Assembling haplotypes faster than ever with HaploMaker

A team from the Biometry Hub at the University of Adelaide has developed an improved algorithm for haplotype assembly that could help researchers more accurately track plant genetic variation.

For plant researchers who strive to breed tougher crops with higher yields, being able to track the inheritance of genetic traits from parent to offspring is essential.

The best way to analyse these traits is to sequence an organism’s genome - this tells researchers exactly what genes it has and whether there are any helpful variants or not. However, without the right technology, it can be impossible to tell which genes came from which parent.

“To figure out which set of genes came from which parent, we need to assemble something called a haplotype,” explained Dr Mario Fruzangohar, who is a Bioinformatics Research Fellow in the School of Agriculture, Food and Wine at the University of Adelaide. “To assemble a haplotype, we analyse very long sequences of genetic material and identify certain groups of genetic variants that allow us to pinpoint their parental origin.”

This complex assembly is performed using algorithms that are based on mathematical models. Previously, this has been a computationally challenging problem due to the sheer length of the sequences being analysed, and the complexity of genetic inheritance.

To assist with this challenge, a team from the Biometry Hub led by Dr Julian Taylor pursued a novel haplotype construction idea from Dr Fruzangohar  and developed a brand new algorithm called HaploMaker that assembles haplotypes faster than ever.

“We’ve shown that HaploMaker is faster and more accurate than the algorithms being used by our world-leading competitors,” Dr Fruzangohar said. “In most cases, our algorithm reduced the computing time by at least 50%, even while producing longer assembled genomes.”

This important work has recently been published in the internationally-recognised journal GigaScience.

What’s next?

Dr Fruzangohar and his colleagues have developed HaploMaker using Java-based software that is free to download and use and is easily portable between operating systems. This means that any research group in the world can now access the algorithm and use it in their own studies.

In addition, the Biometry team is now exploring how HaploMaker can be used to analyse the genetic material from polyploid crops, which contain more than two sets of chromosomes.