Identification of Medically Actionable Secondary Findings in the 1000 Genomes

The American College of Medical Genetics and Genomics (ACMG) recommends that clinical sequencing laboratories return secondary findings in 56 genes associated with medically actionable conditions. Our goal was to apply a systematic, stringent approach consistent with clinical standards to estimate the prevalence of pathogenic variants associated with such conditions using a diverse sequencing reference sample. Candidate variants in the 56 ACMG genes were selected from Phase 1 of the 1000 Genomes dataset, which contains sequencing information on 1,092 unrelated individuals from across the world. These variants were filtered using the Human Gene Mutation Database (HGMD) Professional version and defined parameters, appraised through literature review, and examined by a clinical laboratory specialist and expert physician. Over 70,000 genetic variants were extracted from the 56 genes, and filtering identified 237 variants annotated as disease causing by HGMD Professional. Literature review and expert evaluation determined that 7 of these variants were pathogenic or likely pathogenic. Furthermore, 5 additional truncating variants not listed as disease causing in HGMD Professional were identified as likely pathogenic. These 12 secondary findings are associated with diseases that could inform medical follow-up, including cancer predisposition syndromes, cardiac conditions, and familial hypercholesterolemia. The majority of the identified medically actionable findings were in individuals from the European (5/379) and Americas (4/181) ancestry groups, with fewer findings in Asian (2/286) and African (1/246) ancestry groups. Our results suggest that medically relevant secondary findings can be identified in approximately 1% (12/1092) of individuals in a diverse reference sample. As clinical sequencing laboratories continue to implement the ACMG recommendations, our results highlight that at least a small number of potentially important secondary findings can be selected for return. Our results also confirm that understudied populations will not reap proportionate benefits of genomic medicine, highlighting the need for continued research efforts on genetic diseases in these populations.     

野大豆(Glycine soja)叶绿体的光谱及其激子能量转移

野大豆叶绿体在低温(77K)时出现三条荧光发射谱带,它们来源于不同的色素蛋白复合体。 在纳秒脉冲激光激发下,捕光天线色素的相对荧光量子产额,随激光强度的增加有明显下降现象。用激子理论和动力学方程讨论和计算了激子扩散参量。指出激子转移是随机的,非相干的。     

Methods for rapid screening and isolation of bacteria producing acidic lipase: feasibility studies and novel activity assay protocols

Acidic lipase finds its commercial values in medical applications and bioremediation of food wastes. In this work, approaches for rapid screening of lipase-producing bacteria were developed and the feasibility assessment of the screening methods was performed. From food waste samples, the proposed screening procedures allowed isolation of sixteen pure bacterial strains expressing higher lipase activity at acidic pH (pH 6.0) than at alkaline pH (pH 9.0). To enhance the accuracy of lipase activity determination under acidic conditions, a novel assay procedure was also developed by deactivating lipase activity by microwave treatment prior to back titration. This additional step could minimize interferences arising from residual lipase activity during conventional direct back-titration methods in measuring lipase activity at acidic pH. Using the four strategies proposed in this work, the best acidic-lipase-producing isolate was obtained by strategy C (SSC) and was identified as Aeromonas sp. C14, displaying an optimal lipase activity of 0.7 U/ml at an acidic pH of 6.0.     

Motor-Substrate Interactions in Mycoplasma Motility Explains Non-Arrhenius Temperature Dependence

Mycoplasmas exhibit a novel, substrate-dependent gliding motility that is driven by ∼400 “leg” proteins. The legs interact with the substrate and transmit the forces generated by an assembly of ATPase motors. The velocity of the cell increases linearly by nearly 10-fold over a narrow temperature range of 10-40°C. This corresponds to an Arrhenius factor that decreases from ∼45 k_BT at 10°C to ∼10 k_BT at 40°C. On the other hand, load-velocity curves at different temperatures extrapolate to nearly the same stall force, suggesting a temperature-insensitive force-generation mechanism near stall. In this article, we propose a leg-substrate interaction mechanism that explains the intriguing temperature sensitivity of this motility. The large Arrhenius factor at low temperature comes about from the addition of many smaller energy barriers arising from many substrate-binding sites at the distal end of the leg protein. The Arrhenius dependence attenuates at high temperature due to two factors: 1), the reduced effective multiplicity of energy barriers intrinsic to the multiple-site binding mechanism; and 2), the temperature-sensitive weakly facilitated leg release that curtails the power stroke. The model suggests an explanation for the similar steep, sub-Arrhenius temperature-velocity curves observed in many molecular motors, such as kinesin and myosin, wherein the temperature behavior is dominated not by the catalytic biochemistry, but by the motor-substrate interaction.     

Genetic diversity and population structure of Swertia tetraptera (Gentianaceae), an endemic species of Qinghai-Tibetan Plateau

Swertia tetraptera Maxim is an annual alpine herb endemic to the Qinghai-Tibetan Plateau (QTP). Its populations are locally scattered as isolated patches throughout this region. Genetic variation within and among thirty-four populations of this species was assessed using ISSR fingerprinting with 10 primers. High levels of genetic diversity exist within species (P = 98.9%, I = 0.3475; He = 0.2227), while the within-population diversity is low (P = 32.7%, I = 0.177; He = 0.12). High levels of genetic differentiation were detected among populations based on various statistics, including Nei’s genetic diversity analysis (G_ST = 0.4608), Bayesian analysis (θ^B = 0.476) and AMOVA (F_ST = 0.57). That is, populations shared low levels of genetic identity (I = 0.2622–0.0966). This genetic structure was probably due to severe genetic drift, breeding system and limited gene flow. The observed genetic structure of the populations implies that different populations across the distribution range of the species should be sampled to maintain high genetic diversity when a conservation strategy is implemented.     

The physical mapping of bacteriophage T5 transfer tRNAs.

Transfer RNAs, isolated from Escherichia coli F cells infected with T5 bacteriophage, were charged with radioactive amino acids and used in RNA-DNA hybridization studies to detect and locate T5 tRNA cistrons in the T5 DNA chromosome. Hybridization of 14 3H-aminoacyl-tRNA species, including purified T5 [35S]Met-tRNAm and [35S]Met-tRNAf, to the separated strands of T5+ DNA indicates that most, if not all, of the T5 tRNAs are transcribed from the continuous heavy strand of T5 DNA. Heteroduplex mapping of eight mutant T5 DNA deletions has enabled us to locate and determine the size of these deleted segments. By correlating this information with the presence and absence of specific tDNA sequences in these mutants, as determined by tRNA-DNA hybridization, we were able to define the physical limits of four tDNA-containing loci along the T5 DNA molecule. A physical map for 15 tRNA species examined indicates that the structural genes for these tRNAs are clustered within a segment length of T5 DNA that represents approximately 11.2% of the total wild type T5 DNA. The existence of the deletion mutants indicates that T5 tRNAs are dispensable for T5 replication under the growth conditions and for the host employed.     

Predicting Metabolic Pathways of Small Molecules and Enzymes Based on Interaction Information of Chemicals and Proteins

Metabolic pathway analysis, one of the most important fields in biochemistry, is pivotal to understanding the maintenance and modulation of the functions of an organism. Good comprehension of metabolic pathways is critical to understanding the mechanisms of some fundamental biological processes. Given a small molecule or an enzyme, how may one identify the metabolic pathways in which it may participate? Answering such a question is a first important step in understanding a metabolic pathway system. By utilizing the information provided by chemical-chemical interactions, chemical-protein interactions, and protein-protein interactions, a novel method was proposed by which to allocate small molecules and enzymes to 11 major classes of metabolic pathways. A benchmark dataset consisting of 3,348 small molecules and 654 enzymes of yeast was constructed to test the method. It was observed that the first order prediction accuracy evaluated by the jackknife test was 79.56% in identifying the small molecules and enzymes in a benchmark dataset. Our method may become a useful vehicle in predicting the metabolic pathways of small molecules and enzymes, providing a basis for some further analysis of the pathway systems.