Biology subjects

Melissa Kramer

Publications and source records attributed to Melissa Kramer.

3 recordsLinked to original sources

bioRxiv2016

The Real-time fMRI Neurofeedback Based Stratification of Default Network Regulation Neuroimaging Data Repository.

This data descriptor describes a repository of openly shared data from an experiment to assess inter-individual differences in default mode network (DMN) activity. This repository includes cross-sectional functional magnetic resonance imaging (fMRI) data from the Multi Source Interference Task, to assess DMN deactivation, the Moral Dilemma Task, to assess DMN activation, a resting state fMRI scan, and a DMN neurofeedback paradigm, to assess DMN modulation, along with accompanying behavioral and cognitive measures. We report technical validation from n=125 participants of the final targeted sample of 180 participants. Each session includes acquisition of one whole-brain anatomical scan and whole-brain echo-planar imaging (EPI) scans, acquired during the aforementioned tasks and resting state. The data includes several self-report measures related to perseverative thinking, emotion regulation, and imaginative processes, along with a behavioral measure of rapid visual information processing.\n\nTechnical validation of the data confirms that the tasks deactivate and activate the DMN as expected. Group level analysis of the neurofeedback data indicates that the participants are able to modulate their DMN with considerable inter-subject variability. Preliminary analysis of behavioral responses and specifically self-reported sleep indicate that as many as 73 participants may need to be excluded from an analysis depending on the hypothesis being tested.

Neuroscience↗

bioRxiv2016

C. elegans PVD Neurons: A Platform for Functionally Validating and Characterizing Neuropsychiatric Risk Genes

One of the primary challenges in the field of psychiatric genetics is the lack of an in vivo model system in which to functionally validate candidate neuropsychiatric risk genes (NRGs) in a rapid and cost-effective manner1-3. To overcome this obstacle, we performed a candidate-based RNAi screen in which C. elegans orthologs of human NRGs were assayed for dendritic arborization and cell specification defects using C. elegans PVD neurons. Of 66 NRGs, identified via exome sequencing of autism (ASD)4 or schizophrenia (SCZ)5-9 probands and whose mutations are de novo and predicted to result in a complete or partial loss of protein function, the C. elegans orthologs of 7 NRGs were found to be required for proper neuronal development and represent a variety of functional classes, including transcriptional regulators and chromatin remodelers, molecular chaperones, and cytoskeleton-related proteins. Notably, the positive hit rate, when selectively assaying C. elegans orthologs of ASD and SCZ NRGs, is enriched >14-fold as compared to unbiased RNAi screening10. Furthermore, we find that RNAi phenotypes associated with the depletion of NRG orthologs is recapitulated in genetic mutant animals, and, via genetic interaction studies, we show that the NRG ortholog of ANK2, unc-44, is required for SAX-7/MNR-1/DMA-1 signaling. Collectively, our studies demonstrate that C. elegans PVD neurons are a tractable model in which to discover and dissect the fundamental molecular mechanisms underlying neuropsychiatric disease pathogenesis.

Neuroscience↗

bioRxiv2014

New whole genome de novo assemblies of three divergent strains of rice (O. sativa) documents novel gene space of aus and indica

The use of high throughput genome-sequencing technologies has uncovered a large extent of structural variation in eukaryotic genomes that makes important contributions to genomic diversity and phenotypic variation. Currently, when the genomes of different strains of a given organism are compared, whole genome resequencing data are aligned to an established reference sequence. However when the reference differs in significant structural ways from the individuals under study, the analysis is often incomplete or inaccurate. Here, we use rice as a model to explore the extent of structural variation among strains adapted to different ecologies and geographies, and show that this variation can be significant, often matching or exceeding the variation present in closely related human populations or other mammals. We demonstrate how improvements in sequencing and assembly technology allow rapid and inexpensive de novo assembly of next generation sequence data into high-quality assemblies that can be directly compared to provide an unbiased assessment. Using this approach, we are able to accurately assess the \"pan-genome\" of three divergent rice varieties and document several megabases of each genome absent in the other two. Many of the genome-specific loci are annotated to contain genes, reflecting the potential for new biological properties that would be missed by standard resequencing approaches. We further provide a detailed analysis of several loci associated with agriculturally important traits, illustrating the utility of our approach for biological discovery. All of the data and software are openly available to support further breeding and functional studies of rice and other species.

Genomics↗