Biology subjects

Case, L.

Publications and source records attributed to Case, L..

3 recordsLinked to original sources

bioRxiv2023

Multiple Pleistocene refugia for Arctic White Heather (Cassiope tetragona) supported by population genomics analyses of contemporary and Little-Ice-Age samples

AimArctic plants survived the Pleistocene glaciations in unglaciated refugia, but the number of these refugia is often unclear. We use high-resolution genomic data from present-day and Little-Ice-Age populations of Arctic White Heather (Cassiope tetragona) to re-evaluate the biogeography of this species and determine whether it had multiple independent refugia or a single refugium in Beringia. LocationCircumpolar Arctic and Coastal British Columbia (BC) alpine TaxonCassiope tetragona L., subspecies saximontana and tetragona, outgroup C. mertensiana (Ericaceae) MethodsWe built genotyping-by-sequencing (GBS) libraries using Cassiope tetragona tissue from 36 Arctic locations, including two [~]250-500-year-old populations collected under glacial ice on Ellesmere Island, Canada. We assembled a de novo GBS reference and called variants in dDocent. Population structure, genetic diversity, and demography were inferred from PCA, ADMIXTURE, fastsimcoal2, SplitsTree, and several population genomics statistics. ResultsPopulation structure analyses identified 4-5 clusters that align with geographic locations. Nucleotide diversity was highest in Beringia and decreased eastwards across Canada. Demographic coalescent analysis of the site-frequency-spectrum dated the following splits from Alaska: BC subspecies saximontana (6 mya), Russia (1.5 mya), Europe (>300-600 kya), Greenland (100 kya). Northern Canada populations appear to be from the current interglacial (7-9 kya). Genetic variants from Alaska appeared more frequently in present-day than historic plants on Ellesmere Island. ConclusionsDemographic analyses show BC, Alaska, Russia, Europe, and Greenland all had separate refugia during the last major glaciations. Northern Canadian populations appear to be founded during the current interglacial with genetic contributions from Alaska, Europe, and Greenland. On Ellesmere Island, there is evidence for continued, recent gene flow with foreign variants introduced in the last 250-500 years. These results suggest that a re-analysis of other Arctic species with shallow population structure using higher resolution genomic markers and demographic analyses may help reveal deeper structure and other circumpolar glacial refugia.

genomics↗

bioRxiv2022

Aβ-CT affective touch: Touch pleasantness ratings for gentle stroking and deep pressure exhibit dependence on A-fibers

Gentle stroking of the skin is a common social touch behavior with positive affective consequences. A preference for slow versus fast stroking of hairy skin has been closely linked to the firing of unmyelinated C-tactile (CT) somatosensory afferents. Because the firing of CT afferents strongly correlates with touch pleasantness, the CT pathway has been considered a social-affective sensory pathway. Recently, ablation of the spinothalamic pathway-thought to convey all C-fiber sensations-in patients with cancer pain impaired pain, temperature, and itch, but not ratings of pleasant touch. This suggested integration of A and CT fiber input in the spinal cord, or A-fiber contributions to computations of touch pleasantness in the brain. However, the causal contribution of A-fibers to touch pleasantness- in humans without pain-remains unknown. In the current, single-blinded study we performed two types of peripheral nerve blocks in healthy adults to temporarily eliminate the contribution of A-fibers to touch perception. Our findings show that when A-fiber function is greatly diminished, the perceived intensity and pleasantness of both gentle stroking and deep pressure are nearly abolished. These findings demonstrate that explicit perception of the pleasantness of CT-targeted brushing and pressure both critically depend on A-fibers.

neuroscience↗

bioRxiv2019

Network-based functional prediction augments genetic association to predict candidate genes for histamine hypersensitivity in mice

Genetic mapping is a primary tool of genetics in model organisms; however, many quantitative trait loci (QTL) contain tens or hundreds of positional candidate genes. Prioritizing these genes for validation is often ad hoc and biased by previous findings. Here we present a technique for computationally prioritizing positional candidates based on computationally inferred gene function. Our method uses machine learning with functional genomic networks, whose links encode functional associations among genes, to identify network-based signatures of functional association to a trait of interest. We demonstrate the method by functionally ranking positional candidates in a large locus on mouse Chr 6 (45.9 Mb to 127.8 Mb) associated with histamine hypersensitivity (Hhs). Hhs is characterized by systemic vascular leakage and edema in response to histamine challenge, which can lead to multiple organ failure and death. Although Hhs risk is strongly influenced by genetics, little is known about its underlying molecular or genetic causes, due to genetic and physiological complexity of the trait. To dissect this complexity, we ranked genes in the Hhs locus by predicting functional association with multiple Hhs-related processes. We integrated these predictions with new single nucleotide polymorphism (SNP) association data derived from a survey of 23 inbred mouse strains and congenic mapping data. The top-ranked genes included Cxcl12, Ret, Cacna1c, and Cntn3, all of which had strong functional associations and were proximal to SNPs segregating with Hhs. These results demonstrate the power of network-based computational methods to nominate highly plausible quantitative trait genes even in highly challenging cases involving large QTLs and extreme trait complexity.

genetics↗