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break. Evolutionary rates. Reference: Dan ’ s book chapter 4. Evolutionary rates - history. The first to suggest using DNA and proteins to investigate evolutionary history. (They discussed molecular evolution before the genetic code was established). Linus Pauling (1901-1994).

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slide2

Evolutionary rates

Reference: Dan’s book chapter 4

slide3

Evolutionary rates - history

  • The first to suggest using DNA and proteins to investigate evolutionary history.
  • (They discussed molecular evolution before the genetic code was established).
slide4

Linus Pauling (1901-1994)

  • The only person ever to receive two unshared Nobel Prizes—for Chemistry (1954) and for Peace (1962).
  • His introductory textbook General Chemistry, revised three times since its first printing in 1947 and translated into 13 languages, has been used by generations of undergraduates.
slide5

Linus Pauling (1901-1994)

  • Also wrote popular science books, e.g., “How to Live Longer and Feel Better”, and “Vitamin C and the Common Cold”.
  • Published over 1,000 articles and books.
  • Used to protest against nuclear testing.
slide6

Linus Pauling (1901-1994)

  • He received a Ph.D. in chemistry and mathematical physics from California Institute of Technology (Caltech) in 1925 (age 24).
slide7

Evolutionary rates

Rate is distance divided by time. Distance is number of substitutions per site. Time is in years. The time must be doubled, because the sequences evolved independently.

d

slide8

Evolutionary rates

This formula is not accurate for closely related taxa, in which polymorphism must be taken into account (Takahata and Satta 1997).

slide9

Mean Rate of Nucleotide Substitutions in Mammalian Genomes

~10-9

Substitutions/site/year

Evolution is a very slow process at the molecular level (“Nothing happens…”)

slide10

Sequence alignments

Alignment is needed for phylogeny and for molecular evolution. We will assume that the alignment is given.

How to construct alignment is outside the scope of this course.

slide11

Synonymous vs. nonsynonymous substitutions

For most proteins, it is observed that the rate of synonymous substitutions (silent substitutions) is much larger than the nonsynonymous rate (amino-acid modifying substitutions).

UUU -> UUC (both encode phenylalanine ): synonymous

UUU -> CUU (phenylalanine to leucine): nonsynonymous

slide12

A lot

A little

empirical findings
Empirical findings:

Important proteins evolve slower than unimportantones.

slide19

Insulin

1953, Frederick Sanger determines the amino-acid sequence of insulin.

This is the FIRST protein whose amino-acid sequence was determined.

It demonstrated that insulin is comprised of only L-amino acids.

slide20

Insulin

Insulin was characterized to be composed of two chains (A&B), linked together by S-S bonds.

21 AA

30 AA

slide21

Insulin

  • How is the 2 chain protein synthesized?
  • Donald Steiner (University of Chicago) gave the answer.
  • He studied an islet-cell adenoma of the pancreas, a rare human tumor producing large amounts of insulin.
slide22

Adenoma

  • Adenoma is a benign tumor (not a malignant tumor). Benign in English = harmless
  • Benign tumor: A tumor that does not recur locally and does not spread to other parts of the body.
  • Adenoma is from a glandular (i.e., from a gland) origin.
  • Adenomas can grow from many organs including the colon, adrenal, pituitary, thyroid.
slide23

Insulin

  • He sliced the pancreatic tumor and incubated it with tritiated leucine and then analyzed it.
  • He found a new protein that was later proven to be the biosynthetic precursor of insulin, the proinsulin.
slide24

Insulin

  • Proinsulin has 30 residues that are absent from insulin.
slide26

Insulin

  • There is even a former form of proinsulin, called preproinsulin. It contains additional 19 AA at the N-terminus. This 19 AA hydrophobic stretch directs the preproinsulin to the ER.
  • Preproinsulin -> Proinsulin (ER membrane)
  • From the ER it moves on to the Golgi and then to secretory granules.
  • Proinsulin -> Insulin (Granules)
slide27

Alignment of preproinsulin

Xenopus MALWMQCLP-LVLVLLFSTPNTEALANQHL

Bos MALWTRLRPLLALLALWPPPPARAFVNQHL

**** : **.*: *:..* :. *:****

Xenopus CGSHLVEALYLVCGDRGFFYYPKIKRDIEQ

Bos CGSHLVEALYLVCGERGFFYTPKARREVEG

***************:******* :*::*

Xenopus AQVNGPQDNELDG-MQFQPQEYQKMKRGIV

Bos PQVG---ALELAGGPGAGGLEGPPQKRGIV

.**. *********

Xenopus EQCCHSTCSLFQLENYCN

Bos EQCCASVCSLYQLENYCN

*****.***:*******

empirical findings30
Empirical findings:

Functional regions evolve slower than nonfunctionalregions.

slide32

Clotting – The end reaction

thrombin

fibrinogen fibrin

slide36

Synonymous vs. nonsynonymous substitutions

Histone H4 between human and wheat: excess of synonymous substitutions

slide37

Mean nonsynonymous rate

0.74  0.67 (10-9 substitutions per site per year)

Mean synonymous rate

3.51  1.01 (10-9 substitutions per site per year)

slide38

The coefficient of variation is an attribute of a distribution: its standard deviation divided by its mean

Coefficient of variation of nonsynonymous rate

91%

Coefficient of variation of synonymous rate

29%

slide39

Transition vs. transversion rates

Ratio

1.5

4.4

1.1

Degeneracy class

4

2

0

slide43

Ka/Ks

  • Our goal is to be able to compare two (or later, more) sequences and to compare the rate of neutral evolution (determined by the synonymous rate) with than of the non-synonymous rate.
  • The lower the ratio of non-synonynous substitutions to synonymous ones, the higher the intensity of the purifying selection.
slide44

Computing synonymous and non-synonymous rates

p-distance of synonymous subs. = 3/6

p-distance of nonsynonymous subs. = 3/6

3

3

Problematic: p-distance does not correct for multiple substitutions…

Solution: compute the JC correction to the p-distance.

slide45

Computing synonymous and non-synonymous rates

Assume a protein without selection (evolving neutrally).

CAA (Gln)

GAA (Glu)

TAA (Stop)

AAC (Asn)

ACA (Thr)

AAG (Lys)

AAA (Lys)

AGA (Arg)

AAT (Asn)

ATA (Ile)

The random chance of a synonymous substitution is much smaller than the chance of a nonsynonymous one.

slide46

Computing synonymous and non-synonymous rates

Assume a protein without selection (evolving neutrally).

ACA (Thr)

CCA (Pro)

TCA (Ser)

GCC (Ala)

GAA (Glu)

GCG (Ala)

GCA (Ala)

GGA (Gly)

GCT (Ala)

GTA (Val)

This is also different for different codons.

slide47

Computing synonymous and non-synonymous rates

So when one “observe” 6 times more nonsynonymous substitutions than synonymous ones – does it indicate that the protein is under purifying selection???

We must normalize for the potentials for silent vs. non-silent mutations of the codons in question.

nei gojobori 1986 method
Nei & Gojobori (1986)method

Masatoshi Nei

Takashi Gojobori

slide50

Counting synonymous sites

Consider a particular position in a codon (j=1,2,3). Let fj be the fraction of synonymous changes at this site.

slide51

In TTT (Phe), the first two positions are nonsynonymous, because no synonymous changes can occur in them, and the third position is 1/3 synonymous and 2/3 nonsynonymous because one of the three possible changes is synonymous.

slide52

Counting synonymous sites

Let s be the number of synonymous sites for each codon. s is in fact, the proportion, out of 3, of synonymous substitutions, assuming equal probability for each type of substitution.

For this example, s = 1/3.

slide53

Counting synonymous sites

Let n be the number of non-synonymous sites for each codon. n is in fact, the proportion, out of 3, of non-synonymous substitutions, assuming equal probability for each type of substitution.

For this example, n = 2+2/3.

slide54

Counting synonymous sites

Assume we have r codons (3r sites). Let si and ni be s and n for the i’th codon. We define:

slide55

Classification of sites

S is in fact, the proportion, out of 3r, of synonymous substitutions, assuming equal probability for each type of substitution.

slide56

Classification of sites

We have two sequences

ACG CCG ATT

ATG CCT CTA

S for these two sequences, will be the average S of the 2 sequence. The same goes for N.

slide57

Counting synonymous substitutions

So far we have counted the potential for synonymous and nonsynonymous substitutions. Now we wish to count the actual number of synonymous and nonsynonymous substitutions.

slide58

Counting synonymous substitutions

For two codons that differ by only one nucleotide, the difference is easily inferred.

GTC (Val)  GTT (Val) synonymous

GTC (Val)  GCC (Ala) nonsynonymous.

slide59

Counting synonymous substitutions

We define sd and nd to be the number of synonymous and nonsynonymous substitutions per codon.

GTC (Val)  GTT (Val) sd = 1, nd = 0

GTC (Val)  GCC (Ala) sd = 0, nd = 1

slide60

Counting synonymous substitutions

For two codons that differ by two or more nucleotides, the estimation problem is more complicated, because we need to determine the order in which the substitutions occurred.

slide61

Pathway (1) requires one synonymous and one nonsynonymous substitutions, whereas pathway (2) requires two nonsynonymous substitutions.

slide62

If there are 3 differences between two codons, there are 6 possible paths.

ABC  XYZ

A changed first, B second and finally C.

A changed first, C second and finally B.

B changed first, A second and finally C.

B changed first, C second and finally A.

C changed first, A second and finally B.

C changed first, B second and finally A.

slide64

The unweighted method:Average the numbers of the different types of substitutions for all the possible scenarios. For example, if we assume that the two pathways are equally likely, then the number of nonsynonymous substitutions is (1 + 2)/2 = 1.5, and the number of synonymous substitutions is (1 + 0)/2 = 0.5.

slide65

The weighted method. Employ an a priori criteria to assign the probability of each pathway. For instance, if the weight of pathway 1 is 0.9, and the weight for pathway 2 is 0.1, then the number of nonsynonymous substitutions between the two codons is (0.9  1) + (0.1  2) = 1.1, and the number of synonymous substitutions is 0.9.

slide67

Counting synonymous sites

Assume we have r codons (3r sites). Let

and be sd and nd for the i’th codon. We define:

Total number of “observed” substitutions

slide68

Counting synonymous substitutions per synonymous sites

We define p-distances for each type of substitution:

These distances, are than corrected using the JC formula:

slide69

Three types of selection

If dn < ds purifying selection

If dn = ds  neutral evolution

If dn > ds  positive selection

slide72

Generation time and genomic evolution in primates

Vincent M. Sarich & Allan C. Wilson

Science vol 179: 1144-1147 (1973).

A primate

slide73

Some background on Primates

New world monkeys

(Platyrrhines)

Haplorhines

(Higher primates)

Gibbons

Hominidae

Catarrhines

Old world monkeys

Tarsiers

Prosimians

(Strepsirhines)

http://www.whozoo.org/mammals/Primates/primatephylogeny.htm

slide74

Some background on Primates

  • Primates: 233 species and 13 families
  • The smallest living primate is the pygmy marmoset (NW monkey), which weighs around 70 g; the largest is the gorilla, weighing up to around 175 kg.

http://animaldiversity.ummz.umich.edu/site/accounts/information/Primates.html

slide75

Some background on Primates

  • Most primate species live in the tropics or subtropics, although a few, most notably humans, also inhabit temperate regions.
  • Except for a few terrestrial species, primates are arboreal. Some species eat leaves or fruit; others are insectivorous or carnivorous.

Arbor = tree in Latin

slide77

Great apes

Hominidae is the primate family, which includes the extant species of humans, chimpanzees, gorillas, and orangutans, as well as many extinct species.

The members of the family are called hominids. The family is also called “great apes”.

slide78

Great apes

Originally non-human great apes were called Pongidae. However, this original definition suggests that Pongidae is a monophyletic family – which is not the case.

slide79

Many studies have showed a correlation between time of divergence and amount of evolutionary (molecular) distance:

Protein sequences of species that diverged earlier, show more differences.

p-dist

time

slide80

There’s a big disagreement if time should be measured in terms of astronomical time (i.e., years) or generation length.

slide81

The generation-time-hypothesis:

The number of substitutions is proportional to the number of generations.

A (human)

O

B (tree shrew)

Prediction:

Short generation  More generations since divergence  More substitutions (in B)

slide82

Absolute rates of evolution demand knowledge of divergence dates (from the fossil record).

However, relative rates of evolution can be computed from the phylogeny…

This will be done using the “relative rate method”.

slide83

Assume 3 taxa, A, B and C.

A (human)

O

B (tree shrew)

C (outgroup)

T1

T2

slide84

BO > AO BO+OC > AO+OC BC > AC

Assume 3 taxa, A, B and C.

slide85

Assume 3 taxa, A, B and C.

The generation time hypothesis predicts:

BO > AO BO+OC > AO+OC BC > AC

In words, the distance of species with short generation time from an outgroup, should be higher compared to species with longer generation time.

slide86

Assume 3 taxa, A, B and C.

They used (C) modern carnivore species as their outgroup.

slide87

The authors compared immunological distances between a few species and carnivore species.

The distance between Homo sapiens and each one of 4 carnivore species was computed, and they reported the average.

The 4 carnivore species are: Hyaena, Genetta, Ursus, and Arctogalida.

slide89

Genetta genetta (small-spotted genet)

Although catlike in appearance and habit, the genet is not a cat but a member of the family Viverridae.

Genets were kept as pets by the ancient Egyptians as they are today by Berbers in North Africa. From the Greek empire to the Middle Ages, the genet was kept as a rat catcher and was often portrayed on tapestries of the period. The domestic cat eventually replaced the genet, probably because it is more efficient in killing rats-and perhaps because it is less smelly.

slide90

Results:

Immunological distances from carnivore species:

Homo sapiens 162

Macaca mulatta (rhesus monkey) 166

Ateles geoffroyi (spider monkey) 149

Nycticebus coucang (slow loris) 125

Lemur fulvus (brown lemur) 135

Tarsius spectrum (tarsier) 137

Tupaia glis (tree shrew) 156

slide91

Results:

Immunological distances from carnivore species:

Homo sapiens 162

Macaca mulatta (rhesus monkey) 166

Ateles geoffroyi (spider monkey) 149

Nycticebus coucang (slow loris) 125

Lemur fulvus (brown lemur)135

Tarsius spectrum (tarsier) 137

Tupaia glis (tree shrew) 156

Prosimian

slide92

India, Malaysia, Sumatra, Java, Borneo, Philippines

Nycticebus coucang (slow loris)

Life span is 20 years (generation time < 20 years). Nocturnal and arboreal, they spend the day sleeping in a tight ball up a tree.

slide93

These results are against the generation-time hypothesis…

Homo sapiens 162

Macaca mulatta (rhesus monkey) 166

Ateles geoffroyi (spider monkey) 149

Nycticebus coucang (slow loris) 125

Lemur fulvus (brown lemur) 135

Tarsius spectrum (tarsier) 137

Tupaia glis (tree shrew) 156

No correlation of distances with generation length, for homo-prosimians

Prosimian

slide94

Results:

Immunological distances from carnivore species:

Homo sapiens 162

Macaca mulatta (rhesus monkey) 166

Ateles geoffroyi (spider monkey) 149

Nycticebus coucang (slow loris) 125

Lemur fulvus (brown lemur) 135

Tarsius spectrum (tarsier) 137

Tupaia glis (tree shrew) 156

Scandentia

slide95

Common tree shrew - TUPAIA GLIS

Order: Climbing Mammals (Scandentia)Family: Tupaiidae.

slide96

Common tree shrew - TUPAIA GLIS

This small order of tree shrews was at one time placed in the midst of controversy: is it a primate (order Primates) or an insectivore (order Insectivora).

For several years, different groups placed the tree shrews in either one of these orders. Finally, in 1984 this issue was resolved when they were placed in their own order, called Scandentia. Some researchers still argue that they are the most primitive form of the primates, however.

slide97

Tarsius spectrum(tarsier)

Although data are not available on the lifespan of this species, another member of the genus, T. syrichta, is reported to have lived 13.5 years in captivity. Tarsius spectrum is likely to have a similar maximum lifespan.

slide98

Results:

Immunological distances from carnivore species:

Homo sapiens 162

Macaca mulatta (rhesus monkey) 166

Ateles geoffroyi (spider monkey) 149

Nycticebus coucang (slow loris) 125

Lemur fulvus (brown lemur) 135

Tarsius spectrum (tarsier) 137

Tupaia glis (tree shrew) 156

No correlation of distances with generation length. Homo has the longest, tree shrew, the shortest.

slide100

An evolutionary experiment

Spalax ehrenberghi

slide103

The structural protein composing the lens is called α-crystallin.

It is composed of two subunits, αA and αB.

Each subunit is a single-copy gene located on a different chromosome.

The two subunits have approximately 57% sequence homology, probably reflecting ancient gene duplication.

They also have low sequence similarity to heat-shock proteins (possible origin of family).

slide104

In Spalax, aA-crystallin lost its functional role more than 25 million years ago, when the mole rat became subterranean and presumably lost use of its eyes.

slide105

The aA-crystallin of Spalax evolves 4 times faster than the aA-crystallins in other rodents, such as rats, mice, hamsters, gerbils and squirrels. Functional relaxation.

The aA-crystallin of Spalax evolves 5 times slower than pseudogenes. It is still functional.

slide106

The aA-crystallin of Spalax possess all the prerequisites for normal function and expression, including the proper signals for alternative splicing.

The aA-crystallin of Spalax was shown to still be present in the rudimentary lens of the mole rat. Functional.

slide107

Explanation 1:

There is good evidence that the rudimentary eye, though not able to detect light anymore is still of vital importance for photoperiod perception, which is required for the physiological adaptations of the animal to seasonal changes.

slide108

Explanation 2:

The blind mole rat lost its vision more recently than 25 million years ago. The rate of nonsynonymous substitutions after nonfunctionalization has been underestimated.

Contradicting evidence:

The aA-crystallin gene is still an intact gene as far as the essential molecular structures for its expression are concerned.

slide109

Explanation 3:

The aA-crystallin-gene product serves a function unrelated to that of the eye.

Supporting evidence:

1. aA-crystallin has been found in other tissues.

2. aA-crystallin also functions as a chaperone that binds denaturing proteins and prevents their aggregation.

3. The regions within aA-crystallin responsible for chaperone activity are conserved in the mole rat.