Deepika. has always been the guiding light of my research endeavor for the meaningful and fruitful research in the rapidly growing field of biotechnology and bioinformatics.
5 Development of Seri-related Web-resources 211
Database content- retrieval, curation and categorization
List of Conferences/Workshops/Symposia 289
- Objective 1: Molecular characterization of selected Seri-bioresources of Assam through DNA Barcoding
- Introduction and Review of Literature
- Chapter 2: Molecular characterization of selected Seri-bioresources of Assam through DNA Barcoding
- Chapter 3: Mitochondrial genome sequencing of Antheraea assamensis, a semi-domesticated silkmoth endemic to Assam and North-eastern part of
- Mitochondrial genome sequencing of Cricula trifenestrata, a wild silkmoth from Assam
- Development of Seri-related Web-resources
- Summary and Future Prospects
This chapter further discusses the utility of the DNA barcoding approach in the identification and characterization of insects, host plants, bacteria, fungi, etc. The serial sources in this study were barcoded for the first time based on universal barcode markers.
Published manuscripts
Functional studies can be conducted based on the mitochondrial protein-coding genes, which will help in understanding the expression of genes under different conditions. In the future, more databases can be created to explore the area that is still in its infancy.
Manuscripts under review/preparation
Manuscripts from collaborative work
Literature
CHAPTER 1
Introduction and Review of literature
Seribiodiversity
For example, muga silkworm produces highly attractive and several times more expensive silk when fed on the host plant Mejankari, compared to other host plants (Tikader et al., 2013). The productivity of silk is affected by the attack of various disease pathogens, pests and predators on either silkworms or their host plants (Choudhury, 1981; Rath et al., 2001; Das et al., 2003).
Molecular characterization using DNA Barcoding
- DNA barcoding in insects and animals
- DNA Barcoding in plants
- DNA Barcoding in bacteria
- DNA Barcoding in fungus
- DNA Barcoding in virus and microsporidians
In addition, trnH-psbA and ITS regions have been proposed as complementary barcodes for plant DNA barcoding (Ren et al., 2010). Both ribosomal subunits SSU and GVE were also used for the identification of new fungal clade alone or in combination with ITS region (Arfi et al., 2012).
Mitochondrial genome sequencing of wild silkmoths
- Genome rearrangement and gene content
- Strand asymmetry in the mitogenome
- Transfer RNAs (tRNAs)
- Protein coding genes (PCGs)
- Non-coding regions
- Ribosomal RNAs (rRNAs)
- Importance of mitogenome studies in Saturniid silkmoths (wild silkmoths)
Most of the PCGs of lepidopteran insects are initiated with typical ATN codons (ATG, ATA, ATC, ATT) and terminated with complete termination codons (TAA or TAG) (Liu et al., 2008; Liu et al., 2016) . Similar study carried out in several genera of malacostraca showed that the genes encoding protein complexes (I and V) exhibited higher Ka/Ks ratios compared to those of complex (III and IV), indicating that the former complexes evolved under accelerating (positive) selection while the later evolved under purifying (negative) selection (Zhang et al., 2017).
Seri-informatics databases
- Silkworm databases
- Silkworm host plant databases
- Pest and pathogen databases
- Combined databases
- Need of seri-related databases
Recent advances in HT sequencing technology have led to the generation of mulberry (primary host plant of B. mori) specific databases "Morus Genome Database" (MorusDB) and "Mulberry Microsatellite Database" (MulSatDB) housing information on mulberry genome, as well as EST-based microsatellite (SSR) markers (Li et al., 2014; Krishnan et al., 2014). Many of the genomic and molecular studies on castor (R. communis- a primary host plant of S. cynthia) are being completed focusing on its economic significance (DaSilva et al., 2006). Castor Database”, “JCVI Castor Bean Genome Database” and “CastorDB”, whose information is provided in Table 1.4.
Jatrofa Genome Database” (current version 4.5), contains genomic information and DNA markers of Jatrofa (Sato et al., 2011). Quercus Portal” is the first integrated web resource that covers almost all facets of Quercus data, as listed in Table 1.4 (Ehrenmann et al., 2014). One such database is “HOSTS”, a database of lepidopteran insect host plants (approximately 15%) around the world (Robinson et al., 2010).
Spatio-temporal database of Silk Road” and “Silk Fabric Specification Database” have also been reported by different groups to cover the available information related to silk (biomaterial, Silk Road and fabric characteristics) (Kundu, 2012; Yang et al., 2012 ; Bi et al., 2014).
Chapter 2: Molecular characterization of selected Seri-bioresources of Assam through DNA Barcoding
Mitochondrial genome sequencing of Antheraea assamensis, a semi- domesticated silkmoth endemic to Assam and North-eastern part of India
Molecular characterization and mitochondrial genome
CHAPTER 2
Molecular characterization of selected Seri- bioresources of Assam through DNA
Introduction
These host plants show great diversity in leaf morphology and content, which affects silk quality and quantity (Tikader & Kamble, 2010; Tikader et al., 2013). The growth, fecundity and survival rate of silkworms are affected by various pests, parasitoids and pathogens that infect both silkworms and their host plants (Choudhury, 1981; Subharani & Jayaprakash, 2015; Saikia et al., 2016). Similarly, host plants of eri and muga are infected with various diseases such as leaf blight, leaf spot, brown or gray blight, red rust, anthracnose and root rot, resulting in a reduction in overall leaf yield (Das et al., 2003; Paliwal). & Paliwal, 2015).
Identification and classification of these resources through morphological attributes is time-consuming and fraught with difficulties, as these characters can vary with the environment (Packer et al., 2009). Therefore, DNA barcoding, a DNA-based taxonomic characterization tool, is extremely useful for cataloging these resources (Hebert et al., 2003). DNA barcoding has shown promising results in many insect groups, including Coleoptera, Diptera, Hemiptera, and especially Lepidoptera (Dai et al., 2012; Taylor & Harris, 2012; Karthika et al., 2016).
Mitochondrial DNA has also been used to identify and study phylogenetic relationships among members of the family Bombycidae, some members of the family Saturniidae, and some pest species (Arunkumar et al., 2006; Li et al., 2009; Jalali et al., 2015).
Materials and methods
- Sample collection
- Genomic DNA extraction
- PCR amplification and sequencing of barcode regions
- Sequence analysis and submission to database
- Phylogenetic analysis
Furthermore, phylogenetic trees were derived based on maximum likelihood (ML) method using different markers to study their evolutionary relationships. The single isolated fungal colonies were finally grown in potato dextrose broth for genomic DNA isolation (Quintana-Obregón et al., 2013). Multiple sequence alignment of the sequences was performed using other bioinformatic tools such as Clustal Omega and Muscle (Thompson et al., 2002; Edgar, 2004).
For phylogenetic analysis, several barcode sequences showing similarity to the published sequences were retrieved from the NCBI GenBank database (based on BLAST results), taking organisms from a different order/family as outgroups. The respective sequences (COI, matK, rbcL, trnH-psbA, ITS, ITS2) were aligned via Clustal W and Muscle in Mega 6.0 ( Tamura et al., 2013 ). The phylogenetic tree construction was performed in Mega 6.0 to study evolutionary relationships among the species based on the maximum likelihood (ML) method.
Bootstrap analysis of 1000 replicates was used to estimate the robustness of the trees' clades by partial removal of codons with gaps and missing data.
Results and discussion
- Genomic DNA extraction
- PCR amplification and sequencing of barcode regions
- Sequence analysis and submission to database Analysis of barcode sequences of silkworms and their pests
- Phylogenetic analysis
Detailed results of electrophoresis of PCR products in agarose gel are shown in Figure 2.4 (silkworms, pests and host plants) and Figure 2.5 (fungal and bacterial colonies). Amplified Weevils COI gene using the same set of primers, lane 8: 100 bp DNA ladder; (D) 1% agarose gel electrophoresis of amplified Persea bombycina rbcL gene products. Phylogenetic trees inferred using the ITS region of the fungal isolates clustered the isolates according to their genus based on the ML method (Figure 2.14).
Conclusions
Our study thus suggests that the selected barcode regions and their amplification with the selected primer sets were successful in identifying the selected samples. Phylogenetic trees inferred using barcode sequences based on the ML method grouped the species into specific groups belonging to their families and together with their related species. Our study thus enriches the barcode sequence data of selected serial sources of Assam and thus paves the way for their exploration and characterization.
Sampling taxa from different locations of Assam and Northeast India with their detailed phylogenetic analysis will further facilitate the exploration and characterization of species that are still largely underexplored.
CHAPTER 3
Mitochondrial genome sequencing of Antheraea assamensis, a semi-domesticated
Introduction
The utility and potential of mitochondrial PCGs (cox1 and cox2) as barcode markers has been well demonstrated in the order Lepidoptera (Mandal et al., 2014). The comparative mitogenome analysis also elucidated sequence divergence patterns among domesticated and non-domesticated lepidopteran mitogenomes (Arunkumar et al., 2006; Liu et al., 2012). Although the frequency of mitogenome sequencing of lepidopterans has increased, the evolutionary relationships between many family members of the same order have rarely been investigated.
Most of these silkworms are unexplored and may have potential significance in the field of seculture (Nässig et al., 1996). Antheraea assamensis, muga silkmoth is semi-domesticated and one of the economically important moths of the same family. It is a multivoltine and polyphagous moth that thrives mainly on two host plants Persea bombycina and Litsea monopetala (Tikader et al., 2013).
Like other species of Antheraea, it produces rewoven silk, which is the most expensive silk in the world.
Materials and methods
- Sample processing, DNA sequencing and assembly
- Genome annotation, visualization and comparative analysis
- Comparative phylogenetic analysis
Finally, assembled contig scaffolds and clustering were performed with SSPACE and CAP3 programs, respectively (Huang & Madan, 1999; Bankevich et al., 2012). MITOS is a widely used webserver for annotating metazoan mitochondrial genomes due to its advanced annotation methodology (Bernt et al., 2013). The entire mito-map was then constructed and visualized using the Blast Ring Image Generator (BRIG) tool (Alikhan et al., 2011).
To understand the evolutionary relationships of A. assamensis with various lepidopterans as listed in Table 3.1, the sequences of the entire mitogenome, coding regions, tRNAs, rRNAs and control regions were retrieved from the NCBI GenBank database and comparative analysis was performed. Highlighted among these are the organisms of the superfamily Bombycoidea used for comparative mitogen analysis with respect to A. assamensis). The nucleotide composition of sequences from the entire mitochondrial genome, concatenated and individual PCGs, tRNAs, rRNAs, spacers, and control regions was calculated using MEGA 6.0 software ( Tamura et al., 2013 ).
Similarly, BI analysis was performed in MrBayes v3.2.6 using Markov chain Monte Carlo (MCMC) method for both the datasets (Ronquist et al., 2012).
Results and discussion
- Sample processing, DNA sequencing and assembly
- Genome annotation, visualization and comparative analysis
- Comparative phylogenetic analysis
The arrangement of the mitochondrial genes was found to be the same in order as in other Bombycoidea insects (Figure 3.4). 124 | P a g e Table 3.4 Differences between genes in protein-coding genes at different taxonomic levels, both at the nucleotide and amino acid levels (percentages). Twenty-two tRNA genes with a total length of 1465 bp were found in the A. mitogenome.
On the contrary, the TѰC stem, TѰC loop, and DHU loop showed randomness in the number of base pairs across the organisms and tRNAs. These mismatches are likely to be corrected by the RNA editing mechanism, as observed in other arthropods ( Lavrov et al., 2000 ). The microsatellites (TA)9, also known as Simple Sequence Repeats (SSR), have been proposed to be used as molecular markers due to their abundance and highly polymorphic nature (Kim et al., 2012).
The overlapping sequences (OS) and intergenic spacers (IGS) are commonly found in the mitogenome of lepidoptera. This A+T biasness may result in the change in amino acid composition similar to the other lepidoptera. These results were consistent with the previously reported studies (Kim et al., 2009; Yang et al.,
