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<blockquote data-quote="Haven" data-source="post: 146754" data-attributes="member: 5537"><p>Since you are using AI lets see what it says:</p><p></p><p>The concern that random mutations primarily break existing functions rather than create new ones is a common challenge raised against evolution, but the evolutionary mechanism relies on a crucial distinction: the interplay between <strong>random mutation</strong> and <strong>non-random natural selection</strong>. While it is true that most mutations that <em>do</em> affect function—especially in essential, highly optimized genes—are often deleterious or neutral (a loss-of-function is far more likely than a direct, instant gain-of-function), evolution does not rely on the majority of mutations being beneficial. Instead, it depends on the sheer <strong>power of numbers</strong> over vast timescales.</p><p></p><p>The "complex information" in a cell doesn't arise from a single beneficial leap; it emerges through three main avenues, all stemming from mutations: <strong>gene duplication</strong>, <strong>neutral drift</strong>, and <strong>selection acting on small changes</strong>. Gene duplication is key: one copy retains the original, essential function, while the second, redundant copy is free to accumulate significant, often <em>breaking</em>, mutations without killing the organism. Over time, this redundant copy can accidentally gain a <em>new</em> function (<strong>gain-of-function</strong>) that proves beneficial under selection. Furthermore, many mutations are <strong>neutral</strong> and don't break or immediately improve function; these accumulate and provide a massive reservoir of raw genetic material upon which selection can later act if the environment changes. Therefore, the seemingly "broken" functions are often necessary stepping stones or raw materials that, through duplication and later modification, provide the novel parts needed to build the complex informational structures observed in life.</p></blockquote><p></p>
[QUOTE="Haven, post: 146754, member: 5537"] Since you are using AI lets see what it says: The concern that random mutations primarily break existing functions rather than create new ones is a common challenge raised against evolution, but the evolutionary mechanism relies on a crucial distinction: the interplay between [B]random mutation[/B] and [B]non-random natural selection[/B]. While it is true that most mutations that [I]do[/I] affect function—especially in essential, highly optimized genes—are often deleterious or neutral (a loss-of-function is far more likely than a direct, instant gain-of-function), evolution does not rely on the majority of mutations being beneficial. Instead, it depends on the sheer [B]power of numbers[/B] over vast timescales. The "complex information" in a cell doesn't arise from a single beneficial leap; it emerges through three main avenues, all stemming from mutations: [B]gene duplication[/B], [B]neutral drift[/B], and [B]selection acting on small changes[/B]. Gene duplication is key: one copy retains the original, essential function, while the second, redundant copy is free to accumulate significant, often [I]breaking[/I], mutations without killing the organism. Over time, this redundant copy can accidentally gain a [I]new[/I] function ([B]gain-of-function[/B]) that proves beneficial under selection. Furthermore, many mutations are [B]neutral[/B] and don't break or immediately improve function; these accumulate and provide a massive reservoir of raw genetic material upon which selection can later act if the environment changes. Therefore, the seemingly "broken" functions are often necessary stepping stones or raw materials that, through duplication and later modification, provide the novel parts needed to build the complex informational structures observed in life. [/QUOTE]
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