Sexual dimorphism is a relevant factor in animal science, since it can affect the gene expression of economically important traits. Eventually, the interest in the prenatal phase in a transcriptome study may not comprise the period of development in which male and female conceptuses are phenotypically divergent. Therefore, it would be interesting if sex differentiation could be performed using transcriptome data, with no need for extra techniques. In this study, the sex of pig conceptuses (embryos at 25 days-old and fetuses at 35 days-old) was determined by reads counts per million (CPM) of Y chromosome-linked genes that were discrepant among samples. Thus, ten genes were used: DDX3Y, KDM5D, ZFY, EIF2S3Y, EIF1AY, LOC110255320, LOC110257894, LOC396706, LOC100625207, and LOC110255257. Conceptuses that presented reads CPM sum for these genes (ΣCPM_chrY) greater than 400 were classified as males and those with ΣCPM_chrY below 2 were classified as females. It was demonstrated that the sex identification can be performed at early stages of pig development from RNA-sequencing analysis of genes mapped on Y chromosome. Additionally, these results reinforce that sex determination is a mechanism conserved across mammals, highlighting the importance of using pigs as an animal model to study sex determination during human prenatal development.

We aimed to estimate litter size and litter uniformity genetic parameters and genetic trends of Landrace pigs at birth and at three weeks by using multitrait analyses for 2,787 litters. The following litter traits were evaluated: number of piglets born alive (NBA), within-litter weight mean at birth (MBW), within-litter weight standard deviation at birth (SDB), within-litter weight coefficient of variation at birth (CVB), number of piglets at three weeks (NT), within-litter weight mean at three weeks (MT), within-litter weight standard deviation at three weeks (SDT), and within-litter weight coefficient of variation at three weeks (CVT). Heritability estimates for NBA, MBW, SDB, and CVB were 0.09±0.04, 0.31±0.08, 0.01±0.04, and 0.07±0.05, respectively, greater than those obtained at three weeks (0.06±0.04, 0.10±0.06, 0.01±0.04, and 0.02±0.04 for NT, MT, SDT, and CVT, respectively). The genetic correlations between NBA and MBW and between MBW and CVB (-0.73±0.20 and-0.93±0.21, respectively) were of moderate to high magnitudes, as well as the genetic correlations between CVT and SDT (0.85±0.39). Genetic correlations between MBW and MT, SDB and SDT, CVB and CVT, and NBA and NT were 0.73±0.16, 0.69±0.54, 0.36±0.80, and 0.95±0.06, respectively. The genetic trends were linear for NBA and CVB and quadratic for MBW and SDB, whereas for all traits at three weeks, they were close to zero. Within-litter weight coefficient of variation (CV) may be the most appropriate variation measure for application in breeding programs, especially at birth, due to its greater heritability estimate and high and negative genetic correlation with MBW. The genetic trends show that NT does not follow the increase in NBA, emphasizing the need to review the breeding goals.

Real-time polymerase chain reaction (RT-qPCR) is an important tool for analyzing gene expression. However, before analyzing the expression of target genes, it is crucial to normalize the reference genes, in order to find the most stable gene to be used as an endogenous control. A gene that remains stable in all samples under different treatments is considered a suitable normalizer. In this sense, we aimed to identify stable reference genes for normalization of target genes in the heart and liver tissues from two genetically divergent groups of chickens (Cobb 500^® commercial line and Peloco backyard chickens) under comfort and acute heat stress environmental conditions. Eight reference genes (ACTB, HPRT1, RPL5, EEF1, MRPS27, MRPS30, TFRC and LDHA) were analyzed for expression stability. The samples were obtained from 24 chickens, 12 from the backyard Peloco and 12 from the Cobb 500® line, exposed to two environmental conditions (comfort and heat stress). Comfort temperature was 23°C and heat stress temperature was 39.5°C for one hour. Subsequently, the animals were euthanized, and heart and liver tissue fragments were collected for RNA extraction and amplification. To determine the stability rate of gene expression, three different statistical algorithms were applied: BestKeeper, geNorm and NormFinder, and to obtain an aggregated stability list, the RankAgregg package of R software was used. The most stable genes using BestKeeper tool, including the two factors (genetic group and environmental condition), were LDHA, RPL5 and MRPS27 for heart tissue, and TFRC, RPL5 and EEF1 for liver tissue. Applying geNorm algorithm, the best reference genes were RPL5, EEF1 and MRPS30 for heart tissue and LDHA, EEF1 and RPL5 for liver. Using the NormFinder algorithm, the best normalizer genes were EEF1, RPL5 and LDHA in heart, and EEF1, RPL5 and ACTB in liver tissue. In the overall ranking obtained by RankAggreg package, considering the three algorithms, the RPL5, EEF1 and LDHA genes were the most stable for heart tissue, whereas RPL5, EEF1 and ACTB were the most stable for liver tissue. According to the RankAggreg tool classification based on the three different algorithms (BestKeeper, geNorm and NormFinder), the most stable genes were RPL5, EEF1 and LDHA for heart tissue and RPL5, EEF1 and ACTB for liver tissue of chickens subjected to comfort and acute heat stress environmental conditions. However, the best reference genes may vary depending on the experimental conditions of each study, such as different breeds, environmental stressors, and tissues analyzed. Therefore, the need to perform priori studies to assay the best reference genes at the outset of each study is emphasized.

Since pre- and postnatal development are programmed during early prenatal life, studies addressing the complete transcriptional landscape during organogenesis are needed. Therefore, we aimed to disentangle differentially expressed (DE) genes between fetuses (at 35 days old) and embryos (at 25 days old) through RNA-sequencing analysis using the pig as model. In total, 1705 genes were DE, including the top DE IBSP, COL6A6, HBE1, HBZ, HBB, and NEUROD6 genes, which are associated with developmental transition from embryos to fetuses, such as ossification, skeletal muscle development, extracellular matrix organization, cardiovascular system, erythrocyte differentiation, and neuronal system. In pathway analysis, embryonic development highlighted those mainly related to morphogenic signaling and cell interactions, which are crucial for transcriptional control during the establishment of the main organs in early prenatal development, while pathways related to myogenesis, neuronal development, and cardiac and striated muscle contraction were enriched for fetal development, according to the greater complexity of organs and body structures at this developmental stage. Our findings provide an exploratory and informative transcriptional landscape of pig organogenesis, which might contribute to further studies addressing specific developmental events in pigs and in other mammals.