Atsushi Imai

Genome‐wide association studies (GWAS) have identified numerous genomic regions associated with agronomically important traits in perennial fruit crops, including citrus ( Citrus spp.). Although GWAS are highly successful, they have limitations in separating and prioritizing significant single nucleotide polymorphisms (SNPs) due to the complex patterns of linkage disequilibrium (LD) within associated regions. To handle complex LD patterns and determine the number of causal SNPs, we performed GWAS followed by ‘sum of single effects’ (SuSiE) linear regression, a variable selection method that separates overlapping significant SNPs. We evaluated 9 fruit‐quality traits of 466 citrus accessions over 4 years and obtained 6887 SNPs by genotyping‐by‐sequencing. Using these phenotype and genotype records, GWAS identified 15 genomic regions associated with these traits. In these regions, SuSiE linear regression successfully separated overlapping significant SNPs and identified seven additional GWAS signals in five regions, providing evidence for multiple independent causal SNPs. These results demonstrate that the variable selection method implemented in SuSiE linear regression enables a more precise dissection of genetic architectures and helps identify independent causal SNP underlying complex traits in citrus.

The potential of genomic selection (GS) is currently being evaluated for fruit breeding. GS models are usually constructed based on information from both the genotype and phenotype of population. However, information from phenotyped but non-genotyped relatives can also be used to construct GS models, and this additional information can improve their accuracy. In the present study, we evaluated the utility of single-step genomic best linear unbiased prediction (ssGBLUP) in citrus breeding, which is a genomic prediction method that combines the kinship information from genotyped and non-genotyped relatives into a single relationship matrix for a mixed model to apply GS. Fruit weight, sugar content, and acid content of 1,935 citrus individuals, of which 483 had genotype data of 2,354 genome-wide single nucleotide polymorphisms, were evaluated from 2009–2012. The prediction accuracy of ssGBLUP for genotyped individuals was similar to or higher than that of usual genomic best linear unbiased prediction method using only genotyped individuals, especially for sugar content. Therefore, ssGBLUP could yield higher accuracy in genotyped individuals by adding information from non-genotyped relatives. The prediction accuracy of ssGBLUP for non-genotyped individuals was also slightly higher than that of conventional best linear unbiased prediction method using pedigree information. This indicates that ssGBLUP can enhance prediction accuracy of breeding values for non-genotyped individuals using genomic information of genotyped relatives. These results demonstrate the potential of ssGBLUP for fruit breeding, including citrus.

In the breeding of citrus (Citrus spp.), suitable fruit quality is essential for consumer acceptance of new cultivars. To identify parental combinations producing F₁ progeny with fruit-quality traits exceeding certain selection criteria, we developed a simple and practical method for predicting multiple-trait segregation in an F₁ progeny population. This method uses breeding values of parental genotypes and an additive genetic (co)variance matrix calculated by the best linear unbiased prediction method to construct a model for trait segregation in F₁ progeny. To confirm the validity of our proposed method, we calculated the breeding values and additive genetic (co)variances based on phenotypic records on nine fruit-quality traits in 2122 genotypes, and constructed a trait segregation model. Subsequently, we applied the trait segregation model to all pairs of the 2122 genotypes (i.e., 2,252,503 combinations), and predicted the most promising combinations and evaluated their probabilities of producing superior genotypes exceeding the nine fruit-quality traits of satsuma mandarin (Citrus unshiu Marcow.) or ‘Shiranuhi’ (‘Kiyomi’ × ‘Nakano No. 3’ ponkan), two popular citrus cultivars in Japan. We consider these results to be useful not only for selecting good parental combinations for fruit quality or other important traits but also for determining the scale of breeding programs required to achieve specific breeding goals.

Suicidal behavior (SB) is a major, worldwide health concern. To date there is limited understanding of the associated motivational aspects which accompany this self-initiated conduct. To develop a method for identifying motivational features associated with SB by studying admitted psychiatric patients, and to examine their clinical relevance. By performing a factor analytic study using data obtained from a patient sample exhibiting high suicidality and a variety of SB methods, Motivations for SB Scale (MSBS) was constructed to measure the features. Data included assessments of DSM-IV psychiatric and personality disorders, suicide intent, depressive symptomatology, overt aggression, recent life events (RLEs) and methods of SB, collated from structured interviews. Association of identified features with clinical variables was examined by correlation analyses and MANCOVA. Factor analyses elicited a 4-factor solution composed of Interpersonal-testing (IT), Interpersonal-change (IC), Self-renunciation (SR) and Self-sustenance (SS). These factors were classified according to two distinctions, namely interpersonal vs. intra-personal directedness, and the level of assumed influence by SB or the relationship to prevailing emotions. Analyses revealed meaningful links between patient features and clinical variables. Interpersonal-motivations (IT and IC) were associated with overt aggression, low suicidality and RLE discord or conflict, while SR was associated with depression, high suicidality and RLE separation or death. Borderline personality disorder showed association with IC and SS. When self-strangulation was set as a reference SB method, self-cutting and overdose-taking were linked to IT and SS, respectively. The factors extracted in this study largely corresponded to factors from previous studies, implying that they may be useful in a wider clinical context. The association of these features with SB-related factors suggests that they constitute an integral part of the process leading to SB. These results provide a base for further research into clinical strategies for patient management and therapy.

We analyzed the pedigree records (1995-2010) of the Kuchinotsu Citrus Breeding Program (KCBP) at the National Institute of Fruit Tree Science (NIFTS) in Japan, abbreviated as NIFTS-KCBP, to reveal the genetic background and current status of inbreeding and genetic uniformity of the parental cultivars/genotypes and their F 1 breeding progenies. The founding genotypes mostly used for crossing in NIFTS-KCBP were satsuma mandarin (Citrus unshiu Marcow.), sweet orange (C. sinensis [L.] Osbeck), king mandarin (C. nobilis Lour.), clementine (C. clementina hort. ex Tanaka), mediterranean mandarin (C. deliciosa Ten.), dancy tangerine (C. tangerina hort. ex Tanaka), and ponkan (C. reticulata Blanco). The intensive use of these seven genotypes and their progenies as crossed parents has led to a high degree of inbreeding in the breeding population. Moreover, these seven genotypes have dominated about 80% of the genetic composition of the breeding population. Although further studies are needed to reveal the influence of inbreeding and genetic uniformity on agronomically important traits, these data offer useful information for the selection of cross combinations and breeding strategies in the ongoing NIFTS citrus breeding program, Japan.