Integrating Association Mapping, Linkage Mapping, Fine Mapping with RNA Seq Conferring Seedling Vigor Improvement for Successful Crop Establishment in Deep Sown Direct-Seeded Rice

Background: Ongoing large-scale shift towards direct seeded rice (DSR) necessitates a convergence of breeding and genetic approaches for its sustenance and harnessing natural resources and environmental benefits. Improving seedling vigour remains key objective for breeders working with DSR. The present study aims to understand the genetic control of seedling vigour in deep sown DSR. Combined genome-wide association mapping, linkage mapping, fine mapping, RNA-sequencing to identify candidate genes and validation of putative candidate genes were performed in the present study. Results: Significant phenotypic variations were observed among genotypes in both F3:4:5 and BC2F2:3 populations. The mesocotyl length showed significant positive correlation with %germination, root and shoot length. The 881 kb region on chromosome 7 reported to be associated with mesocotyl elongation. RNA-seq data and RT-PCR results identified and validated seven potential candidate genes. The four promising introgression lines free from linkage drag and with longer mesocotyl length, longer root length, semi-dwarf plant height have been identified. Conclusion: The study will provide rice breeders (1) the pre breeding material in the form of anticipated DSR adapted introgression lines possessing useful traits and alleles improving germination under deep sown DSR field conditions (2) the base for the studies involving functional characterization of candidate genes. The development and utilization of improved introgression lines and molecular markers may play an important role in genomics-assisted breeding (GAB) during the pyramiding of valuable genes providing adaptation to rice under DSR. Our results offer a robust and reliable package that can contribute towards enhancing genetic gains in direct seeded rice breeding programs

Minimizing Liability of the COVID-19 Pandemic on Construction Contracts—A Structural Equation Model for Risk Mitigation of Force Majeure Impacts

A pandemic is a force majeure event, and contracting parties can invoke conditions under force majeure to minimize liability for unforeseen, uncontrollable, and unavoidable circumstances. This study develops a conceptual model to assist in the management of delays and cost overruns due to force majeure events arising from the construction sector in Small Island Developing States (SIDS). A critical case study analysis of past epidemics and pandemics was conducted to develop a survey questionnaire for administration to construction professionals in Trinidad and Tobago. Based on the empirical data of 65 construction professionals, the structural equation model shows that there are strong causal effects from the implications of COVID-19 and force majeure events, which in turn have a dire impact on the construction industry. The leading implication of COVID-19 is the drastic increases in the cost of materials. Also, granting an extension of time to contractors was the main risk variable under the force majeure conditions. From the results, the measurement model verifies that events under force majeure and its perceived implications strongly influence the construction industry, and proposes that force majeure contractual clauses require explicit treatment of the periodic reoccurrence of pandemics to avoid conflicts among contracting parties. This research explores and builds on new avenues from the latest COVID-19 scholarship to better understand existing impacts on the construction industry, and consequently add to the novel body of knowledge on the implications of pandemics on construction contracts. Overall, this research provides a risk-guidance framework for construction professionals and academia to mitigate unforeseen, uncontrollable, and unavoidable risks on construction projects

FOREST CANOPY DENSITY ASSESSMENT USING HIGH RESOLUTION LISS-4 DATA IN YAMUNANAGAR DISTRICT, HARYANA

Forest plays an important role not only in providing ecological services but also economic goods to human beings. However, with increase in population there is a wide gap between demand and supply of these goods and services. This has lead to reduction in forest cover which needs to be taken care on regular time interval. To manage the existing forest area and also to increase the forest cover Forest Canopy Density (FCD) methodology is the main factor which was given by International Tropical timber Organization (ITTO). High resolution remote sensing LISS-4 data gives us chance to assess the quality of forest in terms of FCD as Rikimaru et al (1999) stated that FCD is one important parameter to assess forest cover quality. High resolution LISS-4 data analysis for FCD was never attempted before. Authors here attempted to assess the FCD utilizing methodology adopted by Rikimaru (1999), Huang (2001), Azizia (2008). The adopted methodology is one of the most efficient and cost effective way to derive the FCD. For this study Resourcesat-2 LISS-4 post monsoon data of year 2017 for Yamunanagar district was used to assess FCD within notified forest boundary. Notified forest boundaries at cadastral level prepared previously by Haryana Space Applications Centre (HARSAC) was used. The degree of forest canopy density is expressed in percentages: i.e. < 10% FCD (scrub land), 10–20% (Open Forest-I), 20–40% (Open Forest-II), 40–60% (Moderate Dense), 60–80% (Medium Dense) and > 80% (Highly Dense). Forest Canopy Density was based on three indices i.e. Advanced Vegetation Index (AVI), Bare Soil Index (BSI) and Canopy Shadow Index (CSI). Accuracy assessment was done based on ground data and comparison with Coterminous Google Earth imagery and it was found that the devised methodology has achieved overall accuracy of 93% with kappa coefficient of 0.9153. The result shows that maximum forest area in Yamunanagar district is in medium dense FCD category which is approximately 23948.08 acres. This study tells us that 24.2% of the total forest area is under scrub land and open forest which should be focussed for activities in working plan to increase the forest cover. This paper highlights the utility of high resolution satellite data for monitoring and management of forest and improvement in its quality. This attempt provided large scale (1 : 10,000) maps to the forest managers to better equip them in planning for afforestation, reforestation and rehabilitation of water logged areas, environment management and their future aspect

Structural and functional insights into the candidate genes associated with different developmental stages of flag leaf in bread wheat (Triticum aestivum L.)

Grain yield is one of the most important aims for combating the needs of the growing world population. The role of development and nutrient transfer in flag leaf for higher yields at the grain level is well known. It is a great challenge to properly exploit this knowledge because all the processes, starting from the emergence of the flag leaf to the grain filling stages of wheat (Triticum aestivum L.), are very complex biochemical and physiological processes to address. This study was conducted with the primary goal of functionally and structurally annotating the candidate genes associated with different developmental stages of flag leaf in a comprehensive manner using a plethora of in silico tools. Flag leaf-associated genes were analyzed for their structural and functional impacts using a set of bioinformatics tools and algorithms. The results revealed the association of 17 candidate genes with different stages of flag leaf development in wheat crop. Of these 17 candidate genes, the expression analysis results revealed the upregulation of genes such as TaSRT1-5D, TaPNH1-7B, and TaNfl1-2B and the downregulation of genes such as TaNAP1-7B, TaNOL-4D, and TaOsl2-2B can be utilized for the generation of high-yielding wheat varieties. Through MD simulation and other in silico analyses, all these proteins were found to be stable. Based on the outcome of bioinformatics and molecular analysis, the identified candidate genes were found to play principal roles in the flag leaf development process and can be utilized for higher-yield wheat production. Copyright © 2022 Mehla, Kumar, Kapoor, Singh, Sihag, Sagwal, Balyan, Kumar, Ahalawat, Lakra, Singh, Pesic, Djalovic, Mir and Dhankher

Cells activated for wound repair have the potential to direct collective invasion of an epithelium.

Mechanisms regulating how groups of cells are signaled to move collectively from their original site and invade surrounding matrix are poorly understood. Here we develop a clinically relevant ex vivo injury invasion model to determine whether cells involved in directing wound healing have invasive function and whether they can act as leader cells to direct movement of a wounded epithelium through a three-dimensional (3D) extracellular matrix (ECM) environment. Similar to cancer invasion, we found that the injured cells invade into the ECM as cords, involving heterotypical cell-cell interactions. Mesenchymal cells with properties of activated repair cells that typically locate to a wound edge are present in leader positions at the front of ZO-1-rich invading cords of cells, where they extend vimentin intermediate filament-enriched protrusions into the 3D ECM. Injury-induced invasion depends on both vimentin cytoskeletal function and MMP-2/9 matrix remodeling, because inhibiting either of these suppressed invasion. Potential push and pull forces at the tips of the invading cords were revealed by time-lapse imaging, which showed cells actively extending and retracting protrusions into the ECM. This 3D injury invasion model can be used to investigate mechanisms of leader cell-directed invasion and understand how mechanisms of wound healing are hijacked to cause disease

Disruption of Spectrin-Like Cytoskeleton in Differentiating Keratinocytes by PKCδ Activation Is Associated with Phosphorylated Adducin

Spectrin is a central component of the cytoskeletal protein network in a variety of erythroid and non-erythroid cells. In keratinocytes, this protein has been shown to be pericytoplasmic and plasma membrane associated, but its characteristics and function have not been established in these cells. Here we demonstrate that spectrin increases dramatically in amount and is assembled into the cytoskeleton during differentiation in mouse and human keratinocytes. The spectrin-like cytoskeleton was predominantly organized in the granular and cornified layers of the epidermis and disrupted by actin filament inhibitors, but not by anti-mitotic drugs. When the cytoskeleton was disrupted PKCδ was activated by phosphorylation on Thr505. Specific inhibition of PKCδ(Thr505) activation with rottlerin prevented disruption of the spectrin-like cytoskeleton and the associated morphological changes that accompany differentiation. Rottlerin also inhibited specific phosphorylation of the PKCδ substrate adducin, a cytoskeletal protein. Furthermore, knock-down of endogenous adducin affected not only expression of adducin, but also spectrin and PKCδ, and severely disrupted organization of the spectrin-like cytoskeleton and cytoskeletal distribution of both adducin and PKCδ. These results demonstrate that organization of a spectrin-like cytoskeleton is associated with keratinocytes differentiation, and disruption of this cytoskeleton is mediated by either PKCδ(Thr505) phosphorylation associated with phosphorylated adducin or due to reduction of endogenous adducin, which normally connects and stabilizes the spectrin-actin complex

Increased Expression of Fatty-Acid and Calcium Metabolism Genes in Failing Human Heart

Heart failure (HF) involves alterations in metabolism, but little is known about cardiomyopathy-(CM)-specific or diabetes-independent alterations in gene expression of proteins involved in fatty-acid (FA) uptake and oxidation or in calcium-(Ca(2+))-handling in the human heart.RT-qPCR was used to quantify mRNA expression and immunoblotting to confirm protein expression in left-ventricular myocardium from patients with HF (n = 36) without diabetes mellitus of ischaemic (ICM, n = 16) or dilated (DCM, n = 20) cardiomyopathy aetiology, and non-diseased donors (CTL, n = 6).Significant increases in mRNA of genes regulating FA uptake (CD36) and intracellular transport (Heart-FA-Binding Protein (HFABP)) were observed in HF patients vs CTL. Significance was maintained in DCM and confirmed at protein level, but not in ICM. mRNA was higher in DCM than ICM for peroxisome-proliferator-activated-receptor-alpha (PPARA), PPAR-gamma coactivator-1-alpha (PGC1A) and CD36, and confirmed at the protein level for PPARA and CD36. Transcript and protein expression of Ca(2+)-handling genes (Two-Pore-Channel 1 (TPCN1), Two-Pore-Channel 2 (TPCN2), and Inositol 1,4,5-triphosphate Receptor type-1 (IP3R1)) increased in HF patients relative to CTL. Increases remained significant for TPCN2 in all groups but for TPCN1 only in DCM. There were correlations between FA metabolism and Ca(2+)-handling genes expression. In ICM there were six correlations, all distinct from those found in CTL. In DCM there were also six (all also different from those found in CTL): three were common to and three distinct from ICM.DCM-specific increases were found in expression of several genes that regulate FA metabolism, which might help in the design of aetiology-specific metabolic therapies in HF. Ca(2+)-handling genes TPCN1 and TPCN2 also showed increased expression in HF, while HF- and CM-specific positive correlations were found among several FA and Ca(2+)-handling genes

Predictive models for estimation of labyrinth weir aeration efficiency

Purpose: The purpose of the study is to estimate the aeration efficiency (E20) of Labyrinth weir using artificial intelligent (AI)-based models. Design/methodology/approach: The aeration efficiency (E20) was collected by using the nine models of Labyrinth weir with different shapes and dimensions. A total of 180 observations were used out of which 126 used to train the AI-based models and the remaining used to test the model. This observation consists of input variables such as Fraud number (Fr), Reynolds number (Re), numbers of keys (N), the ratio of head to the width of the channel (H/W), the ratio of crest length to width of the channel (L/W), the ratio of drop height to width of the channel (D/W) and shape factor (SF) and E20 as the output variables. The AI-based models used were Fuzzy Logic, multi-linear regression (MLR), adaptive neuro fuzzy interface system (ANFIS), and artificial neural network (ANN). Findings: The main findings of this investigation are that ANN is the best AI-based model that can estimate the E20 accurately than MLR, ANFIS, and Fuzzy Logic. Sensitivity analysis depicts that drop height at labyrinth weir is the essential factors for the estimation of E20; further, parametric studies have also been performed. Research limitations/implications: The proposed AI-based models can be used in the estimation of E20 with different shapes of labyrinth weir but still it needs improvement for the different dimensions. Practical implications: The best AI-based model can be used to calculate the E20 with the different values of input variables. Originality/value: There are no such AI-based models such as ANN, ANFIS, and Fuzzy Logic, available in the literature which can estimate the values of E20 accurately