Hambone

Just because religions has always been around, does that make it real? Does that mean the stories are true?

I said things that are facts. Facts attack Creationism. I made generalizations. Quote for me, please, some unquestionable personal attacks.

My point of view got deleted.

Thanks thanks. The second installment is still in development, taking pictures at the moment for added l33tness. Taste the anger

Words are quite powerful eh?

MC Ranger, if you didn't read start to finish, you're not obligated to make a post criticizing my writing style. You didn't read everything. One my posts got flat deleted because our favorite moderator didn't like my view of god as a man.

Mossad, religion does not make everyone a better person. Religion is a loose cannon. It justifies great deeds and wicked ones. Religion causes the biggest atrocities in human history. September 11, to use a recent example.

A man was burned in 1320 for denying the Ressurection. Burned to death. Why was he not the savior of humanity, he died for his views on Christ and god?

woot. Disclaimer: If you are offended by the use of a word beginning with F that society has deemed unfit for casual usage, please do not click. It is 3.5mb. http://www.th3fall3n.com/HamFlash.htm edit The first time you watch the timing might be slightly off. Watch it twice.

Is a wicka different from a druid?

The following is merely a theory of mine. I think there is only one true emotion. Hate. I won't explain this here, because that was not the question. I was taught Christianity, and I believed it. After awhile, science came into my life. It taught me real truth, stuff that I can prove, stuff that is real. Church lied to me. Betrayal spawns Hate. Did you really want to know that?

Never heard of wicca. Explain?

I thank you for your kind words then. In return I promise to reread Genesis.

Evolution is based on facts, not faith. You are fundamentally wrong. Monkey also didn't evolve straight to man. I don't think you read everything I posted.

That's enough for now. Upon request I will post more.

The Genome of Methanococcus jannaschii So far, our focus in this activity has been to use sequence comparisons as a way to estimate evolutionary relatedness. We've seen that, by using 16S rRNA gene sequences, we could clearly identify Archaea and Bacteria as two separate groups of organisms. We've also seen, in Part I of the activity, that Archaea and Bacteria differ greatly in their physiology. What we have not yet seen, however, has been evidence that the entire genomes of Archaea (not just the ribosomal RNA genes) are very different from those of the Bacteria. Until 1997, no archaeal DNA had been completely sequenced. Methanococcus jannaschii was isolated in 1982 from the ocean floor at a depth of 2600 meters (8500 feet), at the base of a hydrothermal vent. The organism is named after Holgar Jannasch, a microbiologist from the Woods Hole Oceanographic Institute, who pioneered the exploration of hydrothermal vents as microbiological communities, using the deep sea submersible vessel Alvin. Such vents occur in regions of sea floor spreading, where hot magma underlying the sea floor comes in contact with seawater seeping into the cracked rock. The water becomes heated and takes up chemical compounds, such as hydrogen sulfide and carbon dioxide, which can stimulate microbial growth. M. jannaschii is an archaeon, growing optimally at a temperature of 85 oC and, as its name implies, produces methane. Methanococcus jannaschii contains about 1.6 million base pairs of DNA, a fairly small size, which made it an attractive candidate for gene sequencing. The scientific report of this sequence was published in August, 1996 (Science 273: 1058-1073). The complete genome sequence is available on the Web at the TIGR (The Institute for Genome Research) database. The genome of M. jannaschii contains three distinct elements: Description Size (base pairs) Predicted coding regions (ORFs) Circular chromosome 1,664,976 bp 1682 proteins Large circular DNA element 58,407 bp 44 proteins Small circular DNA element 16,550 bp 12 proteins Total 1738 proteins One of the first things the researchers did after obtaining the sequence was to predict all sections of the genome that coded for proteins. This is done by programming a computer to look for open reading frames, or ORFs. (If you are not familiar with ORFs, see the short Tutorial on ORFs.) Once each ORF is found, computers compare its predicted amino acid sequence with other known proteins, looking for similarity. If, for instance, a protein from M. jannaschii corresponds in 73% of its amino acids with a certain enzyme required for RNA synthesis from E. coli, then the computer identifies the M. jannaschii gene as a predicted RNA synthesis gene. Some ORFs cannot be matched up with any known proteins in current databases; these are called hypothetical proteins.

Ribosomal RNA Genes as a Yardstick for Evolution Scientists have learned that mutations occur far more frequently in some genes than in others, judging from the number of nucleotide substitutions that can be found by comparing different organisms. If you were interested in studying the evolutionary relationships of a group of closely related species (such as humans, chimpanzees, and gorillas), where evolution has occurred within the past 20 million years, you would probably want to examine a gene that mutates frequently, so that you could find some differences to study. But if you were interested in comparing living creatures over a time span as long as 4 billion years, you would be better off choosing to study a gene that mutates only rarely. What gene(s) mutates most slowly in organisms alive today? Possible candidates for this honor include the genes for ribosomal RNA. Cells produce three distinct types of RNA molecules: Messenger RNA (mRNA), which carries genetic information to ribosomes in order to specify the structure of proteins. Bacterial cells may contain many hundreds of different types of mRNAs at any one time. They account for only about 5% of total cell RNA. Transfer RNA (tRNA), which carries amino acids to ribosomes in order to provide the building blocks for growing proteins. Bacterial cells may contain about 60 different types of tRNA, accounting for about 15% of total cell RNA. Ribosomal RNA (rRNA), which is part of the structure of ribosomes. (A short Tutorial on Ribosome Structure reviews relevant concepts in case you need to refresh your understanding of ribosomal RNA.) Bacterial cells often devote as much as 90% of their energy to synthesizing new proteins, and require large numbers of ribosomes. rRNA accounts for about 80% of total cell RNA. The genes for ribosomal RNA are among the most stable and unchanging genes known. Viable mutations do occur, but infrequently. In particular, the genes for the small subunit RNA (16S in prokaryotes, or 18S in eukaryotes) have been used extensively to compare living organisms as diverse as bacteria, mushrooms, and humans. In 1977, Carl Woese of the University of Illinois and colleagues astonished the scientific world by publishing results of their extensive studies of small ribosomal subunit RNAs (Proc. Natl. Acad. Sci. U. S. A. 74:4537, 5088.) Predictably, they found wide differences in the RNAs and RNA gene sequences of bacteria and eukaryotes. What was so surprising, however, was their discovery of a third group of organisms, the Archaea, whose RNA sequences were as different from other bacteria as they were from eukaryotes. These differences are summarized in the following unrooted phylogenetic tree (redrawn from Woese et al.) Archaea share much more 16S RNA sequence homology among themselves than they do with either the other bacteria or the eukaryotes. Based on these studies, Woese suggested abandoning the traditional division of all living organisms into five kingdoms: Monera Protista Fungi Plantae Animalia Instead, Woese proposed grouping all living organisms into three domains: Bacteria (the eubacteria, or "true" bacteria) Archaea (the archaebacteria) Eucarya (the eukaryotes) Scientific reaction to this proposal was mixed. Everyone agreed that the Archaea seemed even more unrelated to ordinary bacteria than had previously been thought. But there was skepticism about the wisdom of entrusting the most fundamental taxonomy entirely to the results of a single methodology, based on comparing only ribosomal RNAs. What if future studies should reveal that ribosomal genes evolved quite differently than other genes? To many, it seemed wiser to wait and see what would be revealed by further study, particularly the sequencing of complete genomes of Archaea.

Example: Using DNA Sequences to Construct an Unrooted Tree The following example shows how an evolutionary tree is constructed for four hypothetical organisms whose DNA sequence in one homologous region is known. AACGTCGAAA (Organism A) AACCTCGAAA (Organism AGGCTAGAAA (Organism C) AGGCTAGTAA (Organism D) A and B differ by one base substitution. C and D also differ by one base substitution. But A and C differ by three substitutions, and A and D by four. B and C differ by three substitutions, and B and D also by four. In terms of evolutionary history, A and B appear to be very similar,as do C and D. A-B and C-D are more distantly related. Since we have no clue about their ancestors from this data, we cannot draw a rooted tree (see Rooted and Unrooted Trees in the previous page if you don't remember this distinction.) We can draw an unrooted tree, letting a computer determine the best data. Here are a couple of ways of drawing such a tree: The choice of line shape is quite arbitrary. What is important is that linear distance between organisms is proportional to the number of base substitutions. Although we assume that these distances are correlated with time, we don't know how frequently mutations occur, so we can't equate distances precisely with time. If organism B differs from C by three times as many nucleotide substitutions as it does from A, we can't assume that C diverged from A exactly three times as long ago as B did from A.

Nucleic Acid Sequence Comparisons as Measures of Evolutionary Separation In the Fable about monks disputing the authenticity of their texts, we explored the use of copy errors to predict something about evolutionary lineages. A somewhat analogous process can be used to compare nucleic acid sequences and infer something about their evolutionary history. DNA encodes the information for genes. DNA is reproduced with great fidelity during replication and repair, but occasional copy errors occur, with frequencies between 1 in a million and 1 in 100 million. For example, normal DNA replication would always place a thymine (T) base opposite an adenine (A) base, and a guanine (G) base opposite a cytosine © base. Occasionally, however, a mistake will occur, leaving a mispaired base. After another round of replication, the mistake will be "locked in" to one lineage of progeny cells. Such heritable mistakes are called mutations. In the example below, cytosine © is accidentally inserted when replicating from an adenine (A) template, instead of the normal complementary base thymine (T). After one further round of replication, the new C base has acted as a template to insert guanine (G) into newly replicated DNA, so the mutation is "locked in." No trace of the original A-T base pair remains. Not all mutations survive. If a mutated gene is critical to the cell and functions poorly in comparison to the non-mutated gene, mutant progeny may fail to survive, and the mutant gene is eliminated from the population. Some mutations do survive, however, and these tend to accumulate with the passage of time. Nucleotide differences between different DNA molecules provide an astonishingly useful way of measuring evolutionary distance. No fossils are required. One assumes that, if two comparable genes or DNA segments have nearly identical nucleotide sequences, then they shared a common ancestry in the recent past. By contrast, if they differ significantly in many nucleotide positions, their lineages must have diverged long ago.

Commentary on the Fable In our day, we are fortunate to have computers available, since they offer by far the most practical way of constructing error trees. Unrooted trees can be represented in a variety of ways, such as: We can devise two type of "error trees," which might better be called "phylogenetic trees" since they illustrate the evolutionary relationships among our objects of study: Rooted trees, where extra data allows us to identify the ancestral phrase or organism. In Biology, fossil data can allow rooting of some trees. Unrooted trees, where we lack data about the true ancestor, and must infer relationships by making comparisons between our phrases or organisms.

Rooted and Unrooted Trees "This is wonderful," exclaimed the monks. "So we now know the true original message, at the base of this tree!" "Yes," replied the Queen, "but only because I knew all along what that message was. You see," she said, pulling a scroll from her desk, "here is the original scroll, signed and dated by the monk who founded your monastic order long ago. It was given to the monarch of that time for preservation, and has been kept safe and unchanged in this palace all that time. Since we know its content, we know the root of the tree, and can place the branches in correct order." "But what if you did not possess that scroll?" asked the monks. "Could you still have deduced the correct ancestral text?" "No," answered the Queen. "If the only copies I had to work with were your differing manuscripts, our problem would be much more difficult. Lacking knowledge of the ancestral phrase, we would have to compare each of your messages to see by how many errors they differed from each other. We could still construct a tree, but it would have to be an 'unrooted tree,' since we did not know the true root message." "For example, comparing messages C and D, we would find that they differed by only two errors:" There is not one true Good, and he who declares otherwiselies. © There is not one true Go d, and he who declares otherwise dies. (D) "However, A and D would differ by at least seven errors, if we count the deletion of several words as a single error, along with letter changes and insertions or deletions:" There is but one who declares motherwise loves.(A) There is not one true God, and he who declares otherwise di es.(D) "We would also have to measure the minimal error distances between A and B, A and C, B and C, and B and D. Then we would have to draw all possible error trees to find which one was the most parsimonious. Frankly, it's a monumental task."

Using Copy Errors to Reconstruct Evolution A Fable Once upon a time, in a faraway land long, long ago, there was a monastic order whose mission was to preserve and spread its sacred writings. Every young monk had to spend years hand-copying these texts, then leave the monastery with his writings, travel, and found a new monastery. Novices at the new monastery, in turn, would recopy the founding monk's manuscripts by their own hand, and subsequently take these as they each journeyed on to found their own monasteries. Not all copies were flawless, however. Occasional mistakes were made, where a letter was carelessly copied incorrectly, or a word or phrase accidentally deleted. Over time, the writings at different monasteries came to differ in a number of particulars. Each monastery had only one complete copy of the text, and there was no "standard reference" to decide which (if any) was the "original" text. There came a time when monks from different monasteries began to quarrel bitterly over the validity of each others' texts, each claiming that theirs was the one "correct" version. A wise Queen ascended to the throne of this land, and she became concerned about the impact that the monks' quarrels were having on the peace of her region. "Bring me these writings, that I may see for myself what you are arguing about!" she proclaimed. The monks complied, and she began examining the texts side by side. Here are four of the excerpts she examined: There is but one who declares motherwise loves. (Monastery A) There is but one true God, and he who declares otherwise flies. (Monastery There is not one true Good, and he who declares otherwise lies. (Monastery C) There is not one true God, and he who declares otherwise dies. (Monastery D) "But this is silly!" she exclaimed. "I don't believe a single one of you has the correct ancestral text. Your texts seem to differ in three ways, all of which were probably the result of errors made while copying these texts from previous versions." Some errors are due to the insertion or deletion of a single letter. For example, two of your texts list the word "God," but one of them lists "Good." It looks like someone accidentally inserted an extra letter "o" to turn "God" into "Good." Some errors are due to changing a letter. For example, the word "dies" occurs in one text, and the word "lies" in another text. I'm pretty sure one of these is the original word, and the other is a mistake made by incorrectly copying the first letter. My guess is that "lies" is the original. A third type of error is the accidental deletion of a whole line. For example, the text from Monastery A is missing the phrase "true God, and he", which is found in some form in all the other texts. Probably the monk copying this phrase skipped a line. I would count that as a single mistake, not an accumulation of many single letter deletions, because that is the simplest explanation. "Futhermore, I can make a reasonable guess as to how your texts might have diverged over time. Would you like me to show you how?" The monks scratched their heads, looked at the four texts, and replied, "Yes, your highness. Please show us how this could be." "Let us proceed as follows," she said. "Arrange all four fragments one under the other, so that we can align individual letters." [Note: On a computer, use a non-proportional font such as Monaco so that every letter has the same width.] There is but one who declares motherwise loves. (A) There is but one true God, and he who declares otherwise flies. ( There is not one true Good, and he who declares otherwise lies. © There is not one true God, and he who declares otherwise dies. (D) "Now color all letters that differ from others in the same column. Let us also be free to move any text to maximize its alignment with the others, even if this means introducing gaps or extra spaces:" There is but one who declares motherwise loves. (A) There is but one true Go d, and he who declares otherwise fli es. ( There is not one true Good, and he who declares otherwise li es. © There is not one true Go d, and he who declares otherwise di es. (D) "We can now estimate the number of copy errors that separate each message from the other three. I'm going to assume that the original, or 'root' text, which none of you possesses, reads:" There is but one true God, and he who declares otherwise lies. "If this indeed the 'root phrase,' then each of your texts then could have originated as follows:" (original) (error 1: 4 words deleted) (error 2: addition of "m") (error 3: insertion of "v") (error 4: "i" ---> "o") (original) (error 1: insertion of "f") (original) (error 1: "b" ---> "n") (error 2: "u" ---> "o") (error 3: insertion of "o") (original) (error 1: "b" ---> "n") (error 2: "u" ---> "o") (error 3: "l" ---> "d") Text A: 4 errors removed from original There is but one true God, and he who declares otherwise li es. There is but one who declares otherwise li es. There is but one who declares motherwise li es. There is but one who declares motherwise lives. There is but one who declares motherwise loves. Text B: 1 error removed from original There is but one true God, and he who declares otherwise lies. There is but one true God, and he who declares otherwise flies. Text C: 3 errors removed from original There is but one true Go d, and he who declares otherwise lies. There is nut one true Go d, and he who declares otherwise lies. There is not one true Go d, and he who declares otherwise lies. There is not one true Good, and he who declares otherwise lies. Text D: 3 errors removed from original There is but one true God, and he who declares otherwise lies. There is nut one true God, and he who declares otherwise lies. There is not one true God, and he who declares otherwise lies. There is not one true God, and he who declares otherwise dies. "I've made several assumptions," said the Queen. Errors occur one at a time. An error can involve a single letter change, insertion or deletion of a single letter, or deletion of a number of letters or words at a single time. The shortest number of errors between two messages is most likely to have occurred (the principle of parsimony.) "I may have erred slightly--for example, in 'text A' I arbitrarily listed the four-word deletion as the first error, when it could equally well have been the second, third, or last. But I have always picked the shortest error path to get from ancestral text to each of your texts. So the number of errors is, in a way, a measure of the evolutionary history of your texts." "Furthermore," said the Queen, "I can even create an 'evolutionary tree' to illustrate how your texts have evolved. I'll let the number of errors be proportional to distance along a line. Then the history of your texts looks like this:" "Note that monasteries C and D must have shared the same text until very recently, whereas monastery A has a long separate history." Keep Reading...

The next 100 million years brings us to the present. Further extinctions occur. Only three species are present today (labeled F1-F3 in the following diagram). If we remove the colors, whose function is only to help us visualize the passage of time, we can represent this evolutionary history as a "tree," or a "bush." But we must remember that there is no observer who has faithfully recorded and reported every nuance of life's history. The "tree" we have created, while logically inescapable, cannot be drawn as an observed fact. Instead, we must try to deduce some of its features from clues, just as a detective must reconstruct a crime not witnessed. How can we do this? We do have two important pieces of data that can help us attempt to reconstruct an evolutionary tree: Living organisms, which we can study from many perspectives, including anatomy, physiology, DNA sequence, etc. Fossils, which, when we are lucky enough to find them, typically provide anatomical data One way to reconstruct an evolutionary tree would be to collect as much data as possible about both living and fossil creatures, and then to try to arrange such data in a logically plausible fashion. For example, we could look for progressive development of a particular anatomical adaptation over time: a wing, a hoof, etc. The biggest problem with such an approach is the lack of fossil data. Imagine, for example, that we were interested in reconstructing the history of our fictional color-coded organisms described above. Let us place some colored balls on our hypothetical evolutionary tree to represent both living organisms and the fossils we can find, as follows: Each red ball represents a living species. Balls of other colors each represent a particular fossil, color-coded to indicate the age from which they derived. Ideally, we would want to find an unbroken chain of fossils for every branch of our tree. In practice, fossils are few and far between, especially as we explore more ancient evolutionary events. Unfortunately, we don't know the pattern of the evolutionary tree -- that is what we're trying to find out. So to give an accurate picture of what we do know, we must erase the tree's branches, preserving only the representation of the living and fossil organisms that make up our data. In fact, we are not yet justified in placing the colored balls in any particular pattern. We don't know for sure which organisms are the ancestors of others. Our real data looks more like this: Here, at last, we are confronted with the real challenge of "doing evolution." We must try to arrange our data in such a way that we can reconstruct a logically plausible evolutionary tree, hoping to capture as many of the branches and dead ends as possible. Here are two of many possible attempted reconstructions of the evolutionary history of our example organisms. Notice that we are not able to do a very good job of reconstructing the "actual" tree (the one which really happened, whose shape we must infer). At this point we should abandon our metaphor (colored balls are not organisms, after all), and consider the real biological challenge. The fossil record is in many cases better than our example would suggest, and evolutionary trees for many "recent" evolutionary processes (particularly for organisms that leave hard fossil remains, such as bones or shells) have been constructed in some detail. Constructing evolutionary trees from fossil data becomes a much more daunting challenge when we attempt to study prokaryotes. We have almost no fossils to help us reconstruct the history of single-celled life, and even if we did, the prokaryotes are generally so small and lacking in morphological complexity that it is hard to imagine any way of reconstructing their evolutionary history. It would seem, at first glance, that we can never hope to penetrate the mists shrouding life's distant past, and that we can never hope to know how Bacteria and Archaea, in particular, evolved. But there is another way to trace life's history than the use of fossils--we can study the way errors accumulate in information over time. Keep Reading....

A Color Wheel Metaphor for the Evolutionary Process To fully appreciate the problem of reconstructing the past, let us use the image of a "color wheel" to help us visualize how life might evolve over time. We will arbitrarily divide time into intervals of 100 million years, and assign each interval a color. The last 100 million years will be diagrammed in red, the interval from 200 to 100 million years ago in orange, from 300 to 200 million years ago in yellow, and so on, back to 600 million years ago, which we will choose as the origin of our study. (Note that the earth is much older than this -- about 4.5 billion years old, by current reckoning, and life on earth is at least 4 billion years old.) We will imagine that some observer is actually keeping track of all life on earth, year by year, and recording all the data. During the period from 600 to 500 million years ago, we focus on one species of a certain type of organism. Its population disperses and becomes very diverse, but even at the end of this period it is still a single species (labeled A on the following diagram.) Over the next 100 million years, different populations of the primitive species become isolated from each other for so long that they evolve into separate species. By the end of this time there are three recognizably different species (labeled B1, B2, and B3 on the following diagram.) The black lines indicate the different groups of organisms, and the fact that they separate represents the growing differences between them over time. Another 100 million years goes by. Evolutionary processes continue, and new species evolve. By the end of this era, we find five species (labeled C1-C5 on the following diagram.) One population has only recently separated into two recognizable species (C2 and C3). Another population (C5) is becoming very diverse, but is still a single species. Over the next 100 million years, further speciation occurs. At the end of this time there are seven species (labeled D1-D7 in the following diagram). Keep reading...

First of all, you certainly can discuss Creation in public school. Heard of a Compartative Religions class? Second, I am 17. Third, a Chihuaha is quite a different species than a Great Dane. Can you not tell just from the physical appearance of the animal? I was hoping that would be semi-obvious.