Comparative evolution of vegetative branching in sorghum.

Tillering and secondary branching are two plastic traits with high agronomic importance, especially in terms of the ability of plants to adapt to changing environments. We describe a quantitative trait analysis of tillering and secondary branching in two novel BC1F2 populations totaling 246 genotypes derived from backcrossing two Sorghum bicolor x S. halepense F1 plants to a tetraploidized S. bicolor. A two-year, two-environment phenotypic evaluation in Bogart, GA and Salina, KS permitted us to identify major effect and environment specific QTLs. Significant correlation between tillering and secondary branching followed by discovery of overlapping sets of QTLs continue to support the developmental relationship between these two organs and suggest the possibility of pleiotropy. Comparisons with two other populations sharing S. bicolor BTx623 as a common parent but sampling the breadth of the Sorghum genus, increase confidence in QTL detected for these two plastic traits and provide insight into the evolution of morphological diversity in the Eusorghum clade. Correspondence between flowering time and vegetative branching supports other evidence in suggesting a pleiotropic effect of flowering genes. We propose a model to predict biomass weight from plant architecture related traits, quantifying contribution of each trait to biomass and providing guidance for future breeding experiments.

Genome sequence and evolution of Betula platyphylla.

Betula L. (birch) is a pioneer hardwood tree species with ecological, economic, and evolutionary importance in the Northern Hemisphere. We sequenced the Betula platyphylla genome and assembled the sequences into 14 chromosomes. The Betula genome lacks evidence of recent whole-genome duplication and has the same paleoploidy level as Vitis vinifera and Prunus mume. Phylogenetic analysis of lignin pathway genes coupled with tissue-specific expression patterns provided clues for understanding the formation of higher ratios of syringyl to guaiacyl lignin observed in Betula species. Our transcriptome analysis of leaf tissues under a time-series cold stress experiment revealed the presence of the MEKK1-MKK2-MPK4 cascade and six additional mitogen-activated protein kinases that can be linked to a gene regulatory network involving many transcription factors and cold tolerance genes. Our genomic and transcriptome analyses provide insight into the structures, features, and evolution of the B. platyphylla genome. The chromosome-level genome and gene resources of B. platyphylla obtained in this study will facilitate the identification of important and essential genes governing important traits of trees and genetic improvement of B. platyphylla.

Quantitative trait mapping of plant architecture in two BC1F2 populations of Sorghum Bicolor × S. halepense and comparisons to two other sorghum populations.

KEY MESSAGE: Comparing populations derived, respectively, from polyploid Sorghum halepense and its progenitors improved knowledge of plant architecture and showed that S. halepense harbors genetic novelty of potential value for sorghum improvement Vegetative growth and the timing of the vegetative-to-reproductive transition are critical to a plant's fitness, directly and indirectly determining when and how a plant lives, grows and reproduces. We describe quantitative trait analysis of plant height and flowering time in the naturally occurring tetraploid Sorghum halepense, using two novel BC1F2 populations totaling 246 genotypes derived from backcrossing two tetraploid Sorghum bicolor x S. halepense F1 plants to a tetraploidized S. bicolor. Phenotyping for two years each in Bogart, GA and Salina, KS allowed us to dissect variance into narrow-sense genetic (QTLs) and environmental components. In crosses with a common S. bicolor BTx623 parent, comparison of QTLs in S. halepense, its rhizomatous progenitor S. propinquum and S. bicolor race guinea which is highly divergent from BTx623 permit inferences of loci at which new alleles have been associated with improvement of elite sorghums. The relative abundance of QTLs unique to the S. halepense populations may reflect its polyploidy and subsequent 'diploidization' processes often associated with the formation of genetic novelty, a possibility further supported by a high level of QTL polymorphism within sibling lines derived from a common S. halepense parent. An intriguing hypothesis for further investigation is that polyploidy of S. halepense following 96 million years of abstinence, coupled with natural selection during its spread to diverse environments across six continents, may provide a rich collection of novel alleles that offer potential opportunities for sorghum improvement.

DeepFlower: a deep learning-based approach to characterize flowering patterns of cotton plants in the field.

BACKGROUND: Flowering is one of the most important processes for flowering plants such as cotton, reflecting the transition from vegetative to reproductive growth and is of central importance to crop yield and adaptability. Conventionally, categorical scoring systems have been widely used to study flowering patterns, which are laborious and subjective to apply. The goal of this study was to develop a deep learning-based approach to characterize flowering patterns for cotton plants that flower progressively over several weeks, with flowers distributed across much of the plant. RESULTS: A ground mobile system (GPhenoVision) was modified with a multi-view color imaging module, to acquire images of a plant from four viewing angles at a time. A total of 116 plants from 23 genotypes were imaged during an approximately 2-month period with an average scanning interval of 2-3 days, yielding a dataset containing 8666 images. A subset (475) of the images were randomly selected and manually annotated to form datasets for training and selecting the best object detection model. With the best model, a deep learning-based approach (DeepFlower) was developed to detect and count individual emerging blooms for a plant on a given date. The DeepFlower was used to process all images to obtain bloom counts for individual plants over the flowering period, using the resulting counts to derive flowering curves (and thus flowering characteristics). Regression analyses showed that the DeepFlower method could accurately (R2 = 0.88 and RMSE = 0.79) detect and count emerging blooms on cotton plants, and statistical analyses showed that imaging-derived flowering characteristics had similar effectiveness as manual assessment for identifying differences among genetic categories or genotypes. CONCLUSIONS: The developed approach could thus be an effective and efficient tool to characterize flowering patterns for flowering plants (such as cotton) with complex canopy architecture.

Transmission Genetics of a Sorghum bicolor × S. halepense Backcross Populations.

Despite a "ploidy barrier," interspecific crosses to wild and/or cultivated sorghum (Sorghum bicolor, 2n = 2x = 20) may have aided the spread across six continents of Sorghum halepense, also exemplifying risks of "transgene escape" from crops that could make weeds more difficult to control. Genetic maps of two BC1F1 populations derived from crosses of S. bicolor (sorghum) and S. halepense with totals of 722 and 795 single nucleotide polymorphism (SNP) markers span 37 and 35 linkage groups, with 2-6 for each of the 10 basic sorghum chromosomes due to fragments covering different chromosomal portions or independent segregation from different S. halepense homologs. Segregation distortion favored S. halepense alleles on chromosomes 2 (1.06-4.68 Mb, near a fertility restoration gene), 7 (1.20-6.16 Mb), 8 (1.81-5.33 Mb, associated with gene conversion), and 9 (47.5-50.1 Mb); and S. bicolor alleles on chromosome 6 (0-40 Mb), which contains both a large heterochromatin block and the Ma1 gene. Regions of the S. halepense genome that are recalcitrant to gene flow from sorghum might be exploited as part a multi-component system to reduce the likelihood of spread of transgenes or other modified genes. Its SNP profile suggests that chromosome segments from its respective progenitors S. bicolor and Sorghum propinquum have extensively recombined in S. halepense. This study reveals genomic regions that might discourage crop-to-weed gene escape, and provides a foundation for marker-trait association analysis to determine the genetic control of traits contributing to weediness, invasiveness, and perenniality of S. halepense.

DeepSeedling: deep convolutional network and Kalman filter for plant seedling detection and counting in the field.

BACKGROUND: Plant population density is an important factor for agricultural production systems due to its substantial influence on crop yield and quality. Traditionally, plant population density is estimated by using either field assessment or a germination-test-based approach. These approaches can be laborious and inaccurate. Recent advances in deep learning provide new tools to solve challenging computer vision tasks such as object detection, which can be used for detecting and counting plant seedlings in the field. The goal of this study was to develop a deep-learning-based approach to count plant seedlings in the field. RESULTS: Overall, the final detection model achieved F1 scores of 0.727 (at I O U all ) and 0.969 (at I O U 0.5 ) on the S e e d l i n g All testing set in which images had large variations, indicating the efficacy of the Faster RCNN model with the Inception ResNet v2 feature extractor for seedling detection. Ablation experiments showed that training data complexity substantially affected model generalizability, transfer learning efficiency, and detection performance improvements due to increased training sample size. Generally, the seedling counts by the developed method were highly correlated ( R 2 = 0.98) with that found through human field assessment for 75 test videos collected in multiple locations during multiple years, indicating the accuracy of the developed approach. Further experiments showed that the counting accuracy was largely affected by the detection accuracy: the developed approach provided good counting performance for unknown datasets as long as detection models were well generalized to those datasets. CONCLUSION: The developed deep-learning-based approach can accurately count plant seedlings in the field. Seedling detection models trained in this study and the annotated images can be used by the research community and the cotton industry to further the development of solutions for seedling detection and counting.

In-field High Throughput Phenotyping and Cotton Plant Growth Analysis Using LiDAR.

Plant breeding programs and a wide range of plant science applications would greatly benefit from the development of in-field high throughput phenotyping technologies. In this study, a terrestrial LiDAR-based high throughput phenotyping system was developed. A 2D LiDAR was applied to scan plants from overhead in the field, and an RTK-GPS was used to provide spatial coordinates. Precise 3D models of scanned plants were reconstructed based on the LiDAR and RTK-GPS data. The ground plane of the 3D model was separated by RANSAC algorithm and a Euclidean clustering algorithm was applied to remove noise generated by weeds. After that, clean 3D surface models of cotton plants were obtained, from which three plot-level morphologic traits including canopy height, projected canopy area, and plant volume were derived. Canopy height ranging from 85th percentile to the maximum height were computed based on the histogram of the z coordinate for all measured points; projected canopy area was derived by projecting all points on a ground plane; and a Trapezoidal rule based algorithm was proposed to estimate plant volume. Results of validation experiments showed good agreement between LiDAR measurements and manual measurements for maximum canopy height, projected canopy area, and plant volume, with R2-values of 0.97, 0.97, and 0.98, respectively. The developed system was used to scan the whole field repeatedly over the period from 43 to 109 days after planting. Growth trends and growth rate curves for all three derived morphologic traits were established over the monitoring period for each cultivar. Overall, four different cultivars showed similar growth trends and growth rate patterns. Each cultivar continued to grow until ~88 days after planting, and from then on varied little. However, the actual values were cultivar specific. Correlation analysis between morphologic traits and final yield was conducted over the monitoring period. When considering each cultivar individually, the three traits showed the best correlations with final yield during the period between around 67 and 109 days after planting, with maximum R2-values of up to 0.84, 0.88, and 0.85, respectively. The developed system demonstrated relatively high throughput data collection and analysis.

GPhenoVision: A Ground Mobile System with Multi-modal Imaging for Field-Based High Throughput Phenotyping of Cotton.

Imaging sensors can extend phenotyping capability, but they require a system to handle high-volume data. The overall goal of this study was to develop and evaluate a field-based high throughput phenotyping system accommodating high-resolution imagers. The system consisted of a high-clearance tractor and sensing and electrical systems. The sensing system was based on a distributed structure, integrating environmental sensors, real-time kinematic GPS, and multiple imaging sensors including RGB-D, thermal, and hyperspectral cameras. Custom software was developed with a multilayered architecture for system control and data collection. The system was evaluated by scanning a cotton field with 23 genotypes for quantification of canopy growth and development. A data processing pipeline was developed to extract phenotypes at the canopy level, including height, width, projected leaf area, and volume from RGB-D data and temperature from thermal images. Growth rates of morphological traits were accordingly calculated. The traits had strong correlations (r = 0.54-0.74) with fiber yield and good broad sense heritability (H2 = 0.27-0.72), suggesting the potential for conducting quantitative genetic analysis and contributing to yield prediction models. The developed system is a useful tool for a wide range of breeding/genetic, agronomic/physiological, and economic studies.

Aerial Images and Convolutional Neural Network for Cotton Bloom Detection.

Monitoring flower development can provide useful information for production management, estimating yield and selecting specific genotypes of crops. The main goal of this study was to develop a methodology to detect and count cotton flowers, or blooms, using color images acquired by an unmanned aerial system. The aerial images were collected from two test fields in 4 days. A convolutional neural network (CNN) was designed and trained to detect cotton blooms in raw images, and their 3D locations were calculated using the dense point cloud constructed from the aerial images with the structure from motion method. The quality of the dense point cloud was analyzed and plots with poor quality were excluded from data analysis. A constrained clustering algorithm was developed to register the same bloom detected from different images based on the 3D location of the bloom. The accuracy and incompleteness of the dense point cloud were analyzed because they affected the accuracy of the 3D location of the blooms and thus the accuracy of the bloom registration result. The constrained clustering algorithm was validated using simulated data, showing good efficiency and accuracy. The bloom count from the proposed method was comparable with the number counted manually with an error of -4 to 3 blooms for the field with a single plant per plot. However, more plots were underestimated in the field with multiple plants per plot due to hidden blooms that were not captured by the aerial images. The proposed methodology provides a high-throughput method to continuously monitor the flowering progress of cotton.

Plant Genome Duplication Database.

Genome duplication, widespread in flowering plants, is a driving force in evolution. Genome alignments between/within genomes facilitate identification of homologous regions and individual genes to investigate evolutionary consequences of genome duplication. PGDD (the Plant Genome Duplication Database), a public web service database, provides intra- or interplant genome alignment information. At present, PGDD contains information for 47 plants whose genome sequences have been released. Here, we describe methods for identification and estimation of dates of genome duplication and speciation by functions of PGDD.The database is freely available at http://chibba.agtec.uga.edu/duplication/.

A genome-wide BAC end-sequence survey of sugarcane elucidates genome composition, and identifies BACs covering much of the euchromatin.

BAC-end sequences (BESs) of hybrid sugarcane cultivar R570 are presented. A total of 66,990 informative BESs were obtained from 43,874 BAC clones. Similarity search using a variety of public databases revealed that 13.5 and 42.8 % of BESs match known gene-coding and repeat regions, respectively. That 11.7 % of BESs are still unmatched to any nucleotide sequences in the current public databases despite the fact that a close relative, sorghum, is fully sequenced, indicates that there may be many sugarcane-specific or lineage-specific sequences. We found 1,742 simple sequence repeat motifs in 1,585 BESs, spanning 27,383 bp in length. As simple sequence repeat markers derived from BESs have some advantages over randomly generated markers, these may be particularly useful for comparing BAC-based physical maps with genetic maps. BES and overgo hybridization information was used for anchoring sugarcane BAC clones to the sorghum genome sequence. While sorghum and sugarcane have extensive similarity in terms of genomic structure, only 2,789 BACs (6.4 %) could be confidently anchored to the sorghum genome at the stringent threshold of having both-end information (BESs or overgos) within 300 Kb. This relatively low rate of anchoring may have been caused in part by small- or large-scale genomic rearrangements in the Saccharum genus after two rounds of whole genome duplication since its divergence from the sorghum lineage about 7.8 million years ago. Limiting consideration to only low-copy matches, 1,245 BACs were placed to 1,503 locations, covering ~198 Mb of the sorghum genome or about 78 % of the estimated 252 Mb of euchromatin. BESs and their analyses presented here may provide an early profile of the sugarcane genome as well as a basis for BAC-by-BAC sequencing of much of the basic gene set of sugarcane.

Inference of subgenomic origin of BACs in an interspecific hybrid sugarcane cultivar by overlapping oligonucleotide hybridizations.

Sugarcane (Saccharum spp.) breeders in the early 20th century made remarkable progress in increasing yield and disease resistance by crossing Saccharum spontaneum L., a wild relative, to Saccharum officinarum L., a traditional cultivar. Modern sugarcane cultivars have approximately 71%-83% of their chromosomes originating from S. officinarum, approximately 10%-21% from S. spontaneum, and approximately 2%-13% recombinant or translocated chromosomes. In the present work, C(0)t-based cloning and sequencing (CBCS) was implemented to further explore highly repetitive DNA and to seek species-specific repeated DNA in both S. officinarum and S. spontaneum. For putatively species-specific sequences, overlappping oligonucleotide probes (overgos) were designed and hybridized to BAC filters from the interspecific hybrid sugarcane cultivar 'R570' to try to deduce parental origins of BAC clones. We inferred that 12 967 BACs putatively originated from S. officinarum and 5117 BACs from S. spontaneum. Another 1103 BACs were hybridized by both species-specific overgos, too many to account for by conventional recombination, thus suggesting ectopic recombination and (or) translocation of DNA elements. Constructing a low C(0)t library is useful to collect highly repeated DNA sequences and to search for potentially species-specific molecular markers, especially among recently diverged species. Even in the absence of repeat families that are species-specific in their entirety, the identification of localized variations within consensus sequences, coupled with the site specificity of short synthetic overgos, permits researchers to monitor species-specific or species-enriched variants.

Attenuated live vaccine usage affects accurate measures of virus diversity and mutation rates in avian coronavirus infectious bronchitis virus.

The full-length genomes of 11 infectious bronchitis virus (IBV) field isolates from three different types of the virus; Massachusetts (Mass), Connecticut (Conn) and California (CAL) isolated over a 41, 25 and 8 year period respectively, were sequenced and analyzed to determine the mutation rates and level of polymorphisms across the genome. Positive selection was not detected and mutation rates ranged from 10(-4) to 10(-6)substitutions/site/year for Mass and Conn IBV types where attenuated live vaccines are routinely used to control the disease. In contrast, for CAL type viruses, for which no vaccine exists, positive selection was detected and mutation rates were 10 fold higher ranging from 10(-2) to 10(-3)substitutions/site/year. Lower levels of genetic diversity among the Mass and Conn viruses as well as sequence similarities with vaccine virus genomes suggest that the origin of the Mass and all but one of the Conn viruses was likely vaccine virus that had been circulating in the field for an unknown but apparently short period of time. The genetic data also identified a recombinant IBV isolate with 7 breakpoints distributed across the entire genome suggesting that viruses within the same serotype can have a high degree of genetic variability outside of the spike gene. These data are important because inaccurate measures of genetic diversity and mutation rates could lead to underestimates of the ability of IBV to change and potentially emerge to cause disease.

Azospirillum genomes reveal transition of bacteria from aquatic to terrestrial environments.

Fossil records indicate that life appeared in marine environments ∼3.5 billion years ago (Gyr) and transitioned to terrestrial ecosystems nearly 2.5 Gyr. Sequence analysis suggests that "hydrobacteria" and "terrabacteria" might have diverged as early as 3 Gyr. Bacteria of the genus Azospirillum are associated with roots of terrestrial plants; however, virtually all their close relatives are aquatic. We obtained genome sequences of two Azospirillum species and analyzed their gene origins. While most Azospirillum house-keeping genes have orthologs in its close aquatic relatives, this lineage has obtained nearly half of its genome from terrestrial organisms. The majority of genes encoding functions critical for association with plants are among horizontally transferred genes. Our results show that transition of some aquatic bacteria to terrestrial habitats occurred much later than the suggested initial divergence of hydro- and terrabacterial clades. The birth of the genus Azospirillum approximately coincided with the emergence of vascular plants on land.

Transcriptome analysis of leaf tissue from Bermudagrass (Cynodon dactylon) using a normalised cDNA library.

A normalised cDNA library was constructed from Bermudagrass to gain insight into the transcriptome of Cynodon dactylon L. A total of 15 588 high-quality expressed sequence tags (ESTs) from the cDNA library were subjected to The Institute for Genomic Research Gene Indices clustering tools to produce a unigene set. A total of 9414 unigenes were obtained from the high-quality ESTs and only 39.6% of the high-quality ESTs were redundant, indicating that the normalisation procedure was effective. A large-scale comparative genomic analysis of the unigenes was carried out using publicly available tools, such as BLAST, InterProScan and Gene Ontology. The unigenes were also subjected to a search for EST-derived simple sequence repeats (EST-SSRs) and conserved-intron scanning primers (CISPs), which are useful as DNA markers. Although the candidate EST-SSRs and CISPs found in the present study need to be empirically tested, they are expected to be useful as DNA markers for many purposes, including comparative genomic studies of grass species, by virtue of their significant similarities to EST sequences from other grasses. Thus, knowledge of Cynodon ESTs will empower turfgrass research by providing homologues for genes that are thought to confer important functions in other plants.

The repetitive landscape of the chicken genome.

Cot-based cloning and sequencing (CBCS) is a powerful tool for isolating and characterizing the various repetitive components of any genome, combining the established principles of DNA reassociation kinetics with high-throughput sequencing. CBCS was used to generate sequence libraries representing the high, middle, and low-copy fractions of the chicken genome. Sequencing high-copy DNA of chicken to about 2.7 x coverage of its estimated sequence complexity led to the initial identification of several new repeat families, which were then used for a survey of the newly released first draft of the complete chicken genome. The analysis provided insight into the diversity and biology of known repeat structures such as CR1 and CNM, for which only limited sequence data had previously been available. Cot sequence data also resulted in the identification of four novel repeats (Birddawg, Hitchcock, Kronos, and Soprano), two new subfamilies of CR1 repeats, and many elements absent from the chicken genome assembly. Multiple autonomous elements were found for a novel Mariner-like transposon, Galluhop, in addition to nonautonomous deletion derivatives. Phylogenetic analysis of the high-copy repeats CR1, Galluhop, and Birddawg provided insight into two distinct genome dispersion strategies. This study also exemplifies the power of the CBCS method to create representative databases for the repetitive fractions of genomes for which only limited sequence data is available.