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Volume 4 Issue 3, November 2011
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Switchgrass (Panicum virgatum L.) is a perennial grass species receiving significant focus as a potential bioenergy crop. In the last 5 yr the switchgrass research community has produced a genetic linkage map, an expressed sequence tag (EST) database, a set of single nucleotide polymorphism (SNP) markers that are distributed across the 18 linkage groups, 4x sampling of the P. virgatum AP13 genome in 400-bp reads, and bacterial artificial chromosome (BAC) libraries containing over 200,000 clones. These studies have revealed close collinearity of the switchgrass genome with those of sorghum [Sorghum bicolor (L.) Moench], rice (Oryza sativa L.), and Brachypodium distachyon (L.) P. Beauv. Switchgrass researchers have also developed several microarray technologies for gene expression studies. Switchgrass genomic resources will accelerate the ability of plant breeders to enhance productivity, pest resistance, and nutritional quality. Because switchgrass is a relative newcomer to the genomics world, many secrets of the switchgrass genome have yet to be revealed. To continue to efficiently explore basic and applied topics in switchgrass, it will be critical to capture and exploit the knowledge of plant geneticists and breeders on the next logical steps in the development and utilization of genomic resources for this species. To this end, the community has established a switchgrass genomics executive committee and work group (http://switchgrassgenomics.org/ [verified 28 Oct. 2011]).
Linkage mapping is relevant to modern plant biology and provides a framework for downstream analyses including quantitative trait loci identification, map-based cloning, assessment of diversity, association mapping, and molecular breeding. Here, we report a consensus genetic map of cowpea [Vigna unguiculata (L.) Walp.] and synteny to other legumes based on expressed sequence tag (EST)-derived single nucleotide polymorphisms (SNPs). In total, 1293 individuals representing 13 mapping populations were genotyped using an Illumina 1536 GoldenGate Assay. A consensus map containing 1107 EST-derived SNP markers (856 bins) on 11 linkage groups (680 cM) was constructed from 13 population-specific maps. This effort combined six new population-specific maps and seven revised population-specific maps to construct an improved consensus map with 33% more bins, 19% more markers, and improved marker order when compared to the previous cowpea SNP consensus map. Comparative and whole genome visualizations are presented as a framework for discussing map quality and synteny with soybean [Glycine max (L.) Merr.].
Iron deficiency chlorosis (IDC) is a significant yield-limiting problem in several major soybean [Glycine max (L.) Merr.] production regions in the United States. Soybean plants display a variety of symptoms that range from a slight yellowing of the leaf to interveinal chlorosis, to stunted growth that reduces yield. The objective of this analysis was to employ single nucleotide polymorphism (SNP)-based genome-wide association mapping to uncover genomic regions associated with IDC tolerance. Two populations [2005 (n = 143) and 2006 (n = 141)] were evaluated in replicated, multilocation IDC trials. After controlling for population structure and individual relatedness, and selecting statistical models that minimized false positives, 42 and 88 loci, with minor allele frequency >10%, were significant in 2005 and 2006, respectively. The loci accounted for 74.5% of the phenotypic variation in IDC in2005 and 93.8% of the variation in 2006. Nine loci from seven genomic locations were significant in both years. These loci accounted for 43.7% of the variation in 2005 and 47.6% in 2006. A number of the loci discovered here mapped at or near previously discovered IDC quantitative trait loci (QTL). A total of 15 genes known to be involved in iron metabolism mapped in the vicinity (<500 kb) of significant markers in one or both populations.
The genome sequence of the woodland strawberry (Fragaria vesca L.) is an important resource providing a reference for comparative genomics studies and future sequenced rosaceous species and has great utility as a model for the development of markers for mapping in the cultivated strawberry Fragaria ×ananassa Duchesne ex Rozier. A set of 152 microsatellite simple sequence repeat (SSR) primer pairs was developed and mapped, along with 42 previously published but unmapped SSRs, permitting the precise assignment of 28.2 Mbp of previously unanchored genome sequence scaffolds (13% of the F. vesca genome sequence). The original ordering of F. vesca sequence scaffolds was performed without a physical map, using predominantly SSR markers to order scaffolds via anchoring to a comprehensive linkage map. This report complements and expands resolution of the Fragaria spp. reference map and refines the scaffold ordering of the F. vesca genome sequence using newly devised tools. The results of this study provide two significant resources: (i) the concurrent validation of a substantial set of SSRs associated with these previously unmapped regions of the Fragaria spp. genome and (ii) the precise placement of previously orphaned genomic sequence. Together, these resources improve the resolution and completeness of the strawberry genome sequence, making it a better resource for downstream studies in Fragaria spp. and the family Rosaceae.
Genome research on oat (Avena sativa L.) has received less attention than wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) because it is a less prominent component of the human food system. To assess the potential of the model grass Brachypodium distachyon (L) P. Beauv. as a surrogate for oat genome research, the whole genome sequence (WGS) of B. distachyon was employed for comparative analysis with oat genetic linkage maps. Sequences of mapped molecular markers from one diploid Avena spp. and two hexaploid oat maps were aligned to the B. distachyon WGS to infer syntenic relationships. Diploid Avena and B. distachyon exhibit a high degree of synteny with 18 syntenic blocks covering 87% of the oat genome, which permitted postulation of an ancestral Avena spp. chromosome structure. Synteny between oat and B. distachyon was also prevalent, with 50 syntenic blocks covering 76.6% of the ‘Kanota’ × ‘Ogle’ linkage map. Coalignment of diploid and hexaploid maps to B. distachyon helped resolve homeologous relationships between different oat linkage groups but also revealed many major rearrangements in oat subgenomes. Extending the analysis to a second oat linkage map (Ogle × ‘TAM O-301’) allowed identification of several putative homologous linkage groups across the two oat populations. These results indicate that the B. distachyon genome sequence will be a useful resource to assist genetics and genomics research in oat. The analytical strategy employed here should be applicable for genome research in other temperate grass crops with modest amounts of genomic data.
Transcriptome sequencing is a powerful method for studying global expression patterns in large, complex genomes. Evaluation of sequence-based expression profiles during reproductive development would provide functional annotation to genes underlying agronomic traits. We generated transcriptome profiles for 12 diverse maize (Zea mays L.) reproductive tissues representing male, female, developing seed, and leaf tissues using high throughput transcriptome sequencing. Overall, ∼80% of annotated genes were expressed. Comparative analysis between sequence and hybridization-based methods demonstrated the utility of ribonucleic acid sequencing (RNA-seq) for expression determination and differentiation of paralagous genes (∼85% of maize genes). Analysis of 4975 gene families across reproductive tissues revealed expression divergence is proportional to family size. In all pairwise comparisons between tissues, 7 (pre- vs. postemergence cobs) to 48% (pollen vs. ovule) of genes were differentially expressed. Genes with expression restricted to a single tissue within this study were identified with the highest numbers observed in leaves, endosperm, and pollen. Coexpression network analysis identified 17 gene modules with complex and shared expression patterns containing many previously described maize genes. The data and analyses in this study provide valuable tools through improved gene annotation, gene family characterization, and a core set of candidate genes to further characterize maize reproductive development and improve grain yield potential.
Expressed sequence tags (ESTs) have proven useful for gene discovery in many crops. In this work, our objective was to construct complementary DNA (cDNA) libraries from root tissues of common beans (Phaseolus vulgaris L.) grown under low and high P hydroponic conditions and to conduct EST sequencing and comparative analyses of the libraries. Expressed sequence tag analysis of 3648 clones identified 2372 unigenes, of which 1591 were annotated as known genes while a total of 465 unigenes were not associated with any known gene. Unigenes with hits were categorized according to biological processes, molecular function, and cellular compartmentalization. Given the young tissue used to make the root libraries, genes for catalytic activity and binding were highly expressed. Comparisons with previous root EST sequencing and between the two libraries made here resulted in a set of genes to study further for differential gene expression and adaptation to low P, such as a 14 kDa praline-rich protein, a metallopeptidase, tonoplast intrinsic protein, adenosine triphosphate (ATP) citrate synthase, and cell proliferation genes expressed in the low P treated plants. Given that common beans are often grown on acid soils of the tropics and subtropics that are usually low in P these genes and the two parallel libraries will be useful for selection for better uptake of this essential macronutrient. The importance of EST generation for common bean root tissues under low P and other abiotic soil stresses is also discussed.
Next-generation DNA sequencing (NGS) technologies can survey sequence variation on a genome-wide scale, but their utility for crop genetic diversity analysis is poorly known. Many challenges remain in their applications, including sampling complex genomes, identifying single nucleotide polymorphisms (SNPs), and analyzing missing data. This study presented a practical application of the Roche 454 GS FLX Titanium technology in combination with genomic reduction and an advanced bioinformatics tool to analyze the genetic relationships of 16 diverse barley (Hordeum vulgare L.) landraces. A full 454 run generated roughly 1.7 million sequence reads with a total length of 612 Mbp. Application of the computational pipeline called DIAL (de novo identification of alleles) identified 2578 contigs and 3980 SNPs. Sanger sequencing of four barley samples confirmed 85 of the 100 selected contigs and 288 of the 620 putative SNPs and identified 735 new SNPs and 39 new indels. Several diversity analyses revealed the eastern and western division in the barley samples. The division is compatible with those inferred with 156 microsatellite alleles of the same 16 samples and consistent with our current knowledge about cultivated barley. These results help to illustrate the utility of NGS technologies for crop diversity studies. The NGS application also provides a new informative set of genomic resources for barley research.
Recent advances in high-throughput genotyping have made it easier to combine information from different mapping populations into consensus genetic maps, which provide increased marker density and genome coverage compared to individual maps. Previously, a single nucleotide polymorphism (SNP)-based genotyping platform was developed and used to genotype 373 individuals in four barley (Hordeum vulgare L.) mapping populations. This led to a 2943 SNP consensus genetic map with 975 unique positions. In this work, we add data from six additional populations and more individuals from one of the original populations to develop an improved consensus map from 1133 individuals. A stringent and systematic analysis of each of the 10 populations was performed to achieve uniformity. This involved reexamination of the four populations included in the previous map. As a consequence, we present a robust consensus genetic map that contains 2994 SNP loci mapped to 1163 unique positions. The map spans 1137.3 cM with an average density of one marker bin per 0.99 cM. A novel application of the genotyping platform for gene detection allowed the assignment of 2930 genes to flow-sorted chromosomes or arms, confirmed the position of 2545 SNP-mapped loci, added chromosome or arm allocations to an additional 370 SNP loci, and delineated pericentromeric regions for chromosomes 2H to 7H. Marker order has been improved and map resolution has been increased by almost 20%. These increased precision outcomes enable more optimized SNP selection for marker-assisted breeding and support association genetic analysis and map-based cloning. It will also improve the anchoring of DNA sequence scaffolds and the barley physical map to the genetic map.
Many important traits in plant breeding are polygenic and therefore recalcitrant to traditional marker-assisted selection. Genomic selection addresses this complexity by including all markers in the prediction model. A key method for the genomic prediction of breeding values is ridge regression (RR), which is equivalent to best linear unbiased prediction (BLUP) when the genetic covariance between lines is proportional to their similarity in genotype space. This additive model can be broadened to include epistatic effects by using other kernels, such as the Gaussian, which represent inner products in a complex feature space. To facilitate the use of RR and nonadditive kernels in plant breeding, a new software package for R called rrBLUP has been developed. At its core is a fast maximum-likelihood algorithm for mixed models with a single variance component besides the residual error, which allows for efficient prediction with unreplicated training data. Use of the rrBLUP software is demonstrated through several examples, including the identification of optimal crosses based on superior progeny value. In cross-validation tests, the prediction accuracy with nonadditive kernels was significantly higher than RR for wheat (Triticum aestivum L.) grain yield but equivalent for several maize (Zea mays L.) traits.
Malting quality comprises one of the most economically relevant set of traits in barley (Hordeum vulgare L.). It is a complex phenotype, expensive and difficult to measure, that would benefit from a marker-assisted selection strategy. Malting quality is a target of the U.S. Barley Coordinated Agricultural Project (CAP) and development of winter habit malting barley varieties is a key objective of the U.S. barley research community. The objective of this work was to detect quantitative trait loci (QTL) for malting quality traits in a winter breeding program that is a component of the U.S. Barley CAP. We studied the association between five malting quality traits and 3072 single nucleotide polymorphisms (SNPs) from the barley oligonucleotide pool assay (BOPA) 1 and 2, assayed in advanced inbred lines from the Oregon State University (OSU) breeding program from three germplasm arrays (CAP I, CAP II, and CAP III). After comparing 16 models we selected a structured association model with posterior probabilities inferred from software STRUCTURE (QK) approach to use on all germplasm arrays. Most of the marker-trait associations are germplasm- and environment-specific and close to previously mapped genes and QTL relevant for malt and beer quality. We found alleles fixed by random genetic drift, novel unmasked alleles, and genetic-background interaction. In a relatively small population size study we provide strong evidence for detecting true QTL.
Cytoplasmic male sterility (CMS) is a maternally inherited inability to produce functional pollen. In Texas (T)-cytoplasm maize (Zea mays L.), CMS results from the action of the URF13 mitochondrial pore-forming protein encoded by the unique T-urf13 mitochondrial gene. Full or partial restoration of fertility to T-cytoplasm maize is mediated by the Rf2a nuclear gene in combination with one of three other genes: Rf1, Rf8, or Rf*. Rf2a encodes a mitochondrial aldehyde dehydrogenase whereas Rf1, Rf8, and Rf* are associated with the accumulation of distinctive T-urf13 mitochondrial transcripts. Rf8-associated RNA processing activity was mapped to a 4.55-Mbp region on chromosome 2L that contains 10 pentatricopeptide repeat (PPR) encoding genes in the B73 5b.60 genome assembly. Genetic linkage analysis also indicated that Rf* is positioned within this PPR cluster as well as Rf3, which restores USDA (S)-cytoplasm maize. Partially male-fertile plants segregated for the presence or absence of the Rf8-associated T-urf13 1.42- and 0.42-kbp transcripts, indicating that the RNA processing event associated with these transcripts is not necessary for anther exsertion. In addition, a statistically significant delay in flowering was observed between partially male-fertile and mostly male-fertile plants. Taken together, these new results indicate that Rf8-mediated male fertility is under the control of more than one nuclear locus.
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