Genetics, Genomics and Breeding of Sunflower (Genetics, Genomics and Breeding of Crop Plants)

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  1. Genetics, Genomics and Breeding of Sunflower - CRC Press Book
  2. Genetics, Genomics and Breeding of Crop Plants
  3. Bestselling Series

Over 50 species of Musa exist, including bananas and plantains. This book assembles the latest information on the genomic research of this genus. A group of leading experts in Musa genetics, genomics, and breeding provide basic as well as Yi-Hong Wang, T. Behera, Chittaranjan Kole November 11, The last two decades has been the most exciting period in cucurbit genetic, genomic, and breeding research especially for cucumber, melon, and watermelon.

In thirteen Cool season grain legumes including pea, faba bean, lentil, chickpea, and grass pea are extensively grown in many parts of the world. They are a primary source of proteins in human diet.

Genetics, Genomics and Breeding of Sunflower - CRC Press Book

This volume deals with the most recent advances in genetics, genomics, and breeding of these crops. The "state The book describes the history of Brassica oilseed crops, introduces the Brassica genome, its evolution, diversity, classical genetic studies, and breeding. It also delves into molecular genetic linkage and physical maps, progress with genome sequencing initiatives, mutagenesis approaches for trait Stay on CRCPress.

Exclusive web offer for individuals on all book. Series Titles Authors. Per Page. Include Forthcoming Titles. Genetics, Genomics and Breeding of Potato 1st Edition. Genetics, Genomics, and Breeding of Soybean 1st Edition. Genetics, Genomics and Breeding of Sunflower 1st Edition. Genetics, Genomics and Breeding of Maize 1st Edition.

Genetics, Genomics and Breeding of Sorghum 1st Edition. Genetics, Genomics and Breeding of Eucalypts 1st Edition. Genetics, Genomics and Breeding of Peanuts 1st Edition. Oil and oleic acid content and confectionery traits are among the important quality traits. Genomic tools enhance crop breeding process by increasing the efficiency and speed of precision breeding to develop improved varieties.

But such approaches have not been widely used in groundnut. Significant progress has been made in groundnut genetics, genomics and breeding, thus contributing to the increased productivity and production of groundnut globally although the rate of increase varies among regions.

It is worth mentioning that the progress has been achieved through strong partnership and collaborations between scientists from national research systems, international research institutes, universities, and private research organizations and service providers. Globally, large numbers of groundnut lines were identified or developed as sources of variability for important traits and many improved varieties were released for target environments by breeding programmes.

The last decade has witnessed the rapid development of genomic tools helping to better understand the groundnut genome.

Genetics, Genomics and Breeding of Crop Plants

Emerging trait mapping approaches are expected to help the search for linked markers for other traits and develop diagnostic markers for breeding applications. It will not be far for such technologies to be routinely utilized by many breeding programmes, if not all, for screening segregating populations, purity testing, genetic mapping, targeted resequencing of specific genomic regions and other studies.

The BMGF financial support has significantly contributed to groundnut research and development globally and in Asia and Africa particularly, through tropical legume TL projects. Haile Desmae wrote the first draft and incorporated all inputs from the coauthors and editors.

If you do not receive an email within 10 minutes, your email address may not be registered, and you may need to create a new Wiley Online Library account. If the address matches an existing account you will receive an email with instructions to retrieve your username. Plant Breeding Early View.


  • Journal of Genetics Genomics and Plant Breeding.
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Haile Desmae Corresponding Author E-mail address: h. Manish K. Babu N. Rajeev K.

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Tools Request permission Export citation Add to favorites Track citation. Share Give access Share full text access. Share full text access. Please review our Terms and Conditions of Use and check box below to share full-text version of article. Abstract Groundnut is an important food and oil crop in the semiarid tropics, contributing to household food consumption and cash income. Alves, D. Development and use of single nucleotide polymorphism markers for candidate resistance genes in wild peanuts Arachis spp. Genetics and Molecular Research , 7 , — Crossref Google Scholar. Google Scholar.

Crossref PubMed Google Scholar. Wiley Online Library Google Scholar. In particular, Phytozome added the web application, PhytoMine, which provides templates for retrieving genomic information. These templates provide defined genomic features, such as gene expression levels of various tissues and a list of genes in selected genomic regions. They also provide application programming interfaces API that can be directly included in various programming languages, such as Perl, Ruby, Java and Python.

These APIs enable the bioinformatician to merge the genomic information of different species without downloading heavy genomic data sets to a local computer.

Genetics, Genomics and Breeding of Maize Genetics, Genomics and Breeding of Crop Plants

The newly published genomes deposit their own databases, as well as public databases, for the agile update of sequence improvement and their genomic resources. In addition to information regarding the reference genome, several databases deal with integrated genetic and genomic resources, such as QTL information, genetic markers, gene expression, traces of DNA methylation and small RNAs.


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Genetic markers are genomic regions that show polymorphisms, thus allowing us to distinguish between different species or cultivars and to observe the genotypes of target species that are linked to phenotypes. SNPs provide higher genome resolution due to their frequent occurrence in the genome and are genotyped according to four discrete nucleotides.

Because the reference genomes and resequencing efforts have evolved, it is now possible to develop a large number of SSR and SNP markers.

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This feature would greatly benefit researchers who are interested in finding polymorphic sites around target genes. Many important agricultural traits, such as flowering time, maturity and yield, are quantitative traits. These traits are usually related to multiple loci, thus making it complicated to implement functional analyses of single genes.

The approximate physical locations of QTLs are highly informative, because they can be regarded as the statistical phenotype annotation of reference genomes. Among all model crops, soya bean and rice have been intensively studied, and their QTLs have been located on the genetic map. Genomic resources that have been deposited in databases. GWAS can be also used to infer statistical associations between variations in genomic regions and phenotypes of populations, such as landraces, breeding population and the nested association mapping population Rafalski, The advancement of NGS and various genotyping technologies makes it feasible to perform association analyses in larger populations with more dense markers increasing the genome resolution to detect precise linkage disequilibrium blocks and recombination breakpoints.

These analyses usually result in several significant loci or markers. They found various domestication signatures, such as selective sweeps and selected copy number variants. The results of GWAS are highly dependent on the structure of the testing population, the phenotypic variation of individuals and the number of markers used; hence, this additional information should also be added to the database. Analysing the expression of genes in various organs at each growth stage would be important for understanding the contribution of genes to particular traits.

Differentially expressed genes can be good candidates for further functional analyses of the phenotypes of interest. Even if candidate genes are not verified by functional analyses, they can be still important clues for understanding the roles of genomic regions. For the consolidation of expression data, the Plant Expression Database was constructed for 14 plant species and provides a gene expression atlas with detailed experimental designs and tested germplasm information, as well as visualization tools.

Therefore, the polymorphisms of these genomic traces should be considered in genetic studies to unravel the causalities of subtle phenotypic variations. The potential effect of small RNA and DNA methylation on gene regulation and inheritance enables us to regard them as important genomic resources for crop breeding. The functionally identified genes are valuable resources for translational genomics and crop breeding. The functionally annotated genes can be mapped to known pathways and can enable the researchers to deduce whether the target genes participate in the traits of interest.

These genes are systematically collected in the UniProt database Consortium, Number of functionally identified genes of each species according to SwissProt in UniProt database. The shared sequence context and QTL annotation may implicate the possible contribution of genomic content to the quantitative trait. For the comparative analysis of QTL among different crop species, it is necessary to integrate published QTLs of the crop species into a single database.

Because biological data points are growing at a rapid rate, the traditional format of databases e. For single species data, genome browsers e. These databases are commonly focused on providing information regarding genes or genomic regions. However, crop breeders usually query agriculturally important phenotypes rather than certain genes or genomic regions because their goals are to improve a specific target trait.

Moreover, this knowledge can be transferred to newly constructed genomic sequences using the translational genomics approach, which takes advantage of the conserved features in plant genome sequences. Advancements in sequencing and genotyping technologies have guided the abundant genomes and genomic resources of model crops. The transferred information would serve as valuable hints for breeding and functional biology, along with various objectives for the species.

Translational genomics aims to take advantage of the perspectives of comparative genomics, systemic genomics and evolutional genomics. Comparative genomics focuses on the similarities and differences among plant species with regard to DNA sequence, protein sequence and gene orders, as well as epigenetic signatures. The conservation of these features suggests the possibility of common phenotype contribution, and this information can be used for the functional annotation of the newly sequenced genome. More information would be transferred from model crops to phylogenetically closer species than distantly related plant species, as the annotation highly depends on pairwise similarity and conservation among neighbouring species.

The domain architecture, which is the functional region within a protein sequence, can be detected by the hidden Markov model HMM algorithm. This algorithm recruits sequence conservation among species. The inferred gene network model could accurately predict regulatory relationships, including previously reported cases. With these general or conditional gene network models, we can further understand the roles of genes in model plants.

Hence, based on the homology with genes in model plants, gene networks can also be transferred to new genomes as functional clues for genes. Even though the chromosomes are shuffled among neighbouring species after speciation, the conservation of gene order within each chromosome has been detected in various genome projects, suggesting that the neighbouring plant species are diverged from a common ancestor.

If we postulate that the traits of interest exist in a common ancestor, we can assume that the conserved gene orders would contribute to the common traits of the descendent species. Based on this assumption, the phenotypic annotations around the syntenic regions of model plants can be transferred to the corresponding genomic regions of neighbouring species. This scheme would be useful for transferring QTLs that are represented by multiple genetic markers linked to the responsible genomic regions of the traits of interest. The disease resistance and flowering time QTLs were conserved along with syntenic regions, even between dicot and monocot species.

It is hard to generalize that transferred QTLs are strong candidates for the traits; however, the presence of multiple QTL annotations from various species would be highly informative for breeding purposes.