Breeding & Genetics

Overview

Plant breeding is the art and science of changing the traits of plants in order to produce desired characteristics. Plant breeding can be accomplished through many different techniques ranging from simply selecting plants with desirable characteristics for propagation, to more complex molecular techniques.

Plant breeding started with sedentary agriculture and particularly the domestication of the first agricultural plants, a practice which is estimated to date back 9,000 to 11,000 years. Initially early farmers simply selected food plants with particular desirable characteristics, and employed these as progenitors for subsequent generations, resulting in an accumulation of valuable traits over time. Gregor Mendel's experiments with plant hybridization led to his establishing laws of inheritance. Once this work became well known, it formed the basis of the new science of genetics, which stimulated research by many plant scientists dedicated to improving crop production through plant breeding. Modern plant breeding is applied genetics, but its scientific basis is broader, covering molecular biology, cytology, systematics, physiology, pathology, entomology, chemistry, and statistics (biometrics).

Classical Breeding

Classical plant breeding uses deliberate interbreeding (crossing) of closely or distantly related individuals to produce new crop varieties or lines with desirable properties. Plants are crossbred to introduce traits/genes from one variety or line into a new genetic background. For example, a mildew-resistant pea may be crossed with a high-yielding but susceptible pea, the goal of the cross being to introduce mildew resistance without losing the high-yield characteristics. Progeny from the cross would then be crossed with the high-yielding parent to ensure that the progeny were most like the high-yielding parent, (backcrossing). The progeny from that cross would then be tested for yield and mildew resistance and high-yielding resistant plants would be further developed. Plants may also be crossed with themselves to produce inbred varieties for breeding. Classical breeding relies largely on homologous recombination between chromosomes to generate genetic diversity. The classical plant breeder may also make use of a number of in vitro techniques such as protoplast fusion, embryo rescue or mutagenesis (see below) to generate diversity and produce hybrid plants that would not exist in nature.

Traits that breeders have tried to incorporate into crop plants in the last 100 years include:

  • Increased quality and yield of the crop
  • Increased tolerance of environmental pressures (salinity, extreme temperature, drought)
  • Resistance to viruses, fungi and bacteria
  • Increased tolerance to insect pests
  • Increased tolerance of herbicides
Projects
2012
Lentil seed is a good source of phenolic compounds, which can have health benefits. This project will try to find how different seed coat colours in lentil can be related to the phenolics profile. A fast extraction method and an optimized LC-MS analysis were applied to compare green, gray, tan, and brown seed coat colour lentils. Also, the so called zero-tannin genotypes were compared with the normal ones based upon their phenolic profile. The effect of storage on phenolic profile of lentil seeds was investigated, as well.
2010 to 2012
The objective of this study is to determine the genetic control of several traits in field pea including mycosphaerella blight resistance, lodging resistance and micronutrient concentration by genotyping and phenotyping a recombinant inbred line population which is segregating for these traits.
2010 to 2012
The nutritional value of pea, lentil, chickpea and dry bean grains are highly important for human health. Biofortification, enriching the nutritional contribution of staple crops through plant breeding, is one option that is now widely discussed in the fields of nutrition and public health at the national and international levels.
2011
Preparation of EST data: Sequences were extracted from dbEST and were subjected to quality control screening (vector, E. coli, polyA, T, or CT removal, minimum length = 100 bp, < 3% N). Preparation of transcript (ET) database: All sequences from the appropriate divisions of GenBank (including RefSeq) were extracted. Non-coding sequences were discarded and cDNAs and coding sequences from genomic entries were saved. Sequences and related information (e.g. PubMed links) are stored in the qcGene database (qcGene). Assembly: Cleaned EST sequences and non-redundant transcript (ET) sequences were combined. Using the Paracel Transcript Assembler Program, sequences were assembled into contigs. TCs are consensus sequences based on two or more ESTs (and possibly an ET) that overlap for at least 40 bases with at least 94% sequence identity. These strict criteria help minimize the creation of chimeric contigs. These contigs are assigned a TC (Tentative Consensus) number. TCs may comprise ESTs derived from different tissues. The best hits for TC's were assigned by searching the TC set against a non-redundant amino acid database(nraa) using BLAT. The top five hits based on score were selected and displayed for each TC. Caveats: TCs are only as good as the ESTs underlying them; there may be unspliced or chimeric ESTs and thus TCs. There is still redundancy in the TC set because sequences must match end to end and at a certain percent identity to be combined. Directionality of the TCs should not be assumed. Not all TCs contain protein-coding regions.
2011
An Illumina Golden Gate array was developed using SNPs identified as part of the Lentil 454 Sequencing & Genotyping Project. Loci where chosen such that the SNPs should be distributed evenly across the genome based on comparison to Medicago truncatula.
2011
<ul><li>Preparation of EST data: Sequences were extracted from dbEST and were subjected to quality control screening (vector, E. coli, polyA, T, or CT removal, minimum length = 100 bp, &lt; 3% N).</li><li>Preparation of transcript (ET) database: All sequences from the appropriate divisions of GenBank (including RefSeq) were extracted. Non-coding sequences were discarded and cDNAs and coding sequences from genomic entries were saved. Sequences and related information (e.g. PubMed links) are stored in the qcGene database (qcGene).</li><li>Assembly: Cleaned EST sequences and non-redundant transcript (ET) sequences were combined. Using the Paracel Transcript Assembler Program, sequences were assembled into contigs. TCs are consensus sequences based on two or more ESTs (and possibly an ET) that overlap for at least 40 bases with at least 94% sequence identity. These strict criteria help minimize the creation of chimeric contigs. These contigs are assigned a TC (Tentative Consensus) number. TCs may comprise ESTs derived from different tissues. The best hits for TC's were assigned by searching the TC set against a non-redundant amino acid database(nraa) using BLAT. The top five hits based on score were selected and displayed for each TC.</li><li>Caveats: TCs are only as good as the ESTs underlying them; there may be unspliced or chimeric ESTs and thus TCs. There is still redundancy in the TC set because sequences must match end to end and at a certain percent identity to be combined. Directionality of the TCs should not be assumed. Not all TCs contain protein-coding regions.</li></ul>
2009 to 2011
Eight germplasm were chosen for this project:CDC WM-2, BAT 93, Expresso, Higuera-E, Jalo EEP-558, PI 430219, SMARC1N-PN1, and W6-15578. Tissue was collected from multiple plants at various developmental stages for RNA extraction which led to the generation of 3'-anchored cDNA libraries using the method described in Parkin et al., 2010. Each line was sequenced using the Roche 454 Titanium sequencing protocol. Sequencing reads were aligned directly to the Phaseolus vulgaris genomic build v0.9 using GMap. Then loci which were polymorphic between at least two of the lines were identified resulting in 133,108 SNPs. All SNPs were re-mapped to the published genome assembly 1.0 (Phytozome.org; Schmutz et al. 2014).
2011
<p>Preparation of EST data: Sequences were extracted from dbEST and were subjected to quality control screening (vector, E. coli, polyA, T, or CT removal, minimum length = 100 bp, &lt; 3% N). Preparation of transcript (ET) database: All sequences from the appropriate divisions of GenBank (including RefSeq) were extracted. Non-coding sequences were discarded and cDNAs and coding sequences from genomic entries were saved. Sequences and related information (e.g. PubMed links) are stored in the qcGene database (qcGene). Assembly: Cleaned EST sequences and non-redundant transcript (ET) sequences were combined. Using the Paracel Transcript Assembler Program, sequences were assembled into contigs. TCs are consensus sequences based on two or more ESTs (and possibly an ET) that overlap for at least 40 bases with at least 94% sequence identity. These strict criteria help minimize the creation of chimeric contigs. These contigs are assigned a TC (Tentative Consensus) number. TCs may comprise ESTs derived from different tissues. The best hits for TC's were assigned by searching the TC set against a non-redundant amino acid database(nraa) using BLAT. The top five hits based on score were selected and displayed for each TC. Caveats: TCs are only as good as the ESTs underlying them; there may be unspliced or chimeric ESTs and thus TCs. There is still redundancy in the TC set because sequences must match end to end and at a certain percent identity to be combined. Directionality of the TCs should not be assumed. Not all TCs contain protein-coding regions.</p>
2011
An Illumina Golden Gate array was developed using SNPs identified as part of the Pea 454 Sequencing & Genotyping Project. Loci where chosen such that the SNPs should be distributed evenly across the genome based on comparison to Medicago truncatula.
2010
Sequencing reads were assembled into contigs using the NGen assembler resulting in 22,927 CDC Frontier contigs. Contigs from the other 10 lines were compared to CDC Frontier and loci which were polymorphic between CDC Frontier and at least one other line were identified resulting in 55,206 SNPs. However, it was later found that aligning the sequencing reads directly to the current genome build produced a much more reliable set of SNPs. As such, THESE SNPS SHOULD NOT BE USED; they are simply here for archival purposes.

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