Genomic investigation of 18,421 lines reveals the genetic architecture of rice.

Understanding how numerous quantitative trait loci (QTL) shape phenotypic variation is an important question in genetics. To address this, we established a permanent population of 18,421 (18K) rice lines with reduced population structure. We generated reference-level genome assemblies of the founders and genotyped all 18K-rice lines through whole-genome sequencing. Through high-resolution mapping, 96 high-quality candidate genes contributing to variation in 16 traits were identified, including OsMADS22 and OsFTL1 verified as causal genes for panicle number and heading date, respectively. We identified epistatic QTL pairs and constructed a genetic interaction network with 19 genes serving as hubs. Overall, 170 masking epistasis pairs were characterized, serving as an important factor contributing to genetic background effects across diverse varieties. The work provides a basis to guide grain yield and quality improvements in rice.

Dissecting the Genetic Architecture of Morphological Traits in Sunflower (Helianthus annuus L.).

The sunflower (Helianthus annuus L.) is one of the most essential oil crops in the world. Several component traits, including flowering time, plant height, stem diameter, seed weight, and kernel weight, determine sunflower seed and oil yield. Although the genetic mechanisms governing the variation of these yield-related traits have been studied using various approaches, genome-wide association studies (GWAS) have not been widely applied to sunflowers. In this study, a set of 342 sunflower accessions was evaluated in 2019 and 2020 using an incomplete randomized block design, and GWAS was conducted utilizing two complementary approaches: the mixed linear model (MLM) and the fixed and random model circulating probability unification (farmCPU) model by fitting 226,779 high-quality SNPs. As a result, GWAS identified a number of trait-associated SNPs. Those SNPs were located close to several genes that may serve as a basis for further molecular characterization and provide promising targets for sunflower yield improvement.

Functional Study of cAMP-Dependent Protein Kinase A in Penicillium oxalicum.

Signaling pathways play a crucial role in regulating cellulase production. The pathway mediated by signaling proteins plays a crucial role in understanding how cellulase expression is regulated. In this study, using affinity purification of ClrB, we have identified sixteen proteins that potentially interact with ClrB. One of the proteins, the catalytic subunit of cAMP-dependent protein kinase A (PoPKA-C), is an important component of the cAMP/PKA signaling pathway. Knocking out PoPKA-C resulted in significant decreases in the growth, glucose utilization, and cellulose hydrolysis ability of the mutant strain. Furthermore, the cellulase activity and gene transcription levels were significantly reduced in the ΔPoPKA-C mutant, while the expression activity of CreA, a transcriptional regulator of carbon metabolism repression, was notably increased. Additionally, deletion of PoPKA-C also led to earlier timing of conidia production. The expression levels of key transcription factor genes stuA and brlA, which are involved in the production of the conidia, showed significant enhancement in the ΔPoPKA-C mutant. These findings highlight the involvement of PoPKA-C in mycelial development, conidiation, and the regulation of cellulase expression. The functional analysis of PoPKA-C provides insights into the mechanism of the cAMP/PKA signaling pathway in cellulase expression in filamentous fungi and has significant implications for the development of high-yielding cellulase strains.

Unraveling Prevalence and Effects of Deleterious Mutations in Maize Elite Lines across Decades of Modern Breeding.

Future breeding is likely to involve the detection and removal of deleterious alleles, which are mutations that negatively affect crop fitness. However, little is known about the prevalence of such mutations and their effects on phenotypic traits in the context of modern crop breeding. To address this, we examined the number and frequency of deleterious mutations in 350 elite maize inbred lines developed over the past few decades in China and the United States. Our findings reveal an accumulation of weakly deleterious mutations and a decrease in strongly deleterious mutations, indicating the dominant effects of genetic drift and purifying selection for the two types of mutations, respectively. We also discovered that slightly deleterious mutations, when at lower frequencies, were more likely to be heterozygous in the developed hybrids. This is consistent with complementation as a potential explanation for heterosis. Subsequently, we found that deleterious mutations accounted for more of the variation in phenotypic traits than nondeleterious mutations with matched minor allele frequencies, especially for traits related to leaf angle and flowering time. Moreover, we detected fewer deleterious mutations in the promoter and gene body regions of differentially expressed genes across breeding eras than in nondifferentially expressed genes. Overall, our results provide a comprehensive assessment of the prevalence and impact of deleterious mutations in modern maize breeding and establish a useful baseline for future maize improvement efforts.

Phosducin-like protein PoPlp1 impacts cellulase and amylase expression and development in Penicillium oxalicum via the G protein-cAMP signaling pathway.

In this study, a phosducin-like protein, PoPlp1, was identified and functionally studied in the cellulase-producing strain Penicillium oxalicum 114-2. PoPlp1 was proven to participate in several biological processes, including mycelium development, conidiation, and expression of cellulases and amylases. With deletion of Poplp1, morphology and development varied significantly in ΔPoplp1. Colony growth, glucose utilization, and the hydrolysis capability of starch and cellulose were limited, whereas conidiation was enhanced. Based on detection of the levels of expression of transcription factors involved in asexual development, we conjectured that PoPlp1 is involved in conidiation via the major factor BrlA. We explored the effect of PoPlp1 on cellulase and amylase expression and observed that cellulase and amylase activity and major gene transcription levels were all dramatically reduced in ΔPoplp1. Deletion of PoPlp1 caused a decrease in intracellular cAMP levels, and the cellulase gene expression level of ΔPoplp1 was restored to a certain extent through external addition of cAMP. These findings demonstrate that PoPlp1 may affect cellulase and amylase expression by regulating cAMP concentration. To comprehensively explore the mechanism of PoPlp1 in regulating multiple biological processes, we performed a comparative transcriptomic analysis between strains P. oxalicum 114-2 and ΔPoplp1. The major cellulase and amylase genes were all downregulated, congrent with the results of real-time quantitative polymerase chain reaction analysis. The genes involved in the G protein-cAMP signaling pathway, including several G-protein-coupled receptors, one regulator of G protein signaling, and two cAMP phosphodiesterases, were disrupted by deletion of PoPlp1. These results confirm the positive function of PoPlp1 in the G protein-cAMP signaling pathway. This functional analysis of PoPlp1 will be very beneficial for further study of the regulatory mechanisms of cellulase expression and other biological processes in P. oxalicum 114-2 via the G protein-cAMP signaling pathway.

A Real-Time Registration Algorithm of UAV Aerial Images Based on Feature Matching.

This study aimed to achieve the accurate and real-time geographic positioning of UAV aerial image targets. We verified a method of registering UAV camera images on a map (with the geographic location) through feature matching. The UAV is usually in rapid motion and involves changes in the camera head, and the map is high-resolution and has sparse features. These reasons make it difficult for the current feature-matching algorithm to accurately register the two (camera image and map) in real time, meaning that there will be a large number of mismatches. To solve this problem, we used the SuperGlue algorithm, which has a better performance, to match the features. The layer and block strategy, combined with the prior data of the UAV, was introduced to improve the accuracy and speed of feature matching, and the matching information obtained between frames was introduced to solve the problem of uneven registration. Here, we propose the concept of updating map features with UAV image features to enhance the robustness and applicability of UAV aerial image and map registration. After numerous experiments, it was proved that the proposed method is feasible and can adapt to the changes in the camera head, environment, etc. The UAV aerial image is stably and accurately registered on the map, and the frame rate reaches 12 frames per second, which provides a basis for the geo-positioning of UAV aerial image targets.

Estimating the genetic parameters of yield-related traits under different nitrogen conditions in maize.

Understanding the genetic basis responding to nitrogen (N) fertilization in crop production is a long-standing research topic in plant breeding and genetics. Albeit years of continuous efforts, the genetic architecture parameters, such as heritability, polygenicity, and mode of selection, underlying the N responses in maize remain largely unclear. In this study, about n = 230 maize inbred lines were phenotyped under high N (HN) and low N (LN) conditions for 2 consecutive years to obtain 6 yield-related traits. Heritability analyses suggested that traits highly responsive to N treatments were less heritable. Using publicly available SNP genotypes, the genome-wide association study (GWAS) was conducted to identify n = 237 and n = 130 trait-associated loci under HN and LN conditions, n = 164 for N-responsive (NR) traits, and n = 31 for genotype by N interaction (G × N). Furthermore, genome-wide complex trait Bayesian (GCTB) analysis, a method complementary to GWAS, was performed to estimate genetic parameters, including genetic polygenicity and the mode of selection (S). GCTB results suggested that the NR value of a yield component trait was highly polygenic and that 4 NR traits exhibited negative correlations between SNP effects and their minor allele frequencies (or the S value <0)-a pattern consistent with negative selection to purge deleterious alleles. This study reveals the complex genetic architecture underlying N responses for yield-related traits and provides candidate genetic loci for N resilient maize improvement.

A common resequencing-based genetic marker data set for global maize diversity.

Maize (Zea mays ssp. mays) populations exhibit vast ranges of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole-genome resequencing strategies, identifying millions of segregating single-nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here, we employ resequencing data from 1276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of approximately 366 million segregating variants and approximately 46 million high-confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering-time genes using previously published trait data sets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.

The Heterogeneity in the Landscape of Gene Dominance in Maize is Accompanied by Unique Chromatin Environments.

Subgenome dominance after whole-genome duplication (WGD) has been observed in many plant species. However, the degree to which the chromatin environment affects this bias has not been explored. Here, we compared the dominant subgenome (maize1) and the recessive subgenome (maize2) with respect to patterns of sequence substitutions, genes expression, transposable element accumulation, small interfering RNAs, DNA methylation, histone modifications, and accessible chromatin regions (ACRs). Our data show that the degree of bias between subgenomes for all the measured variables does not vary significantly when both of the WGD genes are located in pericentromeric regions. Our data further indicate that the location of maize1 genes in chromosomal arms is pivotal for maize1 to maintain its dominance, but location has a less effect on maize2 homoeologs. In addition to homoeologous genes, we compared ACRs, which often harbor cis-regulatory elements, between the two subgenomes and demonstrate that maize1 ACRs have a higher level of chromatin accessibility, a lower level of sequence substitution, and are enriched in chromosomal arms. Furthermore, we find that a loss of maize1 ACRs near their nearby genes is associated with a reduction in purifying selection and expression of maize1 genes relative to their maize2 homoeologs. Taken together, our data suggest that chromatin environment and cis-regulatory elements are important determinants shaping the divergence and evolution of duplicated genes.