Phenotypic Variance Research Articles

The simplicity of protein sequence-function relationships

How complex are the rules by which a protein’s sequence determines its function? High-order epistatic interactions among residues are thought to be pervasive, suggesting an idiosyncratic and unpredictable sequence-function relationship. But many prior studies may have overestimated epistasis, because they analyzed sequence-function relationships relative to a single reference sequence—which causes measurement noise and local idiosyncrasies to snowball into high-order epistasis—or they did not fully account for global nonlinearities. Here we present a reference-free method that jointly infers specific epistatic interactions and global nonlinearity using a bird’s-eye view of sequence space. This technique yields the simplest explanation of sequence-function relationships and is more robust than existing methods to measurement noise, missing data, and model misspecification. We reanalyze 20 experimental datasets and find that context-independent amino acid effects and pairwise interactions, along with a simple nonlinearity to account for limited dynamic range, explain a median of 96% of phenotypic variance and over 92% in every case. Only a tiny fraction of genotypes are strongly affected by higher-order epistasis. Sequence-function relationships are also sparse: a miniscule fraction of amino acids and interactions account for 90% of phenotypic variance. Sequence-function causality across these datasets is therefore simple, opening the way for tractable approaches to characterize proteins’ genetic architecture.

A Genome-Wide Association Study Approach to Identify Novel Major-Effect Quantitative Trait Loci for End-Use Quality Traits in Soft Red Winter Wheat.

Wheat is used for making many food products due to its diverse quality profile among different wheat classes. Since laboratory analysis of these end-use quality traits is costly and time-consuming, genetic dissection of the traits is preferential. This study used a genome-wide association study (GWAS) of ten end-use quality traits, including kernel protein, flour protein, flour yield, softness equivalence, solvent's retention capacity, cookie diameter, and top-grain, in soft red winter wheat (SRWW) adapted to US southeast. The GWAS included 266 SRWW genotypes that were evaluated in two locations over two years (2020-2022). A total of 27,466 single nucleotide markers were used, and a total of 80 significant marker-trait associations were identified. There were 13 major-effect quantitative trait loci (QTLs) explaining >10% phenotypic variance, out of which, 12 were considered to be novel. Five of the major-effect QTLs were found to be stably expressed across multiple datasets, and four showed associations with multiple traits. Candidate genes were identified for eight of the major-effect QTLs, including genes associated with starch biosynthesis and nutritional homeostasis in plants. These findings increase genetic comprehension of these end-use quality traits and could potentially be used for improving the quality of SRWW.

An ultra-dense linkage map identified quantitative trait loci corresponding to fruit quality- and size-related traits in red goji berry.

Goji berries are a small-fruited shrub with industrial importance whose fruit considered beneficial in both fresh and dried forms. Current germplasms of goji berries include small fruits with a short shelf life, less sweet and bitter taste, and a lack of appropriate genetic information. This study aimed to employ whole genome resequencing to generate an ultra-dense bin linkage map and to elucidate the genetic basis of goji fruit quality and size using quantitative trait loci (QTL) mapping analysis in a cross-pollinated hybrid population. To achieve this goal, human sensory tests were carried out to determine the bitter taste (BT) and sweet taste (ST), and to quantify the soluble solid content (SSC), fruit firmness (FF), and fruit size-related traits of fresh goji fruits over three or four years. The results revealed that the goji bin linkage map based on resequencing spanned a total length of 966.42 cM and an average bin interval of 0.03 cM. Subsequent variant calling and ordering resulted in 3,058 bins containing 35,331 polymorphic markers across 12 chromosomes. A total of 99 QTLs, with individual loci in different environments explaining a phenotypic variance of 1.21-16.95% were identified for the studied traits. Ten major effects, including colocalized QTLs corresponding to different traits, were identified on chromosomes 1, 3, 5, 6, 7, and 8, with a maximum Logarithm of Odds (LOD) of 29.25 and 16.95% of explained phenotypic variance (PVE). In addition, four stable loci, one for FF, one for fruit weight (FW), and two for fruit shape index (FSI), were mainly mapped on chromosomes 5, 6, and 7, elucidating 2.10-16.95% PVE. These findings offer valuable insights into the genetic architecture of goji fruit traits along with identified specific loci and markers to further improve and develop sweeter, less bitter and larger fruited goji berry cultivars with extended shelf life.

Genome Engineering of Primary and Pluripotent Stem Cell-Derived Hepatocytes for Modeling Liver Tumor Formation.

Genome editing has demonstrated its utility in generating isogenic cell-based disease models, enabling the precise introduction of genetic alterations into wild-type cells to mimic disease phenotypes and explore underlying mechanisms. However, its application in liver-related diseases has been limited by challenges in genetic modification of mature hepatocytes in a dish. Here, we conducted a systematic comparison of various methods for primary hepatocyte culture and gene delivery to achieve robust genome editing of hepatocytes ex vivo. Our efforts yielded editing efficiencies of up to 80% in primary murine hepatocytes cultured in monolayer and 20% in organoids. To model human hepatic tumorigenesis, we utilized hepatocytes differentiated from human pluripotent stem cells (hPSCs) as an alternative human hepatocyte source. We developed a series of cellular models by introducing various single or combined oncogenic alterations into hPSC-derived hepatocytes. Our findings demonstrated that distinct mutational patterns led to phenotypic variances, affecting both overgrowth and transcriptional profiles. Notably, we discovered that the PI3KCA E542K mutant, whether alone or in combination with exogenous c-MYC, significantly impaired hepatocyte functions and facilitated cancer metabolic reprogramming, highlighting the critical roles of these frequently mutated genes in driving liver neoplasia. In conclusion, our study demonstrates genome-engineered hepatocytes as valuable cellular models of hepatocarcinoma, providing insights into early tumorigenesis mechanisms.

Polygenic risk score portability for common diseases across genetically diverse populations

BackgroundPolygenic risk scores (PRS) derived from European individuals have reduced portability across global populations, limiting their clinical implementation at worldwide scale. Here, we investigate the performance of a wide range of PRS models across four ancestry groups (Africans, Europeans, East Asians, and South Asians) for 14 conditions of high-medical interest.MethodsTo select the best-performing model per trait, we first compared PRS performances for publicly available scores, and constructed new models using different methods (LDpred2, PRS-CSx and SNPnet). We used 285 K European individuals from the UK Biobank (UKBB) for training and 18 K, including diverse ancestries, for testing. We then evaluated PRS portability for the best models in Europeans and compared their accuracies with respect to the best PRS per ancestry. Finally, we validated the selected PRS models using an independent set of 8,417 individuals from Biobank of the Americas-Genomelink (BbofA-GL); and performed a PRS-Phewas.ResultsWe confirmed a decay in PRS performances relative to Europeans when the evaluation was conducted using the best-PRS model for Europeans (51.3% for South Asians, 46.6% for East Asians and 39.4% for Africans). We observed an improvement in the PRS performances when specifically selecting ancestry specific PRS models (phenotype variance increase: 1.62 for Africans, 1.40 for South Asians and 0.96 for East Asians). Additionally, when we selected the optimal model conditional on ancestry for CAD, HDL-C and LDL-C, hypertension, hypothyroidism and T2D, PRS performance for studied populations was more comparable to what was observed in Europeans. Finally, we were able to independently validate tested models for Europeans, and conducted a PRS-Phewas, identifying cross-trait interplay between cardiometabolic conditions, and between immune-mediated components.ConclusionOur work comprehensively evaluated PRS accuracy across a wide range of phenotypes, reducing the uncertainty with respect to which PRS model to choose and in which ancestry group. This evaluation has let us identify specific conditions where implementing risk-prioritization strategies could have practical utility across diverse ancestral groups, contributing to democratizing the implementation of PRS.

Inheritance and QTL mapping identified multi-effects loci for fatty acid related traits in peanut (Arachis hypogaea L.)

Peanut (Arachis hypogaea L.) is an important oil and edible protein crop. The fatty acid composition not only influences the quality of peanut oil but also impacts flavor, shelf life, and consumer health. Peanut oil comprises approximately 80% oleic acid (C18:1) and linoleic acid (C18:2), 10% palmitic acid (C16:0), and the remaining 10% includes stearic acid (C18:0), arachidic acid (C20:0), gadoleic acid (C20:1), behenic acid (C22:0), and lignoceric acid (C24:0). To unravel the genetic foundation of fatty acid content and delve into QTL localization, we utilized high-density SNP microarrays for genotyping the RIL population of ‘SunOleic 97R’ × ‘NC94022’. A genetic linkage map was constructed with 3141 SNP markers, covering a total genetic distance of 3051.81 cM. We identified 60 quantitative trait loci (QTLs) associated with fatty acids which distributed in 11 linkage group, with phenotypic variance explained (PVE) ranging from 1.37% to 44.92%. Notably, the QTL qFAT_A05.1 and qFAT_A08.1 are multiple-effect loci contributing to various fatty acid compositions. Moreover, we identified 15 haplotypes for the QTL qFAT_A05.1 and qFAT_A08.1 through genotyping 178 peanut germplasms. Haplotypes analysis in natural population confirmed the closely relationship of the QTLs with the content of oil, oleic acid, lignoceric acid, palmitic acid and behenic acid. This study serves as a valuable reference for selecting improved peanut genotypes with superior oil quality and desirable fatty acid composition.

Fruit resources shape sexual selection processes in a lek mating system.

The degree to which within-population variation in sexual trait expression relates to resource heterogeneity remains poorly explored. This is particularly true in lek-mating species, where genetic explanations for male phenotypic variance and mating success are dominant. Here, we demonstrate a link between fine-scale fruit resource availability and indices of male mating success in the white-bearded manakin (Manacus manacus), a lek-mating frugivorous bird that produces energetically costly courtship displays. We used motion-activated camera traps to monitor male display behaviour and female visitation at male courts while concurrently conducting twice-monthly fruit surveys around courts. We observed significant variability in ripe fruit biomass among display courts and leks, and mean fruit biomass at courts significantly predicted male display rates. In turn, male display rate was the strongest predictor of female visitation to courts. Causal modelling supported the hypothesis that hyper-local fruit availability indirectly affects female visitation via its direct effects on male display rate. The demonstration that resource availability at fine spatial scales predicts display rate in a lekking organism-for which resource-related variables are typically not considered to play important roles in shaping male reproductive variance-has implications for the expression, honesty and maintenance of sexually selected traits under fluctuating ecological conditions.

Quantitative Trait Loci Mapping of Heading Date in Wheat under Phosphorus Stress Conditions.

Wheat (Triticum aestivum L.) is a crucial cereal crop, contributing around 20% of global caloric intake. However, challenges such as diminishing arable land, water shortages, and climate change threaten wheat production, making yield enhancement crucial for global food security. The heading date (HD) is a critical factor influencing wheat's growth cycle, harvest timing, climate adaptability, and yield. Understanding the genetic determinants of HD is essential for developing high-yield and stable wheat varieties. This study used a doubled haploid (DH) population from a cross between Jinmai 47 and Jinmai 84. QTL analysis of HD was performed under three phosphorus (P) treatments (low, medium, and normal) across six environments, using Wheat15K high-density SNP technology. The study identified 39 QTLs for HD, distributed across ten chromosomes, accounting for 2.39% to 29.52% of the phenotypic variance. Notably, five stable and major QTLs (Qhd.saw-3A.7, Qhd.saw-3A.8, Qhd.saw-3A.9, Qhd.saw-4A.4, and Qhd.saw-4D.3) were consistently detected across varying P conditions. The additive effects of these major QTLs showed that favorable alleles significantly delayed HD. There was a clear trend of increasing HD delay as the number of favorable alleles increased. Among them, Qhd.saw-3A.8, Qhd.saw-3A.9, and Qhd.saw-4D.3 were identified as novel QTLs with no prior reports of HD QTLs/genes in their respective intervals. Candidate gene analysis highlighted seven highly expressed genes related to Ca2+ transport, hormone signaling, glycosylation, and zinc finger proteins, likely involved in HD regulation. This research elucidates the genetic basis of wheat HD under P stress, providing critical insights for breeding high-yield, stable wheat varieties suited to low-P environments.

Influence of selection on the probability of fixation at a locus with multiple alleles

BackgroundGenes exist in a population in a variety of forms (alleles), as a consequence of multiple mutation events that have arisen over the course of time. In this work we consider a locus that is subject to either multiplicative or additive selection, and has n alleles, where n can take the values 2, 3, 4, …\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ldots$$\\end{document}. We focus on determining the probability of fixation of each of the n alleles. For n=2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$n = 2$$\\end{document} alleles, analytical results, that are ‘exact’, under the diffusion approximation, can be found for the fixation probability. However generally there are no equally exact results for n≥3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$n \\ge 3$$\\end{document} alleles. In the absence of such exact results, we proceed by finding results for the fixation probability, under the diffusion approximation, as a power series in scaled strengths of selection such as Ri,j=2Ne(si-sj)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R_{i,j}=2N_{e}(s_{i}-s_{j})$$\\end{document}, where Ne\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N_{e}$$\\end{document} is the effective population size, while si\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$s_{i}$$\\end{document} and sj\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$s_{j}$$\\end{document} are the selection coefficients associated with alleles i and j, respectively.ResultsWe determined the fixation probability when all terms up to second order in the Ri,j\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R_{i,j}$$\\end{document} are kept. The truncation of the power series requires that the Ri,j\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R_{i,j}$$\\end{document} cannot be indefinitely large. For magnitudes of the Ri,j\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R_{i,j}$$\\end{document} up to a value of approximately 1, numerical evidence suggests that the results work well. Additionally, results given for the particular case of n=3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$n = 3$$\\end{document} alleles illustrate a general feature that holds for n≥3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$n \\ge 3$$\\end{document} alleles, that the fixation probability of a particular allele depends on that allele’s initial frequency, but generally, this fixation probability also depends on the initial frequencies of other alleles at the locus, as well as their selective effects.ConclusionsWe have analytically exposed the leading way the probability of fixation, at a locus with multiple alleles, is affected by selection. This result may offer important insights into CDCV traits that have extreme phenotypic variance due to numerous, low-penetrance susceptibility alleles.

QTL-Seq identified a genomic region on chromosome 1 for soil-salinity tolerance in F2 progeny of Thai salt-tolerant rice donor line "Jao Khao".

Owing to advances in high-throughput genome sequencing, QTL-Seq mapping of salt tolerance traits is a major platform for identifying soil-salinity tolerance QTLs to accelerate marker-assisted selection for salt-tolerant rice varieties. We performed QTL-BSA-Seq in the seedling stage of rice from a genetic cross of the extreme salt-sensitive variety, IR29, and "Jao Khao" (JK), a Thai salt-tolerant variety. A total of 462 F2 progeny grown in soil and treated with 160 mM NaCl were used as the QTL mapping population. Two high- and low-bulk sets, based on cell membrane stability (CMS) and tiller number at the recovery stage (TN), were equally sampled. The genomes of each pool were sequenced, and statistical significance of QTL was calculated using QTLseq and G prime (G') analysis, which is based on calculating the allele frequency differences or Δ(SNP index). Both methods detected the overlapping interval region, wherein CMS-bulk was mapped at two loci in the 38.41-38.85 Mb region with 336 SNPs on chromosome 1 (qCMS1) and the 26.13-26.80 Mb region with 1,011 SNPs on chromosome 3 (qCMS3); the Δ(SNP index) peaks were -0.2709 and 0.3127, respectively. TN-bulk was mapped at only one locus in the overlapping 38.26-38.95 Mb region on chromosome 1 with 575 SNPs (qTN1) and a Δ(SNP index) peak of -0.3544. These identified QTLs in two different genetic backgrounds of segregating populations derived from JK were validated. The results confirmed the colocalization of the qCMS1 and qTN1 traits on chromosome 1. Based on the CMS trait, qCMS1/qTN1 stably expressed 6%-18% of the phenotypic variance in the two validation populations, while qCMS1/qTN1 accounted for 16%-20% of the phenotypic variance in one validation population based on the TN trait. The findings confirm that the CMS and TN traits are tightly linked to the long arm of chromosome 1 rather than to chromosome 3. The validated qCMS-TN1 QTL can be used for gene/QTL pyramiding in marker-assisted selection to expedite breeding for salt resistance in rice at the seedling stage.

Sexually divergent selection, allometric constraints, and the evolution of sexual dimorphism in cichlids from Lake Tanganyika.

The evolution of sexual dimorphism is widely acknowledged as manifestation of sex-specific genetic architecture. Although empirical studies suggested that sexual dimorphism evolves as a joint consequence of constraints arising from the genetic architecture and sexually divergent selection, it remains unclear whether and how these established microevolutionary processes scale up to the macroevolutionary patterns of sexual dimorphism among taxa. Here, we studied how sexual selection and parental care drive sexual dimorphism in cichlid fishes from Lake Tanganyika. We found that male-male competition, female choice, and maternal mouthbrooding are associated with sexual dimorphism in body length, body color, and head length, respectively, despite strong allometric relationships between body length and head length. Within-species (static) allometry of head length on body length evolved as sex-specific responses to mouthbrooding where females evolved higher intercepts while males evolved steeper slopes. Thus, selection to increase mouth size in mouthbrooders may have broken down and reorganized the pattern of allometric constraints that are inherently strong and concordant between sexes. Furthermore, sex-specific responses to mouthbrooding left a remarkably clear signature on the macroevolutionary pattern, resulting in a decoupling of co-evolution in parameters of static allometries observed exclusively within maternal mouthbrooders. Our study provides multiple lines of evidence that are consistent with the idea that macroevolutionary patterns of sexual dimorphism in Lake Tanganyika cichlids result from sexually divergent selection. Our approach illustrates that an examination of within-population phenotypic variance in the phylogenetic comparative framework may facilitate nuanced understandings of how macroevolutionary patterns are generated by underlying microevolutionary processes.

Bayesian estimates of genetic parameters for growth traits in Harnali sheep.

The objective of the study was to estimate genetic parameters of the growth traits under Bayesian inference in Harnali sheep. The information of pedigree and targeted traits of 2404 Harnali animals born to 159 sires and 695 dams was collected for the period from 1998 to 2021. The growth traits included weight at birth (BWT), 3 (WWT), 6 (6WT) and 12 (YWT) months of age. The genetic evaluation was carried out using six univariate animal models comprising direct and maternal effects using THRGIBBS1F90 and POSTGIBBSF90 programs. The fixed factors adjusted in the analysis were period of birth, sex of lamb and dam's weight at lambing. Bayesian estimates of direct heritability under best model for BWT, WWT, 6WT and YWT traits were 0.16 ± 0.04, 0.10 ± 0.04, 0.18 ± 0.04, and 0.05 ± 0.03, respectively. The significant maternal influences observed for BWT and WWT traits with 9% and 8% contribution to total phenotypic variances, respectively. Additionally, maternal permanent environmental influences were observed to BWT (4%) and YWT trait (3%). The genetic and phenotypic correlations among studied traits were high and positive. The genetic changes were positive and significant for WWT only. It was concluded that the weight at 6 months of age can be continued as selection criterion for further genetic improvement through selection. Also, maternal effects should be considered in breeding programme for enhancing early growth performance in Harnali sheep.

Experimental unbalance: reflections on genetic parameters and corn selection gain

Genetic progress depends on the components of variance and genetic parameters. In this context, the objective of this work was to identify the maximum allowed percentage of experimental imbalance in the estimation of variance components, genetic parameters and selection gain in intervarietal corn hybrids. The experimental design used was randomized blocks, with 60 corn hybrids with three replications. Random subsets of data were created in order to express unbalance scenarios of the phenotypic matrix, we obtained 9 scenarios (0, 10, 20, 30, 40, 50, 60, 70 and 80% unbalance).Thus, the genetic variance of the paternal genitor, the genetic variance of the maternal genitor, additive variance, individual phenotypic variance, narrow-sense heritability of intervarietal additive effects for the paternal genitor were estimated, narrow-sense heritability of intervarietal additive effects for the maternal genitor, narrow-sense heritability, broad-sense heritability, genotypic variation coefficient between progenies and variation coefficient residual. Narrow sense heritability reveals high magnitude for the characters cob mass and hundred grain mass. Maternal effect is expressed through ear insertion height, ear grain mass, cob mass and diameter, number of rows, ear mass and length, and grain yield. The imbalance inflates the variance components and genetic parameters for the highlighted characters. It supports 10% imbalance in the data matrix without compromising the reliability of the estimates. Pronounceable selection gains are obtained for grain yield based on pressures of 1 and 5%. An unbalance of 10% is supported in the selection gain for cob mass, ear length and hundred grain mass.

Fine Mapping and Candidate Gene Analysis of Two Major Quantitative Trait Loci, qFW2.1 and qFW3.1, Controlling Fruit Weight in Pepper (Capsicum annuum).

Fruit weight is an important agronomic trait in pepper production and is closely related to yield. At present, many quantitative trait loci (QTL) related to fruit weight have been found in pepper; however, the genes affecting fruit weight remain unknown. We analyzed the fruit weight-related quantitative traits in an intraspecific Capsicum annuum cross between the cultivated species blocky-type pepper, cv. Qiemen, and the bird pepper accession, "129-1" (Capsicum annuum var. glatriusculum), which was the wild progenitor of C. annuum. Using the QTL-seq combined with the linkage-based QTL mapping approach, QTL detection was performed; and two major effects of QTL related to fruit weight, qFW2.1 and qFW3.1, were identified on chromosomes 2 and 3. The qFW2.1 maximum explained 12.28% of the phenotypic variance observed in two F2 generations, with the maximum LOD value of 11.02, respectively; meanwhile, the qFW3.1 maximum explained 15.50% of the observed phenotypic variance in the two F2 generations, with the maximum LOD value of 11.36, respectively. qFW2.1 was narrowed down to the 1.22 Mb region using homozygous recombinant screening from BC2S2 and BC2S3 populations, while qFW3.1 was narrowed down to the 4.61Mb region. According to the transcriptome results, a total of 47 and 86 differentially expressed genes (DEGs) in the candidate regions of qFW2.1 and qFW3.1 were identified. Further, 19 genes were selected for a qRT-PCR analysis based on sequence difference combined with the gene annotation. Finally, Capana02g002938 and Capana02g003021 are the most likely candidate genes for qFW2.1, and Capana03g000903 may be a candidate gene for qFW3.1. Taken together, our results identified and fine-mapped two major QTL for fruit weight in pepper that will facilitate marker-assistant breeding for the manipulation of yield in pepper.

Evaluation of Turfgrasses for Qualitative and Quantitative Traits in Varanasi Region of India

The present experiment was conducted at Horticulture Research Farm, Department of Horticulture, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi. This study was carried out to evaluate performance of eleven turfgrass genotypes for qualitative traits, quantitative traits and their genetic variability under same climatic condition. The experimental design was a Randomized Block Design (RBD) with three replications. Eleven genotypes consist of Bermuda grass, Centipede grass, Panama grass, Bargusto grass, Tiftdwarf 419 grass, Local grass, Palma grass, Bahia grass, Manila grass, Crow Foot grass and Tanu Variant grass. These were assessed for their suitability to be used as turfgrass under Varanasi region. All the grasses exhibited semi prostrate growth habit except local grass having upright growth habit. Panama and Local grass showed fine leaf texture whereas, Manila grass exhibited coarse texture. Dark green colour was observed in Local, Crow Foot and Panama grass whereas, Centipede grass showed light green colour. Local grass exhibited maximum canopy height, leaf length, leaf width, chlorophyll content, stolen internode diameter, culm length, shoot length and shoot diameter. The maximum genotypic (187.22) and phenotypic variance (197.80) was observed for parameters like fresh weight. Canopy height showed maximum phenotypic coefficient of variation (47.04) and genotypic coefficient of variation (46.16) over all the parameters. Genetic advance maximum (27.49) for parameter fresh weight and genetic advance as a percentage of mean was maximum also for fresh weight (93.30). The maximum heritability at broad sense was observed for the parameter dry weight (98.25).

Association mapping of important agronomic traits in Mucuna pruriens (L.) DC.

BackgroundThe tropical legume Mucuna pruriens (L.) DC. can meet three agricultural needs: low-cost protein, high-value medicines, and green manure or cover crops. But like other underutilized crops, it needs more modern breeding resources. Identifying marker-trait associations (MTAs) can facilitate marker-assisted breeding and crop improvement. Recent studies have demonstrated the feasibility of identifying MTAs using a small number of accessions (< 100). We have characterized a panel of 70 M. pruriens accessions across two consecutive years and performed association analysis for 16 phenotypic traits related to seed (seed length, seed width, seed thickness, seed yield per plant, hundred seed weight); pod (pod length, pod width, number of pods per cluster, number of pods per plant); inflorescence (inflorescence length, flower buds per inflorescence, flower length, pedicel length), and biochemical attributes (L-DOPA, total protein, total carbohydrate), using 66 genic-microsatellite markers following mixed linear model.ResultsThe results showed significant phenotypic (P < 0.05) and genetic diversity (Shannon’s information index, I = 0.62) in our germplasm collection. Many tested traits were highly heritable (broad-sense heritability ranging from 42.86 to 99.93%). A total of 15 MTAs was detected at an adjusted significance level of P < 5.55 × 10− 3 for nine traits (seed length, seed thickness, seed width, hundred seed weight, seed yield per plant, inflorescence length, flower buds per inflorescence, flower length, and petiole length), contributed by 10 SSR markers (MPU_19, MPU_42, MPU_54, MPU_57, MPU_58, MPU_83, MPU_89, MPU_108, MPU_111, and MPU_122.) with phenotypic variance explained (PVE) ranging from 14.7 to 31.1%. Out of the ten trait-associated markers, the BLAST analysis revealed putative functions of seven markers, except MPU_57, MPU_58, and MPU_83.ConclusionFifteen MTAs identified for important traits with phenotypic variance explained > 10% from mixed linear model offer a solid resource base for improving this crop. This is the first report on association mapping in M. pruriens and our results are expected to assist with marker-assisted breeding and identifying candidate genes in this promising legume.

Bread wheat cultivar Popo harbors QTLs for seedling and adult plant resistance to leaf rust in South African and Argentine environments

Leaf rust, caused by the fungus Puccinia triticina Eriks (Pt), is a destructive disease affecting wheat (Triticum aestivum L.) production in many countries, and a serious threat to food security. As a result, several breeding programs have included leaf rust resistance as an important trait. The discovery and identification of new resistance genes that could aid in incorporating durable or long-lasting leaf rust resistance into wheat is fundamental in these breeding programs. The present study aimed to identify quantitative trait loci (QTLs) for leaf rust resistance in 127 recombinant inbred lines (RIL) developed from the cross between the resistant wheat cultivar Popo and the susceptible cultivar Kariega. The RIL population and parental lines were phenotyped for leaf rust infection type and severity at seedling and adult plant stage, respectively. The former in the greenhouse (in Argentina) and the latter in multiple field test environments comprising 3 locations in South Africa (in Tygerhoek in the Western Cape Province during the 2014, 2015, 2017 and 2018 cropping seasons; Clarens during 2014, 2016 and 2017 cropping seasons and in Bethlehem in the Free State Province during 2017 cropping season) and in 1 location in Argentina (during the 2017 and 2018 cropping seasons in Marcos Juárez, Córdoba Province). The population was genotyped using genotyping-by-sequencing. A total of 12,080 silicoDArT and 2,669 SNP markers were used for QTL analysis. In total, 25 putative QTLs for resistance to leaf rust at seedling and adult plant stages were identified, including 5 QTLs for seedling and 20 QTLs for adult plant resistance (APR). Interestingly, both Popo and Kariega contributed with alleles for resistance. Significant loci for reducing leaf rust infection at seedling stage were designated QLr.arc-1A, QLr.arc-2B, QLr.arc-5B, QLr.arc-6A and QLr.arc-6D. Three minor QTLs derived from Popo designated as QLr.arc-1B1, QLr.arc-2D and QLr.arc-3D were also detected from the field tests, explaining 5–10%, 10–16% and 5–7% of the phenotypic variance, respectively. The identified QTLs and their closely linked silicoDArT and SNP-based markers can be used for fine mapping and candidate gene discovery in wheat breeding programs targeting durable leaf rust resistance.

Brain transcriptomic signatures for mood disorders and suicide phenotypes: an anterior insula and subgenual ACC network postmortem study.

Mood disorders affect over ten percent of humans, but studies dissecting the brain anatomical and molecular neurobiological mechanisms underlying mood (dys)functions have not consistently identified the patterns of pathological changes in relevant brain regions. Recent studies have identified pathological changes in the anterior insula (Ant-Ins) and subgenual anterior cingulate (sgACC) brain network in mood disorders, in line with this network's role in regulating mood/affective feeling states. Here, we applied whole-tissue RNA-sequencing measures of differentially expressed genes (DEGs) in mood disorders versus (vs.) psychiatrically unaffected controls (controls) to identify postmortem molecular pathological markers for mood disorder phenotypes. Using data-driven factor analysis of the postmortem phenotypic variables to determine relevant sources of population variances, we identified DEGs associated with mood disorder-related diagnostic phenotypes by combining gene co-expression, differential gene expression, and pathway-enrichment analyses. We found downregulation/under expression of inflammatory, and protein synthesis-related genes associated with psychiatric morbidity (i.e., all co-occurring mental disorders and suicide outcomes/death by suicide) in Ant-Ins, in contrasts to upregulation of synaptic membrane and ion channel-related genes with increased psychiatric morbidity in sgACC. Our results identified a preponderance of downregulated metabolic, protein synthesis, inflammatory, and synaptic membrane DEGs associated with suicide outcomes in relation to a factor representing longevity in the Ant-Ins and sgACC (AIAC) network. Our study revealed a critical brain network molecular repertoire for mood disorder phenotypes, including suicide outcomes and longevity, and provides a framework for defining dosage-sensitive (i.e., downregulated vs. upregulated) molecular signatures for mood disorder phenotypic complexity and pathological outcomes.

Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries.

Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. We performed GWAS meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and, for the first time, the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signalling and brain ageing-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson's disease and ADHD. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases.

Modeling embryo survival: Genetic and environmental influences on eye-up rate in a north American Atlantic salmon selective breeding program

Selective breeding programs improve target traits but can also unintentionally change genetically correlated traits in the selected strain. The U.S. Department of Agriculture–Agricultural Research Service National Cold Water Marine Aquaculture Center (NCWMAC) in Franklin, Maine maintains a North American Atlantic salmon selective breeding program focused on improving commercially important traits (e.g., carcass weight). However, the program has experienced a significant decline in the percent of eyed embryos over its 14 years of operation, leading to concerns that reproductive performance was being unintentionally changed by selection for the target traits. The aims of this study were to 1) model eye up success as a potentially heritable trait utilizing the recorded pedigree and 2) assess the relationship between eye-up rate and environmental conditions experienced by the broodstock. Over 14 years of data encompassing 1537 full-sib families produced by 1537 dams and 885 sires was analyzed. Counts of eyed embryos and carcass weight were analyzed with a linear multi-trait trait model that included maternal genetic effects and a spawn year effect to determine the strength of genetic and environmental influences on the eyed embryo rate. To investigate the environmental influences in more detail, we assessed the correlation between water quality parameters in the broodstock rearing system observed over the same 14-year time period and the estimated spawn year effects. There was small heritability of the direct genetic effect (0.059 ± 0.009) and the maternal genetic effect (0.039 ± 0.013). Comparatively, the proportion of phenotypic variance explained by the maternal environmental effect was moderate (0.165 ± 0.012). The genetic correlations between carcass weight and eye up rate were very small and had a large amount of uncertainty. The correlation between the direct genetic effects on eye-up and carcass weight was −0.0528 ± 0.1469 while the correlation between the maternal genetic effect on eye-up and the direct genetic effect on carcass weight was 0.2030 ± 0.1791. The correlation between maternal common environmental effects on the two traits was also low at 0.0676 ± −0.0804. The effect of spawn year was statistically significant (p < 0.01), and the values were negatively correlated with mean un-ionized ammonia (mg/L, −0.56, p = 0.04,), nitrate concentrations (mg/L r = −0.65, p = 0.01) and temperature (°C, r = −0.61, p = 0.02) experienced by the broodstock prior to spawning. Overall, the results suggest that the decrease in eyed embryos over time was not caused by inadvertent selection but instead due to increases in water temperature and/or nitrogenous waste concentrations in the broodstock rearing system. Further investigation of the mechanisms behind these apparent environmentally induced declines and potential mitigation measures to prevent decreases in eye-up rates are needed.