Automatic method based on deep learning to identify and account Rhipicephalus microplus larval hatching.

Reports of Rhipicephalus microplus resistant populations worldwide have increased extensively, making it difficult to control this ectoparasite. The adult immersion test, commonly used to screen for acaricide resistance, produces the results only after 40 days of the tick collection because it needs the eggs to be laid and larvae to hatch. The present study aims to develop an automatic method, based on deep learning, to predict the hatching of R. microplus larva based on egg morphology. Initially, the time course of embryonic development of tick eggs was performed to discriminate between viable and non-viable eggs. Secondly, using artificial intelligence deep learning techniques, a method was developed to classify and count the eggs. The larval hatching rate of three populations of R. microplus was evaluated for the software validation process. Groups of three and six images of eggs with 12 days of embryonic development were submitted to the software to predict the larval hatching percent automatically. The results obtained by the software were compared with the prediction results of the hatching percentage performed manually by the specialist and with the results of the hatching percentage of larvae obtained in the biological assay. The group with three images of each population submitted to the software for automatic prediction of the larval hatching percent presented mean values of 96.35% ± 3.33 (Piracanjuba population), 95.98% ± 3.5 (Desterro population) and 0.0% ± 0.0 (Barbalha population). For groups with six images, the values were 94.41% ± 3.84 (Piracanjuba population), 95.93% ± 2.36 (Desterro population) and 0.0% ± 0.0 (Barbalha population). Biological assays showed the following hatching percentage values: 98% ± 1.73 (Piracanjuba population); 96% ± 2.1 (Desterro population); and 0.14% ± 0.25 (Barbalha population). There was no statistical difference between the evaluated methods. The automatic method for predicting the hatching percentage of R. microplus larvae was validated and proved to be effective, with considerable reduction in time to obtain results.

Genome-wide association studies for tick resistance in Bos taurus × Bos indicus crossbred cattle: A deeper look into this intricate mechanism.

Rhipicephalus (Boophilus) microplus is the main cattle ectoparasite in tropical areas. Gir × Holstein crossbred cows are well adapted to different production systems in Brazil. In this context, we performed genome-wide association study (GWAS) and post-GWAS analyses for R. microplus resistance in an experimental Gir × Holstein F2 population. Single nucleotide polymorphisms (SNP) identified in GWAS were used to build gene networks and to investigate the breed of origin for its alleles. Tick artificial infestations were performed during the dry and rainy seasons. Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA) and single-step BLUP procedure was used for GWAS. Post-GWAS analyses were performed by gene ontology terms enrichment and gene transcription factors networks, generated from enriched transcription factors, identified from the promoter sequences of selected gene sets. The genetic origin of marker alleles in the F2 population was assigned using the breed of origin of alleles approach. Heritability estimates for tick counts were 0.40 ± 0.11 in the rainy season and 0.54 ± 0.11 in the dry season. The top ten 0.5-Mbp windows with the highest percentage of genetic variance explained by SNP markers were found in chromosomes 10 and 23 for both the dry and rainy seasons. Gene network analyses allowed the identification of genes involved with biological processes relevant to immune system functions (TREM1, TREM2, and CD83). Gene-transcription factors network allowed the identification of genes involved with immune functions (MYO5A, TREML1, and PRSS16). In resistant animals, the average proportion of animals showing significant SNPs with paternal and maternal alleles originated from Gir breed was 44.8% whereas the proportion of animals with both paternal and maternal alleles originated from Holstein breed was 11.3%. Susceptible animals showing both paternal and maternal alleles originated from Holstein breed represented 44.6% on average, whereas both paternal and maternal alleles originated from Gir breed animals represented 9.3%. This study allowed us to identify candidate genes for tick resistance in Gir × Holstein crossbreds in both rainy and dry seasons. According to the origin of alleles analysis, we found that most animals classified as resistant showed 2 alleles from Gir breed, while the susceptible ones showed alleles from Holstein. Based on these results, the identified genes may be thoroughly investigated in additional experiments aiming to validate their effects on tick resistance phenotype in cattle.

Genome wide scan for quantitative trait loci affecting tick resistance in cattle (Bos taurus x Bos indicus).

BACKGROUND: In tropical countries, losses caused by bovine tick Rhipicephalus (Boophilus) microplus infestation have a tremendous economic impact on cattle production systems. Genetic variation between Bos taurus and Bos indicus to tick resistance and molecular biology tools might allow for the identification of molecular markers linked to resistance traits that could be used as an auxiliary tool in selection programs. The objective of this work was to identify QTL associated with tick resistance/susceptibility in a bovine F2 population derived from the Gyr (Bos indicus) x Holstein (Bos taurus) cross. RESULTS: Through a whole genome scan with microsatellite markers, we were able to map six genomic regions associated with bovine tick resistance. For most QTL, we have found that depending on the tick evaluation season (dry and rainy) different sets of genes could be involved in the resistance mechanism. We identified dry season specific QTL on BTA 2 and 10, rainy season specific QTL on BTA 5, 11 and 27. We also found a highly significant genome wide QTL for both dry and rainy seasons in the central region of BTA 23. CONCLUSIONS: The experimental F2 population derived from Gyr x Holstein cross successfully allowed the identification of six highly significant QTL associated with tick resistance in cattle. QTL located on BTA 23 might be related with the bovine histocompatibility complex. Further investigation of these QTL will help to isolate candidate genes involved with tick resistance in cattle.