Genetic Analysis of Philippine Eagles Pithecophaga jefferyi Ogilvie-Grant 1896 Using Mitochondrial Genomes

Pithecophaga jefferyi Ogilvie-Grant 1896 or the Philippine Eagle is endemic to the Philippines, and is currently listed as an IUCN “critically endangered” species. There is currently an urgent need for genetic information to enhance conservation breeding and preserve the genetic diversity of this species. In this study, we explored the use of mitogenome sequencing as a cost-effective alternative for the genetic studies of Philippine Eagles. Analysis of partial mitogenomes revealed a mean nucleotide diversity of 0.10 to 0.16 from the 27 samples sequenced. This is much lower compared to most threatened bird species. Furthermore, we also observed that most samples belong to a single genetic cluster based on k-means clustering of the pairwise genetic distances, although we detected potentially two distinct subpopulations which was supported by an isolation by distance analysis. Nevertheless, some Philippine Eagle individuals showed distinct nucleotide profiles, with eagles from three key biodiversity area dyads exhibiting high FST, indicating potential genetic differentiation. This suggests limited gene flow between these KBAs, but also their potential use to reinforce the nucleotide diversity in Philippine Eagle captive breeding programs. Finally, phylogenetic analysis of Philippine Eagles and other members of the Order Accipitriformes corroborates previous findings on the non-monophyletic status of the subfamily Circaetinae or the snake-eagles. Altogether, we demonstrate the utility of mitogenomes in assessing the genetic diversity and evolutionary relationships of avian species. Given the huge per-sample cost of whole genome sequencing, the approach utilizing mitogenome sequencing provides a cost-effective alternative to facilitate genetic studies of animals. We therefore anticipate an increasing utility of mitogenomes in population studies for biodiversity and genetic conservation research in the Philippines. Genetic Analysis of Philippine Eagles Pithecophaga jefferyi Ogilvie-Grant 1896 Using Mitochondrial Genomes Michael G. Bacus 1, *, Paul Lorenzo A. Gaite 1, Joan T. Acaso 1,3, Joshua M. Cambronero 1, Gerry N. Ramos, Jr. 1, April Mae M. Numeron 1, Dominic Tadena 2, Christian C. Labrador 1, Mae A. Responte 1,3,4, Lief Erikson D. Gamalo 1,3,4, Jayson C. Ibañez 2,3, and Lyre Anni E. Murao 1,3,4 1 Philippine Genome Center Mindanao, University of the Philippines Mindanao, Mintal, Tugbok District, Davao City 8000, Philippines 2 Philippine Eagle Foundation, Philippine Eagle Center, Barangay Malagos, Baguio District, Davao City 8000, Philippines 3 Department of Biological Sciences and Environmental Studies, College of Science and Mathematics, University of the Philippines Mindanao. Mintal, Tugbok District, Davao City 8000, Philippines 4 Wildlife-Human Interaction Studies, Ecological Research and Biodiversity Conservation Laboratory, University of the Philippines Mindanao, Davao City 8000, Philippines *Corresponding Author: [email protected]

Pithecophaga jefferyi Ogilvie-Grant 1896 or the Philippine Eagle is endemic to the Philippines and is currently listed as an IUCN “critically endangered” species. There is currently an urgent need for genetic information to enhance conservation breeding and preserve the genetic diversity of this species. In this study, we explored the use of mitogenome sequencing as a cost-effective alternative for the genetic studies of Philippine Eagles. Analysis of partial mitogenomes revealed a mean nucleotide diversity of 0.10 to 0.16 from the 27 samples sequenced. This is much lower compared to most threatened bird species. Furthermore, we also observed that most samples belong to a single genetic cluster based on k-means clustering of the pairwise genetic distances, although we detected potentially two distinct subpopulations which was supported by an isolation by distance analysis. Nevertheless, some Philippine Eagle individuals showed distinct nucleotide profiles, with eagles from three key biodiversity area dyads exhibiting high F ST , indicating potential genetic differentiation. This suggests limited gene flow between these KBAs, but also their potential use to reinforce the nucleotide diversity in Philippine Eagle captive breeding programs. Finally, phylogenetic analysis of Philippine Eagles and other members of the Order Accipitriformes corroborates previous findings on the non-monophyletic status of the subfamily Circaetinae or the snake-eagles. Altogether, we demonstrate the utility of mitogenomes in assessing the genetic diversity and evolutionary relationships of avian species. Given the huge per-sample cost of whole genome sequencing, the approach utilizing mitogenome sequencing provides a cost-effective alternative to facilitate genetic studies of animals. We therefore anticipate an increasing utility of mitogenomes in population studies for biodiversity and genetic conservation research in the Philippines.

Philippine Eagle, mitogenome, genetic diversity, phylogenetics, conservation breeding

The Philippine Eagle Pithecophaga jefferyi Ogilvie-Grant 1896 belongs to the Family Accipitridae, a group composed of some of the most threatened bird species (McClure et al. 2023). The species is endemic to the Philippines with population records from four islands of the archipelago namely Mindanao, Luzon, Leyte and Samar (Kennedy et al. 2000). Being a forest-dependent raptor, the eagle’s major threat is the long term problem of deforestation throughout its range, together with other threats such as hunting and climate change (BirdLife International, 2018). The International Union for the Conservation of Nature (IUCN) and the Philippine Department of Environment and Natural Resources (DENR) consider the P. jefferyi as a critically endangered species (BirdLife International, 2018; DENR Administrative Order 2019-09), with an average estimated population of 392 potentially breeding pairs (Sutton et al. 2023). Over the years, the decreasing forest cover in the Philippines, in combination with hunting, retaliatory shooting, and trapping, have caused the continued decline of the Philippine Eagle population (Ibanez et al. 2016). This is further complicated by the fact that Philippine Eagles are late maturing, have a slow breeding cycle, and demonstrate high mate and nest site fidelity (Ibanez et al. 2016; Miranda et al. 2000), which altogether limit the ability of the wild population to recover. The continued decline of the Philippine Eagle population could also result in a genetic bottleneck, a stochastic event that decreases genetic variation (Nei. et al. 1975). Genetic bottlenecks increase inbreeding rates which decreases overall fitness and survival of populations in the wild (Frankham, 2008; Keller and Waller, 2002). A previous study conducted using the mitochondrial control region of 19 Philippine Eagles rescued from the wild together with 3 captive-bred individuals showed high genetic diversity comparable to non-threatened raptor species. However, the same study also detected indicators of possible recent genetic bottlenecks in Philippine Eagles (Luczon et al. 2014). Despite the increasing concern for highly threatened species, information on the genetic background of the Philippine Eagle is still incomplete. There are very few representative samples from the islands of Luzon, Samar and Leyte, which limits our ability to determine the historical patterns of gene flow for Philippine Eagles (Luczon et al. 2014). These underscore the need for more genetic studies that could provide information instrumental for decision-making for the Philippine Eagle’s conservation and management. There is an urgent need for effective conservation breeding efforts that lead to releases of suitably-reared Philippine Eagles to repopulate vacant habitats in the wild and save the species from extinction (Collar and Butchart, 2013). To address this, the Philippine Eagle Foundation (PEF), a private and non-profit organization, works at the forefront of conservation breeding to ensure the survival of Philippine Eagles and in the protection of its rainforest habitat through holistic conservation efforts. Its office base is located at the Philippine Eagle Center in Davao City, Philippines, and functions both as a conservation breeding and species rehabilitation facility for Philippine Eagles rescued from the wild. The PEF also employs both natural pairing techniques and cooperative artificial insemination in breeding eagles in captivity. It has produced 30 captive-bred eagles for the past 37 years since 1988, and 3 of which have been released into the wild (Bastian et al. 2007; Harder et al. 2006). In 2023, a new conservation breeding facility was established for Philippine Eagles to isolate and optimize the productivity of captive birds in Mt. Apo, a pristine forest habitat away from human disturbances and emerging zoonotic and bird infectious diseases. Conservation efforts could benefit from genetic information to improve captive breeding, and consequently, species reintroduction outcomes. However, there is currently a lack of genetic information for both nuclear and mitochondrial genomes of Philippine Eagles that can be used to inform pairing attempts (for natural pairs) and artificial insemination (for imprinted birds) among captive eagles. Describing the genetic variability of the current breeding stock can also guide future decisions on whether it is necessary to have new acquisitions of genetic stocks from the wild to improve genetic representations and the enhanced sustainability of the breeding program (Sato et al 2017). Next-generation sequencing technologies such as de novo whole genome sequencing (WGS) can be used to obtain high quality genetic information (Sohn and Nam, 2018). However, WGS requires considerable monetary investment due to the high cost of sequencing reagents (Schwarze et al. 2018, 2020). An alternative to this is to sequence the much smaller mitochondrial genome which is also a widely acceptable marker for genetic analysis (Bronstein et al. 2018; Elyasigorji et al. 2022; Huang et al. 2023; Lan et al. 2024; Wang et al. 2023). Mitogenome sequencing has been done for many mammal and bird species (Salleh et al. 2017; Sangster and Luksenburg, 2021) and have been used for a comprehensive assessment of the genetic diversity and evolutionary history of animals (Barker, 2014; Ferrari et al. 2024; Pacheco et al. 2011; Zhou et al. 2014). In addition, the availability of reference mitogenomes will contribute to the monitoring of wild populations to complement existing field ocular surveys; such as through the use of eDNA metabarcoding which requires a reference sequence for mitochondrial barcodes (Salleh et al. 2017). In this study, we sequenced the mitochondrial genomes of Philippine Eagles rescued from the wild and are currently housed in captivity at PEF as well as Philippine Eagles that were bred in captivity. Our analysis of the mitogenome assemblies enabled the assessment of the genetic diversity of the Philippine Eagles. We further performed phylogenetic analysis to understand the evolutionary relationship of Philippine Eagles with other accipitrids. Altogether, the new genetic information provided by this study could prove useful in improving the current captive breeding programs and conservation efforts for Philippine Eagles.

List of samples and blood collection A total of 27 Philippine Eagles currently housed at PEF were included in this study with 17 individuals rescued from the wild (9 females, 8 males) herein referred to as wild captives. Thirteen (13) of the wild captives were admitted as juveniles (ca 1-4 years old), 1 was admitted at ca 2-3 months old, two were admitted as adults and one was admitted with an unknown age. The oldest wild captive was rescued last 1984 and the youngest wild captive was rescued last 2020. The remaining 10 Philippine Eagles included in this study are all bred in captivity (5 females, 5 males), the oldest of which hatched last 1992 and the youngest hatched last 2015. The wild captives were from Mt. Kampalili-Puting Bato key biodiversity area (KBA) (5 individuals), Mt. Busa KBA (2 individuals), Mt. Malindang KBA (1 individual), Hilong-hilong KBA (1 individual), Samar Island Natural Park KBA (1 individual), Pantaron Kaulayan-Mt Kinabalian complex KBA (1 individual), Mt. Daguma KBA (1 individual), Mt. Piagayungan KBA (1 individual), Pasonanca KBA (1 individual), Bislig KBA (1 individual), Mt. Apo KBA (1 individual) and Mt. Diwata Range KBA (1 individual). The relevant metadata for each Philippine Eagle included in this study are listed in Table 1. Total of 1 mL blood samples were collected from each of the Philippine Eagles by licensed veterinarians during a scheduled annual physical examination for Philippine Eagles last February 17, 2021. All blood samples were placed in EDTA-containing collection tubes and transported to the Philippine Genome Center Mindanao laboratory for long term storage at -20℃. Table 1. List of Philippine Eagle samples included in this study and genbank accession numbers of the partial mitogenome assemblies. | Sample ID | Sample Name | Sex | Hatch Date | Admission Age | Origin | Origin and Key Biodiversity Area | Province | Region | Admission Date | GenBank Accession Number | | P1 | Ka Brianne | F | unknown | ca 1 year old | wild captive | Mt. Malindang | Misamis Occidental | 10 | July 01, 1987 | PQ839674 | | P2 | Freedom | M | unknown | ca 2-3 month old | wild captive | Mt. Busa | Sarangani | 12 | May 07, 2003 | PQ895382 | | P3 | Sultan | M | unknown | adult | wild captive | Mt. Daguma | South Cotabato | 12 | August 25, 2005 | PV059080 | | P4 | Wao | F | unknown | ca 3 years old | wild captive | Mt. Piagayungan | Lanao del Sur | 12 | April 25, 2015 | PV066235 | | P5 | Kalinawan | F | unknown | unknown | wild captive | Pasonanca | Zamboanga del Sur | 9 | June 06, 2009 | PQ760284 | | P6 | Mayumi | F | unknown | ca 1 year old | wild captive | Bislig | Surigao del Sur | 13 | April 13, 2007 | PV059081 | | P7 | Matatag | M | unknown | ca 1 year old | wild captive | Mt. Apo | Davao del Sur | 11 | April 18, 2011 | PV059082 | | P8 | Jag | M | unknown | adult | wild captive | Mt. Kampalili- Puting Bato | Davao de Oro | 11 | May 05, 1984 | PQ839673 | | P9 | Marikit | F | unknown | ca 1 year old | wild captive | Mt. Diwata Range | Surigao del Sur | 13 | November 10, 1995 | PV059083 | | P10 | Fighter | M | unknown | ca 1 year old | wild captive | Mt. Kampalili- Puting Bato | Davao Oriental | 11 | January 13, 2011 | PQ839677 | | P11 | Magiting | M | unknown | ca 4 years old | wild captive | Hilong-hilong | Agusan del Norte | 13 | September 15, 2002 | PV057430 | | P12 | Maslog | F | unknown | ca 2-3 years old | wild captive | Samar Island Natural Park | Eastern Samar | 8 | June 28, 2019 | PV057429 | | P13 | Caraga 1 | F | unknown | ca 1-2 years old | wild captive | Mt. Kampalili- Puting Bato | Davao Oriental | 11 | August 01, 2020 | PQ839676 | | P14 | Caraga 2 | M | unknown | ca 3-4 years old | wild captive | Mt. Kampalili- Puting Bato | Davao Oriental | 11 | September 26, 2020 | PV057428 | | P15 | Hiyas | F | unknown | ca 1 year old | wild captive | Mt. Kampalili- Puting Bato | Davao Oriental | 11 | April 07, 1999 | PQ839675 | | P16 | Bighani | M | December 07, 2007 | N/A | PEC captive-bred | Philippine Eagle Center | Davao del Sur | 11 | N/A | PV066240 | | P17 | Pagkakaisa | M | October 25, 1992 | N/A | PEC captive-bred | Philippine Eagle Center | Davao del Sur | 11 | N/A | PV081133 | | P18 | Aling Naty | F | November 11, 2000 | N/A | PEC captive-bred | Philippine Eagle Center | Davao del Sur | 11 | N/A | PQ867401 | | P19 | Pag-asa | M | January 15, 1992 | N/A | PEC captive-bred | Philippine Eagle Center | Davao del Sur | 11 | N/A | PV066239 | | P20 | Zeus | M | February 04, 2002 | N/A | PEC captive-bred | Philippine Eagle Center | Davao del Sur | 11 | N/A | PQ867402 | | P21 | Mabuhay | F | February 09, 2013 | N/A | PEC captive-bred | Philippine Eagle Center | Davao del Sur | 11 | N/A | PV066238 | | P22 | Princess Maasim | F | unknown | ca 1-2 years old | wild captive | Mt. Busa | Lanao del Sur | 12 | March 01, 1994 | PV066237 | | P24 | Pangarap | F | February 23, 1999 | N/A | PEC captive-bred | Philippine Eagle Center | Davao del Sur | 11 | N/A | PV066236 | | P25 | Sinag | M | December 07, 2015 | N/A | PEC captive-bred | Philippine Eagle Center | Davao del Sur | 11 | N/A | PQ845448 | | P26 | Dakila | F | November 25, 2005 | N/A | PEC captive-bred | Philippine Eagle Center | Davao del Sur | 11 | N/A | PQ855210 | | P27 | San Fernando | M | unknown | ca 3 year old | wild captive | Pantaron Kaulayan-Mt. Kinabalian Complex KBA | Bukidnon | 10 | October 04, 2020 | PV066234 | | P29 | Pinpin | F | November 23, 2006 | N/A | PEC captive-bred | Philippine Eagle Center | Davao del Sur | 11 | N/A | PQ845449 | DNA extraction and mitogenome enrichment Total DNA was extracted from 10 μl blood samples using the Qiagen DNeasy blood and tissue kit (Qiagen, Germany) according to the manufacturer’s instructions. DNA extracts were assessed for concentration (ng/μl) and purity (A260/A280nm) using a spectrophotometer. All 27 DNA extracts were stored at -20℃ prior to use. We designed 3 sets of primers to enrich the Philippine Eagle mitogenome via long range PCR with an estimated amplicon size of Philippine Eagles, we used mitogenome sequences that were available from GenBank from closely related eagle species belonging to the same Family Accipitridae namely, Spilornis cheela or crested serpent eagle (NC_015887), Aquila chrysaetos or golden eagle (NC_024087), Aquila nipalensis or steppe eagle (NC_045042), and Nisaetus alboniger or blyth’s hawk-eagle (NC_007599). Primers were designed to target conserved regions from the four reference mitogenome sequences (Appendix Figure 1). The resulting primer sequences, their position based on the Spilornis cheela mitogenome, and the in silico properties obtained from the Beacon Designer software (Premier Biosoft) are listed in Appendix Table 1. Long-range PCR was performed to amplify the mitochondrial DNA using the Expand TM Long Range dNTPack PCR kit (Roche, Switzerland). The PCR master mix consisted of 4.0 μl 5X Expand Long Range buffer with 12.5mM MgCl2, 1.0 μl of PCR nucleotide master mix, 0.6 μl each of 10mM forward and reverse primers, 0.6 μl of DMSO, 0.28 μl of Expand Long Range enzyme mix (5U/μl) and 8 μl of template DNA (≤ 500 ng) for a total of 20 μl volume per reaction. The cycling conditions used were as follows: initial denaturation at 94℃ for 2 minutes, first PCR round with 10 cycles of denaturation at 94℃ for 10 seconds, annealing at 58℃ for 15 seconds, and extension at 68℃ for 8 minutes, second PCR round with 25 cycles of denaturation at 94℃ for 10 seconds, annealing at 58℃ for 15 seconds, and extension at 68℃ for 8 minutes with a 20 second increment for every cycle. A final extension at 68℃ for 7 minutes was included and the reaction was held at 8℃. PCR products were visualized with agarose gel electrophoresis using a 2% agarose gel. All PCR products were stored at -20℃ prior to library preparation. Library preparation and DNA sequencing All 27 samples were processed for library preparation and Illumina sequencing. The three PCR amplicons for each sample were individually quantified using a qubit dsDNA HS assay kit according to the manufacturer’s instructions. Each amplicon was diluted to a final concentration of 0.20 ng/μl using nuclease-free water and all three amplicons for each sample were pooled using a volume of 1.67 μl (0.33 ng input DNA per amplicon) for a total of 5 μl volume containing 1 ng of input DNA. DNA tagmentation, amplification of tagmented DNA and clean-up of DNA libraries were performed using the Nextera XT library prep kit according to the manufacturer’s instructions. Cleaned libraries were sent to the Philippine Genome Center (PGC) DNA Sequencing Core Facility (DSCF), normalized, pooled and sequenced using MiSeq reagent kit v2 in a paired-end read format at 2 x 150 bp for 500 cycles. Mitogenome assembly and annotation Raw paired-end sequencing files in fastq format were subjected to Fastp (Chen et al. 2018) software for quality control processing and passed reads were interleaved using the MITObim (Hahn et al. 2013) interleave script. The reads from the interleaved files were used to generate an initial reference assembly using MIRA (Chevreux, 2007), which was subsequently used in MITObim to generate a final assembly using the Spilornis cheela mitogenome (NC_015887) as a seed. The generated assemblies were subjected to quality assessment with metrics such as mitogenome coverage, average consensus sequence quality, average read depth, and GC content (%GC). The generated assemblies were subjected to nucleotide BLAST (blastn) to confirm initial identities. Finally, MITOS (Bernt et al. 2013) was used to annotate the assembled mitogenome sequences to determine the identity, number of mitochondrial genes, and assess the completeness of the mitogenome sequences. The process was then repeated using a near-complete Philippine Eagle mitogenome as a seed sequence. Additional clean-up of mitogenome sequences was performed using the VecScreen tool in NCBI to remove potential vector contaminants. All the assembled Philippine Eagle partial mitogenome sequences were deposited in GenBank and the respective accession numbers are listed in Table 1. Multiple sequence alignment Multiple sequence alignment (MSA) was performed using the MAFFT software (Katoh and Standley, 2013). Briefly, we first removed the ambiguous regions consisting of stretches of Ns and used the E-INS-i algorithm to align the sequences. This algorithm is an iterative refinement method that incorporates weighted sum-of-pairs (WSP) and consistency scores and is appropriate for sequences with long stretches of unalignable regions (e.g., sequences of different lengths). We generated an MSA for the 27 samples sequenced in this study for use in diversity analysis and herein referred to as the Philippine Eagle dataset. Additionally, a separate MSA for phylogenetic analysis was prepared as described above containing the mitogenome sequences of species from the Order Accipitriformes together with four Philippine Eagle partial mitogenomes with more than 95% sequence coverage and herein referred to as the Accipitriformes dataset. Sequences were retrieved from GenBank using the read.GenBank function of the R package ape (Paradis et al. 2004) and the list of accession numbers listed in Appendix Table 2. MSAs were then processed in trimAl (Capella-Gutiérrez et al. 2009) for complete deletion of gaps. Diversity analysis We utilized the Philippine Eagle dataset to calculate the nucleotide diversity (Pi) using two approaches. The first approach used the MEGAX software (Kumar et al. 2018) to calculate the overall mean as well as the pairwise nucleotide distances using a partial deletion with 90% threshold, a maximum composite likelihood model with a gamma distributed rate and 1000 bootstrap replicates. In the second approach, we used the MSA with complete deletion of gaps processed with trimAl resulting to only 2184 nucleotide sites and computed for the nucleotide diversity using both the MEGAX and the DnaSP software v5 (Librado and Rozas, 2009). Principal coordinate analysis (PCoA) and k-means clustering was performed in RStudio using the nucleotide pairwise distance matrix for both MSAs with partial and complete deletion of gaps. We performed these calculations for all samples, as well as for the wild captives and for eagles bred in captivity which were considered distinct subpopulations for purposes of comparison. Using the same MSA which underwent complete deletion of gaps in trimAl, we also computed for the F ST values for subpopulations based on the eagle’s original habitat at the level of the key biodiversity area (KBA) and using the hierfstat package in R (Goudet, 2005) with the Nei87 method (Nei, 1987). The eagles bred in captivity at PEF were grouped as one subpopulation in the F ST calculations. Lastly, we assessed isolation by distance (IBD) of the Philippine Eagle population based on the Mantel test using the Adegene t package (Jombart, 2008) to assess the correlation of the pairwise genetic distance to the pairwise geographic distance. The sample coordinates were obtained from google earth using the centroid method for each province as the geographical area of origin. The correlation plots with local densities of genetic and geographic distances were visualized using non-parametric two-dimensional kernel density estimates (KDE; Jombart, 2008). Phylogenetic analysis To estimate the relationships of P. jefferyi to other bird species, phylogenetic reconstruction was performed using the Accipitriformes dataset which consisted of 11404 nucleotide sites. Representative species from the family Cathartidae, Pandionidae and Sagittariidae were used as an outgroup. The best DNA substitution and site heterogeneity model was initially calculated in MEGA X. Phylogenetic analysis was performed in BEAST v.1.10.4 (Suchard et al. 2018) with the best-fit model GTR+G+I (Pacheco et al. 2011), empirical base frequencies, an uncorrelated relaxed molecular clock with lognormal distribution, and 300 million MCMC iterations with sampling every 10000 trees. The estimated sampling size values (ESS) of all continuous parameters were assessed with Tracer v.1.7.2 (Rambaut et al. 2018) and the maximum clade credibility (MCC) tree was generated using TreeAnnotator v.1.10.4 with a 10% burn-in. The resulting phylogenetic tree was visualized and annotated using the ggtree R package (Yu et al. 2017). Long range PCR enrichment enabled the sequencing of near complete Philippine Eagle mitogenomes using the illumina platform We obtained a range of 1.49 million to 3.28 million paired-end sequencing reads per sample, and all 27 samples had more than 96% of the reads that passed the quality control steps (Appendix Table 3). Assembly using the Spilornis cheela (Latham, 1790) mitogenome as a seed sequence in MIRA-MITObim resulted in Philippine Eagle mitogenome sequences ranging from 13,930 bp to 21,089 bp (Appendix Table 4). All 27 samples, except one, had a total mitogenome assembly length of more than 16,000 bp. In addition, 22 out of 27 samples had a mitogenome sequence coverage of more than 50% and three samples with at least 80%. The Philippine Eagle Kalinawan had the best result with a 93.07% mitogenome sequence coverage from the 21,089 bp total assembled sequence length (Appendix Figure 2). The average read depth for each of the mitogenome assemblies ranged from 4.78 to 8222.71 reads and all the partial mitogenome sequences had comparable GC content at 46-48% (Appendix Table 4). We sought to improve the mitogenome assemblies by using a Philippine Eagle mitogenome as a seed sequence in the MIRA-MITObim pipeline. We hypothesized that by using a more closely related seed sequence, the assembly process can be improved resulting in better mitogenome coverage and read depth. We repeated the assembly process and used the Philippine Eagle Kalinawan original assembly as a seed sequence. We obtained new Philippine Eagle mitogenome assemblies ranging from 17,063 bp to 22,306 bp (Table 2). Furthermore, our results showed that there is a general increase in the mitogenome coverage as well as the average consensus quality in the new mitogenome assemblies compared to the original mitogenome assemblies (Figure 1). All the new mitogenome assemblies had a sequence coverage of more than 60%, with 9 samples that have more than 90% coverage (Table 2). The GC content of the new assemblies ranged from 46.60% to 50.05%, while the average read depth ranged from 10.30 to 10119.51, which was strongly correlated to the average read depth of the original assemblies that has a Pearson’s correlation coefficient of R = 0.98 ( p- value = <0.001) (Table 2) (Appendix Figure 3). Considering all of these improved metrics, we used the new Philippine Eagle mitogenome assemblies for all subsequent analysis. Table 2. Assembly statistics of the Philippine Eagle mitogenome samples using the original Kalinawan mitogenome assembly as a seed sequence. | Eagle Name | Total Sequence Length | # of N’s (Gaps) | Total Nucleotide Bases | # of A’s | # of T’s | # of G’s | # of C’s | %GC | % Genome Coverage | Average Consensus Quality | Average Read Depth | | Ka Brianne | 22306 | 3401 | 18905 | 5390 | 4354 | 3036 | 6125 | 48.46% | 84.75 | 61 | 4912.08 | | Freedom | 19588 | 2923 | 16665 | 4936 | 3831 | 2595 | 5303 | 47.39% | 85.08 | 67 | 233.73 | | Sultan | 20564 | 684 | 19880 | 5837 | 4609 | 3345 | 6089 | 47.50% | 96.67 | 66 | 3159.27 | | Kalinawan | 20873 | 37 | 20836 | 6269 | 4857 | 3196 | 6514 | 46.60% | 99.82 | 63 | 10119.51 | | Mayumi | 20251 | 481 | 19770 | 5859 | 4543 | 3215 | 6153 | 47.38% | 97.62 | 63 | 4599.36 | | Matatag | 19611 | 3356 | 16255 | 4765 | 3706 | 2746 | 5038 | 47.89% | 82.89 | 63 | 979.79 | | Jag | 21110 | 1503 | 19607 | 5648 | 4494 | 3095 | 6370 | 48.27% | 92.88 | 59 | 5592.90 | | Marikit | 19580 | 3660 | 15920 | 4679 | 3674 | 2537 | 5030 | 47.53% | 81.31 | 56 | 1780.48 | | Fighter | 19863 | 1473 | 18390 | 5374 | 4227 | 3037 | 5752 | 47.79% | 92.58 | 67 | 3257.08 | | Magiting | 20001 | 1952 | 18049 | 5327 | 4064 | 2802 | 5856 | 47.97% | 90.24 | 63 | 2795.14 | | Maslog | 19619 | 6022 | 13597 | 3955 | 3177 | 2120 | 4345 | 47.55% | 69.31 | 51 | 118.48 | | Caraga1 | 21717 | 1239 | 20478 | 5626 | 5077 | 3258 | 6517 | 47.73% | 94.29 | 67 | 2469.72 | | Caraga2 | 19584 | 3726 | 15858 | 4656 | 3666 | 2709 | 4827 | 47.52% | 80.97 | 63 | 604.02 | | Hiyas | 19187 | 3138 | 16049 | 4724 | 3722 | 2509 | 5094 | 47.37% | 83.65 | 62 | 10.30 | | Bighani | 19898 | 3130 | 16768 | 5054 | 3832 | 2681 | 5201 | 47.01% | 84.27 | 63 | 1712.53 | | Pagkakaisa | 19733 | 2778 | 16955 | 4974 | 3901 | 2642 | 5438 | 47.66% | 85.92 | 65 | 1406.12 | | Aling Naty | 19921 | 5636 | 14285 | 4170 | 3298 | 2331 | 4486 | 47.72% | 71.71 | 55 | 166.75 | | Pag-asa | 20760 | 119 | 20641 | 6084 | 4747 | 3477 | 6333 | 47.53% | 99.43 | 68 | 3687.66 | | Mabuhay | 19703 | 4734 | 14969 | 4458 | 3505 | 2333 | 4673 | 46.80% | 75.97 | 48 | 7742.72 | | PrincessMaasim | 20203 | 3269 | 16934 | 5143 | 3796 | 2683 | 5312 | 47.21% | 83.82 | 59 | 4761.47 | | Pangarap | 20158 | 2870 | 17288 | 5227 | 3926 | 2818 | 5317 | 47.06% | 85.76 | 60 | 2553.79 | | Sinag | 19800 | 3527 | 16273 | 4730 | 3658 | 2522 | 5363 | 48.45% | 82.19 | 67 | 540.49 | | Wao | 17698 | 4774 | 12924 | 3320 | 3360 | 2667 | 3577 | 48.31% | 73.03 | 48 | 23.77 | | Zeus | 18817 | 6544 | 12273 | 3283 | 2847 | 2695 | 3448 | 50.05% | 65.22 | 41 | 77.19 | | Dakila | 19298 | 5075 | 14223 | 4052 | 3217 | 2348 | 4606 | 48.89% | 73.70 | 50 | 94.73 | | San Fernando | 21804 | 1593 | 20211 | 5725 | 4708 | 3413 | 6365 | 48.38% | 92.69 | 58 | 5727.97 | | Pinpin | 17063 | 5874 | 11189 | 3109 | 2765 | 2036 | 3279 | 47.50% | 65.57 | 38 | 11.93 | Figure 1. The use of a Philippine Eagle mitogenome seed sequence in the MIRA-MITObim pipeline resulted in improved mitogenome assemblies for the Philippine Eagle samples. (A) Improvement in the mitogenome coverage, and (B) Improvement in the average consensus quality. We performed sequence homology analysis of the mitogenome sequences and obtained top blastn hits corresponding to eagle species from the subfamily Circaetinae (e.g., S. cheela and Circaetus pectoralis A. Smith, 1829) and vulture species from the subfamily Aegypiinae (e.g., Gyps fulvus (Hablizl, 1783), Aegypius monachus (Linnaeus, 1766), Gyps himalayensis Hume, 1869, and Gyps coprotheres (Forster, 1798)), all of which belong to the Family Accipitridae of the Order Accipitriformes (Appendix Table 5 and 6). Annotation of the best mitogenome assembly from the Philippine Eagle Kalinawan (mitogenome coverage = 99.82%) with MITOS identified a total of 14 tRNA genes, 2 rRNA genes and 11 protein-coding genes. In addition, based on all the MITOS annotation results, the maximum number of genes identified for each gene type are as follows: 14 tRNA genes, 2 rRNA genes and 12 protein-coding genes (Appendix Table 7). We performed blastn analysis of all the annotated gene segments from the Kalinawan mitogenome sequence and identified Pithecophaga jefferyi as the top hit organism based on cytB gene for which there is an available data from GenBank. Other blastn results for genes wherein there is no available data from NCBI for P. jefferyi identified Circaetinae species as the top hit organism such as for rrnL, CO1, and nad5 (Table 3). Table 3. MITOS annotation of the Kalinawan Philippine Eagle mitogenome assembly and the corresponding top nucleotide BLAST hits. | Position | Length | Gene Type | Top BLAST Hit Description | % Query Cover | E Value | % Identity | Accession ID | | 427-639 | 213 | cox2-3_b | Aegypius monachus mitochondrion, complete genome | 100 | 1.30E-64 | 86.85 | KF682364 | | 707-1831 | 1125 | cob-0 | Pithecophaga jefferyi cytochrome b ( cytb ) gene, partial cds; mitochondrial | 61 | 0 | 99.85 | AY987245 | | 1863-2312 | 450 | cob-1_b | Pithecophaga jefferyi cytochrome b ( cytb ) gene, partial cds; mitochondrial | 76 | 4.22E-151 | 95.29 | AY987245 | | 3125-3193 | 69 | trnF(gaa) | Phoenicurus frontalis mitochondrion, complete genome | 99 | 1.77E-16 | 91.18 | NC_053917 | | 3193-4031 | 839 | rrnS | Arenaria melanocephala voucher JJW3588 mitochondrion, complete genome | 38 | 1.81E-108 | 88.96 | OR242827 | | 4087-4155 | 69 | trnF(gaa) | Phoenicurus frontalis mitochondrion, complete genome | 99 | 1.77E-16 | 91.18 | NC_053917 | | 4155-5126 | 972 | rrnS | TPA_asm: Gymnogyps californianus isolate CaCo_309 mitochondrion, complete genome | 100 | 0 | 87.74 | BK059163 | | 5126-5197 | 72 | trnV(tac) | Recurvirostra americana 12S ribosomal RNA and tRNA-Valk genes, complete sequence; mitochondrial | 99 | 7.18E-22 | 95.77 | DQ485793 | | 5198-6794 | 1597 | rrnL | Aegypius monachus mitochondrion, complete genome | 100 | 0 | 88.37 | KF682364 | | 6794-6867 | 74 | trnL2(taa) | Oceanites oceanicus mitochondrion, complete genome | 99 | 1.20E-25 | 98.63 | NC_052777 | | 6905-7273 | 369 | nad1_a | Phoenicopterus ruber mitochondrion, partial genome | 100 | 1.35E-124 | 87.53 | MN356144 | | 7273-7455 | 183 | nad1_b | Columba rupestris mitochondrion, complete genome | 99 | 2.70E-53 | 86.81 | NC_031867 | | 7669-8049 | 381 | nad1_c | Butastur indicus mitochondrial DNA, complete genome | 100 | 2.22E-109 | 83.73 | NC_032362 | | 8057-8128 | 72 | trnI(gat) | Cuculus canorus 16S ribosomal RNA gene, partial sequence; tRNA-Leu gene, complete sequence; NADH dehydrogenase subunit 1 (ND1) gene, complete cds; tRNA-Ile, tRNA-Gln, and tRNA-Met genes, complete sequence; NADH dehydrogenase subunit 2 (ND2) gene, complete cds; tRNA-Trp, tRNA-Ala, tRNA-Asn, tRNA-Cys, and tRNA-Tyr genes, complete sequence; and cytochrome oxidase subunit I (COI) gene, partial cds; mitochondrial genes for mitochondrial products | 100 | 4.84E-24 | 97.22 | AY274060 | | 8139-8209 | 71 | trnQ(ttg) | Phoebastria albatrus 2003-0071 mitochondrial DNA, complete genome | 100 | 1.64E-23 | 97.18 | LC541455 | | 8209-8277 | 69 | trnM(cat) | Brachypteracias leptosomus mitochondrion, complete genome | 100 | 1.55E-23 | 98.55 | NC_052810 | | 8328-8546 | 219 | cox3-1 | Tachybaptus ruficollis mitochondrion, complete genome | 95 | 2.77E-73 | 90.82 | NC_024594 | | 8537-9310 | 774 | nad2 | Pithecophaga jefferyi voucher TPEF 227, captive NADH dehydrogenase subunit 2 ( ND2 ) gene, complete cds; mitochondrial | 99 | 0 | 99.74 | AY987064 | | 10361-11461 | 1101 | cox1 | Spilornis cheela mitochondrion, complete genome | 100 | 0 | 91.28 | NC_015887 | | 11462-11535 | 74 | trnS2(tga) | Gyps himalayensis mitochondrion, complete genome | 100 | 3.44E-26 | 98.65 | KY594709 | | 11540-11608 | 69 | trnD(gtc) | Halcyon pileata mitochondrion, complete genome | 100 | 1.88E-22 | 97.1 | NC_024198 | | 11612-11824 | 213 | cox2-3_a | Haliaeetus albicilla mitochondrion, partial genome | 99 | 1.69E-69 | 89.05 | MN356434 | | 11886-12671 | 786 | cox2-0 | Circaetus pectoralis mitochondrion, complete genome | 55 | 6.71E-158 | 89.56 | NC_052805 | | 12682-12752 | 71 | trnK(ttt) | Reinwardtoena reinwardtii mitochondrion, complete genome | 100 | 6.98E-22 | 95.77 | NC_077264 | | 12754-12912 | 159 | atp8-0 | Spilornis cheela mitochondrion, complete genome | 100 | 8.98E-46 | 87.04 | NC_015887 | | 13470-14033 | 564 | atp6 | Spilornis cheela mitochondrion, complete genome | 98 | 0 | 88.65 | NC_015887 | | 14036-14665 | 630 | cox3-0_a | Buteo lagopu s voucher AHNU:A0381 mitochondrion, complete genome | 100 | 0 | 91.59 | NC_029189 | | 14695-14832 | 138 | cox3-0_b | Milvus milvus mitochondrion, partial genome | 94 | 1.19E-49 | 95.38 | MN122837 | | 14834-14902 | 69 | trnG(tcc) | Accipiter nisus mitochondrion, complete genome | 100 | 3.64E-25 | 100 | KJ680300 | | 14903-15076 | 174 | nad3-0 | Buteo jamaicensis cytochrome oxidase subunit III gene, partial cds; tRNA-Gly gene, complete sequence; and NADH dehydrogenase subunit III gene, partial cds, mitochondrial genes for mitochondrial products | 100 | 4.02E-57 | 89.66 | AF076298 | | 15085-15180 | 96 | nad3-1 | Pithecophaga jefferyi cytochrome b ( cytb ) gene, partial cds; mitochondrial | 70 | 7.92E-24 | 100 | AY987245 | | 15176-15406 | 231 | cox2-2_a | Aquila chrysaetos mitochondrion, complete genome | 100 | 5.33E-89 | 92.64 | NC_024087 | | 15405-15671 | 267 | nad4l | Spilornis cheela mitochondrion, complete genome | 100 | 9.38E-87 | 87.64 | NC_015887 | | 15732-16007 | 276 | cob-3 | Pithecophaga jefferyi cytochrome b ( cytb ) gene, partial cds; mitochondrial | 100 | 4.72E-135 | 99.64 | AY987245 | | 16405-16617 | 213 | cox2-2_b | Circaetus pectoralis mitochondrion, complete genome | 99 | 9.33E-73 | 90.05 | NC_052805 | | 16611-16880 | 270 | cob-2_b | Pithecophaga jefferyi cytochrome b ( cytb ) gene, partial cds; mitochondrial | 96 | 2.72E-125 | 99.23 | AY987245 | | 17215-17273 | 59 | trnN(gtt) | Butastur indicus mitochondrion, complete genome | 81 | 9.25E-06 | 87.5 | MW017133 | | 17372-17441 | 70 | trnH(gtg) | Accipiter nisus mitochondrion, complete genome | 100 | 1.07E-25 | 100 | KJ680300 | | 17442-17507 | 66 | trnS1(gct) | Chlamydotis macqueeni i mitochondrion, partial genome | 100 | 7.29E-21 | 96.97 | MN356124 | | 17508-17578 | 71 | trnL1(tag) | Pedionomus torquatus mitochondrion, partial genome | 100 | 1.35E-24 | 98.59 | MN356368 | | 17718-18176 | 459 | cox2-1 | Circaetus pectoralis mitochondrion, complete genome | 93 | 9.49E-147 | 87.09 | NC_052805 | | 18195-19529 | 1335 | nad5 | Circaetus pectoralis mitochondrion, complete genome | 100 | 0 | 89.13 | NC_052805 | | 19774-19857 | 84 | atp8-1 | Spilornis cheela mitochondrion, complete genome | 100 | 4.34E-26 | 94.05 | NC_015887 | | 19858-20109 | 252 | cob-2_a | Pithecophaga jefferyi cytochrome b ( cytb ) gene, partial cds; mitochondrial | 100 | 2.35E-119 | 98.81 | AY987245 | | 20154-20444 | 291 | cob-4 | Pithecophaga jefferyi cytochrome b ( cytb ) gene, partial cds; mitochondrial | 43 | 4.71E-53 | 99.2 | AY987245 | | 20631-20873 | 243 | cob-1_a | Rostrhamus sociabilis voucher LSUMZ B49411 cytochrome b ( cytb ) gene, partial cds; mitochondrial | 55 | 4.08E-40 | 89.47 | GQ264854 | Genetic diversity analysis showed weak differentiation of Philippine Eagles from different key biodiversity areas in Southern Philippines Analysis of the partial mitogenome assemblies showed that the mean nucleotide diversity of the Philippine Eagles is around 0.10 to 0.16 when using a complete deletion or 90% partial deletion threshold, respectively (Table 4). The overall mean nucleotide diversity is slightly higher for the Philippine Eagles bred in captivity at PEF (0.11876; 0.21) compared to the wild captives (0.09983; 0.15). PCoA of the pairwise nucleotide distances showed three distinct clusters based on k-means clustering, (i) a group composed of the majority of the samples sequenced, (ii) a group composed of Ka Brianne, Freedom and Sultan, all of which are wild captives and, (iii) a third group represented by one sample, the Philippine Eagle Wao which is also a wild captive (Figure 2). A closer inspection of the first cluster containing the majority of the samples sequenced showed potentially two distinct subgroups based on the pairwise nucleotide distances of the MSA with partial deletion (Figure 2A), although this is not evident when all sites with gaps are excluded in the analysis (Figure 2B). Table 4. Nucleotide diversity of the Philippine Eagles calculated using a partial deletion threshold of 90% and with a complete deletion of gaps. | Software | Alignment Threshold | Nucleotide Diversity (Pi) | || | Overall Mean | Wild Captives | Eagles Bred In Captivity at PEC | || | MEGA X | Partial Deletion (90%) | 0.16000 | 0.15000 | 0.21000 | | MEGA X | Complete Deletion | 0.12000 | 0.12000 | 0.14000 | | DnaSP v5 | Complete Deletion | 0.10556 | 0.09983 | 0.11876 | Figure 2. Principal coordinate analysis of the pairwise genetic distances of the 27 Philippine eagle mitogenomes using (A) partial deletion of gaps with a 90% threshold, and (B) complete deletion of gaps in the sequence alignment. We defined genetic differentiation according to the F ST criterion suggested by Wright (1978): F ST < 0.05 indicates low genetic differentiation; 0.05 to 0.15 as moderate; 0.15-0.25 as high, and F ST calculations among Philippine Eagle subpopulations revealed relatively low values (0.15), such as the Philippine Eagles from Mt. Piagayungan-Mt. Kampalili Puting Bato dyad, Mt. Piagayungan-Mt. Busa dyad and Mt. Piagayungan-PEC dyads (Figure 3). The highest F ST value ( F ST = 0.1633) was recorded between Mt. Piagayungan, located in Lanao del Sur and Mt. Busa located in South Cotabato. Based on the IBD analysis, the Philippine Eagles distributed among the KBAs and the PEC eagles, indicated a weak correlation (R 2 = 0.01967, p -value = 0.00488) between the pairwise genetic distance and the pairwise geographical distance. Nevertheless, the KDE plots show two separate density patches (Figure 4) that could represent two distinct subpopulations. Figure 3. F ST values for each Philippine Eagle subpopulation based on the key biodiversity area (KBA) of origin calculated using the Nei87 method in the hierfstat package in R. The Philippine Eagles bred in captivity were grouped in one subpopulation (PEC). Figure 4. Isolation by distance plot of the Philippine Eagles based on partial mitogenome sequences estimated using the adegenet package. Phylogenetic analysis highlights the divergence of Philippine Eagles from other member species of the subfamily Circaetinae Our bayesian phylogenetic analysis showed the divergence of Elanus caeruleus (Desfontaines, 1789) or black-winged kite, which diverged first from the rest of the Accipitridae, followed by the divergence of the species Pernis ptilorhynchus (Temminck, 1821) or crested honey buzzard from the remaining members of the Accipitridae (Figure 5). At the subfamily level, Accipitrinae and Circaetinae showed non-monophyly while Buteoninae, Aquilinae and Aegypiinae were monophyletic. The non-monophyly of Circaetinae was caused by the paraphyletic groups, P. jefferyi, E. caeruleus and P. ptilorhynchus . Similarly, the non-monophyly of Accipitrinae was caused by the split of Accipiter trivirgatus (Temminck, 1824) from the clade containing all other Accipitrinae and Buteoninae species, which also rendered the genus Accipiter as non-monophyletic. Furthermore, the non-monophyly of the genus Accipiter was also apparent with member species from the genera Circus being embedded within the Accipiter clade. Other seemingly non-monophyletic genus includes Aquila and Hieraaetus with some samples embedded in branches containing species from other genera. All of these observations were supported by a strong posterior value ranging from 0.8 to 1.0 (Figure 5). Finally, the commonly used bird types do not reflect a shared genetic relationship based on mitochondrial genomes (Figure 5). Figure 5. Bayesian phylogenetic analysis of birds of prey from the order Accipitriformes and including four Philippine Eagle mitogenomes with tip labels highlighted in pink. The final alignment used was 11404 bp without gaps. Branch color indicates the posterior support value and tips are labeled with the bird species. The first heatmap ring after the tip labels represents the family taxa, followed by the subfamily taxa and finally the type of bird.

Diversity analysis of the Philippine Eagle partial mitogenome sequences generated from this study indicated an overall nucleotide diversity (Pi) of 0.10 to 0.16. These values are higher compared to what was previously reported for Philippine Eagles using the mitochondrial control region (Luczon et al. 2014) but is much lower than the genetic diversity of most of the threatened bird species based on mitochondrial DNA with an average Pi of 0.4 (Canteri et al. 2021), reinforcing the status of the Philippine Eagle as a critically endangered species. Notably, we observed that the eagles bred in captivity have slightly higher nucleotide diversity compared to the wild captives. This suggests that there is higher inbreeding in the wild population leading to lower genetic diversity and increasing the risk of species extinction (Frankham et al. 2019) which is somehow expected considering the very few remaining Philippine Eagle breeding pairs in the wild (Sutton et al. 2023). Alternatively, the higher nucleotide diversity of Philippine Eagles bred in captivity could also imply that the captive breeding efforts employed at the Philippine Eagle Foundation can be used to increase or maintain the genetic diversity of this highly threatened species. It is noted that progenies of captive breeding programs are often characterized by lower genetic diversity with potential detrimental effects on generational fitness (Farkuharson et al. 2021; Posso-Pelaez et al. 2018; Purohit et al. 2021; Thintip et al. 2021). However, other captive breeding programs were also shown to maintain genetic diversity of captive populations relative to the remaining wild population and has led to population rebound in the case of the endemic pink pigeon Nesoenas mayeri (Prévost, 1843), the California Condor Gymnogyps californianus, the endangered Mauritius Kestrel Falco punctatus, and the Peregrine Falcon Falco peregrinus (Buckley et al. 2024; Campos et al. 2021; Cassin-Sacket et al. 2021; Jackson et al. 2022; Morrison et al. 2020; Nicoll et al. 2021; Tordoff et al. 2001; Walters et al. 2010). Hence, the ability to identify genetic groups among the wild captives and eagles bred in captivity can help design pairing schemes to avoid inbreeding and ensure that genetic diversity is maintained for the resulting progeny (Jansamut et al. 2024; Purohit et al. 2021). Based on the F ST analysis (Figure 3) in this study, we observed one Philippine Eagle group, specifically in Mt. Piagayungan, which showed some degree of differentiation, relative to the rest of the samples. The highest F ST values among the following dyads: Mt. Piagayungan & Mt. Busa; Mt. Piagayungan & Mt. Kampalili Puting Bato; and Mt. Piagayungan and PEC, indicate relatively high genetic diversity within Mt. Piagayungan. These highlight the availability of genetically distinct individuals or subpopulations, as revealed in this study, that can be used for breeding eagles in captivity to minimize inbreeding and its deleterious consequences. In addition to genetic conservation, mitochondrial genomes can also be used to assess the evolutionary relationship of avian species through phylogenetic analysis (Barker, 2014; Pacheco et al. 2011). Currently, there is no consensus on the phylogenetic relationships of the members of the Neornithes or modern birds (Mayr and Clarker, 2004; Pacheco et al. 2011; Springer and Gatesy, 2024). This is highlighted by a recent study that showed a high level of non-monophyly within the currently recognized genus Accipiter in the subfamily Accipitrinae of the Order Accipitriformes (Catanach et al. 2024). Results from our phylogenetic analysis showed the divergence of Philippine Eagles from other members of the family Accipitridae resulting in a non-monophyletic clade for the subfamily Circaetinae which corroborated the previous study of Lerner and Mindell (Lerner and Mindell, 2005), but contrasts with the recent findings of Catanach and colleagues based on ultraconserved elements and legacy markers, although only a single Philippine Eagle sample was used in their analysis (Catanach et al. 2024). Nevertheless, the phylogenetic relationships of many avian taxa including some species of accipitrids remain unresolved (Catanach et al. 2024). While more recent studies are starting to invest in the whole genome sequencing of modern birds such as for the family Accipitridae, due to the large number of extant species comprising the Neornithes, the cost needed to sequence the genomes of all member species is projected to be massive (Callaghan et al. 2021; Catanach et al. 2024; Jetz et al. 2012). In this regard, mitogenome sequencing is a more cost effective alternative to obtain genetic information to expedite the assessment of the phylogenetic relatedness of Neornithes using molecular data. Sequencing of the complete mitogenomes of birds and mammals, including volant mammals such as bats, have been done in several studies by utilizing PCR-based enrichment and amplicon-based sequencing (Barker, 2014; Emser et al. 2021; Finstermeier et al. 2013; Hassanin et al. 2020; Meimberg et al. 2016; Pacheco et al. 2011). Consistent with our results, amplicon-based sequencing has been shown to enable the assembly of high quality mitogenomes from less than 3 million raw sequencing reads per sample (Nuñez and Oleksiak, 2016), a very cost-effective approach that can have a per sample cost of as low as 10 USD (Kneubehl et al. 2022). In comparison, most studies that were able to generate complete mitogenomes from de novo sequencing experiments without any enrichment used tens to hundreds of millions of raw sequencing reads per sample (Groenenberg et al. 2012; Hung et al. 2013; Malmstrom et al. 2017; Nowak et al. 2019). In addition, the utility of long-range PCR-based enrichment for sequencing and assembly of complete animal mitogenomes has also been demonstrated for complex samples such as environmental DNA (Deiner et al. 2017). Although only 4 Philippine Eagle samples yielded near-complete mitogenomes with more than 95% sequence coverage, this can be improved with further optimization of the primer design and/or long-range PCR conditions. Alternatively, primers can be designed to reduce the length of PCR products at around 4-5 kb as has been done for bat mitogenome sequencing (Hassanin et al. 2020), or less than 500 bp as with similar amplicon-based sequencing approaches that have been successfully implemented for small viral genomes less than 30 kb in length (Brunker and Quick, 2020; Quick, 2020). On average, animal mitogenomes are around 16 kb long (Boore, 1999; Sweet et al. 2022), whereas most mitogenomes of birds of prey range from 16 kb to 20 kb in length (Appendix Table 2). The small size of animal mitogenomes thus allows for the easy and rapid design of primers for multiplex PCR and amplicon-based sequencing (Quick et al. 2017). Altogether, these underscore the importance of amplicon-based sequencing as a cost-effective alternative to complement existing PCR-free sequencing workflows for the genetic studies of animals.

Our study demonstrated weak isolation by distance among Philippine Eagles across PEC samples and different KBAs based on partial mitogenomes. This suggests a high rate of inbreeding among Philippine Eagles which is consistent with its conservation status as a critically endangered species. However, we observed high pairwise F ST values in certain KBAs, specifically dyads paired with Mt. Piagayungan samples, indicating high genetic differentiation within this subpopulation. These findings highlight the potential utility of individuals from this genetically distinct subpopulation for conservation breeding programs, which could help enhance genetic diversity in captive-bred eagles and further support its reintroduction into the wild. These results emphasize the need to integrate genetic information in conservation breeding for critically endangered species such as the Philippine Eagle. Finally, the results from our phylogenetic analysis suggests the non-monophyly of the subfamily Circaetinae due to divergence of Philippine Eagles from other member species. Altogether, we demonstrate the value of mitogenome sequencing as a cost-effective alternative in the genetic and evolutionary analysis of animals. We anticipate the wide use of this approach in the Philippines to study population biology and conservation efforts, as well as in assessing the evolutionary phylogeny of the Neornithes. AUTHOR CONTRIBUTIONS Michael Bacus: conceptualization (equal), supervision (equal), methodology (equal), data curation (equal), formal analysis (equal), writing original draft (lead). Paul Lorenzo Gaite: methodology (equal), data curation (equal), writing original draft (supporting). Joan Acaso: sample collection (equal), methodology (equal). Joshua Cambronero: methodology (equal), data curation (equal). Gerry Ramos: methodology (equal), data curation (equal). April Mae Numeron: methodology (equal). Dominic Tadena: sample collection (equal). Christian Labrador: methodology (equal). Mae Responte: formal analysis (equal), review and editing (equal). Lief Erikson Gamalo: conceptualization (equal), sample collection (equal), review and editing (equal), writing original draft (supporting). Jayson Ibañez: conceptualization (equal), sample collection (equal), review and editing (equal). Lyre Anni Murao: conceptualization (equal), supervision (equal), funding acquisition (lead), review and editing (equal). ACKNOWLEDGMENTS The study is led by the Philippine Genome Center Mindanao which was funded by the Department of Science and Technology (DOST) through the Philippine Council for Health Research and Development (PCHRD). The Philippine Eagle Foundation (PEF) provided all the samples used for this study. We thank Dr Bayani Vandenbroeck and Dr Sheen Gadong of the Doc Bayani Animal Wellness Clinic for performing the blood extraction and eagle check-ups. The PEF has a Memorandum of Agreement with the Department of Environment and Natural Resources (DENR) for research and conservation of Philippine Eagles across the country. CONFLICTS OF INTEREST All authors declare no conflict of interest DATA AVAILABILITY STATEMENT All Philippine Eagle partial mitogenome assemblies are deposited in GenBank. The relevant metadata of the Philippine Eagles included in this study and the respective accession numbers are listed in Table 1. The details of the primer design used for mitogenome enrichment are listed in Appendix Table 1. All mitogenome sequences used for phylogenetic analysis are also accessible from GenBank with the accession numbers listed in Appendix Table 2.

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The multiple sequence alignment (MSA) was generated in MEGA X using the MUSCLE algorithm and sequences were manually checked to select for primers. The MSA shown here was generated using the ggmsa package in R for the following primers (from top to bottom): PEmtDNA_1FD, PEmtDNA_1RS, PEmtDNA_2FD, PEmtDNA_2RS, PEmtDNA_3FD, and PEmtDNA_3RS. The reverse primers (RS) are aligned using the reverse complement sequence. Appendix Figure 2. Assembly statistics of Philippine Eagle mitogenomes using MIRA-MITObim and the S. cheela reference mitogenome as a seed sequence. (A) Total assembly sequence length and mitogenome coverage, and (B) ATCG base composition of the Philippine Eagle mitogenome assemblies. Appendix Figure 3. Pearson’s correlation of the average read depth of the original assemblies using the S. cheela mitogenome as a seed sequence compared to the new assemblies using the Kalinawan mitogenome as a seed sequence. Appendix Table 1. List of long range PCR primers designed to amplify the Philippine Eagle mitogenome and the in silico properties. | Primer ID | Nucleotide Sequence (5’-3’) | Position ( S. cheela) | Length (bp) | GC % | T m (ºC) | Hairpin (ΔG) | Self-Dimer (ΔG) | Cross Dimer(ΔG) | | PEmtDNA-1FD | CAT GCA CTA CAC CGC AGA CAC | 159 | 21 | 57.14 | 60.16 | -2.0 | -3.4 | -2.4 | | PEmtDNA-1RS | CTT GAA CCT CTG GGT AAA GGG | 7338 | 21 | 52.38 | 56.18 | -1.5 | -1.5 | | | PEmtDNA-2FD | CCA ACC GAG CTG GGT GAT AG | 6030 | 20 | 60.0 | 57.15 | -1.5 | -3.0 | -5.0 | | PEmtDNA-2RS | GGA AGA ATG CCC AGA AGA AGC C | 13553 | 22 | 54.55 | 58.97 | 0.0 | 0.0 | | | PEmtDNA-3FD | CAA GCC AGC CGC ATC TAA CC | 11537 | 20 | 60.0 | 59.75 | 0.0 | 0.0 | -5.4 | | PEmtDNA-3RS | GTT GGC TGC CGA TTC ATG TGA G | 1027 | 22 | 60.0 | 59.75 | 0.0 | -2.4 | Appendix Table 2. List of mitogenome sequences from the order Accipitriformes obtained from genbank. | Accession ID | Species | Genus | Family | Subfamily | BirdType | CommonName | Mitogenome Size (bp) | | OK662584 | Elanus caeruleus | Elanus | Accipitridae | Elaninae | Kite | Black-winged kite | 18898 | | LC541458 | Pernis ptilorhynchus orientalis | Pernis | Accipitridae | Perninae | Buzzard | Crested honey buzzard | 18340 | | JN191388 | Spilornis cheela | Spilornis | Accipitridae | Circaetinae | Eagle | Crested serpent eagle | 18291 | | MN356306 | Circaetus pectoralis | Circaetus | Accipitridae | Circaetinae | Eagle | Black-chested snake eagle | 17473 | | KX893247 | Gyps fulvus | Gyps | Accipitridae | Aegypiinae | Vulture | Eurasian griffon vulture | 18094 | | KY594709 | Gyps himalayensis | Gyps | Accipitridae | Aegypiinae | Vulture | Himalayan vulture | 17381 | | MF683387 | Gyps coprotheres | Gyps | Accipitridae | Aegypiinae | Vulture | Cape vulture | 16908 | | KF682364 | Aegypius monachus | Aegypius | Accipitridae | Aegypiinae | Vulture | Cinereous vulture | 17811 | | LR822062 | Aquila chrysaetos chrysaetos | Aquila | Accipitridae | Aquilinae | Eagle | Golden eagle | 18265 | | MT319112 | Aquila chrysaetos canadensis | Aquila | Accipitridae | Aquilinae | Eagle | Golden eagle | 17472 | | KF905228 | Aquila chrysaetos | Aquila | Accipitridae | Aquilinae | Eagle | Golden eagle | 17332 | | MK860035 | Aquila nipalensis | Aquila | Accipitridae | Aquilinae | Eagle | Steppe eagle | 18450 | | KU646835 | Aquila heliaca | Aquila | Accipitridae | Aquilinae | Eagle | Eastern imperial eagle | 18067 | | MZ595097 | Aquila audax | Aquila | Accipitridae | Aquilinae | Eagle | Wedge-tailed eagle | 17324 | | MK453378 | Aquila audax | Aquila | Accipitridae | Aquilinae | Eagle | Wedge-tailed eagle | 17284 | | AP008239 | Nisaetus alboniger | Nisaetus | Accipitridae | Aquilinae | Eagle | Blyth’s hawk-eagle | 17977 | | AP008238 | Nisaetus nipalensis | Nisaetus | Accipitridae | Aquilinae | Eagle | Mountain hawk-eagle | 17667 | | MN356300 | Spizaetus tyrannus | Spizaetus | Accipitridae | Aquilinae | Eagle | Black hawk-eagle | 17479 | | KP329567 | Hieraaetus fasciatus | Hieraaetus | Accipitridae | Aquilinae | Eagle | Bonelli’s eagle | 18513 | | MK294165 | Hieraaetus pennatus | Hieraaetus | Accipitridae | Aquilinae | Eagle | Booted eagle | 17666 | | MK294164 | Hieraaetus morphnoides | Hieraaetus | Accipitridae | Aquilinae | Eagle | Little eagle | 17659 | | MK294166 | Harpagornis moorei | Hieraaetus | Accipitridae | Aquilinae | Eagle | New Zealand giant eagle | 17272 | | KJ680300 | Accipiter nisus | Accipiter | Accipitridae | Accipitrinae | Hawk | Eurasian sparrowhawk | 19417 | | KM360148 | Accipiter nisus | Accipiter | Accipitridae | Accipitrinae | Hawk | Eurasian sparrowhawk | 18647 | | MN929010 | Accipiter nisus | Accipiter | Accipitridae | Accipitrinae | Hawk | Eurasian sparrowhawk | 18352 | | MN122826 | Accipiter nisus | Accipiter | Accipitridae | Accipitrinae | Hawk | Eurasian sparrowhawk | 16426 | | OV839400 | Accipiter gentilis | Accipiter | Accipitridae | Accipitrinae | Hawk | Northern goshawk | 18745 | | AP010797 | Accipiter gentilis | Accipiter | Accipitridae | Accipitrinae | Hawk | Northern goshawk | 18266 | | MN122867 | Accipiter gentilis | Accipiter | Accipitridae | Accipitrinae | Hawk | Northern goshawk | 16197 | | PQ049665 | Accipiter gentilis | Accipiter | Accipitridae | Accipitrinae | Hawk | Northern goshawk | 16197 | | MK953813 | Accipiter trivirgatus | Accipiter | Accipitridae | Accipitrinae | Hawk | Crested goshawk | 18454 | | KJ699124 | Accipiter virgatus | Accipiter | Accipitridae | Accipitrinae | Hawk | Besra sparrowhawk | 17952 | | KP336714 | Accipiter virgatus | Accipiter | Accipitridae | Accipitrinae | Hawk | Besra sparrowhawk | 17654 | | KJ680303 | Accipiter soloensis | Accipiter | Accipitridae | Accipitrinae | Hawk | Chinese sparrowhawk | 17900 | | KU237286 | Circus cyaneus | Circus | Accipitridae | Accipitrinae | Harrier | Hen harrier | 20173 | | KX925606 | Circus cyaneus | Circus | Accipitridae | Accipitrinae | Harrier | Hen harrier | 18754 | | MK386464 | Circus teauteensis | Circus | Accipitridae | Accipitrinae | Harrier | Eyles’s harrier | 17873 | | KT438620 | Circus melanoleucos | Circus | Accipitridae | Accipitrinae | Harrier | Pied harrier | 17749 | | MN122837 | Milvus milvus | Milvus | Accipitridae | Buteoninae | Kite | Red kite | 17883 | | OP133375 | Haliastur indus | Haliastur | Accipitridae | Buteoninae | Kite | Brahminy kite | 19055 | | MN356134 | Haliaeetus leucocephalus | Haliaeetus | Accipitridae | Buteoninae | Eagle | Bald eagle | 18645 | | PQ049664 | Haliaeetus leucocephalus | Haliaeetus | Accipitridae | Buteoninae | Eagle | Bald eagle | 18645 | | MK043028 | Haliaeetus albicilla | Haliaeetus | Accipitridae | Buteoninae | Eagle | White-tailed eagle | 17719 | | MN356434 | Haliaeetus albicilla | Haliaeetus | Accipitridae | Buteoninae | Eagle | White-tailed eagle | 16462 | | AB830617 | Butastur liventer | Butastur | Accipitridae | Buteoninae | Buzzard | Rufous-winged buzzard | 19673 | | AB830616 | Butastur indicus | Butastur | Accipitridae | Buteoninae | Buzzard | Grey-faced buzzard | 19059 | | MW017133 | Butastur indicus | Butastur | Accipitridae | Buteoninae | Buzzard | Grey-faced buzzard | 18169 | | LC541471 | Butastur indicus | Butastur | Accipitridae | Buteoninae | Buzzard | Grey-faced buzzard | 18013 | | AF380305 | Buteo buteo | Buteo | Accipitridae | Buteoninae | Buzzard | Common buzzard | 18674 | | OZ076953 | Buteo buteo | Buteo | Accipitridae | Buteoninae | Buzzard | Common buzzard | 18365 | | KM364882 | Buteo buteo burmanicus | Buteo | Accipitridae | Buteoninae | Buzzard | Himalayan buzzard | 18231 | | KP337337 | Buteo lagopus | Buteo | Accipitridae | Buteoninae | Buzzard | Rough-legged buzzard | 18559 | | KT935541 | Buteo hemilasius | Buteo | Accipitridae | Buteoninae | Buzzard | Upland buzzard | 18079 | | MN356325 | Pandion haliaetus | Pandion | Pandionidae | None | Osprey | Osprey | 18153 | | DQ780884 | Pandion haliaetus | Pandion | Pandionidae | None | Osprey | Osprey | 17864 | | KF961184 | Sagittarius serpentarius | Sagittarius | Sagittariidae | None | None | Secretary bird | 16773 | | MN720441 | Cathartes burrovianus | Cathartes | Cathartidae | None | Vulture | Lesser yellow-headed vulture | 19285 | | PQ153910 | Cathartes melambrotus | Cathartes | Cathartidae | None | Vulture | Greater yellow-headed vulture | 19232 | | AY463690 | Cathartes aura | Cathartes | Cathartidae | None | Vulture | Turkey vulture | 16779 | | MN720440 | Coragyps atratus | Coragyps | Cathartidae | None | Vulture | Black vulture | 19329 | | MN720442 | Sarcoramphus papa | Sarcoramphus | Cathartidae | None | Vulture | King vulture | 19302 | | MN720444 | Vultur gryphus | Vultur | Cathartidae | None | Vulture | Andean condor | 19287 | | MZ223429 | Vultur gryphus | Vultur | Cathartidae | None | Vulture | Andean condor | 16808 | Appendix Table 3. Sequencing statistics of the Philippine Eagle mitogenome samples. | Eagle Name | Raw Reads | Filtered Reads | Passed Reads | Bases After Filtering | Q20 Bases After Filtering | GC Content After Filtering | | Ka Brianne | 1.869938 M | 1.839352 M | 98.36% | 426.287816 M | 89.07% | 50.72% | | Freedom | 2.289488 M | 2.265048 M | 98.93% | 507.958749 M | 91.81% | 48.76% | | Sultan | 2.574558 M | 2.535176 M | 98.47% | 527.510327 M | 89.96% | 49.88% | | Kalinawan | 2.708676 M | 2.672330 M | 98.66% | 581.132396 M | 91.96% | 48.98% | | Mayumi | 2.551238 M | 2.508014 M | 98.31% | 514.236340 M | 89.16% | 50.40% | | Matatag | 3.282660 M | 3.255682 M | 99.18% | 634.566684 M | 89.86% | 55.39% | | Jag | 2.815362 M | 2.774546 M | 98.55% | 581.030785 M | 91.08% | 49.92% | | Marikit | 2.706506 M | 2.645570 M | 97.75% | 538.846626 M | 88.91% | 48.18% | | Fighter | 3.201758 M | 3.167828 M | 98.94% | 647.751819 M | 94.62% | 50.03% | | Magiting | 2.517528 M | 2.496374 M | 99.16% | 554.407669 M | 93.21% | 49.87% | | Maslog | 1.845406 M | 1.814644 M | 98.33% | 383.635010 M | 90.25% | 48.96% | | Caraga1 | 2.085824 M | 2.056328 M | 98.59% | 451.506234 M | 89.44% | 51.65% | | Caraga2 | 2.175704 M | 2.151934 M | 98.91% | 466.147105 M | 91.62% | 49.85% | | Hiyas | 2.042160 M | 1.997392 M | 97.81% | 418.676984 M | 89.26% | 48.21% | | Bighani | 2.664586 M | 2.632840 M | 98.81% | 491.507531 M | 93.29% | 50.15% | | Pagkakaisa | 1.953496 M | 1.934866 M | 99.05% | 400.285072 M | 91.00% | 54.55% | | Aling Naty | 2.151748 M | 2.100450 M | 97.62% | 434.826050 M | 89.73% | 48.74% | | Pag-asa | 2.834220 M | 2.797996 M | 98.72% | 585.385909 M | 89.04% | 53.13% | | Mabuhay | 1.835300 M | 1.776312 M | 96.79% | 380.031061 M | 85.51% | 49.37% | | PrincessMaasim | 2.273104 M | 2.244790 M | 98.75% | 490.269835 M | 89.73% | 52.87% | | Pangarap | 2.386824 M | 2.346094 M | 98.29% | 496.092442 M | 90.23% | 49.61% | | Sinag | 2.596326 M | 2.582046 M | 99.45% | 549.087874 M | 90.48% | 56.10% | | Wao | 1.892388 M | 1.850604 M | 97.79% | 419.999394 M | 88.16% | 52.50% | | Zeus | 2.301744 M | 2.272528 M | 98.73% | 513.909606 M | 91.42% | 49.28% | | Dakila | 1.497998 M | 1.450866 M | 96.85% | 330.238376 M | 87.60% | 50.04% | | San Fernando | 1.781092 M | 1.755358 M | 98.56% | 395.506807 M | 89.08% | 52.31% | | Pinpin | 1.722430 M | 1.670388 M | 96.98% | 387.540925 M | 87.89% | 49.81% | Appendix Table 4. Assembly statistics of the Philippine Eagle mitogenome samples using Spilornis cheela reference mitogenome as a seed sequence. | Eagle Name | Total Sequence Length | # of N’s (Gaps) | Total Nucleotide Bases | # of A’s | # of T’s | # of G’s | # of C’s | %GC | % Genome Coverage | Average Consensus Quality | Average Read Depth | | Ka Brianne | 20679 | 4865 | 15814 | 4539 | 3610 | 2633 | 5032 | 48.47% | 76.47 | 58 | 5253.58 | | Freedom | 18339 | 5677 | 12662 | 3750 | 2832 | 1881 | 4199 | 48.02% | 69.04 | 53 | 251.42 | | Sultan | 19152 | 3810 | 15342 | 4628 | 3466 | 2334 | 4914 | 47.24% | 80.11 | 52 | 3599.76 | | Kalinawan | 21089 | 1462 | 19627 | 5858 | 4603 | 3028 | 6138 | 46.70% | 93.07 | 59 | 7941.44 | | Mayumi | 20312 | 3752 | 16560 | 4584 | 4088 | 2491 | 5397 | 47.63% | 81.53 | 52 | 4346.93 | | Matatag | 18058 | 8037 | 10021 | 2932 | 2283 | 1558 | 3248 | 47.96% | 55.49 | 38 | 1166.97 | | Jag | 19032 | 2378 | 16654 | 4883 | 3783 | 2422 | 5566 | 47.96% | 87.51 | 58 | 5587.82 | | Marikit | 18238 | 4983 | 13255 | 3864 | 3113 | 2063 | 4215 | 47.36% | 72.68 | 55 | 2335.95 | | Fighter | 18093 | 4945 | 13148 | 3812 | 3055 | 2010 | 4271 | 47.77% | 72.67 | 53 | 4063.57 | | Magiting | 18794 | 5090 | 13704 | 4025 | 3116 | 2007 | 4556 | 47.89% | 72.92 | 47 | 3080.99 | | Maslog | 16171 | 9182 | 6989 | 2005 | 1663 | 1077 | 2244 | 47.52% | 43.22 | 29 | 128.12 | | Caraga1 | 19567 | 4421 | 15146 | 4318 | 3645 | 2440 | 4743 | 47.43% | 77.41 | 53 | 2706.37 | | Caraga2 | 19191 | 7574 | 11617 | 3328 | 2765 | 2101 | 3423 | 47.55% | 60.53 | 45 | 683.23 | | Hiyas | 18293 | 3031 | 15262 | 4436 | 3601 | 2286 | 4939 | 47.34% | 83.43 | 64 | 11.29 | | Bighani | 16972 | 4068 | 12904 | 3786 | 3028 | 2114 | 3976 | 47.19% | 76.03 | 52 | 1857.62 | | Pagkakaisa | 18720 | 7645 | 11075 | 3192 | 2532 | 1666 | 3685 | 48.32% | 59.16 | 44 | 1532.64 | | Aling Naty | 13930 | 6016 | 7914 | 2320 | 1871 | 1226 | 2497 | 47.04% | 56.81 | 35 | 180.77 | | Pag-asa | 16148 | 3805 | 12343 | 3593 | 2890 | 1932 | 3928 | 47.48% | 76.44 | 46 | 3965.11 | | Mabuhay | 17868 | 8566 | 9302 | 2692 | 2230 | 1433 | 2947 | 47.09% | 52.06 | 32 | 8222.71 | | PrincessMaasim | 18447 | 8345 | 10102 | 2991 | 2325 | 1660 | 3126 | 47.38% | 54.76 | 35 | 5071.02 | | Pangarap | 17828 | 5676 | 12152 | 3601 | 2789 | 1870 | 3892 | 47.42% | 68.16 | 45 | 2816.90 | | Sinag | 18248 | 7187 | 11061 | 3241 | 2489 | 1715 | 3616 | 48.20% | 60.61 | 48 | 573.03 | | Wao | 17690 | 7411 | 10279 | 2951 | 2423 | 1470 | 3435 | 47.72% | 58.11 | 39 | 5.24 | | Zeus | 18556 | 7463 | 11093 | 3131 | 2554 | 2044 | 3364 | 48.75% | 59.78 | 39 | 59.90 | | Dakila | 18823 | 5294 | 13529 | 3982 | 3058 | 2044 | 4445 | 47.96% | 71.87 | 51 | 86.24 | | San Fernando | 18789 | 6995 | 11794 | 3473 | 2636 | 1761 | 3924 | 48.20% | 62.77 | 36 | 6906.55 | | Pinpin | 16811 | 7322 | 9489 | 2794 | 2195 | 1467 | 3033 | 47.42% | 56.45 | 35 | 4.78 | Appendix Table 5. Top blastn search hits for the original Philippine Eagle partial mitogenome sequences with Spilornis cheela reference mitogenome as seed sequence. | Eagle Name | BLAST Most Significant Hit Description | Query Cover | E-value | % Identity | Accession ID | | Ka Brianne | Spilornis cheela mitochondrion, complete genome | 72% | 0 | 84.81% | NC_015887.1 | | Freedom | Gyps fulvus mitochondrion, complete genome | 67% | 0 | 85.36% | NC_036050.1 | | Sultan | Spilornis cheela mitochondrion, complete genome | 75% | 0 | 85.84% | NC_015887.1 | | Kalinawan | Aegypius monachus mitochondrion, complete genome | 84% | 0 | 86.41% | KF682364.1 | | Mayumi | Spilornis cheela mitochondrion, complete genome | 74% | 0 | 89.05% | NC_015887.1 | | Matatag | Spilornis cheela mitochondrion, complete genome | 54% | 0 | 88.99% | NC_015887.1 | | Jag | Gyps coprotheres mitochondrion, complete genome | 85% | 0 | 88.86% | MF683387.1 | | Marikit | Spilornis cheela mitochondrion, complete genome | 69% | 0 | 84.66% | NC_015887.1 | | Fighter | Gyps fulvus mitochondrion, complete genome | 71% | 0 | 89.65% | NC_036050.1 | | Magiting | Gyps coprotheres mitochondrion, complete genome | 71% | 0 | 88.28% | MF683387.1 | | Maslog | Gyps himalayensis mitochondrion, complete genome | 41% | 0 | 89.11% | KY594709.1 | | Caraga1 | Spilornis cheela mitochondrion, complete genome | 75% | 0 | 89.51% | NC_015887.1 | | Caraga2 | Gyps himalayensis mitochondrion, complete genome | 57% | 0 | 88.18% | KY594709.1 | | Hiyas | Gyps himalayensis mitochondrion, complete genome | 83% | 0 | 87.36% | KY594709.1 | | Bighani | Gyps himalayensis mitochondrion, complete genome | 73% | 0 | 88.53% | KY594709.1 | | Pagkakaisa | Gyps himalayensis mitochondrion, complete genome | 58% | 0 | 89.43% | KY594709.1 | | Aling Naty | Aegypius monachus mitochondrion, complete genome | 55% | 0 | 90.44% | KF682364.1 | | Pag-asa | Gyps coprotheres mitochondrion, complete genome | 73% | 0 | 87.76% | MF683387.1 | | Mabuhay | Circaetus pectoralis mitochondrion, complete genome | 49% | 0 | 86.31% | NC_052805.1 | | PrincessMaasim | Spilornis cheela mitochondrion, complete genome | 51% | 0 | 88.90% | NC_015887.1 | | Pangarap | Aegypius monachus mitochondrion, complete genome | 67% | 0 | 87.69% | KF682364.1 | | Sinag | Gyps himalayensis mitochondrion, complete genome | 58% | 0 | 89.90% | KY594709.1 | | Wao | Circaetus pectoralis mitochondrion, complete genome | 57% | 0 | 90.17% | NC_052805.1 | | Zeus | Spilornis cheela mitochondrion, complete genome | 48% | 0 | 91.52% | NC_015887.1 | | Dakila | Spilornis cheela mitochondrion, complete genome | 63% | 0 | 87.64% | NC_015887.1 | | San Fernando | Circaetus pectoralis mitochondrion, complete genome | 62% | 0 | 87.59% | NC_052805.1 | | Pinpin | Aegypius monachus mitochondrion, complete genome | 52% | 0 | 91.28% | KF682364.1 | Appendix Table 6. Top blastn search hits for the new Philippine Eagle partial mitogenome sequences with Kalinawan mitogenome assembly as seed sequence. | Eagle Name | BLAST Most Significant Hit Description | Query Cover | E-value | % Identity | Accession ID | | Ka Brianne | Gyps himalayensis mitochondrion, complete genome | 82% | 0 | 88.49% | KY594709.1 | | Freedom | Aegypius monachus mitochondrion, complete genome | 83% | 0 | 90.51% | KF682364.1 | | Sultan | Aegypius monachus mitochondrion, complete genome | 93% | 0 | 88.59% | KF682364.1 | | Kalinawan | Aegypius monachus mitochondrion, complete genome | 91% | 0 | 86.55% | KF682364.1 | | Mayumi | Aegypius monachus mitochondrion, complete genome | 93% | 0 | 84.20% | KF682364.1 | | Matatag | Aegypius monachus mitochondrion, complete genome | 77% | 0 | 90.40% | KF682364.1 | | Jag | Gyps himalayensis mitochondrion, complete genome | 91% | 0 | 89.89% | KY594709.1 | | Marikit | Aegypius monachus mitochondrion, complete genome | 78% | 0 | 87.25% | KF682364.1 | | Fighter | Gyps himalayensis mitochondrion, complete genome | 86% | 0 | 89.02% | KY594709.1 | | Magiting | Circaetus pectoralis mitochondrion, complete genome | 88% | 0 | 87.44% | NC_052805.1 | | Maslog | Circaetus pectoralis mitochondrion, complete genome | 66% | 0 | 86.17% | NC_052805.1 | | Caraga1 | Aegypius monachus mitochondrion, complete genome | 80% | 0 | 87.77% | KF682364.1 | | Caraga2 | Aegypius monachus mitochondrion, complete genome | 76% | 0 | 89.78% | KF682364.1 | | Hiyas | Circaetus pectoralis mitochondrion, complete genome | 82% | 0 | 87.15% | NC_052805.1 | | Bighani | Gyps himalayensis mitochondrion, complete genome | 80% | 0 | 90.12% | KY594709.1 | | Pagkakaisa | Gyps himalayensis mitochondrion, complete genome | 84% | 0 | 90.03% | KY594709.1 | | Aling Naty | Gyps himalayensis mitochondrion, complete genome | 68% | 0 | 88.30% | KY594709.1 | | Pag-asa | Gyps himalayensis mitochondrion, complete genome | 92% | 0 | 85.42% | KY594709.1 | | Mabuhay | Circaetus pectoralis mitochondrion, complete genome | 72% | 0 | 85.59% | NC_052805.1 | | PrincessMaasim | Aegypius monachus mitochondrion, complete genome | 81% | 0 | 86.19% | KF682364.1 | | Pangarap | Aegypius monachus mitochondrion, complete genome | 81% | 0 | 87.84% | KF682364.1 | | Sinag | Gyps himalayensis mitochondrion, complete genome | 81% | 0 | 90.12% | KY594709.1 | | Wao | Gyps coprotheres mitochondrion, complete genome | 46% | 0 | 90.70% | MF683387.1 | | Zeus | Spilornis cheela mitochondrion, complete genome | 48% | 0 | 91.52% | NC_015887.1 | | Dakila | Spilornis cheela mitochondrion, complete genome | 64% | 0 | 89.24% | NC_015887.1 | | San Fernando | Circaetus pectoralis mitochondrion, complete genome | 87% | 0 | 86.92% | NC_052805.1 | | Pinpin | Gyps fulvus mitochondrion, complete genome | 53% | 0 | 88.08% | NC_036050.1 | Appendix Table 7. List of MITOS-annotated genes for the rest of the Philippine Eagle mitogenome assemblies. | Sample ID | # of rRNA Genes | # of tRNA Genes | # of Protein- Coding Genes | rRNA Genes | tRNA Genes | Protein-Coding Genes | | Ka Brianne | 2 | 8 | 10 | rrnL, rrnS | trnD, trnI, trnK, trnL2, trnM, trnQ, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad3, nad4, nad5 | | Freedom | 2 | 12 | 12 | rrnL, rrnS | trnD, trnG, trnH, trnI, trnK, trnL1, trnL2, trnM, trnQ, trnS1, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4, nad4l, nad5 | | Sultan | 2 | 11 | 10 | rrnL, rrnS | trnD, trnF, trnH, trnI, trnK, trnL2, trnM, trnQ, trnS1, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad4, nad5 | | Kalinawan | 2 | 14 | 11 | rrnL, rrnS | trnD, trnF, trnG, trnH, trnI, trnK, trnL1, trnL2, trnM, trnN, trnQ, trnS1, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4l, nad5 | | Mayumi | 2 | 11 | 9 | rrnL, rrnS | trnD, trnF, trnI, trnK, trnL2, trnM, trnN, trnP, trnQ, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad5 | | Matatag | 2 | 8 | 9 | rrnL, rrnS | trnA, trnD, trnI, trnK, trnL2, trnM, trnQ, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad5 | | Jag | 2 | 10 | 11 | rrnL, rrnS | trnD, trnG, trnI, trnK, trnL2, trnM, trnQ, trnS2, trnV, trnW | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4, nad5 | | Marikit | 2 | 11 | 12 | rrnL, rrnS | trnD, trnG, trnH, trnI, trnK, trnL1, trnL2, trnM, trnQ, trnS1, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4, nad4l, nad5 | | Fighter | 2 | 7 | 11 | rrnL, rrnS | trnD, trnF, trnI, trnK, trnM, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4l, nad5 | | Magiting | 2 | 10 | 11 | rrnL, rrnS | trnD, trnF, trnG, trnI, trnK, trnL2, trnM, trnQ, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4l, nad5 | | Maslog | 1 | 7 | 9 | rrnL | trnD, trnI, trnK, trnL2, trnM, trnQ, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad4, nad5 | | Caraga1 | 2 | 11 | 9 | rrnL, rrnS | trnD, trnG, trnI, trnK, trnL2, trnM, trnN, trnQ, trnS2, trnV, trnW | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad5 | | Caraga2 | 2 | 8 | 9 | rrnL, rrnS | trnD, trnF, trnI, trnK, trnL2, trnS1, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad5 | | Hiyas | 2 | 12 | 12 | rrnL, rrnS | trnD, trnG, trnH, trnI, trnK, trnL1, trnL2, trnM, trnQ, trnS1, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4, nad4l, nad5 | | Bighani | 2 | 14 | 10 | rrnL, rrnS | trnD, trnF, trnG, trnH, trnI, trnK, trnL1, trnL2, trnM, trnQ, trnS1, trnS2, trnV, trnW | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4 | | Pagkakaisa | 2 | 10 | 11 | rrnL, rrnS | trnD, trnH, trnI, trnK, trnL1, trnL2, trnM, trnQ, trnS1, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad4, nad4l, nad5 | | Aling Naty | 2 | 7 | 9 | rrnL, rrnS | trnD, trnI, trnK, trnL2, trnM, trnQ, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad5 | | Pag-asa | 2 | 10 | 9 | rrnL, rrnS | trnD, trnF, trnG, trnI, trnK, trnL2, trnM, trnQ, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad5 | | Mabuhay | 1 | 8 | 12 | rrnL | trnD, trnF, trnG, trnI, trnK, trnL2, trnM, trnQ | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4, nad4l, nad5 | | PrincessMaasim | 2 | 8 | 9 | rrnL, rrnS | trnD, trnI, trnK, trnL2, trnM, trnQ, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad4 | | Pangarap | 2 | 12 | 9 | rrnL, rrnS | trnD, trnF, trnG, trnH, trnI, trnK, trnL2, trnM, trnQ, trnS1, trnV, trnY | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad5 | | Sinag | 2 | 13 | 10 | rrnL, rrnS | trnA, trnC, trnD, trnI, trnK, trnL2, trnM, trnN, trnQ, trnS2, trnV, trnW, trnY | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad4, nad5 | | Wao | 1 | 10 | 10 | rrnL | trnD, trnG, trnH, trnK, trnL1, trnP, trnR, trnS1, trnS2, trnY | atp6, atp8, cob, cox1, cox2, cox3, nad3, nad4, nad4l, nad5 | | Zeus | 2 | 7 | 10 | rrnL, rrnS | trnD, trnG, trnK, trnL2, trnR, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad3, nad4, nad4l, nad5 | | Dakila | 2 | 10 | 12 | rrnL, rrnS | trnF, trnG, trnH, trnL1, trnL2, trnM, trnQ, trnR, trnS1, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4, nad4l, nad5 | | San Fernando | 2 | 11 | 11 | rrnL, rrnS | trnD, trnF, trnG, trnH, trnK, trnL1, trnL2, trnR, trnS1, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad3, nad4, nad4l, nad5 | | Pinpin | 2 | 10 | 12 | rrnL, rrnS | trnG, trnI, trnK, trnL1, trnM, trnP, trnQ, trnS1, trnS2, trnV | atp6, atp8, cob, cox1, cox2, cox3, nad1, nad2, nad3, nad4, nad4l, nad5 | Information & Authors Information Version history Copyright This work is licensed under a Non Exclusive No Reuse License. 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Authors Metrics & Citations Metrics Article Usage 2030views 362downloads Citations Download citation Michael Bacus, Paul Lorenzo Gaite, Joan Acaso, et al. Genetic Analysis of Philippine Eagles Pithecophaga jefferyi Ogilvie-Grant 1896 Using Mitochondrial Genomes. Authorea. 01 March 2025. DOI: https://doi.org/10.22541/au.174084679.92809339/v1 DOI: https://doi.org/10.22541/au.174084679.92809339/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu. Cited by - Gaps and biases in vertebrate wildlife genetics from a global biodiversity hotspot, Environmental Conservation, 52, 3, (127-138), (2025).https://doi.org/10.1017/S0376892925000141 Loading...