The cover of living and dead corals from airborne remote sensing

Trends in coral cover are widely used to indicate the health of coral reefs but are costly to obtain from field survey over large areas. In situ studies of reflected spectra at the coral surface show that living and recently dead colonies can be distinguished. Here, we investigate whether such spectral differences can be detected using an airborne remote sensing instrument. The Compact Airborne Spectrographic Imager (Itres Research Ltd, Canada) was flown in two configurations: 10 spectral bands with 1-m² pixels and 6 spectral bands with 0.25-m² pixels. First, we show that an instrument with 10 spectral bands possesses adequate spectral resolution to distinguish living Porites, living Pocillopora spp., partially dead Porites, recently dead Porites (total colony mortality within 6 months), old dead (>6 months) Porites, Halimeda spp., and coralline red algae when there is no water column to confuse spectra. All substrata were distinguished using fourth-order spectral derivatives around 538 nm and 562 nm. Then, at a shallow site (Tivaru) at Rangiroa Atoll, Tuamotu Archipelago (French Polynesia), we show that live and dead coral can be distinguished from the air to a depth of at least 4 m using first- and fourth-order spectral derivatives between 562–580 nm. However, partially dead and recently dead Porites colonies could not be distinguished from an airborne platform. Spectral differences among substrata are then exploited to predict the cover of reef substrata in ten 25-m² plots at nearby Motu Nuhi (max depth 8 m). The actual cover in these plots was determined in situ using quadrats with a 0.01-m² grid. Considerable disparity occurred between field and image-based measures of substrate cover within individual 25-m² quadrats. At this small scale, disparity, measured as the absolute difference in cover between field and remote-sensing methods, reached 25% in some substrata but was always less than 10% for living coral (99% of which consisted of Porites spp.). At the scale of the reef (all ten 25-m² quadrats), however, disparities in percent cover between imagery and field data were less than 10% for all substrata and extremely low for some classes (e.g. <3% for living Porites, recently dead Porites and Halimeda). The least accurately estimated substrata were sand and coralline red algae, which were overestimated by absolute values 7.9% and 6.6%, respectively. The precision of sampling was similar for field and remote-sensing methods: field methods required 19 plots to detect a 10% difference in coral cover among three reefs with a statistical power of 95%. Remote-sensing methods required 21 plots. However, it took 1 h to acquire imagery over 92,500 m² of reef, which represents 3,700 plots of 25 m² each, compared with 3 days to survey 10 such plots underwater. There were no significant differences in accuracy between 1-m² and 0.25-m² image resolutions, suggesting that the advantage of using smaller pixels is offset by reduced spectral information and an increase in noise (noise was observed to be 1.6–1.8 times greater in 0.25-m² pixels). We show that airborne remote sensing can be used to monitor coral and algal cover over large areas, providing that water is shallow and clear, and that brown fleshy macroalgae are scarce, that depth is known independently (e.g. from sonar survey).     

A small RNA makes a <Emphasis Type="Italic">Bic</Emphasis> difference

The first highly specific knockouts of a microRNA, miR155, in mice result in multiple defects in adaptive immunity, and also show the feasibility of investigating at least some microRNAs by gene knockout.     

Real-time imaging of the dynamics of secretory granules in growth cones

Secretory granules containing a hybrid protein consisting of the regulated secretory protein tissue plasminogen activator and an enhanced form of green fluorescent protein were tracked at high spatial resolution in growth cones of differentiated PC12 cells. Tracking shows that granules, unlike synaptic vesicles, generally are mobile in growth cones. Quantitative analysis of trajectories generated by granules revealed two dominant modes of motion: diffusive and directed. Diffusive motion was observed primarily in central and peripheral parts of growth cones, where most granules diffused two to four orders of magnitude more slowly than comparably sized spheres in dilute solution. Directed motion was observed primarily in proximal parts of growth cones, where a subset of granules underwent rapid, directed motion at average speeds comparable to those observed for granules in neurites. This high-resolution view of the dynamics of secretory granules in growth cones provides insight into granule organization and release at nerve terminals. In particular, the mobility of granules suggests that granules, unlike synaptic vesicles, are not tethered stably to cytoskeletal structures in nerve terminals. Moreover, the slow diffusive nature of this mobility suggests that secretory responses involving centrally distributed granules in growth cones will occur slowly, on a time scale of minutes or longer.     

Selection of haplotype variables from a high-density marker map for genomic prediction

Background

Using haplotype blocks as predictors rather than individual single nucleotide polymorphisms (SNPs) may improve genomic predictions, since haplotypes are in stronger linkage disequilibrium with the quantitative trait loci than are individual SNPs. It has also been hypothesized that an appropriate selection of a subset of haplotype blocks can result in similar or better predictive ability than when using the whole set of haplotype blocks. This study investigated genomic prediction using a set of haplotype blocks that contained the SNPs with large effects estimated from an individual SNP prediction model. We analyzed protein yield, fertility and mastitis of Nordic Holstein cattle, and used high-density markers (about 770k SNPs). To reach an optimum number of haplotype variables for genomic prediction, predictions were performed using subsets of haplotype blocks that contained a range of 1000 to 50 000 main SNPs.

Results

The use of haplotype blocks improved the prediction reliabilities, even when selection focused on only a group of haplotype blocks. In this case, the use of haplotype blocks that contained the 20 000 to 50 000 SNPs with the highest effect was sufficient to outperform the model that used all individual SNPs as predictors (up to 1.3 % improvement in prediction reliability for mastitis, compared to individual SNP approach), and the achieved reliabilities were similar to those using all haplotype blocks available in the genome data (from 0.6 % lower to 0.8 % higher reliability).

Conclusions

Haplotype blocks used as predictors can improve the reliability of genomic prediction compared to the individual SNP model. Furthermore, the use of a subset of haplotype blocks that contains the main SNP effects from genomic data could be a feasible approach to genomic prediction in dairy cattle, given an increase in density of genotype data available. The predictive ability of the models that use a subset of haplotype blocks was similar to that obtained using either all haplotype blocks or all individual SNPs, with the benefit of having a much lower computational demand.     

MicroRNA expression profiling identifies activated B cell status in chronic lymphocytic leukemia cells

Chronic lymphocytic leukemia (CLL) is thought to be a disease of resting lymphocytes. However, recent data suggest that CLL cells may more closely resemble activated B cells. Using microRNA (miRNA) expression profiling of highly-enriched CLL cells from 38 patients and 9 untransformed B cells from normal donors before acute CpG activation and 5 matched B cells after acute CpG activation, we demonstrate an activated B cell status for CLL. Gene set enrichment analysis (GSEA) identified statistically-significant similarities in miRNA expression between activated B cells and CLL cells including upregulation of miR-34a, miR-155, and miR-342-3p and downregulation of miR-103, miR-181a and miR-181b. Additionally, decreased levels of two CLL signature miRNAs miR-29c and miR-223 are associated with ZAP70(+) and IgV(H) unmutated status and with shorter time to first therapy. These data indicate an activated B cell status for CLL cells and suggest that the direction of change of individual miRNAs may predict clinical course in CLL.     

Genomic prediction of genetic merit using LD-based haplotypes in the Nordic Holstein population

Background

A haplotype approach to genomic prediction using high density data in dairy cattle as an alternative to single-marker methods is presented. With the assumption that haplotypes are in stronger linkage disequilibrium (LD) with quantitative trait loci (QTL) than single markers, this study focuses on the use of haplotype blocks (haploblocks) as explanatory variables for genomic prediction. Haploblocks were built based on the LD between markers, which allowed variable reduction. The haploblocks were then used to predict three economically important traits (milk protein, fertility and mastitis) in the Nordic Holstein population.

Results

The haploblock approach improved prediction accuracy compared with the commonly used individual single nucleotide polymorphism (SNP) approach. Furthermore, using an average LD threshold to define the haploblocks (LD≥0.45 between any two markers) increased the prediction accuracies for all three traits, although the improvement was most significant for milk protein (up to 3.1 % improvement in prediction accuracy, compared with the individual SNP approach). Hotelling’s t-tests were performed, confirming the improvement in prediction accuracy for milk protein. Because the phenotypic values were in the form of de-regressed proofs, the improved accuracy for milk protein may be due to higher reliability of the data for this trait compared with the reliability of the mastitis and fertility data. Comparisons between best linear unbiased prediction (BLUP) and Bayesian mixture models also indicated that the Bayesian model produced the most accurate predictions in every scenario for the milk protein trait, and in some scenarios for fertility.

Conclusions

The haploblock approach to genomic prediction is a promising method for genomic selection in animal breeding. Building haploblocks based on LD reduced the number of variables without the loss of information. This method may play an important role in the future genomic prediction involving while genome sequences.     

Metal enrichment in water and fish in a semi-urban Nigerian lake,and their associated risks

Trace metal (Zn, Pb, Cu, Cr and Cd) concentrations in the water column and in the liver, muscle and gill tissues of Parachanna obscura and Clarias gariepinus in Agulu Lake, Nigeria, were investigated in June 2014 and compared with WHO and FAO safe limits for water and fish. Hazard index (HI) values were estimated to assess the potential public health risk of consuming contaminated fish. Lead and cadmium exceeded WHO guideline values for drinking water. In most cases, variations in concentration of the metals in organs were liver > muscle > gill. Differences in tissue-specific concentrations between species were not significant, except for zinc in muscles and gills. Cadmium and chromium were not detected in the fish, but lead was above the FAO maximum value for consumption. Hazard index values were below 1, indicating a low risk to public health. However, trace metal contamination in Agulu Lake is increasing.