An informational view of accession rarity and allele specificity in germplasm banks for management and conservation

Optimizing the accession-level quantity of seeds to put into storage to minimize seed (gene)bank regeneration or re-collection

Seed (gene)banking is an effective way to conserve cultivated and wild plant diversity. However, long-term funding is not always consistently sufficient, and there is a need to both strengthen the effectiveness of genebank operations and maximize cost efficiency. One way to control the cost of maintaining a germplasm collection is to optimize the quantity of seeds per accession that is placed into storage, depending on the expected length of time a seed lot will remain above the viability threshold, expected rates of use for distribution and viability testing and on the requirement to ensure a reserve. Here, we express this as an equation, which can be applied to cultivated species and adjusted to different scenarios, but also to inform decisions about use of accessions of wild species where the number of seeds available is limited, a common scenario for wild-species conservation seed banks. For many crop genebanks, given the expected longevity of seeds, it would be worthwhile to increase the number of seeds produced and processed for storage. This would also help to diminish the risk of genetic drift due to frequent cycles of regeneration but would have implications in terms of how accessions are regenerated, in particular, how many plants are used for regeneration and the size of storage facilities. The equation we present can also be rearranged and used to plan how to allocate seeds for testing and use when the number of seeds available is limited. This may have particular relevance for species conservation seed banks.

SeqSNP-Based Targeted GBS Provides Insight into the Genetic Relationships among Global Collections of Brassica rapa ssp. oleifera (Turnip Rape)

Turnip rape is a multi-purpose crop cultivated in temperate regions. Due to its ability to fit into crop rotation systems and its role as a food and feed source, spring-type turnip rape cultivation is on the rise. To improve the crop's productivity and nutritional value, it is essential to understand its genetic diversity. In this study, 188 spring-type accessions were genotyped using SeqSNP, a targeted genotyping-by-sequencing method to determine genetic relationships between various groups and assess the potential effects of mutations within genes regulating major desirable traits. Single nucleotide polymorphism (SNP) alleles at six loci were predicted to have high effects on their corresponding genes' functions, whereas nine loci had country/region-specific alleles. A neighbor-joining cluster analysis revealed three major clusters (I to III). About 72% of cluster-I accessions were of Asian origin, whereas 88.5% of European accessions and all North American accessions were placed in cluster-II or cluster-III. A principal coordinate analysis explained 65.3% of the total genetic variation. An analysis of molecular variance revealed significant differentiation among different groups of accessions. Compared to Asian cultivars, European and North American cultivars share more genetic similarities. Hence, crossbreeding Asian and European cultivars may result in improved cultivars due to desirable allele recombination. Compared to landraces and wild populations, the cultivars had more genetic variation, indicating that breeding had not caused genetic erosion. There were no significant differences between Swedish turnip rape cultivars and the NordGen collection. Hence, crossbreeding with genetically distinct cultivars could enhance the gene pool's genetic diversity and facilitate superior cultivar development.

Genetic Structure and Geographical Differentiation of Traditional Rice (Oryza sativa L.) from Northern Vietnam

Northern Vietnam is one of the most important centers of genetic diversity for cultivated rice. Over thousands of years of cultivation, natural and artificial selection has preserved many traditional rice landraces in northern Vietnam due to its geographic situation, climatic conditions, and many ethnic groups. These local landraces serve as a rich source of genetic variation—an important resource for future crop improvement. In this study, we determined the genetic diversity and population structure of 79 rice landraces collected from northern Vietnam and 19 rice accessions collected from different countries. In total, 98 rice accessions could be differentiated into japonica and indica with moderate genetic diversity and a polymorphism information content of 0.382. Moreover, we found that genetic differentiation was related to geographical regions with an overall PhiPT (analog of fixation index F_ST) value of 0.130. We also detected subspecies-specific markers to classify rice (Oryza sativa L.) into indica and japonica. Additionally, we detected five marker-trait associations and rare alleles that can be applied in future breeding programs. Our results suggest that rice landraces in northern Vietnam have a dynamic genetic system that can create different levels of genetic differentiation among regions, but also maintain a balanced genetic diversity between regions.

Assessment of genetic diversity and population structure of oil palm (Elaeis guineensis Jacq.) field genebank: A step towards molecular-assisted germplasm conservation

Oil palm (Elaeis guineensis) germplasm is exclusively maintained as ex situ living collections in the field for genetic conservation and evaluation. However, this is not for long term and the maintenance of field genebanks is expensive and challenging. Large area of land is required and the germplasms are exposed to extreme weather conditions and casualty from pests and diseases. By using 107 SSR markers, this study aimed to examine the genetic diversity and relatedness of 186 palms from a Nigerian-based oil palm germplasm and to identify core collection for conservation. On average, 8.67 alleles per SSR locus were scored with average effective number of alleles per population ranging from 1.96 to 3.34 and private alleles were detected in all populations. Mean expected heterozygosity was 0.576 ranging from 0.437 to 0.661 and the Wright's fixation index calculated was -0.110. Overall moderate genetic differentiation among populations was detected (mean pairwise population FST = 0.120, gene flow Nm = 1.117 and Nei's genetic distance = 0.466) and this was further confirmed by AMOVA analysis. UPGMA dendogram and Bayesian structure analysis concomitantly clustered the 12 populations into eight genetic groups. The best core collection assembled by Core Hunter ver. 3.2.1 consisted of 58 palms accounting for 31.2% of the original population, which was a smaller core set than using PowerCore 1.0. This core set attained perfect allelic coverage with good representation, high genetic distance between entries, and maintained genetic diversity and structure of the germplasm. This study reported the first molecular characterization and validation of core collections for oil palm field genebank. The established core collection via molecular approach, which captures maximum genetic diversity with minimum redundancy, would allow effective use of genetic resources for introgression and for sustainable oil palm germplasm conservation. The way forward to efficiently conserve the field genebanks into next generation without losing their diversity was further discussed.

Harnessing Crop Wild Diversity for Climate Change Adaptation

Warming and drought are reducing global crop production with a potential to substantially worsen global malnutrition. As with the green revolution in the last century, plant genetics may offer concrete opportunities to increase yield and crop adaptability. However, the rate at which the threat is happening requires powering new strategies in order to meet the global food demand. In this review, we highlight major recent 'big data' developments from both empirical and theoretical genomics that may speed up the identification, conservation, and breeding of exotic and elite crop varieties with the potential to feed humans. We first emphasize the major bottlenecks to capture and utilize novel sources of variation in abiotic stress (i.e., heat and drought) tolerance. We argue that adaptation of crop wild relatives to dry environments could be informative on how plant phenotypes may react to a drier climate because natural selection has already tested more options than humans ever will. Because isolated pockets of cryptic diversity may still persist in remote semi-arid regions, we encourage new habitat-based population-guided collections for genebanks. We continue discussing how to systematically study abiotic stress tolerance in these crop collections of wild and landraces using geo-referencing and extensive environmental data. By uncovering the genes that underlie the tolerance adaptive trait, natural variation has the potential to be introgressed into elite cultivars. However, unlocking adaptive genetic variation hidden in related wild species and early landraces remains a major challenge for complex traits that, as abiotic stress tolerance, are polygenic (i.e., regulated by many low-effect genes). Therefore, we finish prospecting modern analytical approaches that will serve to overcome this issue. Concretely, genomic prediction, machine learning, and multi-trait gene editing, all offer innovative alternatives to speed up more accurate pre- and breeding efforts toward the increase in crop adaptability and yield, while matching future global food demands in the face of increased heat and drought. In order for these 'big data' approaches to succeed, we advocate for a trans-disciplinary approach with open-source data and long-term funding. The recent developments and perspectives discussed throughout this review ultimately aim to contribute to increased crop adaptability and yield in the face of heat waves and drought events.

Comparison of Morphological and Genetic Characteristics of Avocados Grown in Tanzania

Tanzania has been growing avocado for decades. A wide variability of the avocado germplasm has been found, and the crop is largely contributing to the earnings of the farmers, traders, and the government, but its genetic diversity is scantly investigated. With the purpose of comparing morphological and genetic characteristics of this germplasm and uncovering the correlation between them and the geographical location, 226 adult seedling avocado trees were sampled in southwestern Tanzania. Their morphological characters were recorded, and their genetic diversity was evaluated based on 10 microsatellite loci. Discriminant analysis of principal components showed that the germplasm studied consisted of four genetic clusters that had an overall average gene diversity of 0.59 and 15.9% molecular variation among them. Most of the phenotypes were common in at least two clusters. The genetic clusters were also portrayed by multivariate analysis and hierarchical clustering for the molecular data but not for the morphology data. Using the Mantel test, a weak significant correlation was found between the genetic, morphological, and geographical distances, which indicates that the genetic variation present in the material is weakly reflected by the observed phenotypic variation and that both measures of variation varied slightly with the geographical sampling locations.

Genetic diversity and population structure of black cottonwood (Populus deltoides) revealed using simple sequence repeat markers

Background

Black cottonwood (Populus deltoides) is one of the keystone forest tree species, and has become the main breeding parents in poplar hybrid breeding. However, the genetic diversity and population structure of the introduced resources are not fully understood.

Results

In the present study, five loci containing null alleles were excluded and 15 pairs of SSR (simple sequence repeat) primers were used to analyze the genetic diversity and population structure of 384 individuals from six provenances (Missouri, Iowa, Washington, Louisiana, and Tennessee (USA), and Quebec in Canada) of P. deltoides. Ultimately, 108 alleles (N_a) were detected; the expected heterozygosity (H_e) per locus ranged from 0.070 to 0.905, and the average polymorphic information content (PIC) was 0.535. The provenance ‘Was’ had a relatively low genetic diversity, while ‘Que’, ‘Lou’, and ‘Ten’ provenances had high genetic diversity, with Shannon’s information index (I) above 1.0. The mean coefficient of genetic differentiation (F_st) and gene flow (N_m) were 0.129 and 1.931, respectively. Analysis of molecular variance (AMOVA) showed that 84.88% of the genetic variation originated from individuals. Based on principal coordinate analysis (PCoA) and STRUCTURE cluster analysis, individuals distributed in the Mississippi River Basin were roughly classified as one group, while those distributed in the St. Lawrence River Basin and Columbia River Basin were classified as another group. The cluster analysis based on the population level showed that provenance ‘Iow’ had a small gene flow and high degree of genetic differentiation compared with the other provenances, and was classified into one group. There was a significant relationship between genetic distance and geographical distance.

Conclusions

P. deltoides resources have high genetic diversity and there is a moderate level of genetic differentiation among provenances. Geographical isolation and natural conditions may be the main factors causing genetic differences among individuals. Individuals reflecting population genetic information can be selected to build a core germplasm bank. Meanwhile, the results could provide theoretical support for the scientific management and efficient utilization of P. deltoides genetic resources, and promote the development of molecular marker-assisted breeding of poplar.

The impact of sample selection strategies on genetic diversity and representativeness in germplasm bank collections

BACKGROUND

Germplasm banks maintain collections representing the most comprehensive catalogue of native genetic diversity available for crop improvement. Users of germplasm banks are interested in a fixed number of samples representing as broadly as possible the diversity present in the wider collection. A relevant question is whether it is necessary to develop completely independent germplasm samples or it is possible to select nested sets from a pre-defined core set panel not from the whole collection. We used data from 15,384, maize landraces stored in the CIMMYT germplasm bank to study the impact on 8 diversity criteria and the sample representativeness of: (1) two core selection strategies, a statistical sampling (DM), or a numerical maximization method (CH); (2) selecting samples of varying sizes; and (3) selecting samples of different sizes independently of each other or in a nested manner.

RESULTS

Sample sizes greater than 10% of the whole population size retained more than 75% of the polymorphic markers for all selection strategies and types of sample; lower sample sizes showed more variability (instability) among repetitions; the strongest effect of sample size was observed on the CH-independent combination. Independent and nested samples showed similar performance for all the criteria for the DM method, but there were differences between them for the CH method. The DM method achieved better approximations to the known values in the population than the CH method; 2-d multidimensional scaling plots of the collection and samples highlighted tendency of sample selection towards the extremes of diversity in the CH method, compared with sampling more representative of the overall genotypic distribution of diversity under the DM method.

CONCLUSIONS

The use of core subsets of size greater than or equal to 10% of the whole collection satisfied well the requirement of representativeness and diversity. Nested samples showed similar diversity and representativeness characteristics as independent samples offering a cost effective method of sample definition for germplasm banks. For most criteria assessed the DM method achieved better approximations to the known values in the whole population than the CH method, that is, it generated more statistically representative samples from collections.