The application of MARCO for immune regulation and treatment.

Macrophage receptor with collagen structure (MARCO) is a member of scavenger receptor class A (SR-A) and shares structural and functional similarities with SR-A1. In recent years, many studies have shown that MARCO can trigger an immune response and has therapeutic potential as a target for immunotherapy. Studies have shown that alterations in MARCO expression following pathogen infection cause changes in the functions of innate and adaptive immune cells, including macrophages, dendritic cells, B cells, and T cells, affecting the body's immune response to invading pathogens; thus, MARCO plays a crucial role in triggering the immune response, bridging innate and adaptive immunity, and eliminating pathogens. This paper is a comprehensive summary of the recent research on MARCO. This review focuses on the multiple functions of MARCO, including adhesion, migration, phagocytosis, and cytokine secretion with special emphasis on the complex interactions between MARCO and various types of cells involved in the immune response, as well as possible immune-related mechanisms. In summary, in this review, we discuss the structure and function of MARCO and its role in the immune response and highlight the therapeutic potential of MARCO as a target for immunotherapy. We hope that this review provides a theoretical basis for future research on MARCO.

A comprehensive method for controlling the electrical runout of the rotor for a geared centrifugal compressor.

The internal high-speed geared rotor is the most important component of centrifugal compressors. The electrical runout error of the rotor including mechanical and electrical ones can greatly affect the working performances of the centrifugal compressors. To overcome this problem, this work proposes a practical comprehensive method for controlling the electrical runout of the rotor of a geared centrifugal compressor. An elastic-plastic deformation calculation method based on the slice approach is presented to determine the applied load range calculation for controlling the cross-sectional deviation of the rotor profile. In this method, the demagnetism and remanence detection should be provided to obtain a small residual magnetism value before the mechanical runout detection. A combined method including cold extrusion processing and slight impact processing is proposed to reduce the electrical runout of the rotor. A case study is carried out to validate the proposed method. To avoid the effect of the rotation precision and clearance of the support system on the detection results, a rigid support system is used to detect the mechanical runout of the rotor. Note that single cold extrusion or impact processing cannot completely eliminate the electrical runout. Finally, the results show that the proposed combined method can be a helpful approach in controlling the electrical runout of the rotors.

Genome-wide identification of microsatellite markers from cultivated peanut (Arachis hypogaea L.).

BACKGROUND: Microsatellites, or simple sequence repeats (SSRs), represent important DNA variations that are widely distributed across the entire plant genome and can be used to develop SSR markers, which can then be used to conduct genetic analyses and molecular breeding. Cultivated peanut (A. hypogaea L.), an important oil crop worldwide, is an allotetraploid (AABB, 2n = 4× = 40) plant species. Because of its complex genome, genomic marker development has been very challenging. However, sequencing of cultivated peanut genome allowed us to develop genomic markers and construct a high-density physical map. RESULTS: A total of 8,329,496 SSRs were identified, including 3,772,653, 4,414,961, and 141,882 SSRs that were distributed in subgenome A, B, and nine scaffolds, respectively. Based on the flanking sequences of the identified SSRs, a total of 973,984 newly developed SSR markers were developed in subgenome A (462,267), B (489,394), and nine scaffolds (22,323), with an average density of 392.45 markers per Mb. In silico PCR evaluation showed that an average of 88.32% of the SSR markers generated only one in silico-specific product in two tetraploid A. hypogaea varieties, Tifrunner and Shitouqi. A total of 39,599 common SSR markers were identified among the two A. hypogaea varieties and two progenitors, A. duranensis and A. ipaensis. Additionally, an amplification effectiveness of 44.15% was observed by real PCR validation. Moreover, a total of 1276 public SSR loci were integrated with the newly developed SSR markers. Finally, a previously known leaf spot quantitative trait locus (QTL), qLLS_T13_A05_7, was determined to be in a 1.448-Mb region on chromosome A05. In this region, a total of 819 newly developed SSR markers were located and 108 candidate genes were detected. CONCLUSIONS: The availability of these newly developed and public SSR markers both provide a large number of molecular markers that could potentially be used to enhance the process of trait genetic analyses and improve molecular breeding strategies for cultivated peanut.

Sequencing of Cultivated Peanut, Arachis hypogaea, Yields Insights into Genome Evolution and Oil Improvement.

Cultivated peanut (Arachis hypogaea) is an allotetraploid crop planted in Asia, Africa, and America for edible oil and protein. To explore the origins and consequences of tetraploidy, we sequenced the allotetraploid A. hypogaea genome and compared it with the related diploid Arachis duranensis and Arachis ipaensis genomes. We annotated 39 888 A-subgenome genes and 41 526 B-subgenome genes in allotetraploid peanut. The A. hypogaea subgenomes have evolved asymmetrically, with the B subgenome resembling the ancestral state and the A subgenome undergoing more gene disruption, loss, conversion, and transposable element proliferation, and having reduced gene expression during seed development despite lacking genome-wide expression dominance. Genomic and transcriptomic analyses identified more than 2 500 oil metabolism-related genes and revealed that most of them show altered expression early in seed development while their expression ceases during desiccation, presenting a comprehensive map of peanut lipid biosynthesis. The availability of these genomic resources will facilitate a better understanding of the complex genome architecture, agronomically and economically important genes, and genetic improvement of peanut.

Consensus map integration and QTL meta-analysis narrowed a locus for yield traits to 0.7 cM and refined a region for late leaf spot resistance traits to 0.38 cM on linkage group A05 in peanut (Arachis hypogaea L.).

BACKGROUND: Many large-effect quantitative trait loci (QTLs) for yield and disease resistance related traits have been identified in different mapping populations of peanut (Arachis hypogaea L.) under multiple environments. However, only a limited number of QTLs have been used in marker-assisted selection (MAS) because of unfavorable epistatic interactions between QTLs in different genetic backgrounds. Thus, it is essential to identify consensus QTLs across different environments and genetic backgrounds for use in MAS. Here, we used QTL meta-analysis to identify a set of consensus QTLs for yield and disease resistance related traits in peanut. RESULTS: A new integrated consensus genetic map with 5874 loci was constructed. The map comprised 20 linkage groups (LGs) and was up to a total length of 2918.62 cM with average marker density of 2.01 loci per centimorgan (cM). A total of 292 initial QTLs were projected on the new consensus map, and 40 meta-QTLs (MQTLs) for yield and disease resistance related traits were detected on four LGs. The genetic intervals of these consensus MQTLs varied from 0.20 cM to 7.4 cM, which is narrower than the genetic intervals of the initial QTLs, meaning they may be suitable for use in MAS. Importantly, a region of the map that previously co-localized multiple major QTLs for pod traits was narrowed from 3.7 cM to 0.7 cM using an overlap region of four MQTLs for yield related traits on LG A05, which corresponds to a physical region of about 630.3 kb on the A05 pseudomolecule of peanut, including 38 annotated candidate genes (54 transcripts) related to catalytic activity and metabolic process. Additionally, one major MQTL for late leaf spot (LLS) was identified in a region of about 0.38 cM. BLAST searches identified 26 candidate genes (30 different transcripts) in this region, some of which were annotated as related to regulation of disease resistance in different plant species. CONCLUSIONS: Combined with the high-density marker consensus map, all the detected MQTLs could be useful in MAS. The biological functions of the 64 candidate genes should be validated to unravel the molecular mechanisms of yield and disease resistance in peanut.

Corrigendum: Genome Sequencing and Analysis of the Peanut B-Genome Progenitor (Arachis ipaensis).

[This corrects the article DOI: 10.3389/fpls.2018.00604.].

Genome Sequencing and Analysis of the Peanut B-Genome Progenitor (Arachis ipaensis).

Peanut (Arachis hypogaea L.), an important leguminous crop, is widely cultivated in tropical and subtropical regions. Peanut is an allotetraploid, having A and B subgenomes that maybe have originated in its diploid progenitors Arachis duranensis (A-genome) and Arachis ipaensis (B-genome), respectively. We previously sequenced the former and here present the draft genome of the latter, expanding our knowledge of the unique biology of Arachis. The assembled genome of A. ipaensis is ~1.39 Gb with 39,704 predicted protein-encoding genes. A gene family analysis revealed that the FAR1 family may be involved in regulating peanut special fruit development. Genomic evolutionary analyses estimated that the two progenitors diverged ~3.3 million years ago and suggested that A. ipaensis experienced a whole-genome duplication event after the divergence of Glycine max. We identified a set of disease resistance-related genes and candidate genes for biological nitrogen fixation. In particular, two and four homologous genes that may be involved in the regulation of nodule development were obtained from A. ipaensis and A. duranensis, respectively. We outline a comprehensive network involved in drought adaptation. Additionally, we analyzed the metabolic pathways involved in oil biosynthesis and found genes related to fatty acid and triacylglycerol synthesis. Importantly, three new FAD2 homologous genes were identified from A. ipaensis and one was completely homologous at the amino acid level with FAD2 from A. hypogaea. The availability of the A. ipaensis and A. duranensis genomic assemblies will advance our knowledge of the peanut genome.

Draft genome of the peanut A-genome progenitor (Arachis duranensis) provides insights into geocarpy, oil biosynthesis, and allergens.

Peanut or groundnut (Arachis hypogaea L.), a legume of South American origin, has high seed oil content (45-56%) and is a staple crop in semiarid tropical and subtropical regions, partially because of drought tolerance conferred by its geocarpic reproductive strategy. We present a draft genome of the peanut A-genome progenitor, Arachis duranensis, and 50,324 protein-coding gene models. Patterns of gene duplication suggest the peanut lineage has been affected by at least three polyploidizations since the origin of eudicots. Resequencing of synthetic Arachis tetraploids reveals extensive gene conversion in only three seed-to-seed generations since their formation by human hands, indicating that this process begins virtually immediately following polyploid formation. Expansion of some specific gene families suggests roles in the unusual subterranean fructification of Arachis For example, the S1Fa-like transcription factor family has 126 Arachis members, in contrast to no more than five members in other examined plant species, and is more highly expressed in roots and etiolated seedlings than green leaves. The A. duranensis genome provides a major source of candidate genes for fructification, oil biosynthesis, and allergens, expanding knowledge of understudied areas of plant biology and human health impacts of plants, informing peanut genetic improvement and aiding deeper sequencing of Arachis diversity.

Transcriptome-wide sequencing provides insights into geocarpy in peanut (Arachis hypogaea L.).

A characteristic feature of peanut is the subterranean fructification, geocarpy, in which the gynophore ('peg'), a specialized organ that transitions from upward growth habit to downward outgrowth upon fertilization, drives the developing pod into the soil for subsequent development underground. As a step towards understanding this phenomenon, we explore the developmental dynamics of the peanut pod transcriptome at 11 successive stages. We identified 110 217 transcripts across developmental stages and quantified their abundance along a pod developmental gradient in pod wall. We found that the majority of transcripts were differentially expressed along the developmental gradient as well as identified temporal programs of gene expression, including hundreds of transcription factors. Thought to be an adaptation to particularly harsh subterranean environments, both up- and down-regulated gene sets in pod wall were enriched for response to a broad array of stimuli, like gravity, light and subterranean environmental factors. We also identified hundreds of transcripts associated with gravitropism and photomorphogenesis, which may be involved in the geocarpy. Collectively, this study forms a transcriptional baseline for geocarpy in peanut as well as provides a considerable body of evidence that transcriptional regulation in peanut aerial and subterranean fruits is complex.

Deep sequencing analysis of the transcriptomes of peanut aerial and subterranean young pods identifies candidate genes related to early embryo abortion.

The failure of peg penetration into the soil leads to seed abortion in peanut. Knowledge of genes involved in these processes is comparatively deficient. Here, we used RNA-seq to gain insights into transcriptomes of aerial and subterranean pods. More than 2 million transcript reads with an average length of 396 bp were generated from one aerial (AP) and two subterranean (SP1 and SP2) pod libraries using pyrosequencing technology. After assembly, sets of 49 632, 49 952 and 50 494 from a total of 74 974 transcript assembly contigs (TACs) were identified in AP, SP1 and SP2, respectively. A clear linear relationship in the gene expression level was observed between these data sets. In brief, 2194 differentially expressed TACs with a 99.0% true-positive rate were identified, among which 859 and 1068 TACs were up-regulated in aerial and subterranean pods, respectively. Functional analysis showed that putative function based on similarity with proteins catalogued in UniProt and gene ontology term classification could be determined for 59 342 (79.2%) and 42 955 (57.3%) TACs, respectively. A total of 2968 TACs were mapped to 174 KEGG pathways, of which 168 were shared by aerial and subterranean transcriptomes. TACs involved in photosynthesis were significantly up-regulated and enriched in the aerial pod. In addition, two senescence-associated genes were identified as significantly up-regulated in the aerial pod, which potentially contribute to embryo abortion in aerial pods, and in turn, to cessation of swelling. The data set generated in this study provides evidence for some functional genes as robust candidates underlying aerial and subterranean pod development and contributes to an elucidation of the evolutionary implications resulting from fruit development under light and dark conditions.

A SSR-based composite genetic linkage map for the cultivated peanut (Arachis hypogaea L.) genome.

BACKGROUND: The construction of genetic linkage maps for cultivated peanut (Arachis hypogaea L.) has and continues to be an important research goal to facilitate quantitative trait locus (QTL) analysis and gene tagging for use in a marker-assisted selection in breeding. Even though a few maps have been developed, they were constructed using diploid or interspecific tetraploid populations. The most recently published intra-specific map was constructed from the cross of cultivated peanuts, in which only 135 simple sequence repeat (SSR) markers were sparsely populated in 22 linkage groups. The more detailed linkage map with sufficient markers is necessary to be feasible for QTL identification and marker-assisted selection. The objective of this study was to construct a genetic linkage map of cultivated peanut using simple sequence repeat (SSR) markers derived primarily from peanut genomic sequences, expressed sequence tags (ESTs), and by "data mining" sequences released in GenBank. RESULTS: Three recombinant inbred lines (RILs) populations were constructed from three crosses with one common female parental line Yueyou 13, a high yielding Spanish market type. The four parents were screened with 1044 primer pairs designed to amplify SSRs and 901 primer pairs produced clear PCR products. Of the 901 primer pairs, 146, 124 and 64 primer pairs (markers) were polymorphic in these populations, respectively, and used in genotyping these RIL populations. Individual linkage maps were constructed from each of the three populations and a composite map based on 93 common loci were created using JoinMap. The composite linkage maps consist of 22 composite linkage groups (LG) with 175 SSR markers (including 47 SSRs on the published AA genome maps), representing the 20 chromosomes of A. hypogaea. The total composite map length is 885.4 cM, with an average marker density of 5.8 cM. Segregation distortion in the 3 populations was 23.0%, 13.5% and 7.8% of the markers, respectively. These distorted loci tended to cluster on LG1, LG3, LG4 and LG5. There were only 15 EST-SSR markers mapped due to low polymorphism. By comparison, there were potential synteny, collinear order of some markers and conservation of collinear linkage groups among the maps and with the AA genome but not fully conservative. CONCLUSION: A composite linkage map was constructed from three individual mapping populations with 175 SSR markers in 22 composite linkage groups. This composite genetic linkage map is among the first "true" tetraploid peanut maps produced. This map also consists of 47 SSRs that have been used in the published AA genome maps, and could be used in comparative mapping studies. The primers described in this study are PCR-based markers, which are easy to share for genetic mapping in peanuts. All 1044 primer pairs are provided as additional files and the three RIL populations will be made available to public upon request for quantitative trait loci (QTL) analysis and linkage map improvement.

Utility of EST-derived SSR in cultivated peanut (Arachis hypogaea L.) and Arachis wild species.

BACKGROUND: Lack of sufficient molecular markers hinders current genetic research in peanuts (Arachis hypogaea L.). It is necessary to develop more molecular markers for potential use in peanut genetic research. With the development of peanut EST projects, a vast amount of available EST sequence data has been generated. These data offered an opportunity to identify SSR in ESTs by data mining. RESULTS: In this study, we investigated 24,238 ESTs for the identification and development of SSR markers. In total, 881 SSRs were identified from 780 SSR-containing unique ESTs. On an average, one SSR was found per 7.3 kb of EST sequence with tri-nucleotide motifs (63.9%) being the most abundant followed by di- (32.7%), tetra- (1.7%), hexa- (1.0%) and penta-nucleotide (0.7%) repeat types. The top six motifs included AG/TC (27.7%), AAG/TTC (17.4%), AAT/TTA (11.9%), ACC/TGG (7.72%), ACT/TGA (7.26%) and AT/TA (6.3%). Based on the 780 SSR-containing ESTs, a total of 290 primer pairs were successfully designed and used for validation of the amplification and assessment of the polymorphism among 22 genotypes of cultivated peanuts and 16 accessions of wild species. The results showed that 251 primer pairs yielded amplification products, of which 26 and 221 primer pairs exhibited polymorphism among the cultivated and wild species examined, respectively. Two to four alleles were found in cultivated peanuts, while 3-8 alleles presented in wild species. The apparent broad polymorphism was further confirmed by cloning and sequencing of amplified alleles. Sequence analysis of selected amplified alleles revealed that allelic diversity could be attributed mainly to differences in repeat type and length in the microsatellite regions. In addition, a few single base mutations were observed in the microsatellite flanking regions. CONCLUSION: This study gives an insight into the frequency, type and distribution of peanut EST-SSRs and demonstrates successful development of EST-SSR markers in cultivated peanut. These EST-SSR markers could enrich the current resource of molecular markers for the peanut community and would be useful for qualitative and quantitative trait mapping, marker-assisted selection, and genetic diversity studies in cultivated peanut as well as related Arachis species. All of the 251 working primer pairs with names, motifs, repeat types, primer sequences, and alleles tested in cultivated and wild species are listed in Additional File 1.