High Phenotypic Values Research Articles

Genetic background of hematological parameters in Holstein cattle based on genome-wide association and RNA sequencing analyses

Hematological parameters refer to the assessment of changes in the number and distribution of blood cells, including leukocytes (LES), erythrocytes (ERS), and platelets (PLS), which are essential for the early diagnosis of hematological system disorders and other systemic diseases in livestock. In this context, the primary objectives of this study were to investigate the genomic background of 19 hematological parameters in Holstein cattle, focusing on LES, ERS, and PLS blood components. Genetic and phenotypic (co)variances of hematological parameters were calculated based on the Average Information Restricted Maximum Likelihood (AIREML) method and 1,610 genotyped individuals and 5,499 hematological parameter records from 4,543 cows. Furthermore, we assessed the genetic relationship between these hematological parameters and other economically important traits in dairy cattle breeding programs. We also carried out genome-wide association studies and candidate gene analyses. Blood samples from 21 primiparous cows were used to identify candidate genes further through RNA sequencing (RNA-seq) analyses. Hematological parameters generally exhibited low-to-moderate heritabilities ranging from 0.01 to 0.29, with genetic correlations between them ranging from -0.88 ± 0.09 (between mononuclear cell ratio and lymphocyte cell ratio) to 0.99 ± 0.01 (between white blood cell count and granulocyte cell count). Furthermore, low to moderate approximate genetic correlations between hematological parameters with one longevity, 4 fertility, and 5 health traits were observed. One-hundred-and-99 significant single nucleotide polymorphisms (SNP) located primarily on the Bos taurus autosomes (BTA) BTA4, BTA6, and BTA8 were associated with 16 hematological parameters. Based on the RNA-seq analyses, 6,687 genes were significantly downregulated and 4,119 genes were upregulated when comparing 2 groups of cows with high and low phenotypic values. By integrating genome-wide association studies (GWAS), RNA-seq, and previously published results, the main candidate genes associated with hematological parameters in Holstein cattle were ACRBP, ADAMTS3, CANT1, CCM2L, CNN3, CPLANE1, GPAT3, GRIP2, PLAGL2, RTL6, SOX4, WDFY3, and ZNF614. Hematological parameters are heritable and moderately to highly genetically correlated among themselves. The large number of candidate genes identified based on GWAS and RNA-seq indicate the polygenic nature and complex genetic determinism of hematological parameters in Holstein cattle.

Analysis of liver miRNA in Hu sheep with different residual feed intake.

Feed efficiency (FE), an important economic trait in sheep production, is indirectly assessed by residual feed intake (RFI). However, RFI in sheep is varied, and the molecular processes that regulate RFI are unclear. It is thus vital to investigate the molecular mechanism of RFI to developing a feed-efficient sheep. The miRNA-sequencing (RNA-Seq) was utilized to investigate miRNAs in liver tissue of 6 out of 137 sheep with extreme RFI phenotypic values. In these animals, as a typical metric of FE, RFI was used to distinguish differentially expressed miRNAs (DE_miRNAs) between animals with high (n = 3) and low (n = 3) phenotypic values. A total of 247 miRNAs were discovered in sheep, with four differentially expressed miRNAs (DE_miRNAs) detected. Among these DE_miRNAs, three were found to be upregulated and one was downregulated in animals with low residual feed intake (Low_RFI) compared to those with high residual feed intake (High_RFI). The target genes of DE_miRNAs were primarily associated with metabolic processes and biosynthetic process regulation. Furthermore, they were also considerably enriched in the FE related to glycolysis, protein synthesis and degradation, and amino acid biosynthesis pathways. Six genes were identified by co-expression analysis of DE_miRNAs target with DE_mRNAs. These results provide a theoretical basis for us to understand the sheep liver miRNAs in RFI molecular regulation.

High-density genetic mapping identified QTLs for anaerobic germination tolerance in rice.

The tolerance of rice anaerobic germination (AG) is the main limiting factor for direct seeding application, yet the genetics mechanism is still in its infancy. In the study, recombinant inbred lines population of TD70 Japonica cultivar and Kasalath Indica cultivar, was employed to construct a high-density genetic map by whole genome re-sequencing. As a result, a genetic map containing 12,328 bin-markers was constructed and a total of 50 QTLs were then detected for CL(coleoptile length), CD (coleoptile diameter), CSA (coleoptile surface area) and CV (coleoptile volume) related traits in the two stages of anaerobic treatment using complete interval mapping method (inclusive composite interval mapping, ICIM). Among the four traits associated with coleoptile, coleoptile volume had the largest number of QTLs (17), followed by coleoptile diameter (16), and coleoptile length had 5 QTLs. These QTLs could explain phenotypic contribution rates ranging from 0.34% to 11.17% and LOD values ranging from 2.52 to 11.57. Combined with transcriptome analysis, 31 candidate genes were identified. Furthermore, 12 stable QTLs were used to detect the aggregation effect analysis. Besides, It was found that individuals with more aggregation synergistic alleles had higher phenotypic values in different environments. Totally, high-density genetic map, QTL mapping and aggregation effect analysis of different loci related to the anaerobic germination of rice seeds were conducted to lay a foundation for the fine mapping of related genes in subsequent assisted breeding.

Predicting Phenotypes From High-Dimensional Genomes Using Gradient Boosting Decision Trees

xsxsGenomic selection (GS) is an emerging technique for predicting unknown phenotypes using genome-wide marker coverage, allowing the use of efficient computational models to select individuals with high phenotypic values as candidate breeding populations. However, GS remains challenging inefficient crop breeding due to the limited size of training populations, the nature of genotype-environment interactions, and the complex interaction patterns between molecular markers. In this study, we use ensemble learning algorithms to construct gradient boosted decision tree (GBDT) models to achieve the prediction of phenotypic values from genotypic markers. We trained GBDT using the wheat GS dataset and compared the predictive performance with six other widely used GS models. The mean normalized discounted cumulative gain (MNDCG) method was used to evaluate the ability of each model to select individuals with high phenotypic values. The results of the study show that: (1) Bayesian models converge and reach a steady-state only when a sufficient number of iterations are set. As the number of iterations increases, the prediction accuracy of the Bayesian model increases, but the computational efficiency of the model decreases significantly. When 200,000 iterations are performed, the prediction performance of the five Bayesian models is similar and converges to a smooth state, and their prediction accuracy is 7.60% better than the GBDT model overall, and the computational efficiency of the GBDT model is 70 times that of the Bayesian model. (2) Overall, the overall prediction performance of the RRBLUP model was the best, but for some traits, the GBDT model still had a higher ability to select individuals with high phenotypic values than the RRBLUP and Bayesian models. (3) The prediction accuracy of GBDT and RRBLUP models was influenced by the subset of markers, and the higher the number of markers the higher the prediction accuracy of the models, so the reasonable selection of genetic marker data of appropriate size could improve the prediction performance of the models.

BSA-seq-based identification of a major additive plant height QTL with an effect equivalent to that of Semi-dwarf 1 in a large rice F2 population

Bulked-segregant analysis is a time- and cost-saving strategy for identifying major quantitative trait loci (QTL) in a mapping population. Bulked-segregant analysis combined with whole-genome sequencing (BSA-seq) was performed to rapidly identify QTL for heading date, plant height, and panicle length in a large F2 population derived from two landraces: Chuan 7 (C7) and Haoboka (HBK). Twenty plants with extremely low or high phenotypic values for the target traits were selected from an F2 population of 940 plants to construct low- and high-value bulks. Three pairs of bulks for the three traits were constructed, resulting in six DNA pools. BSA-seq revealed nine QTL: four for heading date, three for plant height, and two for panicle length. These QTL were validated in a random F2 population or BC4F2 populations. The major novel plant height QTL, qPH8, acting additively with an effect equivalent to that of semi-dwarf 1 (sd1), is potentially valuable for hybrid rice breeding. qPH8 controls mainly the elongation of basal internodes. The C7 allele of qPH8 reduces plant height and increases lodging resistance without yield penalty, suggesting a potential role for qPH8 in improving rice plant architecture.

Bovine hepatic miRNAome profiling and differential miRNA expression analyses between beef steers with divergent feed efficiency phenotypes

MicroRNAs (miRNAs) are small RNA molecules involved in regulation of multiple biological processes through modulating expression of their target genes. Here we employed RNAseq to profile liver tissue miRNAome of 60 steers from Angus, Charolais, and Kinsella Composite (KC) populations. Of these animals, 36 animals (n = 12 for each breed) were utilized to identify differentially expressed (DE) miRNAs between animals with high (n = 6) or low (n = 6) phenotypic values of residual feed intake (RFI), a common measurement of feed efficiency. At a threshold of fold-change > 1.5 and P-value < 0.05, we detected 12 (7 up- and 5 downregulated in low-RFI animals), 18 (12 up- and 6 downregulated), and 13 (8 up- and 5 downregulated) DE miRNAs for Angus, Charolais, and KC steers, respectively. Most of the DE miRNAs were breed specific, with bta-miR-449a and bta-miR-AB-2 being differentially expressed in all three breeds. The predicted target genes of the identified DE miRNA are mainly involved in cell cycle, cell death and survival, cell signaling, cellular growth and proliferation, protein trafficking, cell morphology, cell-to-cell signaling and interaction, cellular development, molecular transport, post-translational modification, as well as nutrient metabolism (lipids, carbohydrates, protein and amino acid). Our results provide insights into the bovine hepatic miRNAome and their potential roles in molecular regulation of RFI in beef cattle.

Genotype networks of 80 quantitative Arabidopsis thaliana phenotypes reveal phenotypic evolvability despite pervasive epistasis.

We study the genotype-phenotype maps of 80 quantitative phenotypes in the model plant Arabidopsis thaliana, by representing the genotypes affecting each phenotype as a genotype network. In such a network, each vertex or node corresponds to an individual’s genotype at all those genomic loci that affect a given phenotype. Two vertices are connected by an edge if the associated genotypes differ in exactly one nucleotide. The 80 genotype networks we analyze are based on data from genome-wide association studies of 199 A. thaliana accessions. They form connected graphs whose topography differs substantially among phenotypes. We focus our analysis on the incidence of epistasis (non-additive interactions among mutations) because a high incidence of epistasis can reduce the accessibility of evolutionary paths towards high or low phenotypic values. We find epistatic interactions in 67 phenotypes, and in 51 phenotypes every pairwise mutant interaction is epistatic. Moreover, we find phenotype-specific differences in the fraction of accessible mutational paths to maximum phenotypic values. However, even though epistasis affects the accessibility of maximum phenotypic values, the relationships between genotypic and phenotypic change of our analyzed phenotypes are sufficiently smooth that some evolutionary paths remain accessible for most phenotypes, even where epistasis is pervasive. The genotype network representation we use can complement existing approaches to understand the genetic architecture of polygenic traits in many different organisms.

Validation of QTLs for Fiber Quality Introgressed from Gossypium mustelinum by Selective Genotyping.

Gene introgression from wild species has been shown to be a feasible approach for fiber quality improvement in Upland cotton. Previously, we developed an interspecific G. mustelinum × G. hirsutum advanced-backcross population and mapped over one hundred QTL for fiber quality traits. In the current study, a trait-based selective genotyping approach was utilized to prioritize a small subset of introgression lines with high phenotypic values for different fiber quality traits, to simultaneously validate multiple fiber quality QTL in a single experiment. A total of 75 QTL were detected by CIM and/or single-marker analysis, including 11 significant marker-trait associations (P < 0.001) and three putative associations (P < 0.005) also reported in earlier studies. The QTL that have been validated include three each for fiber length, micronaire, and elongation, and one each for fiber strength and uniformity. Collectively, about 10% of the QTL previously reported have been validated here, indicating that selective genotyping has the potential to validate multiple marker-trait associations for different traits, especially those with a moderate to large-effect detected simultaneously in one experimental population. The G. mustelinum alleles contributed to improved fiber quality for all validated loci. The results from this study will lay the foundation for further fine mapping, marker-assisted selection and map-based gene cloning.

Association of a new 99-bp indel of the CEL gene promoter region with phenotypic traits in chickens

Carboxyl ester lipase (CEL) encodes a cholesterol ester hydrolase that is secreted into the duodenum as a component of pancreatic juice. The objective of this study was to characterize the CEL gene, investigate the association between the CEL promoter variants and chicken phenotypic traits, and explore the CEL gene regulatory mechanism. An insertion/deletion (indel) caused by a 99-bp insertion fragment was shown for the first time in the chicken CEL promoter, and large differences in allelic frequency were found among commercial breeds, indigenous and feral birds. Association analysis demonstrated that this indel site had significant effects on shank length, shank girth, chest breadth at 8 weeks (p < 0.01), evisceration weight, sebum weight, breast muscle weight, and leg weight (p < 0.05). Tissue expression profiles showed extremely high levels of the CEL gene in pancreatic tissue. Moreover, the expression levels of the genes APOB, MTTP, APOV1 and SREBF1, which are involved in lipid transport, were significantly reduced by adding a 4% oxidized soybean oil diet treatment at the individual level and transfecting the embryonic primary hepatocytes with a CEL-overexpression vector. Interestingly, the results showed that the expression level of the II homozygous genotype was significantly higher than that of the ID and DD genotypes, while individuals with DD genotypes had higher phenotypic values. Therefore, these data suggested that the CEL gene might affect body growth by participating in hepatic lipoprotein metabolism and that the 99-bp indel polymorphism could be a potentially useful genetic marker for improving the economically important traits of chickens.

RNA-Seq Reveals Differentially Expressed Genes and Pathways Affecting Intramuscular Fat Metabolism in Huangshan Black Chicken Population

Intramuscular fat (IMF) plays an important role in meat quality due to its positive correlation with juiciness, tenderness, and flavor. However, for chickens, the molecular mechanisms underlying IMF deposition in thigh muscle have not yet been determined. Here, to identify candidate genes and signaling pathways related to IMF deposition, we deeply explored the chicken transcriptome from thigh muscles of Huangshan Black Chickens with extremely high and low phenotypic values for intramuscular fat content. A total of 128 genes differentially expressed genes (DEGs) were detected, of which 94 were up-regulated and 34 were down-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways revealed these DEGs (including FABP4, G0S2, PLIN1, SCD1, LFABP, SLC1A6, SLC45A3, ACSBG1, LY86, ST8SIA5, SNAI2, HPGD, EDN2, and THRSP) were significantly enriched in lipid biosynthetic process, steroid biosynthetic and metabolic process, fatty acid metabolic process, and regulation of unsaturated fatty acid metabolic pathways. Additionally, we concluded an interaction network related to lipid metabolism, which might be contributed to the IMF deposition in chicken. Overall, we proposed some new candidate genes and interaction networks that can be associated with IMF deposition and used as biomarkers in meat quality improvement.

Genetic architecture of phenotypic means and plasticities of kernel size and weight in maize.

Genetic relationships between the phenotypic means and plasticities of kernel size and weight revealed the common genetic control of these traits in maize. Kernel size and weight are crucial components of grain yield in maize, and phenotypic plasticity in these traits facilitates adaptations to changing environments. Elucidating the genetic architecture of the mean phenotypic values and plasticities of kernel size and weight may be essential for breeding climate-robust maize varieties. Here, a maize nested association mapping (CN-NAM) population and association panel were grown in different environments. A joint linkage analysis and genome-wide association mapping were performed for five kernel size and weight phenotypic traits and two phenotypic plasticity measures. The mean phenotypes and plasticities were significantly correlated. The overall results of quantitative trait locus (QTL) and candidate gene analyses indicated moderate and high levels of common genetic control for the two traits. Furthermore, the mean phenotypes or plasticities of the hundred-kernel weight and volume were commonly regulated to a high degree. One pleiotropic locus on chromosome 10 simultaneously controlled the mean phenotypic values and plasticities of kernel size and weight. Therefore, the plasticity of kernel size and weight might be indirectly selected during maize breeding; however, selecting for high or low plasticity in combination with high or low mean phenotypic values of kernel size and weight traits may be difficult.

English

Flag leaf is the most important source of photosynthate for developing rice grains, and flag leaf thickness is an important morphological trait in rice plant-type breeding programs. In the present study, we carried out association mapping for flag leaf thickness in a local rice population which consisted of 86 cultivars derived from breeding programs and planted in large areas in South China. Phenotyping was conducted in the field using nondestructive leaf thickness measurements. Two hundred and thirty-six SSR markers covering 12 chromosomes were employed to genotype the accessions. The association analysis was carried out using a unified mixed-model approach. The Q+K model was selected for investigating marker-trait associations. A total of eleven marker-trait pairs with significant marker-trait associations were identified which were distributed on eight chromosomes. Four of these loci had already been identified as related to flag leaf thickness in previous studies, while the other seven were novel QTLs. The locus PSM163 had the highest r2-marker value of the seven novel loci, explaining 21.54 and 18.49% of the phenotypic variation in 2008 and 2009, respectively. Three of four QTLs, which were detected in a F2 mapping population in the validation study, could correspond to a significant locus in AM, respectively. The six alleles which had the highest phenotypic values at their respective loci should be considered as favored alleles in breeding programs. Pyramiding the favored alleles for flag leaf thickness identified in the study might be a valuable approach to construct an ideal plant architecture in rice breeding. Key words: Rice, flag leaf thickness, breeding programs, association mapping, mixed linear model.

Phenotypic and genotypic variability in a set of sesame genotypes (Sesamum indicum L.).

TOTALLY, 86 sesame (Sesamum indicum L.) genotypes were used for the study of phenotypic and genotypic variability in summer seasons of 2015 and 2016. They were differed significantly values for all studied traits in both seasons. The genotypes mean ranged widely around the general mean in the studied traits. 67.4, 40.7, 46.5 and 48.8% of the genotypes were raised than the average for plant height (159.05cm), capsule length (2.56cm), thousand seed weight (3.65g) and seed yield per plant (14.38g). While 51.2% of genotypes were higher than the average of first capsule height, length of fruiting zone and capsules number per plant in the first season. The higher phenotypic values than overall mean observed as 53.5, 51.2, 52.3, 54.7, 40.7, 48.8 and 48.8% for the plant height, the first capsule height, the fruiting zone length, the capsule number per plant, the capsule length, the thousand seed weight and the seed yield per plant in the second year, respectively. Also, high values (>20%) of phenotypic coefficient variations (PCV) and genotypic coefficients of variations (GCV) were recorded in the first capsule height in both seasons. However, moderate values of genetic advance (GA) were observed for the plant height (18.49) in both seasons and (17.52 & 16.94) for the fruiting zone length in the first and second seasons coupled with high heritability. Higher heritability coupled with high genetic advance estimates (>20) were recorded for the first capsule height (26.05 and 25.85) and the capsules number per plant (22.55 and 26.11) in both seasons. This is indicates that these traits controlled by additive gene action and mostly which is very useful for selection efficiency.

Covariation between Thermally Mediated Color and Performance Traits in a Lizard

Physiological changes in response to environmental cues are not uncommon. Temperature has strong, predictable effects on many traits, such that many traits in ectotherms follow stereotyped thermal performance curves in response to increasing temperature. The prairie lizard-an abundant lizard throughout the central United States-has thermally sensitive, blue abdominal and throat patches. Currently, the role of these patches is not well understood. In this study, we set out to investigate whether individual plasticity in patch color paralleled individual plasticity in sprint speed (do they covary), and if the plasticity in these two patches signal redundant or independent information, testing competing hypotheses suggested for the evolution of multiple signals. We found that both abdominal and throat patch hue follow classical thermal performance curves, suggesting that at the species level hue is a good predictor of sprinting ability. At the individual level, we found that color and performance were statistically repeatable, so individuals with relatively high phenotypic values maintain relatively high phenotypic values across all temperatures. Additionally, we found that abdominal and patch hue covary with sprinting speed at the individual level. Together, these results suggest that the bluest individuals are the fastest individuals across temperatures. However, we found that abdominal and throat patch hue do not covary with each other at the individual level, suggesting that these signals may have independent functions. The importance of examining the function of individual variation cannot be overstated, and overall, more work is needed to better understand both the proximate and ultimate mechanisms underlying signal plasticity in this species and others.

A deep convolutional neural network approach for predicting phenotypes from genotypes.

Deep learning is a promising technology to accurately select individuals with high phenotypic values based on genotypic data. Genomic selection (GS) is a promising breeding strategy by which the phenotypes of plant individuals are usually predicted based on genome-wide markers of genotypes. In this study, we present a deep learning method, named DeepGS, to predict phenotypes from genotypes. Using a deep convolutional neural network, DeepGS uses hidden variables that jointly represent features in genotypes when making predictions; it also employs convolution, sampling and dropout strategies to reduce the complexity of high-dimensional genotypic data. We used a large GS dataset to train DeepGS and compared its performance with other methods. The experimental results indicate that DeepGS can be used as a complement to the commonly used RR-BLUP in the prediction of phenotypes from genotypes. The complementarity between DeepGS and RR-BLUP can be utilized using an ensemble learning approach for more accurately selecting individuals with high phenotypic values, even for the absence of outlier individuals and subsets of genotypic markers. The source codes of DeepGS and the ensemble learning approach have been packaged into Docker images for facilitating their applications in different GS programs.

RNA-Seq reveals differentially expressed genes affecting polyunsaturated fatty acids percentage in the Huangshan Black chicken population.

Fatty acids metabolic products determine meat quality in chickens. Identifying genes associated with fatty acids composition could provide valuable information for the complex genetic networks of genes with underlying variations in fatty acids synthesis. RNA sequencing (RNA-Seq) was conducted to explore the chicken transcriptome from the thigh muscle tissue of 6 Huangshan Black Chickens with 3 extremely high and low phenotypic values for percentage of polyunsaturated fatty acids (PUFAs). In total, we obtained 41,139,108–44,901,729 uniquely mapped reads, which covered 74.15% of the current annotated transcripts including 18964 mRNA transcripts, across all the six thigh muscle tissue samples. Of these, we revealed 274 differentially expressed genes (DEGs) with a highly significant correlation with polyunsaturated fatty acids percentage between the comparison groups based on the ratio of PUFA/SFA. Gene ontology and pathway analysis indicated that the DEGs were enriched in particular biological processes affecting fatty acids metabolism, biosynthesis of unsaturated fatty acids (USFAs), and cell junction-related pathways. Integrated interpretation of differential gene expression and formerly reported quantitative trait loci (QTL) demonstrated that FADS2, DCN, FRZB, OGN, PRKAG3, LHFP, CHCHD10, CYTL1, FBLN5, and ADGRD1 are the most promising candidate genes affecting polyunsaturated fatty acids percentage.

COMPARAÇÕES DE MÉTODOS DE SELEÇÃO EM POPULAÇÕES SIMULADAS DE FRANGOS CAIPIRAS

The purpose of this study was to compare the two types of selection methods known as BLUP and individual selection (IS) in populations of rustic chicken, evaluating the trait of slaughter weight and considering the averages of genetic gain and phenotypic value as response variables. A population of rustic chicken was simulated in the program Genesys, considering the basal population with 500 males and 500 females, from which was randomly chosen 120 males and 240 females. Then, the selected population was simulated considering the sexual ratios of 3, 4, 5 e 6 females per male in two selection types: Individual Selection (IS) and BLUP. In each selection method, the random mating system between breed chickens was used. Selection was performed during 15 consecutive and non-overlapping generations, with 10 simulation repetitions per generation, in order to decrease the genetic oscillation effects. The average genetic gain and the average phenotypic value in all methods and mating systems were evaluated. The results show that the ratio 6:1 was superior to the other sexual ratios in the two types of selection. When comparing the two selection systems, IS was superior to BLUP for the high phenotypic value of slaughter weight. Thus, the sexual ratio of six females for each male is recommended for individual 130 Colloquium Agrariae, vol. 13, n. Especial 2, Jan–Jun, 2017, p. 129-134. ISSN: 1809-8215. DOI: 10.5747/ca.2017.v13.nesp2.000218 selection, with which will allow high phenotypic values, with lower need of males

Genome-Wide Association Study for Muscle Fat Content and Abdominal Fat Traits in Common Carp (Cyprinus carpio).

Muscle fat content is an important phenotypic trait in fish, as it affects the nutritional, technical and sensory qualities of flesh. To identify loci and candidate genes associated with muscle fat content and abdominal fat traits, we performed a genome-wide association study (GWAS) using the common carp 250 K SNP assay in a common carp F2 resource population. A total of 18 loci surpassing the genome-wide suggestive significance level were detected for 4 traits: fat content in dorsal muscle (MFdo), fat content in abdominal muscle (MFab), abdominal fat weight (AbFW), and AbFW as a percentage of eviscerated weight (AbFP). Among them, one SNP (carp089419) affecting both AbFW and AbFP reached the genome-wide significance level. Ten of those loci were harbored in or near known genes. Furthermore, relative expressions of 5 genes related to MFdo were compared using dorsal muscle samples with high and low phenotypic values. The results showed that 4 genes were differentially expressed between the high and low phenotypic groups. These genes are, therefore, prospective candidate genes for muscle fat content: ankyrin repeat domain 10a (ankrd10a), tetratricopeptide repeat, ankyrin repeat and coiled-coil containing 2 (tanc2), and four jointed box 1 (fjx1) and choline kinase alpha (chka). These results offer valuable insights into the complex genetic basis of fat metabolism and deposition.

Identification of Genetic Associations and Functional Polymorphisms of SAA1 Gene Affecting Milk Production Traits in Dairy Cattle.

Our initial RNA sequencing (RNA-seq) revealed that the Serum amyloid A1 (SAA1) gene was differentially expressed in the mammary glands of lactating Holstein cows with extremely high versus low phenotypic values of milk protein and fat percentage. To further validate the genetic effect and potential molecular mechanisms of SAA1 gene involved in regulating milk production traits in dairy cattle, we herein performed a study through genotype-phenotype associations. Six identified SNPs were significantly associated with one or more milk production traits (0.00002< P < 0.0025), providing additional evidence for the potential role of SAA1 variants in milk production traits in dairy cows. Subsequently, both luciferase assay and electrophoretic mobility shift assay (EMSA) clearly demonstrated that the allele A of g.-963C>A increased the promoter activity by binding the PARP factor while allele C did not. Bioinformatics analysis indicated that the secondary structure of SAA protein changed by the substitution A/G in the locus c. +2510A>G. Our findings were the first to reveal the significant associations of the SAA1 gene with milk production traits, providing basis for further biological function validation, and two identified SNPs, g.-963C>A and c. +2510A>G, may be considered as genetic markers for breeding in dairy cattle.

Biometric analysis of protein and oil contents of soybean genotypes in different environments

The objective of this work was to identify by biometric analyses the most stable soybean parents, with higher oil or protein contents, cultivated at different seasons and locations of the state of Minas Gerais, Brazil. Forty-nine genotypes were evaluated in the municipalities of Viçosa, Visconde do Rio Branco, and São Gotardo, in the state of Minas Gerais, from 2009 to 2011. Protein and oil contents were analyzed by infrared spectrometry using a FT-NIR analyzer. The effects of genotype, environment, and genotype x environment interaction were significant. The BARC-8 soybean genotype is the best parent to increase protein contents in the progenies, followed by BR 8014887 and CS 3032PTA276-3-4. Selection for high oil content is more efficient when the crossings involve the Suprema, CD 01RR8384, and A7002 genotypes, which show high mean phenotypic values, wide adaptability, and greater stability to environmental variation.