Variance Component Estimates for Growth Traits in Beef Cattle Using Selected Variants from Imputed Low-Pass Sequence Data

A beef cattle population (n=2,343) was used to assess the impact of variants identified from imputed low-pass sequence (LPS) on the estimation of variance components and genetic parameters of birth weight (BWT) and post weaning gain (PWG). Variants were selected based on functional impact and were partitioned into four groups (Low, Modifier, Moderate, High) based on predicted functional consequences and re-partitioned based on consequence of mutation, such as missense and untranslated region variants, into six groups (G1-G6). Each subset was used to construct a genomic relationship matrix (GRM) for univariate animal models. Multiple analyses were conducted to compare the proportion of additive genetic variation explained by the different subsets individually and collectively, and these estimates were benchmarked against all LPS variants in a single GRM and array (e.g., GeneSeek Genomic Profiler 100K) genotypes. When all variants were included in a single GRM, heritability estimates for BWT and PWG were 0.43±0.05 and 0.38±0.05, respectively. Heritability estimates for BWT ranged from 0.10-0.42 dependent on which variant subsets were included. Similarly, estimates for PWG ranged from 0.05-0.38. Results showed that variants in the subsets Modifier and G1 (untranslated region) yielded similar heritability estimates compared to the inclusion of all variants yielded the highest estimates, while estimates from GRM containing only variants in the categories High, G4 (non-coding transcript exon), and G6 (start and stop loss/gain) were the lowest. All variants combined provided similar heritability estimates to chip genotypes and provided minimal to no additional information when combined with chip data. This suggests that the chip data and the variants from LPS predicted to be less consequential are in relatively high linkage disequilibrium with the underlying causal variants and sufficiently spread throughout the genome to capture larger proportions of additive genetic variation. Advisor: Matthew L. Spangle

Mutations in the Amyloid-β Protein Precursor Reduce Mitochondrial Function and Alter Gene Expression Independent of 42-Residue Amyloid-β Peptide

Background:Dominant missense mutations in the amyloid-β protein precursor (AβPP) cause early-onset familial Alzheimer’s disease (FAD) and are associated with changes in the production or properties of the amyloid-β peptide (Aβ), particularly of the 42-residue variant (Aβ42) that deposits in the Alzheimer’s disease (AD) brain. Recent findings, however, show that FAD mutations in AβPP also lead to increased production of longer Aβ variants of 45–49 residues in length. Objective:We aimed to test neurotoxicity of Aβ42 vis-á-vis longer variants, focusing specifically on mitochondrial function, as dysfunctional mitochondria are implicated in the pathogenesis of AD. Methods:We generated SH-SY5Y human neuroblastoma cells stably expressing AβPP mutations that lead to increased production of long Aβ peptides with or without Aβ42. These AβPP-expressing cells were tested for oxygen consumption rates (OCR) under different conditions designed to interrogate mitochondrial function. These cell lines were also examined for expression of genes important for mitochondrial or neuronal structure and function. Results:The mutant AβPP-expressing cells showed decreased basal OCRs as well as decreased OCRs associated with mitochondrial ATP production, even more so in the absence of Aβ42 production. Moreover, mutant AβPP-expressing cells producing longer forms of Aβ displayed altered expression of certain mitochondrial- and neuronal-associated genes, whether or not Aβ42 was produced. Conclusion:These findings suggest that mutant AβPP can cause mitochondrial dysfunction that is associated with long Aβ but not with Aβ42

A Four-Year, Seven-State Reforestation Trial with Eastern Hemlocks (\u3cem\u3eTsuga canadensis\u3c/em\u3e) Resistant to Hemlock Woolly Adelgid (\u3cem\u3eAdelges tsugae\u3c/em\u3e)

We conducted over a decade of research into individual eastern hemlock (Tsuga canadensis; hemlock) trees that are potentially resistant to hemlock woolly adelgid (Adelges tsugae; HWA), an invasive xylem-feeding insect that is capable of rapidly killing even mature trees. Following clonal propagation of these individuals, in 2015 we planted size- and age-matched HWA-resistant and HWA-susceptible hemlocks in HWA-infested forest plots in seven states. In 2019, we re-surveyed the plots; 96% of HWA-resistant hemlocks survived compared to 48% of susceptible trees. The surviving HWA-resistant trees were also taller, produced more lateral growth, retained more foliage, and supported lower densities of the elongate hemlock scale Fiorinia externa, another invasive hemlock pest, than the surviving HWA-susceptible trees. Our results suggest that HWA management may benefit from additional research exploring the identification, characterization, and use of HWA-resistant eastern hemlocks in future reforestation efforts

Toward open sharing of task-based fMRI data: the OpenfMRI project

The large-scale sharing of task-based functional neuroimaging data has the potential to allow novel insights into the organization of mental function in the brain, but the field of neuroimaging has lagged behind other areas of bioscience in the development of data sharing resources. This paper describes the OpenFMRI project (accessible online at http://www.openfmri.org), which aims to provide the neuroimaging community with a resource to support open sharing of task-based fMRI studies. We describe the motivation behind the project, focusing particularly on how this project addresses some of the well-known challenges to sharing of task-based fMRI data. Results from a preliminary analysis of the current database are presented, which demonstrate the ability to classify between task contrasts with high generalization accuracy across subjects, and the ability to identify individual subjects from their activation maps with moderately high accuracy. Clustering analyses show that the similarity relations between statistical maps have a somewhat orderly relation to the mental functions engaged by the relevant tasks. These results highlight the potential of the project to support large-scale multivariate analyses of the relation between mental processes and brain function

Is Mitigation Translocation an Effective Strategy for Conserving Common Chuckwallas?

Mitigation translocation remains a popular conservation tool despite ongoing debate regarding its utility for population conservation. To add to the understanding of the effectiveness of mitigation translocation, in 2017 and 2018 we monitored a population of protected common chuckwallas (Sauromalus ater) following translocation away from the area of construction of a new highway near the South Mountains, Phoenix, Arizona, USA. We removed chuckwallas from the construction right-of-way, paint-marked and pit-tagged them, and then released them in a nearby municipal preserve. We deployed very high frequency radio-telemetry transmitters on a sub-sample of 15 translocated adult chuckwallas. We monitored the radio-marked chuckwallas once a day at 1- to 3-day intervals for up to 46 days to document survival, body mass, and post-release movements. The average distance moved following translocation was 359 ± 53 m. Using minimum convex polygons, the average home range size of translocated lizards was 0.9 ± 0.3 ha, which was 18–45 times larger than expected for the species. Following translocations, we surveyed the translocation sites 1 month later and again 1 year later to determine the presence of translocated chuckwallas. Translocated individuals were rarely observed a second time: in 2017, only 11 of 160 translocated chuckwallas were seen again, and in 2018, only 11 of 192 translocated chuckwallas were detected. In the light of low recapture rate, consistent loss of body mass, and large movements of marked lizards, we conclude that survival of translocated chuckwallas was low over a single year. In the future, efficacy of mitigation translocation could be better evaluated by assessing the spatial ecology of both resident and translocated individuals simultaneously using radio-telemetry

Prospectus, September 6, 1989

https://spark.parkland.edu/prospectus_1989/1018/thumbnail.jp

FAPRI 1999 U.S. Agricultural Outlook

Crop Production/Industries, Livestock Production/Industries,

Quantum state preparation and macroscopic entanglement in gravitational-wave detectors

Long-baseline laser-interferometer gravitational-wave detectors are operating at a factor of 10 (in amplitude) above the standard quantum limit (SQL) within a broad frequency band. Such a low classical noise budget has already allowed the creation of a controlled 2.7 kg macroscopic oscillator with an effective eigenfrequency of 150 Hz and an occupation number of 200. This result, along with the prospect for further improvements, heralds the new possibility of experimentally probing macroscopic quantum mechanics (MQM) - quantum mechanical behavior of objects in the realm of everyday experience - using gravitational-wave detectors. In this paper, we provide the mathematical foundation for the first step of a MQM experiment: the preparation of a macroscopic test mass into a nearly minimum-Heisenberg-limited Gaussian quantum state, which is possible if the interferometer's classical noise beats the SQL in a broad frequency band. Our formalism, based on Wiener filtering, allows a straightforward conversion from the classical noise budget of a laser interferometer, in terms of noise spectra, into the strategy for quantum state preparation, and the quality of the prepared state. Using this formalism, we consider how Gaussian entanglement can be built among two macroscopic test masses, and the performance of the planned Advanced LIGO interferometers in quantum-state preparation

Searching for a Stochastic Background of Gravitational Waves with LIGO

The Laser Interferometer Gravitational-wave Observatory (LIGO) has performed the fourth science run, S4, with significantly improved interferometer sensitivities with respect to previous runs. Using data acquired during this science run, we place a limit on the amplitude of a stochastic background of gravitational waves. For a frequency independent spectrum, the new limit is $\Omega_{\rm GW} < 6.5 \times 10^{-5}$. This is currently the most sensitive result in the frequency range 51-150 Hz, with a factor of 13 improvement over the previous LIGO result. We discuss complementarity of the new result with other constraints on a stochastic background of gravitational waves, and we investigate implications of the new result for different models of this background.Comment: 37 pages, 16 figure

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species–season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds