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These are the user uploaded subtitles that are being translated: 0 00:00:00,000 --> 00:00:02,970 MICHAEL HEMANN: So there are a couple kinds of main DNA 1 00:00:02,970 --> 00:00:06,360 markers that we'll talk about, and the first of them 2 00:00:06,360 --> 00:00:10,760 are called SSRs. 3 00:00:10,760 --> 00:00:14,285 And SSRs are simple sequence repeats. 4 00:00:14,285 --> 00:00:22,000 5 00:00:22,000 --> 00:00:24,730 So as you know, much of our genome 6 00:00:24,730 --> 00:00:27,280 consists of repetitive elements. 7 00:00:27,280 --> 00:00:31,120 Some of these are different viruses or transposons that 8 00:00:31,120 --> 00:00:32,380 have popped into our genome. 9 00:00:32,380 --> 00:00:35,270 We have lots of repeat sequences at centromeres 10 00:00:35,270 --> 00:00:39,220 and the telomeres, and we also have simple repeats, so two, 11 00:00:39,220 --> 00:00:42,520 or three, or four nucleotide repeats that are actually 12 00:00:42,520 --> 00:00:44,780 found throughout our genome. 13 00:00:44,780 --> 00:00:48,610 And again, they likely have no functional relevance at all, 14 00:00:48,610 --> 00:00:51,220 or very few actually do. 15 00:00:51,220 --> 00:00:53,050 But we have a genome that is much 16 00:00:53,050 --> 00:00:58,630 larger than our actual total sum gene size, or gene content. 17 00:00:58,630 --> 00:01:00,550 And so we have a simple sequence repeats. 18 00:01:00,550 --> 00:01:03,320 And so what does a simple sequence repeat look like? 19 00:01:03,320 --> 00:01:12,620 Well, it could be just two nucleotides, like c and A. 20 00:01:12,620 --> 00:01:17,180 And they'll be present at some length. 21 00:01:17,180 --> 00:01:19,790 There could be 20 repeats, there could be 50 repeats, 22 00:01:19,790 --> 00:01:22,010 there could be hundreds repeats of just 23 00:01:22,010 --> 00:01:24,410 this dinucleotide sequence. 24 00:01:24,410 --> 00:01:29,690 And they're, again, spread out through our entire genome. 25 00:01:29,690 --> 00:01:33,140 And they are variable between individuals and variable 26 00:01:33,140 --> 00:01:34,680 between alleles. 27 00:01:34,680 --> 00:01:37,220 So in some cases, a person may have 28 00:01:37,220 --> 00:01:42,590 a 40 repeat stretch, so 40 copies of CA on one chromosome, 29 00:01:42,590 --> 00:01:48,140 and 80 on the homolog, the one that you got from mom and dad. 30 00:01:48,140 --> 00:01:49,730 So they are variable. 31 00:01:49,730 --> 00:01:50,780 They're polymorphic. 32 00:01:50,780 --> 00:01:54,800 And so we can use these changes and distinctions in size 33 00:01:54,800 --> 00:01:58,070 to identify which allele that we're talking about 34 00:01:58,070 --> 00:01:59,820 and which parent that we're talking about. 35 00:01:59,820 --> 00:02:04,370 So how do we actually mark a particular CA repeat? 36 00:02:04,370 --> 00:02:06,320 Well, you can think of them as just sitting 37 00:02:06,320 --> 00:02:07,470 in a place in the genome. 38 00:02:07,470 --> 00:02:10,830 So you have at some point CACACA. 39 00:02:10,830 --> 00:02:16,520 Maybe this is on chromosome 10, 10p, the short arm. 40 00:02:16,520 --> 00:02:26,520 At some precise location, you have a repeat length 41 00:02:26,520 --> 00:02:30,840 of some n, some number of CA repeats. 42 00:02:30,840 --> 00:02:33,000 And we define their location essentially 43 00:02:33,000 --> 00:02:34,950 by using PCR primers. 44 00:02:34,950 --> 00:02:43,095 So you'll have PCR primer here and a PCR primer here. 45 00:02:43,095 --> 00:02:47,040 46 00:02:47,040 --> 00:02:49,800 And these target sites for the PCR primers 47 00:02:49,800 --> 00:02:51,660 are invariant between people. 48 00:02:51,660 --> 00:02:53,170 So they're exactly the same. 49 00:02:53,170 --> 00:02:56,520 It's just the repeat length between these PCR primers 50 00:02:56,520 --> 00:02:57,340 is different. 51 00:02:57,340 --> 00:03:01,990 So the PCR primers define the precise place in the genome. 52 00:03:01,990 --> 00:03:04,560 So we know these sequences are on 10p 53 00:03:04,560 --> 00:03:11,040 in a particular location, and we can amplify them using PCR. 54 00:03:11,040 --> 00:03:12,990 And we'll get a certain length product 55 00:03:12,990 --> 00:03:14,400 that corresponds with the length, 56 00:03:14,400 --> 00:03:16,480 or the number of CA repeats. 57 00:03:16,480 --> 00:03:22,820 So we can visualize these things on, say, an agarose gel. 58 00:03:22,820 --> 00:03:30,185 So I'm going to draw a gel here with a few wells. 59 00:03:30,185 --> 00:03:35,270 60 00:03:35,270 --> 00:03:39,200 And say we have different lengths. 61 00:03:39,200 --> 00:03:41,800 So we're to run the gel this way, 62 00:03:41,800 --> 00:03:44,230 so bigger things are at the top and smaller things 63 00:03:44,230 --> 00:03:45,650 are the bottom. 64 00:03:45,650 --> 00:03:52,180 And so say that this corresponds to a CA repeat of 80 bases, 65 00:03:52,180 --> 00:03:57,190 and this corresponds to CA repeat of 40 bases. 66 00:03:57,190 --> 00:04:02,530 And so you have maybe a mom, and mom has one of each. 67 00:04:02,530 --> 00:04:07,280 So one allele has 80 repeats and the other has 40 repeats, 68 00:04:07,280 --> 00:04:12,670 and maybe you have dad, and dad has one that's even bigger, 69 00:04:12,670 --> 00:04:15,880 and one that's sort of in the middle. 70 00:04:15,880 --> 00:04:20,829 And you can have a child, and the child 71 00:04:20,829 --> 00:04:27,520 will have, say, one there and one there. 72 00:04:27,520 --> 00:04:29,650 So we can look at inheritance, we 73 00:04:29,650 --> 00:04:34,000 can look at the segregation of both of these alleles 74 00:04:34,000 --> 00:04:39,580 based on this variation in repeat length. 75 00:04:39,580 --> 00:04:43,510 Now I actually remember, when I was starting in science, 76 00:04:43,510 --> 00:04:46,850 I was working as a lab technician over at Harvard 77 00:04:46,850 --> 00:04:48,970 and I was doing this kind of analysis. 78 00:04:48,970 --> 00:05:01,430 And I ran a gel like this and I got this result. 79 00:05:01,430 --> 00:05:04,180 How is this possible? 80 00:05:04,180 --> 00:05:06,060 One of the parents isn't the parent. 81 00:05:06,060 --> 00:05:08,760 This is an example of non-paternity. 82 00:05:08,760 --> 00:05:10,900 It's not the father. 83 00:05:10,900 --> 00:05:15,720 And in fact, this happens, and this is generally 84 00:05:15,720 --> 00:05:17,950 how we do a paternity test. 85 00:05:17,950 --> 00:05:20,370 We don't look at genes, we actually 86 00:05:20,370 --> 00:05:25,350 look at markers that are variable in populations. 87 00:05:25,350 --> 00:05:27,360 And you say, oh, did the child inherit 88 00:05:27,360 --> 00:05:29,310 a marker from the proposed mother 89 00:05:29,310 --> 00:05:31,650 and from the proposed father? 90 00:05:31,650 --> 00:05:34,080 And if they didn't, then it's a possibility 91 00:05:34,080 --> 00:05:37,290 that it's not the father and that it's 92 00:05:37,290 --> 00:05:41,830 a case of non-paternity. 93 00:05:41,830 --> 00:05:45,630 So this is a map of a chromosome. 94 00:05:45,630 --> 00:05:48,360 In this case, it's chromosome 21 where 95 00:05:48,360 --> 00:05:53,040 all of these things that are listed like D21S1410, these 96 00:05:53,040 --> 00:05:56,520 are all simple repeat markers. 97 00:05:56,520 --> 00:05:58,590 And so you imagine that if you are looking 98 00:05:58,590 --> 00:06:04,870 at a bunch of different markers and all these markers 99 00:06:04,870 --> 00:06:09,830 will have a different allele frequency, 100 00:06:09,830 --> 00:06:14,260 which means how common is this length in the population. 101 00:06:14,260 --> 00:06:23,050 So say you have 10 of these markers that you're looking at, 102 00:06:23,050 --> 00:06:25,160 and they have different frequencies. 103 00:06:25,160 --> 00:06:30,640 So maybe one is there at 10%, and 30%, and 5%, 104 00:06:30,640 --> 00:06:34,895 and just putting in different numbers here. 105 00:06:34,895 --> 00:06:42,470 106 00:06:42,470 --> 00:06:44,110 So the different alleles that you're 107 00:06:44,110 --> 00:06:46,540 looking at in an individual are going 108 00:06:46,540 --> 00:06:48,070 to be present at variable amounts. 109 00:06:48,070 --> 00:06:50,810 Sometimes they're in half the population, sometimes 70%, 110 00:06:50,810 --> 00:06:52,750 sometimes they're low frequency. 111 00:06:52,750 --> 00:06:56,440 But you can imagine that looking at 10 of these, if you actually 112 00:06:56,440 --> 00:07:02,620 multiply these out, you're looking at less than 1 113 00:07:02,620 --> 00:07:08,950 in 250 million chance, if you had these markers, of randomly 114 00:07:08,950 --> 00:07:10,660 having these in an individual. 115 00:07:10,660 --> 00:07:14,860 So you can get a really high resolution picture 116 00:07:14,860 --> 00:07:19,270 of somebody's identity based on the identity 117 00:07:19,270 --> 00:07:22,610 of these alleles within them. 118 00:07:22,610 --> 00:07:25,720 And so a lot of forensic testing, paternity testing, 119 00:07:25,720 --> 00:07:30,850 is based entirely on this, what are the repeat markers 120 00:07:30,850 --> 00:07:33,120 that this person has. 9113

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