Bias and Sampling Error of the Estimated Proportion of Genotypic Variance Explained by Quantitative Trait Loci Determined From Experimental Data in Maize Using Cross Validation and Validation With Independent Samples.

Cross validation (CV) was used to analyze the effects of different environments and different genotypic samples on estimates of the proportion of genotypic variance explained by QTL (p). Testcrosses of 344 F(3) maize lines grown in four environments were evaluated for a number of agronomic traits. In each of 200 replicated CV runs, this data set was subdivided into an estimation set (ES) and various test sets (TS). ES were used to map QTL and estimate p for each run (p(ES)) and its median (p(ES)) across all runs. The bias of these estimates was assessed by comparison with the median (p(TS.ES)) obtained from TS. We also used two independent validation samples derived from the same cross for further comparison. The median p(ES) showed a large upward bias compared to p(TS.ES). Environmental sampling generally had a smaller effect on the bias of p(ES) than genotypic sampling or both factors simultaneously. In independent validation, p(TS.ES) was on average only 50% of p(ES). A wide range among p(ES) reflected a large sampling error of these estimates. QTL frequency distributions and comparison of estimated QTL effects indicated a low precision of QTL localization and an upward bias in the absolute values of estimated QTL effects from ES. CV with data from three QTL studies reported in the literature yielded similar results as those obtained with maize testcrosses. We therefore recommend CV for obtaining asymptotically unbiased estimates of p and consequently a realistic assessment of the prospects of MAS.     

Serum netrin and VCAM-1 as biomarker for Egyptian patients with type IΙ diabetes mellitus

ObjectiveThis study aimed to evaluate the serum level of netrin and soluble vascular cell adhesion molecule 1 (VCAM-I) in patients with type IΙ diabetes mellitus (T2DM) and evaluate the association of their levels with the development of a diabetic complication.Patients and methodsThis study was carried out on type II diabetic patients with and without complications and healthy individuals served as controls. All subjects were submitted to the estimation of serum lipid profile, serum creatinine, urinary albumin/creatinine ratio (ACR), fasting blood glucose (FBG), glycated hemoglobin (HbA1c), visceral adiposity index (VAI), atherogenic index of plasma (AIP), lipid accumulation product (LAP) and detection of serum level of netrin1 and VCAM1.ResultsDiabetic patients with complications had significantly higher serum levels of creatinine, ACR, cholesterol, Triglyceride, low-density lipoprotein, netrin1, and VCAM1 than diabetic patients without complications. Likewise, the level of VAI and LAP as markers of excessive body fat were significantly higher in diabetic patients with complications than diabetic patients without complications. The netrin1 and VCAM1 were a significant discriminator of T2DM renal complications with a sensitivity of 96%, 90%, and specificity of 82.7%, 91.3% respectively.ConclusionIt can be concluded that serum netrin1 and VCAM1 correlated significantly with markers of excessive body fat, a renal complication in the patient with type 2 diabetes mellitus.     

An integrative study of a meromictic lake ecosystem in Antarctica

In nature, the complexity and structure of microbial communities varies widely, ranging from a few species to thousands of species, and from highly structured to highly unstructured communities. Here, we describe the identity and functional capacity of microbial populations within distinct layers of a pristine, marine-derived, meromictic (stratified) lake (Ace Lake) in Antarctica. Nine million open reading frames were analyzed, representing microbial samples taken from six depths of the lake size fractionated on sequential 3.0, 0.8 and 0.1 μm filters, and including metaproteome data from matching 0.1 μm filters. We determine how the interactions of members of this highly structured and moderately complex community define the biogeochemical fluxes throughout the entire lake. Our view is that the health of this delicate ecosystem is dictated by the effects of the polar light cycle on the dominant role of green sulfur bacteria in primary production and nutrient cycling, and the influence of viruses/phage and phage resistance on the cooperation between members of the microbial community right throughout the lake. To test our assertions, and develop a framework applicable to other microbially driven ecosystems, we developed a mathematical model that describes how cooperation within a microbial system is impacted by periodic fluctuations in environmental parameters on key populations of microorganisms. Our study reveals a mutualistic structure within the microbial community throughout the lake that has arisen as the result of mechanistic interactions between the physico-chemical parameters and the selection of individual members of the community. By exhaustively describing and modelling interactions in Ace Lake, we have developed an approach that may be applicable to learning how environmental perturbations affect the microbial dynamics in more complex aquatic systems.     

Avidin related protein 2 shows unique structural and functional features among the avidin protein family

Background  

The chicken avidin gene family consists of avidin and several avidin related genes (AVRs). Of these gene products, avidin is the best characterized and is known for its extremely high affinity for D-biotin, a property that is utilized in numerous modern life science applications. Recently, the AVR genes have been expressed as recombinant proteins, which have shown different biotin-binding properties as compared to avidin.