Chitinase Expression in the Stomach of the Aye-Aye (Daubentonia

Home , Duke Lemur Center, Galago, Lemur, Lemuridae, Mouse lemur, Sportive lemur

CHITINASE EXPRESSION IN THE STOMACH OF THE AYE-AYE (DAUBENTONIA

MADAGASCARIENSIS).

A thesis submitted

To Kent State University in partial

Fulfilment of the requirements for the

Degree of Master of Arts

Melia G. Romine

August 2020

Except for previously published materials

Thesis written by

Melia G. Romine

B.S., Kent State University, 2018

M.A., Kent State University, 2020

Approved by

______, Advisor Dr. Anthony J. Tosi

______, Chair, Department of Anthropology Dr. Mary Ann Raghanti

______, Interim Dean, College of Arts and Sciences Dr. Mandy Munro-Stasiuk

TABLE OF CONTENTS ------iii

LIST OF FIGURES ------v

LIST OF TABLES ------vi

DEDICATION ------vii

ACKNOWLEDGEMENTS ------viii

CHAPTERS

I. INTRODUCTION ------1

FEEDING STRATEGIES ------2

OPTIMAL FOOD SOURCES ------3

BODY SIZE ------6

DAUBENTONIA MADAGASCARIENSIS AND THEIR ADAPTIVE SUITE------8

DENTITION ------9

SPECIALIZED MIDDLE DIGIT------9

AUDITORY SYSTEM ------10

BEHAVIOR AND ECOLOGY OF DAUBENTONIA MADAGASCARIENSIS ------11

NATURAL HISTORY OF DAUBENTONIA MADAGASCARIENSIS ------15

PHYLOGENY OF DAUBENTONIA MADAGASCARIENSIS ------15

COMPARATIVE PRIMATE: EULEMUR MACACO ------15

CHITIN AND CHITINASE ------17

HYPOTHESIS ------19

II. METHODS ------21

SAMPLES ------21

RNA SEQUENCING ------22

iii

SEQUENCE ALIGNMENTS AND TRIMMING ------23

BIOINFORMATIC TOOLS FOR ANALYSIS ------24

III. RESULTS ------27

QUALITY REPORT OF SEQUENCE READS------27

ANNOTATION REPORTS ------27

ABUNDANCE REPORTS ------32

STATISTICAL ANALYSIS ------33

EVOLUTIONARY COMPARISONS OF CHIA IN PRIMATES ------34

IV. DISCUSSION AND CONCLUSION ------37

DISCUSSION ------37

FUNCTIONAL CHITINASE IN AYE-AYE AND BLACK LEMUR ------37

AYE-AYE AND CHITINASE ORIGINS ------39

RE-EXAMINING THE JARMAN-BELL PRINCIPLE / KAY’S THRESHOLD ---39

CHITINASE AND INSECT EATING HUMANS ------40

CONCLUSION AND FUTURE CONSIDERATIONS ------40

REFERENCES ------42

LIST OF FIGURES

Figure 1. Image of aye-aye ------2

Figure 2. Table adapted from “A Jarman-Bell Model of Primate Feeding Niches” ------4

Figure 3. Image of Japanese Walnut ------5

Figure 4. Map distribution of aye-aye sightings ------11

Figure 5. Phylogeny of Strepsirrhines------16

Figure 6. 3-D rope model ------17

Figure 7. Example of de novo assembly ------23

Figure 8. Top 10 CHIA1 matches to aye-aye ------29

Figure 9. Top 10 CHIA2 matches to aye-aye ------29

Figure 10. Top 10 CHIA3 matches to aye-aye ------29

Figure 11. Top 10 CHIA4 matches to aye-aye ------30

Figure 12. Top 10 CHIA5 matches to aye-aye ------30

Figure 13. Top 10 CHIA1 matches to black lemur ------30

Figure 14. Top 10 CHIA2 matches to black lemur ------30

Figure 15. Top 10 CHIA3 matches to black lemur ------31

Figure 16. Top 10 CHIA4 matches to black lemur ------31

Figure 17. Top 10 CHIA5 matches to black lemur------31

Figure 18. Top 10 GAPDH matches to aye-aye ------32

Figure 19. Top 10 GAPDH matches to black lemur ------32

Figure 20. Chitinase catalytic site ------34

Figure 21. Chitin-binding domain ------35

Figure 22. Phylogenetic Tree ------36

LIST OF TABLES

Table 1. Overall concept of Jarman-Bell Principle ------6

Table 2. Table adapted from "Testing Convergent Evolution in Auditory Processing------11

Table 3. Notable observational studies ------14

Table 4. Stomach tissue samples ------21

Table 5. Quick Biology sequencing identifiers ------23

Table 6. Kallisto scripts ------25

Table 7. Gene and Protein IDs------26

Table 8. Sequencing Report Summary ------27

Table 9. Transcript per million values for aye-aye ------32

Table 10. Transcript per million values for black lemur ------33

Table 11. CHIA to GAPDH values ------33

Dedication

I dedicate this project to my beloved mother, Martha Renee Romine. You have always seen

my potential even when I could not. You are my rock and I love you always.

Also, to my official cheerleaders, twisted sistas, confidants, and everything else,

Rikayla Wright and Arrik Brown

vii

Acknowledgements

First and foremost, I would like to thank Dr. Anthony Tosi for giving me the opportunity to pursue my master’s degree. Being in this program has opened up the door for new opportunities. Next, I would like to thank my committee members, Dr. Mary Ann

Raghanti and Dr. Richard Meindl. I appreciate your expertise through the program.

Then I would like to take the time to recognize my lab mates and faculty members that helped me through this whole process. Morgan Chaney, you have taken so much time to teach me the foundational techniques I needed for this project. I consider you a mentor and hope to continue to work with you on future projects. You are destined to be great! Cody Ruiz, thank you for always lending an ear and talking me off the ledge so to speak. I will always treasure our friendship. Danielle Jones, you have always been the voice of reason throughout this program and I could not have gotten this far without you.

Dr. Metin Eren, Dr. Owen Lovejoy, and Dr.Linda Spurlock, you all have always believed in me from the start. Your encouraging words made me realize that I do belong in the field of science. Dr. Sangeet Lamichhaney, I appreciate you for taking time out of your schedule to guide me through all the bioinformatics required for my project. You made it easy to learn and I will carry that with me throughout my entire career.

Finally, lastly but certainly not least, thank you to all my cohort! Special thanks to Dusty, Sarah, Alyssa and Anna for forming the official pork and stouts crew.

You all dragged me to the finish line whether I wanted to cross it or not. You all are friends I will have for the rest of my life.

viii

Chapter 1:

Introduction

The biological success of an organism is measured by the amount of offspring they produce.

Adequate nutrition and caloric intake are critical for an organism to not only reach reproductive age, but also to be healthy enough to reproduce. Animals exhibit a wide variety of feeding strategies – not only what they eat, but how they obtain and process the food. The order

Primates includes a variety of diet types (e.g. insectory vs. folivory), as well as morphological and behavioral specializations, such as sacculated stomachs in colobines and coprophagy in lemurs, that help these species to maximize nutrient extraction.

Among the primates, the aye-aye (Daubentonia madagascariensis) is of particular interest for at least two reasons. Principles of primate nutritional ecology suggest that insectivores are constrained to body sizes below 500 grams (Kay, 1984), presumably because a large animal would not be able to catch enough insects, and extract enough nutrition, to sustain it on a daily basis. However, aye-ayes have a considerable diet of insects and larvae and weigh ~2.5 kg; they are theoretically too large to be insectivores. The aye-aye’s digestive system raises a second point of interest. A recent study of mammalian genomes suggests that aye-ayes lack any functional enzymes to break down chitin (Emerling et al. 2018), one of the major structural components of insect exoskeletons; if this is true, aye-ayes would be employing an incredibly

inefficient feeding strategy, considering that a significant amount of their foraging time is dedicated to insects and larvae (Figure 1). This thesis explores these issues in the feeding ecology of aye-ayes, particularly as related to the presence of functional chitinase, and its expression level, in the stomach of these animals.

Figure 1. Image of aye-aye tap foraging found on the Duke Lemur Center website.

1.1 Feeding Strategies

1.1a Optimal Food Sources

Accessing food sources and extracting their benefits are critical for an organism’s survival.

However, all creatures have limited resources in time and energy for foraging. This leads to the general notion of a feeding strategy, including an understanding of what would make an optimal food for an animal. Thomas Schoener developed the following formula to evaluate the relative value of food items in an animal’s diet:

푃표푡푒푛푡𝑖푎푙 푒푛푒푟푔푦 표푓 푓표표푑 𝑖푡푒푚 − 푝푢푟푠푢𝑖푡 푐표푠푡푠 − ℎ푎푛푑푙𝑖푛푔 푎푛푑 푒푎푡𝑖푛푔 푐표푠푡푠 푒 = 푖 푃푢푟푠푢𝑖푡 푡𝑖푚푒 + ℎ푎푛푑푙𝑖푛푔 푎푛푑 푒푎푡𝑖푛푔 푡𝑖푚푒 푡푖

푒푖 “where the ratio ⁄푡 represents the net energy yield per unit time from items of type i” 푖8 (Schoener, 1971). The highest ratio, greatest “e” over “t”, represents the optimal food item because the energy gained in consuming the food item outweighs the costs in time and energy spent trying to obtain the food item. Essentially, the concept is fast food, but high quality.

Figure 2 outlines food sources that are common among wild primates and demonstrates that insects are the highest quality food based on their high protein content. Though they are the highest quality, insects are not easy to obtain: they are mobile and use defensive strategies to avoid predators (Evans & Schmidt, 1990; Gaulin, 1978). Fruits, seeds, gums and flowers are occasionally abundant, but nonetheless limited by seasonality. Generally, the higher the quality of the food item, the harder it is to obtain and/or to extract nutritional benefits from. As suggested, feeding strategies are also affected by food availability. If there is not enough of the optimal food item, or the preferred food item to solely live off, then other food items must be supplemented to accommodate the nutritional needs, a concept denoted as “fallback foods”

(Gaulin, 1978; Marshall, Boyko, Feilen, Boyko, & Leighton, 2009; Marshall & Wrangham,

2007). However, if there is a high abundance of optimal food for an animal, then there will be potential for specialization (Schoener, 1971).

Figure 2. Table adapted from "A Jarman/Bell Model of Primate Feeding Niches"(p. 7), by Steven Gaulin, 1979. The dry components of each food type were measured. The highest nutrient has been highlighted for each food item. The food items are listed in order of increasing quality, starting from poorest at the top.

Schoener’s model was tested in an experiment with Parus major, also known as the great tit, to see if predation choices favor optimal food types (Krebs, Erichsen, Webber, & Charnov,

1977). Two prey types were presented to the birds, mealworms with eight segments and mealworms with four segments. When the prey types were presented in low abundance, the birds had no preference. When the larger mealworms Figure 3. Image of a Japanese walnut consumed by Japanese macaques. (From were presented at a higher abundance, not only did “Extractive foraging on hard-shelled walnuts and variation of feeding techniques in wild the birds select the larger mealworms, but they also Japanese macaques," by M. Tamura, 2020. American Journal of Primatology, Vol 82, p. 3 ignored the smaller mealworms when they appeared. As Schoener’s equation suggests, the birds began to target the more nutritious

(abundant) prey option that also required no extra energy expenditure.

In a more recent study, Macaca fuscata, also known as the Japanese macaque, were observed breaking open hard-shelled walnuts (Tamura, 2020). Japanese walnuts are highly nutritious, containing roughly 23 grams of protein, 60 grams of lipids and 7 grams of carbohydrates (Chiba, 2016). The macaques utilize this food source when the walnuts are available from the months of September to December. Though the walnuts are hard to break open, the macaques have figured out a way using their hands and teeth to access the cotyledon, the inner part of the nut (Figure 3). Such strategies to access foods trapped in hard encasings are known as extractive foraging (King, 1986). Tamura (2020) identified four types of cracking methods used by the Japanese macaques: crunch, bilateral-crack, hole-punch, and the unilateral-

crack. Though this study does not serve as a direct test of Schoener’s equation, the observations can readily be viewed through such a lens. Given that Japanese walnuts are highly nutritious and are abundant during only a limited seasonal window, the Japanese macaques invest time to develop foraging techniques to access this very beneficial food source. Further analyses can be performed to calculate the walnut’s optimization ratio in terms of energy gain to determine whether the time (“t”) variable might be high or low, thereby refuting or supporting the case that foraging walnuts is energetically optimal. Schoener’s equation provides a great theoretical framework for exploring variables for optimal food sources. Understanding the causes of primate food choices is the foundation for studies of nutritional ecology.

1.1 b Body Size

The Jarman-Bell principle proposes that body size is a critical component of feeding strategy

(Bell, 1971; Gaulin, 1978; Jarman, 1974). It highlights the relationship between body size and metabolism: as body weight increases, the metabolic rate increases at a slower rate. In other words, while larger animals need larger amounts of food, they do not need as much energy per unit of body weight (Klieber, 1961; Munro, 1969). Consequently, larger animals can survive on lower quality foods, they simply need to intake a larger volume of them (Table 1).

Table 1. Overall concept of the Jarman/Bell Principle adapted from Gaulin (1979).

Animal Size Amount of Food Nutritious Food Per Body Weight

Small Low Amount High Quality Large High Amount Low Quality

In an effort to generalize ecological diversity of primates, the Jarman-Bell principle has been used to create a model – known as Kay’s threshold – to predict the diet of specific primates, including extinct taxa, based solely on their size (Gaulin, 1978; Kay, 1984; Sailer,

Gaulin, Boster, & Kurland, 1985). Kay’s threshold suggests that insectivorous primates cannot exceed 500 grams and that folivores must be above 700 grams (Kay, 1984). Small-bodied primates have a higher metabolism than larger-bodied primates (Gebo, 2004; Kay, 1984). High caloric intake must accommodate a higher metabolism (Klieber, 1961; Munro, 1969). Smaller primates also have a lower nutrient requirement than larger primates. This means that smaller primates can eat fewer items if the food item has an abundance of high-quality nutrients. Food items that are high in nutrients such as proteins and carbohydrates would be able to fulfill a dietary need of a small primate. The energy gained from high nutrient food sources must outweigh the energy put into finding them. Therefore, smaller primates can afford to spend energy in obtaining difficult food sources such as gums, insects, and seeds (Kay, 1984). The larger the primate, the greater volume of nutrients they require. Due to the high requirement of nutrients, the more effective strategy of larger primates is to focus on food items that occur in bulk quantities and are easily obtainable such as leaves and foliage (Gaulin, 1977).

Sailer et al. (1985) compared the body weights of 72 species, spanning the primate order, against the relative amounts of foliage and animal matter they consumed. Log body weights were plotted against the percent foliage in each primate’s diet. The results were significant, but only 27.7% of the variance was explained by the regression analysis (Sailer et al., 1985). A smaller study (Gaulin, 1978) collected body weights of primates from the suborder

Prosimii, and the superfamilies Ceboidea, Cercopithecoidea, and Hominoidea and plotted them against diet types of increasing quality, from leaves as the lowest quality to insects as the

highest quality.NewWorld monkeys and Old World monkeys followed the trend of low quality diets with increasing body weight (Gaulin, 1978). Hominoids were consistent with the Jarman-

Bell principle, but one thing to note is that they occupy only a few food niches (Gaulin, 1978).

Among the prosimians, Lepilemur mustelinus (sportive lemur) and Daubentonia madagascariensis (aye-aye) were exceptions to the Jarman-Bell principle. The sportive lemur has a unique feeding behavior in that it ingests its own fecal matter (Charles-Dominique, 1972;

Hladik, 1978). Ingesting fecal matter, also known as coprophagy, has a net effect of converting low quality food items into higher quality items (Alexander, 1993). The aye-aye has a whole adaptive suite that allows them to forage for insects regardless of their large body size. The next section will explore these specializations.

1.2 Daubentonia madagascariensis and Their Adaptive Suite

The aye-aye is classified as an insectivore (Gaulin, 1978; Napier & Napier, 1967; Petter, 1965), as its diet consists mostly of larvae and adult insects, along with seeds, cankers, fungus and nectar (Sterling, 1994). Based upon the Jarman-Bell principle and Kay’s Threshold, the aye-aye should be a frugivore (Kay, 1975). Its body size, 2.5-3kg, exceeds the limit to be an insectivore

(Kay, 1975; Sefczek et al., 2020; Sterling & McCreless, 2006). Due to the larger body size, there is a higher caloric need to be met. Though insects are the highest quality of food, it takes time and energy to forage for them. This would make insectivory a disadvantage to larger primates since investment costs (the time and energy needed to obtain a relatively large amount of “mobile” food) would not be outweighed by the benefit in nutrition (Bell, 1971; Jarman, 1974;

Kay, 1975). In order to sustain a greatly insectivorous diet with a large body weight, there have to be additional adaptations that aid in obtaining more insects per unit of foraging time.

1.2a Dentition

The dental formula of the aye-aye is 1 incisor 0 canines 1 premolar and 3 molars (Ankel‐Simons,

1996; Petter, 1977; Sterling & McCreless, 2006). Their incisors constantly grow and resemble that of a rodent (Petter, 1977; Sterling & McCreless, 2006). Their unique incisors allow them to access cotyledon from seeds (Iwano & Iwakawa, 1988) and to remove cankers from trees

(Sterling & McCreless, 2006; Sterling, 1994). The removal of cankers allows access to fungus.Importantly, the incisors are capable of prying off pieces of trees to expose larvae, on which they feed (Petter, 1965; Sterling, 1994).

1.2b Specialized Middle Digit

Aye-ayes exhibit a tapping behavior as they hunt for insects, known as percussive foraging

(Erickson, 1991; Erickson, Nowicki, Dollar, & Goehring, 1998; Thompson, Bankoff, Louis, &

Perry, 2016). They have a very slender, elongated third digit which, though less effective than other digits in locomotion and prehensile strength (Petter, 1977), has a great amount of independent control and extra flexibility due to its ball-and socket metacarpophalangeal joint.

The aye-aye taps this digit along branches to find cavities in trees (Cartmill, 1974; Gaulin, 1978;

Milliken, Ward, & Erickson, 1991; Napier & Napier, 1967; Petter, 1965; Soligo, 2005;

Thompson et al., 2016). Once found, the aye-aye will use its incisors to pry off the surface, and then use its extended third digit to hook the embedded larva without impaling it (Milliken et al.,

1991; Sterling, 1994). They also use this specialized digit to retrieve nectar from flowers and to collect adult ants (Sterling, 1994).

1.2.c Auditory System

The percussive foraging that aye-ayes use to access wood-bearing larva requires a special auditory system. Visual cues do not seem to be a factor in discovering these cavities considering that aye-ayes pry wood in areas that did not have any surface holes

(Erickson, 1991; Sterling & McCreless, 2006). Brain sections of the aye-aye show a relatively large frontal cortex size with a decrease in visual structures (Bush & Allman,

2004; Kaufman, Ahrens, Laidlaw, Zhang, & Allman, 2005; Schwitzer et al., 2013), but a relatively large inferior colliculus, a midbrain section important for sound (Kaufman et al., 2005). Their ears are larger and more mobile than any other lemur (Owen, 1863;

Sterling & McCreless, 2006). As the aye-aye is tapping on wood, their ears rotate forward to listen to reverberations from the tree (Bankoff et al., 2017; Erickson, 1991; Owen,

1863; Sterling & McCreless, 2006). The auditory processing skills of the aye-aye have often been compared to echolocating mammals such as dolphins and bats (Bankoff et al.,

2017). In a recent study, the molecular pathway of the auditory component in percussive foraging in aye-ayes was examined. Interestingly, aye-ayes did not have any amino acid convergence with genes associated with echolocation (Bankoff et al., 2017), indicating that molecular evolution does not always coincide with convergent behavioral ecology. A list of the genes that were a part of this study are briefly outlined in Table 2.

Gene Domain CDH23 Hair bundle formation and Stereocilia organization (Shen, Liang, Li, Murphy, & Zhang, 2012) KCNQ4 Cochlear neuronal excitability (Liu et al., 2011) OTOF Vesicle membrane fusion; knock out causes deafness in mice (Shen et al., 2012) PCDH15 Maintenance of retinal and cochlear function (Parker et al., 2013; Shen et al., 2012) PJVK Proper function of auditory neurons (Davies, Cotton, Kirwan, Teeling, & Rossiter, 2012)

SLC26A5 Cochlear hair motility and ion exchange (Liu et al., 2011; Parker et al., 2013) TMCI Required for normal function of cochlear hair cells (Davies et al., 2012; Parker et al., 2013)

Table 2. Table adapted from "Testing Convergent Evolution in Auditory Processing Genes between Echolocating Mammals and that Aye-Aye, a Percussive-Foraging Primate" by Bankoff et al., 2017.

1.3 Behavior and ecology of Daubentonia madagascariensis

Daubentonia madagascariensis is the most widely distributed extant lemur (Owen, 1863;

Sterling, 2003; Sterling, 1993) (see Figure 4). They have been observed in a wide variety of forests across Madagascar, ranging from dry to humid environments (Iwano & Iwakawa, 1988; Sterling,

1994) as well as primary to patchy forest

(Andriamasimanana, 1994; Petter, 1977). They are nocturnal, and when they return to their nest in the mornings, they often are seen in fruit trees

(Ancrenaz, Lackman-Ancrenaz, & Mundy, 1994;

Petter, 1977). One of the longest studies conducted Figure 4. Map distribution of aye-aye citings across Madagascar reprinted from "Adaptations in the Aye-aye" by Sterling & on aye-ayes took place from 1989 to 1991 on McCreless 2006

Nosy Mangabe, an island located northeast.of Madagascar (Sterling & McCreless, 2006;

Sterling, 1993, 1994). From that study, feeding time on various food items was documented during three different seasons over the span of two years. Canarium seeds, cankers from Instsia bijuga trees, nectar from Ravenala madagascariensis flowers and larva from three different taxonomic families were observed eaten in different frequencies, depending on the season

(Sterling, 1993). Specific larva included long horn beetles, scarab beetles and pyralid moths

(Pollock, Constable, Mittermeier, Ratsirarson, & Simons, 1985; Sterling, 1994). During hot, dry seasons, aye-ayes spent 90% of their feedingtime focusing on seeds and larva (Sterling &

McCreless, 2006; Sterling, 1993). During hot, wet seasons, seeds and larva composed 73% of their diet (Sterling & McCreless, 2006; Sterling, 1993). Lastly, half their diet consisted of cankers during the cold, wet season (Sterling & McCreless, 2006; Sterling, 1993). Table 3 summarizes a few observational studies that have been done on aye-aye ecology that highlight diet consumption, with the two-year study conducted by Sterling being the most comprehensive.

Aye-ayes are mostly solitary (or mother with offspring) outside of mating periods, which do not appear restricted to a particular time of the year (Ancrenaz et al.,

1994; Sterling, 1993).The aye-aye male mating system has been classified as scramble competition polygyny (Kappeler, 1997; Sterling & McCreless, 2006). Essentially, when females are available to conceive, they call out to attract males. Once a male approaches the female they will mate for an hour (Sterling & Richard, 1995). After copulation, a female will continue to call out again for males, ultimately resulting in polyandrous behavior (Sterling, 1993).

The aye-aye is listed as endangered by the International Union for the Conservation of

Nature. A predator capable of hunting the aye-aye is the fossa (Sefczek, Rakotomanana,

Randriamaronirina, & Louis Jr, 2018). The fossa are carnivorous cats, but aye-ayes have been able to manage their population under this predator (Petter, 1977; Sefczek et al., 2018) . Their decreasing numbers are likely the result of deforestation and hunting -- local villagers kill them because they are thought to be evil (Miller, Raharison, & Irwin, 2017; Simons & Meyers, 2001).

Table 3. Notable observational studies of aye-ayes

Research Study Research Number of Food Types Duration of Location Aye- ayes Noted with Research within Frequencies Study Madagascar Re-assessing the Torotorofotsy *Two aye-ayes. *Invertebrates *January 2016- applicability of the , Madagascar December 2017 Jarman/Bell model 1 adult female *Canarium sp. seeds and Kay’s threshold to and 1 juvenile the insectivorous aye- male aye (Daubentonia madagascariensis) (Sefczek et al., 2020)

Deadwood Structural Kianjavato, *Two aye-ayes. *Seeds from *June- Properties May Madagasca Canarium trees August 2013 Influence Aye-Aye r 1 adult male and (Daubentonia 1 adult female *Larva madagascariensis) from Extractive Foraging deadwood Behavior (Thompson et al., 2016) Ecoethological Study Mananara- *Two aye-ayes; *Larva *January 1991- of Free-Ranging Aye- Nord Biosphere June 1991 Ayes (Daubentonia Reserve 1 male and *Coconuts 1 female *January 1992- madagascariensis) in *Terminalia nuts Mdagascar June 1992 (Andriamasimanana, *Musa sp. nectar 1994) *T.catappa seeds *Artocarpus sp. flesh and seeds

Patterns of Range Use Nosy Mangabe * Eight aye-ayes; *Larva *Novembe and Social r 1989- Organization in Aye- 6 males and * Ravenala April Ayes (Daubentonia 2 females madagascariensi 1991 Madagascarensis) on s nectar Nosy Mangabe * Canarium Seeds (Sterling, 1993) * Instsia bijuga tree cankers

1.4 Natural history of Daubentonia madagascariensis

1.4a Phylogeny of Daubentonia madagascariensis

Aye-ayes were first recorded in Western science in 1780 by the French naturalist Pierre Sonnerat

(Petter, 1977). The animal was initially classified as a type of rodent, but 100 years later, after close anatomical examination by Richard Owen (1866), it was placed under the order Primates due to its opposable hallux, postorbital bar and stereoscopic vision (Owen, 1863, 1866; Sterling

& McCreless, 2006). Aye-ayes fall under the suborder Strepsirhini and infraorder Lemuriformes

(Goodman et al., 1998; Herrera & Dávalos, 2016), and they are the sole remaining lineage of the family Daubentoniidae (Gray, 1870; Perry et al., 2012) (see Figure 5). A related subfossil was discovered in 1935 and, given its large body size, was aptly named Daubentonia robusta

(Lamberton, 1934). Among the closest living relatives to the aye-aye are primates within the family Lemuridae (Figure 5). For the purpose of this study Eulemur macaco will be used as a comparative primate due to being a non-insectivorous member of the Lemuridae.

1.4 b Comparative Primate: Eulemur macaco

Eulemur macaco, commonly known as the black lemur, is another native of Madagascar.

Observational studies indicate that their diet consists mainly of fruits with some consumption of leaves and flowers (Andrews & Birkinshaw, 1998; Colquhoun, 1993; Simmen, Bayart, Marez,

& Hladik, 2007). One chemical analysis of a wild black lemur population suggested that the population may actually face a deficiency of daily protein intake during the birth season possibly due to their specialization on fruits (Simmen et al., 2007). Black lemurs have a multi- male multi-female mating system and a defined mating season (Bayart & Simmen, 2005), but of

they lack unique morphological or behavioral adaptations for hunting insects compared to those the aye-aye. Phylogenetically, since black lemurs are cousins of the aye-aye but do not occupy an insectivory niche, they are a good comparative species to highlight aye-aye specializations for insect-feeding (Perelman et al., 2011)

Figure 5. Phylogeny of strepsirrhines reprinted from “Divergence dates for Malagasy lemurs estimated

from Multiple gene loci: geological and evolutionary context” by Yoder and Yang, 2004. Note the divergence of Daubentonia at ~65 MYA

1.5 Chitin and Chitinase

Insects, fungi, and shrimp are some of the organisms that contain chitin for their structural make- up. Chitin is a long repeating chain of sugar molecules and is one of the most abundant sugars in nature, second only to cellulose (Hamid et al., 2013; Rathore & Gupta,

2015). In order to catabolize chitin, the enzyme chitinase must be present. Breaking down chitin begins with cleavage into chitin-oligosaccharides, which have interestingly been shown to be a part of anti- inflammatory processes (Azuma, Osaki, Minami, & Okamoto,

2015; Yoon, Moon, Park, Im, & Kim, 2007). Further breakdown of chitin- oligosaccharides provides N-acetylglucosamine which is important for cell signaling proteins (Konopka, 2012). The gene for chitinase has been a component of the placental mammal genome since its origin at the Cretaceous-Paleogene boundary (Emerling,

Delsuc, & Nachman, 2018). Insectivory during the Late Cretaceous was prominent in mammals due to competition with dinosaurs for other food sources (Emerling et al.,

2018). Even though chitinases may be present in an organism, they may not always able to break down chitin due to low expression levels of the gene (Uehara et al., 2018). Only two types of active chitinases have been found in mammals, chitriosidase and acidic mammalian chitinase (Hamid et al., 2013; Strobel,

Roswag, Becker, Trenczek, & Figure 6. 3-D rope model of acidic mammalian chitinase from Swiss-Model (Bienert et al., 2017).

Encarnaçao, 2013). The specific chitinase of study for this project is acidic mammalian chitinase

(Figure 6).

Five paralogs of the acidic mammalian chitinase gene, also denoted as CHIA, have been discovered and are denoted as CHIA1 through CHIA5. Since each of these paralogs has been detected across multiple placental mammal orders, phylogenetic studies have concluded that early mammals once had catalytic function in all five (Emerling et al., 2018). Over time, acidic mammalian chitinase lost its catalytic function in some species, and this may be due to the occupation of different dietary niches; in other words, there was a relaxation of selective pressure on these genes as mammals began to focus more on foods other than those containing chitin

(insects). Mammalian species that today retain the most functional copies of CHIA have diets that include a large component of invertebrates (Emerling et al., 2018).

The study of chitinase and its relation to insectivory in primates has expanded to a variety of species. The insects that primates consume contain a high protein-to-fat ratio and have some chitin content in their exoskeletons (Finke, 2007; Raubenheimer & Rothman, 2013) with adult insects showing a higher amount of chitinase compared to that of larvae (Finke,

2007). Some insectivorous primates, including Perdicticus potto (potto), Galago senegalensis

(bush babies), Callithrix jacchus (common marmoset), and Macaca fascicularis (crab-eating macaque) have been shown to digest chitin (Cornelius, Dandrifosse, & Jeuniaux, 1976; R. F.

Kay & Sheine, 1979; Tabata et al., 2019; Uehara et al., 2018). Tarsiers are also strongly believed to have functional CHIA genes, considering that the sequences of all five of their

CHIA loci exhibit functional catalytic and chitin-binding domains, intact exon-intron boundaries, and absence of inactivating mutations (Emerling et al. 2018).

Recent studies uncover a relationship between number of functional CHIA genes in

primates and their diets: insectivorous primates were shown to have more putatively functional copies than primates that are primarily folivorous or frugivorous (Janiak, Chaney, & Tosi, 2017).

Viewed in phylogenetic context, Emerling et al. (2018) demonstrated that several of the five CHIA paralogs carried by the placental mammalian ancestor have, over time, lost function in various descendant species, likely due to relaxation of selective pressures associated with changing dietary niches. Notably, the aye-aye was included in this analysis, but was not shown to retain any functional CHIA genes. However, Emerling and colleagues’ analysis of the aye-aye was based on DNA sequences extracted from a genome that does not have full coverage; thus, their conclusions with respect to this species may be premature.

Indeed, after thorough review of the literature on aye-ayes, it is difficult to conclude that aye-ayes do not have active chitinase genes. Observational studies reveal that insects are a large component of their diet. Moreover, many of their unique morphological features appear to be adaptations precisely for insect harvesting. Considering the significant investments of the species in terms of their foraging time budget, and the evolutionary development of specialized features, it seems unlikely that they wouldn’t be able to extract considerable nutrition from their insect prey through the expression of functional chitinases. I therefore investigate the following questions in this thesis:

1. Are functional CHIA genes present in the aye-aye transcriptome?

2. If so, are they expressed significantly higher in the stomach of the aye-aye

compared to that of a non-insectivorous primate?

Hypothesis

The aye-aye is the largest nocturnal primate species in the world (Sterling & McCreless, 2006). The morphological features of the aye-aye – including its rodent-like incisors, specialized third digit, and large

midbrain (inferior colliculus) and mobile ears for echolocation – provide unique access to food resources unavailable to other species in Madagascar (Sterling & McCreless, 2006). Though the anatomy of this highly adapted species has been studied well, the same cannot be said for its molecular make-up. Given their insect-rich diet, it is possible that their digestion system has also adapted to ensure the maximum amount of nutrients are taken from such food sources. Yet, to date, there has not been any study that examines chitinase expression in the aye-aye on the transcriptomic level, which leads to the purpose of this study: to examine whether this enzyme is expressed in the stomach tissue of the aye-aye. I predicted not only the presence of multiple functional forms of chitinase in the aye-aye (Daubentonia madagascariensis), but also that they would be expressed at a significantly higher level than in their non-insectivorous relative, the black lemur (Eulemur macaco). To test these predictions, RNA from the stomach tissue of aye- ayes and black lemurs was extracted and sequenced, and bioinformatic tools were then employed to identify the number of functional chitinase copies, as well as compare the number of transcripts (i.e. expression levels) between the two lemur species.

Chapter 2:

Methods

2.1 Samples

The stomach is the main site of digestion. If acidic mammalian chitinase is being produced, it would be present in this tissue. Stomach tissue of three Daubentonia madagascariensis and three Eulemur macaco were purchased for this study from the Duke Lemur Center (Table 4).

The specific diets fed to each individual are unknown; however, the Duke Lemur Center generally rotates a variety of food items for their lemurs.

Table 4. Stomach tissue samples purchased from Duke Lemur Center

Individual Name Sample Name Species Sex Storage Angelique DmA Daubentonia Female Ultracold madagascariensis

Mephistopheles DmM Daubentonia Male Ultracold madagascariensis

Nosferatu DmN Daubentonia Male Ultracold madagascariensis

Hesperus EmH Eulemur macaco Male Ultracold

Louie EmL Eulemur macaco Male RNAlater- preserved in ultracold Teucer EmT Eulemur macaco Male Ultracold

2.2 RNA sequencing

RNA sequencing is a next-generation sequencing technology that reveals the set of all RNA transcripts present in a population of cells. The results reveal not only which genes are being transcribed but also their relative amount of transcription.

Once samples were obtained, 1 gram of tissue from each individual was placed into 1.5mL tubes. The tubes were packaged on dry ice and sent to Quick Biology

(Pasadena, CA) for total RNA extraction, RNA-seq library preparation, and sequencing via Illumina Hiseq 4000. Quick Biology ran a quality check and reported that the samples had moderate degradation. Consequently, they employed an rRNA depletion method for the library preparation. Since total RNA consists mainly of rRNA, it was beneficial to remove this fraction in order to isolate mRNA which would contain the coding regions for the CHIA genes. This is done by adding special oligonucleotides to the rRNA, creating a hybrid version of the rRNA. Then an antibody designed to attached to the hybrid rRNA facilitates removal via magnetic beads (O’Neil, Glowatz, & Schlumpberger,

2013). Once the rRNA is removed, the mRNA is converted to complementary DNA

(denoted as cDNA). Special adaptor sequences for each sample are then ligated to their cDNA fragments (Table 5). Following the ligation of adapter sequences, the cDNA is loaded into a flow cell for amplification and paired end sequencing. Quick Biology stored the resultant sequence data in a Google Drive folder and emailed the link. The data were downloaded for further analysis.

Table 5. Quick Biology Sequencing Identifiers

Sample Name Adapter Sequence Sequence ID

DmA GATCAGGT SA43884

DmM CTTGTACG SA43885

DmN GCAAGGGT SA47182

EmT AGTCAACA SA47190

EmH AGTTCCGT SA43886

EmL ATGTCAGA SA43887

2.3 Sequence alignments and trimming

The cDNA reads contained sample identifier adapter sequences which needed to be removed prior to transcriptome assembly. A program called Trimmomatic was used to remove adapter sequences and trim any low quality reads due to sequencing error (Bolger, Lohse, & Usadel,

2014). After sequence reads were cleaned up and trimmed, they were aligned. For this project, two transcriptomes (one for each species) were assembled using a program called Trinity with its default settings (Haas et al., 2013). Since the aye- aye and black lemur are not modelorganisms, there are no well annotated genomes available Figure 7. Example of de novo assembly process that was used in Dr. Sagneet for use which means de novo assemblies needed Lamichhaney's genomics course. to be made. De novo assemblies are created by matching overlapping regions together to create

one whole assembly. The length of the regions in the reads to use can be set, a parameter known as a ‘kmer’ – a designation meaning all subsequences of nucleotide length ‘k’. For example, consider the word “HAPPINESS” with the kmer set to four. If copies of this word were fragmented, an algorithm could be created for its reassembly using overlapping fragments of four letters, ultimately leading to the word HAPPINESS again (Figure 7). In a de novo assembly, the word HAPPINESS would not be known beforehand; instead, the word would be synthesized based on the overlapping regions. This same process is followed to reassemble a transcriptome from a set of fragmented cDNA transcripts. In the present study, two de novo assemblies were made, one for the aye-aye (sample DmN) and one for the black lemur (sample EmT).

2.4 Bioinformatic Tools for Analysis

After the assemblies were made, they were processed in Kallisto, a program that quantifies transcript abundance (Bray, Pimentel, Melsted, & Pachter, 2016). Each assembly was used to create an index and a subset of reads from an individual for quantification. Since I was working with two different species, I needed an assembly for each. Within each species, Kallisto was runfor each individual for quantification of the whole gene set transcribed in the stomach. Thus, the program was run a total of 6 times, once for each individual. The scripts used for each are denoted in Table 6.

Table 6. Kallisto scripts for each sample.

Name Script Aye-Aye Index kallisto index -i AyeAyeSeq.Trinity.v1.index AyeAyeSeq.Trinity.v1.fasta

DmA kallisto quant -i AyeAyeSeq.Trinity.v1.index -o SA443884 -b 100 -t 25 SE5609_SA43884_S188_L008_R1_001.fastq.gz SE5609_SA43884_S188_L008_R2_001.fastq.gz

DmM kallisto quant -i AyeAyeSeq.Trinity.v1.index -o SA43885 -b 100 -t 25 SE5609_SA43885_S189_L008_R1_001.fastq.gz SE5609_SA43885_S189_L008_R2_001.fastq.gz DmN kallisto quant -i AyeAyeSeq.Trinity.v1.index -o SA47182 -b 100 -t 25 SE5722_SA47182_S20_L003_R1_001.fastq.gz SE5722_SA47182_S20_L003_R2_001.fastq.gz Black Lemur Index kallisto index -i BlackLemurSeq.Trinity.v1.index BlackLemurSeq.Trinity.v1.fasta EmT kallisto quant -i BlackLemurSeq.Trinity.v1.index -o SA47190 -b 100 -t 25 SE5721_SA47190_S8_L002_R1_001.fastq.gz SE5721_SA47190_S8_L002_R2_001.fastq.gz

EmL kallisto quant -i BlackLemurSeq.Trinity.v1.index -o SA43887 -b 100 -t 25 SE5609_SA43887_S191_L008_R1_001.fastq.gz SE5609_SA43887_S191_L008_R2_001.fastq.gz EmH kallisto quant -i BlackLemurSeq.Trinity.v1.index -o SA43886 -b 100 -t 25 SE5609_SA43886_S190_L008_R1_001.fastq.gz SE5609_SA43886_S190_L008_R2_001.fastq.gz

After determining the relative expressions of the transcripts, the genes they represented were determined using the Basic Local Alignment Search Tool (BLAST)

(Altschul, Gish, Miller, Myers, & Lipman, 1990) on the NCBI website. BLAST has five different programs that can be used to annotate sequences. For this project, BLASTX was used to annotate coding regions for protein sequences. BLASTX will take a region of the transcriptome and translate it into six possible proteins (based on the six possible reading frames). Then, these proteins are matched against a list of known protein sequences

(denoted as an index) for identification. All functional forms of the five types of CHIA

genes have been identified in Tarsius syrichta and were used as an index. The gene accession IDs were taken from the literature (Table 7) and used to find the protein sequences on the NCBI website. A housekeeping gene (from a grey mouse lemur),

GAPDH, was used for normalization purposes (Table 7). BLASTX searches of CHIA and GAPDH were run for the aye-aye and black lemur assemblies to identify the location of the expressed genes. The location ID output of BLASTX corresponds to the ID numbers found in the Kallisto files.

Table 7. Gene and Protein IDs obtained from literature (Emerling et al., 2018) and extracted from NCBI

Gene Name Gene Accession ID Protein Accession Notes ID CHIA1 XM_008068937.2 XP_008067128.2 CHIA2 XM_008068938.1 XP_008067129.1 Removed from NCBI due to standard genome annotation processing CHIA3 XM_008068941.1 XP_008067132.1 CHIA4 XM_008068928.1 XP_008067119.1 CHIA5 XM_008068926.1 XP_008067117.1 GAPDH XM_012760470.2 XP_012615924.1

Chapter 3:

Results

3.1 Quality Report of Sequence Reads

Table 8 summarizes the quality reports for each sample. Samples DmN and EmH had the highest amount of paired sequences within their respective species. Read quality, based on the average per base sequence quality, was high across all samples. DmN and

EmT were chosen randomly and used for sequence assemblies for downstream processes.

Table 8. Sequencing Report Summary provided by Quick Biology

Sample Name Total Paired Sequences Average Read Quality % DmA 30,295,849 93.02 DmM 33,122,078 92.25 DmN 34,969,145 89.36 EmT 30,126,959 90.07 EmH 31,278,517 93.01 EmL 29,803,699 92.35

3.2 Annotation Reports

The Trinity assembly output defines regions of genes with a specific ID number. The ID number can be annotated with the BLASTX program based on a given subset of known protein sequences, in this case the five known CHIA genes found in the tarsiers.

BLASTX gives the following output values:

1. Identity percentage of the unknown gene region to the known gene

2. Length of the alignment of the unknown gene region to the known gene.

3. Number of amino acid mismatches

4. Gap openings of the sequence

5. Start of alignment of the known gene in the assembly’s location

6. End of the alignment of the known gene in the assembly’s location

7. Start of the alignment of the unknown gene region to the known gene’s location

8. End of the alignment of the unknown gene region to the known gene’s location

9. The chance that the hit could be a match to something else

(e-value) (e-values below e-50 are considered robust)

10. The chance of the sequence being a match by similarity in size

(bit score) (the higher the bit score, the better the match)

Though all five CHIA genes were identified within the aye-aye (Figures 8-12) and black lemur (Figures 13-17) assemblies, it does not mean that they were exact matches. Under further examination, some of the same Trinity identifications came up for multiple CHIA genes. In order to distinguish which IDs actually represent the genes, the BLASTX output values required further evaluation. Trinity IDs contain a cluster number

(DNXXX_cX), followed by a gene number (gX) then its isoform number (iX). Among the aye-aye samples, Trinity IDs DN4409_c0_g1_i1 and DN4409_c0_g1_i2 (isoforms 1 and 2) matched across all five CHIA genes. Notably, these IDs had the highest percent identity match with CHIA5 at about 92% and 93% respectively; they also had longer alignment lengths and fewer mismatches than with CHIA1-4. Among the black lemur samples, Trinity ID DN28446_c0_g1_i3 and DN88321_c0_g1_i1 matched across all five

CHIA genes, however the percent identity matches all ranged around 50% with a vast number of mismatches in the alignment.GAPDH was identified in the aye-aye (Figure

18) and black lemur (Figure 19) transcriptomes. Trinity ID DN266733_c0_g1_i1 in the aye-aye had the highest percent identity and longest alignment length. In the black lemur,

Trinity ID DN3045_c0_g1_i26 had the same percent identity, alignment length, and e- value as Trinity ID DN3045_c0_g1_i52, but only i26 was expressed in all black lemur samples. Due to the expression availability, Trinity ID DN3045_c0_g1_i26 was used for downstream analysis.

Figure 8. Top 10 CHIA1 matches to aye-aye assembly based on e-value

Trinity ID Gene Identity Percent Length Mismatch Gaps qstart qend sstart send evalue bit score TRINITY_DN4409_c0_g1_i1 CHIA1 52.621 477 198 3 198 1628 1 449 0 516 TRINITY_DN4409_c0_g1_i2 CHIA1 52.688 465 192 3 251 1645 13 449 6.34E-179 503 TRINITY_DN537589_c0_g1_i1 CHIA1 51.261 119 52 2 3 341 102 220 4.57E-37 120 TRINITY_DN362303_c0_g1_i1 CHIA1 56.757 74 27 1 4 210 197 270 7.05E-26 87.8 TRINITY_DN193579_c0_g1_i1 CHIA1 59.615 52 21 0 18 173 251 302 4.56E-20 71.2 TRINITY_DN97400_c0_g1_i1 CHIA1 24.345 267 167 11 332 1069 113 365 7.29E-13 58.9 TRINITY_DN440625_c0_g1_i1 CHIA1 65 20 7 0 385 444 242 261 3.97E-07 37.4 TRINITY_DN413159_c0_g1_i1 CHIA1 58.065 31 9 1 5 97 282 308 7.69E-07 36.6 TRINITY_DN2724_c7_g1_i1 CHIA1 57.143 21 9 0 63 1 362 382 8.33E-06 31.2 TRINITY_DN84973_c0_g1_i1 CHIA1 58.621 29 12 0 200 286 72 100 8.59E-06 33.1

Figure 9. Top 10 CHIA2 matches to aye-aye assembly based on e-value

Trinity ID Gene Identity Percent Length Mismatch Gaps qstart qend sstart send evalue bit score TRINITY_DN4409_c0_g1_i1 CHIA2 53.291 471 181 7 246 1628 10 451 0 516 TRINITY_DN4409_c0_g1_i2 CHIA2 53.04 477 185 7 245 1645 4 451 0 517 TRINITY_DN537589_c0_g1_i1 CHIA2 52.941 119 50 2 3 341 96 214 5.57E-38 122 TRINITY_DN362303_c0_g1_i1 CHIA2 59.459 74 25 1 4 210 191 264 3.68E-28 94 TRINITY_DN193579_c0_g1_i1 CHIA2 59.615 52 21 0 18 173 245 296 3.03E-20 72 TRINITY_DN97400_c0_g1_i1 CHIA2 26.515 264 163 11 332 1066 107 358 2.74E-14 63.5 TRINITY_DN413159_c0_g1_i1 CHIA2 80.952 21 4 0 5 67 276 296 1.50E-08 41.6 TRINITY_DN440625_c0_g1_i1 CHIA2 70 20 6 0 385 444 236 255 1.44E-07 38.5 TRINITY_DN84973_c0_g1_i1 CHIA2 58.621 29 12 0 200 286 66 94 7.68E-06 33.5 TRINITY_DN38896_c1_g1_i1 CHIA2 36.735 49 25 1 74 220 35 77 1.12E-05 30.8

Figure 10. Top 10 CHIA3 matches to aye-aye assembly based on e-value

Trinity ID Gene Identity Percent Length Mismatch Gaps qstart qend sstart send evalue bit score TRINITY_DN4409_c0_g1_i1 CHIA3 61.67 467 154 4 246 1631 18 464 0 616 TRINITY_DN4409_c0_g1_i2 CHIA3 61.67 467 154 4 263 1648 18 464 0 617 TRINITY_DN537589_c0_g1_i1 CHIA3 48.739 119 55 3 3 341 103 221 9.64E-35 114 TRINITY_DN362303_c0_g1_i1 CHIA3 52.703 74 30 1 4 210 198 271 1.00E-24 84.3 TRINITY_DN193579_c0_g1_i1 CHIA3 52.83 53 24 1 18 173 252 304 1.69E-15 58.5 TRINITY_DN97400_c0_g1_i1 CHIA3 23.759 282 186 11 332 1123 114 384 1.85E-10 51.2 TRINITY_DN440625_c0_g1_i1 CHIA3 75 20 5 0 385 444 243 262 1.45E-07 38.5 TRINITY_DN440625_c0_g1_i1 CHIA3 57.692 26 11 0 3 80 216 241 1.32E-06 35.8 TRINITY_DN49194_c1_g1_i1 CHIA3 41.379 58 26 2 38 211 227 276 1.16E-05 31.2 TRINITY_DN14965_c0_g4_i1 CHIA3 32.727 55 31 1 340 176 338 386 1.40E-05 34.3

Figure 11. Top 10 CHIA4 matches to aye-aye assembly based on e-value

Trinity ID Gene Identity Percent Length Mismatch Gaps qstart qend sstart send evalue bit score TRINITY_DN4409_c0_g1_i2 CHIA4 88.147 464 53 1 260 1645 19 482 0 816 TRINITY_DN4409_c0_g1_i1 CHIA4 86.929 482 61 1 189 1628 1 482 0 818 TRINITY_DN537589_c0_g1_i1 CHIA4 49.153 118 54 2 6 341 106 223 4.49E-36 117 TRINITY_DN362303_c0_g1_i1 CHIA4 55 80 31 1 4 228 200 279 6.43E-28 93.6 TRINITY_DN193579_c0_g1_i1 CHIA4 50.943 53 25 1 18 173 254 306 1.88E-16 61.2 TRINITY_DN440625_c0_g1_i1 CHIA4 100 26 0 0 3 80 218 243 5.16E-14 57 TRINITY_DN97400_c0_g1_i1 CHIA4 24.074 270 176 10 314 1066 110 369 1.01E-12 58.5 TRINITY_DN413159_c0_g1_i1 CHIA4 76.667 30 3 1 2 91 285 310 8.49E-11 48.1 TRINITY_DN440625_c0_g1_i1 CHIA4 90 20 2 0 385 444 245 264 2.54E-09 43.5 TRINITY_DN84973_c0_g1_i1 CHIA4 76.923 26 6 0 215 292 80 105 6.90E-09 42.4

Figure 12. Top 10 CHIA5 matches to aye-aye assembly based on e-value

Trinity ID Gene Identity Percent Length Mismatch Gaps qstart qend sstart send evalue bit score TRINITY_DN4409_c0_g1_i2 CHIA5 93.305 463 29 1 260 1648 19 479 0 857 TRINITY_DN4409_c0_g1_i1 CHIA5 92.516 481 34 1 189 1631 1 479 0 864 TRINITY_DN537589_c0_g1_i1 CHIA5 48.305 118 55 2 6 341 106 223 1.41E-34 113 TRINITY_DN362303_c0_g1_i1 CHIA5 58.108 74 26 1 4 210 200 273 1.01E-27 92.8 TRINITY_DN193579_c0_g1_i1 CHIA5 50.943 53 25 1 18 173 254 306 2.43E-16 60.8 TRINITY_DN440625_c0_g1_i1 CHIA5 96.154 26 1 0 3 80 218 243 1.00E-13 56.2 TRINITY_DN97400_c0_g1_i1 CHIA5 23.704 270 177 9 314 1066 110 369 8.58E-13 58.5 TRINITY_DN413159_c0_g1_i1 CHIA5 80 30 2 1 2 91 285 310 1.85E-11 50.1 TRINITY_DN440625_c0_g1_i1 CHIA5 90 20 2 0 385 444 245 264 3.01E-09 43.5 TRINITY_DN84973_c0_g1_i1 CHIA5 76.923 26 6 0 215 292 80 105 7.29E-09 42.4

Figure 13. Top 10 CHIA1 matches to black lemur assembly based on e-value

Figure 14. Top 10 CHIA2 matches to black lemur assembly based on e-value

Figure 15. Top 10 CHIA3 matches to black lemur assembly based on e-value

Figure 16. Top 10 CHIA4 matches to black lemur assembly based on e-value

Figure 17. Top 10 CHIA5 matches to black lemur assembly based on e-value

Figure 18. Top 10 GAPDH matches to aye-aye assembly based on e-value. Highlighted sample indicates GAPDH representative.

Trinity ID Gene Identity Percent Length Mismatch Gaps qstart qend sstart send evalue bit score TRINITY_DN266733_c0_g1_i1 GAPDH 96.418 335 12 0 61 1065 1 335 0 672 TRINITY_DN504074_c0_g1_i1 GAPDH 89.595 173 18 0 2 520 4 176 4.26E-120 330 TRINITY_DN97165_c0_g1_i1 GAPDH 91.603 131 11 0 394 2 1 131 5.43E-87 246 TRINITY_DN11407_c0_g2_i2 GAPDH 42.815 341 175 7 258 1256 4 332 3.56E-79 248 TRINITY_DN559801_c0_g1_i1 GAPDH 94.34 106 5 1 319 2 228 332 2.86E-72 206 TRINITY_DN232379_c0_g1_i1 GAPDH 85.057 87 13 0 1 261 249 335 7.36E-55 162 TRINITY_DN47436_c0_g1_i1 GAPDH 93.59 78 5 0 8 241 170 247 6.43E-52 152 TRINITY_DN238811_c0_g1_i1 GAPDH 74.074 81 20 1 2 241 130 210 3.42E-31 99 TRINITY_DN314865_c0_g1_i1 GAPDH 58.667 75 31 0 3 227 103 177 3.79E-28 90.5 TRINITY_DN95231_c0_g1_i6 GAPDH 71.014 69 17 1 359 153 161 226 1.59E-27 92.4

Figure 19. Top 10 GAPDH matches to black lemur assembly based on e-value. Highlighted sample indicates GAPDH representative

Trinity ID Gene Identity Percent Length Mismatch Gaps qstart qend sstart send evalue bit score TRINITY_DN3045_c0_g1_i52 GAPDH 97.938 194 4 0 108 689 1 194 0 393 TRINITY_DN3045_c0_g1_i26 GAPDH 97.938 194 4 0 108 689 1 194 0 394 TRINITY_DN3045_c0_g1_i25 GAPDH 93.865 163 10 0 287 775 32 194 0 322 TRINITY_DN3045_c0_g1_i32 GAPDH 98.013 151 3 0 410 862 44 194 0 311 TRINITY_DN3045_c0_g1_i32 GAPDH 97.931 145 3 0 850 1284 191 335 0 293 TRINITY_DN3045_c0_g1_i37 GAPDH 97.931 145 3 0 780 1214 191 335 0 293 TRINITY_DN3045_c0_g1_i26 GAPDH 97.931 145 3 0 677 1111 191 335 0 293 TRINITY_DN3045_c0_g1_i25 GAPDH 97.931 145 3 0 763 1197 191 335 0 293 TRINITY_DN3045_c0_g1_i52 GAPDH 91.724 145 12 0 677 1111 191 335 0 276 TRINITY_DN3045_c0_g1_i37 GAPDH 96.581 117 4 0 442 792 78 194 0 237

3.3 Abundance Reports

After identifying the regions that correspond to CHIA on the aye-aye and black lemur transcriptomes, the amount of expression was extracted from the Kallisto files. Kallisto provides a transcript per million (tpm) value that represents a normalized value of expression within a sample. Table 9 and Table 10 display the tpm values of each individual sample from the top 2 CHIA ID matches and the GAPDH ID matches identified in the previous section.

Table 9. Transcript per million values for Trinity IDs that matched to CHIA and GAPDH in the aye-aye assembly

Sample TRINITY_DN4409_c0_g1_i TRINITY_DN4409_c0_g1_i TRINITY_DN266733_c0_g1_i 1 TPM (CHIA) 2 TPM (CHIA) 1 TPM (GAPDH) DmA 30,132.4 236.161 96.9547 DmM 47,293.7 95.8082 216.864 DmN 50.833 1.82201 235.2

Table 10. Transcript per million values for Trinity IDs that matched to CHIA and GAPDH in the black lemur assembly

Sample TRINITY_DN88321_c0_g1_i TRINITY_DN28446_c0_g1_i TRINITY_DN3045_c0_g1_i2 1 TPM (CHIA) 3 TPM (CHIA) 6 TPM (GAPDH)

EmT .0477958 .23261 83.2803 EmH 2.08507 .188855 119.211 EmL 2.78819 2.54592 107.159

3.4 Statistical Analysis

A Levene Test was run to see if the variance was equal between the species. The test yielded a p-value of 0.174. Thus, variance between the species can be assumed to be equal, but after close examination of the values between the two species I decided to run a Mann-Whitney Test. Since the tpm values are normalized per individual, the

CHIA tpm values were added within each sample and then divided by the individual’s

GAPDH tpm value to get the relative expression of CHIA to GAPDH (Table 11). At a significance of 0.05, the relative CHIA to GAPDH expression in the aye-aye is significantly higher than the black lemur, p-value = 0.05. Based on the probability of concordance, if you were to randomly select an aye-aye and a black lemur CHIA to

GAPDH value, the aye-aye would have the higher value 67% of the time. R-Studio was used to conduct statistical analyses.

Table 11. CHIA to GAPDH values for each sample.

Aye-Aye Sample CHIA: GAPDH Black Lemur Sample CHIA: GAPDH

DmA 313.2242274 EmT 0.003367012

DmM 218.5217842 EmH 0.019074792

DmN 0.223873342 EmL 0.049777527

3.5 Evolutionary comparisons of CHIA in Primates

The aye-aye and black lemur sequence data were added to the primate chitinase dataset of

Janiak et al. (2017) for further evolutionary analysis. The sequences were aligned with the program MUSCLE (Edgar 2004), and the chitinase catalytic domain (Figure 20) and the chitin binding domain (Figure 21) were identified. The aye-aye sequence was consistent with that of the tarsier at the catalytic domain and the six critical residues of the binding domain (and, therefore, putatively functional); however, the black lemur sequence contained a number of differences.

The alignment was also subjected to phylogenetic analysis as a further investigation of which of the five previously identified chitinase genes is functional in the aye-aye. The alignment was run through jModelTest (Posada Figure 20. Chitinase catalytic site in several primates. Red box highlights the two study species. Note that the amino acid sequence of 2008) to determine the the aye-aye is the same as that of tarsier (Tarsius syrichta) CHIA5, supporting its likely functionality. evolutionary model that best fits the data. A phylogenetic tree was then constructed in PhyML (Guindon et al. 2010) with 1020 bootstrap replicates (Figure 22).

Consistent with the identity matches described earlier (Section 3.2), the aye-aye chitinase coding sequence clusters with “hCHIA,” which is synonymous with CHIA5.

Figure 21. Chitin-binding domain of three primate genera and a tree shrew compared against those of the aye-aye and black lemur. Stars highlight six positions where cysteines are critical for a functioning chitinase (Emerling et al. 2018). The aye-aye sequence retains cysteines at each of these sites, whereas the black lemur sequence has a different amino acid at five of them, and is likely non-functional.

Figure 22. Phylogenetic tree constructed from a dataset combining the aye-aye sequence inferred here with the sequences compiled by Janiak et al., 2017. The notation “mCHIA” and “hCHIA” are synonymous with CHIA4 and CHIA5, respectively. Clades/lineages representing different paralogs of CHIA are indicated by arrows. The aye- aye is highlighted in red and clusters in the CHIA5 clade.

Chapter 4:

Discussion and Conclusion

4.1 Discussion

4.1a Functional Chitinase in Aye-aye and Black Lemur

The BLASTX results indicated the same two Trinity ID’s (DN4409 i1 and

DN4409 i2, isoforms of the same gene) as top matches to multiple CHIA paralogs in the aye-aye transcriptome based on e-value. The key value that differed among the ID matches and predicted CHIA paralogs were the percent identities. DN4409 i1 and

DN4409 i2 had their highest percent identities, reaching 92% and 93% respectively, for

CHIA5. Comparisons with CHIA5 also yielded the highest alignment lengths. By contrast, other Trinity IDs had low percent identities, high e-values, and low alignment lengths with the other CHIA paralogs. Thus, it seems that only one CHIA paralog –

CHIA5 – is functional in the aye-aye genome.

Further confirmation comes from examining the tpm values of each Trinity ID that matched with any of the CHIA paralogs. Both isoforms of DN4409 had the highest tpm values across all the aye-aye samples. Samples DnA and DmM had their highest tpm values at 30,132.4 and 47,293.7 respectively. Sample DmN, however, had a relatively low tpm value (50.833), which may be due to its lower sequence quality compared to the other samples. It is also important to note that the diets fed to these animals are unknown.

(Their diet in the time prior to death may have affected chitinase expression level.) Yet, more support for the functionality of the one CHIA paralog being expressed comes from the similarities it shares with the tarsier at the chitinase catalytic and chitin-binding domains.

As for the black lemur samples, all the percent identities of the CHIA paralogs ranged around 50%, suggesting that they may not produce any functional chitinases. The Trinity ID matches with the lowest e-values (DN88321 and DN28446) had small tpm values, indicating very weak expression: samples EmH and EmL had tpm values of 2.08507 and 2.78819, respectively, and Emt had the lowest tpm value at 0.23261. These tpm values were orders of magnitude lower than those of the aye-ayes. Further evidence can be seen in the amino acid sequence alignments of the black lemur against those of the tarsier and several other primate species: the black lemur sequence does not appear to retain functional chitinase catalytic and chitin-binding domains.

The aye-aye CHIA to GAPDH expression was higher from the black lemur based on the

Mann Whitney U test. Although the Leven Test confirmed the use of a parametric test, a non- parametric test was more feasible based on the values of CHIA to GAPDH expression across the species. The probability of concordance value shows that it is more likely for aye- ayes to express normalized CHIA expression levels more that the black lemur. Considering this difference, along with differences at the catalytic and binding domains, it seems very likely that aye-ayes express functional chitinase and black lemurs do not. This would be consistent with their diets: aye-ayes are insectivores, black lemurs are frugivores. The absence (“loss”) of functional chitinase in the black lemur would support the study of Emerling et al.(2018), which found that chitinase genes are lost in mammals that occupy different (non- insectivory) food

niches. However, their conclusions with respect to the aye-aye are refuted by the present study.

It strongly appears that aye-ayes do have a functional CHIA gene – not a pseudogene – based on the transcriptome data outlined above.

4.1b Aye-Aye and Chitinase Origins

Emerling et al. (2018) and Janiak et al. (2017) had two differing views on the evolutionary history of chitinase. Emerling et al. (2018) proposed that the five paralogs of

CHIA existed in the most primitive placental mammals whereas Janiak et al. (2017) attributes different CHIA paralogs to more recent duplication events in primates with different diets. The fact that the black lemur has traces of CHIA (but loss of function) lends more support to the five- paralog hypothesis of Emerling et al. (2018). If five copies were present in the ancestral placental mammal, it raises the question of how the aye-aye only ended up with only one. The answer could lie in the primitive ancestors of the aye-aye. The fossil species Daubentonia robustus was a larger-bodied ancestral relative of the modern aye-aye. A large body would indicate a diet of folivory. It could be that the other four chitinase paralogs were lost through the time of this ancestral form. Also, since modern aye-ayes are able to forage on multiple types of food, including seeds and flowers, they may not be as reliant on insects as we think. Yet, given that one CHIA gene is still very likely being produced as an active enzyme within the stomach of the aye-aye, this implies that insects are still a key item in their diet.

4.1c Re-examining the Jarman-Bell Principle / Kay’s Threshold

Based on the aye-aye’s relatively large body size, an insectivorous diet seems maladaptive given the considerable time and energy investment required to meet its nutrient and caloric needs. However, aye-ayes are likely able to reduce time and energy costs hunting for insects due to their unique suite of adaptations (rodent-like incisors, specialized third digit, and large midbrain and mobile ears for echolocation). Thus, body size cannot determine diet without taking into account specializations that can

negate investment cost. Also, as mentioned, since aye-ayes eat a variety of foods, they may not be considered strict insectivores given that their adaptations also aid in collecting nectar and processing seeds.

4.1 d Chitinase and Insect Eating in Humans

Functional chitinase has been found in the gastric juices of humans (Paoletti, Norberto,

Damini, & Musumeci, 2007). The existence of chitinase in the human stomach can imply that insects were a part of our hominin ancestors’ diets. Indeed, some evidence exists that hominin lineages may have used bone tools for scavenging termites (Backwell & d’Errico, 2008).

Today, there are a wide variety of cultures that eat insects for additional protein, a practice known as entomophagy. There has also been a recent interest in creating insect farms as an alternative to animal farming. Insect farming does not produce pollutants like animal farming and could provide a more economically friendly replacement for animal farming. Insects provide many beneficial nutrients such as protein, vitamin B and vitamin A and, with the ability to digest chitin, carbohydrates. As the concern for the environment increases, and as the population increases, insect eating may become more prevalent across cultures in the future.

4.1 Conclusion and Future Considerations

This study adds to our understanding of nutritional ecology of primates. Obviously, possession of a functional chitinase would maximize the nutrient and caloric benefit for insect hunters. Moreover, aye-ayes are able to specialize in food sources that are not so easy to obtain

(i.e. mobile) because they are aided by their morphological adaptive suite. This study provides strong support that aye-ayes have a functional acidic mammalian chitinase gene, and that such functional chitinases are not expressed in their non-insectivorous relative, the black lemur.

Future studies building on this work should add more samples to increase statistical significance. They should also gather transcriptomic data from more primates that occupy

different dietary niches, as this would further test the Emerling et al. (2018) argument that functional CHIA is lost in mammals that occupy different food niches. Exploring transcriptomics in primates can provide a clearer picture of what enzymes are actually being produced. Future studies should also explore chitinase expression efficiency in the aye-aye by extracting its protein and using yeast vectors to mass produce the enzyme; it could then be added to a chitin filled plate and the amount digested in a given time could be recorded. It would be interesting to see, for example, whether the single aye-aye chitinase gene is more efficient than the five copies possessed by tarsiers!

References

Alexander, R. M. (1993). The energetics of coprophagy: a theoretical analysis. Journal of

Zoology, 230(4), 629–637.

Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990). Basic local

alignment search tool. Journal of Molecular Biology, 215(3), 403–410.

Ancrenaz, M., Lackman-Ancrenaz, I., & Mundy, N. (1994). Field observations of aye-ayes

(Daubentonia madagascariensis) in Madagascar. Folia Primatologica, 62(1–3), 22–36.

Andrews, J. R., & Birkinshaw, C. R. (1998). A comparison between the daytime and night time

diet, activity and feeding height of the black lemur, Eulemur macaco (primates:

Lemuridae), in lokobe forest, Madagascar. Folia Primatologica, 69(Suppl. 1), 175–182.

Andriamasimanana, M. (1994). Ecoethological study of free-ranging aye-ayes (Daubentonia

madagascariensis) in Madagascar. Folia Primatologica, 62(1–3), 37–45.

Ankel‐Simons, F. (1996). Deciduous dentition of the aye aye, Daubentonia madagascariensis.

American Journal of Primatology, 39(2), 87–97.

Azuma, K., Osaki, T., Minami, S., & Okamoto, Y. (2015). Anticancer and anti-inflammatory

properties of chitin and chitosan oligosaccharides. Journal of Functional Biomaterials,

6(1), 33–49.

Backwell, L., & d’Errico, F. (2008). Early hominid bone tools from Drimolen, South Africa.

Journal of Archaeological Science, 35(11), 2880–2894.

Bankoff, R. J., Jerjos, M., Hohman, B., Lauterbur, M. E., Kistler, L., & Perry, G. H. (2017).

Testing convergent evolution in auditory processing genes between echolocating

mammals and the aye-aye, a percussive-foraging primate. Genome Biology and

Evolution, 9(7), 1978– 1989.

Bayart, F., & Simmen, B. (2005). Demography, range use, and behavior in black lemurs

(Eulemur macaco macaco) at Ampasikely, northwest Madagascar. American Journal of

Primatology: Official Journal of the American Society of Primatologists, 67(3), 299–

312.

Bell, R. H. V. (1971). A grazing ecosystem in the Serengeti. Scientific American, 225(1), 86–93.

Bienert, S., Waterhouse, A., de Beer, T. A. P., Tauriello, G., Studer, G., Bordoli, L., & Schwede,

T. (2017). The SWISS-MODEL Repository—new features and functionality. Nucleic

Acids Research, 45(D1), D313–D319.

Bolger AM, Lohse M, & Usadel B. (2014). Trimmomatic: a flexible trimmer for Illumina

sequence data, Bioinformatics, 30(15):2114–2120,

https://doi.org/10.1093/bioinformatics/btu170

Bray, N. L., Pimentel, H., Melsted, P., & Pachter, L. (2016). Near-optimal probabilistic RNA-seq

quantification. Nature Biotechnology, 34(5), 525–527.

Bush, E. C., & Allman, J. M. (2004). The scaling of frontal cortex in primates and carnivores.

Proceedings of the National Academy of Sciences, 101(11), 3962–3966.

Cartmill, M. (1974). Daubentonia, Dactylopsila, woodpeckers and klinorhynchy. Prosimian

Biology, 655–670.

Charles-Dominique, P. (1972). Ecologie et vie sociale de Galago demidovii (Fischer 1808;

Prosimii). Zeitschrift Für Tierpsychologie, 9, 7–41.

Chiba, T. (2016). Characteristic of the nutrient composition of a walnut gathered in

Iwate. Bulletin of Morioka Junior College Iwate Prefectural University,

18:47–51.

Colquhoun, I. C. (1993). The socioecology of Eulemur macaco: a preliminary report. In Lemur

social systems and their ecological basis (pp. 11–23). Springer.

Cornelius, C., Dandrifosse, G., & Jeuniaux, C. (1976). Chitinolytic enzymes of the gastric

mucosa of Perodicticus potto (primate prosimian): purification and enzyme specificity.

International Journal of Biochemistry, 7, 445–448.

Davies, K. T. J., Cotton, J. A., Kirwan, J. D., Teeling, E. C., & Rossiter, S. J. (2012). Parallel

signatures of sequence evolution among hearing genes in echolocating mammals: an

emerging model of genetic convergence. Heredity, 108(5), 480–489.

Edgar RC. (2004). MUSCLE: multiple sequence alignment with high accuracy and high

throughput, Nucleic Acids Research, 32(5):1792–1797,

https://doi.org/10.1093/nar/gkh340

Emerling, C. A., Delsuc, F., & Nachman, M. W. (2018). Chitinase genes (CHIAs) provide

genomic footprints of a post-Cretaceous dietary radiation in placental mammals. Science

Advances, 4(5), eaar6478.

Erickson, C. J. (1991). Percussive foraging in the aye-aye, Daubentonia madagascariensis.

Animal Behaviour, 41(5), 793–801.

Erickson, C. J., Nowicki, S., Dollar, L., & Goehring, N. (1998). Percussive foraging: stimuli for

prey location by aye-ayes (Daubentonia madagascariensis). International Journal of

Primatology, 19(1), 111–122.

Evans, D. L., & Schmidt, J. O. (1990). Insect defenses: adaptive mechanisms and strategies of

prey and predators. Suny Press.

Finke, M. D. (2007). Estimate of chitin in raw whole insects. Zoo Biology: Published in

Affiliation with the American Zoo and Aquarium Association, 26(2), 105–115.

Gaulin, S. J. C. (1977). On the natural diet of primates, including humans. Gaulin, S. J. C.

(1978). A Jarman / Bell Model of Primate Feeding Niches. 7(1).

Gebo, D. L. (2004). A shrew‐sized origin for primates. American Journal of Physical

Anthropology, 125(S39), 40-62.

Goodman, M., Porter, C. A., Czelusniak, J., Page, S. L., Schneider, H., Shoshani, J., … Groves,

C. P. (1998). Toward a phylogenetic classification of primates based on DNA evidence

complemented by fossil evidence. Molecular Phylogenetics and Evolution, 9(3), 585–

598.

Gray, J. E. (1870). Catalogue of monkeys, lemurs, and fruit-eating bats in the collection of the

British Museum. order of the Trustees.

Guindon S, Dufayard J-F, Lefort V, Anisimova M, Hordijk W, & Gascuel O. (2010). New

Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the

Performance of PhyML 3.0, Systematic Biology, 59(3):307–321,

https://doi.org/10.1093/sysbio/syq010

Haas B, Papanicolaou A, Yassour M et al. (2013). De novo transcript sequence reconstruction

from RNA-seq using the Trinity platform for reference generation and analysis. Nature

Protocols 8:1494–1512. https://doi.org/10.1038/nprot.2013.084

Hamid, R., Khan, M. A., Ahmad, M., Ahmad, M. M., Abdin, M. Z., Musarrat, J., & Javed, S.

(2013). Chitinases: An update. Journal of Pharmacy and Bioallied

Sciences.https://doi.org/10.4103/0975-7406.106559

Herrera, J. P., & Dávalos, L. M. (2016). Phylogeny and divergence times of lemurs inferred with

recent and ancient fossils in the tree. Systematic Biology, 65(5), 772–791.

Hladik, C. M. (1978). Adaptive strategies of primates in relation to leaf eating.

Iwano, T., & Iwakawa, C. (1988). Feeding behaviour of the aye-aye (Daubentonia

madagascariensis) on nuts of ramy (Canarium madagascariensis). Folia Primatologica,

50(1–2), 136–142.

Janiak MC, Chaney ME, & Tosi AJ. (2018). Evolution of Acidic Mammalian Chitinase Genes

(CHIA) Is Related to Body Mass and Insectivory in Primates, Molecular Biology and

Evolution, 35(3):607–622, https://doi.org/10.1093/molbev/msx312

Janiak, M. C. (2018). No evidence of copy number variation in acidic mammalian chitinase

genes (CHIA) in New World and Old World monkeys. International Journal of

Primatology, 39(2), 269–284.

Jarman, P. (1974). The social organisation of antelope in relation to their ecology. Behaviour,

48(1–4), 215–267.

Kappeler, P. M. (1997). Determinants of primate social organization: comparative evidence and

new insights from Malagasy lemurs. Biological Reviews, 72(1), 111–151.

Kaufman, J. A., Ahrens, E. T., Laidlaw, D. H., Zhang, S., & Allman, J. M. (2005). Anatomical

analysis of an aye‐aye brain (Daubentonia madagascariensis, primates: Prosimii)

combining histology, structural magnetic resonance imaging, and diffusion‐tensor

imaging. The Anatomical Record Part A: Discoveries in Molecular, Cellular, and

Evolutionary Biology: An Official Publication of the American Association of

Anatomists, 287(1), 1026–1037.

Kay, R. (1984). On the use of anatomical features to infer foraging behavior in extinct primates.

Adaptations for Foraging in Nonhuman Primates, 21–53.

Kay, R. F. (1975). The functional adaptations of primate molar teeth. American Journal of

Physical Anthropology, 43(2), 195–215.

Kay, R. F., & Sheine, W. S. (1979). On the relationship between chitin particle size and

digestibility in the primate Galago senegalensis. American Journal of Physical

Anthropology, 50(3), 301–308.

King, B. J. (1986). Extractive foraging and the evolution of primate intelligence. Human

Evolution, 1(4), 361.

Klieber, M. (1961). The heat loss of animals. The Fire of Life. New York, John Wiley & Sons Inc,

129–145.

Konopka, J. B. (2012). N-acetylglucosamine functions in cell signaling. Scientifica, 2012.

Krebs, J. R., Erichsen, J. T., Webber, M. I., & Charnov, E. L. (1977). Optimal prey selection in

the great tit (Parus major). Animal Behaviour, 25, 30–38.

Lamberton, C. (1934). ... Contribution à la connaissance de la faune subfossile de Madagascar...

Imprimerie moderne de l’Emyrne, G. Pitot & cie.

Liu, Z., Li, S., Wang, W., Xu, D., Murphy, R. W., & Shi, P. (2011). Parallel evolution of

KCNQ4 in echolocating bats. PLoS One, 6(10).

Marshall, A. J., Boyko, C. M., Feilen, K. L., Boyko, R. H., & Leighton, M. (2009). Defining

fallback foods and assessing their importance in primate ecology and evolution.

American Journal of Physical Anthropology: The Official Publication of the American

Association of Physical Anthropologists, 140(4), 603–614.

Marshall, A. J., & Wrangham, R. W. (2007). Evolutionary consequences of fallback foods.

International Journal of Primatology, 28(6), 1219.

Miller, R. T., Raharison, J.-L., & Irwin, M. T. (2017). Competition for dead trees between

humans and aye-ayes (Daubentonia madagascariensis) in central eastern Madagascar.

Primates, 58(2),367–375.

Milliken, G. W., Ward, J. P., & Erickson, C. J. (1991). Independent digit control in foraging by

the aye-aye (Daubentonia madagascariensis). Folia Primatol, 56, 219–224.

Munro, H. N. (1969). Evolution of protein metabolism in mammals. Mammalian Protein

Metabolism, 3, 133–182.

Napier, J. R., & Napier, P. H. (1967). Handbook of living primates.

O’Neil, D., Glowatz, H., & Schlumpberger, M. (2013). Ribosomal RNA depletion for efficient

use of RNA‐seq capacity. Current Protocols in Molecular Biology, 103(1), 4–19.

Owen, R. (1863). Monograph on the aye-aye (Chiromys madagascariensis, Cuvier). Taylor &

Francis.

Owen, R. (1866). On the aye-aye (Chiromys, Cuvier; Chiromys madagascariensis, Desm.;

Sciurus madagascariensis, Gmel., Sonnerat; Lemur psilodactylus, Schreber, Shaw).

Society.

Paoletti, M. G., Norberto, L., Damini, R., & Musumeci, S. (2007). Human gastric juice contains

chitinase that can degrade chitin. Annals of Nutrition and Metabolism, 51(3), 244–251.

Parker, J., Tsagkogeorga, G., Cotton, J. A., Liu, Y., Provero, P., Stupka, E., & Rossiter, S. J.

(2013). Genome-wide signatures of convergent evolution in echolocating mammals.

Nature, 502(7470), 228–231.

Perelman, P., Johnson, W. E., Roos, C., Seuánez, H. N., Horvath, J. E., Moreira, M. A. M., …

Rumpler, Y. (2011). A molecular phylogeny of living primates. PLoS Genet, 7(3),

e1001342.

Perry, G. H., Reeves, D., Melsted, P., Ratan, A., Miller, W., Michelini, K., … Gilad, Y. (2012).

A genome sequence resource for the aye-aye (Daubentonia madagascariensis), a

nocturnal lemur from Madagascar. Genome Biology and Evolution, 4(2), 126–135.

Petter, Jean-Jacques. (1965). The lemurs of Madagascar.

Petter, JEAN-JACQUES. (1977). The aye-aye. Primate Conservation, 37–57.

Pollock, J. I., Constable, I. D., Mittermeier, R. A., Ratsirarson, J., & Simons, H. (1985). A note

on the diet and feeding behavior of the aye-aye Daubentonia madagascariensis.

International Journal of Primatology. https://doi.org/10.1007/BF02736389

Posada D. (2008). jModelTest: Phylogenetic Model Averaging, Molecular Biology and

Evolution, 25(7):1253–1256, https://doi.org/10.1093/molbev/msn083

Rathore, A. S., & Gupta, R. D. (2015). Chitinases from bacteria to human: properties,

applications, and future perspectives. Enzyme Research, 2015.

Raubenheimer, D., & Rothman, J. M. (2013). Nutritional ecology of entomophagy in humans

and other primates. Annual Review of Entomology, 58, 141–160.

Sailer, L. D., Gaulin, S. J. C., Boster, J. S., & Kurland, J. A. (1985). Measuring the relationship

between dietary quality and body size in primates. Primates, 26(1), 14–27.

Schoener, T. W. (1971). Theory of feeding strategies. Annual Review of Ecology and

Systematics, 2(1), 369–404.

Schwitzer, C., Mittermeier, R. A., Davies, N., Johnson, S., Ratsimbazafy, J., Razafindramanana,

J., … Rajaobelina, S. (2013). Lemurs of Madagascar: A strategy for their conservation

2013–2016. Bristol, UK: IUCN SSC Primate Specialist Group, Bristol Conservation and

Science Foundation, and Conservation International, 185.

Sefczek, T. M., Rakotomanana, J., Randriamaronirina, H., & Louis Jr, E. E. (2018).

Unsuccessful predation event of an aye-aye (Daubentonia madagascariensis) by a fosa

(Cryptoprocta ferox). The Newsletter of the Madagascar Section of the IUCN SSC

Primate Specialist Group, 21.

Sefczek, T. M., Randimbiharinirina, D. R., Raharivololona, B. M., Razafimahaleo, H.,

Randrianarison, O., & Louis Jr, E. E. (2020). Re‐assessing the applicability of the

Jarman/Bell model and Kay’s threshold to the insectivorous aye‐aye (Daubentonia

madagascariensis). American Journal of Physical Anthropology, 171(2), 336–341.

Shen, Y.-Y., Liang, L., Li, G.-S., Murphy, R. W., & Zhang, Y.-P. (2012). Parallel evolution of

auditory genes for echolocation in bats and toothed whales. PLoS Genetics, 8(6).

Simmen, B., Bayart, F., Marez, A., & Hladik, A. (2007). Diet, nutritional ecology, and birth

season of Eulemur macaco in an anthropogenic forest in Madagascar. International

Journal of Primatology, 28(6), 1253–1266.

Simons, E. L., & Meyers, D. M. (2001). Folklore and Beliefs about the Aye aye (Daubentonia

madagascariensis). PSG Deputy Chairman: William R. Konstant, 6, 11.

Soligo, C. (2005). Anatomy of the hand and arm in Daubentonia madagascariensis: a functional

and phylogenetic outlook. Folia Primatologica, 76(5), 262–300.

Sterling, E J. (2003). Daubentonia madagascariensis, aye-aye. The Natural History of

Madagascar. SM Goodman & JP Benstead (Eds.), 1348–1351.

Sterling, Eleanor J., & McCreless, E. E. (2006). Adaptations in the Aye-aye: A Review. Lemurs,

159–184. https://doi.org/10.1007/978-0-387-34586-4_8

Sterling, Eleanor J. (1993). Patterns of range use and social organization in aye-ayes

(Daubentonia madagascariensis) on Nosy Mangabe. In Lemur social systems and thei

r ecological basis (pp. 1–10). Springer.

Sterling, Eleanor J. (1994). Aye-ayes: specialists on structurally defended resources. Folia

Primatologica, 62(1–3), 142–154.

Sterling, Eleanor J, & Richard, A. F. (1995). Social organization in the aye-aye (Daubentonia

madagascariensis) and the perceived distinctiveness of nocturnal primates. In Creatures

of the Dark (pp. 439–451). Springer.

Strobel, S., Roswag, A., Becker, N. I., Trenczek, T. E., & Encarnaçao, J. A. (2013).

Insectivorous bats digest chitin in the stomach using acidic mammalian chitinase. PloS

One, 8(9).

Tabata, E., Kashimura, A., Uehara, M., Wakita, S., Sakaguchi, M., Sugahara, Y., … Bauer, P. O.

(2019). High expression of acidic chitinase and chitin digestibility in the stomach of

common marmoset (Callithrix jacchus), an insectivorous nonhuman primate. Scientific

Reports, 9(1), 1–11.

Tamura, M. (2020). Extractive foraging on hard‐shelled walnuts and variation of feeding

techniques in wild Japanese macaques (Macaca fuscata). American Journal of

Primatology, e23130.

Thompson, K. E. T., Bankoff, R. J., Louis, E. E., & Perry, G. H. (2016). Deadwood structural

properties may influence aye-aye (Daubentonia madagascariensis) extractive foraging

behavior. International Journal of Primatology, 37(2), 281–295.

Uehara, M., Tabata, E., Ishii, K., Sawa, A., Ohno, M., Sakaguchi, M., … Oyama, F. (2018).

Chitinase mRNA levels determined by qPCR in crab-eating monkey (Macaca

fascicularis) tissues: Species-specific expression of acidic mammalian chitinase and

chitotriosidase.Genes, 9(5), 244.

Yoder, A. D., & Yang, Z. (2004). Divergence dates for Malagasy lemurs estimated from multiple

gene loci: geological and evolutionary context. Molecular Ecology, 13(4), 757-773.

Yoon, H. J., Moon, M. E., Park, H. S., Im, S. Y., & Kim, Y. H. (2007). Chitosan oligosaccharide

(COS) inhibits LPS-induced inflammatory effects in RAW 264.7 macrophage cells.

Biochemical and Biophysical Research Communications, 358(3), 954–959.