The Training and Tapering Practices of Highland Games Heavy Event Athletes.

ABSTRACT: Winwood, PW, Keogh, JW, Travis, SK, Grieve, I, and Pritchard, HJ. The training and tapering practices of Highland Games heavy event athletes. J Strength Cond Res 38(3): e116-e124, 2024-This study provides the first empirical evidence of how Highland Games heavy event athletes train and taper for Highland Games competitions. Athletes (n = 169) (mean ± SD: age 40.8 ± 10.7 years, height 181.2 ± 9.5 cm, weight 107.2 ± 23.0 kg, 18.8 ± 10.3 years of general resistance training, and 8.1 ± 6.9 years of competitive Highland Games experience) completed a self-reported 4-page online survey on training and tapering practices. Analysis by sex (male and female) and competitive standard (local or regional, national, and international) was conducted. Seventy-eight percent (n = 132) of athletes reported that they used a taper. Athletes stated that their taper length was 5.2 ± 3.5 days, with the step (36%) and linear tapers (33%) being the most performed. Athletes reported that their highest training volume and intensity were 5.5 and 3.8 weeks out (respectively) from competition, and all training ceased 2.4 ± 1.4 days before competition. Training volume decreased during the taper by 34%. Athletes typically stated that, tapering was performed to achieve recovery, peak performance, and injury prevention; training intensity, frequency, and duration stayed the same or decreased; game-specific training increased with reductions in traditional exercises; the caber toss, weight for height, and heavy weight throw were performed further out from competition than other events; muscular power and strength were the most common types of training performed; static stretching, foam rolling, and massage were strategies used in the taper; and poor tapering occurred because of life/work circumstances, lack of sleep/rest, or training too heavy/hard. These results may aid Highland Games athletes to optimize training and tapering variables leading to improved performances.

Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.

The spontaneously hypertensive rat (SHR) is a widely used rodent model of hypertension and metabolic syndrome. Previously we identified thousands of cis-regulated expression quantitative trait loci (eQTLs) across multiple tissues using a panel of rat recombinant inbred (RI) strains derived from Brown Norway and SHR progenitors. These cis-eQTLs represent potential susceptibility loci underlying physiological and pathophysiological traits manifested in SHR. We have prioritized 60 cis-eQTLs and confirmed differential expression between the parental strains by quantitative PCR in 43 (72%) of the eQTL transcripts. Quantitative trait transcript (QTT) analysis in the RI strains showed highly significant correlation between cis-eQTL transcript abundance and clinically relevant traits such as systolic blood pressure and blood glucose, with the physical location of a subset of the cis-eQTLs colocalizing with "physiological" QTLs (pQTLs) for these same traits. These colocalizing correlated cis-eQTLs (c3-eQTLs) are highly attractive as primary susceptibility loci for the colocalizing pQTLs. Furthermore, sequence analysis of the c3-eQTL genes identified single nucleotide polymorphisms (SNPs) that are predicted to affect transcription factor binding affinity, splicing and protein function. These SNPs, which potentially alter transcript abundance and stability, represent strong candidate factors underlying not just eQTL expression phenotypes, but also the correlated metabolic and physiological traits. In conclusion, by integration of genomic sequence, eQTL and QTT datasets we have identified several genes that are strong positional candidates for pathophysiological traits observed in the SHR strain. These findings provide a basis for the functional testing and ultimate elucidation of the molecular basis of these metabolic and cardiovascular phenotypes.

Genome-wide co-expression analysis in multiple tissues.

Expression quantitative trait loci (eQTLs) represent genetic control points of gene expression, and can be categorized as cis- and trans-acting, reflecting local and distant regulation of gene expression respectively. Although there is evidence of co-regulation within clusters of trans-eQTLs, the extent of co-expression patterns and their relationship with the genotypes at eQTLs are not fully understood. We have mapped thousands of cis- and trans-eQTLs in four tissues (fat, kidney, adrenal and left ventricle) in a large panel of rat recombinant inbred (RI) strains. Here we investigate the genome-wide correlation structure in expression levels of eQTL transcripts and underlying genotypes to elucidate the nature of co-regulation within cis- and trans-eQTL datasets. Across the four tissues, we consistently found statistically significant correlations of cis-regulated gene expression to be rare (<0.9% of all pairs tested). Most (>80%) of the observed significant correlations of cis-regulated gene expression are explained by correlation of the underlying genotypes. In comparison, co-expression of trans-regulated gene expression is more common, with significant correlation ranging from 2.9%-14.9% of all pairs of trans-eQTL transcripts. We observed a total of 81 trans-eQTL clusters (hot-spots), defined as consisting of > or =10 eQTLs linked to a common region, with very high levels of correlation between trans-regulated transcripts (77.2-90.2%). Moreover, functional analysis of large trans-eQTL clusters (> or =30 eQTLs) revealed significant functional enrichment among genes comprising 80% of the large clusters. The results of this genome-wide co-expression study show the effects of the eQTL genotypes on the observed patterns of correlation, and suggest that functional relatedness between genes underlying trans-eQTLs is reflected in the degree of co-expression observed in trans-eQTL clusters. Our results demonstrate the power of an integrative, systematic approach to the analysis of a large gene expression dataset to uncover underlying structure, and inform future eQTL studies.

Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass.

Left ventricular mass (LVM) and cardiac gene expression are complex traits regulated by factors both intrinsic and extrinsic to the heart. To dissect the major determinants of LVM, we combined expression quantitative trait locus1 and quantitative trait transcript (QTT) analyses of the cardiac transcriptome in the rat. Using these methods and in vitro functional assays, we identified osteoglycin (Ogn) as a major candidate regulator of rat LVM, with increased Ogn protein expression associated with elevated LVM. We also applied genome-wide QTT analysis to the human heart and observed that, out of 22,000 transcripts, OGN transcript abundance had the highest correlation with LVM. We further confirmed a role for Ogn in the in vivo regulation of LVM in Ogn knockout mice. Taken together, these data implicate Ogn as a key regulator of LVM in rats, mice and humans, and suggest that Ogn modifies the hypertrophic response to extrinsic factors such as hypertension and aortic stenosis.

Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data.

BACKGROUND: Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fisher's exact tests to find GO terms which are over-represented amongst the genes declared to be differentially expressed in the analysis of the microarray experiment. However, due to the high degree of dependence between GO terms, statistical testing is conservative, and interpretation is difficult. RESULTS: We propose testing groups of GO terms rather than individual terms, to increase statistical power, reduce dependence between tests and improve the interpretation of results. We use the publicly available package POSOC to group the terms. Our method finds groups of GO terms significantly over-represented amongst differentially expressed genes which are not found by Fisher's tests on individual GO terms. CONCLUSION: Grouping Gene Ontology terms improves the interpretation of gene set enrichment for microarray data.

The effects of soil horizons and faunal excrement on bacterial distribution in an upland grassland soil.

The density and spatial location of bacteria were investigated within different horizons of an upland grassland soil before and after a liming treatment to increase the numbers of large soil fauna. Bacterial cells were located by image analysis of stained thin sections and densities calculated from these data. Excrement from macro- and meso-fauna was identified using micromorphology and the densities of bacteria on specific areas of excrement measured by image analysis. There were significant differences among horizons in the density of bacterial cells, with the minimum density found in the horizon with least evidence of earthworm activity, but no difference in density between the organic H and organo-mineral Ah horizons. Soil improvement by liming significantly increased bacterial densities in all three horizons, with the greatest increase found in the horizon with the smallest density before liming. There were no differences in bacterial density between areas dominated by excrement from earthworms and excrement from enchytraeids, although densities in both areas were significantly increased by liming. Variability in bacterial density at spatial scales of less than 1 mm was linked to the occurrence of excrement. Bacterial densities within areas of both types of excrement were significantly greater than those in the surrounding soil. However, the frequency distribution of the ratios of density in excrement to that in the soil was bimodal, with a majority of occurrences having a ratio near 1 and only some 20-30% having a much larger ratio. These variations can probably be explained by variations in the age of the excrement and its suitability as a substrate.

Determination of rhizosphere 13C pulse signals in soil thin sections by laser ablation isotope ratio mass spectrometry.

In grassland ecosystems, soil animals act as key soil engineers and architects. The diversity of soil animals is also a regulator of ecosystem carbon flow. However, our understanding of the link between soil animals, carbon fluxes and soil physical organisation remains poor. An integrated approach based on soil micromorphology and laser ablation stable isotope ratio mass spectrometry (LA-IRMS) was developed to provide spatially distributed data of pulse-derived (13)C tracer from roots in the soil environment. This paper describes the development and testing of a LA-IRMS (13)C/(12)C analytical method on soil thin sections as a means to determine the fate of root carbon derived from photosynthesis into soil. Results from this work demonstrated (1) that micro-scale delta(13)C (per thousand) analysis could be made on targeted features located within a soil thin section and (2) that LA-IRMS delta(13)C (per thousand) measurements made on samples obtained from (13)CO(2) pulse labelled plant-soil blocks confirmed the presence of recent photosynthates in the rhizosphere (1 and 4 weeks post-pulse).