Mitochondrial DNA is the DNA located in mitochondria, cellular organelles within eukaryotic cells that convert chemical energy from food into a form that cells can use, adenosine triphosphate. Mitochondrial DNA is only a small portion of the DNA in a eukaryotic cell. In humans, the 16,569 base pairs of mitochondrial DNA encode for only 37 genes. Human mitochondrial DNA was the first significant part of the human genome to be sequenced. In most species, including humans, mtDNA is inherited from the mother. However, in exceptional cases, human babies sometimes inherit mtDNA from both their fathers and their mothers resulting in mtDNA heteroplasmy. Since animal mtDNA evolves faster than nuclear genetic markers, it represents a mainstay of phylogenetics and evolutionary biology, it permits an examination of the relatedness of populations, so has become important in anthropology and biogeography. Nuclear and mitochondrial DNA are thought to be of separate evolutionary origin, with the mtDNA being derived from the circular genomes of the bacteria that were engulfed by the early ancestors of today's eukaryotic cells.
This theory is called the endosymbiotic theory. Each mitochondrion is estimated to contain 2–10 mtDNA copies. In the cells of extant organisms, the vast majority of the proteins present in the mitochondria are coded for by nuclear DNA, but the genes for some, if not most, of them are thought to have been of bacterial origin, having since been transferred to the eukaryotic nucleus during evolution; the reasons why mitochondria have retained some genes are debated. The existence in some species of mitochondrion-derived organelles lacking a genome suggests that complete gene loss is possible, transferring mitochondrial genes to the nucleus has several advantages; the difficulty of targeting remotely-produced hydrophobic protein products to the mitochondrion is one hypothesis for why some genes are retained in mtDNA. Recent analysis of a wide range of mtDNA genomes suggests that both these features may dictate mitochondrial gene retention. In most multicellular organisms, mtDNA is inherited from the mother.
Mechanisms for this include simple dilution, degradation of sperm mtDNA in the male genital tract and in the fertilized egg. Whatever the mechanism, this single parent pattern of mtDNA inheritance is found in most animals, most plants and in fungi. In sexual reproduction, mitochondria are inherited from the mother. Most mitochondria are present at the base of the sperm's tail, used for propelling the sperm cells. In 1999 it was reported that paternal sperm mitochondria are marked with ubiquitin to select them for destruction inside the embryo; some in vitro fertilization techniques injecting a sperm into an oocyte, may interfere with this. The fact that mitochondrial DNA is maternally inherited enables genealogical researchers to trace maternal lineage far back in time; this is accomplished on human mitochondrial DNA by sequencing the hypervariable control regions, sometimes the complete molecule of the mitochondrial DNA, as a genealogical DNA test. HVR1, for example, consists of about 440 base pairs.
These 440 base pairs are compared to the same regions of other individuals to determine maternal lineage. Most the comparison is made with the revised Cambridge Reference Sequence. Vilà et al. have published studies tracing the matrilineal descent of domestic dogs from wolves. The concept of the Mitochondrial Eve is based on the same type of analysis, attempting to discover the origin of humanity by tracking the lineage back in time. MtDNA is conserved, its slow mutation rates make it useful for studying the evolutionary relationships—phylogeny—of organisms. Biologists can determine and compare mtDNA sequences among different species and use the comparisons to build an evolutionary tree for the species examined. However, due to the slow mutation rates, it is hard to distinguish between related species to any large degree, so other methods of analysis must be used. Entities subject to uniparental inheritance and with little to no recombination may be expected to be subject to Muller's ratchet, the accumulation of deleterious mutations until functionality is lost.
Animal populations of mitochondria avoid this through a developmental process known as the mtDNA bottleneck. The bottleneck exploits random processes in the cell to increase the cell-to-cell variability in mutant load as an organism develops: a single egg cell with some proportion of mutant mtDNA thus produces an embryo in which different cells have different mutant loads. Cell-level selection may act to remove those cells with more mutant mtDNA, leading to a stabilisation or reduction in mutant load between generations; the mechanism underlying the bottleneck is debated, with a recent mathematical and experimental
A chromosome is a deoxyribonucleic acid molecule with part or all of the genetic material of an organism. Most eukaryotic chromosomes include packaging proteins which, aided by chaperone proteins, bind to and condense the DNA molecule to prevent it from becoming an unmanageable tangle. Chromosomes are visible under a light microscope only when the cell is undergoing the metaphase of cell division. Before this happens, every chromosome is copied once, the copy is joined to the original by a centromere, resulting either in an X-shaped structure if the centromere is located in the middle of the chromosome or a two-arm structure if the centromere is located near one of the ends; the original chromosome and the copy are now called sister chromatids. During metaphase the X-shape structure is called a metaphase chromosome. In this condensed form chromosomes are easiest to distinguish and study. In animal cells, chromosomes reach their highest compaction level in anaphase during chromosome segregation.
Chromosomal recombination during meiosis and subsequent sexual reproduction play a significant role in genetic diversity. If these structures are manipulated incorrectly, through processes known as chromosomal instability and translocation, the cell may undergo mitotic catastrophe; this will make the cell initiate apoptosis leading to its own death, but sometimes mutations in the cell hamper this process and thus cause progression of cancer. Some use the term chromosome in a wider sense, to refer to the individualized portions of chromatin in cells, either visible or not under light microscopy. Others use the concept in a narrower sense, to refer to the individualized portions of chromatin during cell division, visible under light microscopy due to high condensation; the word chromosome comes from the Greek χρῶμα and σῶμα, describing their strong staining by particular dyes. The term was coined by von Waldeyer-Hartz, referring to the term chromatin, introduced by Walther Flemming; some of the early karyological terms have become outdated.
For example and Chromosom, both ascribe color to a non-colored state. The German scientists Schleiden, Virchow and Bütschli were among the first scientists who recognized the structures now familiar as chromosomes. In a series of experiments beginning in the mid-1880s, Theodor Boveri gave the definitive demonstration that chromosomes are the vectors of heredity, it is the second of these principles, so original. Wilhelm Roux suggested. Boveri was able to confirm this hypothesis. Aided by the rediscovery at the start of the 1900s of Gregor Mendel's earlier work, Boveri was able to point out the connection between the rules of inheritance and the behaviour of the chromosomes. Boveri influenced two generations of American cytologists: Edmund Beecher Wilson, Nettie Stevens, Walter Sutton and Theophilus Painter were all influenced by Boveri. In his famous textbook The Cell in Development and Heredity, Wilson linked together the independent work of Boveri and Sutton by naming the chromosome theory of inheritance the Boveri–Sutton chromosome theory.
Ernst Mayr remarks that the theory was hotly contested by some famous geneticists: William Bateson, Wilhelm Johannsen, Richard Goldschmidt and T. H. Morgan, all of a rather dogmatic turn of mind. Complete proof came from chromosome maps in Morgan's own lab; the number of human chromosomes was published in 1923 by Theophilus Painter. By inspection through the microscope, he counted 24 pairs, his error was copied by others and it was not until 1956 that the true number, 46, was determined by Indonesia-born cytogeneticist Joe Hin Tjio. The prokaryotes – bacteria and archaea – have a single circular chromosome, but many variations exist; the chromosomes of most bacteria, which some authors prefer to call genophores, can range in size from only 130,000 base pairs in the endosymbiotic bacteria Candidatus Hodgkinia cicadicola and Candidatus Tremblaya princeps, to more than 14,000,000 base pairs in the soil-dwelling bacterium Sorangium cellulosum. Spirochaetes of the genus Borrelia are a notable exception to this arrangement, with bacteria such as Borrelia burgdorferi, the cause of Lyme disease, containing a single linear chromosome.
Prokaryotic chromosomes have less sequence-based structure than eukaryotes. Bacteria have a one-point from which replication starts, whereas some archaea contain multiple replication origins; the genes in prokaryotes are organized in operons, do not contain introns, unlike eukaryotes. Prokaryotes do not possess nuclei. Instead, their DNA is organized into a structure called the nucleoid; the nucleoid occupies a defined region of the bacterial cell. This structure is, dynamic and is maintained and remodeled by the actions of a range of histone-like proteins, which associate with the bacterial chromosome. In archaea, the DNA in chromosomes is more organized, with the DNA packaged within structures similar to eukaryotic nucleosomes. Certain bacteria contain plasmids or other extrachromosomal DNA; these are circular structures in the cytoplasm that contain cellular DNA and play a role in horizontal gene transfer. In prokaryotes and viruses, the DNA is densely packed and organized.
Markov chain Monte Carlo
In statistics, Markov chain Monte Carlo methods comprise a class of algorithms for sampling from a probability distribution. By constructing a Markov chain that has the desired distribution as its equilibrium distribution, one can obtain a sample of the desired distribution by observing the chain after a number of steps; the more steps there are, the more the distribution of the sample matches the actual desired distribution. Markov chain Monte Carlo methods are used for calculating numerical approximations of multi-dimensional integrals, for example in Bayesian statistics, computational physics, computational biology, computational linguistics. In Bayesian statistics, the recent development of Markov chain Monte Carlo methods has been a key step in making it possible to compute large hierarchical models that require integrations over hundreds or thousands of unknown parameters. In rare event sampling, they are used for generating samples that populate the rare failure region. Markov chain Monte Carlo methods create samples from a multi-dimensional continuous random variable, with probability density proportional to a known function.
These samples can be used to evaluate an integral over that variable, as its expected value or variance. An ensemble of chains is developed, starting from a set of points arbitrarily chosen and sufficiently distant from each other; these chains are stochastic processes of "walkers" which move around randomly according to an algorithm which looks for places with a reasonably high contribution to the integral to move into next, assigning them higher probabilities. Random walk Monte Carlo methods are a kind of Monte Carlo method. However, whereas the random samples of the integrand used in a conventional Monte Carlo integration are statistically independent, those used in Markov chain Monte Carlo methods are autocorrelated; these algorithms create Markov chains such that they have an equilibrium distribution, proportional to the function given. While MCMC methods were created to address multi-dimensional problems better than simple Monte Carlo algorithms, when the number of dimensions rises they too tend to suffer the curse of dimensionality: the regions of higher probability tend to stretch and get lost in a increasing volume of space that gives little contribution to the desired integral.
One way to address this problem could be shortening the steps of the walker, so that it doesn't continuously try to exit the highest probability region, though this way the process would be autocorrelated and quite ineffective. More sophisticated methods use various ways of reducing the autocorrelation, while managing to keep the process in the regions that give a higher contribution to the integral; these algorithms rely on a more complicated theory, may be harder to implement, but they exhibit faster convergence. Examples of random walk Monte Carlo methods include the following: Metropolis–Hastings algorithm: This method generates a Markov chain using a proposal density for new steps and a method for rejecting some of the proposed moves, it is a general framework which includes as special cases the first and simpler MCMC and many more recent alternatives listed below. Gibbs sampling: This method requires all the conditional distributions of the target distribution to be sampled exactly; when drawing from the full-conditional distributions is not straightforward other samplers-within-Gibbs are used.
Gibbs sampling is popular because it does not require any'tuning'. Metropolis-adjusted Langevin algorithm and other methods that rely on the gradient of the log target density to propose steps that are more to be in the direction of higher probability density. Slice sampling: This method depends on the principle that one can sample from a distribution by sampling uniformly from the region under the plot of its density function, it alternates uniform sampling in the vertical direction with uniform sampling from the horizontal'slice' defined by the current vertical position. Multiple-try Metropolis: This method is a variation of the Metropolis–Hastings algorithm that allows multiple trials at each point. By making it possible to take larger steps at each iteration, it helps address the curse of dimensionality. Reversible-jump: This method is a variant of the Metropolis–Hastings algorithm that allows proposals that change the dimensionality of the space. Markov chain Monte Carlo methods that change dimensionality have long been used in statistical physics applications, where for some problems a distribution, a grand canonical ensemble is used.
But the reversible-jump variant is useful when doing Markov chain Monte Carlo or Gibbs sampling over nonparametric Bayesian models such as those involving the Dirichlet process or Chinese restaurant process, where the number of mixing components/clusters/etc. is automatically inferred from the data. Hamiltonian Monte Carlo: Tries to avoid random walk behaviour by introducing an auxiliary momentum vector and implementing Hamiltonian dynamics, so the potential energy function is the target density; the momentum samples are discarded after sampling. The end result of Hybrid Monte Carlo is. Unlike most of the current Markov chain Monte Carlo methods that ignore the previous trials, using a new algorithm the Markov chain Monte Carlo algorithm is able to use the previous steps and generate the next candidate
In biology, an organism is any individual entity that exhibits the properties of life. It is a synonym for "life form". Organisms are classified by taxonomy into specified groups such as the multicellular animals and fungi. All types of organisms are capable of reproduction and development, some degree of response to stimuli. Humans are multicellular animals composed of many trillions of cells which differentiate during development into specialized tissues and organs. An organism may be either a eukaryote. Prokaryotes are represented by two separate domains -- archaea. Eukaryotic organisms are characterized by the presence of a membrane-bound cell nucleus and contain additional membrane-bound compartments called organelles. Fungi and plants are examples of kingdoms of organisms within the eukaryotes. Estimates on the number of Earth's current species range from 10 million to 14 million, of which only about 1.2 million have been documented. More than 99% of all species, amounting to over five billion species, that lived are estimated to be extinct.
In 2016, a set of 355 genes from the last universal common ancestor of all organisms was identified. The term "organism" first appeared in the English language in 1703 and took on its current definition by 1834, it is directly related to the term "organization". There is a long tradition of defining organisms as self-organizing beings, going back at least to Immanuel Kant's 1790 Critique of Judgment. An organism may be defined as an assembly of molecules functioning as a more or less stable whole that exhibits the properties of life. Dictionary definitions can be broad, using phrases such as "any living structure, such as a plant, fungus or bacterium, capable of growth and reproduction". Many definitions exclude viruses and possible man-made non-organic life forms, as viruses are dependent on the biochemical machinery of a host cell for reproduction. A superorganism is an organism consisting of many individuals working together as a single functional or social unit. There has been controversy about the best way to define the organism and indeed about whether or not such a definition is necessary.
Several contributions are responses to the suggestion that the category of "organism" may well not be adequate in biology. Viruses are not considered to be organisms because they are incapable of autonomous reproduction, growth or metabolism; this controversy is problematic because some cellular organisms are incapable of independent survival and live as obligatory intracellular parasites. Although viruses have a few enzymes and molecules characteristic of living organisms, they have no metabolism of their own; this rules out autonomous reproduction: they can only be passively replicated by the machinery of the host cell. In this sense, they are similar to inanimate matter. While viruses sustain no independent metabolism and thus are not classified as organisms, they do have their own genes, they do evolve by mechanisms similar to the evolutionary mechanisms of organisms; the most common argument in support of viruses as living organisms is their ability to undergo evolution and replicate through self-assembly.
Some scientists argue. In fact, viruses are evolved by their host cells, meaning that there was co-evolution of viruses and host cells. If host cells did not exist, viral evolution would be impossible; this is not true for cells. If viruses did not exist, the direction of cellular evolution could be different, but cells would be able to evolve; as for the reproduction, viruses rely on hosts' machinery to replicate. The discovery of viral metagenomes with genes coding for energy metabolism and protein synthesis fueled the debate about whether viruses belong in the tree of life; the presence of these genes suggested. However, it was found that the genes coding for energy and protein metabolism have a cellular origin. Most these genes were acquired through horizontal gene transfer from viral hosts. Organisms are complex chemical systems, organized in ways that promote reproduction and some measure of sustainability or survival; the same laws that govern non-living chemistry govern the chemical processes of life.
It is the phenomena of entire organisms that determine their fitness to an environment and therefore the survivability of their DNA-based genes. Organisms owe their origin and many other internal functions to chemical phenomena the chemistry of large organic molecules. Organisms are complex systems of chemical compounds that, through interaction and environment, play a wide variety of roles. Organisms are semi-closed chemical systems. Although they are individual units of life, they are not closed to the environment around them. To operate they take in and release energy. Autotrophs produce usable energy using light from the sun or inorganic compounds while heterotrophs take in organic compounds from the environment; the primary chemical element in these compounds is carbon. The chemical properties of this element such as its grea
Microfluidic whole genome haplotyping
Microfluidic whole genome haplotyping is a technique for the physical separation of individual chromosomes from a metaphase cell followed by direct resolution of the haplotype for each allele. Whole genome haplotyping is the process of resolving personal haplotypes on a whole genome basis. Current methods of next generation sequencing are capable of identifying heterozygous loci, but they are not well suited to identify which polymorphisms exist on the same or allelic strand of DNA. Haplotype information contributes to the understanding of the potential functional effects of variants in cis or in trans. Haplotypes are more resolved by inference through comparison with parental genotypes, or from population samples using statistical computational methods to determine linkage disequilibrium between markers. Direct haplotyping is possible through isolation of chromosomes or chromosome segments. Most molecular biology techniques for haplotyping can determine haplotypes of only a limited region of the genome.
Whole genome direct haplotyping involves the resolution of haplotype at the whole genome level through the isolation of individual chromosomes. A haplotype (haplo: from Ancient Greek ἁπλόος is a contiguous section of linked segments of DNA within the larger genome that tend to be inherited together as a unit on a single chromosome. Haplotypes have no defined size and can refer to anything from a few linked loci up to an entire chromosome; the term is used to describe groups of single-nucleotide polymorphisms that are statistically associated. Most of the knowledge of SNP association comes from the effort of the International HapMap Project, which has proved itself a powerful resource in the development of a publicly accessible database of human genetic variation. Phasing is the process of identifying the individual complement of homologous chromosomes. Methods for phasing include pedigree analysis, allele-specific PCR, linkage emulsion PCR haplotype analysis, polony PCR, sperm typing, bacterial artificial chromosome cloning, construction of somatic cell hybrids, atomic force microscopy, among others.
Haplotype phasing can be achieved through computational inference methods. Microfluidics refers to the use of micro-sized channels on a micro-electro-mechanical system. Microfluidic channels have a diameter of 10-100μm, making it possible to manipulate and analyze minute volumes; this technology combines engineering, chemistry and optics. Over the past decades it has revolutionized micro and nanoscale biology and proteomics. Microfluidic devices can combine several analytical steps into one device; this technology has been coined by some as the "lab on a chip" technology. Most current molecular biology methods use some form of MEMS, including microarray technology and next generation sequencing instruments. Direct deterministic phasing of individual chromosomes can be achieved by isolating single chromosomes for genetic analysis through the use of a microfluidic device. A single metaphase cell is isolated from solution; the chromosomes are released from the nucleus, the cytoplasm is digested enzymatically.
Next, the chromosome suspension is directed towards multiple partitioning channels. The chromosomes are physically directed into the partitioning channels using a series of valves. In the first description of this technique, Fan et al. designed a custom-made program to control this process. Once separated, the chromosomes are prepared for amplification by sequential addition and washout of trypsin, denaturation buffer and neutralization solution; the DNA is ready for further processing. Because of the small amount of DNA, amplification needs to be performed using kits specialized for small initial DNA quantities; the amplified DNA is flushed out of the microfluidic device and solubilized by the addition of a buffer. The amplified DNA can now be analyzed by various methods. Once the chromosomes have been isolated and amplified any molecular haplotyping can be applied as long as the chromosomes remain distinct; this could be accomplished by keeping them physically separated, or identifying each sample by genotyping.
Once each chromosome has been identified each pair of homologs can be assorted into one of two haploid genomes. Microfluidic direct deterministic phasing allows all the chromosomes to be isolated in the same experiment; this unique feature suggests possible applications within clinical and personal genomics realms. Some of the possible clinical applications for this technique include phasing of multiple mutations when parental samples are unavailable, preimplantation genetic diagnosis, prenatal diagnosis and in the characterization of cancer cells. Whole genome haplotyping through microfluidics will increase the rate of discovery within the HapMap project, provides an opportunity for corroboration and error detection within the existing database, it will further inform genetic association studies. As methods for amplification of small amounts of DNA improve, single chromosome sequencing is possible using microfluidics to separate each individual chromosome. A cost-effective approach may be to barcode each individual chromosome and perform parallel resequencing of the entire individual genome.
The amplification of each chromosome separately provides a mechanism to fill in some of the gaps that remain in the human reference genome. Single chromosome sequencing will allow for unmapped sequences to be associated with a single chromosome. Additionally, single chromosome sequencing will be more accurate in the identification of copy number variants and repetitive sequences; as of January 2011, only one publication has described use of this technique. The scientific common
Genetic recombination is the exchange of genetic material between different organisms which leads to production of offspring with combinations of traits that differ from those found in either parent. In eukaryotes, genetic recombination during meiosis can lead to a novel set of genetic information that can be passed on from the parents to the offspring. Most recombination is occurring. During meiosis in eukaryotes, genetic recombination involves the pairing of homologous chromosomes; this may be followed by information transfer between the chromosomes. The information transfer may occur without physical exchange. Recombination may occur during mitosis in eukaryotes where it ordinarily involves the two sister chromosomes formed after chromosomal replication. In this case, new combinations of alleles are not produced since the sister chromosomes are identical. In meiosis and mitosis, recombination occurs between similar molecules of DNA. In meiosis, non-sister homologous chromosomes pair with each other so that recombination characteristically occurs between non-sister homologues.
In both meiotic and mitotic cells, recombination between homologous chromosomes is a common mechanism used in DNA repair. Gene conversion - the process during which homologous sequences are made identical falls under genetic recombination. Genetic recombination and recombinational DNA repair occurs in bacteria and archaea, which use asexual reproduction. Recombination can be artificially induced in laboratory settings, producing recombinant DNA for purposes including vaccine development. VJ recombination in organisms with an adaptive immune system is a type of site-specific genetic recombination that helps immune cells diversify to recognize and adapt to new pathogens. During meiosis, synapsis ordinarily precedes genetic recombination. Genetic recombination is catalyzed by many different enzymes. Recombinases are key enzymes. RecA, the chief recombinase found in Escherichia coli, is responsible for the repair of DNA double strand breaks. In yeast and other eukaryotic organisms there are two recombinases required for repairing DSBs.
The RAD51 protein is required for mitotic and meiotic recombination, whereas the DNA repair protein, DMC1, is specific to meiotic recombination. In the archaea, the ortholog of the bacterial RecA protein is RadA. Bacterial recombination In Bacteria there are: regular bacterial recombination, as well as noneffective transfer of genetic material, expressed as unsuccessful transfer or abortive transfer, any bacterial DNA transfer of the donor cell recipients who have set the incoming DNA as part of the genetic material of the recipient. Abortive transfer was registered in conjugation. In all cases, the transmitted fragment is diluted by the culture growth. In eukaryotes, recombination during meiosis is facilitated by chromosomal crossover; the crossover process leads to offspring having different combinations of genes from those of their parents, can produce new chimeric alleles. The shuffling of genes brought about by genetic recombination produces increased genetic variation, it allows sexually reproducing organisms to avoid Muller's ratchet, in which the genomes of an asexual population accumulate genetic deletions in an irreversible manner.
Chromosomal crossover involves recombination between the paired chromosomes inherited from each of one's parents occurring during meiosis. During prophase I the four available chromatids are in tight formation with one another. While in this formation, homologous sites on two chromatids can pair with one another, may exchange genetic information; because recombination can occur with small probability at any location along chromosome, the frequency of recombination between two locations depends on the distance separating them. Therefore, for genes sufficiently distant on the same chromosome, the amount of crossover is high enough to destroy the correlation between alleles. Tracking the movement of genes resulting from crossovers has proven quite useful to geneticists; because two genes that are close together are less to become separated than genes that are farther apart, geneticists can deduce how far apart two genes are on a chromosome if they know the frequency of the crossovers. Geneticists can use this method to infer the presence of certain genes.
Genes that stay together during recombination are said to be linked. One gene in a linked pair can sometimes be used as a marker to deduce the presence of another gene; this is used in order to detect the presence of a disease-causing gene. The recombination frequency between two loci observed, it is the frequency of crossing over between two linked gene loci, depends on the mutual distance of the genetic loci observed. For any fixed set of genetic and environmental conditions, recombination in a particular region of a linkage structure tends to be constant, the same is true for the crossing-over value, used in the production of genetic maps. In gene conversion, a section of genetic material is copied from one chromosome to another, without the donating chromosome being changed. Gene conversion occurs at high frequency at the actual site of the recombination event during meiosis, it is a process by which a DNA sequence
An autosome is a chromosome, not an allosome. The members of an autosome pair in a diploid cell have the same morphology, unlike those in allosome pairs which may have different structures; the DNA in autosomes is collectively known as atDNA or auDNA. For example, humans have a diploid genome that contains 22 pairs of autosomes and one allosome pair; the autosome pairs are labeled with numbers in order of their sizes in base pairs, while allosomes are labelled with their letters. By contrast, the allosome pair consists of two X chromosomes in females or one X and one Y chromosome in males. Unusual combinations of XYY, XXY, XXX, XXXX, XXXXX or XXYY, among other allosome combinations, are known to occur and cause developmental abnormalities. Autosomes still contain sexual determination genes though they are not sex chromosomes. For example, the SRY gene on the Y chromosome encodes the transcription factor TDF and is vital for male sex determination during development. TDF functions by activating the SOX9 gene on chromosome 17, so mutations of the SOX9 gene can cause humans with an ordinary Y chromosome to develop as females.
All human autosomes have been identified and mapped by extracting the chromosomes from a cell arrested in metaphase or prometaphase and staining them with a type of dye. These chromosomes are viewed as karyograms for easy comparison. Clinical geneticists can compare the karyogram of an individual to a reference karyogram to discover the cytogenetic basis of certain phenotypes. For example, the karyogram of someone with Patau Syndrome would show that they possess three copies of chromosome 13. Karyograms and staining techniques can only detect large-scale disruptions to chromosomes—chromosomal aberrations smaller than a few million base pairs cannot be seen on a karyogram. Autosomal genetic disorders can arise due to a number of causes, some of the most common being nondisjunction in parental germ cells or Mendelian inheritance of deleterious alleles from parents. Autosomal genetic disorders which exhibit Mendelian inheritance can be inherited either in an autosomal dominant or recessive fashion.
These disorders are passed on by either sex with equal frequency. Autosomal dominant disorders are present in both parent and child, as the child needs to inherit only one copy of the deleterious allele to manifest the disease. Autosomal recessive diseases, require two copies of the deleterious allele for the disease to manifest; because it is possible to possess one copy of a deleterious allele without presenting a disease phenotype, two phenotypically normal parents can have a child with the disease if both parents are carriers for the condition. Autosomal aneuploidy can result in disease conditions. Aneuploidy of autosomes is not well tolerated and results in miscarriage of the developing fetus. Fetuses with aneuploidy of gene-rich chromosomes—such as chromosome 1—never survive to term, fetuses with aneuploidy of gene-poor chromosomes—such as chromosome 21— are still miscarried over 23% of the time. Possessing a single copy of an autosome is nearly always incompatible with life, though rarely some monosomies can survive past birth.
Having three copies of an autosome is far more compatible with life, however. A common example is Down syndrome, caused by possessing three copies of chromosome 21 instead of the usual two. Partial aneuploidy can occur as a result of unbalanced translocations during meiosis. Deletions of part of a chromosome cause partial monosomies, while duplications can cause partial trisomies. If the duplication or deletion is large enough, it can be discovered by analyzing a karyogram of the individual. Autosomal translocations can be responsible for a number of diseases, ranging from cancer to schizophrenia. Unlike single gene disorders, diseases caused by aneuploidy are the result of improper gene dosage, not nonfunctional gene product. Aneuploidy Autosomal dominant Autosomal recessive Homologous chromosome Pseudoautosomal region XY sex-determination system Genetic disorder