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--- chapter_21 [2024/09/18 19:34] – [Simple sequence repeats (SSRs)] mike
+++ chapter_21 [2024/09/18 19:47] (current) – 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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 SSRs can be used as markers for any kind of mapping of human genes, but they are commonly used in forensics. The Federal Bureau of Investigation (FBI) maintains a DNA database called the Combined DNA Index System (CODIS) that contains data on a core set of SSR alleles from convicted offenders or arrestees of various crimes. Prior to 2017, 13 STR loci were used in CODIS entries; since 2017, an additional 7 STR loci have been added. These loci are chosen such that they are unlinked from each other. This maximizes their utility in identifying unique individuals. This technique of using STR allele combinations to identify individuals is called DNA fingerprinting.
-A consequence of SSR loci being neutral and not under selection is that these loci are usually in Hardy-Weinberg equilibrium ([[chapter_18|Chapter 18]]). This allows forensic scientists to use the principles of population genetics to calculate allele frequencies. When the DNA of a suspect matches forensic evidence at a crime scene, allele frequency (together with information on SSR loci mutation rate) allows forensic scientists to calculate the likelihood that the combination of SSR alleles found in evidence matches that of the suspect is due to random chance. For instance, let's say there 11 different alleles at an SSR locus. Let's say that allele 1 has a frequency of 0.4 and allele 2 has a frequency of 0.2. The likelihood of a random individual in the population being heterozygous at this locus for allele 1 and 2 is $0.4 \times 0.2 = 0.08$ or 8%. Let's round this number up to 10% for easy math, and let's just guesstimate that the likelihood for a random match for most SSR loci is also about 10% (or 0.1). If a forensic investigator compares 13 different loci and gets a perfect match to a suspect, the likelihood that this match is due to random chance is $0.1^{13}$, or one in a trillion! This is why DNA fingerprinting is such a powerful method for law enforcement.
+A consequence of SSR loci being neutral and not under selection is that these loci are usually in Hardy-Weinberg equilibrium ([[chapter_18|Chapter 18]]). This allows forensic scientists to use the principles of population genetics to calculate allele frequencies. When the DNA of a suspect matches forensic evidence at a crime scene, allele frequency (together with information on SSR loci mutation rate) allows forensic scientists to calculate the likelihood that the combination of SSR alleles found in evidence matches that of the suspect is due to random chance. For instance, let's say there 11 different alleles at an SSR locus. Let's say that allele 1 has a frequency of 0.5 and allele 2 has a frequency of 0.2; the remaining alleles are more rare and make up the remaining 0.3. The likelihood of a random individual in the population being heterozygous at this locus for allele 1 and 2 is $0.5 \times 0.2 = 0.1$ or 10. Let's just guesstimate that the likelihood for a random match for most SSR loci is also about 10% (or 0.1). If a forensic investigator compares 13 different loci and gets a perfect match to a suspect, the likelihood that this match is due to random chance is $0.1^{13}=10^{-12}$, or one in a trillion! This is why DNA fingerprinting is such a powerful method for law enforcement.
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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.