Bioinformatics tools for development of fast and cost effective simple sequence repeat (SSR), and single nucleotide polymorphisms (SNP) markers from expressed sequence tags (ESTs)

The development of current molecular biology techniques has led to the generation of huge amount of gene sequence information under the expressed sequence tag (EST) sequencing projects on a large number of plant species. This has opened a new era in crop molecular breeding with identification and/or development of a new class of useful DNA markers called genic molecular markers (GMMs). These markers represent the functional component of the genome in contrast to all other random DNA markers (RMMs). Many recent studies have demonstrated that GMMs may be superior to RMMs for use in the marker assisted selection, comparative mapping and exploration of functional genetic diversity in the germplasms adapted to different environment. Therefore, identification of DNA sequences which can be used as markers remains fundamental to the development of GMMs. Amongst others; bioinformatics approaches are very useful for development of molecular markers, making their development much faster and cheaper. Already, a number of computer programs have been implemented that aim at identifying molecular markers from sequence data. A revision of current bioinformatics tools for development of genic molecular markers is, therefore, crucial in this phase. This mini-review mainly provides an overview of different bioinformatics tools available and its use in marker development with particular reference to SNP and SSR markers.Keywords: Genic molecular marker, simple sequence repeat (SSR), and single nucleotide polymorphisms (SNP) markers from expressed sequence tags (ESTs).African Journal of Biotechnology Vol. 12(30), pp. 4713-472

Evaluation of multifarious plant growth promoting traits, antagonistic potential and phylogenetic affiliation of rhizobacteria associated with commercial tea plants grown in Darjeeling, India

<div><p>Plant growth promoting rhizobacteria (PGPR) are studied in different agricultural crops but the interaction of PGPR of tea crop is not yet studied well. In the present study, the indigenous tea rhizobacteria were isolated from seven tea estates of Darjeeling located in West Bengal, India. A total of 150 rhizobacterial isolates were screened for antagonistic activity against six different fungal pathogens i.e. <i>Nigrospora sphaerica</i> (KJ767520), <i>Pestalotiopsis theae</i> (ITCC 6599), <i>Curvularia eragostidis</i> (ITCC 6429), <i>Glomerella cingulata</i> (MTCC 2033), <i>Rhizoctonia Solani</i> (MTCC 4633) and <i>Fusarium oxysporum</i> (MTCC 284), out of which 48 isolates were antagonist to at least one fungal pathogen used. These 48 isolates exhibited multifarious antifungal properties like the production of siderophore, chitinase, protease and cellulase and also plant growth promoting (PGP) traits like IAA production, phosphate solubilization, ammonia and ACC deaminase production. Amplified ribosomal DNA restriction analysis (ARDRA) and BOX-PCR analysis based genotyping clustered the isolates into different groups. Finally, four isolates were selected for plant growth promotion study in two tea commercial cultivars TV-1 and Teenali-17 in nursery conditions. The plant growth promotion study showed that the inoculation of consortia of these four PGPR isolates significantly increased the growth of tea plant in nursery conditions. Thus this study underlines the commercial potential of these selected PGPR isolates for sustainable tea cultivation.</p></div

Potentiality of Actinomycetia Prevalent in Selected Forest Ecosystems in Assam, India to Combat Multi-Drug-Resistant Microbial Pathogens

Actinomycetia are known for their ability to produce a wide range of bioactive secondary metabolites having significant therapeutic importance. This study aimed to explore the potential of actinomycetia as a source of bioactive compounds with antimicrobial properties against multi-drug-resistant (MDR) clinical pathogens. A total of 65 actinomycetia were isolated from two unexplored forest ecosystems, namely the Pobitora Wildlife Sanctuary (PWS) and the Deepor Beel Wildlife Sanctuary (DBWS), located in the Indo-Burma mega-biodiversity hotspots of northeast India, out of which 19 isolates exhibited significant antimicrobial activity. 16S rRNA gene sequencing was used for the identification and phylogenetic analysis of the 19 potent actinomycetia isolates. The results reveal that the most dominant genus among the isolates was Streptomyces (84.21%), followed by rare actinomycetia genera such as Nocardia, Actinomadura, and Nonomuraea. Furthermore, seventeen of the isolates tested positive for at least one antibiotic biosynthetic gene, specifically type II polyketide synthase (PKS-II) and nonribosomal peptide synthetases (NRPSs). These genes are associated with the production of bioactive compounds with antimicrobial properties. Among the isolated strains, three actinomycetia strains, namely Streptomyces sp. PBR1, Streptomyces sp. PBR36, and Streptomyces sp. DBR11, demonstrated the most potent antimicrobial activity against seven test pathogens. This was determined through in vitro antimicrobial bioassays and the minimum inhibitory concentration (MIC) values of ethyl acetate extracts. Gas chromatography–mass spectrometry (GS-MS) and whole-genome sequencing (WGS) of the three strains revealed a diverse group of bioactive compounds and secondary metabolite biosynthetic gene clusters (smBGCs), respectively, indicating their high therapeutic potential. These findings highlight the potential of these microorganisms to serve as a valuable resource for the discovery and development of novel antibiotics and other therapeutics with high therapeutic potential

PCA analysis showed the effect of PGPR treatments on plant growth parameters of two different varieties of tea clones TV-1 and Teenali-17 in nursery conditions.

<p>The PCA analysis was performed taking the plant growth parameters of root and shoot length, fresh and dry roots and shoots weight and number of tea leaves. (A) and (B) showing the treatment 11 and commercial fertilizer (CF) clustered closer to each other which showed significantly increased in plant growth parameters than the control and other treatments. (The r1, r2, r3, r4 and r5 in the PCA plot are representing the five replications for each treatment). [Control (without bacterial inoculums), CF (N:P:K in 2:1:2 mixture), Treatment1 (strain TT5), Treatment 2 (strain TTD21), Treatment 3 (strain BT22), Treatment 4 (strain NT5), Treatment 5 (strain TTD5+ strain TTD21), Treatment 6 (strain TTD5+ strain BT22), Treatment 7 (strain TTD5+ strain NT5), Treatment 8 (strain TTD21+ strain BT22), Treatment 9 (strain TTD21+ strain NT5), Treatment 10 (strain BT22+ strain NT5) and Treatment 11 (strain TTD5+ strain TTD21+ strain BT22 + strain NT5)].</p

Evaluation of different PGP parameters to show the effect of treatments in two different varieties of tea clones TV-1 and Teenali-17in nursery conditions.

<p>(A) shoot length, (B) root length, (C) fresh shoot weight, (D) fresh root weight, (E) dry shoot weight, (F) dry root weight and (G) number of leaves. Values having different superscripts (a-i) differ significantly (<i>P</i> < 0.05). [Control (without bacterial inoculums), CF (N:P:K in 2:1:2 mixture), Treatment1 (strain TT5), Treatment 2 (strain TTD21), Treatment 3 (strain BT22), Treatment 4 (strain NT5), Treatment 5 (strain TTD5+ strain TTD21), Treatment 6 (strain TTD5+ strain BT22), Treatment 7 (strain TTD5+ strain NT5), Treatment 8 (strain TTD21+ strain BT22), Treatment 9 (strain TTD21+ strain NT5), Treatment 10 (strain BT22+ strain NT5) and Treatment 11 (strain TTD5+ strain TTD21+ strain BT22 + strain NT5)].</p

Map showing the location of sample collection sites.

<p>Map showing the location of sample collection sites.</p

Dendrogram generated using Dice similarity coefficient index from ARDRA banding patterns of the rhizobacterial isolates using NTSYS 2.02 software.

<p>Based on the dendrogram generated the rhizobacterial isolates are divided into four major clusters A, B, C and D where B clustered with only <i>Pseudomonas</i> spp. and C clustered with only <i>Brevibacillus</i> spp.</p

Screening of selected rhizobacteria for PGP and antifungal traits.

<p>Screening of selected rhizobacteria for PGP and antifungal traits.</p

Molecular identification of 16S rRNA gene of potent rhizobacteria, sequence accession numbers and their origin.

<p>Molecular identification of 16S rRNA gene of potent rhizobacteria, sequence accession numbers and their origin.</p

The most promising 15 isolates and their antagonistic activity, antifungal mechanisms along with their PGP traits and general assessment and ranking for their ability to function as PGPR.

<p>The most promising 15 isolates and their antagonistic activity, antifungal mechanisms along with their PGP traits and general assessment and ranking for their ability to function as PGPR.</p