Large scale genome skimming from herbarium material for accurate plant identification and phylogenomics

Fluorescent chemosensors facilitate the visualization of plant health and their living environment in sustainable agriculture

Globally, 91% of plant production encounters diverse environmental stresses that adversely affect their growth, leading to severe yield losses of 50-60%. In this case, monitoring the connection between the environment and plant health can balance population demands with environmental protection and resource distribution. Fluorescent chemosensors have shown great progress in monitoring the health and environment of plants due to their high sensitivity and biocompatibility. However, to date, no comprehensive analysis and systematic summary of fluorescent chemosensors used in monitoring the correlation between plant health and their environment have been reported. Thus, herein, we summarize the current fluorescent chemosensors ranging from their design strategies to applications in monitoring plant-environment interaction processes. First, we highlight the types of fluorescent chemosensors with design strategies to resolve the bottlenecks encountered in monitoring the health and living environment of plants. In addition, the applications of fluorescent small-molecule, nano and supramolecular chemosensors in the visualization of the health and living environment of plants are discussed. Finally, the major challenges and perspectives in this field are presented. This work will provide guidance for the design of efficient fluorescent chemosensors to monitor plant health, and then promote sustainable agricultural development.

Plastid phylogenomics and cytonuclear discordance in Rubioideae, Rubiaceae

In this study of evolutionary relationships in the subfamily Rubioideae (Rubiaceae), we take advantage of the off-target proportion of reads generated via previous target capture sequencing projects based on nuclear genomic data to build a plastome phylogeny and investigate cytonuclear discordance. The assembly of off-target reads resulted in a comprehensive plastome dataset and robust inference of phylogenetic relationships, where most intratribal and intertribal relationships are resolved with strong support. While the phylogenetic results were mostly in agreement with previous studies based on plastome data, novel relationships in the plastid perspective were also detected. For example, our analyses of plastome data provide strong support for the SCOUT clade and its sister relationship to the remaining members of the subfamily, which differs from previous results based on plastid data but agrees with recent results based on nuclear genomic data. However, several instances of highly supported cytonuclear discordance were identified across the Rubioideae phylogeny. Coalescent simulation analysis indicates that while ILS could, by itself, explain the majority of the discordant relationships, plastome introgression may be the better explanation in some cases. Our study further indicates that plastomes across the Rubioideae are, with few exceptions, highly conserved and mainly conform to the structure, gene content, and gene order present in the majority of the flowering plants.

Nuclear Magnetic Resonance Fingerprints and Mini DNA Markers for the Authentication of Cinnamon Species Ingredients Used in Food and Natural Health Products

Cinnamomum verum (syn C. zeylanicum) is considered 'true' cinnamon. However, it is reported that less expensive sources of cinnamon from C. cassia (syn C. aromaticum), C. loureiroi, and C. burmannii (toxic coumarin) may be used in the place of C. verum. We lack the quality assurance tools that are required to differentiate C. verum from other cinnamon species when verifying that the correct species is sourced from ingredient suppliers. The current research on cinnamon species authentication using DNA tools is limited to a few species and the use of high-quality DNA extracted from raw leaf materials. The cinnamon bark traded in the supply chain contains much less DNA and poorer-quality DNA than leaves. Our research advances DNA methods to authenticate cinnamon, as we utilized full-length chloroplast genomes via a genome skimming approach for C. burmannii and C. cassia to facilitate the design of optimal mini DNA markers. Furthermore, we developed and validated the use of NMR fingerprints for several commercial cinnamon species, including the quantification of 16 molecules. NMR fingerprints provided additional data that were useful for quality assessment in cinnamon extract powders and product consistency. Both the new mini DNA markers and NMR fingerprints were tested on commercial cinnamon products.

LocoGSE, a sequence-based genome size estimator for plants

Extensive research has focused on exploring the range of genome sizes in eukaryotes, with a particular emphasis on land plants, where significant variability has been observed. Accurate estimation of genome size is essential for various research purposes, but existing sequence-based methods have limitations, particularly for low-coverage datasets. In this study, we introduce LocoGSE, a novel genome size estimator designed specifically for low-coverage datasets generated by genome skimming approaches. LocoGSE relies on mapping the reads on single copy consensus proteins without the need for a reference genome assembly. We calibrated LocoGSE using 430 low-coverage Angiosperm genome skimming datasets and compared its performance against other estimators. Our results demonstrate that LocoGSE accurately predicts monoploid genome size even at very low depth of coverage (<1X) and on highly heterozygous samples. Additionally, LocoGSE provides stable estimates across individuals with varying ploidy levels. LocoGSE fills a gap in sequence-based plant genome size estimation by offering a user-friendly and reliable tool that does not rely on high coverage or reference assemblies. We anticipate that LocoGSE will facilitate plant genome size analysis and contribute to evolutionary and ecological studies in the field. Furthermore, at the cost of an initial calibration, LocoGSE can be used in other lineages.

DNA Barcoding and Metabarcoding Protocols for Species Identification

The article presents the several steps to be performed on a plant, fungal, insect, or soil sample to obtain DNA sequences for DNA barcode analysis. The chapter begins with a description of sample preparation including procedures for cleaning and proceeds to DNA extraction with methods adapted for the specific type of sample. Next, DNA quantification is described so the proper amount is used for the amplification of the selected barcode regions. Information is provided for reaction mixes and amplification conditions for several referenced barcode primer pairs tuned for the individual sample of interest. This is followed by a description of procedures to access the success of amplification, cleanup, and quantification of the product ready for either Sanger sequencing or library preparation for massive parallel sequencing (MPS). Finally, procedures are provided for Sanger sequencing, library preparation, and MPS sequencing. The chapter provides several references of barcode regions for different sample types.

Whole mitochondrial and chloroplast genome sequencing of Tunisian date palm cultivars: diversity and evolutionary relationships

BACKGROUND

Date palm (Phoenix dactylifera L.) is the most widespread crop in arid and semi-arid regions and has great traditional and socioeconomic importance, with its fruit well-known for its high nutritional and health value. However, the genetic variation of date palm cultivars is often neglected. The advent of high-throughput sequencing has made possible the resequencing of whole organelle (mitochondria and chloroplast) genomes to explore the genetic diversity and phylogenetic relationships of cultivated plants with unprecedented detail.

RESULTS

Whole organelle genomes of 171 Tunisian accessions (135 females and 36 males) were sequenced. Targeted bioinformatics pipelines were used to identify date palm haplotypes and genome variants, aiming to provide variant annotation and investigate patterns of evolutionary relationship. Our results revealed the existence of unique haplotypes, identified by 45 chloroplastic and 156 mitochondrial SNPs. Estimation of the effect of these SNPs on genes functions was predicted in silico.

CONCLUSIONS

The results of this study have important implications, in the light of ongoing environmental changes, for the conservation and sustainable use of the genetic resources of date palm cultivars in Tunisia, where monoculture threatens biodiversity leading to genetic erosion. These data will be useful for breeding and genetic improvement programs of the date palm through selective cross-breeding.

Intraspecific phylogeny and genomic resources development for an important medical plant Dioscorea nipponica, based on low-coverage whole genome sequencing data

Dioscorea nipponica Makino, a perennial twining herb with medicinal importance, has a disjunctive distribution in the Sino-Japanese Floristic Region. It has a long history in traditional Chinese medicine, with demonstrated efficacy against various health conditions. However, the limited genomic data and knowledge of genetic variation have hindered its comprehensive exploration, utilization and conservation. In this study, we undertook low-coverage whole genome sequencing of diverse D. nipponica accessions to develop both plastome (including whole plastome sequences, plastome-derived SSRs and plastome-divergent hotspots) and nuclear genomic resources (including polymorphic nuclear SSRs and single-copy nuclear genes), as well as elucidate the intraspecific phylogeny of this species. Our research revealed 639 plastome-derived SSRs and highlighted six key mutational hotspots (namely CDS ycf1, IGS trnL-rpl32, IGS trnE-trnT, IGS rps16-trnQ, Intron 1 of clpP, and Intron trnG) within these accessions. Besides, three IGS regions (i.e., ndhD-cssA, trnL-rpl32, trnD-trnY), and the intron rps16 were identified as potential markers for distinguishing D. nipponica from its closely related species. In parallel, we successfully developed 988 high-quality candidate polymorphic nuclear SSRs and identified 17 single-copy nuclear genes for D. nipponica, all of which empower us to conduct in-depth investigations into phylogenetics and population genetics of this species. Although our phylogenetic analyses, based on plastome sequences and single-copy nuclear genes revealed cytonuclear discordance within D. nipponica, both findings challenged the current subspecies classification. In summary, this study developed a wealth of genomic resources for D. nipponica and enhanced our understanding of the intraspecific phylogeny of this species, offering valuable insights that can be instrumental in the conservation and strategic utilization of this economically significant plant.

Developing the Protocol Infrastructure for DNA Sequencing Natural History Collections

Intentionally preserved biological material in natural history collections represents a vast repository of biodiversity. Advances in laboratory and sequencing technologies have made these specimens increasingly accessible for genomic analyses, offering a window into the genetic past of species and often permitting access to information that can no longer be sampled in the wild. Due to their age, preparation and storage conditions, DNA retrieved from museum and herbarium specimens is often poor in yield, heavily fragmented and biochemically modified. This not only poses methodological challenges in recovering nucleotide sequences, but also makes such investigations susceptible to environmental and laboratory contamination. In this paper, we review the practical challenges associated with making the recovery of DNA sequence data from museum collections more routine. We first review key operational principles and issues to address, to guide the decision-making process and dialogue between researchers and curators about when and how to sample museum specimens for genomic analyses. We then outline the range of steps that can be taken to reduce the likelihood of contamination including laboratory set-ups, workflows and working practices. We finish by presenting a series of case studies, each focusing on protocol practicalities for the application of different mainstream methodologies to museum specimens including: (i) shotgun sequencing of insect mitogenomes, (ii) whole genome sequencing of insects, (iii) genome skimming to recover plant plastid genomes from herbarium specimens, (iv) target capture of multi-locus nuclear sequences from herbarium specimens, (v) RAD-sequencing of bird specimens and (vi) shotgun sequencing of ancient bovid bone samples.

Ancient DNA genomics and the renaissance of herbaria

Herbaria are undergoing a renaissance as valuable sources of genomic data for exploring plant evolution, ecology, and diversity. Ancient DNA retrieved from herbarium specimens can provide unprecedented glimpses into past plant communities, their interactions with biotic and abiotic factors, and the genetic changes that have occurred over time. Here, we highlight recent advances in the field of herbarium genomics and discuss the challenges and opportunities of combining data from modern and time-stamped historical specimens. We also describe how integrating herbarium genomics data with other data types can yield substantial insights into the evolutionary and ecological processes that shape plant communities. Herbarium genomic analysis is a tool for understanding plant life and informing conservation efforts in the face of dire environmental challenges.

New insights into the plastome evolution of Lauraceae using herbariomics

BACKGROUND

The family Lauraceae possesses ca. 50 genera and 2,500-3,000 species that are distributed in the pantropics. Only half of the genera of the family were represented in previously published plastome phylogenies because of the difficulty of obtaining research materials. Plastomes of Hypodaphnideae and the Mezilaurus group, two lineages with unusual phylogenetic positions, have not been previously reported and thus limit our full understanding on the plastome evolution of the family. Herbariomics, promoted by next generation sequencing technology, can make full use of herbarium specimens, and provides opportunities to fill the sampling gap.

RESULTS

In this study, we sequenced five new plastomes (including four genera which are reported for the first time, viz. Chlorocardium, Hypodaphnis, Licaria and Sextonia) from herbarium specimens using genome skimming to conduct a comprehensive analysis of plastome evolution of Lauraceae as a means of sampling representatives of all major clades of the family. We identified and recognized six types of plastomes and revealed that at least two independent loss events at the IR-LSC boundary and an independent expansion of SSC occurred in the plastome evolution of the family. Hypodaphnis possesses the ancestral type of Lauraceae with trnI-CAU, rpl23 and rpl2 duplicated in the IR regions (Type-I). The Mezilaurus group shares the same plastome structure with the core Lauraceae group in the loss of trnI-CAU, rpl23 and rpl2 in the IRa region (Type-III). Two new types were identified in the Ocotea group: (1) the insertion of trnI-CAU between trnL-UAG and ccsA in the SSC region of Licaria capitata and Ocotea bracteosa (Type-IV), and (2) trnI-CAU and pseudogenizated rpl23 inserted in the same region of Nectandra angustifolia (Type-V). Our phylogeny suggests that Lauraceae are divided into nine major clades largely in accordance with the plastome types. The Hypodaphnideae are the earliest diverged lineage supported by both robust phylogeny and the ancestral plastome type. The monophyletic Mezilaurus group is sister to the core Lauraceae.

CONCLUSIONS

By using herbariomics, we built a more complete picture of plastome evolution and phylogeny of the family, thus providing a convincing case for further use of herbariomics in phylogenetic studies of the Lauraceae.

Old-growth Acer macrophyllum trees host a unique suite of arbuscular mycorrhizal fungi and other root-associated fungal taxa in their canopy soil environment

Canopy soils occur on tree branches throughout the temperate rainforests of the Pacific Northwest Coast and are recognized as a defining characteristic of these ecosystems. Certain tree species extend adventitious roots into these canopy soil environments. Yet, research on adventitious root-associated fungi remains limited. Our study used microscopy to compare fungal colonization intensity between canopy and forest floor roots of old-growth bigleaf maple (Acer macrophyllum) trees. Subsequently, two high-throughput sequencing platforms were used to explore the spatial and seasonal variation of root-associated fungi between the two soil environments over one year. We found that canopy and forest floor roots had similar colonization intensity and were associating with a diversity of arbuscular mycorrhizal fungi and other potential symbionts, many of which were resolved to species level. Soil environment and seasonality affected root-associated fungal community composition, and several fungal species were indicative of the canopy soil environment. In Washington State's (USA) temperate old-growth rainforests, these canopy soil environments host a unique suite of root-associated fungi. The presence of arbuscular mycorrhizae provides further evidence that adventitious roots form fungal associations to exploit canopy soils for resources, and there may be novel relationships forming with other fungi. These soils may be providing a redundancy compartment (i.e., "nutrient reserve"), imparting a resiliency to disturbances for certain old-growth trees.

A comparison of freezer-stored DNA and herbarium tissue samples for chloroplast assembly and genome skimming

Premise

The use of DNA from herbarium specimens is an increasingly important source for evolutionary studies in plant biology, particularly in cases where species are rare or difficult to obtain. Here we compare the utility of DNA from herbarium tissues to their freezer-stored DNA counterparts via the Hawaiian Plant DNA Library.

Methods

Plants collected for the Hawaiian Plant DNA Library were simultaneously accessioned as herbarium specimens at the time of collection, from 1994-2019. Paired samples were sequenced using short-read sequencing and assessed for chloroplast assembly and nuclear gene recovery.

Results

Herbarium specimen-derived DNA was statistically more fragmented than freezer-stored DNA derived from fresh tissue, leading to poorer chloroplast assembly and overall lower coverage. The number of nuclear targets recovered varied mostly by total sequencing reads per library and age of specimen, but not by storage method (herbarium or long-term freezer). Although there was evidence of DNA damage in the samples, there was no evidence that it was related to the length of time in storage, whether frozen or as herbarium specimens.

Discussion

DNA extracted from herbarium tissues will continue to be invaluable, despite being highly fragmented and degraded. Rare floras would benefit from both traditional herbarium storage methods and extracted DNA freezer banks.

Poaceae Chloroplast Genome Sequencing: Great Leap Forward in Recent Ten Years

The first complete chloroplast genome of rice (Oryza sativa) was published in 1989, ushering in a new era of studies of chloroplast genomics in Poaceae. Progresses in Next-Generation Sequencing (NGS) and Third-Generation Sequencing (TGS) technologiesand in the development of genome assembly software, have significantly advanced chloroplast genomics research. Poaceae is one of the most targeted families in chloroplast genome research because of its agricultural, ecological, and economic importance. Over the last 30 years, 2,050 complete chloroplast genome sequences from 40 tribes and 282 genera have been generated, most (97%) of them in the recent ten years. The wealth of data provides the groundwork for studies on species evolution, phylogeny, genetic transformation, and other aspects of Poaceae chloroplast genomes. As a result, we have gained a deeper understanding of the properties of Poaceae chloroplast genomes. Here, we summarize the achievements of the studies of the Poaceae chloroplast genomes and envision the challenges for moving the area ahead.

Phylogenomics and the flowering plant tree of life

The advances accelerated by next-generation sequencing and long-read sequencing technologies continue to provide an impetus for plant phylogenetic study. In the past decade, a large number of phylogenetic studies adopting hundreds to thousands of genes across a wealth of clades have emerged and ushered plant phylogenetics and evolution into a new era. In the meantime, a roadmap for researchers when making decisions across different approaches for their phylogenomic research design is imminent. This review focuses on the utility of genomic data (from organelle genomes, to both reduced representation sequencing and whole-genome sequencing) in phylogenetic and evolutionary investigations, describes the baseline methodology of experimental and analytical procedures, and summarizes recent progress in flowering plant phylogenomics at the ordinal, familial, tribal, and lower levels. We also discuss the challenges, such as the adverse impact on orthology inference and phylogenetic reconstruction raised from systematic errors, and underlying biological factors, such as whole-genome duplication, hybridization/introgression, and incomplete lineage sorting, together suggesting that a bifurcating tree may not be the best model for the tree of life. Finally, we discuss promising avenues for future plant phylogenomic studies.

Applications of environmental DNA (eDNA) in agricultural systems: Current uses, limitations and future prospects

Global food production, food supply chains and food security are increasingly stressed by human population growth and loss of arable land, becoming more vulnerable to anthropogenic and environmental perturbations. Numerous mutualistic and antagonistic species are interconnected with the cultivation of crops and livestock and these can be challenging to identify on the large scales of food production systems. Accurate identifications to capture this diversity and rapid scalable monitoring are necessary to identify emerging threats (i.e. pests and pathogens), inform on ecosystem health (i.e. soil and pollinator diversity), and provide evidence for new management practices (i.e. fertiliser and pesticide applications). Increasingly, environmental DNA (eDNA) is providing rapid and accurate classifications for specific organisms and entire species assemblages in substrates ranging from soil to air. Here, we aim to discuss how eDNA is being used for monitoring of agricultural ecosystems, what current limitations exist, and how these could be managed to expand applications into the future. In a systematic review we identify that eDNA-based monitoring in food production systems accounts for only 4 % of all eDNA studies. We found that the majority of these eDNA studies target soil and plant substrates (60 %), predominantly to identify microbes and insects (60 %) and are biased towards Europe (42 %). While eDNA-based monitoring studies are uncommon in many of the world's food production systems, the trend is most pronounced in emerging economies often where food security is most at risk. We suggest that the biggest limitations to eDNA for agriculture are false negatives resulting from DNA degradation and assay biases, as well as incomplete databases and the interpretation of abundance data. These require in silico, in vitro, and in vivo approaches to carefully design, test and apply eDNA monitoring for reliable and accurate taxonomic identifications. We explore future opportunities for eDNA research which could further develop this useful tool for food production system monitoring in both emerging and developed economies, hopefully improving monitoring, and ultimately food security.

DNA barcoding: an efficient technology to authenticate plant species of traditional Chinese medicine and recent advances

Traditional Chinese medicine (TCM) plays an important role in the global traditional health systems. However, adulterated and counterfeit TCM is on the rise. DNA barcoding is an effective, rapid, and accurate technique for identifying plant species. In this study, we collected manuscripts on DNA barcoding published in the last decade and summarized the use of this technique in identifying 50 common Chinese herbs listed in the Chinese pharmacopoeia. Based on the dataset of the major seven DNA barcodes of plants in the NCBI database, the strengths and limitations of the barcodes and their derivative barcoding technology, including single-locus barcode, multi-locus barcoding, super-barcoding, meta-barcoding, and mini-barcoding, were illustrated. In addition, the advances in DNA barcoding, particularly identifying plant species for TCM using machine learning technology, are also reviewed. Finally, the selection process of an ideal DNA barcoding technique for accurate identification of a given TCM plant species was also outlined.

The repetitive DNA sequence landscape and DNA methylation in chromosomes of an apomictic tropical forage grass, Cenchrus ciliaris

Cenchrus ciliaris is an apomictic, allotetraploid pasture grass widely distributed in the tropical and subtropical regions of Africa and Asia. In this study, we aimed to investigate the genomic organization and characterize some of the repetitive DNA sequences in this species. Due to the apomictic propagation, various aneuploid genotypes are found, and here, we analyzed a 2n = 4x + 3 = 39 accession. The physical mapping of Ty1-copia and Ty3-gypsy retroelements through fluorescence in situ hybridization with a global assessment of 5-methylcytosine DNA methylation through immunostaining revealed the genome-wide distribution pattern of retroelements and their association with DNA methylation. Approximately one-third of Ty1-copia sites overlapped or spanned centromeric DAPI-positive heterochromatin, while the centromeric regions and arms of some chromosomes were labeled with Ty3-gypsy. Most of the retroelement sites overlapped with 5-methylcytosine signals, except for some Ty3-gypsy on the arms of chromosomes, which did not overlap with anti-5-mC signals. Universal retrotransposon probes did not distinguish genomes of C. ciliaris showing signals in pericentromeric regions of all 39 chromosomes, unlike highly abundant repetitive DNA motifs found in survey genome sequences of C. ciliaris using graph-based clustering. The probes developed from RepeatExplorer clusters gave strong in situ hybridization signals, mostly in pericentromeric regions of about half of the chromosomes, and we suggested that they differentiate the two ancestral genomes in the allotetraploid C. ciliaris, likely having different repeat sequence variants amplified before the genomes came together in the tetraploid.

Validation of reference genes as an internal control for studying Avena sativa-Puccinia coronata interaction by RT-qPCR

In this study we evaluated eleven candidate reference genes in Avena sativa during compatible and incompatible interactions with two different pathotypes of Puccinia coronata f. sp. avenae in six time points post-inoculation. The identification of genes with high expression stability was performed by four algorithms (geNorm, NormFinder, BestKeeper and ΔCt method). The results obtained confirmed that the combination of two genes would be sufficient for reliable normalization of the expression data. In general, the most stable in the tested plant-pathogen system were HNR (heterogeneous nuclear ribonucleoprotein 27C) and EF1A (elongation factor 1-alpha). ARF (ADP-ribosylation factor) and EIF4A (eukaryotic initiation factor 4A-3) could also be considered as exhibiting high expression stability. CYP (cyclophilin) was shown by all assessment methods to be the worst candidate for normalization in this dataset. To date, this is the first report of reference genes selection in A. sativa–P. coronata interaction system. Identified reference genes enable reliable and comprehensive RT-qPCR analysis of oat gene expression in response to crown rust infection. Understanding the molecular mechanisms involved in the host–pathogen interactions may expand knowledge of durable resistance strategies beneficial to modern oat breeding.

High-throughput degraded DNA sequencing of subfossil shells of a critically endangered stenoendemic land snail in the Aegean

High-throughput sequencing has enabled the comprehensive genetic exploration of biological diversity, especially by using natural history collections to study hard-to-find, threatened or even extinct-in-the-wild taxa. Mollusk shells are under-exploited as a source for DNA-based approaches, despite their apparent advantages in the field of conservation genetics. More particularly, degraded DNA techniques combined with high-throughput sequencing have never been used to gain insights about the DNA preservation in land snail subfossil or historical shells. Here, we applied degraded DNA analysis on two historical shells of Levantina rechingeri, a stenoendemic Critically Endangered species that has never been found alive, in order to explore the patterns of DNA preservation on land snail shells originating from the eastern Mediterranean, as well as to infer its molecular phylogenetic placement. Our results showed that centuries to decades-old DNA from an empty shell collected in an Aegean island exhibits characteristic post-mortem damage patterns similar to those observed in ancient DNA from eastern Mediterranean terrestrial animals, setting a precedent for future museomics studies on taxa distributed in areas with similar climate. Finally, genome skimming of the empty shell allowed high coverage of multiple nuclear and mitochondrial loci, enabling the phylogenetic placement of the focal taxon, the re-evaluation of its taxonomic classification, and the revealing of a new Aegean land snail lineage, Aristina genus novum. This approach is a non-invasive way to sample DNA from threatened land snail species and suitable to study the evolutionary history of taxa with cryptic ecology, stenoendemics, or extinct-in-the-wild, as well as old museum specimens.

eDNA in subterranean ecosystems: Applications, technical aspects, and future prospects

Monitoring of biota is pivotal for the assessment and conservation of ecosystems. Environments worldwide are being continuously and increasingly exposed to multiple adverse impacts, and the accuracy and reliability of the biomonitoring tools that can be employed shape not only the present, but more importantly, the future of entire habitats. The analysis of environmental DNA (eDNA) metabarcoding data provides a quick, affordable, and reliable molecular approach for biodiversity assessments. However, while extensively employed in aquatic and terrestrial surface environments, eDNA-based studies targeting subterranean ecosystems are still uncommon due to the lack of accessibility and the cryptic nature of these environments and their species. Recent advances in genetic and genomic analyses have established a promising framework for shedding new light on subterranean biodiversity and ecology. To address current knowledge and the future use of eDNA methods in groundwaters and caves, this review explores conceptual and technical aspects of the application and its potential in subterranean systems. We briefly introduce subterranean biota and describe the most used traditional sampling techniques. Next, eDNA characteristics, application, and limitations in the subsurface environment are outlined. Last, we provide suggestions on how to overcome caveats and delineate some of the research avenues that will likely shape this field in the near future. We advocate that eDNA analyses, when carefully conducted and ideally combined with conventional sampling techniques, will substantially increase understanding and enable crucial expansion of subterranean community characterisation. Given the importance of groundwater and cave ecosystems for nature and humans, eDNA can bring to the surface essential insights, such as study of ecosystem assemblages and rare species detection, which are critical for the preservation of life below, as well as above, the ground.

PhyloHerb: A high-throughput phylogenomic pipeline for processing genome skimming data

PREMISE

The application of high-throughput sequencing, especially to herbarium specimens, is rapidly accelerating biodiversity research. Low-coverage sequencing of total genomic DNA (genome skimming) is particularly promising and can simultaneously recover the plastid, mitochondrial, and nuclear ribosomal regions across hundreds of species. Here, we introduce PhyloHerb, a bioinformatic pipeline to efficiently assemble phylogenomic data sets derived from genome skimming.

METHODS AND RESULTS

PhyloHerb uses either a built-in database or user-specified references to extract orthologous sequences from all three genomes using a BLAST search. It outputs FASTA files and offers a suite of utility functions to assist with alignment, partitioning, concatenation, and phylogeny inference. The program is freely available at https://github.com/lmcai/PhyloHerb/.

CONCLUSIONS

We demonstrate that PhyloHerb can accurately identify genes using a published data set from Clusiaceae. We also show via simulations that our approach is effective for highly fragmented assemblies from herbarium specimens and is scalable to thousands of species.

Cross-sectional geometry predicts failure location in maize stalks

BACKGROUND

Stalk lodging (breaking of agricultural plant stalks prior to harvest) is a multi-billion dollar a year problem. Stalk lodging occurs when high winds induce bending moments in the stalk which exceed the bending strength of the plant. Previous biomechanical models of plant stalks have investigated the effect of cross-sectional morphology on stalk lodging resistance (e.g., diameter and rind thickness). However, it is unclear if the location of stalk failure along the length of stem is determined by morphological or compositional factors. It is also unclear if the crops are structurally optimized, i.e., if the plants allocate structural biomass to create uniform and minimal bending stresses in the plant tissues. The purpose of this paper is twofold: (1) to investigate the relationship between bending stress and failure location of maize stalks, and (2) to investigate the potential of phenotyping for internode-level bending stresses to assess lodging resistance.

RESULTS

868 maize specimens representing 16 maize hybrids were successfully tested in bending to failure. Internode morphology was measured, and bending stresses were calculated. It was found that bending stress is highly and positively associated with failure location. A user-friendly computational tool is presented to help plant breeders in phenotyping for internode-level bending stress. Phenotyping for internode-level bending stresses could potentially be used to breed for more biomechanically optimal stalks that are resistant to stalk lodging.

CONCLUSIONS

Internode-level bending stress plays a potentially critical role in the structural integrity of plant stems. Equations and tools provided herein enable researchers to account for this phenotype, which has the potential to increase the bending strength of plants without increasing overall structural biomass.

Progress of Genomics-Driven Approaches for Sustaining Underutilized Legume Crops in the Post-Genomic Era

Legume crops, belonging to the Fabaceae family, are of immense importance for sustaining global food security. Many legumes are profitable crops for smallholder farmers due to their unique ability to fix atmospheric nitrogen and their intrinsic ability to thrive on marginal land with minimum inputs and low cultivation costs. Recent progress in genomics shows promise for future genetic gains in major grain legumes. Still it remains limited in minor legumes/underutilized legumes, including adzuki bean, cluster bean, horse gram, lathyrus, red clover, urd bean, and winged bean. In the last decade, unprecedented progress in completing genome assemblies of various legume crops and resequencing efforts of large germplasm collections has helped to identify the underlying gene(s) for various traits of breeding importance for enhancing genetic gain and contributing to developing climate-resilient cultivars. This review discusses the progress of genomic resource development, including genome-wide molecular markers, key breakthroughs in genome sequencing, genetic linkage maps, and trait mapping for facilitating yield improvement in underutilized legumes. We focus on 1) the progress in genomic-assisted breeding, 2) the role of whole-genome resequencing, pangenomes for underpinning the novel genomic variants underlying trait gene(s), 3) how adaptive traits of wild underutilized legumes could be harnessed to develop climate-resilient cultivars, 4) the progress and status of functional genomics resources, deciphering the underlying trait candidate genes with putative function in underutilized legumes 5) and prospects of novel breeding technologies, such as speed breeding, genomic selection, and genome editing. We conclude the review by discussing the scope for genomic resources developed in underutilized legumes to enhance their production and play a critical role in achieving the "zero hunger" sustainable development goal by 2030 set by the United Nations.

Cytokinin-microbiome interactions regulate developmental functions

BACKGROUND

The interaction of plants with the complex microbial networks that inhabit them is important for plant health. While the reliance of plants on their microbial inhabitants for defense against invading pathogens is well documented, the acquisition of data concerning the relationships between plant developmental stage or aging, and microbiome assembly, is still underway. The plant hormone cytokinin (CK) regulates various plant growth and developmental processes. Here, examining the relationships between plant development and microbiome assembly, we observed developmental-age dependent changes in the phyllopshere microbiome. We show that age-related shifts in microbiome content vary based on content of, or sensitivity to, CK.

RESULTS

We found a developmental age associated decline in microbial richness and diversity, accompanied by a decline in the presence of growth promoting and resistance inducing Bacilli in the phyllosphere. This decline was absent from CK-rich or CK-hypersensitive genotypes. Bacillus isolates we obtained from CK rich genotypes were found to alter the expression of developmental genes to support morphogenesis and alter the leaf developmental program when applied to seedlings, and enhance yield and agricultural productivity when applied to mature plants.

CONCLUSIONS

Our results support the notion that CK supports developmental functions in part via the bacterial community.

High throughput phenotyping of cross-sectional morphology to assess stalk lodging resistance

BACKGROUND

Stalk lodging (mechanical failure of plant stems during windstorms) leads to global yield losses in cereal crops estimated to range from 5% to 25% annually. The cross-sectional morphology of plant stalks is a key determinant of stalk lodging resistance. However, previously developed techniques for quantifying cross-sectional morphology of plant stalks are relatively low-throughput, expensive and often require specialized equipment and expertise. There is need for a simple and cost-effective technique to quantify plant traits related to stalk lodging resistance in a high-throughput manner.

RESULTS

A new phenotyping methodology was developed and applied to a range of plant samples including, maize (Zea mays), sorghum (Sorghum bicolor), wheat (Triticum aestivum), poison hemlock (Conium maculatum), and Arabidopsis (Arabis thaliana). The major diameter, minor diameter, rind thickness and number of vascular bundles were quantified for each of these plant types. Linear correlation analyses demonstrated strong agreement between the newly developed method and more time-consuming manual techniques (R² > 0.9). In addition, the new method was used to generate several specimen-specific finite element models of plant stalks. All the models compiled without issue and were successfully imported into finite element software for analysis. All the models demonstrated reasonable and stable solutions when subjected to realistic applied loads.

CONCLUSIONS

A rapid, low-cost, and user-friendly phenotyping methodology was developed to quantify two-dimensional plant cross-sections. The methodology offers reduced sample preparation time and cost as compared to previously developed techniques. The new methodology employs a stereoscope and a semi-automated image processing algorithm. The algorithm can be used to produce specimen-specific, dimensionally accurate computational models (including finite element models) of plant stalks.

Testing the Complete Plastome for Species Discrimination, Cryptic Species Discovery and Phylogenetic Resolution in Cephalotaxus (Cephalotaxaceae)

Species of Cephalotaxus have great economic and ecological values. However, the taxonomy and interspecific phylogenetic relationships within the genus have been controversial and remained not fully resolved until now. To date, no study examined the efficiency of the complete plastome as super-barcode across Cephalotaxus species with multiple samples per taxon. In this study, we have evaluated the complete plastome in species discrimination and phylogenetic resolution in Cephalotaxus by including 32 individuals of all eight recognized species and five varieties following Farjon's classification (2010) with multiple samples per taxon. Our results indicated that not all species recognized in recent taxonomic revisions of Cephalotaxus could be distinguished and not all were monophyletic. Based on the plastome phylogeny, a new taxonomic classification for the genus comprising nine species and two varieties, including a cryptic species, was proposed. The phylogeny also resolved all interspecific relationships. Compared to the plastome based classification, standard DNA barcodes, alone or in combination, only recognized a maximum of seven out of the nine species. Moreover, two highly variable single loci, ycf1 and rps16, each alone achieved full species discrimination. With the moderate length of 1079 bp, rps16 is proposed as a specific barcode to discriminate Cephalotaxus species. The super-barcodes and specific barcode candidates will aid in the identification of endangered Cephalotaxus species, and to help focus conservation measures.

Development and application of a virus-induced gene silencing protocol for the study of gene function in narrow-leafed lupin

BACKGROUND

Lupins are promising protein crops with an increasing amount of genomic and transcriptomic resources. The new resources facilitate the in silico identification of candidate genes controlling important agronomic traits. However, a major bottleneck for lupin research and crop improvement is the in planta characterization of gene function. Here, we present an efficient protocol for virus-induced gene silencing (VIGS) to down-regulate endogenous genes in narrow-leafed lupin (NLL) using the apple latent spherical virus (ALSV).

RESULTS

We identified ALSV as an appropriate VIGS vector able to infect NLL without causing a discernible phenotype. We created improved ALSV vectors to allow for efficient cloning of gene fragments into the viral genome and for easier viral propagation via agroinfiltration of Nicotiana benthamiana. Using this system, we silenced the visual marker gene phytoene desaturase (PDS), which resulted in systemic, homogenous silencing as indicated by bleaching of newly produced tissues. Furthermore, by silencing lysine decarboxylase (LaLDC)-a gene likely to be involved in toxic alkaloid biosynthesis-we demonstrate the applicability of our VIGS method to silence a target gene alone or alongside PDS in a 'PDS co-silencing' approach. The co-silencing approach allows the visual identification of tissues where silencing is actively occurring, which eases tissue harvesting and downstream analysis, and is useful where the trait under study is not affected by PDS silencing. Silencing LaLDC resulted in a ~ 61% or ~ 67% decrease in transcript level, depending on whether LaLDC was silenced alone or alongside PDS. Overall, the silencing of LaLDC resulted in reduced alkaloid levels, providing direct evidence of its involvement in alkaloid biosynthesis in NLL.

CONCLUSIONS

We provide a rapid and efficient VIGS method for validating gene function in NLL. This will accelerate the research and improvement of this underutilized crop.

Plastome Diversity and Phylogenomic Relationships in Asteraceae

Plastid genomes are in general highly conserved given their slow evolutionary rate, and thus large changes in their structure are unusual. However, when specific rearrangements are present, they are often phylogenetically informative. Asteraceae is a highly diverse family whose evolution is long driven by polyploidy (up to 48x) and hybridization, both processes usually complicating systematic inferences. In this study, we generated one of the most comprehensive plastome-based phylogenies of family Asteraceae, providing information about the structure, genetic diversity and repeat composition of these sequences. By comparing the whole-plastome sequences obtained, we confirmed the double inversion located in the long single-copy region, for most of the species analyzed (with the exception of basal tribes), a well-known feature for Asteraceae plastomes. We also showed that genome size, gene order and gene content are highly conserved along the family. However, species representative of the basal subfamily Barnadesioideae-as well as in the sister family Calyceraceae-lack the pseudogene rps19 located in one inverted repeat. The phylogenomic analysis conducted here, based on 63 protein-coding genes, 30 transfer RNA genes and 21 ribosomal RNA genes from 36 species of Asteraceae, were overall consistent with the general consensus for the family's phylogeny while resolving the position of tribe Senecioneae and revealing some incongruences at tribe level between reconstructions based on nuclear and plastid DNA data.

An accurate assignment test for extremely low-coverage whole-genome sequence data

Genomic assignment tests can provide important diagnostic biological characteristics, such as population of origin or ecotype. Yet, assignment tests often rely on moderate- to high-coverage sequence data that can be difficult to obtain for fields such as molecular ecology and ancient DNA. We have developed a novel approach that efficiently assigns biologically relevant information (i.e., population identity or structural variants such as inversions) in extremely low-coverage sequence data. First, we generate databases from existing reference data using a subset of diagnostic single nucleotide polymorphisms (SNPs) associated with a biological characteristic. Low-coverage alignment files are subsequently compared to these databases to ascertain allelic state, yielding a joint probability for each association. To assess the efficacy of this approach, we assigned haplotypes and population identity in Heliconius butterflies, Atlantic herring, and Atlantic cod using chromosomal inversion sites and whole-genome data. We scored both modern and ancient specimens, including the first whole-genome sequence data recovered from ancient Atlantic herring bones. The method accurately assigns biological characteristics, including population membership, using extremely low-coverage data (as low as 0.0001x) based on genome-wide SNPs. This approach will therefore increase the number of samples in evolutionary, ecological and archaeological research for which relevant biological information can be obtained.

Estimating and evaluating the rice cluster distribution uniformity with UAV-based images

The uniformity of the rice cluster distribution in the field affects population quality and the precise management of pesticides and fertilizers. However, there is no appropriate technical system for estimating and evaluating the uniformity at present. For that reason, a method based on unmanned aerial vehicle (UAV images) is proposed to estimate and evaluate the uniformity in this present study. This method includes rice cluster recognition and location determination based on the RGB color characteristics of the seedlings of aerial images, region segmentation considering the rice clusters based on Voronoi Diagram, and uniformity index definition for evaluating the rice cluster distribution based on the variation coefficient. The results indicate the rice cluster recognition attains a high precision, with the precision, accuracy, recall, and F1-score of rice cluster recognition reaching > 95%, 97%, 97%, 95%, and 96%, respectively. The rice cluster location error is small and obeys the gamma (3.00, 0.54) distribution (mean error, 1.62 cm). The uniformity index is reasonable for evaluating the rice cluster distribution verified via simulation. As a whole process, the estimating method is sufficiently high accuracy with relative error less than 0.01% over the manual labeling method. Therefore, this method based on UAV images is feasible, convenient, technologically advanced, inexpensive, and highly precision for the estimation and evaluation of the rice cluster distribution uniformity. However, the evaluation application indicates that there is much room for improvement in terms of the uniformity of mechanized paddy field transplanting in South China.

Axial variation in flexural stiffness of plant stem segments: measurement methods and the influence of measurement uncertainty

BACKGROUND

Flexural three-point bending tests are useful for characterizing the mechanical properties of plant stems. These tests can be performed with minimal sample preparation, thus allowing tests to be performed relatively quickly. The best-practice for such tests involves long spans with supports and load placed at nodes. This approach typically provides only one flexural stiffness measurement per specimen. However, by combining flexural tests with analytic equations, it is possible to solve for the mechanical characteristics of individual stem segments.

RESULTS

A method is presented for using flexural tests to obtain estimates of flexural stiffness of individual segments. This method pairs physical test data with analytic models to obtain a system of equations. The solution of this system of equations provides values of flexural stiffness for individual stalk segments. Uncertainty in the solved values for flexural stiffness were found to be strongly dependent upon measurement errors. Row-wise scaling of the system of equations reduced the influence of measurement error. Of many possible test combinations, the most advantageous set of tests for performing these measurements were identified. Relationships between measurement uncertainty and solution uncertainty were provided for two different testing methods.

CONCLUSIONS

The methods presented in this paper can be used to measure the axial variation in flexural stiffness of plant stem segments. However, care must be taken to account for the influence of measurement error as the individual segment method amplifies measurement error. An alternative method involving aggregate flexural stiffness values does not amplify measurement error, but provides lower spatial resolution.

The Crop Clamp - A non-destructive electromechanical pinch test to evaluate stalk lodging resistance

Given the ever-increasing world population, maize plays a pivotal role in global food security. A major obstacle facing farmers is stalk lodging (the breakage of the stalk before harvest), which leads to substantial losses in annual yields. Weather, disease, and pest damage are major contributors to stalk lodging. Traditionally, evaluating a stalk's tendency to lodge was achieved with a 'pinch' test: pinching the stalk by hand to estimate its transverse stiffness. This test is inherently qualitative, and results vary from person to person. To combat these problems, a portable, battery-operated, non-destructive device for precisely measuring the transverse stiffness of maize stalks, known as the Crop Clamp, has been developed. The device is capable of recording over 100 measurements per hour and has been validated against laboratory tests.

CONSULT: accurate contamination removal using locality-sensitive hashing

A fundamental question appears in many bioinformatics applications: Does a sequencing read belong to a large dataset of genomes from some broad taxonomic group, even when the closest match in the set is evolutionarily divergent from the query? For example, low-coverage genome sequencing (skimming) projects either assemble the organelle genome or compute genomic distances directly from unassembled reads. Using unassembled reads needs contamination detection because samples often include reads from unintended groups of species. Similarly, assembling the organelle genome needs distinguishing organelle and nuclear reads. While k-mer-based methods have shown promise in read-matching, prior studies have shown that existing methods are insufficiently sensitive for contamination detection. Here, we introduce a new read-matching tool called CONSULT that tests whether k-mers from a query fall within a user-specified distance of the reference dataset using locality-sensitive hashing. Taking advantage of large memory machines available nowadays, CONSULT libraries accommodate tens of thousands of microbial species. Our results show that CONSULT has higher true-positive and lower false-positive rates of contamination detection than leading methods such as Kraken-II and improves distance calculation from genome skims. We also demonstrate that CONSULT can distinguish organelle reads from nuclear reads, leading to dramatic improvements in skim-based mitochondrial assemblies.

Testing genome skimming for species discrimination in the large and taxonomically difficult genus Rhododendron

Standard plant DNA barcodes based on 2-3 plastid regions, and nrDNA ITS show variable levels of resolution, and fail to discriminate among species in many plant groups. Genome skimming to recover complete plastid genome sequences and nrDNA arrays has been proposed as a solution to address these resolution limitations. However, few studies have empirically tested what gains are achieved in practice. Of particular interest is whether adding substantially more plastid and nrDNA characters will lead to an increase in discriminatory power, or whether the resolution limitations of standard plant barcodes are fundamentally due to plastid genomes and nrDNA not tracking species boundaries. To address this, we used genome skimming to recover near-complete plastid genomes and nuclear ribosomal DNA from Rhododendron species and compared discrimination success with standard plant barcodes. We sampled 218 individuals representing 145 species of this species-rich and taxonomically difficult genus, focusing on the global biodiversity hotspots of the Himalaya-Hengduan Mountains. Only 33% of species were distinguished using ITS+matK+rbcL+trnH-psbA. In contrast, 55% of species were distinguished using plastid genome and nrDNA sequences. The vast majority of this increase is due to the additional plastid characters. Thus, despite previous studies showing an asymptote in discrimination success beyond 3-4 plastid regions, these results show that a demonstrable increase in discriminatory power is possible with extensive plastid genome data. However, despite these gains, many species remain unresolved, and these results also reinforce the need to access multiple unlinked nuclear loci to obtain transformative gains in species discrimination in plants.

Characterization of expansin genes and their transcriptional regulation by histone modifications in strawberry

The possible candidate expansin genes, which may be important for strawberry fruit softening, have been identified in the diploid woodland strawberry Fragaria vesca and the octoploid cultivated strawberry Fragaria × ananassa and their transcriptional regulation by histone modifications has been studied. Softening process greatly affects fruit texture and shelf life. Expansins (EXPs) are a group of structural proteins participating in cell wall loosening, which break the hydrogen bonding between cellulose microfibrils and hemicelluloses. However, our knowledge on how EXP genes are regulated in fruit ripening, especially in non-climacteric fleshy fruits, is limited. Here, we have identified the EXP genes in both the octoploid cultivated strawberry (Fragaria × ananassa) and one of its diploid progenitor species, woodland strawberry (Fragaria vesca). We found that EXP proteins in F. × ananassa were structurally more divergent than the ones in F. vesca. Transcriptome data suggested that FaEXP88, FaEXP114, FveEXP11 and FveEXP33 were the four candidate EXP genes more likely involved in fruit softening, whose transcript levels dramatically increased when firmness decreased during fruit maturation. Phylogenetic analyses showed that those candidate genes were closely clustered, indicating the presence of homoeolog expression dominance in the EXP gene family in strawberry. Moreover, we have performed chromatin immunoprecipitation (ChIP) experiments to investigate the distribution of histone modifications along the promoters and genic regions of the EXP genes in F. vesca. ChIP data revealed that the transcript levels of EXP genes were highly correlated with the enrichment of H3K9/K14 acetylation and H3K27 tri-methylation. Collectively, this study identifies the key EXP genes involved in strawberry fruit softening and reveals a regulatory role of histone modifications in their transcriptional regulation, which would facilitate functional studies of the EXP genes in the ripening of non-climacteric fruits.

Genome skimming-based simple sequence repeat (SSR) marker discovery and characterization in Grevillea robusta

Proteaceae, a largely southern hemisphere family consisting of 80 genera distributed in Australia and southern Africa as its centres of greatest diversity, also extends well in northern and southern America. Under this family, Grevillea robusta is a fast-growing species got popularity in farm and avenue plantations. Despite the ecological and economic importance, the species has not yet been investigated for its genetic improvement and genome-based studies. Only a few molecular markers are available for the species or its close relatives, which hinders  genomic and population genetics studies. Genetic markers have been intensively applied for the main strategies in breeding programs, especially for the economically important traits. Hence, it is of utmost priority to develop genomic database resources and species-specific markers for studying quantitative genetics in G. robusta. Given this, the present study aimed to develop de novo genome sequencing, robust microsatellites markers, sequence annotation and their validation in different stands of G. robusta in northern India. Library preparation and sequencing were carried out using Illumina paired-end sequencing technology. Approximately, ten gigabases (Gb) sequence data with 70.87 million raw reads assembled into 425,923 contigs (read mapped to 76.48%) comprising 455 Mb genome size (23 × coverage) generated through genome skimming approach. In total, 9421 simple sequence repeat (SSR) primer pairs were successfully designed from 13,335 microsatellite repeats. Afterward, a subset of 161 primer pairs was randomly selected, synthesized and validated. All the tested primers showed successful amplification but only 13 showed polymorphisms. The polymorphic SSRs were further used to estimate the measures of genetic diversity in 12 genotypes each from the states of Punjab, Haryana, Himachal Pradesh and Uttarakhand. Importantly, the average number of alleles (Na), observed heterozygosity (Ho), expected heterozygosity (He), and the polymorphism information content (PIC) were recorded as 2.69, 0.356, 0.557 and 0.388, respectively. The availability of sequence information and newly developed SSR markers could potentially be used in various genetic analyses and improvements through molecular breeding strategies for G. robusta.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01035-w.

Semi-supervised few-shot learning approach for plant diseases recognition

BACKGROUND

Learning from a few samples to automatically recognize the plant leaf diseases is an attractive and promising study to protect the agricultural yield and quality. The existing few-shot classification studies in agriculture are mainly based on supervised learning schemes, ignoring unlabeled data's helpful information.

METHODS

In this paper, we proposed a semi-supervised few-shot learning approach to solve the plant leaf diseases recognition. Specifically, the public PlantVillage dataset is used and split into the source domain and target domain. Extensive comparison experiments considering the domain split and few-shot parameters (N-way, k-shot) were carried out to validate the correctness and generalization of proposed semi-supervised few-shot methods. In terms of selecting pseudo-labeled samples in the semi-supervised process, we adopted the confidence interval to determine the number of unlabeled samples for pseudo-labelling adaptively.

RESULTS

The average improvement by the single semi-supervised method is 2.8%, and that by the iterative semi-supervised method is 4.6%.

CONCLUSIONS

The proposed methods can outperform other related works with fewer labeled training data.

Phylogenetics and comparative plastome genomics of two of the largest genera of angiosperms, Piper and Peperomia (Piperaceae)

Biological radiations provide unique opportunities to understand the evolution of biodiversity. One such radiation is the pepper plant family Piperaceae, an early-diverging and mega-diverse lineage that could serve as a model to study the diversification of angiosperms. However, traditional genetic markers lack sufficient variation for such studies, and testing hypotheses on poorly resolved phylogenetic frameworks becomes challenging. Limited genomic data is available for Piperaceae, which contains two of the largest genera of angiosperms, Piper (>2100 species) and Peperomia (>1300 species). To address this gap, we used genome skimming to assemble and annotate whole plastomes (152-161kbp) and >5kbp nuclear ribosomal DNA region from representatives of Piper and Peperomia. We conducted phylogenetic and comparative genomic analyses to study plastome evolution and investigate the role of hybridization in this group. Plastome phylogenetic trees were well resolved and highly supported, with a hard incongruence observed between plastome and nuclear phylogenetic trees suggesting hybridization in Piper. While all plastomes of Piper and Peperomia had the same gene content and order, there were informative structural differences between them. First, ycf1 was more variable and longer in Piper than Peperomia, extending well into the small single copy region by thousands of base pairs. We also discovered previously unknown structural variation in 14 out of 25 Piper taxa, tandem duplication of the trnH-GUG gene resulting in an expanded large single copy region. Other early-diverging angiosperms have a duplicated trnH-GUG, but the specific rearrangement we found is unique to Piper and serves to refine knowledge of relationships among early-diverging angiosperms. Our study demonstrates that genome skimming is an efficient approach to produce plastome assemblies for comparative genomics and robust phylogenies of species-rich plant genera.

Metagenomics: A viable tool for reconstructing herbivore diet

Metagenomics can generate data on the diet of herbivores, without the need for primer selection and PCR enrichment steps as is necessary in metabarcoding. Metagenomic approaches to diet analysis have remained relatively unexplored, requiring validation of bioinformatic steps. Currently, no metagenomic herbivore diet studies have utilized both chloroplast and nuclear markers as reference sequences for plant identification, which would increase the number of reads that could be taxonomically informative. Here, we explore how in silico simulation of metagenomic data sets resembling sequences obtained from faecal samples can be used to validate taxonomic assignment. Using a known list of sequences to create simulated data sets, we derived reliable identification parameters for taxonomic assignments of sequences. We applied these parameters to characterize the diet of western capercaillies (Tetrao urogallus) located in Norway, and compared the results with metabarcoding trnL P6 loop data generated from the same samples. Both methods performed similarly in the number of plant taxa identified (metagenomics 42 taxa, metabarcoding 43 taxa), with no significant difference in species resolution (metagenomics 24%, metabarcoding 23%). We further observed that while metagenomics was strongly affected by the age of faecal samples, with fresh samples outperforming old samples, metabarcoding was not affected by sample age. On the other hand, metagenomics allowed us to simultaneously obtain the mitochondrial genome of the western capercaillies, thereby providing additional ecological information. Our study demonstrates the potential of utilizing metagenomics for diet reconstruction but also highlights key considerations as compared to metabarcoding for future utilization of this technique.

High-throughput soybean seeds phenotyping with convolutional neural networks and transfer learning

BACKGROUND

Effective soybean seed phenotyping demands large-scale accurate quantities of morphological parameters. The traditional manual acquisition of soybean seed morphological phenotype information is error-prone, and time-consuming, which is not feasible for large-scale collection. The segmentation of individual soybean seed is the prerequisite step for obtaining phenotypic traits such as seed length and seed width. Nevertheless, traditional image-based methods for obtaining high-throughput soybean seed phenotype are not robust and practical. Although deep learning-based algorithms can achieve accurate training and strong generalization capabilities, it requires a large amount of ground truth data which is often the limitation step.

RESULTS

We showed a novel synthetic image generation and augmentation method based on domain randomization. We synthesized a plenty of labeled image dataset automatedly by our method to train instance segmentation network for high throughput soybean seeds segmentation. It can pronouncedly decrease the cost of manual annotation and facilitate the preparation of training dataset. And the convolutional neural network can be purely trained by our synthetic image dataset to achieve a good performance. In the process of training Mask R-CNN, we proposed a transfer learning method which can reduce the computing costs significantly by finetuning the pre-trained model weights. We demonstrated the robustness and generalization ability of our method by analyzing the result of synthetic test datasets with different resolution and the real-world soybean seeds test dataset.

CONCLUSION

The experimental results show that the proposed method realized the effective segmentation of individual soybean seed and the efficient calculation of the morphological parameters of each seed and it is practical to use this approach for high-throughput objects instance segmentation and high-throughput seeds phenotyping.

Leaf area index estimation model for UAV image hyperspectral data based on wavelength variable selection and machine learning methods

BACKGROUND

To accurately estimate winter wheat leaf area index (LAI) using unmanned aerial vehicle (UAV) hyperspectral imagery is crucial for crop growth monitoring, fertilization management, and development of precision agriculture.

METHODS

The UAV hyperspectral imaging data, Analytical Spectral Devices (ASD) data, and LAI were simultaneously obtained at main growth stages (jointing stage, booting stage, and filling stage) of various winter wheat varieties under various nitrogen fertilizer treatments. The characteristic bands related to LAI were extracted from UAV hyperspectral data with different algorithms including first derivative (FD), successive projections algorithm (SPA), competitive adaptive reweighed sampling (CARS), and competitive adaptive reweighed sampling combined with successive projections algorithm (CARS_SPA). Furthermore, three modeling machine learning methods including partial least squares regression (PLSR), support vector machine regression (SVR), and extreme gradient boosting (Xgboost) were used to build LAI estimation models.

RESULTS

The results show that the correlation coefficient between UAV and ASD hyperspectral data is greater than 0.99, indicating the UAV data can be used for estimation of wheat growth information. The LAI bands selected by using different algorithms were slightly different among the 15 models built in this study. The Xgboost model using nine consecutive characteristic bands selected by CARS_SPA algorithm as input was proved to have the best performance. This model yielded identical results of coefficient of determination (0.89) for both calibration set and validation set, indicating a high accuracy of this model.

CONCLUSIONS

The Xgboost modeling method in combine with CARS_SPA algorithm can reduce input variables and improve the efficiency of model operation. The results provide reference and technical support for nondestructive and rapid estimation of winter wheat LAI by using UAV.

High-throughput image segmentation and machine learning approaches in the plant sciences across multiple scales

Agriculture has benefited greatly from the rise of big data and high-performance computing. The acquisition and analysis of data across biological scales have resulted in strategies modeling inter- actions between plant genotype and environment, models of root architecture that provide insight into resource utilization, and the elucidation of cell-to-cell communication mechanisms that are instrumental in plant development. Image segmentation and machine learning approaches for interpreting plant image data are among many of the computational methodologies that have evolved to address challenging agricultural and biological problems. These approaches have led to contributions such as the accelerated identification of gene that modulate stress responses in plants and automated high-throughput phenotyping for early detection of plant diseases. The continued acquisition of high throughput imaging across multiple biological scales provides opportunities to further push the boundaries of our understandings quicker than ever before. In this review, we explore the current state of the art methodologies in plant image segmentation and machine learning at the agricultural, organ, and cellular scales in plants. We show how the methodologies for segmentation and classification differ due to the diversity of physical characteristics found at these different scales. We also discuss the hardware technologies most commonly used at these different scales, the types of quantitative metrics that can be extracted from these images, and how the biological mechanisms by which plants respond to abiotic/biotic stresses or genotypic modifications can be extracted from these approaches.

DNA barcoding of phytopathogens for disease diagnostics and bio-surveillance

DNA barcoding has proven to be a versatile tool for plant disease diagnostics in the genomics era. As the mass parallel and next generation sequencing techniques gained importance, the role of specific barcodes came under immense scrutiny. Identification and accurate classification of phytopathogens need a universal approach which has been the main application area of the concept of barcode. The present review entails a detailed description of the present status of barcode application in plant disease diagnostics. A case study on the application of Internal Transcribed Spacer (ITS) as barcode for Aspergillus and Fusarium spp. sheds light on the requirement of other potential candidates as barcodes for accurate identification. The challenges faced while barcoding novel pathogens have also been discussed with a comprehensive outline of integrating more recent technologies like meta-barcoding and genome skimming for detecting plant pathogens.

Lake Sedimentary DNA Research on Past Terrestrial and Aquatic Biodiversity: Overview and Recommendations

The use of lake sedimentary DNA to track the long-term changes in both terrestrial and aquatic biota is a rapidly advancing field in paleoecological research. Although largely applied nowadays, knowledge gaps remain in this field and there is therefore still research to be conducted to ensure the reliability of the sedimentary DNA signal. Building on the most recent literature and seven original case studies, we synthesize the state-of-the-art analytical procedures for effective sampling, extraction, amplification, quantification and/or generation of DNA inventories from sedimentary ancient DNA (sedaDNA) via high-throughput sequencing technologies. We provide recommendations based on current knowledge and best practises.

Atractylodis Rhizoma: A review of its traditional uses, phytochemistry, pharmacology, toxicology and quality control

ETHNOPHARMACOLOGICAL RELEVANCE

Atractylodis Rhizoma (AR), mainly includes Atractylodes lancea (Thunb.) DC. (A. lancea) and Atractylodes chinensis (DC.) Koidz. (A. chinensis) is widely used in East Asia as a diuretic and stomachic drug, for the treatment of rheumatic diseases, digestive disorders, night blindness, and influenza as it contains a variety of sesquiterpenoids and other components of medicinal importance.

AIM OF THE REVIEW

A systematic summary on the botany, traditional uses, phytochemistry, pharmacology, toxicology, and quality control of AR was presented to explore the future therapeutic potential and scientific potential of this plant.

MATERIALS AND METHODS

A review of the literature was performed by consulting scientific databases including Google Scholar, Web of Science, Baidu Scholar, Springer, PubMed, ScienceDirect, CNKI, etc. Plant taxonomy was confirmed to the database "The Plant List".

RESULTS

Over 200 chemical compounds have been isolated from AR, notably sesquiterpenoids and alkynes. Various pharmacological activities have been demonstrated, especially improving gastrointestinal function and thus allowed to assert most of the traditional uses of AR.

CONCLUSIONS

The researches on AR are extensive, but gaps still remain. The molecular mechanism, structure-activity relationship, potential synergistic and antagonistic effects of these components need to be further elucidated. It is suggested that further studies should be carried out in the aspects of comprehensive evaluation of the quality of medicinal materials, understanding of the "effective forms" and "additive effects" of the pharmacodynamic substances based on the same pharmacophore of TCM, and its long-term toxicity in vivo and clinical efficacy.

Validation of reference genes for quantitative gene expression in the Lippia alba polyploid complex (Verbenaceae)

Lippia alba (Verbenaceae) is one of the most studied species of the genus Lippia, mainly due to its medicinal properties. The species was described as a polyploid complex with five cytotypes. The comparison of gene expression in species with several ploidal levels needs to be conducted carefully due to possible changes in gene regulation. Quantitative reverse transcription PCR (qRT-PCR) is a widely used method for transcript abundance analyses in plants. Besides being an extremely powerful technique, relative quantification by Real-Time quantitative PCR (RT-qPCR) needs the normalization with a stable reference gene. We evaluated the stability of nine candidate reference genes in Lippia alba with different ploidal levels using NormFinder, geNorm, and RefFinder software. The product of each primer showed a single peak in the melting curve. The R² value ranged from 0.998 to 1000 and primers efficiency ranged from 98.95% to 129%. The CIT gene came up as a stable housekeeping gene, being appropriate for studies in polyploid accessions of Lippia alba. Considering that polyploidy is widely documented in Angiosperms, the results can be used not only for further gene expression studies in L. alba but also as a possible reference gene for other polyploid complexes. Differential stability among different genes highlights the importance of the validation of reference genes used for RT-qPCR approach in polyploid studies.