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Air pollution which negatively impacts both human health and the environment is a mountainous challenge before policymakers and city planners in urban areas. Urban landscaping with effective pollution-combating tree species is one of the soundest strategies to mitigate pollution adversaries. However, not all tree species are equally suitable for urban environments due to varying levels of tolerance to air pollution. This study has been designed to evaluate the physiological and biochemical responses of seven commonly occurring tree species in the Talkatora garden (TG) and Income Tax Office (ITO) representing non-polluted and polluted locations in Delhi, respectively applying Air Pollution Tolerance Index (APTI). The current research study was carried out during 2021–22 at the Division of Floriculture and Landscaping, ICAR-Indian Agricultural Research Institute, New Delhi. In tree species understudy, it was recorded that the pH of leaf extract, total chlorophyll, and relative water content was lower in the winter season than summer season except for the ascorbic acid. Ficus religiosa with the highest APTI value (23.23) followed by Pongamia pinnata (20.85) were found most tolerant tree species to air pollution in Delhi during the winter season at the polluted (ITO) and non-polluted (TG) location respectively with a reverse trend for the summer season. Polyalthia longifolia was found most sensitive (bioindicator plant) to air pollution among the seven trees under study owing to the lowest APTI values (11.14 and 12.58) across the seasons at non-polluted (TG) and polluted (ITO) locations respectively. Furthermore, Ficus religiosa with the highest APTI across the locations and seasons was assessed as the best performer, hence, could be the most efficient option for landscaping in polluted and non-polluted areas.

Copy number variants (CNVs) have dynamic potential and evolutionary significance like other genetic variants, namely, single nucleotide polymorphisms, InDels, short tandem repeat polymorphisms, inversion variants, etc. Discovering CNVs leads to further speculation that the genomic DNA contains more changes than previously thought and contributes to the phenotypic variation. CNVs are big DNA fragments (> 1 kb) being duplicated or deleted. A bridge between CNVs and phenotypic variations supports CNVs to be utilized in GWAS, which are currently mostly based on SNPs. CNV, which refers to the structural differences, influence gene expression and can be an indicator of numerous traits for improvement. There is a severe dearth of research on CNVs in animals, especially equine. The present study investigates the genomes of the Bhutia Equine breed for genome-wide discovery of CNVs using the Axiom™ Equine Genotyping Array chip for a better understanding of its traits which had been unexplored till date. A total of 619 CNVs from 20 Bhutia equines were identified with the median and average size as 49.394 kb and 114.955 kb, respectively. Total 225 frequent CNVRs with > 1% CNV frequency were identified among them along with singleton type. These CNVRs contained 361 genes in all. The information obtained on genomic variation could be utilized to identify economically advantageous genetic features in Bhutia equine breed.

For thousands of years, cereals which include rice, wheat, maize, sorghum and millets etc. have been playing major role in human civilization. These are the principal components of human diet and important staples for daily survival of billions of people globally. The cereal crops belong to poaceae family and rich in vitamins, minerals and fiber. They are reported to reduce the coronary heart disease and other serious diseases. These crops are adversely affected by biotic and abiotic stresses like cold, drought, heat and salinity. With the advent of modern NGS technologies, the plethora of molecular data leads to infer many unexplored facts of the cereal crops using in-silico approach. In the present work, computational techniques were applied to study thoroughly the classification of abiotic stresses (cold, drought, heat and salinity) responsive genes in cereals. The datasets of four stress responsive genes in poaceae family was retrieved from public domain. The machine learning based methodologies namely, Random forest, Support Vector Machines and Deep Learning-Long Short-Term Memory (DL-LSTM) were applied. A comparative analysis was carried out for classification of the retrieved data with k-fold cross validation applying the machine learning techniques at different parameters. It was observed that for all the four sets of data, accuracy was maximum, i.e. 95.11%, 76.88%, 94.31% and 82.04% for cold, drought, heat and salinity, respectively using DL-LSTM. Comparison of the methodologies obviates the outperformance of deep leaning. Such approach of computational studies will help researchers to study the complex biological problems of gene classification more efficiently.

Black pepper (Piper nigrum L.) (2n= 52; Piperaceae), is a perennial, trailing woody flowering vine having global importance with widespread dietary, medicinal, and preservative uses. It is one of the highly traded high cost spice germplasms cultivated for its fruit. Unlike model species, the whole genome sequence information and genomic resources of black pepper are still unavailable in public domain. Crop production is highly affected by abiotic and biotic stresses. Hence transcriptome profiling has permitted a significant enhancement in discovery and expression profiling of genes and functional genomic studies in black pepper. Stress responsive transcriptomic data of various black pepper genotypes were obtained from public domain (SRA database, NCBI) for the de novo transcriptome assembly, identification of transcription factors and mining of putative simple sequence repeat markers. De novo transcriptome assembly was done with SOAP denovo-trans assembler, which generated 53690 transcripts. A total of 14005 transcription factors with BLAST and 39685 without BLAST hits were identified. A total of 4770 putative SSR markers were identified using de novo transcriptome assembly. Myeloblastosis (MYB) related proteins, Basic helix-loop-helix (BHLH), NAC, WRKY and ERF transcriptional factors found in this study are reported to be associated with plant tolerance against stress condition. These SSR markers can be valuable and facilitate advancements in genetic and molecular studies in the endeavour of better productivity of P. nigrum germplasm, especially in the era of rising abiotic stress.

In current investigation, morphological and biochemical characteristics of grape (Vitis vinifera L.) hybrids were evaluated at ICAR-IARI, New Delhi. Hybrids of Pearl of Csaba × Beauty Seedless came earliest in full bloom, maturity and harvest with largest size of bunch, while hybrids of Banqui Abyad × Beauty Seedless harvested last and produced smaller size of bunch. Larger berry size and maximum juice recovery was measured in hybrids Hy.16/2AR1P14 (Cardinal × Beauty Seedless) and Hy.16/2A-R4P13 (Banqui Abyad × Beauty Seedless). The maximum total soluble solids, TSS/acid ratio with least total titratable acidity was estimated in Pearl of Csaba × Beauty Seedless hybrids. Based on morphological and biochemical evaluation, two hybrids, i.e. Hy.ER-R2P36 and Hy.16/2A-R1P14 were found promising especially under subtropical conditions of North India.