High-Throughput SNP Genotyping by SBE/SBH

Despite much progress over the past decade, current Single Nucleotide Polymorphism (SNP) genotyping technologies still offer an insufficient degree of multiplexing when required to handle user-selected sets of SNPs. In this paper we propose a new genotyping assay architecture combining multiplexed solution-phase single-base extension (SBE) reactions with sequencing by hybridization (SBH) using universal DNA arrays such as all $k$-mer arrays. In addition to PCR amplification of genomic DNA, SNP genotyping using SBE/SBH assays involves the following steps: (1) Synthesizing primers complementing the genomic sequence immediately preceding SNPs of interest; (2) Hybridizing these primers with the genomic DNA; (3) Extending each primer by a single base using polymerase enzyme and dideoxynucleotides labeled with 4 different fluorescent dyes; and finally (4) Hybridizing extended primers to a universal DNA array and determining the identity of the bases that extend each primer by hybridization pattern analysis. Our contributions include a study of multiplexing algorithms for SBE/SBH genotyping assays and preliminary experimental results showing the achievable tradeoffs between the number of array probes and primer length on one hand and the number of SNPs that can be assayed simultaneously on the other. Simulation results on datasets both randomly generated and extracted from the NCBI dbSNP database suggest that the SBE/SBH architecture provides a flexible and cost-effective alternative to genotyping assays currently used in the industry, enabling genotyping of up to hundreds of thousands of user-specified SNPs per assay.Comment: 19 page

DEVELOPMENT AND APPLICATION OF 1536-PLEX SINGLE NUCLEOTIDE POLYMORPHISM MARKER CHIP FOR GENOME WIDE SCANNING OF INDONESIAN RICE GERMPLASM

A successful molecular breeding program requires detailed and comprehensive understanding of the diversity of rice germ-plasm and genetic base of target traits. The objective of this research was to develop the high throughput 1536-SNP chip linked to heading date and yield component traits and used it for genotyping the diverse Indonesian rice germplasm. The genotype data obtained could be used for diversity analysis and genome wide association mapping study. A 1536-SNP genome wide assay was developed using the Illumina’s GoldenGate technology. The SNP markers were selected in the rice genome regions containing heading date and yield component genes or regions where the quantitative trait loci (QTLs) of the two traits were mapped. The developed custom SNP chips were then used for genotyping 467 rice accessions showing diversity in heading dates and yield components. The assay can reliably be used for diversity analysis and mapping genes associated with heading date and yield component traits. For 1536-SNP BIO-RiceOPA-1 custom chip designed, a total of 34.832 SNPs distributed in rice genome particularly in the region of heading date and yield component genes or QTLs were identified. A total of 1536-SNP were selected and confirmed to be used for genotyping analysis. Analysis performance and quality of 1536-SNP BIO-RiceOPA1 showed that 60% (918/1536) of total SNP markers had a good differentiating power in scanning the rice accessions tested (MAF > 0.2). The 1536-SNP genome wide assay Illumina’s GoldenGate designed was useful for diversity analysis and could be used as SNP marker for large scale genotyping in rice molecular breeding involving Indica-Indica, Indica-Japonica and Indica-Tropical Japonica crosses

Integrating genomic resources to present full gene and putative promoter capture probe sets for bread wheat

BACKGROUND: Whole-genome shotgun resequencing of wheat is expensive because of its large, repetitive genome. Moreover, sequence data can fail to map uniquely to the reference genome, making it difficult to unambiguously assign variation. Resequencing using target capture enables sequencing of large numbers of individuals at high coverage to reliably identify variants associated with important agronomic traits. Previous studies have implemented complementary DNA/exon or gene-based probe sets in which the promoter and intron sequence is largely missing alongside newly characterized genes from the recent improved reference sequences. RESULTS: We present and validate 2 gold standard capture probe sets for hexaploid bread wheat, a gene and a putative promoter capture, which are designed using recently developed genome sequence and annotation resources. The captures can be combined or used independently. We demonstrate that the capture probe sets effectively enrich the high-confidence genes and putative promoter regions that were identified in the genome alongside a large proportion of the low-confidence genes and associated promoters. Finally, we demonstrate successful sample multiplexing that allows generation of adequate sequence coverage for single-nucleotide polymorphism calling while significantly reducing cost per sample for gene and putative promoter capture. CONCLUSIONS: We show that a capture design employing an "island strategy" can enable analysis of the large gene/putative promoter space of wheat with only 2 × 160 Mbp probe sets. Furthermore, these assays extend the regions of the wheat genome that are amenable to analyses beyond its exome, providing tools for detailed characterization of these regulatory regions in large populations

MOL-PCR For SNP Based Detection and Characterization of STEC non-O157 Strains

Shiga toxin-producing Escherichia coli (STEC) strains are important food-borne pathogens that have been linked to human illness. In the United States, STEC O157:H7 strains have been attributed to the majority of disease and outbreaks; however, the frequency of disease associated with STEC non-O157 strains have also increased and is often under recognized due to diagnostic limitations. In 2012, the Food Safety and Inspection Service (FSIS) implemented mandatory testing for non-O157 STEC serogroups O26, O45, O103, O111, O121, and O145. Single nucleotide polymorphisms (SNPs) have been identified in the O-antigen gene cluster for each of the non-O157 STEC serogroups that can differentiate between a STEC and non-STEC strain. In this study, the multiplex oligonucleotide ligation-PCR (MOL-PCR) detection platform was adapted for the detection and characterization of the above-described non-O157 STEC serogroups. The SNP-based MOL-PCR assay has demonstrated the ability to simultaneously detect the non-O157 serogroups and characterize the strain based on the SNP discriminates identified for each serogroup. This work provides a potential diagnostic platform that can reduce diagnostic limitations for the detection of non-O157 serogroups

Study of Strategies for Genetic Variant Discrimination and Detection by Optosensing

Tesis por compendio[ES] La medicina actual se dirige hacia un enfoque más personalizado basándose en el diagnóstico molecular del paciente a través del estudio de biomarcadores específicos. Aplicando este principio molecular, el diagnóstico, pronóstico y selección de la terapia se apoyan en la identificación de variaciones específicas del genoma humano, como variaciones de un único nucleótido (SNV). Para detectar estos biomarcadores se dispone de una amplia oferta de tecnologías. Sin embargo, muchos de los métodos en uso presentan limitaciones como un elevado coste, complejidad, tiempos de análisis largos o requieren de personal y equipamiento especializado, lo que imposibilita su incorporación masiva en la mayoría de los sistemas sanitarios. Por tanto, existe la necesidad de investigar y desarrollar soluciones analíticas que aporten información sobre las variantes genéticas y que se puedan implementar en diferentes escenarios del ámbito de la salud con prestaciones competitivas y económicamente viables. El objetivo principal de esta tesis ha sido desarrollar estrategias innovadoras para resolver el reto de la detección múltiple de variantes genéticas que se encuentran en forma minoritaria en muestras biológicas de pacientes, cubriendo las demandas asociadas al entorno clínico. Las tareas de investigación se centraron en la combinación de reacciones de discriminación alélica con amplificación selectiva de DNA y el desarrollo de sistemas ópticos de detección versátiles. Con el fin de atender el amplio abanico de necesidades, en el primer capítulo, se presentan resultados que mejoran las prestaciones analíticas de la reacción en cadena de la polimerasa (PCR) mediante la incorporación de una etapa al termociclado y de un agente bloqueante amplificando selectivamente las variantes minoritarias que fueron monitorizadas mediante fluorescencia a tiempo real. En el segundo capítulo, se logró la discriminación alélica combinando la ligación de oligonucleótidos con la amplificación de la recombinasa polimerasa (RPA), que al operar a temperatura constante permitió una detección tipo point-of-care (POC). La identificación de SNV se llevó a cabo mediante hibridación en formato micromatriz, utilizando la tecnología Blu-Ray como plataforma de ensayo y detección. En el tercer capítulo, se integró la RPA con la reacción de hibridación alelo especifica en cadena (AS-HCR), en formato array para genotipar SNV a partir de DNA genómico en un chip. La lectura de los resultados se realizó mediante un smartphone. En el último capítulo, se presenta la síntesis de un nuevo reactivo bioluminiscente que se aplicó a la monitorización de biomarcadores de DNA a tiempo real y final de la RPA basada en la transferencia de energía de resonancia de bioluminiscencia (BRET), eliminando la necesidad de una fuente de excitación. Todas las estrategias permitieron un reconocimiento especifico de la variante de interés, incluso en muestras que contenían tan solo 20 copias de DNA genómico diana. Se consiguieron resultados sensibles (límite de detección 0.5% variante/total), reproducibles (desviación estándar relativa < 19%), de manera sencilla (3 etapas o menos), rápida (tiempos cortos de 30-200 min) y permitiendo el análisis simultaneo de varios genes. Como prueba de concepto, estas estrategias se aplicaron a la detección e identificación en muestras clínicas de biomarcadores asociados a cáncer colorrectal y enfermedades cardiológicas. Los resultados se validaron por comparación con los métodos de referencia NGS y PCR, comprobándose que se mejoraban los requerimientos técnicos y la relación coste-eficacia. En conclusión, las investigaciones llevadas a cabo posibilitaron desarrollar herramientas de genotipado con propiedades analíticas competitivas y versátiles, aplicables a diferentes escenarios sanitarios, desde hospitales a entornos con pocos recursos. Estos resultados son prometedores al dar respuesta a la demanda de tecnologías alternativas para el diagnóstico molecular personalizado.[CA] La medicina actual es dirigeix cap a un enfocament més personalitzat basant-se en el diagnòstic molecular del pacient a través de l'estudi de biomarcadors específics. Aplicant aquest principi molecular, el diagnòstic, pronòstic i selecció de la teràpia es recolzen en la identificació de variacions específiques del genoma humà, com variacions d'un únic nucleòtid (SNV). Per a detectar aquests biomarcadors, es disposa d'una àmplia oferta de tecnologies. No obstant això, molts dels mètodes en ús presenten limitacions com un elevat cost, complexitat, temps d'anàlisis llargues o requereixen de personal i equipament especialitzat, la qual cosa impossibilita la seua incorporació massiva en la majoria dels sistemes sanitaris. Per tant, existeix la necessitat d'investigar i desenvolupar solucions analítiques que aporten informació sobre les variants genètiques i que es puguen implementar en diferents escenaris de l'àmbit de la salut amb prestacions competitives i econòmicament viables. L'objectiu principal d'aquesta tesi ha sigut desenvolupar estratègies innovadores per a resoldre el repte de la detecció múltiple de variants genètiques que es troben en forma minoritària en mostres biològiques de pacients, cobrint les demandes associades a l'entorn clínic. Les tasques d'investigació es van centrar en la combinació de reaccions de discriminació al·lèlica amb amplificació selectiva de DNA i al desenvolupament de sistemes òptics de detecció versàtils. Amb la finalitat d'atendre l'ampli ventall de necessitats, en el primer capítol, es presenten resultats que milloren les prestacions analítiques de la reacció en cadena de la polimerasa (PCR) mitjançant la incorporació d'una etapa al termociclat i d'un agent bloquejant amplificant selectivament les variants minoritàries que van ser monitoritzades mitjançant fluorescència a temps real. En el segon capítol, es va aconseguir la discriminació al·lèlica combinant el lligament d'oligonucleòtids amb l'amplificació de la recombinasa polimerasa (RPA), que en operar a temperatura constant va permetre una detecció tipus point-of-care (POC). La identificació de SNV es va dur a terme mitjançant hibridació en format micromatriu, utilitzant la tecnologia Blu-Ray com a plataforma d'assaig i detecció. En el tercer capítol, es va integrar la RPA amb la reacció d'hibridació al·lel específica en cadena (AS-HCR), en format matriu per a genotipar SNV a partir de DNA genòmic en un xip. La lectura dels resultats es va realitzar mitjançant un telèfon intel·ligent. En l'últim capítol, es presenta la síntesi d'un nou reactiu bioluminescent que es va aplicar al monitoratge de biomarcadors de DNA a temps real i final de la RPA basada en la transferència d'energia de ressonància de bioluminescència (BRET), eliminant la necessitat d'una font d'excitació. Totes les estratègies van permetre un reconeixement específic de la variant d'interès, fins i tot en mostres que només contenien 20 còpies de DNA genòmic diana. Es van aconseguir resultats sensibles (límit de detecció 0.5% variant/total), reproduïbles (desviació estàndard relativa < 19%), de manera senzilla (3 etapes o menys), ràpida (temps curts de 30-200 min) i permetent l'anàlisi simultània de diversos gens. Com a prova de concepte, aquestes estratègies es van aplicar a la detecció i identificació en mostres clíniques de biomarcadors associats a càncer colorectal i a malalties cardiològiques. Els resultats es van validar per comparació amb els mètodes de referència NGS i PCR, comprovant-se que es milloraven els requeriments tècnics i la relació cost-eficàcia. En conclusió, les investigacions dutes a terme van possibilitar desenvolupar eines de genotipat amb propietats analítiques competitives i versàtils, aplicables a diferents escenaris sanitaris, des d'hospitals a entorns amb pocs recursos. Aquests resultats són prometedors en donar resposta a la demanda de tecnologies alternatives per al diagnòstic molecular personalitzat.[EN] Current medicine is moving towards a more personalized approach based on the patients' molecular diagnosis through the study of specific biomarkers. Diagnosis, prognosis and therapy selection, applying this molecular principle, rely on identifying specific variations in the human genome, such as single nucleotide variations (SNV). A wide range of technologies is available to detect these biomarkers. However, many of the employed methods have limitations such as high cost, complexity, long analysis times, or requiring specialized personnel and equipment, making their massive incorporation in most healthcare systems impossible. Therefore, there is a need to research and develop analytical solutions that provide information on genetic variants that can be implemented in different health scenarios with competitive and economically feasible performances. The main objective of this thesis has been to develop innovative strategies to solve the challenge of multiple detection of genetic variants that are found in a minority amount in patient samples, covering the demands associated with the clinical setting. Research tasks focused on the combination of allelic discrimination reactions with selective DNA amplification and the development of versatile optical detection systems. In order to meet the wide range of needs, in the first chapter, the analytical performances of the polymerase chain reaction (PCR) were improved by incorporating a thermocycling step and a blocking agent to amplify selectively minority variants that were monitored by real-time fluorescence. In the second chapter, allelic discrimination was achieved by combining oligonucleotide ligation with recombinase polymerase amplification (RPA), which operates at a constant temperature, allowing point-of-care (POC) detection. SNV identification was carried out by hybridization in microarray format, using Blu-Ray technology as the assay platform and detector. RPA was integrated with allele-specific hybridization chain reaction (AS-HCR), in an array format to genotype SNV from genomic DNA on a chip in the third chapter. The reading of the results was performed using a smartphone. In the last chapter, a new bioluminescent reagent was synthesized. It was applied to real-time and endpoint DNA biomarker monitoring based on bioluminescence resonance energy transfer (BRET), eliminating the need for an excitation source. All the strategies allowed specific recognition of the target variant, even in samples containing as few as 20 copies of target genomic DNA. Sensitive (limit of detection 0.5% variant/total), reproducible (relative standard deviation < 19%), simple (3 steps or less), fast (short times of 30-200 min) results were achieved, allowing simultaneous analysis of several genes. As proof of concept, these strategies were applied to detect and identify biomarkers associated with colorectal cancer and cardiological diseases in clinical samples. The results were validated by comparison with reference methods such as NGS and PCR, proving that the technical requirements and cost-effectiveness were improved. In conclusion, the developed research made it possible to develop genotyping tools with competitive analytical properties and versatile, applicable to different healthcare scenarios, from hospitals to limited-resource environments. These results are promising since they respond to the demand for alternative technologies for personalized molecular diagnostics.The authors acknowledge the financial support received from the Generalitat Valenciana PROMETEO/2020/094, GRISOLIA/2014/024 PhD Grant and GVA-FPI-2017 PhD grant, the Spanish Ministry of Economy and Competitiveness MINECO projects CTQ2016-75749-R and PID2019-110713RB-I00 and European Regional Development Fund (ERDF).Lázaro Zaragozá, A. (2022). Study of Strategies for Genetic Variant Discrimination and Detection by Optosensing [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/185216TESISCompendi

DEVELOPMENT OF MICROFLUIDIC PLATFORMS AS A TOOL FOR HIGH-THROUGHPUT BIOMARKER SCREENING

Droplet microfluidic platforms are in the early stages of revolutionizing high throughput and combinatorial sample screening for bioanalytical applications. However, many droplet platforms are incapable of addressing the needs of numerous applications, which require high degrees of multiplexing, as well as high-throughput analysis of multiple samples. Examples of applications include single nucleotide polymorphism (SNP) analysis for crop improvement and genotyping for the identification of genes associated with common diseases. My PhD thesis focused on developing microfluidic devices to extend their capabilities to meet the needs of a wide array of applications

Optimizing the sensitivity and specificity of genetic disease detection / by Travis E. Marion.

The molecular diagnosis of genetic disease is of great importance to the field of medicine and medical research. Though many rare inherited diseases have been described in the medical literature, the inheritance pattern of more common diseases has yet to be established. Until recently evolutionary disease research has been conducted either by molecular diagnosis of those living with the disease or by archaeological investigations examining the morphological pathologies of tissue remains. It was the purpose of this study to design and optimize a PCR based multi-stepped multiplexed SNE methodology to detect -haemoglobinopathy biomarkers that could be applied to degraded medical and archaeological specimens and expand upon previous work. In order to apply the methodology to degraded tissue samples it was hypothesized that the necessary increase specificity and sensitivity could be obtained by increasing the number of primers used to amplify target sequences and by using the products of previous PCR reactions in subsequent PCR reactions respectively. Furthermore by multiplexing and incorporating an SBE SNP detection methodology the amount o f time, cost, involved in genetic disease detection could be reduced. The optimal methodology to be followed in future applications consists o f three sequential steps: multiplex PCR, hemi-nested PCR, and single base primer extension SNP detection. It was through this methodology that multiple gene amplifications were produced and sequenced from dilution extracts o f 1:1000000 that exhibited 100% homology to the reference sequence. With the increase in detection sensitivity and specificity, multiplex capabilities and the involvement o f SNP detection this methodology can be expanded to detect multiple genetic mutations/variants and be applied to medical screening, association studies, population mapping, identification o f individuals, evolutionary disease studies, and validate pre-existing research

Forensic Ancestry Analysis with Autosomal Polymorphisms

The inference of ancestry from biological material left at a crimescene has been a longstanding but specialised forensic technique, often lacking sufficient detail to make a reliable inference of ancestr y. This thesis describes the key steps in developing a forensic ancestry test that can be adopted by any laboratory using capillary electrophoresis equipment: optimisation of a PCR multiplex to detect DNA markers from contact traces; compilation of population data from which to infer the likely pop ulation of origin of the person; detection of coancestry patterns in an individual with admixed backgr ounds; and development of online statistical tools that calculate the probability of an individual’s an cestry from a submitted SNP profile. Additional types of autosomal markers were compiled from Ind el polymorphisms; short tandem repeats (STRs); multiple allele SNPs; and Microhaplotype markers

Methods, Models, and Machine Learning Approaches for Understanding Pathogen-Specific Humoral Immunity

The humoral immune response is comprised of vast libraries of polyclonal antibodies capable of recognizing a myriad of targets and directing a spectrum of innate immune functions. The complex heterogeneity in antibody profiles across both populations and diseases makes defining mechanisms of protection difficult. Understanding these mechanisms and the factors that influence them is essential to defining immunity and helps inform the design of vaccines and therapeutics. Thus, in this thesis, I describe five studies that present the development of experimental and computational methods, and machine learning approaches for investigating the mechanisms, dynamics, and determinants of pathogen-specific humoral immunity. The first study introduces an assay for probing antigen-specific antibody mediated primary monocyte phagocytosis, that is capable of capturing subsequent downstream functions. The second study describes a machine learning approach for defining the correlates of upper and lower respiratory protection against RSV and methods for evaluating vaccine designs. The third study uses machine learning methods to uncover signatures of humoral protection against SARS-CoV-2. The fourth study presents a method for longitudinally modelling humoral immunity that was used to investigate the temporal dynamics of antibody features across individuals with varying COVID-19 severity. Finally, the last study describes a genome-wide association screen of pathogen-specific polyclonal antibody characteristics and functions that was then validated with transcriptomics data. Ultimately, the methods described in this thesis present new approaches for investigating underlying phenomena related to pathogen-specific humoral immunity.Ph.D