Physical Map of the Short Arm of Bread Wheat Chromosome 3D

GALA: a computational framework for de novo chromosome-by-chromosome assembly with long reads

High-quality genome assembly has wide applications in genetics and medical studies. However, it is still very challenging to achieve gap-free chromosome-scale assemblies using current workflows for long-read platforms. Here we report on GALA (Gap-free long-read Assembly tool), a computational framework for chromosome-based sequencing data separation and de novo assembly implemented through a multi-layer graph that identifies discordances within preliminary assemblies and partitions the data into chromosome-scale scaffolding groups. The subsequent independent assembly of each scaffolding group generates a gap-free assembly likely free from the mis-assembly errors which usually hamper existing workflows. This flexible framework also allows us to integrate data from various technologies, such as Hi-C, genetic maps, and even motif analyses to generate gap-free chromosome-scale assemblies. As a proof of principle we de novo assemble the C. elegans genome using combined PacBio and Nanopore sequencing data and a rice cultivar genome using Nanopore sequencing data from publicly available datasets. We also demonstrate the proposed method's applicability with a gap-free assembly of the human genome using PacBio high-fidelity (HiFi) long reads. Thus, our method enables straightforward assembly of genomes with multiple data sources and overcomes barriers that at present restrict the application of de novo genome assembly technology.

Bioinformatics in Plant Breeding and Research on Disease Resistance

In the context of plant breeding, bioinformatics can empower genetic and genomic selection to determine the optimal combination of genotypes that will produce a desired phenotype and help expedite the isolation of these new varieties. Bioinformatics is also instrumental in collecting and processing plant phenotypes, which facilitates plant breeding. Robots that use automated and digital technologies to collect and analyze different types of information to monitor the environment in which plants grow, analyze the environmental stresses they face, and promptly optimize suboptimal and adverse growth conditions accordingly, have helped plant research and saved human resources. In this paper, we describe the use of various bioinformatics databases and algorithms and explore their potential applications in plant breeding and for research on plant disease resistance.

Chromosome genomics uncovers plant genome organization and function

The identification of causal genomic loci and their interactions underlying various traits in plants has been greatly aided by progress in understanding the organization of the nuclear genome. This provides clues to the responses of plants to environmental stimuli at the molecular level. Apart from other uses, these insights are needed to fully explore the potential of new breeding techniques that rely on genome editing. However, genome analysis and sequencing is not straightforward in the many agricultural crops and their wild relatives that possess large and complex genomes. Chromosome genomics streamlines this task by dissecting the genome to single chromosomes whose DNA is then used instead of nuclear DNA. This results in a massive and lossless reduction in DNA sample complexity, reduces the time and cost of the experiment, and simplifies data interpretation. Flow cytometric sorting of condensed mitotic chromosomes makes it possible to purify single chromosomes in large quantities, and as the DNA remains intact this process can be coupled successfully with many techniques in molecular biology and genomics. Since the first experiments with flow cytometric sorting in the late 1980s, numerous applications have been developed, and chromosome genomics has been having a significant impact in many areas of research, including the sequencing of complex genomes of important crops and gene cloning. This review discusses these applications, describes their contribution to advancements in plant genome analysis and gene cloning, and outlines future directions.

Shifting the limits in wheat research and breeding using a fully annotated reference genome

An annotated reference sequence representing the hexaploid bread wheat genome in 21 pseudomolecules has been analyzed to identify the distribution and genomic context of coding and noncoding elements across the A, B, and D subgenomes. With an estimated coverage of 94% of the genome and containing 107,891 high-confidence gene models, this assembly enabled the discovery of tissue- and developmental stage-related coexpression networks by providing a transcriptome atlas representing major stages of wheat development. Dynamics of complex gene families involved in environmental adaptation and end-use quality were revealed at subgenome resolution and contextualized to known agronomic single-gene or quantitative trait loci. This community resource establishes the foundation for accelerating wheat research and application through improved understanding of wheat biology and genomics-assisted breeding.

Features of the organization of bread wheat chromosome 5BS based on physical mapping

BACKGROUND

The IWGSC strategy for construction of the reference sequence of the bread wheat genome is based on first obtaining physical maps of the individual chromosomes. Our aim is to develop and use the physical map for analysis of the organization of the short arm of wheat chromosome 5B (5BS) which bears a number of agronomically important genes, including genes conferring resistance to fungal diseases.

RESULTS

A physical map of the 5BS arm (290 Mbp) was constructed using restriction fingerprinting and LTC software for contig assembly of 43,776 BAC clones. The resulting physical map covered ~ 99% of the 5BS chromosome arm (111 scaffolds, N50 = 3.078 Mb). SSR, ISBP and zipper markers were employed for anchoring the BAC clones, and from these 722 novel markers were developed based on previously obtained data from partial sequencing of 5BS. The markers were mapped using a set of Chinese Spring (CS) deletion lines, and F2 and RICL populations from a cross of CS and CS-5B dicoccoides. Three approaches have been used for anchoring BAC contigs on the 5BS chromosome, including clone-by-clone screening of BACs, GenomeZipper analysis, and comparison of BAC-fingerprints with in silico fingerprinting of 5B pseudomolecules of T. dicoccoides. These approaches allowed us to reach a high level of BAC contig anchoring: 96% of 5BS BAC contigs were located on 5BS. An interesting pattern was revealed in the distribution of contigs along the chromosome. Short contigs (200-999 kb) containing markers for the regions interrupted by tandem repeats, were mainly localized to the 5BS subtelomeric block; whereas the distribution of larger 1000-3500 kb contigs along the chromosome better correlated with the distribution of the regions syntenic to rice, Brachypodium, and sorghum, as detected by the Zipper approach.

CONCLUSION

The high fingerprinting quality, LTC software and large number of BAC clones selected by the informative markers in screening of the 43,776 clones allowed us to significantly increase the BAC scaffold length when compared with the published physical maps for other wheat chromosomes. The genetic and bioinformatics resources developed in this study provide new possibilities for exploring chromosome organization and for breeding applications.