Highly dense linkage maps from 31 full-sibling families of turbot (Scophthalmus maximus) provide insights into recombination patterns and chromosome rearrangements throughout a newly refined genome assembly.

Highly dense linkage maps enable positioning thousands of landmarks useful for anchoring the whole genome and for analysing genome properties. Turbot is the most important cultured flatfish worldwide and breeding programs in the fifth generation of selection are targeted to improve growth rate, obtain disease resistant broodstock and understand sex determination to control sex ratio. Using a Restriction-site Associated DNA approach, we genotyped 18,214 single nucleotide polymorphism in 1,268 turbot individuals from 31 full-sibling families. Individual linkage maps were combined to obtain a male, female and species consensus maps. The turbot consensus map contained 11,845 markers distributed across 22 linkage groups representing a total normalised length of 3,753.9 cM. The turbot genome was anchored to this map, and scaffolds representing 96% of the assembly were ordered and oriented to obtain the expected 22 megascaffolds according to its karyotype. Recombination rate was lower in males, especially around centromeres, and pairwise comparison of 44 individual maps suggested chromosome polymorphism at specific genomic regions. Genome comparison across flatfish provided new evidence on karyotype reorganisations occurring across the evolution of this fish group.

Performance and precision of double digestion RAD (ddRAD) genotyping in large multiplexed datasets of marine fish species.

The development of Genotyping-By-Sequencing (GBS) technologies enables cost-effective analysis of large numbers of Single Nucleotide Polymorphisms (SNPs), especially in "non-model" species. Nevertheless, as such technologies enter a mature phase, biases and errors inherent to GBS are becoming evident. Here, we evaluated the performance of double digest Restriction enzyme Associated DNA (ddRAD) sequencing in SNP genotyping studies including high number of samples. Datasets of sequence data were generated from three marine teleost species (>5500 samples, >2.5 × 1012 bases in total), using a standardized protocol. A common bioinformatics pipeline based on STACKS was established, with and without the use of a reference genome. We performed analyses throughout the production and analysis of ddRAD data in order to explore (i) the loss of information due to heterogeneous raw read number across samples; (ii) the discrepancy between expected and observed tag length and coverage; (iii) the performances of reference based vs. de novo approaches; (iv) the sources of potential genotyping errors of the library preparation/bioinformatics protocol, by comparing technical replicates. Our results showed use of a reference genome and a posteriori genotype correction improved genotyping precision. Individual read coverage was a key variable for reproducibility; variance in sequencing depth between loci in the same individual was also identified as an important factor and found to correlate to tag length. A comparison of downstream analysis carried out with ddRAD vs single SNP allele specific assay genotypes provided information about the levels of genotyping imprecision that can have a significant impact on allele frequency estimations and population assignment. The results and insights presented here will help to select and improve approaches to the analysis of large datasets based on RAD-like methodologies.