All language subtitles for 27031x_MH_Overview_02_Forward_Reverse_v1-en

af Afrikaans
sq Albanian
am Amharic
ar Arabic
hy Armenian
az Azerbaijani
eu Basque
be Belarusian
bn Bengali
bs Bosnian
bg Bulgarian
ca Catalan
ceb Cebuano
ny Chichewa
zh-CN Chinese (Simplified)
zh-TW Chinese (Traditional)
co Corsican
hr Croatian
cs Czech
da Danish
nl Dutch
en English
eo Esperanto
et Estonian
tl Filipino
fi Finnish
fr French Download
fy Frisian
gl Galician
ka Georgian
de German
el Greek
gu Gujarati
ht Haitian Creole
ha Hausa
haw Hawaiian
iw Hebrew
hi Hindi
hmn Hmong
hu Hungarian
is Icelandic
ig Igbo
id Indonesian
ga Irish
it Italian
ja Japanese
jw Javanese
kn Kannada
kk Kazakh
km Khmer
ko Korean
ku Kurdish (Kurmanji)
ky Kyrgyz
lo Lao
la Latin
lv Latvian
lt Lithuanian
lb Luxembourgish
mk Macedonian
mg Malagasy
ms Malay
ml Malayalam
mt Maltese
mi Maori
mr Marathi
mn Mongolian
my Myanmar (Burmese)
ne Nepali
no Norwegian
ps Pashto
fa Persian
pl Polish
pt Portuguese
pa Punjabi
ro Romanian
ru Russian
sm Samoan
gd Scots Gaelic
sr Serbian
st Sesotho
sn Shona
sd Sindhi
si Sinhala
sk Slovak
sl Slovenian
so Somali
es Spanish
su Sundanese
sw Swahili
sv Swedish
tg Tajik
ta Tamil
te Telugu
th Thai
tr Turkish
uk Ukrainian
ur Urdu
uz Uzbek
vi Vietnamese
cy Welsh
xh Xhosa
yi Yiddish
yo Yoruba
zu Zulu
or Odia (Oriya)
rw Kinyarwanda
tk Turkmen
tt Tatar
ug Uyghur
Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 0 00:00:00,000 --> 00:00:04,970 MICHAEL HEMANN: Good, so why are we here? 1 00:00:04,970 --> 00:00:06,400 Well, genetics, right? 2 00:00:06,400 --> 00:00:10,300 So that is true specific, literally, 3 00:00:10,300 --> 00:00:13,180 and is true cosmically. 4 00:00:13,180 --> 00:00:18,730 But genetics in a large overview essentially 5 00:00:18,730 --> 00:00:36,160 is the connection between genotype and phenotype. 6 00:00:36,160 --> 00:00:40,360 So genotype meaning the genetic status, the DNA sequence, 7 00:00:40,360 --> 00:00:43,980 the gene content of us or the organisms 8 00:00:43,980 --> 00:00:48,840 that we study, and phenotype, meaning what we see, 9 00:00:48,840 --> 00:00:51,970 what is around us. 10 00:00:51,970 --> 00:00:55,080 The movement from phenotype to genotype essentially 11 00:00:55,080 --> 00:00:58,350 underlies the first half of this course. 12 00:00:58,350 --> 00:01:01,290 And the converse movement from genotype to phenotype 13 00:01:01,290 --> 00:01:04,110 represents, to some extent, the second half of this course. 14 00:01:04,110 --> 00:01:06,450 But essentially everything that I'm going to talk about 15 00:01:06,450 --> 00:01:11,220 involves the connection between our gene content 16 00:01:11,220 --> 00:01:14,500 and the biology that we see. 17 00:01:14,500 --> 00:01:21,670 So this movement from phenotype to genotype, we term 18 00:01:21,670 --> 00:01:24,860 forward genetics. 19 00:01:24,860 --> 00:01:27,470 So forward genetics, moving from a phenotype 20 00:01:27,470 --> 00:01:29,148 to genotype, why do you want to do that? 21 00:01:29,148 --> 00:01:30,440 Well, you see something, right? 22 00:01:30,440 --> 00:01:32,240 You have some characteristic and you 23 00:01:32,240 --> 00:01:34,700 want to understand the genetic etiology of it. 24 00:01:34,700 --> 00:01:36,255 You're working on an organism, you 25 00:01:36,255 --> 00:01:37,880 want to know why does it look that way. 26 00:01:37,880 --> 00:01:40,910 You want to know why do we look the way that we look like. 27 00:01:40,910 --> 00:01:42,920 Why do we have the genetic predispositions? 28 00:01:42,920 --> 00:01:45,350 Why do we have the biological conditions, 29 00:01:45,350 --> 00:01:46,340 the medical conditions? 30 00:01:46,340 --> 00:01:50,690 We want to trace those down to a genetic etiology. 31 00:01:50,690 --> 00:01:58,230 And we do that essentially by a process called mapping. 32 00:01:58,230 --> 00:02:00,300 So we look at inheritance. 33 00:02:00,300 --> 00:02:01,770 We perform crosses. 34 00:02:01,770 --> 00:02:06,150 We look at DNA marker analysis, all in an attempt 35 00:02:06,150 --> 00:02:09,960 to move us from very broad phenotypes to very 36 00:02:09,960 --> 00:02:12,330 specific genes, and, specifically, 37 00:02:12,330 --> 00:02:14,910 particular sequence variations that 38 00:02:14,910 --> 00:02:16,440 exist in those genes, that explain 39 00:02:16,440 --> 00:02:17,820 the underlying etiology. 40 00:02:17,820 --> 00:02:20,700 This allows us to predict patterns of inheritance, 41 00:02:20,700 --> 00:02:24,330 to give good counseling if we're genetic counselors. 42 00:02:24,330 --> 00:02:27,240 They allow us to understand a biology that's 43 00:02:27,240 --> 00:02:29,400 governing a process so that perhaps we 44 00:02:29,400 --> 00:02:31,110 have therapeutic interventions that we 45 00:02:31,110 --> 00:02:34,770 can use to actually alter phenotypes or better understand 46 00:02:34,770 --> 00:02:36,340 the basis of those phenotypes. 47 00:02:36,340 --> 00:02:38,790 So there's a lot of work in a lot of organisms 48 00:02:38,790 --> 00:02:42,610 that we'll talk about that allows us to do this mapping. 49 00:02:42,610 --> 00:02:43,840 So how do you do mapping? 50 00:02:43,840 --> 00:02:48,660 How do you go from the very big idea to the very specific gene? 51 00:02:48,660 --> 00:02:57,600 The reverse direction, from genotype to phenotype, we term 52 00:02:57,600 --> 00:02:59,160 reverse genetics. 53 00:02:59,160 --> 00:03:01,800 So how do you go from genotype to phenotype? 54 00:03:01,800 --> 00:03:04,500 Well, essentially, you break things. 55 00:03:04,500 --> 00:03:11,530 And breaking, in a genetic sense, is mutation. 56 00:03:11,530 --> 00:03:14,070 So you have a gene and you wonder what it does. 57 00:03:14,070 --> 00:03:15,690 Well, you introduce a mutation. 58 00:03:15,690 --> 00:03:18,300 Or you mutate all of the genes in a strain 59 00:03:18,300 --> 00:03:22,170 to look at what are the consequent phenotypes following 60 00:03:22,170 --> 00:03:23,620 perturbation of this gene. 61 00:03:23,620 --> 00:03:26,130 So, again, it allows us to explore, 62 00:03:26,130 --> 00:03:31,860 using engineering, the possible functions of a particular gene 63 00:03:31,860 --> 00:03:34,630 of interest. 64 00:03:34,630 --> 00:03:40,380 So let's talk a little bit about phenotypes. 65 00:03:40,380 --> 00:03:43,750 Well, phenotypes are all around us. 66 00:03:43,750 --> 00:03:47,550 We all have a host of really interesting, very 67 00:03:47,550 --> 00:03:50,250 cool phenotypes. 68 00:03:50,250 --> 00:03:54,930 Does anybody-- I don't know if everybody's had cilantro. 69 00:03:54,930 --> 00:03:57,760 But does cilantro tastes like soap to anybody? 70 00:03:57,760 --> 00:03:59,202 I've got cilantro here. 71 00:03:59,202 --> 00:04:00,660 It's actually kind of old cilantro. 72 00:04:00,660 --> 00:04:05,560 73 00:04:05,560 --> 00:04:09,040 I don't know, but it tastes OK, maybe not great. 74 00:04:09,040 --> 00:04:13,532 75 00:04:13,532 --> 00:04:17,680 But it doesn't taste like soap to me. 76 00:04:17,680 --> 00:04:25,170 So we have 80 responders, 81 responders. 77 00:04:25,170 --> 00:04:29,960 And for six of them, it actually tastes like soap. 78 00:04:29,960 --> 00:04:32,140 It's, again, an interesting phenotype. 79 00:04:32,140 --> 00:04:36,420 So you can actually start with this very broad phenotype. 80 00:04:36,420 --> 00:04:38,520 You can map that phenotype. 81 00:04:38,520 --> 00:04:42,780 And you can map it back to a specific difference 82 00:04:42,780 --> 00:04:52,570 in their nucleotide sequence, in a gene called OR6A2. 83 00:04:52,570 --> 00:04:53,770 So what is that? 84 00:04:53,770 --> 00:04:57,560 It's an olfactory receptor, essentially a smell receptor. 85 00:04:57,560 --> 00:05:00,070 So if you have a difference in the gene 86 00:05:00,070 --> 00:05:03,550 sequence in this olfactory receptor, 87 00:05:03,550 --> 00:05:05,458 cilantro essentially tastes like soap. 88 00:05:05,458 --> 00:05:07,000 Now, you can actually deal with this. 89 00:05:07,000 --> 00:05:10,330 You can actually sort of learn to live with this 90 00:05:10,330 --> 00:05:11,508 and sort of overcome it. 91 00:05:11,508 --> 00:05:13,300 I don't know if it's worth it for cilantro. 92 00:05:13,300 --> 00:05:16,450 But if you're really committed to it, you can. 93 00:05:16,450 --> 00:05:19,510 But amazingly, again, just a very simple distinction, 94 00:05:19,510 --> 00:05:21,670 genetic distinction, between us, can 95 00:05:21,670 --> 00:05:26,210 lead to a very peculiar distinction between us. 96 00:05:26,210 --> 00:05:27,460 The phenotype is not peculiar. 97 00:05:27,460 --> 00:05:30,940 It's just peculiar that some of us have it and some of us 98 00:05:30,940 --> 00:05:32,320 don't. 99 00:05:32,320 --> 00:05:36,940 What about this one? 100 00:05:36,940 --> 00:05:40,490 101 00:05:40,490 --> 00:05:46,310 Do any of you sneeze when you go from the dark into sunlight? 102 00:05:46,310 --> 00:05:50,940 So you're in a movie theater and you walk outside. 103 00:05:50,940 --> 00:05:52,620 Maybe you don't know that you do it. 104 00:05:52,620 --> 00:05:54,630 You should try it. 105 00:05:54,630 --> 00:05:57,210 I mean, February is not a good time to try it. 106 00:05:57,210 --> 00:05:59,520 But go from the dark and into the sunlight. 107 00:05:59,520 --> 00:06:03,990 It's estimated about a quarter of the population actually has 108 00:06:03,990 --> 00:06:04,950 this phenotype. 109 00:06:04,950 --> 00:06:07,800 110 00:06:07,800 --> 00:06:12,690 And the phenotype is referred to as ACHOO syndrome, 111 00:06:12,690 --> 00:06:18,060 or autosomal dominant compelling helio-ophthalmic outburst. 112 00:06:18,060 --> 00:06:23,760 ACHOO syndrome is a more simple way of saying it. 113 00:06:23,760 --> 00:06:28,530 But this is due to a genetic polymorphism 114 00:06:28,530 --> 00:06:30,302 adjacent to a gene called Zeb2. 115 00:06:30,302 --> 00:06:32,010 It's actually unclear whether it actually 116 00:06:32,010 --> 00:06:36,100 has anything to do with Zeb2 itself. 117 00:06:36,100 --> 00:06:39,990 But there's a proximal distinction in a nucleotide 118 00:06:39,990 --> 00:06:43,050 sequence between people that have this syndrome and people 119 00:06:43,050 --> 00:06:44,832 that don't. 120 00:06:44,832 --> 00:06:46,290 It's really unclear whether there's 121 00:06:46,290 --> 00:06:48,330 any other problem with anybody that 122 00:06:48,330 --> 00:06:52,110 has this condition, other than their propensity to sneeze. 123 00:06:52,110 --> 00:06:55,530 But it's just representative of the really cool variation 124 00:06:55,530 --> 00:06:57,840 that exists between lots of different people 125 00:06:57,840 --> 00:06:58,760 and populations. 126 00:06:58,760 --> 00:07:01,500 This is a dominant condition. 127 00:07:01,500 --> 00:07:05,980 The cilantro condition is likely a recessive condition. 128 00:07:05,980 --> 00:07:08,700 And we'll talk about what those mean next time. 129 00:07:08,700 --> 00:07:09,960 But these are phenotypes. 130 00:07:09,960 --> 00:07:12,150 And we can map these phenotypes and understand 131 00:07:12,150 --> 00:07:14,880 the genetic etiology by doing mapping studies, which 132 00:07:14,880 --> 00:07:16,740 we'll talk a lot about. 133 00:07:16,740 --> 00:07:18,840 So what about going the opposite direction? 134 00:07:18,840 --> 00:07:22,140 What about going from genotype to phenotype? 135 00:07:22,140 --> 00:07:27,000 Well, here, as I mentioned before, what we generally do 136 00:07:27,000 --> 00:07:30,700 is breaking things. 137 00:07:30,700 --> 00:07:34,230 And so if you think about an equivalent 138 00:07:34,230 --> 00:07:37,470 of this breaking process, it's like asking 139 00:07:37,470 --> 00:07:40,440 what a car part does if you actually pull it out 140 00:07:40,440 --> 00:07:42,420 of the car, all right, so looking 141 00:07:42,420 --> 00:07:45,240 at the overall phenotype of that car 142 00:07:45,240 --> 00:07:48,420 once you actually take out a specific piece. 143 00:07:48,420 --> 00:07:53,950 This is classic genetics approaches. 144 00:07:53,950 --> 00:07:59,770 And so what happens if you actually take a car part out? 145 00:07:59,770 --> 00:08:02,620 Well, here are two phenotypes, right? 146 00:08:02,620 --> 00:08:04,800 Car won't start. 147 00:08:04,800 --> 00:08:06,290 Car won't stop. 148 00:08:06,290 --> 00:08:08,730 These are kind of big phenotypes. 149 00:08:08,730 --> 00:08:12,270 Which one do you think is the most, or the more specific, 150 00:08:12,270 --> 00:08:13,590 phenotype? 151 00:08:13,590 --> 00:08:17,723 The car won't start is a pretty broad phenotype. 152 00:08:17,723 --> 00:08:19,890 So there are lots of things you can think about that 153 00:08:19,890 --> 00:08:21,600 would cause a car not to start. 154 00:08:21,600 --> 00:08:22,810 So you don't have a key. 155 00:08:22,810 --> 00:08:23,935 You don't have an ignition. 156 00:08:23,935 --> 00:08:25,020 You don't have a motor. 157 00:08:25,020 --> 00:08:27,516 You don't have a transmission. 158 00:08:27,516 --> 00:08:29,880 There are lots of problems, lots of things that give you 159 00:08:29,880 --> 00:08:31,830 the same phenotype in the end. 160 00:08:31,830 --> 00:08:35,400 Car won't stop has a pretty specific etiology, right? 161 00:08:35,400 --> 00:08:37,110 You got a problem with your brakes. 162 00:08:37,110 --> 00:08:38,880 And so when we're doing genetics, 163 00:08:38,880 --> 00:08:41,490 we like to have very specific phenotypes. 164 00:08:41,490 --> 00:08:43,740 We want to have informative phenotypes that tell us 165 00:08:43,740 --> 00:08:45,930 that a gene that we're perturbing 166 00:08:45,930 --> 00:08:52,620 is very specifically involved in a particular process. 167 00:08:52,620 --> 00:08:54,450 And the more specific that phenotype 168 00:08:54,450 --> 00:08:57,300 can be, the more informative that screen is going to be, 169 00:08:57,300 --> 00:08:59,550 the more informative our perturbation of this gene 170 00:08:59,550 --> 00:09:00,762 is going to be. 171 00:09:00,762 --> 00:09:02,220 So that's something to bear in mind 172 00:09:02,220 --> 00:09:05,327 as we think about how we do this kind of broad reverse genetics. 173 00:09:05,327 --> 00:09:07,410 A lot of you have probably done this kind of thing 174 00:09:07,410 --> 00:09:08,918 before in a genetic screen. 175 00:09:08,918 --> 00:09:11,460 And again, you want to have a phenotype that really tells you 176 00:09:11,460 --> 00:09:17,000 something very specific about what you're doing. 13196

Can't find what you're looking for?
Get subtitles in any language from opensubtitles.com, and translate them here.