GENtle, a free multi-purpose molecular biology tool

A result of modern techniques in molecular biology, especially DNA sequencing, is the exponentially growing amount of available data. Besides giant, specialized databases, which are accessible over the Internet, all work groups in the field of molecular biology today need to handle, modify, analyze and store sequence information. This trend notwithstanding, general purpose software for these tasks often suffers from severe drawbacks. Free software exists, but is often hard to set up and operate for users on today's point-and-click interfaces, and usually leads to the application of a patch-work of multiple, only partially compatible tools and web services. Commercial software often covers only parts of the required functions, and tends to lock the user into proprietary formats. In my thesis, I have developed GENtle, a free, multi-purpose bioinformatics software, seamlessly integrating diverse applications for every-day lab use in a single package. It was designed for easy and intuitive use, while providing many powerful functions. This C++ application runs on multiple platforms, is optimized for performance, and includes database interfaces for easy sequence management. It features DNA and protein sequence management and analysis, virtual cloning, gels, and PCR, primer design, alignment generation and layout, chromatogram and image display, as well as many related functions. GENtle strives to satisfy the need for an easy and comfortable, yet powerful multi-purpose tool. One design goal of GENtle was "instant responsiveness". Likewise, consistent display and handling are of great importance. GENtle has been outfitted with modules for DNA and protein sequence management, editing, and analysis, primer design, virtual PCR, alignments, virtual gels, a plethora of import and export formats, integrated database management, internet search functionality, an auto-update mechanism, and a number of integrated tools. GENtle is free software licensed under the GPL and available for Windows, Mac OSX, and Linux in several languages. As such, it is already in use in research groups worldwide

A manual for large-scale sample collection, preservation, tracking, DNA extraction, and variety identification analysis

Several alternative options have been used for varietal identification. However most of the traditional methods have inherent uncertainty levels and estimates often have wide confidence intervals. In an attempt to circumvent traditional survey-based measurement errors in varietal identification, DNA-based varietal identification has been implemented in the Cassava Monitoring Survey (CMS) of Nigeria — a large adoption study involving 2500 cassava farming households. The DNA fingerprinting technique offers a reliable method to accurately identify varieties grown by farmers and increases accuracy and credibility in the interpretation of adoption rates and associated economic and policy analyses. Unlike phenotype-based methods, DNA is not affected by environmental conditions or plant growth stage and is more abundant than morphological descriptors. However, undertaking a credible DNA-based varietal identification is not a trivial matter because of the logistical challenges involving sample collection and tracking by a large team of field enumerators. This manual presents the detailed steps required for undertaking reliable DNA-fingerprinting-based identification of cassava varieties. In particular, the manual gives detailed information on the establishment of a sample tracking system, preparation of a readily available and cheap sample collection kit, field sample collection methodology, preparation of samples for DNA isolation, and development of a pipeline for variety identification analysis. This manual is part of the outputs of the CMS project funded by the CGIAR Research Program on Roots, Tubers and Bananas (RTB), the Bill & Melinda Gates Foundation, and the International Institute of Tropical Agriculture (IITA)

Postmortem iris recognition and its application in human identification

Iris recognition is a validated and non-invasive human identification technology currently implemented for the purposes of surveillance and security (i.e. border control, schools, military). Similar to deoxyribonucleic acid (DNA), irises are a highly individualizing component of the human body. Based on a lack of genetic penetrance, irises are unique between an individual’s left and right iris and between identical twins, proving to be more individualizing than DNA. At this time, little to no research has been conducted on the use of postmortem iris scanning as a biometric measurement of identification. The purpose of this pilot study is to explore the use of iris recognition as a tool for postmortem identification. Objectives of the study include determining whether current iris recognition technology can locate and detect iris codes in postmortem globes, and if iris scans collected at different postmortem time intervals can be identified as the same iris initially enrolled. Data from 43 decedents involving 148 subsequent iris scans demonstrated a subsequent match rate of approximately 80%, supporting the theory that iris recognition technology is capable of detecting and identifying an individual’s iris code in a postmortem setting. A chi-square test of independence showed no significant difference between match outcomes and the globe scanned (left vs. right), and gender had no bearing on the match outcome. There was a significant relationship between iris color and match outcome, with blue/gray eyes yielding a lower match rate (59%) compared to brown (82%) or green/hazel eyes (88%), however, the sample size of blue/gray eyes in this study was not large enough to draw a meaningful conclusion. An isolated case involving an antemortem initial scan collected from an individual on life support yielded an accurate identification (match) with a subsequent scan captured at approximately 10 hours postmortem. Falsely rejected subsequent iris scans or "no match" results occurred in about 20% of scans; they were observed at each PMI range and varied from 19-30%. The false reject rate is too high to reliably establish non-identity when used alone and ideally would be significantly lower prior to implementation in a forensic setting; however, a "no match" could be confirmed using another method. Importantly, the data showed a false match rate or false accept rate (FAR) of zero, a result consistent with previous iris recognition studies in living individuals. The preliminary results of this pilot study demonstrate a plausible role for iris recognition in postmortem human identification. Implementation of a universal iris recognition database would benefit the medicolegal death investigation and forensic pathology communities, and has potential applications to other situations such as missing persons and human trafficking cases

SEQGEL: a versatile and comfortable DNA editor which supports a special keyboard and a speech synthesizer

A DNA editor for an Apple II is described which contains many additional functions apart from just editing sequences. The data files are normal ASCII text or binary files and can thus be used easily by other programs. The program supports a special keyboard which greatly facilitates typing of DNA sequences. Furthermore a speech synthesizer is supported by the editor. The speech feedback, together with the special keyboard, reduces typing errors to a minimu

The Role of the Voltage Gradient in the Agarose Gel Electrophoresis of DNA

In Part I of this dissertation, empirical equations for predicting DNA mobility during agarose gel electrophoresis (AGE) from voltage gradient are developed from the data of McDonnel (36) for electrophoresis in a 1.6% agarose gel. These equations represented the data well for DNA between 2 and 10 kilobase pairs (KBp) in length. A computer program, called GELSIM, which incorporates these equations is described in Part II. GELSIM was designed to allow researchers to analyze electrophoresis data by predicting the effect on DNA migration of altering the voltage of electrophoresis. In this way, electrophoretic banding patterns produced using different voltages could be compared. GELSIM was tested by comparing its predicted banding patterns for a DNA standard with those actually obtained in the lab. The patterns matched well for voltages below 5 volts per centimeter of electrode separation, the maximum recommended electrophoresis voltage gradient (34). In Part III, a characterization of the voltage gradient using an electrode grid to measure local voltages, it was found that the voltage gradient is linear from anode to cathode and invariant from lane to lane in the gel. It was also determined that the gradient within the gel was significantly lower than that predicted by simply dividing the electrophoresis voltage by the electrode separation, the usual practice. Part IV of this dissertation details a measurement of local voltage gradient during electrophoresis over very short intervals of time. The apparatus used to make these measurements consisted of an electrode array hooked via an analog to digital converter to a computer. It was found that the local voltages were not constant, as expected, but fluctuated in a roughly sinusoidal manner by as much as 10% of their average value. The frequency of the fluctuations was 60 Hz. The source of the fluctuations was determined to be the DC power supply used during the electrophoresis and the form of the fluctuations, was found to vary from power supply to power supply. It was concluded that these fluctuations were a general feature of AGE and likely to be of theoretical as well as practical importance in electrophoretic separation