Gene-allele system of shade tolerance in southern China soybean germplasm revealed by genome-wide association study using gene-allele sequence as markers.

KEY MESSAGE: Fifty-three shade tolerance genes with 281 alleles in the SCSGP were identified directly using gene-allele sequence as markers in RTM GWAS, from which optimized crosses, evolutionary motivators, and gene-allele networks were explored. Shade tolerance is a key for optimal cultivation of soybean inter/relay-cropped with corn. To explore the shade tolerance gene-allele system in the southern China soybean germplasm, we proposed using gene-allele sequence markers (GASMs) in a restricted two-stage multi-locus model genome-wide association study (GASM-RTM-GWAS). A representative sample with 394 accessions was tested for their shade tolerance index (STI), in Nanning, China. Through whole-genome re-sequencing, 47,586 GASMs were assembled. From GASM-RTM-GWAS, 53 main-effect STI genes with 281 alleles (2-13 alleles/gene) (totally 63 genes with 308 alleles, including 38 G × E genes with 191 alleles) were identified and then organized into a gene-allele matrix composed of eight submatrices corresponding to geo-seasonal subpopulations. The population featured mild STI changes (1.69 → 1.56-1.82) and mild gene-allele changes (92.5% alleles inherited, 0% alleles excluded, 7.5% alleles emerged) from the primitive (SAIII) to the derived seven subpopulations, but large transgressive recombination potentials and optimal crosses were predicted. The 63 STI genes were annotated into six biological categories (metabolic process, catalytic activity, response to stresses, transcription and translation, signal transduction and transport and unknown functions), interacted as gene networks. From the STI gene-allele system, 38 important alleles of 22 genes were nominated for further in-depth study. GASM-RTM-GWAS performed powerful and efficient in germplasm population genetic study comparing to other procedures through facilitating direct and thorough identification of its gene-allele system, from which genome-wide breeding by design could be achieved, and evolutionary motivators and gene-allele networks could be explored.

Methylome and transcriptome analyses of soybean response to bean pyralid larvae.

BACKGROUND: Bean pyralid is one of the major leaf-feeding insects that affect soybean crops. DNA methylation can control the networks of gene expressions, and it plays an important role in responses to biotic stress. However, at present the genome-wide DNA methylation profile of the soybean resistance to bean pyralid has not been reported so far. RESULTS: Using whole-genome bisulfite sequencing (WGBS) and RNA-sequencing (RNA-seq), we analyzed the highly resistant material (Gantai-2-2, HRK) and highly susceptible material (Wan82-178, HSK), under bean pyralid larvae feeding 0 h and 48 h, to clarify the molecular mechanism of the soybean resistance and explore its insect-resistant genes. We identified 2194, 6872, 39,704 and 40,018 differentially methylated regions (DMRs), as well as 497, 1594, 9596 and 9554 differentially methylated genes (DMGs) in the HRK0/HRK48, HSK0/HSK48, HSK0/HRK0 and HSK48/HRK48 comparisons, respectively. Through the analysis of global methylation and transcription, 265 differentially expressed genes (DEGs) were negatively correlated with DMGs, there were 34, 49, 141 and 116 negatively correlated genes in the HRK0/HRK48, HSK0/HSK48, HSK0/HRK0 and HSK48/HRK48, respectively. The MapMan cluster analysis showed that 114 negatively correlated genes were clustered in 24 pathways, such as protein biosynthesis and modification; primary metabolism; secondary metabolism; cell cycle, cell structure and component; RNA biosynthesis and processing, and so on. Moreover, CRK40; CRK62; STK; MAPK9; L-type lectin-domain containing receptor kinase VIII.2; CesA; CSI1; fimbrin-1; KIN-14B; KIN-14 N; KIN-4A; cytochrome P450 81E8; BEE1; ERF; bHLH25; bHLH79; GATA26, were likely regulatory genes involved in the soybean responses to bean pyralid larvae. Finally, 5 DMRs were further validated that the genome-wide DNA data were reliable through PS-PCR and 5 DEGs were confirmed the relationship between DNA methylation and gene expression by qRT-PCR. The results showed an excellent agreement with deep sequencing. CONCLUSIONS: Genome-wide DNA methylation profile of soybean response to bean pyralid was obtained for the first time. Several specific DMGs which participated in protein kinase, cell and organelle, flavonoid biosynthesis and transcription factor were further identified to be likely associated with soybean response to bean pyralid. Our data will provide better understanding of DNA methylation alteration and their potential role in soybean insect resistance.

Determination of the MiRNAs Related to Bean Pyralid Larvae Resistance in Soybean Using Small RNA and Transcriptome Sequencing.

Soybean is one of the most important oil crops in the world. Bean pyralid is a major leaf-feeding insect of soybean. In order to screen out the functional genes and regulatory pathways related to the resistance for bean pyralid larvae, the small RNA and transcriptome sequencing were performed based on the highly resistant material (Gantai-2-2) and highly susceptible material (Wan 82-178) of soybean. The results showed that, when comparing 48 h feeding with 0 h feeding, 55 differentially expressed miRNAs were identified in Gantai-2-2 and 58 differentially expressed miRNAs were identified in Wan82-178. When comparing Gantai-2-2 with Wan82-178, 77 differentially expressed miRNAs were identified at 0 h feeding, and 70 differentially expressed miRNAs were identified at 48 h feeding. The pathway analysis of the predicted target genes revealed that the plant hormone signal transduction, RNA transport, protein processing in the endoplasmic reticulum, zeatin biosynthesis, ubiquinone and other terpenoid-quinone biosynthesis, and isoquinoline alkaloid biosynthesis may play important roles in soybean's defense against the stress caused by bean pyralid larvae. According to conjoint analysis of the miRNA/mRNA, a total of 20 differentially expressed miRNAs were negatively correlated with 26 differentially expressed target genes. The qRT-PCR analysis verified that the small RNA sequencing results were credible. According to the analyses of the differentially expressed miRNAs, we speculated that miRNAs are more likely to play key roles in the resistance to insects. Gma-miR156q, Gma-miR166u, Gma-miR166b, Gma-miR166j-3p, Gma-miR319d, Gma-miR394a-3p, Gma-miR396e, and so on-as well as their negatively regulated differentially expressed target genes-may be involved in the regulation of soybean resistance to bean pyralid larvae. These results laid a foundation for further in-depth research regarding the action mechanisms of insect resistance.

Comparative transcriptome analysis of soybean response to bean pyralid larvae.

BACKGROUND: Soybean is one of most important oilseed crop worldwide, however, its production is often limited by many insect pests. Bean pyralid is one of the major soybean leaf-feeding insects in China. To explore the defense mechanisms of soybean resistance to bean pyralid, the comparative transcriptome sequencing was completed between the leaves infested with bean pyralid larvae and no worm of soybean (Gantai-2-2 and Wan82-178) on the Illumina HiSeq™ 2000 platform. RESULTS: In total, we identified 1744 differentially expressed genes (DEGs) in the leaves of Gantai-2-2 (1064) and Wan82-178 (680) fed by bean pyralid for 48 h, compared to 0 h. Interestingly, 315 DEGs were shared by Gantai-2-2 and Wan82-178, while 749 and 365 DEGs specifically identified in Gantai-2-2 and Wan82-178, respectively. When comparing Gantai-2-2 with Wan82-178, 605 DEGs were identified at 0 h feeding, and 468 DEGs were identified at 48 h feeding. Gene Ontology (GO) annotation analysis revealed that the DEGs were mainly involved in the metabolic process, single-organism process, cellular process, responses to stimulus, catalytic activities and binding. Pathway analysis showed that most of the DEGs were associated with the plant-pathogen interaction, phenylpropanoid biosynthesis, phenylalanine metabolism, flavonoid biosynthesis, peroxisome, plant hormone signal transduction, terpenoid backbone biosynthesis, and so on. Finally, we used qRT-PCR to validate the expression patterns of several genes and the results showed an excellent agreement with deep sequencing. CONCLUSIONS: According to the comparative transcriptome analysis results and related literature reports, we concluded that the response to bean pyralid feeding might be related to the disturbed functions and metabolism pathways of some key DEGs, such as DEGs involved in the ROS removal system, plant hormone metabolism, intracellular signal transduction pathways, secondary metabolism, transcription factors, biotic and abiotic stresses. We speculated that these genes may have played an important role in synthesizing substances to resist insect attacks in soybean. Our results provide a valuable resource of soybean defense genes that will benefit other studies in this field.

Proteomic analysis by iTRAQ-MRM of soybean resistance to Lamprosema Indicate.

BACKGROUND: Lamprosema indicate is a major leaf feeding insect pest to soybean, which has caused serious yield losses in central and southern China. To explore the defense mechanisms of soybean resistance to Lamprosema indicate, a highly resistant line (Gantai-2-2) and a highly susceptible line (Wan 82-178) were exposed to Lamprosema indicate larval feedings for 0 h and 48 h, and the differential proteomic analyses of these two lines were carried out. RESULTS: The results showed that 31 differentially expressed proteins (DEPs) were identified in the Gantai-2-2 when comparing 48 h feeding with 0 h feeding, and 53 DEPs were identified in the Wan 82-178. 28 DEPs were identified when comparing Gantai-2-2 with Wan 82-178 at 0 h feeding. The bioinformatic analysis results showed that most of the DEPs were associated with ribosome, linoleic acid metabolism, flavonoid biosynthesis, phenylpropanoid biosynthesis, peroxisome, stilbenoid, diarylheptanoid and gingerol biosynthesis, glutathione metabolism, pant hormone signal transduction, and flavone and flavonol biosynthesis, as well as other resistance related metabolic pathways. The MRM analysis showed that the iTRAQ results were reliable. CONCLUSIONS: According to the analysis of the DEPs results, the soybean defended or resisted the Lamprosema indicate damage by the induction of a synthesis of anti-digestive proteins which inhibit the growth and development of insects, reactive oxygen species scavenging, signaling pathways, secondary metabolites synthesis, and so on.

Potential of marker selection to increase prediction accuracy of genomic selection in soybean (Glycine max L.).

Genomic selection is a promising molecular breeding strategy enhancing genetic gain per unit time. The objectives of our study were to (1) explore the prediction accuracy of genomic selection for plant height and yield per plant in soybean [Glycine max (L.) Merr.], (2) discuss the relationship between prediction accuracy and numbers of markers, and (3) evaluate the effect of marker preselection based on different methods on the prediction accuracy. Our study is based on a population of 235 soybean varieties which were evaluated for plant height and yield per plant at multiple locations and genotyped by 5361 single nucleotide polymorphism markers. We applied ridge regression best linear unbiased prediction coupled with fivefold cross-validations and evaluated three strategies of marker preselection. For plant height, marker density and marker preselection procedure impacted prediction accuracy only marginally. In contrast, for grain yield, prediction accuracy based on markers selected with a haplotype block analyses-based approach increased by approximately 4 % compared with random or equidistant marker sampling. Thus, applying marker preselection based on haplotype blocks is an interesting option for a cost-efficient implementation of genomic selection for grain yield in soybean breeding.

Identification of two blackleg resistance genes and fine mapping of one of these two genes in a Brassica napus canola cultivar 'Surpass 400'.

Blackleg resistant cultivars have been developed through conventional breeding methods and are successfully used globally to control this disease in canola production. To clone blackleg resistance genes and to understand the mechanism underlying the resistance, a blackleg resistant canola cultivar 'Surpass 400' was used to develop a gene mapping population. A previously reported high density genetic map was used to find a resistance gene region that corresponded to linkage group N10 in B. napus. Differential interactions between the resistant lines and a pathogen isolate were discovered with two resistance genes BLMR1 and BLMR2 identified through linkage analysis of five genome-specific molecular markers. BLMR1 provides resistance through the hypersensitive response that protects inoculated cotyledons from becoming infected, Unlike BLMR1, BLMR2 slows down the development of individual infection loci. BLMR1 and BLMR2 segregated independently in two large F(3)BC(2) populations. Fine mapping of BLMR1 was performed with 12 genome-specific molecular markers. The closest marker with a genetic distance of 0.13 cM to BLMR1 was identified, which lays a solid foundation for cloning BLMR1.

High throughput genome-specific and gene-specific molecular markers for erucic acid genes in Brassica napus (L.) for marker-assisted selection in plant breeding.

A single base change in the Bn-FAE1.1 gene in the A genome and a two-base deletion in the Bn-FAE1.2 gene in the C genome produce the nearly zero content of erucic acid observed in canola. A BAC clone anchoring Bn-FAE1.1 from a B. rapa BAC library and a BAC clone anchoring Bn-FAE1.2 from a B. oleracea BAC library were used in this research. After sequencing the gene flanking regions, it was found that the dissimilarity of the flanking sequences of these two FAE1 homologs facilitated the design of genome-specific primers that could amplify the corresponding genome in allotetraploid B. napus. The two-base deletion in the C genome gene was detected as a sequence-characterized amplified region (SCAR) marker. To increase the throughput, one genome-specific primer was labeled with four fluorescence dyes and combined with 20 different primers to produce PCR products with different fragment sizes. Eventually, a super pool of 80 samples was detected simultaneously. This dramatically reduces the cost of marker detection. The single base change in the Bn-FAE1.1 gene was detected as single nucleotide polymorphic (SNP) marker with an ABI SNaPshot kit. A multiplexing primer set was designed by adding a polyT to the 5' primer end to increase SNP detection throughput through sample pooling. Furthermore, the Bn-FAE1.1 and Bn-FAE1.2 were integrated into the N8 and N13 linkage groups of our previously reported high-density sequence-related amplified polymorphism (SRAP) map, respectively. There were 124 SRAP markers in a N8 bin in which the Bn-FAE1.1 gene-specific SCAR marker was located and 46 SRAP markers in a N13 bin into which the Bn-FAE1.2 SNP marker was integrated. These three kinds of high throughput molecular markers have been successfully implemented in our canola/rapeseed breeding programs.

An ultradense genetic recombination map for Brassica napus, consisting of 13551 SRAP markers.

Sequence related amplified polymorphism (SRAP) was used to construct an ultradense genetic recombination map for a doubled haploid (DH) population in B. napus. A total of 1,634 primer combinations including 12 fluorescently labeled primers and 442 unlabeled ones produced 13,551 mapped SRAP markers. All these SRAPs were assembled in 1,055 bins that were placed onto 19 linkage groups. Ten of the nineteen linkage groups were assigned to the A genome and the remaining nine to the C genome on the basis of the differential SRAP PCR amplification in two DH lines of B. rapa and B. oleracea. Furthermore, all 19 linkage groups were assigned to their corresponding N1-N19 groups of B. napus by comparison with 55 SSR markers used to construct previous maps in this species. In total, 1,663 crossovers were detected, resulting in a map length span of 1604.8 cM. The marker density is 8.45 SRAPs per cM, and there could be more than one marker in 100 kb physical distance. There are four linkage groups in the A genome with more than 800 SRAP markers each, and three linkage groups in the C genome with more 1,000 SRAP markers each. Our studies suggest that a single SRAP map might be applicable to the three Brassica species, B. napus, B. oleracea and B. rapa. The use of this ultra high-density genetic recombination map in marker development and map-based gene cloning is discussed.