Meiotic recombination profiling by multi-locus genotyping and recombination bin mapping of nuclei from F1 pollen
Meiotic recombination is a key fundamental biological process that ensures the reshuffling of parental alleles into new combinations. In molecular breeding the rearrangement of alleles via recombination in offspring is assessed to seek out preferred allele combinations for crop innovation. Molecular marker based screenings are routinely used for recombination profiling of segregating populations, though which is a time-consuming and costly process. Given the recent developments in key technologies (genomics technology, ICT, bioinformatics), high throughput recombination bin mapping has become a feasible approach for efficient recombination profiling with unprecedented resolution, without being dependent on marker based approaches and the construction of large mapping populations. The project addresses the technological innovation that is needed to realize precision breeding for advanced crops. The novelty of the project lies in its multidisciplinary character, tackling genomics from different but yet complementary angles involving state-of-the-art genomics technology and genome bioinformatics. The new technology developed in this project serves as a key technology supporting fundamental and applied research purposes, varying from genome reconstruction and genome evolution related studies, to structural variation analysis, genetic map construction, QTL analysis, and genetic diversity analysis. Here we will focus on sequence based identification of crossover recombination, aiding the identification of compatible trait - plant parent combinations for introgression breeding. We will analyse crossover recombination in pollen gametes from F1 plants obtained from crosses between S. lycopersicum Heinz 1706 and its related wild species (pimpinellifolium, cheesmanii, arcanum, habrochaites, pennellii, etc) as well as crosses preferred by private partners including other species (e.g. pepper, melon, lettuce, tulip, papaya, maize (corn), spinach, sugar beet, etc). The project targets a unique combination of linked read sequencing, bioinformatics and genetics technology which provides new insights and permits the development of breeding tools that will drive innovation for the consortium partners and plant breeding and horticulture in general. The generated knowledge in the project will help to; (i) explain crossover recombination and resolve linkage drag problems for cultivated crops; (ii) analyse sequence features and gene content of recombined segments and CO junctions; and (iii) determine the synteny and structural homology of parental breeding lines. The insight will enable plant breeders to optimize their introgression breeding strategy permitting them to; (1) reduce their ‘time-to-market’ introduction for new crops varieties; (2) realize R&D cost savings and alternative usage of R&D resources; (3) respond more flexible to new consumer requests and market trends; and (4) develop advanced breeding lines with complex traits such as pathogen resistance and improved (a)biotic stress tolerance. Furthermore, the concept potentially can be used for a wide range of economically important crops as well. This applied research project answers to the food security and sustainable production challenges by developing advanced precision breeding methods for the vegetable and field crops subsector in the plant breeding and propagation industry, and strengthening the unique and competitive position of high-tech horticulture and breeding industry.
In this project the following innovative knowledge is gained with which the applied and fundamental research questions stated below are addressed;
1. We will develop a high throughput recombination profiling method which is independent from traditional marker technology and mapping populations. This method describes and involves the data production and processing of NGS data. The method is generic and applicable for a wide variety of crops.
2. We will develop bioinformatics tools for the detection of crossover recombination and gene conversion.
3. We will pinpoint COs from linked read sequence at the nucleotide level representing an unprecedented resolution. We then will attempt to reconstruct a genetic map based on the detected recombination frequencies and the detected CO positions on the reference genome.
4. We will test combinations of parental lines using gene bank accessions and accessions preferred and put forward by the private partners. In the analyses we will take the context of target genes and QTL regions in accessions underlying economically important traits such as drought tolerance, fruit shape and disease resistance loci into account, which is needed to advance on efficient introgressive hybridization breeding.
5. Until now the relationship between genome structure, crossover (CO) recombination, gene conversion (GC) and breeding (in)compatibility is not clear. Recombination map comparisons will be studied in relation to genomic features using machine learning approaches conducted via the MEICOM initiative (see also under impact, and communication) in relation to e.g. genome sequence and structural differences of breeding parent combinations and as such is of both of fundamental and applied importance. The results will be compared to known rearrangements and alien introgressions as detected previously (Aflitos et al., 2014) and will be shared with this consortium.
Recombination bin mapping is a key technology project falling under category ‘Smart technologies in Agri-Horti-Water-Food’ and by its range of applications transects and is linked to missions Circular Agriculture (mission A), Climate neutral agriculture and food production (mission B), and Appreciated, heathy and safe food (mission D) set out in the Knowledge and Innovation Agenda. It answers to economic, environmental, social and health issues inherent to agricultural crop production. The project uses genomics, bioinformatics, and breeding to explore and benefit from the potential of genetically diverse germplasm panels, and test progeny from different parental combinations. This key technology aims to profile meiotic recombination basically on a population level, nonetheless by using recombinant gametes from 1 F1 offspring plant per parental cross instead of profiling a mapping population of several hundred offspring plants per cross. It guides and anticipates on optimal breeding material and puts breeding at a precision level (MMIP S2, sub programmes 1-genome technology, 2-bioinformatics, and 5-guiding breeding technologies) and response level enabling the accelerated development of robust and innovative crops (MMIP A2) that are more in line with economic societal demands. The technology targets decrease on resources, thus contributing to robust horticulture production systems and decreasing ecological footprints (Mission A, MMIP 1 and 2). Testing parental breeding combinations using the newly developed technology permits use of less resources (space, energy and nutrients for growth) and contributes to the development of new innovative crops that is less energy demanding and more sustainable (Mission B3-E12A, B4-E12B). Our key technology will speed up precision breeding e.g. for biotic and abiotic stress tolerance, disease resistance, drought tolerance, longer shelf-life, more safe healthy crops and ‘precision designed food crops’ thereby contributing to MMIP D2 and D3. Here we aim to (1) construct recombination maps with unprecedented resolution and accuracy, and predict (2) optimal combinations of breeding parents. It thus has great potential guiding breeding of advanced crops and thereby contributes to the realization of MJP Breeding 2.0. We argue our approach is generic and can be applied to reliably profile a wide variety of crop species (tomato, pepper, melon, cucumber, lettuce, rice, papaya, tulip, maize (corn), sugar beet, onion, etc) without the laborious and time-consuming production and screening of offspring populations, greatly benefitting introgression hybridization and precision breeding.
• We have developed a gDNA islolation protocol from pollen samples
• We have developed a high throughput recombination profiling method based on 10X genomic sequencing technology
• We have developed an algorithm for the detection of crossover (CO) recombination and gene conversion.
• We have pinpointed COs from linked read sequence at the nucleotide level in pollen gametes from an F1 cross between S. lycopersicum and S. pimpinellifolium with nucleotide resolution.
• We have published these results
• We have grown additional parental lines. Additional parental crosses were made and pollen from parental lines were harvested.
• Cross pollination of parental lines and subsequent fruit harvest was completed
• F1 seedlings were potted and pollen from F1 lines were harvested
• construction of seq. libs. for parental lines and F1.
• Pollen samples from parental lines and F1 crosses have been sequenced
• Sequence analyses for parental and F1 offspring are currently ongoing
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