Biology subjects

Brown, K. C.

Publications and source records attributed to Brown, K. C..

4 recordsLinked to original sources

bioRxiv2024

High-fat diet exacerbates the loss of bone fracture toughness in aging for C57BL/6JN mice

The elderly are at increased risk of bone fracture and more often consume poor quality diets, such as high-fat diet (HFD). We hypothesized that HFD would exacerbate the loss of bone fracture resistance in aging. To test this hypothesis, we fed 5-month and 22-month C57BL/6JN mice of both sexes HFD or low-fat diet for 8 weeks. Aging and HFD lowered bone fracture toughness, while only aging reduced bone strength. At the tissue-scale, aging increased bone mineral maturity, while HFD altered bone mineralization and maturity as well as collagen structure. Cortical bone metabolism was also dysregulated with aging and HFD. Dysregulated pathways in aging and HFD were related to cellular function and viability, or glucose regulation, respectively. Aging with HFD also impacted osteoclast and adipocyte abundance and osteocyte viability. Together, these data demonstrate that HFD may exacerbate the loss of bone matrix quality and fracture resistance in aging.

bioengineering↗

bioRxiv2022

tinyRNA: precision analysis of small RNA-seq data with user-defined hierarchical selection rules

SummarytinyRNA performs precision analysis of small RNAs, including miRNAs, piRNAs, and siRNAs, from high-throughput sequencing experiments. At the core of tinyRNA is a highly flexible counting utility, tiny-count, that allows for hierarchical assignment of small RNA reads to features based on positional information, extent of feature overlap, 5 nucleotide, length, and strandedness. tinyRNA provides an all-in-one solution for small RNA-seq data analysis, with documentation and statistics generated at each step for accurate, reproducible results. Availability and ImplementationtinyRNA tools are implemented in Python and R, and the pipeline workflow is coordinated with CWL. tinyRNA is free and open-source software distributed under the GPLv3 license. tinyRNA is available at https://github.com/MontgomeryLab/tinyRNA. Contacttai.montgomery@colostate.edu Supplementary informationReference data, including genome sequences and features tables, for certain species can be found at https://www.MontgomeryLab.org.

bioinformatics↗

bioRxiv2019

Combining tRNA sequencing methods to characterize plant tRNA expression and post-transcriptional modification

Differences in tRNA expression have been implicated in a remarkable number of biological processes. There is growing evidence that tRNA genes can play dramatically different roles depending on both expression and post-transcriptional modification, yet sequencing tRNAs to measure abundance and detect modifications remains challenging. Their secondary structure and extensive post-transcriptional modifications interfere with RNA-seq library preparation methods and have limited the utility of high-throughput sequencing technologies. Here, we combine two modifications to standard RNA-seq methods by treating with the demethylating enzyme AlkB and ligating with tRNA-specific adapters in order to sequence tRNAs from four species of flowering plants, a group that has been shown to have some of the most extensive rates of post-transcriptional tRNA modifications. This protocol has the advantage of detecting full-length tRNAs and sequence variants that can be used to infer many post-transcriptional modifications. We used the resulting data to produce a modification index of almost all unique reference tRNAs in Arabidopsis thaliana, which exhibited many anciently conserved similarities with humans but also positions that appear to be \"hot spots\" for modifications in angiosperm tRNAs. We also found evidence based on northern blot analysis and droplet digital PCR that, even after demethylation treatment, tRNA-seq can produce highly biased estimates of absolute expression levels most likely due to biased reverse transcription. Nevertheless, the generation of full-length tRNA sequences with modification data is still promising for assessing differences in relative tRNA expression across treatments, tissues or subcellular fractions and help elucidate the functional roles of tRNA modifications.

molecular biology↗

bioRxiv2019

Full Emergence timing and voltinism of phantom midges, Chaoborus spp., in the UK

After introduction of overwintered fourth instar larvae (2027 in total), emergence timing of adult Chaoborus spp. (Diptera: Chaoboridae) was investigated in four outdoor freshwater microcosms in the UK in 2017. Adults started emerging on 13 April and emergence reached a peak on 2 May. The majority of emergence was completed by 3 June. Emergence rates for each microcosm ranged from 51.4% to 66.2% with a mean of 60.9%. The great majority of emerged adults were C. obscuripes (99.68%). Males appeared to emerge slightly earlier than females. The results indicated that for overwintered C. obscuripes larvae, the adults emerged en masse in spring (rather than emerging gradually over the course of spring and summer). In a separate experiment at the same location, the number of Chaoborus spp. life-cycles occurring per year was determined using six replicate groups of microcosms, each group containing four microcosms. Each microcosm contained 200 L of water and was enclosed within a pop-up frame covered with insect-proof mesh (1 mm2 aperture). The first microcosm in each group was seeded with egg rafts (first generation) of Chaoborus spp. Following adult emergence, as soon as the first egg rafts were laid in each microcosm these were removed and transferred to the second microcosm in that group, and so on. The larvae sampled from the second and subsequent generations in the microcosms were all C. crystallinus. C. crystallinus produced up to four discrete generations within the experimental period, and life-cycle times from egg-to-egg ranged from 14 days (replicate group 5, first generation) to 56 days (replicate 3, second generation). These two experiments, indicated that i) adult C. obscuripes arising from overwintered larvae emerged en masse in the spring, and ii) up to four generations of C. crystallinus occurred; i.e. C. crystallinus exhibited a multi-voltine life history under the temperate conditions of this UK study.

ecology↗