Progress on lncRNA regulated disease resistance traits in domesticated animals.

Long non-coding RNA (lncRNA) is a class of non-coding RNAs with a length greater than 200 nucleotides. Although lncRNAs do not have any protein coding capability, they can affect the phenotypes of traits by influencing gene expression through transcriptional regulation, post-transcriptional regulation, and epigenetic modification. In modern animal husbandry production, besides increasing growth and yield traits, investigations on the regulation mechanisms of immune factors, cytokines and other disease resistance-related indicators and traits are particularly important for improving the health and welfare of domesticated animals as well as public health. In recent years, researchers have made significant progress in understanding the regulatory mechanisms of lncRNA on the disease resistance traits of chickens (Gallus gallus), pigs (Sus scrofa), cattle (Bos taurus) and other important domesticated animals, thereby laying the basic foundation for the translational application of epigenetic markers in breeding of animals with disease resistance. In this review, we briefly introduce the biological functions and the origins of lncRNAs, then focus on the research progress on the regulatory effects of lncRNAs on disease resistance traits of domesticated animals, and thus providing the scientific basis for the research of lncRNA and its application in the breeding of disease-resistant animals.

Fixed pattern noise in localization microscopy.

Localization microscopy vastly improves the resolution achieved by fluorescence microscopy by fitting the positions of individual fluorophores. We examine the reconstructions produced by different fitting algorithms for instances of fixed pattern noise--systematic tendencies to alter estimated emitter positions according to their subpixel location in a way that does not reflect the ground truth structure. We show that while not readily visible at standard empirical signal strengths, fixed pattern noise can occur when performing sub-pixel fitting, and that its degree varies according to the algorithm used and the relative size of the pixels compared to the point spread function. For pixel sizes in the range 80-170 nm, this results in variations in accuracy of the order of 2-4 nm-comparatively small for many applications, but non-negligible in scenarios where very high accuracy is sought.