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Does avocado and orange have a common ancestor?

Does avocado and orange have a common ancestor?


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While I'm eating my orange, I felt as if I was eating avocado. It might be genetic manipulations perhaps but it made me think if they have a common evolutionary ancestor. Is there?


Here is a website that presents very accuerately the tree of life: tolweb.org/tree

Yes, they have a common ancestor just like any other living things! How closely related are they?

Both species are:

  • Eukaryotes (cells with a nucleus)
  • Archaeplastidae (plants)
  • Angiosperms (flowering plants)

Then, they split their way! Here is the tolweb.org page that correspond to this speciation: http://tolweb.org/Angiosperms/20646

The avocado is in the Laurales family: http://tolweb.org/Laurales/20672

The orange is in the Rutacea (sapindales, rosids, eudicots) family: http://tolweb.org/Sapindales/21051.

You can use the left arrow on the tree of these pages to come back through times and see the different speciation event that seperate both species.

While the orange is a eudicots, the avocado is part of the magnolids. The oldest fossil records of an angiosperm lived about 132MYA (see Crane et al., 2004). So the two species diverge for quite a long time! In order to give a comparison, they are as distant than humans and rabbits (it is a rough personal estimation, I don't have any reference for that!)

Note: The orange is called Citrus sinensis in latin. The species originated in China. The avocado is called Persea americana and it originated in central american (as their names indicate).

I don't know what make you feel that they are closely related. Maybe someone might say some words about their chemical compounds (and their flavour) but at first glance these two fruits taste very differently to me. Or maybe they have some remarkably similar phenotypic traits due to convergence evolution… I don't quite know about that!


Does avocado and orange have a common ancestor? - Biology

Since a phylogenetic tree is a hypothesis about evolutionary relationships, we want to use characters that are reliable indicators of common ancestry to build that tree. We use homologous characters — characters in different organisms that are similar because they were inherited from a common ancestor that also had that character. An example of homologous characters is the four limbs of tetrapods. Birds, bats, mice, and crocodiles all have four limbs. Sharks and bony fish do not. The ancestor of tetrapods evolved four limbs, and its descendents have inherited that feature — so the presence of four limbs is a homology.

Not all characters are homologies. For example, birds and bats both have wings, while mice and crocodiles do not. Does that mean that birds and bats are more closely related to one another than to mice and crocodiles? No. When we examine bird wings and bat wings closely, we see that there are some major differences.

Bat wings consist of flaps of skin stretched between the bones of the fingers and arm. Bird wings consist of feathers extending all along the arm. These structural dissimilarities suggest that bird wings and bat wings were not inherited from a common ancestor with wings. This idea is illustrated by the phylogeny below, which is based on a large number of other characters.

Bird and bat wings are analogous — that is, they have separate evolutionary origins, but are superficially similar because they have both experienced natural selection that shaped them to play a key role in flight. Analogies are the result of convergent evolution.

Interestingly, though bird and bat wings are analogous as wings, as forelimbs they are homologous. Birds and bats did not inherit wings from a common ancestor with wings, but they did inherit forelimbs from a common ancestor with forelimbs.


A Spanish Navigator Rediscovered The Avocado In Yaharo In the 1500s

But it was the 15th-century navigator Martin Fernandez De Encisco from Seville, Spain, who brought the fruit back to popular knowledge when he set out on his quest of discovering the unknown in the “New World.” Encisco writes in his seminal work Suma de Geografia (1519) about a fruit he chanced upon at the port town of Yaharo that “looks like an orange” but turns “yellowish when it is ready to be eaten.” He goes on to explain the “marvelous flavor” of the insides of the fruit, which tastes “like butter” and is “so good and pleasing to the palate.” 2


Results and Discussion

Interdomain Gene Transfers of proS and alaS

Previously we showed that the genes encoding prolyl-tRNA synthetase and alanyl-tRNA synthetase, respectively, were most likely laterally transferred from Archaea to diplomonads ( Andersson et al. 2003). To explore these interdomain transfers further, we have increased the eukaryotic taxonomic sampling for these genes to include sequences from three additional Entamoeba species, the heterolobosean Naegleria, the pelobiont Mastigamoeba, the parabasalid Trichomonas, the diatom Thalassiosira, the oomycete Phytophthora, and the ciliates Paramecium and Tetrahymena. On the whole, the phylogenetic analyses on the updated data sets of the two proteins agree fairly well with expected organismal phylogeny, with only a few easily identified exceptions ( fig. 1). Only two of these unexpected branching patterns with high bootstrap support are observed among the prokaryotes, both in the proS tree the Pirellula sequence shows close relationship with α-proteobacteria and the Halobacterium sequence is found in a distinct position from the other euryarchaeota sequences ( fig. 1A). Surprisingly, the eukaryotes show up in a handful unexpected positions. The D. discoideum and P. sojaealaS sequences are found outside the main eukaryotic clade ( fig. 1B). Unfortunately, the statistical support for the separation is weak and, therefore, the origins of these sequences are uncertain. Both proS and alaS plant sequences are found nested within the Eubacteria with strong support ( fig. 1), most likely indicating two interdomain gene transfer events—the alaS sequence almost certainly via the chloroplast. Finally, a subset of the eukaryotes is found nested within the Archaea in both trees ( fig. 1), strongly suggesting transfer of the genes between Archaea and eukaryotes. The seemingly similar frequency of observed gene transfer events affecting eukaryotes compared with prokaryotes for these two aminoacyl-tRNA genes may be somewhat surprising ( fig. 1). However, we previously reported that gene transfer appears to have affected prokaryotes and microbial eukaryotes to a similar extent in the glutamate dehydrogenase gene families ( Andersson and Roger 2003), indicating that lateral gene transfer may indeed be a widespread evolutionary mechanism in microbial eukaryotes ( Andersson et al. 2003 Archibald et al. 2003 Gogarten 2003).

Phylogenies of two aminoacyl-tRNA synthetase protein sequence data sets. ML trees of (A) prolyl-tRNA synthetase and (B) alanyl-tRNA synthetase. Protein ML bootstrap values greater than 50% calculated using PHYML are shown (ML+Γ). Bootstrap support for critical bipartitions from additional analyses are shown within boxes for comparison ML bootstrap values calculated using PROML (ML+Γ*), protein ML assuming uniform site rates (ML−Γ), protein ML distance (ML–dist), LogDet distance (LogDet), and maximum parsimony (Pars). Eubacteria are labeled black, Archaea are labeled blue, and Eukaryotes are labeled according to their classification into “supergroups” ( Cavalier-Smith 2002 Simpson and Roger 2002 Baldauf 2003): opisthokonts (orange), amoebozoa (purple), plantae (green), chromalveolates (red), and excavates (brown). The eukaryotic backbone is labeled gray.

Phylogenies of two aminoacyl-tRNA synthetase protein sequence data sets. ML trees of (A) prolyl-tRNA synthetase and (B) alanyl-tRNA synthetase. Protein ML bootstrap values greater than 50% calculated using PHYML are shown (ML+Γ). Bootstrap support for critical bipartitions from additional analyses are shown within boxes for comparison ML bootstrap values calculated using PROML (ML+Γ*), protein ML assuming uniform site rates (ML−Γ), protein ML distance (ML–dist), LogDet distance (LogDet), and maximum parsimony (Pars). Eubacteria are labeled black, Archaea are labeled blue, and Eukaryotes are labeled according to their classification into “supergroups” ( Cavalier-Smith 2002 Simpson and Roger 2002 Baldauf 2003): opisthokonts (orange), amoebozoa (purple), plantae (green), chromalveolates (red), and excavates (brown). The eukaryotic backbone is labeled gray.

A Single Archaeal Origin of the Diplomonad and Parabasalid proS

The topology with a eukaryotic clade including parabasalid and diplomonad sequences nested with the Archaea to the exclusion of other eukaryotes is strongly supported in the proS tree by all phylogenetic methods, likely indicating an interdomain gene-transfer event from the Archaea to a common ancestor of these eukaryotic groups. The specific archaeal origin of the proS gene in diplomonads and parabasalids is more difficult to identify because of large disagreements between the results from the various phylogenetic methods used. A specific relationship between the N. equitans and the eukaryotic sequences is supported by a bootstrap value of 73% in the ML analysis, and the relationship is recovered by the other ML methods, as well as with parsimony ( fig. 1A). However, the LogDet distance analysis disagrees. The Nanoarchaeum relationship is recovered in only 25% of the bootstrap replicates ( fig 1A), whereas 52% of the replicates place the eukaryotic sequences basal to the archaea (data not shown)—a position that is only found in 4% of the replicates in the ML bootstrap analyses that incorporate the gamma model of rate heterogeneity (data not shown). Because both the N. equitans and the G. lamblia sequences failed the test for amino acid compositional heterogeneity applied to the data sets, and the applied phylogenetic methods assume a uniform amino acid composition within the data set (with the exception of LogDet analysis), the specific relationship between the Nanoarchaeota, diplomonad, and parabasalid sequences could be the result of an artifactual attraction caused by the amino acid compositional heterogeneity. On the other hand, a model that incorporates rate heterogeneity within the data set could not be applied to the LogDet analysis, because that would require a larger data set ( Thollesson 2004 M. Thollesson, personal communication), and the attraction between the diplomonad and parabasalid sequences—which represent the longest branches within the archaea/diplomonad/parabasalid subtree ( fig. 1A)—and the long internal branch in this analysis could be an artifact caused by the absence of a rate heterogeneity model. Obviously, in the absence of an efficient method that simultaneously can incorporate models of rate and amino acid heterogeneities, the relationship within the archaea/diplomonad/parabasalid subtree cannot be resolved with a high degree of confidence for proS.

Gene-Transfer Events Have Distributed Archaeal alaS in Diverse Microbial Eukaryotes

The eukaryotic group showing the largest diversity within the alaS tree is found within eubacteria, and a eukaryotic cluster including diplomonads, parabasalid, Entamoeba, and ciliate sequences is found as a sister group to the N. equitans sequence with high bootstrap support (≥98% for all methods [ fig. 1B]). Given current accounts of eukaryotic phylogeny ( Baldauf et al. 2000 Bapteste et al. 2002 Cavalier-Smith 2002 Simpson and Roger 2002 Baldauf 2003), this topology is most easily explained by a gene transfer to a common ancestor of diplomonads and parabasalids, followed by two eukaryote-to-eukaryote gene transfers that replaced the ancient eukaryotic version in the ciliate and Entamoeba lineages. Specifically, the well-supported relationship in ML and parsimony analyses between the Trichomonas sequence and the Entamoeba and ciliate sequences to the exclusion of diplomonads in the alaS tree suggests that a parabasalid was the donor eukaryotic lineage for the first of the two eukaryote-to-eukaryote gene transfers. Interestingly, the LogDet analysis places the Entamoeba and ciliate sequences as a sister clade to the diplomonads with a high bootstrap support (92%). Because all sequences in this cluster passed the test for amino acid compositional heterogeneity, the inconsistency between ML and LogDet analyses probably is explained by the absence of a model incorporating rate heterogeneity in the latter—the Trichomonas sequence represents the longest branch in the cluster and, indeed, is attracted to the root of the cluster in the LogDet analysis. Although only a few lateral gene transfers between eukaryotes have been described ( Andersson et al. 2003 Archibald et al. 2003 Bergthorsson et al. 2003), the inferred intradomain transfers should not be surprising, because both Entamoeba and ciliates are phagotrophic lineages that may ingest both microbial eukaryotes and prokaryotes. The alternative hypothesis—that both alaS versions were present in the last common eukaryotic ancestor and subsequently differentially lost—is much less likely for several reasons. Ciliates, Entamoeba, and parabasalids/diplomonads are specifically related to the apicomplexa, pelobionts, and heterolobosea, respectively ( Baldauf et al. 2000 Bapteste et al. 2002 Cavalier-Smith 2002 Simpson and Roger 2002 Baldauf 2003), which all have the “bacterial” version ( fig. 1B). Plasmodium falciparum (apicomplexa) and M. balamuthi (pelobiont) sequences were excluded from the phylogenetic analyses because of strong amino acid heterogeneity and short length, respectively (data not shown). Thus, many parallel independent losses have to be posited if the “archaeal” version were ancestral to all eukaryotes. Also, all extant eukaryotes have either the “bacterial” or the “archaeal” version of alaS—none has been found to encode both—which argues against retention of both versions in a single genome over a long evolutionary timescale, as required by an “ancient paralogy and differential loss” scenario.

Transfer of Two Unsplit Nanoarchaeota Genes in a Single Event?

A gene-transfer ratchet mechanism could explain the presence of the two archaeal genes in the eukaryotic genomes ( Doolittle 1998) the food ingested by the common ancestor of diplomonads and parabasalids may have been rich in members of the Nanoarchaeota or close relatives to the phylum, or a symbiotic relationship between such an organism and the eukaryote may have existed. Noticeably, the only described species from Nanoarchaeota lives as a symbiont with a crenarchaeon ( Huber et al. 2002 Waters et al. 2003). However, the organization of the genes in Nanoarchaeum hints that the transfer of the two tRNA synthetase genes may have occurred in a single rather than in multiple events. The N. equitansalaS gene is one of several in that genome shown to be “split” into two noncontiguous pieces ( Waters et al. 2003). Curiously, the gene corresponding to the C-terminus of alaS shows a close genetic linkage to the proS gene they are separated by only a single gene encoding a hypothetical protein in the Nanoarchaeum genome. If the ancestral unsplit alaS gene in the nanoarchaeal lineage was located in the current position of the C-terminal gene, the transfer of a single DNA fragment would be sufficient to transfer of both alaS and proS in a single event to a common ancestor of diplomonads and parabasalids. The fact that Nanoarchaeum is the only archaeal genome (among 18 full-genome sequences available from this domain) that shows such a close linkage of these two genes circumstantially supports this scenario.

A Common Ancestor of Diplomonads and Parabasalids to the Exclusion of the Root

These findings have several additional important implications. Both diplomonads ( Chihade et al. 2000) and parabasalids ( Keeling and Palmer 2000) have each been suggested, individually, to represent the deepest eukaryotic branch, and rDNA phylogenies have long depicted them as the two earliest emerging groups ( Sogin 1991). Our data indicate that none of these proposals is correct—the presence of two aminoacyl-tRNA synthetase genes of archaeal ancestry are shared derived features that distinguish them from the other eukaryotes included in the study, indicating that they share a common ancestor. Thus, the root of eukaryotes can neither lie on the branch leading to diplomonads nor lie on the branch leading to parabasalids. Although this has been proposed previously ( Embley and Hirt 1998 Cavalier-Smith 2002 Simpson and Roger 2002 Baldauf 2003 Cavalier-Smith 2003 Simpson 2003), the support from phylogenetic analyses has been relatively weak ( Henze et al. 2001 Simpson et al. 2002 Cavalier-Smith 2003 Simpson 2003). Our data do not directly bear on the phylogenetic position of the diplomonad/parabasalid group within the eukaryotes. Nevertheless, the confirmation of the specific relationship between diplomonads and parabasalids will deepen the understanding of the evolution of two important human pathogens, G. lamblia and T. vaginalis, the genomes of which will both be completely sequenced shortly. For instance, this sister group relationship suggests that hydrogenosomes, mitochondrial-derived, hydrogen-evolving energy-generating organelles in T. vaginalis and the recently discovered mitochondrial remnant organelles (mitosomes) in G. lamblia ( Tovar et al. 2003) may have common anaerobic ancestry. Indeed, because most extant archaeal lineages, including N. equitans, exist in oxygen-poor environments like those inhabited by free-living diplomonads and parabasalids, the transfers probably occurred in an anaerobic ancestor of these two protist lineages that could have already begun to lose canonical aerobic mitochondrial functions.

Ancient Gene Transfers Provide Insights into Nanoarchaeota

The phylogenies of the two transferred genes also indicate that the lineage leading to Nanoarchaeota diverged from Crenarchaeota and Euryarchaeota before the divergence between diplomonads and parabasalids. Moreover, the transfer of a continuous nanoarchaeon alaS gene to a eukaryote indicates that the presence of split noncontiguous genes—one of which is alaS—on the genome of N. equitans likely is a derived feature, rather than a reflection of the ancestral state of genes in early microbial evolution. Thus, the split N. equitans genes are probably not indicators that the lineage represents “a living microbial fossil” ( Thomson et al. 2004). Unfortunately, it remains unclear whether the divergent nature of the N. equitans sequences is a consequence of the symbiotic lifestyle of the lineage ( Boucher and Doolittle 2002) or indicates a truly ancient origin within the Archaea further phylogenomic studies are needed to confirm the phylogenetic position of Nanoarchaeota within Archaea. In any case, our results suggest that there have been mesophilic archaea that are closer relatives to Nanoarchaeota than to Crenarchaeota or Euryarchaeota because the common ancestor of diplomonads and parabasalids most likely was a mesophile ( Cavalier-Smith 2002) and physical proximity of the organisms is likely an important factor that vastly increases the probability of successful gene-transfer events. However, a transfer from a hyperthermophile to a mesophile living close to a hyperthermophilic environment cannot be excluded, and further studies are needed to clarify whether mesophilic organisms related to Nanoarchaeota still exist and wehether they live as symbionts with eukaryotes. Hopefully, further examples of interdomain lateral gene transfer discovered from genomic sequences will continue to resolve the phylogeny within prokaryotes and eukaryotes and allow us to determine the relative timing of major evolutionary events in disparate regions of the tree of life.


An avocado a day keeps your gut microbes happy, study shows

Eating avocado as part of your daily diet can help improve gut health, a new study from University of Illinois shows. Avocados are a healthy food that is high in dietary fiber and monounsaturated fat. However, it was not clear how avocados impact the microbes in the gastrointestinal system or "gut."

"We know eating avocados helps you feel full and reduces blood cholesterol concentration, but we did not know how it influences the gut microbes, and the metabolites the microbes produce," says Sharon Thompson, graduate student in the Division of Nutritional Sciences at U of I and lead author on the paper, published in the Journal of Nutrition.

The researchers found that people who ate avocado every day as part of a meal had a greater abundance of gut microbes that break down fiber and produce metabolites that support gut health. They also had greater microbial diversity compared to people who did not receive the avocado meals in the study.

"Microbial metabolites are compounds the microbes produce that influence health," Thompson says. "Avocado consumption reduced bile acids and increased short chain fatty acids. These changes correlate with beneficial health outcomes."

The study included 163 adults between 25 and 45 years of age with overweight or obesity -- defined as a BMI of at least 25 kg/m2 -- but otherwise healthy. They received one meal per day to consume as a replacement for either breakfast, lunch, or dinner. One group consumed an avocado with each meal, while the control group consumed a similar meal but without the avocado. The participants provided blood, urine, and fecal samples throughout the 12-week study. They also reported how much of the provided meals they consumed, and every four weeks recorded everything they ate.

While other research on avocado consumption has focused on weight loss, participants in this study were not advised to restrict or change what they ate. Instead they consumed their normal diets with the exception of replacing one meal per day with the meal the researchers provided.

The purpose of this study was to explore the effects of avocado consumption on the gastrointestinal microbiota, says Hannah Holscher, assistant professor of nutrition in the Department of Food Science and Human Nutrition at U of I and senior author of the study.

"Our goal was to test the hypothesis that the fats and the fiber in avocados positively affect the gut microbiota. We also wanted to explore the relationships between gut microbes and health outcomes," Holscher says.

Avocados are rich in fat however, the researchers found that while the avocado group consumed slightly more calories than the control group, slightly more fat was excreted in their stool.

"Greater fat excretion means the research participants were absorbing less energy from the foods that they were eating. This was likely because of reductions in bile acids, which are molecules our digestion system secretes that allow us to absorb fat. We found that the amount of bile acids in stool was lower and the amount of fat in the stool was higher in the avocado group," Holscher explains.

Different types of fats have differential effects on the microbiome. The fats in avocados are monounsaturated, which are heart-healthy fats.

Soluble fiber content is also very important, Holscher notes. A medium avocado provides around 12 grams of fiber, which goes a long way toward meeting the recommended amount of 28 to 34 grams of fiber per day.

"Less than 5% of Americans eat enough fiber. Most people consume around 12 to 16 grams of fiber per day. Thus, incorporating avocados in your diet can help get you closer to meeting the fiber recommendation," she notes.

Eating fiber isn't just good for us it's important for the microbiome, too, Holscher states. "We can't break down dietary fibers, but certain gut microbes can. When we consume dietary fiber, it's a win-win for gut microbes and for us."

Holscher's research lab specializes in dietary modulation of the microbiome and its connections to health. "Just like we think about heart-healthy meals, we need to also be thinking about gut healthy meals and how to feed the microbiota," she explains.

Avocado is an energy-dense food, but it is also nutrient dense, and it contains important micronutrients that Americans don't eat enough of, like potassium and fiber.

"It's just a really nicely packaged fruit that contains nutrients that are important for health. Our work shows we can add benefits to gut health to that list," Holscher says.

The paper, "Avocado consumption alters gastrointestinal bacteria abundance and microbial metabolite concentrations among adults with overweight or obesity: a randomized controlled trial" is published in the Journal of Nutrition.

Authors are Sharon Thompson, Melisa Bailey, Andrew Taylor, Jennifer Kaczmarek, Annemarie Mysonhimer, Caitlyn Edwards, Ginger Reeser, Nicholas Burd, Naiman Khan, and Hannah Holscher.

Funding for the research was provided by the Hass Avocado Board and the USDA National Institute of Food and Agriculture, Hatch project 1009249. Sharon Thompson was supported by the USDA National Institute of Food and Agriculture AFRI Predoctoral Fellowship, project 2018-07785, and the Illinois College of ACES Jonathan Baldwin Turner Fellowship. Jennifer Kaczmarek was supported by a Division of Nutrition Sciences Excellence Fellowship. Andrew Taylor was supported by a Department of Food Science and Human Nutrition Fellowship. The Division of Nutritional Sciences provided seed funding through the Margin of Excellence endowment.

The Division of Nutritional Sciences and the Department of Food Science and Human Nutrition are in the College of Agricultural, Consumer and Environmental Sciences, University of Illinois.


The Citrus Family Tree

All the oranges, lemons, limes, and grapefruits you’ve ever eaten are descendants from just a few ancient species.

Citrus, in many ways, stands alone. So many cultivated species have come from so few primary ancestors. Just three, in fact: citrons, pomelos, and mandarins, all native to South and East Asia before they started their journeys west, to places like Florida, California, and Brazil that built entire economies around fruits from the other side of the world.

Such simple lineage is the result of impressive commonality. Almost all citrus has the rare genetic combination of being sexually compatible and highly prone to mutation. Such traits allow their genes to mix, for thousands of years on their own, and eventually, at the hands of humans. The product of so much natural crossing in the wild and selective breeding at research farms and in fields is every orange, lemon, lime, and grapefruit you’ve ever eaten.

No other fruit genus can boast such pedigree, and new research is bringing clarity to the origin of citrus. Grapefruits are a human discovery, less than 300 years old. But citrus itself is ancient. Fossilized leaves discovered in China’s Yunnan Province in 2009 and 2011 suggest citrus has existed since the late Miocene epoch, as many as seven million years ago. Humans, however, have brought a great winnowing: Out of thousands of wild types, only a few dozen have become commercial behemoths like the navel orange, Eureka lemon, and Mexican lime. They’re the citrus one percent.

The scientists who study citrus love it for its appeal, its mystery, and its drama. “There’s something fascinating, freaky, even sexy about citrus,” says pomologist David Karp, whose research informs the above illustration. A bacterial disease called huanglongbing (a.k.a. citrus greening) that causes plants to defoliate, decay, and eventually die, is threatening commercial production on every arable continent, including North America, where the disease arrived in 2005.

Yet a fruit group of such illustrious history won't be exterminated so easily. The future is likely to bring more types of citrus, not fewer. “Citrus is competitive,” says citrus breeder and geneticist Fred Gmitter, explaining how global researchers race to develop, say, mandarin oranges that are sweeter, seedless, and easier to peel. “In the near future you’ll see a lot of outside-the-box new stuff.” And, an ever expanding family tree.


Mother of all citrus: Oranges, grapefruit, lemons and limes all descended from single ancestor

Oranges, grapefruit, lemons and limes are all hybrids, mixed and matched from 10 “wild” citrus species descended from a single Asian ancestor some eight million years ago, scientists said….

A global team of scientists sequenced the genomes of 60 citrus varieties to draw up a family tree going to the very root of one of the world’s best-loved fruit groups.

They traced the mother of all citrus to the southeastern foothills of the Himalayas in the late Miocene period, study co-author Guohong Wu of the US Department of Energy Joint Genome Institute told AFP.

That specimen, he said, likely resembled a present-day, inedible “papeda” — a bitter, sour fruit.

From this source emerged 10 wild or “natural” species — including the pummelo, wild mandarin, and a type of kumquat.

Some of the ten are extinct.

“All other citrus types, including the economically important cultivars (oranges, grapefruits, lemons, limes) are hybrids derived from two or more of the… 10 pure species,” Wu said by email.


Denisovans: Another Human Relative

Scientists have also found DNA from another extinct hominin population: the Denisovans. The only remains of the species that have been found to date are a single fragment of a phalanx (finger bone) and two teeth, all of which date back to about 40,000 years ago (Reich 2010). This species is the first fossil hominin identified as a new species based on its DNA alone. Denisovans are relatives of both modern humans and Neanderthals, and likely diverged from these lineages around 300,000 to 400,000 years ago. You might be wondering: If we have the DNA of Denisovans, why can’t we compare them to modern humans like we do Neanderthals? Why isn’t this article about them too? The answer is simply that we don’t have enough DNA to make a comparison. The three specimen pool of Denisovans found to date is statistically far too small a data set to derive any meaningful comparisons. Until we find more Denisovan material, we cannot begin to understand their full genome in the way that we can study Neanderthals.

Neanderthals and modern humans shared habitats in Europe and Asia

We can study Neanderthal and modern human DNA to see if they interbred with modern humans

We can study the DNA of Neanderthals because we have a large enough Neanderthal sample size (number of individual Neanderthals) to compare to humans


Similarities between plants and algae

We start with similar points between these two types of living beings. These are the main similarities between plants and algae :

  • They have chloroplasts with two membranes. The existence of the two membranes suggests that in this group the organelles that enable photosynthesis evolved from an endosymbiotic event between a primitive eukaryotic ancestor and photosynthetic cyanobacteria. The chloroplasts of plant cells have chlorophyll.
  • Chlorophytes, Rhodophytes, Glaucophytes and Embryophytes store starch as a reserve carbohydrate.
  • The mitochondria of the cells usually have flattened ridges. The mitochondria are the organelles where cellular respiration is performed , a process by which the cell consumes oxygen and organic matter in exchange for energy.
  • The cell walls are constituted by cellulose polysaccharides.
  • They perform photosynthesis . Thanks to solar energy, they fix CO2 and produce oxygen and organic matter that they will need to carry out cellular respiration and obtain energy.
  • They are autotrophic , that is, they make their organic matter from inorganic. Concept related to photosynthesis.
  • Both algae and plants can live in aquatic environments and terrestrial environments .

Author response

Summary:

The reviewers found that the paper provides significant insights into this family of receptors: First, your discovery of GRLs in multiple unicellular organisms supports the claim that you are dealing with a large family with plant homologs, although the analyses of sequence conservation remains speculative. However, the major advance results from the tertiary structures of these proteins that take advantage of the power of trRosetta to provide evidence that the GRL proteins are distant members of the same superfamily. This represents a significant advance in our understanding of the origins of this superfamily of proteins.

However, the reviewers had also two major concerns: One is the serious lack of technical details and you must provide more information about how many genomes were used in your initial search and discuss whether it was exhaustive or so stringent that more members of the family likely exist: Providing more technical details will help make the work more accessible.

We acknowledge this concern and have now provided additional technical details on the initial searches and other analyses in the Materials and methods. We further note that all code and sequence files are provided as Supplementary files, and outputs of the ab initio protein modelling are available on the Dryad repository (doi:10.5061/dryad.s7h44j15f).

We hope these efforts will clarify the search strategies taken and aid in the reproduction and extension of this work by others. Although our searches have been very broad phylogenetically, the extreme divergence in the primary sequences of these proteins and the relatively stringent criteria for retaining hits – to avoid excessive numbers of spurious matches with other polytopic membrane proteins – make it highly likely that additional members of the family exist (as we now stress in the Discussion and Materials and methods sections). In this work, we have preferred to be relatively conservative by including proteins for which several lines of evidence support their homology to insect chemosensory receptors (i.e., from amino acid sequence similarity and predicted secondary and tertiary structural analyses). Although finer scale details of the evolution of this superfamily will likely emerge in the future, we believe the current data support the central conclusion of our work (i.e., the origin of the insect chemosensory receptor superfamily in the last common eukaryotic ancestor).

The second point is that functional data would be very useful, e.g. showing biochemically that distant members behave similarly to the fly proteins, or that they serve (or not!) as ligand-gated channels. If you have already acquired this type of data, they would strengthen your paper. However, a discussion of possible molecular functions would be sufficient in the absence of such data.

We also would very much like to have functional data on these phylogenetically distant homologs, but do not have anything to add to the current manuscript. Functional characterization is far from trivial: if they are ion channels, it is unknown what ligands might gate them if they are not channels, it is not obvious how to determine what biochemical function(s) they do possess. Our planned initial approach would be reverse genetic while this is certainly conceivable for the plant proteins (using Arabidopsis thaliana as a model), for the fungal and protist species possessing GRL homologs, none are yet genetically accessible. Transgenesis was very recently reported in Spizellomyces punctatus (Medina et al., eLife 2020), raising hope that genome-editing approaches will soon be available in this species.

We have expanded the Discussion to discuss possible molecular functions of family members. While we feel that consideration of roles of unicellular eukaryotic GRLs would be pure speculation at this stage (little is known about the biology of these species), we do incorporate some further information on the plant homologs.

Reviewer #1:

Vertebrate and nematode odorant receptors (ORs) function as GPCRs, while insect ORs were derived from gustatory receptors (GRs) and function as ligand gated ion channels. However, the evolutionary origin of insect GRs is not clear. The manuscript of Benton, Dessimoz and Moi titled "A putative origin of insect chemosensory receptors in the last common eukaryotic ancestor" answered this key question. Following the previous studies that identified GR-like proteins (GRLs) in animals, and GR homologs, known as the DUF3537 domain-containing proteins in plants, they further identified and performed phylogenetic analysis on GRL proteins in unicellular eukaryotic organisms, including fungi, protists, and algae, the common ancestor of plants and animals.

Overall, the topic of this manuscript is very interesting and well written. The data are solid. Several key points have been addressed, including role of TM7, consistent predicted orientation of TM domains, presence of intracellular loops (like ORCO), conserved vs diverse regions on GRL proteins, and same origin for plant and animal GRLs. Therefore, I strongly recommend for publication, after the authors properly address the following concerns:

1) The major weakness is that there is no functional analysis. If any of GRL proteins is predicted to be a canonical chemical sensor, would it be possible to utilize Xenopus or another system to test the hypothesis?

As described above in response to the general comments, we also would very much like to have functional data on these phylogenetically distant homologs, but do not have anything to add to the current manuscript. Experimental characterization is far from trivial: if they are ion channels, it is unknown what ligands might gate them (necessitating large-scale chemical screening). If they are not channels, it is unclear how best to determine what biochemical function(s) they do possess. Our planned initial approach would be reverse genetic while this is certainly conceivable for the plant proteins (using Arabidopsis thaliana as a model), for the fungal and protist species possessing GRL homologs, none are yet genetically accessible. Transgenesis was very recently reported in Spizellomyces punctatus (Medina et al., eLife 2020), raising hope that genome-editing approaches will soon be available in this species.

2) If functional study is currently a big challenge, could the authors perhaps add some validation on GRL protein localization in a unicellular eukaryote? I wonder if antibody could be made and used to test membrane localization of GRL, or a tagged protein could be ectopically expressed in a cell line (or yeast).

While it certainly would be possible to tag these proteins with GFP and express them in a heterologous cell type, we do not think such results alone would be particularly informative. It is almost certain – based upon the secondary structure predictions – that these are integral membrane proteins, but they could potentially localize anywhere within the endomembrane system. Without validation in the endogenous cell types, it would be hard to interpret whether localization patterns are real or artefactual (due to, for example, protein over-expression, an impact of the protein tag or an influence of the heterologous cellular environment). Antibodies might be an alternative tool to assess endogenous protein localization, although there has only been very limited success for generation of effective antibodies against insect receptors moreover, this approach would require development of immunofluorescence protocols for the fungal or protist species of interest and ideally a means of validating antibody specificity (e.g., by parallel staining of genetic knock-outs of the corresponding GRL).

An early study of one of the plant proteins, A. thaliana AT4G22270, revealed that an overexpressed GFP-tagged version displayed membrane localization (Guan et al., 2009). Curiously, this study (mis)predicted the family as having four transmembrane domains and did not recognize the similarity with insect chemosensory receptors. This work also found that overexpression of AT4G22270 led to increases in the size of various plant organs, although the relevance of this phenotype (if any) remains to be confirmed by loss-of-function analysis. Nevertheless, the cellular localization may be real and we cite this work in the revised Discussion.

3) "heteromeric (probably tetrameric) complexes composed of a tuning OR, which recognises odour ligands, and a universal co-receptor, ORCO" This describes a dimeric complex with one OR and one ORCO. It seems not consistent with "probably tetrameric"

We have clarified this sentence to indicate that the tetrameric complex probably comprises two tuning OR subunits and two ORCO subunits.

4) Introduction paragraph three provides examples of non-chemosensation functions of GRL proteins. I suggest to expand and add a table or a supplemental table, which should include currently known expression patterns and functions of GR and GRL proteins in animals and plants.

To our knowledge, the work cited in this paragraph, and the revised Discussion (which incorporates further information on the plant proteins – see the comment above) encompasses all known “non-chemosensory” roles of this family. For completeness, we have now added a sentence to this paragraph on the thermosensory and light-sensing functions of D. melanogaster GR28b isoforms. At this stage, we feel that information on non-chemosensory function of members of this repertoire is simply too sparse – and the evidence for certain functions too limited – to warrant a table, which would ultimately be redundant with the information in the text.

Reviewer #2:

In this work, Benton and colleagues consider the evolutionary origin of the immense insect chemoreceptor family, which includes odorant receptors (ORs) and gustatory receptors (GRs). Past sequence mining from the Benton lab and others has suggested that distant members of the GRL family were found in diverse Protostomia and also homologous to a family of uncharacterized plant proteins containing the Domain of Unknown Function 3537. However, despite multiple GRL lineages being present in early branching deuterostomes, GRLs have been completely lost from the chordate lineage suggesting recurrent independent losses, obscuring their exact evolutionary trajectory. Here Benton and colleagues extend their genome mining analyses to identify 17 sequences from fungi, protista and unicellular plants that share the same overall topology and some of the poorly conserved sequence features of this family. Finally, they use the extraordinary power of trRosetta to predict candidate GRL structures from the diverse lineages de novo and demonstrate that they share the same distinct architecture as an experimental structure of an OR. By far the most impressive part of the manuscript is the structure prediction since it would argue that these distantly related members, even bearing little sequence conservation, fold into the same distinct helical arrangement. If correct, this would argue that the GRL family is incredibly ancient, originating in the last eukaryotic ancestor, 1.5-2 Billion years ago, which has important implications for thinking about how this immense family arose.

Overall, I have a few concerns that should be addressed:

1) The Materials and methods are quite sparse and require a lot of effort by the reader to appreciate how well controlled and vetted their results are. Only 17 members of the family were found across the genomes of fungi, protista and unicellular plants, derived from an even smaller subset of species, which the authors acknowledge is extremely sparse and implies either that they propagated by lateral gene transfer or were independently lost many times, making their evolutionary origin still a bit uncertain. The authors should provide more information about how many genomes were used in their initial search and discuss whether it was exhaustive or so stringent that more members of the family likely exist.

As described above in response to the general comments, we acknowledge this concern and have now provided additional technical details on the initial searches and other analyses in the Materials and methods. We further note that all code and sequence files are provided as Supplementary files, and outputs of the ab initio protein modelling are available on the Dryad repository (doi:10.5061/dryad.s7h44j15f).

We hope these efforts will clarify the search strategies taken and aid in the reproduction and extension of this work by others. Although our searches have been very broad phylogenetically, the extreme divergence in the primary sequence of these proteins and the relatively stringent criteria for retaining hits – to avoid excessive numbers of spurious hits with other polytopic membrane proteins – make it highly likely that additional members of the family exist (as we now stress in the Discussion and Materials and methods sections). In this work, we have preferred to be relatively conservative by including proteins for which several lines of evidence support their homology to insect chemosensory receptors (i.e., from amino acid sequence similarity and predicted secondary and tertiary structural analyses). Although finer scale details of the evolution of this superfamily will likely emerge in the future, we believe the current data support the central conclusion of our work (i.e., the origin of the insect chemosensory receptor superfamily in the last common eukaryotic ancestor).

2) One complication of the limited number of sequences from unicellular eukaryotes is that the structure prediction relies on multiple sequence alignments largely built from GRs. This was not obvious from the Materials and methods. I only know this because I took one of their putative GRL sequences and submitted it to the trRosetta website and three hours later got the same structure prediction as in Figure 3 and the MSA the trRosetta algorithm used for prediction. While the algorithm for trRosetta has been previously published, for a general audience the paper would benefit from more detail about how it was used-both what was required as input (apparently just a single sequence plugged into the trRosetta website) and how to evaluate the output, beyond physical inspection. For example, in Figure 3C the assignment of proteins to their groups seems like an arbitrary delimitation without further explanation, since the score/distances between proteins are marginally different. Only in the figure legend it states: TM-scores of 0.0-0.30 indicate random structural similarity TM-scores of 0.5-1.00 indicate that the two proteins adopt generally the same fold. The authors thus suggest a TM score of 0.27 as meaning Orco and HsapAdipoR1 are unrelated but a score of 0.53 as being indicative that VbraGRL2 and AthaAT3G20300 are part of the same structural family, but provide insufficient information to the reader to understand whether this is a stringent cutoff or not.

The reviewer raises a number of important points, which we address individually below:

- structure predictions from multiple sequence alignments (MSAs) largely built from GRs: this reviewer reiterates this issue in the comment below, where we provide a full response.

- use of trRosetta algorithm: we provide additional use and evaluation of this server in the Materials and methods. In brief, the user interface is indeed extremely simple, requiring just entry of an individual sequence, as MSAs are built automatically.

- evaluation of trRosetta output: we describe the pertinent information in Supplementary file 7 and the associated legend. The key parameter to judge the quality of the top model from trRosetta is the “estimated TM-score”. As described in the cited trRosetta paper (Yang et al., 2020), this is calculated based upon a combination of the probability of the predicted top distances and the average pairwise TM-score between the top ten models under no restraints. In test proteins of known structure, the estimated TM-score had a high correlation with the true TM-score (which is calculated based upon comparison of the model and the experimentally-determined protein structure). For proteins for which no experimental information is available (such as GRLs or DUF3537 proteins), the estimated TM-score provides a measure of predicted resemblance of the model to the real structure. While there is no firm cut-off, scores <0.17 are likely to reflect spurious protein structural models (Yang et al., 2020). In our work, as shown in Supplementary file 7, sequences that yielded MSAs with very few proteins gave commensurately extremely low estimated TM-scores (typically around 0.1) these models were not examined further. All trRosetta output files are provided in the Dryad repository (doi:10.5061/dryad.s7h44j15f).

- evaluation of trRosetta models by structure comparisons with Dali and TM-align: for all trRosetta models that had an estimated TM-score >0.17, we assessed whether these had similarity to proteins of known structure in the Protein Data Bank using the Dali server. In all but two cases (TtraGRL4 and TtraGRL5), the ORCO cryo-EM structure was identified as the top hit, usually with a Dali Z-score (a measure of structural similarity) that is substantially higher that the next most similar protein fold. The results of these Dali searches are provided inside the corresponding subfolder of the trRosetta output in the Dryad repository. The consistent retrieval of ORCO by other models of animal GRs/GRLs, protist GRLs and plant DUF3537 proteins is striking and argues these proteins all adopt a similar fold. Regarding the two exceptions: the best TtraGRL4 and TtraGRL5 models identified Diablo (a HECT-type E3 ligase) and Plectin (a cytoskeletal protein) as top hits, respectively. Although these GRL models have estimated TM scores >0.17 and the Dali Z-scores are indicative of “significant similarity” (>2 (Holm et al., 2010)), these are clearly spurious matches. We note that in both cases the number of sequences used in the MSA is very low (<230) compared to models of TtraGRL1-3 (>1200).

We further assessed structural similarity by pairwise comparisons of selected proteins (with the highest estimated TM-score) together with a negative control (AdipoR1, which has the same membrane topology as the OR/GR/GRL/DUF3537 superfamily). For Dali pairwise comparisons (top-right of Figure 3C), the Z-score is substantially higher for all comparisons within the OR/GR/GRL/DUF3537 set than with AdipoR1. Similarly, for TM-align pairwise comparisons, the OR/GR/GRL/DUF3537 comparisons all fall within the range of 0.5-1, which indicates – as described in Zhang and Skolnick NAR 2005 – that the proteins are expected to adopt the same fold (1 would be a perfect match). By contrast, comparisons with AdipoR1 fall within the range (0-0.3) indicative of spurious similarity. We tried to add these numerical ranges on the figure itself but found that it cluttered the panel and would prefer to have the full description of their meaning in the legend.

We emphasize that the cut-offs of trRosetta, Dali and TM-align are defined by the developers of these algorithms based upon analysis of many test cases of proteins of known structure. To our knowledge, these cut-offs are not stringent, and must be viewed in the context of the proteins being analyzed, as many factors could impact these scores (e.g., quality of model, quality of experimentally-determined structure, primary sequence similarity target and query, domain organization of protein (in our experience individual proteins with large inserts in the loops were often problematic)). In our work, the tertiary structural similarity provides additional support for the homology between various proteins that were initially identified based upon primary and secondary structural similarities.

To strengthen our claims, we now provide analyses of the same set of query sequences with an independent ab initio protein folding algorithm, RaptorX, which uses distance-based protein folding driven by deep learning (Kallberg et al., 2012). While this algorithm failed to build sufficiently large MSAs for slightly more queries than trRosetta, several sequences from both protists and plants successfully yielded models that, via Dali searches, retrieved the ORCO structure as the top hit. The results of this new analysis are summarized in Supplementary file 7, and the complete output files from RaptorX, together with the results of the subsequent Dali searches, are provided in the Dryad repository (doi:10.5061/dryad.s7h44j15f).

We hope to have explained the logic of software use, our steps for quality control at each stage and the availability of the source data to allow readers to view and reproduce our results. As we are users, not testers, of the software packages, we felt it out-of-place to have a detailed description of these published algorithms in our work, but we have added additional technical details in this revision to enable a reader to appreciate our procedures for assessing the structure prediction results.

3) One important caveat that the authors should discuss and address is that given that the de novo structure prediction relies heavily on GR sequence covariation, is there any possibility that tertiary structural similarity is imposed onto these more distant members of the GRL family? Ideally the de novo structure prediction would be truly independent and based on similar numbers of GRL sequences from single-celled eukaryotes but this does not seem possible.

This is a very good point: at present, there are indeed insufficient numbers of GRL sequences from unicellular eukaryotes alone to be able to analyze amino acid co-evolution and use this information for modelling. The current models therefore necessarily depend in part upon covariation within the larger animal GR/GRL family. At the level of the global fold, this is only problematic if the query sequence is not homologous to the sequences in the alignment. We believe that the primary and secondary sequence analyses and phylogenetic analysis (in Figure 1, Figure 1—figure supplement 1, Figure 2) do support such homology, notably for the protist GRLs for which we have obtained structural models.

Importantly, the models of the plant proteins used information extracted from alignments of only other DUF3537 family members, because these are more divergent from the animal sequences than those of unicellular eukaryotes. It is therefore striking that the plant structural models are also similar to ORCO, and infer that the entire family is likely to share the same global fold. We briefly mentioned these issues in our original manuscript but have now expanded our comments on these points in the text.

4) The central advance of this study over past work from the Benton lab (Benton, 2015 Hopf et al., 2015) is the dramatic improvement in structure prediction algorithms, which provide tantalizing information about structural similarity (barring the caveat in the point directly above.) I appreciate that the authors don't overstate their claims, suggesting that these GRL proteins may not serve the same function in different organisms but likely form ligand gated channels. To really move into novel territory, I wish the authors could probe the functional or biochemical properties of these ancient GRLs a bit further. For example, for these proteins to serve as ion channels likely requires a multimeric organization. Native gels could biochemically demonstrate this, providing powerful additional evidence that these are part of the same family. Alternatively, could sequence covariation provide evidence for this (e.g. Hopf, 2014). Either way, it would be valuable to discuss this additional feature that does not immediately fall out of the trRosetta predictions.

As described above in response to the general comments, we feel it is premature to begin to assess biochemical properties of these proteins without first some hint of their in vivo role, which in turn requires genetic analysis. It is currently hard also to extract further insights from patterns of amino acid covariation for the protist and fungal GRLs alone because there are too few sequences available.

We have made some preliminary analysis of the plant proteins, by overlaying the degree of amino acid conservation on the predicted structure but this was not particular informative: in contrast to the animal proteins, the plant family has quite high amino acid identity throughout its length and this analysis did not highlight particularly conserved regions (in 3D space) that might indicate functional domains. Moreover, in contrast to ORs, for which there is good (albeit mostly indirect) evidence of heteromeric complex assembly between tuning ORs and ORCOs, we currently do not know if and how DUF3537 proteins may form multimeric complexes. As it is not trivial to distinguish contacts that may be involved in monomer folding versus those involved in potential intersubunit contacts (as described in Hopf et al., eLife 2014), we feel it is premature to attempt to draw conclusions about complex formation from sequence analysis alone at this stage. If such intersubunit interactions exist, we suspect they are slightly different from those reported in ORCO. The cryo-EM ORCO structure revealed that the major interaction interface was within cytoplasmic domain (the “anchor” domain (Butterwick et al., 2018)) comprising cytosolic regions of TM4, TM5, TM6 and TM7a notably, all of the plant proteins have a cytoplasmic insertion of ∼50 amino acids in this region in IC3 (between TM6 + TM7a).

Reviewer #4:

Benton et al. is a well written study on the evolution of insect chemosensory receptors that uses bioinformatics-based approaches to identify putative GRL homologs in several species of unicellular eukaryotes. Both sequence and structure-based approaches are utilized to buttress the authors arguments that fungal and protista GRL homologs are an evolutionary link to DUF3537 proteins they have previously identified in plants and algae thereby extending this evolutionary relationship to "the last common eukaryotic ancestor"

While I am generally supportive of the authors rationale and recognize they have been careful to appropriately qualify their hypothesis throughout this work, I am somewhat disinclined to place a high degree of definitive value on the ab initio structural predictions which underscores much of this analysis. Even so, and despite the fact these evolutionary relationships between animal and plant GRLs are unlikely to ever be definitively tested, this hypothesis seems to me to be reasonable. That said, I remain underwhelmed by their significance.


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