Gene identification is an important step in understanding the molecular basis of any heritable disorder. Identification of the gene(s) associated with a disorder opens the door for understanding the molecular components and biochemical pathways involved in the disorder, enables experimentation into improved diagnostic testing methodologies, provides targets for drug development, and suggests new avenues for therapeutic research, including gene therapy, stem cell therapy, and enzyme replacement therapy. The laboratory mouse and the fruit fly are vital tools for the study of human disorders and the preclinical evaluation of novel therapeutic approaches.

Many genes have been discovered by an approach called linkage analysis. Linkage analysis relies on Mendelian inheritance of chromosomes (and genes). In linkage analysis, polymorphic genetic markers (sites of DNA sequence variations) spread throughout the genome are used to track the transmission of various genomic regions through a family. With linkage analysis, all members of a family are genotyped for the polymorphic markers. The genotype of each family member at each marker is then compared to the genotypes of other family members to determine which markers are present in the family members affected by the disorder. Since linkage analysis does not detect mutations in genes directly, but rather traces a potential disease allele through a family because of a tight association (genetic linkage) between the potential disease gene and the marker, further investigation is required once a genomic region of interest is identified. The goal of the investigation is to identify the gene and mutations associated with the disorder. Since linkage analysis is not a direct mutation detection method, its level of sensitivity relies on how many different forms of the markers there are, the density of the markers throughout the genome, and the genetic distance between the marker and the disease gene. Highly polymorphic markers, and lots of them, improve the success rate of linkage analysis.

Linkage analyses must be performed with data sets based on large, multigenerational families. This is because one needs many individuals, and typically more than one affected individual, within a family to identify the genomic regions associated with a disorder with statistical significance. However, large families segregating genetic disorders are not always easy to find, especially in highly mobile societies like the United States. In some cases, a several small families can be used instead, but this approach requires that the disease is caused by the same gene in all the families. For example, if the disorder is caused by mutations in the same gene in every individual affected by the disorder, then the results of linkage analysis of many small families can be added together because everyone affected by the disorder should share the same disease gene. One example of such a disorder is cystic fibrosis (CF), in which all individuals affected by the disorder have mutations in the gene encoding the cystic fibrosis transmembrane conductance regulator (CFTR). On the other hand, if a disorder is caused by mutations in more than one gene, linkage analysis will be more successful if large, multigenerational families are used because two different families might have the disease because of mutations in different genes. In these cases, the linkage data would appear contradictory and would not be additive. One example of a highly heterogeneous genetic disorder is nonsyndromic hearing loss. More than 100 genes have been mapped so far for hereditary deafness.

Genetic heterogeneity has complicated the search for the genetic factors associated with a number of common complex disorders such as schizophrenia and autism. In these disorders, multiple genetic factors are likely to be involved and each may have only a small effect on susceptibility to develop the disorder. As such, the disorder in any two families may be associated with different sets of genes. Sorting out the genetic factors involved is quite complicated and requires extensive additional investigations.

As a result of the Human Genome Project, researchers now have a collection of polymorphic genetic markers that provide excellent coverage of the genome. These markers are powerful tools for mapping disease genes. Linkage analysis strategies are precise, accurate and effective, but labor intensive. However, while they often require data from large families, they do not require an investigator to know anything about the underlying biochemical mechanisms involved in the disorder.

In the simplified diagram on this slide, a polymorphism associated with an autosomal recessive disorder is indicated by the red star. Only the affected individual has inherited two copies of the disease-associated polymorphism. From this finding, researchers would explore the genetic region surrounding the marker to identify genetic alterations unique to the disease-associated form of the marker.

Another approach to discovering genes associated with disease is candidate gene approach, which is based on assumptions about or knowledge of the biochemistry of a disorder. For example, if the primary symptom of a particular disorder is activation of inflammatory pathways in a particular tissue, genes that encode proteins involved in inflammatory processes might be reasonable candidates to investigate for disease-associated genes. In this case, one might limit the selection of polymorphic markers to be analyzed to those that lie within genes involved in inflammation, as opposed to selecting a group of markers distributed throughout the genome. This approach has been used successfully to discover a number of disease genes. Its advantage is that case-control groups can be studied, eliminating the need to collect data from large, multigenerational families. Its disadvantage is that one must make certain assumptions about the pathophysiology of the disorder. If those assumptions are incorrect, or if the case and control groups are not carefully selected, gene discovery may not be successful.

For the microarray image shown on this slide, let us assume that each spot on the array contains the DNA of a different form of a polymorphic marker. For every form or variation of the marker, there is a separate spot on the array. DNA from the test specimen is applied to the array and allowed to hybridize (bind specifically) to the DNA on the microarray. This hybridization is based on the complementarity of the DNA double helix. Under the proper conditions, the DNA from the specimen will find its complementary counterpart on the array and hybridize (bind) to it. The DNA from the specimen is labeled with a fluorescent tag so that it can be seen with a color camera. In this way, the specimen can be genotyped for each marker represented on the array, based on the pattern of spots to which it hybridizes. For example, if a dimorphic marker (marker with two forms– A and B) is used, test samples can be genotyped as AA, BB or AB based on the pattern of fluorescence on the array. Using this technology, the entire genome of a specimen can be investigated for a large number of markers simultaneously, significantly reducing the labor, time and cost involved in the analysis. Imagine that for a particular marker a preponderance of the B allele is found in the case group but not in the control group: one might suspect that there is a susceptibility gene somewhere in the region of that particular marker. The genomic region surrounding the marker could then be further investigated to attempt to identify disease-associated genes and mutations.

Microarrays also can be used for other purposes as well, such as investigating gene expression in cells. In this application of microarray technology, DNA sequences representing all (or many) of the genes in the genome are immobilized on the array. Fluorescently labeled probes derived from the RNA of a particular cell type are applied to the array to see which genes are being expressed in the cells (and which are not). The spots corresponding to expressed genes will light up because a fluorescently labeled specimen hybridizes there. Spots corresponding to unexpressed genes will remain unlabelled. Under the proper experimental conditions, quantitation of the amount of gene expression also may be possible. This is a useful approach for comparing gene expression between normal and disease tissue. Any differences found could indicate candidate genes associated with susceptibility to or progression of the disease.

To interpret the microarray shown in this slide in a slightly different way, let us now assume that this is a gene expression microarray and that there is a spot on the microarray bearing DNA from every gene in the human genome. Let us also assume that control cDNA, cDNA derived from normal tissue has been tagged with GREEN fluorescent dye and hybridized to the target DNA on the microarray, and that sample cDNA, cDNA derived from diseased tissue is tagged with RED fluorescent dye and hybridized to the target DNA on the microarray. The spots that show green suggest that there is no expression of that particular gene in the disease tissue. The spots that show red suggest that there is no expression of that particular gene in normal tissue. The spots that show yellow would suggest that there is expression of that particular gene in both normal and disease tissue. The spots that show no fluorescence suggest that there is no expression of that particular gene in either normal or disease tissue. Discovery of the differences in gene expression between normal and disease tissue allows researchers to focus their studies on the genes whose expression differs between the normal and disease state and accelerate their understanding of the biochemical pathways that might be activated, or inactivated, in association with a particular disease.

Another use of microarray technology is to search for small gains or losses in genomic DNA in patients with particular disorders. For this application, DNA representing a large percentage of the DNA in the human genome is ordered on an array. A specimen from a patient with a disorder of unknown etiology is labeled with one fluorescent dye and mixed with equal quantities of control DNA from a person without the disorder that has been labeled with a different fluorescent dye. These two DNA samples are then allowed to hybridize to the DNA on the array. By analyzing the fluorescence bound to each of the spots on the array, scientists can determine if portions of the genome are missing from the patient DNA, or occur in more copies than usual in the patient DNA. In this way, researchers can identify regions of the genome where losses or gains of genetic information might be associated with the symptoms in the patient. This is called comparative genomic hybridization.

Because of the specificity of their DNA sequence recognition, restriction enzymes can also be used to detect mutations associated with genetic diseases. In the image shown in this slide, the restriction enzyme DdeI is used to identify the mutation in the beta-globin gene that is associated with sickle cell disease in a fragment of DNA amplified from patients by polymerase chain reaction (PCR). In this case, the mutation associated with sickle cell disease changes the DNA sequence of the beta-globin gene in such a way that it is no longer recognized by DdeI (Panel A). As a result, normal, non-sickle, beta-globin genes are digested by DdeI while sickle cell-associated alleles are not (Panel B).

When DNA from patients is amplified by PCR and the PCR products are digested with DdeI and run on agarose gel electrophoresis, a person with two normal beta-globin genes will demonstrate a two band pattern, indicating that the beta-globin DNA was cut by DdeI (Panel C, Row 1). A person with two copies of the sickle cell-associated gene will show only an uncut band, indicating that neither of the beta-globin genes was cut by DdeI (Panel C, Row 2). A carrier for sickle cell disease will demonstrate both cut and uncut bands (Panel C, Row 3), indicating that he or she has one normal gene and one sickle cell-associated gene.

Understanding the molecular genetic basis of a disorder and developing a DNA-based methodology for mutation detection enable precise DNA-based diagnosis of the disorder, permitting identification of affected and unaffected individuals, and carriers of recessive diseases. In this example, the individual in row 2 of Panel C is affected by sickle cell disease, while the individual in row 3 is a carrier for sickle cell disease.

Genetic testing has many applications. In the case of individuals showing signs or symptoms of a disorder of known genetic etiology, the gene associated with the disorder can be tested for diagnostic purposes. DNA testing also can identify unaffected carriers of recessive diseases so that risk analysis may be performed and parents can understand their risks for having a child affected by a particular genetic disorder. For example, cystic fibrosis (CF) is common in Caucasians. Carrier testing of Caucasian couples planning to have children can provide couples with information about their risks for having a child with CF. In contrast to disorders that affect individuals early in life, some genetic diseases do not begin to affect individuals until later in life. Knowing the genetic basis for such disorders provides an opportunity for presymptomatic testing of individuals at risk for the disorder. In cases where medical or lifestyle interventions can prevent or delay onset of the disease, or reduce the severity of symptoms, presymptomatic genetic testing might be of interest to at-risk individuals.

Finally, genetic testing is being used more frequently in the prescription of medications because researchers are beginning to understand the genetic basis for variable responses to medications and are applying this knowledge to the personalization of drug therapy. In the future, an individual might be tested for various genes that can predict that person’s response to a drug before the drug is prescribed. Those for whom the typical dose of the medication is predicted to have little or no effect, or those likely to experience an adverse reaction to the drug, can be offered a customized dose of the medication or an alternative medication, if one is available.

The adequacy of laws protecting the confidentiality of personal genetic information and prohibiting genetic discrimination in insurance and employment need to be evaluated and updated to keep pace with advances in genetic technologies so that the full potential of genetic medicine can be realized.

In this slide, a family segregating an autosomal dominant disorder is illustrated. The fetus, circled in orange, is at 50% risk of inheriting the gene responsible for the disorder. Genetic testing, if available, could provide information about whether the fetus has inherited the gene associated with the disorder.

Gene identification enables investigation into the causes of genetic disorders, the development of diagnostic tests for genetic disorders, and the exploration of new therapies.

A variety of genetic testing technologies are available, but not every technology is appropriate for every disorder. For example, while a karyotype is very effective for detecting Down syndrome (a chromosomal aneuploidy), it will not diagnose cystic fibrosis (CF, a single gene disorder). Thus, the selection of the appropriate testing strategy for the detection of a particular genetic disorder must be based on an understanding of the molecular basis of the disorder.

A variety of treatment approaches have the potential to impact the course of genetic diseases. For example, enzyme replacement therapies hold promise for patients affected by loss of function mutations in certain enzymes. But this approach will not work for the treatment of muscular dystrophy that is caused by abnormalities in the architecture of muscle cells. Therefore, the investigation into treatments for genetic disorders requires an understanding of the biochemical mechanisms of each disease.

The completion of the Human Genome Project has given scientists new tools with which to identify and understand the genetic factors that contribute to disease, but much work remains to be done. Over the next few decades, the discoveries of genetic factors that influence human health and disease, and patient responses to medications, are expected to revolutionize the practice of medicine. Education is crucial if genetic medicine is to fulfill its potential. We need well-prepared teachers to train students who will become the next generation of researchers, doctors, lawmakers and patients.

In this slide set, we will explore the structures and functions of genomes, including the genomes of eukaryotes, prokaryotes and viruses. We also will explore the human genome in depth and learn how changes in the structure or number of chromosomes in the human genome lead to certain genetic disorders.

Illustration:
The image on this slide is a photograph of the model of the DNA molecule built by Drs. James Watson and Francis Crick in 1953. Drs. Watson and Crick used this model to depict their proposed structure for the DNA double helix. The hypothesized structure was derived from X-ray diffraction data produced by Drs. Maurice Wilkins and Rosalind Franklin. The model was constructed from metal scraps obtained from a machine shop.

Drs. Watson and Crick published their proposed DNA structure in the journal, Nature, on April 2, 1953 (Volume 171, page 737). For their work, Drs. Watson, Crick and Wilkins were awarded the Nobel Prize in Physiology or Medicine in 1962. Dr. Franklin died before 1962. Since Nobel Prizes are awarded only to living individuals, she could not be honored.

The haploid human genome consists of 23 different chromosomes. The diploid human genome consists of 23 pairs of chromosomes. One of each pair of chromosomes is inherited from each parent. For example, each of us carries two copies of chromosome 1: one from our mother, the other from our father. The first 22 pairs of human chromosomes are called autosomes. The 23^rd pair of human chromosomes determine gender. Human females carry two X chromosomes: one inherited from the mother, one from the father. Human males carry one X chromosome and one Y chromosome. Males inherit their X chromosome from their mothers and their Y chromosome from their fathers.

In addition to the nucleus, the mitochondria of human cells also carry one or more copies of a small, circular DNA molecule. The mitochondrial chromosomes are inherited through the egg. Sperm do not contribute mitochondria to embryos. As a result, genetic diseases caused by mutations in genes on the mitochondrial chromosome are passed through the maternal lineage, from mothers to all their children. Children of fathers affected by mitochondrially transmitted genetic disorders are not at risk for inheriting the diseases. However, because mitochondria also import proteins encoded by nuclear genes, the inheritance of diseases of the mitochondria do not always follow this pattern. Examples of mitochondrially transmitted genetic diseases include MERFF (myoclonic epilepsy with ragged red [muscle] fibers), LHON (Leber hereditary optic neuropathy), a form of dementia called MELAS (mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes), MIDD (maternally inherited diabetes and deafness) syndrome, and genetic susceptibility to aminoglycoside ototoxicity (aminoglycosides are a group of antibiotics that include gentamicin, streptomycin, tobramycin, kanamycin, neomycin, amikacin, and others). In general, observable effects of mitochondrial mutations are believed to be a reflection of how sensitive particular tissues (central nervous system, skeletal muscles, heart, kidney, and liver) are to energy metabolism.

The image in the slide shows the karyotype from a normal human male (note one X and one Y chromosome). Karyotyping is a laboratory technique which allows microscopic visualization of the number and gross structure of the chromosomes within a cell. This karyotype would be abbreviated 46,XY: 46 for the number of chromosomes and XY for the sex chromosome makeup. If this karyotype were from a normal female, there would be two X chromosomes and no Y chromosome. A normal female would be designated 46,XX.

The signs and symptoms of genetic disorders caused by disruptions in the structure or number of chromosomes in the human genome are extremely variable and typically related to the particular chromosomal abnormality involved. In the case of structural rearrangements of chromosomes, most effects are likely due to disrupted expression or regulation of genes at or near the sites of structural rearrangements. In the case of chromosomal aneuploidies (the condition of having more or less than the normal number of chromosomes), alteration of the normal copy number of genes on the involved chromosome are likely the cause of most abnormalities.