Molecular breeding

About: Molecular breeding is a research topic. Over the lifetime, 2120 publications have been published within this topic receiving 56908 citations.

Molecular approaches for wheat improvement under drought and heat stress

Abstract: Novel molecular breeding selection strategies were implemented in breeding programs in India for wheat improvement under drought and heat stress. Elite Indian varieties HD2733 and GW322 were targeted for improvement to abiotic stresses through marker assisted backcross breeding approach. Backcross populations were advanced to BC1/BC2 F2 after tracking QTLs for foreground selection covering traits such as canopy temperature (CT), chlorophyll content, normalized difference vegetation index (NDVI), grain filling duration (GFD), thousand kernel weight, grain yield and a range of polymorphic microsatellite markers covering entire genome (4–5 SSR markers per chromosome) being used for tracking the recurrent parent genome. Marker assisted recurrent selection (MARS) involved estimation of marker effects for several small effect/major QTLs followed by two recombination cycles. Designed intermating among selected F5 families were carried out after conducting ANOVA and AMMI analysis on multi-location yield trials and polymorphic markers among the parents in two biparental base populations (F5). Inter-family intermating among the best identified families carried out in different combinations to accumulate and recombine 4–8 QTLs per intermated progeny and confirmed in selfed homozygous lines.

Exploiting genomic knowledge in optimising molecular breeding programmes: algorithms from evolutionary computing.

Abstract: Comparatively few studies have addressed directly the question of quantifying the benefits to be had from using molecular genetic markers in experimental breeding programmes (e.g. for improved crops and livestock), nor the question of which organisms should be mated with each other to best effect. We argue that this requires in silico modelling, an approach for which there is a large literature in the field of evolutionary computation (EC), but which has not really been applied in this way to experimental breeding programmes. EC seeks to optimise measurable outcomes (phenotypic fitnesses) by optimising in silico the mutation, recombination and selection regimes that are used. We review some of the approaches from EC, and compare experimentally, using a biologically relevant in silico landscape, some algorithms that have knowledge of where they are in the (genotypic) search space (G-algorithms) with some (albeit well-tuned ones) that do not (F-algorithms). For the present kinds of landscapes, F- and G-algorithms were broadly comparable in quality and effectiveness, although we recognise that the G-algorithms were not equipped with any ‘prior knowledge’ of epistatic pathway interactions. This use of algorithms based on machine learning has important implications for the optimisation of experimental breeding programmes in the post-genomic era when we shall potentially have access to the full genome sequence of every organism in a breeding population. The non-proprietary code that we have used is made freely available (via Supplementary information).

Functional genomics in chickpea: an emerging frontier for molecular-assisted breeding.

Abstract: Chickpea is a valuable and important agricultural crop, but yield potential is limited by a series of biotic and abiotic stresses, including Ascochyta blight, Fusarium wilt, drought, cold and salinity. To accelerate molecular breeding efforts for the discovery and introgression of stress tolerance genes into cultivated chickpea, functional genomics approaches are rapidly growing. Recently a series of genetic tools for chickpea have become available that have allowed high-powered functional genomics studies to proceed, including a dense genetic map, large insert genome libraries, expressed sequence tag libraries, microarrays, serial analysis of gene expression, transgenics and reverse genetics. This review summarises the development of these genomic tools and the achievements made in initial and emerging functional genomics studies. Much of the initial research focused on Ascochyta blight resistance, and a resistance model has been synthesised based on the results of various studies. Use of the rich comparative genomics resources from the model legumes Medicago truncatula and Lotus japonicus is also discussed. Finally, perspectives on the future directions for chickpea functional genomics, with the goal of developing elite chickpea cultivars, are discussed.

Identification of highly regenerative plants within sugar beet (beta vulgaris l.) breeding lines for molecular breeding

Abstract: Development of an efficient transformation method for recalcitrant crops such as sugar beet (Beta vulgaris L.) depends on identification of germplasm with relatively high regeneration potential. Individual plants of seven sugar beet breeding lines were screened for their ability to form adventitious shoots on leaf disk callus. Disks were excised from the first pair of true leaves of 3-wk-old seedlings or from partially expanded leaves of 8-mo.-old plants and cultured on medium with 4.4 μM 6-benzylaminopurine for 10 wk. At 5 wk of culture, friable calluses and adventitious shoots began to develop. Rates of callus and shoot formation varied between breeding lines and between individual plants of the same line. Line FC607 exhibited the highest percentage (61%) of plants that regenerated shoots on explants. Among the plants with a positive shoot regeneration response, line FC607 also had the highest mean number (8.3±1.1) of shoots per explant. Individual plants within each line exhibited a wide range of percentages of explants that regenerated shoots. A similar variation was observed in the number of shoots that regenerated per explant of an individual plant. No loss of regeneration potential was observed on selected plants maintained in the greenhouse for 3 yr. Regenerated plants exhibited normal phenotypes and regeneration abilities comparable to the respective source plants. Based on our results, it is imperative to screen a large number of individual plants within sugar beet breeding lines in order to identify the high regenerators for use in molecular breeding and improvement programs.