Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 48
Filtrar
Mais filtros










Intervalo de ano de publicação
1.
G3 (Bethesda) ; 2020 Jun 13.
Artigo em Inglês | MEDLINE | ID: mdl-32527748

RESUMO

""Sparse testing" refers to reduced multi-environment breeding trials in which not all genotypes of interest are grown in each environment. Using genomic-enabled prediction and a model embracing genotype × environment interaction (GE), the non-observed genotype-in-environment combinations can be predicted. Consequently, the overall costs can be reduced and the testing capacities can be increased. The accuracy of predicting the unobserved data depends on different factors including (1) how many genotypes overlap between environments, (2) in how many environments each genotype is grown, and (3) which prediction method is used. In this research, we studied the predictive ability obtained when using a fixed number of plots and different sparse testing designs. The considered designs included the extreme cases of (1) no overlap of genotypes between environments, and (2) complete overlap of the genotypes between environments. In the latter case, the prediction set fully consists of genotypes that have not been tested at all. Moreover, we gradually go from one extreme to the other considering (3) intermediates between the two previous cases with varying numbers of different or non-overlapping (NO)/overlapping (O) genotypes. The empirical study is built upon two different maize hybrid data sets consisting of different genotypes crossed to two different testers (T1 and T2) and each data set was analyzed separately. For each set, phenotypic records on yield from three different environments are available. Three different prediction models were implemented, two main effects models ( M1 and M2 ), and a model ( M3) including the genotype-by-environment interaction term (GE). The results showed that the genome-based model including GE ( M3 ) captured more phenotypic variation than the models that did not include this component. Also, M3 provided higher prediction accuracy than models M1 and M2 for the different allocation scenarios. Reducing the size of the calibration sets decreased the prediction accuracy under all allocation designs with M3 being the less affected model; however, using the genome-enabled models (i.e., M2 and M3 ) the predictive ability is recovered when more genotypes are tested across environments. Our results indicate that a substantial part of the testing resources can be saved when using genome-based models including GE for optimizing sparse testing designs.

2.
Plants (Basel) ; 9(4)2020 Apr 08.
Artigo em Inglês | MEDLINE | ID: mdl-32276322

RESUMO

Prior knowledge on heterosis and quantitative genetic parameters on maize lethal necrosis (MLN) can help the breeders to develop numerous resistant or tolerant hybrids with optimum resources. Our objectives were to (1) estimate the quantitative genetic parameters for MLN disease severity, (2) investigate the efficiency of the prediction of hybrid performance based on parental per se and general combining ability (GCA) effects, and (3) examine the potential of hybrid prediction for MLN resistance or tolerance based on markers. Fifty elite maize inbred lines were selected based on their response to MLN under artificial inoculation. Crosses were made in a half diallel mating design to produce 307 F1 hybrids. All hybrids were evaluated in MLN quarantine facility in Naivasha, Kenya for two seasons under artificial inoculation. All 50 inbreds were genotyped with genotyping-by-sequencing (GBS) SNPs. The phenotypic variation was significant for all traits and the heritability was moderate to high. We observed that hybrids were superior to the mean performance of the parents for disease severity (-14.57%) and area under disease progress curve (AUDPC) (14.9%). Correlations were significant and moderate between line per se and GCA; and mean of parental value with hybrid performance for both disease severity and AUDPC value. Very low and negative correlation was observed between parental lines marker based genetic distance and heterosis. Nevertheless, the correlation of GCA effects was very high with hybrid performance which can suggests as a good predictor of MLN resistance. Genomic prediction of hybrid performance for MLN is high for both traits. We therefore conclude that there is potential for prediction of hybrid performance for MLN. Overall, the estimated quantitative genetic parameters suggest that through targeted approach, it is possible to develop outstanding lines and hybrids for MLN resistance.

3.
Inflamm Bowel Dis ; 26(6): 797-808, 2020 05 12.
Artigo em Inglês | MEDLINE | ID: mdl-32333601

RESUMO

BACKGROUND: Patients with inflammatory bowel disease (IBD) have intestinal inflammation and are treated with immune-modulating medications. In the face of the coronavirus disease-19 pandemic, we do not know whether patients with IBD will be more susceptible to infection or disease. We hypothesized that the viral entry molecules angiotensin I converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) are expressed in the intestine. We further hypothesized that their expression could be affected by inflammation or medication usage. METHODS: We examined the expression of Ace2 and Tmprss2 by quantitative polymerase chain reacion in animal models of IBD. Publicly available data from organoids and mucosal biopsies from patients with IBD were examined for expression of ACE2 and TMPRSS2. We conducted RNA sequencing for CD11b-enriched cells and peripheral and lamina propria T-cells from well-annotated patient samples. RESULTS: ACE2 and TMPRSS2 were abundantly expressed in the ileum and colon and had high expression in intestinal epithelial cells. In animal models, inflammation led to downregulation of epithelial Ace2. Expression of ACE2 and TMPRSS2 was not increased in samples from patients with compared with those of control patients. In CD11b-enriched cells but not T-cells, the level of expression of ACE2 and TMPRSS2 in the mucosa was comparable to other functional mucosal genes and was not affected by inflammation. Anti-tumor necrosis factor drugs, vedolizumab, ustekinumab, and steroids were linked to significantly lower expression of ACE2 in CD11b-enriched cells. CONCLUSIONS: The viral entry molecules ACE2 and TMPRSS2 are expressed in the ileum and colon. Patients with IBD do not have higher expression during inflammation; medical therapy is associated with lower levels of ACE2. These data provide reassurance for patients with IBD.


Assuntos
Regulação da Expressão Gênica , Imunossupressores/farmacologia , Síndrome do Intestino Irritável/fisiopatologia , Peptidil Dipeptidase A/genética , Serina Endopeptidases/genética , Adolescente , Adulto , Idoso , Animais , Betacoronavirus/metabolismo , Biópsia , Colo/efeitos dos fármacos , Colo/metabolismo , Biologia Computacional , Infecções por Coronavirus/fisiopatologia , Modelos Animais de Doenças , Feminino , Regulação da Expressão Gênica/efeitos dos fármacos , Humanos , Íleo/efeitos dos fármacos , Íleo/metabolismo , Imunossupressores/uso terapêutico , Inflamação/fisiopatologia , Mucosa Intestinal/metabolismo , Síndrome do Intestino Irritável/tratamento farmacológico , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/fisiopatologia , Reação em Cadeia da Polimerase em Tempo Real , Transcriptoma , Adulto Jovem
4.
Nat Rev Gastroenterol Hepatol ; 17(5): 263-278, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32103203

RESUMO

The human gastrointestinal tract is colonized by trillions of microorganisms that interact with the host to maintain structural and functional homeostasis. Acting as the interface between the site of the highest microbial burden in the human body and the richest immune compartment, a single layer of intestinal epithelial cells specializes in nutrient absorption, stratifies microorganisms to limit colonization of tissues and shapes the responses of the subepithelial immune cells. In this Review, we focus on the expression, regulation and functions of Toll-like receptors (TLRs) in the different intestinal epithelial lineages to analyse how epithelial recognition of bacteria participates in establishing homeostasis in the gut. In particular, we elaborate on the involvement of epithelial TLR signalling in controlling crypt dynamics, enhancing epithelial barrier integrity and promoting immune tolerance towards the gut microbiota. Furthermore, we comment on the regulatory mechanisms that fine-tune TLR-driven immune responses towards pathogens and revisit the role of TLRs in epithelial repair after injury. Finally, we discuss how dysregulation of epithelial TLRs can lead to the generation of dysbiosis, thereby increasing susceptibility to colitis and tumorigenesis.

5.
Gene ; 730: 144259, 2020 Mar 10.
Artigo em Inglês | MEDLINE | ID: mdl-31759989

RESUMO

Mexican Maya populations have a notably high prevalence of type 2 diabetes (T2D) as a consequence of the interaction between environmental factors and a genetic component. To assess the impact of 24 single nucleotide variants (SNVs) located in 18 T2D risk genes, we conducted a family-based association evaluation in samples from Maya communities with a high incidence of the disease. A total of four hundred individuals were recruited from three Maya communities with a high T2D incidence. Family pedigrees (100) and 49 nuclear families were included. Genotyping was performed by allelic discrimination with TaqMan probes. This study also included the family-based association test (FBAT) statistic U to assess the genetic associations with T2D, and the multivariate statistical and haplotype analyses. A positive association with TD2 risk was found for WFS1 rs6446482 (p = 0.046, Z = 1.994) under an additive model, and SIRT1 rs7896005 (p = 0.038, Z = 2.073) under the dominant model. Multivariate model analysis, including T2D status, age, and body mass index (BMI), displayed significant covariance in PPARGC-1α rs8192678; SIRT1 rs7896005; TCF7L2 rs7903146 and rs122243326; UCP3 rs3781907; and HHEX rs1111875 with a P < 0.05. This study revealed an association of SIRT1 and WFS1 with T2D risk.


Assuntos
Diabetes Mellitus Tipo 2/genética , Proteínas de Membrana/genética , Sirtuína 1/genética , Adulto , Idoso , Alelos , Índice de Massa Corporal , Estudos de Casos e Controles , Grupos Étnicos/genética , Família , Feminino , Frequência do Gene/genética , Predisposição Genética para Doença/genética , Variação Genética/genética , Estudo de Associação Genômica Ampla/métodos , Genótipo , Haplótipos , Humanos , Masculino , México , Pessoa de Meia-Idade , Linhagem , Polimorfismo de Nucleotídeo Único/genética , Grupos Populacionais/genética , Fatores de Risco
6.
Cell Mol Gastroenterol Hepatol ; 9(3): 387-402, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-31740421

RESUMO

BACKGROUND & AIMS: The interaction between intestinal microbiota and the immune system plays a vital role in inflammatory bowel disease (IBD). Although numerous deep-sequencing studies have suggested dysbiosis in IBD, identifying specific bacteria from the stool or mucosa that are responsible for disease susceptibility or severity has remained a challenge. Lamina propria phagocytes ideally are localized to interact with bacteria that are in close proximity to, or have invaded, the tissue. Thus, we examined the microbial populations associated with the lamina propria phagocytes in 20 Crohn's disease and 12 ulcerative colitis patients. Specifically, we aimed to address whether the phagocyte-associated microbiota differed from the mucosa-associated microbiota and whether this varied based on IBD type or the state of inflammation. METHODS: 16S ribosomal RNA gene sequencing and innate immune gene expression profiling was done on CD11b+ lamina propria phagocytes isolated from the biopsies obtained from IBD patients. RESULTS: Phagocyte-associated microbiota was enriched in bacterial species belonging to phylum Proteobacteria, whereas species belonging to phylum Bacteroidetes were enriched in the mucosal microbiota of IBD patients. Disease type was the most influential factor in driving differences in the microbiota of both the mucosa and the lamina propria phagocytes, irrespective of inflammation state o`r anatomic location. Crohn's disease and ulcerative colitis specimens showed similar patterns of increased inflammatory gene expression in phagocytes isolated from inflamed areas compared with those isolated from uninflamed regions. CONCLUSIONS: This pilot study shows the feasibility of using lamina propria phagocytes to characterize the microbiota in IBD patients. The approach used in this study can narrow the spectrum of potentially dysbiotic bacterial populations and clinically relevant gene expression signatures in IBD patients.

7.
Front Plant Sci ; 10: 1390, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31781137

RESUMO

Yellow rust (YR) or stripe rust, caused by Puccinia striformis f. sp tritici Eriks (Pst), is a major challenge to resistance breeding in wheat. A genome wide association study (GWAS) was performed using 22,415 single nucleotide polymorphism (SNP) markers and 591 haplotypes to identify genomic regions associated with resistance to YR in a subset panel of 419 pre-breeding lines (PBLs) developed at International Center for Maize and Wheat Improvement (CIMMYT). The 419 PBLs were derived from an initial set of 984 PBLs generated by a three-way crossing scheme (exotic/elite1//elite2) among 25 best elites and 244 exotics (synthetics, landraces) from CIMMYT's germplasm bank. For the study, 419 PBLs were characterized with 22,415 high-quality DArTseq-SNPs and phenotyped for severity of YR disease at five locations in Mexico. A population structure was evident in the panel with three distinct subpopulations, and a genome-wide linkage disequilibrium (LD) decay of 2.5 cM was obtained. Across all five locations, 14 SNPs and 7 haplotype blocks were significantly (P < 0.001) associated with the disease severity explaining 6.0 to 14.1% and 7.9 to 19.9% of variation, respectively. Based on average LD decay of 2.5 cM, identified 14 SNP-trait associations were delimited to seven quantitative trait loci in total. Seven SNPs were part of the two haplotype blocks on chromosome 2A identified in haplotypes-based GWAS. In silico analysis of the identified SNPs showed hits with interesting candidate genes, which are related to pathogenic process or known to regulate induction of genes related to pathogenesis such as those coding for glunolactone oxidase, quinate O-hydroxycinnamoyl transferase, or two-component histidine kinase. The two-component histidine kinase, for example, acts as a sensor in the perception of phytohormones ethylene and cytokinin. Ethylene plays a very important role in regulation of multiple metabolic processes of plants, including induction of defense mechanisms mediated by jasmonate. The SNPs linked to the promising genes identified in the study can be used for marker-assisted selection.

8.
PLoS One ; 14(11): e0224631, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31710611

RESUMO

For doubled haploid (DH) production in maize, F1 generation has been the most frequently used for haploid induction due to facility in the process. However, using F2 generation would be a good alternative to increase genetic variability owing to the additional recombination in meiosis. Our goals were to compare the effect of F1 and F2 generations on DH production in tropical germplasm, evaluating the R1-navajo expression in seeds, the working steps of the methodology, and the genetic variability of the DH lines obtained. Sources germplasm in F1 and F2 generations were crossed with the tropicalized haploid inducer LI-ESALQ. After harvest, for both induction crosses were calculated the haploid induction rate (HIR), diploid seed rate (DSR), and inhibition seed rate (ISR) using the total number of seeds obtained. In order to study the effectiveness of the DH working steps in each generation, the percentage per se and the relative percentage were verified. In addition, SNP markers were obtained for genetic variability studies. Results showed that the values for HIR, ISR, and DSR were 1.23%, 23.48%, and 75.21% for F1 and 1.78%, 15.82%, and 82.38% for F2, respectively. The effectiveness of the DH working step showed the same percentage per se value (0.4%) for F1 and F2, while the relative percentage was 27.2% for F1 and 22.4% for F2. Estimates of population parameters in DH lines from F1 were higher than F2. Furthermore, population structure and kinship analyses showed that one additional generation was not sufficient to create new genotype subgroups. Additionally, the relative efficiency of the response to selection in the F1 was 31.88% higher than F2 due to the number of cycles that are used to obtain the DH. Our results showed that in tropical maize, the use of F1 generation is recommended due to a superior balance between time and genetic variability.


Assuntos
Variação Genética , Haploidia , Zea mays/genética , Cromossomos de Plantas , Genótipo , Melhoramento Vegetal
9.
G3 (Bethesda) ; 9(9): 2913-2924, 2019 09 04.
Artigo em Inglês | MEDLINE | ID: mdl-31289023

RESUMO

Kernel methods are flexible and easy to interpret and have been successfully used in genomic-enabled prediction of various plant species. Kernel methods used in genomic prediction comprise the linear genomic best linear unbiased predictor (GBLUP or GB) kernel, and the Gaussian kernel (GK). In general, these kernels have been used with two statistical models: single-environment and genomic × environment (GE) models. Recently near infrared spectroscopy (NIR) has been used as an inexpensive and non-destructive high-throughput phenotyping method for predicting unobserved line performance in plant breeding trials. In this study, we used a non-linear arc-cosine kernel (AK) that emulates deep learning artificial neural networks. We compared AK prediction accuracy with the prediction accuracy of GB and GK kernel methods in four genomic data sets, one of which also includes pedigree and NIR information. Results show that for all four data sets, AK and GK kernels achieved higher prediction accuracy than the linear GB kernel for the single-environment and GE multi-environment models. In addition, AK achieved similar or slightly higher prediction accuracy than the GK kernel. For all data sets, the GE model achieved higher prediction accuracy than the single-environment model. For the data set that includes pedigree, markers and NIR, results show that the NIR wavelength alone achieved lower prediction accuracy than the genomic information alone; however, the pedigree plus NIR information achieved only slightly lower prediction accuracy than the marker plus the NIR high-throughput data.


Assuntos
Genômica/métodos , Modelos Genéticos , Melhoramento Vegetal/métodos , Espectrofotometria/métodos , Bases de Dados Genéticas , Aprendizado Profundo , Genômica/estatística & dados numéricos , Fenótipo , Espectrofotometria/estatística & dados numéricos , Triticum/genética , Zea mays/genética
10.
PLoS One ; 14(6): e0217571, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31173600

RESUMO

Several studies have shown differences in the abilities of maize genotypes to facilitate or impede Azospirillum brasilense colonization and to receive benefits from this association. Hence, our aim was to study the genetic control, heterosis effect and the prediction accuracy of the shoot and root traits of maize in response to A. brasilense. For that, we evaluated 118 hybrids under two contrasting scenarios: i) N stress (control) and ii) N stress plus A. brasilense inoculation. The diallel analyses were performed using mixed model equations, and the genomic prediction models accounted for the general and specific combining ability (GCA and SCA, respectively) and the presence or not of G×E effects. In addition, the genomic models were fitted considering parametric (G-BLUP) and semi-parametric (RKHS) kernels. The genotypes showed significant inoculation effect for five root traits, and the GCA and SCA were significant for both. The GCA in the inoculated treatment presented a greater magnitude than the control, whereas the opposite was observed for SCA. Heterosis was weakly influenced by the inoculation, and the heterozygosity and N status in the plant can have a role in the benefits that can be obtained from this Plant Growth-Promoting Bacteria (PGPB). Prediction accuracies for N stress plus A. brasilense ranged from 0.42 to 0.78, depending on the scenario and trait, and were higher, in most cases, than the non-inoculated treatment. Finally, our findings provide an understanding of the quantitative variation of maize responsiveness to A. brasilense and important insights to be applied in maize breeding aiming the development of superior hybrids for this association.


Assuntos
Azospirillum brasilense/fisiologia , Genômica/métodos , Vigor Híbrido/genética , Zea mays/genética , Redes Reguladoras de Genes , Genoma de Planta , Heterozigoto , Hibridização Genética , Endogamia , Fenótipo , Raízes de Plantas/genética , Raízes de Plantas/crescimento & desenvolvimento , Característica Quantitativa Herdável , Estresse Fisiológico/genética
11.
G3 (Bethesda) ; 9(8): 2425-2428, 2019 08 08.
Artigo em Inglês | MEDLINE | ID: mdl-31201204

RESUMO

The dna is the fundamental basis of genetic information, just as bits are for computers. Whenever computers are used to represent genetic data, the computational encoding must be efficient to allow the representation of processes driving the inheritance and variability. This is especially important across simulations in view of the increasing complexity and dimensions brought by genomics. This paper introduces a new binary representation of genetic information. Algorithms as bitwise operations that mimic the inheritance of a wide range of polymorphisms are also presented. Different kinds and mixtures of polymorphisms are discussed and exemplified. Proposed algorithms and data structures were implemented in C++ programming language and is available to end users in the R package "isqg" which is available at the R repository (cran). Supplementary data are available online.


Assuntos
Biologia Computacional/métodos , Genômica/métodos , Software , Algoritmos
12.
Euphytica ; 215(4): 80, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31057179

RESUMO

After drought, a major challenge to smallholder farmers in sub-Saharan Africa is low-fertility soils with poor nitrogen (N)-supplying capacity. Many challenges in this region need to be overcome to create a viable fertilizer market. An intermediate solution is the development of maize varieties with an enhanced ability to take up or utilize N in severely depleted soils, and to more efficiently use the small amounts of N that farmers can supply to their crops. Over 400 elite inbred lines from seven maize breeding programs were screened to identify new sources of tolerance to low-N stress and maize lethal necrosis (MLN) for introgression into Africa-adapted elite germplasm. Lines with high levels of tolerance to both stresses were identified. Lines previously considered to be tolerant to low-N stress ranked in the bottom 10% under low-N confirming the need to replace these lines with new donors identified in this study. The lines that performed best under low-N yielded about 0. 5 Mg ha-1 (20%) more in testcross combinations than some widely used commercial parent lines such as CML442 and CML395. This is the first large scale study to identify maize inbred lines with tolerance to low-N stress and MLN in eastern and southern Africa.

13.
PLoS One ; 14(4): e0215387, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31002683

RESUMO

The dextran sulfate sodium (DSS) model of colitis is a common animal model of inflammatory bowel disease that causes pain and distress. In this study, we aimed to determine whether fluid supplementation can be used as a welfare-based intervention to minimize animal suffering. C57Bl/6 females undergoing acute colitis by administration of 3% DSS in drinking water were supplemented with 1 mL intraperitoneal injections of NaCl and compared to non-supplemented control mice. Mouse behavior and locomotive activity were assessed on days 5-6 after DSS initiation by means of tail suspension, novel object recognition and open field activity tests. Mice were euthanized after either the acute (day 7) or the recovery phase (day 12) of colitis and inflammation, epithelial proliferation, and differentiation were assessed by means of histology, immunohistochemistry, quantitative PCR, and western blot. We found that fluid-supplemented mice had reduced signs of colitis with no alterations in behavior or locomotive activity. Furthermore, we observed an accelerated epithelial repair response after fluid hydration during the acute phase of colitis, characterized by increased crypt proliferation, activation of ERK1/2, and modulation of TGF-ß1 expression. Consistent with these findings, fluid-supplemented mice had increased numbers of goblet cells, upregulated expression of differentiation markers for absorptive enterocytes, and reduced inflammation during the recovery phase. Our results show that fluid hydration does not reduce stress in DSS-treated mice but alters colitis evolution by reducing clinical signs and accelerating epithelial repair. These results argue against the routine use of fluid supplementation in DSS-treated mice.


Assuntos
Colite/terapia , Mucosa Intestinal/patologia , Solução Salina/farmacologia , Animais , Colite/induzido quimicamente , Colite/fisiopatologia , Sulfato de Dextrana , Modelos Animais de Doenças , Feminino , Hidratação/métodos , Injeções Intraperitoneais , Mucosa Intestinal/metabolismo , Camundongos Endogâmicos C57BL , Atividade Motora/fisiologia , Solução Salina/administração & dosagem , Cicatrização/fisiologia
14.
Arch Med Sci ; 14(6): 1361-1373, 2018 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-30393491

RESUMO

Introduction: Genetic variants have been replicated for association with type 2 diabetes mellitus (T2D) and many of them with diabetes-related traits. Because T2D is highly prevalent in Mexico, this study aimed to test the association of CDKN2A/B, PPARGC1A, VEGFA, SIRT1 and UCP2 gene polymorphisms (rs10811661, rs8192678, rs2010963, rs7896005 and rs659366 respectively) with metabolic traits in 415 unrelated Mexican mestizos with T2D under three models of inheritance. Material and methods: A total of 415 unrelated Mexican mestizos were genotyped by TaqMan assays. Triglycerides, cholesterol, glucose, high-density lipoprotein cholesterol (HDL-C), insulin and anthropometric measurements were determined and the HOMA-IR was calculated. Association studies were tested by the Kruskal-Wallis test, linear regression, statistical power analysis, Bonferroni correction, paired SNP analysis, and physical interaction by GeneMANIA. Results: All polymorphisms were in Hardy-Weinberg equilibrium, and the association by genotype with T2D-related traits displayed nominal significance for rs8192678 with glucose (p = 0.023) and triglycerides (p = 0.013); rs2010963 with diastolic blood pressure (DBP) (p = 0.012) and cholesterol (p = 0.013); rs7896005 with DBP (p = 0.012) and insulin (p = 0.011); and rs659366 with cholesterol (p = 0.034), glucose (p = 0.031) and triglycerides (p = 0.028); and the association of rs2010963 with HDL-C (p = 0.0007) was significant. Linear regression performed with three models of inheritance, adjusted by age + sex + BMI and corrected with Bonferroni, showed a significant association of rs2010963 with HDL-C in an additive model (p = 0.007); and rs7896005 was significantly associated with DBP in the recessive model (p = 0.006). Conclusions: Rigorous analysis evidenced the association of VEGFA rs2010963 and SIRT1 rs7896005 with HDL-C and DBP respectively; these traits are known predictors of cardiovascular complications, which increase the risk of cardiovascular diseases in this population.

15.
Sci Rep ; 8(1): 12527, 2018 08 21.
Artigo em Inglês | MEDLINE | ID: mdl-30131572

RESUMO

The value of exotic wheat genetic resources for accelerating grain yield gains is largely unproven and unrealized. We used next-generation sequencing, together with multi-environment phenotyping, to study the contribution of exotic genomes to 984 three-way-cross-derived (exotic/elite1//elite2) pre-breeding lines (PBLs). Genomic characterization of these lines with haplotype map-based and SNP marker approaches revealed exotic specific imprints of 16.1 to 25.1%, which compares to theoretical expectation of 25%. A rare and favorable haplotype (GT) with 0.4% frequency in gene bank identified on chromosome 6D minimized grain yield (GY) loss under heat stress without GY penalty under irrigated conditions. More specifically, the 'T' allele of the haplotype GT originated in Aegilops tauschii and was absent in all elite lines used in study. In silico analysis of the SNP showed hits with a candidate gene coding for isoflavone reductase IRL-like protein in Ae. tauschii. Rare haplotypes were also identified on chromosomes 1A, 6A and 2B effective against abiotic/biotic stresses. Results demonstrate positive contributions of exotic germplasm to PBLs derived from crosses of exotics with CIMMYT's best elite lines. This is a major impact-oriented pre-breeding effort at CIMMYT, resulting in large-scale development of PBLs for deployment in breeding programs addressing food security under climate change scenarios.


Assuntos
Sequenciamento de Nucleotídeos em Larga Escala/métodos , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Triticum/genética , Mapeamento Cromossômico , Grão Comestível/genética , Abastecimento de Alimentos , Frequência do Gene , Haplótipos , Temperatura Alta , Melhoramento Vegetal , Banco de Sementes , Análise de Sequência de DNA , Estresse Fisiológico , Triticum/classificação , Triticum/crescimento & desenvolvimento
16.
Gene ; 677: 324-331, 2018 Nov 30.
Artigo em Inglês | MEDLINE | ID: mdl-30130595

RESUMO

Type 2 diabetes mellitus (T2D) is one of the two leading causes of mortality in Mexico. However, most studies have focused on Caucasians or Asians, and there are a small number of studies investigating Maya populations. Furthermore, to the best of our knowledge, there is no information on isolated Maya communities with T2D frequencies of 20% that are primarily attributed to ethnicity. Consequently, this study focused on assessing which genetic risk variants could be involved in the high rates of T2D in 92 individuals with Maya ancestry; 47 were diagnosed with T2D, and 45 were classified as healthy individuals. A pilot genome-wide association study was performed using the Affymetrix Axiom Genome-wide LAT1 array. The population structure was determined with the ADMIXTURE software using 1289 Latin American selected polymorphisms, and 39 polymorphisms associated with T2D were included for replication. Association tests were performed using the Statistical Analysis System (SAS) using the allelic, genotype and Armitage trend tests. The results indicated that population structure analysis displayed no differences between T2D patients and healthy individuals; 24 loci located were identified for probable association with T2D (p > 1.288 × 10-7 and p < 1.348 × 10-4); the polymorphism AGTR2 rs1914711 in chromosome X was identified by the allele test (OR = 6.824; p = 1.448 × 10-9) as a candidate gene for association with T2D; and ARL15 rs4311394 was associated as a T2D protector by genotype and the Armitage trend test (OR = 0.318; p = 0.001). In conclusion, this study proposes 24 candidate SNPs associated with T2D for replication studies and one for protective association with T2D.


Assuntos
Diabetes Mellitus Tipo 2/genética , Loci Gênicos/genética , Predisposição Genética para Doença/genética , Alelos , Estudos de Casos e Controles , Grupos Étnicos/genética , Grupo com Ancestrais do Continente Europeu/genética , Feminino , Estudo de Associação Genômica Ampla/métodos , Genótipo , Humanos , Masculino , México , Pessoa de Meia-Idade , Projetos Piloto , Polimorfismo de Nucleotídeo Único/genética , Risco
17.
G3 (Bethesda) ; 8(9): 3039-3047, 2018 08 30.
Artigo em Inglês | MEDLINE | ID: mdl-30049744

RESUMO

One of the major issues in plant breeding is the occurrence of genotype × environment (GE) interaction. Several models have been created to understand this phenomenon and explore it. In the genomic era, several models were employed to improve selection by using markers and account for GE interaction simultaneously. Some of these models use special genetic covariance matrices. In addition, the scale of multi-environment trials is getting larger, and this increases the computational challenges. In this context, we propose an R package that, in general, allows building GE genomic covariance matrices and fitting linear mixed models, in particular, to a few genomic GE models. Here we propose two functions: one to prepare the genomic kernels accounting for the genomic GE and another to perform genomic prediction using a Bayesian linear mixed model. A specific treatment is given for sparse covariance matrices, in particular, to block diagonal matrices that are present in some GE models in order to decrease the computational demand. In empirical comparisons with Bayesian Genomic Linear Regression (BGLR), accuracies and the mean squared error were similar; however, the computational time was up to five times lower than when using the classic approach. Bayesian Genomic Genotype × Environment Interaction (BGGE) is a fast, efficient option for creating genomic GE kernels and making genomic predictions.


Assuntos
Interação Gene-Ambiente , Genótipo , Modelos Genéticos , Teorema de Bayes , Valor Preditivo dos Testes
19.
Plant Methods ; 14: 46, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29991959

RESUMO

Background: Modern agriculture uses hyperspectral cameras with hundreds of reflectance data at discrete narrow bands measured in several environments. Recently, Montesinos-López et al. (Plant Methods 13(4):1-23, 2017a. 10.1186/s13007-016-0154-2; Plant Methods 13(62):1-29, 2017b. 10.1186/s13007-017-0212-4) proposed using functional regression analysis (as functional data analyses) to help reduce the dimensionality of the bands and thus decrease the computational cost. The purpose of this paper is to discuss the advantages and disadvantages that functional regression analysis offers when analyzing hyperspectral image data. We provide a brief review of functional regression analysis and examples that illustrate the methodology. We highlight critical elements of model specification: (i) type and number of basis functions, (ii) the degree of the polynomial, and (iii) the methods used to estimate regression coefficients. We also show how functional data analyses can be integrated into Bayesian models. Finally, we include an in-depth discussion of the challenges and opportunities presented by functional regression analysis. Results: We used seven model-methods, one with the conventional model (M1), three methods using the B-splines model (M2, M4, and M6) and three methods using the Fourier basis model (M3, M5, and M7). The data set we used comprises 976 wheat lines under irrigated environments with 250 wavelengths. Under a Bayesian Ridge Regression (BRR), we compared the prediction accuracy of the model-methods proposed under different numbers of basis functions, and compared the implementation time (in seconds) of the seven proposed model-methods for different numbers of basis. Our results as well as previously analyzed data (Montesinos-López et al. 2017a, 2017b) support that around 23 basis functions are enough. Concerning the degree of the polynomial in the context of B-splines, degree 3 approximates most of the curves very well. Two satisfactory types of basis are the Fourier basis for period curves and the B-splines model for non-periodic curves. Under nine different basis, the seven method-models showed similar prediction accuracy. Regarding implementation time, results show that the lower the number of basis, the lower the implementation time required. Methods M2, M3, M6 and M7 were around 3.4 times faster than methods M1, M4 and M5. Conclusions: In this study, we promote the use of functional regression modeling for analyzing high-throughput phenotypic data and indicate the advantages and disadvantages of its implementation. In addition, many key elements that are needed to understand and implement this statistical technique appropriately are provided using a real data set. We provide details for implementing Bayesian functional regression using the developed genomic functional regression (GFR) package. In summary, we believe this paper is a good guide for breeders and scientists interested in using functional regression models for implementing prediction models when their data are curves.

20.
G3 (Bethesda) ; 8(9): 3019-3037, 2018 08 30.
Artigo em Inglês | MEDLINE | ID: mdl-30021830

RESUMO

Plant and animal breeders are interested in selecting the best individuals from a candidate set for the next breeding cycle. In this paper, we propose a formal method under the Bayesian decision theory framework to tackle the selection problem based on genomic selection (GS) in single- and multi-trait settings. We proposed and tested three univariate loss functions (Kullback-Leibler, KL; Continuous Ranked Probability Score, CRPS; Linear-Linear loss, LinLin) and their corresponding multivariate generalizations (Kullback-Leibler, KL; Energy Score, EnergyS; and the Multivariate Asymmetric Loss Function, MALF). We derived and expressed all the loss functions in terms of heritability and tested them on a real wheat dataset for one cycle of selection and in a simulated selection program. The performance of each univariate loss function was compared with the standard method of selection (Std) that does not use loss functions. We compared the performance in terms of the selection response and the decrease in the population's genetic variance during recurrent breeding cycles. Results suggest that it is possible to obtain better performance in a long-term breeding program using the single-trait scheme by selecting 30% of the best individuals in each cycle but not by selecting 10% of the best individuals. For the multi-trait approach, results show that the population mean for all traits under consideration had positive gains, even though two of the traits were negatively correlated. The corresponding population variances were not statistically different from the different loss function during the 10th selection cycle. Using the loss function should be a useful criterion when selecting the candidates for selection for the next breeding cycle.


Assuntos
Genoma , Modelos Genéticos , Característica Quantitativa Herdável , Seleção Genética , Teorema de Bayes
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA