Complete mitogenome of endemic plum-headed parakeet Psittacula cyanocephala - characterization and phylogenetic analysis.

Psittacula cyanocephala is an endemic parakeet from the Indian sub-continent that is widespread in the illegal bird trade. Previous studies on Psittacula parakeets have highlighted taxonomic ambiguities, warranting studies to resolve the issues. Since the mitochondrial genome provides useful information concerning the species evolution and phylogenetics, we sequenced the complete mitogenome of P. cyanocephala using NGS, validated 38.86% of the mitogenome using Sanger Sequencing and compared it with other available whole mitogenomes of Psittacula. The complete mitogenome of the species was 16814 bp in length with 54.08% AT composition. P. cyanocephala mitogenome comprises of 13 protein-coding genes, 2 rRNAs and 22 tRNAs. P. cyanocephala mitogenome organization was consistent with other Psittacula mitogenomes. Comparative codon usage analysis indicated the role of natural selection on Psittacula mitogenomes. Strong purifying selection pressure was observed maximum on nad1 and nad4l genes. The mitochondrial control region of all Psittacula species displayed the ancestral avian CR gene order. Phylogenetic analyses revealed the Psittacula genus as paraphyletic nature, containing at least 4 groups of species within the same genus, suggesting its taxonomic reconsideration. Our results provide useful information for developing forensic tests to control the illegal trade of the species and scientific basis for phylogenetic revision of the genus Psittacula.

Introduction

Psittaciformes is a highly speciose order of class Aves containing 86 genera and 362 distinct species [1]. These intriguing birds are gifted with highly expanded brains [2], superior cognitive ability [3] and vocal communication skills [4]. These birds have been kept as pets since ancient times because of their beauty, charm, long life span and astonishing ability to imitate many sounds, including human speech [5]. Unfortunately, this has led to widespread increase in parrot poaching and organized illegal trade of these species the world over, making them the most threatened bird species in the world [6, 7].

Plum-headed parakeet Psittacula cyanocephala, belonging to the genus Psittacula (consisting of 16 long tailed parakeet species of which 13 are extant and 3 extinct) [8], is endemic to Indian sub-continent [9]. This parakeet belongs to one of those bird species which have been widely impacted by illegal live bird trade [10]. Though systematic population assessment of P. cyanocephala has never been conducted, it is suspected that, its population is dwindling which can be attributed to ongoing poaching for its illegal trade and habitat destruction [11]. Besides, it is documented that the rapidly changing climate does contribute to the loss of endemic species [12]. Hence, the management and conservation of endemic species such as P. cyanocephala would provide an umbrella of protection for various species assemblages within its endemic range [13]. However, to adopt and devise a healthy conservation and management plan, we require complete/ more information regarding behaviour, genetic, physiological, and ecological understanding of P. cyanocephala.

P. cyanocephala bears close morphological resemblance to Psittacula roseata in terms of distinctive head plumage and genetic proximity [8, 14]. A number of studies on evolutionary, morphological, and systematic aspects of the Psittacula genus have highlighted taxonomic ambiguities such as the paraphyletic nature of certain species and cladding of the genus Tanygnathus within the genus Psittacula [8, 14–16]. Recently, Braun and coworkers reconstructed the Maximum Likelihood (ML) based phylogenetic tree of Psittacula and other closely related species using a HKY model of two genetic markers (mitochondrial cob and nuclear rag1 gene) and observed that the Asian genus Psittacula is paraphyletic [8]. To create monophyletic genera, Braun and coworkers proposed the recognition of genus Himalayapsitta Braun, 2016 for P. himalayana, P. finschii, P. roseata, and P. cyanocephala [8]. However, the suggested taxonomic revision needs more confirmation using complete mitochondrial genome data.

Mitochondrial genomes are extremely useful in phylogeny and population research of avian taxa because of their inherent properties like small genome size, very less or absence of recombination frequency, maternal inheritance along with highly conserved gene content and evolutionary rate [17-19]. Also, mitochondrial genomes are comparatively more conserved than nuclear genomes during transition events in the evolutionary context, especially in birds [20]. Hence, such unique architecture, organization as well as evolutionary behavior render mitochondrial genomes the ability to carry phylogenetic information more consistently in comparison to nuclear markers [20]. Birds, however, are particularly noteworthy because their mitochondrial genomes are characterized by a gene order different from that in the majority of vertebrate mitogenomes due to rearrangement near the control region [21]. Although, the mitochondrial genome evolves about 10 times faster than the single-copy fraction of the nuclear genome [22], mutations in mitochondrial DNA are largely point mutations with only a few insertions or deletions. Furthermore, it has been reported that complete mitogenomes retain more information than a single gene regarding the evolutionary history of a taxon and provide consistent results compared to nuclear genes [20, 23]. This reduces the effect of homoplasy and frequent stochastic errors in phylogenetic studies [23]. Considering the usefulness of complete mitogenome in phylogenetic and evolutionary studies, we attempted to decode the complete mitogenome of P. cyanocephala using Next Generation Sequencing (NGS). Furthermore, we validated NGS data using Sanger sequencing, which is considered as a gold standard for DNA sequencing, for select protein-coding genes to rule out any possible sequencing error.

We successfully decoded the complete mitochondrial genome sequence of P. cyanocephala for the first time. The newly sequenced mitogenome was validated and compared with other available mitogenomes of related genera to 1) know structural and genomic features of P. cyanocephala mitogenome and its relatedness with other available Psittacula mitogenomes, 2) identify codon usage and selection pressure on the protein-coding genes (PCGs) using bioinformatics and evolutionary analysis across the numerous parrot genera, and 3) build and elucidate comprehensive phylogeny relationships using all the available mitogenomes including that of P. cyanocephala.

Materials and methods

Sample collection and DNA extraction

Sample of Psittacula cyanocephala blood (~50 μl) was obtained from the Veterinary Transit Treatment Centre (21˚10’10”N, 79˚03’30”E), Nagpur, Maharashtra with due permission from Forest Department of Maharashtra [Desk-22(8)/Research/CR-8(19–20)/769/2019-2020] and used for this study. The blood sample was stored in Queen’s lysis buffer [24] and transported under suitable conditions to National Avian Forensic Laboratory (NAFL) at SACON, Coimbatore, Tamil Nadu. About 40μl of blood was digested in lysis buffer (10 mMTris, 10 mM EDTA, 10% SDS and 40μg Proteinase K) and subsequently used for DNA extraction using the Phenol-Chloroform-Isoamyl Alcohol method with minor modifications [25]. The extracted DNA was quantified using DeNovix Spectrophotometer (DeNovix Inc., Delaware, USA), Qubit-4 Fluorometer (ThermoFisher Scientific, USA) and subsequently stored at -80°C till used. The specimen DNA was deposited in the Avian Biobank at NAFL under the accession code NAFL/0305/DNA/180220.

Library preparation

For library preparation, 1.1 micrograms of extracted DNA was utilized as starting material for TruSeq DNA PCR-Free library preparation kit (Illumina Inc., USA). The DNA was fragmented using focused ultrasonicator (Covaris M220, USA) to the desired length of 350 base pairs as per the protocol recommended by the manufacturer. The size of the fragmented DNA population was checked using Fragment Analyzer (Agilent, USA) and made sure the majority of fragment sizes were in the desired range. Following TruSeq DNA PCR-Free library preparation kit protocol, clean-up of the fragmented DNA was performed using magnetic beads provided in the kit. The process of fragmentation creates overhangs at 3’ and 5’ ends of the input DNA. These ends were converted into blunt ends using the kit protocol. After the end repair, the appropriate library size was selected using different ratios of sample purification beads provided in the kit. The 3’ end of the blunt fragments was adenylated with a single “A” nucleotide to prevent them from ligating to each other. Adapter ligation was then carried out following the kit protocol. After completion of library preparation, the mean peak size of the library prepared was checked using Fragment Analyzer. Quantification of the prepared library was carried out using QIAseq Library Quant Assay Kit (Qiagen N.V., Germany). The library was sequenced using NextSeq550 (Illumina Inc., USA) and at the end of the sequencing run, high-quality paired-end reads were obtained.

Mitogenome assemblage

FastQC [http://www.bioinformatics.babraham.ac.uk/projects/fastqc/] was used to check the quality of the sequence data. At first, the de-novo assembly of the genome was attempted using SPAdes [26]. However, due to low coverage (~ 4.7X) of the whole genome of P. cyanocephala, successful retrieval of complete de-novo mitogenome sequence wasn’t possible. Hence the reads were corrected using SPAdes and then mapped directly onto the reference genome (Psittacula roseata (NC045379.1)) using Bowtie2 [27]. A very high coverage (~ 90X) of the mitogenome was obtained using this approach. The final alignment was visualized using IGV software [28].

PCR amplification and sequencing of the protein coding genes using Sanger sequencing

Select protein-coding genes (cox1, cox2, atp8, atp6, nad1, nad2, nd3 and cob) of P. cyanocephala mitogenome were amplified to verify the mitogenome generated using NGS data. The genes were amplified using published primers (S1 and S2 Tables) designed by our lab [29]. Desired amplicons were amplified using thermocycler as per the S1 and S2 Tables. The PCR amplified amplicons were gel purified, and cycle sequenced with Big Dye Terminator ver. 3.1 (Applied Biosystems, Foster City, CA) using Applied Biosystems Genetic Analyzer 3500 (Applied Biosystems, Foster City, CA). Difficulty was faced during cycle sequencing of certain templates due to possible secondary structure formation in respective PCR amplicons. Various PCR adjuvants such as betaine and formamide in suitable concentrations and volumes were used to sequence the templates successfully.

Gene annotation

The complete mitogenome of P. cyanocephala was annotated manually. Using MitosWeb-server all the PCGs, rRNAs and tRNAs were predicted and used as a template for annotation of the newly assembled mitogenome [30, 31]. The tRNA positions and secondary structures were predicted using tRNAscan-SE2.0 [32], verified with the MITOSWeb-server results and carefully annotated on the newly sequenced P. cyanocephala mitogenome. The rRNA genes were initially predicted by MitosWeb-server and the boundaries were confirmed by aligning the P. cyanocephala mitogenome with other Psittacula mitogenomes [P. alexandri (NC045378.1) [33], P. derbiana(NC042409.1) [34], P. eupatria(NC042765.1) [34], P. krameri(MN065674.1) [35] and P. roseata (NC045379.1)] from GenBank (Table 1). Protein coding regions (open reading frames (ORF)) were identified in the sequenced P. cyanocephala mitogenome by using NCBI ORF FINDER [36]. The identified regions were translated using ExPASy-Translate Tool [37] with settings for the vertebrate mitochondrial genetic code. ExPASy-Translate Tool was used to check each ORF region for a protein-coding gene (PCG) with correct start and stop codons The formula “AT-skew = (A-T)/(A+T)” and “GC-skew = (G-C)/(G+C)” was used to calculate nucleotide composition skew [38]. A circular genome map was generated with the help of the CGView Server and edited manually [39].

Table 1

List of the 44 Psittaciformes species used for comparative analysis in this study with their GenBank accession numbers.

Family	Genus	Species	GenBank No.
Cacatuidae	Cacatua	Cacatua moluccensis	MH133972.1
Cacatuidae	Cacatua	Cacatua pastinator	NC040142.1
Cacatuidae	Calyptorhynchus	Calyptorhynchus baudinii	MH133969.1
Cacatuidae	Calyptorhynchus	Calyptorhynchus lathami	JF414241.1
Cacatuidae	Calyptorhynchus	Calyptorhynchus latirostris	JF414243.1
Cacatuidae	Eolophus	Eolophus roseicapilla	NC040154.1
Cacatuidae	Probosciger	Probosciger aterrimus	MH133970.1
Nestoridae	Nestor	Nestor notabilis	KM611472.1
Psittacidae	Aratinga	Aratinga acuticaudata	JQ782214.1
Psittacidae	Amazona	Amazona aestiva	KT361659.1
Psittacidae	Amazona	Amazona barbadensis	JX524615.1
Psittacidae	Amazona	Amazona ochrocephala	KM611467.1
Psittacidae	Ara	Ara militaris	KM611466.1
Psittacidae	Ara	Ara severus	KF946546.1
Psittacidae	Aratinga	Aratinga pertinax	HM640208.1
Psittacidae	Brotogeris	Brotogeris cyanoptera	HM627323.1
Psittacidae	Forpus	Forpus modestus	HM755882.1
Psittacidae	Forpus	Forpus passerinus	KM611470.1
Psittacidae	Guaruba	Guaruba guarouba	NC026031.1
Psittacidae	Poicephalus	Poicephalus gulielmi	MF977813.1
Psittacidae	Primolius	Primolius couloni	KF836419.1
Psittacidae	Primolius	Primolius maracana	KJ562357.1
Psittacidae	Psittacus	Psittacus erithacus	KM611474.1
Psittacidae	Pyrrhura	Pyrrhura rupicola	KF751801.1
Psittacidae	Rhynchopsitta	Rhynchopsitta terrisi	KF010318.1
Psittaculidae	Agapornis	Agapornis lilianae	NC045369.1
Psittaculidae	Agapornis	Agapornis nigrigenis	NC045367.1
Psittaculidae	Agapornis	Agapornis pullarius	NC045368.1
Psittaculidae	Agapornis	Agapornis roseicollis	EU410486.1
Psittaculidae	Eclectus	Eclectus roratus	KM611469.1
Psittaculidae	Lorius	Lorius chlorocercus	MN515396.1
Psittaculidae	Melopsittacus	Melopsittacus undulatus	EF450826.1
Psittaculidae	Prioniturus	Prioniturus luconensis	KM611473.1
Psittaculidae	Psephotellus	Psephotellus pulcherrimus	KU158195.1
Psittaculidae	Psittacula	Psittacula alexandri	NC045378.1
Psittaculidae	Psittacula	Psittacula derbiana	NC042409.1
Psittaculidae	Psittacula	Psittacula eupatria	NC042765.1
Psittaculidae	Psittacula	Psittacula krameri	MN065674.1
Psittaculidae	Psittacula	Psittacula roseata	NC045379.1
Psittaculidae	Tanygnathus	Tanygnathus lucionensis	KM611480.1
Psittaculidae	Trichoglossus	Trichoglossus rubritorquis	MN182499.1
Psittrichasiidae	Coracopsis	Coracopsis vasa	KM611468.1
Psittrichasiidae	Psittrichas	Psittrichas fulgidus	KM611475.1
Strigopidae	Strigops	Strigops habroptilus	AY309456.1

Codon usage and evolutionary analysis

Complete mitochondrial genomes of members from Agapornis, Amazona, Ara, Eupsittula, Brotogeris, Cacatua, Calyptorhynchus, Coracopsis, Eclectus, Eolophus, Forpus, Guaruba, Lorius, Melopsittacus, Nestor, Poicephalus, Primolius, Prioniturus, Probosciger, Psephotellus, Psittacula, Psittacus, Psittrichas, Pyrrhura, Rhynchopsitta, Strigops, Tanygnathus and Trichoglossus genus were downloaded from NCBI GenBank database (Table 1). These genomes were analyzed along with the newly sequenced mitogenome of P. cyanocephala.

CodonW was used for the detailed codon usage analysis [40]. This analysis includes the percentage of AT and GC, nucleotide bias at the third position of codons, frequency of optimal codons (Fop), Effective number of codons (ENc) and Relative Synonymous Codon Usage (RSCU). Overall codon and amino acid usage of the newly sequenced mitogenome was represented by roseplots. Comparative codon and amino acid usage among 45 select mitogenomes were represented by heatmaps. Roseplots and heatmaps were generated using R software [41].

Evolutionary constraints on the individual protein-coding genes in terms of selection pressure were estimated by the ratio of non-synonymous substitution to the synonymous substitution rate (dN/dS). Maximum likelihood approach was adopted for this analysis, where dN/dS<1 indicates neutral or purifying selection and dN/dS>1 indicates positive/ Darwinian selection/ mutational pressure [42]. PAL2NAL program embedded in Phylogenetic Analysis by Maximum Likelihood (PAML) package was used for this analysis. We exploited the standalone Linux version of this server [42]. The protein-coding genes of P. cyanocephala were assessed against the protein-coding genes of other investigated genomes as mentioned earlier. The codons used in mRNAs were aligned and were subjected to dN/dS analysis. The orthologous pair of gene sequences was given as input file and the dN/dS value for that gene was calculated.

Genetic divergence and phylogenetic analysis

Divergence analysis is one of the most popular ways to estimate the cumulative differences among closely related members of a species that separated geographically leading to speciation [43] (allopatric or peripatric speciation). Pairwise base substitutions per site can provide an idea about the genomic distance and evolutionary history amongst the investigated genomes. Both species-level and genus-level divergence analysis was performed. For species-level analysis, each genome was taken as a separate entity while in genus-level analysis members of the same genus were considered as one group. For genus-level analysis members of the same genus were partitioned into a distinct group in MEGA X and average distances between the groups (i.e. generas) was calculated. The species-level analysis elucidates genetic distances at an individual level whereas the genus-level approach helps us to understand the average genetic distances between the grouped taxon from a different point of view. Thus, all considered organisms were clustered into 28 different groups which corresponds to 28 genera. The divergence among these groups was calculated using the Jukes-cantor model in MEGA X software [44].

For the construction of the phylogenetic tree, all the selected sequences were concatenated to 13 PCGs. Species across 28 genera of parrots and parakeets were used for tree construction. Emphasis was given to genus Psittacula, Tanygnathus and Eclectus during phylogenetic analysis. In total, 45 mitogenomes were concatenated to their 13 PCGs and aligned using the MUSCLE alignment program. Phylogenetic tree analysis was carried out by Maximum likelihood (ML) and Bayesian inferences (BI) algorithms following two strategies. At the first instance, a best-fit nucleotide substitution model of TVM+F+G4 was identified for our data set using the Akaike information criterion (AIC) and Bayesian information criterion (BIC) in ModelFinder [45]. ML tree was constructed through IQ-TREE [46] version 1.6.12 using the TVM+F+G4 model with 10,000 bootstrap replicates. For BI analysis, GTR+I+G model was selected from BIC scores in ModelFinder by following previous studies [30]. Mr.Bayes [47] software was used to perform BI analysis following four independent chains running for 100000 generations, sub-sampling every 1000 generations and using a burn-in of 100 generations. FigTree [48] ver1.4.4 was used to edit the resulting phylogenetic trees. The convergence and mixing of Bayesian Markov chains was assessed by calculating the average standard deviation of split frequencies along with effective sample size of the trace respectively.

Results and discussion

Mitogenome organization and gene arrangement

The complete mitochondrial genome of P. cyanocephala was assembled and submitted to GenBank (Accession No. MT433093). Sanger sequencing of eight PCGs (cox1, cox2, atp8, atp6, nad1, nad2, nd3 and cob) showed 99–100% similarity with NGS data. We considered sequence similarity of more than 99% as robust enough for sequence verification in this study. A total of 6595 base pairs comprising the eight PCGs were Sanger sequenced, which makes 38.86% of the total P. cyanocephala mitogenome. The mitogenome was 16,814 base pairs long, which is in agreement with the average size of the complete mitogenomes (16827 bp, Table 1) of other Psittacula species. The mitogenome of P. cyanocephala is composed of 13 protein-coding genes (PCGs), 22 transfer RNAs (tRNA), 2 ribosomal RNA (rRNA) and a mitochondria control region (or D-loop) (Table 2) reported earlier in other birds [1, 30, 49, 50, 52]. Majority of the genes including 12 PCGs, 14 tRNA, 2 rRNAs and the D-loop were located on the heavy (H or +) strand, whereas 8 tRNAs (trn, trn, trn, trn, trn, trn, trn(AGU) and trn and 1 PCG (nad6) were located on the light (L or -) strand (Fig 1). Earlier workers have reported similar arrangement of genes in parrots [1, 49, 50] and other birds [30, 51, 52].

Table 2

Summary of Psittacula cyanocephala mitogenome.

Gene	Start	Stop	Strand	Length	Intragenic Nucleotides	Anti-Codon	Start Codon	Stop codon
tRNAPhe	1	64	+	64	0	GAA
12s rRNA	65	1040	+	976	0
tRNAVal	1041	1112	+	72	1	TAC
16s rRNA	1114	2697	+	1584	0
tRNALeu	2698	2771	+	74	5	TAA
NAD1	2777	3757	+	981	-2		ATG	TAA
tRNAIle	3756	3826	+	71	5	GAT
tRNAGln	3832	3902	_	71	0	TTG
tRNAMet	3903	3970	+	68	0	CAT
NAD2	3971	5010	+	1040	0		ATG	TA(A)
tRNATrp	5011	5081	+	71	1	TCA
tRNAAla	5083	5150	_	68	1	TGC
tRNAAsn	5152	5227	_	76	2	GTT
tRNACys	5230	5296	_	67	0	GCA
tRNATyr	5297	5366	_	70	9	GTA
COI	5376	6923	+	1548	0		GTG	AGG
tRNASer	6924	6989	_	66	4	TGA
tRNAAsp	6994	7062	+	69	2	GTC
COII	7065	7748	+	684	1		ATG	TAA
tRNALys	7750	7818	+	69	1	TTT
Atp8	7820	7987	+	168	-10		ATG	TAA
Atp6	7978	8661	+	684	-1		ATG	TAA
COIII	8661	9444	+	784	0		ATG	T(AA)
tRNAGly	9445	9513	+	69	0	TCC
NAD3	9514….9686	173	+				ATA	TA(A)
	9688….9864	177			0
tRNAArg	9865	9933	+	69	1	TCG
NAD4L	9935	10231	+	297	-7		ATG	TAA
NAD4	10225	11617	+	1393	0		ATG	T(AA)
tRNAHis	11618	11686	+	69	0	GTG
tRNASer	11687	11752	+	66	0	GCT
tRNALeu	11753	11822	+	70	0	TAG
NAD5	11823	13634	+	1812	10		ATG	TAA
CytB	13645	14784	+	1140	0		ATG	TAA
tRNAThr	14785	14853	+	69	3	TGT
tRNAPro	14857	14925	_	69	1	TGG
NAD6	14927	15445	_	519	1		ATG	TAG
tRNAGlu	15447	15497	_	51	0	TTC
D-loop	15498	16814	_	1317

Fig 1

Circular map of the Psittacula cyanocephala mitochondrial genome.

Various genes are represented with different colour blocks. Gene transcription direction is indicated by arrows. Colour codes and legends are displayed at the upper right side of the figure. Black sliding window indicated the GC content of all the regions and GC skew through green and violet colour sliding windows. The figure was drawn by CGView Online server (http://stothard.afns.ualberta.ca/cgview_server/) and edited in PaintDotnet tool.

The total base composition of P. cyanocephala mitogenome was A-5365 (31.9%), T-3728 (22.2%), G-2216 (13.2%) and C-5505 (32.7%). The A+T (54.08%) content was higher than the G+C content (45.92%, Table 3). High A+T content is typical of most vertebrate orders, including the members of Psittaciformes order and certain other birds [30, 51, 52]. The overall A-T and G-C skew were 0.1800 and -0.4259, respectively (Table 3), indicating higher A nucleotide than T nucleotide, and higher C nucleotide than G nucleotide, respectively. The A-T and G-C skew values also indicated that Psittacula species are having higher A and C content than T and G as reported earlier in certain other birds [30, 51]. The skew values of A-T and G-C revealed in P. cyanocephala are nearly identical to what is reported in other species of Psittacula genus. The A-T and G-C skew values of P. alexandri, P. derbiana, P. eupatria, P. krameri and P. roseata were in the range of 0.1588 to 0.1836 and -0.4271 to -0.4151, respectively (Table 4).

Table 3

Nucleotide composition and skew values for Psittacula cyanocephala mitogenome.

P. cyanocephala	Size(bp)	A%	C%	G%	T%	A+T%	G+C%	AT-skew	GC-skew
mtDNA	16814	31.9	32.7	13.2	22.2	54.08	45.92	0.1800	-0.4259
PCGs	11400	31.7	34.8	11.5	22.0	53.73	46.27	0.1794	-0.5025
tRNA	1486	33.8	26.0	16.8	23.4	57.27	42.73	0.1821	-0.2157
rRNA	2560	34.3	30.6	17.8	17.3	51.56	48.44	0.3287	-0.2645
D-loop	1317	26.9	26.4	15.2	31.5	58.39	41.61	-0.0793	-0.2700

Table 4

Comparative nucleotide composition and skew values for five Psittacula species compared in this study.

	Size	A%	C%	G%	T%	A+T%	G+C%	AT-skew	GC-skew
P. roseata	16814	31.9	32.9	13.2	22.0	53.9	46.12	0.1836	-0.4271
P. eupatria	17139	31.7	33.2	13.1	22.0	53.7	46.27	0.1806	-0.4344
P. derbiana	16887	30.9	32.8	13.9	22.4	53.3	46.74	0.1594	-0.4043
P. alexandri	16883	30.9	32.8	13.9	22.4	53.3	46.77	0.1594	-0.4041
P. krameri	16413	31.0	32.9	13.6	22.5	53.5	46.49	0.1588	-0.4151

Gene arrangement analysis revealed the following pattern in P. cyanocephala: trnF>rrnS>trnV>rrnL>trnL2>nad1>trnI>trnQ>trnM>nad2>trnW>trnA>trnN>trnC>trnY>cox1>trnS2>trnD>cox2>trnK>atp8>atp6>cox3>trnG>nad3>trnR>nad4l>nad4>trnH>trnS1>trnL1>nad5>cob>trnT>trnP>nad6>trnE. The gene arrangement pattern was identical with other Psittacula members (S1 Fig).

Protein-coding genes

The total length of all the PCGs of P. cyanocephala was 11,400 base pairs constituting about 67.8% of the entire mitogenome. The occurrence and sequence of all the PCGs of P. cyanocephala mitogenome are following other avian mitochondrial genomes [30, 51, 52]. The entire length of all the PCGs translated into 3789 amino acid coding codons excluding stop codons. 11 PCGs of the P. cyanocephala mitogenome initiated with the start codon ATG, i.e. nad1, nad2, cox2, atp8, atp6, cox3, nad4l, nad4, nad5, cob, and nad6. Exceptions were cox1 and nad3 initiated with a start codon GTG and ATA, respectively. TAA was the most prevalent stop codon being punctuated in sequences of nad1, nad2, cox2, atp8, atp6, cox3, nad3, nad4l, nad4, nad5 and cob. The stop codon TAG was associated with the PCG nad6, whereas the cox1 gene had a stop codon of AGG. The TAA stop codons of nad2, cox3, nad3 and nad4 genes are partially incomplete and were completed by adding of polyadenylated tails at the 3’ ends. Overlapping of sequences was observed only in PCGs of atp8, atp6 (10 nucleotides) and nad4l, nad4 (7 nucleotides). Many of the codon features mentioned here found to be similar across various avian orders [53]. However, within the genus Psittacula, start codons remained almost the same for respective genes irrespective of the species. ATG was the most frequent start codon of the PCGs in all Psittacula species investigated in this study (P. cyanocephala, P. alexandri, P. derbiana, P. eupatria, P. krameri and P. roseata). The exception of cox1 (start codon GTG) and nad3 (start codon ATA) genes, also holds across all the Psittacula species investigated so far.

In the case of stop codons, TAA was the most prevalent stop codon followed by TAG, with the cox1 gene punctuated by AGG stop codon across all the Psittacula species studied so far. The sequence overlaps of atp8, atp6 and nad4l, nad4 genes is common amongst all the Psittacula species analyzed in this study.

Codon usage analysis revealed that either adenine or cytosine was generally at the third positions of the codons. In P. cyanocephala, A3 (0.40) dominated over C3 (0.38) (Fig 2A). This was also validated with codon usage-based roseplots (Fig 2B). For other genera, except Agapornis, adenine and cytosine were dominating at the third position of codons. Agapornis showed a C3 bias at codons’ third position. The amino acid usage-based heatmap along with roseplot of amino acid of P. cyanocephala (Figs 2C and 3B) showed Leucine, Isoleucine, Proline, Serine and Threonine were dominant than other amino acids in the mitogenome of P. cyanocephala. The effective number of codons (ENc) using plot analysis (Fig 2E), revealed that all the investigated mitogenomes were well below the curve of selection pressure. The ENc plot primarily reflects the mutational bias (Fig 2E). Plotting ENc against the GC3 thus provides an evidence of whether mutational pressure/natural selection is acting on the PCGs of an organism. An umbrella-line is drawn with the “expected ENc value” (value assuming only mutational pressure is acting on the considered genes) and is compared to the observed ENc values. Several previous reports have stated, if the observed ENc values exceeds the expected ENc values it will depict complete mutational pressure on the respective genes [54, 55]. However, if the observed value is less than the expected value it is due to the selection pressure, lowering the effective number of codons. In the Fig 2E, all the plotted points have placed below the umbrella-line indicating the selection pressure over mutational bias on those genes. This clearly indicated that all investigated mitogenomes were translationally efficient, and natural selection was playing a crucial role on these genomes. From RSCU analysis, a set of optimal codons among the studied mitogenomes was identified. These optimal codons were- GCC(A), UGC(C), GAC(D), GAA(E), UUC(F), GGA(G), CAC(H), AUC(I), AAA(K), CUA(L), CUC(L), UUA(L), AUA(M), AAC(N), CCC(P), CCA(P), CAA(Q), CGC(R), AGC(S), UCC(S), ACA(T), ACC(T), GUC(V), GUA(V),UGA(W) and UAC(Y) (Fig 2D and S3 Table). Heat-maps based on codon usage (Fig 3A) showed CUA (L), AUC (I), ACC (T), CUC (L), UUC (F) and ACA (T) to be the most used codons among the select mitogenomes. Amino acid usage heat-map also showed Leucine, Isoleucine and Threonine as the most-used amino acids (Fig 3B).

Fig 2

(A) Position-specific nucleotide usage in P. cyanocephala mitogenome. (B) Roseplot based on codon usage of P. cyanocephala mitogenome. (C) Roseplot based on amino acid usage of P. cyanocephala mitogenome. (D) RSCU analysis of P. cyanocephala mitogenome. X-axis represents the codon families with different colour patches. Cumulative codon fraction is plotted on Y-axis. (E) ENC vs GC3 plot revealed the analyzed mitogenomes are translationally efficient and natural selection was playing a crucial role on their evolution.

Fig 3

Heatmaps based on (A) codon usage and (B) amino acid usage of all the 45 species compared in this study.

Ribosomal and transfer RNA genes

Two ribosomal RNAs were packaged into the mitogenome of P. cyanocephala as in most vertebrates. The smaller 12s rRNA gene comprised of 976 base pairs with an A+T content of 50.72% and the larger 16s rRNA gene comprised of 1584 base pairs with an A+T content of 52.08% (Table 3). The rRNAs were nestled between tRNA and tRNA, with tRNA separating 12s and 16s RNA. The A+T content in 12s rRNA and 16s rRNA of other Psittacula species compared in this study were in the range of 49.8–51.13% and 51.5–52.5% respectively, similar to the nucleotide contents of the P. cyanocephala rRNAs. Birds are generally characterized by similar positioning of and high A+T content in their rRNAs, reported across many avian orders [51, 56]. As such the rRNAs of the Psittacula species compared in this study displayed similar positioning and characteristics of rRNAs typical of avian orders.

As in other avian species, 22 tRNAs were identified in the mitogenome of P. cyanocephala in this study and their secondary structures were interpreted. The length of the tRNAs varied from 64 base pairs to 74 base pairs (Table 2). The total concatenated length of all tRNAs present in the mitogenome was calculated to be 1486 base pairs. The A-T skew was calculated at 0.1821 and G-C skew at -0.2157, indicating higher A (33.8%) content than T (23.4%) and higher C (26%) content than G (16.8%) (Table 3). The secondary structures of all the tRNAs displayed a cloverleaf model; the exception was tRNA (GCU), which was missing the entire dihydrouridine arm (Fig 4). One of the key features of tRNA secondary structure is the presence of wobble base pairing. This can often substitute the Watson-crick base pairing and provide thermodynamic stability to tRNA. An extensive study on the tRNAs is crucial for the proper understanding of functional and structural features of mitogenomes. Highest wobble base pairing was found in trn followed by trn and trn. Both trn and trn had three wobble base pairings each in amino acid acceptor arm, DU stem and anticodon stem. However, it was also found trn had an extra wobble base pairing on TψC stem. trn had wobble positions on amino acid acceptor arm, DU stem and TψC stem. The study found trn, and trn (GCU) contained two wobble positions present on the amino acid acceptor arm and anticodon stem. Three tRNAs including trn, trn and trn contained no wobble positions. Rest of the tRNAs was found to have one wobble position each.

Fig 4

Putative secondary structures of the 22 tRNA genes of P. cyanocephala.

Mitochondrial control region

Structurally, the D-loop of P. cyanocephala sequenced in this study consisted of 1317 base pairs similar to other birds, and located between tRNA and tRNA. The D-loop consists of A (26.9%), C (26.4%), G (15.2%) and T (31.5%) indicating very high A+T content (Table 3). High A+T content was also noticed in the D-loop region of the other Psittacula species and in other birds [30, 51, 52].

The mitochondrial D-loop is a non-coding region mostly involved in initiation, replication, and regulation of transcription related activities in vertebrate mitogenomes [1]. The D-loop though hypervariable in sequence, is conserved in very selective fashion within or across various orders of vertebrates. As vertebrate mitochondrial genome is believed to evolve under strong selection pressure, various gene orders around the mitochondrial control region (CR) are believed to be dynamically inherited, duplicated, or degenerated during genome evolution [1]. Psittaciformes is a species-rich and taxonomically confusing taxa [1] and hence, several studies targeting the mitochondrial CR region of Psittaciformes have been undertaken to answer wider phylogenetic and taxonomic queries [50]. As such a typical (or ancestral) avian gene order varies from a typical vertebrate gene order [21]. However, previous studies have identified at least 7 re-arrangements of duplicated ancestral gene orders in some of the Psittaciformes species [1].

We report that the D-loop region of P. cyanocephala mitogenome displays the ancestral avian CR gene order. This typical ancestral gene order is also displayed by other Psittacula species (P. alexandri, P. derbiana, P. eupatria, P. krameri and P. roseata) compared in this study. It is believed that the duplicated CR region provides a selective advantage to size and energy metabolism efficiency [1]. Hence, parrots with duplicated CR regions can live long while supporting large body mass such as Amazona parrots [1]. Parakeets of Psittacula genus are small to medium-sized (~40 cm) and have a lower expected life span than that of the Amazona genus parrots. Such a life history trait can be explained by the presence of the ancestral CR gene order in Psittacula genera, assuming duplications and pseudogenization have resulted avian CR rearrangements [1, 51].

The evolutionary rate of the vertebrate mitochondrial genome is rapid when compared to the nuclear genome while having a relatively stable genome structure and recombination ratio [50]. Hence, mitochondrial genome sequences are widely used to infer phylogenetic relationships as they offer small stable changes over a long period in any given taxa. In this regard, whole mitochondrial genomes relay better phylogenetic information than single-gene (nuclear/mitochondrial) phylogeny. To elucidate phylogenetic relationships in parrots/parakeets with a focus on Psittacula genus, nucleotide sequences of 13 PCGs concatenated from the whole mitochondrial genomes of 28 genera belonging to 6 parrot families were used in this study (Table 1).

The pairwise genetic divergence calculated for each individual genome and when grouped as a genus correlated well while clustering in the phylogenetic tree. The genus-level divergence analysis showed that the Psittacula genus was placed closest to Tanygnathus (0.08 units) then to Eclectus (0.09 units) and showed the highest divergence with Agaporins, Rhynchopsitta, Primolius, Cacatua and Nestor genus (0.19 units) (S4 Table). This result corroborates the previous report that Psittacula genus clusters with Tanygnathus and is closest to the Eclectus genus as a parallel-group [8, 35]. The species-level (mitogenome based) divergence analysis elucidated that P. cyanocephala is closest to P. roseata (divergence of 0.06 units) than to any other Psittacula species (S5 Table). Divergence of P. cyanocephala with P. eupatria, P. krameri, P. alexandri and P. derbiana was calculated at 0.10, 0.12, 0.12 and 0.11 units respectively (S5 Table).

The phylogenetic tree obtained through both ML (Fig 5) and BI (S2 Fig) analysis reveals the same topologies for the Psittacula genus. Species were clustered in respective clades following their genus level separation. The genus Eclectus, Psittacula, Tanygnathus and Prioniturus have originated from a nearest common parrot ancestor. P. cyanocephala and P. roseata have branched together from a common node that runs parallel to other Psittacula and Tanygnathus species. As mentioned earlier this makes a strong case for the creation of monophyletic taxa of P. cyanocephala and P. roseata, which has been indicated by previous studies on single mitochondrial (cob)/nuclear (rag-1) markers [8, 14]. Another important fact evident from the clustering and divergence analysis is that Tanygnathus genus clusters within the Psittacula species, indicating that Tanygnathus and Psittacula species originated from a common ancestor.

Fig 5

ML tree based on the phylogenetic relationships of 45 Psittaciformes species determined using concatenated nucleotide sequences of 13 mitochondrial PCGs.

The tree was constructed in IQ-TREE employing TVM+F+G4 nucleotide substitution model, bootstrapped for 10000 replicates. P. Cyanocephala mitogenome is highlighted with red asterisk mark.

A possible explanation for the phylogenetic incongruence of Tanygnathus and Psittacula generas reported in this study might have resulted from hybridization events i.e. introgression (admixture between genetic material of two species) and/or retention of ancestral polymorphisms because of incomplete lineage sorting during speciation (ILS) [57]. The phenomenon of introgression and ILS have been immensely appreciated in avian genomic studies and highly regarded as a pervasive mechanism of adaptive evolution, especially in birds [57]. Incongruent phylogenetic trees arising as a result of introgression/hybridization incidences are a common phenomenon. Avian orders are especially intriguing with 16% of the total bird species being affected by introgression [58]. Previous reports have attributed conflicting topologies in gene tree to introgression processes in woodpeckers [59], darwin’s finches [60], flycatchers [20] and various other bird species [58]. On the other hand from a population point of view, ILS have been reported to affect the entire phylogeny of the Neoaves as well as the Palaeognathae clade, which have confounded the estimation of their respective species tree [61]. To summarize, speciation level events are notoriously hard to snapshot and hard bifurcations in gene trees difficult to distinguish against the phenomenon of introgression and/or ILS. Hence, the clustering of Tanygnathus genus within Psittacula complex may be attributed to the above mentioned population level incidences and the categorization of which is beyond the scope of our study [20, 61]. Different genomic entities (coding regions, non-coding regions, mitochondrial DNA, nuclear DNA) vary structurally, hence undergo different evolutionary constraints [61]. Phylogenetic analysis associated with varying genomic loci may produce discordance in their respective phylogenetic trees [20, 61]. If the genomic loci is under evolutionary constraint, the phylogenetic signal often gets masked with homoplasmy, multiple substitutions on the same site, and heterogeneous base composition [61]. In such cases whole mitogenomes presents itself as an excellent candidate for phylogenetic analysis. Ideally in absence of such evolutionary constraints (e.g. positive selection) mitochondrial DNA and W-linked loci (both female transmitted) are least less likely to introgress as compared to nuclear DNA loci (e.g. Z-linked loci) during hybridization [20, 61]. Previous studies have shown levels of mitochondrial DNA introgression to be nearly zero in avian hybrid zones, reiterating the fact that mitochondrial DNA are highly conserved across speciation events [20, 61]. In the most likelihood gene trees based on whole mitochondrial genome of P. cyanocephala is expected to ditto the true species phylogeny of Psittacula genus even in incidences of introgression and ILS.

From the pairwise divergence calculations, we observed that species belonging Psittacula genus are more closely related to Tanygnathus than to other Psittacula species. For instance P. cyanocephala is more closely related to T. lucionensis (0.11 units) than to P. krameri (0.12 units). Also, the phylogenetic trees obtained through ML and BI analyses display clustering of 4 separate groups within the trees. These groups include 1) P. cyanocephala, P. roseata; 2) P. alexandri, P. derbiana; 3) T. lucionensis, and 4) P. eupatria, P. krameri. These clustering pattern are supported by perfect nodal values (100%/100%) obtained in both ML and BI trees. Ambiguity in pairwise divergence scores and nestling of Tanygnathus within Psittacula genus complex makes a strong case for its taxonomic reconsideration. Previous studies of Braun [8] and Kundu [62] used morphological markers, genetic data and molecular dating approaches to present a near complete phylogeny of Psittacula genus. The unavailability of complete mitogenomes of all Psittacula and allied species, curtailed our data set and limited the scope of our phylogenetic analysis. However the phylogenetic results obtained in this study exactly mirror the incongruences presented by previous studies [8, 62]. Such genetic and evolutionary evidences weigh in support of Psittacula being is a non-monophyletic genus and warrants taxonomic reconsideration.

Evolutionary analysis

dN/dS ratios were calculated to evaluate the effect of purifying selection via mutational pressure over protein-coding genes of P. cyanocephala. dN/dS values of all protein-coding genes were found to be less than 1 indicating the presence of purifying selection pressure on those genes (S6 Table). These values varied from 0.08 (nad1, nad4l) to 0.14 (nad6, nad5 and nad4) suggesting differential selection constrains among genes. The lowest dN/dS values of nad1 and nad4l indicated the strongest purifying selection, whereas, nad6, nad5 and nad4 were under the least selection pressure. Thus, natural selection (purifying selection pressure) is acting as one of the major indices governing the evolution of Psittaciformes.

Conclusion

We provide for the first time, the high-quality complete mitogenome of P. cyanocephala, a parakeet endemic to the Indian Subcontinent, whose existence is threatened by illegal bird trade. P. cyanocephala mitogenome consists of 37 genes and the gene arrangement shows conserved patterns like other parrots. We also report that D-loop region of P. cyanocephala mitogenome displays the ancestral avian CR gene order. Codon usage analysis revealed that third positions of the codons are dominated by either adenine or cytosine. The dN/dS results indicated that nad1 and nad4l are under the strongest purifying selection whereas nad6, nad5 and nad4 are under the lower selection pressure in P. cyanocephala. Furthermore, phylogenetic results provided concrete evidence of multiple clades/groups clustering within the Psittacula genus supporting the call for a taxonomic reconsideration of the Psittacula genus. The complete mitogenome sequence of P. cyanocephala provided here will help in future phylogenetic and phylogeography studies as well as increase our understanding of the evolutionary relationships of such endemic species. Furthermore, mitogenome data will be instrumental in designing forensic tools for improving the conservation efforts and preventing the illegal trading of parakeet species.

PCR conditions for amplification of primers used for amplification of PCGs of mitogenome of P. cyanocephala.

(DOCX)

Click here for additional data file.

Sequence of primers and their predicted amplicon length used for amplification of various PCGs of mitogenome of P. cyanocephala.

(DOCX)

Click here for additional data file.

The Relative Synonymous Codon Usage (RSCU) values for each codon analysed in the 45 species of Psittaciformes order.

The optimal codons and their values are highlighted in the red font. Asterisk (*) indicates STOP codon. The amino acids are represented by their triple letter codes.

(XLSX)

Click here for additional data file.

Pairwise distance values for 28 genera of Psittaciformes, where each genus is considered as a group for divergence analysis.

The divergence of Psittacula genus with respect to other genera is highlighted in red font.

(XLSX)

Click here for additional data file.

Pairwise distance values for 45 species of Psittaciformes order, considered for divergence analysis in this study.

The divergence analysis values of Psittacula cyanocephala with respect to other species is highlighted in red font and a yellow background.

(XLSX)

Click here for additional data file.

dN/dS values of Psittaculacyanocephala with respect to other parrot species for each Protein Coding Gene (PCG) is provided in the following table.

The Asterisk(*) / Numericals (1,2 ‥ 44) in the first row denotes asterisk (*) as Psittacula cyanocephala and the numbers as 44 species of Psittaciformes order analysed in this study. The numericals denote the following species: 1 (Agapornis lilianae), 2 (Agapornis nigrigenis),3 (Agapornis pullarius), 4 (Agapornis roseicollis), 5 (Amazona aestiva), 6 (Amazona barbadensis), 7 (Amazona ochrocephala), 8 (Ara militaris), 9 (Ara severus), 10 (Aratinga pertinax), 11 (Brotogeris cyanoptera), 12 (Cacatua moluccensis), 13 (Cacatua pastinator), 14 (Calyptorhynchus baudinii), 15 (Calyptorhynchus lathami), 16 (Calyptorhynchus latirostris), 17 (Coracopsis vasa), 18 (Eclectus roratus), 19 (Eolophus roseicapilla), 20 (Forpus modestus), 21 (Forpus passerines), 22 (Guaruba guarouba), 23 (Lorius chlorocercus), 24 (Melopsittacus undulates), 25 (Nestor notabilis), 26 (Poicephalus gulielmi), 27 (Primolius couloni), 28 (Primolius maracana), 29 (Prioniturus lucionensis), 30 (Probosciger aterrimus), 31 (Psephotellus pulcherrimus), 32 (Psittacula alexandri), 33 (Psittacula derbiana), 34 (Psittacula eupatria), 35 (Psittacula krameri), 36 (Psittacula roseata), 37 (Psittacus erithacus), 38 (Psittrichas fulgidus), 39 (Pyrrhura rupicola), 40 (Rhynchopsitta terrisi), 41 (Strigops habroptilus), 42 (Tanygnathus lucionensis), 43 (Aratinga acuticaudata), 44 (Trichoglossus rubritorquis).

(XLSX)

Click here for additional data file.

Gene arrangement of all the 45 species of Psittaciformes family compared in this study.

The abbreviations are as follows: ali (Agapornis lilianae), ani (Agapornis nigrigenis),apu (Agapornis pullarius), aro (Agapornis roseicollis), aaest (Amazona aestiva), abarb (Amazona barbadensis), aochr (Amazona ochrocephala), amilitari (Ara militaris), as (Ara severus), aacu (Aratinga acuticaudata), aper (Aratinga pertinax), boc (Brotogeris cyanoptera), cmolu (Cacatua moluccensis), cpast (Cacatua pastinator), cbau (Calyptorhynchus baudinii), clath (Calyptorhynchus lathami), clatir (Calyptorhynchus latirostris), cvasa (Coracopsis vasa), eror (Eclectus roratus), eros (Eolophus roseicapilla), fomo (Forpus modestus), fopa (Forpus passerines), gugu (Guaruba guarouba), lochlo (Lorius chlorocercus), mun (Melopsittacus undulates), neno (Nestor notabilis), pogu (Poicephalus gulielmi), prico (Primolius couloni), prima (Primolius maracana), pluco (Prioniturus lucionensis),pater (Probosciger aterrimus), psepul (Psephotellus pulcherrimus), palex (Psittacula alexandri), pderb (Psittacula derbiana), peup (Psittacula eupatria), pkra (Psittacula krameri), pro (Psittacula roseata), peri (Psittacus erithacus), pful (Psittrichas fulgidus), prup (Pyrrhura rupicola), rhyter (Rhynchopsitta terrisi), strihab (Strigops habroptilus), tluci (Tanygnathus lucionensis), trub (Trichoglossus rubritorquis), pcyano (Psittacula cyanocephala).

(DOCX)

Click here for additional data file.

BI tree based on the phylogenetic relationships of 45 Psittaciformes species determined using concatenated nucleotide sequences of 13 mitochondrial PCGs.

The tree was constructed in Mr.Bayes employing GTR+I+G nucleotide substitution model following 4 independent chains running for 100,000 generations, sub-sampling every 1000 generations and using a burn-in of 100 generations. P. Cyanocephala mitogenome is highlighted with red asterisk mark.

(DOCX)

Click here for additional data file.

(RAR)

Click here for additional data file.

14 Dec 2020

PONE-D-20-31563

Complete mitogenome of endemic Plum-headed parakeet Psittacula cyanocephala – characterization and phylogenetic analysis

PLOS ONE

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Reviewer #1: The most important results obtained by the authors of the manuscript: “Complete mitogenome of endemic Plum-headed parakeet Psittacula cyanocephala – characterization and phylogenetic analysis” concern the following aspects:

1. Amplification and sequencing of the first Psittacula cyanocephala mitogenome.

2. Its comparison with other mitogenomes representative for avian order Psittaciformes. For this purpose, the authors performed a phylogenetic analysis, determined the pairwise genetic divergence and calculated dN/dS ratios for PCGs.

The impact of the obtained results on the understanding of the taxonomy of the genus Psittacula and Tanygnathus was summarized by the authors in the section conclusion:

“Furthermore, phylogenetic results provided concrete evidence of multiple phyla clustering within the Psittacula genus supporting the call for a taxonomic reconsideration of the Psittacula genus.”

My comments:

I fully agree with the authors of the manuscript that Psittacula cyanocephala mitogenome will be very useful in future phylogenetic and phylogeographic studies, which will allow to understand the evolution of Tanygnathus and Psittacula genera.

But actually …. Phylogenetic analysis presented in this manuscript did not bring anything new. The placement of Psittacula cyanocephala in the clade of roseata/cyanocephala/himlayana/finschi species is commonly known (Kundu et al., 2012; Podsiadłowski et al., 2017; Braun et al., 2019). Moreover, the same publications showed relations between Psittacula groups and Tanygnathus species, which are identical with those presented in the manuscript. Additionally, Braun et al., proposed many taxonomical changes based on obtained results.

In general, anything new from the phylogenetic and taxonomic view is presented in this manuscript. Of course, I fully understand the intention of the authors who wanted to check whether the results obtained from the complete mitochondrial genomes will be consistent with the Braun`s results obtained with the use of only two quite short sequences: mitochondrial cytb and nuclear RAG-1 genes. However, it is impossible to obtain an irrefutable conclusion with the use of one Tanygnathus and six Psittacula mitogenomes, which even do not represent all “taxonomical” clades being considered by Braun. The fact, that Psittacula genus should be taxonomical revised is indisputable but commonly known.

The answer for the question “if taxonomical revision proposed by Braun et al., 2019 is proper” should be the real scientific novelty of this manuscript.

Unfortunately, results presented in this manuscript are only the information about new Psittacula mitogenome and its analysis. These results should be published in journals dedicated to such preliminary analyses. In my opinion, their scientific novelty is not sufficient to be published in PLOS ONE Journal.

Reviewer #2: In this manuscript, the authors aim to describe the complete sequence of the mitochondrial genome of Psittacula cyanocephala. They report general and comparative statistics about the mitochondrial DNA of this species as compared to other related species. Lastly, they estimate a phylogenetic tree based on the protein coding genes and suggest a taxonomic revision of the Psittacula genus based on it. The authors need to address some issues, which are described below, before the paper is suitable for publication.

Major issue

- Phylogenetic results.

The claim that the genus needs a taxonomic revision based on their findings is weak. First, the placement of Tanygnathus together with the Psittacula species may be due to other causes that were not discussed (such as introgression and ILS) by the authors. This should be explicitly addressed (and discussed) in the text. Second, it is not clear in the text what would be the four clusters inside the genus and why they are relevant (the authors use this argument to justify the taxonomic reconsideration). It is mentioned in the abstract that “Phylogenetic analyses revealed the Psittacula genus as paraphyletic nature, containing at least 4 groups of species within the same genus, suggesting its taxonomic reconsideration”. I do not see why this is an argument for taxonomic revision. Please expand the discussion about the phylogenetic results addressing the possible causes for the recovered phylogenetic relationships and provide stronger arguments for a taxonomic revision.

Minor issues:

- English: I recommend that authors seek a scientific editing service to improve the quality of the English.

- Figures: I suggest increasing the font size of the figures.

- Lines 72-74: Braun and coworkers did not use “differences in nucleotide sequences” to reconstruct a phylogenetic tree for Psittacula. They used a ML approach based on a substitution model, which was HKY. Please correct.

- Lines 77-78: Please provide arguments that justify your claim. Why does complete mitochondrial genome data is the best option instead of large amounts of nuclear data?

- Lines 87-89: The work cited is about mammals. Please include a citation for birds, or explicitly state “…provide consistent results compared to nuclear genes for mammals” and justify why the same would be expected for birds.

- Line 148: The select protein coding sequences that were used to verify the mitogenome should me mentioned at this point.

- Lines 194-198: Please provide more details about the ML approach used to estimate dN/dS (parameters, method…).

- Line 203: “The number of base substitutions per site can provide…”. I suggest the use of the “pairwise base substitutions” terminology.

- Lines 205-206: “Both the genome-based and genus-based divergence analysis was performed”. I suggest changing “genome-based” and “genus-based” to “species-level” and “genus-level”, respectively. Additionally, it is advisable to explain why these two distinct approaches were considered.

- Line 207: “members of the same genus were considered as one group”. Explain how this was done (average?).

- Line 208: I suggest rephrasing the sentence to something similar to “Thus all considered organisms were clustered into 28 different groups, which corresponds to the 28 genera”.

- Line 212: Please explain what “emphasis” mean. State the criteria to choose the sequences/genus to keep along the phylogenetic analyses.

- Line 214: Please state if the sequences were aligned independently by gene and based on the amino acid sequence, which is desirable.

- Lines 219-220: Please state what “effective GTR+I+G” means (I am assuming this is somehow different from the regular GTR+I+G, otherwise the word “effective” would not be necessary).

- Lines 220-221: Please provide what statistics were used to check the convergence and mixing of the Bayesian chains.

- Lines 228-229: How did the authors deal with the similarity between the sequences generated by Sanger sequencing and NGS? It seems like 99% of similarity was considered enough, but it should be explicitly mentioned.

- Line 245: Please change “lower” to “upper”.

- Lines 283-285: This sentence is confusing. What does “in nature” mean?

- Lines 304-305: Please explain and discuss why Fig 2E provide evidence for selection pressure.

- Lines 321-322: Please say the meaning of the black squares in Fig 3B.

- Lines 380-381: You can only say that if you assume that the hypothesis of duplicated CRs is correct.

- Line 387: Here, by “single-gene” you mean mitochondrial gene or any gene (nuclear and mitochondrial)?

- Line 389: This sentence is confusing. How can whole mitochondrial genomes be used along with concatenated PCGs? The PCGs are part of the mitogenome.

- Line 398: I suggest rephrasing this sentence to “The mitogenome-based divergence analysis suggest that…”

- Lines 402-404: I did not understand what topology was presented before.

- Lines 408-409: It would be reasonable to mention what kind of data the cited works were based on.

- Lines 409-411: This indicates that the mitochondrial DNA of this species have common ancestry. This pattern does not necessarily imply a paraphyletic genus. It may be caused by populational level phenomena such as introgression.

- Lines 415-419: All these statements are assuming that the mitogenome is always identical to the species phylogeny, which is not true. Also, this part of the text is very confusing. I was not able to understand why there are non-monophiletic clustering os 4 groups.

- Lines 424-433: This analysis is pointless, unless the results are discussed and compared to other birds/vertebrates. Besides that, are the dN/dS values statistically significant?

- Lines 441-443: Change “least” to “lower”.

- Line 444: Change “multiple phyla” to “multiple clades/groups”.

- Line 446: Change “phylogeography” to “phylogeographic”.

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23 Jan 2021

Ms. Ref. No.: PONE-D-20-31563 - EMID:75da62b30f6ba005

Title: Complete mitogenome of endemic Plum-headed parakeet Psittacula cyanocephala – characterization and phylogenetic analysis

Response to reviewers

We would like to thank Dr. Maria Andreína Pacheco (Academic Editor) and the Reviewers for their constructive remarks, which were of great help to improve this manuscript. We have revised the manuscript as suggested by the Reviewers. The revised manuscript is submitted for further consideration. Please find below a point-by-point rebuttal to the issues raised.

Additional Editor Comments:

Comment 1: Please address the issues that both reviewers suggested.

Response: We have addresses all the issues raised by both reviewers.

Reviewer #1

Comment 1: I fully agree with the authors of the manuscript that Psittacula cyanocephala mitogenome will be very useful in future phylogenetic and phylogeographic studies, which will allow to understand the evolution of Tanygnathus and Psittacula genera.

But actually …. Phylogenetic analysis presented in this manuscript did not bring anything new. The placement of Psittacula cyanocephala in the clade of roseata/cyanocephala/himlayana/finschi species is commonly known (Kundu et al., 2012; Podsiad?owski et al., 2017; Braun et al., 2019). Moreover, the same publications showed relations between Psittacula groups and Tanygnathus species, which are identical with those presented in the manuscript. Additionally, Braun et al., proposed many taxonomical changes based on obtained results.

In general, anything new from the phylogenetic and taxonomic view is presented in this manuscript. Of course, I fully understand the intention of the authors who wanted to check whether the results obtained from the complete mitochondrial genomes will be consistent with the Braun`s results obtained with the use of only two quite short sequences: mitochondrial cytb and nuclear RAG-1 genes. However, it is impossible to obtain an irrefutable conclusion with the use of one Tanygnathus and six Psittacula mitogenomes, which even do not represent all “taxonomical” clades being considered by Braun. The fact, that Psittacula genus should be taxonomical revised is indisputable but commonly known.

The answer for the question “if taxonomical revision proposed by Braun et al., 2019 is proper” should be the real scientific novelty of this manuscript.

Unfortunately, results presented in this manuscript are only the information about new Psittacula mitogenome and its analysis. These results should be published in journals dedicated to such preliminary analyses. In my opinion, their scientific novelty is not sufficient to be published in PLOS ONE Journal.

Response: Thank you very much for your thoughtful comments and insight. We performed phylogenetic analysis using whole mitochondrial genomes of Psittacula genus to elucidate phylogenetic inconsistencies within the genus and supported call for its taxonomic reconsideration as suggested by previous studies (Braun et al., 2019; Kundu et al., 2012). We understand that incongruent clustering of different clades within Psittacula genus has been reported by previous studies using single mitochondrial/nuclear genes (Braun et al., 2019; Kundu et al., 2012), hence we aimed at using complete mitogenomes to verify these claims as you pointed out correctly. And through this study we have successfully verified such claims and presented a more comprehensive phylogenetic analysis using complete mitogenomes, than the previous studies.

However, we understand that in absence of complete mitogenomes of all “taxonomical” members of Psittacula genus, recovering an exact and irrefutable phylogenetic tree is impossible. However, we have made efforts to explain in our text {Introduction section (please see lines 78-94 on page 4 of file named ‘Manuscript’); Results and Discussion section (please see lines 440-469 on page 23 of file named ‘Manuscript’)} as why the complete mitochondrial genomes are an indispensable tool to achieve a plausible phylogenetic tree in such cases of taxonomic confusion. Absence of data or missing members of certain “taxonomic clades”, may hinder but definitely not forfeit the quest for a better phylogenetic understanding of Psittacula genus as compared to previously published studies. And through our study we have strived to achieve this scientific understanding. Hence, we believe our results important and re-verified known facts through superior comprehensive approaches, providing baseline data for further analysis on phylogenetic discordances within the Psittacula genus.

Reviewer #2

Major issue: The claim that the genus needs a taxonomic revision based on their findings is weak. First, the placement of Tanygnathus together with the Psittacula species may be due to other causes that were not discussed (such as introgression and ILS) by the authors. This should be explicitly addressed (and discussed) in the text. Second, it is not clear in the text what would be the four clusters inside the genus and why they are relevant (the authors use this argument to justify the taxonomic reconsideration). It is mentioned in the abstract that “Phylogenetic analyses revealed the Psittacula genus as paraphyletic nature, containing at least 4 groups of species within the same genus, suggesting its taxonomic reconsideration”. I do not see why this is an argument for taxonomic revision. Please expand the discussion about the phylogenetic results addressing the possible causes for the recovered phylogenetic relationships and provide stronger arguments for a taxonomic revision.

Response: Our gratitude for your critical comments and valuable suggestion.

We agree the findings on taxonomic incongruence of Psittacula and Tanygnathus genus may have arisen due to introgression and incomplete lineage sorting (ILS), which has been addressed and discussed in the Results and Discussion section in a detailed way. Incongruent phylogenetic trees arising as a result of introgression/hybridization incidences are a common phenomenon with 16% of the total bird species being affected (Otthenburghs et al. 2015; Otthenburghs et al. 2017) such as woodpeckers (Fuchs et al. 2013), darwin’s finches (Lamichhaney et al. 2018), flycatchers (Rheindt and Edwards, 2011) and various other bird species (Otthenburghs et al. 2015). On the other hand from a population point of view, ILS have been reported to affect the entire phylogeny of the Neoaves as well as the Palaeognathae clade, which have confounded the estimation of their respective species tree (Stiller and Zhang, 2019). Hence, the clustering of Tanygnathus genus within Psittacula complex may be attributed to the above mentioned population level incidences and the categorization of which is beyond the scope of our study (Rheindt and Edwards, 2011; Stiller and Zhang, 2019). Please see lines 437-454 on page 23 of file named ‘Manuscript’.

For, the second part of the comment we have explicitly addressed the 4 “taxonomic clusters” inside the genus that include 1) P. cyanocephala, P. roseata; 2) P. alexandri, P. derbiana; 3) T. lucionensis, and 4) P. eupatria, P. krameri. Evidences from the pairwise divergence calculations, pointed that species belonging Psittacula genus (e.g. P. cyanocephala) are more closely related to Tanygnathus than to other members Psittacula genus. Thus clustering pattern of these groups are supported by perfect nodal values (100%/100%) obtained in both ML and BI trees. Previously, Braun (Braun et al. 2019) and Kundu (Kundu et al. 2012) used morphological markers, genetic data and molecular dating approaches to present a near complete phylogeny of Psittacula genus. Evidences from pairwise divergence scores, strong nodal values in phylogenetic trees for discordant branches and mirroring of incongruences presented by previous studies weigh in support of Psittacula being a non-monophyletic genus and warrants taxonomic reconsideration. Please see lines 470-485 on page 23 of file named ‘Manuscript’.

• Ottenburghs J, Kraus RH, van Hooft P, van Wieren SE, Ydenberg RC, Prins HH. Avian introgression in the genomic era. Avian Res. 2017 Dec 1;8(1):30.

• Ottenburghs J, Ydenberg RC, Van Hooft P, Van Wieren SE, Prins HH. The Avian Hybrids Project: gathering the scientific literature on avian hybridization. Ibis. 2015 Oct;157(4):892-4.

• Lamichhaney S, Han F, Webster MT, Andersson L, Grant BR, Grant PR. Rapid hybrid speciation in Darwin’s finches. Science. 2018 Jan 12;359(6372):224-8.

• Fuchs J, Pons JM, Liu L, Ericson PG, Couloux A, Pasquet E. A multi-locus phylogeny suggests an ancient hybridization event between Campephilus and melanerpine woodpeckers (Aves: Picidae). Mol. Phylogenet. Evol. 2013 Jun 1;67(3):578-88.

• Rheindt FE, Edwards SV. Genetic introgression: an integral but neglected component of speciation in birds. The Auk. 2011 Oct 1;128(4):620-32.

• Stiller J, Zhang G. Comparative phylogenomics, a stepping stone for bird biodiversity studies. Diversity. 2019 Jul;11(7):115.

• Braun MP, Datzmann T, Arndt T, Reinschmidt M, Schnitker H, Bahr N. A molecular phylogeny of the genus Psittacula sensulato (Aves: Psittaciformes: Psittacidae: Psittacula, Psittinus, Tanygnathus,†Mascarinus) with taxonomic implications. Zootaxa. 2019 March;4563(3):547-562.

• Kundu S, Jones CG, Prys-Jones RP, Groombridge JJ. The evolution of the Indian Ocean parrots (Psittaciformes): extinction, adaptive radiation and eustacy. Mol. Phylogenet. Evol. 2012 Jan 1;62(1):296-305.

Minor issues:

Comment 1. English: I recommend that authors seek a scientific editing service to improve the quality of the English.

Response: We are unable to take help from scientific editing service due to paucity of funds. However, the quality of English of the manuscript has been improved.

Comment 2. Figures: I suggest increasing the font size of the figures.

Response: The font size in the figures has been adjusted to the maximum to maintain quality and structural integrity of the images.

Comment 3. Lines 72-74: Braun and coworkers did not use “differences in nucleotide sequences” to reconstruct a phylogenetic tree for Psittacula. They used a ML approach based on a substitution model, which was HKY. Please correct.

Response: Phrases corrected in the text to mention Braun and coworkers reconstructed used ML based tree with HKY model. Confusion is regretted. Please see lines 71-74 on page 4 of file named ‘Manuscript’.

Comment 4. Lines 77-78: Please provide arguments that justify your claim. Why does complete mitochondrial genome data is the best option instead of large amounts of nuclear data?

Response: Complete mitochondrial genomes yields more species accurate phylogenetic tree as compared to large amounts of nuclear data (Campbell and Lapointe, 2011; Rheindt and Edwards, 2011). Mitochondrial genomes are comparatively more conserved than nuclear genomes during transition events and its unique architecture provides mitochondrial genomes the ability to carry phylogenetic information more consistently (Rheindt and Edwards, 2011). Even in incidences of introgression or ILS, mitochondrial DNA has proved to be more conserved then nuclear DNA thus avoiding stochastic errors of homoplasmy and heterogeneous base composition during phylogenetic analysis (Stiller and Zhang, 2019). Overall whole mitogenomes presents itself as an excellent candidate for phylogenetic analysis and such a fact has been recorded by previous workers in multiple studies (Rheindt and Edwards, 2011; Stiller and Zhang, 2019). Please see lines 78-96 and 454-471 on page 4 and 23 respectively of file named ‘Manuscript’.

• Campbell V, Lapointe FJ. Retrieving a mitogenomic mammal tree using composite taxa. Mol. Phylogenet. Evol. 2011 Feb 1;58(2):149-56.

• Rheindt FE, Edwards SV. Genetic introgression: an integral but neglected component of speciation in birds. The Auk. 2011 Oct 1;128(4):620-32.

• Stiller J, Zhang G. Comparative phylogenomics, a stepping stone for bird biodiversity studies. Diversity. 2019 Jul;11(7):115.

Comment 5. Lines 87-89: The work cited is about mammals. Please include a citation for birds, or explicitly state “provide consistent results compared to nuclear genes for mammals” and justify why the same would be expected for birds

Response: New citation for birds has been added as Reference No. 20. Please see lines 91-93 on page 4 of file named ‘Manuscript’.

• Rheindt FE, Edwards SV. Genetic introgression: an integral but neglected component of speciation in birds. The Auk. 2011 Oct 1;128(4):620-32.

Comment 6. Line 148: The select protein coding sequences that were used to verify the mitogenome should me mentioned at this point.

Response: The select protein coding genes of cox1, cox2, atp8, atp6, nad1, nad2, nd3 and cob have been mentioned in the text, which were used to verify the mitogenome. Please see lines 150-152 on page 7 of file named ‘Manuscript’.

Comment 7. Lines 194-198: Please provide more details about the ML approach used to estimate dN/dS (parameters, method…).

Response: Additional details about parameters and methods used for the ML approach used to estimate dN/dS ratio has been provided in the Materials and Methods section of the text. PAL2NAL program embedded in Phylogenetic Analysis by Maximum Likelihood (PAML) package was used for this analysis. We have exploited the standalone Linux version of this server. The codons used in mRNAs were aligned and was subjected to dN/dS analysis. The orthologus pair of gene sequences was given as input file and the dN/dS value for that gene was calculated. Please see lines 200-206 on page 10 of file named ‘Manuscript’.

Comment 8. Line 203: “The number of base substitutions per site can provide…”. I suggest the use of the “pairwise base substitutions” terminology.

Response: Terminology changed. Pairwise base substitutions terminology is used hence further in this manuscript. Please see lines 210-212 on page 10 of file named ‘Manuscript’.

Comment 9. Lines 205-206: “Both the genome-based and genus-based divergence analysis was performed”. I suggest changing “genome-based” and “genus-based” to “species-level” and “genus-level”, respectively. Additionally, it is advisable to explain why these two distinct approaches were considered.

Response: The terminologies changed as suggested to the advised terms in the manuscript and further denoted as ‘genus-level’ and ‘species-level’. The reason for adopting two distinct approaches stems for the need to calculate difference between each individual species, where a genetic distance between members of even the same genus can be studied. Whereas studying the average distance between different generas by clubbing multiple mitogenomes as a group, helps us to observe as a genus, which all are closely related and which distantly. Overall, such partitioning patterns help us to understand the genetic divergence indices in a comprehensive way. Please see lines 214-219 on page 11 of file named ‘Manuscript’.

Comment 10. Line 207: “members of the same genus were considered as one group”. Explain how this was done (average?).

Response: Members of the genus were partitioned into groups in MEGA X, wherein the average distances between the genus-level groups were evaluated apart from species-level genetic distances of individual mitogenomes. We followed the pre-embedded programs of MEGA X for partitioning data into groups and evaluating distances within groups. Please see lines 214-217 on page 11 of file named ‘Manuscript’.

Comment 11. Line 208: I suggest rephrasing the sentence to something similar to “Thus all considered organisms were clustered into 28 different groups, which corresponds to the 28 genera”.

Response: Sentence rephrased in the manuscript. Please see lines 219-220 on page 11 of file named ‘Manuscript’.

Comment 12. Line 212: Please explain what “emphasis” mean. State the criteria to choose the sequences/genus to keep along the phylogenetic analyses.

Response: Emphasis means, only the results from the Psittacula, Tanygnathus and Eclectus generas presented in the phylogenetic tree were explained in detail in the Results section. ‘Emphasis’ doesn’t imply any specific statistical weightage given to the above mentioned groups during analysis. Please see lines 219-220 on page 11 of file named ‘Manuscript’.

All available members of Psittaciformes order, belonging to 28 generas and 45 different species were used for phylogenetic analysis. Only one mitogenome from each species (as specified in NCBI-Genbank) were taken for further analysis. By including 45 species, and higher number of out-groups we aimed to construct a comprehensive phylogeny from whole mitogenome of Psittaciformes for the first time. This would in turn show the true position of members of Psittacula genus within the Psittaciformes order in a holistic way. Please see Table. 1 on page 8-9 of file named ‘Manuscript’.

Comment 13. Line 214: Please state if the sequences were aligned independently by gene and based on the amino acid sequence, which is desirable.

Response: The nucleotide sequences were concatenated to the protein coding regions only. These sequences (containing only protein coding genes) were then aligned using MUSCLE. Please see lines 225-226 on page 11 of file named ‘Manuscript’.

Comment 14. Lines 219-220: Please state what “effective GTR+I+G” means (I am assuming this is somehow different from the regular GTR+I+G, otherwise the word “effective” would not be necessary).

Response: Apologies for the confusion. The phrase meant to mean the same GTR+I+G model. The word ‘effective’ in this context has been deleted from the manuscript to increase clarity. Please see lines 231-232 on page 11 of file named ‘Manuscript’.

Comment 15. Lines 220-221: Please provide what statistics were used to check the convergence and mixing of the Bayesian chains.

Response: No statistical tests were used to check the convergence and mixing of Bayesian chains. We trusted that proper model selection along with very high posterior values (~100/100) obtained in the analysis, to provide accurate results. Results from the Bayesian analysis dittoed the tree obtained through ML analysis, thus re-affirming our assumption. Please see the nodal values in Fig. 5 and Supplementary Figure ‘S2 Fig’.

Comment 16. Lines 228-229: How did the authors deal with the similarity between the sequences generated by Sanger sequencing and NGS? It seems like 99% of similarity was considered enough, but it should be explicitly mentioned.

Response: The sequences were expected to be completely similar, however owing to lower confidence of base-calls in certain Sanger sequences, we decide to adopt 99% as considerable score, enough for sequence verification. Quality of base-calls lowered owing to difficulty in sequencing due to possible secondary structures in the template. Please see lines 240-242 on page 12 of file named ‘Manuscript’ where the criteria is mentioned explicitly.

Comment 17. Line 245: Please change “lower” to “upper”.

Response: Apologies for the error. Changed “lower” to “upper” in the manuscript.

Comment 18. Lines 283-285: This sentence is confusing. What does “in nature” mean?

Response: The phrase “in nature” was used as a discourse marker. Regrets for the mistake, the phrase has been deleted and sentence made more legible. Please see lines 295-297 on page 17 of file named ‘Manuscript’.

Comment 19. Lines 304-305: Please explain and discuss why Fig 2E provide evidence for selection pressure.

Response: The effective number of codons (ENc) primarily reflects the mutational bias. Plotting ENc against the GC3 thus provide an evident of whether mutational pressure or natural selection is acting on the protein coding gens of an organism. An umbrella-line is drawn with the “expected ENc value” (value assuming only mutational pressure is acting on considered genes) and is compared to the observed ENc values. Several previous reports including Roy et al. 2015, Smith 2019 (Enhanced effective codon numbers to understand codon usage bias) have stated that, if the observed ENc value exceeds the expected ENc value it will depict the complete mutational pressure on those genes. However, if the observed value is less than the expected value it is due to the selection pressure lowering the effective number of codons. In this figure, all the plotted points have placed below the umbrella-line indicating the selection pressure over mutational bias on those genes. Please see lines 317-328 on page 18 of file named ‘Manuscript’.

• Roy A, Mukhopadhyay S, Sarkar I, Sen A. Comparative investigation of the various determinants that influence the codon and amino acid usage patterns in the genus Bifidobacterium. World. J. Microb. Biot. 2015 Jun 1;31(6):959-81.

• Smith R. Enhanced effective codon numbers to understand codon usage bias. BioRxiv. 2019 Jan 1:644609.

Comment 20. Lines 321-322: Please say the meaning of the black squares in Fig 3B.

Response: Our apologies for the mistake, colour code has been added in the figure Fig. 3B. Black squares denote the lowest values on the amino acid heatmap.

Comment 21. Lines 380-381: You can only say that if you assume that the hypothesis of duplicated CRs is correct.

Response: The statement can be made if only the hypothesis of duplicated CRs is correct, hence we have rephrased the sentence. Multiple previous studies have observed duplicated CR region has contributed to longevity in birds (Sarkar et al. 2020; Skujina et al. 2019). Please see lines 402-404 on page 21 of file named ‘Manuscript’.

• Skujina I, McMahon R, Lenis VP, Gkoutos GV, Hegarty M. Duplication of the mitochondrial control region is associated with increased longevity in birds. Aging (Albany NY). 2016 Aug;8(8):1781.

• Sarkar I, Dey P, Sharma SK, Ray SD, Kochiganti VH, Singh R, Pramod P, Singh RP. Turdoides affinis mitogenome reveals the translational efficiency and importance of NADH dehydrogenase complex-I in the Leiothrichidae family. Sci. Rep. 2020 Oct 1;10(1):1-1.

Comment 22. Line 387: Here, by “single-gene” you mean mitochondrial gene or any gene (nuclear and mitochondrial)?

Response: Regrets for the confusion, here we mean both single nuclear/mitochondrial gene phylogeny. We have rephrased the sentence to increase understanding. Please see lines 409-411 on page 22 of file named ‘Manuscript’.

Comment 23. Line 389: This sentence is confusing. How can whole mitochondrial genomes be used along with concatenated PCGs? The PCGs are part of the mitogenome.

Response: Apologies for the confusion. We meant to convey concatenated PCGs from the whole mitochondrial genomes were used to construct the phylogeny. Hence, sentence rephrased in the text. Please see lines 411-414 on page 22 of file named ‘Manuscript’.

Comment 24. Line 398: I suggest rephrasing this sentence to “The mitogenome-based divergence analysis suggest that…”

Response: As advised in Comment no. 9 all ‘genome-based’ phrases were changed to ‘species-level’. Hence, the sentence was further modified to include ‘species-level’ and ‘mitogenome-based’ terminologies. Please see lines 421-425 on page 22 of file named ‘Manuscript’.

Comment 25. Lines 402-404: I did not understand what topology was presented before.

Response: It is intended to mean both the ML and BI based trees have same topologies, no previous topology presented. Hence, sentence rephrased for better understanding of the idea. Please see lines 426-427 on page 22 of file named ‘Manuscript’.

Comment 26. Lines 408-409: It would be reasonable to mention what kind of data the cited works were based on.

Response: Sentence rephrased to include the data mentioned in this cited studies is based on single mitochondrial (cob) and nuclear (rag-1) gene. Please see lines 431-433 on page 22 of file named ‘Manuscript’.

Comment 27. Lines 409-411: This indicates that the mitochondrial DNA of this species have common ancestry. This pattern does not necessarily imply a paraphyletic genus. It may be caused by population level phenomena such as introgression.

Response: Mitochondrial DNA of the species share common ancestry. Population level phenomenon such as introgression and ILS has been mentioned and discussed in detail in the ‘Major issue’ part of the rebuttal. We do acknowledge the phenomenon of introgression and ILS may cause such phylogenetic incongruences. However, the evidence from previous studies and our divergence analysis, phylogenetic analysis definitely weigh-in support of a non-monophyletic Psittacula genus. Please see lines 437-454 on page 23 of file named ‘Manuscript’.

28. Lines 415-419: All these statements are assuming that the mitogenome is always identical to the species phylogeny, which is not true. Also, this part of the text is very confusing. I was not able to understand why there are non-monophiletic clustering os 4 groups.

Response: Our study put forwards various facts and references in support of mitogenome based phylogeny to show that, more often than not it reflects true species phylogeny. The part of the manuscript mentioned in this comment has been modified to incorporate better arguments in support of our logic. Various reports have shown phylogenetic analysis associated with different genomic loci (nuclear, mitochondrial, coding, non-coding) may produce distinct phylogenetic trees respectively (Rheindt and Edwards, 2011; Stiller and Zhang, 2019). However mitogenomes have shown to provide consistent phylogenetic results in events of speciation and such consistency is even maintained in events of introgression and ILS also, wherein studies have shown levels of introgression in mitochondrial DNA to be nearly zero or significantly lesser than nuclear DNA introgression (Rheindt and Edwards, 2011; Stiller and Zhang, 2019). Such unique qualities of mitogenome eliminates stochastic errors in phylogenetic studies where the phylogenetic signal often gets masked with homoplasmy, multiple substitutions on the same site, and heterogeneous base composition (Stiller and Zhang, 2019). Such evidences support that the phylogenetic tree constructed using whole mitogenome more often than not reflects true species phylogeny. Please see lines 454-469 on page 23 of file named ‘Manuscript’.

The clustering pattern within the Psittacula genus and arguments in support of non-monophyletic nature has been provided in the second part of the ‘Major issue’ comment, kindly consider. Please see lines 470-485 on page 23, 24 of file named ‘Manuscript’.

• Rheindt FE, Edwards SV. Genetic introgression: an integral but neglected component of speciation in birds. The Auk. 2011 Oct 1;128(4):620-32.

• Stiller J, Zhang G. Comparative phylogenomics, a stepping stone for bird biodiversity studies. Diversity. 2019 Jul;11(7):115.

29. Lines 424-433: This analysis is pointless, unless the results are discussed and compared to other birds/vertebrates. Besides that, are the dN/dS values statistically significant?

Response: The main aim of this study was to report the complete mitochondrial genome sequence of Psittacula cyanocephala and its comparison with other Psittaciformes. Hence we have not included birds of other families or other vertebrates. Regarding the evolutionary analysis, we calculated the dN/dS values of 13 protein coding genes of Psittacula cyanocephala with respect to select Psittaciformes mitogenomes and have finally reported the average value for all 13 protein coding genes. The aim was to observe whether those genes were naturally selected or under mutational pressure. Since dN/dS values of all protein coding genes were less than 1, we concluded the presence of natural selection over those genes. And the values obtained are statistically significant. Please see lines 491-499 on page 25 of file named ‘Manuscript’.

30. Lines 441-443: Change “least” to “lower”.

Response: Word changed in manuscript to ‘lower’. Please see lines 508 on page 26 of file named ‘Manuscript’.

31. Line 444: Change “multiple phyla” to “multiple clades/groups”.

Response: Rephrased in manuscript to ‘multiple clades/groups’. Please see line 510 on page 26 of file named ‘Manuscript’.

32. Line 446: Change “phylogeography” to “phylogeographic”.

Response: Word changed in manuscript. Please see line 512 on page 26 of file named ‘Manuscript’.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

16 Feb 2021

PONE-D-20-31563R1

Complete mitogenome of endemic Plum-headed parakeet Psittacula cyanocephala  – characterization and phylogenetic analysis

PLOS ONE

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Reviewer #2: (No Response)

Reviewer #3: All comments have been addressed

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Reviewer #3: Partly

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Reviewer #3: Yes

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Reviewer #2: The authors have incorporated most suggestions and I can say that they addressed my main concerns in the last review satisfactorily. However, I have a few minor comments that the authors may want to consider.

- Lines 197-198: “Evolutionary constraints… were…”

- Line 205: “The codons used … and were …”

- Lines 197-207: to my knowledge, PAL2NAL is not a software from PAML package, but CODEML is. The authors should revise this.

- Lines 234-235: I insist that the authors should report at least one statistic that they used to check the convergence of the Bayesian chains (average standard deviation of the split frequencies…) and one statistic to check the mixing of the Bayesian chains (ESS…).

- Line 415: “The evolutionary rate…”

- The alignment data as well as the phylogenetic trees (nwk/nexus) should be made available (at the supporting material or a public repository)

Reviewer #3: The autors did a really good job improving the manuscript by addressing all the previous reviewers’ concerns. The manuscript is mainly focused on the building and characterization of the genome of Psittacula cyanocephala, and this is the main strenght of it. Phylogenetic analyses, however, as mentioned by one of the previous reviewers, did not provide any new insights on Psittacula parakeets phylogenetic relationships, even thought show support to previous claims on Psittacula paraphyly. The sampling scheme of the includes a limited number of taxa because of the few available mitogenomes (6 of the 16 Psittacula species and only 1 of the 4 Tanygnathus species) and because of this, it only shows the potential applications of the use of mitogenomes for phylogenetic analyses. Phylogenetic analyses also include data from 44 parrot species but these do not provide new information on the relationships within Psittaciformes.

**********

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25 Feb 2021

Ms. Ref. No.: PONE-D-20-31563R1 - EMID: 75cc66b576b95812

Title: Complete mitogenome of endemic Plum-headed parakeet Psittacula cyanocephala – characterization and phylogenetic analysis

Response to reviewers

We would like to thank Dr. Maria Andreína Pacheco (Academic Editor) and the Reviewers for their constructive remarks. We have revised the manuscript as suggested by the Reviewers. The revised manuscript is submitted for further consideration. Please find below a point-by-point rebuttal to the issues raised.

Additional Editor Comments:

Comment 1: Please, pay attention to the reviewer’s comment and incorporate then in a new version.

Response: We have carefully addressed the reviewer’s comment in the new version of the manuscript.

Reviewer #2

Comment 1. Lines 197-198: “Evolutionary constraints… were…”

Response: Sentence rephrased in the manuscript. Please see lines 197-198 on page 10 of file named ‘Manuscript’.

Comment 2. Line 205: “The codons used … and were …”

Response: Sentence rephrased in the manuscript. Please see lines 205 on page 10 of file named ‘Manuscript’.

Comment 3. Lines 197-207: to my knowledge, PAL2NAL is not a software from PAML package, but CODEML is. The authors should revise this.

Response: PAL2NAL is a programme embedded in PAML. PAL2NAL automatically calculates dS and dN using codeml program in PAML (http://www.bork.embl.de/pal2nal/#Ref).

Comment 4. Lines 234-235: I insist that the authors should report at least one statistic that they used to check the convergence of the Bayesian chains (average standard deviation of the split frequencies…) and one statistic to check the mixing of the Bayesian chains (ESS…).

Response: Thanks for the suggestion. To assess convergence, the average standard deviation of split frequencies was calculated. The effective sample size value of the trace was also diagnosed to confirm the mixing of the Bayesian Markov chains. Please see lines 236-239 on page 11, 12 of file named ‘Manuscript’. The resulting values and data are submitted as additional supplementary information.

Comment 5. Line 415: “The evolutionary rate…”

Response: Sentence rephrased in the manuscript. Please see line 410 on page 22 of file named ‘Manuscript’.

Comment 6. The alignment data as well as the phylogenetic trees (nwk/nexus) should be made available (at the supporting material or a public repository).

Response: The alignment file, both BI and ML tree files are submitted as additional supplementary information.

Reviewer #3

Comment 1. The authors did a really good job improving the manuscript by addressing all the previous reviewers’ concerns. The manuscript is mainly focused on the building and characterization of the genome of Psittacula cyanocephala, and this is the main strength of it. Phylogenetic analyses, however, as mentioned by one of the previous reviewers, did not provide any new insights on Psittacula parakeets phylogenetic relationships, even thought show support to previous claims on Psittacula paraphyly. The sampling scheme of the includes a limited number of taxa because of the few available mitogenomes (6 of the 16 Psittacula species and only 1 of the 4 Tanygnathus species) and because of this, it only shows the potential applications of the use of mitogenomes for phylogenetic analyses. Phylogenetic analyses also include data from 44 parrot species but these do not provide new information on the relationships within Psittaciformes.

Response: Thank you very much for your thoughtful comments and insight. The complete mitogenome of Psittacula cyanocephala is necessary to build the complete phylogeny of Psittacula genus complex. Our work does lend support to paraphyly within Psittacula genus as indicated by previous studies. Evidences from multiple sources (complete mitogenomes, single nuclear/mitochondrial genes etc.) are necessary to propose and validate a comprehensive phylogeny (Tietze DT, 2018). We believe our study is an important contribution in this aspect.

• Tietze DT. Bird species: how they arise, modify and vanish. Springer Nature; 2018.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

2 Mar 2021

Complete mitogenome of endemic Plum-headed parakeet Psittacula cyanocephala  – characterization and phylogenetic analysis

PONE-D-20-31563R2

Dear Dr. SINGH,

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Maria Andreína Pacheco, Ph.D.

Academic Editor

PLOS ONE

23 Mar 2021

PONE-D-20-31563R2

Complete mitogenome of endemic Plum-headed parakeet

Dear Dr. Singh:

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