Notes

Phylogenetic indication inside the vocalizations of oral learning along with expressive non-learning parrots.
The swamp buffalo is a domesticated animal commonly found in Southeast Asia. It is a highly valued agricultural animal for smallholders, but the production of this species has unfortunately declined in recent decades due to rising farm mechanization. While swamp buffalo still plays a role in farmland cultivation, this species' purposes has shifted from draft power to meat, milk, and hide production. The current status of swamp buffaloes in Southeast Asia is still understudied compared to its counterparts such as the riverine buffaloes and cattle. This review discusses the background of swamp buffalo, with an emphasis on recent work on this species in Southeast Asia, and associated genetics and genomics work such as cytogenetic studies, phylogeny, domestication and migration, genetic sequences and resources. Recent challenges to realize the potential of this species in the agriculture industry are also discussed. Limited genetic resource for swamp buffalo has called for more genomics work to be done on this species including decoding its genome. As the economy progresses and farm mechanization increases, research and development for swamp buffaloes are focused on enhancing its productivity through understanding the genetics of agriculturally important traits. The use of genomic markers is a powerful tool to efficiently utilize the potential of this animal for food security and animal conservation. Understanding its genetics and retaining and maximizing its adaptability to harsher environments are a strategic move for food security in poorer nations in Southeast Asia in the face of climate change.Networks are powerful tools to represent and investigate biological systems. The development of algorithms inferring regulatory interactions from functional genomics data has been an active area of research. With the advent of single-cell RNA-seq data (scRNA-seq), numerous methods specifically designed to take advantage of single-cell datasets have been proposed. However, published benchmarks on single-cell network inference are mostly based on simulated data. Once applied to real data, these benchmarks take into account only a small set of genes and only compare the inferred networks with an imposed ground-truth. check details Here, we benchmark six single-cell network inference methods based on their reproducibility, i.e., their ability to infer similar networks when applied to two independent datasets for the same biological condition. We tested each of these methods on real data from three biological conditions human retina, T-cells in colorectal cancer, and human hematopoiesis. Once taking into account networks with up to 100,000 links, GENIE3 results to be the most reproducible algorithm and, together with GRNBoost2, show higher intersection with ground-truth biological interactions. These results are independent from the single-cell sequencing platform, the cell type annotation system and the number of cells constituting the dataset. Finally, GRNBoost2 and CLR show more reproducible performance once a more stringent thresholding is applied to the networks (1,000-100 links). In order to ensure the reproducibility and ease extensions of this benchmark study, we implemented all the analyses in scNET, a Jupyter notebook available at https//github.com/ComputationalSystemsBiology/scNET.In less then 20 years, we have witnessed three different epidemics with coronaviruses, SARS-CoV, MERS-CoV, and SARS-CoV-2 in human populations, causing widespread mortality. SARS-CoV-2, through its rapid global spread, has led to the pandemic that we call COVID-19. As of February 1, 2021, the global infections linked to SARS-CoV-2 stand at 103,503,340, with 2,236,960 deaths, and 75,108,099 recoveries. This review attempts to highlight host-pathogen interaction with particular emphasis on the role of epigenetic machinery in regulating the disease. Although researchers, since the start of the pandemic, have been intensely engaged in diverse areas to understand the mechanisms involved in SARS-CoV-2 infection to find answers that can bring about innovative ways to swiftly treat and prevent disease progression, this review provides an overview on how the host epigenetics is modulated and subverted by SARS-CoV-2 to enter the host cells and drive immunopathogenesis. Epigenetics is the study that combines genetic anertinent to SARS-CoV-2, which has been published between 2019 and 2020 to showcase the current knowledge both in terms of success and failures and take lessons that will assist us in understanding the disease to develop better treatments suited to kill SARS-CoV-2.Portulaca oleracea L. (known as purslane) is one of the most nutritious leafy vegetables owing to its high content of antioxidants. In this study, all plants were grown indoors hydroponically with different NaCl salinities. Photosynthetic photo flux density (PPFD) at 200 μmol m-2 s-1 (12 h) was provided to all plants by LED with redblue ratio of 2.2. Thirty days after transplanting, plants grown with100 mM NaCl had the highest productivity and the fastest leaf growth followed by those with 0, 200 and 300 mM NaCl. Grown with 300 mM NaCl, purslane had the lowest specific leaf area due to its highest leaf dry matter content and its lowest water content. All plants had similar values of leaf succulence except for those with 300 mM NaCl. Total chlorophyll and carotenoids contents were significantly higher in plants grown with 0 and 100 mM NaCl than with 200, and 300 mM NaCl. All plants had Fv/Fm ratios close to 0.8. However, electron transport rate and ΔF/Fm' were significantly higher in plants grown with 0 and 10uctivity and better quality. However, the production of antioxidants may depend on not only salinity but also other growth conditions.Photosynthates such as glucose, sucrose, and some of their derivatives play dual roles as metabolic intermediates and signaling molecules that influence plant cell metabolism. Such sugars provide substrates for de novo fatty acid (FA) biosynthesis. However, compared with the well-defined examples of sugar signaling in starch and anthocyanin synthesis, until recently relatively little was known about the role of signaling in regulating FA and lipid biosynthesis. Recent research progress shows that trehalose 6-phosphate and 2-oxoglutarate (2-OG) play direct signaling roles in the regulation of FA biosynthesis by modulating transcription factor stability and enzymatic activities involved in FA biosynthesis. Specifically, mechanistic links between sucrose non-fermenting-1-related protein kinase 1 (SnRK1)-mediated trehalose 6-phosphate (T6P) sensing and its regulation by phosphorylation of WRI1 stability, diacylglycerol acyltransferase 1 (DGAT1) enzyme activity, and of 2-OG-mediated relief of inhibition of acetyl-CoA carboxylase (ACCase) activity by protein PII are exemplified in detail in this review.
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