One New Species and One New Combination in \u3ci\u3eNetechma\u3c/i\u3e Razowski (Lepidoptera: Tortricidae: Euliini)

Netechma similis, new species, from Costa Rica, is described and illustrated, and Netechma caesiata (Clarke), new combination, from Venezuela, is redescribed and illustrated. Netechma Razowski belongs to a group of genera in Euliini characterized by one or more sparganothine-like features of the male genitalia, including a spiny transtilla; a long, slender, hooklike uncus; and densely scaled socii. Adults of the two treated species are superficially most similar to species of Icteralaria Razowski, with a forewing that features a broad, dark, medial band on a pale yellow ground color

Catalog of the type specimens of Gelechioidea (Lepidoptera) in the collection of the National Museum of Natural History, Smithsonian Institution, Washington, DC

The collection of the National Museum of Natural History, Smithsonian Institution, Washington, D.C., is second only to that of The Natural History Museum (formerly British Museum of Natural History), London, in the number of type specimens of the superfamily Gelechioidea (Lepidoptera). The Smithsonian houses 1,375 gelechioid types: 1,249 holotypes, 48 lectotypes, 1 neotype, 69 species represented by one or more syntypes, and 8 species represented by one or more pseudotypes (Le., specimens identified as type by an accompanying label that are unlikely to be the type). Three former curators are responsible for the vast majority of the type specimens: August Busck, ]. F. Gates Clarke, and Ronald W. Hodges. We present a list of the species for which a type is deposited in the USNM, organized alphabetically. For each species we provide an abbreviated reference to the original description and label data. This list represents the second contribution to a larger effort to make available information on the Lepidoptera type holdings of the USNM

An expressed sequence tag (EST) library for Drosophila serrata, a model system for sexual selection and climatic adaptation studies

The native Australian fly Drosophila serrata belongs to the highly speciose montium subgroup of the melanogaster species group. It has recently emerged as an excellent model system with which to address a number of important questions, including the evolution of traits under sexual selection and traits involved in climatic adaptation along latitudinal gradients. Understanding the molecular genetic basis of such traits has been limited by a lack of genomic resources for this species. Here, we present the first expressed sequence tag (EST) collection for D. serrata that will enable the identification of genes underlying sexually-selected phenotypes and physiological responses to environmental change and may help resolve controversial phylogenetic relationships within the montium subgroup

Increased amino acids levels and the risk of developing of hypertriglyceridemia in a 7-year follow-up

BACKGROUND: Recently, five branched-chain and aromatic amino acids were shown to be associated with the risk of developing type 2 diabetes (T2D). AIM: We set out to examine whether amino acids are also associated with the development of hypertriglyceridemia. MATERIALS AND METHODS: We determined the serum amino acids concentrations of 1,125 individuals of the KORA S4 baseline study, for which follow-up data were available also at the KORA F4 7 years later. After exclusion for hypertriglyceridemia (defined as having a fasting triglyceride level above 1.70 mmol/L) and diabetes at baseline, 755 subjects remained for analyses. RESULTS: Increased levels of leucine, arginine, valine, proline, phenylalanine, isoleucine and lysine were significantly associated with an increased risk of hypertriglyceridemia. These associations remained significant when restricting to those individuals who did not develop T2D in the 7-year follow-up. The increase per standard deviation of amino acid level was between 26 and 40 %. CONCLUSIONS: Seven amino acids were associated with an increased risk of developing hypertriglyceridemia after 7 years. Further studies are necessary to elucidate the complex role of these amino acids in the pathogenesis of metabolic disorders

Measurements, Models, Systems and Design

531 s.

Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers

Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8 x 10(-4); Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8 x 10(-10); Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation

A reference map of potential determinants for the human serum metabolome

The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment(1). The origins of specific compounds are known, including metabolites that are highly heritable(2,3), or those that are influenced by the gut microbiome(4), by lifestyle choices such as smoking(5), or by diet(6). However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites-in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts(7,8) that were not available to us when we trained the algorithms. We used feature attribution analysis(9) to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.The levels of 1,251 metabolites are measured in 475 phenotyped individuals, and machine-learning algorithms reveal that diet and the microbiome are the determinants with the strongest predictive power for the levels of these metabolites

A roadmap for gene functional characterisation in wheat

To adapt to the challenges of climate change and the growing world population, it is vital to increase global crop production. Understanding the function of genes within staple crops will accelerate crop improvement by allowing targeted breeding approaches. Despite the importance of wheat, which provides 20 % of the calories consumed by humankind, a lack of genomic information and resources has hindered the functional characterisation of genes in this species. The recent release of a high-quality reference sequence for wheat underpins a suite of genetic and genomic resources that support basic research and breeding. These include accurate gene model annotations, gene expression atlases and gene networks that provide background information about putative gene function. In parallel, sequenced mutation populations, improved transformation protocols and structured natural populations provide rapid methods to study gene function directly. We highlight a case study exemplifying how to integrate these resources to study gene function in wheat and thereby accelerate improvement in this important crop. We hope that this review provides a helpful guide for plant scientists, especially those expanding into wheat research for the first time, to capitalise on the discoveries made in Arabidopsis and other plants. This will accelerate the improvement of wheat, a complex polyploid crop, of vital importance for food and nutrition security