Genome-wide association study for growth traits in Blanco Orejinegro and Romosinuano cattle.

Growth traits are economically important characteristics for the genetic improvement of local cattle breeds. Genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to perform a GWAS to identify genomic regions and genes associated to birth weight, weaning weight adjusted for 240 days, 16 months, and 24 months weight in Romosinuano (ROMO) and Blanco Orejinegro (BON) cattle. A single-step genomic-BLUP was implemented using 596 BON and 569 ROMO individuals that were genotyped with an Illumina BovineSNP50 BeadChip. There were 25 regions of interest identified on different chromosomes, with few of them simultaneously associated with two or more growth traits and some were common to both breeds. The gene mapping allowed to find 173 annotations on these regions, from which 49 represent potential candidate genes with known growth-related functions in cattle and other species. Among the regions that were associated with several growth traits, that at 24 - 27 MB of BTA14, has important candidate genes such as LYPLA1, XKR4, TMEM68 and PLAG1. Another region of interest at 0.40-0.77 Mb of BTA23 was identified in both breeds, containing KHDRBS2 as a potential candidate gene influencing body weight. Future studies targeting these regions could provide more knowledge to uncover the genetic architecture underlying growth traits in BON and ROMO cattle. The genomic regions and genes identified in this study could be used to improve the prediction of genetic merit for growth traits in these creole cattle breeds.

Genetic dissection of flowering time in flax (Linum usitatissimum L.) through single- and multi-locus genome-wide association studies.

In a rapidly changing climate, flowering time (FL) adaptation is important to maximize seed yield in flax (Linum usitatissimum L.). However, our understanding of the genetic mechanism underlying FL in this multipurpose crop remains limited. With the aim of dissecting the genetic architecture of FL in flax, a genome-wide association study (GWAS) was performed on 200 accessions of the flax core collection evaluated in four environments. Two single-locus and six multi-locus models were applied using 70,935 curated single nucleotide polymorphism (SNP) markers. A total of 40 quantitative trait nucleotides (QTNs) associated with 27 quantitative trait loci (QTL) were identified in at least two environments. The number of QTL with positive-effect alleles in accessions was significantly correlated with FL (r = 0.77 to 0.82), indicating principally additive gene actions. Nine QTL were significant in at least three of the four environments accounting for 3.06-14.71% of FL variation. These stable QTL spanned regions that harbored 27 Arabidopsis thaliana and Oryza sativa FL-related orthologous genes including FLOWERING LOCUS T (Lus10013532), FLOWERING LOCUS D (Lus10028817), transcriptional regulator SUPERMAN (Lus10021215), and gibberellin 2-beta-dioxygenase 2 (Lus10037816). In silico gene expression analysis of the 27 FL candidate gene orthologous suggested that they might play roles in the transition from vegetative to reproductive phase, flower development and fertilization. Our results provide new insights into the QTL architecture of flowering time in flax, identify potential candidate genes for further studies, and demonstrate the effectiveness of combining different GWAS models for the genetic dissection of complex traits.

Genetic mapping for agronomic traits in a MAGIC population of common bean (Phaseolus vulgaris L.) under drought conditions.

BACKGROUND: Common bean is an important staple crop in the tropics of Africa, Asia and the Americas. Particularly smallholder farmers rely on bean as a source for calories, protein and micronutrients. Drought is a major production constraint for common bean, a situation that will be aggravated with current climate change scenarios. In this context, new tools designed to understand the genetic basis governing the phenotypic responses to abiotic stress are required to improve transfer of desirable traits into cultivated beans. RESULTS: A multiparent advanced generation intercross (MAGIC) population of common bean was generated from eight Mesoamerican breeding lines representing the phenotypic and genotypic diversity of the CIAT Mesoamerican breeding program. This population was assessed under drought conditions in two field trials for yield, 100 seed weight, iron and zinc accumulation, phenology and pod harvest index. Transgressive segregation was observed for most of these traits. Yield was positively correlated with yield components and pod harvest index (PHI), and negative correlations were found with phenology traits and micromineral contents. Founder haplotypes in the population were identified using Genotyping by Sequencing (GBS). No major population structure was observed in the population. Whole Genome Sequencing (WGS) data from the founder lines was used to impute genotyping data for GWAS. Genetic mapping was carried out with two methods, using association mapping with GWAS, and linkage mapping with haplotype-based interval screening. Thirteen high confidence QTL were identified using both methods and several QTL hotspots were found controlling multiple traits. A major QTL hotspot located on chromosome Pv01 for phenology traits and yield was identified. Further hotspots affecting several traits were observed on chromosomes Pv03 and Pv08. A major QTL for seed Fe content was contributed by MIB778, the founder line with highest micromineral accumulation. Based on imputed WGS data, candidate genes are reported for the identified major QTL, and sequence changes were identified that could cause the phenotypic variation. CONCLUSIONS: This work demonstrates the importance of this common bean MAGIC population for genetic mapping of agronomic traits, to identify trait associations for molecular breeding tool design and as a new genetic resource for the bean research community.

Heat-hardening effects on mating success at high temperature in Drosophila melanogaster.

Reproduction is strongly influenced by environmental temperature in insects. At high temperature, mating success could be influenced not only by basal (non-inducible) thermotolerance but also by inducible plastic responses. Here, mating success at high temperature was tested in flies carrying contrasting genotypes of heat resistance in Drosophila melanogaster. The possible heat-hardening effect was tested. Mating success did not differ between heat-resistant and heat-sensitive genotypes when tested both at high (33 °C) and benign (25 °C) temperature, independently of the heat-hardening status. Importantly, heat-hardening pre-treatment increased in a 70% the number of matings at 33 °C in a mass-mating experiment. Further, mating latency at 33 °C was shorter with heat hardening than without it in single-pair assays Heat-hardening had previously been showed to improve short-term thermotolerance in many organisms including Drosophila, and the present results show that heat hardening also improve mating success at elevated temperature. Previous exposures to a mild heat stress improve short-term mating success as a plastic response of ecological relevance. Such heat-hardening effects on mating success should be relevant for predicting potential evolutionary responses to any possible current scenery of global warming, as well as in sterile insect release programs for pest control in elevated temperature environments.

Descifrando las moléculas ocultas en las sombras grises de la resistencia cuantitativa a patógenos / Unraveling the molecules hidden in the gray shadows of quantitative disease resistance to pathogens

ABSTRACT One of the most challenging questions in plant breeding and molecular plant pathology research is what are the genetic and molecular bases of quantitative disease resistance (QDR)?. The scarce knowledge of how this type of resistance works has hindered plant breeders to fully take advantage of it. To overcome these obstacles new methodologies for the study of quantitative traits have been developed. Approaches such as genetic mapping, identification of quantitative trait loci (QTL) and association mapping, including candidate gene approach and genome wide association studies, have been historically undertaken to dissect quantitative traits and therefore to study QDR. Additionally, great advances in quantitative phenotypic data collection have been provided to improve these analyses. Recently, genes associated to QDR have been cloned, leading to new hypothesis concerning the molecular bases of this type of resistance. In this review we present the more recent advances about QDR and corresponding application, which have allowed postulating new ideas that can help to construct new QDR models. Some of the hypotheses presented here as possible explanations for QDR are related to the expression level and alternative splicing of some defense-related genes expression, the action of "weak alleles" of R genes, the presence of allelic variants in genes involved in the defense response and a central role of kinases or pseudokinases. With the information recapitulated in this review it is possible to conclude that the conceptual distinction between qualitative and quantitative resistance may be questioned since both share important components.

RESUMEN Una de las preguntas más desafiantes del fitomejoramiento y de la fitopatología molecular es ¿cuáles son las bases genéticas y moleculares de la resistencia cuantitativa a enfermedades?. El escaso conocimiento de cómo este tipo de resistencia funciona ha obstaculizado que los fitomejoradores la aprovecharlo plenamente. Para superar estos obstáculos se han desarrollado nuevas metodologías para el estudio de rasgos cuantitativos. Los enfoques como el mapeo genético, la identificación de loci de rasgos cuantitativos (QTL) y el mapeo por asociaciones, incluyendo el enfoque de genes candidatos y los estudios de asociación amplia del genoma, se han llevado a cabo históricamente para describir rasgos cuantitativos y por lo tanto para estudiar QDR. Además, se han proporcionado grandes avances en la obtención de datos fenotípicos cuantitativos para mejorar estos análisis. Recientemente, algunos genes asociados a QDR han sido clonados, lo que conduce a nuevas hipótesis sobre las bases moleculares de este tipo de resistencia. En esta revisión presentamos los avances más recientes sobre QDR y la correspondiente aplicación, que han permitido postular nuevas ideas que pueden ayudar a construir nuevos modelos. Algunas de las hipótesis presentadas aquí como posibles explicaciones para QDR están relacionadas con el nivel de expresión y el splicing alternativo de algunos genes relacionados con la defensa, la acción de "alelos débiles" de genes R, la presencia de variantes alélicas en los genes implicados en la respuesta de defensa y un papel central de quinasas o pseudoqinasas. Con la información recapitulada en esta revisión es posible concluir que la distinción conceptual entre resistencia cualitativa y cuantitativa puede ser cuestionada ya que ambos comparten importantes componentes.

Exploring New Alleles Involved in Tomato Fruit Quality in an Introgression Line Library of Solanum pimpinellifolium.

We have studied a genomic library of introgression lines from the Solanum pimpinellifolium accession TO-937 into the genetic background of the "Moneymaker" cultivar in order to evaluate the accession's breeding potential. Overall, no deleterious phenotypes were observed, and the plants and fruits were phenotypically very similar to those of "Moneymaker," which confirms the feasibility of translating the current results into elite breeding programs. We identified chromosomal regions associated with traits that were both vegetative (plant vigor, trichome density) and fruit-related (morphology, organoleptic quality, color). A trichome-density locus was mapped on chromosome 10 that had not previously been associated with insect resistance, which indicates that the increment of trichomes by itself does not confer resistance. A large number of quantitative trait loci (QTLs) have been identified for fruit weight. Interestingly, fruit weight QTLs on chromosomes 1 and 10 showed a magnitude effect similar to that of QTLs previously defined as important in domestication and diversification. Low variability was observed for fruit-shape-related traits. We were, however, able to identify a QTL for shoulder height, although the effects were quite low, thus demonstrating the suitability of the current population for QTL detection. Regarding organoleptic traits, consistent QTLs were detected for soluble solid content (SSC). Interestingly, QTLs on chromosomes 2 and 9 increased SSC but did not affect fruit weight, making them quite promising for introduction in modern cultivars. Three ILs with introgressions on chromosomes 1, 2, and 10 increased the internal fruit color, making them candidates for increasing the color of modern cultivars. Comparing the QTL detection between this IL population and a recombinant inbred line population from the same cross, we found that QTL stability across generations depended on the trait, as it was very high for fruit weight but low for organoleptic traits. This difference in QTL stability may be due to a predominant additive gene action for QTLs involved in fruit weight, whereas epistatic and genetic background interactions are most likely important for the other traits.

Genome-wide association mapping of quantitative traits in a breeding population of sugarcane.

BACKGROUND: Molecular markers associated with relevant agronomic traits could significantly reduce the time and cost involved in developing new sugarcane varieties. Previous sugarcane genome-wide association analyses (GWAS) have found few molecular markers associated with relevant traits at plant-cane stage. The aim of this study was to establish an appropriate GWAS to find molecular markers associated with yield related traits consistent across harvesting seasons in a breeding population. Sugarcane clones were genotyped with DArT (Diversity Array Technology) and TRAP (Target Region Amplified Polymorphism) markers, and evaluated for cane yield (CY) and sugar content (SC) at two locations during three successive crop cycles. GWAS mapping was applied within a novel mixed-model framework accounting for population structure with Principal Component Analysis scores as random component. RESULTS: A total of 43 markers significantly associated with CY in plant-cane, 42 in first ratoon, and 41 in second ratoon were detected. Out of these markers, 20 were associated with CY in 2 years. Additionally, 38 significant associations for SC were detected in plant-cane, 34 in first ratoon, and 47 in second ratoon. For SC, one marker-trait association was found significant for the 3 years of the study, while twelve markers presented association for 2 years. In the multi-QTL model several markers with large allelic substitution effect were found. Sequences of four DArT markers showed high similitude and e-value with coding sequences of Sorghum bicolor, confirming the high gene microlinearity between sorghum and sugarcane. CONCLUSIONS: In contrast with other sugarcane GWAS studies reported earlier, the novel methodology to analyze multi-QTLs through successive crop cycles used in the present study allowed us to find several markers associated with relevant traits. Combining existing phenotypic trial data and genotypic DArT and TRAP marker characterizations within a GWAS approach including population structure as random covariates may prove to be highly successful. Moreover, sequences of DArT marker associated with the traits of interest were aligned in chromosomal regions where sorghum QTLs has previously been reported. This approach could be a valuable tool to assist the improvement of sugarcane and better supply sugarcane demand that has been projected for the upcoming decades.

Patterns of longevity and fecundity at two temperatures in a set of heat-selected recombinant inbred lines of Drosophila melanogaster.

Quantitative trait loci (QTL) were mapped for longevity and fecundity at two temperatures, 20 and 30 °C, in two sets of recombinant inbred lines (RIL) highly differing in thermotolerance. Early fecundity (EF) and longevity showed a negative association between temperatures. For instance, longevity was higher and fecundity was lower in the RIL panel showing higher life span at 30 °C. One X-linked QTL (7B3-12E) co-localized for longevity and EF at 20 °C, with one QTL allele showing a positive additive effect on longevity and a negative effect on EF. The across-RIL genetic correlation between longevity and EF was not significant within each temperature, and most QTL that affect life span have no effect on EF at each temperature. EF and longevity can mostly be genetically uncoupled in the thermotolerance-divergent RIL within each temperature as opposed to between temperatures. QTL were mostly temperature specific, although some trait-specific QTL showed possible antagonistic effects between temperatures.

From genotype × environment interaction to gene × environment interaction.

Historically in plant breeding a large number of statistical models has been developed and used for studying genotype × environment interaction. These models have helped plant breeders to assess the stability of economically important traits and to predict the performance of newly developed genotypes evaluated under varying environmental conditions. In the last decade, the use of relatively low numbers of markers has facilitated the mapping of chromosome regions associated with phenotypic variability (e.g., QTL mapping) and, to a lesser extent, revealed the differetial response of these chromosome regions across environments (i.e., QTL × environment interaction). QTL technology has been useful for marker-assisted selection of simple traits; however, it has not been efficient for predicting complex traits affected by a large number of loci. Recently the appearance of cheap, abundant markers has made it possible to saturate the genome with high density markers and use marker information to predict genomic breeding values, thus increasing the precision of genetic value prediction over that achieved with the traditional use of pedigree information. Genomic data also allow assessing chromosome regions through marker effects and studying the pattern of covariablity of marker effects across differential environmental conditions. In this review, we outline the most important models for assessing genotype × environment interaction, QTL × environment interaction, and marker effect (gene) × environment interaction. Since analyzing genetic and genomic data is one of the most challenging statistical problems researchers currently face, different models from different areas of statistical research must be attempted in order to make significant progress in understanding genetic effects and their interaction with environment.

Genetic linkage maps of chicken chromosomes 6, 7, 8, 11 and 13 from a Brazilian resource population

A linkage map is essential not only for quantitative trait loci (QTL) mapping, but also for the organization and location of genes along the chromosomes. The present study is part of a project whose major objective is, besides from construction the linkage maps, the whole genome scan for mapping QTL for performance traits in the Brazilian experimental chicken population. Linkage maps of chicken chromosomes 6 to 8, 11 and 13 were constructed based on this population. The population was developed from two generations of crossbreeding between a broiler and a layer line. Fifty-one microsatellite markers were tested, from which 28 were informative: 4, 8, 7, 4 and 5 for chromosomes 6, 7, 8, 11 and 13, respectively. A SNP located in the leptin receptor gene was included for chromosome 8. Ten parental, 8 F1 and 459 F2 chickens from five full-sib families were genotyped with these markers. The number of total informative meioses per locus varied from 232 to 862, and the number of phase-known informative meioses from 0 to 764. Marker orders in the chromosomes coincided with those of the chicken consensus map, except for markers ADL0147 and MCW0213, on chromosome 13, which were inverted. The reduced number of phase-known informative meioses for ADL0147 (150) may be pointed out as a possible cause for this inversion, apart from the relative short distance between the two markers involved in the inversion (10.5 cM).

O mapa de ligação além de ser fundamental no mapeamento de locos de características quantitativas (QTLs) é importante na organização e localização de genes distribuídos ao longo dos cromossomos. O presente estudo é parte de um trabalho cujo objetivo maior, é a análise de mapeamento de QTLs para características de desempenho no genoma de uma população experimental desenvolvida no Brasil. Com base nesta população foram construídos os mapas de ligação dos cromossomos 6 a 8, 11 e 13 da galinha. A população foi desenvolvida a partir de duas gerações de cruzamentos entre uma linhagem de corte e uma de postura. Foram testados 51 marcadores microssatélites, dos quais 28 foram informativos: 4, 8, 7, 4 e 5 dos cromossomos 6, 7, 8, 11 e 13, respectivamente. Um SNP localizado no gene do receptor da leptina foi incluído no cromossomo 8. Os 10 parentais, 8 F1 e um total de 459 aves F2 de cinco famílias de irmãos completos foram genotipados com estes marcadores. O número de meioses informativas totais por loco variou de 232 a 862 e o de meioses informativas de fase conhecida de 0 a 764. A ordem dos marcadores nos cromossomos coincidiu com a do mapa consenso da galinha, com exceção dos marcadores ADL0147 e MCW0213 do cromossomo 13 que tiveram sua ordem invertida. O número reduzido de meioses informativas de fase conhecida para o marcador ADL0147 (150) pode ser apontado como uma possível causa para a inversão, além da relativa proximidade entre os dois marcadores envolvidos na inversão (10,5 cM).

Genetic linkage maps of chicken chromosomes 6, 7, 8, 11 and 13 from a Brazilian resource population

A linkage map is essential not only for quantitative trait loci (QTL) mapping, but also for the organization and location of genes along the chromosomes. The present study is part of a project whose major objective is, besides from construction the linkage maps, the whole genome scan for mapping QTL for performance traits in the Brazilian experimental chicken population. Linkage maps of chicken chromosomes 6 to 8, 11 and 13 were constructed based on this population. The population was developed from two generations of crossbreeding between a broiler and a layer line. Fifty-one microsatellite markers were tested, from which 28 were informative: 4, 8, 7, 4 and 5 for chromosomes 6, 7, 8, 11 and 13, respectively. A SNP located in the leptin receptor gene was included for chromosome 8. Ten parental, 8 F1 and 459 F2 chickens from five full-sib families were genotyped with these markers. The number of total informative meioses per locus varied from 232 to 862, and the number of phase-known informative meioses from 0 to 764. Marker orders in the chromosomes coincided with those of the chicken consensus map, except for markers ADL0147 and MCW0213, on chromosome 13, which were inverted. The reduced number of phase-known informative meioses for ADL0147 (150) may be pointed out as a possible cause for this inversion, apart from the relative short distance between the two markers involved in the inversion (10.5 cM).

O mapa de ligação além de ser fundamental no mapeamento de locos de características quantitativas (QTLs) é importante na organização e localização de genes distribuídos ao longo dos cromossomos. O presente estudo é parte de um trabalho cujo objetivo maior, é a análise de mapeamento de QTLs para características de desempenho no genoma de uma população experimental desenvolvida no Brasil. Com base nesta população foram construídos os mapas de ligação dos cromossomos 6 a 8, 11 e 13 da galinha. A população foi desenvolvida a partir de duas gerações de cruzamentos entre uma linhagem de corte e uma de postura. Foram testados 51 marcadores microssatélites, dos quais 28 foram informativos: 4, 8, 7, 4 e 5 dos cromossomos 6, 7, 8, 11 e 13, respectivamente. Um SNP localizado no gene do receptor da leptina foi incluído no cromossomo 8. Os 10 parentais, 8 F1 e um total de 459 aves F2 de cinco famílias de irmãos completos foram genotipados com estes marcadores. O número de meioses informativas totais por loco variou de 232 a 862 e o de meioses informativas de fase conhecida de 0 a 764. A ordem dos marcadores nos cromossomos coincidiu com a do mapa consenso da galinha, com exceção dos marcadores ADL0147 e MCW0213 do cromossomo 13 que tiveram sua ordem invertida. O número reduzido de meioses informativas de fase conhecida para o marcador ADL0147 (150) pode ser apontado como uma possível causa para a inversão, além da relativa proximidade entre os dois marcadores envolvidos na inversão (10,5 cM).