Introduction

Bats are the second largest group of mammals, with over 1,400 species identified till date (Simmons and Cirranello 2022). Being the only true volant mammals, they are found throughout the planet except for the polar regions (Teeling et al. 2018), colonizing even some of the remotest islands (Garg and Chattopadhyay 2021; Simmons and Cirranello 2022). Bats possess numerous physiological adaptations like flight, echolocation, tempered immune response to pathogens, and long-life span among others, that have allowed them to successfully occupy multiple niches across the globe (Teeling et al. 2018). Bats are keystone species in many habitats, play an important role in ecosystem functioning (Kunz and Fenton 2005), and provide multiple ecosystem services such as pollination, seed dispersal, and pest control (Chattopadhyay 2018; Fleming et al. 2009; Kunz and Fenton 2005; Kunz et al. 2011). For example, fruit bats are important pollinators of many economically important plants like mango, durian, agave, banana, etc. (Chattopadhyay 2018; Fleming et al. 2009). They are efficient long-distant pollinators, and are responsible for pollinating nearly 500 plant species (Fleming et al. 2009). Insect bats, on the other hand are very efficient biological pest control agents, and are important for the agriculture industry. Just in terms of pest control, they provide a minimum service of $3.7 billion per year in North America alone (Boyles et al. 2011).

Bats have been the subject of passionate arguments and studies in the past. Traditional genetic studies have illuminated phylogenetic affinities of bats, discovered footprints of unique adaptations, identified cryptic species, population genetic processes, biogeographic patterns, and highlighted the dynamic nature of bat mating and social systems (Chattopadhyay et al. 2012; Chattopadhyay et al. 2016; Ditchfield 2000; Garg et al. 2012; Jones and van Parijs 1993; Kerth 2008; McCracken and Wilkinson 2000; Tsang et al. 2020; Teeling et al. 2005). However, these studies also raised more questions than the answers they provide. For example, traditional microsatellite markers were unable to uncover fine-scale subdivision patterns in Cynopterus sphinx in India and misattributed the subdivision pattern as gene flow (Chattopadhyay et al. 2016). Whereas, genome-wide SNPs were better suited to uncover fine-scale subdivision as well as identify cryptic diversity within the Cynopterus complex (Chattopadhyay et al. 2016). In addition, studies comparing the power of genome-wide data with microsatellite or DNA sequences from a few markers have identified cases of introgression and mito-nuclear discordance, which was not possible with traditional markers (Chattopadhyay et al. 2014). Similarly, phylogenetic relationships between various lineages of bats, and as well as the relationship between bats and other mammals has been highly debated. Only when nearly complete genomes were available, bat phylogeny and their relationships have been resolved (Jebb et al. 2020; Tsagkogeorga et al. 2013; Teeling et al. 2005). Comparison of orthologous coding genes in echolocating mammals identified signature of molecular convergence in nearly 200 loci coding for hearing and vision (Parker et al. 2013). This was an unexpected result both in terms of the number of genes exhibiting signatures of convergent evolution as well as concordant changes in genes involved in physiological traits other than echolocation (Parker et al. 2013). The availability of next generation sequencing (NGS) data in many such scenarios has proven critical in addressing these unanswered questions.

NGS or high-throughput sequencing involves parallel sequencing of multiple DNA fragments and has revolutionized our understanding of the genomic architecture of organisms (Ekblom and Galindo 2011; Goodwin et al. 2016). Significant reduction in sequencing costs allowed the application of NGS technology to many non-model organisms (Ekblom and Galindo 2011). As with other fields, NGS has had a profound impact on our understanding of bats. From generating draft genomes to chromosomal level assemblies in less than two decades (Fig. 1 and Table 1), bat genomes have shed light on their unique physiological adaptations (Chattopadhyay et al. 2020; Eckalbar et al. 2016; Jebb et al. 2020; Parker et al. 2013; Pavlovich et al. 2018; Seim et al. 2013; Teeling et al. 2018; Zepeda Mendoza et al. 2018; Zhang et al. 2013). Sequencing of bat genomes especially gained traction from 2019 onwards (Fig. 1 and Table 1). Similarly, NGS technologies has proven critical in illuminating the molecular mechanisms of wing formation, pathogen tolerance in bats, disease dynamics, and emergence of zoonotic infectious diseases (Chattopadhyay et al. 2020; Eckalbar et al. 2016; Hayman 2019; Irving et al. 2021; Mandl et al. 2018; Pavlovich et al. 2018). Genomic data have allowed us to explore the co-evolution of bats and their pathogens. Given the COVID-19 pandemic, understanding the disease tolerance in bats and co-evolution of bats and pathogens has received foremost importance. Finally, genome-wide data have played an important role in understanding the evolution of bats, fine-scale pattern of subdivision, introgression, and recent population fluctuations, which was not possible with a handful of genetic markers (Calderón-Acevedo et al. 2022; Chattopadhyay et al.2016; Chattopadhyay et al. 2019a, b; Mao and Rossiter 2020). As part of our effort in highlighting the immense benefit of NGS technologies to bat research we present various advances which were made possible mainly due to the usage of NGS methods, thereby emphasizing why it is critical for understanding bat biology and evolution. We also look into the fields in which application of NGS methods have been appreciably slower, and provide a future roadmap for better leveraging these growing body of methods to address topical questions on bat research.

Fig. 1
figure 1

Chronology of the bat genomes sequenced from 2006 to 2022

Full size image
Table 1 Details of the bat genomes sequenced till now in chronological order
Full size table

Bat Genome Organization and Gene Family Fluctuations

Bats have the shortest mammalian genomes, with sizes ranging from 1.6 to 3.54 Gb (most genomes are around 2 GB) (http://www.genomesize.com), and less intra-order size variation compared to other mammals (Hughes and Hughes 1995; Smith et al. 2013). Birds also have small compact genomes, leading to the idea that achieving flight entails a loss of genomic redundancy and a streamlining of genomic organization in vertebrates (Hughes and Hughes 1995; Kapusta et al. 2017; Kapusta and Suh 2017; Smith and Gregory 2009). Even the extinct pterosaurs had compact streamlined genomes (Organ and Shedlock 2009). High metabolic requirement of powered flight may be the driving factor for a compact genome (Hughes and Hughes 1995; Smith and Gregory 2009). Gene loss and gain are critical components shaping genomic variability and phenotypic diversification (Ohno 2013; Zhang 2003) and within mammals, bats have the highest ratio of DNA loss to gain (Kapusta et al. 2017). Large deletion events have played a major role in streamlining the genomes of both flying vertebrates, bats and birds (Kapusta et al. 2017). Bat genomes are highly flexible in terms of protein-coding genes, and the pace of gene turnover appears to be similar to that of their Laurasiatherian relatives (Kondrashov 2012). The gene family coding for olfactory receptors are one of the largest gene families in mammalian genomes and also very dynamic, with both gene loss/gain observed across Laurasiatheria (Tsagkogeorga et al. 2017). Contraction of olfactory receptor genes in the last common ancestor of all bats and echolocating bats has been observed, although this may not be responsible for compact nature of the bat genome (Tsagkogeorga, et al. 2017). Similarly, gene family fluctuations in immune relate genes was also observed in bats with both loss and gain of genes, which varied across families (Chattopadhyay et al. 2020; Tsagkogeorga et al. 2017).

Further, genome size is generally correlated with the number of transposon elements present (Jebb et al. 2020). Although, the composition and relative age of these transposable elements vary across bat families (Jebb et al. 2020; Pritham and Feschotte 2007). For example, genomes of Old World fruit bats are even smaller compared to insectivorous bats, and genome size reduction in these bats is associated with lineage-specific loss of LINE-1 transposons (Smith and Gregory 2009). Similarly, accumulation of rolling-circle and DNA transposons have been noted in vespertilionids, suggesting the need for detailed comparison across mammals and bats in particular (Jebb et al. 2020; Platt et al. 2016; Pritham and Feschotte 2007). Bats provide a unique understanding to the limits of mammalian genome structure in general and the genomic ramifications of flight adaptation in particular. With the exponential increase in the availability of high-quality bat genomes across the order, we should be able to identify the drivers for genome size evolution and family level variation in genome size.

Ageing

Bats are one of the longest-living mammals based on their size, with an average lifespan of 10 years (Teeling et al. 2018). The longest documented lifespan is over 41 years for the small 4-8 g bat Myotis brandtii (Seim et al. 2013). Bats are nocturnal and capable of true flight, both of which possibly helped them escape most predators. As a result, they have developed the extremely unusual vertebrate combination of long lives and small bodies (Garg and Chattopadhyay 2021; Teeling et al. 2018). Ageing is a complex process and with the anticipated increase in the average human lifespan, model systems to understand the impacts of ageing are necessary (Austad 2010). Because laboratory model animals are easier to control and house, majority of the ageing investigations have been conducted on them (Yuan et al. 2011). An alternative approach is to investigate species that are more 'age-resistant' than humans and have naturally evolved extended health spans (Austad 2010; Teeling et al. 2018). Bats are an excellent model to understand ageing process unlike the short life-spanned current laboratory models like fruit flies and mice (Teeling et al. 2018). However, studying bats is particularly difficult in captivity (Ball et al. 2018), thereby making comparative genomics an invaluable tool for indirect assessments (Chattopadhyay et al. 2020; Kacprzyk et al. 2021; Power et al. 2021; Teeling et al. 2018).

Bats manage cellular damage and oxidative stress quite efficiently and growing body of evidence from comparative genomic studies suggest that a diverse repertoire of strategies are associated with long-life spans. Positive selection of genes associated with a reduction of oxidative stress (Zhang et al. 2013), changes in sequences of growth hormones and insulin-like growth factor 1 (Seim et al. 2013), and an expansion of telomere protective gene families (Chattopadhyay et al. 2020), all contribute to the unique genomic footprints that various bats have evolved to reduce DNA damage and possibly live long. Multiple studies combining traditional methods (mark-capture) and NGS data collected from the long-lived bat Myotis myotis have provided great insights into possible mechanisms of regulating tissue damage, low cancer rate, and long-life spans. While one study observed age-related transcriptional alterations and microRNA (miRNA)-directed regulation (Foley et al. 2018), another identified a few extremely abundant transcripts that are enriched in important cellular maintenance bioprocesses including autophagy and DNA repair when comparable to humans (Huang et al. 2019). Yet others observed longevity associated traits like enhanced epigenetic stability in genes associated with innate immunity and cancer suppression (Wilkinson et al. 2021), and the presences of a complex DNA repair system to maintain the stability of their genomes (Huang et al. 2019). Comparative analysis across a range of bat species with different lifespans is the need of the hour to understand if similar mechanisms are employed by multiple species of bats to reduce the damage caused by ageing.

Immunity in Bats and Viruses

Numerous zoonotic outbreaks including the COVID-19 pandemic have been linked to viruses present in bats (Irving et al. 2021; Letko et al. 2020; Teeling et al. 2018). The ability of bats to employ diverse tactics in response to infections possibly plays an important role in their tolerance to a wide range of viruses (Hayman 2019; Irving et al. 2021; Letko et al. 2020; Teeling et al. 2018). They largely remain asymptomatic, avoiding severe immunological dysfunction in response to most viral infections, making them an important study system to understand disease biology and ecology of emerging infectious diseases and host pathogen coevolution (Letko et al. 2020). Bats possess a rather limited repertoire of genes associated with immunity and such genomic regions are basal to other mammals resembling ancestral state (Chattopadhyay et al. 2020; Ng et al. 2016; Zhou et al. 2016). However, they have evolved a great diversity of strategies to combat viral infection using a combination of antiviral response and dampened inflammation. For example, many species show an expansion of APOBEC3 gene family which contributes to antiviral response by preventing replication of many viruses (Mandl et al. 2018). Other antiviral genes include RNase-L and antiviral myxovirus resistance (Mx) proteins which can prevent viral replication and thus control the number of virus particles (Irving et al. 2021). In addition to the antiviral responses, bats use a host of strategies to reduce inflammatory response (Gorbunova et al. 2020; Irving et al. 2021; Mandl et al. 2018). While all species of bats studied so far reveal the loss of PYHIN gene family thereby controlling inflammation, such contraction along with continuous expression of interferons and interferon stimulating genes in some species of bats have further allowed them to modulate inflammatory response (Irving et al. 2021). An early interferon response is important to restrict viral replication and titer (Banerjee et al. 2020). Interestingly, bats have also evolved unique mechanisms to detect viruses, and some bats can activate interferon simulated genes irrespective of the presence of interferons (Banerjee et al. 2020; Gorbunova et al. 2020). In addition, comparative genomics studies have also identified separate mechanisms to modulate inflammatory response through the loss of multiple alpha and beta defensins, which are responsible for antimicrobial activities in epithelial cells and act as a bridge between innate and adaptive immunity to elicit proinflammatory cytokine production (Moreno-Santillán et al. 2021).

Genomes from paleotropical fruit bats present an interesting example to study the evolution of immunity in bats. All of these bat species whose genomes have been sequenced, have also been implicated in zoonotic spillovers, and as we compare their genomes, we realize that they also employ different pathways to combat viruses and infections (Chattopadhyay et al. 2020). For example, the contraction of genes coding for interferons is observed in Pteropus species, whereas expansion of these genes is observed in Rousettus fruit bats (Pavlovich et al. 2018; Zhang et al. 2013). While the genome of Cynopterus brachyotis reveals the contraction of genes coding for natural killer cell receptors and the MHC class I molecules (Chattopadhyay et al. 2020), expansion of these genes is observed in Rousettus aegyptiacus (Pavlovich et al. 2018). Both MHC class I and natural killer cells interact with each other to get rid of cells infected with viruses. However, our knowledge regarding the cause and consequences of the diverse immune strategies utilized by bats is still in its infancy and as we face a deluge of whole genome sequencing data, future studies will help clear our understanding of immune system evolution in bats and the exact role they play in unison towards immune tolerance.

Dietary Diversification, Physiological and Sensory Adaptations

Diet is one key requirement for survival of any species and the quest to acquire and digest nutrients can lead to the evolution of physiological and morphological traits by posing strong selection pressures on the organism (Hecker et al. 2019; Román‐Palacios et al. 2019). Bats exhibit unparalleled diversity in food habits ranging from feeding on blood to consuming fruits, nectar, insects, and small vertebrates (Potter et al. 2021a and b). Their diverse food habits are associated with similar diversity in physiological adaptations as well as genomics changes (Fig. 2 and Table 2) (Potter et al. 2021a, b; Teeling et al. 2005; Zepeda Mendoza et al. 2018). For example, vampire bats bear footprints of genomic adaptations associated with sanguivory(blood-feeding) (Fig. 2 and Table 2). Genes involved in glucose and lipid metabolism, iron assimilation, and immunity are altered in vampire bat Desmondus rotundus as compared to other bats, and so are their associated gut microbiome profile (Blumer et al. 2022; Gorbunova et al. 2020). As vampire bats lack carbohydrate rich diet, a loss of genes associated with insulin secretion (FFAR1 and SLC30A8), and glycogen storage has been observed (PPP1R3E) (Blumer et al. 2022). Further, we observe excess secretion of iron in vampire bats. This is most probably achieved by the loss of REP15 gene which is responsible for the uptake of iron from the intestines. By reducing the uptake of iron from the intestines, vampire bats are able to regulate their iron levels (Blumer et al. 2022) (Fig. 2 and Table 2). Similar footprints of diet are also observed in other bats. For example, fruit bat’s ability to acquire fluid and potassium rich diets can be attributed to the loss of renal transporter genes like URAT1, GLUT9, and OAT1 and renal ammonium secreting transporter protein RHBG (Sharma et al. 2018). In nectar-feeding bats, positive selection on multiple genes involved in glycolytic and fructolytic enzymes was observed (Fig. 2 and Table 2) (Potter et al. 2021a).

Fig. 2
figure 2

Summary of dietary adaptations in bats based on genomic data. Bat silhouettes were taken from Phylopic. Image credits: Melissa Ingala, Roberto Diaz Sibaja, and Yan Wong

Full size image
Table 2 List of genes which play and important role in dietary specialization in bats
Full size table

Comparative genomics approaches have also established the convergent molecular adaptation of genes involved in metabolism, olfaction, vision, and taste in Old World and Neotropical fruit bats (Gutierrez et al. 2018; Wang et al. 2020). Strong trend of gene loss in the olfaction receptor in bats, particularly echolocating lineages is observed, suggesting a potential trade-off between olfaction and other senses in auditory specialists (Tsagkogeorga et al. 2017). Similar tradeoff between genes responsible for vision and echolocation was observed in both high duty echolocating bats and cave dwelling bats (Gutierrez et al. 2018; Kries et al. 2018; Simões et al. 2019). A comprehensive approach including DNA sequence, expression level data, and detection of opsin proteins in bat retinas, identified multiple parallel pathways for the loss of functional opsin genes in bats (Sadier et al. 2018). In addition to pseudogenes, loss of functional short-wavelength opsin genes at the transcriptional and post-transcriptional level were observed (Sadier et al. 2018). Further, the presence of functional short-wavelength opsin gene was also found to be strongly correlated with fruit consumption (Sadier et al. 2018).

Interestingly, the gene responsible for umami taste i.e., Tas1r1 involved in the detection of appetitive components of any diet was lost in bats, irrespective of whether their diet consisted of fruits, nectar or insects (Zhao et al. 2012). However, one should be careful while associating any gene with diet specialization through comparative genomic analysis as a combination of multidisciplinary approaches is required to validate these findings. For instance, the sweet taste receptor gene TAS1R2 is conserved in both frugivorous and insectivorous bats, but experimental studies suggest that there is no preference for natural sugars in insectivorous bats. Only, frugivorous bats exhibit a preference for natural sugars, suggesting the importance of validating the results obtained from comparative genomic analysis (Jiao et al. 2021). Such observations are critical in understanding how diet might play a role in sweet taste perception and how evidence of an intact coding region does not correlate with intact gene function/animal behavior. Similar results were also observed for opsin genes as well, where intact gene sequence did not result in a functional protein product due to either transcriptional or post-transcriptional changes (Sadier et al. 2018).

In addition to comparative genomics approaches, genetic/genomic studies have also played a critical role in identifying components of a bat’s diet. Bats provide many ecosystem services by helping in pollination and reducing the burden of agricultural pests and therefore bat guano is widely subjected to molecular analyses of its diet components (Clare et al. 2011; 2014). Metabarcoding is a useful method to determine dietary composition and allows for large-scale screening. For example, barcoding of fecal matter using partial cytochrome oxidase I gene sequence enabled the identification of 290 prey arthropods (Galan et al. 2018). Such species diversity data from guano can be used to model species distribution and identify the relationship between ecological traits and geographic range sizes (Alberdi et al. 2020). A detailed inventory of a Neotropical bat community revealed the associations between invertebrates, plant groups and bats and identified fine-scale niche separation even in closely related species (Ingala et al. 2021). A similar approach of network analysis of host and diets can be extrapolated to a range of bat species across widespread geographical locations, forming the foundations for understanding diet specifications for cryptic species and can help develop policies for their conservation.

Emerging Infectious Diseases and Bats

Emerging infectious diseases of zoonotic origin have become a major threat to human well-being in the past few decades, causing enormous economic loss (Irving et al. 2021; Letko et al. 2020; Mandl et al. 2018; Teeling et al. 2018). Bats are arguably the top mammalian reservoir of zoonotic diseases (Letko et al. 2020; Mandl et al. 2018; Teeling et al. 2018). They are one of the most significant reservoirs of RNA viruses and are associated with multiple zoonotic outbreaks in the recent past, with high fatality rate in humans (Letko et al. 2020; Mandl et al. 2018; Teeling et al. 2018). However, most bat borne zoonotic infections are transmitted through intermediate hosts like livestock (Mandl et al. 2018; Subudhi et al. 2019; Teeling et al. 2018). Urbanization and continuous land use change have increased the probability of interaction between bats and livestock, potentially increasing the transfer of pathogens across species (Fagre et al. 2022). Further, the high dispersal ability of bats also increases the probability of transmission of diseases (Garg and Chattopadhyay 2021). Finally, anthropogenic activities like hunting and consumption of bats, collection and handling of bat excreta as a fertilizer (Dovih et al. 2019; Wacharapluesadee et al. 2013), recreational activities like camping in caves, indirect contact via bat excreta contaminated regional beverages like date palm juice or consumption of fruits contaminated with saliva from bats have increased the plausibility of bat borne spillovers to occur in nature (Luby and Gurley 2012).

Surveillance and detection of infectious diseases are critically important in understanding infectious diseases and public health (United Nations Environment Programme and International Livestock Research Institute 2020). With the introduction of NGS in the early 2000s and the recent Covid-19 outbreak, there is a paradigm shift in favor of using NGS in the field of infectious diseases research and viral discovery (Chiara et al. 2020; Temmam et al. 2014). The powerful NGS high-throughput sequencing platforms with an unbiased detection approach offers a wealth of information in disease ecology, discovery of novel pathogens, host–pathogen co-evolution, and disease biology (Chiara et al. 2020; Temmam et al. 2014).

One of the key advantages of NGS over conventional PCR-based methods is that primer designing to target a specific sequence is not required (Lecuit and Eloit 2014). NGS approach can detect a pathogen from a mixture of different genetic materials with high sensitivity and identify virus shedding patterns in reservoir species using environmental sampling (Li et al. 2020; Mendenhall et al. 2019). With the advancement of NGS technologies, several methods have been introduced, particularly targeting sample preparations to optimize the generation of NGS data and identify pathogens of interest.

In addition to targeting specific virus groups through target enrichment, metagenomic approaches involve unbiased sequencing of the entire community of organisms present in a common habitat by targeting gene/genomic fragments (Hugenholtz and Tyson 2008). Metagenomics has played an important role in the discovery of novel microbial communities, reconstruction of pathogen genomes, and as well as analysis of genes involved in various metabolic pathways and adaptation to a given environment (Hugenholtz and Tyson 2008). Knowledge of microbiota and viral shedding pulses from bat reservoirs will hopefully help restructure our conservation efforts to minimize human bat conflict and associated zoonotic spillovers (Bernstein et al. 2022; Carroll et al. 2021; Letko et al. 2020). Metagenomics can provide data regarding the diversity and abundance of pathogens in wildlife, and further help investigate the molecular epidemiology and evolution of specific microbial species (Hugenholtz and Tyson 2008). One advantage of metagenomics is that it does not require isolation of pathogens, and therefore does not need high threat biosafety levels (Hugenholtz and Tyson 2008).

In contrast to the study of viruses, bacterial diversity studies using high-throughput sequencing tools is limited and long-term monitoring efforts comparing bacterial communities across seasons, locations and different dietary niches are needed to better understand the ecology and evolution of bat-bacteria cohabitation (Dimkić et al. 2021). The ecological dynamics of diet and its associated microbes can also provide a holistic understanding of diet acquired bacterial pathogens and their transmission routes across many species. Zoonotic pathogens like Bartonella, Borrelia, and Leptospira detected in bat guano hints at the enormous diversity of bacterial pathogens of high pathogenicity which remains to be explored. Bats can also serve as a reservoir for multi-antibiotic resistance bacteria, which can lead to potential recombination and give rise to novel strains of concern to public health, making it more urgent to study these associations (Dimkić et al. 2021).

A holistic approach involving multiple disciplines like ecology, virology, and cell biology, alongside biotechnological advancements can greatly accelerate the development of reliable genomics tools and improve our understanding of zoonotic spillovers (Plowright et al. 2017). Long-term studies spanning across years and seasons can greatly contribute to improve our understanding of disease ecology and mechanisms of zoonotic spillovers, as finely exemplified by a 25-year study on Hendra virus spillover dynamics that identified habitat loss and climate driven food shortage as critical factors contributing towards the increase in frequency of contact between bats and horses, which in turn led to higher frequency of spillover (Eby et al. 2023). Similar integrative and long-term research paradigms will be critical towards research efforts in pathogen discovery, surveillance, spillover dynamics, host–pathogen coevolution and One Health.

Population Genomics

Application of NGS for population genomics, biogeography and conservation of bats has been appreciably slower compared to comparative genomics and metagenomic studies. Techniques like reduced representation sequencing, genotype by sequencing, target enrichment, and whole genome re-sequencing have been used to address population genomic patterns (Chattopadhyay et al. 2016; Chattopadhyay et al. 2019b; Gignoux‐Wolfsohn et al. 2021; Mao and Rossiter 2020; Sovic et al. 2016). Genome-wide markers have been effective in uncovering cryptic patterns of population divergences, introgression, and to evenly assign individuals to the correct species groups in cohabitation zones where traditional markers have failed (Chattopadhyay et al. 2014; Yi and Latch 2022). Most genome-wide studies in bats have successfully uncovered mito-nuclear discordance and identified introgression patterns between divergent lineages which was not possible through traditional markers (Chattopadhyay et al. 2016; Mao and Rossiter 2020). Population genomic studies have also played an important role in identifying genes potentially under selection. For example, changes in allele frequency of genes associated with fat metabolism and hibernation were observed between bats that survived the white-nose syndrome caused by fungal pathogen, and those that did not survive the infection (Gignoux‐Wolfsohn et al. 2021).

Bats have also provided critical insights into the responses of natural populations to climate change and associated habitat fluctuations. A study comparing fluctuations in effective population size of bats during the Pleistocene with paleohabitat modelling revealed that bats positively responded to habitat fluctuations during events of climate change (Chattopadhyay et al. 2019a). It also observed that overall, bats harbor low effective population size comparable to carnivores and endangered birds, and they entered the Holocene with historically low effective population size (Chattopadhyay et al. 2019a). Effective population size is an indicator of the evolutionary potential of a species and is often used as a proxy for genetic diversity. Thus, an overall low population size coupled with a historical dip in diversity at the advent of Holocene attests to the vulnerability of bats to climate change. Interestingly, while investigating events of fluctuations in genetic diversity in response to more recent habitat changes, a comparison of a historic and current population of an Old World fruit bat, Cynopterus brachyotis, uncovered dramatic decline in genetic diversity and population size post urbanization in Singapore (Chattopadhyay et al. 2019b). These results were unexpected, given that C. brachyotis a commonly occurring and wide-ranging fruit bat and collectively these studies highlight the importance of genome-wide population genomic studies in bats in identifying species response to climate change. However, in comparison to other mammals and birds, population genomic investigations are scant. A substantial effort incorporating genome-wide data to uncover population genomic patterns in necessary for bats and future studies must invest in this direction.

Conclusion and Roadmap for Future Studies

With ambitious projects like the Bat1K, Vertebrate Genome Project and Earth BioGenome, high-quality genomes for known species will be available in the future (Genome 10K Community of Scientists 2009; Lewin et al. 2022; Teeling et al. 2018). Genomes generated by both global consortia as well as local research groups will act as a significant resource for bat research. Hence accumulation of more genomes, transcriptomes, epigenetic data should be leveraged to obtain detailed understanding of genome evolution (e.g., immune system evolution), physiological adaptations, and host pathogen coevolution. For example, the knowledge generated using NGS approaches can help identify target molecules for functional characterization using cell and molecular biology approaches and provide a clear molecular mechanism of physiological adaptations that are observed in bats.

We feel that rapid advances in large-scale and NGS data generation and associated analytical methods will eventually help studies in diverse disciplines like behavioral ecology, population genomic, phylogenomic, and conservation-related research accommodate hundreds to thousands of individuals. Recent improvements in generating genome-wide SNPs, and population level epigenomes from low concentration of DNA have allowed researchers to use both non-lethal and non-invasive sampling methods, which is an added advantage. Application of methods like reduced representation libraries, sequence capture, and genome resequencing in conjunction with the reduction in sequencing cost makes NGS methods the most practical approaches for many research projects. Recent advancements to successfully generate genome-wide data from museum and archaeological samples, have opened a window to our past and can provide direct evidence of impact of climate change on bats. Research looking into temporal patterns of bat microbiome and diet patterns can also immensely benefit from such advancements. Hence a substantial effort in incorporating genome-wide data to uncover evolutionary trends in bats is the need of the hour and future studies must invest in this direction.