In-silico Design of DNA Oligonucleotides: Challenges and Approaches

Techniques, procedures, and applications in host genetic analysis

This chapter overviews genetic techniques' fundamentals and methodological features, including different approaches, analyses, and applications that have contributed to advancing health and disease. The aim is to describe laboratory methodologies and analyses employed to understand the genetic landscape of different biological contexts, from conventional techniques to cutting-edge technologies. Besides describing detailed aspects of the polymerase chain reaction (PCR) and derived types as one of the principles for many novel techniques, we also discuss microarray analysis, next-generation sequencing, and genome editing technologies such as transcription activator-like effector nucleases (TALENs) and the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) systems. These techniques study several phenotypes, ranging from autoimmune disorders to viral diseases. The significance of integrating diverse genetic methodologies and tools to understand host genetics comprehensively and addressing the ethical, legal, and social implications (ELSI) associated with using genetic information is highlighted. Overall, the methods, procedures, and applications in host genetic analysis provided in this chapter furnish researchers and practitioners with a roadmap for navigating the dynamic landscape of host-genome interactions.

RNA-based detection of genetically modified plants via current-voltage characteristic measurement

The widespread adoption of genetically modified (GM) crops has escalated concerns about their safety and ethical implications, underscoring the need for efficient GM crop detection methods. Conventional detection methods, such as polymerase chain reaction, can be costly, lab-bound, and time-consuming. To overcome these challenges, we have developed RapiSense, a cost-effective, portable, and sensitive biosensor platform. This sensor generates a measurable voltage shift (0.1-1 V) in the system's current-voltage characteristics, triggered by an increase in membrane's negative charge upon hybridization of DNA/RNA targets with a specific DNA probe. Probes designed to identify the herbicide resistance gene hygromycin phosphotransferase show a detection range from ∼1 nM to ∼10 μM and can discriminate between complementary, non-specific, and mismatched nucleotide targets. The incorporation of a small membrane sensor to detect fragmented RNA samples substantially improve the platform's sensitivity. In this study, RapiSense has been effectively used to detect specific DNA and fragmented RNA in transgenic variants of Arabidopsis, sweet potato, and rice, showcasing its potential for rapid, on-site GM crop screening.

A tool to automatically design multiplex PCR primer pairs for specific targets using diverse templates

Multiplex PCR is an increasingly popular method for identifying species, investigating environmental diversity, and conducting phylogenetic analysis. The complexity and increasing availability of diverse templates necessitate a highly automated approach to design degenerate primer pairs for specific targets with multiple sequences. Existing tools for degenerate primer design suffer from poor maintenance, semi-automation, low adaptability, and low tolerance for gaps. We developed PMPrimer, a Python-based tool for automated design and evaluation of multiplex PCR primer pairs for specific targets using diverse templates. PMPrimer automatically designs optimal multiplex PCR primer pairs using a statistical-based template filter; performs multiple sequence alignment, conserved region identification, and primer design; and evaluates the primers based on template coverage, taxon specificity, and target specificity. PMPrimer identifies conserved regions using Shannon's entropy method, tolerates gaps using a haplotype-based method, and evaluates multiplex PCR primer pairs based on template coverage and taxon specificity. We tested PMPrimer using datasets with diverse levels of conservation, sizes, and applications, including tuf genes of Staphylococci, hsp65 genes of Mycobacteriaceae, and 16S ribosomal RNA genes of Archaea. PMPrimer showed outstanding performance compared with existing tools and experimental validated primers. PMPrimer is available as a Python package at https://github.com/AGIScuipeng/PMPrimer .

Evaluation of loci to predict ear morphology using two SNaPshot assays

Human ear morphology prediction with SNP-based genotypes is growing in forensic DNA phenotyping and is scarcely explored in Pakistan as a part of EVCs (externally visible characteristics). The ear morphology prediction assays with 21 SNPs were assessed for their potential utility in forensic identification of population. The SNaPshot™ multiplex chemistries, capillary electrophoresis methods and GeneMapper™ software were used for obtaining genotypic data. A total of 33 ear phenotypes were categorized with digital photographs of 300 volunteers. SHEsis software was applied to make LD plot. Ordinal and multinomial logistic regression was implemented for association testing. Multinomial logistic regression was executed to construct the prediction model in 90% training and 10% testing subjects. Several influential SNPs for ear phenotypic variation were found in association testing. The model based on genetic markers predicted ear phenotypes with moderate to good predictive accuracies demonstrated with the area under curve (AUC), sensitivity and specificity of predicted phenotypes. As an additional EVC, the estimated ear phenotypic profiles have the possibility of determining the human ear morphology differences in unknown biological samples found in crimes that do not result in a criminal database hit. Furthermore, this can help in facial reconstruction and act as an investigational lead.

A reinforcement learning framework for pooled oligonucleotide design

MOTIVATION

The goal of oligonucleotide (oligo) design is to select oligos that optimize a set of design criteria. Oligo design problems are combinatorial in nature and require computationally intensive models to evaluate design criteria. Even relatively small problems can be intractable for brute-force approaches that test every possible combination of oligos, so heuristic approaches must be used to find near-optimal solutions.

RESULTS

We present a general reinforcement learning (RL) framework, called OligoRL, to solve oligo design problems with complex constraints. OligoRL allows 'black-box' design criteria and can be adapted to solve many oligo design problems. We highlight the flexibility of OligoRL by building tools to solve three distinct design problems: (i) finding pools of random DNA barcodes that lack restriction enzyme recognition sequences (CutFreeRL); (ii) compressing large, non-degenerate oligo pools into smaller degenerate ones (OligoCompressor) and (iii) finding Not-So-Random hexamer primer pools that avoid rRNA and other unwanted transcripts during RNA-seq library preparation (NSR-RL). OligoRL demonstrates how RL offers a general solution for complex oligo design problems.

AVAILABILITY AND IMPLEMENTATION

OligoRL and all simulation codes are available as a Julia package at http://jensenlab.net/tools and archived at https://archive.softwareheritage.org/browse/origin/directory/?origin_url=https://github.com/bmdavid2/OligoRL.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

True or False: What are the factors that influence COVID-19 diagnosis by RT-qPCR?

Introduction

The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease has had a catastrophic impact on the world resulting in several deaths. Since World Health Organization declared the pandemic status of the disease, several molecular diagnostic kits have been developed to help the tracking of viruses spread.

Areas Covered

This review aims to describe and evaluate the currently reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) diagnosis kit. Several processes used in COVID-19 diagnostic procedures are detailed in further depth to demonstrate optimal practices. Therefore, we debate the main factors that influence the viral detection of SARS-COV-2 and how they can affect the diagnosis of patients.

Expert Opinion

Here is highlighted and discussed several factors that can interfere in the RT-PCR analysis, such as the viral load of the sample, collection site, collection methodology, sample storage, transport, primer, and probe mismatch/dimerization in different brand kits. This is a pioneer study to discuss the factor that could lead to the wrong interpretation of RT-qPCR diagnosis of SARS-CoV-2. This study aimed to help the readers to understand what very likely is behind a bad result of SARS-CoV-2 detection by RT-PCR and what could be done to reach a reliable diagnosis.

Computational Design of Multiplex Oligonucleotide-Based Assays

The success of any oligonucleotide-based experiment strongly depends on the accurate design of the components. Oli2go is a user-friendly web tool that provides efficient multiplex oligonucleotide design including specificity and primer dimer checks. Its fully automated workflow involves important design steps that use specific parameters to produce high-quality oligonucleotides. This chapter describes how these steps are computationally implemented by oli2go.

Full pathogen characterisation: species identification including the detection of virulence factors and antibiotic resistance genes via multiplex DNA-assays

Antibiotic resistances progressively cause treatment failures, and their spreading dynamics reached an alarming level. Some strains have already been classified as highly critical, e.g. the ones summarised by the acronym ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp.). To restrain this trend and enable effective medication, as much information as possible must be obtained in the least possible time. Here, we present a DNA microarray-based assay that screens for the most important sepsis-relevant 44 pathogenic species, 360 virulence factors (mediate pathogenicity in otherwise non-pathogenic strains), and 409 antibiotic resistance genes in parallel. The assay was evaluated with 14 multidrug resistant strains, including all ESKAPE pathogens, mainly obtained from clinical isolates. We used a cost-efficient ligation-based detection platform designed to emulate the highly specific multiplex detection of padlock probes. Results could be obtained within one day, requiring approximately 4 h for amplification, application to the microarray, and detection.

Genetic Approaches for the Treatment of Facioscapulohumeral Muscular Dystrophy

Facioscapulohumeral muscular dystrophy (FSHD) is an autosomal dominant disorder characterized by progressive, asymmetric muscle weakness at the face, shoulders, and upper limbs, which spreads to the lower body with age. It is the third most common inherited muscular disorder worldwide. Around 20% of patients are wheelchair-bound, and some present with extramuscular manifestations. FSHD is caused by aberrant expression of the double homeobox protein 4 (DUX4) gene in muscle. DUX4 codes for a transcription factor which, in skeletal muscle, dysregulates numerous signaling activities that culminate in cytotoxicity. Potential treatments for FSHD therefore aim to reduce the expression of DUX4 or the activity of its toxic protein product. In this article, we review how genetic approaches such as those based on oligonucleotide and genome editing technologies have been developed to achieve these goals. We also outline the challenges these therapies are facing on the road to translation, and discuss possible solutions and future directions.

High Throughput Sequencing for the Detection and Characterization of RNA Viruses

This review aims to assess and recommend approaches for targeted and agnostic High Throughput Sequencing of RNA viruses in a variety of sample matrices. HTS also referred to as deep sequencing, next generation sequencing and third generation sequencing; has much to offer to the field of environmental virology as its increased sequencing depth circumvents issues with cloning environmental isolates for Sanger sequencing. That said however, it is important to consider the challenges and biases that method choice can impart to sequencing results. Here, methodology choices from RNA extraction, reverse transcription to library preparation are compared based on their impact on the detection or characterization of RNA viruses.

The influence of quality of primers on the formation of primer dimers in PCR

Polymerase chain reaction (PCR) is the most commonly used method for nucleic acids amplification. PCR performance depends on several causes, among which the quality of primers is one of the main determinants affecting specificity, sensitivity and reliability of the reaction. Here, we report on the results of the detailed study devoted to the dimerization of the primers during PCR. The course and specificity of the reaction were studied on the model DNA templates as well as genomic DNA using primers that form amplifiable heterodimeric structures with different thermodynamic stability. It was confirmed that more than two 3'-overlapping nucleotides cause a considerable accumulation of primer dimers. It turned out that the presence of any DNA promotes the formation of dimers even for primers, which do not tend to nonspecific amplification in the absence of DNA. It was shown that dimerization could not be eliminated by commonly used techniques. Even the use of hot-start DNA polymerases does not prevent PD formation if primers with stable 3'-overlapping are employed. Despite several advantages of PCR with abutting primers, their close disposition has no benefits regarding the formation of PD if low-quality primers are utilized.