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opencc-zeroDec 2011View details →

Data from: A comment on the use of stochastic character maps to estimate evolutionary rate variation in a continuously valued trait

Phylogenetic comparative biology has progressed considerably in recent years. One of the most important developments has been the application of likelihood-based methods to fit alternative models for trait evolution in a phylogenetic tree with branch lengths proportional to time. An important example of this type of method is O'Meara et al.'s (2006) "noncensored" test for variation in the evolutionary rate for a continuously valued character trait through time or across the branches of a phylogenetic tree. According to this method, we first hypothesize evolutionary rate regimes on the tree (called "painting" in Butler and King, 2004); and then we fit an evolutionary model, specifically the popular Brownian model, in which the instantaneous variance of the Brownian random diffusion process has different values in different parts of the phylogeny. The authors suggest that to test a hypothesis that the state of a discrete character influenced the rate of a continuous character, one could use the approach of Neilsen (2002) to first stochastically map the discretely valued trait, and then "test to see whether the portions of the tree with one state for the discrete character have a different rate of evolution for the continuous character than portions of the tree to which the other discrete state has been mapped" (O'Meara et al., 2006, p. 931). Indeed, this has become common practice for this and other closely related methods. Here, I examine this practice. In particular, I show that evolutionary rates estimated this way (i.e., by using maximum likelihood [ML] to fit a multirate model on each stochastically mapped tree; and then averaging across trees) are systematically biased to be more similar to each other than are the underlying generating parameters. My analysis also reveals that this effect is dependent on the rate of evolution for the discrete trait. Specifically, if the rate of evolution for the discrete character is low then the difference between the true history and any stochastically mapped 1 history is generally small. This results in evolutionary rates for the continuous trait that are estimated with little bias. Conversely, if the rate of evolution for the discrete character is very high, then the true and hypothesized character histories are often extremely dissimilar, evolutionary rate estimates are biased to be more similar to each other than their underlying generating values, and we lose power to distinguish evolutionary rates on the tree.

Data from: Adhesion force mapping on wood by atomic force microscopy: influence of surface roughness and tip geometry

This study attempts to address the interpretation of atomic force microscopy (AFM) adhesion force measurements conducted on the heterogeneous rough surface of wood and natural fibre materials. The influences of wood surface roughness, tip geometry and wear on the adhesion force distribution are examined by cyclic measurements conducted on wood surface under dry inert conditions. It was found that both the variation of tip and surface roughness of wood can widen the distribution of adhesion forces, which are essential for data interpretation. When a common Si AFM tip with nanometre size is used, the influence of tip wear can be significant. Therefore, control experiments should take the sequence of measurements into consideration, e.g. repeated experiments with used tip. In comparison, colloidal tips provide highly reproducible results. Similar average values but different distributions are shown for the adhesion measured on two major components of wood surface (cell wall and lumen). Evidence supports the hypothesis that the difference of the adhesion force distribution on these two locations was mainly induced by their surface roughness.

opencc-zeroNov 2019View details →

Mapping the EORTC QLQ-C30 and QLQ-H&N35 to the EQ-5D for head and neck cancer: can disease-specific utilities be obtained?

Introduction Innovations in head and neck cancer (HNC) treatment are often subject to economic evaluation prior to their reimbursement and subsequent access for patients. Mapping functions facilitate economic evaluation of new treatments when the required utility data is absent, but quality of life data is available. The objective of this study is to develop a mapping function translating the EORTC QLQ-C30 to EQ-5D-derived utilities for HNC through regression modeling, and to explore the added value of disease-specific EORTC QLQ-H&N35 scales to the model. Methods Data was obtained on patients with primary HNC treated with curative intent derived from two hospitals. Model development was conducted in two phases: 1. Predictor selection based on theory- and data-driven methods, resulting in three sets of potential predictors from the quality of life questionnaires; 2. Selection of the best out of four methods: ordinary-least squares, mixed-effects linear, Cox and beta regression, using the first set of predictors from EORTC QLQ-C30 scales with most correspondence to EQ-5D dimensions. Using a stepwise approach, we assessed added values of predictors in the other two sets. Model fit was assessed using Akaike and Bayesian Information Criterion (AIC and BIC) and model performance was evaluated by MAE, RMSE and limits of agreement (LOA). Results The beta regression model showed best model fit, with global health status, physical-, role- and emotional functioning and pain scales as predictors. Adding HNC-specific scales did not improve the model. Model performance was reasonable; R2=0.39, MAE=0.0949, RMSE=0.1209, 95% LOA of -0.243 to 0.231 (bias -0.01), with an error correlation of 0.32. The estimated shrinkage factor was 0.90. Conclusions Selected scales from the EORTC QLQ-C30 can be used to estimate utilities for HNC using beta regression. Including EORTC QLQ-H&N35 scales does not improve the mapping function. The mapping model may serve as a tool to enable cost-effectiveness analyses of innovative HNC treatments, for example for reimbursement issues. Further research should assess the robustness and generalizability of the function by validating the model in an external cohort of HNC patients.

opencc-zeroDec 2014View details →

Data from: Genetic variation and association mapping for 12 agronomic traits in indica rice

Background: Increasing rice (Oryza sativa L.) yield is a crucial challenge for modern agriculture. The ideal plant architecture is considered to be critical to enhance rice yield. Elite plant morphological traits should include compact plant type, short stature, few unproductive tillers, thick and sturdy stems and erect leaves. To reveal the genetic variations of important morphological traits, 523 germplasm accessions were genotyped using the Illumina custom-designed array containing 5,291 single nucleotide polymorphisms (SNPs) and phenotyped in two independent environments. Genome-wide association studies were performed to uncover the genotypic and phenotypic variations using a mixed linear model. Results: In total, 126 and 172 significant loci were identified and these loci explained an average of 34.45 % and 39.09 % of the phenotypic variance in two environments, respectively, and 16 of 298 (~5.37 %) loci were detected across the two environments. For the 16 loci, 423 candidate genes were predicted in a 200-kb region (±100 kb of the peak SNP). Expression-level analyses identified four candidate genes as the most promising regulators of tiller angle. Known (NAL1 and Rc) and new significant loci showed pleiotropy and gene linkage. In addition, a long genome region covering ~1.6 Mb on chromosome 11 was identified, which may be critical for rice leaf architecture because of a high association with flag leaf length and the ratio of flag leaf length and width. The pyramid effect of the elite alleles indicated that these significant loci could be beneficial for rice plant architecture improvements in the future. Finally, 37 elite varieties were chosen as breeding donors for further rice plant architectural modifications. Conclusions: This study detected multiple novel loci and candidate genes related to rice morphological traits, and the work demonstrated that genome-wide association studies are powerful strategies for uncovering the genetic variations of complex traits and identifying candidate genes in rice, even though the linkage disequilibrium decayed slowly in self-pollinating species. Future research will focus on the biological validation of the candidate genes, and elite varieties will also be of interest in genome selection and breeding by design.

opencc-zeroDec 2013View details →

Data from: An SNP-based second-generation genetic map of Daphnia magna and its application to QTL analysis of phenotypic traits

Background: Although Daphnia is increasingly recognized as a model for ecological genomics and biomedical research, there is, as of yet, no high-resolution genetic map for the genus. Such a map would provide an important tool for mapping phenotypes and assembling the genome. Here we estimate the genome size of Daphnia magna and describe the construction of an SNP array based linkage map. We then test the suitability of the map for life history and behavioural trait mapping. The two parent genotypes used to produce the map derived from D. magna populations with and without fish predation, respectively and are therefore expected to show divergent behaviour and life-histories. Results: Using flow cytometry we estimated the genome size of D. magna to be about 238 mb. We developed an SNP array tailored to type SNPs in a D. magna F2 panel and used it to construct a D. magna linkage map, which included 1,324 informative markers. The map produced ten linkage groups ranging from 108.9 to 203.6 cM, with an average distance between markers of 1.13 cM and a total map length of 1,483.6 cM (Kosambi corrected). The physical length per cM is estimated to be 160 kb. Mapping infertility genes, life history traits and behavioural traits on this map revealed several significant QTL peaks and showed a complex pattern of underlying genetics, with different traits showing strongly different genetic architectures. Conclusions: The new linkage map of D. magna constructed here allowed us to characterize genetic differences among parent genotypes from populations with ecological differences. The QTL effect plots are partially consistent with our expectation of local adaptation under contrasting predation regimes. Furthermore, the new genetic map will be an important tool for the Daphnia research community and will contribute to the physical map of the D. magna genome project and the further mapping of phenotypic traits. The clones used to produce the linkage map are maintained in a stock collection and can be used for mapping QTLs of traits that show variance among the F2 clones.

Data from: Application of a dense genetic map for assessment of genomic responses to selection and inbreeding in Heliothis virescens

Adaptation of pest species to laboratory conditions and selection for resistance to toxins in the laboratory are expected to cause inbreeding and genetic bottlenecks that reduce genetic variation. Heliothis virescens, a major cotton pest, has been colonized in the laboratory many times, and a few laboratory colonies have been selected for Bacillus thuringiensis (Bt) resistance. We developed 350-bp double-digest restriction-site associated DNA-sequencing (ddRAD-seq) molecular markers to examine and compare changes in genetic variation associated with laboratory adaptation, artificial selection and inbreeding in this nonmodel insect species. We found that allelic and nucleotide diversity declined dramatically in laboratory-reared H. virescens as compared with field-collected populations. The declines were primarily a result of the loss of low frequency alleles present in field-collected H. virescens. A further, albeit modest decline in genetic diversity was observed in a Bt-selected population. The greatest decline was seen in H. virescens that were sib-mated for 10 generations, in which more than 80% of loci were fixed for a single allele. To determine which regions of the genome were resistant to fixation in our sib-mated line, we generated a dense intraspecific linkage map containing three PCR-based and 659 ddRAD-seq markers. Markers that retained polymorphism were observed in small clusters spread over multiple linkage groups, but this clustering was not statistically significant. Overall, we have confirmed and extended the general expectations for reduced genetic diversity in laboratory colonies, provided tools for further genomic analyses and produced highly homozygous genomic DNA for future whole genome sequencing of H. virescens.

opencc-zeroDec 2013View details →

Data from: Mapping migration in a songbird using high-resolution genetic markers

Neotropical migratory birds are declining across the Western Hemisphere, but conservation efforts have been hampered by the inability to assess where migrants are most limited – the breeding grounds, migratory stopover sites, or wintering areas. A major challenge has been the lack of an efficient, reliable, and broadly applicable method for measuring the strength of migratory connections between populations across the annual cycle. Here we show how high-resolution genetic markers can be used to identify genetically distinct groups of a migratory bird, the Wilson's warbler (Cardellina pusilla), at fine enough spatial scales to facilitate assessing regional drivers of demographic trends. By screening 1626 samples using 96 highly divergent single nucleotide polymorphisms (SNPs) selected from a large pool of candidates (~450,000), we identify novel region-specific migratory routes and timetables of migration along the Pacific Flyway. Our results illustrate that high-resolution genetic markers are more reliable, precise, and amenable to high throughput screening than previously described intrinsic marking techniques, making them broadly applicable to large-scale monitoring and conservation of migratory organisms.

opencc-zeroDec 2009View details →

Data from: Identification of X-linked quantitative trait loci affecting cold tolerance in Drosophila melanogaster and fine-mapping by selective sweep analysis

Drosophila melanogaster is a cosmopolitan species that colonizes a great variety of environments. One trait that shows abundant evidence for naturally segregating genetic variance in different populations of D. melanogaster is cold tolerance. Previous work has found quantitative trait loci (QTL) exclusively on the second and the third chromosomes. To gain insight into the genetic architecture of cold tolerance on the X chromosome and to compare the results with our analyses of selective sweeps, a mapping population was derived from a cross between substitution lines that solely differed in the origin of their X chromosome: one originates from a European inbred line, the other one from an African inbred line. We found a total of six QTL for cold tolerance factors on the X chromosome of D. melanogaster. Although the composite interval mapping revealed slightly different QTL profiles between sexes, a coherent model suggests that most QTL overlapped between sexes and each explained around 5-14% of the genetic variance (which may be slightly overestimated). The allelic effects were largely additive, but we also detected two significant interactions. Taken together, this provides evidence for multiple QTL that are spread along the entire X chromosome and whose effects range from low to intermediate. One detected transgressive QTL influences cold tolerance in different ways for the two sexes. While females benefit from the European allele increasing their cold tolerance, males tend to do better with the African allele. Finally, using selective sweep mapping the candidate gene CG16700 for cold tolerance co-localizing with a QTL was identified.

Data from: Selective breeding and selection mapping using a novel wild-derived heterogeneous stock mice revealed two closely-linked loci for tameness

Tameness is a major behavioral factor for domestication, and can be divided into two potential components: motivation to approach humans (active tameness) and reluctance to avoid humans (passive tameness). We identified genetic loci for active tameness through selective breeding, selection mapping, and association analysis. In previous work using laboratory and wild mouse strains, we found that laboratory strains were predominantly selected for passive tameness but not active tameness during their domestication. To identify genetic regions associated with active tameness, we applied selective breeding over 9 generations for contacting, a behavioural parameter strongly associated with active tameness. The prerequisite for successful selective breeding is high genetic variation in the target population, so we established and used a novel resource, wild-derived heterogeneous stock (WHS) mice from eight wild strains. The mice had genetic variations not present in other outbred mouse populations. Selective breeding of the WHS mice increased the contacting level through the generations. Selection mapping was applied to the selected population using a simulation based on a non-selection model and inferred haplotype data derived from single-nucleotide polymorphisms. We found a genomic signature for selection on chromosome 11 containing two closely linked loci.

opencc-zeroDec 2017View details →

Data from: Compressor map regression modelling based on partial least squares

In this work, two kinds of partial least squares modelling methods are applied to predict a compressor map: one uses a Power function polynomial as the basis function (PLSO), and the other uses a trigonometric function polynomial (PLSN). To demonstrate the potential capabilities of PLSO and PLSN for a typical interpolated prediction and extrapolated prediction, they are compared with two other classical data-driven modelling methods, namely, the look-up table and artificial neural network. PLSO and PLSN are also compared to each other. The results show that PLSO and PLSN have a better prediction performance than the look-up table and the artificial neural network, especially for the extrapolated prediction. At the same time, the computational time is also decreased sharply. Compared with PLSO, PLSN is characterized with higher prediction accuracy and shorter computational time than PLSO. It can be expected that PLSN can be time-saving and improve the accuracy of a thermodynamic model of a diesel engine.

Data from: Mapping and analysis of the connectome of sympathetic premotor neurons in the rostral ventrolateral medulla of the rat using a volumetric brain atlas

Spinally projecting neurons in the rostral ventrolateral medulla (RVLM) play a critical role in the generation of vasomotor sympathetic tone and are thought to receive convergent input from neurons at every level of the neuraxis; the factors that determine their ongoing activity remain unresolved. In this study we use a genetically restricted viral tracing strategy to definitively map their spatially diffuse connectome. We infected bulbospinal RVLM neurons with recombinant rabies variant that drives reporter expression in monosynaptically connected input neurons and mapped their distribution using a MRI-based volumetric atlas and a novel image alignment and visualization tool that efficiently translates the positions of neurons captured in conventional photomicrographs to Cartesian coordinates. We identified prominent inputs from well-established neurohumoral and viscero-sympathetic sensory actuators, medullary autonomic and respiratory subnuclei, and supramedullary autonomic nuclei. The majority of inputs lay within the brainstem (88 – 94%), and included putative respiratory neurons in the pre-Bötzinger Complex and post-inspiratory complex that are therefore likely to underlie respiratory-sympathetic coupling. We also discovered a substantial and previously unrecognized input from the region immediately ventral to nucleus prepositus hypoglossi. In contrast, RVLM sympathetic premotor neurons were only sparsely innervated by suprapontine structures including the paraventricular nucleus, lateral hypothalamus, periaqueductal grey and superior colliculus, and we found almost no evidence of direct inputs from the cortex or amygdala. Our approach can be used to quantify, standardize and share complete neuroanatomical datasets, and therefore provides researchers with a platform for presentation, analysis and independent analysis of connectomic data.

Data from: Integrating regulatory surveys and citizen science to map outbreaks of forest diseases: acute oak decline in England and Wales

The number of emerging tree diseases has increased rapidly in recent times, with severe environmental and economic consequences. Systematic regulatory surveys to detect and establish the distribution of pests are crucial for successful management efforts, but resource intensive and costly. Volunteers who identify potential invasive species can form an important early warning network in tree health, however, what these data can tell us and how they can be best used to inform and direct official survey effort is not clear. Here we use an extensive dataset on Acute Oak Decline (AOD) as an opportunity to ask how verified data received from the public can be utilised. Information on the distribution of AOD was available as (i) systematic regulatory surveys conducted throughout England and Wales (ii) ad-hoc sightings reported by land owners, land managers and members of the public (i.e. 'self-reported' cases). By using the available self-reported cases at the design stage the systematic survey could focus on defining the boundaries of the affected area. This maximised the use of available resources and highlights the benefits to be gained by developing strategies to enhance volunteer efforts in future programs.

opencc-zeroDec 2010View details →

Data from: QTL linkage mapping of wing length in zebra finch using genome-wide single nucleotide polymorphisms markers

Avian wing length is an important trait that covaries with the ecology and migratory behaviour of a species and tends to change rapidly when the conditions are altered. Long-distance migrants typically have longer wings than short-distance migrants and sedentary species, and long-winged species also tend to be more dispersive. Although the substantial heritability of avian wing length is well established, the identification of causal genes has remained elusive. Based on large-scale genotyping of 1404 informative single nucleotide polymorphisms (SNP) in a captive population of 1067 zebra finches, we here show that the within-population variation of relative wing length (h2 = 0.74 ± 0.05) is associated with standing genetic variation in at least six genomic regions (one genome-wide significant and five suggestive). The variance explained by these six quantitative trait loci (QTL) sums to 36.8% of the phenotypic variance (half of the additive genetic variance), although this likely is an overestimate attributable to the Beavis effect. As avian wing length is primarily determined by the length of the primary feathers, we then searched for candidate genes that are related to feather growth. Interestingly, all of the QTL signals co-locate with Wnt growth factors and closely interacting genes (Wnt3a, Wnt5a, Wnt6, Wnt7a, Wnt9a, RhoU and RhoV). Our findings therefore suggest that standing genetic variation in the Wnt genes might be linked to avian wing morphology, although there are many other genes that also fall within the confidence regions.

Data from: Extreme QTL mapping of germination speed in Arabidopsis thaliana

Seed germination is a key life history transition for annual plants and partly determines lifetime performance and fitness. Germination speed, the elapsed time for a nondormant seed to germinate, is a poorly understood trait important for plants' competitiveness and fitness in fluctuating environments. Germination speed varied by 30% among 18 Arabidopsis thaliana populations measured, and exhibited weak negative correlation with flowering time and seed weight, with significant genotype effect (P < 0.005). To dissect the genetic architecture of germination speed, we developed the extreme QTL (X-QTL) mapping method in A. thaliana. The method has been shown in yeast to increase QTL mapping power by integrating selective screening and bulk-segregant analysis in a very large mapping population. By pooled genotyping of top 5% of rapid germinants from ~100 000 F3 individuals, three X-QTL regions were identified on chromosomes 1, 3 and 4. All regions were confirmed as QTL regions by sequencing 192 rapid germinants from an independent F3 selection experiment. Positional overlaps were found between X-QTLs and previously identified seed, life history and fitness QTLs. Our method provides a rapid mapping platform in A. thaliana with potentially greater power. One can also relate identified X-QTLs to the A. thaliana physical map, facilitating candidate gene identification.

opencc-zeroDec 2012View details →

Data from: Comparative linkage maps suggest that fission, not polyploidy, underlies near-doubling of chromosome number within monkeyflowers (Mimulus; Phrymaceae)

Changes in chromosome number and structure are important contributors to adaptation, speciation, and macroevolution. In flowering plants, polyploidy and subsequent reductions in chromosome number by fusion are major sources of chromosomal evolution, but chromosome number increase by fission has been relatively unexplored. Here, we use comparative linkage mapping with gene-based markers to reconstruct chromosomal synteny within the model flowering plant genus Mimulus (monkeyflowers). Two sections of the genus with haploid numbers {greater than or equal to} 14 have been inferred to be relatively recent polyploids because they are phylogenetically nested within numerous taxa with low base numbers (n = 8-10). We combined multiple datasets to build integrated genetic maps of the M. guttatus species complex (section Simiolus, n = 14) and the M. lewisii group (section Erythranthe; n = 8), and then aligned the two integrated maps using >100 shared markers. We observed strong segmental synteny between M. lewisii and M. guttatus maps, with essentially 1-to-1 correspondence across each of 16 chromosomal blocks. Assuming that the M. lewisii (and widespread) base number of 8 is ancestral, reconstruction of 14 M. guttatus chromosomes requires at least eight fission events (likely shared by Simiolus and sister section Paradanthus [n=16]), plus two fusion events. This apparent burst of fission in the yellow monkeyflower lineages raises new questions about mechanisms and consequences of chromosomal fission in plants. Our comparative maps also provide insight into the origins of a chromosome exhibiting centromere-associated female meiotic drive and create a framework for transferring M. guttatus genome resources across the entire genus.

opencc-zeroDec 2010View details →

Data from: Genetic mapping a meiotic driver that causes sex ratio distortion in the mosquito Aedes aegypti

An endogenous meiotic driver in the dengue and yellow fever vector mosquito Aedes aegypti can cause highly male-biased sex ratio distortion in crosses from suitable genetic backgrounds. We previously selected a strain that carries a strong meiotic drive gene (D) linked with the male-determining allele (M) on chromosome 1 in A. aegypti. Here we performed segregation analysis of the MD locus among backcross (BC1) progeny from a driver male and drive-sensitive females. Assessment of sex ratios among BC2 progeny showed ~5.2% recombination between the MD locus and the sex determination locus. Multipoint linkage mapping across this region revealed consistent marker orders and recombination frequencies with the existing reference linkage map and placed the MD locus within a 6.5 cM interval defined by the LF159 locus and microsatellite marker 446GAA, which should facilitate future positional cloning efforts.

opencc-zeroDec 2014View details →

Data from: Genetic mapping of MAPK-mediated complex traits across S. cerevisiae

Signaling pathways enable cells to sense and respond to their environment. Many cellular signaling strategies are conserved from fungi to humans, yet their activity and phenotypic consequences can vary extensively among individuals within a species. A systematic assessment of the impact of naturally occurring genetic variation on signaling pathways remains to be conducted. In S. cerevisiae, both response and resistance to stressors that activate signaling pathways differ between diverse isolates. Here, we present a quantitative trait locus (QTL) mapping approach that enables us to identify genetic variants underlying such phenotypic differences across the genetic and phenotypic diversity of S. cerevisiae. Using a Round-robin cross between twelve diverse strains, we identified QTL that influence phenotypes critically dependent on MAPK signaling cascades. Genetic variants under these QTL fall within MAPK signaling networks themselves as well as other interconnected signaling pathways. Finally, we demonstrate how the mapping results from multiple strain background can be leveraged to narrow the search space of causal genetic variants.

opencc-zeroDec 2013View details →

Data from: Mixed linear model approach for mapping quantitative trait loci underlying crop seed traits

The crop seed is a complex organ that may be composed of the diploid embryo, the triploid endosperm and the diploid maternal tissues. According to the genetic features of seed characters, two genetic models for mapping quantitative trait loci (QTLs) of crop seed traits are proposed, with inclusion of maternal effects, embryo or endosperm effects of QTL, environmental effects and QTL-by-environment (QE) interactions. The mapping population can be generated either from double back-cross of immortalized F2 (IF2) to the two parents, from random-cross of IF2 or from selfing of IF2 population. Candidate marker intervals potentially harboring QTLs are first selected through one-dimensional scanning across the whole genome. The selected candidate marker intervals are then included in the model as cofactors to control background genetic effects on the putative QTL(s). Finally, a QTL full model is constructed and model selection is conducted to eliminate false positive QTLs. The genetic main effects of QTLs, QE interaction effects and the corresponding P-values are computed by Markov chain Monte Carlo algorithm for Gaussian mixed linear model via Gibbs sampling. Monte Carlo simulations were performed to investigate the reliability and efficiency of the proposed method. The simulation results showed that the proposed method had higher power to accurately detect simulated QTLs and properly estimated effect of these QTLs. To demonstrate the usefulness, the proposed method was used to identify the QTLs underlying fiber percentage in an upland cotton IF2 population. A computer software, QTLNetwork-Seed, was developed for QTL analysis of seed traits.

Data from: Microelastic mapping of the rat dentate gyrus

The lineage commitment of many cultured stem cells, including adult neural stem cells (NSCs), is strongly sensitive to the stiffness of the underlying extracellular matrix. However, it remains unclear how well the stiffness ranges explored in culture align with the microscale stiffness values stem cells actually encounter within their endogenous tissue niches. To address this question in the context of hippocampal NSCs, we used atomic force microscopy to spatially map the microscale elastic modulus (E) of specific anatomical substructures within living slices of rat dentate gyrus in which NSCs reside during lineage commitment in vivo. We measured depth-dependent apparent E-values at locations across the hilus (H), subgranular zone (SGZ) and granule cell layer (GCL) and found a two- to threefold increase in stiffness at 500 nm indentation from the H (49 ± 7 Pa) and SGZ (58 ± 8 Pa) to the GCL (115 ± 18 Pa), a fold change in stiffness we have previously found functionally relevant in culture. Additionally, E exhibits nonlinearity with depth, increasing significantly for indentations larger than 1 µm and most pronounced in the GCL. The methodological advances implemented for these measurements allow the quantification of the elastic properties of hippocampal NSC niche at unprecedented spatial resolution.

Data from: Reconstruction of the cortical maps of the Tasmanian tiger and comparison to the Tasmanian devil

The last known Tasmanian tiger (Thylacinus cynocephalus)–aka the thylacine–died in 1936. Because its natural behavior was never scientifically documented, we are left to infer aspects of its behavior from museum specimens and historical recollections of bushmen. Recent advances in brain imaging have made it possible to scan postmortem specimens of a wide range of animals, even more than a decade old. Any thylacine brain, however, would be more than 100 years old. Here, we show that it is possible to reconstruct white matter tracts in two thylacine brains. For functional interpretation, we compare to the white matter reconstructions of the brains of two Tasmanian devils (Sarcophilus harrisii). We reconstructed the cortical projection zones of the basal ganglia and major thalamic nuclei. The basal ganglia reconstruction showed a more modularized pattern in the cortex of the thylacine, while the devil cortex was dominated by the putamen. Similarly, the thalamic projections had a more orderly topography in the thylacine than the devil. These results are consistent with theories of brain evolution suggesting that larger brains are more modularized. Functionally, the thylacine's brain may have had relatively more cortex devoted to planning and decision-making, which would be consistent with a predatory ecological niche versus the scavenging niche of the devil.