Regulation of Gene Expression and Brain Function

Regulation of global gene expression in brain by TMP21
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Mouse Emx1 can rescue brain defects in Drosophila empty spiracles ems mutants, but Acropora [Anthozoa, Cnidaria radially symmetric organisms including corals, anemones and jelly fish ] Emx is not able to replace ems in fly brain development Hirth, A phylogenetic tree is based on evolutionary relationships and can be reconstructed using cladistics.

The cladistic concept is relative; it scores characters for their presence and absence and, if present, for their state in each of the taxa of interest.

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Current cladistics scores morphological as well as molecular characters i. For example sister groups like arthropods and onychophorans share a common panarthropod ancestor, and together they are a sister group to cycloneuralians including nematodes , which together belong to the ecdysozoans, which are a sister group to lophotrochozoans. Monophyly of bilaterally symmetric animals and subsequent interpretations about the origin and evolution of the brain and CNS hinge on the identification of genuine sister and out groups and, thus, on how deep a phylogenetic tree is rooted.

Current cladistics is work in progress which is exemplified by the allocation of Cnidaria but also Acoela as either a sister or out group to bilaterians. The ambiguity is caused by mounting evidence suggesting that cnidarians possess genetic toolkits similar to those active in bilaterian axis and cell type specification, including neurogenesis Gaillot, It follows that the positioning of Cnidaria has an impact on the positioning of Urbilateria and the origin of a brain and CNS.

Cnidarians possess nerve nets and nerve rings but, so far, no evidence of a centralized nervous system has been found [Gaillot, ].

As mentioned, the presence of genetic toolkits does not necessarily reflect a common origin of characters. The existence of equivalent functions of character identity genes, however, allows inferences as to whether genes diverged before the origin of a character or not Wagner, The latter notion is supported by the functional equivalence of another character identity gene.

The cnidarian Hydra achaete scute homolog has proneural activity in Drosophila, can heterodimerize with daughterless , and is able to form ectopic sensory organs in the peripheral nervous system of Drosophila; in addition, it is also able to partially rescue adult external sensory organ formation in viable achaete scute complex mutations. Unfortunately, whether Hydra achaete scute is able to rescue defects in Drosophila achaete scute mutant brain and CNS development was not tested Hirth, It depends on the placement of cnidarians in- or outside the clade Bilateria, whether it is reasonable to propose that Urbilateria already possessed a tripartite brain and probably also a complex CNS, or whether Urbilateria was likely to be 'brainless'.

This concept, though, is challenged by the fact that several proto- and deuterostomians do not possess a brain and complex CNS.

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The conundrum is most obvious when the complex CNS of arthropods is compared to that of cycloneuralians, which are supposed to be sister groups. Comparative data for cycloneuralians are scant, except for Caenorhabditis elegans. The nematode does not possess a complex brain and CNS, yet monophyly of the brain is corroborated by functional equivalence of a character identity gene: the ems homolog ceh-2 of C. These data suggest that C. For the quality and consistency of this conjecture, it is necessary to consider 1 metazoan divergence times, 2 the likelihood of secondary loss, as illustrated by reconstructed cases, and 3 the proposal of an experimental paradigm that can test ancestral character identity genes of brainless bilaterians for their potential to control brain development in Drosophila or mice.

Monophyly implies that ancestral priapulids shared with arthropods the character of a tripartite brain and possibly a segmented CNS. Fossil evidence supports ancestral segmentation in priapulids e. Markuelia even though extant priapulids are nonsegmented and their CNS is 'only' composed of a nerve ring and a single ventral cord running the length of the body. Scaled against molecular clock dates, monophyly of the tripartite brain suggests that the derived character of the priapulid brain and CNS would have had several hundred million years' time for its secondary modification.

Comparative developmental genetics and phylogenomics reveal that morphological evolution is most likely driven by gene duplication and gene loss, together with changes in differential gene regulation, including mutations in cis -regulatory elements of pleiotropic developmental regulatory genes. These genetic modifications can account not only for the acquisition of novel morphological characters but also for the modification and eventual loss of a morphological character. The latter is illustrated by limbless tetrapods, such as whales, snakes, and flightless birds.

Limbless tetrapods are descended from limbed ancestors, and limblessness has been shown to be polygenic, involving pleiotropic regulatory genes that act as modifiers to suppress limb development. In snakes, for example, differential regulation of HoxC genes accounts for the failure to activate the signaling pathways required for proper limb development, eventually leading to limbless snakes. Independent reduction and limb loss in tetrapods occurred repeatedly over several millions of years for lizards, and over or up to 20 million years for whales Hirth, The secondary loss of morphological characters is also exemplified in fish.

In different natural populations of threespined stickleback fish, the secondary loss of the pelvis occurred through regulatory mutations deleting a tissue-specific enhancer of the Pituitary homeobox transcription factor 1 Pitx1 gene. The selective pressures causing secondary loss can be manifold, including energy limitation and environmental constraints which are most obvious for nervous system structures that are characterized by high energy consumption.

For example, populations of cave fish have undergone convergent eye loss at least 3 times within the last 1 million years, whereas populations that continuously lived on the surface retained their eyes. These examples illustrate that the secondary loss of a morphological character can occur repeatedly during the course of evolution within a time frame of million years. The secondary, independent loss of the brain and CNS multiple times during the course of protostomian and deuterostomian evolution is a conjecture that can be tested experimentally.

And that would be without considering glia cells, which make up about half of the cells in the brain and are currently suspected to play a more important role than previously thought. Massive parallel computing has to be an essential part in mapping the brain, and the problem has to be simplified to be ambitious but accomplishable. The first step was to look at a much smaller animal: the mouse. The mouse brain consequently exhibits far less complexity in each of its regions. It also has fewer genes, about 20, Scientists only finished mapping the genetic expression of the mouse brain in Mapping the human brain, however, is orders of magnitude more difficult.

The question by necessity became how to collect as efficiently as possible partial data on the human brain. On the one hand, scientists can look at different brain regions, spliced up in a fairly gross no pun intended way, and identify, for each region, the genes that are expressed. The corresponding method for collecting this data is in situ hybridization. Allen scientists used in situ hybridization to get a rather complete story for the mouse; this was a stunning effort because it involved 20, in situ hybridizations rather than just a few normally, one in situ hybridization could take days.

Human brains are just too big to collect such rich data; thus was born the idea of using microarrays to complement what in situ hybridization could do.


These two techniques form the basis for the Allen strategy toward human brain gene expression — both obtain partial results about how the human brain expresses itself genetically, but together they provide a shimmer of insight into the human brain. This genetic code is fed to a targeted cell or tissue; the expression or lack of expression of the corresponding gene is gathered by various microscopic techniques. One looks for the expression of an individual, specific gene in many regions.

Until recently, ISH was performed in single cells or in a collection of nearby cells in small regions of the generally, rodent brain with at most a few genetic markers. It continues to be used when a specific gene is suspected of playing a role in a specific cell or cellular mechanism, or when a specific gene is suspected of a common mutation.

For example, ISH is used to identify some chromosomal abnormalities in fetuses.

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In The Allen Institute set about industrializing the process. Scientists close to the process realized that with an investment in robotic processes to collect data, and complex computer programs to analyze it, they could do massive parallel computation and create a map of the mouse brain.

It took about two years to set the process up and another year for the data to finally come in. The data were recorded in a searchable database used as a starting point for hundreds of neuroscientists interested in rodent genetics. One key aspect of the mouse program is that hundreds of mice have been used, rather than just a few. This means that the data are largely generalizable and the variation of gene expression among these laboratory mouse populations has been documented.

A paper documenting the mouse findings was published in Nature in While mapping the mouse brain was a huge project, it was only a small stepping stone for mapping human gene expression. Certainly scientists were interested in using ISH to dissect the story for human brains, but a new technique also came into play: microarrays. Imagine a mini-bead box, with separators for each bead type, of size x Together these genetic code wells form a microchip.

Each microchip is then doused with a drop of homogenized brain from each of the separate parts of the brain under consideration. Each well is a microcosm of activity — provided the piece of brain expresses the gene associated with the relevant well. When the genetic code is linked to a fluorescent probe and light is shined on it, the microarray will light up in the wells contained in this location in the brain.

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Gene expression is one of the main molecular processes regulating the differentiation, development, and functioning of cells and tissues. The wonder is that for most people the brain functions effectively and unceasingly for are found in all living organisms and are critical for regulating gene expression. Recent cutting-edge lines of inquiry into gene regulation include work on.

In other words, the genetic expression of the brain region will be recorded in a microchip of 62, bits. One microarray is used per brain region, so the entire genetic expression can be mapped out for each region. It was such a labor-intensive task that they could only do it for 2 male adult humans who had donated their brains to science. Although almost more than regions seems like many, it is actually a coarse way to divide the human brain — to get this coarse information on the whole human brain, we would need to slice up approximately 1,, pieces.

Light can be utilized to control gene function

The microarrays also record other data, such as how much of a gene is expressed; the more information they record, of course, the more analysis is required. Unfortunately the microarray data does not directly translate into genetic data; a collection of approximately 62, genetic probes is used to obtain data on the roughly 30, genes.

Many observations result from a close look at these two brains. The authors plotted gene expression profiles of genes associated with dopamine signaling across brain structures in both brains. They found remarkable similarity between the two brains. They found no significant differences in genetic expression between the left and the right hemisphere. They found that the anatomical structure of the brain which cells are close to which others dictated to some extent the genetic structure — close by cells had more similar genetic expression.

On the other hand, they also looked at some genes identified in the human excitatory postsynaptic density PSD , a region of a neuron receptive to a connection. The authors surmise that these regional differences in synaptic gene expression may well underlie different functions of different regions.

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While the microarray technique has the advantage of revealing all of the gene expression for a small number of homogenized pieces of brain, a parallel effort using in situ hybridization was able to characterize the expression of about genes important for neural functions at a cellular resolution in specific regions of an adult human brain.

University of Buffalo physicist Hao Zeng recently led a team that looked at two different regions of the cortex : the visual cortex and the midtemporal cortex. The visual cortex has a mouse-analogue, making it a good candidate for comparison with other species, while the midtemporal cortex is functionally distinct from the visual cortex — the midtemporal cortex is responsible for language comprehension as well as memory. The comparison between these two regions may offer some insight into the relationship between gene expression and neural function.

The results painted a picture of our genetic diversity, both among our individual brain cells and between species. Different genes had different gene expression patterns, suggesting that genes play diverse roles in our neurons.

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While the considered genes were certainly not randomly chosen, it is notable that cross-cortical differences are not so much greater than cross-species differences. This conservation perhaps belies the importance of the chosen genes. The atlas for the mouse brain has been cited over times according to the Web of Science citation tracking system — and no doubt the results for humans will achieve a similar level of success in influencing scientific research. The point is that any genetic question may well begin by asking where a gene is expressed. An online database is an way for the scientific community to spur scientific growth through open data sharing.

What does it mean for you and me?