FluorescenceIn SituHybridization and Optical Mapping to Correct Scaffold Arrangement in the Tomato Genome

Abstract

The order and orientation (arrangement) of all 91 sequenced scaffolds in the 12 pseudomolecules of the recently published tomato (Solanum lycopersicum, 2n = 2x = 24) genome sequence were positioned based on marker order in a high-density linkage map. Here, we report the arrangement of these scaffolds determined by two independent physical methods, bacterial artificial chromosome–fluorescence in situ hybridization (BAC-FISH) and optical mapping. By localizing BACs at the ends of scaffolds to spreads of tomato synaptonemal complexes (pachytene chromosomes), we showed that 45 scaffolds, representing one-third of the tomato genome, were arranged differently than predicted by the linkage map. These scaffolds occur mostly in pericentric heterochromatin where 77% of the tomato genome is located and where linkage mapping is less accurate due to reduced crossing over. Although useful for only part of the genome, optical mapping results were in complete agreement with scaffold arrangement by FISH but often disagreed with scaffold arrangement based on the linkage map. The scaffold arrangement based on FISH and optical mapping changes the positions of hundreds of markers in the linkage map, especially in heterochromatin. These results suggest that similar errors exist in pseudomolecules from other large genomes that have been assembled using only linkage maps to predict scaffold arrangement, and these errors can be corrected using FISH and/or optical mapping. Of note, BAC-FISH also permits estimates of the sizes of gaps between scaffolds, and unanchored BACs are often visualized by FISH in gaps between scaffolds and thus represent starting points for filling these gaps.

Integrated bioinformatics to decipher the ascorbic acid metabolic network in tomato

“…In particular, root, leaf, flower, flower bud and six developmental stages of fruit (1, 2, 3 cm, mature green, breaker and mature red) tissues were considered. The gene expression level was defined on the basis of the iTAG mRNA loci (Shearer et al 2014) and was normalized by Reads Per Kilobases per Million (RPKM) for each tissue/ stage. Genes with expression level below 1 RPKM were considered as not expressed.…”

“…However, addressing the role of the different pathways and the functionality of the different steps still remains a relevant issue. A major contribution to dissect these aspects can be provided by a suitable integration of data and resources today available for tomato (Chiusano et al 2008;Tomato Genome Consortium 2012;Shearer et al 2014;Bostan and Chiusano 2015). Driven by the recent increase of the ''omics'' data in tomato (Kusano and Fukushima 2013) the aim of this work is to gain insights into the AsA network architecture providing a complete gene survey for the biosynthetic, the recycling and the translocation pathways based on the current annotation of the tomato genome (iTAG2.40).…”

The Juicebox Assembly Tools module facilitatesde novoassembly of mammalian genomes with chromosome-length scaffolds for under $1000

“…Scaffolds can contain errors in contig order (a 'translocation') or orientation (an 'inversion'). Examples of such errors can be found in the best available reference genomes for many species (Robert B. Norgren 2013;Shearer et al 2014;Tang et al 2014;Chen et al 2015;Davey et al 2016;Utsunomiya et al 2016;Schneider et al 2017;Korlach et al 2017). Consequently, inexpensive methods for identifying and correcting assembly errors are crucial for the generation of accurate assemblies (Salzberg and Yorke 2005;Phillippy, Schatz, and Pop 2008;Gnerre et al 2009;Tsai, Otto, and Berriman 2010;Salzberg et al 2012;Hunt et al 2013;Gurevich et al 2013;Bradnam et al 2013;Simão et al 2015;Fierst 2015;Muggli et al 2015;Yuan et al 2017;Harewood et al 2017).…”

A Review of Genome Sequencing in the Largest Cereal Genome, <i>Triticum aestivum</i> L.

“…Miss-assembly and gaps in the sequence data are recurring problems in the assembly of any genome whether by whole genome shotgun approaches [58] [59] [60] or clone-by-clone approaches [61] [62]. Applications providing longer reads have fast become very popular for solving some of the issues associated with genome assemblies and platforms such as PacBio [55] and BioNano [51] show promise to improve the quality of shotgun assemblies.…”