1 00:00:00,790 --> 00:00:07,320 [Music] 2 00:00:12,090 --> 00:00:09,320 [Applause] 3 00:00:14,520 --> 00:00:12,100 hello my name is Anton Mohammed I'm from 4 00:00:16,529 --> 00:00:14,530 Oakland University in Michigan and I'm a 5 00:00:19,380 --> 00:00:16,539 master student and I'm working with dr. 6 00:00:21,960 --> 00:00:19,390 favia but the suit see on domain 7 00:00:26,009 --> 00:00:21,970 signatures of genome complexity and 8 00:00:29,099 --> 00:00:26,019 extremophiles so what are extremophiles 9 00:00:31,980 --> 00:00:29,109 extremophiles are those interesting and 10 00:00:34,260 --> 00:00:31,990 unique organisms that live in extreme 11 00:00:38,910 --> 00:00:34,270 environments and they live in hot and 12 00:00:41,040 --> 00:00:38,920 cold niches and they also live in acid 13 00:00:43,170 --> 00:00:41,050 solutions alkaline solutions salty 14 00:00:46,950 --> 00:00:43,180 environments and they include members of 15 00:00:49,259 --> 00:00:46,960 all they glued members of all domain all 16 00:00:53,189 --> 00:00:49,269 domains of life are kiai eukaryotes and 17 00:00:55,860 --> 00:00:53,199 bacteria and archaea is the major group 18 00:00:57,779 --> 00:00:55,870 that survive in extreme environments and 19 00:00:59,880 --> 00:00:57,789 although members of this group are less 20 00:01:02,040 --> 00:00:59,890 versatile than bacteria and eukaryotes 21 00:01:05,340 --> 00:01:02,050 they're quite skilled at adapting to 22 00:01:08,820 --> 00:01:05,350 extreme conditions and extremophiles 23 00:01:11,310 --> 00:01:08,830 exist in all of the archaeal phyla and 24 00:01:13,380 --> 00:01:11,320 in our data we only have the 25 00:01:15,690 --> 00:01:13,390 crenarchaeota the URI archaea and the 26 00:01:19,950 --> 00:01:15,700 thumb mark iota and these are some 27 00:01:22,830 --> 00:01:19,960 examples of the extremophiles we have 28 00:01:25,530 --> 00:01:22,840 the hyperthermophiles in red and then 29 00:01:27,660 --> 00:01:25,540 the thermo files in green and then we 30 00:01:30,510 --> 00:01:27,670 have the psycho files in blue and then 31 00:01:32,700 --> 00:01:30,520 piezo files also called viral files in 32 00:01:34,410 --> 00:01:32,710 black and as you may know that the 33 00:01:37,950 --> 00:01:34,420 extreme environments are unstable 34 00:01:39,780 --> 00:01:37,960 environments so that they're likely to 35 00:01:43,920 --> 00:01:39,790 lead to high variability at the genomic 36 00:01:45,990 --> 00:01:43,930 level so on any sort of adaptation or 37 00:01:48,719 --> 00:01:46,000 surviving strategy is likely to have 38 00:01:50,550 --> 00:01:48,729 genomic signatures and here we're 39 00:01:53,639 --> 00:01:50,560 looking at these genomic signatures and 40 00:01:55,560 --> 00:01:53,649 the organisms and part of these genomic 41 00:01:58,080 --> 00:01:55,570 signatures which are part of the bigger 42 00:02:00,660 --> 00:01:58,090 group are LCR's the low-complexity 43 00:02:02,819 --> 00:02:00,670 regions and LCR's have been known to be 44 00:02:04,920 --> 00:02:02,829 evolutionarily significant because they 45 00:02:07,709 --> 00:02:04,930 provide genomes and individual genes 46 00:02:12,240 --> 00:02:07,719 with adjustable turning knobs for 47 00:02:13,920 --> 00:02:12,250 efficient adaptation so previous 48 00:02:16,589 --> 00:02:13,930 research has been done by hearting 49 00:02:18,059 --> 00:02:16,599 Golding and showed that LCR's are not 50 00:02:20,730 --> 00:02:18,069 conserved regions and that they 51 00:02:23,400 --> 00:02:20,740 accumulate mutations so here 52 00:02:24,900 --> 00:02:23,410 number zero we have the LCR's and these 53 00:02:27,090 --> 00:02:24,910 are the number of mutations they 54 00:02:29,760 --> 00:02:27,100 accumulate the proportion of snips the 55 00:02:31,200 --> 00:02:29,770 single nucleotide polymorphisms and the 56 00:02:33,390 --> 00:02:31,210 different colors here and the graph 57 00:02:37,200 --> 00:02:33,400 shows the different conditions they 58 00:02:38,700 --> 00:02:37,210 tested the LCR Xen and genomic 59 00:02:41,010 --> 00:02:38,710 variability has been tested in 60 00:02:43,530 --> 00:02:41,020 eukaryotes and viruses and in the 61 00:02:45,810 --> 00:02:43,540 viruses it was suggested that LCR's are 62 00:02:47,910 --> 00:02:45,820 an important source of genomic 63 00:02:49,530 --> 00:02:47,920 variability for the lengthy virus and 64 00:02:51,960 --> 00:02:49,540 that they're an important source for 65 00:02:55,710 --> 00:02:51,970 antigenic variability in the HIV 66 00:02:58,050 --> 00:02:55,720 populations so what are the low 67 00:03:00,120 --> 00:02:58,060 complexity regions the LCR's are 68 00:03:03,360 --> 00:03:00,130 repetitive sequences that contain few 69 00:03:04,800 --> 00:03:03,370 nucleotides or amino acid types and some 70 00:03:06,840 --> 00:03:04,810 regions contain few different 71 00:03:09,930 --> 00:03:06,850 nucleotides or amino acids while others 72 00:03:12,660 --> 00:03:09,940 only contain one and LCR's have various 73 00:03:14,760 --> 00:03:12,670 configurations ranging from periodic to 74 00:03:16,800 --> 00:03:14,770 a periodic motives and they have 75 00:03:19,020 --> 00:03:16,810 different nomenclatures ranging from low 76 00:03:21,060 --> 00:03:19,030 complexity sequences tandem repeats 77 00:03:23,280 --> 00:03:21,070 simple sequence repeats amino acid 78 00:03:27,560 --> 00:03:23,290 repeats but they all basically share the 79 00:03:31,310 --> 00:03:27,570 same low complex or low diverse sequence 80 00:03:33,690 --> 00:03:31,320 so LCR's are ubiquitous in eukaryotes 81 00:03:35,760 --> 00:03:33,700 about still the function and 82 00:03:38,430 --> 00:03:35,770 evolutionary forces that act on these 83 00:03:40,500 --> 00:03:38,440 regions are unknown and are poorly 84 00:03:42,720 --> 00:03:40,510 understood and here on the right we have 85 00:03:45,270 --> 00:03:42,730 examples of LCR's and different 86 00:03:47,910 --> 00:03:45,280 eukaryotic species so for example in the 87 00:03:50,460 --> 00:03:47,920 homo sapiens the humans we have about 88 00:03:53,010 --> 00:03:50,470 18% and then in the Plasmodium 89 00:03:55,980 --> 00:03:53,020 falciparum the malaria agent we have 90 00:03:59,060 --> 00:03:55,990 about 50% so the proportion of genes 91 00:04:02,870 --> 00:03:59,070 that contain LCR's is highly variable 92 00:04:06,180 --> 00:04:02,880 across the different eukaryotic species 93 00:04:09,990 --> 00:04:06,190 so all the information that we have so 94 00:04:12,300 --> 00:04:10,000 far on LCR's is a result of research on 95 00:04:14,370 --> 00:04:12,310 eukaryotes and here you can see the 96 00:04:15,870 --> 00:04:14,380 eukaryotic tree and the parts that are 97 00:04:17,520 --> 00:04:15,880 marked with a star are the ones that 98 00:04:20,520 --> 00:04:17,530 have been studied for LCR's 99 00:04:22,530 --> 00:04:20,530 and even those form the minority in 100 00:04:25,290 --> 00:04:22,540 comparison to the other eukaryotic 101 00:04:27,840 --> 00:04:25,300 species and no one actually has looked 102 00:04:29,700 --> 00:04:27,850 at prokaryotes for LCR's and although 103 00:04:32,370 --> 00:04:29,710 the prokaryotes formed the majority of 104 00:04:34,680 --> 00:04:32,380 the fully sequenced genomes thus they 105 00:04:37,740 --> 00:04:34,690 provide us with a huge set of data 106 00:04:40,410 --> 00:04:37,750 to analyze and work with and prokaryotes 107 00:04:43,110 --> 00:04:40,420 also also form two out of the three 108 00:04:45,450 --> 00:04:43,120 three main domains of life and all the 109 00:04:49,470 --> 00:04:45,460 analysis that has been done so far was 110 00:04:51,930 --> 00:04:49,480 done on model eukaryotic species so in 111 00:04:54,060 --> 00:04:51,940 order to study a full domain we need to 112 00:04:56,820 --> 00:04:54,070 develop new testing methods and analysis 113 00:04:58,650 --> 00:04:56,830 in order to automate the process so we 114 00:05:01,860 --> 00:04:58,660 decided to focus on archaea in our 115 00:05:04,170 --> 00:05:01,870 research because archaea has about 200 116 00:05:07,470 --> 00:05:04,180 species while bacteria have 13,000 117 00:05:09,270 --> 00:05:07,480 species so when we study our km we will 118 00:05:11,400 --> 00:05:09,280 be able to develop these new testing 119 00:05:13,620 --> 00:05:11,410 methods and to automate the process in 120 00:05:15,750 --> 00:05:13,630 our future research so what we actually 121 00:05:18,530 --> 00:05:15,760 did we got the fully sequenced genomes 122 00:05:21,600 --> 00:05:18,540 of archaea from ncbi and it was about 123 00:05:24,240 --> 00:05:21,610 221 species and then we did basic 124 00:05:26,640 --> 00:05:24,250 statistics to see the LCR patterns and 125 00:05:28,950 --> 00:05:26,650 trends in the archaea and at that point 126 00:05:33,000 --> 00:05:28,960 we don't really know if LCR's even 127 00:05:34,920 --> 00:05:33,010 exists in archaea so now i'm going to be 128 00:05:38,460 --> 00:05:34,930 talking about the LCR patterns that we 129 00:05:40,770 --> 00:05:38,470 explored in archaea and the LCR 130 00:05:43,290 --> 00:05:40,780 frequency LCR length versus protein 131 00:05:45,810 --> 00:05:43,300 length the LCR frequency versus the GC 132 00:05:49,640 --> 00:05:45,820 content the amino acid composition and 133 00:05:53,070 --> 00:05:49,650 usage and the LCR location the proteins 134 00:05:55,890 --> 00:05:53,080 so to calculate the LCR frequency we 135 00:05:57,840 --> 00:05:55,900 just followed a simple equation a number 136 00:06:00,510 --> 00:05:57,850 of proteins with LCR's over the total 137 00:06:02,730 --> 00:06:00,520 number of proteins times 100 around this 138 00:06:04,800 --> 00:06:02,740 tree you can see the red are the 139 00:06:06,600 --> 00:06:04,810 temperature extremophiles and then the 140 00:06:08,909 --> 00:06:06,610 yellow are the temperature meter files 141 00:06:12,300 --> 00:06:08,919 and the orange bars are the LCR 142 00:06:13,980 --> 00:06:12,310 frequency so on average the healthy our 143 00:06:16,080 --> 00:06:13,990 frequency arranged between three and 144 00:06:18,270 --> 00:06:16,090 seven percent and when we looked 145 00:06:21,300 --> 00:06:18,280 specifically at certain groups for 146 00:06:23,760 --> 00:06:21,310 example the halobacteria the salt loving 147 00:06:25,860 --> 00:06:23,770 extremophiles we saw that they have the 148 00:06:29,670 --> 00:06:25,870 highest LCR frequency which was about 149 00:06:31,650 --> 00:06:29,680 14% and halobacteria else our salt 150 00:06:33,960 --> 00:06:31,660 loving extremophiles they live in salt 151 00:06:38,159 --> 00:06:33,970 extreme environments and the red water 152 00:06:39,900 --> 00:06:38,169 here shows the halobacteria and then 153 00:06:43,620 --> 00:06:39,910 when we looked at other groups such as 154 00:06:45,350 --> 00:06:43,630 the clan RKO de which are temperature 155 00:06:47,879 --> 00:06:45,360 extremophiles and to be exact 156 00:06:50,010 --> 00:06:47,889 hyperthermophiles and they all 157 00:06:52,320 --> 00:06:50,020 so have a high LCR frequency but it's 158 00:06:57,269 --> 00:06:52,330 lower than the halobacteria and there's 159 00:06:59,939 --> 00:06:57,279 range between 10 and 12 percent so we 160 00:07:01,649 --> 00:06:59,949 decide we are compared the LCR frequency 161 00:07:03,869 --> 00:07:01,659 between these groups to see if there is 162 00:07:05,369 --> 00:07:03,879 any significant difference and as you 163 00:07:07,529 --> 00:07:05,379 can see we saw that the halobacteria 164 00:07:10,080 --> 00:07:07,539 have a higher LCR frequency than the 165 00:07:12,570 --> 00:07:10,090 crenarchaeota and they have a higher LCR 166 00:07:14,939 --> 00:07:12,580 frequency than the URI RK Ora and the 167 00:07:17,879 --> 00:07:14,949 URI are Keota in this case includes both 168 00:07:19,980 --> 00:07:17,889 extremophiles and Misa files so the main 169 00:07:22,800 --> 00:07:19,990 question here is is this high LCR 170 00:07:24,689 --> 00:07:22,810 frequency a characteristic of salt 171 00:07:27,059 --> 00:07:24,699 extremophiles or temperature 172 00:07:30,659 --> 00:07:27,069 extremophiles or extremophiles in 173 00:07:33,689 --> 00:07:30,669 general so to answer this question we 174 00:07:35,640 --> 00:07:33,699 did a further analysis comparing the LCR 175 00:07:37,830 --> 00:07:35,650 frequency between halobacteria and 176 00:07:40,230 --> 00:07:37,840 archaea and as you can see we saw that 177 00:07:42,659 --> 00:07:40,240 halobacteria has a higher LCR frequency 178 00:07:44,490 --> 00:07:42,669 than archaea in general and even when we 179 00:07:46,619 --> 00:07:44,500 compared the needs of files and 180 00:07:48,239 --> 00:07:46,629 extremophiles in the URI our Keota we 181 00:07:51,149 --> 00:07:48,249 see that the Mesa files have a higher 182 00:07:53,129 --> 00:07:51,159 LCR frequency than the extremophiles so 183 00:07:55,050 --> 00:07:53,139 this suggests that the high LCR 184 00:07:57,600 --> 00:07:55,060 frequency is a characteristic and D 185 00:07:59,700 --> 00:07:57,610 salt-loving extremophiles and there are 186 00:08:01,860 --> 00:07:59,710 actually a few possible explanations to 187 00:08:04,740 --> 00:08:01,870 this trend that we just saw and one of 188 00:08:07,079 --> 00:08:04,750 them is that LCR's are an emergent 189 00:08:08,879 --> 00:08:07,089 property of proteins meaning longer 190 00:08:10,860 --> 00:08:08,889 proteins will have longer LCR's 191 00:08:13,589 --> 00:08:10,870 and when we compared them we didn't see 192 00:08:15,389 --> 00:08:13,599 this correlation between them so if the 193 00:08:17,670 --> 00:08:15,399 LCR s are not an emergent property of 194 00:08:19,589 --> 00:08:17,680 proteins the LCR's might be driven by 195 00:08:22,529 --> 00:08:19,599 the GC content of the genome whether 196 00:08:24,749 --> 00:08:22,539 it's high or low GC content so previous 197 00:08:27,749 --> 00:08:24,759 research done by TN showed that the LCR 198 00:08:31,019 --> 00:08:27,759 frequency is driven by the 80 content of 199 00:08:32,850 --> 00:08:31,029 the genome in eukaryotes and in our data 200 00:08:34,829 --> 00:08:32,860 as you can see the hello bacteria and 201 00:08:37,019 --> 00:08:34,839 the yellow temperature extremophiles in 202 00:08:40,259 --> 00:08:37,029 blue temperature mesa files in red they 203 00:08:42,089 --> 00:08:40,269 all follow the same trend and when we 204 00:08:43,680 --> 00:08:42,099 did a comparison for significant 205 00:08:46,560 --> 00:08:43,690 differences we saw that the halobacteria 206 00:08:49,290 --> 00:08:46,570 has a higher GC content than all of the 207 00:08:51,990 --> 00:08:49,300 other groups that Grande URI and then 208 00:08:54,060 --> 00:08:52,000 all of the archaea in general and even 209 00:08:57,240 --> 00:08:54,070 the mesa files had a higher GC content 210 00:08:59,460 --> 00:08:57,250 than the extremophiles so that means yes 211 00:09:01,410 --> 00:08:59,470 the patterns of GC and LC are 212 00:09:02,850 --> 00:09:01,420 frequencies are the same 213 00:09:05,870 --> 00:09:02,860 and that they'll see our frequency is 214 00:09:08,430 --> 00:09:05,880 driven by the GC content of the genome 215 00:09:10,740 --> 00:09:08,440 then we looked at the specific amino 216 00:09:13,050 --> 00:09:10,750 acid usage between extremophiles and 217 00:09:15,750 --> 00:09:13,060 mizore files and we saw that they both 218 00:09:18,360 --> 00:09:15,760 use our GC rich amino acids but 219 00:09:21,060 --> 00:09:18,370 extremophiles also use a T rich amino 220 00:09:23,940 --> 00:09:21,070 acids which is expected as we saw they 221 00:09:25,380 --> 00:09:23,950 have a lower GC content every one we 222 00:09:28,110 --> 00:09:25,390 looked specifically at the hello 223 00:09:30,210 --> 00:09:28,120 bacteria we saw that they use similar 224 00:09:33,120 --> 00:09:30,220 amino acids to the miso files and there 225 00:09:36,180 --> 00:09:33,130 are GC rich amino acids and then we 226 00:09:37,890 --> 00:09:36,190 compared in the amino acids usage 227 00:09:39,810 --> 00:09:37,900 between the halobacteria and the urea 228 00:09:41,370 --> 00:09:39,820 Ark iota and we found that they have 229 00:09:43,740 --> 00:09:41,380 different amino acids in their 230 00:09:46,650 --> 00:09:43,750 composition and actually previous 231 00:09:48,720 --> 00:09:46,660 research in eukaryotes showed that the 232 00:09:50,670 --> 00:09:48,730 amino acid composition is species 233 00:09:53,520 --> 00:09:50,680 specific and it's different between the 234 00:09:54,960 --> 00:09:53,530 groups and as you can see these are 235 00:09:57,210 --> 00:09:54,970 three different research done on 236 00:09:59,640 --> 00:09:57,220 vertebrates drosophila and Plasmodium 237 00:10:01,140 --> 00:09:59,650 falciparum and if you look closely all 238 00:10:02,790 --> 00:10:01,150 of them use different amino acid 239 00:10:04,740 --> 00:10:02,800 composition in their LCR's 240 00:10:07,730 --> 00:10:04,750 and the reason actually behind this 241 00:10:10,530 --> 00:10:07,740 difference is still unknown 242 00:10:13,260 --> 00:10:10,540 so up to this point just to summarize we 243 00:10:16,590 --> 00:10:13,270 saw that the LCR's are driven by the GC 244 00:10:18,990 --> 00:10:16,600 content of the genome and the amino acid 245 00:10:21,660 --> 00:10:19,000 composition confirmed this as we saw 246 00:10:23,490 --> 00:10:21,670 that they use GC rich amino acids so 247 00:10:25,200 --> 00:10:23,500 this suggests the neutrality of these 248 00:10:27,990 --> 00:10:25,210 regions and that there are functionless 249 00:10:30,060 --> 00:10:28,000 regions so we decided to look at the LCR 250 00:10:32,840 --> 00:10:30,070 locations in the proteins because this 251 00:10:35,490 --> 00:10:32,850 might be a sign of potential selection 252 00:10:37,860 --> 00:10:35,500 so we followed a previously developed 253 00:10:39,930 --> 00:10:37,870 methods where we divided the protein 254 00:10:42,240 --> 00:10:39,940 into three segments the n-terminal the 255 00:10:44,160 --> 00:10:42,250 middle and then the c-terminal and then 256 00:10:46,260 --> 00:10:44,170 we calculated the difference between the 257 00:10:48,870 --> 00:10:46,270 observed distribution of the middle 258 00:10:51,930 --> 00:10:48,880 point of the LCR's and the expected 259 00:10:54,300 --> 00:10:51,940 distribution to locate where HL c our 260 00:10:56,700 --> 00:10:54,310 sequence would fall and our null 261 00:10:59,220 --> 00:10:56,710 hypothesis suggests that the LCR's are 262 00:11:00,960 --> 00:10:59,230 randomly distributed and our alternative 263 00:11:03,300 --> 00:11:00,970 hypothesis suggests that they are not 264 00:11:05,520 --> 00:11:03,310 randomly distributed and that means that 265 00:11:08,640 --> 00:11:05,530 there is a potential biological function 266 00:11:11,010 --> 00:11:08,650 for them so the results of our 267 00:11:13,200 --> 00:11:11,020 chi-square shows that in extremophiles 268 00:11:15,660 --> 00:11:13,210 we have 82 percent and in the mesial 269 00:11:17,850 --> 00:11:15,670 files we have 75% significant 270 00:11:19,499 --> 00:11:17,860 which means that the LCR's do prefer 271 00:11:22,139 --> 00:11:19,509 certain locations and that they're not 272 00:11:24,689 --> 00:11:22,149 randomly distributed and when we look at 273 00:11:26,699 --> 00:11:24,699 the extremophiles in the Misa files we 274 00:11:29,280 --> 00:11:26,709 see that they both follow the same trend 275 00:11:32,009 --> 00:11:29,290 where the LCR's are located at the 276 00:11:34,049 --> 00:11:32,019 terminal of the proteins and when we 277 00:11:35,999 --> 00:11:34,059 look at the halobacteria specifically we 278 00:11:38,309 --> 00:11:36,009 also see that they follow the same trend 279 00:11:40,559 --> 00:11:38,319 and the LCR's are at the terminal of the 280 00:11:42,769 --> 00:11:40,569 proteins and this actually follows a 281 00:11:45,600 --> 00:11:42,779 previous trend that was found in 282 00:11:47,910 --> 00:11:45,610 research in eukaryotes and this one 283 00:11:50,009 --> 00:11:47,920 specifically in the drosophila where it 284 00:11:51,989 --> 00:11:50,019 shows that the LCR's prefer to be at the 285 00:11:54,780 --> 00:11:51,999 extremities of the protein rather than 286 00:11:57,329 --> 00:11:54,790 in the middle and this suggests that 287 00:11:58,559 --> 00:11:57,339 there might be a potential function for 288 00:12:02,999 --> 00:11:58,569 these regions and that they're not 289 00:12:05,449 --> 00:12:03,009 functionalist regions so do LCR's 290 00:12:08,730 --> 00:12:05,459 actually help extremophiles to survive 291 00:12:11,489 --> 00:12:08,740 well maybe but we do know the LCR's are 292 00:12:13,799 --> 00:12:11,499 a common feature in archaea and that 293 00:12:16,049 --> 00:12:13,809 they exist in salt-loving extremophiles 294 00:12:19,259 --> 00:12:16,059 and a higher frequency than the other 295 00:12:22,860 --> 00:12:19,269 extremophiles we also saw that the LCR's 296 00:12:24,869 --> 00:12:22,870 are are driven by the GC content of the 297 00:12:26,910 --> 00:12:24,879 genome and this was confirmed with the 298 00:12:27,929 --> 00:12:26,920 amino acid usage as we saw that they use 299 00:12:30,840 --> 00:12:27,939 gc-rich 300 00:12:33,360 --> 00:12:30,850 amino acids and we also saw that the 301 00:12:36,389 --> 00:12:33,370 amino acid usage is species specific and 302 00:12:38,429 --> 00:12:36,399 different between the groups so all of 303 00:12:41,340 --> 00:12:38,439 that with the non-random distribution of 304 00:12:44,249 --> 00:12:41,350 the LCR's we can say that the LCR's 305 00:12:45,600 --> 00:12:44,259 maybe creating genomic variability for 306 00:12:47,730 --> 00:12:45,610 the halobacteria the salt-loving 307 00:12:50,040 --> 00:12:47,740 extremophiles specifically so they can 308 00:12:52,590 --> 00:12:50,050 survive and there are extreme 309 00:12:54,030 --> 00:12:52,600 environment but we did not really see 310 00:12:57,329 --> 00:12:54,040 this trend in the temperature 311 00:12:59,249 --> 00:12:57,339 extremophiles so this suggests that they 312 00:13:01,379 --> 00:12:59,259 may be using different adaptive 313 00:13:04,470 --> 00:13:01,389 strategies to survive in their extreme 314 00:13:06,210 --> 00:13:04,480 environments so I'd like to thank 315 00:13:08,669 --> 00:13:06,220 Oakland University central for 316 00:13:11,189 --> 00:13:08,679 biomedical research NASA and IH for 317 00:13:13,410 --> 00:13:11,199 funding this program and I would like to 318 00:13:15,509 --> 00:13:13,420 thank dr. Sheila Sheila Randall Westrick 319 00:13:17,590 --> 00:13:15,519 and all of my lab members for helping me 320 00:13:18,340 --> 00:13:17,600 in this research thank you for attention 321 00:13:19,350 --> 00:13:18,350 [Applause] 322 00:13:21,010 --> 00:13:19,360 [Music] 323 00:13:23,540 --> 00:13:21,020 [Applause] 324 00:13:25,280 --> 00:13:23,550 all right Thank You Anton so we're 325 00:13:27,920 --> 00:13:25,290 running a little bit short on time but 326 00:13:33,200 --> 00:13:27,930 we have time I'm sorry we have time for 327 00:13:33,210 --> 00:13:40,970 thanks for the good talk 328 00:13:48,170 --> 00:13:44,080 my name is Tian from the University of I 329 00:13:50,780 --> 00:13:48,180 was wondering if you looked at the 330 00:13:59,510 --> 00:13:50,790 distribution of other hit archaea 331 00:14:04,700 --> 00:13:59,520 halophiles we looked specifically at the 332 00:14:06,230 --> 00:14:04,710 fully sequenced genomes so these were 333 00:14:09,970 --> 00:14:06,240 the only ones that were available on 334 00:14:12,980 --> 00:14:09,980 NCBI to look for their distribution 335 00:14:16,310 --> 00:14:12,990 they're like two or three other hello 336 00:14:20,000 --> 00:14:16,320 Felix lineages of like really weird GC 337 00:14:23,090 --> 00:14:20,010 content so well there was actually a 338 00:14:25,850 --> 00:14:23,100 paper back in 2008 that explained the 339 00:14:27,770 --> 00:14:25,860 high GC content and the hallow files and 340 00:14:31,640 --> 00:14:27,780 that convergent evolution have to do 341 00:14:34,370 --> 00:14:31,650 with this weird GC content in the hallow