Quantitative Trait Loci For Oil Content Research Articles

Linkage mapping and genomic prediction of grain quality traits in tropical maize (Zea mays L.).

The suboptimal productivity of maize systems in sub-Saharan Africa (SSA) is a pressing issue, with far-reaching implications for food security, nutrition, and livelihood sustainability within the affected smallholder farming communities. Dissecting the genetic basis of grain protein, starch and oil content can increase our understanding of the governing genetic systems, improve the efficacy of future breeding schemes and optimize the end-use quality of tropical maize. Here, four bi-parental maize populations were evaluated in field trials in Kenya and genotyped with mid-density single nucleotide polymorphism (SNP) markers. Genotypic (G), environmental (E) and G×E variations were found to be significant for all grain quality traits. Broad sense heritabilities exhibited substantial variation (0.18-0.68). Linkage mapping identified multiple quantitative trait loci (QTLs) for the studied grain quality traits: 13, 7, 33, 8 and 2 QTLs for oil content, protein content, starch content, grain texture and kernel weight, respectively. The co-localization of QTLs identified in our research suggests the presence of shared genetic factors or pleiotropic effects, implying that specific genomic regions influence the expression of multiple grain quality traits simultaneously. Genomic prediction accuracies were moderate to high for the studied traits. Our findings highlight the polygenic nature of grain quality traits and demonstrate the potential of genomic selection to enhance genetic gains in maize breeding. Furthermore, the identified genomic regions and single nucleotide polymorphism markers can serve as the groundwork for investigating candidate genes that regulate grain quality traits in tropical maize. This, in turn, can facilitate the implementation of marker-assisted selection (MAS) in breeding programs focused on improving grain nutrient levels.

Integrated analysis of transcriptomic and small RNA sequencing data provides miRNA candidates for engineering agronomically important seed traits in Brassica juncea

Brassica juncea L. is an important oilseed crop that yields edible oil and biofuel. Improving B. juncea seed traits is a primary breeding target, but these traits are genetically complex. MicroRNAs (miRNAs) regulate seed development by modulating gene expression at the post-transcriptional or translational level and are excellent candidates for improving seed traits. However, the roles of miRNAs in B. juncea seed development are yet to be investigated. Here, we report small RNA profiling and miRNA identification from developing seeds of two contrasting varieties of B. juncea, Early Heera2 (EH2) and Pusa Jaikisan (PJK). We identified 326 miRNAs, including 127 known and 199 novel miRNAs, of which 103 exhibited inter-varietal differential expression. Integrating miRNAome and our previous transcriptome data identified 13,683 putative miRNA-target modules. Segregation of differentially expressed miRNAs into different groups based on variety-wise upregulation, followed by comprehensive functional analysis of targets using pathway mapping, gene ontology, transcription factor mapping, and candidate gene analysis, revealed at least 11, 6, and 7 miRNAs as robust candidates for the regulation of seed size, seed coat color, and oil content, respectively. Further, co-localization with previously reported quantitative trait loci (QTL) proffered 29 and 15 miRNAs overlapping with seed weight and oil content QTLs, respectively. Our study is the first comprehensive report of miRNAome expression dynamics from developing seeds and provides candidate miRNAs and target genes for engineering seed traits in B. juncea.

High-resolution mapping of a major and consensus quantitative trait locus for oil content to a ~\u20090.8-Mb region on chromosome A08 in peanut (Arachis hypogaea L.)

Key messageddRAD-seq-based high-density genetic map comprising 2595 loci identified a major and consensus QTL with a linked marker in a 0.8-Mb physical interval for oil content in peanut.Enhancing oil content is an important breeding objective in peanut. High-resolution mapping of quantitative trait loci (QTLs) with linked markers could facilitate marker-assisted selection in breeding for target traits. In the present study, a recombined inbred line population (Xuhua 13 × Zhonghua 6) was used to construct a genetic map based on double-digest restriction-site-associated DNA sequencing (ddRAD-seq). The resulting high-density genetic map contained 2595 loci, and spanned a length of 2465.62 cM, with an average distance of 0.95 cM/locus. Seven QTLs for oil content were identified on five linkage groups, including the major and stable QTL qOCA08.1 on chromosome A08 with 10.14–27.19% phenotypic variation explained. The physical interval of qOCA08.1 was further delimited to a ~ 0.8-Mb genomic region where two genes affecting oil synthesis had been annotated. The marker SNPOCA08 was developed targeting the SNP loci associated with oil content and validated in peanut cultivars with diverse oil contents. The major and stable QTL identified in the present study could be further dissected for gene discovery. Furthermore, the tightly linked marker for oil content would be useful in marker-assisted breeding in peanut.

Mapping quantitative trait loci controlling oil content, oleic acid and linoleic acid content in sunflower (Helianthus annuus L.)

Sunflower oil with high oleic acid content is in great demand due to its nutritional as well as industrial benefits. The trait is mainly controlled by dominant alleles at a major gene, Ol, with other modifiers. The objectives of this research were to map the oil content, oleic acid and linoleic acid content in sunflower seeds. An F2 mapping population from cytoplasmic male-sterile line COSF 7A (33–35 % oleic acid) and high oleic acid inbred line HO 5–13 (88–90 % oleic acid) was developed and phenotyped for oil content, oleic acid and linoleic acid content at the F2 seed level. High phenotypic and genotypic coefficients of variation were recorded for oleic acid and linoleic acid content. High heritability and high genetic advance as percent of mean was recorded for oleic acid and linoleic acid content. This indicated the presence of the additive type of gene action controlling the traits oleic acid content and linoleic acid content. The Ol gene was mapped to linkage group (LG) 14 and tightly linked to the marker HO_Fsp_b. In addition, two more quantitative trait loci (QTLs) for oleic acid content were identified in LG8 and LG9. Two QTLs for oil content and two QTLs for linoleic acid content were also identified. All these QTLs explained over 10 % of phenotypic variation. A study was conducted with 13 genotypes differing in oil quality as well as quantity over three seasons to assess the reliability of the identified QTLs over seasons. It resulted in the identification of two potential QTLs for oleic acid as well as linoleic acid content with the markers ORS 762 and HO_Fsp_b. These markers explained more than 57.6–66.6 % of phenotypic variation. Hence it can be concluded that these markers/QTLs would be useful in the marker-assisted selection breeding programme to improve oil quality. The present study also indicated the presence of at least two other genomic regions controlling oleic and linoleic acid content in sunflower.

Identification of QTLs for seed quality traits in rapeseed (Brassica napus L.) using recombinant inbred lines (RILs)

Rapeseed (Brassica napus L.) is the most important edible oilseed crop in China and the second most important globally after soybean. It provides edible vegetable oil for human consumption and proteins for the feed industry, and has recently gained increasing interest as a source of biodiesel. The improvement of seed quality traits for high protein, oil and oleic acid, and low erucic acid and glucosinolate content remains the most important breeding goal in B. napus. Mapping of quantitative trait loci (QTLs) underlying seed quality traits will allow us to enrich knowledge on these traits and improve the efficiency and precision of conventional rapeseed breeding via marker-assisted selection (MAS). In this study, a genetic linkage map comprising 181 markers (143 sequence-related amplified polymorphisms (SRAPs) and 38 simple-sequence repeats (SSRs)) and 19 linkage groups covering 1307.99 cM was constructed with 94 F7–8 recombinant inbred lines (RILs) derived from a cross between a high oil content line ‘827R’ and a low oil content line ‘Darmor_Sin’. A total of nine QTLs were identified (LOD > 2.5) on four chromosomal regions (LG1, LG10, LG11 and LG12) for seed quality traits: four for oil content (qOC-1, 2, 3, 4), two for protein content (qPC-1, 2), two for oleic acid content (qOAC-1, 2), and one for glucosinolate content (qGLC-1). The phenotypic variance explained by individual QTL was estimated as 7.70, 14.58, 16.00, and 23.11 % respectively for the four oil content QTLs; 13.16 and 14.81 % for the two protein content QTLs; 12.52 and 25.48 % for the two oleic acid content QTLs; and 47.71 % for the glucosinolate content QTL. The overall phenotypic variation explained by the identified QTLs was 61.39 % for oil content, 27.97 % for protein content, 38.00 % for oleic acid content and 47.71 % for glucosinolate content. Of the two QTLs identified for seed protein content, one (qPC-1) was tightly linked to a QTL for oil content (qOC-1) on LG1 and another one (qPC-2) was co-localized with a second QTL for seed oil content (qOC-2) on LG11. The two pairs of QTLs affected both traits with opposite additive effects confirming the negative correlation between oil and protein content in rapeseed. The present results will be of value for ongoing efforts to dissect the molecular basis of seed quality traits and practicing MAS in B. napus breeding programs.

Genetic analysis and QTL mapping of oil content and seed index using two recombinant inbred lines and two backcross populations in Upland cotton

AbstractCottonseed is one of the main by‐products of cotton. To explore the genetic composition of oil content (OC) and seed index (SI) is helpful for utilizing the cottonseed. Under multiple environmental conditions, the genetic structures of OC and SI were explored using two recombinant inbred lines (RILs) and corresponding backcross (BC) populations in Upland cotton. Twenty‐four and 31 quantitative trait loci (QTLs) for OC and SI, respectively, were detected using composite interval mapping, in which 9 QTLs for OC and 18 QTLs controlling SI were simultaneously identified in more than two environments or two populations. Forty‐seven and 37 QTLs with main effects (M‐QTLs) for OC and SI and 114 and 74 QTLs involved in digenic interactions (E‐QTLs), respectively, identified by inclusive composite interval mapping. On average, the E‐QTLs explained a larger portion of the phenotypic variation than the M‐QTLs did. It was concluded that additive effects of single‐locus and epistasis derived from complementary loci with few detectable single‐locus effects played an important role in oil content and seed index in Upland cotton.

Identification of Brassica genotypes and molecular markers for increased seed oil content

Javed, N., Tahir, M., Geng, J., Li, G. and McVetty, P. B. E. 2014. Identification of Brassica genotypes and molecular markers for increased seed oil content. Can. J. Plant Sci. 94: 1103–1108. Carbon dioxide emissions by the transportation sector are major contributors to global climate change. Lower CO2 emissions by the transportation sector are linked to the use of renewable fuels including biodiesel. Canola has high seed oil content, adaptation to temperate climates and favorable fatty acid composition, which make it a preferred feedstock for biodiesel production. Doubled haploid (DH) line, random inbred (RI) line and consensus genetics maps for mapping populations derived from Polo × Topas were developed. The DH line-based genetic map was then used for the identification and tagging of quantitative trait loci (QTL) controlling seed oil biosynthesis. This genetic map consisted of 620 loci identified using several different types of molecular markers, and covered a map distance of 2241.1 cM with marker saturation of 3.7 cM. The phenotypic data on the mapping population for seed oil content and component fatty acids were collected from four-environment replicated field trials. One hundred and thirty-one QTL for various fatty acids in canola oil and 14 QTL for oil content were identified. These QTL, combined with marker-assisted selection, may assist breeders in their attempts to develop canola lines with improved oil quality, oil content and oil production per hectare for biodiesel production.

QTL analysis for phytonutrient compounds and the antioxidant molecule in mustard (Brassica juncea L.)

A recombinant inbred line (RIL) population was developed following hybridization between a low glucosinolate B. juncea genotype, NUDH-YJ-04 and a high glucosinolate cultivar, RL-1359. RILs differed for seed and leaf glucosinolates, total tocopherols and oil content. A linkage map of length covering 2346.9 cM was constructed. It comprised 198 markers distributed across the 18 linkage groups. The linkage map facilitated analysis of quantitative trait loci (QTL) associated with phytonutrient compounds and the antioxidant molecules. The composite interval mapping helped to identify 21 QTLs on 11 linkage groups with R2 values between 15–53 % at logarithmic of odd (LOD) scores of 3.1–8.6. For seed aliphatic glucosinolates, most significant QTL, explaining 53 % of the phenotypic variation was located on J9, for glucoiberin (IBE-S). QTLs were also identified for indole glucosinolate (NEO-S) (44 %) on J7 and aromatic glucosinolate (NAS-S) (38 %) on J4. Total leaf glucosinolates (TGLC-L) explaining 15–21 % phenotypic variance were mapped to three different genetic intervals on J6 and J14, and total seed glucosinolates (TGLC-S) explained 17 % of the variance on J18. Tocopherol (TOC) QTL was confined to chromosome no. J6 (28 %) and J12 (19 %) at LOD score of 4.8 and 3.1. QTL for Oil content was tagged on J9 at LOD score of 3.2. Candidate genes underlying SIN-S, NEO-S and NAS-S QTLs, were considered to be GSL-elong, MYB-76 and MYB-28 in A4, A7 and A10 respectively. Despite a lower coverage, this is a first linkage map in this crop based solely on SSR markers and can serve as a basic map.

Identification and validation of quantitative trait loci for seed yield, oil and protein contents in two recombinant inbred line populations of soybean.

Soybean seeds contain high levels of oil and protein, and are the important sources of vegetable oil and plant protein for human consumption and livestock feed. Increased seed yield, oil and protein contents are the main objectives of soybean breeding. The objectives of this study were to identify and validate quantitative trait loci (QTLs) associated with seed yield, oil and protein contents in two recombinant inbred line populations, and to evaluate the consistency of QTLs across different environments, studies and genetic backgrounds. Both the mapping population (SD02-4-59×A02-381100) and validation population (SD02-911×SD00-1501) were phenotyped for the three traits in multiple environments. Genetic analysis indicated that oil and protein contents showed high heritabilities while yield exhibited a lower heritability in both populations. Based on a linkage map constructed previously with the mapping population and using composite interval mapping and/or interval mapping analysis, 12 QTLs for seed yield, 16 QTLs for oil content and 11 QTLs for protein content were consistently detected in multiple environments and/or the average data over all environments. Of the QTLs detected in the mapping population, five QTLs for seed yield, eight QTLs for oil content and five QTLs for protein content were confirmed in the validation population by single marker analysis in at least one environment and the average data and by ANOVA over all environments. Eight of these validated QTLs were newly identified. Compared with the other studies, seven QTLs for seed yield, eight QTLs for oil content and nine QTLs for protein content further verified the previously reported QTLs. These QTLs will be useful for breeding higher yield and better quality cultivars, and help effectively and efficiently improve yield potential and nutritional quality in soybean.

Mapeamento de QTL para conteúdos de proteína e óleo em soja

O objetivo deste trabalho foi detectar e mapear locos de caracteres quantitativos (QTL) que afetam os conteúdos de proteína e óleo em soja (Glycine max L. Merr.). Plantas F2, derivadas do cruzamento entre a linhagem CS3032PTA276 e a variedade UFVS2012, foram cultivadas em casa de vegetação e forneceram as folhas para extração e análise de DNA. Quarenta e oito marcadores microssatélites (SSR) polimórficos foram avaliados na população F2. A avaliação dos fenótipos foi realizada em 207 famílias das progênies F2:3, em um delineamento em blocos ao acaso, com três repetições, conduzido em Viçosa, MG, em 2006. Foram detectados quatro QTL associados ao conteúdo de proteína, nos grupos de ligação D1a, G, A1, e I, e três QTL associados ao conteúdo de óleo, nos grupos A1, I e O. A variação fenotípica explicada pelos QTL variou de 6,24 a 18,94% e 17,26 a 25,93%, respectivamente, para os conteúdos de proteína e óleo. Foram detectados novos QTL associados aos conteúdos de proteína e óleo, além dos previamente relatados em outros estudos. Regiões distintas das atualmente conhecidas podem estar envolvidas no controle genético do teor de proteína e óleo na soja.

QTL mapping of nutrient components in maize kernels under low nitrogen conditions

AbstractA set of 213 F2:3 families were used to investigate the effects of nitrogen (N) on grain yield and the concentrations of three nutrient components in maize (Zea mays L.) kernels. A genetic linkage map was constructed using 189 SSR (simple sequence repeat) markers, spanning a total of 2003 cM, including 11 linkages, and the families were evaluated under high N and low N conditions at two farm locations. The results indicate that low N conditions may induce an increase in starch concentration, but a decrease in protein levels. Twenty‐six quantitative trait loci (QTL) were detected for four measured traits in the two N treatments at both locations, including eight QTL for grain yield, seven QTL for oil content, six QTL for protein content and five QTL for starch content. The total number of QTL detected for the four measured traits under high N levels was greater than the QTL detected under low N conditions, and several QTL were identified that specifically expressed under different N conditions. These particular QTL could help provide greater understanding of the genetic basis of N‐usage efficiency.

Identification of quantitative trait loci (QTL) for oil and protein contents and their relationships with other seed quality traits in Brassica juncea

A detailed RFLP-genomic map was used to study the genetics of oil, seed and meal protein and sum of oil and seed/meal protein contents in a recombinant doubled-haploid population developed by crossing black- and yellow-seeded Brassica juncea lines. Two yellow seed color genes (SC-B4, SC-A6) and one QTL for erucic acid content (E(1b)) showed pleiotropic effect for oil, protein and sum of oil and seed/meal protein contents. Six (O-A1, O-A6, O-A9, O-B3, O-B4, O-B5) and five (SP-A1, SP-A9, SP-B4, SP-B6, SP-C) QTLs were significant for oil and seed protein contents, respectively. Tight linkage of three of these QTLs (SP-A1, SP-A9, SP-B4, O-A1, O-A9, O-B4), with opposite effects, poses challenge to the plant breeders for simultaneous improvement of negatively correlated (r = -0.7**) oil and seed protein contents. However, one QTL for oil content (O-B3) and two for seed protein content (SP-B6, SP-C) were found to be unlinked, which offer the possibility for simultaneous improvement of these two traits. QTLs significant for meal protein (MP-A1, MP-A6, MP-A9, MP-B5, MP-B6) were significant at least for oil, seed protein or sum of oil and seed/meal protein contents (T-A6, T-A7, T-B4, T-B5). Sum of oil and seed protein contents and sum of oil and meal protein contents had a perfect correlation, as well as same epistatic interactions and QTLs with similar additive effect. This indicates that protein in seed or meal has practically the same meaning for breeding purposes. Epistatic interactions were significant for the quality traits, and their linkage reflected association among the traits.