Identification and characterization of transcript polymorphisms in soybean lines varying in oil composition and content

Abstract

BackgroundVariation in seed oil composition and content among soybean varieties is largely attributed to differences in transcript sequences and/or transcript accumulation of oil production related genes in seeds. Discovery and analysis of sequence and expression variations in these genes will accelerate soybean oil quality improvement.ResultsIn an effort to identify these variations, we sequenced the transcriptomes of soybean seeds from nine lines varying in oil composition and/or total oil content. Our results showed that 69,338 distinct transcripts from 32,885 annotated genes were expressed in seeds. A total of 8,037 transcript expression polymorphisms and 50,485 transcript sequence polymorphisms (48,792 SNPs and 1,693 small Indels) were identified among the lines. Effects of the transcript polymorphisms on their encoded protein sequences and functions were predicted. The studies also provided independent evidence that the lack of FAD2-1A gene activity and a non-synonymous SNP in the coding sequence of FAB2C caused elevated oleic acid and stearic acid levels in soybean lines M23 and FAM94-41, respectively.ConclusionsAs a proof-of-concept, we developed an integrated RNA-seq and bioinformatics approach to identify and functionally annotate transcript polymorphisms, and demonstrated its high effectiveness for discovery of genetic and transcript variations that result in altered oil quality traits. The collection of transcript polymorphisms coupled with their predicted functional effects will be a valuable asset for further discovery of genes, gene variants, and functional markers to improve soybean oil quality.

Transcript Polymorphism Rates in Soybean Seed Tissue Are Increased in a Single Transformant ofGlycine max

“…Less common changes occurred in the first or second bases of the codon, generating a nonsynonymous or missense mutation likely resulting in an amino acid change (Figures 2(e)–2(h)). Missense to silent ratios detected in all experimental groups appear to be higher than previously published results for soybean indicated [40], although the higher nonsynonymous to synonymous mutations may be due to high linkage disequilibrium exhibited in soy [41]. …”

“…Base changes for wild type, ST77, and ST111 events were all comparable, while the 764 event consistently reported SNP rates nearly double that of the other groups (1 SNP detected every ~22,000 bases), which is still well below the previously reported SNP rate of 1 SNP per ~1,400 nucleotides in soybean seeds [40]. Nevertheless, SNP base changes appeared to follow the same pattern of commonality, with all groups demonstrating high percentages of transition base changes with relatively low transversion counts.…”

Integrating GWAS and gene expression data for functional characterization of resistance to white mould in soya bean

“…The quality of total RNA was determined using RiboGreen â RNA Assay Kit. Libraries were constructed and sequenced by MOGENE (Saint Louis, MO), and their sequencing reads were analysed as described by (Goettel et al, 2014). Tophat v2.0.1 (Trapnell et al, 2009) was run on each of the samples using the Williams 82 a2 v1 reference genome and transcriptome annotation from Phytozome v10 to guide the alignments.…”

Whole genome-wide transcript profiling to identify differentially expressed genes associated with seed field emergence in two soybean low phytate mutants

“…The great achievements in soybean genomics have led to application of large-scale gene expression analysis at both mRNA and protein levels to uncover the features of soybean traits. For instance, 69,338 distinct transcripts from 32,885 annotated genes were expressed in soybean seeds which from nine lines varying in oil composition and total oil content [21]. Until now, little is known about the mechanisms responsible for the low seed germination rates in soybean LPA mutants.…”