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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #353895
Research Project: Enhancing Genetic Merit of Ruminants Through Improved Genome Assembly, Annotation, and Selection

Location: Animal Genomics and Improvement Laboratory

Title: Application of multi-omics in single cells

Author
item KANG, XIAOLONG - Ningxia University
item LIU, ANDREW - Centennial High School
item Liu, Ge - George

Submitted to: Annals of Biotechnology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/16/2018
Publication Date: 4/23/2018
Citation: Kang, X., Liu, A., Liu, G. 2018. Application of multi-omics in single cells. Annals of Biotechnology. 2:1007.

Interpretive Summary: Multi-omics and signle cell assay are the current trends of biological researches. We reviewed opportunities and challenges of combining these two exciting technologies. Farmers, scientist, and policy planners who need improve animal health and production based on genome-enable animal selection will benefit from this review.

Technical Abstract: In recent years, single cell assays have made exciting progresses, overcoming the issue of heterogeneity associated with bulk populations. The fast-developing sequencing methods now enable unbiased, high-throughput and high-resolution view of the heterogeneity from individual cell within a population, in terms of its fate decisions, identity and function. The cell’s state is regulated at different levels, such as DNA, RNA and protein, by complex interplay of intrinsic molecules existing in the organism and extrinsic stimuli such as local environment. Comprehensive profiling of single cell requires a simultaneously dissection from different levels (multi-omics) to avoid incomplete information generated from single cell. In this short review, we first examine the whole genome amplification methods, and then survey the features of the single cell approaches for genome, epigenome, transcriptome, proteome and metabolome profiling. Finally, we briefly analyze advantages of multi-omics measurement from single cells as compared to separate measurement of each molecular type, and discuss opportunities and challenges of combining single cell multi-omics information on resolving phenotype variants.