A Consensus Genetic Map and Linkage Panel for Fresh-market Tomato

The first consensus genetic map in fresh-market tomato (Solanum lycopersicum) was constructed, combining genetic recombination data from two biparental F2 segregating populations derived from four different fresh-market tomatoes. Each F2 population was nominated by different academic tomato breeding programs located in major fresh-market tomato-producing areas of the United States, and chromosome-wide variation in recombination rates was observed between tomato populations based on the origin of their breeding programs. A consensus map constructed using 335 common single nucleotide polymorphism (SNP) sites found in both populations spanned 737.3 cM across 12 tomato chromosomes, with chromosome 2 containing more than 40% of the total SNPs and chromosomes 4, 5, 7, and 10 together representing less than 10% of the SNPs. There was a high degree of collinearity between the genetic and physical positions of those 335 SNP markers. The integration of 6553 SNP sites that were detected in either of the two populations with 335 common sites resulted in an extended consensus genetic map. The total length of the extended map was estimated to be 1997.9 cM, which was compatible with a previous estimate for large-fruited fresh-market tomato. A linkage panel for fresh-market tomato was also established using the combined dataset of the consensus map of 335 SNP loci and 73 SNP-genotyped core fresh-market tomatoes. An empirical genetic mapping study of the tomato brachytic trait using the linkage panel demonstrated the value of the consensus map and linkage panel for tomato research. The allelic information in the linkage panel will serve as a basis for SNP marker implementation, such as genotyping platforms and genomic association map, in tomato.

A high-resolution consensus linkage map for barley based on GBS-derived genotypes

As genotyping-by-sequencing (GBS) is widely used in barley genetic studies, the translation of the physical position of GBS-derived SNPs into accurate genetic positions has become relevant. The main aim of this study was to develop a high-resolution consensus linkage map based on GBS-derived SNPs. The construction of this integrated map involved 11 bi-parental populations composed of 3743 segregating progenies. We adopted a uniform set of SNP-calling and filtering conditions to identify 50 875 distinct SNPs segregating in at least one population. These SNPs were grouped into 18 580 non-redundant SNPs (bins). The resulting consensus linkage map spanned 1050.1 cM, providing an average density of 17.7 bins and 48.4 SNPs per cM. The consensus map is characterized by the absence of large intervals devoid of marker coverage (significant gaps), the largest interval between bins was only 3.7 cM and the mean distance between adjacent bins was 0.06 cM. This high-resolution linkage map will contribute to several applications in genomic research, such as providing useful information on the recombination landscape for QTLs/genes identified via GWAS or ensuring a uniform distribution of SNPs when developing low-cost genotyping tools offering a limited number of markers.

Meta-QTLs and candidate genes for stripe rust resistance in wheat

In bread wheat, meta-QTL analysis was conducted using 353 QTLs that were available from earlier studies. When projected onto a dense consensus map comprising 76,753 markers, only 184 QTLs with the required information, could be utilized leading to identification of 61 MQTLs spread over 18 of the 21 chromosomes (barring 5D, 6D and 7D). The range for mean R2 (PVE %) was 1.9% to 48.1%, and that of CI was 0.02 to 11.47 cM; these CIs also carried 37 Yr genes. Using these MQTLs, 385 candidate genes (CGs) were also identified. Out of these CGs, 241 encoded known R proteins and 120 showed differential expression due to stripe rust infection at the seedling stage; the remaining 24 CGs were common in the sense that they encoded R proteins as well as showed differential expression. The proteins encoded by CGs carried the following widely known domains: NBS-LRR domain, WRKY domains, ankyrin repeat domains, sugar transport domains, etc. Thirteen breeders’ MQTLs (PVE > 20%) including four pairs of closely linked MQTLs are recommended for use in wheat molecular breeding, for future studies to understand the molecular mechanism of stripe rust resistance and for gene cloning.

Exploring Users’ Mental Models for Anthropomorphized Voice Assistants through Psychological Approaches

Various perspectives are being studied to increase the usability and persistence of voice assistants (VA) as the use is rapidly expanding to various domains. Particularly, many studies note that users personify VA. Systems designed to suit users differing mental models while using specific systems can provide a positive user experience, increasing usability and persistence. Therefore, we tried to structure the mental model of users using personified VA and proposed these results as an important factor to consider in personifying VA. To determine important factors to consider in personifying VA, this research structures the mental model of users using personified VA. Furthermore, we used two types of psychological approaches that were not applied in previous studies to analyze users’ mental models. Using two types of psychological approaches that were not applied in previous studies, this research analyzed users’ mental models. In Study 1, each user’s thinking process is derived through ZMET (Zaltman metaphor elicitation techniques as a consensus map. Afterward, in Study 2, correlations between the key components analyzed in Study 1 are validated through RG (repertory grid technique). As a result, the research found that there are three different psychological structures. The first structure is of users who feel human-like empathy and warmth in the use of VA. Meanwhile, the second structure is of users who seek help with problem-solving. The last is the psychological structure of users who regarded anthropomorphic VA as just a machine. Users with this mental model expect the potential for development as a machine rather than the personification of VA. Ultimately, this research is meaningful in that it analyzes each user’s psychological mechanism for personified VA through a psychological approach and derives three new mental models in detail.

SME’S Accounting Information in the Eyes of Bank Credit Analyst: Exploration with ZMET Method

This study aims to explore and gain an in-depth understanding of the views of bank credit analysts on SME’s accounting information in credit decision making. This study used the ZMET (Zaltman Metaphor Elicitation Technique) method to dig information from nine credit analysts as research participants with a qualitative approach. With ZMET's projective techniques through image metaphors, the study has identified 16 important constructs that describe bank credit analysts' mental models when facing the vagueness of SME’s accounting information in their credit decision-making process. The connection between constructs is described in the consensus map, which explains the four main themes of the study's findings; SME accounting information blur, the use of alternative information, the dual role of credit analysts, and information needs in credit decision-making. Received: 3 July 2021 / Accepted: 23 August 2021 / Published: 5 November 2021

QTL analysis in multiple sorghum mapping populations facilitates dissection of the genetic control of agronomic and yield-related traits in sorghum [Sorghum bicolor (Moench)]

The genetic architectures of agronomic and yield-related traits are expected to involve multiple loci that are unlikely all to segregate for alternative alleles in a single bi-parental population. Therefore, the identification of quantitative trait loci (QTL) that are expressed in diverse genetic backgrounds of multiple bi-parental populations provides evidence about both background-specific and common genetic variants. The purpose of this study was to map QTLs for agronomic and yield related traits using three connected mapping populations of different genetic backgrounds, to gain insight into the genomic landscape of these important traits in elite Ethiopian sorghum germplasm. The three bi-parental populations, each with 207 F 2:3 lines were evaluated using an alpha lattice design with two replications under two moisture stress environments. Data analysis was done separately for each population using composite interval mapping, finding a total of 105 QTLs. All the QTLs identified from individual populations were projected on a combined consensus map, comprising a total of 25 meta QTLs for seven traits. The consensus map allowed us to deduce locations of a larger number of markers than possible in any individual map, providing a reference for genetic studies in different genetic backgrounds. The meta QTLs identified in this study could be used for marker-assisted breeding programs in sorghum after validation. Only one trait reduced leaf senescence, showed a striking bias of allele distribution, indicating substantial standing variation among the lines that might be employed in improving drought tolerance of sorghum.

Construction of Consensus Genetic Map With Applications in Gene Mapping of Wheat (Triticum aestivum L.) Using 90K SNP Array

Wheat is one of the most important cereal crops worldwide. A consensus map combines genetic information from multiple populations, providing an effective alternative to improve the genome coverage and marker density. In this study, we constructed a consensus map from three populations of recombinant inbred lines (RILs) of wheat using a 90K single nucleotide polymorphism (SNP) array. Phenotypic data on plant height (PH), spike length (SL), and thousand-kernel weight (TKW) was collected in six, four, and four environments in the three populations, and then used for quantitative trait locus (QTL) mapping. The mapping results obtained using the constructed consensus map were compared with previous results obtained using individual maps and previous studies on other populations. A simulation experiment was also conducted to assess the performance of QTL mapping with the consensus map. The constructed consensus map from the three populations spanned 4558.55 cM in length, with 25,667 SNPs, having high collinearity with physical map and individual maps. Based on the consensus map, 21, 27, and 19 stable QTLs were identified for PH, SL, and TKW, much more than those detected with individual maps. Four PH QTLs and six SL QTLs were likely to be novel. A putative gene called TraesCS4D02G076400 encoding gibberellin-regulated protein was identified to be the candidate gene for one major PH QTL located on 4DS, which may enrich genetic resources in wheat semi-dwarfing breeding. The simulation results indicated that the length of the confidence interval and standard errors of the QTLs detected using the consensus map were much smaller than those detected using individual maps. The consensus map constructed in this study provides the underlying genetic information for systematic mapping, comparison, and clustering of QTL, and gene discovery in wheat genetic study. The QTLs detected in this study had stable effects across environments and can be used to improve the wide adaptation of wheat cultivars through marker-assisted breeding.

Identifying Meta-QTLs for Stay-Green in Sorghum

To develop resilient crops it is necessary to understand the underlying genetics of climatic response. A strong association between stay-green and post-flowering drought tolerance in Sorghum has been established. Being a complex quantitative trait, Quantitative Trait Loci (QTL) mapping experiments of stay-green in Sorghum have been frequently performed. The objective of the current study was to find consensus genomic regions that control stay-green by integrating the QTLs mapped in previous studies. Meta-QTL analysis was performed to summarize 115 QTLs projected on the consensus map. The analysis generated 32 Meta-QTL regions within which candidate gene (CG) identification was undertaken. 7 candidate genes were identified using the markers tightly linked to the Meta-QTLs. The results from this study will facilitate future attempts aiming to improve and understand drought tolerance in Sorghum.

Meta-QTL Analysis for Stripe Rust Resistance in Wheat

Stripe rust caused by Puccinia striiformis f. sp. tritici Eriks. & E. Henn (Pst) is one of the most prevalent wheat diseases causing upto 70% yield losses worldwide. The present study was conducted in wheat for the first time to identify important meta-QTL (MQTL) regions for their use in developing stripe rust resistant wheat cultivars and to understand the genetic architecture of stripe rust resistance in wheat. For this purpose, a dense consensus map consisting of 76,753 markers was constructed and 353 QTLs from earlier studies were projected on this consensus map. As many as 61 MQTLs were identified using 184 (out of 353) original QTLs. Ten important genomic regions including six breeders’ MQTLs (PVE >20%) and four MQTL hotspots were selected to be used by wheat breeders. As many as 409 important candidate genes (CGs) were also identified, which either encoded known R proteins (265) or showed differential expression (144) due to stripe rust infection. These included genes encoding the following proteins: NBS-LRR, WRKY domains, ankyrin repeat domains, sugar transporters, etc. Overall, the present study provided robust MQTLs and underlying CGs which may be potential targets for molecular breeding for development of stripe rust resistant wheat cultivars or may be the target for future molecular studies to understand the mechanism of stripe rust resistance.

Meta-Analysis of Quantitative Traits Loci (QTL) Identified in Drought Response in Rice (Oryza sativa L.)

Rice is an important grain that is the staple food for most of the world’s population. Drought is one of the major stresses that negatively affects rice yield. The nature of drought tolerance in rice is complex as it is determined by various components and has low heritability. Therefore, to ensure success in breeding programs for drought tolerant rice, QTLs (quantitative trait loci) of interest must be stable in a variety of plant genotypes and environments. This study identified stable QTLs in rice chromosomes in a variety of backgrounds and environments and conducted a meta-QTL analysis of stable QTLs that have been reported by previous research for use in breeding programs. A total of 653 QTLs for drought tolerance in rice from 27 genetic maps were recorded for analysis. The QTLs recorded were related to 13 traits in rice that respond to drought. Through the use of BioMercartor V4.2, a consensus map containing QTLs and molecular markers were generated using 27 genetic maps that were extracted from the previous 20 studies and meta-QTL analysis was conducted on the consensus map. A total of 70 MQTLs were identified and a total of 453 QTLs were mapped into the meta-QTL areas. Five meta-QTLs from chromosome 1 (MQTL 1.5 and MQTL 1.6), chromosome 2 (MQTL2.1 and MQTL 2.2) and chromosome 3 (MQTL 3.1) were selected for functional annotation as these regions have high number of QTLs and include many traits in rice that respond to drought. A number of genes in MQTL1.5 (268 genes), MQTL1.6 (640 genes), MQTL 2.1 (319 genes), MQTL 2.2 (19 genes) and MQTL 3.1 (787 genes) were annotated through Blast2GO. Few major proteins that respond to drought stress were identified in the meta-QTL areas which are Abscisic Acid-Insensitive Protein 5 (ABI5), the G-box binding factor 4 (GBF4), protein kinase PINOID (PID), histidine kinase 2 (AHK2), protein related to autophagy 18A (ATG18A), mitochondrial transcription termination factor (MTERF), aquaporin PIP 1-2, protein detoxification 48 (DTX48) and inositol-tetrakisphosphate 1-kinase 2 (ITPK2). These proteins are regulatory proteins involved in the regulation of signal transduction and gene expression that respond to drought stress. The meta-QTLs derived from this study and the genes that have been identified can be used effectively in molecular breeding and in genetic engineering for drought resistance/tolerance in rice.