Limits of Performance of Quantitative Polymerase Chain Reaction Systems

Estimation of the DNA copy number in a given biological sample is an important problem in genomics. Quantitative polymerase chain reaction (qPCR) systems detect the target DNA molecules by amplifying their number through a series of thermal cycles and measuring the amount of created amplicons in each cycle. Ideally, the number of target molecules doubles at the end of each cycle. However, in practice, due to biochemical noise the efficiency of the qPCR reaction—defined as the fraction of the target molecules which are successfully copied during a cycle—is always less than 1. In this paper, we formulate the problem of the joint maximum-likelihood estimation of the qPCR efficiency and the initial DNA copy number. Then, we analytically determine the limits of performance of qPCR by deriving the Cramer–Rao lower bound on the mean-square estimation error. As indicated by simulation studies, the performance of the proposed estimator is superior compared to competing statistical approaches. The proposed approach is validated using experimental data

A Long-Term Neuroepigenomic Profile of Prenatal Alcohol Exposure

Fetal Alcohol Spectrum Disorders (FASD) represent the largest preventable cause of cognitive deficits in the western world. The mechanism(s) of how prenatal alcohol exposure (PAE) results in FASD remain unknown. Towards this end, mouse models of PAE have successfully recreated endophenotypes that are characteristic of FASD. This doctoral thesis examines the long-term epigenomic alterations associated with PAE. I have examined both mice with PAE and human patients with FASD. In the first set of experiments, mice with PAE and matched controls were raised to adulthood and then their whole brains were examined for alterations to gene expression, non-coding RNA (ncRNA) expression, and DNA methylation. Long-term alterations were observed in genes related to neurodevelopment, cellular signaling, and immune processes. Furthermore, there was an enrichment for alterations to genomically imprinted clusters of ncRNA and genes related to PTEN/PI3K/AKT/mTOR signaling. In the second set of experiments, buccal epithelial swabs were collected from young children with FASD and matched controls. Children from a discovery cohort were examined for alterations to DNA methylation, which revealed changes to genes involved in neurodevelopment and synaptic signaling as well as hippo signaling. Select candidates (COLEC11 and HTT) were confirmed by sodium bisulfite pyrosequencing. Examination of a replication cohort revealed that while similar pathways are altered, the effect is not identical and that sex and age may alter the methylation profile. A larger group of children, representative of the general population, were then analyzed using a targeted sodium bisulfite next-generation sequencing panel and pyrosequencing. No single gene examined was found to be consistently affected in all FASD children. Finally, the mouse and human results were compared to identify alterations to shared loci, ontologies, and pathways. The clustered protocadherins, which are involved in generating individual neuronal identity, showed increased DNA methylation in both species. Together, the results suggest that a shared DNA methylation profile related to neurodevelopment is present in both the brains of adult mice and the buccal epithelial swabs of young children with PAE. These results may be used in future functional studies of candidate loci as well as towards the development of much needed diagnostics and precision medicine

Neurodevelopmental Consequences of Prenatal Alcohol Exposure: Behavioural and Transcriptomic Alterations in a Mouse Model

Fetal Alcohol Spectrum Disorder (FASD) is an umbrella term referring to a range of physical, behavioural, and cognitive deficits resulting from prenatal alcohol exposure. The resulting abnormalities are heterogeneous and often attributed to timing and dosage of alcohol exposure. However, the specific effects of developmental timing are not well-known. This research used C57BL/6J (B6) as an animal model for early (human trimester one) and mid-gestation (human trimester two) alcohol exposure. Pregnant B6 mice were injected with 2.5 g/kg ethanol on gestational day (GD) 8 and 11 (trimester one equivalent), or on GD 14 and 16 (trimester two equivalent). Resulting pups were followed from birth to adulthood using FASD-relevant behavioural tests. At postnatal day (PD) 70, whole brain tissues were extracted. A third group of dams were injected on GD 16 (short-term). Two hours post injection, fetal brains were removed. Brains were used for genome-wide expression analysis, including microRNAs. Downstream analyses were completed using software packages and online databases. All ethanol-treated pups showed motor skill delays, increased activity, and spatial learning deficits. Gene expression analysis resulted in altered expression of 48 short-term genes between ethanol and control mice treated during the second trimester. Fifty-five and 68 genes were differentially-expressed in the long-term analyses of mice treated during trimester one and two, respectively. Genes involved in immune system response were disrupted across all treatments. Disrupted short-term processes included cytoskeleton development and immunological functions. Processes altered in long-term exposures included stress signaling, DNA stability, and cellular proliferation. MicroRNA analyses returned eight and 20 differentially-expressed miRNAs in trimesters one and two, respectively. Target filtering of trimester one microRNAs and mRNAs resulted in inverse relationships between miR-532-5p and Atf1, Itpripl2, and Stxbp6. Trimester two target filtering resulted in miR-302c targeting Ccdc6. Gene expression and microRNA results demonstrate the stage-specific genes and processes altered during neurodevelopment upon ethanol exposure. Certain cellular processes are disrupted no matter the timing of ethanol exposure. Given that microRNAs are fine-tuners of gene expression, they may play an important role in the maintenance of FASD. Furthermore, transcriptomic changes in the brain may explain the observed behavioural effects of prenatal ethanol exposure

Structual variation detection in the human genome

Thesis advisor: Gabor T. MarthStructural variations (SVs), like single nucleotide polymorphisms (SNPs) and short insertion-deletion polymorphisms (INDELs), are a ubiquitous feature of genomic sequences and are major contributors to human genetic diversity and disease. Due to technical difficulties, i.e. the high data-acquisition cost and/or low detection resolution of previous genome-scanning technologies, this source of genetic variation has not been well studied until the completion of the Human Genome Project and the emergence of next-generation sequencing (NGS) technologies. The assembly of the human genome and economical high-throughput sequencing technologies enable the development of numerous new SV detection algorithms with unprecedented accuracy, sensitivity and precision. Although a number of SV detection programs have been developed for various SV types, such as copy number variations, deletions, tandem duplications, inversions and translocations, some types of SVs, e.g. copy number variations (CNVs) in capture sequencing data and mobile element insertions (MEIs) have undergone limited study. This is a result of the lack of suitable statistical models and computational approaches, e.g. efficient mapping method to handle multiple aligned reads from mobile element (ME) sequences. The focus of my dissertation was to identify and characterize CNVs in capture sequencing data and MEI from large-scale whole-genome sequencing data. This was achieved by building sophisticated statistical models and developing efficient algorithms and analysis methods for NGS data. In Chapter 2, I present a novel algorithm that uses the read depth (RD) signal to detect CNVs in deep-coverage exon capture sequencing data that are originally designed for SNPs discovery. We were one of the early pioneers to tackle this problem. In Chapter 3, I present a fast, convenient and memory-efficient program, Tangram, that integrates read-pair (RP) and split-read (SR) signals to detect and genotype MEI events. Based on the results from both simulated and experimental data, Tangram has superior sensitivity, specificity, breakpoint resolution and genotyping accuracy, when compared to other recently published MEI detection methods. Lastly, Chapter 4 summarizes my work for SV detection in human genomes during my PhD study and describes the future direction of genetic variant researches.Thesis (PhD) — Boston College, 2013.Submitted to: Boston College. Graduate School of Arts and Sciences.Discipline: Biology