Fourier Ptychographic Neural Network Combined with Zernike Aberration Recovery and Wirtinger Flow Optimization.

Fourier ptychographic microscopy, as a computational imaging method, can reconstruct high-resolution images but suffers optical aberration, which affects its imaging quality. For this reason, this paper proposes a network model for simulating the forward imaging process in the Tensorflow framework using samples and coherent transfer functions as the input. The proposed model improves the introduced Wirtinger flow algorithm, retains the central idea, simplifies the calculation process, and optimizes the update through back propagation. In addition, Zernike polynomials are used to accurately estimate aberration. The simulation and experimental results show that this method can effectively improve the accuracy of aberration correction, maintain good correction performance under complex scenes, and reduce the influence of optical aberration on imaging quality.

Divergent selection and genetic introgression shape the genome landscape of heterosis in hybrid rice.

The successful application of heterosis in hybrid rice has dramatically improved rice productivity, but the genetic mechanism for heterosis in the hybrid rice remains unclear. In this study, we generated two populations of rice F1 hybrids with present-day commercial hybrid parents, genotyped the parents with 50k SNP chip and genome resequencing, and recorded the phenotype of ∼2,000 hybrids at three field trials. By integrating these data with the collected genotypes of ∼4,200 rice landraces and improved varieties that were reported previously, we found that the male and female parents have different levels of genome introgressions from other rice subpopulations, including indica, aus, and japonica, therefore shaping heterotic loci in the hybrids. Among the introgressed exogenous genome, we found that heterotic loci, including Ghd8/DTH8, Gn1a, and IPA1 existed in wild rice, but were significantly divergently selected among the rice subpopulations, suggesting these loci were subject to environmental adaptation. During modern rice hybrid breeding, heterotic loci were further selected by removing loci with negative effect and fixing loci with positive effect and pyramid breeding. Our results provide insight into the genetic basis underlying the heterosis of elite hybrid rice varieties, which could facilitate a better understanding of heterosis and rice hybrid breeding.

Transcriptome profiling of two super hybrid rice provides insights into the genetic basis of heterosis.

BACKGROUND: Heterosis is a phenomenon that hybrids show superior performance over their parents. The successful utilization of heterosis has greatly improved rice productivity, but the molecular basis of heterosis remains largely unclear. RESULTS: Here, the transcriptomes of young panicles and leaves of the two widely grown two-line super hybrid rice varieties (Jing-Liang-You-Hua-Zhan (JLYHZ) and Long-Liang-You-Hua-Zhan (LLYHZ)) and their parents were analyzed by RNA-seq. Transcriptome profiling of the hybrids revealed 1,778 ~ 9,404 differentially expressed genes (DEGs) in two tissues, which were identified by comparing with their parents. GO, and KEGG enrichment analysis showed that the pathways significantly enriched in both tissues of two hybrids were all related to yield and resistance, like circadian rhythm (GO:0,007,623), response to water deprivation (GO:0,009,414), and photosynthetic genes (osa00196). Allele-specific expression genes (ASEGs) were also identified in hybrids. The ASEGs were most significantly enriched in ionotropic glutamate receptor signaling pathway, which was hypothesized to be potential amino acid sensors in plants. Moreover, the ASEGs were also differentially expressed between parents. The number of variations in ASEGs is higher than expected, especially for large effect variations. The DEGs and ASEGs are the potential reasons for the formation of heterosis in the two elite super hybrid rice. CONCLUSIONS: Our results provide a comprehensive understanding of the heterosis of two-line super hybrid rice and facilitate the exploitation of heterosis in hybrid rice breeding with high yield heterosis.

The hybrid protein interactome contributes to rice heterosis as epistatic effects.

Heterosis is the phenomenon in which hybrid progeny exhibits superior traits in comparison with those of their parents. Genomic variations between the two parental genomes may generate epistasis interactions, which is one of the genetic hypotheses explaining heterosis. We postulate that protein-protein interactions specific to F1 hybrids (F1 -specific PPIs) may occur when two parental genomes combine, as the proteome of each parent may supply novel interacting partners. To test our assumption, an inter-subspecies hybrid interactome was simulated by in silico PPI prediction between rice japonica (cultivar Nipponbare) and indica (cultivar 9311). Four-thousand, six-hundred and twelve F1 -specific PPIs accounting for 20.5% of total PPIs in the hybrid interactome were found. Genes participating in F1 -specific PPIs tend to encode metabolic enzymes and are generally localized in genomic regions harboring metabolic gene clusters. To test the genetic effect of F1 -specific PPIs in heterosis, genomic selection analysis was performed for trait prediction with additive, dominant and epistatic effects separately considered in the model. We found that the removal of single nucleotide polymorphisms associated with F1 -specific PPIs reduced prediction accuracy when epistatic effects were considered in the model, but no significant changes were observed when additive or dominant effects were considered. In summary, genomic divergence widely dispersed between japonica and indica rice may generate F1 -specific PPIs, part of which may accumulatively contribute to heterosis according to our computational analysis. These candidate F1 -specific PPIs, especially for those involved in metabolic biosynthesis pathways, are worthy of experimental validation when large-scale protein interactome datasets are generated in hybrid rice in the future.

Fine mapping and candidate gene analysis of qHD5, a novel major QTL with pleiotropism for yield-related traits in rice (Oryza sativa L.).

KEY MESSAGE: A major QTL for heading date, qHD5, was fine-mapped to a 52.59-kb region on the short arm of rice chromosome 5. Heading date (HD) is one of the most important traits that enables rice to adapt to seasonal differences and specific growth conditions in diverse growing regions. In this study, a major-effect quantitative trait locus (QTL), qHD5, was resolved as a single Medelian factor that causes NIL(BG1) and NIL(XLJ) (two near-isogenic lines (NILs) used in our study) to have at a minimum of 10-day difference in HD under both long-day and short-day conditions in rice. qHD5 was initially mapped to a 309.52-kb genomic region in our previous study. Here, using an advanced BC4F3 population and map-based cloning, we further narrowed the location of qHD5 to a 52.59-kb region between the H71 and RD502 markers. Sequence analysis revealed that Os05g03040, which putatively encodes an AP2 (APETALA2) transcription factor, has six single nucleotide polymorphisms (SNPs) between NIL(BG1) and NIL(XLJ). On this basis, this gene was concluded to be the most probable candidate gene for qHD5. Our results also showed that Hd3a, RFT1, Hd1, Ehd1, and Ghd7 were differentially expressed in the two NILs. Moreover, qHD5 was found to affect yield-related traits such as flag leaf width, flag leaf length, branch number, and 1000-grain weight.

Pedigree-based analysis of derivation of genome segments of an elite rice reveals key regions during its breeding.

Analyses of genome variations with high-throughput assays have improved our understanding of genetic basis of crop domestication and identified the selected genome regions, but little is known about that of modern breeding, which has limited the usefulness of massive elite cultivars in further breeding. Here we deploy pedigree-based analysis of an elite rice, Huanghuazhan, to exploit key genome regions during its breeding. The cultivars in the pedigree were resequenced with 7.6× depth on average, and 2.1 million high-quality single nucleotide polymorphisms (SNPs) were obtained. Tracing the derivation of genome blocks with pedigree and information on SNPs revealed the chromosomal recombination during breeding, which showed that 26.22% of Huanghuazhan genome are strictly conserved key regions. These major effect regions were further supported by a QTL mapping of 260 recombinant inbred lines derived from the cross of Huanghuazhan and a very dissimilar cultivar, Shuanggui 36, and by the genome profile of eight cultivars and 36 elite lines derived from Huanghuazhan. Hitting these regions with the cloned genes revealed they include numbers of key genes, which were then applied to demonstrate how Huanghuazhan were bred after 30 years of effort and to dissect the deficiency of artificial selection. We concluded the regions are helpful to the further breeding based on this pedigree and performing breeding by design. Our study provides genetic dissection of modern rice breeding and sheds new light on how to perform genomewide breeding by design.

The effect of wrongdoer's status on observer punishment recommendations: the mediating role of envy and the moderating role of belief in a just world.

Our proposition postulates that the correlation between the wrongdoer's status and the punishment suggestions of onlookers is primarily influenced by group-oriented envy rather than the ascription of intentionality and is moderated by the belief in a just world. In three separate studies, 389 university students were asked to read scenarios describing a hit-and-run crime committed by either a rich or a poor individual and then report their opinions on intentionality attribution (Study 1 and Study 2), envy emotions (Study 2), punishment recommendations (all three studies), and belief in a just world (Study 3). Consistently, the findings indicated that those observing recommended harsher penalties to be imposed upon high-status perpetrators engaging in the same wrongdoing (such as hit-and-run) as their low-status equivalents. The effect of the rich receiving more severe punishment was predicted more strongly by envious emotions than by intentionality attributions to high-status wrongdoers and was only present for those observers who endorsed a lower belief in a just world.

Transcriptional pathobiology and multi-omics predictors for Parkinson's disease.

Early diagnosis and biomarker discovery to bolster the therapeutic pipeline for Parkinson's disease (PD) are urgently needed. In this study, we leverage the large-scale whole-blood total RNA-seq dataset from the Accelerating Medicine Partnership in Parkinson's Disease (AMP PD) program to identify PD-associated RNAs, including both known genes and novel circular RNAs (circRNA) and enhancer RNAs (eRNAs). There were 1,111 significant marker RNAs, including 491 genes, 599 eRNAs, and 21 circRNAs, that were first discovered in the PPMI cohort (FDR < 0.05) and confirmed in the PDBP/BioFIND cohorts (nominal p < 0.05). Functional enrichment analysis showed that the PD-associated genes are involved in neutrophil activation and degranulation, as well as the TNF-alpha signaling pathway. We further compare the PD-associated genes in blood with those in post-mortem brain dopamine neurons in our BRAINcode cohort. 44 genes show significant changes with the same direction in both PD brain neurons and PD blood, including neuroinflammation-associated genes IKBIP, CXCR2, and NFKBIB. Finally, we built a novel multi-omics machine learning model to predict PD diagnosis with high performance (AUC = 0.89), which was superior to previous studies and might aid the decision-making for PD diagnosis in clinical practice. In summary, this study delineates a wide spectrum of the known and novel RNAs linked to PD and are detectable in circulating blood cells in a harmonized, large-scale dataset. It provides a generally useful computational framework for further biomarker development and early disease prediction.

Experimental and Computational Methods for Allelic Imbalance Analysis from Single-Nucleus RNA-seq Data.

Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq), and introns are under lower purifying selection and thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. To further investigate ASE in the context of human disease, we applied our methods to a Parkinson's disease cohort of 94 individuals and show that ASE analysis had more power than eQTL analysis to identify significant SNP/gene pairs in our direct comparison of the two methods. Overall, we provide an end-to-end experimental and computational approach for future studies.

Genomic insights on the contribution of introgressions from Xian/Indica to the genetic improvement of Geng/Japonica rice cultivars.

Hybridization between Xian/indica (XI) and Geng/japonica (GJ) rice combined with utilization of plant ideotypes has greatly contributed to yield improvements in modern GJ rice in China over the past 50 years. To explore the genomic basis of improved yield and disease resistance in GJ rice, we conducted a large-scale genomic landscape analysis of 816 elite GJ cultivars representing multiple eras of germplasm from China. We detected consistently increasing introgressions from three XI subpopulations into GJ cultivars since the 1980s and found that the XI genome introgressions significantly increased the grain number per panicle (GN) and decreased the panicle number per plant. This contributed to the improvement of plant type during modern breeding, changing multi-tiller plants to moderate tiller plants with a large panicle size and increasing the blast resistance. Notably, we found that key gene haplotypes controlling plant architecture, yield components, and pest and disease resistance, including IPA1, SMG1, DEP3, Pib, Pi-d2, and Bph3, were introduced from XI rice by introgression. By GWAS analysis, we detected a GN-related gene Gnd5, which had been consistently introgressed from XI into GJ cultivars since the 1980s. Gnd5 is a GRAS transcription factor gene, and Gnd5 knockout mutants showed a significant reduction in GN. The estimated genetic effects of genes varied among different breeding locations, which explained the distinct introgression levels of XI gene haplotypes, including Gnd5, DEP3, etc., to these GJ breeding pedigrees. These findings reveal the genomic contributions of introgressions from XI to the trait improvements of GJ rice cultivars and provide new insights for future rice genomic breeding.

qHD5 encodes an AP2 factor that suppresses rice heading by down-regulating Ehd2 expression.

Heading date is crucial for rice reproduction and the geographical expansion of cultivation. We fine-mapped qHD5 and identified LOC_Os05g03040, a gene that encodes an AP2 transcription factor, as the candidate gene of qHD5 in our previous study. In this article, using two near-isogenic lines NIL(BG1) and NIL(XLJ), which were derived from the progeny of the cross between BigGrain1 (BG1) and Xiaolijing (XLJ), we verified that LOC_Os05g03040 represses heading date in rice through genetic complementation and CRISPR/Cas9 gene-editing experiments. Complementary results showed that qHD5 is a semi-dominant gene and that the qHD5XLJ and qHD5BG1 alleles are both functional. The homozygous mutant line generated from knocking out qHD5XLJ in NIL(XLJ) headed earlier than NIL(XLJ) under both short-day and long-day conditions. In addition, the homozygous mutant line of qHD5BG1 in NIL(BG1) also headed slightly earlier than NIL(BG1). All of these results show that qHD5 represses the heading date in rice. Transient expression showed that the qHD5 protein localizes to the nucleus. Transactivation activity assays showed that the C-terminus is the critical site that affects self-activation in qHD5XLJ. qRT-PCR analysis revealed that qHD5 represses flowering by down-regulating Ehd2. qHD5 may have been selected during indica rice domestication.

Forecasting rice latitude adaptation through a daylength-sensing-based environment adaptation simulator.

Global climate change necessitates crop varieties with good environmental adaptability. As a proxy for climate adaptation, crop breeders could select for adaptability to different latitudes, but the lengthy procedures for that slow development. Here, we combined molecular technologies with a streamlined in-house screening method to facilitate rapid selection for latitude adaptation. We established the daylength-sensing-based environment adaptation simulator (DEAS) to assess rice latitude adaptation status via the transcriptional dynamics of florigen genes at different latitudes. The DEAS predicted the florigen expression profiles in rice varieties with high accuracy. Furthermore, the DEAS showed potential for application in different crops. Incorporating the DEAS into conventional breeding programmes would help to develop cultivars for climate adaptation.

The Asymmetric Expression of SAUR Genes Mediated by ARF7/19 Promotes the Gravitropism and Phototropism of Plant Hypocotyls.

The asymmetric distribution of auxin leads to the bending growth of hypocotyls during gravitropic and phototropic responses, but the signaling events downstream of auxin remain unclear. Here, we identify many SAUR genes showing asymmetric expression in soybean hypocotyls during gravistimulation and then study their homologs in Arabidopsis. SAUR19 subfamily genes have asymmetric expression in Arabidopsis hypocotyls during gravitropic and phototropic responses, induced by the lateral redistribution of auxin. Both the mutation of SAUR19 subfamily genes and the ectopic expression of SAUR19 weaken these tropic responses, indicating the critical role of their asymmetric expression. The auxin-responsive transcription factor ARF7 may directly bind the SAUR19 promoter and activate SAUR19 expression asymmetrically in tropic responses. Taken together, our results reveal that a gravity- or light-triggered asymmetric auxin distribution induces the asymmetric expression of SAUR19 subfamily genes by ARF7 and ARF19 in the hypocotyls, which leads to bending growth during gravitropic and phototropic responses.

Genome-wide selection and genetic improvement during modern maize breeding.

Since the development of single-hybrid maize breeding programs in the first half of the twentieth century1, maize yields have increased over sevenfold, and much of that increase can be attributed to tolerance of increased planting density2-4. To explore the genomic basis underlying the dramatic yield increase in maize, we conducted a comprehensive analysis of the genomic and phenotypic changes associated with modern maize breeding through chronological sampling of 350 elite inbred lines representing multiple eras of germplasm from both China and the United States. We document several convergent phenotypic changes in both countries. Using genome-wide association and selection scan methods, we identify 160 loci underlying adaptive agronomic phenotypes and more than 1,800 genomic regions representing the targets of selection during modern breeding. This work demonstrates the use of the breeding-era approach for identifying breeding signatures and lays the foundation for future genomics-enabled maize breeding.

Genome-wide study of an elite rice pedigree reveals a complex history of genetic architecture for breeding improvement.

Improving breeding has been widely utilized in crop breeding and contributed to yield and quality improvement, yet few researches have been done to analyze genetic architecture underlying breeding improvement comprehensively. Here, we collected genotype and phenotype data of 99 cultivars from the complete pedigree including Huanghuazhan, an elite, high-quality, conventional indica rice that has been grown over 4.5 million hectares in southern China and from which more than 20 excellent cultivars have been derived. We identified 1,313 selective sweeps (SSWs) revealing four stage-specific selection patterns corresponding to improvement preference during 65 years, and 1113 conserved Huanghuazhan traceable blocks (cHTBs) introduced from different donors and conserved in >3 breeding generations were the core genomic regions for superior performance of Huanghuazhan. Based on 151 quantitative trait loci (QTLs) identified for 13 improved traits in the pedigree, we reproduced their improvement process in silico, highlighting improving breeding works well for traits controlled by major/major + minor effect QTLs, but was inefficient for traits controlled by QTLs with complex interactions or explaining low levels of phenotypic variation. These results indicate long-term breeding improvement is efficient to construct superior genetic architecture for elite performance, yet molecular breeding with designed genotype of QTLs can facilitate complex traits improvement.

Genetic mapping of a QTL controlling source-sink size and heading date in rice.

Source size, sink size and heading date (HD) are three important classes of traits that determine the productivity of rice. In this study, a set of recombinant inbred lines (RILs) derived from the cross between an elite indica line Big Grain1 (BG1) and a japonica line Xiaolijing (XLJ) were used to map quantitative trait loci (QTLs) for source-sink size and heading date. Totally, thirty-one QTLs for source size, twenty-two for sink size, four for heading date and seven QTL clusters which included QTLs for multiple traits were identified in three environmental trials. Thirty QTLs could be consistently detected in at least two trials and generally located in the clusters. Using a set of BC4F2 lines, the QTL cluster in C5-1-C5-2 on chromosome 5 was validated to be a major QTL pleiotropically affecting heading date, source size (flag leaf area) and panicle type (neck length of panicle, primary branching number and the ratio of secondary branching number to primary branching number), and was narrowed down to a 309.52Kb region. QTL clusters described above have a large effect on source-sink size and/or heading date, therefore they should be good resources to improve the adaptability and high yield potential of cultivars genetically.

Identification of transcriptome SNPs for assessing allele-specific gene expression in a super-hybrid rice Xieyou9308.

Hybridization, a common process in nature, can give rise to a vast reservoir of allelic variants. Combination of these allelic variants may result in novel patterns of gene action and is thought to contribute to heterosis. In this study, we analyzed genome-wide allele-specific gene expression (ASGE) in the super-hybrid rice variety Xieyou9308 using RNA sequencing technology (RNA-Seq). We identified 9325 reliable single nucleotide polymorphisms (SNPs) distributed throughout the genome. Nearly 68% of the identified polymorphisms were CT and GA SNPs between R9308 and Xieqingzao B, suggesting the existence of DNA methylation, a heritable epigenetic mark, in the parents and their F1 hybrid. Of 2793 identified transcripts with consistent allelic biases, only 480 (17%) showed significant allelic biases during tillering and/or heading stages, implying that trans effects may mediate most transcriptional differences in hybrid offspring. Approximately 67% and 62% of the 480 transcripts showed R9308 allelic expression biases at tillering and heading stages, respectively. Transcripts with higher levels of gene expression in R9308 also exhibited R9308 allelic biases in the hybrid. In addition, 125 transcripts were identified with significant allelic expression biases at both stages, of which 74% showed R9308 allelic expression biases. R9308 alleles may tend to preserve their characteristic states of activity in the hybrid and may play important roles in hybrid vigor at both stages. The allelic expression of 355 transcripts was highly stage-specific, with divergent allelic expression patterns observed at different developmental stages. Many transcripts associated with stress resistance were differently regulated in the F1 hybrid. The results of this study may provide valuable insights into molecular mechanisms of heterosis.