Genetic diversity and connectivity in the East African giant mud crab <i>Scylla serrata</i>: implications for fisheries management

The giant mud crab Scylla serrata provides an important source of income and food to coastal communities in East Africa. However, increasing demand and exploitation due to the growing coastal population, export trade, and tourism industry are threatening the sustainability of the wild stock of this species. Because effective management requires a clear understanding of the connectivity among populations, this study was conducted to assess the genetic diversity and connectivity in the East African mangrove crab S. serrata. A section of 535 base pairs of the cytochrome oxidase subunit I (COI) gene and eight microsatellite loci were analysed from 230 tissue samples of giant mud crabs collected from Kenya, Tanzania, Mozambique, Madagascar, and South Africa. Microsatellite genetic diversity (He) ranged between 0.56 and 0.6. The COI sequences showed 57 different haplotypes associated with low nucleotide diversity (current nucleotide diversity = 0.29%). In addition, the current nucleotide diversity was lower than the historical nucleotide diversity, indicating overexploitation or historical bottlenecks in the recent history of the studied population. Considering that the coastal population is growing rapidly, East African countries should promote sustainable fishing practices and sustainable use of mangrove resources to protect mud crabs and other marine fauna from the increasing pressure of exploitation. While microsatellite loci did not show significant genetic differentiation (p > 0.05), COI sequences revealed significant genetic divergence between sites on the East coast of Madagascar (ECM) and sites on the West coast of Madagascar, mainland East Africa, as well as the Seychelles. Since East African countries agreed to achieve the Convention on Biological Diversity (CBD) target to protect over 10% of their marine areas by 2020, the observed pattern of connectivity and the measured genetic diversity can serve to provide useful information for designing networks of marine protected areas

Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

This corrects the article DOI: 10.1038/sdata.2017.179

Dry Matter Accumulation and Partitioning between Vegetative and Reproductive Organs in Alfalfa (\u3ci\u3eMedicago sativa\u3c/i\u3e L.)

This work investigated the partitioning of dry matter between vegetative and reproductive plant organs in alfalfa during the reproductive period under field conditions. Two French varieties (Europe and Magali) were studied. Both varieties showed similar growth pattern of the different plant organs in 1998 and 1999. The mean dry matter of vegetative organs (shoots and leaves) over the two years was higher in Europe (567g/m2) than Magali (470g/m2). No vegetative growth was observed during the reproductive period. The root organs (measured to a depth of 0.20 m) and the reproductive organs showed an increase in dry matter accumulation during the first 300 °Cd and 600 °Cd, respectively. It indicated that dry matter was preferentially partitioned to the reproductive organs during the first 600 °Cd. The root organs seem to be a competing sink during the early seed growth (200 °Cd to 300 °Cd). The dry matter partitioning was not affected by the year. Thus, when dry matter accumulation ceased only 30% in Europe and 27% in Magali of the aboveground dry weight was in the reproductive organs. The mean inflorescence weight reached its maximum after 450 °Cd from inflorescence flowering

Are researchers deliberately bypassing the technology transfer office? An analysis of TTO awareness

Most universities committed to the commercialization of academic research have established technology transfer offices (TTOs). Nonetheless, many researchers bypass these TTOs and take their inventions directly to the marketplace. While TTO bypassing has typically been portrayed as deliberate and undesirable behavior, we argue that it could be unintentional as many researchers may simply be unaware of the TTO’s existence. Taking an information-processing perspective and using data on 3250 researchers in 24 European universities, we examine researcher attributes associated with TTO awareness. Our evidence confirms that only a minority of researchers are aware of the existence of a TTO at their university. TTO awareness is greater among researchers who possess experience as entrepreneurs, closed many research and consulting contracts with industry partners, conduct research in medicine, engineering or life sciences, or occupy postdoctoral positions. Policy implications of these findings are discussed

Technology transfer offices as boundary spanners in the pre-spin-off process: the case of a hybrid model

Over the past decades, universities have increasingly become ambidextrous organizations reconciling scientific and commercial missions. In order to manage this ambidexterity, technology transfer offices (TTOs) were established in most universities. This paper studies a specific, often implemented, but rather understudied type of TTO, namely a hybrid TTO model uniting centralized and decentralized levels. Employing a qualitative research design, we examine how and why the two TTO levels engage in diverse boundary spanning activities to help nascent spin-off companies move through the pre-spin-off process. Our research identifies differences in the types of boundary spanning activities that centralized and decentralized TTOs perform and in the parties they engage with. We find geographical, technological and organizational proximity to be important antecedents of the TTOs’ engagement in external and internal boundary spanning activities. These results have important implications for both academics and practitioners interested in university technology transfer through spin-off creation

A theoretical model of inflammation- and mechanotransduction- driven asthmatic airway remodelling

Inflammation, airway hyper-responsiveness and airway remodelling are well-established hallmarks of asthma, but their inter-relationships remain elusive. In order to obtain a better understanding of their inter-dependence, we develop a mechanochemical morphoelastic model of the airway wall accounting for local volume changes in airway smooth muscle (ASM) and extracellular matrix in response to transient inflammatory or contractile agonist challenges. We use constrained mixture theory, together with a multiplicative decomposition of growth from the elastic deformation, to model the airway wall as a nonlinear fibre-reinforced elastic cylinder. Local contractile agonist drives ASM cell contraction, generating mechanical stresses in the tissue that drive further release of mitogenic mediators and contractile agonists via underlying mechanotransductive signalling pathways. Our model predictions are consistent with previously described inflammation-induced remodelling within an axisymmetric airway geometry. Additionally, our simulations reveal novel mechanotransductive feedback by which hyper-responsive airways exhibit increased remodelling, for example, via stress-induced release of pro-mitogenic and procontractile cytokines. Simulation results also reveal emergence of a persistent contractile tone observed in asthmatics, via either a pathological mechanotransductive feedback loop, a failure to clear agonists from the tissue, or a combination of both. Furthermore, we identify various parameter combinations that may contribute to the existence of different asthma phenotypes, and we illustrate a combination of factors which may predispose severe asthmatics to fatal bronchospasms

Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants