African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning.

Soil property and class maps for the continent of Africa were so far only available at very generalised scales, with many countries not mapped at all. Thanks to an increasing quantity and availability of soil samples collected at field point locations by various government and/or NGO funded projects, it is now possible to produce detailed pan-African maps of soil nutrients, including micro-nutrients at fine spatial resolutions. In this paper we describe production of a 30 m resolution Soil Information System of the African continent using, to date, the most comprehensive compilation of soil samples ([Formula: see text]) and Earth Observation data. We produced predictions for soil pH, organic carbon (C) and total nitrogen (N), total carbon, effective Cation Exchange Capacity (eCEC), extractable-phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), sodium (Na), iron (Fe), zinc (Zn)-silt, clay and sand, stone content, bulk density and depth to bedrock, at three depths (0, 20 and 50 cm) and using 2-scale 3D Ensemble Machine Learning framework implemented in the mlr (Machine Learning in R) package. As covariate layers we used 250 m resolution (MODIS, PROBA-V and SM2RAIN products), and 30 m resolution (Sentinel-2, Landsat and DTM derivatives) images. Our fivefold spatial Cross-Validation results showed varying accuracy levels ranging from the best performing soil pH (CCC = 0.900) to more poorly predictable extractable phosphorus (CCC = 0.654) and sulphur (CCC = 0.708) and depth to bedrock. Sentinel-2 bands SWIR (B11, B12), NIR (B09, B8A), Landsat SWIR bands, and vertical depth derived from 30 m resolution DTM, were the overall most important 30 m resolution covariates. Climatic data images-SM2RAIN, bioclimatic variables and MODIS Land Surface Temperature-however, remained as the overall most important variables for predicting soil chemical variables at continental scale. This publicly available 30-m Soil Information System of Africa aims at supporting numerous applications, including soil and fertilizer policies and investments, agronomic advice to close yield gaps, environmental programs, or targeting of nutrition interventions.

Revisiting the hetero-fertilization phenomenon in maize.

Development of a seed DNA-based genotyping system for marker-assisted selection (MAS) has provided a novel opportunity for understanding aberrant reproductive phenomena such as hetero-fertilization (HF) by observing the mismatch of endosperm and leaf genotypes in monocot species. In contrast to conventional approaches using specific morphological markers, this approach can be used for any population derived from diverse parental genotypes. A large-scale experiment was implemented using seven F(2) populations and four three-way cross populations, each with 534 to 1024 individuals. The frequency of HF within these populations ranged from 0.14% to 3.12%, with an average of 1.46%. The highest frequency of HF in both types of population was contributed by the pollen gametes. Using three-way crosses allowed, for the first time, detection of the HF contributed by maternal gametes, albeit at very low frequency (0.14%-0.65%). Four HF events identified from each of two F(2) populations were tested and confirmed using 1032 single nucleotide polymorphic markers. This analysis indicated that only 50% of polymorphic markers can detect a known HF event, and thus the real HF frequency can be inferred by doubling the estimate obtained from using only one polymorphic marker. As expected, 99% of the HF events can be detected by using seven independent markers in combination. Although seed DNA-based analysis may wrongly predict plant genotypes due to the mismatch of endosperm and leaf DNA caused by HF, the relatively low HF frequencies revealed with diverse germplasm in this study indicates that the effect on the accuracy of MAS is limited. In addition, comparative endosperm and leaf DNA analysis of specific genetic stocks could be useful for revealing the relationships among various aberrant fertilization phenomena including haploidy and apomixis.

Effects of the nanostructuring of gold films upon their thermal stability.

We report results relating to the thermal stability of nanoparticles and show a remarkable effect of nanostructuring of the metal. Au films are nanostructured by focused ion beam sputtering (FIB) to produce isolated areas of metal, which are imaged by atomic force microscopy (AFM). Images of the surface show that, if the islands are made small enough, the metal in the islands is lost by evaporation, whereas the nonfabricated areas outside are relatively stable and the nanoparticles remain present there.

Monitoring the threat of unintentional transgene flow into maize gene banks and breeding materials

The use of transgenic crops is steadily increasing around the world, led by soybean (based on total area) and maize (in terms of total number of countries). Transgenic maize is grown in at least 17 countries across four continents: Africa, America, Asia and Europe. The comprehensive global spread of transgenic maize has significant implications for organizations involved in germplasm conservation and genetic enhancement; particularly as some countries require a GMO-free declaration when receiving shipments of maize germplasm. This article describes the protocol used by the International Maize and Wheat Improvement Center (CIMMYT) for monitoring unintentional transgene flow in maize genebank and breeding plots. The protocol is based on polymerase chain reaction (PCR) markers for detecting specific recombinant DNA sequences in bulked samples collected from sentinel plots. To date, no unintentional transgene flow has been detected in CIMMYT fields of maize genebank accessions or breeding materials.

Nucleotide diversity and molecular evolution of the PSY1 gene in Zea mays compared to some other grass species.

Phytoene synthase (PSY), which is encoded by the phytoene synthase 1 (PSY1) gene, is the first rate-limiting enzyme in the plant carotenoid biosynthetic pathway. In order to examine the genetic diversity and evolution pattern of PSY1 within the Andropogoneae, sequences of 76 accessions from 5 species (maize, teosinte, tripsacum, coix, and sorghum) of the Andropogoneae were tested, along with 4 accessions of rice (Oryza sativa L.) included as outliers. Both the number and the order of exons and introns were relatively conserved across the species tested. Three domains were identified in the coding sequence, including signal peptide (SP), PSY, and highly conserved squalene synthase (SQS) domain. Although no positive selection signal was detected at an overall coding level among all species tested, the SP domain and the region upstream of the SQS-PSY domain appear to have undergone rapid evolution, as evidenced by a high d (N)/d (S) ratio (>1.0). At the nucleotide level, positive selection and balancing selection were detected only among the yellow maize germplasm and the white maize germplasm, respectively. The phylogenetic tree based on full-length sequences of PSY1-like regions supported the monophyletic theory of the Andropogoneae and the closest relationship between Zea and Tripsacum among the Andropogoneae. Coix, which was theorized to have a closer relationship with maize due to similarities in morphology and chromosome number, has been shown in this study to have diverged relatively early from the other Andropogoneae, including maize.

Genetic characterization and linkage disequilibrium estimation of a global maize collection using SNP markers.

A newly developed maize Illumina GoldenGate Assay with 1536 SNPs from 582 loci was used to genotype a highly diverse global maize collection of 632 inbred lines from temperate, tropical, and subtropical public breeding programs. A total of 1229 informative SNPs and 1749 haplotypes within 327 loci was used to estimate the genetic diversity, population structure, and familial relatedness. Population structure identified tropical and temperate subgroups, and complex familial relationships were identified within the global collection. Linkage disequilibrium (LD) was measured overall and within chromosomes, allelic frequency groups, subgroups related by geographic origin, and subgroups of different sample sizes. The LD decay distance differed among chromosomes and ranged between 1 to 10 kb. The LD distance increased with the increase of minor allelic frequency (MAF), and with smaller sample sizes, encouraging caution when using too few lines in a study. The LD decay distance was much higher in temperate than in tropical and subtropical lines, because tropical and subtropical lines are more diverse and contain more rare alleles than temperate lines. A core set of inbreds was defined based on haplotypes, and 60 lines capture 90% of the haplotype diversity of the entire panel. The defined core sets and the entire collection can be used widely for different research targets.

Molecular characterization of global maize breeding germplasm based on genome-wide single nucleotide polymorphisms.

Characterization of genetic diversity is of great value to assist breeders in parental line selection and breeding system design. We screened 770 maize inbred lines with 1,034 single nucleotide polymorphism (SNP) markers and identified 449 high-quality markers with no germplasm-specific biasing effects. Pairwise comparisons across three distinct sets of germplasm, CIMMYT (394), China (282), and Brazil (94), showed that the elite lines from these diverse breeding pools have been developed with only limited utilization of genetic diversity existing in the center of origin. Temperate and tropical/subtropical germplasm clearly clustered into two separate groups. The temperate germplasm could be further divided into six groups consistent with known heterotic patterns. The greatest genetic divergence was observed between temperate and tropical/subtropical lines, followed by the divergence between yellow and white kernel lines, whereas the least divergence was observed between dent and flint lines. Long-term selection for hybrid performance has contributed to significant allele differentiation between heterotic groups at 20% of the SNP loci. There appeared to be substantial levels of genetic variation between different breeding pools as revealed by missing and unique alleles. Two SNPs developed from the same candidate gene were associated with the divergence between two opposite Chinese heterotic groups. Associated allele frequency change at two SNPs and their allele missing in Brazilian germplasm indicated a linkage disequilibrium block of 142 kb. These results confirm the power of SNP markers for diversity analysis and provide a feasible approach to unique allele discovery and use in maize breeding programs.

Advances in maize genomics and their value for enhancing genetic gains from breeding.

Maize is an important crop for food, feed, forage, and fuel across tropical and temperate areas of the world. Diversity studies at genetic, molecular, and functional levels have revealed that, tropical maize germplasm, landraces, and wild relatives harbor a significantly wider range of genetic variation. Among all types of markers, SNP markers are increasingly the marker-of-choice for all genomics applications in maize breeding. Genetic mapping has been developed through conventional linkage mapping and more recently through linkage disequilibrium-based association analyses. Maize genome sequencing, initially focused on gene-rich regions, now aims for the availability of complete genome sequence. Conventional insertion mutation-based cloning has been complemented recently by EST- and map-based cloning. Transgenics and nutritional genomics are rapidly advancing fields targeting important agronomic traits including pest resistance and grain quality. Substantial advances have been made in methodologies for genomics-assisted breeding, enhancing progress in yield as well as abiotic and biotic stress resistances. Various genomic databases and informatics tools have been developed, among which MaizeGDB is the most developed and widely used by the maize research community. In the future, more emphasis should be given to the development of tools and strategic germplasm resources for more effective molecular breeding of tropical maize products.

Isolation and characterization of novel microsatellite markers and their application for diversity assessment in cultivated groundnut (Arachis hypogaea).

BACKGROUND: Cultivated peanut or groundnut (Arachis hypogaea L.) is the fourth most important oilseed crop in the world, grown mainly in tropical, subtropical and warm temperate climates. Due to its origin through a single and recent polyploidization event, followed by successive selection during breeding efforts, cultivated groundnut has a limited genetic background. In such species, microsatellite or simple sequence repeat (SSR) markers are very informative and useful for breeding applications. The low level of polymorphism in cultivated germplasm, however, warrants a need of larger number of polymorphic microsatellite markers for cultivated groundnut. RESULTS: A microsatellite-enriched library was constructed from the genotype TMV2. Sequencing of 720 putative SSR-positive clones from a total of 3,072 provided 490 SSRs. 71.2% of these SSRs were perfect type, 13.1% were imperfect and 15.7% were compound. Among these SSRs, the GT/CA repeat motifs were the most common (37.6%) followed by GA/CT repeat motifs (25.9%). The primer pairs could be designed for a total of 170 SSRs and were optimized initially on two genotypes. 104 (61.2%) primer pairs yielded scorable amplicon and 46 (44.2%) primers showed polymorphism among 32 cultivated groundnut genotypes. The polymorphic SSR markers detected 2 to 5 alleles with an average of 2.44 per locus. The polymorphic information content (PIC) value for these markers varied from 0.12 to 0.75 with an average of 0.46. Based on 112 alleles obtained by 46 markers, a phenogram was constructed to understand the relationships among the 32 genotypes. Majority of the genotypes representing subspecies hypogaea were grouped together in one cluster, while the genotypes belonging to subspecies fastigiata were grouped mainly under two clusters. CONCLUSION: Newly developed set of 104 markers extends the repertoire of SSR markers for cultivated groundnut. These markers showed a good level of PIC value in cultivated germplasm and therefore would be very useful for germplasm analysis, linkage mapping, diversity studies and phylogenetic relationships in cultivated groundnut as well as related Arachis species.

Association analysis of historical bread wheat germplasm using additive genetic covariance of relatives and population structure.

Linkage disequilibrium can be used for identifying associations between traits of interest and genetic markers. This study used mapped diversity array technology (DArT) markers to find associations with resistance to stem rust, leaf rust, yellow rust, and powdery mildew, plus grain yield in five historical wheat international multienvironment trials from the International Maize and Wheat Improvement Center (CIMMYT). Two linear mixed models were used to assess marker-trait associations incorporating information on population structure and covariance between relatives. An integrated map containing 813 DArT markers and 831 other markers was constructed. Several linkage disequilibrium clusters bearing multiple host plant resistance genes were found. Most of the associated markers were found in genomic regions where previous reports had found genes or quantitative trait loci (QTL) influencing the same traits, providing an independent validation of this approach. In addition, many new chromosome regions for disease resistance and grain yield were identified in the wheat genome. Phenotyping across up to 60 environments and years allowed modeling of genotype x environment interaction, thereby making possible the identification of markers contributing to both additive and additive x additive interaction effects of traits.

Application of identified QTL-marker associations in rice quality improvement through a design-breeding approach.

A permanent mapping population of rice consisting of 65 non-idealized chromosome segment substitution lines (denoted as CSSL1 to CSSL65) and 82 donor parent chromosome segments (denoted as M1 to M82) was used to identify QTL with additive effects for two rice quality traits, area of chalky endosperm (ACE) and amylose content (AC), by a likelihood ratio test based on stepwise regression. Subsequently, the genetics and breeding simulation tool QuLine was employed to demonstrate the application of the identified QTL in rice quality improvement. When a LOD threshold of 2.0 was used, a total of 16 chromosome segments were associated with QTL for ACE, and a total of 15 segments with QTL for AC in at least one environment. Four target genotypes denoted as DG1 to DG4 were designed based on the identified QTL, and according to low ACE and high AC breeding objectives. Target genotypes DG1 and DG2 can be achieved via a topcross (TC) among the three lines CSSL4, CSSL28, and CSSL49. Results revealed that TC2: (CSSL4 x CSSL49) x CSSL28 and TC3: (CSSL28 x CSSL49) x CSSL4 resulted in higher DG1 frequency in their doubled haploid populations, whereas TC1: (CSSL4 x CSSL28) x CSSL49 resulted in the highest DG2 frequency. Target genotypes DG3 and DG4 can be developed by a double cross among the four lines CSSL4, CSSL28, CSSL49, and CSSL52. In a double cross, the order of parents affects the frequency of target genotype to be selected. Results suggested that the double cross between the two single crosses (CSSL4 x CSSL28) and (CSSL49 x CSSL52) resulted in the highest frequency for DG3 and DG4 genotypes in its derived doubled haploid derivatives. Using an enhancement selection methodology, alternative ways were investigated to increase the target genotype frequency without significantly increasing the total cost of breeding operations.

QTL mapping of grain length in rice (Oryza sativa L.) using chromosome segment substitution lines.

Chromosome segment substitution (CSS) lines have the potential for use in QTL fine mapping and map-based cloning. The standard t-test used in the idealized case that each CSS line has a single segment from the donor parent is not suitable for non-idealized CSS lines carrying several substituted segments from the donor parent. In this study, we present a likelihood ratio test based on stepwise regression (RSTEP-LRT) that can be used for QTL mapping in a population consisting of non-idealized CSS lines. Stepwise regression is used to select the most important segments for the trait of interest, and the likelihood ratio test is used to calculate the LOD score of each chromosome segment. This method is statistically equivalent to the standard t-test with idealized CSS lines. To further improve the power of QTL mapping, a method is proposed to decrease multicollinearity among markers (or chromosome segments). QTL mapping with an example CSS population in rice consisting of 65 non-idealized CSS lines and 82 chromosome segments indicated that a total of 18 segments on eight of the 12 rice chromosomes harboured QTLs affecting grain length under the LOD threshold of 2.5. Three major stable QTLs were detected in all eight environments. Some minor QTLs were not detected in all environments, but they could increase or decrease the grain length constantly. These minor genes are also useful in marker-assisted gene pyramiding.

Laboratory Information Management Software for genotyping workflows: applications in high throughput crop genotyping.

BACKGROUND: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow. RESULTS: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. CONCLUSION: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/gt-bt/lims/lims.asp.

A database of annotated tentative orthologs from crop abiotic stress transcripts.

A minimal requirement to initiate a comparative genomics study on plant responses to abiotic stresses is a dataset of orthologous sequences. The availability of a large amount of sequence information, including those derived from stress cDNA libraries allow for the identification of stress related genes and orthologs associated with the stress response. Orthologous sequences serve as tools to explore genes and their relationships across species. For this purpose, ESTs from stress cDNA libraries across 16 crop species including 6 important cereal crops and 10 dicots were systematically collated and subjected to bioinformatics analysis such as clustering, grouping of tentative orthologous sets, identification of protein motifs/patterns in the predicted protein sequence, and annotation with stress conditions, tissue/library source and putative function. All data are available to the scientific community at http://intranet.icrisat.org/gt1/tog/homepage.htm. We believe that the availability of annotated plant abiotic stress ortholog sets will be a valuable resource for researchers studying the biology of environmental stresses in plant systems, molecular evolution and genomics.

Analysis of genomic sequences from peanut (Arachis hypogaea)

Peanut is an important legume crop across the world. However, in contrast to most legume crops, groundnut lacks taxonomic proximity to any major model genome. A relatively large number of genomic sequences were generated from groundnut as part of a microsatellite marker development project. In the current study, a total of 1312 sequences were analyzed of which 448 contained microsatellite motifs. All sequences (GenBank Accessions: BZ999351-CC000573) were analyzed after clustering for possible similarity with publicly available sequences from Arabidopsis, Lotus, soybean and Medicago. At least 39 percent of the sequences analyzed had significant BLAST similarities with sequences from the four databases searched, of which nearly half (47 percent) found significant similarity with Lotus japonicus sequences. Over one quarter (26.7 percent) of sequences found similarity with Arabidopsis thaliana, while the remainder aligned with publicly available sequences from the legumes soybean and Medicago truncatula. At least 17 percent of microsatellite containing sequences could be assigned an identity. The codon usage pattern for Arachis hypogaea most closely resembles that of L. japonicus reflecting the similarly high sequence similarity observed in BLAST searches at the protein level. The implications of these findings for the taxonomy, and comparative genomics of groundnut and its legume family relatives are discussed.

Development of ESTs from chickpea roots and their use in diversity analysis of the Cicer genus.

BACKGROUND: Chickpea is a major crop in many drier regions of the world where it is an important protein-rich food and an increasingly valuable traded commodity. The wild annual Cicer species are known to possess unique sources of resistance to pests and diseases, and tolerance to environmental stresses. However, there has been limited utilization of these wild species by chickpea breeding programs due to interspecific crossing barriers and deleterious linkage drag. Molecular genetic diversity analysis may help predict which accessions are most likely to produce fertile progeny when crossed with chickpea cultivars. While, trait-markers may provide an effective tool for breaking linkage drag. Although SSR markers are the assay of choice for marker-assisted selection of specific traits in conventional breeding populations, they may not provide reliable estimates of interspecific diversity, and may lose selective power in backcross programs based on interspecific introgressions. Thus, we have pursued the development of gene-based markers to resolve these problems and to provide candidate gene markers for QTL mapping of important agronomic traits. RESULTS: An EST library was constructed after subtractive suppressive hybridization (SSH) of root tissue from two very closely related chickpea genotypes (Cicer arietinum). A total of 106 EST-based markers were designed from 477 sequences with functional annotations and these were tested on C. arietinum. Forty-four EST markers were polymorphic when screened across nine Cicer species (including the cultigen). Parsimony and PCoA analysis of the resultant EST-marker dataset indicated that most accessions cluster in accordance with the previously defined classification of primary (C. arietinum, C. echinospermum and C. reticulatum), secondary (C. pinnatifidum, C. bijugum and C. judaicum), and tertiary (C. yamashitae, C. chrossanicum and C. cuneatum) gene-pools. A large proportion of EST alleles (45%) were only present in one or two of the accessions tested whilst the others were represented in up to twelve of the accessions tested. CONCLUSION: Gene-based markers have proven to be effective tools for diversity analysis in Cicer and EST diversity analysis may be useful in identifying promising candidates for interspecific hybridization programs. The EST markers generated in this study have detected high levels of polymorphism amongst both common and rare alleles. This suggests that they would be useful for allele-mining of germplasm collections for identification of candidate accessions in the search for new sources of resistance to pests / diseases, and tolerance to abiotic stresses.

A legume genomics resource: The Chickpea Root Expressed Sequence Tag Database

Chickpea, a lesser-studied grain legume, is being investigated due to its taxonomic proximity with the model legume genome Medicago truncatula and its ability to endure and grow in relatively low soil water contents making it a model legume crop for the study of agronomic response to drought stress. Public databases currently contain very few sequences from chickpea associated with expression in root tissues. However, root traits are likely to be one of the most important components of drought tolerance in chickpea. Thus, we have generated a set of over 2800 chickpea expressed sequence tags (ESTs) from a library constructed after subtractive suppressive hybridization (SSH) of root tissue from two closely related chickpea genotypes possessing different sources of drought avoidance and tolerance (ICC4958 and Annigeri respectively). This database provides researchers in legume genomics with a major new resource for data mining associated with root traits and drought tolerance. This report describes the development and utilization of the database and provides the tools we have developed to facilitate the bioinformatics pipeline used for analysis of the ESTs in this database. We also discuss applications that have already been achieved using this resource.