DNA ANALYSIS USING GRAMMATICAL INFERENCE

An accurate language definition capable of distinguishing between coding and non-coding DNA has important applications and analytical significance to the field of computational biology. The method proposed here uses positive sample grammatical inference and statistical information to infer languages for coding DNA. An algorithm is proposed for the searching of an optimal subset of input sequences for the inference of regular grammars by optimizing a relevant accuracy metric. The algorithm does not guarantee the finding of the optimal subset; however, testing shows improvement in accuracy and performance over the basis algorithm. Testing shows that the accuracy of inferred languages for components of DNA are consistently accurate. By using the proposed algorithm languages are inferred for coding DNA with average conditional probability over 80%. This reveals that languages for components of DNA can be inferred and are useful independent of the process that created them. These languages can then be analyzed or used for other tasks in computational biology. To illustrate potential applications of regular grammars for DNA components, an inferred language for exon sequences is applied as post processing to Hidden Markov exon prediction to reduce the number of wrong exons detected and improve the specificity of the model significantly

Applications and Challenges of Real-time Mobile DNA Analysis

The DNA sequencing is the process of identifying the exact order of nucleotides within a given DNA molecule. The new portable and relatively inexpensive DNA sequencers, such as Oxford Nanopore MinION, have the potential to move DNA sequencing outside of laboratory, leading to faster and more accessible DNA-based diagnostics. However, portable DNA sequencing and analysis are challenging for mobile systems, owing to high data throughputs and computationally intensive processing performed in environments with unreliable connectivity and power. In this paper, we provide an analysis of the challenges that mobile systems and mobile computing must address to maximize the potential of portable DNA sequencing, and in situ DNA analysis. We explain the DNA sequencing process and highlight the main differences between traditional and portable DNA sequencing in the context of the actual and envisioned applications. We look at the identified challenges from the perspective of both algorithms and systems design, showing the need for careful co-design

Evaluation of pre-analytical factors affecting plasma DNA analysis.

Pre-analytical factors can significantly affect circulating cell-free DNA (cfDNA) analysis. However, there are few robust methods to rapidly assess sample quality and the impact of pre-analytical processing. To address this gap and to evaluate effects of DNA extraction methods and blood collection tubes on cfDNA yield and fragment size, we developed a multiplexed droplet digital PCR (ddPCR) assay with 5 short and 4 long amplicons targeting single copy genomic loci. Using this assay, we compared 7 cfDNA extraction kits and found cfDNA yield and fragment size vary significantly. We also compared 3 blood collection protocols using plasma samples from 23 healthy volunteers (EDTA tubes processed within 1 hour and Cell-free DNA Blood Collection Tubes processed within 24 and 72 hours) and found no significant differences in cfDNA yield, fragment size and background noise between these protocols. In 219 clinical samples, cfDNA fragments were shorter in plasma samples processed immediately after venipuncture compared to archived samples, suggesting contribution of background DNA by lysed peripheral blood cells. In summary, we have described a multiplexed ddPCR assay to assess quality of cfDNA samples prior to downstream molecular analyses and we have evaluated potential sources of pre-analytical variation in cfDNA studies

Multi-color fluorescent DNA analysis in an optofluidic chip

Modulation-frequency-encoded fluorescence excitation enables the identification of end-labeled DNA samples of different genetic origin during their electrophoretic separation, opening perspectives for intrinsic size calibration, malign / healthy sample comparison, and exploitation of multiplex ligation-dependent probe amplification

Report of species diagnosis of a tuna at Queens Products B.V. on 23 December 2009

According to a company in the same marketsegment as Queen Products B.V. part of the tuna filet sold by Queens Products B.V. does not consist of the species that is mentioned on the label. According to DNA analysis filets were not from the species on the label, Albacore (Thunnus alalunga), but from Yellowfin tuna (T. albacares). The present intention of Queens Products is to check by means of DNA analysis of different lots of filets the originating species. A Spanish expert on DNA analysis who has travelled to the Netherlands to collect samples, has requested species identification by an independent scientist on the basis of morphological features as back up of the findings by means of DNA analysi

Who knows who we are? Questioning DNA analysis in disaster victim identification

The use of DNA analysis as a mode of identification of disaster victims has become increasingly predominant to other, traditional, methods of identification in recent years. Scientific advances of the technological processes, high-profile use in identification efforts across the globe (such as after 9/11 or in the Asian Tsunami of 2004), and its inclusion in popular media, have led to its popular adoption as one of the primary modes of identification in disaster scenarios, and to the expectation of its use in all cases by the lay public and media. It is increasingly argued to be integral to post-disaster management. However, depending on the circumstances, location, and type of disaster, this technology may not be appropriate, and its use may instead conflict with socio-political and cultural norms and structures of power. Using examples primarily from Cambodia and Iraq this article will explore what these conflicts may be, and in doing so, question the expanding assumption that DNA analysis is a universally appropriate intervention in disaster victim identification. It will argue instead that its use may be a result of a desire for the political and social capital that this highly prestigious technological intervention offers rather than a solely humanitarian intervention on behalf of survivors and the dead

Visible diode lasers can be used for flow cytometric immunofluorescence and DNA analysis

This report describes a feasibility study concerning the use of a visible diode laser for two important fluorescence applications in a flow cytometer. With a 3 mW 635 nm. diode laser, we performed immunofluorescence measurements using the fluorophore allophycocyanin (APC). We have measured CD8 positive lymphocytes with a two-step labeling procedure and the resulting histograms showed good separation between the negative cells and the dim and the bright fluorescent subpopulations. As a second fluorescence application, we chose DNA analysis with the recently developed DNA/ RNA stains TOTO-3 and TO-PRO-3. In our setup TO-PRO-3 yielded the best results with a CV of 3.4%. Our results indicate that a few milliwatts of 635 nm light from a visible diode laser is sufficient to do single color immunofluorescence measurements with allophycocyanin and DNA analysis with TO-PRO-3. The major advantages of using a diode laser in a flow cytometer are the small size, the low price, the high efficiency, and the long lifetime

Analyzing large-scale DNA Sequences on Multi-core Architectures

Rapid analysis of DNA sequences is important in preventing the evolution of different viruses and bacteria during an early phase, early diagnosis of genetic predispositions to certain diseases (cancer, cardiovascular diseases), and in DNA forensics. However, real-world DNA sequences may comprise several Gigabytes and the process of DNA analysis demands adequate computational resources to be completed within a reasonable time. In this paper we present a scalable approach for parallel DNA analysis that is based on Finite Automata, and which is suitable for analyzing very large DNA segments. We evaluate our approach for real-world DNA segments of mouse (2.7GB), cat (2.4GB), dog (2.4GB), chicken (1GB), human (3.2GB) and turkey (0.2GB). Experimental results on a dual-socket shared-memory system with 24 physical cores show speed-ups of up to 17.6x. Our approach is up to 3x faster than a pattern-based parallel approach that uses the RE2 library.Comment: The 18th IEEE International Conference on Computational Science and Engineering (CSE 2015), Porto, Portugal, 20 - 23 October 201

Mitochondrial DNA analysis of eneolithic trypillians from Ukraine reveals neolithic farming genetic roots

The agricultural revolution in Eastern Europe began in the Eneolithic with the Cucuteni-Trypillia culture complex. In Ukraine, the Trypillian culture (TC) existed for over two millennia (ca. 5,400–2,700 BCE) and left a wealth of artifacts. Yet, their burial rituals remain a mystery and to date almost nothing is known about the genetic composition of the TC population. One of the very few TC sites where human remains can be found is a cave called Verteba in western Ukraine. This report presents four partial and four complete mitochondrial genomes from nine TC individuals uncovered in the cave. The results of this analysis, combined with the data from previous reports, indicate that the Trypillian population at Verteba carried, for the most part, a typical Neolithic farmer package of mitochondrial DNA (mtDNA) lineages traced to Anatolian farmers and Neolithic farming groups of central Europe. At the same time, the find of two specimens belonging to haplogroup U8b1 at Verteba can be viewed as a connection of TC with the Upper Paleolithic European populations. At the level of mtDNA haplogroup frequencies, the TC population from Verteba demonstrates a close genetic relationship with population groups of the Funnel Beaker/ Trichterbecker cultural complex from central and northern Europe (ca. 3,950–2,500 BCE)

MISSEL: a method to identify a large number of small species-specific genomic subsequences and its application to viruses classification

Continuous improvements in next generation sequencing technologies led to ever-increasing collections of genomic sequences, which have not been easily characterized by biologists, and whose analysis requires huge computational effort. The classification of species emerged as one of the main applications of DNA analysis and has been addressed with several approaches, e.g., multiple alignments-, phylogenetic trees-, statistical- and character-based methods