Most eukaryotes are diploid, including humans. They have two copies of each autosome. Thousands of human genomes have been sequenced but in almost all cases the resulting genome sequence is a mixture of sequences from homologous chromosomes. If a site is heterogeneous—different alleles on each chromosome—then these are entered as variants.
It would be much better to have complete sequences of each individual chromosome (= diploid sequence) in order to better understand genetic heterogeneity in the human population. Until recently, there were only two examples in the databases. The first was Craig Venter's genome (Levey et al., 2007) and the second was an Asian male (YH) (Cao et al., 2015).
Diploid sequences are much more expensive and time-consuming than standard reference sequences. That's because you can't just match sequence reads to the human reference genome in order to obtain alignment and position information. Instead, you have to pretty much construct de novo assemblies of each chromosome. Using modern technology, it's relatively easy to generate millions of short sequence reads and then match then up to the reference genome to get a genome sequence that combines information from both chromosomes. That's why it's now possible to sequence a genome for less that $1000 (US). De novo assemblies require much more data and more computing power.
A group at a private company (10X Genomics in Pleasanton, California (USA)) has developed new software to assemble diploid genome sequences. They used the technology to add seven new diploid sequences to the databases (Weisenfeld et al., 2017). The resulting assemblies are just draft genomes with plenty of gaps but this is still a significant achievement.
Here's the abstract,
It would be much better to have complete sequences of each individual chromosome (= diploid sequence) in order to better understand genetic heterogeneity in the human population. Until recently, there were only two examples in the databases. The first was Craig Venter's genome (Levey et al., 2007) and the second was an Asian male (YH) (Cao et al., 2015).
Diploid sequences are much more expensive and time-consuming than standard reference sequences. That's because you can't just match sequence reads to the human reference genome in order to obtain alignment and position information. Instead, you have to pretty much construct de novo assemblies of each chromosome. Using modern technology, it's relatively easy to generate millions of short sequence reads and then match then up to the reference genome to get a genome sequence that combines information from both chromosomes. That's why it's now possible to sequence a genome for less that $1000 (US). De novo assemblies require much more data and more computing power.
A group at a private company (10X Genomics in Pleasanton, California (USA)) has developed new software to assemble diploid genome sequences. They used the technology to add seven new diploid sequences to the databases (Weisenfeld et al., 2017). The resulting assemblies are just draft genomes with plenty of gaps but this is still a significant achievement.
Here's the abstract,
Weisenfeld, N.I., Kumar, V., Shah, P., Church, D.M., and Jaffe, D.B. (2017) Direct determination of diploid genome sequences. Genome Research, 27:757-767. [doi: 10.1101/gr.214874.116]
Determining the genome sequence of an organism is challenging, yet fundamental to understanding its biology. Over the past decade, thousands of human genomes have been sequenced, contributing deeply to biomedical research. In the vast majority of cases, these have been analyzed by aligning sequence reads to a single reference genome, biasing the resulting analyses, and in general, failing to capture sequences novel to a given genome. Some de novo assemblies have been constructed free of reference bias, but nearly all were constructed by merging homologous loci into single “consensus” sequences, generally absent from nature. These assemblies do not correctly represent the diploid biology of an individual. In exactly two cases, true diploid de novo assemblies have been made, at great expense. One was generated using Sanger sequencing, and one using thousands of clone pools. Here, we demonstrate a straightforward and low-cost method for creating true diploid de novo assemblies. We make a single library from ∼1 ng of high molecular weight DNA, using the 10x Genomics microfluidic platform to partition the genome. We applied this technique to seven human samples, generating low-cost HiSeq X data, then assembled these using a new “pushbutton” algorithm, Supernova. Each computation took 2 d on a single server. Each yielded contigs longer than 100 kb, phase blocks longer than 2.5 Mb, and scaffolds longer than 15 Mb. Our method provides a scalable capability for determining the actual diploid genome sequence in a sample, opening the door to new approaches in genomic biology and medicine.
Cao, H., Wu, H., Luo, R., Huang, S., Sun, Y., Tong, X., Xie, Y., Liu, B., Yang, H., and Zheng, H. (2015) De novo assembly of a haplotype-resolved human genome. Nature biotechnology, 33:617-622. [doi:10.1038/nbt.3200]
Levy, S., Sutton, G., Ng, P.C., Feuk, L., Halpern, A.L., Walenz, B.P., Axelrod, N., Huang, J., Kirkness, E.F., Denisov, G., Lin, Y., MacDonald, J.R., Pang, A.W. C., Shago, M., Stockwell, T.B., Tsiamouri, A., Bafna, V., Bansal, V., Kravitz, S.A., Busam, D.A., Beeson, K. Y., McIntosh, T.C., Remington, K.A., Abril, J.F., Gill, J., Borman, J., Rogers, Y.-H., Frazier, M.E., Scherer, S.W., Strausberg, R.L., and Venter, J.C. (2007) The diploid genome sequence of an individual human. PLoS Biol, 5:e254. [doi: 10.1371/journal.pbio.0050254]
