In Situ Constructing of Rigid-Soft Coupling Solid-Electrolyte Interphase on Silicon Electrode toward High-Performance Lithium Ion Batteries.

The application of Si anodes is hindered by some critical issues such as large volume changes of bare Si and fragile solid-electrolyte interface (SEI), resulting in low coulombic efficiency and rapid capacity decay. Herein, a multifunctional SEI film with high content of LiF is in situ constructed via the surface grafting of carbon-fluorine functionalized groups on silicon nanoparticles (SiNPs) during cycling. Mechanical study demonstrates that the incorporation of LiF with high modulus and unbroken carbon-fluorine groups with highly elastic guarantee the rigid-soft coupling SEI film on Si electrode. Furthermore, it is demonstrated that the rigid-soft coupling SEI film can effectively accommodate the volume expansion of Si nanoparticles during lithiation process, with the electrode expanding rate of only 114.16% after 100 cycles (263.87% for bare Si without surface modification). Afterward, with the aid of well-designed rigid-soft coupling SEI, the initial Coulomb efficiency of 89.8% is achieved, showing a reversible capacity of 1477 mAh g-1 after 200 cycles at 1.2 A g-1 . This work provides a simple and efficient solution that can potentially facilitate the practical application of Si anodes.

cis-Regulatory variation affecting gene expression contributes to the improvement of maize kernel size.

cis-Regulatory variations contribute to trait evolution and adaptation during crop domestication and improvement. As the most important harvested organ in maize (Zea mays L.), kernel size has undergone intensive selection for size. However, the associations between maize kernel size and cis-regulatory variations remain unclear. We chose two independent association populations to dissect the genetic architecture of maize kernel size together with transcriptomic and genotypic data. The resulting phenotypes reflected a strong influence of population structure on kernel size. Compared with genome-wide association studies (GWASs), which accounted for population structure and relatedness, GWAS based on a naïve or simple linear model revealed additional associated single-nucleotide polymorphisms significantly involved in the conserved pathways controlling seed size in plants. Regulation analyses through expression quantitative trait locus mapping revealed that cis-regulatory variations likely control kernel size by fine-tuning the expression of proximal genes, among which ZmKL1 (GRMZM2G098305) was transgenically validated. We also proved that the pyramiding of the favorable cis-regulatory variations has contributed to the improvement of maize kernel size. Collectively, our results demonstrate that cis-regulatory variations, together with their regulatory genes, provide excellent targets for future maize improvement.

Overexpression of ZmEXPA5 reduces anthesis-silking interval and increases grain yield under drought and well-watered conditions in maize.

Drought is one of the major abiotic stresses affecting the maize production worldwide. As a cross-pollination crop, maize is sensitive to water stress at flowering stage. Drought at this stage leads to asynchronous development of male and female flower organ and increased interval between anthesis and silking, which finally causes failure of pollination and grain yield loss. In the present study, the expansin gene ZmEXPA5 was cloned and its function in drought tolerance was characterized. An indel variant in promoter of ZmEXPA5 is significantly associated with natural variation in drought-induced anthesis-silking interval. The drought susceptible haplotypes showed lower expression level of ZmEXPA5 than tolerant haplotypes and lost the cis-regulatory activity of ZmDOF29. Increasing ZmEXPA5 expression in transgenic maize decreases anthesis-silking interval and improves grain yield under both drought and well-watered environments. In addition, the expression pattern of ZmEXPA5 was analyzed. These findings provide insights into the genetic basis of drought tolerance and a promising gene for drought improvement in maize breeding. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01432-x.

Ultrafast optical clearing method for three-dimensional imaging with cellular resolution.

Optical clearing is a versatile approach to improve imaging quality and depth of optical microscopy by reducing scattered light. However, conventional optical clearing methods are restricted in the efficiency-first applications due to unsatisfied time consumption, irreversible tissue deformation, and fluorescence quenching. Here, we developed an ultrafast optical clearing method (FOCM) with simple protocols and common reagents to overcome these limitations. The results show that FOCM can rapidly clarify 300-µm-thick brain slices within 2 min. Besides, the tissue linear expansion can be well controlled by only a 2.12% increase, meanwhile the fluorescence signals of GFP can be preserved up to 86% even after 11 d. By using FOCM, we successfully built the detailed 3D nerve cells model and showed the connection between neuron, astrocyte, and blood vessel. When applied to 3D imaging analysis, we found that the foot shock and morphine stimulation induced distinct c-fos pattern in the paraventricular nucleus of the hypothalamus (PVH). Therefore, FOCM has the potential to be a widely used sample mounting media for biological optical imaging.

Genetic Variation in ZmPAT7 Contributes to Tassel Branch Number in Maize.

Tassel branch number (TBN) is one of the important agronomic traits that contribute to the efficiency of seed production and has been selected strongly during the modern maize breeding process. However, the genetic mechanisms of TBN in maize are not entirely clear. In this study, we used a B73 × CML247 recombination inbred lines (RILs) population to detect quantitative trait loci (QTLs) for TBN. A total of four QTLs (qTBN2a, qTBN2b, qTBN4, and qTBN6) and six candidate genes were identified through expression analysis. Further, one of the candidates (GRMZM2G010011, ZmPAT7) encoding an S-acyltransferase was selected to validate its function by CRISPR-Cas9 technology, and its loss-of-function lines showed a significant increase in TBN. A key SNP(-101) variation in the promoter of ZmPAT7 was significantly associated with TBN. A total of 17 distant eQTLs associated with the expression of ZmPAT7 were identified in expression quantitative trait loci (eQTL) analysis, and ZmNAC3 may be a major factor involved in regulating ZmPAT7. These findings of the present study promote our understanding of the genetic basis of tassel architecture and provide new gene resources for maize breeding improvement.

Comparing the diagnostic accuracy of computed tomography vs transoesophageal echocardiography for infective endocarditis - A meta-analysis.

Objective: To investigate the comparative diagnostic accuracy of cardiac computed tomography (CT) and transoesophageal echocardiography (TEE) for detecting infective endocarditis. Methods: Original publications published in English language before July, 2021 were thoroughly search in PubMed, CENTRAL (Cochrane Central Register of Controlled Trials), and Google Scholar literature databases. Studies were included if they used CT and/or TEE as an index test, presented data on valvular complications related to infective endocarditis, and used surgical findings as to the reference standard. Results: Literature screening identified fifteen studies that fulfilled the inclusion criteria. Meta-analysis showed that CT sensitivity for detecting valvular abscesses was higher than that of TEE [0.88 (95% confidence interval [CI]: 0.82 to 0.94; 11 studies involving 842 subjects) versus 0.74 (95%CI: 0.65 to 0.84) P = 0.015; 12 studies involving 917 subjects]. TEE showed statistically significantly greater sensitivity than CT for detecting valvular vegetation [0.91 (95% CI: 0.84 to 0.97, 11 studies involving 971 subjects) versus 0.80 (95% CI: 0.69 to 0.82), 12 studies involving 915 subjects, P =0.019. In case of leaflet detection, TEE showed statistically significantly higher sensitivity than CT (0.76 vs 0.46, P =0.010). Conclusion: CT performs statistically significantly better than TEE for detecting abscesses while TEE provides statistically significant superior results for detecting vegetation. There is a need for well-designed prospective studies to further corroborate these findings.

Genome-wide association studies of leaf angle in maize.

Compact plant-type with small leaf angle has increased canopy light interception, which is conducive to the photosynthesis of the population and higher population yield at high density planting in maize. In this study, a panel of 285 diverse maize inbred lines genotyped with 56,000 SNPs was used to investigate the genetic basis of leaf angle across 3 consecutive years using a genome-wide association study (GWAS). The leaf angle showed broad phenotypic variation and high heritability across different years. Population structure analysis subdivided the panel into four subgroups that correspond to the four major empirical germplasm origins in China, i.e., Tangsipingtou, Reid, Lancaster and P. When tested with the optimal GWAS model, we found that the Q + K model was the best in reducing false positive. In total, 96 SNPs accounting for 5.54-10.44% of phenotypic variation were significantly (P < 0.0001) associated with leaf angle across three years. According to the linkage disequilibrium decay distance, 96 SNPs were binned into 43 QTLs for leaf angle. Seven major QTLs with R2 > 8% stably detected in at least 2 years, and BLUP values were clustered in four genomic regions (bins 2.01, 2.07, 5.06, and 10.04). Seven important candidate genes, Zm00001d001961, Zm00001d006348, Zm00001d006463, Zm00001d017618, Zm00001d024919, Zm00001d025018, and Zm00001d025033 were predicted for the seven stable major QTLs, respectively. The markers identified in this study can be used for molecular breeding for leaf angle, and the candidate genes would contribute to further understanding of the genetic basis of leaf angle. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01241-0.

The retromer protein ZmVPS29 regulates maize kernel morphology likely through an auxin-dependent process(es).

Kernel size and morphology are two important yield-determining traits in maize, but their molecular and genetic mechanisms are poorly characterized. Here, we identified a major QTL, qKM4.08, which explains approximately 24.20% of the kernel morphology variance in a recombinant population derived from two elite maize inbred lines, Huangzaosi (HZS, round kernel) and LV28 (slender kernel). Positional cloning and transgenic analysis revealed that qKM4.08 encodes ZmVPS29, a retromer complex component. Compared with the ZmVPS29 HZS allele, the ZmVPS29 LV28 allele showed higher expression in developing kernels. Overexpression of ZmVPS29 conferred a slender kernel morphology and increased the yield per plant in different maize genetic backgrounds. Sequence analysis revealed that ZmVPS29 has been under purifying selection during maize domestication. Association analyses identified two significant kernel morphology-associated polymorphic sites in the ZmVPS29 promoter region that were significantly enriched in modern maize breeding lines. Further study showed that ZmVPS29 increased auxin accumulation during early kernel development by enhancing auxin biosynthesis and transport and reducing auxin degradation and thereby improved kernel development. Our results suggest that ZmVPS29 regulates kernel morphology, most likely through an auxin-dependent process(es).

Candidate loci for the kernel row number in maize revealed by a combination of transcriptome analysis and regional association mapping.

BACKGROUND: The kernel row number (KRN) of an ear is an important trait related to yield and domestication in maize. Exploring the underlying genetic mechanisms of KRN has great research significance and application potential. RESULTS: In the present study, N531 with a KRN of 18-22 and SLN with a KRN of 4-6 were used as the recurrent parent and the donor parent, respectively, to develop two introgression lines (ILs), IL_A and IL_B, both of which have common negative-effect alleles from SLN on chromosomes 1, 5 and 10 and significantly reduced inflorescence meristem (IM) diameter and KRN compared with those of N531. We used RNA-Seq to investigate the transcriptome profiles of 5-mm immature ears of N531, IL_A and IL_B. We identified a total of 2872 differentially expressed genes (DEGs) between N531 and IL_A, 2428 DEGs between N531 and IL_B and 1811 DEGs between IL_A and IL_B. A total of 1252 DEGs were detected as overlapping DEGs, and 89 DEGs were located on the common introgression fragments. Furthermore, three DEGs (Zm00001d013277, Zm00001d015310 and Zm00001d015377) containing three SNPs associated with KRN were identified using regional association mapping. CONCLUSIONS: These results will facilitate our understanding of ear development and provide important candidate genes for further study on KRN.

Machine learning based adaptive optics for doughnut-shaped beam.

The doughnut-shaped beam has been widely applied in the field of super-resolution microscopic imaging, micro-nanostructure lithography, ultra-high-density storage, and laser trapping. However, how to maintain the doughnut-shaped focus inside the scattering medium becomes a challenge, due to the wavefront aberrations. Here we demonstrate a machine learning based adaptive optics method to recover the doughnut-shaped focus with high speed. In our method, the relationship between the distorted doughnut-shaped intensity point spread function and the coefficients of the first 15 Zernike modes for phase correction is established. Experimental results show that the wavefront aberration with 101,784 optical control elements can be predicted within ~17 ms even using a personal computer, and 97.5% correction accuracy can be achieved in 200 repeated tests. Besides, we successfully apply this method in the scanning microscopy theoretically. With a large number of optical control elements and fast operation speed, our method may pave the way for many important applications in bioimaging, such as deep tissue stimulated emission depletion (STED) microscopy.

Genetic architecture of phenotypic means and plasticities of kernel size and weight in maize.

KEY MESSAGE: Genetic relationships between the phenotypic means and plasticities of kernel size and weight revealed the common genetic control of these traits in maize. Kernel size and weight are crucial components of grain yield in maize, and phenotypic plasticity in these traits facilitates adaptations to changing environments. Elucidating the genetic architecture of the mean phenotypic values and plasticities of kernel size and weight may be essential for breeding climate-robust maize varieties. Here, a maize nested association mapping (CN-NAM) population and association panel were grown in different environments. A joint linkage analysis and genome-wide association mapping were performed for five kernel size and weight phenotypic traits and two phenotypic plasticity measures. The mean phenotypes and plasticities were significantly correlated. The overall results of quantitative trait locus (QTL) and candidate gene analyses indicated moderate and high levels of common genetic control for the two traits. Furthermore, the mean phenotypes or plasticities of the hundred-kernel weight and volume were commonly regulated to a high degree. One pleiotropic locus on chromosome 10 simultaneously controlled the mean phenotypic values and plasticities of kernel size and weight. Therefore, the plasticity of kernel size and weight might be indirectly selected during maize breeding; however, selecting for high or low plasticity in combination with high or low mean phenotypic values of kernel size and weight traits may be difficult.

Characterization and fine mapping of qkrnw4, a major QTL controlling kernel row number in maize.

KEY MESSAGE: A major QTL controlling kernel row number, qkrnw4, was identified by combining linkage analysis and association mapping. Within qkrnw4, on the basis of its expression and bioinformatics analysis, Zm00001d052910 was supposed to be the candidate gene for kernel row number. Kernel row number (KRN) is an important yield-related trait that affects kernel number in maize. Understanding the genetic basis of KRN is important for increasing maize yields. In the present study, by the use of a near-isogenic line (NIL) that has a B73 background and that consistently displays a low KRN across environments, qkrnw4, a major quantitative trait locus (QTL) associated with KRN within a yield trait-related QTL hotspot in bin 4.08, was finely mapped to an ~ 33-kb interval. Regional association analysis of a nested association mapping population comprising 5000 recombinant inbred lines revealed Zm00001d052910, which encodes a protein with an unknown function, as the important candidate gene responsible for qkrnw4. Different expression levels of this candidate gene in immature ears were detected between the NIL and its recurrent parent. Moreover, the expression of several auxin-related genes was consistent with that of the candidate gene. Furthermore, the potential associations of this candidate gene with well-known inflorescence-related genes were discussed. The results of this study provide important information for the genetic elucidation of KRN variation in maize.

Genome-wide analysis of the pentatricopeptide repeat gene family in different maize genomes and its important role in kernel development.

BACKGROUND: The pentatricopeptide repeat (PPR) gene family is one of the largest gene families in land plants (450 PPR genes in Arabidopsis, 477 PPR genes in rice and 486 PPR genes in foxtail millet) and is important for plant development and growth. Most PPR genes are encoded by plastid and mitochondrial genomes, and the gene products regulate the expression of the related genes in higher plants. However, the functions remain largely unknown, and systematic analysis and comparison of the PPR gene family in different maize genomes have not been performed. RESULTS: In this study, systematic identification and comparison of PPR genes from two elite maize inbred lines, B73 and PH207, were performed. A total of 491 and 456 PPR genes were identified in the B73 and PH207 genomes, respectively. Basic bioinformatics analyses, including of the classification, gene structure, chromosomal location and conserved motifs, were conducted. Examination of PPR gene duplication showed that 12 and 15 segmental duplication gene pairs exist in the B73 and PH207 genomes, respectively, with eight duplication events being shared between the two genomes. Expression analysis suggested that 53 PPR genes exhibit qualitative variations in the different genetic backgrounds. Based on analysis of the correlation between PPR gene expression in kernels and kernel-related traits, four PPR genes are significantly negatively correlated with hundred kernel weight, 12 are significantly negatively correlated with kernel width, and eight are significantly correlated with kernel number. Eight of the 24 PPR genes are also located in metaQTL regions associated with yield and kernel-related traits in maize. Two important PPR genes (GRMZM2G353195 and GRMZM2G141202) might be regarded as important candidate genes associated with maize kernel-related traits. CONCLUSIONS: Our results provide a more comprehensive understanding of PPR genes in different maize inbred lines and identify important candidate genes related to kernel development for subsequent functional validation in maize.

Characterization and fine mapping of qkc7.03: a major locus for kernel cracking in maize.

KEY MESSAGE: A major locus conferring kernel cracking in maize was characterized and fine mapped to an interval of 416.27 kb. Meanwhile, combining the results of transcriptomic analysis, the candidate gene was inferred. Seed development requires a proper structural and physiological balance between the maternal tissues and the internal structures of the seeds. In maize, kernel cracking is a disorder in this balance that seriously limits quality and yield and is characterized by a cracked pericarp at the kernel top and endosperm everting. This study elucidated the genetic basis and characterization of kernel cracking. Primarily, a near isogenic line (NIL) with a B73 background exhibited steady kernel cracking across environments. Therefore, deprived mapping populations were developed from this NIL and its recurrent parent B73. A major locus on chromosome 7, qkc7.03, was identified to be associated with the cracking performance. According to a progeny test of recombination events, qkc7.03 was fine mapped to a physical interval of 416.27 kb. In addition, obvious differences were observed in embryo development and starch granule arrangement within the endosperm between the NIL and its recurrent parent upon the occurrence of kernel cracking. Moreover, compared to its recurrent parent, the transcriptome of the NIL showed a significantly down-regulated expression of genes related to zeins, carbohydrate synthesis and MADS-domain transcription factors. The transcriptomic analysis revealed ten annotated genes within the target region of qkc7.03, and only GRMZM5G899476 was differently expressed between the NIL and its recurrent parent, indicating that this gene might be a candidate gene for kernel cracking. The results of this study facilitate the understanding of the potential mechanism underlying kernel cracking in maize.

Identification of genetic variants associated with maize flowering time using an extremely large multi-genetic background population.

Flowering time is one of the major adaptive traits in domestication of maize and an important selection criterion in breeding. To detect more maize flowering time variants we evaluated flowering time traits using an extremely large multi- genetic background population that contained more than 8000 lines under multiple Sino-United States environments. The population included two nested association mapping (NAM) panels and a natural association panel. Nearly 1 million single-nucleotide polymorphisms (SNPs) were used in the analyses. Through the parallel linkage analysis of the two NAM panels, both common and unique flowering time regions were detected. Genome wide, a total of 90 flowering time regions were identified. One-third of these regions were connected to traits associated with the environmental sensitivity of maize flowering time. The genome-wide association study of the three panels identified nearly 1000 flowering time-associated SNPs, mainly distributed around 220 candidate genes (within a distance of 1 Mb). Interestingly, two types of regions were significantly enriched for these associated SNPs - one was the candidate gene regions and the other was the approximately 5 kb regions away from the candidate genes. Moreover, the associated SNPs exhibited high accuracy for predicting flowering time.

Numerous genetic loci identified for drought tolerance in the maize nested association mapping populations.

BACKGROUND: Maize requires more water than most other crops; therefore, the water use efficiency of this crop must be improved for maize production under undesirable land and changing environmental conditions. RESULTS: To elucidate the genetic control of drought in maize, we evaluated approximately 5000 inbred lines from 30 linkage-association joint mapping populations under two contrasting water regimes for seven drought-related traits, including yield and anthesis-silking interval (ASI). The joint linkage analysis was conducted to identify 220 quantitative trait loci (QTLs) under well-watered conditions and 169 QTLs under water-stressed conditions. The genome-wide association analysis identified 365 single nucleotide polymorphisms (SNPs) associated with drought-related traits, and these SNPs were located in 354 candidate genes. Fifty-two of these genes showed significant differential expression in the inbred line B73 under the well-watered and water-stressed conditions. In addition, genomic predictions suggested that the moderate-density SNPs obtained through genotyping-by-sequencing were able to make accurate predictions in the nested association mapping population for drought-related traits with moderate-to-high heritability under the water-stressed conditions. CONCLUSIONS: The results of the present study provide important information that can be used to understand the genetic basis of drought stress responses and facilitate the use of beneficial alleles for the improvement of drought tolerance in maize.

Fine-mapping of qGW4.05, a major QTL for kernel weight and size in maize.

BACKGROUND: Kernel weight and size are important components of grain yield in cereals. Although some information is available concerning the map positions of quantitative trait loci (QTL) for kernel weight and size in maize, little is known about the molecular mechanisms of these QTLs. qGW4.05 is a major QTL that is associated with kernel weight and size in maize. We combined linkage analysis and association mapping to fine-map and identify candidate gene(s) at qGW4.05. RESULTS: QTL qGW4.05 was fine-mapped to a 279.6-kb interval in a segregating population derived from a cross of Huangzaosi with LV28. By combining the results of regional association mapping and linkage analysis, we identified GRMZM2G039934 as a candidate gene responsible for qGW4.05. Candidate gene-based association mapping was conducted using a panel of 184 inbred lines with variable kernel weights and kernel sizes. Six polymorphic sites in the gene GRMZM2G039934 were significantly associated with kernel weight and kernel size. CONCLUSION: The results of linkage analysis and association mapping revealed that GRMZM2G039934 is the most likely candidate gene for qGW4.05. These results will improve our understanding of the genetic architecture and molecular mechanisms underlying kernel development in maize.

Joint-linkage mapping and GWAS reveal extensive genetic loci that regulate male inflorescence size in maize.

Both insufficient and excessive male inflorescence size leads to a reduction in maize yield. Knowledge of the genetic architecture of male inflorescence is essential to achieve the optimum inflorescence size for maize breeding. In this study, we used approximately eight thousand inbreds, including both linkage populations and association populations, to dissect the genetic architecture of male inflorescence. The linkage populations include 25 families developed in the U.S. and 11 families developed in China. Each family contains approximately 200 recombinant inbred lines (RILs). The association populations include approximately 1000 diverse lines from the U.S. and China. All inbreds were genotyped by either sequencing or microarray. Inflorescence size was measured as the tassel primary branch number (TBN) and tassel length (TL). A total of 125 quantitative trait loci (QTLs) were identified (63 for TBN, 62 for TL) through linkage analyses. In addition, 965 quantitative trait nucleotides (QTNs) were identified through genomewide study (GWAS) at a bootstrap posterior probability (BPP) above a 5% threshold. These QTLs/QTNs include 24 known genes that were cloned using mutants, for example Ramosa3 (ra3), Thick tassel dwarf1 (td1), tasselseed2 (ts2), liguleless2 (lg2), ramosa1 (ra1), barren stalk1 (ba1), branch silkless1 (bd1) and tasselseed6 (ts6). The newly identified genes encode a zinc transporter (e.g. GRMZM5G838098 and GRMZM2G047762), the adapt in terminal region protein (e.g. GRMZM5G885628), O-methyl-transferase (e.g. GRMZM2G147491), helix-loop-helix (HLH) DNA-binding proteins (e.g. GRMZM2G414252 and GRMZM2G042895) and an SBP-box protein (e.g. GRMZM2G058588). These results provide extensive genetic information to dissect the genetic architecture of inflorescence size for the improvement of maize yield.

Analysis of recombination QTLs, segregation distortion, and epistasis for fitness in maize multiple populations using ultra-high-density markers.

KEY MESSAGE: Using two nested association mapping populations and high-density markers, some important genomic regions controlling recombination frequency and segregation distortion were detected. Understanding the maize genomic features would be useful for the study of genetic diversity and evolution and for maize breeding. Here, we used two maize nested association mapping (NAM) populations separately derived in China (CN-NAM) and the US (US-NAM) to explore the maize genomic features. The two populations containing 36 families and about 7000 recombinant inbred lines were evaluated with genotyping-by-sequencing. Through the comparison between the two NAMs, we revealed that segregation distortion is little, whereas epistasis for fitness is present in the two maize NAM populations. When conducting quantitative trait loci (QTL) mapping for the total number of recombination events, we detected 14 QTLs controlling recombination. Using high-density markers to identify segregation distortion regions (SDRs), a total of 445 SDRs were detected within the 36 families, among which 15 common SDRs were found in at least ten families. About 80 % of the known maize gametophytic factors (ga) genes controlling segregation distortion were overlapped with highly significant SDRs. In addition, we also found that the regions with high recombination rate and high gene density usually tended to have little segregation distortion. This study will facilitate population genetic studies and gene cloning affecting recombination variation and segregation distortion in maize, which can improve plant breeding progress.

Construction of high-quality recombination maps with low-coverage genomic sequencing for joint linkage analysis in maize.

BACKGROUND: A genome-wide association study (GWAS) is the foremost strategy used for finding genes that control human diseases and agriculturally important traits, but it often reports false positives. In contrast, its complementary method, linkage analysis, provides direct genetic confirmation, but with limited resolution. A joint approach, using multiple linkage populations, dramatically improves resolution and statistical power. For example, this approach has been used to confirm that many complex traits, such as flowering time controlling adaptation in maize, are controlled by multiple genes with small effects. In addition, genotyping by sequencing (GBS) at low coverage not only produces genotyping errors, but also results in large datasets, making the use of high-throughput sequencing technologies computationally inefficient or unfeasible. RESULTS: In this study, we converted raw SNPs into effective recombination bins. The reduced bins not only retain the original information, but also correct sequencing errors from low-coverage genomic sequencing. To further increase the statistical power and resolution, we merged a new temperate maize nested association mapping (NAM) population derived in China (CN-NAM) with the existing maize NAM population developed in the US (US-NAM). Together, the two populations contain 36 families and 7,000 recombinant inbred lines (RILs). One million SNPs were generated for all the RILs with GBS at low coverage. We developed high-quality recombination maps for each NAM population to correct genotyping errors and improve the computational efficiency of the joint linkage analysis. The original one million SNPs were reduced to 4,932 and 5,296 recombination bins with average interval distances of 0.34 cM and 0.28 cM for CN-NAM and US-NAM, respectively. The quantitative trait locus (QTL) mapping for flowering time (days to tasseling) indicated that the high-density, recombination bin map improved resolution of QTL mapping by 50 % compared with that using a medium-density map. We also demonstrated that combining the CN-NAM and US-NAM populations improves the power to detect QTL by 50 % compared to single NAM population mapping. Among the QTLs mapped by joint usage of the US-NAM and CN-NAM maps, 25 % of the QTLs overlapped with known flowering-time genes in maize. CONCLUSION: This study provides directions and resources for the research community, especially maize researchers, for future studies using the recombination bin strategy for joint linkage analysis. Available resources include efficient usage of low-coverage genomic sequencing, detailed positions for genes controlling maize flowering, and recombination bin maps and flowering- time data for both CN and US NAMs. Maize researchers even have the opportunity to grow both CN and US NAM populations to study the traits of their interest, as the seeds of both NAM populations are available from the seed repository in China and the US.