SeSAM: software for automatic construction of order-robust linkage maps.

BACKGROUND: Genotyping and sequencing technologies produce increasingly large numbers of genetic markers with potentially high rates of missing or erroneous data. Therefore, the construction of linkage maps is more and more complex. Moreover, the size of segregating populations remains constrained by cost issues and is less and less commensurate with the numbers of SNPs available. Thus, guaranteeing a statistically robust marker order requires that maps include only a carefully selected subset of SNPs. RESULTS: In this context, the SeSAM software allows automatic genetic map construction using seriation and placement approaches, to produce (1) a high-robustness framework map which includes as many markers as possible while keeping the order robustness beyond a given statistical threshold, and (2) a high-density total map including the framework plus almost all polymorphic markers. During this process, care is taken to limit the impact of genotyping errors and of missing data on mapping quality. SeSAM can be used with a wide range of biparental populations including from outcrossing species for which phases are inferred on-the-fly by maximum-likelihood during map elongation. The package also includes functions to simulate data sets, convert data formats, detect putative genotyping errors, visualize data and map quality (including graphical genotypes), and merge several maps into a consensus. SeSAM is also suitable for interactive map construction, by providing lower-level functions for 2-point and multipoint EM analyses. The software is implemented in a R package including functions in C++. CONCLUSIONS: SeSAM is a fully automatic linkage mapping software designed to (1) produce a framework map as robust as desired by optimizing the selection of a subset of markers, and (2) produce a high-density map including almost all polymorphic markers. The software can be used with a wide range of biparental mapping populations including cases from outcrossing. SeSAM is freely available under a GNU GPL v3 license and works on Linux, Windows, and macOS platforms. It can be downloaded together with its user-manual and quick-start tutorial from ForgeMIA (SeSAM project) at https://forgemia.inra.fr/gqe-acep/sesam/-/releases.

Wheat Landrace Genome Diversity.

Understanding the genomic complexity of bread wheat (Triticum aestivum L.) is a cornerstone in the quest to unravel the processes of domestication and the following adaptation of domesticated wheat to a wide variety of environments across the globe. Additionally, it is of importance for future improvement of the crop, particularly in the light of climate change. Focusing on the adaptation after domestication, a nested association mapping (NAM) panel of 60 segregating biparental populations was developed, mainly involving landrace accessions from the core set of the Watkins hexaploid wheat collection optimized for genetic diversity. A modern spring elite variety, "Paragon," was used as common reference parent. Genetic maps were constructed following identical rules to make them comparable. In total, 1611 linkage groups were identified, based on recombination from an estimated 126,300 crossover events over the whole NAM panel. A consensus map, named landrace consensus map (LRC), was constructed and contained 2498 genetic loci. These newly developed genetics tools were used to investigate the rules underlying genome fluidity or rigidity, e.g., by comparing marker distances and marker orders. In general, marker order was highly correlated, which provides support for strong synteny between bread wheat accessions. However, many exceptional cases of incongruent linkage groups and increased marker distances were also found. Segregation distortion was detected for many markers, sometimes as hot spots present in different populations. Furthermore, evidence for translocations in at least 36 of the maps was found. These translocations fell, in general, into many different translocation classes, but a few translocation classes were found in several accessions, the most frequent one being the well-known T5B:7B translocation. Loci involved in recombination rate, which is an interesting trait for plant breeding, were identified by QTL analyses using the crossover counts as a trait. In total, 114 significant QTL were detected, nearly half of them with increasing effect from the nonreference parents.