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      Biomarkers for Detecting Resilience against Mycobacterial Disease in Animals

      , , , ,
      Infection and Immunity
      American Society for Microbiology

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          ABSTRACT

          Paratuberculosis and bovine tuberculosis are two mycobacterial diseases of ruminants which have a considerable impact on livestock health, welfare, and production. These are chronic “iceberg” diseases which take years to manifest and in which many subclinical cases remain undetected. Suggested biomarkers to detect infected or diseased animals are numerous and include cytokines, peptides, and expression of specific genes; however, these do not provide a strong correlation to disease. Despite these advances, disease detection still relies heavily on dated methods such as detection of pathogen shedding, skin tests, or serology. Here we review the evidence for suitable biomarkers and their mechanisms of action, with a focus on identifying animals that are resilient to disease. A better understanding of these factors will help establish new strategies to control the spread of these diseases.

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          Most cited references204

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          MicroRNAs: genomics, biogenesis, mechanism, and function.

          MicroRNAs (miRNAs) are endogenous approximately 22 nt RNAs that can play important regulatory roles in animals and plants by targeting mRNAs for cleavage or translational repression. Although they escaped notice until relatively recently, miRNAs comprise one of the more abundant classes of gene regulatory molecules in multicellular organisms and likely influence the output of many protein-coding genes.
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            Most mammalian mRNAs are conserved targets of microRNAs.

            MicroRNAs (miRNAs) are small endogenous RNAs that pair to sites in mRNAs to direct post-transcriptional repression. Many sites that match the miRNA seed (nucleotides 2-7), particularly those in 3' untranslated regions (3'UTRs), are preferentially conserved. Here, we overhauled our tool for finding preferential conservation of sequence motifs and applied it to the analysis of human 3'UTRs, increasing by nearly threefold the detected number of preferentially conserved miRNA target sites. The new tool more efficiently incorporates new genomes and more completely controls for background conservation by accounting for mutational biases, dinucleotide conservation rates, and the conservation rates of individual UTRs. The improved background model enabled preferential conservation of a new site type, the "offset 6mer," to be detected. In total, >45,000 miRNA target sites within human 3'UTRs are conserved above background levels, and >60% of human protein-coding genes have been under selective pressure to maintain pairing to miRNAs. Mammalian-specific miRNAs have far fewer conserved targets than do the more broadly conserved miRNAs, even when considering only more recently emerged targets. Although pairing to the 3' end of miRNAs can compensate for seed mismatches, this class of sites constitutes less than 2% of all preferentially conserved sites detected. The new tool enables statistically powerful analysis of individual miRNA target sites, with the probability of preferentially conserved targeting (P(CT)) correlating with experimental measurements of repression. Our expanded set of target predictions (including conserved 3'-compensatory sites), are available at the TargetScan website, which displays the P(CT) for each site and each predicted target.
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              The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14

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                Author and article information

                Journal
                Infection and Immunity
                Infect Immun
                American Society for Microbiology
                0019-9567
                1098-5522
                December 17 2019
                December 17 2019
                September 16 2019
                : 88
                : 1
                Article
                10.1128/IAI.00401-19
                6921658
                31527123
                0473ffc8-b517-47a1-8108-532e42f0791a
                © 2019
                History

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