Biology subjects

Robbins, K.

Publications and source records attributed to Robbins, K..

14 recordsLinked to original sources

bioRxiv2025

Axo-Axonic Synapses on Descending Neurons in the Drosophila Ventral Nerve Cord

Axo-axonic synapses can veto, amplify, or synchronize spikes, yet their circuit-scale logic is unknown. Using the complete electron-microscopy connectome of the adult male Drosophila, we charted every axo-axonic input onto the 1,314 descending neurons that carry brain commands to the ventral nerve cord. By definition, any synapse connected to a descending neuron within the cord is axo-axonic. Thus, we uncovered the ascending-descending and interneurons-descending axo-axonic relationship. Neurons with many partners (high-degree) integrate into the network without clustering into an interconnected rich-club of hubs. We identified an octet of ascending neurons (AN08B098) whose axo-axonic input to the Giant Fibers (DNp01) predicted modulation of the escape circuit. Immunostaining confirms their cholinergic identity, while optogenetic activation confirmed that this excitatory cohort increases DNp01 excitability, validating connectome-derived rules. Our work delivers a map of axo-axonic wiring in a complete ventral nerve cord connectome and provides constraints for models of fast motor control.

neuroscience↗

bioRxiv2025

The Intergenerational Classroom: A Case Study Integrating Undergraduate and Lifelong Learning Curricula for Biology Education

According to the US Census Bureau (2019) there are approximately 95 million people in the US 55 years of age and older, and that number is expected to increase dramatically in the next decade. This growing population results in an increasing need for STEM learning opportunities for older adults. This need is partially met by lifelong learning communities across the country that offer non-degree programs on a broad range of topics. While many of these programs are located on a college campus, there are few opportunities for interaction between lifelong learners and students in degree-oriented programs. To improve access to STEM education for lifelong learners, we generated an intergenerational classroom composed of lifelong learners and undergraduate students. The semester-long course focused on the biography and medical writings of the late neurologist Oliver Sacks. Our analysis revealed a high level of satisfaction from both undergraduate students and lifelong learners. Both groups overwhelmingly found the intergenerational format beneficial to learning. Furthermore, self-assessments revealed that students felt more positively about intergenerational interactions following completion of the course. Overall, this course provides a framework for increasing access to STEM for the growing older adult population and fostering positive intergenerational interactions. This model could be readily implemented across the country given the abundance of lifelong learning programs currently affiliated with colleges and universities.

scientific communication and education↗

bioRxiv2025

Development of an open-pollinated genetic mapping framework to facilitate the identification of QTL in apples

Genetic mapping of traits in apples (Malus domestica), a temperate woody perennial, is challenging due to high heterozygosity, long juvenility, and extensive spatial maintenance requirements for the populations. These factors limit the effective use of traditional quantitative trait locus (QTL) mapping methods in identifying the genetic basis of traits critical for apple production, marketability and sustainability. We explored the use of open-pollinated (OP) genetic mapping as an alternative to conventional bi-parental QTL mapping and genome wide association studies (GWAS). A QTL was simulated and the performance of a mixed linear model (MLM) and a multi-locus mixed model (MLMM) in QTL mapping accuracy was compared using a genotyping-by-sequencing (GBS) dataset of seven interspecific Royal Gala x M. sieversii bi-parental F1 populations. The simulation results show that the MLMM outperformed the MLM by accurately identifying the simulated QTL. Analysis of power indicated that a population size of 137 individuals is required to reach an = 0.8 for a simulated major effect QTL. Mapping resolution analysis showed that a population size of 470-600 individuals, depending on local recombination rates, is necessary to achieve high resolution within the OP population. Simulations demonstrate the potential of OP-based genetic mapping for identifying QTL in apples, reducing the logistical challenges associated with traditional QTL mapping methods. Our results show that OP-based genetic mapping could be used to speed up the identification of novel alleles directly from diverse germplasm collections in apples. Core IdeasBi-parental QTL mapping in apples is constrained by limited diversity, high costs, and long-term orchard space. OP-based mapping avoids controlled pollination, clonal propagation, and large-scale F1 orchard requirements. OP-based mapping offers an alternative to bi-parental mapping by leveraging existing germplasm and natural crosses. OP-mapping enables QTL discovery absent full pedigree information to strategically capture broad genetic diversity. OP F1 populations support fast QTL detection, aiding rapid breeding against emerging pathogens.

genetics↗

bioRxiv2025

FRAZZLED/DCC REGULATES GAP JUNCTION FORMATION AT A DROSOPHILA GIANT SYNAPSE THROUGH TRANSCRIPTION

Loss of function Frazzled/DCC mutants demonstrate that the gene regulates synaptogenesis in the Giant Fiber System of Drosophila. In frazzled loss of function (LOF) mutants, we observe weaker physiology, characterized by longer latencies and reduced response frequencies between the GFs and the motor neurons. These physiological phenotypes are linked to a loss of gap junctions in the GFs, specifically the loss of the shaking-B(neural+16) isoform of innexin in the presynaptic terminal. A GF biophysical computational model is provided to test the role of gap junctions and the function of the Giant Fiber System. We present evidence of Frazzleds role in gap junction regulation by utilizing the UAS-GAL4 system in Drosophila to rescue mutant phenotypes. Expression of various UAS-Frazzled constructs in a Frazzled LOF background was used to dissect the role of different parts of the Frazzled receptor in the assembly of electrical synapses. Driving Frazzleds intracellular domain in Frazzled LOF mutants rescued axon pathfinding and synaptogenesis. This is supported by the fact that Frazzled fails to rescue the synaptic function when its transcriptional activation domain is disrupted, as shown by the deletion of the highly conserved intracellular P3 domain or by a construct with a point-mutation in the highly conserved P3 domain known to be required for transcriptional activation. The present work is the first to show how a guidance molecule regulates synaptogenesis through transcriptional regulation of synaptic components.

neuroscience↗

bioRxiv2024

Muller's Ratchet in Action: The Erosion of Sexual Reproduction Genes in Domesticated Cassava (Manihot esculenta)

Centuries of clonal propagation in cassava (Manihot esculenta) have engaged Mullers Ratchet, leading to the accumulation of deleterious mutations due to the absence of sexual recombination. This has resulted in both inbreeding depression affecting yield and a significant decrease in reproductive performance, creating hurdles for contemporary breeding programs. Cassava is a member of the Euphorbiaceae family, including notable species such as rubber tree (Hevea brasiliensis) and poinsettia (Euphorbia pulcherrima). Expanding upon preliminary draft genomes, we annotated 7 long-read genome assemblies and aligned a total of 52 genomes, to analyze selection across the genome and the phylogeny. Through this comparative genomic approach, we identified 48 genes under relaxed selection in cassava. Notably, we discovered an overrepresentation of floral expressed genes, especially focused at six pollen-related genes. Our results indicate that domestication and a transition to clonal propagation has reduced selection pressures on sexually reproductive functions in cassava leading to an accumulation of mutations in pollen-related genes. This relaxed selection and the genome-wide deleterious mutations responsible for inbreeding depression are potential targets for improving cassava breeding, where the generation of new varieties relies on recombining favorable alleles through sexual reproduction.

evolutionary biology↗

bioRxiv2022

Utilizing Evolutionary Conservation to Detect Deleterious Mutations and Improve Genomic Prediction in Cassava

Cassava (Manihot esculenta) is an annual root crop which provides the major source of calories for over half a billion people around the world. Since its domestication [~]10,000 years ago, cassava has been largely clonally propagated through stem cuttings. Minimal sexual recombination has led to an accumulation of deleterious mutations made evident by heavy inbreeding depression. To locate and characterize these deleterious mutations, and to measure selection pressure across the cassava genome, we aligned 52 related Euphorbiaceae and other related species representing millions of years of evolution. With single base-pair resolution of genetic conservation, we used protein structure models, amino acid impact, and evolutionary conservation across the Euphorbiaceae to estimate evolutionary constraint. With known deleterious mutations, we aimed to improve genomic evaluations of plant performance through genomic prediction. We first tested this hypothesis through simulation utilizing multi-kernel GBLUP to predict simulated phenotypes across separate populations of cassava. Simulations showed a sizable increase of prediction accuracy when incorporating functional variants in the model when the trait was determined by <100 quantitative trait loci (QTL). Utilizing deleterious mutations and functional weights informed through evolutionary conservation, we saw improvements in genomic prediction accuracy that were dependent on trait and prediction. We showed the potential for using evolutionary information to track functional variation across the genome, in order to improve whole genome trait prediction. We anticipate that continued work to improve genotype accuracy and deleterious mutation assessment will lead to improved genomic assessments of cassava clones.

plant biology↗

bioRxiv2021

Hoplonemertean larvae are planktonic predators that capture and devour active animal prey

The superficially-simple ciliated planktonic larvae of hoplonemerteans have been assumed to be lecithotrophic direct developers, even though many develop from such small eggs that it is hard to imagine how they could give rise to a viable juvenile without some phase of larval feeding. Indeed, attempts to raise such larvae to settlement without food invariably fail. Observations that some hoplonemertean larvae are found in plankton samples at a range of sizes, and much larger than hatchlings, suggests they must indeed feed somehow. Since these "planuliform" larvae lack apparent means to concentrate suspended algae or other unicellular food, one alternative hypothesis is that they are planktonic predators that hunt large prey. Here we provide direct evidence that this is indeed the case for six distinct species of hoplonemerteans. We recorded wild-caught larvae of Paranemertes californica, Paranemertes sp., Gurjanovella littoralis, Emplectonema viride, Carcinonemertes epialti, and Ototyphlonemertes sp. attacking, subduing, and devouring pelagic crustaceans, including barnacle nauplii, cyprids, copepods and their nauplii, and others. While there is no doubt that some hoplonemerteans are genuine lecithotrophs, our evidence suggests that many species in this group both feed and grow during an extended planktonic larval period. This conclusion has important consequences for biogeographic and life-history studies in this group, because it implies enhanced potential for long-distance dispersal. More broadly, the possibility that many animal larvae are actually carnivores invites reconsideration of prevailing stereotypes about metazoan developmental modes and the trade-offs between them.

zoology↗

bioRxiv2021

Simulation of sugar kelp (Saccharina latissima) breeding guided by practices to prioritize accelerated research gains

The domestication process of sugar kelp in the Northeast U.S. was initiated by selective breeding two years ago. In this study, we will demonstrate how obstacles for accelerated genetic gain can be assessed using simulation approaches that inform resource allocation decisions in our research. Thus far, we have used 140 wild sporophytes (SPs) that were sampled from the northern Gulf of Maine (GOM) to southern New England (SNE). From these SPs, we sampled gametophytes (GPs) and made and evaluated over 600 progeny SPs from crosses among the GPs. The biphasic life cycle of kelp gives a great advantage in selective breeding as we can potentially select both on the SPs and GPs. However, several obstacles exist, such as the amount of time it takes to complete a breeding cycle, the number of GPs that can be maintained in the lab, and whether positive selection can be conducted on farm tested SPs. Using the GOM population characteristics for heritability and effective population size, we simulated a founder population of 1000 individuals and evaluated the impact of overcoming these obstacles on genetic gain. Our results showed that key factors to improve current genetic gain rely mainly on our ability to induce reproduction of the best farm-tested SPs, and to accelerate the clonal vegetative growth of released GPs so that enough GP biomass is ready for making crosses by the next growing season. Overcoming these challenges could improve rates of genetic gain more than two-fold. Future research should focus on conditions favorable for inducing spring and early summer reproduction, and increasing the amount of GP tissue available in time to make fall crosses.

genetics↗

bioRxiv2020

EEG-Beats: Automated analysis of heart rate variability (HVR) from EEG-EKG

Heart rate variability (HRV), the variation of the period between consecutive heartbeats, is an established tool for assessing physiological indicators such as stress and fatigue. In non-clinical settings, HRV is often computed from signals acquired using wearable devices that are susceptible to strong artifacts. In EEG (electroencephalography) experiments, these devices must be synchronized with the EEG and typically provide intermittent interbeat interval information based on proprietary artifact-removal algorithms. This paper describes an automated algorithm that uses the output of an EEG sensor mounted on a subjects chest to accurately detect interbeat intervals and to calculate time-varying metrics. The algorithm is designed for raw signals and is robust to artifacts, resulting in fine-grained capture of HRV that is synchronized with the EEG. An open-source MATLAB toolbox (EEG-Beats) is available to calculate interbeat intervals and many standard HRV time and frequency indicators. EEG-Beats is designed to run in a completely automated fashion on an entire study without manual intervention. The paper applies EEG-Beats to EKG signals measured with an EEG sensor in a large longitudinal study (17 subjects, 6 tasks, 854 datasets). The toolbox is available at https://github.com/VisLab/EEG-Beats.

neuroscience↗

bioRxiv2020

Population genetics of sugar kelp in the Northwest Atlantic region using genome-wide markers

An assessment of genetic diversity of marine populations is critical not only for the understanding and preservation of natural biodiversity but also for its economic potential. As commercial demand rises for marine resources, it is critical to generate baseline information for monitoring wild populations. Furthermore, anthropogenic stressors on the coastal environment, such as warming sea surface temperatures and overharvesting of wild populations, are leading to the destruction of keystone marine species such as kelps. In this study, we conducted a fine-scale genetic analysis using genome-wide high-density markers on Northwest Atlantic sugar kelp species, Saccharina latissima and putative species, Saccharina angustissima. The population structure for a total of 149 samples from the Gulf of Maine (GOM) and Southern New England (SNE) was investigated using AMOVA, Fst, admixture, and PCoA. Genome-wide association analyses were conducted for six morphological traits, and the extended Lewontin and Krakauer (FLK) test was used to detect selection signatures. Our results indicate that the GOM region is moderately more heterogeneous than SNE. While admixture was observed between regions, these results confirm that Cape Cod acts as a biogeographic barrier for sugar kelp gene flow. We detected one significant SNP (P-value=2.03x10-7) associated with stipe length, and 243 SNPs with higher-than-neutral differentiation. The findings of this study provide fundamental knowledge on sugar kelp population genetics for future monitoring, managing and potentially restoring wild populations, as well as assisting in selective breeding to improve desirable traits for cultivation and bioenergy production.

genetics↗

bioRxiv2020

How Sensitive are EEG Results to Preprocessing Methods: A Benchmarking Study

Although several guidelines for best practices in EEG preprocessing have been released, even those studies that strictly adhere to those guidelines contain considerable variation in the ways that the recommended methods are applied. An open question for researchers is how sensitive the results of EEG analyses are to variations in preprocessing methods and parameters. To address this issue, we analyze the effect of preprocessing methods on downstream EEG analysis using several simple signal and event-related measures. Signal measures include recording-level channel amplitudes, study-level channel amplitude dispersion, and recording spectral characteristics. Event-related methods include ERPs and ERSPs and their correlations across methods for a diverse set of stimulus events. Our analysis also assesses differences in residual signals both in the time and spectral domains after blink artifacts have been removed. Using fully automated pipelines, we evaluate these measures across 17 EEG studies for two ICA-based preprocessing approaches (LARG, MARA) plus two variations of Artifact Subspace Reconstruction (ASR). Although the general structure of the results is similar across these preprocessing methods, there are significant differences, particularly in the low-frequency spectral features and in the residuals left by blinks. These results argue for detailed reporting of processing details as suggested by most guidelines, but also for using a federation of automated processing pipelines and comparison tools to quantify effects of processing choices as part of the research reporting.

neuroscience↗

bioRxiv2019

Benchmarking Database Systems for Genomic Selection Implementation

MotivationWith high-throughput genotyping systems now available, it has become feasible to fully integration genotyping information into breeding programs [22]. To make use of this information effectively requires DNA extraction facilities and marker production facilities that can efficiently deploy the desired set of markers across samples with a rapid turnaround time that allows for selection before crosses needed to be made. In reality, breeders often have a short window of time to make decisions by the time they are able collect all their phenotyping data and receive corresponding genotyping data. This presents a challenge to organize information and utilize them in downstream analyses to support decisions made by breeders. In order to implement genomic selection routinely as part of breeding programs one would need an efficient genotype data storage system. We selected and benchmarked six popular open-source data storage systems, including relational database management and columnar storage systems.\n\nResultsWe found that data extract times are greatly influenced by the orientation in which genotype data is stored in a system. HDF5 consistently performed best, in part because it can more efficiently work with both orientations of the allele matrix.\n\nAvailabilityhttp://gobiinx1.bti.cornell.edu:6083/projects/GBM/repos/benchmarking/browse\n\nContactyn259@cornell.edu

genomics↗

bioRxiv2018

Automated EEG mega-analysis II: Cognitive aspects of event related features

In this paper, we present the results of a large-scale analysis of event-related responses based on raw EEG data from 17 studies performed at six experimental sites associated with four different institutions. The analysis corpus represents 1,155 recordings containing approximately 7.8 million event instances acquired under several different experimental paradigms. Such large-scale analysis is predicated on consistent data organization and event annotation as well as an effective automated pre-processing pipeline to transform raw EEG into a form suitable for comparative analysis. A key component of this analysis is the annotation of study-specific event codes using a common vocabulary to describe relevant event features. We demonstrate that Hierarchical Event Descriptors (HED tags) capture statistically significant cognitive aspects of EEG events common across multiple recordings, subjects, studies, paradigms, headset configurations, and experimental sites. We use representational similarity analysis (RSA) to show that EEG responses annotated with the same cognitive aspect are significantly more similar than those that do not share that cognitive aspect. These RSA similarity results are supported by visualizations that exploit the non-linear similarities of these associations. We apply temporal overlap regression to reduce confounds caused by adjacent events instances and extract time and time-frequency EEG features (regressed ERPs and ERSPs) that are comparable across studies and replicate findings from prior, individual studies. Likewise, we use second-level linear regression to separate effects of different cognitive aspects on these features, across all studies. This work demonstrates that EEG mega-analysis (pooling of raw data across studies) can enable investigations of brain dynamics in a more generalized fashion than single studies afford. A companion paper complements this event-based analysis by addressing commonality of the time and frequency statistical properties of EEG across studies at the channel and dipole level.

neuroscience↗

bioRxiv2018

Automated EEG mega-analysis I: Spectral and amplitude characteristics across studies

Significant achievements have been made in the fMRI field by pooling statistical results from multiple studies (meta-analysis). More recently, fMRI standardization efforts have focused on enabling the joint analysis of raw fMRI data across studies (mega-analysis), with the hope of achieving more detailed insights. However, it has not been clear if such analyses in the EEG field are possible or equally fruitful. Here we present the results of a large-scale EEG mega-analysis using 18 studies from six sites representing several different experimental paradigms. We demonstrate that when meta-data are consistent across studies, both channel-level and source-level EEG mega-analysis are possible and can provide insights unavailable in single studies. The analysis uses a fully-automated processing pipeline to reduce line noise, interpolate noisy channels, perform robust referencing, remove eye-activity, and further identify outlier signals. We define several robust measures based on channel amplitude and dispersion to assess the comparability of data across studies and observe the effect of various processing steps on these measures. Using ICA-based dipolar sources, we also observe consistent differences in overall frequency baseline amplitudes across brain areas. For example, we observe higher alpha in posterior vs anterior regions and higher beta in temporal regions. We also detect consistent differences in the slope of the aperiodic portion of the EEG spectrum across brain areas. In a companion paper, we apply mega-analysis to assess commonalities in event-related EEG features across studies. The continuous raw and preprocessed data used in this analysis are available through the DataCatalog at https://cancta.net.

neuroscience↗