Annotation of Cultivar Variations at the Multigeneic Rhg1/Rfs2 Locus: Polymorphisms Underling AlteraAnnotation of Cultivar Variations at the Multigeneic Rhg1/Rfs2 Locus: Polymorphisms Underling Alterations of Root Development and Pest Resistancetions of Root Development and Pest Resistance

Soybean (Glycine max (L.) Merr.) suffers yield loss due to root infection from soil infestation by Heterodera glycine I. (soybean cyst nematode SCN) and Fusarium virguliforme (Aoki; sudden death syndrome (SDS)). The major locus for SCN and SDS resistance has previously been identified as Rhg1/Rfs2 (chr18; LG G) (site reference). The objective of this experiment was to compare the Sanger DNA sequence of a resistant cultivar (‘Forrest’) and two susceptible cultivars (‘Williams 82’ and ‘Asgrow A3244’). Sequences were downloaded from GenBank for Williams 82, Phytzome for A3244 and a newly sequenced BAC-B73P06 (82,157 bp) encompassing the Rfs2/Rhg1 locus. Using the resistant cultivars, 800 single nucleotide polymorphisms (SNPs) and 57 indels were identified. In contrast, the susceptible cultivars had just 12 SNPs and no indels between them. Polymorphisms were clustered within 59 kbp, divided into three sections. There were 5 predicted recombination breakpoints. The third and fourth breakpoints were located before gene 3 and after gene 5 (Glyma18g02680; the RLK at Rhg1/Rfs2) which were therefore inferred to be derived from Peking, within the Rhg1/Rfs2 region. Comparisons of SNPs identified in Illumina sequences from 31 semi-domesticated genomes showed 80% of the total SNPs in Forrest were found among the genomes. Annotation and gene prediction showed the BAC gene prediction encoded 9-10 genes. There were 31 SNPs within exons and 137 among introns. Just 11 SNPs caused amino acid changes. There were 5 SNPs in cis regulatory elements (CREs) and 14 in promoters. Polymorphisms indicated the regions that were introgressed from Peking had defined limits. Proteins across the region were highly conserved compared to non-coding regions, suggesting purifying selection occurred

Characterization of the FAD2 Gene Family in Soybean Reveals the Limitations of Gel-Based TILLING in Genes with High Copy Number

Soybean seed oil typically contains 18–20% oleic acid. Increasing the content of oleic acid is beneficial for health and biodiesel production. Mutations in FAD2-1 genes have been reported to increase seed oleic acid content. A subset of 1,037 mutant families from a mutagenized soybean cultivar (cv.) Forrest population was screened using reverse genetics (TILLING) to identify mutations within FAD2 genes. Although no fad2 mutants were identified using gel-based TILLING, four fad2-1A and one fad2-1B mutants were identified to have high seed oleic acid content using forward genetic screening and subsequent target sequencing. TILLING has been successfully used as a non-transgenic reverse genetic approach to identify mutations in genes controlling important agronomic traits. However, this technique presents limitations in traits such as oil composition due to gene copy number and similarities within the soybean genome. In soybean, FAD2 are present as two copies, FAD2-1 and FAD2-2. Two FAD2-1 members: FAD2-1A and FAD2-1B; and three FAD2-2 members: FAD2-2A, FAD2-2B, and FAD2-2C have been reported. Syntenic, phylogenetic, and in silico analysis revealed two additional members constituting the FAD2 gene family: GmFAD2-2D and GmFAD2-2E, located on chromosomes 09 and 15, respectively. They are presumed to have diverged from other FAD2-2 members localized on chromosomes 19 (GmFAD2-2A and GmFAD2-2B) and 03 (GmFAD2-2C). This work discusses alternative solutions to the limitations of gel-based TILLING in functional genomics due to high copy number and multiple paralogs of the FAD2 gene family in soybean

In silico comparison of transcript abundances during Arabidopsis thaliana and Glycine max resistance to Fusarium virguliforme

<p>Abstract</p> <p>Background</p> <p>Sudden death syndrome (SDS) of soybean (<it>Glycine max </it>L. Merr.) is an economically important disease, caused by the semi-biotrophic fungus <it>Fusarium solani </it>f. sp. <it>glycines</it>, recently renamed <it>Fusarium virguliforme </it>(Fv). Due to the complexity and length of the soybean-Fusarium interaction, the molecular mechanisms underlying plant resistance and susceptibility to the pathogen are not fully understood. <it>F. virguliforme </it>has a very wide host range for the ability to cause root rot and a very narrow host range for the ability to cause a leaf scorch. <it>Arabidopsis thaliana </it>is a host for many types of phytopathogens including bacteria, fungi, viruses and nematodes. Deciphering the variations among transcript abundances (TAs) of functional orthologous genes of soybean and <it>A. thaliana </it>involved in the interaction will provide insights into plant resistance to <it>F. viguliforme</it>.</p> <p>Results</p> <p>In this study, we reported the analyses of microarrays measuring TA in whole plants after <it>A. thaliana </it>cv 'Columbia' was challenged with fungal pathogen <it>F. virguliforme</it>. Infection caused significant variations in TAs. The total number of increased transcripts was nearly four times more than that of decreased transcripts in abundance. A putative resistance pathway involved in responding to the pathogen infection in <it>A. thaliana </it>was identified and compared to that reported in soybean.</p> <p>Conclusion</p> <p>Microarray experiments allow the interrogation of tens of thousands of transcripts simultaneously and thus, the identification of plant pathways is likely to be involved in plant resistance to Fusarial pathogens. Dissection of the set functional orthologous genes between soybean and <it>A. thaliana </it>enabled a broad view of the functional relationships and molecular interactions among plant genes involved in <it>F. virguliforme </it>resistance.</p

Genome reorganization of the GmSHMT gene family in soybean showed a lack of functional redundancy in resistance to soybean cyst nematode

In soybeans, eighteen members constitute the serine hydroxymethyltransferase (GmSHMT) gene family, of which the cytosolic-targeted GmSHMT08c member has been reported to mediate resistance to soybean cyst nematode (SCN). This work presents a comprehensive study of the SHMT gene family members, including synteny, phylogeny, subcellular localizations, haplotypes, protein homology modeling, mutational, and expression analyses. Phylogenetic analysis showed that SHMT genes are divided into four classes refecting their subcellular distribution (cytosol, nucleus, mitochondrion, and chloroplast). Subcellular localization of selected GmSHMT members supports their in-silico predictions and phylogenetic distribution. Expression and functional analyses showed that GmSHMT genes display many overlapping, but some divergent responses during SCN infection. Furthermore, mutational analysis reveals that all isolated EMS mutants that lose their resistance to SCN carry missense and nonsense mutations at the GmSHMT08c, but none of the Gmshmt08c mutants carried mutations in the other GmSHMT genes. Haplotype clustering analysis using the whole genome resequencing data from a collection of 106 diverse soybean germplams (15X) was performed to identify allelic variants and haplotypes within the GmSHMT gene family. Interestingly, only the cytosolic-localized GmSHMT08c presented SNP clusters that were associated with SCN resistance, supporting our mutational analysis. Although eight GmSHMT members respond to the nematode infestation, functional and mutational analysis has shown the absence of functional redundancy in resistance to SCN. Structural analysis and protein homology modeling showed the presence of spontaneous mutations at important residues within the GmSHMT proteins, suggesting the presence of altered enzyme activities based on substrate afnities. Due to the accumulation of mutations during the evolution of the soybean genome, the other GmSHMT members have undergone neofunctionalization and subfunctionalization events

Characterization of the Soluble NSF Attachment Protein gene family identifies two members involved in additive resistance to a plant pathogen

Proteins with Tetratricopeptide-repeat (TPR) domains are encoded by large gene families and distributed in all plant lineages. This study aims to characterize a subfamily of TPR containing proteins named Soluble NSF-Attachment Protein (GmSNAP), of which GmSNAP18 has been reported to mediate resistance to soybean cyst nematode (SCN). This study uses a population of recombinant inbred lines from resistant and susceptible parents to analyse SNAP gene family divergence over time. Five members constitute the soybean SNAP gene family: GmSNAP18, GmSNAP11, GmSNAP14, GmSNAP02, and GmSNAP09. Phylogenetic analysis of genes from 22 diverse plant species showed that SNAP genes were distributed in six monophyletic clades corresponding to the different plant lineages. SNAP genes were duplicated and derived from a common ancestor and unique gene still present in chlorophytic algae. This hypothesis is supported by the conservation of the four TPR motifs in all species, including ancestral lineages. Syntenic analysis of regions harbouring GmSNAP genes reveals that this family arose from segmental and tandem duplications following a tetraploidization event. qRT-PCR analysis of GmSNAP genes indicates a co-regulation following SCN infection. Genetic analysis demonstrates that GmSNAP11 contributes to an additive resistance to SCN. Thus, GmSNAP11 was identified as a novel minor gene conferring resistance to SCN

Genetic Analysis of Relative Water Content (RWC) in Two Recombinant Inbred Line Populations of Soybean [Glycine max (L.) Merr.]

Drought affects soybean [Glycine max (L.) Merr.] and other crops productivity in the US and other parts of the world. Relative water content (RWC) is an important indicator for plant water deficit tolerance (WDT). The objective of this study is to map quantitative trait loci (QTL) for RWC and several other leaf traits such as leaf dry weight (LDW), leaf fresh weight (LFW), and leaf turgid weight (LTW) in two soybean recombinant inbred line (RIL) populations, one derived from a cross of ‘Essex’ and ‘Forrest’ (ExF, n=94) and the other is derived from a cross of ‘PI 438489B’ and ‘Hamilton’ (PIxH, n=50). In the PIxH RIL population, eight QTL were identified and mapped on 6 different linkage groups (LGs) of the soybean genome. No QTL for LFW were identified in this population. In the ExF RIL population, 10 QTL were identified and mapped on 5 different LGs of soybean. Chromosome 18 (LG G) contains clusters of QTL for LFW, LTW, and RWC in the ExF RIL population. This same chromosome contains a QTL for RWC in the PIxH RIL population. The QTL found here are important to be included in breeding programs for soybean water deficit tolerance (WDT)

Quantitative Trait Loci Underlying Seed Sugars Content in “MD96-5722” by “Spencer” Recombinant Inbred Line Population of Soybean

Sucrose, raffinose, and stachyose are important soluble sugars in soybean [Glycine max (L.) Merr.] seeds. Seed sucrose is a desirable trait for taste and flavor. Raffinose and stachyose are undesirable in diets of monogastric animals, acting as anti-nutritional factors that cause flatulence and abdominal discomfort. Therefore, reducing raffinose and stachyose biosynthesis is considered as a key quality trait goal in soy food and feed industries. The objective of this study was to identify genomic regions containing quantitative trait loci (QTL) controlling sucrose, raffinose, and stachyose in a set of 92 F5:7 recombinant inbred lines (RILs) derived from a cross between the lines “MD96- 5722” and “Spencer” by using 5376 Single Nucleotide Polymorphism (SNP) markers from the Illumina Infinium SoySNP6K BeadChip array. Fourteen significant QTL were identified and mapped on eight different linkage groups (LGs) and chromosomes (Chr). Three QTL for seed sucrose content were identified on LGs N (Chr3), K (Chr9), and E (Chr15). Seven QTL were identified for raffinose content on LGs D1a (Chr1), N (Chr3), C2 (Chr6), K (Chr9), B2 (Chr14), and J (Chr16). Four QTL for stachyose content were identified on LG D1a (Chr1), C2 (Chr6), H (Chr12), and B2 (Chr14). Selection for beneficial alleles of these QTLs could facilitate breeding strategies to develop soybean lines with higher concentrations of sucrose and lower levels of raffinose and stachyose

Identification of Quantitative Trait Loci (QTL) Underlying Protein, Oil, and Five Major Fatty Acids’ Contents in Soybean

Improved seed composition in soybean [Glycine max (L.) Merr.] for protein and oil quality is one of the major goals of soybean breeders. A group of genes that act as quantitative traits with their effects can alter protein, oil, palmitic, stearic, oleic, linoleic, and linolenic acids percentage in soybean seeds. The objective of this study was to identify Quantitative Trait Loci (QTL) controlling protein, oil, and fatty acids content in a set of F5:8 RILs de-rived from a cross between lines, ‘MD 96-5722’ and ‘Spencer’ using 5376 Single Nucleotide Polymorphism (SNP) markers from the Illumina Infinium SoySNP6K BeadChip array. QTL analysis used WinQTL Cart 2.5 software for composite interval mapping (CIM). Identified, were; one protein content QTL on linkage group (LG-) B2 or chromosome (Chr_) 14; 11 QTL associated with oil content on six linkage groups LG-N (Chr_3), LG-A1 (Chr_5), LG-K (Chr_9), LG-F (Chr_13), LG-B2 (Chr_14), and LG-J (Chr_16); and sixteen QTL for five major fatty acids (palmitic, stearic, oleic, linoleic, and linolenic acids) on LG-N (Chr_3), LG-F (Chr_13), LG-B2 (Chr_14), LG-E (Chr_15), LG-J (Chr_16), and LG-G (Chr_18). The SNP markers closely linked to the QTL reported here will be useful for development of cultivars with altered oil and fatty acid compositions in soybean breeding programs

Genetic Analysis of Root and Shoot Traits in the ‘Essex’ By ‘Forrest’ Recombinant Inbred Line (RIL) Population of Soybean [Glycine max (L.) Merr.]

Crop productivity is severely reduced by water deficit and drought in many plant species including soybean. Improved root and shoot traits can contribute to drought tolerance ability of the plant. This research was conducted to identify QTL that underlie several root and shoot traits in the ‘Essex’ by ‘Forrest’ (ExF RILs, n=94) recombinant inbred line (RIL) soybean population. Field collected samples were used for gathering phenotypic data of basal root thickness (BRT), lateral root number (LRN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW), shoot fresh weight (SFW), shoot dry weight (SDW), and calculating RFW/SFW, and RDW/SDW ratios. All traits and ratios were compared against DNA markers using the composite interval mapping (CIM). A total of 12 QTL: 3 for MRL, 1 QTL for LRN, 1 QTL for BRT, 2 QTL for RFW, 2 QTL for RDW, 4 QTL for SFW, 3 QTL for SDW, and 3 QTL for SFW/SDW were identified and mapped on different linkage groups (LGs) A2, B2, C2, D1a, F, G, and N. The LOD scores of these QTL ranged from 2.5 to 6.0. No QTL were associated with RFW/RDW. The root and shoot trait QTL of this study may benefit breeding programs for producing cultivars tolerant to water deficit and high yield. Preliminary analyses of genes the QTL regions using GO annotation gave insight into genes that may underlie some of these QTLs

Quantitative Trait Loci Associated with Foliar Trigonelline Accumulation in Glycine Max L

The objective of this study was to utilize a Glycine max RIL population to (1) evaluate foliar trigonelline (TRG) content in field-grown soybean, (2) determine the heritability of TRG accumulation, and (3) identify DNA markers linked to quantitative trait loci (QTLs) conditioning variation in TRG accumulation. Frequency distributions of 70 recombinant inbred lines showed statistically no significant departure from normality (P > .05) for TRG accumulation measured at pod development stage (R4). Six different molecular linkage groups (LGs) (B2, C2, D2, G, J, and K) were identified to be linked to QTLs for foliar TRG accumulation. Two unique microsatellite markers (SSR) on two different linkage groups identified QTL significantly associated with foliar TRG accumulation: a region on LG J (Satt285) (P = .0019, R(2) = 15.9%) and a second region on LG C2 (Satt079) (P = .0029, R(2) = 13.4%)