Genes related to the white face colour pattern in eight Russian cattle breeds

One of the major effects of domestication is change of animal coat colour to up to complete white colour of the whole body. It is possible that white colour of livestock animals had aesthetic significance for humans as well. The first step towards detection of genes and mutations controlling white colouring in animals is the genome-wide association studies. These studies, however, have not been done for the cattle breeds native to the Russian Federation. The aim of this study was therefore to identify genomic intervals and candidate genes that could be responsible for white face colouring in eight Russian cattle breeds. The data on genome-wide genotyping of 131,709 high-quality single nucleotide polymorphisms (SNPs) on 148 animas have been used in the program ­EMMAX. Association analysis has been performed using two related phenotypes: a) the white face with the rest of the body of any colour and b) white face with the rest of the body of different (non-white) colour. In the first case, the only statistically significant marker found was the SNP BovineHD0500019319 located on cattle chromosome (BTA) 5. The same SNP was the most significant within the cluster of three SNPs on BTA5: 68,803,879–69,365,854 associated also with the second phenotype. Five genes were found within this interval in the cattle genome, out of which the most likely functional candidate was SLC41A2, with the SNP BovineHD0500019319 found within its intronic sequence. SLC41A2 encodes a magnesium transporter protein. However, the function of this gene is not well established. Other members of this gene family are the key genes controlling differences in human skin and animal coat colour. Additional significant association signals with the second phenotype have been detected in BTA 1–4, 6–15, 18, 19, 24, 27, and 29. Overall, 37 genomic intervals have been detected associated with white face colouring in eight Russian native cattle breeds

Identifying hybrid heating systems in the residential sector from smart meter data

In this paper, we identify hybrid heating systems on a single residential customer’s premises using smart meter data. A comprehensive methodology is developed at a generic level for residential sector buildings to identify the type of primary and support heating systems. The methodology includes the use of unsupervised and supervised learning algorithms both separately and combined. It is applied to two datasets that vary in size, quality of data, and availability and reliability of background information. The datasets contain hourly electricity consumption profiles of residential customers together with the outdoor temperature. The validation metrics for the developed algorithms are elaborated to provide a probabilistic evaluation of the model. The results show that it is possible to identify the types of both primary and support heating systems in the form of probability of having electric- or non-electric type of heating. The results obtained help estimate the flexibility domain of the residential building sector and thereby generate a high value for the energy system as a whole

Biochar as a potential carrier for agricultural beneficial microbes

© SGEM2018. In the recent years, growing interest to biochar as a means of improving soil quality is observed. Biochar is a product of pyrolysis of biomass such as plant residues or organic wastes. Biochars made of manures are special because they can solve two environmental problems simultaneously – waste reduction and soil fertilization, but they are less studied. In our research, we suggest to improve the properties of biochars derived from manures by means of immobilizing beneficial microbes on them. In this study, the choice of the method of such immobilization was made. Biochar from chicken manure produced at 5000C peak temperature for 3 h was used as a model biochar, and Pseudomonas putida able to suppress soil borne phytopathogens was used as a model microbe. Two types of immobilization in laboratory conditions were used. The first one included spreading of night culture concentrated ~3 fold (final cells amount – about 107 gene copies ml-1) on the surface of biochar in a ratio of 1:1, then drying in sterile conditions for 24 h and packing. The second one included wetting biochar in the culture medium with ~1.5 fold concentrated night culture, shaking for 1 h, then drying in sterile conditions for 24 h and packing. To track the survival rate of immobilized bacteria, scanning electron microscopy as well as quantitative PCR were used. It was shown that bacteria survived similarly after both types of immobilization during the first 10 days, however, later wet immobilization seemed to be more effective, which was proved by higher bacterial gene numbers on that biochar as compared with the dry treated one. We suggest that this is due to deeper penetration of microbes into the pores of biochars while using the wet method

<i>In silico</i> mapping of coronary artery disease genes

To date, more than 100 loci associated with coronary artery disease (CAD) have been detected in large-scale genome-wide studies. For some of the several hundreds of genes located in these loci, roles in the pathogenesis of the disease have been shown. However, the genetic mechanisms and specific genes controlling this disease are still not fully understood. This study is aimed at in silico search for new CAD genes. We performed a gene-based association analysis, where all polymorphic variants within a gene are analyzed simultaneously. The analysis was based on the results of the genome-wide association studies (GWAS) available from the open databases MICAD (120,575 people, 85,112 markers) and UK Biobank (337,199 people, 10,894,597 markers). We used the sumFREGAT package implementing a wide range of new methods for gene-based association analysis using summary statistics. We found 88 genes demonstrating significant gene-based associations. Forty-four of the identified genes were already known as CAD genes. Furthermore, we identified 28 additional genes in the known CAD loci. They can be considered as new candidate genes. Finally, we identified sixteen new genes (AGPAT4, ARHGEF12, BDP1, DHX58, EHBP1, FBF1, HSPB9, NPBWR2, PDLIM5, PLCB3, PLEKHM2, POU2F3, PRKD2, TMEM136, TTC29 and UTP20) outside the known loci. Information about the functional role of these genes allows us to consider many of them as candidates for CAD. The 41 identified genes did not have significant GWAS signals and they were identified only due to simultaneous consideration of all variants within the gene in the framework of gene-based analysis. These results demonstrate that gene-based association analysis is a powerful tool for gene mapping. The method can utilize huge amounts of GWAS results accumulated in the world to map different traits and diseases. This type of studies is widely available, as it does not require additional material costs

Multivariate discovery and replication of five novel loci associated with Immunoglobulin G <i>N</i>-glycosylation

Multivariate analysis methods can uncover the relationship between phenotypic measures characterised by modern omic techniques. Here the authors conduct a multivariate GWAS on IgG N-glycosylation phenotypes and identify 5 novel loci enriched in immune system genes

Regional heritability mapping method helps explain missing heritability of blood lipid traits in isolated populations

Single single-nucleotide polymorphism (SNP) genome-wide association studies (SSGWAS) may fail to identify loci with modest effects on a trait. The recently developed regional heritability mapping (RHM) method can potentially identify such loci. In this study, RHM was compared with the SSGWAS for blood lipid traits (high-density lipoprotein (HDL), low-density lipoprotein (LDL), plasma concentrations of total cholesterol (TC) and triglycerides (TG)). Data comprised 2246 adults from isolated populations genotyped using ∼300 000 SNP arrays. The results were compared with large meta-analyses of these traits for validation. Using RHM, two significant regions affecting HDL on chromosomes 15 and 16 and one affecting LDL on chromosome 19 were identified. These regions covered the most significant SNPs associated with HDL and LDL from the meta-analysis. The chromosome 19 region was identified in our data despite the fact that the most significant SNP in the meta-analysis (or any SNP tagging it) was not genotyped in our SNP array. The SSGWAS identified one SNP associated with HDL on chromosome 16 (the top meta-analysis SNP) and one on chromosome 10 (not reported by RHM or in the meta-analysis and hence possibly a false positive association). The results further confirm that RHM can have better power than SSGWAS in detecting causal regions including regions containing crucial ungenotyped variants. This study suggests that RHM can be a useful tool to explain some of the ‘missing heritability' of complex trait variation

MANAGING OF DEVELOPMENT OF CORPORATE CULTURE OF THE EDUCATIONAL ORGANIZATION AS A FACTOR OF HUMANIZATION OF THE EDUCATIONAL PROCESS

The article deals with improving the corporate culture of the educational organization. The author's technology of modeling of the process of increasing the educational potential of the corporate culture of the educational organization is presented, which consists of nine steps of activities of its leader, which contribute to the planning and implementation of actions to improve corporate culture. In the article diagnostic tools for the study of corporate culture of the educational organization are provided

Biochar as a potential carrier for agricultural beneficial microbes

© SGEM2018. In the recent years, growing interest to biochar as a means of improving soil quality is observed. Biochar is a product of pyrolysis of biomass such as plant residues or organic wastes. Biochars made of manures are special because they can solve two environmental problems simultaneously – waste reduction and soil fertilization, but they are less studied. In our research, we suggest to improve the properties of biochars derived from manures by means of immobilizing beneficial microbes on them. In this study, the choice of the method of such immobilization was made. Biochar from chicken manure produced at 5000C peak temperature for 3 h was used as a model biochar, and Pseudomonas putida able to suppress soil borne phytopathogens was used as a model microbe. Two types of immobilization in laboratory conditions were used. The first one included spreading of night culture concentrated ~3 fold (final cells amount – about 107 gene copies ml-1) on the surface of biochar in a ratio of 1:1, then drying in sterile conditions for 24 h and packing. The second one included wetting biochar in the culture medium with ~1.5 fold concentrated night culture, shaking for 1 h, then drying in sterile conditions for 24 h and packing. To track the survival rate of immobilized bacteria, scanning electron microscopy as well as quantitative PCR were used. It was shown that bacteria survived similarly after both types of immobilization during the first 10 days, however, later wet immobilization seemed to be more effective, which was proved by higher bacterial gene numbers on that biochar as compared with the dry treated one. We suggest that this is due to deeper penetration of microbes into the pores of biochars while using the wet method

Identifying hybrid heating systems in the residential sector from smart meter data

Abstract In this paper, we identify hybrid heating systems on a single residential customer’s premises using smart meter data. A comprehensive methodology is developed at a generic level for residential sector buildings to identify the type of primary and support heating systems. The methodology includes the use of unsupervised and supervised learning algorithms both separately and combined. It is applied to two datasets that vary in size, quality of data, and availability and reliability of background information. The datasets contain hourly electricity consumption profiles of residential customers together with the outdoor temperature. The validation metrics for the developed algorithms are elaborated to provide a probabilistic evaluation of the model. The results show that it is possible to identify the types of both primary and support heating systems in the form of probability of having electric- or non-electric type of heating. The results obtained help estimate the flexibility domain of the residential building sector and thereby generate a high value for the energy system as a whole

Phytochemical study of <i>Tribulus Terrestris</i> L.

Tríbulus terrestris L., an annual herb belonging to the Zygophyllaceae family and growing in moderate and tropical climates, has a rich chemical composition of biologically active substances and chemical elements.The aim of the work is a phytochemical study of Tribulus terrestris L. growing in different geographical zones.Materials and methods. The objects of study were herb specimens of Tribulus terrestris L. collected in different habitats. The samples of the raw materials were shade-dried. The determination of saponins in the raw materials, was carried out by high performance liquid chromatography with a mass spectrometric detection (HPLC-MS / MS). The study of the qualitative and quantitative composition of the elements was carried out on an X-ray fluorescence spectrometer.Results. The saponins had been studied by HPLC-MS/MS, according to which in all the studied samples, dioscin and protodioscin were found. Their retention times coincided with the retention times of dioscin and protodioscin standards. It has been established that among the macroelements of Tríbulus terrestris L., potassium and calcium are mostly accumulated. They account for about 90% of the total content of the elements in the plant. It has been revealed that the distribution of macroand microelements in the plant, varies significantly depending on their place and growing conditions.Conclusion. The maximum dioscin content was observed in the samples harvested in Moldova, and the minimum – in the samples from the nursery garden of the All-Russian Scientific Research Institute of medicinal and aromatic plants. The largest amount of protodioscin was found out in the samples from the Crimea, and the minimum – in the samples from Moldova. The carried out study of the elements content of Tríbulus terrestris L. showed that the habitats (geographical zones) in which the studied samples of raw materials had been were collected, affect the accumulation of the elements by the plant. Based on the data obtained, biological absorption series have been compiled for the samples from each habitat