No abstract

With the boom in industrialization, there is an increase in the level of heavy metals in the soil which drastically affect the growth and development of plants. Nickel is an essential micronutrient for plant growth and development, but elevated level of Ni causes stunted growth, chlorosis, nutrient imbalance, and alterations in the defense mechanism of plants in terms of accumulation of osmolytes or change in enzyme activities like guiacol peroxidase (POD), catalase (CAT), and superoxide dismutase (SOD). Ni-induced toxic response was studied in seedlings of finger millet, pearl millet, and oats in terms of seedling growth, lipid peroxidation, total chlorophyll, proline content, and enzymatic activities. On the basis of germination and growth parameters of the seedling, finger millet was found to be the most tolerant. Nickel accumulation was markedly lower in the shoots as compared to the roots, which was the highest in finger millet and the lowest in shoots of oats. Plants treated with a high concentration of Ni showed significant reduction in chlorophyll and increase in proline content. Considerable difference in level of malondialdehyde (MDA) content and activity of antioxidative enzymes indicates generation of redox imbalance in plants due to Ni-induced stress. Elevated activities of POD and SOD were observed with high concentrations of Ni while CAT activity was found to be reduced. It was observed that finger millet has higher capability to maintain homeostasis by keeping the balance between accumulation and ROS scavenging system than pearl millet and oats. The data provide insight into the physiological and biochemical changes in plants adapted to survive in Ni-rich environment. This study will help in selecting the more suitable crop species to be grown on Ni-rich soils.

No abstract

The present study aims to evaluate the suitability of 10 candidate genes, namely GAPDH, ACTB, RPS15A, RPL4, RPS9, RPS23, HMBS, HPRT1, EEF1A1 and UBI as internal control genes (ICG) to normalize the transcriptional data of mammary epithelial cells (MEC) in Indian cows. A total of 52 MEC samples were isolated from milk of Sahiwal cows (major indigenous dairy breed of India) across different stages of lactation: Early (5-15 days), Peak (30-60 days), Mid (100-140 days) and Late (> 240 days). Three different statistical algorithms: geNorm, Normfinder and BestKeeper were used to assess the suitability of these genes. In geNorm analysis, all the genes exhibited expression stability (M) values below 0.5 with EEF1A1 and RPL4 showing the maximum expression stability. Similar to geNorm, Normfinder also identified EEF1A1 and RPL4 as two of the most stable genes. In Bestkeeper algorithm as well, all the 10 genes showed consistent expression levels. The analysis showed that four genes, that is, EEF1A1, RPL4, GAPDH and ACTB exhibited higher coefficient of correlation to the Bestkeeper index, lower coefficient of variance and standard deviation, indicating their superiority to be used as ICG. The present analysis has provided evidence that RPL4, EEF1A1, GAPDH and ACTB could probably act as most suitable genes for normalizing the transcriptional data of milk-derived mammary epithelial cells of Indian cows.

No abstract