Development and characterization of microsatellite loci in Grevillea robusta

Mantello, Camila Campos; Kestring, Daiane Rigoni; Sousa, V. A. de; Aguiar, A. V. de; Souza, Anete Pereira de

doi:10.1186/1753-6561-5-s7-p16

Cited by 10 publications

(2 citation statements)

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“…Consequently, limited genomic resources have been generated in G. robusta , particularly the sequence data (genome or transcriptome or expressed sequence tags (ESTs)) and sequence-based markers. For instance, five SSR markers were developed in G. robusta through the microsatellite enriched genomic library method (Mantello et al 2011 ). Notably, the development of SSR markers through low-depth high throughput Illumina-based NGS technology is one of the widely used efficient and cost-effective methods in any taxa that devoid the sequence information (Zou et al 2014 ; Abdelkrim et al 2018 ; Li et al 2018 ; Nadeem et al 2018 ; Taheri et al 2018 ).…”

Section: Discussionmentioning

confidence: 99%

Genome skimming-based simple sequence repeat (SSR) marker discovery and characterization in Grevillea robusta

Dabral

Shamoon

Meena

et al. 2021

Physiol Mol Biol Plants

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Section: Discussionmentioning

confidence: 99%

Genome skimming-based simple sequence repeat (SSR) marker discovery and characterization in Grevillea robusta

Dabral

Shamoon

Meena

et al. 2021

Physiol Mol Biol Plants

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“…The species is endemic to Queensland, i.e., eastern Australia, and is widely distributed in southeast Asia, Africa, and the southern part of North America and South America [8]. In the last three decades, G. robusta was introduced from Australia to all regions of the world, viz., China, Eritrea, Ethiopia, India, Indonesia, Jamaica, Kenya, Laos, Malawi, Malaysia, Mauritius, Nepal, Pakistan, the Philippines, South Africa, Sri Lanka, Tanzania, Uganda, the United States of America, Vietnam, Zambia, and Zimbabwe [9][10][11][12][13][14][15][16]. In India, the species is distributed in approx.…”

Section: Introductionmentioning

confidence: 99%

Phenotypic, Geological, and Climatic Spatio-Temporal Analyses of an Exotic Grevillea robusta in the Northwestern Himalayas

et al. 2023

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The last five decades (since 1980) have witnessed the introduction of exotic trees as a popular practice in India to fulfill the demand of forest-based products for utilization in afforestation programmes. This study examines the distribution and habitat suitability of exotic Grevillea robusta trees in the northwestern Himalayas (state: Uttarakhand), focusing on the interaction between G. robusta and abiotic factors, such as climate, soil, and habitat suitability. This multipurpose agroforestry species is mainly grown by farmers as a boundary tree, windbreak, or shelterbelt and among intercrops on small farms in agroforestry systems worldwide. The results indicate that phenotypic plasticity is determined by tree height and diameter, indicating a higher frequency of young and adult trees. The study also highlights spatio-temporal modeling coupled with geological analysis to address the current distribution pattern and future habitat suitability range through MaxEnt modeling. The AUC ranged from 0.793 ± 3.6 (RCP 6.0_70) to 0.836 ± 0.008 (current) with statistical measures, such as K (0.216), NMI (0.240), and TSS (0.686), revealing the high accuracy of the model output. The variables, which include the minimum temperature of the coldest month (Bio 6), the slope (Slo), the mean temperature of the driest quarter (Bio 9), and the precipitation of the driest quarter (Bio 17), contribute significantly to the prediction of the distribution of the species in the Himalayan state. The model predicts a significant habitat suitability range for G. robusta based on bio-climatic variables, covering an area of approximately ~1641 km2 with maximal occurrence in Pauri (~321 km2) and Almora (~317 km2). Notably, the future prediction scenario corroborates with the regions of Tons (Upper Yamuna, Uttarkashi), Kalsi (Mussoorie, Dehradun), the Kedarnath Wildlife Sanctuary, and the Badrinath Forest Division for the potentially suitable areas. The climate was found to have a strong influence on the species’ distribution, as evidenced by its correlation with the Köppen–Geiger climate classification (KGCC) map. While the species demonstrated adaptability, its occurrence showed a high correlation with bedrocks containing an elevated iron content. Furthermore, the study also provides the first trees outside forests (TOF) map of G. robusta in the region, as well as insight into its future habitat suitability.

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Isolation, via 454 sequencing, characterization and transferability of microsatellites for Grevillea thelemanniana subsp. thelemanniana and cross-species amplification in the Grevillea thelemanniana complex (Proteaceae)

Hevrøy

Moody

Krauss

et al. 2013

Conservation Genet Resour

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Development and characterization of microsatellite loci in Grevillea robusta

Cited by 10 publications

References 1 publication

Genome skimming-based simple sequence repeat (SSR) marker discovery and characterization in Grevillea robusta

Genome skimming-based simple sequence repeat (SSR) marker discovery and characterization in Grevillea robusta

Phenotypic, Geological, and Climatic Spatio-Temporal Analyses of an Exotic Grevillea robusta in the Northwestern Himalayas

Isolation, via 454 sequencing, characterization and transferability of microsatellites for Grevillea thelemanniana subsp. thelemanniana and cross-species amplification in the Grevillea thelemanniana complex (Proteaceae)

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