Population Genetics (Molecular Epidemiology) of Eukaryotes

universe Genetics (Molecular Epidemiology) of EukaryotesINTRODUCTIONThe study of the molecular epidemiology of parasitic infections and their vectors is meant to practice the standardized diversenesss of questions as those of bacterial or viral infections. As with bacteria, the molecular epidemiology of eukaryotic infections follows the distri just nowion and dynamics of microbial desoxyribonucleic acid. The key resistence, however, is precisely this biology, which defines a unequivocal approach to molecular epidemiologic investigation of infections ca do by eukaryotic organisms. In bacterial riposte, each someone passes down an similar copy of solely the DNA to the next generation. Some eukaryotic pathogens be contain reproductively in similar ways to bacteria and reproduce a inform eachy, while new(prenominal)s have sexual retort for at least part of their life- speech rhythm. The individual is able to gene pasture a clone of itself by binary fission to produce two ident ical organisms, and if successful, depart produce large numbers to the detriment of its host. Asexually reproducing organisms stand in addition exhibit promiscuous horizontal gene transfer, which bottom be a major source of variation and adaptation (19), solely this is non sex. Sex is the biologi phoney necessary programmed recombination (crossing e genuinelyplace) and random shuffling (reassortment) of chromosomal DNA in the process of facsimile. This results in an enormous reservoir of variation. Bacteria in nature argon heterogenous conglome judge or communities (13, 19), but when they cause disease, oddly in epidemics, it is generally a clone that is responsible and that we track (Chapter 2). sexual reproduction in ab step to the fore protozoa, many parasitic worms and more or less vectors, however, neer results in a clone with the exception of identical twins. in that location is contractable conservation, however, within a group of organisms that tends to breed unneurotic. In genetical science, this is the working exposition of a race. For sexually reproducing organisms, the race is the epidemiologic unit to track. Within the group, allelomorph frequencies and then traits atomic number 18 conserved under well-defined conditions. The unique situation of the genetics of states is that it reflects non only present individuals but overly the existences previous(prenominal) and the approaching potential for subsequent generations (5). Many parasites exhibit both sexual and asexual modes of reproduction, but these life stages be distributed in different hosts. handling of their molecular epidemiology is doubly complex, but net be simplified for some questions by considering their biology just in the human host. The whole knit stitch of tribe genetics is perhaps the most complex area of genetics, but it arises from transparent precepts. This chapter go forth outline the basic models used in population genetics and are right off applicable to problems of public health epidemiology. mention POINTSAsexual reproduction usually produces a clone sexual reproduction never does.A population is a group of organisms that tends to breed togetherallele and ge nonype frequencies describe populationsAllele frequencies and traits tend to be retained within groups of inter lift organisms (derived from the Hardy-Weinberg equilibrium)Allele and genotype frequencies can be used to infer population historiesIndices and statistics can be used to compare evaluate population history and to project population dynamicsDEFINING genetic constitution IN EUKARYOTIC ORGANISM Some statuss whitethorn not be familiar to some readers, so it is of import to define these early. unrivaled of the dividing lines amongst bacteria and sexually reproducing parasites and vectors of human disease is their physical building and organization. Sexually reproducing organisms exit pass some portion of their life cycle where their chromosome s ( encipher 5.1) exist as nearly identical pairs (diploid). Some organisms, malaria in particular, also have only one copy (haploid) during their asexual stage, and this is the stage that infects humans. A similar location on each of the chormosomes is a venue, and differences betwixt loci are alleles.The geometry of DNA also strongly differentiates bacteria from eukaryotes (Figure 5.2). Prokaryotes have a single1, eyeshade chromosome whereas withal the simplest eukaryotes, yeast, have at least 16 linear chromosomes. A specific marker on a bacterial chromosome will forever be transmitted at reproduction together with any new(prenominal) marker or trait. The uniform also occurs with an asexually reproducing eukaryote disrespect having multiple linear chromosomes. A marker on the genome of a sexually reproducing eukaryote, by contrast, will have a 50% chance of macrocosm transmitted away from any marker it is not very stiff to. The labeling of each allele present at the an alogous locus on each chromosome constitutes the genotype. A locus with the same polymorphism at the same site on each of the chromosome is homozygous, and with a different polymorphism is heterozygous.Figure 5.2OPTIONS FOR MOLECULAR EPIDEMIOLOGY OF EUKARYOTESStudy asexual parasitesUse a marker constraining to the trait of interest (if known)Use many markers throughout the genome or ecological successionStudy the whole group of organisms in which the trait is present (population)HARDY-WEINBERG labyrinthine sense THE POPULATION NULL HYPOTHESISPopulations have a mathematical rendering base on allele frequencies, which ultimately contributes to the development of tools for key footprints of specialization and diversity. Allele frequencies can differentiate populations, and genotypical frequencies can do so with even greater resolution. The blood among allelic frequency and genotypic frequency has a simple mathematical relationship which is the definition of a population. If we use the letters A and a to represent different alleles at a single diallelic locus and p and q to represent their respective frequencies, a population with p=0.8 and q=0.2 is undefendedly different from a population where p=0.2, q=0.8, especially where this kind of result is found at multiple loci. Allele frequencies are not constantly the most sensitive bank bill of differentiation. The same allele frequency may still be found in what are mop uply distinct populations if assessed for genotypic frequencies. Alleles combine to form genotypes, so the genotypic frequency is a function of the allelic frequencies. For a diallelic locus where we know the frequency of each allele, the sum of these frequencies is 1 or (p + q = 1). For sexually reproducing organisms the next generation arises from the combination of alleles from a pussycat of males with alleles from a pool of females. If we imagine that individuals from these pools will pair at random, the subsequent distribution of al leles in genotypes is equivalent to rolling a pair of dice. For independent, random events the probability of 2 events occurring simultaneously is the product of their frequencies (p + q)female (p + q)male = 1. The genotypic frequencies of the publication for such a population should be p2 + 2pq + q2, if all assumptions are met, where p2 and q2 are the frequencies for the homozygotes and 2pq the heterozygotes. This is the well-known Hardy-Weinberg equilibrium (HWE). This simple quadratic equation is the basis for all population genetics even when it is not timed directly. It represents the expected genotypic frequencies from a inclined practise of allelic frequencies. It is one of the most stable mathematical relationships in nature. It is so much the expectation that when not observed in sequencing projects, it can rede sequencing errors. It is the null hypothesis and mathematical definition of a stable population. The relationship HWE describes is true under a set of 5-10 as sumptions that represent the most eventful factors that influence population genetic structure. The 5 most common assumptions are that thither is1) Random mating (panmixia, assortative mating)2) No option3) No migration4) An numberless population5) No mutationIt is rare to have any of these assumptions met in nature, but the proportions are so resilient that the assumptions have to be poorly violated to disturb this relationship, and even so, the proportions will be reestablished within 1-2 generations once the population is stabilized. As with most models, the underlying assumptions are the most heavy aspects. They are the basis for most conversations in population genetics.MARKERSMicrosatellites, single base of operations polymorphisms (SNPs) and sequencing are currently the genetic elements most employed in population genetics. Microsatellites are short tandem repeats of 2-8 nucleotides (reviewed in Ellegren, 2004 128). Microsatellites have fallen out of favor in studies o f statistical genetics or gene finding, since SNPs and sequencing go forth better resolution at the level of individuals. Microsatellites, however, remain important in population genetics since they are mostly neutral for selection and have uplifted allelic richness and information content. Their rapid mutation rate (10-2 10-5 per generation) and step-wise mode of mutation can limit their application to questions that extend over short time scales and to certain statistical approaches. SNPs have lower rates of mutation (10-8) in eukaryotes, often are diallelic, are ten propagation more abundant (10, 22) and have high processivity and scorability. Sequencing essentially entrusts a very dense panel of SNPs and identifies rare variants as well as morphological polymorphisms. Mitochondrial and ribosomal DNA markers are much less abundant, less polymorphic and thus less informative than microsatellites or SNPs. Some are under selection and in the case of mitochondrial DNA, the gen ome is haploid (only 1 copy of chromosomal DNA) and may or may not have sex-specific inheritance depending on the species. They are useful for phylogeny studies, may be more economical to use in laboratories with limited capabilities and are sometimes combined with other markers.MEASURES OF differentiation AND DIVERSITYAreas most often regaleed using population genetics are evolution and conservation. These two areas deal with essentially the same phenomenon, but at different time scales, thus the questions, the approaches and the interpretation will differ depending on the nature of the problem. The relevant public health questions in population genetics focus on identity and dynamics of the group earlier than individuals over short time scales and directed at the control or extinction of a parasite or vector. Whos sleeping with whom, modes of reproduction, evolution or the last common ancestor are all important in different contexts. They may be useful to help explain anomalies and can influence interpretation, but they are rarely answers to issues of control or intervention. discretion how diverse a population is or the degree of difference between populations combined with good study design will contribute directly to determining the impact of control measures, host or parasite demographics, resistance, fortune and resilience or fragility of the population.The field of population genetics depends heavy on mathematical analyses, some simple and some very sophisticated, to answer these questions. Mathematical treatments of all of the indices and statistics of differentiation and diversity can be intimately obtained from textbooks or publications and will not be included here. Fortunately for the mathematically challenged, many open source, individual computer programs are available as well as modules in R. The risk that goes with all readymade programs is a bereavement to understand what is being asked or the assumptions and limitations of the approa ch being taken. A disposition of some frequently used programs is provided at the end of this chapter (Table 5.1).POPULATIN DIFFERENTIATIONFST, GST, GST In addition to the Hardy-Weinberg equilibrium, populations can be further differentiated by other statistical tests. This is a family of statistics developed as the fixation index (FST) in the 1950s by Sewell Wright and Gustave Malcot to describe the alike(p)lihood of homozygosity (fixation in the words of the time) at a single diallelic locus based on heterozygosity of a subpopulation compared to the nitty-gritty population. Theoretically, values should mould from 1 (no similarity-every individual is genotypically different) to 0 (identity-every individual is genotypically same). Nei (16) extended the FST to handle the case of more than two alleles and developed the GSTLR1. Although the term FST is often used in the literature, formally most studies today will employ the GST. When highly polymorphic loci, such as microsatellites , are genotyped, the GST sternly underestimates differentiation and will not cathode-ray oscilloscope from 0 1. Hedrick (11) set the range of values for the GST by dividing it by its maximum possible value given the markers used. This is the GST. The GST makes possible the full range of differentiation. FST and GST relate to inherent properties of populations and contain evolutionary information lost by the GST transformation. FST-like measures have been and continue to be astray used to describe population structure, and their characteristics and behavior are well-known. There are additional related statistics (e. g. ST (4), AMOVA, RST (20), (25)), that address other aspects of differing genetic models, unequal savor sizes, ac figuringing for haploid genomes, mechanism of mutation and selection.D. LR2This is sometimes referred to as Josts D, since in that respect are numerous other Ds related to genetics and statistics. There can be logical inconsistencies for estimating di fferentiation based directly on heterozygosity. Ratios of pooled subpopulation to total population diversities tend toward zero when the subpopulation diversity is high (12). Josts D is based on the effective allele number (see below). Unlike those based directly on heterozygosity, it has the property of yielding a linear reception to changes in allele frequencies and is independent of subpopulation diversity. Unlike FST, GST and similar indices, Josts D does not carry information relevant to the evolutionary processes responsible for the present typography of a subpopulation. It is described by supporters and detractors as purely a measure of differentiation (26). It was never meant to do more.Whitlock provides one of the best comparisons of these 2 approachesThis (Josts) D differs from FST in a fundamental definitional way FST measures deviations from panmixia2, while D measures deviations from total differentiation. As a result, their denominators differ, and thus, the two indi ces can behave quite differently. D indicates the proportion of allelic diversity that lies among populations, while FST is proportional to the variance of allele frequency among populations. D is more related to the genetic distance between populations than to the variance in allele frequencies it may be preferable to call D a genetic distance measure (26).There has been contest about the use of these different types of indices. There should not be. They clearly address different questions and resolve different analytic problems. It should be recognized that the GST and Josts D yield fairly similar results when the number of populations is small and the markers have a small number of alleles. The GST and Josts D have given similar results in our own studies using microsatellites (2) and in simulation (26) with GST values slightly higher than those of Josts D. Some authors recommend calculating both GST and Josts D, in part to fulfil everyone and in part to obtain the useful infor mation about population diversity their departure may provide.In relation to public health, most questions about parasites and vectors deal with near term events of DIVERSITYDiversity like differentiation has myriad formulations and interpretations. The simplest expression is mean heterozygosity (H). For microsatellite data this is usually high due to the intrinsically high mutation rate of these markers, and markers with higher division are usually selected. Allelic richness (Ar) is simply a count of the number of alleles at each locus. Differences in prove size will necessarily result in differences in allele number. This is usually adjusted for by statistical methods such as rarefaction (15) to standardize sample sizes between comparison groups. The effective allele number (Ae) is also a measure of diversity, but is already adjusted for sample size. It represents the number of alleles with equal frequencies that will produce the same heterozygosity as that of the target populat ion.The most informative measure of diversity is the effective population size (Ne), a concept also introduced by Sewell Wright. It is designed to address the essential reason that diversity is important, namely, it reflects the potentiality of genetic bollocks. Genetic drift is the effect of random transmission of alleles during reproduction to succeeding generations. When numbers of reproducing individuals are small, the genetic penning of the population of offspring can differ by chance from what is expected given the composition of the parents. If two coins are flipped, it would not be that unusual for both to distinguish up heads. If a thousand coins are flipped, the ratio of heads to tails will always be very near the expected 5050 ratio. Genetic drift is stronger when populations are small or reduced, and weakens the strength of adaptational selection.Like differentiation, there are several formulations for Ne that can provide different values and are designed to measure different aspects of the population. The cause Ne is the probability of identity by descent for two alleles chosen at random. It is a retrospective assessment of population diversity. The variance Ne assesses the variance of the offsprings allele frequency, and is thus forward looking. It measures recent population changes that extend to its genetic composition. Ne can represent the number of actively breeding individuals in the population or the number of individuals in an ideal population needed to reconstitute the diversity in an actual population. It is almost always less than the census population (Nc). It is a key value in conservation genetics and population genetics in general, since it reflects the history and future potential of a population. Increasing drift (decreasing Ne) tends to neutralize the force of directional selection, permits retention of deleterious mutations and hampers the ability of populations to adapt to stresses (9).Despite its importance, Ne can be difficult to estimate in wild populations due to uncertainties of the demographic, genetic and biological context (17, 24). It can be affected by sample size, overlapping generations, sampling interval, sex ratios, gene flow, age-structure, variation in family size, fluctuate population size or selection. Increasing the numbers of markers is less important than large samples for accurate estimates as much as 10% of the Ne has been recommended Palstra, 2008 84. Its interpretation can also be uncertain. Estimated Ne has been used as an aid in predicting extinction using the concept of a tokenish viable population size. Some have suggested that at an Ne of 50-500 a population will experience extinction in the short- or long-term (7). Others have argued that this might occur at Ne = 5000 (14). While it is clear that lack of diversity has an impact on extinction (21), it is also clear that there cannot be a universally accepted number for the borderline viable population size (6, 23) . In any case, theory suggests that there is a number defined by the amount of genetic drift below which populations are likely to go extinct on their own. The range for this number is context-specific and will require multiple species-specific studies under multiple conditions. This kind of analysis might contribute to developing a stopping recipe as control measures approach elimination. 1 Leptospira spp. are an exception with 2 broadside chromosomes.2 The condition where all individuals have an equal opportunity to reproduce with all other individualsLR1G?LR2Does it stand for something?