[ 0 → 7] Welcome to Episode 6 of Foundations Restored, a Catholic Perspective on Origins. [ 7 → 9] I'm your host, Keith Jones. [ 9 → 15] This episode continues to expose the failure of the Darwinian icons, and it explains the [ 15 → 21] foundational flaw of Darwinian evolution, which is the claim that mutations, acting [ 21 → 27] with natural selection over time, constitute a plausible mechanism for molecules to man [ 27 → 28] evolution. [ 28 → 34] This flaw is foundational because once the failure of the Darwinian mechanism is exposed, [ 34 → 40] it allows us to dismiss the notion that fossil finds will one day arise to support Darwinism. [ 58 → 65] Welcome to Episode 6 of Foundations Restored, a Catholic Perspective on Origins. [ 88 → 106] Explaining the failure of the claimed mechanism for evolution will require us to delve into [ 106 → 112] some details related to the genetic code and certain components of the cell. [ 112 → 116] To help, we will define some key terms as we go along. [ 116 → 120] In addition, all of the essential concepts needed to explain the failure of mutations [ 120 → 126] as a mechanism of evolution can be demonstrated through an analogy that is intuitive and will [ 126 → 130] be an aid in understanding the more technical discussion to follow. [ 130 → 136] Biologists Pamela Acker and Dr. Kevin Mark will now introduce the analogy and explain [ 136 → 142] its relevance to the subsequent technical discussion. [ 142 → 147] The failure of the claimed neo-Darwinian mechanism for evolution is easy to visualize and explain [ 147 → 151] once we recall that the genetic code contained in the DNA of living organisms is, in a very [ 151 → 156] real sense, an instruction manual for how to assemble and maintain each organism. [ 156 → 160] The instruction manual is made up of specific letters, or nucleotides, that form what is [ 160 → 162] called the genetic code. [ 162 → 166] These letters are arranged into strands of DNA, and two DNA strands are paired to form [ 166 → 172] a double helix, which resembles a spiral staircase. [ 172 → 178] Since the structure of DNA was first described by Watson and Crick in 1953, we have learned [ 178 → 182] a great deal about the complexity of the genetic code, but our knowledge pales in comparison [ 182 → 184] to what we do not yet understand. [ 184 → 188] For our analogy, we only need to know that the genetic code is the instruction manual [ 188 → 190] for how to build a specific organism. [ 190 → 193] We can choose any animal for our analogy, let's just say we're talking about the [ 193 → 197] genetic code or instruction manual for a squirrel. [ 197 → 202] Our analogy consists of imagining that the instruction manual for building a squirrel [ 202 → 209] contains thousands of pages of genetic information, and each paragraph on each page contains useful [ 209 → 214] information related to some aspect of building and maintaining a squirrel. [ 214 → 219] Since our assumption is that all information in the instruction manual is useful, it is [ 219 → 224] readily apparent that anything causing some of the information in the manual to be destroyed [ 224 → 229] over time will necessarily mean that useful information is lost. [ 229 → 234] Due to the relatively small amount of information contained in any paragraph, the elimination [ 234 → 241] of a paragraph or even a page may not result in an immediately noticeable decrease in a [ 241 → 245] squirrel's functionality, but it is clear that there will be a loss of useful information [ 245 → 250] and that this will be detrimental in some respect. [ 250 → 253] Now let's develop our analogy further. [ 253 → 258] Let's suppose that in North America, there was only one instruction manual printed a [ 258 → 263] few centuries ago, and because the manual was so rare, the original purchaser never [ 263 → 266] gave his copy to anyone else. [ 266 → 270] Nevertheless, the owner of the manual wanted his children to have a copy for their own [ 270 → 277] studies, and so he allowed his children to painstakingly copy the manual, page for page, [ 277 → 279] until they at last had their own copy. [ 279 → 285] In turn, their children had to repeat the same process, painstakingly copying not the [ 285 → 288] original but the copy that their parents had made. [ 288 → 292] This process continued generation after generation. [ 292 → 298] Of course, as this process continues, it is inevitable that there would be copying errors [ 298 → 303] introduced, and other mistakes could arise if, for example, some pages were torn, became [ 303 → 307] too worn to read, or were ruined by a water spill. [ 307 → 312] In each instance, information would be lost and our instruction manual would no longer [ 312 → 319] convey all of the original details about how to build a squirrel from genetic material. [ 319 → 323] We will call this loss of information a mutation. [ 323 → 327] As mutations accumulate from generation to generation, the instruction manuals would [ 327 → 333] contain an increasing number of errors and the information would be increasingly degraded [ 333 → 336] compared to the original copy. [ 336 → 341] Before we go further, let's give a name to the accumulation of copying errors or mutations [ 341 → 343] over long periods of time. [ 343 → 348] Since we are talking about the degradation of a genetic instruction manual, a good scientific [ 348 → 353] description would be the term entropy, which refers to the tendency of everything in the [ 353 → 358] physical universe to go from a state of order to increasing disorder. [ 358 → 364] Also, since our make-believe analogy involves degraded copies of an instruction manual, [ 364 → 369] as it is passed from family members in one generation to the next, and since all members [ 369 → 377] are genetically related, the phenomena we are talking about can be called genetic entropy. [ 377 → 381] From our example, it is clear that genetic entropy would increase from generation to [ 381 → 388] generation due to the presence and accumulation of mutations or copying errors, and that each [ 388 → 394] new generation would experience further degradation of useful information that used to be present [ 394 → 398] in the genetic code instruction manual of their parents. [ 398 → 400] Now here is the key point. [ 400 → 405] While the information in the instruction manual changes from generation to generation due [ 405 → 410] to the increasing accumulation of mutations, it would be a real stretch to call this process [ 410 → 417] evolution, because all that results from genetic entropy is a more imperfectly designed squirrel, [ 417 → 423] not the emergence of a new animal kind like a fox, or the emergence of a complex and functional [ 423 → 429] new organ such as a feathered wing that allows the squirrel to fly like a bird. [ 429 → 435] A new animal kind or feathered wing would require new information, whole new chapters [ 435 → 440] of information, but mutations do not provide these new chapters, they only degrade the [ 440 → 442] information in the instruction manual. [ 442 → 447] To suggest that such degradation would lead to Darwinian evolution is like suggesting [ 447 → 453] that adding multiple random typos to Macbeth would lead to a new highly acclaimed Shakespeare [ 453 → 455] play. [ 455 → 461] In essence, what we have described is what occurs to the genetic code of all living creatures [ 461 → 463] over time. [ 463 → 470] All genomes degrade over time due to mutations, information is lost, and we can't expect [ 470 → 477] new animal kinds and complex new organs to somehow emerge from a genome that can't [ 477 → 479] even maintain what it has. [ 479 → 484] The process of genetic entropy, so named by Dr. John Sanford of Cornell University in [ 484 → 490] his landmark book, effectively deals a death blow to the notion that mutations and natural [ 490 → 497] selection produced amoeba to man evolution over hundreds of millions of years. [ 497 → 500] Entropy is a measure of disorder. [ 500 → 505] The nature of entropy is that it always increases, that is, everything tends to break down. [ 506 → 510] And so you can see it in your car, you can see it in your house, you can see it in your [ 510 → 513] own body as we age, and everything's breaking down. [ 513 → 522] So this entropy problem, this universal degenerative process, is happening within our genome, within [ 522 → 523] our genes. [ 523 → 529] And so that's a problem because our genome is the programming that makes us alive. [ 529 → 534] And if you corrupt a genome, all our functions start to degrade. [ 534 → 540] And so we experience this on a personal level, and there's no question about this simple [ 540 → 544] fact, is there are about three new mutations every cell division. [ 544 → 548] So every cell in our body gets more mutant every day. [ 548 → 551] Every day we're more mutant than we were yesterday. [ 551 → 555] And that is actually the primary reason for aging and death, is mutation. [ 555 → 561] And it's like rusting out of the car, and it's unstoppable. [ 561 → 567] So personally, we all are undergoing entropic decay. [ 567 → 571] First of all, we lose functionality, and eventually we die. [ 571 → 575] So the same thing happens at the population level. [ 575 → 582] Because when we have children, we pass on our mutations to our children. [ 582 → 588] And so we receive mutations from our ancestors, and then we add our own mutations and pass [ 588 → 589] it on to the kids. [ 590 → 593] Every generation has to be more mutant than the previous one. [ 593 → 599] And the rate, mutation rate, how many mutations are passed on to the next generation, is disturbingly [ 599 → 600] high. [ 600 → 605] So basically, every generation has 100 more mutations than the previous generation. [ 605 → 609] It's about 100 mutations per person per generation. [ 609 → 616] And that's bad news because they're almost universally deleterious mutations. [ 616 → 623] There are rare, exceedingly rare beneficials, but it's so rare that they don't really even [ 623 → 624] make a difference. [ 624 → 627] So this is the problem of genetic entropy. [ 627 → 632] We experience it personally, and all populations should be subject to it. [ 632 → 634] Here's a simple way of saying it. [ 634 → 638] We're not going up, we're not evolving upward, we're going down. [ 638 → 640] It's down, not up. [ 640 → 642] It's exactly the opposite of evolution. [ 642 → 645] And it has profound implications. [ 645 → 648] It means there was a beginning, and there has to be an end. [ 648 → 654] There had to be a time when there were no mutations, if you run the video backwards. [ 654 → 660] And it's clear that at some point, as we accumulate more mutations, all populations must eventually [ 660 → 661] go extinct. [ 661 → 666] So it's radically different from the common understanding that things are getting better [ 666 → 668] and better due to mutation selection. [ 668 → 672] And so this is something I've studied for 18 years. [ 672 → 678] I think, I don't know that anybody has studied this issue in as much depth as I have. [ 678 → 683] So people who want to know more about genetic entropy, they can go to geneticentropy.org [ 683 → 685] and find out more about it. [ 685 → 693] Time and mutations are an enemy to any genome, as they only result in degraded genomes, not [ 693 → 699] the additional information needed for new animal kinds. [ 699 → 701] Let's add a final twist to our analogy. [ 701 → 706] Let's assume that after many generations, we learn that in another part of the world, [ 706 → 711] a second copy of the original instruction manual was printed and purchased long ago, [ 711 → 716] and that the contents of this manuscript were handed down through the same process of copying [ 716 → 718] we've previously described. [ 718 → 723] When the present-day copies handed down from the two original printed versions are compared, [ 723 → 728] it is not surprising that the copies are found to be different in many instances due to random [ 728 → 735] mutations that occurred as each manuscript was passed on generation after generation, [ 735 → 737] but in isolation from each other. [ 737 → 742] In fact, it is possible that the instructions from the two versions may have diverged from [ 742 → 747] one another so much that squirrels constructed from the different manuals may no longer be [ 747 → 751] able to interbreed and produce fertile offspring. [ 751 → 756] In this case, scientists may describe the two offspring as belonging to two different [ 756 → 757] species. [ 757 → 760] But is this really a good example of evolution? [ 760 → 764] The answer is that it is not evolution in the Darwinian sense at all, because the squirrels [ 764 → 767] are not on their way to becoming a non-squirrel. [ 767 → 770] They are only degraded squirrels who can no longer produce fertile offspring. [ 770 → 775] In this way, mutations in genetic entropy can lead to speciation according to the biological [ 775 → 779] definition of species, but they will never produce the new information needed for the [ 779 → 782] emergence of new animal kinds. [ 782 → 786] As new details emerge about the genomes of living organisms, it is becoming increasingly [ 786 → 792] clear that genetic entropy is real and that Darwinian evolution is not genetically possible. [ 792 → 798] Based on our analogy of genetic entropy, viewers may be wondering how evolutionists could argue [ 798 → 803] that mutations can be a viable Darwinian mechanism. [ 803 → 808] The answer is that evolutionists make a number of problematic assumptions and ignore the [ 808 → 816] emerging evidence against mutations as a mechanism, because they have no better naturalistic alternative [ 816 → 821] and special creation is eliminated for philosophical reasons. [ 821 → 824] Much of the remainder of the episode will explain the lack of evidence supporting these [ 824 → 826] problematic assumptions. [ 826 → 832] First, however, let's illustrate these assumptions by returning once more to our analogy. [ 832 → 836] Our analogy in the concept of genetic entropy could potentially break down if our assumption [ 836 → 842] that all pages of the instruction manual contain useful information was not true, and instead [ 842 → 847] most pages provided no useful information about how to construct a squirrel. [ 847 → 852] So for example, while our instruction manual on how to build a squirrel was said to contain [ 852 → 858] thousands of pages, if only 2% of the pages actually contained the needed information [ 858 → 864] to build a squirrel, then copying errors or mutations could occur in the remaining 98% [ 864 → 868] of the manual without having a negative effect on the squirrel. [ 868 → 875] In essence, one could view the 98% of non-functional genetic information as junk information that [ 875 → 876] is not used. [ 876 → 881] The existence of large portions of junk in the genetic code instruction manual may allow [ 881 → 887] mutations to accumulate without having a degrading or detrimental impact. [ 887 → 893] In fact, over eons of time, there could even be random beneficial mutations that arise [ 893 → 898] and somehow become functional such that virtually unlimited new characteristics could arise [ 898 → 904] to produce new squirrel variations and eventually non-squirrel animal kinds. [ 904 → 908] This may sound far-fetched, but in essence, is the view professed by evolutionists. [ 908 → 914] But is this view based on fact, or does it amount to a kind of faith? [ 914 → 919] The remainder of this episode explains that of the two views, the emerging evidence since [ 919 → 925] 2007 clearly supports the concept of genetic entropy with the implication that mutations [ 925 → 931] fail as a mechanism of evolution and Darwinism is thus not true. [ 931 → 937] Specifically, following some historical background, we will discuss, firstly, while evolutionists [ 937 → 944] claimed until recently that 98% of the genome is junk DNA, this is now known to be false. [ 944 → 948] Virtually all of the genome is now believed to be functional. [ 948 → 953] The implication of this functionality is that mutations destroy useful information. [ 953 → 957] Secondly, there are no truly neutral mutations. [ 957 → 962] All mutations are somewhat harmful since they destroy information to some degree. [ 962 → 968] Third, even the rare mutation that is claimed to be beneficial comes at a fitness cost. [ 968 → 975] Fourth, even if a rare mutation were beneficial without incurring any fitness cost, it would [ 975 → 980] not lead to evolution because it would take so long for beneficial mutations to accumulate [ 980 → 982] and have an impact. [ 982 → 987] Meanwhile, the cumulative impact of harmful mutations would destroy much more information [ 987 → 990] than beneficial mutations could ever replace. [ 990 → 996] And finally, fifth, all examples of beneficial mutations, such as bacterial resistance to [ 996 → 1002] antibiotics and resistance to HIV, fail to support the claim that mutations are a viable [1002 → 1005] mechanism of evolution. [1005 → 1011] We will now transition into a more technical discussion of evolution's supposed mechanism, [1011 → 1014] starting with a historical overview of its development. [1014 → 1031] Evolution of Species [1031 → 1037] Starting with Charles Darwin, evolutionists speculated as to what caused variations that [1037 → 1042] supposedly worked with natural selection to drive evolutionary processes. [1042 → 1047] In The Origin of Species, Darwin claimed that he saw no limit to the processes that [1047 → 1053] produce variation among parents and offspring such that, given enough time, the processes [1053 → 1056] could account for all animal species. [1056 → 1061] To support this claim, Darwin relied upon his authority as a scientist and also spent [1061 → 1066] much time discussing the selective breeding of pigeons and the differing characteristics [1066 → 1070] that resulted from these artificial breeding experiments. [1070 → 1076] And yet, even Darwin's staunchest supporters admitted that it was inappropriate to extrapolate [1076 → 1082] such observations because experimental evidence clearly suggested that there are limits to [1082 → 1086] variation that could occur in any species. [1086 → 1092] Additionally, Darwin's claim did not adequately consider the tendency of random breeding to [1092 → 1097] produce offspring that reverted back to the original type. [1097 → 1100] Recall, for example, that Lyell noted, [1100 → 1105] Every naturalist admits that there is a general tendency in animals and plants to vary, but [1105 → 1110] it is usually taken for granted that there are certain limits beyond which each species [1110 → 1115] cannot pass under any circumstances or in any number of generations. [1115 → 1121] This comment reflected the observation that artificial and natural selection could, at [1121 → 1126] the most, produce what is called adaptive radiation, a form of variations on the same [1126 → 1130] body plan to fill different ecological niches. [1130 → 1136] But this limit poses a problem for the creation of new body plans and forms needed for molecules [1136 → 1138] to man evolution. [1138 → 1143] It is also interesting to note that Darwin had no idea about what specific and internal [1143 → 1149] process actually drove the variation he speculated led to new species. [1149 → 1154] Recall that the day after The Origin of Species was published, he wrote to Huxley, [1154 → 1159] You have most cleverly hit on one point which has greatly troubled me. [1159 → 1164] If, as I must think, external conditions produce little direct effect, what the devil determines [1164 → 1166] each particular variation? [1166 → 1173] Clearly, a fuller hypothesis about the supposed mechanism of evolution was needed, but it [1173 → 1176] would not be forthcoming until the next century. [1176 → 1183] In the early 1900s, several scientists independently rediscovered the important insights of the [1183 → 1189] Augustinian monk, Gregor Mendel, whose experiments with pea plants fortuitously provided a means [1189 → 1192] of understanding heredity. [1192 → 1197] Mendel observed that there did appear to be some physical quantity that was passed from [1197 → 1203] parent to offspring and determined the traits expressed in the next generation. [1203 → 1209] In 1905, Danish botanist Wilhelm Johansen introduced the term gene to describe this [1209 → 1211] heritable material. [1211 → 1217] Shortly thereafter, Dutch botanist Hugo de Vries speculated that a change or mutation [1217 → 1221] in a gene could lead to the development of a new species. [1221 → 1226] Here at long last was a possibility for the naturalistic mechanism that evolutionary biology [1226 → 1228] had been lacking. [1228 → 1234] Thomas Hunt Morgan, a biologist at Columbia University, carried out the first notable [1234 → 1238] experiments studying mutations within a population. [1238 → 1244] But his discovery of a mutant white-eyed fruit fly in 1909 cast some doubt on de Vries' [1244 → 1250] hypothesis that a single change in a gene could lead to the development of a new species. [1250 → 1253] The paradigm needed to be refined. [1253 → 1255] Ronald Fisher and J.B.S. [1255 → 1261] Haldane soon shed new light on the issue through their work in population genetics that involved [1261 → 1268] creating mathematical models to track variations within a population and the favorability of [1268 → 1271] these variations under certain environmental pressures. [1271 → 1277] But it was not until Theodosius Dobzhansky, a scientist who had worked in Morgan's so-called [1277 → 1283] fly room, published Genetics and the Origin of Species in 1937 that a seemingly plausible [1283 → 1288] role for mutations in the development of new species was fleshed out. [1288 → 1293] Dobzhansky's work began what eventually came to be known as the modern synthesis, [1293 → 1301] the fusion of Darwinian evolution theory with molecular biology and Mendelian genetics. [1301 → 1305] Dobzhansky hypothesized that a large number of mutations are neutral. [1305 → 1310] They confer neither harm nor benefit on the individuals who carry them. [1310 → 1317] These neutral mutations, accumulating in populations over time, create new alleles, or alternative [1317 → 1322] versions of a gene, that give rise to new variations within the population. [1322 → 1330] These variations could lead to a speciation if reproductive isolation occurred in a population. [1330 → 1336] Reproductive isolation could include novel cording behavior or geographical separation. [1336 → 1342] Dobzhansky hypothesized that over long periods of time, as neutral mutations accumulated, [1342 → 1347] and assuming there was no gene flow or breeding between the two isolated populations, the [1347 → 1353] two groups would lose the ability to interbreed entirely and become different species. [1353 → 1359] While Dobzhansky's work represented an advance in the formulation of a mechanism for evolution, [1359 → 1363] specialists understood that more was needed to explain microbe-to-man evolution. [1363 → 1368] The mutations that he discussed were primarily what we now call point mutations, or changes [1368 → 1370] in a single base pair in the DNA. [1370 → 1374] This kind of change can create alternative versions of a gene, but is not sufficient [1374 → 1376] to increase genome size. [1376 → 1380] There must be an increase in genome size if the original common ancestor of all living [1380 → 1385] things resembled a bacterium, as is widely held by evolutionary biologists. [1385 → 1390] Using our analogy, there must be a way to introduce new, information-containing chapters [1390 → 1395] into the instruction manual, not just a way to change an already existing sentence. [1395 → 1402] By the late 1960s and early 1970s, evolutionary biologists seemed to be making progress in [1402 → 1408] understanding how genomes could be increased and new genetic material could be introduced [1408 → 1412] without harming functionality and the fitness of an organism. [1412 → 1417] Much of the progress centered around the belief that large segments of the genetic code were [1417 → 1418] non-functional. [1418 → 1424] As evolutionary biologists studied the supposedly non-functional portion of the genomes, it [1424 → 1431] was observed that many regions appeared to be altered copies of other functional regions. [1431 → 1436] Biologists interpreted this to mean that genomes can be increased in size through various [1436 → 1442] means of duplication, with the result that organisms can possess more functional copies [1442 → 1445] of particular genes than are necessary. [1445 → 1450] These extra copies were then assumed to be free from selective pressure because they [1450 → 1455] were thought to be non-functional, and mutations could theoretically accumulate without affecting [1455 → 1459] the function of the organism. [1459 → 1464] Mutations or stretches of DNA that have nearly identical sequences to functional genes but [1464 → 1470] are not translated into protein are one of the most often cited evidences for this concept [1470 → 1476] involving duplication and the subsequent accumulation of mutations. [1476 → 1482] Additional information on pseudogenes will be discussed later in this episode. [1483 → 1489] Eventually, according to the evolutionary narrative, the accumulated mutations in pseudogenes [1489 → 1493] or other duplicated regions could somehow become functional. [1493 → 1498] The now functional duplications were said to give the population the plasticity required [1498 → 1504] for evolution to occur without the organism having to sacrifice its original advantageous [1504 → 1505] traits. [1505 → 1509] Through this process, it was claimed that the mechanism of evolution had finally been [1509 → 1512] worked out. [1512 → 1517] To summarize, for mutations to be a sufficient mechanism for naturalistic evolution, a large [1517 → 1521] part of the genome must be non-functional, allowing it to mutate without causing harm [1521 → 1522] to the organism. [1522 → 1526] Most mutations must be effectively neutral, causing neither a selective advantage for [1526 → 1529] the organism nor harm to the organism. [1529 → 1534] Some mutations or combinations of mutations must be beneficial, or in some way enable [1534 → 1539] the organism to survive and reproduce better than other members of its species. [1539 → 1543] These beneficial mutations must be passed down to the offspring more frequently than [1543 → 1548] neutral or harmful mutations that would occur in the same genetic space, so that they accumulate [1548 → 1551] in the population over great periods of time. [1551 → 1555] This accumulation of beneficial mutations would then give rise to new species and new [1555 → 1557] kinds of organisms. [1557 → 1563] Writing with confidence that the mechanism of evolution was confirmed through such evidence, [1563 → 1565] Richard Dawkins stated in 2004, [1566 → 1570] Genomes are littered with non-functional pseudogenes, faulty duplicates of functional genes that [1570 → 1574] do nothing, while their functional cousins get on with their business in a different [1574 → 1576] part of the genome. [1576 → 1580] And there's lots more DNA that doesn't even deserve the name pseudogene. [1580 → 1585] It too is derived by duplication, but not duplication of functional genes. [1585 → 1592] It consists of multiple copies of junk, tandem repeats, and other nonsense which may be useful [1592 → 1597] for forensic detectives, but which doesn't seem to be used in the body itself. [1597 → 1602] Once again, creationists might spend some earnest time speculating on why the creator [1602 → 1611] should bother to litter genomes with untranslated pseudogenes and junk tandem repeat DNA. [1611 → 1615] We will now explain why, within only a few years after Dawkins confidently wrote these [1615 → 1621] words, the entire argument for mutations as a mechanism was demolished, and Dawkins' [1621 → 1627] statement reveals a rush to judgment based on scientific ignorance and philosophical bias. [1627 → 1652] As early as the 1970s, scientists were aware that the majority of the human genome was [1652 → 1655] not translated into protein. [1655 → 1658] Richard Dawkins wrote in 1976, [1685 → 1698] As discussed earlier, this non-coding DNA quickly came to be known as junk DNA. [1698 → 1703] But this misnomer was due to an oversight on the part of the biologists, who initially [1703 → 1708] thought it was solely the presence of the protein products created from the genetic [1708 → 1712] information that determined the complexity of the organism. [1712 → 1717] In reality, the presence or absence of protein products is a tightly regulated, finely tuned [1717 → 1721] operation of turning genes on and off. [1721 → 1727] That is, of controlling when the genes are transcribed into RNA and how quickly the RNA [1727 → 1730] is translated into protein in specific cell types. [1730 → 1735] In order for an organism to be multicellular, it must not only possess the genetic code [1735 → 1740] for all the cell types in each cell, but it must have a way to turn the appropriate genes [1740 → 1746] off and on in each specific type of cell so that the eye cell produces proteins and [1746 → 1751] structures appropriate to the eye, and the liver cell produces proteins and structures [1751 → 1754] appropriate to the liver, and so on. [1754 → 1759] The instructions for all of this finely tuned gene regulation appear to lie in the tremendous [1759 → 1764] quantities of non-coding DNA present in the genome. [1764 → 1770] This means that so-called junk DNA is extremely important, an idea that has been confirmed [1770 → 1773] by recent genetic studies. [1773 → 1780] The Encyclopedia of DNA Elements, or the ENCODE project, was begun as a follow-on to the Human [1780 → 1784] Genome Project in 2003 at Stanford University. [1784 → 1790] The mission of ENCODE is to identify all functional elements in the human genome sequence. [1790 → 1796] The project is an open consortium and releases data rapidly and publicly so that it is available [1796 → 1798] to researchers. [1798 → 1804] After a successful pilot study, ENCODE launched a full-scale investigation of the human genome [1804 → 1805] in 2007. [1805 → 1811] The results have been surprising to evolutionists and are completely incompatible with the idea [1811 → 1817] of large amounts of the genome consisting of useless stretches of DNA. [1817 → 1822] According to a paper published in the journal Nature, ENCODE had already found some level [1822 → 1827] of functionality for at least 80% of the human genome by 2012. [1827 → 1833] Their criteria for functionality included, but was not limited to, being associated with [1833 → 1837] transcription of RNA or a chromatin event. [1837 → 1842] RNA, once thought to be limited to its role as a messenger that delivers instructions [1842 → 1848] from the DNA to ribosomes to facilitate protein production, is now known to have a myriad [1848 → 1852] of complex biochemical roles in the cell. [1852 → 1857] The fact that massive amounts of the genome are transcribed into RNA suggests that this [1857 → 1860] RNA has an identifiable function. [1860 → 1864] It would be a tremendous waste of energy and resources and surely detrimental, from an [1864 → 1869] evolutionary standpoint, for the cell to be making biochemical copies of vast amounts [1869 → 1871] of junk. [1871 → 1876] Also, the role of DNA in chromatin-associated events suggests that these stretches of the [1876 → 1882] genome are necessary for 3D and 4D characteristics of DNA. [1882 → 1887] The speed at which genes are transcribed is determined in large part by the way that DNA [1887 → 1893] interacts with its associated proteins, and the speed of transcription significantly impacts [1893 → 1896] the role the genes play in the cell. [1896 → 1902] ENCODE also identified a large number of enhancer-like and promoter-like regions, as well as regions [1902 → 1908] in the genome that appear to be under selective pressure, that is, to be specifically preserved [1908 → 1914] from mutations, likely because change in those regions would be so detrimental to the organism [1914 → 1917] that it would significantly impact its survival. [1917 → 1923] But it is not only ENCODE that is doing away with the idea of junk DNA. [1923 → 1929] Researchers investigating introns, the non-expressed regions of DNA sequence in between the expressed [1929 → 1934] regions, or exons, in a gene, have also been adding to our understanding of the complex [1934 → 1937] functionality of the genome. [1937 → 1941] Just prior to my time in the Corsi lab at the Catholic University of America, the graduate [1941 → 1946] researchers had identified a sequence in our model organism, C. elegans, that was highly [1946 → 1950] conserved, meaning it was present in almost identical form across a number of species [1950 → 1956] of nematodes, the tiny roundworms that belong in the same taxonomic family as C. elegans. [1956 → 1959] The lab members began to look for a function for this sequence, and discovered through [1959 → 1964] mutagenesis studies that it performed an important role in the development of the nematode's [1964 → 1965] muscles. [1965 → 1970] Further studies confirmed that this piece of supposedly useless intronic DNA was actually [1970 → 1973] an important binding site for a transcription factor. [1973 → 1978] Without it, no binding occurred, no protein was produced, and certain muscles just didn't [1978 → 1978] get built. [1986 → 1997] In addition to containing binding sequences for transcription factors, the proteins necessary [1997 → 2003] in gene regulation to turn expression of the gene on, introns within the genes have also [2003 → 2008] been identified as functioning in alternative splicing of genes. [2008 → 2012] Alternative splicing is an example of the highly ordered information present in the [2012 → 2016] genome and the extreme efficiency of the code. [2016 → 2022] In this process, a single piece of RNA created as a copy of a gene sequence can be cut and [2022 → 2026] pasted by cellular machinery in multiple ways. [2026 → 2031] Each one of these ways results in a different protein product, making alternative splicing [2031 → 2036] a highly efficient way to code for traits in the organism. [2036 → 2040] Introns have also been shown to act as enhancers for genes that are quite distant from the [2040 → 2042] intron itself. [2042 → 2047] Changing the length of the intron itself apart from its sequence may play an important [2047 → 2049] role in gene expression. [2049 → 2055] Longer introns would result in slower transcription and slower production of a protein product, [2055 → 2059] while shorter introns would result in quicker production. [2059 → 2064] This is likely to be yet one more way that cells keep the fine-tuned process of gene [2064 → 2068] regulation in check. [2068 → 2073] Even pseudogenes, which have long been put forward by evolutionary biologists as the [2073 → 2078] prime example of evidence for their theory about genome duplications and the accumulation [2078 → 2082] of neutral mutations, have recently been shown to have a function. [2082 → 2088] These genes, once thought to be evolutionary leftovers from duplication events, have been [2088 → 2091] shown to be transcribed into RNA. [2091 → 2096] The transcription alone would suggest that the sequences are functional, but this functionality [2096 → 2102] has been further confirmed by studies that support the idea that these sequences are [2102 → 2104] involved in RNA interference. [2104 → 2112] RNA interference, or RNAi, is a recently discovered phenomenon in which non-gene RNA sequences [2112 → 2119] bind to RNA transcribed from genes and interfere with the production of proteins from the genes, [2119 → 2125] effectively shutting off a gene that is no longer required at that time in a cell. [2125 → 2130] This function is sequence-dependent, meaning that the particular sequence of nucleotides [2130 → 2136] is crucial to the interference effect, and suggesting that the sequence of the pseudogene [2136 → 2142] is not so free from selective pressure as initially thought by evolutionary biologists. [2142 → 2147] It also explains why the pseudogene resembles a gene in sequence, but does not function [2147 → 2148] as a gene. [2148 → 2153] Several other pseudogenes have been found to code for RNA that is necessary for the [2153 → 2159] expression of the related gene, suggesting that some pseudogenes have an alternate function [2159 → 2162] in gene expression. [2162 → 2168] The scientists at ENCODE concurred with these studies in their paper published in Nature, [2168 → 2173] where it was reported that a large number of non-coding variants of genes were located [2173 → 2179] within regions that the ENCODE project had identified as functional. [2179 → 2184] On the whole, these results suggest that rather than simply being accidental duplications [2184 → 2190] that have been changed through mutation, pseudogenes are necessary and highly specific sequences [2190 → 2194] required for the expression of functional genes. [2194 → 2199] The pseudogene's similarity to its related gene should then be attributed to its function, [2199 → 2205] not to a purported evolutionary history. [2205 → 2211] This emerging data, taken together, lead to the logical conclusion that DNA, rather [2211 → 2216] than including large portions of junk that are free to mutate at the rate required for [2216 → 2222] molecules to man evolution, is largely or completely functional, and leaves little to [2222 → 2228] no room for the accumulation of mutations without harmful or deleterious impacts. [2228 → 2234] Dr. John Sanford, inventor of the gene gun and university professor at Cornell University [2234 → 2240] for over 30 years, summarizes the findings of the ENCODE project as follows in his book [2240 → 2242] Genetic Entropy. [2242 → 2249] ENCODE showed that the human genome is vastly more complex than genome scientists had expected [2249 → 2254] and that essentially all of the genome is transcribed, most of it in both directions. [2254 → 2260] They concluded that most nucleotides are not only functional, but are polyfunctional, having [2260 → 2261] multiple roles. [2261 → 2268] This means that the genome's functionality exceeds 100% most of both strands of the DNA [2268 → 2271] are functional. [2271 → 2275] If all of the genome is functional, I invite viewers to think back to our analogy of the [2275 → 2279] instruction manual for squirrels and to consider the implications. [2279 → 2284] The implication of having a fully functional genome is that all mutations must be harmful [2284 → 2286] or deleterious. [2286 → 2290] As Dr. Sanford states in light of the demise of junk DNA, [2290 → 2296] no mutations should be considered perfectly neutral and almost all mutations must be considered [2296 → 2298] deleterious. [2298 → 2303] And so, the question for evolutionists is, how can mutations build up a genome and produce [2303 → 2309] a man from an amoeba if all mutations destroy information and are harmful, even if one in [2309 → 2314] a million mutations appear to be beneficial, as will be discussed later? [2314 → 2316] Mutations tear down, they do not build up. [2316 → 2320] To underscore the truth that mutations destroy information and are therefore not neutral, [2320 → 2324] we will now introduce the next myth about mutations. [2324 → 2351] When the modern synthesis of Darwinian evolution and Mendelian genetics was initially developed, [2351 → 2356] scientists assumed a very low mutation rate, perhaps only on the order of one mutation [2356 → 2358] per generation. [2358 → 2364] By the late 1960s, it had become clear that the rate of mutations in organisms was significantly [2364 → 2368] higher than had been estimated in the 1930s. [2368 → 2373] Scientists now know that mutation rates vary widely among different species, with human [2373 → 2379] beings passing along as many as 50 to 160 mutations per generation. [2379 → 2385] This amount of change in each generation did not mesh well with evolutionary timescales, [2385 → 2390] especially as some mutations were clearly harmful or deleterious. [2390 → 2396] To avoid error catastrophe, or the accumulation of so many harmful mutations in a species [2396 → 2402] that extinction was inevitable, evolutionists had to posit that most mutations are neutral, [2402 → 2405] having little to no impact on the genome. [2405 → 2411] Dr. Sanford succinctly describes the biological constraints that require this designation [2411 → 2413] of neutrality. [2413 → 2418] The overwhelming majority of mutations should be nearly neutral. [2418 → 2424] All population geneticists would agree it can be seen by the total number of nucleotides. [2424 → 2430] On average, each nucleotide position can only contain one three-billionth of the total information [2430 → 2431] in the human genome. [2431 → 2437] Experimentally, we can show that most nucleotide positions have very subtle effects on any [2437 → 2443] given cell function, and only a few mutations are real killers of gene function. [2443 → 2448] Lastly, the nearly neutral impact of most nucleotides can be seen from the very subtle [2448 → 2455] role single nucleotides play in genome-wide patterns, codon preferences, nucleosome binding [2455 → 2457] sites, isochores, etc. [2457 → 2463] With as infinitesimal as these effects are, they are not zero. [2463 → 2468] This last point by Dr. Sanford deserves further consideration. [2468 → 2474] Motu Kimura, a population geneticist famous for developing the neutral theory of evolution, [2474 → 2479] published a paper describing the statistical distribution of mutations in the Proceedings [2479 → 2481] of the National Academy of Sciences. [2481 → 2486] A graphical representation of his calculations showed the relationship between the relative [2486 → 2492] deleteriousness, or damage done to the genome of the organism by the mutation, and the frequency [2492 → 2496] of that type of mutation occurring in the population. [2496 → 2502] As Kimura made visible on his graph, the frequency of mutations in the population decreases nearly [2502 → 2506] exponentially as their deleteriousness increases. [2506 → 2512] Thus, the number of highly deleterious mutations is very small compared to the number of nearly [2512 → 2518] neutral mutations, with the result that most mutations are characterized as neutral. [2518 → 2523] And while Kimura's representation posits that the large majority of mutations approach [2523 → 2530] zero effect, he shows that no mutations ever reach the point of having zero effect on the [2530 → 2531] genome. [2531 → 2536] This distinction between no effect and very little effect is an important one to understanding [2536 → 2544] a major obstacle to the mutations-as-mechanism explanation of evolution theory. [2544 → 2548] Evolutionary biologists often dismiss the impact of nearly neutral mutations, which [2548 → 2555] are really slightly harmful mutations, by simply relabeling them as neutral. [2555 → 2560] It is easy to see why this is a misnomer for mutations that occur within genes, as changes [2560 → 2566] in the DNA sequence of a gene often result in changes in the amino acid sequence of protein [2566 → 2569] coded for by the gene. [2569 → 2572] And as George Wald, a Nobel laureate, puts it, [2572 → 2577] "...one is hard put to find a single instance in which the change in one amino acid in a [2577 → 2582] protein does not change markedly its properties." [2582 → 2587] But it is a misnomer even for those nucleotides that are not part of a gene, as many of them [2587 → 2591] are involved in the regulation of genes as we have seen. [2591 → 2596] And as Dr. Sanford points out, even if a nucleotide were to carry absolutely no information, to [2596 → 2603] have, in effect, zero impact on any gene or any regulation of any gene, it would then, [2603 → 2609] by its very presence, have a deleterious impact on the organism, as it would require the expenditure [2609 → 2614] of energy and raw materials that could have been used elsewhere in a way that actually [2614 → 2618] benefited or enhanced the functioning of the organism. [2618 → 2623] These considerations support the conclusion that there are likely no truly neutral nucleotide [2623 → 2630] sites in the genome, with the logical extension that any mutation that occurs will negatively [2630 → 2634] affect gene expression in some way, however slight. [2634 → 2639] And this makes perfect sense in the context of a fully functional genome. [2639 → 2645] This distinction between truly neutral and nearly neutral mutations, while important, [2645 → 2650] is not the most problematic piece of evidence that nearly neutral mutations provide for [2650 → 2653] the mutations-as-mechanism hypothesis. [2653 → 2658] In Kimura's distribution of mutations, the author notes that the large majority of nearly [2658 → 2664] neutral mutations fall inside what could be called a no-selection zone. [2664 → 2667] These are the mutations that lie in the shaded region of the graph. [2667 → 2673] This means that when these mutations occur in an organism, they result in a deleterious [2673 → 2679] effect so slight that it is not acted upon by natural selection, and the mutations cannot [2679 → 2683] be removed from the population through evolutionary processes. [2683 → 2688] Kimura's premise of a no-selection zone can be seen to be particularly plausible when [2688 → 2694] we remember that natural selection does not act directly on the genotype or genetic sequence, [2694 → 2699] but only on the phenotype or physical characteristics of an organism. [2699 → 2705] A change in a gene sequence may confer a measurable loss of function in a particular protein, [2705 → 2711] but when this damaged protein is factored into the sum of physiological processes and [2711 → 2716] anatomical structures that belong to an individual organism, the change might on the whole be [2716 → 2722] so slight that the individual would not experience a measurable decrease in its fitness or in [2722 → 2724] its reproductive success. [2724 → 2730] Thus, the individual would pass down its defective gene to its offspring, which would pass it [2730 → 2735] down to their offspring, and on through succeeding generations. [2735 → 2740] When this is the case, these slightly deleterious mutations can become prominent or even fixed [2740 → 2747] in a population and contribute to an overall decline in fitness of the group of organisms. [2747 → 2752] But the problem does not stop with slightly deleterious mutations that occur in just one [2752 → 2753] generation. [2753 → 2759] Each generation adds its own nearly neutral or slightly deleterious mutations, and these [2759 → 2762] accumulate over time in the genome. [2762 → 2766] This means that as the genome is waiting for the rare beneficial mutations to accumulate [2766 → 2772] and drive the evolutionary process, the rest of the genome is rapidly degrading in relative [2772 → 2773] terms. [2773 → 2779] Over time, the genome will accumulate so many harmful mutations that it will eventually [2779 → 2785] break down due to the cumulative effect of harmful mutations well before Darwinian evolution [2785 → 2786] can occur. [2786 → 2792] As Dr. Sanford explains, just as rust slowly building up on a vehicle will one day cause [2792 → 2798] the vehicle body to fall apart, so will the slow accumulation of mutations lead to an [2798 → 2801] eventual failure of the organism's body. [2801 → 2807] Time is the enemy of evolution and the genome, not its friend, and degeneration of the genome [2807 → 2809] over time is inevitable. [2809 → 2812] Dr. Sanford concludes, [2812 → 2817] If the genome is actually degenerating, it is bad news for the long-term future of the [2817 → 2818] human race. [2818 → 2821] It is also bad for evolutionary theory. [2821 → 2826] If mutation selection cannot preserve the information already within the genome, it [2826 → 2830] is difficult to imagine how it could have created all that information in the first [2830 → 2831] place. [2831 → 2837] We cannot rationally speak of genome building when there is a net loss of information every [2837 → 2860] generation. [2860 → 2865] Anyone who has taken an introductory biology class will have been exposed to the statement [2865 → 2869] that it is the rare beneficial mutation that drives evolution. [2869 → 2874] Along with such statements, there are usually a number of alleged examples of beneficial [2874 → 2876] mutations provided. [2876 → 2881] These examples may look plausible on the surface, but a closer examination is required to see [2881 → 2887] if they truly confer an evolutionary advantage on the organisms they affect without compromising [2887 → 2893] the overall genetic information available to the organism. [2893 → 2898] One commonly cited example of a beneficial mutation is the development of antibiotic [2898 → 2900] resistance in bacteria. [2900 → 2906] The story of bacterial resistance to antibiotics begins with a single bacterium experiencing [2906 → 2911] a mutation that makes it immune to the action of the antibiotic. [2911 → 2917] When the population is exposed to the antibiotic, the non-resistant bacteria die off, leaving [2917 → 2924] behind only the resistant bacteria, which reproduce until there is a new bacterial population. [2924 → 2929] Since the new population is descended from the resistant bacterium, the entire population [2929 → 2934] is now resistant to the antibiotic. [2934 → 2939] This is seen in real-time in hospitals, where the spread of methicillin-resistant Staphylococcus [2939 → 2945] aureus, or MRSA, presents a tremendous health concern. [2945 → 2950] But the question remains, does this provide an example of a truly beneficial mutation, [2950 → 2956] and if so, is it an example of evolution in action? [2956 → 2961] Before discussing the details of antibiotic-resistant mutations, it is helpful to understand what [2961 → 2967] Dr. Sanford has to say about purported beneficial mutations in bacteria in general. [2967 → 2972] There are a few isolated cases where it is claimed that certain laboratory experiments [2972 → 2977] demonstrate remarkably high rates of beneficial mutation. [2977 → 2982] The key to understanding these claims of superabundant, high-impact beneficial mutations is that a [2982 → 2989] large part, up to 50%, of any microbial genome consists of just-in-case genes which need [2989 → 2992] to be precisely regulated. [2992 → 2997] These genes are crucial in the real world, conferring tolerance to a host of specific [2997 → 2999] stress conditions. [2999 → 3005] But in an artificial and changing laboratory environment, such genes are just dead weight. [3005 → 3011] Breaking or deleting such non-essential genes will very often conserve energy and allow [3011 → 3014] faster growth in the artificial environment. [3014 → 3019] Under these artificial conditions, many diverse beneficial mutations can arise that involve [3019 → 3025] the loss of information, loss of function, a genetic degeneration, like stripping down [3025 → 3027] a car for a race. [3027 → 3031] Describing such mutations as beneficial is really a misnomer. [3031 → 3035] They actually represent adaptive degeneration. [3035 → 3041] This is best seen in the famous long-term Escherichia coli experiment by Lenski and [3041 → 3042] colleagues. [3042 → 3047] E. coli did indeed adapt to a certain artificial environment and on a specific medium could [3047 → 3049] grow slightly faster. [3049 → 3055] But when the enabling beneficial mutations were analyzed, they all involved loss of function [3055 → 3059] events, either broken genes or broken promoters. [3059 → 3062] Genome size consistently shrank. [3062 → 3068] This is clearly not how genomes are built and speaks directly to the problem of genetic [3068 → 3069] degeneration. [3069 → 3077] If this analysis by Dr. Sanford is correct, we would expect to see broken genes in the [3077 → 3080] antibiotic-resistant strains of bacteria. [3080 → 3085] Or in other words, we should expect to see loss or diminishment of function in a gene [3085 → 3088] that the bacterium needs to survive. [3088 → 3094] The antibiotic resistance should only be an accidental side effect of this loss of function [3094 → 3099] and not the gain of an independent newly acquired function. [3099 → 3104] And this is exactly what we do see in the mutation that leads to methicillin resistance [3104 → 3108] in Staphylococcus aureus or MRSA. [3108 → 3114] MRSA strains express a protein variant of a normal protein involved in cross-linking [3114 → 3117] the bacterial cell wall. [3117 → 3123] In non-resistant bacteria, methicillin binds to this protein and prevents cross-linking, [3123 → 3128] weakening the cell wall and leading to the death of the bacterium. [3128 → 3135] The mutation found in MRSA causes the cross-linking protein to have an altered affinity for methicillin. [3135 → 3140] In other words, the antibiotic binds to the mutated protein less efficiently than it does [3140 → 3142] to the normal protein. [3142 → 3147] This makes therapeutic doses of the antibiotic ineffective. [3147 → 3152] While this benefits the bacterium in the presence of the antibiotic, it actually also weakens [3152 → 3155] the cross-linking in the cell wall. [3155 → 3161] So MRSA has weaker cell walls than non-resistant strains of Staphylococcus aureus because of [3161 → 3166] the inefficient cross-linking by the mutated protein. [3166 → 3171] Because of this weakness, MRSA is readily out-competed by non-resistant Staphylococcus [3171 → 3175] aureus when antibiotics are removed. [3175 → 3182] The mutation, while beneficial in one situation, is highly detrimental in others. [3182 → 3189] MRSA is not alone in demonstrating that antibiotic resistance involves broken genes. [3189 → 3195] Certain species of the Klebsiella genus are resistant to the antibiotic streptomycin. [3195 → 3200] In bacteria that are not resistant, streptomycin passes across the cell membrane and binds [3200 → 3205] to the bacterial ribosomes, the protein-making factories inside the cells. [3205 → 3210] The attachment of the antibiotic to the ribosome prevents protein synthesis, and the lack of [3210 → 3215] proteins results in the death of the bacterium. [3215 → 3220] Resistant bacteria have modifications in the site on the ribosome where streptomycin [3220 → 3227] would normally attach, which keeps the antibiotic from binding and disrupting protein synthesis. [3227 → 3232] While this disrupted binding site results in greater fitness of the individual bacterium [3232 → 3237] under the selective pressure of the antibiotic, the ribosomes of the resistant bacteria were [3237 → 3243] significantly less efficient at protein synthesis than the ribosomes of the bacteria that were [3243 → 3246] not resistant. [3246 → 3250] Experiments showed that the non-resistant bacteria, who could still make proteins properly, [3250 → 3256] quickly out-competed the resistant bacteria when the two populations were mixed together [3256 → 3259] in the absence of the antibiotic. [3259 → 3264] This is yet another example of how it is the loss of function of a crucial component of [3264 → 3270] the bacterium that results in the antibiotic resistance, and this loss of function is ultimately [3270 → 3273] detrimental to the organism. [3273 → 3279] In both of these examples, it can easily be seen that the organisms have gained new functions [3279 → 3283] at the expense of losing something and their already existing functions. [3283 → 3287] One might think of an organism, or even of a single cell, in some ways as a zero-sum [3287 → 3288] game. [3288 → 3293] In order for one function to be improved, another function must be changed, modified, [3293 → 3295] or perhaps destroyed. [3295 → 3298] We have to look at what is going on both at the level of the organism and its interactions [3298 → 3302] with the environment, and the DNA sequence. [3302 → 3306] Just because something looks functional on the outside, like antibiotic resistance, it [3306 → 3310] does not mean that from a genetic and molecular perspective that any new information is being [3310 → 3312] added to the genome. [3312 → 3315] In fact, the reverse is most often true. [3315 → 3320] The mutation is causing an overall loss of specificity at the molecular level, and it's [3320 → 3325] hard to imagine how things getting more and more formless could lead to the kind of molecules [3325 → 3330] demand transitions that evolution requires. [3330 → 3333] But what about organisms other than bacteria? [3333 → 3338] We will examine here a notable example of beneficial mutation in humans and determine [3338 → 3344] whether these benefits derive from the input of new information into the genome, or from [3344 → 3350] a similar loss of specificity to what we observed in the bacterial world. [3350 → 3358] A recent example of purported beneficial mutation in human beings is a mutation in CCR5, a protein [3358 → 3362] normally present on the surface of human immune cells. [3362 → 3367] The gene for the mutant protein is missing 32 base pairs that are present in the normal [3367 → 3368] gene. [3368 → 3375] This mutation causes a frameshift or an alternate reading of the genetic code, introducing an [3375 → 3382] early stop signal and making the mutant protein short by 137 amino acids. [3382 → 3389] The absence of these amino acids makes T-cells resistant to infection by the deadly HIV-1 [3389 → 3396] virus and also has been associated with lower numbers of circulating viruses in individuals [3396 → 3398] that are infected. [3398 → 3404] Because of this resistance, the deletion confers a potentially life-saving benefit to individuals [3404 → 3406] exposed to the virus. [3406 → 3412] Unfortunately, the loss of this part of the protein also makes CCR5 incapable of being [3412 → 3415] properly placed in the cell membrane. [3415 → 3421] When it cannot be positioned in the membrane, it cannot perform its normal role as an important [3421 → 3427] receptor for chemical messengers that are integral to the human immune response. [3427 → 3432] Because of this loss of function, the deletion is associated with serious liver disease and [3432 → 3436] early death in patients with multiple sclerosis. [3436 → 3441] The loss of these 32 base pairs can certainly be considered a loss of function. [3441 → 3447] We see again the same pattern of a supposed benefit being the result of a broken protein [3447 → 3455] that negatively impacts the overall health and well-being of the individual. [3455 → 3459] As Dr. Donald Batten of the University of Sydney explains, [3460 → 3465] Evolutionists are continually holding up examples of evolution via adaptive mutations to try [3465 → 3468] to convince us that it really does work. [3468 → 3475] However, the sorts of examples they provide include loss of Satan cavefish and cave salamanders, [3475 → 3480] loss of functional wings in beetles on a windy island, loss of control of the enzyme action [3480 → 3486] or a defective uptake channel causing antibiotic resistance, and a defective gene in tomcod [3486 → 3492] fish that helps them survive in water polluted with PCBs. [3492 → 3498] This repeated loss cannot lead to the gains necessary to drive molecule-to-main evolution. [3517 → 3525] When Darwin published his Origin of Species, he did a disservice to the scientific community [3525 → 3529] by introducing confusion regarding the concept of animal kinds. [3529 → 3535] Prior to Darwin, naturalists grouped animals into kinds, which roughly corresponded to [3535 → 3539] families in the Linnaean system of classification. [3539 → 3544] For example, lions, tigers, and cheetahs, while today we would consider them separate [3544 → 3549] species, all fall under a common can't kind. [3549 → 3554] Though some mistakenly held to a complete immutability of species, variation within [3554 → 3560] a kind was still seen as part of God's plan for creation and not as evidence of a naturalistic [3560 → 3564] mechanism for the development of animals. [3564 → 3570] By discussing species instead of kinds, Darwin used a clever sleight of hand to distract [3570 → 3574] his readers from the lack of evidence he presented for how novel body forms could be [3574 → 3575] developed. [3575 → 3582] Today, nearly 160 years after the Origin of Species, there are still no empirically verified [3582 → 3589] examples of one kind of organism ever evolving into another kind. [3589 → 3596] Today, scientists use at least 26 different conceptions of the idea of a species. [3596 → 3602] The most common definition is the biological species definition, which emphasizes reproductive [3602 → 3603] isolation. [3603 → 3609] Under this definition, two organisms are considered to be of the same species if they can successfully [3609 → 3612] reproduce fertile offspring. [3612 → 3619] But even this seemingly straightforward definition poses a problem for evolutionary biology. [3619 → 3624] One of the most often cited examples of evolution in action are the Galapagos finches. [3624 → 3630] As discussed in episode 5, within the last 25 years, it has been discovered that interbreeding [3630 → 3635] among most of Darwin's finch species produces fertile offspring. [3635 → 3640] According to the biological definition of species, this would force us to conclude that [3640 → 3644] most of the finches do not constitute separate species. [3644 → 3651] Rather than demonstrating evolution, the finches show limited variation within a species, not [3651 → 3658] the development of a new species, and certainly not the development of a new kind. [3658 → 3664] This limited variation within a species is observed over and over again in the laboratory. [3664 → 3670] Fruit flies, Drosophila melanogaster, have been a favorite organism for mutation studies [3670 → 3674] in the laboratory since Morgan's Fly Room in the early 1900s. [3674 → 3681] Yet despite increasing mutation rates in Drosophila by up to 15,000%, scientists have [3681 → 3686] never observed a change that has resulted in anything other than a fruit fly. [3686 → 3691] And the mutations that are observed are often evolutionary dead ends. [3691 → 3694] One notable example of this is the four-winged fruit fly. [3694 → 3700] The fly sports not only the normal wings on the first thoracic segment, but a second pair [3700 → 3704] of fully developed wings on a second thoracic segment. [3704 → 3709] The fly seemed to be an almost irresistible visual aid for textbook writers at the turn [3709 → 3711] of the 21st century. [3711 → 3715] Looking at it, one might easily imagine that mutation and natural selection could give [3715 → 3718] rise to new body forms. [3718 → 3721] But what is really happening at the genetic level? [3721 → 3727] A series of three artificially crossed mutations caused a normal body structure of the fly, [3727 → 3731] the halter, to develop instead into a wing. [3731 → 3737] The halter, while small, is essential to Drosophila for maintaining balance during flight. [3737 → 3744] So, the mutant fly lost a normal body structure, and this normal structure was replaced, not [3744 → 3749] by a new structure, but by a structure that the fly already had coded in its DNA, which [3749 → 3753] was simply repeated at another position on the fly's body. [3753 → 3758] Also, while the new wings look impressive, they are not attached to any musculature within [3758 → 3762] the body of the fly, and so are not operational. [3762 → 3768] Instead, they are dead weight and impair the mutant's ability to fly and to mate with [3768 → 3769] other flies. [3769 → 3774] Without special preservation within the laboratory, the four-winged fly would very quickly die [3774 → 3779] out and be nothing more than an interesting footnote in mutational studies. [3779 → 3784] It would certainly not constitute evidence for the evolution of a new kind of animal, [3784 → 3790] especially since it had no way of passing on its genes. [3790 → 3795] Even within bacteria, the easiest organism to mutagenize, we see an incredible tendency [3795 → 3801] towards a lack of evolution into anything other than slightly modified bacteria. [3801 → 3807] Despite the over 2.5 million generations that could be cultured in 100 years, biologists [3807 → 3812] have not observed the development of a new kind of organism. [3812 → 3818] Even MRSA, with its antibiotic resistance, is not a new organism, but only a modified [3818 → 3822] version of Staphylococcus aureus. [3822 → 3824] According to Pierre Grasse, [3824 → 3830] For millions or even billions of years, bacteria have not transgressed the structural frame [3830 → 3834] within which they have always fluctuated and still do. [3834 → 3838] This observation leads him to the conclusion that [3838 → 3844] to vary and to evolve are two different things. [3844 → 3849] While evolutionists claim that variation within species can be extrapolated into variation [3849 → 3856] between species and the development of completely novel species or kinds, the evidence, as we [3856 → 3860] have seen, is to the contrary. [3860 → 3867] Despite over 100 years of studies of mutations in bacteria, fruit flies, nematodes, mice, [3867 → 3874] and other model organisms, there has not been a single documented case of an organism giving [3874 → 3880] rise to a new kind of organism, but only to a variation on the theme of the organism [3880 → 3882] being mutagenized. [3882 → 3888] The changes that are observed in the laboratory sometimes appear dramatic, as with the four-winged [3888 → 3894] fruit fly, but they involve loss of function and loss of information, and extrapolating [3894 → 3898] them into evidence for molecules to man evolution is simply unreasonable. [3904 → 3922] In conclusion, evolution requires a tremendous amount of junk DNA for the accumulation of [3922 → 3929] mutations, but as we have seen, the vast majority of the genome has at least a putative function, [3929 → 3934] if not an experimentally verified function, which would be disrupted by mutation. [3934 → 3940] Evolution requires that a large number of mutations are neutral and some are beneficial, [3940 → 3945] but as we have seen, all cases of mutation that have been observed experimentally involve [3945 → 3950] the loss of information in the affected gene and the loss of function in the protein for [3950 → 3952] which the gene codes. [3952 → 3958] These mutations would result in reduced reproductive success if they were visible to natural selection [3958 → 3963] and the accumulation of slight damage to the genome in each successive generation if [3963 → 3965] they are not. [3965 → 3970] Evolution requires that the accumulation of mutations give rise to new kinds of organisms, [3970 → 3976] but as we have seen, though some kinds show tremendous variety and adaptability, one kind [3976 → 3979] has never been shown to give rise to another. [3979 → 3985] And, in fact, animal kinds seem to have a remarkable inherent stability and tendency [3985 → 3990] to revert to the mean under changing selection pressures. [3990 → 3992] As we have seen, evolution fails. [3992 → 3997] It fails to take into account a complete or nearly complete lack of room for error in [3997 → 4004] the genome, to establish any examples of known mutations that do not destroy useful information [4004 → 4009] in the genome, or to directly demonstrate that the accumulation of mutations leads to [4009 → 4012] a new organism. [4012 → 4016] Mutations, as a reasonable mechanism to explain the diversity of life, belong to the realm [4016 → 4023] of mythology rather than science, and scientific study will continue to be impeded as long [4023 → 4028] as the false view of mutations as a viable mechanism for evolution remains unchallenged.