School of Mathematics and Statistics - Research Publications

SNP barcodes provide higher resolution than microsatellite markers to measurePlasmodium vivaxpopulation genetics

2020-11-22T00:45:18Z

Fola, AA; Kattenberg, E; Razook, Z; Lautu-Gumal, D; Lee, S; Mehra, S; Bahlo, M; Kazura, J; Robinson, LJ; Laman, M; Mueller, I; Barry, AE 2020-10-20 SNP barcodes provide higher resolution than microsatellite markers to measurePlasmodium vivaxpopulation genetics BACKGROUND: Genomic surveillance of malaria parasite populations has the potential to inform control strategies and to monitor the impact of interventions. Barcodes comprising large numbers of single nucleotide polymorphism (SNP) markers are accurate and efficient genotyping tools, however may need to be tailored to specific malaria transmission settings, since 'universal' barcodes can lack resolution at the local scale. A SNP barcode was developed that captures the diversity and structure of Plasmodium vivax populations of Papua New Guinea (PNG) for research and surveillance. METHODS: Using 20 high-quality P. vivax genome sequences from PNG, a total of 178 evenly spaced neutral SNPs were selected for development of an amplicon sequencing assay combining a series of multiplex PCRs and sequencing on the Illumina MiSeq platform. For initial testing, 20 SNPs were amplified in a small number of mono- and polyclonal P. vivax infections. The full barcode was then validated by genotyping and population genetic analyses of 94 P. vivax isolates collected between 2012 and 2014 from four distinct catchment areas on the highly endemic north coast of PNG. Diversity and population structure determined from the SNP barcode data was then benchmarked against that of ten microsatellite markers used in previous population genetics studies. RESULTS: From a total of 28,934,460 reads generated from the MiSeq Illumina run, 87% mapped to the PvSalI reference genome with deep coverage (median = 563, range 56-7586) per locus across genotyped samples. Of 178 SNPs assayed, 146 produced high-quality genotypes (minimum coverage = 56X) in more than 85% of P. vivax isolates. No amplification bias was introduced due to either polyclonal infection or whole genome amplification (WGA) of samples before genotyping. Compared to the microsatellite panels, the SNP barcode revealed greater variability in genetic diversity between populations and geographical population structure. The SNP barcode also enabled assignment of genotypes according to their geographic origins with a significant association between genetic distance and geographic distance at the sub-provincial level. CONCLUSIONS: High-throughput SNP barcoding can be used to map variation of malaria transmission dynamics at sub-national resolution. The low cost per sample and genotyping strategy makes the transfer of this technology to field settings highly feasible. Journal Article

Estimation of the force of infection and infectious period of skin sores in remote Australian communities using interval-censored data

2020-11-22T00:45:13Z

Lydeamore, MJ; Campbell, PT; Price, DJ; Wu, Y; Marcato, AJ; Cuningham, W; Carapetis, JR; Andrews, RM; McDonald, M; McVernon, J; Tong, SYC; McCaw, JM 2020-10-01 Estimation of the force of infection and infectious period of skin sores in remote Australian communities using interval-censored data Prevalence of impetigo (skin sores) remains high in remote Australian Aboriginal communities, Fiji, and other areas of socio-economic disadvantage. Skin sore infections, driven primarily in these settings by Group A Streptococcus (GAS) contribute substantially to the disease burden in these areas. Despite this, estimates for the force of infection, infectious period and basic reproductive ratio—all necessary for the construction of dynamic transmission models—have not been obtained. By utilising three datasets each containing longitudinal infection information on individuals, we estimate each of these epidemiologically important parameters. With an eye to future study design, we also quantify the optimal sampling intervals for obtaining information about these parameters. We verify the estimation method through a simulation estimation study, and test each dataset to ensure suitability to the estimation method. We find that the force of infection differs by population prevalence, and the infectious period is estimated to be between 12 and 20 days. We also find that optimal sampling interval depends on setting, with an optimal sampling interval between 9 and 11 days in a high prevalence setting, and 21 and 27 days for a lower prevalence setting. These estimates unlock future model-based investigations on the transmission dynamics of skin sores. Journal Article

Key questions for modelling COVID-19 exit strategies

2020-11-22T00:38:44Z

Thompson, RN; Hollingsworth, TD; Isham, V; Arribas-Bel, D; Ashby, B; Britton, T; Challenor, P; Chappell, LHK; Clapham, H; Cunniffe, NJ; Dawid, AP; Donnelly, CA; Eggo, RM; Funk, S; Gilbert, N; Glendinning, P; Gog, JR; Hart, WS; Heesterbeek, H; House, T; Keeling, M; Kiss, IZ; Kretzschmar, ME; Lloyd, AL; McBryde, ES; McCaw, JM; McKinley, TJ; Miller, JC; Morris, M; O'Neill, PD; Parag, K; Pearson, CAB; Pellis, L; Pulliam, JRC; Ross, J; Tomba, GS; Silverman, BW; Struchiner, CJ; Tildesley, MJ; Trapman, P; Webb, CR; Mollison, D; Restif, O 2020-08-12 Key questions for modelling COVID-19 exit strategies Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health. Journal Article

Targeting triple-negative breast cancers with the Smac-mimetic birinapant

2020-11-22T00:38:40Z

Lalaoui, N; Merino, D; Giner, G; Vaillant, F; Chau, D; Liu, L; Kratina, T; Pal, B; Whittle, JR; Etemadi, N; Berthelet, J; Grasel, J; Hall, C; Ritchie, ME; Ernst, M; Smyth, GK; Vaux, DL; Visvader, JE; Lindeman, GJ; Silke, J 2020-04-27 Targeting triple-negative breast cancers with the Smac-mimetic birinapant Smac mimetics target inhibitor of apoptosis (IAP) proteins, thereby suppressing their function to facilitate tumor cell death. Here we have evaluated the efficacy of the preclinical Smac-mimetic compound A and the clinical lead birinapant on breast cancer cells. Both exhibited potent in vitro activity in triple-negative breast cancer (TNBC) cells, including those from patient-derived xenograft (PDX) models. Birinapant was further studied using in vivo PDX models of TNBC and estrogen receptor-positive (ER+) breast cancer. Birinapant exhibited single agent activity in all TNBC PDX models and augmented response to docetaxel, the latter through induction of TNF. Transcriptomic analysis of TCGA datasets revealed that genes encoding mediators of Smac-mimetic-induced cell death were expressed at higher levels in TNBC compared with ER+ breast cancer, resulting in a molecular signature associated with responsiveness to Smac mimetics. In addition, the cell death complex was preferentially formed in TNBCs versus ER+ cells in response to Smac mimetics. Taken together, our findings provide a rationale for prospectively selecting patients whose breast tumors contain a competent death receptor signaling pathway for the further evaluation of birinapant in the clinic. Journal Article

Exploring the association between BMI and mortality in Australian women and men with and without diabetes: the AusDiab study

2020-11-28T12:39:52Z

Zahir, SF; Griffin, A; Veerman, JL; Magliano, DJ; Shaw, JE; Kim-Anh, LC; Mehdi, AM 2019-05-01 Exploring the association between BMI and mortality in Australian women and men with and without diabetes: the AusDiab study AIMS/HYPOTHESIS: There is conflicting evidence about the obesity paradox-the counterintuitive survival advantage of obesity among certain subpopulations of individuals with chronic conditions. It is believed that results supporting the obesity paradox are due to methodological flaws, such as collider bias. The aim of this study was to examine the association between obesity and mortality in Australian men and women. In addition, we explored whether obesity would appear to be protective if the analysis was restricted to a subpopulation with disease, and to discuss the potential role of collider bias in producing such a result. METHODS: The examined cohort included 10,575 Australian adults (4844 men and 5731 women) aged 25-91 years who were recruited for the AusDiab baseline survey in 1999 and followed-up through 2014. The main predictor variable was BMI categorised as normal weight (18.5 to <25 kg/m2), overweight (25 to <30 kg/m2) and obese (≥30 kg/m2), and the outcome of interest was all-cause mortality. Hazard ratios were estimated from Cox proportional hazards regression models in the entire cohort and then in subpopulations with and without diabetes. RESULTS: A total of 1477 deaths occurred during 145,384 person-years (median 14.6 years) of follow-up. Mortality was higher in obese than in normal-weight individuals for the full population (HR 1.18; 95% CI 1.05, 1.32). When an interaction between diabetes status and BMI category was added to the model, there was no evidence of an interaction between BMI and diabetes status (p = 0.92). When participants with and without diabetes were analysed separately, there was no evidence of an association between obesity and mortality in those with diabetes (HR 0.91; 95% CI 0.62, 1.33). CONCLUSIONS/INTERPRETATION: In the entire AusDiab cohort, we found a significantly higher mortality among obese participants as compared with their normal-weight counterparts. We found no difference in the obesity-mortality association between individuals with and without diabetes. Journal Article

A Bayesian approach to modelling heterogeneous calcium responses in cell populations

2020-11-28T12:39:52Z

Tilunaite, A; Croft, W; Russell, N; Bellamy, TC; Thul, R 2017-10-01 A Bayesian approach to modelling heterogeneous calcium responses in cell populations Calcium responses have been observed as spikes of the whole-cell calcium concentration in numerous cell types and are essential for translating extracellular stimuli into cellular responses. While there are several suggestions for how this encoding is achieved, we still lack a comprehensive theory. To achieve this goal it is necessary to reliably predict the temporal evolution of calcium spike sequences for a given stimulus. Here, we propose a modelling framework that allows us to quantitatively describe the timing of calcium spikes. Using a Bayesian approach, we show that Gaussian processes model calcium spike rates with high fidelity and perform better than standard tools such as peri-stimulus time histograms and kernel smoothing. We employ our modelling concept to analyse calcium spike sequences from dynamically-stimulated HEK293T cells. Under these conditions, different cells often experience diverse stimulus time courses, which is a situation likely to occur in vivo. This single cell variability and the concomitant small number of calcium spikes per cell pose a significant modelling challenge, but we demonstrate that Gaussian processes can successfully describe calcium spike rates in these circumstances. Our results therefore pave the way towards a statistical description of heterogeneous calcium oscillations in a dynamic environment. Journal Article

The Genomic Signature of Splicing-Coupled Selection Differs between Long and Short Introns

2020-11-28T12:39:52Z

Farlow, A; Dolezal, M; Hua, L; Schloetterer, C 2012-01-01 The Genomic Signature of Splicing-Coupled Selection Differs between Long and Short Introns Understanding the function of noncoding regions in the genome, such as introns, is of central importance to evolutionary biology. One approach is to assay for the targets of natural selection. On one hand, the sequence of introns, especially short introns, appears to evolve in an almost neutral manner. Whereas on the other hand, a large proportion of intronic sequence is under selective constraint. This discrepancy is largely dependent on intron length and differences in the methods used to infer selection. We have used a method based on DNA strand asymmetery that does not require comparison with any putatively neutrally evolving sequence, nor sequence conservation between species, to detect selection within introns. The strongest signal we identify is associated with short introns. This signal comes from a family of motifs that could act as cryptic 5' splice sites during mRNA processing, suggesting a mechanistic justification underlying this signal of selection. Together with an analysis of intron length and splice site strength, we observe that the genomic signature of splicing-coupled selection differs between long and short introns. Journal Article

Dynamic molecular changes during the first week of human life follow a robust developmental trajectory.

2020-11-28T12:39:52Z

Lee, AH; Shannon, CP; Amenyogbe, N; Bennike, TB; Diray-Arce, J; Idoko, OT; Gill, EE; Ben-Othman, R; Pomat, WS; van Haren, SD; Cao, K-AL; Cox, M; Darboe, A; Falsafi, R; Ferrari, D; Harbeson, DJ; He, D; Bing, C; Hinshaw, SJ; Ndure, J; Njie-Jobe, J; Pettengill, MA; Richmond, PC; Ford, R; Saleu, G; Masiria, G; Matlam, JP; Kirarock, W; Roberts, E; Malek, M; Sanchez-Schmitz, G; Singh, A; Angelidou, A; Smolen, KK; EPIC Consortium; Brinkman, RR; Ozonoff, A; Hancock, REW; van den Biggelaar, AHJ; Steen, H; Tebbutt, SJ; Kampmann, B; Levy, O; Kollmann, TR 2019-03-12 Dynamic molecular changes during the first week of human life follow a robust developmental trajectory. Systems biology can unravel complex biology but has not been extensively applied to human newborns, a group highly vulnerable to a wide range of diseases. We optimized methods to extract transcriptomic, proteomic, metabolomic, cytokine/chemokine, and single cell immune phenotyping data from <1 ml of blood, a volume readily obtained from newborns. Indexing to baseline and applying innovative integrative computational methods reveals dramatic changes along a remarkably stable developmental trajectory over the first week of life. This is most evident in changes of interferon and complement pathways, as well as neutrophil-associated signaling. Validated across two independent cohorts of newborns from West Africa and Australasia, a robust and common trajectory emerges, suggesting a purposeful rather than random developmental path. Systems biology and innovative data integration can provide fresh insights into the molecular ontogeny of the first week of life, a dynamic developmental phase that is key for health and disease. Journal Article

IMI - Myopia Genetics Report

2020-11-28T12:39:52Z

Tedja, MS; Haarman, AEG; Meester-Smoor, MA; Kaprio, J; Mackey, DA; Guggenheim, JA; Hammond, CJ; Verhoeven, VJM; Klaver, CCW; Bailey-Wilson, JE; Baird, PN; Veluchamy, AB; Biino, G; Burdon, KP; Campbell, H; Chen, LJ; Cheng, C-Y; Chew, EY; Craig, JE; Cumberland, PM; Deangelis, MM; Delcourt, C; Ding, X; van Duijn, CM; Evans, DM; Fan, Q; Fossarello, M; Foster, PJ; Gharahkhani, P; Iglesias, AI; Guol, X; Haller, T; Han, X; Hayward, C; He, M; Hewitt, AW; Hoang, Q; Hysi, PG; Igo, RP; Iyengar, SK; Jonas, JB; Kahonen, M; Khawaja, AP; Klein, BE; Klein, R; Lass, JH; Lee, K; Lehtimaki, T; Lewis, D; Li, Q; Li, S-M; Lyytikainen, L-P; MacGregor, S; Martin, NG; Meguro, A; Metspalu, A; Middlebrooks, C; Miyake, M; Mizuki, N; Musolf, A; Nickels, S; Oexle, K; Pang, CP; Parssinen, O; Paterson, AD; Pfeiffer, N; Polasek, O; Rahi, JS; Raitakari, O; Rudan, I; Sahebjada, S; Saw, S-M; Stambolian, D; Simpson, CL; Tai, E-S; Tideman, JWL; Tsujikawa, A; Verhoeven, VJM; Vitart, V; Wang, N; Wedenoja, J; Wei, WB; Williams, C; Williams, KM; Wilson, JF; Wojciechowski, R; Wang, YX; Yamashiro, K; Yam, JCS; Yap, MKH; Yazar, S; Yip, SP; Young, TL; Zhou, X 2019-02-01 IMI - Myopia Genetics Report The knowledge on the genetic background of refractive error and myopia has expanded dramatically in the past few years. This white paper aims to provide a concise summary of current genetic findings and defines the direction where development is needed. We performed an extensive literature search and conducted informal discussions with key stakeholders. Specific topics reviewed included common refractive error, any and high myopia, and myopia related to syndromes. To date, almost 200 genetic loci have been identified for refractive error and myopia, and risk variants mostly carry low risk but are highly prevalent in the general population. Several genes for secondary syndromic myopia overlap with those for common myopia. Polygenic risk scores show overrepresentation of high myopia in the higher deciles of risk. Annotated genes have a wide variety of functions, and all retinal layers appear to be sites of expression. The current genetic findings offer a world of new molecules involved in myopiagenesis. As the missing heritability is still large, further genetic advances are needed. This Committee recommends expanding large-scale, in-depth genetic studies using complementary big data analytics, consideration of gene-environment effects by thorough measurement of environmental exposures, and focus on subgroups with extreme phenotypes and high familial occurrence. Functional characterization of associated variants is simultaneously needed to bridge the knowledge gap between sequence variance and consequence for eye growth. Journal Article

Nonsense-Mediated Decay Enables Intron Gain Drosophila

2020-11-28T12:39:52Z

Farlow, A; Meduri, E; Dolezal, M; Hua, L; Schloetterer, C 2010-01-01 Nonsense-Mediated Decay Enables Intron Gain Drosophila Intron number varies considerably among genomes, but despite their fundamental importance, the mutational mechanisms and evolutionary processes underlying the expansion of intron number remain unknown. Here we show that Drosophila, in contrast to most eukaryotic lineages, is still undergoing a dramatic rate of intron gain. These novel introns carry significantly weaker splice sites that may impede their identification by the spliceosome. Novel introns are more likely to encode a premature termination codon (PTC), indicating that nonsense-mediated decay (NMD) functions as a backup for weak splicing of new introns. Our data suggest that new introns originate when genomic insertions with weak splice sites are hidden from selection by NMD. This mechanism reduces the sequence requirement imposed on novel introns and implies that the capacity of the spliceosome to recognize weak splice sites was a prerequisite for intron gain during eukaryotic evolution. Journal Article

The advantages and limitations of trait analysis with GWAS: a review

2020-11-28T12:39:52Z

Korte, A; Farlow, A 2013-07-22 The advantages and limitations of trait analysis with GWAS: a review Over the last 10 years, high-density SNP arrays and DNA re-sequencing have illuminated the majority of the genotypic space for a number of organisms, including humans, maize, rice and Arabidopsis. For any researcher willing to define and score a phenotype across many individuals, Genome Wide Association Studies (GWAS) present a powerful tool to reconnect this trait back to its underlying genetics. In this review we discuss the biological and statistical considerations that underpin a successful analysis or otherwise. The relevance of biological factors including effect size, sample size, genetic heterogeneity, genomic confounding, linkage disequilibrium and spurious association, and statistical tools to account for these are presented. GWAS can offer a valuable first insight into trait architecture or candidate loci for subsequent validation. Journal Article

Alignment-free inference of hierarchical and reticulate phylogenomic relationships.

2020-11-28T12:39:52Z

Bernard, G; Chan, CX; Chan, Y-B; Chua, X-Y; Cong, Y; Hogan, JM; Maetschke, SR; Ragan, MA 2019-03-22 Alignment-free inference of hierarchical and reticulate phylogenomic relationships. We are amidst an ongoing flood of sequence data arising from the application of high-throughput technologies, and a concomitant fundamental revision in our understanding of how genomes evolve individually and within the biosphere. Workflows for phylogenomic inference must accommodate data that are not only much larger than before, but often more error prone and perhaps misassembled, or not assembled in the first place. Moreover, genomes of microbes, viruses and plasmids evolve not only by tree-like descent with modification but also by incorporating stretches of exogenous DNA. Thus, next-generation phylogenomics must address computational scalability while rethinking the nature of orthogroups, the alignment of multiple sequences and the inference and comparison of trees. New phylogenomic workflows have begun to take shape based on so-called alignment-free (AF) approaches. Here, we review the conceptual foundations of AF phylogenetics for the hierarchical (vertical) and reticulate (lateral) components of genome evolution, focusing on methods based on k-mers. We reflect on what seems to be successful, and on where further development is needed. Journal Article

Strong vibrational coupling in room temperature plasmonic resonators

2020-11-28T12:39:52Z

Wang, J; Yu, K; Yang, Y; Hartland, G; Sader, JE; Wang, GP 2019-04-04 Strong vibrational coupling in room temperature plasmonic resonators Strong vibrational coupling has been realized in a variety of mechanical systems. However, there have been no experimental observations of strong coupling of the acoustic modes of plasmonic nanostructures, due to rapid energy dissipation in these systems. Here we realized strong vibrational coupling in ultra-high frequency plasmonic nanoresonators by increasing the vibrational quality factors by an order of magnitude. We achieved the highest frequency quality factor products of f × Q = 1.0 × 1013 Hz for the fundamental mechanical modes, which exceeds the value of 0.6 × 1013 Hz required for ground state cooling. Avoided crossing was observed between vibrational modes of two plasmonic nanoresonators with a coupling rate of g = 7.5 ± 1.2 GHz, an order of magnitude larger than the dissipation rates. The intermodal strong coupling was consistent with theoretical calculations using a coupled oscillator model. Our results enabled a platform for future observation and control of the quantum behavior of phonon modes in metallic nanoparticles. Journal Article

International consensus on quality standards for brain health-focused care in multiple sclerosis.

2020-11-28T12:39:52Z

Hobart, J; Bowen, A; Pepper, G; Crofts, H; Eberhard, L; Berger, T; Boyko, A; Boz, C; Butzkueven, H; Celius, EG; Drulovic, J; Flores, J; Horáková, D; Lebrun-Frénay, C; Marrie, RA; Overell, J; Piehl, F; Rasmussen, PV; Sá, MJ; Sîrbu, C-A; Skromne, E; Torkildsen, Ø; van Pesch, V; Vollmer, T; Zakaria, M; Ziemssen, T; Giovannoni, G 2019-11 International consensus on quality standards for brain health-focused care in multiple sclerosis. BACKGROUND: Time matters in multiple sclerosis (MS). Irreversible neural damage and cell loss occur from disease onset. The MS community has endorsed a management strategy of prompt diagnosis, timely intervention and regular proactive monitoring of treatment effectiveness and disease activity to improve outcomes in people with MS. OBJECTIVES: We sought to develop internationally applicable quality standards for timely, brain health-focused MS care. METHODS: A panel of MS specialist neurologists participated in an iterative, online, modified Delphi process to define 'core', 'achievable' and 'aspirational' time frames reflecting minimum, good and high care standards, respectively. A multidisciplinary Reviewing Group (MS nurses, people with MS, allied healthcare professionals) provided insights ensuring recommendations reflected perspectives from multiple stakeholders. RESULTS: Twenty-one MS neurologists from 19 countries reached consensus on most core (25/27), achievable (25/27) and aspirational (22/27) time frames at the end of five rounds. Agreed standards cover six aspects of the care pathway: symptom onset, referral and diagnosis, treatment decisions, lifestyle, disease monitoring and managing new symptoms. CONCLUSION: These quality standards for core, achievable and aspirational care provide MS teams with a three-level framework for service evaluation, benchmarking and improvement. They have the potential to produce a profound change in the care of people with MS. Journal Article

De novo and inherited private variants in MAP1B in periventricular nodular heterotopia

2020-11-28T12:39:52Z

Heinzen, EL; O'Neill, AC; Zhu, X; Allen, AS; Bahlo, M; Chelly, J; Chen, MH; Dobyns, WB; Freytag, S; Guerrini, R; Leventer, RJ; Poduri, A; Robertson, SP; Walsh, CA; Zhang, M 2018-05-01 De novo and inherited private variants in MAP1B in periventricular nodular heterotopia Periventricular nodular heterotopia (PVNH) is a malformation of cortical development commonly associated with epilepsy. We exome sequenced 202 individuals with sporadic PVNH to identify novel genetic risk loci. We first performed a trio-based analysis and identified 219 de novo variants. Although no novel genes were implicated in this initial analysis, PVNH cases were found overall to have a significant excess of nonsynonymous de novo variants in intolerant genes (p = 3.27x10-7), suggesting a role for rare new alleles in genes yet to be associated with the condition. Using a gene-level collapsing analysis comparing cases and controls, we identified a genome-wide significant signal driven by four ultra-rare loss-of-function heterozygous variants in MAP1B, including one de novo variant. In at least one instance, the MAP1B variant was inherited from a parent with previously undiagnosed PVNH. The PVNH was frontally predominant and associated with perisylvian polymicrogyria. These results implicate MAP1B in PVNH. More broadly, our findings suggest that detrimental mutations likely arising in immediately preceding generations with incomplete penetrance may also be responsible for some apparently sporadic diseases. Journal Article

Control of Blood Glucose for Type-1 Diabetes by Using Reinforcement Learning with Feedforward Algorithm

2020-11-28T12:39:52Z

Ngo, PD; Wei, S; Holubova, A; Muzik, J; Godtliebsen, F 2018-01-01 Control of Blood Glucose for Type-1 Diabetes by Using Reinforcement Learning with Feedforward Algorithm Background: Type-1 diabetes is a condition caused by the lack of insulin hormone, which leads to an excessive increase in blood glucose level. The glucose kinetics process is difficult to control due to its complex and nonlinear nature and with state variables that are difficult to measure. Methods: This paper proposes a method for automatically calculating the basal and bolus insulin doses for patients with type-1 diabetes using reinforcement learning with feedforward controller. The algorithm is designed to keep the blood glucose stable and directly compensate for the external events such as food intake. Its performance was assessed using simulation on a blood glucose model. The usage of the Kalman filter with the controller was demonstrated to estimate unmeasurable state variables. Results: Comparison simulations between the proposed controller with the optimal reinforcement learning and the proportional-integral-derivative controller show that the proposed methodology has the best performance in regulating the fluctuation of the blood glucose. The proposed controller also improved the blood glucose responses and prevented hypoglycemia condition. Simulation of the control system in different uncertain conditions provided insights on how the inaccuracies of carbohydrate counting and meal-time reporting affect the performance of the control system. Conclusion: The proposed controller is an effective tool for reducing postmeal blood glucose rise and for countering the effects of external known events such as meal intake and maintaining blood glucose at a healthy level under uncertainties. Journal Article

Combined single-cell profiling of expression and DNA methylation reveals splicing regulation and heterogeneity

2020-11-28T12:39:52Z

Linker, SM; Urban, L; Clark, SJ; Chhatriwala, M; Amatya, S; McCarthy, DJ; Ebersberger, I; Vallier, L; Reik, W; Stegle, O; Bonder, MJ 2019-02-11 Combined single-cell profiling of expression and DNA methylation reveals splicing regulation and heterogeneity BACKGROUND: Alternative splicing is a key regulatory mechanism in eukaryotic cells and increases the effective number of functionally distinct gene products. Using bulk RNA sequencing, splicing variation has been studied across human tissues and in genetically diverse populations. This has identified disease-relevant splicing events, as well as associations between splicing and genomic features, including sequence composition and conservation. However, variability in splicing between single cells from the same tissue or cell type and its determinants remains poorly understood. RESULTS: We applied parallel DNA methylation and transcriptome sequencing to differentiating human induced pluripotent stem cells to characterize splicing variation (exon skipping) and its determinants. Our results show that variation in single-cell splicing can be accurately predicted based on local sequence composition and genomic features. We observe moderate but consistent contributions from local DNA methylation profiles to splicing variation across cells. A combined model that is built based on genomic features as well as DNA methylation information accurately predicts different splicing modes of individual cassette exons. These categories include the conventional inclusion and exclusion patterns, but also more subtle modes of cell-to-cell variation in splicing. Finally, we identified and characterized associations between DNA methylation and splicing changes during cell differentiation. CONCLUSIONS: Our study yields new insights into alternative splicing at the single-cell level and reveals a previously underappreciated link between DNA methylation variation and splicing. Journal Article

The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads

2020-11-28T12:39:52Z

Liao, Y; Smyth, GK; Shi, W 2019-05-07 The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads We present Rsubread, a Bioconductor software package that provides high-performance alignment and read counting functions for RNA-seq reads. Rsubread is based on the successful Subread suite with the added ease-of-use of the R programming environment, creating a matrix of read counts directly as an R object ready for downstream analysis. It integrates read mapping and quantification in a single package and has no software dependencies other than R itself. We demonstrate Rsubread's ability to detect exon-exon junctions de novo and to quantify expression at the level of either genes, exons or exon junctions. The resulting read counts can be input directly into a wide range of downstream statistical analyses using other Bioconductor packages. Using SEQC data and simulations, we compare Rsubread to TopHat2, STAR and HTSeq as well as to counting functions in the Bioconductor infrastructure packages. We consider the performance of these tools on the combined quantification task starting from raw sequence reads through to summary counts, and in particular evaluate the performance of different combinations of alignment and counting algorithms. We show that Rsubread is faster and uses less memory than competitor tools and produces read count summaries that more accurately correlate with true values. Journal Article

Using long-read sequencing to detect imprinted DNA methylation

2020-11-28T12:39:52Z

Gigante, S; Gouil, Q; Lucattini, A; Keniry, A; Beck, T; Tinning, M; Gordon, L; Woodruff, C; Speed, TP; Blewitt, ME; Ritchie, ME 2019-05-07 Using long-read sequencing to detect imprinted DNA methylation Systematic variation in the methylation of cytosines at CpG sites plays a critical role in early development of humans and other mammals. Of particular interest are regions of differential methylation between parental alleles, as these often dictate monoallelic gene expression, resulting in parent of origin specific control of the embryonic transcriptome and subsequent development, in a phenomenon known as genomic imprinting. Using long-read nanopore sequencing we show that, with an average genomic coverage of ∼10, it is possible to determine both the level of methylation of CpG sites and the haplotype from which each read arises. The long-read property is exploited to characterize, using novel methods, both methylation and haplotype for reads that have reduced basecalling precision compared to Sanger sequencing. We validate the analysis both through comparison of nanopore-derived methylation patterns with those from Reduced Representation Bisulfite Sequencing data and through comparison with previously reported data. Our analysis successfully identifies known imprinting control regions (ICRs) as well as some novel differentially methylated regions which, due to their proximity to hitherto unknown monoallelically expressed genes, may represent new ICRs. Journal Article

Classification of low quality cells from single-cell RNA-seq data

2020-11-28T12:39:52Z

Ilicic, T; Kim, JK; Kolodziejczyk, AA; Bagger, FO; McCarthy, DJ; Marioni, JC; Teichmann, SA 2016-02-17 Classification of low quality cells from single-cell RNA-seq data Single-cell RNA sequencing (scRNA-seq) has broad applications across biomedical research. One of the key challenges is to ensure that only single, live cells are included in downstream analysis, as the inclusion of compromised cells inevitably affects data interpretation. Here, we present a generic approach for processing scRNA-seq data and detecting low quality cells, using a curated set of over 20 biological and technical features. Our approach improves classification accuracy by over 30 % compared to traditional methods when tested on over 5,000 cells, including CD4+ T cells, bone marrow dendritic cells, and mouse embryonic stem cells. Journal Article

A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor.

2020-11-28T12:39:52Z

Lun, ATL; McCarthy, DJ; Marioni, JC 2016 A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor. Single-cell RNA sequencing (scRNA-seq) is widely used to profile the transcriptome of individual cells. This provides biological resolution that cannot be matched by bulk RNA sequencing, at the cost of increased technical noise and data complexity. The differences between scRNA-seq and bulk RNA-seq data mean that the analysis of the former cannot be performed by recycling bioinformatics pipelines for the latter. Rather, dedicated single-cell methods are required at various steps to exploit the cellular resolution while accounting for technical noise. This article describes a computational workflow for low-level analyses of scRNA-seq data, based primarily on software packages from the open-source Bioconductor project. It covers basic steps including quality control, data exploration and normalization, as well as more complex procedures such as cell cycle phase assignment, identification of highly variable and correlated genes, clustering into subpopulations and marker gene detection. Analyses were demonstrated on gene-level count data from several publicly available datasets involving haematopoietic stem cells, brain-derived cells, T-helper cells and mouse embryonic stem cells. This will provide a range of usage scenarios from which readers can construct their own analysis pipelines. Journal Article

f-scLVM: scalable and versatile factor analysis for single-cell RNA-seq

2020-11-28T12:39:52Z

Buettner, F; Pratanwanich, N; McCarthy, DJ; Marioni, JC; Stegle, O 2017-11-07 f-scLVM: scalable and versatile factor analysis for single-cell RNA-seq Single-cell RNA-sequencing (scRNA-seq) allows studying heterogeneity in gene expression in large cell populations. Such heterogeneity can arise due to technical or biological factors, making decomposing sources of variation difficult. We here describe f-scLVM (factorial single-cell latent variable model), a method based on factor analysis that uses pathway annotations to guide the inference of interpretable factors underpinning the heterogeneity. Our model jointly estimates the relevance of individual factors, refines gene set annotations, and infers factors without annotation. In applications to multiple scRNA-seq datasets, we find that f-scLVM robustly decomposes scRNA-seq datasets into interpretable components, thereby facilitating the identification of novel subpopulations. Journal Article

Dietary intake influences gut microbiota development of healthy Australian children from the age of one to two years

2020-11-28T12:39:52Z

Matsuyama, M; Morrison, M; Le Cao, K-A; Pruilh, S; Davies, PSW; Wall, C; Lovell, A; Hill, RJ 2019-08-28 Dietary intake influences gut microbiota development of healthy Australian children from the age of one to two years Early life nutrition is a vital determinant of an individual's life-long health and also directly influences the ecological and functional development of the gut microbiota. However, there are limited longitudinal studies examining the effect of diet on the gut microbiota development in early childhood. Here, up to seven stool samples were collected from each of 48 healthy children during their second year of life, and microbiota dynamics were assessed using 16S rRNA gene amplicon sequencing. Children's dietary information was also collected during the same period using a validated food frequency questionnaire designed for this age group, over five time points. We observed significant changes in gut microbiota community, concordant with changes in the children's dietary pattern over the 12-month period. In particular, we found differential effects on specific Firmicutes-affiliated lineages in response to frequent intake of either processed or unprocessed foods. Additionally, the consumption of fortified milk supplemented with a Bifidobacterium probiotic and prebiotics (synbiotics) further increased the presence of Bifidobacterium spp., highlighting the potential use of synbiotics to prolong and sustain changes in these lineages and shaping the gut microbiota community in young children. Journal Article

Large-scale parallelization of nanomechanical mass spectrometry with weakly-coupled resonators

2020-11-28T12:39:52Z

Stassi, S; De laurentis, G; Chakraborty, D; Bejtka, K; Chiodoni, A; Sader, JE; Ricciardi, C 2019-09-09 Large-scale parallelization of nanomechanical mass spectrometry with weakly-coupled resonators Nanomechanical mass spectrometry is a recent technological breakthrough that enables the real-time analysis of single molecules. In contraposition to its extreme mass sensitivity is a limited capture cross-section that can hinder measurements in a practical setting. Here we show that weak-coupling between devices in resonator arrays can be used in nanomechanical mass spectrometry to parallelize the measurement. This coupling gives rise to asymmetric amplitude peaks in the vibrational response of a single nanomechanical resonator of the array, which coincide with the natural frequencies of all other resonators in the same array. A rigorous theoretical model is derived that explains the physical mechanisms and describes the practical features of this parallelization. We demonstrate the significance of this parallelization through inertial imaging of analytes adsorbed to all resonators of an array, with the possibility of simultaneously detecting resonators placed at distances a hundred times larger than their own physical size. Journal Article

Application of whole genome and RNA sequencing to investigate the genomic landscape of common variable immunodeficiency disorders

2020-11-28T12:39:52Z

van Schouwenburg, PA; Davenport, EE; Kienzler, A-K; Marwah, I; Wright, B; Lucas, M; Malinauskas, T; Martin, HC; Lockstone, HE; Cazier, J-B; Chapel, HM; Knight, JC; Patel, SY 2015-10-01 Application of whole genome and RNA sequencing to investigate the genomic landscape of common variable immunodeficiency disorders Common Variable Immunodeficiency Disorders (CVIDs) are the most prevalent cause of primary antibody failure. CVIDs are highly variable and a genetic causes have been identified in <5% of patients. Here, we performed whole genome sequencing (WGS) of 34 CVID patients (94% sporadic) and combined them with transcriptomic profiling (RNA-sequencing of B cells) from three patients and three healthy controls. We identified variants in CVID disease genes TNFRSF13B, TNFRSF13C, LRBA and NLRP12 and enrichment of variants in known and novel disease pathways. The pathways identified include B-cell receptor signalling, non-homologous end-joining, regulation of apoptosis, T cell regulation and ICOS signalling. Our data confirm the polygenic nature of CVID and suggest individual-specific aetiologies in many cases. Together our data show that WGS in combination with RNA-sequencing allows for a better understanding of CVIDs and the identification of novel disease associated pathways. Journal Article

A new normalization for Nanostring nCounter gene expression data

2020-11-28T12:39:52Z

Molania, R; Gagnon-Bartsch, JA; Dobrovic, A; Speed, TP 2019-07-09 A new normalization for Nanostring nCounter gene expression data The Nanostring nCounter gene expression assay uses molecular barcodes and single molecule imaging to detect and count hundreds of unique transcripts in a single reaction. These counts need to be normalized to adjust for the amount of sample, variations in assay efficiency and other factors. Most users adopt the normalization approach described in the nSolver analysis software, which involves background correction based on the observed values of negative control probes, a within-sample normalization using the observed values of positive control probes and normalization across samples using reference (housekeeping) genes. Here we present a new normalization method, Removing Unwanted Variation-III (RUV-III), which makes vital use of technical replicates and suitable control genes. We also propose an approach using pseudo-replicates when technical replicates are not available. The effectiveness of RUV-III is illustrated on four different datasets. We also offer suggestions on the design and analysis of studies involving this technology. Journal Article

Decreased maternal serum acetate and impaired fetal thymic and regulatory T cell development in preeclampsia

2020-11-28T12:39:52Z

Hu, M; Eviston, D; Hsu, P; Marino, E; Chidgey, A; Santner-Nanan, B; Wong, K; Richards, JL; Yap, YA; Collier, F; Quinton, A; Joung, S; Peek, M; Benzie, R; Macia, L; Wilson, D; Ponsonby, A-L; Tang, MLK; O'Hely, M; Daly, NL; Mackay, CR; Dahlstrom, JE; Vuillermin, P; Nanan, R; Saffery, R; Allen, KJ; Ranganathan, S; Burgner, D; Harrison, LC; Sly, P; Dwyer, T 2019-07-10 Decreased maternal serum acetate and impaired fetal thymic and regulatory T cell development in preeclampsia Maternal immune dysregulation seems to affect fetal or postnatal immune development. Preeclampsia is a pregnancy-associated disorder with an immune basis and is linked to atopic disorders in offspring. Here we show reduction of fetal thymic size, altered thymic architecture and reduced fetal thymic regulatory T (Treg) cell output in preeclamptic pregnancies, which persists up to 4 years of age in human offspring. In germ-free mice, fetal thymic CD4+ T cell and Treg cell development are compromised, but rescued by maternal supplementation with the intestinal bacterial metabolite short chain fatty acid (SCFA) acetate, which induces upregulation of the autoimmune regulator (AIRE), known to contribute to Treg cell generation. In our human cohorts, low maternal serum acetate is associated with subsequent preeclampsia, and correlates with serum acetate in the fetus. These findings suggest a potential role of acetate in the pathogenesis of preeclampsia and immune development in offspring. Journal Article

Genetic investigation into an increased susceptibility to biliary atresia in an extended New Zealand Maori family

2020-11-28T12:39:52Z

Cameron-Christie, SR; Wilde, J; Gray, A; Tankard, R; Bahlo, M; Markie, D; Evans, HM; Robertson, SP 2018-12-18 Genetic investigation into an increased susceptibility to biliary atresia in an extended New Zealand Maori family BACKGROUND: Biliary atresia (BA), a fibrosing disorder of the developing biliary tract leading to liver failure in infancy, has an elevated incidence in indigenous New Zealand (NZ) Māori. We investigated a high rate of BA in a group of children (n = 12) belonging to a single Māori iwi (or 'tribe', related through a remote ancestor). METHODS: Population and geographical data was used to estimate the rate of BA in Māori sub-groups, and a pedigree linking most of the affected children was constructed from oral and documented history. Array genotyping was used to examine hypotheses about the inheritance of a possible genetic risk factor, and the history of the affected population, and Exome Sequencing to search for candidate genes. RESULTS: Most of these affected children (n = 7) link to a self-reported pedigree and carry a 50-fold increase in BA risk over unrelated Māori (χ2 = 296P < 0.001, 95% CI 23-111). Genetic analysis using FEstim and SNP array genotypes revealed no evidence for elevated consanguinity between parents of affected children (FEstim: F (2,21) = 0.469, P > 0.63). Genome-wide quantitation of intervals of contiguous, homozygous-by-state markers reached a similar conclusion (F (2,399) = 1.99, P = 0.138). Principal component analysis and investigation with STRUCTURE found no evidence of increased allele frequency of either a recessive variant, or additive, low-risk variants due to reproductive isolation. To identify candidate causal factors, Exome Sequencing datasets were scrutinised for shared rare coding variants across 8 affected individuals. No rare, non-synonymous, phylogenetically conserved variants were common to 6 or more affected children. CONCLUSION: The substantially elevated risk for development of BA in this subgroup could be mediated by genetic factors, but the iwi exhibits no properties indicative of recent or remote reproductive isolation. Resolution of any risk loci may rely on extensive genomic sequencing studies in this iwi or investigation of other mechnaisms such as copy number variation. Journal Article

Epidemiology and etiology of infantile developmental and epileptic encephalopathies in Tasmania.

2020-11-28T12:39:52Z

Ware, TL; Huskins, SR; Grinton, BE; Liu, Y-C; Bennett, MF; Harvey, M; McMahon, J; Andreopoulos-Malikotsinas, D; Bahlo, M; Howell, KB; Hildebrand, MS; Damiano, JA; Rosenfeld, A; Mackay, MT; Mandelstam, S; Leventer, RJ; Harvey, AS; Freeman, JL; Scheffer, IE; Jones, DL; Berkovic, SF 2019-09 Epidemiology and etiology of infantile developmental and epileptic encephalopathies in Tasmania. We sought to determine incidence, etiologies, and yield of genetic testing in infantile onset developmental and epileptic encephalopathies (DEEs) in a population isolate, with an intensive multistage approach. Infants born in Tasmania between 2011 and 2016, with seizure onset <2 years of age, epileptiform EEG, frequent seizures, and developmental impairment, were included. Following review of EEG databases, medical records, brain MRIs, and other investigations, clinical genetic testing was undertaken with subsequent research interrogation of whole exome sequencing (WES) in unsolved cases. The incidence of infantile DEEs was 0.44/1000 per year (95% confidence interval 0.25 to 0.71), with 16 cases ascertained. The etiology was structural in 5/16 cases. A genetic basis was identified in 6 of the remaining 11 cases (3 gene panel, 3 WES). In two further cases, WES identified novel variants with strong in silico data; however, paternal DNA was not available to support pathogenicity. The etiology was not determined in 3/16 (19%) cases, with a candidate gene identified in one of these. Pursuing clinical imaging and genetic testing followed by WES at an intensive research level can give a high diagnostic yield in the infantile DEEs, providing a solid base for prognostic and genetic counseling. Journal Article

Solutions of a non-local aggregation equation: Universal bounds, concavity changes, and efficient numerical solutions

2020-11-28T12:39:52Z

Fellner, K; Hughes, BD 2020-05-30 Solutions of a non-local aggregation equation: Universal bounds, concavity changes, and efficient numerical solutions Mathematical Methods in the Applied Sciences published by John Wiley & Sons, Ltd. We consider a one-dimensional aggregation equation for a non-negative density (Formula presented.) associated with a quartic potential (Formula presented.) ((Formula presented.), (Formula presented.)). We show that for the case of symmetric initial data [(Formula presented.)], the solution of the aggregation equation can be expressed in terms of an explicit function of (Formula presented.), (Formula presented.), and (Formula presented.), where the functions (Formula presented.) and (Formula presented.) are determined by an ordinary differential equation initial value problem, the numerical solution of which is relatively straightforward. The function (Formula presented.), which can be interpreted as an upper bound for the radius of the support of (Formula presented.), is finite for all (Formula presented.), even if the support of (Formula presented.) is unbounded, while (Formula presented.) is a potential related to the time integral of the second spatial moment (Formula presented.) of (Formula presented.). We develop various bounds on (Formula presented.) and (Formula presented.) and a number of results concerning convexity and monotonicity that require no knowledge of (Formula presented.) other than its symmetry. We show that many, but not all, of these results persist if the assumption of symmetry is relaxed. Our general results are tested against numerical solutions for two examples of symmetric (Formula presented.). We also exhibit some counterintuitive behaviour of the model, by finding conditions under which (Formula presented.) as (Formula presented.), even if we start with (Formula presented.) and take (Formula presented.), which ensures ultimate collapse to a single Dirac component at the origin. Journal Article