Jump to content

Draft:Chromosome mapping: Difference between revisions

From Wikipedia, the free encyclopedia
Browse history interactively
← Previous editNext edit →
Content deleted Content added
VisualWikitext
Citation bot (talk | contribs)
Bots
5,402,871 edits
Alter: date, journal, pmc. Add: bibcode, doi-access, pmid, authors 1-1. Removed URL that duplicated identifier. Removed parameters. Some additions/deletions were parameter name changes. | Use this bot. Report bugs. | Suggested by Headbomb (alt) | #UCB_toolbar
Citation bot (talk | contribs)
Bots
5,402,871 edits
Altered pages. Added pmc. | Use this bot. Report bugs. | Suggested by Headbomb (alt) | Category:CS1 maint: unflagged free DOI | #UCB_Category 27/43
Line 59: Line 59:
Chromosome mapping helps in identifying genes that are involved in [[drug metabolism]], [[Biological target|drug targets]], or drug transporters.<ref>{{Cite journal |last1=Hoehe |first1=Margret R. |last2=Kroslak |first2=Thomas |date=March 2004 |title=Genetic variation and pharmacogenomics: concepts, facts, and challenges |journal=Dialogues in Clinical Neuroscience |volume=6 |issue=1 |pages=5–26 |doi=10.31887/DCNS.2004.6.1/mhoehe |issn=1294-8322 |pmc=3181790 |pmid=22033504}}</ref> By studying the inheritance patterns of genetic markers associated with drug response in different populations, researchers can identify regions on chromosomes that are likely to contain genes influencing drug response. This helps evaluating the effects and effectiveness of drugs. Moreover, mapping helps develop genetic tests that can predict an individual's response to specific [[Medication|medications]]. By analyzing genetic markers associated with drug response, researchers can identify how genetic differences contribute to the drug effectiveness.<ref>{{Cite web |last=Ina |date=2023-11-16 |title=PERSONALIZED MEDICINE: THE POTENTIAL OF GENOME MAPPING |url=https://lasttechnology.it/en/personalized-medicine-the-potential-of-genome-mapping/ |access-date=2024-04-10 |website=Last Technology |language=en-US}}</ref> Therefore, researchers can develop tests that assess the response of a particular drug of on patients based on their [[DNA profiling|genetic profiles]] and whether they experience [[Adverse drug reaction|adverse reactions]]. This fosters the development of [[personalized medicine]].
Chromosome mapping helps in identifying genes that are involved in [[drug metabolism]], [[Biological target|drug targets]], or drug transporters.<ref>{{Cite journal |last1=Hoehe |first1=Margret R. |last2=Kroslak |first2=Thomas |date=March 2004 |title=Genetic variation and pharmacogenomics: concepts, facts, and challenges |journal=Dialogues in Clinical Neuroscience |volume=6 |issue=1 |pages=5–26 |doi=10.31887/DCNS.2004.6.1/mhoehe |issn=1294-8322 |pmc=3181790 |pmid=22033504}}</ref> By studying the inheritance patterns of genetic markers associated with drug response in different populations, researchers can identify regions on chromosomes that are likely to contain genes influencing drug response. This helps evaluating the effects and effectiveness of drugs. Moreover, mapping helps develop genetic tests that can predict an individual's response to specific [[Medication|medications]]. By analyzing genetic markers associated with drug response, researchers can identify how genetic differences contribute to the drug effectiveness.<ref>{{Cite web |last=Ina |date=2023-11-16 |title=PERSONALIZED MEDICINE: THE POTENTIAL OF GENOME MAPPING |url=https://lasttechnology.it/en/personalized-medicine-the-potential-of-genome-mapping/ |access-date=2024-04-10 |website=Last Technology |language=en-US}}</ref> Therefore, researchers can develop tests that assess the response of a particular drug of on patients based on their [[DNA profiling|genetic profiles]] and whether they experience [[Adverse drug reaction|adverse reactions]]. This fosters the development of [[personalized medicine]].


For example, [[Warfarin]], a commonly prescribed [[anticoagulant]], has been extensively studied in relation to genetic factors and chromosome mapping. Research has identified genetic variants associated with warfarin-related bleeding, such as [[Single-nucleotide polymorphism|single nucleotide polymorphisms (SNPs)]] on [[chromosome 6]].<ref name=":4">{{Cite journal |last1=De |first1=Tanima |last2=Alarcon |first2=Cristina |last3=Hernandez |first3=Wenndy |last4=Liko |first4=Ina |last5=Cavallari |first5=Larisa H. |last6=Duarte |first6=Julio D. |last7=Perera |first7=Minoli A. |date=2018-10-23 |title=Association of Genetic Variants With Warfarin-Associated Bleeding Among Patients of African Descent |url=http://dx.doi.org/10.1001/jama.2018.14955 |journal=JAMA |volume=320 |issue=16 |pages=1670 |doi=10.1001/jama.2018.14955 |pmid=30357299 |issn=0098-7484}}</ref> Additionally, genes like [[VKORC1]] on [[chromosome 16]] have been strongly associated with warfarin dose variability, highlighting the role of genetic variations in determining individual responses to warfarin treatment.<ref>{{Cite journal |last1=Wadelius |first1=Mia |last2=Chen |first2=Leslie Y. |last3=Eriksson |first3=Niclas |last4=Bumpstead |first4=Suzannah |last5=Ghori |first5=Jilur |last6=Wadelius |first6=Claes |last7=Bentley |first7=David |last8=McGinnis |first8=Ralph |last9=Deloukas |first9=Panos |date=March 2007 |title=Association of warfarin dose with genes involved in its action and metabolism |journal=Human Genetics |language=en |volume=121 |issue=1 |pages=23–34 |doi=10.1007/s00439-006-0260-8 |issn=0340-6717 |pmc=1797064 |pmid=17048007}}</ref>
For example, [[Warfarin]], a commonly prescribed [[anticoagulant]], has been extensively studied in relation to genetic factors and chromosome mapping. Research has identified genetic variants associated with warfarin-related bleeding, such as [[Single-nucleotide polymorphism|single nucleotide polymorphisms (SNPs)]] on [[chromosome 6]].<ref name=":4">{{Cite journal |last1=De |first1=Tanima |last2=Alarcon |first2=Cristina |last3=Hernandez |first3=Wenndy |last4=Liko |first4=Ina |last5=Cavallari |first5=Larisa H. |last6=Duarte |first6=Julio D. |last7=Perera |first7=Minoli A. |date=2018-10-23 |title=Association of Genetic Variants With Warfarin-Associated Bleeding Among Patients of African Descent |url=http://dx.doi.org/10.1001/jama.2018.14955 |journal=JAMA |volume=320 |issue=16 |pages=1670–1677 |doi=10.1001/jama.2018.14955 |pmid=30357299 |pmc=6233811 |issn=0098-7484}}</ref> Additionally, genes like [[VKORC1]] on [[chromosome 16]] have been strongly associated with warfarin dose variability, highlighting the role of genetic variations in determining individual responses to warfarin treatment.<ref>{{Cite journal |last1=Wadelius |first1=Mia |last2=Chen |first2=Leslie Y. |last3=Eriksson |first3=Niclas |last4=Bumpstead |first4=Suzannah |last5=Ghori |first5=Jilur |last6=Wadelius |first6=Claes |last7=Bentley |first7=David |last8=McGinnis |first8=Ralph |last9=Deloukas |first9=Panos |date=March 2007 |title=Association of warfarin dose with genes involved in its action and metabolism |journal=Human Genetics |language=en |volume=121 |issue=1 |pages=23–34 |doi=10.1007/s00439-006-0260-8 |issn=0340-6717 |pmc=1797064 |pmid=17048007}}</ref>


== Limitation ==
== Limitation ==

Revision as of 16:42, 29 May 2024

Chromosome mapping is a method determining the relative position of genes within a chromosome. [1] This process creates a map that shows genetic information on chromosomes by showing the gene positions and distances between them, represented on a standardised scale. It is discovered by Thomas Hunt Morgan when investigating the Drosophila gene. The advancement of sequencing technology and statistics make chromosome mapping more commonplace. The development of chromosome mapping also pushed forward the onset of Human Genome Project. By mapping all the chromosomes, a comprehensive map of human genome is created. The outcome serves as a reference of human genome which greatly benefits the future research on genetics.

There are two methods in creating a chromosome map: genetic mapping and physical mapping. For genetic mapping, recombinations of DNA markers and genes in chromosomes are analysed and a probabilistic model helps predict the linear arrangement of genes. In physical mapping, the gene is cleaved by restriction enzymes. The distance between cleavage sites and size of gene fragments are measured in order to generate the genetic map.

History

The concept of chromosome mapping was suggested by biologist Thomas Hunt Morgan in 1911. When he was studying fruit flies, he found that some traits were different from Mendel’s Law of Independent Assortment and there was clear evidence on genetic linkage. He found that the white eye gene in Drosophila was located on the X chromosome. This helps identify other X-linked genes and the mapping. The outcome is a chromosome map that shows a linear arrangement of genes.[1] However, genetic mapping to humans did not become commonplace until the 1950s, due to the obstacle of identifying which traits were associated with genetic mutations. In 1980, the discovery of Restriction Fragment Length Polymorphisms (RFLPs) made mapping easier and pushed forward the development of comprehensive chromosome maps. [2] In the late 1980s, rough maps encompassing the whole chromosomes were constructed successfully. In mid-1990s, the refinement of statistical analysis methods enabled researchers to construct a whole-genome genetic map covering all chromosomes. [3]

One of the major milestones in chromosome mapping is the Human Genome Project, an worldwide collaboration to determine the full sequence of the entire human genome, based on genetic information obtained from chromosomes. [4][5] The project was initiated in 1990 and achieved near completion in 2003, findings were subsequently published in 2004 for worldwide and public access. [5][6] While continuous refinement was ongoing to tackle the remaining gaps in human genome sequence. Ultimately, the complete and gapless sequence of the human genome was mapped in 2022 and published globally, indicating the whole human genome sequence was deciphered successfully. [7] The Human Genome Project provided valuable insights to human genetics and illustrated the continuous progression of genomic research, in addition to its versatile application in various aspects of medicine and public health.

Method

Overview of Chromosome Mapping

An image indicating the human karyogram, involves all twenty-three pairs of homologous chromosomes - including twenty-two pairs of autosomal chromosomes, two sex chromosomes with both female (XX) and male (XY) versions.

Chromosome Mapping provides the relative location of genes in chromosomes, which is crucial for investigating the arrangement and organisation of genetic information. Chromosome mapping is divided into two categories - involves genetic mapping and physical mapping.

Genetic Mapping

Genetic Mapping investigates organisation of genes and DNA markers using linkage analysis, to predict gene positions and recombination frequencies between genes. [1][8]The measurement is based on the unit centiMorgan (cM), where one centiMorgan is roughly one million base pairs in the human genome. Additionally, each centiMorgan indicates a 1% probability of two genetic markers/genes  being separated by recombination during meiosis.[9]Therefore the increase of distance between those genes also increases the chance of recombination occurring, indicating higher recombination frequency.

In particular, genetic linkage between two genes is determined based on their respective distance and locations on the chromosomes – in linked genes, the closer distance leads to a higher probability being inherited together; while for unlinked genes, the distance is further apart where independent inheritance is more likely, indicating the genes are located on different chromosomes. [9]In addition, the inheritance patterns for genes located on same chromosome depend on recombination frequency, which influences their genetic linkage profile – linked or unlinked. [9]Through studying recombination of DNA markers and genes in chromosomes, it provides further insights on inheritance patterns, possibility of recombinations during meiosis.

Types of DNA Molecular markers

DNA molecular markers are DNA sequences that include at least two alleles and could be differentiated easily, which is adapted to locate specific positions in the genome during mapping.[8] By analysing the inheritance patterns of DNA molecular markers, genetic maps visualising gene positions and markers on the genome can be assembled.

Restriction Fragment Length Polymorphisms (RFLP)

Restriction Fragment Length Polymorphisms (RFLP) involves DNA restriction fragments with polymorphic restriction sites, which is processed by restriction enzymes by cutting DNA at specific recognition sites, hence it generates restriction fragments with variable lengths. Through investigating the inheritance pattern of RFLP, its position on the genome map can be determined. [1][8]

Single Sequence Length Polymorphisms (SSLP)

Single Sequence Length Polymorphisms (SSLP) indicate repeat sequences with variable length and number of tandem repeats, hence each SSLP can generate diverse variants. [1][8]It is further classified into microsatellites and minisatellites:

Minisatellites – Variable Number of Tandem Repeats (VNTRs) with longer repeat units, up to a maximum length of 25 base pairs.

Microsatellites – Simple Tandem Repeats (STRs) with shorter repeat units, typically in dinucleotide or tetranucleotide units.

Simple Nucleotide Polymorphisms (SNP)

Simple Nucleotide Polymorphisms (SNP) indicates variations at specific positions in the genome, which have different nucleotides.[8]

Physical Mapping

Physical Mapping involves visualising the distance of restriction enzyme cleavage sites on chromosomal DNA, the measurement is based on the number of nucleotides for determining the size of DNA fragments. [8][9]Additionally, to determine gene positions and provide direct information of chromosomes, which aids the generation of physical maps.

Fluorescence In Situ Hybridisation (FISH)

Fluorescence In Situ Hybridisation (FISH) includes investigation of intact chromosomes through hybridisation by DNA sequences being labelled with fluorescence probes.[1][8]This method allows visualisation of specific positions of DNA sequences on chromosomes based on examining fluorescence signals and location of hybridisation by labelled DNA.

Sequence Tagged Site Mapping (STS)

Sequence Tagged Site Mapping (STS) uses Sequence Tagged Sites, which are DNA sequences that occur distinctly in the genome, with a length between 100 to 500 base pairs.[1][8]Additionally, it must have a known DNA sequence and its position in chromosome or genome must be unique, ensures there won't be any duplicated DNA present.[8] This method enables the generation of genome maps with great detail.

Restriction Mapping

Restriction mapping aims to locate restriction site position in DNA molecules, by comparing sizes of DNA fragments generated using different restriction enzymes which recognise different target sequences. [8]This method is important for locating non-polymorphic restriction sites and increasing the density of DNA markers on genome maps. [8]

Application

Disease diagnosis

Chromosome mapping can help identify the location of specific genes on chromosomes. It involves studying the inheritance patterns of genetic markers or variations within families or populations to determine the association between these markers and the presence of a particular disease or trait, allowing researchers to make predictions about the genes they think are causing the mutant phenotype.[10]An example of a disease where chromosome mapping has been instrumental is Cystic Fibrosis (CF). CF is a genetic disorder caused by mutations in the CFTR gene located on chromosome 7. By mapping the CFTR gene to this specific region on chromosome 7 [11],researchers have been able to understand the genetic mechanisms of CF, and develop diagnostic tests by identifying related biomarkers. [12]

Pharmacogenomics

Chromosome mapping helps in identifying genes that are involved in drug metabolism, drug targets, or drug transporters.[13] By studying the inheritance patterns of genetic markers associated with drug response in different populations, researchers can identify regions on chromosomes that are likely to contain genes influencing drug response. This helps evaluating the effects and effectiveness of drugs. Moreover, mapping helps develop genetic tests that can predict an individual's response to specific medications. By analyzing genetic markers associated with drug response, researchers can identify how genetic differences contribute to the drug effectiveness.[14] Therefore, researchers can develop tests that assess the response of a particular drug of on patients based on their genetic profiles and whether they experience adverse reactions. This fosters the development of personalized medicine.

For example, Warfarin, a commonly prescribed anticoagulant, has been extensively studied in relation to genetic factors and chromosome mapping. Research has identified genetic variants associated with warfarin-related bleeding, such as single nucleotide polymorphisms (SNPs) on chromosome 6.[15] Additionally, genes like VKORC1 on chromosome 16 have been strongly associated with warfarin dose variability, highlighting the role of genetic variations in determining individual responses to warfarin treatment.[16]

Limitation

Incomplete information

Firstly, for an individual homozygous at a gene, it is unknown whether it is inherited from maternity or paternity as the gene has the same locus on two homologous chromosomes. While for an individual heterozygous at a gene, the origin of allele is unknown without studying the individual’s parents’ genes as it could be from either maternal or paternal gene.[17]

Incomplete penetrance

In genetics, penetrance refers to the statistical occurrence of phenotypes given that one contains related genotypes.[18]For some genotypes, there may be reduced penetrance influenced by factors like age, environmental exposure or random chance. These factors may engender a delay of symptoms or even the gene will not be expressed in one’s life. [19]This makes the study on association between genes and complex traits more difficult and harder to conclude. Thus, statistical models and large sample sizes are required to overcome this challenge. [20]

Reference List

  1. ^ a b c d e f g Tamang, Sanju (2023-08-28). "Chromosome Mapping: Definition, Types, Importance". microbenotes.com. Retrieved 2024-04-10.
  2. ^ Beckmann, J. S.; Soller, M. (November 1983). "Restriction fragment length polymorphisms in genetic improvement: methodologies, mapping and costs". Theoretical and Applied Genetics. 67 (1): 35–43. doi:10.1007/bf00303919. ISSN 0040-5752. PMID 24258478.
  3. ^ "Mapping - History Of Genetic Mapping". medicine.jrank.org. Retrieved 2024-03-27.
  4. ^ "Human Genome Project Timeline". www.genome.gov. Retrieved 2024-04-10.
  5. ^ a b "Human Genome Project Fact Sheet". www.genome.gov. Retrieved 2024-04-10.
  6. ^ "Human Genome Project (HGP) | History, Timeline, & Facts | Britannica". www.britannica.com. 2024-02-21. Retrieved 2024-04-10.
  7. ^ "First complete sequence of a human genome". National Institutes of Health (NIH). 2022-04-11. Retrieved 2024-04-10.
  8. ^ a b c d e f g h i j k Brown, Terence A. (2002), "Mapping Genomes", Genomes. 2nd edition, Wiley-Liss, retrieved 2024-04-10
  9. ^ a b c d Genome, National Research Council (US) Committee on Mapping and Sequencing the Human (1988), "Mapping", Mapping and Sequencing the Human Genome, National Academies Press (US), retrieved 2024-04-10
  10. ^ Harper, Marc A.; Chen, Zugen; Toy, Traci; Machado, Iara M. P.; Nelson, Stanley F.; Liao, James C.; Lee, Christopher J. (2011-02-18). "Phenotype Sequencing: Identifying the Genes That Cause a Phenotype Directly from Pooled Sequencing of Independent Mutants". PLOS ONE. 6 (2): e16517. Bibcode:2011PLoSO...616517H. doi:10.1371/journal.pone.0016517. ISSN 1932-6203. PMC 3041756. PMID 21364744.
  11. ^ Information (US), National Center for Biotechnology (1998), "Chromosome Map", Genes and Disease [Internet], National Center for Biotechnology Information (US), retrieved 2024-04-10
  12. ^ Smith, D. R.; Fulton, T. R.; Swain, P.; Bowcock, A.; Daneshvar, L.; Traver, C.; Gruenert, D. C.; Davis, R.; Cavalli-Sforza, L. L.; Donis-Keller, H. (July 1989). "Cystic fibrosis: diagnostic testing and the search for the gene". Clinical Chemistry. 35 (7 Suppl): B17–20. ISSN 0009-9147. PMID 2568193.
  13. ^ Hoehe, Margret R.; Kroslak, Thomas (March 2004). "Genetic variation and pharmacogenomics: concepts, facts, and challenges". Dialogues in Clinical Neuroscience. 6 (1): 5–26. doi:10.31887/DCNS.2004.6.1/mhoehe. ISSN 1294-8322. PMC 3181790. PMID 22033504.
  14. ^ Ina (2023-11-16). "PERSONALIZED MEDICINE: THE POTENTIAL OF GENOME MAPPING". Last Technology. Retrieved 2024-04-10.
  15. ^ De, Tanima; Alarcon, Cristina; Hernandez, Wenndy; Liko, Ina; Cavallari, Larisa H.; Duarte, Julio D.; Perera, Minoli A. (2018-10-23). "Association of Genetic Variants With Warfarin-Associated Bleeding Among Patients of African Descent". JAMA. 320 (16): 1670–1677. doi:10.1001/jama.2018.14955. ISSN 0098-7484. PMC 6233811. PMID 30357299.
  16. ^ Wadelius, Mia; Chen, Leslie Y.; Eriksson, Niclas; Bumpstead, Suzannah; Ghori, Jilur; Wadelius, Claes; Bentley, David; McGinnis, Ralph; Deloukas, Panos (March 2007). "Association of warfarin dose with genes involved in its action and metabolism". Human Genetics. 121 (1): 23–34. doi:10.1007/s00439-006-0260-8. ISSN 0340-6717. PMC 1797064. PMID 17048007.
  17. ^ Calculating the Secrets of Life: Contributions of the Mathematical Sciences to Molecular Biology. Washington, D.C.: National Academies Press. 1995-04-06. doi:10.17226/2121. ISBN 978-0-309-04886-6.
  18. ^ "Phenotype Variability: Penetrance and Expressivity | Learn Science at Scitable". www.nature.com. Retrieved 2024-04-10.
  19. ^ Shieh, Joseph T. C. (January 2019). "Expanding Genomic Sequencing and Incomplete Penetrance". Pediatrics. 143 (Suppl 1): S22–S26. doi:10.1542/peds.2018-1099E. ISSN 0031-4005. PMC 7185999. PMID 30600267.
  20. ^ Kingdom, Rebecca; Wright, Caroline F. (2022-07-25). "Incomplete Penetrance and Variable Expressivity: From Clinical Studies to Population Cohorts". Frontiers in Genetics. 13: 920390. doi:10.3389/fgene.2022.920390. ISSN 1664-8021. PMC 9380816. PMID 35983412.
Retrieved from "https://en.wikipedia.org/enwiki/w/index.php?title=Draft:Chromosome_mapping&oldid=1226276687"