Genomic regions associated with chocolate spot (Botrytis fabae Sard.) resistance in faba bean (Vicia faba L.)

Molecular Breeding - Maize (Zea mays L.) is the most important food crop in the world, with significant acreage and production across the globe. However, it is affected by low temperatures...     

Evaluation of major Acacia species in the nursery towards apicultural landscape restoration around Southwestern Saudi Arabia

Southwestern Saudi Arabia is described by a unique ecosystem and composed of apicultural landscapes where nearly 70% of the beekeeping activities are concentrated. However, this economically important resource is under continuous degradation threat urging restoration. Besides, profound information on the possible major biological components of future restoration; nursery level performances of the native plants, Acacia species is lacking. Hence, the study was aimed at evaluating performances of selected native Acacia species at nursery level as candidate biological tool for apicultural landscape restoration. For this, nine native Acacia species’ seedlings were prepared in accordance to appropriate techniques of nursery operations recommended for arid areas. Meanwhile, species were evaluated and compared based on some performance parameters. Accordingly, significant (P < 0.005) variations were observed among the species in shoot height, collar diameter, height to collar diameter ratio, number of leaves and seedling survival. Acacia origena Hunde, A. gerrardii Benth., and A. johnwoodii Boulos. were superior over the others in most parameters while A. etbaica Schiweinf. and A. asak (Forssk.) willd. were less vulnerable to chanced pathogens. Generally, nursery level performances of all Acacia species under experimentation were within the acceptable range and showed a remarkable score which may lead them to be considered as competent biological tools in the incorporation of the genotypes in apicultural landscape restoration efforts.     

Gaussian process regression model for normalization of LC-MS data using scan-level information

Background

Differences in sample collection, biomolecule extraction, and instrument variability introduce bias to data generated by liquid chromatography coupled with mass spectrometry (LC-MS). Normalization is used to address these issues. In this paper, we introduce a new normalization method using the Gaussian process regression model (GPRM) that utilizes information from individual scans within an extracted ion chromatogram (EIC) of a peak. The proposed method is particularly applicable for normalization based on analysis order of LC-MS runs. Our method uses measurement variabilities estimated through LC-MS data acquired from quality control samples to correct for bias caused by instrument drift. Maximum likelihood approach is used to find the optimal parameters for the fitted GPRM. We review several normalization methods and compare their performance with GPRM.

Results

To evaluate the performance of different normalization methods, we consider LC-MS data from a study where metabolomic approach is utilized to discover biomarkers for liver cancer. The LC-MS data were acquired by analysis of sera from liver cancer patients and cirrhotic controls. In addition, LC-MS runs from a quality control (QC) sample are included to assess the run to run variability and to evaluate the ability of various normalization method in reducing this undesired variability. Also, ANOVA models are applied to the normalized LC-MS data to identify ions with intensity measurements that are significantly different between cases and controls.

Conclusions

One of the challenges in using label-free LC-MS for quantitation of biomolecules is systematic bias in measurements. Several normalization methods have been introduced to overcome this issue, but there is no universally applicable approach at the present time. Each data set should be carefully examined to determine the most appropriate normalization method. We review here several existing methods and introduce the GPRM for normalization of LC-MS data. Through our in-house data set, we show that the GPRM outperforms other normalization methods considered here, in terms of decreasing the variability of ion intensities among quality control runs.

     

The role of sulphidogenesis in anaerobic treatment phase of tannery wastewater treatment in advanced integrated wastewater pond system

An outdoor experiment was conducted to study the competitionbetween Sulphate Reducing Bacteria (SRB) and Methanogenic Archaea (MA) in anaerobictreatment phase of tannery wastewater treatment in pilot-scale Advanced FacultativePond (AFP). The relative electron flow towards sulphate reduction was higher (59–83%) than towardsmethanogenesis (17–41%), although the COD recovery within thereactor varied between 15 and 90%. The results also demonstrated that the flow of electrons towards SRBincreased with increase of the sulphate concentration and decrease of the COD : SO₄ ⁼ ratio.     

Reliability of measurements performed by community-drawn anthropometrists from rural Ethiopia

Background

Undernutrition is an important risk factor for childhood mortality, and remains a major problem facing many developing countries. Millennium Development Goal 1 calls for a reduction in underweight children, implemented through a variety of interventions. To adequately judge the impact of these interventions, it is important to know the reproducibility of the main indicators for undernutrition. In this study, we trained individuals from rural communities in Ethiopia in anthropometry techniques and measured intra- and inter-observer reliability.

Methods and Findings

We trained 6 individuals without prior anthropometry experience to perform weight, height, and middle upper arm circumference (MUAC) measurements. Two anthropometry teams were dispatched to 18 communities in rural Ethiopia and measurements performed on all consenting pre-school children. Anthropometry teams performed a second independent measurement on a convenience sample of children in order to assess intra-anthropometrist reliability. Both teams measured the same children in 2 villages to assess inter-anthropometrist reliability. We calculated several metrics of measurement reproducibility, including the technical error of measurement (TEM) and relative TEM. In total, anthropometry teams performed measurements on 606 pre-school children, 84 of which had repeat measurements performed by the same team, and 89 of which had measurements performed by both teams. Intra-anthropometrist TEM (and relative TEM) were 0.35 cm (0.35%) for height, 0.05 kg (0.39%) for weight, and 0.18 cm (1.27%) for MUAC. Corresponding values for inter-anthropometrist reliability were 0.67 cm (0.75%) for height, 0.09 kg (0.79%) for weight, and 0.22 kg (1.53%) for MUAC. Inter-anthropometrist measurement error was greater for smaller children than for larger children.

Conclusion

Measurements of height and weight were more reproducible than measurements of MUAC and measurements of larger children were more reliable than those for smaller children. Community-drawn anthropometrists can provide reliable measurements that could be used to assess the impact of interventions for childhood undernutrition.     

The diversity and distribution of lianas in the Afromontane rain forests of Ethiopia

The diversity and distribution of lianas were studied in five Afromontane rain forests of Ethiopia. Quadrats of 20 × 20 m were laid down along transects in the Bonga, Berhane‐Kontir, Harenna, Yayu and Maji forests. In all forests, 30,917 liana individuals belonging to 123 species in 87 genera and 40 plant families were recorded. The most species‐rich families were Asclepiadaceae (14), Fabaceae (9), Annonaceae (7) and Cucurbitaceae (7). The top 10 dominant families represented 56% of the total number of species. Over 400 other plant species representing different life forms were recorded growing together with lianas. The lianas accounted for over 30% of the total woody plant diversity and over 20% of the total floral diversity in the study areas. The analysis of floristic composition of the forests indicates that the Berhane‐Kontir Forest had the highest Fisher's diversity index α, and Yayu the lowest. Generally, there were low similarities between the forests in terms of species composition. Although lianas were abundant in almost all forests, there was a considerable variation among the forests in terms of density and spatial distribution. The major dispersal modes of lianas were anemochory (30%), mammaliochory (30%), ornithochory and autochory, and the four mechanisms of climbing of lianas were twining (54%), hooking (24%), rooting and use of tendrils. Altitude and human disturbance were found to be important factors affecting liana distribution. The need for sustainable management and use of lianas in the Afromontane rain forests is emphasized.     

Rational design of novel, potent piperazinone and imidazolidinone BACE1 inhibitors

Guided by structure-based design, we synthesized two novel series of potent inhibitors of BACE1 and generated extensive SAR around both the prime and non-prime side binding pockets. The key feature of both series is a cyclic amine motif specifically crafted to achieve interactions with both the flap and with the S2' pocket.     

Modeling genetic inheritance of copy number variations

Copy number variations (CNVs) are being used as genetic markers or functional candidates in gene-mapping studies. However, unlike single nucleotide polymorphism or microsatellite genotyping techniques, most CNV detection methods are limited to detecting total copy numbers, rather than copy number in each of the two homologous chromosomes. To address this issue, we developed a statistical framework for intensity-based CNV detection platforms using family data. Our algorithm identifies CNVs for a family simultaneously, thus avoiding the generation of calls with Mendelian inconsistency while maintaining the ability to detect de novo CNVs. Applications to simulated data and real data indicate that our method significantly improves both call rates and accuracy of boundary inference, compared to existing approaches. We further illustrate the use of Mendelian inheritance to infer SNP allele compositions in each of the two homologous chromosomes in CNV regions using real data. Finally, we applied our method to a set of families genotyped using both the Illumina HumanHap550 and Affymetrix genome-wide 5.0 arrays to demonstrate its performance on both inherited and de novo CNVs. In conclusion, our method produces accurate CNV calls, gives probabilistic estimates of CNV transmission and builds a solid foundation for the development of linkage and association tests utilizing CNVs.