The echidna rhodopsin sequence

The sequencing of the echidna rhodopsin gene sequence was successful. Table 7 shows the genomic DNA (gDNA) and complementary (cDNA) sequence, and Figure 15 shows the protein-coding amino acid sequence with amino acids differing from bovine rhodopsin highlighted in green.

Exons are highlighted in red.

1

gDNA

ATGAATGGGA

CGGAGGGCCA

GGACTTTTAC

ATCCCCATGT

CCAATAAGAC

GGGGATTGTC

cDNA

ATGAATGGGA

CGGAGGGCCA

GGACTTTTAC

ATCCCCATGT

CCAATAAGAC

GGGGATTGTC

gDNA

AGGAGTCCCT

TTGAGTATCC

CCAGTATTAC

CTGGCAGAGC

CATGGCAGTA

CTCGGTCCTC

cDNA

AGGAGTCCCT

TTGAGTATCC

CCAGTATTAC

CTGGCAGAGC

CATGGCAGTA

CTCGGTCCTC

gDNA

GCTGCGTATA

TGTTCATGCT

CATCATGCTG

GGGTTCCCCA

TCAACTTCCT

CACGCTGTAC

cDNA

GCTGCGTATA

TGTTCATGCT

CATCATGCTG

GGGTTCCCCA

TCAACTTCCT

CACGCTGTAC

gDNA

GTCACCATCC

AGCACAAGAA

ACTCCGCACC

CCTCTCAACT

ACATCCTCCT

GAACCTGGCA

cDNA

GTCACCATCC

AGCACAAGAA

ACTCCGCACC

CCTCTCAACT

ACATCCTCCT

GAACCTGGCA

gDNA

TTTGCCAACC

ACTTCATGGT

GTTGGGTGGT

TTCACCACAA

CCCTGTATAC

TTCCCTGCAT

cDNA

TTTGCCAACC

ACTTCATGGT

GTTGGGTGGT

TTCACCACAA

CCCTGTATAC

TTCCCTGCAT

360

gDNA

GGCTACTTTG

TTTTTGGACC

TACGGGCTGC

AACATCGAAG

GCTTCTTTGC

CACACTGGGA

cDNA

GGCTACTTTG

TTTTTGGACC

TACGGGCTGC

AACATCGAAG

GCTTCTTTGC

CACACTGGGA

gDNA

GGTAAGTTTC

CTCCAGGAGT

CCCCCTAGGA

GACGCTCTCC

TGGGCTATGA

CTTTTTTCCT

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CCTGAAGGGA

GAGGAAAGAT

GTCAGCACCT

CCTCCCCACC

TGGGTAGGCC

GCCTTGCCGG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CGGAAGTCAT

TTTCGAGCTA

ATACCGAGAA

GAGGCTGCTT

TGGCTAATAC

TGGGGACCGA

cDNA

---------

---------

---------

---------

---------

---------

gDNA

GGTCACAGCA

GATCGGGTCA

GTCACTCCAG

AGTCTCTGTC

CCACTCAGCC

CTGGCCCTTT

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CTCTTGGAAT

TCTGAGTCTT

TTGGAAGGAG

AGTGCGGGCC

CCGAGATGAG

GACTGTTAAT

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CGTTAACAGA

GAATGGCAGA

GACCAGCCTG

AGGCCTCCGA

GCAGGAGGTC

TTGTGGGATC

cDNA

----------

----------

----------

----------

----------

----------

gDNA

TGAGGGCAGG

GAGGACAGAA

ATATGGCACT

GGGGCGGAGA

GGGAGGCAGG

TCACCTTCTG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

TTTGGCACCC

AAGTCTCTGG

TAAGGAGTAT

GGGGTTCAGG

GAAGCCATCA

GGGAGCACAC

cDNA

----------

----------

----------

----------

----------

----------

gDNA

AGAGGCTTGG

AGTCTGACCC

CATTCTGCCA

CAAGCTTCCC

TTAAATGAGT

TCCTCGACCT

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CTCTGCCCTT

CAGTTTGTCC

ACTGAGACTG

GGGTGGGGAG

AGAGACCCAG

GGGAGCAGAC

cDNA

----------

----------

----------

----------

----------

----------

gDNA

ACCTCAAAAC

ATGAAGTTCC

ATTATCAATC

CTAAAACCGC

CCTGAGAGTC

TAAATCAGGG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

GAGATTGGGA

GAGGTTGCCC

TTTTGTTCTG

GACCTGTAGC

TTCCCCAAGG

ATATCGCTAT

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CTGGGGCAGG

AACCTATGGC

TCTTGCCTCA

GCTCAACCTC

CTGCTCCTGC

AGCCAGAGTG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

GGAGCCTGGC

ATGGGACAGG

GACGGTGTCT

GATCTGATGA

GCTGGTATCT

ACCCCCGCAC

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CTTAGCCCAG

TGCTTTGGCA

CACATGAGCA

CTAAATAGAT

ACCCTAACTA

GCTTTGTGTC

cDNA

----------

----------

----------

----------

----------

----------

1266

gDNA

TTGCAGGTGA

GATTGCGCTC

TGGTCTCTGG

TGGTGTTGGC

TATCGAGCGG

TATATCGTGG

cDNA

-----GGTGA

GATTGCGCTC

TGGTCTCTGG

TGGTGTTGGC

TATCGAGCGG

TATATCGTGG

gDNA

TCTGCAAGCC

TATGAGCAAC

TTCCGGTTTG

GGGAGAACCA

TGCCATCATG

GGTGTGACTT

cDNA

TCTGCAAGCC

TATGAGCAAC

TTCCGGTTTG

GGGAGAACCA

TGCCATCATG

GGTGTGACTT

1434

gDNA

TCACTTGGAT

CATGGCCCTG

GCCTGTGCCT

TCCCCCCACT

CGTTGGCTGG

TCCAGGTACA

cDNA

TCACTTGGAT

CATGGCCCTG

GCCTGTGCCT

TCCCCCCACT

CGTTGGCTGG

TCCA------

gDNA

GGAGCTGCCT

GAAACCTGCT

CAGTAGCCCA

AGGGAAAGCC

CTGAAATGCC

AGGAGGAGGA

cDNA

----------

----------

----------

----------

----------

----------

gDNA

ACTCAGAGGG

GTTGGGATGG

GAGGGCATCC

TCAACTGTGC

CAGTGACGAA

GCTAGGTCTG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CCAGGGTACC

TGCTCCCCTT

CTTCAACTTG

GCTTTTCCCT

AATCCTTAGC

TAACCTGGGG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

TTTCAAGTCA

AGCATCTTGA

ACAGAGCTAC

CCAAATCCTC

TGATGCAGCG

CTCCCATTGA

cDNA

----------

----------

----------

----------

----------

----------

gDNA

TATTGACCAT

GAGTTCTCCG

AGCCCATGGA

GATGGGGAGA

GATCACGTCT

CTGGAATTGG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

TGTTTGACAG

TGGGGAAATG

GCAGCTGTGG

AGGTGGTGTG

AGTTGGGAGT

GTCATTTGTT

cDNA

----------

----------

----------

----------

----------

----------

gDNA

TTAAAGAGAA

CAACCATAAT

AAAAATGACA

TTTGTTAAGC

GCTCTTTCTG

TGCCAAGCAC

cDNA

----------

----------

----------

----------

----------

----------

gDNA

TGTACTAAGC

GCTGGGGTAG

GTACAGGATA

ATCAGGTTAG

GCACAGTCCC

TGTCCCACCT

cDNA

----------

----------

----------

----------

----------

----------

gDNA

GGGATGAAGA

GTCTAAGTGG

AGGGGACTAT

TCATCCATAA

AGGTGTTTAG

TCCTGCTGAG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

GTGCAAAGAA

GTTCAGTGAC

TTGCTTAAAG

TCACACAGCA

GGCAGGTGGC

AGCTCTGGGA

cDNA

----------

----------

----------

----------

----------

----------

gDNA

TTAGAACCCA

GGTCCTCTGA

CTTCTAGTCT

GGTGCTCTCT

CCACTAAGCC

ACACTGCTTC

cDNA

----------

----------

----------

----------

----------

----------

gDNA

TCCCAGCTCT

AAAGGGTGAT

TAGAGAATCC

TTGGGCCAGA

GGAATCTCCC

TCAGCAGATT

cDNA

----------

----------

----------

----------

----------

----------

gDNA

GTCTCCACTT

CAGCCTCCAG

CAAAGCTATC

CCAGCCTCAG

CAGGCACCAA

CATGCCTGAC

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CAACTGTCAA

GAAGATTCTA

CACCCTCTCC

CGGGGATCTG

TCATAGCTAA

GGAATACCAG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

ATCTCTTCTG

CAGTCGAAGC

CCATGCCTTG

ATCAAAAGCT

GTTCCCCTTC

CTCCTTACAG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

AAAGTCTAAA

CCCATCATAT

AATCTTTAGG

TTGAATGCCT

CCAATATGCC

CTCTTTGCCA

cDNA

----------

----------

----------

----------

----------

----------

gDNA

ATCTCCTCAC

ACATCTACCT

AGGGGGGCTG

CTAAATGGTA

ATGCGGTCAA

TCTGTCTGCA

cDNA

----------

----------

----------

----------

----------

----------

2461

gDNA

GATATATCCC

CGAGGGTATG

CAGTGTTCGT

GTGGGATTGA

CTACTACACT

CTCAAACCTG

cDNA

GATATATCCC

CGAGGGTATG

CAGTGTTCGT

GTGGGATTGA

CTACTACACT

CTCAAACCTG

gDNA

AGGTCAACAA

TGAGTCCTTT

GTCATCTACA

TGTTTGTGGT

TCACTTCACC

ATCCCAATGA

cDNA

AGGTCAACAA

TGAGTCCTTT

GTCATCTACA

TGTTTGTGGT

TCACTTCACC

ATCCCAATGA

2628

gDNA

CAATCATTTT

CTTCTGCTAC

GGCCGCCTGG

TCTTCACTGT

CAAAGAGGTG

AGCAAACCGT

cDNA

CAATCATTTT

CTTCTGCTAC

GGCCGCCTGG

TCTTCACTGT

CAAAGAG G--

----------

gDNA

CTCACGTGCA

TCTACCTGGG

GAGATTGGTT

CTGGTGTTCT

CTGCTGGCCT

AGCCCCTTTC

cDNA

----------

----------

----------

----------

----------

----------

2760

gDNA

CTCAACTGCT

CCCCTCACGA

TTTCCTGCCT

GACCATCCCT

CTCTGCCCCC

CATTTTAGGC

cDNA

----------

----------

----------

----------

----------

---------C

gDNA

TGCAGCCCAG

CAGCAGGAGT

CCGCCACCAC

GCAGAAAGCT

GAGAAGGAAG

TCACCCGCAT

cDNA

TGCAGCCCAG

CAGCAGGAGT

CCGCCACCAC

GCAGAAAGCT

GAGAAGGAAG

TCACCCGCAT

gDNA

GGTGATCATC

ATGGTCATTG

CTTTCCTGAT

CTGCTGGGTG

CCCTACGCCA

GTGTGGCATT

cDNA

GGTGATCATC

ATGGTCATTG

CTTTCCTGAT

CTGCTGGGTG

CCCTACGCCA

GTGTGGCATT

gDNA

CTACATCTTC

ACACACCAGG

GATCAAACTT

CGGCCCCATC

TTCATGACTG

CCCCGGCTTT

cDNA

CTACATCTTC

ACACACCAGG

GATCAAACTT

CGGCCCCATC

TTCATGACTG

CCCCGGCTTT

2998

gDNA

CTTTGCCAAG

AGTTCTGCGA

TCTACAACCC

AGTCATCTAC

ATTATGATGA

ACAAGCAGGT

cDNA

CTTTGCCAAG

AGTTCTGCGA

TCTACAACCC

AGTCATCTAC

ATTATGATGA

ACAAGCAG--

gDNA

AACCGAGAGC

GTGTCTGGTT

TGTCCTTACA

TATAAGTTAA

GGTGCGGCAA

GAGCCCCCAG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CAGGCCGGGG

GGCGGGGGGG

AGGCAGGCAG

ATTCAATCAG

TCAATGGCAT

TTATCTAGTT

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CTTGCTTATG

GTGGGCAGAG

TACTGGCCTG

AGCGTGTGGG

AAAATCCAAT

ACAATGGGGC

cDNA

----------

----------

----------

----------

----------

----------

gDNA

AGGTAGATGT

GATCCCTGCC

CCCAAGGAGC

TTACAGTCTA

GAGGGTCTAA

GTGGGTAGGG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CAGGACAAGA

GTCTCGGAAG

GGCCCAGCCA

ATCGGCATGA

GGTAACAGGG

CCCCAAAAGT

cDNA

----------

----------

----------

----------

----------

----------

gDNA

TGGGAGACAG

GGGTTCTGGT

CTCCGTCCCT

CTTCCAGCTT

TGGTCCCCTC

TGACCTCCGG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

TAAACTTCTC

TATCCATACC

TCAGGGTGAC

AGTACTTGCC

TTCTCCCTTC

ACCTCTCAAG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

GATGAAGTAG

GGCAGAGTGA

AAGGGAACCC

AGATGAAGCC

AAATTCTCCG

GAGGGAGGTG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CTCGCTCTGC

CAAGGTTGAA

GTCTGTTCCG

TTGACATCCT

CATGGGCTTC

TGTGGGCCTG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CAAAAATTGG

GTGGAAGACC

CCCCAAGTAC

CCTGCTGCAC

TGGTGCCAGA

ACTCAAGCTG

cDNA

----------

----------

----------

----------

----------

----------

gDNA

TCTGCTACCT

CCCCCTCCTC

ATTGTGCCAT

TGTTAGCATC

CTGCTGGGGA

TGGGGTGGGC

cDNA

----------

----------

----------

----------

----------

----------

gDNA

CTGGCGTGCC

TGAGCTTGGC

TATCAGCCTG

ATCTAGAAAG

GGGCTGACTG

TTGATTGTGG

cDNA

----------

----------

----------

----------

----------

----------

3762

gDNA

TCTCCTTGTC

CTGGTTTCCA

ACCTAATGCT

TCCTCCCCCA

GTTCCGGAAC

TGCATGCTCA

cDNA

----------

----------

----------

----------

-TTCCGGAAC

TGCATGCTCA

gDNA

CCACCATCTG

CTGCGGCAAG

AACCCGCTGG

GCGATGATGA

GGCTTCGGCC

ACAGCTTCCA

cDNA

CCACCATCTG

CTGCGGCAAG

AACCCGCTGG

GCGATGATGA

GGCTTCGGCC

ACAGCTTCCA

3887

gDNA

AGACCGAGCA

GTCTTCCGTG

TCCACCAGCC

AGGTTTCTCC

AGCATAG

cDNA

AGACCGAGCA

GTCTTCCGTG

TCCACCAGCC

AGGTTTCTCC

AGCATAG

Table 7. Genomic DNA (gDNA) sequence, and complementary DNA (cDNA) sequence of the rhodopsin of the short-beaked echidna, Tachyglossus aculeatus.

Figure 15. Secondary structure of the echidna rhodopsin (modified after Sakmar et al. 2002). 

Amino acids differing from bovine rhodopsin are highlighted in green.

Three ancestral sequences 

Three inferred ancestral sequence for the nodes Amniota, Mammalia, and Theria were inferred by the M3 model in PAML (Tab. 8).

0

1

2

3

4

5

Amniota

MNGTEGPNFY

VPMSNKTGVV

RSPFEYPQYY

LAEPWQYSAL

AAYMFMLILL

GFPINFLTLY

Mammalia

MNGTEGPNFY

VPMSNKTGVV

RSPFEYPQYY

LAEPWQYSVL

AAYMFMLIVL

GFPINFLTLY

Theria

MNGTEGPNFY

VPFSNKTGVV

RSPFEYPQYY

LAEPWQFSVL

AAYMFMLIVL

GFPINFLTLY

1

1

6

7

8

9

0

1

Amniota

VTIQHKKLRT

PLNYILLNLA

VADLFMVLGG

FTTTMYTSMN

GYFVFGPTGC

NIEGFFATLG

Mammalia

VTIQHKKLRT

PLNYILLNLA

VADLFMVFGG

FTTTLYTSLH

GYFVFGPTGC

NIEGFFATLG

Theria

VTIQHKKLRT

PLNYILLNLA

VADLFMVFGG

FTTTLYTSLH

GYFVFGPTGC

NLEGFFATLG

1

1

1

1

1

1

2

3

4

5

6

7

Amniota

GEIALWSLVV

LAIERYVVVC

KPMSNFRFGE

NHAIMGVAFT

WIMALACAAP

PLFGWSRYIP

Mammalia

GEIALWSLVV

LAIERYVVVC

KPMSNFRFGE

NHAIMGVAFT

WIMALACAAP

PLVGWSRYIP

Theria

GEIALWSLVV

LAIERYIVVC

KPMSNFRFGE

NHAIMGVAFT

WIMALACAAP

PLVGWSRYIP

1

1

2

2

2

2

8

9

0

1

2

3

Amniota

EGMQCSCGVD

YYTLKPEVNN

ESFVIYMFVV

HFTIPLTIIF

FCYGRLVCTV

KEAAAQQQES

Mammalia

EGMQCSCGID

YYTLKPEVNN

ESFVIYMFVV

HFTIPMTIIF

FCYGRLVFTV

KEAAAQQQES

Theria

EGMQCSCGID

YYTLKPEVNN

ESFVIYMFVV

HFTIPMIVIF

FCYGQLVFTV

KEAAAQQQES

2

2

2

2

2

2

4

5

6

7

8

9

Amniota

ATTQKAEKEV

TRMVIIMVIS

FLICWVPYAS

VAFYIFTNQG

SDFGPIFMTV

PAFFAKSSAI

Mammalia

ATTQKAEKEV

TRMVIIMVIA

FLICWVPYAS

VAFYIFTHQG

SNFGPIFMTV

PAFFAKSSAI

Theria

ATTQKAEKEV

TRMVIIMVIA

FLICWVPYAS

VAFYIFTHQG

SNFGPIFMTL

PAFFAKSSAI

3

3

3

3

3

3

0

1

2

3

4

5

Amniota

YNPVIYIVMN

KQFRNCMITT

LCCGKNPLGD

DETSAAAGTT

KTETSSVSTS

QVSPA

Mammali a

YNPVIYIMMN

KQFRNCMLTT

LCCGKNPLGD

DEASATAGTS

KTETSSVSTS

QVSPA

Theria

YNPVIYIMMN

KQFRNCMLTT

LCCGKNPLGD

DEASATAGTS

KTETSQVATS

QVSPA

Table 8. Most likely hypothetical ancestral nucleotide sequences for the nodes Amniota, Mammalia, and Theria, inferred by maximum likelihood estimates.

Western blot

In order to confirm that the correct proteins had been expressed in HEK293 cells, a SDS-PAGE analysis transferred onto a nitrocellulose membran was performed on harvested samples (Fig. 16).

Fig. 16A shows the bovine rhodopsin used as control, as well as the echidna protein and the two mutants. Fig. 16B shows the bovine control and the three ancestral pigments. The bovine sample was diluted 1:2 due to its high expression yield.

Bovine rhodopsin has a molecular weight of around 30 kDa (Frank and Rodbard 1975, Reeves et al. 1996); the corresponding band is seen in Fig. 16. All other samples display two distinct bands at around 36 and 40 kDa (Fig. 16). The echidna rhodopsin and the two mutants are 363 amino acids long, which is 5 amino acids longer than bovine rhodopsin, due to a non-therian insertion from AA 358 to 363 in the former (Tab. 4, chapter 2.2.2.). The ancestral pigments also carry this insertion and are 367 amino acids long (Tab. 8, chapter 3.1.2.). This is responsible for the greater size of expressed visual pigments other than bovine. Bovine rhodopsin monomers are seen in an additional band at around 32 kDa (Fig. 16). In addition, echidna rhodopsin and the two mutants show two additional faint bands at around 50 kDa (Fig. 16A). However, the presence of multiple bands is most likely due to proteins undergoing different post-translational modifications, which can differ in different cell types (Reeves et al. 1996, Wong 2006). Proteins are often synthesized with an extra short peptide in the N-terminal end in order to keep the protein in a nonfunctional form until it is activated into the more mature form, or to guide the protein through various compartments in the cell (Wong 2006). Thus, a subsequent treatment with N-glycosidase F would help to remove all N-linked glycosidation, but unfortunately this was not possible due to technical reasons.   

The molecular weight (MW) of each expressed protein was determined with an online tool for calculating the MW based on an input protein sequence (Tab. 9). The results indicate that the upper band in each lane in the western blot, which is at around 40 kDa, is the correct one.

(http://www.expasy.ch/tools/pi_tool.html).

Rhodopsin

MW

Bovine

38.54

Echidna

39.96

Mutant T158A

39.93

Mutant F169A

39.88

Amniota

39.60

Mammalia

39.67

Theria

39.69

Table 9. Molecular weight estimates based on protein sequences

Interestingly, the echidna rhodopsins and the two mutants show only faint bands after being exposed for 3 minutes, whereas bovine and the ancestral pigments show a very strong band, after being exposed for only 1 second. This indicates that the ancestral pigments were expressed much better, which could be due to the fact that their gene sequences had been optimized for expression in mammalian cells.

Figure 16. Western blot analysis of expressed rhodopsin pigments.

(A) From left to right: Bovine, Echidna, mutant T158A, and mutant F169A rhodopsin. (B) From left to right: Bovine, Amniota, Mammalia, and Theria rhodopsin. 

Dark and light spectra

Figure 17 shows dark aborption spectra of all visual pigments expressed in this study. For an accurate determination of λ_max, absorption spectra were curve fitted following Govardovskii’s method (Govardovskii et al. 2000). Ideally, for a reliable determination of λ_max, the curve fitting should be performed at least three times on rhodopsin data from different expressions. However, this was not possible due to technical reasons.

Nonetheless, the following absorption peaks were determined and are shown in Table 10. With a determined λ_max at 500 nm, the bovine rhodopsin expressed in this study shows an absorption peak that falls within the published range (Oprian et al. 1987, Stavenga et al. 1993).

Absorption spectra were curve fitted following Govardovskii’s method (Govardoskii et al. 2000). 

Rhodopsin

λ_max in nm

Bovine

500

Echidna

496.5

Mutant T158A

494.5

Rhodopsin

λ_max in nm

Mutant F169A

495.5

Amniota

500

Mammalia

501

Theria

500.5

Table 10. Absorption peaks of all rhodopsins expressed in this study.

After the dark absorption spectra were taken, pigments were bleached with light for 60s (Fig. 17). A light-bleached opsin shows a characteristic absorption curve with a peak at 380 nm, due to the unquenching of tryptophan after irradiation and subsequent deprotonation of the Schiff base (Farrens and Khorana 1995, Schädel et al. 2003, Salom et al. 2006). This shift in λ_max indicates that each expressed pigment is indeed functional (Fig. 17).

Figure 17. Dark (in red) and light (in black) absorption spectra of expressed and purified rhodopsins, i.e.

(A) bovine, (B) echidna, (C) mutant T158A, (D) mutant F169A, (E) Amniota, (F) Mammalia, and (G) Theria rhodopsin. λ_max of expressed rhodopsins: Bovine: 500 nm, Echidna: 496.5 nm, mutant T158A: 494.5 nm, mutant F169A: 495.5 nm, Amniota: 500 nm, Mammalia: 501 nm, and Theria: 500.5 nm.

The ratio of UV to visible absorbance (A₂₈₀/A_max) was also determined using the dark absorption spectra data. It is the amount of protein in a sample over the amount of absorbing protein in the sample, i.e. the expression yield. For expression in COS-1 cells, a ratio of around 3 was observed (Oprian et al. 1987), as opposed to a ratio of 1.6-1.7 when prepared from rod outer segments (ROS) (Hong et al. 1982). Sakamoto and Khorana (1995) prepared bovine rhodopsin from ROS and reported a ratio of 1.7-1.8. ROS prepared bovine rhodopsin displayed a ratio of around 2 (Radding and Wald 1956). A ratio below 1.6 is considered to indicate a purity close to 100% (Ernst et al. 2007).

All rhodopsins expressed in this study, including bovine, showed a A₂₈₀/A_max ratio in the same range per expression. Ratios between 2.3 to 3.7 were observed.

Acid bleach

Acid bleaches were performed on echidna and its mutants as well as on the three ancestral rhodopsin pigments, including bovine as positive control (Fig. 18). A shift from λ_max to 440 nm at 20°C indicates the break-off of the chromophore from the opsin, relinquishing a protonated Schiff base 11-cis retinal free in solution (Kito et al. 1968); hence, a functional rod pigment.

Figure 18 shows the difference absorbance over time of all acid treated pigments. The white circles indicate difference absorbance at 440 nm and are expected to increase and then stabilize once the chromophore and the opsin are indeed detached. The black circles indicate difference absorbance at λ_max of each rhodopsin and are expected to decline.

In Figures 18B-D there is an initial drop in difference absorbance at 440 nm, which can be explained by bubbles that formed when adding the HCl and which disturbed the reading of the spectrophotometer.

However, the echidna rhodopsin and the two mutants did not react to the acid as quickly as bovine, which occured immediately right after the addition (Figs. 18A, B). Still, within 10 minutes the protonated Schiff base (PSB) had formed. The two mutants reacted to HCl similar to echidna (Figs. 18C, D). For all ancestral rhodopsins, the acidification was complete within 5 minutes; the therian rhodopsin reacted as quickly as the bovine one (Figs. 18E-G).

Figure 18. Acid bleaches of (A) bovine, (B) echidna, (C) mutant T158A, (D) mutant F169A, (E) Amniota, (F) Mammalia, and (G) Theria rhodopsin. 

White circles indicate absorption at 440 nm; black ones indicate absorption at λ_max.

In addition, the molar extinction coefficient of a visual pigment can be estimated based on acid treatment data (Radding and Wald 1956, Starace and Knox 1998). It is a measure of how strongly a chemical absorbs light at a given wavelength.

There are various extinction coefficients published for bovine rhodopsin (estimated λ_max = 498 - 500 nm), ranging from 40 600 to 43 000 M^-1 cm^-1 (Wald and Brown 1953, Shichi et al. 1969, Daemen et al. 1970, Hong and Hubbell 1972, Oprian et al. 1987). All estimated extinction coefficients are shown in Table 11.

Rhodopsin

ε in M^-1 cm^-1

Bovine

40 622

Echidna

34 921

Mutant T158A

31 411

Mutant F169A

40 254

Amniota

49 169

Mammalia

46 961

Theria

45 460

Table 11. Molar extinction coefficients determined for all proteins expressed in this study.

Hydroxylamine sensitivity

All pigments, including bovine rhodopsin as positive control, were treated with 1 M hydroxylamine (NH₂OH) for 2 hrs (Fig. 19). Hydroxylamine assays are used to distinguish between rod and cone opsins, with cone opsins reacting quickly to the compound and forming a retinal oxime, which absorbs light at around 363 nm, and rod opsins not shifting their absorption peak for an extended period of time (Wald et al. 1955, Fager and Fager 1981, Okano et al. 1989, Wang et al. 1992, Starace and Knox 1998). Bovine rhodopsin is known to stay stable in the presence of hydroxylamine for at least 12 hrs (Kawamura and Yokoyama 1998).

In this study, the bovine rhodopsin positive control reacted little to hydroxylamine for the 2 hours during which the measurements were taken, though the dots are very scattered, which is due to the spectrophotometer (Fig. 19A). Also, the degree of increase in difference absorbance at λ_{363 nm} is not very high. An incipient rise is normal, as long as the curve evens out after several minutes. The observed drop in difference absorbance is due to the presence of bubbles or a change in properties of the solution, as was also the case in the acid bleach (Fig. 19A).

Interestingly, the echidna rhodopsin and the two mutants reacted to hydroxylamine more than bovine, as indicated by an increase in difference absorbance of more than 0.005 (Figs. 19B-D). However, cone opsins react to hydroxylamine much stronger (Kawamura and Yokoyama 1998, Starace and Knox 1998). Also, since there were only two runs performed for each mutant, a third run should be performed for a more reliable result.

Figures 19E-F show, though the data points are also somewhat scattered, that the amniote and mammalian rhodopsins react to hydroxylamine just as little as the bovine one. For the Theria rhodopsin, one of the three curves rises slightly, but the other two do not show a strong increase in absorption (Fig. 19G).

The determination of t_1/2 of hydroxylamine treated pigmnents was not possible, because the data points are too scatterered and R² values are not reliable.

In conclusion, there is some indication that echidna and the two mutants are not as stable in the presence of hydroxylamine as bovine rhodopsin, which indicates cone-like characteristics. All ancestral pigments, however, are as insensitive to hydroxylamine as bovine rhodopsin.

Figure 19. Hydroxylamine assays performed on (A) bovine, (B) echidna, (C) mutant T158A, (D) mutant F169A, (E) Amniota, (F) Mammalia, and (G) Theria rhodopsins. 

Circles indicate different runs.

Meta II decay by fluorescence spectroscopy

Meta II is the active state of rhodopsin and a key intermediate in the visual signaling cascade where the crucial transducin activation takes place (Fig. 13, chapter 2.1.8.) (Weitz and Nathans 1993, Imai et al. 2005, Sugawara et al. 2010). Here, the opsin and the chromophore are still bound but the Schiff base is deprotonated, unquenching tryptophan, and has its λ_max at 380 nm (Farrens and Khorana 1995, Sakmar et al. 2002, Heck et al. 2003, Salom et al. 2006). The rhodopsin meta II state is induced by light bleach and finished with the addition of fresh 11-cis retinal, which binds to rhodopsin molecules.

The results of the meta II decay rate assays performed in this study are given in tables 12 and 13. Bovine meta II decay rates are more or less within the expected range of 15 min^-1 (Tab. 12, 13) (Janz and Farrens 2001, Reeves et al. 1996). The amniote rhodopsin displays a t_1/2 similar to bovine (Tab. 12). Most striking are the results for the mammalian ancestor, where t_1/2 is much higher than those of bovine and amniote (Tab. 12). Also, the therian rhodopsin displays a high t_1/2, similar to the mammalian one (Tab. 12). On the other hand, the echidna displays a much lower t_1/2 than bovine (Tab. 13). Due to technical reasons, meta II decay rates were not determined for the two mutants.

Hyphenated numbers in brackets indicate number of expression and assay run.

Expressed rod pigment

t_1/2 in min^-1

R²

Bovine

16.46 ⁽¹⁾

0.9985

17.24 ⁽²⁾

0.9990

21.39 ⁽³⁾

0.9932

12.95 ⁽⁴⁾

0.9921

Amniota

16.74 ⁽¹⁾

0.9989

16.54 ⁽²⁾

0.9992

17.07 ⁽³⁾

0.9976

13.85 ⁽⁴⁾

0.9924

Mammalia

21.33 ⁽¹⁾

0.9986

22.36 ⁽²⁾

0.9994

22.43 ⁽³⁾

0.9938

30.54 ⁽⁴⁾

0.9989

Theria

33.98 ⁽¹⁾

0.9988

25.30 ⁽²⁾

0.9987

38.72 ⁽³⁾

0.9977

14.69 ⁽⁴⁾

0.9120

Table 12. Meta II decay results and their coefficient of determination (R²) of ancestral pigments and bovine rhodopsin as positive control.

Hyphenated numbers in brackets indicate number of expression and assay run.

Expressed rod pigment

t_1/2 in min^-1

R²

Bovine

12.2 ⁽⁵⁾

0.9979

13.8 ⁽⁶⁾

0.9979

13.0 ⁽⁷⁾

0.9977

14.1 ⁽⁸⁾

0.999

13.8 ⁽⁹⁾

0.9987

Echidna

10.3 ⁽⁵⁾

0.9957

9.9 ⁽⁶⁾

0.9968

6.6 ⁽⁷⁾

0.9943

6.1 ⁽⁸⁾

0.9974

6.7 ⁽⁹⁾

0.9972

Table 13. Meta II decay results and coefficients of determination (R²) of echidna rhodopsin and bovine as positive control.

Taking a closer look at the 27 tetrapod rhodopsin amino acid sequences, several interesting substitutions were identified, i.e. substitutions unique to a taxon, a monophyletic group, or individual clades (Tab. 4, chapter 2.2.2.).

Introduction

In order to test the hypothesis that early mammals had indeed been nocturnal, selective pressure acting on the visual pigment resposible for vision at night, the rhodopsin, was assessed by using a maximum likelihood approach that estimates ω, which is the ratio of non-synonymous substitutions to synonymous substitutions. To determine the type and degree of selective constraint, branches of interest were selected as foreground branches with their own estimated ω, one that is different from the background branches, which have a combined ω estimated for all branches. When these two groups are compared, if one has a higher ω, then either the one with the higher ratio has experienced relaxed purifying selection, or the one with the lower value has undergone stronger purifying selection than the other. Positive selection is indicated if ω is significantly greater than 1.

Here, the amniote, reptilian, mammalian, monotreme, therian, marsupial, and placental branches were of interest and marked separately. Then, comparison of alternative and null models as well as significant LRTs tell us if there was positive or relaxed purifying selection acting on the rhodopsin.

Branch models

A comparison of MB2a and MB1n using siginficant LRTs determines whether the foreground branch is significantly different from the background d_N/d_S ratio. If the ω ratio of the foreground branch in MB2a is estimated to be greater than 1, this indicates either relaxed purifying or positive selection. Comparing MB2a and MB2n tests whether the branch of interest has a d_N/d_S ratio that is significantly different from 1, if supported by significant LRTs. If ω₁ is estimated to be greater than 1, positive selection is indicated.

The first branch of interest is the amniote one. With Amniota marked as a foreground branch, we find a value of 999 in model MB2a (Tab. 14). In PAML 4, the number 999 is the upper bound set for ω, meaning the actual value is not known, it might even represent infinity (Yang 2007). The LRT of the comparison of MB2a and MB1n does not show significance. Hence, the foreground value 999 is not significantly different from the background value 0.0532 and, thus, there is no indication for any positive selection along this branch (Tab. 14). Testing whether this value is significantly different from 1, does not show statistical significance using the LRT comparing models MB2a and MB2n (Tab. 14). However, because the foreground ratio is much larger than the background branch, this indicates slightly relaxed selective constraint.

Model

ω₀

ω₁

np

LnL

p-value

Alternative model MB2a

0.0532

999

54

-10646.2

First null model MB1n

0.05432

0.05432

53

-10649.5

MB2a vs MB1n

0.0703

Model

ω₀

ω₁

np

LnL

p-value

Second null model MB2n

0.0533

1

53

-10646.3

MB2a vs MB2n

0.8069

Table 14. Branch model estimates for the branch Amniota. np is number of parameters, LnL is log likelihood of the model.

In the reptilian branch, the foreground ratio in null model MB2n is 999 compared to a background ratio of 0.0537 (Tab. 15). However, neither LRTs of comparing models MB2a and MB1n nor models MB2a and MB2n provide statistical support (Tab. 15). As for Amniota, this also suggests slightly relaxed purifying selection.

Model

ω₀

ω₁

np

LnL

p-value

Alternative model MB2a

0.0537

999

54

-10647.5

First null model MB1n

0.05432

0.05432

53

-10649.5

MB2a vs MB1n

0.1549

Second null model MB2n

0.0537

1

53

-10647.6

MB2a vs MB2n

0.7218

Table 15. Branch model estimates for the branch Reptilia. np is number of parameters, LnL is log likelihood of the model.

For Mammalia, the alternative model MB2a, with foreground and background ratios estimated separately, estimates a foreground ratio of 0.0794 and a background ratio of 0.0538 (Tab. 16). The LRT comparing MB2a and MB1n is not significant and indicates that this value is not significantly different from the background ratio (Tab. 16). However, the LRT comparing MB2a and MB2n is statistically significant (Tab. 16). The foreground ratio is significantly different from 1, and since it is close to the background ratio, this is an indication of purifying selection similar to the background branches.

Model

ω₀

ω₁

np

LnL

p-value

Alternative model MB2a

0.0538

0.0794

54

-10649.0

First null model MB1n

0.05432

0.05432

53

-10649.5

MB2a vs MB1n

0.4965

Second null model MB2n

0.0522

1

53

-10656.9

MB2a vs MB2n

0.0049*

Table 16. Branch model estimates for the branch Mammalia. * indicates statistical significance. np is number of parameters, LnL is log likelihood of the model.

In monotremes, the estimated foreground ratio is less than 1, more precisely 0.0209 compared to a background ratio of 0.056 (Tab. 17). Both model comparisons that are different from the background and also different from 1, are found to be statistically significant by the LRTs (Tab. 17). Hence, stronger purifying selection than the background branches was detected in the monotreme branch.

Model

ω₀

ω₁

np

LnL

p-value

Alternative model MB2a

0.056

0.0209

54

-10645.6

First null model MB1n

0.05432

0.05432

53

-10649.5

MB2a vs MB1n

0.0490*

Second null model MB2n

0.0514

1

53

-10681.5

MB2a vs MB2n

0.000000002*

Table 17. Branch model estimates for the branch Monotremata. * indicates statistical significance. np is number of parameters, LnL is log likelihood of the model.

In the therian branch, a foreground ratio of 8.7588 was estimated in the null model MB2a (Tab. 18). The LRT comparing MB2a and MB1n indicates that this foreground ratio is significantly different from the background ratio 0.0528 (Tab. 18). But testing whether the elevated ω is significantly different from 1 by comparing MB2a and MB2n, we do not find statistical support by the LRT (Tab. 18). However, since ω is still greater than the background ratio, this indicates relaxed purifying or weak positive selection compared to the background.

* indicates statistical significance. np is number of parameters, LnL is log likelihood of the model. 

Model

ω₀

ω₁

np

LnL

p-value

Alternative model MB2a

0.0528

8.7588

54

-10644.3

First null model MB1n

0.05432

0.05432

53

-10649.5

MB2a vs MB1n

0.0224*

Second null model MB2n

0.0529

1

53

-10644.3

MB2a vs MB2n

0.8332

Table 18. Branch model estimates for the branch Theria.

For Marsupialia, a foreground ratio of 0.0186 and a background ratio of 0.00553 was estimated (Tab. 19). The comparison of models MB2a and MB1n using the LRT does not find statistical support, but there is support when comparing MB2a and MB2n (Tab. 19). Since ω₁ is close to the background ω and significantly smaller than 1, this indicates that purifying selection, similar to that of the background, was acting along this branch.

* indicates statistical significance. np is number of parameters, LnL is log likelihood of the model.

Model

ω₀

ω₁

np

LnL

p-value

Alternative model MB2a

0.0553

0.0186

54

-10647.5

First null model MB1n

0.05432

0.05432

53

-10649.5

MB2a vs MB1n

0.1548

Second null model MB2n

0.0532

1

53

-10659.5

MB2a vs MB2n

0.0005*

Table 19. Branch model estimates for the branch Marsupialia.

The last branch of interest is Placentalia. The foreground ratio is 0.0044, compared to a background ratio of 0.0526 (Tab. 20). Both LRTs provide statistical significance, indicating that ω₁ is not only significantly different from ω₀ but also from 1. Because ω₁ is approaching 0 this is evidence for purifiying selection (Tab. 20). Since the estimated foreground ratio is also much smaller than the background ratio, this indicates even stronger purifying selection along this branch compared to the background branches (Tab. 20).

* indicates statistical significance. np is number of parameters, LnL is log likelihood of the model.

Model

ω₀

ω₁

np

LnL

p-value

Alternative model MB2a

0.0526

0.0044

54

-10633.0

First null model MB1n

0.05432

0.05432

53

-10649.5

MB2a vs MB1n

0.00005*

Second null model MB2n

0.0520

1

53

-10692.33

MB2a vs MB2n

< 0.0000000001*

Table 20. Branch model estimates for the branch Placentalia.

Branch-site models

However, positive selection acts on sites. If there are a lot of sites positively selected along a branch of interest, this signal will be detected by branch models. But if there are only a few sites experiencing positive selection, their signal might be overruled by the other negatively selected sites along that branch. In order to test whether positive selection is acting only on a few sites, branch-site models that detect single positively selected sites, were applied as well.

In branch-site models, the comparison of alternative model MA and first null model M1a, tests whether there are sites with a ω greater than 1. It is a test for either positive selection or relaxed purifying selection (Yang 2007). Comparing the alternative model MA and the second null model MA1 tests whether sites with an elevated ω ratio are indeed significantly greater than 1. This tests for positive selection only and is called the branch-site test of positive selection (Yang 2007).

For the amniote branch, model MA detects positively selected sites which is indicated by the estimated ω_2a+b value 10.643 (Tab. 21). However, the LRT comparing models MA and M1a does not provide statistical support, neither does the LRT comparing models MA and MA1 (Tab. 21). Thus, there is no indication for positive selection, nor for relaxed purifying selection. However, the BEB analysis did identify six positively selected sites, but all show low posterior probabilities < 95% (Tab. 22).

Model

ω

np

df

LnL

p-value

Alternative model MA

ω₀ = 0.04521

56

-10567.6

ω₁ = 1

ω_2a = 10.643

ω_2b = 10.643

First null model M1a

ω₀ = 0.04565

54

2

-10567.7

MA vs M1a

ω₁ = 1

0.40568

Second null model MA1

ω₀ = 0.0453

55

1

-10569.4

MA vs MA1

ω₁ = 1

0.67395

ω_2a = 1

ω_2b = 1

Table 21. Branch-site model estimates for the branch Amniota. np is number of parameters, df is degrees of freedom in Likelihood Ratio Test, LnL is log likelihood of the model.

Numbers in brackets refer to numbering in bovine rhodopsin. The programm PAML prints out an * if the posterior probability is > 95%, and ** if the probability is > 99% (Yang 2007).

Branch of interest marked as foreground branch

Positively selected site

Posterior probability

Mutation

Amniota

46

0.535

F

93

0.568

V

328

0.903

F

335

0.773

S

344 (342)

0.899

A

349 (347)

0.896

S

Reptilia

290

0.611

A

336

0.900

A

Monotremata

344 (342)

0.992**

Q

Theria

13

0.997**

M

37

0.967*

Y

49

0.575

L

162

0.534

I

218

0.653

V

225

0.993**

R

290

0.921

A

345 (343)

1.000**

S

346 (344)

1.000**

S

348 (346)

0.972**

S

Marsupialia

26

0.987*

Y

39

0.979*

A

Placentalia

39

0.546

A

Table 22. Positively selected sites estimated by BEB analysis in branch-site model MA (Yang et al. 2005), with posterior probabilities, for branches Amniota, Reptilia, Monotremata, Theria, Marsupialia, and Placentalia.

In Reptilia, again, the alternative model MA identifies positively selected sites, which is displayed by the elevated ω of 12.236 in site class ω_2a+b (Tab. 23). But neither comparing models MA and M1a nor models MA and MA1 show statistical support by the LRTs (Tab. 23). So again, there is no evidence for relaxed purifying or positive selection along this branch. Nevertheless, the BEB analysis estimated two positively selected sites, though with low posterior probabilities < 95% (Tab. 22).

Model

ω

np

df

LnL

p-value

Alternative model MA

ω₀ = 0.04525

56

-10568.6

ω₁ = 1

ω_2a = 12.236

ω_2b = 12.236

First null model M1a

ω₀ = 0.04565

54

2

-10567.7

MA vs M1a

ω₁ = 1

0.68249

Second null model MA1

ω₀ = 0.04527

55

1

-10568.6

MA vs MA1

ω₁ = 1

0.8792

ω_2a = 1

ω_2b = 1

Table 23. Branch-site model estimates for the branch Reptilia. np is number of parameters, df is degrees of freedom in Likelihood Ratio Test, LnL is log likelihood of the model.

In Mammalia, the estimated ω_2a+b value is 1 (Tab. 24). This indicates that there are no sites under positive selection in the foreground branch. Also, statistical support for testing for positive selection or relaxed purifying selection is not given by the LRTs (Tab. 24). The results suggest that the mammalian branch has a similar selective constraint to the background branch.

Model

ω

np

df

LnL

p-value

Alternative model MA

ω₀ = 0.04507

56

-10568.9

ω₁ = 1

ω_2a = 1

ω_2b = 1

First null model M1a

ω₀ = 0.04565

54

2

-10567.7

MA vs M1a

ω₁ = 1

0.77565

Second null model MA1

ω₀ = 0.04527

55

1

-10568.9

MA vs MA1

ω₁ = 1

1

ω_2a = 1

ω_2b = 1

Table 24. Branch-site model estimates for the branch Mammalia. np is number of parameters, df is degrees of freedom in Likelihood Ratio Test, LnL is log likelihood of the model.

Also in the monotreme branch, the MA model identified positively selected sites as indicated by the value 50.166 in site class ω_2a+b (Tab. 25). Neither model comparison provides statistical significance using the LRTs. The monotreme branch has a selective constraint similar to the background branch (Tab. 25). However, the BEB analysis estimated one positively selected site, but since the LRT comparing models MA and MA1 was not significant, this predicted site is not statistically significant either (Tab. 22).

Model

ω

np

df

LnL

p-value

Alternative model MA

ω₀ = 0.04537

56

-10566.1

ω₁ = 1

ω_2a = 50.166

ω_2b = 50.166

First null model M1a

ω₀ = 0.04565

54

2

-10567.7

MA vs M1a

ω₁ = 1

0.19004

Second null model MA1

ω₀ = 0.04541

55

1

-10568.5

MA vs MA1

ω₁ = 1

0.11969

ω_2a = 1

ω_2b = 1

Table 25. Branch-site model estimates for the branch Monotremata. np is number of parameters, df is degrees of freedom in Likelihood Ratio Test, LnL is log likelihood of the model.

For Theria, the MA model estimates a high ω_2a+b ratio of 999 (Tab. 26). This is a signal for positively selected sites. This time, both the comparison of models MA and M1a as well as the one of models MA and MA1 are statistically significant, which is indicated by the LRTs (Tab. 26). This is a clear signal of positive selection acting on sites along this branch. In a second step, the BEB analysis estimated ten BEB sites in total, but only six have posterior probabilites >95% and are, thus, reliable (Tab. 22).

* indicates statistical significance. np is number of parameters, df is degrees of freedom in Likelihood Ratio Test, LnL is log likelihood of the model.

Model

ω

np

df

LnL

p-value

Alternative model MA

ω₀ = 0.04443

56

-10549.8

ω₁ = 1

ω_2a = 999

ω_2b =999

First null model M1a

ω₀ = 0.04565

54

2

-10569.4

MA vs M1a

ω₁ = 1

0.000055*

Second null model MA1

ω₀ = 0.04443

55

1

-10559.0

MA vs MA1

ω₁ = 1

0.00241*

ω_2a = 1

ω_2b = 1

Table 26. Branch-site model estimates for the branch Theria.

A signal of positively selected sites was also detected along the marsupial branch, as indicated by the ω_2a+b value 509.91 in the alternative model MA (Tab. 27). Statistical support is given by the LRT of comparing MA and MA1, which means that the sites which are greater than 1 are significantly greater than 1, an indication for positive selection (Tab. 27). Two predicted BEB sites with confident posterior probabilities < 95% are shown in Table 22.

np is number of parameters, df is degrees of freedom in Likelihood Ratio Test, LnL is log likelihood of the model.

Model

ω

np

df

LnL

p-value

Alternative model MA

ω₀ = 0.04553

56

-10563.3

ω₁ = 1

ω_2a = 509.91

ω_2b = 509.91

First null model M1a

ω₀ = 0.04565

54

2

-10567.7

MA vs M1a

ω₁ = 1

0.04848*

Second null model MA1

ω₀ = 0.04546

55

1

-10568.0

MA vs MA1

ω₁ = 1

0.03139*

ω_2a = 1

ω_2b = 1

Table 27. Branch-site model estimates for the branch Marsupialia.

In the placental branch, the ω_2a+b ratio was estimated to equal 1, indicating the presence of no positively selected sites along this branch (Tab. 28). However, neither model comparison is statistically supported by the LRTs (Tab. 28). Thus, no evidence for relaxed purifying or positive selection is found. For placentals, the BEB analysis estimated one positively selected site with a low posterior probability < 95% (Tab. 22).

np is number of parameters, df is degrees of freedom in Likelihood Ratio Test, LnL is log likelihood of the model.

Model

ω

np

df

LnL

p-value

Alternative model MA

ω₀ = 0.04565

56

-10569.4

ω₁ = 1

ω_2a = 1

ω_2b = 1

First null model M1a

ω₀ = 0.04565

54

2

-10567.7

MA vs M1a

ω₁ = 1

1

Model

ω

np

df

LnL

p-value

Second null model MA1

ω₀ = 0.04565

55

1

-10569.4

MA vs MA1

ω₁ = 1

1

ω_2a = 1

ω_2b = 1

Table 28. Branch-site model estimates for the branch Placentalia.

Summary

In conclusion, the branch-site analyses found evidence for positive selection acting only on the rhodopsin along the branches Theria and Marsupialia (Fig. 22). All other branches experienced slightly relaxed purifying selection (Amniota and Reptilia), purifying selection similar to background branches (Mammalia), or even stronger purifying selection compared to the background branch (Monotremata and Placentalia) (Fig. 22).

Figure 22. Summary figure showing selective constraints acting on rhodopsin along branches and on sites.