Flavonoids are involved in phosphorus-deficiency-induced cluster-root formation in white lupin.

BACKGROUND AND AIMS: Initiation of cluster roots in white lupin (Lupinus albus) under phosphorus (P) deficiency requires auxin signalling, whereas flavonoids inhibit auxin transport. However, little information is available about the interactions between P deficiency and flavonoids in terms of cluster-root formation in white lupin. METHODS: Hydroponic and aeroponic systems were used to investigate the role of flavonoids in cluster-root formation, with or without 75 µm P supply. KEY RESULTS: Phosphorus-deficiency-induced flavonoid accumulation in cluster roots depended on developmental stage, based on in situ determination of fluorescence of flavonoids and flavonoid concentration. LaCHS8, which codes for a chalcone synthase isoform, was highly expressed in cluster roots, and silencing LaCHS8 reduced flavonoid production and rootlet density. Exogenous flavonoids suppressed cluster-root formation. Tissue-specific distribution of flavonoids in roots was altered by P deficiency, suggesting that P deficiency induced flavonoid accumulation, thus fine-tuning the effect of flavonoids on cluster-root formation. Furthermore, naringenin inhibited expression of an auxin-responsive DR5:GUS marker, suggesting an interaction of flavonoids and auxin in regulating cluster-root formation. CONCLUSIONS: Phosphorus deficiency triggered cluster-root formation through the regulation of flavonoid distribution, which fine-tuned an auxin response in the early stages of cluster-root development. These findings provide valuable insights into the mechanisms of cluster-root formation under P deficiency.

Fast neutron-induced structural rearrangements at a soybean NAP1 locus result in gnarled trichomes.

KEY MESSAGE: Three adjacent and distinct sequence rearrangements were identified at a NAP1 locus in a soybean mutant. Genetic dissection and validation revealed the function of this gene in soybean trichome development. A soybean (Glycine max (L.) Merr.) gnarled trichome mutant, exhibiting stunted trichomes compared to wild-type, was identified in a fast neutron mutant population. Genetic mapping using whole genome sequencing-based bulked segregant analysis identified a 26.6 megabase interval on chromosome 20 that co-segregated with the phenotype. Comparative genomic hybridization analysis of the mutant indicated that the chromosome 20 interval included a small structural variant within the coding region of a soybean ortholog (Glyma.20G019300) of Arabidopsis Nck-Associated Protein 1 (NAP1), a regulator of actin nucleation during trichome morphogenesis. Sequence analysis of the candidate allele revealed multiple rearrangements within the coding region, including two deletions (approximately 1-2 kb each), a translocation, and an inversion. Further analyses revealed that the mutant allele perfectly co-segregated with the phenotype, and a wild-type soybean NAP1 transgene functionally complemented an Arabidopsis nap1 mutant. In addition, mapping and exon sequencing of NAP1 in a spontaneous soybean gnarled trichome mutant (T31) identified a frame shift mutation resulting in a truncation of the coding region. These data indicate that the soybean NAP1 gene is essential for proper trichome development and show the utility of the soybean fast neutron population for forward genetic approaches for identifying genes.

The Medicago sativa gene index 1.2: a web-accessible gene expression atlas for investigating expression differences between Medicago sativa subspecies.

BACKGROUND: Alfalfa (Medicago sativa L.) is the primary forage legume crop species in the United States and plays essential economic and ecological roles in agricultural systems across the country. Modern alfalfa is the result of hybridization between tetraploid M. sativa ssp. sativa and M. sativa ssp. falcata. Due to its large and complex genome, there are few genomic resources available for alfalfa improvement. RESULTS: A de novo transcriptome assembly from two alfalfa subspecies, M. sativa ssp. sativa (B47) and M. sativa ssp. falcata (F56) was developed using Illumina RNA-seq technology. Transcripts from roots, nitrogen-fixing root nodules, leaves, flowers, elongating stem internodes, and post-elongation stem internodes were assembled into the Medicago sativa Gene Index 1.2 (MSGI 1.2) representing 112,626 unique transcript sequences. Nodule-specific and transcripts involved in cell wall biosynthesis were identified. Statistical analyses identified 20,447 transcripts differentially expressed between the two subspecies. Pair-wise comparisons of each tissue combination identified 58,932 sequences differentially expressed in B47 and 69,143 sequences differentially expressed in F56. Comparing transcript abundance in floral tissues of B47 and F56 identified expression differences in sequences involved in anthocyanin and carotenoid synthesis, which determine flower pigmentation. Single nucleotide polymorphisms (SNPs) unique to each M. sativa subspecies (110,241) were identified. CONCLUSIONS: The Medicago sativa Gene Index 1.2 increases the expressed sequence data available for alfalfa by ninefold and can be expanded as additional experiments are performed. The MSGI 1.2 transcriptome sequences, annotations, expression profiles, and SNPs were assembled into the Alfalfa Gene Index and Expression Database (AGED) at http://plantgrn.noble.org/AGED/ , a publicly available genomic resource for alfalfa improvement and legume research.

Transgene silencing of sucrose synthase in alfalfa (Medicago sativa L.) stem vascular tissue suggests a role for invertase in cell wall cellulose synthesis.

BACKGROUND: Alfalfa (Medicago sativa L.) is a widely adapted perennial forage crop that has high biomass production potential. Enhanced cellulose content in alfalfa stems would increase the value of the crop as a bioenergy feedstock. We examined if increased expression of sucrose synthase (SUS; EC 2.4.1.13) would increase cellulose in stem cell walls. RESULTS: Alfalfa plants were transformed with a truncated alfalfa phosphoenolpyruvate carboxylase gene promoter (PEPC7-P4) fused to an alfalfa nodule-enhanced SUS cDNA (MsSUS1) or the ß-glucuronidase (GUS) gene. Strong GUS expression was detected in xylem and phloem indicating that the PEPC7-P4 promoter was active in stem vascular tissue. In contrast to expectations, MsSUS1 transcript accumulation was reduced 75-90 % in alfalfa plants containing the PEPC7-P4::MsSUS1 transgene compared to controls. Enzyme assays indicated that SUS activity in stems of selected down-regulated transformants was reduced by greater than 95 % compared to the controls. Although SUS activity was detected in xylem and phloem of control plants by in situ enzyme assays, plants with the PEPC7-P4::MsSUS1 transgene lacked detectable SUS activity in post-elongation stem (PES) internodes and had very low SUS activity in elongating stem (ES) internodes. Loss of SUS protein in PES internodes of down-regulated lines was confirmed by immunoblots. Down-regulation of SUS expression and activity in stem tissue resulted in no obvious phenotype or significant change in cell wall sugar composition. However, alkaline/neutral (A/N) invertase activity increased in SUS down-regulated lines and high levels of acid invertase activity were observed. In situ enzyme assays of stem tissue showed localization of neutral invertase in vascular tissues of ES and PES internodes. CONCLUSIONS: These results suggest that invertases play a primary role in providing glucose for cellulose biosynthesis or compensate for the loss of SUS1 activity in stem vascular tissue.

Biodegradation of atrazine by three transgenic grasses and alfalfa expressing a modified bacterial atrazine chlorohydrolase gene.

The widespread use of atrazine and other s-triazine herbicides to control weeds in agricultural production fields has impacted surface and groundwater in the United States and elsewhere. We previously reported the cloning, sequencing, and expression of six genes involved in the atrazine biodegradation pathway of Pseudomonas sp. strain ADP, which is initiated by atzA, encoding atrazine chlorohydrolase. Here we explored the use of enhanced expression of a modified bacterial atrazine chlorohydrolase, p-AtzA, in transgenic grasses (tall fescue, perennial ryegrass, and switchgrass) and the legume alfalfa for the biodegradation of atrazine. Enhanced expression of p-AtzA was obtained by using combinations of the badnavirus promoter, the maize alcohol dehydrogenase first intron, and the maize ubiquitin promoter. For alfalfa, we used the first intron of the 5'-untranslated region tobacco alcohol dehydrogenase gene and the cassava vein mosaic virus promoter. Resistance of plants to atrazine in agar-based and hydroponic growth assays was correlated with in vivo levels of gene expression and atrazine degradation. The in planta expression of p-atzA enabled transgenic tall fescue to transform atrazine into hydroxyatrazine and other metabolites. Results of our studies highlight the potential use of transgenic plants for bioremediating atrazine in the environment.

An RNA-Seq based gene expression atlas of the common bean.

BACKGROUND: Common bean (Phaseolus vulgaris) is grown throughout the world and comprises roughly 50% of the grain legumes consumed worldwide. Despite this, genetic resources for common beans have been lacking. Next generation sequencing, has facilitated our investigation of the gene expression profiles associated with biologically important traits in common bean. An increased understanding of gene expression in common bean will improve our understanding of gene expression patterns in other legume species. RESULTS: Combining recently developed genomic resources for Phaseolus vulgaris, including predicted gene calls, with RNA-Seq technology, we measured the gene expression patterns from 24 samples collected from seven tissues at developmentally important stages and from three nitrogen treatments. Gene expression patterns throughout the plant were analyzed to better understand changes due to nodulation, seed development, and nitrogen utilization. We have identified 11,010 genes differentially expressed with a fold change ≥ 2 and a P-value < 0.05 between different tissues at the same time point, 15,752 genes differentially expressed within a tissue due to changes in development, and 2,315 genes expressed only in a single tissue. These analyses identified 2,970 genes with expression patterns that appear to be directly dependent on the source of available nitrogen. Finally, we have assembled this data in a publicly available database, The Phaseolus vulgaris Gene Expression Atlas (Pv GEA), http://plantgrn.noble.org/PvGEA/ . Using the website, researchers can query gene expression profiles of their gene of interest, search for genes expressed in different tissues, or download the dataset in a tabular form. CONCLUSIONS: These data provide the basis for a gene expression atlas, which will facilitate functional genomic studies in common bean. Analysis of this dataset has identified genes important in regulating seed composition and has increased our understanding of nodulation and impact of the nitrogen source on assimilation and distribution throughout the plant.

An RNA-Seq transcriptome analysis of orthophosphate-deficient white lupin reveals novel insights into phosphorus acclimation in plants.

Phosphorus, in its orthophosphate form (P(i)), is one of the most limiting macronutrients in soils for plant growth and development. However, the whole-genome molecular mechanisms contributing to plant acclimation to P(i) deficiency remain largely unknown. White lupin (Lupinus albus) has evolved unique adaptations for growth in P(i)-deficient soils, including the development of cluster roots to increase root surface area. In this study, we utilized RNA-Seq technology to assess global gene expression in white lupin cluster roots, normal roots, and leaves in response to P(i) supply. We de novo assembled 277,224,180 Illumina reads from 12 complementary DNA libraries to build what is to our knowledge the first white lupin gene index (LAGI 1.0). This index contains 125,821 unique sequences with an average length of 1,155 bp. Of these sequences, 50,734 were transcriptionally active (reads per kilobase per million reads ≥ 3), representing approximately 7.8% of the white lupin genome, using the predicted genome size of Lupinus angustifolius as a reference. We identified a total of 2,128 sequences differentially expressed in response to P(i) deficiency with a 2-fold or greater change and P ≤ 0.05. Twelve sequences were consistently differentially expressed due to P(i) deficiency stress in three species, Arabidopsis (Arabidopsis thaliana), potato (Solanum tuberosum), and white lupin, making them ideal candidates to monitor the P(i) status of plants. Additionally, classic physiological experiments were coupled with RNA-Seq data to examine the role of cytokinin and gibberellic acid in P(i) deficiency-induced cluster root development. This global gene expression analysis provides new insights into the biochemical and molecular mechanisms involved in the acclimation to P(i) deficiency.

Interactions between light intensity and phosphorus nutrition affect the phosphate-mining capacity of white lupin (Lupinus albus L.).

Light intensity affects photosynthetic carbon (C) fixation and the supply of carbon to roots. To evaluate interactions between carbon supply and phosphorus (P) supply, effects of light intensity on sucrose accumulation, root growth, cluster root formation, carboxylate exudation, and P uptake capacity were studied in white lupin (Lupinus albus L.) grown hydroponically with either 200 µmol m(-2) s(-1) or 600 µmol m(-2) s(-1) light and a sufficient (50 µM P) or deficient (1 µM P) P supply. Plant biomass and root:shoot ratio increased with increasing light intensity, particularly when plants were supplied with sufficient P. Both low P supply and increasing light intensity increased the production of cluster roots and citrate exudation. Transcripts of a phosphoenol pyruvate carboxylase gene (LaPEPC3) in cluster roots (which is related to the exudation of citrate), transcripts of a phosphate transporter gene (LaPT1), and P uptake all increased with increasing light intensity, under both P-sufficient and P-deficient conditions. Across all four experimental treatments, increased cluster root formation and carboxylate exudation were associated with lower P concentration in the shoot and greater sucrose concentration in the roots. It is suggested that C in excess of shoot growth capabilities is translocated to the roots as sucrose, which serves as both a nutritional signal and a C-substrate for carboxylate exudation and cluster root formation.

Legume genomics: understanding biology through DNA and RNA sequencing.

BACKGROUND: The legume family (Leguminosae) consists of approx. 17 000 species. A few of these species, including, but not limited to, Phaseolus vulgaris, Cicer arietinum and Cajanus cajan, are important dietary components, providing protein for approx. 300 million people worldwide. Additional species, including soybean (Glycine max) and alfalfa (Medicago sativa), are important crops utilized mainly in animal feed. In addition, legumes are important contributors to biological nitrogen, forming symbiotic relationships with rhizobia to fix atmospheric N2 and providing up to 30 % of available nitrogen for the next season of crops. The application of high-throughput genomic technologies including genome sequencing projects, genome re-sequencing (DNA-seq) and transcriptome sequencing (RNA-seq) by the legume research community has provided major insights into genome evolution, genomic architecture and domestication. SCOPE AND CONCLUSIONS: This review presents an overview of the current state of legume genomics and explores the role that next-generation sequencing technologies play in advancing legume genomics. The adoption of next-generation sequencing and implementation of associated bioinformatic tools has allowed researchers to turn each species of interest into their own model organism. To illustrate the power of next-generation sequencing, an in-depth overview of the transcriptomes of both soybean and white lupin (Lupinus albus) is provided. The soybean transcriptome focuses on analysing seed development in two near-isogenic lines, examining the role of transporters, oil biosynthesis and nitrogen utilization. The white lupin transcriptome analysis examines how phosphate deficiency alters gene expression patterns, inducing the formation of cluster roots. Such studies illustrate the power of next-generation sequencing and bioinformatic analyses in elucidating the gene networks underlying biological processes.

White lupin cluster root acclimation to phosphorus deficiency and root hair development involve unique glycerophosphodiester phosphodiesterases.

White lupin (Lupinus albus) is a legume that is very efficient in accessing unavailable phosphorus (Pi). It develops short, densely clustered tertiary lateral roots (cluster/proteoid roots) in response to Pi limitation. In this report, we characterize two glycerophosphodiester phosphodiesterase (GPX-PDE) genes (GPX-PDE1 and GPX-PDE2) from white lupin and propose a role for these two GPX-PDEs in root hair growth and development and in a Pi stress-induced phospholipid degradation pathway in cluster roots. Both GPX-PDE1 and GPX-PDE2 are highly expressed in Pi-deficient cluster roots, particularly in root hairs, epidermal cells, and vascular bundles. Expression of both genes is a function of both Pi availability and photosynthate. GPX-PDE1 Pi deficiency-induced expression is attenuated as photosynthate is deprived, while that of GPX-PDE2 is strikingly enhanced. Yeast complementation assays and in vitro enzyme assays revealed that GPX-PDE1 shows catalytic activity with glycerophosphocholine while GPX-PDE2 shows highest activity with glycerophosphoinositol. Cell-free protein extracts from Pi-deficient cluster roots display GPX-PDE enzyme activity for both glycerophosphocholine and glycerophosphoinositol. Knockdown of expression of GPX-PDE through RNA interference resulted in impaired root hair development and density. We propose that white lupin GPX-PDE1 and GPX-PDE2 are involved in the acclimation to Pi limitation by enhancing glycerophosphodiester degradation and mediating root hair development.

The composition and origins of genomic variation among individuals of the soybean reference cultivar Williams 82.

Soybean (Glycine max) is a self-pollinating species that has relatively low nucleotide polymorphism rates compared with other crop species. Despite the low rate of nucleotide polymorphisms, a wide range of heritable phenotypic variation exists. There is even evidence for heritable phenotypic variation among individuals within some cultivars. Williams 82, the soybean cultivar used to produce the reference genome sequence, was derived from backcrossing a Phytophthora root rot resistance locus from the donor parent Kingwa into the recurrent parent Williams. To explore the genetic basis of intracultivar variation, we investigated the nucleotide, structural, and gene content variation of different Williams 82 individuals. Williams 82 individuals exhibited variation in the number and size of introgressed Kingwa loci. In these regions of genomic heterogeneity, the reference Williams 82 genome sequence consists of a mosaic of Williams and Kingwa haplotypes. Genomic structural variation between Williams and Kingwa was maintained between the Williams 82 individuals within the regions of heterogeneity. Additionally, the regions of heterogeneity exhibited gene content differences between Williams 82 individuals. These findings show that genetic heterogeneity in Williams 82 primarily originated from the differential segregation of polymorphic chromosomal regions following the backcross and single-seed descent generations of the breeding process. We conclude that soybean haplotypes can possess a high rate of structural and gene content variation, and the impact of intracultivar genetic heterogeneity may be significant. This detailed characterization will be useful for interpreting soybean genomic data sets and highlights important considerations for research communities that are developing or utilizing a reference genome sequence.

Phenotypic and genomic analyses of a fast neutron mutant population resource in soybean.

Mutagenized populations have become indispensable resources for introducing variation and studying gene function in plant genomics research. In this study, fast neutron (FN) radiation was used to induce deletion mutations in the soybean (Glycine max) genome. Approximately 120,000 soybean seeds were exposed to FN radiation doses of up to 32 Gray units to develop over 23,000 independent M2 lines. Here, we demonstrate the utility of this population for phenotypic screening and associated genomic characterization of striking and agronomically important traits. Plant variation was cataloged for seed composition, maturity, morphology, pigmentation, and nodulation traits. Mutants that showed significant increases or decreases in seed protein and oil content across multiple generations and environments were identified. The application of comparative genomic hybridization (CGH) to lesion-induced mutants for deletion mapping was validated on a midoleate x-ray mutant, M23, with a known FAD2-1A (for fatty acid desaturase) gene deletion. Using CGH, a subset of mutants was characterized, revealing deletion regions and candidate genes associated with phenotypes of interest. Exome resequencing and sequencing of PCR products confirmed FN-induced deletions detected by CGH. Beyond characterization of soybean FN mutants, this study demonstrates the utility of CGH, exome sequence capture, and next-generation sequencing approaches for analyses of mutant plant genomes. We present this FN mutant soybean population as a valuable public resource for future genetic screens and functional genomics research.

Using RNA-Seq for gene identification, polymorphism detection and transcript profiling in two alfalfa genotypes with divergent cell wall composition in stems.

BACKGROUND: Alfalfa, [Medicago sativa (L.) sativa], a widely-grown perennial forage has potential for development as a cellulosic ethanol feedstock. However, the genomics of alfalfa, a non-model species, is still in its infancy. The recent advent of RNA-Seq, a massively parallel sequencing method for transcriptome analysis, provides an opportunity to expand the identification of alfalfa genes and polymorphisms, and conduct in-depth transcript profiling. RESULTS: Cell walls in stems of alfalfa genotype 708 have higher cellulose and lower lignin concentrations compared to cell walls in stems of genotype 773. Using the Illumina GA-II platform, a total of 198,861,304 expression sequence tags (ESTs, 76 bp in length) were generated from cDNA libraries derived from elongating stem (ES) and post-elongation stem (PES) internodes of 708 and 773. In addition, 341,984 ESTs were generated from ES and PES internodes of genotype 773 using the GS FLX Titanium platform. The first alfalfa (Medicago sativa) gene index (MSGI 1.0) was assembled using the Sanger ESTs available from GenBank, the GS FLX Titanium EST sequences, and the de novo assembled Illumina sequences. MSGI 1.0 contains 124,025 unique sequences including 22,729 tentative consensus sequences (TCs), 22,315 singletons and 78,981 pseudo-singletons. We identified a total of 1,294 simple sequence repeats (SSR) among the sequences in MSGI 1.0. In addition, a total of 10,826 single nucleotide polymorphisms (SNPs) were predicted between the two genotypes. Out of 55 SNPs randomly selected for experimental validation, 47 (85%) were polymorphic between the two genotypes. We also identified numerous allelic variations within each genotype. Digital gene expression analysis identified numerous candidate genes that may play a role in stem development as well as candidate genes that may contribute to the differences in cell wall composition in stems of the two genotypes. CONCLUSIONS: Our results demonstrate that RNA-Seq can be successfully used for gene identification, polymorphism detection and transcript profiling in alfalfa, a non-model, allogamous, autotetraploid species. The alfalfa gene index assembled in this study, and the SNPs, SSRs and candidate genes identified can be used to improve alfalfa as a forage crop and cellulosic feedstock.

An integrative approach to genomic introgression mapping.

Near-isogenic lines (NILs) are valuable genetic resources for many crop species, including soybean (Glycine max). The development of new molecular platforms promises to accelerate the mapping of genetic introgressions in these materials. Here, we compare some existing and emerging methodologies for genetic introgression mapping: single-feature polymorphism analysis, Illumina GoldenGate single nucleotide polymorphism (SNP) genotyping, and de novo SNP discovery via RNA-Seq analysis of next-generation sequence data. We used these methods to map the introgressed regions in an iron-inefficient soybean NIL and found that the three mapping approaches are complementary when utilized in combination. The comparative RNA-Seq approach offers several additional advantages, including the greatest mapping resolution, marker depth, and de novo marker utility for downstream fine-mapping analysis. We applied the comparative RNA-Seq method to map genetic introgressions in an additional pair of NILs exhibiting differential seed protein content. Furthermore, we attempted to optimize the comparative RNA-Seq approach by assessing the impact of sequence depth, SNP identification methodology, and post hoc analyses on SNP discovery rates. We conclude that the comparative RNA-Seq approach can be optimized with sufficient sampling and by utilizing a post hoc correction accounting for gene density variation that controls for false discoveries.

Gene expression patterns are correlated with genomic and genic structure in soybean.

Studies have indicated that exon and intron size and intergenic distance are correlated with gene expression levels and expression breadth. Previous reports on these correlations in plants and animals have been conflicting. In this study, next-generation sequence data, which has been shown to be more sensitive than previous expression profiling technologies, were generated and analyzed from 14 tissues. Our results revealed a novel dichotomy. At the low expression level, an increase in expression breadth correlated with an increase in transcript size because of an increase in the number of exons and introns. No significant changes in intron or exon sizes were noted. Conversely, genes expressed at the intermediate to high expression levels displayed a decrease in transcript size as their expression breadth increased. This was due to smaller exons, with no significant change in the number of exons. Taking advantage of the known gene space of soybean, we evaluated the positioning of genes and found significant clustering of similarly expressed genes. Identifying the correlations between the physical parameters of individual genes could lead to uncovering the role of regulation owing to nucleotide composition, which might have potential impacts in discerning the role of the noncoding regions.

Transcript profiling of two alfalfa genotypes with contrasting cell wall composition in stems using a cross-species platform: optimizing analysis by masking biased probes.

BACKGROUND: The GeneChip(R) Medicago Genome Array, developed for Medicago truncatula, is a suitable platform for transcript profiling in tetraploid alfalfa [Medicago sativa (L.) subsp. sativa]. However, previous research involving cross-species hybridization (CSH) has shown that sequence variation between two species can bias transcript profiling by decreasing sensitivity (number of expressed genes detected) and the accuracy of measuring fold-differences in gene expression. RESULTS: Transcript profiling using the Medicago GeneChip(R) was conducted with elongating stem (ES) and post-elongation stem (PES) internodes from alfalfa genotypes 252 and 1283 that differ in stem cell wall concentrations of cellulose and lignin. A protocol was developed that masked probes targeting inter-species variable (ISV) regions of alfalfa transcripts. A probe signal intensity threshold was selected that optimized both sensitivity and accuracy. After masking for both ISV regions and previously identified single-feature polymorphisms (SFPs), the number of differentially expressed genes between the two genotypes in both ES and PES internodes was approximately 2-fold greater than the number detected prior to masking. Regulatory genes, including transcription factor and receptor kinase genes that may play a role in development of secondary xylem, were significantly over-represented among genes up-regulated in 252 PES internodes compared to 1283 PES internodes. Several cell wall-related genes were also up-regulated in genotype 252 PES internodes. Real-time quantitative RT-PCR of differentially expressed regulatory and cell wall-related genes demonstrated increased sensitivity and accuracy after masking for both ISV regions and SFPs. Over 1,000 genes that were differentially expressed in ES and PES internodes of genotypes 252 and 1283 were mapped onto putative orthologous loci on M. truncatula chromosomes. Clustering simulation analysis of the differentially expressed genes suggested co-expression of some neighbouring genes on Medicago chromosomes. CONCLUSIONS: The problems associated with transcript profiling in alfalfa stems using the Medicago GeneChip as a CSH platform were mitigated by masking probes targeting ISV regions and SFPs. Using this masking protocol resulted in the identification of numerous candidate genes that may contribute to differences in cell wall concentration and composition of stems of two alfalfa genotypes.

Transcript profiling of common bean (Phaseolus vulgaris L.) using the GeneChip Soybean Genome Array: optimizing analysis by masking biased probes.

BACKGROUND: Common bean (Phaseolus vulgaris L.) and soybean (Glycine max) both belong to the Phaseoleae tribe and share significant coding sequence homology. This suggests that the GeneChip(R) Soybean Genome Array (soybean GeneChip) may be used for gene expression studies using common bean. RESULTS: To evaluate the utility of the soybean GeneChip for transcript profiling of common bean, we hybridized cRNAs purified from nodule, leaf, and root of common bean and soybean in triplicate to the soybean GeneChip. Initial data analysis showed a decreased sensitivity and accuracy of measuring differential gene expression in common bean cross-species hybridization (CSH) GeneChip data compared to that of soybean. We employed a method that masked putative probes targeting inter-species variable (ISV) regions between common bean and soybean. A masking signal intensity threshold was selected that optimized both sensitivity and accuracy of measuring differential gene expression. After masking for ISV regions, the number of differentially-expressed genes identified in common bean was increased by 2.8-fold reflecting increased sensitivity. Quantitative RT-PCR (qRT-PCR) analysis of 20 randomly selected genes and purine-ureide pathway genes demonstrated an increased accuracy of measuring differential gene expression after masking for ISV regions. We also evaluated masked probe frequency per probe set to gain insight into the sequence divergence pattern between common bean and soybean. The sequence divergence pattern analysis suggested that the genes for basic cellular functions and metabolism were highly conserved between soybean and common bean. Additionally, our results show that some classes of genes, particularly those associated with environmental adaptation, are highly divergent. CONCLUSIONS: The soybean GeneChip is a suitable cross-species platform for transcript profiling in common bean when used in combination with the masking protocol described. In addition to transcript profiling, CSH of the GeneChip in combination with masking probes in the ISV regions can be used for comparative ecological and/or evolutionary genomics studies.

RNA-Seq Atlas of Glycine max: a guide to the soybean transcriptome.

BACKGROUND: Next generation sequencing is transforming our understanding of transcriptomes. It can determine the expression level of transcripts with a dynamic range of over six orders of magnitude from multiple tissues, developmental stages or conditions. Patterns of gene expression provide insight into functions of genes with unknown annotation. RESULTS: The RNA Seq-Atlas presented here provides a record of high-resolution gene expression in a set of fourteen diverse tissues. Hierarchical clustering of transcriptional profiles for these tissues suggests three clades with similar profiles: aerial, underground and seed tissues. We also investigate the relationship between gene structure and gene expression and find a correlation between gene length and expression. Additionally, we find dramatic tissue-specific gene expression of both the most highly-expressed genes and the genes specific to legumes in seed development and nodule tissues. Analysis of the gene expression profiles of over 2,000 genes with preferential gene expression in seed suggests there are more than 177 genes with functional roles that are involved in the economically important seed filling process. Finally, the Seq-atlas also provides a means of evaluating existing gene model annotations for the Glycine max genome. CONCLUSIONS: This RNA-Seq atlas extends the analyses of previous gene expression atlases performed using Affymetrix GeneChip technology and provides an example of new methods to accommodate the increase in transcriptome data obtained from next generation sequencing. Data contained within this RNA-Seq atlas of Glycine max can be explored at http://www.soybase.org/soyseq.

Complementary genetic and genomic approaches help characterize the linkage group I seed protein QTL in soybean.

BACKGROUND: The nutritional and economic value of many crops is effectively a function of seed protein and oil content. Insight into the genetic and molecular control mechanisms involved in the deposition of these constituents in the developing seed is needed to guide crop improvement. A quantitative trait locus (QTL) on Linkage Group I (LG I) of soybean (Glycine max (L.) Merrill) has a striking effect on seed protein content. RESULTS: A soybean near-isogenic line (NIL) pair contrasting in seed protein and differing in an introgressed genomic segment containing the LG I protein QTL was used as a resource to demarcate the QTL region and to study variation in transcript abundance in developing seed. The LG I QTL region was delineated to less than 8.4 Mbp of genomic sequence on chromosome 20. Using Affymetrix Soy GeneChip and high-throughput Illumina whole transcriptome sequencing platforms, 13 genes displaying significant seed transcript accumulation differences between NILs were identified that mapped to the 8.4 Mbp LG I protein QTL region. CONCLUSIONS: This study identifies gene candidates at the LG I protein QTL for potential involvement in the regulation of protein content in the soybean seed. The results demonstrate the power of complementary approaches to characterize contrasting NILs and provide genome-wide transcriptome insight towards understanding seed biology and the soybean genome.

MicroRNA expression profile in common bean (Phaseolus vulgaris) under nutrient deficiency stresses and manganese toxicity.

*MicroRNAs (miRNAs) play a pivotal role in post-transcriptional regulation of gene expression in plants. Information on miRNAs in legumes is as yet scarce. This work investigates miRNAs in an agronomically important legume, common bean (Phaseolus vulgaris). *A hybridization approach employing miRNA macroarrays - printed with oligonucleotides complementary to 68 known miRNAs - was used to detect miRNAs in the leaves, roots and nodules of control and nutrient-stressed (phosphorus, nitrogen, or iron deficiency; acidic pH; and manganese toxicity) common bean plants. *Thirty-three miRNAs were expressed in control plants and another five were only expressed under stress conditions. The miRNA expression ratios (stress:control) were evaluated using principal component and hierarchical cluster analyses. A group of miRNAs responded to nearly all stresses in the three organs analyzed. Other miRNAs showed organ-specific responses. Most of the nodule-responsive miRNAs showed up-regulation. miRNA blot expression analysis confirmed the macroarray results. Novel miRNA target genes were proposed for common bean and the expression of selected targets was evaluated by quantitative reverse transcriptase-polymerase chain reaction. *In addition to the detection of previously reported stress-responsive miRNAs, we discovered novel common bean stress-responsive miRNAs, for manganese toxicity. Our data provide a foundation for evaluating the individual roles of miRNAs in common bean.