Background radioactivity level estimation and passive shield optimization using adjoint Monte Carlo method.

The current study proposes a procedure to estimate the activity concentration of natural radionuclides and to optimize passive shielding solutions for HPGe detectors using adjoint Monte Carlo (MC) simulation technique of Geant4 for the first time. The background spectrum is acquired for 1.56 × 106 s using an HPGe detector model (GC3020), set inside a shielding solution, during 2021-2022 to estimate the activity concentration of natural radionuclides inside the shielding. While, a background spectrum for 65,000 s is acquired with shielding removed to estimate the concentration of natural radionuclides in the building materials of the laboratory. The detector design used in the simulations is validated by comparing computed and measured Full Energy Peak Efficiency (FEPE) for point sources 241Am, 152Eu, 137Cs, 133Ba, and 60Co. Adjoint MC simulations are used to compute the activity concentration of natural radionuclides assuming an isotropic distribution. The activity concentration of 40K, 226Ra and 232Th in the building material is found to be 524 ± 140, 83 ± 20 and 65 ± 18 Bqkg-1, respectively. The computed values are found in good agreement with the published data. The natural radioactivity levels of 40K, 226Ra and 232Th measured in lead shielding are 155.7 ± 0.1 mBqkg-1, 24 ± 13 mBqkg-1 and 33 ± 17 mBqkg-1 respectively. The radiological risks arising due to natural radioactivity is assessed by calculating radium equivalent activity (Raeq), indoor radiation hazard index (Hin) and annual effective dose equivalent. All the radiological parameters are found below their permissible limits and building materials may be considered radiologically safe. The optimal lead shield thickness for the detector is determined to be 12 cm, resulting in reduction of background signal by two orders of magnitude compared to an unshielded detector. The adjoint MC simulations in Geant4 are 103-104 times more rapid as compared to normal simulations for shield optimization of HPGe detectors and therefore, are identified as viable computing solution to calculate the activity of the background radiation.

Clonal gamete-mediated polyploid genome design for stacking genomes.

Hybrid vigor in plants confers better agronomically significant traits in offspring compared with either parent. Recently, Wang et al. reported a mitosis instead of meiosis (MiMe) system in tomato for clonal gamete production, showing the potential to exploit autopolyploid progressive heterosis by stacking genomes from four grandparents in tetraploid hybrids, developed from crossing MiMe hybrids.

Dominance of Cotton leaf curl Multan virus-Rajasthan strain associated with third epidemic of cotton leaf curl disease in Pakistan.

Cotton (Gossypium hirsutum) is an economically potent crop in many countries including Pakistan, India, and China. For the last three decades, cotton production is under the constant stress of cotton leaf curl disease (CLCuD) caused by begomoviruses/satellites complex that is transmitted through the insect pest, whitefly (Bemisia tabaci). In 2018, we identified a highly recombinant strain; Cotton leaf curl Multan virus-Rajasthan (CLCuMuV-Raj), associated with the Cotton leaf curl Multan betasatellite-Vehari (CLCuMuBVeh). This strain is dominant in cotton-growing hub areas of central Punjab, Pakistan, causing the third epidemic of CLCuD. In the present study, we have explored the CLCuD diversity from central to southern districts of Punjab (Faisalabad, Lodhran, Bahawalpur, Rahimyar Khan) and the major cotton-growing region of Sindh (Tandojam), Pakistan for 2 years (2020-2021). Interestingly, we found same virus (CLCuMuV-Raj) and associated betasatellite (CLCuMuBVeh) strain that was previously reported with the third epidemic in the central Punjab region. Furthermore, we found minor mutations in two genes of CLCuMuV-Raj C4 and C1 in 2020 and 2021 respectively as compared to its isolates in 2018, which exhibited virus evolution. Surprisingly, we did not find these mutations in CLCuMuV-Raj isolates identified from Sindh province. The findings of the current study represent the stability of CLCuMuV-Raj and its spread toward the Sindh province where previously Cotton leaf curl Kokhran virus (CLCuKoV) and Cotton leaf curl Shahdadpur virus (CLCuShV) have been reported. The findings of the current study demand future research on CLCuD complex to explore the possible reasons for prevalence in the field and how the virus-host-vector compatible interaction can be broken to develop resistant cultivars.

Comparative analysis, diversification, and functional validation of plant nucleotide-binding site domain genes.

Nucleotide-binding site (NBS) domain genes are one of the superfamily of resistance genes involved in plant responses to pathogens. The current study identified 12,820 NBS-domain-containing genes across 34 species covering from mosses to monocots and dicots. These identified genes are classified into 168 classes with several novel domain architecture patterns encompassing significant diversity among plant species. Several classical (NBS, NBS-LRR, TIR-NBS, TIR-NBS-LRR, etc.) and species-specific structural patterns (TIR-NBS-TIR-Cupin_1-Cupin_1, TIR-NBS-Prenyltransf, Sugar_tr-NBS etc.) were discovered. We observed 603 orthogroups (OGs) with some core (most common orthogroups; OG0, OG1, OG2, etc.) and unique (highly specific to species; OG80, OG82, etc.) OGs with tandem duplications. The expression profiling presented the putative upregulation of OG2, OG6, and OG15 in different tissues under various biotic and abiotic stresses in susceptible and tolerant plants to cotton leaf curl disease (CLCuD). The genetic variation between susceptible (Coker 312) and tolerant (Mac7) Gossypium hirsutum accessions identified several unique variants in NBS genes of Mac7 (6583 variants) and Coker312 (5173 variants). The protein-ligand and proteins-protein interaction showed a strong interaction of some putative NBS proteins with ADP/ATP and different core proteins of the cotton leaf curl disease virus. The silencing of GaNBS (OG2) in resistant cotton through virus-induced gene silencing (VIGS) demonstrated its putative role in virus tittering. The presented study will be further helpful in understanding the plant adaptation mechanism.

Assessment of Genomic Diversity and Selective Pressures in Crossbred Dairy Cattle of Pakistan.

Improving the low productivity levels of native cattle breeds in smallholder farming systems is a pressing concern in Pakistan. Crossbreeding high milk-yielding holstein friesian (HF) breed with the adaptability and heat tolerance of Sahiwal cattle has resulted in offspring that are well-suited to local conditions and exhibit improved milk yield. The exploration of how desirable traits in crossbred dairy cattle are selected has not yet been investigated. This study aims to provide the first overview of the selective pressures on the genome of crossbred dairy cattle in Pakistan. A total of eighty-one crossbred, thirty-two HF and twenty-four Sahiwal cattle were genotyped, and additional SNP genotype data for HF and Sahiwal were collected from a public database to equate the sample size in each group. Within-breed selection signatures in crossbreds were investigated using the integrated haplotype score. Crossbreds were also compared to each of their parental breeds to discover between-population signatures of selection using two approaches: cross-population extended haplotype homozygosity and fixation index. We identified several overlapping genes associated with production, immunity, and adaptation traits, including U6, TMEM41B, B4GALT7, 5S_rRNA, RBM27, POU4F3, NSD1, PRELID1, RGS14, SLC34A1, TMED9, B4GALT7, OR2AK3, OR2T16, OR2T60, OR2L3, and CTNNA1. Our results suggest that regions responsible for milk traits have generally experienced stronger selective pressure than others.

Deciphering the differential expression patterns of yield-related negative regulators in hexaploid wheat cultivars and hybrids at different growth stages.

BACKGROUND: Hexaploid bread wheat underwent a series of polyploidization events through interspecific hybridizations that conferred adaptive plasticity and resulted in duplication and neofunctionalization of major agronomic genes. The genetic architecture of polyploid wheat not only confers adaptive plasticity but also offers huge genetic diversity. However, the contribution of different gene copies (homeologs) encoded from different subgenomes (A, B, D) at different growth stages remained unexplored. METHODS: In this study, hybrid of elite cultivars of wheat were developed via reciprocal crosses (cytoplasm swapping) and phenotypically evaluated. We assessed differential expression profiles of yield-related negative regulators in these cultivars and their F1 hybrids and identified various cis-regulatory signatures by employing bioinformatics tools. Furthermore, the preferential expression patterns of the syntenic triads encoded from A, B, and D subgenomes were assessed to decipher their functional redundancy at six different growth stages. RESULTS: Hybrid progenies showed better heterosis such as up to 17% increase in the average number of grains and up to 50% increase in average thousand grains weight as compared to mid-parents. Based on the expression profiling, our results indicated significant dynamic transcriptional expression patterns, portraying the different homeolog-dominance at the same stage in the different cultivars and their hybrids. Albeit belonging to same syntenic triads, a dynamic trend was observed in the regulatory signatures of these genes that might be influencing their expression profiles. CONCLUSION: These findings can substantially contribute and provide insights for the selective introduction of better cultivars into traditional and hybrid breeding programs which can be harnessed for the improvement of future wheat.

Evaluation of BG, NPR1, and PAL in cotton plants through Virus Induced gene silencing reveals their role in whitefly stress.

Whitefly is one of the most hazardous insect pests that infests a wide range of host plants and causes huge damage to crop worldwide. In order to engineer plants resilient to whitefly stress, it is important to identify and validate the responsive genes by exploring the molecular dynamics of plants under stress conditions. In this study three genes BG, NPR1, and PAL genes have been studied in cotton for elucidating their role in whitefly stress response. Initially, insilico approach was utilized to investigate the domains and phylogeny of BG, NPR1 and PAL genes and found out that these genes showed remarkable resemblance in four cotton species Gossypium hirsutum, G. barbadense, G. arboreum, and G. raimondii. In BG proteins the main functional domain was X8 belonging to glycohydro superfamily, in NPR1 two main functional domains were BTB_POZ at N terminal and NPR1_like_C at C terminal. In PAL functional domain PLN was found which belongs to Lyase class I superfamily. The promoter analysis of these genes displayed enrichment of hormone, stress and stimuli responsive cis elements. Through Virus Induced Gene Silencing (VIGS), these genes were targeted and kept under whitefly infestation. Overall, the whitefly egg and nymph production were observed 60-70% less on gene down regulated plants as compared to control plants. The qPCR-based expression analysis of certain stress-responsive genes showed that in BG down regulated plants the elevated expression of these whitefly responsive genes was detected, in NPR1 down regulated plants JAZ1 and HSP were found up regulated, ERF1 and WRKY40 didn't show significant differential expression, while MAPK6 was slightly down regulated. In PAL down regulated plants ERF1 and JAZ1 showed elevated expression while others didn't show significant alternation. Differential expression in gene down-regulated plants showed that whitefly responsive genes act in a complex inter signaling pathway and their expression impact each other. This study provides valuable insight into the structural and functional analysis of important whitefly responsive genes BG, NPR1, and PAL. The results will pave a path to future development of whitefly resilient crops.

Salicylic acid-driven innate antiviral immunity in plants.

Pathogenic viruses are a constant threat to all organisms, including plants. However, in plants, a small group of cells (stem cells) protect themselves from viral invasion. Recently, Incarbone et al. uncovered a novel salicylic acid (SA) and RNAi mechanism of stem cell resistance, broadening our understanding of RNAi-mediated antiviral plant immunity.

Methyl-salicylate (MeSA)-mediated airborne defence.

Stressed plants emit a variety of chemicals into the environment, leading to increased pest resistance in neighbouring plants but the genetic and molecular mechanisms of the emissions remain obscure. Recently, Gong et al. identified novel methyl salicylate (MeSA)-mediated airborne defence that confers resistance to neighbouring plants against aphids and viruses.

Omics-driven exploration and mining of key functional genes for the improvement of food and fiber crops.

The deployment of omics technologies has obtained an incredible boost over the past few decades with the advances in next-generation sequencing (NGS) technologies, innovative bioinformatics tools, and the deluge of available biological information. The major omics technologies in the limelight are genomics, transcriptomics, proteomics, metabolomics, and phenomics. These biotechnological advances have modernized crop breeding and opened new horizons for developing crop varieties with improved traits. The genomes of several crop species are sequenced, and a huge number of genes associated with crucial economic traits have been identified. These identified genes not only provide insights into the understanding of regulatory mechanisms of crop traits but also decipher practical grounds to assist in the molecular breeding of crops. This review discusses the potential of omics technologies for the acquisition of biological information and mining of the genes associated with important agronomic traits in important food and fiber crops, such as wheat, rice, maize, potato, tomato, cassava, and cotton. Different functional genomics approaches for the validation of these important genes are also highlighted. Furthermore, a list of genes discovered by employing omics approaches is being represented as potential targets for genetic modifications by the latest genome engineering methods for the development of climate-resilient crops that would in turn provide great impetus to secure global food security.