Leaf Transcriptome Sequencing for Identifying Genic-SSR Markers and SNP Heterozygosity in Crossbred Mango Variety ‘Amrapali’ (Mangifera indica L.)

Mahato, Ajay Kumar; Sharma, Nimisha; Singh, Akshay; Srivastav, Manish; Jaiprakash,; Singh, Sanjay Kumar; Singh, Anand Kumar; Sharma, Tilak Raj; Singh, Nagendra

doi:10.1371/journal.pone.0164325

Cited by 29 publications

(15 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…RNA-seq of mango cultivars Neelum, Dashehari and their hybrid Amrapali revealed substantially higher level of heterozygosity in Amrapali over its parents and helped in developing genic simple sequence repeat (SSR) markers (Mahato et al 2016). Hyper-variable SSRs are simple sequence repeats whose repeating unit is > 50 bp and are more polymorphic as compared to other type of SSRs (Singh et al 2010).…”

Section: Designing Of Simple Sequence Repeat Markersmentioning

confidence: 99%

New hyper-variable SSRs for diversity analysis in mango (Mangifera indica L.)

Srivastav¹,

Singh²,

Prakash³

et al. 2021

Indian J. Genet

Self Cite

View full text Add to dashboard Cite

Whole genome sequence in mango offers unprecedented opportunities for genomics assisted crop improvement via enabling access to genome-wide genetic markers. In the present study, simple sequence repeats (SSRs) were predicted from genome sequence of mango. Based on the SSR length (? 50 bp), highly-variable mango SSRs (MSSRs) were sorted. A sub-set of 129 MSSRs was validated on a set of 24 diverse mango genotypes yielding marker validation and polymorphism of 88.96 and 85.27 per cent, respectively. One hundred and ten polymorphic markers were identified for the present set of mango genotypes. Polymorphic information content (PIC) ranged from 0.10 to 0.78 and the highest value was observed with MSSR133. The mean PIC value was 0.40 but 33 MSSR markers showed PIC values ? 0.5, suggesting that these markers can efficiently measure genetic diversity and serve for mapping of quantitative trait loci (QTLs) in mango. MSSRs data was further used for diversity analysis of mango genotypes belonging to different agro-ecological conditions including chance seedlings, landraces, exotic and indigenous germplasm and hybrids. Cluster analysis using UPGMA of 24 mango genotypes revealed that these MSSRs were informative in diversity analysis and distinguished mango genotypes based on their origin, parentage and embryo types. A novel set of 110 hyper-variable SSR markers have been added to the mango repository depicting usefulness in discriminating closely related mango germplasm and their use in mango improvement programme.

show abstract

Section: Designing Of Simple Sequence Repeat Markersmentioning

confidence: 99%

New hyper-variable SSRs for diversity analysis in mango (Mangifera indica L.)

Srivastav¹,

Singh²,

Prakash³

et al. 2021

Indian J. Genet

Self Cite

View full text Add to dashboard Cite

show abstract

“…Genic-SSR markers are highly promising as they have potential to unravel functional diversity available in the analysed germplasm collection of any plant species. In plants, genic-SSRs have been developed either using the publically available expressed sequence tags (ESTs) such as in wheat [ 9 ], rice, [ 10 ], barley, [ 11 ], oat, [ 12 ] or by deep transcriptome sequencing like in pigeonpea [ 13 ], mango [ 14 ] and some other species. Additionally, genic SSR markers can be developed exclusively from the candidate genes associated with targeted traits.…”

Section: Introductionmentioning

confidence: 99%

Identification, analysis and development of salt responsive candidate gene based SSR markers in wheat

et al. 2018

View full text Add to dashboard Cite

BackgroundSalinity severely limits wheat production in many parts of the world. Development of salt tolerant varieties represents the most practical option for enhancing wheat production from these areas. Application of marker assisted selection may assist in fast tracking development of salt tolerant wheat varieties. However, SSR markers available in the public domain are not specifically targeted to functional regions of wheat genome, therefore large numbers of these need to be analysed for identification of markers associated with traits of interest. With the availability of a fully annotated wheat genome assembly, it is possible to develop SSR markers specifically targeted to genic regions. We performed extensive analysis to identify candidate gene based SSRs and assessed their utility in characterizing molecular diversity in a panel of wheat genotypes.ResultsOur analysis revealed, 161 SSR motifs in 94 salt tolerance candidate genes of wheat. These SSR motifs were nearly equally distributed on the three wheat sub-genomes; 29.8% in A, 35.7% in B and 34.4% in D sub-genome. The maximum number of SSR motifs was present in exons (31.1%) followed by promoters (29.8%), 5’UTRs (21.1%), introns (14.3%) and 3’UTRs (3.7%). Out of the 65 candidate gene based SSR markers selected for validation, 30 were found polymorphic based on initial screening and employed for characterizing genetic diversity in a panel of wheat genotypes including salt tolerant and susceptible lines. These markers generated an average of 2.83 alleles/locus. Phylogenetic analysis revealed four clusters. Salt susceptible genotypes were mainly represented in clusters I and III, whereas high and moderate salt tolerant genotypes were distributed in the remaining two clusters. Population structure analysis revealed two sub-populations, sub-population 1 contained the majority of salt tolerant whereas sub-population 2 contained majority of susceptible genotypes. Moreover, we observed reasonably higher transferability of SSR markers to related wheat species.ConclusionWe have developed salt responsive gene based SSRs in wheat for the first time. These were highly useful in unravelling functional diversity among wheat genotypes with varying responses to salt stress. The identified gene based SSR markers will be valuable genomic resources for genetic/association mapping of salinity tolerance in wheat.Electronic supplementary materialThe online version of this article (10.1186/s12870-018-1476-1) contains supplementary material, which is available to authorized users.

show abstract

“…Our database also provides haplotype which can also be compared across varieties in varietal signature development. Such limited varietal differentiation in mango varieties viz., Neelam, Dashehari and Amrapali is recently reported using SNPs 53 .…”

Section: Resultsmentioning

confidence: 99%

MiSNPDb: a web-based genomic resources of tropical ecology fruit mango (Mangifera indica L.) for phylogeography and varietal differentiation

Iquebal¹,

Jaiswal²,

Mahato

et al. 2017

Sci Rep

Self Cite

View full text Add to dashboard Cite

Mango is one of the most important fruits of tropical ecological region of the world, well known for its nutritive value, aroma and taste. Its world production is >45MT worth >200 billion US dollars. Genomic resources are required for improvement in productivity and management of mango germplasm. There is no web-based genomic resources available for mango. Hence rapid and cost-effective high throughput putative marker discovery is required to develop such resources. RAD-based marker discovery can cater this urgent need till whole genome sequence of mango becomes available. Using a panel of 84 mango varieties, a total of 28.6 Gb data was generated by ddRAD-Seq approach on Illumina HiSeq 2000 platform. A total of 1.25 million SNPs were discovered. Phylogenetic tree using 749 common SNPs across these varieties revealed three major lineages which was compared with geographical locations. A web genomic resources MiSNPDb, available at http://webtom.cabgrid.res.in/mangosnps/ is based on 3-tier architecture, developed using PHP, MySQL and Javascript. This web genomic resources can be of immense use in the development of high density linkage map, QTL discovery, varietal differentiation, traceability, genome finishing and SNP chip development for future GWAS in genomic selection program. We report here world’s first web-based genomic resources for genetic improvement and germplasm management of mango.

show abstract

Leaf Transcriptome Sequencing for Identifying Genic-SSR Markers and SNP Heterozygosity in Crossbred Mango Variety ‘Amrapali’ (Mangifera indica L.)

Cited by 29 publications

References 49 publications

New hyper-variable SSRs for diversity analysis in mango (Mangifera indica L.)

New hyper-variable SSRs for diversity analysis in mango (Mangifera indica L.)

Identification, analysis and development of salt responsive candidate gene based SSR markers in wheat

MiSNPDb: a web-based genomic resources of tropical ecology fruit mango (Mangifera indica L.) for phylogeography and varietal differentiation

Contact Info

Product

Resources

About