Grain weight is one of the key components of wheat (Triticum aestivum L.) yield.  Genetic manipulation of grain weight is an efficient approach for improving yield potential in breeding programs.  A recombinant inbred line (RIL) population derived from a cross between W7268 and Chuanyu 12 (CY12) was employed to detect quantitative trait loci (QTLs) for thousand-grain weight (TGW), grain length (GL), grain width (GW), and the ratio of grain length to width (GLW) in six environments.  Seven major QTLs, QGl.cib-2D, QGw.cib-2D, QGw.cib-3B, QGw.cib-4B.1, QGlw.cib-2D.1, QTgw.cib-2D.1 and QTgw.cib-3B.1, were consistently identified in at least four environments and the best linear unbiased estimation (BLUE) datasets, and they explained 2.61 to 34.85% of the phenotypic variance.  Significant interactions were detected between the two major TGW QTLs and three major GW loci.  In addition, QTgw.cib-3B.1 and QGw.cib-3B were co-located, and the improved TGW at this locus was contributed by GW.  Unlike other loci, QTgw.cib-3B.1/QGw.cib-3B had no effect on grain number per spike (GNS).  They were further validated in advanced lines using Kompetitive Allele Specific PCR (KASP) markers, and a comparison analysis indicated that QTgw.cib-3B.1/QGw.cib-3B is likely a novel locus.  Six haplotypes were identified in the region of this QTL and their distribution frequencies varied between the landraces and cultivars.  According to gene annotation, spatial expression patterns, ortholog analysis and sequence variation, the candidate gene of QTgw.cib-3B.1/QGw.cib-3B was predicted.  Collectively, the major QTLs and KASP markers reported here provide valuable information for elucidating the genetic architecture of grain weight and for molecular marker-assisted breeding in grain yield improvement.

Chloroplast is a discrete, highly structured, and semi-autonomous cellular organelle. The small genome of chloroplast makes it an up-and-coming platform for synthetic biology. As a special means of synthetic biology, chloroplast genetic engineering shows excellent potential in reconstructing various sophisticated metabolic pathways within the plants for specific purposes, such as improving crop photosynthetic capacity, enhancing plant stress resistance, and synthesizing new drugs and vaccines. However, many plant species exhibit limited efficiency or inability in chloroplast genetic transformation. Hence, new transformation technologies and tools are being constantly developed. In order to further expand and facilitate the application of chloroplast genetic engineering, this review summarizes the new technologies in chloroplast genetic transformation in recent years and discusses the choice of appropriate synthetic biological elements  for the construction of efficient chloroplast transformation vectors.

African swine fever (ASF), caused by the African swine fever virus (ASFV), is an acute, hemorrhagic, and contagious disease of domestic pigs and wild boars.  The disease is notifiable and listed by the World Organization for Animal Health (WOAH) (Wang N et al. 2019).  The outcomes of ASF infection can be peracute, acute, subacute, and chronic, depending on the virulence of ASFVs.  According to the report of WOAH (https://www.woah.org/app/uploads/2022/12/asf-report24.pdf), from January 2020 to December 2022, ASF led to more than  2 million pig losses.  Currently, ASFV persists continuously in more than 23 countries and poses a serious threat to the global swine industry.  ASF invaded China on 3 August, 2018, caused by genotype II virulent Georgia-07-like ASFVs (Wen et al. 2019; Zhao et al. 2019; Wang et al. 2020; Wang L et al. 2022).  An experimental study showed that Georgia-07-like ASFV HLJ/18 isolated in China is highly lethal and efficiently transmissible in domestic pigs (Zhao et al. 2019; Jiang et al. 2021).  During the past four years, genotype II Georgia-07-like ASFVs dominantly spread in China.  However, the low virulent genotype II and I ASFVs have been successively reported in China in 2020 and 2021, respectively (Sun et al. 2021a, b; Shi et al. 2022).  Compared with the high virulent genotype II HLJ/18 strain, the low virulent genotype I and II ASFVs had lower virulence and high transmissibility in pigs and induced persistent and chronic infection showing irregular virus shedding at low levels (Sun et al. 2021a, b; Tsegay et al. 2022; Wang P et al. 2022).  Notably, when different genotype I and genotype II viruses infect the same pig in the field, a novel virus may be generated through viral genome recombination, which brings new problems and challenges for the prevention and control of ASF in China.  Thus, a diagnostic method that differentiates genotype I and II ASFVs with high sensitivity and stability is urgently needed and will be helpful for the prevention and control of ASF in China.  

ASFVs have been divided into at least 24 genotypes based on the C-terminus of the B646L gene with 478 nt (Bastos et al. 2003).  B646L gene is one of the most used target genes for ASF diagnosis, which is also the target gene for the WOAH recommended PCR and fluorescent quantitative PCR assays (Agüero et al. 2003; King et al. 2003).  Sanger sequencing of targeted amplification of the B646L genes is the main genotyping approach for ASFVs.  Recently, Li et al. (2022) developed the duplex real-time PCR assay based on the ASFV E296R gene, and Cao et al. (2022) established the TaqMAN-MGB probe assay based on the N-terminal sequences of the B646L gene (Cao et al. 2022; Li et al. 2022), which could distinguish genotype I and II ASFVs with detection limits of 10 copies.  However, the target genes or regions in their methods were out of ASFV genotyping regions.  

Single nucleotide polymorphism (SNP) is a single base change at a specific position in the genome of different individuals and can be used as a genotyping marker for the detection of different individual genotypes (Gut 2001).  The amplification refractory mutation system (ARMS), also named Allele-specific PCR (AS-PCR), relies on the extension of primer only when its 3´ end has a perfect complement to the template (Wang M et al. 2019).  ARMS-qPCR technology has been developed and widely used in SNP detection and genotyping (Ochsenreither et al. 2010; Shi et al. 2013; Wang M et al. 2019).  Compared with other assays for SNP detection and genotyping, ARMS-qPCR has the advantage of low-cost, simple operation, high sensitivity, and rapid and real-time detection.

Here, 126 complete or partial B646L genes of ASFVs, including 78 genotype I and 48 genotype II viruses, were obtained from the GenBank database, and their information is shown in Appendix A.  After analyzing these genes by the MegAlign Software (DNAStar), there were 4 SNPs in the C-terminus of the B646L gene, differentiating genotype I viruses from genotype II viruses (Fig. 1-A).  Two SNPs at sites 1 656 and 1 710 were used to design primers and probes for differential detection of genotype I and II ASFVs (Fig. 1-A).  As previously described (Huang et al. 1992; Liu et al. 2012), primers (I F, II F and R) and probes (probe 1 and probe 2) were designed with the targeted gene sequences using Primer 5 Software (Fig. 1-B; Appendix B).  The duplex ARMS-qPCR reaction system volume was 25 μL: 12.5 μL of 2× HyperProbe Mixture (GENFINE), 0.5 μL of I F, II F and R primers (10 μmol L^–1), 0.5 μL of probe 1 and probe 2 (10 μmol L^–1), 5 μL of template DNA, and 5 μL of ddH₂O.  The duplex ARMS-qPCR was performed by using the Bio-Rad CFX96 Touch Real-Time PCR Detection System with the following reaction conditions: 95°C for 30 s, followed by 40 cycles of 95°C for 10 s, and 60°C for 30 s.  Fluorescence signal was detected at the end of each cycle of extension step.  For the positive sample of genotype I ASFV, FAM and Cy5 fluorophores could be detected; however, for the positive sample of genotype II ASFV, only FAM fluorophore could be detected (Fig. 1-B).  

The standard curve test revealed that for the standard plasmids of genotype I ASFV, the slopes were –3.3825 for Cy5 and –3.1906 for FAM; the correlation coefficient R² was 0.999 for Cy5 and 0.998 for FAM; the amplification efficiency was 97.53% for Cy5 and 100.06% for FAM, respectively (Fig. 1-C); for the standard plasmids of genotype II ASFV, the slope was –3.2983 for FAM, the correlation coefficient R² was 0.992 for FAM, the amplification efficiency was 100.01% for FAM, whereas Cy5 fluorophore could not be detected (Fig. 1-C).  In addition, the sensitivity of the duplex ARMS-qPCR was 10 copies per reaction for both genotype I and II ASFVs (Fig. 1-D).  Thus, these results indicated that the duplex ARMS-qPCR assay has high efficiency and sensitivity.  

We then evaluated the specificity of the duplex ARMS-qPCR.  The nucleic acids of 7 other swine viruses, including PRRSV, CSFV, PRV, PCV2, PEDV, TGEV, and PoRV, were used as templates.  There were 3 amplification curves obtained for genotype I ASFV (FAM and Cy5 signals) and II ASFV (FAM signal), whereas no amplification curve was recorded for the nucleic acids of PRRSV, CSFV, PRV, PCV2, PEDV, TGEV, and PoRV, as well as genotype II ASFV (Cy5 signal) and ddH₂O (Fig. 1-E).  The results demonstrated that the duplex ARMS-qPCR has a good specificity without cross-reactivity with other swine viruses.

The results of the stable detection limit test showed that for the standard plasmids of genotype I ASFV, all 12 replicates were tested positive at the dilution of 10 copies, while 7/12 replicates were tested positive at the dilution of 5 copies (Fig. 1-F); for the standard plasmids of genotype II ASFV, all 12 replicates were tested positive at the dilution of 10 copies, while 6/12 replicates were tested positive at the dilution of 1 copy (Fig. 1-F).  Thus, the stable detection limit of the duplex ARMS-qPCR was 10 copies per reaction for both genotype I and II ASFVs (Fig. 1-F).

We further assessed the repeatability and reproducibility of the duplex ARMS-qPCR.  The assay tested the standard plasmids of 3 concentrations (10⁶, 10⁴, and 10² copies).  For the standard plasmids of genotype I ASFV, the intra- and inter-assay variation of Ct value for the duplex ARMS-qPCR ranged from 0.07 to 0.93% and 1.2 to 2.17% in FAM fluorescence channel and from 0.38 to 1.02% and 0.85 to 1.27% in Cy5 fluorescence channel, respectively (Table 1).  For the standard plasmids of genotype II ASFV, the intra- and inter-assay variation of Ct value for the duplex ARMS-qPCR ranged from 0.27 to 0.61% and 0.77 to 1.07% in FAM fluorescence channel (Table 1).  These findings suggested that the duplex ARMS-qPCR assay has satisfactory repeatability and reproducibility.

Finally, we evaluated the duplex ARMS-qPCR compared with WOAH-qPCR.  A total of 40 samples were detected using both assays, including blood, oral and rectal swabs, tissues, and cell cultures from pigs or PAMs infected by genotype I and II ASFVs.  Animal studies have evaluated the virulence and transmissibility of genotype I ASFV SD/DY-I/21 and genotype II virus HLJ/18 (Zhao et al. 2019; Sun et al. 2021a), respectively.  The results showed that 36 samples, including 18 of genotype I ASFV and 18 of genotype II ASFV were detected to be positive and differentiated by the duplex ARMS-qPCR, which were consistent with the results of the WOAH-qPCR (Appendix C).  

In summary, we developed a duplex ARMS-qPCR assay based on ASFV genotyping region of B646L gene, which can effectively differentiate genotype I and II ASFVs.  The assay had high sensitivity and specificity and exhibited good results in detecting samples, including blood, oral and rectal swabs, tissues, and cell culture.  Whether our method could be used for differentiating other genotypes of ASFVs is needed for further evalution.  However, just genotype I and II ASFVs are spreading outside Africa.  Thus, our method will provide an additional epidemiological investigation tool to implement effective ASFV control and prevention.

The B-box (BBX) family of proteins consists of zinc-finger transcription factors with one or two highly conserved B-box motifs at their N-termini.  BBX proteins play crucial roles in various aspects of plant growth and development, including seedling photomorphogenesis, shade avoidance, flowering time, and biotic and abiotic stress responses.  Previous studies have identified many different BBXs from several plant species, although the BBX family members in maize are largely unknown.  Genome-wide identification and comprehensive analysis of maize BBX (ZmBBX) expression and interaction networks would therefore provide valuable information for understanding their functions.  In this study, 36 maize BBXs in three major clades were identified.  The ZmBBXs within a given clade were found to share similar domains, motifs, and genomic structures.  Gene duplication analyses revealed that the expansion of BBX proteins in maize has mainly occurred by segmental duplication.  The expression levels of ZmBBXs were analyzed in various organs and tissues, and under different abiotic stress conditions.  Protein–protein interaction networks of ZmBBXs were established using bioinformatic tools and verified by bimolecular fluorescence complementation (BiFC) assays.  Our findings can facilitate a greater understanding of the complexity of the ZmBBX family and provide novel clues for unravelling ZmBBX protein functions

Whether promoting cash crop production can increase household welfare has long been the focus of the food policy debate.  This study first investigated the determinants of household behavior in commercial pulse farming.  It then examined how households’ commercial pulse production improves their economic welfare.  We used a dataset of 848 households collected from 2018 to 2019 to estimate the determinants of household behavior in commercial pulse farming by the Heckman two-step model.  The endogenous treatment regression (ETR) method was employed to examine the impact of commercial pulse farming on household economic welfare.  The results showed that factors such as market purchase prices, agricultural technology services, farmers’ access to loans, and government subsidies promoted smallholders’ commercial pulse farming; production costs and perceptions of climate change risks constrained smallholders’ commercial pulse production.  Overall, commercial pulse production has increased household farm income but there was a limited impact on household off-farm income.  Our findings suggest that policies aiming to increase households’ cash crop production and market access could significantly improve the economic welfare of pulse farmers.Whether promoting cash crop production can increase household welfare has long been the focus of the food policy debate.  This study first investigated the determinants of household behavior in commercial pulse farming.  It then examined how households’ commercial pulse production improves their economic welfare.  We used a dataset of 848 households collected from 2018 to 2019 to estimate the determinants of household behavior in commercial pulse farming by the Heckman two-step model.  The endogenous treatment regression (ETR) method was employed to examine the impact of commercial pulse farming on household economic welfare.  The results showed that factors such as market purchase prices, agricultural technology services, farmers’ access to loans, and government subsidies promoted smallholders’ commercial pulse farming; production costs and perceptions of climate change risks constrained smallholders’ commercial pulse production.  Overall, commercial pulse production has increased household farm income but there was a limited impact on household off-farm income.  Our findings suggest that policies aiming to increase households’ cash crop production and market access could significantly improve the economic welfare of pulse farmers.

Wheat grain morphology is an important breeding target considering its impact on yield and end-use properties.  However, the genetic basis of grain roundness, a major determinant of grain morphology, remains largely unexplored.  In this study, an F₂ and a recombinant inbred line (RIL) populations from Zhongkemai 138 (ZKM138)×Chinese Spring (CS) cross were employed to analyze the genetic basis of grain shape variation.  Kompetitive Allele Specific PCR (KASP) markers were developed according to single nucleotide polymorphism (SNP) from bulked segregant exome sequencing (BSE-Seq) of F₂ and Wheat 55K SNP array data online, and then were used to construct two genetic maps of F₂ and RIL populations, spanning 148.89 cM (30 KASP markers) and 129.82 cM (25 KASP markers), respectively.  By the traditional QTL mapping method based on these two maps, a stable quantitative trait locus (QTL) for grain roundness (GR), QGr.cib-5A, could be repeatedly highlighted in the interval of 444.8-455.5 Mb on chromosome 5A.  Further conditional QTL mapping analysis revealed that grain width was the major contributor to GR at this locus.  Besides, the utilization of two tightly linked markers 5A4-15 and 55k-31 showed a 96.27% transmissibility of ZKM138-derived alleles in 134 ZKM138 derivatives alongside a 7.38% increase in GR, and a 65.19% distribution of worldwide varieties.  Finally, TraesCS5A02G236400, possibly encoding a hydroxyproline-rich glycoprotein family protein, was deduced to be the candidate gene.  Collectively, these results provided the possibility of facilitating wheat grain shape improvement and enhancing wheat market value.