In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Background: The Major Histocompatibility Complex (MHC) is a genomic region containing genes with crucial roles in immune responses. MHC class I and class II genes encode antigen-presenting molecules expressed on the cell surface. To counteract the high variability of pathogens, the MHC evolved into a region of considerable heterogeneity in its organization, number and extent of polymorphism. Studies of MHCs in different model species contribute to our understanding of mechanisms of immunity, diseases and their evolution. Camels are economically important domestic animals and interesting biomodels. Three species of Old World camels have been recognized: the dromedary (Camelus dromedarius), Bactrian camel (Camelus bactrianus) and the wild camel (Camelus ferus). Despite their importance, little is known about the MHC genomic region, its organization and diversity in camels. The objectives of this study were to identify, map and characterize the MHC region of Old World camelids, with special attention to genetic variation at selected class MHC II loci. Results: Physical mapping located the MHC region to the chromosome 20 in Camelus dromedarius. Cytogenetic and comparative analyses of whole genome sequences showed that the order of the three major sub-regions is "Centromere -Class II -Class III -Class I". DRA, DRB, DQA and DQB exon 2 sequences encoding the antigen binding site of the corresponding class II antigen presenting molecules showed high degree of sequence similarity and extensive allele sharing across the three species. Unexpectedly low extent of polymorphism with low numbers of alleles and haplotypes was observed in all species, despite different geographic origins of the camels analyzed. The DRA locus was found to be polymorphic, with three alleles shared by all three species. DRA and DQA sequences retrieved from ancient DNA samples of Camelus dromedarius suggested that additional polymorphism might exist. Conclusions: This study provided evidence that camels possess an MHC comparable to other mammalian species in terms of its genomic localization, organization and sequence similarity. We described ancient variation at the DRA locus, monomorphic in most species. The extent of molecular diversity of MHC class II genes seems to be substantially lower in Old World camels than in other mammalian species.
The major histocompatibility complex in Old World camelids and low polymorphism of its class II genes

for detecting the gene encoding the σB major outer-capsid protein of novel duck reovirus (NDRV). A set of primers, composed of two outer primers, two inner primers and two loop primers, was designed based on the gene of interest. The LAMP reaction was conducted in a traditional laboratory water bath at 65 °C for 50 min. We compared the performance of calcein/Mn 2+ and SYBR Green I dyes, as well as electrophoresis on agarose gel stained with GoldView nucleic acid dye to detect the RT-LAMP-amplified products and all assays could be employed to discriminate between positive and negative specimens in visible or UV light. Our data showed that there is no cross-reaction with other viruses and the RT-LAMP technique displayed high sensitivity for detecting NDRV with a minimal detection limit of 200 fg RNA input. This assay was more sensitive than conventional PCR in detecting NDRV both in natural and experimental infection. In conclusion, the RT-LAMP technique was remarkably sensitive, specific, rapid, simple and profitable for the identification of NDRV.
Detection of Novel duck reovirus (NDRV) using visual reverse transcription loop-mediated isothermal amplification (RT-LAMP)

With the advent of deep sequencing, genomic surveillance has become a popular method for detection of infectious disease, supplementing information gathered by classic clinical or serological techniques to identify host-determinant markers and trace the origin of transmission. However, two main factors complicate genomic surveillance. First, pathogens exhibiting high genetic diversity demand higher levels of scrutiny to obtain an accurate representation of the entire population. Second, current systems of detection are nonuniform, with significant gaps in certain geographic locations and animal reservoirs. Despite past unforeseen pandemics like the 2009 swine-origin H1N1 influenza virus, there is no standardized way of evaluating surveillance. A more complete surveillance system should capture a greater proportion of pathogen diversity. Here we present a novel quantitative method of assessing the completeness of genomic surveillance that incorporates the time of sequence collection, as well as the pathogen's evolutionary rate. We propose the q2 coefficient, which measures the proportion of sequenced isolates whose closest neighbor in the past is within a genetic distance equivalent to 2 years of evolution, roughly the median time of changing strain selection for influenza A vaccines. Easily interpretable and significantly faster than other methods, the q2 coefficient requires no full phylogenetic characterization or use of arbitrary clade definitions. Application of the q2 coefficient to influenza A virus confirmed poor sampling of swine and avian populations and identified regions with deficient surveillance. We demonstrate that the q2 coefficient can not only be applied to other pathogens, including dengue and West Nile viruses, but also used to describe surveillance dynamics, particularly the effects of different public health policies. IMPORTANCE Surveillance programs have become key assets in determining the emergence or prevalence of pathogens circulating in human and animal populations. Genomic surveillance, in particular, provides comprehensive information on the history of isolates and potential molecular markers for infectivity and pathogenicity. Current techniques for evaluating genomic surveillance are inaccurate, ignoring the pathogen's evolutionary rate and biodiversity, as well as the timing of sequence collection. Using sequence data, we propose the q2 coefficient as a quantitative measure of surveillance completeness that combines elements of time and evolution without defining arbitrary criteria for clades or species. Through several case studies of influenza A, dengue, and West Nile viruses, we employed the q2 coefficient to identify sampling deficiencies in different host species and locations, as well as examine the effects of different public health policies through historical records of the q2 coefficient. These results can guide public health agencies to focus resource allocation and virus collection to bolster specific problems in surveillance. Citation Chan JM, Rabadan R. 2013. Quantifying pathogen surveillance using temporal genomic data. mBio 4(1):e00524-12.

Quantifying Pathogen Surveillance Using Temporal Genomic Data