Tendons heal by fibrosis, which hinders function and increases re-injury risk. Yet the biology that leads to degeneration and regeneration of tendons is not completely understood. Improved understanding of the metabolic nuances that cause diverse outcomes in tendinopathies is required to solve these problems. ‘Omics methods are increasingly used to characterize phenotypes in tissues. Multiomics integrates ‘omic datasets to identify coherent relationships and provide insight into differences in molecular and metabolic pathways between anatomic locations, and disease stages. This work reviews the current literature pertaining to multiomics in tendon and the potential of these platforms to improve tendon regeneration. We assessed the literature and identified areas where ‘omics platforms contribute to the field: (1) Tendon biology where their hierarchical complexity and demographic factors are studied. (2) Tendon degeneration and healing, where comparisons across tendon pathologies are analyzed. (3) The in vitro engineered tendon phenotype, where we compare the engineered phenotype to relevant native tissues. (4) Finally, we review regenerative and therapeutic approaches. We identified gaps in current knowledge and opportunities for future study: (1) The need to increase the diversity of human subjects and cell sources. (2) Opportunities to improve understanding of tendon heterogeneity. (3) The need to use these improvements to inform new engineered and regenerative therapeutic approaches. (4) The need to increase understanding of the development of tendon pathology. Together, the expanding use of various ‘omics platforms and data analysis resulting from these platforms could substantially contribute to major advances in the tendon tissue engineering and regenerative medicine field.

Tendon transcriptomics is a rapidly growing field in musculoskeletal biology. The ultimate aim of many current tendon transcriptomic studies is characterization of in vitro, ex vivo, or in vivo, healthy, and diseased tendon microenvironments to identify the underlying pathways driving human tendon pathology. The transcriptome interfaces between genomic, proteomic, and metabolomic signatures of the tendon cellular niche and the response of this niche to stimuli. Some of the greatest bottlenecks in tendon transcriptomics relate to the availability and quality of human tendon tissue, hence animal tissues are frequently used even though human tissue is most translationally relevant. Here, we review the variability associated with human donor and procurement factors, such as whether the tendon is cadaveric or a clinical remnant, and how these variables affect the quality and relevance of the transcriptomes obtained. Moreover, age, sex, and health demographic variables impact the human tendon transcriptome. Tendons present tissue‐specific challenges for cell, nuclei, and RNA extraction that include a dense extracellular matrix, low cellularity, and therefore low RNA yield of variable quality. Consideration of these factors is particularly important for single‐cell and single‐nuclei resolution transcriptomics due to the necessity for unbiased and representative cell or nuclei populations. Different cell, nuclei, and RNA extraction methods, library preparation, and quality control methods are used by the tendon research community and attention should be paid to these when designing and reporting studies. We discuss the different components and challenges of human tendon transcriptomics, and propose pipelines, quality control, and reporting guidelines for future work in the field.