<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "https://jats.nlm.nih.gov/publishing/1.3/JATS-journalpublishing1-3.dtd"><article xml:lang="en" dtd-version="1.3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article"><front><journal-meta><journal-id journal-id-type="issn">2615-790X</journal-id><journal-title-group><journal-title>Tropical Animal Science Journal</journal-title><abbrev-journal-title>Trop. Anim. Sci. J.</abbrev-journal-title></journal-title-group><issn pub-type="epub">2615-790X</issn><issn pub-type="ppub">2615-787X</issn><publisher><publisher-name>Faculty of Animal Science, IPB University</publisher-name><publisher-loc>Indonesia</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.5398/tasj.2027.50.1.10</article-id><title-group><article-title>Complete Mitochondrial Genome Analysis Reveals the Genetic Diversity of Madura Cattle (<italic>Bos javanicus × Bos indicus</italic> Hybrid)</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Khairunnisa</surname><given-names>N.</given-names></name><address><country>Indonesia</country></address><xref ref-type="aff" rid="AFF-1"></xref></contrib><contrib contrib-type="author"><name><surname>Dharmayanthi</surname><given-names>A. B.</given-names></name><address><country>Indonesia</country></address><xref ref-type="aff" rid="AFF-2"></xref></contrib><contrib contrib-type="author"><name><surname>Noor</surname><given-names>R. R.</given-names></name><address><country>Indonesia</country></address><xref ref-type="aff" rid="AFF-3"></xref></contrib><contrib contrib-type="author"><name><surname>Jakaria</surname><given-names>J.</given-names></name><address><country>Indonesia</country></address><xref ref-type="aff" rid="AFF-3"></xref></contrib></contrib-group><contrib-group><contrib contrib-type="editor"><name><surname>Wiryawan</surname><given-names>Prof. Dr. Komang G</given-names></name><address><country>Indonesia</country></address><xref ref-type="aff" rid="EDITOR-AFF-1"></xref></contrib></contrib-group><aff id="AFF-1"><institution content-type="dept">Graduate Students of Animal Production and Technology Science, Graduate School</institution><institution-wrap><institution>IPB University</institution><institution-id institution-id-type="ror">https://ror.org/05smgpd89</institution-id></institution-wrap><country country="ID">Indonesia</country></aff><aff id="AFF-2"><institution content-type="dept">Research Centre for Biosystematics and Evolution</institution><institution-wrap><institution>National Research and Innovation Agency</institution><institution-id institution-id-type="ror">https://ror.org/02hmjzt55</institution-id></institution-wrap><country country="ID">Indonesia</country></aff><aff id="AFF-3"><institution content-type="dept">Department of Animal Production and Technology, Faculty of Animal Science</institution><institution-wrap><institution>IPB University</institution><institution-id institution-id-type="ror">https://ror.org/05smgpd89</institution-id></institution-wrap><country country="ID">Indonesia</country></aff><aff id="EDITOR-AFF-1">Tropical Animal Science Journal</aff><pub-date date-type="pub" iso-8601-date="2026-10-12" publication-format="electronic"><day>12</day><month>10</month><year>2026</year></pub-date><pub-date date-type="collection" iso-8601-date="2026-10-12" publication-format="electronic"><day>12</day><month>10</month><year>2026</year></pub-date><volume>50</volume><issue>1</issue><issue-title>Tropical Animal Science Journal (Issue in Progress)</issue-title><fpage>10</fpage><lpage>20</lpage><history><date date-type="received" iso-8601-date="2026-5-8"><day>8</day><month>5</month><year>2026</year></date></history><permissions><copyright-statement>Copyright (c) 2026 Tropical Animal Science Journal</copyright-statement><copyright-year>2026</copyright-year><copyright-holder>Tropical Animal Science Journal</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by-sa/4.0/"><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">http://creativecommons.org/licenses/by-sa/4.0/</ali:license_ref><license-p>This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.Authors submitting manuscripts should understand and agree that copyright of manuscripts of the article shall be assigned/transferred to Tropical Animal Science Journal. The statement to release the copyright to Tropical Animal Science Journal is stated in Form A. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA) where Authors and Readers can copy and redistribute the material in any medium or format, as well as remix, transform, and build upon the material for any purpose, but they must give appropriate credit (cite to the article or content), provide a link to the license, and indicate if changes were made. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.</license-p></license></permissions><self-uri xlink:href="https://journal.ipb.ac.id/tasj/article/view/72999" xlink:title="Complete Mitochondrial Genome Analysis Reveals the Genetic Diversity of Madura Cattle (Bos javanicus × Bos indicus Hybrid)">Complete Mitochondrial Genome Analysis Reveals the Genetic Diversity of Madura Cattle (Bos javanicus × Bos indicus Hybrid)</self-uri><abstract><p>Madura cattle are a significant local beef breed in Indonesia, but information about their genetic origins is limited, especially since no studies have fully characterized their mitochondrial DNA. This research aims to sequence the entire mitochondrial genome of Madura cattle and explore their phylogenetic relationships and diversity relative to reference bovine lineages. The study used five blood samples from Madura bulls at Singosari Artificial Insemination Center (BBIB). DNA was extracted from the blood, then the mitochondrial genome was amplified via long-range PCR and sequenced with Oxford Nanopore Technology. Across the five samples, quality-filtered reads ranged from 5061 to 11785, with mean read lengths of 5030 to 7475 bp and mean quality scores of 14.1 to 14.3. Bioinformatics analysis included genome assembly, gene annotation, nucleotide composition, and phylogenetic analysis. The findings showed that the Madura cattle mitochondrial genome is between 16338 and 16451 base pairs (GenBank accession PZ509169) and contains 37 genes: 13 protein-coding, 22 tRNA, 2 rRNA, and 1 control region. Nucleotide analysis indicated positive AT-skew and negative GC-skew in most protein-coding genes. Phylogenetic analysis revealed that Madura cattle cluster into two maternal groups, one aligned with <italic>Bos javanicus</italic> and the other with <italic>Bos indicus</italic>. These results suggest that the maternal lineage of Madura cattle is complex and may reflect historical introgression involving <italic>Bos javanicus</italic> and <italic>Bos indicus</italic>. However, further nuclear genomic analysis is needed to clarify genome-wide ancestry and admixture patterns.</p></abstract><kwd-group><kwd>Bovidae</kwd><kwd>Madura cattle</kwd><kwd>maternal origin</kwd><kwd>mitochondrial whole genome</kwd><kwd>phylogenetics</kwd></kwd-group><custom-meta-group><custom-meta><meta-name>File created by JATS Editor</meta-name><meta-value><ext-link ext-link-type="uri" xlink:href="https://jatseditor.com" xlink:title="JATS Editor">JATS Editor</ext-link></meta-value></custom-meta><custom-meta><meta-name>issue-created-year</meta-name><meta-value>2027</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec><title>INTRODUCTION</title><p>Madura cattle have been recognized by the Indonesian Ministry of Agriculture as one of Indonesia’s local breeds, originating from Madura Island and its surrounding areas. Madura cattle are among Indonesia’s valuable local livestock genetic resources that require protection and conservation (National Standards Agency of Indonesia, 2020). The conservation of Indonesian local cattle is important because these breeds possess unique genetic backgrounds, adaptive traits, and potential breeding value. Recent genetic and genomic studies have emphasized that genetic information is essential for supporting sustainable utilization, conservation, and breeding strategies for the Indonesian local cattle population (Sutarno &amp; Setyawan, 2015). The Madura cattle population on Madura Island makes a significant contribution, meeting approximately 24% of the demand for beef cattle in East Java <xref rid="BIBR-25" ref-type="bibr">(Nurgiartiningsih et al., 2016)</xref>. Additionally, Madura cattle play a vital role as a symbol of identity and culture for the Madura community <xref ref-type="bibr" rid="BIBR-25">(Nurgiartiningsih et al., 2016)</xref>. </p><p>The population of crossbred Madura cattle on Madura Island over the past few decades has reached 53.3% of the total cattle population on the island <xref ref-type="bibr" rid="BIBR-25">(Nurgiartiningsih et al., 2016)</xref>. This poses a potential threat to the genetic diversity of local livestock. Uncontrolled crossbreeding is also believed to be a major threat to the sustainability of Indonesia’s local livestock. Uncontrolled crossbreeding with exotic breeds has also been reported as a factor that may contribute to genetic erosion and reduced quality in Indonesian local cattle populations (Sutarno &amp; Setyawan, 2015).</p><p>To prevent the loss of local genetic resources, comprehensive genetic information on local cattle breeds is needed as baseline data for developing conservation programs and breeding strategies <xref rid="BIBR-28" ref-type="bibr">(Petretto et al., 2022)</xref>; <xref ref-type="bibr" rid="BIBR-30">(Pramod et al., 2018)</xref>; <xref ref-type="bibr" rid="BIBR-41">(Xia et al., 2019)</xref>. Mitochondrial DNA analysis is frequently used to assess intra- and interspecies diversity, trace maternal lineages, and examine evolutionary relationships among various species <xref rid="BIBR-1" ref-type="bibr">(Anwar et al., 2025)</xref>. Popular mtDNA markers have been used in analyses of Bali cattle breeds <xref ref-type="bibr" rid="BIBR-16">(Jakaria et al., 2019)</xref>, Thailand dairy cattle<xref ref-type="bibr" rid="BIBR-3">(Ariyaraphong et al., 2021)</xref>, Alpine cattle <xref ref-type="bibr" rid="BIBR-10">(Granado et al., 2021)</xref>, and Podolian cattle <xref ref-type="bibr" rid="BIBR-7">(Lorenzo et al., 2018)</xref>, albeit only partially. Currently, intensive research on mitochondrial genomes is being conducted to examine genetic diversity in Uruguayan cattle <xref ref-type="bibr" rid="BIBR-24">(Liu et al., 2020)</xref>, Georgian mountain cattle <xref ref-type="bibr" rid="BIBR-23">(Kunelauri et al., 2022)</xref>, Shigaste humped cattle <xref ref-type="bibr" rid="BIBR-13">(Guo et al., 2018)</xref>, Yunling cattle <xref ref-type="bibr" rid="BIBR-42">(Xia et al., 2019)</xref>, Sardinian cattle<xref ref-type="bibr" rid="BIBR-28">(Petretto et al., 2022)</xref>, Native Korean cattle <xref ref-type="bibr" rid="BIBR-37">(Wang et al., 2016)</xref>, Guangxi cattle<xref ref-type="bibr" rid="BIBR-41">(Xia et al., 2019)</xref>, and Bali cattle <xref ref-type="bibr" rid="BIBR-1">(Anwar et al., 2025)</xref>; <xref ref-type="bibr" rid="BIBR-15">(Jakaria et al., 2025)</xref>. Mitochondrial analysis of Madura cattle has been conducted, but only using partial markers such as D-loop <xref ref-type="bibr" rid="BIBR-14">(Hartatik et al., 2015)</xref>, cytB <xref ref-type="bibr" rid="BIBR-31">(Prihandini et al., 2020)</xref>, and COI <xref ref-type="bibr" rid="BIBR-35">(Utami et al., 2024)</xref>. Although these markers provide useful preliminary information, they are insufficient to describe complete mitochondrial genome organization, nucleotide composition, codon usage, tRNA structure, control region variation, and whole mitogenome-based phylogenetic relationships. No studies have been reported on the analysis of the complete mtDNA genome of Madura cattle. Therefore, this study addresses this gap by providing the first complete mitochondrial genome characterization of Madura cattle using long-read Oxford Nanopore Technology. This study aims to fully characterize the mitochondrial genome of Madura cattle, reveal their genetic diversity, and examine their phylogenetic relationships with other cattle breeds worldwide. </p></sec><sec><title>MATERIALS AND METHODS</title><sec><title>Ethical Approval</title><p>This research has been approved by the ethics committee of the National Research and Innovation Agency (BRIN) of the Republic of Indonesia under approval number 071/KE.02/SK/03/2024</p></sec><sec><title>Experimental Design</title><p>This study used five blood samples from Madura bulls collected at the Singosari Artificial Insemination Center (BBIB) in Malang, East Java, Indonesia. Blood samples were collected via the jugular vein, with volumes of 5-8 mL. DNA extraction and PCR amplification were performed at the Genomics Laboratory of the National Research and Innovation Agency (BRIN) in Cibinong, Bogor, while mitochondrial genome sequencing was conducted at PT Genomik Solidaritas Indonesia (GSI) in South Jakarta. This study was carried out in several stages, comprising DNA extraction, amplification, sequencing, bioinformatics analysis, and data analysis. </p></sec><sec><title>DNA Extraction</title><p>Mitochondrial DNA was extracted using the Quick-DNA HMW MagBead Kit (Zymo Research) following the manufacturer’s protocol. DNA concentration was measured using the Qubit 4 Fluorometer (Thermo Fisher Scientific, USA); extracted DNA concentrations ranged from 9.68 to 22.21 ng/µL. The extracted DNA was then used for further analysis. </p></sec><sec><title>Mitochondrial Genome Amplification</title><p>The mitochondrial genome was amplified by a long-range PCR approach using the GoTaq Long PCR Master Mix (Promega). Amplification was performed using two pairs of forward and reverse primers. The first primer pair consisted of forward 5’-ATG AGT TGG TAG TTT CGG TTG G-3’ and reverse 5’-AGT TGA TTG TTG GGG GTA GAG C-3’, while the second primer pair consisted of forward 5’-ACC AAA CAG AAC GCC TAA ACG-3’ and reverse 5’-GCT ATG AAG AAG AGG GCA AAT G-3’ <xref ref-type="bibr" rid="BIBR-1">(Anwar et al., 2025)</xref>, each targeting approximately 9 kb fragments. PCR amplification was performed under the following cycling conditions: pre-denaturation at 95 °C for 2 minutes, followed by 35 cycles of denaturation at 98 °C for 10 seconds, annealing at 63 °C for 30 s, and extension at 68 °C for 5 min, with a final extension at 68 °C for 5 min. PCR products were verified by agarose gel electrophoresis using 0.5 × Tris-Borate-EDTA (TBE) buffer and FluoroSafe DNA stain, and visualized under a UV transilluminator to confirm successful amplification prior to sequencing.</p></sec><sec><title>Mitochondrial Genome Sequencing</title><p>The DNA amplification products were subsequently processed for library preparation using the SQK-LSK110 Ligation sequencing Kit (Oxford Nanopore Technologies, UK). Each sample was barcoded using the Native Barcoding Kit v14 (SQK-NBD114), enabling multi-sample sequencing in a single run. The barcoded DNA was pooled and loaded onto an R10.4.1 flow cell for sequencing using the GridION device (Oxford Nanopore Technologies, UK). Basecalling was performed with Guppy in high-accuracy mode to generate FASTQ sequencing data. The data were subsequently separated by sample barcode using the MinKNOW software for demultiplexing.</p></sec><sec><title>Mitochondrial Genome Assembly</title><p>The sequencing data obtained were processed using several bioinformatics tools. Adapter and barcode trimming were performed using Porechop version 0.2.4 <xref ref-type="bibr" rid="BIBR-39">(Wick, 2017)</xref>, while read quality filtering was performed using NanoFilt version 2.3.0 <xref ref-type="bibr" rid="BIBR-6">(Coster et al., 2018)</xref> with a minimum quality threshold of Q10.</p><p>The filtered reads were then mapped to the <italic>Bos javanicus</italic> (Pq130485.1) and <italic>Bos indicus</italic> (OQ886063.1) reference genomes using Minimap2 version 2.28 with the <italic>map-ont </italic>parameter. The mapping results were saved in Binary Alignment Map (BAM) format and used to generate consensus sequences using iVar version 1.4.2 <xref ref-type="bibr" rid="BIBR-11">(Grubaugh et al., 2019)</xref> with the following parameters: minimum quality score Q20, minimum base frequency 0.6, minimum indel frequency 0.8, and minimum coverage depth 30×. iVar was used because this study applied an amplicon-based targeted sequencing approach, and iVar enables consensus sequence generation from mapped amplicon reads using defined thresholds for base quality, allele frequency, indel frequency, and coverage depth. Sequencing statistics were evaluated after adapter trimming and quality filtering. Across the five samples, quality-filtered reads ranged from 5061 to 11785, total bases ranged from 25.46 to 79.68 Mb, mean read lengths ranged from 5030 to 7475 bp, N50 values ranged from 8987 to 9028 bp, and mean quality scores ranged from 14.1 to 14.3. The resulting consensus sequence was then curated by aligning it with the D-loop sequence obtained via Sanger sequencing from the same sample. The D-loop region used for Sanger sequencing was amplified using the forward primer 5’-GGA AGA AAC TGT AGT CTC AC-3’ and the reverse primer 5’-CAT CTA GGC ATT TTC AGT GC-3’. The trimming process leading to the formation of the consensus sequence was performed using the Galaxy bioinformatics platform (usegalaxy.eu). The complete mitochondrial genome sequences were then annotated using the Mitos2 software <xref ref-type="bibr" rid="BIBR-5">(Bernt et al., 2013)</xref> to identify the position and sizes of genes, including protein-coding genes (PCGs), rRNA, tRNA, and the control region (CR). The complete mitochondrial genome sequence generated in this study is available under GenBank accession number PZ509169.</p></sec><sec><title>Mitochondrial Genome Analysis</title><p>The complete mitochondrial genome sequences were visualized as circular genome maps using Geneious Primer v2025.0.2 <xref ref-type="bibr" rid="BIBR-19">(Kearse et al., 2012)</xref>. Genetic distance analysis was performed using the Kimura 2-parameter (K2P) substitution model <xref ref-type="bibr" rid="BIBR-20">(Kimura, 1980)</xref> in Geneious Primer v2025.0.2. Analysis of Relative Synonymous Codon Usage (RSCU) and calculation of AT-skew and GC-skew were performed based on the nucleotide composition of the mitochondrial genome using the formula AT-skew = (A – T)/(A+T) and GC-skew = (G – C)/(G + C) were performed using bioinformatics tools available at web bioinformatics (jamiemcgowan.ie/bionf/index.htm). Visualization of tRNA secondary structures was performed using Forna (www.rna.tbi.univie.ac.at/forna/).</p><p>Phylogenetic tree reconstruction was performed by aligning sequences with MAFFT <xref ref-type="bibr" rid="BIBR-18">(Katoh et al., 2019)</xref> and the phyml method in Geneious Prime v2025.0.2 with 1000 bootstraps. Reference mitochondrial genome sequences used Zebu cattle (<italic>Bos indicus</italic>) accession ID NC005971.1, Ongole cattle (<italic>Bos indicus</italic>) accession ID NC006853.1, Bali cattle (<italic>Bos javanicus</italic>) accession ID PQ130485.1, CERZA Bali cattle (<italic>Bos javanicus</italic> CERZA) accession ID JN632606.1, Bali cattle (<italic>Bos javanicus</italic>) accession ID PV387265.1, Gaur (<italic>Bos gaurus</italic>) accession ID MT360653.1, Aurochs cattle (<italic>Bos primigenius</italic>) accession ID NC013996.1, Gayal (<italic>Bos frontalis</italic>) accession ID MW763078.1, and Yak (<italic>Bos grunniens</italic>) accession ID OR086006.1. Meanwhile, <italic>Bubalus bubalis</italic> (accession NC049568.1) was used as the outgroup. </p></sec></sec><sec><title>RESULTS</title><sec><title>Mitochondrial Genome Structure of Madura Cattle</title><p>The Madura cattle mitochondrial genome has a total length of 16338 to 16451 base pairs (bp), consisting of 1 control region (D-loop) and 37 genes, including 22 transfer RNA (tRNA) genes, 2 ribosomal RNA (rRNA) genes, and 13 protein-coding genes (PCGs). The protein-coding genes consist of three cytochrome c oxidase (COX1, COX2, and COX3), two subunits of ATP synthase (ATP6 and ATP8), and seven subunits of NADH dehydrogenase (ND1, ND2, ND3, ND4, ND4L, ND5, and ND6). The result of full-length mtDNA genome sequencing of Madura cattle showed that the sequence was the shortest at 16338 bp (Ma1), the longest at 16451 bp (Ma2), and the second longest at 16386 bp (Ma3), while Ma4 and Ma5 were 16,338 bp and 16,339 bp, respectively. The length variation among samples was mainly associated with differences in the control region or D-loop due to the presence of a tandem repeat motif with the motif 5’-ATA AGT ACA TAA TAT TTA TGT A-3’ in samples Ma2 and Ma3. The majority of genes are distributed on the heavy strand (H-strand); 28 of the 37 genes are on the H-strand, and 9 genes are on the light strand (L-strand), namely 8 tRNA genes (trnA, trnC, trnE, trnN, trnP, trnY, trnS2, and trnQ) and one protein-coding gene (ND6) (<xref ref-type="fig" rid="figure-2">Figure 1</xref> and <xref ref-type="table" rid="table-1">Table 1</xref>). The start codons found in protein-coding genes (PCGs) are predominantly ATG and ATA. The stop codons found in the Madura cattle PCGs are AGA (cytB), TAA (ND6, ND5, ND4L, ATP6, ATP8, COX2, and COX1), and incomplete stop codons, namely TA- (ND1) and T (ND4, ND3, COX3, and ND2). The nucleotide composition of the complete mitochondrial genome was dominated by adenine and thymine, with adenine 33.47%, thymine 27.11%, cytosine 26.01%, and guanine 13.40%. The A+T content was 60.58%, whereas the G+C content was 39.42%, indicating an A+T-rich mitochondrial genome. Two amino acid substitutions were detected in the mitochondrial protein-coding genes of Madura cattle, including phenylalanine to leucine (F to L) in ATP8 at position 24 and valine to isoleucine (V to I) in ND5 at position 172.</p></sec><sec><title>AT-Skew and GC-Skew Composition</title><p>The total length of protein-coding genes (PCGs) in Madura cattle is 11403 bp, or 69.79% of the total mitochondrial genome. Analysis of the nucleotide composition of the protein-coding genes (PCGs) in the Madura cattle mtDNA genome shows a positive AT-skew and a negative GC-skew (<xref ref-type="fig" rid="figure-1">Figure 2</xref>). The AT-skew values for the mitochondrial protein-coding genes of Madura cattle (ND1, ND2, COX2, ATP8, ATP6, ND3, ND4L, ND4, ND5, and cytB) yielded positive values, indicating that the adenine (A) content is higher than thymine (T), while the other three genes (COX1, COX3, and ND6) had negative values, indicating a predominance of thymine (T). However, the COX1 and COX2 genes had values close to zero, indicating that adenine and thymine were nearly balanced in these two genes. The GC-skewness values for the 12 protein-coding genes (ND1, ND2, COX1, COX2, COX3, ATP6, ATP8, ND3, ND4L, ND4, ND5, and cytB) are negative, indicating that cytosine (C) content exceeds guanine (G) content.</p><table-wrap id="table-1" ignoredToc=""><label>Table 1</label><caption><p> Structure and characterization of the complete mitochondrial DNA of Madura cattle</p></caption><table frame="box" rules="all"><thead><tr><th rowspan="2" valign="middle" align="left" colspan="1">Name</th><th rowspan="2" valign="middle" align="center" colspan="1">Product</th><th align="center" colspan="1" rowspan="2" valign="middle">Strand</th><th align="center" colspan="2" valign="middle">Position</th><th align="center" colspan="1" rowspan="2" valign="middle">Size (bp)</th><th rowspan="2" valign="middle" align="center" colspan="1">Start codon</th><th rowspan="2" valign="middle" align="center" colspan="1">Stop codon</th><th rowspan="2" valign="middle" align="center" colspan="1">Anti codon</th></tr><tr><th valign="middle" align="center" colspan="1">Min</th><th valign="middle" align="center" colspan="1">Max</th></tr></thead><tbody><tr><td valign="top" align="left" colspan="1">Control Region</td><td align="center" colspan="1" valign="top">-</td><td colspan="1" valign="top" align="center">-</td><td colspan="1" valign="top" align="center">15430</td><td colspan="1" valign="top" align="center">16386</td><td valign="top" align="center" colspan="1">957</td><td colspan="1" valign="top" align="center">-</td><td valign="top" align="center" colspan="1">-</td><td align="center" colspan="1" valign="top">-</td></tr><tr><td colspan="1" valign="top" align="left">trnP</td><td valign="top" align="center" colspan="1">tRNA-Pro</td><td colspan="1" valign="top" align="center">L</td><td valign="top" align="center" colspan="1">15364</td><td valign="top" align="center" colspan="1">15429</td><td align="center" colspan="1" valign="top">66</td><td valign="top" align="center" colspan="1">-</td><td valign="top" align="center" colspan="1">-</td><td align="center" colspan="1" valign="top">TGG</td></tr><tr><td valign="top" align="left" colspan="1">trnT</td><td valign="top" align="center" colspan="1">tRNA-Thr</td><td align="center" colspan="1" valign="top">H</td><td align="center" colspan="1" valign="top">15295</td><td align="center" colspan="1" valign="top">15365</td><td valign="top" align="center" colspan="1">71</td><td align="center" colspan="1" valign="top">-</td><td align="center" colspan="1" valign="top">-</td><td align="center" colspan="1" valign="top">TGT</td></tr><tr><td align="left" colspan="1" valign="top">cytB</td><td colspan="1" valign="top" align="center">cytB</td><td valign="top" align="center" colspan="1">H</td><td valign="top" align="center" colspan="1">14152</td><td valign="top" align="center" colspan="1">15291</td><td valign="top" align="center" colspan="1">1140</td><td valign="top" align="center" colspan="1">ATG</td><td valign="top" align="center" colspan="1">AGA</td><td align="center" colspan="1" valign="top">-</td></tr><tr><td align="left" colspan="1" valign="top">trnE</td><td align="center" colspan="1" valign="top">tRNA-Glu</td><td colspan="1" valign="top" align="center">L</td><td align="center" colspan="1" valign="top">14079</td><td align="center" colspan="1" valign="top">14147</td><td colspan="1" valign="top" align="center">69</td><td valign="top" align="center" colspan="1">-</td><td align="center" colspan="1" valign="top">-</td><td align="center" colspan="1" valign="top">TTC</td></tr><tr><td align="left" colspan="1" valign="top">nad6</td><td valign="top" align="center" colspan="1">ND6</td><td colspan="1" valign="top" align="center">L</td><td valign="top" align="center" colspan="1">13551</td><td valign="top" align="center" colspan="1">14078</td><td valign="top" align="center" colspan="1">528</td><td valign="top" align="center" colspan="1">ATG</td><td align="center" colspan="1" valign="top">TAA</td><td align="center" colspan="1" valign="top">-</td></tr><tr><td colspan="1" valign="top" align="left">nad5</td><td valign="top" align="center" colspan="1">ND5</td><td colspan="1" valign="top" align="center">H</td><td valign="top" align="center" colspan="1">11747</td><td align="center" colspan="1" valign="top">13567</td><td valign="top" align="center" colspan="1">1821</td><td valign="top" align="center" colspan="1">ATA</td><td colspan="1" valign="top" align="center">TAA</td><td valign="top" align="center" colspan="1">-</td></tr><tr><td align="left" colspan="1" valign="top">trnL1</td><td valign="top" align="center" colspan="1">tRNA-Leu</td><td align="center" colspan="1" valign="top">H</td><td valign="top" align="center" colspan="1">11677</td><td valign="top" align="center" colspan="1">11746</td><td align="center" colspan="1" valign="top">70</td><td align="center" colspan="1" valign="top">-</td><td valign="top" align="center" colspan="1">-</td><td valign="top" align="center" colspan="1">TAG</td></tr><tr><td valign="top" align="left" colspan="1">trnS1</td><td valign="top" align="center" colspan="1">tRNA_ser</td><td align="center" colspan="1" valign="top">H</td><td valign="top" align="center" colspan="1">11616</td><td align="center" colspan="1" valign="top">11675</td><td align="center" colspan="1" valign="top">60</td><td align="center" colspan="1" valign="top">-</td><td valign="top" align="center" colspan="1">-</td><td align="center" colspan="1" valign="top">GCT</td></tr><tr><td valign="top" align="left" colspan="1">trnH</td><td valign="top" align="center" colspan="1">tRNA-His</td><td colspan="1" valign="top" align="center">H</td><td valign="top" align="center" colspan="1">11546</td><td align="center" colspan="1" valign="top">11615</td><td valign="top" align="center" colspan="1">70</td><td align="center" colspan="1" valign="top">-</td><td colspan="1" valign="top" align="center">-</td><td align="center" colspan="1" valign="top">GTG</td></tr><tr><td valign="top" align="left" colspan="1">nad4</td><td align="center" colspan="1" valign="top">ND4</td><td align="center" colspan="1" valign="top">H</td><td valign="top" align="center" colspan="1">10168</td><td valign="top" align="center" colspan="1">11545</td><td valign="top" align="center" colspan="1">1378</td><td valign="top" align="center" colspan="1">ATG</td><td valign="top" align="center" colspan="1">T--</td><td align="center" colspan="1" valign="top">-</td></tr><tr><td valign="top" align="left" colspan="1">nad4l</td><td align="center" colspan="1" valign="top">ND4L</td><td valign="top" align="center" colspan="1">H</td><td valign="top" align="center" colspan="1">9878</td><td align="center" colspan="1" valign="top">10174</td><td align="center" colspan="1" valign="top">297</td><td valign="top" align="center" colspan="1">ATG</td><td align="center" colspan="1" valign="top">TAA</td><td valign="top" align="center" colspan="1">-</td></tr><tr><td align="left" colspan="1" valign="top">trnR</td><td valign="top" align="center" colspan="1">tRNA-Arg</td><td valign="top" align="center" colspan="1">H</td><td align="center" colspan="1" valign="top">9808</td><td align="center" colspan="1" valign="top">9877</td><td align="center" colspan="1" valign="top">70</td><td valign="top" align="center" colspan="1">-</td><td align="center" colspan="1" valign="top">-</td><td align="center" colspan="1" valign="top">TCG</td></tr><tr><td align="left" colspan="1" valign="top">nad3</td><td valign="top" align="center" colspan="1">ND3</td><td valign="top" align="center" colspan="1">H</td><td valign="top" align="center" colspan="1">9461</td><td valign="top" align="center" colspan="1">9806</td><td valign="top" align="center" colspan="1">346</td><td valign="top" align="center" colspan="1">ATA</td><td align="center" colspan="1" valign="top">T--</td><td align="center" colspan="1" valign="top">-</td></tr><tr><td valign="top" align="left" colspan="1">trnG</td><td colspan="1" valign="top" align="center">tRNA-Gly</td><td valign="top" align="center" colspan="1">H</td><td valign="top" align="center" colspan="1">9392</td><td align="center" colspan="1" valign="top">9460</td><td valign="top" align="center" colspan="1">69</td><td valign="top" align="center" colspan="1">-</td><td align="center" colspan="1" valign="top">-</td><td valign="top" align="center" colspan="1">TCC</td></tr><tr><td colspan="1" valign="top" align="left">COX3</td><td align="center" colspan="1" valign="top">COX3</td><td valign="top" align="center" colspan="1">H</td><td align="center" colspan="1" valign="top">8608</td><td align="center" colspan="1" valign="top">9391</td><td valign="top" align="center" colspan="1">784</td><td align="center" colspan="1" valign="top">ATG</td><td align="center" colspan="1" valign="top">T--</td><td colspan="1" valign="top" align="center">-</td></tr><tr><td valign="top" align="left" colspan="1">ATP6</td><td valign="top" align="center" colspan="1">ATP6</td><td valign="top" align="center" colspan="1">H</td><td valign="top" align="center" colspan="1">7928</td><td valign="top" align="center" colspan="1">8608</td><td align="center" colspan="1" valign="top">681</td><td align="center" colspan="1" valign="top">ATG</td><td align="center" colspan="1" valign="top">TAA</td><td valign="top" align="center" colspan="1">-</td></tr><tr><td valign="top" align="left" colspan="1">ATP8</td><td align="center" colspan="1" valign="top">ATP8</td><td align="center" colspan="1" valign="top">H</td><td valign="top" align="center" colspan="1">7767</td><td valign="top" align="center" colspan="1">7967</td><td colspan="1" valign="top" align="center">201</td><td align="center" colspan="1" valign="top">ATG</td><td valign="top" align="center" colspan="1">TAA</td><td valign="top" align="center" colspan="1">-</td></tr><tr><td colspan="1" valign="top" align="left">trnK</td><td align="center" colspan="1" valign="top">tRNA-Lys</td><td valign="top" align="center" colspan="1">H</td><td colspan="1" valign="top" align="center">7699</td><td align="center" colspan="1" valign="top">7765</td><td valign="top" align="center" colspan="1">67</td><td valign="top" align="center" colspan="1">-</td><td colspan="1" valign="top" align="center">-</td><td valign="top" align="center" colspan="1">TTT</td></tr><tr><td valign="top" align="left" colspan="1">COX2</td><td align="center" colspan="1" valign="top">COX2</td><td align="center" colspan="1" valign="top">H</td><td valign="top" align="center" colspan="1">7012</td><td valign="top" align="center" colspan="1">7695</td><td valign="top" align="center" colspan="1">684</td><td valign="top" align="center" colspan="1">ATG</td><td valign="top" align="center" colspan="1">TAA</td><td align="center" colspan="1" valign="top">-</td></tr><tr><td align="left" colspan="1" valign="top">trnD</td><td colspan="1" valign="top" align="center">tRNA-Asp</td><td valign="top" align="center" colspan="1">H</td><td valign="top" align="center" colspan="1">6943</td><td valign="top" align="center" colspan="1">7010</td><td colspan="1" valign="top" align="center">68</td><td valign="top" align="center" colspan="1">-</td><td valign="top" align="center" colspan="1">-</td><td valign="top" align="center" colspan="1">GTC</td></tr><tr><td align="left" colspan="1" valign="top">trnS2</td><td valign="top" align="center" colspan="1">tRNA-Ser</td><td valign="top" align="center" colspan="1">L</td><td valign="top" align="center" colspan="1">6867</td><td valign="top" align="center" colspan="1">6937</td><td align="center" colspan="1" valign="top">71</td><td align="center" colspan="1" valign="top">-</td><td valign="top" align="center" colspan="1">-</td><td valign="top" align="center" colspan="1">TGA</td></tr><tr><td valign="top" align="left" colspan="1">COX1</td><td colspan="1" valign="top" align="center">COX1</td><td align="center" colspan="1" valign="top">H</td><td valign="top" align="center" colspan="1">5325</td><td align="center" colspan="1" valign="top">6869</td><td valign="top" align="center" colspan="1">1545</td><td align="center" colspan="1" valign="top">ATG</td><td align="center" colspan="1" valign="top">TAA</td><td align="center" colspan="1" valign="top">-</td></tr><tr><td align="left" colspan="1" valign="top">trnY</td><td valign="top" align="center" colspan="1">tRNA-Tyr</td><td colspan="1" valign="top" align="center">L</td><td valign="top" align="center" colspan="1">5256</td><td align="center" colspan="1" valign="top">5323</td><td valign="top" align="center" colspan="1">68</td><td align="center" colspan="1" valign="top">-</td><td valign="top" align="center" colspan="1">-</td><td align="center" colspan="1" valign="top">GTA</td></tr><tr><td valign="top" align="left" colspan="1">trnC</td><td valign="top" align="center" colspan="1">tRNA-Cys</td><td colspan="1" valign="top" align="center">L</td><td valign="top" align="center" colspan="1">5189</td><td align="center" colspan="1" valign="top">5255</td><td valign="top" align="center" colspan="1">67</td><td valign="top" align="center" colspan="1">-</td><td valign="top" align="center" colspan="1">-</td><td valign="top" align="center" colspan="1">GCA</td></tr><tr><td valign="top" align="left" colspan="1">trnN</td><td valign="top" align="center" colspan="1">tRNA-Asn</td><td align="center" colspan="1" valign="top">L</td><td align="center" colspan="1" valign="top">5084</td><td valign="top" align="center" colspan="1">5156</td><td align="center" colspan="1" valign="top">73</td><td align="center" colspan="1" valign="top">-</td><td align="center" colspan="1" valign="top">-</td><td align="center" colspan="1" valign="top">GTT</td></tr><tr><td valign="top" align="left" colspan="1">trnA</td><td valign="top" align="center" colspan="1">tRNA-Ala</td><td valign="top" align="center" colspan="1">L</td><td colspan="1" valign="top" align="center">5014</td><td align="center" colspan="1" valign="top">5082</td><td valign="top" align="center" colspan="1">69</td><td colspan="1" valign="top" align="center">-</td><td align="center" colspan="1" valign="top">-</td><td valign="top" align="center" colspan="1">TGC</td></tr><tr><td align="left" colspan="1" valign="top">trnW</td><td colspan="1" valign="top" align="center">tRNA-Trp</td><td valign="top" align="center" colspan="1">H</td><td valign="top" align="center" colspan="1">4946</td><td valign="top" align="center" colspan="1">5012</td><td align="center" colspan="1" valign="top">67</td><td valign="top" align="center" colspan="1">-</td><td align="center" colspan="1" valign="top">-</td><td valign="top" align="center" colspan="1">TCA</td></tr><tr><td align="left" colspan="1" valign="top">nad2</td><td valign="top" align="center" colspan="1">ND2</td><td valign="top" align="center" colspan="1">H</td><td valign="top" align="center" colspan="1">3904</td><td valign="top" align="center" colspan="1">4945</td><td valign="top" align="center" colspan="1">1042</td><td colspan="1" valign="top" align="center">ATA</td><td valign="top" align="center" colspan="1">T--</td><td valign="top" align="center" colspan="1">-</td></tr><tr><td valign="top" align="left" colspan="1">trnM</td><td valign="top" align="center" colspan="1">tRNA-Met</td><td valign="top" align="center" colspan="1">H</td><td valign="top" align="center" colspan="1">3835</td><td valign="top" align="center" colspan="1">3903</td><td align="center" colspan="1" valign="top">69</td><td align="center" colspan="1" valign="top">-</td><td align="center" colspan="1" valign="top">-</td><td valign="top" align="center" colspan="1">CAT</td></tr><tr><td colspan="1" valign="top" align="left">trnQ</td><td valign="top" align="center" colspan="1">tRNA-Gln</td><td valign="top" align="center" colspan="1">L</td><td align="center" colspan="1" valign="top">3761</td><td align="center" colspan="1" valign="top">3832</td><td align="center" colspan="1" valign="top">72</td><td align="center" colspan="1" valign="top">-</td><td valign="top" align="center" colspan="1">-</td><td align="center" colspan="1" valign="top">TTG</td></tr><tr><td valign="top" align="left" colspan="1">trnI</td><td align="center" colspan="1" valign="top">tRNA-Ile</td><td align="center" colspan="1" valign="top">H</td><td align="center" colspan="1" valign="top">3695</td><td align="center" colspan="1" valign="top">3763</td><td valign="top" align="center" colspan="1">69</td><td colspan="1" valign="top" align="center">-</td><td valign="top" align="center" colspan="1">-</td><td align="center" colspan="1" valign="top">GAT</td></tr><tr><td align="left" colspan="1" valign="top">nad1</td><td valign="top" align="center" colspan="1">ND1</td><td valign="top" align="center" colspan="1">H</td><td valign="top" align="center" colspan="1">2739</td><td valign="top" align="center" colspan="1">3694</td><td colspan="1" valign="top" align="center">956</td><td colspan="1" valign="top" align="center">ATG</td><td align="center" colspan="1" valign="top">TA-</td><td align="center" colspan="1" valign="top">-</td></tr><tr><td valign="top" align="left" colspan="1">trnL2</td><td align="center" colspan="1" valign="top">tRNA-Leu</td><td valign="top" align="center" colspan="1">H</td><td align="center" colspan="1" valign="top">2662</td><td align="center" colspan="1" valign="top">2736</td><td align="center" colspan="1" valign="top">75</td><td valign="top" align="center" colspan="1">-</td><td valign="top" align="center" colspan="1">-</td><td valign="top" align="center" colspan="1">TAA</td></tr><tr><td colspan="1" valign="top" align="left">rrn 16</td><td valign="top" align="center" colspan="1">16S rRNA</td><td colspan="1" valign="top" align="center">H</td><td valign="top" align="center" colspan="1">1162</td><td valign="top" align="center" colspan="1">2661</td><td align="center" colspan="1" valign="top">1500</td><td valign="top" align="center" colspan="1">-</td><td colspan="1" valign="top" align="center">-</td><td align="center" colspan="1" valign="top">-</td></tr><tr><td colspan="1" valign="top" align="left">trnV</td><td valign="top" align="center" colspan="1">tRNA-Val</td><td valign="top" align="center" colspan="1">H</td><td valign="top" align="center" colspan="1">1023</td><td valign="top" align="center" colspan="1">1089</td><td valign="top" align="center" colspan="1">68</td><td valign="top" align="center" colspan="1">-</td><td valign="top" align="center" colspan="1">-</td><td valign="top" align="center" colspan="1">TAC</td></tr><tr><td valign="top" align="left" colspan="1">rrn 12</td><td align="center" colspan="1" valign="top">12S rRNA</td><td align="center" colspan="1" valign="top">H</td><td valign="top" align="center" colspan="1">67</td><td valign="top" align="center" colspan="1">1021</td><td valign="top" align="center" colspan="1">955</td><td colspan="1" valign="top" align="center">-</td><td valign="top" align="center" colspan="1">-</td><td valign="top" align="center" colspan="1">-</td></tr><tr><td colspan="1" valign="top" align="left">trnF</td><td align="center" colspan="1" valign="top">tRNA-Phe</td><td align="center" colspan="1" valign="top">H</td><td valign="top" align="center" colspan="1">1</td><td align="center" colspan="1" valign="top">66</td><td align="center" colspan="1" valign="top">66</td><td valign="top" align="center" colspan="1">-</td><td align="center" colspan="1" valign="top">-</td><td valign="top" align="center" colspan="1">GAA</td></tr></tbody></table></table-wrap><fig id="figure-2" ignoredToc=""><label>Figure 1</label><caption><p>Annotation of the complete mitochondrial genome of Madura cattle</p></caption><graphic mime-subtype="png" mimetype="image" xlink:href="https://journal.ipb.ac.id/tasj/article/download/72999/version/53495/34456/420154"><alt-text>Image</alt-text></graphic></fig><fig id="figure-1" ignoredToc=""><label>Figure 2</label><caption><p>AT-skewness and GC-skewness profiles of 13 Protein-coding genes (PCGs) in Madura cattle.</p></caption><graphic mime-subtype="jpg" mimetype="image" xlink:href="https://journal.ipb.ac.id/tasj/article/download/72999/version/53495/34456/420155"><alt-text>Image</alt-text></graphic></fig></sec><sec><title>Relative Synonymous Codon Usage (RSCU) </title><p>Analysis of Relative Synonymous Codon Usage (RSCU) in the protein-coding genes (PCGs) of the Madura cattle mtDNA genome showed variation in synonymous codon usage. Analysis of the Relative Synonymous Codon Usage (RSCU) in protein-coding genes (PCGs) of the Madura cattle mtDNA genome shows a strong preference for codons ending in Adenine (A). The highest RSCU values were observed for CGA (Arg, 3.182), CTA (Leu, 2.808), GTA (Val, 2.172), TCA (Ser, 2.161), and ACA (Thr, 1.934). Based on codon counts, the most frequently represented amino acids were leucine (Leu, 532 codons), isoleucine (Ile, 481 codons), threonine (Thr, 304 codons), serine (Ser, 261 codons), and alanine (Ala, 211 codons) (<xref ref-type="fig" rid="figure-3">Figure 3</xref> and <xref ref-type="table" rid="table-2">Table 2</xref>). </p></sec><sec><title>Transfer RNA (tRNA) Genes and Secondary Structure</title><p>Twenty-two tRNA genes were identified, with a total length of approximately 1515 bp. The length of each gene ranged from 60 bp (tRNA-Ser) to 75 bp (tRNA-Leu2). Based on the tRNA structure visualization results, Madura cattle tRNA forms a cloverleaf secondary structure. However, several mitochondrial tRNAs show deviations from this structure, namely trnS1 (tRNA-Ser1) and trnK (tRNA-Lys) (<xref rid="figure-4" ref-type="fig">Figure 4</xref>).</p><table-wrap ignoredToc="" id="table-2"><label>Table 2</label><caption><p> Relative Synonymous Codon Usage (RSCU) values and codon counts in the mitochondrial genome sequence of Madura cattle</p></caption><table frame="box" rules="all"><thead><tr><th colspan="1" valign="top" align="center"><bold>No.</bold></th><th valign="top" align="center" colspan="1"><bold>Codon</bold></th><th colspan="1" valign="top" align="center"><bold>Amino acid</bold></th><th align="center" colspan="1" valign="top"><bold>Codon count</bold></th><th valign="top" align="center" colspan="1"><bold>RSCU</bold></th></tr></thead><tbody><tr><td colspan="1" valign="top" align="center">1</td><td valign="top" align="center" colspan="1">TTT</td><td align="center" colspan="1" valign="top">Phenylalanine (Phe)</td><td valign="top" align="center" colspan="1">87</td><td valign="top" align="center" colspan="1">0.845</td></tr><tr><td valign="top" align="center" colspan="1">2</td><td valign="top" align="center" colspan="1">TTC</td><td valign="top" align="center" colspan="1">Phenylalanine (Phe)</td><td colspan="1" valign="top" align="center">119</td><td valign="top" align="center" colspan="1">1.155</td></tr><tr><td valign="top" align="center" colspan="1">3</td><td align="center" colspan="1" valign="top">TTA</td><td align="center" colspan="1" valign="top">Leucine (Leu)</td><td align="center" colspan="1" valign="top">87</td><td valign="top" align="center" colspan="1">0.981</td></tr><tr><td valign="top" align="center" colspan="1">4</td><td align="center" colspan="1" valign="top">TTG</td><td align="center" colspan="1" valign="top">Leucine (Leu)</td><td align="center" colspan="1" valign="top">7</td><td colspan="1" valign="top" align="center">0.079</td></tr><tr><td align="center" colspan="1" valign="top">5</td><td valign="top" align="center" colspan="1">CTT</td><td align="center" colspan="1" valign="top">Leucine (Leu)</td><td colspan="1" valign="top" align="center">55</td><td valign="top" align="center" colspan="1">0.620</td></tr><tr><td align="center" colspan="1" valign="top">6</td><td colspan="1" valign="top" align="center">CTC</td><td colspan="1" valign="top" align="center">Leucine (Leu)</td><td align="center" colspan="1" valign="top">95</td><td valign="top" align="center" colspan="1">1.071</td></tr><tr><td valign="top" align="center" colspan="1">7</td><td colspan="1" valign="top" align="center">CTA</td><td align="center" colspan="1" valign="top">Leucine (Leu)</td><td valign="top" align="center" colspan="1">249</td><td align="center" colspan="1" valign="top">2.808</td></tr><tr><td colspan="1" valign="top" align="center">8</td><td align="center" colspan="1" valign="top">CTG</td><td valign="top" align="center" colspan="1">Leucine (Leu)</td><td valign="top" align="center" colspan="1">39</td><td valign="top" align="center" colspan="1">0.440</td></tr><tr><td valign="top" align="center" colspan="1">9</td><td valign="top" align="center" colspan="1">ATT</td><td align="center" colspan="1" valign="top">Isoleucine (Ile)</td><td align="center" colspan="1" valign="top">152</td><td align="center" colspan="1" valign="top">0.948</td></tr><tr><td align="center" colspan="1" valign="top">10</td><td colspan="1" valign="top" align="center">ATC</td><td valign="top" align="center" colspan="1">Isoleucine (Ile)</td><td valign="top" align="center" colspan="1">130</td><td valign="top" align="center" colspan="1">0.811</td></tr><tr><td align="center" colspan="1" valign="top">11</td><td align="center" colspan="1" valign="top">ATA</td><td valign="top" align="center" colspan="1">Isoleucine (Ile)</td><td valign="top" align="center" colspan="1">199</td><td valign="top" align="center" colspan="1">1.241</td></tr><tr><td valign="top" align="center" colspan="1">12</td><td align="center" colspan="1" valign="top">ATG</td><td align="center" colspan="1" valign="top">Methionine (Met)</td><td valign="top" align="center" colspan="1">41</td><td align="center" colspan="1" valign="top">1.000</td></tr><tr><td align="center" colspan="1" valign="top">13</td><td align="center" colspan="1" valign="top">GTT</td><td colspan="1" valign="top" align="center">Valine (Val)</td><td valign="top" align="center" colspan="1">25</td><td align="center" colspan="1" valign="top">0.662</td></tr><tr><td valign="top" align="center" colspan="1">14</td><td align="center" colspan="1" valign="top">GTC</td><td colspan="1" valign="top" align="center">Valine (Val)</td><td align="center" colspan="1" valign="top">38</td><td align="center" colspan="1" valign="top">1.007</td></tr><tr><td valign="top" align="center" colspan="1">15</td><td valign="top" align="center" colspan="1">GTA</td><td align="center" colspan="1" valign="top">Valine (Val)</td><td align="center" colspan="1" valign="top">82</td><td align="center" colspan="1" valign="top">2.172</td></tr><tr><td colspan="1" valign="top" align="center">16</td><td valign="top" align="center" colspan="1">GTG</td><td valign="top" align="center" colspan="1">Valine (Val)</td><td colspan="1" valign="top" align="center">6</td><td align="center" colspan="1" valign="top">0.159</td></tr><tr><td valign="top" align="center" colspan="1">17</td><td valign="top" align="center" colspan="1">TCT</td><td valign="top" align="center" colspan="1">Serine (Ser)</td><td valign="top" align="center" colspan="1">44</td><td align="center" colspan="1" valign="top">1.011</td></tr><tr><td align="center" colspan="1" valign="top">18</td><td align="center" colspan="1" valign="top">TCC</td><td valign="top" align="center" colspan="1">Serine (Ser)</td><td colspan="1" valign="top" align="center">59</td><td align="center" colspan="1" valign="top">1.356</td></tr><tr><td valign="top" align="center" colspan="1">19</td><td align="center" colspan="1" valign="top">TCA</td><td valign="top" align="center" colspan="1">Serine (Ser)</td><td colspan="1" valign="top" align="center">94</td><td valign="top" align="center" colspan="1">2.161</td></tr><tr><td align="center" colspan="1" valign="top">20</td><td valign="top" align="center" colspan="1">TCG</td><td valign="top" align="center" colspan="1">Serine (Ser)</td><td colspan="1" valign="top" align="center">7</td><td valign="top" align="center" colspan="1">0.161</td></tr><tr><td valign="top" align="center" colspan="1">21</td><td align="center" colspan="1" valign="top">CCT</td><td align="center" colspan="1" valign="top">Proline (Pro)</td><td colspan="1" valign="top" align="center">35</td><td colspan="1" valign="top" align="center">0.769</td></tr><tr><td align="center" colspan="1" valign="top">22</td><td align="center" colspan="1" valign="top">CCC</td><td align="center" colspan="1" valign="top">Proline (Pro)</td><td valign="top" align="center" colspan="1">69</td><td align="center" colspan="1" valign="top">1.516</td></tr><tr><td colspan="1" valign="top" align="center">23</td><td colspan="1" valign="top" align="center">CCA</td><td valign="top" align="center" colspan="1">Proline (Pro)</td><td valign="top" align="center" colspan="1">72</td><td align="center" colspan="1" valign="top">1.582</td></tr><tr><td align="center" colspan="1" valign="top">24</td><td valign="top" align="center" colspan="1">CCG</td><td valign="top" align="center" colspan="1">Proline (Pro)</td><td valign="top" align="center" colspan="1">6</td><td align="center" colspan="1" valign="top">0.132</td></tr><tr><td align="center" colspan="1" valign="top">25</td><td valign="top" align="center" colspan="1">ACT</td><td valign="top" align="center" colspan="1">Threonine (Thr)</td><td valign="top" align="center" colspan="1">46</td><td valign="top" align="center" colspan="1">0.605</td></tr><tr><td valign="top" align="center" colspan="1">26</td><td align="center" colspan="1" valign="top">ACC</td><td align="center" colspan="1" valign="top">Threonine (Thr)</td><td colspan="1" valign="top" align="center">98</td><td valign="top" align="center" colspan="1">1.289</td></tr><tr><td colspan="1" valign="top" align="center">27</td><td valign="top" align="center" colspan="1">ACA</td><td valign="top" align="center" colspan="1">Threonine (Thr)</td><td align="center" colspan="1" valign="top">147</td><td valign="top" align="center" colspan="1">1.934</td></tr><tr><td align="center" colspan="1" valign="top">28</td><td valign="top" align="center" colspan="1">ACG</td><td align="center" colspan="1" valign="top">Threonine (Thr)</td><td align="center" colspan="1" valign="top">13</td><td valign="top" align="center" colspan="1">0.171</td></tr><tr><td align="center" colspan="1" valign="top">29</td><td align="center" colspan="1" valign="top">GCT</td><td valign="top" align="center" colspan="1">Alanine (Ala)</td><td align="center" colspan="1" valign="top">39</td><td valign="top" align="center" colspan="1">0.739</td></tr><tr><td valign="top" align="center" colspan="1">30</td><td align="center" colspan="1" valign="top">GCC</td><td align="center" colspan="1" valign="top">Alanine (Ala)</td><td align="center" colspan="1" valign="top">82</td><td valign="top" align="center" colspan="1">1.555</td></tr><tr><td colspan="1" valign="top" align="center">31</td><td valign="top" align="center" colspan="1">GCA</td><td colspan="1" valign="top" align="center">Alanine (Ala)</td><td valign="top" align="center" colspan="1">87</td><td align="center" colspan="1" valign="top">1.649</td></tr><tr><td align="center" colspan="1" valign="top">32</td><td colspan="1" valign="top" align="center">GCG</td><td valign="top" align="center" colspan="1">Alanine (Ala)</td><td align="center" colspan="1" valign="top">3</td><td align="center" colspan="1" valign="top">0.057</td></tr><tr><td valign="top" align="center" colspan="1">33</td><td valign="top" align="center" colspan="1">TAT</td><td valign="top" align="center" colspan="1">Tyrosine (Tyr)</td><td valign="top" align="center" colspan="1">46</td><td valign="top" align="center" colspan="1">0.780</td></tr><tr><td valign="top" align="center" colspan="1">34</td><td align="center" colspan="1" valign="top">TAC</td><td valign="top" align="center" colspan="1">Tyrosine (Tyr)</td><td colspan="1" valign="top" align="center">72</td><td valign="top" align="center" colspan="1">1.220</td></tr><tr><td align="center" colspan="1" valign="top">35</td><td valign="top" align="center" colspan="1">CAT</td><td align="center" colspan="1" valign="top">Histidine (His)</td><td colspan="1" valign="top" align="center">33</td><td valign="top" align="center" colspan="1">0.660</td></tr><tr><td valign="top" align="center" colspan="1">36</td><td align="center" colspan="1" valign="top">CAC</td><td align="center" colspan="1" valign="top">Histidine (His)</td><td valign="top" align="center" colspan="1">67</td><td valign="top" align="center" colspan="1">1.340</td></tr><tr><td valign="top" align="center" colspan="1">37</td><td valign="top" align="center" colspan="1">CAA</td><td align="center" colspan="1" valign="top">Glutamine (Gln)</td><td align="center" colspan="1" valign="top">83</td><td valign="top" align="center" colspan="1">1.908</td></tr><tr><td align="center" colspan="1" valign="top">38</td><td align="center" colspan="1" valign="top">CAG</td><td align="center" colspan="1" valign="top">Glutamine (Gln)</td><td valign="top" align="center" colspan="1">4</td><td valign="top" align="center" colspan="1">0.092</td></tr><tr><td align="center" colspan="1" valign="top">39</td><td align="center" colspan="1" valign="top">AAT</td><td align="center" colspan="1" valign="top">Asparagine (Asn)</td><td colspan="1" valign="top" align="center">76</td><td colspan="1" valign="top" align="center">0.910</td></tr><tr><td valign="top" align="center" colspan="1">40</td><td valign="top" align="center" colspan="1">AAC</td><td colspan="1" valign="top" align="center">Asparagine (Asn)</td><td valign="top" align="center" colspan="1">91</td><td valign="top" align="center" colspan="1">1.090</td></tr><tr><td align="center" colspan="1" valign="top">41</td><td valign="top" align="center" colspan="1">AAA</td><td valign="top" align="center" colspan="1">Lysine (Lys)</td><td align="center" colspan="1" valign="top">88</td><td align="center" colspan="1" valign="top">1.692</td></tr><tr><td align="center" colspan="1" valign="top">42</td><td valign="top" align="center" colspan="1">AAG</td><td align="center" colspan="1" valign="top">Lysine (Lys)</td><td valign="top" align="center" colspan="1">16</td><td align="center" colspan="1" valign="top">0.308</td></tr><tr><td valign="top" align="center" colspan="1">43</td><td valign="top" align="center" colspan="1">GAT</td><td valign="top" align="center" colspan="1">Aspartic acid (Asp)</td><td colspan="1" valign="top" align="center">19</td><td align="center" colspan="1" valign="top">0.731</td></tr><tr><td valign="top" align="center" colspan="1">44</td><td colspan="1" valign="top" align="center">GAC</td><td colspan="1" valign="top" align="center">Aspartic acid (Asp)</td><td align="center" colspan="1" valign="top">33</td><td colspan="1" valign="top" align="center">1.269</td></tr><tr><td valign="top" align="center" colspan="1">45</td><td valign="top" align="center" colspan="1">GAA</td><td valign="top" align="center" colspan="1">Glutamic acid (Glu)</td><td colspan="1" valign="top" align="center">70</td><td valign="top" align="center" colspan="1">1.707</td></tr><tr><td valign="top" align="center" colspan="1">46</td><td valign="top" align="center" colspan="1">GAG</td><td valign="top" align="center" colspan="1">Glutamic acid (Glu)</td><td align="center" colspan="1" valign="top">12</td><td valign="top" align="center" colspan="1">0.293</td></tr><tr><td valign="top" align="center" colspan="1">47</td><td valign="top" align="center" colspan="1">TGT</td><td valign="top" align="center" colspan="1">Cysteine (Cys)</td><td align="center" colspan="1" valign="top">7</td><td valign="top" align="center" colspan="1">0.667</td></tr><tr><td valign="top" align="center" colspan="1">48</td><td align="center" colspan="1" valign="top">TGC</td><td valign="top" align="center" colspan="1">Cysteine (Cys)</td><td colspan="1" valign="top" align="center">14</td><td align="center" colspan="1" valign="top">1.333</td></tr><tr><td valign="top" align="center" colspan="1">49</td><td align="center" colspan="1" valign="top">TGG</td><td valign="top" align="center" colspan="1">Tryptophan (Trp)</td><td valign="top" align="center" colspan="1">8</td><td valign="top" align="center" colspan="1">1.000</td></tr><tr><td valign="top" align="center" colspan="1">50</td><td valign="top" align="center" colspan="1">CGT</td><td align="center" colspan="1" valign="top">Arginine (Arg)</td><td valign="top" align="center" colspan="1">6</td><td align="center" colspan="1" valign="top">0.545</td></tr><tr><td align="center" colspan="1" valign="top">51</td><td align="center" colspan="1" valign="top">CGC</td><td valign="top" align="center" colspan="1">Arginine (Arg)</td><td align="center" colspan="1" valign="top">15</td><td valign="top" align="center" colspan="1">1.364</td></tr><tr><td colspan="1" valign="top" align="center">52</td><td align="center" colspan="1" valign="top">CGA</td><td align="center" colspan="1" valign="top">Arginine (Arg)</td><td align="center" colspan="1" valign="top">35</td><td align="center" colspan="1" valign="top">3.182</td></tr><tr><td colspan="1" valign="top" align="center">53</td><td valign="top" align="center" colspan="1">CGG</td><td colspan="1" valign="top" align="center">Arginine (Arg)</td><td align="center" colspan="1" valign="top">2</td><td colspan="1" valign="top" align="center">0.182</td></tr><tr><td align="center" colspan="1" valign="top">54</td><td valign="top" align="center" colspan="1">AGT</td><td align="center" colspan="1" valign="top">Serine (Ser)</td><td valign="top" align="center" colspan="1">15</td><td align="center" colspan="1" valign="top">0.345</td></tr><tr><td align="center" colspan="1" valign="top">55</td><td align="center" colspan="1" valign="top">AGC</td><td align="center" colspan="1" valign="top">Serine (Ser)</td><td valign="top" align="center" colspan="1">42</td><td colspan="1" valign="top" align="center">0.966</td></tr><tr><td valign="top" align="center" colspan="1">56</td><td valign="top" align="center" colspan="1">AGA</td><td align="center" colspan="1" valign="top">Arginine (Arg)</td><td valign="top" align="center" colspan="1">5</td><td align="center" colspan="1" valign="top">0.455</td></tr><tr><td valign="top" align="center" colspan="1">57</td><td valign="top" align="center" colspan="1">AGG</td><td align="center" colspan="1" valign="top">Arginine (Arg)</td><td valign="top" align="center" colspan="1">3</td><td valign="top" align="center" colspan="1">0.273</td></tr><tr><td align="center" colspan="1" valign="top">58</td><td valign="top" align="center" colspan="1">GGT</td><td valign="top" align="center" colspan="1">Glycine (Gly)</td><td valign="top" align="center" colspan="1">22</td><td valign="top" align="center" colspan="1">0.512</td></tr><tr><td align="center" colspan="1" valign="top">59</td><td valign="top" align="center" colspan="1">GGC</td><td align="center" colspan="1" valign="top">Glycine (Gly)</td><td align="center" colspan="1" valign="top">54</td><td valign="top" align="center" colspan="1">1.256</td></tr><tr><td valign="top" align="center" colspan="1">60</td><td valign="top" align="center" colspan="1">GGA</td><td valign="top" align="center" colspan="1">Glycine (Gly)</td><td valign="top" align="center" colspan="1">81</td><td align="center" colspan="1" valign="top">1.884</td></tr><tr><td align="center" colspan="1" valign="top">61</td><td align="center" colspan="1" valign="top">GGG</td><td align="center" colspan="1" valign="top">Glycine (Gly)</td><td colspan="1" valign="top" align="center">15</td><td valign="top" align="center" colspan="1">0.349</td></tr></tbody></table></table-wrap><fig id="figure-3" ignoredToc=""><label>Figure 3</label><caption><p>Relative Synonymous codon usage (RSCU) of mitochondrial protein-coding genes (PCGs) and tRNA genes in Madura cattle </p></caption><graphic mime-subtype="jpg" mimetype="image" xlink:href="https://journal.ipb.ac.id/tasj/article/download/72999/version/53495/34456/420156"><alt-text>Image</alt-text></graphic></fig><fig ignoredToc="" id="figure-4"><label>Figure 4</label><caption><p>Predicted secondary structures of mitochondrial tRNAs in Madura cattle. </p></caption><p>Most tRNAs formed the typical cloverleaf structure consisting of the acceptor stem, D-arm, anticodon arm, TΨC arm, and variable loop, whereas trnS1 and trnK showed structural deviations in the DHU arm.</p><graphic mime-subtype="jpg" mimetype="image" xlink:href="https://journal.ipb.ac.id/tasj/article/download/72999/version/53495/34456/420157"><alt-text>Image</alt-text></graphic></fig></sec><sec><title>Genetic Distance of Madura Cattle</title><p>The mitochondrial genetic distance analysis based on complete mitogenome sequences showed distinct maternal relationships among the five Madura cattle samples and reference cattle breeds (<xref ref-type="fig" rid="figure-5">Figure 5</xref>). Madura cattle 1, 4, and 5 showed very low mitochondrial genetic distances to <italic>Bos indicus</italic>, ranging from 0.000 to 0.002, whereas Madura cattle 2 and 3 showed higher distances to <italic>B. indicus</italic>, ranging from 0.069 to 0.070. In contrast, Madura cattle 2 and 3 showed very low mitochondrial genetic distances to <italic>Bos javanicus</italic>, ranging from 0.000 to 0.001, while Madura cattle 1, 4, and 5 showed higher distances to <italic>B. javanicus</italic> of approximately 0.070. These results indicate the presence of two mitochondrial maternal lineages among the analyzed Madura cattle samples.</p></sec><sec><title>Phylogenetic Analysis</title><p>Phylogenetic reconstruction based on the complete mitochondrial genome revealed that Madura cattle formed two distinct clusters with high bootstrap support. Madura cattle 1, 4, and 5 clustered with <italic>B. indicus</italic>, supported by bootstrap values of 99-100. The second cluster consisted of Madura cattle 2 and 3, which grouped with <italic>B. javanicus </italic>accessions, also with bootstrap values of 99-100. The separation between the <italic>B. indicus</italic>-related and <italic>B. javanicus</italic>-related maternal lineages was also supported by a bootstrap value of 97 (<xref ref-type="fig" rid="figure-6">Figure 6</xref>).</p><fig id="figure-5" ignoredToc=""><label>Figure 5</label><caption><p>	Genetic distance between Madura cattle and reference cattle breeds from GenBank based on the complete mitochondrial genome, with genetic distance values (below the diagonal) and standard deviations (above the diagonal)</p></caption><graphic mime-subtype="jpg" mimetype="image" xlink:href="https://journal.ipb.ac.id/tasj/article/download/72999/version/53495/34456/420158"><alt-text>Image</alt-text></graphic></fig><fig ignoredToc="" id="figure-6"><label>Figure 6</label><caption><p>Phylogenetic tree based on complete mitochondrial genome sequences of Madura cattle and reference bovine species. </p></caption><p>Numbers at internal nodes indicate bootstrap support values based on 100 replicates. <italic>Bubalus bubalis</italic> was used as the outgroup.</p><graphic xlink:href="https://journal.ipb.ac.id/tasj/article/download/72999/version/53495/34456/420159" mime-subtype="jpg" mimetype="image"><alt-text>Image</alt-text></graphic></fig></sec></sec><sec><title>DISCUSSION</title><p>The mitochondrial genome features of Madura cattle, including sequence length, gene organization, and strand distribution, are consistent with those reported in<italic> Bos taurus</italic><xref ref-type="bibr" rid="BIBR-9">(Estrada et al., 2024)</xref>, <italic>B. indicus</italic><xref rid="BIBR-4" ref-type="bibr">(Arya et al., 2025)</xref>, <italic>B. javanicus</italic><xref ref-type="bibr" rid="BIBR-15">(Jakaria et al., 2025)</xref>, <italic>Bos grunniens</italic><xref ref-type="bibr" rid="BIBR-12">(Gu et al., 2007)</xref>, <italic>Bos gaurus</italic><xref ref-type="bibr" rid="BIBR-17">(Kamalakkannan et al., 2020)</xref>, and <italic>Bison bison</italic><xref ref-type="bibr" rid="BIBR-8">(Douglas et al., 2011)</xref>. All of which share a conserved mitochondrial genome length of approximately 16.3 kb, indicating a stable genomic architecture across vertebrates. Protein-coding genes (PCGs) in the mtDNA of Madura cattle show variation in the use of start and stop codons. The start codons in Madura cattle show no differences compared to those of <italic>B. javanicus</italic><xref ref-type="bibr" rid="BIBR-1">(Anwar et al., 2025)</xref>, <italic>Bos taurus </italic><xref ref-type="bibr" rid="BIBR-2">(Arbizu et al., 2022)</xref>, and<italic> B. grunniens </italic><xref ref-type="bibr" rid="BIBR-12">(Gu et al., 2007)</xref>. Meanwhile, the stop codons of the Madura cattle tend to be more varied compared to their codons, namely the stop codon AGA (cytB), TAA (ND6, ND5, ND4L, ATP6, ATP8, COX2, and COX1), TA- (ND1), and T- (ND4, ND3, COX3, and ND2).</p><p>The majority of vertebrates use TAA as the primary stop codon in their mitochondrial DNA (mtDNA) genomes. In the standard genetic code, the AGA and AGG codons code for the amino acid arginine, but in vertebrate mtDNA, they function as stop codons<xref ref-type="bibr" rid="BIBR-44">(Zhang et al., 2022)</xref>. The codon AGA also functions as an alternative codon that acts as a translation terminal signal, particularly in the cytB gene, and has been reported in several vertebrates, such as <italic>B. javanicus</italic><xref ref-type="bibr" rid="BIBR-1">(Anwar et al., 2025)</xref>, <italic>Mustela lutreola</italic><xref ref-type="bibr" rid="BIBR-34">(Skorupski, 2022)</xref>, <italic>B. taurus</italic><xref ref-type="bibr" rid="BIBR-9">(Estrada et al., 2024)</xref>, <italic>Mesechinus miodon </italic><xref ref-type="bibr" rid="BIBR-21">(Kong et al., 2016)</xref>, and <italic>Myotis muricola</italic><xref ref-type="bibr" rid="BIBR-43">(Yoon &amp; Park, 2015)</xref>. The pattern of incomplete stop codon usage (TA- and T--) in Madura cattle is also commonly found in other vertebrates; these codons become complete termination codons (TAA) after undergoing post-transcriptional polyadenylation at the 3’ end of the mRNA <xref rid="BIBR-34" ref-type="bibr">(Skorupski, 2022)</xref>, which is the addition of a poly (A) tail to the mRNA, thereby forming a complete stop codon sequence <xref ref-type="bibr" rid="BIBR-26">(Ojala et al., 1981)</xref>.</p><p>No differences were found in the use of stop codons in the mtDNA genome of Madura cattle compared to <italic>B. javanicus </italic><xref ref-type="bibr" rid="BIBR-15">(Jakaria et al., 2025)</xref>. However, differences were found in the stop codons of the genes ND3, COX3, and ND2 in <italic>B. taurus</italic>, especially TA- <xref rid="BIBR-9" ref-type="bibr">(Estrada et al., 2024)</xref>, whereas the stop codons in Madura cattle for those genes are T--. The Madura cattle stop codon differs from that of Bos grunniens, specifically the AGA stop codon, which is absent and replaced by TAG <xref ref-type="bibr" rid="BIBR-12">(Gu et al., 2007)</xref>. </p><p>The complete mitochondrial genomes of Madura cattle showed gene content and organization generally comparable to those of other Bovidae species. The difference in sequence length is due to the presence of a tandem repeat motif in the control region (D-loop) with the motif 5’-ATA AGT ACA TAA TAT TTA TGT A-3’ in samples Ma2 and Ma3, which was not found in samples Ma1, Ma4, and Ma5. The repeat motif in Ma2 was duplicated 6 times,  whereas in Ma3 it was duplicated only 3 times. The same repeat motif was also found in <italic>B. javanicus </italic><xref ref-type="bibr" rid="BIBR-1">(Anwar et al., 2025)</xref>; <xref ref-type="bibr" rid="BIBR-15">(Jakaria et al., 2025)</xref>. This motif was found only in the species <italic>B. javanicus</italic>. Therefore, it has great potential to serve as a marker for <italic>B. javanicus</italic><xref ref-type="bibr" rid="BIBR-15">(Jakaria et al., 2025)</xref>. To date, the function of repetitive motifs in the D-loop region remains poorly understood. However, it is hypothesized that these motifs act as an independent regulatory region that may enhance the efficiency of mtDNA replication and transcription, providing an adaptive advantage through greater flexibility in regulating energy production and cellular metabolism <xref ref-type="bibr" rid="BIBR-17">(Kamalakkannan et al., 2020)</xref>.</p><p>The nucleotide composition of the PCGs shows that 60.08% consists of adenine (A) and Thymine/uracil (T/U). Translation results indicate that the amino acid sequence of Madura cattle is generally similar to that of <italic>B. indicus</italic>, except for the ND3 gene, which is identical to that of <italic>B. javanicus</italic>. Two amino acid mutation sites were found to be unique to Madura cattle, consisting of a change in the ATP8 and ND5 genes from the amino acid phenylalanine (F) to leucine (L) at position 24, and a mutation from the amino acid valine (V) to isoleucine (I) at position 172.</p><p>The AT-skew values tend to be positive, and the GC-skew values tend to be negative, indicating a pattern of base composition asymmetry that reflects a nucleotide composition bias toward the bases adenine(A) and cytosine (C). This is consistent with the general characteristics of mtDNA genomes in mammalian groups, including the Bovidae family <xref ref-type="bibr" rid="BIBR-32">(Priyono et al., 2020)</xref>. At the gene level, AT-skew values vary among genes. In Madura cattle, the COX1, COX3, and ND6 genes exhibit negative AT-skew values, whereas the genes encoding the proteins (ND1, ND2, COX2, ATP8, ATP6, ND3, ND4L, ND4, ND5, and cytB) have positive values. The same pattern has been reported in<italic> B. javanicus </italic><xref rid="BIBR-1" ref-type="bibr">(Anwar et al., 2025)</xref>, <italic>B. indicus</italic><xref ref-type="bibr" rid="BIBR-4">(Arya et al., 2025)</xref>, <italic>Moschiola indica</italic><xref ref-type="bibr" rid="BIBR-33">(Sarvani et al., 2018)</xref>, and <italic>Bubalus bubalis</italic><xref ref-type="bibr" rid="BIBR-22">(Kumar De et al., 2019)</xref>. However, in Bubalus quarlesi, the AT-skew pattern exhibits a distinct characteristic; a negative AT-skew value was detected only in the ND6 gene, while other protein-coding genes maintained a positive AT-skew <xref ref-type="bibr" rid="BIBR-32">(Priyono et al., 2020)</xref>. These pattern differences indicate lineage-specific variations in mitochondrial nucleotide composition bias among Bovidae, which likely reflect differences in historical mutation pressure, mtDNA replication dynamics, or distinct maternal evolutionary backgrounds between the genera <xref ref-type="bibr" rid="BIBR-17">(Kamalakkannan et al., 2020)</xref>.</p><p>The RSCU pattern in Madura cattle indicates unequal usage of synonymous codons in mitochondrial protein-coding genes. Several codons with relatively high RSCU values ended with adenine, including CGA, CTA, and GTA, suggesting a tendency toward A-ending codon preference. A similar pattern was reported in Bali cattle (<italic>B. javanicus</italic>), where the codons with the highest RSCU values were CUA/CTA (Leu, 1.92), GUA/GTA (Val, 1.75), GGA (Gly, 1.64), and GCA (Ala, 1.54), and codons with adenine at the third codon position were preferentially used <xref ref-type="bibr" rid="BIBR-15">(Jakaria et al., 2025)</xref>. Therefore, the RSCU pattern of Madura cattle is generally consistent with the A-ending codon preference reported in Bali cattle, although the dominant codons were not identical. The frequent representation of leucine and serine in Madura cattle also agrees with the general amino acid usage pattern commonly observed in bovine mitochondrial protein-coding genes. In Madura cattle, leucine and isoleucine were the two most frequent amino acids, with 532 and 481 codons, respectively. <xref ref-type="bibr" rid="BIBR-4">(Arya et al., 2025)</xref> also analyzed RSCU patterns and selection pressure in the complete mitochondrial genome of Badri cattle (<italic>B. indicus</italic>) and reported that mitochondrial protein-coding genes were mainly shaped by purifying selection. This suggests that codon usage variation in bovine mitogenomes may be influenced not only by nucleotide composition bias, but also by functional constraints related to mitochondrial protein translation <xref ref-type="bibr" rid="BIBR-27">(Parvathy et al., 2022)</xref>. </p><p>A total of 22 tRNA genes were identified with a total length of 1515 bp. The tRNA anticodons found correspond to those commonly reported in vertebrates<xref ref-type="bibr" rid="BIBR-15">(Jakaria et al., 2025)</xref>. Based on tRNA structure visualization, the Madura cattle tRNA forms a cloverleaf secondary structure consisting of an acceptor stem, D-arm, anticodon arm, TΨC arm, and variable loop. Several mitochondrial tRNAs show deviations from this structure, namely trnS1 (tRNA-Ser1) and trnK (tRNA-Lys) (<xref ref-type="fig" rid="figure-4">Figure 4</xref>). The structure of trnS1 and trnK differs from other tRNAs due to the loss or instability of the loop on the dihydrouridine (DHU) arm <xref ref-type="bibr" rid="BIBR-38">(Watanabe et al., 2014)</xref>. These findings are consistent with the characteristics of tRNA in vertebrates; the cloverleaf structure and deviations in trnS1 and trnK were also found in <italic>Bos gaurus</italic><xref ref-type="bibr" rid="BIBR-17">(Kamalakkannan et al., 2020)</xref>, <italic>B. javanicus </italic><xref ref-type="bibr" rid="BIBR-15">(Jakaria et al., 2025)</xref>, and <italic>B. taurus</italic><xref ref-type="bibr" rid="BIBR-9">(Estrada et al., 2024)</xref>.</p><p>Phylogenetic reconstruction and genetic distance results using the full mitochondrial genome showed that some Madura cattle samples clustered with <italic>B. indicus</italic>, while others clustered with <italic>B. javanicus</italic>. This topology indicates the presence of distinct mitochondrial lineages within the analyzed Madura cattle samples, reflecting a complex maternal background related to both <italic>B. indicus</italic> and <italic>B. javanicus</italic> lineages. This clustering pattern is also consistent with the theory of mitochondrial genome inheritance, which is passed down exclusively through the maternal line (Ladoukakis &amp; Zouros, 2017). The <italic>B. indicus</italic>-related lineage may be associated with the historical dissemination of indicine cattle across Asia through trade, migration, and livestock management practices <xref ref-type="bibr" rid="BIBR-29">(Pitt et al., 2019)</xref>, whereas the <italic>B. javanicus</italic>-related lineage may reflect maternal introgression from banteng-derived cattle populations <xref ref-type="bibr" rid="BIBR-36">(Wang et al., 2026)</xref>. Because mitochondrial DNA is maternally inherited, these findings describe the maternal history of Madura cattle and should be complemented by nuclear genomic data to resolve genome-wide ancestry and admixture patterns further.</p></sec><sec><title>CONCLUSION </title><p>The complete mitochondrial genome of Madura cattle was successfully characterized using Oxford Nanopore Technology, revealing the typical bovine mitochondrial organization and mitochondrial variation in the D-loop and protein-coding regions. Genetic distance and phylogenetic analysis consistently identified two maternal lineages, with one closely related to <italic>Bos javanicus</italic> and the other to <italic>Bos indicus</italic>. This finding provides baseline information on the maternal genetic diversity of Madura cattle and may support future genetic characterization and conservation. Further studies using broader sampling and nuclear genomic data are needed.</p></sec><sec><title>CONFLICT OF INTEREST </title><p>J. Jakaria, an associate editor at the Tropical Animal Science Journal, was not involved in the decision-making process for this publication. The authors also declare no conflicts of interest related to this study.</p></sec><sec><title>ACKNOWLEDGEMENT </title><p>The authors thank the Ministry of Higher Education, Science, and Technology for funding their research through the Regular Fundamental Research (PFR) scheme, under contract number 22048/IT3.D10/PT.01.03/P/B/2024, and the Master’s Thesis Research Grant (PTM) under the BIMA system, under contract number 18939/IT3.D10/PT.01.03/P/B/2026.</p></sec><sec><title>DECLARATION OF GENERATIVE AI AND AI-ASSISTED TECHNOLOGIES IN THE WRITING PROCESS</title><p>While preparing this work, the authors utilized Grammarly to enhance the writing structure and grammar. Following this, we reviewed and edited the content as necessary and assumed full responsibility for the published material.</p></sec></body><back><sec sec-type="how-to-cite"><title>How to Cite</title><p>Khairunnisa, N., Dharmayanthi, A. B., Noor, R. R., &amp; Jakaria, J. (2026). 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