Molecular breeding

Last updated January 05, 2024

Molecular breeding is the application of molecular biology tools, often in plant breeding ^[1]^[2] and animal breeding.^[3]^[4] In the broad sense, molecular breeding can be defined as the use of genetic manipulation performed at the level of DNA to improve traits of interest in plants and animals, and it may also include genetic engineering or gene manipulation, molecular marker-assisted selection, and genomic selection.^[5] More often, however, molecular breeding implies molecular marker-assisted breeding (MAB) and is defined as the application of molecular biotechnologies, specifically molecular markers, in combination with linkage maps and genomics, to alter and improve plant or animal traits on the basis of genotypic assays.^[6]

Constituent methods

Marker assisted breeding

Methods in marker assisted breeding include:

Genotyping and creating molecular maps - genomics

The commonly used markers include simple sequence repeats (or microsatellites), single nucleotide polymorphisms (SNP). The process of identification of plant genotypes is known as genotyping.

Development of SNPs has revolutionized the molecular breeding process as it helps to create dense markers.^{[ clarification needed ]} Another area that is developing is genotyping by sequencing.^[10]

Phenotyping - phenomics

To identify genes associated with traits, it is important to measure the trait value - known as phenotype ^{[ dubious – discuss ]}. The "omics" for measurement of phenotypes is called phenomics. The phenotype can be indicative of the measurement of the trait itself or an indirectly related or correlated trait.

QTL mapping or association mapping

Genes (Quantitative trait loci (abbreviated as QTL) or quantitative trait genes or minor genes or major genes) involved in controlling trait of interest are identified. The process is known as mapping. Mapping of such genes can be done using molecular markers. QTL mapping can involve single large family, unrelated individuals or multiple families (see: Family based QTL mapping). The basic idea is to identify genes or markers associated with genes that correlate to a phenotypic measurement and that can be used in marker assisted breeding / selection.

Marker assisted selection or genetic selection

Once genes or markers are identified, they can be used for genotyping and selection decisions can be made.

Marker-assisted backcrossing (MABC)

Backcrossing is crossing an F1 with its parents to transfer a limited number of loci (e.g. transgene, disease resistance loci, etc.) from one genetic background to another. Usually the recipient of such genes is a cultivar that is already well performing - except for the gene that is to be transferred. So we want to keep the genetic background of the recipient genotypes, which is done by 4-6 rounds of repeated backcrosses while selecting for the gene of interest. We can use markers from the whole genome to recover the genome quickly in 2-3 rounds of backcrossing might be good enough in such situation.^{[ clarification needed ]}

Marker-assisted recurrent selection (MARS)

MARS include identification and selection of several genomic regions (up to 20 or even more) for complex traits within a single population.

Genomic selection

Genomic selection is a novel approach to traditional marker-assisted selection where selection is made based on only a few markers.^[7] Rather than seeking to identify individual loci significantly associated with a trait, genomics uses all marker data as predictors of performance and consequently delivers more accurate predictions. Selection can be based on genomic selection predictions, potentially leading to more rapid and lower cost gains from breeding. Genomic prediction combines marker data with phenotypic and pedigree data (when available) in an attempt to increase the accuracy of the prediction of breeding and genotypic values.^[11]

Genetic transformation or Genetic engineering

Transfer of genes makes possible the horizontal transfer of genes from one organism to another. Thus plants can receive genes from humans or algae or any other organism. This provides limitless opportunities in breeding crop plants.

By organism

Molecular breeding resources (including multiomics data) are available for:

Some of the millets ^[12]
Wheat ^[13]

Related Research Articles

Biostatistics is a branch of statistics that applies statistical methods to a wide range of topics in biology. It encompasses the design of biological experiments, the collection and analysis of data from those experiments and the interpretation of the results.

A quantitative trait locus (QTL) is a locus that correlates with variation of a quantitative trait in the phenotype of a population of organisms. QTLs are mapped by identifying which molecular markers correlate with an observed trait. This is often an early step in identifying the actual genes that cause the trait variation.

Backcrossing is a crossing of a hybrid with one of its parents or an individual genetically similar to its parent, to achieve offspring with a genetic identity closer to that of the parent. It is used in horticulture, animal breeding, and production of gene knockout organisms.

Genetic architecture is the underlying genetic basis of a phenotypic trait and its variational properties. Phenotypic variation for quantitative traits is, at the most basic level, the result of the segregation of alleles at quantitative trait loci (QTL). Environmental factors and other external influences can also play a role in phenotypic variation. Genetic architecture is a broad term that can be described for any given individual based on information regarding gene and allele number, the distribution of allelic and mutational effects, and patterns of pleiotropy, dominance, and epistasis.

A polygene is a member of a group of non-epistatic genes that interact additively to influence a phenotypic trait, thus contributing to multiple-gene inheritance, a type of non-Mendelian inheritance, as opposed to single-gene inheritance, which is the core notion of Mendelian inheritance. The term "monozygous" is usually used to refer to a hypothetical gene as it is often difficult to distinguish the effect of an individual gene from the effects of other genes and the environment on a particular phenotype. Advances in statistical methodology and high throughput sequencing are, however, allowing researchers to locate candidate genes for the trait. In the case that such a gene is identified, it is referred to as a quantitative trait locus (QTL). These genes are generally pleiotropic as well. The genes that contribute to type 2 diabetes are thought to be mostly polygenes. In July 2016, scientists reported identifying a set of 355 genes from the last universal common ancestor (LUCA) of all organisms living on Earth.

A molecular marker is a molecule, sampled from some source, that gives information about its source. For example, DNA is a molecular marker that gives information about the organism from which it was taken. For another example, some proteins can be molecular markers of Alzheimer's disease in a person from which they are taken. Molecular markers may be non-biological. Non-biological markers are often used in environmental studies.

Steven Dale Tanksley is the Chief Technology Officer of Nature Source Improved Plants. Prior to founding Nature Source Improved Plants, Tanksley served as the Liberty Hyde Bailey professor of plant breeding and biometry and chair of the Genomics Initiative Task Force at Cornell University College of Agriculture and Life Sciences. He is currently a Professor Emeritus at Cornell University.

Marker assisted selection or marker aided selection (MAS) is an indirect selection process where a trait of interest is selected based on a marker linked to a trait of interest, rather than on the trait itself. This process has been extensively researched and proposed for plant- and animal- breeding.

A doubled haploid (DH) is a genotype formed when haploid cells undergo chromosome doubling. Artificial production of doubled haploids is important in plant breeding.

In genetics, association mapping, also known as "linkage disequilibrium mapping", is a method of mapping quantitative trait loci (QTLs) that takes advantage of historic linkage disequilibrium to link phenotypes to genotypes, uncovering genetic associations.

Nested association mapping (NAM) is a technique designed by the labs of Edward Buckler, James Holland, and Michael McMullen for identifying and dissecting the genetic architecture of complex traits in corn. It is important to note that nested association mapping is a specific technique that cannot be performed outside of a specifically designed population such as the Maize NAM population, the details of which are described below.

GeneNetwork is a combined database and open-source bioinformatics data analysis software resource for systems genetics. This resource is used to study gene regulatory networks that link DNA sequence differences to corresponding differences in gene and protein expression and to variation in traits such as health and disease risk. Data sets in GeneNetwork are typically made up of large collections of genotypes and phenotypes from groups of individuals, including humans, strains of mice and rats, and organisms as diverse as Drosophila melanogaster, Arabidopsis thaliana, and barley. The inclusion of genotypes makes it practical to carry out web-based gene mapping to discover those regions of genomes that contribute to differences among individuals in mRNA, protein, and metabolite levels, as well as differences in cell function, anatomy, physiology, and behavior.

A recombinant inbred strain or recombinant inbred line (RIL) is an organism with chromosomes that incorporate an essentially permanent set of recombination events between chromosomes inherited from two or more inbred strains. F1 and F2 generations are produced by intercrossing the inbred strains; pairs of the F2 progeny are then mated to establish inbred strains through long-term inbreeding.

<span class="mw-page-title-main">Plant breeding</span> Humans changing traits, ornamental/crops

Plant breeding is the science of changing the traits of plants in order to produce desired characteristics. It has been used to improve the quality of nutrition in products for humans and animals. The goals of plant breeding are to produce crop varieties that boast unique and superior traits for a variety of applications. The most frequently addressed agricultural traits are those related to biotic and abiotic stress tolerance, grain or biomass yield, end-use quality characteristics such as taste or the concentrations of specific biological molecules and ease of processing.

Quantitative trait loci mapping or QTL mapping is the process of identifying genomic regions that potentially contain genes responsible for important economic, health or environmental characters. Mapping QTLs is an important activity that plant breeders and geneticists routinely use to associate potential causal genes with phenotypes of interest. Family-based QTL mapping is a variant of QTL mapping where multiple-families are used.

Genomic Selection (GS) predicts the breeding values of an offspring in a population by associating their traits with their high-density genetic marker scores. GS is a method proposed to address deficiencies of marker-assisted selection (MAS) in breeding programs. However, GS is a form of MAS that differs from it by estimating, at the same time, all genetic markers, haplotypes or marker effects along the entire genome to calculate the values of genomic estimated breeding values (GEBV). The potentiality of GS is to explain the genetic diversity of a breeding program through a high coverage of genome-wide markers and to assess the effects of those markers to predict breeding values.

"Envirome" is a concept that relates the core of environmental conditions with the successful biological performance of living beings. This concept was created in genetic epidemiology, in which an envirome is defined as the total set of environmental factors, both present, and past, that affect the state, and in particular the disease state, of an organism. The study of the envirome and its effects is termed enviromics. The term was first coined in the field of psychiatric epidemiology by J.C. Anthony in 1995. More recently, use of the term has been extended to the cellular domain, where cell functional enviromics studies both the genome and envirome from a systems biology perspective. In plants, enviromics is directly related to complex ecophysiology, in which the wide environment of the plants, into an omics scale, can be dissected and understood as a mosaic of possible growing factors and the balance of diverse resources available. In ecology, this concept can be related to the Shelford's law of tolerance. The enviromics is conceived as a pillar of the Modern Plant Breeding, capable to connect the design and development of breeding goals concealing it with the agronomic targets for a climate-smart agriculture. It also has the ability to bridge the knowledge gaps between the different levels of systems biology and phenomics in the context of Gene–environment interaction.

Michael Edward "Mike" Goddard is a professorial fellow in animal genetics at the University of Melbourne, Australia.

Complex traits, also known as quantitative traits, are traits that do not behave according to simple Mendelian inheritance laws. More specifically, their inheritance cannot be explained by the genetic segregation of a single gene. Such traits show a continuous range of variation and are influenced by both environmental and genetic factors. Compared to strictly Mendelian traits, complex traits are far more common, and because they can be hugely polygenic, they are studied using statistical techniques such as quantitative genetics and quantitative trait loci (QTL) mapping rather than classical genetics methods. Examples of complex traits include height, circadian rhythms, enzyme kinetics, and many diseases including diabetes and Parkinson's disease. One major goal of genetic research today is to better understand the molecular mechanisms through which genetic variants act to influence complex traits.

Rohan L. Fernando is a Sri Lankan American geneticist who is a professor of quantitative genetics in the Department of Animal Science at Iowa State University (ISU), US. Fernando's efforts have focused primarily on theory and methods for use of genetic markers in breeding, theory and methods for genetic evaluations of crossbred animals, methodology related to the estimation of genetic parameters and the prediction of genetic merit in populations undergoing selection and non-random mating, Bayesian methodology for analysis of unbalanced mixed model data, optimization of breeding programs, and use of computer simulation to study dynamics of genetic system.

References

↑ Voosen, P. (2009). "Molecular Breeding Makes Crops Hardier and More Nutritious Markers, knockouts and other technical advances improve breeding without modifying genes". Scientific American .
↑ "Stephen P. Moose* and Rita H. Mumm (2008) Molecular Plant Breeding as the Foundation for 21st Century Crop Improvement, Plant Physiology 147:969-977".
↑ Dekkers, Jack C. M.; Hospital, Frédéric (2002). "The use of molecular genetics in the improvement of agricultural populations". Nature Reviews Genetics. 3 (1): 22–32. doi:10.1038/nrg701. PMID 11823788. S2CID 32216266.
↑ C.M. Dekkers, Jack (2012). "Application of Genomics Tools to Animal Breeding". Current Genomics. 13 (3): 207–212. doi:10.2174/138920212800543057. PMC 3382275 . PMID 23115522.
↑ Ribaut, J-M; de Vicente, Mc; Delannay, X (April 2010). "Molecular breeding in developing countries: challenges and perspectives". Current Opinion in Plant Biology. 13 (2): 213–218. doi:10.1016/j.pbi.2009.12.011. PMID 20106715.
↑ Hollington, P.A.; Steele, Katherine A. (2007), "Participatory Breeding For Drought and Salt Tolerant Crops", Advances in Molecular Breeding Toward Drought and Salt Tolerant Crops, Dordrecht: Springer Netherlands, pp. 455–478, doi:10.1007/978-1-4020-5578-2_18, ISBN 978-1-4020-5577-5 , retrieved 2020-10-02
1 2 Meuwissen, T. H. E.; Hayes, B. J.; Goddard, M. E. (2001-04-01). "Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps". Genetics. 157 (4): 1819–1829. doi:10.1093/genetics/157.4.1819. ISSN 0016-6731. PMC 1461589 . PMID 11290733.
↑ Jannink, Jean-Luc; Lorenz, Aaron J.; Iwata, Hiroyoshi (2010-03-01). "Genomic selection in plant breeding: from theory to practice". Briefings in Functional Genomics. 9 (2): 166–177. doi:10.1093/bfgp/elq001. ISSN 2041-2649. PMID 20156985.
↑ Heffner, Elliot L.; Sorrells, Mark E.; Jannink, Jean-Luc (2009-01-01). "Genomic Selection for Crop Improvement". Crop Science. 49 (1): 1–12. doi:10.2135/cropsci2008.08.0512. ISSN 1435-0653.
↑ "Analysis". bucklerlab.
↑ Goddard, ME; Hayes, BJ (2007). "Genomic selection". Journal of Animal Breeding and Genetics. 124 (6): 323–30. doi: 10.1111/j.1439-0388.2007.00702.x . PMID 18076469.
↑ Sun, Min; Yan, Haidong; Zhang, Aling; Jin, Yarong; Lin, Chuang; Luo, Lin; Wu, Bingchao; Fan, Yuhang; Tian, Shilin; Cao, Xiaofang; Wang, Zan; Luo, Jinchan; Yang, Yuchen; Jia, Jiyuan; Zhou, Puding; Tang, Qianzi; Jones, Chris Stephen; Varshney, Rajeev K.; Srivastava, Rakesh K.; He, Min; Xie, Zheni; Wang, Xiaoshan; Feng, Guangyan; Nie, Gang; Huang, Dejun; Zhang, Xinquan; Zhu, Fangjie; Huang, Linkai (2023). "Milletdb: a multi‐omics database to accelerate the research of functional genomics and molecular breeding of millets". doi: 10.1111/pbi.14136 . PMC 10579705 .{{cite journal}}: Cite journal requires |journal= (help)
↑ Sun, Congwei; Hu, Huiting; Cheng, Yongzhen; Yang, Xi; Qiao, Qi; Wang, Canguan; Zhang, Leilei; Chen, Da-Yuan; Zhao, Simin; Dong, Zhongdong; Chen, Feng (2023). "Genomics‐assisted breeding: The next‐generation wheat breeding era". doi: 10.1111/pbr.13094 . S2CID 258478136.{{cite journal}}: Cite journal requires |journal= (help)