Erratum to: The relationship of recombination rate, genome structure, and patterns of molecular evolution across angiosperms

Herbgenomics meets Papaveraceae: a promising -omics perspective on medicinal plant research

Herbal medicines were widely used in ancient and modern societies as remedies for human ailments. Notably, the Papaveraceae family includes well-known species, such as Papaver somniferum and Chelidonium majus, which possess medicinal properties due to their latex content. Latex-bearing plants are a rich source of diverse bioactive compounds, with applications ranging from narcotics to analgesics and relaxants. With the advent of high-throughput technologies and advancements in sequencing tools, an opportunity exists to bridge the knowledge gap between the genetic information of herbs and the regulatory networks underlying their medicinal activities. This emerging discipline, known as herbgenomics, combines genomic information with other -omics studies to unravel the genetic foundations, including essential gene functions and secondary metabolite biosynthesis pathways. Furthermore, exploring the genomes of various medicinal plants enables the utilization of modern genetic manipulation techniques, such as Clustered Regularly-Interspaced Short Palindromic Repeats (CRISPR/Cas9) or RNA interference. This technological revolution has facilitated systematic studies of model herbs, targeted breeding of medicinal plants, the establishment of gene banks and the adoption of synthetic biology approaches. In this article, we provide a comprehensive overview of the recent advances in genomic, transcriptomic, proteomic and metabolomic research on species within the Papaveraceae family. Additionally, it briefly explores the potential applications and key opportunities offered by the -omics perspective in the pharmaceutical industry and the agrobiotechnology field.

Mapping causal genes and genetic interactions for agronomic traits using a large F2 population in rice

Dissecting the genetic mechanisms underlying agronomic traits is of great importance for crop breeding. Agronomic traits are usually controlled by multiple quantitative trait loci (QTLs) and genetic interactions, and mapping the underlying causal genes is still labor-intensive and time-consuming. Here, we present a genetic tool for directly targeting the specific causal genes by using a single-gene resolution linkage map that was constructed from 3756 F2 rice plants via targeted sequencing technology and Tukey-Kramer multiple comparisons test. Three large- and moderate-effect QTLs, qHD6-2, qGL3-1, and qGW5-2, were successfully mapped to their specific causal genes, Hd1, GS3, and GW5, respectively. A complex genetic interaction network containing 30 QTL-QTL interactions was constructed, revealing that the alternative allele of hub QTL, qHD6-2, can hide or release the genetic contributions of the alleles at interacting loci. Moreover, arranging genetic interactions in the models lead to more accurate phenotypic predictions. These results provide a community resource and new feasible strategy for deciphering the genetic mechanisms of complex agronomic traits and accelerating crop breeding.