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Download Population Genetics, Molecular Evolution, And The Neutral Theory: Selected Papers

Abstract

Nosotros nowadays selected topics of population genetics and molecular phylogeny. As several first-class review articles have been published and generally focus on European and American scientists, here, we emphasize contributions by Japanese researchers. Our review may too be seen as a belated fifty-twelvemonth celebration of Motoo Kimura'southward early seminal paper on the molecular clock, published in 1968.

Introduction

In contempo years, large amounts of DNA sequencing data accept been generated in various projects such as 1000 Genomes (Genomes Project et al. 2010, 2012, 2015), the ALSPAC database (Fraser et al. 2013; Hameed et al. 2017), and Icelandic (Gudbjartsson et al. 2015), and Japanese populations (Nagasaki et al. 2015). Major achievements of these efforts have been every bit follows: (1) Larger genetic variation is observed within populations than between populations, and (ii) each individual harbors big numbers of variants with low allele frequencies. These findings have long agone been predicted by population genetics and evolutionary studies. Therefore, it is instructive to wait back at historic achievements in population genetics.

Splendid reviews of population genetics have been written (Chakraborty 2006; Charlesworth and Charlesworth 2017; Crow 1987; Crow and Kimura 1970) documenting the evolution of population genetics from early achievements by Mendel (1866), Hardy (1908), and Weinberg (1908) up to highly sophisticated theoretical developments, more often than not by American, British, and Japanese scientists. Hither, we review selected aspects of population genetics, genome evolution, and molecular phylogeny with an emphasis on contributions past Japanese researchers.

Historical aspects of population genetics and road to the neutral theory

Darwin's theory of evolution through selection very well explains changes in time of heritable phenotypes. In the early 1900s, focusing on the evolution of genetic variants in the population, R. A. Fisher, Southward. Wright, and J. B. S. Haldane made fundamental theoretical contributions to population genetics (Provine 1971), Fisher in his 1922 paper (Fisher 1922), which was the get-go to introduce diffusion equations into population genetics, and Haldane in developing in 1927 (Haldane 1927) the approximation of change of numbers of copies of very rare mutants by branching processes. Wright (1938) developed the theory on the effects of genetic drift, that is, random changes in small populations. While his theory was supported just past a minority of scientists in an era when the molecular basis of genes had yet to be proven and the effects of genetic drift were underestimated, Wright's theory made a great contribution to connecting Mendelian Genetics with the Darwinian theory of evolution.

More recently, it has become credible that many molecular changes take no furnishings on phenotypes. Based on Wright'south drift hypothesis and Haldane's approximation model of an advantageous mutation (Haldane 1927), Motoo Kimura (1964) and then developed his neutral theory based on backward diffusion models, which showed the probability of fixation to goose egg of a variant in the population to be equal to two s(N _eastward/N), where s is the selection coefficient, N the size of the breeding population, and N _east the effective population size.

Mutations and selection are driving forces for development. Basically, mutations occur at random Deoxyribonucleic acid bases. Harmful mutations tend to be eliminated within a short period of time and do not contribute to long-term evolution. This process is called negative or purifying selection equally opposed to positive choice. Before Kimura (1964) proposed his neutral theory, there was little notion of neutral variation, although, at about the same time, Lewontin and Hubby (1966) considered the possibility of neutral mutation equally a possible reason for a big corporeality of variation which they institute in electrophoretic mobility. Still, natural selection was the mainstream hypothesis with the idea that advantageous variations in populations are the driving forces for development, and deleterious variations are removed in a rapid fashion.

At the time, population genetics usually considered two alleles at each cistron locus based on the assumption of genes being base pairs. On the other hand, Kimura and Crow (1964) assumed an space allele model ("neutral isoalleles") and proposed that genetic variation in populations arises as to the residuum betwixt mutations and genetic drift. Comparing hemoglobin molecules betwixt different organisms, Kimura (1968) postulated that amino-acid substitution rates are then high that they can simply exist explained by neutral mutations. In other words, mutation and random changes in a finite population can maintain considerable variation through random fixation of selectively neutral or nearly neutral mutants. In the calorie-free of current knowledge, however, Kimura's reasoning appears somewhat flawed. For example, he argued that the "toll of natural selection" would exist too high otherwise—more consideration has shown that no cost is imposed past benign mutations in the absence of environmental deterioration. He also used the total amount of DNA without distinguishing protein-coding regions and non-coding regions. Nonetheless, Kimura'south contributions to population genetics accept been tremendous.

Together with the Darwinian choice hypothesis, the neutral theory is one of the ii pillars of genome development. Thus, 'survival of the luckiest, and not necessarily of the fittest' may be a expert explanation for the evolution of a great majority of genetic changes (Chakraborty 2006). Interestingly, Kimura (1969) also proposed the "infinite sites model". In this model, if the mutation charge per unit is low and the effective population size is pocket-sized (θ = 4N _eµ « 1), a mutant variant will e'er announced at a different site in the genome. If and so, identity past state at the variant tin exist regarded equally identity by descent, and in this respect, the space sites model represents one of the bases for genome-wide association studies using SNPs as genetic markers in unrelated individuals (Sella and Barton 2019).

The nigh neutral theory

The evolutionary rate, λ =fμ, in the neutral theory (f is the proportion of neutral mutations among all mutations in a gene, μ is the mutation charge per unit) disregards mutations favorable to survival and merely classifies other mutations into neutral (f) and deleterious (1 −f) mutations. Nonetheless, the extent of harmfulness measured by the choice coefficient, due south, is a continuous quantity. Based on these ideas, Tomoko Ohta (Ohta 1973, 1992, 2002), who had built the foundation of the neutral theory with Motoo Kimura, proposed the "most neutral" theory, where slightly disadvantageous mutations (attenuated mutations) could persist in the population by run a risk if the population is small. Thus, co-ordinate to her publications (Ohta 1973, 1992, 2002), a substantial fraction of changes is caused past random fixation of nearly neutral changes, a class that includes intermediates between neutral and advantageous, as well every bit between neutral and deleterious classes, although other population geneticists may disagree with this view (Kondrashov 1995; Nei 2005).

A divergence from the neutral theory is that the nearly neutral theory allows for interactions between (1) genes having occurred through weak natural choice (or weak deleterious option) and (2) genes without weak natural selections, and for the two types of genes to jointly contribute to evolution past opposing the action of genetic drift (Hurst 2009). In the nearly neutral theory, the effect of genetic drift is weakened, and slightly disadvantageous mutations are excluded from a population if the population is extremely large; if a population is pocket-size, then slightly disadvantageous mutations are kept (some are even stock-still) by the effects of genetic drift. It seems that the structure of very large datasets such as thousand Genomes or the Exome Sequencing Project 6500 can be explained by the nearly neutral theory, because in that location is increasing evidence that selection pressure in pocket-sized populations such equally mammals including humans is weaker compared to that in bequeathed species, and slightly disadvantageous mutations have been accumulating in populations (Kosiol et al. 2008; Nelson et al. 2012; Nielsen et al. 2009; Tennessen et al. 2012).

Evolutionary rate of pseudogenes

In the second half of 1970, accumulated sequencing data confirmed the prediction past King and Jukes (1969) that mutation rates of synonymous variants are college than those of non-synonymous variants, which supports the neutral theory. Kimura (1977) asserted that co-ordinate to the neutral mutation-random drift hypothesis, most mutant substitutions detected among organisms should be the results of random fixation of selectively neutral or almost neutral mutations. This conjecture was verified by the analysis of mutation rates of pseudogenes, that is, of genes with sequences similar to normal genes having lost their functions as they were duplicated to another location in the genome, and in the process, their transcription sequences were not preserved. Based on the neutral theory, Takashi Miyata calculated the replacement rates of not-synonymous variants and synonymous variants in nucleotide sequences of several pseudogenes, α and β globin, and compared them with those in their functional counterparts (Miyata and Hayashida 1981). Results showed that replacement rates were uniformly the same in different pseudogenes and almost equal to the mutation rate, with no other gene evolving at a faster rate. This observation clearly supported the neutral theory.

Junk DNA, a term publicized by Susumu Ohno (1972) but rarely used today (see below), contains inter-genic regions, most of which are SINEs (Short INterspersed Elements) and LINEs (Long INterspersed Elements). The term 'junk DNA' was mentioned by a few other authors in 1972 and even 9 years earlier in a newspaper little known to human geneticists (Ehret and De Haller 1963), simply Ohno's name tends to be virtually closely associated with this term.

Evolutionary rates of junk DNA are expected to be similar to those of synonymous mutations and pseudogenes. In mammals, virtually of the genome regions, likely well more than 90%, are predicted to be junk Dna. Therefore, evolutionary rates of whole genomes can be approximated every bit existence those of junk DNA.

In 2012, the Encyclopedia of Deoxyribonucleic acid elements (ENCODE) project (Consortium 2012) proved biochemical functions of eighty% of the genome, especially exterior of protein-coding regions, which was once considered junk DNA. The findings from the ENCODE project enable us to further explore the function of the human genome.

Genes and genomic duplication

In higher organisms, genomic duplication is known to exist extremely of import for evolution. Early on, Susumu Ohno proposed that evolution is caused by genomic duplication, which was a visionary idea at a time when big sequencing information were not yet bachelor (Ohno 1970). It has been shown empirically and by theoretical considerations that the advantage of creating new copies of genomes (or private genes) can effect in college fitness. An alternative model explaining genomic duplication is DDC (Duplication Degeneration Complementation) (Lynch and Conery 2000). In the DDC model, regulatory elements each decision-making independent functions are duplicated and random null mutations in the regulatory elements through degeneration atomic number 82 to sub-functionalization, where the regulatory elements complement each other to achieve the total ancestral repertoires. What is important in the process is that it does non crave the assist of positive selection, that is, functional diversification. In practise, it has been proposed that the selection of slightly disadvantageous mutations works with the expression level of each factor changing. Therefore, genetic duplication is predicted to proceed in a nearly neutral fashion based on mutation pressure and genetic migrate. In improver, "concerted evolution" in minisatellites used as markers for hyper-polymorphisms, and in other sequences such as rRNA genes tin be explained well past Ohno's theory (Hillis et al. 1991; Jeffreys et al. 1985).

Molecular phylogeny

Through evolution, currently, living organisms take descended from mutual ancestors. Systematic biology seeks to unravel relationships among organisms and to institute evolutionary trees. As every biological science student knows, the classical approach to such discoveries is through painstaking analysis of morphological details. Depending on which of these phenotypes are considered most important, different relationships among organisms sally.

Rather than relying on phenotypes that may or may not exist heritable, molecular phylogeny relies on DNA sequences and their comparisons among organisms. Researchers with various backgrounds have made meaning contributions to methods of creating phylogenetic trees and the evaluation of phylogenetic relationships. In this field, Joseph Felsenstein almost single-handedly established this field equally a special branch of population genetics (Felsenstein 2004). For example, he introduced the maximum-likelihood method of establishing phylogenetic trees (Felsenstein 1978) (see below). One of his other contributions is the "Felsenstein Zone" (Huelsenbeck and Hillis 1993), which involves the phenomenon of "long-co-operative attraction"; that is, long branches will appear similar to each other and announced as sister taxa on a tree even though they do non share a mutual beginnings. The Zone is the set of trees on which long-branch attraction occurs. Such phenomena have been observed in many datasets and simulation analyses, and have led to the discovery of long-co-operative attraction, which leads to wrongly assuming phylogeny where none exists (Huelsenbeck and Hillis 1993). Furthermore, Felsenstein contributed greatly to molecular phylogeny past developing a program package, PHYLIP, combining various phylogenic tree estimation methods including DNAML. Cheers to his contributions, molecular phylogeny has become increasingly pop for empirical molecular evolutionists.

The development of molecular phylogeny may not seem to exist related to disease factor discovery. However, it greatly contributes to such discoveries through interpretation of huge sequencing datasets obtained from the 1000 Genomes project and other projects. Generating a molecular phylogenetic tree for phylogenetic relationships between species led to the discovery of gene families (orthologs and paralogs). The coalescent theory, which examines the gene tree in a species by reversing the fourth dimension, was too practical to reconstruct the demographic history of species of interest. In particular, regarding the coalescent theory, Tajima (1983) estimated nucleotide diversity based on the limited DNA polymorphic data, calculated the time of coalescence of genes sampled from a unmarried population, and their theory applies to a few genes at the fourth dimension of population splitting. Takahata and Nei (1985) farther developed a coalescent theory from DNA sequencing data and theoretically showed that alleles with deep coalescences are relatively rare.

The neighbor-joining method

Many methods for creating (estimating) phylogenic copse have been developed. Historically, these methods can roughly be classified into two groups, distance matrix methods and grapheme country methods. The erstwhile uses a distance matrix and estimates evolutionary distance such equally the number of amino-acrid substitutions or base substitutions based on all possible pairs of OTUs (Operational Taxonomic Units). This method was offset applied to create phylogenic copse in the class of the UPGMA (Unweighted Pair Grouping Method with Arithmetic hateful) method, where clusters of neighboring OTUs are created and connected in a stepwise style. The method is used not only for amino-acid or base-pair sequences but besides in numerical taxonomy, which deals with expression analysis using microarray (Eisen et al. 1998) or trait-encoded information (Sokal and Michener 1958). Still, since this method assumes constant evolutionary speed, it is problematic to employ to amino-acrid or base-pair sequence data. To overcome this trouble, altitude methods were developed that did not assume a molecular clock (Fitch and Margoliash 1967). Masatoshi Nei and Naruya Saitou greatly improved upon this method and developed a much faster procedure (Saitou and Nei 1987). This method is one of the "star decomposition" methods that determine which, of a given pair of sequences, reduces length of the total tree nearly and combine neighboring nodes until all OTUs are included. In the neighbor-joining method, "neighbors" keep track of nodes on a tree rather than taxa or clusters of taxa. A modified distance matrix is obtained in which the separation between each pair of nodes is adjusted on the basis of their average divergence from all other nodes. The tree is synthetic by joining the least-distant pair of nodes in this modified matrix. When two nodes are joined, their mutual ancestral node is added to the tree and the last nodes with their corresponding branches are removed from the tree. At each stage in the process, two terminal nodes are replaced by one new node. This iterative functioning finds "neighbors" one after another, which creates the final phylogenetic tree. The neighbor-joining method is the near commonly used distance matrix method. Starting in 1971, Nei proposed that Nei'south altitude be used for phylogenetic tree estimation, which was afterwards incorporated into the neighbor-joining program package MEGA (Kumar et al. 1994; Saitou and Nei 1987).

The 2nd group, character state methods, do not utilise a distance matrix and ascertain characters (phenotypes) and employ them for exploring tree topology. 1 of the examples of grapheme state methods is the maximum-likelihood method discussed in the next section.

The maximum-likelihood method

Maximum likelihood (ML) was developed by Fisher (1922) every bit a method to estimate parameters in statistical models. It has several advantages over other methods, merely tends to be more than complicated to apply than simpler methods. In population genetics, Luigi Luca Cavalli-Sforza first applied the ML method to an approach for creating phylogenic trees based on allele frequencies (Cavalli-Sforza and Edwards 1967). The first use of maximum-likelihood inference of trees from molecular sequences was by Jerzy Neyman (Felsenstein 2001; Neyman 1971). Felsenstein proposed ML for creating phylogenic trees based on allele frequencies as continuous quantities (Felsenstein 1973a), thus improving on the method previously proposed by Cavalli-Sforza, and introduced ML for estimating trees based on discrete datasets and the maximum parsimony benchmark (Felsenstein 1973b). Masami Hasegawa incorporated this approach into the MOLPHY program package and pioneered in the use of model selection methods such as AIC in comparison phylogenies (he was a member of Akaike's constitute) (Adachi and Hasegawa 1992, 1996).

The ML method is the nigh efficient approach amidst all tree structure methods. For example, imitation-positive evidence of relationships of long branches ("long-branch attraction") will not occur when trees are estimated past ML and the model of development is correct, although it can occur when the model is not right. Nevertheless, the ML method tends to be time-consuming and, for some big trees, may exist incommunicable to apply.

Impact of variants on multifactorial disorders and missing heritability

Based on the material mentioned then far, we volition now cover some topics on how progress in population genetics, genome evolution, and phylogenic studies can exist applied to medical research.

Multifactorial disorders are assumed to occur through interactions between multiple genetic and ecology factors. Therefore, identifying disease susceptibility genes has been considered difficult, and detecting interactions with environmental factors even more so. Peculiarly in the 1990s, such considerations were widespread, quite in contrast to the relative ease with which increased numbers of gene identifications for monogenic disorders accept been achieved. However, at that place was a researcher to struggle with the solution for genetic causes of multifactorial disorders at that time. Ituro Inoue succeeded in narrowing down disease loci using linkage assay with affected sib-pairs and constructing haplotypes of the angiotensinogen (AGT) factor using limited data (Inoue et al. 1997). Inoue assessed linkage disequilibrium (LD) at each site in the AGT cistron and further demonstrated by in vitro functional assay that the combination between A (− 6) and T235 alleles affects the expression of the AGT gene. This study was visionary, since LD block structures had yet to be proved at that fourth dimension.

Afterward that, genome-wide association studies with large SNP data over the whole genome became bachelor thanks to the HAPMAP projection, SNP collections past Perlegen Scientific discipline, LD block measurements, and construction of haplotype maps (HapMap 2005; Hinds et al. 2005). Although such genome-wide studies contributed to narrowing downwards locations of disease susceptibility genes, results are even so insufficient for identifying many specific disease susceptibility genes, for example Moyamoya disease (Liu et al. 2011). A remaining claiming has been that identified susceptibility loci show just small odds ratios, and all susceptibility loci combined only explicate up to 30% of most of the illness causes. These numbers are generally smaller than the heritability calculated in the previous twin studies, which is known every bit "missing heritability" (Manolio et al. 2009). Nowadays, however, methods for calculating SNP-based heritability have been adult (Yang et al. 2017) that come upwards with heritability estimates close to those obtained by classical segregation assay, and part of the problem seems to be resolved.

Out-of-Africa hypothesis

Contempo advances in sequencing technology have enabled the identification of whole genome structures at population levels. These successes take made it possible to compare electric current human genome sequences with ancient genomes such as Man neanderthalensis or Denisova hominin, which profoundly contributed to the understanding of the origin of Human sapiens (Nielsen et al. 2017). Allan Wilson, along with Rebecca Cann and Mark Stoneking, showtime proposed the "out-of-Africa" hypothesis (Cann et al. 1987), which claims that Homo sapiens originated in Africa so spread all over the earth. They based their results on the assay of mitochondrial DNA of various populations, which represented the kickoff phylogenic tree of Homo sapiens. Piece of work past Masatoshi Nei contributed to the out-of-Africa hypothesis: In the 1970s, Nei calculated heterozygosity for various protein isozymes and created phylogenic copse of Human sapiens (Nei and Roychoudhury 1972, 1974; Nielsen et al. 2017). An interesting finding based on this work is that genetic variation estimated past Nei's distance or Wright'southward F _st is larger within populations than between populations (Lewontin 1972), which was afterwards confirmed by the 1000 Genomes project. In other words, there are greater differences amid individuals in a given population than betwixt populations. However, this notion has besides been challenged (Edwards 2003).

Relationship between recent explosive population growth and origin of deleterious variants

Numerous human genome sequence projects such as g Genomes revealed that each private harbors considerable numbers of private mutations. This fact had been proposed by Haldane in his "genetic load" theory, which predicted an association between the numbers of variants possessed over populations and survival rate (Haldane 1937). In his theory, he claimed that if we consider genetic load for the whole genome rather than a given locus, the fitness decrease by mutations is equal to the mutation rate, v, irrespective of the extent of selection. He also claimed that pathogenic mutations accrue in the grade of heterozygous variants unless such mutations are excluded as lethal homozygous mutations (Haldane 1937) (this theory is as well known as the Haldane–Muller principle). The theory of genetic load was further elaborated upon by Kimura (1960); for neutral mutations, there is no load. Based on this groundwork, for variants whose distributions differ among populations, estimating the age of each variant becomes possible, which is important for agreement the history of human evolution, as well as for developing novel methods for disease factor discovery. The mathematical theory of coalescence allowing haplotype and allele ages to be calculated was developed by John Kingman (2000), and Kimura and Ohta (1973) proposed a formula for determining allele age, − iix(1 −x)/log(ten). This formula represents the expected historic period of a neutral mutation of frequency x in a stationary population based on a improvidence process used in classical population genetics. Although there was a give-and-take regarding the restrictive assumption that the age distribution of a mutant allele with population frequency x should exist the aforementioned equally the distribution of the time to extinction of the allele, conditional on extinction, it made a great contribution to later calculations of allele age (Fu et al. 2013). Computing allele age assuming the infinite many sites of model of mutation developed Kimura and Ohta formula, it showed that about three-quarters of all protein-coding SNV predicted to be deleterious across in the past 5000 years (Fu et al. 2013). This try provides of import practical data that tin can be prioritized variants in disease gene discovery.

Inbreeding (mating betwixt relatives) has so far non been discussed here equally it does not lead to changes in allele frequencies. Information technology does, however, atomic number 82 to a decrease in heterozygotes and a corresponding increase in homozygotes. As is well known, at a bi-allelic locus with allele frequency p, the proportion of heterozygotes is given by 2p(1 −p)(i −F), where F is the inbreeding coefficient. In many human populations, F tends to be rather modest; for example, F = 0.00038 in the UK (Pattison 2016). An exception is offspring of first cousins (F = 1/16). For rare deleterious recessive traits with illness allele frequency p, recessive offspring of first-cousin marriages occur with probability p ² +p(1 −p)F (Haldane and Moshinsky 1939). Through genetic linkage of such a trait with SNPs surrounding it, rare recessive traits tend to be located in long runs of homozygous SNPs (homozygosity mapping (Lander and Botstein 1987)). More modern approaches have been adult, for case, based on the Hamming distance between chromosomes in affected and control individuals (Imai et al. 2015). This approach revealed a mutation, p.H96R in the BOLA3 cistron, possibly having originated in a unmarried Japanese founder individual (Imai et al. 2016).

Darwinian (evolutionary) medicine

From the viewpoint of Darwinian medicine (or evolutionary medicine), which is medicine based on evolution (Williams and Nesse 1991), we discuss a few aspects of how discovering variants can interpret into medical care.

In the 1960s, Richard Lewontin discovered in Drosophila populations that heterozygosity is more ofttimes observed than expected (Lewontin and Hubby 1966). He interpreted this finding every bit advantageous fitness of heterozygosity compared to the homozygous land of the wild type or mutant (so-called over-dominance, or balancing option) and emphasized its importance for survival. After the establishment of the neutral theory, every bit described beneath, the importance of balancing selection for some types of variants with high allele frequencies was rediscovered. Theoretical studies on natural selection also greatly progressed and "Tajima's D", developed by Fumio Tajima, is computed as the difference between two measures of genetic diverseness: the hateful number of pairwise differences and the number of segregating sites, each scaled so that they are expected to be the aforementioned in a neutrally evolving population of abiding size. This is a unique contribution to statistical genetics by Japanese researchers in that this method tin can appraise whether a given variant scattered over the whole genome is neutral or nether selection pressure level (Tajima 1989).

Analyzing genome sequences in several populations using the techniques of next-generation sequencing reveals some signals with positive selection pressure. One such instance is infection-related diseases. Regarding the natural selection for resistance of a pathogen, this was revealed by adjacent-generation sequencing to represent the strongest positive option force per unit area in human development; that is, the well-known balancing signals on glycoproteins and positive option signals on TLRs (Ferrer-Admetlla et al. 2008). Applying the history of evolution for various pathogens to affliction susceptibility research will probable identify functional variants as well as intra-cellular mechanisms and treatment for diverse diseases. We believe that selection pressure for aboriginal pathogens will affect not simply infectious and auto-immune diseases merely also other traits. Recently, the clan between life-style diseases and natural selection has become an attractive topic. Using forty traits from the UK Biobank, functional low-frequency variants take been revealed to be under negative selection (Gazal et al. 2018). An alternative proposition has been that positive selection acts on susceptibility loci for life-mode diseases. An case is the thrifty gene hypothesis. At the dawn of the era of genomic medicine, the ancient history of human evolution is a powerful tool for understanding human being biology leading to improving human health.

Discussion

In this outline, we deliberately emphasized contributions to population genetics past Japanese researchers—in this field, Japanese scientists have arguably carried out comprehensive fundamental work. Thus, we feel justified in presenting this short review of population genetics from a Japanese point of view.

In terms of future developments in population genetics, we expect DNA sequencing to play an ever-increasing role. In an era where human genome sequence projects are underway around the world, established population genetics principles volition be applied to reveal more detailed migration history, population history, and mechanisms of choice pressure, especially in small ethnic populations (Antonio et al. 2019; Lipson et al. 2020).

Technological advances have changed the mural of genetic screening (Ceyhan-Birsoy et al. 2019). Together with epidemiological and molecular genetics studies, population genetics approaches accept demonstrated the association between disease mechanisms and mutations in populations. Cystic fibrosis is one such successful example (Bong et al. 2020). By identifying the relationship between specific mutations and a cystic fibrosis transmembrane conductance regulator (CFTR) defect, we can meliorate patient intendance including disease monitoring and treatment decisions. In the future, comeback of patient care in more diseases tin be achieved by the combination of population genetics, epidemiological studies, and molecular genetics studies.

With the huge corporeality of genomic information currently bachelor, information technology is challenging to link genotypes to phenotypes, predict regulatory functions, and allocate mutant types. Therefore, new and innovative approaches are needed for further agreement of medical biology and connections to genetic disease. One arroyo is to collect previously reported SNV information and create a suitable mathematical model. As an example, a report by Davis et al. (2016) describes a biophysical metric of cardiomyocyte role, which accurately predicts human being cardiac phenotypes.

Another approach is based on neural networks to automatically extract relevant features from input data (Zou et al. 2019). Since advances in sequencing technologies provide large amounts of data, it is realistic to utilize machine learning as a tool for assay in the field of clinical healthcare and population genetics. Although deep learning has great potential, attempts to utilize it to genomics have simply just begun. For case, SpliceAI, a 32-layer deep neural network (DNN) was developed for predicting de novo mutations with predicted splice-altering consequences in patients with neurodevelopmental disorders, which paves the way for the application of deep learning on complex genetic variant prediction (Jaganathan et al. 2019). To identify pathogenic mutations in patients with rare diseases, a DNN model was developed combining common variants derived from human and six not-human primate species. The proposed model achieved an 88% accuracy and found 14 unreported candidate genes associated with intellectual disability (Sundaram et al. 2018).

Finally, epidemics and pandemics of viruses and their sequences provide rich sources of information. For example, population genetic analyses of 103 SARS-CoV-two genomes indicated the presence of 2 major lineages, although the implications of these evolutionary changes remained unclear (Tang et al. 2020).

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Acknowledgements

Helpful comments by Prof. Joseph Felsenstein on an earlier version of this manuscript are gratefully best-selling. This work was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI, Grant numbers JP20K08497 and JP18K15863 (A. O.), and Grant number 19K09408 (Due south. Y.).

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1. Intractable Disease Research Centre, Juntendo University, Tokyo, Japan

   Atsuko Okazaki

2. Laboratory of Statistical Genetics, Rockefeller University, 1230 York Avenue, New York, NY, 10065, The states

   Atsuko Okazaki & Jurg Ott

3. Section of Molecular Pharmacology, National Cerebral and Cardiovascular Center, Osaka, Japan

   Satoru Yamazaki

4. Division of the Human being Genetics, National Institute of Genetics, Shizuoka, Japan

   Ituro Inoue

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Correspondence to Jurg Ott.

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Okazaki, A., Yamazaki, South., Inoue, I. et al. Population genetics: past, present, and future. Hum Genet 140, 231–240 (2021). https://doi.org/x.1007/s00439-020-02208-5

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• Received: 12 May 2020

• Accepted: 14 July 2020

• Published: eighteen July 2020

• Consequence Date: February 2021

• DOI : https://doi.org/10.1007/s00439-020-02208-5

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