Identification of Differential Gene Expression in Brassica rapa Nectaries through Expressed Sequence Tag Analysis

BACKGROUND: Nectaries are the floral organs responsible for the synthesis and secretion of nectar. Despite their central roles in pollination biology, very little is understood about the molecular mechanisms underlying nectar production. This project was undertaken to identify genes potentially involved in mediating nectary form and function in Brassica rapa. METHODOLOGY AND PRINCIPAL FINDINGS: Four cDNA libraries were created using RNA isolated from the median and lateral nectaries of B. rapa flowers, with one normalized and one non-normalized library being generated from each tissue. Approximately 3,000 clones from each library were randomly sequenced from the 5' end to generate a total of 11,101 high quality expressed sequence tags (ESTs). Sequence assembly of all ESTs together allowed the identification of 1,453 contigs and 4,403 singleton sequences, with the Basic Localized Alignment Search Tool (BLAST) being used to identify 4,138 presumptive orthologs to Arabidopsis thaliana genes. Several genes differentially expressed between median and lateral nectaries were initially identified based upon the number of BLAST hits represented by independent ESTs, and later confirmed via reverse transcription polymerase chain reaction (RT PCR). RT PCR was also used to verify the expression patterns of eight putative orthologs to known Arabidopsis nectary-enriched genes. CONCLUSIONS/SIGNIFICANCE: This work provided a snapshot of gene expression in actively secreting B. rapa nectaries, and also allowed the identification of differential gene expression between median and lateral nectaries. Moreover, 207 orthologs to known nectary-enriched genes from Arabidopsis were identified through this analysis. The results suggest that genes involved in nectar production are conserved amongst the Brassicaceae, and also supply clones and sequence information that can be used to probe nectary function in B. rapa

Genomic Rearrangements in Arabidopsis Considered as Quantitative Traits.

To understand the population genetics of structural variants and their effects on phenotypes, we developed an approach to mapping structural variants that segregate in a population sequenced at low coverage. We avoid calling structural variants directly. Instead, the evidence for a potential structural variant at a locus is indicated by variation in the counts of short-reads that map anomalously to that locus. These structural variant traits are treated as quantitative traits and mapped genetically, analogously to a gene expression study. Association between a structural variant trait at one locus, and genotypes at a distant locus indicate the origin and target of a transposition. Using ultra-low-coverage (0.3×) population sequence data from 488 recombinant inbred Arabidopsis thaliana genomes, we identified 6502 segregating structural variants. Remarkably, 25% of these were transpositions. While many structural variants cannot be delineated precisely, we validated 83% of 44 predicted transposition breakpoints by polymerase chain reaction. We show that specific structural variants may be causative for quantitative trait loci for germination and resistance to infection by the fungus Albugo laibachii, isolate Nc14. Further we show that the phenotypic heritability attributable to read-mapping anomalies differs from, and, in the case of time to germination and bolting, exceeds that due to standard genetic variation. Genes within structural variants are also more likely to be silenced or dysregulated. This approach complements the prevalent strategy of structural variant discovery in fewer individuals sequenced at high coverage. It is generally applicable to large populations sequenced at low-coverage, and is particularly suited to mapping transpositions

Autoregulation of RCO by Low-Affinity Binding Modulates Cytokinin Action and Shapes Leaf Diversity

Mechanisms through which the evolution of gene regulation causes morphological diversity are largely unclear. The tremendous shape variation among plant leaves offers attractive opportunities to address this question. In cruciferous plants, the REDUCED COMPLEXITY (RCO) homeodomain protein evolved via gene duplication and acquired a novel expression domain that contributed to leaf shape diversity. However, the molecular pathways through which RCO regulates leaf growth are unknown. A key question is to identify genome-wide transcriptional targets of RCO and the DNA sequences to which RCO binds. We investigate this question using Cardamine hirsuta, which has complex leaves, and its relative Arabidopsis thaliana, which evolved simple leaves through loss of RCO. We demonstrate that RCO directly regulates genes controlling homeostasis of the hormone cytokinin to repress growth at the leaf base. Elevating cytokinin signaling in the RCO expression domain is sufficient to both transform A. thaliana simple leaves into complex ones and partially bypass the requirement for RCO in C. hirsuta complex leaf development. We also identify RCO as its own target gene. RCO directly represses its own transcription via an array of low-affinity binding sites, which evolved after RCO duplicated from its progenitor sequence. This autorepression is required to limit RCO expression. Thus, evolution of low-affinity binding sites created a negative autoregulatory loop that facilitated leaf shape evolution by defining RCO expression and fine-tuning cytokinin activity. In summary, we identify a transcriptional mechanism through which conflicts between novelty and pleiotropy are resolved during evolution and lead to morphological differences between species. Hajheidari et al. identify target genes for the RCO homeodomain protein that drove leaf shape diversity. They show that RCO regulates growth via orchestrating homeostasis for the hormone cytokinin and that it also represses its own transcription via low-affinity binding sites. This autorepression helps delimit RCO expression and shape leaf form

A genome-wide scan for common alleles affecting risk for autism

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm&lt; 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest