Polyploidy often confers emergent properties, such as the higher fibre productivity and quality of tetraploid cottons than diploid cottons bred for the same environments¹. Here we show that an abrupt five- to sixfold ploidy increase approximately 60 million years (Myr) ago, and allopolyploidy reuniting divergent Gossypium genomes approximately 1–2 Myr ago², conferred about 30–36-fold duplication of ancestral angiosperm (flowering plant) genes in elite cottons (Gossypium hirsutum and Gossypium barbadense), genetic complexity equalled only by Brassica³ among sequenced angiosperms. Nascent fibre evolution, before allopolyploidy, is elucidated by comparison of spinnable-fibred Gossypium herbaceum A and non-spinnable Gossypium longicalyx F genomes to one another and the outgroup D genome of non-spinnable Gossypium raimondii. The sequence of a G. hirsutum A_tD_t (in which ‘t’ indicates tetraploid) cultivar reveals many non-reciprocal DNA exchanges between subgenomes that may have contributed to phenotypic innovation and/or other emergent properties such as ecological adaptation by polyploids. Most DNA-level novelty in G. hirsutum recombines alleles from the D-genome progenitor native to its New World habitat and the Old World A-genome progenitor in which spinnable fibre evolved. Coordinated expression changes in proximal groups of functionally distinct genes, including a nuclear mitochondrial DNA block, may account for clusters of cotton-fibre quantitative trait loci affecting diverse traits. Opportunities abound for dissecting emergent properties of other polyploids, particularly angiosperms, by comparison to diploid progenitors and outgroups.

Accuracy in quantitative real-time polymerase chain reaction (qPCR) requires the use of stable endogenous controls. Normalization with multiple reference genes is the gold standard, but their identification is a laborious task, especially in species with limited sequence information. Coffee (Coffea ssp.) is an important agricultural commodity and, due to its economic relevance, is the subject of increasing research in genetics and biotechnology, in which gene expression analysis is one of the most important fields. Notwithstanding, relatively few works have focused on the analysis of gene expression in coffee. Moreover, most of these works have used less accurate techniques such as northern blot assays instead of more accurate techniques (e.g., qPCR) that have already been extensively used in other plant species. Aiming to boost the use of qPCR in studies of gene expression in coffee, we uncovered reference genes to be used in a number of different experimental conditions. Using two distinct algorithms implemented by geNorm and Norm Finder, we evaluated a total of eight candidate reference genes (psaB, PP2A, AP47, S24, GAPDH, rpl39, UBQ10, and UBI9) in four different experimental sets (control versus drought-stressed leaves, control versus drought-stressed roots, leaves of three different coffee cultivars, and four different coffee organs). The most suitable combination of reference genes was indicated in each experimental set for use as internal control for reliable qPCR data normalization. This study also provides useful guidelines for reference gene selection for researchers working with coffee plant samples under conditions other than those tested here.

Background: In response to infection, viral genomes are processed by Dicer-like (DCL) ribonuclease proteins into viral small RNAs (vsRNAs) of discrete sizes. vsRNAs are then used as guides for silencing the viral genome. The profile of vsRNAs produced during the infection process has been extensively studied for some groups of viruses. However, nothing is known about the vsRNAs produced during infections of members of the economically important family Luteoviridae, a group of phloem-restricted viruses. Here, we report the characterization of a population of vsRNAs from cotton plants infected with Cotton leafroll dwarf virus (CLRDV), a member of the genus Polerovirus, family Luteoviridae. Results: Deep sequencing of small RNAs (sRNAs) from leaves of CLRDV-infected cotton plants revealed that the vsRNAs were 21- to 24-nucleotides (nt) long and that their sequences matched the viral genome, with higher frequencies of matches in the 3- region. There were equivalent amounts of sense and antisense vsRNAs, and the 22-nt class of small RNAs was predominant. During infection, cotton Dcl transcripts appeared to be up-regulated, while Dcl2 appeared to be down-regulated. Conclusions: This is the first report on the profile of sRNAs in a plant infected with a virus from the family Luteoviridae. Our sequence data strongly suggest that virus-derived double-stranded RNA functions as one of the main precursors of vsRNAs. Judging by the profiled size classes, all cotton DCLs might be working to silence the virus. The possible causes for the unexpectedly high accumulation of 22-nt vsRNAs are discussed. CLRDV is the causal agent of Cotton blue disease, which occurs worldwide. Our results are an important contribution for understanding the molecular mechanisms involved in this and related diseases.