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--- chapter_21 [2024/09/18 19:37] – [Simple sequence repeats (SSRs)] mike
+++ chapter_21 [2026/10/25 01:20] (current) – [Single nucleotide polymorphisms (SNPs)] mike
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+<- chapter_20|Chapter 20^table_of_contents|Table of Contents^chapter_22|Chapter 22 ->
 <typo fs:x-large> %%Polymorphisms in human DNA sequences%%</typo>
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 </table>
-Of course, to many people humans are the organism in which they are most interested, either for their intrinsic interest in themselves or for biomedical applications. Humans are also more difficult to study compared to the other model organisms we have discussed in this book. The human genome is much larger and less gene dense than invertebrates such as Drosophila or //C. elegans//. More importantly, we cannot study human genetics by designing experiments using true-breeding mutants that can generate large quantities of data to test hypotheses prospectively the way we can with model organisms; for ethical reasons we can only study human genetics retrospectively, using whatever meager quantity of data natural human populations provide. Human geneticists therefore rely on non-invasive DNA tests, genetic mapping, and statistical analyses to make connections between genotype and phenotype. There are, whoever,  some advantages to studying human genetics. First, humans are self-screening; they will self-report interesting phenotypes (usually these are genetic diseases). Second, subtle phenotypes may be more recognizable, as affected individuals may be able to talk directly with researchers.
+Of course, to many people humans are the organism in which they are most interested, either for their intrinsic interest in themselves or for biomedical applications. Humans are also more difficult to study compared to the other model organisms we have discussed in this book. The human genome is much larger and less gene dense than invertebrates such as Drosophila or //C. elegans//. More importantly, we cannot study human genetics by designing experiments using true-breeding mutants that can generate large quantities of data to test hypotheses prospectively the way we can with model organisms; for ethical reasons we can only study human genetics retrospectively, using whatever meager quantity of data natural human populations provide. Human geneticists therefore rely on non-invasive DNA tests, genetic mapping, and statistical analyses to make connections between genotype and phenotype. There are, however,  some advantages to studying human genetics. First, humans are self-screening; they will self-report interesting phenotypes (usually these are genetic diseases). Second, subtle phenotypes may be more recognizable, as affected individuals may be able to talk directly with researchers.
 ===== Polymorphisms and mapping =====
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 The vast majority (probably 99%) of SNPs are selectively “neutral” changes of little or no functional consequence. This is mostly because they likely exist outside coding or gene regulatory regions (>97% of human genome). They can also be silent substitutions in coding sequences, or amino acid substitutions that do not affect protein stability or function. A small minority of SNPs are of functional consequence and are selectively advantageous or disadvantageous; this can affect the allele frequency of these SNPs.
-SNPs can be detected in a variety of ways. Conceptually, all you need to detect a SNP is knowledge of the DNA sequence surrounding the SNP. Armed with this information, you could use PCR to amplify a DNA fragment that contains the SNP from individuals and sequence the DNA ([[chapter_07|chap. 7]]). In practice, you would likely use a device called a DNA microarray that is specifically designed to detect SNPs. Or, you could simply use NGS sequencing technology to sequence the genome of the individual to identify SNPs.
+SNPs can be detected in a variety of ways. Conceptually, all you need to detect a SNP is knowledge of the DNA sequence surrounding the SNP. Armed with this information, you could use PCR to amplify a DNA fragment that contains the SNP from individuals and sequence the DNA ([[chapter_07|Chap. 7]]). In practice, you would likely use a device called a DNA microarray that is specifically designed to detect SNPs. Or, you could simply use NGS sequencing technology to sequence the genome of the individual to identify SNPs.
 ==== Simple sequence repeats (SSRs) ====
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 In 2002, a team of Finnish scientists set out to use human genetics methods to identify mutations that are associated with hypolactasia. They reasoned that mutations that affect individuals are probably not in the protein-coding region of $LCT$, since these individuals could digest lactose as children (they also knew from other studies that there were no mutations in the $LCT$ gene of individuals that had hypolactasia). Instead, they believed that there may be mutations in nearby cis-acting regulatory sequences (see [[chapter_13|Chap. 13]]) that control the expression of $LCT$, such that it is no longer expressed in adults (they also had some other evidence to support this idea).
-The scientists examined the pedigrees of nine Finnish families with a history of hypolactasia (Fig xxx: NOTE: WAITING FOR PERMISSION FROM HHMI TO USE THE FIGURES). From the pedigrees, you can see that the inheritance pattern is consistent with hypolactasia being an autosomal recessive mutation. The scientists then collected DNA samples from volunteers in these families and analyzed various polymorphisms. They utilized seven SSRs that flanked the $LCT$ gene on either side. They found strong statistical evidence (see [[chapter_22|Chap. 22]]) for linkage of hypolactasia to an SSR upstream of the $LCT$ gene - consistent with it being a regulatory mutant instead of a coding mutant. They then used SNPs to further narrow down the genetic interval for the mutations to a 47 kb region of DNA upstream of $LCT$. In this region, they found many DNA polymorphisms among the family members, but only two SNPs that showed complete co-segregation with the hypolactasia trait. Subsequent reverse genetic studies in mice and cultured human cells suggest that these two SNPs may be mutations that affect the ability of a transcription factor called OCT-1 to bind, thereby affecting the expression of $LCT$ in adults.
+The scientists examined the pedigrees of nine Finnish families with a history of hypolactasia (Fig xxx: NOTE: WAITING FOR PERMISSION FROM HHMI TO USE THE FIGURES). From the pedigrees, you can see that the inheritance pattern is consistent with hypolactasia being an autosomal recessive mutation. The scientists then collected DNA samples from volunteers in these families and analyzed various polymorphisms. They utilized seven SSRs that flanked the $LCT$ gene on either side. They found strong statistical evidence (see [[chapter_22|Chap. 22]]) for linkage of hypolactasia to an SSR upstream of the $LCT$ gene - consistent with it being a regulatory mutant instead of a coding mutant. Since SNPs are much denser than SSRs, they then used SNPs to further narrow down the genetic interval for the mutations to a 47 kb region of DNA upstream of $LCT$. In this region, they found many DNA polymorphisms among the family members, but only two SNPs that showed complete co-segregation with the hypolactasia trait. Subsequent reverse genetic studies in mice and cultured human cells suggest that these two SNPs may be mutations that affect the ability of a transcription factor called OCT-1 to bind, thereby affecting the expression of $LCT$ in adults.