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Bovine mastitis is a complex infectious disease that develops in the mammary gland, predominantly by a bacterial infection of mammary tissue. Mastitis is economically important in the context of a long-lasting decrease in milk yield (in the range of 5-25%), cost of treatment, and effect on cow’s health. Genetic variability of mastitis is well established and depends upon different quantitative trait loci (QTL) related to mastitis resistance or susceptibility. The susceptibility is often attributed to single nucleotide polymorphisms (SNPs) in the variable cow breed genomes. Several global investigative attempts have resulted in studies mapping mastitis to the variations in the relevant genes. Reports have been attributed to dramatic genetic expression changes in Toll Like Receptor 4 (TLR4) genes in mastitis-positive cows. However, the mechanism behind this variable genetic expression of TLR4 genes has been studied poorly. This study aims to investigate possible mechanisms behind this variable expression of TLR4 by comparative SNP evaluation and transcriptional factor profile mining. So that the important genetic mutations and effects thereof can be exploited in selecting specific breeds with higher mastitis resistance and milk yields, this paper identifies several mutations of prominence and almost sixteen SNPs falling in TLR4 promoter and 5` untranslated region (5`UTR) sequences in mastitis-positive genotypes compared to reference genomes. The study also investigates the potential transcriptional factor program deployed in response to variable mastitis development resistance. This paper combines the classic parameters of mastitis like somatic cell count (SCC), milk electric conductivity (EC), milk pH, California mastitis test (CMT) and attempts to attribute a genetic cause in relation to variable TLR4 promoter and 5`UTR sequence SNPs. The results of this paper have wide applicability for researchers developing mastitis-resistant breeding programs and the data generated may aid in the selection of better genetic breeds. The transcription factor binding profiles given in the paper will serve as concrete leads about the studies on bovine mastitis at the molecular level and may also aid global research groups working on transcription factor (TF) -based molecular pathology of mastitis.

Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non‐native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non‐native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region‐specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non‐native species richness. Non‐native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series, even more exciting results can be expected, especially about range shifts. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented. We summarize the findings achieved with the standardized sampling protocol developed by the Mountain Invasion Research Network (MIREN) for monitoring the impact of global change on elevational plant species distributions. We intend to promote the use of the protocol to generate global insights into native and non‐native species responses to rapid global change in mountains.