First draft genome sequencing of fennel (<Emphasis Type="Italic">Foeniculum vulgare</Emphasis> Mill.): identification of simple sequence repeats and their application in marker-assisted breeding

The development of F₁ hybrid varieties benefits from the synergistic effect of conventional and molecular marker-assisted breeding schemes. A sequencing run was carried out in Foeniculum vulgare (2n?=?2x?=?22) to develop the first genome draft and to identify microsatellites suitable for implementing multilocus SSR marker assays. A preliminary cytometric analysis allowed us to estimate the genome size (2C?=?2.64–2.86 pg), equal to about 1.34 Mbp for 1C genome, and to calculate the sequencing coverage (53×). The genome draft assembly into 300,408 scaffolds and its bioinformatic analysis enabled the annotation of coding and non-coding regions across the genome, including 103,306 SSR elements. A total of 100 microsatellites were randomly chosen among those with dinucleotide and trinucleotide repeat motifs and with a repeat motif length?≥?25 times and were preliminarily tested. Of these, 27 SSR markers, classified as suitable for genetic diversity analyses, were efficiently organized in five PCR multiplex assays and validated using a core collection of 100 fennel individuals potentially useful for the development of inbred lines and F₁ hybrids. All SSR loci were found to be polymorphic, scoring an observed number of marker alleles Na?=?207 and an average polymorphism information content PIC?=?0.69. The SSR data were used to calculate (i) the degree of homozygosity for the individual inbred lines (0.35?<?Ho?<?0.96), to eventually plan additional selfing or sibling cycles, and (ii) the degree of genetic similarity for all possible pair-wise comparisons between parental inbred lines (GS?=?0.55–0.77), to identify the most divergent combinations for the constitution of experimental F₁ hybrids. The integration of genotypic and phenotypic data was useful for implementing guidelines for precision hybrid breeding schemes in fennel.     

Ecomorphological analysis as a complementary tool to detect changes in fish communities following major perturbations in two South African estuarine systems

Ecomorphological changes as a result of natural perturbations in estuarine fish communities were investigated in two South African estuaries (Swartvlei and East Kleinemonde), both before and after the loss of aquatic macrophyte beds in these systems. The fish communities were analysed using an ecomorphological diversity index (EMI) and the results compared to a traditional index, the Shannon-Wiener diversity index. The EMI revealed that the major changes in fish community composition recorded in both estuaries were associated with quantitative variations at the species level. Both estuaries essentially lost their macrophyte beds and ended up with the same type of bottom habitat (bare sediment). In both cases the fish morphological variability decreased immediately after aquatic macrophyte loss and then increased to end above the initial value. The ecomorphological analysis appeared to be sensitive to major ecological disturbances that occurred during the study period and this was confirmed by the morphospace configuration. The results indicate that the ecomorphology of the fish community responds to habitat changes and that this change corresponds to alterations in the representation of the different feeding types. These findings therefore contribute to the measurement of morphological changes in estuarine fish assemblages as a result of habitat changes within the ecosystem and we propose that ecomorphological analyses add another dimension to the information provided by existing diversity indices in studying changing fish communities.     

Watch and learn: seeing is better than doing when acquiring consecutive motor tasks

During motor adaptation learning, consecutive physical practice of two different tasks compromises the retention of the first. However, there is evidence that observational practice, while still effectively aiding acquisition, will not lead to interference and hence prove to be a better practice method. Observers and Actors practised in a clockwise (Task A) followed by a counterclockwise (Task B) visually rotated environment, and retention was immediately assessed. An Observe-all and Act-all group were compared to two groups who both physically practised Task A, but then only observed (ObsB) or did not see or practice Task B (NoB). The two observer groups and the NoB control group better retained Task A than Actors, although importantly only the observer groups learnt Task B. RT data and explicit awareness of the rotation suggested that the observers had acquired their respective tasks in a more strategic manner than Actor and Control groups. We conclude that observational practice benefits learning of multiple tasks more than physical practice due to the lack of updating of implicit, internal models for aiming in the former.     

Connectivity of Caribbean coral populations: complementary insights from empirical and modelled gene flow

Understanding patterns of connectivity among populations of marine organisms is essential for the development of realistic, spatially explicit models of population dynamics. Two approaches, empirical genetic patterns and oceanographic dispersal modelling, have been used to estimate levels of evolutionary connectivity among marine populations but rarely have their potentially complementary insights been combined. Here, a spatially realistic Lagrangian model of larval dispersal and a theoretical genetic model are integrated with the most extensive study of gene flow in a Caribbean marine organism. The 871 genets collected from 26 sites spread over the wider Caribbean subsampled 45.8% of the 1900 potential unique genets in the model. At a coarse scale, significant consensus between modelled estimates of genetic structure and empirical genetic data for populations of the reef-building coral Montastraea annularis is observed. However, modelled and empirical data differ in their estimates of connectivity among northern Mesoamerican reefs indicating that processes other than dispersal may dominate here. Further, the geographic location and porosity of the previously described east-west barrier to gene flow in the Caribbean is refined. A multi-prong approach, integrating genetic data and spatially realistic models of larval dispersal and genetic projection, provides complementary insights into the processes underpinning population connectivity in marine invertebrates on evolutionary timescales.     

How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use?

RNA-seq is now the technology of choice for genome-wide differential gene expression experiments, but it is not clear how many biological replicates are needed to ensure valid biological interpretation of the results or which statistical tools are best for analyzing the data. An RNA-seq experiment with 48 biological replicates in each of two conditions was performed to answer these questions and provide guidelines for experimental design. With three biological replicates, nine of the 11 tools evaluated found only 20%–40% of the significantly differentially expressed (SDE) genes identified with the full set of 42 clean replicates. This rises to >85% for the subset of SDE genes changing in expression by more than fourfold. To achieve >85% for all SDE genes regardless of fold change requires more than 20 biological replicates. The same nine tools successfully control their false discovery rate at ≲5% for all numbers of replicates, while the remaining two tools fail to control their FDR adequately, particularly for low numbers of replicates. For future RNA-seq experiments, these results suggest that at least six biological replicates should be used, rising to at least 12 when it is important to identify SDE genes for all fold changes. If fewer than 12 replicates are used, a superior combination of true positive and false positive performances makes edgeR and DESeq2 the leading tools. For higher replicate numbers, minimizing false positives is more important and DESeq marginally outperforms the other tools.     

Discovery of a novel site regulating glucokinase activity following characterization of a new mutation causing hyperinsulinemic hypoglycemia in humans

Type 2 diabetes is a global problem, and current ineffective therapeutic strategies pave the way for novel treatments like small molecular activators targeting glucokinase (GCK). GCK activity is fundamental to beta cell and hepatocyte glucose metabolism, and heterozygous activating and inactivating GCK mutations cause hyperinsulinemic hypoglycemia (HH) and maturity onset diabetes of the young (MODY) respectively. Over 600 naturally occurring inactivating mutations have been reported, whereas only 13 activating mutations are documented to date. We report two novel GCK HH mutations (V389L and T103S) at residues where MODY mutations also occur (V389D and T103I). Using recombinant proteins with in vitro assays, we demonstrated that both HH mutants had a greater relative activity index than wild type (6.0 for V389L, 8.4 for T103S, and 1.0 for wild type). This was driven by an increased affinity for glucose (S(0.5), 3.3 ± 0.1 and 3.5 ± 0.1 mm, respectively) versus wild type (7.5 ± 0.1 mm). Correspondingly, the V389D and T103I MODY mutants had markedly reduced relative activity indexes (<0.1). T103I had an altered affinity for glucose (S(0.5), 24.9 ± 0.6 mm), whereas V389D also exhibited a reduced affinity for ATP and decreased catalysis rate (S(0.5), 78.6 ± 4.5 mm; ATP(K(m)), 1.5 ± 0.1 mm; K(cat), 10.3 ± 1.1s(-1)) compared with wild type (ATP(K(m)), 0.4 ± <0.1; K(cat), 62.9 ± 1.2). Both Thr-103 mutants showed reduced inhibition by the endogenous hepatic inhibitor glucokinase regulatory protein. Molecular modeling demonstrated that Thr-103 maps to the allosteric activator site, whereas Val-389 is located remotely to this position and all other previously reported activating mutations, highlighting α-helix 11 as a novel region regulating GCK activity. Our data suggest that pharmacological manipulation of GCK activity at locations distal from the allosteric activator site is possible.