Jagajjit Sahu

(1) Background: To assess the genetic makeup among the agro-economically important members of Euphorbiaceae, the present study was conducted to identify and characterize high-quality single-nucleotide polymorphism (SNP) markers and their comparative distribution in exonic and intronic regions from the publicly available expressed sequence tags (ESTs). (2) Methods: Quality sequences obtained after pre-processing by an EG assembler were assembled into contigs using the CAP3 program at 95% identity; the mining of SNP was performed by QualitySNP; GENSCAN (standalone) was used for detecting the distribution of SNPs in the exonic and intronic regions. (3) Results: A total of 25,432 potential SNPs (pSNP) and 14,351 high-quality SNPs (qSNP), including 2276 indels, were detected from 260,479 EST sequences. The ratio of quality SNP to potential SNP ranged from 0.22 to 0.75. A higher frequency of transitions and transversions was observed more in the exonic than the intronic region, while indels were present more in the intronic region. C↔T (transition) was the most dominant nucleotide substitution, while in transversion, A↔T was the dominant nucleotide substitution, and in indel, A/- was dominant. (4) Conclusions: Detected SNP markers may be useful for linkage mapping; marker-assisted breeding; studying genetic diversity; mapping important phenotypic traits, such as adaptation or oil production; or disease resistance by targeting and screening mutations in important genes.

Male infertility is a global public health concern. Teratozoospermia is a qualitative anomaly of spermatozoa morphology, contributing significantly to male infertility, whereas azoospermia is the complete absence of spermatozoa in the ejaculate. Thus, there is a serious need for unveiling the common origin and/or connection between both of these diseases, if any. This study aims to identify common potential biomarker genes of these two diseases via an in silico approach using a meta-analysis of microarray data. In this study, a differential expression analysis of genes was performed on four publicly available RNA microarray datasets, two each from teratozoospermia (GSE6872 and GSE6967) and azoospermia (GSE145467 and GSE25518). From the analysis, 118 DEGs were found to be common to teratozoospermia and azoospermia, and, interestingly, sperm autoantigenic protein 17 (SPA17) was found to possess the highest fold change value among all the DEGs (9.471), while coiled-coil domain-containing 90B (CCDC90B) and coiled-coil domain-containing 91 (CCDC91) genes were found to be common among three of analyses, i.e., Network Analyst, ExAtlas, and GEO2R. This observation indicates that SPA17, CCDC90B, and CCDC91 genes might have significant roles to play as potential biomarkers for teratozoospermia and azoospermia. Thus, our study opens a new window of research in this area and can provide an important theoretical basis for the diagnosis and treatment of both these diseases.

The complexity of data has burgeoned to such an extent that scientists of every realm are encountering the incessant challenge of data management. Modern-day analytical approaches with the help of free source tools and programming languages have facilitated access to the context of the various domains as well as specific works reported. Here, with this article, an attempt has been made to provide a systematic analysis of all the available reports at PubMed on Proteome using text mining. The work is comprised of scientometrics as well as information extraction to provide the publication trends as well as frequent keywords, bioconcepts and most importantly gene–gene co-occurrence network. Out of 33,028 PMIDs collected initially, the segregation of 24,350 articles under 28 Medical Subject Headings (MeSH) was analyzed and plotted. Keyword link network and density visualizations were provided for the top 1000 frequent Mesh keywords. PubTator was used, and 322,026 bioconcepts were able to extracted under 10 classes (such as Gene, Disease, CellLine, etc.). Co-occurrence networks were constructed for PMID-bioconcept as well as bioconcept–bioconcept associations. Further, for creation of subnetwork with respect to gene–gene co-occurrence, a total of 11,100 unique genes participated with mTOR and AKT showing the highest (64) number of connections. The gene p53 was the most popular one in the network in accordance with both the degree and weighted degree centrality, which were 425 and 1414, respectively. The present piece of study is an amalgam of bibliometrics and scientific data mining methods looking deeper into the whole scale analysis of available literature on proteome.

Foraging disruption caused by human activities is emerging as a key issue in cetacean conservation because it can affect nutrient levels and the amount of energy available to individuals to invest into reproduction. Our ability to predict how anthropogenic stressors affect these ecological processes and ultimately population trajectory depends crucially on our understanding of the complex physiological mechanisms that detect nutrient availability and regulate energy metabolism, foraging behavior and life-history decisions. These physiological mechanisms are likely to differ considerably from terrestrial mammalian model systems. Here, we examine nucleotide substitution rates in cetacean and other artiodactyl genomes to identify signatures of selection in genes associated with nutrient sensing pathways. We also estimated the likely physiological consequences of adaptive amino acid substitutions for pathway functions. Our results highlight that genes involved in the insulin, mTOR and NF-ĸB pathways are subject to significant positive selection in cetaceans compared to terrestrial artiodactyla. These genes may have been positively selected to enable cetaceans to adapt to a glucose-poor diet, to overcome deleterious effects caused by hypoxia during diving (e.g. oxidative stress and inflammation) and to modify fat-depot signaling functions in a manner different to terrestrial mammals. We thus show that adaptation in cetaceans to an aquatic lifestyle significantly affected functions in nutrient sensing pathways. The use of fat stores as a condition index in cetaceans may be confounded by the multiple and critical roles fat has in regulating cetacean metabolism, foraging behavior and diving physiology.

Plants inherently show resistance to pathogen attack but are susceptible to multiple bacteria, viruses, fungi, and phytoplasmas. Diseases as a result of such infection leads to the deterioration of crop yield. Several pathogen-sensitive gene activities, promoters of such genes, associated transcription factors, and promoter elements responsible for crosstalk between the defense signaling pathways are involved in plant resistance towards a pathogen. Still, only a handful of genes and their promoters related to plant resistance have been identified to date. Such pathogen-sensitive promoters are accountable for elevating the transcriptional activity of certain genes in response to infection. Also, a suitable promoter is a key to devising successful crop improvement strategies as it ensures the optimum expression of the required transgene. The study of the promoters also helps in mining more details about the transcription factors controlling their activities and helps to unveil the involvement of new genes in the pathogen response. Therefore, the only way out to formulate new solutions is by analyzing the molecular aspects of these promoters in detail. In this review, we provided an overview of the promoter motifs and cis-regulatory elements having specific roles in pathogen attack response. To elaborate on the importance and get a vivid picture of the pathogen-sensitive promoter sequences, the key motifs and promoter elements were analyzed with the help of PlantCare and interpreted with available literature. This review intends to provide useful information for reconstructing the gene networks underlying the resistance of plants against pathogens.