MADS-Box Gene Classification in Angiosperms by Clustering and Machine Learning Approaches

Sex determination in papaya: Current status and perspectives

Papaya (Carica papaya L.) is an economically significant plant that produces fruit consumed worldwide due to its organoleptic characteristics. Since their commercial production, papaya fruits have faced several problems, such as pests, which have been partly resolved using transgenic varieties. Nevertheless, a principal challenge in this cultivation is the plant's sex determination. The sex issue in papaya is complex because papaya flowers can bear three sex forms: male, female, and hermaphrodite, which affects their fruit production, shape, and yield. Fruits from hermaphrodite plants are preferred more by consumers than female ones, and male plants rarely produce fruits without commercial value. Chromosomes are responsible for sex determination in papaya, denoted as XY for male, XX for female, and XYh for hermaphrodite. However, genes related to sex have been reported but are not conclusive. Factors such as the environment, hormones, and genetic and epigenetic background can also affect sex expression. Therefore, in this review, we will discuss recent research on the sex of papaya, from reported genes to date, their biology, and sexing approaches using molecular markers and their advantages.

Transcriptional Regulation of Pine Male and Female Cone Initiation and Development: Key Players Identified Through Comparative Transcriptomics

With long reproductive timescales, large complex genomes, and a lack of reliable reference genomes, understanding gene function in conifers is extremely challenging. Consequently, our understanding of which genetic factors influence the development of reproductive structures (cones) in monoecious conifers remains limited. Genes with inferred roles in conifer reproduction have mostly been identified through homology and phylogenetic reconstruction with their angiosperm counterparts. We used RNA-sequencing to generate transcriptomes of the early morphological stages of cone development in the conifer species Pinus densiflora and used these to gain a deeper insight into the transcriptional changes during male and female cone development. Paired-end Illumina sequencing was used to generate transcriptomes from non-reproductive tissue and male and female cones at four time points with a total of 382.82 Gbp of data generated. After assembly and stringent filtering, a total of 37,164 transcripts were retrieved, of which a third were functionally annotated using the Mercator plant pipeline. Differentially expressed gene (DEG) analysis resulted in the identification of 172,092 DEGs in the nine tissue types. This, alongside GO gene enrichment analyses, pinpointed transcripts putatively involved in conifer reproductive structure development, including co-orthologs of several angiosperm flowering genes and several that have not been previously reported in conifers. This study provides a comprehensive transcriptome resource for male and early female cone development in the gymnosperm species Pinus densiflora. Characterisation of this resource has allowed the identification of potential key players and thus provides valuable insights into the molecular regulation of reproductive structure development in monoecious conifers.

Draft genome of Korthalsia laciniosa (Griff.) Mart., a climbing rattan elucidates its phylogenetic position

Korthalsia laciniosa (Griff.) Mart. is a climbing rattan used as a source of durable and flexible cane. In the present study, the draft genome of K. laciniosa was sequenced, de novo assembled and annotated. Genome-wide identification of MADS-Box transcription factors revealed loss of Mβ, and Mγ genes belonging to Type I subclass in the rattan lineage. Mining of the genome revealed presence of 13 families of lignin biosynthetic pathway genes and expression profiling of nine major genes documented relatively lower level of expression in cirrus when compared to leaflet and petiole. The chloroplast genome was re-constructed and analysis revealed the phylogenetic relatedness of this genus to Eugeissona, in contrast with its present taxonomic position. The genomic resource generated in the present study will accelerate population structure analysis, genetic resource conservation, phylogenomics and facilitate understanding the unique developmental processes like gender expression at molecular level.

Genome-wide study of flowering-related MADS-box genes family in Cardamine hirsuta

MADS-box genes take part in diverse biological functions especially in development of reproductive structures and control of flowering time. Recently, Cardamine hirsuta has emerged as an exclusively powerful genetic system in comparative studies of development. Although the C. hirsuta genome sequence is available but a comprehensive analysis of its MADS-box family genes is still lacking. Here, we determined 50 Cardamine MADS-box genes through bioinformatics tools and classified them into 2 Mβ, 6 Mα and 2 Mγ and 40 MIKC-type (35 MIKCc and 5MIKC*) genes based on a phylogenetic analysis. The C. hirsuta MIKC subfamily could be further classified into 14 subgroups as Arabidopsis. However the number of MADS-box proteins was not equal among these subgroups. Based on the structural diversity among 50 MADS-box genes, 2 lineages were obtained, type I and type II. The lowest number of introns (0 or 1) was found in the Mα, Mβ, and Mγ groups of the type I genes. The most Cardamine MADS-box genes were randomly distributed on only three chromosomes. C. hirsuta had a relatively lower number of flowering MADS-box genes than A. thaliana and probably tandem duplication event resulted in the expansion of FLC, SQUA and TM3 family members in Arabidopsis. Moreover among the conserved motifs, ChMADS5 of SQUA, ChMADS34 of TM3 and ChMADS51 of AGL15 families had no K-domain. This study provides a basis for further functional investigation of MADS-box genes in C. hirsuta.

A Deep Learning Approach to Population Structure Inference in Inbred Lines of Maize

Analysis of population genetic variation and structure is a common practice for genome-wide studies, including association mapping, ecology, and evolution studies in several crop species. In this study, machine learning (ML) clustering methods, K-means (KM), and hierarchical clustering (HC), in combination with non-linear and linear dimensionality reduction techniques, deep autoencoder (DeepAE) and principal component analysis (PCA), were used to infer population structure and individual assignment of maize inbred lines, i.e., dent field corn (n = 97) and popcorn (n = 86). The results revealed that the HC method in combination with DeepAE-based data preprocessing (DeepAE-HC) was the most effective method to assign individuals to clusters (with 96% of correct individual assignments), whereas DeepAE-KM, PCA-HC, and PCA-KM were assigned correctly 92, 89, and 81% of the lines, respectively. These findings were consistent with both Silhouette Coefficient (SC) and Davies-Bouldin validation indexes. Notably, DeepAE-HC also had better accuracy than the Bayesian clustering method implemented in InStruct. The results of this study showed that deep learning (DL)-based dimensional reduction combined with ML clustering methods is a useful tool to determine genetically differentiated groups and to assign individuals into subpopulations in genome-wide studies without having to consider previous genetic assumptions.

Molecular Mechanisms of the Floral Biology of Jatropha curcas: Opportunities and Challenges as an Energy Crop

Fossil fuel sources are a limited resource and could eventually be depleted. Biofuels have emerged as a renewable alternative to fossil fuels. Jatropha has grown in significance as a potential bioenergy crop due to its high content of seed oil. However, Jatropha's lack of high-yielding seed genotypes limits its potential use for biofuel production. The main cause of lower seed yield is the low female to male flower ratio (1:25-10), which affects the total amount of seeds produced per plant. Here, we review the genetic factors responsible for floral transitions, floral organ development, and regulated gene products in Jatropha. We also summarize potential gene targets to increase seed production and discuss challenges ahead.

Floral Induction and Flower Development of Orchids

Orchids comprise one of the largest, most highly evolved angiosperm families, and form an extremely peculiar group of plants. Various orchids are available through traditional breeding and micro-propagation since they are valuable as potted plants and/or cut flowers in horticultural markets. The flowering of orchids is generally influenced by environmental signals such as temperature and endogenous developmental programs controlled by genetic factors as is usual in many flowering plant species. The process of floral transition is connected to the flower developmental programs that include floral meristem maintenance and floral organ specification. Thanks to advances in molecular and genetic technologies, the understanding of the molecular mechanisms underlying orchid floral transition and flower developmental processes have been widened, especially in several commercially important orchids such as Phalaenopsis, Dendrobium and Oncidium. In this review, we consolidate recent progress in research on the floral transition and flower development of orchids emphasizing representative genes and genetic networks, and also introduce a few successful cases of manipulation of orchid flowering/flower development through the application of molecular breeding or biotechnology tools.