational tool for DNA binding protein identification. .

DNA Methylation Adjusts the Specificity of Memories Depending on the Learning Context and Promotes Relearning in Honeybees

PubMed Central

Biergans, Stephanie D.; Claudianos, Charles; Reinhard, Judith; Galizia, C. G.

2016-01-01

The activity of the epigenetic writers DNA methyltransferases (Dnmts) after olfactory reward conditioning is important for both stimulus-specific long-term memory (LTM) formation and extinction. It, however, remains unknown which components of memory formation Dnmts regulate (e.g., associative vs. non-associative) and in what context (e.g., varying training conditions). Here, we address these aspects in order to clarify the role of Dnmt-mediated DNA methylation in memory formation. We used a pharmacological Dnmt inhibitor and classical appetitive conditioning in the honeybee Apis mellifera, a well characterized model for classical conditioning. We quantified the effect of DNA methylation on naïve odor and sugar responses, and on responses following olfactory reward conditioning. We show that (1) Dnmts do not influence naïve odor or sugar responses, (2) Dnmts do not affect the learning of new stimuli, but (3) Dnmts influence odor-coding, i.e., ‘correct’ (stimulus-specific) LTM formation. Particularly, Dnmts reduce memory specificity when experience is low (one-trial training), and increase memory specificity when experience is high (multiple-trial training), generating an ecologically more useful response to learning. (4) In reversal learning conditions, Dnmts are involved in regulating both excitatory (re-acquisition) and inhibitory (forgetting) processes. PMID:27672359

DNA Methylation Adjusts the Specificity of Memories Depending on the Learning Context and Promotes Relearning in Honeybees.

PubMed

Biergans, Stephanie D; Claudianos, Charles; Reinhard, Judith; Galizia, C G

2016-01-01

The activity of the epigenetic writers DNA methyltransferases (Dnmts) after olfactory reward conditioning is important for both stimulus-specific long-term memory (LTM) formation and extinction. It, however, remains unknown which components of memory formation Dnmts regulate (e.g., associative vs. non-associative) and in what context (e.g., varying training conditions). Here, we address these aspects in order to clarify the role of Dnmt-mediated DNA methylation in memory formation. We used a pharmacological Dnmt inhibitor and classical appetitive conditioning in the honeybee Apis mellifera, a well characterized model for classical conditioning. We quantified the effect of DNA methylation on naïve odor and sugar responses, and on responses following olfactory reward conditioning. We show that (1) Dnmts do not influence naïve odor or sugar responses, (2) Dnmts do not affect the learning of new stimuli, but (3) Dnmts influence odor-coding, i.e., 'correct' (stimulus-specific) LTM formation. Particularly, Dnmts reduce memory specificity when experience is low (one-trial training), and increase memory specificity when experience is high (multiple-trial training), generating an ecologically more useful response to learning. (4) In reversal learning conditions, Dnmts are involved in regulating both excitatory (re-acquisition) and inhibitory (forgetting) processes.

Direct-to-consumer DNA testing: the fallout for individuals and their families unexpectedly learning of their donor conception origins.

PubMed

Crawshaw, Marilyn

2017-07-11

Increasing numbers of donor-conceived individuals (and/or parents) are seeking individuals genetically related through donor conception. One route is through 'direct-to-consumer' (DTC) DNA testing, prompting calls for fertility services to alert donors and prospective parents to the increasing unsustainability of anonymity and secrecy. The complexity of interpreting DNA results in this context has also been discussed, including their lack of absolute certainty, as has the need for professional and peer support. This commentary highlights a different 'threat', from individuals learning of their donor-conception origins through the use of such tests by themselves or relatives for such purposes as genealogy or health checks. It illustrates the personal complexities faced by three older women and their families on learning not only of their genetic relationship to each other but also to 15 more donor-related siblings. DTC DNA services are a growing feature of modern life. This commentary raises ethical questions about their responsibilities towards those inadvertently learning of donor conception origins and the responsibilities of fertility services to inform prospective parents and donors of this new phenomenon. Considerations of how and when parents should tell their children of their donor-conception origins here instead become how and when children should inform their parents.

First demonstration of olfactory learning and long term memory in honey bee queens.

PubMed

Gong, Zhiwen; Tan, Ken; Nieh, James C

2018-05-18

As the primary source of colony reproduction, social insect queens play a vital role. However, the cognitive abilities of queens are not well understood, although queen learning and memory are essential in multiple species such as honey bees, in which virgin queens must leave the nest and then successful learn to navigate back over repeated nuptial flights. Honey bee queen learning has never been previously demonstrated. We therefore tested olfactory learning in queens and workers and examined the role of DNA methylation, which plays a key role in long term memory formation. We provide the first evidence that honey bee queens have excellent learning and memory. The proportion of honey bee queens that exhibited learning was 5-fold higher than workers at every tested age and, for memory, 4-fold higher than workers at a very young age. DNA methylation may play a key role in this queen memory because queens exhibiting remote memory had a more consistent elevation in Dnmt3 gene expression as compared to workers. Both castes also showed excellent remote memory (7 day memory), which was reduced by 14-20% by the DNA methylation inhibitor, zebularine. Given that queens live about 10-fold longer than workers, these results suggest that queens can serve as an excellently long-term reservoir of colony memory. © 2018. Published by The Company of Biologists Ltd.

What Is Huntington Disease?

MedlinePlus

... have it? For more information... Acknowledgments Concept 15 : DNA and proteins are key molecules of the cell nucleus. Learn the basic chemistry of DNA and proteins. Concept 27 : Mutations are changes in ...

What Is Phenylketonuria (PKU)?

MedlinePlus

... have it? For more information... Acknowledgments Concept 15 : DNA and proteins are key molecules of the cell nucleus. Learn the basic chemistry of DNA and proteins. Concept 27 : Mutations are changes in ...

PACE: Probabilistic Assessment for Contributor Estimation- A machine learning-based assessment of the number of contributors in DNA mixtures.

PubMed

Marciano, Michael A; Adelman, Jonathan D

2017-03-01

The deconvolution of DNA mixtures remains one of the most critical challenges in the field of forensic DNA analysis. In addition, of all the data features required to perform such deconvolution, the number of contributors in the sample is widely considered the most important, and, if incorrectly chosen, the most likely to negatively influence the mixture interpretation of a DNA profile. Unfortunately, most current approaches to mixture deconvolution require the assumption that the number of contributors is known by the analyst, an assumption that can prove to be especially faulty when faced with increasingly complex mixtures of 3 or more contributors. In this study, we propose a probabilistic approach for estimating the number of contributors in a DNA mixture that leverages the strengths of machine learning. To assess this approach, we compare classification performances of six machine learning algorithms and evaluate the model from the top-performing algorithm against the current state of the art in the field of contributor number classification. Overall results show over 98% accuracy in identifying the number of contributors in a DNA mixture of up to 4 contributors. Comparative results showed 3-person mixtures had a classification accuracy improvement of over 6% compared to the current best-in-field methodology, and that 4-person mixtures had a classification accuracy improvement of over 20%. The Probabilistic Assessment for Contributor Estimation (PACE) also accomplishes classification of mixtures of up to 4 contributors in less than 1s using a standard laptop or desktop computer. Considering the high classification accuracy rates, as well as the significant time commitment required by the current state of the art model versus seconds required by a machine learning-derived model, the approach described herein provides a promising means of estimating the number of contributors and, subsequently, will lead to improved DNA mixture interpretation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

MutSα's Multi-Domain Allosteric Response to Three DNA Damage Types Revealed by Machine Learning

NASA Astrophysics Data System (ADS)

Melvin, Ryan L.; Thompson, William G.; Godwin, Ryan C.; Gmeiner, William H.; Salsbury, Freddie R.

2017-03-01

MutSalpha is a key component in the mismatch repair (MMR) pathway. This protein is responsible for initiating the signaling pathways for DNA repair or cell death. Herein we investigate this heterodimer’s post-recognition, post-binding response to three types of DNA damage involving cytotoxic, anti-cancer agents - carboplatin, cisplatin, and FdU. Through a combination of supervised and unsupervised machine learning techniques along with more traditional structural and kinetic analysis applied to all-atom molecular dynamics (MD) calculations, we predict that MutSalpha has a distinct response to each of the three damage types. Via a binary classification tree (a supervised machine learning technique), we identify key hydrogen bond motifs unique to each type of damage and suggest residues for experimental mutation studies. Through a combination of a recently developed clustering (unsupervised learning) algorithm, RMSF calculations, PCA, and correlated motions we predict that each type of damage causes MutS↵to explore a specific region of conformation space. Detailed analysis suggests a short range effect for carboplatin - primarily altering the structures and kinetics of residues within 10 angstroms of the damaged DNA - and distinct longer-range effects for cisplatin and FdU. In our simulations, we also observe that a key phenylalanine residue - known to stack with a mismatched or unmatched bases in MMR - stacks with the base complementary to the damaged base in 88.61% of MD frames containing carboplatinated DNA. Similarly, this Phe71 stacks with the base complementary to damage in 91.73% of frames with cisplatinated DNA. This residue, however, stacks with the damaged base itself in 62.18% of trajectory frames with FdU-substituted DNA and has no stacking interaction at all in 30.72% of these frames. Each drug investigated here induces a unique perturbation in the MutS↵complex, indicating the possibility of a distinct signaling event and specific repair or death pathway (or set of pathways) for a given type of damage.

Recombinant DNA for Teachers.

ERIC Educational Resources Information Center

Duvall, James G., III

1992-01-01

A science teacher describes his experience at a workshop to learn to teach the Cold Spring Harbor DNA Science Laboratory Protocols. These protocols lead students through processes for taking E. coli cells and transforming them into a new antibiotic resistant strain. The workshop featured discussions of the role of DNA recombinant technology in…

Visualising DNA in Classrooms Using Nile Blue

ERIC Educational Resources Information Center

Milne, Christine; Roche, Scott; McKay, David

2008-01-01

Giving students the opportunity to extract, manipulate and visualise DNA molecules enhances a constructivist approach to learning about modern techniques in biology and biotechnology Visualisation usually requires agarose gel electrophoresis and staining. In this article, we report on an alternative DNA stain, Nile Blue A, that may be used in the…

What Is Sickle Cell Disease?

MedlinePlus

... have it? For more information... Acknowledgments Concept 15 : DNA and proteins are key molecules of the cell nucleus. Learn the basic chemistry of DNA and proteins. Concept 27 : Mutations are changes in ...

Adaptive scaling of reward in episodic memory: a replication study.

PubMed

Mason, Alice; Ludwig, Casimir; Farrell, Simon

2017-11-01

Reward is thought to enhance episodic memory formation via dopaminergic consolidation. Bunzeck, Dayan, Dolan, and Duzel [(2010). A common mechanism for adaptive scaling of reward and novelty. Human Brain Mapping, 31, 1380-1394] provided functional magnetic resonance imaging (fMRI) and behavioural evidence that reward and episodic memory systems are sensitive to the contextual value of a reward-whether it is relatively higher or lower-as opposed to absolute value or prediction error. We carried out a direct replication of their behavioural study and did not replicate their finding that memory performance associated with reward follows this pattern of adaptive scaling. An effect of reward outcome was in the opposite direction to that in the original study, with lower reward outcomes leading to better memory than higher outcomes. There was a marginal effect of reward context, suggesting that expected value affected memory performance. We discuss the robustness of the reward memory relationship to variations in reward context, and whether other reward-related factors have a more reliable influence on episodic memory.

DNA Barcoding and PBL in an Australian Postsecondary College

ERIC Educational Resources Information Center

Cross, Joseph; Garard, Helen; Currie, Tina

2018-01-01

DNA barcoding is increasingly being introduced into biological science educational curricula worldwide. The technique has a number of features that make it ideal for science curricula and particularly for Project-Based Learning (PBL). This report outlines the development of a DNA barcoding project in an Australian TAFE college, which also combined…

Supervised DNA Barcodes species classification: analysis, comparisons and results

PubMed Central

2014-01-01

Background Specific fragments, coming from short portions of DNA (e.g., mitochondrial, nuclear, and plastid sequences), have been defined as DNA Barcode and can be used as markers for organisms of the main life kingdoms. Species classification with DNA Barcode sequences has been proven effective on different organisms. Indeed, specific gene regions have been identified as Barcode: COI in animals, rbcL and matK in plants, and ITS in fungi. The classification problem assigns an unknown specimen to a known species by analyzing its Barcode. This task has to be supported with reliable methods and algorithms. Methods In this work the efficacy of supervised machine learning methods to classify species with DNA Barcode sequences is shown. The Weka software suite, which includes a collection of supervised classification methods, is adopted to address the task of DNA Barcode analysis. Classifier families are tested on synthetic and empirical datasets belonging to the animal, fungus, and plant kingdoms. In particular, the function-based method Support Vector Machines (SVM), the rule-based RIPPER, the decision tree C4.5, and the Naïve Bayes method are considered. Additionally, the classification results are compared with respect to ad-hoc and well-established DNA Barcode classification methods. Results A software that converts the DNA Barcode FASTA sequences to the Weka format is released, to adapt different input formats and to allow the execution of the classification procedure. The analysis of results on synthetic and real datasets shows that SVM and Naïve Bayes outperform on average the other considered classifiers, although they do not provide a human interpretable classification model. Rule-based methods have slightly inferior classification performances, but deliver the species specific positions and nucleotide assignments. On synthetic data the supervised machine learning methods obtain superior classification performances with respect to the traditional DNA Barcode classification methods. On empirical data their classification performances are at a comparable level to the other methods. Conclusions The classification analysis shows that supervised machine learning methods are promising candidates for handling with success the DNA Barcoding species classification problem, obtaining excellent performances. To conclude, a powerful tool to perform species identification is now available to the DNA Barcoding community. PMID:24721333

Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning.

PubMed

Teng, Haotian; Cao, Minh Duc; Hall, Michael B; Duarte, Tania; Wang, Sheng; Coin, Lachlan J M

2018-05-01

Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling and directly translate the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4,000 reads, we show that our model provides state-of-the-art basecalling accuracy, even on previously unseen species. Chiron achieves basecalling speeds of more than 2,000 bases per second using desktop computer graphics processing units.

A Mini-Library of Sequenced Human DNA Fragments: Linking Bench Experiments with Informatics

ERIC Educational Resources Information Center

Dalgleish, Raymond; Shanks, Morag E.; Monger, Karen; Butler, Nicola J.

2012-01-01

We describe the development of a mini-library of human DNA fragments for use in an enquiry-based learning (EBL) undergraduate practical incorporating "wet-lab" and bioinformatics tasks. In spite of the widespread emergence of the polymerase chain reaction (PCR), the cloning and analysis of DNA fragments in "Escherichia coli"…

Machine Learning–Based Differential Network Analysis: A Study of Stress-Responsive Transcriptomes in Arabidopsis[W

PubMed Central

Ma, Chuang; Xin, Mingming; Feldmann, Kenneth A.; Wang, Xiangfeng

2014-01-01

Machine learning (ML) is an intelligent data mining technique that builds a prediction model based on the learning of prior knowledge to recognize patterns in large-scale data sets. We present an ML-based methodology for transcriptome analysis via comparison of gene coexpression networks, implemented as an R package called machine learning–based differential network analysis (mlDNA) and apply this method to reanalyze a set of abiotic stress expression data in Arabidopsis thaliana. The mlDNA first used a ML-based filtering process to remove nonexpressed, constitutively expressed, or non-stress-responsive “noninformative” genes prior to network construction, through learning the patterns of 32 expression characteristics of known stress-related genes. The retained “informative” genes were subsequently analyzed by ML-based network comparison to predict candidate stress-related genes showing expression and network differences between control and stress networks, based on 33 network topological characteristics. Comparative evaluation of the network-centric and gene-centric analytic methods showed that mlDNA substantially outperformed traditional statistical testing–based differential expression analysis at identifying stress-related genes, with markedly improved prediction accuracy. To experimentally validate the mlDNA predictions, we selected 89 candidates out of the 1784 predicted salt stress–related genes with available SALK T-DNA mutagenesis lines for phenotypic screening and identified two previously unreported genes, mutants of which showed salt-sensitive phenotypes. PMID:24520154

A deep learning method for lincRNA detection using auto-encoder algorithm.

PubMed

Yu, Ning; Yu, Zeng; Pan, Yi

2017-12-06

RNA sequencing technique (RNA-seq) enables scientists to develop novel data-driven methods for discovering more unidentified lincRNAs. Meantime, knowledge-based technologies are experiencing a potential revolution ignited by the new deep learning methods. By scanning the newly found data set from RNA-seq, scientists have found that: (1) the expression of lincRNAs appears to be regulated, that is, the relevance exists along the DNA sequences; (2) lincRNAs contain some conversed patterns/motifs tethered together by non-conserved regions. The two evidences give the reasoning for adopting knowledge-based deep learning methods in lincRNA detection. Similar to coding region transcription, non-coding regions are split at transcriptional sites. However, regulatory RNAs rather than message RNAs are generated. That is, the transcribed RNAs participate the biological process as regulatory units instead of generating proteins. Identifying these transcriptional regions from non-coding regions is the first step towards lincRNA recognition. The auto-encoder method achieves 100% and 92.4% prediction accuracy on transcription sites over the putative data sets. The experimental results also show the excellent performance of predictive deep neural network on the lincRNA data sets compared with support vector machine and traditional neural network. In addition, it is validated through the newly discovered lincRNA data set and one unreported transcription site is found by feeding the whole annotated sequences through the deep learning machine, which indicates that deep learning method has the extensive ability for lincRNA prediction. The transcriptional sequences of lincRNAs are collected from the annotated human DNA genome data. Subsequently, a two-layer deep neural network is developed for the lincRNA detection, which adopts the auto-encoder algorithm and utilizes different encoding schemes to obtain the best performance over intergenic DNA sequence data. Driven by those newly annotated lincRNA data, deep learning methods based on auto-encoder algorithm can exert their capability in knowledge learning in order to capture the useful features and the information correlation along DNA genome sequences for lincRNA detection. As our knowledge, this is the first application to adopt the deep learning techniques for identifying lincRNA transcription sequences.

DNA: The Strand that Connects Us All

ScienceCinema

Kaplan, Matt [Univ. of Arizona, Tucson, AZ (United States). Genetics Core Facility

2018-04-26

Learn how the methods and discoveries of human population genetics are applied for personal genealogical reconstruction and anthropological testing. Dr. Kaplan starts with a short general review of human genetics and the biology behind this form of DNA testing. He looks at how DNA testing is performed and how samples are processed in the University of Arizona laboratory. He also examines examples of personal genealogical results from Family Tree DNA and personal anthropological results from the Genographic Project. Finally, he describes the newest project in the UA laboratory, the DNA Shoah Project.

Association of Amine-Receptor DNA Sequence Variants with Associative Learning in the Honeybee.

PubMed

Lagisz, Malgorzata; Mercer, Alison R; de Mouzon, Charlotte; Santos, Luana L S; Nakagawa, Shinichi

2016-03-01

Octopamine- and dopamine-based neuromodulatory systems play a critical role in learning and learning-related behaviour in insects. To further our understanding of these systems and resulting phenotypes, we quantified DNA sequence variations at six loci coding octopamine-and dopamine-receptors and their association with aversive and appetitive learning traits in a population of honeybees. We identified 79 polymorphic sequence markers (mostly SNPs and a few insertions/deletions) located within or close to six candidate genes. Intriguingly, we found that levels of sequence variation in the protein-coding regions studied were low, indicating that sequence variation in the coding regions of receptor genes critical to learning and memory is strongly selected against. Non-coding and upstream regions of the same genes, however, were less conserved and sequence variations in these regions were weakly associated with between-individual differences in learning-related traits. While these associations do not directly imply a specific molecular mechanism, they suggest that the cross-talk between dopamine and octopamine signalling pathways may influence olfactory learning and memory in the honeybee.

Getting the Most out of Electrophoresis Units

ERIC Educational Resources Information Center

Mulvihill, Charlotte

2007-01-01

At Oklahoma City Community College, they have developed gel electrophoresis activities that support active learning of many scientific concepts, including: pH, electrolysis, oxidation reduction, electrical currents, potentials, conductivity, molarity, gel electrophoresis, DNA and protein separation, and DNA fingerprinting. This article presents…

Liquid biopsies come of age: towards implementation of circulating tumour DNA.

PubMed

Wan, Jonathan C M; Massie, Charles; Garcia-Corbacho, Javier; Mouliere, Florent; Brenton, James D; Caldas, Carlos; Pacey, Simon; Baird, Richard; Rosenfeld, Nitzan

2017-04-01

Improvements in genomic and molecular methods are expanding the range of potential applications for circulating tumour DNA (ctDNA), both in a research setting and as a 'liquid biopsy' for cancer management. Proof-of-principle studies have demonstrated the translational potential of ctDNA for prognostication, molecular profiling and monitoring. The field is now in an exciting transitional period in which ctDNA analysis is beginning to be applied clinically, although there is still much to learn about the biology of cell-free DNA. This is an opportune time to appraise potential approaches to ctDNA analysis, and to consider their applications in personalized oncology and in cancer research.

The DNA Triangle and Its Application to Learning Meiosis.

PubMed

Wright, L Kate; Catavero, Christina M; Newman, Dina L

2017-01-01

Although instruction on meiosis is repeated many times during the undergraduate curriculum, many students show poor comprehension even as upper-level biology majors. We propose that the difficulty lies in the complexity of understanding DNA, which we explain through a new model, the DNA triangle The DNA triangle integrates three distinct scales at which one can think about DNA: chromosomal , molecular , and informational Through analysis of interview and survey data from biology faculty and students through the lens of the DNA triangle, we illustrate important differences in how novices and experts are able to explain the concepts of ploidy , homology , and mechanism of homologous pairing Similarly, analysis of passages from 16 different biology textbooks shows a large divide between introductory and advanced material, with introductory books omitting explanations of meiosis-linked concepts at the molecular level of DNA. Finally, backed by textbook findings and feedback from biology experts, we show that the DNA triangle can be applied to teaching and learning meiosis. By applying the DNA triangle to topics on meiosis we present a new framework for educators and researchers that ties concepts of ploidy, homology, and mechanism of homologous pairing to knowledge about DNA on the chromosomal, molecular, and informational levels. © 2017 L. K. Wright et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Manipulating the "Invisible": Learning Molecular Biology Using Inexpensive Models.

ERIC Educational Resources Information Center

Malacinski, George M.; Zell, Paul W.

1996-01-01

Describes three models that provide a concrete experience of abstract concepts such as DNA replication, RNA synthesis, and protein synthesis. Explains their hands-on use and notes their advantages for teaching and learning. (JRH)

BiRen: predicting enhancers with a deep-learning-based model using the DNA sequence alone.

PubMed

Yang, Bite; Liu, Feng; Ren, Chao; Ouyang, Zhangyi; Xie, Ziwei; Bo, Xiaochen; Shu, Wenjie

2017-07-01

Enhancer elements are noncoding stretches of DNA that play key roles in controlling gene expression programmes. Despite major efforts to develop accurate enhancer prediction methods, identifying enhancer sequences continues to be a challenge in the annotation of mammalian genomes. One of the major issues is the lack of large, sufficiently comprehensive and experimentally validated enhancers for humans or other species. Thus, the development of computational methods based on limited experimentally validated enhancers and deciphering the transcriptional regulatory code encoded in the enhancer sequences is urgent. We present a deep-learning-based hybrid architecture, BiRen, which predicts enhancers using the DNA sequence alone. Our results demonstrate that BiRen can learn common enhancer patterns directly from the DNA sequence and exhibits superior accuracy, robustness and generalizability in enhancer prediction relative to other state-of-the-art enhancer predictors based on sequence characteristics. Our BiRen will enable researchers to acquire a deeper understanding of the regulatory code of enhancer sequences. Our BiRen method can be freely accessed at https://github.com/wenjiegroup/BiRen . shuwj@bmi.ac.cn or boxc@bmi.ac.cn. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Quantum annealing versus classical machine learning applied to a simplified computational biology problem

PubMed Central

Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

2018-01-01

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems. PMID:29652405

Dnmt1 and Dnmt3a are required for the maintenance of DNA methylation and synaptic function in adult forebrain neurons

PubMed Central

Feng, Jian; Zhou, Yu; Campbell, Susan L.; Le, Thuc; Li, En; Sweatt, J. David; Silva, Alcino J.; Fan, Guoping

2011-01-01

Dnmt1 and Dnmt3a, two major DNA methyltransferases, are expressed in postmitotic neurons, but their function in the central nervous system (CNS) is unclear. We generated conditional mutant mice that lack either Dnmt1, or Dnmt3a, or both exclusively in forebrain excitatory neurons and found only double knockout (DKO) mice exhibited abnormal hippocampal CA1 long-term plasticity and deficits of learning and memory. While no neuronal loss was found, the size of hippocampal neurons in DKO was smaller; furthermore, DKO neurons showed a deregulation of gene expression including class I MHC and Stat1 that are known to play a role in synaptic plasticity. In addition, we observed a significant decrease in DNA methylation in DKO neurons. We conclude that Dnmt1 and Dnmt3a are required for synaptic plasticity, learning and memory through their overlapping roles in maintaining DNA methylation and modulating neuronal gene expression in adult CNS neurons. PMID:20228804

DNA curvature and flexibility in vitro and in vivo

PubMed Central

Peters, Justin P.; Maher, L. James

2014-01-01

It has been more than 50 years since the elucidation of the structure of double-helical DNA. Despite active research and progress in DNA biology and biochemistry, much remains to be learned in the field of DNA biophysics. Predicting the sequence-dependent curvature and flexibility of DNA is difficult. Applicability of the conventional worm-like chain polymer model of DNA has been challenged. The fundamental forces responsible for the remarkable resistance of DNA to bending and twisting remain controversial. The apparent “softening” of DNA measured in vivo in the presence of kinking proteins and superhelical strain is incompletely understood. New methods and insights are being applied to these problems. This review places current work on DNA biophysics in historical context and illustrates the ongoing interplay between theory and experiment in this exciting field. PMID:20478077

A Comparison Study for DNA Motif Modeling on Protein Binding Microarray.

PubMed

Wong, Ka-Chun; Li, Yue; Peng, Chengbin; Wong, Hau-San

2016-01-01

Transcription factor binding sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, protein binding microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k = 8∼10). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build TFBS (also known as DNA motif) models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement if choosing di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

Recovering Process from Child Sexual Abuse During Adulthood from an Integrative Approach to Solution-Focused Therapy: A Case Study.

PubMed

Gonzalez, Carolina

2017-10-01

In recent times, strengths-based recovery approaches that focus on the present and build strategies that look toward the future have become popular. However, some cases require the consideration of experiences from previous stages of the clients' development. This single-case study explores the psychotherapeutic process of a middle-aged woman who presented with a history of child sexual abuse (incest) and a long-term adult diagnosis of depression that was treated in public health services. This psychotherapy involved an integrative approach to solution-focused therapy; specifically, the approach proposed by Yvonne Dolan to work with adult survivors of sexual abuse, in conjunction with techniques and strategies from the transtheoretical model. Measures incorporating therapeutic working alliance and outcomes were administered over sessions. Results showed positive outcomes from this therapeutic intervention, which remained at 3-month and 12-month follow-ups. Implications for practitioners' specialist practice in health services are discussed, given the complexity of comorbid mental health conditions with a history of child sexual abuse.

Restoration of Cognitive Performance in Mice Carrying a Deficient Allele of 8-Oxoguanine DNA Glycosylase by X-ray Irradiation.

PubMed

Hofer, Tim; Duale, Nur; Muusse, Martine; Eide, Dag Marcus; Dahl, Hildegunn; Boix, Fernando; Andersen, Jannike M; Olsen, Ann Karin; Myhre, Oddvar

2018-05-01

Environmental stressors inducing oxidative stress such as ionizing radiation may influence cognitive function and neuronal plasticity. Recent studies have shown that transgenic mice deficient of DNA glycosylases display unexpected cognitive deficiencies related to changes in gene expression in the hippocampus. The main objectives of the present study were to determine learning and memory performance in C57BL/6NTac 8-oxoguanine DNA glycosylase 1 (Ogg1) +/- (heterozygote) and Ogg1 +/+ (wild type, WT) mice, to study whether a single acute X-ray challenge (0.5 Gy, dose rate 0.457 Gy/min) influenced the cognitive performance in the Barnes maze, and if such differences were related to changes in gene expression levels in the hippocampus. We found that the Ogg1 +/- mice exhibited poorer early-phase learning performance compared to the WT mice. Surprisingly, X-ray exposure of the Ogg1 +/- animals improved their early-phase learning performance. No persistent effects on memory in the late-phase (6 weeks after irradiation) were observed. Our results further suggest that expression of 3 (Adrb1, Il1b, Prdx6) out of in total 35 genes investigated in the Ogg1 +/- hippocampus is correlated to spatial learning in the Barnes maze.

Teaching a Biotechnology Unit in High School General Biology.

ERIC Educational Resources Information Center

Hays, Lana

1994-01-01

Describes a unit in biotechnology for average and below average high school students. Students developed productive team membership, used math and communication skills to solve problems, and used the scientific method to learn about biotechnology. Students separated DNA, transformed bacterial cells, interpreted DNA fingerprints, completed creative…

Problem-Based Learning in an Online Course: A Case Study

ERIC Educational Resources Information Center

Cheaney, James D.; Ingebritsen, Thomas S.

2005-01-01

Problem-based learning (PBL) is the use of a "real world" problem or situation as a context for learning. The present study explores the use of PBL in an online biotechnology course. In the PBL unit, student groups dealt with the ethical, legal, social, and human issues surrounding pre-symptomatic DNA testing for a genetic disease. Issues…

Predicting DNA Methylation State of CpG Dinucleotide Using Genome Topological Features and Deep Networks

NASA Astrophysics Data System (ADS)

Wang, Yiheng; Liu, Tong; Xu, Dong; Shi, Huidong; Zhang, Chaoyang; Mo, Yin-Yuan; Wang, Zheng

2016-01-01

The hypo- or hyper-methylation of the human genome is one of the epigenetic features of leukemia. However, experimental approaches have only determined the methylation state of a small portion of the human genome. We developed deep learning based (stacked denoising autoencoders, or SdAs) software named “DeepMethyl” to predict the methylation state of DNA CpG dinucleotides using features inferred from three-dimensional genome topology (based on Hi-C) and DNA sequence patterns. We used the experimental data from immortalised myelogenous leukemia (K562) and healthy lymphoblastoid (GM12878) cell lines to train the learning models and assess prediction performance. We have tested various SdA architectures with different configurations of hidden layer(s) and amount of pre-training data and compared the performance of deep networks relative to support vector machines (SVMs). Using the methylation states of sequentially neighboring regions as one of the learning features, an SdA achieved a blind test accuracy of 89.7% for GM12878 and 88.6% for K562. When the methylation states of sequentially neighboring regions are unknown, the accuracies are 84.82% for GM12878 and 72.01% for K562. We also analyzed the contribution of genome topological features inferred from Hi-C. DeepMethyl can be accessed at http://dna.cs.usm.edu/deepmethyl/.

Predicting DNA Methylation State of CpG Dinucleotide Using Genome Topological Features and Deep Networks.

PubMed

Wang, Yiheng; Liu, Tong; Xu, Dong; Shi, Huidong; Zhang, Chaoyang; Mo, Yin-Yuan; Wang, Zheng

2016-01-22

The hypo- or hyper-methylation of the human genome is one of the epigenetic features of leukemia. However, experimental approaches have only determined the methylation state of a small portion of the human genome. We developed deep learning based (stacked denoising autoencoders, or SdAs) software named "DeepMethyl" to predict the methylation state of DNA CpG dinucleotides using features inferred from three-dimensional genome topology (based on Hi-C) and DNA sequence patterns. We used the experimental data from immortalised myelogenous leukemia (K562) and healthy lymphoblastoid (GM12878) cell lines to train the learning models and assess prediction performance. We have tested various SdA architectures with different configurations of hidden layer(s) and amount of pre-training data and compared the performance of deep networks relative to support vector machines (SVMs). Using the methylation states of sequentially neighboring regions as one of the learning features, an SdA achieved a blind test accuracy of 89.7% for GM12878 and 88.6% for K562. When the methylation states of sequentially neighboring regions are unknown, the accuracies are 84.82% for GM12878 and 72.01% for K562. We also analyzed the contribution of genome topological features inferred from Hi-C. DeepMethyl can be accessed at http://dna.cs.usm.edu/deepmethyl/.

Quantum annealing versus classical machine learning applied to a simplified computational biology problem

NASA Astrophysics Data System (ADS)

Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

2018-03-01

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to classify and rank binding affinities. Using simplified data sets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified data sets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems.

Molecular Cloning and Analysis of a DNA Repetitive Element from the Mouse Genome

ERIC Educational Resources Information Center

Geisinger, Adriana; Cossio, Gabriela; Wettstein, Rodolfo

2006-01-01

We report the development of a 3-week laboratory activity for an undergraduate molecular biology course. This activity introduces students to the practice of basic molecular techniques such as restriction enzyme digestion, agarose gel electrophoresis, cloning, plasmid DNA purification, Southern blotting, and sequencing. Students learn how to carry…

Teaching Biology around Themes: Teach Proteins and DNA Together.

ERIC Educational Resources Information Center

Offner, Susan

1992-01-01

Proposes as a unifying theme for high school biology the question of "how chromosomes determine what we are." Describes a sequence of lessons in which students learn about proteins, enzymes, and amino acids. Includes three dry laboratory exercises to demonstrate the DNA sequences for sickle cell anemia and cystic fibrosis. (MDH)

Using Concrete & Representational Experiences to Understand the Structure of DNA: A Four-Step Instructional Framework

ERIC Educational Resources Information Center

Harrell, Pamela Esprivalo; Richards, Debbie; Collins, James; Taylor, Sarah

2005-01-01

A description of learning experience that uses a four-step instrumentational framework involving concrete and representational experiences to promote conceptual understanding of abstract biological concepts by a series of closely-related activities is presented. The students are introduced to the structure and implications of DNA using four…

Comparison of Radio Frequency Distinct Native Attribute and Matched Filtering Techniques for Device Discrimination and Operation Identification

DTIC Science & Technology

identification. URE from ten MSP430F5529 16-bit microcontrollers were analyzed using: 1) RF distinct native attributes (RF-DNA) fingerprints paired with multiple...discriminant analysis/maximum likelihood (MDA/ML) classification, 2) RF-DNA fingerprints paired with generalized relevance learning vector quantized

DNA: The Molecule of Life. A Multimedia CD-ROM. [CD-ROM].

ERIC Educational Resources Information Center

2001

This CD-ROM is designed for classroom and individual use to teach and learn about DNA. Integrated animations, custom graphics, three-dimensional representations, photographs, and sound are featured for use in user-controlled activities. Interactive lessons are available to reinforce the subject material. Pre- and post-testing sections are also…

Avian Semen Collection by Cloacal Massage and Isolation of DNA from Sperm.

PubMed

Kucera, Aurelia C; Heidinger, Britt J

2018-02-05

Collection of semen may be useful for a wide range of applications including studies involving sperm quality, sperm telomere dynamics, and epigenetics. Birds are widely used subjects in biological research and are ideal for studies involving repeated sperm samples. However, few resources are currently available for those wishing to learn how to collect and extract DNA from avian sperm. Here we describe cloacal massage, a gentle, non-invasive manual technique for collecting avian sperm. Although this technique is established in the literature, it can be difficult to learn from the available descriptions. We also provide information for extracting DNA from avian semen using a commercial extraction kit with modifications. Cloacal massage can be easily used on any small- to medium-sized male bird in reproductive condition. Following collection, the semen can be used immediately for motility assays, or frozen for DNA extraction following the protocol described herein. This extraction protocol was refined for avian sperm and has been successfully used on samples collected from several passerine species (Passer domesticus, Spizella passerina, Haemorhous mexicanus, and Turdus migratorius) and one columbid (Columba livia).

Integrating PCR theory and bioinformatics into a research-oriented primer design exercise.

PubMed

Robertson, Amber L; Phillips, Allison R

2008-01-01

Polymerase chain reaction (PCR) is a conceptually difficult technique that embodies many fundamental biological processes. Traditionally, students have struggled to analyze PCR results due to an incomplete understanding of the biological concepts (theory) of DNA replication and strand complementarity. Here we describe the design of a novel research-oriented exercise that prepares students to design DNA primers for PCR. Our exercise design includes broad and specific learning goals and assessments of student performance and perceptions. We developed this interactive Primer Design Exercise using the principles of scientific teaching to enhance student understanding of the theory behind PCR and provide practice in designing PCR primers to amplify DNA. In the end, the students were more poised to troubleshoot problems that arose in real experiments using PCR. In addition, students had the opportunity to utilize several bioinformatics tools to gain an increased understanding of primer quality, directionality, and specificity. In the course of this study many misconceptions about DNA replication during PCR and the need for primer specificity were identified and addressed. Students were receptive to the new materials and the majority achieved the learning goals.

The Bacterial Cytoskeleton

ERIC Educational Resources Information Center

Watters, Christopher

2006-01-01

For a eukaryotic cell biologist, learning new things about old, familiar subjects (such as the differences between eukaryotes and prokaryotes) is one of the pleasures of teaching introductory biology courses. Such learning usually entails examining how bacteria function, in ways other than how they replicate and transcribe DNA and how they…

Family Secrets: The Bioethics of Genetic Testing

ERIC Educational Resources Information Center

Markowitz, Dina G.; DuPre, Michael J.; Holt, Susan; Chen, Shaw-Ree; Wischnowski, Michael

2006-01-01

This article discusses "Family Secrets," a problem-based learning (PBL) curriculum module that focuses on the bioethical implications of genetic testing. In high school biology classrooms throughout New York State, students are using "Family Secrets" to learn about DNA testing; Huntington's disease (HD); and the ethical, legal,…

Personal DNA testing in college classrooms: perspectives of students and professors.

PubMed

Daley, Lori-Ann A; Wagner, Jennifer K; Himmel, Tiffany L; McPartland, Kaitlyn A; Katsanis, Sara H; Shriver, Mark D; Royal, Charmaine D

2013-06-01

Discourse on the integration of personal genetics and genomics into classrooms is increasing; however, limited data have been collected on the perspectives of students and professors. We conducted a cross-sectional survey of undergraduate and graduate students as well as professors at two major universities to assess attitudes regarding the use of personal DNA testing and other personalized activities in college classrooms. Students indicated that they were more likely to enroll (60.2%) in a genetics course if it offered personal DNA testing; undergraduate students were more likely than graduate students to enroll if personal DNA testing was offered (p=0.029). Students who majored in the physical sciences were less likely to enroll than students in the biological or social sciences (p=0.019). Students also indicated that when course material is personalized, the course is more interesting (94.6%) and the material is easier to learn (87.3%). Professors agreed that adding a personalized element increases student interest, participation, and learning (86.0%, 82.6%, and 72.6%, respectively). The results of this study indicate that, overall, students and professors had a favorable view of the integration of personalized information, including personal DNA testing, into classroom activities, and students welcomed more opportunities to participate in personalized activities.

Recognising promoter sequences using an artificial immune system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cooke, D.E.; Hunt, J.E.

1995-12-31

We have developed an artificial immune system (AIS) which is based on the human immune system. The AIS possesses an adaptive learning mechanism which enables antibodies to emerge which can be used for classification tasks. In this paper, we describe how the AIS has been used to evolve antibodies which can classify promoter containing and promoter negative DNA sequences. The DNA sequences used for teaching were 57 nucleotides in length and contained procaryotic promoters. The system classified previously unseen DNA sequences with an accuracy of approximately 90%.

Methyl-donor deficiency in adolescence affects memory and epigenetic status in the mouse hippocampus.

PubMed

Tomizawa, H; Matsuzawa, D; Ishii, D; Matsuda, S; Kawai, K; Mashimo, Y; Sutoh, C; Shimizu, E

2015-03-01

DNA methylation is one of the essential factors in the control of gene expression. Alteration of the DNA methylation pattern has been linked to various neurological, behavioral and neurocognitive dysfunctions. Recent studies have pointed out the importance of epigenetics in brain development and functions including learning and memory. Nutrients related to one-carbon metabolism are known to play important roles in the maintenance of genomic DNA methylation. Previous studies have shown that the long-term administration of a diet lacking essential one-carbon nutrients such as methionine, choline and folic acid (methyl donors) caused global DNA hypermethylation in the brain. Therefore, the long-term feeding of a methyl-donor-deficient diet may cause abnormal brain development including learning and memory. To confirm this hypothesis, 3-week-old mice were maintained on a folate-, methionine- and choline-deficient (FMCD) or control (CON) diet for 3 weeks. We found that the methyl-donor deficiency impaired both novel object recognition and fear extinction after 3 weeks of treatment. The FMCD group showed spontaneous recovery of fear that differed from that in CON. In addition, we found decreased Gria1 gene expression and specific CpG hypermethylation of the Gria1 promoter region in the FMCD hippocampus. Our data suggest that a chronic dietary lack of methyl donors in the developmental period affects learning, memory and gene expressions in the hippocampus. © 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Computer-Aided Drug Discovery: Molecular Docking of Diminazene Ligands to DNA Minor Groove

ERIC Educational Resources Information Center

Kholod, Yana; Hoag, Erin; Muratore, Katlynn; Kosenkov, Dmytro

2018-01-01

The reported project-based laboratory unit introduces upper-division undergraduate students to the basics of computer-aided drug discovery as a part of a computational chemistry laboratory course. The students learn to perform model binding of organic molecules (ligands) to the DNA minor groove with computer-aided drug discovery (CADD) tools. The…

Blended Inquiry with Hands-On and Virtual Laboratories: The Role of Perceptual Features during Knowledge Construction

ERIC Educational Resources Information Center

Toth, Eva Erdosne; Ludvico, Lisa R.; Morrow, Becky L.

2014-01-01

This study examined the characteristics of virtual and hands-on inquiry environments for the development of blended learning in a popular domain of bio-nanotechnology: the separation of different-sized DNA fragments using gel-electrophoresis, also known as DNA-fingerprinting. Since the latest scientific developments in nano- and micro-scale tools…

DNA Structure.

ERIC Educational Resources Information Center

Henderson, Paula

This autoinstructional lesson deals with the study of molecular biology. It is suggested as relevant to high school biology courses. No prerequisites are suggested. Two behavioral objectives are given leading to the learning of nucleotide bases, their parts, and the ways they pair as they do. The time suggested for this learning activity is about…

Practicality in Virtuality: Finding Student Meaning in Video Game Education

ERIC Educational Resources Information Center

Barko, Timothy; Sadler, Troy D.

2013-01-01

This paper looks at the conceptual differences between video game learning and traditional classroom and laboratory learning. It explores the notion of virtual experience by comparing a commonly used high school laboratory protocol on DNA extraction with a similar experience provided by a biotechnology themed video game. When considered…

Learning Molecular Genetics in Teacher-Led Outreach Laboratories

ERIC Educational Resources Information Center

Ben-Nun, Michal Stolarsky; Yarden, Anat

2009-01-01

Learning modern genetics is challenging and students have difficulty acquiring a coherent cognitive mental model of abstract concepts such as DNA, bacteria and enzymes. Here we investigated students' mental models of genetics through analysis and interpretation of the discourse that took place while high-school students practised hands-on…

Beyond textbook illustrations: Hand-held models of ordered DNA and protein structures as 3D supplements to enhance student learning of helical biopolymers.

PubMed

Jittivadhna, Karnyupha; Ruenwongsa, Pintip; Panijpan, Bhinyo

2010-11-01

Textbook illustrations of 3D biopolymers on printed paper, regardless of how detailed and colorful, suffer from its two-dimensionality. For beginners, computer screen display of skeletal models of biopolymers and their animation usually does not provide the at-a-glance 3D perception and details, which can be done by good hand-held models. Here, we report a study on how our students learned more from using our ordered DNA and protein models assembled from colored computer-printouts on transparency film sheets that have useful structural details. Our models (reported in BAMBED 2009), having certain distinguished features, helped our students to grasp various aspects of these biopolymers that they usually find difficult. Quantitative and qualitative learning data from this study are reported. Copyright © 2010 International Union of Biochemistry and Molecular Biology, Inc.

WE-DE-202-01: Connecting Nanoscale Physics to Initial DNA Damage Through Track Structure Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schuemann, J.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Genetic evidence supports song learning in the three-wattled bellbird Procnias tricarunculata (Cotingidae).

PubMed

Saranathan, Vinodkumar; Hamilton, Deborah; Powell, George V N; Kroodsma, Donald E; Prum, Richard O

2007-09-01

Vocal learning is thought to have evolved in three clades of birds (parrots, hummingbirds, and oscine passerines), and three clades of mammals (whales, bats, and primates). Behavioural data indicate that, unlike other suboscine passerines, the three-wattled bellbird Procnias tricarunculata (Cotingidae) is capable of vocal learning. Procnias tricarunculata shows conspicuous vocal ontogeny, striking geographical variation in song, and rapid temporal change in song within a population. Deprivation studies of vocal development in P. tricarunculata are impractical. Here, we report evidence from mitochondrial DNA sequences and nuclear microsatellite loci that genetic variation within and among the four allopatric breeding populations of P. tricarunculata is not congruent with variation in vocal behaviour. Sequences of the mitochondrial DNA control region document extensive haplotype sharing among localities and song types, and no phylogenetic resolution of geographical populations or behavioural groups. The vocally differentiated, allopatric breeding populations of P. tricarunculata are only weakly genetically differentiated populations, and are not distinct taxa. Mitochondrial DNA and microsatellite variation show small (2.9% and 13.5%, respectively) but significant correlation with geographical distance, but no significant residual variation by song type. Estimates of the strength of selection that would be needed to maintain the observed geographical pattern in vocal differentiation if songs were genetically based are unreasonably high, further discrediting the hypothesis of a genetic origin of vocal variation. These data support a fourth, phylogenetically independent origin of avian vocal learning in Procnias. Geographical variations in P. tricarunculata vocal behaviour are likely culturally evolved dialects.

Genome-wide prediction of cis-regulatory regions using supervised deep learning methods.

PubMed

Li, Yifeng; Shi, Wenqiang; Wasserman, Wyeth W

2018-05-31

In the human genome, 98% of DNA sequences are non-protein-coding regions that were previously disregarded as junk DNA. In fact, non-coding regions host a variety of cis-regulatory regions which precisely control the expression of genes. Thus, Identifying active cis-regulatory regions in the human genome is critical for understanding gene regulation and assessing the impact of genetic variation on phenotype. The developments of high-throughput sequencing and machine learning technologies make it possible to predict cis-regulatory regions genome wide. Based on rich data resources such as the Encyclopedia of DNA Elements (ENCODE) and the Functional Annotation of the Mammalian Genome (FANTOM) projects, we introduce DECRES based on supervised deep learning approaches for the identification of enhancer and promoter regions in the human genome. Due to their ability to discover patterns in large and complex data, the introduction of deep learning methods enables a significant advance in our knowledge of the genomic locations of cis-regulatory regions. Using models for well-characterized cell lines, we identify key experimental features that contribute to the predictive performance. Applying DECRES, we delineate locations of 300,000 candidate enhancers genome wide (6.8% of the genome, of which 40,000 are supported by bidirectional transcription data), and 26,000 candidate promoters (0.6% of the genome). The predicted annotations of cis-regulatory regions will provide broad utility for genome interpretation from functional genomics to clinical applications. The DECRES model demonstrates potentials of deep learning technologies when combined with high-throughput sequencing data, and inspires the development of other advanced neural network models for further improvement of genome annotations.

Recognition of multiple imbalanced cancer types based on DNA microarray data using ensemble classifiers.

PubMed

Yu, Hualong; Hong, Shufang; Yang, Xibei; Ni, Jun; Dan, Yuanyuan; Qin, Bin

2013-01-01

DNA microarray technology can measure the activities of tens of thousands of genes simultaneously, which provides an efficient way to diagnose cancer at the molecular level. Although this strategy has attracted significant research attention, most studies neglect an important problem, namely, that most DNA microarray datasets are skewed, which causes traditional learning algorithms to produce inaccurate results. Some studies have considered this problem, yet they merely focus on binary-class problem. In this paper, we dealt with multiclass imbalanced classification problem, as encountered in cancer DNA microarray, by using ensemble learning. We utilized one-against-all coding strategy to transform multiclass to multiple binary classes, each of them carrying out feature subspace, which is an evolving version of random subspace that generates multiple diverse training subsets. Next, we introduced one of two different correction technologies, namely, decision threshold adjustment or random undersampling, into each training subset to alleviate the damage of class imbalance. Specifically, support vector machine was used as base classifier, and a novel voting rule called counter voting was presented for making a final decision. Experimental results on eight skewed multiclass cancer microarray datasets indicate that unlike many traditional classification approaches, our methods are insensitive to class imbalance.

Finite temperature corrections and embedded strings in noncommutative geometry and the standard model with neutrino mixing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martins, R. A.

The recent extension of the standard model to include massive neutrinos in the framework of noncommutative geometry and the spectral action principle involves new scalar fields and their interactions with the usual complex scalar doublet. After ensuring that they bring no unphysical consequences, we address the question of how these fields affect the physics predicted in the Weinberg-Salam theory, particularly in the context of the electroweak phase transition. Applying the Dolan-Jackiw procedure, we calculate the finite temperature corrections, and find that the phase transition is first order. The new scalar interactions significantly improve the stability of the electroweak Z string,more » through the 'bag' phenomenon described by Vachaspati and Watkins ['Bound states can stabilize electroweak strings', Phys. Lett. B 318, 163-168 (1993)]. (Recently, cosmic strings have climbed back into interest due to a new evidence.) Sourced by static embedded strings, an internal space analogy of Cartan's torsion is drawn, and a possible Higgs-force-like 'gravitational' effect of this nonpropagating torsion on the fermion masses is described. We also check that the field generating the Majorana mass for the {nu}{sub R} is nonzero in the physical vacuum.« less

Advances in hemophilia care: report of two symposia at the Hemophilia 2010 World Congress.

PubMed

Dolan, Gerry; Cruz, Jussara Almeida; Steinhagen-Thiessen, Elisabeth; Kessler, Craig; Haaning, Jesper; Lemm, Georg; Altisent, Carmen; Guerrero, Caesar; Hermans, Cedric; Riske, Brenda; Bolton-Maggs, Paula

2012-04-01

The World Federation of Hemophilia (WFH) 2010 World Congress held in Buenos Aires, Argentina, in July 2010, attracted more than 4,300 participants from 106 countries. This report summarizes two symposia held during the congress. The first, titled "Emerging Co-Morbidities in the Aging Hemophilia Population: Healthcare Challenges and Treatment Opportunities," chaired by Gerry Dolan, MD, and Jussara Almeida Cruz, MD, examined the co-morbidities experienced by the aging hemophilic patient population, such as cardiovascular disease, cancer, arthritis, osteoporosis, hypertension, and obesity. In addition, Bayer's products in preclinical and clinical development were reviewed, including a novel factor VIIa variant and a long-acting factor VIII molecule, i.e., one that has undergone site-specific PEGylation (attachment of polyethylene glycol [PEG] polymer chains to another molecule). The other symposium, titled "Practical Steps to Making Better Care for Hemophilia Patients a Reality," chaired by Carmen Altisent, MD, and Cesar Guerrero, RN, reviewed the steps that hemophilia caregivers can take to improve the care of their patients. Issues such as the treatment of hemarthroses, the role of the research nurse, and the management of pediatric patients transitioning to adulthood were discussed.

Using an Active-Learning Approach to Teach Epigenetics

ERIC Educational Resources Information Center

Colon-Berlingeri, Migdalisel

2010-01-01

Epigenetics involves heritable changes in gene expression that do not involve alterations in the DNA sequence. I developed an active-learning approach to convey this topic to students in a college genetics course. I posted a brief summary of the topic before class to stimulate exchange in cooperative groups. During class, we discussed the…

BIOPS Interactive: An e-Learning Platform Focused on Protein Structure and DNA

ERIC Educational Resources Information Center

Pontelli, Enrico; Pinto, Jorge; Qin, Xiaoxiao; He, Jing; Bevan, David; MacCuish, Norah; MacCuish, John; Chapman, Mitch; Moreland, David

2009-01-01

One of the difficulties in teaching basic molecular biology concepts to the students with little biological background is the lack of hands-on exercises that combines the challenges of the concepts with visualization and immediate feedback. BIOPS Interactive is a web-based interactive learning environment for molecular biology that complements…

An introduction to kernel-based learning algorithms.

PubMed

Müller, K R; Mika, S; Rätsch, G; Tsuda, K; Schölkopf, B

2001-01-01

This paper provides an introduction to support vector machines, kernel Fisher discriminant analysis, and kernel principal component analysis, as examples for successful kernel-based learning methods. We first give a short background about Vapnik-Chervonenkis theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations. We illustrate the usefulness of kernel algorithms by discussing applications such as optical character recognition and DNA analysis.

An evolution-based DNA-binding residue predictor using a dynamic query-driven learning scheme.

PubMed

Chai, H; Zhang, J; Yang, G; Ma, Z

2016-11-15

DNA-binding proteins play a pivotal role in various biological activities. Identification of DNA-binding residues (DBRs) is of great importance for understanding the mechanism of gene regulations and chromatin remodeling. Most traditional computational methods usually construct their predictors on static non-redundant datasets. They excluded many homologous DNA-binding proteins so as to guarantee the generalization capability of their models. However, those ignored samples may potentially provide useful clues when studying protein-DNA interactions, which have not obtained enough attention. In view of this, we propose a novel method, namely DQPred-DBR, to fill the gap of DBR predictions. First, a large-scale extensible sample pool was compiled. Second, evolution-based features in the form of a relative position specific score matrix and covariant evolutionary conservation descriptors were used to encode the feature space. Third, a dynamic query-driven learning scheme was designed to make more use of proteins with known structure and functions. In comparison with a traditional static model, the introduction of dynamic models could obviously improve the prediction performance. Experimental results from the benchmark and independent datasets proved that our DQPred-DBR had promising generalization capability. It was capable of producing decent predictions and outperforms many state-of-the-art methods. For the convenience of academic use, our proposed method was also implemented as a web server at .

Advancing neuroscience through epigenetics: molecular mechanisms of learning and memory.

PubMed

Molfese, David L

2011-01-01

Humans share 96% of our 30,000 genes with Chimpanzees. The 1,200 genes that differ appear at first glance insufficient to describe what makes us human and them apes. However, we are now discovering that the mechanisms that regulate how genes are expressed tell a much richer story than our DNA alone. Sections of our DNA are constantly being turned on or off, marked for easy access, or secluded and hidden away, all in response to ongoing cellular activity. In the brain, neurons encode information-in effect memories-at the cellular level. Yet while memories may last a lifetime, neurons are dynamic structures. Every protein in the synapse undergoes some form of turnover, some with half-lives of only hours. How can a memory persist beyond the lifetimes of its constitutive molecular building blocks? Epigenetics-changes in gene expression that do not alter the underlying DNA sequence-may be the answer. In this article, epigenetic mechanisms including DNA methylation and acetylation or methylation of the histone proteins that package DNA are described in the context of animal learning. Through the interaction of these modifications a "histone code" is emerging wherein individual memories leave unique memory traces at the molecular level with distinct time courses. A better understanding of these mechanisms has implications for treatment of memory disorders caused by normal aging or diseases including schizophrenia, Alzheimer's, depression, and drug addiction.

Improved Prediction of Non-methylated Islands in Vertebrates Highlights Different Characteristic Sequence Patterns

PubMed Central

Vingron, Martin

2016-01-01

Non-methylated islands (NMIs) of DNA are genomic regions that are important for gene regulation and development. A recent study of genome-wide non-methylation data in vertebrates by Long et al. (eLife 2013;2:e00348) has shown that many experimentally identified non-methylated regions do not overlap with classically defined CpG islands which are computationally predicted using simple DNA sequence features. This is especially true in cold-blooded vertebrates such as Danio rerio (zebrafish). In order to investigate how predictive DNA sequence is of a region’s methylation status, we applied a supervised learning approach using a spectrum kernel support vector machine, to see if a more complex model and supervised learning can be used to improve non-methylated island prediction and to understand the sequence properties of these regions. We demonstrate that DNA sequence is highly predictive of methylation status, and that in contrast to existing CpG island prediction methods our method is able to provide more useful predictions of NMIs genome-wide in all vertebrate organisms that were studied. Our results also show that in cold-blooded vertebrates (Anolis carolinensis, Xenopus tropicalis and Danio rerio) where genome-wide classical CpG island predictions consist primarily of false positives, longer primarily AT-rich DNA sequence features are able to identify these regions much more accurately. PMID:27984582

NF-κB mediates Gadd45β expression and DNA demethylation in the hippocampus during fear memory formation.

PubMed

Jarome, Timothy J; Butler, Anderson A; Nichols, Jessica N; Pacheco, Natasha L; Lubin, Farah D

2015-01-01

Gadd45-mediated DNA demethylation mechanisms have been implicated in the process of memory formation. However, the transcriptional mechanisms involved in the regulation of Gadd45 gene expression during memory formation remain unexplored. NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells) controls transcription of genes in neurons and is a critical regulator of synaptic plasticity and memory formation. In silico analysis revealed several NF-κB (p65/RelA and cRel) consensus sequences within the Gadd45β gene promoter. Whether NF-κB activity regulates Gadd45 expression and associated DNA demethylation in neurons during memory formation is unknown. Here, we found that learning in a fear conditioning paradigm increased Gadd45β gene expression and brain-derivedneurotrophic factor (BDNF) DNA demethylation in area CA1 of the hippocampus, both of which were prevented with pharmacological inhibition of NF-κB activity. Further experiments found that conditional mutations in p65/RelA impaired fear memory formation but did not alter changes in Gadd45β expression. The learning-induced increases in Gadd45β mRNA levels, Gadd45β binding at the BDNF gene and BDNF DNA demethylation were blocked in area CA1 of the c-rel knockout mice. Additionally, local siRNA-mediated knockdown of c-rel in area CA1 prevented fear conditioning-induced increases in Gadd45β expression and BDNF DNA demethylation, suggesting that c-Rel containing NF-κB transcription factor complex is responsible for Gadd45β regulation during memory formation. Together, these results support a novel transcriptional role for NF-κB in regulation of Gadd45β expression and DNA demethylation in hippocampal neurons during fear memory.

A Novel Computational Method for Detecting DNA Methylation Sites with DNA Sequence Information and Physicochemical Properties.

PubMed

Pan, Gaofeng; Jiang, Limin; Tang, Jijun; Guo, Fei

2018-02-08

DNA methylation is an important biochemical process, and it has a close connection with many types of cancer. Research about DNA methylation can help us to understand the regulation mechanism and epigenetic reprogramming. Therefore, it becomes very important to recognize the methylation sites in the DNA sequence. In the past several decades, many computational methods-especially machine learning methods-have been developed since the high-throughout sequencing technology became widely used in research and industry. In order to accurately identify whether or not a nucleotide residue is methylated under the specific DNA sequence context, we propose a novel method that overcomes the shortcomings of previous methods for predicting methylation sites. We use k -gram, multivariate mutual information, discrete wavelet transform, and pseudo amino acid composition to extract features, and train a sparse Bayesian learning model to do DNA methylation prediction. Five criteria-area under the receiver operating characteristic curve (AUC), Matthew's correlation coefficient (MCC), accuracy (ACC), sensitivity (SN), and specificity-are used to evaluate the prediction results of our method. On the benchmark dataset, we could reach 0.8632 on AUC, 0.8017 on ACC, 0.5558 on MCC, and 0.7268 on SN. Additionally, the best results on two scBS-seq profiled mouse embryonic stem cells datasets were 0.8896 and 0.9511 by AUC, respectively. When compared with other outstanding methods, our method surpassed them on the accuracy of prediction. The improvement of AUC by our method compared to other methods was at least 0.0399 . For the convenience of other researchers, our code has been uploaded to a file hosting service, and can be downloaded from: https://figshare.com/s/0697b692d802861282d3.

Interactive Roles of DNA Helicases and Translocases with the Single-Stranded DNA Binding Protein RPA in Nucleic Acid Metabolism.

PubMed

Awate, Sanket; Brosh, Robert M

2017-06-08

Helicases and translocases use the energy of nucleoside triphosphate binding and hydrolysis to unwind/resolve structured nucleic acids or move along a single-stranded or double-stranded polynucleotide chain, respectively. These molecular motors facilitate a variety of transactions including replication, DNA repair, recombination, and transcription. A key partner of eukaryotic DNA helicases/translocases is the single-stranded DNA binding protein Replication Protein A (RPA). Biochemical, genetic, and cell biological assays have demonstrated that RPA interacts with these human molecular motors physically and functionally, and their association is enriched in cells undergoing replication stress. The roles of DNA helicases/translocases are orchestrated with RPA in pathways of nucleic acid metabolism. RPA stimulates helicase-catalyzed DNA unwinding, enlists translocases to sites of action, and modulates their activities in DNA repair, fork remodeling, checkpoint activation, and telomere maintenance. The dynamic interplay between DNA helicases/translocases and RPA is just beginning to be understood at the molecular and cellular levels, and there is still much to be learned, which may inform potential therapeutic strategies.

Interactive Roles of DNA Helicases and Translocases with the Single-Stranded DNA Binding Protein RPA in Nucleic Acid Metabolism

PubMed Central

Awate, Sanket; Brosh, Robert M.

2017-01-01

Helicases and translocases use the energy of nucleoside triphosphate binding and hydrolysis to unwind/resolve structured nucleic acids or move along a single-stranded or double-stranded polynucleotide chain, respectively. These molecular motors facilitate a variety of transactions including replication, DNA repair, recombination, and transcription. A key partner of eukaryotic DNA helicases/translocases is the single-stranded DNA binding protein Replication Protein A (RPA). Biochemical, genetic, and cell biological assays have demonstrated that RPA interacts with these human molecular motors physically and functionally, and their association is enriched in cells undergoing replication stress. The roles of DNA helicases/translocases are orchestrated with RPA in pathways of nucleic acid metabolism. RPA stimulates helicase-catalyzed DNA unwinding, enlists translocases to sites of action, and modulates their activities in DNA repair, fork remodeling, checkpoint activation, and telomere maintenance. The dynamic interplay between DNA helicases/translocases and RPA is just beginning to be understood at the molecular and cellular levels, and there is still much to be learned, which may inform potential therapeutic strategies. PMID:28594346

How to read and write mechanical information in DNA molecules

NASA Astrophysics Data System (ADS)

Schiessel, Helmut

In this talk I will show that DNA molecules contain another layer of information on top of the classical genetic information. This different type of information is of mechanical nature and guides the folding of DNA molecules inside cells. With the help of a new Monte Carlo technique, the Mutation Monte Carlo method, we demonstrate that the two layers of information can be multiplexed (as one can have two phone conversations on the same wire). For instance, we can guide on top of genes with single base-pair precision the packaging of DNA into nucleosomes. Finally, we study the mechanical properties of DNA molecules belonging to organisms all across the tree of life. From this we learn that in multicellular organisms the stiffness of DNA around transcription start sites differs dramatically from that of unicellular life. The reason for this difference is surprising.

Debating Whether Dinosaurs Should Be "Cloned" from Ancient DNA To Promote Cooperative Learning in an Introductory Evolution Course.

ERIC Educational Resources Information Center

Soja, Constance M.; Huerta, Deborah

2001-01-01

Describes an interactive internet exercise that enables students to engage in cooperative library and web research on a controversial topic in science, specifically the cloning of extinct lifeforms. Creates a dynamic learning environment in a large introductory geology course and demonstrates the importance of scientific literacy. (Author/SAH)

Learning about Inheritance in an Out-of-School Setting

ERIC Educational Resources Information Center

Dairianathan, Anne; Subramaniam, R.

2011-01-01

The purpose of this study was to investigate primary students' learning through participation in an out-of-school enrichment programme, held in a science centre, which focused on DNA and genes and whether participation in the programme led to an increased understanding of inheritance as well as promoted interest in the topic. The sample consisted…

WE-DE-202-02: Are Track Structure Simulations Truly Needed for Radiobiology at the Cellular and Tissue Levels?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stewart, R.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

WE-DE-202-00: Connecting Radiation Physics with Computational Biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

McMahon, S.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

[Epigenome: what we learned from Rett syndrome, a neurological disease caused by mutation of a methyl-CpG binding protein].

PubMed

Kubota, Takeo

2013-01-01

Epigenome is defined as DNA and histone modification-dependent gene regulation system. Abnormalities in this system are known to cause various neuro-developmental diseases. We recently reported that neurological symptoms of Rett syndrome, which is an autistic disorder caused by mutations in methyl-CpG binding protein 2 (MeCP2), was associated with failure of epigenomic gene regulation in neuronal cells, and that clinical differences in the identical twins with Rett syndrome in the differences in DNA methylation in neuronal genes, but not caused by DNA sequence differences. Since central nervus system requires precise gene regulation, neurological diseases including Alzheimer and Parkinson diseases may be caused by acquired DNA modification (epigenomic) changes that results in aberrant gene regulation as well as DNA sequence changes congenitally occurred (mutation).

Neuronal DNA Methyltransferases: Epigenetic Mediators between Synaptic Activity and Gene Expression?

PubMed Central

Bayraktar, Gonca; Kreutz, Michael R.

2017-01-01

DNMT3A and 3B are the main de novo DNA methyltransferases (DNMTs) in the brain that introduce new methylation marks to non-methylated DNA in postmitotic neurons. DNA methylation is a key epigenetic mark that is known to regulate important cellular processes in neuronal development and brain plasticity. Accumulating evidence disclosed rapid and dynamic changes in DNA methylation of plasticity-relevant genes that are important for learning and memory formation. To understand how DNMTs contribute to brain function and how they are regulated by neuronal activity is a prerequisite for a deeper appreciation of activity-dependent gene expression in health and disease. This review discusses the functional role of de novo methyltransferases and in particular DNMT3A1 in the adult brain with special emphasis on synaptic plasticity, memory formation, and brain disorders. PMID:28513272

Imbalanced class learning in epigenetics.

PubMed

Haque, M Muksitul; Skinner, Michael K; Holder, Lawrence B

2014-07-01

In machine learning, one of the important criteria for higher classification accuracy is a balanced dataset. Datasets with a large ratio between minority and majority classes face hindrance in learning using any classifier. Datasets having a magnitude difference in number of instances between the target concept result in an imbalanced class distribution. Such datasets can range from biological data, sensor data, medical diagnostics, or any other domain where labeling any instances of the minority class can be time-consuming or costly or the data may not be easily available. The current study investigates a number of imbalanced class algorithms for solving the imbalanced class distribution present in epigenetic datasets. Epigenetic (DNA methylation) datasets inherently come with few differentially DNA methylated regions (DMR) and with a higher number of non-DMR sites. For this class imbalance problem, a number of algorithms are compared, including the TAN+AdaBoost algorithm. Experiments performed on four epigenetic datasets and several known datasets show that an imbalanced dataset can have similar accuracy as a regular learner on a balanced dataset.

Student conceptions about the DNA structure within a hierarchical organizational level: Improvement by experiment- and computer-based outreach learning.

PubMed

Langheinrich, Jessica; Bogner, Franz X

2015-01-01

As non-scientific conceptions interfere with learning processes, teachers need both, to know about them and to address them in their classrooms. For our study, based on 182 eleventh graders, we analyzed the level of conceptual understanding by implementing the "draw and write" technique during a computer-supported gene technology module. To give participants the hierarchical organizational level which they have to draw, was a specific feature of our study. We introduced two objective category systems for analyzing drawings and inscriptions. Our results indicated a long- as well as a short-term increase in the level of conceptual understanding and in the number of drawn elements and their grades concerning the DNA structure. Consequently, we regard the "draw and write" technique as a tool for a teacher to get to know students' alternative conceptions. Furthermore, our study points the modification potential of hands-on and computer-supported learning modules. © 2015 The International Union of Biochemistry and Molecular Biology.

Drafting human ancestry: what does the Neanderthal genome tell us about hominid evolution? Commentary on Green et al. (2010).

PubMed

Hofreiter, Michael

2011-02-01

Ten years after the first draft versions of the human genome were announced, technical progress in both DNA sequencing and ancient DNA analyses has allowed a research team around Ed Green and Svante Pääbo to complete this task from infinitely more difficult hominid samples: a few pieces of bone originating from our closest, albeit extinct, relatives, the Neanderthals. Pulling the Neanderthal sequences out of a sea of contaminating environmental DNA impregnating the bones and at the same time avoiding the problems of contamination with modern human DNA is in itself a remarkable accomplishment. However, the crucial question in the long run is, what can we learn from such genomic data about hominid evolution?

Genomic resources for songbird research and their use in characterizing gene expression during brain development

PubMed Central

Li, XiaoChing; Wang, Xiu-Jie; Tannenhauser, Jonathan; Podell, Sheila; Mukherjee, Piali; Hertel, Moritz; Biane, Jeremy; Masuda, Shoko; Nottebohm, Fernando; Gaasterland, Terry

2007-01-01

Vocal learning and neuronal replacement have been studied extensively in songbirds, but until recently, few molecular and genomic tools for songbird research existed. Here we describe new molecular/genomic resources developed in our laboratory. We made cDNA libraries from zebra finch (Taeniopygia guttata) brains at different developmental stages. A total of 11,000 cDNA clones from these libraries, representing 5,866 unique gene transcripts, were randomly picked and sequenced from the 3′ ends. A web-based database was established for clone tracking, sequence analysis, and functional annotations. Our cDNA libraries were not normalized. Sequencing ESTs without normalization produced many developmental stage-specific sequences, yielding insights into patterns of gene expression at different stages of brain development. In particular, the cDNA library made from brains at posthatching day 30–50, corresponding to the period of rapid song system development and song learning, has the most diverse and richest set of genes expressed. We also identified five microRNAs whose sequences are highly conserved between zebra finch and other species. We printed cDNA microarrays and profiled gene expression in the high vocal center of both adult male zebra finches and canaries (Serinus canaria). Genes differentially expressed in the high vocal center were identified from the microarray hybridization results. Selected genes were validated by in situ hybridization. Networks among the regulated genes were also identified. These resources provide songbird biologists with tools for genome annotation, comparative genomics, and microarray gene expression analysis. PMID:17426146

On Docking, Scoring and Assessing Protein-DNA Complexes in a Rigid-Body Framework

PubMed Central

Parisien, Marc; Freed, Karl F.; Sosnick, Tobin R.

2012-01-01

We consider the identification of interacting protein-nucleic acid partners using the rigid body docking method FTdock, which is systematic and exhaustive in the exploration of docking conformations. The accuracy of rigid body docking methods is tested using known protein-DNA complexes for which the docked and undocked structures are both available. Additional tests with large decoy sets probe the efficacy of two published statistically derived scoring functions that contain a huge number of parameters. In contrast, we demonstrate that state-of-the-art machine learning techniques can enormously reduce the number of parameters required, thereby identifying the relevant docking features using a miniscule fraction of the number of parameters in the prior works. The present machine learning study considers a 300 dimensional vector (dependent on only 15 parameters), termed the Chemical Context Profile (CCP), where each dimension reflects a specific type of protein amino acid-nucleic acid base interaction. The CCP is designed to capture the chemical complementarities of the interface and is well suited for machine learning techniques. Our objective function is the Chemical Context Discrepancy (CCD), which is defined as the angle between the native system's CCP vector and the decoy's vector and which serves as a substitute for the more commonly used root mean squared deviation (RMSD). We demonstrate that the CCP provides a useful scoring function when certain dimensions are properly weighted. Finally, we explore how the amino acids on a protein's surface can help guide DNA binding, first through long-range interactions, followed by direct contacts, according to specific preferences for either the major or minor grooves of the DNA. PMID:22393431

Student Conceptions about the DNA Structure within a Hierarchical Organizational Level: Improvement by Experiment- and Computer-Based Outreach Learning

ERIC Educational Resources Information Center

Langheinrich, Jessica; Bogner, Franz X.

2015-01-01

As non-scientific conceptions interfere with learning processes, teachers need both, to know about them and to address them in their classrooms. For our study, based on 182 eleventh graders, we analyzed the level of conceptual understanding by implementing the "draw and write" technique during a computer-supported gene technology module.…

Performance of amplicon-based next generation DNA sequencing for diagnostic gene mutation profiling in oncopathology.

PubMed

Sie, Daoud; Snijders, Peter J F; Meijer, Gerrit A; Doeleman, Marije W; van Moorsel, Marinda I H; van Essen, Hendrik F; Eijk, Paul P; Grünberg, Katrien; van Grieken, Nicole C T; Thunnissen, Erik; Verheul, Henk M; Smit, Egbert F; Ylstra, Bauke; Heideman, Daniëlle A M

2014-10-01

Next generation DNA sequencing (NGS) holds promise for diagnostic applications, yet implementation in routine molecular pathology practice requires performance evaluation on DNA derived from routine formalin-fixed paraffin-embedded (FFPE) tissue specimens. The current study presents a comprehensive analysis of TruSeq Amplicon Cancer Panel-based NGS using a MiSeq Personal sequencer (TSACP-MiSeq-NGS) for somatic mutation profiling. TSACP-MiSeq-NGS (testing 212 hotspot mutation amplicons of 48 genes) and a data analysis pipeline were evaluated in a retrospective learning/test set approach (n = 58/n = 45 FFPE-tumor DNA samples) against 'gold standard' high-resolution-melting (HRM)-sequencing for the genes KRAS, EGFR, BRAF and PIK3CA. Next, the performance of the validated test algorithm was assessed in an independent, prospective cohort of FFPE-tumor DNA samples (n = 75). In the learning set, a number of minimum parameter settings was defined to decide whether a FFPE-DNA sample is qualified for TSACP-MiSeq-NGS and for calling mutations. The resulting test algorithm revealed 82% (37/45) compliance to the quality criteria and 95% (35/37) concordant assay findings for KRAS, EGFR, BRAF and PIK3CA with HRM-sequencing (kappa = 0.92; 95% CI = 0.81-1.03) in the test set. Subsequent application of the validated test algorithm to the prospective cohort yielded a success rate of 84% (63/75), and a high concordance with HRM-sequencing (95% (60/63); kappa = 0.92; 95% CI = 0.84-1.01). TSACP-MiSeq-NGS detected 77 mutations in 29 additional genes. TSACP-MiSeq-NGS is suitable for diagnostic gene mutation profiling in oncopathology.

Accelerated age-related cognitive decline and neurodegeneration, caused by deficient DNA repair.

PubMed

Borgesius, Nils Z; de Waard, Monique C; van der Pluijm, Ingrid; Omrani, Azar; Zondag, Gerben C M; van der Horst, Gijsbertus T J; Melton, David W; Hoeijmakers, Jan H J; Jaarsma, Dick; Elgersma, Ype

2011-08-31

Age-related cognitive decline and neurodegenerative diseases are a growing challenge for our societies with their aging populations. Accumulation of DNA damage has been proposed to contribute to these impairments, but direct proof that DNA damage results in impaired neuronal plasticity and memory is lacking. Here we take advantage of Ercc1(Δ/-) mutant mice, which are impaired in DNA nucleotide excision repair, interstrand crosslink repair, and double-strand break repair. We show that these mice exhibit an age-dependent decrease in neuronal plasticity and progressive neuronal pathology, suggestive of neurodegenerative processes. A similar phenotype is observed in mice where the mutation is restricted to excitatory forebrain neurons. Moreover, these neuron-specific mutants develop a learning impairment. Together, these results suggest a causal relationship between unrepaired, accumulating DNA damage, and age-dependent cognitive decline and neurodegeneration. Hence, accumulated DNA damage could therefore be an important factor in the onset and progression of age-related cognitive decline and neurodegenerative diseases.

The biochemical basis of microsatellite instability and abnormal immunohistochemistry and clinical behavior in Lynch Syndrome: from bench to bedside

PubMed Central

Koi, Minoru; Chang, Dong K.; Carethers, John M.

2010-01-01

Lynch syndrome is an inherited disease caused by a germline mutation in one of four DNA mismatch repair (MMR) genes. The clinical manifestations can be somewhat variable depending upon which gene is involved, and where the mutation occurs. Moreover, the approach to the diagnosis of Lynch syndrome is becoming more complex as more is learned about the disease, and one needs to understand how the DNA MMR proteins function, and what makes them malfunction, to have an optimal appreciation of how to interpret diagnostic studies such as microsatellite instability and immunohistochemistry of the DNA MMR proteins. Finally, an understanding of the role of the DNA MMR system in regulation of the cell cycle and the response to DNA damage helps illuminate the differences in natural history and response to chemotherapeutic agents seen in Lynch syndrome. PMID:17636426

Cockayne syndrome group A and B proteins converge on transcription-linked resolution of non-B DNA.

PubMed

Scheibye-Knudsen, Morten; Tseng, Anne; Borch Jensen, Martin; Scheibye-Alsing, Karsten; Fang, Evandro Fei; Iyama, Teruaki; Bharti, Sanjay Kumar; Marosi, Krisztina; Froetscher, Lynn; Kassahun, Henok; Eckley, David Mark; Maul, Robert W; Bastian, Paul; De, Supriyo; Ghosh, Soumita; Nilsen, Hilde; Goldberg, Ilya G; Mattson, Mark P; Wilson, David M; Brosh, Robert M; Gorospe, Myriam; Bohr, Vilhelm A

2016-11-01

Cockayne syndrome is a neurodegenerative accelerated aging disorder caused by mutations in the CSA or CSB genes. Although the pathogenesis of Cockayne syndrome has remained elusive, recent work implicates mitochondrial dysfunction in the disease progression. Here, we present evidence that loss of CSA or CSB in a neuroblastoma cell line converges on mitochondrial dysfunction caused by defects in ribosomal DNA transcription and activation of the DNA damage sensor poly-ADP ribose polymerase 1 (PARP1). Indeed, inhibition of ribosomal DNA transcription leads to mitochondrial dysfunction in a number of cell lines. Furthermore, machine-learning algorithms predict that diseases with defects in ribosomal DNA (rDNA) transcription have mitochondrial dysfunction, and, accordingly, this is found when factors involved in rDNA transcription are knocked down. Mechanistically, loss of CSA or CSB leads to polymerase stalling at non-B DNA in a neuroblastoma cell line, in particular at G-quadruplex structures, and recombinant CSB can melt G-quadruplex structures. Indeed, stabilization of G-quadruplex structures activates PARP1 and leads to accelerated aging in Caenorhabditis elegans In conclusion, this work supports a role for impaired ribosomal DNA transcription in Cockayne syndrome and suggests that transcription-coupled resolution of secondary structures may be a mechanism to repress spurious activation of a DNA damage response.

Is DNA Alive? A Study of Conceptual Change Through Targeted Instruction

NASA Astrophysics Data System (ADS)

Witzig, Stephen B.; Freyermuth, Sharyn K.; Siegel, Marcelle A.; Izci, Kemal; Pires, J. Chris

2013-08-01

We are involved in a project to incorporate innovative assessments within a reform-based large-lecture biochemistry course for nonmajors. We not only assessed misconceptions but purposefully changed instruction throughout the semester to confront student ideas. Our research questions targeted student conceptions of deoxyribonucleic acid (DNA) along with understanding in what ways classroom discussions/activities influence student conceptions. Data sources included pre-/post-assessments, semi-structured interviews, and student work on exams/assessments. We found that students held misconceptions about the chemical nature of DNA, with 63 % of students claiming that DNA is alive prior to instruction. The chemical nature of DNA is an important fundamental concept in science fields. We confronted this misconception throughout the semester collecting data from several instructional interventions. Case studies of individual students revealed how various instructional strategies/assessments allowed students to construct and demonstrate the scientifically accepted understanding of the chemical nature of DNA. However, the post-assessment exposed that 40 % of students still held misconceptions about DNA, indicating the persistent nature of this misconception. Implications for teaching and learning are discussed.

An Introduction to Topic Modeling as an Unsupervised Machine Learning Way to Organize Text Information

ERIC Educational Resources Information Center

Snyder, Robin M.

2015-01-01

The field of topic modeling has become increasingly important over the past few years. Topic modeling is an unsupervised machine learning way to organize text (or image or DNA, etc.) information such that related pieces of text can be identified. This paper/session will present/discuss the current state of topic modeling, why it is important, and…

Digital Academic Revolution Mentorship Competency: #1 The Declaration--Mentoring the Process of Learning with Screencast Assessment--Plugging into Students' Digital DNA a Decade Later

ERIC Educational Resources Information Center

Mehl, Martin; Fose, Luanne

2016-01-01

Spanning the 2015-2016 academic year, Cal Poly Communications Studies Sr. Lecturer, Martin Mehl, and Lead Instructional Designer, Luanne Fose, from the Cal Poly Center for Teaching, Learning, and Technology, conducted a formal, institute-wide research pilot on whether or not video assessment can improve faculty feedback for student assignments.…

Molecular Mechanistic Reasoning: Toward Bridging the Gap between the Molecular and Cellular Levels in Life Science Education

ERIC Educational Resources Information Center

van Mil, Marc H. W.; Postma, Paulien A.; Boerwinkel, Dirk Jan; Klaassen, Kees; Waarlo, Arend Jan

2016-01-01

Although learning about DNA, RNA, and proteins is part of the upper secondary biology curriculum in most countries, many studies report that students fail to connect molecular knowledge to phenomena at the higher level of cells, organs, and organisms. As a result, many students use memorization and rote learning as a coping strategy when presented…

A bispectral q-hypergeometric basis for a class of quantum integrable models

NASA Astrophysics Data System (ADS)

Baseilhac, Pascal; Martin, Xavier

2018-01-01

For the class of quantum integrable models generated from the q-Onsager algebra, a basis of bispectral multivariable q-orthogonal polynomials is exhibited. In the first part, it is shown that the multivariable Askey-Wilson polynomials with N variables and N + 3 parameters introduced by Gasper and Rahman [Dev. Math. 13, 209 (2005)] generate a family of infinite dimensional modules for the q-Onsager algebra, whose fundamental generators are realized in terms of the multivariable q-difference and difference operators proposed by Iliev [Trans. Am. Math. Soc. 363, 1577 (2011)]. Raising and lowering operators extending those of Sahi [SIGMA 3, 002 (2007)] are also constructed. In the second part, finite dimensional modules are constructed and studied for a certain class of parameters and if the N variables belong to a discrete support. In this case, the bispectral property finds a natural interpretation within the framework of tridiagonal pairs. In the third part, eigenfunctions of the q-Dolan-Grady hierarchy are considered in the polynomial basis. In particular, invariant subspaces are identified for certain conditions generalizing Nepomechie's relations. In the fourth part, the analysis is extended to the special case q = 1. This framework provides a q-hypergeometric formulation of quantum integrable models such as the open XXZ spin chain with generic integrable boundary conditions (q ≠ 1).

Toward a Multi-scale Phase Transition Kinetics Methodology: From Non-Equilibrium Statistical Mechanics to Hydrodynamics

NASA Astrophysics Data System (ADS)

Belof, Jonathan; Orlikowski, Daniel; Wu, Christine; McLaughlin, Keith

2013-06-01

Shock and ramp compression experiments are allowing us to probe condensed matter under extreme conditions where phase transitions and other non-equilibrium aspects can now be directly observed, but first principles simulation of kinetics remains a challenge. A multi-scale approach is presented here, with non-equilibrium statistical mechanical quantities calculated by molecular dynamics (MD) and then leveraged to inform a classical nucleation and growth kinetics model at the hydrodynamic scale. Of central interest is the free energy barrier for the formation of a critical nucleus, with direct NEMD presenting the challenge of relatively long timescales necessary to resolve nucleation. Rather than attempt to resolve the time-dependent nucleation sequence directly, the methodology derived here is built upon the non-equilibrium work theorem in order to bias the formation of a critical nucleus and thus construct the nucleation and growth rates. Having determined these kinetic terms from MD, a hydrodynamics implementation of Kolmogorov-Johnson-Mehl-Avrami (KJMA) kinetics and metastabilty is applied to the dynamic compressive freezing of water and compared with recent ramp compression experiments [Dolan et al., Nature (2007)] Lawrence Livermore National Laboratory is operated by Lawrence Livermore National Security, LLC, for the U.S. Department of Energy, National Nuclear Security Administration under Contract DE-AC52-07NA27344.

What Is Genetic Ancestry Testing?

MedlinePlus

... what they can learn from relatives or from historical documentation. Examination of DNA variations can provide clues ... female ancestors that may be lost from the historical record because of the way surnames are often ...

Sequence2Vec: a novel embedding approach for modeling transcription factor binding affinity landscape.

PubMed

Dai, Hanjun; Umarov, Ramzan; Kuwahara, Hiroyuki; Li, Yu; Song, Le; Gao, Xin

2017-11-15

An accurate characterization of transcription factor (TF)-DNA affinity landscape is crucial to a quantitative understanding of the molecular mechanisms underpinning endogenous gene regulation. While recent advances in biotechnology have brought the opportunity for building binding affinity prediction methods, the accurate characterization of TF-DNA binding affinity landscape still remains a challenging problem. Here we propose a novel sequence embedding approach for modeling the transcription factor binding affinity landscape. Our method represents DNA binding sequences as a hidden Markov model which captures both position specific information and long-range dependency in the sequence. A cornerstone of our method is a novel message passing-like embedding algorithm, called Sequence2Vec, which maps these hidden Markov models into a common nonlinear feature space and uses these embedded features to build a predictive model. Our method is a novel combination of the strength of probabilistic graphical models, feature space embedding and deep learning. We conducted comprehensive experiments on over 90 large-scale TF-DNA datasets which were measured by different high-throughput experimental technologies. Sequence2Vec outperforms alternative machine learning methods as well as the state-of-the-art binding affinity prediction methods. Our program is freely available at https://github.com/ramzan1990/sequence2vec. xin.gao@kaust.edu.sa or lsong@cc.gatech.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Affordable hands-on DNA sequencing and genotyping: an exercise for teaching DNA analysis to undergraduates.

PubMed

Shah, Kushani; Thomas, Shelby; Stein, Arnold

2013-01-01

In this report, we describe a 5-week laboratory exercise for undergraduate biology and biochemistry students in which students learn to sequence DNA and to genotype their DNA for selected single nucleotide polymorphisms (SNPs). Students use miniaturized DNA sequencing gels that require approximately 8 min to run. The students perform G, A, T, C Sanger sequencing reactions. They prepare and run the gels, perform Southern blots (which require only 10 min), and detect sequencing ladders using a colorimetric detection system. Students enlarge their sequencing ladders from digital images of their small nylon membranes, and read the sequence manually. They compare their reads with the actual DNA sequence using BLAST2. After mastering the DNA sequencing system, students prepare their own DNA from a cheek swab, polymerase chain reaction-amplify a region of their DNA that encompasses a SNP of interest, and perform sequencing to determine their genotype at the SNP position. A family pedigree can also be constructed. The SNP chosen by the instructor was rs17822931, which is in the ABCC11 gene and is the determinant of human earwax type. Genotypes at the rs178229931 site vary in different ethnic populations. © 2013 by The International Union of Biochemistry and Molecular Biology.

A comprehensive experiment for molecular biology: Determination of single nucleotide polymorphism in human REV3 gene using PCR-RFLP.

PubMed

Zhang, Xu; Shao, Meng; Gao, Lu; Zhao, Yuanyuan; Sun, Zixuan; Zhou, Liping; Yan, Yongmin; Shao, Qixiang; Xu, Wenrong; Qian, Hui

2017-07-08

Laboratory exercise is helpful for medical students to understand the basic principles of molecular biology and to learn about the practical applications of molecular biology. We have designed a lab course on molecular biology about the determination of single nucleotide polymorphism (SNP) in human REV3 gene, the product of which is a subunit of DNA polymerase ζ and SNPs in this gene are associated with altered susceptibility to cancer. This newly designed experiment is composed of three parts, including genomic DNA extraction, gene amplification by PCR, and genotyping by RFLP. By combining these activities, the students are not only able to learn a series of biotechniques in molecular biology, but also acquire the ability to link the learned knowledge with practical applications. This comprehensive experiment will help the medical students improve the conceptual understanding of SNP and the technical understanding of SNP detection. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(4):299-304, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

In the loop: how chromatin topology links genome structure to function in mechanisms underlying learning and memory.

PubMed

Watson, L Ashley; Tsai, Li-Huei

2017-04-01

Different aspects of learning, memory, and cognition are regulated by epigenetic mechanisms such as covalent DNA modifications and histone post-translational modifications. More recently, the modulation of chromatin architecture and nuclear organization is emerging as a key factor in dynamic transcriptional regulation of the post-mitotic neuron. For instance, neuronal activity induces relocalization of gene loci to 'transcription factories', and specific enhancer-promoter looping contacts allow for precise transcriptional regulation. Moreover, neuronal activity-dependent DNA double-strand break formation in the promoter of immediate early genes appears to overcome topological constraints on transcription. Together, these findings point to a critical role for genome topology in integrating dynamic environmental signals to define precise spatiotemporal gene expression programs supporting cognitive processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cervical Cancer Screening (PDQ®)—Patient Version

Cancer.gov

Cervical cancer screening tests (e.g., the Papanicolaou (Pap) Test, HPV DNA, Thin-prep) find cervical changes before cancer develops. Learn more about the potential benefits and harms of these tests in this expert-reviewed summary.

San Diego Supercomputer Center

Science.gov Websites

Nile and Zika virusLearn More image Variants in Non-Coding DNA Contribute to Inherited Autism RiskGene mutations appearing for the first time contribute to approximately one-third of cases of autism spectrum

Genetics Home Reference: RNAse T2-deficient leukoencephalopathy

MedlinePlus

... abundant in the brain. Ribonucleases help break down RNA, a chemical cousin of DNA. Studies suggest that ... in angiogenesis or an immune system response to RNA that has not been properly broken down. Learn ...

Duplication of the genome in normal and cancer cell cycles.

PubMed

Bandura, Jennifer L; Calvi, Brian R

2002-01-01

It is critical to discover the mechanisms of normal cell cycle regulation if we are to fully understand what goes awry in cancer cells. The normal eukaryotic cell tightly regulates the activity of origins of DNA replication so that the genome is duplicated exactly once per cell cycle. Over the last ten years much has been learned concerning the cell cycle regulation of origin activity. It is now clear that the proteins and cell cycle mechanisms that control origin activity are largely conserved from yeast to humans. Despite this conservation, the composition of origins of DNA replication in higher eukaryotes remains ill defined. A DNA consensus for predicting origins has yet to emerge, and it is of some debate whether primary DNA sequence determines where replication initiates. In this review we outline what is known about origin structure and the mechanism of once per cell cycle DNA replication with an emphasis on recent advances in mammalian cells. We discuss the possible relevance of these regulatory pathways for cancer biology and therapy.

DNA polymerase γ and disease: what we have learned from yeast

PubMed Central

Lodi, Tiziana; Dallabona, Cristina; Nolli, Cecilia; Goffrini, Paola; Donnini, Claudia; Baruffini, Enrico

2015-01-01

Mip1 is the Saccharomyces cerevisiae DNA polymerase γ (Pol γ), which is responsible for the replication of mitochondrial DNA (mtDNA). It belongs to the family A of the DNA polymerases and it is orthologs to human POLGA. In humans, mutations in POLG(1) cause many mitochondrial pathologies, such as progressive external ophthalmoplegia (PEO), Alpers' syndrome, and ataxia-neuropathy syndrome, all of which present instability of mtDNA, which results in impaired mitochondrial function in several tissues with variable degrees of severity. In this review, we summarize the genetic and biochemical knowledge published on yeast mitochondrial DNA polymerase from 1989, when the MIP1 gene was first cloned, up until now. The role of yeast is particularly emphasized in (i) validating the pathological mutations found in human POLG and modeled in MIP1, (ii) determining the molecular defects caused by these mutations and (iii) finding the correlation between mutations/polymorphisms in POLGA and mtDNA toxicity induced by specific drugs. We also describe recent findings regarding the discovery of molecules able to rescue the phenotypic defects caused by pathological mutations in Mip1, and the construction of a model system in which the human Pol γ holoenzyme is expressed in yeast and complements the loss of Mip1. PMID:25852747

Colorectal Cancer Screening (PDQ®)—Patient Version

Cancer.gov

There are five types of tests that are used to screen for colorectal cancer: fecal occult blood test, sigmoidoscopy, colonoscopy, virtual colonoscopy, and DNA stool test. Learn more about these and other tests in this expert-reviewed summary.

Whole Genome Sequencing

MedlinePlus

... exons, the parts of DNA that code for proteins in the body. Researchers like this method because it is faster and cheaper. Learn More More still needs to be done before whole genome sequencing becomes a routine part of medical care. Many ...

Leadership DNA: The Ford Motor Story.

ERIC Educational Resources Information Center

Friedman, Stewart D.

2001-01-01

The Ford Motor Company invested in transformational leadership to change itself. Programs center around core principles: adopt a transformational mindset, use action learning, leverage the power of electronic tools, integrate work and life, and generate business impact. (JOW)

Carcinogenicity of ambient air pollution: use of biomarkers, lessons learnt and future directions

PubMed Central

Vineis, Paolo

2015-01-01

The association between ambient air pollution (AAP) exposure and lung cancer risk has been investigated in prospective studies and the results are generally consistent, indicating that long-term exposure to air pollution can cause lung cancer. Biomarkers can enhance research on the health effects of air pollution by improving exposure assessment, increasing the understanding of mechanisms, and enabling the investigation of individual susceptibility. In this review, we assess DNA adducts as biomarkers of exposure to AAP and early biological effect, and DNA methylation as biomarker of early biological change and discuss critical issues arising from their incorporation in AAP health impact evaluations, such as confounding, individual susceptibilities, timing, intensity and duration of exposure, and investigated tissue. DNA adducts and DNA methylation are treated as paradigms. However, the lessons, learned from their use in the examination of AAP carcinogenicity, can be applied to investigations of other biomarkers involved in AAP carcinogenicity. PMID:25694819

Investigations of Escherichia coli promoter sequences with artificial neural networks: New signals discovered upstream of the transcriptional startpoint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pedersen, A.G.; Engelbrecht, J.

1995-12-31

In this paper we present a novel method for using the learning ability of a neural network as a measure of information in local regions of input data. Using the method to analyze Escherichia coli promoters, we discover all previously described signals, and furthermore find new signals that are regularly spaced along the promoter region. The spacing of all signals correspond to the helical periodicity of DNA, meaning that the signals are all present on the same face of the DNA helix in the promoter region. This is consistent with a model where the RNA polymerase contacts the promoter onmore » one side of the DNA, and suggests that the regions important for promoter recognition may include more positions on the DNA than usually assumed. We furthermore analyze the E.coli promoters by calculating the Kullback Leibler distance, and by constructing sequence logos.« less

A parallelized binary search tree

USDA-ARS?s Scientific Manuscript database

PTTRNFNDR is an unsupervised statistical learning algorithm that detects patterns in DNA sequences, protein sequences, or any natural language texts that can be decomposed into letters of a finite alphabet. PTTRNFNDR performs complex mathematical computations and its processing time increases when i...

Genetics by the Numbers

MedlinePlus

... Inside Life Science > Genetics by the Numbers Inside Life Science View All Articles | Inside Life Science Home Page Genetics by the Numbers By Chelsea ... New Genetics NIH's National DNA Day This Inside Life Science article also appears on LiveScience . Learn about related ...

Problem-based learning in an on-line biotechnology course

NASA Astrophysics Data System (ADS)

Cheaney, James Daniel

Problem-based learning (PBL) is a pedagogical tool that uses a "real world" problem or situation as a context for learning. PBL encourages student development of critical thinking skills, a high professional competency, problem-solving ability, knowledge acquisition, the ability to work productively as a team member and make decisions in unfamiliar situations, and the acquisition of skills that support self-directed life-long learning, metacognition, and adaptation to change. However, little research has focused on the use of PBL in on-line "virtual" classes. We conducted two studies exploring the use of PBL in an on-line biotechnology course. In the first study, ethical, legal, social, and human issues were used as a motivation for learning about DNA testing technologies, applications, and bioethical issues. In the second study, we combined PBL pedagogy with a rich multimedia environment of streaming video interviews, physical artifacts, and extensive links to articles and databases to create a multidimensional immersive PBL environment called "Robert's World". In "Robert's World", a man is determining whether to undergo a pre-symptomatic DNA test for an untreatable, incurable, fatal genetic disease for which he has a family history. In both studies, design and implementation issues of the on-line PBL environment are discussed, as are differences between on-line PBL and face-to-face PBL. Both studies provide evidence to suggest that PBL stimulates higher-order learning in students. However, in both studies, student performance on an exam testing acquisition of lower-order factual learning was lower for PBL students than for students who learned the same material through a traditional lecture-based approach. Possible reasons for this lower level of performance are explored. Student feedback expressed engagement with the issues and material covered, with reservations about some aspects of the PBL format, such as the lack of flexibility provided in cooperative learning. We conclude that on-line PBL is a powerful tool in helping to develop higher-order learning in students. The reasons for the decrease in student understanding of factual information are unclear. However, there are certain circumstances unique to on-line classes to keep in mind when implementing on-line PBL. These are summarized in concluding recommendations.

Summer Workshop in Metagenomics: One Week Plus Eight Students Equals Gigabases of Cloned DNA †

PubMed Central

Rios-Velazquez, Carlos; Williamson, Lynn L.; Cloud-Hansen, Karen A.; Allen, Heather K.; McMahon, Mathew D.; Sabree, Zakee L.; Donato, Justin J.; Handelsman, Jo

2011-01-01

We designed a week-long laboratory workshop in metagenomics for a cohort of undergraduate student researchers. During this course, students learned and utilized molecular biology and microbiology techniques to construct a metagenomic library from Puerto Rican soil. Pre-and postworkshop assessments indicated student learning gains in technical knowledge, skills, and confidence in a research environment. Postworkshop construction of additional libraries demonstrated retention of research techniques by the students. PMID:23653755

Intelligence Virtual Analyst Capability: Governing Concepts and Science and Technology Roadmap

DTIC Science & Technology

2014-12-01

system’s perspective. That is to say : what is the information the user needs to achieve his tasks and objective; and what information does the system need...be able to learn from demonstration, which is to say by looking at examples of how a given task is usually performed. Learning is an important part...address, and phone number. Finally it can also include biometric and genetic information such as face attributes, fingerprints, handwriting , DNA. Time

Epigenetic regulation and chromatin remodeling in learning and memory.

PubMed

Kim, Somi; Kaang, Bong-Kiun

2017-01-13

Understanding the underlying mechanisms of memory formation and maintenance has been a major goal in the field of neuroscience. Memory formation and maintenance are tightly controlled complex processes. Among the various processes occurring at different levels, gene expression regulation is especially crucial for proper memory processing, as some genes need to be activated while some genes must be suppressed. Epigenetic regulation of the genome involves processes such as DNA methylation and histone post-translational modifications. These processes edit genomic properties or the interactions between the genome and histone cores. They then induce structural changes in the chromatin and lead to transcriptional changes of different genes. Recent studies have focused on the concept of chromatin remodeling, which consists of 3D structural changes in chromatin in relation to gene regulation, and is an important process in learning and memory. In this review, we will introduce three major epigenetic processes involved in memory regulation: DNA methylation, histone methylation and histone acetylation. We will also discuss general mechanisms of long-term memory storage and relate the epigenetic control of learning and memory to chromatin remodeling. Finally, we will discuss how epigenetic mechanisms can contribute to the pathologies of neurological disorders and cause memory-related symptoms.

High Throughput Measurement of Extracellular DNA Release and Quantitative NET Formation in Human Neutrophils In Vitro.

PubMed

Sil, Payel; Yoo, Dae-Goon; Floyd, Madison; Gingerich, Aaron; Rada, Balazs

2016-06-18

Neutrophil granulocytes are the most abundant leukocytes in the human blood. Neutrophils are the first to arrive at the site of infection. Neutrophils developed several antimicrobial mechanisms including phagocytosis, degranulation and formation of neutrophil extracellular traps (NETs). NETs consist of a DNA scaffold decorated with histones and several granule markers including myeloperoxidase (MPO) and human neutrophil elastase (HNE). NET release is an active process involving characteristic morphological changes of neutrophils leading to expulsion of their DNA into the extracellular space. NETs are essential to fight microbes, but uncontrolled release of NETs has been associated with several disorders. To learn more about the clinical relevance and the mechanism of NET formation, there is a need to have reliable tools capable of NET quantitation. Here three methods are presented that can assess NET release from human neutrophils in vitro. The first one is a high throughput assay to measure extracellular DNA release from human neutrophils using a membrane impermeable DNA-binding dye. In addition, two other methods are described capable of quantitating NET formation by measuring levels of NET-specific MPO-DNA and HNE-DNA complexes. These microplate-based methods in combination provide great tools to efficiently study the mechanism and regulation of NET formation of human neutrophils.

Genomics dataset on unclassified published organism (patent US 7547531).

PubMed

Khan Shawan, Mohammad Mahfuz Ali; Hasan, Md Ashraful; Hossain, Md Mozammel; Hasan, Md Mahmudul; Parvin, Afroza; Akter, Salina; Uddin, Kazi Rasel; Banik, Subrata; Morshed, Mahbubul; Rahman, Md Nazibur; Rahman, S M Badier

2016-12-01

Nucleotide (DNA) sequence analysis provides important clues regarding the characteristics and taxonomic position of an organism. With the intention that, DNA sequence analysis is very crucial to learn about hierarchical classification of that particular organism. This dataset (patent US 7547531) is chosen to simplify all the complex raw data buried in undisclosed DNA sequences which help to open doors for new collaborations. In this data, a total of 48 unidentified DNA sequences from patent US 7547531 were selected and their complete sequences were retrieved from NCBI BioSample database. Quick response (QR) code of those DNA sequences was constructed by DNA BarID tool. QR code is useful for the identification and comparison of isolates with other organisms. AT/GC content of the DNA sequences was determined using ENDMEMO GC Content Calculator, which indicates their stability at different temperature. The highest GC content was observed in GP445188 (62.5%) which was followed by GP445198 (61.8%) and GP445189 (59.44%), while lowest was in GP445178 (24.39%). In addition, New England BioLabs (NEB) database was used to identify cleavage code indicating the 5, 3 and blunt end and enzyme code indicating the methylation site of the DNA sequences was also shown. These data will be helpful for the construction of the organisms' hierarchical classification, determination of their phylogenetic and taxonomic position and revelation of their molecular characteristics.

A Feature-Based Approach to Modeling Protein–DNA Interactions

PubMed Central

Segal, Eran

2008-01-01

Transcription factor (TF) binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position specific scoring matrix (PSSM), which assumes independence between binding positions. However, in many cases, this simplifying assumption does not hold. Here, we present feature motif models (FMMs), a novel probabilistic method for modeling TF–DNA interactions, based on log-linear models. Our approach uses sequence features to represent TF binding specificities, where each feature may span multiple positions. We develop the mathematical formulation of our model and devise an algorithm for learning its structural features from binding site data. We also developed a discriminative motif finder, which discovers de novo FMMs that are enriched in target sets of sequences compared to background sets. We evaluate our approach on synthetic data and on the widely used TF chromatin immunoprecipitation (ChIP) dataset of Harbison et al. We then apply our algorithm to high-throughput TF ChIP data from mouse and human, reveal sequence features that are present in the binding specificities of mouse and human TFs, and show that FMMs explain TF binding significantly better than PSSMs. Our FMM learning and motif finder software are available at http://genie.weizmann.ac.il/. PMID:18725950

Trends in phosphorus loading to the western basin of Lake ...

EPA Pesticide Factsheets

Dave Dolan spent much of his career computing and compiling phosphorus loads to the Great Lakes. None of his work in this area has been more valuable than his continued load estimates to Lake Erie, which has allowed us to unambiguously interpret the cyanobacteria blooms and hypoxia development in the lake. To help understand the re-occurrence of cyanobacteria blooms in the Western Basin of Lake Erie, we have examined the phosphorus loading to the Western Basin over the past 15 years. Furthermore, we have examined the relative contributions from various tributaries and the Detroit River. On an annual basis the total phosphorus load has not exhibited a trend, other than being well correlated with flow from major tributaries. However, the dissolved reactive phosphorus (DRP) load has trended upward, returning to levels observed in the mid-1970s. This increase has largely been attributed to the increase in flow-weighted DRP concentration in the Maumee River. Over the period, about half of the phosphorus load comes from the Maumee River with the other half coming from the Detroit River; other tributaries contribute much small amounts to the load. Seasonal analysis shows the highest percentage of the load occurs in the spring during high flow events. We are very grateful to our friend Dave for making this type of analysis possible not applicable

Your kid could not have done that: even untutored observers can discern intentionality and structure in abstract expressionist art.

PubMed

Snapper, Leslie; Oranç, Cansu; Hawley-Dolan, Angelina; Nissel, Jenny; Winner, Ellen

2015-04-01

Can people with no special knowledge about art detect the skill, intentionality, and expressed meanings in non-representational art? Hawley-Dolan and Winner (2011) showed participants without training in art images of abstract expressionist paintings paired with superficially similar works by children or animals and asked them which they preferred and which was a better work of art. Participants selected the works by artists in response to both questions at a rate above chance. In Study 1, we used the same image pairs but asked a more direct question: which painting is by the artist rather than the child or animal? Individuals with no familiarity with abstract expressionism correctly identified the artists' works at a rate significantly above chance. In Study 2 participants saw each image singly and were asked whether it was by an artist or a child or animal. Participants unfamiliar with abstract expressionism again correctly identified the source of the works at a rate above chance. Study 3 demonstrated that this discrimination is made on the basis of perceived intentionality and perceived structure. People see more than they think they do in abstract art. These findings tell us something about the nature of non-figurative art. They also tell us something about the human tendency to ferret out intentionality. Copyright © 2014 Elsevier B.V. All rights reserved.

Graphical classification of DNA sequences of HLA alleles by deep learning.

PubMed

Miyake, Jun; Kaneshita, Yuhei; Asatani, Satoshi; Tagawa, Seiichi; Niioka, Hirohiko; Hirano, Takashi

2018-04-01

Alleles of human leukocyte antigen (HLA)-A DNAs are classified and expressed graphically by using artificial intelligence "Deep Learning (Stacked autoencoder)". Nucleotide sequence data corresponding to the length of 822 bp, collected from the Immuno Polymorphism Database, were compressed to 2-dimensional representation and were plotted. Profiles of the two-dimensional plots indicate that the alleles can be classified as clusters are formed. The two-dimensional plot of HLA-A DNAs gives a clear outlook for characterizing the various alleles.

Swabbing Students: Should Universities Be Allowed to Facilitate Educational DNA Testing?

PubMed Central

Callier, Shawneequa L.

2012-01-01

Recognizing the profound need for greater patient and provider familiarity with personalized genomic medicine, many university instructors are including personalized genotyping as part of their curricula. During seminars and lectures students run polymerase chain reactions on their own DNA or evaluate their experiences using direct-to-consumer genetic testing services subsidized by the university. By testing for genes that may influence behavioral or health-related traits, however, such as alcohol tolerance and cancer susceptibility, certain universities have stirred debate on the ethical concerns raised by educational genotyping. Considering the potential for psychosocial harm and medically relevant outcomes, how far should university-facilitated DNA testing be permitted to go? The analysis here distinguishes among these learning initiatives and critiques their approaches to the ethical concerns raised by educational genotyping. PMID:22452475

BDNF and exercise enhance neuronal DNA repair by stimulating CREB-mediated production of apurinic/apyrimidinic endonuclease 1.

PubMed

Yang, Jenq-Lin; Lin, Yu-Ting; Chuang, Pei-Chin; Bohr, Vilhelm A; Mattson, Mark P

2014-03-01

Brain-derived neurotrophic factor (BDNF) promotes the survival and growth of neurons during brain development and mediates activity-dependent synaptic plasticity and associated learning and memory in the adult. BDNF levels are reduced in brain regions affected in Alzheimer's, Parkinson's, and Huntington's diseases, and elevation of BDNF levels can ameliorate neuronal dysfunction and degeneration in experimental models of these diseases. Because neurons accumulate oxidative lesions in their DNA during normal activity and in neurodegenerative disorders, we determined whether and how BDNF affects the ability of neurons to cope with oxidative DNA damage. We found that BDNF protects cerebral cortical neurons against oxidative DNA damage-induced death by a mechanism involving enhanced DNA repair. BDNF stimulates DNA repair by activating cyclic AMP response element-binding protein (CREB), which, in turn, induces the expression of apurinic/apyrimidinic endonuclease 1 (APE1), a key enzyme in the base excision DNA repair pathway. Suppression of either APE1 or TrkB by RNA interference abolishes the ability of BDNF to protect neurons against oxidized DNA damage-induced death. The ability of BDNF to activate CREB and upregulate APE1 expression is abolished by shRNA of TrkB as well as inhibitors of TrkB, PI3 kinase, and Akt kinase. Voluntary running wheel exercise significantly increases levels of BDNF, activates CREB, and upregulates APE1 in the cerebral cortex and hippocampus of mice, suggesting a novel mechanism whereby exercise may protect neurons from oxidative DNA damage. Our findings reveal a previously unknown ability of BDNF to enhance DNA repair by inducing the expression of the DNA repair enzyme APE1.

Antarctic glaciations under Pliocene climate conditions from numerical modeling and compilation of local field-based reconstructions

NASA Astrophysics Data System (ADS)

Bernales, Jorge; Rogozhina, Irina; Greve, Ralf

2014-05-01

The mid-Pliocene (3.15 to 2.85 million years before present) is the most recent period in Earth's history when temperatures and CO2 concentrations were likely sustainedly higher than pre-industrial values. Furthermore, the positions of the continents and their sea-land distributions had already reached their present configuration, sharing some similarities with today's patterns of ocean circulation and vegetation distributions. Although significant differences exist -such as a peak sea level that could have been 22 ± 10 m higher than it is today and sea surface temperatures particularly warmer at higher latitudes, mid-Pliocene has been identified as an ideal interval for studying the climate system under conditions similar to those projected for the end of this century. Among the sources of uncertainty in the projections, the response of the Antarctic ice sheet (AIS) to warmer-than-today conditions seems to play a central role. Therefore, a better understanding of AIS's behavior during periods like the mid-Pliocene will provide valuable information that could help improve future predictions. For this purpose, we have compiled a wide range of local field-based reconstructions of the ice-sheet margin from Pliocene sediments (with the inclusions of organic matters such as, for instance, diatoms or palynoflora, or ice rafted debris), geochemical records, volcanic ashes and rocks, and geomorphology, and designed numerical experiments of the AIS dynamics during the mid-Pliocene warm period using the large-scale polythermal ice sheet-shelf model SICOPOLIS (Greve, 1997 [1]; Sato and Greve, 2012 [2]). The model is run with a horizontal resolution of 40 × 40 km by the climatology obtained from the PlioMIP Atmosphere Ocean Global Circulation Model experiments (Dolan et al., 2012 [3]). Parameters of the AIS model (e.g. ice calving, sub-ice shelf and surface ice melt, basal sliding, etc.) have initially been estimated using ice-sheet simulations driven by the present-day climate and ocean conditions and calibrated against available remote-sensed and in-situ observations. In our Pliocene experiments, we employ alternative parameterizations of sub-ice shelf and ice surface melting processes to test the likelihood of numerous controversial theories and reconstructions arguing for or against significant retreat of the East Antarctic ice sheet from the coasts (locally up to 450 km) in the mid-Pliocene. Finally, we assess the sensitivity of the modeled West Antarctic/Antarctic Peninsula ice geometry to the above parameters and emphasize a crucial role of surface mass balance model parameters in modeling the Pliocene ice sheet configuration in agreement with existing reconstructions on a regional scale. References [1] Greve, R. (1997). Application of a polythermal three-dimensional ice sheet model to the Greenland ice sheet: response to steady-state and transient climate scenarios. Journal of Climate, 10(5), 901-918. [2] Sato, T., and Greve, R. (2012). Sensitivity experiments for the Antarctic ice sheet with varied sub-ice-shelf melting rates. Annals of Glaciology, 53(60), 221-228. [3] Dolan, A. M., Koenig, S. J., Hill, D. J., Haywood, A. M., and DeConto, R. M. (2012). Pliocene Ice Sheet Modelling Intercomparison Project (PLISMIP)-experimental design. Geoscientific Model Development, 5(4), 963-974.

Modes of active deformation in Eastern Hispaniola

NASA Astrophysics Data System (ADS)

García-Senz, J.; Pérez-Estaún, A.

2012-04-01

Eastern Hispaniola and the Puerto Rico Island are the emerged part of a doubly vergent thrust wedge formed by oblique arc-continent collision with subduction and underthrusting of the North America Plate in the Puerto Rico trench and underthrusting of the Caribbean crust in The Muertos trough (Dolan et al. 1998, Mann et al., 2002, ten Brink et al. 2010). In the relatively small area of Eastern Hispaniola several types of active crustal deformation have been recognized: 1) At the prowedge of the orogene, the rear of the accretionary prism is cut by the strike-slip Septentrional Fault, bounding a sliver plate (Mann et al, 2002). Recent detailed mapping and aeromagnetic surveys in the onshore part of the prism (Samaná Peninsula and Septentrional Cordillera, Sysmin Team) revealed that the internal structure of the sliver is made of parallel bands of sigmoidal, left-lateral, NW-SE thrust splays, bounded by steep strike-slip faults. We interpreted these structures as transpressional strike-slip duplex. It is worth to note the similarity between the strike and dip of the thrust splays and the 303, 62, 74 focal mechanism calculated by Russo and Villaseñor (1995) for the thrust event of the August 4, 1946 Hispaniola earthquake. 2) The uplifted core of the orogen extends between the accretionary prism and the beginning of the Muertos retrowedge. Half of this area is occupied by the Oriental Cordillera, a recent uplift of cretaceous island-arc rocks arching the Late Neogene reef. The rest of the territory is the Caribbean Coastal Plain modelled on the Late Neogene reef. The Oriental Cordillera is made of two en echelon left-stepping uplifts: the domal-shaped Haitises and the rhombohedral-shaped Seibo (García-Senz et al, 2007); the latter share structural similarities and scaling relations with the 90° neutral stepover model of McClay and Bonora (2001). Therefore we interpret it as a restraining stepover developed over a blind splay of the Septentrional Fault, and the main active fault at surface, the Yabón fault, as a trans pop-up strike-slip fault. 3) The contractive faults and folds that form the Oriental Cordillera disappear to the east replaced by a field of NW-SE to WNW-ESE trending normal faults with fresh scarps up to 75 m high depressing the Late Neogene reef (Punta Cana extended area). In plan form, the faults show multiple relays and transverse ramps at the overlaps. A NE-SW section coast to coast across the Punta Cana area show the Late Neogene reef gently arched and cut by normal faults bounding half-grabens, with the main throw directed to the NE. The amount of extension exceeds 3 km (5% of stretching). A very similar system of normal faults has been documented in seismic lines across the Mona Passage (eg. van Gestel et al., 1998, Mondziel, 2007, Chaytor and ten Brink, 2010) and onshore western Puerto Rico (Hippolyte et al., 2005), which are interpreted by a pinning extension model (Dolan et al., 1998, Mann et al., 2002) or by oblique extension (Chaytor and ten Brink, 2010). Whatever the tectonic model may be, our data places an onshore boundary between transpressional and extensional domains. 4) The retrowedge at the southern margin of Hispaniola form an imbricate of E-W segmented thrusts overriding the Muertos trough (ten Brink et al., 2010). These authors suggest that the transport direction within the Muertos thrust system is southward perpendicular to the regional trend of the belt.

Darwin, Dogs and DNA: Freshman Writing about Biology.

ERIC Educational Resources Information Center

Grant, Michael C.; Pirrto, John

1994-01-01

Describes a successful interdepartmental program at a major research-oriented university that melds freshman writing with freshman biology. Extensive, repeated feedback on individual student writing projects from two instructors appears to work synergistically so that student learning is significantly enhanced. Particulars derived from five years…

Modeling the Dynamics of Gel Electrophorresis in the High School Classroom

NASA Astrophysics Data System (ADS)

Saucedo, Skyler R.

2013-01-01

Gel electrophoresis, used by geneticists and forensic experts alike, is an immensely popular technique that utilizes an electric field to separate molecules and proteins by size and charge. At the microscopic level, a dye or complex protein like DNA is passed through agarose, a gelatinous three-dimensional matrix of pores and nano-sized tunnels. When forced through a maze of holes, the molecule unravels, forming a long chain, slithering through the field of pores in a process colloquially coined "reputation." As a result, the smaller molecules travel farther through the gel when compared to molecules of larger molecular weight. This highly effective "molecular sieve" provides consistent data and allows scientists to compare similar sequences of DNA base pairs in a routine fashion.2 When performed at the high school level, gel electrophoresis provides students the opportunity to learn about a contemporary lab technique of great scientific relevance. Doing real science certainly excites students and motivates them to learn more.

Discrimination among individual Watson–Crick base pairs at the termini of single DNA hairpin molecules

PubMed Central

Vercoutere, Wenonah A.; Winters-Hilt, Stephen; DeGuzman, Veronica S.; Deamer, David; Ridino, Sam E.; Rodgers, Joseph T.; Olsen, Hugh E.; Marziali, Andre; Akeson, Mark

2003-01-01

Nanoscale α-hemolysin pores can be used to analyze individual DNA or RNA molecules. Serial examination of hundreds to thousands of molecules per minute is possible using ionic current impedance as the measured property. In a recent report, we showed that a nanopore device coupled with machine learning algorithms could automatically discriminate among the four combinations of Watson–Crick base pairs and their orientations at the ends of individual DNA hairpin molecules. Here we use kinetic analysis to demonstrate that ionic current signatures caused by these hairpin molecules depend on the number of hydrogen bonds within the terminal base pair, stacking between the terminal base pair and its nearest neighbor, and 5′ versus 3′ orientation of the terminal bases independent of their nearest neighbors. This report constitutes evidence that single Watson–Crick base pairs can be identified within individual unmodified DNA hairpin molecules based on their dynamic behavior in a nanoscale pore. PMID:12582251

DNA Microarray Wet Lab Simulation Brings Genomics into the High School Curriculum

PubMed Central

Zanta, Carolyn A.; Heyer, Laurie J.; Kittinger, Ben; Gabric, Kathleen M.; Adler, Leslie

2006-01-01

We have developed a wet lab DNA microarray simulation as part of a complete DNA microarray module for high school students. The wet lab simulation has been field tested with high school students in Illinois and Maryland as well as in workshops with high school teachers from across the nation. Instead of using DNA, our simulation is based on pH indicators, which offer many ideal teaching characteristics. The simulation requires no specialized equipment, is very inexpensive, is very reliable, and takes very little preparation time. Student and teacher assessment data indicate the simulation is popular with both groups, and students show significant learning gains. We include many resources with this publication, including all prelab introductory materials (e.g., a paper microarray activity), the student handouts, teachers notes, and pre- and postassessment tools. We did not test the simulation on other student populations, but based on teacher feedback, the simulation also may fit well in community college and in introductory and nonmajors' college biology curricula. PMID:17146040

DNA microarray wet lab simulation brings genomics into the high school curriculum.

PubMed

Campbell, A Malcolm; Zanta, Carolyn A; Heyer, Laurie J; Kittinger, Ben; Gabric, Kathleen M; Adler, Leslie; Schulz, Barbara

2006-01-01

We have developed a wet lab DNA microarray simulation as part of a complete DNA microarray module for high school students. The wet lab simulation has been field tested with high school students in Illinois and Maryland as well as in workshops with high school teachers from across the nation. Instead of using DNA, our simulation is based on pH indicators, which offer many ideal teaching characteristics. The simulation requires no specialized equipment, is very inexpensive, is very reliable, and takes very little preparation time. Student and teacher assessment data indicate the simulation is popular with both groups, and students show significant learning gains. We include many resources with this publication, including all prelab introductory materials (e.g., a paper microarray activity), the student handouts, teachers notes, and pre- and postassessment tools. We did not test the simulation on other student populations, but based on teacher feedback, the simulation also may fit well in community college and in introductory and nonmajors' college biology curricula.

Sockeye salmon evolution, ecology, and management

USGS Publications Warehouse

Woody, Carol Ann

2007-01-01

This collection of articles and photographs gives managers a good idea of recent research into what the sockeye salmon is and does, covering such topics as the vulnerability and value of sockeye salmon ecotypes, their homing ability, using new technologies to monitor reproduction, DNA and a founder event in the Lake Clark sockeye salmon, marine-derived nutrients, the exploitation of large prey, dynamic lake spawning migrations by females, variability of sockeye salmon residence, expression profiling using cDNA microarray technology, learning from stable isotropic records of native otolith hatcheries, the amount of data needed to manage sockeye salmon and estimating salmon "escapement." 

DNA transposon-based gene vehicles - scenes from an evolutionary drive

PubMed Central

2013-01-01

DNA transposons are primitive genetic elements which have colonized living organisms from plants to bacteria and mammals. Through evolution such parasitic elements have shaped their host genomes by replicating and relocating between chromosomal loci in processes catalyzed by the transposase proteins encoded by the elements themselves. DNA transposable elements are constantly adapting to life in the genome, and self-suppressive regulation as well as defensive host mechanisms may assist in buffering ‘cut-and-paste’ DNA mobilization until accumulating mutations will eventually restrict events of transposition. With the reconstructed Sleeping Beauty DNA transposon as a powerful engine, a growing list of transposable elements with activity in human cells have moved into biomedical experimentation and preclinical therapy as versatile vehicles for delivery and genomic insertion of transgenes. In this review, we aim to link the mechanisms that drive transposon evolution with the realities and potential challenges we are facing when adapting DNA transposons for gene transfer. We argue that DNA transposon-derived vectors may carry inherent, and potentially limiting, traits of their mother elements. By understanding in detail the evolutionary journey of transposons, from host colonization to element multiplication and inactivation, we may better exploit the potential of distinct transposable elements. Hence, parallel efforts to investigate and develop distinct, but potent, transposon-based vector systems will benefit the broad applications of gene transfer. Insight and clever optimization have shaped new DNA transposon vectors, which recently debuted in the first DNA transposon-based clinical trial. Learning from an evolutionary drive may help us create gene vehicles that are safer, more efficient, and less prone for suppression and inactivation. PMID:24320156

The plateau zokors' learning and memory ability is related to the high expression levels of foxP2 in the brain.

PubMed

Ma, Ben-Yuan; Wei, Lian; Sun, Sheng-Zhen; Wang, Duo-Wei; Wei, Deng-Bang

2014-04-25

Plateau zokor (Myospalax baileyi) is a subterranean mammal. Plateau zokor has high learning and memory ability, and can determine the location of blocking obstacles in their tunnels. Forkhead box p2 (FOXP2) is a transcription factor implicated in the neural control of orofacial coordination and sensory-motor integration, particularly with respect to learning, memory and vocalization. To explore the association of foxP2 with the high learning and memory ability of plateau zokor, the cDNA of foxP2 of plateau zokor was sequenced; by using plateau pika as control, the expression levels of foxP2 mRNA and FOXP2 protein in brain of plateau zokor were determined by real-time PCR and Western blot, respectively; and the location of FOXP2 protein in the brain of plateau zokor was determined by immunohistochemistry. The result showed that the cDNA sequence of plateau zokor foxP2 was similar to that of other mammals and the amino acid sequences showed a relatively high degree of conservation, with the exception of two particular amino acid substitutions [a Gln (Q)-to-His (H) change at position 231 and a Ser (S)-to-Ile (I) change at position 235]. Higher expression levels of foxP2 mRNA (3-fold higher) and FOXP2 protein (>2-fold higher) were detected in plateau zokor brain relative to plateau pika brain. In plateau zokor brain, FOXP2 protein was highly expressed in the cerebral cortex, thalamus and the striatum (a basal ganglia brain region). The results suggest that the high learning and memory ability of plateau zokor is related to the high expression levels of foxP2 in the brain.

Choline nutrition programs brain development via DNA and histone methylation.

PubMed

Blusztajn, Jan Krzysztof; Mellott, Tiffany J

2012-06-01

Choline is an essential nutrient for humans. Metabolically choline is used for the synthesis of membrane phospholipids (e.g. phosphatidylcholine), as a precursor of the neurotransmitter acetylcholine, and, following oxidation to betaine, choline functions as a methyl group donor in a pathway that produces S-adenosylmethionine. As a methyl donor choline influences DNA and histone methylation--two central epigenomic processes that regulate gene expression. Because the fetus and neonate have high demands for choline, its dietary intake during pregnancy and lactation is particularly important for normal development of the offspring. Studies in rodents have shown that high choline intake during gestation improves cognitive function in adulthood and prevents memory decline associated with old age. These behavioral changes are accompanied by electrophysiological, neuroanatomical, and neurochemical changes and by altered patterns of expression of multiple cortical and hippocampal genes including those encoding key proteins that contribute to the biochemical mechanisms of learning and memory. These actions of choline are observed long after the exposure to the nutrient ended (months) and correlate with fetal hepatic and cerebral cortical choline-evoked changes in global- and gene-specific DNA cytosine methylation and with dramatic changes of the methylation pattern of lysine residues 4, 9 and 27 of histone H3. Moreover, gestational choline modulates the expression of DNA (Dnmt1, Dnmt3a) and histone (G9a/Ehmt2/Kmt1c, Suv39h1/Kmt1a) methyltransferases. In addition to the central role of DNA and histone methylation in brain development, these processes are highly dynamic in adult brain, modulate the expression of genes critical for synaptic plasticity, and are involved in mechanisms of learning and memory. A recent study documented that in a cohort of normal elderly people, verbal and visual memory function correlated positively with the amount of dietary choline consumption. It will be important to determine if these actions of choline on human cognition are mediated by epigenomic mechanisms or by its influence on acetylcholine or phospholipid synthesis.

Choline nutrition programs brain development via DNA and histone methylation

PubMed Central

Blusztajn, Jan Krzysztof; Mellott, Tiffany J.

2017-01-01

Choline is an essential nutrient for humans. Metabolically choline is used for the synthesis of membrane phospholipids (e.g. phosphatidylcholine), as a precursor of the neurotransmitter acetylcholine, and, following oxidation to betaine, choline functions as a methyl group donor in a pathway that produces S-adenosylmethionine. As a methyl donor choline influences DNA and histone methylation – two central epigenomic processes that regulate gene expression. Because the fetus and neonate have high demands for choline, its dietary intake during pregnancy and lactation is particularly important for normal development of the offspring. Studies in rodents have shown that high choline intake during gestation improves cognitive function in adulthood and prevents memory decline associated with old age. These behavioral changes are accompanied by electrophysiological, neuroanatomical, and neurochemical changes and by altered patterns of expression of multiple cortical and hippocampal genes including those encoding key proteins that contribute to the biochemical mechanisms of learning and memory. These actions of choline are observed long after the exposure to the nutrient ended (months) and correlate with fetal hepatic and cerebral cortical choline-evoked changes in global- and gene-specific DNA cytosine methylation and with dramatic changes of the methylation pattern of lysine residues 4, 9 and 27 of histone H3. Moreover, gestational choline modulates the expression of DNA (Dnmt1, Dnmt3a) and histone (G9a/Ehmt2/Kmt1c, Suv39h1/Kmt1a) methyltransferases. In addition to the central role of DNA and histone methylation in brain development, these processes are highly dynamic in adult brain, modulate the expression of genes critical for synaptic plasticity, and are involved in mechanisms of learning and memory. A recent study documented that in a cohort of normal elderly people, verbal and visual memory function correlated positively with the amount of dietary choline consumption. It will be important to determine if these actions of choline on human cognition are mediated by epigenomic mechanisms or by its influence on acetylcholine or phospholipid synthesis. PMID:22483275

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

PubMed

Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi

2017-09-22

DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

Epigenetic Mechanisms in Developmental Alcohol-Induced Neurobehavioral Deficits

PubMed Central

Basavarajappa, Balapal S.; Subbanna, Shivakumar

2016-01-01

Alcohol consumption during pregnancy and its damaging consequences on the developing infant brain are significant public health, social, and economic issues. The major distinctive features of prenatal alcohol exposure in humans are cognitive and behavioral dysfunction due to damage to the central nervous system (CNS), which results in a continuum of disarray that is collectively called fetal alcohol spectrum disorder (FASD). Many rodent models have been developed to understand the mechanisms of and to reproduce the human FASD phenotypes. These animal FASD studies have provided several molecular pathways that are likely responsible for the neurobehavioral abnormalities that are associated with prenatal alcohol exposure of the developing CNS. Recently, many laboratories have identified several immediate, as well as long-lasting, epigenetic modifications of DNA methylation, DNA-associated histone proteins and microRNA (miRNA) biogenesis by using a variety of epigenetic approaches in rodent FASD models. Because DNA methylation patterns, DNA-associated histone protein modifications and miRNA-regulated gene expression are crucial for synaptic plasticity and learning and memory, they can therefore offer an answer to many of the neurobehavioral abnormalities that are found in FASD. In this review, we briefly discuss the current literature of DNA methylation, DNA-associated histone proteins modification and miRNA and review recent developments concerning epigenetic changes in FASD. PMID:27070644

Development of High-Throughput DNA Sequencing Techniques to Improve and Advance Environmental Monitoring and Bioassessment

EPA Pesticide Factsheets

Scientists learn about the health of rivers, streams, lakes, and other aquatic ecosystems by looking at the species that live there. Populations of insects, snails, and worms found in different aquatic ecosystems can indicate overall health in those areas.

Lessons learned from DNA-based tool development and use in a genebank

USDA-ARS?s Scientific Manuscript database

In 2002, a molecular genetics laboratory was established at the United States Department of Agriculture Agricultural Research Service (USDA-ARS), National Clonal Germplasm Repository (NCGR), in Corvallis, Oregon. This facility houses the US national genebank for strawberry (Fragaria L.). A main obje...

Selected topics from classical bacterial genetics.

PubMed

Raleigh, Elisabeth A; Elbing, Karen; Brent, Roger

2002-08-01

Current cloning technology exploits many facts learned from classical bacterial genetics. This unit covers those that are critical to understanding the techniques described in this book. Topics include antibiotics, the LAC operon, the F factor, nonsense suppressors, genetic markers, genotype and phenotype, DNA restriction, modification and methylation and recombination.

Research in Undergraduate Instruction: A Biotech Lab Project for Recombinant DNA Protein Expression in Bacteria

NASA Astrophysics Data System (ADS)

Brockman, Mark; Ordman, Alfred B.; Campbell, A. Malcolm

1996-06-01

In the sophomore-level Molecular Biology and Biotechnology course at Beloit College, students learn basic methods in molecular biology in the context of pursuing a semester-long original research project. We are exploring how DNA sequence affects expression levels of proteins. A DNA fragment encoding all or part of the guanylate monokinase (gmk) sequence is cloned into pSP73 and expressed in E. coli. A monoclonal antibody is made to gmk. The expression level of gmk is determined by SDS gel elctrophoresis, a Western blot, and an ELISA assay. Over four years, an increase in enrollment in the course from 9 to 34 students, the 85% of majors pursuing advanced degrees, and course evaluations all support the conclusion that involving students in research during undergraduate courses encourages them to pursue careers in science.

Altered DNA methylation: a secondary mechanism involved in carcinogenesis.

PubMed

Goodman, Jay I; Watson, Rebecca E

2002-01-01

This review focuses on the role that DNA methylation plays in the regulation of normal and aberrant gene expression and on how, in a hypothesis-driven fashion, altered DNA methylation may be viewed as a secondary mechanism involved in carcinogenesis. Research aimed at discerning the mechanisms by which chemicals can transform normal cells into frank carcinomas has both theoretical and practical implications. Through an increased understanding of the mechanisms by which chemicals affect the carcinogenic process, we learn more about basic biology while, at the same time, providing the type of information required to make more rational safety assessment decisions concerning their actual potential to cause cancer under particular conditions of exposure. One key question is: does the mechanism of action of the chemical in question involve a secondary mechanism and, if so, what dose may be below its threshold?

2-Way k-Means as a Model for Microbiome Samples.

PubMed

Jackson, Weston J; Agarwal, Ipsita; Pe'er, Itsik

2017-01-01

Motivation . Microbiome sequencing allows defining clusters of samples with shared composition. However, this paradigm poorly accounts for samples whose composition is a mixture of cluster-characterizing ones and which therefore lie in between them in the cluster space. This paper addresses unsupervised learning of 2-way clusters. It defines a mixture model that allows 2-way cluster assignment and describes a variant of generalized k -means for learning such a model. We demonstrate applicability to microbial 16S rDNA sequencing data from the Human Vaginal Microbiome Project.

2-Way k-Means as a Model for Microbiome Samples

PubMed Central

2017-01-01

Motivation. Microbiome sequencing allows defining clusters of samples with shared composition. However, this paradigm poorly accounts for samples whose composition is a mixture of cluster-characterizing ones and which therefore lie in between them in the cluster space. This paper addresses unsupervised learning of 2-way clusters. It defines a mixture model that allows 2-way cluster assignment and describes a variant of generalized k-means for learning such a model. We demonstrate applicability to microbial 16S rDNA sequencing data from the Human Vaginal Microbiome Project. PMID:29177026

MotifMark: Finding regulatory motifs in DNA sequences.

PubMed

Hassanzadeh, Hamid Reza; Kolhe, Pushkar; Isbell, Charles L; Wang, May D

2017-07-01

The interaction between proteins and DNA is a key driving force in a significant number of biological processes such as transcriptional regulation, repair, recombination, splicing, and DNA modification. The identification of DNA-binding sites and the specificity of target proteins in binding to these regions are two important steps in understanding the mechanisms of these biological activities. A number of high-throughput technologies have recently emerged that try to quantify the affinity between proteins and DNA motifs. Despite their success, these technologies have their own limitations and fall short in precise characterization of motifs, and as a result, require further downstream analysis to extract useful and interpretable information from a haystack of noisy and inaccurate data. Here we propose MotifMark, a new algorithm based on graph theory and machine learning, that can find binding sites on candidate probes and rank their specificity in regard to the underlying transcription factor. We developed a pipeline to analyze experimental data derived from compact universal protein binding microarrays and benchmarked it against two of the most accurate motif search methods. Our results indicate that MotifMark can be a viable alternative technique for prediction of motif from protein binding microarrays and possibly other related high-throughput techniques.

Design pattern mining using distributed learning automata and DNA sequence alignment.

PubMed

Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina

2014-01-01

Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns.

Reading and Generalist Genes

ERIC Educational Resources Information Center

Haworth, Claire M. A.; Meaburn, Emma L.; Harlaar, Nicole; Plomin, Robert

2007-01-01

Twin-study research suggests that many (but not all) of the same genes contribute to genetic influence on diverse learning abilities and disabilities, a hypothesis called "generalist genes". This generalist genes hypothesis was tested using a set of 10 DNA markers (single nucleotide polymorphisms [SNPs]) found to be associated with early reading…

Gel Electrophoresis--The Easy Way for Students

ERIC Educational Resources Information Center

VanRooy, Wilhelmina; Sultana, Khalida

2010-01-01

This article describes a simple, inexpensive, easy to conduct gel-electrophoresis activity using food dyes. It is an alternative to the more expensive counterparts which require agarose gel, DNA samples, purchased chamber and Tris-borate-EDTA buffer. We suggest some learning activities for senior biology students along with comments on several…

Is Genetic Testing Right for You? | NIH MedlinePlus the Magazine

MedlinePlus

... instructions you receive from your mother and father. Genetic tests may identify risks of health problems. This can help people choose treatments or to understand how they may respond to treatments. What can I learn from testing? Genetic testing tells you information about your DNA. ...

Blackboard Electrophoresis: An Inexpensive Exercise on the Principles of DNA Restriction Analysis

ERIC Educational Resources Information Center

Costa, M. J.

2007-01-01

Undergraduates with little training on molecular biology may find the technical level of the typical introductory restriction laboratory too challenging and have problems with mastering the underlying concepts and processes. "Blackboard electrophoresis" is an active learning exercise, which focuses student attention on the sequences and principles…

Genetic Essentialism: On the Deceptive Determinism of DNA

ERIC Educational Resources Information Center

Dar-Nimrod, Ilan; Heine, Steven J.

2011-01-01

This article introduces the notion of genetic essentialist biases: cognitive biases associated with essentialist thinking that are elicited when people encounter arguments that genes are relevant for a behavior, condition, or social group. Learning about genetic attributions for various human conditions leads to a particular set of thoughts…

Sex Determination Using PCR

ERIC Educational Resources Information Center

Kima, Peter E.; Rasche, Madeline E.

2004-01-01

PCR has revolutionized many aspects of biochemistry and molecular biology research. In the following exercise, students learn PCR by isolating their own DNA, amplifying specific segments of the X and Y chromosomes, and estimating the sizes of the PCR products using agarose gel electrophoresis. Based on the pattern of PCR products, students can…

Use DNA to learn from the past: how modern and ancient DNA studies may help reveal the past and predict the future distribution of species

NASA Astrophysics Data System (ADS)

Edwards, M. E.; Alsos, I. G.; Sjögren, P.; Coissac, E.; Gielly, L.; Yoccoz, N.; Føreid, M. K.; Taberlet, P.

2015-12-01

Knowledge of how climate change affected species distribution in the past may help us predict the effect of ongoing environmental changes. We explore how the use of modern (AFLP fingerprinting techniques) and ancient DNA (metabarcoding P6 loop of chloroplast DNA) help to reveal past distribution of vascular plant species, dispersal processes, and effect of species traits. Based on studies of modern DNA combined with species distribution models, we show the dispersal routes and barriers to dispersal throughout the circumarctic/circumboreal region, likely dispersal vectors, the cost of dispersal in term of loss of genetic diversity, and how these relates to species traits, dispersal distance, and size of colonized region. We also estimate the expected future distribution and loss of genetic diversity and show how this relates to life form and adaptations to dispersal. To gain more knowledge on time lags in past range change events, we rely on palaeorecords. Current data on past distribution are limited by the taxonomic and time resolution of macrofossil and pollen records. We show how this may be improved by studying ancient DNA of lake sediments. DNA of lake sediments recorded about half of the flora surrounding the lake. Compared to macrofossil, the taxonomic resolution is similar but the detection rate is considerable improved. By taking into account main determinants of founder effect, dispersal vectors, and dispersal lags, we may improve our ability to forecast effects of climate change, whereas more studies on ancient DNA may provide us with knowledge on distribution time lags.

Establishing a model for assessing DNA damage in murine brain cells as a molecular marker of chemotherapy-associated cognitive impairment

PubMed Central

Krynetskiy, Evgeny; Krynetskaia, Natalia; Rihawi, Diana; Wieczerzak, Katarzyna; Ciummo, Victoria; Walker, Ellen

2013-01-01

Aims Chemotherapy-associated cognitive impairment often follows cancer chemotherapy. We explored chemotherapy-induced DNA damage in the brain cells of mice treated with 5-fluorouracil (5FU), an antineoplastic agent, to correlate the extent of DNA damage to behavioral functioning in an autoshaping-operant mouse model of chemotherapy-induced learning and memory deficits (Foley et al. 2008). Main methods Male, Swiss-Webster mice were injected once with saline or 75 mg/kg 5FU at 0, 12, and 24 h and weighed every 24 h. Twenty-four h after the last injection, the mice were tested in a two-day acquisition and retention of a novel response task for food reinforcement. Murine brain cells were analyzed for the presence of single- and double-strand DNA breaks by the single cell gel electrophoresis assay (the Comet assay). Key findings We detected significant differences (p<0.0001) for all DNA damage characteristics (DNA “comet” tail shape, migration pattern, tail moment and Olive moments) between control mice cohort and 5FU-treated mice cohort: tail length – 119 vs. 153; tail moment – 101 vs. 136; olive moment – 60 vs. 82, correspondingly. We found a positive correlation between increased response rates (r=0.52, p<0.05) and increased rate of errors (r=0.51, p<0.05), and DNA damage on day 1. For all 15 mice (saline-treated and 5FU-treated mice), we found negative correlations between DNA damage and weight (r=−0.75, p<0.02). Significance Our results indicate that chemotherapy-induced DNA damage changes the physiological status of the brain cells and may provide insights to the mechanisms for cognitive impairment after cancer chemotherapy. PMID:23567806

Establishing a model for assessing DNA damage in murine brain cells as a molecular marker of chemotherapy-associated cognitive impairment.

PubMed

Krynetskiy, Evgeny; Krynetskaia, Natalia; Rihawi, Diana; Wieczerzak, Katarzyna; Ciummo, Victoria; Walker, Ellen

2013-10-17

Chemotherapy-associated cognitive impairment often follows cancer chemotherapy. We explored chemotherapy-induced DNA damage in the brain cells of mice treated with 5-fluorouracil (5FU), an antineoplastic agent, to correlate the extent of DNA damage to behavioral functioning in an autoshaping-operant mouse model of chemotherapy-induced learning and memory deficits (Foley et al., 2008). Male, Swiss-Webster mice were injected once with saline or 75 mg/kg 5FU at 0, 12, and 24h and weighed every 24h. Twenty-four h after the last injection, the mice were tested in a two-day acquisition and the retention of a novel response task for food reinforcement. Murine brain cells were analyzed for the presence of single- and double-strand DNA breaks by the single cell gel electrophoresis assay (the Comet assay). We detected significant differences (p<0.0001) for all DNA damage characteristics (DNA "comet" tail shape, migration pattern, tail moment and olive moments) between control mice cohort and 5FU-treated mice cohort: tail length - 119 vs. 153; tail moment - 101 vs. 136; olive moment - 60 vs. 82, correspondingly. We found a positive correlation between increased response rates (r=0.52, p<0.05) and increased rate of errors (r=0.51, p<0.05), and DNA damage on day 1. For all 15 mice (saline-treated and 5FU-treated mice), we found negative correlations between DNA damage and weight (r=-0.75, p<0.02). Our results indicate that chemotherapy-induced DNA damage changes the physiological status of the brain cells and may provide insights to the mechanisms for cognitive impairment after cancer chemotherapy. Copyright © 2013 Elsevier Inc. All rights reserved.

Prediction of Ionizing Radiation Resistance in Bacteria Using a Multiple Instance Learning Model.

PubMed

Aridhi, Sabeur; Sghaier, Haïtham; Zoghlami, Manel; Maddouri, Mondher; Nguifo, Engelbert Mephu

2016-01-01

Ionizing-radiation-resistant bacteria (IRRB) are important in biotechnology. In this context, in silico methods of phenotypic prediction and genotype-phenotype relationship discovery are limited. In this work, we analyzed basal DNA repair proteins of most known proteome sequences of IRRB and ionizing-radiation-sensitive bacteria (IRSB) in order to learn a classifier that correctly predicts this bacterial phenotype. We formulated the problem of predicting bacterial ionizing radiation resistance (IRR) as a multiple-instance learning (MIL) problem, and we proposed a novel approach for this purpose. We provide a MIL-based prediction system that classifies a bacterium to either IRRB or IRSB. The experimental results of the proposed system are satisfactory with 91.5% of successful predictions.

Alchemical Free Energy Calculations for Nucleotide Mutations in Protein-DNA Complexes.

PubMed

Gapsys, Vytautas; de Groot, Bert L

2017-12-12

Nucleotide-sequence-dependent interactions between proteins and DNA are responsible for a wide range of gene regulatory functions. Accurate and generalizable methods to evaluate the strength of protein-DNA binding have long been sought. While numerous computational approaches have been developed, most of them require fitting parameters to experimental data to a certain degree, e.g., machine learning algorithms or knowledge-based statistical potentials. Molecular-dynamics-based free energy calculations offer a robust, system-independent, first-principles-based method to calculate free energy differences upon nucleotide mutation. We present an automated procedure to set up alchemical MD-based calculations to evaluate free energy changes occurring as the result of a nucleotide mutation in DNA. We used these methods to perform a large-scale mutation scan comprising 397 nucleotide mutation cases in 16 protein-DNA complexes. The obtained prediction accuracy reaches 5.6 kJ/mol average unsigned deviation from experiment with a correlation coefficient of 0.57 with respect to the experimentally measured free energies. Overall, the first-principles-based approach performed on par with the molecular modeling approaches Rosetta and FoldX. Subsequently, we utilized the MD-based free energy calculations to construct protein-DNA binding profiles for the zinc finger protein Zif268. The calculation results compare remarkably well with the experimentally determined binding profiles. The software automating the structure and topology setup for alchemical calculations is a part of the pmx package; the utilities have also been made available online at http://pmx.mpibpc.mpg.de/dna_webserver.html .

Promoter Sequences Prediction Using Relational Association Rule Mining

PubMed Central

Czibula, Gabriela; Bocicor, Maria-Iuliana; Czibula, Istvan Gergely

2012-01-01

In this paper we are approaching, from a computational perspective, the problem of promoter sequences prediction, an important problem within the field of bioinformatics. As the conditions for a DNA sequence to function as a promoter are not known, machine learning based classification models are still developed to approach the problem of promoter identification in the DNA. We are proposing a classification model based on relational association rules mining. Relational association rules are a particular type of association rules and describe numerical orderings between attributes that commonly occur over a data set. Our classifier is based on the discovery of relational association rules for predicting if a DNA sequence contains or not a promoter region. An experimental evaluation of the proposed model and comparison with similar existing approaches is provided. The obtained results show that our classifier overperforms the existing techniques for identifying promoter sequences, confirming the potential of our proposal. PMID:22563233

Protein Science by DNA Sequencing: How Advances in Molecular Biology Are Accelerating Biochemistry.

PubMed

Higgins, Sean A; Savage, David F

2018-01-09

A fundamental goal of protein biochemistry is to determine the sequence-function relationship, but the vastness of sequence space makes comprehensive evaluation of this landscape difficult. However, advances in DNA synthesis and sequencing now allow researchers to assess the functional impact of every single mutation in many proteins, but challenges remain in library construction and the development of general assays applicable to a diverse range of protein functions. This Perspective briefly outlines the technical innovations in DNA manipulation that allow massively parallel protein biochemistry and then summarizes the methods currently available for library construction and the functional assays of protein variants. Areas in need of future innovation are highlighted with a particular focus on assay development and the use of computational analysis with machine learning to effectively traverse the sequence-function landscape. Finally, applications in the fundamentals of protein biochemistry, disease prediction, and protein engineering are presented.

Resveratrol protects mouse embryonic stem cells from ionizing radiation by accelerating recovery from DNA strand breakage.

PubMed

Denissova, Natalia G; Nasello, Cara M; Yeung, Percy L; Tischfield, Jay A; Brenneman, Mark A

2012-01-01

Resveratrol has elicited many provocative anticancer effects in laboratory animals and cultured cells, including reduced levels of oxidative DNA damage, inhibition of tumor initiation and progression and induction of apoptosis in tumor cells. Use of resveratrol as a cancer-preventive agent in humans will require that its anticancer effects not be accompanied by damage to normal tissue stem or progenitor cells. In mouse embryonic stem cells (mESC) or early mouse embryos exposed to ethanol, resveratrol has been shown to suppress apoptosis and promote survival. However, in cells exposed to genotoxic stress, survival may come at the expense of genome stability. To learn whether resveratrol can protect stem cells from DNA damage and to study its effects on genomic integrity, we exposed mESC pretreated with resveratrol to ionizing radiation (IR). Forty-eight hours pretreatment with a comparatively low concentration of resveratrol (10 μM) improved survival of mESC >2-fold after exposure to 5 Gy of X-rays. Cells pretreated with resveratrol sustained the same levels of reactive oxygen species and DNA strand breakage after IR as mock-treated controls, but repaired DNA damage more rapidly and resumed cell division sooner. Frequencies of IR-induced mutation at a chromosomal reporter locus were not increased in cells pretreated with resveratrol as compared with controls, indicating that resveratrol can improve viability in mESC after DNA damage without compromising genomic integrity.

One small step for Mot1; one giant leap for other Swi2/Snf2 enzymes?

PubMed Central

Viswanathan, Ramya; Auble, David T.

2011-01-01

The TATA-binding protein (TBP) is a major target for transcriptional regulation. Mot1, a Swi2/Snf2-related ATPase, dissociates TBP from DNA in an ATP dependent process. The experimental advantages of this relatively simple reaction have been exploited to learn more about how Swi2/Snf2 ATPases function biochemically. However, many unanswered questions remain and fundamental aspects of the Mot1 mechanism are still under debate. Here, we review the available data and integrate the results with structural and biochemical studies of related enzymes to derive a model for Mot1’s catalytic action consistent with the broad literature on enzymes in this family. We propose that the Mot1 ATPase domain is tethered to TBP by a flexible, spring-like linker of alpha helical hairpins. The linker juxtaposes the ATPase domain such that it can engage duplex DNA on one side of the TBP-DNA complex. This allows the ATPase to employ short-range, nonprocessive ATP-driven DNA tracking to pull or push TBP off its DNA site. DNA translocation is a conserved property of ATPases in the broader enzyme family. As such, the model explains how a structurally and functionally conserved ATPase domain has been put to use in a very different context than other enzymes in the Swi2/Snf2 family. PMID:21658482

Single Nucleobase Identification Using Biophysical Signatures from Nanoelectronic Quantum Tunneling.

PubMed

Korshoj, Lee E; Afsari, Sepideh; Khan, Sajida; Chatterjee, Anushree; Nagpal, Prashant

2017-03-01

Nanoelectronic DNA sequencing can provide an important alternative to sequencing-by-synthesis by reducing sample preparation time, cost, and complexity as a high-throughput next-generation technique with accurate single-molecule identification. However, sample noise and signature overlap continue to prevent high-resolution and accurate sequencing results. Probing the molecular orbitals of chemically distinct DNA nucleobases offers a path for facile sequence identification, but molecular entropy (from nucleotide conformations) makes such identification difficult when relying only on the energies of lowest-unoccupied and highest-occupied molecular orbitals (LUMO and HOMO). Here, nine biophysical parameters are developed to better characterize molecular orbitals of individual nucleobases, intended for single-molecule DNA sequencing using quantum tunneling of charges. For this analysis, theoretical models for quantum tunneling are combined with transition voltage spectroscopy to obtain measurable parameters unique to the molecule within an electronic junction. Scanning tunneling spectroscopy is then used to measure these nine biophysical parameters for DNA nucleotides, and a modified machine learning algorithm identified nucleobases. The new parameters significantly improve base calling over merely using LUMO and HOMO frontier orbital energies. Furthermore, high accuracies for identifying DNA nucleobases were observed at different pH conditions. These results have significant implications for developing a robust and accurate high-throughput nanoelectronic DNA sequencing technique. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations

PubMed Central

Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

2015-01-01

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions. PMID:26089862

Combining MLC and SVM Classifiers for Learning Based Decision Making: Analysis and Evaluations.

PubMed

Zhang, Yi; Ren, Jinchang; Jiang, Jianmin

2015-01-01

Maximum likelihood classifier (MLC) and support vector machines (SVM) are two commonly used approaches in machine learning. MLC is based on Bayesian theory in estimating parameters of a probabilistic model, whilst SVM is an optimization based nonparametric method in this context. Recently, it is found that SVM in some cases is equivalent to MLC in probabilistically modeling the learning process. In this paper, MLC and SVM are combined in learning and classification, which helps to yield probabilistic output for SVM and facilitate soft decision making. In total four groups of data are used for evaluations, covering sonar, vehicle, breast cancer, and DNA sequences. The data samples are characterized in terms of Gaussian/non-Gaussian distributed and balanced/unbalanced samples which are then further used for performance assessment in comparing the SVM and the combined SVM-MLC classifier. Interesting results are reported to indicate how the combined classifier may work under various conditions.

DNA methylation mediates neural processing after odor learning in the honeybee

PubMed Central

Biergans, Stephanie D.; Claudianos, Charles; Reinhard, Judith; Galizia, C. Giovanni

2017-01-01

DNA methyltransferases (Dnmts) - epigenetic writers catalyzing the transfer of methyl-groups to cytosine (DNA methylation) – regulate different aspects of memory formation in many animal species. In honeybees, Dnmt activity is required to adjust the specificity of olfactory reward memories and bees’ relearning capability. The physiological relevance of Dnmt-mediated DNA methylation in neural networks, however, remains unknown. Here, we investigated how Dnmt activity impacts neuroplasticity in the bees’ primary olfactory center, the antennal lobe (AL) an equivalent of the vertebrate olfactory bulb. The AL is crucial for odor discrimination, an indispensable process in forming specific odor memories. Using pharmacological inhibition, we demonstrate that Dnmt activity influences neural network properties during memory formation in vivo. We show that Dnmt activity promotes fast odor pattern separation in trained bees. Furthermore, Dnmt activity during memory formation increases both the number of responding glomeruli and the response magnitude to a novel odor. These data suggest that Dnmt activity is necessary for a form of homoeostatic network control which might involve inhibitory interneurons in the AL network. PMID:28240742

Designing easy DNA extraction: Teaching creativity through laboratory practice.

PubMed

Susantini, Endang; Lisdiana, Lisa; Isnawati; Tanzih Al Haq, Aushia; Trimulyono, Guntur

2017-05-01

Subject material concerning Deoxyribose Nucleic Acid (DNA) structure in the format of creativity-driven laboratory practice offers meaningful learning experience to the students. Therefore, a laboratory practice in which utilizes simple procedures and easy-safe-affordable household materials should be promoted to students to develop their creativity. This study aimed to examine whether designing and conducting DNA extraction with household materials could foster students' creative thinking. We also described how this laboratory practice affected students' knowledge and views. A total of 47 students participated in this study. These students were grouped and asked to utilize available household materials and modify procedures using hands-on worksheet. Result showed that this approach encouraged creative thinking as well as improved subject-related knowledge. Students also demonstrated positive views about content knowledge, social skills, and creative thinking skills. This study implies that extracting DNA with household materials is able to develop content knowledge, social skills, and creative thinking of the students. © 2016 by The International Union of Biochemistry and Molecular Biology, 45(3):216-225, 2017. © 2016 The International Union of Biochemistry and Molecular Biology.

The identification of cis-regulatory elements: A review from a machine learning perspective.

PubMed

Li, Yifeng; Chen, Chih-Yu; Kaye, Alice M; Wasserman, Wyeth W

2015-12-01

The majority of the human genome consists of non-coding regions that have been called junk DNA. However, recent studies have unveiled that these regions contain cis-regulatory elements, such as promoters, enhancers, silencers, insulators, etc. These regulatory elements can play crucial roles in controlling gene expressions in specific cell types, conditions, and developmental stages. Disruption to these regions could contribute to phenotype changes. Precisely identifying regulatory elements is key to deciphering the mechanisms underlying transcriptional regulation. Cis-regulatory events are complex processes that involve chromatin accessibility, transcription factor binding, DNA methylation, histone modifications, and the interactions between them. The development of next-generation sequencing techniques has allowed us to capture these genomic features in depth. Applied analysis of genome sequences for clinical genetics has increased the urgency for detecting these regions. However, the complexity of cis-regulatory events and the deluge of sequencing data require accurate and efficient computational approaches, in particular, machine learning techniques. In this review, we describe machine learning approaches for predicting transcription factor binding sites, enhancers, and promoters, primarily driven by next-generation sequencing data. Data sources are provided in order to facilitate testing of novel methods. The purpose of this review is to attract computational experts and data scientists to advance this field. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

Problems with DNA

ERIC Educational Resources Information Center

Erickson, Keith A.; Franciszkowicz, Marc J.

2010-01-01

A modified version of this project was used during the final seven days of a year-long calculus sequence at the United States Military Academy to introduce students to the nature of integrative learning. Students from different majors were brought together in groups and spent the first few days going over the mathematics material presented here.…

A Different Kind of Diversity: Collaboration across Content Areas Intensifies Learning

ERIC Educational Resources Information Center

Goble, Ryan R.; Sousanis, Nick

2010-01-01

The discovery of DNA is a classic example of the importance of working across content areas. Conceptually, interdisciplinarity can be fuzzy. Thankfully, scholars like Allen Repko and Julie Thompson Klein offer definitions one can build on. Klein (1990) sees interdisciplinarity as a bridge that links different disciplines while restructuring and…

A Role for Histone Deacetylases in the Cellular and Behavioral Mechanisms Underlying Learning and Memory

ERIC Educational Resources Information Center

Mahgoub, Melissa; Monteggia, Lisa M.

2014-01-01

Histone deacetylases (HDACs) are a family of chromatin remodeling enzymes that restrict access of transcription factors to the DNA, thereby repressing gene expression. In contrast, histone acetyltransferases (HATs) relax the chromatin structure allowing for an active chromatin state and promoting gene transcription. Accumulating data have…

Investigating Novice and Expert Conceptions of Genetically Modified Organisms

ERIC Educational Resources Information Center

Potter, Lisa M.; Bissonnette, Sarah A.; Knight, Jonathan D.; Tanner, Kimberly D.

2017-01-01

The aspiration of biology education is to give students tools to apply knowledge learned in the classroom to everyday life. Genetic modification is a real-world biological concept that relies on an in-depth understanding of the molecular behavior of DNA and proteins. This study investigated undergraduate biology students' conceptions of…

Chromatin accessibility prediction via a hybrid deep convolutional neural network.

PubMed

Liu, Qiao; Xia, Fei; Yin, Qijin; Jiang, Rui

2018-03-01

A majority of known genetic variants associated with human-inherited diseases lie in non-coding regions that lack adequate interpretation, making it indispensable to systematically discover functional sites at the whole genome level and precisely decipher their implications in a comprehensive manner. Although computational approaches have been complementing high-throughput biological experiments towards the annotation of the human genome, it still remains a big challenge to accurately annotate regulatory elements in the context of a specific cell type via automatic learning of the DNA sequence code from large-scale sequencing data. Indeed, the development of an accurate and interpretable model to learn the DNA sequence signature and further enable the identification of causative genetic variants has become essential in both genomic and genetic studies. We proposed Deopen, a hybrid framework mainly based on a deep convolutional neural network, to automatically learn the regulatory code of DNA sequences and predict chromatin accessibility. In a series of comparison with existing methods, we show the superior performance of our model in not only the classification of accessible regions against background sequences sampled at random, but also the regression of DNase-seq signals. Besides, we further visualize the convolutional kernels and show the match of identified sequence signatures and known motifs. We finally demonstrate the sensitivity of our model in finding causative noncoding variants in the analysis of a breast cancer dataset. We expect to see wide applications of Deopen with either public or in-house chromatin accessibility data in the annotation of the human genome and the identification of non-coding variants associated with diseases. Deopen is freely available at https://github.com/kimmo1019/Deopen. ruijiang@tsinghua.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Protecting genomic sequence anonymity with generalization lattices.

PubMed

Malin, B A

2005-01-01

Current genomic privacy technologies assume the identity of genomic sequence data is protected if personal information, such as demographics, are obscured, removed, or encrypted. While demographic features can directly compromise an individual's identity, recent research demonstrates such protections are insufficient because sequence data itself is susceptible to re-identification. To counteract this problem, we introduce an algorithm for anonymizing a collection of person-specific DNA sequences. The technique is termed DNA lattice anonymization (DNALA), and is based upon the formal privacy protection schema of k -anonymity. Under this model, it is impossible to observe or learn features that distinguish one genetic sequence from k-1 other entries in a collection. To maximize information retained in protected sequences, we incorporate a concept generalization lattice to learn the distance between two residues in a single nucleotide region. The lattice provides the most similar generalized concept for two residues (e.g. adenine and guanine are both purines). The method is tested and evaluated with several publicly available human population datasets ranging in size from 30 to 400 sequences. Our findings imply the anonymization schema is feasible for the protection of sequences privacy. The DNALA method is the first computational disclosure control technique for general DNA sequences. Given the computational nature of the method, guarantees of anonymity can be formally proven. There is room for improvement and validation, though this research provides the groundwork from which future researchers can construct genomics anonymization schemas tailored to specific datasharing scenarios.

Recognition Tunneling of Canonical and Modified RNA Nucleotides for Their Identification with the Aid of Machine Learning.

PubMed

Im, JongOne; Sen, Suman; Lindsay, Stuart; Zhang, Peiming

2018-06-28

In the present study, we demonstrate a tunneling nanogap technique to identify individual RNA nucleotides, which can be used as a mechanism to read the nucleobases for direct sequencing of RNA in a solid-state nanopore. The tunneling nanogap is composed of two electrodes separated by a distance of <3 nm and functionalized with a recognition molecule. When a chemical entity is captured in the gap, it generates electron tunneling currents, a process we call recognition tunneling (RT). Using RT nanogaps created in a scanning tunneling microscope (STM), we acquired the electron tunneling signals for the canonical and two modified RNA nucleotides. To call the individual RNA nucleotides from the RT data, we adopted a machine learning algorithm, support vector machine (SVM), for the data analysis. Through the SVM, we were able to identify the individual RNA nucleotides and distinguish them from their DNA counterparts with reasonably high accuracy. Since each RNA nucleoside contains a hydroxyl group at the 2'-position of its sugar ring in an RNA strand, it allows for the formation of a tunneling junction at a larger nanogap compared to the DNA nucleoside in a DNA strand, which lacks the 2' hydroxyl group. It also proves advantageous for the manufacture of RT devices. This study is a proof-of-principle demonstration for the development of an RT nanopore device for directly sequencing single RNA molecules, including those bearing modifications.

Insufficient DNA methylation affects healthy aging and promotes age-related health problems.

PubMed

Liu, Liang; van Groen, Thomas; Kadish, Inga; Li, Yuanyuan; Wang, Deli; James, Smitha R; Karpf, Adam R; Tollefsbol, Trygve O

2011-08-01

DNA methylation plays an integral role in development and aging through epigenetic regulation of genome function. DNA methyltransferase 1 (Dnmt1) is the most prevalent DNA methyltransferase that maintains genomic methylation stability. To further elucidate the function of Dnmt1 in aging and age-related diseases, we exploited the Dnmt1+/- mouse model to investigate how Dnmt1 haploinsufficiency impacts the aging process by assessing the changes of several major aging phenotypes. We confirmed that Dnmt1 haploinsufficiency indeed decreases DNA methylation as a result of reduced Dnmt1 expression. To assess the effect of Dnmt1 haploinsufficiency on general body composition, we performed dual-energy X-ray absorptiometry analysis and showed that reduced Dnmt1 activity decreased bone mineral density and body weight, but with no significant impact on mortality or body fat content. Using behavioral tests, we demonstrated that Dnmt1 haploinsufficiency impairs learning and memory functions in an age-dependent manner. Taken together, our findings point to the interesting likelihood that reduced genomic methylation activity adversely affects the healthy aging process without altering survival and mortality. Our studies demonstrated that cognitive functions of the central nervous system are modulated by Dnmt1 activity and genomic methylation, highlighting the significance of the original epigenetic hypothesis underlying memory coding and function.

Living Organisms Author Their Read-Write Genomes in Evolution

PubMed Central

2017-01-01

Evolutionary variations generating phenotypic adaptations and novel taxa resulted from complex cellular activities altering genome content and expression: (i) Symbiogenetic cell mergers producing the mitochondrion-bearing ancestor of eukaryotes and chloroplast-bearing ancestors of photosynthetic eukaryotes; (ii) interspecific hybridizations and genome doublings generating new species and adaptive radiations of higher plants and animals; and, (iii) interspecific horizontal DNA transfer encoding virtually all of the cellular functions between organisms and their viruses in all domains of life. Consequently, assuming that evolutionary processes occur in isolated genomes of individual species has become an unrealistic abstraction. Adaptive variations also involved natural genetic engineering of mobile DNA elements to rewire regulatory networks. In the most highly evolved organisms, biological complexity scales with “non-coding” DNA content more closely than with protein-coding capacity. Coincidentally, we have learned how so-called “non-coding” RNAs that are rich in repetitive mobile DNA sequences are key regulators of complex phenotypes. Both biotic and abiotic ecological challenges serve as triggers for episodes of elevated genome change. The intersections of cell activities, biosphere interactions, horizontal DNA transfers, and non-random Read-Write genome modifications by natural genetic engineering provide a rich molecular and biological foundation for understanding how ecological disruptions can stimulate productive, often abrupt, evolutionary transformations. PMID:29211049

Living Organisms Author Their Read-Write Genomes in Evolution.

PubMed

Shapiro, James A

2017-12-06

Evolutionary variations generating phenotypic adaptations and novel taxa resulted from complex cellular activities altering genome content and expression: (i) Symbiogenetic cell mergers producing the mitochondrion-bearing ancestor of eukaryotes and chloroplast-bearing ancestors of photosynthetic eukaryotes; (ii) interspecific hybridizations and genome doublings generating new species and adaptive radiations of higher plants and animals; and, (iii) interspecific horizontal DNA transfer encoding virtually all of the cellular functions between organisms and their viruses in all domains of life. Consequently, assuming that evolutionary processes occur in isolated genomes of individual species has become an unrealistic abstraction. Adaptive variations also involved natural genetic engineering of mobile DNA elements to rewire regulatory networks. In the most highly evolved organisms, biological complexity scales with "non-coding" DNA content more closely than with protein-coding capacity. Coincidentally, we have learned how so-called "non-coding" RNAs that are rich in repetitive mobile DNA sequences are key regulators of complex phenotypes. Both biotic and abiotic ecological challenges serve as triggers for episodes of elevated genome change. The intersections of cell activities, biosphere interactions, horizontal DNA transfers, and non-random Read-Write genome modifications by natural genetic engineering provide a rich molecular and biological foundation for understanding how ecological disruptions can stimulate productive, often abrupt, evolutionary transformations.

A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network.

PubMed

Fiannaca, Antonino; La Rosa, Massimo; Rizzo, Riccardo; Urso, Alfonso

2015-07-01

In this paper, an alignment-free method for DNA barcode classification that is based on both a spectral representation and a neural gas network for unsupervised clustering is proposed. In the proposed methodology, distinctive words are identified from a spectral representation of DNA sequences. A taxonomic classification of the DNA sequence is then performed using the sequence signature, i.e., the smallest set of k-mers that can assign a DNA sequence to its proper taxonomic category. Experiments were then performed to compare our method with other supervised machine learning classification algorithms, such as support vector machine, random forest, ripper, naïve Bayes, ridor, and classification tree, which also consider short DNA sequence fragments of 200 and 300 base pairs (bp). The experimental tests were conducted over 10 real barcode datasets belonging to different animal species, which were provided by the on-line resource "Barcode of Life Database". The experimental results showed that our k-mer-based approach is directly comparable, in terms of accuracy, recall and precision metrics, with the other classifiers when considering full-length sequences. In addition, we demonstrate the robustness of our method when a classification is performed task with a set of short DNA sequences that were randomly extracted from the original data. For example, the proposed method can reach the accuracy of 64.8% at the species level with 200-bp fragments. Under the same conditions, the best other classifier (random forest) reaches the accuracy of 20.9%. Our results indicate that we obtained a clear improvement over the other classifiers for the study of short DNA barcode sequence fragments. Copyright © 2015 Elsevier B.V. All rights reserved.

'DNA Strider': a 'C' program for the fast analysis of DNA and protein sequences on the Apple Macintosh family of computers.

PubMed Central

Marck, C

1988-01-01

DNA Strider is a new integrated DNA and Protein sequence analysis program written with the C language for the Macintosh Plus, SE and II computers. It has been designed as an easy to learn and use program as well as a fast and efficient tool for the day-to-day sequence analysis work. The program consists of a multi-window sequence editor and of various DNA and Protein analysis functions. The editor may use 4 different types of sequences (DNA, degenerate DNA, RNA and one-letter coded protein) and can handle simultaneously 6 sequences of any type up to 32.5 kB each. Negative numbering of the bases is allowed for DNA sequences. All classical restriction and translation analysis functions are present and can be performed in any order on any open sequence or part of a sequence. The main feature of the program is that the same analysis function can be repeated several times on different sequences, thus generating multiple windows on the screen. Many graphic capabilities have been incorporated such as graphic restriction map, hydrophobicity profile and the CAI plot- codon adaptation index according to Sharp and Li. The restriction sites search uses a newly designed fast hexamer look-ahead algorithm. Typical runtime for the search of all sites with a library of 130 restriction endonucleases is 1 second per 10,000 bases. The circular graphic restriction map of the pBR322 plasmid can be therefore computed from its sequence and displayed on the Macintosh Plus screen within 2 seconds and its multiline restriction map obtained in a scrolling window within 5 seconds. PMID:2832831

Practicality in Virtuality: Finding Student Meaning in Video Game Education

NASA Astrophysics Data System (ADS)

Barko, Timothy; Sadler, Troy D.

2013-04-01

This paper looks at the conceptual differences between video game learning and traditional classroom and laboratory learning. It explores the notion of virtual experience by comparing a commonly used high school laboratory protocol on DNA extraction with a similar experience provided by a biotechnology themed video game. When considered conceptually, the notion of virtual experience is not limited to those experiences generated by computer aided technology, as with a video game or computer simulation. The notion of virtuality can apply to many real world experiences as well. It is proposed that the medium of the learning experience, be it video game or classroom, is not an important distinction to consider; instead, we should seek to determine what kinds of meaningful experiences apply for both classrooms and video games.

Ten-Year Retrospective Longitudinal-Study of Student Perspectives on Value of REU

NASA Astrophysics Data System (ADS)

Slater, T. F.; Slater, S. J.

2013-12-01

For more than two decades, federal agencies have been enthusiastically supporting summer research experiences for undergraduates. These REU programs are tacitly intended to increase retention and provide "an important educational experience" for undergraduates, particularly women, minorities and underrepresented groups. Numerous authors (viz., Laursen, Lopatto, Dolan, among many others) have enthusiastically described positive impacts of summer REU programs from exit interview data. These results include enhanced persistence to pursue STEM careers and confirmed desire to attend graduate school in the field targeted by a particular REU. Perhaps surprisingly, negative student experiences are rarely described in the scholarly literature, but do appear in more informal publications (viz., Gueterma, 2007). One wonders how REU alumni, looking back over their entire collective portfolio of experiences, now perceive the educational value of their REU experience relative to their other educational experiences. To obtain a backwards-looking, reflective description from REU alumni on the value of their REU experiences, we conducted a 10-year, two-stage study was designed to explore the ways in which the REU acted as an educational experience for 51 women from a single geoscience sub-discipline. The first phase was an ex post facto longitudinal analysis of data, including multiple interviews with each participant during their REU, annual open-ended alumni surveys, faculty interviews, and extensive field notes, over a 10-year period. This analysis informed the second phase, a clinical interview. Over 10 hours of interviews with 8 participants were conducted and analyzed. These 8 participants were selected to represent a variety of career stages, and for their potential to reflect on a wide variety of educational experiences. Results from the interviews, done many years after their REU experience, indicate that the interviewees' REU did not provide a substantive educational experience related to the nature of scientific work, the scientific process, or the culture of academia when considered in a comparative context of students' other educational experiences. Results further indicated that the REU did not serve to transform participants' conceptions about themselves as situated in science, and learning gains with regard to other aspects of the self, were somewhat limited. Instead, the data suggests that these women arrived at the REU with pre-existing and remarkably strong conceptions in these areas, and that the REU did not functional to alter those states. These conceptions were frequently the result of interactions with mentors/scientists from middle school until well into the undergraduate period.

A Faculty Professional Development Model That Improves Student Learning, Encourages Active-Learning Instructional Practices, and Works for Faculty at Multiple Institutions.

PubMed

Pelletreau, Karen N; Knight, Jennifer K; Lemons, Paula P; McCourt, Jill S; Merrill, John E; Nehm, Ross H; Prevost, Luanna B; Urban-Lurain, Mark; Smith, Michelle K

2018-06-01

Helping faculty develop high-quality instruction that positively affects student learning can be complicated by time limitations, a lack of resources, and inexperience using student data to make iterative improvements. We describe a community of 16 faculty from five institutions who overcame these challenges and collaboratively designed, taught, iteratively revised, and published an instructional unit about the potential effect of mutations on DNA replication, transcription, and translation. The unit was taught to more than 2000 students in 18 courses, and student performance improved from preassessment to postassessment in every classroom. This increase occurred even though faculty varied in their instructional practices when they were teaching identical materials. We present information on how this faculty group was organized and facilitated, how members used student data to positively affect learning, and how they increased their use of active-learning instructional practices in the classroom as a result of participation. We also interviewed faculty to learn more about the most useful components of the process. We suggest that this professional development model can be used for geographically separated faculty who are interested in working together on a known conceptual difficulty to improve student learning and explore active-learning instructional practices.

Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding.

PubMed

Min, Xu; Zeng, Wanwen; Chen, Ning; Chen, Ting; Jiang, Rui

2017-07-15

Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing methods fall into two classes: one based on handcrafted k -mer features and the other based on convolutional neural networks. Although both categories have shown good performance in specific applications thus far, there still lacks a comprehensive framework to integrate useful k -mer co-occurrence information with recent advances in deep learning. We fill this gap by addressing the problem of chromatin accessibility prediction with a convolutional Long Short-Term Memory (LSTM) network with k -mer embedding. We first split DNA sequences into k -mers and pre-train k -mer embedding vectors based on the co-occurrence matrix of k -mers by using an unsupervised representation learning approach. We then construct a supervised deep learning architecture comprised of an embedding layer, three convolutional layers and a Bidirectional LSTM (BLSTM) layer for feature learning and classification. We demonstrate that our method gains high-quality fixed-length features from variable-length sequences and consistently outperforms baseline methods. We show that k -mer embedding can effectively enhance model performance by exploring different embedding strategies. We also prove the efficacy of both the convolution and the BLSTM layers by comparing two variations of the network architecture. We confirm the robustness of our model to hyper-parameters by performing sensitivity analysis. We hope our method can eventually reinforce our understanding of employing deep learning in genomic studies and shed light on research regarding mechanisms of chromatin accessibility. The source code can be downloaded from https://github.com/minxueric/ismb2017_lstm . tingchen@tsinghua.edu.cn or ruijiang@tsinghua.edu.cn. Supplementary materials are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding

PubMed Central

Min, Xu; Zeng, Wanwen; Chen, Ning; Chen, Ting; Jiang, Rui

2017-01-01

Abstract Motivation: Experimental techniques for measuring chromatin accessibility are expensive and time consuming, appealing for the development of computational approaches to predict open chromatin regions from DNA sequences. Along this direction, existing methods fall into two classes: one based on handcrafted k-mer features and the other based on convolutional neural networks. Although both categories have shown good performance in specific applications thus far, there still lacks a comprehensive framework to integrate useful k-mer co-occurrence information with recent advances in deep learning. Results: We fill this gap by addressing the problem of chromatin accessibility prediction with a convolutional Long Short-Term Memory (LSTM) network with k-mer embedding. We first split DNA sequences into k-mers and pre-train k-mer embedding vectors based on the co-occurrence matrix of k-mers by using an unsupervised representation learning approach. We then construct a supervised deep learning architecture comprised of an embedding layer, three convolutional layers and a Bidirectional LSTM (BLSTM) layer for feature learning and classification. We demonstrate that our method gains high-quality fixed-length features from variable-length sequences and consistently outperforms baseline methods. We show that k-mer embedding can effectively enhance model performance by exploring different embedding strategies. We also prove the efficacy of both the convolution and the BLSTM layers by comparing two variations of the network architecture. We confirm the robustness of our model to hyper-parameters by performing sensitivity analysis. We hope our method can eventually reinforce our understanding of employing deep learning in genomic studies and shed light on research regarding mechanisms of chromatin accessibility. Availability and implementation: The source code can be downloaded from https://github.com/minxueric/ismb2017_lstm. Contact: tingchen@tsinghua.edu.cn or ruijiang@tsinghua.edu.cn Supplementary information: Supplementary materials are available at Bioinformatics online. PMID:28881969

Bioinformatics algorithm based on a parallel implementation of a machine learning approach using transducers

NASA Astrophysics Data System (ADS)

Roche-Lima, Abiel; Thulasiram, Ruppa K.

2012-02-01

Finite automata, in which each transition is augmented with an output label in addition to the familiar input label, are considered finite-state transducers. Transducers have been used to analyze some fundamental issues in bioinformatics. Weighted finite-state transducers have been proposed to pairwise alignments of DNA and protein sequences; as well as to develop kernels for computational biology. Machine learning algorithms for conditional transducers have been implemented and used for DNA sequence analysis. Transducer learning algorithms are based on conditional probability computation. It is calculated by using techniques, such as pair-database creation, normalization (with Maximum-Likelihood normalization) and parameters optimization (with Expectation-Maximization - EM). These techniques are intrinsically costly for computation, even worse when are applied to bioinformatics, because the databases sizes are large. In this work, we describe a parallel implementation of an algorithm to learn conditional transducers using these techniques. The algorithm is oriented to bioinformatics applications, such as alignments, phylogenetic trees, and other genome evolution studies. Indeed, several experiences were developed using the parallel and sequential algorithm on Westgrid (specifically, on the Breeze cluster). As results, we obtain that our parallel algorithm is scalable, because execution times are reduced considerably when the data size parameter is increased. Another experience is developed by changing precision parameter. In this case, we obtain smaller execution times using the parallel algorithm. Finally, number of threads used to execute the parallel algorithm on the Breezy cluster is changed. In this last experience, we obtain as result that speedup is considerably increased when more threads are used; however there is a convergence for number of threads equal to or greater than 16.

Health Detectives: Uncovering the Mysteries of Disease (LBNL Science at the Theater)

ScienceCinema

Bissell, Mina; Canaria, Christie; Celnicker, Susan; Karpen, Gary

2018-06-20

In this April 23, 2012 Science at the Theater event, Berkeley Lab scientists discuss how they uncover the mysteries of disease in unlikely places. Speakers and topics include: World-renowned cancer researcher Mina Bissell's pioneering research on the role of the cellular microenvironment in breast cancer has changed the conversation about the disease. How does DNA instability cause disease? To find out, Christie Canaria images neural networks to study disorders such as Huntington's disease. Fruit flies can tell us a lot about ourselves. Susan Celniker explores the fruit fly genome to learn how our genome works. DNA is not destiny. Gary Karpen explores how environmental factors shape genome function and disease through epigenetics.

In Touch with Molecules: Improving Student Learning with Innovative Molecular Models

ERIC Educational Resources Information Center

Davenport, Jodi; Silberglitt, Matt; Olson, Arthur

2013-01-01

How do viruses self-assemble? Why do DNA bases pair the way they do? What factors determine whether strands of proteins fold into sheets or helices? Why does handedness matter? A deep understanding of core issues in biology requires students to understand both complex spatial structures of molecules and the interactions involved in dynamic…

Using DNA Technology to Explore Marine Bacterial Diversity in a Coastal Georgia Salt Marsh

ERIC Educational Resources Information Center

Dong, Yihe; Guerrero, Stella; Moran, Mary Ann

2008-01-01

An important aspect of teaching biology is to expose students to the concept of biodiversity. For this purpose, bacteria are excellent examples. The advanced placement (AP) biology class at Cedar Shoals High School in Athens, Georgia, learned how to explore bacterial biodiversity using molecular fingerprinting. They collected marine water samples,…

Tangible Models and Haptic Representations Aid Learning of Molecular Biology Concepts

ERIC Educational Resources Information Center

Johannes, Kristen; Powers, Jacklyn; Couper, Lisa; Silberglitt, Matt; Davenport, Jodi

2016-01-01

Can novel 3D models help students develop a deeper understanding of core concepts in molecular biology? We adapted 3D molecular models, developed by scientists, for use in high school science classrooms. The models accurately represent the structural and functional properties of complex DNA and Virus molecules, and provide visual and haptic…

A Ten-Week Biochemistry Lab Project Studying Wild-Type and Mutant Bacterial Alkaline Phosphatase

ERIC Educational Resources Information Center

Witherow, D. Scott

2016-01-01

This work describes a 10-week laboratory project studying wild-type and mutant bacterial alkaline phosphatase, in which students purify, quantitate, and perform kinetic assays on wild-type and selected mutants of the enzyme. Students also perform plasmid DNA purification, digestion, and gel analysis. In addition to simply learning important…

DNA Replication and Transcription: An Innovative Teaching Strategy

ERIC Educational Resources Information Center

Fossey, Annabel; Hancock, Carolyn

2005-01-01

First-year students in genetics at the University of KwaZulu-Natal, South Africa, attend two general biology modules, one in each semester. Teaching involves four formal lectures per week of 45 min each, one 3-h practical, and one lecture period tutorial. These students, graduating from secondary education, are well schooled in rote learning but…

New approach for the study of mite reproduction: the first transcriptome analysis of a mite, Phytoseiulus persimilis (Acari: Phytoseiidae)

USDA-ARS?s Scientific Manuscript database

Many species of mites and ticks are of agricultural and medical importance. Much can be learned from the study of transcriptomes of acarines which can generate DNA-sequence information of potential target genes for the control of acarine pests. High throughput transcriptome sequencing can also yie...

Semi-Supervised Projective Non-Negative Matrix Factorization for Cancer Classification.

PubMed

Zhang, Xiang; Guan, Naiyang; Jia, Zhilong; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Advances in DNA microarray technologies have made gene expression profiles a significant candidate in identifying different types of cancers. Traditional learning-based cancer identification methods utilize labeled samples to train a classifier, but they are inconvenient for practical application because labels are quite expensive in the clinical cancer research community. This paper proposes a semi-supervised projective non-negative matrix factorization method (Semi-PNMF) to learn an effective classifier from both labeled and unlabeled samples, thus boosting subsequent cancer classification performance. In particular, Semi-PNMF jointly learns a non-negative subspace from concatenated labeled and unlabeled samples and indicates classes by the positions of the maximum entries of their coefficients. Because Semi-PNMF incorporates statistical information from the large volume of unlabeled samples in the learned subspace, it can learn more representative subspaces and boost classification performance. We developed a multiplicative update rule (MUR) to optimize Semi-PNMF and proved its convergence. The experimental results of cancer classification for two multiclass cancer gene expression profile datasets show that Semi-PNMF outperforms the representative methods.

Design Pattern Mining Using Distributed Learning Automata and DNA Sequence Alignment

PubMed Central

Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina

2014-01-01

Context Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. Objective This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. Method The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. Results The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. Conclusion The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns. PMID:25243670

Dynamic DNA Methylation Controls Glutamate Receptor Trafficking and Synaptic Scaling

PubMed Central

Sweatt, J. David

2016-01-01

Hebbian plasticity, including LTP and LTD, has long been regarded as important for local circuit refinement in the context of memory formation and stabilization. However, circuit development and stabilization additionally relies on non-Hebbian, homoeostatic, forms of plasticity such as synaptic scaling. Synaptic scaling is induced by chronic increases or decreases in neuronal activity. Synaptic scaling is associated with cell-wide adjustments in postsynaptic receptor density, and can occur in a multiplicative manner resulting in preservation of relative synaptic strengths across the entire neuron's population of synapses. Both active DNA methylation and de-methylation have been validated as crucial regulators of gene transcription during learning, and synaptic scaling is known to be transcriptionally dependent. However, it has been unclear whether homeostatic forms of plasticity such as synaptic scaling are regulated via epigenetic mechanisms. This review describes exciting recent work that has demonstrated a role for active changes in neuronal DNA methylation and demethylation as a controller of synaptic scaling and glutamate receptor trafficking. These findings bring together three major categories of memory-associated mechanisms that were previously largely considered separately: DNA methylation, homeostatic plasticity, and glutamate receptor trafficking. PMID:26849493

MeCP2 regulates Tet1-catalyzed demethylation, CTCF binding, and learning-dependent alternative splicing of the BDNF gene in Turtle

PubMed Central

Zheng, Zhaoqing; Ambigapathy, Ganesh; Keifer, Joyce

2017-01-01

MECP2 mutations underlying Rett syndrome cause widespread misregulation of gene expression. Functions for MeCP2 other than transcriptional are not well understood. In an ex vivo brain preparation from the pond turtle Trachemys scripta elegans, an intraexonic splicing event in the brain-derived neurotrophic factor (BDNF) gene generates a truncated mRNA transcript in naïve brain that is suppressed upon classical conditioning. MeCP2 and its partners, splicing factor Y-box binding protein 1 (YB-1) and methylcytosine dioxygenase 1 (Tet1), bind to BDNF chromatin in naïve but dissociate during conditioning; the dissociation correlating with decreased DNA methylation. Surprisingly, conditioning results in new occupancy of BDNF chromatin by DNA insulator protein CCCTC-binding factor (CTCF), which is associated with suppression of splicing in conditioning. Knockdown of MeCP2 shows it is instrumental for splicing and inhibits Tet1 and CTCF binding thereby negatively impacting DNA methylation and conditioning-dependent splicing regulation. Thus, mutations in MECP2 can have secondary effects on DNA methylation and alternative splicing. DOI: http://dx.doi.org/10.7554/eLife.25384.001 PMID:28594324

Protocol matters: which methylome are you actually studying?

PubMed Central

Robinson, Mark D; Statham, Aaron L; Speed, Terence P; Clark, Susan J

2011-01-01

The field of epigenetics is now capitalizing on the vast number of emerging technologies, largely based on second-generation sequencing, which interrogate DNA methylation status and histone modifications genome-wide. However, getting an exhaustive and unbiased view of a methylome at a reasonable cost is proving to be a significant challenge. In this article, we take a closer look at the impact of the DNA sequence and bias effects introduced to datasets by genome-wide DNA methylation technologies and where possible, explore the bioinformatics tools that deconvolve them. There remains much to be learned about the performance of genome-wide technologies, the data we mine from these assays and how it reflects the actual biology. While there are several methods to interrogate the DNA methylation status genome-wide, our opinion is that no single technique suitably covers the minimum criteria of high coverage and, high resolution at a reasonable cost. In fact, the fraction of the methylome that is studied currently depends entirely on the inherent biases of the protocol employed. There is promise for this to change, as the third generation of sequencing technologies is expected to again ‘revolutionize’ the way that we study genomes and epigenomes. PMID:21566704

Whose genome is it, anyway?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marshall, E.

1996-09-27

The genome program has issued guidelines to ensure that sequencing is done on DNA from diverse sources who have given informed consent and are anonymous. Most current sources don`t meet those criteria. It may be the first question every nonexpert asks on learning about the Human Genome Project: Whose genome are we studying, anyway? It sounds naive, says one government scientist-so naive, in fact, that {open_quotes}we chuckle as we explain that we aren`t sequencing anyone`s genome in particular; we`re sequencing a representative genome{close_quotes} made up of a mosaic of DNA from a variety of anonymous sources. And Bruce Birren, amore » clone-maker now at the Massachusetts Institute of Technology`s (MIT`s) Whitehead Center for Genome Research says: {open_quotes}We spent many years pooh-poohing the question{close_quotes} of whose genome would be stored in the database. But now that labs have begun working on large stretches of human DNA-aiming to identify all 3 billion base pairs in the genetic code-the question no longer seems to laughable. To the distress of program managers in Bethesda, Maryland, the initial sources of DNA are not as diverse or as anonymous as they had assumed.« less

Aligning Goals, Assessments, and Activities: An Approach to Teaching PCR and Gel Electrophoresis

PubMed Central

Robertson, Amber L.; Batzli, Janet; Harris, Michelle; Miller, Sarah

2008-01-01

Polymerase chain reaction (PCR) and gel electrophoresis have become common techniques used in undergraduate molecular and cell biology labs. Although students enjoy learning these techniques, they often cannot fully comprehend and analyze the outcomes of their experiments because of a disconnect between concepts taught in lecture and experiments done in lab. Here we report the development and implementation of novel exercises that integrate the biological concepts of DNA structure and replication with the techniques of PCR and gel electrophoresis. Learning goals were defined based on concepts taught throughout the cell biology lab course and learning objectives specific to the PCR and gel electrophoresis lab. Exercises developed to promote critical thinking and target the underlying concepts of PCR, primer design, gel analysis, and troubleshooting were incorporated into an existing lab unit based on the detection of genetically modified organisms. Evaluative assessments for each exercise were aligned with the learning goals and used to measure student learning achievements. Our analysis found that the exercises were effective in enhancing student understanding of these concepts as shown by student performance across all learning goals. The new materials were particularly helpful in acquiring relevant knowledge, fostering critical-thinking skills, and uncovering prevalent misconceptions. PMID:18316813

DNA Dispose, but Subjects Decide. Learning and the Extended Synthesis.

PubMed

Lindholm, Markus

Adaptation by means of natural selection depends on the ability of populations to maintain variation in heritable traits. According to the Modern Synthesis this variation is sustained by mutations and genetic drift. Epigenetics, evodevo, niche construction and cultural factors have more recently been shown to contribute to heritable variation, however, leading an increasing number of biologists to call for an extended view of speciation and evolution. An additional common feature across the animal kingdom is learning, defined as the ability to change behavior according to novel experiences or skills. Learning constitutes an additional source for phenotypic variation, and change in behavior may induce long lasting shifts in fitness, and hence favor evolutionary novelties. Based on published studies, I demonstrate how learning about food, mate choice and habitats has contributed substantially to speciation in the canonical story of Darwin's finches on the Galapagos Islands. Learning cannot be reduced to genetics, because it demands decisions, which requires a subject. Evolutionary novelties may hence emerge both from shifts in allelic frequencies and from shifts in learned, subject driven behavior. The existence of two principally different sources of variation also prevents the Modern Synthesis from self-referring explanations.

CB1-receptor knockout neonatal mice are protected against ethanol-induced impairments of DNMT1, DNMT3A, and DNA methylation.

PubMed

Nagre, Nagaraja N; Subbanna, Shivakumar; Shivakumar, Madhu; Psychoyos, Delphine; Basavarajappa, Balapal S

2015-02-01

The significant consequences of ethanol use during pregnancy are neurobehavioral abnormalities involving hippocampal and neocortex malfunctions that cause learning and memory deficits collectively named fetal alcohol spectrum disorder. However, the molecular mechanisms underlying these abnormalities are still poorly understood and therefore warrant systematic research. Here, we document novel epigenetic abnormalities in the mouse model of fetal alcohol spectrum disorder. Ethanol treatment of P7 mice, which induces activation of caspase 3, impaired DNA methylation through reduced DNA methyltransferases (DNMT1 and DNMT3A) levels. Inhibition of caspase 3 activity, before ethanol treatment, rescued DNMT1, DNMT3A proteins as well as DNA methylation levels. Blockade of histone methyltransferase (G9a) activity or cannabinoid receptor type-1 (CB1R), prior to ethanol treatment, which, respectively, inhibits or prevents activation of caspase 3, rescued the DNMT1 and DNMT3A proteins and DNA methylation. No reduction of DNMT1 and DNMT3A proteins and DNA methylation was found in P7 CB1R null mice, which exhibit no ethanol-induced activation of caspase 3. Together, these data demonstrate that ethanol-induced activation of caspase 3 impairs DNA methylation through DNMT1 and DNMT3A in the neonatal mouse brain, and such impairments are absent in CB1R null mice. Epigenetic events mediated by DNA methylation may be one of the essential mechanisms of ethanol teratogenesis. Schematic mechanism of action by which ethanol impairs DNA methylation. Studies have demonstrated that ethanol has the capacity to bring epigenetic changes to contribute to the development of fetal alcohol spectrum disorder (FASD). However, the mechanisms are not well studied. P7 ethanol induces the activation of caspase 3 and impairs DNA methylation through reduced DNA methyltransferases (DNMT1 and DNMT3A) proteins (→). The inhibition or genetic ablation of cannabinoid receptor type-1 or inhibition of histone methyltransferase (G9a) by Bix (-----) or inhibition of caspase 3 activation by Q- quinoline-Val-Asp(Ome)-CH2-O-phenoxy (Q-VD-OPh) () rescue loss of DNMT1, DNMT3A as well as DNA methylation. Hence, the putative DNMT1/DNMT3A/DNA methylation mechanism may have a potential regulatory role in FASD. © 2014 International Society for Neurochemistry.

Optical Materials with a Genome: Nanophotonics with DNA-Stabilized Silver Clusters

NASA Astrophysics Data System (ADS)

Copp, Stacy M.

Fluorescent silver clusters with unique rod-like geometries are stabilized by DNA. The sizes and colors of these clusters, or AgN-DNA, are selected by DNA base sequence, which can tune peak emission from blue-green into the near-infrared. Combined with DNA nanostructures, AgN-DNA promise exciting applications in nanophotonics and sensing. Until recently, however, a lack of understanding of the mechanisms controlling AgN-DNA fluorescence has challenged such applications. This dissertation discusses progress toward understanding the role of DNA as a "genome" for silver clusters and toward using DNA to achieve atomic-scale precision of silver cluster size and nanometer-scale precision of silver cluster position on a DNA breadboard. We also investigate sensitivity of AgN-DNA to local solvent environment, with an eye toward applications in chemical and biochemical sensing. Using robotic techniques to generate large data sets, we show that fluorescent silver clusters are templated by certain DNA base motifs that select "magic-sized" cluster cores of enhanced stabilities. The linear arrangement of bases on the phosphate backbone imposes a unique rod-like geometry on the clusters. Harnessing machine learning and bioinformatics techniques, we also demonstrate that sequences of DNA templates can be selected to stabilize silver clusters with desired optical properties, including high fluorescence intensity and specific fluorescence wavelengths, with much higher rates of success as compared to current strategies. The discovered base motifs can be also used to design modular DNA host strands that enable individual silver clusters with atomically precise sizes to bind at specific programmed locations on a DNA nanostructure. We show that DNA-mediated nanoscale arrangement enables near-field coupling of distinct clusters, demonstrated by dual-color cluster assemblies exhibiting resonant energy transfer. These results demonstrate a new degree of control over the optical properties and relative positions of nanoparticles, selected almost solely by the sequence of DNA. AgN-DNA are promising chemical and biochemical sensors due to the sensitivity of their fluorescence to local environment. However, the mechanisms behind many sensing schemes are not understood, and the nature of the excited state of the silver cluster itself remains unknown. To probe the fluorescence mechanisms of AgN-DNA, we investigate the behavior of purified solutions of these clusters in various solvents. We find that standard models for fluorophore solvatochromism, including the Lippert-Mataga model, do not describe AgN-DNA fluorescence because such models neglect specific interactions between the cluster and surrounding solvent molecules. Fluorescence colors are well-modeled by Mie-Gans theory, suggesting that the local dielectric environment of the cluster does play a role in fluorescence, although additional specific solvent interactions and cluster shape changes may also determine fluorescence color and intensity. These results suggest that AgN-DNA may be sensitive to changes in local dielectric environment on nanometer length scales and may also act as sensors for small molecules with affinity for DNA.

Identification of species based on DNA barcode using k-mer feature vector and Random forest classifier.

PubMed

Meher, Prabina Kumar; Sahu, Tanmaya Kumar; Rao, A R

2016-11-05

DNA barcoding is a molecular diagnostic method that allows automated and accurate identification of species based on a short and standardized fragment of DNA. To this end, an attempt has been made in this study to develop a computational approach for identifying the species by comparing its barcode with the barcode sequence of known species present in the reference library. Each barcode sequence was first mapped onto a numeric feature vector based on k-mer frequencies and then Random forest methodology was employed on the transformed dataset for species identification. The proposed approach outperformed similarity-based, tree-based, diagnostic-based approaches and found comparable with existing supervised learning based approaches in terms of species identification success rate, while compared using real and simulated datasets. Based on the proposed approach, an online web interface SPIDBAR has also been developed and made freely available at http://cabgrid.res.in:8080/spidbar/ for species identification by the taxonomists. Copyright © 2016 Elsevier B.V. All rights reserved.

A new method for enhancer prediction based on deep belief network.

PubMed

Bu, Hongda; Gan, Yanglan; Wang, Yang; Zhou, Shuigeng; Guan, Jihong

2017-10-16

Studies have shown that enhancers are significant regulatory elements to play crucial roles in gene expression regulation. Since enhancers are unrelated to the orientation and distance to their target genes, it is a challenging mission for scholars and researchers to accurately predicting distal enhancers. In the past years, with the high-throughout ChiP-seq technologies development, several computational techniques emerge to predict enhancers using epigenetic or genomic features. Nevertheless, the inconsistency of computational models across different cell-lines and the unsatisfactory prediction performance call for further research in this area. Here, we propose a new Deep Belief Network (DBN) based computational method for enhancer prediction, which is called EnhancerDBN. This method combines diverse features, composed of DNA sequence compositional features, DNA methylation and histone modifications. Our computational results indicate that 1) EnhancerDBN outperforms 13 existing methods in prediction, and 2) GC content and DNA methylation can serve as relevant features for enhancer prediction. Deep learning is effective in boosting the performance of enhancer prediction.

Effective Design of Multifunctional Peptides by Combining Compatible Functions

PubMed Central

Diener, Christian; Garza Ramos Martínez, Georgina; Moreno Blas, Daniel; Castillo González, David A.; Corzo, Gerardo; Castro-Obregon, Susana; Del Rio, Gabriel

2016-01-01

Multifunctionality is a common trait of many natural proteins and peptides, yet the rules to generate such multifunctionality remain unclear. We propose that the rules defining some protein/peptide functions are compatible. To explore this hypothesis, we trained a computational method to predict cell-penetrating peptides at the sequence level and learned that antimicrobial peptides and DNA-binding proteins are compatible with the rules of our predictor. Based on this finding, we expected that designing peptides for CPP activity may render AMP and DNA-binding activities. To test this prediction, we designed peptides that embedded two independent functional domains (nuclear localization and yeast pheromone activity), linked by optimizing their composition to fit the rules characterizing cell-penetrating peptides. These peptides presented effective cell penetration, DNA-binding, pheromone and antimicrobial activities, thus confirming the effectiveness of our computational approach to design multifunctional peptides with potential therapeutic uses. Our computational implementation is available at http://bis.ifc.unam.mx/en/software/dcf. PMID:27096600

Response to immunotherapy in a patient with adult onset Leigh syndrome and T9176C mtDNA mutation.

PubMed

Chuquilin, Miguel; Govindarajan, Raghav; Peck, Dawn; Font-Montgomery, Esperanza

2016-09-01

Leigh syndrome is a mitochondrial disease caused by mutations in different genes, including ATP6A for which no known therapy is available. We report a case of adult-onset Leigh syndrome with response to immunotherapy. A twenty year-old woman with baseline learning difficulties was admitted with progressive behavioral changes, diplopia, headaches, bladder incontinence, and incoordination. Brain MRI and PET scan showed T2 hyperintensity and increased uptake in bilateral basal ganglia, respectively. Autoimmune encephalitis was suspected and she received plasmapheresis with clinical improvement. She was readmitted 4 weeks later with dysphagia and aspiration pneumonia. Plasmapheresis was repeated with resolution of her symptoms. Given the multisystem involvement and suggestive MRI changes, genetic testing was done, revealing a homoplasmic T9176C ATPase 6 gene mtDNA mutation. Monthly IVIG provided clinical improvement with worsening when infusions were delayed. Leigh syndrome secondary to mtDNA T9176C mutations could have an autoimmune mechanism that responds to immunotherapy.

Cultural traditions across a migratory network shape the genetic structure of southern right whales around Australia and New Zealand.

PubMed

Carroll, E L; Baker, C S; Watson, M; Alderman, R; Bannister, J; Gaggiotti, O E; Gröcke, D R; Patenaude, N; Harcourt, R

2015-11-09

Fidelity to migratory destinations is an important driver of connectivity in marine and avian species. Here we assess the role of maternally directed learning of migratory habitats, or migratory culture, on the population structure of the endangered Australian and New Zealand southern right whale. Using DNA profiles, comprising mitochondrial DNA (mtDNA) haplotypes (500 bp), microsatellite genotypes (17 loci) and sex from 128 individually-identified whales, we find significant differentiation among winter calving grounds based on both mtDNA haplotype (FST = 0.048, ΦST = 0.109, p < 0.01) and microsatellite allele frequencies (FST = 0.008, p < 0.01), consistent with long-term fidelity to calving areas. However, most genetic comparisons of calving grounds and migratory corridors were not significant, supporting the idea that whales from different calving grounds mix in migratory corridors. Furthermore, we find a significant relationship between δ(13)C stable isotope profiles of 66 Australian southern right whales, a proxy for feeding ground location, and both mtDNA haplotypes and kinship inferred from microsatellite-based estimators of relatedness. This indicates migratory culture may influence genetic structure on feeding grounds. This fidelity to migratory destinations is likely to influence population recovery, as long-term estimates of historical abundance derived from estimates of genetic diversity indicate the South Pacific calving grounds remain at <10% of pre-whaling abundance.

Why American Business Demands Twenty-First Century Skills: An Industry Perspective

ERIC Educational Resources Information Center

Bruett, Karen

2006-01-01

A solid global strategy must be part of every organization's DNA. For Dell, this means expanding into new countries where it can use its direct model to provide value to customers and create more productive, healthier communities. It also means hiring employees who think and act globally and have a commitment to learn how to work with cultures…

Learning about Heredity and Embryology. Superific Science Book II. A Good Apple Science Activity Book for Grades 5-8+.

ERIC Educational Resources Information Center

Conway, Lorraine

Designed to provide teachers with low cost laboratory exercises, project ideas, and classroom activities for individuals and groups, this document focuses on the concepts of heredity and embryology. The materials address the topics of: (1) cell division; (2) the identification of the human embryo; (3) chromosomes; (4) DNA; (5) differences in the…

PCR-RFLP to Detect Codon 248 Mutation in Exon 7 of "p53" Tumor Suppressor Gene

ERIC Educational Resources Information Center

Ouyang, Liming; Ge, Chongtao; Wu, Haizhen; Li, Suxia; Zhang, Huizhan

2009-01-01

Individual genome DNA was extracted fast from oral swab and followed up with PCR specific for codon 248 of "p53" tumor suppressor gene. "Msp"I restriction mapping showed the G-C mutation in codon 248, which closely relates to cancer susceptibility. Students learn the concepts, detection techniques, and research significance of point mutations or…

Assessing Understanding of Complex Learning Outcomes and Real-World Skills Using an Authentic Software Tool: A Study from Biomedical Sciences

ERIC Educational Resources Information Center

Dermo, John; Boyne, James

2014-01-01

We describe a study conducted during 2009-12 into innovative assessment practice, evaluating an assessed coursework task on a final year Medical Genetics module for Biomedical Science undergraduates. An authentic e-assessment coursework task was developed, integrating objectively marked online questions with an online DNA sequence analysis tool…

Conformation-dependent restraints for polynucleotides: I. Clustering of the geometry of the phosphodiester group

PubMed Central

Kowiel, Marcin; Brzezinski, Dariusz; Jaskolski, Mariusz

2016-01-01

The refinement of macromolecular structures is usually aided by prior stereochemical knowledge in the form of geometrical restraints. Such restraints are also used for the flexible sugar-phosphate backbones of nucleic acids. However, recent highly accurate structural studies of DNA suggest that the phosphate bond angles may have inadequate description in the existing stereochemical dictionaries. In this paper, we analyze the bonding deformations of the phosphodiester groups in the Cambridge Structural Database, cluster the studied fragments into six conformation-related categories and propose a revised set of restraints for the O-P-O bond angles and distances. The proposed restraints have been positively validated against data from the Nucleic Acid Database and an ultrahigh-resolution Z-DNA structure in the Protein Data Bank. Additionally, the manual classification of PO4 geometry is compared with geometrical clusters automatically discovered by machine learning methods. The machine learning cluster analysis provides useful insights and a practical example for general applications of clustering algorithms for automatic discovery of hidden patterns of molecular geometry. Finally, we describe the implementation and application of a public-domain web server for automatic generation of the proposed restraints. PMID:27521371

Fuzzy support vector machine for microarray imbalanced data classification

NASA Astrophysics Data System (ADS)

Ladayya, Faroh; Purnami, Santi Wulan; Irhamah

2017-11-01

DNA microarrays are data containing gene expression with small sample sizes and high number of features. Furthermore, imbalanced classes is a common problem in microarray data. This occurs when a dataset is dominated by a class which have significantly more instances than the other minority classes. Therefore, it is needed a classification method that solve the problem of high dimensional and imbalanced data. Support Vector Machine (SVM) is one of the classification methods that is capable of handling large or small samples, nonlinear, high dimensional, over learning and local minimum issues. SVM has been widely applied to DNA microarray data classification and it has been shown that SVM provides the best performance among other machine learning methods. However, imbalanced data will be a problem because SVM treats all samples in the same importance thus the results is bias for minority class. To overcome the imbalanced data, Fuzzy SVM (FSVM) is proposed. This method apply a fuzzy membership to each input point and reformulate the SVM such that different input points provide different contributions to the classifier. The minority classes have large fuzzy membership so FSVM can pay more attention to the samples with larger fuzzy membership. Given DNA microarray data is a high dimensional data with a very large number of features, it is necessary to do feature selection first using Fast Correlation based Filter (FCBF). In this study will be analyzed by SVM, FSVM and both methods by applying FCBF and get the classification performance of them. Based on the overall results, FSVM on selected features has the best classification performance compared to SVM.

Paternal and maternal alcohol consumption: effects on offspring in two strains of rats.

PubMed

Abel, E L

1989-08-01

Long-Evans and Sprague-Dawley male rats were given liquid alcohol diets containing 35%, 17.5%, or 0% ethanol-derived calories (EDC). The latter two groups were pair fed to the higher alcohol diet group. A fourth group received lab chow and water ad libitum to assess the role of paternal undernutrition associated with alcohol consumption. After three or four weeks of diet consumption, these males were bred to females of the same strain. Pregnant females were divided into similarly treated alcohol groups and were fed these diets beginning on gestation Day 8, thus creating a factorial study with strain, paternal, and maternal alcohol consumption as main factors. Paternal alcohol consumption was associated with decreased litter size, decreased testosterone levels, and a strain-related effect on offspring activity. Offspring activity decreased for those sired by 35% and 17.5% EDC Long-Evans fathers. Activity also decreased for offspring sired by 17.5% EDC Sprague-Dawley fathers but increased for those sired by 35% EDC fathers. Paternal alcohol consumption did not affect postnatal mortality or passive avoidance learning of offspring. Maternal alcohol consumption was associated with lower birth weights, lower offspring weights at weaning, increased postnatal mortality, and poorer passive avoidance learning. However, offspring activity was not affected. In a separate study, levels of alcohol in the testes were found to be somewhat, but not significantly, lower than blood alcohol levels. DNA taken from sperm of Long-Evans males consuming alcohol, migrated farther under pulsed field electrophoresis than DNA from control fathers, suggestive of an alcohol-related effect on sperm DNA.

Health Detectives: Uncovering the Mysteries of Disease (LBNL Science at the Theater)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bissell, Mina; Canaria, Christie; Celnicker, Susan

In this April 23, 2012 Science at the Theater event, Berkeley Lab scientists discuss how they uncover the mysteries of disease in unlikely places. Speakers and topics include: World-renowned cancer researcher Mina Bissell's pioneering research on the role of the cellular microenvironment in breast cancer has changed the conversation about the disease. How does DNA instability cause disease? To find out, Christie Canaria images neural networks to study disorders such as Huntington's disease. Fruit flies can tell us a lot about ourselves. Susan Celniker explores the fruit fly genome to learn how our genome works. DNA is not destiny. Garymore » Karpen explores how environmental factors shape genome function and disease through epigenetics.« less

Mitochondrial transcription in mammalian cells

PubMed Central

Shokolenko, Inna N.; Alexeyev, Mikhail F.

2017-01-01

As a consequence of recent discoveries of intimate involvement of mitochondria with key cellular processes, there has been a resurgence of interest in all aspects of mitochondrial biology, including the intricate mechanisms of mitochondrial DNA maintenance and expression. Despite four decades of research, there remains a lot to be learned about the processes that enable transcription of genetic information from mitochondrial DNA to RNA, as well as their regulation. These processes are vitally important, as evidenced by the lethality of inactivating the central components of mitochondrial transcription machinery. Here, we review the current understanding of mitochondrial transcription and its regulation in mammalian cells. We also discuss key theories in the field and highlight controversial subjects and future directions as we see them. PMID:27814650

Ground-Water Occurrence and Movement, 2006, and Water-Level Changes in the Detrital, Hualapai, and Sacramento Valley Basins, Mohave County, Arizona

USGS Publications Warehouse

Anning, David W.; Truini, Margot; Flynn, Marilyn E.; Remick, William H.

2007-01-01

Ground-water levels for water year 2006 and their change over time in Detrital, Hualapai, and Sacramento Valley Basins of northwestern Arizona were investigated to improve the understanding of current and past ground-water conditions in these basins. The potentiometric surface for ground water in the Basin-Fill aquifer of each basin is generally parallel to topography. Consequently, ground-water movement is generally from the mountain front toward the basin center and then along the basin axis toward the Colorado River or Lake Mead. Observed water levels in Detrital, Hualapai, and Sacramento Valley Basins have fluctuated during the period of historic water-level records (1943 through 2006). In Detrital Valley Basin, water levels in monitored areas have either remained the same, or have steadily increased as much as 3.5 feet since the 1980s. Similar steady conditions or water-level rises were observed for much of the northern and central parts of Hualapai Valley Basin. During the period of historic record, steady water-level declines as large as 60 feet were found in wells penetrating the Basin-Fill aquifer in areas near Kingman, northwest of Hackberry, and northeast of Dolan Springs within the Hualapai Valley Basin. Within the Sacramento Valley Basin, during the period of historic record, water-level declines as large as 55 feet were observed in wells penetrating the Basin-Fill aquifer in the Kingman and Golden Valley areas; whereas small, steady rises were observed in Yucca and in the Dutch Flat area.

Dietary Intake Following Experimentally Restricted Sleep in Adolescents

PubMed Central

Beebe, Dean W.; Simon, Stacey; Summer, Suzanne; Hemmer, Stephanie; Strotman, Daniel; Dolan, Lawrence M.

2013-01-01

Study Objective: To examine the relationship between sleep and dietary intake in adolescents using an experimental sleep restriction protocol. Design: Randomized crossover sleep restriction-extension paradigm. Setting: Sleep obtained and monitored at home, diet measured during an office visit. Participants: Forty-one typically developing adolescents age 14-16 years. Interventions: The 3-week protocol consisting of a baseline week designed to stabilize the circadian rhythm, followed randomly by 5 consecutive nights of sleep restriction (6.5 hours in bed Monday-Friday) versus healthy sleep duration (10 hours in bed), a 2-night washout period, and a 5-night crossover period. Measurements: Sleep was monitored via actigraphy and teens completed validated 24-hour diet recall interviews following each experimental condition. Results: Paired-sample t-tests examined differences between conditions for consumption of key macronutrients and choices from dietary categories. Compared with the healthy sleep condition, sleep-restricted adolescents' diets were characterized by higher glycemic index and glycemic load and a trend toward more calories and carbohydrates, with no differences in fat or protein consumption. Exploratory analyses revealed the consumption of significantly more desserts and sweets during sleep restriction than healthy sleep. Conclusions: Chronic sleep restriction during adolescence appears to cause increased consumption of foods with a high glycemic index, particularly desserts/sweets. The chronic sleep restriction common in adolescence may cause changes in dietary behaviors that increase risk of obesity and associated morbidity. Citation: Beebe DW; Simon S; Summer S; Hemmer S; Strotman D; Dolan LM. Dietary intake following experimentally restricted sleep in adolescents. SLEEP 2013;36(6):827-834. PMID:23729925

Floristic response to urbanization: Filtering of the bioregional flora in Indianapolis, Indiana, USA.

PubMed

Dolan, Rebecca W; Aronson, Myla F J; Hipp, Andrew L

2017-08-09

Globally, urban plant populations are becoming increasingly important, as these plants play a vital role in ameliorating effects of ecosystem disturbance and climate change. Urban environments act as filters to bioregional flora, presenting survival challenges to spontaneous plants. Yet, because of the paucity of inventory data on plants in landscapes both before and after urbanization, few studies have directly investigated this effect of urbanization. We used historical, contemporary, and regional plant species inventories for Indianapolis, Indiana USA to evaluate how urbanization filters the bioregional flora based on species diversity, functional traits, and phylogenetic community structure. Approximately 60% of the current regional flora was represented in the Indianapolis flora, both historically and presently. Native species that survived over time were significantly different in growth form, life form, and dispersal and pollination modes than those that were extirpated. Phylogenetically, the historical flora represented a random sample of the regional flora, while the current urban flora represented a nonrandom sample. Both graminoid habit and abiotic pollination are significantly more phylogenetically conserved than expected. Our results likely reflect the shift from agricultural cover to built environment, coupled with the influence of human preference, in shaping the current urban flora of Indianapolis. Based on our analyses, the urban environment of Indianapolis does filter the bioregional species pool. To the extent that these filters are shared by other cities and operate similarly, we may see increasingly homogenized urban floras across regions, with concurrent loss of evolutionary information. © 2017 Dolan et al. Published by the Botanical Society of America. This work is licensed under a Creative Commons Attribution License (CC-BY-NC).

Machine learning classifier for identification of damaging missense mutations exclusive to human mitochondrial DNA-encoded polypeptides.

PubMed

Martín-Navarro, Antonio; Gaudioso-Simón, Andrés; Álvarez-Jarreta, Jorge; Montoya, Julio; Mayordomo, Elvira; Ruiz-Pesini, Eduardo

2017-03-07

Several methods have been developed to predict the pathogenicity of missense mutations but none has been specifically designed for classification of variants in mtDNA-encoded polypeptides. Moreover, there is not available curated dataset of neutral and damaging mtDNA missense variants to test the accuracy of predictors. Because mtDNA sequencing of patients suffering mitochondrial diseases is revealing many missense mutations, it is needed to prioritize candidate substitutions for further confirmation. Predictors can be useful as screening tools but their performance must be improved. We have developed a SVM classifier (Mitoclass.1) specific for mtDNA missense variants. Training and validation of the model was executed with 2,835 mtDNA damaging and neutral amino acid substitutions, previously curated by a set of rigorous pathogenicity criteria with high specificity. Each instance is described by a set of three attributes based on evolutionary conservation in Eukaryota of wildtype and mutant amino acids as well as coevolution and a novel evolutionary analysis of specific substitutions belonging to the same domain of mitochondrial polypeptides. Our classifier has performed better than other web-available tested predictors. We checked performance of three broadly used predictors with the total mutations of our curated dataset. PolyPhen-2 showed the best results for a screening proposal with a good sensitivity. Nevertheless, the number of false positive predictions was too high. Our method has an improved sensitivity and better specificity in relation to PolyPhen-2. We also publish predictions for the complete set of 24,201 possible missense variants in the 13 human mtDNA-encoded polypeptides. Mitoclass.1 allows a better selection of candidate damaging missense variants from mtDNA. A careful search of discriminatory attributes and a training step based on a curated dataset of amino acid substitutions belonging exclusively to human mtDNA genes allows an improved performance. Mitoclass.1 accuracy could be improved in the future when more mtDNA missense substitutions will be available for updating the attributes and retraining the model.

Genomic DNA Methylation Signatures Enable Concurrent Diagnosis and Clinical Genetic Variant Classification in Neurodevelopmental Syndromes.

PubMed

Aref-Eshghi, Erfan; Rodenhiser, David I; Schenkel, Laila C; Lin, Hanxin; Skinner, Cindy; Ainsworth, Peter; Paré, Guillaume; Hood, Rebecca L; Bulman, Dennis E; Kernohan, Kristin D; Boycott, Kym M; Campeau, Philippe M; Schwartz, Charles; Sadikovic, Bekim

2018-01-04

Pediatric developmental syndromes present with systemic, complex, and often overlapping clinical features that are not infrequently a consequence of Mendelian inheritance of mutations in genes involved in DNA methylation, establishment of histone modifications, and chromatin remodeling (the "epigenetic machinery"). The mechanistic cross-talk between histone modification and DNA methylation suggests that these syndromes might be expected to display specific DNA methylation signatures that are a reflection of those primary errors associated with chromatin dysregulation. Given the interrelated functions of these chromatin regulatory proteins, we sought to identify DNA methylation epi-signatures that could provide syndrome-specific biomarkers to complement standard clinical diagnostics. In the present study, we examined peripheral blood samples from a large cohort of individuals encompassing 14 Mendelian disorders displaying mutations in the genes encoding proteins of the epigenetic machinery. We demonstrated that specific but partially overlapping DNA methylation signatures are associated with many of these conditions. The degree of overlap among these epi-signatures is minimal, further suggesting that, consistent with the initial event, the downstream changes are unique to every syndrome. In addition, by combining these epi-signatures, we have demonstrated that a machine learning tool can be built to concurrently screen for multiple syndromes with high sensitivity and specificity, and we highlight the utility of this tool in solving ambiguous case subjects presenting with variants of unknown significance, along with its ability to generate accurate predictions for subjects presenting with the overlapping clinical and molecular features associated with the disruption of the epigenetic machinery. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Microbes, metagenomes and marine mammals: enabling the next generation of scientist to enter the genomic era

PubMed Central

2013-01-01

Background The revolution in DNA sequencing technology continues unabated, and is affecting all aspects of the biological and medical sciences. The training and recruitment of the next generation of researchers who are able to use and exploit the new technology is severely lacking and potentially negatively influencing research and development efforts to advance genome biology. Here we present a cross-disciplinary course that provides undergraduate students with practical experience in running a next generation sequencing instrument through to the analysis and annotation of the generated DNA sequences. Results Many labs across world are installing next generation sequencing technology and we show that the undergraduate students produce quality sequence data and were excited to participate in cutting edge research. The students conducted the work flow from DNA extraction, library preparation, running the sequencing instrument, to the extraction and analysis of the data. They sequenced microbes, metagenomes, and a marine mammal, the Californian sea lion, Zalophus californianus. The students met sequencing quality controls, had no detectable contamination in the targeted DNA sequences, provided publication quality data, and became part of an international collaboration to investigate carcinomas in carnivores. Conclusions Students learned important skills for their future education and career opportunities, and a perceived increase in students’ ability to conduct independent scientific research was measured. DNA sequencing is rapidly expanding in the life sciences. Teaching undergraduates to use the latest technology to sequence genomic DNA ensures they are ready to meet the challenges of the genomic era and allows them to participate in annotating the tree of life. PMID:24007365

Nanoarchitectonics with Porphyrin Functionalized DNA

PubMed Central

2017-01-01

Conspectus DNA is well-known as bearer of the genetic code. Since its structure elucidation nearly seven decades ago by Watson, Crick, Wilkins, and Franklin, much has been learned about its detailed structure, function, and genetic coding. The development of automated solid-phase synthesis, and with it the availability of synthetic DNA with any desired sequence in lengths of up to hundreds of bases in the best case, has contributed much to the advancement of the field of DNA research. In addition, classic organic synthesis has allowed introduction of a very large number of modifications in the DNA in a sequence specific manner, which have initially been targeted at altering the biological function of DNA. However, in recent years DNA has become a very attractive scaffold in supramolecular chemistry, where DNA is taken out of its biological role and serves as both stick and glue molecule to assemble novel functional structures with nanometer precision. The attachment of functionalities to DNA has led to the creation of supramolecular systems with applications in light harvesting, energy and electron transfer, sensing, and catalysis. Functional DNA is clearly having a significant impact in the field of bioinspired nanosystems. Of particular interest is the use of porphyrins in supramolecular chemistry and bionanotechnology, because they are excellent functional groups due to their electronic properties that can be tailored through chemical modifications of the aromatic core or through insertion of almost any metal of the periodic table into the central cavity. The porphyrins can be attached either to the nucleobase, to the phosphate group, or to the ribose moiety. Additionally, noncovalent templating through Watson–Crick base pairing forms an alternative and attractive approach. With this, the combination of two seemingly simple molecules gives rise to a highly complex system with unprecedented possibilities for modulation of function, and with it applications, particularly when combined with other functional groups. Here, an overview is given on the developments of using porphyrin modified DNA for the construction of functional assemblies. Strategies for the synthesis and characterization are presented alongside selected applications where the porphyrin modification has proven to be particularly useful and superior to other modifiers but also has revealed its limitations. We also discuss implications on properties and behavior of the porphyrin–DNA, where similar issues could arise when using other hydrophobic and bulky substituents on DNA. This includes particularly problems regarding synthesis of the building blocks, DNA synthesis, yields, solubility, and intermolecular interactions. PMID:28272871

Pathogenesis of Germline and Somatic NF1 Rearrangements

DTIC Science & Technology

1999-10-01

de novo DNA deletion in a patient with sporadic neurofibromatosis 1, mental retardation, and dysmorphism . J Med Genet 29:686-90. Leppig, K., Kaplan...a patient with sporadic neurofibromatosis 1, mental retardation, and dysmorphism . J. Med. Genet., 29, 686-690. 13. Kayes, L.M., Burke, W., Riccardi...gene are predominantly of maternal origin and commonly associated with a learning disability, dysmorphic features and developmental delay. Hum. Genet

Genomics Analogy Model for Educators (GAME): Fuzzy DNA Model to Enable the Learning of Gene Sequencing by Visually-Impaired and Blind Students

ERIC Educational Resources Information Center

Butler, Charles; Bello, Julia; York, Alan; Orvis, Kathryn; Pittendrigh, Barry R.

2008-01-01

Much of the general population is aware of terms such as biotechnology, genetic engineering, and genomics. However, there is a lack of understanding concerning these fields among many secondary school students. Few teaching models exist to explain concepts behind genomics and even less are available for teaching the visually impaired and blind.…

Learning from the unexpected in life and DNA self-assembly

PubMed Central

2015-01-01

Summary The greatest lessons in life and science often arise from the unexpected. Thus, rather than viewing these experiences as hindering our progress, they should be embraced and appreciated for their ability to lead to new discoveries. In this perspective, I will discuss the unexpected events that have shaped my career path and the early stages of my independent research program. PMID:26877793

Promoting 21st-Century Skills in the Science Classroom by Adapting Cookbook Lab Activities: The Case of DNA Extraction of Wheat Germ

ERIC Educational Resources Information Center

Alozie, Nonye M.; Grueber, David J.; Dereski, Mary O.

2012-01-01

How can science instruction engage students in 21st-century skills and inquiry-based learning, even when doing simple labs in the classroom? We collaborated with teachers in professional development workshops to transform "cookbook" activities into engaging laboratory experiences. We show how to change the common classroom activity of DNA…

Using Analogy Role-Play Activity in an Undergraduate Biology Classroom to Show Central Dogma Revision

ERIC Educational Resources Information Center

Takemura, Masaharu; Kurabayashi, Mario

2014-01-01

For the study of biology in an undergraduate classroom, a classroom exercise was developed: an analogy role-play to learn mechanisms of gene transcription and protein translation (central dogma). To develop the central dogma role-play exercise, we made DNA and mRNA using paper sheets, tRNA using a wire dress hanger, and amino acids using Lego®…

Cognitive neuroepigenetics: the next evolution in our understanding of the molecular mechanisms underlying learning and memory?

NASA Astrophysics Data System (ADS)

Marshall, Paul; Bredy, Timothy W.

2016-07-01

A complete understanding of the fundamental mechanisms of learning and memory continues to elude neuroscientists. Although many important discoveries have been made, the question of how memories are encoded and maintained at the molecular level remains. So far, this issue has been framed within the context of one of the most dominant concepts in molecular biology, the central dogma, and the result has been a protein-centric view of memory. Here, we discuss the evidence supporting a role for neuroepigenetic mechanisms, which constitute dynamic and reversible, state-dependent modifications at all levels of control over cellular function, and their role in learning and memory. This neuroepigenetic view suggests that DNA, RNA and protein each influence one another to produce a holistic cellular state that contributes to the formation and maintenance of memory, and predicts a parallel and distributed system for the consolidation, storage and retrieval of the engram.

Histone Deacetylase (HDAC) Inhibitors - Emerging Roles in Neuronal Memory, Learning, Synaptic Plasticity and Neural Regeneration

PubMed Central

Ahmad Ganai, Shabir; Ramadoss, Mahalakshmi; Mahadevan, Vijayalakshmi

2016-01-01

Epigenetic regulation of neuronal signalling through histone acetylation dictates transcription programs that govern neuronal memory, plasticity and learning paradigms. Histone Acetyl Transferases (HATs) and Histone Deacetylases (HDACs) are antagonistic enzymes that regulate gene expression through acetylation and deacetylation of histone proteins around which DNA is wrapped inside a eukaryotic cell nucleus. The epigenetic control of HDACs and the cellular imbalance between HATs and HDACs dictate disease states and have been implicated in muscular dystrophy, loss of memory, neurodegeneration and autistic disorders. Altering gene expression profiles through inhibition of HDACs is now emerging as a powerful technique in therapy. This review presents evolving applications of HDAC inhibitors as potential drugs in neurological research and therapy. Mechanisms that govern their expression profiles in neuronal signalling, plasticity and learning will be covered. Promising and exciting possibilities of HDAC inhibitors in memory formation, fear conditioning, ischemic stroke and neural regeneration have been detailed. PMID:26487502

Genome-wide chromatin and gene expression profiling during memory formation and maintenance in adult mice.

PubMed

Centeno, Tonatiuh Pena; Shomroni, Orr; Hennion, Magali; Halder, Rashi; Vidal, Ramon; Rahman, Raza-Ur; Bonn, Stefan

2016-10-11

Recent evidence suggests that the formation and maintenance of memory requires epigenetic changes. In an effort to understand the spatio-temporal extent of learning and memory-related epigenetic changes we have charted genome-wide histone and DNA methylation profiles, in two different brain regions, two cell types, and three time-points, before and after learning. In this data descriptor we provide detailed information on data generation, give insights into the rationale of experiments, highlight necessary steps to assess data quality, offer guidelines for future use of the data and supply ready-to-use code to replicate the analysis results. The data provides a blueprint of the gene regulatory network underlying short- and long-term memory formation and maintenance. This 'healthy' gene regulatory network of learning can now be compared to changes in neurological or psychiatric diseases, providing mechanistic insights into brain disorders and highlighting potential therapeutic avenues.

Histone Deacetylase (HDAC) Inhibitors - emerging roles in neuronal memory, learning, synaptic plasticity and neural regeneration.

PubMed

Ganai, Shabir Ahmad; Ramadoss, Mahalakshmi; Mahadevan, Vijayalakshmi

2016-01-01

Epigenetic regulation of neuronal signalling through histone acetylation dictates transcription programs that govern neuronal memory, plasticity and learning paradigms. Histone Acetyl Transferases (HATs) and Histone Deacetylases (HDACs) are antagonistic enzymes that regulate gene expression through acetylation and deacetylation of histone proteins around which DNA is wrapped inside a eukaryotic cell nucleus. The epigenetic control of HDACs and the cellular imbalance between HATs and HDACs dictate disease states and have been implicated in muscular dystrophy, loss of memory, neurodegeneration and autistic disorders. Altering gene expression profiles through inhibition of HDACs is now emerging as a powerful technique in therapy. This review presents evolving applications of HDAC inhibitors as potential drugs in neurological research and therapy. Mechanisms that govern their expression profiles in neuronal signalling, plasticity and learning will be covered. Promising and exciting possibilities of HDAC inhibitors in memory formation, fear conditioning, ischemic stroke and neural regeneration have been detailed.

Cognitive neuroepigenetics: the next evolution in our understanding of the molecular mechanisms underlying learning and memory?

PubMed Central

Marshall, Paul; Bredy, Timothy W.

2016-01-01

A complete understanding of the fundamental mechanisms of learning and memory continues to elude neuroscientists. Although many important discoveries have been made, the question of how memories are encoded and maintained at the molecular level remains. To date, this issue has been framed within the context of one of the most dominant concepts in molecular biology, the central dogma, and the result has been a protein-centric view of memory. Here we discuss the evidence supporting a role for neuroepigenetic mechanisms, which constitute dynamic and reversible, state-dependent modifications at all levels of control over cellular function, and their role in learning and memory. This neuroepigenetic view suggests that DNA, RNA and protein each influence one another to produce a holistic cellular state that contributes to the formation and maintenance of memory, and predicts a parallel and distributed system for the consolidation, storage and retrieval of the engram. PMID:27512601

Hydroacoustic signatures of Colorado Riverbed sediments in Marble and Grand Canyons using multibeam sonar

USGS Publications Warehouse

Buscombe, Daniel D.; Grams, Paul E.; Kaplinski, Matthew; Tusso, Robert B.; Rubin, David M.

2015-01-01

Characterizing the large-scale sedimentary make-up of heterogeneous riverbeds (Nelson et al., 2014), which consist of a patchwork of sediment types over small scales (less than one to several tens of meters) (Dietrich and Smith, 1984) requires high resolution measurements of sediment grain size. Capturing such variability with conventional physical (e.g. grabs, cores, and dredges) or underwater photographic sampling (Rubin et al., 2007; Buscombe et al., 2014a) would be prohibitively costly and time-consuming. However, characterizing bed sediments using high-frequency (several hundred kilohertz) acoustic backscatter from swath-mapping systems has the potential to provide near complete coverage of the bed (Brown and Blondel, 2009; Brown et al., 2011; Snellen et al., 2013), at resolutions down to a few centimeters, which photographic sampling could not practically achieve within the same time and with the same positional accuracy. In shallow water, the physics of high frequency scattering of sound are relatively poorly understood, therefore acoustic sediment classification are almost always statistical (Snellen et al., 2013). Many such methods proposed to date are designed for characterizing large areas of seabed (Brown and Blondel, 2009; Brown et al., 2011) at relatively poor resolution (tens of meters to several hundred meters) and therefore rely on aggregation of data over scales much larger than the typical scales of sediment patchiness on heterogeneous riverbeds. In response to this need, Buscombe et al. (2014b, 2014c) developed a new statistical method for acoustic sediment classification based on spectral analysis of backscatter. This method is both continuous in coverage and of sufficient resolution (order meter or less) to characterize sediment variability on patchy riverbeds. Here, we apply these methods to multibeam echosounder (MBES) data collected from the bed of the Colorado River in Marble and Grand Canyons. Sediment dynamics on the Colorado River in Grand Canyon National Park have been studied for several decades (e.g. Howard and Dolan, 1981; Rubin et al., 2002). Particular focus has been given to sandbars in large eddies downstream of tributary debris fans (Schmidt, 1990) because they are considered valuable resources by stakeholders and managers. Due to the severe limitations in sand supply imposed by Glen Canyon Dam (Howard and Dolan, 1981; Topping et al., 2000; Hazel et al., 2006), understanding the effectiveness of sandbar management practices, such as controlled floods (Rubin et al. 2002; Topping et al., 2006; Hazel et al., 2010), and the long-term fate of sand in Grand Canyon over decadal timescales, requires construction of accurate sand budgets, which involves detailed monitoring of influx, efflux and changes in sand storage (Topping et al., 2000; Topping et al., 2010; Grams et al., 2013) and assessments of uncertainties in sand-budget calculations (Grams et al., 2013). In order to estimate the sand budget, it is necessary to estimate what component of observed morphological changes is sand and what component is coarser. Grams et al. (2013) classified sand and coarse substrates using topographic roughness derived from digital elevation models, but the classification skill was estimated to be only 60-70%. In addition, sand bedforms had to be delineated manually, and validation was based on grain-size observations with positional uncertainties up to tens of meters. Because the morphology of the Colorado riverbed in Grand Canyon is mapped - to a large extent - using MBES (Kaplinski et al., 2009), the primary motivation for the present study is to examine how uncertainties in sand budgets can be constrained by producing maps of surface sediment types using the completely automated methods of Buscombe et al (2014b, 2014c) based on statistical analysis of MBES acoustic backscatter.

Deep learning for single-molecule science

NASA Astrophysics Data System (ADS)

Albrecht, Tim; Slabaugh, Gregory; Alonso, Eduardo; Al-Arif, SM Masudur R.

2017-10-01

Exploring and making predictions based on single-molecule data can be challenging, not only due to the sheer size of the datasets, but also because a priori knowledge about the signal characteristics is typically limited and poor signal-to-noise ratio. For example, hypothesis-driven data exploration, informed by an expectation of the signal characteristics, can lead to interpretation bias or loss of information. Equally, even when the different data categories are known, e.g., the four bases in DNA sequencing, it is often difficult to know how to make best use of the available information content. The latest developments in machine learning (ML), so-called deep learning (DL) offer interesting, new avenues to address such challenges. In some applications, such as speech and image recognition, DL has been able to outperform conventional ML strategies and even human performance. However, to date DL has not been applied much in single-molecule science, presumably in part because relatively little is known about the ‘internal workings’ of such DL tools within single-molecule science as a field. In this Tutorial, we make an attempt to illustrate in a step-by-step guide how one of those, a convolutional neural network (CNN), may be used for base calling in DNA sequencing applications. We compare it with a SVM as a more conventional ML method, and discuss some of the strengths and weaknesses of the approach. In particular, a ‘deep’ neural network has many features of a ‘black box’, which has important implications on how we look at and interpret data.

The barley EST DNA Replication and Repair Database (bEST-DRRD) as a tool for the identification of the genes involved in DNA replication and repair.

PubMed

Gruszka, Damian; Marzec, Marek; Szarejko, Iwona

2012-06-14

The high level of conservation of genes that regulate DNA replication and repair indicates that they may serve as a source of information on the origin and evolution of the species and makes them a reliable system for the identification of cross-species homologs. Studies that had been conducted to date shed light on the processes of DNA replication and repair in bacteria, yeast and mammals. However, there is still much to be learned about the process of DNA damage repair in plants. These studies, which were conducted mainly using bioinformatics tools, enabled the list of genes that participate in various pathways of DNA repair in Arabidopsis thaliana (L.) Heynh to be outlined; however, information regarding these mechanisms in crop plants is still very limited. A similar, functional approach is particularly difficult for a species whose complete genomic sequences are still unavailable. One of the solutions is to apply ESTs (Expressed Sequence Tags) as the basis for gene identification. For the construction of the barley EST DNA Replication and Repair Database (bEST-DRRD), presented here, the Arabidopsis nucleotide and protein sequences involved in DNA replication and repair were used to browse for and retrieve the deposited sequences, derived from four barley (Hordeum vulgare L.) sequence databases, including the "Barley Genome version 0.05" database (encompassing ca. 90% of barley coding sequences) and from two databases covering the complete genomes of two monocot models: Oryza sativa L. and Brachypodium distachyon L. in order to identify homologous genes. Sequences of the categorised Arabidopsis queries are used for browsing the repositories, which are located on the ViroBLAST platform. The bEST-DRRD is currently used in our project during the identification and validation of the barley genes involved in DNA repair. The presented database provides information about the Arabidopsis genes involved in DNA replication and repair, their expression patterns and models of protein interactions. It was designed and established to provide an open-access tool for the identification of monocot homologs of known Arabidopsis genes that are responsible for DNA-related processes. The barley genes identified in the project are currently being analysed to validate their function.

Improved detection of DNA-binding proteins via compression technology on PSSM information.

PubMed

Wang, Yubo; Ding, Yijie; Guo, Fei; Wei, Leyi; Tang, Jijun

2017-01-01

Since the importance of DNA-binding proteins in multiple biomolecular functions has been recognized, an increasing number of researchers are attempting to identify DNA-binding proteins. In recent years, the machine learning methods have become more and more compelling in the case of protein sequence data soaring, because of their favorable speed and accuracy. In this paper, we extract three features from the protein sequence, namely NMBAC (Normalized Moreau-Broto Autocorrelation), PSSM-DWT (Position-specific scoring matrix-Discrete Wavelet Transform), and PSSM-DCT (Position-specific scoring matrix-Discrete Cosine Transform). We also employ feature selection algorithm on these feature vectors. Then, these features are fed into the training SVM (support vector machine) model as classifier to predict DNA-binding proteins. Our method applys three datasets, namely PDB1075, PDB594 and PDB186, to evaluate the performance of our approach. The PDB1075 and PDB594 datasets are employed for Jackknife test and the PDB186 dataset is used for the independent test. Our method achieves the best accuracy in the Jacknife test, from 79.20% to 86.23% and 80.5% to 86.20% on PDB1075 and PDB594 datasets, respectively. In the independent test, the accuracy of our method comes to 76.3%. The performance of independent test also shows that our method has a certain ability to be effectively used for DNA-binding protein prediction. The data and source code are at https://doi.org/10.6084/m9.figshare.5104084.

Mobius Assembly: A versatile Golden-Gate framework towards universal DNA assembly.

PubMed

Andreou, Andreas I; Nakayama, Naomi

2018-01-01

Synthetic biology builds upon the foundation of engineering principles, prompting innovation and improvement in biotechnology via a design-build-test-learn cycle. A community-wide standard in DNA assembly would enable bio-molecular engineering at the levels of predictivity and universality in design and construction that are comparable to other engineering fields. Golden Gate Assembly technology, with its robust capability to unidirectionally assemble numerous DNA fragments in a one-tube reaction, has the potential to deliver a universal standard framework for DNA assembly. While current Golden Gate Assembly frameworks (e.g. MoClo and Golden Braid) render either high cloning capacity or vector toolkit simplicity, the technology can be made more versatile-simple, streamlined, and cost/labor-efficient, without compromising capacity. Here we report the development of a new Golden Gate Assembly framework named Mobius Assembly, which combines vector toolkit simplicity with high cloning capacity. It is based on a two-level, hierarchical approach and utilizes a low-frequency cutter to reduce domestication requirements. Mobius Assembly embraces the standard overhang designs designated by MoClo, Golden Braid, and Phytobricks and is largely compatible with already available Golden Gate part libraries. In addition, dropout cassettes encoding chromogenic proteins were implemented for cost-free visible cloning screening that color-code different cloning levels. As proofs of concept, we have successfully assembled up to 16 transcriptional units of various pigmentation genes in both operon and multigene arrangements. Taken together, Mobius Assembly delivers enhanced versatility and efficiency in DNA assembly, facilitating improved standardization and automation.

Cultural traditions across a migratory network shape the genetic structure of southern right whales around Australia and New Zealand

PubMed Central

Carroll, E. L.; Baker, C. S.; Watson, M.; Alderman, R.; Bannister, J.; Gaggiotti, O. E.; Gröcke, D. R.; Patenaude, N.; Harcourt, R.

2015-01-01

Fidelity to migratory destinations is an important driver of connectivity in marine and avian species. Here we assess the role of maternally directed learning of migratory habitats, or migratory culture, on the population structure of the endangered Australian and New Zealand southern right whale. Using DNA profiles, comprising mitochondrial DNA (mtDNA) haplotypes (500 bp), microsatellite genotypes (17 loci) and sex from 128 individually-identified whales, we find significant differentiation among winter calving grounds based on both mtDNA haplotype (FST = 0.048, ΦST = 0.109, p < 0.01) and microsatellite allele frequencies (FST = 0.008, p < 0.01), consistent with long-term fidelity to calving areas. However, most genetic comparisons of calving grounds and migratory corridors were not significant, supporting the idea that whales from different calving grounds mix in migratory corridors. Furthermore, we find a significant relationship between δ13C stable isotope profiles of 66 Australian southern right whales, a proxy for feeding ground location, and both mtDNA haplotypes and kinship inferred from microsatellite-based estimators of relatedness. This indicates migratory culture may influence genetic structure on feeding grounds. This fidelity to migratory destinations is likely to influence population recovery, as long-term estimates of historical abundance derived from estimates of genetic diversity indicate the South Pacific calving grounds remain at <10% of pre-whaling abundance. PMID:26548756

Heavy Charged Particle Radiobiology: Using Enhanced Biological Effectiveness and Improved Beam Focusing to Advance Cancer Therapy

PubMed Central

Allen, Christopher; Borak, Thomas B.; Tsujii, Hirohiko; Nickoloff, Jac A.

2011-01-01

Ionizing radiation causes many types of DNA damage, including base damage and single- and double-strand breaks. Photons, including X-rays and γ-rays, are the most widely used type of ionizing radiation in radiobiology experiments, and in radiation cancer therapy. Charged particles, including protons and carbon ions, are seeing increased use as an alternative therapeutic modality. Although the facilities needed to produce high energy charged particle beams are more costly than photon facilities, particle therapy has shown improved cancer survival rates, reflecting more highly focused dose distributions and more severe DNA damage to tumor cells. Despite early successes of charged particle radiotherapy, there is room for further improvement, and much remains to be learned about normal and cancer cell responses to charged particle radiation. PMID:21376738

Genetic screens and functional genomics using CRISPR/Cas9 technology.

PubMed

Hartenian, Ella; Doench, John G

2015-04-01

Functional genomics attempts to understand the genome by perturbing the flow of information from DNA to RNA to protein, in order to learn how gene dysfunction leads to disease. CRISPR/Cas9 technology is the newest tool in the geneticist's toolbox, allowing researchers to edit DNA with unprecedented ease, speed and accuracy, and representing a novel means to perform genome-wide genetic screens to discover gene function. In this review, we first summarize the discovery and characterization of CRISPR/Cas9, and then compare it to other genome engineering technologies. We discuss its initial use in screening applications, with a focus on optimizing on-target activity and minimizing off-target effects. Finally, we comment on future challenges and opportunities afforded by this technology. © 2015 FEBS.

Case Study Teaching Method Improves Student Performance and Perceptions of Learning Gains†

PubMed Central

Bonney, Kevin M.

2015-01-01

Following years of widespread use in business and medical education, the case study teaching method is becoming an increasingly common teaching strategy in science education. However, the current body of research provides limited evidence that the use of published case studies effectively promotes the fulfillment of specific learning objectives integral to many biology courses. This study tested the hypothesis that case studies are more effective than classroom discussions and textbook reading at promoting learning of key biological concepts, development of written and oral communication skills, and comprehension of the relevance of biological concepts to everyday life. This study also tested the hypothesis that case studies produced by the instructor of a course are more effective at promoting learning than those produced by unaffiliated instructors. Additionally, performance on quantitative learning assessments and student perceptions of learning gains were analyzed to determine whether reported perceptions of learning gains accurately reflect academic performance. The results reported here suggest that case studies, regardless of the source, are significantly more effective than other methods of content delivery at increasing performance on examination questions related to chemical bonds, osmosis and diffusion, mitosis and meiosis, and DNA structure and replication. This finding was positively correlated to increased student perceptions of learning gains associated with oral and written communication skills and the ability to recognize connections between biological concepts and other aspects of life. Based on these findings, case studies should be considered as a preferred method for teaching about a variety of concepts in science courses. PMID:25949753

Case study teaching method improves student performance and perceptions of learning gains.

PubMed

Bonney, Kevin M

2015-05-01

Following years of widespread use in business and medical education, the case study teaching method is becoming an increasingly common teaching strategy in science education. However, the current body of research provides limited evidence that the use of published case studies effectively promotes the fulfillment of specific learning objectives integral to many biology courses. This study tested the hypothesis that case studies are more effective than classroom discussions and textbook reading at promoting learning of key biological concepts, development of written and oral communication skills, and comprehension of the relevance of biological concepts to everyday life. This study also tested the hypothesis that case studies produced by the instructor of a course are more effective at promoting learning than those produced by unaffiliated instructors. Additionally, performance on quantitative learning assessments and student perceptions of learning gains were analyzed to determine whether reported perceptions of learning gains accurately reflect academic performance. The results reported here suggest that case studies, regardless of the source, are significantly more effective than other methods of content delivery at increasing performance on examination questions related to chemical bonds, osmosis and diffusion, mitosis and meiosis, and DNA structure and replication. This finding was positively correlated to increased student perceptions of learning gains associated with oral and written communication skills and the ability to recognize connections between biological concepts and other aspects of life. Based on these findings, case studies should be considered as a preferred method for teaching about a variety of concepts in science courses.

Neurotoxicity of low bisphenol A (BPA) exposure for young male mice: Implications for children exposed to environmental levels of BPA.

PubMed

Zhou, Yuanxiu; Wang, Zhouyu; Xia, Minghan; Zhuang, Siyi; Gong, Xiaobing; Pan, Jianwen; Li, Chuhua; Fan, Ruifang; Pang, Qihua; Lu, Shaoyou

2017-10-01

To investigate the neuron toxicities of low-dose exposure to bisphenol A (BPA) in children, mice were used as an animal model. We examined brain cell damage and the effects of learning and memory ability after BPA exposure in male mice (4 weeks of age) that were divided into four groups and chronically received different BPA treatments for 8 weeks. The comet assay and hippocampal neuron counting were used to detect the brain cell damage. The Y-maze test was applied to test alterations in learning and memory ability. Long term potentiation induction by BPA exposure was performed to study the potential mechanism of performance. The percentages of tail DNA, tail length and tail moment in brain cells increased with increasing BPA exposure concentrations. Significant differences in DNA damage were observed among the groups, including between the low-dose and control groups. In the Y-maze test, the other three groups qualified for the learned standard one day earlier than the high-exposed group. Furthermore, the ratio of qualified mice in the high-exposed group was always the lowest among the groups, indicating that high BPA treatment significantly altered the spatial memory performance of mice. Different BPA treatments exerted different effects on the neuron numbers of different regions in the hippocampus. In the CA1 region, the high-exposed group had a significant decrease in neuron numbers. A non-monotonic relationship was observed between the exposure concentrations and neuron quantity in the CA3 region. The hippocampal slices in the control and medium-exposed groups generated long-term potentiation after induction by theta burst stimulation, but the low-exposed group did not. A significant difference was observed between the control and low-exposed groups. In conclusion, chronic exposure to a low level of BPA had adverse effects on brain cells and altered the learning and memory ability of adolescent mice. Copyright © 2017 Elsevier Ltd. All rights reserved.

Degradable self-assembling dendrons for gene delivery: experimental and theoretical insights into the barriers to cellular uptake.

PubMed

Barnard, Anna; Posocco, Paola; Pricl, Sabrina; Calderon, Marcelo; Haag, Rainer; Hwang, Mark E; Shum, Victor W T; Pack, Daniel W; Smith, David K

2011-12-21

This paper uses a combined experimental and theoretical approach to gain unique insight into gene delivery. We report the synthesis and investigation of a new family of second-generation dendrons with four triamine surface ligands capable of binding to DNA, degradable aliphatic-ester dendritic scaffolds, and hydrophobic units at their focal points. Dendron self-assembly significantly enhances DNA binding as monitored by a range of experimental methods and confirmed by multiscale modeling. Cellular uptake studies indicate that some of these dendrons are highly effective at transporting DNA into cells (ca. 10 times better than poly(ethyleneimine), PEI). However, levels of transgene expression are relatively low (ca. 10% of PEI). This indicates that these dendrons cannot navigate all of the intracellular barriers to gene delivery. The addition of chloroquine indicates that endosomal escape is not the limiting factor in this case, and it is shown, both experimentally and theoretically, that gene delivery can be correlated with the ability of the dendron assemblies to release DNA. Mass spectrometric assays demonstrate that the dendrons, as intended, do degrade under biologically relevant conditions over a period of hours. Multiscale modeling of degraded dendron structures suggests that complete dendron degradation would be required for DNA release. Importantly, in the presence of the lower pH associated with endosomes, or when bound to DNA, complete degradation of these dendrons becomes ineffective on the transfection time scale-we propose this explains the poor transfection performance of these dendrons. As such, this paper demonstrates that taking this kind of multidisciplinary approach can yield a fundamental insight into the way in which dendrons can navigate barriers to cellular uptake. Lessons learned from this work will inform future dendron design for enhanced gene delivery. © 2011 American Chemical Society

High-Risk Palliative Care Patients' Knowledge and Attitudes about Hereditary Cancer Testing and DNA Banking.

PubMed

Quillin, John M; Emidio, Oluwabunmi; Ma, Brittany; Bailey, Lauryn; Smith, Thomas J; Kang, In Guk; Yu, Brandon J; Owodunni, Oluwafemi Patrick; Abusamaan, Mohammed; Razzak, Rab; Bodurtha, Joann N

2017-12-04

Even at the end of life, testing cancer patients for inherited susceptibility may provide life-saving information to their relatives. Prior research suggests palliative care inpatients have suboptimal understanding of genetic importance, and testing may be underutilized in this clinical setting. These conclusions are based on limited research. This study aimed to estimate genetic testing prevalence among high-risk palliative care patients in a National Cancer Institute-designated comprehensive cancer center. We also aimed to understand these patients' understanding of, and attitudes toward, hereditary cancer testing and DNA banking. Palliative care in-patients with cancer completed structured interviews, and their medical records were reviewed. Among patients at high risk for hereditary cancer, we assessed history of genetic testing/DNA banking; and related knowledge and attitudes. Among 24 high-risk patients, 14 (58.3%) said they/their relatives had genetic testing or they had been referred for a genetics consultation. Of the remaining 10 patients, seven (70%) said they would "probably" or "definitely" get tested. Patients who had not had testing were least concerned about the impact of future testing on their family relationships; two (20%) said they were "extremely concerned" about privacy related to genetic testing. Of patients without prior testing, five (50%) said they had heard or read "a fair amount" about genetic testing. No high-risk patients had banked DNA. Overall, 23 (95.8%) said they had heard or read "almost nothing" or "relatively little" about DNA banking. Written materials and clinician discussion were most preferred ways to learn about genetic testing and DNA banking. Overall, this study demonstrates underutilization of genetics services at the end of life continues to be problematic, despite high patient interest.

A role for histone deacetylases in the cellular and behavioral mechanisms underlying learning and memory.

PubMed

Mahgoub, Melissa; Monteggia, Lisa M

2014-10-01

Histone deacetylases (HDACs) are a family of chromatin remodeling enzymes that restrict access of transcription factors to the DNA, thereby repressing gene expression. In contrast, histone acetyltransferases (HATs) relax the chromatin structure allowing for an active chromatin state and promoting gene transcription. Accumulating data have demonstrated a crucial function for histone acetylation and histone deacetylation in regulating the cellular and behavioral mechanisms underlying synaptic plasticity and learning and memory. In trying to delineate the roles of individual HDACs, genetic tools have been used to manipulate HDAC expression in rodents, uncovering distinct contributions of individual HDACs in regulating the processes of memory formation. Moreover, recent findings have suggested an important role for HDAC inhibitors in enhancing learning and memory processes as well as ameliorating symptoms related to neurodegenerative diseases. In this review, we focus on the role of HDACs in learning and memory, as well as significant data emerging from the field in support of HDAC inhibitors as potential therapeutic targets for the treatment of cognitive disorders. © 2014 Mahgoub and Monteggia; Published by Cold Spring Harbor Laboratory Press.

Genome organization factor determines the few cells that make a tumor grow | Center for Cancer Research

Cancer.gov

In the September 30, 2016, issue of the journal Science, scientists led by former CCR postdoctoral fellow Paola Scaffidi report that an essential DNA-packing protein called linker histone H1.0 is present in varying levels in the cells of tumors, and plays an important role in determining which cells have the capacity to sustain the tumor’s growth.  Learn more...

Genomics Analogy Model for Educators (GAME): VELCRO® Analogy Model to Enable the Learning of DNA Arrays for Visually Impaired and Blind Students

ERIC Educational Resources Information Center

Bello, Julia; Butler, Charles; Radavich, Rosanne; York, Alan; Oseto, Christian; Orvis, Kathryn; Pittendrigh, Barry R.

2007-01-01

Although members of the general public have often heard of the terms "genetic engineering" and, more recently, genomics, they typically have little to no knowledge about these topics, and in some cases are confused about basic concepts in these areas. There is currently a need for teaching models to explain concepts behind genomics.…

Self-directed student research through analysis of microarray datasets: a computer-based functional genomics practical class for masters-level students.

PubMed

Grenville-Briggs, Laura J; Stansfield, Ian

2011-01-01

This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate active learning through experience of current research methods in bioinformatics and functional genomics. They seek to closely mimic a realistic research environment, and require the students first to propose research hypotheses, then test those hypotheses using specific sections of the microarray dataset. The complexity of the microarray data provides students with the freedom to propose their own unique hypotheses, tested using appropriate sections of the microarray data. This research latitude was highly regarded by students and is a strength of this practical. In addition, the focus on DNA damage by radiation and mutagenic chemicals allows them to place their results in a human medical context, and successfully sparks broad interest in the subject material. In evaluation, 79% of students scored the practical workshops on a five-point scale as 4 or 5 (totally effective) for student learning. More broadly, the general use of microarray data as a "student research playground" is also discussed. Copyright © 2011 Wiley Periodicals, Inc.

A molecular genetic lab to generate inclusive and exclusive forensic evidence: two suspects, a victim, and a bloodstained T-shirt.

PubMed

Smit, Julie; Heath, Daniel D; Walter, Ryan P

2014-01-01

Molecular genetic laboratory exercises can be ineffective due the student's lack of connection to the complex and sequential protocols. In this inquiry-based molecular genetic laboratory exercise, we harness students' fascination with human forensics and provide a real-life scenario using biomolecular techniques to identify "whose blood is on the t-shirt." We use fish blood to create realistic blood stains on clothing and challenge the students to use DNA analyses to clear or implicate suspects. Safety concerns are minimized through the use of fish blood, while maximizing both realism and the likelihood of student success due to fishes' nucleated red blood cells. The goal in designing this laboratory exercise was to create a feasible protocol for large (over 300 students) second year university courses. During two 3 hour laboratory sessions, students learn and apply clean/sterile technique, DNA extraction, polymerase chain reaction, restriction fragment length polymorphisms, and agarose gel electrophoresis. The students also learn to interpret the resulting gel bands in terms of inclusive or exclusive evidence. Students have consistently ranked this lab as their favorite of five taken as part of a second year Genetics course. Copyright © 2013 by The International Union of Biochemistry and Molecular Biology.

Machine Learned Replacement of N-Labels for Basecalled Sequences in DNA Barcoding.

PubMed

Ma, Eddie Y T; Ratnasingham, Sujeevan; Kremer, Stefan C

2018-01-01

This study presents a machine learning method that increases the number of identified bases in Sanger Sequencing. The system post-processes a KB basecalled chromatogram. It selects a recoverable subset of N-labels in the KB-called chromatogram to replace with basecalls (A,C,G,T). An N-label correction is defined given an additional read of the same sequence, and a human finished sequence. Corrections are added to the dataset when an alignment determines the additional read and human agree on the identity of the N-label. KB must also rate the replacement with quality value of in the additional read. Corrections are only available during system training. Developing the system, nearly 850,000 N-labels are obtained from Barcode of Life Datasystems, the premier database of genetic markers called DNA Barcodes. Increasing the number of correct bases improves reference sequence reliability, increases sequence identification accuracy, and assures analysis correctness. Keeping with barcoding standards, our system maintains an error rate of percent. Our system only applies corrections when it estimates low rate of error. Tested on this data, our automation selects and recovers: 79 percent of N-labels from COI (animal barcode); 80 percent from matK and rbcL (plant barcodes); and 58 percent from non-protein-coding sequences (across eukaryotes).

Massively parallel digital high resolution melt for rapid and absolutely quantitative sequence profiling

NASA Astrophysics Data System (ADS)

Velez, Daniel Ortiz; Mack, Hannah; Jupe, Julietta; Hawker, Sinead; Kulkarni, Ninad; Hedayatnia, Behnam; Zhang, Yang; Lawrence, Shelley; Fraley, Stephanie I.

2017-02-01

In clinical diagnostics and pathogen detection, profiling of complex samples for low-level genotypes represents a significant challenge. Advances in speed, sensitivity, and extent of multiplexing of molecular pathogen detection assays are needed to improve patient care. We report the development of an integrated platform enabling the identification of bacterial pathogen DNA sequences in complex samples in less than four hours. The system incorporates a microfluidic chip and instrumentation to accomplish universal PCR amplification, High Resolution Melting (HRM), and machine learning within 20,000 picoliter scale reactions, simultaneously. Clinically relevant concentrations of bacterial DNA molecules are separated by digitization across 20,000 reactions and amplified with universal primers targeting the bacterial 16S gene. Amplification is followed by HRM sequence fingerprinting in all reactions, simultaneously. The resulting bacteria-specific melt curves are identified by Support Vector Machine learning, and individual pathogen loads are quantified. The platform reduces reaction volumes by 99.995% and achieves a greater than 200-fold increase in dynamic range of detection compared to traditional PCR HRM approaches. Type I and II error rates are reduced by 99% and 100% respectively, compared to intercalating dye-based digital PCR (dPCR) methods. This technology could impact a number of quantitative profiling applications, especially infectious disease diagnostics.

Education: DNA replication using microscale natural convection.

PubMed

Priye, Aashish; Hassan, Yassin A; Ugaz, Victor M

2012-12-07

There is a need for innovative educational experiences that unify and reinforce fundamental principles at the interface between the physical, chemical, and life sciences. These experiences empower and excite students by helping them recognize how interdisciplinary knowledge can be applied to develop new products and technologies that benefit society. Microfluidics offers an incredibly versatile tool to address this need. Here we describe our efforts to create innovative hands-on activities that introduce chemical engineering students to molecular biology by challenging them to harness microscale natural convection phenomena to perform DNA replication via the polymerase chain reaction (PCR). Experimentally, we have constructed convective PCR stations incorporating a simple design for loading and mounting cylindrical microfluidic reactors between independently controlled thermal plates. A portable motion analysis microscope enables flow patterns inside the convective reactors to be directly visualized using fluorescent bead tracers. We have also developed a hands-on computational fluid dynamics (CFD) exercise based on modeling microscale thermal convection to identify optimal geometries for DNA replication. A cognitive assessment reveals that these activities strongly impact student learning in a positive way.

A Predictive Approach to Network Reverse-Engineering

NASA Astrophysics Data System (ADS)

Wiggins, Chris

2005-03-01

A central challenge of systems biology is the ``reverse engineering" of transcriptional networks: inferring which genes exert regulatory control over which other genes. Attempting such inference at the genomic scale has only recently become feasible, via data-intensive biological innovations such as DNA microrrays (``DNA chips") and the sequencing of whole genomes. In this talk we present a predictive approach to network reverse-engineering, in which we integrate DNA chip data and sequence data to build a model of the transcriptional network of the yeast S. cerevisiae capable of predicting the response of genes in unseen experiments. The technique can also be used to extract ``motifs,'' sequence elements which act as binding sites for regulatory proteins. We validate by a number of approaches and present comparison of theoretical prediction vs. experimental data, along with biological interpretations of the resulting model. En route, we will illustrate some basic notions in statistical learning theory (fitting vs. over-fitting; cross- validation; assessing statistical significance), highlighting ways in which physicists can make a unique contribution in data- driven approaches to reverse engineering.

iASeq: integrative analysis of allele-specificity of protein-DNA interactions in multiple ChIP-seq datasets

PubMed Central

2012-01-01

Background ChIP-seq provides new opportunities to study allele-specific protein-DNA binding (ASB). However, detecting allelic imbalance from a single ChIP-seq dataset often has low statistical power since only sequence reads mapped to heterozygote SNPs are informative for discriminating two alleles. Results We develop a new method iASeq to address this issue by jointly analyzing multiple ChIP-seq datasets. iASeq uses a Bayesian hierarchical mixture model to learn correlation patterns of allele-specificity among multiple proteins. Using the discovered correlation patterns, the model allows one to borrow information across datasets to improve detection of allelic imbalance. Application of iASeq to 77 ChIP-seq samples from 40 ENCODE datasets and 1 genomic DNA sample in GM12878 cells reveals that allele-specificity of multiple proteins are highly correlated, and demonstrates the ability of iASeq to improve allelic inference compared to analyzing each individual dataset separately. Conclusions iASeq illustrates the value of integrating multiple datasets in the allele-specificity inference and offers a new tool to better analyze ASB. PMID:23194258

A PARP1-ERK2 synergism is required for the induction of LTP

PubMed Central

Visochek, L.; Grigoryan, G.; Kalal, A.; Milshtein-Parush, H.; Gazit, N.; Slutsky, I.; Yeheskel, A.; Shainberg, A.; Castiel, A.; Seger, R.; Langelier, M. F.; Dantzer, F.; Pascal, J. M.; Segal, M.; Cohen-Armon, M.

2016-01-01

Unexpectedly, a post-translational modification of DNA-binding proteins, initiating the cell response to single-strand DNA damage, was also required for long-term memory acquisition in a variety of learning paradigms. Our findings disclose a molecular mechanism based on PARP1-Erk synergism, which may underlie this phenomenon. A stimulation induced PARP1 binding to phosphorylated Erk2 in the chromatin of cerebral neurons caused Erk-induced PARP1 activation, rendering transcription factors and promoters of immediate early genes (IEG) accessible to PARP1-bound phosphorylated Erk2. Thus, Erk-induced PARP1 activation mediated IEG expression implicated in long-term memory. PARP1 inhibition, silencing, or genetic deletion abrogated stimulation-induced Erk-recruitment to IEG promoters, gene expression and LTP generation in hippocampal CA3-CA1-connections. Moreover, a predominant binding of PARP1 to single-strand DNA breaks, occluding its Erk binding sites, suppressed IEG expression and prevented the generation of LTP. These findings outline a PARP1-dependent mechanism required for LTP generation, which may be implicated in long-term memory acquisition and in its deterioration in senescence. PMID:27121568

A PARP1-ERK2 synergism is required for the induction of LTP.

PubMed

Visochek, L; Grigoryan, G; Kalal, A; Milshtein-Parush, H; Gazit, N; Slutsky, I; Yeheskel, A; Shainberg, A; Castiel, A; Seger, R; Langelier, M F; Dantzer, F; Pascal, J M; Segal, M; Cohen-Armon, M

2016-04-28

Unexpectedly, a post-translational modification of DNA-binding proteins, initiating the cell response to single-strand DNA damage, was also required for long-term memory acquisition in a variety of learning paradigms. Our findings disclose a molecular mechanism based on PARP1-Erk synergism, which may underlie this phenomenon. A stimulation induced PARP1 binding to phosphorylated Erk2 in the chromatin of cerebral neurons caused Erk-induced PARP1 activation, rendering transcription factors and promoters of immediate early genes (IEG) accessible to PARP1-bound phosphorylated Erk2. Thus, Erk-induced PARP1 activation mediated IEG expression implicated in long-term memory. PARP1 inhibition, silencing, or genetic deletion abrogated stimulation-induced Erk-recruitment to IEG promoters, gene expression and LTP generation in hippocampal CA3-CA1-connections. Moreover, a predominant binding of PARP1 to single-strand DNA breaks, occluding its Erk binding sites, suppressed IEG expression and prevented the generation of LTP. These findings outline a PARP1-dependent mechanism required for LTP generation, which may be implicated in long-term memory acquisition and in its deterioration in senescence.

Toward a new history and geography of human genes informed by ancient DNA

PubMed Central

Pickrell, Joseph K.; Reich, David

2014-01-01

Genetic information contains a record of the history of our species, and technological advances have transformed our ability to access this record. Many studies have used genome-wide data from populations today to learn about the peopling of the globe and subsequent adaptation to local conditions. Implicit in this research is the assumption that the geographic locations of people today are informative about the geographic locations of their ancestors in the distant past. However, it is now clear that long-range migration, admixture and population replacement subsequent to the initial out-of-Africa expansion have altered the genetic structure of most of the world’s human populations. In light of this, we argue that it is time to critically re-evaluate current models of the peopling of the globe, as well as the importance of natural selection in determining the geographic distribution of phenotypes. We specifically highlight the transformative potential of ancient DNA. By accessing the genetic make-up of populations living at archaeologically-known times and places, ancient DNA makes it possible to directly track migrations and responses to natural selection. PMID:25168683

Cdc7 kinase - a new target for drug development.

PubMed

Swords, Ronan; Mahalingam, Devalingam; O'Dwyer, Michael; Santocanale, Corrado; Kelly, Kevin; Carew, Jennifer; Giles, Francis

2010-01-01

The cell division cycle 7 (Cdc7) is a serine threonine kinase that is of critical importance in the regulation of normal cell cycle progression. Cdc7 kinase is highly conserved during evolution and much has been learned about its biological roles in humans through the study of lower eukaryotes, particularly yeasts. Two important regulator proteins, Dbf4 and Drf1, bind to and modulate the kinase activity of human Cdc7 which phosphorylates several sites on Mcm2 (minichromosome maintenance protein 2), one of the six subunits of the replicative DNA helicase needed for duplication of the genome. Through regulation of both DNA synthesis and DNA damage response, both key functions in the survival of tumour cells, Cdc7 becomes an attractive target for pharmacological inhibition. There are much data available on the pre-clinical anti-cancer effects of Cdc7 depletion and although there are no available Cdc7 inhibitors in clinical trials as yet, several lead compounds are being optimised for this purpose. In this review, we will address the current status of Cdc7 as an important target for new drug development.

Deoxyribozymes: Selection Design and Serendipity in the Development of DNA Catalysts†

PubMed Central

Silverman, Scott K.

2009-01-01

CONSPECTUS One of the chemist’s key motivations is to explore the forefront of catalysis. In this Account, we describe our laboratory’s efforts at one such forefront: the use of DNA as a catalyst. Natural biological catalysts include both protein enzymes and RNA enzymes (ribozymes), whereas nature apparently uses DNA solely for genetic information storage. Nevertheless, the chemical similarities between RNA and DNA naturally lead to laboratory examination of DNA as a catalyst, especially because DNA is more stable than RNA and is less costly and easier to synthesize. Many catalytically active DNA sequences (deoxyribozymes, also called DNAzymes) have been identified in the laboratory by in vitro selection, in which many random DNA sequences are evaluated in parallel to find those rare sequences that have a desired functional ability. Since 2001, our research group has pursued new deoxyribozymes for various chemical reactions. We consider DNA simply as a large biopolymer that can adopt intricate three-dimensional structure and, in the presence of appropriate metal ions, generate the chemical complexity required to achieve catalysis. Our initial efforts focused on deoxyribozymes that ligate two RNA substrates. In these studies, we used only substrates that are readily obtained biochemically. Highly active deoxyribozymes have been identified, with emergent questions regarding chemical selectivity during RNA phosphodiester bond formation. Deoxyribozymes allow synthesis of interesting RNA products, such as branches and lariats, that are otherwise challenging to prepare. Our experiments have demonstrated that deoxyribozymes can have very high rate enhancements and chemical selectivities. We have also shown how the in vitro selection process itself can be directed towards desired goals, such as selective formation of native 3′–5′ RNA linkages. A final lesson is that unanticipated selection outcomes can be very interesting, highlighting the importance of allowing such opportunities in future experiments. More recently, we have begun using non-oligonucleotide substrates in our efforts with deoxyribozymes. We have especially focused on developing DNA catalysts for reactions of small molecules or amino acid side chains. For example, new deoxyribozymes have the catalytic power to create a nucleopeptide linkage between a tyrosine or serine side chain and the 5′-terminus of an RNA strand. Although considerable further work remains to establish DNA as a practical catalyst for small molecules and full-length proteins, the progress to date is very promising. The many lessons learned during the experiments described in this Account will help us and others to realize the full catalytic power of DNA. PMID:19572701

Foxp2 mutations impair auditory-motor association learning.

PubMed

Kurt, Simone; Fisher, Simon E; Ehret, Günter

2012-01-01

Heterozygous mutations of the human FOXP2 transcription factor gene cause the best-described examples of monogenic speech and language disorders. Acquisition of proficient spoken language involves auditory-guided vocal learning, a specialized form of sensory-motor association learning. The impact of etiological Foxp2 mutations on learning of auditory-motor associations in mammals has not been determined yet. Here, we directly assess this type of learning using a newly developed conditioned avoidance paradigm in a shuttle-box for mice. We show striking deficits in mice heterozygous for either of two different Foxp2 mutations previously implicated in human speech disorders. Both mutations cause delays in acquiring new motor skills. The magnitude of impairments in association learning, however, depends on the nature of the mutation. Mice with a missense mutation in the DNA-binding domain are able to learn, but at a much slower rate than wild type animals, while mice carrying an early nonsense mutation learn very little. These results are consistent with expression of Foxp2 in distributed circuits of the cortex, striatum and cerebellum that are known to play key roles in acquisition of motor skills and sensory-motor association learning, and suggest differing in vivo effects for distinct variants of the Foxp2 protein. Given the importance of such networks for the acquisition of human spoken language, and the fact that similar mutations in human FOXP2 cause problems with speech development, this work opens up a new perspective on the use of mouse models for understanding pathways underlying speech and language disorders.

A review of supervised machine learning applied to ageing research.

PubMed

Fabris, Fabio; Magalhães, João Pedro de; Freitas, Alex A

2017-04-01

Broadly speaking, supervised machine learning is the computational task of learning correlations between variables in annotated data (the training set), and using this information to create a predictive model capable of inferring annotations for new data, whose annotations are not known. Ageing is a complex process that affects nearly all animal species. This process can be studied at several levels of abstraction, in different organisms and with different objectives in mind. Not surprisingly, the diversity of the supervised machine learning algorithms applied to answer biological questions reflects the complexities of the underlying ageing processes being studied. Many works using supervised machine learning to study the ageing process have been recently published, so it is timely to review these works, to discuss their main findings and weaknesses. In summary, the main findings of the reviewed papers are: the link between specific types of DNA repair and ageing; ageing-related proteins tend to be highly connected and seem to play a central role in molecular pathways; ageing/longevity is linked with autophagy and apoptosis, nutrient receptor genes, and copper and iron ion transport. Additionally, several biomarkers of ageing were found by machine learning. Despite some interesting machine learning results, we also identified a weakness of current works on this topic: only one of the reviewed papers has corroborated the computational results of machine learning algorithms through wet-lab experiments. In conclusion, supervised machine learning has contributed to advance our knowledge and has provided novel insights on ageing, yet future work should have a greater emphasis in validating the predictions.

The cognitive impairment induced by zinc deficiency in rats aged 0∼2 months related to BDNF DNA methylation changes in the hippocampus.

PubMed

Hu, Yan-Dan; Pang, Wei; He, Cong-Cong; Lu, Hao; Liu, Wei; Wang, Zi-Yu; Liu, Yan-Qiang; Huang, Cheng-Yu; Jiang, Yu-Gang

2017-11-01

This study was carried out to understand the effects of zinc deficiency in rats aged 0∼2 months on learning and memory, and the brain-derived neurotrophic factor (BDNF) gene methylation status in the hippocampus. The lactating mother rats were randomly divided into three groups (n = 12): zinc-adequate group (ZA: zinc 30 mg/kg diet), zinc-deprived group (ZD: zinc 1 mg/kg diet), and a pair-fed group (PF: zinc 30 mg/kg diet), in which the rats were pair-fed to those in the ZD group. After weaning (on day 23), offspring were fed the same diets as their mothers. After 37 days, the zinc concentrations in the plasma and hippocampus were measured, and the behavioral function of the offspring rats was measured using the passive avoidance performance test. We then assessed the DNA methylation patterns of the exon IX of BDNF by methylation-specific quantitative real-time PCR and the mRNA expression of BDNF in the hippocampus by RT-PCR. Compared with the ZA and PF groups, rats in the ZD group had shorter latency period, lower zinc concentrations in the plasma and hippocampus (P < 0.05). Interestingly, the DNA methylation of the BDNF exon IX was significantly increased in the ZD group, compared with the ZA and PF groups, whereas the expression of the BDNF mRNA was decreased. In addition, the DNMT1 mRNA expression was significantly upregulated and DNMT3A was downregulated in the ZD group, but not in the ZA and PF groups. The learning and memory damage in offspring may be a result of the epigenetic changes of the BDNF genes in response to the zinc-deficient diet during 0∼2 month period. Furthermore, this work supports the speculative notion that altered DNA methylation of BDNF in the hippocampus is one of the main causes of cognitive impairment by zinc deficiency.

EMQIT: a machine learning approach for energy based PWM matrix quality improvement.

PubMed

Smolinska, Karolina; Pacholczyk, Marcin

2017-08-01

Transcription factor binding affinities to DNA play a key role for the gene regulation. Learning the specificity of the mechanisms of binding TFs to DNA is important both to experimentalists and theoreticians. With the development of high-throughput methods such as, e.g., ChiP-seq the need to provide unbiased models of binding events has been made apparent. We present EMQIT a modification to the approach introduced by Alamanova et al. and later implemented as 3DTF server. We observed that tuning of Boltzmann factor weights, used for conversion of calculated energies to nucleotide probabilities, has a significant impact on the quality of the associated PWM matrix. Consequently, we proposed to use receiver operator characteristics curves and the 10-fold cross-validation to learn best weights using experimentally verified data from TRANSFAC database. We applied our method to data available for various TFs. We verified the efficiency of detecting TF binding sites by the 3DTF matrices improved with our technique using experimental data from the TRANSFAC database. The comparison showed a significant similarity and comparable performance between the improved and the experimental matrices (TRANSFAC). Improved 3DTF matrices achieved significantly higher AUC values than the original 3DTF matrices (at least by 0.1) and, at the same time, detected notably more experimentally verified TFBSs. The resulting new improved PWM matrices for analyzed factors show similarity to TRANSFAC matrices. Matrices had comparable predictive capabilities. Moreover, improved PWMs achieve better results than matrices downloaded from 3DTF server. Presented approach is general and applicable to any energy-based matrices. EMQIT is available online at http://biosolvers.polsl.pl:3838/emqit . This article was reviewed by Oliviero Carugo, Marek Kimmel and István Simon.

Pharmacokinetics, phenotype and product choice in haemophilia B: how to strike a balance?

PubMed

Berntorp, E; Dolan, G; Hermans, C; Laffan, M; Santagostino, E; Tiede, A

2014-11-01

At the 7th Annual Congress of the European Association for Haemophilia and Allied Disorders (EAHAD) held in Brussels, Belgium, in February 2014, Pfizer sponsored a satellite symposium entitled: "Pharmacokinetics, phenotype and product choice in haemophilia B: How to strike a balance?" Co-chaired by Cedric Hermans (Cliniques Universitaires Saint Luc, Brussels, Belgium) and Mike Laffan (Imperial College, London, UK), the symposium provided an opportunity to debate whether pharmacokinetic (PK) parameters are good surrogates for clinical efficacy for haemophilia B in clinical practice, consider the perceptions and evidence of disease severity, and examine how these considerations can inform approaches to balancing the potential risks and benefits of the currently available treatment options for haemophilia B. PK parameters are routinely measured in clinical practice and are a requirement of regulatory bodies to demonstrate the clinical efficacy of products; however, the relationship between measured PK parameters and clinical efficacy is yet to be determined, an issue that was debated by Gerry Dolan (University Hospital, Queen's Medical Centre, Nottingham, UK) and Erik Berntorp (Lund University, Malmö Centre for Thrombosis and Haemostasis, Malmö, Sweden). Elena Santagostino (Universita degli Studi di Milano, Milano, Italy) reviewed how differing perceptions on the severity of haemophilia B compared with haemophilia A may have an impact on clinical decision-making. Finally, Andreas Tiede (Hannover Medical School, Hannover, Germany), examined the considerations for balancing the potential risks and benefits of the currently available treatment options for haemophilia B. Although the pathophysiology of haemophilia B has been widely studied and is largely understood, continued investigation and discussion around the optimal management course and appropriate therapeutic choice is warranted. © 2014 John Wiley & Sons Ltd.

Loss of quinone reductase 2 function selectively facilitates learning behaviors.

PubMed

Benoit, Charles-Etienne; Bastianetto, Stephane; Brouillette, Jonathan; Tse, YiuChung; Boutin, Jean A; Delagrange, Philippe; Wong, TakPan; Sarret, Philippe; Quirion, Rémi

2010-09-22

High levels of reactive oxygen species (ROS) are associated with deficits in learning and memory with age as well as in Alzheimer's disease. Using DNA microarray, we demonstrated the overexpression of quinone reductase 2 (QR2) in the hippocampus in two models of learning deficits, namely the aged memory impaired rats and the scopolamine-induced amnesia model. QR2 is a cytosolic flavoprotein that catalyzes the reduction of its substrate and enhances the production of damaging activated quinone and ROS. QR2-like immunostaining is enriched in cerebral structures associated with learning behaviors, such as the hippocampal formation and the temporofrontal cortex of rat, mouse, and human brains. In cultured rat embryonic hippocampal neurons, selective inhibitors of QR2, namely S26695 and S29434, protected against menadione-induced cell death by reversing its proapoptotic action. S26695 (8 mg/kg) also significantly inhibited scopolamine-induced amnesia. Interestingly, adult QR2 knock-out mice demonstrated enhanced learning abilities in various tasks, including Morris water maze, object recognition, and rotarod performance test. Other behaviors related to anxiety (elevated plus maze), depression (forced swim), and schizophrenia (prepulse inhibition) were not affected in QR2-deficient mice. Together, these data suggest a role for QR2 in cognitive behaviors with QR2 inhibitors possibly representing a novel therapeutic strategy toward the treatment of learning deficits especially observed in the aged brain.

Heavy charged particle radiobiology: using enhanced biological effectiveness and improved beam focusing to advance cancer therapy.

PubMed

Allen, Christopher; Borak, Thomas B; Tsujii, Hirohiko; Nickoloff, Jac A

2011-06-03

Ionizing radiation causes many types of DNA damage, including base damage and single- and double-strand breaks. Photons, including X-rays and γ-rays, are the most widely used type of ionizing radiation in radiobiology experiments, and in radiation cancer therapy. Charged particles, including protons and carbon ions, are seeing increased use as an alternative therapeutic modality. Although the facilities needed to produce high energy charged particle beams are more costly than photon facilities, particle therapy has shown improved cancer survival rates, reflecting more highly focused dose distributions and more severe DNA damage to tumor cells. Despite early successes of charged particle radiotherapy, there is room for further improvement, and much remains to be learned about normal and cancer cell responses to charged particle radiation. 2011 Elsevier B.V. All rights reserved.

PHYSICAL MODEL FOR RECOGNITION TUNNELING

PubMed Central

Krstić, Predrag; Ashcroft, Brian; Lindsay, Stuart

2015-01-01

Recognition tunneling (RT) identifies target molecules trapped between tunneling electrodes functionalized with recognition molecules that serve as specific chemical linkages between the metal electrodes and the trapped target molecule. Possible applications include single molecule DNA and protein sequencing. This paper addresses several fundamental aspects of RT by multiscale theory, applying both all-atom and coarse-grained DNA models: (1) We show that the magnitude of the observed currents are consistent with the results of non-equilibrium Green's function calculations carried out on a solvated all-atom model. (2) Brownian fluctuations in hydrogen bond-lengths lead to current spikes that are similar to what is observed experimentally. (3) The frequency characteristics of these fluctuations can be used to identify the trapped molecules with a machine-learning algorithm, giving a theoretical underpinning to this new method of identifying single molecule signals. PMID:25650375

Darwin, dogs and DNA: Freshman writing about biology

NASA Astrophysics Data System (ADS)

Grant, Michael C.; Piirto, John

1994-12-01

We describe a successful interdepartmental program at a major research-oriented university that melds freshman writing with freshman biology to the significant benefit of both disciplines. Extensive, repeated feedback on individual student writing projects from two instructors, one a humanities professor, one a biology professor, appears to work synergistically so that learning by the students is significantly enhanced. Particulars derived from five years of experience with intensive, student-centered strategy are included.

Beyond Textbook Illustrations: Hand-Held Models of Ordered DNA and Protein Structures as 3D Supplements to Enhance Student Learning of Helical Biopolymers

ERIC Educational Resources Information Center

Jittivadhna, Karnyupha; Ruenwongsa, Pintip; Panijpan, Bhinyo

2010-01-01

Textbook illustrations of 3D biopolymers on printed paper, regardless of how detailed and colorful, suffer from its two-dimensionality. For beginners, computer screen display of skeletal models of biopolymers and their animation usually does not provide the at-a-glance 3D perception and details, which can be done by good hand-held models. Here, we…

Genomic Diversity and the Microenvironment as Drivers of Progression in DCIS

DTIC Science & Technology

2016-10-01

been acquiring new skills in medical image analysis and learning about the complexities of breast cancer diagnosis. How were the results...database and medical record searching at Duke, 2) Development of methods for isolating DNA from archival DCIS lesions, 3) Deep and comprehensive...on the Aim 3 results to the SPIE Medical Imaging Conference to be held in February 2017. If accepted, those will each be published in the form of a

DNA methylation as a predictor of fetal alcohol spectrum disorder.

PubMed

Lussier, Alexandre A; Morin, Alexander M; MacIsaac, Julia L; Salmon, Jenny; Weinberg, Joanne; Reynolds, James N; Pavlidis, Paul; Chudley, Albert E; Kobor, Michael S

2018-01-01

Fetal alcohol spectrum disorder (FASD) is a developmental disorder that manifests through a range of cognitive, adaptive, physiological, and neurobiological deficits resulting from prenatal alcohol exposure. Although the North American prevalence is currently estimated at 2-5%, FASD has proven difficult to identify in the absence of the overt physical features characteristic of fetal alcohol syndrome. As interventions may have the greatest impact at an early age, accurate biomarkers are needed to identify children at risk for FASD. Building on our previous work identifying distinct DNA methylation patterns in children and adolescents with FASD, we have attempted to validate these associations in a different clinical cohort and to use our DNA methylation signature to develop a possible epigenetic predictor of FASD. Genome-wide DNA methylation patterns were analyzed using the Illumina HumanMethylation450 array in the buccal epithelial cells of a cohort of 48 individuals aged 3.5-18 (24 FASD cases, 24 controls). The DNA methylation predictor of FASD was built using a stochastic gradient boosting model on our previously published dataset FASD cases and controls (GSE80261). The predictor was tested on the current dataset and an independent dataset of 48 autism spectrum disorder cases and 48 controls (GSE50759). We validated findings from our previous study that identified a DNA methylation signature of FASD, replicating the altered DNA methylation levels of 161/648 CpGs in this independent cohort, which may represent a robust signature of FASD in the epigenome. We also generated a predictive model of FASD using machine learning in a subset of our previously published cohort of 179 samples (83 FASD cases, 96 controls), which was tested in this novel cohort of 48 samples and resulted in a moderately accurate predictor of FASD status. Upon testing the algorithm in an independent cohort of individuals with autism spectrum disorder, we did not detect any bias towards autism, sex, age, or ethnicity. These findings further support the association of FASD with distinct DNA methylation patterns, while providing a possible entry point towards the development of epigenetic biomarkers of FASD.

DNA in a Tunnel: A Comfy Spot for Recognition - or -The Structure of BsoBI Complexed with DNA. What can we Learn about Function via Structure Determination and how can this be Applied to Bone or Muscle Biology?

NASA Technical Reports Server (NTRS)

vanderWoerd, Mark

2004-01-01

The structure and function of a biologically active molecule are related. To understand its function, it is necessary (but not always sufficient) to know the structure of the molecule. There are many ways of relating the molecular function with the structure. Mutation analysis can identify pertinent amino acids of an enzyme, or alternatively structure comparison of the of two similar molecules with different function may lead to understanding which parts are responsible for a functional aspect, or a series of "structural cartoons" - enzyme structure, enzyme plus substrate, enzyme with transition state analog, and enzyme with product - may give insight in the function of a molecule. As an example we will discuss the structure and function of the restriction enzyme BsoBI from Bacillus stearothemzophilus in complex with its cognate DNA. The enzyme forms a unique complex with DNA in that it completely encircles the DNA. The structure reveals the enzyme-DNA contacts, how the DNA is distorted compared with the canonical forms, and elegantly shows how two distinct DNA sequences can be recognized with the same efficiency. Based on the structure we may also propose a hypothesis how the enzymatic mechanism works. The knowledge gained thru studies such as this one can be used to alter the function by changing the molecular structure. Usually this is done by design of inhibitors specifically active against and fitting into an active site of the enzyme of choice. In the case of BsoBI one of the objectives of the study was to alter the enzyme specificity. In bone biology there are many candidates available for molecular study in order to explain, alter, or (temporarily) suspend activity. For example, the understanding of a pathway that negatively regulates bone formation may be a good target for drug design to stimulate bone formation and have good potential as the basis for new countermeasures against bone loss. In principle the same approach may aid muscle atrophy, radiation damage, immune response changes and other risks identified for long-duration Space travel.

Mobius Assembly: A versatile Golden-Gate framework towards universal DNA assembly

PubMed Central

Andreou, Andreas I.

2018-01-01

Synthetic biology builds upon the foundation of engineering principles, prompting innovation and improvement in biotechnology via a design-build-test-learn cycle. A community-wide standard in DNA assembly would enable bio-molecular engineering at the levels of predictivity and universality in design and construction that are comparable to other engineering fields. Golden Gate Assembly technology, with its robust capability to unidirectionally assemble numerous DNA fragments in a one-tube reaction, has the potential to deliver a universal standard framework for DNA assembly. While current Golden Gate Assembly frameworks (e.g. MoClo and Golden Braid) render either high cloning capacity or vector toolkit simplicity, the technology can be made more versatile—simple, streamlined, and cost/labor-efficient, without compromising capacity. Here we report the development of a new Golden Gate Assembly framework named Mobius Assembly, which combines vector toolkit simplicity with high cloning capacity. It is based on a two-level, hierarchical approach and utilizes a low-frequency cutter to reduce domestication requirements. Mobius Assembly embraces the standard overhang designs designated by MoClo, Golden Braid, and Phytobricks and is largely compatible with already available Golden Gate part libraries. In addition, dropout cassettes encoding chromogenic proteins were implemented for cost-free visible cloning screening that color-code different cloning levels. As proofs of concept, we have successfully assembled up to 16 transcriptional units of various pigmentation genes in both operon and multigene arrangements. Taken together, Mobius Assembly delivers enhanced versatility and efficiency in DNA assembly, facilitating improved standardization and automation. PMID:29293531

Comparison of diets for Largemouth and Smallmouth Bass in Eastern Lake Ontario using DNA barcoding and stable isotope analysis

PubMed Central

Holden, Jeremy; Eves, Robert; Tufts, Bruce

2017-01-01

Largemouth (LMB: Micropterus salmoides) and Smallmouth Bass (SMB: Micropterus dolomieu) are important species in the recreational fisheries of the Laurentian Great Lakes. The invasion of the Round Goby (Neogobius melanostomus) into these lakes has changed several facets of black bass biology, but there is still much to learn about the relationship between these species. Previous dietary analyses have shown Round Goby to be important prey for bass, but have been limited by low visual identification rates of dissected stomach items. Within the present study, DNA barcoding and stable isotope analysis improve prey identification and provide a more quantitative dietary analysis of adult black bass in Lake Ontario, comparing the importance of Round Goby as prey between these two species. Eighty-four LMB (406mm fork length ±4mm SEM) and two hundred sixty-four SMB (422mm ±2mm) obtained as tournament mortalities had prey identified using DNA-based methods. Round Goby was the most prevalent prey species for both predators. The diet of LMB was three times more diverse than that of SMB, which almost entirely consists of Round Goby. Our results provide further support that recent increases in the size of Lake Ontario bass are a result of Round Goby consumption, and that the effects of this dietary shift on body condition are greater for SMB. Techniques developed in this study include reverse-oriented dual priming oligonucleotides used as blocking primers for predator DNA, and an automated design approach of restriction fragment length polymorphism tests for identifying prey DNA barcodes. PMID:28771612

An investigative graduate laboratory course for teaching modern DNA techniques.

PubMed

de Lencastre, Alexandre; Thomas Torello, A; Keller, Lani C

2017-07-08

This graduate-level DNA methods laboratory course is designed to model a discovery-based research project and engages students in both traditional DNA analysis methods and modern recombinant DNA cloning techniques. In the first part of the course, students clone the Drosophila ortholog of a human disease gene of their choosing using Gateway ® cloning. In the second part of the course, students examine the expression of their gene of interest in human cell lines by reverse transcription PCR and learn how to analyze data from quantitative reverse transcription PCR (qRT-PCR) experiments. The adaptability of the Gateway ® cloning system is ideally suited for students to design and create different types of expression constructs to achieve a particular experimental goal (e.g., protein purification, expression in cell culture, and/or subcellular localization), and the genes chosen can be aligned to the research interests of the instructor and/or ongoing research in a department. Student evaluations indicate that the course fostered a genuine excitement for research and in depth knowledge of both the techniques performed and the theory behind them. Our long-term goal is to incorporate this DNA methods laboratory as the foundation for an integrated laboratory sequence for the Master of Science degree program in Molecular and Cellular Biology at Quinnipiac University, where students use the reagents and concepts they developed in this course in subsequent laboratory courses, including a protein methods and cell culture laboratory. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(4):351-359, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

Base pairing and base mis-pairing in nucleic acids

NASA Technical Reports Server (NTRS)

Wang, A. H. J.; Rich, A.

1986-01-01

In recent years we have learned that DNA is conformationally active. It can exist in a number of different stable conformations including both right-handed and left-handed forms. Using single crystal X-ray diffraction analysis we are able to discover not only additional conformations of the nucleic acids but also different types of hydrogen bonded base-base interactions. Although Watson-Crick base pairings are the predominant type of interaction in double helical DNA, they are not the only types. Recently, we have been able to examine mismatching of guanine-thymine base pairs in left-handed Z-DNA at atomic resolution (1A). A minimum amount of distortion of the sugar phosphate backbone is found in the G x T pairing in which the bases are held together by two hydrogen bonds in the wobble pairing interaction. Because of the high resolution of the analysis we can visualize water molecules which fill in to accommodate the other hydrogen bonding positions in the bases which are not used in the base-base interactions. Studies on other DNA oligomers have revealed that other types of non-Watson-Crick hydrogen bonding interactions can occur. In the structure of a DNA octamer with the sequence d(GCGTACGC) complexed to an antibiotic triostin A, it was found that the two central AT base pairs are held together by Hoogsteen rather than Watson-Crick base pairs. Similarly, the G x C base pairs at the ends are also Hoogsteen rather than Watson-Crick pairing. Hoogsteen base pairs make a modified helix which is distinct from the Watson-Crick double helix.

Dad's Snoring May Have Left Molecular Scars in Your DNA: the Emerging Role of Epigenetics in Sleep Disorders.

PubMed

Morales-Lara, Daniela; De-la-Peña, Clelia; Murillo-Rodríguez, Eric

2018-04-01

The sleep-wake cycle is a biological phenomena under the orchestration of neurophysiological, neurochemical, neuroanatomical, and genetical mechanisms. Moreover, homeostatic and circadian processes participate in the regulation of sleep across the light-dark period. Further complexity of the understanding of the genesis of sleep engages disturbances which have been characterized and classified in a variety of sleep-wake cycle disorders. The most prominent sleep alterations include insomnia as well as excessive daytime sleepiness. On the other side, several human diseases have been linked with direct changes in DNA, such as chromatin configuration, genomic imprinting, DNA methylation, histone modifications (acetylation, methylation, ubiquitylation or sumoylation, etc.), and activating RNA molecules that are transcribed from DNA but not translated into proteins. Epigenetic theories primarily emphasize the interaction between the environment and gene expression. According to these approaches, the environment to which mammals are exposed has a significant role in determining the epigenetic modifications occurring in chromosomes that ultimately would influence not only development but also the descendants' physiology and behavior. Thus, what makes epigenetics intriguing is that, unlike genetic variation, modifications in DNA are altered directly by the environment and, in some cases, these epigenetic changes may be inherited by future generations. Thus, it is likely that epigenetic phenomena might contribute to the homeostatic and/or circadian control of sleep and, possibly, have an undescribed link with sleep disorders. An exciting new horizon of research is arising between sleep and epigenetics since it represents the relevance of the study of how the genome learns from its experiences and modulates behavior, including sleep.

Comparison of diets for Largemouth and Smallmouth Bass in Eastern Lake Ontario using DNA barcoding and stable isotope analysis.

PubMed

Nelson, Erich J H; Holden, Jeremy; Eves, Robert; Tufts, Bruce

2017-01-01

Largemouth (LMB: Micropterus salmoides) and Smallmouth Bass (SMB: Micropterus dolomieu) are important species in the recreational fisheries of the Laurentian Great Lakes. The invasion of the Round Goby (Neogobius melanostomus) into these lakes has changed several facets of black bass biology, but there is still much to learn about the relationship between these species. Previous dietary analyses have shown Round Goby to be important prey for bass, but have been limited by low visual identification rates of dissected stomach items. Within the present study, DNA barcoding and stable isotope analysis improve prey identification and provide a more quantitative dietary analysis of adult black bass in Lake Ontario, comparing the importance of Round Goby as prey between these two species. Eighty-four LMB (406mm fork length ±4mm SEM) and two hundred sixty-four SMB (422mm ±2mm) obtained as tournament mortalities had prey identified using DNA-based methods. Round Goby was the most prevalent prey species for both predators. The diet of LMB was three times more diverse than that of SMB, which almost entirely consists of Round Goby. Our results provide further support that recent increases in the size of Lake Ontario bass are a result of Round Goby consumption, and that the effects of this dietary shift on body condition are greater for SMB. Techniques developed in this study include reverse-oriented dual priming oligonucleotides used as blocking primers for predator DNA, and an automated design approach of restriction fragment length polymorphism tests for identifying prey DNA barcodes.

DNA Modification Study of Major Depressive Disorder: Beyond Locus-by-Locus Comparisons

PubMed Central

Oh, Gabriel; Wang, Sun-Chong; Pal, Mrinal; Chen, Zheng Fei; Khare, Tarang; Tochigi, Mamoru; Ng, Catherine; Yang, Yeqing A.; Kwan, Andrew; Kaminsky, Zachary A.; Mill, Jonathan; Gunasinghe, Cerisse; Tackett, Jennifer L.; Gottesman, Irving I.; Willemsen, Gonneke; de Geus, Eco J.C.; Vink, Jacqueline M.; Slagboom, P. Eline; Wray, Naomi R.; Heath, Andrew C.; Montgomery, Grant W.; Turecki, Gustavo; Martin, Nicholas G.; Boomsma, Dorret I.; McGuffin, Peter; Kustra, Rafal; Petronis, Art

2014-01-01

Background Major depressive disorder (MDD) exhibits numerous clinical and molecular features that are consistent with putative epigenetic misregulation. Despite growing interest in epigenetic studies of psychiatric diseases, the methodologies guiding such studies have not been well defined. Methods We performed DNA modification analysis in white blood cells from monozygotic twins discordant for MDD, in brain prefrontal cortex, and germline (sperm) samples from affected individuals and control subjects (total N = 304) using 8.1K CpG island microarrays and fine mapping. In addition to the traditional locus-by-locus comparisons, we explored the potential of new analytical approaches in epigenomic studies. Results In the microarray experiment, we detected a number of nominally significant DNA modification differences in MDD and validated selected targets using bisulfite pyrosequencing. Some MDD epigenetic changes, however, overlapped across brain, blood, and sperm more often than expected by chance. We also demonstrated that stratification for disease severity and age may increase the statistical power of epimutation detection. Finally, a series of new analytical approaches, such as DNA modification networks and machine-learning algorithms using binary and quantitative depression phenotypes, provided additional insights on the epigenetic contributions to MDD. Conclusions Mapping epigenetic differences in MDD (and other psychiatric diseases) is a complex task. However, combining traditional and innovative analytical strategies may lead to identification of disease-specific etiopathogenic epimutations. PMID:25108803

Cyclin A2 promotes DNA repair in the brain during both development and aging.

PubMed

Gygli, Patrick E; Chang, Joshua C; Gokozan, Hamza N; Catacutan, Fay P; Schmidt, Theresa A; Kaya, Behiye; Goksel, Mustafa; Baig, Faisal S; Chen, Shannon; Griveau, Amelie; Michowski, Wojciech; Wong, Michael; Palanichamy, Kamalakannan; Sicinski, Piotr; Nelson, Randy J; Czeisler, Catherine; Otero, José J

2016-07-01

Various stem cell niches of the brain have differential requirements for Cyclin A2. Cyclin A2 loss results in marked cerebellar dysmorphia, whereas forebrain growth is retarded during early embryonic development yet achieves normal size at birth. To understand the differential requirements of distinct brain regions for Cyclin A2, we utilized neuroanatomical, transgenic mouse, and mathematical modeling techniques to generate testable hypotheses that provide insight into how Cyclin A2 loss results in compensatory forebrain growth during late embryonic development. Using unbiased measurements of the forebrain stem cell niche, we parameterized a mathematical model whereby logistic growth instructs progenitor cells as to the cell-types of their progeny. Our data was consistent with prior findings that progenitors proliferate along an auto-inhibitory growth curve. The growth retardation inCCNA2-null brains corresponded to cell cycle lengthening, imposing a developmental delay. We hypothesized that Cyclin A2 regulates DNA repair and that CCNA2-null progenitors thus experienced lengthened cell cycle. We demonstrate that CCNA2-null progenitors suffer abnormal DNA repair, and implicate Cyclin A2 in double-strand break repair. Cyclin A2's DNA repair functions are conserved among cell lines, neural progenitors, and hippocampal neurons. We further demonstrate that neuronal CCNA2 ablation results in learning and memory deficits in aged mice.

PDNAsite: Identification of DNA-binding Site from Protein Sequence by Incorporating Spatial and Sequence Context

PubMed Central

Zhou, Jiyun; Xu, Ruifeng; He, Yulan; Lu, Qin; Wang, Hongpeng; Kong, Bing

2016-01-01

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community. PMID:27282833

DNA modification study of major depressive disorder: beyond locus-by-locus comparisons.

PubMed

Oh, Gabriel; Wang, Sun-Chong; Pal, Mrinal; Chen, Zheng Fei; Khare, Tarang; Tochigi, Mamoru; Ng, Catherine; Yang, Yeqing A; Kwan, Andrew; Kaminsky, Zachary A; Mill, Jonathan; Gunasinghe, Cerisse; Tackett, Jennifer L; Gottesman, Irving I; Willemsen, Gonneke; de Geus, Eco J C; Vink, Jacqueline M; Slagboom, P Eline; Wray, Naomi R; Heath, Andrew C; Montgomery, Grant W; Turecki, Gustavo; Martin, Nicholas G; Boomsma, Dorret I; McGuffin, Peter; Kustra, Rafal; Petronis, Art

2015-02-01

Major depressive disorder (MDD) exhibits numerous clinical and molecular features that are consistent with putative epigenetic misregulation. Despite growing interest in epigenetic studies of psychiatric diseases, the methodologies guiding such studies have not been well defined. We performed DNA modification analysis in white blood cells from monozygotic twins discordant for MDD, in brain prefrontal cortex, and germline (sperm) samples from affected individuals and control subjects (total N = 304) using 8.1K CpG island microarrays and fine mapping. In addition to the traditional locus-by-locus comparisons, we explored the potential of new analytical approaches in epigenomic studies. In the microarray experiment, we detected a number of nominally significant DNA modification differences in MDD and validated selected targets using bisulfite pyrosequencing. Some MDD epigenetic changes, however, overlapped across brain, blood, and sperm more often than expected by chance. We also demonstrated that stratification for disease severity and age may increase the statistical power of epimutation detection. Finally, a series of new analytical approaches, such as DNA modification networks and machine-learning algorithms using binary and quantitative depression phenotypes, provided additional insights on the epigenetic contributions to MDD. Mapping epigenetic differences in MDD (and other psychiatric diseases) is a complex task. However, combining traditional and innovative analytical strategies may lead to identification of disease-specific etiopathogenic epimutations. Copyright © 2015 Society of Biological Psychiatry. All rights reserved.

Identification and Characterization of the V(D)J Recombination Activating Gene 1 in Long-Term Memory of Context Fear Conditioning

PubMed Central

Castro-Pérez, Edgardo; Soto-Soto, Emilio; Pérez-Carambot, Marizabeth; Dionisio-Santos, Dawling; Saied-Santiago, Kristian; Ortiz-Zuazaga, Humberto G.; Peña de Ortiz, Sandra

2016-01-01

An increasing body of evidence suggests that mechanisms related to the introduction and repair of DNA double strand breaks (DSBs) may be associated with long-term memory (LTM) processes. Previous studies from our group suggested that factors known to function in DNA recombination/repair machineries, such as DNA ligases, polymerases, and DNA endonucleases, play a role in LTM. Here we report data using C57BL/6 mice showing that the V(D)J recombination-activating gene 1 (RAG1), which encodes a factor that introduces DSBs in immunoglobulin and T-cell receptor genes, is induced in the amygdala, but not in the hippocampus, after context fear conditioning. Amygdalar induction of RAG1 mRNA, measured by real-time PCR, was not observed in context-only or shock-only controls, suggesting that the context fear conditioning response is related to associative learning processes. Furthermore, double immunofluorescence studies demonstrated the neuronal localization of RAG1 protein in amygdalar sections prepared after perfusion and fixation. In functional studies, intra-amygdalar injections of RAG1 gapmer antisense oligonucleotides, given 1 h prior to conditioning, resulted in amygdalar knockdown of RAG1 mRNA and a significant impairment in LTM, tested 24 h after training. Overall, these findings suggest that the V(D)J recombination-activating gene 1, RAG1, may play a role in LTM consolidation. PMID:26843989

Student learning outcomes and attitudes when biotechnology lab partners are of different academic levels.

PubMed

Miller, Heather B; Witherow, D Scott; Carson, Susan

2012-01-01

The North Carolina State University Biotechnology Program offers laboratory-intensive courses to both undergraduate and graduate students. In "Manipulation and Expression of Recombinant DNA," students are separated into undergraduate and graduate sections for the laboratory, but not the lecture, component. Evidence has shown that students prefer pairing with someone of the same academic level. However, retention of main ideas in peer learning environments has been shown to be greater when partners have dissimilar abilities. Therefore, we tested the hypothesis that there will be enhanced student learning when lab partners are of different academic levels. We found that learning outcomes were met by both levels of student, regardless of pairing. Average undergraduate grades on every assessment method increased when undergraduates were paired with graduate students. Many of the average graduate student grades also increased modestly when graduate students were paired with undergraduates. Attitudes toward working with partners dramatically shifted toward favoring working with students of different academic levels. This work suggests that offering dual-level courses in which different-level partnerships are created does not inhibit learning by students of different academic levels. This format is useful for institutions that wish to offer "boutique" courses in which student enrollment may be low, but specialized equipment and faculty expertise are needed.

Student Learning Outcomes and Attitudes When Biotechnology Lab Partners Are of Different Academic Levels

PubMed Central

Miller, Heather B.; Witherow, D. Scott; Carson, Susan

2012-01-01

The North Carolina State University Biotechnology Program offers laboratory-intensive courses to both undergraduate and graduate students. In “Manipulation and Expression of Recombinant DNA,” students are separated into undergraduate and graduate sections for the laboratory, but not the lecture, component. Evidence has shown that students prefer pairing with someone of the same academic level. However, retention of main ideas in peer learning environments has been shown to be greater when partners have dissimilar abilities. Therefore, we tested the hypothesis that there will be enhanced student learning when lab partners are of different academic levels. We found that learning outcomes were met by both levels of student, regardless of pairing. Average undergraduate grades on every assessment method increased when undergraduates were paired with graduate students. Many of the average graduate student grades also increased modestly when graduate students were paired with undergraduates. Attitudes toward working with partners dramatically shifted toward favoring working with students of different academic levels. This work suggests that offering dual-level courses in which different-level partnerships are created does not inhibit learning by students of different academic levels. This format is useful for institutions that wish to offer “boutique” courses in which student enrollment may be low, but specialized equipment and faculty expertise are needed. PMID:22949428

Objective detection of apoptosis in rat renal tissue sections using light microscopy and free image analysis software with subsequent machine learning: Detection of apoptosis in renal tissue.

PubMed

Macedo, Nayana Damiani; Buzin, Aline Rodrigues; de Araujo, Isabela Bastos Binotti Abreu; Nogueira, Breno Valentim; de Andrade, Tadeu Uggere; Endringer, Denise Coutinho; Lenz, Dominik

2017-02-01

The current study proposes an automated machine learning approach for the quantification of cells in cell death pathways according to DNA fragmentation. A total of 17 images of kidney histological slide samples from male Wistar rats were used. The slides were photographed using an Axio Zeiss Vert.A1 microscope with a 40x objective lens coupled with an Axio Cam MRC Zeiss camera and Zen 2012 software. The images were analyzed using CellProfiler (version 2.1.1) and CellProfiler Analyst open-source software. Out of the 10,378 objects, 4970 (47,9%) were identified as TUNEL positive, and 5408 (52,1%) were identified as TUNEL negative. On average, the sensitivity and specificity values of the machine learning approach were 0.80 and 0.77, respectively. Image cytometry provides a quantitative analytical alternative to the more traditional qualitative methods more commonly used in studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

DNA Methylation and Transcription Patterns in Intestinal Epithelial Cells From Pediatric Patients With Inflammatory Bowel Diseases Differentiate Disease Subtypes and Associate With Outcome.

PubMed

Howell, Kate Joanne; Kraiczy, Judith; Nayak, Komal M; Gasparetto, Marco; Ross, Alexander; Lee, Claire; Mak, Tim N; Koo, Bon-Kyoung; Kumar, Nitin; Lawley, Trevor; Sinha, Anupam; Rosenstiel, Philip; Heuschkel, Robert; Stegle, Oliver; Zilbauer, Matthias

2018-02-01

We analyzed DNA methylation patterns and transcriptomes of primary intestinal epithelial cells (IEC) of children newly diagnosed with inflammatory bowel diseases (IBD) to learn more about pathogenesis. We obtained mucosal biopsies (N = 236) collected from terminal ileum and ascending and sigmoid colons of children (median age 13 years) newly diagnosed with IBD (43 with Crohn's disease [CD], 23 with ulcerative colitis [UC]), and 30 children without IBD (controls). Patients were recruited and managed at a hospital in the United Kingdom from 2013 through 2016. We also obtained biopsies collected at later stages from a subset of patients. IECs were purified and analyzed for genome-wide DNA methylation patterns and gene expression profiles. Adjacent microbiota were isolated from biopsies and analyzed by 16S gene sequencing. We generated intestinal organoid cultures from a subset of samples and genome-wide DNA methylation analysis was performed. We found gut segment-specific differences in DNA methylation and transcription profiles of IECs from children with IBD vs controls; some were independent of mucosal inflammation. Changes in gut microbiota between IBD and control groups were not as large and were difficult to assess because of large amounts of intra-individual variation. Only IECs from patients with CD had changes in DNA methylation and transcription patterns in terminal ileum epithelium, compared with controls. Colon epithelium from patients with CD and from patients with ulcerative colitis had distinct changes in DNA methylation and transcription patterns, compared with controls. In IECs from patients with IBD, changes in DNA methylation, compared with controls, were stable over time and were partially retained in ex-vivo organoid cultures. Statistical analyses of epithelial cell profiles allowed us to distinguish children with CD or UC from controls; profiles correlated with disease outcome parameters, such as the requirement for treatment with biologic agents. We identified specific changes in DNA methylation and transcriptome patterns in IECs from pediatric patients with IBD compared with controls. These data indicate that IECs undergo changes during IBD development and could be involved in pathogenesis. Further analyses of primary IECs from patients with IBD could improve our understanding of the large variations in disease progression and outcomes. Copyright © 2018 AGA Institute. Published by Elsevier Inc. All rights reserved.

Assessing host-specificity of Escherichia coli using a supervised learning logic-regression-based analysis of single nucleotide polymorphisms in intergenic regions.

PubMed

Zhi, Shuai; Li, Qiaozhi; Yasui, Yutaka; Edge, Thomas; Topp, Edward; Neumann, Norman F

2015-11-01

Host specificity in E. coli is widely debated. Herein, we used supervised learning logic-regression-based analysis of intergenic DNA sequence variability in E. coli in an attempt to identify single nucleotide polymorphism (SNP) biomarkers of E. coli that are associated with natural selection and evolution toward host specificity. Seven-hundred and eighty strains of E. coli were isolated from 15 different animal hosts. We utilized logic regression for analyzing DNA sequence data of three intergenic regions (flanked by the genes uspC-flhDC, csgBAC-csgDEFG, and asnS-ompF) to identify genetic biomarkers that could potentially discriminate E. coli based on host sources. Across 15 different animal hosts, logic regression successfully discriminated E. coli based on animal host source with relatively high specificity (i.e., among the samples of the non-target animal host, the proportion that correctly did not have the host-specific marker pattern) and sensitivity (i.e., among the samples from a given animal host, the proportion that correctly had the host-specific marker pattern), even after fivefold cross validation. Permutation tests confirmed that for most animals, host specific intergenic biomarkers identified by logic regression in E. coli were significantly associated with animal host source. The highest level of biomarker sensitivity was observed in deer isolates, with 82% of all deer E. coli isolates displaying a unique SNP pattern that was 98% specific to deer. Fifty-three percent of human isolates displayed a unique biomarker pattern that was 98% specific to humans. Twenty-nine percent of cattle isolates displayed a unique biomarker that was 97% specific to cattle. Interestingly, even within a related host group (i.e., Family: Canidae [domestic dogs and coyotes]), highly specific SNP biomarkers (98% and 99% specificity for dog and coyotes, respectively) were observed, with 21% of dog E. coli isolates displaying a unique dog biomarker and 61% of coyote isolates displaying a unique coyote biomarker. Application of a supervised learning method, such as logic regression, to DNA sequence analysis at certain intergenic regions demonstrates that some E. coli strains may evolve to become host-specific. Copyright © 2015 Elsevier Inc. All rights reserved.

Challenging the Science Curriculum Paradigm: Teaching Primary Children Atomic-Molecular Theory

NASA Astrophysics Data System (ADS)

Haeusler, Carole; Donovan, Jennifer

2017-11-01

Solutions to global issues demand the involvement of scientists, yet concern exists about retention rates in science as students pass through school into University. Young children are curious about science, yet are considered incapable of grappling with abstract and microscopic concepts such as atoms, sub-atomic particles, molecules and DNA. School curricula for primary (elementary) aged children reflect this by their limitation to examining only what phenomena are without providing any explanatory frameworks for how or why they occur. This research challenges the assumption that atomic-molecular theory is too difficult for young children, examining new ways of introducing atomic theory to 9 year olds and seeks to verify their efficacy in producing genuine learning in the participants. Early results in three cases in different schools indicate these novel methods fostered further interest in science, allowed diverse children to engage and learn aspects of atomic theory, and satisfied the children's desire for intellectual challenge. Learning exceeded expectations as demonstrated in the post-interview findings. Learning was also remarkably robust, as demonstrated in two schools 8 weeks after the intervention and, in one school, 1 year after their first exposure to ideas about atoms, elements and molecules.

Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data.

PubMed

Shah, M; Marchand, M; Corbeil, J

2012-01-01

One of the objectives of designing feature selection learning algorithms is to obtain classifiers that depend on a small number of attributes and have verifiable future performance guarantees. There are few, if any, approaches that successfully address the two goals simultaneously. To the best of our knowledge, such algorithms that give theoretical bounds on the future performance have not been proposed so far in the context of the classification of gene expression data. In this work, we investigate the premise of learning a conjunction (or disjunction) of decision stumps in Occam's Razor, Sample Compression, and PAC-Bayes learning settings for identifying a small subset of attributes that can be used to perform reliable classification tasks. We apply the proposed approaches for gene identification from DNA microarray data and compare our results to those of the well-known successful approaches proposed for the task. We show that our algorithm not only finds hypotheses with a much smaller number of genes while giving competitive classification accuracy but also having tight risk guarantees on future performance, unlike other approaches. The proposed approaches are general and extensible in terms of both designing novel algorithms and application to other domains.

Cancer Biotechnology | Center for Cancer Research

Cancer.gov

Biotechnology advances continue to underscore the need to educate NCI fellows in new methodologies. The Cancer Biotechnology course will be held on the NCI-Frederick campus on January 29, 2016 (Bldg. 549, Main Auditorium) and the course will be repeated on the Bethesda campus on February 9, 2016 (Natcher Balcony C). The latest advances in DNA, protein and image analysis will be presented. Clinical and postdoctoral fellows who want to learn about new biotechnology advances are encouraged to attend this course.

Impaired clearance of neutrophils extracellular trap (NET) may induce detrimental tissular effect.

PubMed

Anjos, Paula M F; Fagundes-Netto, Fernanda S; Volpe, Caroline M O; Nogueira-Machado, Jose A

2014-01-01

Neutrophils Extracellular Trap (NET) is composed of nuclear chromatin with hyper segmentation of nuclear lobes, citrullination of histone-associated DNA and mixing with cytoplasmic proteins including the enzyme myeloperoxidase. It is believed that neutrophils trap can kill microorganisms and constitutes a new form of innate defense. However, in some conditions, NET formation may be detrimental to the organism due to its association with autoantibody formation. Thus, NETs can be beneficial or detrimental depending of the DNA clearance recent registered patents describing the processes, products, methods and therapeutic indications of the neutrophil extracellular trap (NET) phenomenon have been reported. The patents US8710039; EP2465536; EP2651440; US20130302345; US20140099648; US20130183662; WO2012166611; and RU2463349C2, related to NETosis, suggest an association between NET formation and autoimmunity. However, its function is still not fully understood. Some parasites have learned to escape from NET using nucleases. NET persistence could be due to a possible enzymatic inhibition as suggested in Grabar´s theory for explaining the induction of physiologic or pathologic autoantibodies. In the present mini-review NET persistence due to impairment in the homeostasis clearance of DNA is discussed.

Toward a new history and geography of human genes informed by ancient DNA.

PubMed

Pickrell, Joseph K; Reich, David

2014-09-01

Genetic information contains a record of the history of our species, and technological advances have transformed our ability to access this record. Many studies have used genome-wide data from populations today to learn about the peopling of the globe and subsequent adaptation to local conditions. Implicit in this research is the assumption that the geographic locations of people today are informative about the geographic locations of their ancestors in the distant past. However, it is now clear that long-range migration, admixture, and population replacement subsequent to the initial out-of-Africa expansion have altered the genetic structure of most of the world's human populations. In light of this we argue that it is time to critically reevaluate current models of the peopling of the globe, as well as the importance of natural selection in determining the geographic distribution of phenotypes. We specifically highlight the transformative potential of ancient DNA. By accessing the genetic make-up of populations living at archaeologically known times and places, ancient DNA makes it possible to directly track migrations and responses to natural selection. Copyright © 2014 Elsevier Ltd. All rights reserved.

Alteration of Gene Expression, DNA Methylation, and Histone Methylation in Free Radical Scavenging Networks in Adult Mouse Hippocampus following Fetal Alcohol Exposure.

PubMed

Chater-Diehl, Eric J; Laufer, Benjamin I; Castellani, Christina A; Alberry, Bonnie L; Singh, Shiva M

2016-01-01

The molecular basis of Fetal Alcohol Spectrum Disorders (FASD) is poorly understood; however, epigenetic and gene expression changes have been implicated. We have developed a mouse model of FASD characterized by learning and memory impairment and persistent gene expression changes. Epigenetic marks may maintain expression changes over a mouse's lifetime, an area few have explored. Here, mice were injected with saline or ethanol on postnatal days four and seven. At 70 days of age gene expression microarray, methylated DNA immunoprecipitation microarray, H3K4me3 and H3K27me3 chromatin immunoprecipitation microarray were performed. Following extensive pathway analysis of the affected genes, we identified the top affected gene expression pathway as "Free radical scavenging". We confirmed six of these changes by droplet digital PCR including the caspase Casp3 and Wnt transcription factor Tcf7l2. The top pathway for all methylation-affected genes was "Peroxisome biogenesis"; we confirmed differential DNA methylation in the Acca1 thiolase promoter. Altered methylation and gene expression in oxidative stress pathways in the adult hippocampus suggests a novel interface between epigenetic and oxidative stress mechanisms in FASD.

SD-MSAEs: Promoter recognition in human genome based on deep feature extraction.

PubMed

Xu, Wenxuan; Zhang, Li; Lu, Yaping

2016-06-01

The prediction and recognition of promoter in human genome play an important role in DNA sequence analysis. Entropy, in Shannon sense, of information theory is a multiple utility in bioinformatic details analysis. The relative entropy estimator methods based on statistical divergence (SD) are used to extract meaningful features to distinguish different regions of DNA sequences. In this paper, we choose context feature and use a set of methods of SD to select the most effective n-mers distinguishing promoter regions from other DNA regions in human genome. Extracted from the total possible combinations of n-mers, we can get four sparse distributions based on promoter and non-promoters training samples. The informative n-mers are selected by optimizing the differentiating extents of these distributions. Specially, we combine the advantage of statistical divergence and multiple sparse auto-encoders (MSAEs) in deep learning to extract deep feature for promoter recognition. And then we apply multiple SVMs and a decision model to construct a human promoter recognition method called SD-MSAEs. Framework is flexible that it can integrate new feature extraction or new classification models freely. Experimental results show that our method has high sensitivity and specificity. Copyright © 2016 Elsevier Inc. All rights reserved.

Light-driven enzymatic catalysis of DNA repair: a review of recent biophysical studies on photolyase.

PubMed

Weber, Stefan

2005-02-25

More than 50 years ago, initial experiments on enzymatic photorepair of ultraviolet (UV)-damaged DNA were reported [Proc. Natl. Acad. Sci. U. S. A. 35 (1949) 73]. Soon after this discovery, it was recognized that one enzyme, photolyase, is able to repair UV-induced DNA lesions by effectively reversing their formation using blue light. The enzymatic process named DNA photoreactivation depends on a non-covalently bound cofactor, flavin adenine dinucleotide (FAD). Flavins are ubiquitous redox-active catalysts in one- and two-electron transfer reactions of numerous biological processes. However, in the case of photolyase, not only the ground-state redox properties of the FAD cofactor are exploited but also, and perhaps more importantly, its excited-state properties. In the catalytically active, fully reduced redox form, the FAD absorbs in the blue and near-UV ranges of visible light. Although there is no direct experimental evidence, it appears generally accepted that starting from the excited singlet state, the chromophore initiates a reductive cleavage of the two major DNA photodamages, cyclobutane pyrimidine dimers and (6-4) photoproducts, by short-distance electron transfer to the DNA lesion. Back electron transfer from the repaired DNA segment is believed to eventually restore the initial redox states of the cofactor and the DNA nucleobases, resulting in an overall reaction with net-zero exchanged electrons. Thus, the entire process represents a true catalytic cycle. Many biochemical and biophysical studies have been carried out to unravel the fundamentals of this unique mode of action. The work has culminated in the elucidation of the three-dimensional structure of the enzyme in 1995 that revealed remarkable details, such as the FAD-cofactor arrangement in an unusual U-shaped configuration. With the crystal structure of the enzyme at hand, research on photolyases did not come to an end but, for good reason, intensified: the geometrical structure of the enzyme alone is not sufficient to fully understand the enzyme's action on UV-damaged DNA. Much effort has therefore been invested to learn more about, for example, the geometry of the enzyme-substrate complex, and the mechanism and pathways of intra-enzyme and enzyme <-->DNA electron transfer. Many of the key results from biochemical and molecular biology characterizations of the enzyme or the enzyme-substrate complex have been summarized in a number of reviews. Complementary to these articles, this review focuses on recent biophysical studies of photoreactivation comprising work performed from the early 1990s until the present.

Using mobile sequencers in an academic classroom

PubMed Central

Zaaijer, Sophie; Erlich, Yaniv

2016-01-01

The advent of mobile DNA sequencers has made it possible to generate DNA sequencing data outside of laboratories and genome centers. Here, we report our experience of using the MinION, a mobile sequencer, in a 13-week academic course for undergraduate and graduate students. The course consisted of theoretical sessions that presented fundamental topics in genomics and several applied hackathon sessions. In these hackathons, the students used MinION sequencers to generate and analyze their own data and gain hands-on experience in the topics discussed in the theoretical classes. The manuscript describes the structure of our class, the educational material, and the lessons we learned in the process. We hope that the knowledge and material presented here will provide the community with useful tools to help educate future generations of genome scientists. DOI: http://dx.doi.org/10.7554/eLife.14258.001 PMID:27054412

High incidence of HPV-associated head and neck cancers in FA deficient mice is associated with E7's induction of DNA damage through its inactivation of pocket proteins.

PubMed

Park, Jung Wook; Shin, Myeong-Kyun; Pitot, Henry C; Lambert, Paul F

2013-01-01

Fanconi anemia (FA) patients are highly susceptible to solid tumors at multiple anatomical sites including head and neck region. A subset of head and neck cancers (HNCs) is associated with 'high-risk' HPVs, particularly HPV16. However, the correlation between HPV oncogenes and cancers in FA patients is still unclear. We previously learned that FA deficiency in mice predisposes HPV16 E7 transgenic mice to HNCs. To address HPV16 E6's oncogenic potential under FA deficiency in HNCs, we utilized HPV16 E6-transgenic mice (K14E6) and HPV16 E6/E7-bi-transgenic mice (K14E6E7) on genetic backgrounds sufficient or deficient for one of the fanc genes, fancD2 and monitored their susceptibility to HNCs. K14E6 mice failed to develop tumor. However, E6 and fancD2-deficiency accelerated E7-driven tumor development in K14E6E7 mice. The increased tumor incidence was more correlated with E7-driven DNA damage than proliferation. We also found that deficiency of pocket proteins, pRb, p107, and p130 that are well-established targets of E7, could recapitulate E7's induction of DNA damage. Our findings support the hypothesis that E7 induces HPV-associated HNCs by promoting DNA damage through the inactivation of pocket proteins, which explains why a deficiency in DNA damage repair would increase susceptibility to E7-driven cancer. Our results further demonstrate the unexpected finding that FA deficiency does not predispose E6 transgenic mice to HNCs, indicating a specificity in the synergy between FA deficiency and HPV oncogenes in causing HNCs.

The association between dopamine receptor (DRD4) gene polymorphisms and second language learning style and behavioral variability in undergraduate students in Turkey.

PubMed

Maras Atabay, Meltem; Safi Oz, Zehra; Kurtman, Elvan

2014-08-01

The dopamine D4 receptor gene (DRD4) encodes a receptor for dopamine, a chemical messenger used in the brain. One variant of the DRD4 gene, the 7R allele, is believed to be associated with attention deficit hyperactivity disorder (ADHD). The aim of this study was to investigate the relationships between repeat polymorphisms in dopamine DRD4 and second language learning styles such as visual (seeing), tactile (touching), auditory (hearing), kinesthetic (moving) and group/individual learning styles, as well as the relationships among DRD4 gene polymorphisms and ADHD in undergraduate students. A total of 227 students between the ages of 17-21 years were evaluated using the Wender Utah rating scale and DSM-IV diagnostic criteria for ADHD. Additionally, Reid's perceptual learning style questionnaire for second language learning style was applied. In addition, these students were evaluated for social distress factors using the list of Threatening Events (TLE); having had no TLE, having had just one TLE or having had two or more TLEs within the previous 6 months before the interview. For DRD4 gene polymorphisms, DNA was extracted from whole blood using the standard phenol/chloroform method and genotyped using polymerase chain reaction. Second language learners with the DRD4.7+ repeats showed kinaesthetic and auditory learning styles, while students with DRD4.7-repeats showed visual, tactile and group learning, and also preferred the more visual learning styles [Formula: see text]. We also demonstrated that the DRD4 polymorphism significantly affected the risk effect conferred by an increasing level of exposure to TLE.

Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

PubMed

Haque, M Muksitul; Holder, Lawrence B; Skinner, Michael K

2015-01-01

Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp) termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome-wide set of potential epimutations that can be used to facilitate identification of epigenetic diagnostics for ancestral environmental exposures and disease susceptibility.

LMethyR-SVM: Predict Human Enhancers Using Low Methylated Regions based on Weighted Support Vector Machines.

PubMed

Xu, Jingting; Hu, Hong; Dai, Yang

The identification of enhancers is a challenging task. Various types of epigenetic information including histone modification have been utilized in the construction of enhancer prediction models based on a diverse panel of machine learning schemes. However, DNA methylation profiles generated from the whole genome bisulfite sequencing (WGBS) have not been fully explored for their potential in enhancer prediction despite the fact that low methylated regions (LMRs) have been implied to be distal active regulatory regions. In this work, we propose a prediction framework, LMethyR-SVM, using LMRs identified from cell-type-specific WGBS DNA methylation profiles and a weighted support vector machine learning framework. In LMethyR-SVM, the set of cell-type-specific LMRs is further divided into three sets: reliable positive, like positive and likely negative, according to their resemblance to a small set of experimentally validated enhancers in the VISTA database based on an estimated non-parametric density distribution. Then, the prediction model is obtained by solving a weighted support vector machine. We demonstrate the performance of LMethyR-SVM by using the WGBS DNA methylation profiles derived from the human embryonic stem cell type (H1) and the fetal lung fibroblast cell type (IMR90). The predicted enhancers are highly conserved with a reasonable validation rate based on a set of commonly used positive markers including transcription factors, p300 binding and DNase-I hypersensitive sites. In addition, we show evidence that the large fraction of the LMethyR-SVM predicted enhancers are not predicted by ChromHMM in H1 cell type and they are more enriched for the FANTOM5 enhancers. Our work suggests that low methylated regions detected from the WGBS data are useful as complementary resources to histone modification marks in developing models for the prediction of cell-type-specific enhancers.

Prognostication of patients with clear cell renal cell carcinomas based on quantification of DNA methylation levels of CpG island methylator phenotype marker genes.

PubMed

Tian, Ying; Arai, Eri; Gotoh, Masahiro; Komiyama, Motokiyo; Fujimoto, Hiroyuki; Kanai, Yae

2014-10-20

The CpG island methylator phenotype (CIMP) of clear cell renal cell carcinomas (ccRCCs) is characterized by accumulation of DNA methylation at CpG islands and poorer patient outcome. The aim of this study was to establish criteria for prognostication of patients with ccRCCs using the ccRCC-specific CIMP marker genes. DNA methylation levels at 299 CpG sites in the 14 CIMP marker genes were evaluated quantitatively in tissue specimens of 88 CIMP-negative and 14 CIMP-positive ccRCCs in a learning cohort using the MassARRAY system. An additional 100 ccRCCs were also analyzed as a validation cohort. Receiver operating characteristic curve analysis showed that area under the curve values for the 23 CpG units including the 32 CpG sites in the 7 CIMP-marker genes, i.e. FAM150A, ZNF540, ZNF671, ZNF154, PRAC, TRH and SLC13A5, for discrimination of CIMP-positive from CIMP-negative ccRCCs were larger than 0.95. Criteria combining the 23 CpG units discriminated CIMP-positive from CIMP-negative ccRCCs with 100% sensitivity and specificity in the learning cohort. Cancer-free and overall survival rates of patients with CIMP-positive ccRCCs diagnosed using the criteria combining the 23 CpG units in a validation cohort were significantly lower than those of patients with CIMP-negative ccRCCs (P = 1.41 × 10-5 and 2.43 × 10-13, respectively). Patients with CIMP-positive ccRCCs in the validation cohort had a higher likelihood of disease-related death (hazard ratio, 75.8; 95% confidence interval, 7.81 to 735; P = 1.89 × 10-4) than those with CIMP-negative ccRCCs. The established criteria are able to reproducibly diagnose CIMP-positive ccRCCs and may be useful for personalized medicine for patients with ccRCCs.

A Pyrosequencing-Based Assay for the Rapid Detection of the 22q11.2 Deletion in DNA from Buccal and Dried Blood Spot Samples

PubMed Central

Koontz, Deborah; Baecher, Kirsten; Kobrynski, Lisa; Nikolova, Stanimila; Gallagher, Margaret

2015-01-01

The 22q11.2 deletion syndrome is one of the most common deletion syndromes in newborns. Some affected newborns may be diagnosed shortly after birth because of the presence of heart defects, palatal defects, or severe immune deficiencies. However, diagnosis is often delayed in patients presenting with other associated conditions that would benefit from early recognition and treatment, such as speech delays, learning difficulties, and schizophrenia. Fluorescence in situ hybridization (FISH) is the gold standard for deletion detection, but it is costly and time consuming and requires a whole blood specimen. Our goal was to develop a suitable assay for population-based screening of easily collectible specimens, such as buccal swabs and dried blood spots (DBS). We designed a pyrosequencing assay and validated it using DNA from FISH–confirmed 22q11 deletion syndrome patients and normal controls. We tested DBS from nine patients and paired buccal cell and venous blood specimens from 20 patients. Results were 100% concordant with FISH assay results. DNA samples from normal controls (n = 180 cell lines, n = 15 DBS, and n = 88 buccal specimens) were negative for the deletion. Limiting dilution experiments demonstrated that accurate results could be obtained from as little as 1 ng of DNA. This method represents a reliable and low-cost alternative for detection of the common 22q11.2 microdeletions and can be adapted to high-throughput population screening. PMID:24973633

What?s Happening to Your DNA Data?: Genetic Testing Services Abound, but Consumers Opting to Use Them Should Be Aware of the Pitfalls.

PubMed

Grifantini, Kristina

2017-01-01

Over the last decade, technology advances in the field of genetics have led to cheaper and more accurate testing. Public interest in personal genetics has grown thanks to media coverage and high-profile stories, such as actress Angelina Jolie's decision to undergo a double mastectomy as a preventative measure against breast cancer when she learned she carries the BRCA1 mutation (relating to breast cancer type 1 susceptibility).

The Hinge Region as a Key Regulatory Element of Androgen Receptor Dimerization, DNA Binding and Transactivation

DTIC Science & Technology

2006-05-01

Mutations in the human androgen receptor gene as a learning tool for molecular endocrinology’ III. Poster presentations at international meetings...nonconsensus half-site, the cognate half-complex buries slightly more surface area from solvent (1,230 Å2) than the noncognate one (960 Å2). AR Mutations ...energetic penalty in- Fig. 4. (A) The AR DBD dimer interface. The molecular surfaces of the AR subunits are shown in red and blue. Dashed black lines

Fish Immunoglobulins

PubMed Central

Mashoof, Sara; Criscitiello, Michael F.

2016-01-01

The B cell receptor and secreted antibody are at the nexus of humoral adaptive immunity. In this review, we summarize what is known of the immunoglobulin genes of jawed cartilaginous and bony fishes. We focus on what has been learned from genomic or cDNA sequence data, but where appropriate draw upon protein, immunization, affinity and structural studies. Work from major aquatic model organisms and less studied comparative species are both included to define what is the rule for an immunoglobulin isotype or taxonomic group and what exemplifies an exception. PMID:27879632

Synthetic biology: exploring and exploiting genetic modularity through the design of novel biological networks.

PubMed

Agapakis, Christina M; Silver, Pamela A

2009-07-01

Synthetic biology has been used to describe many biological endeavors over the past thirty years--from designing enzymes and in vitro systems, to manipulating existing metabolisms and gene expression, to creating entirely synthetic replicating life forms. What separates the current incarnation of synthetic biology from the recombinant DNA technology or metabolic engineering of the past is an emphasis on principles from engineering such as modularity, standardization, and rigorously predictive models. As such, synthetic biology represents a new paradigm for learning about and using biological molecules and data, with applications in basic science, biotechnology, and medicine. This review covers the canonical examples as well as some recent advances in synthetic biology in terms of what we know and what we can learn about the networks underlying biology, and how this endeavor may shape our understanding of living systems.

Prediction of enhancer-promoter interactions via natural language processing.

PubMed

Zeng, Wanwen; Wu, Mengmeng; Jiang, Rui

2018-05-09

Precise identification of three-dimensional genome organization, especially enhancer-promoter interactions (EPIs), is important to deciphering gene regulation, cell differentiation and disease mechanisms. Currently, it is a challenging task to distinguish true interactions from other nearby non-interacting ones since the power of traditional experimental methods is limited due to low resolution or low throughput. We propose a novel computational framework EP2vec to assay three-dimensional genomic interactions. We first extract sequence embedding features, defined as fixed-length vector representations learned from variable-length sequences using an unsupervised deep learning method in natural language processing. Then, we train a classifier to predict EPIs using the learned representations in supervised way. Experimental results demonstrate that EP2vec obtains F1 scores ranging from 0.841~ 0.933 on different datasets, which outperforms existing methods. We prove the robustness of sequence embedding features by carrying out sensitivity analysis. Besides, we identify motifs that represent cell line-specific information through analysis of the learned sequence embedding features by adopting attention mechanism. Last, we show that even superior performance with F1 scores 0.889~ 0.940 can be achieved by combining sequence embedding features and experimental features. EP2vec sheds light on feature extraction for DNA sequences of arbitrary lengths and provides a powerful approach for EPIs identification.

Epigenetic Mechanisms in Learned Fear: Implications for PTSD

PubMed Central

Zovkic, Iva B; Sweatt, J David

2013-01-01

One of the most exciting discoveries in the learning and memory field in the past two decades is the observation that active regulation of gene expression is necessary for experience to trigger lasting functional and behavioral change, in a wide variety of species, including humans. Thus, as opposed to the traditional view of ‘nature' (genes) being separate from ‘nurture' (environment and experience), it is now clear that experience actively drives alterations in central nervous system (CNS) gene expression in an ongoing fashion, and that the resulting transcriptional changes are necessary for experience to trigger altered long-term behavior. In parallel over the past decade, epigenetic mechanisms, including regulation of chromatin structure and DNA methylation, have been shown to be potent regulators of gene transcription in the CNS. In this review, we describe data supporting the hypothesis that epigenetic molecular mechanisms, especially DNA methylation and demethylation, drive long-term behavioral change through active regulation of gene transcription in the CNS. Specifically, we propose that epigenetic molecular mechanisms underlie the formation and stabilization of context- and cue-triggered fear conditioning based in the hippocampus and amygdala, a conclusion reached in a wide variety of studies using laboratory animals. Given the relevance of cued and contextual fear conditioning to post-traumatic stress, by extension we propose that these mechanisms may contribute to post-traumatic stress disorder (PTSD) in humans. Moreover, we speculate that epigenetically based pharmacotherapy may provide a new avenue of drug treatment for PTSD-related cognitive and behavioral function. PMID:22692566

DEEP: a general computational framework for predicting enhancers

PubMed Central

Kleftogiannis, Dimitrios; Kalnis, Panos; Bajic, Vladimir B.

2015-01-01

Transcription regulation in multicellular eukaryotes is orchestrated by a number of DNA functional elements located at gene regulatory regions. Some regulatory regions (e.g. enhancers) are located far away from the gene they affect. Identification of distal regulatory elements is a challenge for the bioinformatics research. Although existing methodologies increased the number of computationally predicted enhancers, performance inconsistency of computational models across different cell-lines, class imbalance within the learning sets and ad hoc rules for selecting enhancer candidates for supervised learning, are some key questions that require further examination. In this study we developed DEEP, a novel ensemble prediction framework. DEEP integrates three components with diverse characteristics that streamline the analysis of enhancer's properties in a great variety of cellular conditions. In our method we train many individual classification models that we combine to classify DNA regions as enhancers or non-enhancers. DEEP uses features derived from histone modification marks or attributes coming from sequence characteristics. Experimental results indicate that DEEP performs better than four state-of-the-art methods on the ENCODE data. We report the first computational enhancer prediction results on FANTOM5 data where DEEP achieves 90.2% accuracy and 90% geometric mean (GM) of specificity and sensitivity across 36 different tissues. We further present results derived using in vivo-derived enhancer data from VISTA database. DEEP-VISTA, when tested on an independent test set, achieved GM of 80.1% and accuracy of 89.64%. DEEP framework is publicly available at http://cbrc.kaust.edu.sa/deep/. PMID:25378307

Learning a single-hidden layer feedforward neural network using a rank correlation-based strategy with application to high dimensional gene expression and proteomic spectra datasets in cancer detection.

PubMed

Belciug, Smaranda; Gorunescu, Florin

2018-06-08

Methods based on microarrays (MA), mass spectrometry (MS), and machine learning (ML) algorithms have evolved rapidly in recent years, allowing for early detection of several types of cancer. A pitfall of these approaches, however, is the overfitting of data due to large number of attributes and small number of instances -- a phenomenon known as the 'curse of dimensionality'. A potentially fruitful idea to avoid this drawback is to develop algorithms that combine fast computation with a filtering module for the attributes. The goal of this paper is to propose a statistical strategy to initiate the hidden nodes of a single-hidden layer feedforward neural network (SLFN) by using both the knowledge embedded in data and a filtering mechanism for attribute relevance. In order to attest its feasibility, the proposed model has been tested on five publicly available high-dimensional datasets: breast, lung, colon, and ovarian cancer regarding gene expression and proteomic spectra provided by cDNA arrays, DNA microarray, and MS. The novel algorithm, called adaptive SLFN (aSLFN), has been compared with four major classification algorithms: traditional ELM, radial basis function network (RBF), single-hidden layer feedforward neural network trained by backpropagation algorithm (BP-SLFN), and support vector-machine (SVM). Experimental results showed that the classification performance of aSLFN is competitive with the comparison models. Copyright © 2018. Published by Elsevier Inc.

Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data.

PubMed

Yang, Yang; Niehaus, Katherine E; Walker, Timothy M; Iqbal, Zamin; Walker, A Sarah; Wilson, Daniel J; Peto, Tim E A; Crook, Derrick W; Smith, E Grace; Zhu, Tingting; Clifton, David A

2018-05-15

Correct and rapid determination of Mycobacterium tuberculosis (MTB) resistance against available tuberculosis (TB) drugs is essential for the control and management of TB. Conventional molecular diagnostic test assumes that the presence of any well-studied single nucleotide polymorphisms is sufficient to cause resistance, which yields low sensitivity for resistance classification. Given the availability of DNA sequencing data from MTB, we developed machine learning models for a cohort of 1839 UK bacterial isolates to classify MTB resistance against eight anti-TB drugs (isoniazid, rifampicin, ethambutol, pyrazinamide, ciprofloxacin, moxifloxacin, ofloxacin, streptomycin) and to classify multi-drug resistance. Compared to previous rules-based approach, the sensitivities from the best-performing models increased by 2-4% for isoniazid, rifampicin and ethambutol to 97% (P < 0.01), respectively; for ciprofloxacin and multi-drug resistant TB, they increased to 96%. For moxifloxacin and ofloxacin, sensitivities increased by 12 and 15% from 83 and 81% based on existing known resistance alleles to 95% and 96% (P < 0.01), respectively. Particularly, our models improved sensitivities compared to the previous rules-based approach by 15 and 24% to 84 and 87% for pyrazinamide and streptomycin (P < 0.01), respectively. The best-performing models increase the area-under-the-ROC curve by 10% for pyrazinamide and streptomycin (P < 0.01), and 4-8% for other drugs (P < 0.01). The details of source code are provided at http://www.robots.ox.ac.uk/~davidc/code.php. david.clifton@eng.ox.ac.uk. Supplementary data are available at Bioinformatics online.

Cancerous 'floater': a lesson learned about tissue identity testing, endometrial cancer and microsatellite instability.

PubMed

Bossuyt, Veerle; Buza, Natalia; Ngo, Nhu T; Much, Melissa A; Asis, Maria C; Schwartz, Peter E; Hui, Pei

2013-09-01

A 46-year-old woman presented with endometrial cells on a pap smear and underwent endometrial curettage. The specimen revealed secretory endometrium and a possible endometrial polyp. In addition, a single 4 mm fragment of well-differentiated adenocarcinoma was found. Tissue identity DNA genotyping was performed and the adenocarcinoma tissue fragment showed a drastically different allelic pattern from that of the background endometrium. To confirm tissue contamination, genotyping of three other tumor specimens-probable sources for a contaminant-was performed but failed to identify a match. Without confirmation of contamination, a second endometrial curettage was obtained from the patient, in which similar adenocarcinoma tissue was once again found. Further workup demonstrated that the patient had a microsatellite unstable (MSI) endometrial adenocarcinoma by immunohistochemistry and molecular testing. The patient subsequently underwent staging surgery, which revealed an early-stage, well-differentiated endometrioid adenocarcinoma. This case study illustrates an uncommon, yet important caveat of tissue identity testing by DNA genotyping, where MSI instability can significantly alter the allelic pattern of DNA polymorphisms in the tumor genome, leading to erroneous conclusion regarding the tissue identity. Awareness of this phenomenon is crucial for a molecular pathologist to avoid interpretation errors of tissue identity testing in a cancer diagnostic workup.

DNA Encoding Training Using 3D Gesture Interaction.

PubMed

Nicola, Stelian; Handrea, Flavia-Laura; Crişan-Vida, Mihaela; Stoicu-Tivadar, Lăcrămioara

2017-01-01

The work described in this paper summarizes the development process and presents the results of a human genetics training application, studying the 20 amino acids formed by the combination of the 3 nucleotides of DNA targeting mainly medical and bioinformatics students. Currently, the domain applications using recognized human gestures of the Leap Motion sensor are used in molecules controlling and learning from Mendeleev table or in visualizing the animated reactions of specific molecules with water. The novelty in the current application consists in using the Leap Motion sensor creating new gestures for the application control and creating a tag based algorithm corresponding to each amino acid, depending on the position in the 3D virtual space of the 4 nucleotides of DNA and their type. The team proposes a 3D application based on Unity editor and on Leap Motion sensor where the user has the liberty of forming different combinations of the 20 amino acids. The results confirm that this new type of study of medicine/biochemistry using the Leap Motion sensor for handling amino acids is suitable for students. The application is original and interactive and the users can create their own amino acid structures in a 3D-like environment which they could not do otherwise using traditional pen-and-paper.

Design and Development of a Technology Platform for DNA-Encoded Library Production and Affinity Selection.

PubMed

Castañón, Jesús; Román, José Pablo; Jessop, Theodore C; de Blas, Jesús; Haro, Rubén

2018-06-01

DNA-encoded libraries (DELs) have emerged as an efficient and cost-effective drug discovery tool for the exploration and screening of very large chemical space using small-molecule collections of unprecedented size. Herein, we report an integrated automation and informatics system designed to enhance the quality, efficiency, and throughput of the production and affinity selection of these libraries. The platform is governed by software developed according to a database-centric architecture to ensure data consistency, integrity, and availability. Through its versatile protocol management functionalities, this application captures the wide diversity of experimental processes involved with DEL technology, keeps track of working protocols in the database, and uses them to command robotic liquid handlers for the synthesis of libraries. This approach provides full traceability of building-blocks and DNA tags in each split-and-pool cycle. Affinity selection experiments and high-throughput sequencing reads are also captured in the database, and the results are automatically deconvoluted and visualized in customizable representations. Researchers can compare results of different experiments and use machine learning methods to discover patterns in data. As of this writing, the platform has been validated through the generation and affinity selection of various libraries, and it has become the cornerstone of the DEL production effort at Lilly.

What bacteria are living in my food? An open-ended practical series involving identification of unknown foodborne bacteria using molecular techniques.

PubMed

Prasad, Prascilla; Turner, Mark S

2011-01-01

This open-ended practical series titled "Molecular Identification of Unknown Food Bacteria" which extended over a 6-week period was designed with the aims of giving students an opportunity to gain an understanding of naturally occurring food bacteria and skills in contemporary molecular methods using real food samples. The students first isolated two unknown bacterial strains from two food sources from which they extracted DNA and performed PCR targeting the 16S rRNA gene. Gel electrophoresis was used to analyze both genomic DNA preparations and PCR products. Following purification of PCR products, DNA sequencing was carried out and sequence trace quality was analyzed. The students successfully identified the two unknown bacteria using the BLAST search engine and a wide variety of different organisms were found. Assessment of their understanding of the procedure and ability to explain their findings using supporting primary research literature was via an individually prepared written report. Feedback from students over 2 years (n = 52) in a questionnaire revealed that the practical series was an engaging learning experience and lead to perceived improvements in knowledge of molecular techniques and bioinformatics and also about commonly occurring bacteria in foods. Copyright © 2011 Wiley Periodicals, Inc.

The sequential hypothesis of sleep function. IV. A correlative analysis of sleep variables in learning and nonlearning rats.

PubMed

Langella, M; Colarieti, L; Ambrosini, M V; Giuditta, A

1992-02-01

Female adult rats were trained for a two-way active avoidance task (4 h), and allowed free sleep (3 h). Control rats (C) were left in their home cages during the acquisition period. Dural electrodes and an intraventricular cannula, implanted one week in advance, were used for EEG recording during the period of sleep and for the injection of [3H]thymidine at the beginning of the training session, respectively. Rats were killed at the end of the sleep period, and the DNA-specific activity was determined in the main brain regions and in liver. Correlations among sleep, behavioral and biochemical variables were assessed using Spearman's nonparametric method. In learning rats (L), the number of avoidances was negatively correlated with SS-W variables, and positively correlated with SS-PS variables (episodes of synchronized sleep followed by wakefulness or paradoxical sleep, respectively) and with PS variables. An inverse pattern of correlations was shown by the number of escapes or freezings. No correlations occurred in rats unable to achieve the learning criterion (NL). In L rats, the specific activity of brain DNA was negatively correlated with SS-W variables and positively correlated with SS-PS variables, while essentially no correlation concerned PS variables. On the other hand, in NL rats, comparable correlations were positive with SS-W variables and negative with SS-PS and PS variables. Few and weak correlations occurred in C rats. The data support a role of SS in brain information processing, as postulated by the sequential hypothesis on the function of sleep. In addition, they suggest that the elimination of nonadaptive memory traces may require several SS-W episodes and a terminal SS-PS episode. During PS episodes, adaptive memory traces cleared of nonadaptive components may be copied in more suitable brain sites.

Maternal blood contamination of collected cord blood can be identified using DNA methylation at three CpGs.

PubMed

Morin, Alexander M; Gatev, Evan; McEwen, Lisa M; MacIsaac, Julia L; Lin, David T S; Koen, Nastassja; Czamara, Darina; Räikkönen, Katri; Zar, Heather J; Koenen, Karestan; Stein, Dan J; Kobor, Michael S; Jones, Meaghan J

2017-01-01

Cord blood is a commonly used tissue in environmental, genetic, and epigenetic population studies due to its ready availability and potential to inform on a sensitive period of human development. However, the introduction of maternal blood during labor or cross-contamination during sample collection may complicate downstream analyses. After discovering maternal contamination of cord blood in a cohort study of 150 neonates using Illumina 450K DNA methylation (DNAm) data, we used a combination of linear regression and random forest machine learning to create a DNAm-based screening method. We identified a panel of DNAm sites that could discriminate between contaminated and non-contaminated samples, then designed pyrosequencing assays to pre-screen DNA prior to being assayed on an array. Maternal contamination of cord blood was initially identified by unusual X chromosome DNA methylation patterns in 17 males. We utilized our DNAm panel to detect contaminated male samples and a proportional amount of female samples in the same cohort. We validated our DNAm screening method on an additional 189 sample cohort using both pyrosequencing and DNAm arrays, as well as 9 publically available cord blood 450K data sets. The rate of contamination varied from 0 to 10% within these studies, likely related to collection specific methods. Maternal blood can contaminate cord blood during sample collection at appreciable levels across multiple studies. We have identified a panel of markers that can be used to identify this contamination, either post hoc after DNAm arrays have been completed, or in advance using a targeted technique like pyrosequencing.

A pyrosequencing-based assay for the rapid detection of the 22q11.2 deletion in DNA from buccal and dried blood spot samples.

PubMed

Koontz, Deborah; Baecher, Kirsten; Kobrynski, Lisa; Nikolova, Stanimila; Gallagher, Margaret

2014-09-01

The 22q11.2 deletion syndrome is one of the most common deletion syndromes in newborns. Some affected newborns may be diagnosed shortly after birth because of the presence of heart defects, palatal defects, or severe immune deficiencies. However, diagnosis is often delayed in patients presenting with other associated conditions that would benefit from early recognition and treatment, such as speech delays, learning difficulties, and schizophrenia. Fluorescence in situ hybridization (FISH) is the gold standard for deletion detection, but it is costly and time consuming and requires a whole blood specimen. Our goal was to develop a suitable assay for population-based screening of easily collectible specimens, such as buccal swabs and dried blood spots (DBS). We designed a pyrosequencing assay and validated it using DNA from FISH-confirmed 22q11 deletion syndrome patients and normal controls. We tested DBS from nine patients and paired buccal cell and venous blood specimens from 20 patients. Results were 100% concordant with FISH assay results. DNA samples from normal controls (n = 180 cell lines, n = 15 DBS, and n = 88 buccal specimens) were negative for the deletion. Limiting dilution experiments demonstrated that accurate results could be obtained from as little as 1 ng of DNA. This method represents a reliable and low-cost alternative for detection of the common 22q11.2 microdeletions and can be adapted to high-throughput population screening. Copyright © 2014 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Ancestry Dependent DNA Methylation and Influence of Maternal Nutrition

PubMed Central

Mozhui, Khyobeni; Smith, Alicia K.; Tylavsky, Frances A.

2015-01-01

There is extensive variation in DNA methylation between individuals and ethnic groups. These differences arise from a combination of genetic and non-genetic influences and potential modifiers include nutritional cues, early life experience, and social and physical environments. Here we compare genome-wide DNA methylation in neonatal cord blood from African American (AA; N = 112) and European American (EA; N = 91) participants of the CANDLE Study (Conditions Affecting Neurocognitive Development and Learning in Early Childhood). Our goal is to determine if there are replicable ancestry-specific methylation patterns that may implicate risk factors for diseases that have differential prevalence between populations. To identify the most robust ancestry-specific CpG sites, we replicate our results in lymphoblastoid cell lines from Yoruba African and CEPH European panels of HapMap. We also evaluate the influence of maternal nutrition—specifically, plasma levels of vitamin D and folate during pregnancy—on methylation in newborns. We define stable ancestry-dependent methylation of genes that include tumor suppressors and cell cycle regulators (e.g., APC, BRCA1, MCC). Overall, there is lower global methylation in African ancestral groups. Plasma levels of 25-hydroxy vitamin D are also considerably lower among AA mothers and about 60% of AA and 40% of EA mothers have concentrations below 20 ng/ml. Using a weighted correlation analysis, we define a network of CpG sites that is jointly modulated by ancestry and maternal vitamin D. Our results show that differences in DNA methylation patterns are remarkably stable and maternal micronutrients can exert an influence on the child epigenome. PMID:25742137

Aerobic endurance capacity affects spatial memory and SIRT1 is a potent modulator of 8-oxoguanine repair.

PubMed

Sarga, L; Hart, N; Koch, L G; Britton, S L; Hajas, G; Boldogh, I; Ba, X; Radak, Z

2013-11-12

Regular exercise promotes brain function via a wide range of adaptive responses, including the increased expression of antioxidant and oxidative DNA damage-repairing systems. Accumulation of oxidized DNA base lesions and strand breaks is etiologically linked to for example aging processes and age-associated diseases. Here we tested whether exercise training has an impact on brain function, extent of neurogenesis, and expression of 8-oxoguanine DNA glycosylase-1 (Ogg1) and SIRT1 (silent mating-type information regulation 2 homolog). To do so, we utilized strains of rats with low- and high-running capacity (LCR and HCR) and examined learning and memory, DNA synthesis, expression, and post-translational modification of Ogg1 hippocampal cells. Our results showed that rats with higher aerobic/running capacity had better spatial memory, and expressed less Ogg1, when compared to LCR rats. Furthermore, exercise increased SIRT1 expression and decreased acetylated Ogg1 (AcOgg1) levels, a post-translational modification important for efficient repair of 8-oxo-7,8-dihydroguanine (8-oxoG). Our data on cell cultures revealed that nicotinamide, a SIRT1-specific inhibitor, caused the greatest increase in the acetylation of Ogg1, a finding further supported by our other observations that silencing SIRT1 also markedly increased the levels of AcOgg1. These findings imply that high-running capacity is associated with increased hippocampal function, and SIRT1 level/activity and inversely correlates with AcOgg1 levels and thereby the repair of genomic 8-oxoG. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Puzzles in modern biology. V. Why are genomes overwired?

PubMed

Frank, Steven A

2017-01-01

Many factors affect eukaryotic gene expression. Transcription factors, histone codes, DNA folding, and noncoding RNA modulate expression. Those factors interact in large, broadly connected regulatory control networks. An engineer following classical principles of control theory would design a simpler regulatory network. Why are genomes overwired? Neutrality or enhanced robustness may lead to the accumulation of additional factors that complicate network architecture. Dynamics progresses like a ratchet. New factors get added. Genomes adapt to the additional complexity. The newly added factors can no longer be removed without significant loss of fitness. Alternatively, highly wired genomes may be more malleable. In large networks, most genomic variants tend to have a relatively small effect on gene expression and trait values. Many small effects lead to a smooth gradient, in which traits may change steadily with respect to underlying regulatory changes. A smooth gradient may provide a continuous path from a starting point up to the highest peak of performance. A potential path of increasing performance promotes adaptability and learning. Genomes gain by the inductive process of natural selection, a trial and error learning algorithm that discovers general solutions for adapting to environmental challenge. Similarly, deeply and densely connected computational networks gain by various inductive trial and error learning procedures, in which the networks learn to reduce the errors in sequential trials. Overwiring alters the geometry of induction by smoothing the gradient along the inductive pathways of improving performance. Those overwiring benefits for induction apply to both natural biological networks and artificial deep learning networks.

Nonlinear programming for classification problems in machine learning

NASA Astrophysics Data System (ADS)

Astorino, Annabella; Fuduli, Antonio; Gaudioso, Manlio

2016-10-01

We survey some nonlinear models for classification problems arising in machine learning. In the last years this field has become more and more relevant due to a lot of practical applications, such as text and web classification, object recognition in machine vision, gene expression profile analysis, DNA and protein analysis, medical diagnosis, customer profiling etc. Classification deals with separation of sets by means of appropriate separation surfaces, which is generally obtained by solving a numerical optimization model. While linear separability is the basis of the most popular approach to classification, the Support Vector Machine (SVM), in the recent years using nonlinear separating surfaces has received some attention. The objective of this work is to recall some of such proposals, mainly in terms of the numerical optimization models. In particular we tackle the polyhedral, ellipsoidal, spherical and conical separation approaches and, for some of them, we also consider the semisupervised versions.

Hot Technology, Cool Science (LBNL Science at the Theater)

ScienceCinema

Fowler, John

2018-06-08

Great innovations start with bold ideas. Learn how Berkeley Lab scientists are devising practical solutions to everything from global warming to how you get to work. On May 11, 2009, five Berkeley Lab scientists participated in a roundtable dicussion moderated by KTVU's John Fowler on their leading-edge research. This "Science at the Theater" event, held at the Berkeley Repertory Theatre, featured technologies such as cool roofs, battery-driven transportation, a pocket-sized DNA probe, green supercomputing, and a noncontact method for restoring damaged and fragile mechanical recordings.

DNA methylation-based classification of central nervous system tumours.

PubMed

Capper, David; Jones, David T W; Sill, Martin; Hovestadt, Volker; Schrimpf, Daniel; Sturm, Dominik; Koelsche, Christian; Sahm, Felix; Chavez, Lukas; Reuss, David E; Kratz, Annekathrin; Wefers, Annika K; Huang, Kristin; Pajtler, Kristian W; Schweizer, Leonille; Stichel, Damian; Olar, Adriana; Engel, Nils W; Lindenberg, Kerstin; Harter, Patrick N; Braczynski, Anne K; Plate, Karl H; Dohmen, Hildegard; Garvalov, Boyan K; Coras, Roland; Hölsken, Annett; Hewer, Ekkehard; Bewerunge-Hudler, Melanie; Schick, Matthias; Fischer, Roger; Beschorner, Rudi; Schittenhelm, Jens; Staszewski, Ori; Wani, Khalida; Varlet, Pascale; Pages, Melanie; Temming, Petra; Lohmann, Dietmar; Selt, Florian; Witt, Hendrik; Milde, Till; Witt, Olaf; Aronica, Eleonora; Giangaspero, Felice; Rushing, Elisabeth; Scheurlen, Wolfram; Geisenberger, Christoph; Rodriguez, Fausto J; Becker, Albert; Preusser, Matthias; Haberler, Christine; Bjerkvig, Rolf; Cryan, Jane; Farrell, Michael; Deckert, Martina; Hench, Jürgen; Frank, Stephan; Serrano, Jonathan; Kannan, Kasthuri; Tsirigos, Aristotelis; Brück, Wolfgang; Hofer, Silvia; Brehmer, Stefanie; Seiz-Rosenhagen, Marcel; Hänggi, Daniel; Hans, Volkmar; Rozsnoki, Stephanie; Hansford, Jordan R; Kohlhof, Patricia; Kristensen, Bjarne W; Lechner, Matt; Lopes, Beatriz; Mawrin, Christian; Ketter, Ralf; Kulozik, Andreas; Khatib, Ziad; Heppner, Frank; Koch, Arend; Jouvet, Anne; Keohane, Catherine; Mühleisen, Helmut; Mueller, Wolf; Pohl, Ute; Prinz, Marco; Benner, Axel; Zapatka, Marc; Gottardo, Nicholas G; Driever, Pablo Hernáiz; Kramm, Christof M; Müller, Hermann L; Rutkowski, Stefan; von Hoff, Katja; Frühwald, Michael C; Gnekow, Astrid; Fleischhack, Gudrun; Tippelt, Stephan; Calaminus, Gabriele; Monoranu, Camelia-Maria; Perry, Arie; Jones, Chris; Jacques, Thomas S; Radlwimmer, Bernhard; Gessi, Marco; Pietsch, Torsten; Schramm, Johannes; Schackert, Gabriele; Westphal, Manfred; Reifenberger, Guido; Wesseling, Pieter; Weller, Michael; Collins, Vincent Peter; Blümcke, Ingmar; Bendszus, Martin; Debus, Jürgen; Huang, Annie; Jabado, Nada; Northcott, Paul A; Paulus, Werner; Gajjar, Amar; Robinson, Giles W; Taylor, Michael D; Jaunmuktane, Zane; Ryzhova, Marina; Platten, Michael; Unterberg, Andreas; Wick, Wolfgang; Karajannis, Matthias A; Mittelbronn, Michel; Acker, Till; Hartmann, Christian; Aldape, Kenneth; Schüller, Ulrich; Buslei, Rolf; Lichter, Peter; Kool, Marcel; Herold-Mende, Christel; Ellison, David W; Hasselblatt, Martin; Snuderl, Matija; Brandner, Sebastian; Korshunov, Andrey; von Deimling, Andreas; Pfister, Stefan M

2018-03-22

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.

The School Malaise Trap Program: Coupling educational outreach with scientific discovery

PubMed Central

Breton, Vanessa; Berzitis, Emily; Hebert, Paul D. N.

2017-01-01

The School Malaise Trap Program (SMTP) provides a technologically sophisticated and scientifically relevant educational experience that exposes students to the diversity of life, enhancing their understanding of biodiversity while promoting environmental stewardship. Since 2013, the SMTP has allowed 15,000 students at 350 primary and secondary schools to explore insect diversity in Canadian schoolyards. Students at each school collected hundreds of insects for an analysis of DNA sequence variation that enabled their rapid identification to a species. Through this hands-on approach, they participated in a learning exercise that conveys a real sense of scientific discovery. As well, the students contributed valuable data to the largest biodiversity genomics initiative ever undertaken: the International Barcode of Life project. To date, the SMTP has sequenced over 80,000 insect specimens, which includes representatives of 7,990 different species, nearly a tenth of the Canadian fauna. Both surprisingly and importantly, the collections generated the first DNA barcode records for 1,288 Canadian species. PMID:28437475

Identification of Biomolecular Building Blocks by Recognition Tunneling: Stride towards Nanopore Sequencing of Biomolecules

NASA Astrophysics Data System (ADS)

Sen, Suman

DNA, RNA and Protein are three pivotal biomolecules in human and other organisms, playing decisive roles in functionality, appearance, diseases development and other physiological phenomena. Hence, sequencing of these biomolecules acquires the prime interest in the scientific community. Single molecular identification of their building blocks can be done by a technique called Recognition Tunneling (RT) based on Scanning Tunneling Microscope (STM). A single layer of specially designed recognition molecule is attached to the STM electrodes, which trap the targeted molecules (DNA nucleoside monophosphates, RNA nucleoside monophosphates or amino acids) inside the STM nanogap. Depending on their different binding interactions with the recognition molecules, the analyte molecules generate stochastic signal trains accommodating their "electronic fingerprints". Signal features are used to detect the molecules using a machine learning algorithm and different molecules can be identified with significantly high accuracy. This, in turn, paves the way for rapid, economical nanopore sequencing platform, overcoming the drawbacks of Next Generation Sequencing (NGS) techniques. To read DNA nucleotides with high accuracy in an STM tunnel junction a series of nitrogen-based heterocycles were designed and examined to check their capabilities to interact with naturally occurring DNA nucleotides by hydrogen bonding in the tunnel junction. These recognition molecules are Benzimidazole, Imidazole, Triazole and Pyrrole. Benzimidazole proved to be best among them showing DNA nucleotide classification accuracy close to 99%. Also, Imidazole reader can read an abasic monophosphate (AP), a product from depurination or depyrimidination that occurs 10,000 times per human cell per day. In another study, I have investigated a new universal reader, 1-(2-mercaptoethyl)pyrene (Pyrene reader) based on stacking interactions, which should be more specific to the canonical DNA nucleosides. In addition, Pyrene reader showed higher DNA base-calling accuracy compare to Imidazole reader, the workhorse in our previous projects. In my other projects, various amino acids and RNA nucleoside monophosphates were also classified with significantly high accuracy using RT. Twenty naturally occurring amino acids and various RNA nucleosides (four canonical and two modified) were successfully identified. Thus, we envision nanopore sequencing biomolecules using Recognition Tunneling (RT) that should provide comprehensive betterment over current technologies in terms of time, chemical and instrumental cost and capability of de novo sequencing.

High Incidence of HPV-Associated Head and Neck Cancers in FA Deficient Mice Is Associated with E7’s Induction of DNA Damage through Its Inactivation of Pocket Proteins

PubMed Central

Park, Jung Wook; Shin, Myeong-Kyun; Pitot, Henry C.; Lambert, Paul F.

2013-01-01

Fanconi anemia (FA) patients are highly susceptible to solid tumors at multiple anatomical sites including head and neck region. A subset of head and neck cancers (HNCs) is associated with ‘high-risk’ HPVs, particularly HPV16. However, the correlation between HPV oncogenes and cancers in FA patients is still unclear. We previously learned that FA deficiency in mice predisposes HPV16 E7 transgenic mice to HNCs. To address HPV16 E6’s oncogenic potential under FA deficiency in HNCs, we utilized HPV16 E6-transgenic mice (K14E6) and HPV16 E6/E7-bi-transgenic mice (K14E6E7) on genetic backgrounds sufficient or deficient for one of the fanc genes, fancD2 and monitored their susceptibility to HNCs. K14E6 mice failed to develop tumor. However, E6 and fancD2-deficiency accelerated E7-driven tumor development in K14E6E7 mice. The increased tumor incidence was more correlated with E7-driven DNA damage than proliferation. We also found that deficiency of pocket proteins, pRb, p107, and p130 that are well-established targets of E7, could recapitulate E7’s induction of DNA damage. Our findings support the hypothesis that E7 induces HPV-associated HNCs by promoting DNA damage through the inactivation of pocket proteins, which explains why a deficiency in DNA damage repair would increase susceptibility to E7-driven cancer. Our results further demonstrate the unexpected finding that FA deficiency does not predispose E6 transgenic mice to HNCs, indicating a specificity in the synergy between FA deficiency and HPV oncogenes in causing HNCs. PMID:24086435

Impact of neonatal iron deficiency on hippocampal DNA methylation and gene transcription in a porcine biomedical model of cognitive development.

PubMed

Schachtschneider, Kyle M; Liu, Yingkai; Rund, Laurie A; Madsen, Ole; Johnson, Rodney W; Groenen, Martien A M; Schook, Lawrence B

2016-11-03

Iron deficiency is a common childhood micronutrient deficiency that results in altered hippocampal function and cognitive disorders. However, little is known about the mechanisms through which neonatal iron deficiency results in long lasting alterations in hippocampal gene expression and function. DNA methylation is an epigenetic mark involved in gene regulation and altered by environmental factors. In this study, hippocampal DNA methylation and gene expression were assessed via reduced representation bisulfite sequencing and RNA-seq on samples from a previous study reporting reduced hippocampal-based learning and memory in a porcine biomedical model of neonatal iron deficiency. In total 192 differentially expressed genes (DEGs) were identified between the iron deficient and control groups. GO term and pathway enrichment analysis identified DEGs associated with hypoxia, angiogenesis, increased blood brain barrier (BBB) permeability, and altered neurodevelopment and function. Of particular interest are genes previously implicated in cognitive deficits and behavioral disorders in humans and mice, including HTR2A, HTR2C, PAK3, PRSS12, and NETO1. Altered genome-wide DNA methylation was observed across 0.5 million CpG and 2.4 million non-CpG sites. In total 853 differentially methylated (DM) CpG and 99 DM non-CpG sites were identified between groups. Samples clustered by group when comparing DM non-CpG sites, suggesting high conservation of non-CpG methylation in response to neonatal environment. In total 12 DM sites were associated with 9 DEGs, including genes involved in angiogenesis, neurodevelopment, and neuronal function. Neonatal iron deficiency leads to altered hippocampal DNA methylation and gene regulation involved in hypoxia, angiogenesis, increased BBB permeability, and altered neurodevelopment and function. Together, these results provide new insights into the mechanisms through which neonatal iron deficiency results in long lasting reductions in cognitive development in humans.

Assessment of a novel group-centered testing schema in an upper-level undergraduate molecular biotechnology course.

PubMed

Srougi, Melissa C; Miller, Heather B; Witherow, D Scott; Carson, Susan

2013-01-01

Providing students with assignments that focus on critical thinking is an important part of their scientific and intellectual development. However, as class sizes increase, so does the grading burden, prohibiting many faculty from incorporating critical thinking assignments in the classroom. In an effort to continue to provide our students with meaningful critical thinking exercises, we implemented a novel group-centered, problem-based testing scheme. We wanted to assess how performing critical thinking problem sets as group work compares to performing the sets as individual work, in terms of student attitudes and learning outcomes. During two semesters of our recombinant DNA course, students had the same lecture material and similar assessments. In the Fall semester, student learning was assessed by two collaborative take-home exams, followed immediately by individual, closed-book in-class exams on the same content, as well as a final cumulative exam. Student teams on the take-home exams were instructor-assigned, and each team turned in one collaborative exam. In the Spring semester, the control group of students were required to turn in their own individual take-home exams, followed by the in-class exams and final cumulative exam. For the majority of students, learning outcomes were met, regardless of whether they worked in teams. In addition, collaborative learning was favorably received by students and grading was reduced for instructors. These data suggest that group-centered, problem-based learning is a useful model for achievement of student learning outcomes in courses where it would be infeasible to provide feedback on individual critical thinking assignments due to grading volume. Copyright © 2013 Wiley Periodicals, Inc.

Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data

PubMed Central

Yang, Yang; Niehaus, Katherine E; Walker, Timothy M; Iqbal, Zamin; Walker, A Sarah; Wilson, Daniel J; Peto, Tim E A; Crook, Derrick W; Smith, E Grace; Zhu, Tingting; Clifton, David A

2018-01-01

Abstract Motivation Correct and rapid determination of Mycobacterium tuberculosis (MTB) resistance against available tuberculosis (TB) drugs is essential for the control and management of TB. Conventional molecular diagnostic test assumes that the presence of any well-studied single nucleotide polymorphisms is sufficient to cause resistance, which yields low sensitivity for resistance classification. Summary Given the availability of DNA sequencing data from MTB, we developed machine learning models for a cohort of 1839 UK bacterial isolates to classify MTB resistance against eight anti-TB drugs (isoniazid, rifampicin, ethambutol, pyrazinamide, ciprofloxacin, moxifloxacin, ofloxacin, streptomycin) and to classify multi-drug resistance. Results Compared to previous rules-based approach, the sensitivities from the best-performing models increased by 2-4% for isoniazid, rifampicin and ethambutol to 97% (P < 0.01), respectively; for ciprofloxacin and multi-drug resistant TB, they increased to 96%. For moxifloxacin and ofloxacin, sensitivities increased by 12 and 15% from 83 and 81% based on existing known resistance alleles to 95% and 96% (P < 0.01), respectively. Particularly, our models improved sensitivities compared to the previous rules-based approach by 15 and 24% to 84 and 87% for pyrazinamide and streptomycin (P < 0.01), respectively. The best-performing models increase the area-under-the-ROC curve by 10% for pyrazinamide and streptomycin (P < 0.01), and 4–8% for other drugs (P < 0.01). Availability and implementation The details of source code are provided at http://www.robots.ox.ac.uk/~davidc/code.php. Contact david.clifton@eng.ox.ac.uk Supplementary information Supplementary data are available at Bioinformatics online. PMID:29240876

Divergence of mechanistic pathways mediating cardiovascular aging and developmental programming of cardiovascular disease

PubMed Central

Allison, Beth J.; Kaandorp, Joepe J.; Kane, Andrew D.; Camm, Emily J.; Lusby, Ciara; Cross, Christine M.; Nevin-Dolan, Rhianon; Thakor, Avnesh S.; Derks, Jan B.; Tarry-Adkins, Jane L.; Ozanne, Susan E.; Giussani, Dino A.

2016-01-01

Aging and developmental programming are both associated with oxidative stress and endothelial dysfunction, suggesting common mechanistic origins. However, their interrelationship has been little explored. In a rodent model of programmed cardiovascular dysfunction we determined endothelial function and vascular telomere length in young (4 mo) and aged (15 mo) adult offspring of normoxic or hypoxic pregnancy with or without maternal antioxidant treatment. We show loss of endothelial function [maximal arterial relaxation to acetylcholine (71 ± 3 vs. 55 ± 3%) and increased vascular short telomere abundance (4.2–1.3 kb) 43.0 ± 1.5 vs. 55.1 ± 3.8%) in aged vs. young offspring of normoxic pregnancy (P < 0.05). Hypoxic pregnancy in young offspring accelerated endothelial dysfunction (maximal arterial relaxation to acetylcholine: 42 ± 1%, P < 0.05) but this was dissociated from increased vascular short telomere length abundance. Maternal allopurinol rescued maximal arterial relaxation to acetylcholine in aged offspring of normoxic or hypoxic pregnancy but not in young offspring of hypoxic pregnancy. Aged offspring of hypoxic allopurinol pregnancy compared with aged offspring of untreated hypoxic pregnancy had lower levels of short telomeres (vascular short telomere length abundance 35.1 ± 2.5 vs. 48.2 ± 2.6%) and of plasma proinflammatory chemokine (24.6 ± 2.8 vs. 36.8 ± 5.5 pg/ml, P < 0.05). These data provide evidence for divergence of mechanistic pathways mediating cardiovascular aging and developmental programming of cardiovascular disease, and aging being decelerated by antioxidants even prior to birth.—Allison, B. J., Kaandorp, J. J., Kane, A. D., Camm, E. J., Lusby, C., Cross, C. M., Nevin-Dolan, R., Thakor, A. S., Derks, J. B., Tarry-Adkins, J. L., Ozanne, S. E., Giussani, D. A. Divergence of mechanistic pathways mediating cardiovascular aging and developmental programming of cardiovascular disease. PMID:26932929

Precarious rock and overturned transformer evidence for ground shaking in the Ms 7.7 Kern County earthquake: An analog for disastrous shaking from a major thrust fault in the Los Angeles basin

USGS Publications Warehouse

Brune, J.N.; Anooshehpoor, A.; Shi, B.; Zheng, Yen

2004-01-01

Precariously balanced rocks and overturned transformers in the vicinity of the White Wolf fault provide constraints on ground motion during the 1952 Ms 7.7 Kern County earthquake, a possible analog for an anticipated large earthquake in the Los Angeles basin (Shaw et al., 2002; Dolan et al., 2003). On the northeast part of the fault preliminary estimates of ground motion on the footwall give peak accelerations considerably lower than predicted by standard regression curves. On the other hand, on the hanging-wall, there is evidence of intense ground shattering and lack of precarious rocks, consistent with the intense hanging-wall accelerations suggested by foam-rubber modeling, numerical modeling, and observations from previous thrust fault earthquakes. There is clear evidence of the effects of rupture directivity in ground motions on the hanging-wall side of the fault (from both precarious rocks and numerical simulations). On the southwest part of the fault, which is covered by sediments, the thrust fault did not reach the surface ("blind" thrust). Overturned and damaged transformers indicate significant transfer of energy from the hanging wall to the footwall, an effect that may not be as effective when the rupture reaches the surface (is not "blind"). Transformers near the up-dip projection of the fault tip have been damaged or overturned on both the hanging-wall and footwall sides of the fault. The transfer of energy is confirmed in a numerical lattice model and could play an important role in a similar situation in Los Angeles. We suggest that the results of this study can provide important information for estimating the effects of a large thrust fault rupture in the Los Angeles basin, specially given the fact that there is so little instrumental data from large thrust fault earthquakes.

Testing the application of Teflon/quartz soil solution samplers for DOM sampling in the Critical Zone: Field and laboratory approaches

NASA Astrophysics Data System (ADS)

Dolan, E. M.; Perdrial, J. N.; Vazquez, A.; Hernández, S.; Chorover, J.

2010-12-01

Elizabeth Dolan1,2, Julia Perdrial3, Angélica Vázquez-Ortega3, Selene Hernández-Ruiz3, Jon Chorover3 1Deptartment of Soil, Environmental, and Atmospheric Science, University of Missouri. 2Biosphere 2, University of Arizona. 3Deptartment of Soil, Water, and Environmental Science, University of Arizona. Abstract: The behavior of dissolved organic matter (DOM) in soil is important to many biogeochemical processes. Extraction methods to obtain DOM from the unsaturated zone remain a current focus of research as different methods can influence the type and concentration of DOM obtained. Thus, the present comparison study involves three methods for soil solution sampling to assess their impact on DOM quantity and quality: 1) aqueous soil extracts, 2) solution yielded from laboratory installed suction cup samplers and 3) solutions from field installed suction cup samplers. All samples were analyzed for dissolved organic carbon and total nitrogen concentrations. Moreover, DOM quality was analyzed using fluorescence, UV-Vis and FTIR spectroscopies. Results indicate higher DOC values for laboratory extracted DOM: 20 mg/L for aqueous soil extracts and 31 mg/L for lab installed samplers compared to 12 mg/L for field installed samplers. Large variations in C/N ratios were also observed ranging from 1.5 in laboratory extracted DOM to 11 in field samples. Fluorescence excitation-emission matrices of DOM solutions obtained for the laboratory extraction methods showed higher intensities in regions typical for fulvic and humic acid-like materials relative to those extracted in the field. Similarly, the molar absorptivity calculated from DOC concentration normalization of UV-Vis absorbance of the laboratory-derived solutions was significantly higher as well, indicating greater aromaticity. The observed differences can be attributed to soil disturbance associated with obtaining laboratory derived solution samples. Our results indicate that laboratory extraction methods are not comparable to in-situ field soil solution extraction in terms of DOM.

Divergence of mechanistic pathways mediating cardiovascular aging and developmental programming of cardiovascular disease.

PubMed

Allison, Beth J; Kaandorp, Joepe J; Kane, Andrew D; Camm, Emily J; Lusby, Ciara; Cross, Christine M; Nevin-Dolan, Rhianon; Thakor, Avnesh S; Derks, Jan B; Tarry-Adkins, Jane L; Ozanne, Susan E; Giussani, Dino A

2016-05-01

Aging and developmental programming are both associated with oxidative stress and endothelial dysfunction, suggesting common mechanistic origins. However, their interrelationship has been little explored. In a rodent model of programmed cardiovascular dysfunction we determined endothelial function and vascular telomere length in young (4 mo) and aged (15 mo) adult offspring of normoxic or hypoxic pregnancy with or without maternal antioxidant treatment. We show loss of endothelial function [maximal arterial relaxation to acetylcholine (71 ± 3 vs. 55 ± 3%) and increased vascular short telomere abundance (4.2-1.3 kb) 43.0 ± 1.5 vs. 55.1 ± 3.8%) in aged vs. young offspring of normoxic pregnancy (P < 0.05). Hypoxic pregnancy in young offspring accelerated endothelial dysfunction (maximal arterial relaxation to acetylcholine: 42 ± 1%, P < 0.05) but this was dissociated from increased vascular short telomere length abundance. Maternal allopurinol rescued maximal arterial relaxation to acetylcholine in aged offspring of normoxic or hypoxic pregnancy but not in young offspring of hypoxic pregnancy. Aged offspring of hypoxic allopurinol pregnancy compared with aged offspring of untreated hypoxic pregnancy had lower levels of short telomeres (vascular short telomere length abundance 35.1 ± 2.5 vs. 48.2 ± 2.6%) and of plasma proinflammatory chemokine (24.6 ± 2.8 vs. 36.8 ± 5.5 pg/ml, P < 0.05). These data provide evidence for divergence of mechanistic pathways mediating cardiovascular aging and developmental programming of cardiovascular disease, and aging being decelerated by antioxidants even prior to birth.-Allison, B. J., Kaandorp, J. J., Kane, A. D., Camm, E. J., Lusby, C., Cross, C. M., Nevin-Dolan, R., Thakor, A. S., Derks, J. B., Tarry-Adkins, J. L., Ozanne, S. E., Giussani, D. A. Divergence of mechanistic pathways mediating cardiovascular aging and developmental programming of cardiovascular disease. © FASEB.

Focal brain inflammation and autism.

PubMed

Theoharides, Theoharis C; Asadi, Shahrzad; Patel, Arti B

2013-04-09

Increasing evidence indicates that brain inflammation is involved in the pathogenesis of neuropsychiatric diseases. Autism spectrum disorders (ASD) are characterized by social and learning disabilities that affect as many as 1/80 children in the USA. There is still no definitive pathogenesis or reliable biomarkers for ASD, thus significantly curtailing the development of effective therapies. Many children with ASD regress at about age 3 years, often after a specific event such as reaction to vaccination, infection, stress or trauma implying some epigenetic triggers, and may constitute a distinct phenotype. ASD children respond disproportionally to stress and are also affected by food and skin allergies. Corticotropin-releasing hormone (CRH) is secreted under stress and together with neurotensin (NT) stimulates mast cells and microglia resulting in focal brain inflammation and neurotoxicity. NT is significantly increased in serum of ASD children along with mitochondrial DNA (mtDNA). NT stimulates mast cell secretion of mtDNA that is misconstrued as an innate pathogen triggering an auto-inflammatory response. The phosphatase and tensin homolog (PTEN) gene mutation, associated with the higher risk of ASD, which leads to hyper-active mammalian target of rapamycin (mTOR) signalling that is crucial for cellular homeostasis. CRH, NT and environmental triggers could hyperstimulate the already activated mTOR, as well as stimulate mast cell and microglia activation and proliferation. The natural flavonoid luteolin inhibits mTOR, mast cells and microglia and could have a significant benefit in ASD.

The loss of SMG1 causes defects in quality control pathways in Physcomitrella patens

PubMed Central

Lang, Daniel; Zimmer, Andreas D; Causier, Barry

2018-01-01

Abstract Nonsense-mediated mRNA decay (NMD) is important for RNA quality control and gene regulation in eukaryotes. NMD targets aberrant transcripts for decay and also directly influences the abundance of non-aberrant transcripts. In animals, the SMG1 kinase plays an essential role in NMD by phosphorylating the core NMD factor UPF1. Despite SMG1 being ubiquitous throughout the plant kingdom, little is known about its function, probably because SMG1 is atypically absent from the genome of the model plant, Arabidopsis thaliana. By combining our previously established SMG1 knockout in moss with transcriptome-wide analysis, we reveal the range of processes involving SMG1 in plants. Machine learning assisted analysis suggests that 32% of multi-isoform genes produce NMD-targeted transcripts and that splice junctions downstream of a stop codon act as the major determinant of NMD targeting. Furthermore, we suggest that SMG1 is involved in other quality control pathways, affecting DNA repair and the unfolded protein response, in addition to its role in mRNA quality control. Consistent with this, smg1 plants have increased susceptibility to DNA damage, but increased tolerance to unfolded protein inducing agents. The potential involvement of SMG1 in RNA, DNA and protein quality control has major implications for the study of these processes in plants. PMID:29596649

Chemo brain or tumor brain - that is the question: the presence of extracranial tumors profoundly affects molecular processes in the prefrontal cortex of TumorGraft mice

PubMed Central

Kovalchuk, Anna; Ilnytskyy, Yaroslav; Rodriguez-Juarez, Rocio; Shpyleva, Svitlana; Melnyk, Stepan; Pogribny, Igor; Katz, Amanda; Sidransky, David; Kovalchuk, Olga; Kolb, Bryan

2017-01-01

Cancer chemotherapy causes numerous persistent central nervous system complications. This condition is known as chemo brain. Cognitive impairments occur even before treatment, and hence are referred to as cancer associated cognitive changes, or tumor brain. There is much yet to be learned about the mechanisms of both chemo brain and tumor brain. The frequency and timing of chemo brain and tumor brain occurrence and persistence strongly suggest they may be epigenetic in nature and associated with altered gene expression. Here we used TumorGraftTM models wherein part of a patient's tumor is removed and grafted into immune-deficient mice and conducted global gene expression and DNA methylation analysis. We show that malignant non-central nervous system tumor growth causes profound molecular alterations in the brain. Mice harbouring triple negative or progesterone positive breast cancer TumorGrafts exhibited altered gene expression, decreased levels of DNA methylation, increased levels of DNA hydroxymethylation, and oxidative stress in the prefrontal cortex. Interestingly, chemotherapy did not have any additional synergistic effects on the analyzed processes. The molecular changes observed in this study are known signs of neurodegeneration and brain aging. This study provides an important roadmap for future large-scale analysis of the molecular and cellular mechanisms of tumor brain. PMID:28758896

Genetic connectivity across marginal habitats: the elephants of the Namib Desert.

PubMed

Ishida, Yasuko; Van Coeverden de Groot, Peter J; Leggett, Keith E A; Putnam, Andrea S; Fox, Virginia E; Lai, Jesse; Boag, Peter T; Georgiadis, Nicholas J; Roca, Alfred L

2016-09-01

Locally isolated populations in marginal habitats may be genetically distinctive and of heightened conservation concern. Elephants inhabiting the Namib Desert have been reported to show distinctive behavioral and phenotypic adaptations in that severely arid environment. The genetic distinctiveness of Namibian desert elephants relative to other African savanna elephant (Loxodonta africana) populations has not been established. To investigate the genetic structure of elephants in Namibia, we determined the mitochondrial (mt) DNA control region sequences and genotyped 17 microsatellite loci in desert elephants (n = 8) from the Hoanib River catchment and the Hoarusib River catchment. We compared these to the genotypes of elephants (n = 77) from other localities in Namibia. The mtDNA haplotype sequences and frequencies among desert elephants were similar to those of elephants in Etosha National Park, the Huab River catchment, the Ugab River catchment, and central Kunene, although the geographically distant Caprivi Strip had different mtDNA haplotypes. Likewise, analysis of the microsatellite genotypes of desert-dwelling elephants revealed that they were not genetically distinctive from Etosha elephants, and there was no evidence for isolation by distance across the Etosha region. These results, and a review of the historical record, suggest that a high learning capacity and long-distance migrations allowed Namibian elephants to regularly shift their ranges to survive in the face of high variability in climate and in hunting pressure.

DNA Methylation Program in Developing Hippocampus and Its Alteration by Alcohol

PubMed Central

Chen, Yuanyuan; Ozturk, Nail Can; Zhou, Feng C.

2013-01-01

During hippocampal development, the Cornus Ammonis (CA) and the dentate gyrus (DG) undergo waves of neurogenesis and neuronal migration and maturation independently. This stage is widely known to be vulnerable to environmental stresses, but its underlying mechanism is unclear. Alcohol exposure has been shown to alter the expression of genes that regulate the fate, survival, migration and differentiation of pyramidal and granule cells. Undermining this process might compromise hippocampal development underlying the learning and memory deficits known in Fetal Alcohol Spectrum Disorders (FASD). We have previously demonstrated that DNA methylation was programmed along with neural tube development. Here, we demonstrated that DNA methylation program (DMP) proceeded along with hippocampal neuronal differentiation and maturation, and how this DMP was affected by fetal alcohol exposure. C57BL/6 mice were treated with 4% v/v ethanol through a liquid diet along with pair-fed and chow-fed controls from gestation day (E) 7 to E16. We found that a characteristic DMP, including 5-methylcytidine (5mC), 5-hydroxylmethylcytidine (5hmC) and their binding proteins, led the hippocampal neuronal differentiation and maturation spatiotemporally as indicated by their phenotypic marks in the CA and DG pre- and post-natally. Alcohol hindered the acquisition and progression of methylation marks, and altered the chromatin translocation of these marks in the nucleus, which was correlated with developmental retardation. PMID:23544149

Mouse model for deficiency of methionine synthase reductase exhibits short-term memory impairment and disturbances in brain choline metabolism.

PubMed

Jadavji, Nafisa M; Bahous, Renata H; Deng, Liyuan; Malysheva, Olga; Grand'maison, Marilyn; Bedell, Barry J; Caudill, Marie A; Rozen, Rima

2014-07-15

Hyperhomocysteinaemia can contribute to cognitive impairment and brain atrophy. MTRR (methionine synthase reductase) activates methionine synthase, which catalyses homocysteine remethylation to methionine. Severe MTRR deficiency results in homocystinuria with cognitive and motor impairments. An MTRR polymorphism may influence homocysteine levels and reproductive outcomes. The goal of the present study was to determine whether mild hyperhomocysteinaemia affects neurological function in a mouse model with Mtrr deficiency. Mtrr+/+, Mtrr+/gt and Mtrrgt/gt mice (3 months old) were assessed for short-term memory, brain volumes and hippocampal morphology. We also measured DNA methylation, apoptosis, neurogenesis, choline metabolites and expression of ChAT (choline acetyltransferase) and AChE (acetylcholinesterase) in the hippocampus. Mtrrgt/gt mice exhibited short-term memory impairment on two tasks. They had global DNA hypomethylation and decreased choline, betaine and acetylcholine levels. Expression of ChAT and AChE was increased and decreased respectively. At 3 weeks of age, they showed increased neurogenesis. In the cerebellum, mutant mice had DNA hypomethylation, decreased choline and increased expression of ChAT. Our work demonstrates that mild hyperhomocysteinaemia is associated with memory impairment. We propose a mechanism whereby a deficiency in methionine synthesis leads to hypomethylation and compensatory disturbances in choline metabolism in the hippocampus. This disturbance affects the levels of acetylcholine, a critical neurotransmitter in learning and memory.

Robust k-mer frequency estimation using gapped k-mers

PubMed Central

Ghandi, Mahmoud; Mohammad-Noori, Morteza

2013-01-01

Oligomers of fixed length, k, commonly known as k-mers, are often used as fundamental elements in the description of DNA sequence features of diverse biological function, or as intermediate elements in the constuction of more complex descriptors of sequence features such as position weight matrices. k-mers are very useful as general sequence features because they constitute a complete and unbiased feature set, and do not require parameterization based on incomplete knowledge of biological mechanisms. However, a fundamental limitation in the use of k-mers as sequence features is that as k is increased, larger spatial correlations in DNA sequence elements can be described, but the frequency of observing any specific k-mer becomes very small, and rapidly approaches a sparse matrix of binary counts. Thus any statistical learning approach using k-mers will be susceptible to noisy estimation of k-mer frequencies once k becomes large. Because all molecular DNA interactions have limited spatial extent, gapped k-mers often carry the relevant biological signal. Here we use gapped k-mer counts to more robustly estimate the ungapped k-mer frequencies, by deriving an equation for the minimum norm estimate of k-mer frequencies given an observed set of gapped k-mer frequencies. We demonstrate that this approach provides a more accurate estimate of the k-mer frequencies in real biological sequences using a sample of CTCF binding sites in the human genome. PMID:23861010

Robust k-mer frequency estimation using gapped k-mers.

PubMed

Ghandi, Mahmoud; Mohammad-Noori, Morteza; Beer, Michael A

2014-08-01

Oligomers of fixed length, k, commonly known as k-mers, are often used as fundamental elements in the description of DNA sequence features of diverse biological function, or as intermediate elements in the constuction of more complex descriptors of sequence features such as position weight matrices. k-mers are very useful as general sequence features because they constitute a complete and unbiased feature set, and do not require parameterization based on incomplete knowledge of biological mechanisms. However, a fundamental limitation in the use of k-mers as sequence features is that as k is increased, larger spatial correlations in DNA sequence elements can be described, but the frequency of observing any specific k-mer becomes very small, and rapidly approaches a sparse matrix of binary counts. Thus any statistical learning approach using k-mers will be susceptible to noisy estimation of k-mer frequencies once k becomes large. Because all molecular DNA interactions have limited spatial extent, gapped k-mers often carry the relevant biological signal. Here we use gapped k-mer counts to more robustly estimate the ungapped k-mer frequencies, by deriving an equation for the minimum norm estimate of k-mer frequencies given an observed set of gapped k-mer frequencies. We demonstrate that this approach provides a more accurate estimate of the k-mer frequencies in real biological sequences using a sample of CTCF binding sites in the human genome.

Cell-free fetal nucleic acid testing: a review of the technology and its applications.

PubMed

Sayres, Lauren C; Cho, Mildred K

2011-07-01

Cell-free fetal nucleic acids circulating in the blood of pregnant women afford the opportunity for early, noninvasive prenatal genetic testing. The predominance of admixed maternal genetic material in circulation demands innovative means for identification and analysis of cell-free fetal DNA and RNA. Techniques using polymerase chain reaction, mass spectrometry, and sequencing have been developed for the purposes of detecting fetal-specific sequences, such as paternally inherited or de novo mutations, or determining allelic balance or chromosome dosage. Clinical applications of these methods include fetal sex determination and blood group typing, which are currently available commercially although not offered routinely in the United States. Other uses of cell-free fetal DNA and RNA being explored are the detection of single-gene disorders, chromosomal abnormalities, and inheritance of parental polymorphisms across the whole fetal genome. The concentration of cell-free fetal DNA may also provide predictive capabilities for pregnancy-associated complications. The roles that cell-free fetal nucleic acid testing assume in the existing framework of prenatal screening and invasive diagnostic testing will depend on factors such as costs, clinical validity and utility, and perceived benefit-risk ratios for different applications. As cell-free fetal DNA and RNA testing continues to be developed and translated, significant ethical, legal, and social questions will arise that will need to be addressed by those with a stake in the use of this technology. Obstetricians & Gynecologists and Family Physicians Learning Objectives: After participating in this activity, physicians should be better able to evaluate techniques and tools for analyzing cell-free fetal nucleic acids, assess clinical applications of prenatal testing, using cell-free fetal nucleic acids and barriers to implementation, and distinguish between relevant clinical features of cell-free fetal nucleic acid testing and existing prenatal genetic screening and diagnostic procedures.

Neurobehavioral changes and alteration of gene expression in the brains of metallothionein-I/II null mice exposed to low levels of mercury vapor during postnatal development.

PubMed

Yoshida, Minoru; Honda, Masako; Watanabe, Chiho; Satoh, Masahiko; Yasutake, Akira

2011-10-01

This study examined the neurobehavioral changes and alteration in gene expression in the brains of metallothionein (MT)-I/II null mice exposed to low-levels of mercury vapor (Hg(0)) during postnatal development. MT-I/II null and wild-type mice were repeatedly exposed to Hg(0) at 0.030 mg/m(3) (range: 0.023-0.043 mg/m(3)), which was similar to the current threshold value (TLV), for 6 hr per day until the 20th day postpartum. The behavioral effects were evaluated with locomotor activity in the open field (OPF), learning ability in the passive avoidance response (PA) and spatial learning ability in the Morris water maze (MM) at 12 weeks of age. Hg(0)-exposed MT-I/II null mice showed a significant decrease in total locomotor activity in females, though learning ability and spatial learning ability were not affected. Immediately after Hg(0) exposure, mercury concentrations in the brain did not exceed 0.5 µg/g in any animals. Hg(0) exposure resulted in significant alterations in gene expression in the brains of both strains using DNA microarray analysis. The number of altered genes in MT-I/II null mice was higher than that in wild-type mice and calcium-calmodulin kinase II (Camk2a) involved in learning and memory in down-regulated genes was detected. These results provide useful information to elucidate the development of behavioral toxicity following low-level exposure to Hg(0).

Active learning in the lecture theatre using 3D printed objects.

PubMed

Smith, David P

2016-01-01

The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme's active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student.

Benefits and Limitations of Online Instruction in Natural Science Undergraduate Liberal Arts Courses

NASA Astrophysics Data System (ADS)

Liddicoat, Joseph; Roberts, Godfrey; Liddicoat, Kendra; Porzecanski, Ana Luz; Mendez, Martin; McMullen, David

2013-04-01

Online courses in the Natural Sciences are taught three ways at New York University to undergraduate students majoring in the liberal arts and professional programs - synchronous courses in which students communicate online with the instructor and classmates in real time, asynchronous courses when faculty present course material for students to access and learn at their leisure, and hybrid or blended courses when part is taught asynchronously and part is taught face-to-face in a classroom with all students present. We have done online courses each way - Global Ecology (synchronous); Stars, Planets, and Life (synchronous and asynchronous); Darwin to DNA: An Overview of Evolution (asynchronous); Biodiversity Conservation (asynchronous); and Biology of Hunger and Population (blended). We will present the advantages and challenges we experienced teaching courses online in this fashion. Besides the advantages listed in the description for this session, another can be programmed learning that allows a set of sequential steps or a more complex branching of steps that allows students to repeat lessons multiple times to master the material. And from an academic standpoint, course content and assessment can be standardized, making it possible for each student to learn the same material. Challenges include resistance to online learning by a host of stakeholders who might be educators, students, parents, and the community. Equally challenging might be the readiness of instructors and students to teach and learn online. Student integrity issues such as plagiarism and cheating are a concern in a course taught online (Thormann and Zimmerman, 2012), so we will discuss our strategies to mitigate them.

Active learning in the lecture theatre using 3D printed objects

PubMed Central

Smith, David P.

2016-01-01

The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme’s active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student. PMID:27366318

“I think we’ve got too many tests!”: Prenatal providers’ reflections on ethical and clinical challenges in the practice integration of cell-free DNA screening

PubMed Central

Gammon, B.L.; Kraft, S.A.; Michie, M.; Allyse, M.

2016-01-01

Background The recent introduction of cell-free DNA-based non-invasive prenatal screening (cfDNA screening) into clinical practice was expected to revolutionize prenatal testing. cfDNA screening for fetal aneuploidy has demonstrated higher test sensitivity and specificity for some conditions than conventional serum screening and can be conducted early in the pregnancy. However, it is not clear whether and how clinical practices are assimilating this new type of testing into their informed consent and counselling processes. Since the introduction of cfDNA screening into practice in 2011, the uptake and scope have increased dramatically. Prenatal care providers are under pressure to stay up to date with rapidly changing cfDNA screening panels, manage increasing patient demands, and keep up with changing test costs, all while attempting to use the technology responsibly and ethically. While clinical literature on cfDNA screening has shown benefits for specific patient populations, it has also identified significant misunderstandings among providers and patients alike about the power of the technology. The unique features of cfDNA screening, in comparison to established prenatal testing technologies, have implications for informed decision-making and genetic counselling that must be addressed to ensure ethical practice. Objectives This study explored the experiences of prenatal care providers at the forefront of non-invasive genetic screening in the United States to understand how this testing changes the practice of prenatal medicine. We aimed to learn how the experience of providing and offering this testing differs from established prenatal testing methodologies. These differences may necessitate changes to patient education and consent procedures to maintain ethical practice. Methods We used the online American Congress of Obstetricians and Gynecologists Physician Directory to identify a systematic sample of five prenatal care providers in each U.S. state and the District of Columbia. Beginning with the lowest zip code in each state, we took every fifth name from the directory, excluding providers who were retired, did not currently practice in the state in which they were listed, or were not involved in a prenatal specialty. After repeating this step twice and sending a total of 461 invitations, 37 providers expressed interest in participating, and we completed telephone interviews with 21 providers (4.6%). We developed a semi-structured interview guide including questions about providers’ use of and attitudes toward cfDNA screening. A single interviewer conducted and audio-recorded all interviews by telephone, and the interviews lasted approximately 30 minutes each. We collaboratively developed a codebook through an iterative process of transcript review and code application, and a primary coder coded all transcripts. Results Prenatal care providers have varying perspectives on the advantages of cfDNA screening and express a range of concerns regarding the implementation of cfDNA screening in practice. While providers agreed on several advantages of cfDNA, including increased accuracy, earlier return of results, and decreased risk of complications, many expressed concern that there is not enough time to adequately counsel and educate patients on their prenatal screening and testing options. Providers also agreed that demand for cfDNA screening has increased and expressed a desire for more information from professional societies, labs, and publications. Providers disagreed about the healthcare implications and future of cfDNA screening. Some providers anticipated that cfDNA screening would decrease healthcare costs when implemented widely and expressed optimism for expanded cfDNA screening panels. Others were concerned that cfDNA screening would increase costs over time and questioned whether the expansion to include microdeletions could be done ethically. Conclusions The perspectives and experiences of the providers in this study allow insight into the clinical benefit, burden on prenatal practice, and potential future of cfDNA screening in clinical practice. Given the likelihood that the scope and uptake of cfDNA screening will continue to increase, it is essential to consider how these changes will affect frontline prenatal care providers and, in turn, patients. Providers’ requests for additional guidance and data as well as their concerns with the lack of time available to explain screening and testing options indicate significant potential issues with patient care. It is important to ensure that the clinical integration of cfDNA screening is managed responsibly and ethically before it expands further, exacerbating pre-existing issues. As prenatal screening evolves, so should informed consent and the resources available to women making decisions. The field must take steps to maximize the advantages of cfDNA screening and responsibly manage its ethical issues. PMID:28180146

"I think we've got too many tests!": Prenatal providers' reflections on ethical and clinical challenges in the practice integration of cell-free DNA screening.

PubMed

Gammon, B L; Kraft, S A; Michie, M; Allyse, M

2016-01-01

The recent introduction of cell-free DNA-based non-invasive prenatal screening (cfDNA screening) into clinical practice was expected to revolutionize prenatal testing. cfDNA screening for fetal aneuploidy has demonstrated higher test sensitivity and specificity for some conditions than conventional serum screening and can be conducted early in the pregnancy. However, it is not clear whether and how clinical practices are assimilating this new type of testing into their informed consent and counselling processes. Since the introduction of cfDNA screening into practice in 2011, the uptake and scope have increased dramatically. Prenatal care providers are under pressure to stay up to date with rapidly changing cfDNA screening panels, manage increasing patient demands, and keep up with changing test costs, all while attempting to use the technology responsibly and ethically. While clinical literature on cfDNA screening has shown benefits for specific patient populations, it has also identified significant misunderstandings among providers and patients alike about the power of the technology. The unique features of cfDNA screening, in comparison to established prenatal testing technologies, have implications for informed decision-making and genetic counselling that must be addressed to ensure ethical practice. This study explored the experiences of prenatal care providers at the forefront of non-invasive genetic screening in the United States to understand how this testing changes the practice of prenatal medicine. We aimed to learn how the experience of providing and offering this testing differs from established prenatal testing methodologies. These differences may necessitate changes to patient education and consent procedures to maintain ethical practice. We used the online American Congress of Obstetricians and Gynecologists Physician Directory to identify a systematic sample of five prenatal care providers in each U.S. state and the District of Columbia. Beginning with the lowest zip code in each state, we took every fifth name from the directory, excluding providers who were retired, did not currently practice in the state in which they were listed, or were not involved in a prenatal specialty. After repeating this step twice and sending a total of 461 invitations, 37 providers expressed interest in participating, and we completed telephone interviews with 21 providers (4.6%). We developed a semi-structured interview guide including questions about providers' use of and attitudes toward cfDNA screening. A single interviewer conducted and audio-recorded all interviews by telephone, and the interviews lasted approximately 30 minutes each. We collaboratively developed a codebook through an iterative process of transcript review and code application, and a primary coder coded all transcripts. Prenatal care providers have varying perspectives on the advantages of cfDNA screening and express a range of concerns regarding the implementation of cfDNA screening in practice. While providers agreed on several advantages of cfDNA, including increased accuracy, earlier return of results, and decreased risk of complications, many expressed concern that there is not enough time to adequately counsel and educate patients on their prenatal screening and testing options. Providers also agreed that demand for cfDNA screening has increased and expressed a desire for more information from professional societies, labs, and publications. Providers disagreed about the healthcare implications and future of cfDNA screening. Some providers anticipated that cfDNA screening would decrease healthcare costs when implemented widely and expressed optimism for expanded cfDNA screening panels. Others were concerned that cfDNA screening would increase costs over time and questioned whether the expansion to include microdeletions could be done ethically. The perspectives and experiences of the providers in this study allow insight into the clinical benefit, burden on prenatal practice, and potential future of cfDNA screening in clinical practice. Given the likelihood that the scope and uptake of cfDNA screening will continue to increase, it is essential to consider how these changes will affect frontline prenatal care providers and, in turn, patients. Providers' requests for additional guidance and data as well as their concerns with the lack of time available to explain screening and testing options indicate significant potential issues with patient care. It is important to ensure that the clinical integration of cfDNA screening is managed responsibly and ethically before it expands further, exacerbating pre-existing issues. As prenatal screening evolves, so should informed consent and the resources available to women making decisions. The field must take steps to maximize the advantages of cfDNA screening and responsibly manage its ethical issues.

Genome engineering with TALENs and ZFNs: repair pathways and donor design.

PubMed

Carroll, Dana; Beumer, Kelly J

2014-09-01

Genome engineering with targetable nucleases depends on cellular pathways of DNA repair after target cleavage. Knowledge of how those pathways work, their requirements and their active factors, can guide experimental design and improve outcomes. While many aspects of both homologous recombination (HR) and nonhomologous end joining (NHEJ) are shared by a broad range of cells and organisms, some features are specific to individual situations. This article reviews the influence of repair mechanisms on the results of gene targeting experiments, with an emphasis on lessons learned from experiments with Drosophila. Copyright © 2014 Elsevier Inc. All rights reserved.

Genetics of Human Cardiovascular Disease

PubMed Central

Kathiresan, Sekar; Srivastava, Deepak

2012-01-01

Cardiovascular disease encompasses a range of conditions extending from myocardial infarction to congenital heart disease most of which are heritable. Enormous effort has been invested in understanding the genes and specific DNA sequence variants responsible for this heritability. Here, we review the lessons learned for monogenic and common, complex forms of cardiovascular disease. We also discuss key challenges that remain for gene discovery and for moving from genomic localization to mechanistic insights with an emphasis on the impact of next generation sequencing and the use of pluripotent human cells to understand the mechanism by which genetic variation contributes to disease. PMID:22424232

The Science and Issues of Human DNA Polymorphisms: A Training Workshop for High School Biology Teachers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Micklos, David A.

2006-10-30

This project achieved its goal of implementing a nationwide training program to introduce high school biology teachers to the key uses and societal implications of human DNA polymorphisms. The 2.5-day workshop introduced high school biology faculty to a laboratory-based unit on human DNA polymorphisms â which provides a uniquely personal perspective on the science and Ethical, Legal and Social Implications (ELSI) of the Human Genome Project. As proposed, 12 workshops were conducted at venues across the United States. The workshops were attended by 256 high school faculty, exceeding proposed attendance of 240 by 7%. Each workshop mixed theoretical, laboratory, andmore » computer work with practical and ethical implications. Program participants learned simplified lab techniques for amplifying three types of chromosomal polymorphisms: an Alu insertion (PV92), a VNTR (pMCT118/D1S80), and single nucleotide polymorphisms (SNPs) in the mitochondrial control region. These polymorphisms illustrate the use of DNA variations in disease diagnosis, forensic biology, and identity testing - and provide a starting point for discussing the uses and potential abuses of genetic technology. Participants also learned how to use their Alu and mitochondrial data as an entrée to human population genetics and evolution. Our work to simplify lab techniques for amplifying human DNA polymorphisms in educational settings culminated with the release in 1998 of three Advanced Technology (AT) PCR kits by Carolina Biological Supply Company, the nationâÂÂs oldest educational science supplier. The kits use a simple 30-minute method to isolate template DNA from hair sheaths or buccal cells and streamlined PCR chemistry based on Pharmacia Ready-To-Go Beads, which incorporate Taq polymerase, deoxynucleotide triphosphates, and buffer in a freeze-dried pellet. These kits have greatly simplified teacher implementation of human PCR labs, and their use is growing at a rapid pace. Sales of human polymorphism kits by Carolina Biological rose from 700 units in 1999 to 1,132 in 2000 â a 62% increase. Competing kits using the Alu system, and based substantially on our earlier work, are also marketed by Biorad and Edvotek. In parallel with the lab experiments, we developed a suite of database/statistical applications and easy-to-use interfaces that allow students to use their own DNA data to explore human population genetics and to test theories of human evolution. Database searches and statistical analyses are launched from a centralized workspace. Workshop participants were introduced to these and other resources available at the DNALC WWW site (http://vector.cshl.org/bioserver/): 1) Allele Server tests Hardy-Weinberg equilibrium and statistically compares PV92 data from world populations. 2) Sequence Server uses DNA sequence data to search Genbank using BLASTN, compare sequences using CLUSTALW, and create phylogenetic trees using PHYLIP. 3) Simulation Server uses a Monte Carlo generator to model the long-term effects of drift, selection, and population bottlenecks. By targeting motivated and innovative biology faculty, we believe that this project offered a cost-effective means to bring high school biology education up-to-the-minute with genomic biology. The workshop reached a target audience of highly professional faculty who have already implemented hands-on labs in molecular genetics and many of whom offer laboratory electives in biotechnology. Many attend professional meetings, develop curriculum, collaborate with scientists, teach faculty workshops, and manage equipment-sharing programs. These individuals are life-long learners, anxious for deeper insight and additional training to further extend their leadership. This contention was supported by data from a mail survey, conducted in February-March 2000 and 2001, of 256 faculty who participated in workshops conducted during the current term of DOE support. Seventy percent of participants responded, providing direct reports on how their teaching behavior had changed since taking the DOE workshop. About nine of ten respondents said they had provided new classroom materials and first-hand accounts of DNA typing, sequencing, or PCR. Three-fourths had introduced new units on human molecular genetics. Most strikingly, half had students use PCR to amplify their own insertion polymorphisms (PV92), and better than one-fourth amplified a VNTR polymorphism and the mitochondrial control region. One in five had mitochondrial DNA sequenced by the DNALC Sequencing Service. A majority (58%) used online materials at the DNALC WWW site, and 28% analyzed student polymorphism data with Bioservers at the DNALC site. A majority (58%) assisted other faculty with student labs on polymorphisms, reaching an additional 786 teachers.« less

The Science and Issues of Human DNA Polymoprhisms: A Training Workshop for High School Biology Teachers

DOE Office of Scientific and Technical Information (OSTI.GOV)

David. A Micklos

2006-10-30

This project achieved its goal of implementing a nationwide training program to introduce high school biology teachers to the key uses and societal implications of human DNA polymorphisms. The 2.5-day workshop introduced high school biology faculty to a laboratory-based unit on human DNA polymorphisms – which provides a uniquely personal perspective on the science and Ethical, Legal and Social Implications (ELSI) of the Human Genome Project. As proposed, 12 workshops were conducted at venues across the United States. The workshops were attended by 256 high school faculty, exceeding proposed attendance of 240 by 7%. Each workshop mixed theoretical, laboratory, andmore » computer work with practical and ethical implications. Program participants learned simplified lab techniques for amplifying three types of chromosomal polymorphisms: an Alu insertion (PV92), a VNTR (pMCT118/D1S80), and single nucleotide polymorphisms (SNPs) in the mitochondrial control region. These polymorphisms illustrate the use of DNA variations in disease diagnosis, forensic biology, and identity testing - and provide a starting point for discussing the uses and potential abuses of genetic technology. Participants also learned how to use their Alu and mitochondrial data as an entrée to human population genetics and evolution. Our work to simplify lab techniques for amplifying human DNA polymorphisms in educational settings culminated with the release in 1998 of three Advanced Technology (AT) PCR kits by Carolina Biological Supply Company, the nation’s oldest educational science supplier. The kits use a simple 30-minute method to isolate template DNA from hair sheaths or buccal cells and streamlined PCR chemistry based on Pharmacia Ready-To-Go Beads, which incorporate Taq polymerase, deoxynucleotide triphosphates, and buffer in a freeze-dried pellet. These kits have greatly simplified teacher implementation of human PCR labs, and their use is growing at a rapid pace. Sales of human polymorphism kits by Carolina Biological rose from 700 units in 1999 to 1,132 in 2000 – a 62% increase. Competing kits using the Alu system, and based substantially on our earlier work, are also marketed by Biorad and Edvotek. In parallel with the lab experiments, we developed a suite of database/statistical applications and easy-to-use interfaces that allow students to use their own DNA data to explore human population genetics and to test theories of human evolution. Database searches and statistical analyses are launched from a centralized workspace. Workshop participants were introduced to these and other resources available at the DNALC WWW site (http://vector.cshl.org/bioserver/): 1) Allele Server tests Hardy-Weinberg equilibrium and statistically compares PV92 data from world populations. 2) Sequence Server uses DNA sequence data to search Genbank using BLASTN, compare sequences using CLUSTALW, and create phylogenetic trees using PHYLIP. 3) Simulation Server uses a Monte Carlo generator to model the long-term effects of drift, selection, and population bottlenecks. By targeting motivated and innovative biology faculty, we believe that this project offered a cost-effective means to bring high school biology education up-to-the-minute with genomic biology. The workshop reached a target audience of highly professional faculty who have already implemented hands-on labs in molecular genetics and many of whom offer laboratory electives in biotechnology. Many attend professional meetings, develop curriculum, collaborate with scientists, teach faculty workshops, and manage equipment-sharing programs. These individuals are life-long learners, anxious for deeper insight and additional training to further extend their leadership. This contention was supported by data from a mail survey, conducted in February-March 2000 and 2001, of 256 faculty who participated in workshops conducted during the current term of DOE support. Seventy percent of participants responded, providing direct reports on how their teaching behavior had changed since taking the DOE workshop. About nine of ten respondents said they had provided new classroom materials and first-hand accounts of DNA typing, sequencing, or PCR. Three-fourths had introduced new units on human molecular genetics. Most strikingly, half had students use PCR to amplify their own insertion polymorphisms (PV92), and better than one-fourth amplified a VNTR polymorphism and the mitochondrial control region. One in five had mitochondrial DNA sequenced by the DNALC Sequencing Service. A majority (58%) used online materials at the DNALC WWW site, and 28% analyzed student polymorphism data with Bioservers at the DNALC site. A majority (58%) assisted other faculty with student labs on polymorphisms, reaching an additional 786 teachers.« less

Mutation and repair induced by the carcinogen 2-(hydroxyamino)-1-methyl-6-phenylimidazo[4,5-b]pyridine (N-OH-PhIP) in the dihydrofolate reductase gene of Chinese hamster ovary cells and conformational modeling of the dG-C8-PhIP adduct in DNA.

PubMed

Carothers, A M; Yuan, W; Hingerty, B E; Broyde, S; Grunberger, D; Snyderwine, E G

1994-01-01

Three experiments using 20 microM 2-(hydroxyamino)-1-methyl-6-phenylimidazo[4,5-b]pyridine (N-OH-PhIP) were performed to induce mutations in the dihydrofolate reductase (DHFR) gene of a hemizygous Chinese hamster ovary (CHO) cell line (UA21). Metabolized forms of this chemical primarily bind at the C-8 position of guanine in DNA. In total, 21 independent induced mutants were isolated and 20 were characterized. DNA sequencing showed that the preferred mutation type found in 75% of the induced DHFR- clones was G.C-->T.A single and tandem double transversions. In addition to base substitutions, one mutant carried a-1 frameshift and another one had lost the entire locus by deletion. The induced changes affected purine targets on the nontranscribed strand of the gene in nearly all of the mutants sequenced (18/19). At the time that the first two experiments were performed, the initial adduct levels were quantitated in treated cells at the mutagenic dose by 32P-postlabeling. While the induced frequency of mutation was relatively low (approximately 5 x 10(-6), the adduct levels after a 1-h exposure of UA21 cells to 20 microM N-OH-PhIP were relatively high (13 adducts x 10(-6) nucleotides). This latter method was then employed to learn if the induced mutation frequency correlated with rapid overall genome repair of PhIP-DNA adducts. Total adduct levels, determined using DNA samples from treated cells collected after intervals of time, were reduced by about 50% after 6 h, and about 70% after 24 h. Since overall genome repair in CHO cells is relatively slow compared with preferential gene repair, the removal of dG-C8-PhIP adducts was apparently efficient. In order to better understand the mutational and repair results, we performed computational modeling to determine the lowest energy structure for the major dG-C8-PhIP adduct in a repetitively mutated duplex sequence opposite dA. Results of this analysis indicate that the PhIP-modified base resembles previous structural determinations of (deoxyguanosin-8-yl)-aminofluorene; the carcinogen is in the B-DNA minor groove and its adopts a syn conformation mispaired with an anti A. The implications of this conformational distortion in DNA structure for damage recognition by cellular repair enzymes are discussed.

Lessons Learned from Autopsying an Unidentified Body with Iodine-125 Seeds Implanted for Prostate Brachytherapy.

PubMed

Idota, Nozomi; Nakamura, Mami; Masui, Koji; Kakiuchi, Yasuhiro; Yamada, Kei; Ikegaya, Hiroshi

2017-03-01

We report here lessons learned from an autopsy case involving radioactive materials. We performed an autopsy of an unidentified mummified man with no available medical history whom from imaging findings we suspected had received radioactive seed implants for prostate brachytherapy. We returned the excised prostate and seeds to the body. A few days later, the body was identified by DNA matching and cremated. According to the man's medical record, he had undergone iodine-125 seeds implantation for prostate cancer 11 months earlier. We should have removed the radioactive seeds from the body to prevent radiation exposure to the bereaved family and/or environmental pollution due to cremation. Surprisingly, one seed was found in the stored prostate specimen. Forensic experts should be cognizant of the risk of both radiation exposure in the autopsy room and environmental pollution. We must remain abreast of the latest advances in medicine. © 2016 American Academy of Forensic Sciences.

Self-Organizing Hidden Markov Model Map (SOHMMM).

PubMed

Ferles, Christos; Stafylopatis, Andreas

2013-12-01

A hybrid approach combining the Self-Organizing Map (SOM) and the Hidden Markov Model (HMM) is presented. The Self-Organizing Hidden Markov Model Map (SOHMMM) establishes a cross-section between the theoretic foundations and algorithmic realizations of its constituents. The respective architectures and learning methodologies are fused in an attempt to meet the increasing requirements imposed by the properties of deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and protein chain molecules. The fusion and synergy of the SOM unsupervised training and the HMM dynamic programming algorithms bring forth a novel on-line gradient descent unsupervised learning algorithm, which is fully integrated into the SOHMMM. Since the SOHMMM carries out probabilistic sequence analysis with little or no prior knowledge, it can have a variety of applications in clustering, dimensionality reduction and visualization of large-scale sequence spaces, and also, in sequence discrimination, search and classification. Two series of experiments based on artificial sequence data and splice junction gene sequences demonstrate the SOHMMM's characteristics and capabilities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Cocaine Directly Impairs Memory Extinction and Alters Brain DNA Methylation Dynamics in Honey Bees.

PubMed

Søvik, Eirik; Berthier, Pauline; Klare, William P; Helliwell, Paul; Buckle, Edwina L S; Plath, Jenny A; Barron, Andrew B; Maleszka, Ryszard

2018-01-01

Drug addiction is a chronic relapsing behavioral disorder. The high relapse rate has often been attributed to the perseverance of drug-associated memories due to high incentive salience of stimuli learnt under the influence of drugs. Drug addiction has also been interpreted as a memory disorder since drug associated memories are unusually enduring and some drugs, such as cocaine, interfere with neuroepigenetic machinery known to be involved in memory processing. Here we used the honey bee (an established invertebrate model for epigenomics and behavioral studies) to examine whether or not cocaine affects memory processing independently of its effect on incentive salience. Using the proboscis extension reflex training paradigm we found that cocaine strongly impairs consolidation of extinction memory. Based on correlation between the observed effect of cocaine on learning and expression of epigenetic processes, we propose that cocaine interferes with memory processing independently of incentive salience by directly altering DNA methylation dynamics. Our findings emphasize the impact of cocaine on memory systems, with relevance for understanding how cocaine can have such an enduring impact on behavior.

Cocaine Directly Impairs Memory Extinction and Alters Brain DNA Methylation Dynamics in Honey Bees

PubMed Central

Søvik, Eirik; Berthier, Pauline; Klare, William P.; Helliwell, Paul; Buckle, Edwina L. S.; Plath, Jenny A.; Barron, Andrew B.; Maleszka, Ryszard

2018-01-01

Drug addiction is a chronic relapsing behavioral disorder. The high relapse rate has often been attributed to the perseverance of drug-associated memories due to high incentive salience of stimuli learnt under the influence of drugs. Drug addiction has also been interpreted as a memory disorder since drug associated memories are unusually enduring and some drugs, such as cocaine, interfere with neuroepigenetic machinery known to be involved in memory processing. Here we used the honey bee (an established invertebrate model for epigenomics and behavioral studies) to examine whether or not cocaine affects memory processing independently of its effect on incentive salience. Using the proboscis extension reflex training paradigm we found that cocaine strongly impairs consolidation of extinction memory. Based on correlation between the observed effect of cocaine on learning and expression of epigenetic processes, we propose that cocaine interferes with memory processing independently of incentive salience by directly altering DNA methylation dynamics. Our findings emphasize the impact of cocaine on memory systems, with relevance for understanding how cocaine can have such an enduring impact on behavior. PMID:29487536

Genomic and Molecular Landscape of DNA Damage Repair Deficiency across The Cancer Genome Atlas.

PubMed

Knijnenburg, Theo A; Wang, Linghua; Zimmermann, Michael T; Chambwe, Nyasha; Gao, Galen F; Cherniack, Andrew D; Fan, Huihui; Shen, Hui; Way, Gregory P; Greene, Casey S; Liu, Yuexin; Akbani, Rehan; Feng, Bin; Donehower, Lawrence A; Miller, Chase; Shen, Yang; Karimi, Mostafa; Chen, Haoran; Kim, Pora; Jia, Peilin; Shinbrot, Eve; Zhang, Shaojun; Liu, Jianfang; Hu, Hai; Bailey, Matthew H; Yau, Christina; Wolf, Denise; Zhao, Zhongming; Weinstein, John N; Li, Lei; Ding, Li; Mills, Gordon B; Laird, Peter W; Wheeler, David A; Shmulevich, Ilya; Monnat, Raymond J; Xiao, Yonghong; Wang, Chen

2018-04-03

DNA damage repair (DDR) pathways modulate cancer risk, progression, and therapeutic response. We systematically analyzed somatic alterations to provide a comprehensive view of DDR deficiency across 33 cancer types. Mutations with accompanying loss of heterozygosity were observed in over 1/3 of DDR genes, including TP53 and BRCA1/2. Other prevalent alterations included epigenetic silencing of the direct repair genes EXO5, MGMT, and ALKBH3 in ∼20% of samples. Homologous recombination deficiency (HRD) was present at varying frequency in many cancer types, most notably ovarian cancer. However, in contrast to ovarian cancer, HRD was associated with worse outcomes in several other cancers. Protein structure-based analyses allowed us to predict functional consequences of rare, recurrent DDR mutations. A new machine-learning-based classifier developed from gene expression data allowed us to identify alterations that phenocopy deleterious TP53 mutations. These frequent DDR gene alterations in many human cancers have functional consequences that may determine cancer progression and guide therapy. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Sleep Deprivation and the Epigenome.

PubMed

Gaine, Marie E; Chatterjee, Snehajyoti; Abel, Ted

2018-01-01

Sleep deprivation disrupts the lives of millions of people every day and has a profound impact on the molecular biology of the brain. These effects begin as changes within a neuron, at the DNA and RNA level, and result in alterations in neuronal plasticity and dysregulation of many cognitive functions including learning and memory. The epigenome plays a critical role in regulating gene expression in the context of memory storage. In this review article, we begin by describing the effects of epigenetic alterations on the regulation of gene expression, focusing on the most common epigenetic mechanisms: (i) DNA methylation; (ii) histone modifications; and (iii) non-coding RNAs. We then discuss evidence suggesting that sleep loss impacts the epigenome and that these epigenetic alterations might mediate the changes in cognition seen following disruption of sleep. The link between sleep and the epigenome is only beginning to be elucidated, but clear evidence exists that epigenetic alterations occur following sleep deprivation. In the future, these changes to the epigenome could be utilized as biomarkers of sleep loss or as therapeutic targets for sleep-related disorders.

Rett Syndrome Mutation MeCP2 T158A Disrupts DNA Binding, Protein Stability and ERP Responses

PubMed Central

Goffin, Darren; Allen, Megan; Zhang, Le; Amorim, Maria; Wang, I-Ting Judy; Reyes, Arith-Ruth S.; Mercado-Berton, Amy; Ong, Caroline; Cohen, Sonia; Hu, Linda; Blendy, Julie A.; Carlson, Gregory C.; Siegel, Steve J.; Greenberg, Michael E.; Zhou, Zhaolan (Joe)

2011-01-01

Mutations in the MECP2 gene cause the autism spectrum disorder Rett Syndrome (RTT). One of the most common mutations associated with RTT occurs at MeCP2 Threonine 158 converting it to Methionine (T158M) or Alanine (T158A). To understand the role of T158 mutation in the pathogenesis of RTT, we generated knockin mice recapitulating MeCP2 T158A mutation. Here we show a causal role for T158A mutation in the development of RTT-like phenotypes including developmental regression, motor dysfunction, and learning and memory deficits. These phenotypes resemble those in Mecp2-null mice and manifest through a reduction in MeCP2 binding to methylated DNA and a decrease in MeCP2 protein stability. Importantly, the age-dependent development of event-related neuronal responses are disrupted by MeCP2 mutation, suggesting that impaired neuronal circuitry underlies the pathogenesis of RTT and that assessment of event-related potentials may serve as a biomarker for RTT and treatment evaluation. PMID:22119903

Applied spectrophotometry: analysis of a biochemical mixture.

PubMed

Trumbo, Toni A; Schultz, Emeric; Borland, Michael G; Pugh, Michael Eugene

2013-01-01

Spectrophotometric analysis is essential for determining biomolecule concentration of a solution and is employed ubiquitously in biochemistry and molecular biology. The application of the Beer-Lambert-Bouguer Lawis routinely used to determine the concentration of DNA, RNA or protein. There is however a significant difference in determining the concentration of a given species (RNA, DNA, protein) in isolation (a contrived circumstance) as opposed to determining that concentration in the presence of other species (a more realistic situation). To present the student with a more realistic laboratory experience and also to fill a hole that we believe exists in student experience prior to reaching a biochemistry course, we have devised a three week laboratory experience designed so that students learn to: connect laboratory practice with theory, apply the Beer-Lambert-Bougert Law to biochemical analyses, demonstrate the utility and limitations of example quantitative colorimetric assays, demonstrate the utility and limitations of UV analyses for biomolecules, develop strategies for analysis of a solution of unknown biomolecular composition, use digital micropipettors to make accurate and precise measurements, and apply graphing software. Copyright © 2013 Wiley Periodicals, Inc.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buckner, Mark A; Bobrek, Miljko; Farquhar, Ethan

Wireless Access Points (WAP) remain one of the top 10 network security threats. This research is part of an effort to develop a physical (PHY) layer aware Radio Frequency (RF) air monitoring system with multi-factor authentication to provide a first-line of defense for network security--stopping attackers before they can gain access to critical infrastructure networks through vulnerable WAPs. This paper presents early results on the identification of OFDM-based 802.11a WiFi devices using RF Distinct Native Attribute (RF-DNA) fingerprints produced by the Fractional Fourier Transform (FRFT). These fingerprints are input to a "Learning from Signals" (LFS) classifier which uses hybrid Differentialmore » Evolution/Conjugate Gradient (DECG) optimization to determine the optimal features for a low-rank model to be used for future predictions. Results are presented for devices under the most challenging conditions of intra-manufacturer classification, i.e., same-manufacturer, same-model, differing only in serial number. The results of Fractional Fourier Domain (FRFD) RF-DNA fingerprints demonstrate significant improvement over results based on Time Domain (TD), Spectral Domain (SD) and even Wavelet Domain (WD) fingerprints.« less

Classifying chemical mode of action using gene networks and machine learning: a case study with the herbicide linuron.

PubMed

Ornostay, Anna; Cowie, Andrew M; Hindle, Matthew; Baker, Christopher J O; Martyniuk, Christopher J

2013-12-01

The herbicide linuron (LIN) is an endocrine disruptor with an anti-androgenic mode of action. The objectives of this study were to (1) improve knowledge of androgen and anti-androgen signaling in the teleostean ovary and to (2) assess the ability of gene networks and machine learning to classify LIN as an anti-androgen using transcriptomic data. Ovarian explants from vitellogenic fathead minnows (FHMs) were exposed to three concentrations of either 5α-dihydrotestosterone (DHT), flutamide (FLUT), or LIN for 12h. Ovaries exposed to DHT showed a significant increase in 17β-estradiol (E2) production while FLUT and LIN had no effect on E2. To improve understanding of androgen receptor signaling in the ovary, a reciprocal gene expression network was constructed for DHT and FLUT using pathway analysis and these data suggested that steroid metabolism, translation, and DNA replication are processes regulated through AR signaling in the ovary. Sub-network enrichment analysis revealed that FLUT and LIN shared more regulated gene networks in common compared to DHT. Using transcriptomic datasets from different fish species, machine learning algorithms classified LIN successfully with other anti-androgens. This study advances knowledge regarding molecular signaling cascades in the ovary that are responsive to androgens and anti-androgens and provides proof of concept that gene network analysis and machine learning can classify priority chemicals using experimental transcriptomic data collected from different fish species. © 2013.

Global structure–activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors

PubMed Central

Cunningham, Albert R.; Trent, John O.

2012-01-01

Structure–activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins. Two learning sets were developed. One set was from the Carcinogenic Potency Database, where chemicals tested for rat carcinogenesis along with Salmonella mutagenicity data were provided. The second was from Malacarne et al. who developed a learning set of nonalerting compounds based on rodent cancer bioassay data and Ashby’s structural alerts. When the rat cancer models were categorized based on mutagenicity, the traditional fragment model outperformed the ligand-based model. However, when the learning sets were composed solely of nonmutagenic or nonalerting carcinogens and noncarcinogens, the fragment model demonstrated a concordance of near 50%, whereas the ligand-based models demonstrated a concordance of 71% for nonmutagenic carcinogens and 74% for nonalerting carcinogens. Overall, these findings suggest that expert system analysis of virtual chemical protein interactions may be useful for developing predictive SAR models for nonmutagenic carcinogens. Moreover, a more practical approach for developing SAR models for carcinogenesis may include fragment-based models for chemicals testing positive for mutagenicity and ligand-based models for chemicals devoid of DNA reactivity. PMID:22678118

Regulation of BDNF chromatin status and promoter accessibility in a neural correlate of associative learning

PubMed Central

Ambigapathy, Ganesh; Zheng, Zhaoqing; Keifer, Joyce

2015-01-01

Brain-derived neurotrophic factor (BDNF) gene expression critically controls learning and its aberrant regulation is implicated in Alzheimer's disease and a host of neurodevelopmental disorders. The BDNF gene is target of known DNA regulatory mechanisms but details of its activity-dependent regulation are not fully characterized. We performed a comprehensive analysis of the epigenetic regulation of the turtle BDNF gene (tBDNF) during a neural correlate of associative learning using an in vitro model of eye blink classical conditioning. Shortly after conditioning onset, the results from ChIP-qPCR show conditioning-dependent increases in methyl-CpG-binding protein 2 (MeCP2) and repressor basic helix-loop-helix binding protein 2 (BHLHB2) binding to tBDNF promoter II that corresponds with transcriptional repression. In contrast, enhanced binding of ten-eleven translocation protein 1 (Tet1), extracellular signal-regulated kinase 1/2 (ERK1/2), and cAMP response element-binding protein (CREB) to promoter III corresponds with transcriptional activation. These actions are accompanied by rapid modifications in histone methylation and phosphorylation status of RNA polymerase II (RNAP II). Significantly, these remarkably coordinated changes in epigenetic factors for two alternatively regulated tBDNF promoters during conditioning are controlled by Tet1 and ERK1/2. Our findings indicate that Tet1 and ERK1/2 are critical partners that, through complementary functions, control learning-dependent tBDNF promoter accessibility required for rapid transcription and acquisition of classical conditioning. PMID:26336984

Global structure-activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors.

PubMed

Cunningham, Albert R; Carrasquer, C Alex; Qamar, Shahid; Maguire, Jon M; Cunningham, Suzanne L; Trent, John O

2012-10-01

Structure-activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins. Two learning sets were developed. One set was from the Carcinogenic Potency Database, where chemicals tested for rat carcinogenesis along with Salmonella mutagenicity data were provided. The second was from Malacarne et al. who developed a learning set of nonalerting compounds based on rodent cancer bioassay data and Ashby's structural alerts. When the rat cancer models were categorized based on mutagenicity, the traditional fragment model outperformed the ligand-based model. However, when the learning sets were composed solely of nonmutagenic or nonalerting carcinogens and noncarcinogens, the fragment model demonstrated a concordance of near 50%, whereas the ligand-based models demonstrated a concordance of 71% for nonmutagenic carcinogens and 74% for nonalerting carcinogens. Overall, these findings suggest that expert system analysis of virtual chemical protein interactions may be useful for developing predictive SAR models for nonmutagenic carcinogens. Moreover, a more practical approach for developing SAR models for carcinogenesis may include fragment-based models for chemicals testing positive for mutagenicity and ligand-based models for chemicals devoid of DNA reactivity.

A Foray into Fungal Ecology: Understanding Fungi and Their Functions Across Ecosystems

NASA Astrophysics Data System (ADS)

Francis, N.; Dunkirk, N. C.; Peay, K.

2015-12-01

Despite their incredible diversity and importance to terrestrial ecosystems, fungi are not included in a standard high school science curriculum. This past summer, however, my work for the Stanford EARTH High School Internship program introduced me to fungal ecology through experiments involving culturing, genomics and root dissections. The two fungal experiments I worked on had very different foci, both searching for answers to broad ecological questions of fungal function and physiology. The first, a symbiosis experiment, sought to determine if the partners of the nutrient exchange between pine trees and their fungal symbionts could choose one another. The second experiment, a dung fungal succession project, compared the genetic sequencing results of fungal extractions from dung versus fungal cultures from dung. My part in the symbiosis experiment involved dissection, weighing and encapsulation of root tissue samples characterized based on the root thickness and presence of ectomycorrhizal fungi. The dung fungi succession project required that I not only learn how to culture various genera of dung fungi but also learn how to extract DNA and RNA for sequencing from the fungal tissue. Although I primarily worked with dung fungi cultures and thereby learned about their unique physiologies, I also learned about the different types of genetic sequencing since the project compared sequences of cultured fungi versus Next Generation sequencing of all fungi present within a dung pellet. Through working on distinct fungal projects that reassess how information about fungi is known within the field of fungal ecology, I learned not only about the two experiments I worked on but also many past related experiments and inquiries through reading scientific papers. Thanks to my foray into fungal research, I now know not only the broader significance of fungi in ecological research but also how to design and conduct ecological experiments.

A heuristic method for simulating open-data of arbitrary complexity that can be used to compare and evaluate machine learning methods.

PubMed

Moore, Jason H; Shestov, Maksim; Schmitt, Peter; Olson, Randal S

2018-01-01

A central challenge of developing and evaluating artificial intelligence and machine learning methods for regression and classification is access to data that illuminates the strengths and weaknesses of different methods. Open data plays an important role in this process by making it easy for computational researchers to easily access real data for this purpose. Genomics has in some examples taken a leading role in the open data effort starting with DNA microarrays. While real data from experimental and observational studies is necessary for developing computational methods it is not sufficient. This is because it is not possible to know what the ground truth is in real data. This must be accompanied by simulated data where that balance between signal and noise is known and can be directly evaluated. Unfortunately, there is a lack of methods and software for simulating data with the kind of complexity found in real biological and biomedical systems. We present here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating complex biological and biomedical data. Further, we introduce new methods for developing simulation models that generate data that specifically allows discrimination between different machine learning methods.

Metagenome-Wide Association Study and Machine Learning Prediction of Bulk Soil Microbiome and Crop Productivity

PubMed Central

Chang, Hao-Xun; Haudenshield, James S.; Bowen, Charles R.; Hartman, Glen L.

2017-01-01

Areas within an agricultural field in the same season often differ in crop productivity despite having the same cropping history, crop genotype, and management practices. One hypothesis is that abiotic or biotic factors in the soils differ between areas resulting in these productivity differences. In this study, bulk soil samples collected from a high and a low productivity area from within six agronomic fields in Illinois were quantified for abiotic and biotic characteristics. Extracted DNA from these bulk soil samples were shotgun sequenced. While logistic regression analyses resulted in no significant association between crop productivity and the 26 soil characteristics, principal coordinate analysis and constrained correspondence analysis showed crop productivity explained a major proportion of the taxa variance in the bulk soil microbiome. Metagenome-wide association studies (MWAS) identified more Bradyrhizodium and Gammaproteobacteria in higher productivity areas and more Actinobacteria, Ascomycota, Planctomycetales, and Streptophyta in lower productivity areas. Machine learning using a random forest method successfully predicted productivity based on the microbiome composition with the best accuracy of 0.79 at the order level. Our study showed that crop productivity differences were associated with bulk soil microbiome composition and highlighted several nitrogen utility-related taxa. We demonstrated the merit of MWAS and machine learning for the first time in a plant-microbiome study. PMID:28421041

Molecular fragil X screening in normal populations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spence, W.C.; Black, S.H.; Fallon, L.

In December, 1993, we initiated a pilot project in which DNA fragile X (fraX) testing was offered during routine prenatal or genetic counseling to all pregnant women seen at the Genetics & IVF Institute, most of whom were referred for the indication of advanced maternal age. A brochure on fragile X syndrome was sent to each patient prior to her appointment and was reviewed by a counselor or physician during the counseling session. As of June 1995, 3,345 patients were offered testing; 474 women with no identified family history of mental retardation or learning disability and 214 women with amore » positive family history accepted the test on a self-pay basis. The second population screened was 271 potential donors in our anonymous egg donor program. DNA from blood was tested by Southern blot using EcoRI/EagI and StB12.3. If an expansion was detected, CGG repeat number was determined by PCR-based analysis. Among the 474 patients with unremarkable family histories, three fraX carriers were identified (repeat sizes = 60+), whereas none were found in the 214 patients with a positive family history. Among the potential egg donors, two high borderline patients were identified (repeat sizes = between 50 and 59). Our ongoing study indicates that screening of pregnant or preconceptual populations for fraX carrier status using DNA testing is accepted by many patients and is an important addition to current medical practice. 12 refs., 1 tab.« less

Analysis of a SNP linked to lactase persistence: An exercise for teaching molecular biology techniques to undergraduates.

PubMed

Schultheis, Patrick J; Bowling, Bethany V

2011-01-01

Recent experimental evidence indicates that the ability of adults to tolerate milk, cheese, and other lactose-containing dairy products is an autosomal dominant trait that co-evolved with dairy farming in Central Europe about 7,500 years ago. Among persons of European descent, this trait is strongly associated with a C to T substitution at a polymorphic site 13,910 bp upstream of the lactase gene. This mutation results in the persistent expression of lactase into adulthood enabling individuals carrying a T(-13,910) allele to digest lactose as adults. In this report, we describe a laboratory exercise for an undergraduate molecular biology course in which students determine their own genotype at the -13,910 polymorphic site and correlate this with their ability to tolerate dairy products. The exercise is used as a tool to teach basic molecular biology procedures such as agarose gel electrophoresis, PCR1, and DNA sequencing. Students are actively engaged in the learning process, not only by analyzing their own DNA but also by applying their knowledge and skills to answer an authentic question. The exercise is also integrated with lecture material on the control of gene expression at the transcriptional level, in particular, how transcription factors can influence the activity of a promoter by binding to cis-acting DNA regulatory elements located within the proximal promoter of a gene or distant enhancer regions. Copyright © 2010 Wiley Periodicals, Inc.

Racial differences in clinically localized prostate cancers of black and white men.

PubMed

deVere White, R W; Deitch, A D; Jackson, A G; Gandour-Edwards, R; Marshalleck, J; Soares, S E; Toscano, S N; Lunetta, J M; Stewart, S L

1998-06-01

Tumor grade, deoxyribonucleic acid (DNA) ploidy, proliferation, p53 and bcl-2 expression were examined in clinically localized prostate cancers of black and white American men to learn whether these features showed racial differences. A total of 117 prostate cancers (43 black and 74 white patients) obtained at radical prostatectomy for clinically localized disease were assigned Gleason scores by a single pathologist. Enzymatically dissociated nuclei from archival prostate cancers were examined by DNA flow cytometry using propidium iodide staining and the multicycle program to remove debris and sliced nuclei and to perform cell cycle analysis. For immunostaining after microwave antigen retrieval we used a DO-1/DO-7 monoclonal antibody cocktail for p53 and the clone 124 antibody for bcl-2. Significantly more black than white men had Gleason score 7 tumors. The DNA ploidy distribution of Gleason 6 or less tumors was similar for both races. As anticipated, the ploidy distribution of higher grade prostate cancer in white men was more abnormal but, unexpectedly, this was not found for higher grade prostate cancer in black men. No significant racial differences were found in S phase fractions, p53 or bcl-2 immunopositivity. However, for prostate cancer in black men there was a significant association between bcl-2 immunopositivity and higher S-phase fractions. The aggressive prostate cancers of black men may be characterized by the 2 features of high proliferation and a block to programmed cell death.

Molecular and Histopathological Changes in Mouse Intestinal Tissue After Proton Exposure

NASA Technical Reports Server (NTRS)

Purgason, A.; Zhang, Y.; Wu, H.

2010-01-01

Radiation in space, including types from solar particle events (SPE's), poses serious health risks to astronauts and is especially dangerous for long duration missions. Protons are the most abundant particles in deep space and to date there is little known about the details of the negative consequences crew members will face upon exposure to them. This ongoing project involves a mouse model subjected to several minutes of proton radiation at an energy of 250 MeV and doses of 0 Gy, 0.1 Gy, 1 Gy, and 2 Gy. The gastrointestinal tract of each animal was dissected four hours post-irradiation and the small intestine was isolated and flash-frozen. Three specimens per dose were studied. Tissue was homogenized and RNA was isolated in order for cDNA synthesis and real-time PCR to be performed. Gene expression changes are currently being analyzed specific to mouse apoptosis. Immunohistochemistry will be used to confirm any significant changes found in the analyses. Immunohistochemistry is also being used to observe gamma H2AX staining to learn of any DNA damage that occurred as a result of proton exposure. We expect to see increased DNA damage due to proton exposure. Finally, histopathologic observation of the tissue will be completed using standard H&E staining methods to screen for morphologic changes. Increased apoptosis is expected to be seen in the tissues which is typical of radiation damage. Observations will be confirmed by a pathologist.

DNA methylation markers for diagnosis and prognosis of common cancers

PubMed Central

Hao, Xiaoke; Luo, Huiyan; Krawczyk, Michal; Wei, Wei; Wang, Wenqiu; Wang, Juan; Flagg, Ken; Hou, Jiayi; Zhang, Heng; Yi, Shaohua; Jafari, Maryam; Lin, Danni; Chung, Christopher; Caughey, Bennett A.; Li, Gen; Dhar, Debanjan; Shi, William; Zheng, Lianghong; Hou, Rui; Zhu, Jie; Zhao, Liang; Fu, Xin; Zhang, Edward; Zhang, Charlotte; Zhu, Jian-Kang; Karin, Michael; Xu, Rui-Hua; Zhang, Kang

2017-01-01

The ability to identify a specific cancer using minimally invasive biopsy holds great promise for improving the diagnosis, treatment selection, and prediction of prognosis in cancer. Using whole-genome methylation data from The Cancer Genome Atlas (TCGA) and machine learning methods, we evaluated the utility of DNA methylation for differentiating tumor tissue and normal tissue for four common cancers (breast, colon, liver, and lung). We identified cancer markers in a training cohort of 1,619 tumor samples and 173 matched adjacent normal tissue samples. We replicated our findings in a separate TCGA cohort of 791 tumor samples and 93 matched adjacent normal tissue samples, as well as an independent Chinese cohort of 394 tumor samples and 324 matched adjacent normal tissue samples. The DNA methylation analysis could predict cancer versus normal tissue with more than 95% accuracy in these three cohorts, demonstrating accuracy comparable to typical diagnostic methods. This analysis also correctly identified 29 of 30 colorectal cancer metastases to the liver and 32 of 34 colorectal cancer metastases to the lung. We also found that methylation patterns can predict prognosis and survival. We correlated differential methylation of CpG sites predictive of cancer with expression of associated genes known to be important in cancer biology, showing decreased expression with increased methylation, as expected. We verified gene expression profiles in a mouse model of hepatocellular carcinoma. Taken together, these findings demonstrate the utility of methylation biomarkers for the molecular characterization of cancer, with implications for diagnosis and prognosis. PMID:28652331

Gene-culture coevolution in whales and dolphins.

PubMed

Whitehead, Hal

2017-07-24

Whales and dolphins (Cetacea) have excellent social learning skills as well as a long and strong mother-calf bond. These features produce stable cultures, and, in some species, sympatric groups with different cultures. There is evidence and speculation that this cultural transmission of behavior has affected gene distributions. Culture seems to have driven killer whales into distinct ecotypes, which may be incipient species or subspecies. There are ecotype-specific signals of selection in functional genes that correspond to cultural foraging behavior and habitat use by the different ecotypes. The five species of whale with matrilineal social systems have remarkably low diversity of mtDNA. Cultural hitchhiking, the transmission of functionally neutral genes in parallel with selective cultural traits, is a plausible hypothesis for this low diversity, especially in sperm whales. In killer whales the ecotype divisions, together with founding bottlenecks, selection, and cultural hitchhiking, likely explain the low mtDNA diversity. Several cetacean species show habitat-specific distributions of mtDNA haplotypes, probably the result of mother-offspring cultural transmission of migration routes or destinations. In bottlenose dolphins, remarkable small-scale differences in haplotype distribution result from maternal cultural transmission of foraging methods, and large-scale redistributions of sperm whale cultural clans in the Pacific have likely changed mitochondrial genetic geography. With the acceleration of genomics new results should come fast, but understanding gene-culture coevolution will be hampered by the measured pace of research on the socio-cultural side of cetacean biology.

Gene–culture coevolution in whales and dolphins

PubMed Central

Whitehead, Hal

2017-01-01

Whales and dolphins (Cetacea) have excellent social learning skills as well as a long and strong mother–calf bond. These features produce stable cultures, and, in some species, sympatric groups with different cultures. There is evidence and speculation that this cultural transmission of behavior has affected gene distributions. Culture seems to have driven killer whales into distinct ecotypes, which may be incipient species or subspecies. There are ecotype-specific signals of selection in functional genes that correspond to cultural foraging behavior and habitat use by the different ecotypes. The five species of whale with matrilineal social systems have remarkably low diversity of mtDNA. Cultural hitchhiking, the transmission of functionally neutral genes in parallel with selective cultural traits, is a plausible hypothesis for this low diversity, especially in sperm whales. In killer whales the ecotype divisions, together with founding bottlenecks, selection, and cultural hitchhiking, likely explain the low mtDNA diversity. Several cetacean species show habitat-specific distributions of mtDNA haplotypes, probably the result of mother–offspring cultural transmission of migration routes or destinations. In bottlenose dolphins, remarkable small-scale differences in haplotype distribution result from maternal cultural transmission of foraging methods, and large-scale redistributions of sperm whale cultural clans in the Pacific have likely changed mitochondrial genetic geography. With the acceleration of genomics new results should come fast, but understanding gene–culture coevolution will be hampered by the measured pace of research on the socio-cultural side of cetacean biology. PMID:28739936

Isolation of expressed sequences from the region commonly deleted in Velo-cardio-facial syndrome

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sirotkin, H.; Morrow, B.; DasGupta, R.

Velo-cardio-facial syndrome (VCFS) is a relatively common autosomal dominant genetic disorder characterized by cleft palate, cardiac abnormalities, learning disabilities and a characteristic facial dysmorphology. Most VCFS patients have interstitial deletions of 22q11 of 1-2 mb. In an effort to isolate the gene(s) responsible for VCFS we have utilized a hybrid selection protocol to recover expressed sequences from three non-overlapping YACs comprising almost 1 mb of the commonly deleted region. Total yeast genomic DNA or isolated YAC DNA was immobilized on Hybond-N filters, blocked with yeast and human ribosomal and human repetitive sequences and hybridized with a mixture of random primedmore » short fragment cDNA libraries. Six human short fragment libraries derived from total fetus, fetal brain, adult brain, testes, thymus and spleen have been used for the selections. Short fragment cDNAs retained on the filter were passed through a second round of selection and cloned into lambda gt10. cDNAs shown to originate from the YACs and from chromosome 22 are being used to isolate full length cDNAs. Three genes known to be present on these YACs, catechol-O-methyltransferase, tuple 1 and clathrin heavy chain have been recovered. Additionally, a gene related to the murine p120 gene and a number of novel short cDNAs have been isolated. The role of these genes in VCFS is being investigated.« less

DNA fingerprint similarity between female and juvenile brown-headed cowbirds trapped together

USGS Publications Warehouse

Hahn, D.C.; Fleischer, R.C.

1995-01-01

This DNA fingerprinting study investigates whether females of the brood parasite brown-headed cowbird, Molothrus ater, associate with their own juvenile offspring at feeding sites more often than would be expected by chance. Cowbirds lay their eggs in the nests of a variety of host species and, as far as is known, leave them to the care of foster parents. Using baited walk-in funnel traps, 36 adult female-juvenile pairs (or trios) of cowbirds were trapped. Blood samples were collected from these individuals to conduct DNA fingerprinting analyses, calculate similarity indices, and to compare S-values for the 11 comparisons of juveniles and the females with which they were caught with S-values of random pairings of juveniles and the females in adjacent gel lanes with which they were not caught. Overall band-sharing was significantly higher for the individuals trapped together than for the random pairings. These associations between juvenile cowbirds and their mothers could occur as a result of female cowbirds monitoring the development of their young in the nests where they have laid. Alternatively, nestling cowbirds in the nest could become familiar visually and locally with a female parent that is frequently in their territory and could follow her when she departs for feeding grounds. In either case these data suggest that adult cowbirds associate with juveniles, in some cases their own offspring, and that offspring may learn to function as cowbirds in part from this association.

Two new computational methods for universal DNA barcoding: a benchmark using barcode sequences of bacteria, archaea, animals, fungi, and land plants.

PubMed

Tanabe, Akifumi S; Toju, Hirokazu

2013-01-01

Taxonomic identification of biological specimens based on DNA sequence information (a.k.a. DNA barcoding) is becoming increasingly common in biodiversity science. Although several methods have been proposed, many of them are not universally applicable due to the need for prerequisite phylogenetic/machine-learning analyses, the need for huge computational resources, or the lack of a firm theoretical background. Here, we propose two new computational methods of DNA barcoding and show a benchmark for bacterial/archeal 16S, animal COX1, fungal internal transcribed spacer, and three plant chloroplast (rbcL, matK, and trnH-psbA) barcode loci that can be used to compare the performance of existing and new methods. The benchmark was performed under two alternative situations: query sequences were available in the corresponding reference sequence databases in one, but were not available in the other. In the former situation, the commonly used "1-nearest-neighbor" (1-NN) method, which assigns the taxonomic information of the most similar sequences in a reference database (i.e., BLAST-top-hit reference sequence) to a query, displays the highest rate and highest precision of successful taxonomic identification. However, in the latter situation, the 1-NN method produced extremely high rates of misidentification for all the barcode loci examined. In contrast, one of our new methods, the query-centric auto-k-nearest-neighbor (QCauto) method, consistently produced low rates of misidentification for all the loci examined in both situations. These results indicate that the 1-NN method is most suitable if the reference sequences of all potentially observable species are available in databases; otherwise, the QCauto method returns the most reliable identification results. The benchmark results also indicated that the taxon coverage of reference sequences is far from complete for genus or species level identification in all the barcode loci examined. Therefore, we need to accelerate the registration of reference barcode sequences to apply high-throughput DNA barcoding to genus or species level identification in biodiversity research.

Two New Computational Methods for Universal DNA Barcoding: A Benchmark Using Barcode Sequences of Bacteria, Archaea, Animals, Fungi, and Land Plants

PubMed Central

Tanabe, Akifumi S.; Toju, Hirokazu

2013-01-01

Taxonomic identification of biological specimens based on DNA sequence information (a.k.a. DNA barcoding) is becoming increasingly common in biodiversity science. Although several methods have been proposed, many of them are not universally applicable due to the need for prerequisite phylogenetic/machine-learning analyses, the need for huge computational resources, or the lack of a firm theoretical background. Here, we propose two new computational methods of DNA barcoding and show a benchmark for bacterial/archeal 16S, animal COX1, fungal internal transcribed spacer, and three plant chloroplast (rbcL, matK, and trnH-psbA) barcode loci that can be used to compare the performance of existing and new methods. The benchmark was performed under two alternative situations: query sequences were available in the corresponding reference sequence databases in one, but were not available in the other. In the former situation, the commonly used “1-nearest-neighbor” (1-NN) method, which assigns the taxonomic information of the most similar sequences in a reference database (i.e., BLAST-top-hit reference sequence) to a query, displays the highest rate and highest precision of successful taxonomic identification. However, in the latter situation, the 1-NN method produced extremely high rates of misidentification for all the barcode loci examined. In contrast, one of our new methods, the query-centric auto-k-nearest-neighbor (QCauto) method, consistently produced low rates of misidentification for all the loci examined in both situations. These results indicate that the 1-NN method is most suitable if the reference sequences of all potentially observable species are available in databases; otherwise, the QCauto method returns the most reliable identification results. The benchmark results also indicated that the taxon coverage of reference sequences is far from complete for genus or species level identification in all the barcode loci examined. Therefore, we need to accelerate the registration of reference barcode sequences to apply high-throughput DNA barcoding to genus or species level identification in biodiversity research. PMID:24204702

Learned Vocal Variation Is Associated with Abrupt Cryptic Genetic Change in a Parrot Species Complex

PubMed Central

Ribot, Raoul F. H.; Buchanan, Katherine L.; Endler, John A.; Joseph, Leo; Bennett, Andrew T. D.; Berg, Mathew L.

2012-01-01

Contact zones between subspecies or closely related species offer valuable insights into speciation processes. A typical feature of such zones is the presence of clinal variation in multiple traits. The nature of these traits and the concordance among clines are expected to influence whether and how quickly speciation will proceed. Learned signals, such as vocalizations in species having vocal learning (e.g. humans, many birds, bats and cetaceans), can exhibit rapid change and may accelerate reproductive isolation between populations. Therefore, particularly strong concordance among clines in learned signals and population genetic structure may be expected, even among continuous populations in the early stages of speciation. However, empirical evidence for this pattern is often limited because differences in vocalisations between populations are driven by habitat differences or have evolved in allopatry. We tested for this pattern in a unique system where we may be able to separate effects of habitat and evolutionary history. We studied geographic variation in the vocalizations of the crimson rosella (Platycercus elegans) parrot species complex. Parrots are well known for their life-long vocal learning and cognitive abilities. We analysed contact calls across a ca 1300 km transect encompassing populations that differed in neutral genetic markers and plumage colour. We found steep clinal changes in two acoustic variables (fundamental frequency and peak frequency position). The positions of the two clines in vocal traits were concordant with a steep cline in microsatellite-based genetic variation, but were discordant with the steep clines in mtDNA, plumage and habitat. Our study provides new evidence that vocal variation, in a species with vocal learning, can coincide with areas of restricted gene flow across geographically continuous populations. Our results suggest that traits that evolve culturally can be strongly associated with reduced gene flow between populations, and therefore may promote speciation, even in the absence of other barriers. PMID:23227179

Biological classification with RNA-Seq data: Can alternatively spliced transcript expression enhance machine learning classifier?

PubMed

Johnson, Nathan T; Dhroso, Andi; Hughes, Katelyn J; Korkin, Dmitry

2018-06-25

The extent to which the genes are expressed in the cell can be simplistically defined as a function of one or more factors of the environment, lifestyle, and genetics. RNA sequencing (RNA-Seq) is becoming a prevalent approach to quantify gene expression, and is expected to gain better insights to a number of biological and biomedical questions, compared to the DNA microarrays. Most importantly, RNA-Seq allows to quantify expression at the gene and alternative splicing isoform levels. However, leveraging the RNA-Seq data requires development of new data mining and analytics methods. Supervised machine learning methods are commonly used approaches for biological data analysis, and have recently gained attention for their applications to the RNA-Seq data. In this work, we assess the utility of supervised learning methods trained on RNA-Seq data for a diverse range of biological classification tasks. We hypothesize that the isoform-level expression data is more informative for biological classification tasks than the gene-level expression data. Our large-scale assessment is done through utilizing multiple datasets, organisms, lab groups, and RNA-Seq analysis pipelines. Overall, we performed and assessed 61 biological classification problems that leverage three independent RNA-Seq datasets and include over 2,000 samples that come from multiple organisms, lab groups, and RNA-Seq analyses. These 61 problems include predictions of the tissue type, sex, or age of the sample, healthy or cancerous phenotypes and, the pathological tumor stage for the samples from the cancerous tissue. For each classification problem, the performance of three normalization techniques and six machine learning classifiers was explored. We find that for every single classification problem, the isoform-based classifiers outperform or are comparable with gene expression based methods. The top-performing supervised learning techniques reached a near perfect classification accuracy, demonstrating the utility of supervised learning for RNA-Seq based data analysis. Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Neuroprotective actions of perinatal choline nutrition

PubMed Central

Blusztajn, Jan Krzysztof; Mellott, Tiffany J.

2017-01-01

Choline is an essential nutrient for humans. Studies in rats and mice have shown that high choline intake during gestation or the perinatal period improves cognitive function in adulthood, prevents memory decline of old age, and protects the brain from damage and cognitive and neurological deterioration associated with epilepsy and hereditary conditions such as Down’s and Rett syndromes. These behavioral changes are accompanied by modified patterns of expression of hundreds of cortical and hippocampal genes including those encoding proteins central for learning and memory processing. The effects of choline correlate with cerebral cortical changes in DNA and histone methylation, thus suggesting an epigenomic mechanism of action of perinatal choline. PMID:23314544

Microbiome Tools for Forensic Science.

PubMed

Metcalf, Jessica L; Xu, Zhenjiang Z; Bouslimani, Amina; Dorrestein, Pieter; Carter, David O; Knight, Rob

2017-09-01

Microbes are present at every crime scene and have been used as physical evidence for over a century. Advances in DNA sequencing and computational approaches have led to recent breakthroughs in the use of microbiome approaches for forensic science, particularly in the areas of estimating postmortem intervals (PMIs), locating clandestine graves, and obtaining soil and skin trace evidence. Low-cost, high-throughput technologies allow us to accumulate molecular data quickly and to apply sophisticated machine-learning algorithms, building generalizable predictive models that will be useful in the criminal justice system. In particular, integrating microbiome and metabolomic data has excellent potential to advance microbial forensics. Copyright © 2017. Published by Elsevier Ltd.

Development of molecular biology at the University of Wisconsin, Madison.

PubMed

Halvorson, Harlyn O

2007-12-01

Dramatic changes in the foundation of academic departments in our universities are uncommon. With the demonstration that DNA was the cellular source of genetic information, and that this information could be regulated, the field of molecular biology was born. Later, when scientists found that they could tinker with this information, the field matured. In an unusually rapid manner, molecular biology was integrated into the University of Wisconsin, Madison, in the late 1950s and early 1960s. This present article is a chronology of how it happened. What are the factors that made this transition possible in the University of Wisconsin? What lessons have we learned from this experience?

Robust Bioinformatics Recognition with VLSI Biochip Microsystem

NASA Technical Reports Server (NTRS)

Lue, Jaw-Chyng L.; Fang, Wai-Chi

2006-01-01

A microsystem architecture for real-time, on-site, robust bioinformatic patterns recognition and analysis has been proposed. This system is compatible with on-chip DNA analysis means such as polymerase chain reaction (PCR)amplification. A corresponding novel artificial neural network (ANN) learning algorithm using new sigmoid-logarithmic transfer function based on error backpropagation (EBP) algorithm is invented. Our results show the trained new ANN can recognize low fluorescence patterns better than the conventional sigmoidal ANN does. A differential logarithmic imaging chip is designed for calculating logarithm of relative intensities of fluorescence signals. The single-rail logarithmic circuit and a prototype ANN chip are designed, fabricated and characterized.

The Use of DNA Barcoding in Identification and Conservation of Rosewood (Dalbergia spp.)

PubMed Central

Hartvig, Ida; Czako, Mihaly; Kjær, Erik Dahl; Nielsen, Lene Rostgaard; Theilade, Ida

2015-01-01

The genus Dalbergia contains many valuable timber species threatened by illegal logging and deforestation, but knowledge on distributions and threats is often limited and accurate species identification difficult. The aim of this study was to apply DNA barcoding methods to support conservation efforts of Dalbergia species in Indochina. We used the recommended rbcL, matK and ITS barcoding markers on 95 samples covering 31 species of Dalbergia, and tested their discrimination ability with both traditional distance-based as well as different model-based machine learning methods. We specifically tested whether the markers could be used to solve taxonomic confusion concerning the timber species Dalbergia oliveri, and to identify the CITES-listed Dalbergia cochinchinensis. We also applied the barcoding markers to 14 samples of unknown identity. In general, we found that the barcoding markers discriminated among Dalbergia species with high accuracy. We found that ITS yielded the single highest discrimination rate (100%), but due to difficulties in obtaining high-quality sequences from degraded material, the better overall choice for Dalbergia seems to be the standard rbcL+matK barcode, as this yielded discrimination rates close to 90% and amplified well. The distance-based method TaxonDNA showed the highest identification rates overall, although a more complete specimen sampling is needed to conclude on the best analytic method. We found strong support for a monophyletic Dalbergia oliveri and encourage that this name is used consistently in Indochina. The CITES-listed Dalbergia cochinchinensis was successfully identified, and a species-specific assay can be developed from the data generated in this study for the identification of illegally traded timber. We suggest that the use of DNA barcoding is integrated into the work flow during floristic studies and at national herbaria in the region, as this could significantly increase the number of identified specimens and improve knowledge about species distributions. PMID:26375850

Biotechnology by Design: An Introductory Level, Project-Based, Synthetic Biology Laboratory Program for Undergraduate Students.

PubMed

Beach, Dale L; Alvarez, Consuelo J

2015-12-01

Synthetic biology offers an ideal opportunity to promote undergraduate laboratory courses with research-style projects, immersing students in an inquiry-based program that enhances the experience of the scientific process. We designed a semester-long, project-based laboratory curriculum using synthetic biology principles to develop a novel sensory device. Students develop subject matter knowledge of molecular genetics and practical skills relevant to molecular biology, recombinant DNA techniques, and information literacy. During the spring semesters of 2014 and 2015, the Synthetic Biology Laboratory Project was delivered to sophomore genetics courses. Using a cloning strategy based on standardized BioBrick genetic "parts," students construct a "reporter plasmid" expressing a reporter gene (GFP) controlled by a hybrid promoter regulated by the lac-repressor protein (lacI). In combination with a "sensor plasmid," the production of the reporter phenotype is inhibited in the presence of a target environmental agent, arabinose. When arabinose is absent, constitutive GFP expression makes cells glow green. But the presence of arabinose activates a second promoter (pBAD) to produce a lac-repressor protein that will inhibit GFP production. Student learning was assessed relative to five learning objectives, using a student survey administered at the beginning (pre-survey) and end (post-survey) of the course, and an additional 15 open-ended questions from five graded Progress Report assignments collected throughout the course. Students demonstrated significant learning gains (p < 0.05) for all learning outcomes. Ninety percent of students indicated that the Synthetic Biology Laboratory Project enhanced their understanding of molecular genetics. The laboratory project is highly adaptable for both introductory and advanced courses.

Insulin Resistance in Alzheimer Disease: p53 and MicroRNAs as Important Players.

PubMed

Gasiorowski, Kazimierz; Brokos, Barbara; Leszek, Jerzy; Tarasov, Vadim V; Ashraf, Ghulam Md; Aliev, Gjumrakch

2017-01-01

Glucose homeostasis is crucial for neuronal survival, synaptic plasticity, and is indispensable for learning and memory. Reduced sensitivity of cells to insulin and impaired insulin signaling in brain neurons participate in the pathogenesis of Alzheimer disease (AD). The tumor suppressor protein p53 coordinates with multiple cellular pathways in response to DNA damage and cellular stresses. However, prolonged stress conditions unveil deleterious effects of p53-evoked insulin resistance in neurons; enhancement of transcription of pro-oxidant factors, accumulation of toxic metabolites (e.g. ceramide and products of advanced glycation) and ROS-modified cellular components, together with the activation of proapoptotic genes, could finally induce a suicide death program of autophagy/apoptosis in neurons. Recent studies reveal the impact of p53 on expression and processing of several microRNAs (miRs) under DNA damage-inducing conditions. Additionally, the role of miRs in promotion of insulin resistance and type 2 diabetes mellitus has been well documented. Detailed recognition of the role of p53/miRs crosstalk in driving insulin resistance in AD brains could improve the disease diagnostics and aid future therapy. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Molecular basis of the dopaminergic system in the cricket Gryllus bimaculatus.

PubMed

Watanabe, Takayuki; Sadamoto, Hisayo; Aonuma, Hitoshi

2013-12-01

In insects, dopamine modulates various aspects of behavior such as learning and memory, arousal and locomotion, and is also a precursor of melanin. To elucidate the molecular basis of the dopaminergic system in the field cricket Gryllus bimaculatus DeGeer, we identified genes involved in dopamine biosynthesis, signal transduction, and dopamine re-uptake in the cricket. Complementary DNA of two isoforms of tyrosine hydroxylase (TH), which convert tyrosine into L-3,4-dihydroxyphenylalanine, was isolated from the cricket brain cDNA library. In addition, four dopamine receptor genes (Dop1, Dop2, Dop3, and DopEcR) and a high-affinity dopamine transporter gene were identified. The two TH isoforms contained isoform-specific regions in the regulatory ACT domain and showed differential expression patterns in different tissues. In addition, the dopamine receptor genes had a receptor subtype-specific distribution: the Dop1, Dop2, and DopEcR genes were broadly expressed in various tissues at differential expression levels, and the Dop3 gene was restrictedly expressed in neuronal tissues and the testicles. Our findings provide a fundamental basis for understanding the dopaminergic regulation of diverse physiological processes in the cricket.

Stool-based biomarkers of interstitial cystitis/bladder pain syndrome.

PubMed

Braundmeier-Fleming, A; Russell, Nathan T; Yang, Wenbin; Nas, Megan Y; Yaggie, Ryan E; Berry, Matthew; Bachrach, Laurie; Flury, Sarah C; Marko, Darlene S; Bushell, Colleen B; Welge, Michael E; White, Bryan A; Schaeffer, Anthony J; Klumpp, David J

2016-05-18

Interstitial cystitis/bladder pain syndrome (IC) is associated with significant morbidity, yet underlying mechanisms and diagnostic biomarkers remain unknown. Pelvic organs exhibit neural crosstalk by convergence of visceral sensory pathways, and rodent studies demonstrate distinct bacterial pain phenotypes, suggesting that the microbiome modulates pelvic pain in IC. Stool samples were obtained from female IC patients and healthy controls, and symptom severity was determined by questionnaire. Operational taxonomic units (OTUs) were identified by16S rDNA sequence analysis. Machine learning by Extended Random Forest (ERF) identified OTUs associated with symptom scores. Quantitative PCR of stool DNA with species-specific primer pairs demonstrated significantly reduced levels of E. sinensis, C. aerofaciens, F. prausnitzii, O. splanchnicus, and L. longoviformis in microbiota of IC patients. These species, deficient in IC pelvic pain (DIPP), were further evaluated by Receiver-operator characteristic (ROC) analyses, and DIPP species emerged as potential IC biomarkers. Stool metabolomic studies identified glyceraldehyde as significantly elevated in IC. Metabolomic pathway analysis identified lipid pathways, consistent with predicted metagenome functionality. Together, these findings suggest that DIPP species and metabolites may serve as candidates for novel IC biomarkers in stool. Functional changes in the IC microbiome may also serve as therapeutic targets for treating chronic pelvic pain.

Introducing DNA concepts to Swiss high school students based on a Brazilian educational game.

PubMed

da S Cardona, Tânia; Spiegel, Carolina N; Alves, Gutemberg G; Ducommun, Jacques; Henriques-Pons, Andrea; Araújo-Jorge, Tania C

2007-11-01

Subjects such as techniques for genetic diagnosis, cloning, sequencing, and gene therapy are now part of our lives and raise important questions about ethics, future medical diagnosis, and such. Students from different countries observe this explosion of biotechnological applications regardless of their social, academic, or cultural backgrounds, although they are not usually familiar with their theoretical genetic bases. To introduce some molecular biology concepts for high school students, we developed a new problem for the Brazilian board game "Discovering the cell" ("Célula Adentro©" in Portuguese), a pedagogic tool based on inquiry-, cooperative-, and problem-based learning. This problem (Case) is based on the forensic DNA, which represents an interesting theme for students, as it recurrently appears on newspapers and television series. In this work, we tested this game with secondary students and teachers from Switzerland. Our results indicate that the game "Discovering the cell" is well accepted by both students and teachers and may represent a good pedagogical approach to help teaching complex themes in molecular biology, even with students from different socioeconomical, cultural, and academic backgrounds. Copyright © 2007 International Union of Biochemistry and Molecular Biology, Inc.

Discriminative Prediction of A-To-I RNA Editing Events from DNA Sequence

PubMed Central

Sun, Jiangming; Singh, Pratibha; Bagge, Annika; Valtat, Bérengère; Vikman, Petter; Spégel, Peter; Mulder, Hindrik

2016-01-01

RNA editing is a post-transcriptional alteration of RNA sequences that, via insertions, deletions or base substitutions, can affect protein structure as well as RNA and protein expression. Recently, it has been suggested that RNA editing may be more frequent than previously thought. A great impediment, however, to a deeper understanding of this process is the paramount sequencing effort that needs to be undertaken to identify RNA editing events. Here, we describe an in silico approach, based on machine learning, that ameliorates this problem. Using 41 nucleotide long DNA sequences, we show that novel A-to-I RNA editing events can be predicted from known A-to-I RNA editing events intra- and interspecies. The validity of the proposed method was verified in an independent experimental dataset. Using our approach, 203 202 putative A-to-I RNA editing events were predicted in the whole human genome. Out of these, 9% were previously reported. The remaining sites require further validation, e.g., by targeted deep sequencing. In conclusion, the approach described here is a useful tool to identify potential A-to-I RNA editing events without the requirement of extensive RNA sequencing. PMID:27764195

Tegument Assembly and Secondary Envelopment of Alphaherpesviruses

PubMed Central

Owen, Danielle J.; Crump, Colin M.; Graham, Stephen C.

2015-01-01

Alphaherpesviruses like herpes simplex virus are large DNA viruses characterized by their ability to establish lifelong latent infection in neurons. As for all herpesviruses, alphaherpesvirus virions contain a protein-rich layer called “tegument” that links the DNA-containing capsid to the glycoprotein-studded membrane envelope. Tegument proteins mediate a diverse range of functions during the virus lifecycle, including modulation of the host-cell environment immediately after entry, transport of virus capsids to the nucleus during infection, and wrapping of cytoplasmic capsids with membranes (secondary envelopment) during virion assembly. Eleven tegument proteins that are conserved across alphaherpesviruses have been implicated in the formation of the tegument layer or in secondary envelopment. Tegument is assembled via a dense network of interactions between tegument proteins, with the redundancy of these interactions making it challenging to determine the precise function of any specific tegument protein. However, recent studies have made great headway in defining the interactions between tegument proteins, conserved across alphaherpesviruses, which facilitate tegument assembly and secondary envelopment. We summarize these recent advances and review what remains to be learned about the molecular interactions required to assemble mature alphaherpesvirus virions following the release of capsids from infected cell nuclei. PMID:26393641

Epigenomics in marine fishes.

PubMed

Metzger, David C H; Schulte, Patricia M

2016-12-01

Epigenetic mechanisms are an underappreciated and often ignored component of an organism's response to environmental change and may underlie many types of phenotypic plasticity. Recent technological advances in methods for detecting epigenetic marks at a whole-genome scale have launched new opportunities for studying epigenomics in ecologically relevant non-model systems. The study of ecological epigenomics holds great promise to better understand the linkages between genotype, phenotype, and the environment and to explore mechanisms of phenotypic plasticity. The many attributes of marine fish species, including their high diversity, variable life histories, high fecundity, impressive plasticity, and economic value provide unique opportunities for studying epigenetic mechanisms in an environmental context. To provide a primer on epigenomic research for fish biologists, we start by describing fundamental aspects of epigenetics, focusing on the most widely studied and most well understood of the epigenetic marks: DNA methylation. We then describe the techniques that have been used to investigate DNA methylation in marine fishes to date and highlight some new techniques that hold great promise for future studies. Epigenomic research in marine fishes is in its early stages, so we first briefly discuss what has been learned about the establishment, maintenance, and function of DNA methylation in fishes from studies in zebrafish and then summarize the studies demonstrating the pervasive effects of the environment on the epigenomes of marine fishes. We conclude by highlighting the potential for ongoing research on the epigenomics of marine fishes to reveal critical aspects of the interaction between organisms and their environments. Copyright © 2016 Elsevier B.V. All rights reserved.

Personalised Medicine: Genome Maintenance Lessons Learned from Studies in Yeast as a Model Organism.

PubMed

Abugable, Arwa A; Awwad, Dahlia A; Fleifel, Dalia; Ali, Mohamed M; El-Khamisy, Sherif; Elserafy, Menattallah

2017-01-01

Yeast research has been tremendously contributing to the understanding of a variety of molecular pathways due to the ease of its genetic manipulation, fast doubling time as well as being cost-effective. The understanding of these pathways did not only help scientists learn more about the cellular functions but also assisted in deciphering the genetic and cellular defects behind multiple diseases. Hence, yeast research not only opened the doors for transforming basic research into applied research, but also paved the roads for improving diagnosis and innovating personalized therapy of different diseases. In this chapter, we discuss how yeast research has contributed to understanding major genome maintenance pathways such as the S-phase checkpoint activation pathways, repair via homologous recombination and non-homologous end joining as well as topoisomerases-induced protein linked DNA breaks repair. Defects in these pathways lead to neurodegenerative diseases and cancer. Thus, the understanding of the exact genetic defects underlying these diseases allowed the development of personalized medicine, improving the diagnosis and treatment and overcoming the detriments of current conventional therapies such as the side effects, toxicity as well as drug resistance.

Detection of Splice Sites Using Support Vector Machine

NASA Astrophysics Data System (ADS)

Varadwaj, Pritish; Purohit, Neetesh; Arora, Bhumika

Automatic identification and annotation of exon and intron region of gene, from DNA sequences has been an important research area in field of computational biology. Several approaches viz. Hidden Markov Model (HMM), Artificial Intelligence (AI) based machine learning and Digital Signal Processing (DSP) techniques have extensively and independently been used by various researchers to cater this challenging task. In this work, we propose a Support Vector Machine based kernel learning approach for detection of splice sites (the exon-intron boundary) in a gene. Electron-Ion Interaction Potential (EIIP) values of nucleotides have been used for mapping character sequences to corresponding numeric sequences. Radial Basis Function (RBF) SVM kernel is trained using EIIP numeric sequences. Furthermore this was tested on test gene dataset for detection of splice site by window (of 12 residues) shifting. Optimum values of window size, various important parameters of SVM kernel have been optimized for a better accuracy. Receiver Operating Characteristic (ROC) curves have been utilized for displaying the sensitivity rate of the classifier and results showed 94.82% accuracy for splice site detection on test dataset.

Where Environment Meets Cognition: A Focus on Two Developmental Intellectual Disability Disorders

PubMed Central

Ossowski, S.

2016-01-01

One of the most challenging questions in neuroscience is to dissect how learning and memory, the foundational pillars of cognition, are grounded in stable, yet plastic, gene expression states. All known epigenetic mechanisms such as DNA methylation and hydroxymethylation, histone modifications, chromatin remodelling, and noncoding RNAs regulate brain gene expression, both during neurodevelopment and in the adult brain in processes related to cognition. On the other hand, alterations in the various components of the epigenetic machinery have been linked to well-known causes of intellectual disability disorders (IDDs). Two examples are Down Syndrome (DS) and Fragile X Syndrome (FXS), where global and local epigenetic alterations lead to impairments in synaptic plasticity, memory, and learning. Since epigenetic modifications are reversible, it is theoretically possible to use epigenetic drugs as cognitive enhancers for the treatment of IDDs. Epigenetic treatments act in a context specific manner, targeting different regions based on cell and state specific chromatin accessibility, facilitating the establishment of the lost balance. Here, we discuss epigenetic studies of IDDs, focusing on DS and FXS, and the use of epidrugs in combinatorial therapies for IDDs. PMID:27547454

Where Environment Meets Cognition: A Focus on Two Developmental Intellectual Disability Disorders.

PubMed

Toma, I De; Gil, L Manubens; Ossowski, S; Dierssen, M

2016-01-01

One of the most challenging questions in neuroscience is to dissect how learning and memory, the foundational pillars of cognition, are grounded in stable, yet plastic, gene expression states. All known epigenetic mechanisms such as DNA methylation and hydroxymethylation, histone modifications, chromatin remodelling, and noncoding RNAs regulate brain gene expression, both during neurodevelopment and in the adult brain in processes related to cognition. On the other hand, alterations in the various components of the epigenetic machinery have been linked to well-known causes of intellectual disability disorders (IDDs). Two examples are Down Syndrome (DS) and Fragile X Syndrome (FXS), where global and local epigenetic alterations lead to impairments in synaptic plasticity, memory, and learning. Since epigenetic modifications are reversible, it is theoretically possible to use epigenetic drugs as cognitive enhancers for the treatment of IDDs. Epigenetic treatments act in a context specific manner, targeting different regions based on cell and state specific chromatin accessibility, facilitating the establishment of the lost balance. Here, we discuss epigenetic studies of IDDs, focusing on DS and FXS, and the use of epidrugs in combinatorial therapies for IDDs.

The potential of epigenetics in stress-enhanced fear learning models of PTSD

PubMed Central

Blouin, Ashley M.; Sillivan, Stephanie E.; Joseph, Nadine F.

2016-01-01

Prolonged distress and dysregulated memory processes are the core features of post-traumatic stress disorder (PTSD) and represent the debilitating, persistent nature of the illness. However, the neurobiological mechanisms underlying the expression of these symptoms are challenging to study in human patients. Stress-enhanced fear learning (SEFL) paradigms, which encompass both stress and memory components in rodents, are emerging as valuable preclinical models of PTSD. Rodent models designed to study the long-term mechanisms of either stress or fear memory alone have identified a critical role for numerous epigenetic modifications to DNA and histone proteins. However, the epigenetic modifications underlying SEFL remain largely unknown. This review will provide a brief overview of the epigenetic modifications implicated in stress and fear memory independently, followed by a description of existing SEFL models and the few epigenetic mechanisms found to date to underlie SEFL. The results of the animal studies discussed here highlight neuroepigenetics as an essential area for future research in the context of PTSD through SEFL studies, because of its potential to identify novel candidates for neurotherapeutics targeting stress-induced pathogenic memories. PMID:27634148

Analysis of the morphology, stability, and folding pathways of ring polymers with supramolecular topological constraints using molecular simulation and nonlinear manifold learning

NASA Astrophysics Data System (ADS)

Wang, Jiang; Ferguson, Andrew

Ring polymers offer a wide range of natural and engineered functions and applications, including as circular bacterial DNA, crown ethers for cation chelation, and ``molecular machines'' such as mechanical nanoswitches. The morphology and dynamics of ring polymers are governed by the chemistry and degree of polymerization of the ring, and intramolecular and supramolecular topological constraints such as knots or mechanically-interlocked rings. We perform molecular dynamics simulations of polyethylene ring polymers as a function of degree of polymerization and in different topological states, including a knotted state, catenane state (two interlocked rings), and borromean state (three interlocked rings). Applying nonlinear manifold learning to our all-atom simulation trajectories, we extract low-dimensional free energy surfaces governing the accessible conformational states and their relative thermodynamic stability. The free energy surfaces reveal how degree of polymerization and topological constraints affect the thermally accessible conformations, chiral symmetry breaking, and folding and collapse pathways of the rings, and present a means to rationally engineer ring size and topology to preferentially stabilize particular conformational states.

From trace evidence to bioinformatics: putting bryophytes into molecular biology education.

PubMed

Fuselier, Linda; Bougary, Azhar; Malott, Michelle

2011-01-01

Students benefit most from their science education when they participate fully in the process of science in the context of real-world problems. We describe a student-directed open-inquiry lab experience that has no predetermined outcomes and requires students to engage in all components of scientific inquiry from posing a question through evaluating and reporting results. Over 5 weeks, students learn how bryophytes are used in forensics and become proficient in important molecular biology lab skills including DNA isolation, polymerase chain reaction, gel electrophoresis, capillary electrophoresis, and genotyping. For this portion of the experience, there is no specialized equipment necessary outside of gel electrophoresis supplies and a thermocycler. In an optional extension of the experience, students sequence a plastid intron and use introductory bioinformatics skills to identify species related to their forensics case. Students who participated in the lab experience performed well on content-based assessment, and student attitudes toward the experience were positive and indicative of engaged learning. The lab experience is easily modified for higher or lower level courses and can be used in secondary education. Copyright © 2011 Wiley Periodicals, Inc.

Hidden Markov models and other machine learning approaches in computational molecular biology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baldi, P.

1995-12-31

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In thismore » tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.« less

The opportunities and challenges of large-scale molecular approaches to songbird neurobiology

PubMed Central

Mello, C.V.; Clayton, D.F.

2014-01-01

High-through put methods for analyzing genome structure and function are having a large impact in song-bird neurobiology. Methods include genome sequencing and annotation, comparative genomics, DNA microarrays and transcriptomics, and the development of a brain atlas of gene expression. Key emerging findings include the identification of complex transcriptional programs active during singing, the robust brain expression of non-coding RNAs, evidence of profound variations in gene expression across brain regions, and the identification of molecular specializations within song production and learning circuits. Current challenges include the statistical analysis of large datasets, effective genome curations, the efficient localization of gene expression changes to specific neuronal circuits and cells, and the dissection of behavioral and environmental factors that influence brain gene expression. The field requires efficient methods for comparisons with organisms like chicken, which offer important anatomical, functional and behavioral contrasts. As sequencing costs plummet, opportunities emerge for comparative approaches that may help reveal evolutionary transitions contributing to vocal learning, social behavior and other properties that make songbirds such compelling research subjects. PMID:25280907

The acquisition and transfer of knowledge of electrokinetic-hydrodynamics (EKHD) fundamentals: an introductory graduate-level course

NASA Astrophysics Data System (ADS)

Pascal, Jennifer; Tíjaro-Rojas, Rocío; Oyanader, Mario A.; Arce, Pedro E.

2017-09-01

Relevant engineering applications, such as bioseparation of proteins and DNA, soil-cleaning, motion of colloidal particles in different media, electrical field-based cancer treatments, and the cleaning of surfaces and coating flows, belongs to the family of 'Applied Field Sensitive Process Technologies' requiring an external field to move solutes in a fluid within a fibrous (or porous) domain. This field incorporates an additional variable that makes the analysis very challenging and can create for the student a number of new problems to solve. A graduate-level course, based on active-learning approaches and High Performance Learning Environments, where transfer of knowledge plays a key role, was designed by the Chemical Engineering Department at Tennessee Technological University. This course, where the fundamentals principles of EKHD were taught to science, engineering and technology students was designed by the Chemical Engineering Department at the Tennessee Technological University, Cookeville, TN. An important number of these students were able to grasp the tools required to advance their research projects that led to numerous technical presentations in professional society meetings and publications in peered-reviewed journals.

Using Comparative Genomics for Inquiry-Based Learning to Dissect Virulence of Escherichia coli O157:H7 and Yersinia pestis

PubMed Central

Baumler, David J.; Banta, Lois M.; Hung, Kai F.; Schwarz, Jodi A.; Cabot, Eric L.; Glasner, Jeremy D.; Perna, Nicole T.

2012-01-01

Genomics and bioinformatics are topics of increasing interest in undergraduate biological science curricula. Many existing exercises focus on gene annotation and analysis of a single genome. In this paper, we present two educational modules designed to enable students to learn and apply fundamental concepts in comparative genomics using examples related to bacterial pathogenesis. Students first examine alignments of genomes of Escherichia coli O157:H7 strains isolated from three food-poisoning outbreaks using the multiple-genome alignment tool Mauve. Students investigate conservation of virulence factors using the Mauve viewer and by browsing annotations available at the A Systematic Annotation Package for Community Analysis of Genomes database. In the second module, students use an alignment of five Yersinia pestis genomes to analyze single-nucleotide polymorphisms of three genes to classify strains into biovar groups. Students are then given sequences of bacterial DNA amplified from the teeth of corpses from the first and second pandemics of the bubonic plague and asked to classify these new samples. Learning-assessment results reveal student improvement in self-efficacy and content knowledge, as well as students' ability to use BLAST to identify genomic islands and conduct analyses of virulence factors from E. coli O157:H7 or Y. pestis. Each of these educational modules offers educators new ready-to-implement resources for integrating comparative genomic topics into their curricula. PMID:22383620

Better understanding of homologous recombination through a 12-week laboratory course for undergraduates majoring in biotechnology.

PubMed

Li, Ming; Shen, Xiaodong; Zhao, Yan; Hu, Xiaomei; Hu, Fuquan; Rao, Xiancai

2017-07-08

Homologous recombination, a central concept in biology, is defined as the exchange of DNA strands between two similar or identical nucleotide sequences. Unfortunately, undergraduate students majoring in biotechnology often experience difficulties in understanding the molecular basis of homologous recombination. In this study, we developed and implemented a 12-week laboratory course for biotechnology undergraduates in which gene targeting in Streptococcus suis was used to facilitate their understanding of the basic concept and process of homologous recombination. Students worked in teams of two to select a gene of interest to create a knockout mutant using methods that relied on homologous recombination. By integrating abstract knowledge and practice in the process of scientific research, students gained hands-on experience in molecular biology techniques while learning about the principle and process of homologous recombination. The learning outcomes and survey-based assessment demonstrated that students substantially enhanced their understanding of how homologous recombination could be used to study gene function. Overall, the course was very effective for helping biotechnology undergraduates learn the theory and application of homologous recombination, while also yielding positive effects in developing confidence and scientific skills for future work in research. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(4):329-335, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

High-confidence assessment of functional impact of human mitochondrial non-synonymous genome variations by APOGEE.

PubMed

Castellana, Stefano; Fusilli, Caterina; Mazzoccoli, Gianluigi; Biagini, Tommaso; Capocefalo, Daniele; Carella, Massimo; Vescovi, Angelo Luigi; Mazza, Tommaso

2017-06-01

24,189 are all the possible non-synonymous amino acid changes potentially affecting the human mitochondrial DNA. Only a tiny subset was functionally evaluated with certainty so far, while the pathogenicity of the vast majority was only assessed in-silico by software predictors. Since these tools proved to be rather incongruent, we have designed and implemented APOGEE, a machine-learning algorithm that outperforms all existing prediction methods in estimating the harmfulness of mitochondrial non-synonymous genome variations. We provide a detailed description of the underlying algorithm, of the selected and manually curated training and test sets of variants, as well as of its classification ability.

Heterogeneous data fusion for brain tumor classification.

PubMed

Metsis, Vangelis; Huang, Heng; Andronesi, Ovidiu C; Makedon, Fillia; Tzika, Aria

2012-10-01

Current research in biomedical informatics involves analysis of multiple heterogeneous data sets. This includes patient demographics, clinical and pathology data, treatment history, patient outcomes as well as gene expression, DNA sequences and other information sources such as gene ontology. Analysis of these data sets could lead to better disease diagnosis, prognosis, treatment and drug discovery. In this report, we present a novel machine learning framework for brain tumor classification based on heterogeneous data fusion of metabolic and molecular datasets, including state-of-the-art high-resolution magic angle spinning (HRMAS) proton (1H) magnetic resonance spectroscopy and gene transcriptome profiling, obtained from intact brain tumor biopsies. Our experimental results show that our novel framework outperforms any analysis using individual dataset.

Implications for the formation of the Hollywood Basin from gravity interpretations of the northern Los Angeles Basin, California

USGS Publications Warehouse

Hildenbrand, Thomas G.; Davidson, Jeffrey G.; Ponti, Daniel J.; Langenheim, V.E.

2001-01-01

Gravity data provide insights on the complex tectonic history and structural development of the northern Los Angeles Basin region. The Hollywood basin appears to be a long (> 12 km), narrow (up to 2 km wide) trough lying between the Santa Monica Mountains and the Wilshire arch. In the deepest parts of the Hollywood basin, the modeled average thickness ranges from roughly 250 m if filled with only Quaternary sediments to approximately 600 m if Pliocene sediments are also present. Interpretations of conflicting drill hole data force us to consider both these scenarios. Because of the marked density contrast between the dense Santa Monica Mountains and the low-density sediments in the Los Angeles Basin, the gravity method is particularly useful in mapping the maximum displacement along the Santa Monica-Hollywood-Raymond fault zone. The gravity-defined Santa Monica–Hollywood fault zone deviates, in places, from the mapped active fault and fold scarps located with boreholes and trenching and by geomorphological mapping by Dolan and others (1997). Our models suggest that the Santa Monica–Hollywood fault zone dips northward approximately 63°. Three structural models are considered for the origin of the Hollywood basin: pull-apart basin, flexural basin, and a basin related to a back limb of a major fold. Although our preferred structural model involves flexure, the available geologic and geophysical data do not preclude contributions to the deepening of the basin from one or both of the other two models. Of particular interest is that the distribution of red-tagged buildings and structures damaged by the Northridge earthquake has a strong spatial correlation with the axis of the Hollywood basin defined by the gravity data. Several explanations for this correlation are explored, but two preferred geologic factors for the amplification of ground motion besides local site effects are (1) focussing of energy by a fault along the axis of the Hollywood basin and (2) focussing effects related to differential refraction of seismic rays across the basin.

Dynamic compression of water to 700 GPa: single- and double shock experiments on Sandia's Z machine, first principles simulations, and structure of water planets

NASA Astrophysics Data System (ADS)

Mattsson, Thomas R.

2011-11-01

Significant progress has over the last few years been made in high energy density physics (HEDP) by executing high-precision multi-Mbar experiments and performing first-principles simulations for elements ranging from carbon [1] to xenon [2]. The properties of water under HEDP conditions are of particular importance in planetary science due to the existence of ice-giants like Neptune and Uranus. Modeling the two planets, as well as water-rich exoplanets, requires knowing the equation of state (EOS), the pressure as a function of density and temperature, of water with high accuracy. Although extensive density functional theory (DFT) simulations have been performed for water under planetary conditions [3] experimental validation has been lacking. Accessing thermodynamic states along planetary isentropes in dynamic compression experiments is challenging because the principal Hugoniot follows a significantly different path in the phase diagram. In this talk, we present experimental data for dynamic compression of water up to 700 GPa, including in a regime of the phase-diagram intersected by the Neptune isentrope and water-rich models for the exoplanet GJ436b. The data was obtained on the Z-accelerator at Sandia National Laboratories by performing magnetically accelerated flyer plate impact experiments measuring both the shock and re-shock in the sample. The high accuracy makes it possible for the data to be used for detailed model validation: the results validate first principles based thermodynamics as a reliable foundation for planetary modeling and confirm the fine effect of including nuclear quantum effects on the shock pressure. Sandia National Laboratories is a multiprogram laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under Contract No. DE-AC04-94AL85000. [4pt] [1] M.D. Knudson, D.H. Dolan, and M.P. Desjarlais, SCIENCE 322, 1822 (2008).[0pt] [2] S. Root, et al., Phys. Rev. Lett. 105, 085501 (2010).[0pt] [3] M. French, et al., Phys. Rev. B 79, 054107 (2009).

DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

PubMed

Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S; Vikesland, Peter; Zhang, Liqing

2018-02-01

Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The DeepARG models and database are available as a command line version and as a Web service at http://bench.cs.vt.edu/deeparg .

PySeqLab: an open source Python package for sequence labeling and segmentation.

PubMed

Allam, Ahmed; Krauthammer, Michael

2017-11-01

Text and genomic data are composed of sequential tokens, such as words and nucleotides that give rise to higher order syntactic constructs. In this work, we aim at providing a comprehensive Python library implementing conditional random fields (CRFs), a class of probabilistic graphical models, for robust prediction of these constructs from sequential data. Python Sequence Labeling (PySeqLab) is an open source package for performing supervised learning in structured prediction tasks. It implements CRFs models, that is discriminative models from (i) first-order to higher-order linear-chain CRFs, and from (ii) first-order to higher-order semi-Markov CRFs (semi-CRFs). Moreover, it provides multiple learning algorithms for estimating model parameters such as (i) stochastic gradient descent (SGD) and its multiple variations, (ii) structured perceptron with multiple averaging schemes supporting exact and inexact search using 'violation-fixing' framework, (iii) search-based probabilistic online learning algorithm (SAPO) and (iv) an interface for Broyden-Fletcher-Goldfarb-Shanno (BFGS) and the limited-memory BFGS algorithms. Viterbi and Viterbi A* are used for inference and decoding of sequences. Using PySeqLab, we built models (classifiers) and evaluated their performance in three different domains: (i) biomedical Natural language processing (NLP), (ii) predictive DNA sequence analysis and (iii) Human activity recognition (HAR). State-of-the-art performance comparable to machine-learning based systems was achieved in the three domains without feature engineering or the use of knowledge sources. PySeqLab is available through https://bitbucket.org/A_2/pyseqlab with tutorials and documentation. ahmed.allam@yale.edu or michael.krauthammer@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Biotechnology by Design: An Introductory Level, Project-Based, Synthetic Biology Laboratory Program for Undergraduate Students†

PubMed Central

Beach, Dale L.; Alvarez, Consuelo J.

2015-01-01

Synthetic biology offers an ideal opportunity to promote undergraduate laboratory courses with research-style projects, immersing students in an inquiry-based program that enhances the experience of the scientific process. We designed a semester-long, project-based laboratory curriculum using synthetic biology principles to develop a novel sensory device. Students develop subject matter knowledge of molecular genetics and practical skills relevant to molecular biology, recombinant DNA techniques, and information literacy. During the spring semesters of 2014 and 2015, the Synthetic Biology Laboratory Project was delivered to sophomore genetics courses. Using a cloning strategy based on standardized BioBrick genetic “parts,” students construct a “reporter plasmid” expressing a reporter gene (GFP) controlled by a hybrid promoter regulated by the lac-repressor protein (lacI). In combination with a “sensor plasmid,” the production of the reporter phenotype is inhibited in the presence of a target environmental agent, arabinose. When arabinose is absent, constitutive GFP expression makes cells glow green. But the presence of arabinose activates a second promoter (pBAD) to produce a lac-repressor protein that will inhibit GFP production. Student learning was assessed relative to five learning objectives, using a student survey administered at the beginning (pre-survey) and end (post-survey) of the course, and an additional 15 open-ended questions from five graded Progress Report assignments collected throughout the course. Students demonstrated significant learning gains (p < 0.05) for all learning outcomes. Ninety percent of students indicated that the Synthetic Biology Laboratory Project enhanced their understanding of molecular genetics. The laboratory project is highly adaptable for both introductory and advanced courses. PMID:26753032

De novo identification of replication-timing domains in the human genome by deep learning.

PubMed

Liu, Feng; Ren, Chao; Li, Hao; Zhou, Pingkun; Bo, Xiaochen; Shu, Wenjie

2016-03-01

The de novo identification of the initiation and termination zones-regions that replicate earlier or later than their upstream and downstream neighbours, respectively-remains a key challenge in DNA replication. Building on advances in deep learning, we developed a novel hybrid architecture combining a pre-trained, deep neural network and a hidden Markov model (DNN-HMM) for the de novo identification of replication domains using replication timing profiles. Our results demonstrate that DNN-HMM can significantly outperform strong, discriminatively trained Gaussian mixture model-HMM (GMM-HMM) systems and other six reported methods that can be applied to this challenge. We applied our trained DNN-HMM to identify distinct replication domain types, namely the early replication domain (ERD), the down transition zone (DTZ), the late replication domain (LRD) and the up transition zone (UTZ), using newly replicated DNA sequencing (Repli-Seq) data across 15 human cells. A subsequent integrative analysis revealed that these replication domains harbour unique genomic and epigenetic patterns, transcriptional activity and higher-order chromosomal structure. Our findings support the 'replication-domain' model, which states (1) that ERDs and LRDs, connected by UTZs and DTZs, are spatially compartmentalized structural and functional units of higher-order chromosomal structure, (2) that the adjacent DTZ-UTZ pairs form chromatin loops and (3) that intra-interactions within ERDs and LRDs tend to be short-range and long-range, respectively. Our model reveals an important chromatin organizational principle of the human genome and represents a critical step towards understanding the mechanisms regulating replication timing. Our DNN-HMM method and three additional algorithms can be freely accessed at https://github.com/wenjiegroup/DNN-HMM The replication domain regions identified in this study are available in GEO under the accession ID GSE53984. shuwj@bmi.ac.cn or boxc@bmi.ac.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

A new method for species identification via protein-coding and non-coding DNA barcodes by combining machine learning with bioinformatic methods.

PubMed

Zhang, Ai-bing; Feng, Jie; Ward, Robert D; Wan, Ping; Gao, Qiang; Wu, Jun; Zhao, Wei-zhong

2012-01-01

Species identification via DNA barcodes is contributing greatly to current bioinventory efforts. The initial, and widely accepted, proposal was to use the protein-coding cytochrome c oxidase subunit I (COI) region as the standard barcode for animals, but recently non-coding internal transcribed spacer (ITS) genes have been proposed as candidate barcodes for both animals and plants. However, achieving a robust alignment for non-coding regions can be problematic. Here we propose two new methods (DV-RBF and FJ-RBF) to address this issue for species assignment by both coding and non-coding sequences that take advantage of the power of machine learning and bioinformatics. We demonstrate the value of the new methods with four empirical datasets, two representing typical protein-coding COI barcode datasets (neotropical bats and marine fish) and two representing non-coding ITS barcodes (rust fungi and brown algae). Using two random sub-sampling approaches, we demonstrate that the new methods significantly outperformed existing Neighbor-joining (NJ) and Maximum likelihood (ML) methods for both coding and non-coding barcodes when there was complete species coverage in the reference dataset. The new methods also out-performed NJ and ML methods for non-coding sequences in circumstances of potentially incomplete species coverage, although then the NJ and ML methods performed slightly better than the new methods for protein-coding barcodes. A 100% success rate of species identification was achieved with the two new methods for 4,122 bat queries and 5,134 fish queries using COI barcodes, with 95% confidence intervals (CI) of 99.75-100%. The new methods also obtained a 96.29% success rate (95%CI: 91.62-98.40%) for 484 rust fungi queries and a 98.50% success rate (95%CI: 96.60-99.37%) for 1094 brown algae queries, both using ITS barcodes.

Characterization and machine learning prediction of allele-specific DNA methylation.

PubMed

He, Jianlin; Sun, Ming-an; Wang, Zhong; Wang, Qianfei; Li, Qing; Xie, Hehuang

2015-12-01

A large collection of Single Nucleotide Polymorphisms (SNPs) has been identified in the human genome. Currently, the epigenetic influences of SNPs on their neighboring CpG sites remain elusive. A growing body of evidence suggests that locus-specific information, including genomic features and local epigenetic state, may play important roles in the epigenetic readout of SNPs. In this study, we made use of mouse methylomes with known SNPs to develop statistical models for the prediction of SNP associated allele-specific DNA methylation (ASM). ASM has been classified into parent-of-origin dependent ASM (P-ASM) and sequence-dependent ASM (S-ASM), which comprises scattered-S-ASM (sS-ASM) and clustered-S-ASM (cS-ASM). We found that P-ASM and cS-ASM CpG sites are both enriched in CpG rich regions, promoters and exons, while sS-ASM CpG sites are enriched in simple repeat and regions with high frequent SNP occurrence. Using Lasso-grouped Logistic Regression (LGLR), we selected 21 out of 282 genomic and methylation related features that are powerful in distinguishing cS-ASM CpG sites and trained the classifiers with machine learning techniques. Based on 5-fold cross-validation, the logistic regression classifier was found to be the best for cS-ASM prediction with an ACC of 0.77, an AUC of 0.84 and an MCC of 0.54. Lastly, we applied the logistic regression classifier on human brain methylome and predicted 608 genes associated with cS-ASM. Gene ontology term enrichment analysis indicated that these cS-ASM associated genes are significantly enriched in the category coding for transcripts with alternative splicing forms. In summary, this study provided an analytical procedure for cS-ASM prediction and shed new light on the understanding of different types of ASM events. Published by Elsevier Inc.

Expectations and experiences of gamete donors and donor-conceived adults searching for genetic relatives using DNA linking through a voluntary register.

PubMed

van den Akker, O B A; Crawshaw, M A; Blyth, E D; Frith, L J

2015-01-01

What are the experiences of donor-conceived adults and donors who are searching for a genetic link through the use of a DNA-based voluntary register service? Donor-conceived adults and donors held positive beliefs about their search and although some concerns in relation to finding a genetically linked relative were reported, these were not a barrier to searching. Research with donor-conceived people has consistently identified their interest in learning about-and in some cases making contact with-their donor and other genetic relatives. However, donor-conceived individuals or donors rarely have the opportunity to act on these desires. A questionnaire was administered for online completion using Bristol Online Surveys. The survey was live for 3 months and responses were collected anonymously. The survey was completed by 65 donor-conceived adults, 21 sperm donors and 5 oocyte donors who had registered with a DNA-based voluntary contact register in the UK. The questionnaire included socio-demographic questions, questions specifically developed for the purposes of this study and the standardized Aspects of Identity Questionnaire (AIQ). Motivations for searching for genetic relatives were varied, with the most common reasons being curiosity and passing on information. Overall, participants who were already linked and those awaiting a link were positive about being linked and valued access to a DNA-based register. Collective identity (reflecting self-defining feelings of continuity and uniqueness), as assessed by the AIQ, was significantly lower for donor-conceived adults when compared with the donor groups (P < 0.05), but not significantly different between linked/not linked or length of time since disclosure of donor conception (all Ps > 0.05) for donor-conceived adults. Participants were members of a UK DNA-based registry which is unique. It was therefore not possible to determine how representative participants were of those who did not register for the service, those in other countries or of those who do not seek information exchange or contact. This is the first survey exploring the experiences of donor-conceived adults and donors using a DNA-based voluntary register to seek information about and contact with genetic relatives and the first to measure aspects of identity using standardized measures. Findings provide valuable information about patterns of expectations and experiences of searching through DNA linking, identity and of having contact in the context of donor conception that will inform future research, practice and policy development. No funding was obtained for this study. The authors have no competing interests to declare except for M.C. who was national adviser to UKDL from 2003-2013. Not applicable. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Screening for fragile X syndrome.

PubMed

Murray, J; Cuckle, H; Taylor, G; Hewison, J

1997-01-01

BACKGROUND AND AIM OF REVIEW. In 1991, the gene responsible for fragile X syndrome, a common cause of learning disability, was discovered. As a result, diagnosis of the disorder has improved and its molecular genetics are now understood. This report seems to provide the information needed to decide whether to use DNA testing to screen for the disorder. HOW THE RESEARCH WAS CONDUCTED. A literature search of electronic reference databases of published and 'grey' literature was undertaken together with hand searching of the most recent publications. RESEARCH FINDINGS. NATURAL HISTORY. Physical characteristics of fragile X syndrome include facial atypia, joint laxity and, in boys, macro-orchidism. Most affected males have moderate-to-severe learning disabilities with IQs under 50 whereas most females have borderline IQs of 70-85. Behavioural problems are similar to those seen with autism and attention-deficit disorders. Although fragile X syndrome is not curable there are a number of medical, educational, psychological and social interventions that can improve the symptoms. About 6% of those with learning disabilities tested in institutions have fragile X syndrome. Population prevalence figures are 1 in 4000 in males and 1 in 8000 in females. GENETICS. The disorder is caused by a mutation in a gene on the X chromosome which includes a trinucleotide repeat sequence. The mutation is characterized by hyper-expansion of the repeat sequence leading to down-regulation of the gene. In males an allele with repeat size in excess of 200, termed a full mutation (FM), is always associated with the affected phenotype, whereas in females only half are affected. Individuals with alleles having repeat size in the range 55-199 are unaffected but in females the sequence is heritably unstable so that it is at high risk of expansion to an FM in her offspring. This allele is known as a pre-mutation (PM) to contrast it with the FM found in the affected individual. No spontaneous expansions directly from a normal allele to an FM have been observed. SCREENING STRATEGIES. The principal aims of screenng for fragile X syndrome is to reduce the birth prevalence of the disorder, by prenatal diagnosis and selective termination of pregnancy, or by reducing the number of pregnancies in women who have the FM or PM alleles. Possible screening strategies are: routine antenatal testing of apparently low risk pregnancies, preconceptual testing of young women, and systematic testing in affected families ('cascade' screening). A secondary aim is to bring forward the diagnosis of affected individuals so that they might benefit from early treatment. Active paediatric screening and neonatal screening could achieve this but there is no direct evidence of any great benefit from early diagnosis. SCREENING TESTS. Cytogenetic methods are unsuitable for screening purposes. Southern blotting of genomic DNA can be used but is inaccurate in measuring the size of small PMs, there is a long laboratory turnaround time, and it is relatively expensive. The best protocol is to amplify the DNA using polymerase chain reaction on all samples, and when there is a possible failure to amplify, a Southern blot.(ABSTRACT TRUNCATED)

Mild clinical involvement in two males with a large FMR1 premutation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagerman, R.; O`Connor, R.; Staley, L.

1994-09-01

Both male and female individuals who carry the FMR1 premutation are considered to be clinically unaffected and have been reported to have normal transcription of their FMR1 gene and normal FMR1 protein (FMRP) production. We have evaluated two males who are mildly affected clinically with features of fragile X syndrome and demonstrate a large premutation on DNA studies. The first patient is a 2 year 8 month old boy who demonstrated the fragile X chromosome in 3% of his lymphocytes on cytogenetic testing. His physical features include mildly prominent ears and hyperextensible finger joints. He has language delays along withmore » behavioral problems including tantrums and attention deficit. Developmental testing revealed a mental scale of 116 on the Bayley Scales of Infant Development, which is in the normal range. DNA testing demonstrated a premutation with 161 CGG repeats. This premutation was methylated in a small percent of his cells (<2%). These findings were observed in both blood leukocytes and buccal cells. Protein studies of transformed lymphocytes from this boy showed approximately 50 to 70% of the normal level of FMRP. The second patient is a 14 year old male who was cytogenetically negative for fragile X expression. His physical exam demonstrates a long face, a high palate and macroorchidism, (testicular volume of approximately 35 ml). His overall full scale IQ on the WISC-III is 73. He has language deficits and visual spatial perceptual deficits which have caused significant learning problems in school. Behaviorally he has problems with shyness and social anxiety, although he does not have attention deficit hyperactivity disorder. DNA testing revealed an FMR1 mutation of approximately 210 CGG repeats that is methylated in 4.7% of his cells.« less

Human Papillomavirus Drives Tumor Development Throughout the Head and Neck: Improved Prognosis Is Associated With an Immune Response Largely Restricted to the Oropharynx

PubMed Central

Chakravarthy, Ankur; Henderson, Stephen; Thirdborough, Stephen M.; Ottensmeier, Christian H.; Su, Xiaoping; Lechner, Matt; Feber, Andrew; Thomas, Gareth J.

2016-01-01

Purpose In squamous cell carcinomas of the head and neck (HNSCC), the increasing incidence of oropharyngeal squamous cell carcinomas (OPSCCs) is attributable to human papillomavirus (HPV) infection. Despite commonly presenting at late stage, HPV-driven OPSCCs are associated with improved prognosis compared with HPV-negative disease. HPV DNA is also detectable in nonoropharyngeal (non-OPSCC), but its pathogenic role and clinical significance are unclear. The objectives of this study were to determine whether HPV plays a causal role in non-OPSCC and to investigate whether HPV confers a survival benefit in these tumors. Methods Meta-analysis was used to build a cross-tissue gene-expression signature for HPV-driven cancer. Classifiers trained by machine-learning approaches were used to predict the HPV status of 520 HNSCCs profiled by The Cancer Genome Atlas project. DNA methylation data were similarly used to classify 464 HNSCCs and these analyses were integrated with genomic, histopathology, and survival data to permit a comprehensive comparison of HPV transcript-positive OPSCC and non-OPSCC. Results HPV-driven tumors accounted for 4.1% of non-OPSCCs. Regardless of anatomic site, HPV+ HNSCCs shared highly similar gene expression and DNA methylation profiles; nonkeratinizing, basaloid histopathological features; and lack of TP53 or CDKN2A alterations. Improved overall survival, however, was largely restricted to HPV-driven OPSCCs, which were associated with increased levels of tumor-infiltrating lymphocytes compared with HPV-driven non-OPSCCs. Conclusion Our analysis identified a causal role for HPV in transcript-positive non-OPSCCs throughout the head and neck. Notably, however, HPV-driven non-OPSCCs display a distinct immune microenvironment and clinical behavior compared with HPV-driven OPSCCs. PMID:27863190

Prenatal Nutritional Deficiency Reprogrammed Postnatal Gene Expression in Mammal Brains: Implications for Schizophrenia

PubMed Central

Xu, Jiawei; He, Guang; Zhu, Jingde; Zhou, Xinyao; St Clair, David; Wang, Teng; Xiang, Yuqian; Zhao, Qingzhu; Xing, Qinghe; Liu, Yun; Wang, Lei; Li, Qiaoli

2015-01-01

Background: Epidemiological studies have identified prenatal exposure to famine as a risk factor for schizophrenia, and animal models of prenatal malnutrition display structural and functional brain abnormalities implicated in schizophrenia. Methods: The offspring of the RLP50 rat, a recently developed animal model of prenatal famine malnutrition exposure, was used to investigate the changes of gene expression and epigenetic modifications in the brain regions. Microarray gene expression analysis was carried out in the prefrontal cortex and the hippocampus from 8 RLP50 offspring rats and 8 controls. MBD-seq was used to test the changes in DNA methylation in hippocampus depending on prenatal malnutrition exposure. Results: In the prefrontal cortex, offspring of RLP50 exhibit differences in neurotransmitters and olfactory-associated gene expression. In the hippocampus, the differentially-expressed genes are related to synaptic function and transcription regulation. DNA methylome profiling of the hippocampus also shows widespread but systematic epigenetic changes; in most cases (87%) this involves hypermethylation. Remarkably, genes encoded for the plasma membrane are significantly enriched for changes in both gene expression and DNA methylome profiling screens (p = 2.37×10–9 and 5.36×10–9, respectively). Interestingly, Mecp2 and Slc2a1, two genes associated with cognitive impairment, show significant down-regulation, and Slc2a1 is hypermethylated in the hippocampus of the RLP50 offspring. Conclusions: Collectively, our results indicate that prenatal exposure to malnutrition leads to the reprogramming of postnatal brain gene expression and that the epigenetic modifications contribute to the reprogramming. The process may impair learning and memory ability and result in higher susceptibility to schizophrenia. PMID:25522397

GHEP-ISFG collaborative simulated exercise for DVI/MPI: Lessons learned about large-scale profile database comparisons.

PubMed

Vullo, Carlos M; Romero, Magdalena; Catelli, Laura; Šakić, Mustafa; Saragoni, Victor G; Jimenez Pleguezuelos, María Jose; Romanini, Carola; Anjos Porto, Maria João; Puente Prieto, Jorge; Bofarull Castro, Alicia; Hernandez, Alexis; Farfán, María José; Prieto, Victoria; Alvarez, David; Penacino, Gustavo; Zabalza, Santiago; Hernández Bolaños, Alejandro; Miguel Manterola, Irati; Prieto, Lourdes; Parsons, Thomas

2016-03-01

The GHEP-ISFG Working Group has recognized the importance of assisting DNA laboratories to gain expertise in handling DVI or missing persons identification (MPI) projects which involve the need for large-scale genetic profile comparisons. Eleven laboratories participated in a DNA matching exercise to identify victims from a hypothetical conflict with 193 missing persons. The post mortem database was comprised of 87 skeletal remain profiles from a secondary mass grave displaying a minimal number of 58 individuals with evidence of commingling. The reference database was represented by 286 family reference profiles with diverse pedigrees. The goal of the exercise was to correctly discover re-associations and family matches. The results of direct matching for commingled remains re-associations were correct and fully concordant among all laboratories. However, the kinship analysis for missing persons identifications showed variable results among the participants. There was a group of laboratories with correct, concordant results but nearly half of the others showed discrepant results exhibiting likelihood ratio differences of several degrees of magnitude in some cases. Three main errors were detected: (a) some laboratories did not use the complete reference family genetic data to report the match with the remains, (b) the identity and/or non-identity hypotheses were sometimes wrongly expressed in the likelihood ratio calculations, and (c) many laboratories did not properly evaluate the prior odds for the event. The results suggest that large-scale profile comparisons for DVI or MPI is a challenge for forensic genetics laboratories and the statistical treatment of DNA matching and the Bayesian framework should be better standardized among laboratories. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Epigenetic mechanisms in experience-driven memory formation and behavior.

PubMed

Puckett, Rosemary E; Lubin, Farah D

2011-10-01

Epigenetic mechanisms have long been associated with the regulation of gene-expression changes accompanying normal neuronal development and cellular differentiation; however, until recently these mechanisms were believed to be statically quiet in the adult brain. Behavioral neuroscientists have now begun to investigate these epigenetic mechanisms as potential regulators of gene-transcription changes in the CNS subserving synaptic plasticity and long-term memory (LTM) formation. Experimental evidence from learning and memory animal models has demonstrated that active chromatin remodeling occurs in terminally differentiated postmitotic neurons, suggesting that these molecular processes are indeed intimately involved in several stages of LTM formation, including consolidation, reconsolidation and extinction. Such chromatin modifications include the phosphorylation, acetylation and methylation of histone proteins and the methylation of associated DNA to subsequently affect transcriptional gene readout triggered by learning. The present article examines how such learning-induced epigenetic changes contribute to LTM formation and influence behavior. In particular, this article is a survey of the specific epigenetic mechanisms that have been demonstrated to regulate gene expression for both transcription factors and growth factors in the CNS, which are critical for LTM formation and storage, as well as how aberrant epigenetic processing can contribute to psychological states such as schizophrenia and drug addiction. Together, the findings highlighted in this article support a novel role for epigenetic mechanisms in the adult CNS serving as potential key molecular regulators of gene-transcription changes necessary for LTM formation and adult behavior.