A novel strategy for sibship determination in trio sibling model

Aim To use a virtually simulated population, generated from published allele frequencies based on 15 short tandem repeats (STR), to evaluate the efficacy of trio sibship testing and sibling assignment for forensic purposes. Methods Virtual populations were generated using 15 STR loci to create a large number of related and unrelated genotypes (10 000 trio combinations). Using these virtual populations, the probability of related and unrelated profiles can be compared to determine the chance of inclusions of being siblings if they are true siblings and the chance of inclusion if they are unrelated. Two specific relationships were tested – two reference siblings were compared to a third true sibling (3S trio, sibling trio) and two reference siblings were compared to an unrelated individual (2S1U trio, non-sibling trio). Results When the likelihood ratio was greater than 1, 99.87% of siblings in the 3S trio population were considered as siblings (sensitivity); 99.88% of non-siblings in the 2S1U trio population were considered as non-siblings (specificity); 99.9% of both populations were identified correctly as siblings and non-siblings; and the accuracy of the test was 99.88%. Conclusions The high sensitivity and specificity figures when using two known siblings compared to a putative sibling are significantly greater than when using only one known relative. The data also support the use of increasing number of loci allowing for greater confidence in genetic identification. The system established in this study could be used as the model for evaluating and simulating the cases with multiple relatives

The risk of false inclusion of a relative in parentage testing – an in silico population study

Aim To investigate the potential of false inclusion of a close genetic relative in paternity testing by using computer generated families. Methods 10 000 computer-simulated families over three generations were generated based on genotypes using 15 short tandem repeat loci. These data were used in assessing the probability of inclusion or exclusion of paternity when the father is actually a sibling, grandparent, uncle, half sibling, cousin, or a random male. Further, we considered a duo case where the mother’s DNA type was not available and a trio case including the mother’s profile. Results The data showed that the duo scenario had the highest and lowest false inclusion rates when considering a sibling (19.03 ± 0.77%) and a cousin (0.51 ± 0.14%) as the father, respectively; and the rate when considering a random male was much lower (0.04 ± 0.04%). The situation altered slightly with a trio case where the highest rate (0.56 ± 0.15%) occurred when a paternal uncle was considered as the father, and the lowest rate (0.03 ± 0.03%) occurred when a cousin was considered as the father. We also report on the distribution of the numbers for non-conformity (non-matching loci) where the father is a close genetic relative. Conclusions The results highlight the risk of false inclusion in parentage testing. These data provide a valuable reference when incorporating either a mutation in the father’s DNA type or if a close relative is included as being the father; particularly when there are varying numbers of non-matching loci

A novel strategy for sibship determination in trio sibling model

Aim To use a virtually simulated population, generated from published allele frequencies based on 15 short tandem repeats (STR), to evaluate the efficacy of trio sibship testing and sibling assignment for forensic purposes. Methods Virtual populations were generated using 15 STR loci to create a large number of related and unrelated genotypes (10 000 trio combinations). Using these virtual populations, the probability of related and unrelated profiles can be compared to determine the chance of inclusions of being siblings if they are true siblings and the chance of inclusion if they are unrelated. Two specific relationships were tested – two reference siblings were compared to a third true sibling (3S trio, sibling trio) and two reference siblings were compared to an unrelated individual (2S1U trio, non-sibling trio). Results When the likelihood ratio was greater than 1, 99.87% of siblings in the 3S trio population were considered as siblings (sensitivity); 99.88% of non-siblings in the 2S1U trio population were considered as non-siblings (specificity); 99.9% of both populations were identified correctly as siblings and non-siblings; and the accuracy of the test was 99.88%. Conclusions The high sensitivity and specificity figures when using two known siblings compared to a putative sibling are significantly greater than when using only one known relative. The data also support the use of increasing number of loci allowing for greater confidence in genetic identification. The system established in this study could be used as the model for evaluating and simulating the cases with multiple relatives

The risk of false inclusion of a relative in parentage testing - an in silico population study FORENSIC SCIENCE

Aim To investigate the potential of false inclusion of a close genetic relative in paternity testing by using computer generated families. Methods 10 000 computer-simulated families over three generations were generated based on genotypes using 15 short tandem repeat loci. These data were used in assessing the probability of inclusion or exclusion of paternity when the father is actually a sibling, grandparent, uncle, half sibling, cousin, or a random male. Further, we considered a duo case where the mother's DNA type was not available and a trio case including the mother's profile. Results The data showed that the duo scenario had the highest and lowest false inclusion rates when considering a sibling (19.03 ± 0.77%) and a cousin (0.51 ± 0.14%) as the father, respectively; and the rate when considering a random male was much lower (0.04 ± 0.04%). The situation altered slightly with a trio case where the highest rate (0.56 ± 0.15%) occurred when a paternal uncle was considered as the father, and the lowest rate (0.03 ± 0.03%) occurred when a cousin was considered as the father. We also report on the distribution of the numbers for non-conformity (non-matching loci) where the father is a close genetic relative. Conclusions The results highlight the risk of false inclusion in parentage testing. These data provide a valuable reference when incorporating either a mutation in the father's DNA type or if a close relative is included as being the father; particularly when there are varying numbers of non-matching loci

When Cytokinin, a Plant Hormone, Meets the Adenosine A2A Receptor: A Novel Neuroprotectant and Lead for Treating Neurodegenerative Disorders?

It is well known that cytokinins are a class of phytohormones that promote cell division in plant roots and shoots. However, their targets, biological functions, and implications in mammalian systems have rarely been examined. In this study, we show that one cytokinin, zeatin riboside, can prevent pheochromocytoma (PC12) cells from serum deprivation-induced apoptosis by acting on the adenosine A2A receptor (A2A-R), which was blocked by an A2A-R antagonist and a protein kinase A (PKA) inhibitor, demonstrating the functional ability of zeatin riboside by mediating through A2A-R signaling event. Since the A2A-R was implicated as a therapeutic target in treating Huntington’s disease (HD), a cellular model of HD was applied by transfecting mutant huntingtin in PC12 cells. By using filter retardation assay and confocal microscopy we found that zeatin riboside reversed mutant huntingtin (Htt)-induced protein aggregations and proteasome deactivation through A2A-R signaling. PKA inhibitor blocked zeatin riboside-induced suppression of mutant Htt aggregations. In addition, PKA activated proteasome activity and reduced mutant Htt protein aggregations. However, a proteasome inhibitor blocked both zeatin riboside-and PKA activator-mediated suppression of mutant Htt aggregations, confirming mediation of the A2A-R/PKA/proteasome pathway. Taken together, zeatin riboside might have therapeutic potential as a novel neuroprotectant and a lead for treating neurodegenerative disorders

ULK1/2 Constitute a Bifurcate Node Controlling Glucose Metabolic Fluxes in Addition to Autophagy

揭示了在外界能量供应缺乏时，细胞通过激活ULK1来介导葡萄糖分解代谢重编程以维持胞内的能量与氧化还原稳态的详细机制，并创新地发现了ULK1独立于自噬的关键功能。基于自噬和糖代谢与人类健康的重要相关性，该研究将很可能为我们预防和治疗各类代谢疾病提供新的思路和药物靶点。Metabolic reprogramming is fundamental to biological homeostasis, enabling cells to adjust metabolic routes after sensing altered availability of fuels and growth factors. ULK1 and ULK2 represent key integrators that relay metabolic stress signals to the autophagy machinery. Here, we demonstrate that, during deprivation of amino acid and growth factors, ULK1/2 directly phosphorylate key glycolytic enzymes including hexokinase (HK), phosphofructokinase 1 (PFK1), enolase 1 (ENO1), and the gluconeogenic enzyme fructose-1,6-bisphosphatase (FBP1). Phosphorylation of these enzymes leads to enhanced HK activity to sustain glucose uptake but reduced activity of FBP1 to block the gluconeogenic route and reduced activity of PFK1 and ENO1 to moderate drop of glucose-6-phosphate and to repartition more carbon flux to pentose phosphate pathway (PPP), maintaining cellular energy and redox homeostasis at cellular and organismal levels. These results identify ULK1/2 as a bifurcate-signaling node that sustains glucose metabolic fluxes besides initiation of autophagy in response to nutritional deprivation.State Key Program of National Natural Science of China， the 973 Program；National Natural Science Foundation of China for Fostering Talents in Basic Research ；the Foundation for Innovative Research Groups of the National Natural Science Foundation of China； and the 111 Project of Education of China

Формирование эмоциональной культуры как компонента инновационной культуры студентов

Homozygosity has long been associated with rare, often devastating, Mendelian disorders1 and Darwin was one of the first to recognise that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity, ROH), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3,4. Here we use ROH to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts and find statistically significant associations between summed runs of homozygosity (SROH) and four complex traits: height, forced expiratory lung volume in 1 second (FEV1), general cognitive ability (g) and educational attainment (nominal p<1 × 10−300, 2.1 × 10−6, 2.5 × 10−10, 1.8 × 10−10). In each case increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing convincing evidence for the first time that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5,6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein (LDL) cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts