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

Bolon, Yung–Tsi; Joseph, Bindu; Cannon, Steven B.; Graham, Michelle A.; Diers, Brian W.; Farmer, Andrew; May, Gregory D.; Muehlbauer, Gary J.; Specht, James E.; Tu, Zheng Jin; Weeks, Nathan T.; Xu, Wayne; Shoemaker, Randy C.; Vance, Carroll P.

doi:10.1186/1471-2229-10-41

Cited by 104 publications

(110 citation statements)

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“…The remaining SNPs in each experiment were randomly scattered across the genome. Our method was able to easily identify the well-known introgressed region on chromosome 20 (Nichols et al, 2006;Bolon et al, 2010). It also identified regions on chromosome 16 and chromosome 18 that were previously unknown (Fig.…”

Section: Application Of the Advanced Ngs Introgression Mapping On A Smentioning

confidence: 95%

“…The two NILs, derived by introgressing Glycine soja into a soybean background (see "Materials and Methods"), exhibit differential seed protein content (Nichols et al, 2006;Bolon et al, 2010). In this case, we were interested in identifying differential introgression patterns between the two lines; therefore, the RNA-Seq SNP comparison was performed directly between HiPro and LoPro, rather than between the NILs and the soybean recurrent parent.…”

Section: Application Of the Advanced Ngs Introgression Mapping On A Smentioning

confidence: 99%

“…More recently, automated genotyping technologies have accelerated the efficiency of genetic mapping. Such methods, including single feature polymorphisms (SFP) analysis of microarray data and single nucleotide polymorphism (SNP)-based genotyping methods, have been successfully applied to the mapping of soybean NILs and other mapping populations (Hyten et al, 2008;Kaczorowski et al, 2008;Bolon et al, 2010). However, the mapping resolution of all of these platforms is limited by the location and depth of informative markers available for a given species.…”

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An Integrative Approach to Genomic Introgression Mapping

Severin

Peiffer

et al. 2010

Plant Physiology

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(C.P.V., R.M.S.)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.

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Section: Application Of the Advanced Ngs Introgression Mapping On A Smentioning

confidence: 95%

Section: Application Of the Advanced Ngs Introgression Mapping On A Smentioning

confidence: 99%

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confidence: 99%

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An Integrative Approach to Genomic Introgression Mapping

Severin

Peiffer

et al. 2010

Plant Physiology

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“…A single QTL explaining 65% of the variation in protein content was mapped on the linkage group by Sebolt, Shoemaker, & Diers, (2000) and other QTLs were mapped in the same genomic region by Nichols, Lgover, Carlson, Specht & Diers (2006);Bolon, Joseph, Cannon, Graham, Diers, Farmer, May, Muehlbauer, Specht, Tu, Weeks, Xu, Shoemaker & Vance (2010);and Rodrigues, Miranda, Borges, Silva, Good-God, Piovesan, Barros, Cruz & Moreira (2010). In addition, this analysis reveals the presence of genetic variation in the main region of the linkage group I, which is the most reported and related to the protein content in soybean.…”

Section: Discussionmentioning

confidence: 88%

Untitled

et al. 2017

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Pre-mejoramiento vegetal para el volumen incrementado de proteína en soya Glycine max (L. ) AbstractThe aim of this research were to determine protein content and genetic divergence of soybean genotypes in QTL regions of the trait grain protein content for plant breeding purposes. Twenty-nine soybean genotypes were grown in the field in four environments (Viçosa-MG Dec/2009, Visconde do Rio Branco-MG Feb/2010, São Gotardo-MG Feb/2010, and São Gotardo-MG Oct/2011) using the randomized block design with three replicates. The grain protein content was quantified by the infrared spectrometry method. The genetic divergence was estimated by the analysis of 39 microsatellite markers from QTL regions for the soybean grain protein content. The pairs of genotypes with greater genetic distances and protein contents were as follows: BARC-8/CS3032PTA276-3-4 (D=0.71) (45.18%/44.31%); BARC-8/CS3032PTA276-1-2 (D=0.71) (45.18%/43.75%); BARC-8/CS3032PTA190-5-1 (D=0.71) (45.18%/43.63%); B3PTA382-2-10/CS3032PTA276-3-4 (D=0.62) (43.80%/44.31%); CS3032PTA276-1-2/ B3PTA382-2-10 (D=0.62) (43.75%/43.80%); B3PTA382-2-10/CS3032PTA190-5-1 (D=0.62) (43.80%/43.63%); B3PTA216-1-9/CS3032PTA276-3-4 (D=0.61) (43.48%/44.31%); and B3PTA216-1-9/CS3032PTA276-1-2 (D=0.61) (43.48%/43.75%), respectively. Other promising combinations for the improvement of protein content were as follows: BR8014887/CS3032PTA190-5-1 (D=0.57) (44.71%/43.63%); BARC-8/CS3032PTA182 (D=0.78) (45.18%/41.84%); BR8014887/CS3032PTA182 (D=0.65) (44.71%/41.84%); BR8014887/PI417360 (D=0.76) (44.71%/41.01%), respectively; and PI417360/B3PTA216-1-9 (D=0.80) (41.01%/43.48%). These pairs of genotypes when crossed should produce populations with higher means and genetic variances and greater gains with selection.

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“…One of the world's top commodity production is soybean (Glycine max L.). In fact, much of the world's protein and oil comes from soybean and this legume contains more protein (40%) and oil (20%) than any other ordinary food source, including meat, cheese and fish (Krishnan, 2005;Bolon et al, 2010). The appropriate addition of soy to different products, results in lower calorie alternative food products, with high content of protein, dietary fiber and minerals, preserving the physical and sensory characteristics of the product (Dhingra and Jood, 2001).…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of iron deficiency chlorosis responses in soybean (Glycine max) and barrel medic (Medicago truncatula)

Santos¹,

Serrão²,

Vasconcelos³

2016

Rev. Ciênc. Agr.

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A B S T R A C TLegume grains have an important socio-economical role, being highly utilized in human and animal nutrition. Although iron (Fe) is abundant in the earth's crust, its limited solubility makes it poorly bioavailable for plants, contributing to iron deficiency chlorosis (IDC). In this work the physiological and molecular mechanisms associated with IDC were studied, namely, the mechanisms involved on Fe deficiency response, as well as a new Fe metabolism related gene in two important legume crops, Glycine max and Medicago truncatula. Fe deficient plants developed: decreased root and shoot length, increased number of secondary roots and lower chlorophyll levels. Fe shoot content decreased six-and 11-fold for G. max and M truncatula in Fe-deficiency. Whilst in G. max roots no significant differences were detected, in M. truncatula roots Fe decreased nine-fold in Fe-deficiency. Genes involved in Fe uptake (FRO2-like and IRT1-like), were over-expressed in roots of Fe-sufficient G. max and in Fe-deficient M. truncatula. VIT1-like, YSL1-like and ferritin presented higher expression levels in Fe-sufficient shoots and roots, whereas NRAMP3-like and GCN2-like showed higher expression values in Fe-deficiency.

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

Cited by 104 publications

References 112 publications

An Integrative Approach to Genomic Introgression Mapping

An Integrative Approach to Genomic Introgression Mapping

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Comparative analysis of iron deficiency chlorosis responses in soybean (Glycine max) and barrel medic (Medicago truncatula)

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