QTL fine mapping with Bayes C(π): a simulation study

Background

Accurate QTL mapping is a prerequisite in the search for causative mutations. Bayesian genomic selection models that analyse many markers simultaneously should provide more accurate QTL detection results than single-marker models. Our objectives were to (a) evaluate by simulation the influence of heritability, number of QTL and number of records on the accuracy of QTL mapping with Bayes Cπ and Bayes C; (b) estimate the QTL status (homozygous vs. heterozygous) of the individuals analysed. This study focussed on the ten largest detected QTL, assuming they are candidates for further characterization.

Methods

Our simulations were based on a true dairy cattle population genotyped for 38 277 phased markers. Some of these markers were considered biallelic QTL and used to generate corresponding phenotypes. Different numbers of records (4387 and 1500), heritability values (0.1, 0.4 and 0.7) and numbers of QTL (10, 100 and 1000) were studied. QTL detection was based on the posterior inclusion probability for individual markers, or on the sum of the posterior inclusion probabilities for consecutive markers, estimated using Bayes C or Bayes Cπ. The QTL status of the individuals was derived from the contrast between the sums of the SNP allelic effects of their chromosomal segments.

Results

The proportion of markers with null effect (π) frequently did not reach convergence, leading to poor results for Bayes Cπ in QTL detection. Fixing π led to better results. Detection of the largest QTL was most accurate for medium to high heritability, for low to moderate numbers of QTL, and with a large number of records. The QTL status was accurately inferred when the distribution of the contrast between chromosomal segment effects was bimodal.

Conclusions

QTL detection is feasible with Bayes C. For QTL detection, it is recommended to use a large dataset and to focus on highly heritable traits and on the largest QTL. QTL statuses were inferred based on the distribution of the contrast between chromosomal segment effects.     

On the use of weighting in LCA: translating decision makers’ preferences into weights via linear programming

Purpose

The main goal of any life cycle assessment (LCA) study is to identify solutions leading to environmental savings. In conventional LCA studies, practitioners select from some alternatives the one which better matches their preferences. This task is sometimes simplified by ranking these alternatives using an aggregated indicator defined by attaching weights to impacts. We address here the inverse problem. That is, given an alternative, we aim to determine the weights for which that solution becomes optimal.

Methods

We propose a method based on linear programming (LP) that determines, for a given alternative, the ranges within which the weights attached to a set of impact metrics must lie so that when a weighting combination of these impacts is optimized, the alternative can be optimal, while if the weights fall outside this range, it is guaranteed that the solution will be suboptimal. A large weight value implies that the corresponding LCA impact is given more importance, while a low value implies the converse. Furthermore, we provide a rigorous mathematical analysis on the implications of using weighting schemes in LCA, showing that this practice guides decision-making towards the adoption of some specific alternatives (those lying on the convex envelope of the resulting trade-off curve).

Results and discussion

A case study based on the design of hydrogen infrastructures is taken as a test bed to illustrate the capabilities of the approach presented. Given are a set of production and storage technologies available to produce and deliver hydrogen, a final demand, and cost and environmental data. A set of designs, each achieving a unique combination of cost and LCA impact, is considered. For each of them, we calculate the minimum and maximum weight to be given to every LCA impact so that the alternative can be optimal among all the candidate designs. Numerical results show that solutions with lower impact are selected when decision makers are willing to pay larger monetary penalties for the environmental damage caused.

Conclusions

LP can be used in LCA to translate the decision makers’ preferences into weights. This information is rather valuable, particularly when these weights represent economic penalties, as it allows screening and ranking alternatives on the basis of a common economic basis. Our framework is aimed at facilitating decision making in LCA studies and defines a general framework for comparing alternatives that show different performance in a wide variety of impact metrics.     

A Powerful Molecular Engineering Tool Provided Efficient Chlamydomonas Mutants as Bio-Sensing Elements for Herbicides Detection

This study was prompted by increasing concerns about ecological damage and human health threats derived by persistent contamination of water and soil with herbicides, and emerging of bio-sensing technology as powerful, fast and efficient tool for the identification of such hazards. This work is aimed at overcoming principal limitations negatively affecting the whole-cell-based biosensors performance due to inadequate stability and sensitivity of the bio-recognition element. The novel bio-sensing elements for the detection of herbicides were generated exploiting the power of molecular engineering in order to improve the performance of photosynthetic complexes. The new phenotypes were produced by an in vitro directed evolution strategy targeted at the photosystem II (PSII) D1 protein of Chlamydomonas reinhardtii, using exposures to radical-generating ionizing radiation as selection pressure. These tools proved successful to identify D1 mutations conferring enhanced stability, tolerance to free-radical-associated stress and competence for herbicide perception. Long-term stability tests of PSII performance revealed the mutants capability to deal with oxidative stress-related conditions. Furthermore, dose-response experiments indicated the strains having increased sensitivity or resistance to triazine and urea type herbicides with I₅₀ values ranging from 6×10⁻⁸ M to 2×10⁻⁶ M. Besides stressing the relevance of several amino acids for PSII photochemistry and herbicide sensing, the possibility to improve the specificity of whole-cell-based biosensors, via coupling herbicide-sensitive with herbicide-resistant strains, was verified.     

Inhibition of Dopamine Transporter Activity by G Protein βγ Subunits

Uptake through the Dopamine Transporter (DAT) is the primary mechanism of terminating dopamine signaling within the brain, thus playing an essential role in neuronal homeostasis. Deregulation of DAT function has been linked to several neurological and psychiatric disorders including ADHD, schizophrenia, Parkinson’s disease, and drug addiction. Over the last 15 years, several studies have revealed a plethora of mechanisms influencing the activity and cellular distribution of DAT; suggesting that fine-tuning of dopamine homeostasis occurs via an elaborate interplay of multiple pathways. Here, we show for the first time that the βγ subunits of G proteins regulate DAT activity. In heterologous cells and brain tissue, a physical association between Gβγ subunits and DAT was demonstrated by co-immunoprecipitation. Furthermore, in vitro pull-down assays using purified proteins established that this association occurs via a direct interaction between the intracellular carboxy-terminus of DAT and Gβγ. Functional assays performed in the presence of the non-hydrolyzable GTP analog GTP-γ-S, Gβγ subunit overexpression, or the Gβγ activator mSIRK all resulted in rapid inhibition of DAT activity in heterologous systems. Gβγ activation by mSIRK also inhibited dopamine uptake in brain synaptosomes and dopamine clearance from mouse striatum as measured by high-speed chronoamperometry in vivo. Gβγ subunits are intracellular signaling molecules that regulate a multitude of physiological processes through interactions with enzymes and ion channels. Our findings add neurotransmitter transporters to the growing list of molecules regulated by G-proteins and suggest a novel role for Gβγ signaling in the control of dopamine homeostasis.     

Prevalence of BRCA1 Mutations in Familial and Sporadic Greek Ovarian Cancer Cases

Germline mutations in the BRCA1 and BRCA2 genes contribute to approximately 18% of hereditary ovarian cancers conferring an estimated lifetime risk from 15% to 50%. A variable incidence of mutations has been reported for these genes in ovarian cancer cases from different populations. In Greece, six mutations in BRCA1 account for 63% of all mutations detected in both BRCA1 and BRCA2 genes. This study aimed to determine the prevalence of BRCA1 mutations in a Greek cohort of 106 familial ovarian cancer patients that had strong family history or metachronous breast cancer and 592 sporadic ovarian cancer cases. All 698 patients were screened for the six recurrent Greek mutations (including founder mutations c.5266dupC, p.G1738R and the three large deletions of exon 20, exons 23–24 and exon 24). In familial cases, the BRCA1 gene was consequently screened for exons 5, 11, 12, 20, 21, 22, 23, 24. A deleterious BRCA1 mutation was found in 43/106 (40.6%) of familial cancer cases and in 27/592 (4.6%) of sporadic cases. The variant of unknown clinical significance p.V1833M was identified in 9/698 patients (1.3%). The majority of BRCA1 carriers (71.2%) presented a high-grade serous phenotype. Identifying a mutation in the BRCA1 gene among breast and/or ovarian cancer families is important, as it enables carriers to take preventive measures. All ovarian cancer patients with a serous phenotype should be considered for genetic testing. Further studies are warranted to determine the prevalence of mutations in the rest of the BRCA1 gene, in the BRCA2 gene, and other novel predisposing genes for breast and ovarian cancer.     

Genetic Instability and Intratumoral Heterogeneity in Neuroblastoma with MYCN Amplification Plus 11q Deletion

Background/Aim

Genetic analysis in neuroblastoma has identified the profound influence of MYCN amplification and 11q deletion in patients’ prognosis. These two features of high-risk neuroblastoma usually occur as mutually exclusive genetic markers, although in rare cases both are present in the same tumor. The purpose of this study was to characterize the genetic profile of these uncommon neuroblastomas harboring both these high-risk features.

Methods

We selected 18 neuroblastomas with MNA plus 11q loss detected by FISH. Chromosomal aberrations were analyzed using Multiplex Ligation-dependent Probe Amplification and Single Nucleotide Polymorphism array techniques.

Results and Conclusion

This group of tumors has approximately the same high frequency of aberrations as found earlier for 11q deleted tumors. In some cases, DNA instability generates genetic heterogeneity, and must be taken into account in routine genetic diagnosis.     

Metastatic risk and resistance to BRAF inhibitors in melanoma defined by selective allelic loss of ATG5

Melanoma is a paradigm of aggressive tumors with a complex and heterogeneous genetic background. Still, melanoma cells frequently retain developmental traits that trace back to lineage specification programs. In particular, lysosome-associated vesicular trafficking is emerging as a melanoma-enriched lineage dependency. However, the contribution of other lysosomal functions such as autophagy to melanoma progression is unclear, particularly in the context of metastasis and resistance to targeted therapy. Here we mined a broad spectrum of cancers for a meta-analysis of mRNA expression, copy number variation and prognostic value of 13 core autophagy genes. This strategy identified heterozygous loss of ATG5 at chromosome band 6q21 as a distinctive feature of advanced melanomas. Importantly, partial ATG5 loss predicted poor overall patient survival in a manner not shared by other autophagy factors and not recapitulated in other tumor types. This prognostic relevance of ATG5 copy number was not evident for other 6q21 neighboring genes. Melanocyte-specific mouse models confirmed that heterozygous (but not homozygous) deletion of Atg5 enhanced melanoma metastasis and compromised the response to targeted therapy (exemplified by dabrafenib, a BRAF inhibitor in clinical use). Collectively, our results support ATG5 as a therapeutically relevant dose-dependent rheostat of melanoma progression. Moreover, these data have important translational implications in drug design, as partial blockade of autophagy genes may worsen (instead of counteracting) the malignant behavior of metastatic melanomas.     

Dynamic changes in microbiota and mycobiota during spontaneous ‘Vino Santo Trentino’ fermentation

Vino Santo is a sweet wine produced from late harvesting and pressing of Nosiola grapes in a small, well‐defined geographical area in the Italian Alps. We used metagenomics to characterize the dynamics of microbial communities in the products of three wineries, resulting from spontaneous fermentation with almost the same timing and procedure. Comparing fermentation dynamics and grape microbial composition, we show a rapid increase in a small number of wine yeast species, with a parallel decrease in complexity. Despite the application of similar protocols, slight changes in the procedures led to significant differences in the microbiota in the three cases of fermentation: (i) fungal content of the must varied significantly in the different wineries, (ii) Pichia membranifaciens persisted in only one of the wineries, (iii) one fermentation was characterized by the balanced presence of Saccharomyces cerevisiae and Hanseniaspora osmophila during the later phases. We suggest the existence of a highly winery‐specific ‘microbial‐terroir’ contributing significantly to the final product rather than a regional ‘terroir’. Analysis of changes in abundance during fermentation showed evident correlations between different species, suggesting that fermentation is the result of a continuum of interaction between different species and physical–chemical parameters.