Mosaicism  or  genetic mosaicism  is a condition in which a  multicellular organism  possesses more than one  genetic line  as the result of genetic  mutation . [ 1 ] [ 2 ]  This means that various genetic lines resulted from a single  fertilized   egg . Mosaicism is one of several possible causes of  chimerism , wherein a single organism is composed of cells with more than one distinct  genotype .


Genetic mosaicism can result from many different mechanisms including chromosome  nondisjunction ,  anaphase lag , and  endoreplication . [ 3 ]  Anaphase lagging is the most common way by which mosaicism arises in the preimplantation embryo. [ 3 ]  Mosaicism can also result from a  mutation  in one cell during  development , in which case the mutation will be passed on only to its daughter cells (and will be present only in certain adult cells). [ 4 ]  Somatic mosaicism is not generally inheritable as it does not generally affect germ cells. [ 2 ]


In 1929,  Alfred Sturtevant  studied mosaicism in  Drosophila , a genus of fruit fly. [ 5 ]  H. J. Muller in 1930 demonstrated that mosaicism in  Drosophila  is always associated with  chromosomal rearrangements , and Schultz in 1936 showed that, in all cases studied, these rearrangements were associated with  heterochromatic  inert regions. Several hypotheses on the nature of such mosaicism were proposed. One hypothesis assumed that mosaicism appears as the result of a break and loss of chromosome segments.  Curt Stern  in 1935 assumed that the structural changes in the chromosomes took place as a result of  somatic crossing , as a result of which mutations or small chromosomal rearrangements in somatic cells. Thus the inert region causes an increase in mutation frequency or small chromosomal rearrangements in active segments adjacent to inert regions. [ 6 ]


In the 1930s, Stern demonstrated that  genetic recombination , normal in  meiosis , can also take place in  mitosis . [ 7 ] [ 8 ]  When it does, it results in somatic (body) mosaics. These organisms contain two or more genetically distinct types of tissue. [ 9 ]  The term  somatic mosaicism  was used by CW Cotterman in 1956 in his seminal paper on  antigenic variation . [ 10 ]


In 1944, M. L. Belgovskii proposed that mosaicism could not account for certain mosaic expressions caused by chromosomal rearrangements involving heterochromatic inert regions. The associated weakening of biochemical activity led to what he called a  genetic chimera . [ 6 ]


Germline or gonadal mosaicism is a particular form of mosaicism wherein some  gametes —i.e.,  sperm  or  oocytes —carry a mutation, but the rest are normal. [ 11 ] [ 12 ]  The cause is usually a mutation that occurred in an early stem cell that gave rise to all or part of the gametes.


Somatic mosaicism (also known as clonal mosaicism) occurs when the  somatic cells  of the body are of more than one genotype. In the more common mosaics, different genotypes arise from a single fertilized egg cell, due to  mitotic  errors at first or later cleavages.


Somatic mutation leading to mosaicism is prevalent in the beginning and end stages of human life. [ 10 ]  Somatic mosaics are common in  embryogenesis  due to  retrotransposition  of  long interspersed nuclear element-1  (LINE-1 or L1) and  Alu   transposable elements . [ 10 ]  In early development, DNA from undifferentiated cell types may be more susceptible to mobile element invasion due to long,  unmethylated  regions in the genome. [ 10 ]  Further, the accumulation of DNA copy errors and damage over a lifetime lead to greater occurrences of mosaic tissues in aging humans. As longevity has increased dramatically over the last century, human genome may not have had time to adapt to cumulative effects of  mutagenesis . [ 10 ]  Thus,  cancer research  has shown that somatic mutations are increasingly present throughout a lifetime and are responsible for most  leukemia ,  lymphomas , and solid tumors. [ 13 ]


The most common form of mosaicism found through prenatal diagnosis involves  trisomies . Although most forms of trisomy are due to problems in  meiosis  and affect all cells of the organism, some cases occur where the trisomy occurs in only a selection of the cells. This may be caused by a nondisjunction event in an early mitosis, resulting in a loss of a chromosome from some trisomic cells. [ 14 ]  Generally, this leads to a milder  phenotype  than in nonmosaic patients with the same disorder.


In rare cases,  intersex  conditions can be caused by mosaicism where some cells in the body have  XX  and others XY chromosomes ( 46, XX/XY ). [ 15 ] [ 16 ]  In the fruit fly  Drosophila melanogaster , where a fly possessing two X chromosomes is a female and a fly possessing a single X chromosome is a sterile male, a loss of an X chromosome early in embryonic development can result in sexual mosaics, or  gynandromorphs . [ 5 ] [ 17 ]  Likewise, a loss of the  Y chromosome  can result in XY/X mosaic males. [ 18 ]


An example of this is one of the milder forms of  Klinefelter syndrome , called 46,XY/47,XXY mosaic wherein some of the patient's cells contain XY chromosomes, and some contain XXY chromosomes. The 46/47 annotation indicates that the XY cells have the normal number of 46 total chromosomes, and the XXY cells have a total of 47 chromosomes.


Also  monosomies  can present with some form of mosaicism. The only non-lethal full monosomy occurring in humans is the one causing  Turner's syndrome . Around 30% of Turner's syndrome cases demonstrate mosaicism, while complete monosomy (45, X) occurs in about 50–60% of cases.


Mosaicism isn't necessarily deleterious, though. Revertant somatic mosaicism is a rare recombination event with a spontaneous correction of a mutant,  pathogenic allele . [ 19 ]  In revertant mosaicism, the healthy tissue formed by mitotic recombination can outcompete the original, surrounding mutant cells in tissues such as  blood  and  epithelia  that regenerate often. [ 19 ]  In the skin disorder  ichthyosis with confetti , normal skin spots appear early in life and increase in number and size over time. [ 19 ]


Other endogenous factors can also lead to mosaicism, including  mobile elements ,  DNA polymerase  slippage, and unbalanced  chromosome segregation . [ 10 ]  Exogenous factors include  nicotine  and  UV radiation . [ 10 ]  Somatic mosaics have been created in  Drosophila  using X‑ray treatment and the use of  irradiation  to induce somatic mutation has been a useful technique in the study of genetics. [ 20 ]


True mosaicism should not be mistaken for the phenomenon of  X-inactivation , where all cells in an organism have the same genotype, but a different copy of the X chromosome is expressed in different cells. The latter is the case in normal (XX) female mammals, although it is not always visible from the phenotype (as it is in  calico cats ). However, all  multicellular organisms  are likely to be somatic mosaics to some extent. [ 21 ]


Gonosomal mosaicism is a type of somatic mosaicism that occurs very early in the organisms development and thus is present within both germline and somatic cells. [ 1 ] [ 22 ]  Somatic mosaicism is not generally inheritable as it does not usually affect germ cells.  In the instance of gonosomal mosaicism, organisms have the potential to pass the genetic alteration, including to potential offspring because the altered allele is present in both somatic and germline cells. [ 22 ]


A frequent type of neuronal genomic mosaicism is  copy number variation . Possible sources of such variation were suggested to be incorrect  repairs of DNA damage  and  somatic recombination . [ 23 ]


One basic mechanism that can produce mosaic tissue is  mitotic recombination  or  somatic crossover . It was first discovered by  Curt Stern  in  Drosophila  in 1936. The amount of tissue that is mosaic depends on where in the tree of cell division the exchange takes place. A phenotypic character called "twin spot" seen in  Drosophila  is a result of mitotic recombination. However, it also depends on the allelic status of the genes undergoing recombination. Twin spot occurs only if the heterozygous genes are linked in repulsion, i.e. the trans phase. The recombination needs to occur between the centromeres of the adjacent gene. This gives an appearance of yellow patches on the wild-type background in  Drosophila . another example of mitotic recombination is the Bloom's syndrome, which happens due to the mutation in the  blm  gene. The resulting BLM protein is defective. The defect in RecQ, a helicase, facilitates the defective unwinding of DNA during replication, thus is associated with the occurrence of this disease. [ 24 ] [ 25 ]


Genetic mosaics are a particularly powerful tool when used in the commonly studied  fruit fly , where specially selected strains frequently lose an X [ 17 ]  or a Y [ 18 ]  chromosome in one of the first embryonic cell divisions. These mosaics can then be used to analyze such things as courtship behavior, [ 17 ]  and female sexual attraction. [ 26 ]


More recently, the use of a  transgene  incorporated into the  Drosophila  genome has made the system far more flexible. The  flip recombinase (or  FLP )  is a gene from the commonly studied yeast  Saccharomyces cerevisiae  that recognizes "flip recombinase target" (FRT) sites, which are short sequences of DNA, and induces  recombination  between them. FRT sites have been inserted transgenically near the  centromere  of each chromosome arm of  D. melanogaster . The  FLP  gene can then be induced selectively, commonly using either the heat shock promoter or the  GAL4/UAS system . The resulting clones can be identified either negatively or positively.


In negatively marked clones, the fly is  transheterozygous  for a gene encoding a visible marker (commonly the  green fluorescent protein ) and an allele of a gene to be studied (both on chromosomes bearing FRT sites). After induction of  FLP  expression, cells that undergo recombination will have progeny homozygous for either the marker or the allele being studied. Therefore, the cells that do not carry the marker (which are dark) can be identified as carrying a mutation.


Using negatively marked clones is sometimes inconvenient, especially when generating very small patches of cells, where seeing a dark spot on a bright background is more difficult than a bright spot on a dark background. Creating positively marked clones is possible using the so-called  MARCM  ("mosaic analysis with a repressible cell marker" system, developed by  Liqun Luo , a professor at  Stanford University , and his postdoctoral student Tzumin Lee, who now leads a group at  Janelia Farm Research Campus . This system builds on the GAL4/UAS system, which is used to express GFP in specific cells. However, a globally expressed  GAL80  gene is used to repress the action of GAL4, preventing the expression of GFP. Instead of using GFP to mark the wild-type chromosome as above, GAL80 serves this purpose, so that when it is removed by  mitotic recombination , GAL4 is allowed to function, and GFP turns on. This results in the cells of interest being marked brightly in a dark background. [ 27 ]


In  human mitochondrial genetics ,  Haplogroup Z  is a  human mitochondrial DNA (mtDNA) haplogroup .


Haplogroup Z is believed to have arisen in Central Asia, and is a descendant of  haplogroup CZ .


The greatest clade diversity of haplogroup Z is found in  East Asia  and  Central Asia .  However, its greatest frequency appears in some peoples of  Russia , such as  Evens  from  Kamchatka  (8/39 Z1a2a, 3/39 Z1a3, 11/39 = 28.2% Z total) and from  Berezovka, Srednekolymsky District, Sakha Republic  (3/15 Z1a3, 1/15 Z1a2a, 4/15 = 26.7% Z total), and among the  Saami  people of northern Scandinavia. With the exception of three Khakasses who belong to Z4, [ 5 ]  two Yakut who belong to Z3a1, [ 5 ]  two Yakut, a Yakutian Evenk, a Buryat, and an Altai Kizhi who belong to Z3(xZ3a, Z3c), [ 5 ]  and the presence of the Z3c clade among populations of Altai Republic, [ 5 ]  nearly all members of haplogroup Z in North Asia and Europe belong to subclades of Z1. The TMRCA of Z1 is 20,400 [95% CI 7,400 <-> 34,000] ybp according to Sukernik  et al.  2012, [ 2 ]  20,400 [95% CI 7,800 <-> 33,800] ybp according to Fedorova  et al.  2013, [ 5 ]  or 19,600 [95% CI 12,500 <-> 29,300] ybp according to YFull. [ 3 ]  Among the members (Z1, Z2, Z3, Z4, and Z7) of haplogroup Z, Nepalese populations were characterized by rare clades Z3a1a and Z7, of which Z3a1a was the most frequent sub-clade in Newar, with a frequency of 16.5%. [ 6 ]  Z3, found in East Asia, North Asia, and MSEA, is the oldest member of haplogroup Z with an estimated age of ~ 25.4 Kya. [ 6 ]   Haplogroup Z3a1a is also detected in other Nepalese populations, such as Magar (5.4%), Tharu, Kathmandu (mixed population) and Nepali-other (mixed population from Kathmandu and Eastern Nepal). [ 6 ]  S6).  Z3a1a1 detected in Tibet, Myanmar, Nepal, India, Thai-Laos and Vietnam trace their ancestral roots to China with a coalescent age of ~ 8.4 Kya [ 6 ]


Fedorova  et al.  2013 have reported finding Z* (xZ1a, Z3, Z4) in 1/388 Turks and 1/491 Kazakhs. These individuals should belong to Z1* (elsewhere observed in a Tofalar), Z2 (observed in Japanese), Z7 (observed in the Himalaya), Z5 (observed in Japanese), or basal Z* (observed in a  Blang  individual in  Northern Thailand ). [ 5 ]


This phylogenetic tree of haplogroup Z subclades is based on the paper by Mannis van Oven and Manfred Kayser  Updated comprehensive phylogenetic tree of global human mitochondrial DNA variation [ 4 ]  and subsequent published research.


Multifactorial diseases  are not confined to any specific pattern of single gene inheritance and are likely to be caused when multiple genes come together along with the effects of  environmental factors . [ 1 ]


In fact, the terms ' multifactorial'  and ' polygenic'  are used as synonyms and these terms are commonly used to describe the architecture of disease causing genetic component. [ 2 ]  Multifactorial diseases are often found gathered in families yet, they do not show any distinct pattern of inheritance. It is difficult to study and treat multifactorial diseases because specific factors associated with these diseases have not yet been identified. Some common multifactorial disorders include  schizophrenia ,  diabetes ,  asthma ,  depression ,  high blood pressure ,  Alzheimer's ,  obesity ,  epilepsy ,  heart diseases ,  Hypothyroidism ,  club foot ,  cancer ,  birth defects  and even  dandruff .


The  multifactorial threshold model [ 3 ]  assumes that gene defects for multifactorial traits are usually distributed within populations.  Firstly, different populations might have different thresholds. This is the case in which occurrences of a particular disease is different in males and females (e.g.  Pyloric stenosis ). The distribution of susceptibility is the same but threshold is different. Secondly, threshold may be same but the distributions of susceptibility may be different. It explains the underlying risks present in first degree relatives of affected individuals.


Multifactorial disorders exhibit a combination of distinct characteristics which are clearly differentiated from Mendelian inheritance.


The risk for multifactorial disorders is mainly determined by universal risk factors. Risk factors are divided into three categories; genetic, environmental and complex factors (for example overweight).


Genetic risk factors are associated with the permanent changes in the base pair sequence of human genome. In the last decade, many studies have been generated data regarding genetic basis of multifactorial diseases. Various polymorphism have been shown to be associated with more than one disease, examples include  polymorphisms  in  TNF-a ,  TGF-b  and  ACE  genes, as well as mutations in BRCA1. BRCA2, BARD1, and BRIP1. [ 6 ] [ 7 ] [ 8 ] [ 9 ]


Environmental risk factors vary from events of life to medical interventions. The quick change in the patterns of morbidity, within one or two generations, clearly demonstrates the significance of environmental factors in the development and reduction of multifactorial disorders. [ 10 ]  Environmental risk factors include change in life style (diet, physical activity, stress management) and medical interventions (surgery, drugs).


Many risk factors originate from the interactions between genetic and environmental factors and referred as complex risk factors. Examples include  epigenetic  changes, body weight, pollution, and plasma cortisol level. [ 11 ]


Autosomal  or  sex-linked  single gene conditions generally produce distinct phenotypes, said to be discontinuous: the individual either has the trait or does not. However, multifactorial traits may be discontinuous or continuous. [ citation needed ]


Continuous traits exhibit normal distribution in population and display a gradient of phenotypes while discontinuous traits fall into discrete categories and are either present or absent in individuals. It is interesting to know that many disorders arising from discontinuous variation show complex phenotypes also resembling continuous variation  [ 12 ]  This occurs due to the basis of continuous variation responsible for the increased susceptibility to a disease. According to this theory, a disease develops after a distinct liability threshold is reached and severity in the disease phenotype increases with the increased liability threshold. On the contrary, disease will not develop in the individual who does not reach the liability threshold. Therefore, an individual either having disease or not, the disease shows discontinuous variation. [ citation needed ]


An example of how the liability threshold works can be seen in individuals with cleft lip and palate. Cleft lip and palate is a birth defect in which an infant is born with unfused lip and palate tissues. An individual with cleft lip and palate can have unaffected parents who do not seem to have a family history of the disorder. [ citation needed ]


Francis Galton  was the first scientist who studied multifactorial diseases and was the cousin of  Charles Darwin . Major focus of Galton was on 'inheritance of traits' and he observed "blending" characters. [ 13 ]  The average contribution of each several ancestor to the total heritage of the offspring  [ 14 ]  and is now known as continuous variation. When a trait (human height) exhibiting  continuous variation  is plotted against a graph, the majority of population distribution is centered around the mean.  [ 15 ]   Galton's work is contrary to work done by Gregor Mendel; as the latter studied "nonblending" traits and kept them in different categories. [ 16 ]   The traits exhibiting discontinuous variation, occur in two or more distinct forms in a population as Mendel found in color of petals. [ citation needed ]


[ 9 ]
 [ 4 ]


Museomics  is the study of  genomic  data obtained from  ancient DNA  (aDNA) and historic DNA (hDNA) specimens in  museum collections . [ 1 ] [ 2 ]
Early research in this area focused on short sequences of DNA from  mitochondrial genes , but sequencing of  whole genomes  has become possible. [ 1 ]
 Next-generation sequencing  (NGS) and  high-throughput sequencing  (HTS) methods can be applied to the analysis of genetic datasets extracted from collections materials. [ 3 ]  Such techniques have been described as a "third revolution in sequencing technology". [ 4 ]  Like  radiocarbon dating , the techniques of museomics are a transformative technology. Results are revising and sometimes overturning previously accepted theories about a wide variety of topics such as the  domestication of the horse . [ 5 ] [ 6 ]


Museum collections contain unique resources such as  natural history  specimens, which can be used for genome-scale examinations of species, their evolution, and their responses to environmental change.  Ancient DNA provides a unique window into genetic change over time. It enables scientists to directly study evolutionary and ecological processes, comparing ancient and modern populations, identifying distinct populations, and revealing patterns of change such as  extinctions  and  migrations . [ 7 ] [ 8 ] [ 9 ]  Research may be used to identify isolated populations and inform conservation priorities. [ 2 ]


However, museum specimens can be poorly preserved and are subject to degradation [ 7 ]  and contamination. [ 2 ] [ 10 ]  Genomic analyses face considerable challenges as a result of the highly degraded DNA typical of museum specimens. DNA from such samples is often subject to post-mortem nucleotide damage such as the hydrolytic deamination of  cytosine  (C) to  uracil  (U) residues.  PCR  amplification of damaged templates can further substitute uracils with  thymine  (T), completing a C to T substitution path. Such errors tend to occur towards the ends of molecules, accumulate with time, and can be significant in specimens a century-old or later. Robust genomic and statistical techniques are needed to rigorously detect and avoid errors and genotyping uncertainties when carrying out analyses based on museum collections. [ 7 ]  Optimal methods for working with hDNA and aDNA can differ as a result of differences in their DNA degradation history. [ 1 ]


Museomics also involves destructive sampling, irreversibly removing parts of sometimes rare specimens to obtain DNA. [ 11 ]  This can be contentious for curators and collection staff, [ 1 ]  involving a variety of ethical issues around the handling and destruction of objects, colonial acquisition and repatriation practices, and present-day social and political implications of research. Museums, universities and journals are increasingly developing ethics statements, best practices and guidelines for such work. [ 12 ] [ 13 ]


The  mutation accumulation theory of aging  was first proposed by  Peter Medawar  in 1952 as an evolutionary explanation for biological aging and the associated decline in fitness that accompanies it. [ 1 ]  Medawar used the term ' senescence ' to refer to this process. The theory explains that, in the case where harmful  mutations  are only expressed later in life, when reproduction has ceased and future survival is increasingly unlikely, then these mutations are likely to be unknowingly passed on to future generations. [ 2 ]  In this situation the force of  natural selection  will be weak, and so insufficient to consistently eliminate these mutations. Medawar posited that over time these mutations would accumulate due to  genetic drift  and lead to the evolution of what is now referred to as aging.


Despite  Charles Darwin 's completion of his theory of  biological evolution  in the 19th century, the modern logical framework for evolutionary theories of aging wouldn't emerge until almost a century later. Though  August Weismann  did propose his theory of programmed death, it was met with criticism and never gained mainstream attention. [ 3 ]  It wasn't until 1930 that  Ronald Fisher  first noted the conceptual insight which prompted the development of modern aging theories. This concept, namely that the force of natural selection on an individual decreases with age, was analysed further by  J. B. S. Haldane , who suggested it as an explanation for the relatively high prevalence of  Huntington's disease  despite the autosomal dominant nature of the mutation. Specifically, as Huntington's only presents after the age of 30, the force of natural selection against it would have been relatively low in pre-modern societies. [ 2 ]  It was based on the ideas of Fisher and Haldane that Peter Medawar was able to work out the first complete model explaining why aging occurs, which he presented in a lecture in 1951 and then published in 1952 [ 1 ]


Amongst almost all populations, the likelihood that an individual will reproduce is related directly to their age. [ 1 ]  Starting at 0 at birth, the probability increases to its maximum in young adulthood once sexual maturity has been reached, before gradually decreasing with age. This decrease is caused by the increasing likelihood of death due to external pressures such as  predation  or illness, as well as the internal pressures inherent to organisms that experience senescence. In such cases deleterious mutations which are expressed early on are strongly selected against due to their major impact on the number of offspring produced by that individual. [ 3 ]  Mutations that present later in life, by contrast, are relatively unaffected by selective pressure, as their carriers have already passed on their genes, assuming they survive long enough for the mutation to be expressed at all. The result, as predicted by Medawar, is that deleterious late-life mutations will accumulate and result in the evolution of aging as it is known colloquially. [ 2 ]  This concept is portrayed graphically by Medawar through the concept of a " selection shadow ". The shaded region represents the 'shadow' of time during which selective pressure has no effect. [ 4 ]  Mutations that are expressed within this selection shadow will remain as long as reproductive probability within that age range remains low. [ citation needed ]


In populations where extrinsic mortality is low, the drop in reproductive probability after maturity is less severe than in other cases. The mutation accumulation theory therefore predicts that such populations would evolve delayed senescence. [ 5 ]  One such example of this scenario can be seen when comparing birds to organisms of equivalent size. It has been suggested that their ability to fly, and therefore lower relative risk of predation, is the cause of their longer than expected life span. [ 6 ]  The implication that flight, and therefore lower predation, increases lifespan is further born out by the fact that bats live on average 3 times longer than similarly sized mammals with comparable metabolic rates. [ 7 ]  Providing further evidence, insect populations are known to experience very high rates of extrinsic mortality, and as such would be expected to experience rapid senescence and short life spans. The exception to this rule, however, is found in the longevity of eusocial insect queens. As expected when applying the mutation accumulation theory, established queens are at almost no risk of predation or other forms of extrinsic mortality, and consequently age far more slowly than others of their species. [ 8 ]


In the interest of finding specific evidence for the mutation accumulation theory, separate from that which also supports the similar antagonistic pleiotropy hypothesis, an experiment was conducted involving the breeding of successive generations of  Drosophila Melanogaster .  Genetic models predict that, in the case of mutation accumulation, elements of fitness, such as reproductive success and survival, will show age-related increases in  dominance , homozygous genetic variance and additive variance.  Inbreeding depression  will also increase with age. This is because these variables are proportional to the equilibrium frequencies of deleterious alleles, which are expected to increase with age under mutation accumulation but not under the antagonistic pleiotropy hypothesis. This was tested experimentally by measuring age specific reproductive success in 100 different genotypes of  Drosophila Melanogaster,  with findings ultimately supporting the mutation accumulation theory of aging. [ 9 ]


Under most assumptions, the mutation accumulation theory predicts that mortality rates will reach close to 100% shortly after reaching post-reproductive age. [ 10 ]  Experimental populations of  Drosophila Melanogaster,  and other organisms, however, exhibit age-specific mortality rates that plateau well before reaching 100%, making mutation accumulation alone an insufficient explanation. It is suggested instead that mutation accumulation is only one factor among many, which together form the cause of aging. In particular, the mutation accumulation theory, the antagonistic pleiotropy hypothesis and the disposable soma theory of aging are all believed to contribute in some way to senescence. [ 11 ]


Neofunctionalization , one of the possible outcomes of  functional divergence , occurs when one gene copy, or  paralog , takes on a totally new function after a  gene duplication  event.  Neofunctionalization is an adaptive mutation process; meaning one of the gene copies must mutate to develop a function that was not present in the ancestral gene. [ 1 ] [ 2 ] [ 3 ]  In other words, one of the duplicates retains its original function, while the other accumulates molecular changes such that, in time, it can perform a different task. [ 4 ]


The process of neofunctionalization begins with a  gene duplication  event, which is thought to occur as a defense mechanism against the accumulation of deleterious mutations. [ 5 ] [ 6 ] [ 7 ]  Following the gene duplication event there are two identical copies of the ancestral gene performing exactly the same function. This redundancy allows one the copies to take on a new function. In the event that the new function is advantageous, natural selection positively selects for it and the new mutation becomes fixed in the population. [ 3 ] [ 8 ]
The occurrence of neofunctionalization can most often be attributed to changes in the coding region or changes in the regulatory elements of a gene. [ 6 ]  It is much more rare to see major changes in protein function, such as subunit structure or substrate and ligand affinity, as a result of neofunctionalization. [ 6 ]


Neofunctionalization is also commonly referred to as "mutation during non-functionality" or "mutation during redundancy". [ 9 ]   Regardless of if the mutation arises after non-functionality of a gene or due to redundant gene copies, the important aspect is that in both scenarios one copy of the duplicated gene is freed from selective constraints and by chance acquires a new function which is then improved by natural selection. [ 6 ]  This process is thought to occur very rarely in evolution for two major reasons. The first reason is that functional changes typically require a large number of amino acid changes; which has a low probability of occurrence. Secondly, because deleterious mutations occur much more frequently than advantageous mutations in evolution. [ 6 ]  This makes the likelihood that gene function is lost over time (i.e. pseudogenization) far greater than the likelihood of the emergence of a new gene function. [ 8 ]
Walsh discovered that the relative probability of neofunctionalization is determined by the selective advantage and the relative rate of advantageous mutations. [ 10 ]  This was proven in his derivation of the relative probability of neofunctionalization to pseudogenization, which is given by:

 ρ

 S
 −
 1

 1
 −

 e

 s

 {\displaystyle {\frac {\rho \,\!S-1}{1-e^{s}}}}

   where ρ is the ratio of advantageous mutation rate to null mutation rate and S is the population selection 4NeS  (Ne: effective population size S: selection intensity). [ 10 ]


In 1936,   Muller   originally proposed neofunctionalization as a possible outcome of a gene duplication event. [ 11 ]  In 1970,  Ohno  suggested that neofunctionalization was the only evolutionary mechanism that gave rise to new gene functions in a population. [ 6 ]  He also believed that neofunctionalization was the only alternative to pseudogenization. [ 2 ]   Ohta  (1987) was among the first to suggest that other mechanisms may exist for the preservation of duplicated genes in the population. [ 6 ]  Today, subfunctionalization is a widely accepted alternative fixation process for gene duplicates in the population and is currently the only other possible outcome of functional divergence. [ 2 ]


Neosubfunctionalization occurs when neofunctionalization is the result of  subfunctionalization . In other words, once a gene duplication event occurs forming paralogs that after an evolutionary period subfunctionalize, one gene copy continues on this evolutionary journey and accumulates mutations that give rise to a new function. [ 6 ] [ 12 ]  Some believe that neofunctionalization is the end stage for all subfunctionalized genes.  For instance, according to Rastogi and Liberles "Neofunctionalization is the terminal fate of all duplicate gene copies retained in the genome and subfunctionlization merely exist as a transient state to preserve the duplicate gene copy." [ 2 ]   The results of their study become punctuated as population size increases.


The evolution of the antifreeze protein in the Antarctic  zoarcid  fish  Lycodichthys  dearborni  provides a prime example of neofunctionalization after gene duplication.  In the case of the Antarctic zoarcid fish type III antifreeze protein gene (AFPIII;  P12102 ) diverged from a paralogous copy of sialic acid synthase (SAS) gene. [ 13 ]  The ancestral SAS gene was found to have both sialic acid synthase and rudimentary ice-binding functionalities. After duplication one of the paralogs began to accumulate mutations that lead to the replacement of SAS domains of the gene allowing for further development and optimization of the antifreeze functionality. [ 13 ]  The new gene is now capable of noncolligative freezing-point depression, and thus is neofunctionalized. [ 13 ]  This specialization allows Antarctic zoarcid fish to survive in the frigid temperatures of the Antarctic Seas.


Another example concerns the  light-sensitive opsin proteins in vertebrate eyes  that allow them to see different wavelengths of light. Extant vertebrates typically have four  cone  opsin classes (LWS, SWS1, SWS2, and Rh2) as well as one  rod  opsin class ( rhodopsin , Rh1), all of which were inherited from early vertebrate ancestors. These five classes of vertebrate visual opsins emerged through a series of gene duplications beginning with LWS and ending with Rh1. [ 14 ] [ 15 ]


Limitations exist in neofunctionalization as a model for functional divergence primarily because:


Neurocriminology  is an emerging sub-discipline of  biocriminology  and  criminology  that applies  brain imaging  techniques and principles from  neuroscience  to understand, predict, and prevent crime.


While crime is partially a social and environmental problem, the main idea behind neurocriminology (also known as neurolaw) is that the condition of an individual's brain often needs to be included in the analysis for a complete understanding. [ 1 ] [ 2 ]  This can include conditions such as brain tumors, psychoses, sociopathy, sleepwalking, and many more. Deviant brain theories have always been part of biocriminology, which explains crime with biological reasons. [ 3 ]  Neurocriminology has become mainstream during the past two decades, [ timeframe? ] [ 4 ]  since contemporary biocriminologists focus almost exclusively on brain [ 5 ]  due to significant advances in neuroscience. Even though neurocriminology is still at odds with traditional sociological theories of crime, [ 4 ]  it is becoming more popular in the scientific community. [ 6 ]


The origins of neurocriminology go back to one of the founders of modern criminology, 19th-century Italian  psychiatrist  and prison doctor  Cesare Lombroso , whose beliefs that the crime originated from brain abnormalities were partly based on phrenological theories about the shape and size of the human head. Lombroso conducted a postmortem on a serial killer and rapist, who had an unusual indentation at the base of the skull. Lombroso discovered a hollow part in the killer's brain where the cerebellum would be. Lombroso's theory was that crime originated in part from abnormal brain physiology and that violent criminals where throwbacks to less evolved human types identifiable by ape-like physical characteristics. Criminals, he believed, could be identified by physical traits, such as a large jaw and sloping forehead. [ 6 ]  The contemporary neuroscientists further developed his idea that physiology and traits of the brain underlie all crime. [ 7 ]  The term “neurocriminology” was first introduced [ when? ]  by James Hilborn (Cognitive Centre of Canada) and adopted [ when? ]  by the leading researcher in the field,  Dr. Adrian Raine , the chair of the Criminology Department at University of Pennsylvania. [ 8 ]  He was the first to conduct brain imaging study on violent criminals. [ when? ] [ 9 ]


Many recent studies [ which? ]  have revealed that sometimes structural and functional abnormalities [ which? ]  are so striking that anyone can see them. [ citation needed ]  Some violent offenders, [ which? ]  however, have subtle structural or functional abnormalities [ which? ]  and even highly experienced neuroradiologists cannot detect these irregularities right away. [ citation needed ]  Yet, the abnormalities can be detected using brain imaging and state-of-the-art analytic tools. [ 10 ]


Studies on structural deficiencies suggest that people consistently behaving antisocially have structurally impaired brains. [ citation needed ]  The abnormalities can be either of general character or affect specific regions of the brain that control emotions, aggression or are responsible for ethical decisions:


Low number of neurons in the prefrontal cortex .
A study in 2000 determined that people with a history of persistent antisocial behavior had an 11 percent reduction in the volume of gray matter in the prefrontal cortex, while white matter volume was normal. [ 11 ]
Similarly, A 2009 meta-analysis study, which pooled together the findings of 12 anatomical brain-imaging studies conducted on offender populations, found that the prefrontal cortex of the brain is indeed structurally impaired in offenders. [ 12 ]


Underdeveloped amygdalae . Two studies found that both the left and especially the right amygdalae are impaired in psychopaths. The psychopaths had on average 18 percent reduction in the volume of the right amygdala. [ 13 ] [ 14 ]


Cavum septi pellucidi maldevelopment . A study in 2010 suggested that people with  cavum septi pellucidi  were prone to psychopathy, antisocial personality disorder, and had more charges and convictions for criminal offenses. This brain maldevelopment was especially linked to lifelong antisocial behavior, i.e. a reckless disregard for self and others, lack of remorse, and aggression. [ 15 ]


Bigger right hippocampus . A 2004 study suggested that the psychopaths’ right hippocampus that partially controls emotions and regulates aggression was significantly bigger than the left. This asymmetry was also true in normal people, but it was much more noticeable in psychopaths. [ 16 ]


Increase in the volume of the striatum . A study in 2010 found that psychopathic individuals showed a 10 percent increase in the volume of the striatum. [ 17 ]


Damage by foreign objects . A large number of studies on structural damage by foreign objects convincingly shows that adults suffering head injuries damaging the prefrontal cortex show impulsive and antisocial behavior that does not conform to the norms of society. [ 18 ]
There is a number of famous life stories showing the same causal connection. For example, P. Gage was a well-respected, well-liked, and responsible gentleman. In 1848 because of a construction accident he suffered a serious damage to his brain when a metal rod propelled by an explosive entered his lower left cheek and exited from the top-middle part of his head. Gage healed quickly. After that accident, however, he became erratic, disrespectful, and vulgar. Gage had been transformed from a well-controlled, well-respected person to an individual with psychopathic traits. [ 19 ]


Damage by tumors . There is also a number of famous U.S. criminal cases showing that damage of the brain by tumors can result in the same transformation as the damage by foreign objects.


Charles Whitman, for instance, was a young man who studied architectural engineering at the University of Texas. Whitman had no history of violence or crime. As a child, he scored 138 on the Stanford-Binet IQ test, placing in the 99th percentile. He was an Eagle Scout, volunteered as a scoutmaster, and served in Marine Corps. In 1966 Whitman unexpectedly killed his mother as well as wife, ascended the belltower of the University of Texas, Austin, and fired a rifle at students below. He killed 15 people and wounding 31 more before police officers shot him. Whitman in his final note complained of inability to control his thoughts and requested an autopsy, which revealed a brain tumor in the hypothalamus region of his brain, a growth that, some hypothesized, put pressure on his amygdala. [ 20 ] [ 21 ]


Another example would be Michael Oft. Oft was a teacher in Virginia who had no prior psychiatric nor deviant behavior history. At the age of forty, his behavior suddenly changed. He began to frequent massage parlors, collect child pornography, abuse his step-daughter, and was soon found guilty of child molestation. Mr. Oft opted for a treatment program for pedophiles, but still couldn't resist soliciting sexual favors from staff and other clients at the rehabilitation center. A neurologist advised a brain scan, which showed a tumor growing at the base of his orbitofrontal cortex, compressing the right prefrontal region of his brain. After the tumor was removed, Mr. Oft's emotion, behavior and sexual activity returned to normal. But after several months of normal behavior Mr. Oft again began to collect child pornography. Neurologists rescanned his brain and found that the tumor had grown back. After the second surgery removing the tumor, his behavior has been totally appropriate. [ 22 ]


Similarly to neurophysiological studies neurofunctional showed that brains of criminals and psychopaths not only are structures differently but also operate in a different way. As you can see below, both structural and functional abnormalities tend to affect the same areas of the brain. These are the major abnormalities found:


Lack of Activation in the Prefrontal Cortex . A number of studies replicated the observance that violent criminals’ brains showed a significant reduction in prefrontal glucose metabolism. [ 23 ] [ 12 ]


Reduced Activity In The Amygdala . A study found that individuals with high psychopathy scores showed reduced activity in the amygdala during emotional, personal moral decision-making. [ 24 ]


Dysfunctional Posterior Cingulate . Two studies found that posterior cingulate functions poorly in adult criminal psychopaths and aggressive patients. [ 25 ] [ 26 ]


Reduced Cerebral Blood Flow in Angular Gyrus . A couple of studies found reduced cerebral blood flow in angular gyrus of murderers and impulsive, violent criminals. [ 27 ] [ 28 ] [ 29 ]


Higher Activation of Subcortical Limbic Regions . A 1998 study showed higher activation of subcortical limbic regions of two groups of reactive and proactive murderers, especially in the more “emotional” right hemisphere of the brain. [ 30 ]


Functional Disturbances of the Hippocampus and Its Parahippocampal Gyrus . A number of studies suggest that this region of the brain is not working properly in murders and violent offenders in general. [ 31 ] [ 32 ]


Differences in hormone levels:  A 2022 study observed reported crime and hormone levels–mainly that of testosterone and cortisol–within a population of university students as consenting participants. Results from the research found that there was a positive direct correlation between testosterone levels and criminal behavior, particularly in terms of impulsive behavior and aggression. However, further tests may need to be conducted to determine if those behaviors are connected to criminal behavior through dominance-seeking behavior associated with testosterone or if it is more so due to testosterone’s influence in the mesolimbic reward system by instant gratification related to committing crime. It was also found that cortisol–a major hormone in the stress response system–in both high and low levels is correlated with an increase in criminal behavior. In response to stress or threats, high levels of cortisol boost energy, suppress the immune system and increase cardiovascular activity while low levels are associated with signs of psychopathy including a lack of empathy. The two hormones were found to interact to create influence on criminal behavior with low levels of cortisol and baseline levels of testosterone correlating with income-generating crime.  [ 33 ]


Effects of drugs : Illegal drug use and drug abuse are found to be highly correlated with antisocial behaviors leading to crime. Drugs function to mimic and take the place of naturally-occurring neurotransmitters–or chemical brain signals–that activate brain chemical receptors and affect arousal, mood, as well as physiological and cognitive function among other neurophysiological effects. In cases of addiction, particular drugs may affect the brain’s rewards system, making it overly sensitive to the drug: thus making naturally occurring, healthy behaviors less rewarding and increasing deviant behaviors like attention-seeking, impulsivity, and aggression–often related to withdrawal behavioral traits–all of which can promote criminal behavior. In particular, inhibition caused by drug use can impair regular brain functioning, especially that of the pre-frontal cortex, impairing the ability to make decisions and perform higher-level thinking and reasoning that is otherwise critical in preventing criminal and deviant behaviors. [ 34 ]


Unlike the founding father of criminology, Cesare Lombroso, who thought that crime was fundamentally biological in its origin and criminals lacked free will altogether, contemporary neurocriminologists seem to take the middle ground approach. [ citation needed ]  They do not argue that biological factors alone cause behavioral problems, but recognize that behavior results from interaction between biology and environment. [ 35 ] [ 36 ]  Some authors, [ who? ]  however, are more determinist in their views. As Stanford neuroscientist  David Eagleman  writes:  "Free will may exist (it may simply be beyond our current science), but one thing seems clear: if free will does exist, it has little room in which to operate. It can at best be a small factor riding on top of vast neural networks shaped by genes and environment. In fact, free will may end up being so small that we eventually think about bad decision-making in the same way we think about any physical process, such as diabetes or lung disease." [ 37 ]


US legal defense teams increasingly use brain scans as mitigating evidence in trials of violent criminals and sex offenders. See  Neurolaw  for more. Here are some of the most famous cases:


In 1991, a sixty-five-year-old advertising executive with no prior history of crime or violence after an argument strangled his wife, opened the window and threw her out of their 12th-floor apartment. His defense team had a structural brain scan done using MRI and PET scan. The images showed a big piece missing from the prefrontal cortex of the brain, i.e., a subarachnoid cyst was growing in his left frontal lobe. The defense team used these images to argue that Weinstein had an impaired ability to regulate his emotions and make rational decisions. The team went with an insanity defense, and the prosecution and defense agreed to a plea of manslaughter. As a result, Weinstein was given a seven-year sentence in contrast to the twenty-five-year sentence he would have served if he had been convicted of second-degree murder. He ended up serving until 2006. [ 38 ]


Bustamante was a well-behaved teenager who suddenly at the age of 22 became a career criminal. His crimes included theft, breaking and entering, drug offenses, and robbery. In 1990 Bustamante was charged with a homicide. The defense team discovered that the client had suffered a head injury from a crowbar at the age of twenty. Bustamante's behavior changed fundamentally after that, transforming him from a normal individual into an impulsive and emotionally labile criminal. The defense team had his client's brain scanned, which revealed malfunctioning of the prefrontal cortex. At the end the jury believed that Bustamante's brain was not normal and spared him from the death penalty. [ 39 ]


In 1999, Page robbed, raped and killed a female student in Denver. He later was found guilty of first-degree murder and was a candidate for the death penalty. Professor A. Raine from the University of Pennsylvania was an expert witness for defense and brought Page into a laboratory to assess his brain function. Brain imaging scans revealed a distinct lack of activation in the ventral prefrontal cortex. Professor Raine argued for a deep-rooted biological explanation for Mr. Page's violence, who escaped death penalty partly on the basis of his brain pathology. [ 6 ]


Even though currently there are no preventive programs in place utilizing the recent discoveries in neurocriminology, there are a number of offender rehabilitation programs (Cognitive Centre of Canada).


Some scientists [ who? ]  propose using brain imaging to help decide which soon-to-be-released offenders are at greater risk for reoffending. The brain imaging data would be used along with common factors like age, prior arrests, and marital status. [ 6 ]  To support this idea, in a 2013 study, Professor  Kent Kiehl  from the University of New Mexico studying the population of 96 male offenders in the state's prisons found that offenders with low activity in the anterior cingulate cortex where twice as likely to commit an offense in the four years after their release as those who had high activity in this region. [ 6 ]  Similarly, Dustin Pardini conducted that which shows that men with a smaller amygdala are three times more likely to commit violence three years after their release. [ 40 ]


Trials demonstrated the efficacy of a number of medications, i.e. stimulants antipsychotics, antidepressants and mood stabilizers, in diminishing aggression in adolescents and children. [ 6 ]
Even a simple omega-3 supplements in the diets of young offenders reduces offending and aggression. [ 41 ] [ 42 ]  However, drug treatment is subject to vary based on biological and environmental influences. Variation in genes predisposes differences in biological systems and brain structure and function within individuals, influencing outcomes.  [ 34 ]


Meditation can also affect brains, and even change them permanently. In 2003 Professor Richie Davidson from the University of Wisconsin performed a revolutionary study. People were randomly selected into either a mindfulness training group or a control group that was put on a waiting list for training. Davidson showed that even eight weekly sessions of meditation enhanced left frontal EEG functioning. [ 43 ]  Similar study was later replicated by Professor Holzel. [ 44 ]


In preventing crime on the basis of association to neurobiological function, there could also be adverse effects in increased stigma around those with atypical brain functioning and mental disorders. Although much research has been discovered in relation to neurocriminology, all atypical brain functions do not objectively result in deviant, criminal, or problematic behaviors. This bias can potentially bring bias towards those with divergent mental functionings into being categorized as those who are unable to make–morally–correct decisions. It is also worth considering that while focusing on neurobiological aspects, the social-environmental facets and causes of criminal behaviors cannot be ignored. Research has found that although an early intervention may benefit those who are at risk of violent, anti-social behaviors–especially in children and adolescents–it can adversely cause negative effects. When stigma is associated with the labeling of mental functions, it can increase anxiety and potentially trigger the development of maladaptive cognitions and narratives. Although neurological research is important in crime prevention, performing intervention in light of the criminal justice system is ideally done while respecting the rights of people and earning consent to perform prevention strategies. [ 45 ]


Neurogenomics  is the study of how the genome of an organism influences the development and function of its nervous system. [ 1 ]  This field intends to unite  functional genomics  and  neurobiology  in order to understand the nervous system as a whole from a genomic perspective.


The nervous system in vertebrates is made up of two major types of cells –  neuroglial cells  and  neurons . Hundreds of different types of neurons exist in humans, with varying functions – some of them process external stimuli; others generate a response to stimuli; others organize in centralized structures ( brain ,  spinal ganglia ) that are responsible for cognition, perception, and regulation of motor functions. Neurons in these centralized locations tend to organize in giant networks and communicate extensively with each other. Prior to the availability of  expression arrays  and  DNA sequencing methodologies , researchers sought to understand the cellular behaviour of neurons (including  synapse formation  and neuronal development and regionalization in the human nervous system) in terms of the underlying molecular biology and biochemistry, without any understanding of the influence of a neuron's genome on its development and behaviour. As our understanding of the genome has expanded, the role of networks of gene interactions in the maintenance of neuronal function and behaviour has garnered interest in the  neuroscience  research community. Neurogenomics allows scientists to study the nervous system of organisms in the context of these underlying regulatory and transcriptional networks. This approach is distinct from  neurogenetics , which emphasizes the role of single genes without a network-interaction context when studying the nervous system. [ 2 ]


In 1999, Cirelli & Tononi [ 3 ]  first reported the association of genome-wide brain gene expression profiling (using  microarrays ) with a behavioural phenotype in mice. Since then, global brain gene expression data, derived from microarrays, has been aligned to various behavioural quantitative trait loci (QTLs) and reported in several publications. [ 4 ] [ 5 ] [ 6 ]  However, microarray based approaches have their own problems that confound analysis – probe saturation can result in very small measurable variance of gene expression between genetically unique individuals, [ 7 ]  and the presence of single nucleotide polymorphisms (SNPs) can result in hybridization artifacts. [ 8 ] [ 9 ]  Furthermore, due to their probe-based nature, microarrays can miss out on many types of transcripts ( ncRNAs ,  miRNAs , and  mRNA   isoforms ). Probes can also have species-specific binding affinities that can confound comparative analysis.


Notably, the association between behavioural patterns and high  penetrance  single  gene loci  falls under the purview of  neurogenetics  research, wherein the focus is to identify a simple causative relationship between a single, high penetrance gene and an observed function/behaviour. However, it has been shown that several neurological diseases tend to be  polygenic , being influenced by multiple different  genes  and  regulatory regions  instead of one gene alone. There has hence been a shift from single gene approaches to network approaches for studying neurological development and diseases, a shift that has been greatly propelled by the advent of  next generation sequencing  methodologies.


Twin studies  have revealed that  schizophrenia , [ 10 ]   bipolar disorder , [ 11 ]   autism spectrum disorder  (ASD), [ 12 ] [ 13 ]  and  attention deficit hyperactivity disorder [ 14 ]  (ADHD) are highly heritable, genetically complex  psychiatric disorders . However, linkage studies have largely failed at identifying causative variants for psychiatric disorders such as these, primarily because of their complex genetic architecture. Multiple low penetrance  risk variants  can be aggregated in affected individuals and families, and sets of causative variants could vary across families. Studies along these lines have determined a  polygenic  basis for several  psychiatric disorders . [ 15 ]  Several independently occurring  de novo mutations  in patients  Alzheimer's disease  have been found to disrupt a shared set of functional pathways involved with neuronal signalling, for example. [ 16 ]  The quest to understand the causative biology of psychiatric disorders is hence greatly assisted by the ability to analyse entire genomes of affected and unaffected individuals in an unbiased manner. [ 17 ]


With the availability of massively parallel  next generation sequencing  methodologies, scientists have been able to look beyond the probe based captures of expressed genes.  RNA-seq , for example, identifies 25-60% more expressed genes than microarrays do. In the upcoming field of neurogenomics, it is hoped that by understanding the genomic profiles of different parts of the brain, we might be able to improve our understanding of how the interactions between genes and pathways influence cellular function and development. This approach is expected to be able to identify the secondary gene networks that are disrupted in neurological disorders, subsequently assisting drug development stratagems for brain diseases. [ 18 ]  The  BRAIN initiative  launched in 2013, for example, seeks to " inform the development of future treatments for brain disorders, including Alzheimer's disease, epilepsy, and traumatic brain injury " .


Rare variant association studies (RVAS) have highlighted the role of  de novo   mutations  in several  congenital  and early-childhood-onset disorders like  autism . [ 19 ] [ 20 ]  Several of these protein disrupting mutations have been able to be identified only with the aid of  whole genome sequencing  efforts, and validated with  RNA-Seq . Additionally, these mutations are not statistically enriched in individual genes, but rather, exhibit patterns of statistical enrichment in groups of genes associated with networks regulating neurological development and maintenance. Such a discovery would have been impossible with prior gene-centric approaches ( neurogenetics ,  behavioural neuroscience ). Neurogenomics allows for a high-throughput system-based approach for understanding the  polygenic  basis of  neuropsychiatric  disorders. [ 17 ]


When  autism  was identified as a distinct biological disorder in the 1980s, researchers found that autistic individuals showed a brain growth abnormality in the  cerebellum  in their early developmental years. [ 21 ]  Subsequent research has indicated that 90% of autistic children have a larger brain volume than their peers by 2 to 4 years of age, and show an expansion in the white and gray matter content in the  cerebrum . [ 22 ]  The white and gray matter in the cerebrum is associated with learning and cognition respectively, and the formation of  amyloid plaques  in the white matter has been associated with  Alzheimer's disease . These findings highlighted the influence of structural variance in the brain on psychiatric disorders, and have motivated the use of imaging technologies to map regions of divergence between healthy and diseased brains. Furthermore, while it may not always be possible to retrieve biological specimens from different areas live human brains,  neuroimaging  techniques offer a noninvasive means to understanding the biological basis of neurological disorders. It is hoped that an understanding of localization patterns of different psychiatric diseases could in turn inform network analysis studies in neurogenomics.


Structural Magnetic Resonance Imaging  (MRI) can be used to identify the structural composition of the brain. Particularly in the context of neurogenomics, MRI has played an extensive role in the study of  Alzheimer's disease  over the past four decades. It was initially used to rule out other causes of  dementia , [ 16 ]  but recent studies indicated the presence of characteristic changes in patients with Alzheimer's disease. As a result, MRI scans are currently being used as a neuroimaging tool to help identify the temporal and spatial pathophysiology of Alzheimer's disease, such as specific cerebral alterations and  amyloid imaging . [ 16 ]


The ease and non-invasive nature of MRI scans has motivated research projects that trace the development and onset of psychiatric diseases in the brain. Alzheimer disease has become a key candidate in this topographical approach to psychiatric diseases. For example, MRI scans are currently being used to track the resting and task-dependent functional profiles of brains in children with autosomal dominant Alzheimer disease. [ 23 ]  These studies have found indications of early onset brain alterations in at-risk individuals for Alzheimer's disease. [ 16 ]  The Autism Center of Excellence at University of California, San Diego, is also conducting MRI studies with children between 12 and 42 months, in the hopes of characterizing brain development abnormalities in children who present behavioural symptoms of autism. [ 24 ]


Additional research has indicated that there are specifics patterns of  atrophy  in the cerebrum (as a repercussion of  neurodegeneration ) in different neurological disorders and diseases. These disease-specific patterns of progression of atrophy can be identified with MRI scans, and provide a clinical phenotype context to neurogenomic research. The temporal information about disease progression provided by this approach can also potentially inform the interpretation of gene network-level perturbations in psychiatric diseases. [ 16 ]


One prohibitive feature of 2nd generation sequencing methodologies is the upper limit on the genomic range accessible by  mate-pairing.   Optical mapping  is an emerging methodology used to span large-scale variants that cannot usually be detected using paired end reads. This approach has been successfully applied to detect  structural variants  in  oligodendroglioma , a type of brain cancer. [ 25 ]  Recent work has also highlighted the versatility of optical maps in improving existing genome assemblies.  Chromosomal rearrangements ,  microdeletions , and large-scale  translocations  have been associated with impaired neurological and  cognitive function , for example in hereditary  neuropathy  and  neurofibromatosis . Optical mapping can significantly improve variant detection and inform gene interaction network models for the diseased state in neurological disorders.


Apart from neurological disorders, there are additional diseases that manifest in the brain and have formed exemplar use-case scenarios for the application of brain imaging in network analysis. In a classic example of imaging-genomic analyses, a research study in 2012 compared MRI scans and gene expression profiles of 104 glioma patients in order to distinguish treatment outcomes and identify novel targetable genomic pathways in  Glioblastoma Multiforme  (GBM). Researchers found two distinct groups of patients with significantly different organization of  white matter  (invasive vs non-invasive). Subsequent pathway analysis of the gene expression data indicated mitochondrial dysfunction as the top canonical pathway in an aggressive, low-mortality GBM phenotype. [ 26 ]


Expansion of brain imaging approaches to other diseases can be used to rule out other medical illnesses while diagnosing psychiatric disorders, but cannot be used to inform the presence or absence of a psychiatric disorder.


The current approaches in collecting gene expression data in human brains are to use either  microarrays  or  RNA-seq . Currently, it is rare to gather "live" brain tissue – only when treatments involve brain surgery is there a chance that brain tissue is collected during the procedure. This is the case with epilepsy.


Currently, gene expression data is usually collected on post mortem brains and this is often a barrier to neurogenomics research in humans. [ 27 ] [ 28 ]  After death, the amount of time between death and when the data from the post mortem brain is collected is known as the  post mortem interval  (PMI). Since RNA degrades after death, a fresh brain is optimal – but not always available. This in turn can influence a variety of downstream analyses. Consideration should be taken of the following factors when working with  'omics data  collected from post-mortem brains:


Differential diagnosis  also remains a critical pre-analytical confounder of cohort-wide studies of spectrum neurological disorders. Specifically, this has been noted to be a problem for Alzheimer's disease and autism spectrum disorder studies. Furthermore, as our understanding of the diverse symptoms and genomic underpinnings of various neurogenomic disorders improves, the diagnostic criteria itself undergoes rearrangements and review. [ 32 ]


Ongoing genomics research in neurological disorders tends to use animal models (and corresponding  gene homologs ) to understand the network interactions underlying a particular disorder due to ethical issues surrounding the retrieval of biological specimens from live human brains. This, too, is not without its roadblocks.


Neurogenomic research with a model organism is contingent on the availability of a fully sequenced and annotated reference genome. Additionally, the RNA profiles ( miRNA ,  ncRNA ,  mRNA ) of the model organism need to be well catalogued, and any inferences applied from them to humans must have a basis in functional/sequence  homology . [ 33 ]


Zebrafish  development relies on gene networks that are highly conserved among all  vertebrates . [ 34 ]  Additionally, with an extremely well annotated set of 12,000 genes and 1,000 early development mutants that are actually visible in the optically clear zebrafish embryos and larvae, zebrafish offer a sophisticated system for  mutagenesis  and real-time imaging of developing pathologies. This early development model has been employed to study the nervous system at cellular resolution. [ 35 ] [ 36 ]  The zebrafish model system has already been used to study  neuroregeneration [ 37 ]  and severe  polygenic  human diseases like cancer and heart disease. [ 38 ]  Several zebrafish mutants with behavioural variations in response to cocaine and alcohol dosage have been isolated and can also form a basis for studying the pathogenesis of behavioural disorders. [ 39 ] [ 40 ]


Rodent models have been preeminent in studying human disorders. These models have been extensively annotated with gene homologs of several  monogenic  disorders in humans.  Knockout studies  of these homologs have led to expansion of our understanding of network interactions of genes in human tissues. For example, the  FMR1  gene has been implicated with autism from a number of network studies. [ 41 ] [ 42 ]  Using a knockout of  FMR 1  in mice creates the model for  Fragile X Syndrome , one of the disorders in the  Autism spectrum . [ 43 ]


Mice  xenografts  are particularly useful for drug discovery, [ 44 ]  and were extremely important in the discovery of early  anti-psychotic  drugs. The development of animal models for complex psychiatric diseases has also improved over the last few years. Rodent models have demonstrated behavioural phenotype changes resembling a positive  schizophrenia  state, either after genetic manipulation or after treatment with drugs that target the areas of the brain suspected to influence hyperactivity or neurodevelopment. [ 45 ]  Interest has been generated in identifying the network disruptions mediated by these laboratory manipulations, and collection of genomic data from  rodent studies  has contributed significantly to a better understanding of the genomics of psychiatric diseases.


The first  mouse brain   transcriptome  was generated in 2008. [ 46 ]  Since then, extensive work has been done with building  social-stress  mice models to study the pathway level expression signatures of various psychiatric diseases. A recent paper simulated features of Post Traumatic Stress Disorder (PTSD) in mice, and profiled the entire transcriptome of these mice. [ 47 ]  The authors found differential regulation in many biological pathways, some of which were implicated in anxiety disorders ( hyperactivity ,  fear response ), mood disorders, and impaired cognition. These findings are backed by extensive  transcriptomic analyses  of anxiety disorders, and expression level changes in biological pathways involved with fear learning and memory are thought to contribute to the behavioural manifestations of these disorders. [ 47 ]  It is thought that functional enrichment of genes involved in long term synaptic potentiation, depression, and plasticity has an important role to play in the acquisition, consolidation, and maintenance of traumatic memories underlying anxiety disorders. [ 47 ] [ 48 ]


A common approach to using a mouse model is to apply an experimental treatment to a pregnant mouse in order to affect a whole litter. However, a key issue in the field is the treatment of litters in a statistical analysis. Most studies consider the total number of offspring produced as that may lead to an increase in statistical power. However, the correct way is to count by the number of litters and to normalize based on litter size. It was found that several autism studies incorrectly performed their statistical analyses based on total number of offspring instead of number of litters. [ 49 ]


Several anxiety disorders such as  post-traumatic stress disorder  (PTSD) involve  heterogeneous  changes in several different brain regions, such as the  hippocampus ,  amygdala , and  nucleus accumbens . The cellular encoding of traumatic events and the behavioral responses triggered by such events has been shown to lie primarily in changes in signaling molecules associated with  synaptic transmission .


Global  gene expression profiling  of the various gene regions implicated in fear and anxiety processing, using mice models, has led to the identification of temporally and spatially distinct sets of differentially expressed genes. Pathway analysis of these genes has indicated possible roles in  neurogenesis  and anxiety-related behavioural responses, alongside other functional and phenotypic observations. [ 47 ]


Mice models for brain research have contributed significantly to  drug development  and increased our understanding of the genomic underpinnings of several neurological diseases in the last generation.  Chlorpromazine , the first  antipsychotic  drug (discovered in 1951), was identified as a viable treatment option after it was shown to suppress response to aversive stimuli in rats in a behavioural screen.


The modelling and assessment of latent symptoms (thoughts, verbal learning, social interactions, cognitive behaviour) remains a challenge when using model organisms to study  psychiatric disorders  with a complex genetic  pathology . For example, a given genotype+phenotype in a mouse model must imitate the genomic underpinnings of a phenotype observed in a human.


This is a particularly crucial item of consideration in spectrum disorders such as  autism . Autism is a disorder whose symptoms can be divided into two categories: (i) deficits of social interactions and (ii) repetitive behaviours and restricted interests. Since mice tend to be more social creatures amongst all members of the order  Rodentia  currently being used as model organisms, mice are generally used to model human psychiatric disorders as closely as possible. Particularly for autism, the following work-arounds are currently in place to emulate human behavioural symptoms:


In any of these experiments, the 'autistic' mice have a 'normal' socializing partner and the scientists observing the mice are unaware ("blind") to the genotypes of the mice.


The gene expression profile of the  central nervous system  (CNS) is unique. Eighty percent of all human genes are expressed in the brain; 5,000 of these genes are solely expressed in the CNS. The human brain has the highest amount of gene expression of all studied mammalian brains. In comparison, tissues outside of the brain will have more similar expression levels in comparison to their mammalian counterparts. One source of the increased expression levels in the human brain is from the non-protein coding region of the genome. Numerous studies have indicated that the human brain have a higher level of expression in regulatory regions in comparison to other mammalian brains. There is also notable enrichment for more  alternative splicing  events in the human brain. [ 2 ]


Gene expression profiles also vary within specific regions of the brain. A  microarray study  showed that the transcriptome profile of the CNS clusters together based on region. A different study characterized the regulation of gene expression across 10 different regions based on their  eQTL  signals. [ 52 ]  The cause of the varying expression profiles relates to function,  neuron migration  and cellular heterogeneity of the region. Even the three layers of the  cerebral cortex  have distinct expression profiles. [ 53 ]


A study completed at Harvard Medical School in 2014 was able to identify developmental lineages stemming from single base neuronal mutations. The researchers sequenced 36 neurons from the cerebral cortex of three normal individuals, and found that highly expressed genes, and neural associated genes, were significantly enriched for single-neuron  SNVs . These SNVs, in turn, were found to be correlated with chromatin markers of transcription from fetal brain. [ 54 ]


Gene expression of the brain changes throughout the different phases of life. The most significant levels of expression are found during early development, with the rate of gene expression being highest during fetal development. This results from the rapid growth of neurons in the embryo. Neurons at this stage are undergoing  neuronal differentiation ,  cell proliferation , migration events and dendritic and  synaptic development . [ 55 ]  Gene expression patterns shift closer towards specialized functional profiles during embryonic development, however, certain developmental steps are still ongoing at parturition. Consequently, gene expression profiles of the two brain hemispheres appear asymmetrical at birth. At birth, gene expression profiles appear asymmetrical between  brain hemispheres . As development continues, the gene expression profiles become similar between the hemispheres. Given a healthy adult, expression profiles stay relatively consistent from the late twenties into the late forties. From the fifties onwards, there is significant decrease in the expression of genes important for regular function. Despite this, there is an increase in the diversity of genes being expressed across the brain. This age related change in expression may be correlated with  GC content . At later stages of life, there is an increase in the induction of low GC-content pivotal genes as well as an increase in the repression of high GC-content pivotal genes. [ 53 ]  Another cause of the shift in gene diversity is the accumulation of mutations and DNA damage. Gene expression studies show that genes that accrue these age-related mutations are consistent between individuals in the aging population. Genes that are highly expressed at development decrease significantly at late stages in life, whereas genes that are highly repressed at development increase significantly at the late stages. [ 54 ]


The evolution of  Homo sapiens  since the divergence from the primate common ancestor has shown a marked expansion in the size and complexity of the brain, especially in the  cerebral cortex . [ 56 ] [ 57 ] [ 58 ] [ 59 ]  In comparison to  primates , the human  cerebral cortex  has a larger surface area but differs only slightly in thickness. Many large scale studies in understanding the differences of the human brain from other species have indicated expansion of gene families and changes in  alternative splicing  to be responsible for the corollary increase in cognitive capabilities and cooperative behaviour in humans. [ 60 ] [ 61 ]  However, we are yet to determine the exact phenotypic consequences of all these changes. One difficulty is that only primates have developed subdivisions in their cerebral cortex, making the modeling of human specific neurological problems difficult to mimic in  rodents . [ 58 ] [ 62 ] [ 63 ]


Sequence data is used to understand the evolutionary genetic changes which led to the development of the human CNS. We can then understand how the neurological phenotypes differ between species.  Comparative genomics  entails comparison of sequence data across a  phylogeny  to pinpoint the genotypic changes that occur within specific lineages, and understand how these changes might have arisen. The increase in high quality mammalian reference sequences generally makes  comparative analysis  better as it increases  statistical power . However, the increase in number of species in a  phylogeny  does risk adding unnecessary noise as the alignments of the  orthologous  sequences usually decrease in quality. Furthermore, different classes of species will have significant differences in their phenotypes. [ 64 ]


Despite this, comparative genomics has allowed us to connect the genetic changes found in a phylogeny to specific pathways. In order to determine this, lineages are tested for the functional changes that accrue over time. This is often measured as a ratio of  nonsynonymous substitutions  to  synonymous substitutions  or the  dN/dS ratio  (sometimes, further abbreviated to ω). When the dN/dS ratio is greater than 1, this indicates  positive selection . A dN/dS ratio equal to 1 is evidence of no selective pressures. A dN/dS ratio less than 1 indicates  negative selection . For example, the conserved regions of the genome will generally have a dN/dS ratio of less than 1 since any changes to those positions will likely be detrimental. [ 65 ]  Of the genes expressed in the human brain, it is estimated that 342 of them have a dN/dS ratio greater than 1 in the human lineage in comparison to other primate lineages. [ 64 ]  This indicates positive selection on the human lineage for brain phenotypes. Understanding the significance of the  positive selection  is generally the next step. For example,  ASPM ,  CDK5RAP2  and  NIN  are genes that are positively selected for on the human lineage and have been directly correlated with brain size. This finding may help elucidate why human brains are larger than other mammalian brains. [ 65 ]


It is thought that gene expression changes, being the ultimate response for any genetic changes, are a good proxy for understanding  phenotypic  differences within biological samples. Comparative studies have revealed a range of differences in the  transcriptional controls  between  primates  and  rodents . For example, the gene  CNTNAP2  is specifically enriched for in the  prefrontal cortex . The mouse homolog of  CNTNAP2  is not expressed in the mouse brain.  CNTNAP2  has been implicated in cognitive functions of language as well as  neurodevelopmental disorders  such as Autism Spectrum Disorder. This suggests that the control of expression plays a significant role in the development in unique human cognitive function. As a consequence, a number of studies have investigated the brain specific enhancers.  Transcription factors  such as  SOX5  have been found to be positively selected for on the human lineage. Gene expression studies in humans,  chimpanzees  and  rhesus macaques , have identified human specific co-expression networks, and an elevation in gene expression in the human cortex in comparison to primates. [ 66 ]


Neurogenomic disorders manifest themselves as  neurological disorders  with a complex genetic architecture and a  non-Mendelian -like pattern of inheritance. [ 18 ]  Some examples of these disorders include  Bipolar disorder  and  Schizophrenia . [ 15 ]  Several genes may be involved in the manifestation of the disorder, and mutations in such disorders are generally rare and  de novo.  Hence it becomes extremely unlikely to observe the same (potentially causative) variant in two unrelated individuals affected with the same neurogenomic disorder. [ 15 ]  Ongoing research has implicated several  de novo  exonic variations and structural variations in  Autism Spectrum Disorder  (ASD), for example. [ 15 ]  The  allelic spectrum  of the rare and common variants in neurogenomic disorders therefore necessitates a need for large cohort studies in order to effectively exclude low effect variants and identify the overarching pathways frequently mutated in the different disorders, rather than specific genes and specific  high penetrance  mutations.


Whole genome sequencing  (WGS) and  whole exome sequencing  (WES) has been used in  Genome Wide Association Studies  (GWAS) to characterize genetic variants associated with neurogenomic disorders. However, the impact of these variants cannot always be verified because of the non-Mendelian inheritance patterns observed in several of these disorders. [ 15 ]  Another prohibitive feature in network analysis is the lack of large-scale datasets for many psychiatric (neurogenomic) diseases. Since several diseases with neurogenomic underpinnings tend to have a  polygenic  basis, several nonspecific, rare, and partially penetrant  de novo  mutations in different patients can contribute to the same observed range of phenotypes, as is the case with Autism Spectrum Disorder and schizophrenia. [ 67 ]  Extensive research in  alcohol dependence  has also highlighted the need for high-quality genomic profiling of large sample sets [ 68 ] [ 69 ]  when studying  polygenic ,  spectrum disorders .


The  1000 Genomes Project  was a successful demonstration of how a concerted effort to acquire representative genomic data from the broad spectrum of humans can result in identification of actionable biological insights for different diseases. [ 70 ]  However, a large-scale initiative like this is still lacking in the field of neurogenomic disorders specifically.


One major  GWAS  study identified 13 new risk loci for  schizophrenia . [ 71 ]  Studying the impact of these candidates would ideally demonstrate a schizophrenia phenotype in animal models, which is usually difficult to observe due to its manifestation as a latent personality. This approach is able to determine the molecular impact the  candidate gene . Ideally the candidate genes would have a neurological impact, which in turn would suggest that it plays a role in the neurological disorder. For example, in the aforementioned schizophrenia GWAS study, Ripke and colleagues [ 71 ]  determined that these candidate genes were all involved in calcium signalling. Alternatively, one can study these variants in model organisms in the context of affected neurological function. It is important to note that the  high penetrance  variants of these disorders tend to be  de novo  mutations.


A further complication to studying neurogenomic disorders is the heterogeneous nature of the disorder. In many of these disorders, the mutations observed from case to case do not stay consistent. In autism, an affected individual may experience a large amount of deleterious mutations in gene X. A different affected individual may not have any significant mutations on gene X but have a large amount of mutations in gene Y. The alternative is to determine if gene X and gene Y impact the same biochemical pathway—one that influences a neurological function. A bioinformatics network analysis is one approach to this problem. Network analyses methodologies provide a generalized, systems overview of a molecular pathway.


One final complication to consider is the comorbidity of neurogenomic genes. Several disorders, especially at the more severe ends of the spectrum tend to be comorbid with each other. For example, more severe cases of  ASD  tend to be associated with  intellectual disability  (ID). This raises the question of whether or not there are true, unique ASD genes and unique ID genes or if there are just genes just associated with neurological function that can be mutated into an abnormal phenotype. One confounding factor may be the actual diagnostic category and methods of the spectrum disorders as symptoms between severe disorders may be similar. One study investigated the comorbid symptoms between groups of ID and ASD, and found no significant difference between the symptoms of ID children, ASD children with ID and ASD children without ID. Future research may help establish a more stringent genetic basis for the diagnoses of these disorders.


The main goal of network analysis in neurogenomics is to identify statistically significant nonrandom associations between genes that contain risk variants. [ 15 ]  While several algorithm implementations of this approach already exist, [ 72 ] [ 73 ]  the general steps for network analysis remain the same.


The underlying principle of this approach is that the genes that cluster together, will also jointly affect the same molecular pathway. Again, they would ideally be part of a neurological function. The candidate genes can then be used to prioritize variants for wet lab validation.


Historically, due to the behavioural stimulation manifested as a symptom in several the neurogenomic disorders, the therapies would rely mostly on  anti-psychotics  or antidepressants. These classes of medications would suppress common symptoms of the disorders, but with questionable efficacy. The biggest barrier to neruopharmacogenomic research was the cohort sizes. Given newly available large-cohort sequencing data, there has been a recent push to expand therapeutic options. The heterogenous nature of neurological diseases is the key motivation for personalized medicine approaches to their therapies. It is rare to find single high penetrance causative genes in neurological diseases. The genomic profiles understandably vary between cases, and logically, the therapies would need to vary between cases. Further complicating the issue is that many of these disorders are spectrum disorders. Their genetic etiology will vary within this spectrum. For example, severe ASD is associated with high penetrance de novo mutations. Milder forms of ASD is usually associated with a mixture of common variants.


The key issue then is the translation of these newly identified genetic variants (from  Copy Number Variant  studies, candidate gene sequencing and high throughput sequencing technologies) into an intervention for patients with neurogenomic disorders. One aspect will be if the neurological disorder are medically actionable (i.e. is there a simple metabolic pathway that a therapy can target). For example, specific cases of  ASD  have been associated with microdeletions on  TMLHE  gene. This gene codes for the enzyme of  carnitine biosynthesis . Supplements to elevate carnitine levels appeared to alleviate certain ASD symptoms but the study was confounded by many influencing factors. As mentioned earlier, using a gene network approach will help identify relevant pathways of interest. Many neuropharmacogenomic approaches have focused on targeting the downstream products of these pathways. [ 75 ] [ 76 ]


Studies in animal models for several brain diseases has shown that the  blood brain barrier  (BBB) undergoes modification at many levels; for example, the surface glycoprotein composition can influence the types of HIV-1 strains transported by the BBB. The BBB has been found to be key in the onset of  Alzheimer's  disease. [ 77 ]  It is extremely difficult, however, to be able to study this in humans due to obvious restrictions with accessing the brain and retrieving biological specimens for sequencing or morphological analysis. Mice models of the BBB and models of disease states have served well in conceptualizing the BBB as a regulatory interface between disease and good health in the brain.


The heterogenous nature of neurological diseases is the key motivation for personalized medicine approaches to their therapies. [ 75 ]  Genomic samples of individual patients could be used to identify predictive factors, or to better understand the specific prognosis of a neurogenomic disease, and use this information to guide treatment options. [ 78 ]  While there is a clear clinical utility to this approach, the adaptation of this approach is still nonexistent.


There are various issues prohibiting the application of personalized genomics to the assessment, diagnosis, and treatment of psychiatric disorders.


A  neuronal lineage marker  is an endogenous tag that is expressed in different cells along  neurogenesis  and differentiated cells such as  neurons . It allows detection and identification of cells by using different techniques. A neuronal lineage marker can be either DNA, mRNA or RNA expressed in a cell of interest. It can also be a  protein tag , as a partial protein, a protein or an  epitope  that discriminates between different cell types or different states of a common cell. An ideal marker is specific to a given cell type in normal conditions and/or during injury. Cell markers are very valuable tools for examining the function of cells in normal conditions as well as during disease. The discovery of various proteins specific to certain cells led to the production of cell-type-specific antibodies that have been used to identify cells. [ 1 ]


The techniques used for its detection can be  immunohistochemistry ,  immunocytochemistry , methods that utilize transcriptional modulators and site-specific recombinases to label specific neuronal population, [ 2 ]   in situ hybridization  or  fluorescence in situ hybridization  (FISH). [ 3 ]   A neuronal lineage marker can be a neuronal antigen that is recognized by an autoantibody for example  Hu , which is highly restricted to neuronal nuclei. By immunohistochemistry, anti-Hu stains the nuclei of neurons. [ 4 ]  To localize mRNA in brain tissue, one can use a fragment of DNA or RNA as a neuronal lineage marker, a  hybridization probe  that detects the presence of nucleotide sequences that are complementary to the sequence in the probe. This technique is known as  in situ hybridization . Its application have been carried out in all different tissues, but particularly useful in  neuroscience . Using this technique, it is possible to locate gene expression to specific cell types in specific regions and observe how changes in this distribution occur throughout the development and correlate with the behavioral manipulations. [ 5 ]


Although  immunohistochemistry  is the staple methodology for identifying neuronal cell types, since it is relatively low in cost and a wide range of immunohistochemical markers are available to help distinguish the phenotype of cells in the brain, sometimes it is time-consuming to produce a good antibody. [ 6 ]  Therefore, one of the most convenient methods for the rapid assessment of the expression of a cloned ion channel could be in situ hybridization histochemistry.


After cells are isolated from tissue or differentiated from  pluripotent  precursors, the resulting population needs to be characterized to confirm whether the target population has been obtained. Depending on the goal of a particular study, one can use  neural stem cells  markers, neural  progenitor cell  markers,  neuron  markers or  PNS  neuronal markers.


The study of the nervous system dates back to ancient Egypt but only in the ninetieth century it became more detailed. With the invention of the microscope and a technique of staining developed by  Camillo Golgi , it was possible to study individual neurons. This scientist started to impregnate nervous tissue with metal, as silver. The reaction consists in fixing particles of silver chromate to the  neurilemma , and resulted in a stark black deposit in the soma, axon and dendrites of the neuron. Thus, it was possible to identify different types of neurons, as  Golgi Cell ,  Golgi I  and  Golgi II . [ 7 ]
In 1885 there was a German medical researcher called  Franz Nissl  who developed another staining technique now known by  Nissl staining . This technique is slightly different from Golgi staining since it stains the cell body and the endoplasmic reticulum. [ 8 ]
In 1887, a Spanish scientist called  Santiago Ramon y Cajal  learned the staining technique with Golgi and started his famous work of  neuroanatomy . [ 9 ]   With this technique he made an extensive study of several areas of the brain and in different species. He also described very precisely the  purkinje cells , the chick  cerebellum  and the neuronal circuit of the rodent  hippocampus .
In 1941 Dr.  Albert Coons  used for the first time a revolutionary technique that uses the principle of  antibodies  binding specifically to  antigens  in the tissues. He created an immunoflorescent technique for labelling the antibodies. [ 10 ]   This technique continues to be widely used in neuroscience studies for identifying different structures. The most important neural markers used nowadays are the GFAP, Nestin,  NeuroD  antibodies and others. [ 11 ]  For the past years there are still creating new neural markers for  immunocytochemistry  or/and  immunohistochemistry .
In 1953  Heinrich Klüver  invented a new staining technique called,  Luxol Fast Blue stain  or LFB, and with this technique it's possible to detect  demyelination  in the central nervous system.  Myelin sheath  will be stained blue, but other structures will be  stained  as well.
The next revolutionary technique was invented in 1969 by an American scientist called  Joseph G. Gall . [ 12 ]  This technique is called  in situ Hybridization  and it is used in a large variety of studies but mainly used in developmental biology. With this technique it is possible to mark some genes expressed in determined areas of the animal. In  neurobiology , it's very useful for understanding the formation of the nervous system.


This is one of the most powerful techniques to mark cells. This method consists of hybridizing a labeled  complementary DNA  or  RNA  strand to a specific DNA or RNA in the tissue. By doing this hybridization we will be able to reveal the location of a specific  mRNA , giving us information about the physiological process of organization, regulation and function of the genes. [ 13 ]


Using this technique we can now know what are the genes and proteins that are behind a certain process, like the formation of the  neural crest , or a specific behavior; and what is the location of that same genes. We can also see how changes in the distribution of these genes can affect the development of a tissue, and correlate it with behavioral manipulations. [ 13 ]  Some examples are the use of, digoxigenin- or fluorophore-conjugated  oligo- nucleotide  probes, for the detection of localized mRNAs in dendrites, spines, axons, and  growth cones  of cultured neurons; or digoxigenin-labeled RNA probes and fluorescence tyramide amplification for the detection of less abundant mRNAs localized to dendrites in vivo. [ 14 ]  These examples use FISH (Fluorescent in situ hybridization). With this technique we can understand the physiological processes and neurological diseases.


Immunohistochemistry is a technique that uses  antibodies  with fluorescent staining tags that target a specific  antigen  present in a certain protein. This high specificity allows us to localize the peptidergic and classical transmitter compounds, their synthetic enzymes and other cell specific antigen in neuronal tissue.


An example of the application of this technique in neuroscience is the  immunolabeling  of antigens like NGF-Inducible Large External glycoprotein ( NILE-GF ),  choline acetyltransferase ,  parvalbumin , and  neurofilament protein . [ 15 ]  All of these antigens are present in specific neuronal cell types. With these we can define anatomical circuits with a high degree of resolution, and understand the role of some proteins and cells in the nervous system, as well as the location of that same proteins and cells.


Although this is a very potent technique there are some drawbacks. The procedure has a nonquantifiable nature and has the occurrence of both false positives and false negatives. [ 16 ]


Immunocytochemistry uses the same method that immunohistochemistry, but with the difference that this technique is used in isolated cells in culture, and the other is in tissues. The results are the same but with more resolution, once we are looking to one cell only.


Neural stem cells  are an example of somatic stem cell found in various tissues, both during development and in the adult. They have two fundamental characteristics: they are self-renewing and upon terminal division and differentiation, they can give rise to the full range of cells classes within the relevant tissue. Hence, a neural stem cell can give rise to another neural stem cell, or to any of the differentiated cell types found in the central and peripheral nervous systems (inhibitory and excitatory  neurons ,  astrocytes  and  oligodendrocytes ). [ 17 ]