67 research outputs found

    Insights into the Development and Evolution of Exaggerated Traits Using \u3ci\u3e De Novo \u3c/i\u3e Transcriptomes of Two Species of Horned Scarab Beetles

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    Scarab beetles exhibit an astonishing variety of rigid exo-skeletal outgrowths, known as ‘‘horns’’. These traits are often sexually dimorphic and vary dramatically across species in size, shape, location, and allometry with body size. In many species, the horn exhibits disproportionate growth resulting in an exaggerated allometric relationship with body size, as compared to other traits, such as wings, that grow proportionately with body size. Depending on the species, the smallest males either do not produce a horn at all, or they produce a disproportionately small horn for their body size. While the diversity of horn shapes and their behavioural ecology have been reasonably well studied, we know far less about the proximate mechanisms that regulate horn growth. Thus, using 454 pyrosequencing, we generated transcriptome profiles, during horn growth and development, in two different scarab beetle species: the Asian rhinoceros beetle, Trypoxylus dichotomus, and the dung beetle, Onthophagus nigriventris. We obtained over half a million reads for each species that were assembled into over 6,000 and 16,000 contigs respectively. We combined these data with previously published studies to look for signatures of molecular evolution. We found a small subset of genes with horn-biased expression showing evidence for recent positive selection, as is expected with sexual selection on horn size. We also found evidence of relaxed selection present in genes that demonstrated biased expression between horned and horn-less morphs, consistent with the theory of developmental decoupling of phenotypically plastic traits

    Gene Discovery in the Threatened Elkhorn Coral: 454 Sequencing of the Acropora palmata Transcriptome

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    BACKGROUND: Cnidarians, including corals and anemones, offer unique insights into metazoan evolution because they harbor genetic similarities with vertebrates beyond that found in model invertebrates and retain genes known only from non-metazoans. Cataloging genes expressed in Acropora palmata, a foundation-species of reefs in the Caribbean and western Atlantic, will advance our understanding of the genetic basis of ecologically important traits in corals and comes at a time when sequencing efforts in other cnidarians allow for multi-species comparisons. RESULTS: A cDNA library from a sample enriched for symbiont free larval tissue was sequenced on the 454 GS-FLX platform. Over 960,000 reads were obtained and assembled into 42,630 contigs. Annotation data was acquired for 57% of the assembled sequences. Analysis of the assembled sequences indicated that 83-100% of all A. palmata transcripts were tagged, and provided a rough estimate of the total number genes expressed in our samples (~18,000-20,000). The coral annotation data contained many of the same molecular components as in the Bilateria, particularly in pathways associated with oxidative stress and DNA damage repair, and provided evidence that homologs of p53, a key player in DNA repair pathways, has experienced selection along the branch separating Cnidaria and Bilateria. Transcriptome wide screens of paralog groups and transition/transversion ratios highlighted genes including: green fluorescent proteins, carbonic anhydrase, and oxidative stress proteins; and functional groups involved in protein and nucleic acid metabolism, and the formation of structural molecules. These results provide a starting point for study of adaptive evolution in corals. CONCLUSIONS: Currently available transcriptome data now make comparative studies of the mechanisms underlying coral's evolutionary success possible. Here we identified candidate genes that enable corals to maintain genomic integrity despite considerable exposure to genotoxic stress over long life spans, and showed conservation of important physiological pathways between corals and bilaterians

    Effect of the down-regulation of the high Grain Protein Content (GPC) genes on the wheat transcriptome during monocarpic senescence

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    <p>Abstract</p> <p>Background</p> <p>Increasing the nutrient concentration of wheat grains is important to ameliorate nutritional deficiencies in many parts of the world. Proteins and nutrients in the wheat grain are largely derived from the remobilization of degraded leaf molecules during monocarpic senescence. The down-regulation of the NAC transcription factor <it>Grain Protein Content </it>(<it>GPC</it>) in transgenic wheat plants delays senescence (>3 weeks) and reduces the concentration of protein, Zn and Fe in the grain (>30%), linking senescence and nutrient remobilization.</p> <p>Based on the early and rapid up-regulation of <it>GPC </it>in wheat flag leaves after anthesis, we hypothesized that this transcription factor is an early regulator of monocarpic senescence. To test this hypothesis, we used high-throughput mRNA-seq technologies to characterize the effect of the <it>GPC </it>down-regulation on the wheat flag-leaf transcriptome 12 days after anthesis. At this early stage of senescence <it>GPC </it>transcript levels are significantly lower in transgenic GPC-RNAi plants than in the wild type, but there are still no visible phenotypic differences between genotypes.</p> <p>Results</p> <p>We generated 1.4 million 454 reads from early senescing flag leaves (average ~350 nt) and assembled 1.2 million into 30,497 contigs that were used as a reference to map 145 million Illumina reads from three wild type and four GPC-RNAi plants. Following normalization and statistical testing, we identified a set of 691 genes differentially regulated by <it>GPC </it>(431 ≥ 2-fold change). Transcript level ratios between transgenic and wild type plants showed a high correlation (<it>R </it>= 0.83) between qRT-PCR and Illumina results, providing independent validation of the mRNA-seq approach. A set of differentially expressed genes were analyzed across an early senescence time-course.</p> <p>Conclusions</p> <p>Monocarpic senescence is an active process characterized by large-scale changes in gene expression which begins considerably before the appearance of visual symptoms of senescence. The mRNA-seq approach used here was able to detect small differences in transcript levels during the early stages of senescence. This resulted in an extensive list of <it>GPC</it>-regulated genes, which includes transporters, hormone regulated genes, and transcription factors. These <it>GPC</it>-regulated genes, particularly those up-regulated during senescence, provide valuable entry points to dissect the early stages of monocarpic senescence and nutrient remobilization in wheat.</p

    Federated learning enables big data for rare cancer boundary detection.

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    Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

    Author Correction: Federated learning enables big data for rare cancer boundary detection.

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    10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

    Canagliflozin and renal outcomes in type 2 diabetes and nephropathy

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    BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to &lt;90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], &gt;300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of &lt;15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P&lt;0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P&lt;0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

    Federated Learning Enables Big Data for Rare Cancer Boundary Detection

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    Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

    A Strategy for High Throughput Microarray Oligo Probe Design Using 454 and Sanger Sequencing Data of \u3ci\u3eEisenia fetida\u3c/i\u3e Expressed Sequence Tags

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    High density oligonucleotide probe arrays have increasingly become an important tool in genomics studies. However, the lack of full genome sequences for many non-genomics model organisms has hampered researchers to pursue relevant ecological, toxicological, and other non-fundamental genomics questions. Historically, researchers have sequenced ESTs in the organism of interest prior to or in the absence of genome sequencing. Recent technological advances such as massively parallel pyrosequencing (454 sequencing) have provided ultra high throughput opportunities to sequence millions of bases in a few hours. Nevertheless, the sequence reads produced by the next generation sequencing technologies are relatively short and needs to be assembled into longer contigs, which created new challenges for probe design. Ideally, one oligo probe should target one unique gene or gene product (e.g., transcript). In the absence of genome sequence, one strategy is to target every unique transcript sequence while reduce the number of unique sequences (and costs of arrays) through bioinformatic analysis and experimental testing. Here we report a case study and demonstrate how this strategy was applied in the design of a transcriptome-wide oligo array for a non-gneomics model organisms Eisenia fetida

    Data from: Genetic variation in HIF signaling underlies quantitative variation in physiological and life history traits within lowland butterfly populations

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    Oxygen conductance to the tissues determines aerobic metabolic performance in most eukaryotes but has cost/benefit tradeoffs. Here we examine in lowland populations of a butterfly a genetic polymorphism affecting oxygen conductance via the hypoxia inducible factor (HIF) pathway, which senses intracellular oxygen and controls the development of oxygen delivery networks. Genetically distinct clades of Glanville fritillary (Melitaea cinxia) across a continental scale maintain, at intermediate frequencies, alleles in a metabolic enzyme (succinate dehydrogenase, SDH) that regulates hypoxia inducible factor (HIF-1α). One Sdhd allele was associated with reduced SDH activity rate, two-fold greater cross-sectional area of tracheoles in flight muscle, and better flight performance. Butterflies with less tracheal development had greater post-flight hypoxia signaling, swollen, disrupted mitochondria and accelerated aging of flight metabolic performance. Allelic associations with metabolic and aging phenotypes were replicated in samples from different clades. Experimentally elevated succinate in pupae increased the abundance of hypoxia inducible factor (HIF-1α) and expression of genes responsive to HIF activation, including tracheal morphogenesis genes. These results indicate that the hypoxia inducible pathway, even in lowland populations, can be an important axis for genetic variation underlying intraspecific differences in oxygen delivery, physiological performance and life history

    T. dichotomus: NCBI accession codes

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    Accession codes for the T. dichotomus bioproject, assembly, and raw reads
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