An ordered draft sequence of the 17-gigabase hexaploid bread wheat (Triticum aestivum) genome has been produced by sequencing isolated chromosome arms. We have annotated 124,201 gene loci distributed nearly evenly across the homeologous chromosomes and subgenomes. Comparative gene analysis of wheat subgenomes and extant diploid and tetraploid wheat relatives showed that high sequence similarity and structural conservation are retained, with limited gene loss, after polyploidization. However, across the genomes there was evidence of dynamic gene gain, loss, and duplication since the divergence of the wheat lineages. A high degree of transcriptional autonomy and no global dominance was found for the subgenomes. These insights into the genome biology of a polyploid crop provide a springboard for faster gene isolation, rapid genetic marker development, and precise breeding to meet the needs of increasing food demand worldwide.

A chromosome-based draft sequence of the hexaploid bread wheat (Triticum aestivum) genome

During the past decade, numerous studies have been published on molecular mapping of Fusarium head blight (FHB) resistance in wheat. We summarize the relevant findings from 52 quantitative trait loci (QTL) mapping studies, nine research articles on marker-assisted selection and seven on marker-assisted germplasm evaluation. QTL for FHB resistance were found on all wheat chromosomes except chromosome 7D. Some QTL were found in several independent mapping studies indicating that such QTL are stable and therefore useful in breeding programmes. We summarize and update current knowledge on the genetics of FHB resistance in wheat resulting from QTL mapping investigations and review and suggest FHB breeding strategies based on the available information and DNA markers.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1439-0523.2008.01550.x

QTL mapping and marker-assisted selection for Fusarium head blight resistance in wheat: A review

In the last 20 years, we have observed an exponential growth of the DNA sequence data and simular increase in the volume of DNA polymorphism data generated by numerous molecular marker technologies. Most of the investment, and therefore progress, concentrated on human genome and genomes of selected model species. Diversity Arrays Technology (DArT), developed over a decade ago, was among the first "democratizing" genotyping technologies, as its performance was primarily driven by the level of DNA sequence variation in the species rather than by the level of financial investment. DArT also proved more robust to genome size and ploidy-level differences among approximately 60 organisms for which DArT was developed to date compared to other high-throughput genotyping technologies. The success of DArT in a number of organisms, including a wide range of "orphan crops," can be attributed to the simplicity of underlying concepts: DArT combines genome complexity reduction methods enriching for genic regions with a highly parallel assay readout on a number of "open-access" microarray platforms. The quantitative nature of the assay enabled a number of applications in which allelic frequencies can be estimated from DArT arrays. A typical DArT assay tests for polymorphism tens of thousands of genomic loci with the final number of markers reported (hundreds to thousands) reflecting the level of DNA sequence variation in the tested loci. Detailed DArT methods, protocols, and a range of their application examples as well as DArT's evolution path are presented.

Diversity arrays technology: a generic genome profiling technology on open platforms.

Advancements in Lorenz, USDA-ARS, R.W. Holley Center for Agriculture and Health, genotyping are rapidly decreasing Cornell Univ., Ithaca, NY 14853. Received 9 Nov. 2009. *Corremarker costs and increasing genome coverage. This is facilitating the use of marker-assisted selection (MAS) in plant breeding. Commonly employed MAS strategies, however, are not well suited for agronomically important complex traits, requiring extra time for !eld-based phenotyping to identify agro-nomically superior lines. Genomic selection (GS) is an emerging alternative to MAS that uses all marker information to calculate genomic esti-mated breeding values (GEBVs) for complex traits. Selections are made directly on GEBV without further phenotyping. We developed an analytical framework to (i) compare gains from MAS and GS for complex traits and (ii) provide a plant breeding context for interpreting results from studies on GEBV accuracy. We designed MAS and GS breeding strategies with equal budgets for a high-investment maize (Zea mays L.) program and a low-investment winter wheat (Triticum aestivum L.) program. Results indicate that GS can outperform MAS on a per-year basis even at low GEBV accuracies. Using a previ-ously reported GEBV accuracy of 0.53 for net merit in dairy cattle, expected annual gain from GS exceeded that of MAS by about threefold for maize and twofold for winter wheat. We con-clude that if moderate selection accuracies can be achieved, GS could dramatically accelerate genetic gain through its shorter breeding"cycle.E.L. He-ner and M.E. Sorrells, Cornell Univ., Dep. of Plant Breeding and Genetics, Emerson Hall, Ithaca, NY 14853; J.-L. Jannink and A.J. -sponding author (mes12@cornell.edu).

Plant Breeding with Genomic Selection: Gain per Unit Time and Cost

Genomic selection (GS) uses genomewide molecular markers to predict breeding values and make selections of individuals or breeding lines prior to phenotyping. Here we show that genotyping-by-sequencing (GBS) can be used for de novo genotyping of breeding panels and to develop accurate GS models, even for the large, complex, and polyploid wheat (Triticum aestivum L.) genome. With GBS we discovered 41,371 single nucleotide polymorphisms (SNPs) in a set of 254 advanced breeding lines from CIMMYT’s semiarid wheat breeding program. Four different methods were evaluated for imputing missing marker scores in this set of unmapped markers, including random forest regression and a newly developed multivariate-normal expectation-maximization algorithm, which gave more accurate imputation than heterozygous or mean imputation at the marker level, although no signifi cant differences were observed in the accuracy of genomic-estimated breeding values (GEBVs) among imputation methods. Genomic-estimated breeding value prediction accuracies with GBS were 0.28 to 0.45 for grain yield, an improvement of 0.1 to 0.2 over an established marker platform for wheat. Genotyping-bysequencing combines marker discovery and genotyping of large populations, making it an excellent marker platform for breeding applications even in the absence of a reference genome sequence or previous polymorphism discovery. In addition, the fl exibility and low cost of GBS make this an ideal approach for genomics-assisted breeding.

Genomic Selection in Wheat Breeding using Genotyping-by-Sequencing

Despite a substantial investment in the development of panels of single nucleotide polymorphism (SNP) markers, the simple sequence repeat (SSR) technology with a limited multiplexing capability remains a standard, even for applications requiring whole-genome information. Diversity arrays technology (DArT) types hundreds to thousands of genomic loci in parallel, as previously demonstrated in a number diploid plant species. Here we show that DArT performs similarly well for the hexaploid genome of bread wheat (Triticum aestivum L.). The methodology previously used to generate DArT fingerprints of barley also generated a large number of high-quality markers in wheat (99.8% allele-calling concordance and approximately 95% call rate). The genetic relationships among bread wheat cultivars revealed by DArT coincided with knowledge generated with other methods, and even closely related cultivars could be distinguished. To verify the Mendelian behaviour of DArT markers, we typed a set of 90 Cranbrook x Halberd doubled haploid lines for which a framework (FW) map comprising a total of 339 SSR, restriction fragment length polymorphism (RFLP) and amplified fragment length polymorphism (AFLP) markers was available. We added an equal number of DArT markers to this data set and also incorporated 71 sequence tagged microsatellite (STM) markers. A comparison of logarithm of the odds (LOD) scores, call rates and the degree of genome coverage indicated that the quality and information content of the DArT data set was comparable to that of the combined SSR/RFLP/AFLP data set of the FW map.

Bill Rathmell

Papers

Diversity arrays technology (DArT) for high-throughput profiling of the hexaploid wheat genome