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. Conclusions: 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/bt-software-d-lims.htm

A consensus genetic map of sorghum that integrates multiple component maps and high-throughput Diversity Array Technology (DArT) markers

Background: Sorghum genome mapping based on DNA markers began in the early 1990s and numerous genetic linkage maps of sorghum have been published in the last decade, based initially on RFLP markers with more recent maps including AFLPs and SSRs and very recently, Diversity Array Technology (DArT) markers. It is essential to integrate the rapidly growing body of genetic linkage data produced through DArT with the multiple genetic linkage maps for sorghum generated through other marker technologies. Here, we report on the colinearity of six independent sorghum component maps and on the integration of these component maps into a single reference resource that contains commonly utilized SSRs, AFLPs, and high-throughput DArT markers. Results: The six component maps were constructed using the MultiPoint software. The lengths of the resulting maps varied between 910 and 1528 cM. The order of the 498 markers that segregated in more than one population was highly consistent between the six individual mapping data sets. The framework consensus map was constructed using a "Neighbours" approach and contained 251 integrated bridge markers on the 10 sorghum chromosomes spanning 1355.4 cM with an average density of one marker every 5.4 cM, and were used for the projection of the remaining markers. In total, the sorghum consensus map consisted of a total of 1997 markers mapped to 2029 unique loci ( 1190 DArT loci and 839 other loci) spanning 1603.5 cM and with an average marker density of 1 marker/0.79 cM. In addition, 35 multicopy markers were identified. On average, each chromosome on the consensus map contained 203 markers of which 58.6% were DArT markers. Non-random patterns of DNA marker distribution were observed, with some clear marker-dense regions and some marker-rare regions. Conclusion: The final consensus map has allowed us to map a larger number of markers than possible in any individual map, to obtain a more complete coverage of the sorghum genome and to fill a number of gaps on individual maps. In addition to overall general consistency of marker order across individual component maps, good agreement in overall distances between common marker pairs across the component maps used in this study was determined, using a difference ratio calculation. The obtained consensus map can be used as a reference resource for genetic studies in different genetic backgrounds, in addition to providing a framework for transferring genetic information between different marker technologies and for integrating DArT markers with other genomic resources. DArT markers represent an affordable, high throughput marker system with great utility in molecular breeding programs, especially in crops such as sorghum where SNP arrays are not publicly available.

High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.

High-throughput Phenotyping of Wheat Seminal Root Traits in a Breeding Context

Water availability is a major limiting factor for wheat (Triticum aestivum L.) in rain-fed agricultural systems worldwide. Root architecture has important functional implications for the timing and extent of soil water extraction, yet selection for root traits in wheat breeding programs has been largely limited due to the lack of suitable phenotyping methods. The aim of this research was to develop a low-cost high-throughput phenotyping method to facilitate selection for desirable root traits. We developed a method to assess ‘seminal root angle’ and ‘seminal root number’ in seedlings – two proxy traits associated to root architecture of mature wheat plants (1). The method involves measuring the angle between the first pair of seminal roots and the number of roots of wheat seedlings grown in transparent pots (Figure 1). Images captured at 5 to 10 days after sowing are analyzed to calculate seminal root angle and number. Performing this technique under “speed breeding” conditions (plants grown at a density of 600 plants / m2, under controlled temperature and constant light) allows the selection based on the desired root traits of up to 5 consecutive generations within 12 months. Alternatively, when focusing only on germplasm screening, up to 52 successive phenotypic assays can be conducted within 12 months. This approach has been shown to be highly reproducible, it requires little resource (time, space, and labour) and can be used to rapidly enrich breeding populations with desirable alleles for narrow root angle and a high number of seminal roots to indirectly target the selection of deeper root system with higher branching at depth. Such root characteristics are highly desirable in wheat to cope with the climate model projections, especially in summer rainfall dominant regions including some Australian, Indian, South American and African cropping regions, where winter crops mainly rely on deep stored water.

Novel Anti-Campylobacter Compounds Identified Using High Throughput Screening of a Pre-selected Enriched Small Molecules Library

Campylobacter is a leading cause of foodborne bacterial gastroenteritis worldwide and infections can be fatal. The emergence of antibiotic-resistant Campylobacter spp. necessitates the development of new antimicrobials. We identified novel anti-Campylobacter small molecule inhibitors using a high throughput growth inhibition assay. To expedite screening, we made use of a “bioactive” library of 4,182 compounds that we have previously shown to be active against diverse microbes. Screening for growth inhibition of Campylobacter jejuni, identified 781 compounds that were either bactericidal or bacteriostatic at a concentration of 200 µM. Seventy nine of the bactericidal compounds were prioritized for secondary screening based on their physico-chemical properties. Based on the minimum inhibitory concentration against a diverse range of C. jejuni and a lack of effect on gut microbes, we selected 12 compounds. No resistance was observed to any of these 12 lead compounds when C. jejuni was cultured with lethal or sub-lethal concentrations suggesting that C. jejuni is less likely to develop resistance to these compounds. Top 12 compounds also possessed low cytotoxicity to human intestinal epithelial cells (Caco-2 cells) and no hemolytic activity against sheep red blood cells. Next, these 12 compounds were evaluated for ability to clear C. jejuni in vitro. A total of 10 compounds had an anti-C. jejuni effect in Caco-2 cells with some effective even at 25 µM concentrations. These novel 12 compounds belong to five established antimicrobial chemical classes; piperazines, aryl amines, piperidines, sulfonamide and pyridazinone. Exploitation of analogues of these chemical classes may provide Campylobacter specific drugs that can be applied in both human and animal medicine.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials. © 2015, The Author(s).

Transcriptome analysis of Neotyphodium and Epichloë grass endophytes

Large-scale gene discovery has been performed for the grass fungal endophytes Neotyphodium coenophialum, Neotyphodium lolii, and Epichloë festucae. The resulting sequences have been annotated by comparison with public DNA and protein sequence databases and using intermediate gene ontology annotation tools. Endophyte sequences have also been analysed for the presence of simple sequence repeat and single nucleotide polymorphism molecular genetic markers. Sequences and annotation are maintained within a MySQL database that may be queried using a custom web interface. Two cDNA-based microarrays have been generated from this genome resource. They permit the interrogation of 3806 Neotyphodium genes (NchipTM microarray), and 4195 Neotyphodium and 920 Epichloë genes (EndoChipTM microarray), respectively. These microarrays provide tools for high-throughput transcriptome analysis, including genome-specific gene expression studies, profiling of novel endophyte genes, and investigation of the host grass–symbiont interaction. Comparative transcriptome analysis in Neotyphodium and Epichloë was performed

Domestication to crop improvement: Genetic resources for Sorghum and Saccharum (Andropogoneae).

Background: Both sorghum (Sorghum bicolor) and sugarcane (Saccharum officinarum) are members of the Andropogoneae tribe in the Poaceae and are each other's closest relatives amongst cultivated plants. Both are relatively recent domesticates and comparatively little of the genetic potential of these taxa and their wild relatives has been captured by breeding programmes to date. This review assesses the genetic gains made by plant breeders since domestication and the progress in the characterization of genetic resources and their utilization in crop improvement for these two related species. Genetic Resources: The genome of sorghum has recently been sequenced providing a great boost to our knowledge of the evolution of grass genomes and the wealth of diversity within S. bicolor taxa. Molecular analysis of the Sorghum genus has identified close relatives of S. bicolor with novel traits, endosperm structure and composition that may be used to expand the cultivated gene pool. Mutant populations (including TILLING populations) provide a useful addition to genetic resources for this species. Sugarcane is a complex polyploid with a large and variable number of copies of each gene. The wild relatives of sugarcane represent a reservoir of genetic diversity for use in sugarcane improvement. Techniques for quantitative molecular analysis of gene or allele copy number in this genetically complex crop have been developed. SNP discovery and mapping in sugarcane has been advanced by the development of high-throughput techniques for ecoTILLING in sugarcane. Genetic linkage maps of the sugarcane genome are being improved for use in breeding selection. The improvement of both sorghum and sugarcane will be accelerated by the incorporation of more diverse germplasm into the domesticated gene pools using molecular tools and the improved knowledge of these genomes.

Characterization of tree-to-tree variation in morphological, nutritional and medicinal properties of Canarium indicum nuts

As part of a feasibility study of the commercialization potential of C. indicum nuts as Agroforestry Tree Products in Papua New Guinea, preliminary characterization studies have examined the tree-to-tree variation in morphological traits (nut and kernel mass and kernel:nut ratio), as well as nutritional (carbohydrate, fat, protein, sodium, vitamin E) and medicinal traits (anti-oxidant activity, anti-inflammatory activity and phenolic content) of kernels from 18 to 72 trees in a small number of different villages of Papua New Guinea (East New Britain Province). There was continuous variation in these traits indicating opportunities for multiple trait cultivar development targeted at food and pharmaceutical markets. Certain traits, for example anti-inflammatory activity, in which tree-to-tree variation was highly significant, present greater opportunities than others, such as saturated:unsaturated fatty acid ratio. This intraspecific variation was greater within populations than between populations. The data presented has allowed the development of a strategy to domesticate C. indicum for cultivation in homegardens and cocoa-coconut agroforests, using a participatory approach aimed at the production of agroforestry tree products (AFTPs) to empower small-holders and enhance their livelihoods and income.

DArT markers: Diversity analyses and mapping in Sorghum bicolor

The sequential nature of gel-based marker systems entails low throughput and high costs per assay. Commonly used marker systems such as SSR and SNP are also dependent on sequence information. These limitations result in high cost per data point and significantly limit the capacity of breeding programs to obtain sufficient return on investment to justify the routine use of marker-assisted breeding for many traits and particularly quantitative traits. Diversity Arrays Technology (DArT™) is a cost effective hybridisation-based marker technology that offers a high multiplexing level while being independent of sequence information. This technology offers sorghum breeding programs an alternative approach to whole-genome profiling. We report on the development, application, mapping and utility of DArT™ markers for sorghum germplasm. Results: A genotyping array was developed representing approximately 12,000 genomic clones using PstI+BanII complexity with a subset of clones obtained through the suppression subtractive hybridisation (SSH) method. The genotyping array was used to analyse a diverse set of sorghum genotypes and screening a Recombinant Inbred Lines (RIL) mapping population. Over 500 markers detected variation among 90 accessions used in a diversity analysis. Cluster analysis discriminated well between all 90 genotypes. To confirm that the sorghum DArT markers behave in a Mendelian manner, we constructed a genetic linkage map for a cross between R931945-2-2 and IS 8525 integrating DArT and other marker types. In total, 596 markers could be placed on the integrated linkage map, which spanned 1431.6 cM. The genetic linkage map had an average marker density of 1/2.39 cM, with an average DArT marker density of 1/3.9 cM. Conclusion: We have successfully developed DArT markers for Sorghum bicolor and have demonstrated that DArT provides high quality markers that can be used for diversity analyses and to construct medium-density genetic linkage maps. The high number of DArT markers generated in a single assay not only provides a precise estimate of genetic relationships among genotypes, but also their even distribution over the genome offers real advantages for a range of molecular breeding and genomics applications.

Black Sigatoka disease: new technologies to strengthen eradication strategies in Australia

In 2001, an incursion of Mycosphaerella fijiensis, the causal agent of black Sigatoka, was detected in Australia's largest commercial banana growing region, the Tully Banana Production Area in North Queensland. An intensive surveillance and eradication campaign was undertaken which resulted in the reinstatement of the disease-free status for black Sigatoka in 2005. This was the first time black Sigatoka had ever been eradicated from commercial plantations. The success of the eradication campaign was testament to good working relationships between scientists, growers, crop monitors, quarantine regulatory bodies and industry. A key contributing factor to the success was the deployment of a PCR-based molecular diagnostic assay, developed by the Cooperative Research Centre for Tropical Plant Protection (CRCTPP). This assay complemented morphological identification and allowed high throughput diagnosis of samples facilitating rapid decision-making during the eradication campaign. This paper describes the development and successful deployment of molecular diagnostics for black Sigatoka. Shortcomings in the gel-based assay are discussed and the advantages of highly specific real-time PCR assays, capable of differentiating between Mycosphaerella fijiensis, Mycosphaerella musicola and Mycosphaerella eumusae are outlined. Real-time assays may provide a powerful diagnostic tool for applications in surveillance, disease forecasting and resistance testing for Sigatoka leaf spot diseases.

Rapid internal drainage rates in Ferrosols

Adoption of conservation tillage practices on Red Ferrosol soils in the inland Burnett area of south-east Queensland has been shown to reduce runoff and subsequent soil erosion. However, improved infiltration resulting from these measures has not improved crop performance and there are suggestions of increased loss of soil water via deep drainage. This paper reports data monitoring soil water under real and artificial rainfall events in commercial fields and long-term tillage experiments, and uses the data to explore the rate and mechanisms of deep drainage in this soil type. Soils were characterised by large drainable porosities (≥0.10 m3/m3) in all parts of the profile to depths of 1.50 m, with drainable porosity similar to available water content (AWC) at 0.25 and 0.75 m, but >60% higher than AWC at 1.50 m. Hydraulic conductivity immediately below the tilled layer in both continuously cropped soils and those after a ley pasture phase was shown to decline with increasing soil moisture content, although the rate of decline was much greater in continuously cropped soil. At moisture contents approaching the drained upper limit (pore water pressure = -100cm H2O), estimates of saturated hydraulic conductivity after a ley pasture were 3-5 times greater than in continuously cropped soil, suggesting much greater rates of deep drainage in the former when soils are moist. Hydraulic tensiometers and fringe capacitance sensors monitored during real and artificial rainfall events showed evidence of soils approaching saturation in the surface layers (top 0.30-0.40 m), but there was no evidence of soil moistures exceeding the drained upper limit (i.e. pore water pressures ≤ -100 cm H2O) in deeper layers. Recovery of applied soil water within the top 1.00-1.20 m of the profile during or immediately after rainfall events declined as the starting profile moisture content increased. These effects were consistent with very rapid rates of internal drainage. Sensors deeper in the profile were unable to detect this drainage due to either non-uniformity of conducting macropores (i.e. bypass flow) or unsaturated conductivities in deeper layers that far exceed the saturated hydraulic conductivity of the infiltration throttle at the bottom of the cultivated layer. Large increases in unsaturated hydraulic conductivities are likely with only small increases in water content above the drained upper limit. Further studies with drainage lysimeters and large banks of hydraulic tensiometers are planned to quantify drainage risk in these soil types.

Simple sequence repeat markers associated with three quantitative trait loci for black point resistance can be used to enrich selection populations in bread wheat

Black point in wheat has the potential to cost the Australian industry $A30.4 million a year. It is difficult and expensive to screen for resistance, so the aim of this study was to validate 3 previously identified quantitative trait loci (QTLs) for black point resistance on chromosomes 2B, 4A, and 3D of the wheat variety Sunco. Black point resistance data and simple sequence repeat (SSR) markers, linked to the resistance QTLs and suited to high-throughput assay, were analysed in the doubled haploid population, Batavia (susceptible) × Pelsart (resistant). Sunco and Pelsart both have Cook in their pedigree and both have the Triticum timopheevii translocation on 2B. SSR markers identified for the 3 genetic regions were gwm319 (2B, T. timopheevii translocation), wmc048 (4AS), and gwm341 (3DS). Gwm319 and wmc048 were associated with black point resistance in the validation population. Gwm341 may have an epistatic influence on the trait because when resistance alleles were present at both gwm319 and wmc048, the Batavia-derived allele at gwm341 was associated with a higher proportion of resistant lines. Data are presented showing the level of enrichment achieved for black point resistance, using 1, 2, or 3 of these molecular markers, and the number of associated discarded resistant lines. The level of population enrichment was found to be 1.83-fold with 6 of 17 resistant lines discarded when gwm319 and wmc048 were both used for selection. Interactions among the 3 QTLs appear complex and other genetic and epigenetic factors influence susceptibility to black point. Polymorphism was assessed for these markers within potential breeding material. This indicated that alternative markers to wmc048 may be required for some parental combinations. Based on these results, marker-assisted selection for the major black point resistance QTLs can increase the rate of genetic gain by improving the selection efficiency and may facilitate stacking of black point resistances from different sources.