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Abstract:
Identifying and quantifying the target and strength of selection is an important task in quantitative genetics. With short-read sequencing, many population genomics analyses focus on single nucleotide polymorphisms (SNPs) but lack data on the underlying haplotype block - valuable information for natural selection on a genomic region. We introduce here “haplotagging”, a simple, one-step technique for linked-readsequencing using standard Illumina reagents with no instrumentation or extra costs. Haplotagging preserves linkage information among short reads enabling reconstruction of molecules and haplotypes hundreds ofkilobase in size. It is affordable and scalable, allowing multiplexing of 96 or 384 samples into single Illuminalanes, and enables haplotype discovery at low sequencing coverage. We demonstrate haplotagging with a mouse selection experiment for longer legs ("Longshanks" mice). By sequencing 1400 breeders in a fully pedigreed time series, we directly track the frequency and segregation of haplotypes through 20 generations of selection and estimate selection coefficients across the genome. Next, using 500 Heliconius butterflies from a hybrid zone, we show how direct haplotyping of selected variants reveals candidate SNPs unique to the selected haplotype. In both cases, using haplotypes enhances the genetic signature and avoids problems common in SNP-based analyses. We anticipate that haplotagging to be broadly useful in quantitative genetics, including (meta-)genome assembly and large-scale mapping studies with thousands of samples.
