Razib Khan's Unsupervised Learning
Razib Khan's Unsupervised Learning
John Logsdon: what has genomics done for evolution?
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John Logsdon: what has genomics done for evolution?

Understanding the evolutionary basis of the genome
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We’re about a generation into the “age of genomics,” or as it’s sometimes termed the “post-genomic era.” Today Razib talks to John Logsdon, a professor of biology at the University of Iowa, about what genomics has wrought in relation to our understanding of evolution, and what evolution has taught us about the structure and nature of the genome. In 2014, Logdson and Sarah J Hanson contributed a chapter entitled “Genome Evolution” to the Princeton Guide to Evolution. Razib uses this mid-2010s review to scaffold his discussion with Logdson about where we are in 2023. But first, he asks what the exact difference between genetics and genomics is. It is sometimes said that quantity has a quality all its own, and Razib and Logdson discuss the different analytic challenges of analyzing the evolutionary trajectory of a single gene, a task up the alley of classical genetics, and describing the evolution of the whole genome of an organism like a human, with thousands of genes.

They then move on to various issues relating to the architecture and evolution of the genome that are of deep interest and curiosity to researchers but rarely surfaced to the public. Why do bacterial genomes have so much less “junk” than those of complex organisms, like humans? Why is the relationship between organism complexity and genome size still so uncertain? How has evolution impacted the “molecular machinery” of the genome (like promoters)? And what is the difference between those scientists who use genomics to understand evolution and those who attempt to understand the evolutionary forces that shape the nature of the genome?

By inspecting where we are on many specific issues relating to evolution and genomics, Razib and Logdson begin a sketch of how the emergence of genomics has changed evolutionary biology, as the entire genetic maps of vast numbers of species are now at our fingertips. The discussion finally concludes with future possibilities in the next few decades, as the post-genomic era moves from a revolution to a background condition, a  banality.

Note: Logsdon mentioned HHMI molecular genetic videos. Here is an excellent example:

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Razib Khan's Unsupervised Learning
Razib Khan's Unsupervised Learning
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