16

Chapter-III

Materials and methods

3.1 The study area

The present study focuses on the molecular characterization of the freshwater eel

species of the genus Monopterus in different states of Northeast India (Assam and

Manipur) including bordering area of Assam-Meghalaya, part of the two hotspot

region, viz. Indo-Burma and Himalayan hotspots (CEPF, 2005). The GPS location of

the study area is 26°10'22.79''- 27°39'32.79''N Latitude and 91°26'39.74''-

96°15'39.84''E Longitude.

3.1.1 Assam

The major part of the present study was conducted in the state of Assam, located in

the tropical Latitudes (24.30

N and 280

N) and eastern longitudes (89.50 E and 96.1

0E)

within the territorial jurisdiction of Northeast India. The entire state is drained by the

dense networks of two river system, viz. the Brahmaputra and Barak system.

3.1.2 Manipur

Manipur in northeast India is covering the border area of Myanmar to its east, falls

under Northeast India at the Indo-Malayan biodiversity hotspot (Roach, 2005).

Situated between latitudes 23.80oN to 25.68

oN and longitudes 93.03

oE to 94.78

oE, it

covers a total geographical area of 22,327 Sq. Km. It is unique for providing

profusion of habitats with characteristic diverse biota and high level of endemism.

Northeast India is regarded as a mega-biodiversity centre (De and Medhi, 2014). The

region of Indo-Burma biodiversity is known to be one of the most threatened

biodiversity hotspots due to the high rate of resource exploitation and habitat loss of

the total area of Manipur; about nine-tenths constitute the hills which surrounds the

remaining one-tenth valley.

3.1.3 Meghalaya

Some of the sampling locations of the present study also fall under Assam-Meghalaya

border area in Kulshi River. These study sites were situated near the Loharghat range

under West Kamrup forest division bordering Meghalaya (26.03°N; 91.26° E).

17

3.1.4 Beels and paddy fields

Sampling also carried out in beels (wetlands) and paddy fields of the study area too.

The study area includes following wetlands -

(i) Chandubi beel, situated within the Loharghat range of Kamrup, West division

(25° 51' N; 91° 21' E), which is surrounded by natural forest and hilly terrain of

Rajapara and Mayang hill range on its North-West and South-West respectively. In

the West there is Kulsia River.

(ii) Deepor beel Ramsar site, located between 91° 37′ 6.46″ E to 91° 40′ 48.82″ E

and 26° 5′ 40.02″ N to 26° 9′ 5.18″ N, south of Brahmaputra River in Kamrup

District, 18 km south west of Guwahati city in Assam .It lies at an altitude of 53 meter

above MSL and covers an area of about 4,000 ha. The wetland is surrounded by the

Bharalu basin on the east, Basistha basin in the south East, Kalmani River on the

west, Jhalukbari Beel on the north and Rani and Garbhanga Reserve forests on the

south.

(iii) Loktak Lake of Manipur, located in Bishnupur district of Manipur (24.25° -

24.42° N; 93.46°- 93.55°E).

The sampling sites were selected based on distribution of selected genera in

each region. At least five individuals were studied and sampled from each sampling

site.

3.2 Sample collection

Field work was carried out during January, 2012 to February, 2014 in paddy- field

and swamps of different parts of Assam and Manipur to collect M. cuchia and M.

albus samples (Table 3.1; Figure 3.1). From each sampling site 5-15 samples were

collected. A total of 230 Monopterus individuals were sampled. Geographically, the

Monopterus individuals collected were allocated into four populations based on the

geographical proximity of the water bodies of each sampling area. Each Monopterus

population was sampled at a gap of about 100-400 km away from other populations

(Table 3.1). Taxonomy and nomenclature were followed after Rosen and Greenwood

(1976) and Talwar and Jhingran (1992). The eels were released at their points of

capture.

18

Table 3.1. GPS coordinates of the sampling sites of Monopterus cuchia and Monopterus

albus.

Population Name/

Sampling area

Population

Code

Sampling Site(s) Coordinates

Manipur

1

Loktak Lake 24.3°N, 93.5°E

Ijei River, Longmai, Tamenglong 24.5°N, 93.4°E

Tuivel River, Manipur 24.08°N , 93.2°E

Assam

2

Wetlands, Hallawgaon, Sadiya,

Tinsukia

27.50°N, 95.45°E

Rice field, Mariani, Jorhat 27.52°N, 95.37°E

Bhogdoi River, Jorhat 26.77°N, 94.22°E

Kakodonga River, Golaghat 26.43°N, 94.3 °E

Dhansiri River, Golaghat 26.35°N, 93.35°E

3

Kolong River, Nagaon 26.36°N, 92.69°E

Jia Bhorali River, Sonitpur 26.69°N, 92.87°E

Bishwanath Ghat, Sonitpur 26.66°N, 93.17°E

4

Chandubi beel, Kamrup 25.51°N; 91.21° E

Kulshi river, Kamrup 26.03°N; 91.26° E

Rice field, Nalbari 26.14°N, 91.08°E

Puthimari river, Kamrup 26.22°N, 91.4°E

Rice field, Hajo, Kamrup 26.14°N, 91.32°E

Wetland, Manikpur, Bangaigaon 26.45°N, 90.80°E

Rice field, Bilaishipara, Dhubri 26.11°N, 90.16°E

Rice field, Dhubri 26.01°N, 89.6°E

Urpad Beel, Goalpara 26.06°N, 90.35°E

Rice field, Dudhnoi, Goalpara 25.98°N, 90.79°E

3.3 General protocol followed for numbering of samples

All codes start with M followed by an identifier C or A respectively.

Numbering methodology:

1. The target samples were collected from each sampling site from their potential

distribution range.

2. Morphological character and measurements were performed. The juveniles

and abnormal individuals (such as specimen having broken tail) were avoided

from the analysis.

19

3. Coloration of specific markings (stripes, spots and other body markings) on

the body of Monopterus individuals was recorded.

4. Tissue samples were collected following the non-invasive tail tip clipping

process and preserved in 95% alcohol.

5. Live specimens were released in same location treating with antiseptic.

6. GPS location of the place was recorded by GPS (Garmin 72) and other web

based database.

Figure 3.1. Map of study area showing the sampling sites.

3.4 Study of phenotypic variations

The phenotypic variations were captured and used for the analysis of molecular data.

Twenty three (23) reliably measurable morphometric characters were selected for the

study (Table 3.2).

20

Table 3.2. The morphological characters measured

Sl

No. Characters Description

1 Total length (TL) Distance from the tip of the snout to the longest

caudal fin ray

2 Pre dorsal length (PDL) Distance from the snout tip to the anterior base of

the dorsal fin

3 Post dorsal length (PoDL) Distance from posterior base of the dorsal fin to

last part of the caudal fin

4 Pre anal length (PAL) Distance from the tip of the snout to the anal base

5 Post anal length (PoAL) Distance from the anal base to the last part of the

caudal fin

6 Length of lateral line (LAL) Distance from the first base to the last base of

lateral line

7 Head length (HL) Distance from the tip of the snout to the posterior

margin of the opercula

8 Snout length (SnL) Distance from tip of mouth to nostril

9 Upper jaw length (UJL) Upper jaw length (UJL)

10 Lower jaw length (LJL) Length of lower jaw

11 Mouth gape (MG) Length of mouth gape

12 Eye diameter (ED) Distance between margins of the eye ball across

the cornea

13 Head depth (HD)

The perpendicular distance from the midline at

the back of head vertically downward to the

vertical contour of the head

14 Head width (HW) It is the greatest distance across the head

15 Pre orbital length (POL) Distance from tip of mouth to anterior base of

eye

16 Post orbital length (PoOrL) Distance from posterior base of eye to last hard

part of head

17 Greatest body depth (GBD) Greatest body depth of the body

18 Least body depth (LBD) Least body depth of the body

19 Greatest width of body (GWB) Width of body at greatest part

20 Highest body diameter (HBD) Diameter of the highest body part

21 Width of body at vent (WBV) At vent base width of the upper part of the body

22 Depth of body at vent (DBV) Depth of body at vent base

23

Distance between vent and

commencement of dorsal fin

(DBCB)

Distance between vent base to dorsal fin base

21

3.5 Mapping of distribution pattern

As a major objective of the present work, sampling locations were recorded using

handheld Garmin 72 GPS and were plotted on habitat map using the software

ARCVIEW (Ormsby and Alvi, 1999) to find out the phylogeographic relations.

3.6 DNA extraction

From each captured specimen, approximately 1 cm of tail tissue was removed with

forceps and was placed it in a sterile 1.5 ml microtube containing 95% ethanol and

was stored at –20 oC until processing. The eels were released at their points of

capture. The samples were placed in an ice chest during transport to the laboratory.

The samples were used simultaneously for genomic DNA extraction, SSR analysis,

sequencing of targeted regions of genome.

3.6.1 Chemicals and Reagents prepared

A. Homogenizing buffer (100ml)

a. 0.4M Nacl-2.33g

b. 10 mM Tris(PH8)-0.12114g

c. 2 mM EDTA(PH8)-0.05845g

B. Preparation of 5XTBE electrophoresis buffer (stock solution):

a. 0.445 M Tris borate

b. 0.01 M EDTA

(PH

was adjusted to 8.2-8.4 at 25oC)

C. 1XTBE electrophoresis buffer (working solution):

a. 89 mM Tris borate

b. 2 mM EDTA

(PH

was adjusted to 8.2-8.4 at 25oC)

D. 10X Proteinase K buffer

a. 100 mM Tris-Cl(PH

8)

b. 50 mM EDTA(PH

8)

c. 500 mM NaCl

E. Tris Chloride (1 M)

a. Tris-Cl base-121.1g

b. Double distilled water-800ml

22

(PH

was adjusted to 8)

c. Sterilized the solution by autoclaving.

F. 6X Gel-Loading Buffer

a.0.25 % (w/v) bromophenol blue

b. 0.25% (w/v) xylene cyanol FF

c. 40% (w/v) sucrose in water

3.6.2 DNA Extraction by using Chloroform-Octanol method

Genomic DNA was isolated from the tissue using the Chloroform-Octanol method

(Salah and Iciar, 1997; Cabe et al., 2007).

The steps followed in the Chloroform-Octanol method of DNA isolation:

1. Around 100 mg (0.1gm) of tissue was incised from the specimen using surgical

sterile blade and used for DNA extraction.

2. The pieces were chopped into fine bits and transferred into a sterile 2ml micro

centrifuge tube.

3. Then, added 500 μl homogenizing buffer to the sample and homogenized using

polytron tissue homogenizer for 10-15 s.

4. 50μl of 20% SDS (2% final concentration) + 11μl of 20mg/ml proteinase K(400

μg /ml final concentration) was added and mixed well.

5. Samples were incubated at 500C for overnight, mixed periodically by inversion.

6. Cooled the samples to 370C.

7. Added with 2.29 μl of 4 μg /μl RNase to the sample (s) for a final volume of 550

μl.

8. Samples were incubated at 370C for 30min. and added with equal volume of

Chloroform: Octanol (24:1).

9. Allowed to shake for 1h and centrifuged the sample at 14000g for 10 minutes.

10. Removed about 90% of the upper aqueous layer to a clean tube, carefully

avoiding proteins and added ¾ volume i.e. 400 μl of Isopropanol and mixed by

inverting the tubes and placed the same at -200C for 2 h.

11. Spined the tube at 14000g for 10min.

12. DNA pallets were taken and mixed with 500μl of 76% ethanol and washed the

pallet.

23

13. The tubes were placed in an oven at 500C and dried the DNA pallet for 5-10

minutes.

14. The dried DNA pallets were dissolved in 1XTBE buffer and kept in deep

freezer.

3.6.3 Preparation of 1% Agarose Gel for genomic DNA

1. 1g of Agarose was dissolved in 100ml of 1X TBE buffer by mixing thoroughly in

a clean conical flask.

2. Carefully warmed the solution to dissolve the Agarose. Kept the solution to cool

down to about 60 °C at room temperature, or water bath. Stirred the solution

while cooling.

3. 5 μl of 1X Ethidium Bromide was added into the conical flask containing

Agarose solution and swirled gently.

4. The solution was sufficiently cooled and poured the molten gel into the gel cast

which should be washed immediately with water and alcohol prior to use and

comb was fixed.

5. The gel was allowed to cool for solidification for 30-45 minutes.

6. The comb was removed and transferred the gel into an Electrophoretic tank filled

with 1X TBE buffer sufficient enough to just immerse the gel fully.

3.6.4 Running the genomic DNA Sample on the Agarose Gel

1. 4 μl of DNA sample and 1 μl of 6X Loading dye was mixed on a paraffin strip

and loaded this into each well. The same was done for each sample.

2. The loaded sample(s) in the well were allowed to run at 90 volts for 30-40

minutes or till the dye has run to 3/4th of the length of the gel.

3. The DNA bands in gel were visualized under UV using the Gel Doc.

Quantification of the DNA was performed using Evolution 201- UV-Visible

spectrophotometer (Thermo Scientific, Mumbai), used 20 ng DNA for PCR. DNA

was diluted to 1:5 or 1:10 of the original concentration obtained after isolation for

amplification in a PCR.

24

3.7 Selection of molecular markers

The present study has used SSR markers for genotyping of different populations of

Monopterus. The study also employed both mitochondrial and nuclear DNA for PCR

amplification. Sequencing and molecular characterization were carried out for two

mitochondrial (COI and D loop region) and two nuclear (gst: Glutathione s

transferase and gs: Glutamine Synthetase) genes, to infer differences and relationships

of Monopterus species complex.

Table 3.3. PCR Primers used for amplified from microsatellite loci

#Sl.

No.

SSR

Locus

GenBank

Accession

no.

Repeat Motif PCR Primers Tm

(°C)

1 Mal01 DQ987569 (TG)2CA(TG)4(TG)11 F: ATATTTGCAAGCGAGCCTGT

R: CTCTTCAATGCAGGCACAAA

57

2 Mal02 DQ987574 (AC)23 F: TTGAAGAGCTCCGAGAGCAG

R: TTTGGTGCTGGAAAACTGGT

55

3 Mal04 DQ987576 (CA)21 F: CCACTGAGATTCACCCTCGT

R: GCTCTGTCTGTGTCGTCTGG

64

4 Mal05 DQ987579 (GT)10 F:TATTTCTCCAAGGGCTGGTG

R:CACATGCACACAAACAGCA

48

5 Mal07 DQ987581 (CA)4(TA)6(CA)13 F:CCCATACAGACATTTGCCACT

R: CCAGACAACCTCTTTCCACA

55

6 Mal09 DQ987583 (TC)21(CA)20 F: GCCCAGATGATACAAGTC

R: TGGGAGAAAGGAAGCACAAG

55

7 Mal10 DQ987584 (TC)10(AGG)6 F: GTGGGCCTTTATCTGCATGTG

R: TGCTTGTCTGTCCCTTACGA

62

8 Mal11 DQ987590 (TG)11 F: GTGGGCCTTTATCTGCATGT

R: CTGTCCCTTACGCACCTCTC

65

9 Mal13 DQ987593 (TG)19 F: CAGCAAAAGTAAAGCCGACTA

R: TGTCGCATTTCTGCAAGTTT

65

10 Mal008 DQ987582 (AC)13 F:AGCTCACTATTCCCGTCTGTCTGA

R:CCTGCCCTTTCTCACATTACAAAC

55

11 Mal043 JN712692 (TG)20 F: CAGCCGCAGAGTTAAACATCACCA

R: CCTAAACCCCAAAGGTCCCAGAAA

55

#Primer Reference: Li et al. (2007): Sl No.1- 9; Lei et al. (2012): Sl No.10- 11.

25

3.8 Microsatellite Genotyping

The sequences of 11 Monopterus–specific microsatellite primers (Table 3.3) were

obtained from Li et al. (2007), Lei et al. (2012). Polymerase Chain Reactions (PCRs)

were carried out in 25 μL of reaction volume containing 20 ng of genomic DNA, 1.25

U Taq polymerase, 200 μM dNTP, 0.2 μM primer, and 1X amplification buffer

(containing 2 mM MgCl2). The condition for amplification was an initial denaturation

temperature 94 °C for 5 min, followed by 36 cycles of 94

°C for 30 s, then by 30 s at

appropriate annealing temperature (Table 3.3) followed by 72°C for 45 s followed by

a final extension at 72 °C for 10 min. Amplicons and DNA size marker (HiMedia)

were resolved on 7.5% nondenaturing polyacrylamide gels containing acrylamide and

N,N’-methylenebisacrylamide in 19:1 ratio. Electrophoresis was done at 8 V/cm for

120 min. DNA bands were stained using ethidium bromide 10 mg/ml solution for 30

min and visualized with Ultraviolet Gel Document System (UVIdoc) (Tong and Liao,

2005; Zhu et al., 2005). The sizes of the microsatellite bands were measured by using

the software UVItec ver 12.8.

3.8.1 Data analysis in Microsatellite Genotyping

The 230 Monopterus samples used in SSR studies were allocated into four

populations based on the geographical proximity of the water bodies. Microsateliite

allele size permutation test was performed as described by Hardy et al. (2003) using

the software SPAGeDi (Hardy and Vekemans, 2002) to determine whether allele size-

based or allele identity-based statistics were appropriate for the analysis of

microsatellite dataset. The test revealed that allele identity-based analyses were more

suitable for the dataset of the present study.

Agreement of genotype frequencies with the expected Hardy-Weinberg

equilibrium, and existence of linkage disequilibrium were analyzed using exact test

implemented by Genepop (Raymond and Rousset, 1995).

Estimates of identity-based gene diversity parameters, He (expected

heterozygosity or gene diversity corrected for sample size, Nei, 1978) and NAe

(effective number of alleles, Nielsen et al., 2003) were computed using SPAGeDi.

F-statistics, FIT and FIS, were computed with help of Genepop 4.2.2 (Rousett,

2008). The F-statistics, were defined according to Rousset (2002) and Cocherham and

Weir (1987). The ANOVA approach of Weir and Cockerham (1984) was

26

implemented to compute single locus estimates of FIS and FIT.

Polymorphism Information Content (PIC) was calculated according to

Botstein et al. (1980) who defined PIC values as a probability of a given marker being

informative at a random mating.

The programs Structure 2.3.4 (Pritchard et al., 2000), Structure Harvester

(Earl and vonHoldt, 2012) and CLUMPP 1.1.2 (Jackobson and Rosenberg, 2007)

were utilized to determine the most probable number (K) of genetic clusters

represented by sampled individuals irrespective of their geographical locations.

Structure version 2.3.4 was set to output the likelihood Ln [P(X/K)] for values

of K from 1 to 12; both the burn-in period and data collection were set at 10,000 steps,

20 runs were performed for each value of K. The admixture model and correlated

allele frequencies were used for every run. The output files of ‘Structure software’

were submitted to the online tool Structure Harvester (Earl and vonHoldt, 2012) for

further analysis, which followed the procedure of Evanno et al. (2005) to identify the

values of K. CLUMPP was then used to perform permutations of the 20 Q matrices

associated with the best value of K and to output a mean of permuted matrices. This

matrix was then input into the cluster visualization program distruct (Rosenberg,

2004) to obtain the bar plot.

3.9 PCR amplification of COI, D-loop and gst genes

Selected samples (6 each from M. cuchia and M. albus) were used for sequencing of

targeted regions of mitochondrial genome (D-Loop and COI gene) and nuclear

genome (gst gene). The informative regions of selected genes (D-Loop, COI and gst

genes) were PCR amplified from multiple individuals per species using taxa specific

primers. The PCR primer pairs used for amplification of D loop region were F-

TTCCAATGGAGGGATGGTGC and R- AACCACCGAAAAGCGAAAGC (Metz

et al., 1998). The COI gene was amplified using primers F-TCAACCAACCACAT

TGGCAC and R-TAGACTTCTGGGTGGCCAAAGAATCA (Chandra et al., 2012).

[Table 3.4].The gst gene was PCR amplified using primer pairs GST1-F-

GATGTGTTCCTGCCTTCTCCACA and GST1-R-GAAGACCAATCACCACAAA

GGGAA (Fu and Xie, 2006) (Table 3.4).

27

Table 3.4. PCR primer sequences used for amplification and for sequencing of DNA

Gene Name Primer

Name

5'<-----Sequence----->3' Tm (0C) Reference

Cytochrome c

oxidase

COI-F TGATCCGGCTTAGTCGGAACTGC Chandra et

al., 2012 COI-R GATGTGTTGAAATTACGGTCGGT 50

D loop region D loop-F TTGTTCGTTACCCACCAAGC 54 Metz et

al.,1998 D loop-R TGCCTGTGGGACTTTTTAGG

Glutathione S

transferase-1

GST1-F GATGTGTTCCTGCCTTCTCCACA 55 Fu and Xie,

2006 GST1-R GAAGACCAATCACCACAAAGGGAA

All PCR amplifications were carried out in 25 μL reaction volume, with 1.5

units of Taq DNA Polymerase (Bangalore Genei, Bangalore, India), 0.25 mM of

dNTPs (Bangalore Genei), 2.0 mM of MgCl2, 0.1 M (Sigma) of each primer and 20

ng of genomic DNA (Tables 3.4 & 3.5). The condition for amplification was an initial

denaturation temperature 94 °C for 5 min, followed by 35 cycles of 94

°C denaturing

temperature for 50 sec , then by 45 sec at appropriate annealing temperature (Table

3.3; Figure 3.2) followed by extension temperature of 72°C for 90 sec and then by a

final extension at 72 °C for 10 min. The annealing temperature used for amplification

mitochondrial (COI, D-loop region) genes were Tm = 500C for COI gene, 54

0C for D-

loop region and the Tm = 550C for nuclear (gst) gene (Figure 3.2 A-D; Table 3.4).

Table 3.5. Constitution of PCR mixture

Reagents Concentration in final reaction mixture

10X 1X

dNTPs (2.5 mM) 0.25 mM

MgCl2 (25 mM) 1.5-2 mM

Primer (10 μM) 0.1+0.1 μM (forward + reverse primers)

Taq (3U/μl) 1.5-2.0 U/tube

Template DNA 1 μl / sample (20 ng)

MQ H2O Added to make the volume up to 25 μl

28

A. Stages of PCR cycle for COI gene

B. Stages of PCR cycle for D-loop region

C. Stages of PCR cycle for Nuclear genes (gst )

Figure 3.2 (A-C): Thermocycler profiles in which mitochondrial and nuclear

DNA were amplified.

29

3.10 Agarose gel electrophoresis of amplified PCR products

The amplified products were separated in 2% agarose gel (i.e. 2g Agarose in 100 ml

1X TBE or 0.6 g agarose in 30 ml 1x TBE) by electrophoresis. Low Range DNA

Ruler or 1 kb ladder was used as MW markers. 4 μl PCR products with 1μl of 6X

Loading dye were loaded in each of the wells. Electrophoresis was performed at 90 V

till the tracking dye; bromophenol blue reached the anodal end of the gel. The results

of electrophoresis was observed and recorded in a gel documentation system

(UVIdoc). The amplified PCR products were purified using QIAquick PCR

Purification kit (Qiagen).

3.11 Sequencing of mitochondrial and nuclear genes

Sequencing of mitochondrial (COI and D-loop region) and nuclear (gst: Glutathione s

transferase and gs: Glutamine Synthetase) genes were performed by ABI PRISM®

377 DNA sequencer (at BioAxis DNA Research Centre, Hyderabad). After

verification the nucleotide sequences were deposited to GenBank (NCBI) public

sequence repository (Benson et al., 2013).

3.12 In silico analysis

3.12.1 Acquisition of additional nucleotide sequences

In addition to the sequences generated from the present study, the study also included

the seqences of coi, D-loop, gst and gs genes (gs01, gso2 and gso3), extracted from

GenBank (NCBI) (Benson et al., 2013) by database keyword search and by BLASTp

(Altschul et al., 1997) and FASTA (Pearson, 1991) searches. The existing GenBank

sequences of closely related species was used as outgroup of phylogenetic analysis.

3.12.2 Translation of coding region and acquisition of protein sequences

The coding regions for COI, gs01 and GST genes were translated into amino acids of

Cytochrome C Oxydase, Glutamine synthetase-1 and Glutathione-s-tranferese

proteins (using EMBOSS Transeq; Rice et al., 2000) for structural and evolutionary

studies. Apart from these, amino acid sequences of Cytochrome C Oxydase,

Glutamine synthetase-1 and Glutathione-s-tranferese were also extracted from Protein

30

Knowledgebase (UniProtKB, Apweiler et al., 2004) both by database keyword search

and by BLASTp (Altschul et al., 1997) and FASTA (Pearson, 1991) searches.

3.12.3 Sequence Alignment and Comparative sequence analysis

The in silico analysis were carried out in the Bioinformatics Centre (DBT-BIF),

Gauhati University. Data mining and sequence analyses of mitochondrial (COI and D

loop region) and nuclear (gst and gs) genes along with COI, Glutamine synthetase-1

and Glutathione-S-tranferese proteins were performed using the CLC Genomics

Workbench 7.0.3 (CLC Bio, Hydarabad, India). The nucleotide and protein sequences

were simultaneously aligned using CLUSTAL-W (Higgins et al., 1994) and Modeller

version 9.12 (Fiser et al., 2000) programs.

The physico-chemical parameters of COI, Glutamine synthetase-1 and

Glutathione-S-tranferese proteins were computed using CLC Genomics Workbench

7.0.3 (CLC Bio, Hydarabad, India) and ProtParam (Gasteiger et al., 2005). The

important calculations for the amino acid composition, atomic composition,

theoretical pI, molecular weight, Formula, extinction coefficients, half-life, instability

index, aliphatic index, hydrophobicity, charge vs. pH were carried out under

sequence analysis.

3.12.4 Molecular Phylogenetic analysis

The sequences of outgroup species for each gene (COI and D-loop region, gs and gst)

were downloaded from GenBank and UniProtKB. For COI gene-based phylogeny, the

nucleotide sequence of COI of other eel shaped fishes belonging to the families

Anguillidae (Anguilla bengalensis), Mastacembelidae (Mastacembelus armatus,

Macrognathus pancalus, Macrognathus aral, Macrognathus aculeatus) were included

to establish the evolutionary relationships of Monopterus albus and Monopterus

cuchia with other eel species. The sequences for the mitochondrial (COI and D-loop

region) and nuclear markers [gs (gs01,gs02, gs03) and gst genes] were aligned using

ClustalW 1.6 (Thompson et al., 1994) integrated in software MEGA (Tamura et al.,

2007), using default parameters. The datasets were subjected to phylogenetic analyses

carried out in MEGA6 (Tamura et al., 2013). The evolutionary history was inferred

by using two different methods namely the Maximum Parsimony (Eck and Dayhoff,

1966) and Maximum Likelihood (Jones et al., 1992) methods. Maximum parsimony

31

(MP) tree was estimated using the Close-Neighbor-Interchange algorithm (Nei and

Kumar, 2000). The percentage of replicate trees in which the associated taxa clustered

together in the bootstrap test (1000 replicates) (Felsenstein, 1985). The branch lengths

calculated using the average pathway method (Nei and Kumar, 2000).

Nucleotide substitution model that best fits each dataset and the model

parameters were estimated using Akaike information criterion implemented in the

program MODELTEST version 3.7 (Posada and Crandall, 1998). The Maximum

Likelihood analysis was carried out on the Hasegawa-Kishino-Yano model

(Hasegawa et al., 1985).

3.12.5 Three-dimensional structure prediction

Comparative modeling of important proteins namely Cytochrome C Oxydase,

Glutamine synthetase-1 and Glutathione-S-tranferese were conducted by using

Modeller9v12 program (Marti-Renom et al., 2000).

BlastP (Altschul et al., 1997) and FASTA (Pearson, 1991) searches were

performed independently with PDB (Berman et al., 2007) for obtaining a suitable

template. The significance of the BLAST results was assessed by expect values (e-

value) generated by BLAST family of search algorithm (Altschul et al., 1991). The

target-template alignment (Lassmann and Sonnhammer, 2005) was carried out using

ClustalW version 2.1 (Higgins et al., 1994) and Modeller version 9.12 (Fiser et al.,

2000) programmes. Comparative modelling was conducted by the Modeller version

9.12 programme (Marti-Renom et al., 2002). The loop regions were modeled using

MODLOOP server (Fiser and Sali, 2003). The final 3D structures with all the

coordinates for COI, GS and GST were obtained by optimization of a molecular

probability density function (pdf) of Modeller (Eswar et al., 2006). The molecular pdf

for homology modelling was optimized with the variable target function procedure in

Cartesian space that employed the method of conjugate gradients and molecular

dynamics with simulated annealing (Sali and Blundell, 1993).

The computational protein structures were evaluated (Giorgetti et al., 2005) by

ERRAT (Colovos and Yeates, 1993) and ProCheck (Laskowski et al., 2003)

programmes. After fruitful verification, the coordinate files were successfully

deposited to PMDB (Protein Model Database) (Tiziana et al., 2006). All the graphic

presentations of the 3D structures were prepared using Chimera version 1.8.1

(Pettersen et al., 2004).

32

3.12.6 Molecular evolution of proteins

Evolutionary analyses of proteins (COI, GS and GST) were conducted in MEGA6

(Tamura et al., 2013). The evolutionary history was inferred by using the Maximum

Parsimony (Eck and Dayhoff, 1966) and Maximum Likelihood (Jones et al., 1992)

methods.

3.12.7 Data mining and sequence analysis and functional annotation

Modern bioinformatics tools including the Expasy Proteomics tools were used for

sequence analysis, transcription, translation, structural analysis, functional annotation

etc. The proteomics analyses were carried out using CLC Genomics Workbench 7.0.3

(CLC Bio, Hydarabad, India). ProFunc server (Laskowski et al., 2005) was used to

identify the likely biochemical function of proteins from the predicted three-

dimensional structure. Databases like PFam, PROSITE, PRINTS, ProDom,

InterProScan (Zdobnov and Apweiler, 2001) were used for functional

characterization.

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