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The main aim of DNA barcoding is to establish a shared community resource of DNA sequences that can be used for organismal identification and taxonomic clarification. This approach was successfully pioneered in animals using a portion of the cytochrome oxidase 1 (CO1) mitochondrial gene. In plants, establishing a standardized DNA barcoding system has been more challenging. In this paper, we review the process of selecting and refining a plant barcode; evaluate the factors which influence the discriminatory power of the approach; describe some early applications of plant barcoding and summarise major emerging projects; and outline tool development that will be necessary for plant DNA barcoding to advance.

Barcodes are short segments of DNA that can be used to uniquely identify an unknown specimen to species, particularly when diagnostic morphological features are absent. These sequences could offer a new forensic tool in plant and animal conservation-especially for endangered species such as members of the Cycadales. Ideally, barcodes could be used to positively identify illegally obtained material even in cases where diagnostic features have been purposefully removed or to release confiscated organisms into the proper breeding population. In order to be useful, a DNA barcode sequence must not only easily PCR amplify with universal or near-universal reaction conditions and primers, but also contain enough variation to generate unique identifiers at either the species or population levels. Chloroplast regions suggested by the Plant Working Group of the Consortium for the Barcode of Life (CBoL), and two alternatives, the chloroplast psbA-trnH intergenic spacer and the nuclear ribosomal internal transcribed spacer (nrITS), were tested for their utility in generating unique identifiers for members of the Cycadales. Ease of amplification and sequence generation with universal primers and reaction conditions was determined for each of the seven proposed markers. While none of the proposed markers provided unique identifiers for all species tested, nrITS showed the most promise in terms of variability, although sequencing difficulties remain a drawback. We suggest a workflow for DNA barcoding, including database generation and management, which will ultimately be necessary if we are to succeed in establishing a universal DNA barcode for plants.

Driven by limited resources and a sense of urgency, the prioritization of species for conservation has been a persistent concern in conservation science. Gymnosperms (comprising ginkgo, conifers, cycads, and gnetophytes) are one of the most threatened groups of living organisms, with 40% of the species at high risk of extinction, about twice as many as the most recent estimates for all plants (i.e. 21.4%). This high proportion of species facing extinction highlights the urgent action required to secure their future through an objective prioritization approach. The Evolutionary Distinct and Globally Endangered (EDGE) method rapidly ranks species based on their evolutionary distinctiveness and the extinction risks they face. EDGE is applied to gymnosperms using a phylogenetic tree comprising DNA sequence data for 85% of gymnosperm species (923 out of 1090 species), to which the 167 missing species were added, and IUCN Red List assessments available for 92% of species. The effect of different extinction probability transformations and the handling of IUCN data deficient species on the resulting rankings is investigated. Although top entries in our ranking comprise species that were expected to score well (e.g. Wollemia nobilis , Ginkgo biloba ), many were unexpected (e.g. Araucaria araucana ). These results highlight the necessity of using approaches that integrate evolutionary information in conservation science.

For DNA barcoding to succeed as a scientific endeavor an accurate and expeditious query sequence identification method is needed. Although a global multiple-sequence alignment can be generated for some barcoding markers (e.g. COI, rbcL), not all barcoding markers are as structurally conserved (e.g. matK). Thus, algorithms that depend on global multiple-sequence alignments are not universally applicable. Some sequence identification methods that use local pairwise alignments (e.g. BLAST) are unable to accurately differentiate between highly similar sequences and are not designed to cope with hierarchic phylogenetic relationships or within taxon variability. Here, I present a novel alignment-free sequence identification algorithm--BRONX--that accounts for observed within taxon variability and hierarchic relationships among taxa. BRONX identifies short variable segments and corresponding invariant flanking regions in reference sequences. These flanking regions are used to score variable regions in the query sequence without the production of a global multiple-sequence alignment. By incorporating observed within taxon variability into the scoring procedure, misidentifications arising from shared alleles/haplotypes are minimized. An explicit treatment of more inclusive terminals allows for separate identifications to be made for each taxonomic level and/or for user-defined terminals. BRONX performs better than all other methods when there is imperfect overlap between query and reference sequences (e.g. mini-barcode queries against a full-length barcode database). BRONX consistently produced better identifications at the genus-level for all query types.

We have generated matK, rbcL, and nrITS2 DNA barcodes for 320 specimens representing all 18 extant genera of the conifer family Podocarpaceae. The sample includes 145 of the 198 recognized species. Comparative analyses of sequence quality and species discrimination were conducted on the 159 individuals from which all three markers were recovered (representing 15 genera and 97 species). The vast majority of sequences were of high quality (B 30 = 0.596-0.989). Even the lowest quality sequences exceeded the minimum requirements of the BARCODE data standard. In the few instances that low quality sequences were generated, the responsible mechanism could not be discerned. There were no statistically significant differences in the discriminatory power of markers or marker combinations (p = 0.05). The discriminatory power of the barcode markers individually and in combination is low (56.7% of species at maximum). In some instances, species discrimination failed in spite of ostensibly useful variation being present (genotypes were shared among species), but in many cases there was simply an absence of sequence variation. Barcode gaps (maximum intraspecific p-distance > minimum interspecific p-distance) were observed in 50.5% of species when all three markers were considered simultaneously. The presence of a barcode gap was not predictive of discrimination success (p = 0.02) and there was no statistically significant difference in the frequency of barcode gaps among markers (p = 0.05). In addition, there was no correlation between number of individuals sampled per species and the presence of a barcode gap (p = 0.27).

Although the seed is a key morphological innovation, its origin remains unknown and molecular data outside angiosperms is still limited. Ginkgo biloba, with a unique place in plant evolution, being one of the first extant gymnosperms where seeds evolved, can testify to the evolution and development of the seed. Initially, to better understand the development of the ovules in Ginkgo biloba ovules, we performed spatio-temporal expression analyses in seeds at early developing stages, of six candidate gene homologues known in angiosperms: WUSCHEL, AINTEGUMENTA, BELL1, KANADI, UNICORN, and C3HDZip . Surprisingly, the expression patterns of most these ovule homologues indicate that they are not wholly conserved between angiosperms and Ginkgo biloba . Consistent with previous studies on early diverging seedless plant lineages, ferns, lycophytes, and bryophytes, many of these candidate genes are mainly expressed in mega- and micro-sporangia. Through in-depth comparative transcriptome analyses of Ginkgo biloba developing ovules, pollen cones, and megagametophytes we have been able to identify novel genes, likely involved in ovule development. Finally, our expression analyses support the synangial or neo-synangial hypotheses for the origin of the seed, where the sporangium developmental network was likely co-opted and restricted during integument evolution.

A novel result of the current research is the development and implementation of a unique functional phylogenomic approach that explores the genomic origins of seed plant diversification. We first use 22,833 sets of orthologs from the nuclear genomes of 101 genera across land plants to reconstruct their phylogenetic relationships. One of the more salient results is the resolution of some enigmatic relationships in seed plant phylogeny, such as the placement of Gnetales as sister to the rest of the gymnosperms. In using this novel phylogenomic approach, we were also able to identify overrepresented functional gene ontology categories in genes that provide positive branch support for major nodes prompting new hypotheses for genes associated with the diversification of angiosperms. For example, RNA interference (RNAi) has played a significant role in the divergence of monocots from other angiosperms, which has experimental support in Arabidopsis and rice. This analysis also implied that the second largest subunit of RNA polymerase IV and V (NRPD2) played a prominent role in the divergence of gymnosperms. This hypothesis is supported by the lack of 24nt siRNA in conifers, the maternal control of small RNA in the seeds of flowering plants, and the emergence of double fertilization in angiosperms. Our approach takes advantage of genomic data to define orthologs, reconstruct relationships, and narrow down candidate genes involved in plant evolution within a phylogenomic view of species' diversification.

The evolution of seeds transformed life on earth and is responsible for our most important food crops. Gymnosperms, the oldest living seed plants, are an untapped genomic reservoir for genes involved in seed evolution. To tap this resource, we assemble deep transcriptomes of 14 gymnosperms, four angiosperms, and two ferns and identified 22,429 phylogenetically informative ortholog groups. We observe that genes differentially expressed in ovules or leaves provide the majority of phylogenomic support for the evolutionary splits between 1) seed and non-seed plants; 2) gymnosperms and angiosperms; and/or 3) within gymnosperms (conifers vs. “ancient” gymnosperms). Our gymnosperm data identifies unreported candidate ovule regulated genes in Arabidopsis . Moreover, prior knowledge from Arabidopsis helps uncover 4,076 candidate ovule genes that influence these evolutionary splits. We validate the expression of candidate ovule genes in gymnosperm-specific ovule structures. Our work provides a resource for seed gene discovery, conservation, and crop improvement. Making use of phylogenomic and transcriptome analysis of 20 plant species, including 14 gymnosperms, Sondervan et al. uncover candidate ovule genes and find that orthologs with differential tissue expression patterns across species most influence major evolutionary splits of seed plants.

Premise The automated recognition of Latin scientific names within vernacular text has many applications, including text mining, search indexing, and automated specimen‐label processing. Most published solutions are computationally inefficient, incapable of running within a web browser, and focus on texts in English, thus omitting a substantial portion of biodiversity literature. Methods and Results An open‐source browser‐executable solution, Quaesitor, is presented here. It uses pattern matching (regular expressions) in combination with an ensembled classifier composed of an inclusion dictionary search (Bloom filter), a trio of complementary neural networks that differ in their approach to encoding text, and word length to automatically identify Latin scientific names in the 16 most common languages for biodiversity articles. Conclusions In combination, the classifiers can recognize Latin scientific names in isolation or embedded within the languages used for >96% of biodiversity literature titles. For three different data sets, they resulted in a 0.80–0.97 recall and a 0.69–0.84 precision at a rate of 8.6 ms/word.

Herbarium sheets present a unique view of the world's botanical history, evolution, and biodiversity. This makes them an all–important data source for botanical research. With the increased digitization of herbaria worldwide and advances in the domain of fine–grained visual classification which can facilitate automatic identification of herbarium specimen images, there are many opportunities for supporting and expanding research in this field. However, existing datasets are either too small, or not diverse enough, in terms of represented taxa, geographic distribution, and imaging protocols. Furthermore, aggregating datasets is difficult as taxa are recognized under a multitude of names and must be aligned to a common reference. We introduce the Herbarium 2021 Half–Earth dataset: the largest and most diverse dataset of herbarium specimen images, to date, for automatic taxon recognition. We also present the results of the Herbarium 2021 Half–Earth challenge, a competition that was part of the Eighth Workshop on Fine-Grained Visual Categorization (FGVC8) and hosted by Kaggle to encourage the development of models to automatically identify taxa from herbarium sheet images.