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The SARS-CoV-2 (COVID-19) pandemic is a global crisis that threatens our way of life. As of November 18, 2020, SARS-CoV-2 has claimed more than 1,342,709 lives, with a global mortality rate of ~2.4% and a recovery rate of ~69.6%. Understanding the interaction of cellular targets with the SARS-CoV-2 infection is crucial for therapeutic development. Therefore, the aim of this study was to perform a comparative analysis of transcriptomic signatures of infection of SARS-CoV-2 compared to other respiratory viruses (EBOV, H1N1, MERS-CoV, and SARS-CoV), to determine a unique anti-SARS-CoV-2 gene signature. We identified for the first time that molecular pathways for heparin-binding, RAGE, miRNA, and PLA2 inhibitors were associated with SARS-CoV-2 infection. The NRCAM and SAA2 genes, which are involved in severe inflammatory responses, and the FGF1 and FOXO1 genes, which are associated with immune regulation, were found to be associated with the cellular gene response to SARS-CoV-2 infection. Moreover, several cytokines, most significantly IL-8 and IL-6 , demonstrated key associations with SARS-CoV-2 infection. Interestingly, the only response gene that was shared among the five viral infections was SERPINB1 . The protein-protein interaction (PPI) analysis shed light on genes with high interaction activity that SARS-CoV-2 shares with other viral infections. The findings showed that the genetic pathways associated with rheumatoid arthritis, the AGE-RAGE signaling system, malaria, hepatitis B, and influenza A were of high significance. We found that the virogenomic transcriptome of infection, gene modulation of host antiviral responses, and GO terms of SARS-CoV-2 and EBOV were more similar than to SARS, H1N1, and MERS. This work compares the virogenomic signatures of highly pathogenic viruses and provides valid targets for potential therapy against SARS-CoV-2.

Environmental stresses, particularly drought, limit symbiotic nitrogen fixation in legumes, resulting in decreased yielding capacity. Drought is one of the most important constraints limiting yield potential in crops and it is the major abiotic stress that can cause more than 70% yield loss in chickpea. In this study, a total of two hundred four chickpea ( Cicer arietinum L.) genotypes were selected to study the interaction between drought stress and nodule formation. This interaction was assessed by using morphological, yield and yield components. The field experiments were laid out in two locations (Terbol and Kfardan stations, Bekaa valley, Lebanon) using Alpha lattice design with two replications and two watering treatments (irrigation and rainfed) during 2016 and 2017 seasons. Parameters that were measured include days to 50% flowering (DFL), day to maturity (DM), plant height (PLH), nodule biomass (NB), nodule fresh weight (NFW), nodule dry weight (NDW), grain yield (GY), Biological yield (BY), 100 seed weight (100SW) and drought tolerance stress (DTS). The results indicated a significant variation between genotypes, environments and other morphological, yield and yield components traits. Drought stress reduced significantly the yield and the nodule’s characteristics, biological and grain yield. The genotypes with the highest levels of drought tolerance, such as IG70399, IG8256, IG71832, IG70270, and IG70272, showed a minimal decrease in yield and nodule biomass. Nodule observations significantly and positively correlated with GY (0.36-0.38) under drought stress treatment. The correlation values for nodule characteristics with DFL and DM were higher under drought stress compared to irrigated conditions. This is a comparative study between drought stress and nodule formation traits associated with morphological, yield and yield components traits.

Recently, Cicer species have experienced increased research interest due to their economic importance, especially in genetics, genomics, and crop improvement. The Cicer arietinum , Cicer reticulatum , and Cicer echinospermum genomes have been sequenced and provide valuable resources for trait improvement. Since the publication of the chickpea draft genome, progress has been made in genome assembly, functional annotation, and identification of polymorphic markers. However, work is still needed to identify transposable elements (TEs) and make them available for researchers. In this paper, we present CicerSpTEdb, a comprehensive TE database for Cicer species that aims to improve our understanding of the organization and structural variations of the chickpea genome. Using structure and homology-based methods, 3942 C . echinospermum , 3579 C . reticulatum , and 2240 C . arietinum TEs were identified. Comparisons between Cicer species indicate that C . echinospermum has the highest number of LTR-RT and hAT TEs. C . reticulatum has more Mutator, PIF Harbinger, Tc1 Mariner, and CACTA TEs, while C . arietinum has the highest number of Helitron. CicerSpTEdb enables users to search and visualize TEs by location and download their results. The database will provide a powerful resource that can assist in developing TE target markers for molecular breeding and answer related biological questions. Database URL: http://cicersptedb.easyomics.org/index.php

Next-generation sequencing technologies have opened new avenues for using genomic data to study and develop molecular markers and improve genetic resources. Simple Sequence Repeats (SSRs) as genetic markers are increasingly used in molecular diversity and molecular breeding programs that require bioinformatics pipelines to analyze the large amounts of data. Therefore, there is an ongoing need for online tools that provide computational resources with minimal effort and maximum efficiency, including automated development of SSR markers. These tools should be flexible, customizable, and able to handle the ever-increasing amount of genomic data. Here we introduce MegaSSR (https://bioinformatics.um6p.ma/MegaSSR), a web server and a standalone pipeline that enables the design of SSR markers in any target genome. MegaSSR allows users to design targeted PCR-based primers for their selected SSR repeats and includes multiple tools that initiate computational pipelines for SSR mining, classification, comparisons, PCR primer design, in silico PCR validation, and statistical visualization. MegaSSR results can be accessed, searched, downloaded, and visualized with user-friendly web-based tools. These tools provide graphs and tables showing various aspects of SSR markers and corresponding PCR primers. MegaSSR will accelerate ongoing research in plant species and assist breeding programs in their efforts to improve current genomic resources.

Multiple sequence alignment (MSA) is essential for understanding genetic variations controlling phenotypic traits in all living organisms. The post-analysis of MSA results is a difficult step for researchers who do not have programming skills. Especially those working with large scale data and looking for potential variations or variable sample groups. Generating bi-allelic data and the comparison of wild and alternative gene forms are important steps in population genetics. Customising MSA visualisation for a single page view is difficult, making viewing potential indels and variations challenging. There are currently no bioinformatics tools that permit post-MSA analysis, in which data on gene and single nucleotide scales could be combined with gene annotations and used for cluster analysis. We introduce “AlignStatPlot,” a new R package and online tool that is well-documented and easy-to use for MSA and post-MSA analysis. This tool performs both traditional and cutting-edge analyses on sequencing data and generates new visualisation methods for MSA results. When compared to currently available tools, AlignStatPlot provides a robust ability to handle and visualise diversity data, while the online version will save time and encourage researchers to focus on explaining their findings. It is a simple tool that can be used in conjunction with population genetics software.

LTR-retrotransposons (LTR-RTs) are a large group of transposable elements that replicate through an RNA intermediate and alter genome structure. The activities of LTR-RTs in plant genomes provide helpful information about genome evolution and gene function. LTR-RTs near or within genes can directly alter gene function. This work introduces PlantLTRdb, an intact LTR-RT database for 195 plant species. Using homology- and de novo structure-based methods, a total of 150.18 Gbp representing 3,079,469 pseudomolecules/scaffolds were analyzed to identify, characterize, annotate LTR-RTs, estimate insertion ages, detect LTR-RT-gene chimeras, and determine nearby genes. Accordingly, 520,194 intact LTR-RTs were discovered, including 29,462 autonomous and 490,732 nonautonomous LTR-RTs. The autonomous LTR-RTs included 10,286 Gypsy and 19,176 Copia , while the nonautonomous were divided into 224,906 Gypsy , 218,414 Copia , 1,768 BARE-2, 3,147 TR-GAG and 4,2497 unknown. Analysis of the identified LTR-RTs located within genes showed that a total of 36,236 LTR-RTs were LTR-RT-gene chimeras and 11,619 LTR-RTs were within pseudo-genes. In addition, 50,026 genes are within 1 kbp of LTR-RTs, and 250,587 had a distance of 1 to 10 kbp from LTR-RTs. PlantLTRdb allows researchers to search, visualize, BLAST and analyze plant LTR-RTs. PlantLTRdb can contribute to the understanding of structural variations, genome organization, functional genomics, and the development of LTR-RT target markers for molecular plant breeding. PlantLTRdb is available at https://bioinformatics.um6p.ma/PlantLTRdb .

Chickpea, renowned for its exceptional nutritional value, stands as a crucial crop, serving as a dietary staple in various parts of the world. However, its productivity faces a significant challenge in the form of drought stress. This challenge highlights the urgent need to find genetic markers linked to drought tolerance for effective breeding programs. The primary objective of this study is to identify genetic markers associated with drought tolerance to facilitate effective breeding programs. To address this, we cultivated 185 chickpea accessions in two distinct locations in Lebanon over a two-year period, subjecting them to both irrigated and rain-fed environments. We assessed 11 drought-linked traits, including morphology, growth, yield, and tolerance score. SNP genotyping revealed 1344 variable SNP markers distributed across the chickpea genome. Genetic diversity across populations originating from diverse geographic locations was unveiled by the PCA, clustering, and structure analysis indicating that these genotypes have descend from five or four distinct ancestors. A genome-wide association study (GWAS) revealed several marker trait associations (MTAs) associated with the traits evaluated. Within the rainfed conditions, 11 significant markers were identified, each associated with distinct chickpea traits. Another set of 11 markers exhibited associations in both rainfed and irrigated environments, reflecting shared genetic determinants across these conditions for the same trait. The analysis of linkage disequilibrium (LD) highlighted two genomic regions with notably strong LD, suggesting significant interconnections among several investigated traits. This was further investigated by the correlation between major markers associated with these traits. Gene annotation of the identified markers has unveiled insights into 28 potential genes that play a role in influencing various chickpea drought-linked traits. These traits encompass crucial aspects such as blooming organ development, plant growth, seed weight, starch metabolism, drought regulation, and height index. Among the identified genes are CPN60-2 , hsp70 , GDSL(GELP) , AHL16 , NAT3 , FAB1B , bZIP , and GL21 . These genes collectively contribute to the multifaceted response of chickpea plants to drought stress. Our identified genetic factors exert their influence in both irrigated and rainfed environments, emphasizing their importance in shaping chickpea characteristics.

Chickpea (* ) is an important pulse crop mainly grown in marginal lands around the world. Drought stress highly impacts symbiotic nitrogen fixation (SNF) in chickpeas, which can limit productivity. Therefore, selecting high nitrogen fixation chickpea genotypes that can tolerate water stress is important for breeding programs. A total of 204 chickpea genotypes were assessed in eight different environments across Lebanon during the 2016 and 2017 growing seasons, under both rainfed and irrigated conditions. The study employed an Alpha Lattice design with two replications at two distinct locations. Data were collected for yield and nodule characteristics, then subjected to AMMI and GGE biplot analysis. The AMMI analysis indicated that genotype (G), environments (E), and genotype × environment interaction (GEI) had significant effects on grain yield (P<0.001), highlighting the presence of genetic variation and the potential for selecting stable genotypes. The findings revealed that the environmental effect predominantly influenced chickpea grain yield, with GEI following, and G having the least impact. Environment explained 34.5% of the total (G + E + GE) variation, whereas G and GEI captured 16.4% and 24.3%, respectively. According to grain yield (GY), genotype IG70399 demonstrated the highest performance across all environments, while genotype IG8256 displayed the most consistent performance across different conditions. In a rainfed environment, genotype IG73394 had higher nodulation, while IG70384 and IG70410 had higher nodulation biomass (NB) under an irrigated environment. The NB for ten highly tolerant genotypes increased by 24% compared to the two susceptible genotypes under drought stress conditions, while the NB for these ten genotypes increased by 14.6% compared to all studied genotypes.

The study investigated subtropical Egyptian goat populations (382 does) from different hot dry ecological zones (Upper Egypt, Coastal Zone of Western Desert, and New Valley Desert Oasis) to identify genes associated with tolerance to heat stress. Animals were encouraged to walk for 7 km under direct solar radiation from 12:00 to 14:00 pm in July and August (imitating summer grazing on poor pasture under hot dry conditions). Temperature Humidity Index (THI) ranged from 98.6 to 109.3, indicating that the animals were under severe heat stress. Physiological parameters were measured at rest (7:00 am) and after exposure to heat stress (14.00 pm). Animal heat tolerant index (AHTI) was estimated from their response in the four main physiological parameters ranged from (0: high tolerant to 4: low tolerant). The GWAS analysis revealed 90 marker SNPs associated with heat stress in 108 genotypes of Egyptian goat. Ninety markers are found in forty-seven distinct genes distributed across the genome. In terms of the markers (SNPs) that have direct effect on these traits via homozygous alleles, twenty-eight SNPs are connected to heat stress. The snpeff approach revealed that KDM6A, TRPM3, USP54, GLTSCR2, NAALADL2, GATAD2A, CTNNA2, LOC102175876, ZBTB8A, ETNPPL, LRRC43, SNTB1, RPS6KA5, and ARHGAP26 genes influence tolerance to heat stress. These genes offer crucial insights into the biological mechanisms that enhance resilience to elevated temperature conditions. The studied subtropical Egyptian goat breeds showed a high ability to tolerate heat stress and identifying these genomic loci can be utilized to monitor and control tolerance of subtropical goat to heat stress, while maintaining their production performance.

Background Monkeypox (Mpox) is an important human pathogen without etiological treatment. A viral-host interactome study may advance our understanding of molecular pathogenesis and lead to the discovery of suitable therapeutic targets. Methods GEO Expression datasets characterizing mRNA profile changes in different host responses to poxviruses were analyzed for shared pathway identification, and then, the Protein–protein interaction (PPI) maps were built. The viral gene expression datasets of Monkeypox virus (MPXV) and Vaccinia virus (VACV) were used to identify the significant viral genes and further investigated for their binding to the library of targeting molecules. Results Infection with MPXV interferes with various cellular pathways, including interleukin and MAPK signaling. While most host differentially expressed genes (DEGs) are predominantly downregulated upon infection, marked enrichments in histone modifiers and immune-related genes were observed. PPI analysis revealed a set of novel virus-specific protein interactions for the genes in the above functional clusters. The viral DEGs exhibited variable expression patterns in three studied cell types: primary human monocytes, primary human fibroblast, and HeLa, resulting in 118 commonly deregulated proteins. Poxvirus proteins C6R derived protein K7 and K7R of MPXV and VACV were prioritized as targets for potential therapeutic interventions based on their histone-regulating and immunosuppressive properties. In the computational docking and Molecular Dynamics (MD) experiments, these proteins were shown to bind the candidate small molecule S3I-201, which was further prioritized for lead development. Results MPXV circumvents cellular antiviral defenses by engaging histone modification and immune evasion strategies. C6R-derived protein K7 binding candidate molecule S3I-201 is a priority promising candidate for treating Mpox.