Genome-Wide Screening Reveals Sex-Specific SNP Markers in Pengba (Osteobrama belangeri)

Genome-Wide Screening Reveals Sex-Specific SNP Markers in Pengba (Osteobrama belangeri) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genome-Wide Screening Reveals Sex-Specific SNP Markers in Pengba (Osteobrama belangeri) Sukriti Mandal, Himanshu Priyadarshi, Sagar Chandra Mandal, Wanglar Chimwar, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8163459/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Osteobrama belangeri , the state fish of Manipur, exhibits sexual dimorphism, with females growing faster than males, making it a promising candidate for monosex culture in aquaculture. To identify sex-associated SNP markers, whole-genome sequencing was performed on 20 individuals (10 males, 10 females) using the Illumina NovaSeq platform. Sequencing generated 40.5 GB of high-quality reads, which were assembled de novo into 5,49,073 scaffolds. SNP discovery revealed a total of 8,41,800 variants, including 9,636 male-specific and 21,045 female-specific SNPs. Among 363 candidate genes analysed, 68 contained 164 genic SNPs (36 exonic and 128 intronic) with a Ts/Tv ratio of 1.22. The exonic SNPs comprised 13 non-synonymous and 23 synonymous substitutions, with a shift in codon preference. Notably, 11 type I SNPs were identified across seven key sex-associated genes. Of these, four were non-synonymous, with three predicted to enhance protein stability in males, while only one such SNP was observed in females. These sex-associated SNPs represent promising markers for monosex culture, early sex determination, and reproductive trait studies. Their further validation could facilitate the development of SNP chips for marker-assisted selection in O. belangeri . Pengba Genome sequencing Type I marker Single Nucleotide Polymorphism Sex association Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Osteobrama belangeri (Valenciennes, 1844), locally known as “pengba,” is an economically and culturally important medium carp native to Northeast India, Myanmar, and Yunnan Province of China (Basudha and Singh 2022 ). Once abundant in Loktak Lake and its associated rivers, where it contributed nearly 40% of regional fisheries (Behera et al. 2009 ), the species has faced drastic population decline due to the construction of the Ithai barrage, habitat destruction, hydropower development, pollution, and introduction of exotic species, particularly common carp ( Cyprinus carpio ) (Behera et al. 2015 ). As a consequence, Pengba was initially declared "extinct in the wild" by the IUCN Red List (Das et al. 2020 ) and later reclassified as "near-threatened" after its sighting in Loktak Lake (IUCN 2010 ; Vishwanath 2010 ). Due to its ecological importance and high nutritional value, pengba was declared the State Fish of Manipur in 2007. Artificial propagation techniques have been standardized (Das et al. 2016 ), and its herbivorous feeding habit makes it suitable for pond culture and as a replacement for grass carp in polyculture systems (Behera et al. 2015 ). Females grow significantly faster than males (Angel et al. 2015 ), and being prolific breeders, they are more profitable for aquaculture, making the species an attractive candidate for mono-sex culture (Hafeez-ur-Rehman et al. 2008 ). Developing genetic markers linked to reproductive traits is essential for advancing selective breeding and enhancing aquaculture productivity (Eze 2019 ). Over the years, various molecular markers such as allozymes, RFLPs, RAPDs, and AFLPs have been employed to study genetic variation, but their limited reproducibility and low throughput restricted their broader application. Microsatellites later became the preferred markers owing to their high polymorphism and ability to differentiate populations, though they were still only moderately scalable (Lemopoulos et al. 2019 ). The advent of high-throughput sequencing technologies has positioned single-nucleotide polymorphisms (SNPs) as the most powerful and widely used markers. SNPs account for nearly 90% of genetic variation, are abundant and evenly distributed across genomes, and offer high efficiency, reliability, and suitability for marker-assisted selection and genetic evaluation (Seeb et al. 2011 ). Type I SNPs, located in coding regions, are of particular interest as they can alter protein function, gene regulation, and performance traits, including growth, reproduction, and sex determination (Du et al. 2010 ; Geng et al. 2015 ; Zhou et al. 2018 ). SNPs are valuable tools for assessing genetic variation within populations and for characterizing genetic stocks (Chaturvedi et al. 2011 ). The advent of Next-Generation Sequencing (NGS) has greatly advanced this field by enabling the rapid sequencing of millions of DNA fragments and accurate identification of nucleotide variation across entire genomes or targeted regions (Zhou et al. 2010 ). This technology has made a significant breakthrough in genomic research via extensive parallel and deep sequencing for revealing genetic differences and diversity, providing a broad view of the entire genome (Hess et al. 2020 ). Compared to traditional Sanger sequencing, it offers far greater throughput, speed, and cost efficiency, making it the method of choice for SNP discovery. NGS-based approaches now widely support linkage mapping, association studies, genetic diversity assessments, and marker-assisted selection across aquaculture species (Cortés et al. 2011 ). Since females of Osteobrama belangeri (pengba) exhibit faster growth than males (Angel et al. 2015 ), the identification of sex-specific SNPs and sex-differentiated regions can enable accurate early sex determination, supporting all-female mono-sex culture and sex-controlled breeding programs to enhance farm profitability. However, both cultured and wild populations of O. belangeri show reduced genetic diversity due to inbreeding and the release of inbred stocks into natural waters (Rakkannan et al. 2023 ). In this context, sex-associated SNPs can play a dual role in improving aquaculture productivity and aiding conservation by facilitating sex ratio management in cultured populations. Moreover, such markers provide a valuable resource for molecular ecology and evolutionary studies, particularly in fish species with weakly differentiated sex chromosomes. Access to genome-wide SNPs enables applications in linkage mapping, map-based cloning, marker-assisted breeding, population structure analysis, functional genomics, and association studies. Therefore, the present study aims to identify SNPs in across the genome of Osteobrama belangeri and to develop markers from both anonymous and genic regions associated with sex determination. Materials and methods Ethics statement The research undertaken complies with the current animal welfare laws in India. The care and treatment of animals used in this study were in accordance with the guidelines of the CPCSEA [(Committee for the Purpose of Control and Supervision of Experiments on Animals), Ministry of Environment and Forests (Animal Welfare Division), Government of India] on care and use of animals in scientific research. The study was approved by the College Research Advisory Committee (CRAC), College of Fisheries, CAU (Imphal), Tripura. Sample collection and whole genome sequencing Pengba fish samples of age group 1.5 + years were collected from the culture ponds of the College of Fisheries, CAU (I), Lembucherra, Tripura (23.9036° N, 91.3077° E), India. A total of 20 fish (10 male and 10 female) samples were obtained in four groups, i.e., female large (FL), male large (ML), female small (FS) and male small (MS). Genomic DNA was isolated from the fin of each sample, and DNAs from each group were pooled in equimolar quantities and barcoded separately during genomic DNA library preparation. Thus, four genomic DNA libraries were prepared for each group. The whole genomic sequencing (paired-end) was performed at NCGM (Neuberg Center for Genomic Medicine, Ahmedabad) using the Illumina NovaSeq 6000 platform (BioProject: PRJNA417100), and it has been used for the current study for mining SNPs linked with the specific sex. De novo assembly and annotation The raw reads were supplied in the FASTQ format, and the quality of the reads was determined using the FastQC version 0.12.1 software (Andrews 2010 ). Low-quality reads were trimmed using Trimmomatic version 0.32 software (Bolger et al. 2014 ) to discard reads of length < 50 bp and a quality score of < 25. The trimmed sequence reads were collected and used for further study. Due to the unavailability of the pengba reference genome, de novo assembly was carried out using CLC Genomics Workbench 24.0.2 and Trinity v2.15.2 software and scaffolds were generated. The trimmed sequences from all four groups were used for the assembly to produce the maximum number of scaffolds and contigs. The de novo assembled genome was used further for identifying genetic variants, predicting genes or genomic regions, annotating their functions, and associating with the sex determination of pengba. The homology search of all scaffolds was carried out using the BLASTx (version 2.2.31+) algorithm in Blast2GO (version 4.0.7) by querying with the NCBI non-redundant (nr) nucleotide database with an E-value ≤ 1e − 5 , and the output file was obtained in XML format with a maximum of 10 alignment hits. Gene Ontology (GO) assignments were used to classify the predicted coding sequences (CDS) based on their functions. GO mapping also provides an ontology of defined terms representing gene product properties, which are grouped into three main domains: Biological processes, Molecular functions and Cellular components. GO mapping was carried out to retrieve GO terms for all the BLAST functionally annotated CDS with the Blast2GO programme. Mapping the reads and sex-associated SNPs mining The de novo assembled scaffolds were used as the reference genome for mapping the group-specific sequences. All filtered raw reads of all the males and females were mapped separately against the reference using the tool Bowtie2 (Langmead and Salzberg 2012 ) and the SNPs were detected through SAMtools v1.22 (Li et al. 2009 ) in Galaxy Server ( https://usegalaxy.org/ ). SNP detection was performed using stringent filters with the minimum average quality of surrounding bases and minimum quality of the central base of 15 and 20 quality score units, respectively; minimum coverage of 10 reads; minimum variant frequency or count of 20%; and SNPs present in the read ends (last three bases) were discarded during analysis to avoid chances of sequencing errors. Figure 1 depicts the bioinformatics pipeline used for the above analysis. The SNPs detected in each of the four groups were downloaded and used to create a Venn diagram using Version 2.1.0 online server ( https://bioinfogp.cnb.csic.es/tools/venny/index2.0.2.html ). Then the SNPs specific to males and females were filtered out. These SNPs were considered as sex specific SNPs and used for further analysis (Fig. 3 ). Analysis of SNPs effect The genes related to sex determination, reproduction, growth, development, stress, immunity, and transport-related were selected, and the presence of SNPs was assessed. From these, genes with at least one SNP in the exonic region were screened and classified as synonymous or non-synonymous based on the change in the position of the base in the codon using Gene Runner (Version 6.5.52). In the case of nsSNPs, the protein stability was checked using I-mutant (Version 2.0) ( https://folding.biofold.org/i-mutant/i-mutant2.0.html ). The effect of mutation on protein function was determined using the web tool SIFT (Sorting Intolerant From Tolerant) ( https://sift.bii.a-star.edu.sg/ ). For the synonymous SNPs, codon preference was assessed from the codon preference table (Sup. Table 1) generated using the Gene Infinity tool ( http://www.geneinfinity.org/sp/sp_codonusage.html ). Molecular characterization of sex associated genes The genes containing sex specific SNPs were further analysed for the detection of the effect of the SNPs on the structure of the protein and to detect their possible role in determining sex in pengba. The coding region of the amino acid sequences was determined using NCBI ORF finder ( https://www.ncbi.nlm.nih.gov/orffinder/ ). The sequences were further assessed for full or partial length using the ExPASy Translation Tool ( https://web.expasy.org/translate/ ) (Gasteiger et al. 2003 ) and were submitted to the NCBI database. The ProtParam tool ( https://web.expasy.org/protparam/ ) (Gasteiger et al. 2005 ) in ExPASy was used to explore the physiochemical parameters of the amino acid sequences. The 3-D protein structure was predicted using the online tool SWISS-MODEL ( https://swissmodel.expasy.org/ ), which predicts the protein structure in an automated way based on homology modelling. The appropriate template having the highest sequence similarity and coverage with the query was selected for homology modelling. Once the template and query sequence were aligned, the 3D model was automatically generated. The alpha helices and beta sheets were deduced using the Mol* Viewer tool ( https://molstar.org/viewer/ ). The SAVES (Version 6.1) (Structural Analysis and Verification Server) ( https://saves.mbi.ucla.edu/ ) was used for structural and stereochemical quality evaluation, and a Ramachandran plot was generated using the PROCHECK tool. Additionally, the ERRAT quality score and the Verify 3D program aided in validating the modelled protein structures. Phylogenetic tree analysis The derived amino acid sequences from the full-length genes of Osteobrama belangeri (pengba) were subjected to multiple sequence alignment with their orthologs from Sinocyclocheilus rhinocerous , Sinocyclocheilus anshuensis , Cyprinus carpio , Onychostoma macrolepis , Labeo rohita , Megalobrama amblycephala , Myxocyprinus asiaticus , Mus musculus (mouse) and Homo sapiens (human) using Clustal Omega software ( https://www.ebi.ac.uk/jdispatcher/msa/clustalo?stype=protein ). The sequence alignment obtained was used to construct a neighbour-joining tree with 1000 bootstrap replicates by MEGA11 software in which Mus musculus (mouse) and Homo sapiens (human) were used as an outgroup (Tamura et al. 2021 ). Results Whole Genome Sequencing, de novo assembly and annotation A total of 43.6 GB of data containing 270 million reads was obtained from the whole genome sequencing of pengba with a mean read length of 161 bp. The generated reads were checked for quality, and low-quality reads were trimmed. After trimming, a total of 40.5 GB of data were yielded, which produced 265 million reads with an average read length of 155 bp, and of these, 20.2 GB and 20.3 GB of data were obtained from male and female, respectively. All reads were subjected to de novo assembly using the CLC Genomics Workbench with a minimum length parameter of 200 bp and an average GC content of 35%. A total of 5,49,073 scaffolds were generated, with a length of 647,155,667 bp and an N50 value of 67,840. This scaffold was used as a reference genome for mapping of SNPs (Table 1). All the scaffold sequences were searched against GenBank (Sequence database) for putative identification of homologous genes using NCBI-BLAST (Altschul et al. 1990) in Blast2GO, and the sex-related genes were screened. The gene ID, gene name and protein name of the query sequence were mined, and the percentage identity, value and species associated with the query sequence were revealed. A Gene Ontology (GO) annotation summary described the biological role, molecular functions and cellular locations of the genes as depicted in Fig. 2. Detection of sex-specific SNPs All the reads were mapped against the assembled reference genome for SNP calling. Altogether, 203 (76.8%) million trimmed reads could be mapped and a total of 8,41,800 SNPs were detected among the four groups and the group-specific SNPs were shown in Fig. 3. To detect sex-associated SNPs, reads of males and females were mapped separately with the reference genome. Mapping of 136.8 million male reads and 129.8 million female reads revealed 9636 (1.1%) male-specific SNPs, 21045 (2.5%) female-specific SNPs, and 7710 (0.9%) common between the groups (Fig. 3). Distribution of SNPs in selected genes A total of 363 sex-specific genes were selected from the whole genome, of which 68 genes contained 164 SNPs in the genic regions (36 SNPs in the exon and 128 SNPs in the intron), shown in Sup. Table 2. Among these, 36 SNPs were present in the exonic region of 26 genes, which were used for further studies (Table 2). Of the 36 SNPs, 28 altered alleles showed association with females, while the remaining 8 showed association with males. Thirteen non-synonymous SNPs were detected (Table 2), which showed a decrease in protein stability, and 23 SNPs were synonymous in nature. Among the nsSNPs, 4 SNPs resulted in substitution by an amino acid of a different class. All 4 SNPs changed from non-polar to polar amino acids, and the rest did not change the class of amino acid. Among the nsSNPs, 6 SNPs were predicted to be deleterious in nature, while 7 SNPs were neutral on protein function. Out of 23 synonymous SNPs, increased codon preferences were observed for five SNPs, while ten were changed to less preferred and no alteration in the codon preference was found for 8 SNPs (Table 2). Out of 164 SNPs detected, 90 transitions (Ts) and 74 transversions (Tv) were observed with a Ts: Tv ratio of 1.22 across the sex associated genes, where A↔G transitions (35%) were most frequent, followed by A↔T transversions (21%) (Fig. 4a, b). As expected, the Ts: Tv ratio in the exonic regions was much higher at 2.27 compared to the intronic region, where it was 0.96. Protein sequence analysis of the selected genes The sequences of 12 full-length genes containing sex specific SNPs were submitted to the NCBI database, are mentioned in Table 3. Among them, four vital sex associated genes containing nsSNPs were assessed for their molecular characterisation and functional annotation. It was found that RAB39B, ITGB1BP1 and ATL3 were hydrophilic in nature, while CLDN10 was hydrophobic. The highest thermostability was observed for ITGB1BP1 protein with an aliphatic index of 94.38, followed by CLDN10 (90.20), ATL3 (82.52) and RAB39B (78.98), indicating potential stability under elevated temperatures. The Molecular weight of RAB39B, ITGB1BP1, CLDN10 and ATL3 proteins was 49.54 kDa, 34.68 kDa, 33.13 kDa and 98.58 kDa, with pI values of 7.09, 5.07, 6.51 and 8.53, respectively. The 3-D protein structure of the four proteins was generated (Fig. 5a-d), and it was observed that RAB39B showed the highest protein structure similarity with Sinocyclocheilus anshuensis , ITGB1BP1 with Pundamilia nyererei , CLDN10 with Danio rario and ATL3 with Bagarius yarrell , which was used as a template for homology modelling. The ribbon diagram showed 8, 4, 5 and 26 alpha helices, while 7, 7, 5 and 18 beta sheets in RAB39B, ITGB1BP1, CLDN10 and ATL3, respectively and no alteration in the number of helices and beta sheets was found due to mutation (Fig. 5a-d). Ramachandran plot analysis revealed that RAB39B showed the most stable model of pengba with 96.9% of the residues in the most favoured regions, while 3.1% of residues were in the additional allowed region. The Ramachandran plots for the remaining genes are illustrated in Fig. 6a-d. The data statistics showed that the 3-D models generated were stable. By considering both ERRAT score and Verify 3D results, RAB39B was found to be the best model among all the protein models with an ERRAT score of 94.6809, demonstrating the overall quality factor of the initial 3D model, and a Verify 3D score of 86.38%, indicating a more accurate and reliable protein structure model. Moreover, it was observed that in the case of RAB39, the mutation did not cause any alteration in the model quality and structure. In the case of the ITGB1BP1 mutation, there was a minute drop in ERRAT quality, but it slightly improved the stereochemistry. In CLDN10, the effect of the mutation was negligible, and in ATL3, the mutation slightly improved the overall quality. Phylogenetic studies The phylogenetic tree was constructed using the full-length coding sequences of the sex associated genes containing nsSNPs (Fig. 7a-d). It was observed that O. belangeri RAB39B clustered closely with Cyprinus carpio , followed by Sinocyclocheilus spp. , Myxocyprinus asiaticus and Labeo rohita . Homo sapiens (Human) and Mus musculus (house mouse) were used as the mammalian outgroup, which clustered distantly with 67% sequence similarity with the other fish clusters in the gene. The O. belangeri ITGB1BP1 protein clustered with Onychostoma macrolepis , Cyprinus carpio , Sinocyclocheilus spp ., Labeo rohita , Myxocyprinus asiaticus , and Megalobrama amblycephala . The mammalian outgroup clustered distantly with 84% sequence similarity with the cyprinids in the gene. In case of CLDN10 and ATL3, O. belangeri clustered closely with Onychostoma macrolepis and Megalobrama amblychephala , with outgroups showing 89% and 84% sequence similarity, respectively, with other fishes. Thus, the SNP in Osteobrama belangeri did not did not change the overall topology of the tree. Discussion Osteobrama belangeri (Pengba) is a culturally and nutritionally valued medium-sized carp native to rivers and lakes of Northeast India and adjacent regions (Devi et al. 2009 ). It is often reared in polyculture with Indian major carps, but culture performance is limited by slow male growth, disease susceptibility, and feed issues (Deepti et al. 2023 ). Because females typically outgrow males (Angel et al. 2015 ), harnessing female growth through all-female culture or selective breeding could greatly improve yields. To enable this, we conducted genome-wide SNP discovery in O. belangeri to identify genetic markers linked to sex. SNPs are favoured markers in modern aquaculture breeding programs due to their abundance and compatibility with high-throughput genotyping (Liu and Cordes 2004 ). Single nucleotide polymorphisms (SNPs) are widely recognized as powerful genomic markers due to their abundance, stability, and amenability to high-throughput genotyping (Liu and Cordes 2004 ). Genome-wide SNP discovery has transformed aquaculture genetics, enabling the development of species-specific SNP arrays such as the 7K SNP panel for Atlantic salmon ( Salmo salar ) (Karlsson et al. 2011 ), the 250K SNP chip for channel catfish ( Ictalurus punctatus ) (Liu et al. 2014 ), and high-density arrays for genomic selection in salmonids (Houston et al. 2014 ; Yáñez et al. 2016 ). In Indian major carp ( Labeo rohita ), SNPs have been linked to resistance against Aeromonas infections (Robinson et al. 2014 ). For O. belangeri , previous studies have relied primarily on mitochondrial DNA (Singh et al. 2016 ; Barman et al. 2017 ) and microsatellites (Rakkannan et al. 2023 ) for genetic diversity analysis, with sex-linked SNPs remaining unexplored. The present study, therefore, provides the first genome-wide insight into sex-associated SNPs in pengba. In total we identified ~ 841,800 putative SNPs in the pengba genome. This is comparatively lower than reported in other teleosts like E. coioides (6.5 million SNPs; Weng et al. 2021 ), Protosalanx hyalocranius (3.8 million SNPs; Li et al. 2020 ) and Anguilla japonica (9.9 million; Liu et al. 2020 ). This relatively low SNP count is consistent with the reduced genetic diversity previously reported in O. belangeri by Singh et al. ( 2016 ) using mtDNA markers, likely reflecting inbreeding and limited founder populations in hatcheries. Among the identified SNPs, 164 were located within 68 sex-associated genes, with 36 in exonic and 128 in intronic regions, yielding a Ts/Tv ratio of 1.22. The exonic SNPs comprised 13 non-synonymous and 23 synonymous substitutions. Most variants were synonymous or intronic; only four were non-synonymous. This skew toward synonymous changes is expected under purifying selection in coding sequences (Ramensky et al. 2002 ). Importantly, 11 type I SNPs were identified across seven sex-linked genes ( SOX30, ITGB1BP1, LIFR, GGNBP2, ARMC3, HORMAD1 , and AZIN1 ), highlighting their potential involvement in sexual differentiation and reproduction. Two nsSNPs (ARMC3.1544A > G and ARMC3.688T > C) in Armadillo repeat-containing protein 3 ( ARMC3 ) increased protein stability in males (ΔG > 0). ARMC3 plays a critical role in signal transduction, cell adhesion, and motility, and supports sperm capacitation and the acrosome reaction via PKA–AKAP3 signalling (Huang et al. 2021 ). Its expression is elevated in highly active sperm (D’Amours et al. 2019 ), and exon 11 deletion in cattle leads to premature translation termination, sperm defects, and male infertility (Pausch et al. 2016 ), underscoring its essential role in male reproduction. Another nsSNP (ITGB1BP1.134T > C) in Integrin beta-1-binding protein 1 ( ITGB1BP1 ) also enhanced protein stability in males. Notably, ITGB1BP1 has been reported as a male-biased sex-determining gene in Channa maculata (Liu et al. 2025 ), where its expression regulates epididymis and efferent duct cell attachment to the extracellular matrix (Snyder et al. 2010 ). Conversely, one nsSNP (LIFR.437G > A) in Leukaemia inhibitory factor receptor ( LIFR ) enhanced protein stability in females. LIF–LIFR signalling promotes ovarian follicle transition (Nilsson et al. 2002 ), bovine oocyte maturation (Mo et al. 2014 ; Vendrell-Flotats et al. 2020 ), and regulates cell proliferation, differentiation, and survival in mammals (Nicola et al. 2015), as well as neural development in zebrafish (Hanington et al. 2008 ). Together, these findings reveal sex-specific molecular signatures that could be exploited for selective breeding. Additionally, two male-associated synonymous SNPs (SOX30.384A > G and SOX30.1896C > T) were detected in Transcription factor SOX-30 ( SOX30 ), which plays a central role in spermiogenesis and male gonadal development in Nile tilapia (Han et al. 2010 ; Zhang et al. 2018 ). Both variants displayed codon preference in males, suggesting sex-biased functional relevance. A male-specific SNP (GGNBP2.630A > G) in Gametogenetin-binding protein 2 ( GGNBP2 ), a regulator of spermatogenesis and Sertoli cell function (Chen et al. 2017 ), showed association without codon bias. Another synonymous SNP (HORMAD1.510G > T) in HORMA domain-containing protein 1 ( HORMAD1 ) exhibited increased codon preference in males; notably, knockout of HORMAD1 in mice causes infertility in both sexes (Shin et al. 2010 ; Pangas et al. 2004 ), indicating its conserved role in fertility. Male-specific synonymous SNPs were also identified in ARMC3 (ARMC3.2796T > C) and Antizyme inhibitor 1 (AZIN1.1242A > G), though neither altered codon preference, while another AZIN1 SNP (AZIN1.1242A > G) enhanced codon preference in females. Mutations in ARMC3 are linked with male infertility in cattle (Pausch et al. 2016 ), whereas AZIN1 regulates β-casein expression during mammary gland development in mice (Murakami et al. 2010 ). While most nsSNPs introduced subtle rather than drastic structural changes, these findings are consistent with earlier reports showing that coding variants often exert minor yet biologically relevant effects on protein stability and function (Tokuriki and Tawfik 2009 ; Hartl et al. 2011 ). Collectively, the identified SNPs provide novel molecular insights into reproductive biology and sex differentiation in O. belangeri . This study represents the first genome-wide discovery of sex-linked SNPs in pengba, providing foundational resources for aquaculture genetics. These markers hold promise for developing molecular tools to support monosex culture, early sexing, and reproductive trait improvement. However, a low number of SNPs obtained indicates a significant lack of genetic diversity in O. belangeri , possibly due to extensive inbreeding in hatcheries and employing inbred species when ranching in the wild. Future research should focus on validating these sex-associated SNPs across larger and more diverse populations, developing SNP chips for high-throughput genotyping, and exploring their utility in comparative studies on sex chromosome evolution in teleosts. Declarations No animals were harmed during the study. Fin samples were collected using a non-invasive method (fin clipping) solely for the purpose of genome sequencing. Fin samples were collected using a non-invasive method (fin clipping) solely for the purpose of genome sequencing. The anesthetic agent MS‐222 was used during fin-clipping procedures to facilitate safe and efficient handling of the fish. Acknowledgments The authors are grateful to the Vice Chancellor, Central Agricultural University, Imphal and Dean College of Fisheries, CAU(I), Lembucherra, Tripura, India, for providing all the facilities to conduct the present research work and thankful to ICAR for providing a fellowship to the first author. The authors are also thankful to Department of Biotechnology (DBT), Government of India for providing fund for Pengba genome sequencing. Funding Declaration: The genome sequencing was supported under Phase II of the Centre of Excellence in Fisheries and Aquaculture Biotechnology (CoE-FAB), Department of Biotechnology (DBT), Government of India. Ethics, Consent to Participate, and Consent to Publish declarations: This study involved only routine, non-invasive sampling of fish from aquaculture facilities. Formal ethics approval was not required; however, all procedures were carried out in accordance with institutional guidelines for the ethical handling of aquatic organisms and complied with relevant national regulations (CPCSEA norms, Government of India). The study was approved by the College Research Advisory Committee (CRAC), College of Fisheries, CAU (Imphal), Tripura. DAS statement request: The genome sequence datasets generated and analysed during the current study are available from the corresponding author upon reasonable request. However, the full-length sequences used in the study have been deposited in the GenBank database (NCBI), and the corresponding accession numbers are provided in Table 3. Disclosure statement No potential conflict of interest was reported by the authors. References Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215(3):403–10. Andrews S. (2010) FastQC: A Quality Control Tool for High Throughput Sequence Data. Babraham Bioinformatics. https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ Angel JR, Tiwari VK, Suresh Babu PP, Rawat KD, Ignatius B, Pramod Kiran RB, Dam Roy S, Charan R, Nair DR, Rao PS, Sreeramamurty P. Captive breeding of a near threatened fish, pengba Osteobrama belangeri (Valenciennes, 1844) using three different inducing agents. 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Tables Table 1 De novo assembly statistics Assembly Statistics No. of Scaffolds 5,49,073 Total Scaffold Length (bp) 647,155,667 Scaffold N50 67,840 No. of Contigs 5,58,342 Total Contig Length (bp) 646,613,697 Contig N50 71,901 Table 2. List of sex-associated genes S.No. Gene Name # CDS/SNP position SNP type* Sex NS/S Alt. AA Effect 1. RAB39B 1-1302, 450 GA G > GA A F S Glu Increasing codon preference 2. ITGB1BP1 1- 948, 134 A T G > A C G F NS Met > Thr Decreased stability 3. CLDN10 1-921, 392 T G T > T C T F NS Cys > Ser Decreased stability 4. CERS2 1->927, 263 C G A > C A A F NS Arg > Gln Decreased stability 5. ATL3 1-2631, 2066 G G C > G A C F NS Gly > Asp Decreased stability 6. ARMC3 1->3105, 1544 C A G > C G G F NS Gln > Arg Decreased stability 7. 1->3105, 688 T GC > C GC F NS Cys > Arg Decreased stability 8. 1->3105, 2796 CA T > CA C F S His No change 9. TRIM75 C AT F NS Asn > His Decreased stability 10. GA T F NS Glu > Asp Decreased stability 11. SOX30 1-2088, 384 AC A > AC G F S Thr Decreased codon preference 12. 1-2088, 1896 AT C > AT T F S Ile Decreased codon preference 13. TDRD1 CT T F S Leu Increased codon preference 14. EI24 1->1161, 405 TC G > TC A F S Ser No change 15. 1->1161, 426 TC C > TC A F S Ser Decreased codon preference 16. DRC11 1->510, 18 GC A > GC G F S Ala Decreased codon preference 17. FAM83B 1-2043, 1428 AA A > AA G F S Lys No change 18. HORMAD1 1->1359, 510 GT G > GT T F S Val Decreased codon preference 19. CRY1 1-876, 525 GC A > GC G F S Ala Decreased codon preference 20. DUSP1-A 1-1395, 1257 CT C > CT T F S Leu No change 21. KNG1 1-1398, 291 TG C > TG T F S Cys Decreased codon preference 22. AZIN1 1-1311, 131 GA C > GA T F S Asp No change 23. NCF1 TT C F S Phe No change 24. POGLUT2 1-3498, 981 CC A > CC G F S Pro Increased codon preference 25. SHANK1 1->1056, 513 TC A > TC C F S Ser Increased codon preference 26. CCNP CT C F S Leu Increased codon preference 27. HRAS 1-618, 207 GA T > GA C F S Asp No change 28. 1-618, 186 GA A > GA G F S Glu Decreased codon preference 29. RAB39B 1-1302, 314 G T C > G A C M NS Val > Asp Decreased stability 30. 1-1302, 315 GT C > GT A M S Val Decreased stability 31. LIFR A A A M NS Arg > Lys Decreased stability 32. CNTN5 1275, 418 G GA > A GA M NS Gly > Arg Decreased stability 33. GMPR2 G T T M NS Ala > Val Decreased stability 34. TRIM75 C AA M NS Lys > Gln Decreased stability 35. GGNBP2 1->2175, 630 AG A > AG G M S Arg No change 36. AZIN1 1-1311, 1242 GA A > GA G M S Glu Decreased codon preference #Full gene name in Sup Table 1; *Altered codon is sex associated; NS: Non-Synonymous; S: Synonymous; F: Female; M: Male Table 3 Characteristics of sequences with complete ORF Sl. No. Gene Name Sequence length (start codon + exon + stop codon) NCBI accession number 1. SOX30 (Transcription factor SOX-30) 2088 PV464453 2. RAB39B (Ras-related protein Rab-39B) 1302 PV568094 3. FAM83B (Protein FAM83B) 2043 PV573996 4. CRY1 (Cryptochrome-1) 876 PV573997 5. DUSP1-A (Dual specificity protein phosphatase 1-A) 1395 PV573998 6. KNG1 (Kininogen-1) 1398 PV600739 7. AZIN1 (Antizyme inhibitor 1) 1311 PV600740 8. POGLUT2 (Protein O-glucosyltransferase 2) 3498 PV634343 9. HRAS (GTPase HRas) 618 PV634344 10 ITGB1BP1 (Integrin beta-1-binding protein 1) 948 PV634345 11. CLDN10 (Claudin-10) 921 PV789843 12. ATL3 (Atlastin-3) 2631 PV789844 Additional Declarations No competing interests reported. Supplementary Files SUPPLEMENTARYTABLES.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":130265,"visible":true,"origin":"","legend":"\u003cp\u003eBioinformatics pipeline\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8163459/v1/a113f1cb10474c2a6bc46b83.png"},{"id":97895563,"identity":"e67fbaca-86ae-40e5-b088-08df35edd8a8","added_by":"auto","created_at":"2025-12-10 15:34:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":271916,"visible":true,"origin":"","legend":"\u003cp\u003eGO Annotation Summary\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8163459/v1/78be7a7b7e9dd17cb797207d.png"},{"id":97895940,"identity":"df328c0d-7cdf-43a3-905e-ec10a04d1e32","added_by":"auto","created_at":"2025-12-10 15:35:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":315342,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagram showing the group-specific SNPs among the four groups of \u003cem\u003eO. belangeri\u003c/em\u003e in the whole genome.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8163459/v1/c04c2b1fdb25b0dccf7f5032.png"},{"id":97896905,"identity":"fd28c781-6c83-491c-a21c-e55ed2c31f27","added_by":"auto","created_at":"2025-12-10 15:37:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":41196,"visible":true,"origin":"","legend":"\u003cp\u003eOverall distribution of SNP mutation.\u003cstrong\u003e a \u003c/strong\u003eDifferent types of altered allele frequency.\u003cstrong\u003e b \u003c/strong\u003eNumber of substitution mutations in sex related genes\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8163459/v1/1e1f4d1f8e134bd6991bdc98.png"},{"id":97778432,"identity":"ee40bba4-734d-45ff-aed3-cc0c91c16916","added_by":"auto","created_at":"2025-12-09 09:18:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":331017,"visible":true,"origin":"","legend":"\u003cp\u003eRibbon diagram showing the tertiary structure of \u003cem\u003eO. belangeri\u003c/em\u003e predicted proteins.\u003cstrong\u003e a\u003c/strong\u003e RAB39B \u003cstrong\u003eb\u003c/strong\u003e ITGB1BP1 \u003cstrong\u003ec\u003c/strong\u003e CLDN10 \u003cstrong\u003ed\u003c/strong\u003e ATL3. Alpha helices are shown in red colour, beta sheets in yellow colour, and coils are shown in green colour\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8163459/v1/bec6297862044a66c772797e.png"},{"id":97895869,"identity":"a79882e6-051b-4514-b87e-a21a770e9276","added_by":"auto","created_at":"2025-12-10 15:35:12","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":365987,"visible":true,"origin":"","legend":"\u003cp\u003eRamachandran Plot of \u003cem\u003eO. belangeri\u003c/em\u003e predicted proteins showing the dihedral angles Psi and Phi of amino acid residues. \u003cstrong\u003ea\u003c/strong\u003e RAB39B \u003cstrong\u003eb\u003c/strong\u003e ITGB1BP1 \u003cstrong\u003ec\u003c/strong\u003e CLDN10 \u003cstrong\u003ed\u003c/strong\u003eATL3. The residues which lie in most favoured regions are shown in red curves and the residues which lie in additional allowed regions are in dark yellow curves\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8163459/v1/cf2a837084e94181e5ce5850.png"},{"id":97778425,"identity":"3a22ca23-6b9f-42c6-b1d8-4d595251a333","added_by":"auto","created_at":"2025-12-09 09:18:33","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":153875,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree analysis of O. belangeri different genes deduced amino acid\u003cstrong\u003e \u003c/strong\u003esequences with orthologs from other species.\u003cstrong\u003e a \u003c/strong\u003eRAB39B \u003cstrong\u003eb\u003c/strong\u003e ITGB1BP1 \u003cstrong\u003ec\u003c/strong\u003e CLDN10 \u003cstrong\u003ed\u003c/strong\u003e ATL3\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8163459/v1/9b6f02b10191b9ca291b4043.png"},{"id":106415136,"identity":"67037e43-2dd8-4237-8211-2e622d05a59b","added_by":"auto","created_at":"2026-04-08 10:33:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2615758,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8163459/v1/98f6f414-7822-4399-a005-1eefec4f8ada.pdf"},{"id":97778423,"identity":"eaf315f6-127f-4f3b-b5c9-d52a4d7e45e4","added_by":"auto","created_at":"2025-12-09 09:18:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":35744,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYTABLES.docx","url":"https://assets-eu.researchsquare.com/files/rs-8163459/v1/ccb917370d5baeff278f9aaf.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genome-Wide Screening Reveals Sex-Specific SNP Markers in Pengba (Osteobrama belangeri)","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cem\u003eOsteobrama belangeri\u003c/em\u003e (Valenciennes, 1844), locally known as \u0026ldquo;pengba,\u0026rdquo; is an economically and culturally important medium carp native to Northeast India, Myanmar, and Yunnan Province of China (Basudha and Singh \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Once abundant in Loktak Lake and its associated rivers, where it contributed nearly 40% of regional fisheries (Behera et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), the species has faced drastic population decline due to the construction of the Ithai barrage, habitat destruction, hydropower development, pollution, and introduction of exotic species, particularly common carp (\u003cem\u003eCyprinus carpio\u003c/em\u003e) (Behera et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). As a consequence, Pengba was initially declared \"extinct in the wild\" by the IUCN Red List (Das et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and later reclassified as \"near-threatened\" after its sighting in Loktak Lake (IUCN \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Vishwanath \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Due to its ecological importance and high nutritional value, pengba was declared the State Fish of Manipur in 2007. Artificial propagation techniques have been standardized (Das et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and its herbivorous feeding habit makes it suitable for pond culture and as a replacement for grass carp in polyculture systems (Behera et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Females grow significantly faster than males (Angel et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and being prolific breeders, they are more profitable for aquaculture, making the species an attractive candidate for mono-sex culture (Hafeez-ur-Rehman et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Developing genetic markers linked to reproductive traits is essential for advancing selective breeding and enhancing aquaculture productivity (Eze \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Over the years, various molecular markers such as allozymes, RFLPs, RAPDs, and AFLPs have been employed to study genetic variation, but their limited reproducibility and low throughput restricted their broader application. Microsatellites later became the preferred markers owing to their high polymorphism and ability to differentiate populations, though they were still only moderately scalable (Lemopoulos et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe advent of high-throughput sequencing technologies has positioned single-nucleotide polymorphisms (SNPs) as the most powerful and widely used markers. SNPs account for nearly 90% of genetic variation, are abundant and evenly distributed across genomes, and offer high efficiency, reliability, and suitability for marker-assisted selection and genetic evaluation (Seeb et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Type I SNPs, located in coding regions, are of particular interest as they can alter protein function, gene regulation, and performance traits, including growth, reproduction, and sex determination (Du et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Geng et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Zhou et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). SNPs are valuable tools for assessing genetic variation within populations and for characterizing genetic stocks (Chaturvedi et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The advent of Next-Generation Sequencing (NGS) has greatly advanced this field by enabling the rapid sequencing of millions of DNA fragments and accurate identification of nucleotide variation across entire genomes or targeted regions (Zhou et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). This technology has made a significant breakthrough in genomic research via extensive parallel and deep sequencing for revealing genetic differences and diversity, providing a broad view of the entire genome (Hess et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Compared to traditional Sanger sequencing, it offers far greater throughput, speed, and cost efficiency, making it the method of choice for SNP discovery. NGS-based approaches now widely support linkage mapping, association studies, genetic diversity assessments, and marker-assisted selection across aquaculture species (Cort\u0026eacute;s et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSince females of \u003cem\u003eOsteobrama belangeri\u003c/em\u003e (pengba) exhibit faster growth than males (Angel et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), the identification of sex-specific SNPs and sex-differentiated regions can enable accurate early sex determination, supporting all-female mono-sex culture and sex-controlled breeding programs to enhance farm profitability. However, both cultured and wild populations of \u003cem\u003eO. belangeri\u003c/em\u003e show reduced genetic diversity due to inbreeding and the release of inbred stocks into natural waters (Rakkannan et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this context, sex-associated SNPs can play a dual role in improving aquaculture productivity and aiding conservation by facilitating sex ratio management in cultured populations. Moreover, such markers provide a valuable resource for molecular ecology and evolutionary studies, particularly in fish species with weakly differentiated sex chromosomes. Access to genome-wide SNPs enables applications in linkage mapping, map-based cloning, marker-assisted breeding, population structure analysis, functional genomics, and association studies. Therefore, the present study aims to identify SNPs in across the genome of \u003cem\u003eOsteobrama belangeri\u003c/em\u003e and to develop markers from both anonymous and genic regions associated with sex determination.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eEthics statement\u003c/h2\u003e\u003cp\u003eThe research undertaken complies with the current animal welfare laws in India. The care and treatment of animals used in this study were in accordance with the guidelines of the CPCSEA [(Committee for the Purpose of Control and Supervision of Experiments on Animals), Ministry of Environment and Forests (Animal Welfare Division), Government of India] on care and use of animals in scientific research. The study was approved by the College Research Advisory Committee (CRAC), College of Fisheries, CAU (Imphal), Tripura.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSample collection and whole genome sequencing\u003c/h3\u003e\n\u003cp\u003ePengba fish samples of age group 1.5\u0026thinsp;+\u0026thinsp;years were collected from the culture ponds of the College of Fisheries, CAU (I), Lembucherra, Tripura (23.9036\u0026deg; N, 91.3077\u0026deg; E), India. A total of 20 fish (10 male and 10 female) samples were obtained in four groups, i.e., female large (FL), male large (ML), female small (FS) and male small (MS). Genomic DNA was isolated from the fin of each sample, and DNAs from each group were pooled in equimolar quantities and barcoded separately during genomic DNA library preparation. Thus, four genomic DNA libraries were prepared for each group. The whole genomic sequencing (paired-end) was performed at NCGM (Neuberg Center for Genomic Medicine, Ahmedabad) using the Illumina NovaSeq 6000 platform (BioProject: PRJNA417100), and it has been used for the current study for mining SNPs linked with the specific sex.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDe novo\u003c/b\u003e \u003cb\u003eassembly and annotation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe raw reads were supplied in the FASTQ format, and the quality of the reads was determined using the FastQC version 0.12.1 software (Andrews \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Low-quality reads were trimmed using Trimmomatic version 0.32 software (Bolger et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) to discard reads of length\u0026thinsp;\u0026lt;\u0026thinsp;50 bp and a quality score of \u0026lt;\u0026thinsp;25. The trimmed sequence reads were collected and used for further study. Due to the unavailability of the pengba reference genome, \u003cem\u003ede novo\u003c/em\u003e assembly was carried out using CLC Genomics Workbench 24.0.2 and Trinity v2.15.2 software and scaffolds were generated. The trimmed sequences from all four groups were used for the assembly to produce the maximum number of scaffolds and contigs. The \u003cem\u003ede novo\u003c/em\u003e assembled genome was used further for identifying genetic variants, predicting genes or genomic regions, annotating their functions, and associating with the sex determination of pengba. The homology search of all scaffolds was carried out using the BLASTx (version 2.2.31+) algorithm in Blast2GO (version 4.0.7) by querying with the NCBI non-redundant (nr) nucleotide database with an E-value\u0026thinsp;\u0026le;\u0026thinsp;1e\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e, and the output file was obtained in XML format with a maximum of 10 alignment hits. Gene Ontology (GO) assignments were used to classify the predicted coding sequences (CDS) based on their functions. GO mapping also provides an ontology of defined terms representing gene product properties, which are grouped into three main domains: Biological processes, Molecular functions and Cellular components. GO mapping was carried out to retrieve GO terms for all the BLAST functionally annotated CDS with the Blast2GO programme.\u003c/p\u003e\n\u003ch3\u003eMapping the reads and sex-associated SNPs mining\u003c/h3\u003e\n\u003cp\u003eThe \u003cem\u003ede novo\u003c/em\u003e assembled scaffolds were used as the reference genome for mapping the group-specific sequences. All filtered raw reads of all the males and females were mapped separately against the reference using the tool Bowtie2 (Langmead and Salzberg \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and the SNPs were detected through SAMtools v1.22 (Li et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) in Galaxy Server (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://usegalaxy.org/\u003c/span\u003e\u003cspan address=\"https://usegalaxy.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). SNP detection was performed using stringent filters with the minimum average quality of surrounding bases and minimum quality of the central base of 15 and 20 quality score units, respectively; minimum coverage of 10 reads; minimum variant frequency or count of 20%; and SNPs present in the read ends (last three bases) were discarded during analysis to avoid chances of sequencing errors. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e depicts the bioinformatics pipeline used for the above analysis. The SNPs detected in each of the four groups were downloaded and used to create a Venn diagram using Version 2.1.0 online server (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinfogp.cnb.csic.es/tools/venny/index2.0.2.html\u003c/span\u003e\u003cspan address=\"https://bioinfogp.cnb.csic.es/tools/venny/index2.0.2.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Then the SNPs specific to males and females were filtered out. These SNPs were considered as sex specific SNPs and used for further analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eAnalysis of SNPs effect\u003c/h3\u003e\n\u003cp\u003eThe genes related to sex determination, reproduction, growth, development, stress, immunity, and transport-related were selected, and the presence of SNPs was assessed. From these, genes with at least one SNP in the exonic region were screened and classified as synonymous or non-synonymous based on the change in the position of the base in the codon using Gene Runner (Version 6.5.52). In the case of nsSNPs, the protein stability was checked using I-mutant (Version 2.0) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://folding.biofold.org/i-mutant/i-mutant2.0.html\u003c/span\u003e\u003cspan address=\"https://folding.biofold.org/i-mutant/i-mutant2.0.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The effect of mutation on protein function was determined using the web tool SIFT (Sorting Intolerant From Tolerant) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sift.bii.a-star.edu.sg/\u003c/span\u003e\u003cspan address=\"https://sift.bii.a-star.edu.sg/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). For the synonymous SNPs, codon preference was assessed from the codon preference table (Sup. Table\u0026nbsp;1) generated using the Gene Infinity tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.geneinfinity.org/sp/sp_codonusage.html\u003c/span\u003e\u003cspan address=\"http://www.geneinfinity.org/sp/sp_codonusage.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eMolecular characterization of sex associated genes\u003c/h3\u003e\n\u003cp\u003eThe genes containing sex specific SNPs were further analysed for the detection of the effect of the SNPs on the structure of the protein and to detect their possible role in determining sex in pengba. The coding region of the amino acid sequences was determined using NCBI ORF finder (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/orffinder/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/orffinder/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The sequences were further assessed for full or partial length using the ExPASy Translation Tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://web.expasy.org/translate/\u003c/span\u003e\u003cspan address=\"https://web.expasy.org/translate/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Gasteiger et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and were submitted to the NCBI database. The ProtParam tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://web.expasy.org/protparam/\u003c/span\u003e\u003cspan address=\"https://web.expasy.org/protparam/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Gasteiger et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) in ExPASy was used to explore the physiochemical parameters of the amino acid sequences. The 3-D protein structure was predicted using the online tool SWISS-MODEL (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://swissmodel.expasy.org/\u003c/span\u003e\u003cspan address=\"https://swissmodel.expasy.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), which predicts the protein structure in an automated way based on homology modelling. The appropriate template having the highest sequence similarity and coverage with the query was selected for homology modelling. Once the template and query sequence were aligned, the 3D model was automatically generated. The alpha helices and beta sheets were deduced using the Mol* Viewer tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://molstar.org/viewer/\u003c/span\u003e\u003cspan address=\"https://molstar.org/viewer/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The SAVES (Version 6.1) (Structural Analysis and Verification Server) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://saves.mbi.ucla.edu/\u003c/span\u003e\u003cspan address=\"https://saves.mbi.ucla.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used for structural and stereochemical quality evaluation, and a Ramachandran plot was generated using the PROCHECK tool. Additionally, the ERRAT quality score and the Verify 3D program aided in validating the modelled protein structures.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003ePhylogenetic tree analysis\u003c/h2\u003e\u003cp\u003eThe derived amino acid sequences from the full-length genes of \u003cem\u003eOsteobrama belangeri\u003c/em\u003e (pengba) were subjected to multiple sequence alignment with their orthologs from \u003cem\u003eSinocyclocheilus rhinocerous\u003c/em\u003e, \u003cem\u003eSinocyclocheilus anshuensis\u003c/em\u003e, \u003cem\u003eCyprinus carpio\u003c/em\u003e, \u003cem\u003eOnychostoma macrolepis\u003c/em\u003e, \u003cem\u003eLabeo rohita\u003c/em\u003e, \u003cem\u003eMegalobrama amblycephala\u003c/em\u003e, \u003cem\u003eMyxocyprinus asiaticus\u003c/em\u003e, \u003cem\u003eMus musculus\u003c/em\u003e (mouse) and \u003cem\u003eHomo sapiens\u003c/em\u003e (human) using Clustal Omega software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ebi.ac.uk/jdispatcher/msa/clustalo?stype=protein\u003c/span\u003e\u003cspan address=\"https://www.ebi.ac.uk/jdispatcher/msa/clustalo?stype=protein\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The sequence alignment obtained was used to construct a neighbour-joining tree with 1000 bootstrap replicates by MEGA11 software in which \u003cem\u003eMus musculus\u003c/em\u003e (mouse) and \u003cem\u003eHomo sapiens\u003c/em\u003e (human) were used as an outgroup (Tamura et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eWhole Genome Sequencing, \u003cem\u003ede novo\u003c/em\u003e assembly and annotation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 43.6 GB of data containing 270 million reads was obtained from the whole genome sequencing of pengba with a mean read length of 161 bp.\u0026nbsp;The generated reads were checked for quality, and low-quality reads were trimmed. After trimming, a total of 40.5 GB of data were yielded, which produced 265 million reads with an average read length of 155 bp, and of these, 20.2 GB and 20.3 GB of data were obtained from male and female, respectively. All reads were subjected to \u003cem\u003ede novo\u003c/em\u003e assembly using the CLC Genomics Workbench with a minimum length parameter of 200 bp and an average GC content of 35%. A total of 5,49,073 scaffolds were generated, with a length of 647,155,667 bp and an N50 value of 67,840. This scaffold was used as a reference genome for mapping of SNPs (Table 1). \u0026nbsp;All the scaffold sequences were searched against GenBank (Sequence database) for putative identification of homologous genes using NCBI-BLAST (Altschul et al.\u003cem\u003e\u0026nbsp;\u003c/em\u003e1990) in Blast2GO, and the sex-related genes were screened. The gene ID, gene name and protein name of the query sequence were mined, and the percentage identity, value and species associated with the query sequence were revealed. A Gene Ontology (GO) annotation summary described the biological role, molecular functions and cellular locations of the genes as depicted in Fig. 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDetection of sex-specific SNPs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the reads were mapped against the assembled reference genome for SNP calling. Altogether, 203 (76.8%) million trimmed reads could be mapped and a total of 8,41,800 SNPs were detected among the four groups and the group-specific SNPs were shown in Fig. 3. To detect sex-associated SNPs, reads of males and females were mapped separately with the reference genome. Mapping of 136.8 million male reads and 129.8 million female reads revealed 9636 (1.1%) male-specific SNPs, 21045 (2.5%) female-specific SNPs, and 7710 (0.9%) common between the groups (Fig. 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDistribution of SNPs in selected genes\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 363 sex-specific genes were selected from the whole genome, of which 68 genes contained 164 SNPs in the genic regions (36 SNPs in the exon and 128 SNPs in the intron), shown in Sup. Table 2.\u0026nbsp;Among these, 36 SNPs were present in the exonic region of 26 genes, which were used for further studies (Table 2). Of the 36 SNPs, 28 altered alleles showed association with females, while the remaining 8 showed association with males. Thirteen non-synonymous SNPs were detected (Table 2), which showed a decrease in protein stability, and 23 SNPs were synonymous in nature. Among the nsSNPs, 4 SNPs resulted in substitution by an amino acid of a different class. All 4 SNPs changed from non-polar to polar amino acids, and the rest did not change the class of amino acid. Among the nsSNPs, 6 SNPs were predicted to be deleterious in nature, while 7 SNPs were neutral on protein function. Out of 23 synonymous SNPs, increased codon preferences were observed for five SNPs, while ten were changed to less preferred and no alteration in the codon preference was found for 8 SNPs (Table 2).\u0026nbsp;Out of 164 SNPs detected, 90 transitions (Ts) and 74 transversions (Tv) were observed with a Ts: Tv ratio of 1.22 across the sex associated genes, where A\u0026harr;G transitions (35%) were most frequent, followed by A\u0026harr;T transversions (21%) (Fig. 4a, b). As expected, the Ts: Tv ratio in the exonic regions was much higher at 2.27 compared to the intronic region, where it was 0.96. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein sequence analysis of the selected genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sequences of 12 full-length genes containing sex specific SNPs were submitted to the NCBI database, are mentioned in Table 3. Among them, four vital sex associated genes containing nsSNPs were assessed for their molecular characterisation and functional annotation. It was found that RAB39B, ITGB1BP1 and ATL3 were hydrophilic in nature, while CLDN10 was hydrophobic. The highest thermostability was observed for ITGB1BP1 protein with an aliphatic index of 94.38, followed by CLDN10 (90.20), ATL3 (82.52) and RAB39B (78.98), indicating potential stability under elevated temperatures. The Molecular weight of RAB39B, ITGB1BP1, CLDN10 and ATL3 proteins was 49.54 kDa, 34.68 kDa, 33.13 kDa and 98.58 kDa, with pI values of 7.09, 5.07, 6.51 and 8.53, respectively. \u0026nbsp;The 3-D protein structure of the four proteins was generated (Fig. 5a-d), and it was observed that RAB39B showed the highest protein structure similarity with \u003cem\u003eSinocyclocheilus anshuensis\u003c/em\u003e, ITGB1BP1 with \u003cem\u003ePundamilia nyererei\u003c/em\u003e, CLDN10 with \u003cem\u003eDanio rario\u003c/em\u003e and ATL3 with \u003cem\u003eBagarius yarrell\u003c/em\u003e, which was used as a template for homology modelling. The ribbon diagram showed 8, 4, 5 and 26 alpha helices, while 7, 7, 5 and 18 beta sheets in RAB39B, ITGB1BP1, CLDN10 and ATL3, respectively and no alteration in the number of helices and beta sheets was found due to mutation (Fig. 5a-d). Ramachandran plot analysis revealed that RAB39B showed the most stable model of pengba with 96.9% of the residues in the most favoured regions, while 3.1% of residues were in the additional allowed region. The Ramachandran plots for the remaining genes are illustrated in Fig. 6a-d. The data statistics showed that the 3-D models generated were stable. By considering both ERRAT score and Verify 3D results, RAB39B was found to be the best model among all the protein models with an ERRAT score of 94.6809, demonstrating the overall quality factor of the initial 3D model, and a Verify 3D score of 86.38%, indicating a more accurate and reliable protein structure model. Moreover, it was observed that in the case of RAB39, the mutation did not cause any alteration in the model quality and structure. In the case of the ITGB1BP1 mutation, there was a minute drop in ERRAT quality, but it slightly improved the stereochemistry. In CLDN10, the effect of the mutation was negligible, and in ATL3, the mutation slightly improved the overall quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhylogenetic studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe phylogenetic tree was constructed using the full-length coding sequences of the sex associated genes containing nsSNPs (Fig. 7a-d). It was observed that \u003cem\u003eO. belangeri\u003c/em\u003e RAB39B clustered closely with \u003cem\u003eCyprinus carpio\u003c/em\u003e, followed by\u003cem\u003e\u0026nbsp;Sinocyclocheilus\u003c/em\u003e \u003cem\u003espp.\u003c/em\u003e, \u003cem\u003eMyxocyprinus asiaticus\u003c/em\u003e and \u003cem\u003eLabeo rohita\u003c/em\u003e. \u003cem\u003eHomo sapiens\u0026nbsp;\u003c/em\u003e(Human) and \u003cem\u003eMus musculus\u0026nbsp;\u003c/em\u003e(house mouse) were used as the mammalian outgroup, which clustered distantly with 67% sequence similarity with the other fish clusters in the gene. The \u003cem\u003eO. belangeri\u003c/em\u003e ITGB1BP1 protein clustered with \u003cem\u003eOnychostoma macrolepis\u003c/em\u003e, \u003cem\u003eCyprinus carpio\u003c/em\u003e, \u003cem\u003eSinocyclocheilus\u003c/em\u003e \u003cem\u003espp\u003c/em\u003e., \u003cem\u003eLabeo rohita\u003c/em\u003e, \u003cem\u003eMyxocyprinus asiaticus\u003c/em\u003e, and \u003cem\u003eMegalobrama amblycephala\u003c/em\u003e. The mammalian outgroup clustered distantly with 84% sequence similarity with the cyprinids in the gene. In case of CLDN10 and ATL3, \u003cem\u003eO. belangeri\u003c/em\u003e clustered closely with \u003cem\u003eOnychostoma macrolepis\u003c/em\u003e and \u003cem\u003eMegalobrama amblychephala\u003c/em\u003e, with outgroups showing 89% and 84% sequence similarity, respectively, with other fishes. Thus, the SNP in \u003cem\u003eOsteobrama belangeri\u003c/em\u003e did not did not change the overall topology of the tree.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cem\u003eOsteobrama belangeri\u003c/em\u003e (Pengba) is a culturally and nutritionally valued medium-sized carp native to rivers and lakes of Northeast India and adjacent regions (Devi et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). It is often reared in polyculture with Indian major carps, but culture performance is limited by slow male growth, disease susceptibility, and feed issues (Deepti et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Because females typically outgrow males (Angel et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), harnessing female growth through all-female culture or selective breeding could greatly improve yields. To enable this, we conducted genome-wide SNP discovery in \u003cem\u003eO. belangeri\u003c/em\u003e to identify genetic markers linked to sex. SNPs are favoured markers in modern aquaculture breeding programs due to their abundance and compatibility with high-throughput genotyping (Liu and Cordes \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Single nucleotide polymorphisms (SNPs) are widely recognized as powerful genomic markers due to their abundance, stability, and amenability to high-throughput genotyping (Liu and Cordes \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Genome-wide SNP discovery has transformed aquaculture genetics, enabling the development of species-specific SNP arrays such as the 7K SNP panel for Atlantic salmon (\u003cem\u003eSalmo salar\u003c/em\u003e) (Karlsson et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), the 250K SNP chip for channel catfish (\u003cem\u003eIctalurus punctatus\u003c/em\u003e) (Liu et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and high-density arrays for genomic selection in salmonids (Houston et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Y\u0026aacute;\u0026ntilde;ez et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In Indian major carp (\u003cem\u003eLabeo rohita\u003c/em\u003e), SNPs have been linked to resistance against \u003cem\u003eAeromonas\u003c/em\u003e infections (Robinson et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). For \u003cem\u003eO. belangeri\u003c/em\u003e, previous studies have relied primarily on mitochondrial DNA (Singh et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Barman et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and microsatellites (Rakkannan et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) for genetic diversity analysis, with sex-linked SNPs remaining unexplored. The present study, therefore, provides the first genome-wide insight into sex-associated SNPs in pengba.\u003c/p\u003e\u003cp\u003eIn total we identified\u0026thinsp;~\u0026thinsp;841,800 putative SNPs in the pengba genome. This is comparatively lower than reported in other teleosts like \u003cem\u003eE. coioides\u003c/em\u003e (6.5\u0026nbsp;million SNPs; Weng et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), \u003cem\u003eProtosalanx hyalocranius\u003c/em\u003e (3.8\u0026nbsp;million SNPs; Li et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and \u003cem\u003eAnguilla japonica\u003c/em\u003e (9.9\u0026nbsp;million; Liu et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This relatively low SNP count is consistent with the reduced genetic diversity previously reported in \u003cem\u003eO. belangeri\u003c/em\u003e by Singh et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) using mtDNA markers, likely reflecting inbreeding and limited founder populations in hatcheries. Among the identified SNPs, 164 were located within 68 sex-associated genes, with 36 in exonic and 128 in intronic regions, yielding a Ts/Tv ratio of 1.22. The exonic SNPs comprised 13 non-synonymous and 23 synonymous substitutions. Most variants were synonymous or intronic; only four were non-synonymous. This skew toward synonymous changes is expected under purifying selection in coding sequences (Ramensky et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Importantly, 11 type I SNPs were identified across seven sex-linked genes (\u003cem\u003eSOX30, ITGB1BP1, LIFR, GGNBP2, ARMC3, HORMAD1\u003c/em\u003e, and \u003cem\u003eAZIN1\u003c/em\u003e), highlighting their potential involvement in sexual differentiation and reproduction. Two nsSNPs (ARMC3.1544A\u0026thinsp;\u0026gt;\u0026thinsp;G and ARMC3.688T\u0026thinsp;\u0026gt;\u0026thinsp;C) in \u003cem\u003eArmadillo repeat-containing protein 3\u003c/em\u003e (\u003cem\u003eARMC3\u003c/em\u003e) increased protein stability in males (ΔG\u0026thinsp;\u0026gt;\u0026thinsp;0). \u003cem\u003eARMC3\u003c/em\u003e plays a critical role in signal transduction, cell adhesion, and motility, and supports sperm capacitation and the acrosome reaction via PKA\u0026ndash;AKAP3 signalling (Huang et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Its expression is elevated in highly active sperm (D\u0026rsquo;Amours et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and exon 11 deletion in cattle leads to premature translation termination, sperm defects, and male infertility (Pausch et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), underscoring its essential role in male reproduction. Another nsSNP (ITGB1BP1.134T\u0026thinsp;\u0026gt;\u0026thinsp;C) in \u003cem\u003eIntegrin beta-1-binding protein 1\u003c/em\u003e (\u003cem\u003eITGB1BP1\u003c/em\u003e) also enhanced protein stability in males. Notably, \u003cem\u003eITGB1BP1\u003c/em\u003e has been reported as a male-biased sex-determining gene in \u003cem\u003eChanna maculata\u003c/em\u003e (Liu et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), where its expression regulates epididymis and efferent duct cell attachment to the extracellular matrix (Snyder et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Conversely, one nsSNP (LIFR.437G\u0026thinsp;\u0026gt;\u0026thinsp;A) in \u003cem\u003eLeukaemia inhibitory factor receptor\u003c/em\u003e (\u003cem\u003eLIFR\u003c/em\u003e) enhanced protein stability in females. LIF\u0026ndash;LIFR signalling promotes ovarian follicle transition (Nilsson et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), bovine oocyte maturation (Mo et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Vendrell-Flotats et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and regulates cell proliferation, differentiation, and survival in mammals (Nicola et al. 2015), as well as neural development in zebrafish (Hanington et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Together, these findings reveal sex-specific molecular signatures that could be exploited for selective breeding.\u003c/p\u003e\u003cp\u003eAdditionally, two male-associated synonymous SNPs (SOX30.384A\u0026thinsp;\u0026gt;\u0026thinsp;G and SOX30.1896C\u0026thinsp;\u0026gt;\u0026thinsp;T) were detected in \u003cem\u003eTranscription factor SOX-30\u003c/em\u003e (\u003cem\u003eSOX30\u003c/em\u003e), which plays a central role in spermiogenesis and male gonadal development in Nile tilapia (Han et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Both variants displayed codon preference in males, suggesting sex-biased functional relevance. A male-specific SNP (GGNBP2.630A\u0026thinsp;\u0026gt;\u0026thinsp;G) in \u003cem\u003eGametogenetin-binding protein 2\u003c/em\u003e (\u003cem\u003eGGNBP2\u003c/em\u003e), a regulator of spermatogenesis and Sertoli cell function (Chen et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), showed association without codon bias. Another synonymous SNP (HORMAD1.510G\u0026thinsp;\u0026gt;\u0026thinsp;T) in \u003cem\u003eHORMA domain-containing protein 1\u003c/em\u003e (\u003cem\u003eHORMAD1\u003c/em\u003e) exhibited increased codon preference in males; notably, knockout of \u003cem\u003eHORMAD1\u003c/em\u003e in mice causes infertility in both sexes (Shin et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Pangas et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), indicating its conserved role in fertility. Male-specific synonymous SNPs were also identified in \u003cem\u003eARMC3\u003c/em\u003e (ARMC3.2796T\u0026thinsp;\u0026gt;\u0026thinsp;C) and \u003cem\u003eAntizyme inhibitor 1\u003c/em\u003e (AZIN1.1242A\u0026thinsp;\u0026gt;\u0026thinsp;G), though neither altered codon preference, while another \u003cem\u003eAZIN1\u003c/em\u003e SNP (AZIN1.1242A\u0026thinsp;\u0026gt;\u0026thinsp;G) enhanced codon preference in females. Mutations in \u003cem\u003eARMC3\u003c/em\u003e are linked with male infertility in cattle (Pausch et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), whereas \u003cem\u003eAZIN1\u003c/em\u003e regulates β-casein expression during mammary gland development in mice (Murakami et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). While most nsSNPs introduced subtle rather than drastic structural changes, these findings are consistent with earlier reports showing that coding variants often exert minor yet biologically relevant effects on protein stability and function (Tokuriki and Tawfik \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Hartl et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Collectively, the identified SNPs provide novel molecular insights into reproductive biology and sex differentiation in \u003cem\u003eO. belangeri\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThis study represents the first genome-wide discovery of sex-linked SNPs in pengba, providing foundational resources for aquaculture genetics. These markers hold promise for developing molecular tools to support monosex culture, early sexing, and reproductive trait improvement. However, a low number of SNPs obtained indicates a significant lack of genetic diversity in \u003cem\u003eO. belangeri\u003c/em\u003e, possibly due to extensive inbreeding in hatcheries and employing inbred species when ranching in the wild. Future research should focus on validating these sex-associated SNPs across larger and more diverse populations, developing SNP chips for high-throughput genotyping, and exploring their utility in comparative studies on sex chromosome evolution in teleosts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eNo animals were harmed during the study. Fin samples were collected using a non-invasive method (fin clipping) solely for the purpose of genome sequencing. Fin samples were collected using a non-invasive method (fin clipping) solely for the purpose of genome sequencing. The anesthetic agent MS‐222 was used during fin-clipping procedures to facilitate safe and efficient handling of the fish.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to the Vice Chancellor, Central Agricultural University, Imphal and Dean College of Fisheries, CAU(I), Lembucherra, Tripura, India, for providing all the facilities to conduct the present research work and thankful to ICAR for providing a fellowship to the first author. The authors are also thankful to Department of Biotechnology (DBT), Government of India for providing fund for Pengba genome sequencing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe genome sequencing was supported under Phase II of the Centre of Excellence in Fisheries and Aquaculture Biotechnology (CoE-FAB), Department of Biotechnology (DBT), Government of India.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics, Consent to Participate, and Consent to Publish declarations:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study involved only routine, non-invasive sampling of fish from aquaculture facilities. Formal ethics approval was not required; however, all procedures were carried out in accordance with institutional guidelines for the ethical handling of aquatic organisms and complied with relevant national regulations (CPCSEA norms, Government of India). The study was approved by the College Research Advisory Committee (CRAC), College of Fisheries, CAU (Imphal), Tripura.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDAS statement request:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe genome sequence datasets generated and analysed during the current study are available from the corresponding author upon reasonable request. However, the full-length sequences used in the study have been deposited in the GenBank database (NCBI), and the corresponding accession numbers are provided in Table 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo potential conflict of interest was reported by the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAltschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. 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Mol Ecol Resour. 2016;16(4):1002\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/1755-0998.12503\u003c/span\u003e\u003cspan address=\"10.1111/1755-0998.12503\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang D, Xie D, Lin X, Ma L, Chen J, Zhang D, Wang Y, Duo S, Feng Y, Zheng C, Jiang B, Ning Y, Han C. The transcription factor SOX30 is a key regulator of mouse spermiogenesis. Development. 2018;145(20):dev164723. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1242/dev.164723\u003c/span\u003e\u003cspan address=\"10.1242/dev.164723\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhou T, Bao L, Liu S, Dunham R, Liu Z. Development of a high-density SNP array and its application in genomic selection for the catfish aquaculture industry. Anim Genet. 2018;49(6):599\u0026ndash;604. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/age.12715\u003c/span\u003e\u003cspan address=\"10.1111/age.12715\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhou X, Ren L, Li Y, Zhang M, Yu Y, Yu J. The next-generation sequencing technology: A technology review and future perspective. Sci China Life Sci. 2010;53(1):44\u0026ndash;57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11427-010-0032-6\u003c/span\u003e\u003cspan address=\"10.1007/s11427-010-0032-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDe novo\u003c/em\u003e assembly statistics\u003c/strong\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAssembly Statistics\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo. of Scaffolds\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5,49,073\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal Scaffold Length (bp)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e647,155,667\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eScaffold N50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67,840\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo. of Contigs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5,58,342\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal Contig Length (bp)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e646,613,697\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eContig N50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e71,901\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\"\u003e\u003cstrong\u003eTable 2. List of sex-associated genes\u003c/strong\u003e\u003c/div\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eS.No.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene Name\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCDS/SNP position\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSNP type*\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNS/S\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAlt. AA\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEffect\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRAB39B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-1302, 450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGA\u003cstrong\u003eG\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;GA\u003cstrong\u003eA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreasing codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eITGB1BP1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1- 948, 134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA\u003cstrong\u003eT\u003c/strong\u003eG\u0026thinsp;\u0026gt;\u0026thinsp;A\u003cstrong\u003eC\u003c/strong\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMet\u0026thinsp;\u0026gt;\u0026thinsp;Thr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCLDN10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-921, 392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003cstrong\u003eG\u003c/strong\u003eT\u0026thinsp;\u0026gt;\u0026thinsp;T\u003cstrong\u003eC\u003c/strong\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCys\u0026thinsp;\u0026gt;\u0026thinsp;Ser\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCERS2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-\u0026gt;927, 263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003cstrong\u003eG\u003c/strong\u003eA\u0026thinsp;\u0026gt;\u0026thinsp;C\u003cstrong\u003eA\u003c/strong\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArg\u0026thinsp;\u0026gt;\u0026thinsp;Gln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eATL3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-2631, 2066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG\u003cstrong\u003eG\u003c/strong\u003eC\u0026thinsp;\u0026gt;\u0026thinsp;G\u003cstrong\u003eA\u003c/strong\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGly\u0026thinsp;\u0026gt;\u0026thinsp;Asp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eARMC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-\u0026gt;3105, 1544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u003cstrong\u003eA\u003c/strong\u003eG\u0026thinsp;\u0026gt;\u0026thinsp;C\u003cstrong\u003eG\u003c/strong\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGln\u0026thinsp;\u0026gt;\u0026thinsp;Arg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-\u0026gt;3105, 688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003eGC\u0026thinsp;\u0026gt;\u0026thinsp;\u003cstrong\u003eC\u003c/strong\u003eGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCys\u0026thinsp;\u0026gt;\u0026thinsp;Arg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-\u0026gt;3105, 2796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCA\u003cstrong\u003eT\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;CA\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo change\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTRIM75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1-999, 910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003eAT\u0026thinsp;\u0026gt;\u0026thinsp;\u003cstrong\u003eC\u003c/strong\u003eAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsn\u0026thinsp;\u0026gt;\u0026thinsp;His\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1-999, 330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGA\u003cstrong\u003eG\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;GA\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlu\u0026thinsp;\u0026gt;\u0026thinsp;Asp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSOX30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-2088, 384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAC\u003cstrong\u003eA\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;AC\u003cstrong\u003eG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-2088, 1896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAT\u003cstrong\u003eC\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;AT\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTDRD1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1-873, 36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCT\u003cstrong\u003eG\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;CT\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eEI24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-\u0026gt;1161, 405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTC\u003cstrong\u003eG\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;TC\u003cstrong\u003eA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo change\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-\u0026gt;1161, 426\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTC\u003cstrong\u003eC\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;TC\u003cstrong\u003eA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDRC11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-\u0026gt;510, 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGC\u003cstrong\u003eA\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;GC\u003cstrong\u003eG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAla\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFAM83B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-2043, 1428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAA\u003cstrong\u003eA\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;AA\u003cstrong\u003eG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo change\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHORMAD1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-\u0026gt;1359, 510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGT\u003cstrong\u003eG\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;GT\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRY1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-876, 525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGC\u003cstrong\u003eA\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;GC\u003cstrong\u003eG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAla\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDUSP1-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-1395, 1257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCT\u003cstrong\u003eC\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;CT\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo change\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKNG1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-1398, 291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTG\u003cstrong\u003eC\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;TG\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAZIN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-1311, 131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGA\u003cstrong\u003eC\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;GA\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo change\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNCF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1-1170, 102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTT\u003cstrong\u003eT\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;TT\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo change\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePOGLUT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-3498, 981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCC\u003cstrong\u003eA\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;CC\u003cstrong\u003eG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSHANK1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-\u0026gt;1056, 513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTC\u003cstrong\u003eA\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;TC\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCCNP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1-1005, 69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCT\u003cstrong\u003eG\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;CT\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eHRAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-618, 207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGA\u003cstrong\u003eT\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;GA\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo change\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-618, 186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGA\u003cstrong\u003eA\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;GA\u003cstrong\u003eG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eRAB39B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-1302, 314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG\u003cstrong\u003eT\u003c/strong\u003eC\u0026thinsp;\u0026gt;\u0026thinsp;G\u003cstrong\u003eA\u003c/strong\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVal\u0026thinsp;\u0026gt;\u0026thinsp;Asp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-1302, 315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGT\u003cstrong\u003eC\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;GT\u003cstrong\u003eA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLIFR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1-1686, 437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eA\u003cstrong\u003eG\u003c/strong\u003eA\u0026thinsp;\u0026gt;\u0026thinsp;A\u003cstrong\u003eA\u003c/strong\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArg\u0026thinsp;\u0026gt;\u0026thinsp;Lys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCNTN5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1-\u0026gt;1275, 418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eG\u003c/strong\u003eGA\u0026thinsp;\u0026gt;\u0026thinsp;\u003cstrong\u003eA\u003c/strong\u003eGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGly\u0026thinsp;\u0026gt;\u0026thinsp;Arg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGMPR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1-2244, 287\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG\u003cstrong\u003eC\u003c/strong\u003eT\u0026thinsp;\u0026gt;\u0026thinsp;G\u003cstrong\u003eT\u003c/strong\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAla\u0026thinsp;\u0026gt;\u0026thinsp;Val\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTRIM75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;1-999, 223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003eAA\u0026thinsp;\u0026gt;\u0026thinsp;\u003cstrong\u003eC\u003c/strong\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLys\u0026thinsp;\u0026gt;\u0026thinsp;Gln\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased stability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGGNBP2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-\u0026gt;2175, 630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAG\u003cstrong\u003eA\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;AG\u003cstrong\u003eG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo change\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAZIN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1-1311, 1242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGA\u003cstrong\u003eA\u0026thinsp;\u0026gt;\u003c/strong\u003e\u0026thinsp;GA\u003cstrong\u003eG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreased codon preference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e#Full gene name in Sup Table\u0026nbsp;1; *Altered codon is sex associated; NS: Non-Synonymous; S: Synonymous; F: Female; M: Male\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab3\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of sequences with complete ORF\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSl. No.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene Name\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSequence length (start codon\u0026thinsp;+\u0026thinsp;exon\u0026thinsp;+\u0026thinsp;stop codon)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNCBI accession number\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSOX30 (Transcription factor SOX-30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePV464453\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRAB39B (Ras-related protein Rab-39B)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePV568094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFAM83B (Protein FAM83B)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePV573996\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCRY1 (Cryptochrome-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePV573997\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDUSP1-A (Dual specificity protein phosphatase 1-A)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePV573998\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKNG1 (Kininogen-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePV600739\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAZIN1 (Antizyme inhibitor 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePV600740\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePOGLUT2 (Protein O-glucosyltransferase 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePV634343\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHRAS (GTPase HRas)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePV634344\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eITGB1BP1 (Integrin beta-1-binding protein 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePV634345\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCLDN10 (Claudin-10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePV789843\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eATL3 (Atlastin-3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePV789844\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pengba, Genome sequencing, Type I marker, Single Nucleotide Polymorphism, Sex association","lastPublishedDoi":"10.21203/rs.3.rs-8163459/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8163459/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eOsteobrama belangeri\u003c/em\u003e, the state fish of Manipur, exhibits sexual dimorphism, with females growing faster than males, making it a promising candidate for monosex culture in aquaculture. To identify sex-associated SNP markers, whole-genome sequencing was performed on 20 individuals (10 males, 10 females) using the Illumina NovaSeq platform. Sequencing generated 40.5 GB of high-quality reads, which were assembled \u003cem\u003ede novo\u003c/em\u003e into 5,49,073 scaffolds. SNP discovery revealed a total of 8,41,800 variants, including 9,636 male-specific and 21,045 female-specific SNPs. Among 363 candidate genes analysed, 68 contained 164 genic SNPs (36 exonic and 128 intronic) with a Ts/Tv ratio of 1.22. The exonic SNPs comprised 13 non-synonymous and 23 synonymous substitutions, with a shift in codon preference. Notably, 11 type I SNPs were identified across seven key sex-associated genes. Of these, four were non-synonymous, with three predicted to enhance protein stability in males, while only one such SNP was observed in females. These sex-associated SNPs represent promising markers for monosex culture, early sex determination, and reproductive trait studies. Their further validation could facilitate the development of SNP chips for marker-assisted selection in \u003cem\u003eO. belangeri\u003c/em\u003e.\u003c/p\u003e","manuscriptTitle":"Genome-Wide Screening Reveals Sex-Specific SNP Markers in Pengba (Osteobrama belangeri)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-09 09:18:28","doi":"10.21203/rs.3.rs-8163459/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2da91dc3-3ab0-481b-b287-d90043c6a456","owner":[],"postedDate":"December 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-08T08:43:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-09 09:18:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8163459","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8163459","identity":"rs-8163459","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}