A total of 21 Gb of Roche/454 Titanium shotgun and matepair reads and 3.3 Gb of Sanger paired-end reads, including ~200,000 BAC and fosmid end sequence pairs, were generated from the ‘Heinz 1706’ inbred line (Supplementary Sections 1.1-1.7 ), assembled using both Newbler and CABOG and integrated into a single assembly (Supplementary Sections 1.17-1.18 ). The scaffolds were anchored using two BAC-based physical maps, one high density genetic map, overgo hybridization and genome-wide BAC FISH (Supplementary Sections 1.8-1.16 and 1.19 ). Over 99.9% of BAC/fosmid end pairs mapped consistently on the assembly and over 98% of EST sequences could be aligned to the assembly (Supplementary Section 1.20 ). Chloroplast genome insertions in the nuclear genome were validated using a matepair method and the flanking regions were identified (Supplementary Sections 1.22-1.24 ). Annotation was carried out using a pipeline based on EuGene that integrates de novo gene prediction, RNA-Seq alignment and rich function annotation (Supplementary Section 2 ). To facilitate interspecies comparison, the potato genome was re-annotated using the same pipeline. LTR retrotransposons were detected de novo with the LTR-STRUC program and dated by the sequence divergence between left and right solo LTR (Supplementary Section 2.10 ). The genome of S. pimpinellifolium was sequenced to 40x depth using Illumina paired end reads and assembled using ABySS (Supplementary Section 3 ). The tomato and potato genomes were aligned using LASTZ (Supplementary Section 4.1 ). Identification of triplicated regions was done using BLASTP, in-house generated scripts and three way comparisons between tomato, potato and S. pimpinellifolium using MCscan (Supplementary Sections 4.2-4.4 ). Specific gene families/groups (genes for ascorbate, carotenoid and jasmonate biosynthesis, cytochrome P450s, genes controlling cell wall architecture, hormonal and transcriptional regulators, resistance genes) were subjected to expert curation/analysis, (Supplementary Section 5 ). PHYML and MEGA were used to reconstruct phylogenetic trees and MCSCAN was used to infer gene collinearity (Supplementary Section 5.2 ).
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Carotenoids
Carotenoids
Carotenoids are a diverse group of natural pigments found in plants, algae, and photosynthetic bacteria.
These lipid-soluble molecules play crucial roles in photosynthesis, photoprotection, and antioxidant defense.
Carotenoids can be divided into two main classes: carotenes (e.g., beta-carotene) and xanthophylls (e.g., lutein, zeaxanthin).
They are widely studied for their potential health benefits, including their ability to scavenge free radicals, support eye health, and potentially reduce the risk of certain chronic diseases.
Reserach into the optimal use of carotenoins is an active area of investigation, with PubCompare.ai offering a powerful AI-driven platform to streamline this process and enhance the reproducability and accuracy of carotenoid studies.
These lipid-soluble molecules play crucial roles in photosynthesis, photoprotection, and antioxidant defense.
Carotenoids can be divided into two main classes: carotenes (e.g., beta-carotene) and xanthophylls (e.g., lutein, zeaxanthin).
They are widely studied for their potential health benefits, including their ability to scavenge free radicals, support eye health, and potentially reduce the risk of certain chronic diseases.
Reserach into the optimal use of carotenoins is an active area of investigation, with PubCompare.ai offering a powerful AI-driven platform to streamline this process and enhance the reproducability and accuracy of carotenoid studies.
Most cited protocols related to «Carotenoids»
Anabolism
Carotenoids
Cell Wall
Chromosome Mapping
Crossbreeding
Cytochrome P450
Fishes
Genes
Genome
Genome, Chloroplast
Insertion Mutation
jasmonate
Lycopersicon esculentum
Microtubule-Associated Proteins
Physical Examination
Retrotransposons
RNA-Seq
Solanum tuberosum
Titanium
Transcription, Genetic
We used a semi-quantitative FFQ of 101 food items to assess the usual daily intake of foods and nutrients (available at: http://bibliodieta.umh.es/files/2011/07/CFA101.pdf ). The FFQ was a modified version from a previous FFQ based on the Harvard questionnaire [15 (link)], which we developed and validated using four 1-week dietary records in an adult population in Valencia. The validity correlation coefficients (adjusted for energy intake) ranged from 0.27 for folate intake to 0.67 for calcium intake (average 0.47), and the reproducibility correlation coefficient s ranged from 0.30 for carotene intake to 0.65 for calcium intake (average 0.40) [16 ,17 (link)]; this is a similar range to other established diet questionnaires [3 ,4 (link)]. For the dietary assessment of pregnant women in the INMA cohort study, we added additional food items in the FFQ in order to capture the major sources of the most relevant nutrients, including specific carotenoids.
Participants in the study were asked twice during pregnancy how often, on average, they had consumed each food item over two periods of several months. The first period covered the time from the last menstruation to the first prenatal visit that occurred between the 10–13 weeks of pregnancy; the second period was the time between the first visit and the second one between weeks 28–32 of gestation. Serving sizes were specified for each food item in the FFQ. The questionnaire had nine possible responses, ranging from ‘never or less than once per month’ to ‘six or more per day’. Additionally, we asked whether study participants followed special diets.
Nutrient values were primarily obtained from the food composition tables of the US Department of Agriculture publications as well as other published sources for Spanish foods and portion sizes [18 ,19 ]. In order to obtain average daily nutrient intakes from diet for each individual, we multiplied the frequency of use for each food by the nutrient composition of the portion/serving size specified on the FFQ and added the results across all foods. For those nutrients often used in supplements during pregnancy such as folate, vitamin C and vitamin B12, the total daily nutrient intake was estimated by adding the average daily intake from supplements and the usual daily nutrient intake from the FFQ. In order to convert folic acid intake from supplements to dietary folate, we used the equivalence of 1 mcg of folate in the diet equals to 0.6 mcg of folic acid from supplements [20 (link)]. We estimated the mean daily consumption for 17 foods and food groups by grouping the intake of specific foods in the FFQ (Table1 ).
Participants in the study were asked twice during pregnancy how often, on average, they had consumed each food item over two periods of several months. The first period covered the time from the last menstruation to the first prenatal visit that occurred between the 10–13 weeks of pregnancy; the second period was the time between the first visit and the second one between weeks 28–32 of gestation. Serving sizes were specified for each food item in the FFQ. The questionnaire had nine possible responses, ranging from ‘never or less than once per month’ to ‘six or more per day’. Additionally, we asked whether study participants followed special diets.
Nutrient values were primarily obtained from the food composition tables of the US Department of Agriculture publications as well as other published sources for Spanish foods and portion sizes [18 ,19 ]. In order to obtain average daily nutrient intakes from diet for each individual, we multiplied the frequency of use for each food by the nutrient composition of the portion/serving size specified on the FFQ and added the results across all foods. For those nutrients often used in supplements during pregnancy such as folate, vitamin C and vitamin B12, the total daily nutrient intake was estimated by adding the average daily intake from supplements and the usual daily nutrient intake from the FFQ. In order to convert folic acid intake from supplements to dietary folate, we used the equivalence of 1 mcg of folate in the diet equals to 0.6 mcg of folic acid from supplements [20 (link)]. We estimated the mean daily consumption for 17 foods and food groups by grouping the intake of specific foods in the FFQ (Table
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A-101
Adult
Ascorbic Acid
Calcium, Dietary
Carotene
Carotenoids
Cobalamins
Diet
Dietary Supplements
Eating
Folate
Folic Acid
Food
Hispanic or Latino
Menstruation
Nutrient Intake
Nutrients
Pregnancy
Pregnant Women
Antioxidants
Ascorbic Acid
Biological Factors
Biological Markers
BLOOD
Carotenoids
Dietary Supplements
Estradiol
F2-Isoprostanes
Hormones
Menstrual Cycle
Oxidative Stress
Pharmaceutical Preparations
Progesterone
Reproduction
Retinoids
Serum
Sex Hormone-Binding Globulin
Tocopherol
Vitamins
Woman
Dietary intake was assessed using a semi-quantitative food-frequency questionnaire (FFQ) with 126 items, adapted and validated for this population [55 (link)]. The FFQ, based on the National Cancer Institute-Block FFQ format, was revised to include appropriate foods and portion sizes, and was shown to capture intakes reported in 24-hour recalls more accurately than the original questionnaire, both in total nutrient estimates and in ranking of individuals [55 (link)]. This FFQ has been validated against plasma carotenoids [56 (link)], vitamin E [57 (link)] and vitamin B12 [58 (link)] in Hispanics aged ≥ 60 years. Those with energy intakes < 600 or > 4800 kilocalories and/or > 10 questions blank on the FFQ were excluded from dietary analyses.
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Carotenoids
Cobalamins
Diet
Food
Hispanics
Mental Recall
Nutrients
Plasma
Vitamin E
To analyze the chlorophylls and total carotenoids content in the transgenic lines, 200 mg of leaves homogenized in liquid nitrogen was extracted twice with 2 ml of 100% methanol. Extraction was carried out at room temperature for 1 h in the dark with constant shaking. Methanol fraction from both extracts was pooled and diluted 5 folds before their absorbance values at wavelengths 666 nm, 653 nm and 470 nm were determined using an Infinite M2000 microplate reader (Tecan, Switzerland). The relative amount of chlorophyll a, chlorophyll b and total carotenoids were calculated from their absorbance values using previously reported formula [46 (link)].
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Animals, Transgenic
Carotenoids
Chlorophyll
Chlorophyll A
chlorophyll b
Methanol
Nitrogen
Most recents protocols related to «Carotenoids»
The contents of chlorophyll, carotenoid, and anthocyanin of the QHP, ZSY, and L2025 leaves were determined based on a previously described method (Tian et al., 2021b (link)). Fresh leaves were used to measure total chlorophyll content based on the method described by Wu et al. (2020) (link). Leaf tissue (0.1 g) was ground into powder and extracted in 5 mL of 95% ethanol at 50°C for 2 h. The mixture was vortexed and centrifuged at 5,000 rpm for 5 min. The absorbance of the supernatant was measured at 470, 649, and 665 nm using an ultraviolet–visible spectrophotometer (Wu et al., 2020 (link); Zhuang et al., 2021b (link)). Fresh leaves were used to determine the carotenoid content in accordance with the method used by (Gao et al., 2021 (link)). Approximately 100 mg of fresh leaf tissue were cut into pieces with scissors, and extracted in 10 mL of 1% (v/v) HCl–ethanol at 60°C for 30 min. The mixture was vortexed and centrifuged at 13,000 × g for 5 min. The absorbance of the supernatant was measured at 530, 620, and 650 nm using an ultraviolet-visible spectrophotometer (Gao et al., 2021 (link)).
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Anthocyanins
Carotenoids
Chlorophyll
Ethanol
Plant Leaves
Powder
Tissues
QHP with bright purple leaves, L2025 with green leaves, and ZSY with bright purple and green leaves were planted in the experimental field of Nanjing Botanical Garden, Memorial Sun Yat-Sen (32°3′N, 118°49′E). The fourth and fifth fully expanded mature leaves were collected from two-year-old seedlings of QHP (P) and L2025 (G), respectively. Fully expanded purple leaves (F_P) and green leaves (F_G) from two-year-old ZSY seedlings were also harvested. The leaf samples were immediately frozen in liquid nitrogen and stored at −80°C until use for the determination of chlorophyll, carotenoid, and anthocyanin contents, metabolite detection, RNA-seq, and qRT-PCR analyses. Three independent biological replicates were used for each experiment.
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Anthocyanins
Biopharmaceuticals
Carotenoids
Chlorophyll
Freezing
Nitrogen
Plant Leaves
RNA-Seq
Seedlings
The well-stirred egg yolk (0.5 g) was added to acetone (10 ml), vortexed for 15 min and then centrifuged at 4000 rpm for 15 min. The absorbance value of the supernatant at 475 nm was determined by UV–visible spectrophotometer. Carotenoids content was calculated according to the following formula:
where A is absorbance value at 475 nm; V is the volume of acetone being added, ml; 0.16 is molar extinction coefficient of carotene; W is weight of the egg yolk used in the measurement process, g.
where A is absorbance value at 475 nm; V is the volume of acetone being added, ml; 0.16 is molar extinction coefficient of carotene; W is weight of the egg yolk used in the measurement process, g.
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Acetone
Carotene
Carotenoids
Extinction, Psychological
Molar
Yolks, Egg
Carotenoids content in Rhodotorula glutinis was determined by the hydrochloride acid thermal breakage method, as follows: the liquid culture (30 ml) was centrifuged (4,000 rpm, 15 min). 3 M HCl (30 ml) was added to the yeast cell pellet, shaken for 45 min, and then heated at 100°C for 5 min. The mixture was cooled and centrifuged (4,000 rpm, 15 min). The sterilized water (30 ml) was added to the yeast cell pellet. And the above process was repeated three times. Acetone (10 ml) was added to the yeast cell pellet, shaken for 1 h and centrifuged (4,000 rpm, 15 min) to obtain carotenoids extracts. The absorbance of the carotenoids extracts was measured at 475 nm. Formula for calculating the carotenoids content:
where Wc is carotenoids content of fermentation broth, μg/g; Amax is absorbance at 475 nm; D is dilution of sample; V is organic solvent volume for pigment extraction, ml; m is dry yeast mass, g; 0.16 is molar extinction coefficient of carotenoids.
where Wc is carotenoids content of fermentation broth, μg/g; Amax is absorbance at 475 nm; D is dilution of sample; V is organic solvent volume for pigment extraction, ml; m is dry yeast mass, g; 0.16 is molar extinction coefficient of carotenoids.
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Acetone
Acids
Carotenoids
Cells
Extinction, Psychological
Fermentation
Molar
Organic Pigments
Rhodotorula glutinis
Solvents
Technique, Dilution
Yeast, Dried
The medium was prepared according to factors and levels as shown in Supplementary Table 1 and R. glutinis SRY grown. The effects of initial pH value, glucose content, manganese ion content, copper ion content, magnesium ion content, zinc ion content and ferrous iron ion content on SRY biomass, carotenoids content and viable yeast count were investigated.
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Carotenoids
Copper
Glucose
Iron
Magnesium
Manganese
Rhodotorula glutinis
Yeast, Dried
Zinc
Top products related to «Carotenoids»
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β-carotene is a carotenoid compound commonly used in laboratory research and product development. It functions as a provitamin, which means it can be converted into vitamin A in the body. β-carotene is a natural colorant and antioxidant with potential applications in various industries.
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The UV-1800 is a UV-Visible spectrophotometer manufactured by Shimadzu. It is designed to measure the absorbance or transmittance of light in the ultraviolet and visible wavelength regions. The UV-1800 can be used to analyze the concentration and purity of various samples, such as organic compounds, proteins, and DNA.
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Lutein is a natural carotenoid compound found in various plants, fruits, and vegetables. It is a yellow pigment that plays a crucial role in the human eye, contributing to the health and function of the macula, the part of the eye responsible for central vision. Lutein is often used in laboratory settings for research and analysis related to vision and eye health.
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The C30 carotenoid column is a type of laboratory equipment used for the separation and analysis of carotenoid compounds. It is designed to provide efficient and accurate separation of a wide range of carotenoids, including those found in food, plants, and biological samples. The column features a specialized stationary phase that allows for the selective retention and separation of carotenoid compounds based on their structural differences.
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The Shimadzu UV-1800 spectrophotometer is a laboratory instrument used for the quantitative analysis of various samples. It measures the absorption of light by a sample across the ultraviolet and visible light spectrum. The instrument is designed to provide accurate and reliable results for a wide range of applications.
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Zeaxanthin is a carotenoid compound found in nature. It is a natural pigment that can be extracted and purified for use in various laboratory applications. Zeaxanthin exhibits certain optical and chemical properties that make it suitable for use in specialized lab equipment and research settings.
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The C30 column is a chromatography column designed for the separation and purification of a wide range of organic compounds. It features a stationary phase made of a highly cross-linked polymer material, providing efficient and reliable separation performance.
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The LI-6400 is a portable photosynthesis system designed for measuring gas exchange in plants. It is capable of measuring net carbon dioxide and water vapor exchange, as well as environmental conditions such as temperature, humidity, and light levels.
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Lycopene is a natural pigment found in various fruits and vegetables, particularly tomatoes. It is a carotenoid compound that is primarily responsible for the red color of these foods. Lycopene is commonly used as a laboratory reagent for various research and analytical applications.
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Acetone is a colorless, volatile, and flammable liquid. It is a common solvent used in various industrial and laboratory applications. Acetone has a high solvency power, making it useful for dissolving a wide range of organic compounds.
More about "Carotenoids"
Carotenoids are a diverse family of natural pigments found in plants, algae, and photosynthetic bacteria.
These lipid-soluble molecules play pivotal roles in photosynthesis, photoprotection, and antioxidant defense.
The carotenoid group can be further divided into two main classes: carotenes (e.g., β-carotene) and xanthophylls (e.g., lutein, zeaxanthin).
These vibrant pigments have garnered significant attention for their potential health benefits, including their ability to scavenge free radicals, support eye health, and potentially reduce the risk of certain chronic diseases.
Optimization of carotenoid research is an active area of investigation, and PubCompare.ai offers a powerful AI-driven platform to streamline this process.
The platform helps researchers locate the best protocols from literature, pre-prints, and patents, while providing accurate comparisons to enhance reproducibility and accuracy.
This is particularly useful for studies involving carotenoid-related compounds, such as β-carotene, lutein, zeaxanthin, lycopene, and others.
Researchers can utilize PubCompare.ai to access a wealth of information on carotenoid-related topics, including the use of analytical techniques like UV-1800 spectrophotometry and C30 carotenoid columns for separation and quantification.
The platform also offers insights on the practical applications of carotenoids, such as their use in photobioreactors (LI-6400) and their extraction using solvents like acetone.
By leveraging the power of PubCompare.ai, scientists can streamline their carotenoid research, improve the quality and reproducibility of their studies, and ultimately advance our understanding of these fascinating and valuable natural pigments.
These lipid-soluble molecules play pivotal roles in photosynthesis, photoprotection, and antioxidant defense.
The carotenoid group can be further divided into two main classes: carotenes (e.g., β-carotene) and xanthophylls (e.g., lutein, zeaxanthin).
These vibrant pigments have garnered significant attention for their potential health benefits, including their ability to scavenge free radicals, support eye health, and potentially reduce the risk of certain chronic diseases.
Optimization of carotenoid research is an active area of investigation, and PubCompare.ai offers a powerful AI-driven platform to streamline this process.
The platform helps researchers locate the best protocols from literature, pre-prints, and patents, while providing accurate comparisons to enhance reproducibility and accuracy.
This is particularly useful for studies involving carotenoid-related compounds, such as β-carotene, lutein, zeaxanthin, lycopene, and others.
Researchers can utilize PubCompare.ai to access a wealth of information on carotenoid-related topics, including the use of analytical techniques like UV-1800 spectrophotometry and C30 carotenoid columns for separation and quantification.
The platform also offers insights on the practical applications of carotenoids, such as their use in photobioreactors (LI-6400) and their extraction using solvents like acetone.
By leveraging the power of PubCompare.ai, scientists can streamline their carotenoid research, improve the quality and reproducibility of their studies, and ultimately advance our understanding of these fascinating and valuable natural pigments.