Final Report Summary - IDOMMSEED (Identification of molecular mechanisms of seed longevity in the model legume Medicago truncatula)
Survival in the dry state is one of the most astonishing phenomena in nature. Considering that water is essential for life, it is remarkable that biological mechanisms have evolved allowing complete loss of cellular water without loss of viability. This phenomenon is often encountered in seeds whose development includes the successive acquisition of the capacity to germinate, to withstand desiccation to low moisture content and to remain alive in a dried ametabolic state. More strikingly, seeds can stay alive in the dry state for an extended period of time, ranging from decades to even 2 000 years. Seed longevity is a paramount factor on which seed banks rely to preserve biodiversity and an important trait in maintaining the seed quality over time, allowing for rapid, homogeneous seed germination and seedling emergence. Seeds with elevated longevity will deteriorate only slowly during conservation, and will retain high germination vigour. Changes in environmental conditions during seed development also affect potential seed longevity. The lack of understanding of seed longevity in seed crops is causing considerable losses to the seed industry whereas in wild species, it leads to major difficulties in securing high-quality seed conservation for dedicated seed banks. Therefore, the aim of the proposed project is to identify the key determinants seed longevity.
Two main factors contribute to the seed longevity. First, it is strongly dependent on the storage conditions, namely temperature and relative humidity. The second factor determining the longevity of seeds is linked to the intrinsic properties of the stored material. However, the genetic make-up that makes a seed live longer during storage is unknown. Therefore, the global objective of our project was to provide a comprehensive overview on those genes that are involved in seed longevity of the model legume Medicago truncatula using an approach that coupled quantitative trait loci (QTL) analysis to physiology and transcriptomics. Firstly, the project aimed at unravelling the transcriptome of developing and germinating seeds exhibiting different longevities. The two genotypes that were used were the parents of the recombinant inbred line used for the longevity QTL analysis and that differ greatly in storage behaviour. Samples were also analysed at different developmental stages during the acquisition of longevity. Using a heat-shock treatment, we also set up a protocol where longevity was increased in pregerminated seeds. Using a newly developed Nimblegene transcriptomic tool, we found 279 and 255 genes that are systematically over-expressed and repressed, respectively, in seeds exhibiting a higher longevity. Bioinformatic analysis revealed that seed longevity is a complex trait involving many cellular processes associated for example, with lipid and carbohydrate metabolism as well as secondary metabolism.
The second part of the project was devoted at identifying candidate genes that have an influence on seed longevity in different Medicago genotypes. The host laboratory has produced a list of longevity QTL based on an analysis of a RIL population obtained from a cross between DZA315.16 and J6 (Buitink et al., unpublished data). To link the list of the potential candidate genes revealed by the transcriptome analysis to the longevity, we identified in silico the genes that are co-located with those QTL. This approach led to a drastic reduction in the number of candidate genes, varying from 4 to 86 candidate genes, depending on the QTL. The overlap between the different longevity systems allowed to retain 17 and 4 genes that are differentially up- or down-regulated respectively with higher longevity. The advances in genetics, genomics and bioinformatics make the association analysis a more powerful and efficient approach to dissect the role of genes in complex traits such as longevity. Combining the publically available single nucleotide polymorphism (SNP) data and our longevity data, we were able to test the association between SNPs of 11 candidate genes. We also carried out the SNP analysis to the complete regions of the longevity QTL. Combining both approaches, we identified 3 genes that exhibited an increased expression associated with longevity and 2 genes whose expression leads to decreased longevity. These results are highly innovative since these candidate genes and the underlying cellular processes have not yet been associated with seed longevity.
Two main factors contribute to the seed longevity. First, it is strongly dependent on the storage conditions, namely temperature and relative humidity. The second factor determining the longevity of seeds is linked to the intrinsic properties of the stored material. However, the genetic make-up that makes a seed live longer during storage is unknown. Therefore, the global objective of our project was to provide a comprehensive overview on those genes that are involved in seed longevity of the model legume Medicago truncatula using an approach that coupled quantitative trait loci (QTL) analysis to physiology and transcriptomics. Firstly, the project aimed at unravelling the transcriptome of developing and germinating seeds exhibiting different longevities. The two genotypes that were used were the parents of the recombinant inbred line used for the longevity QTL analysis and that differ greatly in storage behaviour. Samples were also analysed at different developmental stages during the acquisition of longevity. Using a heat-shock treatment, we also set up a protocol where longevity was increased in pregerminated seeds. Using a newly developed Nimblegene transcriptomic tool, we found 279 and 255 genes that are systematically over-expressed and repressed, respectively, in seeds exhibiting a higher longevity. Bioinformatic analysis revealed that seed longevity is a complex trait involving many cellular processes associated for example, with lipid and carbohydrate metabolism as well as secondary metabolism.
The second part of the project was devoted at identifying candidate genes that have an influence on seed longevity in different Medicago genotypes. The host laboratory has produced a list of longevity QTL based on an analysis of a RIL population obtained from a cross between DZA315.16 and J6 (Buitink et al., unpublished data). To link the list of the potential candidate genes revealed by the transcriptome analysis to the longevity, we identified in silico the genes that are co-located with those QTL. This approach led to a drastic reduction in the number of candidate genes, varying from 4 to 86 candidate genes, depending on the QTL. The overlap between the different longevity systems allowed to retain 17 and 4 genes that are differentially up- or down-regulated respectively with higher longevity. The advances in genetics, genomics and bioinformatics make the association analysis a more powerful and efficient approach to dissect the role of genes in complex traits such as longevity. Combining the publically available single nucleotide polymorphism (SNP) data and our longevity data, we were able to test the association between SNPs of 11 candidate genes. We also carried out the SNP analysis to the complete regions of the longevity QTL. Combining both approaches, we identified 3 genes that exhibited an increased expression associated with longevity and 2 genes whose expression leads to decreased longevity. These results are highly innovative since these candidate genes and the underlying cellular processes have not yet been associated with seed longevity.