Zhao Lai

The F-Box Protein AhSLF-S2 Controls the Pollen Function of S-RNase–Based Self-Incompatibility

Recently, we have provided evidence that the polymorphic self-incompatibility (S) locus-encoded F-box (SLF) protein AhSLF-S2 plays a role in mediating a selective S-RNase destruction during the self-incompatible response in Antirrhinum hispanicum. To investigate its role further, we first transformed a transformation-competent artificial chromosome clone (TAC26) containing both AhSLF-S2 and AhS2-RNase into a self-incompatible (SI) line of Petunia hybrida. Molecular analyses showed that both genes are correctly expressed in pollen and pistil in four independent transgenic lines of petunia. Pollination tests indicated that all four lines became self-compatible because of the specific loss of the pollen function of SI. This alteration was transmitted stably into the T1 progeny. We then transformed AhSLF-S2 cDNA under the control of a tomato (Lycopersicon esculentum) pollen-specific promoter LAT52 into the self-incompatible petunia line. Molecular studies revealed that AhSLF-S2 is specifically expressed in pollen of five independent transgenic plants. Pollination tests showed that they also had lost the pollen function of SI. Importantly, expression of endogenous SLF or SLF-like genes was not altered in these transgenic plants. These results phenocopy a well-known phenomenon called competitive interaction whereby the presence of two different pollen S alleles within pollen leads to the breakdown of the pollen function of SI in several solanaceaous species. Furthermore, we demonstrated that AhSLF-S2 physically interacts with PhS3-RNase from the P. hybrida line used for transformation. Together with the recent demonstration of PiSLF as the pollen determinant in P. inflata, these results provide direct evidence that the polymorphic SLF including AhSLF-S2 controls the pollen function of S-RNase–based self-incompatibility.

Microarray analysis reveals differential gene expression in hybrid sunflower species

This paper describes the creation of a cDNA microarray for annual sunflowers and its use to elucidate patterns of gene expression in Helianthus annuus, Helianthus petiolaris, and the homoploid hybrid species Helianthus deserticola. The array comprises 3743 ESTs (expressed sequence tags) representing approximately 2897 unique genes. It has an average clone/EST identity rate of 91%, is applicable across species boundaries within the annual sunflowers, and shows patterns of gene expression that are highly reproducible according to real‐time RT–PCR (reverse transcription–polymerase chain reaction) results. Overall, 12.8% of genes on the array showed statistically significant differential expression across the three species. Helianthus deserticola displayed transgressive, or extreme, expression for 58 genes, with roughly equal numbers exhibiting up‐ or down‐regulation relative to both parental species. Transport‐related proteins were strongly over‐represented among the transgressively expressed genes, which makes functional sense given the extreme desert floor habitat of H. deserticola. The potential adaptive value of differential gene expression was evaluated for five genes in two populations of early generation (BC2) hybrids between the parental species grown in the H. deserticola habitat. One gene (a G protein‐coupled receptor) had a significant association with fitness and maps close to a QTL controlling traits that may be adaptive in the desert habitat.

Identification and mapping of SNPs from ESTs in sunflower

More than 67,000 expressed sequence tags (ESTs) have recently been generated for sunflower (Helianthus), including 44,000 from cultivated confectionery (RHA280) and oilseed (RHA801) lines of Helianthus annuus and 23,000 from drought- and salt-tolerant wild sunflowers, H. argophyllus and H. paradoxus, respectively. To create a transcript map for sunflower, we identified 605 ESTs that displayed small insertion–deletion polymorphism (SNP) variation in silico, had apparent tissue-specific expression patterns, and/or were ESTs with candidate functions in traits such as development, cell transport, metabolism, plant defense, and tolerance to abiotic stress. Primer pairs for 535 of the loci were designed from the ESTs and screened for polymorphism in recombinant inbred lines derived from a cross between the same cultivars (RHA280 × RHA801) employed for sequencing. In total, 273 of the loci amplified polymorphic products, of which 243 mapped to the 17 linkage groups previously identified for sunflower. Comparisons with previously mapped QTL revealed some cases where ESTs with putatively related functions mapped near QTLs identified in other crosses for salt tolerance and for domestication traits such as stem diameter, shattering, flowering time, and achene size.

Genomic Patterns of Adaptive Divergence between Chromosomally Differentiated Sunflower Species

Understanding the genetic mechanisms of speciation and basis of species differences is among the most important challenges in evolutionary biology. Two questions of particular interest are what roles divergent selection and chromosomal differentiation play in these processes. A number of recently proposed theories argue that chromosomal rearrangements can facilitate the development and maintenance of reproductive isolation and species differences by suppressing recombination within rearranged regions. Reduced recombination permits the accumulation of alleles contributing to isolation and adaptive differentiation and protects existing differences from the homogenizing effects of introgression between incipient species. Here, we examine patterns of genetic diversity and divergence in rearranged versus collinear regions in two widespread, extensively hybridizing sunflower species, Helianthus annuus and Helianthus petiolaris, using sequence data from 77 loci distributed throughout the genomes of the two species. We find weak evidence for increased genetic divergence near chromosomal break points but not within rearranged regions overall. We find no evidence for increased rates of adaptive divergence on rearranged chromosomes; in fact, collinear chromosomes show a far greater excess of fixed amino acid differences between the two species. A comparison with a third sunflower species indicates that much of the nonsynonymous divergence between H. annuus and H. petiolaris probably occurred during or soon after their formation. Our results suggest a limited role for chromosomal rearrangements in genetic divergence, but they do document substantial adaptive divergence and provide further evidence of how species integrity and genetic identity can be maintained at many loci in the face of extensive hybridization and gene flow.

Comparative Mapping and Rapid Karyotypic Evolution in the Genus Helianthus

Comparative genetic linkage maps provide a powerful tool for the study of karyotypic evolution. We constructed a joint SSR/RAPD genetic linkage map of the Helianthus petiolaris genome and used it, along with an integrated SSR genetic linkage map derived from four independent H. annuus mapping populations, to examine the evolution of genome structure between these two annual sunflower species. The results of this work indicate the presence of 27 colinear segments resulting from a minimum of eight translocations and three inversions. These 11 rearrangements are more than previously suspected on the basis of either cytological or genetic map-based analyses. Taken together, these rearrangements required a minimum of 20 chromosomal breakages/fusions. On the basis of estimates of the time since divergence of these two species (750,000–1,000,000 years), this translates into an estimated rate of 5.5–7.3 chromosomal rearrangements per million years of evolution, the highest rate reported for any taxonomic group to date.

Genomics of Compositae weeds: EST libraries, microarrays, and evidence of introgression.

PREMISE OF STUDY Weeds cause considerable environmental and economic damage. However, genomic characterization of weeds has lagged behind that of model plants and crop species. Here we describe the development of genomic tools and resources for 11 weeds from the Compositae family that will serve as a basis for subsequent population and comparative genomic analyses. Because hybridization has been suggested as a stimulus for the evolution of invasiveness, we also analyze these genomic data for evidence of hybridization. METHODS We generated 22 expressed sequence tag (EST) libraries for the 11 targeted weeds using Sanger, 454, and Illumina sequencing, compared the coverage and quality of sequence assemblies, and developed NimbleGen microarrays for expression analyses in five taxa. When possible, we also compared the distributions of Ks values between orthologs of congeneric taxa to detect and quantify hybridization and introgression. RESULTS Gene discovery was enhanced by sequencing from multiple tissues, normalization of cDNA libraries, and especially greater sequencing depth. However, assemblies from short sequence reads sometimes failed to resolve close paralogs. Substantial introgression was detected in Centaurea and Helianthus, but not in Ambrosia and Lactuca. CONCLUSIONS Transcriptome sequencing using next-generation platforms has greatly reduced the cost of genomic studies of nonmodel organisms, and the ESTs and microarrays reported here will accelerate evolutionary and molecular investigations of Compositae weeds. Our study also shows how ortholog comparisons can be used to approximately estimate the genome-wide extent of introgression and to identify genes that have been exchanged between hybridizing taxa.

Differential expression analysis of RNA sequencing data by incorporating non-exonic mapped reads

BackgroundRNA sequencing (RNA-seq) is a powerful tool for genome-wide expression profiling of biological samples with the advantage of high-throughput and high resolution. There are many existing algorithms nowadays for quantifying expression levels and detecting differential gene expression, but none of them takes the misaligned reads that are mapped to non-exonic regions into account. We developed a novel algorithm, XBSeq, where a statistical model was established based on the assumption that observed signals are the convolution of true expression signals and sequencing noises. The mapped reads in non-exonic regions are considered as sequencing noises, which follows a Poisson distribution. Given measureable observed and noise signals from RNA-seq data, true expression signals, assuming governed by the negative binomial distribution, can be delineated and thus the accurate detection of differential expressed genes.ResultsWe implemented our novel XBSeq algorithm and evaluated it by using a set of simulated expression datasets under different conditions, using a combination of negative binomial and Poisson distributions with parameters derived from real RNA-seq data. We compared the performance of our method with other commonly used differential expression analysis algorithms. We also evaluated the changes in true and false positive rates with variations in biological replicates, differential fold changes, and expression levels in non-exonic regions. We also tested the algorithm on a set of real RNA-seq data where the common and different detection results from different algorithms were reported.ConclusionsIn this paper, we proposed a novel XBSeq, a differential expression analysis algorithm for RNA-seq data that takes non-exonic mapped reads into consideration. When background noise is at baseline level, the performance of XBSeq and DESeq are mostly equivalent. However, our method surpasses DESeq and other algorithms with the increase of non-exonic mapped reads. Only in very low read count condition XBSeq had a slightly higher false discovery rate, which may be improved by adjusting the background noise effect in this situation. Taken together, by considering non-exonic mapped reads, XBSeq can provide accurate expression measurement and thus detect differential expressed genes even in noisy conditions.

Natural Variation in Gene Expression Between Wild and Weedy Populations of Helianthus annuus

The molecular genetic changes underlying the transformation of wild plants into agricultural weeds are poorly understood. Here we use a sunflower cDNA microarray to detect variation in gene expression between two wild (non-weedy) Helianthus annuus populations from Utah and Kansas and four weedy H. annuus populations collected from agricultural fields in Utah, Kansas, Indiana, and California. When grown in a common growth chamber environment, populations differed substantially in their gene expression patterns, indicating extensive genetic differentiation. Overall, 165 uni-genes, representing ∼5% of total genes on the array, showed significant differential expression in one or more weedy populations when compared to both wild populations. This subset of genes is enriched for abiotic/biotic stimulus and stress response proteins, which may underlie niche transitions from the natural sites to agricultural fields for H. annuus. However, only a small proportion of the differentially expressed genes overlapped in multiple wild vs. weedy comparisons, indicating that most of the observed expression changes are due to local adaptation or neutral processes, as opposed to parallel genotypic adaptation to agricultural fields. These results are consistent with an earlier phylogeographic study suggesting that weedy sunflowers have evolved multiple times in different regions of the United States and further indicate that the evolution of weedy sunflowers has been accompanied by substantial gene expression divergence in different weedy populations.

Targeting RPL39 and MLF2 reduces tumor initiation and metastasis in breast cancer by inhibiting nitric oxide synthase signaling

Significance This manuscript describes the identification and characterization of two previously unidentified cancer genes, ribosomal protein L39 and myeloid leukemia factor 2, that play an important role in tumor initiation and metastasis. Knockdown of these genes in triple negative breast cancer (TNBC) models significantly reduces primary-tumor growth, as well as metastasis. Mutations in these genes are associated with worse survival in breast-cancer patients. Both genes are regulated by the nitric oxide signaling pathway. Identification of these two genes represents a significant breakthrough in our understanding of treatment resistance in TNBC. Targeting these genes could alter clinical practice for tumor metastasis in future and improve outcomes of patients with breast cancer. We previously described a gene signature for breast cancer stem cells (BCSCs) derived from patient biopsies. Selective shRNA knockdown identified ribosomal protein L39 (RPL39) and myeloid leukemia factor 2 (MLF2) as the top candidates that affect BCSC self-renewal. Knockdown of RPL39 and MLF2 by specific siRNA nanoparticles in patient-derived and human cancer xenografts reduced tumor volume and lung metastases with a concomitant decrease in BCSCs. RNA deep sequencing identified damaging mutations in both genes. These mutations were confirmed in patient lung metastases (n = 53) and were statistically associated with shorter median time to pulmonary metastasis. Both genes affect the nitric oxide synthase pathway and are altered by hypoxia. These findings support that extensive tumor heterogeneity exists within primary cancers; distinct subpopulations associated with stem-like properties have increased metastatic potential.

De Novo Genome Assembly of the Economically Important Weed Horseweed Using Integrated Data from Multiple Sequencing Platforms

De novo genome assembly and genomic resources of horseweed will be useful to understand the genetic and molecular bases of weediness. Horseweed (Conyza canadensis), a member of the Compositae (Asteraceae) family, was the first broadleaf weed to evolve resistance to glyphosate. Horseweed, one of the most problematic weeds in the world, is a true diploid (2n = 2x = 18), with the smallest genome of any known agricultural weed (335 Mb). Thus, it is an appropriate candidate to help us understand the genetic and genomic bases of weediness. We undertook a draft de novo genome assembly of horseweed by combining data from multiple sequencing platforms (454 GS-FLX, Illumina HiSeq 2000, and PacBio RS) using various libraries with different insertion sizes (approximately 350 bp, 600 bp, 3 kb, and 10 kb) of a Tennessee-accessed, glyphosate-resistant horseweed biotype. From 116.3 Gb (approximately 350× coverage) of data, the genome was assembled into 13,966 scaffolds with 50% of the assembly = 33,561 bp. The assembly covered 92.3% of the genome, including the complete chloroplast genome (approximately 153 kb) and a nearly complete mitochondrial genome (approximately 450 kb in 120 scaffolds). The nuclear genome is composed of 44,592 protein-coding genes. Genome resequencing of seven additional horseweed biotypes was performed. These sequence data were assembled and used to analyze genome variation. Simple sequence repeat and single-nucleotide polymorphisms were surveyed. Genomic patterns were detected that associated with glyphosate-resistant or -susceptible biotypes. The draft genome will be useful to better understand weediness and the evolution of herbicide resistance and to devise new management strategies. The genome will also be useful as another reference genome in the Compositae. To our knowledge, this article represents the first published draft genome of an agricultural weed.