Association Genetics Identifies Single Nucleotide Polymorphisms

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Association genetics identifies single nucleotide polymorphisms related to kernel oil content and quality in Camellia oleifera Ping Lin, Hengfu Yin, Chao Yan, Xiaohua Yao, and Kailiang Wang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b03399 • Publication Date (Web): 13 Feb 2019 Downloaded from http://pubs.acs.org on February 13, 2019

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Journal of Agricultural and Food Chemistry

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Association genetics identifies single nucleotide polymorphisms related to kernel oil content and quality in Camellia oleifera

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Ping Lin1,2*, Hengfu Yin1,2, Chao Yan1,2,3, Xiaohua Yao1,2 and Kailiang Wang1,2*

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1. State Key Laboratory of Tree Genetics and Breeding, Research Institute of Subtropical Forestry,

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Chinese Academy of Forestry, Hangzhou 311400, China 2. Key Laboratory of Forest Genetics and Breeding, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China 3. Experimental Center for Subtropical Forestry, Chinese Academy of Forestry, Fenyi, 336600, China

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* Corresponding Authors:

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Ping Lin, [email protected]; + (86) 571-63320229

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Kailiang Wang, [email protected]; + (86) 571-63379095

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1

ACS Paragon Plus Environment


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Abstract

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Camellia oleifera, as an important non-wood tree species for seed oil in China, has

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received enormous attentions owing to its high unsaturated fatty acid contents

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benefited to human health. It is necessary to examine allelic diversity of key genes

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which are associated with oil production in C. oleifera cultivars with a large variation

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of fatty acid compositions. In this study, we performed the association analysis

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between four key genes (two CoSAD and two Cofad2) coding fatty acid desaturases

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and traits including oil content and fatty acid composition. We identified two single

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nucleotide insertion-deletion (InDel) and 362 single-nucleotide polymorphisms (SNPs)

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within the four candidate genes by sequencing an association population (216

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accessions). Single-marker (or haplotype) and traits association tests were conducted

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by linkage disequilibrium (LD) approaches to detect significant marker-trait

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associations. Validation population (279 hybrid individuals from six full-sibs families)

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studies were performed to validate the function of allelic variations significantly

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associated. In all, 90 single marker-trait and one haplotype-trait associations were

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significant in association population, and these loci explained 1.87%~17.93%

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proportion of the corresponding phenotypic variance. Further, six SNP marker–trait 2


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associations (Q < 0.10) from Cofad2-A, CoSAD1 and CoSAD2 were successfully

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validated in the validation population. The SNP markers identified in this study can

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potentially be applied for future marker-assisted selection to improve oil content and

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quality in C. oleifera.

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Keywords: candidate-gene-based association mapping; Camellia oleifera; single

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nucleotide polymorphisms (SNPs); oil content (OC) and fatty acid composition;

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stearoyl-ACP desaturase gene (CoSAD) and Δ12 (ω6)-desaturase gene (Cofad2)

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Introduction

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China is the largest country of edible oil consumption in the world. With the economy

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developing and people’s living standards improving, the per capita possession of

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edible oil and imports of raw materials for edible oil have kept increasing every year

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in China 1. Camellia oleifera is planted widely as an important edible oil-bearing tree

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species in south China. It was reported that the dry seed production was around ~2.2

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million tons over a cultivated area of four million ha in 2015 2. At present, Camellia

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oil has become the fourth important plant edible oil produced in China. Camellia oil,

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nearly 50% of dry kernel weight, is the major product of C. oleifera seeds and is

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considered to be one kind of the highest quality oil

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approximately 90% of all fatty acids (FAs) are the unsaturated FAs (UFA), which

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include oleic acid (C18:1, monounsaturated fatty acid, MUFA) and linoleic acid

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(C18:2, polyunsaturated fatty acid, PUFA), mainly. Because of its high UFA contents,

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especially high MUFA content is good for human health, C. oleifera has received

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much more attention, and the study of factors that influence UFA biosynthesis is very

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important in C. oleifera breeding. The identification of genes and the allelic variation

4


2-4.

In the Camellia oil,

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associated with oil and FAs biosynthesis in the C. oleifera would provide useful

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information for breeding programs to improve oil content and quality.

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The oil and FA biosynthesis has been extensively studied in C. oleifera 2, 5-7. The

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seed oil of C. oleifera was dominant with C18:1, which was similar to hickory and

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olive

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stearoyl-ACP desaturase gene (CoSAD) with a low level of Δ12 (ω6)-desaturase gene

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(Cofad2) was associated with the C18:1 synthesis in C. oleifera 2. C18:1 biosynthesis

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is catalyzed by stearoyl-ACP desaturases (SAD) which are encoded by SAD genes, a

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multigene family with several members

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impacts the ratio of saturated and unsaturated FAs, and is a major determinant of FA

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composition 13-21. The Δ12 (ω6)-desaturase (FAD2) desaturates the C18:1 to synthesize

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the C18:2 in endoplasmic reticulum, which is the key rate-determining procedure for

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the PUFA synthesis in some oil crops

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which belong to a multigene family 24. There are at least five fad2 genes in olive (Olea

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europaea var. sylvestris) 9, three in Camelina sativa 25, two in sesame (Sesamum indicum)

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26

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8, 9.

Previous studies had indicated that the expression of a high level of

10-15.

22, 23.

The activity of SAD significantly

The FAD2s are encoded by fad2 genes,

and at least seven in soybean (Glycine max) 27-33, respectively. Linkage disequilibrium (LD)-based association mapping provides a powerful 5



34-38.

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strategy to genetically dissect complex quantitative traits

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which the LD rapidly decays, association mapping based on candidate gene is

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appropriate to detect the association between sequence variations and specific

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interested traits 39. In generally, LD decays rapidly within genes in outcrossing species

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and can’t extend over the entire gene region, such as tea (Camellia sinensis)

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Chinese white poplar (Populus tomentosa)

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trichocarpa)

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perenne)

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candidate gene association mapping approach may be suitable to establish

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associations between polymorphic loci in targeted genes and complex traits.

42.

40,

sunflower (Helianthus annuus)

35,

41

For the species in

34,

black cottonwood (Populus and perennial ryegrass (Lolium

C. oleifera is an oil-bearing tree species with self-incompatibility, and

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To further explore the functions of CoSAD and Cofad2 genes in Camellia oil FA

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composition formation, we had isolated two CoSAD and two Cofad2 genes from C.

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oleifera based on previously publications

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And the expression levels of these four genes were significantly associated with the

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oil accumulation and FA composition during the seed developing of C. oleifera 2.

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Nevertheless, little is known about whether the allelic diversities of these key genes

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contribute to FA composition variation in the C. oleifera germplasms. In this study, in

2, 6, 43,

respectively (Table 1 and File S1).

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order to explore allelic effects, two InDels and 362 SNPs developed from CoSAD and

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Cofad2 genes were used for single-marker and haplotype-based association mapping

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through the sequencing of a natural population of C. oleifera. Subsequently, we

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validated the significant associations in the C. oleifera by a hybrid population to

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confirm the allelic loci associated with phenotypic traits. This work provides insights

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into the regulation of seed oil biosynthesis in C. oleifera and benefits the genetic

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improvement of Camellia oil quality and yield.

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1. Material and Methods

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1.1 Plant materials

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Association population In 2004, the Research Institute of Subtropical Forestry,

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Chinese Academy of Forestry (Hangzhou, China) maintained a collection of 494

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accessions from the mostly natural distribution region of C. oleifera, covering nine

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provinces in China subtropical areas. These accessions were propagated by grafting

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and established a clonal plantation using a randomized complete block design with

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three replications in Dongfanghong Forest Farm of Zhejiang Province, Jinhua city,

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Zhejiang province, China. In this study, a set of 216 unrelated accessions of C.

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oleifera from the collection were sampled for association analysis. 7



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Validation population In this study, 279 hybrid individuals from six full-sibs

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families were selected for validation analysis. The progenies were grown in 2009 in

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Dongfanghong Forest Farm of Zhejiang Province, Jinhua city, Zhejiang province,

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China, using a randomized complete block design with three replications.

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Phenotypic evaluation OC and oil quality traits, which depended on FA composition,

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were the important breeding aims of C. oleifera. In this study, OC, palmitic acid

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(C16:0), palmitoleic acid (C16:1), stearic acid (C18:0), C18:1, C18:2, linolenic acid

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(C18:3) and cis-11-eicosenoic acid (C20:1) contents of Camellia oil were evaluated.

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The 216 accessions of the association population were scored on eight quantitative

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traits, with at least three ramets per genotype for three years. The mature seeds were

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collected, and the Soxtec extraction method was performed to measure OC as

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described 44. The total lipid was extracted from kernel by petroleum ether, and seven

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kinds of FA components were quantified using gas chromatography according to the

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previous study 45.

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The same eight quantitative traits were measured with three replicates in the 279

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hybrid individuals in 2014, using the same methods for the association population.

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Data Processing System (DPS 14.50, http://www.chinadps.net/dps_eng/) software 8


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was used to perform the analysis of normal fitting and phenotypic correlations for

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eight traits 46. The box-plots were made by R (https://www.r-project.org/).

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1.2 DNA extraction, amplification, and sequencing

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The genomic DNA (gDNA) was isolated from young leaves (one ramet per clone for

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association population) using the TaKaRa MiniBEST Plant Genomic DNA Extraction

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Kit (TaKaRa, Dalian, China) according to the user manual. Based on the cDNA

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sequences of two CoSAD and two Cofad2 2, the specific primer sets (Table 1) were

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designed and used for the amplification of gene regions with gDNA as template. PCR

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was performed in a final reaction volume of 50 μL containing 60 ng of gDNA, 2 ×

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LAmpTM Master Mix (Vazyme, Nanjing, China) 25 μL, 0.4 mM of forward primer,

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and 0.4 mM of reverse primer. The PCR procedure was: 94 ℃ for five min, followed

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by 35 cycles of 94 ℃ denaturation for 30 s, 55 ℃ annealing for 30 s, and 72 ℃

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extension for two min, with a final extension at 72 ℃ for seven min. The amplified

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DNA fragments were purified in 1.2% agarose gels and sequenced with an ABI

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3730XL DNA Analyzer by sequencing primers (Table 2). In total, 7610 bp of gDNA

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sequences from four unique genes Cofad2-A (GenBank ID: JQ739518.1), Cofad2-B

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(GenBank ID: KJ995981.1), CoSAD1 (GenBank ID: MH836317) and CoSAD2 9



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(GenBank ID: MH836318), with an average of 1903 bp per gene, were obtained

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without considering InDels, and the gene length ranged from 1160 bp (Cofad2-B) to

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3548 bp (CoSAD2; Table 1 and File S1).

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1.3 SNP discovery, genotyping and linkage disequilibrium (LD)

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SNP discovery and genotyping were performed using NovoSNP version 3.0.1

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(http://www.molgen.vib-ua.be/bioinfo/novosnp/) from sequence trace files, and the

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SNPs with the score > 12 were selected as true variations 47. All un-filtered SNPs data

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of association and validation populations have been submitted to the European

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Variation Archive (EVA), and the Project accession number is PRJEB31224

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(https://www.ebi.ac.uk/eva). Minor alleles with frequency < 5% were filtered before

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the further analysis. After filtering, the squared correlation of allele frequencies (r2)

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was measured to estimate the LD between pairs of SNPs, using software package

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TASSEL version 3.0 48. The decay of LD with physical distance (base pairs) between

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SNP sites within the candidate genes was evaluated by nonlinear regression analysis

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of r2 values 34, 49.

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1.4 Population structure and relative kinship

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In our previous study, 500 SRAP primer pairs were developed and 46 primer pairs 10


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were used to analyze C. oleifera clones (same to the ones of the association

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population) genetic diversity

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kinship matrix was calculated using TASSEL version 3.0

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The population structure of the association population was evaluated using

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STRUCTURE

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(http://web.stanford.edu/group/pritchardlab/structure.html)

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Model-admixture model

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run five times across a range of K values from K=2 to K=9, with 10000 Burn-in

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period and 10000 repeats. The highest likelihood with lnP(D) and α value settling

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down to be relatively constant were used for estimating the most likely number of

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subpopulations.

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1.5 Single marker-trait association analysis

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In the association population, all association tests between SNP markers and traits

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were performed, using mixed linear model (MLM) method with 5×104 permutations

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in the software TASSEL version 3.0 48. The MLM can be described as y = SNP + Q +

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kinship + e. In the MLM method, the matrix from STUCTURE software (Q) were

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used to define the population structure, and the kinship matrix were used to evaluate

50.

Based on the SRAP analysis data, The pairwise

version

51

48

and shown in Table S1.

2.3.4

software by

Ancestry

based on the same SRAP analysis data. The program was

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the coancestry coefficients, e is the residual. P-values for all association were

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corrected using Benjamini and Hochberg’s method to control FDR

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dominance (d) to additive (a) effect were calculated for each significant marker to

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quantify the mode of gene action according to the previous study

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tests of significant SNP loci identified in the association population were performed in

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the validation population using a χ2 test by Data Processing System (DPS 14.50)

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software 46. And P-values were corrected using Benjamini and Hochberg’s method to

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control FDR 52.

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1.6 Haplotype-trait association analysis

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The haplotype (a block of linked ordered markers) frequencies of locus genotypes

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were estimated by Haploview version 4.2 54 and the tests of the haplotype association

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with the traits were performed using the software TASSEL version 3.0

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correction for multiple testing was performed using Benjamini and Hochberg’s

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method to control FDR 52.

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1.7 Quantitative RT-PCR (qRT-PCR) testing

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qRT-PCR was performed using single-strand cDNA samples, which were synthesized

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from the total RNA in developing seeds of C. oleifera accessions (ten accessions per 12


52.

The ratios of

40, 53.

Inheritance

48.

A

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particular genotypes ) using PrimeScriptTM RT Master Mix (TaKaRa, Dalian, China).

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The qRT-PCR program and the analysis of relative expression level of genes were

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performed as described by Lin et al 2. The primer pairs (Table S2) were individually

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designed for the CoSAD genes according to the SNP-based association results using

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Primer 5.0 software. The glyceraldehyde-3-phosphate dehydrogenase gene (GAPHD)

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was used as the reference gene 55.

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2. Results

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2.1 Phenotypic analyses of traits distribution and correlations

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We extracted and measured the total OC and seven main kinds of FAs composition,

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which accounted for over 99% of all FAs in Camellia oil. In the association

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population, OC ranged from 128.17 mg/g to 510.26mg/g with mean 362.42mg/g

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(Table S3 and S4). The relative contents of C16:0 and C18:1 ranged from 6.70% to

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12.30% (mean 8.66%) and from 69.10% to 84.70% (mean 78.94%), respectively

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(Table S3 and S4). Descriptive statistics of the trait distributions were presented in

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Table S4. In the validation population, OC ranged from 121.61 mg/g to 447.48mg/g

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with mean 317.93mg/g (Table S5 and S6). The relative contents of C16:0 and C18:1

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ranged from 6.70% to 11.00% (mean 8.65%) and from 68.70% to 85.80% (mean 13



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78.19%), respectively (Table S5 and S6). The descriptive trait-distribution statistics of

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the validation population were showed in Table S6. As expected, the distributions for

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most traits measured in both populations followed an approximately normal

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distribution (Fig. 1 and Fig. S1).

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The OC and FA relative contents showed significant correlations in the

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association population (Table 3 above diagonal). The OC was positively correlated

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with C18:0 (R = 0.4366, P < 0.01) and negatively correlated with C18:2 (R = -0.3406,

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P < 0.01) and C18:3 (R = -0.6806, P < 0.01), which resembled the scenario of

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validation population (Table 3 below diagonal). In addition, OC was significant

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positively correlated with C18:1 and negatively correlated with C16:0 in association

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population (P < 0.01). According to the correlation, the FA content traits were divided

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into two groups. The first group included C16:0, C18:2 and C18:3, and the other

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group included C18:0 and C18:1. In the both groups, the significant positive pairwise

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correlations were observed respectively, while between groups, each one in group1

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showed significant negative pairwise correlations with one in group2 in association

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population (P < 0.01) (Table 3 above diagonal). Similar FA content correlation results

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were observed in the validation population (Table 3 below diagonal). It's worth noting 14


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that C18:1 and C18:2 contents showed significant negative correlations and the

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correlation coefficient (R) were nearly 1, which were 0.9618 and 0.9763 in

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association and validation populations, respectively (Table 3).

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2.2 SNP detection and LD test

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After removing the SNPs with Minimum Allele Frequency (MAF) less than 5%, total

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364 polymorphic sites including two single nucleotide InDels and 362 SNPs (Table

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S7) were detected in the four candidate genes in which two genes for CoSAD and two

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ones for Cofad2, with an average density of one SNP every 21bp (π ranged from

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0.0005 to 0.00739 and θw from 0.0013 to 0.0116). For these polymorphic sites, 67.03%

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were derived from the intron regions and 31.87% from the exon regions, and four

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SNP sites were detected in the 3’ UTR. The polymorphic sites had an average density

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of one SNP every 38.73bp in the exon regions and 9.90bp in the intron regions,

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respectively. In these 362 SNP sites, 53.57% were nucleotide transitions (including 70

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GA and 125 CT) and 45.88% nucleotide transversions (including 35 GT，51

239

AT，48 AC and 33 GC).

240

Pairwise LD between SNP markers were estimated by r2 within the candidate

241

genes (Fig. 2). We showed that the SNPs in LD were in the same gene, and limited 15



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LD of the SNPs within the candidate genes did not extend over the entire gene region

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(Fig. 2A, B, C, D). We further calculated the average decay distance associated with

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LD within the candidate genes, and the results showed that the LD distance decayed

245

quickly with the DNA length increasing. The most of SNPs were in linkage

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equilibrium when the distance of SNPs were over 1.8kb (r2 < 0.3; P < 0.05; Fig. 2E;

247

Table S8). Several loci with the distance over 1.8kb were in significant LD in

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CoSAD2, such as marker pairs SNP6U.2655 - SNP6U.331, SNP6U.3443 -

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SNP6U.891, SNP6U.2744 - SNP6U.331, SNP6U.3443 - SNP6U.958, SNP6U.3410 -

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SNP6U.958, and etc (r2 > 0.4; P < 0.001; Fig. 2E; Table S8). Therefore, the LD

251

between SNPs decayed within the candidate genes in C. oleifera genome, and the

252

SNP markers-based LD association analysis was feasible within the genes.

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2.3 Population structure

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The presence of the population deviations from Hardy-Weinberg proportions, can

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lead to spurious associations and confound association studies. We showed that K=4

256

had the highest likelihood which with the lnP(D) and α value settling down to be

257

relatively constant using software STRUCTURE version 2.3.4. The association

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population could be subdivided to four subpopulations, which were under the 16


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Hardy-Weinberg equilibrium (HWE). The proportions of membership of the samples

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in the four subpopulations were 13.5%, 9.0%, 70.1% and 7.4%, respectively (Fig. 3).

261

The expected heterozygosity between individuals of subpopulation 2 was the highest

262

(0.1002), that of subpopulation 3 was the lowest (0.0506), and that of subpopulation 1

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and 4 were parallel (0.0793 and 0.0714, respectively). In agreement with tests for

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HWE, all Fst values were over 0.50 (the mean Fst = 0.6093) and suggested there were

265

extensive genetic divergence among the four subpopulations. The details of samples

266

estimated membership in every subpopulation were in Table S9.

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2.4 Summary of single-SNP and haplotype based associations

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Single SNP maker-trait associations In total, 2912 (364 SNPs (or InDel) × 8 traits)

269

single-marker association tests were performed with 5×104 permutations using MLM

270

model (Table S10). In all, 132 associations were significant at threshold of P < 0.05

271

(Table S10). After multiple test correction, there were 90 associations were significant

272

with a threshold of Q < 0.05 (Table 4). These loci explained the considerable

273

proportion of the phenotypic variance from 1.87% to 17.93% (Table 4). Of these, 15

274

SNP markers were associated with C16:0 content, 13 ones were associated with

275

C16:1 content. C18:1 and C18:2 had seven significant associations each; ten C18:0 17



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associations, 14 C18:3 associations, and twelve associations respectively with C20:1

277

and OC were observed in the association population (Q < 0.05; Table 4). The 90

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associations represented 63 SNP loci from four genes. Multiple SNP markers were

279

significantly associated with more than one trait, which suggesting these loci had a

280

pleiotropic effect for certain traits (Table 4). The dominant and additive effects of the

281

twelve of 90 marker-trait pairs were calculated. In these twelve marker-trait pairs,

282

there were eight pairs with the mode of gene action which consistent with under- or

283

overdominance (|d/a| > 1.25). The remaining four markers had the mode of gene

284

action that was partially to fully dominant (0.50 < |d/a| < 1.25). And we couldn’t

285

detect the markers with the codominant (additive) gene action mode (|d/a| < 0.50)

286

(Table 5).

287

Haplotype-trait associations In all, 22 haplotypes were identified from four

288

candidate genes by the software Haploview with a significance threshold of P < 0.01

289

(Table S11). Haplotype-based association tests were performed, and no significant

290

association were found between haplotypes and phenotypic traits with a threshold of

291

P < 0.05 and Q < 0.05 (Table 6). With a significance threshold of P < 0.10, six

292

haplotypes from one candidate gene (CoSAD2) were significantly associated with the 18


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five phenotypic traits excluding C16 :0, C18 :1 and C18 :2 contents (Table 6).

294

Multiple test correction analysis reduced this number to only one (Q < 0.10; Table 6).

295

The association of SNP6U.1577 (in this haplotype block) and the C18 :0 content (Q
0.4; P < 0.001).

826

Fig. 3 Population structure of 216 individuals of association population analyzed

827

by the STRUCTURE program. Numbers on the y-axis indicate the membership

828

coefficient. Each bar on the x-axis represents an individual; colored segments within

829

one bar reflect the proportional contributions of each subpopulation to this individual.

830

The color of the bar indicates the four groups identified by the STRUCTURE

831

software (P1 = red, P2 = green, P3 = blue, and P4 = yellow).

832

Fig. 4 Genotypic effect of significant SNPs for traits in both association and

833

validation populations. Genotypic effects of significant (a) SNP 2.A.705 and (b) SNP

834

6U.1577 for C18:0 content, (c) SNP 6U.1031 for C18:1 content, (d) SNP 6U.2366 for

835

C20:1 content, (e) SNP 40U.548 and (f) SNP 6U.505 for OC in association (left) and

836

validation (right) populations, respectively.

837

Fig.5 Relative expression levels for candidate genes and the associated

838

phenotype levels in different groups representing different significant genotypes (the

839

error bars represent +SD). The relative expression levels of CoSAD2 and the 50


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840

associated phenotype levels in different groups based on SNP 6U.1577 genotypes (a),

841

SNP 6U.1031 genotypes (b) and SNP 6U.505 genotypes (c), respectively. The relative

842

expression levels of CoSAD1 and OC in different groups based on SNP 40U.548

843

genotypes (d). Every group involved ten C. oleifera individuals. Relative expression

844

levels of qRT-PCR calculated using GAPDH as the reference gene are shown in the

845

left y-axis. The associated phenotype levels are shown in the right y-axis.

846

51



Fig. 1 The frequency distributions for traits measured in association population. Individual numbers were shown in the right y-axis, and (a) oil content in the kernel, (b) C16:0 content, (c) C16:1 content, (d) C18:0 content, (e) C18:1 content, (f) C18:2 content, (g) C18:3 content, (h) C20:1 content in x-axis, respectively. 191x244mm (300 x 300 DPI)


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Fig. 2 LD levels among pairwise SNPs in CoSAD2 (A), CoSAD1 (B), Cofad2-A (C), Cofad2-B (D) and decay of LD with distance in base pairs between sites in four candidate genes (E). LD decayed within the candidate genes, and several loci pairs with the distance over 1.8kb were in significant LD which were in the same genes, such as (a) SNP6U.2655 - SNP6U.331, (b) SNP6U.3443 - SNP6U.891, (c) SNP6U.2744 - SNP6U.331, (d) SNP6U.3443 - SNP6U.958, (e) SNP6U.3410 - SNP6U.958, and etc (r2 > 0.4; P < 0.001). 220x280mm (300 x 300 DPI)



Fig. 3 Population structure of 216 individuals of association population analyzed by the STRUCTURE program. Numbers on the y-axis indicate the membership coefficient. Each bar on the x-axis represents an individual; colored segments within one bar reflect the proportional contributions of each subpopulation to this individual. The color of the bar indicates the four groups identified by the STRUCTURE software (P1 = red, P2 = green, P3 = blue, and P4 = yellow). 169x56mm (300 x 300 DPI)


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Fig. 4 Genotypic effect of significant SNPs for traits in both association and validation populations. Genotypic effects of significant (a) SNP 2.A.705 and (b) SNP 6U.1577 for C18:0 content, (c) SNP 6U.1031 for C18:1 content, (d) SNP 6U.2366 for C20:1 content, (e) SNP 40U.548 and (f) SNP 6U.505 for OC in association (left) and validation (right) populations, respectively. 155x157mm (300 x 300 DPI)



Fig.5 Relative expression levels for candidate genes and the associated phenotype levels in different groups representing different significant genotypes (the error bars represent +SD). The relative expression levels of CoSAD2 and the associated phenotype levels in different groups based on SNP 6U.1577 genotypes (a), SNP 6U.1031 genotypes (b) and SNP 6U.505 genotypes (c), respectively. The relative expression levels of CoSAD1 and OC in different groups based on SNP 40U.548 genotypes (d). Every group involved ten C. oleifera individuals. Relative expression levels of qRT-PCR calculated using GAPDH as the reference gene are shown in the left y-axis. The associated phenotype levels are shown in the right y-axis.


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LD decayed within genes and six significant SNP- oil traits associations were defected in candidate genes 247x206mm (300 x 300 DPI)


Association Genetics Identifies Single Nucleotide Polymorphisms

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