Genes as Events

"Contemporary molecular genetics focuses on the simultaneous tasks of
identifying genes and articulating the processes through which they synthesize
proteins. Gene identification alone is not a simple task. Genes, while we
typically think of them as objects, can really be thought of more accurately
as events. Genes are sequences of nucleotides that have the capacity to
produce proteins, which are in turn the foundational building blocks of cell
biology. Most of the DNA in the human genome is referred to as “junk DNA”
because it is not involved in protein synthesis. We cannot simply look at
strands of DNA and see the genes – we must catch them in action and only
through their behavior can we distinguish genes from junk DNA. It is in this
way that genes are in many ways events rather than objects and it is the
reason that it is so very difficult to identify them. This is also the reason
that the process of identifying genes is dependent upon simultaneously
understanding how they work to synthesize proteins. In the last five years,
revolutionary advances in research technology have been made in both the
identification and functional facets of molecular genetics. This has led to an
equally revolutionary revision of our understanding of genes and how they
work.

Some of the more notable findings are that: 1. The human genome is contains far fewer genes than was previously estimated – only approximately 30,000 as
compared to the 120,000 historically assumed. This is of importance because,
given that this is far fewer than the approximately 100,000 genes of the
nematode (flat-worm), it suggests a complex relationship between genes and the complex biological structures and behaviors of human beings. 2. A single gene is capable of synthesizing more than a single protein, which has severe
consequences for relating genes to phenotypic outcomes as compared to the old
dogma that there was a one to one relationship between genes and proteins.
Thus, knowledge of the gene sequence itself, without the developmental
conditions differentiating when a given protein might be synthesized, provides
no information about how gene sequences relate to proteins, let alone complex
behaviors such as depression and schizophrenia. 3. That both gene expression
and the process of protein synthesis are much more probabilistic and complex
than previously thought. Indeed, gene expression is dependent upon the
activity many other genes in the genome and highly sensitive to cellular and
extra-cellular contexts (see Garcia-Coll, Bearer, & Lerner, In press)
The two sciences redoux: behavioral genetics and developmental psychobiology
Behavioral genetics, relying on population genetics methodology has
traditionally held as its aim the statistical estimation of behavioral traits
given the presence of those traits in parents, non-twin siblings, fraternal-
twin siblings, and identical-twin siblings. The key statistic of behavioral
genetics is the heritability quotient, signified as h2. This statistic is
derived from the differential correlations in a given behavioral trait (e.g.,
schizophrenia, depression, alcoholism, extroverted personality, etc.) among
various relative relationships (i.e., parent-child, non-twin siblings,
fraternal-twin siblings, and identical-twin siblings). The h2 statistic can
range in value from 0 to 1 and is thought to reflect the percent of variation
in a given behavioral trait due to shared genes (e.g., if h2 = .75 for a given
trait, then it is argued that 75% of the variance in that trait is due to
genes). However, this interpretation is a substantial misinterpretation of
the true meaning of the statistic. The h2 coefficient simply reflects the
likelihood of a phenotypic trait given that trait is present in a relative –
it in absolutely no way indicates a mechanism of heritability (Michel & Moore,
1995). The implication of the gene as the mechanism is an assumption based on
an adherence to the non-developmental preformationist approach to genetics.
Indeed, the genetic basis of human behavior was estimated using this
statistical approach before any scientist had ever identified an actual gene!
Moreover, the more we have learned about genes and their functioning, the more we find that the statistical assumptions underlying the h2 coefficient are
largely invalid. "