Biology subjects

Kennedy, P. J.

Publications and source records attributed to Kennedy, P. J..

6 recordsLinked to original sources

bioRxiv2023

Variation in female-biased sexual size dimorphism of Northern Pike (Esox lucius) associated with environment and life history

BackgroundSexual size dimorphism (SSD) is a widespread phenomenon in the animal world resulting from differential selection on the sexes. The Northern Pike (Esox lucius) is a freshwater apex predatory fish species that exhibits female-biased SSD, but the degree to which SSD varies among populations and what variables might dictate variation in SSD in this species remain poorly understood. AimWe sought to quantify the degree of variation in SSD among Northern Pike populations across a large portion of their North American range, as well as evaluate associations between the magnitude of SSD in Northern Pike populations with environmental variables and life history traits of populations. MethodsWe quantified SSD in 102 populations of Northern Pike across the province of Ontario, Canada, using a standardized gillnetting database. We further investigated the degree to which both environmental variables (Cisco abundance as catch-per-unit-effort, lake surface area, and latitude) and Northern Pike life-history traits (early growth and mortality rates) explained variation in female-biased SSD using linear models. ResultsFemale-biased SSD in mean weight of Northern Pike increased with increasing Cisco (Coregonus artedi) abundance, and the difference in female and male mean age increased with increasing latitude. Furthermore, SSD was greater in populations with lower female mortality and early growth rates. ConclusionThis study indicates that slow-growing, long-lived populations of Northern Pike should exhibit greater female-biased SSD, and that these conditions may be facilitated by the availability of large, energy-dense prey and cooler temperatures at northern latitudes.

ecology↗

bioRxiv2021

MCKAT, a multi-dimensional copy numbervariant kernel association test

BackgroundCopy number variants (CNVs) are the gain or loss of DNA segments in the genome. Studies have shown that CNVs are linked to various disorders, including autism, intellectual disability, and schizophrenia. Consequently, the interest in studying a possible association of CNVs to specific disease traits is growing. However, due to the specific multi-dimensional characteristics of the CNVs, methods for testing the association between CNVs and the disease-related traits are still underdeveloped. We propose a novel multi-dimensional CNV kernel association test (MCKAT) in this paper. We aim to find significant associations between CNVs and disease-related traits using kernel-based methods. ResultsWe address the multi-dimensionality in CNV characteristics. We first design a single pair CNV kernel, which contains three sub-kernels to summarize the similarity between two CNVs considering all CNV characteristics. Then, aggregate single pair CNV kernel to the whole chromosome CNV kernel, which summarizes the similarity between CNVs in two or more chromosomes. Finally, the association between the CNVs and disease-related traits is evaluated by comparing the similarity in the trait with kernel-based similarity using a score test in a random effect model. We apply MCKAT on genome-wide CNV datasets to examine the association between CNVs and disease-related traits, which demonstrates the potential usefulness the proposed method has for the CNV association tests. We compare the performance of MCKAT with CKAT, a uni-dimensional kernel method. Based on the results, MCKAT indicates stronger evidence, smaller p-value, in detecting significant associations between CNVs and disease-related traits in both rare and common CNV datasets. ConclusionA multi-dimensional copy number variant kernel association test can detect significantly associated CNVs with any disease-related trait. MCKAT can help biologists detect significantly associated CNVs with any disease-related trait across a patient group instead of examining the CNVs case by case in each subject.

bioinformatics↗

bioRxiv2021

Identification of differentially distributed gene expression and distinct sets of cancer-related genes identified by changes in expression mean and variability

There is increasing evidence that changes in the variability or overall distribution of gene expression are important both in normal biology and in diseases, particularly cancer. Genes whose expression differs in variability or distribution without a difference in mean are ignored by traditional differential expression-based analyses. Using a Bayesian hierarchical model that provides tests for both differential variability and differential distribution for bulk RNA-seq data, we report here an investigation into differential variability and distribution in cancer. Analysis of eight paired tumour-normal datasets from The Cancer Genome Atlas confirms that differential variability and distribution are able to identify cancer-related genes. We further demonstrate that differential variability identifies cancer-related genes that are missed by differential expression analysis, and that differential expression and differential variability identify functionally distinct sets of genes. These results suggest that differential variability analysis may provide insights into genetic aspects of cancer that would not be revealed by differential expression, and that differential distribution analysis may allow for more comprehensive identification of cancer-related genes than analyses based on changes in mean or variability alone.

genomics↗

bioRxiv2020

Adolescent Social Isolation Reprograms the Medial Amygdala: Transcriptome and Sex Differences in Reward

Adolescence is a sensitive window for reward- and stress-associated behavior. Although stress during this period causes long-term changes in behavior in males, how females respond is relatively unknown. Here we show that social isolation stress in adolescence, but not adulthood, induces persistent but opposite effects on anxiety- and cocaine-related behaviors in male vs. female mice, and that these effects are reflected in transcriptional profiles within the adult medial amygdala (meA). By integrating differential gene expression with co-expression network analyses, we identified crystallin mu (Crym), a thyroid-binding protein, as a key driver of these transcriptional profiles. Manipulation of Crym specifically within adult meA neurons recapitulates the behavioral and transcriptional effects of social isolation and re-opens a window of plasticity that is otherwise closed. Our results establish that meA is essential for sex-specific responses to stressful and rewarding stimuli through transcriptional programming that occurs during adolescence.

neuroscience↗

bioRxiv2019

Honeybee colony performance affected by crop diversity and farmland structure: a modelling framework

Forage availability has been suggested as one driver of the observed decline in honeybees. However, little is known about the effects of its spatiotemporal variation on colony success. We present a modelling framework for assessing honeybee colony viability in cropping systems. Based on two real farmland structures, we developed a landscape generator to design cropping systems varying in crop species identity, diversity, and relative abundance. The landscape scenarios generated were evaluated using the existing honeybee colony model BEEHAVE, which links foraging to in-hive dynamics. We thereby explored how different cropping systems determine spatiotemporal forage availability and, in turn, honeybee colony viability (e.g., time to extinction, TTE) and resilience (indicated by, e.g. brood mortality). To assess overall colony viability, we developed metrics, PH and PP, which quantified how much nectar and pollen provided by a cropping system per year was converted into a colonys adult worker population. Both crop species identity and diversity determined the temporal continuity in nectar and pollen supply and thus colony viability. Overall farmland structure and relative crop abundance were less important, but details mattered. For monocultures and for four-crop species systems composed of cereals, oilseed rape, maize and sunflower, PH and PP were below the viability threshold. Such cropping systems showed frequent, badly timed, and prolonged forage gaps leading to detrimental cascading effects on life stages and in-hive work force, which critically reduced colony resilience. Four-crop systems composed of rye-grass-dandelion pasture, trefoil-grass pasture, sunflower and phacelia ensured continuous nectar and pollen supply resulting in TTE > 5 years, and PH (269.5 kg) and PP (108 kg) being above viability thresholds for five years. Overall, trefoil-grass pasture, oilseed rape, buckwheat and phacelia improved the temporal continuity in forage supply and colonys viability. Our results are hypothetical as they are obtained from simplified landscape settings, but they nevertheless match empirical observations, in particular the viability threshold. Our framework can be used to assess the effects of cropping systems on honeybee viability and to develop land-use strategies that help maintain pollination services by avoiding prolonged and badly timed forage gaps.

ecology↗

bioRxiv2017

Habits are negatively regulated by HDAC3 in the dorsal striatum

Optimal behavior results from a balance of control between two strategies, one cognitive/goal-directed and one habitual, which rely on the anatomically distinct dorsomedial (DMS) and dorsolateral (DLS) striatum, respectively. The transcriptional regulatory mechanisms required to learn and transition between these strategies are unknown. Here we identified a critical negative regulator of habit learning. Histone deacetylase (HDAC) inhibition following instrumental conditioning accelerated habitual control of behavior. HDAC3, a transcriptional repressor, was removed from the promoters of learning-related genes in the dorsal striatum as habits formed with overtraining and with post-training HDAC inhibition. Decreasing HDAC3 function in the DLS accelerated habit formation, while DLS HDAC3 overexpression prevented habit. HDAC3 activity in the DMS was also found to constrain habit formation. These results challenge the strict dissociation between DMS and DLS function in goal-directed v. habitual behavioral control and identify dorsal striatal HDAC3 as a critical molecular substrate of the transition to habit.

neuroscience↗