Milan Malinsky | bioRxiv Science

bioRxiv2016

RADpainter and fineRADstructure: population inference from RADseq data

Powerful approaches to inferring recent or current population structure based on nearest neighbour haplotype coancestry have so far been inaccessible to users without high quality genome-wide haplotype data. With a boom in non-model organism genomics, there is a pressing need to bring these methods to communities without access to such data. Here we present RADpainter, a new program designed to infer the coancestry matrix from restriction-site-associated DNA sequencing (RADseq) data. We combine this program together with a previously published MCMC clustering algorithm into fineRADstructure - a complete, easy to use, and fast population inference package for RADseq data (https://github.com/millanek/fineRADstructure). Finally, with two example datasets, we illustrate its use, benefits, and robustness to missing RAD alleles in double digest RAD sequencing.

Evolutionary Biology↗

bioRxiv2016

trio-sga: facilitating de novo assembly of highly heterozygous genomes with parent-child trios

MotivationMost DNA sequence in diploid organisms is found in two copies, one contributed by the mother and the other by the father. The high density of differences between the maternally and paternally contributed sequences (heterozygous sites) in some organisms makes de novo genome assembly very challenging, even for algorithms specifically designed to deal with these cases. Therefore, various approaches, most commonly inbreeding in the laboratory, are used to reduce heterozygosity in genomic data prior to assembly. However, many species are not amenable to these techniques.\n\nResultsWe introduce trio-sga, a set of three algorithms designed to take advantage of mother-father-offspring trio sequencing to facilitate better quality genome assembly in organisms with moderate to high levels of heterozygosity. Two of the algorithms use haplotype phase information present in the trio data to eliminate the majority of heterozygous sites before the assembly commences. The third algorithm is designed to reduce sequencing costs by enabling the use of parents reads in the assembly of the genome of the offspring. We test these algorithms on a simulated trio from four hap-loid datasets, and further demonstrate their performance by assembling three highly heterozygous Heliconius butterfly genomes. While the implementation of trio-sga is tuned towards Illumina-generated data, we note that the trio approach to reducing heterozygosity is likely to have cross-platform utility for de novo assembly.

Bioinformatics↗