Development of novel microsatellite markers for population differentiation and detection of natural selection in wild populations of Butter catfish, Ompok bimaculatus (Bloch, 1794)

doi:10.21203/rs.3.rs-2124779/v1

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Development of novel microsatellite markers for population differentiation and detection of natural selection in wild populations of Butter catfish, Ompok bimaculatus (Bloch, 1794)

https://doi.org/10.21203/rs.3.rs-2124779/v1

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published 03 Jan, 2023

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Background: Butter catfish (Ompok bimaculatus) is a preferred species in South East Asia, with huge aquaculture potential. However, there is limited information about genetic stock composition due to insufficient markers. The goal of this study was to develop de novo microsatellite markers.

Methods and Results: For sequencing, genomic SMRT bell libraries (1.5 Kbp size) were prepared for O. bimaculatus. A total of 114 SSR containing sequences were used for primer designing and tested. Polymorphic loci were validated by genotyping 83 individuals from four distant riverine populations, viz., Brahmaputra, Bichiya, Gomti and Kaveri. A total of 30 microsatellite loci were polymorphic, of which, five were found to be associated with functional genes and eight (four positive and four negatives) loci were found to be under selection pressure. A total of 115 alleles were detected in all loci and PIC ranged from 0.539 to 0.927 and pair-wise F_ST values from 0.1267 to 0.26002 (p<0.001), with overall F_ST value of 0.17047, indicating presence of population sub-structure. Cross-species transferability of 29 loci (96.67%) was successful in congener species, O. pabda.

Conclusion: The novel SSR markers developed in this study will facilitate stock characterization of natural populations, to be used in future selection breeding programs and planning conservation strategies in these species. Identified non-neutral markers will give insights into the effect of local adaptation on genetic differentiation in the natural population of this species.

Ompok bimaculatus

Microsatellite markers

genetic stock

selection pressure

Cross-species amplification

Catfishes are most sought-after food fish and freshwater siluroids form important fisheries, with global contribution of 123184.6 tonnes in 2020 [1]. Ompok bimaculatus has a wide distribution and preferred freshwater catfish in South and South East Asian countries, commonly known as Butter catfish or pabda, due to its taste, high nutritional value, soft bony structure and rich lipoprotein content. Moreover, it has adapted to culture conditions, making it a favourable candidate species for aquaculture diversification. In India, this species is widely distributed in rivers, lakes and sub montane regions, however, a decline in wild populations have been observed at an alarming rate [2]. The species has been declared as an endangered species (nationally) in 1998 [3], however, was listed as Near Threatened in the IUCN Red List of threatened Species in 2009 [4]. However, there is limited information about genetic stock composition and genetic diversity, only with mitochondrial markers [2].

Microsatellites (SSRs) are marker of choice for characterization of genetic resources due to highly polymorphic, co-dominant inheritance and conformity to Mendelian segregation [5]. NGS technologies have been extensively used to discover microsatellites in various fish species [6, 7]. In addition to neutral markers, NGS can also facilitate identification of non-neutral markers or adaptive regions, which are influenced by natural selection, resulting in local adaptations [8].

The present study developed, for the first time, a panel of validated polymorphic microsatellite markers for evaluating genetic diversity in wild populations of O. bimaculatus, in addition, markers under natural selection and genes associated with them were also identified. This information will be used for precise assessment of genetic variability in O. bimaculatus, which will assist in management of stock for sustainable fisheries. Further, possibilities of cross amplification of developed loci in another congeneric species, i.e., Ompok pabda will provide markers for population genetic studies.

Sample collection and DNA extraction

A total of 83 specimens of O. bimaculatus, collected from across four geographical locations of rivers i.e., Brahmaputra (n = 18, Guwahati-Assam), Bichiya (n = 19, Rewa-Madhya Pradesh), Gomti (n = 37, Lucknow, Uttar Pradesh) and Kaveri (n = 9 Chennai, Tamil Nadu) were used in the study (Supplementary Fig. 1). The muscle tissues were collected and preserved in 95% ethanol in a 1:5 (tissue sample: ethanol) ratio at the sampling site and stored at 4°C for long term storage. The experiments were approved by Institute Animal Ethics Committee (IAEC), ICAR-NBFGR, vide No. G/IAEC/2020/022.

Dna Extraction And Sequencing

Total genomic DNA (gDNA) was extracted from muscle tissue, following modified phenol-chloroform method (PCM) [9]. The DNA was eluted in TE buffer (10 mM Tris-HCL pH 7.6, 1 mM EDTA pH 8.0), purified with AMPure PB beads (Beckman Coulter, Inc., CA). DNA integrity and purity were determined by agarose gel electrophoresis (1%) and spectrophotometry (DeNovix DS-11; Wilmington, Delaware). For sequencing, high quality gDNA was sheared using the Covaris S220 fragmentation system (Covaris, Inc. USA) and genomic SMRT bell libraries (1.5 Kbp size) were prepared using the PacBio DNA template preparation kit 1.0 (Pacific Biosciences, Inc., Menlo Park, CA, USA) and 2 SMRT cells were used for sequencing, using P6-C4 chemistry using PacBio RSII platform (Pacific Biosciences, Inc., CA). The PacBio CCS reads were assembled using CD-HIT [10] and CAP3 program [11].

Genome-wide Identification Of Ssrs And Primer Design

The SSR loci were scanned in the assembly using MISA tools [12]. The MISA was performed using the parameters (unit size, min repeats): 3–5 4–5 5–5 6 − 4. Primers were designed for tri, tetra, penta and hexa microsatellite repeats, with sufficient flanking sequences using Primer 3.0 tool [13]. Dinucleotide repeats were omitted to avoid the stutter, as shorter repeat motifs (dinucleotides) exhibit more stutter than higher repeat motifs (tri-or tetranucleotides) [14]. Loci with a predictive target sequence amplicon length 100 bp- 150 bp were selected and primers were synthesized.

Pcr Amplification And Genotyping

Primers were tested with Traditional PCR amplifications, in six individuals, from three different riverine populations. The PCR amplification was carried out in 25 µl reaction volume containing approximately 50 ng of DNA, 1×PCR buffer, 25 mM dNTPs, 1.5 mM MgCl₂, 5 pM primers (2.5 pM each forward and reverse primer) and 1.5 U Taq polymerase (Genei, Bengaluru, India). Amplification conditions were denaturation at 95°C for 5 min, followed by 30 cycles of 95°C for 30 s, primer specific annealing temperatures (T_a) for 30 s, 72°C for 1.5 min, final extension at 72°C for 10 min and hold at 4°C. PCR amplicons were resolved in 10% native polyacrylamide gels (10 × 10.5 cm, Wipro GE Healthcare Pvt. Ltd.) using 1×TBE buffer for about 5 h at 150 V. For visualization silver staining were done, using MspI digested PBR-322 as a ladder and molecular sizing of alleles was carried out on UVP Imaging System (Cambridge, UK).

Polymorphic 30 SSR loci were genotyped using 83 O. bimaculatus individuals from four different riverine locations, employing QIAxcel capillary electrophoresis system with QIAxcel DNA high resolution kit (Qiagen, Hilden, Germany) using Qiaxcel screen Gel v1.6.0. These amplified fragments were automatically scored for size polymorphisms in the specimens.

Data analysis

Number of alleles per locus (N_a), Polymorphic Information Content (PIC), observed heterozygosity (H_o), expected heterozygosity (H_e) was calculated using CERVUS 3.0.7 [15]. Genetic Hardy–Weinberg expectations (HWE), Null allele frequency, Linkage Disequilibrium (LD), Inbreeding coefficient (F_IS), Genetic differentiation (F_ST), rate of inbreeding in populations (F_IT), Genotypic differentiation (P-value) was determined using Genepop 4.2 [16]. Arlequin 3.11 [17] was used to determine genetic divergence between each pair of the population (F-statistics) and hierarchical analysis of Molecular Variance (AMOVA).

Test Of Selection Pressure

Loci under selection from genetic structure analysis were detected using Arlequin 3.5 [18] and BayeScan [19]. Arlequin uses coalescent simulations to get the p-values of locus-specific F-statistics conditioned on observed levels of heterozygosity whereas BayeScan implements a reversible-jump Markov chain Monte Carlo (MCMC) algorithm to estimate the posterior probability of balancing or purifying selection models.

Functional Annotation Of Contigs Containing Microsatellites

All the polymorphic loci were searched for associated functional gene using Basic Local Alignment Search Tool against the National Centre for Biotechnology Information (NCBI) database (https://www.ncbi.nlm.nih.gov/). Position of the microsatellites associated with genes, into coding and non-coding regions, were identified using Augustus [20]. Identification of Molecular pathways for annotated genes were carried out using KAAS (KEGG Automatic Annotation Server) [21] database (FDR < = 0.15).

Cross-amplification Of Microsatellite Markers

For estimating the cross transferability of polymorphic microsatellite loci in Ompok pabda, cross-amplification of all the polymorphic SSR loci were tested in a set of 13 individuals of O. pabda from three riverine populations i.e., Bichiya (Rewa - Madhya Pradesh), Mahanadi (Dhodrokusum – Odisha) and Brahmaputra (Kalangpar - Assam). The Individuals were genotyped using QIAxcel Capillary Electrophoresis System for estimating allele size range and number of alleles.

Development of Microsatellite markers

A total of 3.0779 Gb from PacBio long raw reads with 54,737 polymerase reads and sequence assembly of 46.029 Mb with 51219 contigs were generated. From the assembly, 53,730 repetitive motifs were identified and the repeats were distributed across 20,284 contigs (Supplementary Table 1). Maximum number of repeats were of dinucleotides (39448, 73.4%), followed by tetranucleotide repeats (7546, 14.04%), then trinucleotide repeats (6302, 11.72%), pentanucleotide repeats (373, 0.69%) and hexanucleotide repeats (61, 0.11%) (Supplementary Fig. 2).

Among the dinucleotide and trinucleotide repeats, AC/GT and AAT/ATT repeats were the most abundant, attributing 65.8% and 56.0%, respectively. Of the tetranucleotide repeats, AGAT/ATCT and AAAT/ATTT were the two most common motifs with 29.9% and 22.2% respectively. Among the higher repeat motifs, i.e., pentanucleotide and hexanucleotide repeats, AATAT/ATATT and AACCCT/AGGGTT were the most dominant motifs, accounting for 29.0 % and 37.7%, respectively (Supplementary Fig. 3; Supplementary Table 3).

A total of 114 primers were designed, of which 42 were for trinucleotide, 53 tetranucleotide, 8 pentanucleotide and 11 hexanucleotide repeats. A total of 30 microsatellite loci were polymorphic, which included 5 hexanucleotide, 2 pentanucleotide, 13 tetranucleotide and 10 trinucleotides motifs (Supplementary Table 2), exhibiting allele lengths ranging from 96 to 246 bp (Table 1).

Characteristics of microsatellite markers

Out of total 30 SSR loci, five were identified with their best matched protein (Supplementary Table 4), associated with functional genes, of which repeat regions in three loci were in intron and two in exon. OBL1326 (ATTT₆), was present in the intron region of Insulin Like Growth Factor 2 Receptor (IGF2R), OBL1181 (GGAT₈) in the intron region of Potassium Two Pore Domain Channel Subfamily K Member 2 (KCNK2), OBL958 (GCT₅) in the exon region of Epsin-2 (EPN2), OBL133599 (AGGATG₉) in the exon region of Chondroitin Sulfate Proteoglycan 5a (CSPG5A) and OBL624 (ATGT₅) in the intron region of Clustered Histone 14 (H3C14) (Supplementary Table 5, Fig. 1). Allele frequencies at 30 loci are given in Supplementary Table 6.

The calculated PIC values for all 30 loci were >0.5, where OBL1181 with highest PIC value (0.927), followed by OBL786 (0.881), OBL2442 (0.875) and lowest PIC value was observed in OBL133599 (0.539), with an average of 0.778. The number of alleles (N_a) ranged between 5 to 21 (5 alleles at locus OBL92038 and OBL1913; and 21 alleles at locus OBL1181), with mean number of alleles per locus was 10.93. The majority of loci observed low to moderate observed heterozygosity (H_o = 0.025, OBL1874 – 0.675, OBL49202) and moderate to high expected heterozygosity (He = 0.569, OBL133599 – 0.937, OBL1181), with mean observed and expected heterozygosity value of 0.268 and 0.807, respectively. The F_IS,F_ST and F_IT value ranged from 0.022 to 0.955, 0.032 to 0.3674 and 0.0316 to 0.9718. All the loci were found to have genotypic differential potential (Table 1). Significant deviation was observed from Hardy–Weinberg equilibrium (HWE) in seventeen loci (Supplementary Table 7)and frequency of null alleles observed in all populations ranged from 0 to 0.5599 (n=18, Brahmaputra). However, in Gomti with n=37, null allele frequency ranged from 0.0024 to 0.4285 (Supplementary Table 8) and as highest frequency was lower than 0.5, all the loci were included in the further analysis [22]. Analysis through MICROCHECKER indicated homozygote excess at these loci, but no evidence for scoring error due to stuttering and large allele dropout were observed.

Significant cumulative Linkage Disequilibrium (LD) after Bonferroni correction (p<0.001) was observed only between locus pair OBL949 × OBL958 (p= 0.000094 and chi²= 27.99), out of total 435 pairs (Supplementary Table 9). Significance levels were adjusted using Bonferroni correction [23] through multiple testing.

Detection of Loci under selection from genome scans based on F_ST

Out of total 30 microsatellite loci, eight (four positive and four negatives, Fig. 2; Table 2, a) and three (two positive and one negative, Table 2, b) loci were found to be under selection pressure through Arlequin and BayeScan, respectively. And out of total 5 type II SSR loci, two loci i.e., one positive (associated with Insulin Like Growth Factor 2 Receptor, IGF2R) and one negative (Epsin-2, EPN2) were found to be under selection pressure. Both these genes fall under Endocytosis (ko4144) pathway, under Transport and Catabolism. Sequence of IGF2R and EPN2 from the present study aligned with NCBI Accession no. VMHU01008964.1 and VMHU01003507.1 (O. bimaculatus) given in Supplementary Fig. 4.

Genetic variation and diversity in four riverine populations

Estimated pairwise F_STi.e., coefficient of genetic differentiation analysis based on total 30 SSR loci, ranged from 0.1267 (Gomti vs Kaveri) to 0.26002 (Bichiya vs Kaveri) (p<0.001), with overall F_ST among all populations was 0.1705 (p<0.001). Similarly, pairwise F_ST for 25 loci (neutral: Type I SSR loci) ranged from 0.12876 (Gomti vs Kaveri) to 0.26599 (Bichiya vs Kaveri) and overall F_STvalue of 0.17308. Further, pairwise F_ST analysis based on 5 type II (gene associated) SSR loci showed lower F_ST values as compared to neutral loci, ranging between 0.1157 (Brahmaputra vs Bichiya) to 0.23059 (Bichiya vs Kaveri) (p<0.001) with overall F_STvalue of 0.15737. The non-neutral markers (under selection) revealed higher genetic differentiation, that is pairwise F_ST for 4 loci (under positive selection) ranged from 0.19448 (Gomti vs Kaveri) to 0.54401 (Bichiya vs Kaveri) (p<0.001) with overall F_STvalue of 0.341(Supplementary Table 10). AMOVA results indicating the variance among populations and within individuals are given in Table 3.

Cross-species amplification in congener species, Ompok pabda

Cross-amplification of 30 polymorphic loci of O. bimaculatus showed amplification of 29 polymorphic loci in Ompok pabda, with success rate of 96.67%. Cross amplified loci exhibited polymorphism in O. pabda with 2 - 8 alleles and number of alleles per locus (N_a) ranged from 3 (OBL1874) to 9 (OBL949). Total 150 alleles were observed, which ranged from 97-210 bp (Supplementary Table 11).

The Next generation sequencing has become the technology of choice for Genome-wide identification and development of SSR markers [7]. In O. bimaculatus, majority of repeats were dinucleotide (73.4%), followed by tetranucleotide repeats (14.06%) and trinucleotide repeats (11.72%) with very low frequency of pentanucleotide and hexanucleotide repeats. Similar pattern of distribution of the repeat motifs was observed in three neotropical catfishes by Restrepo-Escobar [24]. In this study, PIC values of thirty novel polymorphic SSR loci indicated that all thirty loci are highly informative, indicating the usefulness for genetic stock structure analysis [25]. OBL1181 locus with PIC value of 0.927 implied highly informative loci. With these 30 polymorphic loci, all four riverine populations revealed relatively lower genetic diversity within population. It was reported that fishes with large population size that migrate during breeding season have high genetic diversity [26]. In contrast, O. bimaculatus is considered to be a local migrant and travels short distance for feeding or locating suitable breeding grounds in new water bodies, to avoid stress conditions of existing habitat [27], this might be the reason for relatively lower genetic diversity within population.

The number (N_a) of allele per locus ranged from 5 (OBL92038) to 21 (OBL1913), with an average allele per locus 10.93, indicating higher genetic variability than the reported average allele number per loci (9.1) for fresh water species [28]. High N_a was also observed in other catfish with high genetic diversity [25]. It was interesting to find highest number of alleles (21) to be located in the intron of KCNK2 gene. It may be possible that the polymorphism present due to this intronic microsatellite is not presenting any functional constraint, however it needs to be further investigated.

The departure from Hardy-Weinberg equilibrium was noticed in seventeen loci, which might be due to homozygote excess (as indicated by positive F_IS values). However, presence of significant level of null alleles were only in two loci (OBL894 and OBL1957). It may be due to small number of samples studied in the present study, and thus Hardy-Weinberg may be violated [29]. The significant value of genetic differentiation (overall F_ST) agreed with that of the results obtained through molecular variance. Positive F_IS values in loci may be due to reduction in heterozygotes, which may be the result of reduction in population size by overexploitation, adverse ecological changes, localised isolated population and non-migratory nature [27].

Under current study, analysis of five gene-associated SSR markers (Type II) showed lower overall pairwise F_ST value of 0.1574, as compared to that of neutral loci. It has been reported that in contrast to neutral markers (microsatellites in noncoding regions), gene-associated microsatellites marker might be more susceptible to selection pressure and therefore, showed low values of gene diversity which is concurrent to current study [25].

Present study revealed the effects of divergent and balancing selection on eight loci (four each), which also included two gene-associated loci. It was interesting to find both the associated genes under selection pressure have been reported to respond to environmental changes. One marker is associated with Insulin Like Growth Factor 2 Receptor (IGF2R), which is a cell-surface receptor and known to have a binding site for Insulin Like Growth Factor 2 (IGF2), where it endocytoses the growth factor and regulates the concentration of IGF2 within tissues in mammals [30]. It was reported that growth related diseases have been found to be associated with deregulation of expression of IGF2R in human. However, in teleost, role of the IGF2 is not clear in growth [31], and was found to be divergent selective pressures for adaptation in sticklebacks [32]. Another gene, under negative selectin is Epsin-2, encodes a protein, involved in clathrin-mediated endocytosis [33], which plays important role in nutrient uptake and cell to cell communications [34]. However, little information on its function in fishes is available. Nevertheless, both the genes found to be under selection pressure belong to the same pathway: Endocytosis, important for regulation of cell signalling and antigen presentation (keg.jp/entry/ko4144). It has also been reported to have an adaptive response in plasma membrane remodelling in the face of environmental changes [34].

With all 30 loci, the major genetic variation, present among individuals within populations with overall moderate genetic differentiation was as per the threshold values suggested by Wright [35]. Above all, the level of variation remained at the same level, when the type I and type II markers were analysed separately. However, the markers under balancing (positive) selection revealed lower genetic variation within individuals and higher differentiation. As the balancing selection, exerted by the adaptive forces, resulting in the maintenance of genetic variation and increased diversity at the linked sites [36]. In the present data set, at the balancing loci (regime), population differentiation is increased due to the maintenance of different sets of alleles in four populations analysed and it was proposed as the difference in fitness of the genotypes in populations, under the different environmental conditions [37]. Thus, in addition to the fact that the species under study is a non-migratory nature of species, the selection pressure working on the loci under study may contribute to the existence of high genetic differentiation within the same river system. A similar pattern of high genetic differentiation was observed in other catfishes in India, i.e., Indian Catfish, Clarias magur (F_ST: 0 .01383 to 0.62069) [38], giant river-catfish Sperata seenghala (0.135–0.173) [25], however selection pressure has not been examined in these cases.

Genetic diversity analysis showed significant differences between different riverine populations across India, i.e., Kaveri river (South India), Brahmaputra (North east India, Assam), Bichiya a tributary of Ganga river (Central India, Madhya Pradesh) and Gomti, a tributary of Ganga river (North India, Uttar Pradesh). In general, the population of same riverine system are expected to have low genetic variability as a result of genetic decline, genetic drift, selection and inbreeding [39]. However, in this study high genetic variability in populations Bichiya and Gomti river (p < 0.01) could be considered from different perspectives: (1) Bichiya river had originated from plateau of central India and before commencing into Ganga river system it has to go through the barrage and dams in the river resulting in isolated population; (2) Kaveri river is originated in Western Ghats and do not have any connectivity with Ganga and Brahmaputra river (3) Brahmaputra and Ganga river is fragmented by Farakka barrage (4) Non-migratory nature of the species (5) recent genetic bottlenecks in the wild population.

Some studies on fish have reported bottlenecks in natural populations, particularly due to habitat loss and fragmentation of river [40]. Fragmented populations exhibit higher genetic variation, especially in freshwater fishes [41]. In the case of Bichiya River, the fragmentation of the river was seen due to barrage in Maraila, Madhya Pradesh (24°79'00.13"N, 81°31'00.60"E); hydroelectric project Rewa, Madhya Pradesh, (24°48 '46.76"N, 81°29 '62.43"E); Jhinna, Madhya Pradesh (24°22 '25.36"N, 81°27 '49.03"E). There are considerable number of hydropower dams and barrage in the river, which can affect migration, egg and larvae drift of fish [42] and subsequent high genetic differentiation of Bichiya population from Gomti and other populations. Alteration of the migratory flow, leads to a reduction or interruption of gene flow, consequently reducing the population size and making it more susceptible to the effects of genetic drift [43], which results in genetic structure in fishes [44]. Furthermore, the higher genetic diversity could be expected as rivers belong to distant geographical locations and it is likely that the populations investigated could have evolved in isolation after fragmentation.

The cross-species amplification efficiency is inversely proportional to the phylogenetic distance between the two species [45]. Based on the mitogenome sequences analysis, O. pabda showed the highest similarity to O. bimaculatus in the genus with 86% identity [46]. Cross-amplification of 30 polymorphic loci of O. bimaculatus successfully amplified for 29 polymorphic loci in Ompok pabda. The allele size pattern of O. pabda was similar to that of O. bimaculatus. Cross-species amplification can be successfully used in genotyping and genetic stock characterization in O. pabda which will help in saving resources, effort and time. Cross-species amplification has been successful in other catfishes i.e., four related species of Silonia silondia [47], endangered catfish Rita rita [48].

In the current study, thirty microsatellite markers have been developed for the first time in O. bimaculatus, out of which eight are non-neutral markers, which are influenced by natural selection. These markers would help in studying the selection pressure enforced by environmental conditions and adaptation of natural population to the local environment. Such loci will give insights into the effect of local adaptation on genetic differentiation in the natural population of this species.

Acknowledgments The authors are thankful to The Director, National Bureau of Fish Genetic Resources (NBFGR), Lucknow for facilitating the work. The present work is the part of ICAR-NBFGR Project entitled, “Establishment of standardized genomic markers for cataloguing diversity below species level” (FISHNBFGRSIL202000900224) funded by Indian Council of Agricultural Research, New Delhi. Mr. Kantharajan is acknowledged for his role in preparing location map.

Funding This investigation was supported by ICAR-National Bureau of Fish Genetic Resources, Lucknow, India, under project No. FISHNBFGRSIL202000900224.

Conflict of interest The authors have no conflict of interest to declare.

Author Contributions Kuldeep K. Lal conceived the idea and designed the experiments. Investigation, data collection and analysis were performed by Labrechai Mog Chowdhury, Shradha Chaturvedi, Sangeeta Mandal, Rajesh Kumar and Vindhya Mohindra. The first draft of the manuscript was written by Sangeeta Mandal, Shradha Chaturvedi, Labrechai Mog Chowdhury, Vindhya Mohindra and all authors commented on previous versions of the manuscript. All authors approved the manuscript.

Ethical approval The experiments were approved by Institute Animal Ethics Committee (IAEC), ICAR-NBFGR, Lucknow vide No. G/IAEC/2020/022 dated 09-02-2021.

Consent to participate and publish All authors reviewed and approved the final version for publication.

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Table 1 Genetic variability and diversity parameters of thirty microsatellite markers in Ompok bimaculatus

S. No.	Locus Name	Allele size range (bp)	Na	Ho/He	PIC value	F_IS	F_ST	F_IT	Genotypic differentiation (P-value)
1	OBL133599	100-136	7	0.317/0.569	0.539	0.4213	0.056	0.4537	0.01098
2	OBL958	147-171	9	0.337/0.892	0.782	0.5703	0.0513	0.5923	6.20E-05
3	OBL1326	140-164	10	0.061/0.802	0.77	0.8958	0.3511	0.9324	0
4	OBL624	135-179	10	0.048/0.842	0.818	0.9381	0.1129	0.9451	0
5	OBL1181	121-195	21	0.366/0.937	0.927	0.583	0.0925	0.6216	0
6	OBL98532	101-146	14	0.634/0.845	0.821	0.1735	0.1291	0.2802	0
7	OBL49202	96-138	8	0.675/0.686	0.653	-0.0219	0.0524	0.0316	0
8	OBL92038	118-160	5	0.518/0.659	0.594	0.1324	0.1301	0.2453	0
9	OBL16581	112-196	16	0.542/0.843	0.826	0.3438	0.032	0.3648	0.003876
10	OBL1874	97-157	13	0.205/0.867	0.848	0.7216	0.2084	0.7797	0
11	OBL1825	186-246	13	0.169/0.841	0.819	0.7783	0.1378	0.8088	0
12	OBL894	149-165	7	0.025/0.783	0.742	0.9554	0.3674	0.9718	0
13	OBL2290	124-164	10	0.157/0.806	0.777	0.7716	0.206	0.8187	0
14	OBL1957	103-135	6	0.06/0.66	0.6	0.8849	0.277	0.9168	0
15	OBL616	118-150	12	0.229/0.809	0.779	0.6963	0.1002	0.7267	0
16	OBL437	110-144	10	0.301/0.737	0.694	0.5655	0.0872	0.6034	0.00016
17	OBL149	147-171	12	0.313/0.861	0.839	0.5916	0.1539	0.6544	0
18	OBL832	122-158	11	0.482/0.852	0.828	0.3968	0.0897	0.451	0
19	OBL949	157-201	12	0.361/0.856	0.834	0.5619	0.0553	0.5861	0.000112
20	OBL577	186-222	10	0.097/0.863	0.841	0.8633	0.237	0.8957	0
21	OBL2442	167-215	14	0.123/0.89	0.875	0.847	0.1359	0.8678	0
22	OBL1329	107-164	15	0.084/0.862	0.843	0.8948	0.1043	0.9058	0
23	OBL1316	131-167	8	0.229/0.781	0.742	0.6952	0.0604	0.7136	0.004128
24	OBL1651	126-147	9	0.205/0.755	0.714	0.7031	0.1251	0.7402	0.000138
25	OBL1939	112-142	11	0.173/0.868	0.847	0.7428	0.2985	0.8196	0
26	OBL1913	132-153	5	0.293/0.735	0.683	0.5631	0.1269	0.6185	6.60E-05
27	OBL721	114-144	10	0.301/0.785	0.751	0.5081	0.2909	0.6512	0
28	OBL194	97-142	15	0.132/0.839	0.817	0.8199	0.1729	0.8511	0
29	OBL684	139-160	11	0.277/0.875	0.856	0.6381	0.1748	0.7013	0
30	OBL786	102-150	14	0.341/0.895	0.881	0.5658	0.1696	0.6395	0

^Na^{-Number of alleles (CervusV-3.0.7), Ho-Observed Heterozygosities (CervusV-3.0.7), He-Expected Heterozygosities (CervusV-3.0.7), PIC-Polymorphic Information Content (CervusV-3.0.7), F}_IS^{- Inbreeding coefficient,}^F_ST^-^{Genetic differentiation}^{, F}_IT^-^{Rate of inbreeding in populations,}^{Genotypic differentiation (P-value)}^{(GenepopV-4.3.2)}

Table 2 Detection of Loci under selection from genome scans based on F_ST

a. Arlequin

S. No.	Locus Name	Gene name	Obs. Het. BP	Obs. F_ST	F_STP-value	1-F_STquantile	Balancing or purifying selection models
1	OBL958	EPN2	0.829	0.066	0.058	0.942	Purifying/ Negative
2	OBL1326	IGF2R	0.9	0.366	0.009	0.009	Balancing/ Positive
3	OBL49202	-	0.695	0.051	0.058	0.942	Purifying/ Negative
4	OBL16581	-	0.855	0.041	0.016	0.984	Purifying/ Negative
5	OBL894	-	0.89	0.384	0.005	0.005	Balancing/ Positive
6	OBL949	-	0.874	0.069	0.034	0.966	Purifying/ Negative
7	OBL1939	-	0.955	0.312	0.01	0.01	Balancing/ Positive
8	OBL721	-	0.863	0.3	0.039	0.039	Balancing/ Positive

*Obs. Het. BP - Observed heterozygosity between population, Obs. F_ST -observed F_ST value

b. Bayescan

S. No.	Locus Name	Gene name	Probability	log10(PO)	qval	Alpha	F_ST	Balancing or purifying selection models
1	OBL1326	IGF2R	1	1000	0	1.296	0.40836	Balancing/ Positive
2	OBL1939	-	0.60712	0.18902	0.13096	0.46276	0.24272	Balancing/ Positive
3	OBL16581	-	1	1000	0	-1.562	0.043651	Purifying/ Negative

Table 3 AMOVA analysis in four population. (a) Values for 30 polymorphic loci. (b) Values for 25 Type I loci. (c) Values for 5 Type II loci. (d) Values for 4 loci under Positive selections

(a)	Source of variation	Sum of squares	Variance components	Percentage of variation (%)	Fixation index/P-value
	Among populations	267.615	2.07208 Va	17.05	F_ST: 0.17047
	Within individuals	1633.457	10.08307 Vb	82.95	P value = 0.00000±0.00000*
	Total	1901.072	12.15515
(b)	Source of variation	Sum of squares	Variance components	Percentage of variation (%)	Fixation index/P-value
	Among populations	226.056	1.75391 Va	17.31	F_ST 0.17308
	Within individuals	1357.463	8.3794 Vb	82.69	P value = 0.00000±0.00000*
	Total	1583.518	10.1333
(c)	Source of variation	Sum of squares	Variance components	Percentage of variation (%)	Fixation index/P-value
	Among populations	41.56	0.31818 Va	15.74	F_ST: 0.15737
	Within individuals	275.995	1.70367 Vb	84.26	P value = 0.00000±0.00000*
	Total	317.554	2.02185
(d)	Source of variation	Sum of squares	Variance components	Percentage of variation (%)	Fixation index/P-value
	Among populations	71.515	0.59421 Va	34.1	F_ST: 0.341
	Within individuals	186.034	1.14835 Vb	65.9	P value = 0.00000±0.00000*
	Total	257.548	1.74257

^{AMOVA - Analysis of Molecular Variance (ArlequinV-3.0) *P<0.05}

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Development of novel microsatellite markers for population differentiation and detection of natural selection in wild populations of Butter catfish, Ompok bimaculatus (Bloch, 1794)

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Abstract

Figures

Introduction

Materials And Methods

Sample collection and DNA extraction

Dna Extraction And Sequencing

Genome-wide Identification Of Ssrs And Primer Design

Pcr Amplification And Genotyping

Data analysis

Test Of Selection Pressure

Functional Annotation Of Contigs Containing Microsatellites

Cross-amplification Of Microsatellite Markers

Results

Discussion

Conclusions

Declarations

References

Tables

Supplementary Files

Status:

Journal Publication

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