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Cultivated peanut (Arachis hypogaea) is an allotetraploid with closely related subgenomes of a total size of ~2.7 Gb. This makes the assembly of chromosomal pseudomolecules very challenging. As a foundation to understanding the genome of cultivated peanut, we report the genome sequences of its diploid ancestors (Arachis duranensis and Arachis ipaensis). We show that these genomes are similar to cultivated peanut's A and B subgenomes and use them to identify candidate disease resistance genes, to guide tetraploid transcript assemblies and to detect genetic exchange between cultivated peanut's subgenomes. On the basis of remarkably high DNA identity of the A. ipaensis genome and the B subgenome of cultivated peanut and biogeographic evidence, we conclude that A. ipaensis may be a direct descendant of the same population that contributed the B subgenome to cultivated peanut. A r t i c l e s npg © 2016 Nature America, Inc. All rights reserved.Nature GeNetics VOLUME 48 | NUMBER 4 | APRIL 2016 4 3 9 subgenomes of A. hypogaea. Progeny are vigorous, phenotypically normal and fertile and showed lower segregation distortion 16,17 than has been observed for some populations derived from A. hypogaea intraspecific crosses [18][19][20][21] . Therefore, as a first step to characterizing the genome of cultivated peanut, we sequenced and analyzed the genomes of the two diploid ancestors of cultivated peanut. RESULTS Sequencing and assembly of the diploid A and B genomesConsidering that A. duranensis V14167 and A. ipaensis K30076 are likely good representatives of the ancestral species of A. hypogaea, we sequenced their genomes. After filtering, the data generated from the seven paired-end libraries corresponded to an estimated 154× and 163× base-pair coverage for A. duranensis and A. ipaensis, respectively (Supplementary Tables 1-6). The total assembly sizes were 1,211 and 1,512 Mb for A. duranensis and A. ipaensis, respectively, of which 1,081 and 1,371 Mb were represented in scaffolds of 10 kb or greater in size (Supplementary Table 7). Ultradense genetic maps were generated through genotyping by sequencing (GBS) of two diploid recombinant inbred line (RIL) populations (Supplementary Data Set 1). SNPs within scaffolds were used to validate the assemblies and confirmed their high quality; 190 of 1,297 initial scaffolds of A. duranensis and 49 of 353 initial scaffolds of A. ipaensis were identified as chimeric, on the basis of the presence of diagnostic population-wide switches in genotype calls occurring at the point of misjoin. Chimeric scaffolds were split, and their components were remapped. Thus, approximate chromosomal placements were obtained for 1,692 and 459 genetically verified scaffolds, respectively. Conventional molecular marker maps (Supplementary Data Set 2) and syntenic inferences were then used to refine the ordering of scaffolds within the initial genetic bins. Generally, agreement was good for maps in euchromatic arms and poorer in pericentromeric regions (although one map 22 showed large inversions in two lin...

Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding.

Pigeonpea is an important legume food crop grown primarily by smallholder farmers in many semi-arid tropical regions of the world. We used the Illumina next-generation sequencing platform to generate 237.2 Gb of sequence, which along with Sangerbased bacterial artificial chromosome end sequences and a genetic map, we assembled into scaffolds representing 72.7% (605.78 Mb) of the 833.07 Mb pigeonpea genome. Genome analysis predicted 48,680 genes for pigeonpea and also showed the potential role that certain gene families, for example, drought tolerance-related genes, have played throughout the domestication of pigeonpea and the evolution of its ancestors. Although we found a few segmental duplication events, we did not observe the recent genome-wide duplication events observed in soybean. This reference genome sequence will facilitate the identification of the genetic basis of agronomically important traits, and accelerate the development of improved pigeonpea varieties that could improve food security in many developing countries.

BackgroundHigh density genetic maps of plants have, nearly without exception, made use of marker datasets containing missing or questionable genotype calls derived from a variety of genic and non-genic or anonymous markers, and been presented as a single linear order of genetic loci for each linkage group. The consequences of missing or erroneous data include falsely separated markers, expansion of cM distances and incorrect marker order. These imperfections are amplified in consensus maps and problematic when fine resolution is critical including comparative genome analyses and map-based cloning. Here we provide a new paradigm, a high-density consensus genetic map of barley based only on complete and error-free datasets and genic markers, represented accurately by graphs and approximately by a best-fit linear order, and supported by a readily available SNP genotyping resource.ResultsApproximately 22,000 SNPs were identified from barley ESTs and sequenced amplicons; 4,596 of them were tested for performance in three pilot phase Illumina GoldenGate assays. Data from three barley doubled haploid mapping populations supported the production of an initial consensus map. Over 200 germplasm selections, principally European and US breeding material, were used to estimate minor allele frequency (MAF) for each SNP. We selected 3,072 of these tested SNPs based on technical performance, map location, MAF and biological interest to fill two 1536-SNP "production" assays (BOPA1 and BOPA2), which were made available to the barley genetics community. Data were added using BOPA1 from a fourth mapping population to yield a consensus map containing 2,943 SNP loci in 975 marker bins covering a genetic distance of 1099 cM.ConclusionThe unprecedented density of genic markers and marker bins enabled a high resolution comparison of the genomes of barley and rice. Low recombination in pericentric regions is evident from bins containing many more than the average number of markers, meaning that a large number of genes are recombinationally locked into the genetic centromeric regions of several barley chromosomes. Examination of US breeding germplasm illustrated the usefulness of BOPA1 and BOPA2 in that they provide excellent marker density and sensitivity for detection of minor alleles in this genetically narrow material.

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Using next-generation sequencing technologies it is possible to resequence entire plant genomes or sample entire transcriptomes more efficiently and economically and in greater depth than ever before. Rather than sequencing individual genomes, we envision the sequencing of hundreds or even thousands of related genomes to sample genetic diversity within and between germplasm pools. Identification and tracking of genetic variation are now so efficient and precise that thousands of variants can be tracked within large populations. In this review, we outline some important areas such as the large-scale development of molecular markers for linkage mapping, association mapping, wide crosses and alien introgression, epigenetic modifications, transcript profiling, population genetics and de novo genome/organellar genome assembly for which these technologies are expected to advance crop genetics and breeding, leading to crop improvement.