Mapping Quantitative Trait Loci (QTLs) for Hundred-Pod and Hundred-Seed Weight under Seven Environments in a Recombinant Inbred Line Population of Cultivated Peanut (Arachis hypogaea L.).

The cultivated peanut (Arachis hypogaea L.) is a significant oil and cash crop globally. Hundred-pod and -seed weight are important components for peanut yield. To unravel the genetic basis of hundred-pod weight (HPW) and hundred-seed weight (HSW), in the current study, a recombinant inbred line (RIL) population with 188 individuals was developed from a cross between JH5 (JH5, large pod and seed weight) and M130 (small pod and seed weight), and was utilized to identify QTLs for HPW and HSW. An integrated genetic linkage map was constructed by using SSR, AhTE, SRAP, TRAP and SNP markers. This map consisted of 3130 genetic markers, which were assigned to 20 chromosomes, and covered 1998.95 cM with an average distance 0.64 cM. On this basis, 31 QTLs for HPW and HSW were located on seven chromosomes, with each QTL accounting for 3.7-10.8% of phenotypic variance explained (PVE). Among these, seven QTLs were detected under multiple environments, and two major QTLs were found on B04 and B08. Notably, a QTL hotspot on chromosome A08 contained seven QTLs over a 2.74 cM genetic interval with an 0.36 Mb physical map, including 18 candidate genes. Of these, Arahy.D52S1Z, Arahy.IBM9RL, Arahy.W18Y25, Arahy.CPLC2W and Arahy.14EF4H might play a role in modulating peanut pod and seed weight. These findings could facilitate further research into the genetic mechanisms influencing pod and seed weight in cultivated peanut.

GWAS and bulked segregant analysis reveal the Loci controlling growth habit-related traits in cultivated Peanut (Arachis hypogaea L.).

BACKGROUND: Peanut (Arachis hypogaea L.) is a grain legume crop that originated from South America and is now grown around the world. Peanut growth habit affects the variety's adaptability, planting patterns, mechanized harvesting, disease resistance, and yield. The objective of this study was to map the quantitative trait locus (QTL) associated with peanut growth habit-related traits by combining the genome-wide association analysis (GWAS) and bulked segregant analysis sequencing (BSA-seq) methods. RESULTS: GWAS was performed with 17,223 single nucleotide polymorphisms (SNPs) in 103 accessions of the U.S. mini core collection genotyped using an Affymetrix version 2.0 SNP array. With a total of 12,342 high-quality polymorphic SNPs, the 90 suggestive and significant SNPs associated with lateral branch angle (LBA), main stem height (MSH), lateral branch height (LBL), extent radius (ER), and the index of plant type (IOPT) were identified. These SNPs were distributed among 15 chromosomes. A total of 597 associated candidate genes may have important roles in biological processes, hormone signaling, growth, and development. BSA-seq coupled with specific length amplified fragment sequencing (SLAF-seq) method was used to find the association with LBA, an important trait of the peanut growth habit. A 4.08 Mb genomic region on B05 was associated with LBA. Based on the linkage disequilibrium (LD) decay distance, we narrowed down and confirmed the region within the 160 kb region (144,193,467-144,513,467) on B05. Four candidate genes in this region were involved in plant growth. The expression levels of Araip.E64SW detected by qRT-PCR showed significant difference between 'Jihua 5' and 'M130'. CONCLUSIONS: In this study, the SNP (AX-147,251,085 and AX-144,353,467) associated with LBA by GWAS was overlapped with the results in BSA-seq through combined analysis of GWAS and BSA-seq. Based on LD decay distance, the genome range related to LBA on B05 was shortened to 144,193,467-144,513,467. Three candidate genes related to F-box family proteins (Araip.E64SW, Araip.YG1LK, and Araip.JJ6RA) and one candidate gene related to PPP family proteins (Araip.YU281) may be involved in plant growth and development in this genome region. The expression analysis revealed that Araip.E64SW was involved in peanut growth habits. These candidate genes will provide molecular targets in marker-assisted selection for peanut growth habits.

Insights into the Genomic Architecture of Seed and Pod Quality Traits in the U.S. Peanut Mini-Core Diversity Panel.

Traits such as seed weight, shelling percent, percent sound mature kernels, and seed dormancy determines the quality of peanut seed. Few QTL (quantitative trait loci) studies using biparental mapping populations have identified QTL for seed dormancy and seed grade traits. Here, we report a genome-wide association study (GWAS) to detect marker-trait associations for seed germination, dormancy, and seed grading traits in peanut. A total of 120 accessions from the U.S. peanut mini-core collection were evaluated for seed quality traits and genotyped using Axiom SNP (single nucleotide polymorphism) array for peanut. We observed significant variation in seed quality traits in different accessions and different botanical varieties. Through GWAS, we were able to identify multiple regions associated with sound mature kernels, seed weight, shelling percent, seed germination, and dormancy. Some of the genomic regions that were SNP associated with these traits aligned with previously known QTLs. For instance, QTL for seed dormancy has been reported on chromosome A05, and we also found SNP on the same chromosome associated with seed dormancy, explaining around 20% of phenotypic variation. In addition, we found novel genomic regions associated with seed grading, seed germination, and dormancy traits. SNP markers associated with seed quality and dormancy identified here can accelerate the selection process. Further, exploring the function of candidate genes identified in the vicinity of the associated marker will assist in understanding the complex genetic network that governs seed quality.

Association of differentially expressed R-gene candidates with leaf spot resistance in peanut (Arachis hypogaea L.).

Early leaf spot (ELS) and late leaf spot (LLS) are major fungal diseases of peanut that can severely reduce yield and quality. Development of acceptable genetic resistance has been difficult due to a strong environmental component and many major and minor QTLs. Resistance genes (R-genes) are an important component of plant immune system and have been identified in peanut. Association of specific R-genes to leaf spot resistance will provide molecular targets for marker-assisted breeding strategies. In this study, advanced breeding lines from different pedigrees were evaluated for leaf spot resistance and 76 candidate R-genes expression study was applied to susceptible and resistant lines. Thirty-six R-genes were differentially expressed and significantly correlated with resistant lines, of which a majority are receptor like kinases (RLKs) and receptor like proteins (RLPs) that sense the presence of pathogen at the cell surface and initiate protection response. The largest group was receptor-like cytoplasmic kinases (RLCKs) VII that are involved in pattern-triggered kinase signaling resulting in the production reactive oxygen species (ROS). Four R-genes were homologous to TMV resistant protein N which has shown to confer resistance against tobacco mosaic virus (TMV). When mapped to peanut genomes, 36 R-genes were represented in most chromosomes except for A09 and B09. Low levels of gene-expression in resistant lines suggest expression is tightly controlled to balance the cost of R-gene expression to plant productively. Identification and association of R-genes involved in leaf spot resistance will facilitate genetic selection of leaf spot resistant lines with good agronomic traits.

Comparison of Arachis monticola with Diploid and Cultivated Tetraploid Genomes Reveals Asymmetric Subgenome Evolution and Improvement of Peanut.

Like many important crops, peanut is a polyploid that underwent polyploidization, evolution, and domestication. The wild allotetraploid peanut species Arachis monticola (A. monticola) is an important and unique link from the wild diploid species to cultivated tetraploid species in the Arachis lineage. However, little is known about A. monticola and its role in the evolution and domestication of this important crop. A fully annotated sequence of ≈2.6 Gb A. monticola genome and comparative genomics of the Arachis species is reported. Genomic reconstruction of 17 wild diploids from AA, BB, EE, KK, and CC groups and 30 tetraploids demonstrates a monophyletic origin of A and B subgenomes in allotetraploid peanuts. The wild and cultivated tetraploids undergo asymmetric subgenome evolution, including homoeologous exchanges, homoeolog expression bias, and structural variation (SV), leading to subgenome functional divergence during peanut domestication. Significantly, SV-associated homoeologs tend to show expression bias and correlation with pod size increase from diploids to wild and cultivated tetraploids. Moreover, genomic analysis of disease resistance genes shows the unique alleles present in the wild peanut can be introduced into breeding programs to improve some resistance traits in the cultivated peanuts. These genomic resources are valuable for studying polyploid genome evolution, domestication, and improvement of peanut production and resistance.

Construction of High-Density Genetic Map and Mapping Quantitative Trait Loci for Growth Habit-Related Traits of Peanut (Arachis hypogaea L.).

Plant growth habit is an important and complex agronomic trait and is associated with yield, disease resistance, and mechanized harvesting in peanuts. There are at least two distinct growth habits (erect and prostrate) and several intermediate forms existing in the peanut germplasm. A recombinant inbred line population containing 188 individuals was developed from a cross of "Jihua 5" and "M130" for genetically dissecting the architecture of the growth habit. A new high-density genetic linkage map was constructed by using specific locus amplified fragment sequencing technology. The map contains 2,808 single-nucleotide polymorphism markers distributed on 20 linkage groups with a total length of 1,308.20 cM and an average inter-marker distance of 0.47 cM. The quantitative trait locus (QTL) analysis of the growth habit-related traits was conducted based on phenotyping data from seven environments. A total of 39 QTLs for growth habit-related traits was detected on 10 chromosomes explaining 4.55-27.74% of the phenotypic variance, in which 6 QTLs were for lateral branch angle, 8 QTLs were for extent radius, 7 QTLs were for the index of plant type, 11 QTLs were for main stem height, and 7 QTLs were for lateral branch length. Among these QTLs, 12 were co-localized on chromosome B05 spanning an approximately 0.17 Mb physical interval in comparison with the allotetraploid reference genome of "Tifrunner." Analysis of the co-localized genome region has shown that the putative genes are involved in light and hormones and will facilitate peanut growth habit molecular breeding and study of peanut domestication.

Transcriptome Analysis Reveals Unique Relationships Among Eleusine Species and Heritage of Eleusine coracana.

Relationships in the genus Eleusine were obtained through transcriptome analysis. Eleusine coracana (E. coracana ssp. coracana), also known as finger millet, is an allotetraploid minor crop primarily grown in East Africa and India. Domesticated E. coracana evolved from wild E. africana (E. coracana ssp. africana) with the maternal genome donor largely supported to be E. indica; however, the paternal genome donor remains elusive. We developed transcriptomes for six Eleusine species from fully developed seedlings using Illumina technology and three de novo assemblers (Trinity, Velvet, and SOAPdenovo2) with the redundancy-reducing EvidentialGene pipeline. Mapping E. coracana reads to the chloroplast genes of all Eleusine species detected fewer variants between E. coracana and E. indica compared to all other species. Phylogenetic analysis further supports E. indica as the maternal parent of E. coracana and E. africana, in addition to a close relationship between E. indica and E. tristachya, and between E. floccifolia and E. multiflora, and E. intermedia as a separate group. A close relationship between E. floccifolia and E. multiflora was unexpected considering they are reported to have distinct nuclear genomes, BB and CC, respectively. Further, it was expected that E. intermedia and E. floccifolia would have a closer relationship considering they have similar nuclear genomes, AB and BB, respectively. A rethinking of the labeling of ancestral genomes of E. floccifolia, E. multiflora, and E. intermedia is maybe needed based on this data.

Development of a goosegrass (Eleusine indica) draft genome and application to weed science research.

BACKGROUND: Genomes are vital to the study of genomics, population genetics, and evolution of species. To date, only one genome (Echinochloa crus-galli) for C4 annual weedy grass species has been sequenced. Research was conducted to develop a draft genome of goosegrass (Eleusine indica; 2n = 2x = 18), one of the most common and troublesome weeds in the world. RESULTS: A draft assembly of an approximately 492 Mb whole-genome sequence of goosegrass was obtained by de novo assembly of paired-end and mate-paired reads generated by Illumina sequencing of total genomic DNA. The genome was assembled into 24,072 scaffolds with N50 = 233,459 bp. More than 99% of transcriptome sequences were mapped to the goosegrass draft genome, and 95% of the commonly conserved plant genes were present. The assembled genome contains 25,467 unique protein-coding genes. Genes associated with herbicide resistance were obtained and variant calling allowed the detection of 754,409 single nucleotide polymorphisms. In addition, we also report 115,417 simple sequence repeats which can be deployed in population genetics and phylogenetic analysis. CONCLUSION: This is the first report of genome sequence of goosegrass. Our assembly was able to identify all major herbicide-resistance related genes and develop a useful tool for other genomic and evolutionary analysis. © 2019 Society of Chemical Industry.

Identification of expressed R-genes associated with leaf spot diseases in cultivated peanut.

Peanut (Arachis hypogaea L.) is an important food and oilseed crop worldwide. Yield and quality can be significantly reduced by foliar fungal diseases, such as early and late leaf spot diseases. Acceptable levels of leaf spot resistance in cultivated peanut have been elusive due to environmental interactions and the proper combination of QTLs in any particular peanut genotype. Resistance gene analogs, as potential resistance (R)-genes, have unique roles in the recognition and activation of disease resistance responses. Novel R-genes can be identified by searches for conserved domains such as nucleotide binding site, leucine rich repeat, receptor like kinase, and receptor like protein from expressed genes or through genomic sequences. Expressed R-genes represent necessary plant signals in a disease response. The goals of this research are to identify expressed R-genes from cultivated peanuts that are naturally infected by early and late spot pathogens, compare these to the closest diploid progenitors, and evaluate specific gene expression in cultivated peanuts. Putative peanut R-genes (381) were available from a public database (NCBI). Primers were designed and PCR products were sequenced. A total of 214 sequences were produced which matched to proteins with the corresponding R-gene motifs. These R-genes were mapped to the genome sequences of Arachis duranensis and Arachis ipaensis, which are the closest diploid progenitors for tetraploid cultivated peanut, A. hypogaea. Identification and association of specific gene-expression will elucidate potential disease resistance mechanism in peanut and may facilitate the selection of breeding lines with high levels of leaf spot resistance.

Soybean Resistance to White Mold: Evaluation of Soybean Germplasm Under Different Conditions and Validation of QTL.

Soybean (Glycine max L. Merr.) white mold (SWM), caused by Sclerotinia sclerotiorum (Lib) de Barry), is a devastating fungal disease in the Upper Midwest of the United States and southern Canada. Various methods exist to evaluate for SWM resistance and many quantitative trait loci (QTL) with minor effect governing SWM resistance have been identified in prior studies. This study aimed to predict field resistance to SWM using low-cost and efficient greenhouse inoculation methods and to confirm the QTL reported in previous studies. Three related but independent studies were conducted in the field, greenhouse, and laboratory to evaluate for SWM resistance. The first study evaluated 66 soybean plant introductions (PIs) with known field resistance to SWM using the greenhouse drop-mycelium inoculation method. These 66 PIs were significantly (P < 0.043) different for resistance to SWM. However, year was highly significant (P < 0.00001), while PI x year interaction was not significant (P < 0.623). The second study compared plant mortality (PM) of 35 soybean breeding lines or varieties in greenhouse inoculation methods with disease severity index (DSI) in field evaluations. Moderate correlation (r) between PM under drop-mycelium method and DSI in field trials (r = 0.65, p < 0.0001) was obtained. The PM under spray-mycelium was also correlated significantly with DSI from field trials (r = 0.51, p < 0.0018). Likewise, significant correlation (r = 0.62, p < 0.0001) was obtained between PM across greenhouse inoculation methods and DSI across field trials. These findings suggest that greenhouse inoculation methods could predict the field resistance to SWM. The third study attempted to validate 33 QTL reported in prior studies using seven populations that comprised a total of 392 F4 : 6 lines derived from crosses involving a partially resistant cultivar "Skylla," five partially resistant PIs, and a known susceptible cultivar "E00290." The estimates of broad-sense heritability (h2) ranged from 0.39 to 0.66 in the populations. Of the seven populations, four had h2 estimates that were significantly different from zero (p < 0.05). Single marker analysis across populations and inoculation methods identified 11 significant SSRs (p < 0.05) corresponding to 10 QTL identified by prior studies. Thus, these five new PIs could be used as new sources of resistant alleles to develop SWM resistant commercial cultivars.

Changes of Seed Weight, Fatty Acid Composition, and Oil and Protein Contents from Different Peanut FAD2 Genotypes at Different Seed Developmental and Maturation Stages.

The level of oleic acid in peanut seed is one of the most important factors in determining seed quality and is controlled by two pairs of homeologous genes ( FAD2A and FAD2B). The genotypes of eight F8 breeding lines were determined as AABB, aaBB, AAbb, and aabb by real-time polymerase chain reaction and sequencing. Fresh seeds were collected from five seed developmental stages and, after drying, were used for chemical analysis. Our results showed that (1) as seeds developed, seed weight, oil content, and oleic acid level significantly increased, whereas four other fatty acid levels decreased, but protein content and another four fatty acid levels did not significantly change, (2) FAD2A/ FAD2B significantly affected fatty acid profiles but not oil and protein contents, and (3) the data were consistent across 2 years. The variability of seed quality traits revealed here will be useful for peanut breeders, farmers, processers, and consumers.

Refining a major QTL controlling spotted wilt disease resistance in cultivated peanut (Arachis hypogaea L.) and evaluating its contribution to the resistance variations in peanut germplasm.

BACKGROUND: Spotted wilt, caused by tomato spotted wilt virus (TSWV), has been one of major diseases in cultivated peanut grown in the southeastern United States (US) since 1990. Previously a major quantitative trait locus (QTL) controlling spotted wilt disease resistance was mapped to an interval of 2.55 cM genetic distance corresponding to a physical distance of 14.4 Mb on chromosome A01 of peanut by using a segregating F2 population. The current study focuses on refining this major QTL region and evaluating its contributions in the US peanut mini-core germplasm. RESULTS: Two simple sequence repeat (SSR) markers associated with the major QTL were used to genotype F5 individuals, and 25 heterozygous individuals were selected and developed into an F6 segregating population. Based on visual evaluation in the field, a total of 194 susceptible F6 individuals were selected and planted into F7 generation for phenotyping. Nine SSR markers were used to genotype the 194 F6 individuals, and QTL analysis revealed that a confidence interval of 15.2 Mb region had the QTL with 22.8% phenotypic variation explained (PVE). This QTL interval was further genotyped using the Amplicon-seq method. A total of 81 non-redundant single nucleotide polymorphism (SNP) and eight InDel markers were detected. No recombinant was detected among the F6 individuals. Two InDel markers were integrated into the linkage group and helped to refine the confidence interval of this QTL into a 0.8 Mb region. To test the QTL contributes to the resistance variance in US peanut mini-core germplasm, two flanking SSR markers were used to genotype 107 mini-core germplasm accessions. No statistically significant association was observed between the genotype at the QTL region and spotted wilt resistance in the mini-core germplasm, which indicated that the resistance allelic region at this QTL didn't contribute to the resistance variance in the US peanut mini-core germplasm, thus was a unique resistance source. CONCLUSION: A major QTL related to spotted wilt disease resistance in peanut was refined to a 0.8 Mb region on A01 chromosome, which didn't relate to spotted wilt disease resistance in the US peanut mini-core germplasm and might be a unique genetic source.

A genome-wide association study of seed composition traits in wild soybean (Glycine soja).

BACKGROUND: Cultivated soybean (Glycine max) is a major agricultural crop that provides a crucial source of edible protein and oil. Decreased amounts of saturated palmitic acid and increased amounts of unsaturated oleic acid in soybean oil are considered optimal for human cardiovascular health and therefore there has considerable interest by breeders in discovering genes affecting the relative concentrations of these fatty acids. Using a genome-wide association (GWA) approach with nearly 30,000 single nucleotide polymorphisms (SNPs), we investigated the genetic basis of protein, oil and all five fatty acid levels in seeds from a sample of 570 wild soybeans (Glycine soja), the progenitor of domesticated soybean, to identify quantitative trait loci (QTLs) affecting these seed composition traits. RESULTS: We discovered 29 SNPs located on ten different chromosomes that are significantly associated with the seven seed composition traits in our wild soybean sample. Eight SNPs co-localized with QTLs previously uncovered in linkage or association mapping studies conducted with cultivated soybean samples, while the remaining SNPs appeared to be in novel locations. Twenty-four of the SNPs significantly associated with fatty acid variation, with the majority located on chromosomes 14 (6 SNPs) and seven (8 SNPs). Two SNPs were common for two or more fatty acids, suggesting loci with pleiotropic effects. We also identified some candidate genes that are involved in fatty acid metabolism and regulation. For each of the seven traits, most of the SNPs produced differences between the average phenotypic values of the two homozygotes of about one-half standard deviation and contributed over 3% of their total variability. CONCLUSIONS: This is the first GWA study conducted on seed composition traits solely in wild soybean populations, and a number of QTLs were found that have not been previously discovered. Some of these may be useful to breeders who select for increased protein/oil content or altered fatty acid ratios in the seeds. The results also provide additional insight into the genetic architecture of these traits in a large sample of wild soybean, and suggest some new candidate genes whose molecular effects on these traits need to be further studied.

Environmental versus geographical effects on genomic variation in wild soybean (Glycine soja) across its native range in northeast Asia.

A fundamental goal in evolutionary biology is to understand how various evolutionary factors interact to affect the population structure of diverse species, especially those of ecological and/or agricultural importance such as wild soybean (Glycine soja). G. soja, from which domesticated soybeans (Glycine max) were derived, is widely distributed throughout diverse habitats in East Asia (Russia, Japan, Korea, and China). Here, we utilize over 39,000 single nucleotide polymorphisms genotyped in 99 ecotypes of wild soybean sampled across their native geographic range in northeast Asia, to understand population structure and the relative contribution of environment versus geography to population differentiation in this species. A STRUCTURE analysis identified four genetic groups that largely corresponded to the geographic regions of central China, northern China, Korea, and Japan, with high levels of admixture between genetic groups. A canonical correlation and redundancy analysis showed that environmental factors contributed 23.6% to population differentiation, much more than that for geographic factors (6.6%). Precipitation variables largely explained divergence of the groups along longitudinal axes, whereas temperature variables contributed more to latitudinal divergence. This study provides a foundation for further understanding of the genetic basis of climatic adaptation in this ecologically and agriculturally important species.

Development and Utilization of InDel Markers to Identify Peanut (Arachis hypogaea) Disease Resistance.

Peanut diseases, such as leaf spot and spotted wilt caused by Tomato Spotted Wilt Virus, can significantly reduce yield and quality. Application of marker assisted plant breeding requires the development and validation of different types of DNA molecular markers. Nearly 10,000 SSR-based molecular markers have been identified by various research groups around the world, but less than 14.5% showed polymorphism in peanut and only 6.4% have been mapped. Low levels of polymorphism limit the application of marker assisted selection (MAS) in peanut breeding programs. Insertion/deletion (InDel) markers have been reported to be more polymorphic than SSRs in some crops. The goals of this study were to identify novel InDel markers and to evaluate the potential use in peanut breeding. Forty-eight InDel markers were developed from conserved sequences of functional genes and tested in a diverse panel of 118 accessions covering six botanical types of cultivated peanut, of which 104 were from the U.S. mini-core. Results showed that 16 InDel markers were polymorphic with polymorphic information content (PIC) among InDels ranged from 0.017 to 0.660. With respect to botanical types, PICs varied from 0.176 for fastigiata var., 0.181 for hypogaea var., 0.306 for vulgaris var., 0.534 for aequatoriana var., 0.556 for peruviana var., to 0.660 for hirsuta var., implying that aequatoriana var., peruviana var., and hirsuta var. have higher genetic diversity than the other types and provide a basis for gene functional studies. Single marker analysis was conducted to associate specific marker to disease resistant traits. Five InDels from functional genes were identified to be significantly correlated to tomato spotted wilt virus (TSWV) infection and leaf spot, and these novel markers will be utilized to identify disease resistant genotype in breeding populations.

Oil, fatty acid, flavonoid, and resveratrol content variability and FAD2A functional SNP genotypes in the U.S. peanut mini-core collection.

Peanut seeds contain high amounts of oil and protein as well as some useful bioactive phytochemicals which can contribute to human health. The U.S. peanut mini-core collection is an important genetic resource for improving seed quality and developing new cultivars. Variability of seed chemical composition within the mini-core was evaluated from freshly harvested seeds for two years. Oil, fatty acid composition, and flavonoid/resveratrol content were quantified by NMR, GC, and HPLC, respectively. Significant variability was detected in seed chemical composition among accessions and botanical varieties. Accessions were further genotyped with a functional SNP marker from the FAD2A gene using real-time PCR and classified into three genotypes with significantly different O/L ratios: wild type (G/G with a low O/L ratio <1.7), heterozygote (G/A with O/L ratio >1.4 but <1.7), and mutant (A/A with a high O/L ratio >1.7). The results from real-time PCR genotyping and GC fatty acid analysis were consistent. Accessions with high amounts of oil, quercetin, high seed weight, and O/L ratio were identified. The results from this study may be useful not only for peanut breeders, food processors, and product consumers to select suitable accessions or cultivars but also for curators to potentially expand the mini-core collection.

Modified method for combined DNA and RNA isolation from peanut and other oil seeds.

Isolation of good quality RNA and DNA from seeds is difficult due to high levels of polysaccharides, polyphenols, and lipids that can degrade or co-precipitate with nucleic acids. Standard RNA extraction methods utilizing guanidinium-phenol-chloroform extraction has not shown to be successful. RNA isolation from plant seeds is a prerequisite for many seed specific gene expression studies and DNA is necessary in marker-assisted selection and other genetic studies. We describe a modified method to isolate both RNA and DNA from the same seed tissue and have been successful with several oil seeds including peanut, soybean, sunflower, canola, and oil radish. An additional LiCl precipitation step was added to isolate both RNA and DNA from the same seed tissues. High quality nucleic acids were observed based on A(260)/A(280) and A(260)/A(230) ratios above 2.0 and distinct bands on gel-electrophoresis. RNA was shown to be suitable for reverse transcriptase polymerase chain reaction based on actin or 60S ribosomal primer amplification and DNA was shown to have a single band on gel-electrophoresis analysis. This result shows that RNA and DNA isolated using this method can be appropriate for molecular studies in peanut and other oil containing seeds.

Evaluation of five peanut (Arachis hypogaea) genotypes to identify drought responsive mechanisms utilising candidate-gene approach.

Drought can significantly limit yield and quality in peanut (Arachis hypogaea L.), depending on its timing, duration and severity. The objective of this study was to identify potential molecular mechanism(s) utilising a candidate-gene approach in five peanut genotypes with contrasting drought responses. An early season drought stress treatment was applied under environmentally controlled rain-out shelters. When water was completely withheld for 3 weeks, no physical differences were observed for treated plants compared with their fully irrigated counterparts as indicated by relative water content; however, yield, grades (total sound mature kernel, TSMK), specific leaf area, and leaf dry matter content showed significant differences. Comparing expression levels of candidate genes, 'C76-16' exhibited significantly higher levels for CuZnSOD, NsLTP and drought protein 1 week earlier compared to the other genotypes, followed by significantly lower levels for the same genes. This suggested an early recognition of drought in C76-16 followed by an acclimation response. Cultivar 'Georgia Green' showed different patterns of gene-expression than C76-16. AP-3, a susceptible genotype, showed generally lower levels of gene-expression than C76-16 and Georgia Green. Myo-inositol phosphate synthase gene-expression showed high levels in irrigated treatment, ranging from 4-fold for 08T-12 to 12-fold for Georgia Green, but were significantly inhibited in drought treatment after 2 weeks of drought and after recovery.

Population structure and marker-trait association analysis of the US peanut (Arachis hypogaea L.) mini-core collection.

Peanut (Arachis hypogaea L.) is one of the most important oilseed and nutritional crops in the world. To efficiently utilize the germplasm collection, a peanut mini-core containing 112 accessions was established in the United States. To determine the population structure and its impact on marker-trait association, this mini-core collection was assessed by genotyping 94 accessions with 81 SSR markers and two functional SNP markers from fatty acid desaturase 2 (FAD2). Seed quality traits (including oil content, fatty acid composition, flavonoids, and resveratrol) were obtained through nuclear magnetic resonance (NMR), gas chromatography (GC), and high-performance liquid chromatography (HPLC) analysis. Genetic diversity and population structure analysis identified four major subpopulations that are related to four botanical varieties. Model comparison with different levels of population structure and kinship control was conducted for each trait and association analyses with the selected models verified that the functional SNP from the FAD2A gene is significantly associated with oleic acid (C18:1), linoleic acid (C18:2), and oleic-to-linoleic (O/L) ratio across this diverse collection. Even though the allele distribution of FAD2A was structured among the four subpopulations, the effect of FAD2A gene remained significant after controlling population structure and had a likelihood-ratio-based R ( 2 ) (R ( LR ) ( 2 ) ) value of 0.05 (oleic acid), 0.09 (linoleic acid), and 0.07 (O/L ratio) because the FAD2A alleles were not completely fixed within subpopulations. Our genetic analysis demonstrated that this peanut mini-core panel is suitable for association mapping. Phenotypic characterization for seed quality traits and association testing of the functional SNP from FAD2A gene provided information for further breeding and genetic research.

Mapping QTLs of root morphological traits at different growth stages in rice.

Roots are a vital organ for absorbing soil moisture and nutrients and influence drought resistance. The identification of quantitative trait loci (QTLs) with molecular markers may allow the estimation of parameters of genetic architecture and improve root traits by molecular marker-assisted selection (MAS). A mapping population of 120 recombinant inbred lines (RILs) derived from a cross between japonica upland rice 'IRAT109' and paddy rice 'Yuefu' was used for mapping QTLs of developmental root traits. All plant material was grown in PVC-pipe. Basal root thickness (BRT), root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW) and root volume (RV) were phenotyped at the seedling (I), tillering (II), heading (III), grain filling (IV) and mature (V) stages, respectively. Phenotypic correlations showed that BRT was positively correlated to MRL at the majority of stages, but not correlated with RN. MRL was not correlated to RN except at the seedling stage. BRT, MRL and RN were positively correlated to RFW, RDW and RV at all growth stages. QTL analysis was performed using QTLMapper 1.6 to partition the genetic components into additive-effect QTLs, epistatic QTLs and QTL-by-year interactions (Q x E) effect. The results indicated that the additive effects played a major role for BRT, RN and MRL, while for RFW, RDW and RV the epistatic effects showed an important action and Q x E effect also played important roles in controlling root traits. A total of 84 additive-effect QTLs and 86 pairs of epistatic QTLs were detected for the six root traits at five stages. Only 12 additive QTLs were expressed in at least two stages. This indicated that the majority of QTLs were developmental stage specific. Two main effect QTLs, brt9a and brt9b, were detected at the heading stage and explained 19% and 10% of the total phenotypic variation in BRT without any influence from the environment. These QTLs can be used in breeding programs for improving root traits.