Daily Archives: June 26, 2022

If you look different to your close relatives, you may have felt separate from your family. As a child, during particularly stormy fall outs you might have even hoped it was a sign that you were adopted.

As our new research shows, appearances can be deceptive when it comes to family. New DNA technology is shaking up the family trees of many plants and animals.

The primates, to which humans belong, were once thought to be close relatives of bats because of some similarities in our skeletons and brains. However, DNA data now places us in a group that includes rodents (rats and mice) and rabbits. Astonishingly, bats turn out to be more closely related to cows, horses, and even rhinoceroses than they are to us.

Scientists in Darwin's time and through most of the 20th century could only work out the branches of the evolutionary tree of life by looking at the structure and appearance of animals and plants. Life forms were grouped according to similarities thought to have evolved together.

About three decades ago, scientists started using DNA data to build "molecular trees". Many of the first trees based on DNA data were at odds with the classical ones.

Sloths and anteaters, armadillos, pangolins (scaly anteaters), and aardvarks were once thought to belong together in a group called edentates ("no teeth"), since they share aspects of their anatomy.

Molecular trees showed that these traits evolved independently in different branches of the mammal tree. It turns out that aardvarks are more closely related to elephants while pangolins are more closely related to cats and dogs.

There is another important line of evidence that was familiar to Darwin and his contemporaries. Darwin noted that animals and plants that appeared to share the closest common ancestry were often found close together geographically. The location of species is another strong indicator they are related: species that live near each other are more likely to share a family tree.

For the first time, our recent paper cross-referenced location, DNA data, and appearance for a range of animals and plants. We looked at evolutionary trees based on appearance or on molecules for 48 groups of animals and plants, including bats, dogs, monkeys, lizards, and pine trees.

Evolutionary trees based on DNA data were two-thirds more likely to match with the location of the species compared with traditional evolution maps. In other words, previous trees showed several species were related based on appearance.

Our research showed they were far less likely to live near each other compared to species linked by DNA data.

It may appear that evolution endlessly invents new solutions, almost without limits. But it has fewer tricks up its sleeve than you might think.

Animals can look amazingly alike because they have evolved to do a similar job or live in a similar way. Birds, bats and the extinct pterosaurs have, or had, bony wings for flying, but their ancestors all had front legs for walking on the ground instead.

(Oyston et al., Communication Biology, 2022)

Above:The color wheels and key indicate where members of each order are found geographically. The molecular tree has these colors grouped together better than the morphological tree, indicating closer agreement of the molecules to biogeography.

Similar wing shapes and muscles evolved in different groups because the physics of generating thrust and lift in air are always the same. It is much the same with eyes, which may have evolved 40 times in animals, and with only a few basic "designs".

Our eyes are similar to squid's eyes, with a crystalline lens, iris, retina, and visual pigments. Squid are more closely related to snails, slugs, and clams than us. But many of their mollusk relatives have only the simplest of eyes.

Moles evolved as blind, burrowing creatures at least four times, on different continents, on different branches of the mammal tree. The Australian marsupial pouched moles (more closely related to kangaroos), African golden moles (more closely related to aardvarks), African mole rats (rodents), and the Eurasian and North American talpid moles (beloved of gardeners, and more closely related to hedgehogs than these other "moles") all evolved down a similar path.

Until the advent of cheap and efficient gene sequencing technology in the 21st century, appearance was usually all evolutionary biologists had to go on.

While Darwin (1859) showed that all life on Earth is related in a single evolutionary tree, he did little to map out its branches. The anatomist Ernst Haeckel (1834-1919) was one of the first people to draw evolutionary trees that tried to show how major groups of life forms are related.

(Ernest Haeckel)

Haeckel's drawings made brilliant observations of living things that influenced art and design in the 19th and 20th centuries. His family trees were based almost entirely on how those organisms looked and developed as embryos.Many of his ideas about evolutionary relationships were held until recently.

As it becomes easier and cheaper to obtain and analyze large volumes of molecular data, there will be many more surprises in store.

Matthew Wills, Professor of Evolutionary Palaeobiology at the Milner Centre for Evolution, University of Bath.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Read more from the original source:

New DNA Technology Is Shaking Up The Branches of The Evolutionary Tree - ScienceAlert

An international team of 114 scientists has performed the most comprehensive study of aging and longevity to date with data collected in the wild from 107 populations of 77 species of reptiles and amphibians worldwide.

MSU Professor Anne Bronikowski

The team, led by researchers at Michigan State University, Pennsylvania State University and Northeastern Illinois University, reported its findings in the journal Science on June 23.

Among their many findings, the researchers documented for the first time that turtles, salamanders and crocodilians (an order that includes crocodiles, alligators and caimans) have particularly slow aging rates and extended lifespans for their sizes.

We are committed to studying long-lived species in the wild because nature has already done the experiment of how to age slowly, wrote MSU researchers Anne Bronikowski and Fredric Janzen.

Bronikowski is one of the leaders of the study who recently joined MSU as a professor of integrative biology in the College of Natural Science and at the W. K. Kellogg Biological Station, or KBS. Janzen is the director of KBS, as well as a professor in the College of Natural Science and the College of Agriculture and Natural Resources.

MSU Professor Fredric Janzen

Anne sometimes calls these examples evolutions solutions to growing old, Janzen said.

They are relevant to studies of human frailty because our cellular and genomic pathways are shared across much of animal life, Bronikowski said.

If we can understand what allows some animals to age more slowly, we can better understand aging in humans as well, and we can also inform conservation strategies for reptiles and amphibians, many of which are threatened or endangered, said David Miller, a senior author of the Science paper and an associate professor of wildlife population ecology at Penn State.

In their study, the researchersapplied methods used in both ecological and evolutionary sciences to analyze variation in aging and longevity of reptiles and amphibians. These cold-blooded" or ectothermic animals offer a contrast to "warm-blooded" or endothermic mammals and birds.

One of the interesting findings was that each group has a slow or negligible aging species across all these different ectotherms, wrote Bronikowski and Janzen.

It sounds dramatic to say that they dont age at all, said Beth Reinke, the first author of the Science report and an assistant professor of biology at Northeastern Illinois University. But basically their likelihood of dying does not change with age once theyre past reproduction.

The face of a tuatara (Sphenodon punctatus), a slow-aging reptile found in New Zealand. Credit: Sarah Lamar

Negligible aging means that if an animals chance of dying in a year is 1% at age 10, if it is alive at 100 years, its chance of dying is still 1%. By contrast, in adult U.S. females, the risk of dying in a year is about 1-in-2,500 at age 20 and 1-in-24 at age 80, said Penn States Miller, citing a current U.S. Social Security Administration actuarial table. When a species exhibits negligible mortality senescence, this mortality aging just doesnt happen.

The researchers also compared their findings in ectotherms to what is known about endotherms and explored previous hypotheses related to aging.

For instance, the thermoregulatory mode hypothesis suggests that endotherms age faster than ectotherms because endotherms have higher metabolisms to help regulate their body temperatures.

People tend to think, for example, that mice age quickly because they have high metabolisms, whereas turtles age slowly because they have low metabolisms, Miller said.

The teams findings, however, reveal that ectotherms aging rates and lifespans range both well above and below the known aging rates for similar-sized endotherms. Thus, it appears that the way an animal regulates its temperature cold-blooded versus warm-blooded is not necessarily indicative of its aging rate or lifespan.

A photo of a painted turtle (Chrysemys picta), a widespread North American species of freshwater turtle. Credit: Beth A. Reinke

We didnt find support for the idea that a lower metabolic rate means ectotherms are aging slower, Miller said. That relationship was only true for turtles, which suggests that turtles are unique among ectotherms.

Then theres the protective phenotypes hypothesis, which suggests that animals with traits that confer protection such as armor, spines or shells have greater longevity. This, in turn, promotes slower aging.

The team documented that these protective traits do, indeed, enable animals to age more slowly and live much longer for their size than those without protective phenotypes.

These various protective mechanisms may reduce animals mortality rates within generations, said Reinke. Thus, theyre more likely to live longer, and that can change the selection landscape across generations for the evolution of slower aging. We found the biggest support for the protective phenotype hypothesis in turtles. Again, this demonstrates that turtles, as a group, are unique.

In fact, a tortoise named Jonathan recently made news for being the worlds oldest living land animal at 190 years old.

It could be that their altered morphology with hard shells provides protection and has contributed to the evolution of their life histories, including negligible aging or lack of demographic aging and exceptional longevity, said MSUs Bronikowski.

A female Darwins frog (Rhinoderma darwinii) in southern Chile. Credit: ONG Ranita de Darwin

Bronikowski helped seed the study with support from a grant from the National Institute on Aging, one of the National Institutes of Health, to study aging in painted turtles. Hugo Cayeula, a postdoctoral researcher at the University of Lyon in France, was leading a similar project on frogs and amphibians, so it made sense to collaborate, Bronikowski said.

From there, Northeastern Illinoiss Reinke reached out to more and more researchers to include more and more ectotherms (for a full list of authors and their affiliations, please see the published manuscript in Science).

The teams novel study was only possible because of the contributions of a large number of collaborators from across the world studying a wide variety of species, Reinke said.

See more here:

Revealing 'evolution's solutions' to aging | MSUToday | Michigan State University - MSUToday

The middle ear of humans evolved from fish gills, according to a study of a 438 million-year-old fossil fish brain.

Scientists discovered the fossil of the braincase of a Shuyu fish. Despite its skull only being the size of a fingernail they were able to recreate seven virtual casts of the brain.

They also unearthed the first 419 million-year-old armored galeaspid fossil completely preserved with gill filaments.

The team from the Institute of Vertebrate Paleontology and Paleoanthropology (IVPP) of the Chinese Academy of Sciences found the spiracle, slits behind the eyes leading to the mouth which allows some species to breathe.

In sharks and all rays, the spiracle is responsible for the intake of water before being expelled from the gills.

The spiracle evolved into the ear of modern four-legged vertebrates eventually becoming the hearing canal used for transmitting sound to the brain via tiny inner ear bones.

This function has remained throughout the evolution to humans.

The detail derived from the two fossils is the last piece of the jigsaw proving the line from fish gills to the human ear.

The human middle ear houses three tiny, vibrating bones which are key to transporting sound vibrations into the inner ear, where they become nerve impulses that allow us to hear.

Professor Zhikun Gai from IVPP and first author of the study said: "These fossils provided the first anatomical and fossil evidence for a vertebrate spiracle originating from fish gills."

A total of seven virtual endocasts of the Shuyu braincase were reconstructed.

Almost all details of the cranial anatomy of Shuyu were revealed in its fingernail-sized skull, including five brain divisions, sensory organs, and cranial nerve and blood vessel passages.

The fossils found in China's Changxing, Zhejiang Province and Qujing, Yunnan Province were hailed as the 'missing links' from the gill to the middle ear.

Professor Min Zhu, academician of the Chinese Academy of Sciences added: "Many important structures of human beings can be traced back to our fish ancestors, such as our teeth, jaws, middle ears, etc.

"The main task of paleontologists is to find the important missing links in the evolutionary chain from fish to humans.

"Shuyu has been regarded as a key missing link as important as Archaeopteryx."

Professor Per Ahlberg from Uppsala University and academician of the Royal Swedish Academy of Sciences who collaborated on the research, said: "Our finding bridges the entire history of the spiracular slit, bringing together recent discoveries from the gill pouches of fossil jawless vertebrates, via the spiracles of the earliest jawed vertebrates, to the middle ears of the first tetrapods, which tells this extraordinary evolutionary story."

The study was published in the journal Frontiers in Ecology and Evolution.

This story was provided to Newsweek by Zenger News.

Read the original here:

Middle Ear of Humans Evolved From Fish Gills, According to Study - Newsweek

Photo credit: Foam, via Flickr (cropped).

I am reviewing Jason Rosenhouses new book,The Failures of Mathematical Anti-Evolutionism(Cambridge University Press), serially.For the full series so far, go here.

Because of the centrality of the searching protein space model to Jason Rosenhouses argument, its instructive to illustrate it with the full rigor of his track 2 (see my post from yesterday on that). Let me therefore lay out such a model in detail. Consider a 100-dimensional discrete hypercube of 100-tuples of the form (a_1,a_2, ,a_100), where thea_is are all natural numbers between 0 and 100. Consider now the following path in the hypercube starting at (0, 0, , 0) and ending at (100,100, , 100). New path elements are now defined by adding 1s to each position of any existing path element, starting at the left and moving to the right, and then starting over at the left again. Thus the entire path takes the form

0: (0, 0, , 0)

1: (1, 0, , 0)

2: (1, 1, , 0)

100: (1, 1, , 1)

101: (2, 1, , 1)

102: (2, 2, , 1)

200: (2, 2, , 2)

300: (3, 3, , 3)

1,000: (10, 10, , 10)

2.000: (20, 20, , 20)

10,000: (100, 100, , 100)

The hypercube consists of 101^100, or about 2.7 x 10^200 elements, but the path itself has only 10,001 path elements and 10,000 implicit path edges connecting the elements.

For simplicity, lets put this discrete hypercube under a uniform probability distribution (we dont have to, but its convenient for the purposes of illustration Rosenhouse mistakenly claims that intelligent design mathematics automatically defaults to uniform or equiprobability, but thats not the case, as we will see; but there are often good reasons to begin an analysis there). Given a uniform probability on the discrete hypercube, the path elements, all 10,001 of them considered together, have probability roughly 1 in 2.7 x 10^196 (10,001 divided by the total number of elements making up the hypercube). Thats very small, indeed smaller than the probability of winning 23 Powerball jackpots in a row (the probability of winning one Powerball jackpot is 1 in 292,201,338).

Each path element in the hypercube has 200 immediate neighbors. Note that in one dimension there would be two neighbors, left and right; in two dimensions there would be four neighbors, left and right as well as up and down; in three dimensions there would be six neighbors, left and right, up and down, forward and backward; etc. Note also for path elements on the boundary of the hypercube, we can simply extend the hypercube into the ambient discrete hyperspace, finding there neighbors that never actually end up getting used (alternatively, the boundaries can be treated as reflecting barriers, a device commonly used by probabilists).

Next, lets define a fitness functionFthat is zero off the path and assigns to path elements of the form (a_1,a_2, ,a_100) the suma_1 +a_2 + +a_100. The starting point (0, 0, , 0) then has minimal fitness and the end point (100, 100, , 100) then has maximal fitness. Moreover, each successive path element, as illustrated above, has higher fitness, by 1, than its immediate predecessor. If we now stay with a uniform probability, and thus sample uniformly from the adjoining 200 neighbors, then the probabilitypof getting to the next element on the path, as judged by the fitness functionF, is 1 in 200 for any given sample query, which we can think of and describe as amutational step.

The underlying probability distribution for moving between adjacent path elements is thegeometric distribution. Traversing the entire path from starting point to end point can thus be represented by a sum of independent and identically distributed (with geometric distribution) random variables. Thus, on average, it takes 200 evolutionary sample queries, or mutational steps, to move from one path element to the next, and it therefore takes on average 2,000,000 (= 200 x 10,000) evolutionary sample queries, or mutational steps, to move from the starting to the end point. Probabilists call these numberswaiting times. Thus, the waiting time for getting from one path element to the next is, on average, 200; and for getting from the starting to the end point is, on average, 2,000,000.

As it is, the geometric distribution is easy to work with and illustrates nicely Rosenhouses point about evolution not depending on brute improbability. But suppose I didnt see that I was dealing with a geometric distribution or suppose the problem was much more difficult probabilistically, allowing no closed-form solution as here. In that case, I could have written a simulation to estimate the waiting times: just evolve across the path from all zeros to all one-hundreds over and over on a computer and see what it averages to. Would it be veering from Rosenhouses track 2 to do a simulation to estimate the probabilities and waiting times? Throughout his book, he insists on an exact and explicit identification of the probability space, its geometry, and the relevant probability distributions. But thats unnecessary and excessive.

In many practical situations, we have no way of assigning exact theoretical probabilities. Instead, we must estimate them by sampling real physical systems or by running computer simulations of them. Even in poker, where all the moving parts are clearly identified, the probabilities can get so out of hand that only simulations can give us a grasp of the underlying probabilities. And whats true for poker is even more true for biology. The level of specificity Ive given in this hypercube example is way more than Rosenhouse gives in his searching protein space example. The hypercube makes explicit what he leaves implicit, namely, it distinguishes mathematically the entire search space from the evolutionary paths through it from the neighborhoods around points on the path. It thus captures a necessary feature of Darwinian evolution. But it does so at the cost of vast oversimplification, rendering the connection between Darwinian and real-world evolution tenuous at best.

Why have I just gone through this exercise with the 100-dimensional discrete hypercube, giving it the full track 2 monty? Two reasons. One, it is to rebut Rosenhouses insistence on Darwinian gradualism in the face of intelligent design (more on this later in this review series). Two, it is to show Darwinist critics like Rosenhouse that we in the intelligent design community know exactly what they are talking about when they stress that rather than brute improbability, the real issue for evolvability is the improbability of traversing evolutionary pathways subject to fitness. Ive known this for decades, as have my intelligent design colleagues Mike Behe, Steve Meyer, and Doug Axe. Rosenhouse continually suggests that my colleagues and I are probabilistically nave, failing to appreciate the nuances and subtleties of Darwinism. Were not. Ill be returning to the hypercube example because it also illustrates why Rosenhouses Darwinism is so implacably committed to sequential mutations and must disallow simultaneous mutations at all costs. But first

Next, Rosenhouse and Mathematical Proof.

Editors note: This review is cross-posted with permission of the author fromBillDembski.com.

See the original post here:

Rosenhouse and Discrete Hypercube Evolution - Discovery Institute

By Seth Matlins Managing Director, Forbes CMO Network

No matter how you measure marketing influence, no matter the tweaks made to methodology over time, no matter the sea-change across the marketing landscape itself, the chief marketers being inducted into this first class of The Forbes CMO Hall of Fame, have been mainstays of The Forbes Worlds Most Influential CMOs List since its launch in 2012.

We consider this proof positive of their enduring influence on the brands and businesses they help lead, on industry, the marketing community and the attitudes and behaviors of people the world over. Individually and collectively, they have shown us what true (marketing) leadership and impactin the face of unimaginable and unforeseen changelooks like.

Given their influence, given the scope and scale of their achievements over time we thought their perspective on the changes these Chief Marketers have seen (and driven) over the past decade, and the ones they expect to continue to confront in the exercise of their influence were worth sharing.

While we werent able to connect with each of those being inducted, we asked those we did how, over the past decade, they thought marketing and marketing influence had evolved, and what and/or who moving forward a chief marketers influence will be in service of? Weve organized the perspectives theyve shared in 3 buckets.

Some of answers have been edited for clarity. They are presented in alphabetical order:

Whats clear from whats been shared is that the worlds most frequently recognized influential marketers recognize in turn that while theyve been and will be confronted by torrents of change, what remains unchanged is that understanding and serving the user to drive growth remains fundamental even if and as the how-to-do-it continues to evolve. While one could reasonably argue this isnt news, given that change often begets more change and a reflexive shift in focus, wed suggest that maybe this is exactly the point.

Whats equally clear and we hope offers reason for optimism at a time when socio-economic indicators globally provide few, is that these chief marketers clearly see their role and influence serving more than a shot-term sales imperative but, rather, the long-term best interests of an eco-system of stakeholders and the world at large. And that they consider the activation and expression of purposea word oft over and mis-usednot as window dressing but as an economic engine.

Finally, by definition, induction into any Hall of Fame is rooted in looking backwards, in what has already been done and accomplished and contributed. But, we consider at least the early years of The Forbes CMO Hall of Fame more as a living museum because those inducted continue to do, contribute, accomplish and, yes, influence.

With this in mind, we give the last word to inductee Michelle Peluso:

Heres to owning our own future and having the curiosity, grit, and grace to shape it.

Here is the original post:

Forbes CMO Hall Of Fame Inductees On The Evolution Of Marketing And Marketing Influence - Forbes