Clonal evolution and genome stability in a 2,500-year-old fungal individual, bioRxiv, 2018-07-26

AbstractIn the late 1980s, a genetic individual of the fungus Armillaria gallica that extended over at least 37 hectares of forest floor and encompassed hundreds of tree root systems was discovered on the Upper Peninsula of Michigan. Based on observed growth rates, the individual was estimated to be at least 1500 years old with a mass of more than 105 kg. Nearly three decades on, we returned to the site of individual for new sampling. We report here that the same genetic individual of A. gallica is still alive on its original site, but we estimated that it is older and larger than originally estimated, at least 2,500 years and 4 × 105 kg, respectively. We also show that mutation has occurred within the somatic cells of the individual, reflecting its historical pattern of growth from a single point. The overall rate of mutation, however, was extremely low. The large individual of A. gallica has been remarkably resistant to genomic change as it has persisted in place.

biorxiv evolutionary-biology 0-100-users 2018

A Chromosome-Scale Assembly of the En ormous (32 Gb) Axolotl Genome, bioRxiv, 2018-07-20

ABSTRACTThe axolotl (Ambystoma mexicanum) provides critical models for studying regeneration, evolution and development. However, its large genome (~32 gigabases) presents a formidable barrier to genetic analyses. Recent efforts have yielded genome assemblies consisting of thousands of unordered scaffolds that resolve gene structures, but do not yet permit large scale analyses of genome structure and function. We adapted an established mapping approach to leverage dense SNP typing information and for the first time assemble the axolotl genome into 14 chromosomes. Moreover, we used fluorescence in situ hybridization to verify the structure of these 14 scaffolds and assign each to its corresponding physical chromosome. This new assembly covers 27.3 gigabases and encompasses 94% of annotated gene models on chromosomal scaffolds. We show the assembly’s utility by resolving genome-wide orthologies between the axolotl and other vertebrates, identifying the footprints of historical introgression events that occurred during the development of axolotl genetic stocks, and precisely mapping several phenotypes including a large deletion underlying the cardiac mutant. This chromosome-scale assembly will greatly facilitate studies of the axolotl in biological research.

biorxiv genomics 0-100-users 2018

Nested oscillatory dynamics in cortical organoids model early human brain network development, bioRxiv, 2018-06-29

SUMMARYStructural and transcriptional changes during early brain maturation follow fixed developmental programs defined by genetics. However, whether this is true for functional network activity remains unknown, primarily due to experimental inaccessibility of the initial stages of the living human brain. Here, we developed cortical organoids that spontaneously display periodic and regular oscillatory network events that are dependent on glutamatergic and GABAergic signaling. These nested oscillations exhibit cross-frequency coupling, proposed to coordinate neuronal computation and communication. As evidence of potential network maturation, oscillatory activity subsequently transitioned to more spatiotemporally irregular patterns, capturing features observed in preterm human electroencephalography (EEG). These results show that the development of structured network activity in the human neocortex may follow stable genetic programming, even in the absence of external or subcortical inputs. Our approach provides novel opportunities for investigating and manipulating the role of network activity in the developing human cortex.HIGHLIGHTS<jatslist list-type=bullet><jatslist-item>Early development of human functional neural networks and oscillatory activity can be modeled in vitro.<jatslist-item><jatslist-item>Cortical organoids exhibit phase-amplitude coupling between delta oscillation (2 Hz) and high-frequency activity (100-400 Hz) during network-synchronous events.<jatslist-item><jatslist-item>Differential role of glutamate and GABA in initiating and maintaining oscillatory network activity.<jatslist-item><jatslist-item>Developmental impairment of MECP2-KO cortical organoids impacts the emergence of oscillatory activity.<jatslist-item><jatslist-item>Cortical organoid network electrophysiological signatures correlate with human preterm neonatal EEG features.<jatslist-item>eTOCBrain oscillations are a candidate mechanism for how neural populations are temporally organized to instantiate cognition and behavior. Cortical organoids initially exhibit periodic and highly regular nested oscillatory network events that eventually transition to more spatiotemporally complex activity, capturing features of late-stage preterm infant electroencephalography. Functional neural circuitry in cortical organoids exhibits emergence and development of oscillatory network dynamics similar to those found in the developing human brain.

biorxiv neuroscience 0-100-users 2018

Up, down, and out optimized libraries for CRISPRa, CRISPRi, and CRISPR-knockout genetic screens, bioRxiv, 2018-06-27

ABSTRACTAdvances in CRISPR-Cas9 technology have enabled the flexible modulation of gene expression at large scale. In particular, the creation of genome-wide libraries for CRISPR knockout (CRISPRko), CRISPR interference (CRISPRi), and CRISPR activation (CRISPRa) has allowed gene function to be systematically interrogated. Here, we evaluate numerous CRISPRko libraries and show that our recently-described CRISPRko library (Brunello) is more effective than previously published libraries at distinguishing essential and non-essential genes, providing approximately the same perturbation-level performance improvement over GeCKO libraries as GeCKO provided over RNAi. Additionally, we developed genome-wide libraries for CRISPRi (Dolcetto) and CRISPRa (Calabrese). Negative selection screens showed that Dolcetto substantially outperforms existing CRISPRi libraries with fewer sgRNAs per gene and achieves comparable performance to CRISPRko in the detection of gold-standard essential genes. We also conducted positive selection CRISPRa screens and show that Calabrese outperforms the SAM library approach at detecting vemurafenib resistance genes. We further compare CRISPRa to genome-scale libraries of open reading frames (ORFs). Together, these libraries represent a suite of genome-wide tools to efficiently interrogate gene function with multiple modalities.tracr

biorxiv genomics 0-100-users 2018

Measuring narrative engagement The heart tells the story, bioRxiv, 2018-06-20

AbstractStories play a fundamental role in human culture. They provide a mechanism for sharing cultural identity, imparting knowledge, revealing beliefs, reinforcing social bonds and providing entertainment that is central to all human societies. Here we investigated the extent to which the delivery medium of a story (audio or visual) affected conscious and subconscious engagement with the narrative. Although participants self-reported greater involvement for watching video relative to listening to auditory scenes, stronger physiological responses were recorded for auditory stories. Sensors placed at their wrists showed higher and more variable heart rates, greater electrodermal activity, and even higher body temperatures. We interpret these findings as physiological evidence that the stories were more cognitively and emotionally engaging when presented in an auditory format. This may be because listening to a story, rather than watching a video, is a more active process of co-creation, and that this imaginative process in the listener’s mind is detectable on the skin at their wrist.

biorxiv neuroscience 0-100-users 2018

Towards reconstructing intelligible speech from the human auditory cortex, bioRxiv, 2018-06-19

AbstractAuditory stimulus reconstruction is a technique that finds the best approximation of the acoustic stimulus from the population of evoked neural activity. Reconstructing speech from the human auditory cortex creates the possibility of a speech neuroprosthetic to establish a direct communication with the brain and has been shown to be possible in both overt and covert conditions. However, the low quality of the reconstructed speech has severely limited the utility of this method for brain-computer interface (BCI) applications. To advance the state-of-the-art in speech neuroprosthesis, we combined the recent advances in deep learning with the latest innovations in speech synthesis technologies to reconstruct closed-set intelligible speech from the human auditory cortex. We investigated the dependence of reconstruction accuracy on linear and nonlinear (deep neural network) regression methods and the acoustic representation that is used as the target of reconstruction, including auditory spectrogram and speech synthesis parameters. In addition, we compared the reconstruction accuracy from low and high neural frequency ranges. Our results show that a deep neural network model that directly estimates the parameters of a speech synthesizer from all neural frequencies achieves the highest subjective and objective scores on a digit recognition task, improving the intelligibility by 65% over the baseline method which used linear regression to reconstruct the auditory spectrogram. These results demonstrate the efficacy of deep learning and speech synthesis algorithms for designing the next generation of speech BCI systems, which not only can restore communications for paralyzed patients but also have the potential to transform human-computer interaction technologies.

biorxiv neuroscience 0-100-users 2018