Genetic variation of growth dynamics in maize (Zea mays L.) revealed through automated non‐invasive phenotyping

Hitherto, most quantitative trait loci of maize growth and biomass yield have been identified for a single time point, usually the final harvest stage. Through this approach cumulative effects are detected, without considering genetic factors causing phase‐specific differences in growth rates. To assess the genetics of growth dynamics, we employed automated non‐invasive phenotyping to monitor the plant sizes of 252 diverse maize inbred lines at 11 different developmental time points; 50 k SNP array genotype data were used for genome‐wide association mapping and genomic selection. The heritability of biomass was estimated to be over 71%, and the average prediction accuracy amounted to 0.39. Using the individual time point data, 12 main effect marker‐trait associations (MTAs) and six pairs of epistatic interactions were detected that displayed different patterns of expression at various developmental time points. A subset of them also showed significant effects on relative growth rates in different intervals. The detected MTAs jointly explained up to 12% of the total phenotypic variation, decreasing with developmental progression. Using non‐parametric functional mapping and multivariate mapping approaches, four additional marker loci affecting growth dynamics were detected. Our results demonstrate that plant biomass accumulation is a complex trait governed by many small effect loci, most of which act at certain restricted developmental phases. This highlights the need for investigation of stage‐specific growth affecting genes to elucidate important processes operating at different developmental phases.     

Functional mapping of N deficiency‐induced response in wheat yield‐component traits by implementing high‐throughput phenotyping

As overfertilization leads to environmental concerns and the cost of N fertilizer increases, the issue of how to select crop cultivars that can produce high yields on N‐deficient soils has become crucially important. However, little information is known about the genetic mechanisms by which crops respond to environmental changes induced by N signaling. Here, we dissected the genetic architecture of N‐induced phenotypic plasticity in bread wheat (Triticum aestivum L.) by integrating functional mapping and semiautomatic high‐throughput phenotyping data of yield‐related canopy architecture. We identified a set of quantitative trait loci (QTLs) that determined the pattern and magnitude of how wheat cultivars responded to low N stress from normal N supply throughout the wheat life cycle. This analysis highlighted the phenological landscape of genetic effects exerted by individual QTLs, as well as their interactions with N‐induced signals and with canopy measurement angles. This information may shed light on our mechanistic understanding of plant adaptation and provide valuable information for the breeding of N‐deficiency tolerant wheat varieties.     

High‐throughput two‐dimensional root system phenotyping platform facilitates genetic analysis of root growth and development

High‐throughput phenotyping of root systems requires a combination of specialized techniques and adaptable plant growth, root imaging and software tools. A custom phenotyping platform was designed to capture images of whole root systems, and novel software tools were developed to process and analyse these images. The platform and its components are adaptable to a wide range root phenotyping studies using diverse growth systems (hydroponics, paper pouches, gel and soil) involving several plant species, including, but not limited to, rice, maize, sorghum, tomato and Arabidopsis. The RootReader2D software tool is free and publicly available and was designed with both user‐guided and automated features that increase flexibility and enhance efficiency when measuring root growth traits from specific roots or entire root systems during large‐scale phenotyping studies. To demonstrate the unique capabilities and high‐throughput capacity of this phenotyping platform for studying root systems, genome‐wide association studies on rice (Oryza sativa) and maize (Zea mays) root growth were performed and root traits related to aluminium (Al) tolerance were analysed on the parents of the maize nested association mapping (NAM) population.     

Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency

In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the study of natural variation in photosynthetic efficiency, for which forward genetics studies have yielded only a little progress in our understanding of the genetic layout of the trait. High‐throughput phenotyping, primarily from chlorophyll fluorescence imaging, should help to dissect the genetics of photosynthesis at the different levels of both plant physiology and development. Specific emphasis should be directed towards understanding the acclimation of the photosynthetic machinery in fluctuating environments, which may be crucial for the identification of genetic variation for relevant traits in food crops. Facilities should preferably be designed to accommodate phenotyping of photosynthesis‐related traits in such environments. The use of forward genetics to study the genetic architecture of photosynthesis is likely to lead to the discovery of novel traits and/or genes that may be targeted in breeding or bio‐engineering approaches to improve crop photosynthetic efficiency. In the near future, big data approaches will play a pivotal role in data processing and streamlining the phenotype‐to‐gene identification pipeline.     

Non‐replication of genome‐wide‐based associations of efficient food conversion in dairy cows

Animal growth relative to food energy input is of key importance to agricultural production. Several recent studies highlighted genetic markers associated with food conversion efficiency in beef cattle, and there is now a requirement to validate these associations in additional populations and to assess their potential utility for selecting animals with enhanced food‐use efficiency. The current analysis tested a population of dairy cattle using 138 DNA markers previously associated with food intake and growth in a whole‐genome association analysis of beef animals. Although seven markers showed point‐wise significance at P < 0.05, none of the single‐nucleotide polymorphisms tested were significantly associated with food conversion efficiency after correction for multiple testing. These data do not support the involvement of this subset of previously implicated markers in the food conversion efficiency of the physiologically distinct New Zealand Holstein‐Friesian dairy breed.     

Equalizing growth in high‐throughput small scale cultivations via precultures operated in fed‐batch mode

An often underestimated problem when working with different clones in microtiter plates and shake flask screenings is the non‐parallel and non‐equal growth of batch cultures. These growth differences are caused by variances of individual clones regarding initial biomass concentration, lag‐phase or specific growth rate. Problems arising from unequal growth kinetics are different induction points in expression studies or uneven cultivation periods at the time of harvest. Screening for the best producing clones of a library under comparable conditions is thus often impractical or even impossible. A new approach to circumvent the problem of unequal growth kinetics of main cultures is the application of fed‐batch mode in precultures in microtiter plates and shake flasks. Fed‐batch operation in precultures is realized through a slow‐release system for glucose. After differently growing cultures turn to glucose‐limited growth, they all consume the same amount of glucose due to the fixed feed profile of glucose provided by the slow‐release system. This leads to equalized growth. Inherent advantages of this method are that it is easy to use and requires no additional equipment like pumps. This new technique for growth equalization in high‐throughput cultivations is simulated and verified experimentally. The growth of distinctly inoculated precultures in microtiter plates and shake flasks could be equalized for different microorganisms such as Escherichia coli and Hansenula polymorpha. Biotechnol. Bioeng. 2009;103: 1095–1102. © 2009 Wiley Periodicals, Inc.     

Genome‐wide association QTL mapping for teat number in a purebred population of Duroc pigs

Because of increasing litter size in Western pig breeds, additional teats are desirable to increase the capacity for nursing offspring. We applied genome‐wide SNP markers to detect QTL regions that affect teat number in a Duroc population. We phenotyped 1024 animals for total teat number. A total of 36 588 SNPs on autosomes were used in the analysis. The estimated heritability for teat number was 0.34 ± 0.05 on the basis of a genomic relationship matrix constructed from all SNP markers. Using a BayesC method, we identified a total of 18 QTL regions that affected teat number in Duroc pigs; 9 of the 18 regions were newly detected.     

Elucidating cryptic dynamics of Theileria communities in African buffalo using a high‐throughput sequencing informatics approach

1. Increasing access to next‐generation sequencing (NGS) technologies is revolutionizing the life sciences. In disease ecology, NGS‐based methods have the potential to provide higher‐resolution data on communities of parasites found in individual hosts as well as host populations.
2. Here, we demonstrate how a novel analytical method, utilizing high‐throughput sequencing of PCR amplicons, can be used to explore variation in blood‐borne parasite (Theileria—Apicomplexa: Piroplasmida) communities of African buffalo at higher resolutions than has been obtained with conventional molecular tools.
3. Results reveal temporal patterns of synchronized and opposite fluctuations of prevalence and relative abundance of Theileria spp. within the host population, suggesting heterogeneous transmission across taxa. Furthermore, we show that the community composition of Theileria spp. and their subtypes varies considerably between buffalo, with differences in composition reflected in mean and variance of overall parasitemia, thereby showing potential to elucidate previously unexplained contrasts in infection outcomes for host individuals.
4. Importantly, our methods are generalizable as they can be utilized to describe blood‐borne parasite communities in any host species. Furthermore, our methodological framework can be adapted to any parasite system given the appropriate genetic marker.
5. The findings of this study demonstrate how a novel NGS‐based analytical approach can provide fine‐scale, quantitative data, unlocking opportunities for discovery in disease ecology.

     

Seasonal diversity and dynamics of haptophytes in the Skagerrak,Norway, explored by high‐throughput sequencing

Microalgae in the division Haptophyta play key roles in the marine ecosystem and in global biogeochemical processes. Despite their ecological importance, knowledge on seasonal dynamics, community composition and abundance at the species level is limited due to their small cell size and few morphological features visible under the light microscope. Here, we present unique data on haptophyte seasonal diversity and dynamics from two annual cycles, with the taxonomic resolution and sampling depth obtained with high‐throughput sequencing. From outer Oslofjorden, S Norway, nano‐ and picoplanktonic samples were collected monthly for 2 years, and the haptophytes targeted by amplification of RNA/cDNA with Haptophyta‐specific 18S rDNA V4 primers. We obtained 156 operational taxonomic units (OTUs), from c. 400.000 454 pyrosequencing reads, after rigorous bioinformatic filtering and clustering at 99.5%. Most OTUs represented uncultured and/or not yet 18S rDNA‐sequenced species. Haptophyte OTU richness and community composition exhibited high temporal variation and significant yearly periodicity. Richness was highest in September–October (autumn) and lowest in April–May (spring). Some taxa were detected all year, such as Chrysochromulina simplex, Emiliania huxleyi and Phaeocystis cordata, whereas most calcifying coccolithophores only appeared from summer to early winter. We also revealed the seasonal dynamics of OTUs representing putative novel classes (clades HAP‐3–5) or orders (clades D, E, F). Season, light and temperature accounted for 29% of the variation in OTU composition. Residual variation may be related to biotic factors, such as competition and viral infection. This study provides new, in‐depth knowledge on seasonal diversity and dynamics of haptophytes in North Atlantic coastal waters.     

A predictive high‐throughput scale‐down model of monoclonal antibody production in CHO cells

Multi‐factorial experimentation is essential in understanding the link between mammalian cell culture conditions and the glycoprotein product of any biomanufacturing process. This understanding is increasingly demanded as bioprocess development is influenced by the Quality by Design paradigm. We have developed a system that allows hundreds of micro‐bioreactors to be run in parallel under controlled conditions, enabling factorial experiments of much larger scope than is possible with traditional systems. A high‐throughput analytics workflow was also developed using commercially available instruments to obtain product quality information for each cell culture condition. The micro‐bioreactor system was tested by executing a factorial experiment varying four process parameters: pH, dissolved oxygen, feed supplement rate, and reduced glutathione level. A total of 180 micro‐bioreactors were run for 2 weeks during this DOE experiment to assess this scaled down micro‐bioreactor system as a high‐throughput tool for process development. Online measurements of pH, dissolved oxygen, and optical density were complemented by offline measurements of glucose, viability, titer, and product quality. Model accuracy was assessed by regressing the micro‐bioreactor results with those obtained in conventional 3 L bioreactors. Excellent agreement was observed between the micro‐bioreactor and the bench‐top bioreactor. The micro‐bioreactor results were further analyzed to link parameter manipulations to process outcomes via leverage plots, and to examine the interactions between process parameters. The results show that feed supplement rate has a significant effect (P < 0.05) on all performance metrics with higher feed rates resulting in greater cell mass and product titer. Culture pH impacted terminal integrated viable cell concentration, titer and intact immunoglobulin G titer, with better results obtained at the lower pH set point. The results demonstrate that a micro‐scale system can be an excellent model of larger scale systems, while providing data sets broader and deeper than are available by traditional methods. Biotechnol. Bioeng. 2009; 104: 1107–1120. © 2009 Wiley Periodicals, Inc.     

Population structure and genetic basis of the agronomic traits of upland cotton in China revealed by a genome‐wide association study using high‐density SNPs

Gossypium hirsutum L. represents the largest source of textile fibre, and China is one of the largest cotton‐producing and cotton‐consuming countries in the world. To investigate the genetic architecture of the agronomic traits of upland cotton in China, a diverse and nationwide population containing 503 G. hirsutum accessions was collected for a genome‐wide association study (GWAS) on 16 agronomic traits. The accessions were planted in four places from 2012 to 2013 for phenotyping. The CottonSNP63K array and a published high‐density map based on this array were used for genotyping. The 503 G. hirsutum accessions were divided into three subpopulations based on 11 975 quantified polymorphic single‐nucleotide polymorphisms (SNPs). By comparing the genetic structure and phenotypic variation among three genetic subpopulations, seven geographic distributions and four breeding periods, we found that geographic distribution and breeding period were not the determinants of genetic structure. In addition, no obvious phenotypic differentiations were found among the three subpopulations, even though they had different genetic backgrounds. A total of 324 SNPs and 160 candidate quantitative trait loci (QTL) regions were identified as significantly associated with the 16 agronomic traits. A network was established for multieffects in QTLs and interassociations among traits. Thirty‐eight associated regions had pleiotropic effects controlling more than one trait. One candidate gene, Gh_D08G2376, was speculated to control the lint percentage (LP). This GWAS is the first report using high‐resolution SNPs in upland cotton in China to comprehensively investigate agronomic traits, and it provides a fundamental resource for cotton genetic research and breeding.     

Identification of loci governing eight agronomic traits using a GBS‐GWAS approach and validation by QTL mapping in soya bean

Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome‐wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping‐by‐sequencing (GBS) approach was used to provide dense genome‐wide marker coverage (>47 000 SNPs) for a panel of 304 short‐season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean.     

Biomass market dynamics supporting the large‐scale deployment of high‐octane fuel production in the United States

US Department of Energy research aimed at co‐optimizing fuels and engine performance identified several bioblendstocks that can improve fuel economy including an aromatic‐rich hydrocarbon derived from woody biomass. This work supports an analysis of its large‐scale deployment implying a production target of approximately 15 billion liters of bioblendstock for the supply of 57 billion liters of high‐octane fuel by 2050. It simulates potential transition pathways to lignocellulosic feedstock market structures capable of supplying a mature biorefining industry at this scale. In the present absence of biorefineries, transitions are modeled via nonbiofuel feedstock markets, so‐called companion markets. The resource distribution across several demand industries is simulated to determine biomass availability and price dynamics over time. Results indicate that the wood supply base is mainly influenced by traditional markets including housing and pulp and paper. The selected companion market of wood pellet combustion for heat and electricity generation is found to positively stimulate biomass mobilization, especially in the initial absence of biorefineries. Eventually, biorefineries are found to be able to out‐compete the companion market. As such, they directly benefit from the processing (i.e., pelleting) capacity established to produce commodity‐type intermediates for the companion market. We conclude that the amount of bioblendstock produced is directly related to the size of the companion market (and its pelleting capacity). An initially larger companion market generates up to 20 million dry tonnes of additional feedstock, equivalent to 27 commercial‐scale biorefineries, or an additional production of 5 billion liters by 2050. Distinguishing between industry‐specific feedstock preferences based on average biomass quality characteristics, this analysis goes beyond past research efforts that assume automatic fungibility across different feedstocks. Improving engine performance is a key driver for the promotion of low‐carbon fuels derived from bioblendstocks. This analysis portrays feedstock market transition pathways for their large‐scale deployment.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

Identification of acetylcholinesterase inhibitors using homogenous cell‐based assays in quantitative high‐throughput screening platforms

Acetylcholinesterase (AChE) is an enzyme responsible for metabolism of acetylcholine, a neurotransmitter associated with muscle movement, cognition, and other neurobiological processes. Inhibition of AChE activity can serve as a therapeutic mechanism, but also cause adverse health effects and neurotoxicity. In order to efficiently identify AChE inhibitors from large compound libraries, homogenous cell‐based assays in high‐throughput screening platforms are needed. In this study, a fluorescent method using Amplex Red (10‐acetyl‐3,7‐dihydroxyphenoxazine) and the Ellman absorbance method were both developed in a homogenous format using a human neuroblastoma cell line (SH‐SY5Y). An enzyme‐based assay using Amplex Red was also optimized and used to confirm the potential inhibitors. These three assays were used to screen 1368 compounds, which included a library of pharmacologically active compounds (LOPAC) and 88 additional compounds from the Tox21 program, at multiple concentrations in a quantitative high‐throughput screening (qHTS) format. All three assays exhibited exceptional performance characteristics including assay signal quality, precision, and reproducibility. A group of inhibitors were identified from this study, including known (e.g. physostigmine and neostigmine bromide) and potential novel AChE inhibitors (e.g. chelerythrine chloride and cilostazol). These results demonstrate that this platform is a promising means to profile large numbers of chemicals that inhibit AChE activity.     

Reducing the interval of a growth QTL on chromosome 4 in laying hens

In our previous research, we identified a QTL with an interval of 3.4 Mb for growth on chicken chromosome (GGA) 4 in an advanced intercross population of an initial cross between the New Hampshire inbred line (NHI) and the White Leghorn inbred line (WL77). In the current study, an association analysis was performed in a population of purebred white layers (WLA) with White Leghorn origin. Genotypic data of 130 SNPs within the previously identified 3.4‐Mb region were obtained using a 60K SNP chip. In total, 24 significant SNPs (LOD ≥ 4.44) on GGA4 were detected for daily weigh gain from 8 to 14 weeks and two SNPs (LOD ≥ 4.80) for body weight at 14 weeks. The QTL interval was reduced by 1.9 Mb to an interval of 1.5 Mb (74.6–76.1 Mb) that harbors 15 genes. Furthermore, to identify additional loci for chicken growth, a genome‐wide association study (GWAS) was carried out in a WLA population. The GWAS identified an additional QTL on GGA6 for body weight at six weeks (19.8–21.2 Mb). Our findings showed that by using a WLA population we were able to further reduce the QTL confidence interval previously detected using a NHI × WL77 advanced intercross population.     

Oxidative folding and preparation of α‐conotoxins for use in high‐throughput structure–activity relationship studies

α‐Conotoxins are peptide neurotoxins that selectively inhibit various subtypes of nicotinic acetylcholine receptors. They are important research tools for studying numerous pharmacological disorders, with profound potential for developing drug leads for treating pain, tobacco addiction, and other conditions. They are characterized by the presence of two disulfide bonds connected in a globular arrangement, which stabilizes a bioactive helical conformation. Despite extensive structure–activity relationship studies that have produced α‐conotoxin analogs with increased potency and selectivity towards specific nicotinic acetylcholine receptor subtypes, the efficient production of diversity‐oriented α‐conotoxin combinatorial libraries has been limited by inefficient folding and purification procedures. We have investigated the optimized conditions for the reliable folding of α‐conotoxins using simplified oxidation procedures for use in the accelerated production of synthetic combinatorial libraries of α‐conotoxins. To this end, the effect of co‐solvent, redox reagents, pH, and temperature on the proportion of disulfide bond isomers was determined for α‐conotoxins exhibiting commonly known Cys loop spacing frameworks. In addition, we have developed high‐throughput ‘semi‐purification’ methods for the quick and efficient parallel preparation of α‐conotoxin libraries for use in accelerated structure–activity relationship studies. Our simplified procedures represent an effective strategy for the preparation of large arrays of correctly folded α‐conotoxin analogs and permit the rapid identification of active hits directly from high‐throughput pharmacological screening assays. Copyright © 2012 European Peptide Society and John Wiley & Sons, Ltd.     

A rapid and high‐throughput method for the determination of serum uric acid based on microarray technology and nanomaterial

Serum uric acid (SUA) is a new therapeutic target for non‐alcoholic fatty liver disease (NAFLD). In this study, we introduced a chemiluminescence (CL) method combined with microarray technology and a simple fabrication procedure to obtain a highly sensitive SUA probe based on a mesoporous metal oxide nanomaterial. The high‐throughput method was based on the generation of H₂O₂ from SUA by immobilized uricase and its measurement by a CL reaction catalyzed by mesoporous metal oxide nanomaterials. The CL probe was designed for SUA The linear range of the uric acid concentration was 0.6–9 μM and the detection limit was 0.1 μM. In comparison with the other SUA detection techniques, this method has the advantages of a low detection limit, high sensitivity and simplicity. A new sensitive high‐throughput approach was obtained for the determination of SUA.