Biology subjects

Ambrose, M.

Publications and source records attributed to Ambrose, M..

3 recordsLinked to original sources

bioRxiv2024

Genomic and Genetic Insights into Mendel's Pea Genes

Pea, Pisum sativum, is an excellent model system through which Gregor Mendel established the foundational principles of inheritance. Surprisingly, till today, the molecular nature of the genetic differences underlying the seven pairs of contrasting traits that Mendel studied in detail remains partially understood. Here, we present a genomic and phenotypic variation map, coupled with haplotype-phenotype association analyses across a wide range of traits in a global Pisum diversity panel. We focus on a genomics-enabled genetic dissection of each of the seven traits Mendel studied, revealing many previously undescribed alleles for the four characterized genes, R, Le, I and A, and elucidating the gene identities and mutations for the remaining three uncharacterized traits. Notably, we identify: (1) a ca. 100kb deletion upstream of the Chlorophyll synthase (ChlG) gene, which generates aberrant transcripts and confers the yellow pod phenotype of gp mutants; (2) an in-frame premature stop codon mutation in a Dodeca-CLE41/44 signalling peptide which explains the parchmentless mutant phenotype corresponding to p; and (3) a 5bp in-frame deletion in a CIK-like receptor kinase gene corresponding to the fasciated stem phenotype fa, which Mendel described in terms of flower position, and we postulate the existence of a Modifier of fa (Mfa) locus that masks this meristem defect. Mendel noted the pleiotropy of the a mutation, including inhibition of axil ring anthocyanin pigmentation, a trait we found to be controlled by allelic variants of the gene D within an R2R3-MYB gene cluster. Furthermore, we characterize and validate natural variation of a quantitative genetic locus governing both pod width and seed weight, characters that Mendel deemed were not sufficiently demarcated for his analyses. This study establishes a cornerstone for fundamental research, education in biology and genetics, and pea breeding practices.

genetics↗

bioRxiv2019

Quantifying transmission of emerging zoonoses: Using mathematical models to maximize the value of surveillance data

Understanding and quantifying the transmission of zoonotic pathogens is essential for directing public health responses, especially for pathogens capable of transmission between humans. However, determining a pathogens transmission dynamics is complicated by challenges often encountered in zoonotic disease surveillance, including unobserved sources of transmission (both human and zoonotic), limited spatial information, and unknown scope of surveillance. In this work, we present a model-based inference method that addresses these challenges for subcritical zoonotic pathogens using a spatial model with two levels of mixing. After demonstrating the robustness of the method using simulation studies, we apply the new method to a dataset of human monkeypox cases detected during an active surveillance program from 1982-1986 in the Democratic Republic of the Congo (DRC). Our results provide estimates of the reproductive number and spillover rate of monkeypox during this surveillance period and suggest that most human-to-human transmission events occur over distances of 30km or less. Taking advantage of contact-tracing data available for a subset of monkeypox cases, we find that around 80% of contact-traced links could be correctly recovered from transmission trees inferred using only date and location. Our results highlight the importance of identifying the appropriate spatial scale of transmission, and show how even imperfect spatiotemporal data can be incorporated into models to obtain reliable estimates of human-to-human transmission patterns.\n\nAuthor SummarySurveillance datasets are often the only sources of information about the ecology and epidemiology of zoonotic infectious diseases. Methods that can extract as much information as possible from these datasets therefore provide a key advantage for informing our understanding of the disease dynamics and improving our ability to choose the optimal intervention strategy. We developed and tested a likelihood-based inference method based on a mechanistic model of the spillover and human-to-human transmission processes. We first used simulated datasets to explore which information about the disease dynamics of a subcritical zoonotic pathogen could be successfully extracted from a line-list surveillance dataset with non-localized spatial information and unknown geographic coverage. We then applied the method to a dataset of human monkeypox cases detected during an active surveillance program in the Democratic Republic of the Congo between 1982 and 1986 to obtain estimates of the reproductive number, spillover rate, and spatial dispersal of monkeypox in humans.

epidemiology↗

bioRxiv2017

Do maternal antibodies facilitate hemagglutinin imprinting to influenza A viruses encountered early in childhood?

In a recent study, we showed evidence for childhood HA imprinting, a phenomenon in which children develop preferential, lifelong immune memory against zoonotic influenza viruses with hemagglutinin (HA) antigens in the same phylogenetic group as the first influenza virus encountered in childhood (Gostic et al. 2016). Although our original study showed strong, population-level HA imprinting effects, it did not resolve the underlying immunological mechanisms.\n\nSimilar immune imprinting phenomena, where individuals preferentially recall immune responses primed early in life, also influence seasonal influenza epidemiology via antigenic seniority (Lessler et al. 2012) and original antigenic sin (Francis 1960), yet the mechanisms underlying all these childhood immune imprinting phenomena remain poorly understood (Cobey & Hensley 2017). A recent letter from Dr. H. Lemke (Lemke 2017) suggested that these childhood imprinting effects might be mediated by the combined action of maternal antibodies (mAbs) and influenza antigen. In other words, that imprinting may require that children are exposed to influenza A virus in the first year of life, while maternal antibodies are still present.

immunology↗