Biology subjects

Martin, R.

Publications and source records attributed to Martin, R..

3 recordsLinked to original sources

bioRxiv2018

Selection-free, high frequency genome editing by homologous recombination of human pluripotent stem cells using Cas9 RNP and AAV6

Combination of genome editing and human pluripotent stem cells (hPSCs) offers a platform for in vitro disease modeling, drug discovery and personalized stem cell therapeutics. However, incorporation of large modifications using CRISPR/Cas9-based genome editing in hPSCs typically requires the use of selection markers due to low editing efficiencies. Here we report a novel editing technology in hPSCs using Cas9 protein complexed with chemically modified single guide RNA (sgRNA) and recombinant AAV6 (rAAV6) vectors for donor delivery without marker selection. With these components, we demonstrate targeted integration of a 2.2 kb DNA expression cassette in hPSCs at frequencies up to 94% and 67% at the HBB and MYD88 loci, respectively. We used this protocol to correct the homozygous sickle cell disease (SCD) mutation in an iPSC line derived from a SCD patient with a frequency of 63%. This Cas9/AAV6 system allows for both the integration of large gene cassettes and the creation of single nucleotide changes in hPSCs at high frequencies, eliminating the need for multiple editing steps and marker selection, thus increasing the potential of editing human pluripotent cells for both research and translational applications.

bioengineering↗

bioRxiv2017

Brain Modularity Mediates the Relation of Cognitive Performance to Task Complexity

Recent work in cognitive neuroscience has focused on analyzing the brain as a network, rather than as a collection of independent regions. Prior studies taking this approach have found that individual differences in the degree of modularity of the brain network relate to performance on cognitive tasks. However, inconsistent results concerning the direction of this relationship have been obtained, with some tasks showing better performance as modularity increases and other tasks showing worse performance. A recent theoretical model (Chen & Deem, 2015) suggests that these inconsistencies may be explained on the grounds that high-modularity networks favor performance on simple tasks whereas low-modularity networks favor performance on more complex tasks. The current study tests these predictions by relating modularity from resting-state fMRI to performance on a set of simple and complex behavioral tasks. Complex and simple tasks were defined on the basis of whether they did or did not draw on executive attention. Consistent with predictions, we found a negative correlation between individuals modularity and their performance on a composite measure combining scores from the complex tasks but a positive correlation with performance on a composite measure combining scores from the simple tasks. These results and theory presented here provide a framework for linking measures of whole brain organization from network neuroscience to cognitive processing.

neuroscience↗

bioRxiv2017

Static and dynamic measures of human brain connectivity predict complementary aspects of human cognitive performance

In cognitive network neuroscience, the connectivity and community structure of the brain network is related to cognition. Much of this research has focused on two measures of connectivity - modularity and flexibility - which frequently have been examined in isolation. By using resting state fMRI data from 52 young adults, we investigate the relationship between modularity, flexibility and performance on cognitive tasks. We show that flexibility and modularity are highly negatively correlated. However, we also demonstrate that flexibility and modularity make unique contributions to explain task performance, with modularity predicting performance for simple tasks and flexibility predicting performance on complex tasks that require cognitive control and executive functioning. The theory and results presented here allow for stronger links between measures of brain network connectivity and cognitive processes.

neuroscience↗