The typical plastid genome (plastome) of photosynthetic angiosperms comprises a pair of Inverted Repeat regions (IRs), which separate a Large Single Copy region (LSC) from a Small Single Copy region (SSC). The independent losses of IRs have been documented in only a few distinct plant lineages. The majority of these taxa show uncommonly high levels of plastome structural variations, while a few have otherwise conserved plastomes. For a better understanding of the function of IRs in stabilizing plastome structure, more taxa that have lost IRs need to be investigated. We analyzed the plastomes of eight species from two genera of the putranjivoid clade of Malpighiales using Illumina paired-end sequencing, the de novo assembly strategy GetOrganelle, as well as a combination of two annotation methods. We found that all eight plastomes of the putranjivoid clade have lost their IR B , representing the fifth case of IR loss within autotrophic angiosperms. Coinciding with the loss of the IR, plastomes of the putranjivoid clade have experienced significant structural variations including gene and intron losses, multiple large inversions, as well as the translocation and duplication of plastome segments. However, Balanopaceae, one of the close relatives of the putranjivoid clade, exhibit a relatively conserved plastome organization with canonical IRs. Our results corroborate earlier reports that the IR loss and additional structural reorganizations are closely linked, hinting at a shared mechanism that underpins structural disturbances.

Genetic control of the timing of flowering in woody plants is complex and has yet to be adequately investigated due to their long life-cycle and difficulties in genetic modification. Studies in Populus, one of the best woody plant models, have revealed a highly conserved genetic network for flowering timing in annuals. However, traits like continuous flowering cannot be addressed with Populus. Roses and strawberries have relatively small, diploid genomes and feature enormous natural variation. With the development of new genetic populations and genomic tools, roses and strawberries have become good models for studying the molecular mechanisms underpinning the regulation of flowering in woody plants. Here, we review findings on the molecular and genetic factors controlling continuous flowering in roses and woodland strawberries. Natural variation at TFL1 orthologous genes in both roses and strawberries seems be the key plausible factor that regulates continuous flowering. However, recent efforts suggest that a two-recessive-loci model may explain the controlling of continuous flowering in roses. We propose that epigenetic factors, including non-coding RNAs or chromatin-related factors, might also play a role. Insights into the genetic control of flowering time variation in roses should benefit the development of new germplasm for woody crops and shed light on the molecular genetic bases for the production and maintenance of plant biodiversity.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut–brain axis (GBA) has been implicated in ASD although with limited reproducibility across studies. In this study, we developed a Bayesian differential ranking algorithm to identify ASD-associated molecular and taxa profiles across 10 cross-sectional microbiome datasets and 15 other datasets, including dietary patterns, metabolomics, cytokine profiles and human brain gene expression profiles. We found a functional architecture along the GBA that correlates with heterogeneity of ASD phenotypes, and it is characterized by ASD-associated amino acid, carbohydrate and lipid profiles predominantly encoded by microbial species in the genera Prevotella, Bifidobacterium, Desulfovibrio and Bacteroides and correlates with brain gene expression changes, restrictive dietary patterns and pro-inflammatory cytokine profiles. The functional architecture revealed in age-matched and sex-matched cohorts is not present in sibling-matched cohorts. We also show a strong association between temporal changes in microbiome composition and ASD phenotypes. In summary, we propose a framework to leverage multi-omic datasets from well-defined cohorts and investigate how the GBA influences ASD.