Our brain requires a lot of energy to work properly. Sugars are usually the main type of fuel for the body, but when they run low – for example during a food shortage – fat, in the form of fatty acids, can be used instead. However, the brain cannot directly process these molecules; instead, fatty acids need to go through ketogenesis, a process that turns fat into ketone bodies, which the organ can then burn. Scientists believe that the ability to create ketone bodies was essential for us to evolve large brains. Yet, it is still unclear if all mammals can transform fatty acids into ketone bodies. One way to look into this question is to track whether other species have HMGCS2, the main enzyme that drives ketogenesis.

Jebb and Hiller examined the genomes of 70 different species of mammals for the gene that codes for HMGCS2. The comparisons revealed that cetaceans (whales, dolphins and porpoises), Old World fruit bats and the African savanna elephant have all independently lost their working version of HMGCS2. Yet, many members of these three groups have evolved brains that are large for their body size. The genetic analyses showed that dolphins and elephants developed big brains after the enzyme became inactive, challenging the idea that HMGCS2 – and by extension ketogenesis – is always required for the evolution of large brains.

These results may also be useful for conservation efforts. Many fruit bats across the world are severely threatened, and their lack of ketogenesis could explain why these animals are highly sensitive to starvation and quickly die when food becomes scarce.

Periods of fasting are a common event for many animals (Secor and Carey, 2016). Fasting occurs due to natural food scarcity or as part of the life history strategy, for example during hibernation or migration. During fasting, the organism relies on stored sources of energy such as glucose in the form of glycogen and fatty acids (Secor and Carey, 2016). In addition, ketone bodies become an alternative fuel source that is important for many mammals to survive episodes of fasting or starvation (Baird et al., 1972; Bouchat et al., 1981; Sicart et al., 1978). For example, ketone bodies are used as an energy source in hibernating ground squirrels or elephant seal pups during their post-weaning fasting period (Krilowicz, 1985; Castellini and Costa, 1990). Notably, while the brain cannot metabolize fatty acids, ketone bodies can cross the blood-brain barrier and provide fuel under conditions of low blood glucose levels. For example, after starving for 3 days, the human brain takes 25% of its energy from ketone bodies and if fasting continues, ketone bodies replace glucose as the predominant fuel for brain metabolism (Owen et al., 1967; Hasselbalch et al., 1994). During the neonatal period, the developing human brain has high energy requirements and also relies on ketone bodies as a major fuel (Cunnane and Crawford, 2003; Cahill, 2006). Given their importance in fueling large, energetically expensive brains, it has been posited that ketone bodies do not only have an important role during fasting, but have also been crucial for brain expansion during human evolution (Cunnane and Crawford, 2003; Wang et al., 2014).

Ketone bodies comprise acetoacetate, acetone, and d-β-hydroxybutyrate (Figure 1A) and are mainly produced in the liver by ketogenesis. This metabolic process occurs in the mitochondria and uses fatty acid-derived acetyl-CoA to generate the water-soluble, acidic ketone bodies, which are secreted into the blood. The rate limiting step of ketogenesis is the production of 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) by HMG-CoA synthase (Hegardt, 1999). Mammals possess two HMG-CoA synthases that originated by gene duplication. While the cytosolic enzyme, encoded by HMGCS1, is broadly expressed and is necessary to produce cholesterol (Hegardt, 1999), the mitochondrial HMG-CoA synthase, encoded by HMGCS2, is primarily expressed in the liver and is only used for ketone body production. HMGCS2 is required for ketogenesis, as mutations in the human gene and mouse gene-knockdown experiments abolish or greatly reduce ketogenesis (Bouchard et al., 2001; Ramos et al., 2013; Thompson et al., 1997; Wolf et al., 2003; Pitt et al., 2015; Cotter et al., 2014). HMG-CoA synthase-2 deficiency in human can lead to coma after fasting for more than 22 hours due to low glucose levels (Thompson et al., 1997; Morris et al., 1998). Human individuals with HMGCS2 mutations therefore require regular carbohydrate intake but show no other symptoms, suggesting that this deficiency is probably underdiagnosed.

Figure 1 with 5 supplements see all

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Here we investigated the evolution of HMGCS2 in mammals. Unexpectedly, we identified three independent losses of this gene in cetaceans (dolphins and whales), pteropodids (Old World fruit-eating bats) and Elephantimorpha (elephants and mastodons). Remarkably, these species have relatively large brains, suggesting that, unlike in humans, ketone bodies are not strictly required for fueling complex brains. Furthermore, we show that in the cetacean and Elephantimorpha clades HMGCS2 was lost before brain size expansion happened, suggesting that the lack of ketogenesis did not prohibit the evolution of large brains in these lineages. While strong conservation of HMGCS2 in other mammals indicates that ketogenesis is a crucial metabolic process, the recurrent loss of this gene highlights an unexpected flexibility in mammalian energy metabolism.

To investigate the evolution of HMGCS2, we used a previously published whole genome alignment to inspect the gene sequence and the surrounding locus across 70 placental mammals (Sharma and Hiller, 2017). Surprisingly, we discovered that three independent lineages (cetaceans, pteropodids and the African savanna elephant) exhibit large deletions that remove HMGCS2 exons or gene-inactivating mutations that shift the HMGCS2 reading frame and destroy conserved splice site dinucleotides (Figure 1B). All three lineages have a deletion of exon one that encodes the mitochondrial targeting domain; such a deletion causes HMG-CoA synthase-2 deficiency in human individuals (Pitt et al., 2015). Other mutations affect exons encoding key residues required for HMG-CoA synthase catalytic activity and leave little of the coding sequence intact. Together with the deletion of the promoter region in pteropodids, the elephant and the sperm whale (Figure 1—figure supplement 1), this shows that three mammalian lineages lost the enzyme that is required for ketogenesis.

In cetaceans and pteropodids, the remnants of the once-functional HMGCS2 gene are located in a conserved genomic context with REG4 upstream and PHGDH downstream. In elephant, the three remaining HMGCS2 exons also occur in the same genomic locus adjacent to the conserved PHGDH gene, but inversions that already happened in the ancestor of elephants and the closely related manatees rearranged the locus upstream of HMGCS2 (Figure 1—figure supplement 2). These rearrangements were succeeded by a large deletion in the elephant lineage that removed the first five HMGCS2 exons together with the REG4 gene.

To rule out that the gene-inactivating mutations are sequencing or genome assembly errors, we validated all smaller mutations and exon deletions with unassembled sequencing reads from the SRA and TRACE archives using blastn. All 22 mutations in cetaceans were confirmed by at least 30 reads, with no support for the non-gene-inactivating allele (Figure 1B, Supplementary file 1). This includes the deletion of exon one that exhibits shared breakpoints in the toothed and baleen whale lineages (Figure 1—figure supplement 3), which strongly suggests that this deletion and thus HMGCS2 loss already occurred before the split of the main cetacean lineages (Figure 1C). This is further supported by the 2 bp frameshifting insertion in exon two that is shared between killer whale and minke whale, and was later deleted in dolphin and sperm whale.

In pteropodid bats, the ~4.5 kb deletion that removed coding exon two is validated by sequencing reads and is shared between both flying foxes (Figure 1B), suggesting that HMGCS2 was already lost in their common ancestor. Using the HMGCS2 sequence of the David’s myotis bat, we detected no evidence for the presence of the deleted HMGCS2 exons in unassembled sequencing reads of both flying fox species, while we readily found all exons of the HMGCS1 paralog, showing that the search is sufficiently sensitive. In the Egyptian fruit bat, HMGCS2 is entirely removed by a large deletion between the REG4 and PHGDH genes, which we validated with an independent PacBio assembly (Figure 1—figure supplement 4). Consistent with ongoing gene erosion, the 1 bp deletion in exon three is heterozygous in the black flying fox (Figure 1B).

To rule out that the partial gene deletion in the African savanna elephant is an assembly error, we used the manatee HMGCS2 sequence. Sensitive blastn searches found no significant hits for the deleted HMGCS2 exons or the deleted neighboring REG4 gene in the unassembled sequencing reads of two different savanna elephant individuals (Cortez et al., 2014). In contrast, the three remaining HMGCS2 exons as well as all exons of the paralogous HMGCS1 could be recovered. We also investigated related elephant species, making use of recently published sequence data from the African forest elephant and the Asian elephant (Palkopoulou et al., 2018; Reddy et al., 2015). Further, we queried sequence data from two American mastodons, extinct Elephantimorpha that split from elephants 28–24 Mya (Rohland et al., 2007). As for the savanna elephant, the three remaining HMGCS2 exons and entire HMGCS1 gene were found in all three species, while the deleted HMGCS2 exons and the REG4 gene were not found (Figure 1B). Parsimony suggests that the deletion, which removed large parts of HMGCS2, occurred prior to the divergence of mastodons and the elephant species.

We further found that the remaining HMGCS2 sequence evolves under relaxed selection in cetaceans, pteropodids and Elephantimorpha (p<3e-3, Supplementary file 2). Together with the conserved genomic context, the lack of any evidence of a remaining functional HMGCS2 in unassembled reads and the validated gene-inactivating mutations, we conclude that the main ketogenesis enzyme is lost in three independent mammalian lineages. Finally, we considered the possibility that HMGCS1, the cytosolic HMG-CoA synthase, may compensate for HMGCS2 loss, which would require HMGCS1 to be localized in the mitochondria, where ketogenesis happens in other species. We found that the HMGCS1 protein of cetaceans, pteropodids and elephant does not possess a mitochondrial targeting domain. Furthermore, an analysis of available liver RNA-seq data from the minke whale and Egyptian fruit bat provides no indication of alternative or novel exons in HMGCS1 that could encode such a targeting signal. Thus, HMGCS1 does not seem to be capable of compensating for the loss of HMGCS2, suggesting that ketogenesis is lost in cetaceans, pteropodids and Elephantimorpha.

Next, we investigated whether the loss of HMGCS2 is associated with the loss of other enzymes in the ketogenesis pathway (Figure 1A). ACAT1 and HMGCL do not exhibit inactivating mutations in cetaceans, pteropodids and the elephant, likely because the respective enzymes are not only required for the production of ketone bodies but are also involved in leucine and isoleucine metabolism. In contrast to these two pleiotropic genes, BDH1 is only involved in converting acetoacetate into the ketone body d-β-hydroxybutyrate (Figure 1A). We found that BDH1 exhibits several inactivating mutations and evolved under relaxed selection in cetaceans and pteropodids (Figure 1—figure supplement 5, Supplementary file 2). Overall, this suggests that the loss of HMGCS2 is only associated with the loss of non-pleiotropic genes in the ketogenesis pathway.

The 59 other mammals, for which the genome assembly fully covered the HMGCS2 locus (Figure 1B), do not exhibit inactivating mutations in this gene. Consistent with the presence of a functional gene, we further estimated an average non-synonymous/synonymous (dN/dS) ratio of 0.16, which indicates that HMGCS2 evolves under strong purifying selection in other mammals.

The observation that HMGCS2 is well-conserved in the majority of mammals is consistent with ketogenesis being an important metabolic process. However, the recurrent loss of HMGCS2 raises the question of which energy source is used by the brain during fasting. Consistent with the loss of ketogenesis in cetaceans, bottlenose dolphins do not produce ketone bodies after fasting for 3 days but are nevertheless able to maintain high blood glucose levels over this entire period (Ridgway, 2013). It was suggested that dolphins maintain high glucose levels by synthesis of glucose from non-carbohydrates (gluconeogenesis), in particular from glucogenic amino acids that are abundant in their diet (Ridgway, 2013). This suggests that ketogenesis became dispensable in dolphins and that HMGCS2 was lost as a consequence of relaxed or no selection to maintain this gene. Similarly, the loss of ketogenesis in pteropodid fruit bats may be a consequence of the relatively constant availability of fruit year-round, which provides large quantities of glucose. This is in agreement with molecular dating, which estimates that the loss of HMGCS2 happened rather late in the lineage leading to the fruit bat clade and may even have occurred independently after the split of the frugivorous flying foxes and the Egyptian fruit bat (Figure 2A). Consistent with lack of ketone bodies as alternative fuel, Egyptian fruit bats that were fasted for more than 24 hours in captivity frequently died (van der Westhuyzen, 1978). Thus, like HMG-CoA synthase-2 deficient human individuals, these bats are sensitive to starvation. Hence, while ketogenesis may have been lost under ancestral conditions of constantly available, glucose-rich food, the loss of HMGCS2 may now represent a disadvantage, which will be of interest to ongoing conservation efforts for ecologically and economically important species in the pteropodid family. In contrast to cetaceans and fruit bats, little is known about how elephants respond to fasting; however, the following observation is consistent with the loss of ketogenesis. During musth, when elephant males experience longer periods of fasting and can lose 10% of their body weight, their blood becomes slightly more alkaline (Rasmussen and Perrin, 1999). This is contrary to an increased blood acidity that would be expected from an increasing production of acidic ketone bodies.

Figure 2

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Figure 2—source data 1

Sequence alignment.

This file contains the HMGCS2 sequence alignment (fasta format) including the sequences of the African forest elephant, the Asian elephant and the American mastodon. This alignment was used to date the loss of HMGCS2.

https://doi.org/10.7554/eLife.38906.010

Download elife-38906-fig2-data1-v1.txt

Given the importance of ketogenesis to provide energy to the brain during starvation, it is noteworthy that species in all three HMGCS2-loss lineages generally have large relative brain sizes (Stephan et al., 1981; Boddy et al., 2012). For example, the encephalization quotient (EQ), measuring the ratio between the observed brain size and the size expected for a mammal of the same body weight, is 3.7 for the bottlenose dolphin (Montgomery et al., 2013). Compared to human, dolphins and elephants are also among the few mammals that have a higher degree of neocortex folding, a measure that positively correlates with neuron number (Manger et al., 2012; Lewitus et al., 2014). Furthermore, while powered flight imposes a constraint on body and brain size in bats, pteropodid fruit bats exhibit a well-developed visual brain system and have brains nearly twice as large as that of insectivorous vesper bats of equal body weight (Stephan et al., 1981). Species in all three lineages also exhibit cognitive behaviors that are regarded as a sign of intelligence, exemplified by vocal learning and, in dolphins and elephants, by complex social structures, tool use and self-recognition (Krützen et al., 2005; Foerder et al., 2011; Poole et al., 2005; Prat et al., 2015; Plotnik et al., 2006). Thus, the loss of HMGCS2 in independent large-brained species suggests that ketone bodies are not strictly required to fuel large mammalian brains during fasting.

Finally, the timing of HMGCS2 loss has implications for understanding the general preconditions for brain size expansion during the evolution of mammals. While the loss of HMGCS2 in pteropodids likely happened after brain size expansion in this lineage (Figure 2A), shared inactivating mutations show that HMGCS2 was already inactivated in the cetacean ancestor, and thus prior to a period of brain size expansion that resulted in the large brains of dolphins (Boddy et al., 2012; Montgomery et al., 2013) (Figure 2B). For the elephant lineage, we used molecular dating to estimate that HMGCS2 was lost around 45–42 Mya (Supplementary file 3). Thus, like in toothed whales, the loss of this gene likely occurred prior to the period that led to large relative brain sizes in modern elephants (Shoshani et al., 2006) (Figure 2C). Consequently, while ketogenesis was likely a crucial factor for brain size increase in humans (Cunnane and Crawford, 2003; Wang et al., 2014), the loss of ketogenesis has not prohibited drastic evolutionary brain size expansion in two other mammalian lineages.

In conclusion, we have identified three independent losses of HMGCS2 in placental mammals. While this may contribute to starvation sensitivity in fruit bats, cetaceans and elephants can withstand periods of fasting. Hence, alternative strategies to fuel large brains during fasting have evolved at least twice, revealing flexibility in the energy metabolism of mammals. Finally, the timing of HMGCS2 loss indicates that ketogenesis is not a universal precondition for the evolution of large mammalian brains. More generally, our results further highlight the potential of comparative gene analyses (Emerling and Springer, 2014; Meredith et al., 2009; Castro et al., 2014; Albalat and Cañestro, 2016; Lopes-Marques et al., 2017; Hecker et al., 2017; Gaudry et al., 2017; Sharma et al., 2018a; Sharma et al., 2018b; Meyer et al., 2018; Emerling et al., 2018) to reveal novel insights into the evolution of metabolic, physiological or morphological phenotypes.

All data analyzed during this study are publicly available on NCBI, SRA and the Trace Archive. The alignment used to date gene loss provided as a source file.

1. 1. Zhang G
   2. Cowled C
   3. Shi Z
   4. Huang Z
   5. Bishop-Lilly KA
   6. Fang X
   7. Wynne JW
   8. Xiong Z
   9. Baker ML
   10. Zhao W
   11. Tachedjian M
   12. Zhu Y
   13. Zhou P
   14. Jiang X
   15. Ng J
   16. Yang L
   17. Wu L
   18. Xiao J
   19. Feng Y

   (2013) Black flying fox raw sequence reads

   Publicly available at the NCBI Sequence Read Archive (accession no. SRX174444).

   https://www.ncbi.nlm.nih.gov/sra/SRX174444
2. 1. Zhang G
   2. Cowled C
   3. Shi Z
   4. Huang Z
   5. Bishop-Lilly KA
   6. Fang X
   7. Wynne JW
   8. Xiong Z
   9. Baker ML
   10. Zhao W
   11. Tachedjian M
   12. Zhu Y
   13. Zhou P
   14. Jiang X
   15. Ng J
   16. Yang L
   17. Wu L
   18. Xiao J
   19. Feng Y
   20. Chen Y
   21. Sun X
   22. Zhang Y
   23. Marsh GA
   24. Crameri G
   25. Broder CC
   26. Frey KG
   27. Wang LF
   28. Wang J.

   (2013) Black flying fox raw sequence reads

   Publicly available at the NCBI Sequence Read Archive (accession no. SRX174445).

   https://www.ncbi.nlm.nih.gov/sra/SRX174445
3. 1. Zhang G
   2. Cowled C
   3. Shi Z
   4. Huang Z
   5. Bishop-Lilly KA
   6. Fang X
   7. Wynne JW
   8. Xiong Z
   9. Baker ML
   10. Zhao W
   11. Tachedjian M
   12. Zhu Y
   13. Zhou P
   14. Jiang X
   15. Ng J
   16. Yang L
   17. Wu L
   18. Xiao J
   19. Feng Y
   20. Chen Y
   21. Sun X
   22. Zhang Y
   23. Marsh GA
   24. Crameri G
   25. Broder CC
   26. Frey KG
   27. Wang LF
   28. Wang J.

   (2013) Black flying fox raw sequence reads

   Publicly available at the NCBI Sequence Read Archive (accession no. SRX174446.

   https://www.ncbi.nlm.nih.gov/sra/SRX174446
4. 1. Zhang G
   2. Cowled C
   3. Shi Z
   4. Huang Z
   5. Bishop-Lilly KA
   6. Fang X
   7. Wynne JW
   8. Xiong Z
   9. Baker ML
   10. Zhao W
   11. Tachedjian M
   12. Zhu Y
   13. Zhou P
   14. Jiang X
   15. Ng J
   16. Yang L
   17. Wu L
   18. Xiao J
   19. Feng Y
   20. Chen Y
   21. Sun X
   22. Zhang Y
   23. Marsh GA
   24. Crameri G
   25. Broder CC
   26. Frey KG
   27. Wang LF
   28. Wang J.

   (2013) Black flying fox raw sequence reads

   Publicly available at the NCBI Sequence Read Archive (accession no. SRX174448).

   https://www.ncbi.nlm.nih.gov/sra/SRX174448
5. 1. Kerstin Lindblad-Toh
   2. Manuel Garber
   3. Or Zuk
   4. Michael F. Lin
   5. Brian J. Parker
   6. Stefan Washietl
   7. Pouya Kheradpour
   8. Jason Ernst
   9. Gregory Jordan
   10. Evan Mauceli
   11. Lucas D. Ward
   12. Craig B. Lowe
   13. Alisha K. Holloway
   14. Michele Clamp
   15. Sante Gnerre
   16. Jessica Alföldi
   17. Kathryn Beal
   18. Jean Chang
   19. Hiram Clawson
   20. James Cuff
   21. Federica Di Palma
   22. Stephen Fitzgerald
   23. Paul Flicek
   24. Mitchell Guttman
   25. Melissa J. Hubisz
   26. David B. Jaffe
   27. Irwin Jungreis
   28. W. James Kent
   29. Dennis Kostka
   30. Marcia Lara
   31. Andre L. Martins
   32. Tim Massingham
   33. Ida Moltke
   34. Brian J. Raney
   35. Matthew D. Rasmussen
   36. Jim Robinson
   37. Alexander Stark
   38. Albert J. Vilella
   39. Jiayu Wen
   40. Xiaohui Xie
   41. Michael C. Zody
   42. Broad Institute Sequencing Platform and Whole Genome Assembly Team
   43. Kim C. Worley
   44. Christie L. Kovar
   45. Donna M. Muzny
   46. Richard A. Gibbs
   47. Baylor College of Medicine Human Genome Sequencing Center Sequencing Team
   48. Wesley C. Warren
   49. Elaine R. Mardis
   50. George M. Weinstock
   51. Richard K. Wilson
   52. Genome Institute at Washington University
   53. Ewan Birney
   54. Elliott H. Margulies
   55. Javier Herrero
   56. Eric D. Green
   57. David Haussler
   58. Adam Siepel
   59. Nick Goldman
   60. Katherine S. Pollard
   61. Jakob S. Pedersen
   62. Eric S. Lander & Manolis Kellis

   (2011) Large flying fox raw sequence reads

   Publicly available at the Human Genome Sequencing Center.

   https://www.hgsc.bcm.edu/other-mammals/megabat-genome-project
6. 1. Kerstin Lindblad-Toh
   2. Manuel Garber
   3. Or Zuk
   4. Michael F. Lin
   5. Brian J. Parker
   6. Stefan Washietl
   7. Pouya Kheradpour
   8. Jason Ernst
   9. Gregory Jordan
   10. Evan Mauceli
   11. Lucas D. Ward
   12. Craig B. Lowe
   13. Alisha K. Holloway
   14. Michele Clamp
   15. Sante Gnerre
   16. Jessica Alföldi
   17. Kathryn Beal
   18. Jean Chang
   19. Hiram Clawson
   20. James Cuff
   21. Federica Di Palma
   22. Stephen Fitzgerald
   23. Paul Flicek
   24. Mitchell Guttman
   25. Melissa J. Hubisz
   26. David B. Jaffe
   27. Irwin Jungreis
   28. W. James Kent
   29. Dennis Kostka
   30. Marcia Lara
   31. Andre L. Martins
   32. Tim Massingham
   33. Ida Moltke
   34. Brian J. Raney
   35. Matthew D. Rasmussen
   36. Jim Robinson
   37. Alexander Stark
   38. Albert J. Vilella
   39. Jiayu Wen
   40. Xiaohui Xie
   41. Michael C. Zody
   42. Broad Institute Sequencing Platform and Whole Genome Assembly Team
   43. Kim C. Worley
   44. Christie L. Kovar
   45. Donna M. Muzny
   46. Richard A. Gibbs
   47. Baylor College of Medicine Human Genome Sequencing Center Sequencing Team
   48. Wesley C. Warren
   49. Elaine R. Mardis
   50. George M. Weinstock
   51. Richard K. Wilson
   52. Genome Institute at Washington University
   53. Ewan Birney
   54. Elliott H. Margulies
   55. Javier Herrero
   56. Eric D. Green
   57. David Haussler
   58. Adam Siepel
   59. Nick Goldman
   60. Katherine S. Pollard
   61. Jakob S. Pedersen
   62. Eric S. Lander & Manolis Kellis

   (2011) Large flying fox raw sequence reads

   Publicly available at the NCBI Sequence Read Archive (accession no. SRX708163).

   https://www.ncbi.nlm.nih.gov/sra/SRX708163
7. 1. Kerstin Lindblad-Toh
   2. Manuel Garber
   3. Or Zuk
   4. Michael F. Lin
   5. Brian J. Parker
   6. Stefan Washietl
   7. Pouya Kheradpour
   8. Jason Ernst
   9. Gregory Jordan
   10. Evan Mauceli
   11. Lucas D. Ward
   12. Craig B. Lowe
   13. Alisha K. Holloway
   14. Michele Clamp
   15. Sante Gnerre
   16. Jessica Alföldi
   17. Kathryn Beal
   18. Jean Chang
   19. Hiram Clawson
   20. James Cuff
   21. Federica Di Palma
   22. Stephen Fitzgerald
   23. Paul Flicek
   24. Mitchell Guttman
   25. Melissa J. Hubisz
   26. David B. Jaffe
   27. Irwin Jungreis
   28. W. James Kent
   29. Dennis Kostka
   30. Marcia Lara
   31. Andre L. Martins
   32. Tim Massingham
   33. Ida Moltke
   34. Brian J. Raney
   35. Matthew D. Rasmussen
   36. Jim Robinson
   37. Alexander Stark
   38. Albert J. Vilella
   39. Jiayu Wen
   40. Xiaohui Xie
   41. Michael C. Zody
   42. Broad Institute Sequencing Platform and Whole Genome Assembly Team
   43. Kim C. Worley
   44. Christie L. Kovar
   45. Donna M. Muzny
   46. Richard A. Gibbs
   47. Baylor College of Medicine Human Genome Sequencing Center Sequencing Team
   48. Wesley C. Warren
   49. Elaine R. Mardis
   50. George M. Weinstock
   51. Richard K. Wilson
   52. Genome Institute at Washington University
   53. Ewan Birney
   54. Elliott H. Margulies
   55. Javier Herrero
   56. Eric D. Green
   57. David Haussler
   58. Adam Siepel
   59. Nick Goldman
   60. Katherine S. Pollard
   61. Jakob S. Pedersen
   62. Eric S. Lander & Manolis Kellis

   (2011) Large flying fox raw sequence reads

   Publicly available at the NCBI Sequence Read Archive (accession no. SRX708167).

   https://www.ncbi.nlm.nih.gov/sra/SRX708167
8. 1. Kerstin Lindblad-Toh
   2. Manuel Garber
   3. Or Zuk
   4. Michael F. Lin
   5. Brian J. Parker
   6. Stefan Washietl
   7. Pouya Kheradpour
   8. Jason Ernst
   9. Gregory Jordan
   10. Evan Mauceli
   11. Lucas D. Ward
   12. Craig B. Lowe
   13. Alisha K. Holloway
   14. Michele Clamp
   15. Sante Gnerre
   16. Jessica Alföldi
   17. Kathryn Beal
   18. Jean Chang
   19. Hiram Clawson
   20. James Cuff
   21. Federica Di Palma
   22. Stephen Fitzgerald
   23. Paul Flicek
   24. Mitchell Guttman
   25. Melissa J. Hubisz
   26. David B. Jaffe
   27. Irwin Jungreis
   28. W. James Kent
   29. Dennis Kostka
   30. Marcia Lara
   31. Andre L. Martins
   32. Tim Massingham
   33. Ida Moltke
   34. Brian J. Raney
   35. Matthew D. Rasmussen
   36. Jim Robinson
   37. Alexander Stark
   38. Albert J. Vilella
   39. Jiayu Wen
   40. Xiaohui Xie
   41. Michael C. Zody
   42. Broad Institute Sequencing Platform and Whole Genome Assembly Team
   43. Kim C. Worley
   44. Christie L. Kovar
   45. Donna M. Muzny
   46. Richard A. Gibbs
   47. Baylor College of Medicine Human Genome Sequencing Center Sequencing Team
   48. Wesley C. Warren
   49. Elaine R. Mardis
   50. George M. Weinstock
   51. Richard K. Wilson
   52. Genome Institute at Washington University
   53. Ewan Birney
   54. Elliott H. Margulies
   55. Javier Herrero
   56. Eric D. Green
   57. David Haussler
   58. Adam Siepel
   59. Nick Goldman
   60. Katherine S. Pollard
   61. Jakob S. Pedersen
   62. Eric S. Lander & Manolis Kellis

   (2011) Large flying fox raw sequence reads

   Publicly available at the NCBI Sequence Read archive (accession no. SRX708168).

   https://www.ncbi.nlm.nih.gov/sra/SRX708168
9. 1. Kerstin Lindblad-Toh
   2. Manuel Garber
   3. Or Zuk
   4. Michael F. Lin
   5. Brian J. Parker
   6. Stefan Washietl
   7. Pouya Kheradpour
   8. Jason Ernst
   9. Gregory Jordan
   10. Evan Mauceli
   11. Lucas D. Ward
   12. Craig B. Lowe
   13. Alisha K. Holloway
   14. Michele Clamp
   15. Sante Gnerre
   16. Jessica Alföldi
   17. Kathryn Beal
   18. Jean Chang
   19. Hiram Clawson
   20. James Cuff
   21. Federica Di Palma
   22. Stephen Fitzgerald
   23. Paul Flicek
   24. Mitchell Guttman
   25. Melissa J. Hubisz
   26. David B. Jaffe
   27. Irwin Jungreis
   28. W. James Kent
   29. Dennis Kostka
   30. Marcia Lara
   31. Andre L. Martins
   32. Tim Massingham
   33. Ida Moltke
   34. Brian J. Raney
   35. Matthew D. Rasmussen
   36. Jim Robinson
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   52. Genome Institute at Washington University
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   55. Javier Herrero
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10. 1. Beijing Genomics Institute

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11. 1. Beijing Genomics Institute

    (2015) Dolphin raw sequence reads

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12. 1. Beijing Genomics Institute

    (2015) Dolphin raw sequence reads

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13. 1. The National Institute of Standards and Technology

    (2016) Dolphin raw sequence reads

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14. 1. The National Institute of Standards and Technology

    (2016) Dolphin raw sequence reads

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15. 1. The National Institute of Standards and Technology

    (2016) Dolphin raw sequence reads

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    10. Eric S. Lander & Manolis Kellis

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    26. Gibbs RA.

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    24. Worley KC
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    (2015) Killer whale raw sequence reads

    Publicly available at the NCBI Sequence Read Archive (accession no. SRX188933).

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    12. Tae Wan Kim
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    16. Dong Han Choi
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    20. Hyunmin Kim
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    31. Tae Hyung Kim
    32. Lili Yu
    33. Sha Liu
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    45. Hang Lee
    46. Jumpei Kimura
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    52. Jun Wang
    53. Jong Bhak
    54. Hyun Sook Lee & Jung-Hyun Lee

    (2014) Minke whale raw sequence reads

    Publicly available at the NCBI Sequence Read Archive (accession no. SRX302112).

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    5. Jae-Yeon Jeong
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    7. Hyun-Myung Oh
    8. Jae-Hak Lee
    9. Eun Chan Yang
    10. Kae Kyoung Kwon
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    16. Dong Han Choi
    17. Sungwoong Jho
    18. Hak-Min Kim
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    20. Hyunmin Kim
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    22. Hyun-Ju Jung
    23. Yuan Zheng
    24. Zhuo Wang
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    28. Erli Li
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    32. Lili Yu
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    35. Jesse Cooper
    36. Sin-Gi Park
    37. Chang Pyo Hong
    38. Wook Jin
    39. Heui-Soo Kim
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    41. Kyooyeol Lee
    42. Sung Chun
    43. Phillip A Morin
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    45. Hang Lee
    46. Jumpei Kimura
    47. Dae Yeon Moon
    48. Andrea Manica
    49. Jeremy Edwards
    50. Byung Chul Kim
    51. Sangsoo Kim
    52. Jun Wang
    53. Jong Bhak
    54. Hyun Sook Lee & Jung-Hyun Lee

    (2015) Minke whale raw sequence reads

    Publicly available at the NCBI Sequence Read Archive (accession no. SRX316745).

    https://www.ncbi.nlm.nih.gov/sra/SRX316745
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    2. Bjørghild B. Seliussen
    3. María Quintela
    4. Geir Dahle
    5. Francois Besnier
    6. Hans J. Skaug
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    8. Hiroko K. Solvang
    9. Tore Haug
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    11. Naohisa Kanda
    12. Luis A. Pastene
    13. Inge Jonassen and Kevin A. Glover

    (2016) Minke whale raw sequence reads

    Publicly available at the NCBI Sequence Read Archive (accession no. SRX2007381).

    https://www.ncbi.nlm.nih.gov/sra/SRX2007381
22. 1. Ketil Malde
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    4. Geir Dahle
    5. Francois Besnier
    6. Hans J. Skaug
    7. Nils Øien
    8. Hiroko K. Solvang
    9. Tore Haug
    10. Rasmus Skern-Mauritzen
    11. Naohisa Kanda
    12. Luis A. Pastene
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    (2016) Minke whale sequence reads

    Publicly available at the NCBI Sequence Read Archive (accession no. SRX2007379).

    https://www.ncbi.nlm.nih.gov/sra/SRX2007379
23. 1. Ketil Malde
    2. Bjørghild B. Seliussen
    3. María Quintela
    4. Geir Dahle
    5. Francois Besnier
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    7. Nils Øien
    8. Hiroko K. Solvang
    9. Tore Haug
    10. Rasmus Skern-Mauritzen
    11. Naohisa Kanda
    12. Luis A. Pastene
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    (2016) Minke whale sequence reads archive

    Publicly available at the NCBI Read Archive (accession no. SRX2007373).

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24. 1. Ketil Malde
    2. Bjørghild B. Seliussen
    3. María Quintela
    4. Geir Dahle
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    6. Hans J. Skaug
    7. Nils Øien
    8. Hiroko K. Solvang
    9. Tore Haug
    10. Rasmus Skern-Mauritzen
    11. Naohisa Kanda
    12. Luis A. Pastene
    13. Inge Jonassen and Kevin A. Glover\

    (2016) Minke whale sequence reads

    Publicly available at the NCBI Sequence Read Archive (accession no. SRX2007368).

    https://www.ncbi.nlm.nih.gov/sra/SRX2007368
25. 1. Wesley C. Warren
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    5. Jose G. Perez-Silva
    6. Carlos Lopez-Otın
    7. Vıctor Quesada
    8. Patrick Minx
    9. Chad Tomlinson
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    13. Tomas Marques-Bonet
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    15. Troy J. Kieran
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    17. John Pierce Wise Jr
    18. Robert M. Waterhouse
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    (2017) Sperm whale sequence reads

    Publicly available at the NCBI Sequence Read Archive (accession no. SRX220365).

    https://www.ncbi.nlm.nih.gov/sra/SRX220365
26. 1. Wesley C. Warren
    2. Lukas Kuderna
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    5. Jose G. Perez-Silva
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    7. Vıctor Quesada
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    17. John Pierce Wise Jr
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    (2017) Sperm whale raw sequence reads

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27. 1. Wesley C. Warren
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    18. Robert M. Waterhouse
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    (2017) Sperm whale sequence reads

    Publicly available at the NCBI Sequence Read Archive (accession no. SRX220367).

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28. 1. Puli Chandramouli Reddy
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    6. Raman Sukumar
    7. Sanjeev Galande

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29. 1. Palkopoulou E
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30. 1. Palkopoulou E
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Author details

1. David Jebb

   1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
   2. Max Planck Institute for the Physics of Complex Systems, Dresden, Germany
   3. Center for Systems Biology Dresden, Dresden, Germany

   Contribution

   Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6362-7378

2. Michael Hiller

   1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
   2. Max Planck Institute for the Physics of Complex Systems, Dresden, Germany
   3. Center for Systems Biology Dresden, Dresden, Germany

   Contribution

   Conceptualization, Supervision, Funding acquisition, Investigation, Visualization, Writing—original draft, Project administration, Writing—review and editing

   For correspondence

   hiller@mpi-cbg.de

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3024-1449

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