-Sristi Raj Rai, Amity University Kolkata
In the whirlpool of diseases that strike humans, how worthy will it be to pinpoint the origin behind by just using 4 English alphabets that conclude specie’s fate? Hidden in 98% non-coding regions occurring in the large size of 6.4 bn bp human genome, with minor allele frequency (MAF) <1% are some large-effect rare variants (RVs), linked with risk of complex diseases. Therefore, recognizing abundantly present RVs and their functionality, eventually connecting to its phenotypic consequences is a tough task. However, Ferraro et al. crafted a way out by analyzing RVs contributing to outlier patterns in total gene expression (eOutliers), allelic expression (aseOutliers), and alternative splicing (sOutliers) with 838 donor’s data of both whole-genome and transcriptome in the Genotype-Tissue Expression (GTEx-v8) project.
Multi-tissue RNA-sequencing data informed each signal generated points to a unique class of RVs. The group developed a probabilistic model – Watershed to improve standard genome annotations by integrating all 3 signals from an individual to predict the variant function. These prognostics were verified through experimentation and evaluated for association with diverse traits through computational analysis. The report suggests more than 50 RVs are linked to diverse molecular effects affecting the human transcriptome across 49 tissues. The designed model promises improved disease gene identification and delivery of precision genomics.
SOURCE – Ferraro, N., Strober, B., Einson, J., Abell, N., Aguet, F., Barbeira, A., Brandt, M., Bucan, M., Castel, S., Davis, J., Greenwald, E., Hess, G., Hilliard, A., Kember, R., Kotis, B., Park, Y., Peloso, G., Ramdas, S., Scott, A., Smail, C., Tsang, E., Zekavat, S., Ziosi, M., Aradhana, Ardlie, K., Assimes, T., Bassik, M., Brown, C., Correa, A., Hall, I., Im, H., Li, X., Natarajan, P., Lappalainen, T., Mohammadi, P., Montgomery, S. and Battle, A., 2020. Transcriptomic signatures across human tissues identify functional rare genetic variation. Science, 369(6509), p.eaaz5900.
LINK – https://science.sciencemag.org/content/369/6509/eaaz5900.full
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