Tag Archive for 'de novo assembly'

Going green: lessons from plant genomics for human sequencing studies

This is a guest post by Jeffrey Rosenfeld. Jeff is a next-generation sequencing advisor in the High Performance and Research Computing group at the University of Medicine and Dentistry of New Jersey, working on a variety of human and microbial genetics projects. He is also a Visiting Scientist at the American Museum of Natural History where he focuses on whole-genome phylogenetics. He was trained at the University of Pennsylvania, New York University and Cold Spring Harbor Laboratory.

As human geneticists, it is all too easy to ignore papers published about non-human organisms – especially when those organisms are plants. After all, how much can the analysis of (say) Arabidopsis genome diversity possibly assist in my quest to better understand the human genome and determine which genes cause disease? Quite a bit, as it happens: a fascinating recent paper in Nature demonstrates a number of lessons that we can learn from our distant green relatives.

By exploiting the small genome size of Arabidopsis (~120 million bases, compared to the relatively gargantuan 3 billion bases of Homo sapiens), researchers were able to perform complete genome sequencing and transcriptome profiling in 18 different ecotypes of the plant (similar to what we would call strains of an animal).

In a normal genome re-sequencing experiment, the procedure is to obtain DNA from an individual, sequence the DNA, align it to a reference sequence and then to call variants (i.e. differences from the reference). This approach is used by the 1000 Genomes Project and basically all of the hundreds of disease-focused human sequencing projects currently underway around the world. This approach allows researchers to relatively easily identify single-base substitution (SNP) and small insertion/deletion (indel) differences between genomes. However, the amount of variability that can be identified is restricted by the use of a reference: regions where there is extreme divergence between the reference and sample genomes are often badly called, and more complex variants (e.g. large, recurrent rearrangements of DNA) can be missed. Additionally, and crucially, sequences that are not present in the reference genome will be completely missed by this approach.
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