Biology subjects

Andrew, R.

Publications and source records attributed to Andrew, R..

7 recordsLinked to original sources

bioRxiv2023

Plant genome evolution in the genus Eucalyptus driven by structural rearrangements that promote sequence divergence

Genomes have a highly organised architecture (non-random organisation of functional and non-functional genetic elements within chromosomes) that is essential for many biological functions, particularly, gene expression and reproduction. Despite the need to conserve genome architecture, a surprisingly high level of structural variation has been observed within species. As species separate and diverge, genome architecture also diverges, becoming increasingly poorly conserved as divergence time increases. However, within plant genomes, the processes of genome architecture divergence are not well described. Here we use long-read sequencing and de novo assembly of 33 phylogenetically diverse, wild and naturally evolving Eucalyptus species, covering 1-50 million years of diverging genome evolution to measure genome architectural conservation and describe architectural divergence. The investigation of these genomes revealed that following lineage divergence genome architecture is highly fragmented by rearrangements. As genomes continue to diverge, the accumulation of mutations and subsequent divergence beyond recognition of rearrangements becomes the primary driver of genome divergence. The loss of syntenic regions also contribute to genome divergence, but at a slower pace than rearrangements. We hypothesise that duplications and translocations are potentially the greatest contributors to Eucalyptus genome divergence.

genomics↗

bioRxiv2023

Re-analysis of lipidomic data reveals Specialised Pro-Resolution Lipid Mediators (SPMs) to be lower than quantifiable limits of assay in a human model of resolving inflammation.

Using a model of UV-killed E. coli driven dermal inflammation in healthy human volunteers we originally reported that following inflammatory resolution there was the infiltration of macrophages, which, through prostanoids including prostaglandin (PG)E2, imprints long-term tissue immunity. In addition to the prostanoids, we also presented data on levels of Specialised Pro-Resolution Lipid Mediators (SPMs) throughout inflammatory onset, resolution and post-resolution phases of this model. However, our collaborators who carried out the lipidomic analysis received a complaint concerning how they generally present SPM data in their publications, namely their use of graphical illustrations to depict data. Importantly, such lipidomic illustrations were used in our human UV-killed E. coli study. Therefore, in the interest of transparency and to replace these illustrations with more meaningful images, the original data from our human UV-killed E. coli model were re-analysed by two independent experts. It transpires that the integrated areas of the chromatographic peaks of the SPM lipid mediators were below the amounts that could be reliably either detected and/or quantified using community standards for quantitation. Here we show the outcome of this reanalysis. Importantly, with prostanoids including PGE2 being robustly detected, this re-analysis does not alter the original report that post-resolution PGs imprint tissue immunity.

immunology↗

bioRxiv2023

Gene networks driven by genetic variation for plasma cortisol in hepatic and adipose tissues implicate corticosteroid binding globulin in modulating tissue glucocorticoid action and cardiovascular risk

Genome wide association meta-analyses (GWAMA) by the CORtisol NETwork (CORNET) consortium identified genetic variants spanning the SERPINA6/ SERPINA1 locus on chromosome 14 associated with morning plasma cortisol, cardiovascular disease (CVD), and SERPINA6 mRNA expression encoding corticosteroid binding globulin (CBG) in liver. These and other findings indicate that higher plasma cortisol levels are causally associated with cardiovascular disease, however, the mechanisms by which variations in CBG lead to CVD are undetermined. Using genomic and transcriptomic data from The Stockholm Tartu Atherosclerosis Reverse Networks Engineering Task (STARNET) study, we identified plasma cortisol linked Single Nucleotide Polymorphisms (SNPs) that are trans-associated with genes from 7 different vascular and metabolic tissues, finding the highest representation of transgenes in liver, subcutaneous adipose and visceral abdominal adipose tissue (FDR = 15%). We identified a sub-set of cortisol-associated trans-genes that are putatively regulated by the Glucocorticoid Receptor (GR), the primary transcription factor activated by cortisol. Using causal inference, we identified GR-regulated trans-genes that are responsible for the regulation of tissue specific gene networks. Cis-expression Quantitative Trait Loci (eQTLs) were used as genetic instruments for identification of pairwise causal relationships from which gene networks could be reconstructed. Gene networks were identified in liver, subcutaneous fat and visceral abdominal fat, including a high confidence gene network specific to subcutaneous adipose (FDR = 10%) under the regulation of the interferon regulatory transcription factor, IRF2. These data identify a plausible pathway through which variation in liver CBG production perturbs cortisol-regulated gene networks in peripheral tissues and thereby promote CVD.

genetics↗

bioRxiv2022

Evolutionary survival strategies of the female giant panda: optimizing energy resources and expenditure prior to pregnancy by postponing corpus luteum reactivation

The giant panda reproductive physiology shows important similarities with at least six of the eight existing bear species: the occurrence of diapause and/or pseudopregnancy is commonly described in bears. Nevertheless, significant differences including the earlier breeding season with - in general - a single estrus, a shorter delay of implantation and a more variable birth season, indicate an evolutionary adaptation from the seasonal reproductive traits described in hibernating bear species. In this study we aimed to determine true pregnancy length for giant pandas and to open the discussion on the peculiarities of giant panda reproductive biology, more specifically focusing on the rationale behind their short-seasoned reproductive cycle compared to the other bear species. For this purpose, metabolic (body weight and fecal output) profiles were matched with endocrine changes, mainly urinary progesterone metabolites, in 5 pregnant, 8 non-birth and 6 pseudopregnant cycles of 6 female giant pandas. Pregnancy in giant pandas lasts only 42 days from early reactivation of the corpora lutea (CLs) until birth. In addition, our findings urged the need to redefine the generally accepted biphasic progesterone profile into a triphasic primary progesterone rise (corpus luteum dormancy (CLD) I, II and III) prior to entering the active luteal phase (= secondary progesterone rise). Two episodes of progesterone increase (CLDII: 81.20 {+/-} 5.85 days versus CLDIII: 60.80 {+/-} 3.83 days prior to birth for pregnant cycles) were identified, respectively corresponding to CL reactivation (74-88 days prior to birth) and implantation ({+/-} 60 days prior to birth) in other bear species. The progesterone concentration during CLDIII was higher in pregnant cycles, indicating a potential communication between maternal tissues and blastocyst(s) enhancing progesterone concentrations and thus allowing optimal priming of uterine tissues to better prepare for blastocyst reactivation/development. Compared with other bear species, giant pandas seem to shorten the active luteal phase, and thus pregnancy, by approximately 30 days by actively postponing CL reactivation. Potential mechanisms in play overruling and suppressing the evolutionary conserved photoperiodical triggers of CL reactivation are discussed while a parallel study will further elaborate on the CL dynamics during giant panda gestation.

evolutionary biology↗

bioRxiv2022

Increased adipose tissue indices of androgen catabolism and aromatization in women with metabolic dysfunction

BackgroundBody fat distribution is a risk factor for obesity-associated comorbidities, and adipose tissue dysfunction plays a role in this association. In humans, there is a sex difference in body fat distribution, and steroid hormones are known to regulate several cellular processes within adipose tissue. Our aim was to investigate if intra-adipose steroid concentration and expression or activity of steroidogenic enzymes were associated with features of adipose tissue dysfunction in individuals with severe obesity. MethodsSamples from 40 bariatric candidates (31 women, 9 men) were included in the study. Visceral (VAT) and subcutaneous adipose tissue (SAT) were collected during surgery. Adipose tissue morphology was measured by a combination of histological staining and semi-automated quantification. Following extraction, intra-adipose and plasma steroid concentrations were determined by liquid chromatography, electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS). Aromatase activity was estimated using product-over-substrate ratio, while AKR1C2 activity was measured directly by fluorogenic probe. Gene expression was measured by quantitative PCR. ResultsVAT aromatase activity was positively associated with VAT adipocyte hypertrophy (p-valueadj < 0.01) and negatively with plasma HDL-cholesterol (p-valueadj < 0.01), while SAT aromatase activity predicted dyslipidemia in women even after adjustment for waist circumference, age and hormonal contraceptive use. We additionally compared women with high and low visceral adiposity index (VAI) and found that VAT excess is characterized by adipose tissue dysfunction, increased androgen catabolism mirrored by increased AKR1C2 activity and higher aromatase expression and activity indices. ConclusionIn women, increased androgen catabolism or aromatization is associated with visceral adiposity and adipose tissue dysfunction. DISCLOSURE SUMMARYAT obtained consulting fees form Bausch Health, Novo Nordisk and research funding from Johnson & Johnson Medical Companies as well as Medtronic and GI Windows for studies unrelated to this manuscript. The other authors have nothing to disclose.

physiology↗

bioRxiv2021

11β-HSD1 inhibition does not affect murine tumour angiogenesis but may exert a selective effect on tumour growth by modulating inflammation and fibrosis

Glucocorticoids inhibit angiogenesis by activating the glucocorticoid receptor. Inhibition of the glucocorticoid-activating enzyme 11{beta}-hydroxysteroid dehydrogenase type 1 (11{beta}-HSD1) reduces tissue-specific glucocorticoid action and promotes angiogenesis in murine models of myocardial infarction. Angiogenesis is important in the growth of some solid tumours. This study used murine models of squamous cell carcinoma (SCC) and pancreatic ductal adenocarcinoma (PDAC) to test the hypothesis that 11{beta}-HSD1 inhibition promotes angiogenesis and subsequent tumour growth. SCC or PDAC cells were injected into female FVB/N or C57BL6/J mice fed either standard diet, or diet containing the 11{beta}-HSD1 inhibitor UE2316. SCC tumours grew more rapidly in UE2316-treated mice, reaching a larger (P<0.01) final volume (0.158 {+/-} 0.037 cm3) than in control mice (0.051 {+/-} 0.007 cm3). However, PDAC tumour growth was unaffected. Immunofluorescent analysis of SCC tumours did not show differences in vessel density (CD31/alpha-smooth muscle actin) or cell proliferation (Ki67) after 11{beta}-HSD1 inhibition, and immunohistochemistry of SCC tumours did not show changes in inflammatory cell (CD3- or F4/80-positive) infiltration. In culture, the growth/viability (assessed by live cell imaging) of SCC cells was not affected by UE2316 or corticosterone. Second Harmonic Generation microscopy showed that UE2316 reduced Type I collagen (P<0.001), whilst RNA-sequencing revealed that multiple factors involved in the innate immune/inflammatory response were reduced in UE2316-treated SCC tumours. 11{beta}-HSD1 inhibition increases SCC tumour growth, likely via suppression of inflammatory/immune cell signalling and extracellular matrix deposition, but does not promote tumour angiogenesis or growth of all solid tumours.

cancer biology↗

bioRxiv2020

Regarding the F-word: the effects of data Filtering on inferred genotype-environment associations

Genotype-environment association (GEA) methods have become part of the standard landscape genomics toolkit, yet, we know little about how to filter genotype-by-sequencing data to provide robust inferences for environmental adaptation. In many cases, default filtering thresholds for minor allele frequency and missing data are applied regardless of sample size, having unknown impacts on the results. These effects could be amplified in downstream predictions, including management strategies. Here, we investigate the effects of filtering on GEA results and the potential implications for adaptation to environment. Using empirical and simulated datasets derived from two widespread tree species to assess the effects of filtering on GEA outputs. Critically, we find that the level of filtering of missing data and minor allele frequency affect the identification of true positives. Even slight adjustments to these thresholds can change the rate of true positive detection. Using conservative thresholds for missing data and minor allele frequency substantially reduces the size of the dataset, lessening the power to detect adaptive variants (i.e. simulated true positives) with strong and weak strength of selections. Regardless, strength of selection was a good predictor for GEA detection, but even SNPs under strong selection went undetected. We further show that filtering can significantly impact the predictions of adaptive capacity of species in downstream analyses. We make several recommendations regarding filtering for GEA methods. Ultimately, there is no filtering panacea, but some choices are better than others, depending largely on the study system, availability of genomic resources, and desired objectives of the study.

genomics↗