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Journal of Biotechnology & Biomaterials | ISSN: 2155-952X | Volume: 8

World Biotechnology Congress

December 03-04, 2018 Sao Paulo, Brazil

Meta-analysis of RNA seq data to gain insight into crop responses to environmental stresses

Federico Martinelli, Jubina Benny

and

Tiziano Caruso

University of Palermo, Italy

NA-Seq analysis is a strong tool to gain insight into the molecular responses to biotic stresses in plants. Transcriptomic studies

are usually conducted in a singular time, they do not provide any repetition across different seasons and frequently they are

performed in field conditions where environmental variability is high and disturbing factors are frequently present. The identification

of up- or down-regulated genes is often not enough to draw meaningful biological conclusions because it is hard to identify which

gene plays a key role in specific signaling networks in host responses. This issue leads to high difficulties in deriving conclusive

models for understanding disease symptomatology. For these reasons, more meta-analysis is needed in order to validate singular

transcriptomic works with other similar studies performed with the same research purposes. Meta-analysis of transcriptomic data will

identify commonalities and differences between differentially regulated gene lists and will allow screen which genes are key players

in gene-gene and protein-protein interaction networks. These analyses will allow delivering important information on how a specific

environmental factor affects plant molecular responses and how plants activate general stress responses to environmental stresses. An

early “stress condition” in plants is similar to the “inflammatory response” occurring in animals in response to pathogen-associated

factors. The objective of this work is to identify specific and common molecular features (genes, proteins, gene sets, pathways), linked

to both abiotic and biotic stress resistances among key crops. The identification of common genes between different biotic stress will

allow to gain insight into these general responses and help the diagnosis of an early “stress state” of the plants. These analyses will help

in monitoring stressed plants to start early specific management procedures for each disease or disorder.

J Biotechnol Biomater 2018, Volume: 8

DOI: 10.4172/2155-952X-C7-107