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Article

Population Genomics and Application for Growth Improvement of Domesticated Asian Seabass Lates calcarifer from Thailand

by
Bavornlak Khamnamtong
1,†,
Atra Chaimongkol
2,†,
Sirikan Prasertlux
1,
Sirithorn Janpoom
1,
Jutaporn Chaimongkol
2,
Sureerat Tang
1,
Wanwipa Ittarat
1,
Putth Songsangjinda
3,
Takashi Sakamoto
4,
Panya Sae-Lim
5,6 and
Sirawut Klinbunga
1,*
1
Aquatic Molecular Genetics and Biotechnology Research Team, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Khlong Nueng, Khlong Luang, Pathum Thani 12120, Thailand
2
Coastal Aquaculture Technology and Innovation Research and Development Center, Department of Fisheries, Ministry of Agriculture and Cooperative, Songkhla 90000, Thailand
3
Department of Fisheries, Ministry of Agriculture and Cooperative, Chatuchak, Bangkok 10900, Thailand
4
Department of Aquatic Biosciences, Tokyo University of Marine Science and Technology, Tokyo 108-8477, Japan
5
Faculty of Veterinary Medicine, Rajamangala University of Technology Srivijaya, Songkhla 90000, Thailand
6
MOWI Genetics AS, 5835 Bergen, Norway
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Diversity 2025, 17(6), 383; https://doi.org/10.3390/d17060383
Submission received: 14 April 2025 / Revised: 27 May 2025 / Accepted: 27 May 2025 / Published: 29 May 2025
Browse Figures
Versions Notes

Abstract

:
A breeding program of Asian seabass (Lates calcarifer, also called barramundi) was established for sustainable aquaculture in Thailand. Estimated breeding values (EBVs) for growth of the base population (G0, 51 families, N = 1655) were evaluated. Fish exhibited either high (HEBV, averaged body weight = 1036.80 ± 250.80 g, N = 133) or low (LEBV, averaged body weight = 294.50 ± 167.20 g, N = 147) growth EBVs, and their parental fish (N = 26) were analyzed by Specific Locus Amplified Fragment Sequencing (SLAF-Seq). An average of 159,769 SLAF tags/sample was generated, covering 13.79-fold of the genome size, and 225,498 SNPs were applied for population genomics. Observed (Ho) and expected (He) heterozygosity values were 0.224 and 0.308, 0.178 and 0.246, and 0.184 and 0.305, respectively. Polymorphic information content (PIC) ranged from 0.205–0.251. A selective sweep was performed based on Fst, and nucleotide polymorphism (π) revealed significant differences between allelic contents of growth- and immune-related genes in HEBV and LEBV populations. Kinship analysis revealed that 84.38% of examined fish showed r values < 0.2, and population admixture analysis revealed three subpopulations in HEBV and four subpopulations in LEBV groups. Fish that possessed a single cluster were found in each subgroup of both populations, along with those exhibiting mixed ancestral clusters. This information is critically important for further applications in our ongoing seabass improvement breeding program.

1. Introduction

Genome-wide analysis of single-nucleotide polymorphism (SNP) provides essential data to support domestication and breeding programs for aquaculture species [1]. Genomic localization of positive selection signals reflects long-term natural selection and short-term artificial selection during the establishment of cultured stocks and may promote improved performance in commercial traits [2,3,4]. Appropriate mating between brooders from different families/populations is the key factor for success in breeding programs of aquaculture species [5]. Population genomics is useful for the application of genetic data to assist breeding programs of economically important species.
Genome-wide SNPs analysis allows for identification of selection signatures in a genome as reduced heterozygosity in (and/or surrounding) genes associated with important traits that are affected by domestication and selection [6]. Selective sweep analysis has been used in several applications such as identifying genomic signatures for selection, determining the impact of recent artificial selection, domestication, and climate adaptation [3,7,8,9,10].
Whole genome sequencing (WGS) data are ideal for evaluation of estimated breeding values (EBVs) at the genome-wide scale and SNPs involved with quantitative complex traits [11]. In aquaculture species, WGS has been applied to produce genomic resources of several important commercial species [1]. For the identification of SNPs associated with commercial traits, a large number of samples is required. Cost-effective approaches like SNP arrays and genotyping by sequencing (GBS) based on reduced representation library (RRL) approaches have been extensively applied to generate genome-wide SNP genotype data [12]. Although RRLs (e.g., restriction-site associated DNA sequencing; RAD-Seq and double-digestion RAD-Seq, ddRAD-Seq) impose limitations on the coverage of functional regions, they are effective for identifying phenotype-associated markers for molecular selection and genomic selection in aquaculture species when combined with genome-wide association studies (GWAS) and genomic best linear unbiased prediction (GBULP) [1,11,12,13,14,15,16].
Specific Length Amplified Fragment Sequencing (SLAF-Seq), an improved version of GBS, is a high-throughput sequencing approach used for the identification of SNPs [6,17]. SLAF-Seq is a de novo SNP discovery and genotyping approach that uses an enhanced RAD-Seq method to avoid repetitive sequences. This approach does not require reference genome sequences. Large numbers of samples and SNP loci could be analyzed simultaneously [17].
Asian seabass (Lates calcarifer, also called barramundi) is a commercially important species in Thailand [18]. It has been cultured worldwide for several decades and is regarded as a highly priced commercial species [19,20]. The aquaculture production of L. calcarifer in Thailand was >400,000 tons in 2022 [21]. Asian seabass are protandrous hermaphrodites. They first mature as males at 2–4 years old and subsequently undergo sex conversion to females, such that large numbers of fish cannot be sexed [22]. This results in uneven sex ratios at different ages after initial maturation [20]. Owing to a long generation period, selective breeding programs for the improvement of commercially important traits (e.g., growth and/or disease resistance) based on molecular approaches were not implemented in Thailand.
Selective breeding programs for the improvement of economically important traits are crucial for elevating the culture and production efficiency of L. calcarifer [19,20,22,23]. For the past decade, the Department of Fisheries, Thailand (DOF) has operated a domestication program for L. calcarifer based on a mass spawning approach. Established stocks were maintained separately in several Research and Development Centers. However, genetic improvement of these stocks was not carried out.
Recently, a genetically based breeding program for L. calcarifer was established. Domesticated Asian seabass stocks were acquired from previously cultivated Asian seabass broodstock rather than from wild populations. Genetic diversity of each stock was evaluated using microsatellite polymorphism. Moderate levels of genetic diversity were observed. Significant genetic differences between most pairwise comparisons were found (p < 0.001). Phylogenetic and population admixture analyses clearly indicated two different genetic clusters of recruited stocks [5]. Subsequently, inter-populational crosses between these acquired stocks were carried out to increase the genetic diversity above that of the original stocks. A high heritability estimate (h2) for growth in the G0 population was found (0.386 ± 0.020 at 519 days post hatch, N = 1655 from 51 families), suggesting the potential for growth improvement of the newly established population [5].
In L. calcarifer, Diversity Array Technology-Sequencing (DArTseq) and GWAS were applied, and four growth-associated SNPs were identified [11]. However, population genomics [24,25] and selective sweeps for selective breeding programs and brooder selection of L. calcarifer have not yet been reported.
Initially, EBVs for growth [5] of the G0 population of L. calcarifer were evaluated. Subsequently, fish with high (N = 133) and low (N = 147) EBVs for growth were chosen and subjected to population genomic analysis using SLAF-Seq. The information obtained revealed subdivisions within high and low EBV (HEBV and LEBV) populations and their admixture between different genetic lineages. The information obtained could be applied to assist in the selection of brooders to improve subsequent generations.

2. Materials and Methods

2.1. Stock Maintenance and Rearing

To generate the G0 population of the breeding program, a partial diallelic cross was carried out in 2020 using brooders from six cultivated stocks (Chachoengsao, Chachoengsao 1, Chachoengsao 2, Songkhla, Trang, and Phuket). Artificial fertilization was intermittently performed on 22 males and 26 females to generate 51 G0 families (Table S1). The brooders (P0 population) and their offspring (G0) were maintained at the DOF facilities, Songkhla province.
When fish reached approximately 75 g in weight, fingerlings from each family (N = 30–50) were pit-tagged and further maintained in a 266 m2 concrete pond (water volume = 425 m3, N = 2027) as described previously [5]. The G0 fish exhibiting high and low EBVs for body weight at 519 dph (N = 133 from the greatest EBVs and N = 147 from the lowest EBVs for respective groups) and a sample of 26 P0 individuals chosen at random were subjected to SLAF-Seq and population genomic analysis.

2.2. Estimation of EBVs for Growth

EBVs for growth were estimated with best linear unbiased prediction (BLUP) in the mixed model equation [26] as previously described [5,27]. The estimate was evaluated using MME in ASReml 4.0 [28].

2.3. DNA Extraction

Genomic DNA was extracted from the dorsal spine of each fish using a GF-1 Tissue DNA Extraction Kit (Vivantis Technologies, Selangor, Malaysia). The quality (0.8% agarose gel electrophoresis and OD260/OD280) and quantity (OD260) of extracted DNA were estimated. DNA was kept at −20 °C until further use.

2.4. SLAF-Sequencing

Total genomic DNA was subjected to the preparation of the SLAF libraries. The libraries were generated using the method previously described [24]. To select the appropriate restriction enzymes for the construction of SLAF libraries, Lates_calcarifer: GCF_001640805.2 was chosen as the reference genome. Genomic DNA was digested with HaeIII and Hpy166II. Dual-index sequencing adapters were added at the 3′ and 5′ ends of the digested DNA products. PCR was performed, and the products were purified using an E.Z.N.A.H Cycle Pure Kit (Omega, GA, USA). The purified products were mixed and incubated with HaeIII and Hpy166II again. After ligation of paired-end Solexa adaptors, the reaction products were purified using a Quick Spin column (Qiagen, Venlo, The Netherlands) and subjected to agarose gel electrophoresis (2%). Fragments of 364–414 bp in length were eluted from the gel using a Gel Extraction Kit (Tiangen Biotech, Beijing, China). PCR was carried out to add barcodes. The resulting products were re-amplified. Paired-end sequencing was performed on an Illumina HiSeq sequencing platform (Illumina, CA, USA).

2.5. Population Genomics Data Analysis

Adaptor sequences, poly N, and low-quality sequence reads were removed from raw reads using fastp software version 0.21.0 [29]. Downstream analysis was performed using clean reads. Q30 and GC-content were calculated. SNP/INDEL calling was performed using GATK v3.8 [30] and SAMtools v1.9.1 packages [31]. SNPs with a minor allele frequency (MAF) > 0.05 and locus integrity > 0.5 retained. SNP annotation was performed against the reference genome (Lates calcarifer: GCF_001640805.2) using snpEff software 3.6c [32].
Gene functions were annotated against various databases: Nr (NCBI non-redundant protein sequences [33,34,35,36], Pfam (protein family) [37,38], KOG/COG (clusters of orthologous groups of proteins) [39], Swiss-Prot (a manually annotated and reviewed protein sequence database) [40], KO (KEGG ortholog database) [41,42,43], and GO (gene ontology) [44].
For analysis of phylogenetic relationships between examined samples, a neighbor-joining tree was constructed using a p-distance model in MEGA-CC software version X [45], with 1000 bootstrap replicates.
Principal component analysis (PCA) [46] of SNP data across samples was conducted to determine the clustering status of examined populations using the smartPCA program version 6.0 in the EIGENSOFT package [47]. The first two PCs were used to explain the variation.
Kinship between individuals in populations was estimated using GCTA v1.92.1 [48]. Linkage disequilibrium (LD) analysis was calculated between each pair of SNPs using PopLDdecay v3.41 software [49]. The squared correlation coefficient (r2) values were analyzed for all chromosomes with a 1000 kb window.
Genome-wide detection of selective sweep regions was performed by calculating the population genetic index of all SNPs within a sliding window of 100 kb bins with 10 kb steps. Population differentiation fixation index (Fst) and nucleotide polymorphism (π) were calculated using vcftools v0.1.15 [50]. The nucleotide diversity level was measured using a 100 kb window with a step size of 10 kb for each population.
Population admixture analysis was examined using ADMIXTURE (v1.22) [51] with K values (the putative number of populations) ranging from 1 to 10. The number of sub-populations was assessed using five-fold cross-validation. The clustering results were cross-verified to determine the optimal number of subgroups according to the valley value of the cross-validation error rate. The Q matrix for each K value, stacked assignment bar plots were generated using the R package Pophelper (http://royfrancis.github.io/pophelper, accessed on 22 November 2024).

3. Results

3.1. EBVs for Growth of L. calcarifer G0

EBV values estimated following the mixed model equation have properties according to BLUP analysis, commonly applied for EBV estimation. The mean EBVs (519 dph) for the founder population were 0 (−343.62–+446.55, Figure 1A). In total, 133 fish exhibiting the highest EBV values from the top and 147 fish exhibiting the lowest EBV values from the bottom were collected. The LEBV group exhibited body weights between 141.20 and 802.20 g (average BW = 294.50 ± 167.20 g), while the HEBV group exhibited body weights between 635.40 and 2000.00 g (average BW = 1036.80 ± 250.80 g) [5].

3.2. SLAF-Seq Library Preparation and Processing

Simultaneous digestion of L. calcarifer genomic DNA with HaeIII + Hpy166II generated digested fragments of 364–414 bp in length (Figure 1B). An average SLAF tag per sample of 159,769 was generated while the mean sequencing depth of SLAF tags was 13.79× the L. calcarifer genome.
The average GC content for LEBV, HEBV, and parental groups of L. calcarifer in this study was 38.74, 40.41, and 40.68%, and the Q30 values were 95.54, 95.76, and 95.59%, respectively (Table 1). In total, 1600.80 Mb reads were generated by sequencing, and 389,719 SLAF tags were obtained. Among them, 257,893 polymorphic SLAF tags were annotated to various chromosomes of L. calcarifer (Figure 1C). The lowest number of SLAF tags of 8188 was annotated for chromosome 14, while the greatest number of SLAF tags was allocated to chromosome 7 (Table 2). In total, 1,748,411 SNPs were detected. SNPs were retained for downstream analysis if MAF ≥ 0.05 and locus integrity ≥ 0.5, and 225,498 SNP loci were obtained. Comparatively high numbers of sequences (99.52, 99.49, and 99.47%) could be mapped to the reference genome, and 89.21, 89.31, and 90.89% could be properly mapped in respective populations (Table 1).

3.3. Intrapopulation Diversity of Domesticated L. calcarifer

The expected allele number (Ae) and heterozygosity (He) in HEBVs (1.497 & 0.308) were greater than those in the parental group (1.455 & 0.305) and LEBV (1.363 & 0.246) group. Generally, the observed allele number (Ao) was greater than the expected parameters. Ao in the parental population was 1.914, but increased values of 1.951 and 1.984 were found in the LEBV and HEBV groups. In contrast, Ho was lower than He across all populations, and the Ho values varied from 0.178 and 0.184 in the LEBV and parental populations, respectively, and to 0.224 in the HEBV population. Both HEBV and parental populations exhibited a greater PIC than the LEBV group (0.251 and 0.249 compared with 0.205). However, the parental group had a Nei diversity index of 0.317, which was greater than those of HEBV (0.309) and LEBV (0.247) groups. Interestingly, the HEBV and parental group showed higher Shannon Wiener indices of 0.472 and 0.470, respectively, compared with 0.392 for the LEBV population (Table 3). The average MAF values were 0.220, 0.167, and 0.217, respectively.

3.4. Phylogenetic Analysis and PCA

A neighbor-joining tree allocated examined samples into several subgroups. Eight fish individuals that exhibited HEBVs for body weight were misallocated to the LEBV group. In contrast, only three fish with LEBVs were placed in the HEBVs clade. Nearly identical numbers of parents were phylogenetically allocated to either HEBV (N = 14, accounting for 53.85%) or LEBV clade (N = 12, 46.15%) (Figure 2A). PCA results also supported the genetic difference between HEBV and LEBV groups of domesticated L. calcarifer (Figure 2B).

3.5. Relatedness Between HEBV and LEBV Populations of Domesticated L. calcarifer

From kinship analysis, negative relatedness values (r) were found in 68.645% of the counts. The additional group of 15.735% exhibited r values between 0.0–0.2. The remaining samples (15.620%) exhibited r > 0.2 (Table 4). The rxy values < 0.125 corresponded to unrelated individuals, while 0.125 ≤ rxy ≤ 0.375 corresponded to half-siblings, and rxy > 0.375 was regarded as full-siblings [52,53]. This suggested relatively low levels of inbreeding coefficient in the newly established population of domesticated L. calcarifer. LD analysis was performed, and the value in the LEBV population was greater than that in the HEBV population (Figure 3).

3.6. Selective Sweep, GO, and KEGG Enrichment Analysis

Selective sweep analysis reflects positive selection within a genome. From genome scanning based on the Fst and π1/π2 analysis, large differences between HEBV and LEBV groups of L. calcarifer were found in several chromosomes (Figure 4). In total, 731 and 205 genes were identified when Fst and π1/π2 approaches were applied (p < 0.01). This identified 120 and 99 genomic regions that contained significantly lower SNP heterozygosity in HEBV fish when compared to LEBV fish, respectively (Tables S2 and S3). The Fst approach indicated that 266, 115, and 64 genes located on chromosomes 15, 18, and 4, respectively, revealed significantly reduced heterozygosity. The remaining chromosome contained ≤ 27 significant genes (p < 0.01). The analysis based on π2/π1 further indicated clear differences in large portions of chromosome 18 (48 genes), followed by chromosomes 7_2 (24), 8 (17), 15 (15), and 14 (13).
Considering significantly different allele contents between HEBVs and LEBVs following both Fst and π2/π1 approaches, 140 genes located in 34 regions were found, and 20, 17, 15, and 13 genes were located in chromosomes 18, 8, 7_2, and 14, respectively (Table S4). Examples of growth-related genes were fibroblast growth factor 12-like (LcFgf12), myosin heavy chain, muscle-like (LcMhc), TGF-beta receptor type-2-like (LcTgfbr2), thyrotropin-releasing hormone-degrading ectoenzyme (LcTrh-de), meiosis expressed gene 1 protein (LcMeig1), RCC1 and BTB domain-containing protein 1-like (LcRcbtb1), cyclin-D-binding Myb-like transcription factor 1 (LcDmtf1), gamma-tubulin complex component 3 (Lctubgcp3), kinesin heavy chain-like (Lckif), G1/S-specific cyclin-D1-like (LcCcnd1) zinc finger CCCH domain-containing protein 13-like (LcZc3H13), and hydroxysteroid dehydrogenase-like protein 2 (LcHsd2).
In addition, several genes functionally related to innate and humoral immunity and stress responses also showed significant allele content differences between HEBV and LEBV fish. They were carbonic anhydrase-like (LcCahz), double-stranded RNA-specific editase B2 (LcAdarb2), low affinity immunoglobulin gamma Fc region receptor II-a-like (LcFcgr2a), LcFcgr2b, LcFcgr3, NF-kappa-B-activating protein-like (LcNkap), NF-kappa-B-repressing factor-like (LcNkrf), bestrophin-3 isoform X1 (LcBest3), T-complex protein 1 subunit beta (LcCct2), protocadherin beta-16-like (LcPcdhb16), protocadherin gamma-A2-like (LcPcdhga2), LcPcdhga11 and LcPcdhga12, and dnaJ homolog subfamily B member 6-like (LcDnajb6).
Genes identified by selective sweep analysis (p < 0.01) were further analyzed by gene ontology (GO) enrichment analysis. Significant differences between G0 fish with HEBVs and LEBVs regarding the biological process were found. Of these, genes in immune response were the most abundant group, followed by lipoprotein metabolic process and lipid transport (Figure 5A). This implied possible differences in immunity performance between fish in high and low growth groups. For the cellular component, differences between allele contents of genes categorized in vacuole, autophagosome, filopodium, peroxisome, and connexin complex were found (Figure 5C). For molecular function, genes in lipid binding predominated, followed by those categorized in transition metal binding and chemokine activity (Figure 5E).
In addition, KEGG enrichment analysis revealed significant differences in the cytokine-cytokine receptor interaction pathway, followed by those functionally involved with Samonella infection, purine metabolism, and spliceosome (Figure 5G). GO and KEGG enrichment analysis based on π_1/π_2 (p < 0.01) are shown in Figure 5B,D,F,H, respectively.

3.7. Genetic Distance and Population Admixture Analysis

Genetic diversity within each population was 6.049 × 10−5, 4.668 × 10−5, and 4.277 × 10−5 for HEBV, LEBV, and parental populations, respectively. Pairwise genetic distance based on the Fst statistics was 0.106 between HEBVs-LEBVs, 0.026 between HEBVs-parents, and 0.087 between LEBVs-parents.
Seven (K = 7, Figure 6A) lineages of L. calcarifer, with clear differences between HEBV and LEBV fish, were found. Interestingly, they were allocated to different clusters and were not highly mixed between different clusters (Figure 6B). The LEBV fish could be further divided into four subpopulations (L-1, L-2, L3, and L-4, Figure 6C–F) while the HEBV fish could be further divided into three subpopulations (H-1, H-2, and H-3, Figure 6G–I).
Considering the LEBV subgroups, all individuals of LEBV-subgroup 2 (L-2) revealed a pure LEBV genetic lineage, while only a few LEBV-subgroup 4 (L-4) individuals were genetically mixed with other genetic lineages. The existence of both pure and higher frequencies of individuals with mixed lineages was found in LEBV-subgroups 1 (L-1) and 3 (L-3). Similarly, both pure and mixed genetic lineages were found in HEBV subgroups 1 (H-1, Figure 6G), H-2 (Figure 6H), and H-3 (Figure 6I). Together, patterns of population admixture analysis and EBV ranks could be combined to assist the mating plan within and between H-1, H-2, and H-3 subpopulations in our ongoing breeding program of L. calcarifer.

4. Discussion

4.1. Population Genomic Studies of Domesticated L. calcarifer

The main objective for breeding programs is the production of broodstock and fingerlings with better growth performance than that of parents [54,55,56]. Our present G0 population of L. calcarifer was established from inter-populational crosses between six cultivated stocks (Chachoengsao, Chachoengsao 1, Chachoengsao 2, Songkhla, Trang, and Phuket) [5]. A greater genetic diversity in the G0 population (average number of alleles per locus was 9.286, Ho = 0.804, He = 0.754, and Ne = 18.1) than in the parental populations (average NA = 6.647, Ho = 0.609, He = 0.628, and Ne = 6.2–13.5) was observed.
Although microsatellite analysis revealed useful information on the genetic diversity of the newly established stock, the use of population genomic data based on SNP polymorphism generated by high-throughput sequencing provided additional information to assist breeding of L. calcarifer. The LEBV and HEBV groups (N = 133 and 147) were further genotyped in this study. In total, 221949, 214,420, and 206,202 polymorphic SNPs were identified in HEBV, LEBV, and parental populations, respectively. The observed number of alleles in HEBV (1.984) and LEBV (1.951) was greater than that in the parental population (1.914). Other parameters (Ho, He, PIC, and Shannon Wiener index) in the HEBV were higher than those in the parental and LEBV groups in order. Therefore, HEBV fish possessed a greater level of genetic diversity than LEBV fish. Disregarding the limited sample size (N = 26), genetic diversity of the parental population seemed to be lower than that of the HEBV stock but slightly greater than that of the LEBV stock.

4.2. Genetic Differentiation of HEBV and LEBV Populations

Previously, microsatellite polymorphism was applied and indicated significant genetic differentiation between HEBV and LEBV stocks [5]. In the present study, phylogenetic analysis based on SNP polymorphism further confirmed these genetic differences between HEBV and LEBV populations, as most individuals of each group (93.985 and 97.959%) were correctly allocated into the same phylogenetic lineage. This critically indicated that EBV values could be applied to improve the growth performance of our L. calcarifer populations. Crossbreeding was performed between phylogenetic clusters of parental stocks and between stocks within the same phylogenetic clusters. We speculated that the clear genetic differentiation between the HEBV and LEBV clusters would result in more successful outcomes than breeding within the same clusters.
Results from PCA clustering of the three populations were consistent and showed that the HEBV and LEBV G0 populations were genetically differentiated. Each population was related to the parental population. However, several individuals of the HEBV population were distributed in different dimensions. The PCA plot displayed the distribution of individuals into groups, and they could be clearly separated by three eigenvectors, which further supported the significant genetic differences among individuals from HEBV and LEBV groups. This was reflected by higher degrees of pairwise genetic differentiation between HEBV-LEBV G0 than HEBV-parents and LEBV-parents.
Kinship analysis showed that most L. calcarifer were unrelated since approximately 5.919% revealed an r value greater than 0.4 (i.e., rxy > 0.375 is regarded as full-siblings, Wang, 2002 and 2011 [52,53]). High positive values should result from parent–offspring relationships as brooders of HEBV and LEBV populations were also included in the data analysis (N = 26 accounting for 8.50% of examined fish samples). The findings suggested that close life-cycle production of subsequent generations of L. calcarifer could be carried out using the established G0 population without the necessity to introduce Asian seabass from different geographic origins to maintain high genetic diversity and to avoid inbreeding depression.

4.3. Selective Sweep Analysis Implied Different Performance of Fast- and Slow-Growing L. calcarifer

Detection of genomic regions significantly affected by positive selection is one of the major goals of selective sweep analysis [3]. It provides information on SNPs in genes that are functionally involved with traits of interest for genetic improvement of aquaculture species [2,4]. Both natural selection following the evolutionary scale and artificial selection signals following positive selection of economic traits can leave signatures in the genome [4,8,57]. Despite this capability, genomic changes following domestication are not well understood in current aquaculture species.
Recently, selective sweep analysis based on whole genome sequences of wild and farmed European Atlantic salmon has been reported. For example, genomic regions 139 and 81 from independent datasets revealed a significant increase in SNP homozygosity [8].
The breeding program of L. calcarifer in Thailand started in 2012. Therefore, the G0 population in our ongoing breeding program constitutes the third generation after initial recruitment of wild populations from various geographic locations in Thai waters. Selective sweep analysis of the examined samples was applied to identify the genome region where polymorphism was eliminated owing to positive selection within the genome [58]. Comparing HEBV and LEBV populations, several regions distributed across different chromosomes revealed significant differences in genome scanning results between the two groups.
GO enrichment analysis of genes that showed significantly reduced nucleotide diversity revealed the predominance of genes in immune response and lipid metabolism. KEGG enrichment analysis revealed that the cytokine-cytokine receptor interaction pathway predominated. Genome-wide SNPs analysis provided data to support the localization of positive selection signals in our L. calcarifer stocks. Natural selection may promote improved performance in disease resistance for HEBV and LEBV populations.
For selective sweep signal analysis, growth-related genes in the transforming growth factor β (TGF-β) domain were examined. For example, Tgfbr2, which is the only type II receptor for TGF-βs, was identified. It is a positive regulator of skeletal muscle tissue regeneration [59]. In addition, Fgf12, plays an important role in cell proliferation and differentiation, and tissue regeneration [60], while myosin proteins (e.g., Mhc) are involved in both structural and kinetic functions in muscle growth [61], and Dmtf1 is a transcriptional activator that promotes p53/TP53-dependent growth arrest [62]. All of these were significantly different between HEBV and LEBV populations.
On the basis of Fst analysis, genes in the insulin-like growth factor system (e.g., IGF2) and those of receptors for TGF-β (e.g., activin receptor type-2A-like, ActRIIA) revealed significant positive selection. These genes regulate skeletal muscle growth in fish. Association analysis between SNPs in these signaling pathways and growth would allow the application for the selection of fast-growing L. calcarifer [63].
In contrast to GWAS, where samples exhibiting different performances of economic traits are initially selected and analyzed, selective sweep analyzes the target population first, before the selection of genome signatures for different populations is chosen. The major disadvantage of selective sweep is that false positive results may be generated from bottlenecks and founder effects of the examined populations [2,4,57]. Therefore, genes identified in the present study should be further validated before they are applied as marker-assisted selection (MAS) for subsequent generations in our L. calcarifer breeding program.

4.4. Application of Population Admixture Analysis for Genetic Improvement of L. calcarifer

Results inferred from microsatellites revealed clear genetic differences between HEBV and LEBV G0 populations. Phylogenetic analysis further supported stock differentiation into two different clades. Our previous genetic analysis based on seven loci of microsatellites revealed predefined genetic populations (k) = 2. HEBV fish revealed clusters I < cluster II (0.315 compared with 0.685) genetic components, while LEBV fish exhibited the opposite direction (I = 0.657 and II = 0.343) [5]. In contrast, a population genomic study using genome-wide SNP detection generated the most optimal K value = 7. This readily elevates the selection efficiency of our G0 population.
Both HEBV and LEBV populations could be further divided into three and four subgroups. Genetic admixture between LEBV and HEBV subgroups was low. Most fish within each subgroup represented a single genetic cluster of genotypes. These fish could be considered as pure lines for each subpopulation. High coefficients of additive genetic variance both between and within families for the G0 population were found. A genetic gain of 28.5% (approximately 175.8 g) per generation is expected following EBV-based selection with one genetic SD [5].
To generate the subsequent G1 fish, the findings in this study should be applied in the breeding program by crossing top EBV-ranked fish that exhibit a single ancestral lineage of genotypes from different families within each subpopulation of the HEBV group. This could generate three different lines (from fish exhibiting top EBVs of H-1, H-2, and H-3 subgroups) for which the performance on growth could be monitored and selected. Previous studies indicated that the maintenance of genetic diversity is essential for the line selection of L. calcarifer to increase survival rates against big belly disease [64]. Accordingly, inter-subpopulation crosses of top EBV fish between H-1, H-2, and H-3 subpopulations (HEBV; NA = 8.286 with allelic richness = 4.042, Ho = 0.839, and He = 0.731) [5] may be performed to generate fish with relatively high genetic diversity in the ongoing breeding program.
Recently, the heritability estimate (h2) [28] for infectious spleen and kidney necrosis virus (ISKNV) resistance of the same G0 population was reported for L. calcarifer [27]. ISKNV is a major pathogen of L. calcarifer, and a moderate heritability estimate was found from disease resistance based on the binary survival (h2 = 0.29 ± 0.12) and time to death (h2 = 0.24 ± 0.10) data [27]. The information on heritability estimates, and the discovery of significant positive selection of genes in innate and humoral immunity suggest the potential to improve ISKNV resistance along with the growth of our L. calcarifer population.
In this study, genome-wide SNP analysis provided useful data to support the domestication and breeding of L. calcarifer. Interestingly, genomic localization of positive selection signals in L. calcarifer stocks was found. Therefore, long-term natural selection and short-term artificial selection during the initial establishment of each P0 stock may promote different performances on multiple traits (e.g., growth and disease resistance of HEBV and LEBV populations). Population admixture analysis revealed unique characteristics of our genetically improved populations. This important information, in combination with an EBV estimate of each fish, could be applied to elevate the efficiency of the ongoing breeding program for L. calcarifer.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/d17060383/s1, Table S1: Dams and sires used for production of G0 offspring of L. calcarifer. Table S2: Selective sweep results illustrating significantly different regions and genes between HEBV and LEBV populations of L. calcarifer based on the Fst approach. Table S3: Selective sweep results illustrating significantly different regions and genes between HEBV and LEBV populations of L. calcarifer based on the nucleotide diversity approach. Table S4: Selective sweep results illustrating significantly different regions and genes between HEBV and LEBV populations of L. calcarifer based on Fst and nucleotide diversity approaches.

Author Contributions

Conceptualization, B.K., A.C., P.S.-L. and S.K.; Methodology, J.C., S.J., S.P., S.T. and B.K.; Formal Analysis, S.J., S.P., S.T., J.C. and W.I.; Investigation, S.J., S.P. and S.T.; Resources, A.C. and J.C.; Data Curation, S.T.; Writing—Original Draft Preparation, B.K.; Writing—Review & Editing, S.K.; Supervision, T.S., P.S. and S.K. All authors have read and agreed to the published version of the manuscript.

Funding

The research was supported by the Science and Technology Research Partnership for Sustainable Development (SATREPS), Japan Science and Technology Agency (JST)/Japan International Cooperation Agency (JICA), grant no. JPMJSA1806.

Institutional Review Board Statement

All experimental animal protocols in this study were reviewed and approved by the Animal Care and Use for Scientific Research Committee of the Department of Fisheries, Ministry of Agriculture and Cooperatives (approval dated 28 January 2019). The experimental animal protocols were carried out by following the guidelines of the Institute of Animals for Scientific Purposes Development (IAD), Government of the Kingdom of Thailand, on the care and use of animals in scientific research.

Data Availability Statement

Data are available from the corresponding author on request.

Acknowledgments

The authors would also like to thank the National Center for Genetic Engineering and Biotechnology (BIOTEC), the National Science and Technology Development Agency (NSTDA) for providing facilities. They would also like to thank T.W. Flegel for assistance in editing the manuscript.

Conflicts of Interest

Author Panya Sae-Lim was employed by the company MOWI Genetics AS. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
SLAF-SeqSpecific Locus Amplified Fragment Sequencing (SLAF-Seq)
HEBVsHigh estimated breeding values
LEBVsLow estimated breeding values

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Figure 1. The average EBV values of fast-growing (HEBV) and slow-growing (LEBV) groups of L. calcarifer (A). SLAF libraries were prepared by digestion of genomic DNA of each fish with HaeIII + Hpy166II. Digested products between 374–414 bp were obtained (B). Polymorphic SLAF fragments were annotated using the reference genome. The distribution map of SLAF tags on twenty chromosomes is shown (C).
Figure 1. The average EBV values of fast-growing (HEBV) and slow-growing (LEBV) groups of L. calcarifer (A). SLAF libraries were prepared by digestion of genomic DNA of each fish with HaeIII + Hpy166II. Digested products between 374–414 bp were obtained (B). Polymorphic SLAF fragments were annotated using the reference genome. The distribution map of SLAF tags on twenty chromosomes is shown (C).
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Figure 2. (A) Neighbor-joining tree and PCA of individuals of L. calcarifer. (B) Samples are clustered into three dimensions by PCA, including HEBV (N = 133), LEBV (N = 147), and parental (N = 26) populations.
Figure 2. (A) Neighbor-joining tree and PCA of individuals of L. calcarifer. (B) Samples are clustered into three dimensions by PCA, including HEBV (N = 133), LEBV (N = 147), and parental (N = 26) populations.
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Figure 3. Linkage disequilibrium coefficient (r2) and LD distance (LDD) of SNPs within a 1000 kb window for all chromosomes of HEBV, LEBV and the parental populations. Longer LDD indicates lower recombination rate of chromosomes within the same distance, and vice versa.
Figure 3. Linkage disequilibrium coefficient (r2) and LD distance (LDD) of SNPs within a 1000 kb window for all chromosomes of HEBV, LEBV and the parental populations. Longer LDD indicates lower recombination rate of chromosomes within the same distance, and vice versa.
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Figure 4. Selective sweep of positive selection based on population differentiation fixation index (Fst, A) and nucleotide polymorphism (π1/π2, B) between HEBV and LEBV populations on twenty chromosomes of L. calcarifer. Blue dashed lines indicate the corresponding value of top 5% (p < 0.05). Red dashed lines indicate the corresponding value of top 1% (p < 0.01). Dots above the threshold lines are candidate gene regions showing significant positive selection.
Figure 4. Selective sweep of positive selection based on population differentiation fixation index (Fst, A) and nucleotide polymorphism (π1/π2, B) between HEBV and LEBV populations on twenty chromosomes of L. calcarifer. Blue dashed lines indicate the corresponding value of top 5% (p < 0.05). Red dashed lines indicate the corresponding value of top 1% (p < 0.01). Dots above the threshold lines are candidate gene regions showing significant positive selection.
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Figure 5. GO enrichment analysis based on Fst (A,C,E) and Fst-π1/π2 (B,D,F) categorized as biological function (A,B), cellular component (C,D), and molecular function (E,F), and on KEGG enrichment analysis (G,H) for genes identified in HEBV and LEBV populations.
Figure 5. GO enrichment analysis based on Fst (A,C,E) and Fst-π1/π2 (B,D,F) categorized as biological function (A,B), cellular component (C,D), and molecular function (E,F), and on KEGG enrichment analysis (G,H) for genes identified in HEBV and LEBV populations.
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Figure 6. (A) The most optimal K values (red dot) were estimated. (B) Admixture analysis using the K values = 7. Asian seabass subpopulations with LEBV values are shown in (C–F) (L-1, L-2, L-3, and L-4, respectively) while those with HEBV values are shown in panels (G–I) (H-1, H-2, and H-3, respectively). Different colors in the structure analysis represent different genotype clusters.
Figure 6. (A) The most optimal K values (red dot) were estimated. (B) Admixture analysis using the K values = 7. Asian seabass subpopulations with LEBV values are shown in (C–F) (L-1, L-2, L-3, and L-4, respectively) while those with HEBV values are shown in panels (G–I) (H-1, H-2, and H-3, respectively). Different colors in the structure analysis represent different genotype clusters.
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Table 1. Sequencing reads and depth, Q30, GC content, and mapped SLAF of parents from HEBV and LEBV groups.
Table 1. Sequencing reads and depth, Q30, GC content, and mapped SLAF of parents from HEBV and LEBV groups.
ParameterHEBVsLEBVsParent
Total reads1,706,574–24,836,624
(5,380,913.85)		1,802,730–23,074,886
(5,170,992.62)		1,704,794–29,396,770
(5,106,726.10)
Q30 (%)90.52–97.09 (95.76)89.49–96.95 (95.54)88.17–97.01 (95.59)
GC (%)32.1–42.7 (40.41)34.77–42.96 (38.74)31.38–43.16 (40.68)
Total depth674,159–11,042,360
(2,322,203.03)		809,377–10,621,017
(2,224,944.23)		772,403–13,495,035
(2,117,953.73)
Average depth5.3671–85.2515 (14.51)5.7312–72.7642 (15.8)5.0578–53.9756 (12.78)
Mapped (%)96.91–99.8 (99.49)98.81–99.8 (99.52)95.53–99.84 (99.47)
Properly mapped (%)84.15–97.62 (89.31)83.75–98.85 (89.21)83.89–98.75 (90.86)
SLAF number42,827–263,201
(162,972.89)		63,899–250,664
(131,852.73)		32,906–251,003
(161,807.99)
Table 2. The total number and polymorphic SLAF tags annotated to different chromosomes of L. calcarifer.
Table 2. The total number and polymorphic SLAF tags annotated to different chromosomes of L. calcarifer.
Chromosome IDSLAF NumberPolymorphic SLAF
115,32710,308
218,86713,022
314,1229825
415,52610,970
517,33211,869
617,37511,640
7_114,0889919
7_284776002
815,87211,071
913,8339575
1016,90611,689
1114,1429957
1216,91810,826
1317,04612,171
1481185645
1518,87613,175
16_LG2215,29410,305
1716,84411,503
1811,6498280
1915,0989270
2014,80510,445
2117,63312,211
2311,0767715
2411,9247999
Table 3. Data for diversity of experimental samples.
Table 3. Data for diversity of experimental samples.
Parameters/GroupHEBVsLEBVsParent
Average MAF0.2200.1670.217
No. of polymorphic markers221,949214,420206,202
Observed no. of allele (Ao)1.000–2.000 (1.984)1.000–2.000 (1.951)1.000–2.000 (1.914)
Expected no. of allele (Ae)1.000–2.000 (1.497)1.000–2.000 (1.363)1.000–2.000 (1.455)
Observed heterozygosity (Ho)0.008–0.992 (0.224)0.007–0.986 (0.178)0.038–1.000 (0.184)
Expected heterozygosity (He)0.007–0.500 (0.308)0.007–0.500 (0.246)0.038–0.500 (0.305)
PIC0.007–0.375 (0.251)0.007–0.375 (0.205)0.037–0.375 (0.249)
Nei diversity index0.008–0.505 (0.309)0.007–0.505 (0.247)0.038–0.667 (0.317)
Shannon Wiener index0.025–0.693(0.472)0.023–0.693(0.392)0.095–0.693 (0.470)
Table 4. Calculated relatedness of L. calcarifer used in this study.
Table 4. Calculated relatedness of L. calcarifer used in this study.
ValueCountPercentage
−0.6–−0.425705.489
−0.4–−0.215053.215
−0.2–0.028,06359.941
0.0–0.2736715.735
0.2–0.445429.701
0.4–0.621844.665
0.6–0.82200.470
0.8–1.01140.243
1.0–1.2126.50.270
1.2–1.4890.190
1.4–1.6100.021
1.6–1.81.50.003
1.8–2.05.50.012
2.0–2.28.50.018
2.2–2.47.50.016
2.4–2.64.50.010
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Khamnamtong, B.; Chaimongkol, A.; Prasertlux, S.; Janpoom, S.; Chaimongkol, J.; Tang, S.; Ittarat, W.; Songsangjinda, P.; Sakamoto, T.; Sae-Lim, P.; et al. Population Genomics and Application for Growth Improvement of Domesticated Asian Seabass Lates calcarifer from Thailand. Diversity 2025, 17, 383. https://doi.org/10.3390/d17060383

AMA Style

Khamnamtong B, Chaimongkol A, Prasertlux S, Janpoom S, Chaimongkol J, Tang S, Ittarat W, Songsangjinda P, Sakamoto T, Sae-Lim P, et al. Population Genomics and Application for Growth Improvement of Domesticated Asian Seabass Lates calcarifer from Thailand. Diversity. 2025; 17(6):383. https://doi.org/10.3390/d17060383

Chicago/Turabian Style

Khamnamtong, Bavornlak, Atra Chaimongkol, Sirikan Prasertlux, Sirithorn Janpoom, Jutaporn Chaimongkol, Sureerat Tang, Wanwipa Ittarat, Putth Songsangjinda, Takashi Sakamoto, Panya Sae-Lim, and et al. 2025. "Population Genomics and Application for Growth Improvement of Domesticated Asian Seabass Lates calcarifer from Thailand" Diversity 17, no. 6: 383. https://doi.org/10.3390/d17060383

APA Style

Khamnamtong, B., Chaimongkol, A., Prasertlux, S., Janpoom, S., Chaimongkol, J., Tang, S., Ittarat, W., Songsangjinda, P., Sakamoto, T., Sae-Lim, P., & Klinbunga, S. (2025). Population Genomics and Application for Growth Improvement of Domesticated Asian Seabass Lates calcarifer from Thailand. Diversity, 17(6), 383. https://doi.org/10.3390/d17060383

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