Breeding for improve nutritional quality traits in carrot
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Breeding for improve nutritional quality traits in carrot
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Breeding for improve nutritional quality traits in carrot
- 2. Scenario of nutritional Security India is home to more than 230 million undernourished people - (FAO Report on- The State of Food Insecurity in the World 2013) Vitamin A deficiency is the leading cause of blindness in children. Thus there is a need to increase vitamin A in the human diet
- 3. Breeding for improve nutritional quality traits in carrot Speaker: Hemant Ghemeray II PhD VSC ID-10908 Seminar Leader Dr. NAVEEN SINGH Principal Scientist Genetics and Plant Breeding
- 4. Outline of the seminar Introduction Nutritive value Target nutritive traits Biochemistry of target trait Biochemical Pathways Genetics of the target nutritive traits Germplasm sources of ways to create a trait variability Breeding methods Conventional methods Biotechnological methods Case study Conclusion
- 5. Why carrot..? Carrot is an important source of pro-vitamin A (carotene) Crops is relatively rich in vitamin and nutrients source Majorly consumed vegetable Spatial distribution (covers higher latitude – lower latitude) Affordability Could reach to marginal's to marginal Could supplement of vitamins( not synthesized in our body) Antioxidants, etc.
- 6. Quality traits in carrot Intrinsic quality attributes Extrinsic quality attributes Sensory attributes Health attributes i. Sweet taste ii. Mild to strong aroma i. Vitamin A ii. Anthocyanin iii. Carotenoids iv. Anthocyanin i. Orange carrot ii. Purple carrot iii. Yellow carrot iv. Red carrot Target quality traits in carrot • Carotenoids • Anthocyanins • Others
- 7. • >455 genera (Apiaceae) Dacus = 20 recognized species •The cultivated species - var. sativum. •Wild species -var. carota.(queen anne lace) +maritimus,major, gummifer, etc. D.capellifolius D.syriticus D.sahaariensis Taxonomy: Species are intercrosssible Carrot (Daucus carota L.) >> Family:Apiaceae>>Angiosperms>> Kingdom:Plantae (P. W. Simon ,2008)
- 8. Edible portion : carrot root /fleshy tap root Carrot root : •Primarily of phleom / cortex and core / xylem • Good quality carrots cortex >>core (‘Coreless’ cultivars =desired) core or xylem phleom or cortex (Just et al ,2003)
- 9. . Western /Carotene carrots: These have orange, yellow roots , white roots(Banga 1960) Eastern/Asiatic carrots: These are often called anthocyanin carrots because or their purple roots and red (Yamaguchi and Sugiyama 1962) Asiatic carrots Western carrots •Afghanistan is considered as centre of diversity •Carrot domestication took differing its paths east and west of central Asia •The genetic improvement of carrot has been an ongoing effort throughout its cultivation and domestication Origin and domestication
- 10. Nutritive value of various carrots genotypes for enhanced nutrition (IARI) Inbred Anthocyanin Total Lycopene TSS Moisture (mg/100g fw) carotenoids (mg/100g ( Brix) per cent (mg/100g fw) fw) 1 2 3 4 5 6 IPC-109 0.19 7.91 6.33 8.41 92.73 IPC-031 0.14 9.27 7.85 7.74 90.82 IPC-085 0.46 7.63 6.02 8.49 93.17 IPC-011 0.21 9.99 8.20 8.22 92.54 IPC-061 0.52 8.10 7.80 8.79 89.42 IPC-118 0.26 8.86 7.57 10.09 92.85 IPC-106 0.39 5.82 4.65 9.07 91.23 IPC-124 0.14 14.46 11.85 9.03 92.48 IPC-039 0.31 5.40 5.48 7.94 91.32 IPC-011 0.25 4.86 2.07 8.35 88.50 IPC-007 0.21 7.77 6.33 7.57 93.91 IPC-004 0.25 7.22 5.65 9.08 90.91 IPC-008 0.31 8.62 7.73 7.93 89.28 IPC-098 0.22 6.16 5.45 8.30 92.99 IPC-123 0.18 6.71 6.16 8.79 92.33 IPC-034 0.23 8.74 7.11 7.93 94.75 IPC-029 0.51 5.76 2.12 7.74 92.98 IPC-053 0.20 5.66 4.91 9.76 92.15 1 2 3 4 5 6 IPC-104 0.31 6.73 2.56 8.90 91.10 IPC Ht-2 0.04 6.91 5.24 9.14 92.47 IPC-116 0.12 5.42 3.41 7.83 92.77 IPC-076 0.17 8.28 6.73 8.62 92.63 IPC-013 0.61 6.52 5.18 7.23 93.28 IPC-055 0.14 5.50 5.17 6.76 92.56 IPC-122 0.19 9.00 8.19 7.23 93.13 IPC-010 0.19 6.61 5.09 7.82 92.42 IPC-001 0.17 9.51 7.31 8.21 92.72 IPC-035 0.13 5.85 4.92 7.39 93.37 IPC-075 0.23 5.18 4.24 7.15 92.24 IPC-126 333.81 1.18 0.50 10.48 89.21 IPC-096 0.25 5.96 5.31 6.87 92.63 IPC-020 4.74 5.87 4.66 8.42 90.55 IPC-105 0.35 8.36 6.96 9.67 90.91 IPC-005 0.36 7.27 7.29 6.70 92.83 IPC-013 0.36 9.77 8.11 8.27 90.58 IPC-030 0.31 6.84 8.93 8.55 87.98 IPC-025 0.18 7.96 9.75 8.71 93.35 IPC-091 0.10 6.62 10.58 8.80 93.39 CD 0.51 2.17 1.48 0.52 1.70 CV (%) 4.82 12.47 15.88 5.57 1.62 (Saha et al. 2016)
- 11. Carrot type Pigments Health benefits Red carrot Lycopene reductions in probabilities of cancer, vascular diseases Orange carrot (hydrocarbon pigments) a- carotene Prevent night blindness and other eye problems. Decreases risk for heart disease and stroke β-carotene White carrot No bigments -does not accumulate any detectable levels of carotenoid pigments Yellow carrot Lutein normal cell growth and cell division. Purple carrot Anthocyninin Antioxidant , improve memory, protect against heart attacks, The carotenoids(C40) and anthocyanin rich carrot *There is positive correlation between colour intensity and total carotenoids
- 12. •The structure was determined by the Nobel prize-winning researcher - Paul Karrer in 1930-31 •It was first isolated frrom roots of carrot and named the substance -"carotin”. •Carotenoid it is light absorbing chromophore •Among carotenoids , β -carotene is the most studied physiologically and nutritionally •Carotenoid biosynthesis pathway is highly conserved in plants •Structural genes has been characterized in terms of sequence , action and location •Colour range of yellow to red and its quantitative composition is affected by QTLs Carotenoids
- 13. Tertiary structure Fig 1: Carotenoids biosynthesis pathway
- 14. Fig 2: Schematic diagram of anthocyanin biosynthesis pathway
- 15. Genetics of carrot pigments Carrot pigments contents is quantitative inheritance in nature (complex genetic factors and environmental factors) (Simon 2002) Major QTL for carrot colour: Y at linkage group 2 and Y2 at linkage group 5 controls most variation White >> yellow, orange (Genes of white phenotype inhibited the synthesis of α and β carotene in F1 progenies) Additional genes: A/L =red carrot Modifier genes :xylem- Io(intense xylem) - O (orange xylem) -rp (reduced pigmentation) *Y inhibits carotene accumulation
- 16. Gene symbolz Character description Gene source Reference Ms-1, Ms-2 Maintenance of male sterility 'Tendersweet' Thompson 1962 Y-1 Differential xylem / phloem carotene levels Miscellaneous T.Kust, 1970 Y-2 Differential xylem / phloem carotene levels Miscellaneous T.Kust, 1970 y Yellow xylem Miscellaneous T.Kust, 1970 O Orange xylem Miscellaneous T.Kust, 1970 lo Intense orange xylem Miscellaneous T.Kust, 1970 y Yellow xylem Miscellaneous T.Kust, 1970 g g = Green petiole, G = Purple petiole 'Tendersweet' Angell and Gabelman 1970 L Lycopene synthesis 'Kintoki' Umiel and Gabelman 1972 A a-Carotene synthesis (may be identical to lo or O) 'Kintoki' Umiel and Gabelman 1972 gls Glabrous seedstalk W-93 Wisconsin inbred Morelock and Hosfield 1976 rs Reducing sugar in root Miscellaneous Freeman and Simon 1983 P-1 Purple root PI 173687 Simon 1996 rp Reduced carotenoid pigmentation W266 Wisconsin inbred Goldman and Breitbach 1996 Genetics of specific trait in carrot
- 17. Orange yellow X Indicating complementary gene action -complex genetic system (polygenic control) of root in carrot; i.e., pigment inhibiting ,enhancing and specific pigment W93 KHN, KOS,KDA X F1 Orange >> Red • In F2 Segregation suggested that involvement of 2 dominant gene •One for accumulation of α- carotene in W93 and another for accumulation of lycopene in red line •Homozygous recessive at both the loci give only β- carotene Inheritance of colour of root
- 18. Genetic resources of carrot-basis for crop improvement 1. Global carrot genepool -5600 accessions (gene bank ) 2. The total carotenoid content ranged from 0 -white to 450 ppm hi-carotene carrots with potential of 950ppm 3. Sugar content varied from 5.1% to 13.6% in European carrot 4. Carotenoid content- European accessions >> Asian accessions (Simon & Pollak 2009) (Baranski et al., 2012)
- 19. 1. Good eating quality 2. Scarlet/orange colour roots 3. Pigments- High carotene or anthocynin content in roots 4. Uniformity in root shape and size 5. Thin and self coloured core in roots 6. Breeding for use purpose 7. Texture 8. High sugar and dry matter in roots Breeding for quality traits
- 20. • Conventional breeding -allows incorporation of favourable genes from easily crossable donors responsible for producing carotenoids or other bioactives but time and resource consuming Breeding methods Identification of germplasm (variation in population) o Anthocyanin: Purple carrot o Beta-carotene: orange carrot,etc Breeding methods: o Introduction :Zeno ,Nantes half long , Imperator, Danvers o Bulk : Pusa kesar as selection from a cross between Nantes and Local Asiatic o Heterosis breeding o Backcross breeding o Line breeding and mass selection
- 21. •Carrot is a biennial crop but it is grown as an annual •Protandry in the flowers promotes outcrossing by insects •Inbreeding results in severe depression •Emasculation is rarely performed for variety production Hybrid production is based on cytoplasmic male sterility Floral biology :
- 22. 1) Brown anthers: anthers dried and deformed (Welch &Grimball, 1947) 2)Petaloid : stamens modified to petals(petaloid is mutation where second whorl of petals exist in place of anther).( Munger, 1953 & Morell, 1970) sources of male sterility Dacus carota ssp. gummifer, maritimus ,Var.tendersweet CMS system in carrots: :
- 23. Pusa Asita : indigenously bred anthocyanin rich carrot variety It contains 154.65 mg /100gm anthocynin. Its roots purple balck coloured. They are not the product of hybridization or genetic engineering, rather, an open- pollinated variety (recurrent selection) approximate marketable yield of 25 – 30 t/ha. . (Kalia ,2008)
- 24. Promising carrot hybrid combination's- roots and cross sections line ×tester Kalia et al., 2009
- 25. Molecular breeding methods: • MAS can be useful to select the traits that are difficult or expensive to measure, exhibit low heritability and express at later stage in development. • Plants selected for one or more (up to 8-10) alleles • Success of MAS is influenced by the relationship between marker and the genes of interest i.e. Gene-assisted selection (GAS) is most successful followed by Linkage disequilibrium-MAS (LD-MAS) Marker assisted selection (MAS) An indirect selection process for traits of interest using linked DNA marker
- 26. CASE STUDY- 1 Objective: To identify the genetic variants linked carotenoid accumulation and root color
- 27. 380 individuals from the third generation of intercrossing of an initial group of 67 cultivars used This group represents a large diversity of cultivated carrot: • Three White (Europe and Middle-east), • Eight yellow (Europe, Central Asia, Asia), • Two red (Asia), • 45 orange (Europe, South & North America,Australia, Madagascar, Asia) • eight purple (Europe & Middle East) Material and methods Background Genetic linkage maps Several have been published Santos and Simon (2004,2007) merged maps for six linkage groups in two populations PCR-based codominant markers Several published, but limited usefulness across unrelated populations
- 28. SNP discovery selection and genotyping -SNP Genotyping- SNP genotyping was carried out by KAS Par • This technology is based on a property competitive allele-specific PCR • A total of 470 SNPs were found over all the 12,351 bp sequences from 17 genes SSR Genotyping- 15 primers Population structure and relatedness Genotyping
- 29. Table 1: Phenotypic variation for carotenoid and color in unstructured population Phytofluene Phytoene Lutein Α-carotene Β-carotene Total Mean 1.436 1.134 3.624 5.900 16.388 28.831 SD 1.822 1.503 2.428 9.739 20.165 33.228 Min 0.000 0.000 0.949 0.014 0.083 1.253 Max 11.440 9.706 16.615 88.076 136.531 254.248 Results & Discussion
- 30. Fig 3: Population STRUCTURE based on 15 SSR markers
- 31. Fig 5: Major role of the carotenoid catabolic gene : Manhattan plots of the K-SNP model for carotenoid content It shows the association of carotenoid contents and color components
- 32. Fig 6: Boxplots of the ZEP-117 alleles: mean and group according to kruskal wallis test Associated compounds were significantly different from each other .This reveals a typical dominant action for this locus.
- 33. Original unstructured population - limiting the risk of bias association Several SNPs and genes associated with carotenoid content and color components. Zeaxanthin epoxydase (ZEP) and phytoene desaturase (PDS) are candidate genes involved in carotenoid accumulation of non-photosynthetic organs Study brings new insights in the understanding of the carotenoid pathway in non-photosynthesis organs Inference
- 34. Objectives To investigate the genetic architecture conditioning anthocyanin pigmentation CASE STUDY- 2
- 35. To investigate the genetic architecture conditioning anthocyanin pigmentation - >>Scored root color visually >>Quantified root anthocyanin pigments ( mapping population) >>Mapped quantitative trait loci (QTL) >> Performed comparative trait mapping with two unrelated populations Background: Informative saturated linkage maps associated with well characterized populations segregating for anthocyanin pigmentation have not been developed.
- 36. Material Fig 7: material shows ultimate source of purple color in 3 mapping population which were varied geographically and phenotypically 2170(N =65) 70349 (N=519) 10117 (N=72)
- 37. • Two dominant loci interact epistatically in the genetic control of root purple pigmentation in the 70349 background. • Single gene model for both 2170 and 10117 populations. Generation Number of progeny Expected seg. ratio X2 Purple Non-purple Total F2 (70349) - gh 279 218 497 9:7 0.003 F2 (70349) -f 12 10 22 9:7 0.03 F2 (2170) PI652188 49 16 65 3:1 0.01 F2 (10117) B7262 59 16 75 3:1 0.54 Table 3: Inheritance of purple root and petiole color Result and Discussion
- 38. Fig 7: Carrot genetic linkage map of the 70349 mapping population The narrow QTL region that influenced Cy3XGG content co-localized with Raa1 in linkage map – supporting that single chromosomal region may control anthocyanin acylation in carrots roots.
- 39. Trait QTL ID Ch Position (cM) LOD value Nearest marker % variation explained RTPE Q1 3 49.1 26.7 K2287 50.5 Q2 1 63.0 3.7 K1664 4.9 Cy3XG Q1 3 50.7 14.8 GSSR-017 26.4 Q2 8 56.1 7.2 K0973 11.3 Q3 2 68.5 6.2 K2669 9.6 Q4 6 0 3.6 K1768 5.3 Cy3XGG Q1 3 27.1 104.7 Raa1 73.3 Q2 3 50.1 84.2 K0627 36.6 Q3 1 74.0 71.4 K1964 23.4 Cy3XSGG Q1 3 44.1 41.6 P3 51.7 Q2 3 25.9 17.5 K1323 13.9 Q3 6 49.0 8.4 K2617 5.7 Cy3XFGG Q1 3 44.1 66.8 P3 59.2 Q2 3 27.1 38.3 K0149 18.9 Q3 4 19.1 13.9 K3591 4.4 Table 4: Summary of QTL for root total pigment estimate (RTPE) and anthocyanin pigments in the 70349 F2 population
- 40. Genetics of anthocyanin pigmentation in carrot Single dominant gene controlling significant anthocyanin pigment accumulation in carrot – Raa1 gene based on – Examination of structure of 5 cynidin glycosides: Available information of anthocyanin biochemistry in carrot. Co-localisation of large QTL for Cy3XGG and Cy3XSGG , Cy3XFGG (map region 3.6cM of CH -3). Combined pigment and linkage analysis data for Cy3XGG also provide evidence that suggests a single dominant gene controlling this trait.
- 41. Fig 8:Comparative mapping of loci on chromosome - in three carrot genetic backgrounds •Data indicate loci controlling anthocyanin pigmentation in roots of diverse genetic backgrounds differs substantially Raa1 –locus controlling anthocyanin acylation P3 –locus controlling purple pigmentation in roots and petiole P1 –locus controlling purple pigmentation
- 42. This study generated the first high resolution gene-derived SNP-based linkage map in the Apiaceae Two regions of chromosome 3 with co-localized QTL for all anthocyanin pigments and for root color largely condition anthocyanin accumulation in carrot roots and leaves Loci controlling root and petiole anthocyanin pigmentation differ across diverse carrot genetic backgrounds Inference
- 43. Carrot- nutritionally important crop Anti oxidants- carotenoids and anthocyanin Large variation for nutritional compounds Carotenoids and anthocyanins biosynthesis and its accumulation- extensively studied evolutionary conserved Varietal differences have been noted for several attributes of carrot root quality With the knowledge of these varietal differences it may be possible to improve carrot through genetic selection to alter quality attributes Conclusion Rich nutrient source
- 44. • Genes identified to be associated with color components and carotenoid content may be useful in marker-assisted selection for carotenoid content enhancement in a breeding program • The set of 20 carotenoid biosynthetic structural genes - tool for the future study of carotenoid biosynthesis in carrot and other species • Study the functionality of these genes by producing the protein products Future outlook
- 45. THANK YOU
Editor's Notes
- 1.Report stated – 2.Report also says – vitamin defeciency is also the major one cause malnutrition 3.But combating with these problems is not so easy as rapid exponential population increase wrosen the problem 4.So need of sustianable breeeding technology is need of the hour to enhancing nutrition and development crops which we consumed daily
- The color of carrots was an important attribute during its domestication as a root crop. Modern carrot researchers continue to study color, and carrot genetic stocks have been developed with not only orange, but also distinctive dark orange, red, yellow and purple color Carrot has been demonstrated to be a sustainable source of dietary provitamin A and other phytonutrients of interest for researchers and consumers.
- 1.Carrot is rich source of carotene a precursor of vitamin A
- 1.The rising awareness of environmental, nutritional and health concerns have led to changes in consumer behaviour, increasingly demanding only highest quality products. 2. Quality of food is a multi-dimentional concept which not only depends on the property of the food but also on the consumer and his perception of the food.
- Basically we see these carrot root as horticultural produce and do necessary improvement to make it rich in nutritional quality and edible.
- Thirty eight inbreds of tropical carrot were evaluated for different quantitative and nutritional traits for four consecutive years (2009-2012) The different quality attributes showed significant differences. Maximum anthocyanin was noted in IPC-126 (333.81 mg/100g) which is a dark purple black carrot inbred. The total carotenoid in IPC-124 (14.46 mg/100g) followed by IPC-11 red (9.99 mg/100g) Orange roots contained on an average 6.78 mg/100g of carotenoid with maximum in IPC-13 orange (9.77 mg/100g), whereas black carrot had minimum total carotenoids (1.18 mg/100g) The lycopene content ranged from 2.07 mg/100g (IPC-11 orange) to 11.85 mg/100g (IPC- 124).
- normal cell growth and cell division. DNA replication requires the presence of vitamin A to function properly. Antioxidant ,block a number of harmful chemical reactions. The visual assesment and selection are generally applicable upto 115ppm total carotenoids .
- Total carotenoids range from 80 ppm to 120 ppm
- Depending on the species, all carotenoid biosynthetic genes may be involved in the genetic basis of carotenoid content and are therefore meaningful candidate genes . In some species, engineering the pathway using biosynthetic genes is now possible for crop enhancement of the carotenoid content. Golden Rice is such an example of metabolic pathway engineering for quality enhancement. read for golden rice – Two major loci Y and Y2 governing the orange intensity of xylem/phloem were identified . The Y locus may block the synthesis of carotene and xanthophyll, whereas the Y2 locus determines the carotene accumulation but not the xanthophyll one. A path analysis showed that phytoene accumulation may be one key step limiting carotenoid accumulation in white roots [9]. This was confirmed by turned a white rooted carrot in orange by overexpressing a phytoene synthase gene
- Genetic studies dealing with carotenoid accumulation in carrot roots are not entirely conclusive since significant environmental and developmental influences have been observed for this trait. For example, low temperature during the growing season can lead to slower maturing carrots that usually contain less carotene. In addition, the total amount and relative proportion of individual carotenoid pigments varies with specific genetic by environment interactions. The cultivar ranking, however, was found to be quite stable in a group of genetic materials evaluated across distinct years and locations.
- A collection of naturally occurring single-locus mutations affecting carotenoid accumulation has been identified in carrot. They include dominant alleles such as A (α-carotene synthesis), Io (intense orange xylem, which may be an allelic form of A), L (lycopene synthesis), O (orange xylem, which may also be an allelic form of A) as well as one recessive allele y (yellow xylem). Three dominant loci named Y, Y1, and Y2 control differential distribution of α- and β-carotene (xylem/phloem carotene levels). The mutation Y2 controls low carotene content of the storage root xylem (‘core’) in high carotene orange backgrounds. AFLP molecular markers for Y2 in carrot have been successfully converted to a PCR-based, codominant marker and can now be employed as a tool in marker-assisted selection.
- So all genes that enhances the cariotent content is reccessive Root shape: Governed by three genes D,N,P Long or Desi: Long and tapay, D-N-P. Eg. Pusa Desi. •Cylindrical type: Cylindrical, dd, nn, p. Eg. Nantes. •Chanteny type: Obvate root,dd,N-,Pp. Eg. Red variety Inheritance studies indicated that carotenoid type and amount (with color range from white to orange) are controlled by at least three genes. Degree of orange color intensity seems to be a typical polygenic trait. Gene action studies for β-carotene content indicated additive and dominance effects as well as additive × dominance and dominance × dominance interactions as being significant. No indication of overdominance was obtained so far and only partial degree of dominance was observed for β-carotene content. Progressive and continuous gains observed for total carotenoid concentration in root via recurrent selection is a clear indication that
- 3 way hybrid – to minimise the IBD Petalod 2 dominant nuclear gene - stable in india Ba – 2 recessive nuclear gene – not stable in india( stable in europe) 3-way crosses, (AxB)xC. Temperate and sub-ropical. Most breeding efforts are on temperate types because of their higher value and larger market share. Cultivars of one class do not perform well in regions outside their range of adaptation. Sub-tropical types include Kuroda, Brasilia, and Tropical Nantes
- The aim of this study was to investigate the implication of biosynthetic genes in carrot root carotenoid content and related color traits using a broad unstructured population in a candidate-gene association approach. This work will offer new insights in the global understanding of the carotenoid biosynthetic pathway in carrot. This will allow us to identify favorable alleles with associated markers usable in marker-assisted selection (MAS) for product quality enhancement. Genetic variants linked to carotenoids done by association mapping and approach is candidate gene approach Candidate gene - approach to conducting genetic association studies focuses on associations between genetic variation within pre-specified genes of interest and phenotypes or disease states. This is in contrast to genome-wide association studies (GWAS), which scan the entire genome for common genetic variation. Candidate genes are most often selected for study based on a priori knowledge of the gene's biological functional impact on the trait or disease in question Genetic association- is when one or more genotypes within a population co-occur with a phenotypic trait more often than would be expected by chance occurrence. Studies of genetic association aim to test whether single-locus alleles or genotype frequencies (or more generally, multilocus haplotype frequencies) differ between two groups of individuals (usually diseased subjects and healthy controls) Association between genetic polymorphisms occurs when there is non-random association of their alleles as a result of their proximity on the same chromosome; this is known as genetic linkage. Genetic association studies are performed to determine whether a genetic variant is associated with a disease or trait: if association is present, a particular allele, genotype or haplotype of a polymorphism or polymorphisms will be seen more often than expected by chance in an individual carrying the trait. Thus, a person carrying one or two copies of a high-risk variant is at increased risk of developing the associated disease or having the associated trait. Why unstructured population-Population stratification can be a problem for association studies, such as case-control studies, where the association could be found due to the underlying structure of the population and not a carotenoid associated locus. Also the real trait causing locus might not be found in the study if the locus is less prevalent in the population where the case subjects are chosen.
- SSR Genotyping- For SSR markers, 15 primers used in [35] were chosen regarding to their genome coverage and reproducibility [50]. PCR reactions, capillary electrophoresis and fragment sizing were identical as in [35] The basic cause of population stratification -is nonrandom mating between groups, often due to their physical separation (e.g., for populations of African and European descent) followed by genetic drift of allele frequencies in each group. Population stratification was first investigated on SSR dataset with the Bayesian modelbased STRUCTURE software Population stratification was also studied by PCA analysis by using SNP dataset on TASSEL software In order to study the relatedness between individuals, two Kinship matrixes were calculated by using TASSEL software based on SSR (K-SSR) markers and SNP (K-SNP) markers respectively Haplotype- is (haploid genotype) a group of genes in an organism that are inherited together from a single parent. Set of single-nucleotide polymorphisms (SNPs) on one chromosome that tend to always occur together (i.e., that are associated statistically). It is thought that identifying these statistical associations and few alleles of a specific haplotype sequence can facilitate identifying all other such polymorphic sites that are nearby on the chromosome. Such information is critical for investigating the genetics of common carotenoids Haplotype-tagging SNP - is a representative single nucleotide polymorphism (SNP) in a region of the genome with high linkage disequilibrium that represents a group of SNPs called a haplotype. It is possible to identify genetic variation and association to phenotypes without genotyping every SNP in a chromosomal region. This reduces the expense and time of mapping genome areas associated with disease, since it eliminates the need to study every individual SNP. Tag SNPs are useful in whole-genome SNP association studies in which hundreds of thousands of SNPs across the entire genome are genotyped. SSR Genotyping- SSR genotyping involves the use of simple sequence repeats (SSRs) as DNA markers. SSRs contain repeats of a motif sequence 1–6 bp in length. Due to this structure SSRs frequently undergo mutations, mainly due to DNA polymerase errors, which involve the addition or subtraction of a repeat unit. Hence, SSR sequences are highly polymorphic and may be readily used for detection of allelic variation within populations. SSR genotyping involves the design of DNA-based primers to amplify SSR sequences from extracted genomic DNA, followed by amplification of the SSR repeat region using polymerase chain reaction, and subsequent visualization of the resulting DNA products, usually using gel electrophoresis. Population structure – Relatedness-
- On average-b-carotene represented almost half of total carotenoid content and a-carotene represented about the third of b-carotene content (Table 1). Lutein- content was relatively low as well as precursor compounds like phytoene and phytofluene. The unstructured population exhibited a large variation for all carotenoid compounds as shown by the high standard deviation Color components were measured for epidermis, secondary phloem and secondary xylem. Phenotypic variations were quite similar between tissues (Table 3).
- Population stratification (or population structure) is the presence of a systematic difference in allele frequencies between subpopulations in a population, possibly due to different ancestry, especially in the context of association studies. As they can lead to false positive detection during association annalysis . Daucus carota L. genetic resources are known to be structured into two distinct genetic groups according to their geographical origin. Moreover carotenoid content pattern is closely linked to these genetic groups: cultivars with high lycopene content belong mostly to one genetic group In order to overcome the structure bias, we have created a specific unstructured population with a broad genetic basis to perform an association mapping study for carrot root carotenoid content. Bayesian model STRUCTURE software infer distinct populations = all these shows unstructured in the population= no bias All 15 SSR markers were polymorphic and 132 alleles were identified with a mean of 8.8 alleles per locus. Population stratification was first investigated with STRUCTURE based on SSR markers. LnP (K) plot (Fig. 4A) did not reach a plateau as expected in the presence of structure in the sample. The number of genetic groups was also investigated with the Evanno’s method [51].As shown on Fig. 2B, the most probable K was 2, 3 or 5 As shown on Fig. 2B, the most probable K was 2, 3 or 5. However, as shown in Fig. 2 (C, D, E) all individuals were admixed and none of them was clearly assigned to one group. At least the proportion of samples assigned to each group was roughly symmetric (*1/K). All these elements showed an absence of structure in the population. This conclusion is reinforced by the principal component analysis performed with SNP data (Fig. 3), in which no group was clearly defined.
- With the K-SNP model, 93 SNPs were tested against 21 traits. Among the 1953 markertrait pairs, 23 significant associations were found with a Bonferroni corrected threshold of 5,3×10-5 (Fig. 6). ZEP is one of the major steps in the carotenoid pathway. Nevertheless, carotenoid accumulation in various organs is known to be the result of biosynthesis, degradation and storage [4,8]. As b-carotene, phytoene and phytofluene were highly and positively correlated, a high level of b-carotene was often associated with a high level of precursors phytoene and phytofluene. It also seems that the zeaxanthin epoxydase gene may drive the biosynthesis pathway towards the b-branch. Two SNPs (ZEP-117 and ZEP-361) in the zeaxanthin epoxydase gene were associated with total carotenoids (R2ZEP-117 = 0.21), b-carotene (R2ZEP-117 = 0.22), phytoene (R2ZEP-117 = 0.22) and phytofluene (R2ZEP-117 = 0.23) content. These two SNPs were in high LD (r2 = 1) and therefore redundant. These SNPs were located in a non-coding region As the two polymorphisms associated with traits were in a non-coding region, we were unable to detect the causal polymorphism of the phenotypic variation. One polymorphism in the carotenoid isomerase gene (CRTISO) was associated with total carotenoids, b-carotene and a-carotene. At least one SNP in the plastid terminal oxidase (PTOX) – a cofactor of the phytoene desaturase – was associated with a-carotene (Fig. 5). No association was detected between the Y2 related marker and carotenoid content. A Manhattan plot - is a type of scatter plot, usually used to display data with a large number of data-points - many of non-zero amplitude, and with a distribution of higher-magnitude values, for instance in genome-wide association studies (GWAS).[1] In GWAS Manhattan plots, genomic coordinates are displayed along the X-axis, with the negative logarithm of the association P-value for each single nucleotide polymorphism (SNP) displayed on the Y-axis, meaning that each dot on the Manhattan plot signifies a SNP. Because the strongest associations have the smallest P-values (e.g., 10−15), their negative logarithms will be the greatest
- Fig. 6 shows the distribution of carotenoid content for each allele of the ZEP-117 SNP (Results were similar for the ZEP-361 SNP, data not shown). For all associated compounds, C:C, C:T and T:T genotype means were significantly different from each other (p < 0.05, Kruskal-Wallis test). This reveals a typical dominant action for this locus.
- They identified several SNPs and genes associated with carotenoid content and color components. Our results bring evidence that zeaxanthin epoxydase and phytoene desaturase are candidate genes involved in carotenoid accumulation of non-photosynthetic organs. Our study brings new insight into the carotenoid pathway functioning by stressing out two major steps in carotenoid metabolism and catabolism in a storage organ. Functional validation and dissection of the regulation of ZEP expression may clarify the mechanisms involved in carotenoid accumulation. Clarification of the involvement of the PTOX has also to be investigated. A mechanism explaining both the accumulation of xanthophylls and the pathway orientation towards the a-branch as well as lutein accumulation still remains to be specified. However, the genes identified in this study as associated with color components and carotenoid content may be useful in marker-assisted selection for carotenoid content enhancement in a breeding program.
- Background: Purple carrots accumulate large quantities of anthocyanins in their roots and leaves. These flavonoid pigments possess antioxidant activity and are implicated in providing health benefits. Informative, saturated linkage maps associated with well characterized populations segregating for anthocyanin pigmentation have not been developed. To investigate the genetic architecture conditioning anthocyanin pigmentation we- scored root color visually, quantified root anthocyanin pigments by high performance liquid chromatography in segregating F2, F3 and F4generations of a mapping population, mapped quantitative trait loci (QTL) onto a dense gene-derived single nucleotide polymorphism (SNP)-based linkage map, and performed comparative trait mapping with two unrelated populations
- Key words :(HPLC)high performance liquid chromatography
- Inheritance of purple pigmentation was studied in F2, F3 and F4 families derived from an initial cross between P4201 and B6320. P4201 is an inbred line with purple outer phloem and yellow xylem storage roots and purple leaves that was derived from a cross between inbred P9547 (with purple xylem and phloem rootcolor derived from Central Anatolia) and B2566 (an inbred with orange root color from diverse European sources). B6320 is an inbred with orange roots and green petioles derived from the European open-pollinated cultivars Nantes and Camberly. A single F1 plant with purple root outer phloem and yellow xylem, and purple leaves, was self-pollinated to produce the F2 population 70349 (N = 519), which was used for genetic mapping studies. For phenotyping, plants of the F2 population were grown in pots under greenhouse conditions in2007. After phenotyping as described below, roots were vernalized at 1–2°C, planted at the University of Wisconsin West Madison Agricultural Research Station (WMARS), and individual plants were self-pollinated to produce F3 families. A subset of the F2 and the F3 families were field-grown at El Centro, California, in 2009, and phenotyped for root pigmentation. Individual F3 plants underwent another cycle of self-pollination and their F4 progenies were grown in Madison-WI and phenotyped in 2012. For comparison purposes, linkage analyses were also performed in two mapping populations unrelated to population 70349 but also segregating for root and petiole purple pigmentation. Population 2170 was an F3 family (N = 65) derived from a cross between a purple rooted carrot with purple leaves derived from an intercross between PI652188 (a purple carrot from China, and the ultimate purple source in 2170) and PI326011,an orange-rooted European carrot with green leaves. An F2 plant of this family with the same phenotype as the purple parent was self-pollinated to generate the F3 family evaluated. The other mapping population, 10117, was an F2 family (N = 72) derived from a cross between B1896 (a true-breeding inbred with yellow roots derived from a cross between PI173687, a population from eastern Turkey segregating for presence or absence of purple root color) and B493, an inbred with orange roots and green petioles derived from diverse European sources) and B7262 an inbred with purple outer phloem and orange inner phloem and xylem, and purple leaves from the same cross as B1896).
- Purple petiole pigmentation was conditioned by a single dominant gene that co-segregates with one of the genes conditioning root pigmentation
- In gene mapping- any sequence feature that can be faithfully distinguished from the two parents can be used as a genetic marker. A quantitative trait locus (QTL) is a section of DNA (the locus) which correlates with variation in a phenotype (the quantitative trait).[1] Usually the QTL is linked to, or contains, the genes which control that phenotype. QTLs are mapped by identifying which molecular markers (such as SNPs or AFLPs) correlate with an observed trait. This is often an early step in identifying and sequencing the actual genes that cause the trait variation. In total, 15 QTL were mapped onto the carrot linkage map (Figure 10). Consistent with the two-gene model observed for root purple color segregation in F2- F4 families, two QTL were detected for RTPE on chromosomes 3 and 1. The QTL in chromosome 3 had a strong statistical support (LOD = 26.7) and the largest effect on phenotype, explaining 50.5% of the observed variation. The support interval for this large-effect QTL was delimited within a 1.4 cM map region. The other RTPE QTL, located in chromosome 1, had less statistical support (LOD = 3.7) and only accounted for 4.9% of the variation, and its support interval covered a large region (28 cM) of chromosome 1. The locus controlling anthocyanin pigmentation in leaves -mapped to CH3 and was tightly linked (at 1.9 cM) to marker K2309 P3 mapped within the 43.1-55.1 cM region harboring four QTL for root anthocyanins, suggesting that this 12 cM region harbors the genetic determinants conditioning both root and petiole pigmentation The 24.1-27.7 cM region of chromosome 3 harbors overlapping QTL for Cy3XSGG, Cy3XFGG and Cy3XGG (Fig. 2 and Table 5). The Cy3XGG QTL had the highest statistical support (LOD = 104.7) and the largest phenotypic effect (73.3%) of all 15 mapped QTL. In addition, the support interval of Cy3XGG overlapped the shortest map distance (0.7 cM) of all QTL. Interestingly, the narrow QTL region that influenced Cy3XGG content co-localized with Raa1 in the linkage map, supporting the idea that a single chromosomal region may control anthocyanin acylation in carrot roots.
- Lod> =good r2 (phenotypic variation ) > 10 - major QTL
- Proposed scheme- an inverse balance between the acylated and non- acylated with the balance modulated by the activity of acyltrarsferase a strong negetaive corelation found between both forms acylation of cy3XGG by acyltransferase and cause shift from non acylated to acylated forms Co localization of a large-effect QTL for Cy3XGG and two QTL for the major acylated anthocyanins (Cy3XSGG and Cy3XFGG) in a very narrow map region (3.6 cM) of chromosome 3, not only reinforces the notion that Cy3XGG is the chemical substrate for acylation, giving rise to Cy3XSGG and Cy3XFGG, but also suggests that this region is largely responsible for the genetic control of root anthocyanin acylation.
- Petiole anthocyanin pigmentation segregated as a simply-inherited trait in populations 70349 and 2170, and was mapped for the first time. Furthermore, in this study, we present clear evidence for pleiotropy at a single gene controlling both petiole and root pigmentation in these two populations. This is in contrast to a previous study which found, in a population not included in this study, that root pigmentation and petiole pigmentation were controlled by different genes .