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There are numerous genetic factors like MC4R (Melanocortin-4 receptor), POMC (Proopiomelanocortin), SIM1 (Single Minded Gene) etc. important in obesity, which can be used as biomarker. But more reliable diagnostic markers are the need for today, along with new therapeutic strategies that target specific molecules in the disease pathways. As in mouse and human genes, where mutations in one or both species are associated with some phenotypic characteristics as observed in human disease. In molecular mechanisms of development, differentiation, and disease gene expression data provide crucial insights. Up-regulation and down-regulation of selective genes can have major effects on diet-induced obesity, but there is little or no effect when animals are fed a low-fat diet. In present study we have studied the gene expression data of mouse at different theiler stages using GXD BioMart. The interacting partners and pathway of the genes that are already used as biomarker in mouse as well as in humans have been studied. A gene NPY1R (Neuropeptide Y1 receptor) was taken as common after STRING and KEGG results on the basis of biochemical pathways and interactions similar to MC4R. Our present work focuses on comparative genomics and proteomics analysis of NPY1R, which has led to identification of biomarker by comparing it with already known MC4R human and mouse biomarker. It has been concluded that both the proteins are structurally and functionally similar.
Trees are long living organisms, rarely used in molecular experiments because of large size of the genome and long time of reproduction cycle. Sequencing data from Populus trichocarpa genome allowed for the development of research on the processes associated with tree biology such as secondary wood formation, long-term perennial growth, seasonal changes, biotic interactions, evolution etc. Reference data enable the investigation of non-model trees such as Quercus or Fagus, having ecological and economic significance. During projects scientists use genomic, transcriptomic, proteomic and metabolomic approaches which contribute to better understanding of the physiological processes regulating tree biology. Data collected from these multiple studies need to be integrated. The integration of data is the subject of the newly established field of science called systems biology. This review presents progress in tree research after finishing the sequencing project of Populus. It concentrates on modern trends in 'omics' and systems biology study of temperate broadleave trees during the last 10 years of studies.
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Where are we in genomics?

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Genomic studies provide scientists with methods to quickly analyse genes and their products en masse. The first high-throughput techniques to be developed were sequencing methods. A great number of genomes from different organisms have thus been sequenced. Genomics is now shifting to the study of gene expression and function. In the past 5-10 years genomics, proteomics and high-throughput microarray technologies have fundamentally changed our ability to study the molecular basis of cells and tissues in health and diseases, giving a new comprehensive view. For example, in cancer research we have seen new diagnostic opportunities for tumour classification, and prognostication. A new exciting development is metabolomics and lab-on-a-chip techniques (which combine miniaturisation and automation) for metabolic studies. However, to interpret the large amount of data, extensive computational development is required. In the coming years, we will see the study of biological networks dominating the scene in Physiology. The great accumulation of genomics information will be used in computer programs to simulate biologic processes. Originally developed for genome analysis, bioinformatics now encompasses a wide range of fields in biology from gene studies to integrated biology (i.e. combination of different data sets from genes to metabolites). This is systems biology which aims to study biological organisms as a whole. In medicine, scientific results and applied biotechnologies arising from genomics will be used for effective prediction of diseases and risk associated with drugs. Preventive medicine and medical therapy will be personalised. Widespread applications of genomics for personalised medicine will require associations of gene expression pattern with diagnoses, treatment and clinical data. This will help in the discovery and development of drugs. In agriculture and animal science, the outcomes of genomics will include improvement in food safety, in crop yield, in traceability and in quality of animal products (dairy products and meat) through increased efficiency in breeding and better knowledge of animal physiology. Genomics and integrated biology are huge tasks and no single lab can pursue this alone. We are probably at the end of the beginning rather than at the beginning of the end because Genomics will probably change Biology to a greater extent than previously forecasted. In addition, there is a great need for more information and better understanding of genomics before complete public acceptance.
Genomic imprinting is a normal process causing genes to be expressed from only one of the two parental chromosome homologues according to their parental origin. Imprinted genes function in a range of developmental processes. In recent years, data has emerged indicating discordance of imprinting between mouse and man, polymorphic imprinting between different individuals and tissue-specific imprinting within individuals. This suggests that imprinting might be an adaptable and dynamic process with the potential to act as a mechanism regulating gene dosage in different developmental contexts. Delta-like homologue 1 (Dlk1) is a paternally expressed imprinted gene that encodes both a transmembrane protein and a secreted isoform generated by alternative splicing, and is an atypical member of the Notch/Delta/Serrate family of developmental signalling molecules. Although widely expressed during embryonic development, only a few tissues including neurogenic regions of the brain retain Dlk1 expression in adults. Analysis of neurogenesis in the SVZ of Dlk1 mutant mice shows a reduction in the numbers of stem cells in vivo and an impairment of newborn neurons incorporated into the olfactory bulb as well as fewer primary neurospheres in vitro suggesting that normal levels of Dlk1 are necessary for the life-long maintenance of neural stem cells (NSCs). Within the SVZ, DLK1 is a niche factor secreted by astrocytes and that membrane-bound DLK1 is required in NSCs to respond to it. In contrast to the neighbouring Gtl2 gene, we observe specific absence of Dlk1 imprinting in the stem cell and astrocyte populations in the SVZ niche indicating that the mechanism conferring biallelic expression can override the imprint selectively at Dlk1 to control normal neurogenesis in the adult brain. This neurogenic requirement for both the maternally and paternally expressed alleles of the canonically imprinted Dlk1 gene supports the hypothesis that control of gene dosage by absence of imprinting is an important developmental process. We are testing the hypothesis that other imprinted genes important in neurogenesis may also modulate imprinting to control gene dosage.
In the future an approach incorporating cows’ measured phenotypes and marker genotypes of cows and bulls within a single model can be applied. The most important advantage of such a model is the simultaneous use of pedigree and marker-based genomic relationship data. Such a solution allows the use of both genotyped and non-genotyped animals in the prediction procedure. This pilot study is aimed towards implementation of a one-step approach in a random regression test day model context for the Polish Holstein Friesian population, considering various ways of adjusting the relationship matrix. Data consisted of 890 animals (10 genotyped bulls, 100 cows with phenotypic data and 780 ancestors without genotypes or phenotypes). Random regression test day models with a polygenic effect on milk yield modeled by second order Legendre polynomials for the estimation of variance-covariance parameters and were used for prediction of genomically enhanced breeding values (GEBV). In this model, a matrix combining pedigree and marker-based information was used instead of a traditional numerator relationship matrix. In this matrix the proportions of information coming from pedigree and markers were defined by weighting parameters w and 1-w for pedigree and marker-based information matrices, respectively. Various weights of the two sources of information were considered. The accuracy of GEBV both for genotyped bulls and for cows with phenotypes was highest for weighting parameter w=0 and lowest for w=l. Incorporating genomic information into a conventional genetic evaluation improves reliabilities of breeding value prediction, however, pedigree information is important to maintain the stability of evaluation for non-genotyped animals. Implementation of the single-step approach in a random regression test day model framework is very attractive for genomic prediction in dairy cattle, since it allows to incorporate genomic information directly into a conventional genetic evaluation. However, for accurate predictions it is essential to achieve the right balance between the numerator relationship and markers-based relationship information.
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Understanding mitotane mode of action

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Protein crystallography, the main experimental method of structural biology, has undergone in the recent past three revolutionary changes leading to its unexpected renaissance. They were connected with (i) the introduction of synchrotron radiation sources for X-ray diffraction experiments, (ii) implementation of Se-Met multiwavelength anomalous diffraction (MAD) for phasing, and (iii) initiation of structural genomics (SG) programs. It can be foreseen that in the next 10-15 years protein crystallography will continue to be in this revolutionary phase. We can expect not only an; avalanche of protein crystal structures from SG centers, but also attacking of more demanding projects, such as the structure of membrane proteins and of very large macromolecular complexes. On the technological front, the introduction of X-ray radiation from free-electron lasers will revolutionize the experimental possibilities, making feasible even the imaging of single molecules and of intact biological cells.
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Plastid origin: who, when and why?

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The origin of plastids is best explained by endosymbiotic theory, which dates back to the early 1900s. Three lines of evidence based on protein import machineries and molecular phylogenies of eukaryote (host) and cyanobacterial (endosymbiont) genes point to a single origin of primary plastids, a unique and important event that successfully transferred two photosystems and oxygenic photosynthesis from prokaryotes to eukaryotes. The nature of the cyanobacterial lineage from which plastids originated has been a topic of investigation. Recent studies have focused on the branching position of the plastid lineage in the phylogeny based on cyanobacterial core genes, that is, genes shared by all cyanobacteria and plastids. These studies have delivered conflicting results, however. In addition, the core genes represent only a very small portion of cyanobacterial genomes and may not be a good proxy for the rest of the ancestral plastid genome. Information in plant nuclear genomes, where most genes that entered the eukaryotic lineage through acquisition from the plastid ancestor reside, suggests that heterocyst-forming cyanobacteria in Stanier’s sections IV and V are most similar to the plastid ancestor in terms of gene complement and sequence conservation, which is in agreement with models suggesting an important role of nitrogen fixation in symbioses involving cyanobacteria. Plastid origin is an ancient event that involved a prokaryotic symbiont and a eukaryotic host, organisms with different histories and genome evolutionary processes. The different modes of genome evolution in prokaryotes and eukaryotes bear upon our interpretations of plastid phylogeny.
The DNA microarray technology delivers an experimental tool that allows survey­ing expression of genetic information on a genome-wide scale at the level of single genes — for the new field termed functional genomics. Gene expression profiling — the primary application of DNA microarrays technology — generates monumental amounts of information concerning the functioning of genes, cells and organisms. However, the expression of genetic information is regulated by a number of factors that cannot be directly targeted by standard gene expression profiling. The genetic material of eukaryotic cells is packed into chromatin which provides the compaction and organization of DNA for replication, repair and recombination processes, and is the major epigenetic factor determining the expression of genetic information. Genomic DNA can be methylated and this modification modulates interactions with proteins which change the functional status of genes. Both chromatin structure and transcriptional activity are affected by the processes of replication, recombination and repair. Modified DNA microarray technology could be applied to genome-wide study of epigenetic factors and processes that modulate the expression of genetic in­formation. Attempts to use DNA microarrays in studies of chromatin packing state, chromatin/DNA-binding protein distribution and DNA methylation pattern on a ge­nome-wide scale are briefly reviewed in this paper.
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