Root precursors of microRNAs in wild emmer and modern wheats show major differences in response to drought stress

Akpınar, Bala Anı; Kantar, Melda; Budak, Hikmet

doi:10.1007/s10142-015-0453-0

Cited by 107 publications

(77 citation statements)

References 71 publications

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“…To develop the better hulless barley cultivars with desirable dietary characteristics, it is significantly necessary to the exploitation of hulless barley germplasm resources and to reveal the molecular mechanism of grain development in hulless barley, especially seed starch biosynthesis (Akpinar et al 2015). In this study, RNA-seq technology was used to profile the grain dynamics development of two Tibetan hulless barley landraces Zangqing 2000 (Q) and 08-1127 (C2), with the differential grain starch synthesis traits.…”

Section: Discussionmentioning

confidence: 99%

Transcriptomics analysis of hulless barley during grain development with a focus on starch biosynthesis

Tang

Zeng

Wang

et al. 2016

Funct Integr Genomics

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Hulless barley, with its unique nutritional value and potential health benefits, has increasingly attracted attentions in recent years. However, the transcription dynamics during hulless barley grain development is not well understood. In the present study, we investigated the transcriptome changes during barley grain development using Illumina paired-end RNA-sequencing. Two datasets of the developing grain transcriptomes from two barley landraces with the differential seed starch synthesis traits were generated, and comparative transcriptome approach in both genotypes was performed. The results showed that 38 differentially expressed genes (DEGs) were found co-modulated in both genotypes during the barley grain development. Of those, the proteins encoded by most of those DGEs were found, such as alpha-amylase-related proteins, lipid-transfer protein, homeodomain leucine zipper (HD-Zip), NUCLEAR FACTOR-Y, subunit B (NF-YBs), as well as MYB transcription factors. More interestingly, two genes Hvulgare_GLEAN_10012370 and Hvulgare_GLEAN_10021199 encoding SuSy, AGPase (Hvulgare_GLEAN_10033640 and Hvulgare_GLEAN_10056301), as well as SBE2b (Hvulgare_GLEAN_10018352) were found to significantly contribute to the regulatory mechanism during grain development in both genotypes. Moreover, six co-expression modules associated with specific biological processes or pathways (M1 to M6) were identified by consensus co-expression network. Significantly enriched pathways of those module genes showed difference in both genotypes. These results will expand our understanding of the complex molecular mechanism of starch synthesis during barley grain development.Electronic supplementary materialThe online version of this article (doi:10.1007/s10142-016-0537-5) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Transcriptomics analysis of hulless barley during grain development with a focus on starch biosynthesis

Tang

Zeng

Wang

et al. 2016

Funct Integr Genomics

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“…Previously, we have developed an automated pipeline consisting of two consecutively run scripts, “SUmirFind” and “SUmirFold” for in silico plant miRNA identification from large-scale sequencing data (Lucas and Budak, 2012), which helped unlock many potential miRNA species from Triticeae family members (Akpinar et al, 2015; Akpinar and Budak, 2016; Alptekin and Budak, 2016). Herein, we refined our pipeline with the implementation of two additional scripts by taking aim at providing increased sensitivity and specificity in course of homology-based in silico miRNA identification.…”

Section: Discussionmentioning

confidence: 99%

“…This miRNA identification pipeline basically utilizes two sequential and easy-to-use Perl scripts, “SUmirFind” and “SUmirFold” which were originally published in 2012 (Lucas and Budak, 2012) and successfully employed in the identification of several miRNAs, particularly from cereal species (Kurtoglu et al, 2013, 2014; Akpinar et al, 2015; Alptekin and Budak, 2016). Here, a new Perl script, “SUmirPredictor” (Supplementary Document 1), is added to our pipeline which automates the final evaluation of candidate sequences and generation of final miRNA list.…”

Section: Methodsmentioning

confidence: 99%

“…Considering all the above-mentioned issues, specialized criteria for miRNA identification and annotation are required for both animals and plants, and the utilization of separate tools optimized for each group is highly suggested (Meyers et al, 2008). Computational approaches, in particular, benefitting from the homology-based support, have achieved large-scale and efficient detection of plant miRNAs (Kantar et al, 2010; Kurtoglu et al, 2014; Wu et al, 2014; Akpinar et al, 2015; Ebrahimi Khaksefidi et al, 2015; Akpinar and Budak, 2016). In such studies, the selection of reference miRNA set, used in these homology-based approaches, has a great impact on the accuracy of miRNA identification.…”

Section: Introductionmentioning

confidence: 99%

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A Comprehensive Prescription for Plant miRNA Identification

2017

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microRNAs (miRNAs) are tiny ribo-regulatory molecules involved in various essential pathways for persistence of cellular life, such as development, environmental adaptation, and stress response. In recent years, miRNAs have become a major focus in molecular biology because of their functional and diagnostic importance. This interest in miRNA research has resulted in the development of many specific software and pipelines for the identification of miRNAs and their specific targets, which is the key for the elucidation of miRNA-modulated gene expression. While the well-recognized importance of miRNAs in clinical research pushed the emergence of many useful computational identification approaches in animals, available software and pipelines are fewer for plants. Additionally, existing approaches suffers from mis-identification and annotation of plant miRNAs since the miRNA mining process for plants is highly prone to false-positives, particularly in cereals which have a highly repetitive genome. Our group developed a homology-based in silico miRNA identification approach for plants, which utilizes two Perl scripts “SUmirFind” and “SUmirFold” and since then, this method helped identify many miRNAs particularly from crop species such as Triticum or Aegliops. Herein, we describe a comprehensive updated guideline by the implementation of two new scripts, “SUmirPredictor” and “SUmirLocator,” and refinements to our previous method in order to identify genuine miRNAs with increased sensitivity in consideration of miRNA identification problems in plants. Recent updates enable our method to provide more reliable and precise results in an automated fashion in addition to solutions for elimination of most false-positive predictions, miRNA naming and miRNA mis-annotation. It also provides a comprehensive view to genome/transcriptome-wide location of miRNA precursors as well as their association with transposable elements. The “SUmirPredictor” and “SUmirLocator” scripts are freely available together with a reference high-confidence plant miRNA list.

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“…RNAseq was recently used to reveal unique DIC microRNAs related to drought tolerance in roots, which may have an important role in adaptation to drought-prone environments (2). However, the interpretation of transcriptome analyses may be hampered by the fact that the wheat genome is not yet fully sequenced.…”

Section: Molecular Mechanisms For Adaptation To Drought In Dicmentioning

confidence: 99%

Evolution and Adaptation of Wild Emmer Wheat Populations to Biotic and Abiotic Stresses

Huang

Raats

Sela

et al. 2016

Annu. Rev. Phytopathol.

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The genetic bottlenecks associated with plant domestication and subsequent selection in man-made agroecosystems have limited the genetic diversity of modern crops and increased their vulnerability to environmental stresses. Wild emmer wheat, the tetraploid progenitor of domesticated wheat, distributed along a wide range of ecogeographical conditions in the Fertile Crescent, has valuable "left behind" adaptive diversity to multiple diseases and environmental stresses. The biotic and abiotic stress responses are conferred by series of genes and quantitative trait loci (QTLs) that control complex resistance pathways. The study of genetic diversity, genomic organization, expression profiles, protein structure and function of biotic and abiotic stress-resistance genes, and QTLs could shed light on the evolutionary history and adaptation mechanisms of wild emmer populations for their natural habitats. The continuous evolution and adaptation of wild emmer to the changing environment provide novel solutions that can contribute to safeguarding food for the rapidly growing human population.

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Root precursors of microRNAs in wild emmer and modern wheats show major differences in response to drought stress

Cited by 107 publications

References 71 publications

Transcriptomics analysis of hulless barley during grain development with a focus on starch biosynthesis

Transcriptomics analysis of hulless barley during grain development with a focus on starch biosynthesis

A Comprehensive Prescription for Plant miRNA Identification

Evolution and Adaptation of Wild Emmer Wheat Populations to Biotic and Abiotic Stresses

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