Uncovering the Novel QTLs and Candidate Genes of Salt Tolerance in Rice with Linkage Mapping, RTM-GWAS, and RNA-seq

Salinity is a major abiotic stress that limits plant growth and crop productivity. Indica rice and japonica rice show significant differences in tolerance to abiotic stress, and it is considered a feasible method to breed progeny with stronger tolerance to abiotic stress by crossing indica and japonica rice. We herein developed a high-generation recombinant inbred lines (RILs) from Luohui 9 (indica) X RPY geng (japonica). Based on the high-density bin map of this RILs population, salt tolerance QTLs controlling final survival rates were analyzed by linkage mapping and RTM-GWAS methods. A total of seven QTLs were identified on chromosome 3, 4, 5, 6, and 8. qST-3.1, qST-5.1, qST-6.1, and qST-6.2 were novel salt tolerance QTLs in this study and their function were functionally verified by comparative analysis of parental genotype RILs. The gene aggregation result of these four new QTLs emphasized that the combination of the four QTL synergistic genotypes can significantly improve the salt stress tolerance of rice. By comparing the transcriptomes of the root tissues of the parents’ seedlings, at 3 days and 7 days after salt treatment, we then achieved fine mapping of QTLs based on differentially expressed genes (DEGs) identification and DEGs annotations, namely, LOC_Os06g01250 in qST-6.1, LOC_Os06g37300 in qST-6.2, LOC_Os05g14880 in qST-5.1. The homologous genes of these candidate genes were involved in abiotic stress tolerance in different plants. These results indicated that LOC_Os05g14880, LOC_Os06g01250, and LOC_Os06g37300 were the candidate genes of qST-5.1, qST-6.1, and qST-6.2. Our finding provided novel salt tolerance-related QTLs, candidate genes, and several RILs with better tolerance, which will facilitate breeding for improved salt tolerance of rice varieties and promote the exploration tolerance mechanisms of rice salt stress.

Does Tomato Breeding for Improved Performance Under LED Supplemental Lighting Make Sense?

Differences in growth have been reported for tomato under LED compared to HPS light, however, it is not clear if breeding specific for LED supplemental light is worthwhile. Therefore, we derived four recombinant inbred line (RIL) tomato populations from parents with contrasting growth responses to different light spectra. These RIL populations were grown for four weeks under supplemental HPS or 95% red and 5% blue LED light in the greenhouse. For one population we also studied fruit production. Plant height and size of the side shoots of the young plants were strongly reduced under LED supplemental lighting compared to HPS in all populations. The adult plants showed shorter internode lengths, less trusses, less fruits, and lower yield of ripe fruits per plant under LED. However, when the unripe fruits at the last harvest day were included, the difference in yield between HPS and LED disappeared, indicating that the plants under LED light were compacter and slower in development, but in the end produced similar yield. We found numerous QTL, but hardly any of these QTL appeared to be significantly LED-specific. Also, we found very significant genetic effects of maternally inherited plastids and mitochondria, showing the importance of using a parental genotype as mother or as father. However, these effects were very similar between the two light conditions. We conclude that our study does not justify tomato breeding programs that are specifically targeted at 95% red and 5% blue LED supplemental lighting.

The causal effects of body mass index (BMI) on childhood symptoms of depression, anxiety disorder, and attention-deficit hyperactivity disorder: a within family Mendelian randomization study

Objectives: Higher BMI in childhood predicts neurodevelopmental and emotional problems, but it is unclear if these associations are causal. Previous genetic studies imply causal effects of childhood BMI on depression and attention-deficit hyperactivity disorder (ADHD), but these observations might also reflect effects of demography and the family environment. We used within-family Mendelian randomization, which accounts for familial effects by controlling for parental genotype, to investigate the impact of BMI on symptoms of depression, anxiety, and ADHD symptoms at age 8. Methods: This study is based on the Norwegian Mother, Father and Child Cohort Study (MoBa) and uses data from the Medical Birth Registry of Norway (MBRN). Participants were 26,370 8-year-old children (48.7% female) born 1999-2009, together with their parents. We applied multivariable regression, classic Mendelian randomization (classic MR), and within-family Mendelian randomization (within-family MR). We report estimates of the effects of the child's own BMI, mother's BMI, and father's BMI on the child's depressive, anxiety, and ADHD symptoms, reported by mothers when the child was aged 8. Results: In multivariable regression, higher BMI was marginally associated with more depressive and ADHD symptoms, and associated with fewer anxiety symptoms, in 8-year-old children. Classic MR models implied a causal effect of children's higher BMI on higher depressive and ADHD symptoms, and to a lesser degree, lower anxiety symptoms. In within-family MR models, there was less evidence that children's own BMI affected any of these symptoms. For example, a 5kg/m2 increase in BMI was associated with 0.04 standard deviations (SD) higher depressive symptoms (95% CI -0.01 to 0.09) in multivariable regression, with corresponding effect estimates of 0.41 SD (95% CI 0.10 to 0.56) in classic MR and 0.08 SD (95% CI -0.25 to 0.42) in within-family MR. Within-family MR suggested that maternal but not paternal BMI was associated with children's depressive symptoms. Conclusions: The influence of childhood BMI on depressive, anxiety and ADHD symptoms may have been overstated by MR approaches that do not account for parental genotype. Factors correlated with maternal BMI may influence offspring symptoms of depression.

399The causal effect of BMI on neurodevelopment: a within family Mendelian randomization study using MoBa

Background Higher BMI in childhood predicts subsequent neurodevelopmental and emotional problems, but it is unclear if associations are causal. Observational studies are vulnerable to reverse causation and confounding. Mendelian randomization (MR) studies with unrelated individuals can also suffer from familial biases, such as dynastic effects (“genetic nurture”). Methods We apply within-family MR (WFMR) to overcome these biases. We used genetic information from 26,370 family trios in the Norwegian Mother, Father and Child Cohort Study (MoBa) to construct BMI polygenic scores in children and both parents. By using all three polygenic scores to instrument BMI, we avoided familial biases affecting previous studies. Results Multivariable-adjusted and conventional MR models implied an impact of children’s BMI on depressive, ADHD, and autism symptoms. In conventional MR models, a 5kg/m2 increase in BMI corresponded to depressive symptoms 0.49 SD higher (95%CI: 0.24-0.73), and ADHD symptoms 0.49 SD higher (95%CI: 0.28-0.70). WFMR estimates were less precise but gave little evidence of causal impacts of children’s BMI. Maternal BMI was positively associated with children’s depressive (0.16 SD per 5kg/m2, 95%CI: 0.04-0.28) and autism symptoms, and paternal BMI with children’s ADHD symptoms. Conclusions Compared to conventional MR models, MR models accounting for parental genotype found less evidence of causal effects of children’s own BMI on emotional and neurodevelopmental symptoms. The discrepancy may suggest an influence of family or population-level effects. Key messages The influence of children’s own BMI on emotional and neurodevelopmental problems may have been overstated. Parental BMI, familial or population level effects may influence these outcomes.

Assessment of genetic divergence of Sesame seeds based on biochemical parameters

The assessment of genetic divergence plays a significant role to identify promising genotypes to initiate crossing programme for crop improvement. The sesame being a nutritious oil seed crop containing various biochemical constituents used as a good dietary choice. The biochemical analysis was done taking freshly harvested seeds of eight (8) parental genotypes and twenty one (21) advance lines. The studies revealed that all the genotypes differed significantly among themselves for all the biochemical parameters including moisture content, oil content, its iodine number and saponification value, both crude and soluble protein, some mineral matters – Ca, P, Mn, Zn, Cu & Fe and Carbohydrate and ascorbic acid content. Mahalanobis generalized genetic distance using D² statistics for the assessment of genetic divergence amongst 29 genotypes based on biochemical parameters. All the genotypes were grouped into eleven distinct clusters. Maximum intra cluster divergence was noted against cluster IX with advance lines having black coloured seeds as its constituents. With regard to inter-cluster distance values the cluster X was mostly divergent from all other clusters and cluster II as the less divergent one from the rest. Cluster X with parental genotype B-14 was identified as superior cluster for the biochemical parameters on the basis of securing higher position for maximum number of characters. Constitution pattern clustering was independent of eco-geographical isolation. Promising segregants with higher oil yielding potentially may yield from inter se mating of advance line 14 and HT-1 with T-12, R-9 or advance lines 10, 14, 20.

Combining ability analysis for yield and contributing traits in short duration rice (Oryza sativa L.)

The breeding value is an important genetic parameter determines utility of lines/genotypes to be used as parent in breeding program. This study was aimed at dissecting the breeding values (combining abilities) in 8 short duration rice lines for yield and 15 attributing traits. Altogether, 28 F1s developed under half-diallel fashion along with eight parents were evaluated. The study revealed importance of both additive and non-additive gene effects in governing yield and yield components with preponderance of non-additive gene action for most of the yield components. Additive gene action was found important for 1000-grain weight. The parental genotype (NUD3) and (NDR 359) were found to be good general combiners. The hybrids namely NDR359/Sarjoo-52, NDR359/NUD2, NDR359/NDRK5088, NDR359/NDR1, NDR359/Nagina22, NDR359/NUD3, NDR359/CSR10, Sarjoo52/NDRK5088, Sarjoo52 X NDR 1, NUD 2/NDR1, NUD 2/NUD3, NDRK5088/Nagina22, NDRK5088/NUD3, NDRK5088/CSR10, NUD 3/Nagina 22, Nagina 22/NUD3, NUD3/CSR 10 have shown significant favourable sca effect for yield and different yield components.

QTL Mapping in Outbred Tetraploid (and Diploid) Diallel Populations

Over the last decade, multiparental populations have become a mainstay of genetics research in diploid species. Our goal was to extend this paradigm to autotetraploids by creating computational tools for the analysis of connected F1 populations derived from a set of shared parents. In a companion paper, software to reconstruct F1 progeny in terms of parental haplotypes was described. For this study, we developed software for quantitative trait locus (QTL) mapping via Bayesian regression of phenotypes on the parental genotype probabilities. Statistical properties of the QTL model were explored by analyzing simulated half-diallel diploid and tetraploid populations with different population sizes, genome sizes, and numbers of parents. As expected, the LOD threshold needed to control the false positive rate increased with genome size, ploidy, and parents. Across the different scenarios, the number of progeny per parental haplotype (pph) largely determined the statistical power for QTL detection and the accuracy of the estimated haplotype effects. A QTL with heritability 0.1 was detected with 90% probability at 60 pph, while only 40 pph were needed to estimate the haplotypes with 90% accuracy. Our methodology includes a comprehensive treatment of dominance for multi-allelic QTL, which was illustrated by analyzing potato tuber shape in a 3 × 3 half-diallel population. A well-known QTL on chromosome 10 was detected, and the best-fit model included both additive and dominance effects. In terms of practical impacts on breeding, the software is already being used to select offspring based on the effect and dosage of particular haplotypes.

Gamete simulation improves polygenic transmission disequilibrium analysis

Polygenic risk scores (PRS) derived from summary statistics of genome-wide association studies (GWAS) have enjoyed great popularity in human genetics research. Applied to population cohorts, PRS can effectively stratify individuals by risk group and has promising applications in early diagnosis and clinical intervention. However, our understanding of within-family polygenic risk is incomplete, in part because the small samples per family significantly limits power. Here, to address this challenge, we introduce ORIGAMI, a computational framework that uses parental genotype data to simulate offspring genomes. ORIGAMI uses state-of-the-art genetic maps to simulate realistic recombination events on phased parental genomes and allows quantifying the prospective PRS variability within each family. We quantify and showcase the substantially reduced yet highly heterogeneous PRS variation within families for numerous complex traits. Further, we incorporate within-family PRS variability to improve polygenic transmission disequilibrium test (pTDT). Through simulations, we demonstrate that modeling within-family risk substantially improves the statistical power of pTDT. Applied to 7,805 trios of autism spectrum disorder (ASD) probands and healthy parents, we successfully replicated previously reported over-transmission of ASD, educational attainment, and schizophrenia risk, and identified multiple novel traits with significant transmission disequilibrium. These results provided novel etiologic insights into the shared genetic basis of various complex traits and ASD.

Genetic Diversity and Population Structure of Polish Konik Horse Based on Individuals from All the Male Founder Lines and Microsatellite Markers

The Polish Konik horse is a primitive native breed included in the genetic resource conservation program in Poland. After World War II, intensive breeding work began, aimed at rebuilding this breed. Now, the whole Polish Konik population is represented by six male founder lines (Wicek, Myszak, Glejt I, Goraj, Chochlik and Liliput). Individuals representing all six paternal lineages were selected based on their breeding documentation. We performed a fragment analysis with 17 microsatellite markers (STRs) recommended by the International Society for Animal Genetics (ISAG). The genetic diversity and structure within the paternal lineages and the whole of the studied group were investigated. The average allelic richness was 6.497 for the whole studied group. The fixation index (FST; measure of population differentiation) was low (about 3%), the mean inbreeding coefficient (FIT) was low and close to 0, and the mean inbreeding index value (FIS) was negative. The mean expected heterozygosity was established at 0.7046 and was lower than the observed heterozygosity. The power of discrimination and power of exclusion were 99.9999%. The cumulative parentage exclusion probability equaled 99.9269% when one parental genotype was known and 99.9996% with both parents’ genotypic information was available. About 3% of the genetic variation was caused by differences in the breed origin and about 97% was attributed to differences among individuals. Our analysis revealed that there has been no inbreeding in the Polish Konik breed for the studied population. The genetic diversity was high, and its parameters were similar to those calculated for native breeds from other countries reported in the literature. However, due to the small number of breed founders and paternal lineages with unknown representation, the population’s genetic diversity and structure should be monitored regularly.