63 research outputs found

    Cereal Domestication and Evolution of Branching: Evidence for Soft Selection in the Tb1 Orthologue of Pearl Millet (Pennisetum glaucum [L.] R. Br.)

    Get PDF
    BACKGROUND: During the Neolithic revolution, early farmers altered plant development to domesticate crops. Similar traits were often selected independently in different wild species; yet the genetic basis of this parallel phenotypic evolution remains elusive. Plant architecture ranks among these target traits composing the domestication syndrome. We focused on the reduction of branching which occurred in several cereals, an adaptation known to rely on the major gene Teosinte-branched1 (Tb1) in maize. We investigate the role of the Tb1 orthologue (Pgtb1) in the domestication of pearl millet (Pennisetum glaucum), an African outcrossing cereal. METHODOLOGY/PRINCIPAL FINDINGS: Gene cloning, expression profiling, QTL mapping and molecular evolution analysis were combined in a comparative approach between pearl millet and maize. Our results in pearl millet support a role for PgTb1 in domestication despite important differences in the genetic basis of branching adaptation in that species compared to maize (e.g. weaker effects of PgTb1). Genetic maps suggest this pattern to be consistent in other cereals with reduced branching (e.g. sorghum, foxtail millet). Moreover, although the adaptive sites underlying domestication were not formerly identified, signatures of selection pointed to putative regulatory regions upstream of both Tb1 orthologues in maize and pearl millet. However, the signature of human selection in the pearl millet Tb1 is much weaker in pearl millet than in maize. CONCLUSIONS/SIGNIFICANCE: Our results suggest that some level of parallel evolution involved at least regions directly upstream of Tb1 for the domestication of pearl millet and maize. This was unanticipated given the multigenic basis of domestication traits and the divergence of wild progenitor species for over 30 million years prior to human selection. We also hypothesized that regular introgression of domestic pearl millet phenotypes by genes from the wild gene pool could explain why the selective sweep in pearl millet is softer than in maize

    Comparison of immunohistochemistry with PCR for assessment of ER, PR, and Ki-67 and prediction of pathological complete response in breast cancer

    Get PDF
    Background: Proliferation may predict response to neoadjuvant therapy of breast cancer and is commonly assessed by manual scoring of slides stained by immunohistochemistry (IHC) for Ki-67 similar to ER and PgR. This method carries significant intra- and inter-observer variability. Automatic scoring of Ki-67 with digital image analysis (qIHC) or assessment of MKI67 gene expression with RT-qPCR may improve diagnostic accuracy. Methods: Ki-67 IHC visual assessment was compared to the IHC nuclear tool (AperioTM) on core biopsies from a randomized neoadjuvant clinical trial. Expression of ESR1, PGR and MKI67 by RT-qPCR was performed on RNA extracted from the same formalin-fixed paraffin-embedded tissue. Concordance between the three methods (vIHC, qIHC and RT-qPCR) was assessed for all 3 markers. The potential of Ki-67 IHC and RT-qPCR to predict pathological complete response (pCR) was evaluated using ROC analysis and non-parametric Mann-Whitney Test. Results: Correlation between methods (qIHC versus RT-qPCR) was high for ER and PgR (spearman´s r = 0.82, p < 0.0001 and r = 0.86, p < 0.0001, respectively) resulting in high levels of concordance using predefined cut-offs. When comparing qIHC of ER and PgR with RT-qPCR of ESR1 and PGR the overall agreement was 96.6 and 91.4%, respectively, while overall agreement of visual IHC with RT-qPCR was slightly lower for ER/ESR1 and PR/PGR (91.2 and 92.9%, respectively). In contrast, only a moderate correlation was observed between qIHC and RT-qPCR continuous data for Ki-67/MKI67 (Spearman’s r = 0.50, p = 0.0001). Up to now no predictive cut-off for Ki-67 assessment by IHC has been established to predict response to neoadjuvant chemotherapy. Setting the desired sensitivity at 100%, specificity for the prediction of pCR (ypT0ypN0) was significantly higher for mRNA than for protein (68.9% vs. 22.2%). Moreover, the proliferation levels in patients achieving a pCR versus not differed significantly using MKI67 RNA expression (Mann-Whitney p = 0.002), but not with qIHC of Ki-67 (Mann-Whitney p = 0.097) or vIHC of Ki-67 (p = 0.131). Conclusion: Digital image analysis can successfully be implemented for assessing ER, PR and Ki-67. IHC for ER and PR reveals high concordance with RT-qPCR. However, RT-qPCR displays a broader dynamic range and higher sensitivity than IHC. Moreover, correlation between Ki-67 qIHC and RT-qPCR is only moderate and RT-qPCR with MammaTyper® outperforms qIHC in predicting pCR. Both methods yield improvements to error-prone manual scoring of Ki-67. However, RT-qPCR was significantly more specific

    Genome-wide association study identifies 25 known breast cancer susceptibility loci as risk factors for triple-negative breast cancer

    Get PDF
    Triple-negative (TN) breast cancer is an aggressive subtype of breast cancer associated with a unique set of epidemiologic and genetic risk factors. We conducted a two-stage genome-wide association study of TN breast cancer (stage 1: 1529 TN cases, 3399 controls; stage 2: 2148 cases, 1309 controls) to identify loci that influence TN breast cancer risk. Variants in the 19p13.1 and PTHLH loci showed genome-wide significant associations (P < 5 × 10− 8) in stage 1 and 2 combined. Results also suggested a substantial enrichment of significantly associated variants among the single nucleotide polymorphisms (SNPs) analyzed in stage 2. Variants from 25 of 74 known breast cancer susceptibility loci were also associated with risk of TN breast cancer (P < 0.05). Associations with TN breast cancer were confirmed for 10 loci (LGR6, MDM4, CASP8, 2q35, 2p24.1, TERT-rs10069690, ESR1, TOX3, 19p13.1, RALY), and we identified associations with TN breast cancer for 15 additional breast cancer loci (P < 0.05: PEX14, 2q24.1, 2q31.1, ADAM29, EBF1, TCF7L2, 11q13.1, 11q24.3, 12p13.1, PTHLH, NTN4, 12q24, BRCA2, RAD51L1-rs2588809, MKL1). Further, two SNPs independent of previously reported signals in ESR1 [rs12525163 odds ratio (OR) = 1.15, P = 4.9 × 10− 4] and 19p13.1 (rs1864112 OR = 0.84, P = 1.8 × 10− 9) were associated with TN breast cancer. A polygenic risk score (PRS) for TN breast cancer based on known breast cancer risk variants showed a 4-fold difference in risk between the highest and lowest PRS quintiles (OR = 4.03, 95% confidence interval 3.46–4.70, P = 4.8 × 10− 69). This translates to an absolute risk for TN breast cancer ranging from 0.8% to 3.4%, suggesting that genetic variation may be used for TN breast cancer risk prediction
    • …
    corecore