Search

This study was conducted at Crop Research Farm, Nawabganj, C. S. Azad University of Agriculture and Technology, Kanpur (U. P.) during rabi 2021-22 for estimating the components of variance and other genetic parameters through 8 x 8 parent diallel cross excluding reciprocals for 11 characters in bread wheat. The variance component analysis indicated significant role of additive (D^) and dominant (H^1 and H^2) genetic components for all the traits viz., days to 75% heading, days to maturity, plant height (cm), number of productive tillers per plant, spike length (cm), number of grains per spike, biological yield per plant (g), harvest index (%) and grain yield per plant (g) except additive component for 1000-grain weight (2.60) and dominant component for number of spikelets per spike (2.91 and 2.53). The estimates of dominant components (H^1 and H^2) were mostly greater than additive component (D^) for all the characters indicating the greater role of non-additive gene action in the expression of attributes. The relative magnitudes of H^1 component were higher than H^2 component for all the characters except spike length (0.39) indicating unequal distribution of positive and negative alleles in the parent. Over dominance expression for all the attributes was due to the involvement of asymmetrical distribution of dominant genes with positive and negative effects in the parents for all the characters except spike length. Based on study, it was revealed that both additive and non-additive genes were responsible for expression of almost major of the traits. [ABSTRACT FROM AUTHOR]

The topological characteristics of biological networks enable us to identify the key nodes in terms of modularity. However, due to a large size of the biological networks with many hubs and functional modules across intertwined layers within the network, it often becomes difficult to accomplish the task of identifying potential key regulators. We use for the first time a generalized formalism of Hamiltonian Energy (HE) with a recursive approach. The concept, when applied to the Apoptosis Regulatory Gene Network (ARGN), helped us identify 11 Motif hubs (MHs), which influenced the network up to motif levels. The approach adopted allowed to classify MHs into 5 significant motif hubs (S-MHs) and 6 non-significant motif hubs (NS-MHs). The significant motif hubs had a higher HE value and were considered as high-active key regulators; while the non-significant motif hubs had a relatively lower HE value and were considered as low-active key regulators, in network control mechanism. Further, we compared the results of the HE analyses with the topological characterization, after subjecting to the three conditions independently: (i) removing all MHs, (ii) removing only S-MHs, and (iii) removing only NS-MHs from the ARGN. This procedure allowed us to cross-validate the role of 5 S-MHs, NFk-B1, BRCA1, CEBPB, AR, and POU2F1 as the potential key regulators. The changes in HE calculations further showed that the removal of 5 S-MHs could cause perturbation at all levels of the network, a feature not discernible by topological analysis alone. [ABSTRACT FROM AUTHOR]

The breast cancer network constructed from 70 experimentally verified genes is found to follow hierarchical scale free nature with heterogeneous modular organization and diverge leading hubs. The topological parameters (degree distributions, clustering co-efficient, connectivity and centralities) of this network obey fractal rules indicating absence of centrality lethality rule, and efficient communication among the components. From the network theoretical approach, we identified few key regulators out of large number of leading hubs, which are deeply rooted from top to down of the network, serve as backbone of the network, and possible target genes. However, p53, which is one of these key regulators, is found to be in low rank and keep itself at low profile but directly cross-talks with important genes BRCA2 and BRCA3. The popularity of these hubs gets changed in unpredictable way at various levels of organization thus showing disassortive nature. The local community paradigm approach in this network shows strong correlation of nodes in majority of modules/sub-modules (fast communication among nodes) and weak correlation of nodes only in few modules/sub-modules (slow communication among nodes) at various levels of network organization. [ABSTRACT FROM AUTHOR]

The article focuses on the comparison of the expression of embryonic developmental related genes in different stages of haploid and diploid parthenogenetic embryos in goat. The authors' study involved aspiration of good quality oocytes from the ovary that was then matured in a maturation medium without or with cytochalasin B. Based on the study's result, they conclude that there was undetectable level of embryonic developmental related genes in haploid parthenogenetic embryos.

DNA methylation affects important developmental processes in both plants and animals. The process of methylation of cytosines at C-5 is catalysed by DNA methyltransferases (MTases), which are highly conserved, both structurally and functionally, in eukaryotes. In this study, we identified and characterized cytosine DNA MTase genes that are activated with the onset of reproductive development in rice. The rice genome ( Oryza sativa L. subsp. japonica) encodes a total of 10 genes that contain the highly conserved MTase catalytic domain. These genes have been categorized into subfamilies on the basis of phylogenetic relationships. A microarray-based gene expression profile of all 10 MTases during 22 stages/tissues that included 14 stages of reproductive development and five vegetative tissues together with three stresses, cold, salt and dehydration stress, revealed specific windows of MTase activity during panicle and seed development. The expression of six methylases was specifically/preferentially upregulated with the initiation of floral organs. Significantly, one of the MTases was also activated in young seedlings in response to cold and salt stress. The molecular studies presented here suggest a greater role for these proteins and the epigenetic process in affecting genome activity during reproductive development and stress than was previously anticipated. [ABSTRACT FROM AUTHOR]

Identification of key regulators and regulatory pathways is an important step in the discovery of genes involved in cancer. Here, we propose a method to identify key regulators in prostate cancer (PCa) from a network constructed from gene expression datasets of PCa patients. Overexpressed genes were identified using BioXpress, having a mutational status according to COSMIC, followed by the construction of PCa Interactome network using the curated genes. The topological parameters of the network exhibited power law nature indicating hierarchical scale-free properties and five levels of organization. Highest degree hubs (k ≥ 65) were selected from the PCa network, traced, and 19 of them was identified as novel key regulators, as they participated at all network levels serving as backbone. Of the 19 hubs, some have been reported in literature to be associated with PCa and other cancers. Based on participation coefficient values most of these are connector or kinless hubs suggesting significant roles in modular linkage. The observation of non-monotonicity in the rich club formation suggested the importance of intermediate hubs in network integration, and they may play crucial roles in network stabilization. The network was self-organized as evident from fractal nature in topological parameters of it and lacked a central control mechanism. [ABSTRACT FROM AUTHOR]