Advances in sequencing technology provide special opportunities for genotyping individuals with speed and thrift, but the lack of software to automate the calling of tens of thousands of genotypes over hundreds of individuals has hindered progress. Stacks is a software system that uses short-read sequence data to identify and genotype loci in a set of individuals either de novo or by comparison to a reference genome. From reduced representation Illumina sequence data, such as RAD-tags, Stacks can recover thousands of single nucleotide polymorphism (SNP) markers useful for the genetic analysis of crosses or populations. Stacks can generate markers for ultra-dense genetic linkage maps, facilitate the examination of population phylogeography, and help in reference genome assembly. We report here the algorithms implemented in Stacks and demonstrate their efficacy by constructing loci from simulated RAD-tags taken from the stickleback reference genome and by recapitulating and improving a genetic map of the zebrafish, Danio rerio.

https://webpages.uidaho.edu/hohenlohe/Catchenetal2011.pdf

Stacks: Building and Genotyping Loci De Novo From Short-Read Sequences

Algae biofuels may provide a viable alternative to fossil fuels; however, this technology must overcome a number of hurdles before it can compete in the fuel market and be broadly deployed. These challenges include strain identification and improvement, both in terms of oil productivity and crop protection, nutrient and resource allocation and use, and the production of co-products to improve the economics of the entire system. Although there is much excitement about the potential of algae biofuels, much work is still required in the field. In this article, we attempt to elucidate the major challenges to economic algal biofuels at scale, and improve the focus of the scientific community to address these challenges and move algal biofuels from promise to reality.

/pdf/biofuels-from-algae-challenges-and-potential-596xth9xzn.pdf

Biofuels from algae: challenges and potential.

Preface to the First Edition. Preface to the Second Edition. Contributors. List of Abbreviations. 1 Production and Trade of Vegetable Oils ( Frank D. Gunstone ). 1.1 Extraction, refining and processing. 1.2 Vegetable oils: Production, consumption and trade. 1.3 Some topical issues. 2 Palm Oil ( Siew Wai Lin ). 2.1 Introduction. 2.2 Composition and properties of palm oil and fractions. 2.3 Physical characteristics of palm oil products. 2.4 Minor components of palm oil products. 2.5 Food applications of palm oil products. 2.5.1 Cooking/frying oil. 2.6 Nutritional aspects of palm oil. 2.7 Sustainable palm oil. 2.8 Conclusions. 3 Soybean Oil ( Tong Wang ). 3.1 Introduction. 3.2 Composition of soybean and soybean oil. 3.3 Recovery and refining of soybean oil. 3.4 Oil composition modification by processing and biotechnology. 3.5 Physical properties of soybean oil. 3.6 Oxidation evaluation of soybean oil. 3.7 Nutritional properties of soybean oil. 3.8 Food uses of soybean oil. 4 Canola/Rapeseed Oil ( Roman Przybylski ). 4.1 Introduction. 4.2 Composition. 4.3 Physical and chemical properties. 4.4 Major food uses. 4.5 Conclusion and outlook. 5 Sunflower Oil ( Maria A. Grompone ). 5.1 Introduction. 5.2 Sunflower oil from different types of seed. 5.3 Physical and chemical properties. 5.4 Melting properties and thermal behaviour. 5.5 Extraction and processing of sunflower oil. 5.6 Modified properties of sunflower oil. 5.7 Oxidative stability of commercial sunflower oils. 5.8 Food uses of different sunflower oil types. 5.9 Frying use of commercial sunflower oil types. 6 The Lauric (Coconut and Palm Kernel) Oils ( Ibrahim Nuzul Amri ). 6.1 Introduction. 6.2 Coconut oil. 6.3 Palm kernel oil. 6.4 Processing. 6.5 Food uses. 6.6 Health aspects. 7 Cottonseed Oil ( Michael K. Dowd ). 7.1 Introduction. 7.2 History. 7.3 Seed composition. 7.4 Oil composition. 7.5 Chemical and physical properties of cottonseed oil. 7.6 Processing. 7.7 Cottonseed oil uses. 7.8 Co-product uses. 8 Groundnut (Peanut) Oil ( Lisa L. Dean, Jack P. Davis, and Timothy H. Sanders ). 8.1 Peanut production, history, and oil extraction. 8.2 Oil uses. 8.3 Composition of groundnut oil. 8.4 Chemical and physical characteristics of groundnut oil. 8.5 Health issues. 9 Olive Oil ( Dimitrios Boskou ). 9.1 Introduction. 9.2 Extraction of olive oil from olives. 9.3 Olive oil composition. 9.4 Effect of processing olives on the composition of virgin olive oils. 9.5 Refining and modification. 9.6 Hardening and interesterification. 9.7 Quality, genuineness and regulations. 9.8 Consumption and culinary applications. 10 Corn Oil ( Robert A. Moreau ). 10.1 Composition of corn oil. 10.2 Properties of corn oil. 10.3 Major food uses of corn oil. 10.4 Conclusions. 11 Minor and Speciality Oils ( S. Prakash Kochhar ). 11.1 Introduction. 11.2 Sesame seed oil. 11.3 Rice bran oil. 11.4 Flaxseed (linseed and linola) oil. 11.5 Safflower oil. 11.6 Argan kernel oil. 11.7 Avocado oil. 11.8 Camelina seed oil. 11.9 Grape seed oil. 11.10 Pumpkin seed oil. 11.11 Sea buckthorn oil. 11.12 Cocoa butter and CBE. 11.13 Oils containing a-linolenic acid (GLA) and stearidonic acid (SDA). 11.14 Tree nut oils. Useful Websites. Index.

http://health120years.com/cn/pdf/hd_Vegetable.Oils.pdf

Vegetable Oils in Food Technology: Composition, Properties, and Uses

Genetic linkage maps are cornerstones of a wide spectrum of biotechnology applications, including map-assisted breeding, association genetics, and map-assisted gene cloning. During the past several years, the adoption of high-throughput genotyping technologies has been paralleled by a substantial increase in the density and diversity of genetic markers. New genetic mapping algorithms are needed in order to efficiently process these large datasets and accurately construct high-density genetic maps. In this paper, we introduce a novel algorithm to order markers on a genetic linkage map. Our method is based on a simple yet fundamental mathematical property that we prove under rather general assumptions. The validity of this property allows one to determine efficiently the correct order of markers by computing the minimum spanning tree of an associated graph. Our empirical studies obtained on genotyping data for three mapping populations of barley (Hordeum vulgare), as well as extensive simulations on synthetic data, show that our algorithm consistently outperforms the best available methods in the literature, particularly when the input data are noisy or incomplete. The software implementing our algorithm is available in the public domain as a web tool under the name MSTmap.

/pdf/efficient-and-accurate-construction-of-genetic-linkage-maps-39efho3jfe.pdf

Efficient and accurate construction of genetic linkage maps from the minimum spanning tree of a graph.

In mammals, cadmium is widely considered as a non-genotoxic carcinogen acting through a methylation-dependent epigenetic mechanism. Here, the effects of Cd treatment on the DNA methylation patten are examined together with its effect on chromatin reconfiguration in Posidonia oceanica. DNA methylation level and pattern were analysed in actively growing organs, under short- (6 h) and long- (2 d or 4 d) term and low (10 mM) and high (50 mM) doses of Cd, through a Methylation-Sensitive Amplification Polymorphism technique and an immunocytological approach, respectively. The expression of one member of the CHROMOMETHYLASE (CMT) family, a DNA methyltransferase, was also assessed by qRT-PCR. Nuclear chromatin ultrastructure was investigated by transmission electron microscopy. Cd treatment induced a DNA hypermethylation, as well as an up-regulation of CMT, indicating that de novo methylation did indeed occur. Moreover, a high dose of Cd led to a progressive heterochromatinization of interphase nuclei and apoptotic figures were also observed after long-term treatment. The data demonstrate that Cd perturbs the DNA methylation status through the involvement of a specific methyltransferase. Such changes are linked to nuclear chromatin reconfiguration likely to establish a new balance of expressed/repressed chromatin. Overall, the data show an epigenetic basis to the mechanism underlying Cd toxicity in plants.

/pdf/in-posidonia-oceanica-cadmium-induces-changes-in-dna-3cu7uj83mr.pdf

In Posidonia oceanica cadmium induces changes in DNA methylation and chromatin patterning

Increasing the flow of carbon into seed oil.

Sequence related amplified polymorphism (SRAP) was used to construct an ultradense genetic recombination map for a doubled haploid (DH) population in B. napus. A total of 1,634 primer combinations including 12 fluorescently labeled primers and 442 unlabeled ones produced 13,551 mapped SRAP markers. All these SRAPs were assembled in 1,055 bins that were placed onto 19 linkage groups. Ten of the nineteen linkage groups were assigned to the A genome and the remaining nine to the C genome on the basis of the differential SRAP PCR amplification in two DH lines of B. rapa and B. oleracea. Furthermore, all 19 linkage groups were assigned to their corresponding N1-N19 groups of B. napus by comparison with 55 SSR markers used to construct previous maps in this species. In total, 1,663 crossovers were detected, resulting in a map length span of 1604.8 cM. The marker density is 8.45 SRAPs per cM, and there could be more than one marker in 100 kb physical distance. There are four linkage groups in the A genome with more than 800 SRAP markers each, and three linkage groups in the C genome with more 1,000 SRAP markers each. Our studies suggest that a single SRAP map might be applicable to the three Brassica species, B. napus, B. oleracea and B. rapa. The use of this ultra high-density genetic recombination map in marker development and map-based gene cloning is discussed.

An ultradense genetic recombination map for Brassica napus, consisting of 13551 SRAP markers.

A glabrous, yellow-seeded doubled haploid (DH) line and a hairy, black-seeded DH line in Chinese cabbage (B. rapa) were used as parents to develop a DH line population that segregated for both hairiness and seed coat color traits. The data showed that both traits completely co-segregated each other, suggesting that one Mendelian locus controlled both hairiness and seed coat color in this population. A fine genetic map was constructed and a SNP marker that was located inside a Brassica ortholog of TRANSPARENT TESTA GLABRA 1 (TTG1) in Arabidopsis showed complete linkage to both the hairiness and seed coat color gene, suggesting that the BrassicaTTG1 ortholog shared the same gene function as its Arabidopsis counterpart. Further sequence analysis of the alleles from hairless, yellow-seeded and hairy, black-seeded DH lines in B. rapa showed that a 94-base deletion was found in the hairless, yellow-seeded DH lines. A nonfunctional truncated protein in the hairless, yellow-seeded DH lines in B. rapa was suggested by the coding sequence of the TTG1 ortholog. Both of the TTG1 homologs from the black and yellow seeded B. rapa lines were used to transform an Arabidopsis ttg1 mutant and the results showed that the TTG1 homolog from the black seeded B. rapa recovered the Arabidopsis ttg1 mutant, while the yellow seeded homolog did not, suggesting that the deletion in the Brassica TTG1 homolog had led to the yellow seeded natural mutant. This was the first identified gene in Brassica species that simultaneously controlled both hairiness and seed coat color traits.

Map-based cloning and characterization of a gene controlling hairiness and seed coat color traits in Brassica rapa.

A genetic map was constructed with 353 sequence-related amplified polymorphism and 34 simple sequence repeat markers in oilseed rape (Brassica napus L.). The map consists of 19 linkage groups and covers 1,868 cM of the rapeseed genome. A recombinant doubled haploid (DH) population consisting of 150 lines segregating for oil content and other agronomic traits was produced using standard microspore culture techniques. The DH lines were phenotyped for days to flowering, oil content in the seed, and seed yield at three locations for 3 years, generating nine environments. Data from each of the environments were analyzed separately to detect quantitative trait loci (QTL) for these three phenotypic traits. For oil content, 27 QTL were identified on 14 linkage groups; individual QTL for oil content explained 4.20–30.20% of the total phenotypic variance. For seed yield, 18 QTL on 11 linkage groups were identified, and the phenotypic variance for seed yield, as explained by a single locus, ranged from 4.61 to 24.44%. Twenty-two QTL were also detected for days to flowering, and individual loci explained 4.41–48.28% of the total phenotypic variance.

Identification of QTL for oil content, seed yield, and flowering time in oilseed rape (Brassica napus)

Stellar summer rape (Brassica napus L.) is the first canola quality cultivar which produces seed oil with 3% linolenic acid and 28% linoleic acid. This oil has shorter hydrogenation time and better stability than standard canola oil. Stellar is adapted to the southern B. napus growing areas of western Canada, particularly the Black and Grey soil zones of Manitoba and Saskatchewan.Key words: Rape (summer), low linolenic-high linoleic acid, cultivar description

Peter B. E. McVetty

Papers

Increasing the flow of carbon into seed oil.

An ultradense genetic recombination map for Brassica napus, consisting of 13551 SRAP markers.

Map-based cloning and characterization of a gene controlling hairiness and seed coat color traits in Brassica rapa.

Identification of QTL for oil content, seed yield, and flowering time in oilseed rape (Brassica napus)

Stellar low linolenic-high linoleic acid summer rape