Biology subjects

Zimmer, A.

Publications and source records attributed to Zimmer, A..

4 recordsLinked to original sources

bioRxiv2018

Scale-invariant geometric data analysis (SIGDA) provides robust, detailed visualizations of human ancestry specific to individuals and populations

Scale invariance is a common property of physical laws and a key concept in perspective drawing, which aims to provide a meaningful two-dimensional representation of a more complex, three-dimensional scene. Here we describe Scale Invariant Geometric Data Analysis (SIGDA), a new, general exploratory data analysis (EDA) method based on normalization of data to scale invariance. We discuss similarities and differences between SIGDA and two widely-used EDA methods, Correspondence Analysis (CA) and Principal Components Analysis (PCA). We then illustrate SIGDAs ability to analyze and visualize population structure relationships within the data that inspired its development: genetic marker data, in which context PCA is considered a standard method. We show that SIGDA provides significant advantages over PCA of the same data, including: (a) robust detection and separation of a larger number of population axes, leading to (b) better separation of annotated populations; (c) separation of an independent allele frequency axis interpretable as a proxy for allele age, (d) visualization of marker flow between populations (population history), and (d) robust detection and visualization of relationships between closely-related individuals and among family groups. Although this illustration focuses on a specific task, SIGDA is a general-purpose EDA method and derives its advantages from its novel approach to fundamental issues in data analysis, rather than clever sampling or other task-specific methodology.\n\nOne Sentence SummaryWe illustrate the advantages of Scale Invariant Geometric Data Analysis (SIGDA), a new exploratory data analysis method similar to PCA, by applying SIGDA to derive detailed, robust visualizations of the complex history of human population structure from a large sample of single nucleotide variants.

bioinformatics↗

bioRxiv2018

Universal cancer tasks, evolutionary tradeoffs, and the functions of driver mutations

Recent advances have led to an appreciation of the vast molecular diversity of cancer. Detailed data has enabled powerful methods to sort tumors into groups with benefits for prognosis and treatment. We are still missing, however, a general theoretical framework to understand the diversity of tumor gene-expression and mutations. To address this, we present a framework based on multi-task evolution theory, using the fact that tumors evolve in the body, and that tumors are faced with multiple tasks that contribute to their fitness. In accordance with the theory, we find that tradeoff between tasks constrains tumor gene-expression to a continuum bounded by a polyhedron. The vertices of the polyhedron are gene-expression profiles each specializing in one task, allowing the tasks to be identified. We find five universal cancer tasks across tissue-types: cell-division, biomass & energy, lipogenesis, immune-interaction and invasion & tissue remodeling. Tumors whose gene-expression lies close to a vertex are task specialists. We find evidence that such specialists are more sensitive to drugs that interfere with this task. We find that driver mutations, but not passenger mutations, tune gene-expression towards specialization in specific tasks. This approach can integrate additional types of molecular data into a theoretically-based framework for understanding tumor diversity.

cancer biology↗

bioRxiv2017

A unified web platform for network-based analyses of genomic data

Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to quantitatively compare the signal-to-noise ratio of different networks, the biology they describe, and to identify the optimal network to interpret a particular genetic dataset. Via GeNets users can train a machine-learning model (Quack) to make such comparisons; and they can execute, store, and share analyses of genetic and RNA sequencing datasets.

genomics↗

bioRxiv2017

Activation of Somatostatin Inhibitory Neurons by Lypd6-nAChRα2 System Restores Juvenile-like Plasticity in Adult Visual Cortex

The limitation of plasticity in the adult brain impedes functional recovery later in life from brain injury or disease. This pressing clinical issue may be resolved by enhancing plasticity in the adult brain. One strategy for triggering robust plasticity in adulthood is to reproduce one of the hallmark physiological events of experience-dependent plasticity observed during the juvenile critical period - rapidly reduce the activity of parvalbumin (PV)-expressing interneurons and disinhibit local excitatory neurons. This may be achieved through enhancement of local inhibitory inputs, particularly those of somatostatin (SST)-expressing interneurons. However, to date the means for manipulating SST interneurons for enhancing cortical plasticity in the adult brain are not known. We show that SST interneuron-selective overexpression of Lypd6, an endogenous nicotinic signaling modulator, enhances ocular dominance plasticity in the adult primary visual cortex (V1). Lypd6 overexpression mediates a rapid experience-dependent increase in the visually evoked activity of SST interneurons as well as a simultaneous reduction in PV interneuron activity and disinhibition of excitatory neurons. Recapitulating this transient activation of SST interneurons using chemogenetics similarly enhanced V1 plasticity. Notably, we show that SST-selective Lypd6 overexpression restores visual acuity in amblyopic mice that underwent early long-term monocular deprivation. Our data in both male and female mice reveal selective modulation of SST interneurons and a putative downstream circuit mechanism as an effective method for enhancing experience-dependent cortical plasticity as well as functional recovery in adulthood. Significance StatementThe decline of cortical plasticity after closure of juvenile critical period consolidates neural circuits and behavior, but this limits functional recovery from brain diseases and dysfunctions in later life. Here we show that activation of cortical SST interneurons by Lypd6, an endogenous modulator of nicotinic acetylcholine receptors (nAChRs), enhances experience-dependent plasticity and recovery from amblyopia in adulthood. This manipulation triggers rapid reduction of PV interneuron activity and disinhibition of excitatory neurons, which are known hallmarks of cortical plasticity during juvenile critical periods. Our study demonstrates modulation of SST interneurons by Lypd6 to achieve robust levels of cortical plasticity in the adult brain and may provide promising targets for restoring brain function in the event of brain trauma or disease.

neuroscience↗